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Transactional and QoS-aware selection algorithm for reliable Web service composition

Journal of Computational Information systems 2012年第11期8卷 4633-4640页

作者： Shen, Hongjie Ding, Zhijun Wang, Pengwei Chen, Hongzhong Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 China

At present, most of the work has focused on Web services composition from the QoS side, little work being done on investigating how to implement service selection based on transactional and QoS requirements. In complicated network environment, composite services need transactional support for correct and reliable execution. Therefore, How to design a composite service to ensure not only correct and reliable execution but also optimal QoS is a challenging issue. This paper addresses the problem of selecting services by aggregating the transactional and QoS requirements. First, we presented global optimization selection algorithms based on two selection models of composite service with transactional requirements. Then, a heuristic selection algorithm is presented to select an approximately optimal transactional composite service within a reasonable time. Lastly, experiments are conducted to analyze the performance of our proposed algorithms. © 2012 Binary Information Press.

关键词： Quality of service

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Coverage optimization in wireless mobile sensor networks

Coverage optimization in wireless mobile sensor networks

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5th International Conference on Wireless Communications, Networking and Mobile computing, WiCOM 2009

作者： Xingzhen, Bai Shu, Li Changjun, Jiang Zhengzhong, Gao Electronics and Information Engineering School Tongji University Shanghai 201804 China Key Laboratory for the Embedded System and Service Computing of Ministry of Education Tongji University Shanghai 201804 China College of Information and Electrical Engineering Shandong University of Science and Technology Qingdao 266510 China

ISBN: (纸本)9781424436934

The coverage of Wireless Sensor Networks (WSNs) is one of the most important measurement criteria of Qos. Optimal coverage of sensors is propitious to the maximum possible utilization of the available sensors. It can balance node energy consumption, and elongate network lifetime. In this paper, particle swarm optimization (PSO) approach is applied to maximize the coverage of mobile sensor networks. We first analyze the node distribution of random deployed sensor networks. There are big coverage holes as the network size grows. In order to reduce energy consumption during node move process, we study the sensor network coverage optimization in the limited mobility model. The simulation results show that sensor node move in the limited region can also realize the coverage optimization , and it can reduce the moving distance greatly. ©2009 IEEE.

关键词： Sensor nodes

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LBRM algorithm for rule extraction based on rough membership

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2013 3rd International Symposium on Chemical Engineering and Material Properties, ISCEMP 2013

作者： Zhang, Xian Yong Miao, Duo Qian College of Mathematics and Software Science Sichuan Normal University Chengdu Sichuan 610068 China Department of Computer Science and Technology Tongji University Shanghai 201804 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China

ISBN: (纸本)9783037858363

Rule extraction is a main goal for rough set theory. This paper mainly constructs a new algorithm (LBRM Algorithm) for rule extraction based on rough membership. The confidence principle is established based on rough membership. Thus, LBRM Algorithm is proposed by utilizing discretization and clearness strategies under the fuzzy environment, and is applied to both interval rules and general rules in fuzzy classification. LBRM Algorithm effectiveness is illustrated by a medical example. In particular, LBRM Algorithm integrates the confidence on both previous LBR Algorithm and fundamental rough membership, and has some improvements on rule confidence. © (2013) Trans Tech Publications, Switzerland.

关键词： Rough set theory

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Based on transmission line compositing left and right rules to realize optimal matching in RF part of 77GHz automotive radar

Based on transmission line compositing left and right rules ...

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International Radar Symposium (IRS)

作者： Renzhou Gui Key Laboratory of Embedded System and Service Computing Ministry of Eduction College of Electronics & Information Engineering Tongji University Shanghai China

77GHz Automotive radar based on SiGe technique is the hot topics. The optimal matching in the RF part of the automotive radar should be solved and considered firstly. Left hand material(LHM) has special properties such as low loss, negative phase velocity. The paper focus on designing a new transmission line which is made by LHM and RHM (right hand material) together. We analysis the theory of the TL (transmission line) based on compositing LHM and RHM together, then design the match circuits based on the TL. Moreover, the simulating results of the circuit based on the special TL are shown. Lastly, the possibility of using the TL to match at the automotive radar system is valued.

关键词： Power transmission lines Materials Compounds Radio frequency Microstrip Radar Permeability

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Research of Meridian Diagnosis system Based on SVM

Research of Meridian Diagnosis System Based on SVM

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The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

作者： Guo-Xia Zhang Fu-Qiang Liu Chun-Lin Song Pei-Yuan Lai BW&M Institute The Key Laboratory of Embedded System and Service ComputingMinistry of Education Tongji University ShanghaiChina

Aiming at the deficiency of the current meridian diagnosis algorithms, SVM is applied to meridian diagnosis system. The system structure is described firstly, then the model selection of SVM is discussed in detail by taking chronic pharyngitis as an example: one-against-one method is used to realize multi-class;the problem of non-symmetrical samples of C-SVM is solved by giving positive and negative samples of different weights;a margin-based bound on generalization method is used to search parameters of the model. Finally, test results show that the classifier, which is realized and tested using vc++6.0, possess a very high recognition rate and can be applied to meridian diagnosis system.

关键词： Meridians Diagnosis system SVM Nonsymmetrical Samples Generalization Bound

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A Petri Nets Based Approach for Detecting the Data Races and Deadlocks in OpenMP Program

A Petri Nets Based Approach for Detecting the Data Races and...

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2012 Third International Conference on Theoretical and Mathematical Foundations of Computer Science(ICTMF 2012)

作者： Yulong Xian Zhijun Ding Department of Computer Science and Technology Tongji University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

Because of OpenMP programs shielding the underlying parallel execution and scheduling details,data races and deadlocks are tend to occur during program ***,this paper puts forward the modeling method of OpenMP programs based on Petri *** flow of programs are modeled according to the semantics of program control statements and directives of OpenMP programs;Data flow of programs are modeled by abstracting read and write operations related to shared *** two detection algorithms of data race and deadlock for OpenMP program are given based on the coverability tree of Petri ***,corresponding software tool is designed and implemented,and an OpenMP program example of the dining philosophers problem is analyzed to indicate the effectiveness of this method and tools.

关键词： OpenMP, Data races, Deadlock, Static detection, Petri nets

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Multi-label Learning for Protein Subcellular Location Prediction

Multi-label Learning for Protein Subcellular Location Predic...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiao Wang Guo-Zheng Li Jia-Ming Liu Rui-Wei Zhao The Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Control Science and Engineering Tongji University Shanghai China

Protein subcellular localization aims at predicting the location of a protein within a cell using computational methods. Knowledge of subcellular localization of proteins indicates protein functions and helps in identifying drug targets. Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. To better reflect the characteristics of multiplex proteins, we formulate prediction of subcellular localization of multiplex proteins as a multi-label learning problem. We present and compare two multi-label learning approaches, which exploit correlations between labels and leverage label-specific features, respectively, to induce a high quality prediction model. Experimental results on six protein data sets under various organisms show that our described methods achieve significantly higher performance than any of the existing methods. Among the different multi-label learning methods, we find that methods exploiting label correlations performs better than those leveraging label-specific features.

关键词： Proteins Correlation Protein engineering Multiplexing Machine learning Humans Learning systems

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A fast restarting particle swarm optimizer

A fast restarting particle swarm optimizer

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Congress on Evolutionary Computation

作者： Junqi Zhang Xiong Zhu Wei Wang Jing Yao Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

Particle swarm optimization (PSO) is a swarm intelligence technique that optimizes a problem by iterative exploration and exploitation in the search space. However, PSO cannot achieve the preservation of population diversity on solving multimodal optimization problems, and once the swarm falls into local convergence, it cannot jump out of the local trap. In order to solve this problem, this paper presents a fast restarting particle swarm optimization (FRPSO), which uses a novel restarting strategy based on a discrete finite-time particle swarm optimization (DFPSO). Taking advantage of frequently speeding up the swarm to converge along with a greater exploitation capability and then jumping out of the trap, this algorithm can preserve population diversity and provide a superior solution. The experiment performs on twenty-five benchmark functions which consists of single-model, multimodal and hybrid composition problems, the experimental result demonstrates that the performance of the proposed FRPSO algorithm is better than the other three representatives of the advanced PSO algorithm on most of these functions.

关键词： Particle swarm optimization Sociology Statistics Convergence Oscillators Algorithm design and analysis Benchmark testing

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A New MPI Parallel computing Environment Based on Fibre-channel Token-Routing Network for Materials Simulation Research

A New MPI Parallel Computing Environment Based on Fibre-chan...

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2011 International Conference on Advanced Materials in Microwaves and Optics（AMMO 2011）

作者： Xiaohui ZENG Dongsheng LIU Wenlang LUO Lixin FU school of Electronics and Information Engineering Jinggangshan University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

In order to apply our high efficiency fibre-channel token-routing network(shortened as FC-TR network) to the field of materials simulation research, a new MPI parallel computing environment is proposed and designed, and independently developed a parallel programming environment FC-TR-MPI based on FC-TR network. In FC-TR-MPI, a new method was applied to point-to-point communication that the network communications between processes in the same computing node were changed into memory operations;moreover, according to the underlying software and hardware features of FC-TR network, new algorithms were proposed to optimize the communication performance of some collective communications. Experimental results show that, compared with Sca MPI parallel programming environment, FC-TR-MPI has a higher parallel efficiency and speedup.

关键词： MPI,parallel computing environment,fibre-channel,materials simulation

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Cross-Modal Representation Reconstruction for Zero-Shot Classification

Cross-Modal Representation Reconstruction for Zero-Shot Clas...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yu Wang Shenjie Zhao Key Laboratory of Embedded System and Service Computing Ministry of Education P. R. China Mojie Technology (Ningbo)

ISBN: (纸本)9781728176055;9781728176062

Zero-shot learning (ZSL) aims to recognize novel classes without training samples through transferring knowledge from seen classes, based on the assumption that both the seen and unseen classes share a latent semantic space. Previous works either focus on directly learning various mapping functions between visual space and semantic space, or searching a latent common subspace to alleviate semantic gap between different modalities. However, few methods directly learn modality-invariant representations for ZSL. In this paper, we propose a Cross-Modal Representation Reconstruction (CM-RR) framework to bridge the semantic gap between visual features and semantic attributes, as well as introducing a novel regularizer for automatically feature selection. Moreover, an iterative optimization process based on the ALM (Augmented Lagrangian Method) algorithm with the alternating direction strategy is developed to solve the proposed formulation. Extensive experiments on four benchmark datasets show the effectiveness of the proposed approach, and even the performance surpasses some deep learning based methods.

关键词： Training Visualization Semantics Signal processing algorithms Signal processing Feature extraction Iterative algorithms

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