"Scientific research" Almanac

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  INFORMATION SECURITY OF HOSPITALS IN BULGARIA

  The relevance of this study is determined by the increasing requirements of and threats to the information security of healthcare facilities. The aim of the study is to investigate the state of information security of hospitals in Bulgaria and to define the concept of the model for information security. The following tasks are solved: studying the ... The relevance of this study is determined by the increasing requirements of and threats to the information security of healthcare facilities. The aim of the study is to investigate the state of information security of hospitals in Bulgaria and to define the concept of the model for information security. The following tasks are solved: studying the state of information security of hospitals in Bulgaria and opportunities for improvements; highlighting the good practices; analysing the capability of new technologies. On this basis, a concept for an information security model is developed, taking into account the features of Bulgarian hospitals. The research thesis, which is defended, is that threats and information security requirements have been steadily increasing. This requires precautionary measures and a high level of security and protection of data and services, as well as business continuity and is particular important to hospitals that collect, store and process personal data and health data of their patients. The information security level can be increased by applying an information security model. The studies have analysed the state of information security of medical establishments in Bulgaria and defined a concept for an information security model based on: good practices; following the recommendations for technical implementation required by the GDPR; accounting for the principle of protection levels.

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  EVALUATION OF CONVERGENCE IN SOCIAL PROTECTION EXPENDITURE IN THE EUROPEAN UNION

  The purpose of this paper is to evaluate the degree of convergence across the EU Member States in social protection expenditure for the period 2008-2016 by using statistical and econometric approaches for measuring convergence. This is achieved by accomplishing several tasks: presentation of theoretical concepts and statistical and econometric ... The purpose of this paper is to evaluate the degree of convergence across the EU Member States in social protection expenditure for the period 2008-2016 by using statistical and econometric approaches for measuring convergence. This is achieved by accomplishing several tasks: presentation of theoretical concepts and statistical and econometric approaches for convergence evaluation; exploring the convergence process through the club convergence approach; exploring the convergence process through the beta-convergence approach across European Union Member States as a whole, and between countries in individual convergence clubs; analysis of the impact of structural variables on social protection expenditure and the cohesion process. The thesis defended by the author is that by using the applied approaches for the study of the club convergence and beta-convergence, an adequate evaluation of the degree of convergence of the EU Member States is achieved. This makes it possible to establish the rate of convergence to the general equilibrium both within the European Union and within separate convergence clubs. As a result of the study of club convergence, convergence clubs, clubs in a process of transitional divergence, as well as countries that are not involved in that process are identified. The study of beta-convergence shows a process of reducing disparities in convergence clubs and the European Union as a whole. The findings of the study indicate that the additional variables in the models of conditional beta-convergence have a significant impact on the increase in the social protection expenditure and the cohesion process. EU countries converge at a faster pace into the general equilibrium level of social protection expenditure when it is presented as a percentage of Gross Domestic Product.

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  DEEP NEURAL NETWORKS FOR DETECTION OF CREDIT CARD FRAUD

  This publication presents research on the possibility of using Deep Neural Net-works (DNNs) for detection of credit card fraud. The research is based on an open da-taset and aims to determine how the varying number of hidden layers and other archi-tectural parameters (width of each layer, activation functions) affects training and predictive ... This publication presents research on the possibility of using Deep Neural Net-works (DNNs) for detection of credit card fraud. The research is based on an open da-taset and aims to determine how the varying number of hidden layers and other archi-tectural parameters (width of each layer, activation functions) affects training and predictive potential of the network. It also aims to determine how to use generative-adversarial approach efficiently in order to overcome the problem with the imbalance between legitimate and fraudulent transactions, which is crucial characteristic of the datasets related to detection of credit card fraud. The publication presents the results of various experiments, conducted to achieve the stated goals. A number of experiments have been carried out combining network training of various depth of the network and with different parameters of the learning process, for example, activation function and dropout values. The experiments focus on using generative-adversarial approach as a method for oversampling, in par-ticular. The results indicate that deep neural networks with moderate hidden layers, combined with methods for oversampling are performing much better in identifying fraudulent transactions than the classical neural networks, consisting of only one hid-den layer. The results also indicate that using generative-adversarial approach as a method for oversampling is comparable in efficiency to other widely used techniques.