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12th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2023

作者： Encalada-Dávila, Ángel Mohamed Ellithy, Kareim Salah Abdelhalim, Mariam Shalaby, Raafat Nile University Giza Egypt MECT Program School of EAS Nile University Giza Egypt Faculty of Electronic Engineering Menofia University MECT Program School of EAS Nile University Giza Egypt

In this work, three control strategies are presented, compared, and discussed, applied on a load-coupled DC motor. The purpose is to control in an optimal way the motor speed in terms of the armature voltage. Two strategies are based on PID control, working on the classical PID controller and the optimized one by using particle swarm optimization (PSO) to tune the PID controller parameters. The other strategy is based on neural networks (NNs) where two NNs are built to model and control the system. Based on the results, all the strategies reach excellent performances, however, in terms of system response characteristics like rising time or settling time the PID-based controllers show faster responses than the NN controller. Moreover, by comparing these results with other studies that are working with an unloaded DC motor and even when the working system is more complex, the obtained results have a better performance. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： DC motors

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WIND FARM SENSOR FAULT DIAGNOSIS USING ARTIFICIAL INTELLIGENCE AND WAVELET TRANSFORM

WIND FARM SENSOR FAULT DIAGNOSIS USING ARTIFICIAL INTELLIGEN...

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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Aly, Mahmoud Shaaba, Mahmoud Kasem, Tamer Shalaby, Raafat Mechatronics Program Nile University Giza Egypt Nile University Giza Egypt Dept. of Engineering Mathematics and Physics Cairo University Giza Egypt Automatic Control Dept. Faculty of Electronic Engineering Menofia University Egypt

ISBN: (纸本)9781837242689

A methodology for the diagnosis of sensor faults in wind farms is introduced. Simulations are performed using a multi-domain model that integrates mechanical, electromagnetic, electronic control, and power grid components. The prevalent issue of intermittent sensor failures is addressed. The discrete wavelet transform is employed for feature extraction. The transient signals are processed effectively. Various wavelet families are evaluated to identify optimal candidates for fault diagnosis. Additionally, the methodology integrates three machine learning classifiers, achieving accuracy rates consistently exceeding 99%. The outcomes demonstrate the advantages of this approach in terms of enhanced accuracy. This research represents a significant advancement in sensor fault diagnosis, contributing valuable insights for the operation and maintenance of renewable energy systems. © The Institution of engineering & Technology 2024.

关键词： Windmill

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SFA-Net: A Selective Features Absorption Network for Object Detection in Rainy Weather Conditions

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IEEE Transactions on Neural Networks and Learning Systems 2023年第8期34卷 5122-5132页

作者： Huang, Shih-Chia Hoang, Quoc-Viet Le, Trung-Hieu National Taipei University of Technology Department of Electronic Engineering Taipei10608 Taiwan National Taipei University of Technology International Graduate Program in Electrical Engineering and Computer Science Taipei10608 Taiwan Hung Yen University of Technology and Education Faculty of Information Technology Hungyen 17000 Viet Nam

In recent years, object detection approaches using deep convolutional neural networks (CNNs) have derived major advances in normal images. However, such success is hardly achieved with rainy images due to lack of visibility. Aiming to bridge this gap, in this article, we present a novel selective features absorption network (SFA-Net) to improve the performance of object detection not only in rainy weather conditions but also in favorable weather conditions. SFA-Net accomplishes this objective by utilizing three subnetworks, where the feature selection subnetwork is concatenated with the object detection subnetwork through the feature absorption subnetwork to form a unified model. To promote further advancement in object detection impaired by rain, we propose a large-scale rainy image dataset, named srRain, which contains both synthetic rainy images and real-world rainy images for training and testing purposes. srRain is comprised of 25 900 rainy images depicting diverse driving scenarios in the presence of rain with a total of 181 164 instances interpreting five common object categories. Experimental results display that our SFA-Net reaches the highest mean average precision (mAP) of 77.53% on a normal image set, 62.52% on a synthetic rainy image set, 37.34% on a collected natural rainy image set, and 32.86% on a published real rainy image set, surpassing current state-of-the-art object detectors and the combination of image deraining and object detection models while retaining a high speed. © 2012 IEEE.

关键词： Feature extraction

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Reinforcement learning-enhanced adaptive sliding mode control for nonlinear systems

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Complex & Intelligent Systems 2025年第8期11卷 1-18页

作者： Youssef, Omnia Wafa, Mohamed Shalaby, Raafat School of EAS MECT Program Nile Uni. Giza Egypt Faculty of Engineering Cairo University Giza Egypt Faculty of Electronic Engineering Menofia University Menouf Egypt

This paper presents a novel Adaptive Relaxed Sliding Mode Control (ARSMC) framework for nonlinear systems, enhanced by an actor-critic reinforcement learning algorithm. ARSMC addresses the limitations of traditional sliding mode control by providing a chattering-free control signal, minimizing steady-state error, and effectively managing unbounded uncertainties and disturbances. The algorithm’s stability is rigorously proven via the Lyapunov theorem. Simulations on an electronic throttle system demonstrate ARSMC’s superior performance over traditional and relaxed sliding mode controllers under various disturbances and uncertainties. Performance metrics, including integral absolute error (IAE) and integral squared error (ISE), highlight ARSMC’s improved control precision and robustness. The results also showcase enhancements in the rise time and maximum overshoot, further validating its effectiveness. The proposed ARSMC framework marks a significant advancement in nonlinear control, providing a robust solution for systems with complex dynamics and parameter uncertainties. It improves upon traditional sliding mode controllers by minimizing steady-state error and chattering while maintaining the ability to handle unbounded external disturbances.

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Optimizing Automotive electronic Throttle Control with a Modified Grey Wolf Algorithm 5

Optimizing Automotive Electronic Throttle Control with a Mod...

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5th International IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2023

作者： Youssef, Omnia Shalaby, Raafat Eas School Nile University Meng Program Giza Sheikh Zayed Egypt Menofia Uni. Faculty of Electronic Engineering Menouf Egypt

ISBN: (纸本)9798350381030

electronic Throttle Control (ETC) systems have become increasingly popular in the automotive industry due to their ability to improve fuel efficiency and vehicle performance. However, designing effective control strategies for these systems is challenging due to the non-linearities and external load affecting the throttle gate angle. This paper proposes a novel control approach for ETC systems using a modified Grey Wolf optimization algorithm combined with a fractional-order PID controller. The proposed approach is designed to handle the tuning of the controller's five parameters in the presence of many non-linearities and external disturbances. To better understand the effects of non-linearities, a comprehensive survey of ETC system control methods is presented, highlighting the challenges posed by non-linearities and external load. A mathematical model is developed to incorporate the effects of friction and limp home dual springs to understand the system's behavior. Modifications are made to the Grey Wolf optimizer to improve its convergence and ability to find the best solution. Simulation studies are conducted to compare the proposed approach with traditional PID and fractional-order PID controllers, demonstrating its superiority in terms of tracking performance and robustness to disturbances. The proposed approach has the potential to be applied to other control systems in the automotive industry and beyond © 2023 IEEE.

关键词： Automotive industry

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Design and Evaluation of Magnetic Induction Spectroscopy Probe for pH Measurement in Fetal Hypoxia Using COMSOL Multiphysics Simulation 3rd

Design and Evaluation of Magnetic Induction Spectroscopy Pro...

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3rd International Conference on Control, Instrumentation and Mechatronics engineering, CIM 2022

作者： Halim, S. F. Abdul Zakaria, M.H. Zakaria, Z. Ahmed, A.A. Norali, A.N. Noor, A. Mohd Pusppanathan, J. Rahiman, M. H. Fazalul Muji, S. Z. Mohd Rahim, R. Abdul Biomedical Electronic Engineering Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Arau02600 Malaysia Universiti Teknologi Malaysia Johor Skudai81310 Malaysia Mechatronic Engineering Program Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Perlis Arau02600 Malaysia Electronic Engineering Department Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Johor Batu Pahat Parit Raja86400 Malaysia School of Electrical Engineering Faculty of Engineering Universiti Teknologi Malaysia Johor Skudai81310 Malaysia

ISBN: (纸本)9789811939228

Fetal Blood Sampling (FBS) is the term used to describe the current method of monitoring the foetal condition within the mother’s womb. FBS required the medical officer to make a small incision on the foetus’s head in order to collect blood for analysis of the blood pH level in order to prevent acidosis or foetal hypoxia. The FBS method, on the other hand, is invasive and increases the risk of infection for both mother and child. Magnetic Induction Spectroscopy (MIS) is a novel method for diagnosing the foetus’s pH level that is non-invasive and non-intrusive. A single channel MIS system is composed of a transmitter (TX), a receiver (RX), and an electrical circuit that generates and receives magnetic fields in response to the conductivity of the sample (blood) due to the presence of weak electrolytes (H+ and OH-). The purpose of this research is to develop and evaluate five different designs of TX-RX coils. The coils are designed using the Planar Zero Flow Coil (PZFC) concept, which allows for multiple coil configurations and input-output configurations. The results show that Design 2 open set model was the optimal coil design for MIS system probe, as well as some contributions to the pH evaluation process. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Spectroscopy

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Design and Implementation of Decisioning System for Wifi Access Point Installation using Genetic Algorithm

Design and Implementation of Decisioning System for Wifi Acc...

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2022 International Electrical engineering Congress, iEECON 2022

作者： Thitinaruemit, Aphirak Sitjongsataporn, Suchada Prongnuch, Sethakarn Mahanakorn University of Technology Electrical Engineering Graduate Program Faculty of Engineering and Technology Bangkok Thailand Faculty of Engineering and Technology Dept. of Electronic Engineering Bangkok Thailand Suan Sunandha Rajabhat University Faculty of Industrial Technology Dept. of Robotics Engineering Bangkok Thailand

ISBN: (纸本)9781665402064

This paper presents the design and implementation of a WiFi indoor localization system using genetic algorithm. The coverage capability of the wireless access point is an important parameter in the design to estimate the distance from the transmitted and received signals. The main purpose of this work is to find the effective number of wireless access points in the design area by using genetic algorithm. The Received Signal Strength (RSSI) is measured for the signal quality. The test area consists of the multiple classrooms on the same floor inside the building and the conditions are unobstructed and used the line-of-sight for transmitted and received signals. The experimental results by measuring the received signal through a laptop are indicated that RSSI = -35 dBm at a distance of 5 meters is a prominent indicator of signal quality that can be used to search a variety of information from internet inside the classroom. © 2022 IEEE.

关键词： Genetic algorithms

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Acquisition of EMG Signals for the Analysis of Muscle Electrical Activity in High-Performance Athletes: An Experimental Procedure 1

Acquisition of EMG Signals for the Analysis of Muscle Electr...

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1st IEEE Colombian Caribbean Conference, C3 2023

作者： Polo, Aura Moreno-Barriga, Orlando Ayala, Diego Viloria-Porto, Julie Solano, Lacides Antonio Ripoll Luengas-C, Lely A. Universidad Del Norte Faculty of Engineering Universidad Del Magdalena Department of Electrical and Electronic Engineering Colombia Universidad Del Magdalena Centro de Investigación de Alto Rendimiento Deportivo y Estudios Biomédicos Ciardeb Santa Marta Colombia Universidad Del Magdalena Electronic Engineering Program Faculty of Engineering Santa Marta Colombia Universidad Del Magdalena Vicerrectoría de Investigación Santa Marta Colombia Universidad Del Norte Department of Electrical and Electronic Engineering Puerto Colombia Colombia Universidad Distrital Francisco José de Caldas Faculty of Engineering Bogotá Colombia

ISBN: (纸本)9798350341799

The present research work describes the experimental process carried out, thanks to the use of surface electromyography (sEMG) for the acquisition of signals from the muscles of high-performance athletes for the analysis of the electrical activity of the muscles in preparation before the university competitions of Colombia. The signals were obtained using a wireless acquisition system based on dry active electrodes when performing a series of exercises focused on the muscles that are involved in controlling the center of gravity of the human body, such as: the rectus femoris, Internal Oblique (IO), External Oblique (EO), and spinal erector. Then, a characterization of the population under study was developed depending on the type of discipline and the exercise used. The results obtained come from the visual inspection and organization of these signals by using basic preprocessing and visualization techniques in MATLAB software. Thus, a compendium is presented with the means of the RMS values and the duration of each muscular activity depending on the type of exercise, showing ranges of values from 0.2-7mV. © 2023 IEEE.

关键词： Muscle

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Design of Four-Core Uncoupled Multicore Fiber for Next-Generation Inter-Data Center Networks

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Journal of Mobile Multimedia 2022年第2期18卷 163-178页

作者： Ponchua, Jirasak Sitjongsataporn, Suchada Electrical Engineering Graduate Program Faculty of Engineering Mahanakorn University of Technology 140 Cheumsamphan Rd. Nongchok Bangkok Thailand Department of Electronic Engineering Mahanakorn Institute of Innovation (MII) Faculty of Engineering Mahanakorn University of Technology 140 Cheumsamphan Rd. Nongchok Bangkok Thailand

The increasing demands within and between the data centers used for data traffic has required. Efficient links are important to data center applications for supporting the unlimited demand. Transmission capacity of single-mode fiber (SMF) is limited by fiber nonlinearity which prevents the increasing transmission power and finite amplifier bandwidth. Single-mode multi-core fibers (SM-MCFs) that are expected to overcome the current limitation of optical communication capacity. However, the inter-core crosstalk still has an effect on SM-MCF, which can limit the transmission of the inter-data center. In this paper, the design of four-core uncoupled multicore fiber is discussed for next generation inter-data center networks in order to support the unlimited use of data traffic in the future. The objective of this paper is to determine the appropriate range of core radius and core pitch, which are taken into consideration to reduce the inter-core crosstalk inside the optical fiber. These parameters can be able to improve various constraints to achieve the best multi-core fibers design. From the simulation concerned with the inter-core crosstalk, the experiment results show that the range of core pitch is at 47.5 µm to 50 µm and the range of core radius starts from 4.5 µm to 5.5 µm, that can achieve with crosstalk lower than – 30 dB/100 km for the future inter-data center networks. © 2021 River Publishers

关键词： Inter-core crosstalk Inter-data centers Single-mode fiber Single-mode multi-core fibers

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Optimal Synergic Deep Learning for COVID-19 Classification Using Chest X-Ray Images

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Computers, Materials & Continua 2023年第6期75卷 5255-5270页

作者： JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Safa Alsafari Ayman Yafoz Romany F.Mansour Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080002Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Department of Computer Science and AI Faculty of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.

关键词： Artificial intelligence chest X-ray COVID-19 optimized synergic deep learning preprocessing public health

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