In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

The current examines the influence of Islamic values on smoking behaviors among undergraduate students at Yarmouk University in Irbid, Jordan (N: 334). Tobacco use, in religious and cultural terms, is viewed as abhorrent; it is a significant concern for this population group. The study intends to identify how Islamic values affect the perception of students on smoking and, consequently, their smoking behavior. A self-administered questionnaire assessed sociodemographic data and the past 30 days of cigarette use. Descriptive statistics, such as frequencies and percentages, midpoint and standard deviation, and inferential statistics, such as chi-square tests, t-tests, ANOVA, Pearson correlation, and hierarchical regression, were used to analyze smoking behaviors, Islamic values, and demographic attributes. The study shows that Islamic values have a strong negative attitude towards smoking; students attributed smoking to religion, family and social expectations and perceptions, health and economic implications. Further, the hierarchical regression analysis revealed that cigarette use, hookah and e-cigarette, gender, and attitude towards Islamic values were suitable predictors for cigarette use. This study advances knowledge regarding smoking behaviors from the cultural-religious perspective. It highlights the importance of historically and culturally informed gender-sensitive prevention programs that address smoking-related beliefs, attitudes, and practices. Collaboration with the Ministry of Health and media outlets to integrate Islamic values into public health campaigns can reduce smoking among university students by aligning cultural and religious beliefs with health messaging.

This study aimed at measuring the level of job burnout among King Khalid University staff. The descriptive-analytical approach was employed to describe job burnout, determine its prevalence, identify its causes, and propose ways to address it. This method was used for comparison, interpretation, and generating information to assist in understanding the phenomena of job burnout and to devise recommendations for mitigating its prevalence. The results showed that the overall mean estimation of the dimensions of the level of occupational burnout from the perspective of university staff was (2.28), with a standard deviation of (0.81), indicating a low degree. The arithmetic means of the study sample responses to the dimensions ranged from (1.98–2.66). This provides a good indicator of the prevalence of occupational burnout. The findings showed that individuals in higher ranks experience higher levels of job burnout compared to the rest of the ranks classified in the study.

Gender inequality is a structural social problem, associated with history, culture, education, religion and politics, this difficulty occurs in all social institutions due to the heterogeneity of the structure in the sexual division of labor, socioeconomic inequality, inclusion and inequity in participation in the public space between men and women. Public policies and attitudes towards gender equality in Peruvian university students were analyzed according to socio-academic variables. A descriptive-comparative study, with a quantitative approach, and not experimental cross-sectional, involved 776 university students from a public and a private university in Peru, intentionally selected. Adaptive attitudes (57.9%) were found to tend to be sexist; Likewise, in the study dimensions, the same trend was found in the sociocultural and relational levels, while in the personal dimension students develop sexist attitudes (62.4%). It is concluded, attitudes towards gender equality are sexist reproduction that is influenced by the sociocultural environment of the family, this situation occurs to a greater extent in men, while female students present attitudes of equality in greater intensity to seek equity in the distribution of roles.

The scientific discourse on university towns (UT) has progressed for a long time, with a surge of interest in recent years. However, a global overview of the research conducted on this topic have yet to exist. This paper aims to re-examine the relationship between UT and urbanization in literature. Built environment and people are often the most talked aspects in UT literatures. The variety of definitions remains largely uncharted. Policies behind UT development are also rarely studied. This article used an R studio-based bibliometric literature review to synthesize findings from various scientific literature. Keywords related to university towns and urban were used in digital search engines to examine and analyse the literature. Results revealed a significant gap in scientific research on critical theoretical concepts that planners can use as a guide in creating, formulating, and evaluating UT, especially in developing countries. This study promotes simplification of existing literature by examining the impact of UT on the stakeholders involved.