This research presents an intelligent control algorithm to improve the energy efficiency of parallel centrifugal pumping systems, widely used in industrial and municipal applications. Parallel pumping systems are vital for handling variable flow demands and ensuring operational reliability. However, conventional control methods often lead to energy inefficiencies due to suboptimal operation and static control mechanisms.

The study begins by modeling the dynamics of parallel pumping systems, considering parameters such as flow rate, head, and energy consumption. Using pump performance curves and affinity laws, the proposed control algorithm dynamically adjusts pump operations based on real-time demand, ensuring optimal energy efficiency. Unlike traditional methods, the algorithm eliminates the need for startup measurements and integrates adaptive staging and de-staging techniques. Experimental results show that the intelligent control algorithm improves energy efficiency by 15% compared to traditional methods.

The methodology includes simulation and experimental validation. MATLAB/Simulink simulations verify the algorithm's effectiveness under varying operational conditions, while a prototype system with DSP-based VFD controllers demonstrates its practical applicability. The results indicate significant energy savings, enhanced operational stability, and reduced wear and tear compared to conventional methods.

The proposed approach offers scalability and adaptability, making it suitable for diverse applications such as power generation, wastewater treatment, and industrial processes. This work contributes to the development of sustainable and energy-efficient solutions for industrial systems.

Water is a critical resource in industrial operations, essential for various processes ranging from manufacturing to power generation. However, unsustainable water use by industries poses significant challenges, including water scarcity, pollution, and increased operational costs. This article explores the current state of water management in industry, identifies key issues, and proposes solutions for improving efficiency and sustainability. The methodology includes a comprehensive literature review of water management practices, analysis of successful case studies, and synthesis of recommendations from industry experts. Data on water consumption, pollution levels, and industry practices are sourced from authoritative publications, academic journals, industry reports, and government sources.

This article provides proposals for the organization of work on forecasting tax revenues for the formation of the state budget and the introduction of a wide range of methods for forecasting tax revenues in order to improve existing innovative approaches to determining the needs of expenditures in the budget and the main aspects of equalization programs, improving the efficiency of public finance management.

Signaling systems are the foundation of a modern telecommunications network supporting call setup, control, routing and overall network management functions. In the transition of telecommunications networks from traditional analog switching to digital based and IP based networks, signaling mechanisms have also transitioned from channel associated signalling (CAS) styles to the more efficient common channel signalling (CCS) systems. This paper discusses the architecture, operation, and evolution of main signaling systems, such as R2, SS7, SIP, and Diameter signalling systems. It highlights interoperability and latencies, along with security challenges, along with modern signalling applicability for next generation networks, such as LTE, VoIP, and 5G Core. The discussion also shows that signalling efficiency has a direct effect on service quality, scalability, and reliability of the network.

The rapid growth of web-based education has intensified the need for personalized learning approaches capable of addressing individual differences among learners. Traditional PHP-based educational systems often rely on static learning structures that fail to adapt to students’ varying abilities, learning pace, and preferences. This limitation reduces learning effectiveness and learner engagement. In response to this challenge, artificial intelligence (AI) offers new opportunities for designing adaptive and personalized learning environments. This article proposes an AI-driven framework for generating personalized learning paths within PHP-based educational systems. The approach leverages learner activity data, assessment results, and interaction patterns to dynamically recommend educational content tailored to individual needs. Machine learning techniques are conceptually integrated into the PHP architecture to analyze learner behavior and adjust learning sequences accordingly. The proposed system architecture demonstrates how AI components can be embedded into existing PHP platforms without requiring a complete system redesign. The results indicate that AI-driven personalization can significantly enhance learner engagement and learning efficiency by providing adaptive content recommendations and individualized learning trajectories. The findings highlight the practical potential of combining PHP web technologies with artificial intelligence to develop intelligent educational systems. This research contributes to the field of educational technology by presenting a scalable and adaptable model for personalized learning path generation in PHP-based environments.

The Solar Energy is produced by the Sunlight is a non-vanishing renewable source of energy which is free from eco-friendly. Every hour enough sunlight energy reaches the earth to meet the world’s energy demand for a whole year. In today’s generation we needed Electricity every hour. This Solar Energy is generated by as per applications like industrial, commercial, and  residential. It cans easily energy  drawn from  direct sunlight.  So it  is very  efficiency &  free environment  pollution for surrounding. In this article, we have reviewed about the Solar Energy from Sunlight and discussed about their future trends and aspects.  The article  also  tries to  discussed  working,  solar panel  types;  emphasize  the various  applications  and methods  to promote the benefits of solar energy

Lithium-ion batteries have become a crucial factor in the widespread adoption of electric vehicles, thanks to their high energy density and seamless integration with powertrain systems. However, their performance is highly dependent on operating temperature, necessitating an efficient thermal management system to ensure optimal efficiency, safety, cost-effectiveness, and longevity, particularly in high-capacity Li-ion batteries. This review provides a comprehensive analysis of heat generation mechanisms and thermal modeling in lithium-ion batteries, along with various thermal management systems. It examines the impact of extreme conditions on battery performance, including thermal runaway and aging. Ultimately, it aims to establish a comprehensive framework for future research and development in battery thermal management systems.

In this article, a study was made of the possibility of creating and using a stable conducting channel in a dielectric liquid under the influence of laser radiation

The article discusses household waste management within the framework of implementing the “Green Economy” in the Republic of Kazakhstan. Improving the efficiency of household waste management is a pressing issue both for the entire Republic of Kazakhstan and the West Kazakhstan region. Currently, Kazakhstan lacks a systematic approach to separate waste collection at the “source” of generation. Therefore, a comprehensive economic analysis is being conducted across the country to develop systems for waste separation, separate disposal, recycling, and resale. Household waste recycling, especially the reuse of waste cooking oil, is an urgent problem. This study proposes the idea of producing environmentally friendly soap by reusing waste cooking oil.

This article provides proposals for the organization of work on forecasting tax revenues for the formation of the state budget and the introduction of a wide range of methods for forecasting tax revenues in order to improve existing innovative approaches to determining the needs of expenditures in the budget and the main aspects of equalization programs, improving the efficiency of public finance management.

The present work deals with the socio-economic efficiency of the development of transport service in the Qashqadaryo region of Uzbekistan in 2024-2025 from the regional model perspective. The study shows the importance of transport for economic performance, social accessibility and institutional reform in a transitional setting. Evidence is found that investment in transport services brought about tangible gains in employment generation, access to rural areas, and contribution to the regional GDP from the transport sector. The growing use of information and communications technology in the region, the increasing involvement of the private sector in these sectors, and the emergence of new public sector investment in these areas can further illustrate that regional efforts are increasingly oriented toward national modernisation.