https://www.ihu.gr/ucips/post-1198/the-international-hellenic-university-responds-rapidly-to-the-fight-against-covid-19-by-printing-3d-protective-face-shields

Springer book ‘Chaos and Complex Systems’

Proceedings of the “5th International Interdisciplinary Chaos Symposium on (CCS2019)”

coedited by Dr Stavros Stavrinides, Faculty Member of the IHU School of Science and Technology

 

The International Hellenic University proudly announces the release by SPRINGER, of the book coedited by Dr Stavros G. Stavrinides (School of Science and Technology), presenting the proceedings of the5th International Interdisciplinary Chaos Symposium on Chaos and Complex Systems (CCS2019)” (https://www.springer.com/gp/book/9783030354404).

The conference was chaired by Dr. Stavrinides (International Hellenic University) and co-organized with Prof. M. Ozer (Istanbul Kultur University).

The scope of the latest CCS Symposium was enriched with a variety of contemporary interdisciplinary topics, including but not limited to: fundamental theory of nonlinear dynamics, networks, circuits, systems, biology, evolutionand ecology, fractals and pattern formation, nonlinear time series analysis, neural networks, sociophysics and econophysics, complexity management and global systems.

In CCS2019 (www.ccs2019.org) participants (scientists, engineers, economists and social scientists) from EU, USA, Canada as well as Asia, came together in a vivid forum, presentingtheir work and discussing the latest insights and findings obtained in the areas of complexity, nonlinear dynamics andchaos theory, as well as their interdisciplinary applications.

 

 

A new epidemiological model by the International Hellenic University and the University of West Attica

The International Hellenic University announces the results of the research work on a new epidemiological model, based on self-organized criticality (SOC), elaborated by its researchers Dr Stavros G. Stavrinides (School of Science and Technology) and Assoc. Prof. Michael Hanias (Physics Dept.) in collaboration with researchers from the University of West Attica.

This research has already attracted the interest of the community and the Hellenic National News Agency (AMNA) has already reported the related results: https://www.amna.gr/macedonia/article/447921/Ereuna-DIPAE-kai-PADA-gia-ton-koronoio

The proposed model is coming from the area of Critical Phenomena Statistics and Complexity. It has the ability to distinguish viruses according to their aggression, further treating epidemics as self-organized systems, a mechanism widely followed (non-exhaustively) by natural systems. The arising complexity of the system allows for its self-organization; when the system freely evolves (approach of the herd immunity), the epidemic spread takes place in a smooth way, demonstrating low durations, as long as the virus possesses characteristics of low aggressiveness. Otherwise, (in the case of aggressive viruses) the system is led to uncontrollable situations, both in terms of the patients’ percentage and duration of the epidemic.

The proposed model reinforces, proves and confirms the approach of imposing restrictive measures, in a timely and consistent way, is not only to the right direction, but it appears to be imperative.

A preprint of this work has already been published in the digital repository arxiv.org (University of Cornell): https://arxiv.org/abs/2004.00682, and has been submitted for publication to an international scientific journal.

 

https://www.ihu.edu.gr/index.php/news-events/item/https://www.ihu.edu.gr/index.php/news-events/item/1616-erasmus-programme-presentation.html

Announcement:

Τhe application/completion of application procedure for scholarships based on Law 4485/2017 (article 35) is open until 24 December 2019, 12:00 noon. More information about the required documents are available on official gazettes 114/Α/4-8-2017, 3387/Β/10-08-2018 and 2743/Β/03-07-2019.

Applications should be sent by email to This email address is being protected from spambots. You need JavaScript enabled to view it.

Ανακοίνωση:

Αιτήσεις ή/και συμπλήρωση δικαιολογητικών για λήψη υποτροφίας δυνάμει του Ν. 4485/2017 αρ. 35 γίνονται δεκτές έως την 24η Δεκεμβρίου 2019, 12:00 μεσημέρι. Απαιτούμενα δικαιολογητικά ορίζονται στα ΦΕΚ με αρ. 114/τ.Α΄/4-8-2017, 3387/τ.Β΄/10-08-2018 και 2743/τ.Β΄/03-07-2019.

Οι αιτήσεις θα αποστέλλονται ηλεκτρονικά στο This email address is being protected from spambots. You need JavaScript enabled to view it.

**IHU Students' Success Stories**
 

We are very proud that Dimosthenis Beleveslis MSc in Data Science , at the School of Science & Technology, under the supervision of Asst. Prof. Christos Tjortjis, and in collaboration with Dimitris Psaradelis and Dimitris Nikoglou of InfiLab GmbH had his paper on: “A Hybrid Method for Sentiment Analysis of Election Related Tweets”, accepted by the 4th IEEE SE Europe Design Automation, Computer Engineering, Computer Networks, and Social Media Conf. ( EEDA-CECNSM 2019).

Also, Dimitrios Tasios, MSc in Data Science , at the School of Science & Technology, under the supervision of Asst. Prof. Christos Tjortjis, and in collaboration with Asst. Prof. Andreas Gregoriades of the Cyprus University of Technology, had his paper on: “Mining Traffic Accident Data for Hazard Causality Analysis”, accepted by the 4 th IEEE SE Europe Design Automation, Computer Engineering, Computer Networks, and Social Media Conf. ( EEDA-CECNSM 2019 ).

Figure 1: Number of tweets per class



Figure 2: Accident Frequency per age group

You can find more ‘IHU Students’ Stories’ here .

Mr. D. Beleveslis

Mr. D. Tasios
**IHU Students' Success Stories**
 

We are very proud that Paraskevas Koukaras MSc in ICT Systems graduate, and Dimitris Rousidis, both PhD candidates at the School of Science & Technology, under the supervision of Asst. Prof. Christos Tjortjis, had their paper on: “Social Media Types: Introducing a Data Driven Taxonomy”, accepted by the prestigious international peer reviewed journal Computing , published by Springer.

You can find more ‘IHU Students’ Stories’ here .

Mr. P. Koukaras

Mr. D. Rousidis
**IHU Students' Success Stories**
 

We are very proud that Konstantinos Christantonis and Konstantinos Apostolou, both MSc in Data Science students, supervised by Asst. Prof. Christos Tjortjis had their respective papers on:

· “Data Mining for Smart Cities: Predicting Electricity Consumption by Classification”, and

· “Sports Analytics algorithms for performance prediction”,


accepted by the IEEE 10th International Conference on Information, Intelligence, Systems and Applications ( IISA 19).

You can find more ‘IHU Students’ Stories’ here .

Mr. K. Christantonis

Mr. K. Apostolou

Research Seminar 9/5: “A combinatorial approach to entity matching for products”

School of Science and Technology
International Hellenic University

Thursday 9 May 2019
17:00-18:00

International Hellenic University, Lecture Room B1

Seminar Title

A combinatorial approach to entity matching for products”

Dr Leonidas Akritidis

Speaker information:
Leonidas Akritidis is a post-doctoral researcher at the Data Structuring and Engineering (DaSE) Lab of the Department of Electrical & Computer Engineering, University of Thessaly, Greece. He is also an MSc studies instructor in the same Department, teaching Data Structures, Algorithms and World Wide Web technologies. He obtained his PhD degree in 2013, and his BSc from the Department of Electrical & Computer Engineering of the Aristotle University of Thessaloniki, Greece, in 2003. His research interests include Data Mining, Machine Learning, Large-scale Data Processing, Big Data Engineering, and Information Retrieval.

Presentation at a glance:
The continuous growth of the e-commerce industry has rendered the problem of product retrieval particularly important. As more enterprises move their activities on the Web, the volume and the diversity of the product-related information increase quickly. These factors make it difficult for the users to identify and compare the features of their desired products. Recent studies proved that the standard similarity metrics cannot effectively identify identical products, since similar titles often refer to different products and vice-versa. Other studies employed external data sources (search engines) to enrich the titles; these solutions are rather impractical since the process of fetching external data is inefficient. In this presentation we will review the state-of-the-art approaches to entity matching and we will introduce UPM, an unsupervised algorithm for matching products by their titles. UPM is independent of any external sources and consists of three stages: during the first stage, the algorithm analyzes the titles and extracts combinations of words out of them. These combinations are evaluated in stage 2 according to several criteria, and the most appropriate of them are selected to form the initial clusters. The third phase is a post-processing verification stage which performs a refinement of the initial clusters by correcting the erroneous matches. This stage is designed to operate in combination with all clustering approaches, especially when the data possess properties which prevent the co-existence of two data points within the same cluster. We shall also present experimental results which demonstrate the superiority of the algorithm against multiple string similarity metrics and clustering methods.

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