The development of cutting-edge motor technologies for electric vehicles (EVs) has been fueled by the global movement towards sustainable mobility. Because of its great efficiency, power density, and flexibility to operate at various speeds, Permanent-Magnet Synchronous Motors (PMSMs) have become the go-to option for small-class EVs. However, the accuracy and applicability of standard mathematical modeling techniques are limited because they frequently miss real-world nonlinearities and parameter fluctuations.

In this paper, a data-driven methodology for PMSM modeling that is tailored for small-class EV applications is presented. The suggested method improves the precision, flexibility, and computational efficiency of PMSM models by utilizing real-world operational data. The efficiency map and peak torque characteristics of the WULING MACARON EV's electric drive were defined using regression analysis, which produced low residual errors and high R-squared values of 0.9647 and 0.9789, respectively. The outcomes show that the model can optimize energy use, forecast performance under various circumstances, and assist real-time control applications.  

Generative AI is rapidly reshaping the landscape of software (SW) companies’ operations, offering unprecedented capabilities for creating new code, documentation, designs, and more. By harnessing advanced machine learning architectures such as large language models (LLMs), agent-based frameworks, retrieval-augmented generation (RAG), and multimodal systems, organizations can reduce development cycles, improve service quality, and unlock innovative business opportunities. Recent articles highlight how these AI-driven approaches not only address routine tasks—such as boilerplate code generation or automated testing—but also facilitate more complex undertakings, including self-healing infrastructure and intelligent orchestration of multi-step workflows. However, integrating generative AI into software operations requires strategic planning around data governance, infrastructure scalability, workforce reskilling, and ethical guardrails. This research article examines the current applications of generative AI in software organizations, details emerging approaches for operational efficiency, and discusses implementation challenges. In doing so, it presents a holistic framework for understanding and adopting generative AI techniques—ranging from code completion to multimodal content creation—while emphasizing the synergy between agent-based architectures and retrieval-augmented generation. The discussion concludes with recommendations on how software firms can realize long-term benefits by blending AI-driven automation with robust oversight mechanisms, ensuring that generative AI becomes a catalyst for sustainable and ethical operational improvements.

The article identifies and describes testing methods that take into account the specifics of perception and orientation in the interface of such users. Interaction with voice interfaces creates a number of difficulties for users who use screen readers, as it requires the development of special approaches to create an accessible and user-friendly interface. Throughout the course of this work, the functional and cognitive aspects of voice interaction were investigated, compatibility with screen readers was evaluated, and synchronization of audio streams was studied.

Scientific articles were used as methodological sources, and for the practical part of the work, data contained in open access on the Internet was used, which made it possible to widely consider the chosen topic and form one's own position on the topic under consideration.

The results of the analysis showed that improved audio stream management and command settings reduce the burden on information perception and make it easier to interact with the interface. The conclusion of the work emphasizes the necessity of conducting tests in real-world conditions, considering the characteristics of the target audience.

The information presented in this article will be valuable to developers, designers, and testers who are interested in creating inclusive applications for visually impaired users.

The production and implementation of solar-powered water heaters represent a significant step toward sustainable energy solutions, particularly for rural communities in Uzbekistan. This paper discusses the development of an innovative solar-powered water heating device, its technological features, and its benefits in enhancing living conditions while reducing environmental impact. The depletion of fossil fuels and the associated global energy crisis necessitate a transition to renewable energy sources (RES), such as solar energy, which is abundant and sustainable. In line with Uzbekistan's energy strategy, the government has been promoting alternative energy sources (AES) to decrease reliance on traditional fuels and increase energy efficiency. The proposed solar-powered water heating system leverages modern technological advancements to maximize energy absorption and storage, ensuring a reliable supply of hot water. This development aligns with the nation's broader energy policy, which emphasizes renewable energy integration to address economic and environmental challenges. By implementing these systems, Uzbekistan aims to contribute to global efforts in reducing carbon emissions and promoting sustainable energy solutions. The study also highlights international best practices in renewable energy adoption, offering insights into future strategies for enhancing energy sustainability in the region.   

This review article explores the potential benefits of implementing the Capability Maturity Model Integration (CMMI) methodology in gaming industry companies. The work begins by describing the role of ISACA and the CMMI Institute in developing professional process management standards. The article examines the structure of CMMI and its application in the context of game development. Key stages of the CMMI audit in gaming companies are highlighted, from the initial assessment to post-audit activities, and a strategy for improving business processes is formulated, considering the industry's specific characteristics. Special attention is given to existing research findings and practical examples of Particular attention is given to analyzing the feasibility of applying CMMI in gaming companies, based on the results of a technical report published by ISACA, as well as examples of CMMI-certified companies such as Tietronix, XcelTec, WebClues Infotech, ISHIR, and Team In India, which specialize in game development. 

This article identifies the primary advantages of automating the testing processes of medical applications, significantly enhancing their reliability and safety. Special attention is given to methodologies such as Total Quality Management and Plan-Do-Check-Act, as well as the application of mobile technologies in healthcare, which contribute to error minimization and improved treatment quality. The article describes a multi-stage study, including an analysis of scientific publications, experimental testing using automation tools, and statistical data processing. The study also examined the importance ranking of various quality criteria identified during the evaluation of different medical applications. The results demonstrate significant improvements in diagnostic accuracy and patient satisfaction through the use of electronic medical records and feedback systems. This article will be particularly valuable to healthcare professionals and software developers, including quality engineers and developers of medical applications, as well as researchers studying the impact of technologies on the medical industry. This work serves as a valuable resource for those aiming to enhance the quality and safety of medical services through innovative automation methods. 

Efficient energy management on ferry ships is critical to reducing operational costs and promoting sustainability. This study introduces a LoRa-based wireless telemetry system for real-time monitoring of electronic equipment loads in ferry passenger cabins. The system leverages LoRa’s long-range, low-power communication capabilities to collect and transmit energy usage data, enabling precise tracking and management of electrical loads. Through field testing, the proposed system demonstrated reliability, scalability, and energy efficiency. The implementation of this technology allows for enhanced operational insights, reduced energy waste, and improved onboard energy efficiency. This approach provides a cost-effective solution for modernizing energy management in maritime transportation.

This paper explores active defense for UAVs globally, with the main emphasis on detection and countermeasure technologies. Questionnaires were administered to 139 individuals in the USA, and the results were analyzed with the help of the Statistic Package for Social Sciences (SPSS), including reliability analysis, descriptive frequency, and regression analysis. The results concerning Hypothesis 1 concerning technological detection impact on the adequacy of UAV defense are the following. Analyzing the data, it was established that detection technology influences UAV defense significantly with F =12. 27 and a signification p, therefore, is less than 0,001. Total regression analysis showed that In relation to this aspect, the regression coefficient (b = 0. 292, p <. 001) shows that detection technology has a positive influence on UAV defense and accounts for 8. Two percent of the total aggregated variation across the defense effectiveness of the participating countries (R² = 0. 082) could solely be attributed to these potentates. Thus, the findings of Hypothesis 2 prove that countermeasure technology also plays another major role in the defense of UAVs. Analysis of variance for the model revealed that technology used in countermeasures tremendously impacts UAV defense with F = 113. 465, and the calculated p is less than 0. 000; hence, the findings are highly significant. Thus, the regression coefficient (b = 0.782, p < 0.000) indicates a significant contribution of countermeasure technology influencing the reduction rate, which amounts to 45 %. 14% of the variance in UAV defense effectiveness gives a coefficient of determination of 0.453. Based on these findings, developing detection and countermeasure technologies are crucial to improving UAV defense systems. The research findings suggest that azimuth and elevation tracking and invariant pattern recognition technologies used in this system can be enhanced to enhance the effectiveness of a UAV countermeasure system.