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Varying Periods of In-Field Testing With Storage and Counter Based Logic Built-In Self-Test

IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Pomeranz, Irith Purdue University School of Electrical and Computer Engineering West LafayetteIN47907 United States

In-field testing is important for detecting defects that escaped manufacturing tests or occurred during the lifetime of a chip. When in-field testing is performed periodically, some of the test periods may be shorter than others. Short test periods should focus on the faults that are the most likely to occur with aging, whereas long test periods can apply a more comprehensive test set. This article studies this scenario in the context of a logic built-in self-test (LBIST) approach that partitions compressed tests into subvectors for on-chip storage, and combines subvectors into compressed tests on-chip using counters. This approach has low storage requirements, allows complete fault coverage to be achieved, and uses moderate numbers of tests. The problem of applying a small number of tests during a short testing period is formulated as a static problem of rearranging the subvectors (with possible repetitions and modification) such that the first n1 subvectors are sufficient for detecting a subset of faults F1, and n1 is as small as possible. Experimental results for benchmark circuits in an academic environment demonstrate the numbers of tests and overall storage requirements. © 2025 IEEE.

关键词： Built-in self test

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The Smart Performance Optimization of An Evolutionary Algorithm-Based Framework for Automated Design of Adaptive Systems

The Smart Performance Optimization of An Evolutionary Algori...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Manivasagam Shukla, Gaurav Doda, Davendra Kumar Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798350383348

This look intends to propose a framework based on evolutionary algorithms (EAs) that can be used to automate the layout of adaptive structures. The layout of complex adaptive systems is challenging and typically requires manual tuning of numerous parameters., which may be time-consuming and useless. Consequently., this framework seeks to automate the layout system even by optimizing the overall performance of adaptive structures via evolutionary algorithms. The center of the framework uses a multi-objective evolutionary set of rules to robotically generate design parameters which include architecture complexity and the family members among software program components. The generated designs are then evaluated using simulations of the system that comprise one-of-a-kind environmental conditions and personal alternatives. An optimization engine evaluates every generated layout and uses the results of the simulations to determine the exceptional design. Diverse experiments and use instances are used to assess the practicality and effectiveness of the proposed framework. The effects demonstrate that the proposed framework can optimize the overall performance of adaptive systems in dynamic and uncertain environments. © 2024 IEEE.

关键词： automatically demonstrate evolutionary experiments proposed

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Broad Angle Resolver for THz Band

Broad Angle Resolver for THz Band

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Amarasinghe, Yasith Guerboukha, Hichem Shiri, Yaseman Shrestha, Rabi Klarskov, Pernille Mittleman, Daniel M. Department of Electrical and Computer Engineering Aarhus University Finlandsgade 22 Aarhus NDK-8200 Denmark School of Engineering Brown University 184 Hope St. ProvidenceRI02912 United States

We design a broad angle receiver using a leaky parallel plate waveguide by manipulating the plate separation. The device operates at 200 GHz, has a broad angle of acceptance and can resolve the received angle. © ... 详细信息

ISBN: (纸本)9781957171395

关键词： Terahertz waves

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Mechanically Reconfigurable Terahertz Quasi-Optical Components for Spectral Filtering and Polarization Control

Mechanically Reconfigurable Terahertz Quasi-Optical Componen...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Quader, Sakib Lv, Xiaojing You, Xiaolong Ako, Rajour T. Bhaskaran, Madhu Sriram, Sharath Fumeaux, Christophe Withayachumnankul, Withawat Terahertz Engineering Laboratory The University of Adelaide Adelaide Australia School of Mechanical and Mechatronic Engineering University of Technology Sydney Sydney Australia Functional Materials and Microsystems Research Group RMIT University Melbourne Australia School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia

ISBN: (纸本)9798350379693

Terahertz technologies present unique opportunities for high throughput communications, short-distance high-resolution radar, and spectral sensing/imaging. This spectral range presents some interesting challenges in terms of tunability of transmissive quasi-optical components for spectral filtering or polarization control. The concept of multi-layer periodic structures with sub-wavelength elements, such as frequency-selective surfaces or metasurfaces, allows to create terahertz optical components with unique properties. In this context, this paper reviews three distinctive realizations of such multilayer transmissive devices with reconfigurable properties. The controlled dynamic adaptation of transmission properties is achieved through mechanical reconfiguration based on relative translation or rotation of layers. These presented devices are illustrative of three efficient implementations based on different physical mechanisms, with application for tunable spectral filtering and dynamic polarization control. © 2024 IEEE.

关键词： Terahertz waves

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Heart Disease Identification Based on Butterfly Optimization and Machine Learning

Heart Disease Identification Based on Butterfly Optimization...

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Asrar, Manal Bawazir, Joud Khan, Sibghatullah I. Qaisar, Saeed Mian Effat University Computer Science Department Jeddah22332 Saudi Arabia Department of Electronics and Communication Engineering Hyderabad India Effat University Electrical and Computer Engineering Department Jeddah22332 Saudi Arabia Cesi Engineering School Lineact Laboratory Villeurbanne69100 France

ISBN: (纸本)9798350347050

This paper aims to make use of The Physionet Challenge 2016 collection of normal and abnormal heart sound recordings that were classified by automated identification of PCG sounds to help detect heart diseases earlier and prevent incidents. People with heart diseases have been increasing and most of them lead to fatalities so the detection of sound signals through PCGs can be applied in machine learning models by extracting features from data. In this study, the dataset's recordings are segmented to be used in variational mode decomposition. Once they are decomposed, those means will be fused together into a set of features given to the Butterfly Optimization Algorithm which will conduct a selection of features. As the features are selected, MATLAB was used to test various machine learning algorithms. Results from Support Vector Machines (SVM) and artificial neural networks were used in this investigation (ANN). The ANN model, which had an accuracy rate of 94.8%, was the most accurate of them. © 2023 IEEE.

关键词： Variational mode decomposition

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Deep learning based three-dimensional computer holography from stereo/single images

Deep learning based three-dimensional computer holography fr...

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2024 Conference on Lasers and Electro-Optics/Pacific Rim, CLEO-PR 2024

作者： Chang, Chenliang Dai, Bo Zhuang, Songlin Zhang, Dawei School of Optical-Electrical and Computer Engineering Engineering Research Center of Optical Instrument and System Ministry of Education Shanghai Key Laboratory of Modern Optics System University of Shanghai for Science and Technology Shanghai200093 China

In the field of computer holography, generating three-dimensional (3D) computer-generated hologram (CGH) in real-time speed has been a significant challenge due to the huge amount of data in 3D object wave. Deep learning has been proposed to compute CGH very fast using convolutional neural network (CNN). However, the input of the such CNN still depends on the acquisition of 3D information like RGB-D image. Here we present novel deep learning based computer holography technique which can rapidly generate CGH using CNN directly from stereo/single images rather than from RGB-D data. The method can simplify the CGH generation by using images as input, therefore avoiding the cumbersome 3D depth measuring process. © 2024 The Author(s)

关键词： Stereocenters

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Mobility-aware Seamless Service Migration and Resource Allocation in Multi-edge IoV Systems

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IEEE Transactions on Mobile Computing 2025年第7期24卷 6315-6332页

作者： Chen, Zheyi Huang, Sijin Min, Geyong Ning, Zhaolong Li, Jie Zhang, Yan Fuzhou University College of Computer and Data Science Fuzhou350116 China Ministry of Education Engineering Research Center of Big Data Intelligence Fuzhou350002 China Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China University of Exeter Department of Computer Science Faculty of Environment Science and Economy ExeterEX4 4QF United Kingdom Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China University of Oslo Department of Informatics Oslo0316 Norway

Mobile Edge Computing (MEC) offers low-latency and high-bandwidth support for Internet-of-Vehicles (IoV) applications. However, due to high vehicle mobility and finite communication coverage of base stations, it is hard to maintain uninterrupted and high-quality services without proper service migration among MEC servers. Existing solutions commonly rely on prior knowledge and rarely consider efficient resource allocation during the service migration process, making it hard to reach optimal performance in dynamic IoV environments. To address these important challenges, we propose SR-CL, a novel mobility-aware seamless Service migration and Resource allocation framework via Convex-optimization-enabled deep reinforcement Learning in multi-edge IoV systems. First, we decouple the Mixed Integer Nonlinear Programming (MINLP) problem of service migration and resource allocation into two sub-problems. Next, we design a new actor-critic-based asynchronous-update deep reinforcement learning method to handle service migration, where the delayed-update actor makes migration decisions and the one-step-update critic evaluates the decisions to guide the policy update. Notably, we theoretically derive the optimal resource allocation with convex optimization for each MEC server, thereby further improving system performance. Using the real-world datasets of vehicle trajectories and testbed, extensive experiments are conducted to verify the effectiveness of the proposed SR-CL. Compared to benchmark methods, the SR-CL achieves superior convergence and delay performance under various scenarios. © 2025 IEEE.

关键词： Convex optimization

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Design and Implementation of a Strong Arbiter PUF for the Security of FPGA 14

Design and Implementation of a Strong Arbiter PUF for the Se...

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14th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023

作者： Khanam, Jobeda Cavicchi, Kevin A Electrical and Computer Engineering Technology Farmingdale State College NY United States University of Akron School of Polymer Science and Polymer Engineering AkronOH United States

ISBN: (纸本)9798350304138

Physical unclonable function (PUF) is a promising process for safe key generation on ICs and IoT devices for authentication and cryptographic applications. Each Physical Unclonable Function (PUF) stands apart due to tiny variations introduced during manufacturing, like minuscule gate delays. PUF provides responses when input challenges are given. One of the core advantages of Arbiter PUFs lies in their resilience against conventional attack methods like reverse engineering, side-channel attacks, and brute-force attempts. As the PUF's distinctiveness and randomness stem from its physical structure, adversaries face formidable obstacles when attempting to simulate or forecast its behavior. Recently, researchers proved that some arbiter PUFs can be susceptible to modeling and Machine Learning (ML) Attacks. Researchers continue to explore countermeasures and improvements to enhance the security of Arbiter PUFs and other PUF variants. In our paper, utilizing a computer-aided (CAD) tool, a strong arbiter PUF (APUF) is designed and implemented on a Field Programmable Gate Array (FPGA). The challenges and responses of APUF are 64 bits, which makes it unpredictable and difficult to break using machine learning and deep learning algorithms. Our implemented APUF's performance was evaluated based on inter and intra-hamming distance of responses. The arbiter PUF achieved 0.031% intra-hamming distance (HDintra) and 30% inter-hamming distance (HDinter), which are closely ideal. © 2023 IEEE.

关键词： Hamming distance

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Secure Medical Data Management Based on Homomorphic Encryption and Secret Sharing

Secure Medical Data Management Based on Homomorphic Encrypti...

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8th IEEE International Conference on Smart Cloud, SmartCloud 2023

作者： Law, Po Ying Tsai, Chia-Cheng Fok, Tsz Wun Wang, Ching-Ting Chang, Chi-Hsien Chin, Tsung-Yu Liao, Yi-Chen Lee, Jen-Kuang Lin, Chung-Wei Department of Computer Science and Information Engineering Taiwan Department of Electrical Engineering Taiwan Department of Engineering Science and Ocean Engineering Taiwan School of Medicine National Taiwan University Taiwan

ISBN: (纸本)9798350313505

Medical data are highly sensitive and require secure storage systems to protect patients’ privacy. Centralized databases pose significant risks in the context of a breach, since all data are concentrated in a single location. Additionally, privacy concerns often prevent medical institutions from sharing data, hindering potential research breakthroughs. To address these challenges, we propose a novel cloud storage system that utilizes homomorphic encryption and secret sharing. Our approach enables secure cloud storage of medical data and allows for secure data sharing without compromising patients’ privacy. In addition to enhancing confidentiality, our proposed approach also improves data integrity and availability. We implement a proof-of-concept that demonstrates the feasibility of our storage system. ©2023 IEEE.

关键词： Cloud storage

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Vision-Based Fixed-Time Uncooperative Aerial Target Tracking for UAV

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1322-1324页

作者： Peng Sun Siqi Li Bing Zhu Zongyu Zuo Xiaohua Xia the Seventh Research Division Beihang UniversityBeijing 100191China the School of Automation Beijing Institute of TechnologyBeijing 100081China the Department of Electrical Electronic and Computer EngineeringUniversity of PretoriaPretoria 0002South Africa

Dear Editor,In this letter,a vision-based fixed-time control is proposed for an unmanned aerial vehicle(UAV)with actuator saturation to track an uncooperative *** fixed-time control is designed in backstepping *** rel... 详细信息

关键词： Fixed cooperative letter

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