Invited Speakers

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Prof. Dr. Iñigo Cuiñas

- Prof. Dr. Antanas Verikas


Prof. Dr. Iñigo Cuiñas (University of Vigo / Vigo, Spain)

An Introduction to Cybersecurity at Physical Layer: Obstacles at Radio Channel to Mitigate Hackers Chance

Monday, 15th June, 10:15–11:00, Room A

Iñigo Cuiñas is a Professor at the Dept. of Signal Theory and Communications, and the Dean of the School of Telecommunication Engineering, Universidade de Vigo, Spain, where he teaches courses on Remote Sensing and the social links of Engineering.His main research interest focuses on radio wave propagation in complex environments, as vegetation media; environmental aspects of radiofrequency systems, as the development of techniques to reduce the electromagnetic pollution; as well as information security at physical level. Prof. Cuiñas has authored or co-authored more than 80 papers in JCR-ranked journals and 110 contributions to international conferences. 

Cybersecurity is a must in current Information Society research and professional development. This issue mostly focus on activities at very high level (session, presentation or application). The lowest layer within OSI model, the Physical one, is commonly "the ugly duckling" among the rest in terms of Cybersecurity interest. In parallel, more and more wireless communication systems are deployed providing a collection of services that deserve a moment to think on security. Obviously, if the hacker is not within the coverage of the radio system, it is not possible for him to access the information. Then, proposals that allow something like controlling the radio coverage range of a wireless system would act as a defense against malicious accesses. This fact opens a world of solutions that involves hard walls, vegetation fences and frequency selective surface, from those very primitive to the more sophisticated solutions. Results from our experimental research are presented along this talk, combined with the effect on the cybersecurity application.


Prof. Dr. Antanas Verikas (Kaunas University of Technology / Kaunas, Lithuania)

Data Mining-based Prediction of Athletic Performance

Monday, 15th June, 11:45–12:30, Room A

Antanas Verikas was awarded a PhD degree in pattern recognition from Kaunas University of Technology, where he currently holds a professor position. For more than 25 years he has conducted research at Halmstad University Sweden and led the Department of Intelligent Systems. His research interests include machine learning, deep learning, computer vision, pattern recognition, classification, information fusion, fuzzy logic, and visual media technology. He published more than 200 peer reviewed articles in international journals and conference proceedings and served as conference chair, invited speaker and program committee member in numerous international conferences. 

Bicycling and golf are two kinds of sports considered in this work. Golf shot effectiveness, expressed in terms of club head speed or ball carry distance, and a blood lactate concentration level and an oxygen uptake rate are parameters used to assess performance of golfers and bicyclists in this work. Predicting the performance parameters using information extracted from multi-channel surface electromyography (sEMG) signals recorded from relevant body muscles is the main aim of this work.

Surface EMG data enable wearable computing in the field of ambient intelligence and has potential to enhance exercising of a long carry distance shot. We argue that muscle coordination patterns change during fatiguing cycling exercises and these changes provide important information for tracking two important physiological parameters, blood lactate concentration level and oxygen uptake rate. The investigations have also shown that the canonical correlation analysis is a promising tool for studying relations between sEMG and biomechanical data. Better understanding of these relations may lead to guidelines concerning muscle engagement and coordination of thorax, pelvis and arms during a golf swing and will help golf coaches in providing substantiated advices.