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International Waveform Diversity and Design Conference, WDD 2012

作者： Jezak, Joseph A. Gadola, Guy Berdanier, Charles Levitan, Steven P. Chiarulli, Donald M. Computer Engineering Graduate Program University of Pittsburgh United States Department of Electrical Engineering Wright State University United States Department of Electrical and Computer Engineering University of Pittsburgh United States Department of Computer Science University of Pittsburgh United States

ISBN: (纸本)9781509005987

In this paper we describe an extension to the MATLAB Phased Array Toolkit that adds a configurable clutter object to model clutter signals returned along a specified signal path. The clutter model is based on the Simkins Unified Clutter Model[1]. The current implementation supports sea clutter in any of five sea states with configurable polarization, grazing angle, and beam width. We describe the implementation and give examples of modeled clutter returns. © 2012 IEEE.

关键词： MATLAB

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Doungtap, Surasachai Petchhan, Jirayu Phanichraksaphong, Varinya Wang, Jenq-Haur International Graduate Program of Electrical Engineering and Computer Science Taiwan National Taiwan University of Science & Technology Dept. of Electrical Engineering Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-depth utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle. © 2023 IEEE.

关键词： Virtual reality

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A study of fine-tuning CNN models based on thermal imaging for breast cancer classification

A study of fine-tuning CNN models based on thermal imaging f...

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2019 IEEE International Conference on Cybernetics and Computational Intelligence, CYBERNETICSCOM 2019

作者： Roslidar, Roslidar Saddami, Khairun Arnia, Fitri Syukri, Maimun Munadi, Khairul Universitas Syiah Kuala Post Graduate Programme in Engineering Banda Aceh23111 Indonesia Post Graduate Programme in Engineering Universitas Syiah Kuala Department of Electrical and Computer Engineering Banda Aceh23111 Indonesia Medical Faculty Universitas Syiah Kuala Banda Aceh23111 Indonesia

ISBN: (纸本)9781728108674

This paper discusses the initial experiments on fine-tuning the convolutional neural network (CNN) models of ResNet101, DenseNet, MobileNetV2, and ShuffleNetV2 for breast cancer detection. These models have been tested using the ImageNet database and shown their high performance on the image classification. Here, the dataset used to train the model are thermal breast images downloaded from the Database for Mastology Research (DMR). There are only two classification classes here, cancer and healthy. During the training, we used three epochs for the training iteration, 10, 20, and 30. For this preliminary study, we set the learning rate to 0.001, momentum to 0.9, learning rate factor for weight and bias each to 10, and minibatch size to 10. The training results showed that ResNet101 and DenseNet with deep networks have 100% accuracy only in 10 epochs. Whereas, MobileNetV2 and ShuffleNetV2 respectively need 20 epochs and 30 epochs of training to achieve 100% accuracy. Finally, we evaluated the performance of each pretrained model using testing results. The DenseNet was able to classify all the testing dataset correctly. ResNet101 and MobileNetV2 have the same performance, correctly classified static dataset while slightly missed in classifying dynamic dataset with 0.996 of accuracy. ShuffleNetV2 has a little lower performance with only 0.98 of accuracy. In term of training time, ShuffleNetV2 spent a short duration, but MobileNetV2 with competitive elapse time was able to show equal performance to ResNet101. © 2019 IEEE.

关键词： Image classification

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Data-driven analysis of kinaesthetic and tactile information for shape classification

Data-driven analysis of kinaesthetic and tactile information...

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2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015

作者： De Oliveira, Thiago Eustaquio Alves Prado Da Fonseca, Vinicius Huluta, Emanuil Rosa, Paulo F. F. Petriu, Emil M. School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9781479960910

Humans sense of touch consists in a complexity of sensors and nervous system. The information inferred by this system enables the daily dexterous manipulation tasks. In biological systems, there is no conscious prioritization of sensors while performing tactile exploration and the selection of exploratory movements is driven by learning instincts and data gathered by previous movements. The development of artificial systems tries to mimic such systems with engineered sensors and strategies for movement selection. This paper presents a data-driven analysis to the problem of sensor selection in the contour following for shape discrimination task. This task consists of a 4-DOF robotic finger exploring a set of 7 synthetic shapes. The data collected from the motors, inertial measurement unit, and magnetometer was analyzed applying principal component analysis and a multilayer perceptron neural network. Results show the variation of classification rate depending on the fingertip material and sensor considered. It is worth to observe that the magnetometer was the most robust in both cases. © 2015 IEEE.

关键词： Magnetometers

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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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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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Author Correction: Dynamical flexible inference of nonlinear latent factors and structures in neural population activity

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Nature biomedical engineering 2025年第2期9卷 283页

作者： Hamidreza Abbaspourazad Eray Erturk Bijan Pesaran Maryam M Shanechi Ming Hsieh Department of Electrical and Computer Engineering Viterbi School of Engineering University of Southern California Los Angeles CA USA. Departments of Neurosurgery Neuroscience and Bioengineering University of Pennsylvania Philadelphia PA USA. Ming Hsieh Department of Electrical and Computer Engineering Viterbi School of Engineering University of Southern California Los Angeles CA USA. shanechi@usc.edu. Thomas Lord Department of Computer Science Alfred E. Mann Department of Biomedical Engineering Neuroscience Graduate Program University of Southern California Los Angeles CA USA. shanechi@usc.edu.

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Carbon nanostructure field emission devices

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Journal of Vacuum Science and Technology B: Microelectronics and Nanometer Structures 2006年第2期24卷 1008-1012页

作者： Wong, Y.M. Kang, W.P. Davidson, J.L. Soh, K.L. Choi, B.K. Hofmeister, W. Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN 37235 Interdisciplinary Graduate Program in Material Science Vanderbilt University Nashville TN 37235 Department of Chemical Engineering Vanderbilt University Nashville TN 37235

The microwave plasma chemical vapor deposition (MPCVD) method is capable of synthesizing various forms of carbon allotropes such as diamond, carbon nanotubes (CNTs), and diamondlike carbon (DLC) while varying the growth parameters or utilizing substrate coated with catalytic thin film. In this article, needlelike carbon nanostructures (CNs) were synthesized utilizing high power (5 kW) and high working pressure (120 Torr) MPCVD on a thin catalytic film of nickel with a diffusion barrier layer of titanium on a micropatterned silicon substrate. The effects of in situ doping by trimethylboron (TMB) on the morphologies and field emission properties of the CNs were also investigated. Straight, needlelike CNs with random orientation were obtained for 15 min growth time with or without TMB doping. However, the CNs appear to transform into diamondlike nanocrystals after prolonged growth of 30 min with TMB doping. Unlike MPCVD grown CNTs, it was found that the CNs have strong adhesion to the substrate and could withstand postgrowth processing such as ultrasonic agitation cleaning in solvents. Field emission tests performed show that in situ TMB doping of the patterned needlelike CNs lowers the turn-on field of the cathode. A vacuum field emission triode with self-aligned gate utilizing CNs as the field emitter is also fabricated. © 2006 American Vacuum Society.

关键词： Carbon nanotubes

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THE LOGICAL RECORD ACCESS APPROACH TO DATABASE DESIGN

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COMPUTING SURVEYS 1980年第2期12卷 179-211页

作者： TEOREY, TJ FRY, JP Electrical and Computer Engineering CICE Program The University of Michigan Ann Arbor Michigan Database Systems Research Group Graduate School of Business Administration The University of Michigan Ann Arbor Michigan

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Towards Developing an Intelligent HAJJ Guide system 8th

Towards Developing an Intelligent HAJJ Guide system

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8th International Conference on Information Technology, ICIT 2017

作者： Shaout, Adnan Oman, Malak University of Michigan - Dearborn Electrical and Computer Engineering Department Dearborn United States Sudan University of Science and Technology Collage of Post Graduate Studies Khartoum Sudan

ISBN: (纸本)9781509063321

Navigating unfamiliar places is a common problem pilgrim face during Hajj. There exists few research-based applications that provide support but are less suited for highly crowded situations such as Hajj religious event. Therefore there is need to investigate support systems for use in large crowded events. Towards Developing an Intelligent HAJJ Guide system is a PhD thesis that investigates the issues of guidance for pilgrim and how it can make Hajj more suitable for pilgrims who navigate in groups in unfamiliar areas. This paper is will present the mean findings of the PhD dissertation. © 2017 IEEE.

关键词： navigation hajj guidance system pilgrims track system Crowding Guidance systems Theses navigation Guidance Support Systems

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