This paper proposes a framework for highlighting the significance of cultural communication in Islamic thought, sociology, and law, areas deeply intertwined with human values. It examines how Islam presents a clear vision and noble conduct in establishing peace values and fostering principles of tolerance among all. Additionally, it explores the potential of virtual communication networks to promote a culture of peace.

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 menace of road traffic accidents (RTAs) has become a major constraint to development in most developing countries because of driving behaviour. This study examines the effects of road users’ education programmes on driving behaviour toward RTA reduction in Nigeria. Data for the study were collected by random sampling of 287 respondents. The respondents comprising road safety officers and drivers were selected at six (6) zonal headquarters of the Federal Road Safety Commission. The questionnaire presented seventeen (17) statements in a 5-point Likert scale for the respondents to rank in order of importance as they have influenced driving behaviour. The data collected were analysed using exploratory factor analysis to identify the most significant effects of road user education on driving behaviour. The study found that road user education programmes have influenced driving behaviour by improving bad driving acts, maintaining good vehicle conditions, and obeying road communication signs. The finding implies that appropriate driving behaviour will reduce road traffic accidents.

The present research focuses on researching the impact of the diverse communication media that facilitate or develop Student Motivation and Engagement in the educational systems of the states in the Gulf, especially Oman. The main goal of this work is to determine which type of method is most effective in encouraging students in view of cultural and technological factors present in the region. Comparisons using hypothesis testing and structural models which provided higher T value for Technology-Based Communication Methods (TBCM) and Human Face-to-Face Communication Methods (HFtFCM). Next, the research hypothesis H2 that TBCM has a direct positive relationship with SMaE was supported by the following regression coefficients: β = 0.177, t = 4.493; p = 0.000. On the other hand, there was no effect of HFtFCM on SMaE as indicated by a regression coefficient of 0.056 (p < 0.124) for this hypothesis and therefore, this hypothesis was rejected. The analysis using the mediator of Student Perception of Communication Effectiveness (SPoCE) only partly mediates TBCM and SMaE (β = 0.047, t = 3.737, p = 0.000). However, SPoCE was found not to moderate the relationship between HFtFCM and SMaE (β = −0.01, t = 1.125, p = 0.005). The present study underlines the efficiency of TBCM in the area of student engagement, while face-to-face conversation does not play significant part in this process. The obtain results conclude that, the traditional and technological evolution in the Gulf region supports the adoption of TBCM in educational systems. Such approaches support with the technological learning and likings of students, offering greater flexibility and engagement. Educational systems must highlight TBCM to better meet the growing needs of their student, while identifying that face-to-face remains important, though secondary, in energetic motivation.

The Malaysian government has been actively strengthening the information and communication industry’s ecosystem through talent retention to realize Malaysia 5.0 and transform the country into a developed human-centered society that balances economic advancement with the resolution of talent problems. This is done to recognize the significance of emerging in building a vibrant and dynamic economy for the country. Few of these studies, however, had developed comprehensive policy recommendations for keeping information specialists in Malaysia’s information businesses. To address this gap, a comprehensive literature review was conducted to understand the factors driving information professionals to leave the sector. The findings aim to inform talent retention strategies that will strengthen the industry’s sustainability and attract skilled leaders, ensuring the information sector’s readiness for a successful digital transition.

As a product of the integration of AI technology and media, the debate surrounding the potential replacement of human anchors by AI anchors has persisted since their inception. This paper conducts a systematic literature review of research on AI anchors in China from 2000 to 2023, grounded in theories of personalization within the field of communication studies. The analysis aims to compare the differences in personalized representation between AI anchors and human anchors, summarizing the advancements, challenges, and future directions of AI anchor communication based on personality. This contribution seeks to enhance the existing knowledge base surrounding AI anchor research.