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International Conference on Mechatronics (ICOM)

作者： Abdulkadir Tasdelen Mohamed Hadi Habaebi Md Rafiqul Islam Dept. of Software Engineering Faculty of Engineering and Natural Sciences Ankara Yildirim Beyazit University Ankara Türkiye Faculty of Engineering IIUM Malaysia Dept. of Electrical and Computer Engineering Faculty of Engineering International Islamic University Malaysia Kuala Lumpur Malaysia

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

Blockchain technologies and cryptocurrencies have garnered significant attention for their potential to revolutionize various industries. This paper investigates the landscape of blockchain technologies in the context of cryptocurrencies, focusing on performance metrics, trade-offs, trends, and underlying issues. Through comprehensive analysis, the most utilized consensus mechanisms among the top cryptocurrencies are identified. The distribution of top mining pools by hash rate over the last two years reveals dominance by a few major pools, with implications for decentralization and security. In Bitcoin mining pool distribution, trends indicate the dominance of established pools like Foundry USA Pool and AntPool, alongside notable growth from smaller pools like MARA Pool and Luxor. Comparative analysis across different cryptocurrencies highlights variations in hashing rate, block production, and energy consumption, underscoring the complex dynamics of blockchain mining. Moreover, the comparative analysis of energy consumption in blockchain mining hardware reveals insights into energy efficiency and sustainability. Smaller mining pools demonstrate significant growth and momentum, contributing to the diversification and decentralization of mining operations.

关键词： Measurement Industries Energy consumption Mechatronics Production Market research Hardware

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Computational Model of Swarm Algorithm for Optimizing Process of Keywords Extraction from Text Information Presented as Graph

Computational Model of Swarm Algorithm for Optimizing Proces...

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International Conference on Information Technologies in engineering Education (Inforino)

作者： Yury Kravchenko Elmar Kuliev Daniil Kravchenko Sergey Rodzin Nikolay Pavlov Lada Rodzina Dept. of Computer Aided Design Southern Federal University Taganrog Russia Department of Software Engineering Southern Federal University Taganrog Russia

ISBN: (数字)9798350371369

ISBN: (纸本)9798350371376

The article describes the scientific problem of optimizing the processes of acquiring knowledge when processing textual information presented in the form of a graph, based on the development of a modified bioinspired algorithm for extracting keywords. The solution proposed by the authors differs from the known ones by introducing new attractive operators and behavioral patterns of bacterial agents into the computational model of the bacterial swarm algorithm. This approach allows you to balance the ratio of the speed of convergence of the algorithm with the diversification of the search space for solutions. The article also presents an analytical study of the features of two types of parsing: constituency parsing and dependency parsing. As part of the study, algorithms for syntactic parsing of dependencies between elements of text information and a graph-based dependency parsing algorithm are described. The formulation of the problem of keyword extraction is given. The task of achieving a balance between accuracy and speed of a linguistic parser is an open topic that requires further research due to the importance of this problem for improving the efficiency of text analysis, especially in applications that require real-time accuracy. To increase the efficiency of solving the problem, the authors propose a modified bioinspired algorithm for extracting keywords. The computational experiment carried out allows us to conclude that the modified bacterial optimization method proposed by the authors is in a leading position, which confirms the need to continue research into the applicability of bioinspired methods for solving problems of acquiring knowledge when processing text information presented in the form of a graph. This article is focused on the direction of study in the master’s program “Informatics and computer Science”, as well as the scientific specialty of postgraduate training “Artificial Intelligence and Machine Learning”.

关键词： Microorganisms Accuracy Text analysis Machine learning algorithms Computational modeling Optimization methods Syntactics

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Exploiting TAS schemes to Enhance the PHY-security in Cooperative NOMA Networks: A Deep Learning Approach

Exploiting TAS schemes to Enhance the PHY-security in Cooper...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Yushintia Pramitarini Ridho Hendra Yoga Perdana Kyusung Shim Beongku An Dept. of Software and Communications Engineering in Graduate School Hongik University Republic of Korea School of Computer Engineering and Applied Mathematics Hankyong National University Republic of Korea Dept. of Software and Communications Engineering Hongik University Republic of Korea

In this paper, we propose a novel antenna selection scheme to enhance the secrecy performance in a relay-aided non-orthogonal multiple access (NOMA) network against an eavesdropper. Different from the conventional antenna selection schemes that does not use channel information, the proposed antenna selection scheme can employ each channel information to maximize the main channel capacity and minimize the eaves-dropper channel capacity, respectively. In order to evaluate the secrecy performance, we propose a deep learning (DL)-based framework that can do real-time configuration since the DL-based framework is based on a compact mapping function. In detail, the proposed min-max relay transmit antenna selection (MMRTAS) scheme can improve the secrecy performance compared to that of the benchmark scheme. Numerical results show that the proposed MMRTAS scheme improves the secrecy performance compared to that of the benchmark scheme. The proposed DL-based framework can estimate the main channel and eavesdropper channel capacities for the near user and far user with an accuracy of 99.79%, respectively.

关键词： Deep learning NOMA Channel capacity Transmitting antennas Receiving antennas Channel estimation Benchmark testing

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TRUSTCACHE: Trust-based Content Caching in Information-Centric Networks

TRUSTCACHE: Trust-based Content Caching in Information-Centr...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Sean Tsikteris Aisha B Rahman Md Sadman Siraj Panagiotis Charatsaris Eirini Eleni Tsiropoulou Symeon Papavassiliou Institute of Communication and Computer Systems School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The Information-Centric Networking (ICN) paradigm has reshaped the modern network architectures and promises efficient content delivery to the end-users. This paper introduces TRUSTCACHE, a novel framework enabling the content caching within ICNs and focusing on the trust-based ICN selection and optimal cache memory allocation to the Content Providers (CPs). The TRUSTCACHE framework incorporates the Optimistic Q-learning with Upper Confidence Bound reinforcement learning algorithm that enables the CPs to autonomously select ICNs based on their cache memory availability and trust levels. Also, TRUSTCACHE enables the CPs to jointly consider the reliability of the ICNs and their cache memory availability by integrating a novel trust model. Furthermore, TRUSTCACHE leverages the multilateral bargaining principles in order to ensure the optimal cache memory allocation among the CPs, in terms of aligning with their profit margin characteristics. Simulation-based experiments validate TRUSTCACHE’s operational efficiency across diverse CP profit margin profiles and highlight its superiority over alternative models lacking trust-based ICN selection or employing proportional fairness strategies for cache memory allocation.

关键词： Q-learning Cache memory Information-centric networking Focusing Resource management Reliability Global communication Game theory

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Enhanced Healthcare Through Metaverse Integration: Explainable AI and Blockchain for Trust, Security, and Immersive Experiences

Enhanced Healthcare Through Metaverse Integration: Explainab...

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Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Bilal Ibrahim Sowan Hazem Qattous Mohammad Fasha Ahmad Altarawneh Dept. of Bus. Intell. & Data Analytics University of Petra Amman Jordan Dept. of Software Engineering Princess Sumaya University for Technology Amman Jordan Dept. of Computer Science Brunel University of London London UK

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

The metaverse, a dynamic blend of virtual and augmented reality, holds extraordinary promise for reshaping the healthcare landscape. By integrating advanced technologies such as virtual reality (VR), artificial intelligence (AI), blockchain, and digital twins, the metaverse introduces transformative opportunities in patient care, medical education, and healthcare operations. These tools foster immersive, personalized, and data-driven environments, significantly improving diagnostic precision, therapeutic strategies, and training methodologies. This paper provides a framework to utilize this potential while navigating key concerns, including systems scale, user customization, and ethical adequacy. In that case, the framework's goal should be eliminating existing limitations and barriers within healthcare systems by utilizing state-of-the-art technologies with real-world applications. The framework involves virtual consultation sites that enable provider-patient interactions, intelligent virtual agents with specific care recommendations, blockchain integration for data integrity, and dynamic VR segments that are functional in delivering healthcare education and training. The study focuses on scenario-based modeling and the use of pilot deployment in various healthcare settings to test for practicability and feasibility. The research also emphasizes that ethical issues and inclusion during the design and implementation of the innovations should also consider society's values regarding the medical field and promote equal access to healthcare. This framework proves a comprehensive blueprint for continuous progress and places the metaverse as one cornerstone in the global healthcare system.

关键词： Training Ethics Technological innovation Solid modeling Metaverse Medical services Blockchains Digital twins Security Medical diagnostic imaging

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Web Accessibility of the Cyprus Island Food Retailers' Websites

Web Accessibility of the Cyprus Island Food Retailers' Websi...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Erkut Inan Iseri Kaan Uyar Umit Ilhan Dept. of Physics Near East University Nicosia Turkey Dept. of Software Engineering Near East University Nicosia Turkey Dept. of Computer Engineering Near East University Nicosia Turkey

Accessibility is the process of making information and electronic communication environments meaningful and usable for most people including those with disabilities. It is not always an easy task to provide all user communities with different areas of interests and needs with exact styles and contents. It is a good practice to employ responsible designs and a certain degree of interaction that provide equitable conditions to suit the needs of the most user communities. It became evident that in the passed two years the world went thru a terrifying Coronavirus disease which made the accessibility of web sites of retailers even more challenging. Most of the food supplying companies introduced shop-to door deliveries of food products with web based applications. Although, technically speaking, these web sites accomplished the task for most of the people but with some accessibility issues. These issues can be identified and solved by following the international standards to gain world wide acceptance. This study covers the investigation of the accessibility of the Food Retailers' websites in the whole of Cyprus Island. Web Content Accessibility Guidelines 2.1 (WCAG 2.1) published by the World Wide Web Consortium (W3C) is followed in the process. Three testing software are used to determine the degree of compliance of the food retailers with the WCAG 2.1 in Cyprus Island. The aim of this study is to raise awareness about web accessibility among general public. The findings are not so promising and the sites examined are not in compliance with the standard of the guidelines defined in WCAG.

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Driving Behavior Classification Using Smartphone Sensor Data

Driving Behavior Classification Using Smartphone Sensor Data

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International Conference on computer Science and engineering (UBMK)

作者： Deniz Dikbıyık Fatih Alagöz Dept. of Software Engineering Boğaziçi University İstanbul Türkiye Dept. of Computer Engineering Boğaziçi University İstanbul Türkiye

Given the substantial number of accidents because of human error, the development of automatic driver behavior monitoring systems has become a pressing need. By providing real-time monitoring and analysis of driving behavior, these systems have the potential to decrease the incidence of accidents and improve overall road safety. This study presents a novel analysis framework for classifying driving behavior based on data gathered from passengers' smartphones. The data were collected using our mobile application installed on the smartphones and processed using machine learning algorithms. The study utilized several machine learning classification t echniques, w ith a focus on developing a Long Short Term Memory (LSTM) algorithm for improved accuracy. A Federated Learning algorithm was also developed to collect the data not into one area and train a global model to apply for labeling the driving behavior. The results show the efficacy of the proposed approach in accurately classifying driving behavior based on data obtained from smartphones.

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Noise-Robust Hearing Aid Voice Control

arXiv

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arXiv 2024年

作者： López-Espejo, Iván Roselló, Eros Edraki, Amin Harte, Naomi Jensen, Jesper Dept. of Signal Theory Telematics and Communications UGR Spain Dept. of Electrical and Computer Engineering QU Canada School of Eng. TCD Ireland Dept. of Electronic Systems AAU Denmark

Advancing the design of robust hearing aid (HA) voice control is crucial to increase the HA use rate among hard of hearing people as well as to improve HA users’ experience. In this work, we contribute towards this goal by, first, presenting a novel HA speech dataset consisting of noisy own voice captured by 2 behind-the-ear (BTE) and 1 in-ear-canal (IEC) microphones. Second, we provide baseline HA voice control results from the evaluation of light, state-of-the-art keyword spotting models utilizing different combinations of HA microphone signals. Experimental results show the benefits of exploiting bandwidth-limited bone-conducted speech (BCS) from the IEC microphone to achieve noise-robust HA voice control. Furthermore, results also demonstrate that voice control performance can be boosted by assisting BCS by the broader-bandwidth BTE microphone signals. Aiming at setting a baseline upon which the scientific community can continue to progress, the HA noisy speech dataset has been made publicly available. Copyright © 2024, The Authors. All rights reserved.

关键词： Hearing aids

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Synergia: Device-Edge Server Association for ISAC-assisted Mobile Edge Computing systems

Synergia: Device-Edge Server Association for ISAC-assisted M...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Panagiotis Charatsaris Arianna Santamaria Penafiel Maria Diamanti Eirini Eleni Tsiropoulou Symeon Papavassiliou Institute of Communication and Computer Systems School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The efficient operation of the unified Integrated Sensing and Communication (ISAC) – Mobile Edge Computing (MEC) systems is important for enhancing data sensing, communication, and computation processes in next-generation wireless systems. Despite prior research focusing on these systems, little attention has been given to optimizing the device-edge server associations. This paper addresses this gap by introducing the novel two-stage device-edge server association Synergia framework. Firstly, representative utility functions capture the characteristics of the devices and MEC servers by jointly considering their sensing, communication, and computation characteristics. Secondly, the Estimated Synergia framework leverages the Matching Theory to rapidly determine an initial device-server matching by disregarding the devices’ externalities, i.e., the matching decisions of other devices. Thirdly, the Accurate Synergia model refines and improves this matching by using the coalition formation games, while considering the devices’ externalities in optimizing the utilities of both the devices and the MEC servers. Extensive numerical evaluations demonstrate the Synergia’s operational efficiency and scalability, outperforming reinforcement learningbased approaches. Also, a real-world application involving car accident detection validates its applicability.

关键词： Wireless communication Multi-access edge computing Scalability Games Pricing Integrated sensing and communication Numerical models Servers Global communication Next generation networking

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A Multi-Level HXRI-Based Approach for XR-Based Surgical Training

A Multi-Level HXRI-Based Approach for XR-Based Surgical Trai...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Gupta, Avinash Cecil, J. Pirela-Cruz, Miguel University of Illinois Department of Industrial and Systems Enterprise Engineering Urbana-Champaign United States Center for Cyber-Physical Systems Dept. of Computer Science Oklahoma State University Stillwater United States Creighton University Dignity Regional Medical Center Chandler United States

ISBN: (纸本)9798350337020

In the past decade, Extended Reality (XR), through rapid technological advancement, has managed to make modest changes in surgical training approaches. Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR)-based simulators have been adopted for training in various surgical domains such as brain, eye, laparoscopic, and orthopedic surgery among others. However, there is a lack of effort in exploring Human Extended Reality Interaction (HXRI)-based concepts to design effective training environments that corroborate the actual training procedure. In this paper, an HXRI-based multi-level approach has been proposed for the creation of XR-based training environments. The multi-level approach takes advantage of both Virtual and Mixed Reality to create a holistic training environment while eliminating the disadvantage arising from using stand-alone VR and MR-based training environments. The approach was based on the results of an exhaustive study in which medical personnel interacted with VR and MR environments to train in an orthopedic surgical procedure. The approach, design, and development of the XR environments, the study, and the results from the study which underscore the importance of such a multi-level approach are presented in the paper. © 2023 IEEE.

关键词： Affordance Cognitive Load eXtended Reality (XR) HXRI surgery

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