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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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Gaussian artificial bee colony algorithm approach applied to Loney's solenoid benchmark problem

Gaussian artificial bee colony algorithm approach applied to...

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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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COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT systems IMPLEMENTATION TO OPTIMIZE BUSINESS SUSTAINABILITY 9

COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT SYS...

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9th International Conference on Information Technology: IoT and Smart City, ICIT 2021

作者： Sardjono, Wahyu Lusia, Erma Utomo, Hargo Sukardi, Samudra Rahmasari, Aninda Regent Montororing, Yuri Delano Information Systems Management Department Binus Graduate Program Bina Nusantara University Indonesia Research Capacity Building Research & Development Bina Nusantara University Indonesia Department of Management Faculty of Economic and Business Gajah Mada University Indonesia Graduate Program Faculty of Economy and Business University of Indonesia Indonesia International Relations Department Faculty of Humanities Bina Nusantara University Indonesia Industrial Engineering Study Program Bhayangkara University Indonesia

ISBN: (纸本)9781450384971

Complaint resolution that arise due to internal and external factors in a company can be monitored through the Service Recovery Index (SRI), and SRI is developed through a number of factors that influence it. Meanwhile, the SRI model needs to be developed to see the business sustainability through implementation knowledge management system in the organization. The data collection method was carried out, starting with building a research instrument based on knowledge management theory and continued with observation and distributing questionnaires to respondents who were involved in the business process of managing SRI. The data analysis method was used to process the data from the questionnaire, factor analysis method was used and the method to build the model used was the regression analysis method. The results obtained from this study are the discovery of 4 (four) factors with a number of indicators that are grouped on each formed factor, which can then be made and built a readiness model that reflects current conditions, so that it can be used to build predictions in the future related to readiness. implementation of knowledge management system development in order to support increased understanding of the service recovery index in the organization. © 2021 ACM.

关键词： Knowledge management

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Predicting Factors Influencing the Actual Use of E-Learning Platform among Medical Students in the Philippines: Unified Theory of Acceptance and Use of Technology Approach 24

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

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4th International Conference on Internet and E-Business, ICIEB 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 Taiwan Department of Industrial Engineering and Management Yuan Ze University Taiwan School of Industrial Engineering and Engineering Management Mapua University Philippines School of Graduate Studies Mapua University Philippines Department of Information Systems Sepuluh Nopember Institute of Technology Indonesia University of Surabaya Indonesia

ISBN: (纸本)9798400709739

eLearning has been utilized as a mode of instruction among medical students amidst the COVID-19 pandemic. The present study aimed to investigate the factors influencing the acceptance of eLearning platforms in medical education during the COVID-19 pandemic in the Philippines by employing the latent variables of UTAUT2, along with two additional latent variables gathered from various related literature. A sum of 360 medical students participated and answered an online survey that consists of 40 questions. A stepwise multiple linear regression was utilized and found that performance expectancy (PE), habit (HB), and instructor characteristics (IC), can successfully predict the actual use (AU) of medical students with a precision of 54.22%. A higher performance expectancy (PE), habit (HB), and instructor characteristics (IC) can enhance and promote the acceptance of medical eLearning platforms. This is the first study that has examined the acceptance of eLearning platforms among medical students in the Philippines during the COVID-19 pandemic. The outcomes of this research can serve as guidelines for the Commission on Higher Education of the Philippines for the enhancement of eLearning platforms. Although this study only utilized the latent variables of UTAUT2 along with two additional variables: Learning Value and Instructor Characteristics;the findings of this study would still hold significant value for promoting open innovation in eLearning platforms in medical fields worldwide. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： COVID-19

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Retroactivity Affects the Adaptive Robustness of Transcriptional Regulatory Networks

Retroactivity Affects the Adaptive Robustness of Transcripti...

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American Control Conference

作者： Junmin Wang Calin Belta Bioinformatics Graduate Program Boston University Boston MA 02215 USA Division of Systems Engineering and the Bioinformatics Graduate Program Boston University Boston MA 02215 USA

ISBN: (纸本)9781538679012;9781538679265

Adaptation refers to the system's ability to respond transiently to an input signal and subsequently recover to the initial states. Adaptive robustness, the ability of a network to achieve adaptation, is subject to the loading effects arising from modular interconnections, known as retroactivity. Studying the effects of retroactivity on adaptive robustness facilitates the employment of retroactivity to improve circuit performance in synthetic biology. In this paper, we developed a framework for quantifying adaptive robustness via statistical model checking and used this framework to investigate the effects of retroactivity on adaptive robustness. We found that increasing retroactivity tends to raise adaptive robustness in networks where the output protein does not perform regulatory functions, such as incoherent feedforward loops.

关键词： Self tuning input signal Robustness Circuit optimization Model checking Frameworks synthetic biology Network Gene Regulatory Networks Regulatory

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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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Capacitance Estimation Algorithm for Condition Monitoring of Electrolytic DC-Link Capacitors Using Artificial Neural Network in Front-End Diode Rectifier Three-Phase Motor Drive systems

Capacitance Estimation Algorithm for Condition Monitoring of...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Mateus Abreu de Andrade Rodolfo César Costa Flesch Graduate Program in Automation and Systems Engineering Universidade Federal de Santa Catarina Florianópolis Brazil

A factor that must be taken into account in the modern design of power electronics converters is the reliability of dc-link capacitors, but traditional condition monitoring methods require extra hardware that increase the overall cost. This work proposes and experimentally evaluates a condition monitoring method for electrolytic dc-link capacitors in three-phase front-end diode rectifier motor drives which does not require hardware modifications. The presented method uses an artificial neural network (ANN) to predict the capacitance value of the dc-link capacitor bank. Based on time-domain parameters, the ANN is trained and evaluated using an error analysis to determine the effectiveness of the proposed method with a printed circuit board capacitor jig and aged samples. The proposed method is evaluated in several operating conditions and the results show that the prediction errors are less than 2.4% and that the method is able to monitor the degradation level of the dc-link capacitor bank.

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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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Single Inductor Dual Buck Inverter Classical and Predictive Linear Voltage Controller Comparison 8

Single Inductor Dual Buck Inverter Classical and Predictive ...

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8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Patarroyo-Gutierrez, Luis David Nakamoto Yamaguti, Nelson Nayoshi Hernández-Gómez, Oscar Mauricio MacEdo Da Silva, Daniel Abreu School of Electronic Engineering Universidad Pedagógica y Tecnológica de Colombia Tunja Boyacá Colombia Federal University of Santa Catarina Dep. of Automation and Systems SC Florianopolis Brazil Electrical Engineering Graduate Program Federal University of Pará Belem Brazil

ISBN: (纸本)9798350321128

This article presents the mathematical model of a 2 KW DBI (Dual Buck Inverter) converter that can be used in renewable energy applications. The inverter operating modes are described with the equations that model their behavior with the activation signals of the MOSFETs. The switching model is built. Simulation results are presented by applying linear control through a PI controller and GPC (Generalized Predictive Controller) hybridized in PID structure;simulation results are recorded in PSIM © verifying the control response due to changes in the load and the input DC voltage level.

关键词： Automatic Voltage Control Control of Power Electronic systems DC-AC Power Converters Dual Buck Inverter Inverter

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Weblab of a control experiment in a newborn baby incubator

Weblab of a control experiment in a newborn baby incubator

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International Conference on Remote engineering and Virtual Instrumentation (REV)

作者： Karine Bauer Luciano Antonio Mendes Systems and Production Engineering Graduate Program - PPGEPS Pontifical Catholic University of Parana Curitiba Brazil Country

WebLabs, or Remotely Operated Laboratories, allow for remote control and monitoring of interactive or batched systems with educational objectives. Considered as additional resources in education, they contribute to a flexible learning model and make possible for students to perform laboratory experiments remotely, off-class, in collaboration, thus contributing to the reduction of laboratory equipment idleness. The purpose of this paper is to report steps in designing and enabling a WebLab with background theme on the control and monitoring of thermal comfort parameters in a newborn baby incubator. Three didactical experiments can be performed in this WebLab: transfer function evaluation, on-off control and PID controller tuning, with users challenged to optimally tune the parameters of a controller algorithm. In the end of the session, the user can enter his/her impressions regarding the WebLab usage by answering a questionnaire. The WebLab design includes the evaluation of students' abilities through performance indexes while keeping operation within the requirements of an associated medical safety standard. A systematic approach for the WebLab design process has been employed, with the system design split in three layers: physical system, hardware and software. Sets of qualitative and quantitative requirements to be attended were defined. System and product design techniques, such as House of Quality, Morphological Matrix and Pugh's Method, have been employed to address the conversion of the project requirements into the Weblab overall solution. Virtual Instrumentation resources have been used to acquire temperature, humidity and air speed signals. The LabVIEW platform was used to support experiment integration and to create the user interface using LabVIEW Remote Panel architecture. The WebLab has been successfully implemented and presently can be accessed within the university network.

关键词： Temperature measurement Temperature sensors Software Pediatrics Humidity Temperature control

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