Sensor localization is crucial for the configuration and applications of wireless sensor network (WSN). A novel distributed localization algorithm, MDS-DC was proposed for wireless sensor network based on multidimensi...Sensor localization is crucial for the configuration and applications of wireless sensor network (WSN). A novel distributed localization algorithm, MDS-DC was proposed for wireless sensor network based on multidimensional scaling (MDS) and the shortest path distance correction. In MDS-DC, several local positioning regions with reasonable distribution were firstly constructed by an adaptive search algorithm, which ensures the mergence between the local relative maps of the adjacent local position regions and can reduce the number of common nodes in the network. Then, based on the relationships between the estimated distances and actual distances of anchors, the distance estimation vectors of sensors around anchors were corrected in each local positioning region. During the computations of the local relative coordinates, an iterative process, which is the combination of classical MDS algorithm and SMACOF algorithm, was applied. Finally, the global relative positions or absolute positions of sensors were obtained through merging the relative maps of all local positioning regions. Simulation results show that MDS-DC has better performances in positioning precision, energy efficiency and robustness to range error, which can meet the requirements of applications for sensor localization in WSN.展开更多
Currently,psychiatry lacks a field that can be called“theoretical psychiatry”,which uses theoretical concepts and explanatory models:The main stream of research is to collect data of all kinds in the hope that the c...Currently,psychiatry lacks a field that can be called“theoretical psychiatry”,which uses theoretical concepts and explanatory models:The main stream of research is to collect data of all kinds in the hope that the computational Big Data approach will shed a bright light on the black box of mental disorders.Accordingly,the biology-based Research Domain Criteria of the National Institute of Mental Health have been established.However,as philosophical analyses of concepts and methods have shown,several epistemological gaps stand in the way of a consistent multilevel understanding of mental disorders.Also,the implicit ontological problems in the biological reduction of the psychosocial level and in the integration of so-called hard and soft disciplines are mostly left out.As a consequence,a non-reductive psychological theory of mental disorders is sought that also integrates correlating biological and sociological issues.In this context,one example of promising nonreductive psychiatric research is the option of systems/network psychopathology.The possibilities for integrating different psychological perspectives are highlighted for the field of addiction research and treatment,where pragmatic behaviorist approaches dominate over the theorybased practice of psychoanalysis.In comparing the theoretical constructs of these two approaches,the relevance of the concept of“(social)environment”as the wealth of influential sociocultural factors is discussed at levels superior to the interpersonal micro-level,namely the organizational meso-and societal macro level,which is not sufficiently considered in current biopsychiatry.On this basis of argumentation,the usefulness of grounding and framing psychiatry through the field of ecological sciences,especially human ecology,is demonstrated.Finally,to this end,an outline of an ecological model of mental health and illness is presented.展开更多
In this paper, we study the optimization of network traffic by considering the effects of node buffer ability and capacity. Two node buffer settings are considered. The node capacity is considered to be proportional t...In this paper, we study the optimization of network traffic by considering the effects of node buffer ability and capacity. Two node buffer settings are considered. The node capacity is considered to be proportional to its buffer ability. The node effects on network traffic systems are studied with the shortest path protocol and an extension of the optimal routing [Phys. Rev. E 74 046106 （2006）]. In the diagrams of flux-density relationships, it is shown that a nodes buffer ability and capacity have profound effects on the network traffic.展开更多
Scale-free topology and high clustering coexist in some real networks, and keep invariant for growing sizes of the systems. Previous models could hardly give out size-independent clustering with self- organized mechan...Scale-free topology and high clustering coexist in some real networks, and keep invariant for growing sizes of the systems. Previous models could hardly give out size-independent clustering with self- organized mechanism when succeeded in producing power-law degree distributions. Always ignored, some empirical statistic results display flat-head power-law behaviors. We modify our recent coevo- lutionary model to explain such phenomena with the inert property of nodes to retain small portion of unfavorable links in self-organized rewiring process. Flat-head power-law and size-independent clustering are induced as the new characteristics by this modification. In addition, a new scaling relation is found as the result of interplay between node state growth and adaptive variation of connections.展开更多
基金Supported by National Natural Science Foundation of China (No60702037)Research Fund for the Doctoral Program of Higher Education of China (No20070056129)Natural Science Foundation of Tianjin (No09JCYBJC00800)
文摘Sensor localization is crucial for the configuration and applications of wireless sensor network (WSN). A novel distributed localization algorithm, MDS-DC was proposed for wireless sensor network based on multidimensional scaling (MDS) and the shortest path distance correction. In MDS-DC, several local positioning regions with reasonable distribution were firstly constructed by an adaptive search algorithm, which ensures the mergence between the local relative maps of the adjacent local position regions and can reduce the number of common nodes in the network. Then, based on the relationships between the estimated distances and actual distances of anchors, the distance estimation vectors of sensors around anchors were corrected in each local positioning region. During the computations of the local relative coordinates, an iterative process, which is the combination of classical MDS algorithm and SMACOF algorithm, was applied. Finally, the global relative positions or absolute positions of sensors were obtained through merging the relative maps of all local positioning regions. Simulation results show that MDS-DC has better performances in positioning precision, energy efficiency and robustness to range error, which can meet the requirements of applications for sensor localization in WSN.
文摘Currently,psychiatry lacks a field that can be called“theoretical psychiatry”,which uses theoretical concepts and explanatory models:The main stream of research is to collect data of all kinds in the hope that the computational Big Data approach will shed a bright light on the black box of mental disorders.Accordingly,the biology-based Research Domain Criteria of the National Institute of Mental Health have been established.However,as philosophical analyses of concepts and methods have shown,several epistemological gaps stand in the way of a consistent multilevel understanding of mental disorders.Also,the implicit ontological problems in the biological reduction of the psychosocial level and in the integration of so-called hard and soft disciplines are mostly left out.As a consequence,a non-reductive psychological theory of mental disorders is sought that also integrates correlating biological and sociological issues.In this context,one example of promising nonreductive psychiatric research is the option of systems/network psychopathology.The possibilities for integrating different psychological perspectives are highlighted for the field of addiction research and treatment,where pragmatic behaviorist approaches dominate over the theorybased practice of psychoanalysis.In comparing the theoretical constructs of these two approaches,the relevance of the concept of“(social)environment”as the wealth of influential sociocultural factors is discussed at levels superior to the interpersonal micro-level,namely the organizational meso-and societal macro level,which is not sufficiently considered in current biopsychiatry.On this basis of argumentation,the usefulness of grounding and framing psychiatry through the field of ecological sciences,especially human ecology,is demonstrated.Finally,to this end,an outline of an ecological model of mental health and illness is presented.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 71171185, 71001001, and 71071044)the Doctoral Program of the Ministry of Education, China (Grant No. 20110111120023)PhD Program Foundation of Hefei University of Technology, China (Grant No. 2011HGBZ1302)
文摘In this paper, we study the optimization of network traffic by considering the effects of node buffer ability and capacity. Two node buffer settings are considered. The node capacity is considered to be proportional to its buffer ability. The node effects on network traffic systems are studied with the shortest path protocol and an extension of the optimal routing [Phys. Rev. E 74 046106 （2006）]. In the diagrams of flux-density relationships, it is shown that a nodes buffer ability and capacity have profound effects on the network traffic.
基金Acknowledgements We acknowledge the financial suppor~ from the National Basic Science Program of China Project No. 2006CB705500 and the National Natural Science Foundation of China under the grant Nos. 70471084, 10775071, 10635040, and 60676056. C. P. Zhu thanks the hospitable accommodation of Bao- Wen Li at NUS and Visitors Program of MPIPKS in Dresden, Germany.
文摘Scale-free topology and high clustering coexist in some real networks, and keep invariant for growing sizes of the systems. Previous models could hardly give out size-independent clustering with self- organized mechanism when succeeded in producing power-law degree distributions. Always ignored, some empirical statistic results display flat-head power-law behaviors. We modify our recent coevo- lutionary model to explain such phenomena with the inert property of nodes to retain small portion of unfavorable links in self-organized rewiring process. Flat-head power-law and size-independent clustering are induced as the new characteristics by this modification. In addition, a new scaling relation is found as the result of interplay between node state growth and adaptive variation of connections.
