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2008 IEEE International Conference on Automation Science and engineering (CASE 2008), vol.2

作者： Maria D. Di Benedetto Alessandro D'Innocenzo Emmanuele Serra Emmanuel Witrant Department of Electrical and Computer Engineering and Center of Excellence DEWS - University of L’ Aquila L’Aquila Italy GIPSA Laboratory Université Joseph Fourier Grenoble Grenoble France Université Joseph Fourier / GIPSA-lab Grenoble France

We address a wireless networked control problem for a mine ventilation system. Ventilation control is essential for the control of the operation of a mine for safety and energy optimization. The main control objective is to guarantee safety of the closed loop system. This test-case is simple enough to be computationally tractable, and yet it exposes the main difficulties encountered when using wireless networked systems for safety-critical applications. The focus of this paper is the formal verification of the operation of a closed loop control system for the so called secondary ventilation system that ensures air flow in the chambers of the mine where extraction takes place. The secondary ventilation system is modeled conservatively in the sense that if the formal verification process provides a positive answer then the system is guaranteed to work correctly while the converse is not necessarily true. For control, we use a simple threshold scheme. The overall closed-loop system is described by a hybrid model that takes into account the effects of time-delay, transmission errors and allows the precise formulation of the safety constraints. To ensure that the formal verification process is computationally tractable, we reason in the framework of temporal logics, and apply abstraction techniques and model checking tools that we developed previously.

关键词： Bridges USA Councils Automation Conferences

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Automatic Digest Generation by Extracting Important Scenes from the Content of Presentations

Automatic Digest Generation by Extracting Important Scenes f...

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International Workshop on Database and Expert Systems Applications

作者： Hieu Hanh Le Thitiporn Lertrusdachakul Tetsutaro Watanabe Haruo Yokota Department of Computer Science Tokyo Institute of Technology Japan Department of Computer Science Graduate School of Information and Engineering Tokyo Institute of Technology Japan Application Lab Ricoh Company Ltd Application Laboratory Software R&D Group Ricoh Company Limited Japan Department of Computer Science Tokyo Institute of Technology Global Scientific Information and Computing Center Tokyo Institute of Technology

Recently, combining a video recording of a presentation along with the digital slides used in it has become popular in e-learning and presentation of archives. For users of the archives, it is useful to preview a digest of such content to grasp the atmosphere and/or an outline of the presentation. This paper proposes a method of automatic digest generation by extracting important scenes from the presentation content. The extracted scenes are chosen based on several factors such as frequency and specificity of words, scene duration and order. Finally, the effectiveness of the proposed methods are evaluated by comparing with testers' answer sets for actual lectures.

关键词： Data mining Speech Proposals Electronic learning Arrays Video recording software

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Towards an inclusive computational model of visual cortex

Towards an inclusive computational model of visual cortex

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： M. Gheiratmand H. Soltanian-Zadeh H. Khaloozadeh Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA School of Cognitive Sciences Institute for Studies Theoretical Physics and Mathematics (IPM) Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on different aspects of visual processing in the cortex, a comprehensive computational model of visual cortex is still missing. We have implemented a computational model of object recognition in ventral visual pathway in our previous work. This hierarchical model covers visual areas V1/V2, V4/PIT, and AIT sending inputs to the Prefrontal Cortex (PFC) for categorization. To extend our model, in this work, we have added a simple model of motion detection in neurons of areas V1 and MT of the dorsal stream to our previous model. This has enabled the model to perform another principal function of the visual cortex, i.e., motion perception.

关键词： Brain modeling Computational modeling Neurons Biological system modeling Object recognition Motion analysis Solid modeling Visual system computer vision Motion detection

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Pointwise Logic on Completely Distributive Lattices and Approximate Reasoning

Pointwise Logic on Completely Distributive Lattices and Appr...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Yalin Zheng Guang Yang Jing Zheng Jinsheng Xing State Key Laboratory for Intelligent Technology and Systems Department of Automation Faculty of Information Science and Technology Tsinghua University Beijing China Research Center of Intelligent Information Technology Department of Computer Science and Technology Faculty of Software Dongguan University of Science and Technology Dongguan China Research Center of Dongguan Economy Department of Economy and Commerce Dongguan University of Science and Technology Dongguan China Faculty of Mathematics and Computer Science Shanxi Normal University Linfen China Research Center of System Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China

In this paper, we propose the basic framework of point- wise topological logic on completely distributive lattices and explore approximate reasoning in it. The logic of this paper is based on pointwise characterization, therefore the pointwise conception is pervasive. We explore approximate reasoning in abstract logical framework Fl on completely distributive lattice L. We propose the structure of point- wise topological logic F TL , the structure of matching function sigma. and the structure of matching neighborhood group. We investigate approximate reasoning in pointwise topological logic F TL with matching function sigma, develop pointwise topological algorithm of simple approximate reasoning, introduce the essential characteristics of this scheme.

关键词： Lattices Fuzzy logic computer science Knowledge engineering Fuzzy systems Information technology Laboratories Intelligent systems Automation Information science

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Hybrid Artificial Intelligence Systems: Third International Workshop, HAIS 2008 Burgos, Spain, September 24-26, 2008 Proceedings - Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2008年 5271 LNAI卷 V-VI页

作者： Corchado, Emilio Abraham, Ajith Pedrycz, Witold Universidad de Burgos Escuela Politécnica Superior GICAP Research Group Norwegian University of Science and Technology Center of Excellence for Quantifiable Quality of Service 7491 Trondheim Norway University of Alberta Department of Electrical and Computer Engineering Edmonton AB T6G 2V4 Canada

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Defining and detecting bad smells of aspect-oriented software

Defining and detecting bad smells of aspect-oriented softwar...

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31st Annual International computer software and Applications Conference, COMPSAC 2007

作者： Srivisut, Komsan Muenchaisri, Pornsiri Department of Computer Engineering Center of Excellence in Software Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9780769528700

Bad Smells are software patterns that are generally associated with bad design and bad programming. They can be removed by using the refactoring technique which improves the quality of software. Aspect-Oriented (AO) software development, which involves new notions and the different ways of thinking for developing software and solving the crosscutting problem, possibly introduces different kinds of design flaws. Defining bad smells hidden in AO software in order to point out bad design and bad programming is then necessary. This paper proposes the definition of new AO bad smells. Moreover, appropriate existing AO refactoring methods for eliminating each bad smell are presented. The proposed bad smells are validated. The results show that after removing the bad smells by using appropriate refactoring methods, the software quality is increased. © 2007 IEEE.

关键词： computer software

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Feature fusion as a practical solution toward noncooperative iris recognition

Feature fusion as a practical solution toward noncooperative...

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International Conference on Information Fusion

作者： Nima Tajbakhsh Babak N. Araabi Hamid Soltanianzadeh Control & Intelligent Processing Center of Excellence School of Electrical & Computer Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel approach for iris recognition is proposed so that extracted features of NIR and VL images are fused to improve the recognition rate. When the images do not have enough quality due to focus, contrast, etc., effects of feature fusion is more pronounced. This is the situation in UTIRIS database, which is used in our experiments. Experimental results show that the proposed approach, especially in small training samples, leads to a remarkable improvement on recognition rate compared with either NIR or VL recognition.

关键词： Iris Feature extraction Discrete cosine transforms Image recognition Databases Training Humans

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Constrained optimization of nonparametric entropy-based segmentation of brain structures

Constrained optimization of nonparametric entropy-based segm...

引用

IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi Asl Hamid Soltanian-Zadeh School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

We propose a constrained, three-dimensional, nonparametric, entropy-based, coupled, multi-shape approach to segment subcortical brain structures from magnetic resonance images (MRI). The proposed method uses PCA to develop shape models that capture structural variability. It integrates geometrical relationship between different structures into the algorithm by coupling them (limiting their independent deformations). On the other hand, to allow variations among coupled structures, it registers each structure separately when building the shape models. It defines an entropy-based energy function, which is minimized using quasi-Newton algorithm. To this end, probability density functions (pdf) are estimated iteratively using nonparametric Parzen window method. In the optimization algorithm, constraints are used to improve segmentation quality. These constraints are extracted from training data. Sample results are given for the segmentation of caudate, hippocampus, and putamen, illustrating highly superior performance of the proposed method compared to the most similar methods in the literature.

关键词： Constraint optimization Brain Iterative algorithms Image segmentation Shape Couplings Magnetic resonance Magnetic resonance imaging Principal component analysis Buildings

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Introducing an Incremental Learning Method for Fuzzy Descriptor Models to Identify Nonlinear Singular Systems

Introducing an Incremental Learning Method for Fuzzy Descrip...

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2008 Mediterranean Conference on Control Automation, vol.1

作者： M. Mirmomeni C. Lucas M. Shafiee B. N. Araabi Islamic Azad University슠 Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Eng University of Tehran Tehran Iran School of Cognitive Sciences Institute of studies in theoretical Physics and Mathematics Tehran Iran Electrical Engineering Department Amirkabir University of Technology슠 Tehran Iran

Singular systems have been the subject of interest over the last two decades due to their many practical applications. But it has to be said that system identification of such system is still a challenging area because of the difficulty of identification of such systems for their complex structures. In addition, it seems that by developing a useful method for identification of singular system, one can use the useful property of such systems in describing the natural complex phenomena. This paper presents a novel methodology for identifying nonlinear singular systems from empirical data. Singular systems are idealized models for systems with slow and quick modes of change. However, their identification is a challenging problem even for the linear case. A new learning method, generalized locally linear model tree (GLoLiMoT) algorithm is introduced. The contribution of this paper is to provide a method for adjusting the parameters of fuzzy descriptor model, e.g. the splitting ratio and the standard deviation, the number of locally linear neurons or the number of linear singular systems for the consequent part in fuzzy descriptor model as well as the order of the singular system. By these modifications an accurate model of nonlinear singular system is obtained which is compared with several other methods in two case studies. Results depict the power of the proposed approach in describing nonlinear complex phenomena.

关键词： Automation Conferences

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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-...

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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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