The community discovery technology is proposed based on the double-weight Gaussian kernel similarity to meet the need of intellectual precise delivery business of broadcast television. The text proposes a community technique based on the double-weight Gaussian kernel similarity, according to the user rating data and program broadcast data. It takes user preferences of program category as nodes and the similarity of difierent nodes as edges to build the diagram of TV broadcast community. In order to realize the segmentation of TV users, it adopts the spectral clustering algorithm and transfer the diagram into the matrix of user preferences of program category. In addition, it proposes Gaussian kernel similarity algorithm based on double-weight. For the multivariate data, such as Wine data and Heart data, its veracity can be enhanced by 2% according to the similarity based on the attribute character and the spatial character of the data. Checking the community discovery technique based on double-weight Gaussian kernel similarity, the result shows that it can flnd out user communities of difierent preferences of program category, converge to the global optimal situation and simplify the computational complexity.
{"title":"The Research of Broadcast Television Community Discovery Technology Based on Double-weight Gaussian Kernel Similarity ?","authors":"Wang Xin, Fulian Yin, Jianping Chai, Xinran Wang","doi":"10.12733/JICS20105669","DOIUrl":"https://doi.org/10.12733/JICS20105669","url":null,"abstract":"The community discovery technology is proposed based on the double-weight Gaussian kernel similarity to meet the need of intellectual precise delivery business of broadcast television. The text proposes a community technique based on the double-weight Gaussian kernel similarity, according to the user rating data and program broadcast data. It takes user preferences of program category as nodes and the similarity of difierent nodes as edges to build the diagram of TV broadcast community. In order to realize the segmentation of TV users, it adopts the spectral clustering algorithm and transfer the diagram into the matrix of user preferences of program category. In addition, it proposes Gaussian kernel similarity algorithm based on double-weight. For the multivariate data, such as Wine data and Heart data, its veracity can be enhanced by 2% according to the similarity based on the attribute character and the spatial character of the data. Checking the community discovery technique based on double-weight Gaussian kernel similarity, the result shows that it can flnd out user communities of difierent preferences of program category, converge to the global optimal situation and simplify the computational complexity.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124883512","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}
Qingyong Xu, Shunliang Jiang, Wei Huang, Famao Ye, Shaoping Xu
In the last decades, Content Based Image Retrieval and image classification have become popular, and among them Region-based Image Retrieval is quite active. More and more descriptors and retrieval methods have been proposed and investigated in order to improve the retrieval performance. This paper proposed a feature fusion deep learning method. The features including colors, texture and shape, which are extracted from both the entire image and regions. The features are then trained using diverse deep learning methods. The conducted deep learning methods include Sparse Auto-encoders, Denoising Autoencoding, Deep Belief Nets, Drop Out Neural Networks, and Deep Boltzmann Machine. The method is evaluated through extensive experiments on Corel 10K datasets. Experimental results demonstrate that the introduced methods are comparable with the state-of-arts in this image retrieval application.
{"title":"Feature Fusion Based Image Retrieval Using Deep Learning","authors":"Qingyong Xu, Shunliang Jiang, Wei Huang, Famao Ye, Shaoping Xu","doi":"10.12733/JICS20105681","DOIUrl":"https://doi.org/10.12733/JICS20105681","url":null,"abstract":"In the last decades, Content Based Image Retrieval and image classification have become popular, and among them Region-based Image Retrieval is quite active. More and more descriptors and retrieval methods have been proposed and investigated in order to improve the retrieval performance. This paper proposed a feature fusion deep learning method. The features including colors, texture and shape, which are extracted from both the entire image and regions. The features are then trained using diverse deep learning methods. The conducted deep learning methods include Sparse Auto-encoders, Denoising Autoencoding, Deep Belief Nets, Drop Out Neural Networks, and Deep Boltzmann Machine. The method is evaluated through extensive experiments on Corel 10K datasets. Experimental results demonstrate that the introduced methods are comparable with the state-of-arts in this image retrieval application.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130424745","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}
Recommendation system, as an information filtering method, has been widely applied and the hybrid recommendation algorithm is by far the most commonly used technique. But in the field of online learning system, recommendation system is not mature enough. In this paper, we analyzed the Tianjin University Online Judge, established a model to apply the recommendation algorithm to it, and then proposed a label-based hybrid recommendation algorithm which is applicable to the system. Also, by conducting experiments on real users’ data of Tianjin University Online Judge System, we evaluated our algorithm and obtained good results.
{"title":"Lable-based Hybrid Recommendation Algorithm: Implementation and Analysis","authors":"Ruiguo Yu, Hongyue Mao, Zan Wang, Minjie Zhang, Zhenxia Yuan, MuWen He, Peng Chang","doi":"10.12733/JICS20105696","DOIUrl":"https://doi.org/10.12733/JICS20105696","url":null,"abstract":"Recommendation system, as an information filtering method, has been widely applied and the hybrid recommendation algorithm is by far the most commonly used technique. But in the field of online learning system, recommendation system is not mature enough. In this paper, we analyzed the Tianjin University Online Judge, established a model to apply the recommendation algorithm to it, and then proposed a label-based hybrid recommendation algorithm which is applicable to the system. Also, by conducting experiments on real users’ data of Tianjin University Online Judge System, we evaluated our algorithm and obtained good results.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130858556","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}
Micro-expression cognition is a vital useful input to develop affective computing strategies in modern human-computer/robot interaction. In this paper, an effective system for micro-expression cognition and emotional regulation is described. As input, a micro-expressional face is represented as a point in a 3D space characterized by arousal, valence and stance factors. The capture and recognition method of micro-expressions is based on a novel combination of 3D-Gradient projection descriptor, multi-scale and multi-direction Gabor filter bank and the gradient magnitude weighted Nearest Neighbor Algorithm (NNA) in facial feature regions. The main distinguishing feature of our work is that the emotional regulation model does not simply provide the classification and jump in terms of a set of discrete emotional labels, but that it operates in a continuous 3D emotional space enabling a wide range of intermediary emotional states to be obtained. The micro-expression recognition method has been tested with the Yale University’s facial database and universal participants’ facial database so that it is capable of analyzing any adult subject, male or female in the typical database and interactive process. Then the cognition and emotion system has been applied to the human-robot interaction, and the results are very encouraging and show that our micro-expression cognition and emotion model is generally consistent with human brain emotional regulation mechanisms.
{"title":"Micro-expression Cognition and Emotion Modeling Based on Gross Reappraisal Strategy","authors":"Lun Xie, Xin Liu, Zhiliang Wang","doi":"10.12733/JICS20105593","DOIUrl":"https://doi.org/10.12733/JICS20105593","url":null,"abstract":"Micro-expression cognition is a vital useful input to develop affective computing strategies in modern human-computer/robot interaction. In this paper, an effective system for micro-expression cognition and emotional regulation is described. As input, a micro-expressional face is represented as a point in a 3D space characterized by arousal, valence and stance factors. The capture and recognition method of micro-expressions is based on a novel combination of 3D-Gradient projection descriptor, multi-scale and multi-direction Gabor filter bank and the gradient magnitude weighted Nearest Neighbor Algorithm (NNA) in facial feature regions. The main distinguishing feature of our work is that the emotional regulation model does not simply provide the classification and jump in terms of a set of discrete emotional labels, but that it operates in a continuous 3D emotional space enabling a wide range of intermediary emotional states to be obtained. The micro-expression recognition method has been tested with the Yale University’s facial database and universal participants’ facial database so that it is capable of analyzing any adult subject, male or female in the typical database and interactive process. Then the cognition and emotion system has been applied to the human-robot interaction, and the results are very encouraging and show that our micro-expression cognition and emotion model is generally consistent with human brain emotional regulation mechanisms.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"87 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113943990","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}
This paper studies the properties of rational general solutions for first order multivariate autonomous rational differential systems. We obtain a necessary and sufficient conditions for existence of rational general solution of first order multivariate autonomous rational differential system if the degree bound of rational solutions of this system is given. Due to the problem for computing a rational solution of the multivariate rational differential system can be reduced to finding a linear rational solution of an autonomous differential equation, we also prove that the linear rational solvability of the resulting autonomous differential equation does not depend on the choice of proper parametrizations of invariant algebraic space curves. In addition, two different rational solutions corresponding to the same invariant algebraic space curve are proved to be related by a shifting of the variable.
{"title":"Properties of Rational General Solutions for First Order Multivariate Autonomous Rational Differential Systems","authors":"Yanli Huang","doi":"10.12733/JICS20105672","DOIUrl":"https://doi.org/10.12733/JICS20105672","url":null,"abstract":"This paper studies the properties of rational general solutions for first order multivariate autonomous rational differential systems. We obtain a necessary and sufficient conditions for existence of rational general solution of first order multivariate autonomous rational differential system if the degree bound of rational solutions of this system is given. Due to the problem for computing a rational solution of the multivariate rational differential system can be reduced to finding a linear rational solution of an autonomous differential equation, we also prove that the linear rational solvability of the resulting autonomous differential equation does not depend on the choice of proper parametrizations of invariant algebraic space curves. In addition, two different rational solutions corresponding to the same invariant algebraic space curve are proved to be related by a shifting of the variable.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133997934","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 the Direction of Arrival approximation, Compressed Sensing algorithm will fail to identify correct atoms due to high cumulative coherence of the redundant dictionary (manifold matrix). For insufficient number of samples, especially for a single snapshot, less statistical information aggravates such adverse effects. In this paper, we utilize the observed signal to construct a weighted matrix which can reduce the cross cumulative coherence of the redundant dictionary. And then, we develop a constructive algorithm combing with the weighted matrix to estimate Direction of Arrival. The simulation results prove our algorithm can effectively reduce the signal deviation caused by high coherence of dictionary, specifically in the circumstance of closely spatial sources.
{"title":"Dictionary Optimization for DOA Approximation in a Single Snapshot","authors":"Xiaochuan Wu, Weibo Deng, Qiang Yang","doi":"10.12733/JICS20105699","DOIUrl":"https://doi.org/10.12733/JICS20105699","url":null,"abstract":"In the Direction of Arrival approximation, Compressed Sensing algorithm will fail to identify correct atoms due to high cumulative coherence of the redundant dictionary (manifold matrix). For insufficient number of samples, especially for a single snapshot, less statistical information aggravates such adverse effects. In this paper, we utilize the observed signal to construct a weighted matrix which can reduce the cross cumulative coherence of the redundant dictionary. And then, we develop a constructive algorithm combing with the weighted matrix to estimate Direction of Arrival. The simulation results prove our algorithm can effectively reduce the signal deviation caused by high coherence of dictionary, specifically in the circumstance of closely spatial sources.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117060571","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}
This paper proposed an new gateway deployment algorithm (GA GD) which based on load balancing in Wireless Mesh Networks. The algorithm in the premise of minimizing the number of gateways and maximizing the transmission success rate, to achieve the load balancing of the network. And introduced the idea of combined the clustering algorithm and the genetic algorithm, make full use of the advantages of genetic algorithm in terms of multi-objective optimization, with fewer iterations to obtain the better solution. Simulation results show that adjusting and optimizing in the limited times, the algorithm can obtained the fewer number of gateways, the maximize of the transmission success rate and achieving the load balancing for the entire network. Ultimately improved the overall performance of the Wireless Mesh Networks.
{"title":"Gateway Deployment Algorithm for Load Balance in Wireless Mesh Networks","authors":"Chunfei Zhang, Zhiyi Fang","doi":"10.12733/JICS20105697","DOIUrl":"https://doi.org/10.12733/JICS20105697","url":null,"abstract":"This paper proposed an new gateway deployment algorithm (GA GD) which based on load balancing in Wireless Mesh Networks. The algorithm in the premise of minimizing the number of gateways and maximizing the transmission success rate, to achieve the load balancing of the network. And introduced the idea of combined the clustering algorithm and the genetic algorithm, make full use of the advantages of genetic algorithm in terms of multi-objective optimization, with fewer iterations to obtain the better solution. Simulation results show that adjusting and optimizing in the limited times, the algorithm can obtained the fewer number of gateways, the maximize of the transmission success rate and achieving the load balancing for the entire network. Ultimately improved the overall performance of the Wireless Mesh Networks.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124733662","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}
Adjustment of WBAN nodes in the length of transmission power reasonably can expand life of the equipment, making it possible to monitor humans health for a long time. The article studies WBAN nodes power control based on standard IEEE 802.15.6, designing classification function as a sub-parameter through remaining power and priority data based on the IEEE 802.15.6. The node parameter is classified into different categories real time step factor corresponding to different step factor. The article proposes a WBAN power control scheme named NDC1 in information feedback. The NDC1 reduces the node energy consumption through the simulation effectively.
{"title":"A Scheme for the Power Control of WBAN Based on RSSI/LQI All-feed Information ⋆","authors":"Changbiao Xu, Zheng Zhang, Shimeng Zhang","doi":"10.12733/JICS20105689","DOIUrl":"https://doi.org/10.12733/JICS20105689","url":null,"abstract":"Adjustment of WBAN nodes in the length of transmission power reasonably can expand life of the equipment, making it possible to monitor humans health for a long time. The article studies WBAN nodes power control based on standard IEEE 802.15.6, designing classification function as a sub-parameter through remaining power and priority data based on the IEEE 802.15.6. The node parameter is classified into different categories real time step factor corresponding to different step factor. The article proposes a WBAN power control scheme named NDC1 in information feedback. The NDC1 reduces the node energy consumption through the simulation effectively.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127393059","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}
Apparently the comprehensive performance of array becomes impaired with the increasing of the relative bandwidth. In this paper, an algorithm based on Digital Up Converter (DUC) is proposed to reduce the relative bandwidth of the input broadband signal. The method works by changing the interelement spacing and sampling rate to carry the frequency spectrum of the input signal of array to higher frequency. When the carrier frequency is high enough, the broadband array signal processing will become a narrowband array signal processing, the narrowband array method can be used directly, and the computation could be reduced greatly. Simulation results and analysis confirm that the effect of reducing the relative bandwidth of the broadband signal is obvious and the proposed method is competent with any beamforming algorithm to form broadband patterns.
{"title":"A Reducing Relative Bandwidth Method Based on Digital up Converter","authors":"Ye Tian, Yuan Tian","doi":"10.12733/JICS20106152","DOIUrl":"https://doi.org/10.12733/JICS20106152","url":null,"abstract":"Apparently the comprehensive performance of array becomes impaired with the increasing of the relative bandwidth. In this paper, an algorithm based on Digital Up Converter (DUC) is proposed to reduce the relative bandwidth of the input broadband signal. The method works by changing the interelement spacing and sampling rate to carry the frequency spectrum of the input signal of array to higher frequency. When the carrier frequency is high enough, the broadband array signal processing will become a narrowband array signal processing, the narrowband array method can be used directly, and the computation could be reduced greatly. Simulation results and analysis confirm that the effect of reducing the relative bandwidth of the broadband signal is obvious and the proposed method is competent with any beamforming algorithm to form broadband patterns.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121797140","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}
The long delay and low stability are the primary characteristics of space information networks. Due to the increasing requirements for transmitting large amount data, the congestion collapse problem becomes the focus. In this paper, an optimal admission fee based congestion control algorithm is proposed to maximum the profit of the network. Instead of the feedback mode of traditional congestion control scheme, it utilizes the active selectivity of users. So as to differentiate the service demands of users, the waiting cost of a user is defined as a random variable. Then our system model is formulated based on queuing game theory, and the solved optimal admission fee decides the final congestion control scheme for different users in space information networks. The simulation results indicate the improvement of the network performance and the rational allocation of resources.
{"title":"The Optimal Admission Fee Based Congestion Control Scheme in Space Information Networks","authors":"Chao Guo, Haitao Xu, Zhiyong Yao","doi":"10.12733/JICS20106177","DOIUrl":"https://doi.org/10.12733/JICS20106177","url":null,"abstract":"The long delay and low stability are the primary characteristics of space information networks. Due to the increasing requirements for transmitting large amount data, the congestion collapse problem becomes the focus. In this paper, an optimal admission fee based congestion control algorithm is proposed to maximum the profit of the network. Instead of the feedback mode of traditional congestion control scheme, it utilizes the active selectivity of users. So as to differentiate the service demands of users, the waiting cost of a user is defined as a random variable. Then our system model is formulated based on queuing game theory, and the solved optimal admission fee decides the final congestion control scheme for different users in space information networks. The simulation results indicate the improvement of the network performance and the rational allocation of resources.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129233438","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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