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International Workshop on Empirical software engineering in Practice (IWESEP)

作者： Tomomi Hatano Takashi Ishio Joji Okada Yuji Sakata Katsuro Inoue Graduate School of Information Science and Technology Osaka University Suita Osaka Japan NTT DATA Corporation Research and Development Headquarters Center for Applied Software Engineering Koto-ku Tokyo Japan

In the maintenance of a business system, developers must understand the computational business rules implemented in the system. Computational business rules define how an output value of a feature is computed from inputs, the rules are represented by conditional statements in the source code. Unfortunately, understanding business rules is a tedious and error-prone activity. Since a feature computes various outputs, developers must analyze the implementation of the feature and extract the conditional statements relevant to a particular output. In this paper, we propose a program dependence analysis technique tailored for understanding business rules. Given a variable representing an output, our approach extracts conditional statements that may affect the computation of the output. To evaluate the usefulness of the approach, we conducted an experiment with eight developers in a company. The results showed that our approach enables developers to accurately identify conditional statements relevant to business rules.

关键词： Feature extraction Arrays data mining Companies Accuracy Reverse engineering

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Coevolutionary modeling in network formation

Coevolutionary modeling in network formation

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IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Ibrahim Al-Shyoukh Georgios Chasparis Jeff S. Shamma Georgia Institute of Technology Atlanta GA US Department of Data Analysis Systems Software Competence Center Hagenberg GmbH Hagenberg Austria CEMSE Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA

ISBN: (纸本)9781479970896

Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

关键词： Network topology Biological system modeling Economics Topology Nash equilibrium Educational institutions Cost function

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Design of a high-performance full-system instrumentation

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Dongbei Daxue Xuebao/Journal of Northeastern University 2014年 35卷 129-134页

作者： Min, Qing-Hao Zhang, Zheng Wang, Hao-Jun Zhang, Wei-Hua Software School Fudan University Shanghai201203 China Shanghai Key Laboratory of Data Science Fudan University Shanghai201203 China Parallel Processing Institute Fudan University Shanghai201203 China State Key Laboratory of Mathematic Engineering and Advanced Computing PLA Information Engineering University Zhengzhou450001 China

Instrumentation is an important mechanism to collect run-time information of applications for further analysis like bottleneck analysis, hotspot analysis and even bug detection and revision. Currently there are lots of analyzers using instrumentation to collect their source data. However, most of these tools lack of full-system support and thus become inadequate for analyzing multi-core programs as they cannot provide full-system information like scheduling, system calls and inter-process communication, etc. Meanwhile, full-system instrumentation needs to collect OS and hardware information, resulting to performance degradation. In this paper, a high-performance full-system instrumentation method was designed for collecting full-system information as well as application information. The proposed method was implemented inside the QEMU full-system emulator, and 40 MIPS performance on average was achieved after optimization, which was appropriated for normal program analysis. ©, 2014, Northeastern University. All right reserved.

关键词： Full-system High-performance Instrumentation Multi-core

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Probability tree based passenger flow prediction and its application to the Beijing subway system

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Frontiers of Computer science 2013年第2期7卷 195-203页

作者： Biao LENG Jiabei ZEN Zhang XIONG Weifeng LV Yueliang WAN State Key Laboratory of Software Development Environment Beihang UniversityChina Beijing 100191 School of Computer Science and Engineering Beihang UniversityChina Beijing 100191 Shenzhen Key Laboratory of Data Vitalization (Smart City) Research Institute of Beihang University in Shenzhen China Shenzhen 518057 The Third Research Institute of Ministry of Public Security Run Technologies Co. Ltd. China Beijing 100044

In order to provide citizens with safe, convenient and comfortable services and infrastructure in a metropolis, the prediction of passenger flows in the metro-net of subway system has become more important than ever before. Al- though a great number of prediction methods have been pre- sented in the field of transportation, all of them belong to the station oriented approach, which is not well suited to the Bei- jing subway system. This paper proposes a novel metro-net oriented method, called the probability tree based passenger flow model, which is also based on historic origin-destination （OD） information. First it learns and obtains the appearance probabilities for each kind of OD pair. For the real-time origin datum, the destination datum is calculated, and then several kinds of passenger flow in the metro-net can be pre- dicted by gathering all the contributions. The results of exper- iments, using the historical data of Beijing subway, show that although the proposed method has lower performance than existing prediction approaches for forecasting exit passenger flows, it is able to predict several additional kinds of passen- ger flow in stations and throughout the subway system; and it is a more feasible, suitable, and advanced passenger flow prediction model for Beijing subway system.

关键词： passenger flow prediction tree model origin-destination information

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Fuzzy control approach to reconfigurable manufacturing system involving equipment representation

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2013 3rd International Conference on Mechanical science and engineering, ICMSE 2013

作者： Sun, Heng Cai, Shu Bin Massawe, Richard Happson Joseph Department of Computer Science Jinan University Guangzhou 510632 China Software Engineering Department Shenzhen University Shenzhen 518060 China Shenzhen Key Laboratory of High Performance Data Mining Shenzhen 518055 China International School Jinan University Guangzhou 510632 China

ISBN: (纸本)9783037857120

The reconfigurable manufacturing system is a cost-effective system that can accommodate a variety of equipments required by customers. However, because of the surprisingly increasing volume and semantically fuzzy nature of the equipment information, one of the main difficulties to realize efficient equipment reconfiguration is the lack of effective equipment representation technologies and semantic description methods. In this paper, a fuzzy ontology model is proposed for storing semantic concepts in the reconfigurable manufacturing system. To discuss fuzzy inference mechanism has indicated that the fuzzy ontology-based method can promote productivity of the reconfigurable manufacturing system. © (2013) Trans Tech Publications, Switzerland.

关键词： Fuzzy control

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GPU accelerated item-based collaborative filtering for big-data applications

GPU accelerated item-based collaborative filtering for big-d...

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IEEE International Conference on Big data

作者： Chandima Hewa Nadungodage Yuni Xia John Jaehwan Lee Myungcheol Lee Choon Seo Park Department of Computer & Information Science Purdue School of Science Indianapolis USA Department of Electrical & Computer Engineering Purdue School of Engineering & Technology Indianapolis USA Big-Data Software Platform Research Department Software Research Laboratory Electronics & Telecommunications Research Institute Korea

Recommendation systems are a popular marketing strategy for online service providers. These systems predict a customer's future preferences from the past behaviors of that customer and the other customers. Most of the popular online stores process millions of transactions per day; therefore, providing quick and quality recommendations using the large amount of data collected from past transactions can be challenging. Parallel processing power of GPUs can be used to accelerate the recommendation process. However, the amount of memory available on a GPU card is limited; thus, a number of passes may be required to completely process a large-scale dataset. This paper proposes two parallel, item-based recommendation algorithms implemented using the CUDA platform. Considering the high sparsity of the user-item data, we utilize two compression techniques to reduce the required number of passes and increase the speedup. The experimental results on synthetic and real-world datasets show that our algorithms outperform the respective CPU implementations and also the naïve GPU implementation which does not use compression.

关键词： Graphics processing units Runtime Kernel Instruction sets Indexes Memory management Acceleration

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Study on fuzzy semantic controlling for machinery and equipment manufacturing

Study on fuzzy semantic controlling for machinery and equipm...

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2013 2nd International Conference on Manufacture engineering, Quality and Production System, ICMEQP 2013

作者： Sun, Heng Cai, Shu Bin Joseph Massawe, Richard Happson Chen, Ling Department of Computer Science Jinan University Guangzhou 510632 China Software Engineering Department Shenzhen University Shenzhen 518060 China Shenzhen Key Laboratory of High Performance Data Mining Shenzhen 518055 China International School Jinan University Guangzhou 510632 China Jinan University Guangzhou 510632 China

ISBN: (纸本)9783037856970

Machinery and equipment descriptions play an important role in the design and manufacturing of industrial machinery devices and help reducing the design time and manufacturing costs of machinery devices. However, one of the main obstacles to realize efficient device design and manufacturing is the lack of effective semantic description method because of the surprisingly increasing volume and semantically fuzzy natures of the industrial device descriptions. To overcome this problem, this paper presents a novel fuzzy ontology-based device description method and implements the intelligent device retrieval and representation system based on the fuzzy ontology. The fuzzy inference and semantic fusion mechanisms of this approach are demonstrated. © (2013) Trans Tech Publications, Switzerland.

关键词： Machinery

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Study on Fuzzy Semantic Controlling for Machinery and Equipment Manufacturing

Study on Fuzzy Semantic Controlling for Machinery and Equipm...

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2013 2nd International Conference on Manufacture engineering,Quality and Production System(ICMEQP 2013)

作者： Heng Sun Shubin Cai Richard Happson Joseph Massawe Ling Chen Department of Computer Science Jinan University Software Engineering Department Shenzhen University Shenzhen Key Laboratory of High Performance Data Mining International School Jinan University Library Jinan University

关键词： Machinery and equipment manufacturing Fuzzy ontology Device description

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C2MS: Dynamic Monitoring and Management of Cloud Infrastructures

C2MS: Dynamic Monitoring and Management of Cloud Infrastruct...

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IEEE International Conference on Cloud Computing Technology and science (CloudCom)

作者： Gary A. McGilvary Josep Rius Íñigo Goiri Francesc Solsona Adam Barker Malcolm Atkinson Edinburgh Data-Intensive Research Group The University of Edinburgh ICG Software Industrial Polygon Torrefarrera Spain Dept. of Computer Science Rutgers University Dept. of Computer Science and Industrial Engineering Univrsity of Lleida School of Computer Science University of St Andrews

Server clustering is a common design principle employed by many organisations who require high availability, scalability and easier management of their infrastructure. Servers are typically clustered according to the service they provide whether it be the application(s) installed, the role of the server or server accessibility for example. In order to optimize performance, manage load and maintain availability, servers may migrate from one cluster group to another making it difficult for server monitoring tools to continuously monitor these dynamically changing groups. Server monitoring tools are usually statically configured and with any change of group membership requires manual reconfiguration, an unreasonable task to undertake on large-scale cloud infrastructures. In this paper we present the Cloudlet Control and Management System (C2MS), a system for monitoring and controlling dynamic groups of physical or virtual servers within cloud infrastructures. The C2MS extends Ganglia - an open source scalable system performance monitoring tool - by allowing system administrators to define, monitor and modify server groups without the need for server reconfiguration. In turn administrators can easily monitor group and individual server metrics on large-scale dynamic cloud infrastructures where roles of servers may change frequently. Furthermore, we complement group monitoring with a control element allowing administrator-specified actions to be performed over servers within service groups as well as introduce further customized monitoring metrics. This paper outlines the design, implementation and evaluation of the C2MS.

关键词： Servers Monitoring Temperature measurement Clouds Temperature sensors Educational institutions

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A Generic Construction of Proxy Signatures from Certificateless Signatures

A Generic Construction of Proxy Signatures from Certificatel...

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Lei Zhang Qianhong Wu Bo Qin Josep Domingo-Ferrer Peng Zeng Jianwei Liu Ruiying Du Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University Shanghai China UNESCO Chair in Data Privacy Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Tarragona Spain Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Computer Wuhan University China Department of Maths School of Science Xi'an University of Technology China School of Electronic and Information Engineering Beijing University of Aeronautics and Astronautics China

The primitive of proxy signatures allows the original signer to delegate proxy signers to sign on messages on behalf of the original signer. It has found numerous applications in distributed computing scenarios where delegation of signing rights is common. Certificate less public key cryptography eliminates the complicated certificates in traditional public key cryptosystems without suffering from the key escrow problem in identity-based public key cryptography. In this paper, we reveal the relationship between the two important primitives of proxy signatures and certificate less signatures and present a generic conversion from the latter to the former. Following the generic transformation, we propose an efficient proxy signature scheme with a recent certificate less signature scheme.

关键词： Artificial intelligence Bismuth Games Public key cryptography Educational institutions

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