The development of artificial intelligence (AI) technologies in recent years has become one of the key factors in the transformation of the modern legal system. Machine learning algorithms, neural networks, and generative models are already capable of creating works that are indistinguishable from the results of human creativity.: texts, music, paintings, scripts, and even program code. The relevance of the topic is determined by the rapid introduction of AI into all areas of creative activity and the lack of a unified legal approach to regulating such results. The legislation of most countries, including the Russian Federation, was initially formed around the idea of human authorship, which presupposes the existence of a person with consciousness, will and the ability to create. Artificial intelligence, which has no subjective perception, calls into question these traditional criteria. This creates legal conflicts, from issues of authorship recognition to the distribution of property rights between the developer, the user, and AI technologies. Modern discussions focus on three key issues: the possibility of recognizing artificial intelligence as a subject of copyright; determining the status of a person using AI as a tool to create a work; and the need to adapt existing legislation. The formation of a stable legal model capable of combining innovative technologies and protecting the interests of intellectual property participants depends on solving these issues.
With the rapid growth of network traffic and the complexity of the cyber threat structure, traditional methods of analysis and monitoring are becoming less effective, which creates serious vulnerabilities in information security systems. Existing signature-based approaches are unable to cope with new types of attacks, especially those that use polymorphic malware, exploit zero-day vulnerabilities or use stealthy penetration methods. This necessitates the implementation of more intelligent and adaptive solutions that can effectively analyze large volumes of heterogeneous data in real time and promptly detect anomalies in network traffic. The presented study is aimed at developing and testing modern methods for detecting anomalies in network traffic based on machine learning algorithms, including both classical and advanced approaches - deep neural networks and ensemble methods. The goal of the project is to create effective models that can automatically identify suspicious activity, classify possible threats and predict potential attack vectors. Particular attention is paid to the practical application of these models in real time without a significant increase in computational costs. To implement the tasks set, the work uses the KNIME (Konstanz Information Miner) analytical platform, which provides a visual environment for building, training and testing machine learning models. Thanks to its modular architecture and intuitive interface, KNIME simplifies the process of data processing, building workflows and interpreting results. This makes the platform especially attractive to specialists who do not have deep knowledge of programming, but are interested in using intelligent data analysis to improve cybersecurity.
Introduction. This article examines the operational characteristics of a bistatic radar system installed on an unmanned aerial vehicle (UAV) and substantiates the selection of an optimal antenna- feeder system for it. The importance of considering the influence of the UAV body, made of conductive material, on the antenna directivity and polarization of emitted signals is emphasized. A lack of sufficient information and recommendations regarding the selection of an antenna-feeder system for a bistatic radar system installed on UAVs is noted, which determines the relevance of this study.Goal. The objective of this work is to develop requirements for the selection, calculation, and modeling of an antenna-feeder system that meets operating conditions within a bistatic radar system. Materials and methods. The stages of development and testing of the selected solution are presented, including determining the technical requirements for the antenna-feeder system, assessing the applicability of existing antenna designs, calculating and manufacturing prototypes, and conducting experimental studies. The specialized Antenna Designer software package in MATLAB was used to model and optimize the characteristics of microstrip antennas.Results and discussion. The results of the studies revealed that microstrip antennas provide unidirectional radiation, stable electrical parameters across the operating frequency range, and easy manufacturing. The design advantages of microstrip antennas identified during the studies are described.Conclusion. A conclusion is reached regarding the feasibility of using microstrip antennas for the tasks being solved, and a direction for further research related to the development of two-element antenna arrays to improve the efficiency of bistatic radar systems is proposed.
Introduction. The article provides an answer to the question of why infrastructure resources and trade and transport facilities have become one of the most important priorities of American foreign policy towards the Western Hemisphere in 2025? Materials and methods. The study focuses on the dramatic process of implementing the coercive diplomacy of the American political class in relation to the Panama Canal. Results and discussion. To better understand why the Panama Canal found itself at the center of the geopolitical discussion initiated by the new administration of President Donald Trump the authors turned to the cognitive potential of transit geopolitics. Conclusion. It demonstrates what political interests and what selfish incentives fuel the US coercive policy towards Chinese positions in the Western Hemisphere.
Introduction. The resettlement of peoples and their establishment in a new territory is a long- term historical process that is influenced by a variety of political, socio-economic, and conflict-related factors. Over time, ethnic groups that have relocated can form full-fledged diasporas that become active participants in the political process.Materials and methods. In this context, the phenomenon of the Muhajirs of the North Caucasus, who, having experienced several waves of migration to the Ottoman Empire, are currently settled in various countries of the Middle East, is of significant research interest. The Muhajirs include the Circassians, the Nogais, the peoples of Dagestan, and others. The Chechens, who played a role in the political development of the modern Middle East, were also forced to relocate. Currently, the Chechen people are predominantly settled in Iraq, Jordan, Syria, and Turkey. However, their diaspora status and opportunities for participation in the political process vary in each of these countries.Results and discussion. Equations are obtained for determining the values of the established amplitudes of oscillations. The influence of dispersion caused by the non-coincidence of temperatures and velocities of gas-suspension phases on the nonlinear interaction of standing waves is investigated. This is primarily due to the fact that all of these countries have their own specific features of government, as well as face numerous conflicts at the interfaith and interethnic levels. Consequently, there is a scientific and practical need to study the historical and political context of the formation of the Chechen diaspora in the Middle East in order to gain a deeper understanding of the political process in the region and the influence of the diasporas on it. The article provides a brief historical analysis of the emergence of the Chechen diaspora in Middle Eastern countries, taking into account the specific features of their political life. Special attention is given to the role played by Chechens in the development of Middle Eastern countries after the collapse of the Ottoman Empire, as well as during the post-colonial period.Conclusion. Based on this research approach, the current characteristics of the Chechen diaspora in the countries of the region are identified.
