Journals
2020
Spyropoulou N., Glaroudis D., Iossifides A., Zaharakis I. D., “Fostering Secondary Students’ STEM Career Awareness Through IoT Hands-on Educational Activities: Experiences and Lessons Learned”, 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 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
2019
«A semi-supervised self-trained two-level algorithm for forecasting students’ graduation timΕ».I.E. Livieris, V. Tampakas, N. Karacapilidis and P.Pintelas. Intelligent Decision Technologies, 13 (2019) 367–378
«A weighted voting ensemble SSL algorithm for the detection of lung abnormalities from X-rays» E. Livieris, A. Kanavos, V. Tampakas, P. Pintelas, Algorithms 2019, 12(3), 64; https://doi.org/10.3390/a12030064.
Panagiotou P., Sklavos N., Darra E., Zaharakis I. D., “Cryptographic System for Data Applications, in the Context of Internet of Things”, Microprocessors and Microsystems 72 (2019). DOI: https://doi.org/10.1016/j.micpro.2019.102921
«Improving the evaluation process of students’ performance utilizing a decision support software», I.E. Livieris T. Kotsilieris V. Tampakas P. Pintelas, Neural Comput & Applic 31, 1683–1694 (2019). https://doi.org/10.1007/s00521-018-3756-y
2018
«An Auto-Adjustable Semi-Supervised Self-Training Algorithm», Ioannis E. Livieris, Andreas Kanavos, Vassilis Tampakas and Panagiotis Pintelas, Algorithms 2018, 11(9), 139; https://doi.org/10.3390/a11090139.
«On Ensemble SSL Algorithms for Credit Scoring Problem», Ioannis E. Livieris, Niki Kiriakidou, Andreas Kanavos, Vassilis Tampakas and Panagiotis Pintelas, Informatics 2018, 5(4), 40; https://doi.org/10.3390/informatics5040040.
«CST-VOTING – A SEMI-SUPERVISED ENSEMBLE METHOD FOR CLASSIFICATION PROBLEMS». Kostopoulos, I.E. Livieris, S. Kotsiantis and V. Tampakas, Journal of Intelligent and Fuzzy Systems 2018, pp 99-109.
«PREDICTING SECONDARY SCHOOL STUDENTS’ PERFORMANCE UTILIZING A SEMI-SUPERVISED APPROACH». 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.
«LARGE SCALE PRODUCT RECOMMENDATION OF SUPERMARKET WARE BASED ON CUSTOMER BEHAVIOUR ANALYSIS», A. Kanavos, S. Iakovou, S. Sioutas, V. Tampakas, Journal of Big Data and Cognitive Computing, 2018, 2, 11;doi 10.3390/bdcc2020011.
«An Ensemble SSL Algorithm for Efficient Chest X-Ray Image Classification», Ioannis E. Livieris 1, Andreas Kanavos 1, Vassilis Tampakas and Panagiotis Pintelas, in J. Imaging 2018, 4(7), 95
2017
«A DESCENT HYBRID CONJUGATE GRADIENT METHOD BASED ON THE MEMORYLESS BFGS UPDATE», Ioannis Livieris, Vassilis Tampakas, Panagiotis Pintelas, accepted to Numerical algorithms (Springer), ISSN: 1017-1398 (Print) 1572-9265, 2017.
Tsakanikas, V., & Dagiuklas, T. (2017). Video surveillance systems-current status and future trends. Computers & Electrical Engineering. (doi.org/10.1016/j.compeleceng.2017.11.011)
2012
Zaharakis I. D., Komninos, A., “Ubiquitous computing – a multidisciplinary endeavor”, IEEE Latin America Transactions, 10(3):1850-1852, April 2012. ISSN: 1548-0992. DOI: 10.1109/TLA.2012.6222593.
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, “Novel methodology for 3D reconstruction of carotid arteries and plaque characterization, based upon magnetic resonance imaging carotid angiography data”. Magnetic Resonance Imaging, 2012 Oct;30(8):1068-82
Lambros S. Athanasiou, Petros S. Karvelis, Vasilis D. Tsakanikas, Katerina K. Naka, Lampros K. Michalis, Christos V. Bourantas and Dimitrios I. Fotiadis, “A novel semi-automated atherosclerotic plaque characterization method using grayscale intravascular ultrasound images. Comparison with Virtual Histology” IEEE Transactions on Information Technology in Biomedicine (TITB), 2012 May;16(3):391-400
2011
«COMBINING HETEROGENEOUS CLASSIFIERS: A RECENT OVERVIEW», S. Kotsiantis, V. Tampakas, JCITQ: Journal of Convergence Information Technology (ISSN: 1975-9320), Vol. 6, No. 10, pp. 164 ~ 172, 2011.
Christos Bourantas, Vasilis Tsakanikas, Lampros Michalis, Katerina Naka, Dimitrios Fotiadis, Farqad Alamgir, “Fusion of optical coherence tomography and coronary angiography – in vivo assessment of shear stress in plaque rupture” , International Journal of Cardiology 2012 Mar 8;155(2):e24-6
2010
«FINANCIAL APPLICATION OF MULTI-INSTANCE LEARNING: TWO GREEK CASE STUDIES», S. Kotsiantis, D. Kanellopoulos, V. Tampakas, Journal of Convergence Information Technology, Volume 5, Number 8, October 2010, pp. 42-53.
George Xylomenos, Konstantinos Katsaros and Vasilis Tsakanikas, Support of Multiple Content Variants in the Multimedia Broadcast / Multicast Service», International Journal of Communication Systems, International Journal of Communication Systems, 24 (6), June 2011, p. 691-708, John Wiley and Sons Ltd. Chichester, UK
2008
«INTEGRATING ACTIVITY-BASED COSTING WITH SIMULATION AND DATA MINING», H. Kostakis, C. Sarigiannidis, Β.Βoutsinas, K. Varvakis, V. Tampakas, Intenational Journal of Accounting and Information Management (εκδόσεις Emerald), Vol. 16, No. 1, 2008, pp.25-35
Zaharakis I. D., Kameas A. D., “Modeling Spiking Neural Networks”, Theoretical Computer Science, 395(1), 2008, pp. 57-76. Elsevier. DOI: 10.1016/j.tcs.2007.11.002
2007
«SELECTIVE COSTING VOTING FOR BANKRUPTCY PREDICTION» S. Kotsiantis, D. Tzelepis, E. Koumanakos, V. Tampakas, International Journal of Knowledge-Based & Intelligent Engineering Systems (KES),11(2007), pp 115-127.
2006
«FORECASTING FRAUDULENT FINANCIAL STATEMENTS USING DATA MINING» S. Kotsiantis, E. Koumanakos, D. Tzelepis, V. Tampakas, , International Journal of Computational Intelligence , 2006, Vol 3(2), pp. 104-110.
«ON IMPLEMENTING A FINANCIAL DECISION SUPPORT SYSTEM» 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.
Kotsiantis, S. B., Zaharakis I. D., Pintelas P. E., “Machine Learning: A Review of Classification and Combining Techniques”, Artificial Intelligence Review, 26(3):159-190, 2006. Springer. DOI:10.1007/s10462-007-9052-3
Zaharakis I. D., Kameas A. D., “Emergent Phenomena in AmI Spaces”. The EASST (European Association of Software Science and Technology) Newsletter, Volume 12 (March 2006 / No. 2006 – 12), pp. 82-96. EASST e.V.
2005
«TEXT CLASSIFICATION USING MACHINE LEARNING TECHNIQUES» M. Ikonomakis, S. Kotsiantis, V. Tampakas, , WSEAS Transactions on Computers, Issue 8, Volume 4, August 2005, pp. 966-974.
Triantis A. G., Kameas A. D., Zaharakis I. D., Pintelas P. E., “4Ds: An Architecture that Dynamically Synthesizes Distributed Content with Distributed Expertise into Educational Applications that Support Sustainable Sessions for Distributed Learners”. Themes in Education, Special Edition “Information and Communication Technologies in Distance Learning: Issues and Trends”, 6 (2), 2005, pp. 169-187.
2003
«Parallel Processing of Multiple Text Queries on Hypercube Interconnection Networks» B. Mamalis, P. Spirakis, B. Tampakas, International Journal of Computers and their Applications, (IJCA), Vol. 10, No 1, pp. 115-132, March 2003.
1999
«HIGH PERFORMANCE PARALLEL TEXT RETRIEVAL OVER LARGE SCALE DOCUMENT COLLECTIONS : THE PFIRE SYSTEM», B. Mamalis, P. Spirakis, B. Tampakas, International Journal of Computers and their Applications, Vol. 6, No. 3, Sept. 1999.
«Optimal High Performance Parallel Text Retrieval via Fat Trees», B. Mamalis, P. Spirakis, B. Tampakas, in journal of The Theory of Computing Systems (TOCS), 32, 591-623 (1999).
1998
Zaharakis I. D., Kameas A. D. and Nikiforidis G. C., “A Multi-agent Architecture for Teaching Dermatology”. Medical Informatics, 23 (4), 1998, pp. 289-307. doi: 10.3109/14639239809025366
1997
Zaharakis I. D., Kameas A. D. and Pintelas P. E., “A Hybrid Expert System as an Embedded Module in Tutoring Systems”. Digital Creativity, 8 (2), 1997, pp. 47-58.
DOI: 10.1080/09579139708567075
Zaharakis I. D., Kameas A. D. and Pintelas P. E., “MeT: The Expert Methodology Tutor of GENITOR”. Microprocessing and Microprogramming, 40 (10-12), 1994, pp. 855-860. DOI: 10.1016/0165-6074(94)90055-8
1994
«Tentative and Definite Distributed Computations: an Optimistic approach to Network Synchronization», J. Garofalakis, S. Rajsbaum, P. Spirakis and B. Tampakas, Theoretical Computer Science, Special Issue on Reliable Distributed Computing, vol. 128, 1994, pp. 63-74.
1989
«Efficient Distributed Algorithms by using the Archimedean Time Assumption», P. Spirakis and B. Tampakas, Theoretical Informatics and Applications (RAIRO), vol. 23, 1989, pp. 113-128.