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Comprehensive multimodal approach for Parkinson’s disease classification using artificial intelligence: insights and model explainability

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Soft Computing 2025年第3期29卷 1845-1877页

作者： balaha, Hossam Magdy Hassan, Asmaa El-Sayed Ahmed, Rawan Ayman balaha, Magdy Hassan Bioengineering Department J.B. Speed School of Engineering University of Louisville LouisvilleKY United States Computer Science and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Mathematics and Engineering Physics Department Faculty of Engineering Mansoura University Mansoura Egypt Department of Obstetrics and Gynecology Faculty of Medicine Tanta University Tanta Egypt

Parkinson’s disease (PD) is a debilitating neurodegenerative disorder affecting millions worldwide. Early detection is vital for effective management, yet remains challenging. In this study, we investigated four distinct datasets for PD detection. Through comprehensive experimentation employing ensemble methods and feature selection, we achieved high classification accuracies across the datasets. For the Oxford Parkinson’s Disease Detection Dataset, an accuracy of 95.67%, precision of 97.59%, recall of 84.5%, specificity of 99.32%, and F1-score of 90.57% were achieved. For the Alzheimer Parkinson Diseases 3 Class Dataset, the "Stacking" approach surpasses individual models, reaching an accuracy of 99.85%, precision of 99.81%, recall of 99.81%, specificity of 99.86%, and F1 of 99.81%. For the NewHandPD dataset, Regarding the Spiral category, The "base-P32-384" model surpasses others with an accuracy of 97.35%, precision of 96.50%, recall of 98.57%, and F1-score of 97.53%. The collective "Stacking" approach proves highly effective regarding the Circle category, achieving 100% across all performance metrics. Regarding the Meander category, the "base-P16-224" model achieves an accuracy of 97.35%, precision of 99.26%, recall of 95.71%, specificity of 99.19%, and F1 of 97.45%. The Mobile Device Voice Recordings at King’s College London (MDVR-KCL) dataset contains two datasets. Regarding the "SpontaneousDialogue" dataset, accuracy, bAC, precision, recall, specificity, and F1-score were computed, resulting in values of 94.03%, 92.83%, 90.78%, 100.0%, and 85.67%, respectively. Regarding the "ReadText" dataset, accuracy, bAC, precision, recall, specificity, and F1-score were computed, resulting in values of 91.89%, 90.62%, 87.5%, 100.0%, and 81.25%, respectively. Our findings highlight the efficacy of leveraging diverse data sources and advanced machine learning techniques to enhance PD detection accuracy. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germa

关键词： Neurodegenerative diseases

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Model Identification and control of Electromagnetic Actuation in Continuous Casting Process With Improved Quality

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 203-215页

作者： Isabela birs Cristina Muresan Dana Copot Clara Ionescu Research Group of Dynamical Systems and Control Faculty of Engineering and ArchitectureGhent University and with EEDT Decision&ControlFlanders Make ConsortiumTech Lane Science Park 125 and 131B-9052 GhentBelgium.I.Birs the Automation Department Faculty of Automation and Applied InformaticsTechnical University of Cluj-NapocaRomania IEEE

This paper presents an original theoretical framework to model steel material properties in continuous casting line process. Specific properties arising from non-Newtonian dynamics are herein used to indicate the natural convergence of distributed parameter systems to fractional order transfer function models. Data driven identification from a real continuous casting line is used to identify model of the electromagnetic actuator device to control flow velocity of liquid steel. To ensure product specifications, a fractional order control is designed and validated on the system. A projection of the closed loop performance onto the quality assessment at end production line is also given in this paper.

关键词： Electromagnetic actuator fractional order control fractional order system model non-Newtonian material

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Assessment of Dangerous Traffic Situations for Autonomous Vehicles

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Periodica Polytechnica Transportation engineering 2022年第3期50卷 260-266页

作者： Galántai, Péter Department of Control for Transportation and Vehicle Systems Faculty of Transportation and Engineering and Vehicle Engineering Budapest University of Technology and Economics P.O.B. 91 BudapestH-1521 Hungary

This article will show some dangerous situations with autonomous vehicles. The main question in this article is how does the ACC (Adaptive Cruise control) as an autonomous vehicle function work? In which cases must the driver act and how. The research showed some real life examples based on a Euro NCAP test. The car manufacturers say that the modern ACC systems can be well used in urban traffic, especially in traffic jam, but there can be some critical situations which can cause an accident if the driver does not act. These situations are collected in this article. The main aim of the article is to identify a methodological framework for estimating the proper operation conditions related to the analyzed automated driving assistant systems. © 2022 budapest University of Technology and Economics. All rights reserved.

关键词： Autonomous vehicles

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Analytic Mechanism for the Cumulative Effect of Wind Power Fluctuations from Single Wind Farm to Wind Farm Cluster

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CSEE Journal of Power and Energy systems 2022年第5期8卷 1290-1301页

作者： Gang Mu Fangze Wu Xiaoping Zhang Ziheng Fu bai Xiao Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China Department of Electronic Electrical and Systems EngineeringSchool of EngineeringUniversity of BirminghamBirmingham B152TTU.K

The use of wind power is rapidly growing worldwide as a means of reducing carbon emissions for the energy *** has the world’s largest wind power installation and multiple large-scale wind farm clusters,each comprising dozens of wind *** the planning and operation of the power system,it is important to understand the power fluctuation characteristics of wind farm *** studies demonstrate that the relative power fluctuation of a wind farm cluster is less than that of a single wind *** this decreasing trend a random occurrence or does it have a regular pattern?This scientific question is addressed by investigating the mechanism of the cumulative effect of a wind farm *** this study,a cumulative model is proposed by examining the spatiotemporal relationships of wind power variations and wind farm *** gain function and critical cumulative frequency are defined as the foundations to analytically describing the cumulative *** investigating the cumulative effect mechanism,the relationship between power fluctuation and spatiotemporal parameters of the wind farm cluster are *** power fluctuation of a cluster can be predicted using the cumulative model even before it is completely *** mechanism of the cumulative effect is validated on the basis of the data of two actual wind farm clusters.

关键词： Analytic mechanism cumulative effect evolution regularity wind farm cluster wind power fluctuation

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Nonlinear Model Predictive control for Autonomous Sailboat with Optimization of Sail Angle

Nonlinear Model Predictive Control for Autonomous Sailboat w...

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OCEANS 2024 - Halifax, OCEANS 2024

作者： Wu, Junzhuo Pan, Ya-Jun Shen, Chao Smith, Sean Witrant, Emmanuel Dalhousie University Advanced Control and Mechatronics Lab Department of Mechanical Engineering HalifaxB3H 4R2 Canada Carleton University Department of Systems and Computer Engineering OttawaK1S-5B6 Canada Université Grenoble Alpes-CNRS GIPSA-lab GrenobleF-38000 France Dalhousie University Departement of Mechanical Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9798331540081

This paper studies trajectory tracking control problems of sailing vessels using a nonlinear model predictive control (NMPC) approach with a novel sail angle optimization approach. The proposed sail angle optimization method accounts for physical constraints during practical implementation such as operational sail angle bound and rate of change in sail angles. This technique also emphasizes the potential to use the sail to plan a safe trajectory, while a simple proportional-derivative (PD) controller is used for rudder angle regulation. The NMPC is implemented for trajectory tracking control in the simulation. Results show that the proposed controller can achieve excellent tracking performance in the presence of environmental disturbances in terms of ocean waves. © 2024 IEEE.

关键词： Water waves

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Securing the Future after Pager bombs:Lifecycle Protection of Smart Devices via blockchain Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2355-2358页

作者： Fei Lin Qinghua Ni Jing Yang Juanjuan Li Nan Zheng Levente Kovács Radu Prodan Mariagrazia Dotoli Qing-Long Han Fei-Yue Wang the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBei-jing 100049China IEEE Obuda University John von Neumann Faculty of InformaticsBecsi Str.96/bH-1034 BudapestHungary the Institute of Information Technology University of Klagenfurt9020 Klagenfurt am WortherseeAustria the Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190

THE Lebanese wireless device explosion incident has drawn widespread attention,involving devices such as pagers,walkie-talkies,and other common devices[1].This event has revealed and highlighted the security vulnerabilities in global supply chains from raw material manufacturing and distribution to the usage of devices and equipment,signaling the onset of a new wave of"supply chain warfare"[2].

关键词： Smart cycle chains

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Robust Frequency Regulation for Dual-Area Interconnected Grids Using Hybrid controller: A Comparative Study 3

Robust Frequency Regulation for Dual-Area Interconnected Gri...

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3rd IEEE International Conference on Smart Technologies for Power, Energy and control, STPEC 2023

作者： Wazir, Awadh ba Alhussainy, Abdullah A. Alobaidi, Abdulraheem H. Altaf, Aatif Kumar, Anil Kumar, Mahendra Alghamdi, Sultan King Abdulaziz University Faculty of Engineering Department of Electrical and Computer Engineering Jeddah Saudi Arabia King Abdulaziz University Center of Research Excellence in Renewable Energy and Power Systems Jeddah Saudi Arabia Dr. B R Ambedkar National Institute of Technology Jalandhar Instrumentation and Control Engineering Department Punjab Jalandhar India

ISBN: (纸本)9798350304732

This paper introduces a robust controller designed for load frequency control in a dual-area integrated power grid. Here, the suggested controller is a blend of a fuzzy logic controller with an integral controller. The parameters of the integral controller and frequency bias settings are optimized to enhance the dynamic response of the proposed controller. To attain this, three distinct optimization algorithms are employed, i.e., genetic algorithm, simulated annealing, and pattern search. A new objective function using settling time, settling-max, and settling-min with a suitable weight factor is used to improve the parameters estimation process. A comparative analysis is performed using the proposed approach and classical-I controller under two cases considering several load disturbance scenarios. Furthermore, the suggested hybrid controller is evaluated and compared with similar models in the literature. As expected, the proposed controller exhibits superior performance. © 2023 IEEE.

关键词： Fuzzy logic controller integral controller load frequency control optimization technique parameter estimation

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Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear systems ⁎

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IFAC-PapersOnLine 2024年第15期58卷 265-270页

作者： Patrick J.W. Koelewijn Rajiv Singh Peter Seiler Roland Tóth Sioux Technologies B.V. Eindhoven The Netherlands Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands The MathWorks Inc. Natick USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor USA Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples.

关键词： Reduced-order modeling Neural Networks Linear Parameter-Varying Models

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Fractional order MRAC control design for a lightning system based on a fractional order second degree model

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IFAC-PapersOnLine 2024年第12期58卷 95-100页

作者： Samir Ladaci Seif Eddine Khelas Amani R Ynineb Dana Copot Clara-Mihaela Ionescu Ecole Nationale Polytechnique Depart. Automatic Control Eng. El Harrach 16200 Algiers Algeria National Polytechnic School of Constantine E.E.A. Department 25100 Constantine Algeria Research Group on Dynamical Systems and Control Department of Electromechanical Systems and Metal Engineering Ghent University B-9052 Ghent Belgium

This paper presents a new adaptive fractional-order MRAC controller design for the class of non-integer second-order systems. The update of the control law gains follows a derivative of fractional order equal to the order of the controlled system model. The stability analysis of the control system has been performed based on Lyapunov theorem. We apply this control law to an experimental multivariable lightning system. The results obtained show the efficiency and performance improvement of the proposed control solution compared to the classical MRAC.

关键词： Fractional order system adaptive control MRAC FOMRAC Lightning system

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