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2023 Winter Simulation Conference, WSC 2023

作者： Huang, Yining Wan, Hong Chen, Xi North Carolina State University Operations Research Graduate Program 915 Partners Way RaleighNC27606 United States North Carolina State University Department of Industrial and Systems Engineering 915 Partners Way RaleighNC27606 United States Virginia Tech Grado Department of Industrial and Systems Engineering 1145 Perry Street BlacksburgVA24061 United States

ISBN: (纸本)9798350369663

This study delves into the utilization of Generative Adversarial Networks (GANs) for generating subject-specific time series sensor data, offeringaninnovativealternativetotraditionalmetamodel-basedsimulations. We undertake an in-depth analysis of DoppelGANger, a prominent GAN variant for time series data and metadata generation, evaluating its efficiency and efficacy. The sensor data for this investigation was sourced from the National Health and Nutrition Examination Survey, which served as the foundational training set. We scrutinized the synthesized sensor data corresponding to various physical attributes, focusing on the temporal and multi-dimensional statistical properties. Our empirical findings underscore the potential of GANs to adeptly capture the time-dependent correlations and the intricate statistical characteristics inherent in multi-dimensional data. This insight into GANs' capabilities is a crucial step towards more sophisticated synthetic data generation, with significant implications for future applications in wearable technology and personalized health monitoring systems. © 2023 IEEE.

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Structural health monitoring: Frequency domain analysis of beam with breathing crack 2

Structural health monitoring: Frequency domain analysis of b...

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2nd International Conference on Biospheric Harmony Advanced Research, ICOBAR 2020

作者： Gunawan, F.E. Kanto, Y. Kamil, I. Sutikno Tran, H.N. Industrial Engineering Department BINUS Graduate Program-Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Mechanical Systems Engineering College of Engineering Ibaraki University Ibaraki Japan Department of Industrial Faculty of Engineering Andalas University Padang Indonesia Department of Mechanical Engineering Department Faculty of Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Automotive Engineering Faculty of Transportation Engineering Ho Chi Minh City University of Technology Ho Chi Minh City Viet Nam

Structural Health Monitoring (SHM) system can be considered as an Internet-of-Things (IoT) system implemented to engineering structure to provide real-time information on the integrity of the structure. In doing so, the system acquires data from various sensors distributed across the structure and infers damage sensitive quantities. In the research, we proposed a damage index derived from the governing dynamics of the structure in the frequency domain. The proposal was empirically verified by applying the index to analyze the case of a cracked cantilever beam subjected to a harmonic load. The value of the damage index was computed at some points surrounding the crack to understand the effect of the distance of the monitoring point to the crack to the index sensitivity. The results suggest that the index is sensitive to the crack particularly when the observation point is near the crack. © Published under licence by IOP Publishing Ltd.

关键词： Internet of things

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Agent-Based Modeling for Forest Fire Simulation in Chiang Mai, Thailand 23

Agent-Based Modeling for Forest Fire Simulation in Chiang Ma...

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23rd International Symposium on Communications and Information Technologies, ISCIT 2024

作者： Tappanom, Teerapat Leelawat, Natt Saengtabtim, Kumpol Tang, Jing Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Graduate School of System Design and Management Keio University Yokohama Japan Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9798350353952

Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is a need for advanced simulation models. This research uses Agent-Based Modeling (ABM) to develop a forest fire simulation for Chiang Mai. The methodology involves collecting historical data, performing Multiple Regression Analysis, designing the simulation, and testing it. Data from 1998 to 2021, including temperature, relative humidity, wind speed/direction, burn area, and slope, were collected from various sources. Multiple regression analysis identified wind speed as the most significant factor affecting burn area. The forest fire simulation, designed using ZF Wang's spread model and tested with AnyLogic, showed that wind direction and speed are crucial in fire spread. The simulation accurately predicted high-risk areas, helping in proactive planning and response. This study confirms that wind is a critical factor in forest fire spread, providing a valuable tool for fire districts to improve preparedness and management. Future research should focus on refining the model with localized data and integrating real-time detection to improve its accuracy and applicability. © 2024 IEEE.

关键词： Forest ecology

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Power Demand Forecast Using Least-Squares Support Vector Machines

Power Demand Forecast Using Least-Squares Support Vector Mac...

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International Conference on Intelligent systems Applications to Power systems (ISAP)

作者： Leandro dos Santos Coelho Carlos Eduardo Klein Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil

This paper aims to share the results on forecasting power demand using least-squares support vector machines. The development is based on model estimation taking in consideration the past measurements for power demand and ambient temperature. All approximated models were evaluated using the multiple correlation coefficient (R 2 ) or mean absolute percentage error (MAPE) and maximum error combined as quality parameters.

关键词： Power demand Demand forecasting Support vector machines Power system modeling Temperature Power generation Power engineering and energy systems engineering and theory Power measurement System identification

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Quantum Gaussian particle swarm optimization approach for PID controller design in AVR system

Quantum Gaussian particle swarm optimization approach for PI...

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IEEE International Conference on systems, Man and Cybernetics

作者： Leandro dos Santos Coelho Bruno Avila de Meirelles Herrera Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil

During the history of science of computational intelligence, many evolutionary algorithms approaches were proposed having more or less success in solving various optimization problems. In this context, the Particle Swarm Optimization (PSO) is a bio-inspired optimization mechanism based on the metaphor of social behaviour of birds flocking and fish schooling in search for food. Inspired by the classical PSO method and quantum mechanics theories, this work presents a quantum-behaved PSO (QPSO) approach using Gaussian probability distribution function (G-QPSO). Numerical simulations based on optimized proportional-integral-derivative (PID) control of an automatic regulator voltage system for nominal system parameters and step reference voltage input demonstrate the effectiveness and efficiency of G-QPSO approach. Simulation results of G-QPSO to determine the PID parameters are compared with the classical PSO and QPSO.

关键词： Particle swarm optimization Three-term control Control systems Quantum mechanics History Computational intelligence Evolutionary computation Birds Marine animals Educational institutions

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Gait proficiency index in children aged 3.5 to 9.5 years old

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Research on Biomedical engineering 2021年第2期37卷 429-437页

作者： das Neves, Ana Maria Bender Seidenfuss de Souza, Leandro Daniel Aires, Andréia Gomes Souza, Thalita Borges Giacomazzi, Leandro Peserico Dachi, Édison Pereira Baptista, Rafael Reimann School of Technology Graduate Program in Electrical Engineering PUCRS Porto Alegre Brazil School of Health and Life Sciences Undergraduate Program in Physical Education PUCRS Porto Alegre Brazil School of Technology Undergraduate Program in Electrical Engineering PUCRS Porto Alegre Brazil School of Technology Associate Degree Program in Industrial Automation and Embedded Systems SENAI Porto Alegre Brazil School of Technology and School of Health and Life Sciences Pontifical Catholic University of Rio Grande do Sul Av. Ipiranga 6681 Partenon Porto Alegre90619-900 Brazil

Introduction: The purpose of this study is to present a novel approach for gait assessment called gait proficiency index (GPI) using only ground reaction forces (GRF)-derived parameters. Material and methods: Barefoot gait from 51 healthy children was evaluated with the GPI in this study. The participants walked at their self-selected speed along a 6-m walkway with 8 force platforms placed in pairs. The force-time analysis resulted in a dynamic symmetry assessment (DSA) that is the result of vertical GRF component distribution for all gait cycles both the left and right foot. DSA and impulse calculation from GRF led to the calculation of the GPI, which is the relationship between the impulse of load response and mid-stance and impulse of terminal stance and pre-swing of both right and left feet multiplied by the DSA index. The children were divided into three groups with 17 participants each and classified according to age (mean age ± standard deviation): G1 (4.39 ± 0.511), G2 (6.33 ± 0.639), G3 (8.49 ± 0.636). Results: The results show that as children mature, the GPI seems to increase from G1 to G2 and decreases from G2 to G3 and that both the standard deviations and coefficient of variation decrease with the increase of age. Conclusions: This can be an indicative that the index can assess improvements in gait quality through age. However, there was no statistical significance between the groups in this variable. Also, the correlation between either DSA and age or GPI and age found is weak to make other conclusions but that the study of adults should be included to either validate or refute the use of GPI. © 2021, Sociedade Brasileira de Engenharia Biomedica.

关键词： Biophysics

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Extending the Core Ontology on Decision Making according to Behavioral Economics 14

Extending the Core Ontology on Decision Making according to ...

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14th Seminar on Ontology Research in Brazil, ONTOBRAS 2021 and 5th Doctoral and Masters Consortium on Ontologies, WTDO 2021

作者： Ramos, Eduardo C. Campos, Maria Luiza M. Baião, Fernanda Guizzardi, Renata Graduate Program in Informatics Universidade Federal do Rio de Janeiro RJ Rio de Janeiro Brazil RJ Rio de Janeiro Brazil Department of Industrial Engineering and Business Information Systems University of Twente Enschede Netherlands

Decisions are constantly made and some of them may be extremely critical. However, most decision makers are unaware that their decisions may be biased. We used Behavioral Economics as a foundation to propose an ontology that shows how decision makers’ preferences are set and the situation in which they occur in an intuitive decision under risk and uncertainty. Our aim is that this ontology be used to improve their decisions by allowing them a better understanding of how they decide. In addition, this ontology can be used as part of a strategy to reduce biases. © 2021 Copyright for this paper by its authors.

关键词： Ontology

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A Conjoint Analysis on the Preference of Pipe Welding Materials and Procedures

A Conjoint Analysis on the Preference of Pipe Welding Materi...

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2024 IEEE International Conference on industrial engineering and engineering Management, IEEM 2024

作者： Dela Cruz, Erick D. Prasetyo, Yogi Tri Ayuwati, Irene Dyah Cahigas, Maela Madel L. Nadlifatin, Reny School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines School of Graduate Studies Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan University of Surabaya Surabaya Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798350386097

Welding is both as art and science and its common use is the jointing of points. Some of the welding procedures used for jointing metal pipes are Tungsten Inert Gas and Gas Metal Arc welding and in common practice plastic pipes are bonded with the use of butt-fusion welding procedure. Since 1970’s conjoint analysis was used as a way of finding out what the preference of consumers. The objective of this study is to determine the combination welding attributes that were most preferred using a conjoint analysis approach. With conjoint analysis, together with, the orthogonal design the preference for welding materials and procedures were analyzed. It showed that pipe material with 29.24% was the most preferred attribute and Nondestructive test as the least preferred with 2.66%. The result of this study may be utilized in future related reviews and could be applicable in other related Mechanical systems requiring welding works. © 2024 IEEE.

关键词： Nondestructive examination

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Swim velocity profile identification through a Dynamic Self-adaptive Multiobjective Harmonic Search and RBF neural networks 22

Swim velocity profile identification through a Dynamic Self-...

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22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2014

作者： Ayala, Helon V.H. Da Cruz, Luciano F. Coelho, Leandro S. Freire, Roberto Z. Pontifical Catholic University of Parana - PUCPR Industrial and Systems Engineering Graduate Program - PPGEPS Imaculada Conceição Curitiba Parana1155 Brazil Federal University of Parana - UFPR Department of Electrical Engineering - DEE/PPGEE Polytechnic School of UFPR Curitiba Parana Brazil

ISBN: (纸本)9782874190957

Technology has been successfully applied in sports, where biomechanical analysis is one of the most important areas used to raise the performance of athletes. In this context, this paper focuses on swim velocity profile identification using Radial Basis Functions Neural Networks (RBF-NN) trained by the Gustafson-Kessel clustering combined with a novel Dynamic Self-adaptive Multiobjective Harmony Search (DS-MOHS). One study case is analyzed, from real data acquired of an elite female athlete, swimming breaststroke style. Better results are obtained by DS-MOHS when compared with standard multiobjective harmony search in terms of accuracy and generalization of the model.

关键词： Radial basis function networks

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Cascaded evolutionary multiobjective identification based on correlation function statistical tests for improving velocity analyzes in swimming

Cascaded evolutionary multiobjective identification based on...

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IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM

作者： Helon Vicente Hultmann Ayala Luciano Ferreira da Cruz Roberto Zanetti Freire Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program PUCPR Curitiba Brazil Department of Electrical Engineering PUCPR UFPR Curitiba Brazil

By using biomechanical analyses applied to sports many researchers are providing important information to coaches and athletes in order to reach better performance in a shorter time. In swimming, these kinds of analyses are being used to evaluate, to detect and to improve the skills of high level athletes. Recently, evolutionary computing theories have been adopted to support swim velocity profile identification. Based on velocity profiles recognition, it is possible to identify distinct characteristics and classify swimmers according to their abilities. In this way, this work presents an application of Radial Basis Function Neural Network (RBF-NN) associated to a proposed cascaded evolutionary procedure composed by a genetic and Multiobjective Differential Evolution (MODE) algorithms as optimization method for searching the best fitness within a set of parameters to configure the RBF-NN. The main goal and novelty of the proposed approach is to enable, through the adoption of cascaded multiobjective optimization, the use of correlation based tests in order to select both the model lagged inputs and the associated parameters in a supervised fashion. Finally, the real data of a Brazilian elite female swimmer in crawl and breaststroke styles obtained into a 25 meters swimming pool have been identified by the proposed method. The soundness of the approach is illustrated with the adherence to the model validity tests and the values of the multiple correlation coefficients between 0.95 and 0.93 for two tests for both breaststroke and crawl strokes, respectively.

关键词： Sociology Correlation Optimization Genetic algorithms Time series analysis Training

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