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RCS Reduction and Shielding Effectiveness of 3-D Dielectric Bodies Coated with Thin Conductive Materials Using the Method of Auxiliary Sources

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IEEE Transactions on Antennas and Propagation 2025年

作者： Kouroublakis, Minas Zouros, Grigorios P. Anastassiu, Hristos T. Tsitsas, Nikolaos L. Aristotle University of Thessaloniki School of Informatics Thessaloniki54124 Greece National Technical University of Athens School of Electrical and Computer Engineering Athens15780 Greece International Hellenic University Department of Computer Informatics and Telecommunications Engineering Serres62124 Greece

Electromagnetic (EM) wave scattering and shielding effectiveness (SE) of three-dimensional (3-D) dielectric bodies coated by ultra-thin conductive materials are investigated using the method of auxiliary sources (MAS). With the increasing demand for lightweight and stealthy structures in radar, telecommunications, and aerospace applications, this study presents a theoretical framework for applying MAS for dielectric bodies coated with indium tin oxide (ITO), graphene, and MXene, and discusses numerical results for radar cross section (RCS) and SE, providing insights for future research. The application of MAS, along with the impedance matrix boundary condition (IMBC), enables accurate predictions of the scattering behavior of smooth dielectric bodies of various shapes. Monolayer graphene (MLG) and MXene are evaluated as alternatives to ITO for RCS reduction and EM shielding. The MAS theory is fully validated with the HFSS commercial software. The study demonstrates the potential of these advanced material combinations in practical applications, such as military aircraft canopies and drone sensor casings. © 1963-2012 IEEE.

关键词： Conductive plastics

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Explainable Artificial Intelligence to Enhance Data Trustworthiness in Crowd-Sensing Systems 19

Explainable Artificial Intelligence to Enhance Data Trustwor...

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19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Afzal-Houshmand, Sam Papamartzivanos, Dimitrios Homayoun, Sajad Veliou, Entso Jensen, Christian D. Voulodimos, Athanasios Giannetsos, Thanassis Cyber Security Section Denmark Ubitech Ltd. Digital Security and Trusted Computing Group Greece University of West Attica Department of Informatics and Computer Engineering Athens Greece School of Electrical and Computer Engineering National Technical Univ. of Athens Greece

ISBN: (纸本)9798350346497

Around the world there has been an advancement of IoT edge devices, that in turn have enabled the collection of rich datasets as part of the Mobile Crowd Sensing (MCS) paradigm, which in practice is implemented in a variety of safety critical applications. In spite of the advantages of such datasets, there exists an inherent data trustworthiness challenge due to the interference of malevolent actors. In this context, there has been a great body of proposed solutions which capitalize on conventional machine algorithms for sifting through faulty data without any assumptions on the trustworthiness of the source. However, there is still a number of open issues, such as how to cope with strong colluding adversaries, while in parallel managing efficiently the sizable influx of user data. In this work we suggest that the usage of explainable artificial intelligence (XAI) can lead to even more efficient performance as we tackle the limitation of conventional black box models, by enabling the understanding and interpretation of a model's operation. Our approach enables the reasoning of the model's accuracy in the presence of adversaries and has the ability to shun out faulty or malicious data, thus, enhancing the model's adaptation process. To this end, we provide a prototype implementation coupled with a detailed performance evaluation under different scenarios of attacks, employing both real and synthetic datasets. Our results suggest that the use of XAI leads to improved performance compared to other existing schemes. © 2023 IEEE.

关键词： Time series analysis

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Machine Learning Techniques for Sensor-based Human Activity Recognition with Data Heterogeneity - A Review

arXiv

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arXiv 2024年

作者： Ye, Xiaozhou Sakurai, Kouichi Nair, Nirmal Wang, Kevin I-Kai Department of Electrical Computer and Software Engineering The University of Auckland New Zealand Department of Informatics Kyushu University Japan

Sensor-based Human Activity Recognition (HAR) is crucial in ubiquitous computing, analysing behaviours through multi-dimensional observations. Despite research progress, HAR confronts challenges, particularly in data distribution assumptions. Most studies often assume uniform data distributions across datasets, contrasting with the varied nature of practical sensor data in human activities. Addressing data heterogeneity issues can improve performance, reduce computational costs, and aid in developing personalized, adaptive models with less annotated data. This review investigates how machine learning addresses data heterogeneity in HAR, by categorizing data heterogeneity types, applying corresponding suitable machine learning methods, summarizing available datasets, and discussing future challenges. © 2024, CC BY.

关键词： Ubiquitous computing

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Tackling heavy-tailed noise in distributed estimation: Asymptotic performance and tradeoffs 32

Tackling heavy-tailed noise in distributed estimation: Asymp...

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32nd Telecommunications Forum, TELFOR 2024

作者： Bajovic, Dragana Jakovetic, Dusan Kar, Soummya Vukovic, Manojlo University of Novi Sad Faculty of Technical Sciences Department of Power Electronic and Communication Engineering Serbia University of Novi Sad Faculty of Sciences Department of Mathematics and Informatics Serbia Carnegie Mellon University Department of Electrical and Computer Engineering United States University of Novi Sad Faculty of Technical Sciences Department of Fundamental Sciences Serbia

ISBN: (纸本)9798350391053

We present an algorithm for distributed estimation of an unknown vector parameter θ∗ ∈ M in the presence of heavy-tailed observation and communication noises. Heavy-tailed noises frequently appear, e.g., in densely deployed Internet of Things (IoT) or wireless sensor network systems. The presented algorithm falls within the class of consensus+innovation estimators and combats the effect of the heavy-tailed noises by adding general nonlinearities in the consensus and innovations update parts. We present results on almost sure convergence and asymptotic normality of the estimator. In addition, we provide novel analytical studies that reveal interesting tradeoffs between the system noises and the underlying network topology. © 2024 IEEE.

关键词： Internet of things

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UAV-RIS-Aided Energy-Efficient and QoS-Aware Emergency Communications Based on DRL 100

UAV-RIS-Aided Energy-Efficient and QoS-Aware Emergency Commu...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Hu, Jiawei Ju, Ying Wang, Haoyu Liu, Lei Pei, Qingqi Shee, Y.G. Zhu, Xiaojie Wu, Celimuge University of California Department of Electrical Engineering and Computer Science IrvineCA92697 United States Xidian University Guangzhou Institute of Technology Guangzhou510555 China Xi'an University of Posts Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an710121 China Universiti Tunku Abdul Rahman Department of Electrical and Electronic Engineering Kajang43000 Malaysia King Abdullah University of Science and Technology Department of Computer Electrical and Mathematical Sciences and Engineering Thuwal239556900 Saudi Arabia The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo182-8585 Japan

ISBN: (纸本)9798331517786

Ensuring reliable communication can be incredibly challenging in emergencies due to the breakdown of conventional infrastructure. However, a promising solution is on the horizon: the integration of reconfigurable intelligent surfaces (RIS) onto unmanned aerial vehicles (UAV), known as UAV-RIS. This innovative approach holds the potential to offer agile and adaptable communication services during crises, overcoming the limitations of traditional systems. This paper establishes an innovative UAV-RIS system with an active RIS to enhance the uplink communication between ground devices (GDs) and the air base station (ABS). We present an advanced communication strategy utilizing deep reinforcement learning (DRL) for UAV-RIS-supported uplink communication in dynamic emergencies. This scheme is designed to optimize the energy efficiency of the UAV-RIS communication system while adhering to quality of service (QoS) constraints for all GDs. It achieves this by jointly optimizing the trajectory of the UAV-RIS and the phase of the active RIS, ensuring efficient and reliable communication in challenging environments. To optimize the performance of the system, we propose a hierarchical Proximal Policy Optimization (H-PPO) algorithm and the upper and lower layers of H-PPO optimize the trajectory and phase control, respectively. Simulation results demonstrate that our scheme can effectively learn the communication strategy to enhance the performance of dynamic emergency communication networks. © 2024 IEEE.

关键词： active reconfigurable intelligent surface deep reinforcement learning quality of service UAV trajectory

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Simultaneous Multi-User MIMO Communications and Multi-Target Tracking with Full Duplex Radios

Simultaneous Multi-User MIMO Communications and Multi-Target...

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Islam, Md Atiqul Alexandropoulos, George C. Smida, Besma University of Illinois Department of Electrical and Computer Engineering Chicago United States National and Kapodistrian University of Athens Department of Informatics and Telecommunications Athens Greece

ISBN: (纸本)9781665459754

In this paper, we present an Integrated Sensing and Communications (ISAC) system enabled by in-band Full Duplex (FD) radios, where a massive Multiple-Input Multiple-Output (MIMO) base station equipped with hybrid Analog and Digital (A/D) beamformers is communicating with multiple DownLink (DL) users, while simultaneously estimating, via the same signaling waveforms, the Direction of Arrival (DoA) as well as the range of radar target, which are randomly distributed within its coverage area. Capitalizing on a recent reduced-complexity FD hybrid A/D beamforming architecture, we devise a joint radar target tracking and DL data transmission protocol. An optimization framework for the joint design of the massive A/D beamformers and the self-interference cancellation unit, with the dual objective of maximizing the radar tracking accuracy and DL communication performance, is presented. Our simulation results at millimeter wave frequencies using 5G NR wideband waveforms, showcase the accuracy of the radar target tracking performance of the proposed system, which simultaneously offers increased sum rate compared with benchmark schemes. © 2022 IEEE.

关键词： Millimeter waves

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"Impressively Scary:' Exploring User Perceptions and Reactions to Unraveling Machine Learning Models in Social Media Applications 25

"Impressively Scary:' Exploring User Perceptions and Reactio...

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2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： West, Jack Cagiltay, Bengisu Zhang, Shirley Li, Jingjie Fawaz, Kassem Banerjee, Suman Department of Computer Sciences University of Wisconsin-Madison MadisonWI United States School of Informatics University of Edinburgh Edinburgh United Kingdom Electrical and Computer Engineering University of Wisconsin-Madison MadisonWI United States

ISBN: (纸本)9798400713941

Machine learning models deployed locally on social media applications are used for features, such as face filters which read faces in-real time, and they expose sensitive attributes to the apps. However, the deployment of machine learning models, e.g., when, where, and how they are used, in social media applications is opaque to users. We aim to address this inconsistency and investigate how social media user perceptions and behaviors change once exposed to these models. We conducted user studies (N=21) and found that participants were unaware to both what the models output and when the models were used in Instagram and TikTok, two major social media platforms. In response to being exposed to the models' functionality, we observed long term behavior changes in 8 participants. Our analysis uncovers the challenges and opportunities in providing transparency for machine learning models that interact with local user data. © 2025 Copyright held by the owner/author(s).

关键词： Tweets

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Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems:A Medical Case Study

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Journal of Bionic engineering 2024年第1期21卷 409-425页

作者： Adel Got Djaafar Zouache Abdelouahab Moussaoui Laith Abualigah Ahmed Alsayat Faculty of informatics University of Science and Technology Houari BoumedieneAlgiersAlgeria LRIA Laboratory University of Science and Technology Houari BoumedieneAlgiersAlgeria Computer Science Department University of Mohamed El Bachir El IbrahimiBordj Bou ArreridjAlgeria Computer Science Department University of Ferhat AbbasSetifAlgeria Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq 25113Jordan Department of Computer Science College of Computer and Information SciencesJouf UniversityJoufSaudi Arabia Department of Electrical and Computer Engineering Lebanese American University13-5053ByblosLebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied science research center Applied science private universityAmman 11931Jordan School of Computer Sciences Universiti Sains Malaysia11800 PenangMalaysia School of Engineering and Technology Sunway University Malaysia27500 Petaling JayaMalaysia

Support Vector Machine(SVM)has become one of the traditional machine learning algorithms the most used in prediction and classification ***,its behavior strongly depends on some parameters,making tuning these parameters a sensitive step to maintain a good *** the other hand,and as any other classifier,the performance of SVM is also affected by the input set of features used to build the learning model,which makes the selection of relevant features an important task not only to preserve a good classification accuracy but also to reduce the dimensionality of *** this paper,the MRFO+SVM algorithm is introduced by investigating the recent manta ray foraging optimizer to fine-tune the SVM parameters and identify the optimal feature subset *** proposed approach is validated and compared with four SVM-based algorithms over eight benchmarking ***,it is applied to a disease Covid-19 *** experimental results show the high ability of the proposed algorithm to find the appropriate SVM’s parameters,and its acceptable performance to deal with feature selection problem.

关键词： Support vector machine Parameters tuning Feature selection Bioinspired algorithms Manta ray foraging optimizer

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Full Duplex Holographic MIMO for Near-Field Integrated Sensing and Communications 31

Full Duplex Holographic MIMO for Near-Field Integrated Sensi...

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31st European Signal Processing Conference, EUSIPCO 2023

作者： Gavras, Ioannis Islam, Md Atiqul Smida, Besma Alexandropoulos, George C. Department of Informatics and Telecommunications National and Kapodistrian University of Athens Greece Qualcomm Technologies Inc. Santa ClaraCA United States Department of Electrical and Computer Engineering University of Illinois Chicago United States

ISBN: (纸本)9789464593600

This paper presents an in-band Full Duplex (FD) integrated sensing and communications system comprising a holographic Multiple-Input Multiple-Output (MIMO) base station, which is capable to simultaneously communicate with multiple users in the downlink direction, while sensing targets being randomly distributed within its coverage area. Considering near-field wireless operation at THz frequencies, the FD node adopts dynamic metasurface antenna panels for both transmission and reception, which consist of massive numbers of sub-wavelength-spaced metamaterials, enabling reduced cost and power consumption analog precoding and combining. We devise an optimization framework for the FD node's reconfigurable parameters with the dual objective of maximizing the targets' parameters estimation accuracy and the downlink communication performance. Our simulation results verify the integrated sensing and communications capability of the proposed FD holographic MIMO system, showcasing the interplays among its various design parameters. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Antennas

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Applications of Particle Swarm Optimization Algorithms in Coordination between Power System Stabilizer and Flexible AC Transmission 21

Applications of Particle Swarm Optimization Algorithms in Co...

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21st IEEE International Symposium on Intelligent Systems and informatics, SISY 2023

作者： Moazzami, Majid Shahgholian, Ghazanfar Heydaran-Daroogheh-Amnyieh, Zahra Mosavi, Amirhosein Fathollahi, Arman Islamic Azad University Najafabad Branch Smart Microgrid Research Center Najafabad Iran Islamic Azad University Najafabad Branch Department of Electrical Engineering Najafabad Iran Islamic Azad University Dolatabad Branch Department of Computer Engineering Dolatabad Iran Obuda University John von Neumann Faculty of Informatics Budapest Hungary Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark

ISBN: (纸本)9798350343366

Interconnected power systems require the damping of oscillations to ensure secure operation. Traditional power system stabilizers (PSSs) may, however, not be able to sufficiently dampen inter-Area oscillations in multi-machine energy networks. PSSs and flexible AC transmission systems (FACTS) devices are frequently utilized to improve system stability. Meta-heuristic algorithms using search strategies are utilized to find near-optimal solutions. These strategies typically rely on a fitness function to evaluate candidate solutions and are inspired by natural systems. In this work, we furnish a concise overview of particle swarm optimization algorithms applied for the coordinated arrangement of PSS and FACTS controllers, presenting new directions for researchers working on meta-heuristic algorithms and coordination design of FACTS and PSS controllers for inter-Area oscillation damping in power systems. © 2023 IEEE.

关键词： Soft computing

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