The method of statistical processing of cyclic random processes by reducing them to isomorphic periodic random sequences, which significantly simplifies analytical expressions and formulas for calculations, and also reduces the computational complexity of the tasks of statistical processing and computer simulation (generalization) of cyclical signals in intelligent information systems in medicine, technology and economics, which is especially important for their implementation in portable systems with significantly limited computing capacity is developed in the paper. The example of statistical evaluation of the initial moment function of the first order of cyclic random process of discrete argument using the existing method, and also with the use of the new method of statistical evaluation, based on the procedure of reducing the investigated cyclic random process to isomorphic periodic random sequence, which statistical processing methods are characterized by much less calculations complexity. Isomorphic in terms of order and values, cyclic random processes, in general, differ only in their rhythmic structures (functions of rhythm) and in their totality form an equivalence class. Any class of isomorphic with respect to the order and values of cyclic random processes of a discrete argument, as its subset, contains a subclass of isomorphic with respect to the order and values of periodic random sequences. Based on this fact, the paper developed a method of reducing the statistical processing (estimation, analysis, forecasting) of a cyclic random process of a discrete argument to an isomorphic periodic random sequence. The computational complexity of the known method of statistical estimation of the probabilistic characteristics of a cyclic random process of a discrete argument is investigated and the method of statistical analysis of the probabilistic characteristics of a cyclic random process of a discrete argument developed in this work to the corresponding statistical processing of an isomorphic periodic random sequence is obtained. Examples of statistical estimation of the initial moment function of the first order of a cyclic random process of a discrete argument using the known method are given, as well as with the use of a new method of statistical estimation based on the procedure of reducing the investigated cyclic random process to an isomorphic periodic random sequence, methods of statistical processing of which is characterized by much less computational complexity.

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Method for reducing the computational complexity of processing discrete cyclic random processes in digital data analysis systems

The market of modern neurointerfaces, despite its active development, unfortunately, can offer users only a number of existing prototypes that have a relatively low accuracy and identification reliability of the human operator control effects. In addition, any neurointerface on the market must be individually tailored to each operator, which makes it difficult to objectify its accuracy, precision and reliability. The first step in solving the above problems is to conduct a comparative analysis of different price segments of the market of existing neurointerface technologies, as presented in this article. The market research revealed that despite the disadvantages of electroencephalography, it is one of the most accessible non-invasive methods of recording biological signals in neurointerface systems. To facilitate future research, the main advantages and disadvantages of known models and methods of signal analysis in neurointerfaces have been considered and analyzed. In particular, in the context of signal pre-processing, advantages and disadvantages of such methods as Common Average Referencing, Independent Component Analysis, Common Spatial Patterns, Surface Laplacian, Common Spatio-Spatial Patterns and Adaptive Filtering are considered. At the stage of evaluating the informative characteristics of the signal, the analysis of models and methods based on the models of adaptive parameters of autoregression, bilinear autoregression, multidimensional autoregression, fast Fourier transform, wavelet transformation, wave packet decomposition is performed. Besides, a comparative analysis of the most common methods of identification (recognition) of control effects of the human neurointerface operator, namely, the method of discriminant analysis, the method of reference vectors, nonlinear Bayesian classifiers, classifiers of nearest neighbors, artificial neural networks is carried out. The study of neurointerface technologies provides researchers with additional grounds for a sound choice of mathematical, software and hardware of neurointerface systems, as well as contributes to the development of new versions with increased accuracy, reliability and reliability.

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Comparative analysis of neurointerface technologies for the problem of their reasonable choice in human-machine information systems

The article is devoted to development of onto-oriented information systems for folk (unconventional) medical directions. The problems of forming scientific directions of folk medicine types on the way of their transformation into a single integrated medical system are analyzed. The ways of solving these problems are outlined and the strategy of integration of folk medicine types as components of Integrative Scientific Medicine using the ontological approach based on the example of Chinese Image Medicine is presented. The diagnostic ontology of Chinese Image Medicine and the prototype of the ontooriented system of professional healing activity "Image-Therapist", which as the core of the knowledge base, uses this ontology, have been developed.

Ontooriented Information Systems for Folk Medical Directions

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Mathematical Modeling And Processing Of High Resolution Rhythmocardio Signal Based On A Vector Of Stationary And Stationary Related Random Sequences.

The task of writing a novel textbook on general probability theory seems virtually impossible nowadays. In Theory of Stochastic Objects, the author Athanasios Micheas aims to overcome this challeng...

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2020.1721248

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference.

The substantiation of a complex of methods and means of knowledge elicitation in Chinese Image Medicine (CIM) for the tasks of its ontological modeling in addition to the development of intellectualized information systems is the topical issue of the article. The methods of specific knowledge elicitation from the CIM experts has been defined in the research, the templates of questionnaires for a group survey have been developed as well, the axiomatic-deductive strategy of the structural and logical organization of the acquired knowledge has been used, according to this data a fragment of the diagnostic ontology of the CIM has been implemented.

Methods and Means of Knowledge Elicitation in Chinese Image Medicine for Achieving the Tasks of Its Ontological Modeling

З метою дослідження потенціалу, перспектив та ефективності використання відомих математичних моделей циклічних сигналів та процесів як фундаменту математичного забезпечення інформаційних систем, їх аналізу, прогнозування та імітації, проведено компаративний аналіз широкого класу математичних об’єктів, що використовуються або можуть бути використані як моделі сигналів та процесів циклічної структури. Проведене аналітичне дослідження допоможе досліднику обґрунтовано вибрати та адаптувати (адекватно структурі досліджуваних сигналів та задачам дослідження) математичну модель із наявної їх сукупності, що суттєво підвищить ефективність (спростить та пришвидшить) розбудови математичного забезпечення проектованої інформаційної системи.

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The comparative analysis of mathematical models of cyclic signals structure and processes

In this paper we consider a modernized of the software system for the automated determination of morphological and rhythmic diagnostic signs of electrocardio signal. The modification of the system is to create a new method and appropriate software that involves processing electrocardio signals by reducing the discrete cyclic random process, as a model of electrocardio signal to isomorphic random periodic sequence. The use of a new mathematical model of electrocardio signals in the form of conditional discrete cyclic random process allowed to take into account and carry out automatic determination of both morphological and rhythmic diagnostic sings of electrocardio signal within the same mathematical model. The use of a new method of statistical processing based on the new model, allowed to obtain statistical characteristics that are infomative diagnostic signs (morphological and signs of rhythm) of the electrocardio signal. The application of the method of reducing a discrete cyclic random process to isomorphic random periodic sequence before the procedures of statistical processing of the electrocardio signal, in particular before obtaining morphological and rhythmic sings allowed to increase the speed of automated processing of the electrocardio signal in comparison with the previously developed methods which were based on it model in the form of a cyclic random process and did not account for the double stochastic model.In the structure of the modified software system, after the evaluation of the rhythmic structure of the electrocardio signal and the procedure of reduction to a random periodic sequence of a discrete cyclic random process, its processing is branched into two parallel stages. The first stage carries out the morphological analysis, which involves the statistical processing of the electrocardio signal, normalization of statistical estimates and their distribution in the Chebyshev base and decision making on the obtained morphological sings.

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Modification of the Software System for the Automated Determination of Morphological and Rhythmic Diagnostic Signs by Electrocardio Signals.

Air pollution influences human activities, leads to global warming, poses a hazard to the ecosystem and life quality on the Earth. To avoid such adverse instability in nature, increasing the efficiency of air pollution monitoring means and methods is extremely important. In this paper the development and implementation of an effective solution for remote air pollution monitoring based on IoT is proposed. The system is developed using the Arduino Leonardo module and Raspberry Pi microcomputer. The concentration level in the air of the LPG, carbon monoxide, methane, and carbon dioxide using MQ2, MQ7, MQ9, and MQ135 gas sensors are measured. These sensors can reveal many hazardous gases and can be used for measuring their quantity very precisely. The air pollution monitoring system measures air quality parameters and transfers them to a cloud server in real-time in order to provide remote access. Experimentation results performed using the designed computerized air quality monitoring system show that it provides a reliable source of real-time air pollution data. The essential aspect of this work is to produce a low-cost infrastructure to enable data aggregation and proliferation to all users.

Halyna Osukhivska

Papers

Methods and Means of Knowledge Elicitation in Chinese Image Medicine for Achieving the Tasks of Its Ontological Modeling

The comparative analysis of mathematical models of cyclic signals structure and processes

Modification of the Software System for the Automated Determination of Morphological and Rhythmic Diagnostic Signs by Electrocardio Signals.

Remote Air Pollution Monitoring System Based on Internet of Things