Water resource management is critical for sustainable agriculture, especially in regions like Kazakhstan that face significant water scarcity challenges. This paper presents the development of a real-time water-level monitoring system designed to optimize water use in agriculture. The system integrates IoT sensors and cloud technologies, and analyzes data on water levels, temperature, humidity, and other environmental parameters. The architecture comprises a data collection layer with solar-powered sensors, a network layer for data transmission, a storage and integration layer for data management, a data processing layer for analysis and forecasting, and a user interface for visualization and interaction. The system was tested at the Left Bypass Canal in Taraz, Kazakhstan, demonstrating its effectiveness in providing real-time data for informed decision-making. The results indicate that the system significantly improves water use efficiency, reduces non-productive losses, and supports sustainable agricultural practices.

A hydraulic drive invariant to reversal loads with a counterbalance valve is developed. The dependencies of static, dynamic, and energy characteristics on the counterbalance valve design parameters are found. The design parameters of the counterbalance valve for a hydraulic drive invariant to reversal loads are optimized.

The dynamic processes of the system of stabilization of the speed of the conveyor belt with a built-in hydraulic drive on the basis of an improved mathematical model, which takes into account the physical phenomena occurring in the hydraulic system during the action of alternating load. The influence of the main parameters of the hydraulic system and the magnitude of the load on the course of dynamic processes is analyzed and recommendations for their selection are formulated. The proposed scheme of the built-in hydraulic drive of a conveyor belt with system of stabilization of speed of movement automatically provides its uninterrupted work. The use of an additional hydraulic pump allowed to stabilize the speed of the conveyor belt to 7.8%, provided that the load on the working link is 2.3 times.

Currently, ontologies are recognized as the most effective means of formalizing and systematizing knowledge and data in scientific subject area (SSA). Practice has shown that using ontology design patterns is effective in developing the ontology of scientific subject areas. This is due to the fact that scientific subject areas ontology, as a rule, contains a large number of typical fragments that are well described by patterns of ontology design. In the paper, we present an approach to ontology engineering of automatic text processing methods based on ontology design patterns. In order to get an ontology that would describe automatic text processing sufficiently fully, it is required to process a large number of scientific publications and information resources containing information from modeling area. It is possible to facilitate and speed up the process of updating ontology with information from such sources by using lexical and syntactic patterns of ontology design. Our ontology of automatic text processing will become the conceptual basis of an intelligent information resource on modern methods of automatic text processing, which will provide systematization of all information on these methods, its integration into a single information space, convenient navigation through it, as well as meaningful access to it.

A new method of successive approximation ADC calibration without interruption of the main conversion process is proposed. The method is based on the use of information redundancy in the form of redundant positional number systems. The method is based on the selection and analysis of unused combinations in the redundant ADC conversion characteristic.

The Working Set concept, originally introduced by P. Denning for memory management, defines a dynamic subset of system elements actively in use. Designed to reduce page faults and prevent thrashing, it has proven effective in optimizing memory performance. This study explores the interdisciplinary potential of the Working Set by applying it to two distinct domains: virtual memory systems and epidemiological modeling. We demonstrate that focusing on the active subset of a system enables optimization in both contexts—minimizing page faults and containing epidemics via dynamic isolation. The effectiveness of this approach is validated through memory access simulations and agent-based epidemic modeling. The advantages of using the Working Set as a general framework for describing the behavior of dynamic systems are discussed, along with its applicability across a wide range of scientific and engineering problems.