3D spatial data model and simulating are the core of 3D GIS can be adopted indifferent domains. A data model based on Quasi Tri-Prism Volume (QTPV) has been proposed. QTPVdefinition and its special cases have been dis...3D spatial data model and simulating are the core of 3D GIS can be adopted indifferent domains. A data model based on Quasi Tri-Prism Volume (QTPV) has been proposed. QTPVdefinition and its special cases have been discussed. Using QTPV and its special cases, irregularnatural geological bodies and regular subsurface engineering can be described efficiently. Theproposed model is composed of five primitives and six objects. Data structures and topologicalrelationship of the fives primitives and three objects describing stratigraphy are designed indetail. Some schemes are designed for the QTPV modelling of stratigraphy and subsurface engineeringaccording to modelling data. The model manipulation method of QTPV cutting by an arbitrary plane isdiscussed. Using VC^(++)6. 0 programming language integrated with SQL database and OpenGL graphiclibrary under windows environment, a system prototype 3DGeoMV has been developed. The experimentresult shows that the QTPV model is feasible and efficient in modelling subsurface engineering.展开更多
Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information.However,other performance requirements such as life cycle of nodes,stability and security are ...Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information.However,other performance requirements such as life cycle of nodes,stability and security are not set as primary design objectives.This makes data collection ability of vehicular nodes in real application environment inferior.By considering the features of nodes in wireless IoV,such as large scales of deployment,volatility and low time delay,an efficient data collection algorithm is proposed for mobile vehicle network environment.An adaptive sensing model is designed to establish vehicular data collection protocol.The protocol adopts group management in model communication.The vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding nodes.It will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding nodes.In addition,secure data collection between sensing nodes is undertaken as well.The simulation and experiments show that the vehicular node can realize secure and real-time data collection.Moreover,the proposed algorithm is superior in vehicular network life cycle,power consumption and reliability of data collection by comparing to other algorithms.展开更多
According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are comput...According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.展开更多
Abstract： A hierarchical method for scene analysis in audio sensor networks is proposed. This meth-od consists of two stages： element detection stage and audio scene analysis stage. In the former stage, the basic au...Abstract： A hierarchical method for scene analysis in audio sensor networks is proposed. This meth-od consists of two stages： element detection stage and audio scene analysis stage. In the former stage, the basic audio elements are modeled by the HMM models and trained by enough samples off-line, and we adaptively add or remove basic ele- ment from the targeted element pool according to the time, place and other environment parameters. In the latter stage, a data fusion algorithm is used to combine the sensory information of the same ar-ea, and then, a role-based method is employed to analyze the audio scene based on the fused data. We conduct some experiments to evaluate the per-formance of the proposed method that about 70% audio scenes can be detected correctly by this method. The experiment evaluations demonstrate that our method can achieve satisfactory results.展开更多
In this paper, we research on the research on the mass structured data storage and sorting algorithm and methodology for SQL database under the big data environment. With the data storage market development and center...In this paper, we research on the research on the mass structured data storage and sorting algorithm and methodology for SQL database under the big data environment. With the data storage market development and centering on the server, the data will store model to data- centric data storage model. Storage is considered from the start, just keep a series of data, for the management system and storage device rarely consider the intrinsic value of the stored data. The prosperity of the Internet has changed the world data storage, and with the emergence of many new applications. Theoretically, the proposed algorithm has the ability of dealing with massive data and numerically, the algorithm could enhance the processing accuracy and speed which will be meaningful.展开更多
In order to solve the bottleneck problem of the traditional K-Medoids clustering algorithm facing to deal with massive data information at the time of memory capacity and processing speed of CPU, the paper proposed a ...In order to solve the bottleneck problem of the traditional K-Medoids clustering algorithm facing to deal with massive data information at the time of memory capacity and processing speed of CPU, the paper proposed a parallel algorithm MapReduce programming model based on the research of K-Medoids algorithm. This algorithm increase the computation granularity and reduces the communication cost ratio based on the MapReduce model. The experimental results show that the improved parallel algorithm compared with other algorithms, speedup and operation efficiency is greatly enhanced.展开更多
This paper proposes a distributed fair queuing algorithm which is based on compensation coordi- nation scheduling in wireless mesh networks, considering such problems as the location-dependent competition and unfair c...This paper proposes a distributed fair queuing algorithm which is based on compensation coordi- nation scheduling in wireless mesh networks, considering such problems as the location-dependent competition and unfair channel bandwidth allocation among nodes. The data communication process requiring the establishment of compensation coordination scheduling model is divided into three periods： the sending period, the compensation period and the dormancy period. According to model parameters, time constraint functions are designed to limit the execution length of each period. The algorithms guarantee that the nodes complete fair transmission of network packets together in accordance with the fixed coordination scheduling rule of the model. Simulations and analysis demonstrate the effectiveness of the proposed algorithm in network throughput and fairness.展开更多
基金Funded by the Hong Kong Polytechnic University ASD research fund (No. 1.34.A222),Open Research Fund Program of LIESMARS (No. WKL(01) 0302) and the National Natural Science Foundation of China(No. 40401021)
文摘3D spatial data model and simulating are the core of 3D GIS can be adopted indifferent domains. A data model based on Quasi Tri-Prism Volume (QTPV) has been proposed. QTPVdefinition and its special cases have been discussed. Using QTPV and its special cases, irregularnatural geological bodies and regular subsurface engineering can be described efficiently. Theproposed model is composed of five primitives and six objects. Data structures and topologicalrelationship of the fives primitives and three objects describing stratigraphy are designed indetail. Some schemes are designed for the QTPV modelling of stratigraphy and subsurface engineeringaccording to modelling data. The model manipulation method of QTPV cutting by an arbitrary plane isdiscussed. Using VC^(++)6. 0 programming language integrated with SQL database and OpenGL graphiclibrary under windows environment, a system prototype 3DGeoMV has been developed. The experimentresult shows that the QTPV model is feasible and efficient in modelling subsurface engineering.
基金supported by the National Nature Science Foundation of China(Grant61572188)A Project Supported by Scientif ic Research Fund of Hunan Provincial Education Department(14A047)+4 种基金the Natural Science Foundation of Fujian Province(Grant no.2014J05079)the Young and Middle-Aged Teachers Education Scientific Research Project of Fujian province(Grant nos.JA13248JA14254 and JA15368)the special scientific research funding for colleges and universities from Fujian Provincial Education Department(Grant no.JK2013043)the Research Project supported by Xiamen University of Technology(YKJ15019R)
文摘Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information.However,other performance requirements such as life cycle of nodes,stability and security are not set as primary design objectives.This makes data collection ability of vehicular nodes in real application environment inferior.By considering the features of nodes in wireless IoV,such as large scales of deployment,volatility and low time delay,an efficient data collection algorithm is proposed for mobile vehicle network environment.An adaptive sensing model is designed to establish vehicular data collection protocol.The protocol adopts group management in model communication.The vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding nodes.It will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding nodes.In addition,secure data collection between sensing nodes is undertaken as well.The simulation and experiments show that the vehicular node can realize secure and real-time data collection.Moreover,the proposed algorithm is superior in vehicular network life cycle,power consumption and reliability of data collection by comparing to other algorithms.
基金Project(70671039) supported by the National Natural Science Foundation of China
文摘According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.
基金This work was supported by the Projects of the National Nat-ura! Science Foundation of China under Crant No.U0835001 the Fundamental Research Funds for the Central Universities-2011PTB-00-28.
文摘Abstract： A hierarchical method for scene analysis in audio sensor networks is proposed. This meth-od consists of two stages： element detection stage and audio scene analysis stage. In the former stage, the basic audio elements are modeled by the HMM models and trained by enough samples off-line, and we adaptively add or remove basic ele- ment from the targeted element pool according to the time, place and other environment parameters. In the latter stage, a data fusion algorithm is used to combine the sensory information of the same ar-ea, and then, a role-based method is employed to analyze the audio scene based on the fused data. We conduct some experiments to evaluate the per-formance of the proposed method that about 70% audio scenes can be detected correctly by this method. The experiment evaluations demonstrate that our method can achieve satisfactory results.
文摘In this paper, we research on the research on the mass structured data storage and sorting algorithm and methodology for SQL database under the big data environment. With the data storage market development and centering on the server, the data will store model to data- centric data storage model. Storage is considered from the start, just keep a series of data, for the management system and storage device rarely consider the intrinsic value of the stored data. The prosperity of the Internet has changed the world data storage, and with the emergence of many new applications. Theoretically, the proposed algorithm has the ability of dealing with massive data and numerically, the algorithm could enhance the processing accuracy and speed which will be meaningful.
文摘In order to solve the bottleneck problem of the traditional K-Medoids clustering algorithm facing to deal with massive data information at the time of memory capacity and processing speed of CPU, the paper proposed a parallel algorithm MapReduce programming model based on the research of K-Medoids algorithm. This algorithm increase the computation granularity and reduces the communication cost ratio based on the MapReduce model. The experimental results show that the improved parallel algorithm compared with other algorithms, speedup and operation efficiency is greatly enhanced.
基金Supported by the National Natural Science Foundation of China （61071096, 61003233, 61073103 ） and the Research Fund for the Doctoral Program of Higher Education （20100162110012）.
文摘This paper proposes a distributed fair queuing algorithm which is based on compensation coordi- nation scheduling in wireless mesh networks, considering such problems as the location-dependent competition and unfair channel bandwidth allocation among nodes. The data communication process requiring the establishment of compensation coordination scheduling model is divided into three periods： the sending period, the compensation period and the dormancy period. According to model parameters, time constraint functions are designed to limit the execution length of each period. The algorithms guarantee that the nodes complete fair transmission of network packets together in accordance with the fixed coordination scheduling rule of the model. Simulations and analysis demonstrate the effectiveness of the proposed algorithm in network throughput and fairness.
