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作者： Dos Santos Coelho, Leandro Alotto, Piergiorgio Industrial and Systems Engineering Graduate Program Automation and Systems Laboratory LAS PPGEPS Pontifical Catholic University of Paraná Rua Imaculada Conceião Curitiba 80010 Paraná Brazil Dipartimento Ingegneria Elettrica Università di Padova Padova 35131 Italy

Optimization metaheuristics, such as Particle Swarm Optimization, Ant Colony Optimization and bacterial foraging strategies have become very popular in the optimization community and have been successfully applied to electromagnetic device design. The Artificial Bee Colony (ABC) algorithm is a rather new bio-inspired swarm intelligence approach which is competitive with other population-based algorithms and has the advantage of using fewer control parameters. In this work, a standard and an improved version of the ABC algorithm using Gaussian distribution are applied to Loney's solenoid problem, showing the suitability of these methods for electromagnetic optimization. © 2011 IEEE.

关键词： Solenoids

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A Framework of Risk Profile in Public Healthcare System Development: A Literature Review 2nd

A Framework of Risk Profile in Public Healthcare System Deve...

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2nd International Symposium on Disaster Resilience and Sustainable Development, 2021

作者： Krutphong, Kodchakorn Tang, Jing Leelawat, Natt Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand International School of Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9789811947148

Risk profile has been utilized in a variety of knowledge fields beyond disaster management or risk management it also plays as the tools in assessment process before the planning both in operation and *** public healthcare system is considered as one of the most critical stakeholders during crises such as disasters and *** risk profile in the public healthcare system requires experts to help developing it according to its *** to a limited number of reviews in the field, this review study focuses on the public healthcare system risk profile’s guideline and development from well-known research *** study also provides the SWOT analysis to realize the strengths, weaknesses, opportunities, and threats of each specific guideline for further *** research results found the ratio of the research in the keywords of the risk profile mostly in the field of medicine and rising number since 2011–*** order to develop the risk profile in such a specific area, it is necessary to use the strength part which suits with the appropriate area. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Risk management

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Automated 3D bone modelling based on geometric features from images 24

Automated 3D bone modelling based on geometric features from...

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24th International Conference on Production Research, ICPR 2017

作者： Rudek, M. Gumiel, Y.B. Canciglieri, O. Carvalho, D.R. Trajanovic, M. Industrial and Systems Engineering Post-Graduate Program PUCPR Imaculada Conceicao Street 1155 zip code CuritibaParana80215-901 Brazil Graduate Program on Health Technology in Pontifical Catholic University of Parana PUCPR Imaculada Conceicao Street 1155 zip code CuritibaParana80215-901 Brazil Faculty of Mechanical Engineering University of Nis Aleksandra Medvedeva 14 Niš18000 Serbia

ISBN: (纸本)9781605955070

Currently the computational modelling tools, expert algorithms for image segmentation and three-dimensional printing devices have improved the process of manufacture of customized pieces in the context of automation of prosthesis modelling. Among several strategies to obtain the correct shape of a missing bone part, we explore a modelling method based on geometric features defined by Bezier cubic curves. The data is obtained from sets of slices of tomographic scans as a reference. From the images, we know about data from the edges in the image but we do not have any information about a missing area in a specific bone region. Thus, the objective is to search patterns for features whose values are known from similar tomographic image which matches to fill a hole in a bone. Due the free form of a bone there are a lot of parameters to be evaluated. Thus, a Data Mining approach is applied for classification and to discover the best features as shape descriptors. In this way, the prosthesis manufacture can be automated in all stages among image scanning and printing. © 2017 DEStech Publications. All rights reserved.

关键词： Image enhancement

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Framework for Automated Synthetic Image Generation for Vehicle Detection 23

Framework for Automated Synthetic Image Generation for Vehic...

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Proceedings of the 2023 6th International Conference on Sensors, Signal and Image Processing

作者： Vitória Biz Cecchetti Bruno José Souza Roberto Zanetti Freire Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Brazil and Pumatronix Electronic Equipment Ltd. Brazil Industrial and Systems Engineering Graduate Program (PPGEPS) Universidade Tecnológica Federal do Paraná (UTFPR) Brazil

ISBN: (纸本)9798400707995

The use of synthetic images has been highlighted within the computer vision field as a more practical option that helps reduce the time and cost spent on vehicle detection tasks in urban environments. This paper presents a framework for automated synthetic image generation, aiming at the detection of vehicles in urban environments. The creation of the 3D scenario is carried out through the Blender software. Some adverse conditions of the scenes were developed, including: rain, fog, occlusion by tree branches and electrical power lines, and low lighting. Then the algorithm for the automated generation of images was developed based on parameters chosen by the user to generate the scene and to generate the annotations of the images. Additionally, a convolutional neural network with YOLOv5 architecture along with a cross-validation technique was applied to carry out vehicle detections on the developed synthetic dataset, on both real and mixed datasets. The proposed framework generated a consistent dataset that can be used in vehicle detection networks, obtaining a mAP 0.5 above 96% and mAP 0.5:0.95 above 82%, also the precision values remained above 92%, and recall above 95%. It was also observed that the combination of synthetic images with real images can improve the performance of the model.

关键词： Computer vision Convolutional neural networks Object detection Synthetic images Vehicle detection.

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Wavelet neural network approach applied to biomechanics of swimming

Wavelet neural network approach applied to biomechanics of s...

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2013 13th UK Workshop on Computational Intelligence, UKCI 2013

作者： Puchalski, Weslly Mariani, Viviana Cocco Schauenburg, Felipe Fidelis Dos Santos Coelho, Leandro Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Parana Curitiba Brazil Department of Mechanical Engineering PPGEM Pontifical Catholic University of Parana Federal University of Parana Curitiba Brazil Department of Electrical Engineering Pontifical Catholic University of Parana Federal University of Parana Curitiba Brazil

ISBN: (纸本)9781479915682

An artificial neural network (ANN) consists of a number of interconnecting artificial neurons and employs mathematical or computational models for information processing. ANNs are suitable for handling large amounts of dynamic, noisy and nonlinear data. On the other hand, the wavelet theory provides a multi-resolution approximation for discriminate functions. The combination of the wavelet transforms theory with the basic concept of ANNs leads to new mapping networks called wavelet neural networks (WNNs) or wavenets, which are proposed as an alternative to feedforward ANNs for approximating arbitrary nonlinear functions. Generalized from radial basis function ANNs, WNNs are in fact feed-forward neural networks with one hidden layer, radial wavelets as activation functions in the hidden nodes and a linear output layer. The contribution of this paper is to evaluate the WNNs to model a parathlete swimmer behavior. The parathlete swimmer swims the breaststroke style using biomechanics data generated by the software tool called SWUMSUIT, which was developed in Tokyo Technological Institute in Japan. The forecasted results clearly show that WNN has good prediction properties. The proposed WNN modeling approach can benefit disabled swimmers (parathletes) to gain competitive advantage by studying the biomechanics involved in the sport and considering the help of simulations systems. © 2013 IEEE.

关键词： Biomechanics

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Modeling of a 2-DOF Piezoelectric Micromanipulator at High Frequency Rates through Nonlinear Black-box System Identification

Modeling of a 2-DOF Piezoelectric Micromanipulator at High F...

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2018 Annual American Control Conference, ACC 2018

作者： Ayala, Helon Vicente Hultmann Rakotondrahe, Micky Coelho, Leandro Dos Santos Pontifical Catholic University of Rio de Janeiro Department of Mechanical Engineering Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Brazil FEMTO-ST Institute Université Bourgogne Franche-Comté CNRS Besançon France Department of Electrical Engineering Federal University of Paraná Brazil

ISBN: (纸本)9781538654286

In the present paper we proceed the data-driven modeling of a two degrees of freedom (2-DOF) piezoelectric micromanipulator through models with the Nonlinear AutoRegressive with eXogenous inputs (NARX) structure and real acquired data. We show the results when the system is excited at high frequencies, aiming towards rapid and precise micropositioning. The order of NARX the models are increased until they satisfy the statistical tests based on higher-order correlations and the multiple correlation coefficients, which are close to unity for both measured outputs. The results herein presented encourage the use of data-driven methods for modeling piezoelectric micromanipulators. © 2018 AACC.

关键词： Data models Mathematical model Micromanipulators Analytical models Actuators"

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Heuristic Kalman Algorithm for Multiobjective Optimization.

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IFAC-PapersOnLine 2017年第1期50卷 4460-4465页

作者： Hultmann Ayala H.V. dos Santos Coelho L. Reynoso-Meza G. Industrial and Systems Engineering Graduate Program PPGEPS Polytechnic School Pontifical Catholic University of Paraná PUCPR Rua Imaculada Conceição 1155 Curitiba PR code 80215-901 Brazil Department of Electrical Engineering (PPGEE) Federal University of Parana (UFPR) Polytechnic Center Curitiba Parana 81531-970 Brazil

This papers presents a new heuristic multiobjective optimization procedure based on Kalman filtering. The novel approach is compared to the well-known Nondominated Sorting Genetic Algorithm version II with the Zitzler, Deb and Thiele test suite showing favorable results for the Kalman based solution. Further improvement on the proposed algorithm is made with respect to the learning factor, which is set to be time-dependent, improving the algorithm in most cases and diminishing the number of control parameters. The proposed multiobjective optimization algorithm is interesting due to its convergence and coverage quality, its computational complexity and few parameters to be adjusted. © 2017

关键词： loop pairing Multi-input/multi-output systems Multi-objective optimization Multiloop control

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Predicting Factors Influencing the Actual Use of E-learning Platform Among Medical Students in the Philippines

Predicting Factors Influencing the Actual Use of E-learning ...

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

作者： Benito, Omar Paolo Prasetyo, Yogi Tri Roque, Ralph Andre C. Flores, Fernan Patrick Cahigas, Maela Madel L. Nadlifatin, Reny Ayuwati, Irene Dyah International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines School of Graduate Studies Mapúa University Manila Philippines Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia Rectorate University of Surabaya Surabaya Indonesia

ISBN: (纸本)9798350386097

This study aimed to examine the factors influencing the acceptance of eLearning platforms in medical education during the COVID-19 pandemic in the Philippines, using the latent variables from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and two additional variables derived from relevant literature. A total of 360 medical students participated by completing an online survey comprising 40 questions. The analysis, conducted using stepwise multiple linear regression, revealed that Performance Expectancy (PE), Habit (HB), and Instructor Characteristics (IC) were significant predictors of Actual Use (AU) with an accuracy of 54.22%. Higher levels of PE, HB, and IC were found to positively influence the acceptance and utilization of medical eLearning platforms. The findings from this study can provide valuable insights for the Commission on Higher Education in the Philippines, aiding in the enhancement of eLearning platforms for medical education. Although this research primarily focused on UTAUT2 and two additional variables-Learning Value and Instructor Characteristics-the results offer substantial implications for the broader development of eLearning platforms in the medical field. © 2024 IEEE.

关键词： Multiple linear regression

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Classification of the Structural Integrity by the General Vibration Method

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Procedia Computer Science 2019年 157卷 382-387页

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information Systems Information Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

Traditionally, for the purpose of classifying the integrity of an engineering structure, one may use the information of the natural frequencies or mode shapes or some other measures derived from the two. In this research, we propose a classification method on the basis of the general vibration model. The general vibration model is essentially a set of differential equations describing the dynamics of the structure under consideration. For the purpose of damage detection, a deviation of the general vibration model from the dynamic equilibrium point marks the occurrence of the damage. To demonstrate the effectiveness of the method, we study two simplest dynamical systems consisting of one- and two-concentrated masses subjected to a prescribed dynamic load. The structural damages are introduced artificially by reducing the stiffness of spring in the structures. We find that the general vibration model is more sensitive to damages than the traditional methods.

关键词： General Vibration Model Structural Integrity Structural Health Monitoring Power Spectral Density Damage Index

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Preliminary Plan for Data Collection on Stakeholder Information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai industrial Zones 23

Preliminary Plan for Data Collection on Stakeholder Informat...

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

作者： Arayachookiat, Penpitcha Saengtabtim, Kumpol Kodaka, Akira Leelawat, Natt Tang, Jing Watanabe, Kenji Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan International School of Engineering Chulalongkorn University Faculty of Engineering Bangkok Thailand Graduate School of Social Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (纸本)9798350353952

The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness. © 2024 IEEE.

关键词： Area-Business Continuity Management Flood Index of Item-Objective Congruence Information Interdependence

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