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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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An influence-based k-nearest neighbour classifier for classification of data with different densities

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International Journal of Business Intelligence and Data Mining 2024年第2期25卷 147-167页

作者： Motallebi, Hassan Fakhteh, Amir-Hossein Faculty of Electrical and Computer Engineering Graduate University of Advanced Technology Kerman Iran

The k-nearest neighbour (KNN) is a simple and yet effective classification rule. To achieve robustness against outliers, several local mean-based extensions of the KNN classifier have been proposed which assign the query to the class with nearest local mean. However, using the conventional proximity measures causes poor performance in situations with multi-scale classes. Here, we propose a new local mean-based KNN classifier that uses a new modified distance measure which adjusts the proximity around each sample with respect to the situation and density. We scale the distance from the sample to each class with respect to the size of its influence set such that the sample seems closer to classes in which it has a higher number of reverse neighbours. We apply the proposed method on three local mean-based KNN classifiers. Our results show that the proposed method improves the performance of the local mean-based classifiers. © 2024 Inderscience Enterprises Ltd.

关键词： Nearest neighbor search

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Experimental evaluation of MIMO configurations in indoor visible light communications under the consideration of illumination

Optics Continuum

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Optics Continuum 2025年第4期4卷 789-803页

作者： Esteban Farfán-Guillén, David Camporez, Higor Silva, Jair Adriano Lima Castellano Rodriguez, Juan Camilo Pohl, Alexandre De Almeida Prado CPGEI–Graduate Program in Electrical Engineering and Computer Science Federal University of Technology Paraná Curitiba80230–901 Brazil Graduate Program in Electrical Engineering Federal University of Espírito Santo Vitória29075-960 Brazil

Visible light communications (VLC) enable wireless data transmission using existing light-emitting diode (LED) illumination. This experimental study evaluates the performance of multiple input and multiple output (MIMO) configurations in indoor VLC systems by analyzing their impact on both communication and illumination. Various MIMO setups (2 × 2, 3 × 2, and 4 × 2) are compared against single input single output (SISO), and single input multiple outputs (SIMO) schemes, using commercial LED luminaires as transmitters. While the 4 × 2 MIMO configuration demonstrates superior overall performance, intermediate configurations like 3 × 2 or 2 × 2 MIMO offer an attractive trade-off between system complexity and performance enhancement, particularly in scenarios with space or cost constraints. The results show that MIMO configurations significantly outperform SISO systems, achieving reliable communication (BER ≤ 10−3) at practical indoor distances of up to 2 meters while maintaining illumination levels above 300 lux, where conventional SISO setups do not meet these dual requirements. These findings demonstrate the practical feasibility of MIMO-VLC systems for indoor deployments. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Frequency division multiplexing Modulation techniques Multiple input multiple output Quadrature amplitude modulation Signal processing Visible light communications

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Measuring Public Wi-Fi Security Awareness via Captive Portal Connections Using a Microcontroller

Measuring Public Wi-Fi Security Awareness via Captive Portal...

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2024 Workshop on Communication Networks and Power Systems, WCNPS 2024

作者： Mariano, Hyago Santana Cafe, Daniel Chaves Professional Graduate Program in Electrical Engineering-PPEE Department of Electrical Engineering Brazil

ISBN: (纸本)9798331507152

This article proposes the implementation of a captive portal system on a microcontroller to assess users' maturity regarding the safe use of public Wi-Fi networks. The use of public Wi-Fi networks has become increasingly common in places like cafes, airports, shopping centers, and hotels. However, many users are unaware of the risks associated with using these unsecured networks, such as personal information theft, privacy invasion, and cyberattacks. This study aims to utilize a microcontroller to generate a signal mimicking a known public network, where, upon user login, an educational authentication portal will be displayed. This portal will not only provide information about security risks but also evaluate the users' maturity level in adopting safe practices on public Wi-Fi networks, offering guidelines on how to protect their data and devices. © 2024 IEEE.

关键词： Wi-Fi

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Deep Convolutional Neural Networks for Accurate Solar Module Classification in Thermal Images 12

Deep Convolutional Neural Networks for Accurate Solar Module...

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12th International electrical engineering Congress, iEECON 2024

作者： Phungket, Chutinun Nangthin, Prasit Pathumwan Institute Of Technology The Graduate Program Faculty Of Engineering Faculty Of Engineering Bangkok Thailand Pathumwan Institute Of Technology Faculty Of Engineering Department Of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9798350383591

The rapid and continuous technological advancements in computer and internet technologies, combined with data management techniques, find applications in various domains. For example, they aid in predictive maintenance systems, evaluate the performance of solar modules, and differentiate efficiently performing solar modules from less efficient ones using thermal imagery. The accuracy of solar module classification significantly impacts the subsequent assessment. In this study, we employ advanced techniques, particularly deep learning through Convolutional Neural Networks (CNN), to classify thermal images of solar modules. The practical aspects of applying CNN to the dataset of thermal images are explored, including transfer learning from pretrained CNN architectures and custom CNN architecture training. Experiments are conducted with three prominent types of solar module conditions: normal, cracked, and dusty. The results reveal that the most effective approach involves learning and fine-tuning pre-trained architectures on detailed studies, achieving a classification accuracy of up to 94.5% © 2024 IEEE.

关键词： Convolutional neural networks

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Reduced-RSS: Reduced Residual Search Space for Nash Bargaining Solutions

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8215-8225页

作者： Cha, Chaeyeon Park, Hyunggon Ewha Womans University Graduate Program in Smart Factory Department of Electronic and Electrical Engineering Seoul03760 Korea Republic of

A fair and efficient resource allocation is crucial to maximize the efficiency of vehicular networks with time-varying resources among dynamically changing vehicles. The Nash Bargaining Solution (NBS) from the cooperative game theory has been one of the fair and optimal resource management solutions for multiple users. However, the computational complexity required to find the NBS for general utility functions exponentially increases either as the number of users increases or as the resources change over time. This is because the size of bargaining sets where the NBS should be found changes. In this paper, we propose an algorithm to reduce the size of the search spaces by considering the adjacent bargaining sets correlated by resource changes. We use the axiom of independence of linear transformations in NBS for the linear approximation of NBS in the adjacent bargaining sets based on its linear transform, leading to reduced residual search space. Moreover, we prove that the NBS is always included in the reduced residual search space based on the axiom of independence of irrelevant alternatives in NBS. Through simulations and experiments on synthetic and real traffic data, we demonstrate that the complexity of existing algorithms for NBS is lowered with the reduced residual search spaces. © 1967-2012 IEEE.

关键词： NIST Resource management Heuristic algorithms Vectors Dynamical systems Computational complexity Accuracy Vehicle dynamics Dynamic scheduling System performance

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Heuristic-Based Recommendation System for Dealing with Abnormal Situations in Industrial Applications

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ASCE-ASME Journal of Risk and Uncertainty in engineering Systems, Part B: Mechanical engineering 2025年第2期11卷 021104页

作者： Da Silva, Márcio J. Pereira, Carlos E. PPGEE-Graduate Program on Electrical Engineering Federal University of Rio Grande Do sul RS Porto Alegre90035190 Brazil

The effective management of process deviations and abnormal events depends on operational actions in providing the appropriate responses to each situation. Applications with requirements focused on the provision of resources tend to be handled by a human-machine interface (HMI) along with supervisory control and data acquisition (SCADA). Process reliability is achieved if the operation ensures that actions will be performed according to the required response and priority levels. This paper presents a novel architecture entitled the heuristic-based recommendation system (HB-RS). The main goal is to provide resources capable of streamlining the process of actively handling abnormal situations. For recommendation purposes, the use of probabilistic networks is proposed, which are well suited to represent uncertainty elements present in engineering applications. To create the inference mechanism for these systems, a multi-entity Bayesian network (MEBN) is proposed, highlighting the importance of semantic characterization via knowledge-based, probabilistic graphical model formalism, which is closely linked to the modeling paradigm in which we can predict situations. The developed capabilities have been applied to a real case study in the operation of a metro train system, and the results obtained indicate the value of the proposed method. Copyright © 2025 by ASME.

关键词： Subway cars

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Real Time Chest X-Ray Interpretation Applying Vision Transformer for Tuberculosis Detection

Real Time Chest X-Ray Interpretation Applying Vision Transfo...

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2024 International Conference on Computer engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Irhamsyah, Muhammad Roslidar Yunidar Al Lail Qadrillah, M. Nasaruddin Arnia, Fitri Munadi, Khairul Universitas Syiah Kuala Post Graduate Program in Engineering Banda Aceh2311 Indonesia Faculty of Engineering Department of Electrical and Computer Engineering 2311 Indonesia

ISBN: (纸本)9798350368802

Tuberculosis (TB) is an infectious disease that can attack the lungs and other organs. In the diagnosis of TB, the interpretation of X-ray radiological images requires special skills from medical specialists. However, the lack of experience of medical personnel and focus on X-ray examinations can be a challenge for radiologists because it has the potential to cause diagnostic errors in image interpretation. Therefore, we proposed a web-based application of real-time chest X-ray interpreter by integrating the deep learning model of Vision Transformer (ViT) to interpret chest X-ray images. The inference model was trained and tested on 652 normal and 652 tuberculosis X-ray images. The data preprocessing of Contrast Adaptive Histogram Equalization (CLAHE) was implemented to increase chest X-ray image contrast as well as inference model performance. The proposed real time system can inteprete the tested chest x-ray images with an accuracy of 95% and with simulation duration time of 4.7 seconds. © 2024 IEEE.

关键词： Diagnosis

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Optimal Planning of Integrating Distributed Generations in Unbalanced Distribution Network by Using Particle Swarm Optimization 11

Optimal Planning of Integrating Distributed Generations in U...

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11th International Conference on electrical and Electronics engineering, ICEEE 2024

作者： Chumwong, Kitipong Premrudeepreechacharn, Suttichai Chiang Mai University Graduate Program in Electrical Engineering Faculty of Engineering Dept. of Electrical Engineering Chiang Mai Thailand Provincial Electricity Authority Bangkok Thailand Chiang Mai University Faculty of Engineering Dept. of Electrical Engineering Chiang Mai Thailand

ISBN: (纸本)9798350362541

In recent years, Distributed Generation (DG) have been a high penetration rate in the distribution network. Planning the active power of electricity from DG can save energy from grid side and reduce power losses in the unbalanced distribution system by considering the capacity to generate electricity. This research was aimed to appropriately generate the active power of DG for managing the energy on grid side and enable distributed system operators (DSO) can forecast production capabilities, maintain the grid balancing, and ensuring the stability of the distribution system. Particle Swarm Optimization (PSO) algorithm was implemented in MATLAB for optimal active power for each DG using Peer-to-Peer (P2P) communication with DIgSILENT for power flow analysis by shared data via comma-separated values file. Additionally, specifying equality and inequality constraint were applied. The results indicated that the active power of DG who is injected to the grid effect to the total power loss, voltage deviation, and power flow direction. In conclusion, the DSO can use them as the considerate guideline for issuing commands to adjust the increase or decrease in the production capacity of DG within reliability and security of the distributed system. © 2024 IEEE.

关键词： Power distribution planning

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Comparison of 2L and 3L-NPC Power Converter-Based a Level-2 Isolated Off-Board Charger

Comparison of 2L and 3L-NPC Power Converter-Based a Level-2 ...

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2023 IEEE International Conference on electrical, Computer and Energy Technologies, ICECET 2023

作者： Thanakam, Thidarat Kumsuwan, Yuttana Graduate Program in Electrical Engineering Chiang Mai University Faculty of Engineering Department of Electrical Engineering Chiang Mai Thailand Chiang Mai University Faculty of Engineering Department of Electrical Engineering Chiang Mai Thailand

ISBN: (纸本)9798350327816

This paper presents an off-board charger system for any electric vehicle based on a single-stage power converter operation that performs as a three-phase pulse width modulation rectifier. To enhance the safety issue by itself, a step-down transformer with galvanic isolation is added. Additionally, the off-board charger system allows bidirectional power flow in both grid-to-vehicle (G2V) and vehicle-to-grid operations. To analyze this system, only G2V operation is shown by comparing a two-level power converter charger with a three-level neutral point clamped power converter charger. In light of its controller, the off-board charger is designed to charge a battery in constant current and constant voltage mode in compliance with Level 2 of charging power. Based on this controller, it can support grid power quality under a unity power factor. Simulation-based verification is conducted on a maximum power rating of 22 kW to claim the performance of steady-state operation and dynamic operation. © 2023 IEEE.

关键词： Electric vehicles galvanic isolation off-board charger three-level neutral point clamped power converter two-level power converter

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