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2022 International Conference on Power, Energy and Innovations, ICPEI 2022

作者： Jamtsho, Karma Suwanasri, Thanapong Panmala, Nattapon Suwanasri, Cattareeya EPE Program The Sirindhorn International Thai-German Graduate School of Engineering KMUTNB 1518 Pracharat 1 Rd.Bangsue Bangkok Thailand Department of Teacher Training in Electrical Engineering Faculty of Technical Education KMUTNB 1518 Pracharat 1 Rd. Bangsue Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering KMUTNB 1518 Pracharat 1 Rd.Bangsue Bangkok Thailand

ISBN: (数字)9781665460194

ISBN: (纸本)9781665460194

This paper presents the Partial Discharge (PD) investigation of defective medium voltage (3.6/6(7.2) kV) cable terminations and the impact of using different voltage sources namely AC 50 Hz and Very Low Frequency (VLF) voltage source of 0.1 Hz as supply voltage. The PD is detected by High Frequency Current Transformer (HFCT). Electric field stress investigation is carried out by using Finite Element Method Magnetic (FEMM) simulation tool. The defective cable terminations used are no-stress control, needle tip on insulation screen and sandpaper scrubbed termination. PD investigation is carried out by applying 50 Hz and 0.1 Hz voltage sources and Partial Discharge Inception Voltage (PDIV), Partial Discharge Extinction Voltage (PDEV), PD magnitude and Pulse Repetition Rate are recorded. The comparison of PDIV values demonstrates the impact of different voltage sources. © 2022 IEEE.

关键词： Electric connectors

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Adaptive Strategies and Handover Optimization in 5G Networks to Address High Mobility Challenges

Adaptive Strategies and Handover Optimization in 5G Networks...

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International Conference on electrical engineering and Informatics (ICELTICs)

作者： Murhaban Syahrial Teuku Yuliar Arif Fitri Arnia Departement Information Technology Engineering Doctoral Program School of Engineering Universitas Syiah Kuala Universitas Teuku Umar Banda Aceh Aceh Barat Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia

ISBN: (数字)9798350366822

ISBN: (纸本)9798350366839

This study develops an adaptive handover strategy in 5G networks to tackle high mobility challenges and improve service continuity and quality. The research method uses a 5G network emulator with a topology of four base stations (gNBs) to test user equipment (UE) speeds of 20 km/h and 130 km/h. The adaptive algorithm developed utilizes data from the Received Signal Strength Indicator (RSSI) as well as the speed and direction of user mobility to make optimal handover decisions. The results show that at a speed of 130 km/h, the average handover latency reaches 12 ms, compared to 8 ms at 80 km/h. Additionally, the signal quality (RSSI) is lower at higher speeds, negatively affecting service quality. This adaptive algorithm successfully reduces handover latency and improves the stability and efficiency of the overall network. The testing also indicates that this adaptive algorithm can predict handover targets by considering UE speed and direction and uses hysteresis mechanisms to prevent overly frequent handovers. By employing technologies such as Multiple Input Multiple Output (MIMO) and beamforming, this strategy is expected to maintain high service quality even under high mobility conditions.

关键词： Adaptive systems 5G mobile communication Network topology Adaptive algorithms Handover Topology Received signal strength indicator Informatics Optimization Testing

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A 21.6-bit programmable-Gain Triple-Sampling Incremental ΔΣADC With 4 ppm INL for Bridge Transducers

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IEEE Sensors Journal 2025年

作者： Kang, Junho Rhee, Jooyeol Kim, Suhwan Jun, Jaehoon Seoul National University Department of Electrical and Computer Engineering Inter-University Semiconductor Research Center (ISRC) Seoul 08826 South Korea Gachon University Department of Semiconductor Engineering College of Semiconductor Seongnam 13120 South Korea Seoul National University Department of Electrical and Computer Engineering Seoul 08826 South Korea Gwanak Analog Company Ltd Seoul 08826 South Korea Inha University Department of Electrical and Computer Engineering Program in Semiconductor Convergence Incheon 22212 South Korea

This article presents a high-resolution programmable-gain incremental delta-sigma (ΔΣ) analog-to-digital converter (ADC) optimized for high-accuracy bridge transducer measurements. The proposed design incorporates a triple-sampling (TRS) technique and an auto-zeroing (AZ) integrator that are effectively combined to suppress DC offset and 1/f noise, reduce input-referred noise (IRN), and improve effective resolution (ER). Implemented using a switched-capacitor (SC) ΔΣ modulator architecture, the proposed ADC provides accurate gain control without the need for additional power-hungry amplifiers. With the AZ-TRS integrator, a low IRN of 1.03 μV_RMS is achieved. Furthermore, the ADC demonstrates an integral nonlinearity (INL) of ±4 ppm across all gain settings, with a maximum gain of 13. Additionally, it achieves power supply rejection ratio (PSRR) and common-mode rejection ratio (CMRR) values of 117.1 dB and 122.0 dB, respectively. The prototype chip was fabricated using a 0.18-μm CMOS process, and the ΔΣ modulator occupies a compact area of 0.34 mm². The ADC operates with a supply voltage of 3.0 V and a current consumption of 361 μA for the analog circuitry, while the digital filter consumes 36 μA at 1.8 V. © 2001-2012 IEEE.

关键词： Bridge transducer measurement CMOS process delta-sigma (ΔΣ) modulator high-resolution analog-to-digital converter (ADC) industrial sensing applications triple-sampling (TRS)

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Implementation of LEACH Protocol for Cluster Head Selection in D2D Cooperative Communication Systems

Implementation of LEACH Protocol for Cluster Head Selection ...

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2021 International Conference on computer System, Information Technology, and electrical engineering, COSITE 2021

作者： Raziah, Isyatur Yunida, Yunida Muharar, Rusdha Away, Yuwaldi Nasaruddin, Nasaruddin Universitas Syiah Kuala Doctoral Program School of Engineering Banda Aceh Indonesia Universitas Syiah Kuala Department of Electrical and Computer Engineering Banda Aceh Indonesia

ISBN: (纸本)9781665425094

Device-to-device communication (D2D) is a promising technology for future mobile networks that allow users to communicate directly without using the cellular system's infrastructure. However, since the battery power of each mobile device is limited, it is necessary to extend the network life by reducing its energy consumption. Clustering-based protocols could reduce the energy consumption by balancing all nodes into cluster heads (CH). This paper implements the recent hierarchical routing based on the Low Energy Adaptive Hierarchical Clustering (LEACH) protocol for a CH selection to increase device lifetime in cooperative D2D communication systems. First, the CH is selected based on each device's distance and the residual energy. Then, the LEACH protocol is implemented to choose CH in the D2D cooperative communication system to reduce energy consumption and increase the network life and aims to increase the reliability of the cooperative D2D communication system. Moreover, the proposed system model is provided to analyze cluster formation and energy consumption using computer simulation. The simulation results show that implementing the LEACH protocol can increase network life by knowing the number of dead devices and reducing energy consumption in cooperative D2D communication systems. © 2021 IEEE.

关键词： Energy utilization

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Measurement of Muscle Stimulation and Hot Compression for Rehabilitation 3

Measurement of Muscle Stimulation and Hot Compression for Re...

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3rd International Conference on electrical, Communication and computer engineering, ICECCE 2021

作者： Chirakanphaisarn, Neramitr Thongkanluang, Thadsanee Thammasat University Faculty of Engineering Department of Electrical and Computer Engineering Thailand Suratthani Rajabhat University Program in Materials Technology Manufacturing Faculty of Science and Technology Thailand

ISBN: (纸本)9781665438971

This research is to study the electric muscle stimulation system and hot compress. As well as focusing on building tools for applications in rehabilitation medicine and physical therapy. The neuromuscular system is an important mechanism in human life. In the event that the muscles are stressed or contracted while the subject is recovering, the need for recovery and stimulation tools is an important part of the physical therapy. We designed electrical circuits for automatic control and used an ARDUINO microcontroller to connect analog and digital ports to transmit and receive clinical parameters. The number of voluntary subjects was 20. Each subject remembered to perform 5 stimulation sessions for 10 minutes. Total period that the researcher collects data is approximately 3 months. The trials were based on ethical studies in humans, where trials and researches showed that subjects were 980% satisfied with very few side effects, and subjects had improved muscle development. © 2021 IEEE.

关键词： Muscle

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Twenty years of e-learning in health science: A bibliometric 7

Twenty years of e-learning in health science: A bibliometric

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7th International Conference on computer Science and Computational Intelligence, CSCI 2022

作者： Maulana, Fairuz Iqbal Febriantono, M. Aldiki Raharja, Dwi Risza Budi Khaeruddin Herasmara, Ridho Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health Sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health Sciences field, which Scopus index. © 2022 Elsevier B.V.. All rights reserved.

关键词： Publishing

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FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks

arXiv

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arXiv 2022年

作者： Jang, Jaehee Ha, Heonseok Jung, Dahuin Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Department of Electrical and Computer Engineering Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea Republic of

Personalized federated learning is aimed at allowing numerous clients to train personalized models while participating in collaborative training in a communication-efficient manner without exchanging private data. However, many personalized federated learning algorithms assume that clients have the same neural network architecture, and those for heterogeneous models remain understudied. In this study, we propose a novel personalized federated learning method called federated classifier averaging (FedClassAvg). Deep neural networks for supervised learning tasks consist of feature extractor and classifier layers. FedClassAvg aggregates classifier weights as an agreement on decision boundaries on feature spaces so that clients with not independently and identically distributed (non-iid) data can learn about scarce labels. In addition, local feature representation learning is applied to stabilize the decision boundaries and improve the local feature extraction capabilities for clients. While the existing methods require the collection of auxiliary data or model weights to generate a counterpart, FedClassAvg only requires clients to communicate with a couple of fully connected layers, which is highly communication-efficient. Moreover, FedClassAvg does not require extra optimization problems such as knowledge transfer, which requires intensive computation overhead. We evaluated FedClassAvg through extensive experiments and demonstrated it outperforms the current state-of-the-art algorithms on heterogeneous personalized federated learning tasks. © 2022, CC BY.

关键词： Deep neural networks

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Multiscale Numerical Modeling for Near-Field Microwave Impedance Microscopy

Multiscale Numerical Modeling for Near-Field Microwave Imped...

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CLEO: Science and Innovations, S and I 2022

作者： Tami, Diego Ohlberg, Douglas A.A. Ramirez, Jhonattan C. do Rego, Cássio Gonçalves Medeiros-Ribeiro, Gilberto Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Brazil Microscopy Center Universidade Federal de Minas Gerais Brazil Department of Electronic Engineering Universidade Federal de Minas Gerais Brazil Computer Science Department Universidade Federal de Minas Gerais Brazil

In this work, we analyzed numerically a multiscale nanosystem based on sMIM on TBG. Spontaneous formation of a water-meniscus by the approximation between the tip-sample concentrates the microwave fields, reaching res...

ISBN: (纸本)9781557528209

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Short Wave Infrared Upconversion Imager with Electron Blocking Layer to Screen Electron Injection into Photosensitive Layer

Short Wave Infrared Upconversion Imager with Electron Blocki...

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IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)

作者： Chanho Shin Ning Li Tse Nga Ng Material Science and Engineering Program University of California San Diego La Jolla USA Department of Electrical and Computer Engineering University of California San Diego La Jolla USA

In this work, we demonstrated upconversion imagers integrated with shortwave infrared photodetectors paired with an electron blocking layer. The use of electron blocking layer screened charge injection to prevent recombination in photosensitive layer. The characteristics of each electron blocking layer were analyzed in aspects of noise and detectivity. For the optimized device, the parasitic luminance in the dark was efficiently suppressed, and the photon-to-photon efficiency was increased. The electron blocking layer used in this work is generally applicable for upconversion imagers using different absorption and emitting materials.

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Proactive Opinion-Driven Robot Navigation Around Human Movers

Proactive Opinion-Driven Robot Navigation Around Human Mover...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Charlotte Cathcart María Santos Shinkyu Park Naomi Ehrich Leonard Department of Mechanical and Aerospace Engineering Princeton University Princeton NJ USA Park is with the Electrical and Computer Engineering program King Abdullah University of Science and Technology Thuwal Saudi Arabia

We propose, analyze, and experimentally verify a new proactive approach for robot social navigation driven by the robot's “opinion” for which way and by how much to pass human movers crossing its path. The robot forms an opinion over time according to nonlinear dynamics that depend on the robot's observations of human movers and its level of attention to these social cues. For these dynamics, it is guaranteed that when the robot's attention is greater than a critical value, deadlock in decision making is broken, and the robot rapidly forms a strong opinion, passing each human mover even if the robot has no bias nor evidence for which way to pass. We enable proactive rapid and reliable social navigation by having the robot grow its attention across the critical value when a human mover approaches. With human-robot experiments we demonstrate the flexibility of our approach and validate our analytical results on deadlock-breaking. We also show that a single design parameter can tune the trade-off between efficiency and reliability in human-robot passing. The new approach has the additional advantage that it does not rely on a predictive model of human behavior.

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