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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Yu, Xipei Feng, Junjie Zhu, Liyan Li, Qiang Virginia Polytechnic Institute and State University Center for Power Electronics Systems The Bradley Department of Electrical and Computer Engineering Blacksburg United States

ISBN: (纸本)9798350376067

Recently, omnidirectional wireless power transfer (WPT) has gained widespread popularity since 2010s especially in consumer electronics application benefiting from ease of integration with furniture. In such applications, angular misalignment occurs frequently. Obviously, it will affect the stable operation of system significantly. However, the coil optimization is not investigated accurately. In other words, the modelling and effects under angular misalignment are not investigated completely. Targeting at this, this article proposes a planar omnidirectional wireless power transfer system with three sets of planar coils. Afterwards, the modelling process is conducted for the planar omnidirectional WPT system under angular misalignment and Ns effect is investigated. Afterwards, the coil optimization is conducted to increase its usability in real applications. Finally in the experiment, three sets of coils are fabricated and the transfer efficiency are measured under orientation and angular misalignment at 6.78MHz. When charging the mobile phone and electronic watch receivers, the overall efficiency is 69%-78% and 55%-65%, considering the orientation and angular misalignment. © 2024 IEEE.

关键词： Inductive power transmission

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Mutual Inductance Extraction and Power Allocation of a Planar Omnidirectional WPT System

Mutual Inductance Extraction and Power Allocation of a Plana...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

ISBN: (纸本)9798350376067

In recent times, planar omnidirectional wireless power transfer has emerged as a prominent technology, especially in consumer electronics application. However, in such scenario, the presence of multiple receivers with angular misalignment often results in unstable operation due to variations in mutual inductance. To address this challenge, this article undertakes the modelling of several receiver coils and proposes a method to extract mutual inductance between them utilizing additional DC/DC converters. This extraction process serves to mitigate these effects, thereby enabling effective power allocation among multiple receivers Finally, the experimental validation is conducted. at 6.78MHz. When charging the mobile phone and electronic watch receivers, the overall efficiency is 68%-77% and 56%-66%, considering the orientation and angular misalignment. © 2024 IEEE.

关键词： Inductive power transmission

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Brain inspired iontronic fluidic memristive and memcapacitive device for self-powered electronics

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Microsystems & Nanoengineering 2025年第1期11卷 465-476页

作者： Muhammad Umair Khan Bilal Hassan Anas Alazzam Shimaa Eissa Baker Mohammad Center for Cyber-Physical Systems-System on Chip Lab Khalifa UniversityAbu Dhabi 127788UAE Department of Computer and Information Engineering Khalifa UniversityAbu Dhabi 127788UAE Department of Electrical Engineering Khalifa UniversityAbu Dhabi 127788UAE Division of Engineering New York UniversityAbu Dhabi 129188UAE Department of Mechanical and Nuclear Engineering Khalifa UniversityAbu Dhabi 127788UAE Department of Chemistry Khalifa UniversityAbu Dhabi 127788UAE

Ionic fluidic devices are gaining interest due to their role in enabling self-powered neuromorphic computing *** this study,we present an approach that integrates an iontronic fluidic memristive(IFM)device with low input impedance and a triboelectric nanogenerator(TENG)based on ferrofluid(FF),which has high input *** incorporating contact separation electromagnetic(EMG)signals with low input impedance into our FF TENG device,we enhance the FF TENG’s performance by increasing energy harvesting,thereby enabling the autonomous powering of IFM devices for self-powered ***,replicating neuronal activities using artificial iontronic fluidic systems is key to advancing neuromorphic *** fluidic devices,composed of soft-matter materials,dynamically adjust their conductance by altering the solution *** developed voltage-controlled memristor and memcapacitor memory in polydimethylsiloxane(PDMS)structures,utilising a fluidic interface of FF and polyacrylic acid partial sodium salt(PAA Na^(+)).The confined ion interactions in this system induce hysteresis in ion transport across various frequencies,resulting in significant ion memory *** IFM successfully replicates diverse electric pulse patterns,making it highly suitable for neuromorphic ***,our system demonstrates synapse-like learning functions,storing and retrieving short-term(STM)and long-term memory(LTM).The fluidic memristor exhibits dynamic synapse-like features,making it a promising candidate for the hardware implementation of neural *** TENG/EMG device adaptability and seamless integration with biological systems enable the development of advanced neuromorphic devices using iontronic fluidic materials,further enhanced by intricate chemical designs for self-powered electronics.

关键词： iontronic memristive ionic fluidic devices memcapacitive ff teng s ff teng fluidic triboelectric nanogenerator teng based

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A Multifunctional Hydrogel with Multimodal Self-Powered Sensing Capability and Stable Direct Current Output for Outdoor Plant Monitoring systems

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Nano-Micro Letters 2025年第4期17卷 1-24页

作者： Xinge Guo Luwei Wang Zhenyang Jin Chengkuo Lee Department of Electrical&Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117576Singapore Center for Intelligent Sensors and MEMS(CISM) National University of Singapore5 Engineering Drive 1Singapore 117608Singapore NUS Graduate School-Integrative Sciences and Engineering Program(ISEP) National University of SingaporeSingapore 119077Singapore Research Center for Sustainable Urban Farming(SUrF) National University of SingaporeSingapore 117558Singapore

Smart farming with outdoor monitoring systems is critical to address food shortages and sustainability *** systems facilitate informed decisions that enhance efficiency in broader environmental *** outdoor systems equipped with energy harvesters and self-powered sensors often struggle with fluctuating energy sources,low durability under harsh conditions,non-transparent or non-biocompatible materials,and complex ***,a multifunctional hydrogel is developed,which can fulfill all the above requirements and build selfsustainable outdoor monitoring systems solely by *** can serve as a stable energy harvester that continuously generates direct current output with an average power density of 1.9 W m^(-3)for nearly 60 days of operation in normal environments(24℃,60%RH),with an energy density of around 1.36×10^(7)J m^(-3).It also shows good self-recoverability in severe environments(45℃,30%RH)in nearly 40 days of continuous ***,this hydrogel enables noninvasive and self-powered monitoring of leaf relative water content,providing critical data on evaluating plant health,previously obtainable only through invasive or high-power consumption *** potential extends to acting as other self-powered environmental *** multifunctional hydrogel enables self-sustainable outdoor systems with scalable and low-cost production,paving the way for future agriculture.

关键词： Self-powered sensor Hydrogel Energy harvester Outdoor farming Self-sustainable IoT

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GENERALIZED BAYES SURE FOR MULTIVARIATE NORMAL DISTRIBUTION UNDER BALANCED-QUADRATIC LOSS

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Journal of Mathematical Sciences (United States) 2024年第2期280卷 262-274页

作者： Karamikabir, Hamid Afshari, Mahmoud Karamikabir, Nasrin Kiaei, Seyed Faridoddin Department of Statistics Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran Department of Mathematics Hamedan Branch Islamic Azad University Hamedan Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

One of the most important subjects in statistics is the theory of estimation. In this paper, we consider the generalized Bayes shrinkage estimator of the mean vector for multivariate normal distribution with the unknown covariance matrix under balanced quadratic loss. Also, we find the minimax and admissible estimator of the mean vector based on the generalized Bayes estimator. We obtain Stein’s unbiased risk estimator (SURE) threshold with a generalized Bayes shrinkage estimator and we find the wavelet shrinkage generalized Bayes SURE. Finally, we present a simulation study to test the validity of the generalized Bayes SURE and the concrete compressive strength dataset is given to test the efficiency of this estimator in denoising. © 2024, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Balanced-quadratic loss Generalized bayes estimator Shrinkage estimaton Shrinkage wavelet SURE threshold

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Digital Twins for Creating Virtual Models of Solar Photovoltaic Plants

Digital Twins for Creating Virtual Models of Solar Photovolt...

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： George, Deborah Venayagamoorthy, Ganesh K. Clemson University Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering ClemsonSC29634 United States

ISBN: (纸本)9781665430654

Amidst the challenges posed by the high penetration of distributed energy resources (DERs), particularly a number of distributed photovoltaic plants (DPVs), in modern electric power distribution systems (MEPDS), the integration of new technologies and frameworks become crucial for addressing operation, management, and planning challenges. Situational awareness (SA) and situational intelligence (SI) over multi-time scales is essential for enhanced and reliable PV power generation in MEPDS. In this paper, data-driven digital twins (DTs) are developed using AI paradigms to develop actual and/or virtual models of DPV s, These DTs are then applied for estimating and forecasting the power outputs of physical and virtual PV plants. Virtual weather stations are used to estimate solar irradiance and temperature at user-selected locations in a localized region, using inferences from physical weather stations. Three case studies are examined based on data availability: physical PV plant, hybrid PV plants, and virtual PV plants, generating real-time estimations and short-term forecasts of PV power production that can support distribution system studies and decision-making. © 2023 IEEE.

关键词： - AI digital twin distributed energy resources power distribution systems virtual systems weather stations

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Adaptive nonsingular integral-type dynamic terminal sliding mode synchronizer for disturbed nonlinear systems and its application to secure communication systems

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JVC/Journal of Vibration and Control 2023年第11-12期29卷 2566-2578页

作者： Vaseghi, Behrouz Mobayen, Saleh Din, Sami ud Hashemi, Seyedeh Somayeh Vu, Mai The Department of Electrical and Computer Engineering Abhar Branch Islamic Azad University Abhar Iran Department of Electrical Engineering University of Zanjan Zanjan Iran Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Electrical Engineering Namal University Mianwali Mianwali Pakistan School of Intelligent Mechatronics Engineering Sejong University Seoul Korea Republic of

This study proposes an adaptive nonsingular integral dynamic terminal sliding mode tracker/synchronizer for disturbed nonlinear systems along with its usage in safe communication systems. The convergence of the closed-loop structure under unknown uncertainty and disturbances is guaranteed via Lyapunov analysis. Furthermore, a parameter-tuning method is planned to approximate the upper bound of uncertainty and disturbance terms, since this latter is typically unknown in practice. The proposed approach is used to design a digital secure transmission scheme according to the chaotic systems. The effectiveness of the suggested approach is validated using computer simulations on a benchmark example of chaotic system. The obtained outcomes clearly confirm the ability of the planned control approach enables to attain the desired tracking/synchronizing performance despite the disturbances. Additionally, when implemented to the data encryption of a communication system, the proposed control and secure communication techniques enabled the complete and secure retrieval of the original digital sequences. © The Author(s) 2022.

关键词： Chaotic systems

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Design of Supervisory Model Predictive Control for HVAC systems and Two Zones with Consideration of Energy Efficiency and Thermal Comfort 23

Design of Supervisory Model Predictive Control for HVAC Syst...

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23rd International Conference on Control, Automation and systems, ICCAS 2023

作者： Srisurapanon, Panithan Banjerdpongchai, David Chulalongkorn University Center of Excellence in Intelligent Control Automation for Process Systems Faculty of Engineering Department of Electrical Engineering Pathumwan Bangkok10330 Thailand

ISBN: (纸本)9788993215274

This paper presents the design of supervisory model predictive control for HVAC systems and two zones. The supervisory control (SC) is designed to find the optimal reference temperature of each zone. The design criteria consist of the total operating cost (TOC) and the thermal comfort cost (TCC). Then, the model predictive control (MPC) is designed to track the optimal reference signals. When SC and MPC are designed for two zones simultaneously, they are referred to centralized SC and centralized MPC. On the other hand, when SC and MPC are designed for two zones separately, they referred to decentralized SC and decentralized MPC. We then compare the results between the decentralized control and the centralized control. The trade-off curve shows that the performance of centralized control is better than that of decentralized control. In particular, centralized MPC improves the performance in tracking reference signals. Furthermore, TOC of centralized control is lower than that of decentralized control. It can be concluded that the centralized control is appropriate for two zones in terms of the tracking of reference and the electrical charge. © 2023 ICROS.

关键词： Model predictive control

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Robust Authentication: Leveraging Hardware Fingerprints and AI to Enhance Security Against Spoofing

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IEEE Access 2025年 13卷 86912-86926页

作者： Nimmy, K. Jain, Kurunandan Sachin, S.M. Abekaesh, P.A. Venkitasubramaniam, Parv Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri690525 India Center for Cybersecurity Systems and Networks Amrita Vishwa Vidyapeetham Amritapuri Campus Kerala Amritapuri690525 India Lehigh University Department of Electrical and Computer Engineering BethlehemPA18015 United States

Fingerprint authentication blends biometric precision with user convenience, leveraging unique ridge patterns for fast, reliable, and tamper-resistant identity verification. However, it remains vulnerable to spoofing attacks, where adversaries create synthetic fingerprints using materials like gelatin. To mitigate this, multi-factor authentication (MFA) enhances security by verifying both the fingerprint and the user’s device, restricting access to authorized hardware and complicating attacks. Although Photo Response Non-Uniformity (PRNU) has been explored for device authentication, its reliability diminishes under varying lighting conditions. To address this, we propose an AI-driven approach to generate robust hardware fingerprints from fingerprint scanners, enabling high-accuracy device identification. Our method, trained on 2,000 fingerprint images from 10 scanners, achieves an impressive 98% accuracy in identifying the source scanner. By integrating fingerprint biometrics, hardware fingerprints, and passwords, our novel MFA protocol significantly enhances security against spoofing and forgery attacks. Through security analysis, we demonstrate its effectiveness in preventing unauthorized access. Finally, we validate our authentication framework using an AI-powered binary classifier model, showcasing its practicality for real-world security applications. © 2013 IEEE.

关键词： Authentication Protocol

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Automated lumpy skin grading in bovine images using novel deep convolutional neural networks

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Multimedia Tools and Applications 2024年 1-26页

作者： Muhammad, Abdul Malik ur Rehman, Muhammad Zia Mushtaq, Zohaib Qureshi, Muhammad Farrukh Department of Biomedical Engineering Riphah International University Islamabad44000 Pakistan Department of Electrical Electronics and Computer Systems University of Sargodha Sargodha40100 Pakistan Department of Electrical Engineering Namal University Mianwali Mianwali42250 Pakistan Center of AI and BigData Namal University Mianwali Mianwali42250 Pakistan

The diagnosis and prevention of lumpy skin disease, a viral ailment affecting cattle and buffalo, present significant financial implications for the livestock industry. Traditional methods for identifying lumpy skin disease rely on manual visual inspection by veterinarians, which can be labor-intensive, subjective, and prone to errors. To address these challenges, this study proposes a novel deep convolutional neural network (DCNN) model for the automatic recognition and grading of lumpy skin disease from bovine images. The primary contributions of this research include the development of a DCNN architecture specifically tailored for this task, comprising five convolutional layers, five max pooling layers, two fully connected layers with ReLU activation, and a final fully connected layer with softmax activation. The model’s detection accuracy is further enhanced by applying image cropping and patching techniques, which divide each input image into 12 patches to improve local feature extraction. The proposed model was trained and tested using a publicly available dataset from Kaggle. Comparative analysis was conducted against several state-of-the-art models, including InceptionV3, ResNet50, MobileNetV3, VGG19, and Xception. The DCNN model demonstrated superior performance, achieving the highest validation accuracy of 0.96875, outperforming the compared models in terms of accuracy, precision, recall, and F1 score. Additionally, the study explores the potential of transitioning from binary to multiclass classification, which would allow for the assessment of the severity of lumpy skin disease. This future direction aims to provide more nuanced and actionable information for veterinary diagnostics. The significance of this research lies in its potential to offer an objective, efficient, and scalable solution for early disease detection and prevention in livestock, thereby presenting considerable economic benefits for farmers and the livestock industry as a whole. The me

关键词： Convolutional neural networks

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