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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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DCMSim: Didactic cache memory simulator 33

DCMSim: Didactic cache memory simulator

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33rd Annual Frontiers in Education, FIE 2003

作者： Cordeiro, Eduardo Santos Abdanur Stefani, Italo Giovani Do Amaral Pales Soares, Tays Cristina Da Silva Martins, Carlos Augusto Paiva Pontifical Catholic University of Minas Gerais Graduate Program in Computer Science 500 Av. Dom Cabral Coração Eucaristico Belo HarizonteMinas Gerais Brazil Pontifical Catholic University of Minas Gerais Graduate Program in Computer Science Graduate Program in Electrical Engineering 500 Av. Dom Cabral Coração Eucaristico Belo HarizonteMinas Gerais Brazil

ISBN: (纸本)0780379616

We present a functional and structural didactic simulator of Cache Memory Systems developed at the Pontifical Catholic University of Minas Gerais, Brazil. The development occurred during the undergraduate computer Architecture discipline, in the computer Science course. Its implementation is one part of a new didactic method, in which developers (students of the computer Architecture discipline) must learn the concepts and theory of the discipline topics to correctly apply them in the simulator. In our simulator, DCMSim, there are features to allow students to construct and verify knowledge, testing and comparing several different configurations and memory access traces. © 2003 IEEE.

关键词： Cache memory

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Using immersive Virtual environments for realistic life-Size fire safety training for children

Using immersive Virtual environments for realistic life-Size...

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3rd IASTED International Conference on Human-computer Interaction, HCI 2008

作者： Ericson, Emily Smith, Shana Human-Computer Interaction Graduate Program Iowa State University Taipei United States Department of Mechanical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9780889867253

Injuries from residential fires are often overlooked as a dangerous safety concern for children. While lectures and classroom learning techniques can be effective in mitigating this risk, studies have shown that kids retain information better if they are allowed to practice escape techniques. Virtual Reality has been used to simulate situations that are too dangerous to practice in real life. This paper presents a fire safety program that combines classroom activities and small group interaction with fire professionals with a virtual simulation of an at-risk house. Students help firefighters to identify home fire hazards and then practice escaping from a simulated fire in a virtual environment. A CAVE is used to immerse participants in the fire scene.

关键词： Virtual reality

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Classification of musical styles using liquid state machines

Classification of musical styles using liquid state machines

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Ju, Han Xu, Jian-Xin Vandongen, Antonius M.J. Program for Neuroscience and Behavioral Disorders Duke-NUS Graduate Medical School Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (纸本)9781424469178

Music Information Retrieval (MIR) is an interdisciplinary field that facilitates indexing and content-based organization of music databases. Music classification and clustering is one of the major topics in MIR. Music can be defined as 'organized sound'. The highly ordered temporal structure of music suggests it should be amendable to analysis by a novel spiking neural network paradigm: the liquid state machine (LSM). Unlike conventional statistical approaches that require the presence of static input data, the LSM has a unique ability to classify music in real-time, due to its dynamics and fading-memory. This paper investigates the performance of an LSM in classifying musical styles (ragtime vs. classical), as well as its ability to distinguish music from note sequences without temporal structure. The results show that the LSM performs admirably in this task. © 2010 IEEE.

关键词： Music

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Measurement of capacitance and electrical potential of plural points for estimation of permittivity distribution

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IEEJ Transactions on Fundamentals and Materials 2013年第4期133卷 173-179+5页

作者： Okada, Shota Ohchi, Masashi Furukawa, Tatsuya Itoh, Hideaki Fukumoto, Hisao Master's Program in Electrical Graduate School of Engineering Chiba Institute of Technology 2-17-1 Tudanuma Narashino 275-0016 Japan Department of Electrical Electronics and Computer Engineering Faculty of Engineering Chiba Institute of Technology 2-17-1 Tudanuma Narashino 275-0016 Japan Graduate School of Science and Engineering Saga University 1 Honjo-machi Saga 840-8502 Japan

Recently, a method for estimating permittivity distributions was reported. The method combined a numerical technique (Finite Element Method) with Genetic Algorithm (GA). However, methods for estimating the distribution of permittivity have not yet been established. The purpose of this study is to obtain experimental data in order to improve the estimation method. We measured capacitance and electrical potential of plural points when an acrylic rod is placed in various positions within a measurement system. © 2013 The Institute of Electrical Engineers of Japan.

关键词： Capacitance

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Overview of Versatile Video Coding (H.266/VVC) and Its Coding Performance Analysis

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IEIE Transactions on Smart Processing and Computing 2023年第2期12卷 122-154页

作者： Lee, Minhun Song, HyeonJu Park, Jeeyoon Jeon, Byeungwoo Kang, Jungwon Kim, Jae-Gon Lee, Yung-Lyul Kang, Je-Won Sim, Donggyu Department of Computer Engineering Kwangwoon University Seoul Korea Republic of Department of Computer Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Kyunggi-do Korea Republic of Communication and Media Research Laboratory Electronics and Telecommunications Research Institute Deajeon Korea Republic of School of Electronics and Information Engineering Korea Aerospace University Kyunggi-do Korea Republic of Department of Electronic and Electrical Engineering Graduate Program in Smart Factory Ewha Womans University Seoul Korea Republic of

Versatile Video Coding (H.266/VVC) is the newest video coding standard jointly developed by the Joint Video Experts Team (JVET), which is organized by the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). H.266/VVC provides about 40% bitrate reduction compared with High Efficiency Video Coding (H.265/HEVC) for the same visual quality. This paper introduces in detail the core structure of H.266/VVC by highlighting its features within block partitioning structure, intra/inter prediction, transform, quantization, and in-loop filtering, compared to its predecessor (H.265/HEVC). H.266/VVC yields significantly improved the coding performance, but it increased the computational complexity, particularly for the encoder side, which remains a problem to be tackled for successful commercialization in the future. This paper examined the statistical performance of H.266/VVC coding tools from the bitstreams encoded by the VVC test model (VTM12.0) encoder through rate-distortion optimization under the JVET common test conditions. In addition, the complexity and performance analyses are conducted on the block partitioning structure and group of picture structure. It is expected that an optimized H.266/VVC encoder can be designed and developed by minimizing the coding loss based on the analysis data. © 2023 Institute of Electronics and Information Engineers. All rights reserved.

关键词： Image compression

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computer Vision and Fuzzy Logic for Sustainable Indonesian Fisheries 3

Computer Vision and Fuzzy Logic for Sustainable Indonesian F...

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3rd International Conference on Eco engineering Development, ICEED 2019

作者： Liawatimena, Suryadiputra Atmadja, Wiedjaja Abbas, Bahtiar Saleh Trisetyarso, Agung Wibowo, Antoni Barlian, Erland Hardanto, Lilik Tri Saputra, Adi Sakinah, Putri Purwoko, Hery Zulardi, Indra Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor Computer Science Bina Nusantara University Jakarta11480 Indonesia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Management Department BINUS Business School - Doctor of Research in Management Bina Nusantara University Jakarta11480 Indonesia

Tuna fishing in Indonesia is excessive and if left unchecked, some types of tuna will become extinct within 3-10 years. There is an urgent need to help MMAF for producing more accurate fish catches data. This paper proposed a system that utilizes computer vision, fuzzy logic and Global Positioning System (GPS) for supporting a sustainableIndonesian fishery by recognizing and measuring fish length, determine fish age and where is the catch location. The system can help authority to manage sustainable fisheries management in Indonesia. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Machine learning

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Drones computer Vision using Deep Learning to Support Fishing Management in Indonesia 3

Drones Computer Vision using Deep Learning to Support Fishin...

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3rd International Conference on Eco engineering Development, ICEED 2019

作者： Liawatimena, Suryadiputra Atmadja, Wiedjaja Abbas, Bahtiar Saleh Trisetyarso, Agung Wibowo, Antoni Barlian, Erland Hardanto, Lilik Tri Triany, Natassya Afdalena Faisal Sulistiawan, Jaka Yojana, Albert Cahya Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor Computer Science Bina Nusantara University Jakarta11480 Indonesia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Management Department BINUS Business School - Doctor of Research in Management Bina Nusantara University Jakarta11480 Indonesia

It is necessary to study technical factors such as bait used, oceanographic conditions of fishing areas and skipjack tuna trade patterns (Katsuwonus pelamis) as well as other factors in Sulawesi Fisheries. Supporting data to study these technical factors need to be obtained so that it can be improved throughout the year as a skipjack fishing standard with weights taken by the skipjack weights. Therefore, drones and underwater drones with cameras with high-resolution video and images to be fed and processed by computer vision. These drones are operated via Huhate ships which are then used to test efficient technical factors as expected, can be used in determining the size, shape, and colour as well as the analysis of skipjack fish that are in the Fish Aggregating Devices (FADs or Rumpon) in order to manage the management of fisheries managed in Indonesia. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Drones

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Towards bio-inspired place recognition over multiple spatial scales

Towards bio-inspired place recognition over multiple spatial...

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2013 Australasian Conference on Robotics and Automation, ACRA 2013

作者： Chen, Zetao Jacobson, Adam Erdem, Uʇur M. Hasselmo, Michael E. Milford, Michael School of Electrical Engineering and Computer Science Queensland University of Technology Australia Center for Memory and Brain and Graduate Program for Neuroscience Boston University United States

ISBN: (纸本)9780980740448

This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

关键词： Brain mapping

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Smart environmental architecture for node localization in a wireless sensor network

Smart environmental architecture for node localization in a ...

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8th International Conference on Intelligent Environments, IE 2012

作者： Jauregui-Ortiz, Salvador Siller, Mario Ramos, Felix Scalabrin, Edson Electrical Engineering and Computer Science Department Center of Research and Advanced Studies Guadalajara Jalisco Mexico Graduate Program in Computer Science Pontifical Catholic University Parana Brazil Curitiba Parana Brazil

ISBN: (纸本)9780769547411

As far as we know, there is not a Node Localization Algorithm (NLA) that presents the same accuracy for all possible scenarios. We believe that a NLA should be able to interpret the dynamic information of the environment. In this sense, simple NLAs are rather focused and might perform well for specific scenarios and applications. Therefore, information fusion and context awareness seems to be an appropriate approach to address this issue. We propose the Smart Environmental Architecture for Node Localization (SEA-NL), which is composed by two main elements: (i) the Smart Beacon Nodes (SBNs) and (ii) the Logical Position of Nodes (LPN). In (i) the obstruction level indicator is estimated and can improve the estimation of distances among nodes. In (ii) environment information and a one to one relation between a node and an object are used and can also improve location estimation. Via simulation, our architecture was tested indoors and outdoors considering three localization algorithms: the Weighed Centroid Localization (WCL), the Centroid Localization, and the Triangular Centroid Localization. Finally, we present an accuracy comparison among NLAs used in isolated way, and by using the SBNs, the LPN, and the SEA-NL, where our architecture improves WCL up to ~30.88%. © 2012 IEEE.

关键词： Information fusion

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