Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00128
Yihuai Yang, Sunyan Hong
In-body channel models of WBAN s are gaining great interesting as they innovation application in heal-care services, military and amusement areas. In the paper, we present a study base on experimental investigation and simulation results. A seven-state semi-Markov model, which including the line-of-sight state, the shadowed state and the blocked state, is proposed. The model parameters are derived from data of measurements. Simulation results of the proposed model match well with the statistical analysis of the measured data, which provide the effectiveness and reliability of the semi-Markov channel model.
{"title":"Channel Characteristics Modeling Based on Measurement","authors":"Yihuai Yang, Sunyan Hong","doi":"10.1109/ICAA53760.2021.00128","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00128","url":null,"abstract":"In-body channel models of WBAN s are gaining great interesting as they innovation application in heal-care services, military and amusement areas. In the paper, we present a study base on experimental investigation and simulation results. A seven-state semi-Markov model, which including the line-of-sight state, the shadowed state and the blocked state, is proposed. The model parameters are derived from data of measurements. Simulation results of the proposed model match well with the statistical analysis of the measured data, which provide the effectiveness and reliability of the semi-Markov channel model.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"2674 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131234806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00057
Ruhua Lu, Yalan Li, Yanwen Yan, Weiqiao Yao
Convolution neural networks include convolution computation and feedforward neural networks with depth structure. It is one of the most successful application fields of deep learning algorithm that can learn a lot of mapping relationship between input and output without any precise mathematical expression between input and output. The basic structure of convolutional neural network is input layer, convolution layer, pooling layer, full connection layer and output layer. Some improvements are proposed in this paper. First, a convolution layer and a pool layer are added to the original basic structure. Second, the new structure adopts hybrid pool in the pool stage. Thirdly, the maxout activation function is used in the full connection layer. Finally, based on the data set cifar-10, this paper studies the training and testing of convolutional neural networks for 10 categories of aircraft, horse, bird, ship, deer, dog, frog, automobile, cat and truck. The experimental results show that the accuracy rate of testing is 69.48%. Obviously the testing result is satisfactory.
{"title":"The Object Recognition Research Based on Convolution Neural Network","authors":"Ruhua Lu, Yalan Li, Yanwen Yan, Weiqiao Yao","doi":"10.1109/ICAA53760.2021.00057","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00057","url":null,"abstract":"Convolution neural networks include convolution computation and feedforward neural networks with depth structure. It is one of the most successful application fields of deep learning algorithm that can learn a lot of mapping relationship between input and output without any precise mathematical expression between input and output. The basic structure of convolutional neural network is input layer, convolution layer, pooling layer, full connection layer and output layer. Some improvements are proposed in this paper. First, a convolution layer and a pool layer are added to the original basic structure. Second, the new structure adopts hybrid pool in the pool stage. Thirdly, the maxout activation function is used in the full connection layer. Finally, based on the data set cifar-10, this paper studies the training and testing of convolutional neural networks for 10 categories of aircraft, horse, bird, ship, deer, dog, frog, automobile, cat and truck. The experimental results show that the accuracy rate of testing is 69.48%. Obviously the testing result is satisfactory.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130840151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00078
Qingwu Fan, Guanghuang Chen, Shuo Li
The heat exchange station is an essential part of the central heating system. In the actual heating system operation control, the short-term heating load prediction of the heat exchange station based on historical operation data plays an important role. In this paper, firstly, based on the Long Short-Term Memory (LSTM) neural network, a short-term heating load prediction model of heat exchange station is established. Secondly, because of the difficulty of adjusting parameters of the traditional LSTM neural network, a Dynamic Auxiliary Individual Genetic Algorithm (DAIGA) was proposed. Then, the primary hyperparameters of the prediction model were optimized by the proposed genetic algorithm to make the prediction performance of the model more accurate and stable. Finally, through comparison experiments with a variety of typical heating load prediction models, the proposed DAIGA-LSTM prediction model has strong applicability and good prediction performance.
{"title":"Short-term Heating Load Prediction of Heat Exchange Station Based on DAIGA-LSTM Neural Network","authors":"Qingwu Fan, Guanghuang Chen, Shuo Li","doi":"10.1109/ICAA53760.2021.00078","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00078","url":null,"abstract":"The heat exchange station is an essential part of the central heating system. In the actual heating system operation control, the short-term heating load prediction of the heat exchange station based on historical operation data plays an important role. In this paper, firstly, based on the Long Short-Term Memory (LSTM) neural network, a short-term heating load prediction model of heat exchange station is established. Secondly, because of the difficulty of adjusting parameters of the traditional LSTM neural network, a Dynamic Auxiliary Individual Genetic Algorithm (DAIGA) was proposed. Then, the primary hyperparameters of the prediction model were optimized by the proposed genetic algorithm to make the prediction performance of the model more accurate and stable. Finally, through comparison experiments with a variety of typical heating load prediction models, the proposed DAIGA-LSTM prediction model has strong applicability and good prediction performance.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130930036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, social-based recommendation uses social information to alleviate the problems of cold start and data sparseness in traditional recommendation, which is widely used in e-commerce and movie recommendation. However, most of the existing researches make recommendations based on users' short-term preferences or historical records, and fail to fully dig out the user's preference characteristics. This paper proposes a user long-term and short-term preference model based on graph neural network, which uses the nodes of the user's social graph and the user's product graph to aggregate neighbor information, and iteratively updates the feature representation of the target node. The gated recurrent units is used to extract the long-term and short-term preferences of users, and the attention mechanism is used for weight distribution. In addition, we use specific vectors to represent the long-term characteristics of slow changes in users. By conducting experiments on two commonly used data sets, it can be shown that our proposed model is better than the compared baseline method.
{"title":"Multi-preference Social Recommendation of Users Based on Graph Neural Network","authors":"Yongjie Niu, Xing Xing, Mindong Xin, Qiuyang Han, Zhichun Jia","doi":"10.1109/ICAA53760.2021.00040","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00040","url":null,"abstract":"In recent years, social-based recommendation uses social information to alleviate the problems of cold start and data sparseness in traditional recommendation, which is widely used in e-commerce and movie recommendation. However, most of the existing researches make recommendations based on users' short-term preferences or historical records, and fail to fully dig out the user's preference characteristics. This paper proposes a user long-term and short-term preference model based on graph neural network, which uses the nodes of the user's social graph and the user's product graph to aggregate neighbor information, and iteratively updates the feature representation of the target node. The gated recurrent units is used to extract the long-term and short-term preferences of users, and the attention mechanism is used for weight distribution. In addition, we use specific vectors to represent the long-term characteristics of slow changes in users. By conducting experiments on two commonly used data sets, it can be shown that our proposed model is better than the compared baseline method.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132275257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00046
Xi Ganga
In order to further the application,research and development of artificial intelligence (AI), The Office of Science and Technology Policy of the White House released two reports commissioned “Preparation for the Future of Artificial Intelligence“ and “The National Artificial Intelligence Research and Development Strategic Plan” in October 2016. According to the reports, AI has been playing a growing role in every area of society, among which education is an important one. Educational artistic intelligence (EAI) is a new field which combinations AI with learning science. Current, the key technologies of EAI are knowledge representation, machine learning, deep learning, natural language processing, intelligent agent, affective computing, etc. The development of EAI in education focuses on the intelligent tutor and assistant, intelligent evaluation, learning partner, data mining, learning analysis, etc.On this account, there is a urgent need to strengthen the training of the workforce of EAI at all levels, in accordance with the rapid development of AI.
{"title":"Educational Artificial Intelligence (EAI) Connotation, Key Technology and Application Trend -Interpretation and analysis of the two reports entitled “Preparing for the Future of Artificial Intelligence” and “The National Artificial Intelligence Research and Development Strategic Plan”","authors":"Xi Ganga","doi":"10.1109/ICAA53760.2021.00046","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00046","url":null,"abstract":"In order to further the application,research and development of artificial intelligence (AI), The Office of Science and Technology Policy of the White House released two reports commissioned “Preparation for the Future of Artificial Intelligence“ and “The National Artificial Intelligence Research and Development Strategic Plan” in October 2016. According to the reports, AI has been playing a growing role in every area of society, among which education is an important one. Educational artistic intelligence (EAI) is a new field which combinations AI with learning science. Current, the key technologies of EAI are knowledge representation, machine learning, deep learning, natural language processing, intelligent agent, affective computing, etc. The development of EAI in education focuses on the intelligent tutor and assistant, intelligent evaluation, learning partner, data mining, learning analysis, etc.On this account, there is a urgent need to strengthen the training of the workforce of EAI at all levels, in accordance with the rapid development of AI.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133146134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00052
Jing Cheng, W. Wang
Due to the rapid growth of mobile applications, the requirements for software testing speed are getting higher and higher. Therefore, automated testing is gradually replacing inefficient manual testing methods. However, most of the existing mobile applications are not open source code, and testing open source mobile applications is time-consuming and inefficient. Therefore, we propose automated robot testing based on black box testing. Firstly, YOLOV3 algorithm is used to obtain the information of mobile application interface components. Then, the perceptual hashing algorithm is used to identify the isomorphic GUI of mobile application, and the nodes that are the isomorphic GUI after the jump are merged to improve the test efficiency by simplifying the model. The experimental results show that the method can identify the isomorphic GUI quickly and accurately, and can better simplify the interface model and improve the test efficiency.
{"title":"Mobile Application GUI Similarity Comparison Based on Perceptual Hash for Automated Robot Testing","authors":"Jing Cheng, W. Wang","doi":"10.1109/ICAA53760.2021.00052","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00052","url":null,"abstract":"Due to the rapid growth of mobile applications, the requirements for software testing speed are getting higher and higher. Therefore, automated testing is gradually replacing inefficient manual testing methods. However, most of the existing mobile applications are not open source code, and testing open source mobile applications is time-consuming and inefficient. Therefore, we propose automated robot testing based on black box testing. Firstly, YOLOV3 algorithm is used to obtain the information of mobile application interface components. Then, the perceptual hashing algorithm is used to identify the isomorphic GUI of mobile application, and the nodes that are the isomorphic GUI after the jump are merged to improve the test efficiency by simplifying the model. The experimental results show that the method can identify the isomorphic GUI quickly and accurately, and can better simplify the interface model and improve the test efficiency.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114081856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00109
Hongli Zhao, Li Zhu
In existing Communication Based Train Control (CBTC) system, there are many information security threats especially in train-ground communication, so information security protection methods of CBTC system are designed. For reasons of increasing information security, blockchain technology is used to train-ground communication of CBTC system. Based on blockchain technology, CBTC system information security testing environment is set up. Testing results demonstrate that the train-ground communication information security of CBTC system based on blockchain overcomes the single-point failure of centralization key management, and doesn't influence the real time of CBTC system.
{"title":"Blockchain Based Train-ground Communication of CBTC System","authors":"Hongli Zhao, Li Zhu","doi":"10.1109/ICAA53760.2021.00109","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00109","url":null,"abstract":"In existing Communication Based Train Control (CBTC) system, there are many information security threats especially in train-ground communication, so information security protection methods of CBTC system are designed. For reasons of increasing information security, blockchain technology is used to train-ground communication of CBTC system. Based on blockchain technology, CBTC system information security testing environment is set up. Testing results demonstrate that the train-ground communication information security of CBTC system based on blockchain overcomes the single-point failure of centralization key management, and doesn't influence the real time of CBTC system.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114459271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00114
Jinjian Yang, Haoqi Yu, Jiangshen Pan
Blockchain, as a technology and tool for strengthening social trust and improving social relations, has the application prospect of changing the world. The application of blockchain in the field of accounting has also started, and it will bring great changes to the business of accounting and accountancy supervision. Small and medium-sized enterprises (hereinafter referred to as “SME”), as the pillar of social economy, should build decentralized, trusted, automated and modular financial systems based on blockchain technology which are according to their specific and actual needs.
{"title":"Research on Optimization of Financial System of SMEs Based on Blockchain Technology","authors":"Jinjian Yang, Haoqi Yu, Jiangshen Pan","doi":"10.1109/ICAA53760.2021.00114","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00114","url":null,"abstract":"Blockchain, as a technology and tool for strengthening social trust and improving social relations, has the application prospect of changing the world. The application of blockchain in the field of accounting has also started, and it will bring great changes to the business of accounting and accountancy supervision. Small and medium-sized enterprises (hereinafter referred to as “SME”), as the pillar of social economy, should build decentralized, trusted, automated and modular financial systems based on blockchain technology which are according to their specific and actual needs.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":" 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131977075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/icaa53760.2021.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/icaa53760.2021.00003","DOIUrl":"https://doi.org/10.1109/icaa53760.2021.00003","url":null,"abstract":"","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132262884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00156
Duo Wang
Applying the catastrophe theory to the performance evaluation of the seeker, constructing an evaluation system from two aspects: basic performance and anti-interference performance, according to the catastrophe model and normalization formula, obtain the seeker performance evaluation value. Take infrared seeker for example, result shows that: the performance evaluation system considers the influence of multiple index factors, the calculation is simple, efficient and easy to implement. Provides certain value for performance evaluation of seeker.
{"title":"Research on the Application of Catastrophe Theory in Seeker Performance Evaluation","authors":"Duo Wang","doi":"10.1109/ICAA53760.2021.00156","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00156","url":null,"abstract":"Applying the catastrophe theory to the performance evaluation of the seeker, constructing an evaluation system from two aspects: basic performance and anti-interference performance, according to the catastrophe model and normalization formula, obtain the seeker performance evaluation value. Take infrared seeker for example, result shows that: the performance evaluation system considers the influence of multiple index factors, the calculation is simple, efficient and easy to implement. Provides certain value for performance evaluation of seeker.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134240910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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