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Abstrakt

Although the emotions and learning based on emotional reaction are individual-specific, the main features are consistent among all people. Depending on the emotional states of the persons, various physical and physiological changes can be observed in pulse and breathing, blood flow velocity, hormonal balance, sound properties, face expression and hand movements. The diversity, size and grade of these changes are shaped by different emotional states. Acoustic analysis, which is an objective evaluation method, is used to determine the emotional state of people’s voice characteristics. In this study, the reflection of anxiety disorder in people’s voices was investigated through acoustic parameters. The study is a case-control study in cross-sectional quality. Voice recordings were obtained from healthy people and patients. With acoustic analysis, 122 acoustic parameters were obtained from these voice recordings. The relation of these parameters to anxious state was investigated statistically. According to the results obtained, 42 acoustic parameters are variable in the anxious state. In the anxious state, the subglottic pressure increases and the vocalization of the vowels decreases. The MFCC parameter, which changes in the anxious state, indicates that people can perceive this situation while listening to the speech. It has also been shown that text reading is also effective in triggering the emotions. These findings show that there is a change in the voice in the anxious state and that the acoustic parameters are influenced by the anxious state. For this reason, acoustic analysis can be used as an expert decision support system for the diagnosis of anxiety.
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Abstrakt

This study presents a possibility of detecting wear of a valve plate in multi-piston axial pump based on time-frequency analysis of measured signals. Short-time Fourier transform STFT and the generalized Wigner-Ville algorithm WVD were used for this purpose. The tests were carried out on a multi-piston axial pump with swinging plate, in which the worn valve plates were mounted. Valve plate wear was related with the formation of flow micro-channels between the pump suction hole and its pumping hole on the plate transition zone surface. The developed channels initiate flow of the operational fluid, the results of which is lack of leak-tightness between suction and pumping zones, associated with a decrease in operational pressure and drop in general efficiency.
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Abstrakt

In this paper, the author presents the possibility of using phase trajectory for detecting damage in an axial piston pump. The wear on main part of pump elements, such as the rotor and the valve plate, was investigated, and phase trajectories were determined based on vibration signal measured in three directions on the pump's body. In order to obtain a quantitative measure of the analyzed trajectory, the At_{p,i} parameter was introduced, and the relation between this parameter and the wear on the pump's parts was determined.
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Abstrakt

Quantitative ultrasound has been widely used for tissue characterization. In this paper we propose a new approach for tissue compression assessment. The proposed method employs the relation between the tissue scatterers’ local spatial distribution and the resulting frequency power spectrum of the backscattered ultrasonic signal. We show that due to spatial distribution of the scatterers, the power spectrum exhibits characteristic variations. These variations can be extracted using the empirical mode decomposition and analyzed. Validation of our approach is performed by simulations and in-vitro experiments using a tissue sample under compression. The scatterers in the compressed tissue sample approach each other and consequently, the power spectrum of the backscattered signal is modified. We present how to assess this phenomenon with our method. The proposed in this paper approach is general and may provide useful information on tissue scattering properties.
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Abstrakt

The article is devoted to the problem of voice signals recognition means introduction in the system of distance learning. The results of the conducted research determine the prospects of neural network means of phoneme recognition. It is also shown that the main difficulties of creation of the neural network model, intended for recognition of phonemes in the system of distance learning, are connected with the uncertain duration of a phoneme-like element. Due to this reason for recognition of phonemes, it is impossible to use the most effective type of neural network model on the basis of a multilayered perceptron, at which the number of input parameters is a fixed value. To mitigate this shortcoming, the procedure, allowing to transform the non-stationary digitized voice signal to the fixed quantity of mel-cepstral coefficients, which are the basis for calculation of input parameters of the neural network model, is developed. In contrast to the known ones, the possibility of linear scaling of phoneme-like elements is available in the procedure. The number of computer experiments confirmed expediency of the fact that the use of the offered coding procedure of input parameters provides the acceptable accuracy of neural network recognition of phonemes under near-natural conditions of the distance learning system. Moreover, the prospects of further research in the field of development of neural network means of phoneme recognition of a voice signal in the system of distance learning is connected with an increase in admissible noise level. Besides, the adaptation of the offered procedure to various natural languages, as well as to other applied tasks, for instance, a problem of biometric authentication in the banking sector, is also of great interest.
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