Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision p...Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision payoff functions hinge on individual covariates and the choices of their friends.However,peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model.For this reason,we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks.The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios.To estimate peer pressure in the model,we first present two algorithms based on the initialize expand merge method and the polynomial-time twostage method to estimate homogeneity parameters.Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure.Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error.We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.展开更多
High quality mesh plays an important role for finite element methods in science computation and numerical simulation.Whether the mesh quality is good or not,to some extent,it determines the calculation results of the ...High quality mesh plays an important role for finite element methods in science computation and numerical simulation.Whether the mesh quality is good or not,to some extent,it determines the calculation results of the accuracy and efficiency.Different from classic Lloyd iteration algorithm which is convergent slowly,a novel accelerated scheme was presented,which consists of two core parts:mesh points replacement and local edges Delaunay swapping.By using it,almost all the equilateral triangular meshes can be generated based on centroidal Voronoi tessellation(CVT).Numerical tests show that it is significantly effective with time consuming decreasing by 40%.Compared with other two types of regular mesh generation methods,CVT mesh demonstrates that higher geometric average quality increases over 0.99.展开更多
A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal ...A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal transformation of variables with routine monitoring data and normal assumption of variables without routine monitoring data,a conditional linear Gaussian Bayesian network is constructed.A "two-constraint selection" procedure is proposed to estimate potential parameter values under small data.Among all potential parameter values,the ones that are most probable are selected as the "representatives".Finally,the risks of pollutant concentration exceeding national water quality standards are calculated and pollution reduction decisions for decision-making reference are proposed.The final results show that conditional linear Gaussian Bayesian network and "two-constraint selection" procedure are very useful in evaluating risks when there is limited data and can help managers to make sound decisions under small data.展开更多
Recent research has revealed that human exposure to air pollutants such as CO, NO_x, and particulates can lead to respiratory diseases, especially among school-age children. Towards understanding such health impacts, ...Recent research has revealed that human exposure to air pollutants such as CO, NO_x, and particulates can lead to respiratory diseases, especially among school-age children. Towards understanding such health impacts, this work estimates local-scale vehicular emissions and concentrations near a highway traffic network, where a school zone is located in. In the case study, VISSIM traffic micro-simulation is used to estimate the source of vehicular emissions at each roadway segment. The local-scale emission sources are then used as inputs to the California line source dispersion model(CALINE4) to estimate concentrations across the study area. To justify the local-scale emissions modeling approach, the simulation experiment is conducted under various traffic conditions. Different meteorological conditions are considered for emission dispersion. The work reveals that emission concentrations are usually higher at locations closer to the congested segments, freeway ramps and major arterial intersections. Compared to the macroscopic estimation(i.e. using network-average emission factors), the results show significantly different emission patterns when the local-scale emission modeling approach is used. In particular, it is found that the macroscopic approach over-estimates emission concentrations at freeways and under-estimations are observed at arterials and local streets. The results of the study can be used to compare to the US environmental protection agency(EPA) standards or any other air quality standard to further identify health risk in a fine-grained manner.展开更多
In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of...In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.展开更多
Based on the problem that the service entity only has the partial field of vision in the network environment,a trust evolvement method of the macro self-organization for Web service combination was proposed.In the met...Based on the problem that the service entity only has the partial field of vision in the network environment,a trust evolvement method of the macro self-organization for Web service combination was proposed.In the method,the control rule of the trust degree in the Dempster-Shafer(D-S)rule was utilized based on the entity network interactive behavior,and a proportion trust control rule was put up.The control rule could make the Web service self-adaptively study so as to gradually form a proper trust connection with its cooperative entities and to improve the security performance of the whole system.The experimental results show that the historical successful experience is saved during the service combination alliance,and the method can greatly improve the reliability and success rate of Web service combination.展开更多
Security vulnerability of denial of service (DoS) in time out-medium access control (T-MAC) protocol was discussed and analysis of power consumption at each stage of T-MAC protocol was carried out. For power efficient...Security vulnerability of denial of service (DoS) in time out-medium access control (T-MAC) protocol was discussed and analysis of power consumption at each stage of T-MAC protocol was carried out. For power efficient authentication scheme which can provide reliability, efficiency, and security for a general T-MAC communication, a novel synchronization and authentication scheme using authentication masking code was proposed. Authentication data were repeated and masked by PN sequence. The simulation results show that the proposed approach can provide synchronization and authentication simultaneously for nodes in wireless sensor network (WSN). 63 bits AMC code gives above 99.97% synchronization detection and 93.98% authentication data detection probability in BER 0.031 7.展开更多
Vehicular ad-hoc networks （VANETs） are a significant field in the intelligent transportation system （ITS） for improving road security. The interaction among the vehicles is enclosed under VANETs. Many experiments ...Vehicular ad-hoc networks （VANETs） are a significant field in the intelligent transportation system （ITS） for improving road security. The interaction among the vehicles is enclosed under VANETs. Many experiments have been performed in the region of VANET improvement. A familiar challenge that occurs is obtaining various constrained quality of service （QoS） metrics. For resolving this issue, this study obtains a cost design for the vehicle routing issue by focusing on the QoS metrics such as collision, travel cost, awareness, and congestion. The awareness of QoS is fuzzified into a price design that comprises the entire cost of routing. As the genetic algorithm （GA） endures from the most significant challenges such as complexity, unassisted issues in mutation, detecting slow convergence, global maxima, multifaceted features under genetic coding, and better fitting, the currently established lion algorithm （LA） is employed. The computation is analyzed by deploying three well-known studies such as cost analysis, convergence analysis, and complexity investigations. A numerical analysis with quantitative outcome has also been studied based on the obtained correlation analysis among various cost functions. It is found that LA performs better than GA with a reduction in complexity and routing cost.展开更多
Prevailing ambient wind is the main reason thatcauses inlet flow rate(air mass flow rate)decreasingand air flowing backward to the air-cooled condenserfans upward to the wind,hence a set of wind guidingnets is designe...Prevailing ambient wind is the main reason thatcauses inlet flow rate(air mass flow rate)decreasingand air flowing backward to the air-cooled condenserfans upward to the wind,hence a set of wind guidingnets is designed to improve the detrimental effect.Fig.1 shows four typical units of a 1000MW directair-cooled condenser(DACC)and a set of windguiding nets installed under its edge upward to theambient wind.As shown in Fig.2,the fan inlet flowrate decreases as the prevailing ambient wind velocityincreasing,especially for the first two units upward tothe wind.展开更多
The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors w...The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors were calculated by semi-empirical calculations. Models were established using partial least square(PLS) regression and back-propagation artificial neural network(BP-ANN). The QSPR results indicate that the descriptors of these derivatives have significant relationship with half-wave reduction potential. The stability and prediction ability of these models were validated using leave-one-out cross-validation and external test set.展开更多
Objective speech quality is difficult to be measured without the input reference speech.Mapping methods using data mining are investigated and designed to improve the output-based speech quality assessment algorithm.T...Objective speech quality is difficult to be measured without the input reference speech.Mapping methods using data mining are investigated and designed to improve the output-based speech quality assessment algorithm.The degraded speech is firstly separated into three classes(unvoiced,voiced and silence),and then the consistency measurement between the degraded speech signal and the pre-trained reference model for each class is calculated and mapped to an objective speech quality score using data mining.Fuzzy Gaussian mixture model(GMM)is used to generate the artificial reference model trained on perceptual linear predictive(PLP)features.The mean opinion score(MOS)mapping methods including multivariate non-linear regression(MNLR),fuzzy neural network(FNN)and support vector regression(SVR)are designed and compared with the standard ITU-T P.563 method.Experimental results show that the assessment methods with data mining perform better than ITU-T P.563.Moreover,FNN and SVR are more efficient than MNLR,and FNN performs best with 14.50% increase in the correlation coefficient and 32.76% decrease in the root-mean-square MOS error.展开更多
A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) i...A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) in a cluster, which is revealed by formulating resource allocation as a network utility maximization problem. Then, by maximizing the total network utility with constrains of minimizing collision probability, the optimal value of CW (Wopt) can be computed according to the number of sensor nodes. The new backoff algorithm uses the common optimal value Wopt and leads to fewer collisions than binary exponential backoff algorithm. The simulation results show that the proposed algorithm outperforms standard 802.11 DCF and S-MAC in average collision times, packet delay, total energy consumption, and system throughput.展开更多
基金supported by the National Nature Science Foundation of China(71771201,72531009,71973001)the USTC Research Funds of the Double First-Class Initiative(FSSF-A-240202).
文摘Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision payoff functions hinge on individual covariates and the choices of their friends.However,peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model.For this reason,we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks.The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios.To estimate peer pressure in the model,we first present two algorithms based on the initialize expand merge method and the polynomial-time twostage method to estimate homogeneity parameters.Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure.Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error.We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.
基金Project(11002121) supported by the National Natural Science Foundation of ChinaProject(09QDZ09) supported by Doctor Foundation of Xiangtan University, China+2 种基金Project(2009LCSSE11) supported by Hunan Key Laboratory for CSSE, ChinaProject(2011FJ3231) supported by Planned Science and Technology Project of Hunan Province,ChinaProject(12JJ3054) supported by the Provincial Natural Science Foundation of Hunan,China
文摘High quality mesh plays an important role for finite element methods in science computation and numerical simulation.Whether the mesh quality is good or not,to some extent,it determines the calculation results of the accuracy and efficiency.Different from classic Lloyd iteration algorithm which is convergent slowly,a novel accelerated scheme was presented,which consists of two core parts:mesh points replacement and local edges Delaunay swapping.By using it,almost all the equilateral triangular meshes can be generated based on centroidal Voronoi tessellation(CVT).Numerical tests show that it is significantly effective with time consuming decreasing by 40%.Compared with other two types of regular mesh generation methods,CVT mesh demonstrates that higher geometric average quality increases over 0.99.
基金Project(50809058)supported by the National Natural Science Foundation of China
文摘A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal transformation of variables with routine monitoring data and normal assumption of variables without routine monitoring data,a conditional linear Gaussian Bayesian network is constructed.A "two-constraint selection" procedure is proposed to estimate potential parameter values under small data.Among all potential parameter values,the ones that are most probable are selected as the "representatives".Finally,the risks of pollutant concentration exceeding national water quality standards are calculated and pollution reduction decisions for decision-making reference are proposed.The final results show that conditional linear Gaussian Bayesian network and "two-constraint selection" procedure are very useful in evaluating risks when there is limited data and can help managers to make sound decisions under small data.
文摘Recent research has revealed that human exposure to air pollutants such as CO, NO_x, and particulates can lead to respiratory diseases, especially among school-age children. Towards understanding such health impacts, this work estimates local-scale vehicular emissions and concentrations near a highway traffic network, where a school zone is located in. In the case study, VISSIM traffic micro-simulation is used to estimate the source of vehicular emissions at each roadway segment. The local-scale emission sources are then used as inputs to the California line source dispersion model(CALINE4) to estimate concentrations across the study area. To justify the local-scale emissions modeling approach, the simulation experiment is conducted under various traffic conditions. Different meteorological conditions are considered for emission dispersion. The work reveals that emission concentrations are usually higher at locations closer to the congested segments, freeway ramps and major arterial intersections. Compared to the macroscopic estimation(i.e. using network-average emission factors), the results show significantly different emission patterns when the local-scale emission modeling approach is used. In particular, it is found that the macroscopic approach over-estimates emission concentrations at freeways and under-estimations are observed at arterials and local streets. The results of the study can be used to compare to the US environmental protection agency(EPA) standards or any other air quality standard to further identify health risk in a fine-grained manner.
基金Project(107021) supported by the Key Foundation of Chinese Ministry of Education Project(2009643013) supported by China Scholarship Fund
文摘In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.
基金Project(60673169)supported by the National Natural Science Foundation of China
文摘Based on the problem that the service entity only has the partial field of vision in the network environment,a trust evolvement method of the macro self-organization for Web service combination was proposed.In the method,the control rule of the trust degree in the Dempster-Shafer(D-S)rule was utilized based on the entity network interactive behavior,and a proportion trust control rule was put up.The control rule could make the Web service self-adaptively study so as to gradually form a proper trust connection with its cooperative entities and to improve the security performance of the whole system.The experimental results show that the historical successful experience is saved during the service combination alliance,and the method can greatly improve the reliability and success rate of Web service combination.
文摘Security vulnerability of denial of service (DoS) in time out-medium access control (T-MAC) protocol was discussed and analysis of power consumption at each stage of T-MAC protocol was carried out. For power efficient authentication scheme which can provide reliability, efficiency, and security for a general T-MAC communication, a novel synchronization and authentication scheme using authentication masking code was proposed. Authentication data were repeated and masked by PN sequence. The simulation results show that the proposed approach can provide synchronization and authentication simultaneously for nodes in wireless sensor network (WSN). 63 bits AMC code gives above 99.97% synchronization detection and 93.98% authentication data detection probability in BER 0.031 7.
文摘Vehicular ad-hoc networks （VANETs） are a significant field in the intelligent transportation system （ITS） for improving road security. The interaction among the vehicles is enclosed under VANETs. Many experiments have been performed in the region of VANET improvement. A familiar challenge that occurs is obtaining various constrained quality of service （QoS） metrics. For resolving this issue, this study obtains a cost design for the vehicle routing issue by focusing on the QoS metrics such as collision, travel cost, awareness, and congestion. The awareness of QoS is fuzzified into a price design that comprises the entire cost of routing. As the genetic algorithm （GA） endures from the most significant challenges such as complexity, unassisted issues in mutation, detecting slow convergence, global maxima, multifaceted features under genetic coding, and better fitting, the currently established lion algorithm （LA） is employed. The computation is analyzed by deploying three well-known studies such as cost analysis, convergence analysis, and complexity investigations. A numerical analysis with quantitative outcome has also been studied based on the obtained correlation analysis among various cost functions. It is found that LA performs better than GA with a reduction in complexity and routing cost.
文摘Prevailing ambient wind is the main reason thatcauses inlet flow rate(air mass flow rate)decreasingand air flowing backward to the air-cooled condenserfans upward to the wind,hence a set of wind guidingnets is designed to improve the detrimental effect.Fig.1 shows four typical units of a 1000MW directair-cooled condenser(DACC)and a set of windguiding nets installed under its edge upward to theambient wind.As shown in Fig.2,the fan inlet flowrate decreases as the prevailing ambient wind velocityincreasing,especially for the first two units upward tothe wind.
基金Project supported by the Postdoctoral Science Foundation of Central South University,ChinaProject(2015SK20823)supported by Science and Technology Project of Hunan Province,China+2 种基金Project(15A001)supported by Scientific Research Fund of Hunan Provincial Education Department,ChinaProject(CX2015B372)supported by Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject supported by Innovation Experiment Program for University Students of Changsha University of Science and Technology,China
文摘The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors were calculated by semi-empirical calculations. Models were established using partial least square(PLS) regression and back-propagation artificial neural network(BP-ANN). The QSPR results indicate that the descriptors of these derivatives have significant relationship with half-wave reduction potential. The stability and prediction ability of these models were validated using leave-one-out cross-validation and external test set.
基金Projects(61001188,1161140319)supported by the National Natural Science Foundation of ChinaProject(2012ZX03001034)supported by the National Science and Technology Major ProjectProject(YETP1202)supported by Beijing Higher Education Young Elite Teacher Project,China
文摘Objective speech quality is difficult to be measured without the input reference speech.Mapping methods using data mining are investigated and designed to improve the output-based speech quality assessment algorithm.The degraded speech is firstly separated into three classes(unvoiced,voiced and silence),and then the consistency measurement between the degraded speech signal and the pre-trained reference model for each class is calculated and mapped to an objective speech quality score using data mining.Fuzzy Gaussian mixture model(GMM)is used to generate the artificial reference model trained on perceptual linear predictive(PLP)features.The mean opinion score(MOS)mapping methods including multivariate non-linear regression(MNLR),fuzzy neural network(FNN)and support vector regression(SVR)are designed and compared with the standard ITU-T P.563 method.Experimental results show that the assessment methods with data mining perform better than ITU-T P.563.Moreover,FNN and SVR are more efficient than MNLR,and FNN performs best with 14.50% increase in the correlation coefficient and 32.76% decrease in the root-mean-square MOS error.
基金Project(60772088) supported by the National Natural Science Foundation of China
文摘A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) in a cluster, which is revealed by formulating resource allocation as a network utility maximization problem. Then, by maximizing the total network utility with constrains of minimizing collision probability, the optimal value of CW (Wopt) can be computed according to the number of sensor nodes. The new backoff algorithm uses the common optimal value Wopt and leads to fewer collisions than binary exponential backoff algorithm. The simulation results show that the proposed algorithm outperforms standard 802.11 DCF and S-MAC in average collision times, packet delay, total energy consumption, and system throughput.
