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arXiv 2025年

作者： Vaarandi, Risto Tsiopoulos, Leonidas Visky, Gabor Rehman, Muaan Ur Bahşi, Hayretdin Department of Software Science Tallinn University of Technology Tallinn Estonia School of Informatics Computing and Cyber Systems Northern Arizona University United States

In recent years, many cyber incidents have happened in the maritime sector, targeting the information technology (IT) and operational technology (OT) infrastructure. Although several systematization-of-knowledge papers have been published in the maritime field, none of the previous studies has focused on cyber security monitoring, which aims at timely detection of cyber attacks with automated methods. The current article addresses this research gap and surveys the methods, algorithms, tools and architectures used for cyber security monitoring in the maritime sector. For the survey, a systematic literature review of cyber security monitoring studies is conducted in this article, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The first contribution of this article is the bibliometric analysis of related literature and the identification of the main research themes in previous works. For that purpose, our article presents a taxonomy for existing studies which highlights the main properties of maritime cyber security monitoring research. The second contribution of this article is an in-depth analysis of previous works and the identification of research gaps and limitations in existing literature. Based on our findings, we outline future research directions for cyber security monitoring in the maritime field. © 2025, CC BY.

关键词： Network intrusion

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Reinforcement Learning-based Optimization of EBike Charging infrastructure

Reinforcement Learning-based Optimization of EBike Charging ...

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IEEE/ACM International Symposium on Big Data computing (BDC)

作者： Muddsair Sharif Huseyin Seker Faculty of Computing Engineering and the Built Environment Birmingham City University Birmingham U.K. Department of Information Systems College of Computing and Informatics The University of Sharjah Sharjah UAE

ISBN: (数字)9798350367300

ISBN: (纸本)9798350367317

This paper presents a novel technique for enhancing the allocation of resources in the charging infrastructure for e-bikes by employing deep reinforcement learning (DRL) in a context-specific manner. With the evolving transportation land-scape and the increasing popularity of electric micro-mobility solutions, efficient resource management plays a vital role. The methodology involves utilizing deep Q networks (DQN) in virtual environments to dynamically allocate charging resources based on contextual parameters. Through empirical analysis, we demonstrate the efficacy of our approach in achieving optimal resource allocation while considering the needs of diverse stakeholders. Findings suggest that the DQN model, when integrated with context-awareness and stakeholder objectives, enables efficient resource allocation, maximize fleet utilization, ensures charging station availability, enhances user satisfaction, and promotes environmental sustainability. The findings of this study offer valuable insights for policymakers, urban planners, and industry stakeholders seeking to enhance the sustainability and effectiveness of micro-mobility services in urban settings. Overall, this study contributes to the advancement of sustainable urban mobility solutions and underscores the potential of DRL in addressing complex urban transportation challenges.

关键词： Computational modeling Green products Transportation Charging stations Resource management Stakeholders Sustainable development Optimization Carbon emissions Context modeling

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A Quantum Algorithm for the Classification of Patterns of Boolean Functions

arXiv

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arXiv 2025年

作者： Andronikos, Theodore Bitsakos, Constantinos Nikas, Konstantinos Goumas, Georgios I. Koziris, Nectarios Department of Informatics Ionian University 7 Tsirigoti Square Corfu49100 Greece Computing Systems Laboratory National Technical University of Athens Greece

This paper introduces a novel quantum algorithm that is able to classify a hierarchy of classes of imbalanced Boolean functions. The fundamental characteristic of imbalanced Boolean functions is that the proportion of elements in their domain that take the value 0 is not equal to the proportion of elements that take the value 1. For every positive integer n, the hierarchy contains a class of Boolean functions defined based on their behavioral pattern. The common trait of all the functions belonging to the same class is that they possess the same imbalance ratio. Our algorithm achieves classification in a straightforward manner as the final measurement reveals the unknown function with probability 1. Let us also note that the proposed algorithm is an optimal oracular algorithm because it can classify the aforementioned functions with a single query to the oracle. At the same time we explain in detail the methodology we followed to design this algorithm in the hope that it will prove general and fruitful, given that it can be easily modified and extended to address other classes of imbalanced Boolean functions that exhibit different behavioral patterns. © 2025, CC BY.

关键词： Boolean functions

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SP-DSTS-MIMO Scheme-Aided H.266 for Reliable High Data Rate Mobile Video Communication

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Computers, Materials & Continua 2023年第1期74卷 995-1010页

作者： Khadem Ullah Nasru Minallah Durre Nayab Ishtiaque Ahmed Jaroslav Frnda Jan Nedoma Department of Computer Systems Engineering University of Engineering and Technology PeshawarPeshawar25000Pakistan National Centre in Big Data and Cloud Computing University of Engineering and Technology Peshawar(NCBC-UETP)Peshawar25000Pakistan Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and CommunicationsUniversity of Zilina01026ZilinaSlovakia Department of Telecommunications Faculty of Electrical Engineering and Computer ScienceVSB-Technical University of OstravaOstrava-PorubaCzech Republic

With the ever growth of Internet users,video applications,and massive data traffic across the network,there is a higher need for reliable bandwidth-efficient multimedia *** Video Coding(VVC/H.266)is finalized in September 2020 providing significantly greater compression efficiency compared to Highest Efficient Video Coding(HEVC)while providing versatile effective use for Ultra-High Definition(HD)*** article analyzes the quality performance of convolutional codes,turbo codes and self-concatenated convolutional(SCC)codes based on performance metrics for reliable future video *** advent of turbo codes was a significant achievement ever in the era of wireless communication approaching nearly the Shannon *** codes are operated by the deployment of an interleaver between two Recursive Systematic Convolutional(RSC)encoders in a parallel *** RSC encoders may be operating on the same or different architectures and code *** proposed work utilizes the latest source compression standards H.266 and H.265 encoded standards and Sphere Packing modulation aided differential Space Time Spreading(SP-DSTS)for video transmission in order to provide bandwidth-efficient wireless video ***,simulation results show that turbo codes defeat convolutional codes with an averaged E_(b)/N_(0) gain of 1.5 dB while convolutional codes outperformcompared to SCC codes with an E_(b)/N_(0) gain of 3.5 dBatBit ErrorRate(BER)of 10−*** Peak Signal to Noise Ratio(PSNR)results of convolutional codes with the latest source coding standard of H.266 is plotted against convolutional codes with H.265 and it was concluded H.266 outperform with about 6 dB PSNR gain at E_(b)/N_(0) value of 4.5 dB.

关键词： H.265 RSC turbo codes SCC SP-DSTS BP-CNN BER PSNR

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Quantum Repeaters Enhanced by Vacuum Beam Guides

arXiv

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arXiv 2025年

作者： Gan, Yu Azari, Mohadeseh Chandra, Nitish Kumar Jin, Xin Cheng, Jinglei Seshadreesan, Kaushik P. Liu, Junyu Department of Computer Science School of Computing & Information University of Pittsburgh PittsburghPA15260 United States Department of Informatics & Networked Systems School of Computing & Information University of Pittsburgh PittsburghPA15260 United States

The development of large-scale quantum communication networks faces critical challenges due to photon loss and decoherence in optical fiber channels. These fundamentally limit transmission distances and demand dense networks of repeater stations. This work investigates using vacuum beam guides (VBGs)—a promising ultra-low-loss transmission platform—as an alternative to traditional fiber links. By incorporating VBGs into repeater-based architectures, we demonstrate that the inter-repeater spacing can be substantially extended, resulting in fewer required nodes and significantly reducing hardware and operational complexity. We perform a cost-function analysis to quantify performance trade-offs across first, second, and third-generation repeaters. Our results show that first-generation repeaters reduce costs dramatically by eliminating entanglement purification. Third-generation repeaters benefit from improved link transmission success, which is crucial for quantum error correction. In contrast, second-generation repeaters exhibit a more nuanced response;although transmission loss is reduced, their performance remains primarily limited by logical gate errors rather than channel loss. These findings highlight that while all repeater generations benefit from reduced photon loss, the magnitude of improvement depends critically on the underlying error mechanisms. Vacuum beam guides thus emerge as a powerful enabler for scalable, high-performance quantum networks, particularly in conjunction with near-term quantum hardware capabilities. Copyright © 2025, The Authors. All rights reserved.

关键词： Quantum communication

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Feature Selection on Epistatic Problems Using Genetic Algorithms with Nested Classifiers 26th

Feature Selection on Epistatic Problems Using Genetic Algor...

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26th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of EvoStar 2023

作者： Carvalho, Pedro Ribeiro, Bruno Rodrigues, Nuno M. Batista, João E. Vanneschi, Leonardo Silva, Sara University of Coimbra Centre for Informatics and Systems of the University of Coimbra Department of Informatics Engineering Coimbra Portugal GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI - Intelligent Systems Associate LAboratory Polytechnic of Porto Rua Dr. António Bernardino de Almeida 431 Porto4249-015 Portugal LASIGE Department of Informatics Faculty of Sciences University of Lisbon Lisbon Portugal Universidade Nova de Lisboa Campus de Campolide Lisboa1070-312 Portugal

ISBN: (纸本)9783031302282

Feature selection is becoming an essential part of machine learning pipelines, including the ones generated by recent AutoML tools. In case of datasets with epistatic interactions between the features, like many datasets from the bioinformatics domain, feature selection may even become crucial. A recent method called SLUG has outperformed the state-of-the-art algorithms for feature selection on a large set of epistatic noisy datasets. SLUG uses genetic programming (GP) as a classifier (learner), nested inside a genetic algorithm (GA) that performs feature selection (wrapper). In this work, we pair GA with different learners, in an attempt to match the results of SLUG with less computational effort. We also propose a new feedback mechanism between the learner and the wrapper to improve the convergence towards the key features. Although we do not match the results of SLUG, we demonstrate the positive effect of the feedback mechanism, motivating additional research in this area to further improve SLUG and other existing feature selection methods. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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Optimization Techniques in University Timetabling Problem:Constraints,Methodologies,Benchmarks,and Open Issues

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Computers, Materials & Continua 2023年第3期74卷 6461-6484页

作者： Abeer Bashab Ashraf Osman Ibrahim Ibrahim Abakar Tarigo Hashem Karan Aggarwal Fadhil Mukhlif Fuad A.Ghaleb Abdelzahir Abdelmaboud Faculty of Computer Science&Information Technology Alzaiem Alazhari University13311KhartoumSudan Faculty Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400SabahMalaysia Department of Computer Science University of SharjahSharjah27272United Arab Emirates Electronic and Communication Engineering Department Maharishi Markandeshwar Deemed to be UniversityMullanaAmbala133207HaryanaIndia Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi Malaysia81310JohorMalaysia Department of Information Systems King Khaled UniversityMuhayel61913AseerSaudi Arabia

University timetabling problems are a yearly challenging task and are faced repeatedly each *** problems are considered nonpolynomial time(NP)and combinatorial optimization problems(COP),which means that they can be solved through optimization algorithms to produce the aspired optimal *** techniques have been used to solve university timetabling problems,and most of them use optimization *** paper provides a comprehensive review of the most recent studies dealing with concepts,methodologies,optimization,benchmarks,and open issues of university timetabling *** comprehensive review starts by presenting the essence of university timetabling as NP-COP,defining and clarifying the two formed classes of university timetabling:University Course Timetabling and University Examination Timetabling,illustrating the adopted algorithms for solving such a problem,elaborating the university timetabling constraints to be considered achieving the optimal timetable,and explaining how to analyze and measure the performance of the optimization algorithms by demonstrating the commonly used benchmark datasets for the *** is noted that meta-heuristic methodologies are widely used in the ***,recently,multi-objective optimization has been increasingly used in solving such a problem that can identify robust university timetabling ***,trends and future directions in university timetabling problems are *** paper provides good information for students,researchers,and specialists interested in this area of *** challenges and possibilities for future research prospects are also explored.

关键词： University timetabling timetabling approaches meta-heuristics combinatorial optimization

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Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol

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SN Computer Science 2024年第5期5卷 546页

作者： Khan, Surbhi Bhatia Kumar, Ankit Mashat, Arwa Pruthviraja, Dayananda Imam Rahmani, Mohammad Khalid Mathew, Jimson School of Science Engineering and Environment University of Salford Salford United Kingdom Department of Information Technology Guru Ghasidas Vishwavidyalaya Chhattisgarh Bilaspur India Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Rabigh 21911 Saudi Arabia Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal 576104 India Department of Computer Science College of Computing and Informatics Saudi Electronic University Riyadh 11673 Saudi Arabia Department of Computer Science and Engineering Indian Institute of Technology Patna Bihar Patna India

The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) is significantly transforming the landscape of future networking. The Internet of Things (IoT) is a technological paradigm that encompasses embedded systems, wireless sensors, and automation, facilitating the integration of various applications ranging from smart homes to wearable devices. In addition, the advent of artificial intelligence (AI) amplifies this influence by providing data-driven analytics, optimising processes, and presenting novel opportunities for growth. Nevertheless, the widespread adoption of devices within Internet of Things (IoT) networks gives rise to apprehensions regarding increased energy consumption. In order to ensure the longevity of network operations, it is imperative to employ energy-efficient protocols for sensor nodes that possess limited power resources. One example of a protocol that demonstrates this concept is the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. This protocol effectively divides networks into clusters and dynamically adjusts the cluster heads to optimise the transmission of data to the base stations. Our study enhances the LEACH protocol by incorporating digital twin simulation, thereby enhancing the efficiency of IoT systems. Virtual network models and AI analytics are employed to assess energy consumption and performance. Cache nodes play a crucial role within this framework as they collect data from cluster heads in order to transmit it to the base station. By leveraging artificial intelligence (AI) and simulation techniques, we are able to improve the energy efficiency and reliability of the Internet of Things (IoT) systems. The findings indicate a significant reduction of 83% in non-functioning nodes and a notable increase of 1.66 times in energy levels of nodes compared to conventional approaches. This study highlights a potential direction for energy-efficient, AI-enhanced Internet of Things (IoT) networking through

关键词： Cluster head Clustering Data aggregation Gateway Internet of things LEACH Lifetime

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Diagnosing Breast Cancer Accurately Based on Weighting of HeterogeneousClassification Sub-Models

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Computer systems Science & Engineering 2022年第9期42卷 1257-1272页

作者： Majdy Mohamed Eltayeb Eltahir Tarig Mohammed Ahmed Department of Information Systems College of Science&Arts at MahayilKing Khalid UniversityMuhayel Aseer62529Kingdom of Saudi Arabia Department of Information Technology Faculty of Computing and Information TechnologyKing Abdul-Aziz UniversityJeddah21589Kingdom of Saudi Arabia Department of Computer Sciences Faculty of Mathematical Sciences and InformaticsUniversity of KhartoumKhartoum11115Sudan

In developed and developing countries, breast cancer is one of the leading forms of cancer affecting women alike. As a consequence of growing lifeexpectancy, increasing urbanization and embracing Western lifestyles, the highprevalence of this cancer is noted in the developed world. This paper aims todevelop a novel model that diagnoses Breast Cancer by using heterogeneous datasets. The model can work as a strong decision support system to help doctors tomake the right decision in diagnosing breast cancer patients. The proposed modelis based on three datasets to develop three sub-models. Each sub-model worksindependently. The final diagnosis decision is taken by the three sub-models independently. The power of the model comes from the diversity checks of patientsand this reduces the risk of wrong diagnosing. The model has been developedby conducting intensive experiments. Several classification algorithms were usedto select the best one in each sub-model. As the final results, the sub-modelaccuracies were 72%, 74% and 97%.

关键词： Breast cancer data mining classification

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Hybrid Cybersecurity Research and Education Environment for Maritime Sector

Hybrid Cybersecurity Research and Education Environment for ...

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Cyber Security and Resilience (CSR), IEEE International Conference on

作者： Gabor Visky Aleksei Šiganov Muaan ur Rehman Risto Vaarandi Hayretdin Bahşi Hayretdin Bahsi Leonidas Tsiopoulos Department of Software Science Tallinn University of Technology Tallinn Estonia School of Informatics Computing and Cyber Systems Northern Arizona University United States

ISBN: (数字)9798350375367

ISBN: (纸本)9798350375374

Digitalization is a global trend affecting many crit-ical infrastructures, including maritime transportation. Incorpo-rating information and operational technologies into transportation processes significantly enhances efficiency but also introduces substantial risks originating from cyberspace. It is a significant endeavour to develop lab environments to research offensive and defensive aspects of cybersecurity and facilitate hands-on experience in educational settings. This paper introduces a hybrid cybersecurity research and education lab environment for the maritime domain. It enables real-world data to be fed into a controlled setting equipped with various emulation system components. The lab, which combines open-source and low-cost commercial software, also benefits from virtualization technologies and real hardware devices. Its scala-bility and affordability make it a viable solution for educational purposes. Although the environment is defended against external access, it can be provided for third parties on demand. We conducted a series of cyberattacks on the network and an open-source navigation application to demonstrate the effective-ness of our lab setting. The recorded and shared network traffic from these attacks not only serves as a fertile ground for our own research but also invites other researchers to develop and test their solutions, fostering a collaborative environment for the advancement of cybersecurity in the sector.

关键词： Navigation Emulation Transportation Telecommunication traffic Market research Software Hardware

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