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An agent-based architecture for knowledge management in context-aware business processes

An agent-based architecture for knowledge management in cont...

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International Conference on Computer Supported Cooperative Work in Design

作者： De C. Gatti, Leonardo A. Santoro, Flávia Maria Nunes, Vanessa T. NP2TEC - Research and Practice Group in Information Technology Department of Applied Informatics Federal University of the State of Rio de Janeiro UNIRIO Rio de Janeiro Brazil COPPE - Systems Engineering and Computer Science Program Federal University of Rio de Janeiro UFRJ Rio de Janeiro Brazil

ISBN: (纸本)9781424467631

The main knowledge management challenges are to capture, store and reuse contextual knowledge generated during interactions that occur daily in an organization. In this paper, we propose an activity context-aware architecture to support knowledge management in working processes. The required features for this architecture are processing, reasoning and sharing contextual knowledge involving information about activities performed. We also present results from evaluation of our proposal - A-CoBrA - for a specific domain. © 2010 IEEE.

关键词： Knowledge management

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Analysis and Identification Gamelan Bonang Sound Spectrum

Analysis and Identification Gamelan Bonang Sound Spectrum

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International Conference on Computational Intelligence, Modelling and Simulation (CSSIM)

作者： Muhammad Nur Latief Ford Lumban Gaol Bambang Heru Iswanto Graduate Program in Informatics Engineering Bina Nusantara University Jakarta Indonesia Bina Nusantara University Jakarta Indonesia Physics Department Universitas Negeri Jakarta Jakarta Indonesia

In this research will show a method for sound-recognition with artificial neural network back propagation concept. The artificial neural network use sigmoid activation function to all layer. Steps to the extraction, first, divide into ten component, second do the Fast Fourier Transform, third continue with Power Spectral Density, fourth count the average. The end result show that the pattern will recognize by the Artificial Neural Network. Extraction performed, as well as Fourier transform, and also calculate the power density, and then process them with artificial neural networks, allows the system to do the identification of voice data Gamelan Bonang using In this research will show a method for sound-recognition with artificial neural network back propagation concept.

关键词： Artificial neural networks Training Neurons Backpropagation Frequency domain analysis Fourier transforms Transfer functions

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Metabolomics as molecular analysis tool in cell culture engineering

Metabolomics as molecular analysis tool in cell culture engi...

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作者： Vernardis, S.I. Chrysanthopoulos, P.K. Goudar, C.T. Klapa, M.I. Foundation for Research and Technology-Hellas Metabolic Engineering and Systems Biology Laboratory Institute of Chemical Engineering and High-Temperature Chemical Processes Patras GR- 265 04 Greece Cell Culture Development Global Biological Development Bayer HealthCare 800 Dwight Way Berkeley CA 94710 United States Interdepartmental Graduate Program in Informatics in Life Sciences Medical School University of Patras Greece Departments of Chemical and Biomolecular Engineering and Bioengineering University of Maryland College Park MD 20742 United States

ISBN: (纸本)9783902661708

So far, cell culture engineering has used the high-throughput transcriptional and more recently protein profiling techniques attempting to further understand and resolve significant issues regarding the cell culture performance and its optimization. At the metabolic level, flux analysis has been used to monitor changes in the metabolic state that could affect the successful outcome of cell cultures. Metabolomics, referring to the simultaneous quantification of the (relative) concentration of the free small metabolites, is the most recently introduced high-throughput method for the measurement of the metabolic fingerprint of a biological system. Considering the role of metabolism in the context of the overall cellular function, it is easily understandable why quantifying a complete and accurate metabolomic profile is foreseen to have a major positive impact in cell culture engineering research. We will present application of Gas Chromatorgaphy-Mass Spectrometry metabolomics to monitor and analyze mammalian cell culture systems. Specifically, two bioreactor processes will be discussed in which baby hamster kidney cells were cultivated in high-cell density perfusion reactors at both laboratory and manufacturing scales and samples were analyzed over the course of the cultivation. Metabolomics enabled the differentiation between cell cultures based on bioreactor type, and stage of cell growth. Multivariate statistical analysis enabled the identification of the metabolites whose change in concentration was characteristic of the modification in any of these macroscopic parameters. The acquired results support the usefulness of metabolomics as a molecular analysis tool in cell culture engineering. © 2010 IFAC.

关键词： Bioreactors

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A fuzzy inference system to determine the number of clones in the clonal selection algorithm

A fuzzy inference system to determine the number of clones i...

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World Congress on Nature & Biologically Inspired Computing (NaBIC)

作者： Luiz Antonio Carraro Leandro Nunes de Castro Angelita Maria de Ré Computer and Informatics Faculty & Graduate Program in Electrical Engineering Mackenzie University São Paulo Brazil Computer Science Department State University of West-Center Parana Guarapuava Brazil

Artificial Immune Systems (AISs) are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the binding of antigens and antibodies. As an immune response can be elicited even when the binding between an antigen and an antibody is not perfect, an approximate binding might suffice, and a Fuzzy Logic mechanism might be the most appropriate mechanism to control such process. This paper presents a novel hybrid model based on concepts of Immune and Fuzzy Systems with applications to pattern recognition problems. The preliminary results obtained here suggest the proposed model is a promising pattern recognition tool.

关键词： Variable speed drives Animals

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Principles of Bioimage informatics: Focus on Machine Learning of Cell Patterns

Principles of Bioimage Informatics: Focus on Machine Learnin...

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Workshop of the BioLINK Special Interest Group on Linking Literature, Information and Knowledge for Biology

作者： Coelho, Luis Pedro Glory-Afshar, Estelle Kangas, Joshua Quinn, Shannon Shariff, Aabid Murphy, Robert F. Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology United States Lane Center for Computational Biology Carnegie Mellon University United States Center for Bioimage Informatics Carnegie Mellon University United States Department of Biological Sciences Carnegie Mellon University United States Machine Learning Department Carnegie Mellon University United States Department of Biomedical Engineering Carnegie Mellon University United States

ISBN: (纸本)9783642131301

The field of bioimage informatics concerns the development and use of methods for computational analysis of biological images. Traditionally, analysis of such images has been done manually. Manual annotation is, however, slow, expensive, and often highly variable from one expert to another. Furthermore, with modern automated microscopes, hundreds to thousands of images can be collected per hour, making manual analysis infeasible. This field borrows from the pattern recognition and computer vision literature (which contain many techniques for image processing and recognition), but has its own unique challenges and tradeoff's. Fluorescence microscopy images represent perhaps the largest class of biological images for which automation is needed. For this modality, typical problems include cell segmentation, classification of phenotypical response, or decisions regarding differentiated responses (treatment vs. control setting). This overview focuses on the problem of subcellular location determination as a running example, but the techniques discussed are often applicable to other problems.

关键词： Pattern recognition

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Enhanced Wireless Sensor Network setup strategy supported by intelligent software agents

Enhanced Wireless Sensor Network setup strategy supported by...

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IEEE SENSORS

作者： Edison Pignaton de Freitas Tales Heimfarth Ivayr Farah Netto Alex Guimarães Cardoso de Sá Carlos Eduardo Pereira Armando Morado Ferreira Flávio Rech Wagner Tony Larsson IDE Halmstad University Halmstad Sweden Institute of Informatics Federal University of Rio Grande do Sul Porto Alegre Brazil Federal University of Lavras Lavras Brazil Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

A well know problem in the Wireless Sensor Network (WSN) research area is the usage of appropriate strategies to setup the sensor nodes such that they may accomplish sensing missions. This problem refers to the selection of appropriate nodes to perform the different tasks required to the missions' accomplishment and may be thus characterized as an instance of the task and resource allocation problem. Traditional approaches consider pre-planned strategies, which are not flexible to deal with changes in the network and environment operating conditions. This paper presents an enhanced agent-oriented strategy, which consists of a usage of mobile intelligent agents to disseminate missions and nodes' information over the network, as well as stationary software agents installed in the sensor nodes to provide advanced reasoning apparatus for decision making purposes. The proposed enhancement complements the original agent-based approach with robustness features required to overcome extreme adverse conditions in which an ordinary WSN presents poor results. Results from simulations provide evidences of the efficiency of the complete enhanced approach.

关键词： Wireless sensor networks Software agents Temperature sensors Conferences Atmosphere Accuracy

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An efficient ICA approach based on neural network framework for biomedical applications

An efficient ICA approach based on neural network framework ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Yue-Der Lin Chih-Yu Hsu Hung-Yun Chen Kuo-Kun Tseng Department of Automatic Control Engineering and Master Program of Biomedical Informatics and Biomedical Engineering Feng Chia University FCU Taichung Taiwan Department of Information and Communication Engineering Chao Yang University of Technology Taichung Taiwan Department of Automatic Control Engineering Feng Chia University FCU Taichung Taiwan Department of Computer Science and Engineering Hung Kuang University Taichung Taiwan

The paper developed a block-wise approach for ICA algorithms which can improve the computational efficiency of ICA without the degradation of performance for the separation of biomedical signals. Source signals including electrocardiogram (ECG), electromyogram (EMG) and 60-Hz sinusoid are linearly mixed for experimental tests. The mean-square errors (MSE) between the original sources and the separated signals are calculated for the evaluation of separation performance. These results demonstrated that the proposed block-wise approach can achieve the desired separation performance of signals in a more efficient way.

关键词： Equations Algorithm design and analysis Electrocardiography Electromyography Source separation Iterative algorithm Indexes

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UAV relay network to support WSN connectivity

UAV relay network to support WSN connectivity

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International Conference on Ultra Modern Telecommunications and Workshops (ICUMT)

作者： Edison Pignaton de Freitas Tales Heimfarth Ivayr Farah Netto Carlos Eduardo Lino Carlos Eduardo Pereira Armando Morado Ferreira Flávio Rech Wagner Tony Larsson IDE Halmstad University Halmstad Sweden Institute of Informatics Federal University of Rio Grande do Sul Porto Alegre Brazil Computer Science Department Federal University of Lavras Lavras Brazil Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

An important problem in Wireless Sensor Networks (WSN) is the occurrence of failures that lead to the disconnection of parts of the network, compromising the final results achieved by the WSN operation. A way to overcome such problem is to provide a reliable connection to support the connectivity via other types of nodes that communicate with the sensor nodes. This paper proposes the usage of a network composed by Unmanned Aerial Vehicles (UAVs) as a relay network to guarantee the delivery of data produced by WSN nodes on the ground to the users. Results from simulations of the proposed technique are provided and discussed.

关键词： Base stations Unmanned aerial vehicles Mobile communication Wireless sensor networks Peer to peer computing Mobile computing Relays

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Multivariable nonlinear boiler power plant identification through neural networks and Particle Swarm Optimization approaches

Multivariable nonlinear boiler power plant identification th...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Fábio A. Guerra Helon V. H. Ayala André E. Lazzaretti Marcio R. Sans Leandro S. Coelho Cesar A. Tacla Eletroelectronics Department (DPEE) Electrical System Division (DVSE) Centro Politécnico da UFPR LACTEC-Institute of Technology for Development Curitiba Parana Brazil Industrial and Systems Engineering Graduate Program (LAS/PPGEPS) Pontifical Catholic University of Paraná Curitiba Parana Brazil Graduate Program in Eletrical Engineering and Industrial Informatics (CPGEI) Federal University of Technology Parana Curitiba Parana Brazil

The identification of nonlinear systems with artificial neural networks models has been successfully used in many applications. Most processes in industry are characterized by nonlinear and time-varying behavior. In this context, the identification of mathematical models for nonlinear systems is vital in many fields of engineering. The Radial Basis Function Neural Network (RBF-NN) is a powerful approach for nonlinear identification and can be improved using Particle Swarm Optimization (PSO) approaches. This paper presents a multivariable nonlinear system identification using RBF-NN combined with standard PSO and Constriction Factor PSO (CFPSO) approaches in order to determine the RBF-NN parameters. RBF-NN is considered to be a good choice for black-box modeling problems due to its rapid learning capacity and, therefore, has been applied successfully to nonlinear time series modeling and nonlinear identification. On the other hand, PSO was inspired by the choreography of bird flocks and fish schools and can be seen as a distributed behavior algorithm that performs multidimensional search. Furthermore, promising simulation results from performance analysis of the proposed RBF-NN with PSO training approaches are presented and discussed in this paper showing promising results.

关键词： Artificial neural networks Boilers Neurons Modeling Power generation Optimization Nonlinear systems

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Empirical Studies on Application of Genetic Algorithms and Ant Colony Optimization for Data Clustering

Empirical Studies on Application of Genetic Algorithms and A...

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Computer Science Society (SCCC) International Conference Chilean FLAGGED

作者： Thelma Elita Colanzi Wesley Klewerton Guez Assunção Aurora Trinidad Ramirez Pozo Ana Cristina B. Kochem Vendramin Diogo Augusto Barros Pereira Computer Science Postgraduate Program Federal University of Paraná (UFPR) Curitiba Paraná Brazil Graduate School of Electrical Engineering and Computer Science (CPGEI) Federal Technological University of Paraná (UTFPR) Curitiba Paraná Brazil Informatics Department (DAINF)

Cluster analysis is used in several research areas to classify data sets in groups by their similar characteristics. Metaheuristic-based techniques, such as Genetic Algorithms (GAs) and Ant Colony Optimization (ACO), have been applied in order to increase the clustering algorithm performance. GA and ACO-based clustering algorithms are capable of efficiently and automatically forming natural groups from a pre-defined number of clusters. This paper presents a GA and an ACO algorithm to the clustering problem. Both algorithms were refined using local search in order to improve the clustering accuracy. The results are compared on numeric UCI databases.

关键词： Clustering algorithms Search problems Equations Mathematical model Gallium Genetic algorithms Memetics

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