The need for research using modern methods of physical and chemical analysis in combination with methods for processing the graphical results arises with an increase of developments aimed at changing the structure and properties of hydration-hardening materials. Currently, the method of scanning electron microscopy is widely used for the qualitative and quantitative analysis of materials. Additional information, including fractal analysis of the image, determines the information-entropy levels and the state of the information system in the form of the microstructure based on the generalized structural entropy that increases the volume and quality of analytical information extracted from the obtained images. Images with a magnification of 20,000 times were used to analyze the microstructure of a control cement composite and a carbon black modified composite. The fractal analysis of the images revealed a change in the relative organization of the system, which justifiedthe nature of the change in the physical and technical properties of the modified cement composite relative to the additive-free cement composite from the perspective of self-organization.

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Most methods of morphological analysis of the electrocardiogram (ECG) are based on the search for R-wave. Knowing the position of the R-wave, it is rather simple to determine the remaining components of the QRS complex. The main problems of machine detection of the R-wave are ECG trace artifacts and high variability of cardiac complexes. The algorithm for detecting the QRS-complex consisting of two stages is proposed and implemented. At the preliminary stage, time-frequency transformations as in the Pan-Tompkins detector are used to remove noise and non-informative ECG components. The algorithm has adaptive parameters to account for the variability of R-wave. The arithmetic mean and the standard deviation of the height of the preceding R-wave and the lengths of the RR intervals are used as these parameters. At the main stage of the algorithm, adaptive parameters are used to predict the characteristics of the next R-wave. A function evaluating the difference between the current metrics of the conditional R-wave with a vertex at the given point and the expected ones is proposed. The minimum of the given function on a given interval is a criterion for the detection of the R-wave. The software implementation of the algorithm showed high sensitivity and specificity on MIT-BIH test databases. The algorithm can be used in cardiomonitors, automatic defibrillators, artificial pacemakers with feedback and other devices with real-time ECG processing