Multimedia live stream multicasting and on-line real-time applications are popular recently. Real-time multicast system can use peer-to-peer technology to keep stability and scalability without any additional support from the underneath network or a server. Our proposed scheme focuses on the mesh architecture of peer-to-peer live streaming system and experiments with the buffering mechanisms. We design the dynamic buffer to substitute the traditional fixed buffer.

According to the existing measurements and our simulation results, using the traditional static buffer in a dynamic peer-to-peer environment has a limit of improving quality of service. In our proposed method, the buffering mechanism can adjust buffer to avoid the frozen or reboot of streaming based on the input data rate. A self-adjusted buffer control can be suitable for the violently dynamic peer-to-peer environment. Without any support of infrastructure and modification of peer-to-peer protocols, our proposed scheme can be workable in any chunk-based peer-to-peer streaming delivery. Hence, our proposed dynamic buffering mechanism varies the existing peer-to-peer live streaming system less to improve quality of experience more.

In order to balance the load between cluster head, save the energy consumption of the inter-cluster routing, enhance reliability and flexibility of data transmission, the paper proposes a new clustering routing protocol based on connected graph (CRPCG). The protocol optimizes and innovates in three aspects: cluster head election, clusters formation and clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads, using the excellent algorithm of the graph theory, to guarantee the network connectivity and reliability, improve the link quality, balance node energy and prolong the network life cycle. The results of simulation show that, the protocol significantly prolong the network life cycle, balance the energy of network nodes, especially in the phase of inter-cluster data transmission, improving the reliability and efficiency of data transmission.

Parallel parsing is one of the key technologies of parallel system. Grammatical character affects the efficiency of parallel parsing and degree of difficulty of implement. Existing methods have problems as follows: Parallelism of grammar that adapt different data object is difference, if there is a large difference between considering attribute and analysis object structure, then affect efficiency. Specific grammar parallel parsing is systematically studied. Scanning parallel parsing methods from the new angle of sequence span after word lattice distortion. Considering sequence span attribute between some specific grammars makes parsing without changing structure and data of CYK table based on the structure of word lattice CYK initialization table; In passing item of the form [i , j , Bη•] in parallel parsing item table memory structure in circle structure is adopted chain breaking technology; When indexed optimize analysis, the key algorithms of increasing the feasibility and validity of sequence span attribute、reusing parsing tree、calculating of d space function and node separating are further studied, then unification and optimize effect between analysis table middle structure and data object structure is reached. New algorithm and implement strategy of parallel parsing of specific grammar is proposed.

Traditional Clustering is a powerful technique for revealing the hot topics among Web information. However, it failed to discover the trending events coming out gradually. In this paper, we propose a novel method to address this problem which is modeled as detecting the new cluster from time-streaming documents. Our approach concludes three parts: the cluster definition based on Multi-Representation Index Tree (MI-Tree), the new cluster detecting process and the metrics for measuring a new cluster. Compared with the traditional method, we process the newly coming data first and merge the old clustering tree into the new one. Our algorithm can avoid that the documents owning high similarity were assigned to different clusters. We designed and implemented a system for practical application, the experimental results on a variety of domains demonstrate that our algorithm can recognize new valuable cluster during the iteration process, and produce quality clusters.

A novel transient component bus protection based on mathematical morphology is presented in this paper, which takes the morphological max top-bottom-operator of current traveling wave to fast distinguish the bus internal fault from the external fault. The method is based on the principle that the high frequency component of transient traveling wave caused by bus external fault will be attenuated by the bus capacitance but the traveling wave caused by bus internal fault changes slightly. Simulation is carried out with the electromagnetic transient simulation software PSCAD/EMTDC, the result verifies the bus protection is reliable and accurate. The novel bus protection also can treat lightning failure or lightning disturbance happened on transmission lines as bus external fault, without malfunction.

Mind Evolutionary Algorithm (MEA) imitates the human mind evolution by using similartaxis and dissimilation operations, which overcomes the prematurity and improves searching efficiency. But the generation of the initial population is blind and the addition of naturally washed out temporary subpopulations is random. This paper improved MEA by introducing chaos and difference into it, which brought adequate diversity to the initial population and saved the excellent genes in the evolution. Then the improved MEA is used in the synthesis of sparse antenna arrays. The excellent results of computer simulation show the advantage of array antenna patterns synthesis using the improved MEA.

There is a smoothing reactor and DC filter between the inverter and the direct current line to form a boundary in the HVDC transmission system. Since this boundary presents the stop-band characteristic to the high frequency transient voltage signals, the high-frequency transient voltage signal caused by external faults through boundary will be attenuated and the signals caused by internal faults will be unchanged. The wavelet analysis can be used as a tool to extract the feature of the fault to classify the internal fault and the external fault in HVDC transmission system. This paper explores the new method of wavelet based Multi-Resolution Analysis for signal decomposition to classify the difference types fault.

Soft subspace clustering is an important part and research hotspot in clustering research. Clustering in high dimensional space is especially difficult due to the sparse distribution of the data and the curse of dimensionality. By analyzing limitations of the existing algorithms, the concept of subspace difference and an improved initialization method are proposed. Based on these, a new objective function is given by taking into account the compactness of the subspace clusters and subspace difference of the clusters. And a subspace clustering algorithm based on k-means is presented. Theoretical analysis and experimental results demonstrate that the proposed algorithm significantly improves the accuracy.