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International Conference on Grid and Cloud computing

作者： Zhao, Bin Cai, Guangjun Jin, Zhi Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Graduate University of the Chinese Academy of Sciences Beijing China Software Engineering Institute Peking University Beijing China

ISBN: (纸本)9780769543130

One fundamental problem in services computing is how to bridge the gap between business requirements and various heterogeneous IT services. This involves eliciting business requirements and building a solution accordingly by reusing availab.e services. While the business requirements are commonly elicited through use cases and scenarios, it is not straightforward to transform the use case model into a service model, and the existing manual approach is cumbersome and error-prone. In this paper, the environment ontology, which is used to model the problem space, is utilized to facilitate the model transformation process. The environment ontology provides a common understanding between business analysts and software engineers. The required software functionalities as well as the availab.e services' capabilities are described using this ontology. By semi-automatically matching the required capability of each use case to the availab.e capabilities provides by services, a use case is realized by that set of services. At the end of this paper, a fictitious case study was used to illustrate how this approach works. © 2010 IEEE.

关键词： Ontology

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Application of multidimensional association rule techniques in manufacturing resource planning system

Application of multidimensional association rule techniques ...

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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Wang, Fayu Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Ministry of Education Tianjin 300191 China

ISBN: (纸本)9781424459346

Association rules mining is a popular and well researched method in data mining research field , its purpose is to mine interesting relations between attributes in transaction database. Classic Apriori algorithm is one of the most influential association rules in mining boolean frequent itemsets algorithms, However, it has some disadvantages such as inefficient in generating candidate itemsets and frequently scanning database, it is not suitable for mining multiple dimensional data model which rise in recent years. A "second cut" method is proposed, which is on the basis of the Apriori algorithm. The algorithm applies to multidimensional mining association rules, and to some extent improved the efficiency of the algorithm. Referring to the manufacturing resource planning system (MRP) features of the retail points, the article sets up the sales association analysis data model based on the above algorithm. It proves that it can increase the sales dramatically by applying this methodology to the real business environment. ©2010 IEEE.

关键词： Association rules

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Research on adaptive strategy for end-hopping system

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Tongxin Xuebao/Journal on Communications 2011年第11 A期32卷 51-57页

作者： Zhao, Chun-Lei Jia, Chun-Fu Weng, Chen Lin, Kai College of Information Technical Science Nankai University Tianjin 300071 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300384 China Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China

An adaptive strategy was proposed for EH system. Modules of attack detection, feedback transmission and adaptive control were added to original EH system. They could help to make threats analysis and adjust hopping strategy in real time, so as to reduce the probability of the system stepping into the attackers' target area. With the experiments proving the anti-attack ability of the prototype system, the feasibility and effectiveness of adaptive strategy were demonstrated for EH system.

关键词： Network security

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Rationale management challenges in requirements engineering

Rationale management challenges in requirements engineering

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作者： Liang, Peng Avgeriou, Paris He, Keqing State Key Lab. of Software Engineering Computer School Wuhan University China Department of Computing Science University of Groningen Netherlands

ISBN: (纸本)9781424487837

Rationale and rationale management have been playing an increasingly prominent role in software system development mainly due to the knowledge demand during system evaluation, maintenance, and evolution, especially for large and complex systems. The rationale management for requirements engineering, as a commencing and critical phase in software development life cycle, is still under-exploited. In this paper, we first survey briefly the state-of-the-art on rationale employment and applications in requirements engineering. Secondly, we identify the challenges in integrating rationale management in requirements engineering activities in order to promote further investigations and define a research agenda on rationale management in requirements engineering. ©2010 IEEE.

关键词： Knowledge management

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A new evidence fusion approach for decision of proactive service

A new evidence fusion approach for decision of proactive ser...

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2010 2nd International Conference on Computational Intelligence and Natural computing, CINC 2010

作者： Zhang, De-Gan Li, Chao Li, Wei-Wei Chen, Xu-Yan School of Computer Science and Technology Tianjin University of Technology 300191 China Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin 300191 China

ISBN: (纸本)9781424477036

Multi-source heterogeneous information fusion is an extremely challenging problem because of the complex and highly irregular nature of environment. We consider decision fusion problem in the presence of m-dependent evidences in this paper. A new evidence fusion approach for decision of proactive service has introduced, which is extending of Class D-S Evidence method. We applied this approach in our active space project for seamless nomadic service of pervasive computing paradigm, good results have been attained. The validity of approach of this paper has been tested. ©2010 IEEE.

关键词： Ubiquitous computing

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From collective knowledge to intelligence: Pre-requirements analysis of large and complex systems

From collective knowledge to intelligence: Pre-requirements ...

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1st Workshop on Web 2.0 for software engineering at ICSE 2010, Web2SE 2010, in Conjunction with the 32nd ACM/IEEE International Conference on software engineering, ICSE 2010

作者： Liang, Peng Avgeriou, Paris He, Keqing Xu, Lai State Key Lab. of Software Engineering Wuhan University China Department of Computing Science University of Groningen Netherlands Software Systems Research Centre Bournemouth University United Kingdom

ISBN: (纸本)9781605589756

Requirements engineering is essentially a social collab.rative activity in which involved stakeholders have to closely work together to communicate, elicit, negotiate, define, confirm, and finally come up with the requirements for the system to be implemented or upgraded. In the development of large and complex systems, with a huge number of uncertain stakeholders, the requirements engineering process becomes a challenging task due to overwhelming and dynamic social interactions, tradeoffs, and collective decisions made by above stakeholders. Traditional approaches and techniques are deficient in supporting this kind of social interactions in requirements-related activities, and managing the evolving requirements and their traceability caused by the social interactions. This paper proposes to address the challenges in the pre-requirements analysis of large and complex systems by employing the techniques from collective intelligence based on Web 2.0 tools and technologies, which is composed of three steps: first, obtain collective requirements knowledge through collab.rative tagging by stakeholders;second, transform collab.rative requirement tags into requirement ontologies;third, support collective requirement decision-making (i.e., collective intelligence) based on the requirement ontologies through requirements reasoning. © 2010 ACM.

关键词： World Wide Web

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Research on face detection based on combination of Haar and skin colors features

Research on face detection based on combination of Haar and ...

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2010 3rd International Congress on Image and Signal Processing, CISP 2010

作者： Wang, Fayu Qi, Baokun Xing, Yong Lu, Baoan Ministry of Education Tianjin University of Technology Tianjin 300191 China Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China

ISBN: (纸本)9781424465149

Face detection and recognition is a hot research subject in the fields of image processing, pattern recognition and computer vision, which emphasize on the enhancement of the precision of detection in as short a time as possible. This paper expounds on how to detect human faces accurately from complex pictures by means of the technology of judgement based on the combination of the feature of Haar and the features of skin colors, and depicts in detail the principles and methods of detection. By the combination of the two methods, we can draw on each other's strength and promote the performance of the algorithm. It has been justified by experiments that this algorithm can produce better detection result, and, for other machinery vision application systems, it is of high value to make use of it as reference. ©2010 IEEE.

关键词： Face recognition

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Medical image retrieval with query-dependent feature fusion based on one-class SVM

Medical image retrieval with query-dependent feature fusion ...

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International Conference on Computational Science and engineering

作者： Huang, Yonggang Zhang, Jun Zhao, Yongwang Ma, Dianfu Institute of Advanced Computing Technology BeiHang University China National Lab. of Software Development Environment BeiHang University China School of Computer Science and Software Engineering University of Wollongong Australia

ISBN: (纸本)9780769543239

Due to the huge growth of the World Wide Web, medical images are now availab.e in large numbers in online repositories, and there exists the need to retrieval the images through automatically extracting visual information of the medical images, which is commonly known as content-based image retrieval (CBIR). Since each feature extracted from images just characterizes certain aspect of image content, multiple features are necessarily employed to improve the retrieval performance. Meanwhile, experiments demonstrate that a special feature is not equally important for different image queries. Most of existed feature fusion methods for image retrieval only utilize query independent feature fusion or rely on explicit user weighting. In this paper, we present a novel query dependent feature fusion method for medical image retrieval based on one class support vector machine. Having considered that a special feature is not equally important for different image queries, the proposed query dependent feature fusion method can learn different feature fusion models for different image queries only based on multiply image samples provided by the user, and the learned feature fusion models can reflect the different importances of a special feature for different image queries. The experimental results on the IRMA medical image collection demonstrate that the proposed method can improve the retrieval performance effectively and can outperform existed feature fusion methods for image retrieval. © 2010 IEEE.

关键词： Support vector machines

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A k-hyperplane-based neural network for non-linear regression

A k-hyperplane-based neural network for non-linear regressio...

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IEEE International Conference on Cognitive Informatics

作者： He, Hongmei Qin, Zengchang Department of Engineering Mathematics University of Bristol Bristol United Kingdom Intelligent Computing and Machine Learning Lab. School of Automation and Electrical Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781424480401

For the time series prediction problem, the relationship between the abstracted independent variables and the response variable is usually strong non-linear. We propose a neural network fusion model based on k-hyperplanes for non-linear regression. A k-hyperplane clustering algorithm is developed to split the data to several clusters. The experiments are done on an artificial time series, and the convergence of k-hyperplane clustering algorithm and neural network gradient training algorithm is examined. The dimension of inputs affect the clustering performance very much. Neural network fusion can get some compensation in performance. It is shown that the prediction performance of the model for the time series is very good. The model can be further exploited for many real applications. © 2010 IEEE.

关键词： Clustering algorithms

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Research on automatic construction of the dynamic Chinese porn feature knowledge system

Research on automatic construction of the dynamic Chinese po...

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2010 International Conference on Computer Design and Applications, ICCDA 2010

作者： Peno, Yu-Zhong Yuan, Chang-An Qin, Xiao Key Lab. of Scientific Computing and Intelligent Information Processing in Universities of Guangxi School of Computer and Information Engineering Guangxi Teacher Education University Nanning 530001 China

ISBN: (纸本)9781424471638

As the Web continues to grow, the pornographic texts in varied forms run rampant on Internet, despite repeated prohibitionsm. It severely does harms to the development of people's mental health and the stability of sociality. In this paper, We propose a novel and effective feature weight-value calculating method named FEFP for such objectionable information, and design a scheme to auto-build system of porn feature knowledge which can be dynamically updated. The experiments are designed and conducted to compare the FEFP with four famous existing methods of Web page feature extraction. Experimental results show that the proposed approach has both higher feature coverage and lower redundancy rates for either porn on conventional forms or porn whose form has been changed. It is very good and very suitable for processing the harmful information in current form which is volatile and increasingly hidden. © 2010 IEEE.

关键词： Feature extraction

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