This paper, describes a developed simulation model that gives the ability to simulate various situations of possible fire occurrence and study the behavior of people during their evacuation, taking into account various factors in different types of buildings, which allows the prediction of the consequences of a fire and subsequently develop rules for human behavior in extreme situations. Studies have shown that the optimization of movement during the simulation of a fire made it possible to reduce the likelihood of fire by approximately 20%, and the presence of an emergency exit reduces it by another 30%, which makes it possible to optimize the results of modeling the consequences of a fire in rooms of various types.
The paper presents the results of the studies of the probability of a “flip” of the approximating function when processing the measurement results under conditions of a priori uncertainty about the signal function and the statistical characteristics of additive noise. It is analytically proved that the confidence intervals of the probability of the absence and the presence of a “flip” are equal, which is confirmed by the experimental results. The dependences of the “flipping” of the approximating function on the sample length, the dispersion of additive noise and the rate of change of the function itself are obtained.
The internal state of the material formed as a result of technological processing, indirectly affects the state of the material surface. A non-contact method of non-destructive control of the state of materials based on a visual analysis of the surface, requires high-quality images which can be obtained either using lens objectives or lenseless technologies. The results of studying image processing obtained by lensless technologies are presented. We used methods for modeling phase masks and image processing based on Gerchberg – Saxton iterative algorithms, adaptive-additive and phase mask rotation based algorithms. Materials such as granite, graphite, sand and carbon steel were analyzed. It is shown that the construction of cameras can provide significant reduction of their dimensions at the same or even improved characteristics. The images obtained using lensless technologies and the proposed methods of image processing also provide a significant increase in the accuracy of visual inspection of materials. The results obtained can be used in refining lensless technologies, improving the quality of images and reducing time of their processing.
The paper discusses the issues of practical implementation of increasing the accuracy of signal extraction, which is achieved by eliminating the «flip» of the approximating function when dividing the measured process into intervals under conditions of a priori uncertainty about the signal function, which significantly increases the error of allocating a useful signal. The probability of a «flip» of the approximating function depends significantly on the variance of the additive noise and the sample length. The use of the proposed methods and their software implementation makes it possible to increase the accuracy of the useful signal extraction up to 30 percent in the absence of a priori information about the function of the measured process for complex signals and at least 20% for simpler ones. The use of the proposed methods will significantly increase the processing efficiency in the conditions of a priori uncertainty about the function of the measured process (useful signal) and the statistical characteristics of the additive noise components.
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