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Multi-Scale Analysis Combined Operando Elemental/Spectroscopic Measurement Techniques in Oxide-Type All-Solid-State Na Batteries

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Energy & Environmental Materials 2025年第2期8卷 38-47页

作者： Koji Hiraoka Kazuo Yamamoto Takeshi Kobayashi Tetsuo Sakamoto Shiro Seki Graduate School of Engineering Applied Chemistry and Chemical Engineering Program Kogakuin University Nanostructures Research Laboratory Japan Fine Ceramics Center Energy Transformation Research Laboratory Central Research Institute of Electric Power Industry Graduate School of Engineering Electrical Engineering and Electronics Program Kogakuin University

Understanding the charge/discharge mechanism of batteries plays an important role in the development of high-performance systems,but extremely complicated reactions are *** these complex phenomena are also bottlenecks for the establishment of all-sol id-state batteries(ASSB),we conducted multi-scale analysis using combined multi-measurement techniques,to directly observe charge/discharge reactions at hierarchical scales for the oxide-type ASSB using Na as the carrier *** particular,all of measurement techniques are applied to cross-section ASSB in the same cell,to complementarily evaluate the elemental distributions and structural *** Operando scanning electron microscopy-energy-dispersive X-ray spectroscopy,the Na concentration in the electrode layers changes on the micrometer scale under charge/discharge reactions in the first ***,Operando Raman spectroscopy reveal changes in the bonding states at the atomic scale in the active material,including changes in reversible structural *** cycling the ASSB,the elemental distributions are clearly observed along with the particle shapes and can reveal the Na migration mechanism at the nanometer scale,by time-of-flight secondary ion mass ***,this study can provide a fundamental and comprehensive understanding of the charge/discharge mechanism by observing reaction processes at multiple scales.

关键词： Operando oxide-type all-solid-state battery Raman SEM-EDS sodium battery TOF-SIMS

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Verification of Impedance Matching Using Input/Output Current Equalization Control in Wireless Power Transfer Systems with Active Rectifier

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IEEJ Transactions on Industry Applications 2025年第4期145卷 261-271页

作者： Kobayashi, Seiya Maekawa, Sari Electrical Engineering Program Graduate School of Science and Technology Meiji University 1-1-1 Higashimita Tama-ku Kanagawa Kawasaki214-8571 Japan

The efficiency of a wireless power transfer system changes with the load. To solve this problem, an impedance matching method has been developed. Conventional methods control the equivalent load to the optimal value using circuit parameters and the detected load voltage and current. However, they require estimating the mutual inductance M in case of misalignment or an airgap change. M-estimation has some issues such as a limited operating range. In this study, we developed a high-efficiency operation method that can respond to a change in M without its estimation by controlling the currents in the coils to equalize them. We confirmed that the developed method enables highly efficient operation without M-estimation despite misalignment. © 2025 The Institute of electrical Engineers of Japan.

关键词： Inductive power transmission

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Vision-Based Landing Guidance Through Tracking and Orientation Estimation

Vision-Based Landing Guidance Through Tracking and Orientati...

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2025 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2025

作者： Ferreira, João P. K. Pinto, João P. Moura, Júlia Li, Yi Castro, Cristiano L. Angelov, Plamen Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Brazil School of Computing and Communications Lancaster University United Kingdom

ISBN: (纸本)9798331510831

Fixed-wing aerial vehicles are equipped with functional-ities such as ILS (instrument landing system), PAR (precision approach radar) and, DGPS (differential global positioning system), enabling fully automated landings. How-ever, these systems impose significant costs on airport op-erations due to high installation and maintenance requirements. Moreover, since these navigation parameters come from ground or satellite signals, they are vulnerable to in-terference. A more cost-effective and independent alternative for guiding landing is a vision-based system that de-tects the runway and aligns the aircraft, reducing the pi-lot's cognitive load. This paper proposes a novel frame-work that addresses three key challenges in developing au-tonomous vision-based landing systems. Firstly, to over-come the lack of aerial front-view video data, we created high-quality videos simulating landing approaches through the generator code available in the LARD (landing approach runway detection dataset) repository. Secondly, in contrast to former studies focusing on object detection for finding the runway, we chose the state-of-the-art model Lo-RAT to track runways within bounding boxes in each video frame. Thirdly, to align the aircraft with the designated landing runway, we extract runway keypoints from the re-sulting LoRAT frames and estimate the camera relative pose via the Perspective-n-Point algorithm. Our experimental re-sults over a dataset of generated videos and original images from the LARD dataset consistently demonstrate the proposed framework's highly accurate tracking and alignment capabilities. Our approach source code and the Lo-RAT model pre-trained with LARD videos are available at https://***/jpklock2/vision-based-landing-guidance © 2025 IEEE.

关键词： Global positioning system

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An Ensemble-Based Classifier to Determine the Harmonic Contribution Responsibility Between Utility’s Grid and Microgrids

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IEEE Access 2025年 13卷 85873-85881页

作者： Mella, Matheus C. Fernandes, Ricardo A.S Barbosa, Daniel Federal University of São Carlos Graduate Program in Electrical Engineering São Carlos Brazil University of São Paulo São Carlos School of Engineering Department of Electrical and Computer Engineering São Carlos Brazil Federal University of Bahia Department of Electrical Engineering Salvador Brazil

The integration of nonlinear loads and distributed energy resources in microgrids (MG) has increased the levels of harmonic distortions in distribution feeders. Identifying the responsibility for the harmonic distortions measured at the MG’s point of common coupling (PCC) is essential for managing the power quality. For this purpose, the present paper aims to determine whether the responsibility predominates from the utility’s grid or the MG itself. Thus, an ensemble-based approach was proposed, comparing the behaviour of Random Forest and XGBoost classifiers to identify the side with the predominant harmonic contribution. In order to validate the proposed approach, scenarios were simulated in the IEEE 34-node test feeder using the ATP/ATPDraw software, considering the harmonic sources located at different nodes of the feeder. Three-phase voltage and current signals were acquired at MG’s PCC to train and validate the ensembles. However, a feature extraction stage was performed to obtain time and frequency features used as inputs to the predictive models. The results demonstrated that the proposed approach effectively identified the contribution side, achieving an average F1-score above 99% for both ensembles, representing a feasible solution for determining the harmonic distortion responsibilities at the MG’s PCC. © 2013 IEEE.

关键词： Software testing

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Production and characterization of polymeric nanocomposite foams based on starch and cellulose nanofibers from oil palm mesocarp fiber

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Applied Nanoscience (Switzerland) 2025年第2期15卷 1-11页

作者： Souza, Mariana Costa Gonçalves, Ana Paula Bispo da Silva Oliveira, Emanoel Igor dos Santos, Juscivaldo Passos Lazzari, Lídia Kunz Zattera, Ademir José José, Nadia Mamede Chemical Engineering Graduate Program Polytechnic School Federal University of Bahia Bahia Salvador Brazil Department of Education Federal Institute of Education Science and Technology Feira de Santana Bahia Brazil Postgraduate Program in Process Engineering and Technologies University of Caxias Do Sul Rio Grande Do Sul Caxias Do Sul Brazil

The demand for sustainable and eco-friendly materials has promoted studies over the years to explore different polymeric materials that meet requirements such as biodegradability and sustainability. In this context, biopolymer materials based on cellulose nanoparticles and starch from different botanical sources have been investigated, aiming to achieve satisfactory performance. The present study aims to develop and characterize cassava starch foams based on density, scanning electron microscopy (SEM), and three-point flexure tests, and to evaluate the effect of cellulose nanofibers obtained from palm mesocarp fibers using the ultrafine friction grinding method after different processing times, characterized by X-ray diffractometry (XRD), microscopy, and chemical composition, as a reinforcing filler. The chemical composition and scanning electron microscopy revealed the effectiveness of the cellulose isolation process, with the analysis of the chemical composition revealing a cellulose content of 55.70% in the fibers after pulping and bleaching, in addition to changes in the visual characteristics of the material after the process aimed at isolating the cellulose. After grinding, XRD showed an increase in crystallinity (76.1% at the maximum grinding time), along with typical microscopy images of cellulose nanofibers. The analysis of the obtained nanocomposites provided insights into the role of these nanostructures in the thermo-expanded starch matrix, indicating that the nanofibers promoted changes such as an increase in mechanical properties and crystallinity, which contributed to improving overall mechanical performance. A 67.48% increase in flexural strength was achieved for the formulation with cellulose nanofibers that underwent 150 min of grinding, without causing major variations in density. © King Abdulaziz City for Science and Technology 2025.

关键词： Starch

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ZeroCAN: Anomaly-Based Zero-Day Attack Detection in Vehicular CAN Bus Networks 33

ZeroCAN: Anomaly-Based Zero-Day Attack Detection in Vehicula...

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33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2025

作者： Rendel, Jonathan Balte, William Kurunathan, Harrison Ali, Hazem Ismail Roque, Alexandre Dos Santos Morais, Wagner Ourique De Fazeli, Mahdi Halmstad Sweden Polytechnic Institute of Porto CISTER/ISEP Portugal Federal University of Rio Grande do Sul - UFRGS Graduate Program of Electrical Engineering Porto Alegre Brazil

ISBN: (纸本)9798331524937

Zero-day attacks present a significant security threat to vehicular networks, exploiting vulnerabilities at both software and hardware levels within such systems that remain undiscovered. Mitigating these threats is essential to ensuring the safety and security of vehicular systems. Support Vector Machine (SVM) is a good candidate for anomaly detection of zero-day attacks within vehicular networks because it can handle highdimensional data and effectively distinguish between normal and abnormal patterns in complex and dynamic environments. A trained SVM on the normal operation data of in-vehicular network can identify flag deviations, thus making it effective in the detection of any previously unknown attack patterns, which is a common behaviour of zero-day attacks. In this paper, we introduce an anomaly detection method called "ZeroCAN"which models the behaviour of every single electronic control unit on the network with a separate SVM and a set of high-level features that capture the timing and data payload aspects of CANbus traffic. This approach achieves an anomaly detection rate of over 99% and a false positive rate below 0.01% during normal operation in most cases. © 2025 IEEE.

关键词： Anomaly detection CAN bus IDS Feature engineering Zero-day

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Robust Health Monitoring for Lithium-Ion Batteries under Guidance of Proxy Labels: A Deep Multi-Task Learning Approach

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IEEE Transactions on Power Electronics 2025年第8期40卷 10272-10285页

作者： Guo, Ruohan Zhang, Kui He, Shangyang Tao, Shengyu Zhang, Xuan Liu, Kailong Li, Xiangjun Tian, Jinpeng Shen, Weixiang Chung, Chi Yung The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Research Centre for Grid Modernisation Kowloon999077 Hong Kong Tsinghua University Tsinghua Shenzhen International Graduate School Shenzhen518055 China Shandong University School of Control Science and Engineering Jinan250100 China China Electric Power Research Institute Beijing100192 China Swinburne University of Technology School of Engineering MelbourneVIC3122 Australia

State of health (SOH) estimation is foundational for effective health prognosis and management of lithium-ion batteries. However, conventional data-driven approaches struggle to ensure robust generalisability when training data lacks sufficient SOH labels. In this work, we explore the potential utility of ageing information, gathered from routine operational data beyond the standard input collection region, as proxy labels (PLs) to establish nonlinear mappings between a short charging segment and SOH. To achieve this, we develop a multi-task learning (MTL) framework for battery health monitoring, which comprises two critical components: (1) a deep MTL model, and (2) a multivariate Gaussian process regression (GPR) model. The deep MTL model is designed with four distinct tasks, each with a specific goal to exploit data under different labelling conditions, facilitating the extraction of domain-invariant and target-specific features for PL estimation. Using the estimated PLs, the GPR model is employed to provide precise mappings to SOH. Validations are conducted on batteries with diverse chemistries and cycling temperatures, particularly under severe label scarcity below 5%. The results confirm the effectiveness of the proposed method, outperforming baseline methods and achieving a mean absolute error of less than 1.3% in all case studies. © 1986-2012 IEEE.

关键词： Electronic health record

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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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A Hybrid Data-Driven Approach Integrating Temporal Fusion Transformer and Soft Actor-Critic Algorithm for Optimal Scheduling of Building Integrated Energy Systems

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Journal of Modern Power Systems and Clean Energy 2025年第3期13卷 878-891页

作者： Ze Hu Peijun Zheng Ka Wing Chan Siqi Bu Ziqing Zhu Xiang Wei Yosuke Nakanishi Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong China Graduate School of Environment and Energy Engineering Waseda University Tokyo Japan

Building integrated energy systems (BIESs) are pivotal for enhancing energy efficiency by accounting for a significant proportion of global energy consumption. Two key barriers that reduce the BIES operational efficiency mainly lie in the renewable generation uncertainty and operational non-convexity of combined heat and power (CHP) units. To this end, this paper proposes a soft actor-critic (SAC) algorithm to solve the scheduling problem of BIES, which overcomes the model non-convexity and shows advantages in robustness and generalization. This paper also adopts a temporal fusion transformer (TFT) to enhance the optimal solution for the SAC algorithm by forecasting the renewable generation and energy demand. The TFT can effectively capture the complex temporal patterns and dependencies that span multiple steps. Furthermore, its forecasting results are interpretable due to the employment of a self-attention layer so as to assist in more trustworthy decision-making in the SAC algorithm. The proposed hybrid data-driven approach integrating TFT and SAC algorithm, i.e., TFT-SAC approach, is trained and tested on a real-world dataset to validate its superior performance in reducing the energy cost and computational time compared with the benchmark approaches. The generalization performance for the scheduling policy, as well as the sensitivity analysis, are examined in the case studies.

关键词： Optimization Thin film transistors Uncertainty Heating systems Energy consumption Forecasting Decision making Cogeneration Job shop scheduling Buildings

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Vision-Based Landing Guidance Through Tracking and Orientation Estimation

Vision-Based Landing Guidance Through Tracking and Orientati...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： João P. K. Ferreira João P. Pinto Júlia Moura Yi Li Cristiano L. Castro Plamen Angelov Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais School of Computing and Communications Lancaster University

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

关键词： Visualization Codes Accuracy Atmospheric modeling Pose estimation Video sequences Radar tracking Generators Aircraft navigation Global Positioning System

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