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arXiv 2022年

作者： Hu, Jie Doshi, Vishwaraj Eun, Do Young Department of Electrical and Computer Engineering United States Operations Research Graduate Program North Carolina State University RaleighNC United States

We study the file transfer problem in opportunistic spectrum access (OSA) model, which has been widely studied in throughput-oriented applications for max-throughput strategies and in delay-related works that commonly assume identical channel rates and fixed file sizes. Our work explicitly considers minimizing the file transfer time for a given file in a set of heterogeneous-rate Bernoulli channels, showing that max-throughput policy doesn’t minimize file transfer time in general. We formulate a mathematical framework for static extend to dynamic policies by mapping our file transfer problem to a stochastic shortest path problem. We analyze the performance of our proposed static and dynamic optimal policies over the max-throughput policy. We propose a mixed-integer programming formulation as an efficient alternative way to obtain the dynamic optimal policy and show a huge reduction in computation time. Then, we propose a heuristic policy that takes into account the performance-complexity tradeoff and consider the online implementation with unknown channel parameters. Furthermore, we present numerical simulations to support our analytical results and discuss the effect of switching delay on different policies. Finally, we extend the file transfer problem to Markovian channels and demonstrate the impact of the correlation of each channel. Copyright © 2022, The Authors. All rights reserved.

关键词： Stochastic systems

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NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report

NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report

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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Ancuti, Codruta O. Ancuti, Cosmin Vasluianu, Florin-Alexandru Timofte, Radu Zhou, Han Dong, Wei Liu, Yangyi Chen, Jun Liu, Huan Li, Liangyan Wu, Zijun Dong, Yubo Li, Yuyan Qiu, Tian He, Yu Lu, Yonghong Wu, Yinwei Jiang, Zhenxiang Liu, Songhua Yang, Xingyi Jing, Yongcheng Benjdira, Bilel Ali, Anas M. Koubaa, Anis Yang, Hao-Hsiang Chen, I-Hsiang Chen, Wei-Ting Huang, Zhi-Kai Chen, Yi-Chung Hsieh, Chia-Hsuan Chang, Hua-En Chiang, Yuan-Chun Kuo, Sy-Yen Guo, Yu Gao, Yuan Liu, Ryan Wen Lu, Yuxu Qu, Jingxiang He, Shengfeng Ren, Wenqi Hoang, Trung Zhang, Haichuan Yazdani, Amirsaeed Monga, Vishal Yang, Lehan Wu, Alex Jiahao Mai, Tiancheng Cong, Xiaofeng Yin, Xuemeng Yin, Xuefei Emad, Hazim Abdallah, Ahmed Yasser, Yahya Elshahat, Dalia Elbaz, Esraa Li, Zhan Kuang, Wenqing Luo, Ziwei Gustafsson, Fredrik K. Zhao, Zheng Sjölund, Jens Schön, Thomas B. Zhang, Zhao Wei, Yanyan Wang, Junhu Zhao, Suiyi Zheng, Huan Guo, Jin Sun, Yangfan Liu, Tianli Hao, Dejun Jiang, Kui Sarvaiya, Anjali Prajapati, Kalpesh Patra, Ratnadeep Barik, Pragnesh Rathod, Chaitanya Upla, Kishor Raja, Kiran Ramachandra, Raghavendra Busch, Christoph ETcTI Universitatea Politehnica Timisoara Romania ICTEAM UCL Belgium Computer Vision Lab University of Wuerzburg Germany Computer Vision Lab ETH Zurich Switzerland Department of Electrical and Computer Engineering McMaster University Canada Department of Electrical and Computer Engineering University of Alberta Canada McMaster University Canada Xidian University China Research Institute Singapore National University of Singapore Singapore University of Sydney Australia Robotics and Internet-of-Things Laboratory Prince Sultan University Riyadh12435 Saudi Arabia Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Wuhan University of Technology China Singapore Management University Singapore Singapore Sun Yat-sen University China Electrical Engineering Department Pennsylvania State University United States The University of Sydney Australia Southeast University China University of California Los Angeles United States Beijing Jiaotong University China Mansoura Univeristy Egypt College of Information Science and Technology Jinan University China Department of Information Technology Uppsala University Sweden Hefei University of Technology China Zhejiang Dahua Technology China Sardar Vallabhbhai National Institute of Technology India Norwegian University of Science and Technology Norway

ISBN: (纸本)9798350302493

This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated using a professional setup that replicated real-world conditions of hazy scenarios. The competition had 246 participants and 17 teams submitted solutions for the final testing phase. The proposed solutions demonstrated the cutting-edge in image dehazing technology. © 2023 IEEE.

关键词： Demulsification

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A 4 GS/s 3-bit Highly Linear Time-Based Analog- to-Digital Converter for Massive MIMO Systems 9

A 4 GS/s 3-bit Highly Linear Time-Based Analog- to-Digital C...

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9th International Japan-Africa Conference on electronics, Communications, and Computations, JAC-ECC 2021

作者： Elgreatly, Ahmed Lutfi Shaaban, Ahmed Ahmed Mostafa, Hassan Abdalla, Rania Mohamed El-Rabaie, El-Sayed Mahmoud Port-Said University Faculty of Engineering Electrical Engineering Department Port-Said Egypt University of Science and Technology Zewail City of Science and Technology 6th of October Nanotechnology and Nanoelectronics Program Giza Egypt Menoufia University Faculty of Electronic Engineering Electronics and Communications Department Menouf Egypt

ISBN: (纸本)9781665482929

Recent studies on modern wireless communication systems are focusing on Massive Multiple- Input Multiple-Output (MIMO) technology for its high potential. MIMO systems require high resolution Analog-to- Digital Converters (ADCs) in the Base Stations (BS) to reduce quantization noise. However, using high resolution ADCs causes higher power consumption at the BS and the hardware costs increase. Reducing the resolution of the ADCs at the BS causes severe non-linearity errors due to additional quantization noise. In other words, MIMO systems cannot achieve high performance without highly linear and low resolution ADCs. In this paper, a 3-bit highly linear Time- based ADC (T-ADC) is presented. The proposed circuit exhibits high linearity, simple design and low power which make it the best solution for the problems that limit the performance of the MIMO systems. The proposed ADC exhibits a linearity error of 0.56 % with a dynamic range equals to 800 mV and at small power consumption of 2.2 mW. The supply voltage used equals to 1.2 V using industrial 65 nm TSMC CMOS technology. The clock frequency equals to 4 GHz at a maximum input frequency of 2 GHz. © 2021 IEEE.

关键词： Electric power utilization

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IR Reasoner: Real-time Infrared Object Detection by Visual Reasoning

IR Reasoner: Real-time Infrared Object Detection by Visual R...

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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Meryem Mine Gündoğan Tolga Aksoy Alptekin Temizel Ugur Halici Aselsan Inc. Turkey Graduate School of Informatics Middle East Technical University Turkey Arizona State University USA Department of Electrical and Electronics Engineering Middle East Technical University Turkey

Thermal Infrared (IR) imagery is utilized in several applications due to their unique properties. However, there are a number of challenges, such as small target objects, image noise, lack of textural information, and background clutter, negatively affecting detection of objects in IR images. Current real-time object detection methods treat each image region separately and, in face of these challenges, this sole dependency on feature maps extracted by convolutional layers is not ideal. In this paper, we introduce a new architecture for real-time object detection in IR images by reasoning the relations between image regions by using self-attention. The proposed method, IR Reasoner, takes the spatial and semantic coherency between image regions into account to enhance the feature maps. We integrated this approach into the current state-of-the-art one-stage object detectors YOLOv4, YOLOR, and YOLOv7, and trained them from scratch on the FLIR ADAS dataset. Experimental evaluations show that the Reasoner variants perform better than the baseline models while still running in real-time. Our best performing Reasoner model YOLOv7-W6-Reasoner achieves 40.5% AP at 32.7 FPS. The code is publicly available. 1

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Event-triggered control of TS fuzzy systems with guaranteed membership function mismatch ⁎

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IFAC-PapersOnLine 2021年第4期54卷 74-79页

作者： Rafael N. Silva Luciano Frezzatto Fernando O. Souza Víctor C.S. Campos Graduate program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Electronics Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil

This paper proposes augmenting the traditional quadratic event-triggered conditions for Takagi-Sugeno (TS) fuzzy models, by also considering triggering conditions defined by a variation of the membership function values. Suitable Linear Matrix Inequality (LMI) conditions are presented that make full use of the proposed modified triggering conditions to co-design the control law and triggering conditions. Under some mild assumptions, the closed loop system is guaranteed to avoid the Zeno behavior for its triggering instants. A numerical example is presented to illustrate the proposed conditions.

关键词： Event-based control Convex Optimization Takagi-Sugeno fuzzy models Linear Matrix Inequalities Stability of Nonlinear Systems

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Extended Cauer Equivalent Circuit Model of Inductors: Representing Multi-resonant Characteristics Due to Parasitic Capacitance

Extended Cauer Equivalent Circuit Model of Inductors: Repres...

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Annual IEEE Conference on Applied Power electronics Conference and Exposition (APEC)

作者： Yuki Sato Kenji Kawano Hajime Igarashi Hirokazu Matsumoto Department of Electrical Engineering and Electronics Aoyama Gakuin University Sagamihara JAPAN Kilby Labs Texas Instruments Japan Limited Tokyo JAPAN Graduate School of Science and Technology Hokkaido University Sapporo JAPAN

This study presents an extended Cauer circuit model of power inductors that can represent both eddy current effects and capacitive properties. This model is valid from DC to higher frequencies beyond the resonance because it considers the skin and proximity effects of windings as well as the parasitic capacitance. The inductive part is represented by a Cauer circuit whose circuit parameters are recursively determined from the frequency properties of the inductor obtained through measurements or simulations. Moreover, the impedance profile around the resonance is expressed by introducing hierarchical RLC series circuits to the Cauer circuit. The extended Cauer circuit can be embedded in circuit simulators once constructed to perform time-domain simulations.

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Intrinsic Parameter Fluctuation and Process Variation Effect of Vertically Stacked Silicon Nanosheet Complementary Field-Effect Transistors

Intrinsic Parameter Fluctuation and Process Variation Effect...

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IEEE International Symposium on Quality Electronic Design

作者： Sekhar Reddy Kola Yiming Li Min-Hui Chuang Parallel and Scientific Computing Laboratory Hsinchu Taiwan Electrical Engineering and Computer Science International Graduate Program Hsinchu Taiwan Institute of Communications Engineering Hsinchu Taiwan Institute of Biomedical Engineering Hsinchu Taiwan Institute of Pioneer Semiconductor Innovation Hsinchu Taiwan Institute of Artificial Intelligence Innovation Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Center for mmWave Smart Radar System and Technologies National Yang Ming Chiao Tung University Hsinchu Taiwan

We study the variability of vertically stacked gate-all-around silicon nanosheet (GAA Si NS) complementary field-effect transistors (CFETs). The process variation effect (PVE), the work function fluctuation (WKF), and the random dopant fluctuation (RDF) of CFETs are statistically estimated using an experimentally validated device simulation technique. Among five factors of PVE, the channel thickness (T Nch /T Pch ), the channel width (W ch ), and the gate length (L G ) are significant. Owing to superior GAA channel control and increased effective gate area, both WKF and RDF are suppressed. Notably, the PVE on both N-/P-FETs of GAA Si CFET induce the largest off-state current fluctuations of 80% and 278%, respectively, because the device characteristic is very sensitive to the layer thickness and width of channel.

关键词： Fluctuations Gallium arsenide Logic gates Electric variables Silicon Resource description framework Semiconductor process modeling

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Classifying Tweet Sentiment Analysis on Airlines using Random Forest Classifier, Naïve Bayes Classifier and K-Nearest Neighbors Classifier Algorithm

Classifying Tweet Sentiment Analysis on Airlines using Rando...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Ivan Alexander Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Departement Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

Opinion has always affected businesses and individuals especially from the Public. People react through social media and spread it incompletely. The situation was then accepted as public opinion. There are three categories of opinion i.e., positive, negative, and neutral. To investigate public opinion on a particular issue of interest, sentiment analysis might be employed. By offering a solution to the text classification challenge, this experiment focuses on the perception of airline tweets among the American public. We offer a method to classify tweets as positive, negative, or neutral using three machine learning classifiers: Random Forest Classifier, Naive Bayes Classifier, and K-Nearest Neighbors Classifier. We examined the performance of three machine learning classifiers in terms of accuracy, average precision, average recall, and average f-1 score. The results demonstrate that the Random Forest Classifier, which produces 82% accuracy, 80% average precision, 82% average recall, and 80% average f1-score, performs the best among the machine learning classifiers.

关键词： Training Sentiment analysis Accuracy Social networking (online) Text categorization Nearest neighbor methods Naive Bayes methods Random forests Robots Airline industry

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Role of Wireless Communications in Digital Economy in the Present Context 6

Role of Wireless Communications in Digital Economy in the Pr...

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6th International Conference on Trends in electronics and Informatics, ICOEI 2022

作者： Revathi, S. Shrivastava, Arpan Yussupova, Ardak Hidayatulloh, A. Nururrochman Saltanat, Daurbekova Mishra, Arpana Sri Ramakrishna Institute of Technology Department of Computer Science and Engineering Coimbatore India Management Devi Ahilya Vishva Vidyalaya Madhya Pradesh India Kazakh National University of Arts Department of Art Studies Nur-Sultan Kazakhstan Universitas Gadjah Mada Leadership and Policy Innovation Program Indonesia International Education Corporation Department of Construction Almaty050042 Kazakhstan Sharda University Electrical Electronics and Communication Engineering Greater Noida India

ISBN: (纸本)9781665483285

Wireless communication has connected millions of people across the world to internet to enable them to reap benefits of digital economy in present scenario. Almost all the sectors of economy including healthcare, agriculture and transportation nowadays rely largely upon wireless communications. In the present context, the sudden outbreak of Covid-19 has caused governments to impose restrictions on various activities and employees have been directed to work from their homes to ensure safety. In such a situation, wireless communication has made it possible to connect with each other via the internet. Apart from this, Smart healthcare-system has been developed through utilisation of wireless communication systems. During this pandemic situation, delivery of healthcare services in remote areas has gained huge momentum and wireless communication plays a vital role in this regard. Aim of current critical assessment is to provide an in-depth analysis of the role played by wireless communication in establishment of a well-structured digital economy in present scenario. In literature-review, different applications of wireless technology via ICT in various sectors and aspects of life have been discussed through a conceptual and a theoretical framework. The Method section of current study has provided an in-depth insight into the ways required information have been collected in this study. As found in the results and discussion section, a positive relation exists between wireless-communication and establishment of digital economy in current situation. This study has concluded that there are certain challenges associated with wireless communication;however, it has significant influence in making processes smarter and faster as compared to earlier. © 2022 IEEE.

关键词： Internet of things

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An Evaluation of Energy-efficient AI Models for Edge Deployment in 12-lead ECG Classification

An Evaluation of Energy-efficient AI Models for Edge Deploym...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Angger Baskoro Yu-Chi Lin Sirapop Nuannimnoi Himmatur Rijal Gnangze Elie Gildas Traore Milzam Waf Azhar Ching-Yao Huang EECS International Graduate Program National Yang Ming Chiao Tung Univ. Hsinchu Taiwan Institute of Electronics National Yang Ming Chiao Tung Univ. Hsinchu Taiwan Department of Electronics Engineering National Yang Ming Chiao Tung Univ. Hsinchu Taiwan

ISBN: (数字)9798350368086

ISBN: (纸本)9798350368093

In recent years, artificial intelligence (AI) techniques, particularly deep learning, have shown significant promise in modern tele-medicine. Deep learning models, particularly Convolutional Neural Networks (CNNs), have been trained on large datasets to identify patterns and anomalies within 12-lead electrocardiograms (ECGs), which are crucial for diagnosing various cardiac conditions. In this study, we conducted a comparative analysis to identify and evaluate models that can be effectively deployed in rural healthcare settings, where energy efficiency, low computational requirements, and ease of use are critical factors. We compare the performance of two well-known sequential data processing model architectures: time-series RetNet and Mamba. The best model from this comparative study achieves a notable precision of over 95% in a 10 fold cross-validation for the classification of nine types of cardiac arrhythmias (CA) in the 2018 PhysioNet/CinC Challenge (CPSC 2018) dataset.

关键词： Deep learning Adaptation models Analytical models Accuracy Computational modeling Arrhythmia Medical services Electrocardiography Real-time systems Energy efficiency

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