The regulations of agreement between defense and prosecution in criminal procedure: State and development perspectives

The problem of current criminal procedural legislation improvement still retains a high degree of urgency. And one of the promising trends of such a development is the clarification of contractual regulation place and content in the field of criminal justice and, accordingly, the optimization of its parameters, which acquires a special significance in the context of a number of negative criminal trends development in Russian Federation, forming the prerequisites for their localization and overcoming. The specificity of a current criminal situation and the alarming forecasts of its development predetermine the activity of society and the state in search of optimal ways to increase the efficiency of criminal proceedings, also by improving the norms that support the existence and the actual content of contractual relations in criminal proceedings. Negative trends in crime and the declining of clear-up rate reveal that traditional, established legal institutions aimed at the elimination of the criminal-legal conflict between the state and the person who committed the crime, as well as its causes, can not always be applied effectively and require qualitatively different approaches to solve this problem, the introduction of new procedures to stop the expansion of crim

THE METHOD OF AUTOMATED BUILDING OF DOMAIN ONTOLOGY

This article is devoted to the tasks of automating the construction of domain ontologies. In the beginning, the limitations and problems of constructing the ontology of the domain using the well-known methods are discussed. Next, a model of the domain ontology is proposed, which provides the ability to automatically build the ontological hierarchy, including the automatic synthesis of generalized concepts. Then, the article discusses the method of building an ontology based on the proposed model using machine learning, and discusses its capabilities and limitations

COMPARISON OF OBJECT-ORIENTED PROGRAMMING AND DATA-ORIENTED DESIGN FOR IMPLEMENTING TRADING STRATEGIES BACKTESTER

This research proposes a way to accelerate backtesting of trading strategies using data-oriented design (DOD). The research discusses the differences between DOD and object-oriented approach (OOP), which is the most popular at the current moment. Then, the paper proposes efficient way to parallelize a backtesting using DOD. Finally, this research provides a performance comparison between DOD and OOP backtester implementations on the example of typical technical indicators. The comparison shows that use of DOD can speed up the process of quantitative features calculation up to 33% and allows for parallelization scheme that better utilizes resources in multiprocessor systems

RESEARCH OF APPROACHES TO THE RECOGNITION OF SEMANTIC IMAGES OF SCIENTIFIC PUBLICATIONS BASED ON NEURAL NETWORKS

The paper is devoted to the problems of orientation and navigation in the world of verbal presentation of scientific knowledge. The solution of these problems is currently hampered by the lack of intelligent information retrieval systems that allow comparing descriptions of various scientific works at the level of coincidence of semantic situations, rather than keywords. The article discusses methods for the formation and recognition of semantic images of scientific publications belonging to specific subject areas. The method for constructing a semantic image of a scientific text developed by Iuliia Bruttan allows to form an image of the text of a scientific publication, which can be used as input data for a neural network. Training of this neural network will automate the processes of pattern recognition and classification of scientific publications according to specified criteria. The approaches to the recognition of semantic images of scientific publications based on neural networks considered in the paper can be used to organize the semantic search for scientific publications, as well as in the design of intelligent information retrieval systems

RESEARCH OF APPROACHES TO CONSTRUCTING PREDICTIVE MODELS OF THE SPREAD OF VIRAL DISEASES

The article is devoted to the analysis of the available mathematical models in epidemiology and the possibility of their modification. We note that the situation with the COVID-19 virus pandemic is characterized by several features not comprehensively studied in the existing models. For a rational response to existing challenges, it is necessary to have a predictive and analytical apparatus in the complex (national and regional scale) mathematical models with a planning horizon of 2 years (the expected period of mass production of vaccines). The article discusses the existing approaches to predicting the spread of the COVID-19 virus in Russia based on mathematical models of epidemics. The possibilities and limitations of the proposed approaches are considered. In the conditions of the Russian Federation, transport connectivity at the interregional and intraregional levels plays an important role, and for megalopolises - transport flows within large agglomerations and the age structure of the population. In contrast to previous pandemics and epidemics, public policy plays a significant role. The approach, which consist in building multi-agent models that combine the advantages of compartment models and models based on the Monte Carlo method (individually oriented) is proposed by the authors. It is planned to use compartment models to assess the dynamics of the process and individually-oriented models - at the level of individual territories and districts.