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检索条件"机构=CPGEI - Graduate Program in Electrical and Computer Engineering"

共 1267 条记录，以下是121-130 订阅

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BAQET: BRAM-aware Quantization for Efficient Transformer Inference via Stream-based Architecture on an FPGA 25

BAQET: BRAM-aware Quantization for Efficient Transformer Inf...

引用

Proceedings of the 2025 ACM/SIGDA International Symposium on Field programmable Gate Arrays

作者： Ling-Chi Yang Chi-Jui Chen Trung Le Bo-Cheng Lai Scott Hauck Shih-Chieh Hsu Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Degree Program of College of Electrical and Computer Engineering in National Yang Ming Chiao Tung University Hsinchu Taiwan Electrical and Computer Engineering in University of Washington Seattle USA Electrical and Computer Engineering University of Washington Seattle USA Physics University of Washington Seattle USA

ISBN: (纸本)9798400713965

FPGAs are a compelling substrate for supporting machine learning inference. Tools such as High-Level Synthesis and hls4ml can shorten the development cycle for deploying ML algorithms on FPGAs, but can struggle to handle the large on-chip storage needed for many of these models. In particular the high BRAM usage found in many of these flows can cause Place & Route failures during synthesis. In this paper we propose using a Simulated-Annealing based flow to perform BRAM-aware quantization. This approach trades off inference accuracy with BRAM usage, to provide a high-quality inference engine that still meets on-chip resource constraints. We demonstrate this flow for Transformer-based machine learning algorithms, which include Flash Attention in a Stream-based Dataflow architecture. Our system imposes minimal accuracy drops, yet can reduce BRAM usage by 20%-50%, and improve power efficiency by 264%-812% compared to existing Transformer-based accelerators on FPGAs

关键词： efficient transformer

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Light-induced tunable optical properties of 1T-TaS2 at different temperatures

Light-induced tunable optical properties of 1T-TaS2 at diffe...

引用

CLEO: QELS_Fundamental Science, QELS 2022

作者： Li, Weijian Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Electrical and Computer Engineering Rice University HoustonTX77005 United States

The c-axis permittivity of 1T-TaS2 - a quasi-2D charge-density-wave material - changes upon illumination due to light-induced reorganization of CDW stacking. Here we probe the mechanism of this reorganization and find... 详细信息

ISBN: (纸本)9781557528209

关键词： Charge density

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Ti02-based Flexible Integrated Photonics for High-sensitivity Temperature Sensing

Ti02-based Flexible Integrated Photonics for High-sensitivit...

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2022 Conference on Lasers and Electro-Optics, CLEO 2022

作者： Zhao, Xuan Fan, Bo Veeraraghavan, Ashok Robinson, Jacob Applied Physics Graduate Program Smattey-Curl Institute Rice University HoustonTX77005 United States Electrical & Computer Engineering Rice University HoustonTX77005 United States

We report a flexible temperature sensor based on Ti02 photonics that shows double the sensitivity compared to silicon photonics. This high sensitivity and biocompatibility pave the way towards point-of-care temperatur... 详细信息

ISBN: (纸本)9781957171050

关键词： Biocompatibility

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Application of Artificial Neural Network Method for Forecasting Weekly Electricity Load Based on Daily Pattern Classification

Application of Artificial Neural Network Method for Forecast...

引用

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

作者： Husni Ramzi Adriman Ira Devi Sara Rio Syahputra Graduate program of Electrical Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh Aceh Department of Electrical and Computer Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh Aceh

Accurate weekly electricity load prediction is of utmost importance for electricity providers to ensure uninterrupted power supply to customers. This study applies an Artificial Neural Network (ANN) to achieve precise weekly electricity load prediction. The dataset used for the ANN model consists of three months’ worth of data, including daily workload profiles, holiday work profiles, temperature, and humidity. For model training, 90% of the data is utilized with the Levenberg-Marquardt algorithm, while the remaining 10% is used for testing. The Mean Average Percentage Error (MAPE) is employed as the error metric. Based on the test results, the weekly load prediction error rate using ANN is determined to be 1.78% based on the MAPE value.

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1T-TaS2 based dynamically tunable plasmonic metasurface

1T-TaS2 based dynamically tunable plasmonic metasurface

引用

CLEO: QELS_Fundamental Science, QELS 2022

作者： Li, Weijian Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Electrical & Computer Engineering Rice University HoustonTX77005 United States

We demonstrate a dynamically tunable plasmonic metasurface enabled by light-tunable optical constants of a quantum material - 1T-TaS2. We observe a relative reflectance change of 10% under low-intensity incoherent ill... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781557528209

关键词： Reflectivity MIM devices Lighting Lasers and electrooptics Metasurfaces Plasmons Optical materials

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TiO2-based Flexible Integrated Photonics for High-sensitivity Temperature Sensing

TiO2-based Flexible Integrated Photonics for High-sensitivit...

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CLEO: Science and Innovations, S and I 2022

作者： Zhao, Xuan Fan, Bo Veeraraghavan, Ashok Robinson, Jacob Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Electrical & Computer Engineering Rice University HoustonTX77005 United States

We report a flexible temperature sensor based on TiO2 photonics that shows double the sensitivity compared to silicon photonics. This high sensitivity and biocompatibility pave the way towards point-of-care temperatur... 详细信息

ISBN: (纸本)9781557528209

关键词： Titanium dioxide

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A Platform for Monitoring Student Commuting in the Use of School Transport in Smart Cities - A Facial Recognition Based Approach

A Platform for Monitoring Student Commuting in the Use of Sc...

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2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

作者： Da Costa Rocha, Jesse De Souza, Marcela Alves Cardoso, Evelin Helena Silva Vijaykumar, Nandamudi De Araujo, Jasmine Priscyla Leite Frances, Renato Lisboa Graduate Program in Electrical Engineering Belém Para Brazil Information and Communication Technology Center Marabá Para Brazil Department of Computer Science Capitão Poço Para Brazil Coordination of Applied Research and Technological Development São Paulo Brazil

ISBN: (纸本)9798350302523

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics. © 2023 IEEE.

关键词： Students

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Analytical reference compensation for tracking dynamic target signals with linear robust MPC strategies

Analytical reference compensation for tracking dynamic targe...

引用

American Control Conference (ACC)

作者： Tito L. M. Santos Bruno S. S. Pereira Department of Electrical and Computer Engineering Federal University of Bahia Salvador Bahia Brazil Graduate Program on Electrical and Engineering Federal University of Bahia Salvador Bahia Brazil Department of Robotics SENAI-CIMATEC Salvador Bahia Brazil

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper proposes an analytical target modifi-cation for linear robust model predictive control strategies in order to deal with time-varying references defined by dynamic signal targets. The new approach can be directly integrated to linear robust model predictive control algorithms that achieve piecewise constant reference tracking if recursive feasibility is ensured for any set-point. The main contribution is to present a direct analytical approach that provides a potentially improved steady-state tracking error performance with the same computation complexity of the original MPC for tracking piecewise constant reference. A simulation case study based on the trajectory tracking control of a quadrotor is used to illustrate the usefulness of the new analytical target modification layer.

关键词： Sufficient conditions Target tracking Trajectory tracking Heuristic algorithms Prediction algorithms Steady-state Computational complexity

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Condition Assessment of Underground Cable System Using Fuzzy Logic and Scoring and Weighting Average Methods

Condition Assessment of Underground Cable System Using Fuzzy...

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2023 International Conference on Power, Energy and Innovations, ICPEI 2023

作者： Romphoyen, Dineenath Panmala, Nattapon Suwanasri, Thanapong Suwanasri, Cattareeya King Mongkut's University of Technology North Bangkok The Sirindhorn International Thai-German Graduate School of Engineering EPE Program Bangsue Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangsue Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangsue Bangkok Thailand

ISBN: (纸本)9798350344585

In this paper, the overall health index of underground cable system is determined using Fuzzy Logic and Scoring and Weighting Average methods. The relevant data of 73 feeders has been collected in the prepared evaluation forms, divided into five major component groups: cable, joint, termination, manhole, and ductbank. In each component, various testing methods and diagnostic techniques are applied, and then the numerical score is determined according to the technical criteria for condition assessment. Subsequently, the obtained overall health index is multiplied with the conditional factor to incorporate the differences in installation type and configuration as well as the operating and environmental conditions. Finally, the overall health index based on these two methods is compared to verify the accuracy of the obtained results to properly plan the preventive and condition-based maintenance and to improve the reliability of the underground cable system. © 2023 IEEE.

关键词： Fuzzy logic

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Low-Resolution Face Recognition for CCTV and Edge-Powered Smart Attendance Systems

Low-Resolution Face Recognition for CCTV and Edge-Powered Sm...

引用

IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Nico Surantha Edward Yose Sani Muhamad Isa Department of Electrical Electronics and Communication Engineering Faculty of Science and Engineering Tokyo City University Tokyo Japan Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Attendance systems have become more modern, and one of the biometric systems without physical contact is face recognition. However, many face-based attendance systems still carry out attendance individually and cannot detect multiple faces simultaneously. In addition, capturing facial data in real-time is still a challenge because the relatively large distance between the camera and the individual reduces the ability to recognize faces. The general solution is to use super-resolution to generate better-quality faces while maintaining the main facial recognition features. One technique still being researched is super-resolution generative adversarial networks (SRGAN). SRGAN can enlarge the resolution of captured images and maintain image quality sufficient for face recognition. The attendance system can be easily integrated into edge devices such as the Jetson Nano. This paper proposes automatic and effective attendance systems with the super-resolution technique to detect and recognize faces in low-resolution input. The experimental results show that using face data capture with a resolution of 40 × 40 pixels and a four-fold magnification results in a resolution of 160 × 160 pixels. Combining Face SRGAN with FaceNet architecture as the basis of face recognition can achieve an accuracy rate of 78.19% and an F1-Score of 81.13% with an average processing time of 1.61 seconds per frame on a PC and 14.55 seconds per frame on a Jetson Nano at an average of face recognition per frame of as many as up to 8 faces simultaneously.

关键词： Support vector machines Image quality Accuracy Face recognition Image edge detection Superresolution Generative adversarial networks

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