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6th World Symposium on Communication engineering, WSCE 2023

作者： Christofas, Vasileios Amanatidis, Petros Karampatzakis, Dimitris Lagkas, Thomas Goudos, Sotirios K. Psannis, Konstantinos E. Sarigiannidis, Panagiotis International Hellenic University Department of Computer Science Kavala Greece Aristotle University of Thessaloniki Department of Physics Thessaloniki Greece University of Macedonia Department of Applied Informatics Thessaloniki Greece University of Western Macedonia Department of Electrical and Computer Engineering Kozani Greece

ISBN: (纸本)9798350339505

Embedded AI development has been rapidly im-proving for the past few years and has had a great impact on edge AI networks. However, as neural networks become deeper and deeper it becomes more difficult to execute complicated tasks without sacrificing a good amount of power and performance. In this paper, we make a comparative evaluation between two AI acceleration devices. The first one features a RISC- V 64-bit processor while the other one is ARM powered. These devices are combined with AI co-processors, or ASICs, with computer vision capabilities. Our benchmark consists of a simple classification task split into multiple versions. The results showed that the RISC- V inference machine had 4 times lower consumption while the ARM machine was up to 15 times faster in our largest network. We discuss the results in great detail while keeping our focus on all aspects equally. Finally, we make recommendations based on their usage and application. © 2023 IEEE.

关键词： computer vision

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Cybersecurity Revolution via Large Language Models and Explainable AI 17

Cybersecurity Revolution via Large Language Models and Expla...

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

作者： Ghazal, Taher M. Janjua, Jamshaid Iqbal Abushiba, Walid Ahmad, Munir Ihsan, Anuam Al-Dmour, Nidal A. College of Arts & Science Applied Science University Manama Bahrain Center for Cyber Security Faculty of Information Science and Technology Selangor Malaysia Lahore Pakistan College of Engineering Applied Science University Bahrain College of Informatics Korea University Seoul02841 Korea Republic of College of Engineering Mutah University Department of Computer Engineering Jordan

ISBN: (纸本)9798331509736

Integrating Groundbreaking advancements in AI, like language models, interpretable AI, and machine learning, opens up a world of exciting new possibilities. The Evolving face of cybersecurity and Modern cyber threats are complex and well crafted;hence, conventional cybersecurity mechanisms show difficulty in staying relevant. LLMs, especially based on Transformer architecture will noticeably increase the accuracy and speed of detecting threats. Transparency and trust are increased by XAI approaches like SHAP and LIME, which offer facts about ML model predictions. This paper explores the literature that demonstrates the integration between XAI and LLMs in cybersecurity, exemplifying how this trinity of models has the potential to help attenuate errors producing reduced false positives and improve how we detect threats. Thinking about the possibilities the challenges including performance Explainability trade-offs, the need for common evaluation metrics, and the black-box nature of AI Models, remain in place. Solving these will help to enhance AI-driven solutions in cybersecurity. © 2024 IEEE.

关键词： Cybersecurity Explainable AI (XAI) Large Language Models (LLMs) Machine Learning (ML) Reliability Threat Detection Transformer Architecture Transparency

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A review of federated learning in renewable energy applications:Potential,challenges,and future directions

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Energy and AI 2024年第3期17卷 444-457页

作者： Albin Grataloup Stefan Jonas Angela Meyer Bern University of Applied Sciences School of Engineering and Computer ScienceQuellgasse 21Biel2501Switzerland Universitàdella Svizzera italiana Faculty of InformaticsVia la Santa 1Lugano-Viganello6962Switzerland Delft University of Technology Department of Geoscience and Remote SensingStevinweg 1Delft2628The Netherlands

Federated learning has recently emerged as a privacy-preserving distributed machine learning *** learning enables collaborative training of multiple clients and entire fleets without sharing the involved training *** preserving data privacy,federated learning has the potential to overcome the lack of data sharing in the renewable energy sector which is inhibiting innovation,research and *** paper provides an overview of federated learning in renewable energy *** discuss federated learning algorithms and survey their applications and case studies in renewable energy generation and *** also evaluate the potential and the challenges associated with federated learning applied in power and energy ***,we outline promising future research directions in federated learning for applications in renewable energy.

关键词： Federated learning Renewable energy Dis tributed learning Data heterogeneity Privacy Data sharing Wind energy Solar energy Buildings Review

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Towards Swarm Intelligence Ontology for Formal Description of Metaheuristics Algorithms 4

Towards Swarm Intelligence Ontology for Formal Description o...

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4th International Conference on Computing, Networking, Telecommunications and engineering Sciences Applications, CoNTESA 2023

作者： Tulicic, Domagoj Horvat, Marko Lovrencic, Sandra University of Applied Science in Information Technology Department of Computer System and Networks Zagreb Croatia University of Zagreb Faculty of Electrical Engineering and Computing Department of Applied Computing Zagreb Croatia University of Zagreb Faculty of Organization and Informatics Foundations of Information Sciences Department of Theoretical and Applied Varaždin Croatia

ISBN: (纸本)9798350382754

Swarm intelligence is a class of nature-inspired metaheuristic algorithms, that is specifically derived from biological systems in nature with an emphasis on their social interactions. These algorithms have been primarily developed to solve complex combinatorial optimization problems and are extremely popular among researchers in metaheuristic algorithms. This is evident from the numerous published scientific papers describing algorithms inspired by biological systems, ranging from insects such as ants and bees to the largest animals on the planet like whales. All these algorithms share some common concepts and relationships that can be explicitly identified, named, and formalized. These shared concepts and relationships can be organized and represented through the construction of an ontology. The goal of this paper is to present a formal ontology that standardizes vocabulary, as well as a set of rules enabling precise communication and reasoning about these algorithms. Ultimately, this will improve our understanding, analysis, research processes, and utilization of these computational approaches. © 2023 IEEE.

关键词： Swarm intelligence

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Improving Communication Systems Through Federated Learning: An Optimization of Decision-Making 6

Improving Communication Systems Through Federated Learning: ...

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6th World Symposium on Communication engineering, WSCE 2023

作者： Stergiou, Konstantinos D. Ishibashi, Yutaka Goudos, Sotirios K. Lagkas, Thomas Sarigiannidis, Panagiotis Psannis, Konstantinos E. University of Macedonia Department of Applied Informatics Thessaloniki Greece Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan Aristotle University of Thessaloniki Department of Physics Thessaloniki Greece International Hellenic University Department of Computer Science Kavala Greece University of Western Macedonia Department of Informatics and Telecommunications Engineering Kozani Greece

ISBN: (纸本)9798350339505

This paper discusses the use of federated learning as a method for optimizing decision-making in communication systems. Federated learning is a machine learning technique that enables the training of models on decentralized data, allowing for the collection and analysis of data from multiple sources while maintaining the privacy and security of the data. This approach is particularly useful in communication systems, as it allows for the optimization of decision-making across a wide range of devices and networks. The paper examines the advantages of federated learning, including the ability to collect a large amount of data from a diverse range of devices, the protection of sensitive data, and the ability to adapt to changing conditions in real-time. The paper also provides specific examples of how federated learning can be used in the optimization of mobile networks and content delivery. The conclusion highlights the growing importance of federated learning in improving communication systems. © 2023 IEEE.

关键词： Learning systems

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Indoor 3D Visible Light Positioning Analysis with Channel Estimation Errors 30

Indoor 3D Visible Light Positioning Analysis with Channel Es...

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30th International Conference on Systems, Signals and Image Processing, IWSSIP 2023

作者： Bozanis, Dimitrios Evgenidis, Nikos G. Papanikolaou, Vasilis K. Bouzinis, Pavlos S. Tegos, Sotiris A. Dowhuszko, Alexis A. Diamantoulakis, Panagiotis D. Karagiannidis, George K. Department of Electrical and Computer Engineering Thessaloniki54124 Greece Germany University of Macedonia Department of Applied Informatics Thessaloniki54636 Greece Aalto University Department of Communications and Networking Espoo02150 Finland Cyber Security Systems and Applied Ai Research Center Lebanon

ISBN: (纸本)9798350337297

Since radio-frequency signals are affected signifi-cantly by multipath fading, the localization accuracy they offer cannot meet the sixth generations (6G) demanding specifications. On the other hand, visible light positioning (VLP) has emerged as a low cost alternative that takes into account the highly deterministic channel characteristics of visible light communications to provide cm-level accuracy provided that the investigated spaces are adequately covered by LEDs. However, imperfect channel state information and modeling can lead to positioning errors. In this paper, localization accuracy is quantified in terms of channel estimation errors via low complexity lateration algorithm. The channel estimation errors can be caused by a variety of issues and the provided analysis is general so that it can be easily applied to a plethora of applications. Finally, Monte Carlo simulations validate the proposed method and offer valuable insights for the design and performance bounds of VLP systems. © 2023 IEEE.

关键词： Monte Carlo methods

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Semi-analytical finite element method applied for characterizing micropolar fibrous composites

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applied Mathematics and Mechanics(English Edition) 2024年第12期45卷 2147-2164页

作者： J.A.OTERO Y.ESPINOSA-ALMEYDA R.RODRIGUEZ-RAMOS J.MERODIO School of Engineering and Sciences Monterrey Institute of TechnologyEstado de Mexico 52926Mexico Institute of Engineering and Technology Autonomous University of Ciudad JuarezCiudad JuarezChihuahua 32310Mexico Postgraduate Program in Computational Modeling in Science and Technology Federal Fluminense UniversityRıo de Janeiro 27255-125Brazil Faculty of Mathematics and Computer Science University of HavanaLa Habana 10400Cuba Department of Mathematics Applied to ICT School of Informatics Systems EngineeringTechnical University of MadridMadrid 28031Spain

A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.

关键词： semi-analytical approach fiber-reinforced composite(FRC) effective property finite element method(FEM) asymptotic homogenization method(AHM) micropolar elasticity

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Experimental Learning in Electrical engineering with the Erasmus+ DIG-SENSING Blended Intensive Program 32

Experimental Learning in Electrical Engineering with the Era...

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32nd Annual Conference of the European Association for Education in Electrical and Information engineering, EAEEIE 2023

作者： Laura, Grindei Lorente, Vicent Posadas-Yague, Juan-Luis Grout, Ian Fischer, Thomas Technical University of Cluj-Napoca Department of Electrotechnics and Measurements Cluj-Napoca Romania Universitat Politècnica de València School of Informatics Department of Computer Engineering Valencia Spain University of Limerick Department of Electronic and Computer Engineering Limerick Ireland University of Applied Sciences Campus Vienna Department Engineering Vienna Austria

ISBN: (纸本)9789038656908

This paper presents the Erasmus+ DIG-SENSING project which is a Blended Intensive Program (BIP) that has the main objective to increase the motivation of students in achieving knowledge and practical experience in the field of electronic circuits. This is to be achieved through projects that integrate the design of electronic circuits, and the programming of microcontrollers through an initial online series of Webinars and local activities within the partner institutions from March to May 2023 that are then followed by a physical Summer School in July 2023. The structure and implementation of DIG-SENSING, with the benefits for students, academic staff, and partner universities will be presented. In this project, the participating students must develop and tackle a challenge that brings together Information and Communication Technologies in the framework of solving socio-environmental *** paper also presents and evaluation of students perception after the first webinar. © 2023 Fontys University of applied Science.

关键词： Students

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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore Software Maintenance

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computers, Materials & Continua 2022年第11期73卷 3827-3845页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Nadeem Iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyaKuwait

Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of *** the work is done offshore,these agreements or images must be shared through the Internet or stored over the *** breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of *** article proposes a novel algorithm for securing the NDAs in the form of *** an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the *** the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of *** confusion effects have been realized through an XOR operation between the confused image,and chaotic ***,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it *** machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.

关键词： Non-disclosure agreement encryption decryption secret key chaoticmap confusion diffusion

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An overview of data integration principles for heterogeneous databases 45

An overview of data integration principles for heterogeneous...

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Stojanovic, Aleksandar Horvat, Marko Kovacevic, Zeljko Zagreb University of Applied Sciences Department of Informatics and Computer Science Zagreb Croatia University of Zagreb Department of Applied Computing Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9789532331035

Modern large-scale information systems often use multiple database management systems, not all of which are necessarily relational. In recent years, NoSQL databases have gained acceptance in certain domains while relational databases remain de facto standard in many others. Many "legacy"information systems also use relational databases. Unlike relational database systems, NoSQL databases do not have a common data model or query language, making it difficult for users to access data in a uniform manner when using a combination of relational and NoSQL databases or simply several different NoSQL database systems. Therefore, the need for uniform data access from such a variety of data sources becomes one of the central problems for data integration. In this paper we provide an overview of the main problems, methods, and solutions for data integration between relational and NoSQL databases, as well as between different NoSQL databases. We focus mainly on the problems of structural, syntactic, and semantic heterogeneity and on proposed solutions for uniform data access, emphasizing some of the more recent proposals. © 2022 Croatian Society MIPRO.

关键词： Query languages

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