{"id":1544,"date":"2021-03-05T23:24:23","date_gmt":"2021-03-05T21:24:23","guid":{"rendered":"http:\/\/DISyD-Lab.ece.uop.gr\/?page_id=1544"},"modified":"2021-03-17T06:53:13","modified_gmt":"2021-03-17T04:53:13","slug":"journals","status":"publish","type":"page","link":"http:\/\/DISyD-Lab.ece.uop.gr\/?page_id=1544","title":{"rendered":"Journals"},"content":{"rendered":"\n<div class=\"wp-block-cover has-background-dim-70 has-background-dim has-background-gradient\" style=\"min-height:50px\"><span aria-hidden=\"true\" class=\"wp-block-cover__gradient-background\" style=\"background:linear-gradient(180deg,rgb(255,215,172) 0%,rgba(164,223,255,0.87) 100%)\"><\/span><img loading=\"lazy\" width=\"626\" height=\"442\" class=\"wp-block-cover__image-background wp-image-2562\" alt=\"\" src=\"http:\/\/DISyD-Lab.ece.uop.gr\/wp-content\/uploads\/2021\/03\/high-tech-technology-geometric_29971-408.jpg\" style=\"object-position:55% 33%\" data-object-fit=\"cover\" data-object-position=\"55% 33%\" srcset=\"http:\/\/DISyD-Lab.ece.uop.gr\/wp-content\/uploads\/2021\/03\/high-tech-technology-geometric_29971-408.jpg 626w, http:\/\/DISyD-Lab.ece.uop.gr\/wp-content\/uploads\/2021\/03\/high-tech-technology-geometric_29971-408-300x212.jpg 300w\" sizes=\"(max-width: 626px) 100vw, 626px\" \/><div class=\"wp-block-cover__inner-container\">\n<p class=\"has-text-align-left has-black-color has-text-color\" style=\"font-size:22px\">Journals<\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<hr class=\"wp-block-separator has-text-color has-background has-cyan-bluish-gray-background-color has-cyan-bluish-gray-color is-style-wide\"\/>\n\n\n\n<p style=\"text-align: justify;\">2020 <br \/>Spyropoulou N., Glaroudis D., Iossifides A., Zaharakis I. D., \u201cFostering Secondary Students\u2019 STEM Career Awareness Through IoT Hands-on Educational Activities: Experiences and Lessons Learned\u201d, IEEE Communications Magazine 58(2):86-92, 2020, IEEE. <br \/>DOI: <a href=\"https:\/\/doi.org\/10.1109\/MCOM.001.1900288\" target=\"_blank\" rel=\"noopener\">https:\/\/doi.org\/10.1109\/MCOM.001.1900288<\/a><\/p>\n<p style=\"text-align: justify;\">Tsakanikas VD, Gatsios D, Dimopoulos D, Pardalis A, Pavlou M, Liston MB and Fotiadis DI (2020) Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System. Front. Digit. Health 2:545885. doi: 10.3389\/fdgth.2020.545885<\/p>\n<p style=\"text-align: justify;\">2019<br \/>\u00abA semi-supervised self-trained two-level algorithm for forecasting students\u2019 graduation tim\u0395\u00bb.I.E. Livieris, V. Tampakas, N. Karacapilidis and P.Pintelas. Intelligent Decision Technologies, 13 (2019) 367\u2013378<\/p>\n<p style=\"text-align: justify;\">\u00abA weighted voting ensemble SSL algorithm for the detection of lung abnormalities from X-rays\u00bb E. Livieris, A. Kanavos, V. Tampakas, P. Pintelas, Algorithms 2019, 12(3), 64; <a href=\"https:\/\/doi.org\/10.3390\/a12030064\" target=\"_blank\" rel=\"noopener\">https:\/\/doi.org\/10.3390\/a12030064<\/a>.<\/p>\n<p style=\"text-align: justify;\">Panagiotou P., Sklavos N., Darra E., Zaharakis I. D., \u201cCryptographic System for Data Applications, in the Context of Internet of Things\u201d, Microprocessors and Microsystems 72 (2019). DOI:<a href=\"https:\/\/doi.org\/10.1016\/j.micpro.2019.102921\" target=\"_blank\" rel=\"noopener\"> https:\/\/doi.org\/10.1016\/j.micpro.2019.102921<\/a><\/p>\n<p style=\"text-align: justify;\">\u00abImproving the evaluation process of students&#8217; performance utilizing a decision support software\u00bb, I.E. Livieris T. Kotsilieris V. Tampakas P. Pintelas, Neural Comput &amp; Applic 31, 1683\u20131694 (2019). <a href=\"https:\/\/doi.org\/10.1007\/s00521-018-3756-y\" target=\"_blank\" rel=\"noopener\">https:\/\/doi.org\/10.1007\/s00521-018-3756-y<\/a><\/p>\n<p style=\"text-align: justify;\"><br \/>2018<br \/>\u00abAn Auto-Adjustable Semi-Supervised Self-Training Algorithm\u00bb, Ioannis E. Livieris, Andreas Kanavos, Vassilis Tampakas and Panagiotis Pintelas, Algorithms 2018, 11(9), 139; <a href=\"https:\/\/doi.org\/10.3390\/a11090139\" target=\"_blank\" rel=\"noopener\">https:\/\/doi.org\/10.3390\/a11090139<\/a>.<\/p>\n<p style=\"text-align: justify;\">\u00abOn Ensemble SSL Algorithms for Credit Scoring Problem\u00bb, Ioannis E. Livieris, Niki Kiriakidou, Andreas Kanavos, Vassilis Tampakas and Panagiotis Pintelas, Informatics 2018, 5(4), 40;<a href=\"https:\/\/doi.org\/10.3390\/informatics5040040\" target=\"_blank\" rel=\"noopener\"> https:\/\/doi.org\/10.3390\/informatics5040040<\/a>.<\/p>\n<p style=\"text-align: justify;\">\u00abCST-VOTING &#8211; A SEMI-SUPERVISED ENSEMBLE METHOD FOR CLASSIFICATION PROBLEMS\u00bb. Kostopoulos, I.E. Livieris, S. Kotsiantis and V. Tampakas, Journal of Intelligent and Fuzzy Systems 2018, pp 99-109.<\/p>\n<p style=\"text-align: justify;\">\u00abPREDICTING SECONDARY SCHOOL STUDENTS\u2019 PERFORMANCE UTILIZING A SEMI-SUPERVISED APPROACH\u00bb. I.E. Livieris, K. Drakopoulou, V. Tampakas, T.A. Mikropoulos and P. Pintelas, Journal of Educational Computing Research, Volume: 57 issue: 2, page(s): 448-470, 2018.<\/p>\n<p style=\"text-align: justify;\">\u00abLARGE SCALE PRODUCT RECOMMENDATION OF SUPERMARKET WARE BASED ON CUSTOMER BEHAVIOUR ANALYSIS\u00bb, A. Kanavos, S. Iakovou, S. Sioutas, V. Tampakas, Journal of Big Data and Cognitive Computing, 2018, 2, 11;doi 10.3390\/bdcc2020011.<\/p>\n<p style=\"text-align: justify;\">\u00abAn Ensemble SSL Algorithm for Efficient Chest X-Ray Image Classification\u00bb, Ioannis E. Livieris 1, Andreas Kanavos 1, Vassilis Tampakas and Panagiotis Pintelas, in J. Imaging 2018, 4(7), 95<\/p>\n<p style=\"text-align: justify;\">2017 <br \/>\u00abA DESCENT HYBRID CONJUGATE GRADIENT METHOD BASED ON THE MEMORYLESS BFGS UPDATE\u00bb, Ioannis Livieris, Vassilis Tampakas, Panagiotis Pintelas, accepted to Numerical algorithms (Springer), ISSN: 1017-1398 (Print) 1572-9265, 2017.<\/p>\n<p style=\"text-align: justify;\">Tsakanikas, V., &amp; Dagiuklas, T. (2017). Video surveillance systems-current status and future trends. Computers &amp; Electrical Engineering. (doi.org\/10.1016\/j.compeleceng.2017.11.011)<\/p>\n<p style=\"text-align: justify;\">2012 <br \/>Zaharakis I. D., Komninos, A., \u201cUbiquitous computing \u2013 a multidisciplinary endeavor\u201d, IEEE Latin America Transactions, 10(3):1850-1852, April 2012. ISSN: 1548-0992. DOI: 10.1109\/TLA.2012.6222593.<\/p>\n<p style=\"text-align: justify;\">Antonis I. Sakellarios, Kostas Stefanou, Panagiotis Siogkas, Vasilis D. Tsakanikas, Christos V. Bourantas, Lambros Athanasiou, Themis P. Exarchos, Evaggelos Fotiou, Katerina K. Naka, Michail I. Papafaklis, Andrew J. Patterson, Victoria EL. Young, Jonathan H. Gillard, Lampros K. Michalis and Dimitrios I. Fotiadis, \u201cNovel methodology for 3D reconstruction of carotid arteries and plaque characterization, based upon magnetic resonance imaging carotid angiography data\u201d. Magnetic Resonance Imaging, 2012 Oct;30(8):1068-82<\/p>\n<p style=\"text-align: justify;\">Lambros S. Athanasiou, Petros S. Karvelis, Vasilis D. Tsakanikas, Katerina K. Naka, Lampros K. Michalis, Christos V. Bourantas and Dimitrios I. Fotiadis, \u201cA novel semi-automated atherosclerotic plaque characterization method using grayscale intravascular ultrasound images. Comparison with Virtual Histology\u201d IEEE Transactions on Information Technology in Biomedicine (TITB), 2012 May;16(3):391-400<\/p>\n<p style=\"text-align: justify;\">2011 <br \/>\u00abCOMBINING HETEROGENEOUS CLASSIFIERS: A RECENT OVERVIEW\u00bb, S. Kotsiantis, V. Tampakas, JCITQ: Journal of Convergence Information Technology (ISSN: 1975-9320), Vol. 6, No. 10, pp. 164 ~ 172, 2011.<\/p>\n<p style=\"text-align: justify;\">Christos Bourantas, Vasilis Tsakanikas, Lampros Michalis, Katerina Naka, Dimitrios Fotiadis, Farqad Alamgir, \u201cFusion of optical coherence tomography and coronary angiography &#8211; in vivo assessment of shear stress in plaque rupture\u201d , International Journal of Cardiology 2012 Mar 8;155(2):e24-6<\/p>\n<p style=\"text-align: justify;\">2010 <br \/>\u00abFINANCIAL APPLICATION OF MULTI-INSTANCE LEARNING: TWO GREEK CASE STUDIES\u00bb, S. Kotsiantis, D. Kanellopoulos, V. Tampakas, Journal of Convergence Information Technology, Volume 5, Number 8, October 2010, pp. 42-53. <br \/>George Xylomenos, Konstantinos Katsaros and Vasilis Tsakanikas, Support of Multiple Content Variants in the Multimedia Broadcast \/ Multicast Service\u00bb, International Journal of Communication Systems, International Journal of Communication Systems, 24 (6), June 2011, p. 691-708, John Wiley and Sons Ltd. Chichester, UK<\/p>\n<p style=\"text-align: justify;\">2008<br \/>\u00abINTEGRATING ACTIVITY-BASED COSTING WITH SIMULATION AND DATA MINING\u00bb, H. Kostakis, C. Sarigiannidis, \u0392.\u0392outsinas, K. Varvakis, V. Tampakas, Intenational Journal of Accounting and Information Management (\u03b5\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 Emerald), Vol. 16, No. 1, 2008, pp.25-35<\/p>\n<p style=\"text-align: justify;\">Zaharakis I. D., Kameas A. D., \u201cModeling Spiking Neural Networks\u201d, Theoretical Computer Science, 395(1), 2008, pp. 57-76. Elsevier. DOI: 10.1016\/j.tcs.2007.11.002<\/p>\n<p style=\"text-align: justify;\"><br \/>2007<br \/>\u00abSELECTIVE COSTING VOTING FOR BANKRUPTCY PREDICTION\u00bb S. Kotsiantis, D. Tzelepis, E. Koumanakos, V. Tampakas, International Journal of Knowledge-Based &amp; Intelligent Engineering Systems (KES),11(2007), pp 115-127.<\/p>\n<p style=\"text-align: justify;\">2006<br \/>\u00abFORECASTING FRAUDULENT FINANCIAL STATEMENTS USING DATA MINING\u00bb S. Kotsiantis, E. Koumanakos, D. Tzelepis, V. Tampakas, , International Journal of Computational Intelligence , 2006, Vol 3(2), pp. 104-110.<\/p>\n<p style=\"text-align: justify;\">\u00abON IMPLEMENTING A FINANCIAL DECISION SUPPORT SYSTEM\u00bb S. Kotsiantis, D. Kanellopoulos, V. Tampakas in International Journal in Computer Science and Network Security (IJCSNS), Vol. 6, no.1A, January 2006, pp 103-112.<\/p>\n<p style=\"text-align: justify;\">Kotsiantis, S. B., Zaharakis I. D., Pintelas P. E., \u201cMachine Learning: A Review of Classification and Combining Techniques\u201d, Artificial Intelligence Review, 26(3):159-190, 2006. Springer. DOI:10.1007\/s10462-007-9052-3<\/p>\n<p style=\"text-align: justify;\">Zaharakis I. D., Kameas A. D., \u201cEmergent Phenomena in AmI Spaces\u201d. The EASST (European Association of Software Science and Technology) Newsletter, Volume 12 (March 2006 \/ No. 2006 &#8211; 12), pp. 82-96. EASST e.V.<\/p>\n<p style=\"text-align: justify;\"><br \/>2005<br \/>\u00abTEXT CLASSIFICATION USING MACHINE LEARNING TECHNIQUES\u00bb M. Ikonomakis, S. Kotsiantis, V. Tampakas, , WSEAS Transactions on Computers, Issue 8, Volume 4, August 2005, pp. 966-974.<\/p>\n<p style=\"text-align: justify;\">Triantis A. G., Kameas A. D., Zaharakis I. D., Pintelas P. E., \u201c4Ds: An Architecture that Dynamically Synthesizes Distributed Content with Distributed Expertise into Educational Applications that Support Sustainable Sessions for Distributed Learners\u201d. Themes in Education, Special Edition &#8220;Information and Communication Technologies in Distance Learning: Issues and Trends&#8221;, 6 (2), 2005, pp. 169-187.<\/p>\n<p style=\"text-align: justify;\"><br \/>2003<br \/>\u00abParallel Processing of Multiple Text Queries on Hypercube Interconnection Networks\u00bb B. Mamalis, P. Spirakis, B. Tampakas, International Journal of Computers and their Applications, (IJCA), Vol. 10, No 1, pp. 115-132, March 2003.<\/p>\n<p style=\"text-align: justify;\">1999<br \/>\u00abHIGH PERFORMANCE PARALLEL TEXT RETRIEVAL OVER LARGE SCALE DOCUMENT COLLECTIONS : THE PFIRE SYSTEM\u00bb, B. Mamalis, P. Spirakis, B. Tampakas, International Journal of Computers and their Applications, Vol. 6, No. 3, Sept. 1999.<\/p>\n<p style=\"text-align: justify;\">\u00abOptimal High Performance Parallel Text Retrieval via Fat Trees\u00bb, B. Mamalis, P. Spirakis, B. Tampakas, in journal of The Theory of Computing Systems (TOCS), 32, 591-623 (1999).<\/p>\n<p style=\"text-align: justify;\">1998<br \/>Zaharakis I. D., Kameas A. D. and Nikiforidis G. C., \u201cA Multi-agent Architecture for Teaching Dermatology\u201d. Medical Informatics, 23 (4), 1998, pp. 289-307. doi: 10.3109\/14639239809025366<\/p>\n<p style=\"text-align: justify;\">1997<br \/>Zaharakis I. D., Kameas A. D. and Pintelas P. E., \u201cA Hybrid Expert System as an Embedded Module in Tutoring Systems\u201d. Digital Creativity, 8 (2), 1997, pp. 47-58. <br \/>DOI: 10.1080\/09579139708567075<\/p>\n<p style=\"text-align: justify;\">Zaharakis I. D., Kameas A. D. and Pintelas P. E., \u201cMeT: The Expert Methodology Tutor of GENITOR\u201d. Microprocessing and Microprogramming, 40 (10-12), 1994, pp. 855-860. DOI: 10.1016\/0165-6074(94)90055-8<\/p>\n<p style=\"text-align: justify;\"><br \/>1994<br \/>\u00abTentative and Definite Distributed Computations: an Optimistic approach to Network Synchronization\u00bb, J. Garofalakis, S. Rajsbaum, P. Spirakis and B. Tampakas, Theoretical Computer Science, Special Issue on Reliable Distributed Computing, vol. 128, 1994, pp. 63-74.<\/p>\n<p style=\"text-align: justify;\">1989<br \/>\u00abEfficient Distributed Algorithms by using the Archimedean Time Assumption\u00bb, P. Spirakis and B. Tampakas, Theoretical Informatics and Applications (RAIRO), vol. 23, 1989, pp. 113-128.<\/p>\n<p style=\"text-align: justify;\">\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>2020 Spyropoulou N., Glaroudis D., Iossifides A., Zaharakis I. D., \u201cFostering Secondary Students\u2019 STEM Career Awareness Through IoT Hands-on Educational Activities: Experiences and Lessons Learned\u201d, IEEE Communications Magazine 58(2):86-92, 2020, IEEE. DOI: https:\/\/doi.org\/10.1109\/MCOM.001.1900288 Tsakanikas VD, Gatsios D, Dimopoulos D, Pardalis A, Pavlou M, Liston MB and Fotiadis DI (2020) Evaluating the Performance of Balance Physiotherapy &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"http:\/\/DISyD-Lab.ece.uop.gr\/?page_id=1544\"> <span class=\"screen-reader-text\">Journals<\/span> Read More &raquo;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"pefanis27","author_link":"http:\/\/DISyD-Lab.ece.uop.gr\/?author=1"},"uagb_comment_info":0,"uagb_excerpt":"2020 Spyropoulou N., Glaroudis D., Iossifides A., Zaharakis I. D., \u201cFostering Secondary Students\u2019 STEM Career Awareness Through IoT Hands-on Educational Activities: Experiences and Lessons Learned\u201d, IEEE Communications Magazine 58(2):86-92, 2020, IEEE. DOI: https:\/\/doi.org\/10.1109\/MCOM.001.1900288 Tsakanikas VD, Gatsios D, Dimopoulos D, Pardalis A, Pavlou M, Liston MB and Fotiadis DI (2020) Evaluating the Performance of Balance Physiotherapy&hellip;","_links":{"self":[{"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/pages\/1544"}],"collection":[{"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1544"}],"version-history":[{"count":0,"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/pages\/1544\/revisions"}],"wp:attachment":[{"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1544"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}