The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.

The use of public transport is one of the concepts of sustainable transport. However, people prefer to use private vehicles, which causes various problems, one of which is the high carbon emissions produced. This research aims to encourage programs to use passenger public transportation through a carbon tax. The method in this research is descriptive quantitative with primary data and secondary data. Secondary data was developed in the research by collecting literature study sources on the concept of sustainable transportation development as well as primary data carried out by analyzing calculations regarding the implementation of the carbon tax. There are several proposals that can significantly accelerate the achievement of goals, namely a collaborative approach through collaboration between local government agencies, a policy of progressively implementing a carbon tax as a coercive policy and supported by a program to provide supporting facilities for public transportation. Decision making in this research was carried out by looking at the percentage increase in public transportation use based on the application of a carbon tax or carbon tax.

Political representation is responsible for choices regarding the supply and the management of transport infrastructure, but its decisions are sometimes in conflict with the will and the general interest expressed by citizens. This situation has progressively prompted the use of specific corrective measures in order to obtain socially sustainable decisions, such as the deliberative procedures for the appraisal of public goods. The standard Stated Choice Modelling Technique (SCMT) can be used to estimate the community appreciation for public goods such as transport infrastructure; but the application of the SCMT in its standard form would be inadequate to provide an estimation that expresses the general interest of the affected community. Hence the need to adapt the standard SCMT on the basis of the operational conditions imposed by deliberative appraisal procedures. Therefore, the general aim of the paper is to outline the basic conditions on which a modified SCMT with deliberative procedure can be set up. Firstly, the elements of the standard SCMT on which to make the necessary adjustments are identified; subsequently, modifications and additions to make to the standard technique are indicated; finally, the contents of an extensive program of experimentation are outlined.

The relationship between new-quality productivity and educational equity is characterized by close mutual influence and co-evolution. Driven by technological innovation, new-quality productivity is profoundly transforming the economic and social landscape. Educational equity, a crucial component of social justice, is vital for ensuring equal development opportunities for all individuals. The robust growth of new-quality productivity not only optimizes the distribution of educational resources and enhances educational quality but also poses new challenges and demands for equity in education. In turn, the continuous advancement of educational equity provides a solid talent foundation and a conducive environment for innovation to new-quality productivity. These two aspects intertwine and progress together in various domains, including policy systems, cultural values, and educational practices. This interplay highlights the central role of new-quality productivity and educational equity in societal development, while also demonstrating their dynamic and complementary relationship.

The competencies of public health professionals serve as the cornerstone for curriculum development ensuring that educational programs are pertinent efficient and attuned to the requirements of both the public health workforce and the communities they serve. This study endeavors to investigate the knowledge competency of public health professionals in Thailand with the intention of refining the suitability of knowledge competency for curriculum development tailored to the needs of public health professionals in Thailand. Employing a qualitative study, the study conducted semi-structured interviews with 17 university lecturers in public health programs in Northeastern Thailand. The data collected were transcribed and analyzed using content analysis. The findings elucidate that the lecturers articulated a core knowledge content pertinent to public health professionals in Thailand delineated across five principal themes and thirteen subjects within the public health curriculum. These themes encompassed: 1) Epidemiology and disease prevention (comprising two subjects), 2) Health promotion and community health (comprising four subjects), 3) Research methods in public health and biostatistics (comprising two subjects), 4) Public health administration, health system, and laws (comprising three subjects), and 5) Environmental health and occupational health and safety (comprising two subjects). Subsequently, this study scrutinized five core courses to formulate a model curriculum for public health. The proposed model curriculum is intended for application in both planning and the development of the public health workforce, fostering interdisciplinary learning and nurturing public health professionals rooted in the authentic context of Thailand.