Prof. Chrysostomos Stylios
Industrial Systems Institute, Pátrai, Greece
+1
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Academic Career Length
29Years (1998-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Journal Article
Stylianos MystakidisJBJeries Besharat
Jeries BesharatGPGeorge Papantzikos
George Papantzikos
Athanasios ChristopoulosChrysostomos StyliosDTDimitrios Tselentis
Dimitrios Tselentis +1
Immersive virtual reality (VR) is a technology that can be effective for procedural skills training through game-based simulations such as serious games. The current study describes the instructional design, development, and evaluation of the FSCHOOL fire preparedness serious game in a cave automatic virtual environment (CAVE-VR) for elementary school teachers. The main game mechanics include a storytelling scenario, enhanced realism, freedom of movement, levels, and points corresponding to the learning mechanics of instruction, action, simulation, discovery, repetition, and imitation. The game was developed in Unity 3D with the help of the Fire Dynamics Simulator and a script to emulate and visualize fire propagation. The game featured three levels to respond to school fire safety regulations and was evaluated by elementary school teachers (N = 33) in Greece. A comparative quantitative study was conducted with experimental and control groups. The results indicate that the VR serious game is appropriate for training, providing challenge, enjoyment, and mastery.
6 March 2020 in Ships and Offshore Structures
Journal Article
PKPetros Karvelis
Petros KarvelisGGGeorge Georgoulas
George Georgoulas
Vassilios KappatosChrysostomos StyliosCorrosion, fatigue and corrosion-fatigue cracking are the most pervasive types of structural problems experienced by ship structures. These damage modes, can potentially lead to unanticipated out of service time or catastrophic failure. Acoustic Emission is gaining ground as a complementary Structural Health Monitoring (SHM) technique, since it can offer real-time damage detection. Deep learning, on the other hand, has shown great success over the last years for a large number of applications. In this paper, the SHM on ship hulls is treated as a classification problem. Firstly, the AE signals are transformed, using the Discrete Cosine Transform, followed by a dimensionality reduction stage. Afterwards, a Deep Neural Network is employed by the classification module. The proposed approach was validated and the results indicate that our proposed method can be very effective and efficient, selecting the optimum AE sensor positions and providing almost perfect localisation results.
Journal Article
GDGrzegorz Dec
Grzegorz Dec
Dorota StadnickaŁPŁukasz Paśko
Łukasz Paśko
Maksymilian MądzielRFRoberto Figliè
Roberto FiglièXBXavier Solé Beteta
Xavier Solé Beteta +4
Universities play an essential role in preparing human resources for the industry of the future. By providing the proper knowledge, they can ensure that graduates will be able to adapt to the ever-changing industrial sector. However, to achieve this, the courses provided by academia must cover the current and future industrial needs by considering the trends in scientific research and emerging technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and Edge Computing (EC). This work presents the survey results conducted among academics to assess the current state of university courses, regarding the level of knowledge and skills provided to students about the Internet of Things, Artificial Intelligence, and Edge Computing. The novelty of the work is that (a) the research was carried out in several European countries, (b) the current curricula of universities from different countries were analyzed, and (c) the results present the teachers’ perspective. To conduct the research, the analysis of the relevant literature took place initially to explore the issues of the presented subject, which will increasingly concern the industry in the near future. Based on the literature review results and analysis of the universities’ curricula involved in this study, a questionnaire was prepared and shared with academics. The outcomes of the analysis reveal the areas that require more attention from scholars and possibly modernization of curricula.
7 September 2023 in Granular Computing
Journal Article
Fuzzy Cognitive Maps (FCMs) are a graph-based methodology successfully applied for knowledge representation of complex systems modelled through an interactive structure of nodes connected with causal relationships. Due to their flexibility and inherent interpretability, FCMs have been used in various modelling and prediction tasks to support human decisions. However, a notable limitation of FCMs is their susceptibility to inadvertently capturing spurious correlations from data, undermining their prediction accuracy and interpretability. In addressing this challenge, our primary contribution is the introduction of a novel framework for constructing FCMs using the Liang-Kleeman Information Flow (L-K IF) analysis, a quantitative causality analysis rigorously derived from first principles. The novelty of the proposed approach lies in the identification of actual causal relationships from the data using an automatic causal search algorithm. These relationships are subsequently imposed as constraints in the FCM learning procedure to rule out spurious correlations and improve the aggregate predictive and explanatory power of the model. Numerical simulations validate the superiority of our method against state-of-the-art FCM-based models, thereby bolstering the reliability, accuracy, and interpretability of FCMs.
3 August 2015 in IEEE Transactions on Industrial Informatics
Journal Article
PKPetros Karvelis
Petros KarvelisGGGeorge Georgoulas
George Georgoulas
ITIoannis P. Tsoumas
Ioannis P. Tsoumas
Jose Alfonso Antonino DaviuVCVicente Climente-Alarcon
Vicente Climente-AlarconChrysostomos StyliosOne of the most common deficiencies of currently existing induction motor fault diagnosis techniques is their lack of automatization. Many of them rely on the qualitative interpretation of the results, a fact that requires significant user expertise, and that makes their implementation in portable condition monitoring devices difficult. In this paper, we present an automated method for the detection of the number of broken bars of an induction motor. The method is based on the transient analysis of the start-up current using wavelet approximation signal that isolates a characteristic component that emerges once a rotor bar is broken. After the isolation of this component, a number of stages are applied that transform the continuous-valued signal into a discrete one. Subsequently, an intelligent icon-like approach is applied for condensing the relative information into a representation that can be easily manipulated by a nearest neighbor classifier. The approach is tested using simulation as well as experimental data, achieving high-classification accuracy.
Journal Article
VLVASILIKI LIAGKOU
VASILIKI LIAGKOUChrysostomos Stylios
Lamprini PappaAPAlexander Petunin
Alexander PetuninIndustry 4.0 has risen as an integrated digital manufacturing environment, and it has created a novel research perspective that has thrust research to interdisciplinarity and exploitation of ICT advances. This work presents and discusses the main aspects of Industry 4.0 and how intelligence can be embedded in manufacturing to create the smart factory. It briefly describes the main components of Industry 4.0, and it focuses on the security challenges that the fully interconnected ecosystem of Industry 4.0 has to meet and the threats for each component. Preserving security has a crucial role in Industry 4.0, and it is vital for its existence, so the main research directions on how to ensure the confidentiality and integrity of the information shared among the Industry 4.0 components are presented. Another view is in light of the security issues that come as a result of enabling new technologies.
About Me
Prof. Chrysostomos Stylios is Director of the Laboratory of Knowledge and Intelligent Computing, Department of Informatics and Telecommunication, University of Ioannina, Greece, a collaborating Academic staff at Industrial Systems Institute (Athena RC), and an affiliate project manager at Computer Technology Institute and Press “Diophantus”. Based on his pioneering research on fuzzy cognitive maps (FCMs), FCMs are applied in discipline research areas. He has published over 200 journals, conference papers, and book chapters. His research work has been acknowledged by the scientific community, receiving more than 5500 citations and he has h-index 28 (based on Scopus) and h-index 36 (based on Scholar google). His main scientific interests include fuzzy cognitive maps, artificial intelligence, big data, data mining, soft computing, computational intelligence techniques, biosignal processing and analysis, modeling and decision support systems, support vector machines, knowledge-based systems, simulation and modeling complex systems, intelligent systems, hierarchical systems and supervisory control, intelligent manufacturing systems, open innovation, technology transfer, educational methodologies and tools, and virtual and augmentative reality. Prof. Stylios has been a scientific coordinator in more than 30 R&D projects funded by EU and national funds with more than EUR 5 million budget. Prof. Stylios is a senior member of IEEE and a member of the TC 8.2 and TC 5.4 of IFAC.