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Optimizing skyline queries in SPA distributed networks

Tien Tzu Hsueh Pao/Acta Electronica Sinica 2013年第8期41卷 1515-1520页

作者： Huang, Zhen-Hua Xiang, Yang Sun, Sheng-Li Chen, Qian Department of Computer and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China School of Software and Microelectronics Peking University Beijing 102600 China

Skyline query has recently received a lot of attention in information service community. The TPAOSS (Three-Phase Algorithm for Optimizing Skyline Scalar) algorithm has two performance drawbacks: (1) in the third phase of TPAOSS, as the number of objects on net nodes increases, the length of bloom filter will increases exponentially, which will seriously influence the efficiency of obtaining replicated values and the occupation size of memory;(2) the TPAOSS algorithm does not consider the computation efficiency of local or global subspace skyline queries in each net node. Motivated by these facts, we propose EPSSQDN (Efficient Processing of Subspace Skyline Queries in Distributed Networks), an algorithm for efficient processing of subspace skyline queries in SPA distributed networks. Moreover, in order to further reduce the computation cost of subspace skyline queries and decrease the volume of data transferred, we present an efficient optimized techniques. Furthermore, we present extensive experiments that demonstrate our method is more advantageous than the TPAOSS algorithm.

关键词： Information services

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Berth-crane allocation model and algorithm of container berths in the uncertain environment

Berth-crane allocation model and algorithm of container bert...

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8th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2013

作者： Liu, Jian-Xin Du, Yu-Yue Hong, Yong-Fa Sun, Lin-Lin College of Information Science Engineering Shandong University of Science and Technology QingdaoShandong266590 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai200092 China College of Civil Engineering and Architecture SUST QingdaoShandong266590 China

ISBN: (纸本)9783642375019

According to the randomness of the vessel’s arrival time and handling time, the establishment of a randomly-oriented environment container berths— crane allocation model, the optimizing goal is to minimize the average ship-waiting time. Taking into account the complexity of the model solution, this paper offers the design of an improved genetic algorithm to reduce the searching space, and according to the characteristics of the optimal solution. With testing example to verify that the model can simulate decision-making environment of berths— crane allocation problem and reflect the decision-maker’s attitude toward risks and preferences. The algorithm can gain a stable and satisfactory solution within the operating time. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Genetic algorithms

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A service selection method based on web service clusters

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Journal of Applied Sciences 2013年第24期13卷 5734-5738页

作者： Liu, Wei Du, Yu-Yue Yan, Chun College of Information Science and Engineering Shandong University of Science and Technology 266590 Qingdao China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University 200092 Shanghai China

service selection is an essential issue in service discovery based on Web service clusters. The ratio of trust value to price is introduced to select the most suitable service in a cluster. The method of computing the initial trust, the direct trust and the recommendation trust are, respectively presented and the overall trust is derived based on them. The proposed method keeps the balance between the price and service quality. © 2013 Asian Network for Scientific Information.

关键词： Web services

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Predictive Control for Visual Servo Stabilization of Nonholonomic Mobile Robots

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Acta Automatica Sinica 2013年第8期39卷 1238-1245页

作者： Zheng-Cai CAO Long-Jie YIN Yi-Li FU Tian-Long LIU College of Information Science and Technology Beijing University of Chemical Technology Beijing 100029 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin 150080 China

Visual servo stabilization of nonholonomic mobile robots has gained extensive attention. However, currently, the solution of the problem does not consider both the visibility constraints and the actuator limitations, so the designed controller is difficult to realize satisfactory performance in practical application. In this paper, a predictive controller for the visual servo stabilization of a mobile robot is presented. Firstly, a kinematic predictive stabilization controller utilized to generate the command of velocity is introduced. Then, in order to make the actual velocity of the mobile robot asymptotically approach to the desired one, a dynamic predictive controller is designed. The proposed predictive controller can deal with the constraints easily. Finally, several simulations are performed, and the results illustrate that the proposed control scheme is effective to solve the visual servo stabilization problem.

关键词： Nonholonomic mobile robots visual servo stabilization predictive control constraints

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Maximally permissive distributed control of large scale automated manufacturing systems modeled with Petri nets

Maximally permissive distributed control of large scale auto...

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

作者： Hu, Hesuan Zhou, Mengchu Liu, Yang School of Electro-mechanical Engineering Xidian University Xi'an Shaanxi 710071 China School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

ISBN: (纸本)9781479915156

Ensuring nonblockingness remains challenging for automated manufacturing systems (AMS) owing to their discrete event dynamics. Both scalability and maximal permissiveness are essential for the synthesis and implementation of their centralized supervisors. Inspired by the divide and conquer philosophy, this work proposes a partition methodology and distributed control technique for large scale AMS. They are represented as interconnected and overlapping subsystems sharing some common components in terms of buffers. For each subsystem, a local supervisor is designed based on its local behavior and neighboring information only. Generalizing the existing results, we develop a condition under which the control law via decomposition promises the maximal permissiveness. Buffer capacities are well designed for the sake of their decomposition into multiple overlapping subsystems. Theoretical results are developed to characterize the behavior compatibility among local controllers. An experimental study illustrates the effectiveness of the proposed method. © 2013 IEEE.

关键词： Supervisory personnel

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Supervisor synthesis and performance improvement for automated manufacturing systems by using Petri nets

Supervisor synthesis and performance improvement for automat...

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

ISBN: (纸本)9781479915156

Behavior management and performance evaluation are two significant issues in the design and operation of automated manufacturing systems (AMS). The former constrains their dynamics so as to avoid improper behavior and eliminate downtime, while the latter aims to evaluate cycle time. Although abundant research has been conducted on each issue independently, researchers rarely address both in a correlative way. Without accurate and prompt guidance to route parts, it is difficult for an AMS to manage the production process in an optimal manner. In the paradigm of Petri nets, we show that it is crucial to optimize certain local priorities for the sake of cycle time minimization or throughput maximization. Without making radical changes to the system structure, our method can well design some control parameters in order to meet system performance requirement. An algorithm of polynomial complexity is presented to derive supervisory controllers, if existing, to improve system performance. © 2013 IEEE.

关键词： Petri nets

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Scheduling of time constrained dual-arm cluster tools with wafer revisiting

Scheduling of time constrained dual-arm cluster tools with w...

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

作者： Qiao, Yan Wu, Naiqi Zhou, Mengchu Department of Industrial Engineering School of Electro-Mechanical Engineering Guangdong University of Technology Guangzhou 510006 China Macau University of Science and Technology China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102-1982 United States

ISBN: (纸本)9781479915156

This work intends to schedule a dual-arm cluster tool for the atomic layer deposition (ALD) process with wafer residency time constraints. ALD is a typical wafer revisiting process. Based on the analysis of system properties, a novel scheduling strategy called modified 1-wafer cyclic scheduling is derived. With this strategy, necessary and sufficient schedulability conditions are established. If schedulable, scheduling algorithms are presented to obtain a feasible and optimal schedule. By the proposed method, a schedule can be found by just simple calculation. An illustrative example is given to show the application of the proposed approach. © 2013 IEEE.

关键词： Atomic layer deposition

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Covariance free incremental principal component analysis with exact mean update

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Journal of Computational Information systems 2013年第16期9卷 6703-6710页

作者： Zeng, Xueqiang Li, Guozheng The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Computer Center Nanchang University Nanchang 330029 China Department of Control Science and Engineering Tongji University Shanghai 201804 China

Incremental feature extraction is an essential data preprocessing technique for large-scale and streaming data mining. Among various covariance matrix-free Incremental Principal Component Analysis (IPCA) methods, Candid Covariance-free Incremental Principal Component Analysis (CCIPCA) is a state-of-the art algorithm. Since the training samples are required to be centred, CCIPCA applies an approximate centric alignment on the input data, where only the current sample is correctly centred and all historical data are not updated properly. In this paper, we propose a novel centred incremental principal component analysis algorithm with exact historical mean update, where not only the current sample is centred, but also all historical data are updated by the current mean correctly. Compared to CCIPCA, the proposed method converges more quickly, and the performance improvement is especially obvious when the data's inherent covariance is not stable. The experiments on real streaming dataset show that the proposed method is much superior to CCIPCA in convergence speed. © 2013 Binary Information Press.

关键词： Principal component analysis

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$\varepsilon$-Constraint and Fuzzy Logic-Based Optimization of Hazardous Material Transportation via Lane Reservation

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IEEE Transactions on Intelligent Transportation systems 2013年第2期14卷 847-857页

作者： Zhen Zhou Feng Chu Ada Che MengChu Zhou Computing Integrative Biology and Complex Systems Laboratory University of Evry-Val dEssonne Evry France School of Management Northwestern Polytechnical University Xian China Key Laboratory of Embedded System and Service Computing of Ministry of Education Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

With economic development, a great amount of hazardous material is shipped in the transport network every day. Hazardous material transportation is well known for its high potential risk. An accident can cause very serious economic damage and will have a negative impact on public health and the environment over the long term. Transporting hazardous materials on special lanes can reduce the risk. However, a lane reservation strategy may worsen traffic conditions for other vehicles. This paper investigates a hazardous material transportation problem with lane reservation. The problem lies in how to choose lanes to be reserved in the network and select the path for each hazardous material shipment from the reserved lanes. The goal is to obtain the best compromise between the impact on normal traffic and the transportation risk. A multiobjective integer programming model is presented for the new problem. Then, an algorithm is developed based on the ε -constraint method and a fuzzy-logic-based approach. Pareto optimal solutions are obtained by the former, and a preferred solution is selected by the fuzzy-logic-based approach. Computational results demonstrate the efficiency of the proposed algorithm using an instance based on a real network topology and randomly generated instances.

关键词： Hazardous materials Accidents Roads Linear programming Vectors Optimization

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Neighborhood Rough Sets based Multi-Label classification

Neighborhood Rough Sets based Multi-Label classification

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Ying Yu Witold Pedrycz Duoqian Miao Hongyun Zhang Tongji University Shanghai Shanghai CN University of Alberta Edmonton AB CA Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781479903467

Nowadays, multi-label classification methods are of growing interest. Due to the relationships among the labels, traditional single-label classification methods are not directly applicable to the multi-label classification problem. This paper presents a novel multi-label classification framework based on the variable precision neighborhood rough sets, called Multi-Label classification using Rough Sets (MLRS) which considers the impact of correlation among the labels and the uncertainty that exists in the mapping between the feature space and label space. A series of experiments reported for seven multi-label datasets show that MLRS achieves promising performance when compared with some famous multi-label learning algorithms.

关键词： Classification algorithms Rough sets Training Testing Approximation methods Uncertainty Prediction algorithms

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