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IEEE Workshop on Distributed Intelligent systems: Collective Intelligence and Its Applications (DIS)

作者： T. Pirttioja A. Halme A. Pakonen I. Seilonen K. Koskinen Automation Technology Laboratory Helsinki University of Technology Finland Centre of Finland VTT Technical Research Center of Finland Finland Information and Computer Systems in Systems in Helsinki University of Technology Finland

This paper studies issues concerning the application of user configurable cooperative information agents for monitoring tasks in process automation. Within this application area the amount of information gathered from the processes has been growing vastly and the supervising personnel has been minimized in the production plants. As this trend seems to keep going further, the end users need more effective information handling tools. However, the information overflow problem has also shown up in other application domains, and it is useful to discuss the similarities and differences with solutions used in these areas. This paper proposes an agent-based architecture to support active monitoring of the changes in process related data situated in various heterogeneous information sources. This approach is based on a BDI agent model, where individual user-configurable information processing modules are flexibly linked. The approach is demonstrated with an industrially inspired test scenario

关键词： Multiagent systems Application software Office automation Intelligent systems Laboratories computerized monitoring Personnel Production information processing Testing

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Multitarget Tracking Applications of the Bi-i Platform: Attention-selection, Tracking and Navigation

Multitarget Tracking Applications of the Bi-i Platform: Atte...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： Gergely Timar Csaba Rekeczky Analogic and Neural Computing Systems Laboratory of the Computer and Automation Institute of the Hungarian Academy of Sciences Budapest Hungary Information Technology Department Pazmany Peter Catholic University Budapest Hungary

A multitarget tracking framework implemented on the Bi-i platform is presented. The demonstration applications include a target tracking system with laser actuation, an attention-selection algorithm and a laser dot de... 详细信息

关键词： Navigation Target tracking Cellular neural networks Application software computer networks Laser theory Circuits and systems Circuit testing Laboratories automation

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CNNUM-Based Methods Using Deformable Contours on Smooth Boundaries

CNNUM-Based Methods Using Deformable Contours on Smooth Boun...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： Tamas Szabo Peter Szolgay Department of Image Processing and Neurocomputing Faculty of Information Technology University of Pannonia Veszprem Hungary Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In this paper two methods are presented. A CNNUM-based method is shown to quantify the displacement of the normal interhemisperic bilateral symmetry line. The method uses a deformable open contouring technique. Anothe... 详细信息

关键词： Active contours Computed tomography Magnetic resonance Anatomical structure Image segmentation Biomedical imaging Electronic mail computer networks Pixel Image resolution

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CNN Wave Computing: Theory, Architectures, Implementations and Applicaions

CNN Wave Computing: Theory, Architectures, Implementations a...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： Marco Gilli Csaba Rekeczky Bertram Shi Department of Electronics Politecnico di Turino Torino Italy Analogic and Neural Computing Systems Laboratory of the Computer and Automation Information Technology Department Institute of the Hungarian Academy of Sciences Budapest Hungary Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong China

A cellular neural/nonlinear network (CNN) is any spatial arrangement of mainly locally coupled cells, where each cell is a dynamical system which has an input, an output and a state that evolves according to some prescribed dynamical laws. Since the CNN was first introduced in 1988, research in this field has developed rapidly. The goal of this tutorial is to provide participants with a snapshot of the current state of the art and research trends. It covers the broad multi-disciplinary areas of CNN research, from theoretical aspects to applications. The presenters have experience ranging from theoretical analysis of CNN dynamics, VLSI implementation and system level applications

关键词： Cellular neural networks computer architecture computer networks Very large scale integration Analog computers computer interfaces computer vision Biological system modeling Nonlinear dynamical systems computer industry

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Hierarchical modelling in biology: Systematic building of limb models

Hierarchical modelling in biology: Systematic building of li...

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作者： Fazekas, C.S. Kozmann, G.Y. Hangos, K.M. Department of Information Systems University of Veszprém Veszprém Hungary Research Institute for Technical Physics and Materials Sciences Department of Biomedical Engineering Budapest Hungary Computer and Automation Research Institute Systems and Control Laboratory Budapest Hungary

ISBN: (纸本)008045108X

A multi-level model, that provides a hierarchically structured description of a complex, multi-scale limb system is proposed in this paper for predicting and analyzing movement patters generated by various activation signals. The levels, the sub-models on each level and their interconnections are developed and described following a systematic modelling procedure. The computational properties (degree of freedom and differential index) of the developed model have been analyzed and a sub-model has been transformed to meet the index-one requirement for solving the resulting differential algebraic equation (DAE) model by standard methods implemented in MATLAB. The model is extensively verified against engineering expectations using parameter values found in the literature, and a good agreement was found. Parameter sensitivity analysis has also been performed. Copyright © 2005 IFAC.

关键词： Hierarchical systems

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Reactive and deliberative control and cooperation in multi-agent system based process automation

Reactive and deliberative control and cooperation in multi-a...

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2005 IEEE International Symposium on Computational Intelligence in Robotics and automation CIRA 2005

作者： Seilonen, Ilkka Koskinen, Kari Pirttioja, Teppo Appelqvist, Pekka Halme, Aarne Information and Computer Systems in Automation Helsinki University of Technology P.O.Box 5500 02015 TKK Espoo Finland Automation Technology Laboratory Helsinki University of Technology P.O.Box 5500 02015 TKK Espoo Finland

An approach to intelligent process automation based on a society of BDI-agents is presented in this paper. According to this approach a higher-level multi-agent systems based automation layer supervises an ordinary process automation system. The purpose of the agent layer is to monitor the operation of the lower-level automation system and semi-autonomously reconfigure its control logic when needed. The agent layer operates as a multi-agent system consisting of BDI-agents, which cooperatively create and run reconfiguration sequences on the ordinary automation system in order to adapt its control logic to various situations. The adaptation process may take place both in reactive and deliberative fashion. In this way the approach aims to increase the flexibility and responsiveness properties of the automation system. The approach is demonstrated with a laboratory test process where process startup and fault recovery experiments have been performed. Results from the experiments are described. © 2005 IEEE.

关键词： Multi agent systems

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Adaptive nonlinear auto-associative modeling through manifold learning

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9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005

作者： Zhang, Junping Li, Stan Z. Intelligent Information Processing Laboratory Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences China National Laboratory of Pattern Recognition Center for Biometrics and Security Research Institute of Automation Beijing 100080 China

ISBN: (纸本)3540260765

We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separately and recognition thereby. Unlike traditional supervised manifold learning algorithm, the proposed ANAM algorithm has several advantages: 1) it implicitly embodies discriminant information because the suboptimal parameters of ANAM are determined based on error rate of the validation set. 2) it avoids the curse of dimensionality without loss accuracy because recognition is completed in the original space. Experiments on character and digit databases show that the advantages of the proposed ANAM algorithm. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Learning systems

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Multi-agent based information access services for condition monitoring in process automation

Multi-agent based information access services for condition ...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： T. Pirttioja A. Pakonen I. Seilonen A. Halme K. Koskinen Automation Technology Laboratory Helsinki University of Technology Finland VTT Industrial Systems Espoo Finland Information and Computer Systems in Automation Helsinki University of Technology Finland

This paper studies issues concerning the application of goal-oriented information agents to condition monitoring tasks in process automation. In the presented approach, an agent-based information access layer is operating as a mediator for various types of process-related information. The agent system may be seen as an active partner for human users in this information intensive application domain. In the future, more and more automation related information will be available in electronic form. Physical sensors provide not only measurements but also reliability information, and numerous configuration details are available in electronic form. The challenge is to integrate as much of the available information as possible, and to automate the processing of this information to enable easy decision-making for end users.

关键词： Condition monitoring automation Humans Paper technology Laboratories computer industry Application software Decision making computerized monitoring Ontologies

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HIERARCHICAL MODELLING IN BIOLOGY: SYSTEMATIC BUILDING OF LIMB MODELS

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IFAC Proceedings Volumes 2005年第1期38卷 49-54页

作者： Cs. Fazekas Gy. Kozmann K.M. Hangos Department of Information Systems University of Veszprém Veszprém Hungary Department of Biomedical Engineering Research Institute for Technical Physics and Materials Sciences Budapest Hungary Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary

关键词： Biomedical system model hierarchical system muscle tendon aponeurosis pennation sarcomere

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Supervised tensor learning

Supervised tensor learning

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IEEE International Conference on Data Mining (ICDM)

作者： Dacheng Tao Xuelong Li Weiming Hu S. Maybank Xindong Wu School of Computer Science and Information Systems Birkbeck College University of London UK National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China Department of Computer Science University of Vermont USA

This paper aims to take general tensors as inputs for supervised learning. A supervised tensor learning (STL) framework is established for convex optimization based learning techniques such as support vector machines (SVM) and minimax probability machines (MPM). Within the STL framework, many conventional learning machines can be generalized to take n/sup th/-order tensors as inputs. We also study the applications of tensors to learning machine design and feature extraction by linear discriminant analysis (LDA). Our method for tensor based feature extraction is named the tenor rank-one discriminant analysis (TR1DA). These generalized algorithms have several advantages: 1) reduce the curse of dimension problem in machine learning and data mining; 2) avoid the failure to converge; and 3) achieve better separation between the different categories of samples. As an example, we generalize MPM to its STL version, which is named the tensor MPM (TMPM). TMPM learns a series of tensor projections iteratively. It is then evaluated against the original MPM. Our experiments on a binary classification problem show that TMPM significantly outperforms the original MPM.

关键词： Tensile stress Machine learning Support vector machines Supervised learning Data mining Support vector machine classification computer science Minimax techniques Feature extraction Linear discriminant analysis

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