It is generally accepted that knowledge based systems would be smarter if they can deal with uncertainty. Some research has been done to extend Description Logics(DLs) towards the management of uncertainty, most of wh...
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In this paper we evaluate the performance impact of traffic patterns on wireless mesh networks. Modeling and simulation of the wireless mesh networks were performed using the NS-2 tool. Trace-driven simulations with g...
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In this paper we evaluate the performance impact of traffic patterns on wireless mesh networks. Modeling and simulation of the wireless mesh networks were performed using the NS-2 tool. Trace-driven simulations with genuine traffic trace collected from the wireless mesh networks are used to evaluate the performance. This trace tends to exhibit long-range dependent behavior. Simulation results indicate that genuine traffic traces, compared to traditional traffic models such as the Poisson model, produce longer queues and, thus, require larger buffers in the deployed networks' elements.
Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description fram...
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Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space, through constructing its state （abnormality） relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validiw is proved through case.
A key problem of electronic commerce （for short e-commerce） is fair exchange which guarantees that at the end of the transaction, either both parties involved in the trausaction receive each other＇s items or none d...
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A key problem of electronic commerce （for short e-commerce） is fair exchange which guarantees that at the end of the transaction, either both parties involved in the trausaction receive each other＇s items or none do. A non-interactive optimistic fair exchange e-commerce protocol model based on the publicly verifiable secret sharing is presented. The main idea of our exchange protocol is to interchange verifiable and recoverable keys of the symmetric encryption for participants＇ items. So it is especially suitable for exchange of large-size items. Furthermore, our protocol is efficient and simple as it does not need interactive proof system which has been adopted by a large quantity of previously proposed fair exchange protocols. Based on a modified （2,2） secret sharing scheme, a concrete non-interactive fair exchange e-commerce protocol is designed.
Notice of Violation of IEEE Publication Principles "Multi-paradigm and Multi-grain Parallel Execution Model Based on SMP-Cluster," by Jue Wang, Changjun Hu, Jianxin Lai, Yudi Zhao, and Suqin Zhang, in the Pr...
Notice of Violation of IEEE Publication Principles "Multi-paradigm and Multi-grain Parallel Execution Model Based on SMP-Cluster," by Jue Wang, Changjun Hu, Jianxin Lai, Yudi Zhao, and Suqin Zhang, in the Proceedings of the IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing, 2006 (JVA '06) pp.266-272 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper contains portions of original text from the papers cited below. The original text was copied without appropriate attribution. "Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster," by Gabriele Jost, Haoqiang Jin, Dieter an Mey, and Ferhat F. Hatay, in IEEE Transactions on Parallel and Distributed Systems, 10(2), February 1999 In this paper, we propose a multi-paradigm and multi-grain parallel execution model based on SMP-Cluster, which integrates coarse grain, mid grain and fine grain parallelism. Multiple paradigms supported by our model include task parallel, data parallel, sequential execution, data pipeline and task-farming paradigm. It can be achieved by extending the OpenMP specification, and the extensions include directives for computing resource partition, data distribution and alignment, sequential execution and data pipeline, and functions for Master/Slave model in Macro-Task group. We also compare the performance of different implementations of three benchmark applications, using the same numerical algorithm but employing different programming approaches
There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of knowledge discovery and data mi...
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There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of knowledge discovery and data mining has become an urgent problem to be solved. On the base of analysis and study of existing research results, the united model of knowledge discovery state space （UMKDSS） is presented, and the structured data mining and the complex type data mining are associated together. UMKDSS can provide theoretical guidance for complex type data mining. An application example of UMKDSS is given at last.
The previous particle swarm optimizers lack direct mechanism to prevent particles beyond predefined search space, which results in invalid solutions in some special cases. A momentum factor is introduced into the orig...
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The previous particle swarm optimizers lack direct mechanism to prevent particles beyond predefined search space, which results in invalid solutions in some special cases. A momentum factor is introduced into the original particle swarm optimizer to resolve this problem. Furthermore, in order to accelerate convergence, a new strategy about updating velocities is given. The resulting approach is mromentum-PSO which guarantees that particles are never beyond predefined search space without checking boundary in every iteration. In addition, linearly decreasing wight PSO （LDW-PSO） equipped with a boundary checking strategy is also discussed, which is denoted as LDWBC-PSO. LDW-PSO, LDWBC-PSO and momentum-PSO are compared in optimization on five test functions. The experimental results show that in some special cases LDW-PSO finds invalid solutions and LDWBC-PSO has poor performance, while momentum-PSO not only exhibits good performance but also reduces computational cost for updating velocities.
While conventional sensor networks have revealed their vast potentials, simple and special purposed data doubtlessly will limit their expansion into information hungry domains. Video sensor networks present an unprece...
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With the development of video encoding techniques, video compression algorithms become more complicated. A real-time high resolution video encoder cannot be implemented with a single CPU or DSP. We design and implemen...
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With the development of video encoding techniques, video compression algorithms become more complicated. A real-time high resolution video encoder cannot be implemented with a single CPU or DSP. We design and implement a MPEG-4 video encoder based on coordinated DSP-FPGA techniques. The FPGA module takes the tasks of video acquisition, YUV separation and data I/O functions, while the DSP is dedicated for video compression. We optimize the data flow scheme of the MPEG-4 video compression to utilize the DSP's on-chip memory. A MB (macro block) type judging algorithm is proposed based on MB's space complexity. It effectively reduces the computational complexity of the video compression. The experimental results indicate that our MPEG-4 video encoder implementation can encode 39.2 fps in CIF resolution.
A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on (fuzzy) cross-entropy(CE). This algorithm is divide...
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A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on (fuzzy) cross-entropy(CE). This algorithm is divided into two parts: initial clustering process and incremental clustering process. The former calculates fuzzy cross-entropy or cross-entropy of one point relative to others and a hierachical method based on cross-entropy is used for clustering static data sets. Moreover, it has the lower time complexity. The latter assigns new points to the suitable cluster by calculating membership of data point to existed centers based on the cross-entropy measure. Experimental comparisons show the proposed method has lower time complexity than common methods in the large-scale data situations or dynamic work environments.
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