The paper constitutes an attempt to define the role of soft skills in the process of FL learning. The data derive from the questionnaire distributed among the English philology students, and reveal the subjects’ attitudes to the qualities under investigation, as well as their strengths and weaknesses within the competences given. Having identified the students’ needs, the author of the project suggests ways of developing and promoting soft skills when shaping FL competence.

Fiber reinforced polymers (FRPs) due to their specific high-strength properties become more and more popular and replace traditional structural materials like conventional steel in prestressed concrete structures. FRP reinforced structures are relatively new when compared to structures prestressed with steel tendons. For that reason only several studies and applications of pre-tensioned FRP reinforcement have been conducted until now. Moreover, researchers only considered short-term behavior of FRP reinforced concrete members. The precise information about long-term behavior of FRP reinforcement is necessary to evaluate the prestress losses, which should be taken into account in the design of prestressed RC structures. One of the most important factor influencing long term behavior of FRP reinforcement is stress relaxation. The overview of experimental tests results described in the available literature considering the prestress losses obtained in FRP prestressed concrete members is presented herein.

Conventional field-orientated Induction motor drives operate at rated flux even at low load. To improve the efficiency of the existing motor it is important to regulate the flux of the motor in the desired operating range. In this paper a loss model controller (LMC) based on the real coded genetic algorithm is proposed, it has the straightforward goal of maximizing the efficiency for each given load torque. In order to give more accuracy to the motor model and the LMC a series model of the motor which consider the iron losses as a resistance connected in series with the mutual inductance is considered. Digital computer simulation demonstrates the effectiveness of the proposed algorithm and also simulation results have confirmed that this algorithm yields the optimal efficiency.

Biometric identification systems, i.e. the systems that are able to recognize humans by analyzing their physiological or behavioral characteristics, have gained a lot of interest in recent years. They can be used to raise the security level in certain institutions or can be treated as a convenient replacement for PINs and passwords for regular users. Automatic face recognition is one of the most popular biometric technologies, widely used even by many low-end consumer devices such as netbooks. However, even the most accurate face identification algorithm would be useless if it could be cheated by presenting a photograph of a person instead of the real face. Therefore, the proper liveness measurement is extremely important. In this paper we present a method that differentiates between video sequences showing real persons and their photographs. First we calculate the optical flow of the face region using the Farnebäck algorithm. Then we convert the motion information into images and perform the initial data selection. Finally, we apply the Support Vector Machine to distinguish between real faces and photographs. The experimental results confirm that the proposed approach could be successfully applied in practice.

The paper presented the wavelet transform method for de-noising and singularity detection to soil compressive stress signal. The study results show that the reconstruction signals by the wavelet de-noising keeps the low frequency component at [0, 31.25 Hz] of the original signal and improves the high frequency property at other frequency bands. The impaction time from the start time to resonance time of the stress signals is varies with the depth of the soil. With the increase of times of compaction, the impaction time of the stress is decreasing in every layer. But the speed of reaching compacted status in each layer is different.