This article presents a comprehensive analysis and strategic framework for enhancing social welfare in Kazakhstan through the adoption of international social security standards. This article aims to formulate scientific and practical recommendations for enhancing the legal framework governing Kazakhstan’s social security system. It posits that integrating international social protection standards is pivotal for refining national legislation and charting future developmental courses. Employing a novel methodology, this study analyzes key documents from the International Labour Organization (ILO), the United Nations, the Commonwealth of Independent States (CIS), and the Eurasian Economic Union (EAEU). It also examines efforts to assimilate these international norms into Kazakhstan’s social security laws. The investigation reveals a stagnation in the evolution of the nation’s social sector, marked by a dearth of innovative ideas and initiatives to elevate the subpar social security standards. The adoption of international social standards emerges as a catalyst for rejuvenating the national social sphere, aiming to elevate the Kazakhstani social protection system to meet global benchmarks. This research outlines the pathways for Kazakhstan’s ratification of and accession to key social protection instruments and offers expert recommendations to support this endeavor. The conclusions and recommendations developed are poised for application in legislative reforms, aiming to amend and enhance existing laws to foster a more robust and inclusive social security framework. The findings suggest that the adoption of international social security standards not only contributes to the improvement of individual lives but also fosters social cohesion and economic stability. The article concludes with tailored recommendations for Kazakhstan, highlighting the role of stakeholder engagement, phased implementation, and continuous evaluation in the successful integration of global social security norms. This research contributes to the ongoing discourse on social security reform, offering a valuable perspective for scholars, policymakers, and practitioners involved in social welfare enhancement efforts in Kazakhstan and similar contexts.

This article examines the legal challenges associated with the utilization of marine genetic resources (MGR) at both the national level and beyond national jurisdiction (BBNJ). The legal challenges addressed are as follows: 1) MGR are located across various jurisdictions, encompassing both national and international domains. The analysis starts with an overview of the international regulations that govern the utilization of genetic resources (GR) and their influence on national legislation. It emphasizes the principle of state sovereignty over natural resources while defining MGR and determining ownership; 2) It further highlights the intersection of national and international laws, particularly in transboundary contexts and within Indigenous and Afro-descendant peoples (IADP) territories, analyzing how these regulations are interpreted and applied in such scenarios; 3) The legal challenges related to the use of MGR in international waters are examined. Special emphasis is placed on the recent United Nations (UN) Agreement concerning this issue. This includes an analysis of its impact and specific provisions related to the utilization of MGR, such as the quantity to be collected, the methodology employed, collection sites, among others. The article concludes by asserting that the equitable distribution of benefits from the use of GR should begin at the earliest stages of access to these resources, including project planning and sample collection, rather than being delayed until the patenting and commercialization phases. Early benefit-sharing is essential for promoting fairness and equity in the use of MGR.

This article summarizes the mine safety situation of the Internet of Things, proposes a mine safety system scheme that combines a sense of unity with a sense of isolation, and a sense of mobility with a sense of fixation. It analyzes in detail the feasibility and scientificity of the mine safety system scheme, laying a good foundation for establishing a mine safety system.

Innovation in teaching models is a basic requirement of the Ministry of Education for schools. If a school wants to achieve development, it cannot adhere to traditional rigid teaching models. At the same time, innovating teaching models is also an important requirement for improving education and teaching effectiveness. Through innovation in teaching models, the inherent drawbacks of the current teaching model can be removed and the classroom teaching effect can be better played. The rapidly developing internet era provides unprecedented development opportunities for innovative teaching models. Schools should establish internet learning platforms to encourage students to actively and independently participate in online learning. This paper discusses the classroom teaching model in vocational colleges under the background of "Internet plus", and how it serves our daily teaching activities.

In order to optimize the environmental factors for cucumber growth, a fertilizer and water control system was designed based on the Internet of Things (IoT) system. The IoT system monitors environmental factors such as temperature, light and soil Ec value, and uses image processing to obtain four growth indicators such as cucumber stem height, stem diameter size, number of leaves and number of fruit set to establish a single growth indicator model for temperature, light, soil Ec value and growth stage, and the four growth indicators were fused to obtain the comprehensive growth indicator I_c for cucumber, and calculates its deviation to determine the cucumber growth status. Based on the integrated growth index I_c of cucumber, a soil Ec control model was established to provide the optimal environment and fertilizer ration for cucumber at different growth stages to achieve stable and high yield of cucumber.

The growth of mobile Internet has facilitated access to information by minimizing geographical barriers. For this reason, this paper forecasts the number of users, incomes, and traffic for operators with the most significant penetration in the mobile internet market in Colombia to analyze their market growth. For the forecast, the convolutional neural network (CNN) technique is used, combined with the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit (GRU) techniques. The CNN training data corresponds to the last twelve years. The results currently show a high concentration in the market since a company has a large part of the market; however, the forecasts show a decrease in its users and revenues and the growth of part of the competition. It is also concluded that the technique with the most precision in the forecasts is CNN-GRU.