Vol.17 No.6 May - December, 2018
Human body detection and gait recognition in sports
According to the different gait characteristics of human body, using the video segmentation to extract gait features in human walking state is the category of computer vision. Based on the Gauss model, when the shadow area of the image was changed, the change of the brightness was used to detect the change of the shadow part in this study; by using the periodic determination of the horizontal width feature as the reference data, adaptive picture frames were randomly found; at the same time, the same 5~6 frames in the same cycle were selected, and 5~6 gait key points were extracted for different frames; finally, the human gait characteristics were matched based on the HMM image recognition method.
Interference suppression of dance action based on wearable technology
With the development of science and technology, the wearable technology has made a breakthrough, but there are still some problems. In this paper, a wearable wireless sensor platform for interference suppression in dance action was introduced. Compared with previous systems, the system has high-level features computed by individual nodes from raw signals, and the base station performs data collection and tuning of sensor node parameters according to energy availability, radio link quality, and application specific policies. Based on energy consumption per node, sensor operation and data transmission were adjusted, and data was processed under strict computational constraints. In addition, a corresponding improved algorithm was proposed to enhance the suppression of interference signals.
Effects of ph value of common solvents on physical & chemical properties of 4 kinds of obstetrics and gynecology drugs
The purpose of this paper is to discuss the effects of solvent choice on the clinical application of drugs. By analyzing the 4 kinds of obstetrics and gynecology drugs, it can be proved that pH value of common solvents will affect physical & chemical properties, resulting in changes in physical and chemical properties of drugs. Through consulting relevant literature and combining the actual work problems, the influence of solvents on 4 kinds of gynecological drugs in the process of compatibility is discussed. The four drugs are aminophylline, ambroxol, labetalol and ritodrine. The correct choice in different cases is also discussed, so as to achieve rational drug use and ensure the safety of patient medication. The results show that the pH value of solvent has a certain influence on the logD and solubility of 4 kinds of drugs, and the trend of change is exponential. Based on the above finding, it can be concluded that all 4 drugs are used in combination with glucose injection or 0.9% sodium chloride injection. In addition, the use of attention has its own characteristics.
Electrochemiluminescence Detection Of Local Anesthetic Drugs And Ephedrine
Electrochemical luminescence detection is a sensitive detection method. Compared with other detection methods, the advantages are as the following, which the detection sensitivity is high, the linear range is wide, the reagent is small and the instrument is simple and so on. In electrochemical luminescence, trisodium pyridine ruthenium that is the most widely used detection technology in electrochemical luminescence detection systems has been widely used in the fields of protein, amino acids and drugs, etc. The CE-ECL detection technology is produced by combining CE separation and ECL detection technology. And the combination technique of CE and Ru(bpy)32+ ECL has gotten important development, the advantages of the efficient separation of CE and sensitive detection of ECL are effective means of trace components to analyze complex samples. First of all, a new method for the detection of procaine, lidocaine, ropivacaine and bupivacaine was established by CE-ECL. The use of SDS with Tween 20 mixed micelles in CE could improve significantly the resolution of analytes with the similar structure. The sensitivity can be increased by utilization of Eu-PB modifying Pt working electrode. In order to quantitatively analyze the analytes in the actual biological samples, the quantitative limits and linear ranges of the four local anesthetic drugs in urine samples and serum are measured. Second, a new method for the detection of ephedrine hydrochloride, methamphetamine hydrochloride and pseudoephedrine hydrochloride was developed by capillary electrophoresis coupled with electrochemiluminescence detection using internal standard method. The separation efficiency and detection sensitivity of the three analytes and internal standard are effectively improved by the addition of ionic liquid BMIMBF4 to the electrophoretic buffer solution. In order to quantitatively analyze the three analytes in the actual biological samples, the quantitative and linear ranges of the three ephedrine drugs in traditional Chinese medicine and urine samples are determined respectively.
The prediction of basketball match results based on conditional random field
Nowadays, the basketball lottery market is developing rapidly, which makes the prediction of the result of the basketball match become a new challenge. Due to various reasons, the efficiency of the existing methods is low and the accuracy rate is poor. Based on this, in this paper, the prediction of basketball match results was studied based on conditional random field. Host and guest, three-point shot, penalty shot, intercept, player information, and the values of Team Rank were used as feature inputs. And based on conditional random field method, the NBA Prediction model was constructed. Then based on the existing data sets, 30 teams were modeled respectively. The training predictions were carried out for the case where there were Team Rank features and no Team Rank features. The results show that in the case of Team Rank features, the highest accuracy rate can reach 0.7262, and the prediction results are good.
Competitive thinking mode of basketball players based on simulation technology
The research of competitive thinking model mainly follows two different research ideas, including the information processing theory and ecology view. The two theories represent different levels of thinking patterns matching. In this paper, in order to study the competitive thinking mode of basketball players, with the simulation technology as the support, computer technology was adopted to simulate the application of virtual reality technology in basketball through the sample collection method. In addition, the method of data comparison and analysis was used to design the experiment, so as to explore the mode of competitive thinking. The final experimental results show that the virtual reality simulation technology can greatly enhance the athletes' competitive thinking mode, and make the team's technical level remarkable progress.
The optimization of sports competitive skills based on cluster analysis
The vigorous development of competitive sports in China has promoted the image and status of our country in the world. With the increase of the scale and quantity of international competitions, the competition of competitive sports is becoming fiercer and fiercer, which tests the psychological endurance of athletes. In this situation, it is very important to make use of cluster analysis to alleviate the psychological pressure of athletes in competition, and to make them achieve excellent results in competitive sports. Therefore, in this paper, starting from the psychological endurance of athletes, the theoretical support of athletes in sports competition was obtained from the psychological level, thus contributing to the development of competitive sports in China.
Computer artistic design based on artificial intelligence
With the continuous progress of computer science and technology, computers are gradually applied to many fields, including the art design. In this paper, in order to improve the efficiency and comprehensive level of art design, the art design assistant system was studied on the premise of the whole inquiry of art design. In this system, the leading image processing technology is used in contemporary art design, which can obviously reduce the amount of labor of the design staff, and create a harmonious development space for the above-mentioned personnel. However, at this time, the art design workers also need to improve their own ability.
Financial risk prediction technology based on data mining
Data mining method is used to predict the financial risk, and the time series nonlinear and non-dynamic characteristics of the model prediction are obvious. Therefore, the opportunities and challenges of financial prediction exist simultaneously, which have high market application value. In this paper, based on the above background, the financial risk prediction model based on data mining was designed. Due to the big volatility of the result accuracy of the traditional fuzzy prediction model, the fuzzy prediction model was revised and the financial risk was estimated on the basis of the revised model. The results show that the method can predict the fluctuation situation of the financial stock market and reflect the future market trend.
Sports service system for community residents based on network genetic algorithm
With the improvement of community management, the community resident sports service system has gradually penetrated into people's lives. In view of this, the sports service system for community residents based on the network genetic algorithm was studied and analyzed, and the status quo of the sports service system for community residents and its related research theory were briefly introduced; then the network genetic algorithm and its coding process and application were described in detail, and a community in Jinan City, Shandong Province was taken as a research sample; at the same time, the network genetic algorithm was used to optimize and schedule its sports service system. Finally, it is concluded that the network genetic algorithm can help to integrate and optimize the resources of sports service system.
Community sports information management system
Community sports informationization is the optimization of community management and community service, which is an important way to improve the physical quality of community residents. According to the development of community information, the principles of community sports construction were combined, and the framework of community sports information construction theory system was built, so as to provide theoretical support for the sound development of community sports and give full play to the role of the community information platform. At the same time, in this paper, a convenient and efficient community sports management system was designed for community sports management, and the platform with a rich community sports exchange function was established for community residents. Other streets and communities can refer to the research and design of community sports management information system according to their own conditions.
Application of data mining technology in badminton on-spot tactical analysis system
With the development of science and technology, all walks of life in China have begun to use information technology extensively. The sports cause not only represents the physical quality of the people, but also represents the strength of the country. Therefore, the use of digital technology in sports has become necessary. At present, the domestic decision-making system established based on data mining technology has been used more and more in the domestic sports training. As our country's sports strong point, badminton is also facing new challenges in the introduction of data mining technology. In this paper, the theory of data mining technology was analyzed in the field of badminton tactical analysis. Through the data collection, processing and mining, the complete and in-depth analysis of badminton was carried out to achieve visual effects, so as to provide a scientific basis for badminton to continue to maintain strong strength.
Application of three axis accelerometer in energy consumption monitoring of college students sports
Jogging as a common sporting event, it is popular with young people. Based on the study of exercise intensity, we use biosynthetic acceleration sensors to monitor the exercise intensity of 140 teenagers. We apply the statistical software to process 108 sets of valid data, and analyze the characteristics of different gender, BMI, exercise heart rate and energy consumption. By analyzing the distribution characteristics of heart rate and energy consumption of college students during jogging, we establish a linear regression equation of heart rate and energy consumption, and put forward a program for teenagers' jogging. The conclusions of this study are as follows: (1) The heart rate of teenagers is mainly distributed in the range of 141-160 b / min, and the exercise heart rate, exercise speed and energy consumption of boys are higher than girls. (2) There is a significant difference in the rest heart rate between boys and girls (P <0.01), and there is significant difference in mean heart rate and average energy consumption between boys and girls (P<0.05). (3) During the jogging process, the exercise heart rate and the average energy consumption increase with the increase of the moving speed. Boys are mainly moderate intensity jogging (8 ~ 10km / h), and girls are mainly low intensity jogging (6 ~ 8km / h). The average speed of boys and girls is significantly different (P <0.05). (4) When jogging (about 8km / h), we recommend three times a week, and each time is not less than 35min.
Research on improvement of remote dynamic request scheduling algorithm for multi- core web server
Chuanxu cheng, meirong li
Multi-core Web server is difficult to achieve dynamic balance in the process of remote dynamic request scheduling, so it is necessary to improve it based on the traditional scheduling algorithm to enhance the actual effect of the algorithm. This article do research on the multi-core Web server, Focusing on multi-core Web server queuing model. On this basis, the author draws the drawbacks of the multi-core Web server in the remote dynamic request scheduling algorithm, and improves the traditional algorithm with the demand analysis. Not only it overcomes the drawbacks of traditional algorithms, but also promotes the system threads carrying the same amount of tasks, and promotes the server being always in a dynamic balance. On the basis of this, it achieves an effective solution to customer requests.
The design and research of entrepreneurial support service platform system
In order to meet the call of "mass entrepreneurship and innovation", a convenient and comprehensive open entrepreneurial support service platform is in urgent need to meet the needs of entrepreneurs of different levels. The platform can also provide the majority of innovative entrepreneurs many services combined with online and offline such as business-oriented, resource sharing, exchange interaction, professional advice and so on. Based on the investigation and analysis of the current status of global entrepreneurship support service platform both at home and abroad, this paper identifies the main functions that the system will achieve: publish project, background administrator audit the project, project generation, news management, message management, etc, intended to provide a good service platform for entrepreneurs.
Reading teaching system design for teaching chinese as a foreign language
Along with the globalization of English, Chinese literature is working up gradually and penetrating into the cultures of the rest of the world. The popularization of Chinese -learning grants the study of teaching system for Teaching Chinese as a Foreign Language (TCFL) a great significance. This paper first presents the current development of TCFL, analyzes the deficiencies of the two existing methods in TCFL learning system, and then designs a web-based learning system in line with the current popularity of Chinese in other countries to improve the convenience of Chinese learning. The concept behind this design is that the improvement of reading ability is beneficial for the better of Chinese.
Analysis and design of university library management system
Yuan-yuan wang, xiao-guang zhang, yi-jie zhao
The design on the inventory management is the focus of the system design, mainly including six aspects: stock management, out-storage management, storage, librarian information and password service and supplier information. Applying Jsp + JavaBean development mode and the Microsoft SQL Server 2005 as the database platform, the design mainly aims at realizing the browsing, query, adding, deletion, modification, report of the information and other functions. It fully meets the needs for book management and applies to any other domestic libraries.
Development and realization of virtual landscape architecture design system based on 3d
In the 1940s, computers have been developed. With the development of science and technology and the upgrading of computer network technology, a large number of high technology emerged. Virtual reality technology is one of them, which is gradually used in various fields, Medicine, aerospace, film industry and so on. Through the introduction of 3D virtualization technology, combining with the requirements of the landscape architecture design for mathematical modeling in the first place, and then developing the correspondent system according to the relevant requirements, this paper intends to provide a visual viewing Platform for landscape architecture and thus increase the design effect through the systematic research.
Research On The Multi-Feature Extraction Technology Of Color Microimage Under Complex Background
Xinyu Hu*, Liangyi Wu, Lei Qian, Daode Zhang
In order to realize the effective recognition of color microimage, the research on the multi-feature extraction technology of color microimage under complex background has been performed. Owing to the property of complex background for pebrine image, the difference of color feature has been applied to realize the direct separation of color target image from the background impurities, and the initial characteristic parameter set is extracted according to the morphological characteristics of the pebrine image. Aiming at the optimal selection problem of multi-feature for pebrine image, the feature selection technology based on multi-feature fusion for pebrine image is put forward. The method includes the following two steps: firstly, the redundant feature information of the initial feature set is removed by the method of correlation analysis; secondly, the technique of the optical feature selection based on the classifier learning is adopted to determine the optimal feature set of classification for pebrine image. The result shows the approach effective, which not only reduces the characteristic dimension effectively, but improves the accuracy rate of recognition.
The research of wearable nanosensors in sports
In order to better identify the behavior of the athletes in the high jump motion, this paper proposes a feature selection algorithm based on genetic algorithm optimization. The nonzero eigenvalues of the inter-class dispersion matrices in LDA are used as the planning variables. The genetic algorithm is used to operate the planning variables in the aspects of selection, crossover and mutation to search for optimal projection space. Smart Volume Management (SVM) is used to identify the three kinds of high jumps. The results show that the error is obviously lower after using this method, which effectively reduces the dimension of the feature space and has the advantage in sports.
Segmentation and processing of athletes' targets based on fuzzy algorithm
With the development of modern information technology and computer technology, video has become a very important information carrier. In high semantic level video processing, video moving object segmentation must be used. In order to apply video processing technology better to the development of sports, the segmentation and processing technique based on fuzzy algorithm was proposed in this paper. By introducing the concept of fuzzy logic mathematics, the synthetic similarity of code words was constructed, so as to provide a segmentation method for each video sequence and enhance the adaptability of the algorithm. In order to verify the feasibility and effectiveness of the method, simulation experiments were carried out. The simulation results show that the proposed method has high segmentation accuracy.
Graphic design system based on image recognition
The application of graphic design in today's society is more and more extensive, and the influence of information technology also has a great impact on graphic design. Therefore, in this paper, the graphic design system based on image recognition was studied; and the image recognition of this image processing technique was illustrated; then a computer system for image location recognition in graphic design was designed by image recognition technology; at the same time, the ability of identifying errors, location and other abilities of the system were verified. The results of the verification show that the system can be used to identify and locate the image if it is compatible with the relevant instrument.
Analysis of the training ability of competitive sports coaches based on image processing technology
Since the 2008 Olympic Games, China's sports industry has entered a stage of vigorous development. In the pursuit of higher sports competition results, people have actively studied the means and methods of sports coaches training. In this paper, an intelligent shooting assistant training system based on image processing technology was proposed. Through the image processing technology, the target position was calculated. And then the target position and target standard were compared and analyzed, and thus the aiming and shooting performance was obtained. The system can collect and process video during shooting training, and replay it as needed. By testing the function of the system, it can be seen that the system has friendly interface, and can be applied to the specific training practice of sports coaches.
Design and application of interactive english language learning system
Deyi li, qian yu
In the mobile Internet era, the means of information have been widely used in people's work, study, life, entertainment and many other fields, so educational informatization has become the inevitable choice of the times. In this paper, the combination of mobile learning theory and English teaching practice was explored, and traditional classroom teaching was implemented on mobile terminals such as mobile phones based on Android platform and PDA, and text messaging and voice chat based on Openfire instant messaging servers and XMPP protocols were achieved. Finally, the experiment shows that the system basically meets the needs of interactive learning of users in the mobile network environment at anytime and anywhere; and through voice chat and text information exchange platform, an effective communication channel can be established between teachers and students.
Design and implementation of teaching management system in colleges and universities
Haiyan zhan*, binbin song, ailian dong, lianming su
With the rapid development of computer technology and network technology, the reform of education system is deepening, and the scale of various colleges and universities is expanding, and the campus network environment is built. According to the design and implementation of teaching management system in colleges and universities, J2EE architecture and JSP technology were used mainly in the process of preparation, the system was developed by technology, and the teaching management information was mainly queried. Database was adopted in windows in background. The background of the system was used for the login of administrator login to manage system information. The results show that according to the process flow of software engineering standard, from requirement analysis, system design to implementation and test, the whole text shows the whole link of system from design to implementation.
Design and implementation of teaching management system based on web
As a new teaching method, the teaching management system with the main content of the online education system and online examination system has begun to enter the major universities, and the development of education has formed a new impetus. In this paper, firstly, through the demand analysis, a teaching management system based on WEB was designed and implemented from the two major groups of students and teachers. Two important subsystems, online examination subsystem and online education subsystem, were extracted according to requirements. Finally, the method of system testing was introduced mainly based on black box testing and white box testing, and the function testing process of the system was introduced in detail. The final experimental results show that the user can operate normally and use the system, and the system can meet the needs of users.
Analysis of pressure source in sports competition based on clustering and recommendation algorithm
The analysis of the pressure source of sports competition based on clustering and recommendation algorithm is of great importance to the cognition and mitigation of the stress status of the athletes. In order to make the algorithm better integrate with our traditional sports industry, in this paper, the related theories were summarized; furthermore, 10 sports students in a university were taken as examples; at the same time, clustering and recommendation algorithm was also used, and the stress sources and coping ability of sports students were analyzed. The results show that the algorithm can effectively improve the cognitive ability of athletes to stressors, and can provide data support for the development of more efficient mitigation schemes. The purpose of this study is to provide references for follow-up studies.
Research on the interactive design technology of 3d landscape based on virtual technology
The three-dimensional landscape interactive design based on virtual technology has a very important positive influence on the display of landscape and the promotion of tourists' interest. In this study, in order to promote the integration of virtual technology in the three-dimensional landscape in China, on the basis of understanding the relevant theory, the actual case was introduced and the landscape design of the three-dimensional garden was carried out. The results show that the three-dimensional landscape system studied and designed can be used to show the landscape of the garden from multiple perspectives. According to further factor analysis and research, it is found that the main advantage factor of virtual technology in 3D landscape design is that it provides visitors with a more innovative way of viewing. The purpose of this study is to provide theoretical basis and reference for the improvement of the following three-dimensional landscape design technology
Research on optimal route planning of tourism based on cloud computing
The use of tourism optimal route planning based on cloud computing has a positive impetus for the efficiency of national tourism and the reduction of tourist pressure in scenic spots. In order to better promote the combination of cloud computing technology and traditional tourism route planning in our country, on the basis of understanding the relevant theories, Nanjing tourism was taken as a practical case, and then the tourism routes of Nanjing scenic spots were planned through the related mathematical model of cloud computing. The results show that the tourism planning route of cloud computing can meet the actual demand of tourists, and thus has a certain accuracy. The purpose of the study is to provide the reference and theoretical support for the planning of the optimal route of tourism.
Design And Implementation Of Jumper Simulation System In Basketball Match
Yang He, Zhengbing Xia*
The three-dimensional monitoring of jumper in basketball can improve the precision of the jumper. In this paper, a three-dimensional (3D) reconstruction method of KLT feature points for basketball jumper was improved; then the algorithm of KLT feature points was used to acquire the jumper images of basketball players in different angles and set up the projection matrix of the camera, so as to obtain the external parameters of the cameras; in addition, the specific coordinates of the space points of the jumper for each image matching point were calculated, the 3D information was obtained, and the 3D video surveillance of the jumper's precision was completed. Simulation results show that the proposed algorithm can accurately establish a 3D model of the jumper for basketball players and improve the precision of the jumper.
Application of feature selection approach in automatic scoring system for english composition
The automatic scoring system for English compositions based on feature selection approach has a positive effect on the accuracy of English composition scoring. In order to make the feature selection method better integrate with automatic scoring system for English compositions in China, in this paper, the actual case was further introduced on the basis of understanding the relevant theories. Then different feature selection methods were chosen, and the accuracy of the automatic scoring system for English compositions was compared and analyzed. The analysis shows that the accuracy of the automatic scoring system for English compositions under different feature selection methods is different. When the feature value is in 10-15, the accuracy of the automatic scoring system is the highest. The purpose of the study is to provide a theoretical basis for the improvement and development of the automatic scoring system for English composition.
The english vocabulary intelligentized ubiquitous learning system
Mobile education is the product of mobile communication technology, network technology, multimedia technology and contemporary education, and it is also the frontier of modern educational technology. Its promotion and development will lead to the transformation of educational technology and educational means. In this paper, the development model of educational software, such as English intelligent local learning system, mobile and mobile education support platform, PDA and palmtop computer, was discussed in this paper, so as to provide a universal learning platform for the study of English words. Using this platform, people can learn English at anytime and anywhere.
Research On Data Mining Of Economic Management Supported By Cloud Computing
Data mining of economic management supported by cloud computing can provide some theoretical support for the sustainable development of some enterprises. In order to perfect this technology of our country, in this paper, the relevant theories were understood. Further, the system was constructed and the database was constructed. Then, the construction enterprises were taken as examples of the study, and the data mining was carried out for economic management. The research results provide the basis for the development of the enterprise. The purpose of this study is to provide technical support and reference for follow-up research.
Interactive Design And Implementation Of Multimedia English Smart Client
In language teaching, the application of multimedia teaching systems has fundamentally changed the traditional way of teaching and learning, and has provided new and efficient technical means for modern language teaching. In this paper, firstly, the requirement analysis and system design of the client were discussed; then, from the two aspects of usability goals and user experience goals, the interaction designs in smart client were described; then, major problems and corresponding solutions of data storage and management, script based development and browser compatibility encountering in the development process were analyzed; finally, the interface evaluation and application situation of the system were introduced. The final experimental results show that the client can better improve the teaching effect and students' performances.
DESIGN OF SPORT HEALTH PRESERVATION CONSULTATIVE SERVICE SYSTEM
XIA HUANG, ZHENG LIU
At present, improving the quality of life and promoting the physical and mental health have gradually become the realistic goals of people's life. In many ways and means to improve the quality of life and promote the physical and mental health, scientific and rational exercise is undoubtedly one of the cheapest, most reliable and most effective ways. Under this background, in this paper, based on the standard of national physical fitness measurement, the idea of developing sports health consultation service system and the module of system component were put forward; according to the principle of network development and the characteristics of physical fitness, the database and the corresponding application software were used to preliminarily design the user sport health preservation consultative service system under limited conditions.
A Grid-Based Information Service Model For Digital Library
To introduce the conception, theory and method to library grid resource management systematically, and improve the utilization efficiency of information resource in grid, a conception model of information resource management and information resources organization under grid environment is proposed base on the study of metadata standards. The major procedures during the process of information resource organization of DL are provided in this article. In the meta data description, the metadata management module in grid middleware is studied, and the technology of semantic association is introduced to design a resource matching algorithm based on semantic association. Then a dynamic solution for reliability scheduling of resources is also put forward. We establish a DL grid environment in the experiment and make simulation tests on the information service model and related research findings. The experiments verify the feasibility of organization model proposed in this article and the performance superiority of improved scheme.
Evaluation Model Of Microblog Information Confidence Based On Bp Neural Network
As the carrier of social media, microblog has become an important broadcasting tool for news. However, the characteristics of microblog platform causes that they cannot provide effective mechanisms to avoid the transmission of rumours or false information. Then we take the information around the main context as the features of microblog classification, integrated with the context to form a mixed feature for feature extraction based on classification. The BP-based network is established to evaluate the confidence of news by the mixed features. During the simulations, we adopt the real data in certain large websites to perform detailed analysis on the features and model proposed in this paper. The results show that the improved evaluation model has better performance to distinguish the authenticity of the news. The mixed features can provide better review of discrimination so our model can effectively solve the problems on confidence evaluation and rumour detection.
Diagnostic Practice And Test System For College English
Yali Yang, Zhijuan Li
The application of diagnostic training and testing system for College English is of great significance to the cognition of college students' English proficiency. In order to perfect the system of our country, based on the understanding of relevant theories, further examples were introduced to test the system. The results show that the system can effectively analyze the cognitive level of all aspects of the students' English learning process, and various systems have a certain degree of credibility. The purpose of this study is to provide reference and theoretical support for the evaluation of English learners' personal competence in colleges.
Performance Improvement Of Pvdf Chemical Sensors In Sports Shoes Design
Athletic sports have aroused more and more people's attention in the world, and sports shoes required in the sports plays an increasingly important role. China is a big country in the production of sports shoes that in every five pairs of sports shoes in the world, there is a pair made in China. At present, the majority of domestic shoes-making enterprises lack sports shoes testing and analysis system. In consequence, it is difficult to provide scientific and reasonable basis for sports shoes design, research and development. If the athletes worn unreasonably designed shoes, long-term training and competition may lead to foot structure deformity, and result in the knee, ankle, and toe joint damage and muscle contusion. Poly vinylidene fluoride (PVDF) is a new type of polymer sensing material. The sensing element based on PVDF material has the advantages of good piezoelectric properties, low acoustic impedance, wide frequency response and so on, which can be widely used in actual measurement of all kinds of pressures. In this study, through the design and fabrication of PV film as a protective layer, a conductive silica gel as the base of PVDF piezoelectric chemical sensor, starting from the sports mechanics and biological structure, we made a scientific layout of the chemical sensor array. In addition, we improved and analyzed the performance of sports shoes in the design of PVDF chemical sensor, to provide scientific guidance to the design of sports shoes. Moreover, we made use of advanced technology to guide the design, development and production of sports shoes, which is of great significance to improve the performance of athletes, protect athletes, and promote the rehabilitation of sports injuries.
Research On Electronic Commerce Teaching Experiment Simulation System
The electronic commerce teaching curriculum has the extremely strong practical nature. Therefore, to carry out the electronic commerce professional colleges and universities, must have relevant to keep up with the situation of the hardware facilities, to meet the network practice teaching needs of the experimental simulation system. In view of this, this article has carried on the research to the electronic commerce teaching experiment simulation system. First of all, this paper introduces the development purpose, the overall structure and the characteristics of the electronic commerce teaching experiment simulation system, and then designs the working principle and the function module of the system. At the same time, through the description of the system's business process, focusing on the analysis of the online B to C and analog CA authentication system functions. This system combines the real electronic commerce application and school teaching need, students through play different roles to experience of e-commerce logistics, capital flow, information flow and the transaction process, the teacher can be very convenient to monitor and control the progress of the students' experimental project, through experimental grouping, for students to operate the distribution of authority, you can also directly to the student's performance in this experiment to make the score. Through the research, we can draw the following conclusions: the use of the system can synchronize the theory study and practice teaching, students in the acceptance of the theory of knowledge at the same time, practical operating abilities get improved, also the development of this system also conducive to the promotion of knowledge, knowledge popularization of electronic commerce.
Application Of Chemical Bio-Sensor Based On Layered Nano-Materials In Monitoring The Oxidative Damage Of Human Body
Hydrotalcite is a layered compound composed of negatively charged anion filled among layers of positively charged metal hydroxides. The study found that the enzyme was immobilized on nano-scaled anion layered, then the second-generation enzyme chemical sensors showed higher sensitivity. The detection limit reached nm level, and the kinetic parameters and the cycle performance of chemical bio-sensor also showed more advantages, so nano hydrotalcite material has good application value. But most researches are limited to research on the first and second generation chemical bio-sensors. The experiment preliminary studied anionic nano layered hydrotalcite and its effects on H, namely direct electrochemistry and substrate catalytic behavior, and the direct electrochemical effect on the glucose oxidase (GOD). It was found that the MnO2-HRP C modified electrode has a catalytic behavior for the substrate H2O2, and successfully constructed the third-generation chemical bio-sensor with high sensitivity, low detection limit and good anti-interference ability.
Application Of Glucose Chemical Bio-Sensor Based On Nano-Materials In Monitoring Physiological Signals Of Human Movement
The unique physical and chemical properties of nano-materials will lead to changes in many areas. Among them, it has attracted the interest of a wide range of chemical bio-sensor researchers taking nano-materials as a new bio-sensing medium. The development of electrochemical chemical bio-sensor modified by nano-material is the crossover between nanotechnology and life sciences. Chemical bio-sensor has the characteristics of high sensitivity, good selectivity, simple operation, fast detection and low cost, which is widely used in environmental, clinical, food and other aspects of monitoring. In this paper, the application of glucose chemical bio-sensor based on nano-titanium dioxide and carbon nanotubes in the monitoring of human physiological signals has been studied. In the best experimental conditions, the chemical sensor has a good linear response to glucose in the range of . The detection limit is . Due to the synergistic effect between the nanoparticles, the chemical sensor has the advantages of high sensitivity, good stability and selectivity.
Analysis Of Traditional Chinese Medicine Based On Microemulsion
Chinese medicine has thousands of years of clinical experience in China. Along with the enhancing awareness to drug efficacy and safety, the quality of traditional Chinese medicine is getting more and more attention. The quality control of traditional Chinese medicine has become one of the important factors to ensure the development of traditional Chinese medicine (TCM) industry and one of the important research contents of the modernization of traditional Chinese medicine. Because of the complexity and diversity of traditional Chinese medicine and the limitations of the research on the basis of material, the development of quality control technology of TCM has become the key of the quality control of traditional Chinese medicine. In many current analysis methods involved in quality control of traditional Chinese medicine, chromatography method can adapt to the new concepts and requirements. From traditional thin-layer chromatography, liquid chromatography and gas chromatography to the capillary electrophoresis and coupling technology, they all showed the respective advantages in the complex composition analysis of TCM and solved a lot of problems. Because of the multiple choice of chromatography, various detectors and changeable mobile phase, high performance liquid chromatography is suitable for the analysis of most compounds. It becomes the most promising and widely used method undoubtedly.
Application Of Polyvinylidene Fluoride Piezoelectric Thin Film Chemical Bio-Sensor In The Mechanical Measurement Of Athletic Sports Foot Movement
Lei Tian, Naxin Wang
Due to the needs of chemical bio-mechanics, rehabilitation medicine, orthopedic surgery, sports training, footwear industry and so on, it is very important to measure and analyze the stress in different regions of the foot. Through the piezoelectric properties analysis of the polymer sensing material - PVDF piezoelectric film, we made a further research on its mechanics’ characteristics. In addition, based on the analysis of the biological characteristics of human foot structure and foot movement, according to the characteristics of piezoelectric thin film, we designed and prepared the piezoelectric chemical sensor in cantilever structure, did experiments and made the simulation. Through the special conditioning circuit, we converted the plantar local pressure signal into electrical signal output, laying a good foundation for the follow-up plantar test system.
Application Of Chemical Bio-Sensor In Athlete's Doping Test
A new optical fiber chemical bio-sensor for the detection of stimulants is proposed. According to the binding ratio of the stimulant molecule to its fluorescently labeled competitive molecule on the receptor, the information of the stimulant molecule content is converted into the intensity of the fluorescent signal. The chemical sensor can detect the estrogen with lowest concentration of 10-9mol／L, and the linear range is 10-7mol／L~10-8mol／L. The chemical sensor can detect the androgen with lowest concentration of 10-9mol／L, and the linear range is 10-8mol／L~10-9mol／L. The physical response time of the optical fiber chemical bio-sensor is less than 0.1 seconds, and the error of the experimental fiber chemical bio-sensor system is less than 0.25%. The agarose self-assembled film is -4℃. In the dark and moisturizing conditions, it can be saved for more than a month. The chemical sensor can use a fixed receptor to detect a class of stimulant molecules, especially for the screening of stimulants.
Effects Of Aquatic Feed Supplementation On Growth And Immune Function Of Aquatic Animals
The aim is to further explore the mechanism of antimicrobial peptides to control the growth and immune function, to provide theoretical basis for the application of antimicrobial peptides in the practice. The contents are as below. The effects of antimicrobial peptides on the growth and immune function of carcasses are systematically described from the perspective of apparent traits, biochemistry and molecular biology. Healthy fishes are selected and randomly divided into 5 groups, it is carried out in the temperature control single cycle breeding system. During the test, the fishes are fed fully. At the end of the test, the weight and length of the fishes are measured. The effects of antimicrobial patricides on growth performance and immune-related enzyme activities of carcasses are studied. The results show that there is dose relationship between the amount of antimicrobial peptides in the feed and the weight gain rate, the specific growth rate and the feed coefficient. With the increase of the amount of antimicrobial peptides, the activity of the acid phosphatase and the lysozyme in the serum of the carp are increased firstly and then decreased with the increase of the dosage. It can be concluded that antibacterial peptides have the antibacterial activity and it can promote animal growth.
Analysis And Design Of Power Marketing Management Information System
Qiang Zhang, Hui Zhang, Luli Qiao
Due to the rapid development of China's national economy, the power market is undergoing large structural changes. At the same time, the management system operates separately from the manufacturer grid, according to the different needs of customers, power supply enterprises need to make a certain marketing management work adjustment. Based on the above background, the design and analysis of power marketing management information system was put forward; according to the requirements of the functional modules of the power system, the modules of the software were divided and the system of the database was designed; in addition, Oracle10g was used as the system database development platform, the computer network technology was combined, and the relatively perfect power marketing management information system was built.
SEMANTIC TECHNOLOGY IN PERSONALIZED ENGLISH LEARNING SYSTEM
Learning English in Internet can enrich the learning resources and realize the sharing of information in the open and distributed space. Traditional Internet learning provides users with a lot of resources, but the semantic information that is really used for English learners is limited. Therefore, in this paper, it was argued that a personalized English learning system needed to be built and personalized service mode should be provided according to the special requirements of semantics. Based on semantic network technology, semantic technology in this study was integrated into the personalized English learning system. The semantic reasoning can satisfy the customer's knowledge base and improve the efficiency of English learning.
Construction Of English Pronunciation Quality Evaluation System Based On Deep Learning
With the deepening of the degree of globalization, English, which is one of the widely used languages, has become the object of people's attention and learning. However, as a result of our country's education and language environment, most people in China are in the "dumb English" state. In order to change this state, the construction of English pronunciation quality evaluation system based on deep learning was put forward. The necessity of choosing deep learning on the basis of traditional speech recognition system was expounded and the corresponding model was constructed according to the actual needs. Finally, by comparing the time and computing power of the detection experiment, it is concluded that the English pronunciation quality evaluation system based on the depth learning has better voice feature extraction performance and data processing ability.
Application Research On Specific Sports Result Prediction Based On Neural Network Algorithm
Li Yan-Xia, Li Lin, Peng Li-Na
The function relation between existing specific sports result prediction and relative factors is rather complicated. Given mathematical expression can not fit their relation well. The utilization of multivariate regression and gray method will cause larger error and show unreasonable features. Therefore, this paper studies the prediction model for specific results of the atheletes. It first determine relative quality training index of specific sports result. Then BP neural network is adopted to train the training sample and establish corresponding model, without determining the mathematical expression of the prediction model beforehead. The tests show that, our model overcomes the defects of traditional models, and it can reflect the relation between quality training level of athletes and their specific results. In addition it can acquire higher fitness and prediction accuracy.
Paper-Cut Design Based On Image Boundary Representation
In the face of the loss of folk traditional arts today, how to better preserve and inherit folk traditional art has become one of the problems faced by the state and society. Therefore, in this paper, the research of paper-cut design based on image boundary representation was put forward. In this study, the common techniques of image boundary representation were firstly summarized, and then a set of computer system for paper-cut design on the basis of pattern recognition technology in image boundary representation technology was designed. Then, with the design and drawing of the frog paper cutting, it proves that the function of each module of the system meets the requirements of the beginning of the design, thus proving that folk traditional art can gain a new development and inheritance with the help of computer.
Simulation System Of Sports Behavior Based On Correlation Analysis
With the development of science and technology, it is of great significance to use computer system to improve the training quality of athletes. The simulation research of sports behavior plays an important role in promoting the development of sports. In this paper, the movement of golfers was taken as the object of study. Based on the theory of correlation analysis, the simulation system of motion behavior of the project was designed; then the athletes' sports behaviors were collected and analyzed; and through data collection, play, drawing analysis and maintenance of training records, intelligent analysis and other operations, the behavior of sports personnel was guided and corrected, thus to improve the training effect and the competition performance of the athletes.
Ecological Environment Sound Classification Algorithm Based On Support Vector Machines
Monitoring is one of the main means of ecological environment protection. Therefore, the research on ecological environment sound classification algorithm based on support vector machines was proposed in this study. The current computer can’t recognize the sound directly, and must recognize the sound by identifying the audio signal. Therefore, the advantages of the hidden Markov model and the support vector machine model that were commonly used in sound classification algorithm were combined, a new audio classification algorithm based on support vector machines and a set of computer sound classifiers were designed. Experiments show that the algorithm and system have great advantages in the classification of ecological environment sounds.
Design And Implementation Of English Classroom Assistant Based On Smart Phone
The popularization of information technology has been expanding the service group of software. As an increasingly important communication tool, smart phones have gradually become the means to obtain information. How to establish a digital learning environment to ensure proper learning and interactive information in the right way at the right time and place has become an urgent problem to be solved. In this paper, based on the point of interaction between teaching and learning, the advantages of traditional classroom learning and mobile learning were combined, and a portable data communication module was designed and implemented as the basic system of the whole classroom assistant, which satisfied the random interactive demands of the learners to a certain extent.
Design And Implementation Of Quantification System For Sports Action In Competitive Sports
Sports movement is the core of sports in the process of competitive sports. In order to improve the athletes' competitive level, modern methods should be used to quantitatively analyze the movements of athletes to determine the normative action of the athletes in the course of the competitive games, in this way, the standardization of athletes' behavior in athletic activities can be improved. In this study, computer technology was used to manage, process and analyze the athletes' pictures, all data of movements was analyzed, and the difference of action was analyzed concretely, so that the quality of sports teaching and the scientific nature of competitive sports were improved effectively.
Application Of 3d Reconstruction Technology In Basketball Video Scene
The explosive growth of multimedia information requires people to study and develop video retrieval technologies. In recent years, the research with the main target of video content analysis has become a hot topic. Sports video analysis and reconstruction require high intelligence as well as visual and auditory technology work, and practical applications require careful attentions to a wide range of technologies. In this paper, the key technologies were studied, and the algorithm of restoring 3D scene information in broadcast video was proposed. The advantage of this algorithm is that it relies only on the data of a camera, which assumes that the camera is located at a fixed position of the site. The algorithm can estimate not only the position of the object on the surface of the golf course, but also the three-dimensional position of the ball in the air. The algorithm determines the internal matrix of the camera by rotating and zooming automatic camera calibration, then, the external parameters of the camera can be obtained according to the corresponding relationship between the ground plane and the image plane.
Application Of Neural Network Algorithm In Financial Market Modeling
In order to succeed in a competitive world, any organization should not only maintain a good understanding of the current situation, but also predict the future as accurately as possible. Therefore, neural network technology is well suited for analyzing the historical trends of data and predicting it as a critical task. In this paper, based on the neural network, the trend of the financial market was modeled and predicted. The results show that the neural network model produces better accurate prediction than other time series prediction models. In the financial market, this system usually involves the use of other financial indicators and domain knowledge, and can greatly facilitate the prediction of exchange rates.
Application Of Data Mining Technology In English Online Learning Platform
With the maturity of Internet technology, more and more people choose online platform for learn online. The emergence of English online learning platform has ushered in a wave of upsurge. In order to improve learner's response abilities and enjoy good learning resources, the online behavior modeling analysis was used to greatly improve the effect of English online learning. On the basis of the existing platform, the learners' operation cookies in the platform command behavior were obtained, so as to establish a suitable online learning behavior evaluation model from the perspectives of learners' preferences and learning outcomes. The establishment of learning behavior evaluation model can provide scientific and reasonable guidance and help for learners' learning behavior.
Application Of Apriori Association Rule Mining Algorithm In University Management System
Liu Yan, Wang Cunrui, Wang Nannan
The emergence of the digital era has made a revolutionary change to the design of the management system of colleges and universities. Apriori association rule mining algorithm has been run through the whole process of the university management system. An appropriate algorithm for the management of data resources was used in fragmented and chaotic Universities，which can accelerate the standardization of local resources and improve the utilization of data management resources in Colleges and universities. Based on this, the application of Apriori Association Rule Mining Algorithm in the university management system was studied. The university digital data archives were introduced firstly and then the Apriori algorithm was introduced in this paper, and finally the application of Apriori Association Rule Mining Algorithm in the university management system was introduced in details. Test results showed that the application of Apriori Association Rule Mining Algorithm in the university management system was more practical and reasonable.
Design And Implementation Of The Syntax Check In English Writing Assisted Reading And Appraising System
In the globalized modern society, in order to strengthen the foreign exchange, it is necessary to face some English writings, and some grammatical mistakes are inevitable in our daily English practices. Therefore, some syntax check and error correction software has been developed. In this paper, the current situation of English assisted reading and appraising system and their respective advantages and disadvantages were firstly elaborated; then the system modules of article and preposition error corrections were proposed respectively, and were judged based on the word segmentation and part of speech tagging technology; finally, the proposed scheme was validated, and the F value was used to detect and evaluate the proposed scheme.
Tourism E-Commerce Website Quality Evaluation Based On Ahp
Tourism e-commerce as a new thing, its development has a strong uncertainty, this paper studies the quality evaluation index system of tourism e-commerce model mainly through the evaluation of website function. From the perspective of the value chain, this paper uses AHP to evaluate the tourism e-business model, which can solve the problem of uncertainty and establish the index system more systematically. First, use analytic hierarchy process (AHP) to establish five first-level indexes and 22 second-level indexes. The Delphi scores are obtained by experts to get the pairwise comparison matrix, and then calculate the weights of each index value to complete the construction of evaluation system.
The Design And Development Of The Painting Color Learning System Based On Android
In recent years, mobile learning has been widely used in the education and training of schools, enterprises and other institutes. It has received wide attention because which can use the fragmentation of time and improve the efficiency of learners. Color has a great influence on people's life and work. Mobile learning methods for color learning brings reform in education, which increase the communication between learners and learning environment. The painting color learning system proposed in this paper is to aim at providing a more convenient color knowledge base and making it easy for learners communicate with each other. As a teaching tool, the system can train people’s sensitivity to different color. In order to achieve this goal, recommendation engine technology is added to the system. Through the learner's preferences and other colors match instance, best match was pushed to learners based on color similarity, which improves learners' interest and education quality.
Research On Art Education System Based On Bs
With the development of network technology and the rapid development of computer technology, the traditional mode of education is also quietly changing. Online education system based on network is a kind of system which can effectively manage and share the resources between the students, so that students can better communicate with the teachers and students. In this paper, the concept of BS system was introduced, and then the overall design of the system and the database logic structure were introduced. Finally, the system test method was presented and analyzed. Nowadays the network education is more and more developed, so teachers should keep up with the times, and actively use technical advantages, to achieve a more convenient and efficient education.
The Design And Application Of English Online Learning System Based On Bs
Since the inception of the new era, the development of the Internet technology has also promoted the upgrading of electronic equipment. And the online education mode budding at the end of last century has also yielded extraordinary results; especially for English, its online learning system has become more mature because of its needs of more voice communication and training. Taking this as the research object, this paper firstly introduces the related concepts, and then conducts a demand analysis of the system, and finally elaborates the related information about the system structure and database, hoping to provide a reference for the related research.
Research On Calculus Teaching Based On Matlab
MATLAB algorithm has been widely applied into calculus teaching system, while there are some deficiencies in the interactivity of system and the richness of curriculum. Therefore, it is necessary to further improve the calculus teaching system with MATLAB. Based on the embedded technology and GeoGebra program, this paper extends the symbolic feature system of GeoGebra, and provides geometric, algebra and calculation functions in software with cross-border user community approach. In addition, the basic calculus concept of derivatives and anti-derivatives is proposed in this paper. Furthermore, a precise and rapid calculus teaching system has been designed, which can be used for college- level calculus teaching.
The Application Of Computer Modeling In Teaching Test Based On Rasch Model
As computers are increasingly applied into science instruction, studies on computer modeling have transferred from macroscopic theory description to microcosmic empirical research and from experience-based explanation to the revelation of measurement-based statistics method. As an important tendency of information technology and subject instruction integration, the study of computer modeling is increasingly connected to the modern learning theory. Guided by the modern test theory, this article reveals the general method and process of the design and test of computer modeling in teaching test. The results show that the Rasch theory and the "four--stone" model can effectively guide the development and revision of the teaching model of computer test.
Design And Realization Of Sports State Monitoring System Based On Intelligent Mobile Terminal
Cui Shengli, Wang Limiao, Li Junyu
The maturity of highly integrated hardware technology and the rapidly development of sensor technology provided a material basis for the study of the sports state based on intelligent mobile terminals, and the mature model method theory provided a theoretical basis for the study. Based on this, we designed and realized the sports state monitoring system based on the intelligent mobile terminal. We presented the concept of human sports state monitoring based on three-axis acceleration sensor, and gave the basic design of three-axis acceleration signal acquisition, basic motion state recognition algorithm, fall detection and sedentary monitoring. At the same time, the system was verified and the test results were given. Test results showed that the design of intelligent mobile terminal based on the sports state monitoring system can meet the actual needs.
Research On The Application Of Software Auralia And Overture In The Solfeggio Teaching
Through the present music education of Higher Normal University, analyzed the using software to assist teaching method to solve the problem. Focusing on Solfeggio software Auralia and music score Overture software applications; select the part of the students tracking research. The results show that Auralia software to improve student achievement in solfeggio has obvious help.
Planning Research Of Tourist Villages With Gis -- Taking Jinqiao Village Of Yuanan County As An Example
By adopting the theory of landscape ecology and basing on GIS, a modern research method of geoscience, this paper takes Jinqiao Village of Yuanan County as example of village landscape and establishes database of village landscape. The landscape richness index, dominance index, evenness index, divergence index and fragmentation index of Jinqiao village are choosed to do quantitative analysis for its landscape characteristics and space differences, so as to make structural plan for its landscape and promote the formation of its tourist characteristics.
A Study Of Oral English Teaching Based On Secondlife
SecondLife is a support environment for oral English teaching research, focusing on the teaching activities in the SecondLife environment. First of all, this paper on SecondLife 3D virtual environment where system is introduced, then the SecondLife environment of spoken English learning activities designed and described. Then, this paper on the basis of the above design specific oral English learning activities of the experimental scheme and put into SecondLife oral English learning situation is in the test. Finally, the experimental results are analyzed and discussed. The results show that the SecondLife environment of oral English learning activities can promote the learner's learning of spoken English. It effectively supports the learning activities of the elements of each link, improves the learning initiative. In this paper, the design of learning activities is reasonable. The learning effect is obvious. And it effectively improves the learners' oral English level in the abstract.
Study On Anti-Oxidative And Anti-Exercise-Fatigue Function Of Extracted Maca
This paper discusses the effects of the Maca in alcohol extracted Chinese herbal compound on improving sexual function of mice and anti-fatigue of the exercise mice. Sixty ICR male mice were randomly divided into 6 groups. The mice in the blank control group were fed with distilled water. The mice in the traditional Chinese medicine compound alcohol extraction group were given stomach doses respectively in accordance with 1.0, 2.1, 4.2 g dry powder / kg and 2.83 g traditional Chinese medicine / kg. The mice in maca alcohol extract group were given stomach doses in accordance with 2.1 g Maca dry powder / kg. Viagra can be a positive reference drug. The content of nitric oxide (NO) and testosterone in the serum of mice were determined by continuous administration once daily for 15 days. Another sixty ICR male mice were divided into groups according to the above-mentioned dosagee (the positive drug was set as American ginseng tablets) to measure the weight-bearing swimming time, blood urea nitrogen content, lactate dehydrogenase activity and succinate dehydrogenase activity in muscle of mice after exhaustive swimming. Compared with the blank control group, the alcohol extract of Maca Compound could significantly increase the serum NO level (P <0.01), but had no significant effect on the testosterone content. Also, it can significantly prolonged the weight-bearing swimming time(P <0.01), reduce the BUN content(P＜0.01) and the LDH activity(P＜0.01), improve the activity of SDH in muscle (P <0.01). The alcohol extract of Maca Chinese herbal compound can significantly improve the sexual function of mice and has obvious anti-fatigue effect.
System Design And Implementation Of Online Examination System Based On Intelligent Test Paper Composition
Peng Liangqing, Wu Yanpeng
Great changes have taken place in the traditional examination forms with the development of the Internet. By studying the needs of some schools, this paper introduces the design and implementation of the online examination system based on intelligent test paper composition. To begin with, the theoretical basis of the online examination system and intelligent test paper composition is elaborated. After that, this author clarifies the idea of this system design, writes an algorithm, and finally designs an online examination system that takes a browser/server mode, is equipped with one huge question bank and a number of integrated functions underpinned by ASP and SQL Server 2000. Online examinations are of great significance in online teaching and its system implementation can be extended to the field of online education.
Research On Image Recognition And Matching Based On Ant Colony Algorithm
Zhengkai Zhang, Daoyou Huang
With the rapid rise of cloud computing, all industries attached great importance to the collection of information and the search engines also provide the image search mode. As is known to all, computers can only recognize computer language and we can input image, which is just this research all about. This paper first introduced related limit concept as well as the working principle of ant colony algorithm, and then conducted an in-depth research into the image recognition and matching methods based on ant colony algorithm via computer technology and statistics algorithm. The paper first adopted ant colony optimization algorithm to conduct the recognition research on the image and then discussed the specific significance of ant colony algorithm in image recognition.
Evaluation Of Rural Financial Ecological Environment Based On Ahp-Dea Model
Lezhu Zhang, Weiqing Wang
In recent years, problems related to agriculture, rural areas and farmers have gained much attention from the party and the state. gained much attention from the paz-ty and the state. From 2004 to 2011，the central government has given top priority to solving problems related to agriculture, rural areas and farmers through the “NO. 1”s document for eight years, including promoting agricultural production and farmers' income. Based on the overall layout of the cause of socialism with Chinese characteristics, the Third Plenary Session of the party depicted the grand blueprint for China's rural well-off construction, and developed a program of action for promoting rural reform and development under the new situation. As the core of modern economy, finance plays a leading hub role in the allocation of resources. Largely the level of rural financial service affects the level of economic development in rural areas. The benign development of the rural finance can't go without the rural financial ecological environment. And in turn, the optimization of the rural financial ecological environment can also improve the rural financial service system and gather more funds for the development of the rural economy, accordingly, to improve the economic competitiveness of rural areas and promote the harmonious development of the rural economy and society. The scientific evaluation of the rural financial ecological environment and the solution of the relevant problems are the important parts to promote economic development and ensure financial stability. In this paper, we take the rural financial and ecological environment of Shandong Province, use AHP and DEA to analyze the problems from the economic foundation, financial resources, government behavior, legal environment, intermediary service and education technology, and give the views and suggestions to optimize the rural financial ecological environment.
Application Of Dynamic Programming Algorithm In Accounting Management
Based on the optimization principle, the dynamic programming algorithm can transform the multi-stage process into a series of single stage problems and then solve them one by one, which can efficiently solve many problems that can't be solved by greedy algorithm or divide and conquer algorithm. In this paper, combined with the problems in management accounting, operations research and financial modeling were applied, and the normative research method was used simultaneously. Then, in view of the combination of data mining and strategic management accounting, the application of dynamic programming algorithm in management accounting was discussed. The results show that the dynamic programming algorithm plays an important role in the enterprise competition environment and enterprise crisis warning. Finally, the analysis of competitive environment of accounting firms based on dynamic programming algorithm, and the realization model of enterprise crisis warning were put forward.
Design and implementation of accounting computerization system in colleges and universities
Xiaofeng Dai 1,2 ,Weidong Zhu 1,2
The design and optimization of accounting computerization system is helpful to improve the level of financial management in colleges and universities. In order to improve the efficiency of financial management in colleges and universities, in this paper, the current research situation of accounting computerization at home and abroad was introduced, and the construction and application of data access model were expounded. Finally, the data results of the system test were analyzed and the conclusion was drawn. The results show that the university accounting computerization system is running normally and ADO.NET computer database technology can improve the operation efficiency of accounting computerization system in colleges and universities. The research results were summarized and the relevant suggestions were put forward, and a new way was provided for the improvement of the financial management efficiency of colleges and universities.
Early warning of international trade in agricultural products based on cart algorithm
Today, society has entered a highly information-based era. Huge amounts of information will appear every day. How to extract useful information from vast amounts of data and create value has become a key issue. In this paper, in view of the trade frictions and disputes in international trade, the application of CART algorithm in international anti-dumping was briefly introduced. And taking the anti-dumping case published by China trade remedy information network as the object of study, trade data was collected. The CART algorithm was adopted, and a decision tree of antidumping classification was constructed. Through this decision tree, whether anti-dumping cases can occur in international trade can be warned and judged, so as to provide decision-making basis for the relevant government departments and enterprises to avoid risks.
The design and simulation of the website dynamic security defense system based on the game theory
The website defense process is a game process and in the constitution course, it requires people to pay attention to the stability of the game process. This paper not only analyzes the game theory, but also the possible forms of attack happened in the actual operation work process and the principle of how websites work. Combined with the game theory, it analyzes the game object and the game process in the course of the website dynamic security defense. According to the system definition, it is known that ensuring certain stability of the system is the first priority when it comes to the strategic analysis course of the system evolution. Namely, make sure a dynamic balance of two parties in the evolution course. It tries to build up a system structure that is suitable for the common forms of website attack, to simulate the system and to research into its actual working performance.
Swimming teaching system based on simulation technology
The development of computer application technology and mechanical engineering has laid a solid foundation for the study of virtual human. Simulation technology has been widely used in people's daily life. Through the currently known virtual humanoid behavior technology, the periodic action of swimming was explored; and then the actions produced by human swimming were broken down, in which four key actions frames were extracted and solved, so as to realize the simulation of the swimming position of the human body. Finally, the result of the system operation shows that the method can achieve the smooth process of human swimming, and greatly improve the efficiency and quality of swimming teaching.
Target tracking technology of sports video based on particle filter
With the development of sports, people pay more and more attention to it. At the same time, the demand for target tracking in sports video is also increasing. Aiming at the difficulty of target tracking in sports video, in this paper, the research on target tracking technology of sports video based on particle filter was proposed. Through the construction of particle filter model and the construction of mean shift algorithm, the algorithm of target tracking in sports video was optimized. The test results show that the time spent on the algorithm of target tracking technology of sports video based on particle filter algorithm is short, the number of particles needed for accurate tracking is less, but the real-time and accuracy are good.
Research and implementation of art animation system based on video streaming
In order to design and study the video-based art animation system, in this paper, firstly, the problems existing in the process of traditional manual drawing art animation were analyzed. Then, the art animation research system based on video streaming was designed through video segmentation, graphic matching, non-realistic rendering and other methods, so that the random transitions in video styles were achieved. Furthermore, the high degree of space-time consistency was also guaranteed. Through the video segmentation and matching, the contour line of the video was easily adjusted, and the semantic region of two temporal and spatial domains between the split contour lines and interpolated contour lines was formed. In addition, according to the style selected and drawn by users in the semantic area, the system could automatically generate the corresponding style of art animation. The system designed in this paper can not only guarantee the continuity of time and the smoothness of time dimension, but also avoid the fragmentation of adjacent semantic area, which lays a theoretical foundation for the design and research of art animation system based on video streaming.
Tactical analysis of sports competition based on data mining tools
In order to study the specific application of data mining technology in sports competition tactical analysis and competition data analysis, in this paper, the tactical analysis system of table tennis and badminton was taken as an example, and the application of data mining technology in the tactical analysis of sports competitions and the problems faced were introduced; then the association rule analysis, Markov process analysis and cluster analysis were used, and the traditional tactical analysis system of table tennis was optimized and upgraded; in addition, the data mining was introduced into the tactical analysis system, then the game data were summarized and analyzed, and the tactical skills were analyzed in real time, and the data mining techniques used were tested. The results show that data mining technology plays an important supporting role in the tactical analysis of sports events and the establishment of scientific training programs.
Dance teaching system based on somatosensory technology
Dance entertainment has been a popular cultural and recreational activity since ancient times because of its high artistic value and fitness value. Today's dance entertainment products are diverse, yet which will generally give users a relatively high cognitive load in use. Based on this, the dance teaching system based on somatosensory technology was studied in this paper. Firstly, the application scope of natural somatosensory interaction technology was introduced. Then, the application of dance entertainment was analyzed. After that, the dance teaching system based on somatosensory technology was studied. Finally, the practical application experiment was carried out. The application results show that users believe that dance entertainment system has the advantages of easy sense of body interaction, easy operation and low learning load, and can greatly improve the effect of dance teaching.
The game type identification technique for sports video based on finite-state machine
With the significant technological progress in the manufacture, storage and dissemination of multimedia data, digital video has become an indispensable part of people's daily life. How to manage and retrieve massive amounts of video data has become one of the most challenging hot topics in the world for academics and industry over the past decade. In this paper, a fast and robust global motion estimation algorithm was used to estimate the global motion of the video sequence, and a series of image feature extraction algorithms such as dominant color histogram and cumulative histogram were used to complete the low-level feature extraction of frame images. Through this study, the construction of FSM, the training of FSM parameters and the identification of the game type were carried out in the typical game of sports video.
Research on virtual interaction design based on augmented reality concept
In recent years, with the rapid development of science and technology, a new technology, the augmented reality technology, is developed. At present, the development of the augmented reality system is generally to pursue the practicality of the system. Therefore, in this paper, firstly, the research status of the augmented reality technology was expounded, and the system was reformed by fast quadrilateral detection. Thus, the computer virtual interaction technology was designed to improve the practicability of the system. Through the research, finally, a set of computer interaction system based on the concept of augmented reality was obtained, which can realize the convenience of the user when using the system. And the way and mode of virtual interaction of strong display system were expanded.
The mobile teaching system for teacher training based on self-adaption
The traditional teacher training is hierarchical and regional with some difficulties in the implementation of the training. The teaching system of teacher training based on Internet can break the limitation of time and space and improve the feasibility of implementation. Thus, in this paper, the research of the mobile teaching system for teacher training based on self-adaption was proposed, and the adaptive teaching model was added to the general teaching system for teacher training, so as to meet basic requirements of teaching students in accordance with their aptitudes. The system can support mobile devices and can make good use of fragmented time for learning and training, so it can improve the efficiency and effectiveness of training, and it is more in line with the individual needs of teachers.
Research on ecological environment information system based on component gis
In order to comprehensively analyze and manage the ecological environment systems involved in a number of research departments and research areas, it is necessary to establish an eco-environmental information system. Through the use of geographic information system GIS, eco-environmental information system can break the traditional eco-environmental management system development model and promote the development of spatial data conversion of eco-environmental information management in the traditional statistical data management. Based on the theory and technology of GIS, in this paper, the research and application of GIS in system integration environment protection work were combined. Then a new approach to eco-environmental information systems was explored, and strong technical support was provided for eco-environmental management and decision-making science and technology.
The application of computer simulation analysis in the study of virtual economy and real economy
With the development of economic globalization and e-commerce, enterprises are under increasing pressure. The virtual economy and the real economy reflect two different modes of economic operation. In this paper, starting from the different operation characteristics of virtual economy and real economy, the research was carried out on the basis of the computer simulation. Then comprehensive variation coordination method and coupling coordination model were adopted, and the static coordination degree and the dynamic coordination degree between the virtual economy and the real economy system in China were calculated. Finally, the experiment proves that the virtual economy depends on the real economy, and the real economy is the foundation of the virtual economy. The appropriate development of the virtual economy plays a positive role in promoting the real economy.
Application of decision tree algorithm in student performance management in colleges and universities
Due to the continuous enrollment expansion in Colleges and universities, many schools have accumulated a large number of the basic data information of students and the data information of students' academic achievements. However, the data still remains in the stage of backup, query and simple statistics, and can’t play its proper role. In this paper, the data mining classification algorithm was studied emphatically. The theory of the decision tree ID3 algorithm and the C4.5 algorithm was introduced and analyzed in detail. The advantages and disadvantages of various classification algorithms were summarized by comparing the common classification algorithms, and the basis was provided for choosing the C4.5 decision tree algorithm. The final experimental results show that the calculation method proposed in this paper can accomplish the student performance management better.
Information Sharing And Application Of 3d Design Software In Interior Design
With the development of computer design software, computer design software with characteristics of authenticity and rapidity can easily reflect the design concept and design scheme, therefore, the three-dimensional design software of architectural design and interior design has become the most important design tool of the modern architectural drawing scheme design. In this paper, the architectural design and interior design were taken as the main objects of study; after fully understanding the characteristics of architectural design, the information sharing and application of 3D design software in design were discussed; and then the process and key technology of integrated application of 3D design software were discussed. The final experimental results show that the interactive use of information among multiple design software can make the architectural design and interior design more convenient and efficient.
Design And Implementation Of The Auxiliary System Of Syntax Check In English Composition Review
In order to improve the accuracy of grammar check, the supplementary system for English writing marking and grammar check was designed and developed. In this paper, the multilayer syntax rule library and the N-gram model were used to provide the effective error correction capabilities for common grammars; at the same time, the grammar checking model based on machine learning algorithms was designed; grammar modules of articles and sections were checked and corrected; in addition, the error interpolation algorithm was used to reduce the dependence on the characteristics of preposition statements, thus effectively ensuring the stable accuracy. The results show that the supplementary system for English writing marking and grammar check designed in this paper can efficiently complete the grammatical examination of English compositions for students in our country, and the F value can reach 39.7. The system has good performances, and it can provide the theoretical basis for improvement and wide applications of the supplementary system for English writing marking and grammar check.
Virtual exhibition platform of landscape
With the rapid development of computer graphics and 3D technology, landscape design mainly uses 3D display applications to carry out the aided design and results display, but the production in a single scene and the results of 3D technology can't be reused. Based on this, the virtual display platform of landscape architecture was studied in this paper. In view of the above problems, the virtual display platform of landscape architecture was designed and studied. Through the relatively simple interaction, the virtual display application platform was completed, and the landscape scene was displayed in the process, thus achieving the special effects and the reusability of the scene. The application results show that this research can not only guarantee the authenticity of garden leaves, but can also greatly improve the rendering effect of garden scenes.
The decision support system for urban and rural planning supported by cloud computing
At present, the planning business management model which takes the construction of "one map" platform for urban and rural planning as the core is facing unprecedented opportunities and challenges. In order to study the support system for urban and rural planning supported by cloud computing, "one map" of urban and rural planning in professional sectors was promoted to "one map" of smart cities in the whole city; and then the dispersed data center was promoted to the cloud data center of the city; at the same time, the closed business office system was promoted to the intelligent decision support system based on Internet and big data. The final experimental results show that the construction of smart city should begin with the planning of intelligence, and its essence is a set of decision support services for the whole life cycle of urban and rural planning.
Research on cloud security technology in mobile internet environment
With the rapid development of Internet applications, the community depends more and more on the Internet. The network illegal crime becomes the new tendency. A large number of location information and user contact information are generated by the user through the use of mobile Internet-related applications. Therefore, unsafe mobile network technology will enable illegal personnel to obtain this information. Application security has become the main problem of mobile Internet promotion. By analyzing the current problems of mobile Internet networks, constructive security recommendations are given.
Design and application of mobile platform for power marketing
Luli Qiao, Qiang Zhang, Hui Zhang
Due to the rapid development of electronic information technology, China's mobile intelligent terminals and other electronic information technology has matured and has been widely used in life, which has provided the necessary prerequisite for the establishment of intelligent terminal mobile interactive site. Based on the mobile platform, the modern communication technology, power marketing management and computer technology make power marketing have a broader space, which can provide more practical and convenient service, so as to avoid the congenital defect to the greatest extent. The main body of this paper is power marketing system based on mobile platform.
Design and application of power information acquisition system in power marketing
Hui zhang, luli qiao, qiang zhang
With the changing demand of power users, the business demand of power industry has also changed. In this case, new subsystems (SS) or information may be required. In the case of platform conventions, the application of SOA enables different systems to conform to the enterprise service bus (ESB) information interface integration protocol, so that information interaction and application integration can be applied in a multi-tier application system, and the connectivity of the traditional endpoint plug-in application end to interface end can be achieved. In this paper, GPS clock synchronization technology and simulation platform technology of PTP clock synchronization power information acquisition system were applied to ensure that the clocks of the collection terminal and the intelligent instrument are unified with the main station.
Art layout system based on 3d technology
The advent of 3D printing technology represents that China's human science and technology enters a new level, and its impact on today's art circle is unique. In the context of 3D technology, the printing technology was studied. First of all, its essential attributes and functional features were understood in detail; and then the scientific prediction of its future was made and gradually spread to the actual use of art field; in addition, 3D printing was modeled, and the coordinate transformation theory used here provided a solid theoretical support for the application and extension of this technology; finally, through the actual interpretation of some cases, the superiority of 3D printing technology was explained in detail through the display of game scenes, terrain and characters.
Design of marketing system based on clustering algorithm
Due to the rapid development of society, as a product of the new era, e-commerce is in a state of rapid development, and the e-commerce market is also in fierce competition. Based on the characteristics of e-commerce, the analysis of user consumption data will help enterprises to make better marketing programs, so businesses attach great importance to the user data collection and data analysis algorithms. Excellent algorithm will determine to adopt what kind of marketing means, whether it is efficient, whether the product can be recommended better while bringing the intimate service for users. In this paper, the marketing system based on clustering algorithm was analyzed and studied.
Quantitative research on sports behavior based on fuzzy relation theory
More and more attention has been paid to the implementation of video surveillance by computer. The detection of human behavior in sports based on the fuzzy theory is the direction that the research pays more attention to at present. In this paper, an associative network differentiation method based on fuzzy memory was proposed to solve the static and dynamic behavior relationship in human motions. By simplifying the structure of the bones and limbs of human body, a model of the contour change of the limbs of human body in human movement stage was designed, and fuzzy function solving algorithm was adopted to recognize and quantify the act of sports movements.
The logistics management system based on internet of things
Logistics management is the flow law management in the production and sales process of material entities, and scientific and effective management method is adopted to improve the operational economic benefits of logistics. With the continuous development of computer science and technology, the change of intelligent management has taken place on the logistics management system, and the Internet of things logistics is born under this background. Based on the Internet of things application technology, the tools of logistics management system were developed for the enterprise logistics management system in this paper. Combined with the integration technology of Internet of things, the B/S three layer structure design idea was adopted to insert the Internet of things sensing technology into the logistics management data processing system. In addition, SQL Server was used for the database, so as to store and process the data efficiently.
Tourism Education Platform Based On Virtual Technology
Today, the Internet technology has entered the mobile Internet era, and everyone can use mobile devices to access information and access each other. Seizing the opportunity of the Internet and realizing the transformation and upgrading of the tourism industry resources have become the hot topic in the current study. In this paper, with virtual technology as platform, a set of travel experience and education platform based on Internet technology and panoramic VR technology was developed. The consumer can realize the full enjoyment of the local tourism resources through the technology. At the same time, the platform can be built to create a better, transparent, open and fair tourism environment. To create a realistic physical environment can promote tourism education intuitively.
Design Of English Massive Open Online Courses (Moocs) Platform Based On Cloud Computing
The massive open online course (MOOCs) is a digital learning environment for a large number of learners to provide "free" teaching. This technical enhanced learning form provides free and accessible knowledge and opens up a wide field of view for all people. The main contents of this study are as follows: first of all, extensive review of literature was made on MOOCs; secondly, two learning and analysis components were designed and developed for the review of scientific literature; thirdly, the environment of MOOCs was designed and implemented, and the learning analysis evaluation framework was used to evaluate it. The result shows that the whole system allows teachers to access the Internet online, which allows students to study online on the basis of simple, user-friendly, flexible, practical and secure requirements.
Tourism Management System Based On Intelligent Algorithm
Tourism management decision-making needs to dynamically monitor the utilization of tourism resources and evaluate the development of tourism market. In this paper, an intelligent decision support system based on data was proposed and the problem of tourism management decision-making in complex environment was solved. Firstly, a decision support system architecture that combines with several intelligent technologies was put forward and the achievement of some key technologies was introduced, such as 3S and large decision table decomposition. Then, some data analysis methods were proposed to be used in the decision support system, including the tourism information category, the tourism time and space model, the tourism planning navigation, the tourism situation warning and the security events. Finally, several applications of this system were given.
Feature Extraction And Recognition Algorithm Of Paper-Cut Pattern
The paper-cut art has a long history, and this art has become a very good material for the development of animation technology. On the basis of the development of digital media, computer technology and paper-cut technology are effectively combined to promote the rapid development of paper-cut art. In this paper, the recognition technology of paper-cut pattern was studied in depth, and a unique identification algorithm was proposed to improve the recognition effect of paper-cut art. Firstly, the pattern database was established, and the LM algorithm and BP neural network were adopted to train the BP neural network through normalization, so that the recognition efficiency and image representation ability of the recognition algorithm were improved. The identification method can be realized in the computer system, and it lays a good foundation for the development of automatic paper cutting.
Research On The Network Security Defense Model Based On Firewall And Ips Portfolio Strategy
Ying Li, Xin Cheng
With the development of information, Internet has entered people’s life gradually, and the network security accompanied with Internet is also concerned by the public. This paper mainly studied the network security defense model based on firewall and IPS portfolio strategy. First, it analyzed the firewall technology and IPS technology respectively, then studied the two technical work models that is their protections on computer system. After that, it also analyzed the features of the two technologies and their limitations as well as their complementary possibility. Based on this, the paper then studied the portfolio defense system combined with the two technologies, established a firewall technology and IPS technology model, realized a dynamic defense working process with closely integrated interaction to assure user’s network environment security.
Research On Moving Human Bodydetection And Behavior Analysis Under Complex Background
Nowadays the analysis of the human body movement gesture detection is becoming more and more important and it is being widely used. However, the moving human body detection under complex background is still insufficient. This paper puts forward the background subtraction method to trace the moving features of human body and its behavior analysis through the modeling design under complex background. After the research, this paper puts up with a comprehensive survey on the human body movement analysis based on computer vision with its focus on three major questions of human body movement analysis system, namely human detection, trace and activity interpretation. Then this paper discusses all sorts of methods of each question to examine the status of the current technology. Finally this paper ends with the conclusion that behavior interpretation is the analysis and recognition of human movement model and then it will generate higher lever activity and interactive description. This paper also covers some challenges in the research and the future direction of development.
Research On Oral Japanese Teaching System Based On Speech Recognition
Wenting Wu, Tingliang Yan
Most teachers have not received pronunciation training and the self-study of pronunciation skills based on speech recognition can make up for the lack of teaching experience of teachers. This paper develops a CALL (Computer-assisted Language Learning) system to help non-Japanese speakers practice their pronunciation by introducing Japanese bilingual phoneme. The CALL system requires learners to read minimal pairs and these intelligibility fractions are based on perception experiments. Then the system will instruct learners to shorten or prolong their pronunciation. When the communication performance reaches their expectation, the learners can stop the training. When the learners reach the vertex of learning, the understandability index can help them decide whether to further the learning process. The experiments show that the CALL system can point out the mistakes of learners and show them how to improve, which speeds up the process of learning for the learners of Japanese.
Research On Decision Algorithm For Audio Segments Average Short-Time Energy Fusion
Yuyang Wang, Runhua Wu
Audio recognition technology is now widely applied in multimedia. But how to improve its accuracy has been a problem in research field for a long time. In this paper, an automatic segmentation and classification method for audio-visual materials is proposed based on the analysis of audio contents. The basic audio signals in movies or TV programs (e.g. voice, music, songs, and environmental sound) are analyzed briefly to verify the feasibility of real-time processing. It is suggested that the audio signals should be segmented and classified based on the process of heuristic rules. Besides, the forms of time-varied function and statistical analysis are also presented. Based on the audio features, an average short-time energy fusion decision algorithm is established. The experimental results improve that the method proposed in this paper can lead to an accuracy of over 90%.
English Listening And Speaking Simulation Test System
The difficulty of conducting English listening and speaking examination in computer is speech recognition and automatic evaluation. This paper focuses on current listening and speaking system. Integrating the real situation of English speaking and listening test, the paper analyzes the functional requirement of system construction and set up several user identities like student, teacher and administrator in the system. On the basis of this, we build the English listening and speaking simulation test system, combine the function requirements to set up a number of functions in the system, realize the system function through the system use case diagram, exert the role of student, teacher and administrator in the system and facilitate the effective operation of the system. We also conduct feasibility assessment of the system to make it can be applied in reality.
Experimental Research On Item Parameter In The English Self-Adaptation System
This paper is aimed at the lacking of research on self-adaptation system in English teaching in China. On the basis of establishing self-adaptation testing system, this paper combines the system with the English subject in high school, constructs the question bank, and designs the experiment. In the experiment, the tested samples will be compared under two testing models. The self-adaptation testing of the computer should be superior to the normal testing based on the classical testing theories. Further experimental research is conducted on the parameters in the experiment, which solves the inadequacy in the research of self-adaptation system in English teaching in China and lays a foundation for its further development.
Request Scheduling Algorithm For Web Server In Remote Control System
The demand of a network user is, by way of the request, transferred to a Web server for processing. In the transferring process, the emphasis and difficulty is how to effectively improve the ability of processing the request by the server. This paper makes analysis on the service process of the currently common Web server, in which the improvement of the performance is reflected in improvement of hardware performance and the optimization of the request scheduling algorithm. In the optimization of the request scheduling algorithm, the queuing discipline is instituted reasonably, a certain weight, given to each queue, is reasonably allocated to server threads for processing to ensure the request is done within the shortest time. On the basis of the above process, the performance of the Web server itself is improved, and thereby laying a foundation for the effective running of the server.
A Parallel Algorithm Based On Cpu / Gpu Dynamic Coordination Control And Scheduling
Hanyang Jiang1,2 ,Danhua Wang
CPU / GPU dynamic coordination technology is gradually applied to the development of parallel algorithms, but the current algorithm has some shortcomings in terms of efficiency and power consumption. Therefore, it is necessary to further study the parallel algorithm based on dynamic coordination control and scheduling. Based on the power cap technology, this paper sets up the device frequency and the single computing node of the synchronization system by studying the synchronization system of the computer, controlling DVFS and mapping mode. In order to avoid power failure and load imbalance, this paper has developed a new empirical model of performance and synchronization system, these models make the most of the power of the system to reduce the power consumption to a predetermined level, Good settings can be done.
Web Image Retrieval Based On Cloud Computing Model
With the rapid increase of mobile Internet data, it is increasingly difficult to obtain various information accurately. Image retrieval technology is still developing, and it is more difficult to retrieve images in a big data environment, so we need an advanced platform to create retrieval systems. This paper carries out research of web image retrieval based on cloud computing models. Firstly, cloud computing and web image retrieval are researched, and the most common Hadoop distributed platform is explored as a basis for constructing web image retrieval. In view of this, system construction is carried out. While designing the web image retrieval system based on cloud computing models, image retrieval, feature extraction, cloud computing platform, user interaction and other subsystem modules are set up, and the main modules are designed and constructed, thereby building a perfect web image retrieval system.
Connection Between Fine Arts Theoretical Basis And Applied Ability In University Based On K-Means Algorithm
Ying Cheng, Taojing Li
Under the background of higher and higher level of college students' comprehensive quality in the current social strata, the research on the connection between the fine arts theoretical basis and the application ability of university based on K-means algorithm was put forward in this paper. The clustering algorithm was briefly described; then, the computer analysis model was built on the basis of the teaching management system of university C's art major, and the improved k-means algorithm was used to experiment the students. The results of computer cluster calculation show that the theoretical basis and application ability of fine arts students are positively related; when the theoretical foundation is strong, the application ability is generally strong, and vice versa.
Students’ Psychological Forecasts Using Bp Algorithms
Although college students’ mental health is of great importance to families, universities, and social stability, research on this field still slightly lag behind. Based on BP neural network weights, this paper puts forward the concept of mental health forecasting system whose input samples are comprised of ten key factors by using genetic optimization algorithms. It is a system which can offer advanced forecasts and appropriate measures to solve students’ potential psychological problems, improving universities’ stability and students’ mental health degree with great directive significance.
Designs And Application Of College English Listening And Speaking Course Based On Moodle
Teaching patterns are facing the change of reform because of the popularization of Internet technology. After analyzing and discussing the concept, operation, as well as the constructions of online teaching platforms, procedures and practices for designing courses, this paper provides practical methods of course designs and application for online teaching platforms. Through designs of online teaching platforms, college English listening and speaking course is expected to be operated in a better way. Among the Internet teaching platforms, Moodle has its own advantages in terms of design and application. By exploring designs and application of college English listening and speaking course which were designed on the basis of Moodle, this paper aims to offer suggestions and inspirations for the development of online courses of listening and speaking for college students.
Tourism Development Of Minority Counties On Ree Comprehensive Evaluation Model
The comprehensive evaluation model has been widely used in the research of tourism development, but there are still some shortcomings in the sustainability and completeness of the tourism development plan. Therefore, it is necessary to further improve the research of tourism development of the minority counties based on the REE comprehensive evaluation model. Based on the difference analysis technique and the SEQC reference data set, this paper uses the comprehensive evaluation algorithm to analyze the difference of the collected ENCODE data and normalize the key characteristic factors. And this accuracy differential formula is obtained. The design gives a detailed and complete plan for the development of the ethnic minority counties, which improves the accuracy of the evaluation model.
The translation techniques of business english based on spss
By means of statistical analysis software SPSS, the thesis has made a design and an analysis on the translation of words and sentences in business English. The translation of business English is characterized by the use of appropriate annotations, more formal and rigorous language as well as the techniques of amplification and omission, which contribute to adjusting sentences and make it more suitable to the language features of business English. Based on data analysis, the study has investigated the main problems existing in business English translation and found the solutions accordingly, thus achieving the intelligence and precision of translation and promoting the automatic translation of business English. Therefore, the study enjoys great significance in the further development of business English.
Implementation of digital media teaching system on xml
As the rapid development of the internet, various industries blossom because of the advancement of computer performance. With richer resources in teaching industry, its management, integration and establishment of the relevant system have become the concerns of the government and education circle. The thesis introduces the related concepts combined with the current situation of education and teaching, realizes the real-time communication of data information as well as establishes the multimedia teaching system according to the ideas of XML, which is aimed at providing a modern teaching mode for the education circle and improving the teaching quality through the research of the system.
Students’ Psychological Emotion Recognition System On Expression Recognition
Although several methods of human emotion recognition, which are based on facial expressions or voice, have been proposed, the accuracy and robustness of emotion recognition system are still in need of prompt improvement. This paper puts forward and analyzes the advantages and limitations of the system based on facial expressions. It also discusses two methods for the purpose of improving this mode: the integration of decision level and feature level. Detailed facial movements are grabbed through motion capture by using markers on a female student's face. The results show that the system based on facial expressions has better performance than acoustic information system based only on emotions. The results also reveal that the performance and robustness of the system can be improved when two modes are integrated.
Study on accounting system in light of dynamic programming algorithm
Traditional accounting information processing method cannot meet the actual demand. Modern accounting computerization, adopting advanced algorithm to deal with accounting information system, has become an inevitable requirement for modern accounting development. Based on the dynamic programming algorithm, this paper attempts to analyze the principles, combine the basic idea with the accounting information processing to construct the accounting system in light of the algorithm, and then set up the corresponding functional modules in accordance with the system demand. Furthermore, integrating the dynamic programming algorithm with accounting information in system analysis, then the entire accounting system will be promoted effectively to meet the needs of modern accounting data analysis on the basis of this algorithm.
Wireless Networked Sensors In Track And Field Competition Timing System On Dynamic Time Slotted Aloha Algorithm
Wei Zeng, Jin Wang*
In the design of wireless networked sensors in track and field competition timing system on dynamic time slotted ALOHA algorithm, the concept of label is adopted for possible problems. In ALOHA algorithm, several labels send information at any time slot; the reader has certain concepts in the process of receiving information; the reader also has a certain range receiving information for each frame, while reception will be impacted once beyond range. In this study, combining ALOHA algorithm, a new algorithm is proposed to improve the stability of the system. Finally, the algorithm is optimized by MATLAB simulation.
Research On Sports Behavior Characteristics Based On Motion Recognition Theory
Quanyun Liu, Shaohua Yu*
Human motion recognition technology is the focus of research in the field of computer vision worldwide, it can be widely applied in interpersonal intelligence interaction, virtual reality and video surveillance and so on. The technology can transform human motion into action information such as data and symbols, so as to understand, extract and classify these motion features. Based on the study of human motion recognition theory, the characteristics of human physical fitness behavior were discussed in depth, so the current characteristics of human physical fitness were fully understood, so as to lay a certain theoretical basis for the future development of national fitness countermeasures.
Jewelry Design Based On Simulation Technology
The key of jewelry design is to cater for customers' visual needs considering fashion of the times and artistic style. By analyzing the current design of jewelry, this paper draws conclusions of the common design styles, ways of artistic expression and simulations of the way of artistic expression. Intrinsically, the elements of jewelry design mainly include points, lines and surfaces, which convey various feelings combined with varied artistic styles. Jewelry design has its roots in artistic innovation, which can be achieved through the interaction between contemporary elements and traditional artistic styles.
Research On Basketball Skills And Tactics Teaching Based On Non-Scene Target Characteristics
Breakthrough in skills and tactics is one of the difficulties of basketball teaching. How to improve the breakthrough ability of basketball players has become the common concern of physical education teachers. Now many teachers start to use video teaching in basketball class. The thesis takes basketball techniques and tactics teaching as the research case, and provides a new perspective for the dynamic evaluation based on non-scene target characteristics. The innovation lies in that the analysis of basketball skills and tactics is not only spread from the teaching characteristics, but also evaluated from the non-scene target characteristics, hoping to improve the skills and tactics of basketball players through the explanation of the non-scene target characteristics.
Music Recommendation Technology Based On Hybrid Algorithm
There are some deficiencies in the traditional music recommendation algorithm based on theme recommendation combining with suggestion and filtering, for example, music without rating won’t be recommended and the classification of the recommended artists was disordered. Aiming at these deficiencies, this paper hereinafter proposes a music recommendation technology based on hybrid algorithm, which analyses and ranks the theme data with Bayesian network model comprehensively, and introduces statistical simulation variables to indicate the taste of consumers directly. Through experiments comparing music’s audio signal with the rating data, the superiority of the technology in recommending accuracy and artists variety was verified.
Analysis Of Sports Based On Computer Vision
With the wide application of computer in various fields, the intelligent analysis of sports is combined with computer vision technology. Compared with the traditional motion method, it can quickly capture moving targets and record various motion data. Therefore, based on computer vision, sports analysis was carried out in this paper. The development and existing problems of computer vision technology were described, and the human model building and motion capture system were realized. Through the example of table tennis, computer vision technology can improve the scientificity and accuracy of sports analysis. But in the application of artificial intelligence and other high-level analysis methods, it also needs further exploration.
Evaluation Of Regional Economic Development Using Clustering Algorithms
Lina Yuan, Hongying Li*, Dongli Zhang
There are great differences among different regional economic levels in our country. Therefore, to facilitate overall economic development, a scientific economic development strategy is required to be worked out by discovering problems from regional economic development. This paper aims to analyze regional economic development in our country through clustering algorithms, explain the clustering analysis process, classify regions with similar conditions to form corresponding clusters by clustering algorithms, conclude reasons concerning regional economic development from the analysis of those clusters, develop strategies for enhancing economic development levels in accordance with economic development factors of other regions, take regional economic development in China’s seventeen regions for examples to conduct analysis, and then do research into the application of clustering algorithms on regional economic development. And finally, a scientific and effective policy will be formulated for economic development.
Digital Archives Management Platform Using Decision Tree-Based Classification Algorithm
With the application of big data, the way to carry out rapid classification processing and exploit the potential value for the huge data base indicates a research direction for computer information technology and mathematical statistic field. Digitization for archives has exerted a great influence on the storage of information, making management for archives more efficient and orderly. Meanwhile, the application of decision tree-based classification algorithm is able to achieve more effective way for digital archives management and henceforth to enhance the value of the data. In this paper, in light of the data mining, the application of decision tree-based classification algorithm in specific digital archives examples would be discussed, which also provides a reference for the further development of this field.
Appraisal Of Trainees’ Qualities In Taekwondo Teaching Process From The Perspective Of Fuzzy Evaluation
Taekwondo has been listed as one of the most popular sports in the world, whereas there is no conclusion of its influences upon trainees’ qualities. Adopting fuzzy evaluation, this paper researches into trainees’ qualities during Taekwondo teaching process and uses contrastive methods to conduct quantitative analysis upon trainees’ qualities. Conclusions reveal that trainees’ qualities are constantly improved throughout Taekwondo training, which is superior to traditional Kungfu training. Finally, the study points out that blending traditional Kungfu with Taekwondo can achieve their greatest value.
Construction And Application Of Accounting Information System Based On Internal Control
It is witnessed widely that China's market economy has developed a lot in the world, but there still exist phenomena such as financial revenue and expenditure chaos, management out of control, accounting information distortion in many state-owned enterprises and private enterprises. In this paper, the internal control and accounting information system are combined for weak internal control system and single control means. The paper forms an internal control system with texture effect and high efficiency and establish an efficient and applicable accounting information system through the means of contrasting research on the traditional way to build control mode, in order to enhance the current domestic enterprise management level, to prevent the investment risk between enterprises, and to improve international and domestic competitiveness.
Construction Cost Estimation System Based On Artificial Intelligence
Construction cost estimation has occupied a large part of research benefits in construction management. It is very hard to estimate project costs during different stages because costs, sales and profits amount were difficult to be estimated accurately, also short of control information, and problems like analytic errors between direct and indirect cost and project risks. This paper has developed a construction cost estimation system based on artificial intelligence, overcoming the project uncertainties by means of advanced and intelligent computer networks. At the same time, this paper also studies the availability of artificial intelligence.
Optimization Of Self-Study Examination System In Continuing Education Based On Artificial Intelligence
Ruqing Fan, Hong Su, Shujing Pan
The examination system based on artificial intelligence is designed to intelligently select paper and analyze association rules in the paper data. Through genetic algorithm of AI and mining algorithm of association rules, a relevant item bank of self-study examination for continuing education is created which further optimizes the genetic algorithm and improves the rate of paper selection and legitimacy of paper structure based on education test. Apriori algorithm is adopted to optimize data in this system to ensure a better and more stable design.
Research On English Expert Teaching System Based On Artificial Intelligence
Computer-assisted English teaching has become increasingly popular in China, but the existing teaching system is still lacking in feedback mechanism as well as the speed and accuracy of responses in human-computer interaction. In this paper, an English expert teaching system based on artificial intelligence is proposed, a new framework of all-round integrated artificial intelligence is proposed, and the related algorithms are optimized to improve the speed and accuracy of responses in system feedback. The system can also evaluate the score and practice of students, which can effectively complete the information feedback function and carry on the teaching task assignment to the student objectively, thus making the whole teaching process integrated.
Research On Intelligent Dance Teaching System Based On 3d Motion Analysis
This study presents a method of automatically generating a prerequisite diagram, based on which the intelligent dance system is analyzed through the 3D motion analysis. In this paper, an automatic method is proposed to generate the learning path in a rising order of difficulty, which can be used to guide the dance effectively with the three-dimensional action analysis. Also, a self-adaptive discrete incremental teaching method is put forward to further assist the implementation of the design research of the system with the 3D motion as the main research methods, thus achieving the analysis of intelligent dance and realizing the overall design goals.
Engineering Cost Management System On Data Mining
With the penetration of internet and big data, China’s construction industry is undergoing a prompt reform to meet new demands of this era. The reasonable quantitative model is usually developed for the project to manage and process theses data related to engineering cost with minimum cost as well as high efficiency. In this paper, with the help of data mining, an engineering cost management system was worked out which would be able to store and calculate cost data to analyze multidimensional cost by using online analytical technique and in another hand provides some useful recommendations on the design and utility of the engineering cost management system.
Management Accounting System Based On Data Mining
This thesis adopts the standard researching method to analyze the relationship between data mining and strategic management as well as its relative theories, which further describes the relationship between data mining and management accounting. Then, the thesis analyzes the challenges faced by strategic management accounting in new commercial environment, the enhancement of the role of data mining in management accounting as well as the system framework for strategic management accounting. Finally, under the guidance of relevant theories, the role of data mining in the crisis warning in enterprise competition environment is analyzed and its function in enterprise competition and enterprise crisis warning is further put forward.
Research On The Administrative System Based On Data Mining
With the rapid growth of data in today’s world, how to extract effective information from massive data becomes the shackle of development. In this context, data mining has emerged and provides a solution for the problems. Based on data warehouse, data mining, management software and other technologies, especially through data mining, that is extracting useful information from large bodies of data, organizing identifiable and valuable customers, and predicting future behaviors, the study focuses on the special dichotomies between neural network and chi-square automatic interaction detection, and discusses the advantages and challenges of various technologies in data mining software. The study is useful in achieving the automation based on data mining, and enabling the enterprises to use knowledge to make effective decisions.
Research On Human Body Detection And Gait Recognition Based On Sports
With the increasing demands of security in today's society and the development of computer and artificial intelligence technology, human detection and gait recognition techniques have been widely used in medical research, human-computer interaction and intelligent monitoring. This paper studies the human body detection and gait recognition based on sports, explores the human detection technology, finds out the existing problems, puts forward the research method of human body detection and gait recognition for the problem, and adopts the experimental contrast method. This paper use the shape matching method to detect, and then use the human body model to match. The machine learning is used for each of the detection to be extracted, and then the classifier is used to identify the human body and non-human body. Based on the motion segmentation and contour image processing of gait recognition, a detailed description of the image is obtained by using the shape context, and the gait recognition motion segmentation. After that, modeling, non-modeling and gait data are described. And comparative analysis is made through the image.
A Study Of Landscape Design On Physical Model
Heng Wang, Yanxia Gu, Shuo Wang
The landscape design is a process of mutual integration between human and the natural environment in which there are still deficiencies. This paper does some research into the landscape design with the main method of physical model. Standing on the case of Baiyun Valley, the landscape is expected to make a corresponding improvement and construction based on physical model so as to achieve mutual integration and promotion between people and nature as well as possible. After the introduction of physical model and landscape design, the results of the study based on the convergence of the two points are to prove its feasibility and effectiveness.
Aerobics Teaching System Based On The Technology Of Virtual Character
At present, aerobics teaching activities in colleges and universities are mainly based on the traditional classroom teaching mode, lacking resources for students' autonomous learning, unfavorable to the cultivation of autonomous learning ability. This thesis is based on the research of status quo of aerobics teaching in colleges and universities, and the students’ demand for the aerobics learning. Virtual character technology integrates role modeling, skeletal animation technology and virtual character interaction. This thesis develops a virtual teaching system, which is applied to students’ learning process. It analyzes and reflects on the problems encountered in practice. With the development of information technology, all kinds of teaching methods arise. Virtual character technology becomes more mature when applied to sports skill teaching.
Research On Multi-Modal English Vocabulary Auxiliary Teaching System In Colleges Based On Mobile Application
Currently, the level of education has been continuously improved, but educational reform is still urgent. There are still some deficiencies in the existing educational model. Under the guidance of the educational model both at home and abroad, using the research results of Internet technology, this paper combines the existing mobile terminal with English theory teaching and apply them to the teaching of college English vocabulary and construct the multi-modal auxiliary teaching system. This model combines traditional English vocabulary teaching and multi-modal mobile application teaching, which can effectively stimulate non-English major students’ 'interest in English vocabulary and increase their vocabulary.
Optimization Of Wireless Sensor Network Based On The Genetic Algorithm
Chengsong Hu, Lian Xue
In order to reduce the working energy consumption and increase the service life of the wireless sensor network, a genetic algorithm for optimizing the sensor network routing has been designed. Through the combination of important parameters, the thesis has established the corresponding fitness function and set the appropriate coding mechanism. Applying the genetic algorithm into optimizing the network energy is to find the best routing path based on the node’s residual energy and reference transmission on the energy consumption. The simulation result shows that the design based on the genetic algorithm can make the energy consumption of nodes and the number of adjacent nodes reach the equilibrium state, and can optimize the energy consumption management, thus prolonging the service life of the network.
Research On Image Optimization Based On Ant Colony Algorithm
To explore the problem of image optimization based on ant colony algorithm, this paper summarizes the research results of ant colony algorithm based on its emergence, development and application history, and proposes the function and method of image optimization by presenting the specific process of image optimization based on ant colony algorithm. In this paper, the image optimization design based on ant colony algorithm is described in detail; the initial value of ant colony equation is given; the image optimization model based on ant colony algorithm is designed; and the solution process of image optimization by ant colony algorithm is analyzed in detail. The simulation results show that the proposed method of image optimization based on ant colony algorithm is effective.
Research On Application Of Financial Data Mining Based On Incremental Clustering Algorithm
In this paper, we use the idea of center point to express the summary information in BIRCH algorithm, and use the idea of incremental distance algorithm to improve the efficiency of the determined center point. At the same time, the method based on the conceptual model is applied to the result of the clustering output, which further improves the output quality of the algorithm by making the output result more compatible with the understood hierarchical relationship. And then we further put forward to apply this core tree algorithm to the national foreign exchange information management decision-making system, and make the appropriate analysis to prove the feasibility of this approach, so as to make the use of whole algorithm more reasonable.
A Research On The Design Of Exhibition System Based On Intelligent Technology
Xiaobo An, Zhaohui Zheng
Although information devices and systems have been widely used in the guidance service of exhibition, there are still some key requirements that are not satisfactory. This study systematically reviews the requirements and then presents a new architecture to guide the exhibition services; furthermore, based on ZigBee and ontology, provides a new design of guide device and guidance recommendation system. The paper presents a comprehensive and extensible architecture of guidance service, and an automated and personalized system of guidance service, which overcomes the limitations and weaknesses of short-range constraints and network saturation problems in conventional booting systems in congested environments and can provide online user with condition monitoring and real-time recommendation services.
Hardness Test And Strike Experiment On Ping-Pong Balls
Yu Zhang, Qun Sun, Fanyou Meng, Huan Meng
Traditional testing method of ping-pong balls has become insufficient because the sales volume of ping-pong ball keeps rising as this kind of sport is gaining an increasing popularity. This paper puts forward two new methods for the detection of ping-pong ball hardness and the strike experiment, which both need the assistance from elaborate equipment which is produced by contemporary technologies. The accuracy and scientific attributes of the conclusion of the experiment is ensured by single-factor and multi-factor tests. In the test, the change of ping-pong ball is observed under different loads and form variables. Relevant data are processed, analyzed and verified.
Design And Implementation Of Enterprise Financial Management Information System
With the development of the Internet, the management of enterprises has changed a lot. The traditional management methods have been unable to adapt to the existing management. How to make the enterprise financial management informatization and networking has become the focus of research. Under this background, the present situation of domestic and foreign enterprise financial management system was analyzed in this paper. Based on ASP technology, combined with the specific functions and the overall framework of the system, the management system was designed. And its security and functionality were tested and analyzed. Thus some contributions were made to the design and implementation of enterprise financial management information system.
Research On Design Of Sport Detection System And Method Of Fall Predictions
Falling down is the most common cause for the short career of athletes. Based on this, it is necessary to study the effective detection system on the fall of athletes, thus minimizing the impact of fall on the athletes. In this paper, the design of sport detection system and method of fall forecasting are studied. Firstly, the fall detection system is constructed by analyzing the demand of fall detection system, on the basis of which the whole frame of fall detection system is formed, the design and modeling of the fall detection systemic framework are developed, and the system functions are realized at the principle of fall detection method supporting vector machine. Then the fall prediction of athletes is studied by predicting the fall process of the athletes with the fall forecasting algorithm based on Hidden Markov Model, reducing the risk of fall of the athletes fundamentally.
Research On The Core Teaching Content Of Network Database Development Course
Yufen Feng, Yubin Liu, Peng Zong
Database system research is often the core of undergraduate and postgraduate courses related to computer science and information system. However, this course has some parts that learners find difficult, especially in database analysis and design of abstract and complex areas. This article reflects these difficulties and describes a teaching method that is inspired by the principles of constructivist epistemology to help overcome these difficulties and provide knowledge and high-level skills to effectively understand and perform database analysis and design as a professional practitioner. This article presents some preliminary results of this work, demonstrating that students can learn how to develop effective modern information systems.
Research On Image Quality Evaluation Based On Human Visual System
Image quality assessment aims at finding accurate computational models to predict changes in visual quality of images. Image is a visual entity obtained by using various observation systems to depict the objective world in different ways. It is relative to the text and graphics information contained more vivid and more abundant, is the so-called "seeing is believing". Because the image data in the process of acquisition, compression, processing, transmission and recovery may introduce a variety of distortions, these distortions will be difficult for subsequent image processing, analysis and understanding, is not conducive to people's correct understanding of the objective world. Therefore, it is necessary to design the method and optimize the system by measuring the degree of visual distortion of the image to provide the best visual quality with the least cost. According to the basic problem of image quality evaluation, explore the human visual system and digital information link based image sparse representation in feature modeling and distortion, construct the objective evaluation method for various caused by unknown factors in image processing, to measure the degree of distortion of images and the ability to provide information, so as to provide a reasonable basis for the evaluation of visual quality.
Research On Optimization Of Gprs Wireless Data Transmission System
With the rapid growth of mobile users, there are more and more problems in mobile network operation. On the one hand, traffic density, frequency resource and equipment interconnection network configuration make the rationality and adaptability should be improved; on the other hand, with the construction of GPRS network and services of the opening of the pace of business and increase user's GRpS network problems gradually exposed. This requires operators to invest more energy and capital into the network optimization to meet the needs of users. This article from the perspective of GPRS network optimization, introduces the GPRS mobile communication system and related interface protocol, lists and descriptions of the main parameters influencing the performance of GPRS, with the optimization of GPRS process are given, and according to the related work experience, put forward the problem and parameter adjustment method is often encountered in GPRS optimization and adjustment according to the design data the software parameter adjustment method. Starting from the example of the daily CQT test, according to the access performance issues, data transmission performance, abnormal PDP dropped and abnormal TBF dropped a detailed solution is proposed.
Numerical Analysis On The Stope Safety With Effect Of Fluid-solid Coupling In Underground Mining
Shuqi Ma, Shuran Lyu, Wei Liang
Taking stope of underground mine as the object of study, this paper research the effect of burying depth and bilateral coefficient on the roof of stope with taking hydraulics into account. The fluid-solid coupling model was constructed and solved by the numerical method with using FLAC3d. According to the result, the coupling model is accurate to calculate and predict the safety of stope after comparing with measuring data. Therefore, it is shown that the maximum tension stress and settlement of roof increase with the growth of burying depth and decrease with the bilateral pressure coefficient; the maximum height of plastic failure increase with the burying depth and bilateral pressure coefficient.
Kinematics Analysis On The Walking Posture Of Exoskeleton With Wearable And Power-assisted Lower Extremity
Zheng Yi, Zhong Peisi, Liu Kunhua, Yang Kaige
Abstract：The exoskeleton with power-assisted lower extremity is the organization helping the wearer’s movement based on the anthropomorphic design principle. The kinematics analysis was conducted on the common walking posture aiming at the working principle of exoskeleton with power-assisted lower extremity. The kinetic feature of people’s lower extremity joint and the kinetic period of people’s walking posture were analyzed, the DOF distribution for the kinetic joint at the lower extremity was conducted, the coordinate system for people’s walking posture was established, D-H kinematics model for people’s walking posture was built, D-H parameter table for the walking posture of lower extremity was obtained, the formula deduction was made on the location of three kinetic joints in the basic coordinate system, and the simulation was conducted to verify the correctness of the theoretical analysis. The kinematics research on the exoskeleton with power-assisted lower extremity provides the vital theoretical basis for the control system, and the research result also offers the important reference basis for the research of humanoid robot’s walking kinematics.
Analysis Of Lifting Force For The Four-leg Jacket Platform
Xiao Shi, Aixia Cao
Taking the offshore four-leg Jacket Platform as the research object, regardless of the environmental load such as the wind, the ocean current and the wave, the Jacking platform model for lifting was established considering only the gravity. ANSYS software was used to analyze the force of model. By comparing the results of bending moment, equivalent strain distribution map, Mises equivalent stress map, displacement contour map and overall structure deformation map from the different lifting schemes, the optimal lifting point position is selected. In the scheme 6, the strain and stress of the node are relatively smaller than other nodes, which is convenient for processing and convenient to install the lifting lug structure and is closer to the midpoint of the two bracing. This scheme is the optimal node location choice. The calculation results have some reference value.
Research On The Influence Of Island Mining On Mine Ventilation System
Xiao-ling Liu, Ai-xia Cao, Fu-zhen Qin
Aiming at the ventilation difficulties on isolated island in working face A after mining, increasing air leakage quantity into working face C, increasing remarkably for resistance of the local roadway, determination analysis and simulation for the ventilation basic data has been made, the reliabie wind network calculation model has been established ；the paper simulates and calculates for ventilation of the isolated island working face A through the computer network simulation software.Basing on the result,the ventilation optimization scheme has been made for working face A .The study ,providing technical guidance for ventilation difficulties and prevention of gob fire in isolated island mining,has important practical significance and economic value.
Research On Ship Integrated Navigation Technology Based On Ais Data Processing Technology
Fu-zhen Qin, Ai-xia Cao, Xiao-ling Liu
The AIS system could not only provide static information associated with the data of the ship, but also could provide dynamic information related to the sailing ship, in order to use the advantage of AIS, AIS technology and navigation technology were integrated in this paper, a ship integrated navigation system design based on AIS data processing technology was proposed. The results shown that the data provided by AIS could help the navigation system to route planning effectively, and reduced the occurrence of ship collision accident.
Magneto-mechanical Modeling For Intelligent Boring Bar Driven By Gmm
In order to solve the precision machining of special-shaped parts especially non-cylinder pin hole we often encountered, a precision drive structure for non-cylinder pin hole machining is designed which embedded giant magnetostrictive materials on a boring bar. According to the structure, ignore the influence of temperature, the relationships among electrical, magnetic and mechanical of intelligent boring bar driven by giant magnetostrictive material is comprehensively considered, the output structure model of boring bar is established, and the force of the structure model is analyzed in this paper, from the modeling of electromagnetic link, magnetic and mechanical parts, eventually derived the nonlinear model of intelligent boring bar driven by magnetostrictive material, through the analysis of the cutting force of boring bar, verified the assumption of Fr for constant during the nonlinear model establishing for intelligent boring bar, through doing mechanics experiment about boring bar, we can draw a conclusion that the intelligent boring bar could bore the non-cylinder pin hole precisely in the frequency of 100 hz.Detection the size of piston's non-cylinder pin hole machining under the condition, its error is less than 0.5 µm, the precision of piston pin hole fully meet the demand of mechanical device.
Trusted Data Fusion Algorithm For Internet Of Things Based On Fuzzy Trust
Xiao-qiang Wu, Chun-you Zhang, Li-hua Wang
The sensing layer of Internet of Things (IoT) usually involves a large number of sensor nodes, which is limited by data redundancy and easy attack. Traditional network security has been unable to provide security protection for WSNs．Aiming at this problem, a trusted data fusion algorithm to WSNs which based on the fuzzy trust is proposed. First, on the basis of analyzing the structure of the network model, a fuzzy trust model of the wireless sensor of the Internet of Things is established. Then, in order to improve the credibility and effectiveness of WSNs data fusion, a trusted data fusion algorithm based on fuzzy trust is proposed. The proposed data fusion algorithm can reduce the energy consumption of WSNs, identify trusted nodes, and improve data fusion accuracy. The proposed algorithm provides a new idea for improving the data fusion reliability of WSNs.
Wsn Coverage Optimization Based On Artificial Fish Swarm Algorithm
Changlin He, Yufen Li
A kind of coverage optimization method based on artificial fish swarm algorithm was proposed in order to solve the unreasonableness and low network coverage of sensor node in WSN at the random distribution. Firstly, the current research status of WSN coverage was analyzed, the node coverage and regional coverage in WSN on the basis were analyzed, the corresponding mathematical model was established, the artificial fish swarm algorithm was taken to solve the established mathematical model, and the WSN coverage optimization program based on the artificial fish swarm was obtained. Finally, MATLAB was used for the simulation experiment, and the simulation results showed that the introduction of artificial fish swarm algorithm improved the node coverage in WSN effectively, the coverage area was huger at the same amount of nodes. Moreover, the algorithm can get the optimal solution in the global scope, and reach the better network coverage optimization effect with less sensor nodes, and the number of iterations was decreased significantly.
The Effect Of Yttrium On The Grain Growth Behavior And The Oxidation Resistance Behavior In Fe-cr-al Electrothermal Alloy
Wu Zhaoyu, Xueshan Xiao
This paper mainly studies the effect of yttrium in Fe-Cr-Al alloy on the recrystallization, the grain growth behavior at 1150 °C and the oxidation resistance behavior at 1250 ℃. XRD, OM, SEM and RM were used to study the microstructure evolution. The results show that: yttrium can effectively refine the recrystallized grain size, and the refinement is more obvious with more addition. Adding yttrium can significantly inhibit the grain growth of Fe-Cr-Al alloy at high temperature. The alloy with 0.1 wt. % Y works best, the average grain size is the smallest, and the grains grow the most slowly. The average grain size increases with the increase content of Y. When the content of Y reaches to 0.4 wt. %, the grain size is much larger than that without Y, and the grains grow faster. Adding Y can improve the high temperature oxidation resistance of Fe-Cr-Al alloy, and promotes a continuous dense layer of oxide film on the substrate surface. The isothermal oxidation kinetic curves show a parabolic rule at 1250 °C. The oxidation weight gain reduces significantly with the addition of Y. Adding small amount of Y (0.1 wt. %) can improve the anti-shedding property of the Al2O3 film on the surface of Fe-Cr-Al electric heating alloy, it makes the oxide film more continuous and compact, improving the adhesion of oxide film. But the alloy with an excess of Y (0.4 wt. %) shows the thick and porous oxide film, the high temperature oxidation resistance declines.
Research On The Forecast Of Air Quality In Guangdong Based On Gbrt
Qing Tian, Jun-ling Zhu
With the economic development of Guangdong, people have increasingly higher demands for air quality. Therefore, it has become hot topics to analyze factors affecting air quality and predict air quality. To this end, this paper proposes an integrated learning forecast model based on GBRT to predict air quality with the influencing factors of pollutants, meteorological, region, season and indirect wind direction. Experiments are carried out to verify the effectiveness of the GBRT integrated learning model to air quality forecast, and at the same time, the influence of features proposed in this paper on the air quality forecast is verified.
A Wheat Bran Group Biomass Detection Method Base On Default Threshold Symlet Wavelet Denoising
Feijiang Huang, Zhengda Li, Zhuxian Zhang, Qingxiao Shan, Junjun Zhang
The information like electrical noise, sample background noise and stray light are included normally in the spectrum collected from the near infrared(NIR) analysis mode. Therefore, it is important to remove the noises fast and effectively. As the first step of the spectrum analysis, the stability and accuracy of the modeling are influenced directly by the spectrum denoising. The denoising method based on the wavelet transform was taken to carry out the spectrum denoising for the microbial biomass during the wheat straw fermentation, and the denoising effect was verified in this paper. 85 samples were prepared for the experiment in total, of which 68 samples were taken as calibration set and 17 samples as validation set. The comparison was made with the traditional denoising way by choosing SymN series wavelet (Sym2-Sym6) through Penalty, Brige-Massart, Default threshold method under the different decomposition layers. It was found that the correlation coefficient of the model validation set r was increased from 0.71126 to 0.78508, the Root Mean Square Error Prediction(RMSEP) of the validation set was decreased from 24.3199 to 19.9832 after the comparison of Sym3 4 layers default threshold. Featured bands were selected from 519 wave lengths in the whole spectral range to establish the segment models with the interval size of 10, 20, 30 and 40 respectively. Finally 4450-4925cm-1 was chosen as the feature band; the correlation coefficient of the model validation set r was increased from 0.93418 to 0.96335 and the RMSEP of the validation set was decreased from 9.6334 to 8.2033 after the band selection. The above results indicated that it was feasible to take the rapid test for the biomass of the straw fermentation with the NIR analysis method.
Research On Text Topic Mining Of Social Media Based On Lda
Qing Tian, Jun-ling Zhu
With the rise of social media, more and more people begin to express their views and opinions through social media, emotion analysis and topic model analysis have been developed and applied rapidly in the field of text analysis. By analyzing LDA topic model, this paper proposes to add emotion analysis before topic analysis, then conduct topic analysis according to result classification of emotion analysis, mix with demographic information of user at last, analyze user's character with corresponding topic, in order to realize the improvement of LDA topic model. Finally, the experiment about the topic "Higher Education" taken from Zhihu question-answer sharing platform is conducted, to verify the effectiveness of the method.
An Improved Educational Resource Recommendation System Based On Hybrid Algorithm
The recommendation algorithm is the core module that constitutes the recommendation system. The merits of the recommended algorithm play a crucial role in the overall recommendation system. Content-based and collaborative filtering are the two most commonly used recommendation algorithms in the recommender system. Both algorithms have some disadvantages in their application. Mixing the two recommended algorithms can complement each other and overcome the shortcomings in each other's algorithms. However, in the specific application of the two algorithms, there are cases where the recommendation efficiency is low, and then the hybrid algorithm needs to be improved to improve the recommendation performance of the hybrid algorithm and improve the recommendation efficiency of the hybrid algorithm.
Significance Of Decoy Receptor 3 Mrna In Peripheral Blood Of Systemic Lupus Erythematosus
Kexin Sun, Chen Zhao, Yiju Hou, Suhong Guo, Zhengyi Li
Abstract. To investigate DcR3 Levels of peripheral blood in systemic lupus erythematosus(SLE)，and analyzes the correlation between the DcR3 Levels of Peripheral Blood and the Disease Activity in Systemic lupus erythematosus.The expression levels of DcR3 mRNA in peripheral Blood monocytes of 58 SLE patients and 52 healthy controls were detected by real-time polymerase chain reaction，the levels of DcR3、IL-4 and IFN-γ in serum were detected by ELISA(enzyme-linked immuno sorbent assay)．The expression levels of DcR3 mRNA of active stage in SLE patients were higher than that of remission stage in SLE patients and healthy controls(P<0.05)；The levels of DcR3、IFN-γ and IFN-γ/IL-4 of active stage in SLE patients were higher than that of remission stage in SLE patients and healthy controls(P<0.01)；The correlationships between DcR3 mRNA levels、IFN-γ/IL-4 and active renal score ( SLEDAI)show positive correlation.The expression levels of peripheral blood DcR3 does significant increase in SLE active patients and it is closely related with the activity of the disease which suggesting that DcR3 migh involved in the pathological process.
Prediction Of Wine Alcohol Concentration Based On Sample Selection And Pso-ann
Lingyu Xing, Qiaoyun Wang, Xiangyuyin, Nianzu Zheng
In order to improve the accuracy and robustness of the Raman spectroscopy quantitative analysis model, a new sample selection algorithm named KM was proposed. In the experiment, 40 samples of wine were used as the analysis objects, and the KM algorithms was compared with traditional sample selection algorithms. The experimental results showed that |RMSEP-RMSEC| obtained by the KM algorithm was superior to the other three algorithms, and there were significant differences in RPD, which indicated that KM method had a good prediction accuracy. For the problem that BP neural network was easy to fall into local extremum, the particle swarm optimization algorithm was used to optimize the parameters of neural network (PSO-ANN). The results showed that this algorithm can improve the convergence velocity of training, robustness and the accuracy of classification than genetic algorithm, artificial fish swarm algorithm, and shuffled frog-leaping algorithm.
Detection Of Wine Alcohol Concentration Based On Bp Neural Network And Swarm Intelligence Algorithms
Lingyu Xing, Qiaoyun Wang, Xiangyuyin, Nianzu Zheng
In this paper, a series of tests were conducted to improve the accuracy and robustness of the Raman spectroscopic quantitative analysis model. Taking 40 wine samples as the research object, a variety of pretreatment methods were combined and analyzed to obtain a preprocessing method—MSC, which can effectively remove noise and improve the robustness of modeling. The KM algorithm was used for sample selection. Comparing oPLS and BP neural network regression modeling, experimental results showed that: BP neural network modeling has higher prediction accuracy and robustness compared with PLS method modeling; hybrid algorithm based on particle swarm optimization and artificial fish swarm algorithm is better than other algorithms such as PSO-BP,GA -BP, and AFSA-BP, the optimized neural network has the advantages of fast convergence rate, high prediction accuracy and strong robustness. This research provides a solution to the practical application of neural networks.
Reaction Mechanism And Influence Factors During Preparation Of Ti(c,n) Powders By Carbo-thermal Reduction–nitridation Of Ilmenite
Jun Wang, Yingtao Zhao, Li Cao
Preparation Ti (C1-x,Nx) titanium rich material via carbothermal reduction of ilmenite in nitrogen atmosphere were studied. Phase transition during carbo-thermal reduction-nitridation of ilmenite in nitrogen atmosphere was calculated by thermodynamic equilibrium. Meanwhile it was investigated in this paper that the effects of synthesizing temperature on the C/N ratio by experiment. The results show that, the phase evolution sequences are: FeTiO2→TiO2→Ti3O5→Ti(C1-x,Nx). Ti(C1-x,Nx) begins to generate at 1250℃，The mechanism of Ti(C1-x,Nx) synthesis is that TiN is formed in the system at firstly , then Ti(C1-x,Nx) occurred through diffusion by C atoms. With elevated reaction temperature, the content of carbon in the products was increased.
Configurational Simulations And Theoretical Analysis Of Molecularly Imprinted Polymers For The Recognition Of 2,4,6-trichlorophenol
Haiyan Wu, Wei Zheng, Jianghong Tang, Suci Meng, Fengxian Qiu
A theoretical calculation study was performed to characterize the 2,4,6-trichlorophenol (2,4,6-TCP) imprinted polymer. In the present work, density functional theory (DFT) method was employed to obtain the optimized configuration and reaction energies in the template-functional monomer complexes. 2,4,6-TCP was selected as template, and acrylic acid (AA), methacrylic acid (MAA), trifluoromethylacrylic acid (TFMAA), acrylamide (AAm) and methylacrylamide (MAAm) were chosen as functional monomers. The geometries, binding sites, bond lengths and reaction energies at two template-to-functional monomer molar ratios (1:1 and 1:2) were analyzed in this work. The simulating data were used to evaluate the ability of functional monomers interacted with 2,4,6-TCP to form non-covalently bonded under vacuum. Computational simulation indicated that AA, MAA, AAm and MAAm yield the relative high binding capacity at 1:2 molar ratio. The values were -18.2429, -18.0567, -18.1717, -18.0013 kcal mol-1 for ΔE, and -3.1539 -3.3158, -2.6330, -2.3588 kcal mol-1 for ΔG, respectively. This work may provide useful information for the selection of suitable functional monomer in the fabrication of 2,4,6-TCP molecularly imprinted polymers.
Design And Implementation Of Process Protection Card Based On Usb
Renjie Wu, Xiaoling Guo, Ying Liang, Mengchen Zhang
In this article, a process protection card based on USB is designed and implemented. The whole process of hardware structure design, component selection, schematic diagram, PCB diagram making and software realization is given in detail. The problems and solutions in the design process are put forward and solved one by one. Compared with traditional process protection technology, new technology has more advantages. New technology provides a new protection plan for process protection.
Speech Recognition Of Minority Language In Low Resource Based On Deep Transfer Learning
Chunyu Wu, Jie Sun
Abstract. In this paper, we propose cross-lingual convolutional neural network acoustic modeling for low-resource minority language speech recognition. First, the database from the same family of language is used to pre-train CNN. Then, the mapping of phones between the rich resource and the limited resource language is established by using data-driven method and is used to label target language data. Finally，CNN is fine-tuned by using limited target language data. we show that framework suggested ,provides a relative improvement of accuracy of 4.81% over the baseline system using DNN.
Prediction Of Deep Hole Cutting Shape Based On Support Vector Regression
Yan Li, Xiao-qiang Wu, Chun-you Zhang
Cutting shape is an important index for monitoring quality and optimizing process parameter of deep hole drilling. For shortcomings of the existing BP neural network in predicting the deep hole cutting shape, a new prediction model based on support vector regression was proposed. First, the main factors affecting the prediction of deep hole cutting shape were analysed, and then the prediction model of deep hole cutting shape based on support vector regression was established. The results of simulation show that the prediction model has strong generalization ability and high prediction accuracy.
Research On The Evaluation Of University Library Service Quality Based On User Perception
Wei Yan, Xiao-qiang Wu, Chun-you Zhang, Hong-na Zhang
The user satisfaction is the starting point of the library service work. In order to better satisfy the user's expectation of the service quality and service level of the library, and further improve the service quality of the library, many university libraries have a deep understanding of the user's opinion and measure the user satisfaction objectively and systematically as the optimization of the library. The criteria and action basis of service process, service quality improvement and service level improvement, and corresponding measures are taken according to the measurement results. Through the analysis of the existing evaluation models, Delphi method designed the evaluation system based on basic conditions, readers' satisfaction and librarians' service quality, and the weight value of each index was determined by the analytic hierarchy process. An empirical study was carried out in the library of Jilin University and Shandong University by the construction of the index system, and the service quality of the two libraries was compared horizontally, and the correctness of the evaluation system was verified.
Design And Implementation Of Afdx Terminal Protocol Core
Xingcheng Ran, Guangwei Li
With the emergence of a variety of transmission tasks in the avionics system, the existing data bus can not meet its requirements. As an ideal protocol for the new generation of avionics, Avionics Full Duplex Switched Ethernet(AFDX) has great advantages in reliability and safety of message transmission. In order to realize the engineering application of the protocol in the avionics system and shorten the development cycle of the terminal interface, the AFDX terminal protocol core is designed and implemented based on FPGA platform, the logic planning of sending、receiving channels and MAC module is carried out in detail. The test results under Quartus II software show that the chip protocol function is in good condition and meet the design requirements.
On The Problem-solving Activity Model That Facilitates Teachers’ Tpack Construction In Online Research And Studies
In the information era, teachers’ Technological Pedagogical and Content Knowledge (TPACK) is teachers’ important knowledge foundation and guarantee, and online research and studies is a new pattern for teachers to develop education. In consideration of this, the mode of problem-solving is proposed in the paper to facilitate teachers’ TPACK construction in online research and studies, and a problem-solving activity model is also established. Afterwards, the method of quasi-experiment is adopted to compare and verify the effect of the implementation of the aforesaid model. The main content of such verification is that in information-oriented instructional design and classroom record, the two-tailed probability p of information-oriented instructional design in the experimental group and control group is 0, which is significantly correlated, and the mean value of the experimental group is higher than the control group 2.5486. The mean value of classroom record in the experimental group is higher than the control group 11.2219. In conclusion, this model can satisfyingly facilitate teachers’ TPACK construction.
Blind Signal Separation Of The Unknown Sources Number Based Under The Constraint Of Space Direction
Jinde Huang, Meimei Huang, Zhiheng Lin
Abstract: The blind signal separation based on eigenvalue decomposition, and under the number of unknown sources, when the dimensionality of signal space is determined to be wrong, it will result in larger separation error. This paper uses the directional information of the array structure to build the blind signal separation algorithm based on the "Space kurtosis" spectrum, which can avoid the eigenvalue decomposition. The algorithm takes full use of the statistical independence of source signals and spatial distribution independence that can better separate the source signal and suppression noise. The simulation experiment results show the algorithm under the unknown source number that proposed in this paper features high accuracy and high robustness.
Personalized Cross Language Query Expansion Based On User Interest Model
Huihong Lan, Haiping Huang
For the problems existing in the traditional cross-language query expansion method, a personalized cross-language query expansion method based on user interest model is proposed. The method establishes user interest model with the use of the user’s historical browsing log information. On the foundation of the model, the initial retrieval results are analyzed. Taking the documents which are more relevant to the user’s interest in the initial retrieval result documents as the basis for query expansion, the query keywords acquired after expansion will better express user’s personalized demands. As shown by the experiment results on real users’ search log data, the algorithm in the present paper can better satisfy users’ personalized demands and can effectively improve as well as enhance the accuracy of cross-language information retrieval. Compared with the cross-language information retrieval which has not gone through personalized query expansion and the existing algorithm, the MAP, P@5, P@10 values of the experiment results have all been increased, with the maximal increase extent up to 26.51%.
Modeling Seasonal Tuberculosis In Guangxi, China
Zhonghua Ling, Xifeng Fan, Lei Zhang
Tuberculosis is one of the most common diseases in Guangxi, China, the monthly tuberculosis cases data reported by the Guangxi Health and Family Planning Commission exhibit a seasonal pattern. Based on this observation, we develop a mathematical model with periodic transmission rate and reactivation rate to investigate the seasonal TB epidemics in Guangxi. We define the basic reproduction number, prove that the unique disease-free equilibrium is globally asymptotically stable if the basic reproduction number < 1, simulate the tuberculosis cases data, and carry out some sensitivity analysis on some parameters. Our studies show that tuberculosis in Guangxi can be controlled by improving the treatment rates of infectious individual and increasing the immunization rate of the newborn.
Research On Energy-saving Optimization Of Improved Dv-hop Localization Algorithm In Wireless Sensor Networks
Huijie Qu, Liu Yang, Zhi Zhao
Abstract: Based on the existing wireless sensor network DV-Hop algorithm and its improvement ideas, inheriting the advantages of various thinking algorithms, and combining with the low energy consumption requirements of wireless sensor networks, this paper proposes an energy-saving and high-precision DV-Hop positioning method, and the corresponding simulation experiment has be carried out. The experimental results show that under the experimental scenario, when the proportion of anchor nodes is 10%, the number of flooding packages is reduced by more than 80%. If the connectivity is above 15, the saving rate is basically maintained at more than 90%. In the case of different anchor node ratios and network connectivity at 10, the number of flooding packets can still be reduced by more than 10%. Therefore, the improved DV-Hop algorithm has better energy efficiency than the classical DV-Hop algorithm, achieving the purpose of energy saving.
Analysis On Online Education Plate Investment Based On Curve Similarity
Fang Yu, Dong Xie, Li-zhu Zhang, Xiaoming Huang
Abstract. By taking the winning rate, annual rate of return and net profit margin as management goals, this paper establishes an investment mathematic model by making use of curve similarity. Via empirical analysis, the share price fluctuation of 57 listed companies of the online education plate has been compared and elaborated, results of which indicate that the winning rate, annual rate of return and net profit margin of anti-directional movement index are comprehensively superior to that of directional movement index. The winning rate, annual rate of return and net profit margin of BIAS are 1.77 times, 36.73 times and 36.30 times that of MACD. Regarding the RSI system, its winning rate is the highest, being 93.75%. Its annual rate of return and net profit margin are 5.78 and 10.59 respectively, ranking in the moderate position of all systems. The annual rate of return and net profit margin of the improved RSI system are 1.51 times that of the original system with its winning rate 0.76 times that of the original system. According to data results, the improved RSI system is steady in terms of the three management goals and it is quite suitable for investment on the online education plate.
Map Log Sheet Conflict Evading Algorithm Based On Multi-core Pc
Ting Zhang, Feng Su, Xing Li
The traditional transactional memory system can only deal with conflicts, but it is without the prevention of conflicts in advance. Thus, a conflict evading algorithm based on MAP log sheet is proposed. Before the transaction starts, the possibility of conflict occurrence can be predicted in accordance with the historic conflict situations, and the transaction can be regulated according to the prediction result, so as to reduce its failure rate. The evading for the read-write conflict between the transaction and thread is conducted along with the provision of parallel algorithm and application examples. Experimental results show that the algorithm can well reflect the actual operating procedure of the conflict evading of transaction memory, and it is considered effective in realizing the parallel control and operation of the transactional memory system.
Back Propagation Neural Network Rainfall Prediction Model Based On Particle Swarm Optimization
Zhi Zhao, Huan Deng, Jinde Huang
Abstract: It is a feasible method to use neural network construction to predict rainfall in the region. However, the error of this method is bigger, and its error is from the neural network structure itself. In view of the problem that the rainfall prediction precision based on BP neural network construction is low, this thesis proposes to optimize BP neural network rainfall prediction model with particle swarm optimization (PSO) algorithm, and then use the same training samples and testing samples to conduct a simulation experiment to the forecast model before and after optimization. The results show that the experimental testing result of the forecast model after optimization is more in line with the actual value.
Study On Control Method Of Acceleration Slip Regulation Of Electric Vehicle Based On Fuzzy Logic Control Principle
Lin Zheng, Yuegang Luo, Rubo Zhang, Changjian Feng, Zhanqun Shi
In response to the problem of driving wheels slipping when driving on a low-adherent road surface of the EV (Electric Vehicle), some researches are carried out focusing on the driving ASR (Acceleration Slip Regulation) control of independently driven EVs. In this paper, an adaptive fuzzy logic control method based on fuzzy road recognition was proposed in order to improve the EV's stability under extreme conditions. Based on the advantage of measurable data of the hub motor torque and speed, the Burckhardt method is used for calculation of friction forces. Then, the model-based approach of the road recognition algorithm using fuzzy logic control is designed. According to the motion of the vehicle, the road surface recognition algorithm identifies the current road surface and the optimal slip rate. The adaptive fuzzy controller is used to control the drive wheel slip rate in real time around the optimal slip rate. The simulation results show that the fuzzy road recognition algorithm could identify the friction co-efficient and the optimal slip rate superiorly. The ASR control method based on road surface recognition has a good control ability, which could improve the vehicle’s control stability and manipulability significantly.
Research On River-ocean combined transportation Handling Process Of Major And Key Equipments
Qing Li, Rui Yang
Based on developing the research on river-ocean combined transportation handling process of weighty equipment in inland rivers and the transhipment key technology of river-ocean combined transportation, the type of understudied Inland Shallow and wide ship is studied. Combined with the real ship design parameters and ship model test data, the ship dynamic fuel consumption model is established, the combine transportation organization key technology of weighty equipment river-ocean combined transportation in Inland River. This paper puts forward schemes and measures of weighty equipment transportation suitable for inland rivers with the emphasis on handling and transporting equipment of weighty equipment.
Analysis Of Approximate Dispensable Set In Fuzzy Soft Set
Zhi Kong, Shicheng Li, Lifu Wang, Lianjie Ma, Fuqiang Lu, Yonghui Han, Liqian Wang
Abstract: Fuzzy soft set is a good mathematical tool to deal with uncertain decision making problems. There is much dispensable information in data. Reduction is used to deleting redundant information. Approximate normal parameter reduction of fuzzy soft set is a good method to solve the problems of suboptimal choice and added parameters. In this paper, the approximate dispensable set in fuzzy soft set is studied. Two problems are considered: one is after deleting approximate dispensable set in fuzzy soft set, the reason of the decision sequence is almost unchanged; the other is about maximal deviation . Some examples are shown to illustrate the two problems.
Research On Human Resource Allocation Model In Colleges And Universities Based On Multi Objective Optimization
Whether an organization's structure is reasonable and whether its activity is effective is not the absolute number of excellent talents, but whether the internal human resource allocation is reasonable, whether the job requirements and personnel capabilities match. The scientific and reasonable allocation of human resources can create or maintain the competitive advantage of the organization. In this paper, the multi-objective programming model is used to establish an optimal allocation model of human resources for various types of organizations from a general point of view. This paper proposes a hybrid genetic algorithm based on multi objective human resource allocation method, which uses multi stage decision model to deal with this problem, the task as a decision maker and a series of external interactions, each stage there are some of the available decision, and easy to calculate their immediate effect. In order to effectively acquire a set of Pareto optimal solutions, a multi-objective hybrid genetic algorithm for solving combinatorial optimization problems is proposed, that is, using multi-objective hybrid genetic algorithm to search for feasible solutions in all stages.
Optimized Configuration Of Sustainable Supply Chain Model For Cross-border E-commerce Based On Big Data
A good sustainable supply chain performance evaluation model helps to better understand and manage enterprises. Through the reasonable research and analysis of the original performance evaluation system of cross-border companies, we choose the appropriate performance indicators. In this paper, from the perspective of supply chain management, the configuration model of process cluster supply chain and assembled cluster supply chain is proposed respectively. Secondly, we analyze the profit and the optimal supply chain configuration structure of the cluster system and its cooperation partners under the change of order quantity, and also provide an analytical method for the optimal cooperation mode of cluster supply chain with different orders for each chain. Then, the data are substituted into the constructed structural equation model, and the weight of each index is obtained. Finally, a suitable cross border e-commerce performance evaluation model is obtained. Finally, through the ant colony algorithm based on large data, the optimized configuration of the sustainable supply chain model of cross-border e-commerce is optimized.
Evaluation Of Higher Vocational Students' Learning Effect Based On Evaluation Index System Construction And Empirical Analysis
As an effective means of teaching management in colleges and universities, students’ evaluation of teaching has established an effective communication platform for schools, teachers, and students to teach, learn, and manage. In a certain sense, the success or failure of students' evaluation of teaching can directly affect the success or failure of teaching management. The core of students' evaluation of teaching is the truth, objectivity and comprehensiveness of data and content. This puts forward high standards for the construction of student evaluation index system. On the one hand, we must establish the target system of index system construction on the basis of the index system, that is, the use of development evaluation to improve the ability of the evaluators to achieve the purpose of teaching; The principle of integrity and conciseness should always be followed in the process of building the index system. Based on the features of the higher vocational courses and the students' realities, this article has established a set of indicators system suitable for the detection and evaluation of students' learning quality in higher vocational colleges in China, and constructed an evaluation model of student learning quality using the analytic hierarchy process.
A Self-learning English Keyword Extraction Algorithm Applied To The Internet
Keywords usually consist of several words or phrases and represent a summary of the article. Accurate number of keywords can effectively represent the basic content of the article. Users can quickly and accurately grasp the content of articles by using these keywords. In the era of big data, the user's energy is limited relative to the available data. Users can discover the information which they are interested in through keywords, and then further in-depth understanding them without having to waste time on irrelevant content and data. As an important credential for information retrieval, the keyword is an important reference indicator when users hope to extract content of interest from massive information through certain technical means. The paper proposes a self-learning English keyword extraction algorithm, which can assist in the realization of intelligent information acquisition on the Internet, so as to effectively solve the Internet information explosion problem. This algorithm has been used in the development of the Internet information intelligence tool developed by the research group. Experiments show that the algorithm has a high recall rate and precision rate, and has a broad application prospect in the Internet information intelligence acquisition.
Research On Consumer Clustering Based On Cross-border E-commerce And Big Data
Consumers' emotional needs are the result of a series of psychological activities, reflecting their emotional expectations for product modelling, affecting their image perception of product modelling, and further affecting consumers' purchase behaviour. However, consumers emotional needs have the characteristics of ambiguity and complexity. Therefore, how to tap consumer's perceptual requirements and reduce them through analysis and clustering can provide designers with more accuracy in product design process. The design basis is an important issue in the field of industrial design. This article selects the search data for the wedding dress industry of the AliExpress cross-border e-commerce platform, associating the number of stores in the platform, consumer search data, and data generated by purchases with consumer behaviour. .Through the correlation analysis, regression analysis and cluster analysis of the data, the relationship between consumer search behaviours, comparative behaviours, and purchasing behaviours is studied to analyse the categories of consumers and adopt certain strategies for various types of consumers.
Based On Anp In Flipped Classroom Mode, The Teaching Research Of Music Analysis And Writing Is Realized
Min Liu,dunguang Xu
Flip is a new type of classroom teaching organization form. Through the research on multi part of music analysis and writing course teaching practice, it is found that the flip classroom can improve the students' learning enthusiasm. And it can promote the student to the curriculum awareness through practical teaching experience. As a result, it can put forward the multi part turn classroom in university music analysis and application of the basic teaching thinking in writing teaching, and put forward the operation case based on hybrid flip classroom teaching mode combining teaching theory. It is designed a new type of flip classroom based hybrid teaching model. And the teaching of hybrid (B-Learning) is a traditional teaching (Face to Face) and network teaching (E - Learning) complementary advantages of a teaching mode. It is an important research direction of present college teaching reform.
The Application Of Big Data In Improving College Students' Outdoor Training Methods
With the advent of the big data era, exploring the world operation rules through large-scale data research has become one of the characteristics of contemporary scientific research. For the field of scientific research in outdoor sports training for college students, large data is not only a useful practical tool, but more important is a way of thinking. The big data thinking opens up a new methodology for the scientific complexity research of college sports training, which leads to the new research paradigm of modern sports training. In this paper, we mainly discuss the value of data, bring unstructured data into the research system, establish a multi-dimensional three-dimensional model, and explore the law of cause and effect from the correlation between data. The experiment shows that the NPSVM- LD algorithm based on conjugate gradient method can quickly and accurately train the data set within 10000, and achieves good results.
Research On Logistics Cost Control Strategy Of Fresh Agricultural Products Based On Supply Chain
In recent years, the quality and safety issues of fresh agricultural products in China have been severe. An efficient supply chain model for fresh agricultural products has constructed to reduce the loss of logistics and costs of fresh produce, which helps to improve food safety and the logistics efficiency of fresh produce. It is an urgent need to solve the problem. Based on the concept of supply chain business flow and knowledge flow based on the flow integration model of supply chain knowledge, this paper studies the multi-agent knowledge sharing system based on supply chain. The article mainly uses the theory research method to organize the knowledge involved in the supply chain knowledge and flow coordination. On this basis, the status and existing problems have carefully analyzed to improve the level of development of the logistics supply chain of fresh produce, and to adopt a safe and efficient logistics supply chain model for fresh agricultural products. The research results of this paper will provide a practical solution for the knowledge management of supply chain enterprise; provide a reference model for the construction of supply chain management. This paper can improve the efficiency of supply chain flow, and benefit the supply chain enterprises.
Teaching Reform Design And Improvement Method Of Physical Education Major In University Based On Flipping Classroom
Flipping classroom is a new type of teaching mode that has been spawned with the development of modern information dissemination, especially the gradual development of internet technology. It has reformed the traditional teaching model, changed the role of teachers and students, enabled students to truly participate in the entire learning process, and effectively improved the efficiency of classroom teaching. This paper studies the application of flipping classroom teaching model in the teaching of physical education in colleges and universities. The results show that the flipping classroom teaching mode can be carried out before class, during class and after class, which effectively runs through the entire learning process and is not restricted by the region. Greatly improved the efficiency of classroom teaching and students' enthusiasm for learning, and cultivated students' ability to think independently.
Research On The Theory Construction And Effect Of Wisdom Preschool Education System Under Background Of Big Data
The quality of preschool education has an important influence on the development of children's entire life. All countries have successively formulated standards and indicators for the evaluation of education quality to supervise and monitor the quality of preschool education, regulate various behaviors in the education process, which guide preschool education. Under the background of big data, with the rapid development of the Internet of Things, cloud computing, mobile Internet, and artificial intelligence technologies, smart education has ushered in a smart and intelligent cloud era. This article reviews the concepts and research status of big data and wisdom education, and presents the composition and system architecture of a smart education cloud platform. It uses Hadoop technology to analyze and process big data, adopts data mining algorithms and combines cloud computing. Research on the acquisition, presentation, modeling and integration of smart resources, establish a data analysis and processing model diagram, integrate the data intelligence into the wisdom education cloud platform, and test the application and performance of the platform.
The Study Of Radiotherapy Image Registration Based On The Principle Of Space Transformation
Zhiyu Ling, Yingyi Xia, Wei Liu
With the development of biomedical engineering and computer technology, medical imaging provides a variety of modality medical images for clinical diagnosis. However, different modes of medical imaging have different imaging principles, resolutions, and imaging parameters. Therefore, image registration must be performed before image fusion. In this paper, the radiation image registration method based on spatial transformation is studied, and obtained quiet good experimental results. It is proofed that it’s a method with promotion potential.
Pattern Recognition Based Image Processing And Its Application In Moving Object Recognition
Xinjun An, Na Su, Changsheng Zhu
With the development of computer and artificial intelligence technology, pattern recognition has become more and more widely used in image processing. This paper reviews the feature extraction, main recognition methods of pattern recognition in image processing, statistical decision-making method, syntax recognition, fuzzy identification, and neural network. Finally, ARTI neural network algorithm is used to solve the problems in actual image processing and moving target recognition.
Analysis And Risk Management Of Supply Chain Financing Based On Grey Evaluation
With the continuous improvement of China’s economic development level, China’s corporate development has achieved very significant achievements, and competition among enterprises is becoming increasingly motivating. With the intensification of industrial competition, the competition evolved from the supply chain has become a trend and model. As a result, supply chain finance has become a new financial model. How to evaluate the company's supply chain financing capacity has become a very critical issue. As a brand-new financial model, supply chain finance can use the supply chain management chain to expand financial service methods and approaches. However, how to achieve effective management of the corresponding credit risk under the supply chain finance model to strengthen the resilience of supply chain finance is waiting to be solved. This paper uses a grey evaluation method to make a more realistic assessment of the company's supply chain financing capabilities.
Research On The Application Of .net-based Auxiliary System In College Music Teaching
Using ASP.NET, ADO.NET and other technologies combined with a 3-tier architecture, a .NET-based network-assisted education system was implemented. The system's architecture model and database model are planned, and the specific implementation process is described. Several strategies for enhancing system security and improving system performance are proposed and the main features of the system are analyzed. The network-assisted teaching system built on the .NET architecture greatly improves the development efficiency of the system and enhances the system's scalability and maintainability.
Application Of "internet Plus" In Vocal Music Teaching
Vocal music teaching can help students establish vocal music concepts and cultivate the correct singing habits, so that students can have the ability to sing songs. However, vocal music teaching lacks enough intuitionisticness, which leads to the disadvantages of traditional vocal music teaching. The extensive application of information technology can well solve the above problems. As a modern teaching method, the Internet is characterized by visualization and high information. Multimedia technology has abandoned the traditional vocal music teaching mode. Both of them can fully mobilize the enthusiasm of students' learning and effectively improve the quality of vocal music teaching. This paper explains the importance of Internet and network multimedia in vocal music teaching and describes specific application measures.
Research On Optimized Application Of Computer Assisted Instruction In Vocal Music Teaching
With the rapid development of modern educational technology, a piano, a book, and a mouth of traditional music teaching models are far from being able to adapt. Multimedia computers expand the amount of knowledge transferred, increase teaching capacity and density, use sound, light and shape. Various means, such as color, reproduce the knowledge accumulated by human beings, and at the same time, it is highly variable and controllable. It broadens students' horizons of music knowledge, and adds musical sensation, aesthetic sense, sense of space, and dynamic sense to music teaching. The music education of the teachers in the middle school is closely related to life, effectively cultivating the overall musical quality of the teachers and students. The skillful and reasonable application of multimedia computer-assisted teaching in music lessons can arouse students' interest in learning, improve their music appreciation and musical skills, and contribute to the breakthrough of teaching difficulties. This paper proposes a design method of multimedia vocal music teaching and develops an interactive multimedia vocal music teaching system. This makes vocal music teaching achieve more autonomous choices and human-computer interaction functions, laying the foundation for the vocal music teaching autonomy. At the same time, it also provides a new way for the realization of multimedia vocal music teaching.
An Analysis Of The Development And Aesthetic Value Of Piano Performance Based On Musical Auditory
In music performances, piano performance is one of its important forms. Musical auditory is very important for the development of piano art. It is a personal’s psychological process. It is the cultivation of human aesthetic ability and mood. In the form of art, piano also gradually began to accept and embody our aesthetic values and aesthetic interests, playing an increasingly important role in social harmony. This paper deeply analyses the development path of piano aesthetic value based on the music auditory and also analysed the development process of performance skills.
Research On Location Privacy Protection Based On Distributed Gradient Algorithm In Internet Of Things
Xingchao Bian,binli Zhang
The issue of personal privacy has long existed, and personal privacy issues have become more prominent in the era of big data. With the constant improvement of our country’s social legal system, the issue of personal privacy has attracted widespread attention from all occupations. This paper describes the research status and development trend of multi-sensor distributed signal detection, and discusses the network structure and fusion criteria of multi-sensor detection systems, as well as channel perception problems, transmission power of optimization problems, transmission strategy and clustering in distributed detection systems. The questions have summarized. This paper researches on IoT Location Privacy Protection Based on Distributed Gradient Algorithm; it proposes a model and method for protecting the privacy of location information in location-based services. By introducing the concept of privacy correlates into the access control matrix, a three-dimensional of control matrix model is proposed. The three-dimensional access control matrix can better describe and satisfy the user's need for privacy protection of location information. In the three-dimensional access control matrix, through the establishment of an appropriate access control strategy, all privacy stakeholders related to location information can jointly control who, when and where to access the location information that needs protection.
An Athlete's Motion Capture And Auxiliary Physical Performance Monitoring System Based On Optical Flow Method
In order to solve the problem that the current motion capture algorithm for athletes is complex in the background model and the target features are not obvious, leading to the problem of insufficient capture capability of the algorithm, this article proposes the basic optical flow method for athletes' motion capture from the perspective of optical flow analysis and auxiliary physical monitoring systems,this system has effectively achieved the optimal design of the athlete's motion capture and auxiliary physical monitoring, and improved the system's compatibility, reliability and scalability,and it is obviously practical compared to previous studies.
Research On Multidimensional Ideological And Political Education Of College Students Based On Network Platform Data Analysis
Lei Li, Guofeng Xu
With the rapid development of the Internet, an increasing range of Internet life is slowly forming. College students' activities on the Internet are no longer satisfied with the purpose of obtaining information. The Internet is becoming a platform for college students to learn, play, and socialize, and is becoming an integral part of life. Using the Internet platform to grasp the dynamics of college students' thinking and help educators better perform ideological and political education is very important for the education of college students. This article uses the social platform as an entry point to analyse the behaviour of college students' microblogging, and use statistics only to establish a Markov-based user influence evaluation model, which further validates the analysis conclusions.
Data Association Coverage Algorithm Based On Energy Balance And Controlled Parameters In Wireless Sensor Networks
Qing Lv, Yachuan Liu, Hua Zhao
Based on a position-independent and computationally simple node scheduling algorithm, a scheduling algorithm based on energy balance is proposed. The analysis and simulation results show that the algorithm can extend the life of the entire network while ensuring energy balance. Data aggregation is a relatively time-consuming operation in sensor networks, especially in high-density networks. Therefore, minimizing the problem of data aggregation delay has become a hot topic of research. The algorithm adopts a clustering idea of low power in the cluster and high power between clusters, combined with channel allocation to reduce data aggregation delay, and data aggregation between clusters can be performed without collisions. The number of channels used in different network topologies tends to be constant. In the simulation experiment, the algorithm MPMC is compared with the best single-channel and multi-channel data aggregation scheduling algorithm, and the average delay of the MPMC is verified to be the smallest.
Three-dimensional Digital Image Modeling And Application In Imaging Diagnosis And Interventional Treatment
Bingrong Li, Jianfei Tu, Yangrui Xiao, Jian Lou, Jiansong Ji, Weiwen Liu
In recent years, three-dimensional digital modeling has become more and more widely used in imaging diagnosis and interventional treatment.This article first systematically discusses the basic processes and methods for the establishment of human three-dimensional models, including the core steps of feature acquisition and processing, image matching, double image analysis, photogrammetry, and calibration.Then Mimics software was used to establish a three-dimensional model of the human body, providing a research model for imaging diagnosis and interventional treatment.This model can also be applied to computer numerical simulations and finite element analysis of human body structures, and individualized preoperative planning and surgical simulations can be developed.
Simulation Of Action Amplitude Tracking Method In Sports Based On Multi-dimensional Cobweb Model
Huadi Wang, Xinhao Ji
In order to accurately identify and correct the incorrect posture of athletes and effectively improve the quality of athletes' training on weekdays, it is necessary to conduct in-depth research on the movement of athletes in sports. Accurate motion image amplitude detection is the basis for improving the remote recognition and tracking of human motion target images. However, when using current methods to track motion motion amplitude, it is not possible to calculate the marker points in the motion image of adjacent monocular sequences. The magnitude of the tracking error is large. For this reason, a three-dimensional visual motion amplitude tracking method based on a multi-dimensional web model is proposed. The method first calibrates the camera imaging plane according to the pinhole camera model, and the positioning marker points appear in the marker points of the amplitude of the adjacent monocular sequence. Based on this, the rotation angle method is used to predict the position of the action amplitude in the image. The time series model of the action amplitude is obtained, and the probability that the three-dimensional visual motion amplitude is outside the optimization region is given. Based on this, the three-dimensional visual motion amplitude tracking in sports is completed. Experimental simulations show that the proposed method has high tracking accuracy and lays a solid foundation for improving the training quality of athletes.
Analysis Of The Surface Electromyography Characteristics Of Trampoline Athletes At The Stage Of Network Takeoff In Meltingaction Classification Algorithm
Feng Benyu, Xing Kailong, Liu Pan
Abstract:The network takeoff is the basic technology of trampoline, and it is the prerequisite and condition for the athletes to master the difficult technology.If the athlete grasps the force mode of the net take-off and the time to reach the highest point, it can easily complete the high quality air tossing and turning movement.In order to improve the technical level of athletes' network landing take-off, this paper analyzes the surface electromyography characteristics of the trampoline athletes in the take-off stage of our country by using the fusion action classification method, introduces the related concepts of EMG and EMG, and expounds the application of surface EMG in sports scientific research. After collecting experimental data, this paper analyzes the order of surface electromyography, calculates the change of root mean square amplitude (RMS) and working percentage of surface EMG in the network landing take-off stage, and puts forward suggestions for trampoline training, which is beneficial to further improve the technical level of trampoline training in China.
Research On Enterprise Talent Management And Evaluation Algorithm Based On Deep Convolutional Neural Network
In view ofthe imperfect construction of the enterprise talent management and evaluation system at the present stage, it is impossible to know the resource integration of enterprises on talent and carry out more efficient evaluation work,and it cannot provide a scientific evaluation and guidance plan for the innovation and management of enterprise talents, so this paper proposes an enterprise talent management and evaluation algorithm based on deep convolutional neural network. The algorithm first gives comprehensive evaluation indexes through experts, then reduces the dimensions by clustering reduction algorithms, and finally inputs the comprehensive evaluation indexes of reduced-dimension into the deep convolutional neural network. The actual evaluation results are given by a trained deep convolutional neural network, and then the comprehensive evaluation indexes of enterprise talents are given according to the actual evaluation results. The simulation experiment is carried out in the enterprise of a new and high-tech zones, and the experimental results show that the algorithm can provide scientific and innovative management and evaluation results for enterprise talents through clustering reduction, deep convolutional neural network and comprehensive evaluation indexes. Compared with the traditional neural network algorithm, it has a great improvement in efficiency and accuracy.
Research On Hydration Process Of Concrete Based On Electrochemical Impedance Spectroscopy
Jiang Fengjiao, Gong Jinxin, Zhu Jichao
The cement hydration of concrete mixed with fly ash or slag has been studied by using the electrochemical impedance spectroscopy method. The influence of mineral admixture on the electrochemical impedance parameters in the concrete cement hydration process is analyzed and the changes of the concrete structure are discussed from the characteristics of electrochemical impedance spectroscopy at different stages. The results show that the variation trend of concrete electrochemical impedance spectroscopy is identical for different dosage of fly ash or slag.During the early age of hydration, the impedance parameters , and reduced and the total porosity of the concrete increased with the raise of mineral admixtures content incorporated in concrete and the structure of concrete become loose. In the later stage of hydration, the impedance parameters , and gradually increase due to the secondary hydration effects and the effect is more significant with the increase of mineral admixtures content, that is, the more dosage of mineral admixture the concrete has, the more significant the effect is.
Integrated Optimization Of Port Yard Layout And Scheduling To Reduce Carbon Emissions Based On A Multi-objective Fruit Fly Optimization Algorithm
Rongtao Ding, Wei Ren, Youming Zhu
In this paper, the problem of integration of space distribution and handling equipment scheduling in container yard with the minimum carbon emission and the shortest completion time is studied. In order to decide the location and allocation of containers at the same time, a fruit fly optimization algorithm is introduced to solve this problem. Fruit fly optimization algorithm is simple, small in computation and high in accuracy, but unstable. The algorithm has been improved in the following aspects: In olfactory search phase, greedy algorithm and group insertion method are applied to generate neighborhood solutions; In the visual search stage, the design part crossover strategy chooses the best neighborhood solution to update individuals, which guides the poor individuals to move to the population center location. Finally, an example is given to illustrate the effectiveness of the multi-objective fruit fly optimization algorithm to solve the integrated optimization problem, and the validity of the model is verified.
Research On Smart Grid Fault Location System Based On Intelligent Algorithm
Hongna Li, Hui Zhao1
The present article mainly solved the existing problems of low accuracy and reliability of distribution network fault location system, and studied the distribution network fault location system based on FTU technology and SCADA, using the adaptive genetic algorithm to locate. This system mainly consists of two parts, namely FTU and master station SCADA. FTU is responsible for real-time communication with the main station and management of peripheral matters; whereas, master station SCADA is responsible for processing data and providing the data to the detection software. Positioning software employs an adaptive genetic algorithm, and quickly finds out the fault section according to the fault current information passed from the FTU . According to the simulation results, we can draw a conclusion that the method in this article has a strong fault tolerance and practicality.
Simulation And Analysis Of Node Deployment In Wireless Sensor Networks In warehouse Environment Monitoring Systems
Jia Mao1, Ruiping Liu1, Xiuzhi Zhang
The deployment of nodes is directly related to the application of sensor networks in the storage environment. This article discusses the application advantages of wireless sensor networks in storage environment monitoring, and it focuses on the deployment of sensor nodes in a warehouse environment. Because the sensor's perception model affects the effectiveness of the node deployment scheme, this paper proposes a collaborative awareness model for the 0-1 perception model and exponential model that were commonly used in researching node deployment. It transforms the sensor node deployment into a node deployment problem in 3D space, and draws on the idea of Voronoi's division, uses the polyhedron incremental coverage algorithm. Through simulation analysis, under the guarantee of coverage and connectivity, the optimal deployment scheme for deploying wireless sensor nodes in a warehouse environment with the least number of nodes is obtained.
The Correlation Empirical Analysis Of Resource Industrial Structure Adjustment And Industrial Engineering Under The Economic Transformation
National economy is closely related to the engineering structure, and the adjustment of resource industrial structure influences and changes the development of engineering structure. Taking Wuhan as an example, we observe the development status of resource industrial structure and the engineering industry with qualitative analysis. Combined with gray relational theory, we can describe and analyze the detailed relationship between resource industrial structure and engineering structure quantitatively. And the correlation degree would allow us to represent the competing models among the three main engineering modes, thus providing a theoretical basis for a reasonable forecast of engineering development.
An Efficient And Highly Secured Key Management Signcryption Scheme For Dynamic Hierarchical Access Control
A.Sivasundari, Dr. M. Ramakrishnan
Access control mechanism is a core of crypto scheme that data is encrypted using secret key consequently that only the consumers are alert of the correct key to decrypt the information to achieve the further encryption procedure. Lot of access control systems utilized to uphold the security but diffident in contradiction of great level attacks i.e., man in middle attacks. Lin and Hsu projected key management system to resolve the cooperating attacks on the basis of polynomial interruption and ECC (elliptic curve cryptography). The system is prohibited from cooperating attacks, but it hurts from huge computation cost. The computation cost of Lin and Hsu system is augmented because of the multifaceted ECC point growth in ECC key generation phase. In this article we convey a novel system that associated with Lin and Hsu system suggestively decreases calculation cost of ECC point multiplication. A consumer hierarchy, our system is protected against all conceivable attacks embraces man in middle attacks and does not need polynomial interruption methods, for creating the public polynomials for safety classes in the hierarchy, and is on the basis of exclusively on an improved symmetric key cryptosystem i.e., compressed ECC together with one method hash function (SHA-1). We also add in security system by merge the ECC with improved signcryption cryptosystem.
A Dynamic And Hybridized Classifier For Prognostic Decision Making In Breast Cancers
Breast cancer is one of the extreme common kinds of cancer, and also the important reason of mortality among women. To perform a comparative study, algorithms namely, Artificial Neural Networks (ANNs) are evaluated in this research. One of the data mining function is said to be known as the classification, which allocate items/instances from the data set in a gathering of target categories. For the purpose of classification between malignant and benign samples, the optimum features of the classifier are modelled using ID3 and ELM. The Classifier is trained using two-thirds of the total samples. Most of the algorithm that has been created for learning the trees is the deviation in a particular core algorithm that utilizes a top-down, greedy search throughout the gap of probable trees. This approach is demonstrated by ID3. The experimental results obtained from the system developed in this research prove to be beneficial for the automated detection of breast cancer.
Cluster Based Deep Neural Network (C-DNN) Approach to Detect Heart Disease
Priyanga , Dr. Naveen N C
The term ‘heart disease’ refers to circumstances that block blood vessels and may lead to a heart attack, chest pain or stroke. The heart conditions will the affect heart’s muscle, valves or rhythm leading to heart diseases and bypass surgery or coronary intervention is used for solving these issues. In this research work, an effective Cluster based Deep Neural Network approach is proposed to detect the angiographic heart disease (i.e. to detect the patients with 50% diameter reduction of a major coronary artery). The data set is grouped using K-Means clustering algorithm and then the heart disease is predicted using cluster based deep learning approach. The proposed method is compared with various parameters for classifier algorithms like DNN, SVM- Linear, SVM- polynomial, KNN, ELM, ELM- cluster and to prove the system effectiveness in terms of accuracy.
Fast Image Segmentation Algorithm And Data Mining Techniques To Predict Lung Tumors From Lung Ct Images
B.Muthazhagan, Dr.T.Ravi, Dr. Rajinigirinath D
Cancer is one of the predominant killer diseases that cause maximum human death worldwide and it is on the rise. There are more than 200 varieties of cancer pervades among the mankind. Lung cancer also called as lung carcinoma retains in the top few positions of the list of all types of cancers in the past few decades. CT images are the most commonly approach used for Lung cancer treatment. In cancer diagnosis, Computed Tomography (CT) images provide the best facts on thicker tissue with less falsehood. In the Lung CT image analysis, the lung tumor segmentation phase plays a vital role to get more accurate results which in turn helps in decision making, surgical planning and assessments. The manual segmentation will be impractical and time consuming. The enhanced segmentation results would give better results for diagnosis and this would help the surgeons for correct treatment. Based on recent studies, calculation of image pixel percentage is used to detect the CT image features in image assessment. It remains useful to categorise and ascertain the abnormality issues in unprejudiced allegories, especially in various sarcoma tumours such as lung cancer. This research proposes an enhanced segmentation algorithm, Fast Boundary Box (FBB) method using Segmentation Genetic algorithm which is been used for CT image segmentation process. Genetic Algorithm is been used for threshold calculation, denoised image, training count, and tumor detection. GLCM2 algorithm is been used for feature selection of the segmented image. Adaptive Neuron-Fuzzy Inference System (ANFIS) is been employed for classification, in order to classify the lungs as normal or middle stage or abnormal stage. The results are been compared with watershed segmentation results and shown significant improvements.
Improving The Security In Web Application Cloud Service Karatsuba Montgomery Multiplier Ecc Algorithm
In recent times, web application is gaining its popularity in our daily routine such as banking, online shopping, reading news etc. It is observed that web application based cloud service undergoes certain problem due to its poor security features. This leads to generalized loss of information, which affects the confidentiality in web application cloud servers. In this paper, we introduce the idea of Elliptical Curve Cryptography to provide security into Web Application based cloud services. It aims at providing security to the cloud user (data, software) and cloud server. We then propose a Karatsuba-based Montgomery Multiplier and integrate it with Elliptical Curve Cryptography to improve the data security in web based cloud computing services. The main reason behind choosing the lightweight algorithm is to reduce computational burden of web based cloud services than existing method. Finally, a comparison is made between existing and proposed method in terms of its encryption and computational burden to check the efficiency and applicability of proposed protocol in web based cloud service. The results shows that proposed method attains better results than other methods in terms of its reduced encryption time, decryption time and computational cost.
A Novel Regression Neural Network Based Optimized Algorithm for Software Development Cost and Effort Estimation
H. AZATH, Dr. P. AMUDHAVALLI, Dr. S. RAJALAKSHMI, Dr. M. MARIKANNAN
Estimation of software development cost and effort is part of the software development life cycle, which consists of several problems for estimating cost and effort. The problems may occur in several circumstances during the development of a project. Time and quality are considered as fundamental issues in software development cost and effort estimation (SDCEE). Therefore, we propose an accurate estimation way as a successful factor which provides the risk reduction of SDCEE. In recent years, the evaluation of software tests has attracted considerable attention from researchers and it is a challenge in the software industry. For the last two decades, many researchers and Software developers have introduced the software initiative based on statistical and machine learning. Software development industry processes have been changed and the speed makes the task much easier to predict overall costs for SDCEE. In this work, cluster optimization algorithm based Meta-heuristic harmony search Algorithm is proposed which provides optimized results in which customer requirements and associated cost are assessed and the proposed technique takes decision based on SDCEE. The datasets are collected from open source web pages, in which we categorize datasets in four ways like finance, communication, game, and non-profitable organizations. Dataset takes in data to test the results in which parameters such as scaling factor, effort multiplayer estimation, consolidated size and effort, requirement effort, designing effort, documentation effort, deployment effort, on-site management effort are assumed and then divided into six datasets based on the productivity value of each software project. Furthermore, the General Regression Neural Network (GRNN) and Radial Basis Function Neural Network (RBFNN) are used in datasets.
Data Deduplication For Disaster Recovery In Private Cloud Storage
Dr. S. Pavai Madheswari, X.Ignatious Viola
The Disaster Recovery System provides continuous service and recovers the crushed information system when disaster occurs. Today natural calamities play a havoc in our lives and this has brought in the need for Disaster Recovery. The proposed methodology performs data de-duplication for private cloud storage backup in Disaster Recovery. In a typical Disaster Recovery System as a Disaster Recovery plan, backup data is replicated in a separate physical site for restoring operations. If the primary data center becomes unavailable the replicated data center will be made available to restore data. In this work as an effective disaster recovery plan, instead of replicating the entire backup, only unique instance of data is retained, using hashing algorithm in the cloud storage. It will avoid storing identical data. This will reduce the overall expenditure on storage and minimizes infrastructure costs for space, power and cooling. This is also a cost-effective solution for businesses with an internet connection.
Remote Sensing For Forest Fire Detection Using Landsat Images
P. Chanthiya, Dr.V.Kalaivani
The major root cause of forest degradation is Forest fire in India. The forest fire detection using remote sensing techniques can be analyzed with the help of satellite images like ASTER, LANDSAT images. The thermal band on Landsat 7 has a spatial resolution of 60 m, it is 120 m on Landsats 5 and 4 Thematic Mapper sensors. Thermal band and TIR band are the bands those are extracted from the LANDSAT and ASTER images respectively. Thermal Infrared (TIR) band is useful to observe temperature and its effects, the vegetation density, moisture, and land cover type. The features are analyzed by using the threshold values of each feature in the thermal bands. Land Surface Temperature is estimated for the particular area and the forest fire is predicted based on the intensity of pixels in the ASTER images.
An Improved Haze Removal Method For The Application Of Geographical Data Analysis
Anju J Prakash, Dr. A Ferdinand Christopher
The images taken in ghastly climatic conditions is a lot tainted owing to the occurrence of haze. It may also affect heavily, such images used in the ground of computer visualization, object recognition etc. As an aim to resolve this problem in this paper a better image enhancement as well as classification method is employed. The projected work takes benefit of SVD as this solo value allow us to characterize the picture with a minimal set of value that shrink storage space and progress the quality. For a superior quality and feature improvement a rate based alteration is completed with the help of gaussian filter. The eventual dehazed image is then classified using an improved knn as part of geographical data analysis.
Performance Metrics for Classification of Employee Absence at Work Place
When employees don’t turn up for labour it roots interruption to work proposals, taking the treasured time and drops the organization’s output or work rate. It can smash minor trades particularly inflexible, both economically and socially. Data mining algorithms such as J48, Naïve Bayes, Lazy IBk and Function Logistics are applied in this study for predicting absenteeism. The investigation outcome illustrates likelihood accuracy of 98.78%. Data mining facilitate the management to envisage designs in the dataset.
Gradient Boost Machine Learning Tree To Detect And Isolate Intrusions In Mobile Ad Hoc Network
E.Selvi, M.S. Shashidhara
Mobile Ad hoc Network (MANET) is a type of network, operating as a stand –alone network which communicates through wireless links. In this paper we have proposed Gradient Boost Decision Tree Classification (GBDTC) Mechanism. The GBDTC Mechanism is developed to aim the objective of improving the performance of intrusion and isolation in MANETs with minimum false positive rate. At initially used Pearson's Chi-Squared Distribution for selecting the optimal features from dataset. Then, GBDTC Mechanism is proposed for classifying the nodes in a network as normal or abnormal which results in improved intrusion detection rate and time. Finally, intrusion node isolation process is performed in order to separate the intruder nodes from network resulting in improved packet delivery ratio. The simulation of GBDTC Mechanism is conducted on parameters such as intrusion detection rate, packet delivery ratio, intrusion detection time and false positive rate. The simulation result shows that the proposed work performs better than other methods.
Requirements Fuzzy Possibilistic C-Means (Rfpcm) -Information Retrieval (Rfpcm-Ir) And Hybrid Test Criteria With Afa (Htcafa) For Regression Testing (Rt) With Traceable Links Analysis
V. Keerthika, Dr. P.G. Sapna
Software regression testing assesses the existing features on a software product while it is revised or novel features are included to it. It is an expensive process owing to the nature of regression testing. Numerous methods were presented to decrease the costs of this activity, amongst which are: prioritization, minimization, and choice of test cases. At present, so as to create regression testing more effective as well as active by hybrid criteria, soft computing methods, for instance machine learning, data mining, and others were utilized. On the other hand for the period of software regression testing and evolution, requirement traceable links turn out to be out-dated as developers don’t/can’t dedicate effort to update them. With the aim resolving this issue, this research work design, implements, as well as access Requirements Fuzzy Possibilistic C-Means (RFPCM) -Information Retrieval (RFPCM-IR) algorithm amongst software requirements as well as source code. This method could inevitably recover traceable links amongst free-text requirements as well as original code. After that, present Adaptive Firefly Algorithm (AFA) for RT in the company of test cases function values. The presentedAFA based RT validates the idea of merging multiple criteria into a hybrid combinations, Rank, Merge, and Choice, and illustrates their worth. For the purpose of enhancing the precision and recall,RFPCM-IR algorithm abandon/rerank the links. The mining software bugs as well as merging mined outcomes with RFPCM-IR algorithm enhances the accurateness of requirements analysis as well as outcomes.The outcomes prove that HTCAFA most regularly outdone their constituent individual condition for instance Rank, Merge and Choice formulations.
Natural Language User Query To Sparql Conversion For Web Service Discovery From Ontology Based Web Services Registry
A.Jebaraj Ratnakumar, K.Venkatachalam, S.Balakrishnan
Web services provide a standard means for interoperable operations between electronic devices in a network. Even in spite of emergence of semantic web standards, still Web Service Definition Language (WSDL) continues to be the most popular web standard for describing a web service without consideration of semantic information. This work aim to make a bridge the semantic gap between the discovery process and WSDL based registries. It is used to allow semantic web discovery using natural language search queries from ontology based web service registry. The major contribution of the work is to mapping to each Simple Protocol and Resource Description Framework Query Language (SPARQL) language construct for each DL query type classification. Proposed approach is to convert the natural language query, which generally has multiple ways of representing; to description logic based form and then converts this unambiguous form to SPARQL query which can be directly executed on the ontology web registry. Ontology which process Web Ontology Language (OWLS) files and adds the information to ontology web registry. This approach increases the efficiency because SPARQL queries can be executed faster on ontologies compared to any other retrieval method like keyword search, eXtensible Markup Language (XML) search etc.
Adaptive Equalization Method For Dereverberation And Savitzky-Golay Filtering In Speech Signals Over The Web
Jasmine J.C.Sheeja ,Dr.B.Sankaragomathi
Speech signals are apprehended by distant microphone in an enclosed atmosphere is frequently tainted by interferences of many speech signals and reverberations of the room. Accordingly, the separation of source signals is important and validates the Blind source separation (BSS) and Blind de-reverberation (BD). This signifies the frequency domain BSS for speech signals by a separation matrix through an Independent Component Analysis (ICA) for separation in the BSS. Subsequently, the permutation ambiguities of the ICA solutions are prearranged so that the alienated signals are shaped accurately in the time domain. While most speech enhancement algorithms improve the excellence of speech, they could not increase speech transparency in reverberation. This paper motivates on the improvement of an algorithm that can be modified for an acoustic environment and recover speech transparency. This paper proposes the Adaptive Equalization Method for dereverberation and Savitzky-golay filtering is used to reduce the noise. This paper has presented a short summary of how the wedding of speech signal and language technologies with the Web is varying the way people converse and access data. Advances are occurrence at a rapid pace through enhanced algorithms, wider diffusion of the Web, accessibility of information, and faster computing. As the Web continues to develop, study plan require maintaining to deal with complex issues in areas of mining of information regarding multimedia data of Web and media contents, speaker identification for decreasing Internet fraud, interactive answering designed for Web-based self-service, Web mining designed for knowledge discovery.
Maintaining Software Requirements Using Frequent Path Mining And Clustering Algorithm For Web Usage Data
Rajkumar N, Viji C, Duraisamy s
The data mining for software engineering is progressing over the past years. It is related to the application of data mining for offering beneficial perceptions the way of enhancing software engineering processes as well as software itself, aiding decision-making. So, data generated by software engineering processes as well as products, subsequently software development are utilized. Regardless of hopeful outcomes, there is often a deficiency of discussion on the role of software engineering practitioners among the data mining methods. On the other hand maintenance as well as advancement of the software could be problematic as often the requirements are no longer actual and/or frequently not even subsist documented. Examining the application of the websites could find out enhancements and aid to keep the website in addition to its software requirements. This paper Software Requirement with Data Mining Analytics (SRDMAnalytics), a recommender system, which collects the data regarding the use of a website, processes it and makes suggestions to the requirements specification of the website. It encompasses five main steps: mapping, Navigation of frequent paths, Traceability Matrix analysis, Requirements Analytics and report analysis. The second and third steps turn out to be most significant step to raise the SRDMAnalytics outcomes. In this research, with the help of Improved Ant Colony Optimization (IACO) algorithm, Navigation of frequent paths are carryout as well as with the help of Fuzzy C Means (TM-FCM) clustering algorithm, traceability matrix formation is carried out. TM-FCM algorithm, relate the links amid the functional requirements as well as the web pages in addition to the website elements. This presented Data Mining based Recommender System (DMRS) for Software Engineering (DMRSSE) is a new method to aid developers in decision making. It could assist developers to identify alternate decisions in an extensive range of software engineering tasks from reusing code to write efficient bug reports. This presented DMRSSE system is utilized for the enhancement of the quality of a web application. The presented system is assessed in real environments with the help of software development experts utilizing an exhaustive collection of criteria, and the outcomes are hopeful.
A novel approach to the performability of VANET: VBRCP with UGFT
Dr.M. Rajeswari , Dr.C.Sivamani, Dr.K.S.Meena
A reliable Vehicular Based Reliable Clustering Protocol (VBRCP) for transmitting road safety information between vehicular nodes is presented in this paper. Transmission range of vehicular nodes are said to be identified during phase-I of VBRCP. Nodes are grouped to form a cluster based on this transmission range of vehicular nodes. The parameters like Degree, Degree In Difference, Sum of Degree, Battery power, Node movement and Combined weight are used to elect the cluster head. The reliability of transportation system is considered as the probability of successful delivery of information from a source vehicle to the destination vehicle. This is attained by using UGF (Universal Generating Function). Node UGF of a member node / cluster head and link UGF are used to define the reliability of VBRCP. Algorithm is proposed in UGF in order to calculate the link reliability which represents the successful delivery of traffic information between the ongoing vehicles on the roadside. Proposed protocol is compared with some other existing protocols. Simulation results show that VBRCP outperforms other protocols in terms of delay, packet delivery and throughput.
An Web Based Alarm System For The Border Crossing Indian Fishermen
Every day we come to know through news channels and magazines the Tamil Nadu Fishermen being arrested by Sri Lankan police for border crossing. Recently peoples in the order to find the suitable path from source the destination via one aspect of a mobile phone have been extensively used web applications. After the discharge of android based open source mobile phone, a user is able to access the hardware directly, design customized applications to develop Web, and Global Positioning System (GPS) enabled services. In Gujarat, also the fishermen arrested and killed by Pakistanis. This is happening because of poor knowledge about sea borders between countries. Therefore, a new system has to be developed to overcome border-crossing problem. In this paper, we suggest a new Global Positioning System (GPS) for fishermen problem .
The GPS receiver is used to find the current fishermen boat location by identifying the latitude and longitude values and is send to the microcontroller unit. The found latitude and longitude values are compared with predefined values. Based on that value the distance between the current location and border has to identified. Based on that value fishermen can able to know they are near to border or not.
The area can be divided into 4 Zones (i) Safe Zone (ii) Nearby Warning Zone (iii) Nearby Dangerous Zone (iv) Dangerous Zone
When the boat is in Safe Zone, there is no problem for fishermen and they continue to do their process. If the boat is entered into nearby warning zone automatic alarm rings twice with 5 minutes snoozing time . If the fishermen did not consider that alarm and continuously doing their work. In that case the zone limit checked continuously. When the boat will reach the nearby dangerous zone then again alarm rings continuously and the speed of boat reduced to 50% automatically. Again the fishermen continuous his work without react for that alarm process and then the boat reaches dangerous zone. After that automatically the boat will take a ‘U’ turn either in left or right direction.
A Cluster Approach for maximizing packet delivery rate in Wireless sensor Network
Wireless Sensor Network (WSN) plays a vital role and part of real time communication applications. Location of unknown node is difficult to find in the presence of mobile sensor nodes. Navigator plays an important role in identifying network fault and unknown node location. In existing schemes, either trilateration or geographical position routing were deployed to increase the location accuracy. However this research method doesn’t focus on the neighbour location and signal strength which might lead to path failure leads to reduced packet delivery rate. In this research, Neighbor based Cluster Location Aware Routing (NCLAR) is proposed to achieve more packet delivery rate with high location accuracy. The main contribution of this research method is to ensure the guaranteed packet delivery rate with reduced path failure and neighbour node coordination. The proposed method consists of three phases. In first phase, cluster region is formed with less signal delay value and more signal strength. In second phase, neighbor node routing table is constructed and updated with addition of more fields. These fields are reliability, probability of successful transmission of packets and delay. The back off timer is estimated to update the table within a periodical time. In last phase, location status navigator is calculated to increase location accuracy and to maximize the packet delivery ratio. Based on the simulation results, the proposed scheme NCLAR achieves high location accuracy, more packet delivery ratio, less overhead, less delay and high network lifetime.
An Intelligent Inter-Vehicle Data Dissemination in Vehicular Ad-Hoc Networks for Online Health Care Applications
P. Nivethitha, Dr. J. Suguna
Background: In a traffic control system the safety and efficiency can be greatly improved by using Intelligent Transportation Systems (ITS) technology. The data distribution design is the most important challenge in VANET, since the messages can be resourcefully distributed in a high vehicular speed, highly dynamic topology and the irregular connectivity.
Objectives: In current scenario, VANET integrated with ITS is an evolving topology which gives a direct communication between a Vehicle-To-Vehicle and Vehicle-to-Infrastructure.
Methods: In this work, by using the Scalar Algebraic Triangular Network Coding (SATNC) to solve the inter-vehicle data distribution problem based on Wireless Access for Vehicular Environments (WAVE)/802.11p in a VANET. This SATNC model is used to effectively deal with the high encoding and decoding computational difficulty. In the Long Term Proportional Fairness with Quantum-behaved Particle Swam Optimization (LTPFQ) scheduler the distributor role is performed on a node by node in the required promulgation way. In this work, to select the weight values by using Quantum QPSO to all the users.
Results and Conclusions: Simulation results show that the SATNC protocol gives significant performance in terms of Qos parameters. This work is exclusively simulated for medical data in the Ambulance vehicle for securing the bio-medical data.
Generic Hybrid SOA Architecture for Cloud Computing
Mr. Kumaresan .S, Dr. Sumithra Devi.K.A
In information technology stack Cloud services provides easy coupling implementation to enhance encapsulation data between multiple platform data exchanges. My finding towards introducing High Availability Architecture for cloud environment which covers Load Balancing, Failover, High Availability Resources. To achieve this feature, it’s identified framework architecture which is called as Generic hybrid SOA Architecture Cloud Computing which increase cloud services standard in high with easy adaptable security. Even though cloud service supports loose coupling and isolation business logics. At current cloud service provide wants to launch new web service request on fly same service will not notified into client in real-time scenario. To overcome this complicated situation, we have introduced (GHSAC) Generic Architecture Framework in Cloud Computing. Which will support data exchanges between producer and consumer on the fly with real time scenario.
Network Failure Detection and Diagnosis by Analyzing Syslog and SNS
Data: Applying Big Data Analysis to Network Operations
M.Susila, Dr. R.Udayakumar
We present two major information examination strategies for diagnosing the reasons for system disappointments and for identifying system disappointments early. Syslogs contain log information created by the framework. We dissected syslogs what's more, prevailing with regards to distinguishing the reason for a system disappointment via consequently learning more than 100 million logs without requiring any past learning of log information. Investigation of the information of an interpersonal interaction benefit (in particular, Twitter) empowered us to recognize conceivable system disappointments by extricating system disappointment related tweets, which represent under 1% of all tweets, continuously and with high exactness.
Reconfigurable On-Chip Communication Link for Efficient Communication
S.Beulah Hemalatha, Dr.T.Vigneswaran, M.Jasmin, Dr.M.Sundararajan
Application specific reconfiguration of On-chip communication link is a fast growing research area in system on chip (SoC) based system design. Optimization of the communication link is important to achieve a trade-off between efficient communication and low power consumption. So achieving both efficient communication and low power consumption requires a special optimization mechanism. Such Optimization problems can be solved using a genetic algorithm. Here, in this paper genetic algorithm based On-chip communication link reconfiguration is presented. The algorithm will optimize efficiency of communication link with constrain of low power consumption. The parameters involved in power consumption and efficient communication link are coded in the chromosomes. By evolutionary iteration the optimal parameters of the communication link are derived that is used for the communication link successfully in the simulated system. The performance of the simulated system is analysed which shows the out performance of the proposed system.
D2D Communications in Mobile Networks with High Reliability and Privacy Outage Restrictions using Feedback Scheme
N. Divya Lakshmi, Dr. V. Khanaa, Dr.R.Udayakumar
In this article, we suggest a D2D- device to device communication situation under laying a mobile network where both mobile users and D2D are distinct power-rate systems with restricted criticism from the recipients. It is understood that there survives a challenger which needs to snoop on the data communication from the BS-base station to Mobile unit. Since D2D-communication stocks the similar spectrum with cellular network, irritated intrusion must be deliberated. Though, when privacy capability is painstaking, the meddling caused by D2D communication may help to increase the secrecy communications by mystifying the listeners. Since both systems segment the similar spectrum, cross intrusion must be measured. We suggested efficient data downloading and data sharing system with minimum interference or traffic using AODV protocol and topology based routing method. The enactment of the proposed system is calculated using mathematical outcomes for various circumstances
An Adaptive Coding Scheme For Reliable Data Streaming Over Delay-Tolerant Networks (DTNS)
C.Rukkumani, Dr.Krishna Mohanta.S, Govindaraj.S, Dr.R.Udayakumar
Delay Tolerant Network (DTN) is a testing undertaking because of long delay and continuous link interruptions. To empower reliability, is presently taking a gander at methodologies to coordinate eradication coding instruments inside DTN architecture. Data segmenting over Delay-Tolerant Networks is a testing undertaking considering mutually the particular attributes of DTN situations, the requesting idea of segmenting applications and their wide relevance. Be contrast from conventional networks, the nodes in delay tolerant networks are associated irregularly and they are mobile persistently, which result in high transmission delay and low delivery proportion. By and by, there are no best in class components accessible to help this usefulness and run of the mill setups neglect to effectively exchange data segments. In this paper, we exhibit our continuous work in data segmenting over DTNs and propose the a system to enhance the data segments reliability. To start with, every node constructs its own topology and the nodes in every topology are positioned in the best s in numerous measurements. The link weight, which mirrors the packet delivery capacity between the two nodes in the topology, is characterized by the reciprocals of ranking estimations of the two nodes in numerous measurements and the reciprocals of vital coefficients of each measurement. Second, in view of the parallel topology, every node could choose through the congestion border, appropriate routing for each particular packet sending. Third, we acquainted coding based adaptive instrument with affirm the reliable communication. Simulation comes about demonstrate that the proposed work permits a critical diminishment as far as network overhead infused by deletion codes while guaranteeing the conclusion to end reliability
Hybrid rate less codes with compression for overhead reduction and multiple bit error correction scheme for NOC
M.Jasmin , Dr.T.Vigneswaran, S.Beulah Hemalatha , Dr.M.Sundararajan
Because of ceaseless change in CMOS technology there is a need for coordination of countless heterogeneous devices that need to communicate productively on a single chip. For this routers are needed to be proficient to communicate between these gadgets. Network-on-Chip (NoC) architectures are supplanting the bus based Systems-on-Chip (SoC) models, with productive communication among centers at essential design and power costs. Error Correcting Codes (ECCs) are getting main stream in the most recent years, because of the improvement of new standard for high throughput communication, for both remote and wired terminals. Such high throughput can be accomplished by the optimal hardware architecture. Hardware models for high throughput ECC encoding and decoding is to configure parallel designs, where the decoder depends on a few processing elements. Hence we came up with an innovative error control plan to adapt to mistakes influencing the correspondence connections of a Network-on-Chip. Our plan possibly designed in hybrid Mode, Correction Mode, and Detection Mode, contingent upon a specific function to meet distinctive QoS echelons as far as error control. For each of the above mode, we recommended different error control schemes. We assess points of interest and downsides of each approach, regarding signal trustworthiness, territory overhead also, effect on execution.
Modern Metrics (MM): Size Estimation of Modern Software and its Metrics Analysis
John T Mesia Dhas, Dr. C.R. Bharathi,T.S.Shiny Angel,J. Sheeba
The actual size estimation of the modern versatile software is very hard with existing methods. A novel method Modern Metrics (MM) analyse all the possible functional units and complexity factors of the modern software and give the actual size of the software. This new method considers internal operations, Data Base, System Development Life Cycles, output formats, international standards and multiple software usage. It increases the accuracy of the results and also reflects good results in cost, size and time constraints. This paper explains the procedure for finding the size of the software using MM and also compare with traditional Function Point (FP) methods.
Power and Delay aware Relay Node Selection Algorithm for Cluster based Mobile Wireless Sensor Networks
G Lakshmi Vara Prasad, Dr. C. Nalini, Dr. R. Udayakumar
Mobile Wireless Sensor Networks (MWSN) is made up of several minute highly mobile sensor nodes which communicate wirelessly with one another. This network has a very dynamic topology. Due to the wireless nature of the network, the network resources are limited. During continuous network operation, the chances for the nodes to get depleted of its resources are very high, which effects the lifetime of the nodes. The continuously changing network topology makes the nodes to keep looking for effective path to its destination. This increases the overall delay in data transmission. In this paper, we propose to develop a Power and Delay aware Relay Node Selection Algorithm for Cluster based MWSN. In this algorithm, the packets will be prioritized and then the cluster head selects a relay node to forward the highest priority packet based on the reward value estimated through probing, power consumed i.e., probing cost and waiting delay involved in the network. The most appropriate relay node is selected to forward the data packet to its destination.
Stock Price Prediction Using Web News Based Soft Computing Approach
In the stock market prediction foremost basic of these is that the gain. What is more there's the challenge of proving whether or not the markets are certain or not. The foregone conclusion of the market is a difficulty that has been much mentioned by researchers and scientists. In our proposed concept of finance a hypothesis has been formulated, referred to as the Proficient Market Hypothesis, which means that there is no pace to build profit by predicting the market. In our stock exchange prediction task reads news and information to predict the market and those that believe that the market is proficient and whenever new data comes up the market absorbs it by correcting itself, therefore there's no pace for prediction using artificial intelligence. Moreover they believe that the stock exchange follows a stochastic process, which suggests that the most effective prediction you'll have regarding tomorrow’s worth is today’s worth. The suggestions of news will be cross checked with the experts group.
A Hybrid Bootstrapping Framework Using QoE and QoS for Effective Web Services Composition and Discovery
Web services are becoming the technology of choice for comprehending service-oriented architectures. Web services provide ease of application integration and simplify interoperability. It also helps for wrapping with the available applications so that the developers can access them through standard languages and protocols. Selecting the correct service according to the user request is the challenging task to the user since the behavior of the participant service regulates the overall performance in discovery, selection, and composition.Hence it is significant to choose high-quality service for these processes.Existing methods trust on nonfunctional characteristics for discovery and selection but the user cannot trust these characteristics always, and these QoS values cannot determine the user viewpoints (or) perspectives of Quality.Moreover, during selection, the user shows interest in a high-quality service based on quality attributes (or) the service which has a good reputation rather than selecting a newly registered service.So a proper bootstrapping mechanism is needed to judge the newly registered service before the service requestors use them.The contribution in this paper involves: (a) an evaluation approach to analyzing the QoS attributes assesses on performance specific values such as response time, execution time throughput, latency, reliability, etc. (b) an evaluation approach to analyze the QoE attributes based on the user reviews assesses on attributes and opinions (c) Bootstrap the newly registered service based on Quality of service and Quality of experience (d) Building a Recommender system that suggests the top rated service for composition .The results of the evaluation process are used to augment the current web services by providing an up to date QoS, and QoE attributes for Discovery, selection, and composition.
Performance Analysis of Data Manipulators Based on IoT using Neural Networks
This work is to design a neural network based intelligent model reference adaptive controller. In this scheme, the intelligent supervisory loop is incorporated into the conventional model reference adaptive controller framework by utilizing an online growing multilayer back propagation neural network structure in parallel with it. The Conventional Model Reference Adaptive Controller (MRAC) schemes the controllers were designed to realize plant output converges with reference model which is linear. But this scheme is more efficient for controlling linear plant with unknown parameters. However, using MRAC for controlling the nonlinear system in a real time application is a challenging one. The control input parameter values are given by the sum of the output of conventional MRAC and the output of Neural Networks (NN). The NN is used because to compensate the non-linearity of the plant. The parallel neural controller is designed to precisely track the system output to the desired commend trajectory. The proposed work can improve the system behavior and also force the system to follow the reference model. The effectiveness of the proposed work is demonstrated by MATLAB simulation. The results of the proposed work have been demonstrated by simulations and compared with the existing methods for improved results. This MRAC scheme doesn’t need any initial parameters and works even in uncertain environmental conditions. It easily adopted for all real time environmental conditions without any pollution and fuel consumptions.
Experimental Study Of Single Basin Solar Still With Flat Plate Collector
This research work addresses various issues and advantages in using flat plate collector to increase the daily productivity of solar still with less heat losses Flat plate collector is an alternate solution which replaces the traditional reservoir system, this modification increases the productivity and experimental setup reaches maximum temperature of 96°C which is 35% more than the traditional distillation method. Collector and still are coupled naturally and the design parameters of solar still presented as experimental setup and the daily average of distilled water is found to be 099 which is higher than the normal solar still.
Optimal Control Techniques For Energy Saving And Cost Saving Of Using Variable Frequency Control Method In Flow Process Station
P.Anantha Christu Raj, R.Rajeswari
In recent years, energy saving play a major role in industrial system including liquid transfer and hydraulic processing. In addition, there is an enormous demand for cost saving of flow process in industries. The flow process station consists of a reservoir from which the liquid is transferred to the overhead tank by means of a motor. The process variable in this process is flow. An orifice meter is employed to measure the flow rate of the liquid passing through the pipe. Differential Pressure Transmitter (DPT) senses the pressure difference and it is calibrated to provide the correct flow rate. DPT sends the measured value to the process computer where the controller is employed. Here PC acts as error detector and controller. According to the error signal, corresponding signal is given to the I/P converter. It controls the fluid flow in pipeline by varying stem position of the control valve. The present arrangement of flow control station comprises of a control valve, which throttles the liquid stream in the pipe as per the control standard given by the controller. Flow process station found in oil and gas, chemical and food production plants around the world. During the last 10 –15 years the industry has seen a significant increase in the adaptation of variable frequency control in wastewater transport systems. A general desire is to better control the wastewater flow through the pump stations. Variable speed systems can provide a more flexible and powerful solution compared to using constant-speed pumps. The cost and energy are compared with valve control method, Variable Speed method and Variable Frequency method.The two major constrains energy and cost is addressed in this paper. Minimization of both results in increased productivity. Hence both these factors where measured and analysed. To analyse the cost following factor are conceded .
1.The utilization factor is considered as 24*7 for 365 days
2.The commercial tariff Rs. 6.25 per unit is considered.
Based on these factor further experimental study and analysis are performed and it was concluded that frequency controlled method outstands the performance of valve control and voltage control method. The variable frequency method of flow control proves to be an effective control scheme as the settling time and oscillations are highly reduced, hence improving the overall performance of the system, with energy and cost conservation.
The Impact Of Learning Style To Enrich The Performance Of Learner In E-Learning System
G.Deena, Dr. K.Raja
to lead everyday activities in the universe, the learning is an extremely fundamental to everyone. To gain the knowledge there are many different possible ways that are available in the world. Among those, the E-Learning is greatly recognizable to each and every one. In this era, E-Learning has become more popular in learning community because of its features such as anytime anywhere learning. In reality, as a collection there are sizeable amounts of course materials are available in the website. The E-learners are able to access the course materials without any guidance. But the point is sometimes they feel very confused in accessing the exact content from the web collection. This confusion or frustration may lead the learner to put an end to the course. In order to avoid these issues, the proposed methodology helps to identify the learning style of a learner, and their ability level using blooms taxonomy. Based on the identified learning style the course material has been supplied to the learner. In an experimental analysis, a set of 27 students were considered from the same course and examined the post assessment with the existing methodology. From this, a proper guidance has been given to the learner to continue the learning process without any distraction. So, the learner has to so know the level of complexity while understanding the concepts should be there when they are learning something. The learners should not get distracted while continue the learning process so there is a chance to put an end to the learning. In order to avoid this issue, the proposed methodology is used to find the learning style of a learner, the ability level by using blooms taxonomy. In the experimental analysis, we have captured the post assessment for the proposed methodology compared to the existing methodology by taking the set of 27 students. By this, the proper guidance will be given to the learner in order to continue the course without distraction.
Gro And Wego - Algorithmic Approaches To Integrate The Hetrogenous Databases And Enhance The Evaluation Of Ontology Mapping Systems In The Semantic Web
Dr. V. Rajeswari, Ms. M. Kavitha, Dr.Dharmistan K.Varughese
In the present day world, where information driven economy and information enhanced living standards rule everything, the sources of data from which the information is derived, are highly heterogeneous. The heterogeneity necessitates a mechanism for integrating data, existing in a variety of forms, before it is presented to the user in a fruitful manner. Different strategies have been developed with a number of implementations available to help the world population benefit from the ocean of data available across sources through massive network of computers. The Internet and World Wide Web, forming the backbone of the information highway will benefit from research solutions that enable people to retrieve data or information that fit their specific queries or requirements. Semantic web is an initiative in achieving that goal of “machine processed information” being available to us than requiring human intelligence for processing information. This work is carried out to address the heterogeneity problem that exists among data sources and provides a solution through the application of ontology. The ontology by itself is a structured data representation and intended for information processing through machine intelligence. Artificial intelligence is a thrust area for ontology applications. Ontology is a conceptual tool for handling semantic heterogeneity. The algorithmic approach adopted in the mapping solution system, considers the most common structure of ontology representation viz. the graph model. The graph nodes or the elements of ontology are compared carefully by a set of nine matching parameters to obtain various indices or scores as explained subsequently. Then a comprehensive similarity analysis is carried out to arrive at the degree of matching of individual nodes as well as the ontology in totality for an ontology alignment.
An Modified IDEA-HMAC Cryptography Based MAODV Routing for MANET through Cluster Based Intrusion Detection System
Mobile Adhoc Network (MANET) is a group of remote compact hubs confining a short term framework without any guidance of any settled communication establishment. In view of confined resources, visit organize packets and surprising topological changes, proactive gathering designs get high overheads in this condition. To keep the security of compact uniquely selected frameworks various wellbeing endeavors are arranged, for instance, encryption estimations, firewalls et cetera. However there is some degree of threatening exercises. In this work, a Modified IDEA-HMAC based secure disseminated grouping calculation for MAODV routing protocol is proposed for secure message transmission, routing through Cluster based Intrusion Detection System in MANET. This algorithm for Intrusion recognition frameworks are proposed to distinguish any intruder in the system and its vindictive exercises. It is additionally utilized for cluster arrangement, upkeep and purging activities and grouping data for speedy course disclosure, support and cluster conveyance. The Modified IDEA is utilized for encryption, it is one of the safe and most generally utilized square figures and the cryptographic quality of Modified IDEA depends on a blend of three inconsistent gathering tasks – XOR, expansion and particular duplication and it is secure against powerless key assaults . To upgrade verification, for the Modified IDEA encryption, a hash message confirmation code (HMAC) utilizes a cryptographic hash work combined with a mystery key for secure message transmission and correspondence among the portable hubs in systems. Likewise, this calculation used to add versatility to the MAODV routing protocol to forestall against routing assaults in MANET. This proposed calculation additionally guarantees verification, encryption and honesty of the message which are transmitted by means of portable adhoc arrange.
Habitual Failure Recovery by Traffic Rerouting with Pre-Configured Backup Paths in OpenFlow based Software Defined Networks
Senthil Kumaran N, Thangarajan R
Software Defined Networks (SDNs) is a modern network management architecture enabling the design of control plane independent of data plane as a split architecture. An SDN controller in control plane dynamically configures and controls the networking nodes by allowing them to focus only on data plane functions. Though this design also suffers from scalability, security and load balancing issues, failure recovery is considered as the key task in order to avoid data loss in large scale data center networks. This paper addresses this issue and proposes a failure recovery technique that automatically reroutes the traffic with pre-configured backup paths in case of link or node failure in the working path. Bidirectional Forwarding Detection is employed to quickly detect such failures. In this work, a proactive protection approach is followed by configuring the primary and alternate backup paths for each networking node to every other node. Hence, automatic recovery is done by the node itself without overloading the controller and the flow tables’ reminiscence. Alternate backup paths are computed using braided multipath scheme that provides a relaxation on node-disjointedness. The performance of the proposed system is analysed with respect to packet loss and recovery time. Despite the increase in memory to store backup paths, it produces good results in recovering from the failure.
A Hybrid Enhanced Fractal Texture Analysis with Layout Descriptor approach for Image Segmentation
Kandavalli Michael Angelo , S Abraham Lincon
Image features can be extracted from various ways basing on the shape features, color features and texture features. There is a wide need for segmenting objects in complex situations and identification of the objects. It has become complex due to the variability of objects and the background. This paper aims at designing a hybrid approach called Enhanced Fractal Texture Analysis with Layout Descriptor by analyzing various feature extraction and object recognition techniques. In this process, at first the Adaptive Switching Median Filter preprocesses the image. This is done for removing noise that is present in the image without losing the fine qualities. Besides the noise reduction, it is important to preserve edges this is addressed by a noise-protected edge detector. Later, a morphological gradient technique that is the combination of shape and texture gradient, removal is applied for obtaining the qualities of the image. This approach supports in improving accuracy prediction for the object. This design method extracts shape feature from the first stage output. Various details like compactness, eccentricity and moment invariants can be obtained in the approach. The hybrid approach reduces the execution time when compared to existing techniques. This design is robust and generates better values in terms of performance evaluation.
Anomaly based Web Intrusion detection system in Wireless sensor network using Interdependent Security Game Model
Gethzi Ahila Poornima I, Dr.Paramasivan B
Wireless Sensor Networks (WSNs) contains small devices that able to process, route the sensed data and able to detect the intruders. The method of identifying any anomalous attacker or moving object within the reach of WSN region is said to be intrusion detection. In order to protect WSNs from malicious nodes, this study proposes a new game theory model. Because of low complexity, scalability and scattered behavior of WSNs, the malicious attacks may be modeled efficiently by game theory. In this research, a new Dynamic Bayesian Security Game Model is developed to perform anomaly based web intrusion detection in WSN. Initially, malicious node utility is estimated for detecting specific nodes that engaged in misbehavior activities. The regular nodes examine continuously to estimate their neighbors by using belief estimation and belief update system of Bayes rule. The experimental findings reveal that the proposed technique might significantly reduce the mischievous activities of intruders and thereby improve the secure routing
Probabilistic Sparse Fuzzy C Means clustering with Actor Critic Neural Network for intrusion detection
Intrusion detection is the process of attack identification in the computer systems and it paves way for the identification of penetrations, breakings, and other computer related abuses. However, the growth of the internet-based devices makes the detection process a complicated procedure, posing the need for the automated system to identify the attacks. With this in mind, the paper proposes an automatic method of intrusion detection using the Brain storm-Crow Search based Actor Critic Neural Network (BCS-ACNN) classifier. Data clustering forms clusters of the input data using the proposed Probabilistic Sparse Fuzzy C-Means (Probabilistic Sparse FCM) Clustering algorithm. The clusters are subjected to the two-step classification that is progressed using the proposed optimization algorithm, and in the second level of classification, the intrusion in the data is detected. The Brain storm-Crow Search (BCS) algorithm, which is the integration of Brain Storm Optimization (BSO) and Crow Search Algorithm (CSA), optimally tunes the weight of the Actor Critic Neural Network. Similarly, the Probabilistic Sparse FCM algorithm is the integration of Probabilistic theory in Sparse FCM. The experimentation of the proposed method using the KDD Cup dataset yields an accuracy of 0.7682, True Positive Rate (TPR) of 0.7984, and False Positive Rate (FPR) of 0.4580.
Ontology-Based Event Detection Framework For Journalist
The progress of digital technology and the fame of social media sites such as Facebook, YouTube, Flickr etc. fashioned an attention to share memories. This leads to a colossal amount of multimedia content such as text, audio, photographs and video on the web. This social media has become a traditional news sources. The social media is considered and monitored by the journalists for news coverage. But, this information is noisy, unstructured, unfiltered and needs manual processing which is difficult in the huge information available on the web. One way to retrieve the multimedia data is by identifying them as events. Automatic organization of a multimedia collection into groups of items, where each group corresponds to a distinct event is described as event detection. This paper addresses the problem of journalists in handling the huge volume of data by proposing a framework for social event detection, where hybrid clustering approach is done over ontological modeling. This proposed approach outperforms the existing event detection task. The use of semantic based ontological modeling holds richer semantics and pulls needed information automatically resulting in increased retrieval performance by reducing false positives. This approach is useful for journalists to identify media sources related to events as effective clustering approaches are used on contextual features. The proposed work was implemented with samples of 70000 photographs of various events. The F-measure was increased to 0.9098 in the proposed work after considering contextual semantic features such as temporal, spatial, textual and weather information.
Artificial Intelligence based attack mitigation Using Stochastic Game Theory Modelling with WQLA in Cognitive Radio Networks
Cognitive radio network (CR)is a promising paradigm that helps the unlicensed user such as Secondary User (SU) to analyse the spectrum and coordinate the spectrum access to support the creation of common control channel (CCC). It leads to security threats in CR. The cooperation of SUs and broadcasting between them is done through transmitting messages in CCC. It directly degrades the network’s performance while the control channels get jammed. Such scenario jammers devastate the control channels. In this, Hopping sequences technique used to fight against this problem to confront jammer. Stochastic games model is proposed to alleviated the jamming attack and analysed with more single users to provide the flexible control channels against intrusive attacks by mentioning the states of each player, strategies, actions and players reward. The proposed stochastic game theory scheme uses a modern player action and better strategic view to prevent the jamming attack in CR network. The decision is based on wolf Q learning approach to mitigate the jamming nodes using the multi-agent Markov decision process.
Watchdog- Round Trip Time Method to Detect and Prevent the Wormhole Attack using AODV Routing Protocol
Wireless Sensor Network (WSN) has gained lot of popularity in recent decades. However, the security aspect of WSN has also been a concerning factor in recent years. In wormhole attack, the affected node can make a new short route that is shorter than the original path. This can confuse the routing mechanism. The affected node can make tunnel between them to transfer the packets from one location to another. The Ad-hoc on demand distance vector (AODV) routing protocol is used to discover the route. The proposed method is used to identify the wormhole attack nodes and detect them based on Watchdog-RTT mechanism and also identify the supporting nodes which will help the malicious node. The main idea of this paper is to identify the malicious node as well as the supporting node by Watchdog-RTT method to detect and prevent the wormhole attack. The simulation results showed that the proposed work has significant improvement compared to existing works.
Optical Character Recognition of Odia Handwritten Scripts and Numerals: A Survey on Web Based Utility Application
Recognition system to various scripts was very much challenging and fascinating in this digital world. This character recognition has vast number of application in the current scenario of the digital world. Character Recognition with respect printed, handwritten and degrades characters of different zonal languages comes under Indian regional scripts has been reported from last few years. But usually Character recognition put emphasis on the variation of shape, scale, orientation and format in hand written characters by various aged writers. Here in this paper we have make a complete analysis regarding a depth survey on character recognition with reference to Odia script, which is followed up by various approaches of soft computing and machine learning techniques. All the analysis has been reported over both printed and handwritten characters of numeral and characters set in the process of character recognition. This paper has been segmented into different section in order to convey the recognition process of Odia scripts in details. Here we also try to establish a relation between the digital worlds through computational intelligence. The work also focuses on web-based utility application wherein the recognition is stored online (cloud storage). Numerous feature extraction procedure has evaluated along with several classifiers have been taken into account for the character recognition such as Neural Network, Hidden Markov Model, Support Vector Machine, Genetic Algorithm etc.
DNA Compression Method Using Auto-Regression and Firefly Algorithm
The genome of an organism has all the hereditary information, which is encoded in DNA. It is highly critical to have the genome sequenced to decide on the survival, development and multiplication of the organisms. In recent times, the whole genome sequences are having an exponential growth with time. Moreover, to compress the enormous sized genomes, an effective algorithm is necessary. For this issue, the earlier system presented a technique based on Auto Regression (AR) modeling, and the model parameters are decided using Particle Swarm Optimization (PSO), results in lower compression ratio, because of PSO’s partial optimism. To boost the compression ratio, a new system, Hybrid Optimization Dependent Auto-Regression DNA Compression (HOARDNAComp) is proposed which uses soft computing techniques; auto-regression and firefly algorithm. This algorithm operates in horizontal mode by using substitutional-statistical method that is on the basis of AR, and the model parameters are decided with Modified FireFly (MFF) Algorithm. In the fundamental firefly algorithm, the brightest firefly moves in random, this result in the degradation of its performance during certain iterations, hence modified firefly is proposed. Here, when this brightest firefly is permitted to move just in a direction, where there is an improvement in its brightness, then it will not reduce the algorithm’s performance in terms of global best solution for all solutions obtained in that certain iteration. The proposed system targets at reaching a greater compression ratio that make its application advantageous owing to decrease in storage, retrieval, transmission expense and the inferring structure along with the function of sequences obtained from compression. The implementation outcome proves that the proposed MFF algorithm can achieve better compression ratio than the existing research methods.
Fadasn - Force Attenuation Delay Aware Acoustic Waves Underwater Sensor Network
The world is covered by three parts of water region and one part of the land. There are some big oceans ar
e contains the global water and offers plentiful resources. This work focuses on acoustic signal propagation base
d routing protocols for calculating channel propagation loss in the underwater (UW) environment taking attenua
tion, delay and water force as its primary constraints. The global announcement uses a velocity in meter per min
ute as the underwater announcement is minimum than global contacts. So, the routing in this atmosphere is extr
emely disordered with compact channel bandwidth, transmission delay and consumption of energy.
Real Time Nano Constrained Based Location Selection Approach For Data Transmission Between The Nanomachine In Mobile Ad Hoc Network
The data transmission in Mobile Ad hoc Network (MANET) is a challenging task which has to be performed efficiently. There is some approaches has been declared for the problem of data transmission in Nanomachine, which uses several methods and factors in the selection of mobile nodes which has data stored. But not only the choice could improve the performance of data transmission, and there are so many factors which affect data transmission indirectly. It's considered such implicit factors in data transmission to propose a Real Time Nano Constrained Based Location Selection Approach (RTNCBLS). The proposed method maintains the list of mobile nodes and the trace about their data availability, reliability, the last time window data collection performed, number of supporting node available in wakeup mode. Based on all the above factors the method computes the efficient data transmission for each of the location considered, and at each region, the method calculates the data availability measure for different data nodes to select them for data collection. When a Real Time Nano Constrained Based Location Selection Approach is deployed in an environment, various parameters like the throughput ratio, impact of delivery ratio, packet delay and data transmission efficiency, these parameters mainly affect the robustness of nodes, scalability and group management.
Mobility Based Improved Call Admission Control Scheme For Mobile Wimax Networks
Worldwide Interoperability for Microwave Access (WiMAX) technology has emerged out as one among the popular technologies in this era of wireless technology. WiMAX network faces higher call dropping or call blocking issues during handover process as the user moves from one base station to another. Call admission control (CAC) is a technique to satisfy the greater demand for the limited availability of the resources in the network. To satisfy the QoS needs of the handoff connection, the CAC scheme is used so that the available bandwidth required for connection is considered in advance. To reduce the call dropping issue and to enable smoother handover process, a Mobility Based Improved Call Admission Control Scheme for Mobile WiMAX Networks is proposed in this work. In this scheme, a part of the total bandwidth is allocated for handover processs. During new call arrival, if the allocated bandwidth for handover becomes insufficient for handover process, then the dynamic adjustment of the handover bandwidth is performed based on fuzzy logic controller (FLC). The call dropping rate, requested bandwidth and available bandwidth are considered as the input variables for FLC. Based on the outcome of the fuzzy rules, the adjusted bandwidth of handover is returned as the output variable. Simulation results show that the proposed scheme achieves the requested bandwidth and fairness along with reduced call dropping rate.
An Efficient Localization For Smart Defense Node Connection Based Node Position Tracking And Identification In Wireless Sensor Network
A.V. Kalpana, Dr. S. Rukmani Devi, N.Indira
Wireless sensor networks have an entry point which is called a gateway or router; the router is the only way to reach the other nodes present in the system. The router handles the packet incoming and outgoing, and each packet is approaching the router will be stored in the input buffer and will be scheduled at the output buffer. The abilities of individual nodes are extremely restricted, and nodes are frequently serviced by batteries as it were. To save energy, the relationship between nodes is required. To accomplish this objective for nodes in WSNs, it ends up essential to decide the location of individual sensor nodes without depending on outer frameworks. Thus first, the positioning algorithm must be distributed and localized to balance well for large sensor networks. The point of the examination is to grow new and better localization calculation for sensor networks. It additionally intends to research the execution of recently created localization calculation. This has been expert in creating Smart node Defense Connection based Localization (SNDCL) Algorithm. The localization algorithm estimates the energy effective moreover. In this algorithm, once the unknown node is limited it winds up accessible for position estimation of staying hidden nodes, which is known as the improvised node. To find the position of an object or a device, the necessary step is to use reference points or the anchors whose location is known. The purpose determines the distance, angle, or both, between itself and the reference point. Finally, our proposed method gives better result compare to all another current way.
Cross-Layer Analysis Of Dmmpp Queuing With Adaptive Modulation And Coding
A.Manikandan, K.Balasubadra , K.G.Shanthi
In wireless systems, the buffer in the data link layer is not occupied always because of the data traffic. The queue state of the data link layer is unique as indicated by the characteristics of data traffic. The research conducted so far is derived based on the Finite State Markov Chain (FSMC) model that needs more fitting parameters for large complex channels. Furthermore the Adaptive Modulation and Coding (AMC) works well when there is no over flow at the buffer. In case of overflow,AMC has to be designed along with a queuing process to reduce the Packet Dropping Probability (PDP), Packet Error Rate(PER), and to achieve the required throughput. In this paper, a joint frame work of queuing with AMC has been proposed using the dynamic Markov Modulated Poisson Process (dMMPP) model for Quality of Service guaranteed traffic. The performance of proposed queuing model is simulated under the 3G simulation environment comprising Qualnet and MATLAB. Average delay, packet error rate, packet dropping probability and throughput were the metrics used to validate the performance of the dMMPP model. The average delay of packets is reduced by more than 40% in dMMPP when compared with Markov Modulated Poisson Process (MMPP) and Circulant MMPP (CMMPP) without AMC. The minimum packet dropping probability of dMMPP queuing process is around10-8 whereas in MMPP queuing process it is around10-5 with AMC. Furthermore the average delay of the dMMPP queuing process is 20% - 25% less and also yields a better throughput with a difference of more than 0.2 packets/slot, in comparison with MMPP queuing process. The proposed work can also be extended with MIMO Systems with critical traffic issues in future.
Assessment Of Particle Swarm Optimization Based Quasi Z-Source Inverter Fed Induction Motor Drive
Particle swarm optimization controlled Quasi Z-Source inverter for speed control of induction motor drive is proposed in this paper. The objective of utilizing Particle swarm optimization in this article is to control inverter output frequency in order to maintain speed under various loads. The Quasi Z-Source inverter is an inverter that provides buck/boost output along with DC-AC conversion in a single stage. This topology has numerous advantages which make it reliable and suitable for renewable energy or battery applications. Induction motor drives are widely used industries for its benefits compared to synchronous motors and DC motors in numerous aspects, like size, efficiency, cost, life span and maintainability. ANN is a machine learning algorithm that provides an adaptive learning ability to the controllers to better characterize the system dynamics for achieving accurate and fast responses. In this paper performance of ANN based QZSI fed induction motor control is compared with the performance of proposed evolutionary computational PSO based system. The entire system is analyzed using Matlab.
Layered Software Architecture for Heterogeneous Distributed Control System Using Hybrid Communication Channel
Pramod U, Chavan, Ramadevi R, Murugan M, Sheela Rani B
This paper addresses the pivotal issues of the software architecture like platform independent, hardware modularity, scalability, code maintainability, testability, etc. for Distributed Control Systems (DCS). To resolve these issues, it aims to develop the Layered Software Architecture (LSA) for the Heterogeneous Distributed Control System (HDCS). The system consists of a master and the multiple slave units equipped with the master software and hardware modules i.e. sensors and actuators respectively. The master and/ or slave units access the individual module services through the Hybrid Communication Channel (HCC) for information processing, monitoring and control. The performance of LSA is evaluated in terms of average round trip time at the standard baud rate of 9600 using Histogram and Probability Distributions. From the analysis, it reveals that the normal distribution is best suited amongst Beta, Normal and Gamma distributions. It validates the LSA for distributed monitoring and control in the modern HDCS. Therefore, the specified architecture facilitates the reconfiguration of the software and the hardware components and suggests the modularity in the design to find the similar attributes to reduce design time, cost and less susceptibility to errors.
ELAS: An Extended Lightweight Authentication Scheme for Secure M2M Communications
B. Satyanarayana Murthy, Dr. L. Sumalatha
In the recent advancements in the industrial applications, machine-to-machine (M2M) verbal exchange generation is taken into consideration as a key underlying era, in which Machine Type Communication Devices (MTCDs) are adopted to switch over statistics with each different in an independent manner with no person interference. Conversely, maximum of the prevailing M2M protocols are also used in business field offer protection strategies depends on traditional asymmetric ciphering consequential in excessive calculation overhead. As a result, the inhibited nodes aren't intelligent to help them properly therefore, numerous safety issues get up for the M2M background. Consequently, lightweight safety approaches are necessary for M2M transportation with a purpose to offer safety. As a modern step, in this paper, we advocate an extended light-weight authentication mechanism, based handiest on easy signature schemes and certificates, for light weight communications in business environment. The projected scheme is comprised by way of low processing cost, transmission, and storage space overhead, even as attaining communal verification among the nodes in a M2M communication, i.e, the scheme offers a way of mutual authentication between any two nodes in a network.
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