Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.

The livelihood of ethnic minority households in Vietnam is mainly in the fields of agriculture and forestry. The percentage of ethnic minorities who have jobs in industry, construction, and services is still limited. Moreover, due to harsh climate conditions, limited resources, poor market access, low education level, lack of investment capital for production, and inadequate policies, job opportunities in the off-farm and non-farm activities are very limited among ethnic minority areas. This paper assessed the contribution of livelihood diversification activities to poverty reduction of ethnic minority households in Son La Province of Vietnam. The analysis was based on the data using three stages sampling procedure of 240 ethnic minority households in Son La Province. The finding showed that the livelihood diversification activities had positively significant contribution to poverty reduction of ethnic minority households in Son La Province. In addition, the factors positively affecting the livelihood choices of ethnic minority households in Son La Province of Vietnam are education level, labor size, access to credit, membership of associations, support policies, vocational training, and district. Thus, improving ethnic minority householder’s knowledge through formal educational and training, expanding availability of accessible infrastructure, and enhancing participation of social/political associations were recommended as possible policy interventions to diversify livelihood activities so as to mitigate the level of poverty in the study area.

The new oil derivatives transportation scheme proposed by the 2013 Mexican Energy Reform allowed new participants to enter the sector. The new legal framework requires fulfilling many requirements and corresponding duties for the transportation of oil products. The Mexican government already has an institution dedicated to measuring the regulatory cost of each federal procedure. This work aims to quantify the regulatory costs associated with the procedures and their compliance to obtain permits for transporting oil products by truck. We use the standard cost method to measure these costs, considering all associated costs. The results showed that two government offices did not adequately measure these costs. They did not consider relevant information on frequency and opportunity costs, resulting in undervaluation and leading to wrong expectations. As a result of this research, we provide a more accurate way of estimating these costs, which brings greater certainty in the budgeting of these projects and, therefore, increases the probability of survival and success.

This research was conducted using a survey research method to investigate the influence of Artificial Intelligence (AI) on Nigerian students’ academic performances in tertiary institutions. Nigerian tertiary institutions have an estimated population of about 2.5 million students across the universities, polytechnics, monotechnics, and colleges of education. A sample size of 509 was used. The researchers adopted an online questionnaire (Google Form) to administer questions to respondents across Nigeria to elicit responses from the respondents bordering on their awareness and the use of AI and its attendant impacts on their academic performance. Five research objectives were raised for the proper investigation of this study. From the findings of the study, the researchers found that the majority of Nigerian students use AI and that AI has positive impacts on the educational performance of Nigerian students. It was also found that Nigerian students have training on the use of AI for educational purposes and that they are more familiar with Snapchat AI and ChatGPT. Conclusively, AI is useful to students in the sense that it enhances their knowledge of their courses, improves their learning and speaking skills, and helps them to have a quick understanding of their course by way of simplifying technical aspects of their courses. The researchers therefore recommend as follows: Nigerian tertiary institutions should formally train students as well as teachers on the use of AI for academic purposes so that they can understand the ethical implications of the use of AI. Using AI for writing could be interpreted to mean examination malpractice, and this should not be condoned in the educational sector; however, at the moment, a small number of students used AI for examinations. Albeit, the appropriate use of AI should be fully integrated into Nigerian tertiary institutions’ curricula.

The allocation of funds in the local budget is a matter of concern for the governments and economic scholars. The study examines the influence of local budget expenditures on the GRDP per capita of 63 provinces and municipalities in Vietnam from 2018 to 2022. Regression analysis of panel data reveals that capital expenditure has a positive correlation with local GRDP per capita, whereas current expenditure has a negative correlation with GRDP per capita. Furthermore, the analysis indicates that the percentage of individuals aged 15 and above who are employed and the percentage of urban citizens have an equivalent influence as the GRDP per capita. Conversely, the average age and local Gini coefficient have contrasting effects on GRDP per capita. The author suggests several policy alternatives to assist localities in boosting their GRDP per capita based on the findings of the study model.

This study proposes a fuzzy analytic hierarchy process (FAHP) method to support strategic decision-makers in choosing a project management research agenda. The analytical hierarchy process (AHP) model is the basic tool used in this study. It is a mathematical tool for evaluating decisions with multiple alternatives by decomposing them into successive levels according to their degree of importance. The Sustainable Development Goals (SDG) oriented theme of project management was chosen from among four themes that emerged from a strategic monitoring study. The FAHP method is an effective decision-making tool for multiple aspects of project management. It eliminates subjectivity and produces decisions based on consistent judgment.