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Numerical electric field analysis of capacitance and potential in space for estimation of permittivity distribution

IEEJ Transactions on Fundamentals and Materials 2018年第4期138卷 119-126页

作者： Yamanobe, Hiroshi Ohchi, Masashi Master's Program in Electrical Electronics and Computer Engineering Graduate School of Engineering Chiba Institute of Technology 2-17-1 Tsudanuma Narashino275-0016 Japan Department of Electrical and Electronic Engineering Faculty of Engineering Chiba Institute of Technology 2-17-1 Tsudanuma Narashino275-0016 Japan

We have been studying on measuring capacitance and potential using long distance electrode for estimating a permittivity distribution. The estimating method of permittivity distribution was proposed using Finite Element Method (FEM) and Genetic Algorithm (GA). However, the measurement accuracy was not reviewed. In this paper, we carried out numerical analysis using FEM in case of change of diameter, position and permittivity of a rod of dielectric and discussed the measurement accuracy of capacitance and potential. © 2018 The Institute of Electrical Engineers of Japan.

关键词： Finite element method

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Tube-based MPC with Nonlinear Control for Load Transportation using a UAV

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IFAC-PapersOnLine 2018年第25期51卷 459-465页

作者： Santos, Marcelo A. Ferramosca, Antonio Raffo, Guilherme V. Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo HorizonteMG Brazil CONICET UTN Facultad Regional Reconquista SantaFe 3560 Argentina Department of Electronics Engineering Federal University of Minas Gerais Belo HorizonteMG Brazil

This paper presents a two-stage cascade control framework to solve hierarchically the trajectory tracking problem of a Tilt-rotor Unmanned Aerial Vehicle (UAV) carrying a suspended load. Initially, a nonlinear dynamic model is presented, which is after decoupled into two subsystems. The outer control system is designed by means of a robust tube-based Model Predictive Control (MPC) strategy, which is used to control the UAV's planar motion and stabilize the suspended load. For the inner control system, the input-output feedback linearization (IOFL) technique combined with the dynamic extension approach and a discrete mixed H2/H∞ controller is considered to control the UAV's altitude and attitude. Simulations results are carried out to corroborate the proposed control strategy. © 2018

关键词： Aircraft control Aircraft detection Altitude control Antennas Cascade control systems Feedback linearization Model predictive control Predictive control systems Unmanned aerial vehicles (UAV) Cascade control Control strategies Dynamic extension Input output feedback linearization Non linear control Planar motion Suspended loads Trajectory tracking problems

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Characteristics of a High-impedance Folded Dipole Antenna in the Millimeter Wave Band

Characteristics of a High-impedance Folded Dipole Antenna in...

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2022 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2022

作者： Yamashiro, Koki Takashima, Yoshiki Noguchi, Keisuke Kanazawa Institute of Technology Graduate Program in Electrical Engineering and Electronics Ishikawa Nonoichi Japan Toko Electrical Constriction Chiyoda Tokyo Japan Kanazawa Institute of Technology Electrical and Electronics Engineering Ishikawa Nonoichi Japan

ISBN: (数字)9781665432382

ISBN: (纸本)9781665432382

Rectenna with high rectification efficiency is demanded for wireless power transfer systems. In order to improve rectification efficiency at mm-wave band, we study on high impedance antennas. This paper reports the characteristics of a folded dipole antenna consisting of open-Terminated two strips on an Alumina substrate. We designed the antenna with over 1000Ω at 28 GHz using EM simulator. As results, we obtained input resistance of 1463.7Ω with radiation efficiency of 86.7%. © 2022 IEEE.

关键词： Energy transfer

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Long-lasting superhydrophiilic PDMS surface by atmospheric-pressure plasma polymerization

Long-lasting superhydrophiilic PDMS surface by atmospheric-p...

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15th International Conference on Miniaturized Systems for Chemistry and Life Sciences 2011, MicroTAS 2011

作者： Lee, Donghee Hyun, Ji-Chul Hong, Sung A. Yang, Sung Graduate-program of Medical System Engineering Korea Republic of School of Mechatronics Korea Republic of Department of Nanobio Materials and Electronics GIST Korea Republic of

ISBN: (纸本)9781618395955

In this study, a method to modify hydrophobic PDMS (Polydimethylsiloxane) surface to be long-lasting hydrophilic surface by applying atmospheric-pressure plasma polymerization is proposed. To enhance the sustainability of the modified hydrophilic PDMS, two kinds of plasma polymerized layers were implemented on the surface of the PDMS block sequentially. The highly cross-linked hydrocarbon layer deposited by atmospheric-pressure plasma polymerization from CH 4 plays a role as a physical barrier layer (PBL) to prevent hydrophobic recovery of the hydrophilic layer deposited from TEOS (Tetraethylorthosilicate) and O2. The modified PDMS surface shows long-lasting superhydrophilic wetting property over 28 days of aging time. Copyright © (2011) by the Chemical and Biological Microsystems Society.

关键词： Surface treatment

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ZETA: a library for Zonotope-based EsTimation and fAult diagnosis of discrete-time systems

arXiv

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arXiv 2025年

作者： Rego, Brenner S. Scott, Joseph K. Raimondo, Davide M. Terra, Marco H. Raffo, Guilherme V. Department of Electrical and Computer Engineering University of São Paulo SP São Carlos13566-590 Brazil Department of Chemical and Biomolecular Engineering Georgia Institute of Technology 311 Ferst Dr. AtlantaGA30318 United States Department of Engineering and Architecture University of Trieste Trieste34127 Italy Department of Electronics Engineering Graduate Program in Electrical Engineering Federal University of Minas Gerais MG Belo Horizonte31270-901 Brazil

This paper introduces ZETA, a new MATLAB library for Zonotope-based EsTimation and fAult diagnosis of discrete-time systems. It features user-friendly implementations of set representations based on zonotopes, namely zonotopes, constrained zonotopes, and line zonotopes, in addition to a basic implementation of interval arithmetic. This library has capabilities starting from the basic set operations with these sets, including propagations through nonlinear functions using various approximation methods. The features of ZETA allow for reachability analysis and state estimation of discrete-time linear, nonlinear, and descriptor systems, in addition to active fault diagnosis of linear systems. Efficient order reduction methods are also implemented for the respective set representations. Some examples are presented in order to illustrate the functionalities of the new library. © 2025, CC BY.

关键词： Digital arithmetic

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Auxiliary Classifier based Residual RNN for Image Captioning 30

Auxiliary Classifier based Residual RNN for Image Captioning

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30th European Signal Processing Conference, EUSIPCO 2022

作者： Çayli, Özkan Kiliç, Volkan Onan, Aytug Wang, Wenwu Electrical and Electronics Engineering Graduate Program Izmir Katip Çelebi University Turkey Department of Computer Engineering Izmir Katip Çelebi University Turkey University of Surrey United Kingdom

ISBN: (纸本)9789082797091

Image captioning aims to generate a description of visual contents with natural language automatically. This is useful in several potential applications, such as image understanding and virtual assistants. With recent advances in deep neural networks, natural and semantic text generation has been improved in image captioning. However, maintaining the gradient flow between neurons in consecutive layers becomes challenging as the network gets deeper. In this paper, we propose to integrate an auxiliary classifier in the residual recurrent neural network, which enables the gradient flow to reach the bottom layers for enhanced caption generation. Experiments on the MSCOCO and VizWiz datasets demonstrate the advantage of our proposed approach over the state-of-the-art approaches in several performance metrics. © 2022 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Recurrent neural networks

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Automated Image Captioning with Multi-layer Gated Recurrent Unit 30

Automated Image Captioning with Multi-layer Gated Recurrent ...

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30th European Signal Processing Conference, EUSIPCO 2022

作者： Moral, Özge Taylan Kiliç, Volkan Onan, Aytug Wang, Wenwu Electrical and Electronics Engineering Graduate Program Izmir Katip Celebi University Turkey Department of Computer Engineering Izmir Katip Celebi University Turkey University of Surrey United Kingdom

ISBN: (纸本)9789082797091

Describing the semantic content of an image via natural language, known as image captioning, has recently attracted substantial interest in computer vision and language processing communities. Current image captioning approaches are mainly based on an encoder-decoder framework in which visual information is extracted by an image encoder and captions are generated by a text decoder, using convolution neural networks (CNN) and recurrent neural networks (RNN), respectively. Although this framework is promising for image captioning, it has limitations in utilizing the encoded visual information for generating grammatically and semantically correct captions in the RNN decoder. More specifically, the RNN decoder is ineffective in using the contextual information from the encoded data due to its limited ability in capturing long-term complex dependencies. Inspired by the advantage of gated recurrent unit (GRU), in this paper, we propose an extension of conventional RNN by introducing a multi-layer GRU that modulates the most relevant information inside the unit to enhance the semantic coherence of captions. Experimental results on the MSCOCO dataset show the superiority of our proposed approach over the state-of-the-art approaches in several performance metrics. © 2022 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Recurrent neural networks

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Transfer learning approach to modeling multichannel gate-all-around nanosheet field-effect transistors under work function fluctuations

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engineering Applications of Artificial Intelligence 2025年 148卷

作者： Dash, Sagarika Li, Yiming Parallel and Scientific Computing Laboratory National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Communications Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Biomedical Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Artificial Intelligence Innovation National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Department of Microelectronics National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan

Deep learning (DL) has significantly advanced various industries, including semiconductors, by providing sophisticated methods for analyzing emerging device data. Transfer learning (TL), a prominent DL topology, leverages knowledge from a pre-trained model to improve the performance of a specific target task. This study aims to apply TL to predict the impact of work function fluctuation (WKF) on the variability of threshold voltage (σVTH) in gate-all-around silicon nanosheet field-effect transistors (GAA Si NS FETs). We used TL to transfer knowledge from models trained on 1-channel (1ch) GAA Si NS FETs to more complex 4-channel (4ch) counterparts. The prediction accuracy is evaluated by using the mean square error(MSE), root mean square error (RMSE), and the mean absolute error(MAE) metrics. Our TL approach achieved an error rate of less than 1%, demonstrating high accuracy in predicting WKF effects on σ VTH of 4ch GAA Si NS FETs using only 500 samples. This study presents a pioneering application of TL using a one-dimensional (1D) convolutional neural network (CNN) long short-term memory (LSTM) topology in semiconductor device technology. The results effectively address the challenge of predicting σ VTH variations in advanced GAA Si NS FETs because of WKF, which eliminates the need for extensive semiconductor device simulations. © 2025 Elsevier Ltd

关键词： Convolutional neural networks

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Quantitative Analysis of Ankle Spasticity Through Electromyography Signal

Quantitative Analysis of Ankle Spasticity Through Electromyo...

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2024 Medical Technologies Congress, TIPTEKNO 2024

作者： Gurluk, Ayse Bilal, Hafiz Muhammad Hocaoglu, Elif Living Robotics Laboratory Graduate School of Health Sciences Physiotherapy and Rehabilitation Program Istanbul Medipol University Istanbul Turkey Living Robotics Laboratory Graduate School of Engineering and Natural Sciences Electrical-Electronics Engineering and Cyber-Systems Program Istanbul Medipol University Istanbul Turkey Living Robotics Laboratory Department of Electrical and Electronics Engineering Istanbul Medipol University Istanbul Turkey

ISBN: (纸本)9798331529819

This study presents a more accurate evaluation method for assessing ankle spasticity compared to conventional goniometric techniques by utilizing measurements obtained from Inertial Measurement Units (IMU) and surface electromyography (sEMG) devices. Integrating IMU and EMG sensors provides substantial benefits for accurately determining the range of motion (ROM) associated with spasticity during targeted movements. In this study, the proposed method provides precise measurement and an objective evaluation of onset time detection of antagonistic muscle co-contraction, and accordingly the ROM of the actuated joint. Moreover, the implementation of cost-effective wearable sensors enables the monitoring of muscle spasticity in clinical environments and can be particularly valuable in regions with limited access to experienced therapists, providing a more efficient approach to tracking spasticity levels. © 2024 IEEE.

关键词： Electromyography

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Utilization Extract, Transform, Load for Developing Data Warehouse in Education Using Pentaho Data Integration 4

Utilization Extract, Transform, Load for Developing Data War...

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4th International Conference on Electrical, electronics, Informatics, and Vocational Education, ICE-ELINVO 2021

作者： Barahama, A.D. Wardani, R. Department of Electronics and Informatics Engineering Education Post-Graduate Program Universitas Negeri Yogyakarta Jalan Colombo 01 Daerah Istimewa Yogyakarta 55281 Indonesia

The utilization of data warehouses in various fields is an absolute necessity. A data warehouse is a database that contains large amounts of data that aims to help organizations, fields, and institutions specifically for decision making. Data warehouses can produce important information in the future. Loading data from various sources and processed through an ETL (Extract, Transform, Load) process that displays data consistently is the basis for creating a data warehouse architecture. The development of a data warehouse in education will provide significant benefits for the progress of education. Integration of data and processing results stored in the data warehouse can be the basis for evaluating better planning. Development of data warehouse adopt the multidimensional modelling method which consists of four stages: select the business process, declare the grain, select dimensions, and identify facts. This stage produces a data warehouse architecture and influences and contributes to the advanced information technology in education. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Data warehouses

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