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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Kanta Shiku Masafumi Kuromizu Yuji Gotoh Takaaki Nara Graduate School of Information Science and Technology The University of Tokyo bunkyo-ku Japan Division of Materials Science and Production Engineering Graduate School of Engineering Oita University Oita Japan Intelligent Mechanical Systems Program Faculty of Science and Technology Oita University Oita Japan

ISBN: (数字)9798350362213

ISBN: (纸本)9798350362220

Electromagnetic nondestructive inspection for high-speed moving ferromagnetic materials is necessary for manufacturing efficiency. In this paper, we present a novel leakage magnetic flux (LMF) method to estimate the crack position in a moving cylindrical ferromagnetic rod. The method directly measures the first-order Fourier coefficients of the LMF moving with the crack by using only two coils with DC excitation. The location of a crack is estimated by the proposed method, as demonstrated for an S45C cylindrical rod.

关键词： Location awareness Coils Magnetic flux Inspection Ferromagnetic materials Manufacturing Electromagnetics

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Analysis of the Brazilian Climate Data Influence on Soybean Pricing by Using Long Short-Term Memory Models

SSRN

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SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Dal Molin, Viviane Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

This work uses machine learning to verify whether the Brazilian climate influences international soybean price prediction. For this, climatic data, dollar quotes, inflation, and annual soybean production were collected from different data sources. Then, the collected data were pre-processed and grouped by Brazilian state. Afterward, data from the five most productive Brazilian states are chosen, such as Mato Grosso (MT), Mato Grosso do Sul (MS), Goiás (GO), Paraná (PR), and Rio Grande do Sul (RS). Afterward, predictive models are built using the long short-term memory (LSTM) method, which is applied in each chosen state dataset considering two different settings: with and without climatic data. Thus, two models were built for each Brazilian state, totaling ten predictors. In the experimental evaluation, when trained with climatic data, the PR model achieved the lowest values of root mean squared error (RMSE) and mean absolute error (MAE). Regarding predictors trained without climate data, the RS and PR obtained the lowest values of RMSE and MAE, respectively. After conducting statistical hypothesis tests, no significant difference was found among models, stating, with 95% certainty, that, in this study, the Brazilian climatic data did not influence the model performance for predicting soybean prices. On the other hand, one of the main contributions of work is conducting an unprecedented study about soybean price prediction using Brazilian climatic data. © 2024, The Authors. All rights reserved.

关键词： Long short-term memory

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Soybean Price Prediction by Using Lstm Models Based on Brazilian Climatic Data

SSRN

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SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Molin, Viviane Dal Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

关键词： Long short-term memory

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Electromagnetic Device Optimization using Improved Differential Evolution Methods

Electromagnetic Device Optimization using Improved Different...

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IEEE Conference on Electromagnetic Field Computation

作者： L. dos Santos Coelho P. Alotto Rcductim and Systems Engineering Gmduale Rogmm Aulmation and Systms Labaratcry PUCPR/PPGEPS/LAS Pontifical Catholic University of Paraná Curitiba Parana Brazil Production and Systems Engineering Graduate Program Aulmation and Systms Labaratory Curitiba Parana Brazil Dip. Inssgneria Eldtrica UnivslniU di I'adovn Italy

Recently, evolutionary algorithms (e.g. genetic algorithms, evolutionary programming, and evolution strategies) have proven to be useful tools for the optimization of difficult problems in electromagnetics. Differential evolution (DE) is one comparatively simple variant of an evolutionary algorithm using floating-point encoding and few control parameters. This work presents improved DE algorithms based on linearly time varying control parameters, sinusoidal functions, and diversity analysis of population

关键词： Electromagnetic devices Optimization methods Algorithm design and analysis Evolutionary computation USA Councils Writing Differential equations Encoding Convergence of numerical methods Testing

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Artificial Intelligence-Based Recommendation System for Detecting and Diagnosing Broken Bars in Induction Motors Under Transient Operation

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IFAC-PapersOnLine 2024年第19期58卷 1156-1161页

作者： Narco A.R. Maciejewski Roberto Z. Freire Anderson L. Szejka Thiago P.M. Bazzo Sofia M.A. Lopes Rogério A. Flauzino Department of Electrical Engineering - DAELT-CT Universidade Tecnológica Federal do Paraná - UTFPR Curitiba PR 80230-90 Brazil Production and Systems Engineering - PPGEPS-PB Energy Systems - PPGSE-CT Industrial and Systems Engineering Graduate Program - PPGEPS Pontifical Catholic University of Parana - PUCPR Curitiba PR 80215-901 Brazil Electrical Engineering - PPGEE-SC São Carlos School of Engineering - EESC Universidade de São Paulo - USP São Carlos SP 13566-590 Brazil

Three-phase induction motors are the main elements for converting electrical energy into mechanical energy and are extensively used in industry. Reducing maintenance costs becomes an incentive for developing systems capable of identifying defects. This research proposes a framework for recommending machine learning algorithms that diagnose and detect broken bar defects in three-phase induction motors under transient operation based on artificial intelligence. Employing experimental data, features were extracted and selected based on current, voltage, and vibration. A protocol of insertion of white noise showed that the proposed framework admitted 80% of noise without losing the predictive capacity based on a multicriteria performance measure.

关键词： condition monitoring fault detection fault classification machine learning maintenance engineering smart systems three-phase induction motor

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Image-guided targeting of mitochondrial metabolism sensitizes pediatric malignant rhabdoid tumors to low-dose radiotherapy

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Science Advances 2025年第21期11卷 eadv2930页

作者： Wenxi Xia Esther Need Carmine Schiavone Neetu Singh Jiemin Huang Matthew Goff Joseph Cave David L. Gillespie Randy L. Jensen Mark D. Pagel Prashant Dogra Sixiang Shi Shreya Goel Department of Molecular Pharmaceutics University of Utah Salt Lake City UT 84112 USA. Mathematics in Medicine Program Department of Medicine Houston Methodist Research Institute Houston TX 77030 USA. Department of Chemical Materials and Industrial Production Engineering University of Naples Federico II Naples Italy. Physiology Biophysics and Systems Biology Program Graduate School of Medical Sciences Weill Cornell Medicine New York NY 10065 USA. Department of Neurosurgery Huntsman Cancer Institute University of Utah Salt Lake City UT 84132 USA. Department of Medical Physics University of Wisconsin-Madison Madison WI 53705 USA. Department of Physiology and Biophysics Weill Cornell Medical College New York NY 10065 USA. Department of Radiology and Imaging Sciences University of Utah Salt Lake City UT 84112 USA. Department of Biomedical Engineering University of Utah Salt Lake City UT 84112 USA.

Tumor hypoxia leads to radioresistance and markedly worse clinical outcomes for pediatric malignant rhabdoid tumors (MRTs). Our transcriptomics and bioenergetic profiling data reveal that mitochondrial oxidative phosphorylation is a metabolic vulnerability of MRT and can be exploited to overcome consumptive hypoxia by repurposing an FDA-approved antimalarial drug, atovaquone (AVO). We then establish the utility of oxygen-enhanced-multispectral optoacoustic tomography, a label-free, ionizing radiation-free imaging modality, to visualize and quantify spatiotemporal changes in tumor hypoxia in response to AVO. We show a potent but transient increase in tumor oxygenation upon AVO treatment that results in complete elimination of tumors in all tested mice when combined with 10-gray radiotherapy, a dose several times lower than the current clinic standard. Last, we use translational mathematical modeling for systematic evaluation of dosing regimens, administration timing, and therapeutic synergy in a virtual patient cohort. Together, our work establishes a framework for safe and pediatric patient-friendly image-guided metabolic radiosensitization of rhabdoid tumors.

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Use of corncob and pineapple peel as associated substrates for biosurfactant production

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Environmental Science and Pollution Research 2024年第47期31卷 57973-57988页

作者： Santos, Brenda Lohanny Passos Vieira, Isabela Maria Monteiro Santos, Pablo Omar Lubarino Menezes, Millena Souza de Souza, Roberto Rodrigues Ruzene, Denise Santos Silva, Daniel Pereira Northeastern Biotechnology Network Federal University of Sergipe SE São Cristóvão49100-000 Brazil Center for Exact Sciences and Technology Federal University of Sergipe SE São Cristóvão49100-000 Brazil Graduate Program in Biotechnology Federal University of Sergipe SE São Cristóvão49100-000 Brazil Graduate Program in Intellectual Property Science Federal University of Sergipe SE São Cristóvão49100-000 Brazil CISAS – Center for Research and Development in Agrifood Systems and Sustainability Instituto Politécnico de Viana Do Castelo Viana Do Castelo4900-347 Portugal Department of Production Engineering Federal University of Sergipe Rodovia Marechal Rondon S/N Jardim Rosa Elze Sergipe São Cristóvão49100-000 Brazil

Biosurfactants are amphiphilic biomolecules with promising tensoative and emulsifying properties that find application in the most varied industrial sectors: environment, food, agriculture, petroleum, cosmetics, and hygiene. In the current work, a 23 full-factorial design was performed to evaluate the effect and interactions of pineapple peel and corncob as substrates for biosurfactant production by Bacillus subtilis LMA-ICF-PC 001. In a previous stage, an alkaline pretreatment was applied to corncob samples to extract the xylose-rich hydrolysate. The results indicated that pineapple peel extract and xylose-rich hydrolysate acted as partial glucose substitutes, minimizing production costs with exogenous substrates. Biosurfactant I (obtained at 8.11% pineapple peel extract, 8.11% xylose-rich hydrolysate from corncob, and 2.8109 g/L glucose) exhibited a significant surface tension reduction (52.37%) and a promising bioremediation potential (87.36%). On the other hand, biosurfactant III (obtained at 8.11% pineapple peel extract, 31.89% xylose-rich hydrolysate from corncob, and 2.8109 g/L glucose) exhibited the maximum emulsification index in engine oil (69.60%), the lowest critical micellar concentration (68 mg/L), and the highest biosurfactant production (5.59 g/L). These findings demonstrated that using pineapple peel extract and xylose-rich hydrolysate from corncob effectively supports biosurfactant synthesis by B. subtilis, reinforcing how agro-industrial wastes can substitute traditional carbon sources, contributing to cost reduction and environmental sustainability. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Ananas comosus Bacillus subtilis Zea mays Agro-industrial waste Bioremediation potential Emulsification index Surface tension

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Case Study: Gain Scheduling Adaptive Control Applied on a Didactic Level System

Case Study: Gain Scheduling Adaptive Control Applied on a Di...

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International Carpathian Control Conference (ICCC)

作者： Vinícius Berno Da Silva Paulo César Barros Rodrigues Murillo Ferreira Dos Santos Paolo Mercorelli Milena Faria Pinto Wolmar Araújo Neto Department of Electroelectronics CEFET-MG Leopoldina Brasil Institute for Production Technology and Systems (IPTS) Leuphana University of Lüneburg Germany Graduate Program in Electrical Engineering CEFET-RJ Rio de Janeiro Brasil Federal University of Espírito Santo UFES Vitória Brazil

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

Gain scheduling has been successfully applied in many different areas due to the positive results achieved when applied to nonlinear control. Its utilization enables the controller to respond rapidly to changes in operating conditions. This study demonstrates the application of gain scheduling to a SMAR didactic level system to implement adaptive control. The results exhibited a strong response with minor errors using a Proportional and Integral (PI) controller, which facilitated the development of two generic equations for determining the values of K p (proportional gain) and K i (integral gain) based on the desired set point.

关键词： Adaptive scheduling PI control Liquids System dynamics Integral equations Noise Gain measurement

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Photovoltaic Generation Potential of Paraná State, Brazil – A Comparative Analysis with European Countries

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Energy Procedia 2014年 57卷 725-734页

作者： Gerson Maximo Tiepolo Jair Urbanetz Junior Osiris Canciglieri Junior Trajano Viana Department of Electrical Engineering Technological Federal University of Paraná – UTFPR Avenida Sete de Setembro 3165 80230-901 Curitiba Paraná Brazil Graduate Program in Production Engineering and Systems – PPGEPS Pontifical Catholic University of Parana - PUCPR Rua Imaculada Conceição 115 80215-901 Curitiba Paraná Brazil Federal Center of Technological Education - CEFET/RJ Avenida Maracanã 229 20271-110 Rio de Janeiro Brazil

The theme of sustainable development has increasingly impacted the spheres of Brazilian society and has contributed to greater awareness to the need of natural resources conservation as well as issues on how to continue promoting socio-economic development of regions. One of the key issues for sustainable development is the generation of electricity with more use of renewable sources and, therefore, less environmental degradation. In this scenario, historically, Paraná State of Brazil has been one of the largest producers of electricity in the country, almost entirely from hydraulic source, due to the large existing river basin in the state. However, the use of this source in Brazil is declining due to depletion of water potential and also the pressure of society with respect to environmental, social and economic impacts caused by damming of rivers and flooding of cities and areas to form large reservoirs. To overcome these limitations, other sources have been studied and used, such as biomass and wind. Photovoltaic generation has been contemplated in Brazilian government policies only to supply electricity with off-grid systems in remote locations. However, due to the recent Resolution 482/2012 of ANEEL (Brazilian Electricity Regulatory Agency), which establishes rules for micro and mini-generation of electricity, it is possible that consumers install grid connected photovoltaic systems up to 1 MWp, as have been widely used in the urban environment installed or integrated on roofs as a form of distributed generation, particularly in Europe, where counts with installed capacity in GW range, while in Brazil it counts only with a few MW. Given this new perspective of growth of the Brazilian photovoltaic electricity generation this paper presents the potential of solar photovoltaic power generation in Paraná State, Brazil, with a comparative analysis with the potential presented by some European countries. The presented solar and photovoltaic maps uses irradiation data

关键词： Sustainable Development Renewable Energy Photovoltaic Generation Distributed Generation Public Policy

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Design approach for additive manufacturing in spare part supply chains

arXiv

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arXiv 2020年

作者： de Brito, Filipe Marinho da Cruz Júnior, Gélson Frazzon, Enzo Morosini Basto, João Pedro Tavares Vieira Alcalá, Symone Gomes Soares School of Electrical Mechanical and Computer Engineering Federal University of Goiás GoiâniaGoiás74605-010 Brazil INESC P&D Brasil São Paulo11055-300 Brazil Graduate Program in Production Engineering Department of Production Engineering and Systems Federal University of Santa Catarina Florianópolis88040-900 Brazil Department of Industrial Engineering and Management Faculty of Engineering University of Porto Porto4200-465 Portugal INESC TEC - Technology Faculty of Engineering University of Porto Porto4200-465 Portugal Production Engineering Faculty of Sciences and Technology Federal University of Goiás Aparecida de Goiânia Goiás74968-755 Brazil

In the current industrial revolution, additive manufacturing (AM) embodies a promising technology that can enhance the effectiveness, adaptability, and competitiveness of supply chains (SCs). Moreover, it facilitates the development of distributed SCs, thereby enhancing product availability, inventory levels, and lead time. However, the wide adoption of AM in industrial SCs creates various challenges, leading to new difficulties for SC design. In this context, this paper proposes a new design approach to AM SCs using optimization methods. More specifically, the proposed approach, comprising the pmedian and mixed-integer linear programming models, considers the decision of deploying productive resources (3D printers) in specific locations of generic spare part SCs. The approach was evaluated in a real-world use case of an elevator maintenance service provider. The obtained results demonstrated the promising capabilities of the proposed design approach in managing the challenges arising from the forthcoming widespread use of 3D printers in manufacturing SCs. © 2020, CC-BY-NC-ND.

关键词： 3D printers

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