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2018 International Symposium on Electrical Machines, SME 2018

作者： Gabor, Rafal Kowol, Marcin Kolodziej, Janusz Mynarek, Piotr Opole University of Technology Faculty of Electrical Engineering Automatic Control and Computer Science Opole Poland

ISBN: (纸本)9781538652107

The paper contains a proposition of the application of a SRM motor with a modified stator geometry for an electric drive, in particular in an electric bicycle. The study involved a comparison of the cyclicity of the electromagnetic torque and self-inductance in the function of the rotor angle in 2D and 3D models based on the application of the finite element method. © 2018 IEEE.

关键词： Finite element method

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Forced variational integrator for distance-based shape control with flocking behavior of multi-agent systems

arXiv

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arXiv 2020年

作者： Colombo, Leonardo Moreno, Patricio Ye, Mengbin de Marina, Héctor Garcia Cao, Ming Madrid Spain LAR-GPSIC Facultad de Ingeniería Universidad de Buenos Aires Argentina Optus-Curtin Centre of Excellence in Artificial Intelligence Curtin University Australia Faculty of Physics Department of Computer Architecture and Automatic Control Universidad Complutense de Madrid Madrid Spain Faculty of Science and Engineering ENTEG University of Groningen Netherlands

A multi-agent system designed to achieve distance-based shape control with flocking behavior can be seen as a mechanical system described by a Lagrangian function and subject to additional external forces. Forced variational integrators are given by the discretization of Lagrange-d’Alembert principle for systems subject to external forces, and have proved useful for numerical simulation studies of complex dynamical systems. We derive forced variational integrators that can be employed in the context of control algorithms for distance-based shape with velocity consensus. In particular, we provide an accurate numerical integrator with a lower computational cost than traditional solutions, while preserving the configuration space and symmetries. We also provide an explicit expression for the integration scheme in the case of an arbitrary number of agents with double integrator dynamics. For a numerical comparison of the performances, we use a planar formation consisting of three autonomous agents. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

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Granger-Causality Mining in Atmospheric Visibility Based on Deep Learning 9th

Granger-Causality Mining in Atmospheric Visibility Based on ...

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9th International Conference on Frontier Computing, FC 2019

作者： Liu, Bo He, Xi Li, Jianqiang Qu, Guangzhi Lang, Jianlei Gu, Rentao Faculty of Information Technology School of Software Engineering Beijing University of Technology Beijing100124 China Computer Science and Engineering Department Oakland University RochesterMI48309 United States Key Laboratory of Beijing on Regional Air Pollution Control College of Environmental and Energy Engineering Beijing University of Technology Beijing100124 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789811532498

Causal relationship mining of multi-dimensional meteorological time series data can reveal the potential connection between visibility and other influencing factors, and it is meaningful in terms of environmental management, air pollution chasing, and haze control. However, because causality analysis based on statistical methods or traditional machine learning techniques cannot represent the complex relationship between visibility and its influencing factors, as an extension of traditional Granger-causality analysis, we propose a causality mining method based on the seq2seq-LSTM deep learning model. The method can profoundly reveal the hidden relationship between different features and visibility and the regular pattern of bad weather, which can provide theoretical support for air pollution control. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Time series

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Structural Decomposition Approach to Design of No-Wait Cyclic Schedules for Repeatedly Operating Transport System Dedicated to Supply Loops

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IFAC-PapersOnLine 2020年第2期53卷 10542-10549页

作者： Robert Wójcik Arkadiusz Gola Jarosław Pempera Justyna Patalas-Maliszewska Department of Computer Engineering Faculty of Electronics Wrocław University of Science and Technology Wrocław Poland Institute of Technological Systems of Information Lublin University of Technology Lublin Poland Department of Control Systems and Mechatronics Faculty of Electronics Wrocław University of Science and Technology Wrocław Poland Institute of Mechanical Engineering University of Zielona Góra Zielona Góra Poland

The paper presents a method allowing to construct no-wait cyclical schedules for repetitive transport systems (e.g. the milk-run) servicing cyclic material supply loops in the production system using selected means of transport (e.g. AGVs). The transport means are following established routes and given arrival times. The routes are composed of sectors linking workstations. Transport trolleys may share specific sectors of the route in mutual exclusion mode and must wait in a given sector to enter the next sector of the route when another trolley occupies it. The job-shop repetitive transportation system is a system of cyclic processes with a fixed structure that are executing sequences of operations (routes) using shared resources (sectors). The work aims to find a no-wait cyclic schedule that guarantees the required delivery dates or establish that such a schedule does not exist. It considers cyclic process systems for which each resource can be used by at most two operations, and the deadlock state cannot occur as a result of waiting processes on shared resources. For specified initial operations of cyclic processes and their start times (the initial system state), the problem of determining no-wait cyclical schedules decomposes into subproblems. Each subproblem consists of the verification of necessary and sufficient conditions for the existence of solutions for each of 2-process subsystems composed of one shared resource and two processes using this resource. The method aims of prototyping various variants of process starting times for which the conditions guaranteeing no-wait property of the system hold simultaneously for each of the 2-process subsystems. It allows designing cyclic schedules for complex systems composed of 2-process subsystems that are structurally deadlock-free. The class of cyclical processes considered in this article is broader than the class of cascade-like (chain-like, sequential) process systems analysed so far in the literature. In this

关键词： repetitive delivery systems milk-run routing scheduling vehicle routing problem job-shop type transportation systems resource blocking deadlock problem no-wait cyclic schedule two cyclic processes with a shared resource decomposition of the system structure

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ARIMA Models for Predicting the End of COVID-19 Pandemic and the Risk of a Second Rebound

Research Square

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Research Square 2020年

作者： Malki, Zohair Atlam, El-Sayed Ewis, Ashraf Dagnew, Guesh Alzighaibi, Ahmad Reda Elmarhomy, Ghada Elhosseini, Mostafa A. Hassanien, Aboul Ella Gad, Ibrahim College of Computer Science and Engineering Taibah University Yanbu Saudi Arabia Faculty of Science Tanta University Egypt Department of Public Health and Occupational Medicine Faculty of Medicine Minia University El-Minia Egypt Department of Public Health Faculty of Health Sciences – AlQunfudah Umm AlQura University Mecca Saudi Arabia Department of Computer Science Institute of Technology Dire Dawa University Ethiopia Mansoura University Computers Engineering and Control Systems Department Faculty of Engineering Mansoura Egypt Faculty of Computers and Artificial Intelligence Cairo University Egypt

Globally, many research works are going on to study the infectious nature of COVID-19 and every day we learn something new about it through the flooding of the huge data that are accumulating hourly rather than daily which instantly opens hot research topics for artificial intelligence researchers. However, the public’s concern by now is to find answers for two questions;1) when this COVID-19 pandemic will be over? and 2) After coming to its end, will COVID-19 return again in what is known as a second rebound of the pandemic?. This research developed a predictive model that can estimate the expected period of time that the virus can possibly stopped and the risk of a second rebound of COVID-19 pandemic. Therefore, this study considered SARIMA model to predict the spread of the virus on several selected countries and is used for pandemic life cycle and end date predictions. The study can be applied to predict the same for other countries as the nature of the virus is the same everywhere. The advantages of this study are that it helps the governments in making decisions and planning now for the future, reduces anxiety and prepares the mentality of people for the next phases of the pandemic. The most striking finding to emerge from this experimental and simulation study is that the proposed algorithm show that the expected COVID-19 infections for the top countries of highest number of confirmed case will slowdown in October, 2020. Moreover, our study forecasts that there may be a second rebound of the pandemic in a year time, if the current taken precautions are eased completely. We have to consider the uncertain nature of the current COVID-19 pandemic and the growing inter-connected and complex world, what are ultimately required are the flexibility, robustness and resilience to cope up the unexpected future events and scenarios. © 2020, CC BY.

关键词： COVID-19

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Imitation dynamics in population games on community networks

arXiv

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arXiv 2020年

作者： Como, Giacomo Fagnani, Fabio Zino, Lorenzo Department of Mathematical Sciences "G.L. Lagrange " Politecnico di Torino Torino10129 Italy Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Department of Automatic Control Lund University Lund22100 Sweden

We study the asymptotic behavior of deterministic, continuous-time imitation dynamics for population games over networks. The basic assumption of this learning mechanism — encompassing the replicator dynamics— is that players belonging to a single population exchange information through pairwise interactions, whereby they get aware of the actions played by the other players and the corresponding rewards. Using this information, they can revise their current action, imitating the one of the players they interact with. The pattern of interactions regulating the learning process is determined by a community structure. First, the set of equilibrium points of such network imitation dynamics is characterized. Second, for the class of potential games and for undirected and connected community networks, global asymptotic convergence is proved. In particular, our results guarantee convergence to a Nash equilibrium from every fully supported initial population state in the special case when the Nash equilibria are isolated and fully supported. Examples and numerical simulations are offered to validate the theoretical results and counterexamples are discussed for scenarios when the assumptions on the community structure are not verified. Copyright © 2020, The Authors. All rights reserved.

关键词： Game theory

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Multi-model least squares-based recomputation framework for large data analysis

arXiv

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arXiv 2021年

作者： Zhang, Wandong Wu, Q.M. Jonathan Yang, Yimin Zhao, W.G. Will Wang, TianLei Zhang, Hui Department of Electrical and Computer Engineering University of Windsor Windsor Canada Department of Computer Science Lakehead University Thunder Bay Canada Vector Institute for Artificial Intelligence Toronto Canada Faculty of Business Administration Lakehead University Canada Artificial Intelligence Group CEGEP de Ste Foy Canada Institute of Information and Control Hangzhou Dianzi University Hangzhou China School of Robotics Hunan University Changsha China

Most multilayer least squares (LS)-based neural networks, such as deep random vector functional link (RVFL), are structured with two separate stages: unsupervised feature encoding and supervised pattern classification. Once the unsupervised learning is finished, the latent encoding would be fixed without supervised fine-tuning. However, in complex tasks such as handling the ImageNet dataset, there are often many more clues that can be directly encoded, while the unsupervised learning, by definition, cannot know exactly what is useful for a certain task. There is a need to retrain the latent space representations in the supervised classification stage to learn some clues that unsupervised learning has not yet learned. In particular, the error matrix from the output layer is pulled back to each hidden layer, and the parameters of the hidden layer are recalculated with Moore-Penrose (MP) inverse for more generalized representations. In this paper, a recomputation-based multilayer network using MP inverse (RML-MP) is developed. A sparse RML-MP (SRML-MP) model to boost the performance of RML-MP is then proposed. The experimental results with varying training samples (from 3 K to 1.8 M) show that the proposed models provide better generalization performance than most representation learning algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal encoding

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Eddy Current Method in Non-Magnetic Aluminide Coating Thickness Assessment

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Journal of Nondestructive Evaluation 2025年第3期44卷

作者： Tytko, Grzegorz Adamczyk-Habrajska, Malgorzata Li, Yong Pengpeng, Shi Kopec, Mateusz Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland Faculty of Science and Technology University of Silesia Chorzów41-500 Poland State Key Laboratory for Strength and Vibration of Mechanical Structures Shaanxi Engineering Research Centre of NDT and Structural Integrity Evaluation Xi’an Jiaotong University Shaanxi Xi’an China School of Mathematics and Statistics Ningxia University Ningxia Yinchuan750021 China Institute of Fundamental Technological Research Polish Academy of Sciences Pawińskiego 5B Warsaw02-106 Poland

This study investigates the use of eddy current testing (ECT) as a non-destructive technique to evaluate the thickness and structural variations of non-magnetic aluminide coatings on MAR-M247 nickel-based superalloy. Coatings with thicknesses of 20 μm and 40 μm were applied to substrates exhibiting fine, coarse, and columnar grain structures. Using sensors of different geometries, impedance measurements were performed within a frequency range of 11.5 MHz to 12.5 MHz. Results demonstrated the designed sensor’s superior sensitivity, with the highest values of absolute resistance difference significantly exceeding the threshold for reliable distinction due to coating thicknesses or grain structures. The study highlights the impact of eddy current penetration depth and edge effects on the measurement accuracy, emphasizing the need for optimized sensor design and frequency selection. Findings confirm the efficacy of ECT in differentiating coatings of varying thicknesses and substrate structures, offering a reliable tool for quality control in high-temperature applications. © The Author(s) 2025.

关键词： Eddy current testing

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AI and Reading Fluency for Brazilian Portuguese: A Preliminary Study

SSRN

引用

SSRN 2023年

作者： Rodrigues, Aline Do Nascimento Ribeiro, Gabriela L. Silva, Victor H.A. Carvalho, Wesley S. Ramírez, Miguel A. Alves, Luciana M. Finger, Marcelo Navas, Ana Luiza G.P. Ribeiro, Carlos H.C. Computer Science Division Aeronautics Institute of Technology Praça Mal. Eduardo Gomes 50 SP Sao Jose dos Campos12228-900 Brazil Federal University of Minas Gerais Medicine Faculty Department of Speech Therapy Av. Prof. Alfredo Balena 190 MG Belo Horizonte30130-100 Brazil University of Sao Paulo Escola Politecnica Department of Telecommunications and Control Engineering Av. Prof. Luciano Gualberto trav. 3 158 SP Sao Paulo05508-010 Brazil University of Sao Paulo Institute of Mathematics and Statistics Department of Computer Science Rua do Matao 1010 SP Sao Paulo05508-090 Brazil University of Sao Paulo Escola Politecnica Department of Electronic Systems Engineering Av. Prof. Luciano Gualberto trav. 3 158 SP Sao Paulo05508-010 Brazil School of Medical Sciences of Santa Casa de Sao Paulo Department of Speech Therapy R. Dr. Cesario Motta Jr. 61 SP Sao Paulo01221-020 Brazil

automatic assessment of oral reading fluency — either for completely autonomous operation or as a facilitator for human decision making — is a likely requirement for timely interventions regarding educational policies for Literacy, especially at the initial years of formal Education. Countries with huge populations such as Brazil have a more urgent demand for such automated procedures, considering the scale of the evaluation needs and the disproportional lack of specialized personnel, compared to more advanced countries. Nevertheless, computational methods as educational aids for Literacy evaluation have been developed mainly for English and other languages associated with those high income countries. Therefore there is an obvious need for studies on languages and countries (especially those with large educational populations) that are less developed. We report on a computational model for fluency assessment based on an automatic speech recognizer (ASR) readily available in the software literature, trained via a deep learning model on a publicly available dataset for Brazilian Portuguese. The model was previously trained for ASR purposes, and therefore was not designed for Literacy assessment of children, this aspect was dealt with through a series of pre and post-processing of the audio samples. Extensive comparative results on reading oral fluency for standardized assessment texts considering the proposed automated process compared to a benchmark by human expert annotations showed a high matching for measures on word and word error rates, despite the fact that the learning model did not include samples from the target population. © 2023, The Authors. All rights reserved.

关键词： Computational methods

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On a Network SIS Model with Opinion Dynamics

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IFAC-PapersOnLine 2020年第2期53卷 2582-2587页

作者： Weihao Xuan Ruijie Ren Philip E. Paré Mengbin Ye Sebastian Ruf Ji Liu School of Mechanical Engineering at University of Leeds UK Division of Decision and Control Systems at KTH Royal Institute of Technology Stockholm Sweden Faculty of Science and Engineering ENTEG University of Groningen Netherlands Center for Complex Networks Research and the Department of Psychology at Northeastern University USA Department of Electrical and Computer Engineering at Stony Brook University USA

This paper proposes a network continuous-time susceptible-infected-susceptible (SIS) model coupled with individual opinion dynamics, where the opinion dynamics models an individual’s perceived severity of illness or perceived susceptibility. The effects of opinion dynamics on the network SIS model are studied by analyzing the limiting behaviors of the system model, equilibria of the system and their stability.

关键词： SIS model opinion dynamics health belief model

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