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17th International Conference on Security of Information and Networks, SIN 2024

作者： Limpek, Marton Bertalan Szabo, Geza Hevizi, Laszlo Godor, Istvan Ericsson Hungary Ltd. Budapest Hungary Budapest University of Technology and Economics Hsn Lab Faculty of Electrical Engineering and Informatics Department of Telecommunications and Artificial Intelligence Hungary

ISBN: (纸本)9798331509736

This paper presents a deep learning approach for drone navigation aimed at accurately estimating a drone's position based on Received Signal Strength (RSS) in a simulated environment. A predefined route is established, and the drone collects RSS and Inertial Measurement Unit (IMU) data while traversing it multiple times. This dataset serves as the foundation for training various neural network architectures. We create multiple training and test datasets to compare different models and identify the most effective approach for predicting the drone's location. After training, the neural networks are evaluated using distinct test data, showing that deep learning models can reliably predict a drone's position in simulation. The developed predictive models enhance the accuracy and reliability of autonomous drone operations in real-world scenarios. © 2024 IEEE.

关键词： Prediction models

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AIDetx: A Compression-Based Method for Identification of Machine-Learning Generated Text

AIDetx: A Compression-Based Method for Identification of Mac...

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2025 Data Compression Conference, DCC 2025

作者： Almeida, Leonardo Rodrigues, Pedro Magalhaes, Diogo Pinho, Armando J. Pratas, Diogo IEETA/LASI - Institute of Electronics and Informatics Engineering of Aveiro University of Aveiro Aveiro3810-193 Portugal University of Aveiro DETI - Department of Electronics Telecommunications and Informatics Aveiro3810-193 Portugal University of Helsinki DoV - Department of Virology Helsinki00014 Finland

ISBN: (纸本)9798331534714

We present AIDetx, a framework for detecting AI-generated text using finite-context models (FCMs) by classifying human and AI-generated text. Unlike deep learning classifiers, which are resource-intensive and less interpretable, AIDetx builds separate compression models for human and AI-generated text (shown in Fig 1), classifying new inputs by determining which model compresses the text more effectively. Evaluations on the HC3 and AI-human-text datasets showed strong performance, achieving F1 scores of 97% and 99%, with notable computational efficiency, no need for GPUs, while offering enhanced interpretability compared to deep learning models. © 2025 IEEE.

关键词： Deep learning

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FANET and MANET, a Support and Composition Relationship

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Computers, Materials & Continua 2025年第2期82卷 1699-1732页

作者： Carlos Andrés Tavera Romero Jesús Hamilton Ortiz Luis Carlos Rodríguez Timaná Fernando Vélez Varela Andrés Hernando Aristizábal Montufar Javier Gamboa-Cruzado COMBA R&D Laboratory Faculty of EngineeringUniversidad Santiago de CaliCali76001Colombia Development Department Closemobile R&D Telecommunications LSMadrid28070Spain GIEIAM Research Group Faculty of EngineeringUniversidad Santiago de CaliCali76001Colombia Faculty of Engineering Universidad LibreCali760031Colombia Faculty of Systems and Informatics Engineering Universidad Nacional Mayor de San MarcosLima15001Perú

This study investigates the design and implementation of Flying Ad Hoc Networks(FANETs),a network architec-ture inspired by the Mobile Ad Hoc Network(MANET)model,specifically tailored to support unmanned aerial vehicles(UAVs).As UAVs increasingly contribute to diverse fields,from surveillance to delivery,FANETs have emerged as essential in ensuring stable,dynamic communication channels among drones in *** research adopts a dual approach,combining rigorous theoretical analysis with detailed practical simulations to assess the performance,adaptability,and efficiency of FANETs in varying *** findings emphasize the ability of FANETs to manage network congestion effectively in densely populated areas,a critical feature for maintaining reliable communications in complex ***,FANETs demonstrate high potential to support critical applications,such as emergency response,disaster management,and public safety operations,where quick and coordinated action is *** study also underscores the importance of establishing a hierarchical structure among nodes within the network,which allows for more efficient data exchange and helps optimize the overall network *** this work,significant insights are offered into the design principles that can enhance UAV communication networks,providing a foundation for the development of more resilient,scalable,and efficient technological *** advancements could accelerate the deployment of UAVs across a variety of sectors,including logistics,agriculture,environmental monitoring,and *** such,this study not only contributes to the field of ad hoc networking but also holds potential for transformative impacts across industries where UAVs play an increasingly central role,promoting greater integration and operational success.

关键词： Ad hoc FANET MANET network UAV

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On the Rate-Exponent Region of Integrated Sensing and Communications with Variable-Length Coding

On the Rate-Exponent Region of Integrated Sensing and Commun...

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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Papoutsidakis, Ioannis Alexandropoulos, George C. National and Kapodistrian University of Athens Department of Informatics and Telecommunications Panepistimiopolis Ilissia Athens15784 Greece University of Illinois Chicago Department of Electrical and Computer Engineering IL60601 United States

ISBN: (纸本)9798350368369

This paper considers the achievable rate-exponent region of integrated sensing and communication systems in the presence of variable-length coding with feedback. This scheme is fundamentally different from earlier studies, as the coding methods that utilize feedback impose different constraints on the codewords. The focus herein is specifically on the Gaussian channel, where three achievable regions are analytically derived and numerically evaluated. In contrast to a setting without feedback, we show that a trade-off exists between the operations of sensing and communications. © 2025 IEEE.

关键词： Digital arithmetic

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Batch Selection for Multi-Label Classification Guided by Uncertainty and Dynamic Label Correlations 39

Batch Selection for Multi-Label Classification Guided by Unc...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhou, Ao Liu, Bin Wang, Jin Tsoumakas, Grigorios Key Laboratory of Data Engineering and Visual Computing School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China School of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)157735897X

The accuracy of deep neural networks is significantly influenced by the effectiveness of mini-batch construction during training. In single-label scenarios, such as binary and multi-class classification tasks, it has been demonstrated that batch selection algorithms preferring samples with higher uncertainty achieve better performance than difficulty-based methods. Although there are two batch selection methods tailored for multi-label data, none of them leverage important uncertainty information. Adapting the concept of uncertainty to multi-label data is not a trivial task, since there are two issues that should be tackled. First, traditional variance or entropy-based uncertainty measures ignore fluctuations of predictions within sliding windows and the importance of the current model state. Second, existing multi-label methods do not explicitly exploit the label correlations, particularly the uncertainty-based label correlations that evolve during the training process. In this paper, we propose an uncertainty-based multi-label batch selection algorithm. It assesses uncertainty for each label by considering differences between successive predictions and the confidence of current outputs, and further leverages dynamic uncertainty-based label correlations to emphasize instances whose uncertainty is synergistically expressed across multiple labels. Empirical studies demonstrate the effectiveness of our method in improving the performance and accelerating the convergence of various multi-label deep learning models. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Deep learning

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Highly Compact Wideband High-Gain Four-Element MIMO Antenna for 5G New Radio IoT

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IEEE Internet of Things Journal 2025年第12期12卷 22350-22365页

作者： Khan, Shahid Khan, Owais Shah, Syed Ahson Ali Nasir, Jamal Malik, Bilal Tariq Khan, Salahuddin Koziel, Slawomir COMSATS University Islamabad Department of Electrical and Computer Engineering Islamabad45550 Pakistan Gwangju Institute of Science and Technology Department of Electrical Engineering and Computer Science Gwangju61005 Korea Republic of King Saud University College of Engineering Riyadh11421 Saudi Arabia Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Gdansk80-233 Poland Reykjavik University Department of Engineering Engineering Optimization and Modeling Center Reykjavik101 Iceland

Wideband millimeter-wave (mm-wave) coverage is essential for the high-speed, low-latency communication required in next-generation 5G New radio (NR) Internet of Things (IoT) systems. This study develops a T-shaped four-element, highly compact wideband multiple-input multiple-output (MIMO) antenna covering the mm-wave n260 (37 40 GHz) and n259 (42 43.5 GHz) bands for 5G NR IoT applications. The antenna is designed on a 0.76 mm-thick Rogers RO4350B substrate with overall dimensions of 28 28 mm2 (3.3 3.3 ?2). For design simplicity, a T-shaped patch backed by a full-ground plane is devised to serve as the radiator of a single-element antenna with the dimensions of (Ls Ws) mm2, optimized through a systematic three-step design process for improved performance. Moreover, the design has evolved into a 4 4 orthogonal MIMO configuration, achieving improved gain, polarization diversity, and higher data rates, with each element exhibiting wideband characteristics across 11.5 GHz (36.5 48 GHz) with high gains of 9.8 dBi and 6.6 dBi at n260 and n259 5G mm-wave bands, respectively. Additionally, arc-shaped complementary split-ring resonators (CSRR) are integrated into the ground plane to significantly enhance the gain while effectively reducing mutual coupling, remarkably achieving a maximum gain of 9.8 dBi. Furthermore, the MIMO antenna exhibits an envelope correlation coefficient of less than 0.10 between any two MIMO elements encountering the required condition of © 2025 IEEE.

关键词： Microwave antennas

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The Teacher of the Future

International Journal of Emerging Technologies in Learning

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International Journal of Emerging Technologies in Learning 2023年第16期18卷 87-114页

作者： Drigas, Athanasios Chaidi, Irene Papoutsi, Chara Institute of Informatics and Telecommunications N.C.S.R. ‘Demokritos’ Athens Greece Department of Special Education University of Thessaly Volos Greece Information & Communication Systems Engineering Department University of the Aegean Samos Greece

Schools are cultural curators, along with libraries and museums. The development and use of technologies are a fact and an important tool in the evolution of the educational process, shaping new attitudes in the functioning of the educational community among parents, students, and teachers. At the same time, cultivating and improving the emotional intelligence of all those who make up the school environment will lead to well-being without stress, which is benefitial for the whole world. The teacher of the future is called and must give a resounding presence as he is the connecting link between the school, students, and parents. This article is a bibliographic review of the research results and articles to date about the school and especially the teacher of the future and deals with the existential technological identity of the educational future, its role in shaping the existential identity of the student in educational and social becoming, and the additional important skills a teacher should have for creative, happy, and well-balanced students. © 2023 by the authors of this article. Published under CC-BY.

关键词： Students

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Simultaneous Communications and Sensing with Hybrid Reconfigurable Intelligent Surfaces 19

Simultaneous Communications and Sensing with Hybrid Reconfig...

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19th European Conference on Antennas and Propagation, EuCAP 2025

作者： Gavras, Ioannis Alexandropoulos, George C. National and Kapodistrian University of Athens Department of Informatics and Telecommunications Greece University of Illinois Department of Electrical and Computer Engineering Chicago United States

ISBN: (纸本)9788831299107

Hybrid Reconfigurable Intelligent Surfaces (HRISs) constitute a new paradigm of truly smart metasurfaces with the additional features of signal reception and processing, which have been primarily considered for channel estimation and self-reconfiguration. In this paper, leveraging the simultaneous tunable reflection and signal absorption functionality of HRIS elements, we present a novel framework for the joint design of transmit beamforming and the HRIS parameters with the goal to maximize downlink communications, while simultaneously illuminating an area of interest for guaranteed localization coverage performance. Our simulation results verify the effectiveness of the proposed scheme and showcase the interplay of the various system parameters on the achievable Integrated Sensing and Communications (ISAC) performance. © 2025 European Association on Antennas and Propagation.

关键词： hybrid reconfigurable intelligent surface Integrated sensing and communications position error bound THz

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Development of the System Assurance Reference Model for Generating Modular Assurance Cases 28

Development of the System Assurance Reference Model for Gene...

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28th IEEE Pacific Rim International Symposium on Dependable Computing, PRDC 2023

作者： Wardzinski, Andrzej Jarzebowicz, Aleksander Argevide Gdańsk Poland Gdańsk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Software Engineering Gdańsk Poland

ISBN: (纸本)9798350358766

Assurance cases are structured arguments used to demonstrate specific system properties such as safety or security. They are used in many industrial sectors including automotive, aviation and medical devices. Larger assurance cases are usually divided into modules to manage the complexity and distribute the work. Each of the modules is developed to address specific goals allocated to the specific objects i.e. components of the system's architecture. Such goals are applicable for given conditions of use, for instance, operational modes or target environments. It is recommended that the complete context of each of the argument modules, encompassing information about systems/components, goals and conditions of use, is described explicitly to enable efficient management and proper use of each module. This becomes even more important for component-based design, including the use of out-of-context components. In this paper, we describe a concept of a generic System Assurance Reference Model (SARM), which bridges the gap between assurance cases and the related context models. We identify the key factors that condition the high-level assurance case structure, explain how they can drive its decomposition into assurance case modules and outline the process of creating and using context models. We present a prototype solution which implements the SARM model and enables automatic data flow between models and assurance cases. © 2023 IEEE.

关键词： Digital storage

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A Tutorial on Hybrid Feedback Control 63

A Tutorial on Hybrid Feedback Control

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Casau, Pedro Ferrante, Francesco Sanfelice, Ricardo G. University of Aveiro Department of Electronics Telecommunications and Informatics Portugal University of Perugia Department of Engineering Italy University of California Faculty of Electrical and Computer Engineering Santa Cruz United States Instituto de Telecomunicações Portugal

ISBN: (纸本)9798350316339

This tutorial paper introduces hybrid feedback control through a self-contained examination of hybrid control systems modeled by the combination of differential and difference equations with constraints. Using multiple examples, it illustrates the power of hybrid feedback control, which stems from the integration of continuous and discrete dynamics, where state variables update instantaneously at specific events while flowing continuously otherwise. The paper defines hybrid closed-loop systems as interconnected hybrid plants and controllers with designated inputs and outputs, and formalizes their solutions. It summarizes key properties of hybrid systems and reviews various control strategies, including supervisory control with logic variables to select feedback controllers, event-triggered control to minimize control input updates, and strategies using multiple Lyapunov-like functions for stabilization. Pointers to further reading and other strategies in the literature are provided. © 2024 IEEE.

关键词： Feedback control

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