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Prediction of solid particle erosion behavior in PMMA using artificial neural network and metaheuristic algorithms

Neural Computing and Applications 2024年第4期37卷 2825-2847页

作者： Fidan, Sinan Ürgün, Satılmış Yiğit, Halil Faculty of Aeronautics and Astronautics Department of Airframe and Powerplant Maintenance Kocaeli University Kocaeli Turkey Faculty of Aeronautics and Astronautics Department of Aviation Electrics and Electronics Kocaeli University Kocaeli Turkey Faculty of Technology Information Systems Engineering Department of Information Systems Engineering Kocaeli University Kocaeli Turkey

This paper aims to predict and optimize the behavior of solid particle erosion in polymethyl methacrylate material through artificial neural networks assisted with the implementation of metaheuristic algorithms. For the study, artificial neural networks (ANNs) and the corresponding metaheuristic algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO), whale optimization algorithm (WOA), gray wolf optimizer (GWO), student psychology-based optimization algorithm (SPBO), ant lion optimizer (ALO), teaching learning-based optimization (TLBO), equilibrium optimizer (EO), flow direction algorithm (FDA), and covariance matrix adaptation evolution strategy (CMA-ES) have been implemented along with jellyfish search optimizer (JSO) to predict the erosion rate and erosion velocity of poly methyl methacrylate (PMMA) eroded by white aluminum oxide at different impact angles and particle sizes. It was indicated that ANN and metaheuristic prediction models were suited to the experimental results, affirming that the approach used is a successful one in predicting solid particle erosion of polymeric materials. JSO exhibited the most robust results with the lowest standard deviation of the erosion rate. In the present study, it is observed that the experimental data are in good agreement with what is obtained from the ANN model fed with input parameters optimized using various metaheuristic algorithms. In the experiment, characterization with polynomials was done regarding the aluminum oxide (Al2O3) abrasive particles' erosion behavior on PMMA at three different mesh sizes and three different blasting pressures. These polynomials were used as the fitness functions for the metaheuristic algorithms applied. The results show that the combined use of ANNs and metaheuristics yields even higher prediction accuracy than those provided by each alone. The JSO algorithm has demonstrated excellence in erosion rate and amount and in its ability to optimize over other approac

关键词： Particle swarm optimization (PSO)

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Development of an IoT-Based Water Pumping Management System for Rice Fields 13

Development of an IoT-Based Water Pumping Management System ...

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13th International Electrical engineering Congress, iEECON 2025

作者： Yanuchit, Chirapong Pislae-Ngam, Kattakamon Kumkhet, Boonyarit Pukrongta, Nisit Sangmahamad, Pubet Pirajnanchai, Virote Digital Media Technology Faculty of Mass Communication Technology Thailand Information Systems Faculty of Busineess of Administration Thailand Electronics and Telecommunication Engineering Faculty of Engineering Thailand

ISBN: (纸本)9798331543952

Efficient water management is essential for rice cultivation. This requires a large amount of water resources to keep the plants healthy and have maximum yields. Traditional pumping methods, which rely on manual monitoring and control, are time-consuming and often result in water waste and potential equipment theft. This paper proposes the development of an IoT-based automated pumping management system specifically designed to support farmers who grow rice. The system uses an ESP32 microcontroller, a 3-level water level sensor, and a GPS module for real-time water level monitoring and pump control. Notifications are included with the LINE application, allowing farmers to be notified about the water level and location of the pump, thereby reducing the risk of theft. The experimental results found high accuracy in water level monitoring and pump control, with a 100% success rate in preventing overflow and reducing wasteful water consumption. This system provides a reliable and resource-efficient solution for remote water management in the agricultural sector. This helps to increase the sustainability of water use for rice cultivation. © 2025 IEEE.

关键词： Fluoridation

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A New Hybrid Model for Segmentation of the Skin Lesion Based on Residual Attention U-Net

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Computers, Materials & Continua 2023年第6期75卷 5177-5192页

作者： Saleh Naif Almuayqil Reham Arnous Noha Sakr Magdy M.Fadel Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia Department of Communications and Electronics Delta Higher Institute for Engineering and Technology(DHIET)MansouraEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Skin segmentation participates significantly in various biomedical applications,such as skin cancer identification and skin lesion *** paper presents a novel framework for segmenting the *** framework contains two main stages:The first stage is for removing different types of noises from the dermoscopic images,such as hair,speckle,and impulse noise,and the second stage is for segmentation of the dermoscopic images using an attention residual U-shaped Network(U-Net).The framework uses variational Autoencoders(VAEs)for removing the hair noises,the Generative Adversarial Denoising Network(DGAN-Net),the Denoising U-shaped U-Net(D-U-NET),and Batch Renormalization U-Net(Br-U-NET)for remov-ing the speckle noise,and the Laplacian Vector Median Filter(MLVMF)for removing the impulse *** the second main stage,the residual attention u-net was used for *** framework achieves(35.11,31.26,27.01,and 26.16),(36.34,33.23,31.32,and 28.65),and(36.33,32.21,28.54,and 27.11)for removing hair,speckle,and impulse noise,respectively,based on Peak Signal Noise Ratio(PSNR)at the level of(0.1,0.25,0.5,and 0.75)of *** framework also achieves an accuracy of nearly 94.26 in the dice score in the process of segmentation before removing noise and 95.22 after removing different types of *** experiments have shown the efficiency of the used model in removing noise according to the structural similarity index measure(SSIM)and PSNR and in the segmentation process as well.

关键词： Skin tumor speckle noise impulse noise hair noise deep learning segmentation

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Power optimization of photovoltaic modules under varying environmental conditions based on current equalization collaborating with constant voltage control

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Clean Energy 2024年第4期8卷 169-182页

作者： DaiBin Tang Fei Lu Siaw Tzer Hwai Gilbert Thio School of Electrical Engineering Anhui Technical College of Mechanical and Electrical EngineeringWuhu 241002China Centre for Sustainability in Advanced Electrical and Electronics Systems(CSAEES) Faculty of EngineeringBuilt Environment and Information TechnologySEGi University47810 Petaling JayaSelangorMalaysia

The performance of photovoltaic(PV)modules is affected by environmental factors such as irradiance and temperature,which can lead to a decrease in output performance or even *** study proposes an improved formula for calculating the real maximum power of PV modules by analysing the influence of irradiance and temperature.A simulation model is developed using PLECS software to simulate the global maximum power of PV modules under different environmental conditions and the results are compared with the calculated real maximum power.A power optimization scheme for PV modules is then proposed based on current equalization and constant voltage *** scheme employs a single-switch multi-winding forward-flyback converter to equalize the mismatched currents between cell strings,thereby enhancing the output *** proportional-integral controllers are utilized to achieve constant voltage control and obtain the real maximum power of PV *** models are built in the PLECS simulation platform to evaluate the performance of a global maximum power point tracking scheme based on the traditional perturb-and-observe(TPO)algorithm with current equalization,a segment perturb-and-observe algorithm without current equalization,and the proposed power optimization *** simulation results demonstrate that the proposed constant voltage control has greater efficiency than the TPO *** proposed scheme achieves a significant improvement in efficiency,with a 27.87%increase compared with the segment perturb-and-observe algorithm without current equalization.

关键词： current equalization constant voltage control forward-flyback converter PV modules perturb-and-observe(P&O)algorithm

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Fuzzy clustering for electric field characterization and its application to thunderstorm interpretability

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Digital Communications and Networks 2025年第2期11卷 299-307页

作者： Xu Yang Hongyan Xing Xinyuan Ji Wei Xu Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye University34010 IstanbulTurkey

Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm ***,little attention has been paid to the ambiguous weather information implicit in AEFS *** this paper,a Fuzzy C-Means(FCM)clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by ***,a time series dataset is created in the time domain using AEFS *** AEFS-based weather is evaluated according to the time-series Membership Degree(MD)changes obtained by inputting this dataset into the ***,thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF ***,a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space ***,the rationality and reliability of the proposed method are verified by combining radar charts and expert *** results confirm that this method accurately characterizes the weather attributes and changes in the AEFS,and a negative distance-MD correlation is obtained for the first *** detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.

关键词： Atmospheric electric field(AEF) Thunderstorm Fuzzy C-means(FCM) Attribute

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Optimizing Power Consumption in Data Centers Through Intelligent Load Balancing Algorithms 8

Optimizing Power Consumption in Data Centers Through Intelli...

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Cengiz, Korhan Biruni University Department of Electrical-Electronics Engineering Istanbul Turkey University of Jordan Faculty of Information Technology and Systems Jordan

ISBN: (纸本)9798350354423

Efficiently managing energy consumption, optimizing resource allocation, and improving computational performance are crucial objectives in contemporary data processing environments. This paper presents a novel methodology designed to address these challenges effectively. This paper introduces a novel methodology aimed at enhancing energy efficiency, optimizing resource utilization, and improving computational performance in data processing tasks. Through rigorous experimentation and analysis, our approach showcases substantial advancements over existing methods by achieving notable reductions in power consumption, achieving balanced resource allocation, and optimizing response times. The experimental findings underscore the efficacy of our methodology in tackling the intricate challenges inherent in contemporary data processing environments, thereby offering promising prospects for the development of sustainable and scalable computing infrastructures. © 2024 IEEE.

关键词： Computational Performance Data Processing Energy Efficiency Optimization Resource Utilization

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Optimizing Energy Efficiency in Smart Buildings Through Intelligent HVAC Control systems 8

Optimizing Energy Efficiency in Smart Buildings Through Inte...

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Cengiz, Korhan Biruni University Department of Electrical-Electronics Engineering Istanbul Turkey University of Jordan Faculty of Information Technology and Systems Jordan

ISBN: (纸本)9798350354423

This work explores the optimization of HVAC systems in smart buildings through the integration of advanced methodologies, including machine learning algorithms. Specif-ically, we investigate the application of neural networks, and genetic algorithms to enhance energy efficiency and user comfort. Through a comprehensive experimental evaluation, we validated of our proposed approach over existing optimization strategies, as evidenced by improvements in predictive accuracy, user satisfaction, and energy consumption reduction. Our findings highlight the efficacy of leveraging advanced optimization techniques in addressing the complex challenges of HVAC control in modern building infrastructures. © 2024 IEEE.

关键词： Smart homes

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Feature Extraction of Gait Data via PCA and Personal Identification Using Neural Networks 9

Feature Extraction of Gait Data via PCA and Personal Identif...

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9th International Conference on Big Data Analytics, ICBDA 2024

作者： Nishimura, Kazuki Ishida, Akio Murakami, Jun Yamamoto, Naoki National Institute of Technology Kumamoto College Advanced Course of Electronics and Information Systems Engineering Kumamoto Japan National Institute of Technology Kumamoto College Faculty of Liberal Arts Kumamoto Japan National Institute of Technology Kumamoto College Faculty of Electronics and Information Systems Engineering Kumamoto Japan

ISBN: (纸本)9798350352962

Gait analysis is used in a wide range of fields, including clinical applications such as diagnosis and rehabilitation, investigation of gender and racial differences, and personal identification, which is important in forensic investigations and security. In recent years, gait data can be obtained from force plates, 3D motion capture, RGB cameras, and so on. In this study, we applied principal component analysis (PCA) to gait data captured with an RGB camera and analyzed the main data characteristics. However, the data used here is joint information whose posture is estimated using neural networks (NN) from gait videos taken with the camera. Furthermore, we created a NN model for personal identification using data whose dimensionality was reduced using PCA and attempted the identification. © 2024 IEEE.

关键词： Phishing

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Analysis of the performance of robotic assembly systems considering the usage of tools or jigs for the task-board task in the WRS 2018

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Advanced Robotics 2023年第20期37卷 1329-1346页

作者： Dobashi, Hiroki Ogawa, Koki Shibata, Mizuho Uemura, Wataru Yokokohji, Yasuyoshi Faculty of Systems Engineering Wakayama University Wakayama Japan Graduate School of Systems Engineering Wakayama University Wakayama Japan Department of Robotics Faculty of Engineering Kindai University Higashi-Hiroshima Japan Electronics Information and Communication Engineering Course Faculty of Advanced Science and Technology Ryukoku University Otsu Japan Department of Mechanical Engineering Graduate School of Engineering Kobe University Kobe Japan

A task-board task is a task in which robots perform a set of fundamental assembly operations related to the assembly of a specific product such as inserting a part into another part, tightening bolts and nuts, attaching flexible parts, etc. In the task-board task competition in the industrial robotics category of the World Robot Summit (WRS) 2018, 15 teams from around the world performed the task. In our previous work, we observed recorded videos of the competition frame by frame and manually investigated the performance of robotic systems of the top four teams, focusing only on whether robots contact target parts. In this paper, we introduce frame sets to represent mainly contact states between robots, tools, or jigs and target parts to be handled for such a frame-by-frame analysis of the recorded videos, and based on the frame sets, we analyze the performance of robotic assembly systems of other teams as well as the top four teams in the task-board task competition in the WRS 2018, considering the usage of tools or jigs. © 2023 Informa UK Limited, trading as Taylor & Francis Group and The Robotics Society of Japan.

关键词： Robotic assembly

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Remote Monitoring System of Patient Status in Social IoT Environments Using Amazon Web Services Technologies and Smart Health Care

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International Journal of Crowd Science 2025年第2期9卷 110-125页

作者： Abu-Jassar, Amer Tahseen Attar, Hani Amer, Ayman Lyashenko, Vyacheslav Yevsieiev, Vladyslave Solyman, Ahmed College of Information Technology Amman Arab University Amman11937 Jordan Faculty of Engineering Zarqa University Zarqa13110 Jordan College of Engineering University of Business and Technology Jeddah23847 Saudi Arabia Department of Media Systems and Technology Kharkiv National University of Radio Electronics Kharkiv61166 Ukraine Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Nişantaşı University Istanbul34398 Turkey

This study investigates the problematic characteristics of contemporary methods for remote and portable patient monitoring. The consideration is based on recent breakthroughs in information technology and progressive strategies for processing and storing biomedical data. The proposed system represents the Medicine 4.0 concept’s next technological leap. Existing methods for remote and portable monitoring of a patient’s status have several vital disadvantages in system flexibility and the convenience of processing and evaluating biomedical data, according to an analysis of these systems. The authors have created a new concept for a Remote Patient Monitoring System (RPMS) that allows for undetectable wear during the patient’s daily activities. Small modules comprising a microcontroller and a collection of medical sensors transfer data in real-time via wireless Internet of Things (IoT) technologies to a cloud service for the attending physician’s processing and visualization convenience. Based on the proposed concept, the authors created a structural diagram of the experimental RPMS and its built prototype. Amazon Web Services (AWS) is used for the real-time processing of biomedical patient data and its subsequent analysis using a graph-based information visualization system. The performed experimental procedure confirmed that the developed experimental RPMS has minimal latency in transmitting data to AWS;it can alert both the patient and the physician about the need for emergency intervention or treatment adjustments, even if critical indicators are detected. Additionally, the proposed system can incorporate components of expert systems and Artificial Intelligence (AI) systems. The authors advocate using the accomplished system for functional diagnostics specialists, paramedics, and cardiologists in medical facilities and the military medical system for rapid diagnosis and direct monitoring of troops’ health state on the battlefield. © The author(s) 2025.

关键词： Remote patient monitoring

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