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检索条件"机构=Dept. of Computer and Elec. Eng. and Computer Science"

共 5064 条记录，以下是51-60 订阅

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Enhancing the Maximum Tolerable Number of Active Users for Unsourced Random Access

Enhancing the Maximum Tolerable Number of Active Users for U...

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IEEE International Symposium on Information Theory

作者： Shan Lu Hiroshi Kamabe Graduate School of Engineering Nagoya University Nagoya Japan Dept. of Elec. Elec. and Computer Eng. Gifu University Gifu Japan

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

In the unsourced random access (U-RA), only a portion of users in a large number of users are active during the same time slot. Each user employs the same codebook, and the task of the decoder is to recover a list of transmitted messages, regardless of the user's identity. A concatenated coding approach, referred to as a coded compressed sensing scheme, decreases the computational complexity. However, there is a limitation that the inner CS decoding only decodes the support of a sparse vector, which leads to each user at the same sub-slot must send a different message, and the maximum tolerable active user number is low. In this paper, we consider an inner CS decoding scheme that initially decodes the amplitudes of a sparse vector and quantifies them to determine the number of active users choosing the same columns. This eliminates the constraint of requiring each user to send different messages in the same sub-slot, thereby increasing the maximum tolerable number of active users. We also show the maximum tolerable active user number with various codeleng.hs. Next, we improve the survival probabilities' upper and lower bounds of the outer tree encoder.

关键词： Codes Vectors Encoding Decoding Task analysis Computational complexity Compressed sensing

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Fool 'Em All - Fool-X: A Powerful & Fast Method for Generating Effective Adversarial Images

Fool 'Em All - Fool-X: A Powerful & Fast Method for Generati...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Khamaiseh, Samer Y. Mancino, Mathew Jost, Deirdre Al-Alaj, Abdullah Bagagem, Derek Serra, Edoardo Miami University Dept. of Computer Science & Software Eng. OH United States Caci International NJ United States Miami University Dept. of Computer Science & Software Eng. Oxford United States Virginia Wesleyan University Department of Computer Science VA United States Boise State University Deptartment of Computer Science ID United States Boise State University Department of Computer Science Boise United States

ISBN: (纸本)9798350362480

The well-trained image classification neural networks are vulnerable to adversarial examples. An adversarial example is a malicious input carefully crafted by adding small perturbations to the original input, leading to misclassification. Despite advancements in generating adversarial examples, to the best of our knowledge, none of the well-known adversarial attacks can generate effective adversarial examples that work efficiently on large-scale datasets and very deep neural network architectures. In contrast to ordinary adversarial examples, effective adversarial examples have all the following four characteristics: (1) the ability to maximize the loss of DNNs, (2) the ability to cause a high misclassification rate for both undefended and defended DNN models using various defense methods, (3) minimal perturbations with low computational overhead on large-scale datasets, (4) the ability to be transferable across different DNN *** fill this void, we propose Fool-X, an algorithm to generate effective adversarial examples with the least perturbations that can fool state-of-the-art image classification neural networks. To evaluate the performance of Fool-X, we have conducted extensive experiments using 12 baseline adversarial training defense methods and six state-of-the-art adversarial attacks. The results reported on ImageNet-ILSVRC, CIFAR-100, and CIFAR-10 demonstrate that the proposed Fool-X algorithm can generate effective adversarial examples on large-scale datasets that can successfully fool the well-trained, defended image classification neural networks and significantly outperform the state-of-the-art adversarial attacks. The code is available: https://***/LAiSR-SK/fool-X-Attack © 2024 IEEE.

关键词： Deep neural networks

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Adaptive Traffic Signal Timing: Leveraging YOLOv10 and computer Vision for Real-Time Optimization 8

Adaptive Traffic Signal Timing: Leveraging YOLOv10 and Compu...

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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Papanashi, Suhas Chadaga, Manya Kshithi, R. Huddar, Santosh S. Sreelakshmi, K. Ramakanth Kumar, P. Rv College of Engineering Dept. of Electronics and Telecomm Bengaluru India Rv College of Engineering Dept. of Computer Science & Eng. Bengaluru India

ISBN: (纸本)9798331505462

Traffic congestion poses a significant challeng. in modern urban environments, particularly in densely populated cities. Traditional traffic signals, which operate on fixed timings, often require manual adjustments to respond to varying traffic densities, leading to inefficient traffic flow. This issue arises because fixed intervals do not account for the dynamic nature of traffic patterns throughout the day. While developing intelligent systems that adjust signal durations dynamically offers a potential solution, such systems involve substantial financial investment and extended implementation timelines. This paper proposes a method to optimize green light durations by analyzing footage collected from a traffic junction in Beng.luru. This analysis can be performed using existing CCTV footage or manually gathered data. Even limited sample sizes can provide valuable insights for preliminary adjustments. The approach utilizes YOLOv10, a state-of-the-art computer vision algorithm, to extract relevant traffic data. The data is processed by an algorithm designed to reallocate green light durations, which are then compared with the original timings. An experimental setup involved recording one-minute videos over three days at the selec.ed junction and applying the proposed algorithm to assess and refine signal durations. The results demonstrate the feasibility of using such algorithms to improve traffic signal management effectively. © 2024 IEEE.

关键词： Investments

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Design Method of Effective Passband Flat Variable FIR Filters for Weight Measurement

Design Method of Effective Passband Flat Variable FIR Filter...

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Annual Conference of Industrial elec.ronics Society

作者： Toma Miyata Yasunori Sugita Naoyuki Aikawa Dept. of Elec. Elec. and Info. Eng. Kanagawa Institute of Technology Japan Dept. of Elec. Elec. and Info. Eng. Nagaoka University of Technology Niigata Japan Dept. of Applied Elec. Tokyo University of Science Tokyo Japan

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In order to efficiently eliminate noise in the mass measurement of objects, design methods of FIR filters with high attenuation in a part of the stopband and variable characteristics in the stopband have been proposed. Recently, we have proposed a design method for variable FIR filters with a flat amplitude in the passband and equiripple in the stopband, where the magnitude of the high attenuation can be specified in dB to improve measurement accuracy. In this paper, we present a design method for a variable linear phase-variable FIR filter with a specified attenuation in a part of the stopband. The proposed design method produces a variable filter whose magnitude is greater than or equal to the specified attenuation even if the position of the specified attenuation changes. Finally, we confirm the effectiveness of the proposed method by actually designing a variable filter using the method.

关键词： Weight measurement Industrial elec.ronics Finite impulse response filters Design methodology Noise Attenuation measurement Attenuation Linear programming Passband Noise measurement

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Goal Driven Code Generation for Smart Contract Assemblies 23

Goal Driven Code Generation for Smart Contract Assemblies

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12th International Conference on Software and computer Applications, ICSCA 2023

作者： Tsiounis, Konstantinos Kontogiannis, Kostas Western University Dept. of Computer Science LondonON Canada York University Dept. of Electrical Eng. & Computer Sci. TorontoON Canada

ISBN: (纸本)9781450398589

We are currently witnessing the proliferation of blockchain environments to support a wide spectrum of corporate applications through the use of smart contracts. It is of no surprise that smart contract programming language technology constantly evolves to include not only specialized languages such as Solidity, but also general purpose languages such as GoLang and JavaScript. Furthermore, blockchain technology imposes unique challeng.s related to the monetary cost of deploying smart contracts, and handling roll-back issues when a smart contract fails. It is therefore evident that the complexity of systems involving smart contracts will only increase over time thus making the maintenance and evolution of such systems a very challeng.ng task. One solution to these problems is to approach the implementation and deployment of such systems in a disciplined and automated way. In this paper, we propose a model-driven approach where the structure and inter-dependencies of smart contract, as well as stakeholder objectives, are denoted by extended goal models which can then be transformed to yield Solidity code that conforms with those models. More specifically, we present first a Domain Specific Language (DSL) to denote extended goal models and second, a transformation process which allows for the Abstract Syntax Trees of such a DSL program to be transformed into Solidity smart contact source code. The transformation process ensures that the generated smart contract skeleton code yields a system that is conformant with the model, which serves as a specification of said system so that subsequent analysis, understanding, and maintenance will be easier to achieve. © 2023 Copyright held by the owner/author(s).

关键词： Smart contract

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Improving the performance of characteristic recognition for unknown antennas with limited data

Improving the performance of characteristic recognition for ...

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2023 International Symposium on elec.romagnetic Compatibility - EMC Europe, EMC Europe 2023

作者： Oh, Dong-Hyun Yang, Sung-Jun Han, Jung-Hoon Jeju Nat'l Univ. Dept. of Telecomm. Eng. Jejusi Korea Republic of Seoul Nat'l Univ. of Science and Tech. Dept. of Elec. Eng. Seoul Korea Republic of

ISBN: (纸本)9798350324006

Identifying the elec.romagnetic features of an unknown antenna and evaluating its elec.romagnetic vulnerability are crucial for enhancing the effectiveness of high-power elec.romagnetic attacks or defenses. Sparse measurement of the radiation pattern combined with Infinitesimal Dipole Modeling (IDM) can be an effective method for antenna modeling. IDM uses mathematical representations of infinitesimal current-carrying elements to model the behavior of the unknown antenna. The more measurement data used, the higher the correlation with the original pattern. However, given the practical limitations of the observation environment, a method of obtaining high correlation with minimal data is necessary. In this paper, a method is presented to probabilistically increase the recognition performance of antenna characteristics, even when IDM is applied with limited data. This is achieved by utilizing general elec.romagnetic properties of antennas and data augmentation. A simulation and measurement were conducted using a rigid horn antenna. The results showed that the same correlation performance can be achieved with IDM enhanced by data augmentation, compared to traditional IDM, even when using fewer measurement points. © 2023 IEEE.

关键词： Horn antennas

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Finite Element Model in LTspice of a Distributed RC-Structure Fractional-Order Capacitor Device

Finite Element Model in LTspice of a Distributed RC-Structur...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Prokup, Lauryn A. Kubanek, David Freeborn, Todd J. The University of Alabama Dept. Elec. Computer Eng. Tuscaloosa United States Brno University of Technology Dept. Telecommunications Brno Czech Republic The University of Alabama Dept. Elec. Comp. Eng. Tuscaloosa United States

ISBN: (纸本)9798331504847

Fractional-order capacitors can potentially be fabricated using MOS technologies taking advantage of their distributed resistive-capacitive structure. However, there are limited models to simulate the characteristics of these designs. In this work, an equivalent circuit model to represent a finite-element of a MOS structure is used to assemble a hierarchical model of a complete design in LTspice. This equivalent circuit model is validated (for designs with phases of -77°, -74°, -58°, and -53° with a maximum of ±2° tolerance) against previously established matrix model representations. Using this validated model varying gate leng.h connections (from 100% to 6.25%) caused deviations less than 0.25° supporting that this characteristic of MOS technologies is not likely to have a significant effect on fabricated designs. © 2025 IEEE.

关键词： Equivalent circuits

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Optimizing Data Stream Freshness for Enhanced Communication in Autonomous Vehicle Networks

Optimizing Data Stream Freshness for Enhanced Communication ...

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IEEE Conference on Wireless Communications and Networking

作者： Dariush Ebrahimi Pronab Ghosh Fadi Alzhouri Thiago E. Alves De Oliveira Dept. of Computer Science Wilfrid Laurier University Waterloo Ontario Canada Dept. of Computer Science Lakehead University Thunder Bay Ontario Canada Dept. of Elec. & Computer Eng. GUST University Mishref Kuwait

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Autonomous vehicles (AVs) are anticipated to play a pivotal role in intelligent transportation systems, particularly in the context of future smart cities. Common performance measures like throughput and latency are not sufficient for capturing the timing and freshness of data in applications like autonomous driving and accident prevention. Therefore, this paper addresses the challeng. of minimizing the Age of Information (AoI) in AVassisted vehicular networks. First, the problem is mathematically formulated as linear programming to derive optimal solutions. Recognizing the computational complexity, a scalable heuristic method tailored for large networks is proposed. Additionally, for comparative analysis, the problem is modeled as a Markov decision process and solved using Q-learning, an algorithm of Reinforcement Learning (RL). The numerical results highlight the efficacy of the proposed heuristic method in minimizing the average AoI, considering both computational efficiency and its potential to complement RL algorithms in a hybrid approach.

关键词： Q-learning Smart cities Computational modeling Optimization models Throughput Computational efficiency Timing Resource management Problem-solving Autonomous vehicles

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On the Design of Simultaneous Motion Controller for the Four-axis SCARA System 14

On the Design of Simultaneous Motion Controller for the Four...

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14th IEEE International Conference on Power elec.ronics and Drive Systems, PEDS 2023

作者： Li, Yen-Fang Xu, Zhong-Wei Zhang, Yi-Jun Wu, Yong-Bin Chuang, Lilan Ming-Hsin University of Science and Technology Dept. of Elec. Eng. Hsin-Chu30401 Taiwan Chang Gung University of Science and Technology Dept. of Nursing Taoyuan333324 Taiwan

ISBN: (纸本)9798350399967

This paper conducted the design and implementation of a four-axis Selec.ive Compliance Assembly Robot Arm (SCARA) motion controller. Combining the SoC and FPGA circuits, a SoC/FPGA based four-axis simultaneous motion controller is proposed. The SoC-based controller operates the real-time forward and inverse kinematics computing, while the FPGA-based controller paralleled modulates the position and speed control of each axis. The SoC communicates with the PC-based host controller through TCP/Modbus so that the latter no longer requires the forward and inverse kinematics computing, in which the distributed control between SoC and PC can be achieved. The PC-based host controller only instructs the motion path order in the space, accurate path planning on each axis of the SCARA would be completed through proper movement segment calculation by the SoC-based controller, such design architect is able to accomplish a high speed, high accuracy motion control of the SCARA system. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Automated segmentation and classification of the atherosclerotic carotid plaque in ultrasound videos 24

Automated segmentation and classification of the atheroscler...

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24th International Conference on Digital Signal Processing, DSP 2023

作者： Liapi, Georgia D. Gemenaris, Michalis Loizou, Christos P. Kyriacou, Efthyvoulos Constatninou, Kyriacos P. Nicolaides, Andrew Dept. of Electrical Eng. Computer Eng. and Informatics Cyprus University of Technology Limassol Cyprus Dept. of Computer Science University of Cyprus Nicosia Cyprus Vascular Screening and Diagnostic Centre Nicosia Cyprus

ISBN: (纸本)9798350339598

The automated and reliable delineation of atherosclerotic carotid plaques in ultrasound (CUS) videos is of significant clinical relevance for management of the disease and the prediction of future stroke events. To facilitate stroke risk assessment, in this study, we propose an integrated software system for the automated segmentation and classification of atherosclerotic carotid plaques in longitudinal CUS videos, which was evaluated using 10 CUS videos, from 10 patients (5 Asymptomatic, AS, and 5 Symptomatic, SY). The proposed methodology involves the following steps: a) CUS video frame (VF) resolution and intensity normalization, b) speckle reduction filtering, c) Motion-mode state-based cardiac cycle (CC) identification, d) deep learning (DL)-based plaque segmentation, e) extraction and selec.ion of plaque region of interest (ROI)-specific textural features, and f) machine learning (ML)-based plaque classification. Initially, one CC (cardiac diastole-systole-diastole) was selec.ed per CUS video, and the CC's consecutive VFs were identified and reduced in number to exclude redundant VFs. All standardized VFs per patient were extracted, cropped and resized to mainly accommodate the ROI and were fed into a priorly trained and evaluated 2-dimensional DL plaque segmentation model. For each VF, the DL-based segmented plaque ROI was projected onto its primary resolution-normalized VF counterpart, from which textural and amplitude modulation-frequency modulation (AM-FM) plaque ROI features were extracted. Statistical analysis on the total AS and SY VFs was used for feature selec.ion. We identified 2 plaque-originating AM-FM features, which exhibited statistically significant differences between the AS and SY standardized VFs (p © 2023 IEEE.

关键词： Frequency modulation

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