2006 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications

12-14 July 2006

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Displaying Results 1 - 25 of 38
  • [Front cover]

    Publication Year: 2006, Page(s): C1
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  • Copyright page

    Publication Year: 2006, Page(s): II
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  • Message from the Chairpersons

    Publication Year: 2006, Page(s):III - IV
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  • Table of contents

    Publication Year: 2006, Page(s):V - VII
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  • Author index

    Publication Year: 2006, Page(s): IX
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  • [Breaker page]

    Publication Year: 2006, Page(s): 1
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  • A Soft Computing-Based Measurement System for Medical Applications in Diagnosis of Cardiac Arrhythmias by ECG Signals Analysis

    Publication Year: 2006, Page(s):2 - 7
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (7075 KB) | HTML iconHTML

    In this paper a telemedicine application in support of heart patients homecare is proposed. Diagnosis of cardiac arrhythmias typically requires heart monitoring for 24 or 48 consecutive hours, so it causes long waiting lists in hospital. In this sight the authors have projected an user-friendly virtual assistant able to acquire and analyze patient ECG signals by soft computing procedures. The syst... View full abstract»

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  • [Breaker page]

    Publication Year: 2006, Page(s): 8
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  • Morphological Neural Networks for Localization and Mapping

    Publication Year: 2006, Page(s):9 - 14
    Cited by:  Papers (1)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6657 KB) | HTML iconHTML

    Morphological associative memories (MAM) have been proposed for image denoising and pattern recognition. We have shown that they can be applied to other domains, like image retrieval and hyperspectral image unsupervised segmentation. In both cases the key idea is that morphological auto associative memories (MAAM) selective sensitivity to erosive and dilative noise can be applied to detect the mor... View full abstract»

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  • Modeling Technology for One Class of Multi-Agent Systems with Automata Based Programming

    Publication Year: 2006, Page(s):15 - 20
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6338 KB) | HTML iconHTML

    The technology of modeling of one class of multi-agent systems with automata based programming is proposed in the paper. The technology is illustrated on the example of system of interacting drone flying objects creation. UniMod - a tool intended for supporting automata based programming is used for building a control system for each flying object. UniMod also supports the concept of "executable U... View full abstract»

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  • Multiple Waypoint Path Planning for a Mobile Robot using Genetic Algorithms

    Publication Year: 2006, Page(s):21 - 26
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (7415 KB) | HTML iconHTML

    This investigation developed a MATLAB program, based on genetic algorithms that generated an optimal (shortest distance) path plan for a mobile robot to visit all of the specified waypoints without colliding with the known obstacles. The designed genetic algorithm path planner was shown to accomplish this task and produce superior results when compared against a full search path planner. Next, it ... View full abstract»

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  • [Breaker page]

    Publication Year: 2006, Page(s): 27
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  • A Computational Intelligence Application for Environmental Measurements by a DSP-Based Smart Web-Sensor

    Publication Year: 2006, Page(s):28 - 33
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (7832 KB) | HTML iconHTML

    In this paper the authors propose an intelligent and stand-alone measurement instrument for environmental monitoring and control applications. By an embedded computational intelligence technique, the instrument can acquire and test data according to available information. The projected system consists in a smart Web-sensor sensing the electromagnetic field exposure levels. The sensor equipment inc... View full abstract»

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  • Hall Effect Sensor and Artificial Neural Networks Applied on Diagnosis of Broken Rotor Bars in Large Induction Motors

    Publication Year: 2006, Page(s):34 - 39
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4237 KB) | HTML iconHTML

    This paper presents the use of the neural networks techniques in order to help on diagnosis of broken bars in large induction motors in real time. The obtained signal of the Hall effect sensor is applied in an artificial neural network to identify a fault and to estimate the number of broken bars. Simulation results are presented from the model implemented in the SIMULINK/MATLAB tool View full abstract»

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  • Computational intelligence techniques to detect toxic gas presence

    Publication Year: 2006, Page(s):40 - 44
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6013 KB) | HTML iconHTML

    The detection of toxic gas in industrial environments (performed by means of an array of low-cost on-chip chemical sensors) is a valuable approach to increase daily safety. The aim of this paper is to critically discuss the use of a-priori knowledge in the design of gas sensor systems implementing computational intelligence techniques for signal processing and gas presence detection. The availabil... View full abstract»

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  • [Breaker page]

    Publication Year: 2006, Page(s): 45
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  • Hybrid filtering for map-aided vehicle navigation

    Publication Year: 2006, Page(s):46 - 50
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5429 KB) | HTML iconHTML

    In order to provide an accurate positioning, the land-vehicle navigation applications are based on GPS. The addition of a digital road map allows to locate the vehicle continuously and helps the driver to get the best path. These systems are usually enhanced with dead reckoning sensors due to GPS outages in urban areas especially. For instance, the odometer sensors can be used to correct the vehic... View full abstract»

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  • Target Registration Correction Using the Neural Extended Kalman Filter

    Publication Year: 2006, Page(s):51 - 56
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5141 KB) | HTML iconHTML

    Target registration can be considered a problem in aligning the reports of two sensor platforms. It is often a result of sensor misalignment and navigation errors. One technique to alleviate these errors is to re-compute continually a correction with each report. In this paper, a different approach using a modification of an adaptive neural network technique is proposed and developed. The techniqu... View full abstract»

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  • Measurement and Comparison of Non-verbal Behavior and Cognitive Behavior in Human Resource Management - Application in Sales Recruitment

    Publication Year: 2006, Page(s):57 - 62
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6432 KB) | HTML iconHTML

    Emotions form an important component of human behavior and decision making. In this paper we employ image processing and soft computing techniques to design and implement emotional state profiling of a sales candidate while they provide psychological inputs related to their selling behavior to an intelligent sales recruitment and benchmarking system. This research is part of a larger effort aimed ... View full abstract»

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  • [Breaker page]

    Publication Year: 2006, Page(s): 63
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  • Management of Complex Dynamic Systems based on Model-Predictive Multi-objective Optimization

    Publication Year: 2006, Page(s):64 - 69
    Cited by:  Papers (9)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (8265 KB) | HTML iconHTML

    Over the past two decades, model predictive control and decision-making strategies have established themselves as powerful methods for optimally managing the behavior of complex dynamic industrial systems and processes. This paper presents a novel model-based multi-objective optimization and decision-making approach to model-predictive decision-making. The approach integrates predictive modeling b... View full abstract»

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  • An Intelligent System for Decentralized Load Management

    Publication Year: 2006, Page(s):70 - 74
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5522 KB) | HTML iconHTML

    This work proposes a model of an intelligent short term demand side management system based on a MAS. The system is designed to avoid peaks of power request greater than a given threshold and to give maximum comfort to user. The proposed system is composed of a distributed network of processing nodes (PN). Each PN hosts one agent and it is able to manage a single socket tap allowing or disallowing... View full abstract»

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  • A Novel Ontology for Sensor Networks Data

    Publication Year: 2006, Page(s):75 - 79
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5109 KB) | HTML iconHTML

    Sensor networks have seen an exponential growth in the last few years. They involve deploying a large number of small sensing nodes for capturing environmental data. Searching such networks is limited by two major constraints: scalability and precision. We argue that the key to enabling scalable and precise sensor information search is to define an ontology that associates sensor information taxon... View full abstract»

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  • [Breaker page]

    Publication Year: 2006, Page(s): 80
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  • A Training Methodology for Neural Networks Noise-Filtering when no Training Sets are available for Supervised Learning

    Publication Year: 2006, Page(s):81 - 85
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4865 KB)

    Noise filtering is considered one of the main applications of neural networks due to its importance in a wide range of scientific and technological areas. The standard methodology needs to obtain first an accurate measure of the desired signal, which is a must in supervised learning. Nevertheless, in some areas these data sets are rarely available, nor can be determined noise function although its... View full abstract»

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