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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Dejan Milić Nenad Petrović Milan Jović Radiša Stefanović Mejdin Saliji Elida Suljović Faculty of Electronic Engineering University of Niš Niš Serbia Applied Engineering Sciences Academy of Vocational Studies Polytechnic Belgrade Serbia Faculty of Mathematics and Natural Sciences Cyril and Methodius University Skopje Republic of North Macedonia Informatics and Computer Science Technical School in Novi Pazar Novi Pazar Serbia

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

In this paper, a micro-MRC receiver with L branches operating in a correlated gamma-shadowed η-μ fading channel is considered. For such a system, the channel capacity (CC) is determined based on the maximum signal-to-noise ratio (SNR) at the L branches at the input of the MRC receiver. The results are presented graphically to illustrate the impact of different system parameters on performance and the improvements that result from the advantages of combined diversity. Additionally, we introduce the application of Large Language Models (LLMs) to make network experimentation more practical, using the previously presented expression as a case study. Moreover, a Vision Language Model (VLM) aided method aiming to make model-driven network design and experimentation more convenient is introduced and evaluated for the previously considered case study

关键词： Fading channels Wireless communication Visualization Channel capacity System performance Scalability Large language models Receivers Signal to noise ratio

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Pose Estimation of Spacecraft Using Dual Transformers and Efficient Bayesian Hyperparameter Optimization

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International Journal of Advanced computer Science and Applications 2025年第4期16卷 629-644页

作者： Raja, N. Kannaiya Ramesh, Janjhyam Venkata Naga El-Ebiary, Yousef A. Baker Muniyandy, Elangovan Reddy, N. Konda Kumar, Vanipenta Ravi Devarasetty, Prasad School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Bhopal466114 India Department of CSE Graphic Era Hill University Dehradun248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun248002 India Faculty of Informatics and Computing UniSZA University Malaysia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Engineering Mathematics K L University Greenfields Guntur Dist Andhra Pradesh Vaddeswaram522302 India Department of Mathematics Annamacharya University New Boyanapalli Rajampet India Department of Computer Science and Engineering DVR & Dr HS MIC College of Technology Andhra Pradesh Kanchikacherla India

Spacecraft pose estimation is an essential contribution to facilitating central space mission activities like autonomous navigation, rendezvous, docking, and on-orbit servicing. Nonetheless, methods like Convolutional Neural Networks (CNNs), Simultaneous Localization and Mapping (SLAM), and Particle Filtering suffer significant drawbacks when implemented in space. Such techniques tend to have high computational complexity, low domain generalization capacity for varied or unknown conditions (domain generalization problem), and accuracy loss with noise from the space environment causes such as fluctuating lighting, sensor limitations, and background interference. In order to overcome these challenges, this study suggests a new solution through the combination of a Dual-Channel Transformer Network with Bayesian Optimization methods. The innovation is at the center with the utilization of EfficientNet, augmented with squeeze-and-excitation attention modules, to extract feature-rich representations without sacrificing computational efficiency. The dual-channel architecture dissects satellite pose estimation into two dedicated streams—translational data prediction and orientation estimation via quaternion-based activation functions for rotational precision. Activation maps are transformed into transformer-compatible sequences via 1×1 convolutions, allowing successful learning in the transformer's encoder-decoder system. To maximize model performance, Bayesian Optimization with Gaussian Process Regression and the Upper Confidence Bound (UCB) acquisition function makes the optimal hyperparameter selection with fewer queries, conserving time and resources. This entire framework, used here in Python and verified with the SLAB Satellite Pose Estimation Challenge dataset, had an outstanding Mean IOU of 0.9610, reflecting higher accuracy compared to standard models. In total, this research sets a new standard for spacecraft pose estimation, by marrying the versatility of deep le

关键词： Convolutional neural networks

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A gravitational meta-heuristic algorithm for solving resource-constrained project scheduling problems

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Sadhana - Academy Proceedings in engineering Sciences 2025年第2期50卷 1-14页

作者： Attari, Mahdi Yousefi Nejad Ala, Ali Simic, Vladimir Pamucar, Dragan Aydin, Nezir Department of Industrial Engineering Bon.C. Islamic Azad University Bonab Iran Tamil Nadu Thandalam Chennai602105 India School of Mechanical and Materials Engineering University College Dublin DublinD04 V1W8 Ireland Faculty of Transport and Traffic Engineering University of Belgrade Vojvode Stepe 305 Belgrade11010 Serbia Department of Industrial Engineering and Management College of Engineering Yuan Ze University Yuandong Rd. Zhongli Dist. Taoyuan City320315 Taiwan Department of Computer Science and Engineering College of Informatics Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of Transport and Logistics Competence Centre Vilnius Gediminas Technical University Vilnius Lithuania College of Science and Engineering Hamad Bin Khalifa University Doha34110 Qatar Department of Industrial Engineering Yildiz Technical University Besiktas Istanbul34349 Turkey

In recent years, the resource-constrained project scheduling problem (RCPSP) has been recognized as one of the most well-known problems in the project management context. Project managers always try to assign the resources to the project activities optimally in a short period. However, this is a challenging and complex problem that is categorized as an NP-hard problem. This paper proposes a novel gravitational search algorithm (GSA) to solve RCPSP for organizations and project managers in two steps. In the first step, a mathematical model for the RCPSP is developed, including the problem's purposes, constraints and limitations, and several factor levels. In the second step, the GSA algorithm is deployed to solve the problem efficiently. The suggested GSA's effectiveness is demonstrated by simulation results based on benchmarks and compared with various existing algorithms. The findings reveal that the proposed technique improved existing algorithms and decreased the gap. © Indian Academy of Sciences 2025.

关键词： Project management

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On the Difficulty of NOT being Unique: Fingerprinting Users from Wi-Fi Data in Mobile Devices 25

On the Difficulty of NOT being Unique: Fingerprinting Users ...

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Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing

作者： Mariana Cunha Ricardo Mendes Yves-Alexandre de Montjoye João P. Vilela CRACS/INESC TEC CISUC and Department of Computer Science Faculty of Sciences University of Porto Porto Portugal CISUC and Department of Informatics Engineering University of Coimbra Coimbra Portugal Imperial College London London United Kingdom

ISBN: (纸本)9798400706295

The pervasiveness of mobile devices has fostered a multitude of services and applications, but also raised serious privacy concerns. In order to avoid users' tracking and/or users' fingerprinting, smartphones have been tightening the access to unique identifiers. Nevertheless, smartphone applications can still collect diverse data from available sensors and smartphone resources. Using real-world data from a field study we performed, this paper demonstrates the possibility of fingerprinting users from Wi-Fi data in mobile devices and the consequent privacy impact. From the performed analysis, we concluded that a single snapshot of a set of scanned Wi-Fi BSSIDs (MAC addresses) per user is enough to uniquely identify about 99% of the users. In addition, the most frequent Wi-Fi BSSID is sufficient to re-identify more than 90% of the users, a percentage that goes up to 97% of the users with the top-2 scanned BSSIDs. The Wi-Fi SSID (network name) also leads to a re-identification risk of about 83% and 97% with 1 and 2 of the strongest Wi-Fi Access Points (APs), respectively.

关键词： privacy

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Fast Computation of the Discrete Fourier Transform Rectangular Index Coefficients

arXiv

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arXiv 2025年

作者： Queiroz, Saulo Vilela, João P. Ng, Benjamin Koon Kei Lam, Chan-Tong Monteiro, Edmundo PR Ponta Grossa Brazil Portugal CRACS INESCTEC CISUC the Department of Computer Science Faculty of Sciences University of Porto Portugal Macao Polytechnic University China Department of Informatics Engineering the University of Coimbra CISUC Portugal

In [1], authors show that the "square index coefficients" (SIC) of the N-point discrete Fourier transform (DFT), (i.e., Xk√N, k = 0, 1, · · ·, √N − 1) can be compressed from N to √N points, thereby speeding up the DFT computation accordingly. Following up on that, in this article we generalize SICs into what we refer to as rectangular index coefficients (RICs) of the DFT, formalized as XkL, k = 0, 1, · · ·, C − 1, in which the integers C and L are generic roots of N such that N = LC. We present an algorithm to compress the N-point input signal x into a C-point signal xˆ at the expense of O(N) complex sums and no complex multiplication. We show that a DFT on xˆ is equivalent to a DFT on the RICs of x. In case where specific frequencies of x are of interest (as turns out to be in harmonic analysis), one can conveniently adjust the signal parameters (e.g., frequency resolution) to match RICs to those frequencies and use our algorithm to compute them significantly faster. If N is a power of two (as usual, due to the fast Fourier transform (FFT) algorithm’s requirement), then C can be any power of two in the range [2, N/2] and one can use our algorithm along with the FFT to compute all RICs in O(C log C) time complexity. © 2025, CC BY.

关键词： Discrete Fourier transforms

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Editorial – Elsevier smart health special issue: Advancing ICT for health, accessibility, and wellbeing

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Smart Health 2025年 36卷

作者： Achilleos, Achilleas Pissaloux, Edwige Papadopoulos, George A. Velazquez, Ramiro Faculty of Engineering Universidad Panamericana Mexico Department of Computer Science University of Cyprus 75 Kallipoleos St P.O Box 20537 Nicosia CY 1678 Cyprus Physics Department University of Rouen France Department of Electrical Engineering Computer Engineering and Informatics Frederick University Cyprus

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A Novel Double Pruning method for Imbalanced Data using Information Entropy and Roulette Wheel Selection for Breast Cancer Diagnosis

arXiv

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arXiv 2025年

作者： Soufiane, Bacha Ning, Huansheng Mostefa, Belarbi Sarwatt, Doreen Sebastian Dhelim, Sahraoui School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China of University of Tiaret University of Tiaret Faculty of Mathematics and Informatics Department of Computer Science BP 78 Zaâroura Tiaret14000 Algeria School of Computing Dublin City University Ireland

—Accurate illness diagnosis is vital for effective treatment and patient safety. Machine learning models are widely used for cancer diagnosis based on historical medical data. However, data imbalance remains a major challenge, leading to hindering classifier performance and reliability. The SMOTEBoost method addresses this issue by generating synthetic data to balance the dataset, but it may overlook crucial overlapping regions near the decision boundary and can produce noisy samples. This paper proposes RE-SMOTEBoost, an enhanced version of SMOTEBoost, designed to overcome these limitations. Firstly, RE-SMOTEBoost focuses on generating synthetic samples in overlapping regions to better capture the decision boundary using roulette wheel selection. Secondly, it incorporates a filtering mechanism based on information entropy to reduce noise, and borderline cases and improve the quality of generated data. Thirdly, we introduce a double regularization penalty to control the synthetic samples’ proximity to the decision boundary and avoid class overlap. These enhancements enable higher-quality oversampling of the minority class, resulting in a more balanced and effective training dataset. The proposed method outperforms existing state-of-the-art techniques when evaluated on imbalanced datasets. Compared to the top-performing sampling algorithms, RE-SMOTEBoost demonstrates a notable improvement of 3.22% in accuracy and a variance reduction of 88.8%. These results indicate that the proposed model offers a solid solution for medical settings, effectively overcoming data scarcity and severe imbalance caused by limited samples, data collection difficulties, and privacy constraints. Copyright © 2025, The Authors. All rights reserved.

关键词： Patient treatment

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A Dynamic Optimization Framework for Computation Rate Maximization in UAV-Assisted Mobile Edge Computing

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IEEE Transactions on Vehicular Technology 2025年

作者： Chen, Yang Pi, Dechang Yang, Shengxiang Xu, Yue Wang, Bi Qin, Shuo Wang, Yintong Xi'an University of Science and Technology Artificial Intelligence and Computer Science Xi'an China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China De Montfort University School of Computer Science and Informatics LeicesterLE1 9BH United Kingdom Jiangxi University of Science and Technology Faculty of Information Engineering Ganzhou China Xi'an University of Posts and Telecommunications School of Computer Science and Technology Xi'an China Nanjing Xiaozhuang University School of Information Engineering Nanjing China

Mobile edge computing (MEC) significantly boosts the computing power and reduces the energy consumption of Internet of Things (IoT) devices, serving as a valuable complement to cloud computing. The application of unmanned aerial vehicle (UAV) for MEC systems can effectively alleviate the issue of insufficient or damaged communication facilities in remote areas, further expanding the scope of MEC applications. In this article, we present a system model for UAV-assisted wireless-powered MEC systems in a dynamic environment with the objective of maximizing the computation rate of user devices. Due to the complexity of the optimization objective in dynamic environments, we propose a swarm intelligence-based optimization framework with a mechanism for responding to environmental changes, which is intended to enhance population diversity in both static and dynamic environments with the aim of overcoming premature convergence. We integrate particle swarm optimization and harmony search into the proposed framework, naming them DOPSO and DOHS, respectively. Simulation results for two offloading modes in UAV-assisted MEC systems indicate that the proposed framework significantly outperforms other dynamic optimization algorithms. © 1967-2012 IEEE.

关键词： Energy utilization

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Supply Chain Sustainability in Disruption: SC Intelligence, Customer Knowledge Transfer, and the Mediating Role of IS/IT

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IEEE engineering Management Review 2025年

作者： Ratna, Silvia Saide, Saide Rater, Salya Svyazhanovna, Baizakova Saule Herzavina, Herzavina Faculty of Information Technology Department of Informatics Engineering and Department of Information Systems Banjarmasin Indonesia State Islamic University of Sultan Syarif Kasim Riau Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau Department of Information Systems Faculty of Science and Technology Indonesia PRO Knowledge Indonesia Pekanbaru Indonesia Universitas Pahlawan Tuanku Tambusai Indonesia Lembaga Enreach UIN Suska Riau Indonesia Politeknik Aceh Selatan Department of Informatics Engineering Aceh Indonesia Information Communication Technologies Robotics in Arkalyk Pedagogical Institute Master of Natural Sciences Educational Program for the Informatics Computer Science Kazakhstan Universitas Pahlawan Tuanku Tambusai Department of Informatics Engineering Indonesia National Taiwan University of Science and Technology Taiwan

Knowledge resource and information system/technology (IS/IT) capability have been considered to improve firm performance, however there is still a gap regarding the sustainability of supply chain to face and recover from disruption (e.g., COVID-19). Questionnaire-based surveys was adopted and received feedback from sixty (160) Indonesian companies or about 28.07% of response rate. © 1973-2011 IEEE.

关键词： customer knowledge transfer disruption information system/technology (IS/IT) responding knowledge management resource-based view (RBV) Supply chain (SC) sustainability supply chain knowledge transfer

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Visual data security in healthcare and cloud applications using a novel 2D-HCFCM, polynomial chains and NLDSR

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Connection Science 2025年第1期37卷

作者： Khan, Sajid Peng, Hao Haseeb, Abdul Usman, Sardar College Computer Science and Technology Zhejiang Normal University Jinhua China Zhejiang Institute of Photoelectronics Jinhua China Faculty of College of Computer Science and Technology Zhejiang Normal University Jinhua China Faculty of Engineering and Technology HITEC University Taxila Taxila Pakistan Faculty of School of Informatics and Robotics Institute for Arts and Culture Lahore Pakistan

Over the past two decades, numerous encryption schemes leveraging chaotic systems have been developed to ensure data integrity in healthcare and cloud environments. In this paper, we first assess the performance of a two-dimensional Higher Complexity Folium Chaotic Map (2D-HCFCM) and then introduce a robust encryption algorithm for 8-bit and 24-bit images. The algorithm constructs polynomials of (Formula presented.) with 2D-HCFCM, followed by polynomial chaining and 8-bit conditional logical operation ((Formula presented.)), driven by (Formula presented.) to introduce additional dynamic control. Furthermore, the Nested Layered with Diagonal Swapping and Relocation (NLDSR) technique introduces nonlinearity and resistance to chosen plaintext attacks. In summary, the algorithm offers an encryption key of 800 bits and demonstrates satisfactory security performance, with a (Formula presented.) of 236.0598, an NBCR of 49.7%, and an NPCR value of 99.6389, with optimal computational efficiency. The security analysis confirms that the algorithm is effective in preserving the integrity of visual data. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Network security

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