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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/eai.25-9-2017.153146">Welcome message from the Editor-in-Chief and Co-Editor-in-Chief</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>17</strong><span class="info-separator">(</span>14<span class="info-separator">)</span><span class="info-separator">: </span>e1</dd><br><dt class="title">Author: </dt><dd class="value">Xiaohua Jia</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened"> </span><span class="full"> <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.25-9-2017.153147">A Comparative Analysis of Feature Extraction Methods for Classifying Colon Cancer Microarray Data</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>17</strong><span class="info-separator">(</span>14<span class="info-separator">)</span><span class="info-separator">: </span>e2</dd><br><dt class="title">Authors: </dt><dd class="value">M.O. Arowolo, R.M. Isiaka, S.O. Abdulsalam, Y.K. Saheed, K.A. Gbolagade</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Feature extraction is a proficient method for reducing dimensions in the analysis and prediction of cancer classification. Microarray procedure has shown great importance in fetching informative genes th at needs enhancement in diagnosis. Microarray data is a challenging task due to high dimensiona…</span><span class="full">Feature extraction is a proficient method for reducing dimensions in the analysis and prediction of cancer classification. Microarray procedure has shown great importance in fetching informative genes th at needs enhancement in diagnosis. Microarray data is a challenging task due to high dimensional-low sample dataset with a lot of noisy or irrelevant genes and missing data. In this paper, a comparative study to demonstrate the effectiveness of feature ext raction as a dimensionality reduction process is proposed, and concludes by investigating the most efficient approach that can be used to enhance classification of microarray. Principal Component Analysis (PCA) as an unsupervised technique and Partial Least Square (PLS) as a supervised technique are considered, Support Vector Machine (SVM) classifier were applied on the dataset. The overall result shows that PLS algorithm provides an improved performance of about 95.2% accu racy compared to PCA algorithms. <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.25-9-2017.153148">An Unsupervised Approach of Knowledge Discovery from Big Data in Social Network</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>17</strong><span class="info-separator">(</span>14<span class="info-separator">)</span><span class="info-separator">: </span>e3</dd><br><dt class="title">Author: </dt><dd class="value">Mohiuddin Ahmed</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Social network is a common source of big data. It is becoming increasingly diﬃcult to understand what is happening in the network due to the volume. To gain meaningful information or identifying the underlying patterns from social networks, summarization is an useful approach to enhance understandi…</span><span class="full">Social network is a common source of big data. It is becoming increasingly diﬃcult to understand what is happening in the network due to the volume. To gain meaningful information or identifying the underlying patterns from social networks, summarization is an useful approach to enhance understanding of the pattern from big data. However, existing clustering and frequent item-set based summarization techniques lack the ability to produce meaningful summary and fails to represent the underlying data pattern. In this paper, the eﬀectiveness co-clustering is explored to create meaningful summary of social network data such as Twitter. Experimental results show that, using co-clustering for creating summary provides signiﬁcant beneﬁt over the existing techniques.<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.25-9-2017.153149">Software Defined Network-based Scalable Resource Discovery for Internet of Things</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>17</strong><span class="info-separator">(</span>14<span class="info-separator">)</span><span class="info-separator">: </span>e4</dd><br><dt class="title">Authors: </dt><dd class="value">Mahbuba Afrin, Redowan Mahmud</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Geo-distributed and heterog eneous Internet of Things (IoT) devices can gener ate hug e amoun t of data. Ineÿcien t manag emen t of IoT-da ta promotes netw ork cong estion and increases computa tional overhead on the data-processing entities. Traditional netw orking architecture, tha t is lack of f…</span><span class="full">Geo-distributed and heterog eneous Internet of Things (IoT) devices can gener ate hug e amoun t of data. Ineÿcien t manag emen t of IoT-da ta promotes netw ork cong estion and increases computa tional overhead on the data-processing entities. Traditional netw orking architecture, tha t is lack of functional abstr action and monitoring capabilities, often fails to meet the dynamics of IoT. Softw are Define Netw ork (SDN) can be a viable alterna tiv e of the traditional netw orking architecture while dealing with IoT. In SDN, manag emen t, monitoring and context sensing of the connected componen ts are sim plifie and can be customized. In this paper , SDN-sensed contextual inf orma tion of dieren t componen ts (computa tional entities, netw ork, IoT devices) are combined together to facilita te scalable resource discov ery in IoT. The proposed policy targ ets balanced processing and cong estion-less forw arding of IoT-da ta. Through sim ula tion studies, it has been demonstr ated tha t the SDN-based resource discov ery in IoT outperf orms the traditional netw orking based approaches in terms of resource discov ery time and Quality of Service (QoS) satisf action rate.<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.25-9-2017.153150">Software-Defined Network Testbed Using ZodiacFX a Hardware Switch for OpenFlow</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>17</strong><span class="info-separator">(</span>14<span class="info-separator">)</span><span class="info-separator">: </span>e5</dd><br><dt class="title">Authors: </dt><dd class="value">Fahad Nazir, Qazi Humayun, R Badlishah Ahmad, Shamsul Jamel Elias</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">Software-defined network (SDN) is a new programmable networking designed to perform tasks easier by enabling network administrators to add network control via a centralized control platform and open interfaces. Common network use procedures such as traffic shifts, troubleshooting and various types …</span><span class="full">Software-defined network (SDN) is a new programmable networking designed to perform tasks easier by enabling network administrators to add network control via a centralized control platform and open interfaces. Common network use procedures such as traffic shifts, troubleshooting and various types of device configuration. Thus devices are needed to reconfigure with the network, in order to create a reaction with events. In this paper, we have developed an SDN testbed using Zodiac FX a hardware switch for OpenFlow experiment. This research is utilized Zodiac FX a hardware switch to test the usage and discuss about the SDN controllers. Ryu controller is configured for testbed development. The main contribution of this paper in threefold as follows: first it provides the configuration of Ryu controller, second, it provides the configuration of Zodiac FX switch and lastly it develops a simple SDN testbed for OpenFlow. <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.25-9-2017.153151">Intricacies of Unstructured Data</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">sis<span class="info-separator"> </span><strong>17</strong><span class="info-separator">(</span>14<span class="info-separator">)</span><span class="info-separator">: </span>e6</dd><br><dt class="title">Author: </dt><dd class="value">Rajeshwari K Rai</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">This research paper is an attempt to explore unstructured data that has taken the world of data science by storm. Handling the unprecedented growth of unstructured data is a big challenge faced by most data scientists. This paper discusses about the types and sources of unstructured data and effe…</span><span class="full">This research paper is an attempt to explore unstructured data that has taken the world of data science by storm. Handling the unprecedented growth of unstructured data is a big challenge faced by most data scientists. This paper discusses about the types and sources of unstructured data and effective ways of processing and analysing this data. <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">4</dd></dl><dl class="metadata"><dt class="title">Published</dt> <dd class="value">2017-09-25</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/4/14","name":"Issue 14","image":null}}]}</script></body></html>