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1st IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022

作者： Elbabo Mohammed, Omer Mohammed Liu, Yi Xu, Wei Islam, Md. Rabiul University of Sinnar Faculty of Engineering Department of Electrical Engineering Sinnar Sudan Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan China University of Wollongong School of Electrical Computer and Telecommunications Engineering Wollongong Australia

ISBN: (数字)9781665443579

ISBN: (纸本)9781665443579

Without brushes and slip rings, the brushless double-fed induction generator (BDFIG) can operate more stably and reliably, so it is prospective to be one of important machines for standalone systems in the next few years. The stability of amplitude of voltage and frequency of power winding (PW) is major aim of control in off-grid system. Also, the standalone system is oversensitive to abnormal running situations, especially with unbalanced conditions. The unbalanced loads would lead to harmful phenomena, such as the unbalanced impact of current and voltage of PW. To handle this issue, the reactive power loop is presented to minimize voltage unbalance of PW through creating control winding (CW) compensation voltage via converter of machine side (MSC). The simulation is executed to test the performance of presented method. © 2022 IEEE.

关键词： Reactive power

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An Efficient GCD-Based Cancelable Biometric Algorithm for Single and Multiple Biometrics

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computers, Materials & Continua 2021年第11期69卷 1571-1595页

作者： Naglaa F.Soliman Abeer D.Algarni Walid El-Shafai Fathi E.Abd El-Samie Ghada M.El Banby Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things(IoT)*** objective of using cancelable biometrics is to save the original ones from hacking attempts.A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT *** original biometric is blurred with two co-prime ***,it can be recovered as the Greatest Common Divisor(GCD)between its two blurred *** changes if induced in the biometric image prior to processing with co-prime operators prevents the recovery of the original biometric image through a GCD ***,the ability to change cancelable templates is guaranteed,since the owner of the biometric can pre-determine and manage the minimal change induced in the biometric ***,we test the utility of the proposed algorithm in the single-and multi-biometric *** multi-biometric scenario depends on compressing face,fingerprint,iris,and palm print images,simultaneously,to generate the cancelable *** metrics such as Equal Error Rate(EER)and Area and Receiver Operator Characteristic curve(AROC)are *** results on single-and multi-biometric scenarios show high AROC values up to 99.59%,and low EER values down to 0.04%.

关键词： Cloud IoT cancelable biometrics GCD single-and multi-biometrics security applications

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Reconfigurable Pattern Patch Antenna for Mid-Band 5G:A Review

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computers, Materials & Continua 2022年第2期70卷 2699-2725页

作者： Siti Rahena Isa Muzammil Jusoh Thennarasan Sabapathy Jamel Nebhen Muhammad Ramlee Kamarudin Mohamed Nasrun Osman Qammer Hussain Abbasi Hasliza A.Rahim Mohd Najib Mohd Yasin Ping Jack Soh Department of Electrical Engineering Politeknik Sultan Abdul Halim Mu’adzam ShahJitra06000Malaysia Advanced Communication Engineering(ACE) Centre of ExcellenceUniversiti Malaysia Perlis.Faculty of Electronic Engineering TechnologyUniversiti Malaysia PerlisPauh Putra02600Malaysia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityP.O.Box 151Alkharj11942Saudi Arabia Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn MalaysiaParit Raja86400Malaysia School of Engineering University of GlasgowGlasgowG128QQU.K

New requirements in communication technologies make it imperative to rehash conventional features such as reconfigurable antennas to adapt with the future adaptability *** paper presents a comprehensive review of reconfigurable antennas,specifically in terms of radiation patterns for adaptation in the upcoming Fifth Generation(5G)New Radio frequency *** represent the key of antenna technology for materializing a high rate transmission,increased spectral and energy efficiency,reduced interference,and improved the beam steering and beam shaping,thereby land a great promise for planar antennas to boost the mid-band *** review begins with an overview of the underlying principals in reconfiguring radiation patterns,followed by the presentations of the implemented innovative antenna topologies to suit particular advanced *** various adaptation techniques of radiation pattern reconfigurable planar antennas and the understanding of its antenna design approaches has been investigated for its radiation pattern enhancement.A variety of design configurations have also been critically studied for their compatibilities to be operated in the midband communication *** review provides new insights on pattern reconfigurable antenna where such antennas are categorized as beam steering antenna and beamshaping antennas where the operation modes and purposes are clearly *** review also revealed that for mid-band 5G communication,the commonly used electronic switching such as PIN diodes have sufficient isolation loss to provide the required beam performance.

关键词： 5G mid-band pattern antenna reconfigurable antenna phased array antenna antenna and propagation

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Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI

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IEEE Transactions on Communications 2024年 1-1页

作者： Zhang, Yuchen Ni, Wanli Wang, Jianquan Tang, Wanbin Jia, Min Eldar, Yonina C. Niyato, Dusit National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu China Department of Electronic Engineering Tsinghua University Beijing China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel School of Computer Science and Engineering Nanyang Technological University Singapore

We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and outage-constrained robust optimization problems of joint transceiver beamforming and radar waveform design to balance the radar performance of multiple targets while ensuring the communications performance and covertness of the system. The optimization problems are challenging due to the non-convexity arising from the semi-infinite constraints (SICs) and the coupled transceiver variables. In an effort to tackle the former difficulty, S-procedure and Bernstein-type inequality are introduced for converting the SICs into finite convex linear matrix inequalities (LMIs) and second-order cone constraints. A robust alternating optimization framework referred to alternating double-checking is developed for decoupling the transceiver design problem into feasibility-checking transmitter- and receiver-side subproblems, transforming the rank-one constraints into a set of LMIs, and verifying the feasibility of beamforming by invoking the matrix-lifting scheme. Numerical results are provided to demonstrate the effectiveness and robustness of the proposed algorithm in improving the performance of covert ISAC systems. IEEE

关键词： Linear matrix inequalities

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Performance Evaluation of YOLO Models for Automatic Crop and Weed Detection

Performance Evaluation of YOLO Models for Automatic Crop and...

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International Conference on Microelectronics, MIEL

作者： L. Stankovic T. Nikolic T. Talaska R. Dlugosz Faculty of Electronic Engineering University of Nis Nis Serbia Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz University of Science and Technology Bydgoszcz Poland

Accurate weed mapping is essential for the implementation of weed management in order to maintain high crop yields and less chemical pollution. This paper focuses on the performance evaluation of YOLO models for automatic crop and weed detection. The research aims to develop weed detection models using one-stage deep learning-based object detectors by transferring pre-trained object detection models to a selected weed dataset. The models are trained on annotated images from a public dataset and evaluated based on detection accuracy. Results demonstrate promising training performance, with approximately 70% mean average precision achieved in 100 training epochs. YOLOv5x exhibits the best performance among the studied models, achieving the highest precision, recall, and mean average precision (0.72, 0.75, and 0.74, respectively). The findings indicate that models with deeper or larger backbone networks tend to provide higher detection accuracy.

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PeanutAD: A Real-World Dataset for Anomaly Detection in Agricultural Product Processing Line

PeanutAD: A Real-World Dataset for Anomaly Detection in Agri...

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International Conference on Communications and electronics, ICCE

作者： Duc-Hai Nguyen Trong-Hiep Do Quoc-Khanh Nguyen Hoang-Linh-Phuong Nguyen Thi-Huong Nguyen Duc-Tan Tran Van-Toi Nguyen Faculty of Computer Science PHENIKAA University Hanoi Vietnam Hanoi College of High Technology Hanoi Vietnam Faculty of Electrical and Electronic Engineering PHENIKAA University Hanoi Vietnam

ISBN: (数字)9798350379792

ISBN: (纸本)9798350379808

Anomaly detection in production lines - automatically detecting defects in product processes - plays a vital role across several domains. Several industrial anomaly detection datasets have been built with severe challenges to overcome. However, the need for more amount and diversity of training data in specific systems in the real world, especially in agricultural product processing lines, remains to be considered. In this work, we introduce a peanut anomaly detection dataset (PeanutAD), a real-world dataset for anomaly detection tasks, reflecting the actual conditions in production lines. Experiments on this dataset demonstrated significant room for improvement because of some challenges. With PeanutAD, we aim to expand the anomaly detection database quantitatively and qualitatively, allowing researchers to further enhance and evaluate anomaly detection techniques with the most realistic setup possible. PeanutAD and experimental results on baseline methods shall be kept fully open-source as a contribution to the research community 1 .

关键词： Databases Training data Production Agricultural products Task analysis Anomaly detection

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Explainable AI for Epileptic Seizure Prediction: A SHAPE and LIME Approach

Explainable AI for Epileptic Seizure Prediction: A SHAPE and...

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Information technology (ACIT)

作者： Md. Simul Hasan Talukder Sohag Kumar Mondal Oyshi Tabassum Aditi Mohammad Aljaidi Rejwan Bin Sulaiman Ahmad Al-Qerem Electrical and Electronic Engineering Dhaka University of Engineering & Technology Gazipur Bangladesh Electrical and Electronic Engineering Khulna University of Engineering and Technology Khulna Bangladesh Khulna Bangladesh Department of Computer Science and Engineering Daffodil International University Savar Bangladesh Department of Computer Science Faculty of Information Technology Zarqa University Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia School of Computer Science & Technology Northumbria University Newcastle Tayne United Kingdom

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Epilepsy is a neurological chaos typified by frequent, spontaneous seizures. Early recognition of epilepsy by utilising AI techniques to scan EEG signals can enhance the prevention and management of it. This study aims to improve the classification of epileptic seizures by using the preprocessed version of the Epileptic Seizure (ERS) dataset. The preprocessed dataset is subjected to multiple stages in order to improve its quality and achieve balanced class representation. Data cleaning, outlier management, merging, and oversampling are those. After that, an 80:20 split of the dataset is made into subsets for testing and training. Next, training, testing, and evaluation are performed on the models of Gradient Boosting Classifier (GBC), Decision Tree Classifier (DTC), Random Forest Classifier (RFC), CatBoost Classifier (CBC), and ExtraTree Classifier (ETC). The ExtraTree Classifier is remarkably accurate, with a 99.51% accuracy rate, which is the highest accuracy. Finally, explainable artificial intelligence (SHAP and LIME) is used to clarify the ExtraTree Classifier's decision-making procedure. By providing a visual representation of significant variables and their influence on the model's predictions, this interpretability tool improves comprehension of the classification results.

关键词： Training Visualization Accuracy Shape Prevention and mitigation Epilepsy Predictive models Brain modeling Random forests Testing

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A novel hybrid cryptosystem based on DQFrFT watermarking and 3D-CLM encryption for healthcare services

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Frontiers of Information technology & electronic engineering 2023年第7期24卷 1045-1061页

作者： Fatma KHALLAF Walid EL-SHAFAI El-Sayed M.EL-RABAIE Naglaa F.SOLIMAN Fathi EAbd E.L-SAMIE Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Electrical Engineering Faculty of EngineeringAhram Canadian University6^(th)October CityGiza 12451Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh I1586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia

Quaternion algebra has been used to apply the fractional Fourier transform(FrFT)to color images in a comprehensive ***,the discrete fractional random transform(DFRNT)with adequate basic randomness remains to be *** paper presents a novel multistage privacy system for color medical images based on discrete quaternion fractional Fourier transform(DQFrFT)watermarking and three-dimensional chaotic logistic map(3D-CLM)***,we describe quaternion DFRNT(QDFRNT),which generalizes DFRNT to handle quaternion signals effectively,and then use QDFRNT to perform color medical image adaptive *** efficiently evaluate QDFRNT,this study derives the relationship between the QDFRNT of a quaternion signal and the four components of the DFRNT ***,it uses the human vision system's(HVS)masking qualities of edge,texture,and color tone immediately from the color host image to adaptively modify the watermark strength for each block in the color medical image using the QDFRNT-based adaptive watermarking and support vector machine(SVM)*** limitations of watermark embedding are also explained to conserve watermarking ***,3D-CLM encryption is employed to improve the system's security and efficiency,allowing it to be used as a multistage privacy *** proposed security system is effective against many types of channel noise attacks,according to simulation results.

关键词： Color medical image Quaternion Adaptive watermarking Encryption Fractional transform Three-dimensional chaotic logistic map(3D-CLM)

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Game-Theory-Guided Reinforcement Learning for Autonomous Vehicles in Highway Scenarios 8

Game-Theory-Guided Reinforcement Learning for Autonomous Veh...

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8th IEEE Information technology and Mechatronics engineering Conference, ITOEC 2025

作者： Wang, Jiayang Sun, Wanlu Xiao, Pengbo Li, Qian Universiti Malaya Faculty of Computer Science and Information Technology Kuala Lumpur Malaysia Co. Ltd. Suzhou China Hangzhou University of Electronic Science and Technology College of Mechanical Engineering Hangzhou China Tianjin University State Key Laboratory of Engines Tianjin China

ISBN: (纸本)9798331517915

Autonomous vehicles have become a popular topic with the development of technology. In the early stages of an automated driving system, the key to correctly guiding the vehicle's behavior lies in the effective collection and application of expert driving experience. This study introduces a game-theoretic guided reinforcement learning (GTG-RL) framework that merges game-theoretic expert models with reinforcement learning to enhance decision-making efficiency for autonomous vehicles in complex motorway scenarios. Validation confirms the framework's effectiveness in improving performance and adaptability under dynamic traffic conditions. The results underscore the potential of integrating game-theoretic expertise with reinforcement learning to tackle autonomous driving challenges. © 2025 IEEE.

关键词： Reinforcement learning

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Effect of pH on Electrochemical, Morphological and Optical Properties of Electrodeposited Molybdenum Sulfide Thin Film

Effect of pH on Electrochemical, Morphological and Optical P...

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IEEE International Conference on Semiconductor electronics (ICSE)

作者： Iskandar Dzulkarnain Rummaja Muhammad Idzdihar Idris Radi Husin Ramlee Zul Atfyi Mohammed Napiah Marziani Rashid Ahmad Muhajer Abdul Aziz Faculty of Electronic and Computer Technology and Engineering Universiti Teknikal Malaysia Melaka (UTeM) Melaka Malaysia Micro and Nano Research Group (MINE) Centre for Telecomunication Research and Innovation (CeTRI) Faculty of Electronic and Computer Technology and Engineering Universiti Teknikal Malaysia Melaka (UTeM) Melaka Malaysia School of Physics Universiti Sains Malaysia Penang Malaysia

ISBN: (数字)9798350378313

ISBN: (纸本)9798350378320

Third-generation dye-sensitized solar cells (DSSC) provide many benefits over ordinary solar cells. DSSCs efficiently convert visible light into electrical energy and work well in low light environments. Platinum is a common counter electrode due to its electrocatalytic, conductivity, and reflection properties. Due to its drawbacks, alternative counter electrode materials have been explored. The potential counter electrode of DSSC is molybdenum Sulfide (MoS 2 ), an inorganic compound of molybdenum and sulphur which has good properties in terms of electrochemical properties and long-term stability. Electrodeposition is one of the deposition techniques used in thin film deposition. Due to several challenges in thin deposition techniques with control over film properties, complexity and cost, electrodeposition is a good alternative due to its cost-effectiveness, simplicity, and deposition control. In this work, we studied the effect of deposition electrolyte condition (acidic, neutral, alkaline) to the electrochemical, morphological, and optical properties of molybdenum sulfide thin film. Overall, the study reveals that MoS 2 films exhibit good hydrogen evolution reaction (HER) activity at pH 6 and pH 8, with pH 6 showing the highest performance, while also indicating minimal variation in grain size across different pH levels and highlighting the influence of pH on optical and electronic properties.

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