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11th IEEE High Assurance Systems Engineering Symposium(HASE 2008)(第十一届IEEE高可信系统工程国际研讨会)

作者： Zhou Zhou Linzhang Wang Zhanqi Cui Xin Chen Jianhua Zhao State Key Laboratory of Novel Software Technology Nanjing University Nanjing P.R.China 210093 Department of Computer Science and Technology Nanjing University Nanjing P.R.China 210093

This paper describes the Jasmine tool to detect inconsistencies between the modelled behavior depicted in UML behavior models and monitored runtime behavior of Java programs by runtime verification. Jasmine takes Java programs under verification and corresponding UML models including sequence diagrams, activity diagrams and state machine diagrams. Jasmine imports and parses UML models created by any UML modelling tools. Jasmine instruments the code directed by the UML models,so as to relate the monitored runtime behavior to the UML models. Jasmine drives the instrumented program by existing test suites to collect the program execution traces. Jasmine checks the consistencies between the collected program execution traces and the UML models. It is implemented in Eclipse framework,working as a stand-alone Java application as well as a plug-in in Eclipse platform. It is highly automated and has been evaluated on several case studies.

关键词： Runtime Unified modeling language Testing Java Instruments Monitoring Model driven engineering Programming profession Systems engineering and theory Laboratories

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Research on Motion Vector Accuracy in OvercompleteWavelet-Domain Scalable Video Coding Based on Human Visual System Characteristics

Research on Motion Vector Accuracy in OvercompleteWavelet-Do...

引用

The 9th International Conference for Young computer Scientists(第九届国际青年计算机大会)

作者： Chuanming Song Xianghai Wang Fuyan Zhang Department of Computer Science & Technology Nanjing University Nanjing 210093 China College of Computer & Information Technol. Liaoning Normal University Dalian 116029 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China

This paper proposes an accuracy-distortion model for overcomplete wavelet-based scalable motion estimation by exploiting the theory of stationary random process. We first estimate the motion compensation errors in spatial domain due to inaccurate motion vectors, then extend the results to overcomplete wavelet domain, and further derive the errors caused by fraction-pixel motion vectors. Finally, combining with a visibility model of wavelet coefficient errors, this paper proposes a novel algorithm to estimate the motion vector accuracy with which the motion compensation errors will be invisible. Experimental results show that the proposed algorithm is effective in estimating the visually lossless accuracy threshold of motion vectors. The proposed algorithm can be used in scalable coding of motion vectors. Also it can accelerate the motion estimation speed by stopping halfway at the accuracy that will not cause any visible errors.

关键词： Scalable video coding scalable motion vector human visual system wavelet.

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Fundamental problems with available bandwidth measurement systems

引用

Ruan Jian Xue Bao/Journal of software 2008年第5期19卷 1234-1255页

作者： Zhou, Hui Li, Dan Wang, Yong-Ji Institute of Software Chinese Acad. of Sci. Beijing 100190 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China State Key Laboratory of Computer Science Chinese Acad. of Sci. Beijing 100190 China Graduate University Chinese Acad. of Sci. Beijing 100049 China

Based on the analysis of 13 well-known available bandwidth systems and the experience in designing, building, and deploying the BNeck system, the fundamental problems with available bandwidth measurement systems are a... 详细信息

关键词： computer networks

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A Novel Method of Combined Feature Extraction for Recognition

A Novel Method of Combined Feature Extraction for Recognitio...

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IEEE International Conference on Data Mining (ICDM)

作者： Tingkai Sun Songcan Chen Jingyu Yang Pengfei Shi School of Computer Science and Technology Nanjing University of Science and Technology of PLA Nanjing China Department of Computer Science & Engineering Nanjing University of Aeronautics and Astronautics Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China School of Electronic Information and Electrical Engineering Shanghai Jiaotong University Shanghai China

Multimodal recognition is an emerging technique to overcome the non-robustness of the unimodal recognition in real applications. Canonical correlation analysis (CCA) has been employed as a powerful tool for feature fusion in the realization of such multimodal system. However, CCA is the unsupervised feature extraction and it does not utilize the class information of the samples, resulting in the constraint of the recognition performance. In this paper, the class information is incorporated into the framework of CCA for combined feature extraction, and a novel method of combined feature extraction for multimodal recognition, called discriminative canonical correlation analysis (DCCA), is proposed. The experiments show that DCCA outperforms some related methods of both unimodal recognition and multimodal recognition.

关键词： Feature extraction Space technology Electronic mail computer science Signal mapping Pattern recognition Speech recognition Data mining Data engineering Application software

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A Dynamic Trust Model for the Multi-agent Systems

A Dynamic Trust Model for the Multi-agent Systems

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International Symposiums on Information Processing (ISIP)

作者： Bin li Maolin Xing JunWu Zhu Tongshen Che State Key Laboratory for Novel Software Nanjing University Nanjing China Department of Computer Science and Engineering Yangzhou University Yangzhou China College of Information Science and Technology Nanjing University of Aeronautics and Astronautics China

Internet provides a fertile medium for new breeds of computer viruses. Many people who have access to a wealth of information via Internet are attacked by more computer viruses than they can effectively process. We present a dynamic computer virus detection model that can detect known viruses and previously unknown viruses to prevent information systems from damage. This model is inspired by biological immune systems that protect the body against damage from pathogens. The architecture of this model, the formal definitions of self nonself antigen, antibody, and vaccine gene library are introduced. Furthermore, the evolution of self and nonself, the generation of the antibody, the evolution of the virus vaccine gene, and the detection of the antigen are depicted. Experiment results show that this model has better capacity of self-adaptability and self-learning in detecting unknown viruses than traditional models.

关键词： Multiagent systems computer viruses Biological system modeling Internet Vaccines Evolution (biology) Biology computing Information systems Immune system Protection

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Perspective distortion minimization algorithm for image repairing from a large displacement view

引用

Ruan Jian Xue Bao/Journal of software 2008年第SUPPL.期19卷 202-212页

作者： Liu, Chun-Xiao Peng, Qun-Sheng Yang, Ying-Zhen Wang, Jin Chen, Wei State Key Laboratory of CAD and CG Zhejiang University Hangzhou 310058 China Department of Mathematics Zhejiang University Hangzhou 310058 China College of Computer Science and Technology Zhejiang University Hangzhou 310058 China

A coarse-to-fine perspective distortion minimization algorithm is proposed for image repairing based on an additional large displacement view (LDV) of the same scene. It works by correcting the perspective distortion in the LDV image, and then utilizing the rectified LDV image to recover the missing areas on the target image. First, under the assumption of a planar scene, the LDV image is globally warped according to a homography to generate the initial distortion correction. Second, a mismatch recognition mechanism detects the remaining distortions in the initially corrected LDV image. They are further relaxed by energy optimization of overlap correspondences with the expectations of color constancy and displacement field smoothness. Third, under the constraints of epipolar geometry, displacement field smoothness and color consistency among the neighboring pixels, the missing pixels are orderly restored according to a specially-defined repairing priority function. Poisson image blending is adopted to eliminate the ghost effect between the repaired region and its surroundings and get the seamless repairing effect. Experimental results demonstrate that this method outperforms recent state-of-the-art image completion algorithms, especially for completing large damaged area with complex structure information. © 2008 by of Journal of software. All rights reserved.

关键词： Pixels

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DIGITAL IMAGE FORENSICS USING STATISTICAL FEATURES AND NEURAL NETWORK CLASSIFIER

DIGITAL IMAGE FORENSICS USING STATISTICAL FEATURES AND NEURA...

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2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： WEI LU JI-WU HUANG WEI SUN HONG-TAO LU School of Information Science and Technology and Guangdong Key Laboratory of Information Security Te School of Software and Guangdong Key Laboratory of Information Security Technology Sun Yat-sen Univ Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 Chin

Digital image forensics is a new topic in recent years, which deals with the authenticity and credibility of digital images. How to recognize fake images is still a problem. This paper presents a fake image classification scheme using higher order image statistics and KBF neural networks. The features constructed on the higher order statistics reveal the intrinsic statistical features between fake images and real images. Then a classifier based on RBF neural networks is used to classify the fake and real images using these features. Experimental results demonstrated the effectiveness of the proposed scheme.

关键词： Digital Image Forensics Higher Order Autocorrelation Statistics RBF Neural Network

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A new technique for assessing the diversity of close-Pareto-optimal front

A new technique for assessing the diversity of close-Pareto-...

引用

Congress on Evolutionary Computation

作者： Sanyou Zeng Guang Chen Rui Wang Hui Li Hui Shi Lixin Ding Lishan Kang Department of Computer Science Technology Research Center for Space cience & Technology The State Key Laboratory of geological process and Mineral Resources China University of Geoscience Wuhan China School of Management Huazhong University of Science and Technology Wuhan Hubei China Statekey Laboratory of Software Engineering Wuhan University of China Wuhan Hubei China

The quality of an approximation set usually includes two aspects-- approaching distance and spreading diversity. This paper introduces a new technique for assessing the diversity of an approximation to an exact Pareto-optimal front. This diversity is assessed by using an ldquoexposure degreerdquo of the exact Pareto-optimal front against the approximation set. This new technique has three advantages: Firstly, The ldquoexposure degreerdquo combines the uniformity and the width of the spread into a direct physical sense. Secondly, it makes the approaching distance independent from the spreading diversity at the most. Thirdly, the new technique works well for problems with any number of objectives, while the widely used diversity metric proposed by Deb would work poor in problems with 3 objectives or over. Experimental computational results show that the new technique assesses the diversity well.

关键词： Evolutionary computation Approximation methods Distance measurement Optimization

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An improved Particle Swarm Optimization with adaptive jumps

An improved Particle Swarm Optimization with adaptive jumps

引用

Congress on Evolutionary Computation

作者： Hui Wang Yong Liu Zhijian Wu Hui Sun Sanyou Zeng Lishan Kang Department of Computer Science and Technoloy Nanchang Institute of Technology Nanchang China School of Computer Chain University of Geosciences Wuhan China University of Aizu Fukuoka Japan State key Laboratory of Software Engineering Wuhan University of China Wuhan China

Particle swarm optimization (PSO) has shown its fast search speed in many complicated optimization and search problems. However, PSO could often easily fall into local optima. This paper presents an improved PSO with adaptive jump. The proposed method combines a novel jump strategy and an adaptive Cauchy mutation operator to help escape from local optima. The new algorithm was tested on a suite of well-known benchmark functions with many local optima. Experimental results were compared with some similar PSO algorithms based on Gaussian distribution and Cauchy distribution, and showed better performance on those test functions.

关键词： Evolutionary computation

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Unsupervised key-phrases extraction from scientific papers using domain and linguistic knowledge

Unsupervised key-phrases extraction from scientific papers u...

引用

International Conference on Digital Information Management (ICDIM)

作者： Mikalai Krapivin Maurizio Marchese Andrei Yadrantsau Yanchun Liang Department of Information Engineering and Computer Science University of Trento Italy Department of Computer Science Belarusian State University Minsk Belarus College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University China

The domain of Digital Libraries presents specific challenges for unsupervised information extraction to support both the automatic classification of documents and the enhancement of userspsila navigation in the digital content. In this paper, we propose a combined use of machine learning techniques (i.e. Support Vector Machines) and Natural Language Processing techniques (i.e. Stanford NLP parser) to tackle the problem of unsupervised key-phrases extraction from scientific papers. The proposed method strongly depends on the robust structural properties of a scientific paper as well as on the lexical knowledge that we are able to mine from its text. For the experimental assessment we have use a subset of ACM papers in the computer science domain containing 400 documents. Preliminary evaluation of the approach shows promising result that improves - on the same data-set - on state-of-the-art Bayesian learning system KEA from a minimum 27% to a maximum 77% depending on KEA parameters tuning and specific evaluation set. Our assessment is performed by comparison with key-phrases assigned by human experts in the specific domain and freely available through ACM portal.

关键词： Data mining software libraries Navigation Machine learning Support vector machines Support vector machine classification Natural language processing Robustness computer science Bayesian methods

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