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2024 IEEE Sustainable Smart Lighting World Conference and Expo, LS24 2024

作者： Nomura, Hiroki Kihara, Seiji Zukeran, Akinori Sawai, Jun Misu, Takayuki Kanagawa Institute of Technology Graduate School of Engineering Master's Degree Program in Electrical and Electronic Engineering Atsugi Kanagawa243-0292 Japan Kanagawa Institute of Technology Faculty of Engineering Department of Electrical and Electronic Engineering Atsugi Kanagawa243-0292 Japan Kanagawa Institute of Technology Faculty of Health and Medical Sciences Department of Nutrition and Life Science Atsugi Kanagawa243-0292 Japan

ISBN: (纸本)9798331540197

The purpose of this study is to investigate the disinfection effect of Near-UV LED light, which is pulsed using PWM control, on Staphylococcus aureus. To evaluate the disinfection effect of Near-UV LED light, three types of Near-UV LEDs with wavelengths of 395 nm, 385 nm, and 365 nm were installed within a sealed space inside an incubator and energized with a forward current of 1000 mA and a forward voltage of 3.6 V, and the disinfection rate under each type of light was assessed. Additionally, the disinfection effect was evaluated when the same three types of Near-UV LEDs were pulsed with a 50% duty cycle. As a result, 100% disinfection was achieved with 365 nm Near-UV LED direct-current irradiation for 120 seconds, and a 93% disinfection rate was obtained with pulsed irradiation for 150 seconds. © 2024 IEEE.

关键词： Light emitting diodes

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Deep Learning-Based Energy Efficiency Maximization in Massive MIMO-NOMA Networks with Multiple RISs 6

Deep Learning-Based Energy Efficiency Maximization in Massiv...

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6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Perdana, Ridho Hendra Yoga Nguyen, Toan-Van Pramitarini, Yushintia An, Beongku Hongik University Dept. of Software and Communications Engineering in Graduate School Korea Republic of San Diego State University Department of Electrical and Computer Engineering San DiegoCA United States Hongik University Dept. of Software and Communications Engineering Korea Republic of

ISBN: (纸本)9798350344349

In this paper, we study a deep learning (DL)-based energy efficiency maximization (EEM) problem in massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) networks with multiple reconfigurable intelligent surfaces (RISs). These RISs are deployed randomly at the edge of the near radius to assist the base station (BS) in communicating with near and far users. We formulate the problem of jointly optimizing the precoding matrix and phase shift of the RISs to maximize the overall energy efficiency subject to the quality-of-service of each user, phase shift of RISs, and power budget of the BS constraints. To address this challenging non-convex problem with mixed-integer constraints, the original problem is decoupled into phase shift and beamforming sub-problems, then addressed them separately. We introduce the bisection search algorithm to address the challenge of the phase shifts optimization problem. For the beamforming optimization, it is transformed into an equivalent non-convex problem but with a more tractable form. Then, we propose an iterative algorithm based on the inner approximation method for its solution. To support real-Time optimization, we design a deep learning framework to predict optimal solutions of phase shifts at RISs and precoding matrix under different parameter settings. Simulation results show that the proposed DL-based approach can predict the optimal solution with high accuracy in a short time compared to the conventional approach. Additionally, the effect of the maximum power budget at the base station, the number of RISs, and BS's antennas are evaluated thoroughly. © 2024 IEEE.

关键词： Energy efficiency

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A Zero Harmonic Distortion Grid-Forming Converter for Islanded Microgrids

A Zero Harmonic Distortion Grid-Forming Converter for Island...

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2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

作者： Ramos, Gabriel V. Parreiras, Thiago M. Brandao, Dener A. De L. Silva, Sidelmo M. Filho, Braz De J. C. Universidade Federal de Minas Gerais Graduate Program in Electrical Engineering MG Belo Horizonte31270-901 Brazil Centro Federal de Educacão Tecnológica de Minas Gerais Department of Electrical Engineering Belo Horizonte Brazil Universidade Federal de Minas Gerais Department of Electrical Engineering Belo Horizonte Brazil

ISBN: (纸本)9798350320169

The world has been experiencing a fast change in the production and use of electrical energy. The electric power system is fast changing from the conventional centralized generation to a more distributed generation (DG) with renewable energy sources installed near the consumers. The evolution of DG paves the way for the concept of grid-forming converters improving voltage and frequency stability in microgrids (MGs) and islanded applications, due to the growth of inverter-based resources. In islanded MG, power quality is a concern due to the presence of disturbing loads and possible resonance issues encountered with multiple electronically interfaced distributed energy resources (DERs) and loads. The present work proposes the application of the Zero Harmonic Distortion Converter (ZHD) as a grid-forming converter due to its inherently sinusoidal voltage source characteristic without the need of capacitive filtering elements that negatively impact in costs, efficiency, size and can be a source of resonances issues. These features are achieved by the proper combination of harmonic cancellation in a three-winding transformer and harmonic elimination using the Selective Harmonic Elimination Pulse Width Modulation (SHE PWM). Simulation results show the ZHD converter setting voltage and frequency to an islanded microgrid, delivering sinusoidal voltage waveforms even in the presence of nonlinear loads. The converter is able to maintain the voltage distortion below the IEEE 519 limits by respecting the current harmonic limits imposed by the same standard. © 2023 IEEE.

关键词： Harmonic distortion

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IoT-based tire pressure monitoring system for air and temperature pressure using MPX5500D and LM35 sensor 8

IoT-based tire pressure monitoring system for air and temper...

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8th IEEE International Conference on Computing, engineering and Design, ICCED 2022

作者： Pangestu, Agung Sodikin, Iing Yusro, Muhammad Sapundani, Rum Al Hakim, Rosyid Ridlo Wilyanti, Sinka Jakarta Global University Faculty of Engineering and Computer Science Electrical Engineering Department Depok Indonesia State University of Jakarta Faculty of Engineering Department of Electronic Engineering Jakarta Indonesia University of Muhammadiyah Purwokerto Electromedical Engineering Technology Faculty of Health Science Purwokerto Indonesia Jakarta Global University Graduate Program in Electrical Engineering Faculty of Engineering and Computer Science Depok Indonesia

ISBN: (纸本)9781665453899

Research has been carried out to monitor vehicle tires before they are used and can reduce damage, including overcoming vehicle fuel waste because air pressure is continuously monitored. This research aims to utilize the MPX5500DP sensor as an air pressure device, the LM35 sensor as a temperature reader, and a buzzer based on IoT to build a tire pressure monitoring system (TPMS). The MPX5500DP and LM35 sensor inputs to the Arduino Uno microcontroller are distributed by the NodeMCU, fitted with a Wi-Fi module. The Blynk application sends and displays the data on a smartphone using the IoT-based. Based on this research, data on the percentage of errors in monitoring air pressure and tire temperature on vehicles were obtained by comparing the data to the pressure gauge and thermometer: 1-the results of the average reading of the sensor error value. MPX5500DP air pressure against pressure gauge is 5.3%. 2-the average reading of the LM35 sensor error value on the temperature thermometer is 6.8%. With this research, the air pressure and temperature in the tires can be monitored in real-Time via a smartphone using the IoT-based. © 2022 IEEE.

关键词： Thermometers

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Enhancing the Performance of E-Mode AlGaN/GaN HEMTs With Recessed Gates Through Low-Damage Neutral Beam Etching and Post-Metallization Annealing

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 150-155页

作者： Chen, Yi-Ho Ohori, Daisuke Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan Tohoku University Institute of Fluid Science Sendai980-8577 Japan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Pioneer Semiconductor Innovation Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Hsinchu300093 Taiwan

This study investigated the electrical properties of AlGaN/GaN high-electron-mobility transistors (HEMTs) with varied recess depths under the gate electrode. We demonstrated a recess depth of approximately 6 nm, which was achieved through neutral beam etching (NBE) technique with a low etch rate of 1.8 nm/min, resulting in device enhancement-mode (E-mode) behavior with threshold voltage (Vth) of 0.49 V. The effects of post-metallization annealing (PMA) on the device performance were also examined. The results revealed that PMA treatment improves the DC characteristics of the devices, including maximum drain current (IDMAX), transconductance (gm), subthreshold swing (SS), on-off ratio, and off-state leakage current, with maximum enhancement percentage of 18.3% for IDMAX, 3758% for on-off ratio, and 54.3% for SS. Moreover, this study compared the recess depths of metal-insulator-semiconductor high-electron-mobility transistors (MIS-HEMTs) with the SiN dielectric layer. The results showed that MIS-HEMTs exhibit more negative Vth values, which can be attributed to the controlled surface states achieved through passivation. © 2020 IEEE.

关键词： Etching

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Hyperautomation for Air Quality Evaluations: A Perspective of Evidential Three-way Decision-making

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Cognitive Computation 2024年第5期16卷 2437-2453页

作者： Ding, Juanjuan Zhang, Chao Li, Deyu Sangaiah, Arun Kumar School of Computer and Information Technology Shanxi University Shanxi Taiyuan030006 China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Shanxi Taiyuan030006 China International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology Douliou64002 Taiwan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

Hyperautomation acts as a real digital transformation with the support of several cutting-edge cognitive computation methods that include robotic process automation, natural language processing, artificial intelligence, and other emerging ones, which is conducive to processing complex industrial processes via extending the range of various data-driven cognitive decision-making algorithms. The study of air quality evaluations (AQE) plays a significant role in ensuring healthy atmospheric environments. In view of the objective existence of uncertainties, AQE can be modeled and addressed by a typical data-driven automated decision-making problem, and hyperautomation can provide a reasonable solution via associating with a variety of techniques. This article explores hyperautomation for AQE via evidential three-way large-scale group decision-making (LSGDM) in an intuitionistic fuzzy (IF) setting. First, the notion of intuitionistic fuzzy sets (IFSs) is incorporated into the paradigm of multi-granularity (MG) three-way decisions (TWD), and the model of adjustable MG IF probabilistic rough sets (PRSs) is developed. Second, an IF clustering analysis with the improved technique for order preference by similarity to ideal solution (TOPSIS) method is conducted to affirm representative members within a decision group. Third, a novel IF LSGDM method is built via adjustable MG IF PRSs and the evidence reasoning (ER) method. Finally, a case study in the setting of AQE is studied by using the presented evidential three-way LSGDM method. Corresponding experimental analyses are carried out for illustrating the efficiency of hyperautomation for AQE. In general, the proposed method improves the performance of information fusion by virtue of adjustable MG IF PRSs, and the TOPSIS method avoids the influence of subjective factors on decision results. Meanwhile, the evaluation information of decision-makers (DMs) is fully analyzed by means of the ER method, which can provide more explaina

关键词： Decision making

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Application of Chaotic Encryption and Decryption in Wireless Transmission From Sensory Toolholders on Machine Tools

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IEEE Sensors Journal 2023年第11期23卷 11453-11468页

作者： Lin, Chi-Yuan Wu, Shu-Cing Kuo, Ping-Huan Huang, Meng-Jun Hong, Song-Wei Yau, Her-Terng National Chin-Yi University of Technology Department of Electronic Engineering Taichung411030 Taiwan National Chin-Yi University of Technology Prospective Technology of Electrical Engineering and Computer Science Program Taichung411030 Taiwan Chiayi62102 Taiwan National Chung Cheng University Department of Mechanical Engineering Chiayi62102 Taiwan

In recent years, several industries have increased their demand for processing precision, automatic detection, and visualization interfaces. Therefore, to keep pace with the fourth industrial revolution, machine tool operators install a large number of sensors on machine tools to obtain more precise physical quantities during processing and use a variety of sensors to obtain measurements in various situations. However, these additional sensors on machine tools result in complicated wire layouts, which exhibit negative effects on processing. Such problems lead to the birth of wireless data transmission, which is expected to become the new standard in the future. At present, there is more and more interactive integration between relevant embedded system and the machine tool, which allows information communication between each other in the wireless domain. However, generally, the majority of machine tool operators focus on optimizing the sensing conditions during processing, but they disregard the importance of information security. In the current era of the Internet of Things (IoT), information security is regarded as a crucial factor. For the wireless communication between the IoT equipment for each machine in the machining field, the transmitted data are almost exposed within public space directly due to the loss in constraint and protection of physical wiring. Therefore, such a process can easily be intercepted by other devices that capture information on relevant status of the machine or command messages received by the controller, where intentional individual may possibly control the operating mechanism and progress of entire plant. This leads to theft of relevant secrets in manufacturing technology for the subject company, or intentional shutdown, machine damage, and vicious blackmailing attacks. Therefore, introducing the mechanism of safety protection during wireless signal transmission is an inevitable technology to maintain the company interests and also the

关键词： Synchronization

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First Demonstration of HZO-LNOI Integrated Ferroelectric Electro-Optic Modulator and Memory to Enable Reconfigurable Photonic Systems

First Demonstration of HZO-LNOI Integrated Ferroelectric Ele...

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2023 International Electron Devices Meeting, IEDM 2023

作者： Xu, Zefeng Chen, Chun-Kuei Lin, Hong-Lin Gao, Yuan Ke, Wei Xu, Baochang Dmitriev, Pavel Arbiz, Carlan Zamburg, Evgeny Touzard, Steven Cai, Xinlun Lee, James Venkatesan, Suresh Danner, Aaron Thean, Aaron Voon-Yew Department of Electrical and Computer Engineering Singapore Nus Graduate School Integrative Sciences and Engineering Program Singapore 117583 Singapore School of Electronics and Information Technology 117583 Singapore Centre for Quantum Technologies Nus Singapore Poet Technologies Canada Sun Yat-Sen University 510275 China

ISBN: (纸本)9798350327670

We have successfully demonstrated, for the first time, an innovative back-end-of-line (BEOL) compatible electro-optic modulator and memory (EOMM) based on Lithium Niobate on Insulator (LNOI) micro-ring resonator (MRR) integrated with Ferroelectric Hafnium Zirconate Hf0.5Zr0.5O (HZO) non-volatile analog memory. High non-volatile memory and modulation performances are both achieved in a single compact device, exhibiting high extinction ratio of 13.3 dB, excellent efficiency of 66pm/V, stable nine-state switching, record-high endurance exceeding 109 cycles. This is accomplished by utilizing Pockels effect in LNOI, induced by electric-field effect from remnant HZO ferroelectric polarization. We studied the system implementation of reconfigurable chiplet-interposer photonic interconnect, enabled by the EOMM and EOMM with hybrid thermal-optical modulation. Our model shows a potential 70% energy efficiency improvement over conventional electrical interposer interconnect. We have also tested the integration of the EOMM with POET technologies' 400G Tx/Rx optical interposer chip and studied a limited scale demonstration of the EOMM device. © 2023 IEEE.

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Graph Coordinates and Conventional Neural Networks - An Alternative for Graph Neural Networks

Graph Coordinates and Conventional Neural Networks - An Alte...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Qin, Zheyi Paffenroth, Randy Jayasumana, Anura P. Colorado State University Electrical and Computer Engineering Fort Collins United States Worcester Polytechnic Institute Department of Data Science Program WorcesterMA United States

ISBN: (纸本)9798350324457

Graph-based data present unique challenges and opportunities for machine learning. Graph Neural Networks (GNNs), and especially those algorithms that capture graph topology through message passing for neighborhood aggregation, have been a leading solution. However, these networks often require substantial computational resources and may not optimally leverage the information contained in the graph's topology, particularly for large-scale or complex *** propose Topology Coordinate Neural Network (TCNN) and Directional Virtual Coordinate Neural Network (DVCNN) as novel and efficient alternatives to message passing GNNs, that directly leverage the graph's topology, sidestepping the computational challenges presented by competing algorithms. Our proposed methods can be viewed as a reprise of classic techniques for graph embedding for neural network feature engineering, but they are novel in that our embedding techniques leverage ideas in Graph Coordinates (GC) that are lacking in current *** results, benchmarked against the Open Graph Benchmark Leaderboard, demonstrate that TCNN and DVCNN achieve competitive or superior performance to message passing GNNs. For similar levels of accuracy and ROC-AUC, TCNN and DVCNN need far fewer trainable parameters than contenders of the OGBN Leaderboard. The proposed TCNN architecture requires fewer parameters than any neural network method currently listed in the OGBN Leaderboard for both OGBN-Proteins and OGBN-Products datasets. Conversely, our methods achieve higher performance for a similar number of trainable parameters. These results hold across diverse datasets and edge features, underscoring the robustness and generalizability of our methods. By providing an efficient and effective alternative to message passing GNNs, our work expands the toolbox of techniques for graph-based machine learning. A significantly lower number of tunable parameters for a given evaluation metric makes TCNN and DVCNN especiall

关键词： graph analytics graph coordinate graph embedding green AI network embedding

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Experimental validation of multiferroic antennas in GHz frequency range

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Applied Physics Letters 2023年第16期123卷 1-6页

作者： Xu, Rui-Fu Ippet-Letembet, Louis-Charles Tiwari, Sidhant Yao, Zhi [Jackie] Huang, Shih-Ming Candler, Rob N. Chen, Shih-Yuan Graduate Institute of Communication Engineering National Taiwan University Taipei10617 Taiwan Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States California NanoSystems Institute Los AngelesCA90095 United States Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan

Various mechanical antennas have emerged to overcome the inherently narrower bandwidth and degraded efficiency in electrically small antennas. Among them, multiferroic antennas are expected to realize high-frequency applications and maintain their performance, even with significantly reduced sizes. However, experimental proof of such radiation from multiferroic or magnetoelectric coupling in the GHz range deserves further examination. This paper designs and fabricates a series of multiferroic antenna samples with mechanical resonances at around 3.5 and 6 GHz, and their radiation transmissions are tested at these resonances. Nickel, a magnetoelastic material, consistently exhibits magnetically induced radiation at both resonances. However, magnetic material consisting of Permalloy (Ni78Fe22), known for its much weaker magnetoelastic effects, still shows similar transmission behaviors at 3.67 GHz and enhanced power absorption at 6.42 GHz. Our results indicate that the dynamic response of magnetoelastic materials in the GHz band should differ from their response at the MHz and below bands. This evidence calls for further investigations of the source of magnetoelectric radiation. © 2023 Author(s).

关键词： Iron alloys

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