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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Xiao He Bohan Qin Yan Zhu Xing Chen Yi Liu School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China National Computer Network Emergency Response Technical Team Coordination Center of China

ISBN: (纸本)9781538626672

The smart contract is an interdisciplinary concept that concerns business, finance, contract law and information technology. Designing and developing a smart contract may require the close cooperation of many experts coming from different fields. How to support such collaborative development is a challenging problem in blockchain-oriented software engineering. This paper proposes SPESC, a specification language for smart contracts, which can define the specification of a smart contract for the purpose of collaborative design. SPESC can specify a smart contract in a similar form to real-world contracts using a natural-language-like grammar, in which the obligations and rights of parties and the transaction rules of cryptocurrencies are clearly defined. The preliminary study results demonstrated that SPESC can be easily learned and understood by both IT and non-IT users and thus has greater potential to facilitate collaborative smart contract development.

关键词： Contracts Cryptography Contract law Syntactics Collaboration Software

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Online optimization scheduling for scientific workflows with deadline constraint on hybrid clouds

Online optimization scheduling for scientific workflows with...

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作者： Lin, Bing Guo, Wenzhong Lin, Xiuyan School of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China

The tremendous parallel computing ability of cloud computing encourages investigators to research its drawbacks and advantages on processing large-scale scientific applications such as workflows. The current cloud market is composed of numerous diverse public clouds and a local private cloud, and workflow scheduling is one of the biggest challenges on hybrid clouds due to the highly fragmented cloud market with respect to service provisions, pricing models, and bandwidths. In this paper, we propose an online-scheduling strategy for continuous submitted scientific workflows on hybrid clouds, which aims to complete the deadline-constrained applications as more as possible at a lower price. Firstly, a hierarchical iterative application partition (HIAP) algorithm is proposed to partition the application into a set of dependent tasks. Moreover, many online-scheduling algorithms cooperated with HIAP are presented to finish the workflows with a low average payment. Our strategy takes into account the basic characteristics on hybrid clouds such as bandwidth constraints, data transfer cost and computational cost. Various well-known workflows are used for evaluating the multiple scheduling algorithms and the results show that the MLF_ID approach can achieve a promising performance. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： Data transfer

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A method of off-line signature verification for digital forensics

A method of off-line signature verification for digital fore...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Weiwei Pan Guolong Chen College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou Fujian China

Signature verification is an important part of digital forensics. In order to solve the shortcomings of manual identification in technical accuracy and subjectivity, this paper proposed an off-line signature identification method based on Support Vector Machine (SVM). A powerful feature set is collected by extracting grid features and global features of a signature picture. The method is applied for identifying different writing systems and the highest correct probability of identification arrives at 100%. The results indicated that the method is workable and can be an effectively technical support for digital forensics.

关键词： Feature extraction Support vector machines Training Kernel Digital forensics Forgery

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XGRouter： high-quality global router in X-architecture with particle swarm optimization

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Frontiers of Computer Science 2015年第4期9卷 576-594页

作者： Genggeng LIU Wenzhong GUO Rongrong LI Yuzhen NIU Guolong CHEN College of Mathematics and Computer Science Fuzhou University Fuzhou 350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou 350116 China

This paper presents a high-quality very large scale integration （VLSI） global router in X-architecture, called XGRouter, that heavily relies on integer linear pro- gramming （ILP） techniques, partition strategy and particle swarm optimization （PSO）. A new ILP formulation, which can achieve more uniform routing solution than other formu- lations and can be effectively solved by the proposed PSO is proposed. To effectively use the new ILP formulation, a partition strategy that decomposes a large-sized problem into some small-sized sub-problems is adopted and the routing re- gion is extended progressively from the most congested re- git）n. In the post-processing stage of XGRouter, maze rout- ing based on new routing edge cost is designed to further optimize the total wire length and mantain the congestion uniformity. To our best knowledge, XGRouter is the first work to use a concurrent algorithm to solve the global rout- ing problem in X-architecture. Experimental results show that XGRouter can produce solutions of higher quality than other global routers. And, like several state-of-the-art global touters, XGRouter has no overflow.

关键词： global routing overflow total wire length con-gestion uniformity X-architecture particle swarm optimiza-tion integer linear programming

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VLSI multilayer obstacle-avoiding Steiner minimal tree construction algorithms in X-architecture

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2015年第3期27卷 523-532页

作者： Liu, Genggeng Guo, Wenzhong Chen, Guolong College of Mathematics and Computer Sciences Fuzhou University Fuzhou350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China

Steiner minimal tree is a fundamental model in VLSI routing. Further considering X-architecture, the presence of obstacles, and the requirements of multilayer routing, this paper presented an efficient algorithm based on particle swarm optimization for constructing the multilayer obstacle-avoiding X-architecture Steiner minimal tree. Edge transformation was designed to make the particles have the greater ability to change the topology of the routing tree and avoided the obstacles. The new operators combined with union-find set were designed to prevent the generation of the loops. In order to avoid obstacle and discourage the generation of vias, the penalty function related to obstacle-avoiding and vias was proposed. The proposed algorithm finally optimizes the total cost of routing tree which is the most important optimization target of the multilayer routing. The experimental results show that, the proposed algorithm is effective and superior to state-of-the-art multilayer routing algorithms on the total cost. ©, 2015, Institute of computing Technology. All right reserved.

关键词： Multilayers

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A New Logistic Map Based Chaotic Biogeography-based Optimization Approach for Cluster Analysis

A New Logistic Map Based Chaotic Biogeography-based Optimiza...

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2016 IEEE International Conference on Progress in Informatics and computing

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang School of Computer Science and Technology Nanjing Normal University Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Department of Electrical Engineering The city college of New YorkCUNY Department of Mechanical and Control Engineering Kyushu Institute of Technology School of Information Engineering Yangzhou University School of Physics and Electronic Engineering Taizhou University School of Electronic Information Shanghai Dianji University School of Energy and Mechanical Engineering Nanjing Normal University Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： chaotic biogeography-based optimization cluster analysis centroid-based clustering simulation particle swarm optimization

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A new logistic map based chaotic biogeography-based optimization approach for cluster analysis

A new logistic map based chaotic biogeography-based optimiza...

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IEEE International Conference on Progress in Informatics and computing (PIC)

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Changsha Hunan China School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China Department of Electrical Engineering CUNY New York NY USA Department of Mechanical and Control Engineering Kyushu Institute of Technology Fukuoka Prefecture Japan School of Information Engineering Yangzhou University Yangzhou Jiangsu China School of Physics and Electronic Engineering Taizhou University Taizhou Zhejiang China School of Electronic Information Shanghai Dianji University Shanghai China School of Energy and Mechanical Engineering Nanjing Normal University Nanjing Jiangsu China Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University Quanzhou Fujian China

ISBN: (纸本)9781509034857

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： Genetic algorithms Optimization Clustering algorithms Particle swarm optimization Algorithm design and analysis Logistics Mathematical model

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XGRouter: high-quality global router in X-architecture with particle swarm optimization

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Frontiers of Computer Science 2015年

作者： Liu, Genggeng Guo, Wenzhong Li, Rongrong Niu, Yuzhen Chen, Guolong College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China

This paper presents a high-quality very large scale integration (VLSI) global router in X-architecture, called XGRouter, that heavily relies on integer linear programming (ILP) techniques, partition strategy and particle swarm optimization (PSO). A new ILP formulation, which can achieve more uniform routing solution than other formulations and can be effectively solved by the proposed PSO is proposed. To effectively use the new ILP formulation, a partition strategy that decomposes a large-sized problem into some small-sized sub-problems is adopted and the routing region is extended progressively from the most congested region. In the post-processing stage of XGRouter, maze routing based on new routing edge cost is designed to further optimize the total wire length and mantain the congestion uniformity. To our best knowledge, XGRouter is the first work to use a concurrent algorithm to solve the global routing problem in X-architecture. Experimental results show that XGRouter can produce solutions of higher quality than other global routers. And, like several state-of-the-art global routers, XGRouter has no overflow. © 2015 Higher Education Press and Springer-Verlag Berlin Heidelberg

关键词： VLSI circuits

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A weighted lexicon-based generative model for opinion retrieval

A weighted lexicon-based generative model for opinion retrie...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Xiang-Wen Liao Hu Chen Jing-Jing Wei Zhi-Yong Yu Guo-Long Chen Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (纸本)9781479942145

In recent years, opinion retrieval attracted a growing research interest as online users' opinions become more and more valuable for market survey, political polls, etc. The goal of opinion retrieval is to find relevant and opinionate documents according to a user's query. Compared with previous lexicon-based generative model for opinion retrieval considering that the sentiment words are equal for a query, which cannot reflect different sentiment words' relevant opinion strength, we propose a graph-based approach by using HITS model to capture the sentiment words' relevant opinion strength. Then the weights are incorporated into the weighted lexicon-based generative model for opinion retrieval. Experimental results on two datasets show the effectiveness of the proposed generative model. Compared with the baseline approach, improvements of 4% and 11% have been obtained on two real datasets.

关键词： Computational modeling Twitter Analytical models Abstracts

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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