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<html><head><title>EAI Endorsed Transactions on Industrial Networks and Intelligent Systems - EUDL</title><link rel="icon" href="/images/favicon.ico"><link rel="stylesheet" type="text/css" href="/css/screen.css"><link rel="stylesheet" href="/css/zenburn.css"><meta http-equiv="Content-Type" content="charset=utf-8"><meta name="viewport" content="width=device-width, initial-scale=1.0"><meta name="Description" content="Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/inis/index"><script type="text/javascript" src="https://services.eai.eu//load-signup-form/EAI"></script><script type="text/javascript" src="https://services.eai.eu//ujs/forms/signup/sso-client.js"></script><script type="text/javascript">if (!window.EUDL){ window.EUDL={} };EUDL.cas_url="https://account.eai.eu/cas";EUDL.profile_url="https://account.eai.eu";if(window.SSO){SSO.set_mode('eai')};</script><script type="text/javascript" src="/js/jquery.js"></script><script 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1</a></div></div></section></section><section class="info-and-search"><div class="manage-menu"></div><a href="/journal/inis"><h1>EAI Endorsed Transactions on Industrial Networks and Intelligent Systems</h1></a><section class="issue-number">Issue 4, 2023</section><section class="editors"><strong>Editor(s)-in-Chief: </strong><span class="editor">Trung Q. Duong</span>, <span class="editor">Le Nguyen Bao</span> and <span class="editor">Nguyen-Son Vo</span></section><section class="issue-tabs"><div class="tabs"><ul><li><a name="articles">Articles</a></li><li><a name="meta">Information</a></li></ul></div><div class="content"><div name="articles"><section id="publications-results" class="search-results"><ul class="results-list"><li class="result-item article-light first"><h3><a href="/doi/10.4108/eetinis.v10i4.4359">Jointly power allocation and phase shift optimization for RIS empowered downlink cellular networks</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>23</strong><span class="info-separator">(</span>4<span class="info-separator">)</span><span class="info-separator">: </span></dd><br><dt class="title">Authors: </dt><dd class="value">Phuc Quang Truong, Tan Do-Duy, Van-Ca Phan, Antonino Masaracchia</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Reconfigurable Intelligent Surfaces (RIS) have been highlighted by the research community as a key enabling technology for the enhancement of next-generation wireless network performance, including energy efficiency, spectral efficiency, and network throughput. This paper investigates how RIS-assis…</span><span class="full">Reconfigurable Intelligent Surfaces (RIS) have been highlighted by the research community as a key enabling technology for the enhancement of next-generation wireless network performance, including energy efficiency, spectral efficiency, and network throughput. This paper investigates how RIS-assisted communication can effectively maximize the downlink throughput of a cellular network. Specifically, the paper considers a communication scenario where a single base station serves multiple ground users with the aid of an RIS placed on a building facade. For such a communication scenario, we considered an optimization problem aimed at maximizing the overall downlink throughput by jointly optimizing power allocation at the base station and phase shift of RIS reflecting elements, subject to power consumption and quality-of-service constraints. To address its non-convex nature, the original optimization problem has been divided into two subproblems. The first one, for power control with fixed phase shift values, is a convex problem that can be easily solved. Subsequently, a phase shift searching procedure to solve the non-convex problem of RIS phase shift optimization has been adopted. The results from numerical simulations show that the proposed method outperforms other conventional methods proposed in the literature. In addition, computational complexity analysis has been conducted to prove the low complexity of the proposed method. <br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li><li class="result-item article-light"><h3><a href="/doi/10.4108/eetinis.v10i4.4315">An Intelligent Fashion Object Classification Using CNN</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>23</strong><span class="info-separator">(</span>4<span class="info-separator">)</span><span class="info-separator">: </span>e2</dd><br><dt class="title">Authors: </dt><dd class="value">Debabrata Swain, Kaxit Pandya, Jay Sanghvi, Yugandhar Manchala</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Every year the count of visually impaired people is increasing drastically around the world. At present time, approximately 2.2 billion people are suffering from visual impairment. One of the major areas where our model will affect public life is the area of house assistance for specially-abled per…</span><span class="full">Every year the count of visually impaired people is increasing drastically around the world. At present time, approximately 2.2 billion people are suffering from visual impairment. One of the major areas where our model will affect public life is the area of house assistance for specially-abled persons. Because of visual improvement, these people face lots of issues. Hence for this group of people, there is a high need for an assistance system in terms of object recognition. For specially-abled people sometimes it becomes really difficult to identify clothing-related items from one another because of high similarity. For better object classification we use a model which includes computer vision and CNN. Computer vision is the area of AI that helps to identify visual objects. Here a CNN-based model is used for better classification of clothing and fashion items. Another model known as Lenet is used which has a stronger architectural structure. Lenet is a multi-layer convolution neural network that is mainly used for image classification tasks. For model building and validation MNIST fashion dataset is used. <br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li><li class="result-item article-light"><h3><a href="/doi/10.4108/eetinis.v10i4.4192">On the Security and Reliability Trade-off of the Satellite Terrestrial Networks with Fountain Codes and Friendly Jamming</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>23</strong><span class="info-separator">(</span>4<span class="info-separator">)</span><span class="info-separator">: </span>e3</dd><br><dt class="title">Authors: </dt><dd class="value">Quang Sang Nguyen, Van Hien Nguyen, Trung Duy Tran, Luong Nhat Nguyen, Lam-Thanh Tu</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">The performance of the satellite-terrestrial network with Fountain codes (FCs) is conducted in the present work. More precisely, the air-to-ground link is modeled according to the shadow-Rician distribution to capture the strong light-of-sight (LOS) path as well as the impact of the shadowing. As a…</span><span class="full">The performance of the satellite-terrestrial network with Fountain codes (FCs) is conducted in the present work. More precisely, the air-to-ground link is modeled according to the shadow-Rician distribution to capture the strong light-of-sight (LOS) path as well as the impact of the shadowing. As a result, we employ the directional beamforming at both the satellite and relay to mitigate such an ultra-long transmission distance. We investigate the trade-off between the reliability and security aspects. Particularly, we derive the outage probability (OP) and intercept probability (IP) in the closed-form expressions. To further facilitate the security of the considered networks, the friendly jamming scheme is deployed as well. Finally, simulation results based on the Monte-Carlo method are given to corroborate the exactness of the developed mathematical framework and to identify key parameters such as antenna gain, and transmit power that have a big impact on the considered networks. <br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li><li class="result-item article-light"><h3><a href="/doi/10.4108/eetinis.v10i4.4237">Cybersecurity in Motion: A Survey of Challenges and Requirements for Future Test Facilities of CAVs</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>23</strong><span class="info-separator">(</span>4<span class="info-separator">)</span><span class="info-separator">: </span>e5</dd><br><dt class="title">Authors: </dt><dd class="value">Ioannis Mavromatis, Theodoros Spyridopoulos, Pietro Carnelli, Woon Hau Chin, Ahmed Khalil, Jennifer Chakravarty, Lucia Cipolina Kun, Robert J. Piechocki, Colin Robbins, Daniel Cunnington, Leigh Chase, Lamogha Chiazor, Chris Preston, Rahul , Aftab Khan</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">The way we travel is changing rapidly and Cooperative Intelligent Transportation Systems (C-ITSs) are at the forefront of this evolution. However, the adoption of C-ITSs introduces new risks and challenges, making cybersecurity a top priority for ensuring safety and reliability. Building on this pr…</span><span class="full">The way we travel is changing rapidly and Cooperative Intelligent Transportation Systems (C-ITSs) are at the forefront of this evolution. However, the adoption of C-ITSs introduces new risks and challenges, making cybersecurity a top priority for ensuring safety and reliability. Building on this premise, this paper introduces an envisaged Cybersecurity Centre of Excellence (CSCE) designed to bolster researching, testing, and evaluating the cybersecurity of C-ITSs. We explore the design, functionality, and challenges of CSCE's testing facilities, outlining the technological, security, and societal requirements. Through a thorough survey and analysis, we assess the effectiveness of these systems in detecting and mitigating potential threats, highlighting their flexibility to adapt to future C-ITSs. Finally, we identify current unresolved challenges in various C-ITS domains, with the aim of motivating further research into the cybersecurity of C-ITSs. <br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li></ul></section></div><div name="meta"><h2>Scope</h2><div class="abstract"><div class="shortened"><p>EAI Endorsed Transactions on Industrial Networks and Intelligent Systems is open access, a peer-reviewed scholarly journal focused on ubiquitous computing, cloud computing, and cyber-physical system, all kinds of networks in large-scale factories, including a lot of traditional and new industries. …</p></div><div class="full"><p>EAI Endorsed Transactions on Industrial Networks and Intelligent Systems is open access, a peer-reviewed scholarly journal focused on ubiquitous computing, cloud computing, and cyber-physical system, all kinds of networks in large-scale factories, including a lot of traditional and new industries. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications with a quarterly frequency (four issues per year). Authors are not charged for article submission and processing. This journal is co-organised, and managed by Duy Tan University, Vietnam.</p> <p>INDEXING: Scopus (CiteScore: 3.1), Compendex, DOAJ, ProQuest, EBSCO, DBLP</p></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Topics</h2><div class="abstract"><div class="shortened"><ul> <li>Applications of wireless sensor networks, body area networks in large-scale industrial applications, such as fault theories of wireless networks, including routing, network control and management, reliable transmission and architectures, etc.</li> <li>Applications of social networking, big data, ubiqui…</li> </ul></div><div class="full"><ul> <li>Applications of wireless sensor networks, body area networks in large-scale industrial applications, such as fault theories of wireless networks, including routing, network control and management, reliable transmission and architectures, etc.</li> <li>Applications of social networking, big data, ubiquitous computing, mobile computing, and cloud computing in various industries and services (e.g., intelligent systems enhanced by social networking, cloud-based industrial networks, cloud-assisted intelligent systems, etc.)</li> <li>Analysis of industrial control and communication networks, including network lifetime, security, network scalability, reliability, stability, etc.</li> <li>Design and choice of industrial, intelligent, application-specific network protocols and algorithms (e.g., EtherNet/IP, Ethernet Powerlink, EtherCAT, Modbus-TCP, Profinet, SERCOS III, etc.) at any communication layer</li> <li>Opportunistic networks in the industry, such as underwater sensor networks in sewage treatment systems, including establishing a temporary data transmission structure using available devices (e.g., underwater robot, surface data station, surface sink and under water sink), optimizing horizontal multi-hop data links (e.g., 3D data transmission), etc.</li> <li>Applications of intelligent systems in various industries, including collaborative systems, quality control, optimization, decision support, planning, high-level control concepts (e.g., multi-agent and holonic systems, service-oriented architectures), low-level control concepts (e.g., IEC 61131-3 and IEC 61499-based control), advanced system engineering concepts (e.g., model-driven development, component-based design), supply chains, value chains, virtual organizations, and virtual societies, emergency preparedness, crisis management, business channels, electronic marketplaces, enterprise resources planning, etc.</li> <li>Design and analysis of real-time embedded industrial systems, including real-time computing, real-time operating systems, real-time communications, networked embedded systems technology, etc.</li> <li>Novel control techniques, with respect to process control, equipment control, supervisory control, adaptive control, motion control, etc.</li> <li>Automated manufacturing systems, regarding formal modeling and analysis of manufacturing systems, scheduling of manufacturing systems, queuing systems and petri nets in manufacturing systems, etc.</li> <li>Computational intelligence in automation, including neural, fuzzy, evolutionary approaches in automation, ant colonies optimization and swarm intelligence in automation, machine learning, expert systems, etc.</li> <li>Hardware and software design and development for intelligent systems, such as intelligent and humanized production monitoring and control, etc.</li> <li>Big data analysis and processing in various industries and services, including constructing data analysis models, providing data analysis and processing tools and designing various optimization algorithms based on data analysis.</li> <li>Crowd-sourced behavior analysis in various industry and services, such as measuring and calculating the diffusion direction and speed of gas in the petrochemical industry based on crowd-sourced data from a large number of and various types of sensors, as well as product and service evaluation.</li> <li>Simulation and testbed of current industrial networks and intelligent systems, including network performance analysis, automated manufacturing, intelligent monitoring, disaster prevention, etc.</li> <li>Vision of future smart factories, service, marketing, and their integration, incorporating current existing technologies.</li> <li>Multimedia applications, content management, process management and knowledge management for various industries, services, and engineering education: including multimedia processing, multimedia retrieval, multimedia indexing, image sensing, image processing, image coding, image recognition, etc.</li> <li>Pattern recognition methods for various industries and services: including statistical theory, clustering, similarity measures, unsupervised learning, supervised learning, etc.</li> <li>Survey, review and essay of current industrial networks researches and intelligent systems development.</li> </ul></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Indexing</h2><div class="abstract"><div class="shortened"><ul> <li><a href="https://www.scopus.com/sourceid/21101049547">Scopus</a></li> <li><a href="https://doaj.org/toc/2410-0218">DOAJ</a></li> <li><a href="https://dblp.uni-trier.de/db/journals/inis/">DBLP</a></li> <li><a href="https://search.crossref.org/?q=2410-0218">CrossRef</a></li> <li>[OCLC Discovery Services](https://www.worldcat.org/search?q=eai+endorsed+tran…</li> </ul></div><div class="full"><ul> <li><a href="https://www.scopus.com/sourceid/21101049547">Scopus</a></li> <li><a href="https://doaj.org/toc/2410-0218">DOAJ</a></li> <li><a href="https://dblp.uni-trier.de/db/journals/inis/">DBLP</a></li> <li><a href="https://search.crossref.org/?q=2410-0218">CrossRef</a></li> <li><a href="https://www.worldcat.org/search?q=eai+endorsed+transactions+on+industrial+networks&qt=owc_search">OCLC Discovery Services</a></li> <li><a href="https://europub.co.uk/journals/8120">EuroPub</a></li> <li><a href="https://publons.com/journal/29023/eai-endorsed-transactions-on-industrial-networks-a">Publons</a></li> <li><a href="https://app.dimensions.ai/discover/publication?or_facet_source_title=jour.1152852">Dimensions</a></li> <li><a href="https://www.proquest.com/products-services/Publicly-Available-Content-Database.html#overviewlinkSection">Publicly Available Content Database (ProQuest)</a></li> <li><a href="https://www.proquest.com/products-services/adv_tech_aero.html">Advanced Technologies & Aerospace Database (ProQuest)</a></li> <li><a href="https://www.proquest.com/products-services/adv_tech_aero.html">SciTech Premium Collection (ProQuest)</a></li> <li><a href="https://scholar.google.sk/scholar?as_ylo=2018&q=source:EAI+source:Endorsed+source:Transactions+source:on+source:Industrial+source:Networks+source:and+source:Intelligent+source:Systems&hl=es&as_sdt=0,5">Google Scholar</a></li> </ul></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Editorial Board</h2><div class="abstract"><div class="shortened"><ul> <li>Ala Al-Fuqaha (Western Michigan University, USA)</li> <li>Al-Sakib Khan Pathan (Southeast University, Bangladesh)</li> <li>Ammar Rayes (Cisco Systems, USA)</li> <li>Antonino Masaracchia (IIT-CNR, Italy)</li> <li>Athanasios Maglaras (Dr, Prof . ofT.E.I. of Larissa)</li> <li>Berk Canberk (Northeastern University, USA)</li> <li>Ca V. Phan (…</li> </ul></div><div class="full"><ul> <li>Ala Al-Fuqaha (Western Michigan University, USA)</li> <li>Al-Sakib Khan Pathan (Southeast University, Bangladesh)</li> <li>Ammar Rayes (Cisco Systems, USA)</li> <li>Antonino Masaracchia (IIT-CNR, Italy)</li> <li>Athanasios Maglaras (Dr, Prof . ofT.E.I. of Larissa)</li> <li>Berk Canberk (Northeastern University, USA)</li> <li>Ca V. Phan (Ho Chi Minh City University of Technology and Education, Vietnam)</li> <li>Chau Yuen (Singapore University of Technology and Design, Singapore)</li> <li>Chengfei Liu (Swinburne University of Technology, Australia)</li> <li>Chinmoy Kundu (University of Texas at Dallas, USA)</li> <li>Christer Carlsson (Åbo Akademi University, Finland)</li> <li>Chunsheng Zhu (University of British Columbia)</li> <li>Constandinos Mavromoustakis (University of Nicosia, Cyprus)</li> <li>Der-Jiunn Deng (National Changhua University of Education, Taiwan)</li> <li>Dickson Chiu (The University of Hong Kong)</li> <li>Eleanna Kafeza (Athens University of Economics and Business, Greece)</li> <li>Fu-ren Lin (National Tsing Hua University, Taiwan)</li> <li>Gerhard Hancke (University of London, UK)</li> <li>Guangjie Han (Hohai University, China)</li> <li>Guojun Wang (Central South University, China)</li> <li>Hacene Fouchal (University of Reims Champagne-Ardenne, France)</li> <li>Haklae Kim (Chung-Ang University, South Korea)</li> <li>Halil Yetgin (Bitlis Eren University, Turkey)</li> <li>Hideyasu Sasaki (Ritsumeikan University, Kyoto, Japan)</li> <li>Ho-fung Leung (Chinese University of Hong Kong, Hong Kong)</li> <li>Honggang Wang (University of Massachusetts Dartmouth, USA)</li> <li>Hua Hu (Hangzhou Dianzi University, China)</li> <li>Ibrahim Kushchu (Mobile Government Consortium International, UK)</li> <li>Irene Kafeza (Irene Law Office, Greece)</li> <li>Isabelle Comyn-Wattiau (ESSEC Business School Paris, France)</li> <li>Jaime Lloret- Mauri (Universitat Politècnica de València, Spain)</li> <li>Javier M. Aguiar (Universidad de Valladolid, Valladolid, Spain)</li> <li>Jesus Alonso-Zarate (Telecommunications Technology Center of Catalonia, Spain)</li> <li>Jian Yang (Macquarie University, Australia)</li> <li>Jiankun Hu (University of New South Wales, Australia)</li> <li>Jianmin Jiang (Shenzhen University)</li> <li>Jianwei Niu (Beihang University, China)</li> <li>Jinlei Jiang (Tsinghua University, China)</li> <li>Jinsong Wu (Bell Laboratory, China)</li> <li>Joel Rodrigues (Inst. Telecomunicações, Univ. of Beira Interior, Portugal)</li> <li>Juan Trujillo (University of Alicante, Spain)</li> <li>Jucheng Yang (Tianjing University of Technology, China)</li> <li>Junqing Zhang (Queen's University Belfast)</li> <li>KUN WANG (Nanjing University of Posts and Telecommunications)</li> <li>Kuo-Ming Chao (Leader – Distributed Systems and Modelling Research Group, UK)</li> <li>Leandros A. Maglaras (De Montfort University, UK)</li> <li>Lei Wang (Dalian University of Technology, China)</li> <li>Liang Zhou (Nanjing University of Posts and Telecommunications, China)</li> <li>Long D. Nguyen (Dong Nai University, Vietnam)</li> <li>Maggie M. Wang (The University of Hong Kong, Hong Kong)</li> <li>Nghia Duong-Trung (German Research Center for Artificial Intelligence, Germany)</li> <li>Ngo Hoang Tu (Seoul National University of Science and Technology, South Korea)</li> <li>Nguyen Van Nam (Viettel, Vietnam)</li> <li>Nicholas C Romano (Oklahoma State University, USA)</li> <li>Noel Crespi (Institut Mines-Telecom, Telecom SudParis, France)</li> <li>Panlong Yang (PLA University of Science and Technology, China)</li> <li>Pasi Tyrväinen (University of Jyväskylä, Finland)</li> <li>Patrick C.K. Hung (University of Ontario Institute of Technology, Canada)</li> <li>Periklis Chatzimisios (Alexander TEI of Thessaloniki, Greece)</li> <li>Pierluigi Siano (Università degli Studi di Salerno, Italy)</li> <li>Pirkko Walden (Abo Akademi University, Finland)</li> <li>Phuong Bui (Duy Tan University, Vietnam)</li> <li>Raymond Y.K Lau (City University of Hong Kong, Hong Kong)</li> <li>Richard Yu (Carleton University, Canada)</li> <li>Rong Yu (Guangdong University of Technology, China)</li> <li>Rose Hu (Utah State University, USA)</li> <li>Sammy Chan (City University of HongKong, HK)</li> <li>Shing-Chi Cheung (Hong Kong University of Science and Technology, Hong Kong)</li> <li>Stephen J. H. Yang (National Central University, Taiwan)</li> <li>Syed Hassan Ahmed (University of Central Florida, USA)</li> <li>Thanh-Phuong Nguyen (University of Toulon, France)</li> <li>Tran Trung Duy (PTIT, VietNam)</li> <li>Trang Hoang (Ho Chi Minh City University of Technology - Vietnam National University Ho Chi Minh City, Vietnam)</li> <li>Tuan-Minh Pham (Phenikaa University, Vietnam)</li> <li>Umar Zakir Abdul Hamid (Sensible 4 Oy, Helsinki)</li> <li>Victor Leung (The University of British Columbia)</li> <li>Vo Nguyen Son Dr. (Duy Tan University, Vietnam)</li> <li>Wai-Wa Fung (Information Security and Forensics Society, Hong Kong)</li> <li>Walid Gaaloul (Institut National des Télécommunications, France)</li> <li>Weiwei Jiang, (Beijing University of Posts and Telecommunications (BUPT), China)</li> <li>Wendy W. Y. Hui (University of Nottingham at Ningbo, China)</li> <li>William Cheung (Hong Kong Baptist University, Hong Kong)</li> <li>Xianfu Chen (VTT Technical Research Centre of Finland, Finland)</li> <li>Xiang Gui (Massey University, New Zealand)</li> <li>Xiaoling Wu (Chinese Academy of Sciences, China)</li> <li>Xu Wang (Heriot Watt University, UK)</li> <li>Yan Bai (University of Washington Tacoma, USA)</li> <li>Yan Zhang (Simula Research Laboratory and University of Oslo, Norway)</li> <li>Yi Zhuang (Zhejian Gongshang University, China)</li> <li>Yong Li (Tsinghua University, China)</li> <li>Yong Tang (South China Normal University, China)</li> <li>Yuanfang Chen (Institute Mines-Telecom, University Pierre and Marie Curie )</li> <li>Yuexing Peng (Beijing University of Posts and Telecommunications, China)</li> <li>Yuqing Sun (Shangdong University, China)</li> <li>Zakaria Maamar (Zayed University, UAE)</li> <li>Zhangbing Zhou (China University of Geosciences, China)</li> <li>Zhichao Sheng (Shanghai University, China)</li> <li>ZhiMing Cai (Macau University of Science and Technology, Macau)</li> <li>Mithun Mukherjee (Nanjing University of Information Science and Technology, China)</li> <li> </li> </ul></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Journal Blurb</h2><div class="abstract"><div class="shortened"><p>Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/inis/index</p></div><div class="full"><p>Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/inis/index</p></div> <span class="expander more"><a class="trigger">more »</a></span></div></div></div></section><section class="publication-info"><dl class="metadata"><dt class="title">Publisher</dt> <dd class="value">EAI</dd> <dt class="title">ISSN</dt> <dd class="value">2410-0218</dd> <dt class="title">Volume</dt> <dd class="value">10</dd></dl><dl class="metadata"><dt class="title">Published</dt> <dd class="value">2023-11-06</dd></dl></section></section></form></section></section><div class="clear"></div><footer><div class="links"><a href="https://www.ebsco.com/" target="_blank"><img class="logo ebsco-logo" src="/images/ebsco.png" alt="EBSCO"></a><a href="https://www.proquest.com/" target="_blank"><img class="logo proquest-logo" src="/images/proquest.png" alt="ProQuest"></a><a href="https://dblp.uni-trier.de/db/journals/publ/icst.html" target="_blank"><img class="logo dblp-logo" src="/images/dblp.png" alt="DBLP"></a><a 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