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2024 International Conference on electrical Machines, ICEM 2024

作者： Ajamloo, Akbar Mohammadi Ibrahim, Mohamed N. Sergeant, Peter Ghent University Department of Electromechanical Systems and Metal Engineering Gent Belgium FlandersMake@UGent-corelab MIRO Leuven Belgium Kafrelshiekh University Department of Electrical Engineering Kafrelshiekh Egypt

ISBN: (纸本)9798350370607

Additive Manufacturing (AM) is a new topic in the field of electrical machines (EMs), offering the potential to overcome the limitations in the design of EMs. Through AM, complex 3D geometries and the utilization of Fe-Si cores with 6.5% silicon can be achieved, leading to enhanced EM performance without concerns about manufacturing cost and complexity. This paper provides an overview of various AM methods and materials used in manufacturing soft magnetic cores for EMs, with a particular emphasis on the multi-physics properties of these cores. Due to the distinct fusion processes in each AM method, the microstructural properties of the printed cores vary, leading to diverse multi-physics properties that require detailed investigation. The paper outlines both the benefits and challenges associated with AM techniques and materials. Importantly, it explores the detailed characteristics of Fe-Si and Fe-Co cores manufactured through different AM methods, comparing them with commercial laminations such as 35A300, JNEX Super Core, and Hiperco 50A. © 2024 IEEE.

关键词： Direct energy conversion

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Transaction transmission model for blockchain channels based on non-cooperative games

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Science China(Information Sciences) 2023年第1期66卷 97-114页

作者： Peiyun ZHANG Chenxi LI Mengchu ZHOU Wenjun HUANG Abdullah ABUSORRAH Omaimah O.BAMASAG Engineering Research Center of Digital Forensics of Ministry of Education School of Computer and SoftwareNanjing University of Information Science and Technology School of Computer and Information Anhui Normal University Department of Electrical and Computer Engineering New Jersey Institute of Technology Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Faculty of Engineering and K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University Department of Computer Science Faculty of Computing and Information Technology Center of Excellence in Smart Environment Research King Abdulaziz University

In blockchain networks, transactions can be transmitted through channels. The existing transmission methods depend on their routing information. If a node randomly chooses a channel to transmit a transaction, the transmission may be aborted due to insufficient funds(also called balance) or a low transmission rate. To increase the success rate and reduce transmission delay across all transactions, this work proposes a transaction transmission model for blockchain channels based on non-cooperative game *** balance, channel states, and transmission probability are fully considered. This work then presents an optimized channel transaction transmission algorithm. First, channel balances are analyzed and suitable channels are selected if their balance is sufficient. Second, a Nash equilibrium point is found by using an iterative sub-gradient method and its related channels are then used to transmit transactions. The proposed method is compared with two state-of-the-art approaches: Silent Whispers and Speedy Murmurs. Experimental results show that the proposed method improves transmission success rate, reduces transmission delay,and effectively decreases transmission overhead in comparison with its two competitive peers.

关键词： Blockchain channel transaction transmission channel balance channel state channel transmission probability non-cooperative game

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Permissioned Blockchain-Based Monitoring Framework for DER-Integrated Distribution Networks 14

Permissioned Blockchain-Based Monitoring Framework for DER-I...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Angın, Pelin Zehir, Alparslan Ceylan, Oguzhan Eissa, Mohamed Aly Amin Selim Yüksel, Murat Can Deveci, Umur Yılmaz, Seyit Cem Göl, Murat Department of Computer Engineering Middle East Technical University Ankara Turkey Department of Electrical and Electronics Engineering Marmara University Turkey Department of Management Information Systems Kadir Has University Turkey Istanbul Turkey Department of Electrical and Electronics Engineering Middle East Technical University Ankara Turkey

ISBN: (纸本)9781837242689

SCADA systems are used for real-time monitoring of key systems and the status of critical assets in both transmission and distribution networks. The trend towards different types of"new" loads and sources such as photovoltaic (PV), electric vehicle (EV) charging stations and battery storage systems is changing the operational approach of distribution grids. Well-known fit-and-forget philosophy is being replaced and requires more operational activities and more thorough monitoring of end devices in new active distribution networks (ADNs). In this paper, a permissioned blockchain-based monitoring framework for distribution networks hosting different types of distributed energy resources (DERs) is presented. The proposed tool operates independently of the SCADA system while it can utilise SCADA measurements for anomaly and fraud detection. In addition, seamless integration and visibility is facilitated by the flow of information between DERs and the distribution system operator through adapters between the blockchain network and the main protocols used for smart metering, inverter management and EV charging stations. The coordinated use of SCADA and the proposed framework will provide a redundant set of observations that will contribute to unbiased state estimation and successful anomaly detection. © The Institution of engineering & Technology 2024.

关键词： Charging stations

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Predictive Maintenance by Machine Learning Methods 11

Predictive Maintenance by Machine Learning Methods

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11th IEEE International Conference on Intelligent Computing and Information systems, ICICIS 2023

作者： Amer, Sara Mohamed, Hoda K. Badr Monir Mansour, Marvy Ain Shams University Department of Computer and Systems Engineering Cairo Egypt British University in Egypt Department of Electrical Engineering Cairo Egypt

ISBN: (纸本)9798350322101

Predictive maintenance techniques are designed to determine the state of equipment in action to help us know when we can intervene to perform maintenance on it. Predictive maintenance design applies artificial intelligence techniques such as machine learning to analyze data and monitor efficiency. In this paper, we predict the maintenance of any equipment before it stops to reduce unplanned equipment maintenance by means of machine learning algorithms. We adopted in our work the following supervised machine learning algorithms: Random Forest, Support Vector Machine, KNN, Decision Tree, Logistic Regression, Naïve Bayes, and XGBOOST. Simulations and results show that the Random Forest and XGBOOST have almost the same performance. The XGBOOST machine learning algorithm is preferred for bigger datasets compared to Random Forest and it works more effectively in the case of small datasets. Finally, the proposed predictive maintenance system is successful in identifying possible failure indicators and reducing some production stoppages as shown by our simulation results. © 2023 IEEE.

关键词： Decision trees

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Parallel Execution of the Viola-Jones Algorithm on MCUs for Low-Cost Automated Pest Detection 1

Parallel Execution of the Viola-Jones Algorithm on MCUs for ...

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1st IEEE Conference on AgriFood Electronics, CAFE 2023

作者： Rusci, Manuele Bompani, Luca Baldoni, Olmo Montanari, Carlo Brunelli, Davide Benini, Luca Ku Leuven Department of Electrical Engineering Belgium University of Trento Department of Industrial Engineering Italy University of Bologna Department of Electrical Electronic and Information Engineering Italy Eth Zürich Integrated Systems Laboratory Switzerland

ISBN: (纸本)9798350327113

This paper presents an energy-optimized solution for on-device pest detection, preventing image streaming from the traps installed in the monitored orchard surface. We optimize the Viola-Jones object detector to run on a low-cost 8-core MicroController (MCU), which is coupled to a low-power image sensor. Thanks to the adopted memory management scheme and the algorithm parallelization, our solution presents a processing latency of only 0.4 sec per image while scoring >80% detection accuracy on low-quality images. This design reduces the memory requirements and complexity of precedent processing pipelines based on Deep Neural Networks and presents a power envelope > 10x lower than more expensive existing solutions. © 2023 IEEE.

关键词： Microcontrollers

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Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser Hameed Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical Engineering Balochistan University of Information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

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DDDAS-Based Learning for Edge Computing at 5G and Beyond 5G 4th

DDDAS-Based Learning for Edge Computing at 5G and Beyond 5G

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4th International Conference on Dynamic Data Driven Applications systems, DDDAS 2022

作者： Runsewe, Temitope Yavuz, Abdurrahman Celik, Nurcin Saad, Walid Department of Industrial and Systems Engineering University of Miami MiamiFL33146 United States Department of Electrical and Computer Engineering Virginia Tech ArlingtonVA22203 United States

ISBN: (纸本)9783031526695

The emerging and foreseen advancements in 5G and Beyond 5G (B5G) networking infrastructures enhance both communications capabilities and the flexibility of executing computational tasks in a distributed manner, including those encountered in edge computing (EC). Both, 5G & B5G and EC environments present complexities and dynamicity in their multi-level and multimodal infrastructures. DDDAS-based design and adaptive and optimized management of the respective 5G, B5G, and EC infrastructures are needed, to tackle the stochasticity inherent in these complex and dynamic systems, and to provide quality solutions for respective requirements. In fact, both emerging communication and computational technologies and infrastructure systems can benefit from their symbiotic relationship in optimizing their corresponding adaptive and optimized management. EC enabled by 5G (and future B5G) allows efficient distributed execution of computational tasks. DDDAS-based methods can support the adaptivity in bandwidth and energy efficiencies in 5G and B5G communications. On the other hand, EC has become a very attractive feature for critical infrastructure such as energy grids as it allows for secure and efficient real-time data processing. In order to fully exploit the advantages of EC, the communication network should be able to tackle the changing requirements related to the task management within edge servers. Thus, leveraging the DDDAS paradigm, we jointly optimize the scheduling and offloading of computational tasks in an EC-enabled microgrid considering both physical constraints of microgrid and network requirements. The results showcase the superiority of the proposed DDDAS-based approaches in terms of network utilization and operational efficiencies achieved, with microgrids as case example. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Energy efficiency

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Designed harmonic step filter automatic control system to improve power quality and electric efficiency

Designed harmonic step filter automatic control system to im...

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2024 International Conference on Power Electronics and Energy System, ICPEES 2024

作者： Pasaribu, Faisal Irsan Sara, Ira Devi Tarmizi, Tarmizi Nasaruddin, Nasaruddin Doctoral Program School of Engineering Universitas Syiah Kuala Aceh23111 Indonesia Department Electrical and Computer Engineering Universitas Syiah Kuala Aceh23111 Indonesia

Good power quality and high-power efficiency are important aspects of power system management. Harmonic, as an unwanted frequency component in electrical signals, can interfere with power quality and reduce electrical efficiency. A passive harmonic filter is a device used to reduce or filter harmonics in electrical power systems. This research proposes technology Internet of Things with an automatic control system that moves the step filter to solve the harmonic problem, with the aim of improving the quality of power and electrical efficiency. The step filter functions to identify and isolate the harmonic, thus enabling appropriate controls to suppress the impact of the harmonic. The proposed system uses sophisticated control algorithms using sensors that can read current, voltage, frequency, and power factor to adjust the step filter parameters dynamically, following changes in load conditions and harmonizing. Simulation of the control network using the proteus software is subsequently undertaken in further research to design the control device. Using an automatic control set in the control simulation results reduced the need for manual intervention and let the system adjust the step filter automatically in response to changing network conditions. This showed that this method worked to lower harmonic distortion, increases the power factor through the filter used, and make the system more energy efficient overall. The study emphasizes the importance of applying sophisticated control strategies to manage harmonics efficiently, which ultimately paves the way to a cleaner and more reliable power grid. © Published under licence by IOP Publishing Ltd.

关键词： Power quality

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Toward better semantic segmentation by retaining spectral information using matched wavelet pooling

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Neural Computing and Applications 2025年第10期37卷 7049-7066页

作者： El-Khamy, Said El-Bana, Shimaa Al-Kabbany, Ahmad Elragal, Hassan Department of Electrical Engineering Alexandria University Alexandria21544 Egypt Intelligent Systems Lab Arab Academy for Science Technology and Maritime Transport Alexandria21937 Egypt Department of Research and Development VRapeutic Inc. Cairo11613 Egypt Alexandria Higher Institute of Engineering and Technology Alexandria21311 Egypt

Pooling operations, such as average pooling, strided convolution, and max pooling, have become fundamental components of convolutional neural networks (CNNs) due to their ability to capture local features, expand receptive fields, and reduce computational costs. However, in the context of semantic segmentation, these pooling techniques can lead to the loss of crucial spatial details that are necessary for accurate pixel-level predictions. To tackle this issue, extensive research has focused on refining deep CNN models through architectural adaptations and novel training methods. Recent studies have demonstrated the importance of pooling layers, exemplified by innovations like the introduction of wavelet pooling. In our study, we highlight the value of incorporating our previously proposed matched wavelet pooling (MWP) into CNNs to enhance semantic segmentation pipelines. The core concept of MWP challenges the notion that including all sub-bands generated from wavelet decomposition consistently improves accuracy. Instead, we advocate for selecting specific sub-bands for the pooling process in each image during both training and testing. This approach introduces sub-band selection protocols customized for image-specific pooling, designed specifically for semantic segmentation CNN architectures, with a particular focus on the UNet and SegNet models. Across three widely used datasets, our proposed MWP- based pipeline, featuring the MWP-UNet architecture, consistently outperforms conventional pooling methods. It achieves a significant average improvement in intersection over union (IoU) of over 25% compared to recent literature. Additionally, our MWP-SegNet model outperformed the standard SegNet by 12.5% mIoU, further demonstrating the effectiveness of our matched wavelet pooling approach across different network architectures. © The Author(s) 2025.

关键词： Semantic Segmentation

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Nonlinear Sparse Channel Estimator for Hybrid MIMO Millimeter Wave Communication 35

Nonlinear Sparse Channel Estimator for Hybrid MIMO Millimete...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Jain, Sandesh Singya, Praveen Kumar Shukla, Vidya Bhasker Majhi, Sudhan Bhatia, Vimal Department of Electrical and Electronics Engineering Gwalior474015 India Center for Autonomous Systems ABV-IIITM Gwalior 474015 India Department of Electrical Engineering Indore453552 India Indian Institute of Science Department of Electrical Communication Engineering Bangalore560012 India Iit Indore and Soochow University Center for Advanced Electronics China

ISBN: (纸本)9798350362244

The multi-input multi-output (MIMO) millimeter wave (mmWave) is a promising technology for beyond 5G communication systems, which provides high data rates, ultra-low latency, massive connectivity, and high spectral efficiency. However, a typical mmWave communication link is severely impaired by path loss, nonlinear device impairments, and non-Gaussian noise. Furthermore, MIMO mmWave channel exhibits sparseness due to blockage and scattering. The conventional orthogonal matching pursuit (OMP), zero-attracting least mean square (ZA-LMS), and their variants deliver suboptimal performance for nonlinear mmWave systems. To improve the estimation accuracy, we propose a random Fourier features (RFF) based sparsity-aware kernel maximum correntropy (SA-KMC) algorithm, which is robust for MIMO mmWave sparse channel estimation in the presence of nonlinear hardware impairments and non-Gaussian distortions. Simulations indicate that the proposed RFF-SA-MCC algorithm outperforms the existing state-of-art approaches. © 2024 IEEE.

关键词： Channel estimation

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