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class="search-results"><ul class="results-list"><li class="result-item article-light first"><h3><a href="/doi/10.4108/eai.13-7-2018.159408">Intelligent reliability management in hyper-convergence cloud infrastructure using fuzzy inference system</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>23<span class="info-separator">)</span><span class="info-separator">: </span>e1</dd><br><dt class="title">Authors: </dt><dd class="value">Nadia Tabassum, Muhammad Saleem Khan, Sagheer Abbas, Tahir Alyas, Atifa Athar, Muhammad Adnan Khan</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Hyper-convergence is a new innovation in data center technology, it changes the way clouds manage and maintain enterprise IT infrastructure. Hyper-convergence is more efficient and basically agile technology environment. Cloud computing is a latest technology due to provision of latest cloud servi…</span><span class="full">Hyper-convergence is a new innovation in data center technology, it changes the way clouds manage and <br>maintain enterprise IT infrastructure. Hyper-convergence is more efficient and basically agile technology environment. Cloud computing is a latest technology due to provision of latest cloud services over the internet. The cloud service providers cannot promise accurate reliability of their services i.e. problem in provisioning of software or hardware failure etc. Reliability of cloud computing services depends on the ability of fault tolerance during the execution of services. There are so many factors can cause faults, such as network failure, browser crash, request time out or hacker attacks. When users are facing these types of faults, they usually resubmit their requests. However, if there is any key element involved in faults or errors, additional action may be needed to deal with system logs. If there is anomaly behavior occurred in faulted virtual machine, these VMs may need extra attention from cloud system protection and security point of view. In this paper, provision of reliability management in hyper-convergence cloud infrastructure is proposed and self-healing techniques in software as a service on the basis of failure in cloud services. Intelligent cloud service reliability framework will increase the reliability during execution of cloud service.<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/eai.13-7-2018.159409">A Step towards the Efficiency of Collisions in the Wireless Sensor Networks</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>23<span class="info-separator">)</span><span class="info-separator">: </span>e2</dd><br><dt class="title">Authors: </dt><dd class="value">Poonam K.K, Asif Ali Laghari, Rashid Ali Laghari</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Wireless Sensor Networks (WSNs) have an ideal tactic for implementing the number of applications due to evading complex wirings connections and their maintenance. On the other hand, the main source of data communication in other networks is protocols. The Medium Access control Protocol defines when…</span><span class="full">Wireless Sensor Networks (WSNs) have an ideal tactic for implementing the number of applications due to evading complex wirings connections and their maintenance. On the other hand, the main source of data communication in other networks is protocols. The Medium Access control Protocol defines when a wireless sensor (WS) transmits its recognizer <br>data. However, MAC protocols suffer from collisions that ultimately affect the performance of WSNs. Consequently, care must be taken for improving the efficiency of medium access protocol. This paper presents a model of the Lightweight medium access protocol (LMAC) protocol, which is energy efficient protocol suitable to analyze the probability of collisions for SN (Sensor Nodes) when the data is transmitted at the same time. This paper we consider connected <br>topologies that consist of 5 nodes. For analysis, we have used UMC PRO 0.2 (UPPAAL Model Checker Probabilistic) and results show that the chances of collisions decreases if the weight of nodes before they transmit data is increased. After that, we also compare the results of five nodes with their time slot 5, 6, and 7 depend on the chances of the collisions and suggest an optimistic choice of efficiency and also decrease the cost of networks a network set-up that improves the <br>performance and reduces the cost of the network.<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/eai.13-7-2018.159621">Empirical Analysis of Recent Advances, Characteristics and Challenges of Big Data</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>23<span class="info-separator">)</span><span class="info-separator">: </span>e3</dd><br><dt class="title">Authors: </dt><dd class="value">Burhanullah Khattak, Aurangzeb Khan, Khairullah Khan, Wahab Khan, Muhammad Kamran, Muhammad Fahad</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Here in this study, we provide an empirical analysis of recent advances, characteristic and challenges of big data. Initially, we acquaint the readers with the general background, history, and characteristics of big data including volume, velocity, value and variety etc. The scope of applications f…</span><span class="full">Here in this study, we provide an empirical analysis of recent advances, characteristic and challenges of big data. Initially, we acquaint the readers with the general background, history, and characteristics of big data including volume, velocity, value and variety etc. The scope of applications for big data including political services and government monitoring, enterprise <br>management, scientific research, public utilities, public administration and internet of things are illustrated. A detailed analysis is presented regarding opportunities and challenges faced by the public and private sectors during analysis phase of big data management such as storing, visualizing, capturing and so on. In addition, we investigated and reported a detailed empirical analysis of the most recent management tools like Hadoop and MapReduce, along with their different components, <br>usage, and limitation. Finally, open issues and future directions for this new and dynamic area of research are provided. The primary objective of this empirical analysis is to present a broad-spectrum perspective of this emerging research area with the goal to present big data related concepts in a coherent manner to the beginners.<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/eai.13-7-2018.159624">The impact of Planned Special Events (PSEs) on urban traffic congestion</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>23<span class="info-separator">)</span><span class="info-separator">: </span>e4</dd><br><dt class="title">Author: </dt><dd class="value">Ruwangi Fernando</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">The transport infrastructure of many cities has not been able to keep up with the pace of growth in the motorization rate or to counteract the intensification of urban traffic. Rising in traffic congestion in cities not only impacts the productivity costing billions but also responsible for more th…</span><span class="full">The transport infrastructure of many cities has not been able to keep up with the pace of growth in the motorization rate or to counteract the intensification of urban traffic. Rising in traffic congestion in cities not only impacts the productivity costing billions but also responsible for more than 40% of all CO2 emissions which results in global warming. While expansion <br>and construction of new roads may be considered in some cases, in most, better management of existing infrastructure to lower traffic congestion is the only option. <br>The current state of the art commercial solutions can predict the recurring traffic situations, as this behavior can be easily learned from historical data. The challenge is to predict the non-recurrent congestion caused by events such as accidents, adverse weather, construction zones and Planned Special Event (PSE). Past research has shown, PSEs such as concerts or <br>sports games, festivals and conventions has a huge impact on everyday urban transportation. Therefore, the aim of the proposed research is to investigate the impact PSEs on urban traffic congestion. <br>The proposed research is applying spatial-temporal big data mining methods to predict the impact of PSEs on the urban concession. Specifically, the proposed research will consider the characteristics of PSEs such as location, type, duration, audience and time and day of the event in the proposed analysis approach which enables to predict of urban congestion for future PSEs.<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/eai.13-7-2018.159794">Simulation and Security Calibration of Weather Management System for the Least Rainy Areas of Pakistan through Quantum Key Distribution</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>23<span class="info-separator">)</span><span class="info-separator">: </span>e5</dd><br><dt class="title">Authors: </dt><dd class="value">Nimra Dilawar, Sara Nadeem, Sania Arooj, Muhammad Rizwan, Fahad Ahmad</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Water plays a vital role for the survival of life. We get water in different forms of precipitation and rain is the most beneficial of all types. The demand for water is very high throughout the Pakistan, especially where we have limited natural water resources. Summer monsoon season has profound i…</span><span class="full">Water plays a vital role for the survival of life. We get water in different forms of precipitation and rain is the most beneficial of all types. The demand for water is very high throughout the Pakistan, especially where we have limited natural water resources. Summer monsoon season has profound impact in reducing water scarcity in Pakistan. Heavy rainfall results into floods whereas less rainfall creates drought which not only affects the economy but also puts human <br>life in risk. The aim of this research is to manage the movement of clouds from heavy rainfall areas to those areas where there is paucity of water, through satellite using electromagnetic waves. To accommodate such a sensitive satellite data which is paramount to a country, it is required to have some special systems based on quantum mechanics that are more efficient and pregnable than conventional computers. The consequences will be very high of not securing weather <br>management system, implies to country level disasters. In this paper we first discuss the technology behind quantum computer then proposed a secure architecture by employing quantum computers to ensure the security of data transmission for weather management system.<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/eai.29-7-2019.159800">Automated Skin Lesion Detection towards Melanoma</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>23<span class="info-separator">)</span><span class="info-separator">: </span>e6</dd><br><dt class="title">Authors: </dt><dd class="value">Maryam Bibi, Anmol Hamid, Samabia Tehseen</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Skin cancer melanoma is one of the most dangerous cancers in the world. It is crucial to diagnose it in initial phases before it invades other organs. However, it requires an efficient and reliable diagnostic computer aided system for early detection. In this research study we aim to detect the ski…</span><span class="full">Skin cancer melanoma is one of the most dangerous cancers in the world. It is crucial to diagnose it in initial phases before it invades other organs. However, it requires an efficient and reliable diagnostic computer aided system for early detection. In this research study we aim to detect the skin cancer from two different image datasets. We also present the solution for <br>images that contain disk objects. In initial phase we perform pre-processing, which is followed by segmentation phase. Then candidate dataset is evaluated using different measures such as accuracy, specificity, sensitivity and similarity. Obtained results are compared with results of techniques used in academic literature. We claim that our techniques give <br>better accuracy for cancer detection.<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/eai.29-7-2019.159834">Detection and mitigation of DDoS attack in cloud computing using machine learning algorithm</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>23<span class="info-separator">)</span><span class="info-separator">: </span>e7</dd><br><dt class="title">Authors: </dt><dd class="value">Aroosh Amjad, Tahir Alyas, Umer Farooq, Muhammad Arslan Tariq</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Cloud computing, with its staggering and on-demand services had revamped the technology so far. Cloud consumers are freely to use the applications and software on the premises of Pay-as-you go concept. This concept decreased the cost and make the services less expensive and more reliable. One of t…</span><span class="full">Cloud computing, with its staggering and on-demand services had revamped the technology so far. Cloud <br>consumers are freely to use the applications and software on the premises of Pay-as-you go concept. This concept decreased the cost and make the services less expensive and more reliable. One of the most important characteristic of cloud structure is on demand self-service. Cloud computing applications can be accessed anywhere at any time with much less cost. As cloud provide its consumers with its tremendous on demand services, besides this it is surviving from the excruciating security issues that are discourteous towards the cloud. There are, as many different attacks that results in making the servers down. One of the most hazardous attack is DDoS. This paper hiloghted the DDoS attack and its prevention technique which results in making the server side less vulnerable. The scenario includes, a transmission of million and trillion of packets in the form of DDoS at cloud-based websites, thus making it differentiated though different hosts. Making use of operating systems such as ParrotSec to make the attack possible. Last step includes detection and prevention through the most effective algorithms namely, Naïve Bayes and Random forest. This paper also focused the categories of attacks on cloud computing.<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/eai.13-7-2018.159975">Optimization of Governance Factors for Smart City Through Hierarchical Mamdani Type-1 Fuzzy Expert System Empowered with Intelligent Data Ingestion Techniques</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>23<span class="info-separator">)</span><span class="info-separator">: </span>e8</dd><br><dt class="title">Authors: </dt><dd class="value">Areej Fatima, Sagheer Abbas, Muhammad Asif, Muhammad Adnan Khan, Muhammad Saleem Khan</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">A Smart City is an urban area that uses the Internet of things (IoT) sensors to collect data and information to enhance the operational aptitude, in a way to manage assets and resources efficiently. Smart governance is a factor of a smart city for intelligent utilization of ICT to enhance the basic…</span><span class="full">A Smart City is an urban area that uses the Internet of things (IoT) sensors to collect data and information to enhance the operational aptitude, in a way to manage assets and resources efficiently. Smart governance is a factor of a smart city for intelligent utilization of ICT to enhance the basic leadership. The smart government may be considered as a reason for creating smart governance, through the application of rising information and communication technology for administering. Smart Governance is totally dependent on the information that is being recorderded. Smart consists of multiple factors that an essential role in smart city activities, which require complex collaborations between governments, citizens and different partners. In this article, a new computational method is proposed for the evaluation of the Governance factors of the smart city using Hierarchical Mamdani Type-1 Fuzzy Expert System and empowered with fuzzy based data ingestion techniques.<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>As the data volumes continue to increase and the ways of information dispersion across the globe continue to diversify, new scalable methods and structures are needed for efficiently processing those distributed and autonomous data. Grid computing, P2P technology, distributed information retrieval …</p></div><div class="full"><p>As the data volumes continue to increase and the ways of information dispersion across the globe continue to diversify, new scalable methods and structures are needed for efficiently processing those distributed and autonomous data. Grid computing, P2P technology, distributed information retrieval technology and networking technology all must be merged to address the scalability concern.</p></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Topics</h2><div class="abstract"><div class="shortened"><p>The scope of the journal includes:</p> <ul> <li>Scalable distributed information systems</li> <li>Scalable grid information systems</li> <li>Parallel information processing and systems</li> <li>Web information searching and retrieval</li> <li>Data mining</li> <li>Content delivery networks (CDN)</li> <li>VLDB</li> <li>P2P systems</li> <li>Scalable mobile…</li> </ul></div><div class="full"><p>The scope of the journal includes:</p> <ul> <li>Scalable distributed information systems</li> <li>Scalable grid information systems</li> <li>Parallel information processing and systems</li> <li>Web information searching and retrieval</li> <li>Data mining</li> <li>Content delivery networks (CDN)</li> <li>VLDB</li> <li>P2P systems</li> <li>Scalable mobile and wireless database systems</li> <li>Large scale sensor network systems</li> <li>Index compression methods</li> <li>Architectures for scalability</li> <li>Scalable information system applications</li> <li>Evaluation metrics for scalability</li> <li>Information security</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://mjl.clarivate.com/home">Web of Science Core Collection</a></li> <li><a href="https://www.engineeringvillage.com/home.url">Ei Compendex</a></li> <li><a href="https://doaj.org/toc/2032-9407">DOAJ</a></li> <li><a href="https://search.crossref.org/?q=2032-9407">CrossRef</a></li> <li>[EBSCO Discovery Service](https://www.ebsco.com/products/ebsco-disco…</li> </ul></div><div class="full"><ul> <li><a href="https://mjl.clarivate.com/home">Web of Science Core Collection</a></li> <li><a href="https://www.engineeringvillage.com/home.url">Ei Compendex</a></li> <li><a href="https://doaj.org/toc/2032-9407">DOAJ</a></li> <li><a href="https://search.crossref.org/?q=2032-9407">CrossRef</a></li> <li><a href="https://www.ebsco.com/products/ebsco-discovery-service">EBSCO Discovery Service</a></li> <li><a href="https://www.worldcat.org/title/eai-endorsed-transactions-on-scalable-information-systems/oclc/913714002&referer=brief_results">OCLC Discovery Services</a></li> <li><a href="https://europub.co.uk/journals/8124">EuroPub</a></li> <li><a href="http://miar.ub.edu/issn/2032-9407">MIAR</a></li> <li><a href="https://rzblx1.uni-regensburg.de/ezeit/detail.phtml?bibid=AAAAA&colors=7&lang=de&jour_id=237211">Elektronische Zeitschriftenbibliothek</a></li> <li><a href="https://publons.com/journal/37157/icst-transactions-on-scalable-information-systems">Publons</a></li> <li><a href="http://ulrichsweb.serialssolutions.com/login">UlrichsWEB</a></li> <li><a href="https://www.heal-link.gr/en/home-2/">Hellenic Academic Libraries Link</a></li> <li><a href="https://www.ingentaconnect.com/content/doaj/20329407">Ingenta Connect</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/databases/pq_scitech.html">SciTech Premium Collection (ProQuest)</a></li> <li><a href="https://scholar.google.sk/scholar?start=0&q=source:eai+source:endorsed+source:transactions+source:on+source:scalable+source:information+source:systems&hl=es&as_sdt=0,5&as_ylo=2018">Google Scholar</a></li> </ul></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Special Issues</h2><div class="abstract"><div class="shortened"><p><em>Call for Papers:</em> <a href="https://escripts.eai.eu/publication/366">Special issue on: Real-time image information processing with deep neural networks and data mining technologies</a> (Manuscript submission deadline: 2022-02-28; Notification of acceptance: 2022-04-15; Submission of final revised paper: 2022-…</p></div><div class="full"><p><em>Call for Papers:</em> <a href="https://escripts.eai.eu/publication/366">Special issue on: Real-time image information processing with deep neural networks and data mining technologies</a> (Manuscript submission deadline: 2022-02-28; Notification of acceptance: 2022-04-15; Submission of final revised paper: 2022-05-15; Publication of special issue (tentative): 2022-06-15)</p> <p><em>Guest Editor:</em> Dr. Prof. Hang Li (Northeastern University, China) <em>Guest Editor:</em> Dr. Prof. Jochen Schiewe (HafenCity Universität Hamburg, Germany)</p></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Editorial Board</h2><div class="abstract"><div class="shortened"><ul> <li>Editors-in-Chief</li> <li>Hua Wang, Victoria University, Australia</li> <li>Xiaohua Jia, City University of Hong Kong</li> <li>Editorial board</li> <li>Manik Sharma, DAV University, India</li> <li>Ajay Kattepur (Tata Consultancy Services)</li> <li>Aniello Castiglione (University of Salerno)</li> <li>Chang Choi (Chosun University)</li> <li>Cho-…</li> </ul></div><div class="full"><ul> <li>Editors-in-Chief</li> <li>Hua Wang, Victoria University, Australia</li> <li>Xiaohua Jia, City University of Hong Kong</li> <li>Editorial board</li> <li>Manik Sharma, DAV University, India</li> <li>Ajay Kattepur (Tata Consultancy Services)</li> <li>Aniello Castiglione (University of Salerno)</li> <li>Chang Choi (Chosun University)</li> <li>Cho-Li Wang (University of Hong Kong)</li> <li>Daniel S. Katz (University of Chicago)</li> <li>Fabrizio Silvestri (ISTI – CNR, Italy)</li> <li>Hamed Taherdoost (Hamta Business Solution Snd)</li> <li>Heng Tao Shen (University of Queensland)</li> <li>Houbing Song (Embry-Riddle Aeronautical University)</li> <li>José Manuel Machado (University of Minho, Portugal)</li> <li>Jose Merseguer (Universidad de Zaragoza)</li> <li>Jie Li (University of Tsukuba)</li> <li>Lin Yun (Harbin Engineering University)</li> <li>Phan Cong Vinh (Nguyen Tat Thanh University)</li> <li>Raj Gururajan (University of Southern Queensland)</li> <li>Sherman Chow (Chinese University of Hong Kong)</li> <li>Silva Fábio (University of Minho, Portugal)</li> <li>Steve Beitzel (Telcordia)</li> <li>Tzung-Pei Hong (National University of Kaohsiung, Kaohsing City, Taiwan)</li> <li>Wang-Chien Lee (The Pennsylvania State University)</li> <li>Weili Wu (The University of Texas at Dallas)</li> <li>Xueyan Tang (Nanyang Technological University)</li> <li>Vijayakumar Ponnusamy (SRM University, India)</li> <li>J Amudhavel (KL University, India)</li> <li>Yingshu Li (Georgia State University)</li> <li>Jerry Chun-Wei Lin (Western Norway University of Applied Sciences, Norway)</li> <li>Karolj Skala (Ruđer Bošković Institute, Croatia)</li> <li>Xiao-Zhi Gao (University of Eastern Finland, Finland)</li> <li>Thaier Hayajneh (Fordham University, USA)</li> <li>Chin-Ling Chen (Chaoyang University of Technology, Taiwan)</li> <li>Nuno M. Garcia (Faculty of Sciences, University of Lisbon, Portugal)</li> <li>Arianna D'Ulizia (Consiglio Nazionale delle Ricerche (CNR), Italy)</li> <li>Robertas Damaševičius (Kaunas University of Technology (KTU), Lithuania)</li> <li>Hiep Xuan Huynh (Can Tho University, VietNam)</li> <li>Ji Zhang (University of Southern Queensland, Australia)</li> <li>Xiaohui Tao (University of Southern Queensland, Australia)</li> <li>Ye Wang (National University of Defense Technology, China)</li> <li>Nageswara Rao Moparthi (KL University, India)</li> <li>Shuai Liu (Hunan Normal University, China)</li> <li>Prof Xiaoming Fu (Georg-August-University of Goettingen, Germany)</li> <li>Prof Zhisheng Huang (Vrije University of Amsterdam)</li> <li>Prof Rose Quan (Northumbria University, UK)</li> <li>Prof Shi Dong (Zhoukou Normal University, China)</li> <li>Dr Limei Peng (Kyungpook National University, South Korea)</li> <li>Prof Hui Ma( Victoria University of Wellington, New Zealand)</li> <li>Dr. Venkatesan Subramanian (Indian Institute of Information Technology – Allahabad, India)</li> <li>Dr Pon Harshavardhanan (VIT Bhopal University, India)</li> <li>Dr. Manish Kumar (The Indian Institute of Information Technology, Allahabad, India)</li> <li>Muzammil Hussain, University of Management and Technology, Lahore, Pakistan</li> <li>Michael Bewong, Charles Sturt University, Australia</li> <li>Shabir Ahmad, Gachon University, Korea</li> <li>Vu Nguyen, University of Science, Vietnam</li> <li>Xiaodi Huang, Charles Sturt University, Australia</li> <li>Jianming Yong, University of Southern Queensland, Australia</li> <li>Yogeshwar Vijayakumar Navandar; National Institute of Technology, Indian.</li> <li>Zhengyi Chai, Tiangong University in China, China</li> <li>Chuanlong Wang, Taiyuan Normal University, China</li> <li>Chin-Feng Lee, Chaoyang University of Technology, Taiwan</li> <li>Hsing-Chung Chen (Jack Chen), Asia University, Taiwan</li> <li>Wen-Yang Lin, National University of Kaohsiung, Taiwan</li> <li>Chun-Hao Chen, National Kaohsiung University of Science and Technology, Taiwan</li> <li>Mudasir Mohd, University of Kashmir, India.</li> <li>BalaAnand Muthu, INTI International University, Malaysia.</li> <li>Md Rafiqul Islam, Australian Institute of Higher Education, Australia.</li> <li>Jin Wang, Institute of Applied Physics and Computational Mathematics, China.</li> <li>Chandu Thota, University of Nicosia, Cyprus.</li> <li>Haris M. Khalid, University of Dubai, UAE.</li> <li>Dr. G. Reza Nasiri, Alzahra University, Tehran, Iran.</li> <li>Siuly Siuly, Victoria University, Australia</li> <li>Bishnu Prasad Gautam, Kanazawa Gakuin University, Japan</li> <li>Sivaparthipan C B, Bharathiar University, India</li> <li>Ting-Chia Hsu, National Taiwan Normal University, Taiwan</li> <li>Punitha Palanisamy, Tagore IET, India</li> <li>Lakshmana Kumar R, Tagore IET, India</li> <li>Weiwei Jiang, Beijing University of Posts and Telecommunications, Taiwan</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/sis/index</p></div><div class="full"><p>Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/sis/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">2032-9407</dd> <dt class="title">Volume</dt> <dd class="value">6</dd></dl><dl class="metadata"><dt class="title">Published</dt> <dd class="value">2019-10-18</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 href="https://doaj.org/search?source=%7B%22query%22%3A%7B%22filtered%22%3A%7B%22filter%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22term%22%3A%7B%22index.publisher.exact%22%3A%22European%20Alliance%20for%20Innovation%20(EAI)%22%7D%7D%5D%7D%7D%2C%22query%22%3A%7B%22query_string%22%3A%7B%22query%22%3A%22european%20alliance%20for%20innovation%22%2C%22default_operator%22%3A%22AND%22%2C%22default_field%22%3A%22index.publisher%22%7D%7D%7D%7D%7Dj" target="_blank"><img class="logo doaj-logo" src="/images/doaj.jpg" alt="DOAJ"></a><a href="https://www.portico.org/publishers/eai/" target="_blank"><img class="logo portico-logo" src="/images/portico.png" alt="Portico"></a><a href="http://eai.eu/" target="_blank"><img class="logo eai-logo" src="/images/eai.png"></a></div></footer></div><div class="footer-container"><div class="footer-width"><div class="footer-column logo-column"><a href="https://eai.eu/"><img src="https://eudl.eu/images/logo_new-1-1.png" alt="EAI Logo"></a></div><div class="footer-column"><h4>About EAI</h4><ul><li><a href="https://eai.eu/who-we-are/">Who We Are</a></li><li><a href="https://eai.eu/leadership/">Leadership</a></li><li><a href="https://eai.eu/research-areas/">Research Areas</a></li><li><a href="https://eai.eu/partners/">Partners</a></li><li><a href="https://eai.eu/media-center/">Media Center</a></li></ul></div><div class="footer-column"><h4>Community</h4><ul><li><a href="https://eai.eu/eai-community/">Membership</a></li><li><a href="https://eai.eu/conferences/">Conference</a></li><li><a href="https://eai.eu/recognition/">Recognition</a></li><li><a href="https://eai.eu/corporate-sponsorship">Sponsor Us</a></li></ul></div><div class="footer-column"><h4>Publish with EAI</h4><ul><li><a href="https://eai.eu/publishing">Publishing</a></li><li><a href="https://eai.eu/journals/">Journals</a></li><li><a href="https://eai.eu/proceedings/">Proceedings</a></li><li><a href="https://eai.eu/books/">Books</a></li><li><a href="https://eudl.eu/">EUDL</a></li></ul></div></div></div><script type="text/javascript" src="https://eudl.eu/js/gacode.js"></script><script src="/js/highlight.pack.js"></script><script>hljs.initHighlightingOnLoad();</script><script type="application/ld+json">{"@context":"http://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"item":{"@id":"http://eudl.eu","name":"Home","image":null}},{"@type":"ListItem","position":2,"item":{"@id":"http://eudl.eu/journals","name":"Journals","image":null}},{"@type":"ListItem","position":3,"item":{"@id":"http://eudl.eu/journal/sis","name":"sis","image":null}},{"@type":"ListItem","position":4,"item":{"@id":"/issue/sis/6/23","name":"Issue 23","image":null}}]}</script></body></html>