Applying ontology to describe resource metadata richly in the peer-to-peer environment has become current research trend. In this semantic peer-to-peer environment, indexing semantic element of resource description to...Applying ontology to describe resource metadata richly in the peer-to-peer environment has become current research trend. In this semantic peer-to-peer environment, indexing semantic element of resource description to support efficient resource location is a difficult and challenging problem. This paper provided a hybrid indexing architecture, which combines local indexing and global indexing. It uses community strategy and semantic routing strategy to organize key layer metadata element and uses DHT (distributed hash table) to index extensional layer metadata element. Compared with related system, this approach is more efficient in resource location and more scalable.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
Air temperature and relative humidity have been the main parameters of meteorology study. In the past data could be obtained from in-situ observations, but the observations are local and sparse, especially over ocean....Air temperature and relative humidity have been the main parameters of meteorology study. In the past data could be obtained from in-situ observations, but the observations are local and sparse, especially over ocean. Now we can get them from satellites, yet it is hard to estimate them from sat- ellites directly so far. This paper presents a new method to retrieve monthly averaged sea air temper- ature （SAT） and relative humidity （RH） near sea surface from satellite data with artificial neural networks （ANN）. Compared with the observations in Pacific and Atlantic, the root mean square （RMS） and the correlation between the estimated SAT and the observations are about 0.91 ~C and 0.99, respectively. The RMS and the correlation of RH are about 3.73% and 0.65, respectively. Compared with the multiple regression method, the ANN methodology is more powerful in building nonlinear relations in this research. Thus the global monthly average SAT and RH are retrieved from the fixed ANN network from July 1987 to May 2004. In general the annual average SAT shows the increasing trend in recent 18 years. The abnormality of SAT is decomposed with the empirical or- thogonal function （EOF）. The leading three EOFs could explain 84% of the total variation. EOF1 （76.1%） presents the seasonal change of the SAT abnormality. EOF2 （4.6%） is mainly related with ENSO. EOF3 （3.3%） shows some new interesting phenomena appearing in the three main currents in Pacific, Atlantic and Indian Ocean.展开更多
Controller area networks （CANs） have been designed for multiplexing communication between electronic control units （ECUs） in vehicles and many high-level industrial control applications. When a CAN bus is overload...Controller area networks （CANs） have been designed for multiplexing communication between electronic control units （ECUs） in vehicles and many high-level industrial control applications. When a CAN bus is overloaded by a large number of ECUs connected to it, both the waiting time and the error probability of the data transmission are increased. Thus, it is desirable to reduce the CAN frame length, since the duration of data transmission is proportional to the frame length. In this paper, we present a CAN message compression method to reduce the CAN frame length. Experimental results indicate that CAN transmission data can be compressed by up to 81.06% with the proposed method. By using an embedded test board, we show that 64-bit engine management system （EMS） CAN data compression can be performed within 0.16 ms; consequently, the proposed algorithm can be successfully used in automobile applications.展开更多
文摘Applying ontology to describe resource metadata richly in the peer-to-peer environment has become current research trend. In this semantic peer-to-peer environment, indexing semantic element of resource description to support efficient resource location is a difficult and challenging problem. This paper provided a hybrid indexing architecture, which combines local indexing and global indexing. It uses community strategy and semantic routing strategy to organize key layer metadata element and uses DHT (distributed hash table) to index extensional layer metadata element. Compared with related system, this approach is more efficient in resource location and more scalable.
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.
基金Supported by The National Key Technology R&D Program(No.2013BAD13B01)the National High Technology Research and Development Program of China(No.2001AA633060)
文摘Air temperature and relative humidity have been the main parameters of meteorology study. In the past data could be obtained from in-situ observations, but the observations are local and sparse, especially over ocean. Now we can get them from satellites, yet it is hard to estimate them from sat- ellites directly so far. This paper presents a new method to retrieve monthly averaged sea air temper- ature （SAT） and relative humidity （RH） near sea surface from satellite data with artificial neural networks （ANN）. Compared with the observations in Pacific and Atlantic, the root mean square （RMS） and the correlation between the estimated SAT and the observations are about 0.91 ~C and 0.99, respectively. The RMS and the correlation of RH are about 3.73% and 0.65, respectively. Compared with the multiple regression method, the ANN methodology is more powerful in building nonlinear relations in this research. Thus the global monthly average SAT and RH are retrieved from the fixed ANN network from July 1987 to May 2004. In general the annual average SAT shows the increasing trend in recent 18 years. The abnormality of SAT is decomposed with the empirical or- thogonal function （EOF）. The leading three EOFs could explain 84% of the total variation. EOF1 （76.1%） presents the seasonal change of the SAT abnormality. EOF2 （4.6%） is mainly related with ENSO. EOF3 （3.3%） shows some new interesting phenomena appearing in the three main currents in Pacific, Atlantic and Indian Ocean.
基金Project supported by the Information Technology R&D Program of MOTIE/KEIT(No.10044092)Research Funds of Chonbuk National University in 2013
文摘Controller area networks （CANs） have been designed for multiplexing communication between electronic control units （ECUs） in vehicles and many high-level industrial control applications. When a CAN bus is overloaded by a large number of ECUs connected to it, both the waiting time and the error probability of the data transmission are increased. Thus, it is desirable to reduce the CAN frame length, since the duration of data transmission is proportional to the frame length. In this paper, we present a CAN message compression method to reduce the CAN frame length. Experimental results indicate that CAN transmission data can be compressed by up to 81.06% with the proposed method. By using an embedded test board, we show that 64-bit engine management system （EMS） CAN data compression can be performed within 0.16 ms; consequently, the proposed algorithm can be successfully used in automobile applications.
