This study sought an innovative quality management framework for Chinese Prefabricated Buildings (PB) projects. The framework combines TQM, QSP, Reconstruction Engineering, Six Sigma (6Σ), Quality Cost Management, and Quality Diagnosis Theories. A quantitative assessment of a representative sample of Chinese PB projects and advanced statistical analysis using Structural Equation Modeling supported the framework, indicating an excellent model fit (CFI = 0.92, TLI = 0.90, RMSEA = 0.06). The study significantly advances quality management and industrialized building techniques, but it also emphasizes the necessity for ongoing research, innovation, and information exchange to address the changing problems and opportunities in this dynamic area. In addition, this study’s findings and recommendations can help construction stakeholders improve quality performance, reduce construction workload and cost, minimize defects, boost customer satisfaction, boost productivity and efficiency in PB projects, and boost the Chinese construction industry’s growth and competitiveness.

The aim of this paper is to develop a methodology for determining the size of the unified land tax in agriculture based on the results of the economic assessment of agricultural land to form the foundation of a new effective system of macroeconomic instruments for state regulation of the innovative development of the agro-industrial complex of the Republic of Kazakhstan. There were used gatherings of facts and summaries, induction and deduction, analysis and synthesis, historical and logical, normative, comparison, index and modeling methods in the research. The article provides an overview of various scholarly perspectives on the challenges and strategies for improving the tax system. The base rates of the unified land tax per hectare of arable land have been calculated to establish equal conditions for all land users. This unified land tax rate is expected to encourage the efficient utilization of land resources and enable the optimization of production structure. The article addresses avenues for improving water management relations in agriculture, aimed at fostering a shared interest and creating incentives for adopting innovative technologies in both agriculture and the water management sector. An essential condition for achieving the effective functioning of Kazakhstan’s agro-industrial complex is its transformation to an innovative development model. This necessitates the development and application of a new system of macroeconomic tools for its implementation, aimed at creating a favorable environment for entrepreneurial development.

The proposed research work encompasses implications for infrastructure particularly the cybersecurity as an essential in soft infrastructure, and policy making particularly on secure access management of infrastructure governance. In this study, we introduce a novel parameter focusing on the timestamp duration of password entry, enhancing the algorithm titled EPSBalgorithmv01 with seven parameters. The proposed parameter incorporates an analysis of the historical time spent by users entering their passwords, employing ARIMA for processing. To assess the efficacy of the updated algorithm, we developed a simulator and employed a multi-experimental approach. The evaluation utilized a test dataset comprising 617 authentic records from 111 individuals within a selected company spanning from 2017 to 2022. Our findings reveal significant advancements in EPSBalgorithmv01 compared to its predecessor namely EPSBalgorithmv00. While EPSBalgorithmv00 struggled with a recognition rate of 28.00% and a precision of 71.171, EPSBalgorithmv01 exhibited a recognition rate of 17% with a precision of 82.882%. Despite a decrease in recognition rate, EPSBalgorithmv01 demonstrates a notable improvement of approximately 14% over EPSBalgorithmv00.

Praxeology is the study of practice, i.e., human activity, primarily in the context of its rationality. The study of manager’s praxeological activity from the point of view of management theory is an important direction of modern science, since it contributes not only to improving the management effectiveness in an organization, but also to the development of new managerial concepts and techniques. In the article, the authors’ concept of praxeological managerial activity is proposed based on the analysis of existing scientific approaches to praxeology. An extended list of criteria for the manager’s praxeological activity efficiency was developed. These criteria include performance, productivity, accuracy of the decisions taken, purposefulness, reliability, innovativeness, quality, and ethics. The authors’ model of the manager’s praxeological activity includes the following elements: a subject (a manager), an object (a company, its staff and activities, etc.), motives (success, growth, profit, etc.), the goal (to ensure the effectiveness of the company’s activities), methods and tools (analysis, planning, organization, motivation, and control), process (praxeological activity), result (efficiency improvement), and reflexivity, correction and iteration. Within the framework of the model of praxeological managerial activity, the manager’s ability to influence the managed object (an organization, employees or the manager’s activities) is particularized. This influence should result in an increase in the employees’ performance, an increase in the managers’ performance, and an increase in the performance of the organization as a whole. The article will be of interest to specialists in the field of management, and corporate governance, as well as for anyone interested in the problems of effective management.

The COVID-19 pandemic has significantly restricted household resilience, particularly in developing countries. The study investigates the correlation between livelihood capital and household resilience amid uncertainties due to the COVID-19 pandemic, specifically in Bekasi Regency, West Java Province, Indonesia. Livelihood capital encompasses social, human, natural, physical, and financial, which are crucial in shaping household resilience. This study used the SEM-PLS method and utilized a survey of 120 respondents (household heads) from four villages in two districts (Muaragembong and South Tambun) in Bekasi Regency to identify critical factors that either enhance or impede rural household resilience during and after the pandemic. Findings reveal that households possessing human capital, financial capital, and empowerment are more adept at navigating socioeconomic difficulties during and after the pandemic. However, this research stated that trust and social networks enhance household resilience during the pandemic, whereas social norms are crucial for rebuilding household resilience in the post-pandemic phase. The finding revealed that social cohesion adversely affected household resilience during and after the pandemic, while trust diminished household resilience in the post-pandemic COVID-19 phase. These findings offer insight to policymakers, scholars, and other stakeholders aiming to foster household resilience during and in recovery efforts after the pandemic.

The usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.