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2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)最新文献

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An improved LMMSE algorithm for SC-FDMA SC-FDMA中一种改进的LMMSE算法
2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS) Pub Date : 2015-08-01 DOI: 10.1109/ICCSS.2015.7281153
Lu Yating, Kan Chunrong, Duan Haoyang, Zhao Qian
{"title":"An improved LMMSE algorithm for SC-FDMA","authors":"Lu Yating, Kan Chunrong, Duan Haoyang, Zhao Qian","doi":"10.1109/ICCSS.2015.7281153","DOIUrl":"https://doi.org/10.1109/ICCSS.2015.7281153","url":null,"abstract":"The channel estimation algorithm which has excellent performance is necessary for Single Carrier Frequency Division Multiple Access (SC-FDMA) system. The traditional Least Square (LS) algorithm and Linear Minimum Mean-Square (LMMSE) algorithm exist many problems. The problem of the LMMSE algorithm which is too complex is found to be applied effectively by researching LMMSE algorithm. The traditional LMMSE algorithm can be improved with the help of Jacobi iterative algorithm for solving linear equations. Meantime, theoretical analysis and simulation results indicate that: The improved LMMSE algorithm has more superior performance at low SNR, it not only can reduce the computational complexity, but also has more precise estimation result.","PeriodicalId":299619,"journal":{"name":"2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)","volume":"AES-9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126515730","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}
引用次数: 0
Detection method for cheating behavior in examination room based on artificial bee colony algorithm 基于人工蜂群算法的考场作弊行为检测方法
2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS) Pub Date : 2015-08-01 DOI: 10.1109/ICCSS.2015.7281161
Yongzheng Lin, Jin Zhou
{"title":"Detection method for cheating behavior in examination room based on artificial bee colony algorithm","authors":"Yongzheng Lin, Jin Zhou","doi":"10.1109/ICCSS.2015.7281161","DOIUrl":"https://doi.org/10.1109/ICCSS.2015.7281161","url":null,"abstract":"A detection method for cheating behavior in examination room based on artificial bee colony algorithm is presented. The problem of moving objects detection is transformed into the difference function of color value between foreground and background. Artificial bee colony algorithm is applied for optimizing the objective function. The background component is separated from the sequence images by value of comparing with proper threshold and the moving target track can be successfully extracted. Simulation experiments with real surveillance image show that the mothed can attain good results for finding the track of moving objects and achieve the purpose of detecting the cheating behaviors in examination room.","PeriodicalId":299619,"journal":{"name":"2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124889623","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}
引用次数: 2
Collaborative filtering recommendation combining FCM and Slope One algorithm 结合FCM和Slope One算法的协同过滤推荐
2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS) Pub Date : 2015-08-01 DOI: 10.1109/ICCSS.2015.7281159
Yan Ying, Yan Cao
{"title":"Collaborative filtering recommendation combining FCM and Slope One algorithm","authors":"Yan Ying, Yan Cao","doi":"10.1109/ICCSS.2015.7281159","DOIUrl":"https://doi.org/10.1109/ICCSS.2015.7281159","url":null,"abstract":"In view of the data sparseness problem existed in the traditional collaborative filtering recommendation algorithm, this paper proposes a hybrid collaborative filtering recommender framework integrated FCM clustering and Slope One algorithm and FSUBCF algorithm. Firstly this algorithm use the Slope One algorithm based on FCM cluster to predict item ratings that users have not rated in matrix, and then, to implement recommendation by the collaborative filtering recommendation algorithm based on user. The experimental results show that this algorithm can improved the prediction accuracy compared to the original Slope One algorithm and can adapt to the data sparser recommendation system. Compared with other traditional collaborative filtering algorithms, the recommendation accuracy also has obvious advantages.","PeriodicalId":299619,"journal":{"name":"2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122812300","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}
引用次数: 6
Time-varying universe based linguistic dynamic analysis of timing design for parallel traffic light 基于时变全域的并行交通灯时序设计语言动态分析
2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS) Pub Date : 2015-08-01 DOI: 10.1109/ICCSS.2015.7281163
H. Mo, Feiyue Wang, F. Zhu
{"title":"Time-varying universe based linguistic dynamic analysis of timing design for parallel traffic light","authors":"H. Mo, Feiyue Wang, F. Zhu","doi":"10.1109/ICCSS.2015.7281163","DOIUrl":"https://doi.org/10.1109/ICCSS.2015.7281163","url":null,"abstract":"Reasonable timing design for traffic light can induce and maintain the transportation systems in good order. How to allocate the time are the keys. In the paper, the theory of time-varying universe is used to describe the circle time, and corresponding fuzzy sets on the universe are also discussed to modeling the situation of traffic flow, then the parallel traffic management and control methods which are dynamic with the time change are presented. A simulation example are provided to analyze the linguistic dynamic evolution of timing design of traffic light when the traffic flow is change with time-varying for an intersection.","PeriodicalId":299619,"journal":{"name":"2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128761709","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}
引用次数: 0
Deep learning and its application to general image classification 深度学习及其在一般图像分类中的应用
2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS) Pub Date : 2015-08-01 DOI: 10.1109/ICCSS.2015.7281139
Po-Hsien Liu, S. Su, Ming-Chang Chen, Chih-Ching Hsiao
{"title":"Deep learning and its application to general image classification","authors":"Po-Hsien Liu, S. Su, Ming-Chang Chen, Chih-Ching Hsiao","doi":"10.1109/ICCSS.2015.7281139","DOIUrl":"https://doi.org/10.1109/ICCSS.2015.7281139","url":null,"abstract":"Deep learning has recently exhibited good performance in many applications. The convolution neural network is an often-used architecture for deep learning and has been widely used in computer vision and audio recognition, and outperformed other related handcraft designed feature in recent years. These techniques compared to other artificial intelligence algorithms and handcraft features need extremely much more time in training and testing and then were not widely used in the early days. Our study is about the impacts of different factors used in the convolution neural network. The considered factors are network depth, numbers of filters, and filter sizes. The used data set is the CIFAR dataset. According to our experiments, some suggestions about those factors are recommended in this study.","PeriodicalId":299619,"journal":{"name":"2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131177910","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}
引用次数: 16
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