Hotspot topic trends can be captured by analyzing user attributes and historical behavior in social network. In this paper,we propose a user participation behavior prediction model for social hotspots,based on user be...Hotspot topic trends can be captured by analyzing user attributes and historical behavior in social network. In this paper,we propose a user participation behavior prediction model for social hotspots,based on user behavior and relationship data,to predict user participation behavior and topic development trends. Firstly,for the complex factors of user behavior,three dynamic influence factor functions are defined,including individual,peer and community influence. These functions take timeliness into account using a time discretization method. Secondly,to determine laws of individual behavior and group behavior within a social topic,a hotspot user participation behavior prediction model is proposed and associated with the basic concepts of random field and Markov property in information diffusion. The experimental results show that the model can not only dynamically predict the individual behavior,but also grasp the development trends of topics.展开更多
The problem of profile matching in electronic social networks asks to find those offering profiles of actors in the network fitting best to a given search profile. In this article this problem is mathematically formul...The problem of profile matching in electronic social networks asks to find those offering profiles of actors in the network fitting best to a given search profile. In this article this problem is mathematically formulated as an optimization problem. For this purpose the underlying search space and the objective function are defined precisely. In particular, data structures of search and offering profiles are proposed, as well as a function measuring the matching of the attributes of a search profile with the corresponding attributes of an offering profile. This objective function, given in Equation (29), is composed of the partial matching degrees for numerical attributes, discrete non-numerical attributes, and fields of interests, respectively. For the matching degree of numerical profile attributes a fuzzy value approach is presented, see Equation (22), whereas for the matching degree of fields of interest a new measure function is introduced in Equation (26). The resulting algorithm is illustrated by a concrete example. It not only is applicable to electronic social networks but also could be adapted for resource discovery in grid computation or in matchmaking energy demand and supply in electrical power systems and smart grids, especially to efficiently integrate renewable energy resources.展开更多
This paper presents the speed control of a separately excited DC motor using Neural Network (NN) controller in field weakening region. In armature control, speed controller has been used in outer loop while current co...This paper presents the speed control of a separately excited DC motor using Neural Network (NN) controller in field weakening region. In armature control, speed controller has been used in outer loop while current controller in inner loop is used. The function of NN is to predict the field current that realizes the field weakening to drive the motor over rated speed. The parameters of NN are optimized by the Social Spider Optimization (SSO) algorithm. The system has been implemented using MATLAB/SIMULINK software. The simulation results show that the proposed method gives a good performance and is feasible to be applied instead of others conventional combined control methods.展开更多
Purpose： This paper focuses on the impact of social capital on urban children＇s use behavior of information communication technology （ICT）.Design/methodology/approach： Using the field survey and in-depth intervie...Purpose： This paper focuses on the impact of social capital on urban children＇s use behavior of information communication technology （ICT）.Design/methodology/approach： Using the field survey and in-depth interviews, we interviewed 40 children aged 6 to 12 and their parents from a staff residential quarter of the Zhengzhou University--＂Shengheyuan＂ community （SHY）, and a commercial residential quarter--＂Wanfenghuicheng＂ community （WFHC） in the high-tech zone of Zhengzhou City, Henan Province. We used the social capital theory to analyze the interviewees＇ record.Findings： In urban communities, social capital is the most important factor for children （aged 6 to 12） in their ICT use. Our findings indicate that children in families with higher levels of social capital, such as internal resources, family income, parent educational backgrounds and parents＇ social network, have more-highly developed ICT skills. Personal motivation and obstacles, such as lack of access to computers on a regular basis, also have an impact on children＇s ICT use. External social capital, including schools, libraries, and public service institutes, have little impact on children＇s ICT use, if not combined with internal social capital factors.Research limitations： Our research samples were collected from two communities within the same city, which may influence the generalization of this research result.Originality/value： To explore the social capital＇s influence on children＇s ICT use, we used field observation for ICT use of children aged 6 to 12 in urban communities in China, and studied the children＇s ICT behavior from the perspective of internal and external social capital.展开更多
基金supported by the National Key Basic Research Program(973 program)of China(No.2013CB329606)National Science Foundation of China(Grant No.61272400)+2 种基金Science and Technology Research Program of the Chongqing Municipal Education Committee(No.KJ1500425)Wen Feng Foundation of CQUPT(No.WF201403)Chongqing Graduate Research And Innovation Project(No.CYS14146)
文摘Hotspot topic trends can be captured by analyzing user attributes and historical behavior in social network. In this paper,we propose a user participation behavior prediction model for social hotspots,based on user behavior and relationship data,to predict user participation behavior and topic development trends. Firstly,for the complex factors of user behavior,three dynamic influence factor functions are defined,including individual,peer and community influence. These functions take timeliness into account using a time discretization method. Secondly,to determine laws of individual behavior and group behavior within a social topic,a hotspot user participation behavior prediction model is proposed and associated with the basic concepts of random field and Markov property in information diffusion. The experimental results show that the model can not only dynamically predict the individual behavior,but also grasp the development trends of topics.
文摘The problem of profile matching in electronic social networks asks to find those offering profiles of actors in the network fitting best to a given search profile. In this article this problem is mathematically formulated as an optimization problem. For this purpose the underlying search space and the objective function are defined precisely. In particular, data structures of search and offering profiles are proposed, as well as a function measuring the matching of the attributes of a search profile with the corresponding attributes of an offering profile. This objective function, given in Equation (29), is composed of the partial matching degrees for numerical attributes, discrete non-numerical attributes, and fields of interests, respectively. For the matching degree of numerical profile attributes a fuzzy value approach is presented, see Equation (22), whereas for the matching degree of fields of interest a new measure function is introduced in Equation (26). The resulting algorithm is illustrated by a concrete example. It not only is applicable to electronic social networks but also could be adapted for resource discovery in grid computation or in matchmaking energy demand and supply in electrical power systems and smart grids, especially to efficiently integrate renewable energy resources.
文摘This paper presents the speed control of a separately excited DC motor using Neural Network (NN) controller in field weakening region. In armature control, speed controller has been used in outer loop while current controller in inner loop is used. The function of NN is to predict the field current that realizes the field weakening to drive the motor over rated speed. The parameters of NN are optimized by the Social Spider Optimization (SSO) algorithm. The system has been implemented using MATLAB/SIMULINK software. The simulation results show that the proposed method gives a good performance and is feasible to be applied instead of others conventional combined control methods.
文摘Purpose： This paper focuses on the impact of social capital on urban children＇s use behavior of information communication technology （ICT）.Design/methodology/approach： Using the field survey and in-depth interviews, we interviewed 40 children aged 6 to 12 and their parents from a staff residential quarter of the Zhengzhou University--＂Shengheyuan＂ community （SHY）, and a commercial residential quarter--＂Wanfenghuicheng＂ community （WFHC） in the high-tech zone of Zhengzhou City, Henan Province. We used the social capital theory to analyze the interviewees＇ record.Findings： In urban communities, social capital is the most important factor for children （aged 6 to 12） in their ICT use. Our findings indicate that children in families with higher levels of social capital, such as internal resources, family income, parent educational backgrounds and parents＇ social network, have more-highly developed ICT skills. Personal motivation and obstacles, such as lack of access to computers on a regular basis, also have an impact on children＇s ICT use. External social capital, including schools, libraries, and public service institutes, have little impact on children＇s ICT use, if not combined with internal social capital factors.Research limitations： Our research samples were collected from two communities within the same city, which may influence the generalization of this research result.Originality/value： To explore the social capital＇s influence on children＇s ICT use, we used field observation for ICT use of children aged 6 to 12 in urban communities in China, and studied the children＇s ICT behavior from the perspective of internal and external social capital.
