Kasimova S.
doctor of technical sciences, professor,
Azerbaijan Technical University
Kasimov E.
doctor of physical and mathematical sciences.
Baku, Azerbaijan

Abstract
The conditions and frequency band of complete absorption of electromagnetic radiation in the absorbing magnet-dielectric system were studied depending on the selective values of the dielectric constant of the substrate, magnetic properties and thickness of the magnetic coating layer, which make it possible to almost completely extinguish the radiation when creating anti-radar non-reflective coatings, providing shelter for objects from their light detection.

Keywords: non-reflective coatings, magnetic coatings, dielectric coatings, total absorption, electromagnetic radiation, substrate, layers.

Jabbarova K.
PhD,assoc.prof, Azerbaijan state oil and industry university
Shukurzade J.
master’s student,Azerbaijan state oil and industry university

Abstract
The call center is organized in order to ensure compliance with laws and regulations in the central government body, objective investigation and response to complaints, prevention of illegal activities, analysis to improve performance and ensuring public satisfaction. An analysis of the data received by the call center is required in order to assure the fairness of government services, the fight against corruption, the objective activities of civil officials, and the prevention of cases aimed at causing public displeasure. There is a need for call centers to operate more rationally and perfectly as an important structural element of government agencies. There is a need for call centers to operate more rationally and perfectly as an important structural element of government agencies. Therefore, in this paper we apply multi-criteria decision making method to selection best software selection for call center. Decision matrix consist of five alternative (Orange Line, ProCall,VoIPTime, Instacall, K3) and five criteria (Telephony, Callback; Call Forward; Reporting, System integration). The obtained results show effectiveness this method.

 Keywords: MCDM, call center, PROMETHEE method, software selection

Mamatov N.
Doctor of Technical Sciences, Professor, Head of the Department of Digital Technologies and Artificial Intelligence,
National Research University Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan
Ibrokhimov S.
Assistant, Department of Digital Technologies and Artificial Intelligence,
National Research University Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan
Samijonov A.
Assistant, Department of Digital Technologies and Artificial Intelligence,
National Research University Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan 

Abstract
The development of artificial intelligence (AI) has created the problem of analyzing and revising the entire world’s educational process. This is inextricably linked with the strong interest in using AI in the educational process and the differences between its practical application. Some business representatives consider modern universities to be factories for mass production of higher education diplomas. Employers often emphasize that educational standards and programs do not meet the requirements of modern times, and the need to retrain graduates. This article is devoted to the prospects and consequences of the use of AI in higher education, which includes the stages of AI development, negative and positive effects on the educational process, the use of AI technologies in the educational process, its economic and moral importance, student and AI mutual relations, social effects are described.

 Keywords: artificial intelligence(AI), IT, algorithm, virtual reality, robotics, machine learning, ChatGPT.

Jabbarova K.I.
Doctor of Philosophy, associate professor of Azerbaijan State Oil and Industry University
Mammadaliyeva G.N.
master’s student of Azerbaijan State Oil and Industry University

Abstract
Choosing the best big data analytics platform is essential for companies looking to gain valuable insights in today’s data-driven environment. However, due to the variety of available platforms and different application requirements, this selection procedure is inherently complex. To solve this problem, we use fuzzy TOPSIS method. This method allows you to systematically evaluate and select the most suitable approach for a big data analytics platform based on the company’s requirements. The fuzzy number based decision matrix consist of three alternatives and four criteria (Availability and fault tolerance,  Data security, Ease of installation and maintenance, User interface and reporting). The getting results show validaty of the considered approach.

 Keywords: Big data analytics, Multi-Criteria Decision Making (MCDM), platform selection, fuzzy TOPSIS method

Zeynalzade G.
Nakhchivan State University, lecturer
Nakhchivan, Azerbaijan

Abstract
The integration of big data analytics has significantly influenced business strategy and decision-making processes across industries. This paper examines the multifaceted impact of big data on strategic planning, resource allocation, market insights, and customer experiences. It delves into the role of data-driven decision-making in enhancing operational efficiency and competitive advantage. The study also explores the challenges and opportunities associated with big data adoption, including data governance, privacy concerns, and technological advancements. Through case studies and industry examples, this paper provides insights into how businesses can leverage big data to drive informed decision-making and achieve sustainable growth in today’s dynamic business environment.

 Keywords: big data,business strategy,decision making,data analytics,data-driven decisions,strategic planning,market trends

Mammadov E.
Master of Science in Computer Engineering (2nd year student)
Azerbaijan State Oil and Industrial University
Baku,Azerbaijan

Abstract
The optimization of query understanding within search engines is a critical endeavor that marries the complexities of Natural Language Processing (NLP) with advanced mathematical models. Central to enhancing search engine performance, this exploration covers the roles of syntactic analysis, part-of-speech tagging, and named entity recognition in dissecting and interpreting the structure of user queries. It further delves into the mathematical theories underlying these NLP techniques, spotlighting the use of probabilistic models such as Hidden Markov Models (HMMs) and Conditional Random Fields (CRFs), alongside the emergence of neural network-based approaches. Through a nuanced examination of these methodologies, the discussion underscores how mathematical approaches to NLP significantly bolster the accuracy and relevance of search engine responses, paving the way for a more intuitive and efficient retrieval of information in the digital age.

 Keywords: Natural Language Processing (NLP), query understanding,probabilistic models,Syntactic Analysis,Part-of-specch Tagging (POS),Named Entity Recognition (NER)

Cristian Purece
PhD, Scientific Secretary, INCDIE ICPE-CA Bucharest Subunit ICEMENERG
Daniela Adriana Sima
PhD student, UNŞTPB/INCDIE ICPE-CA Bucureşti

Abstract
In this paper, the authors briefly present the methods for determining in situ the efficiency / performance of a hydraulic turbine as well as the purpose, the necessity of applying the methods of in situ determination of the efficiency of the hydraulic turbines from a hydropower plant. These efficiency tests are an essential practice to ensure that the performance of the hydraulic turbine and the hydropower plant have not degraded to unacceptable levels. Also in the paper are presented the results of the efficiency tests carried out at a cascade of three hydropower plants, form Romania, from the arrangement of the Râul Mare downstream.

Keywords: hydropower plants, discharge determination, turbine efficiency, in situ tests, hydro-unit.

Banza Plandi Kantshiama
postgraduate student
Komrakov Vladimir Viktorovich
Candidate of Technical Sciences, Associate Professor
Gomel State Technical University named after P.O. Sukhoi

Abstract
In the contemporary industry of machine manufacture, the analysis of the interplay between machine elements that are susceptible to friction is of paramount importance. The magnitude and qualities of this friction have a direct impact on the efficiency of mechanisms, their longevity, and their dependability. However, friction is not solely a resistive force to be surmounted, but it also has latent potential to engender heat, oscillation, and attrition. Coulomb’s law, which governs the ratio of friction force to normal force, is the central point of investigation for academics. Precise determination of the friction coefficient, as well as comprehension of the dynamics of this phenomenon, can profoundly enhance the performance and longevity of mechanisms. This is especially true in the context of incessant growth and integration of automatic systems, where even a minor shift in frictional characteristics can have momentous implications on the operations of all machinery.
As per the esteemed Journal of Friction and Wear (2019), a conspicuous surge in the longevity of machines, up to 15-20%, can be attained via rectifying the geometric parameters of kinematic pairs. However, notwithstanding the multitude of publications on this matter, the issue of the numerical correlation between said geometry and the level of wear remains unresolved. The State Institute of Mechanical Engineering (2020) has reported that a staggering 60% of equipment malfunctions are attributable to the imprudent selection of geometric parameters.

Keywords: kinematic pairs, geometric parameters, wear, optimization, mathematical model, experimental studies.