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2024 Laser Science, LS 2024

作者： Kadhim, Ahmed C. Azzahrani, Ahmad S. Taha, Bakr A. Department of Communications Engineering University of Technology-Iraq Baghdad Iraq Department of Electrical Engineering Northern Border University Arar Saudi Arabia Department of Electrical Electronic and Systems Engineering University of Kebangsaan Malaysia UKM Bangi43600 Malaysia

In this paper, the spatial distribution of refractive index components is performed using quantitative phase imaging (QPI) and optical path difference. The outcomes provide a three-dimensional projection of RI which h... 详细信息

关键词： Refractive index

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Robust Stability Analysis of Smith Predictor Based Interval Fractional-Order Control systems:A Case Study in Level Control Process

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 762-780页

作者： Majid Ghorbani Mahsan Tavakoli-Kakhki Aleksei Tepljakov Eduard Petlenkov Department of Computer Systems Tallinn University of TechnologyTallinn 12618Estonia Faculty of Electrical Engineering K.N.Toosi University of TechnologyTehran ***Iran IEEE

The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this *** uncertainties are a type of parametric uncertainties that cannot be avoided when modeling real-world ***,in the considered Smith predictor control structure it is supposed that the controller is a fractional-order proportional integral derivative(FOPID)*** the best of the authors'knowledge,no method has been developed until now to analyze the robust stability of a Smith predictor based fractional-order control system in the presence of the simultaneous uncertainties in gain,time-constants,and time *** three primary contributions of this study are as follows:ⅰ)a set of necessary and sufficient conditions is constructed using a graphical method to examine the robust stability of a Smith predictor-based fractionalorder control system—the proposed method explicitly determines whether or not the FOPID controller can robustly stabilize the Smith predictor-based fractional-order control system;ⅱ)an auxiliary function as a robust stability testing function is presented to reduce the computational complexity of the robust stability analysis;andⅲ)two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise ***,four numerical examples and an experimental verification are presented in this study to demonstrate the efficacy and significance of the suggested technique.

关键词： Interval uncertainty FOPID controller fractional-order systems robust stability analysis smith predictor

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Electric Bike Security and Protection System 2

Electric Bike Security and Protection System

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2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Maniraj, P. Murugan, A. Durai Gokul, R. Shalini, A.S. Kesavan, K. Kavin, P. M. Kumarasamy College of Engineering Department of Electrical and Electronics Engineering Karur India M. Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India M. Kumarasamy College of Engineering Computer Science and Business Systems Karur India M. Kumarasamy College of Engineering Electrical and Electronics Engineering Karur India

ISBN: (纸本)9798350349221

With the developing prevalence of electric bicycles (e-bicycles) as a feasible and proficient method of transportation, guaranteeing their security has turned into a foremost concern. Electric bicycles are important resources helpless against robbery and harm, to conquer this issue the venture proposes the improvement of an Electric Vehicle Burglary Location and Warning Framework utilizing IOT innovation. The framework integrates sensors to screen electric vehicles for unapproved access and utilizes Radio Recurrence ID innovation to improve security. After recognizing an unfair RFID section or any dubious movement, the framework sets off a caution to tell the proprietor and naturally locks the back tire, forestalling robbery. This framework could be an instrument for deflecting the robbery of electric vehicles and keeping proprietors from monetary misfortunes. In a period of developing IOT-based security arrangements, this framework offers an important expansion to safeguard electric vehicle and their venture. © 2024 IEEE.

关键词： Electric vehicles

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A Novel Rotor Switching Theory for Optimizing Small Vertical Axis Wind Turbine Performance: Insights from Experimental Study 4

A Novel Rotor Switching Theory for Optimizing Small Vertical...

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4th IEEE International Conference on electrical, Computer, and Energy Technologies, ICECET 2024

作者： Irawan, Elysa Nensy Yamashita, Ken-Ichiro Fujita, Goro Functional Control Systems Shibaura Institute of Technology Tokyo Japan Salesian Polythecnic Department of Electrical Engineering Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798350395914

In recent years, research on hybrid Savonius-Darrieus has significant attention within the wind energy sector. According to earlier research, this hybrid can produce higher torque at low tip speed ratios than a solo Darrieus model. However, as tip speed ratio increase, hybrids tend to perform lower than solo Darrieus. This study introduces an innovative paradigm termed rotor switching theory. It suggests switching from hybrid to solo Darrieus rotation at higher tip speed ratio for the turbine. Current study is conducted experimentally using testing models of small hybrid Savonius-Darrieus and solo Darrieus turbines. The internal rotor consists of two stages of Savonius turbines with a 0.2 overlap and a bucket angle of 135°, each having two blades. The external rotor features a NREL S809 Darrieus airfoil with a 5 cm cord length and three blades. Outer radius is 10 cm and its height is 15.4 cm. The experiments are conducted within an open-circuit wind tunnel with the wind speed variations of 3 - 12 m/s. Based on the results, the intersection of the moment and power coefficient graphs for both the hybrid and solo Darrieus occurs at TSR 1.7. When reaching this condition, switching the turbine rotation state from hybrid to solo Darrieus can offer advantages. By employing this concept, the turbine will achieve an expected initial power coefficient that is 150% better than the solo Darrieus and a maximum power coefficient that is 21% greater than the hybrid model. © 2024 IEEE.

关键词： Windmill

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A machine learning approach for skin lesion classification on iOS: implementing and optimizing a convolutional transfer learning model with Create ML

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International Journal of Computers and Applications 2024年第8期46卷 666-685页

作者： Benedek Szabo, Aron Katona, Jozsef Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Instrumentation and Automation Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Department of Informatics GAMF Faculty of Engineering and Computer Science Kecskemét Hungary

The integration of machine learning (ML) into mobile applications presents unique challenges, particularly in resource-constrained environments such as iOS devices. Skin lesion classification is a critical task in dermatology, where accurate and efficient diagnostic tools can significantly aid in early detection of malignant lesions. This study aims to implement a machine learning-based iOS mobile application and develop a binary classification model for skin lesion images to determine whether a lesion is malignant. The research utilized Create ML to develop a convolutional neural network optimized for iOS, employing a transfer learning approach. A logistic regression model was cascaded with the convolutional neural network N to enhance classification accuracy. The model's performance was assessed through various validation metrics, ensuring its robustness and efficiency within the constraints of mobile hardware. A curated dataset from the International Skin Imaging Collaboration archive was used for training and testing. The model achieved an accuracy of 92%, a precision of 90%, a recall of 93%, and an F1-score of 91% in classifying skin lesions. These metrics validate the model's efficacy in identifying malignant lesions. Data curation involved collecting, labeling, and preparing a dataset from publicly available sources, ensuring the inclusion of diagnostically relevant features. The final model was integrated into an iOS application using Core ML and Vision frameworks. The developed application demonstrates reliable performance in classifying skin lesions with high accuracy on iOS devices. The inclusion of comprehensive performance metrics justifies the efficacy of the proposed approach. Future work will explore enhancements in model architecture and object detection capabilities to further improve diagnostic precision and application usability. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Image recognition

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INVESTIGATION OF ELECTROMAGNETIC ACOUSTIC TRANSDUCER EFFICIENCY WITH COMPOSITE MAGNETISATION DIRECTION MAGNETS 10

INVESTIGATION OF ELECTROMAGNETIC ACOUSTIC TRANSDUCER EFFICIE...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Li, Haitian Wang, Shen Zhao, Yuxuan Huang, Songling Department of Electrical Engineering State Key Lab of Power Systems Tsinghua University Beijing China

ISBN: (纸本)9781837242672

This study investigates Electromagnetic Acoustic Transducers (EMATs) efficiency with composite magnetisation direction magnets. EMATs are an essential technology for non-destructive testing (NDT) in industrial applications, offering advantages such as non-contact operation and suitability for harsh environments. However, the application of EMATs is often limited by weak testing signals. This research explores the optimisation of bias magnetic fields through various magnet arrangements to enhance transduction efficiency. The study uses finite element simulations to compare magnetic field distributions and their effects on EMAT performance for different magnet configurations, including periodic permanent magnets (PPM), ring-type magnets, and Halbach arrays. Results indicate that specific composite magnet configurations can significantly improve both the normal and tangential magnetic flux density, thereby increasing the strength of the generated and received ultrasonic waves. This optimisation of the bias magnetic field is crucial for advancing EMAT technology and improving testing accuracy in industrial NDT applications. © The Institution of engineering & Technology 2024.

关键词： Permanent magnets

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Threshold-Based Electroencephalography Brain-Computer Interface for Robot Arm Control 8

Threshold-Based Electroencephalography Brain-Computer Interf...

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8th Asia-Pacific Conference on Intelligent Robot systems, ACIRS 2023

作者： Rusydi, Muhammad Ilhamdi Amrina, Elita Winata, Yoan Ramadhani, Salisa Nofendra, Riko Graduate School Universitas Andalas Engineering Faculty Program of Engineer Professional Education Electrical Engineering Department Padang Indonesia Universitas Andalas Engineering Faculty Electrical Engineering Department Padang Indonesia

ISBN: (纸本)9798350302851

Brain-Computer Interface (BCI) is a technique that uses real-Time brain impulses to connect with and control external devices. BCI provides a new method for controlling external devices by translating brain signals into computer commands, facilitating the daily lives of people with disabilities and enhancing their ability to exhibit expected behavior. A Brain-Computer Interface (BCI) system based on Electroencephalography (EEG) was built to control the robotic arm. The EEG signals utilized included both eyes blinking, the right eye, the left eye, and the jaw contraction. EEG data were recorded from seven healthy subjects. The threshold approach is used to classify EEG signals, with the feature employed being the amplitude of the EEG signal. The highest threshold value for the blinking signal was 0.6 mV with an accuracy of 97.9%, while the best threshold value for jaw contraction was 0.4 mV with an accuracy of 93.34 percent. The healthy, inexperienced participants took part in system testing. The total results of testing each robot movement yielded an overall success rate of 84.52 percent. Therefore, it was determined that the system could facilitate the operation of the length robot even if the user lacked prior experience with EEG-based systems. © 2023 IEEE.

关键词： Brain computer interface

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Machine learning algorithms for predicting the risk of chronic kidney disease in type 1 diabetes patients: a retrospective longitudinal study

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Neural Computing and Applications 2024年第26期36卷 16545-16565页

作者： Chowdhury, Md Nakib Hayat Reaz, Mamun Bin Ibne Ali, Sawal Hamid Md Crespo, María Liz Cicuttin, Andrés Ahmad, Shamim Haque, Fahmida Bakar, Ahmad Ashrif A. Razak, Mohd Ibrahim Bin Shapiai Abd Bhuiyan, Mohammad Arif Sobhan Department of Electrical Electronic and Systems Engineering Universiti Kebangsaan Malaysia UKM Selangor Bangi43600 Malaysia Saidpur Cantonment Saidpur Nilphamari5310 Bangladesh Department of Electrical and Electronic Engineering Independent University Bangladesh Dhaka Bashundhara Bangladesh Department of Electrical Electronic and Systems Engineering Centre of Advanced Electronic and Communication Engineering Universiti Kebangsaan Malaysia UKM Selangor Bangi43600 Malaysia Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Jalan Sultan Yahya Petra Kuala Lumpur54100 Malaysia Trieste34151 Italy Department of Computer Science and Engineering University of Rajshahi Rajshahi6205 Bangladesh Artificial Intelligence Resource Molecular Imaging Branch National Cancer Institute BethesdaMD United States Department of Electrical and Electronics Engineering Xiamen University Malaysia Selangor Bandar Sunsuria Sepang43900 Malaysia

Chronic kidney disease (CKD) is a significant concern for individuals with type 1 diabetes (T1D), impacting their quality of life and healthcare costs. Identifying T1D patients at greater risk of developing CKD is crucial for preventive measures. However, it is challenging due to the asymptomatic progression of CKD and limited nephrologist availability in many countries. This study explores machine learning algorithms to predict CKD risk in T1D patients using ten years of retrospective data from the Epidemiology of Diabetes Interventions and Complications clinical trial. Eleven machine learning algorithms were applied to twenty-two readily available features from T1D patients’ routine check-ups and self-assessments to develop 10-year CKD risk prediction models. In addition, we also proposed a heterogeneous ensemble model (STK) using a stacking generalization approach. The models’ performance was evaluated using different evaluation metrics and repeated stratified k-fold cross-validation. Several predictive models showed reliable performance in CKD risk prediction, with the proposed ensemble model being the best performing with an average accuracy of 0.97, specificity of 0.98, sensitivity/recall of 0.96, precision of 0.98, F1 score of 0.97, Kappa and MCC score of 0.94, AUROC of 0.99, and Precision-Recall curve of 0.99. The proposed machine learning approach could be applicable for CKD risk prediction in T1D patients to ensure the necessary precautions to overcome the risk. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Machine learning

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UAV-Assisted Offloading Via Satellite Backhaul for Post-Disaster and Crowded Cellular Networks

UAV-Assisted Offloading Via Satellite Backhaul for Post-Disa...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Omran, Allafi Cheriet, Mohamed Sboui, Lokman College of Technical Sciences Electrical Engineering Department Bani Waleed Libya Systems Engineering Department Montreal Canada

ISBN: (纸本)9798350370218

In this paper, our aim is to enhance network resilience and efficiency in post-disaster and crowded cellular networks by integrating unmanned aerial vehicles (UAVs) and satellites. The proposed two-step network recovery involves determining the optimal 3D placement of UAVs to maximize user coverage in disrupted or congested areas, followed by allocating each UAV to a satellite for reliable backhauling and efficient offloading, while considering satellite visibility and UAV caching constraints. The numerical results demonstrate the superior performance of the proposed 3D placement algorithm compared to the existing methods. Additionally, we analyze and discuss the impact of the number of satellites on backhauling delay and cached demand at UAVs. © 2023 IEEE.

关键词： 3D UAV deployment Base station congestion/damage Network resilience Satellites Backhauling

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Improved Impedance Based Parameter Free Fault Location Estimation Algorithm for Two Terminal Transmission Line Using Phasor Components 3

Improved Impedance Based Parameter Free Fault Location Estim...

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3rd IEEE International Conference on electrical Power and Energy systems, ICEPES 2024

作者： Latha, Adharapurapu Hema Bhimasingu, Ravikumar Power Systems Wing APTRANSCO Vijayawada India IIT Hyderabad Department of Electrical Engineering India

ISBN: (纸本)9798350390728

This paper presents a new impedance based fault location identification method on two terminal transmission lines without using transmission line parameters. The voltage and current phasors from both the terminals of the transmission line are used for calculating fault distance on the transmission line. The value of the zero sequence compensation factor is also calculated using the during fault values of voltages and currents without using the known values. The impedances calculated from the pre-fault and during-fault values of the voltages and current phasors are compared for fault location identification. Further, the fault point voltage, thereby fault resistance is also obtained accurately. The proposed method is independent of transmission line parameters accuracy and the efficiency is tested for different fault types and fault distance on the transmission line. A 10 bus system is considered for simulation studies which is modelled in PSCAD software and the algorithm is implemented in MATLAB. © 2024 IEEE.

关键词： MATLAB

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