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International Conference on Image, Vision and Computing (ICIVC)

作者： Yan Li Li Du Dept. Computer Liaoning Equipment Manufacturing Vocational and Technical College Shenyang China Dept. Control Science and Engineering Shenyang University Shenyang China

ISBN: (纸本)9781538649923

Instantaneous frequency is a primary parameter used for analyzing vibration signals of rolling bearings under harsh working conditions, which contains rich information besides the rotating speeds of the shaft. Such vibration signals exhibits characteristics of non-stationary and multi-components. The generalized demodulation time-frequency analysis approach is a novel signal processing method, which is suitable for processing non-stationary and multi-component signals. Its novelty lies in that the signal whose time-frequency distributions are curved paths can be transformed into that whose time-frequency distributions are linear paths paralleling time axis by using generalized demodulation. In this paper, to deal with the vibration signals under variable working speed condition, the generalized demodulation as well as a band-pass filter is used to separate the interested component from original vibration signal. The analysis results demonstrate the validity of the proposed approach.

关键词： Time-frequency analysis Demodulation Vibrations Rolling bearings Frequency estimation Transforms

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EEG Multi-Objective Feature Selection Using Temporal Extension

EEG Multi-Objective Feature Selection Using Temporal Extensi...

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IEEE International Conference on Intelligent computer Communication and Processing (ICCP)

作者： Lavinia Ferariu Corina Cîmpanu Tiberius Dumitriu Florina Ungureanu Dept. of Automatic Control and Appplied Informatics Gheorghe Asachi Technical University of Iaşi Iaşi Romania Dept. of Computer Engineering Gheorghe Asachi Technical University of Iaşi Iaşi Romania

Nowadays Electroencephalogram (EEG) devices allow the recording of signals that can be used to extract information necessary to identify different types of cognitive processes. In EEG classification, Feature Selection (FS) represents a pivotal phase, as these problems request the processing of a large amount of high-dimensional patterns. In this paper, FS has been solved by an embedded multi-objective genetic optimization procedure which evolves a population of potential solutions (subsets of features), subject to the simultaneous minimization of the misclassification ratio and number of selected attributes. Random Forests (RF) classifiers are adopted, due to their fast training and their compatibility with spread classes of very diverse patterns. The main contribution presented in this paper consists in introducing an inertial behavior to feature extraction. The available feature set is extended with features from previous time frames, and FS is performed on this extended set. In this context, the experimental analysis illustrates the impact of the temporal extension on FS. Additionally, two enhancements are proposed for the multi-objective optimization, to support an effective Pareto-ranking of the solutions in the expanded exploration search space. Thus, the number of trees in the embedded RF classifier is gradually increased, for reducing the computational load requested for the evaluation of the misclassification ratio, without impeding the exploration. Also, the preference for the minimization of misclassifications is set by introducing a dynamic objective function for describing the parsimony of the selected subset of attributes. The proposed FS is experimentally demonstrated on EEG data collected during mathematical tasks of gradual complexities.

关键词： Electroencephalography Feature extraction Radio frequency Encoding Task analysis Genetic algorithms Optimization

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Conducting Online Lab Experiments with Blockly

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IFAC-PapersOnLine 2017年第1期50卷 13474-13479页

作者： Galan, Daniel Heradio, Ruben de la Torre, Luis Dormido, Sebastian Esquembre, Francisco Dept. of Computer Science and Automatic Control Universidad Nacional de Educación a Distancia Juan del Rosal 16 MadridE-28040 Spain Dept. of Software Engineering and Computer Systems Universidad Nacional de Educación a Distancia Juan del Rosal 16 MadridE-28040 Spain Dept. of Mathematics Universidad de Murcia Campus de Espinardo MurciaE-30071 Spain

Laboratory experimentation plays an essential role in control education. To reduce the high costs of maintaining apparatus in traditional labs and to support distance and blended learning, online laboratories are used as a possible alternative to conventional hands-on labs. In these labs it is often desirable to allow students to define their own experiments. This paper presents the definition and implementation of a generic experimentation language for conducting automatic experiments on existing online laboratories. The main objective is to use an online lab, created independently, as a component in which users can perform experiments. To achieve it, authors present the Experiment Application. It is composed by Blockly, to define and design the experiments, and Google Chart, review and visualize the experiment results. This tool offers benefits to students, teachers and, even, lab designers. For the moment, it can be used with any existing lab or simulation created with the authoring tool Easy Java(script) Simulations. Since there are repositories with hundreds of free available labs created with this tool, the potential applicability of the described tool is considerable. To illustrate the utility of the Experiment Application a very well-known system is used: the Simple Harmonic Oscillator system. © 2017

关键词： computer software Experiments Research laboratories Teaching Blockly Easy java(script) Simulations Experimentation Language Javascript Remote laboratories Virtual laboratories

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Detection and Tracking of Astral Microtubules in Fluorescence Microscopy Images

Detection and Tracking of Astral Microtubules in Fluorescenc...

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IEEE International Conference on Image Processing

作者： Joshua Levine Marco Grangetto Marilena Varrecchia Gabriella Olmo Computer Science dept. Università degli Studi di Torino Torino Italy Dept. of Control and Computing Engineering Politecnico di Torino Torino Italy

In this paper we explore detection and tracking of astral micro-tubules, a sub-population of microtubules which only exists during and immediately before mitosis and aids in the spindle orientation by connecting it to the cell cortex. Its analysis can be useful to determine the presence of certain diseases, such as brain pathologies and cancer. The proposed algorithm focuses on overcoming the problems regarding fluorescence microscopy images and microtubule behaviour by using various image processing techniques and is then compared with three existing algorithms, tested on consistent sets of images.

关键词： Microscopy Standards Image segmentation Signal to noise ratio Heuristic algorithms Fluorescence Drugs

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Streaming Process Discovery for Lambda Architecture-based Process Monitoring Platform

Streaming Process Discovery for Lambda Architecture-based Pr...

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International Scientific and Technical Conference on computer science and Information Technologies

作者： Anatoliy Batyuk Volodymyr Voityshyn Dept. of Automated Control Systems Institute of Computer Science and Information Technologies Lviv Polytechnic National University Lviv Ukraine

Having precise information about how business processes are performed in real-life is an important competitive advantage for a modern company. The digital footprint left by processes in IT systems can be transformed to event data for further analysis by process mining techniques. One of the biggest challenge of process mining is to deal with streaming event data and provide operational support for the on-going processes. Current paper is devoted to a streaming process discovery algorithm implemented by the authors upon a near real-time process monitoring platform which is based on the lambda architecture.

关键词： Process mining Streaming process discovery Lambda architecture Heuristic Miner Event data Event logs XES Digital footprint

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Fast bird direction-of-arrival estimation using an isotopic array of microphones 26

Fast bird direction-of-arrival estimation using an isotopic ...

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26th International Congress on Sound and Vibration, ICSV 2019

作者： Hudon, R.E. Yao, K. Taylor, C.E. Yu, K. Hedley, R.W. Electrical and Computer Engineering Dept UCLA Los AngelesCA United States Department of Ecology and Evolutionary Biology UCLA Los AngelesCA United States Dept. of Control Science and Engineering Zhejiang University Hanzhou China Erin Bayne Laboratory University of Alberta EdmontonAB Canada

ISBN: (纸本)9781999181000

Various wide-band multiple source detection and direction-of-arrival (DOA) estimation using array methods have been proposed. For multiple wide-band 2D source DOA estimation, an Approximate Maximum-Likelihood (AML) method was proposed with later extension to 3D applications. AML is an iterative method that is computationally demanding, so must typically be performed off-line. Now we propose a new, analytic, method to separate and localize overlapping sources that is much faster and less computationally demanding. We used the k-th subband of the cross-covariance matrix Ck of H-frame of a contiguous array of N sensors data to perform an eigen-decomposition [Vk, Dk ] = eig(Ck ) . The ratios of the larger eigenvalues in Dk relative to the smallest eigenvalue provide a possible detection criterion for various sources and the corresponding eigenvectors can be used to estimate the DOA's of multiple sources. The phase differences among the sensors are used to analytically obtain the DOA without needing any optimization operations. Simulations of field measured array data are used to confirm the proposed scheme © Proceedings of the 26th International Congress on Sound and Vibration, ICSV 2019. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Hybrid petri net model based decision support system

arXiv

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arXiv 2017年

作者： Culita, Janetta Caramihai, Simona Munteanu, Calin Politehnica" University of Bucharest Dept. of Automatic Control and Computer Science

It is well known that the complex system operation requires the use of new scientific tools and computer simulation. This paper presents a modular approach for modeling and analysis of the complex systems (in communication or transport systems area) using Hybrid Petri nets. The performance evaluation of the hybrid model is made by a simulation methodology that allows building up various functioning scenario. A Decision Support System based on the above mentioned methodologies of modeling and analysis will be designed for performance evaluation and time optimization of large scale communication and/or transport systems. Copyright © 2017, The Authors. All rights reserved.

关键词： Decision support systems

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A cooperative enterprise agent based control architecture

arXiv

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arXiv 2017年

作者： Caramihai, Simona Dumitrache, Ioan Stanescu, Aurelian Culita, Janetta Politehnica University of Bucharest Dept. of Automatic Control and Computer Science

The paper proposes a hierarchical, agent-based, DES supported, distributed architecture for networked organization control. Taking into account enterprise integration engineering frameworks and business process management techniques, the paper intends to apply control engineering approaches for solving some problems of coordinating networked organizations, such as performance evaluation and optimization of workflows. Copyright © 2017, The Authors. All rights reserved.

关键词： Enterprise resource management

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A DECISION SUPPORT SYSTEM FOR COMMUNICATION NETWORK ANALYSIS BASED ON HYBRID PETRI NET MODELS

arXiv

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arXiv 2017年

作者： Caramihai, Simona Iuliana Munteanu, Călin Culiţă, Janetta Politehnica" University of Bucharest Dept. of Automatic Control and Computer Science Romania

It is well known that the complex system operation requires the use of new scientific tools and computer simulation. This paper presents a modular approach for modeling and analysis of the complex systems (in communication or transport systems area) using Hybrid Petri nets. The performance evaluation of the hybrid model is made by a simulation methodology that allows building up various functioning scenarios. A Decision Support System based on the above mentioned methodologies of modeling and analysis will be designed for performance evaluation and time optimization of large scale communication and/or transport systems. Copyright © 2017, The Authors. All rights reserved.

关键词： Decision support systems

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Maintaining Diversity in an SVM integrated Case Based GA for Solar Flare Prediction

Maintaining Diversity in an SVM integrated Case Based GA for...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Yoshio Taniguchi Yoshihiko Kubota Setsuo Tsuruta Yoshiyuki Mizuno Takayuki Muranushi Yuko Hada Muranushi Yoshitaka Sakurai Rainer Knauf Andrea Kutics Hitachi Industry & Control Solutions Ltd. Yokohama Japan School of System Design and Technology Tokyo Denki University Tokyo Japan Faculty for the Study of Contemporary Society Kyoto Women’s University Kyoto Japan RIKEN Advanced Institute of Computational Science Kobe Japan Kwasan and Hida Observatories Kyoto University Kyoto Japan School of Interdisciplinary Sciences Meiji University Tokyo Japan Dept. of Computer Science and Automation Technische Universität Ilmenau Ilmenau Germany Dept. of Natural Sciences International Christian University Tokyo Japan

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

Unusually intense solar flares may cause serious calamities such as damages of electric/nuclear power plants. It is thereupon highly demanded, but is quite difficult, to predict intense solar flares due to the imbalanced character of the available data. To cope with this problem, we have heretofore developed and applied a Case Based Genetic Algorithm (CBGALO) that contains a Local Optimizer, which is a Support Vector Machine (SVM). However, the prediction performance significantly depends on input data for learning. Hereupon, CBGALO is further extended by a Case Based automatically restartable Good combination searching GA for both learning features and input data (CBRsGcmbGA). Even the powerful but computationally expensive Deep Learning cannot automatically (evolutionarily, in our approach) search the learning data. Our approach solved this problem a little better by the case-based approach. However, it became obvious that even this work suffers from the typical GA effect in falling into local optima. To improve the results, we hence developed newly a diversity maintenance approach that inserts good individuals with large Hamming distance into the case base as elite individuals in GA's population. In 2 out of 3 classes of solar flares, the performance of our new approach became as high as the best ones among the conventional world top records. Namely, even in those ≥ C class solar flares, our approach applying the Hamming distance to increase diversity had as high a performance 0.662 as compared with the conventional world top record 0.650.

关键词： Genetic algorithms Support vector machines Evolutionary computation Deep learning

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