NERYO-CHAGI KINEMATIC CHARACTERISTICS EVALUATION IN IMPACT SINGLE COMBATS BY EXAMPLE OF WTF TAEKWONDO VIA FEEDBACK TECHNOLOGIES

This article is dedicated to topical issues related to feedback information technologies. As of now, there is not enough research on the topic of studying the kinematic characteristics of athletes in full-contact martial arts using tracking feedback systems. Research methodology: To test the hypothesis concerning the practicability of modern information technologies application, there was held an experiment with WTF taekwondo martial arts athletes. The researchers examined 4 athletes: 2 highly qualified athletes (elite) and 2 sub-elite athletes. The GPS/LPS RealTrack System by Wimu Pro Spain, was chosen to record the motion parameters. Neryo-Chagi was randomly chosen to assess the kinematic characteristics (exploratory study). Neryo-Chagi was considered as an integral motor action, which consists of two types of movement: 1) swing and 2) shock movement (strike). Research results: At the moment of Neryo-Chagi strike, there is a linear increase in the angular velocity (degrees/sec) from low to maximum. When performing a swing and a shock movement (strike), the angular velocity (deg / s) is different. The maximum angular speed during the swing is observed when strikes the way they are in a fight are compared to the maximum, medium and slow intensity. Swing time (s) with elite athletes is higher compared to sub-elite ones, while the time to perform a strike movement does not differ. Elite athletes have higher maximum angular velocity during the swing and strike movement. Evaluation of the main motor actions of athletes, classified by kinematic characteristics, allows a new assessment of their effectiveness.  Article visualizations

Reconstruction of Radio Signals from Air-Showers with Autoencoder

The Tunka Radio Extension (Tunka-Rex) is a digital antennaarray (63 antennas distributed over≈1 km2) co-located with the TAIGAobservatory in Eastern Siberia. Tunka-Rex measures radio emission ofair-showers induced by ultra-high energy cosmic rays in the frequencyband of 30-80 MHz. Air-shower signal is a short (tens of nanoseconds)broadband pulse. Using time positions and amplitudes of these pulses,we reconstruct parameters of air showers and primary cosmic rays. Theamplitudes of low-energy event (E<1017eV) cannot be used for suc-cesful reconstruction due to the domination of background. To lower theenergy threshold of the detection and increase the efficiency, we use au-toencoder neural network which removes noise from the measured data.This work describes our approach to denoising raw data and furtherreconstruction of air-shower parameters. We also present results of thelow-energy events reconstruction with autoencoder