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arXiv 2024年

作者： Sen, Jaydip Mayer, Joceli Dasgupta, Subhasis Nandi, Subrata Krishnaswamy, Srinivasan Mitra, Pinaki Singh, Mahendra Pratap Kundeti, Naga Prasanthi Rao, Chandra Sekhara M.V.P. Chekuri, Sudha Sree Pallapothu, Seshu Babu Nanjundan, Preethi George, Jossy P. Allali, Abdelhadi E.I. Morino, Ilham Oussous, Salma A.I.T. Beloualid, Siham Tamtaoui, Ahmed Bajit, Abderrahim Department of Data Science Praxis Business School Kolkata India Department of Computer Science and Engineering IIT Guwahati Assam India Department of Electronics and Electrical Engineering IIT Guwahati Assam India Department of Computer Science and Engineering National Institute of Technology Karnataka Surathkal Mangaluru India Department of CSE Lakireddy Balireddy College of Engineering Affiliated to JNTU Mylavaram Kakinada India Department of CSE RVR & JC college of Engineering Guntur India Department of Mathematics and statistics K.B.N. College Vijayawada India Department of Electrical Engineering Federal University of Santa Catarina Florianópolis Brazil Department of Data Science Christ University Lavasa Pune India National School of Applied Sciences Kenitra Morocco SC Department Mohammed V University Laboratory of Advanced Systems National Institute of Posts and Telecommunications Rabat Morocco

In the era of generative artificial intelligence and the Internet of Things,while there is explosive growth in the volume of data and the associated needfor processing, analysis, and storage, several new challenges are faced inidentifying spurious and fake information and protecting the privacy ofsensitive data. This has led to an increasing demand for more robust andresilient schemes for authentication, integrity protection, encryption,non-repudiation, and privacy-preservation of data. The chapters in this bookpresent some of the state-of-the-art research works in the field ofcryptography and security in computing and communications. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital storage

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IRS-Enhanced Anti-Jamming Precoding Against DISCO Physical Layer Jamming Attacks

IRS-Enhanced Anti-Jamming Precoding Against DISCO Physical L...

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IEEE International Conference on Communications (ICC)

作者： Huan Huang Hongliang Zhang Yi Cai Yunjing Zhang A. Lee Swindlehurst Zhu Han Electronic Information School Soochow University Suzhou China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China Department of Electrical and Computer Engineering University of Houston Houston USA Center for Pervasive Communications and Computing University of California Irvine USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Illegitimate intelligent reflective surfaces (IRSs) can pose significant physical layer security risks on multi-user multiple-input single-output (MU-MISO) systems. Recently, a DISCO approach has been proposed an illegitimate IRS with random and time-varying reflection coefficients, referred to as a “disco” IRS (DIRS). Such DIRS can attack MU-MISO systems without relying on either jamming power or channel state information (CSI), and classical anti-jamming techniques are in-effective for the DIRS-based fully-passive jammers (DIRS-based FPJs). In this paper, we propose an IRS-enhanced anti-jamming precoder against DIRS-based FPJs that requires only statistical rather than instantaneous CSI of the DIRS-jammed channels. Specifically, a legitimate IRS is introduced to reduce the strength of the DIRS-based jamming relative to the transmit signals at a legitimate user (LU). In addition, the active beamforming at the legitimate access point (AP) is designed to maximize the signal-to-jamming-plus-noise ratios (SJNRs). Numerical results are presented to evaluate the effectiveness of the proposed IRS-enhanced anti-jamming precoder against DIRS-based FPJs.

关键词： Array signal processing Precoding Computational modeling Interference MISO communication Physical layer security Reflection coefficient

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Energy-Efficient Design in STAR-RIS Assisted Communication System with Antenna Selection

Energy-Efficient Design in STAR-RIS Assisted Communication S...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Guangyang Zhang Yang Lu Bo Ai Zhangdui Zhong Zhiguo Ding Tony Q. S. Quek School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Computer and Information Technology Beijing Jiaotong University Beijing China Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong University Beijing China Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi UAE Department of Electrical and Electronic Engineering University of Manchester Manchester UK Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore

This paper investigates the energy-efficient beamforming design in a simultaneous transmission and reflection-reconfigurable intelligent surface (STAR-RIS) assisted wireless communication system, where the antenna selection scheme is adopted. An energy efficiency (EE) maximization problem is formulated by optimizing the transmit beamformers and the phase shift vectors subject to the power budget constraint of the base station (BS), the maximum transmit power constraint per antenna and the users' data rate requirements. An alternating optimization-based algorithm is proposed to tackle the coupled variables, and the quadratic transform is used to deal with the fractional formulations. Simulation results demonstrate that the antenna selection scheme can significantly improve the EE performance by suppressing the energy consumption due to massive antennas. With the assistance of the STAR-RIS, the EE performance is further enhanced.

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Secure state estimation over Markov wireless communication channels

Secure state estimation over Markov wireless communication c...

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IEEE Conference on Decision and Control

作者： Anastasia Impicciatore Anastasios Tsiamis Yuriy Zacchia Lun Alessandro D’Innocenzo George J. Pappas Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Automatic Control Laboratory ETH Zürich Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA United States

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This note studies state estimation in wireless networked control systems with secrecy against eavesdropping. Specifically, a sensor transmits a system state information to the estimator over a legitimate user link, and an eavesdropper overhears these data over its link independent of the user link. Each connection may be affected by packet losses and is modeled by a finite-state Markov channel (FSMC), an abstraction widely used to design wireless communication systems. This paper presents a novel concept of optimal mean square expected secrecy over FSMCs and delineates the design of a secrecy parameter requiring the user mean square estimation error (MSE) to be bounded and eavesdropper MSE unbounded. We illustrate the developed results on an example of an inverted pendulum on a cart whose parameters are estimated remotely over a wireless link exposed to an eavesdropper.

关键词： Wireless communication Wireless sensor networks Estimation error Networked control systems Channel estimation Packet loss Markov processes

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A Leader-Follower Based Parallel Accelerated Particle Swarm Optimization Algorithm for Smart Grid Resource Allocation

A Leader-Follower Based Parallel Accelerated Particle Swarm ...

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Annual North-American Power Symposium

作者： Sheroze Liaquat Robert Fourney Timothy M. Hansen Tanveer Hussain Berk Celik Department of Electrical Engineering and Computer Science South Dakota State University Brookings USA Power and Energy Systems Idaho National Laboratory Idaho Falls ID USA AVENUES Université de Technologie de Compiègne Compiègne France

Smart grid resource allocation (SGRA) is a large-scale demand response optimization problem to lower the electricity cost of customers by intelligently shifting their schedulable devices via an aggregator. The SGRA problem aims to maximize the aggregator profit while still considering the inconvenience and the availability constraints of each customer's assets. A heuristic approach provides a reliable method to find near-optimal solutions to non-convex, complex, and multi-dimensional problems by reducing the computational time and not relying on gradients. To further improve the computational time of the heuristics, high-performance parallel computing concepts can be used to divide the formulated problem into smaller sub-problems. This research proposes a leader-follower based parallel Accelerated Particle Swarm Optimization (APSO) to find near-optimal solutions of SGRA using the OpenMP framework in MATLAB. The leader-follower topology allows the parallel execution of each particle, resulting in lower execution time. The proposed parallel APSO was both significantly faster (2 - 7×) than existing SGRA literature methods, and achieves similar aggregator profit, customer savings, and peak demand reduction.

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Absolute Localization in Feature-Poor Industrial Confined Spaces

Absolute Localization in Feature-Poor Industrial Confined Sp...

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IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Rune Y. Brogaard Robert A. Hewitt Sarah Etter Arash Kalantari Evangelos Boukas Faculty of Electrical Engineering Technical University of Denmark Kgs Lyngby Denmark Mobility and Robotic Systems Section NASA Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA Department of Computer Science University of Texas Austin TX USA

Autonomous inspection of dark, confined, and feature-poor spaces requires robotic platforms to utilize accurate and reliable localization systems for safe and reliable operation. This paper presents an absolute localization system for highly feature-poor spaces, using visual inertial odometry and GPU-based point cloud registrations for limited field-of-view sensors. The extracted structural elements from sensor scans, along side IMU measurements, are used to limit the search area for the GPU-based point cloud registrations. We employ Stein-ICP which is an uncertainty aware variant of ICP. The 3D registrations are then fused with a visual-inertial odometry estimate in an Extended Kalman Filter to provide a fast and accurate absolute pose estimate. The proposed localization system is tested in both a simulated environment and in a mock-up model of a chemical distillation column - both highly feature-poor areas.

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Creating embedded radiofrequency structures using polyjet material jetting 26

Creating embedded radiofrequency structures using polyjet ma...

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26th Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference, SFF 2015

作者： Dumene, Richard L. Kennedy, Paul Williams, Christopher B. Sweeney, Dennis Earle, Greg Design Research and Education for Additive Manufacturing Systems Laboratory Department of Mechanical Engineering Virginia Tech United States Director of Instructional Laboratories Bradley Department of Electrical and Computer Engineering Center for Space Science and Engineering Research Bradley Department of Electrical and Computer Engineering

Embedding of integrated systems via Additive Manufacturing (AM) offers the potential to save weight, space, and time in the production of electronics and vehicles. Of specific interest are embedded electrical systems that operate in the radiofrequency (RF) range as they have great potential utility in communication systems and aircraft avionics including navigation. However, systems in this frequency range pose unique manufacturing challenges such as the need to minimize impedance discontinuities in the system. In this work, the authors explore various techniques for embedding RF structures such as antennas and filters via a multi-material jetting AM process. Specifically, the dielectric constants and loss tangents of Vero White and Tango Black polymers were determined to facilitate the design of RF structures with these materials. It is shown that measurements of S-parameters of the resultant embedded RF structures approach or match the performance of non-embedded electronics. © SFF *** rights reserved.

关键词： Embeddings

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Electromagnetic Channel Modeling and Capacity Analysis for HMIMO Communications

arXiv

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arXiv 2025年

作者： Wei, Li Yuan, Shuai S.A. Huang, Chongwen Zhang, Jianhua Bader, Faouzi Zhang, Zhaoyang Muhaidat, Sami Debbah, Mérouane Yuen, Chau School of Electrical and Electronics Engineering Nanyang Technological University Singapore639798 Singapore College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China Technology Innovation Institute Masdar City Abu Dhabi United Arab Emirates KU 6G Research Center Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada KU 6G Research Center Khalifa University of Science and Technology P O Box 127788 Abu Dhabi United Arab Emirates

Advancements in emerging technologies, e.g., reconfigurable intelligent surfaces and holographic MIMO (HMIMO), facilitate unprecedented manipulation of electromagnetic (EM) waves, significantly enhancing the performance of wireless communication systems. To accurately characterize the achievable performance limits of these systems, it is crucial to develop a universal EM-compliant channel model. This paper addresses this necessity by proposing a comprehensive EM channel model tailored for realistic multi-path environments, accounting for the combined effects of antenna array configurations and propagation conditions in HMIMO communications. Both polarization phenomena and spatial correlation are incorporated into this probabilistic channel model. Additionally, physical constraints of antenna configurations, such as mutual coupling effects and energy consumption, are integrated into the channel modeling framework. Simulation results validate the effectiveness of the proposed probabilistic channel model, indicating that traditional Rician and Rayleigh fading models cannot accurately depict the channel characteristics and underestimate the channel capacity. More importantly, the proposed channel model outperforms free-space Green’s functions in accurately depicting both near-field gain and multi-path effects in radiative near-field regions. These gains are much more evident in tri-polarized systems, highlighting the necessity of polarization interference elimination techniques. Moreover, the theoretical analysis accurately verifies that capacity decreases with expanding communication regions of two-user communications. Copyright © 2025, The Authors. All rights reserved.

关键词： Antenna arrays

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Exploring the Frontiers of Synthetic Image-Based Deep Learning Training in Digital X-ray Radiography.

e-Journal of Nondestructive Testing

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e-Journal of Nondestructive Testing 2024年第8期29卷

作者： Hena, Bata Wei, Ziang Perron, Luc Castanedo, Clemente Ibarra Maldague, Xavier Department of Electrical and Computer Engineering Université Laval 1065 Ave de la Médecine Quebec CityQCG1V 0A6 Canada Computer Vision and Systems Laboratory Department of Electrical and Computer Engineering Université Laval 1065 Ave de la Médecine Quebec CityQCG1V 0A6 Canada GI Lab Solutions 475 Pruneau Ave Québec CityQCG1M 2J8 Canada

Industrial radiography is a pivotal non-destructive testing (NDT) method that ensures quality and safety in a wide range of industrial sectors. Nevertheless, the conventional human-based approaches to carrying out industrial radiography are prone to challenges that negatively impact the accuracy and efficiency of defect detection. To solve this challenge, numerous computer-based alternatives have been developed, including Automated Defect Recognition (ADR) using deep learning algorithms. At the core of training, these ADR algorithms demand large volumes of qualitative data that should be representative of real-world cases to be expected during deployment. However, the availability of digital X-ray radiography data, especially for open research, is limited by non-disclosure contractual terms in the industry. In this study, we present a pipeline that is capable of modelling synthetic images based on real digital X-ray radiography images. This is achieved through a systematic analysis of the intensity distribution, considering grey value (GV) statistical uniqueness related to exposure conditions used during image acquisition, type of imaged component, material thickness variations, X-ray beam divergence, anode heel effect, scatter radiation, edge delineation, etc. The generated synthetic images were exclusively utilized to train a deep learning model, yielding an impressive model performance with mean intersection over union (IoU) of 0.93, and mean dice coefficient of 0.96 when tested on real unseen digital X-ray radiography images. The presented methodology is scalable and adaptable, making it suitable for diverse industrial applications. © 2024 The Authors.

关键词： X ray radiography

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Hybrid Disassembly Line Balancing for Human-robot Collaborative Remanufacturing

Hybrid Disassembly Line Balancing for Human-robot Collaborat...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Feng Guo XiWang Guo MengChu Zhou Weitian Wang ShuJin Qin Qi Kang College of Information and Control Engineering Liaoning Petrochemical University Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Collaborative Robotics and Smart Systems Laboratory (CRoSS Lab) Montclair State University Montclair NJ USA College of Economics and Management Shangqiu Normal University Shangqiu P R. China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

As technologies advance rapidly, the urgency of remanufacturing is escalating. Efficient disassembly processes are crucial at the outset of remanufacturing. This work proposes an innovative disassembly scheme aimed at amplifying efficiency through the utilization of parallelization and human-robot collaboration in the context of a hybrid disassembly line. A single-objective mixed-integer programming model is developed to optimize disassembly profit. A discrete salp swarm algorithm is proposed to solve it since it is NP-hard. We have proposed and integrated uniform variation and two-point crossover operators in this algorithm. After comparing its results with those of the exact solver and other intelligent optimization methods, we conclude its competitive performance in both solution quality and efficiency.

关键词： computer aided software engineering Automation Optimization methods Human-robot interaction Collaboration Programming

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