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The paper deals with the analysis of the banking system of Ukraine. It is shown that for Ukraine the frequency and depth of crisis phenomena in the banking sector are exacerbated by the raw material orientation of the economy, underdeveloped domestic market and the circulation of foreign currency (dollarization of the economy). It should be noted that in the pre-crisis during 2006-2007, excessive mortgage lending created a "bubble" in the real estate market, which, comparing its devastating effects, corresponded to this phenomenon in the real estate market in the United States. Although the crisis of 2008-2009 demonstrated the vulnerability of the Ukrainian banking system to numerous economic and political upheavals, no significant changes in banking supervision took place to minimize systemic risks. Restoration of the banking system of Ukraine in 2015-2016 is generally in line with post-crisis trends to streamline the banking system and increase its efficiency in the world. At the same time, the weakness of the institutional environment makes it impossible to use both administrative tools and state development banks to increase productive lending in Ukraine. On the other hand, commercial banks will use refinancing loans instead of private-sector savings to lend. In this case, the probability of the need for financial support from banks increases, which will lead to a significant increase in public debt.Moreover, a system of vector autoregression models has been developed to research the impact of crisis periods on the performance of commercial banks in Ukraine. The simulation results (mainly the analysis of impulse response functions) allow concluding that interbank lending in post-crisis conditions recovers relatively rapidly (with a lag of two years). Lending to non-financial corporations and non-residents showed a decline and recovery only within four years after the crisis. Lending to the general government sector is growing every year, but at the same time loans to other resident sectors are declining. In addition, during the year after the crisis, the volume of deposits in the banking system is demonstrating a decrease. Other variables do not show any response to the crisis.

The topicality of the research lies in the fact that the long-term evolution of financial markets, reinforced by global transformations, has led to the development of convergent processes in banking activities in the presence of significant paradigmatic differences between the major banking systems of the world. The existing peculiarities in the mechanisms and methods of regulation of the banking sector within individual countries have caused drastic changes in views on the nature of the bank and its activities. The traditional view of banks as institutions of financial intermediation, providing the exchange of monetary assets between the owners of savings and borrowers, does not provide for the creation of new money. Instead, proponents of the alternative viewpoint emphasize that in today's world banks finance borrowers mainly through the mechanism of money emission. Both points of view are present to varying degrees in various theoretical and conceptual approaches to understanding the essence of the bank as an institution of financial intermediation. The current economic realities require a detailed study of national banking systems, which largely developed historically, and methodological aspects of their evolution in the context of global transformations. The research subject. In the process of evolution of theoretical and conceptual approaches to the definition of the essence of money, banks, the banking system, the prevailing point of view on this issue has not yet taken a definite form. Nevertheless, the recognition of the effectiveness of banks as a factor of economic growth brings together the positions of competing schools of economic theory. Banks become a factor in the investment process even in the theoretical models of the neoclassical school, which traditionally denies the dependence of economic growth on the money supply. Endogenous growth models recognize the role of banks primarily as a factor in accumulating capital and increasing savings, as well as a mediator between owners of savings and borrowers. Although the Keynesian school of thought initially gave little weight to the functioning of the banking system, neo-Keynesian models have attempted to explain the importance of confidence in the banking system and the need for sound regulatory constraints. The above-mentioned has urged us to carry out this research. The methodological framework of the research is based on an analysis of research on the global debate about the nature of banks in the economy and the architecture of monetary policy. A wide range of theoretical and empirical research methods were used: systematic analysis, synthesis and generalization to formulate conclusions. The aim of the research is to generalize and systematize the evolution of perspectives on money in the interpretations of today’s main economic schools. Conclusion. The findings consist of a conceptualization views' evolution on money, the banking sector in a more open economy to capital flows, and our firm belief that the banking system and the related process of money issuance affect income levels cyclically and over the long term.

Convenient and accurate verification of the user of a car sharing system is one of the key components of the successful functioning of the car sharing system as a whole. The machine learning-based KYC (Know your customer) process algorithm makes it possible to improve the accuracy of customer data validation and verification. This makes it possible to eliminate possible losses and reputational losses of the company in case of unforeseen situations while using the client's car sharing services. The object of this study is to find a solution to the problem of user verification in a car sharing system based on the KYC process using deep learning methods with a combination of OCR (Optical Character Recognition) methods. The statement of the user verification problem in the car sharing system was formalized and the key parameters for the KYC process have been determined. The algorithm of the KYC process was constructed. The algorithm includes six successive stages: separating a face in the photograph, comparing faces, checking documents and their validity period, establishing and recognizing ROI (region of interest), formulating a verification decision. To separate the face in the client's photograph and compare faces, methods based on deep learning, as well as the quick HoG method (Histogram of oriented gradients), were considered and implemented. Verification of these methods on a test dataset, which includes images of documents of two thousand clients, showed that the recognition accuracy was 91% according to Jaccard's metric. The average time of face separation using the HoG method was 0.2 seconds and when using trained models – 3.3 seconds. Using a combination of ROI and ORC separation methods makes it possible to significantly improve the accuracy of verification. The proposed client verification algorithm is implemented as an API on an ML server and integrated into the car sharing system.

Research on the development of methods for identifying signs of hidden manipulation (destructive information and psychological impact) in text messages that are published on Internet sites and distributed among users of social networks is relevant. One of the main problems in the development of these methods is the difficulty of formalizing the process of identifying signs of manipulation in text messages of social network agents. To do this, based on morphological synthesis, it is necessary to determine relevant indicators for analyzing text messages and criteria for making a decision about the presence of signs of manipulation in text messages. Based on morphological synthesis, a method for determining manipulation indicators in text messages was developed, taking into account the achievements of modern technologies of intelligent content analysis of text messages, machine learning methods, fuzzy logic and computational linguistics, which made it possible to reasonably determine a group of indicators for evaluating text messages for signs of manipulation. The stages of the method include evaluating the text message at the level of perception by the indicator of text readability, at the phonetic level by the indicator of emotional impact on the subconscious, at the graphic level by the indicator of text marking intensity, and calculating the integral indicator for making a decision about the presence of manipulation in the text message. Based on the proposed method, specialized software was developed that provided 13% greater accuracy in evaluating messages for manipulative impact compared to the known method of expert evaluations, which reduced the influence of the subjective factor on the evaluation result

Objective: Battlefield Acupuncture (BFA) is a form of auricular acupuncture that is increasingly rising in popularity as a method of managing pain in military settings. This study aims to contribute to the growing body of literature on the efficacy of BFA by evaluating pain pre- and post- BFA administration and by measuring that pain by level and type. Materials and Methods: This was a retrospective study evaluating active duty Army members who were receiving care at the outpatient military clinic. Data evaluated all patients undergoing a BFA procedure between March 1, 2020, and November 1, 2020. The pain was rated using a standardized DOD/VA pain scale. Results: Of the 26 patients that met our inclusion criteria, 21 (81%) experienced a decrease in pain following BFA administration, while 5 (19%) experienced no change. No patients experienced an increase in pain. Individuals with a baseline pain of 6 or less experienced a greater decrease in pain than did those with a baseline pain of more than 6. Those with low back pain also experienced a greater reduction in pain than did those with other pain types. Conclusions: BFA effectively reduces pain and can be considered a promising treatment option for pain reduction in a military setting. Further research is needed to evaluate the efficacy of BFA on various pain types.

The article presents a new algorithm of accelerated multiplication, in which the time of multiplication has been reduced through the decrease in the number of nonzero digits of the multiplier. In this case, the multiplier has been presented in the form of the extended binary code. The article proves the algorithm's efficiency in comparison to previously known methods. The developed algorithm has been implemented using the hardware description language AHDL (Altera Hardware Description Language) in the Logic Development System MAX+PLUS II.