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IEEE Conference on Wireless Communications and Networking

作者： Konstantinos G. Rallis Vasilis K. Papanikolaou Sotiris A. Tegos Alexis A. Dowhuszko Panagiotis D. Diamantoulakis Mohammad-Ali Khalighi George K. Karagiannidis Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Department of Applied Informatics University of Macedonia Thessaloniki Greece Department of Communications and Networking Aalto University Espoo Finland Aix-Marseille University CNRS Centrale Marseille Institut Fresnel Marseille France

In this paper, we propose and evaluate a hybrid visible light communication (VLC)/radio-frequency (RF) network architecture, where a VLC access point serves two user equipments (UEs), which also act as RF relays in order to extend the network’s coverage to a third UE outside the VLC cell. The proposed protocol is inspired by uplink rate-splitting multiple access to efficiently route the messages to the UEs. In more detail, the proposed protocol utilizes the nuances of the specific network architecture to efficiently utilize the wireless resource blocks for both coverage and throughput. The protocol is then optimized by maximizing the minimum achievable rate. Simulation results show that the proposed method achieves superior results compared with a more conventional benchmark scheme, that is also optimized under the same constraints.

关键词： Radio frequency Wireless communication Simulation Microprocessors computer architecture Network architecture Benchmark testing

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The future of E-commerce in the publishing industry 2

The future of E-commerce in the publishing industry

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2nd International Conference on Smart Computing and Electronic Enterprise, ICSCEE 2021

作者： Aseh, Khairi Al-Qudah, Omar Mohammed Ali Abdullah Yusoff, M. Hafiz Pathmanathan, P. Ravindran Latiff, Nurul Adilah Abdul Jusoh, Julaily Aida Abu-Ulbeh, Waheeb El-Ebiary, Yousef A. Baker Al Moaiad, Yazeed International Institute of Applied Science Swiss School of Management Netherlands Irbid National University Faculty of Financial and Business Science Head of E-Marketing Department Jordan Albukhary International University School of Computing and Informatic Kedah Malaysia Faculty of Informatics and Computing UniSZA Malaysia UMT Faculty of Ocean Engineering Technology and Informatics Malaysia UniSZA Faculty of Informatics and Computing Malaysia Faculty of Computer Science and Informatics Cybersecurity Department Jordan MEDIU Faculty of Computer and Information Technology Malaysia

ISBN: (纸本)9781665432221

In comparison to conventional book-printed content, electronic "publishing"has allowed users to import files to either a personal computer or an e-book reader to read text in a digital format. Reduced printing costs and reduced time to market by streamlined drafting, proofing, and printing methods are the benefits of the publishing industry over the conventional printed book (p-book). It prevents binding, distribution and shipping. The intent of this paper is to explore the strategic use of e-commerce in the transformation of the publishing industry. The first part of the paper discusses the strategic use of e-commerce/Web-Based Business in the transition from a single distribution channel mass producer of printed books to a multiple distribution channel that will include e-books and print on demand technology in the publishing industry. Emphasis is put on management techniques in the global marketplace for the use of emerging information technologies. The second section of this paper addresses the transfer in competitive influence between the different levels of the supply chain of the publishing industry, including the latest trends in electronic publishing from the stakeholders' point of view. Expected to serve as the base for development within the digitized print industry. As e-publishing becomes popular and moves towards maturity, to allow a "mainstream"status, common standards must emerge and combine. © 2021 IEEE.

关键词： Electronic publishing

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Streamlining Video Summarization with NLP: Techniques, Implementation, and Future Direction

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SN computer Science 2025年第2期6卷 1-17页

作者： Alqurni, Jehad Saad Alsmadi, Mutasem K. Alfagham, Hayat Alzoubi, Sharaf Ihab, Sohayla Sameh, Ahmed AbdElminaam, Diaa Salama Khalaf, Osamah Ibrahim Department of Educational Technologies College of Education Imam Abdulrahman Bin Faisal University P.O. Box 1982 Dammam Saudi Arabia Department of MIS College of Applied Studies and Community Service Imam Abdulrahman Bin Faisal University P.O. Box 1982 Dammam Saudi Arabia College of Computer Sciences and Informatics Amman Arab University Amman 11953 Jordan Faculty of Engineering Ain Shams University Cairo 19648 Egypt MEU Research Unit Middle East University Amman 11831 Lebanon Jadara Research Center Jadara University Irbid 21110 Jordan Department of Solar Al-Nahrain Research Center for Renewable Energy Al-Nahrain University Baghdad 42115 Iraq

The rapid growth of digital video content presents significant challenges in information accessibility and consumption, creating a pressing need for efficient video summarization techniques. This paper explores using natural language processing (NLP) to enhance video summarization by leveraging associated textual data such as subtitles, titles, and descriptions. Video summarization can be broadly divided into two main approaches: abstractive and extractive. We focus on extractive summarization, implementing various NLP techniques, including Pure NLTK, TextRank, LexRank, KL-Sum, and Naïve Reduction, each encapsulated in dedicated pipelines to tokenize, rank, and extract essential content. Subsequently, summaries are generated and presented as shortened video formats. Our methodology includes comparing these NLP-based techniques with current state-of-the-art approaches and evaluating them through various quantitative metrics such as Rouge, BLEU, and F1-score to ensure a comprehensive summarization quality and efficiency assessment. The study also addresses computational trade-offs, particularly focusing on optimizing summarization for real-time applications. Recognizing the reliance on textual data, we propose enhancements for handling videos with limited text, such as integrating audio-to-text conversion and visual analysis. Our findings underscore the potential of NLP-driven summarization in improving accessibility across varied video content types and provide a roadmap for future research to enhance scalability, personalization, and real-time applicability. The evaluation results demonstrate the effectiveness and potential of NLP techniques in video summarization regardless of video length, accent, or language. The findings highlight the effect of various NLP techniques on the form of the generated summaries. In addition, a comparison with state-of-the-art methodologies is performed to provide clearer insights into the quality of the summaries, not only regarding a

关键词： Abstractive summarization Audio-to-text conversion Computational efficiency Extractive summarization Multimedia content analysis Natural language processing (NLP) Personalization Real-time processing Scalability Video accessibility Video summarization

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Supporting single responsibility through automated extract method refactoring

arXiv

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arXiv 2023年

作者： Ardalani, Alireza Parsa, Saeed Zakeri-Nasrabadi, Morteza Chatzigeorgiou, Alexander School of Computer Engineering Iran University of Science and Technology Resalat Hengam St. Tehran Tehran16846-13114 Iran Department of Applied Informatics University of Macedonia 156 Egnatia Str. Thessaloniki Thessaloniki54636 Greece

The responsibility of a method/function is to perform some desired computations and disseminate the results to its caller through various deliverables, including object fields and variables in output instructions. Based on this definition of responsibility, this paper offers a new algorithm to refactor long methods to those with a single responsibility. We propose a backward slicing algorithm to decompose a long method into slightly overlapping slices. The slices are computed for each output instruction, representing the outcome of a responsibility delegated to the method. The slices will be non-overlapping if the slicing criteria address the same output variable. The slices are further extracted as independent methods, invoked by the original method, if certain behavioral preservation are made. The proposed method has been evaluated on the GEMS extract method refactoring benchmark and three real-world projects. On average, our experiments demonstrate at least a 29.6% improvement in precision and a 12.1% improvement in the recall of uncovering refactoring opportunities compared to the state-of-the-art approaches. Furthermore, our tool improves method-level cohesion metrics by an average of 20% after refactoring. Experimental results confirm the applicability of the proposed approach in extracting methods with a single responsibility. © 2023, CC BY.

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Quantum Computing based Channel and Signal Modeling for 6G Wireless System

TechRxiv

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TechRxiv 2023年

作者： Farouk, Ahmed AbuAli, Najah Abed Mumtaz, Shahid The Department of Computer Science Faculty of Computers and Artificial Intelligence South Valley University Hurghada Egypt United Arab Emirates Department of Applied Informatics Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Nottingham Trent University Engineering Department United Kingdom

Sixth-generation wireless technology (6G) introduces a paradigm shift and fundamental transformation of digital wireless connectivity by converging pillars of softwarization, virtualization, and wireless networks. Terahertz (THz) communication technologies are predicted to become more significant in 6G applications as the requirement for bandwidth grows and wireless cell sizes shrink. As a result, 6G will be able to deal with and manage numerous devices and services requiring enhanced spectral throughput and efficiently work with high interference levels. This convergence highlights the increased threat surface of 6G networks and the potentially severe impacts of sophisticated cyber incidents. Furthermore, the heterogeneity of connected devices and provided services will generate a huge amount of data to be processed and managed efficiently. Quantum computing (QC) can efficiently solve several 6G computationally hard problems with a quadratic speedup and provide adaptive techniques for controlling the current and future significant security threats of the 6G network. This article will discuss the role of various QC components on 6G and explore the opportunities and challenges to achieving such transformation. © 2023, CC BY.

关键词： Quantum cryptography

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Digital Twins for Energy-Efficient Manufacturing

Digital Twins for Energy-Efficient Manufacturing

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Annual IEEE Systems Conference

作者： Nader Mohamed Sanja Lazarova-Molnar Jameela Al-Jaroodi Department of Computer Science and Information Systems Pennsylvania Western University California PA USA Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Karlsruhe Germany Faculty of Engineering University of Southern Denmark Odense Denmark Department of Engineering Robert Morris University Pittsburgh PA USA

Some manufacturing industries consume massive energy for their manufacturing and logistics processes. The costs of manufacturing can increase significantly as the energy cost increases. Such increase amplifies the final cost of the created products on the consumers. This makes finding different approaches that utilize innovative technologies to improve energy efficiency in manufacturing extremely important. This paper investigates how digital twins can be utilized to enable improved energy efficiency in manufacturing. Different applications of digital twins for energy-efficient manufacturing are investigated. In addition, the paper discusses some challenges of utilizing digital twins for this purpose. A framework for utilizing digital twins for energy-efficient manufacturing is also discussed.

关键词： Manufacturing industries Costs Manufacturing processes Buildings Energy efficiency Raw materials Manufacturing

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Digital Twin Definition for Detecting Abnormal Perspiration Patterns in High-Stress Professions

Digital Twin Definition for Detecting Abnormal Perspiration ...

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Roedunet International Conference (RoEduNet)

作者： Cristian Vizitiu Ioan Turcin Kevin Alexander Dominey Selver Softic Adrian-Cătălin Dinculescu Vlad I. Bocăneţ Cosmin Dugan Sorin-Aurel Moraru The Space Applications and Technologies Laboratory Institute of Space Science -Subsidiary of INFLPR Magurele Romania Department of Automatics and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania Department Automation Technology CAMPUS 02 University of Applied Sciences Graz Austria Department IT & Business Informatics CAMPUS 02 University of Applied Sciences Graz Austria Department of Manufacturing Engineering Faculty of Industrial Engineering Robotics and Production Management Technical University of Cluj-Napoca Cluj-Napoca Romania Bucharest University Emergency Hospital Bucharest Romania

ISBN: (数字)9798331540388

ISBN: (纸本)9798331540395

Perspiration is a physiological response in high-stress situations, that also plays a key role in thermoregulation and stress management. Understanding perspiration patterns is used for assessing physiological responses and optimizing human performance especially in professions such as emergency medical services and military operations, as well as for individuals exposed to Isolated Confined Extreme (ICE) environments such as astronauts and space analog mission participants. This paper defines a Digital Twin (DT) model, that will be integrated with an existing physical sweat simulator module (SSM) prototype. Its goal is to simulate human perspiration under high-stress conditions by integrating environmental, physiological, and psychological data. The system architecture is developed via Model-Based Systems engineering (MBSE). The scope of the designed virtual model is to accurately reflect physical perspiration, detect abnormal perspiration patterns, and generate recommendations regarding stress countermeasures. The goal is to influence the behavioral and/or physiological state of the physical twin, thereby creating a dynamic, responsive system. Machine learning (ML) models will be used to identify patterns in the environmental, physiological, and psychological inputs and predict sweat volume, chemical composition, and regional sweat distributions across the body. ML will also be used to detect abnormal perspiration patterns based on input data. The application of generative AI for creating test data from simulation templates is anticipated to facilitate the comparative analysis of two to three distinct profiles, such as astronauts, soldiers, and paramedics or firefighters, using simulated values. The SSM, with its integrated sensors, will serve the dual purpose of validating the model and providing realistic physical simulation.

关键词： Adaptation models Generative AI Psychology Human factors Machine learning Predictive models Physiology Digital twins Modeling Biomedical monitoring

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An equivalent reformulation and multi-proximity gradient algorithms for a class of nonsmooth fractional programming

arXiv

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arXiv 2023年

作者： Zhou, Junpeng Zhang, Na Li, Qia School of Computer Sciences and Engineering Sun Yat-Sen University Guangzhou510006 China Department of Applied Mathematics College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China School of Computer Sciences and Engineering Guangdong Province Key Laboratory of Computational Science Sun Yat-Sen University Guangzhou510006 China

In this paper, we consider a class of structured fractional programs, where the numerator part is the sum of a block-separable (possibly nonsmooth nonconvex) function and a locally Lipschitz differentiable (possibly nonconvex) function, while the denominator is a convex (possibly nonsmooth) function. We first present a novel reformulation for the original problem and show the relationship between optimal solutions, critical points and KL exponents of these two problems. Inspired by the reformulation, we propose a flexible framework of multi-proximity gradient algorithms (MPGA), which computes the proximity operator with respect to the Fenchel conjugate associated with the convex denominator of the original problem rather than evaluating its subgradient as in the existing methods. Also, MPGA employs a nonmonotone linear-search scheme in its gradient descent step, since the smooth part in the numerator of the original problem is not globally Lipschitz differentiable. Based on the framework of MPGA, we develop two specific algorithms, namely, cyclic MPGA and randomized MPGA, and establish their subsequential convergence under mild conditions. Moreover, the sequential convergence of cyclic MPGA with the monotone line-search (CMPGA ML) is guaranteed if the extended objective associated with the reformulated problem satisfies the Kurdyka-Lojasiewicz (KL) property and some other mild assumptions. In particular, we prove that the corresponding KL exponents are 12 for several special cases of the fractional programs, and so, CMPGA ML exhibits a linear convergence rate. Finally, some preliminary numerical experiments are performed to demonstrate the efficiency of our proposed algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Gradient methods

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Benchmarking Advanced Text Anonymisation Methods: A Comparative Study on Novel and Traditional Approaches

arXiv

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arXiv 2024年

作者： Asimopoulos, Dimitris Siniosoglou, Ilias Argyriou, Vasileios Karamitsou, Thomai Fountoukidis, Eleftherios Goudos, Sotirios K. Moscholios, Ioannis D. Psannis, Konstantinos E. Sarigiannidis, Panagiotis R&D Department MetaMind Innovations P.C. Kozani Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Department of Networks and Digital Media Kingston University Kingston upon Thames United Kingdom Sidroco Holdings Ltd. Nicosia Cyprus Physics Department Aristotle University of Thessaloniki Thessaloniki Greece Department of Informatics and Telecommunications Department University of Peloponnese Tripoli Greece Department of Applied Informatics School of Information Sciences University of Macedonia Thessaloniki Greece

In the realm of data privacy, the ability to effectively anonymise text is paramount. With the proliferation of deep learning and, in particular, transformer architectures, there is a burgeoning interest in leveraging these advanced models for text anonymisation tasks. This paper presents a comprehensive benchmarking study comparing the performance of transformer-based models and Large Language Models(LLM) against traditional architectures for text anonymisation. Utilising the CoNLL-2003 dataset, known for its robustness and diversity, we evaluate several models. Our results showcase the strengths and weaknesses of each approach, offering a clear perspective on the efficacy of modern versus traditional methods. Notably, while modern models exhibit advanced capabilities in capturing contextual nuances, certain traditional architectures still keep high performance. This work aims to guide researchers in selecting the most suitable model for their anonymisation needs, while also shedding light on potential paths for future advancements in the field. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Benchmarking Advanced Text Anonymisation Methods: A Comparative Study on Novel and Traditional Approaches

Benchmarking Advanced Text Anonymisation Methods: A Comparat...

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International Conference on Modern Circuits and Systems Technologies (MOCAST)

作者： Dimitris Asimopoulos Ilias Siniosoglou Vasileios Argyriou Thomai Karamitsou Eleftherios Fountoukidis Sotirios K. Goudos Ioannis D. Moscholios Konstantinos E. Psannis Panagiotis Sarigiannidis R&D Department MetaMind Innovations P.C. Kozani Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Sidroco Holdings Ltd. Nicosia Cyprus Department of Networks and Digital Media Kingston University Kingston upon Thames United Kingdom Physics Department Aristotle University of Thessaloniki Thessaloniki Greece Department of Informatics and Telecommunications Department University of Peloponnese Tripoli Greece Department of Applied Informatics School of Information Sciences University of Macedonia Thessaloniki Greece

ISBN: (数字)9798350385427

ISBN: (纸本)9798350385434

关键词： Deep learning Data privacy Circuits and systems Benchmark testing Transformers Robustness Task analysis

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