The reference urban plan is an urban planning tool often used to orient the development of Chadian cities. However, expanding Chadian urban centers, such as Sarh, face challenges in implementing urban planning orientations of their urban plans within the set deadlines. The objective of this study is to identify the factors impeding the effective implementation of the reference urban plan for Sarh town. The methodology employed encompasses a literature review, individual interviews with urban planning experts, geographic information system (GIS) data, household surveys and statistical analysis. The results revealed that less than a quarter (19.72%) of the households surveyed were aware of the reference urban plan. The applied logistic regression model identified age, occupation and level of education as the main factors influencing public participation in the preparation of the reference urban plan. On average, 33.33% of the urban planning guidelines and 21.74% of the projected urban projects were implemented, with a difference of 1631.28 hectares (ha) between the projected plan and the actual plan for the town. Five factors were identified as contributing to the failure to implement the reference urban plan for Sarh town, including low funding, inadequate land management, a lack of political will, weak governance and poor communication. Consequently, participatory and inclusive planning approaches, effective financial mobilisation, strong governance, and the use of modern technologies such as GIS tools are recommended to enhance the implementation of urban planning tools.

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.

While some conflict can serve as a more sophisticated stimulus to student achievement, significant or unresolved conflict can delay or even frustrate even the best-planned curriculum. The aim of our study is to get a clear picture of the conflicts with whom and to what extent the international students studying on our campuses have conflicts that affect their performance, and how they can manage them. In our study, based on a questionnaire survey (n = 480), we revealed that the international students at our university have the most conflicts with other foreign students, and the least with Hungarians, including their teachers. On the other hand, we found that according to the Thomas-Kilmann Conflict Instrument, they solve their problems by the Compromising and Accommodating style. The results obtained by detailed socio-demographic aspects show significant differences, mainly between gender, age, and country groups. Knowledge of the revealed facts and connections can offer conscious and careful solutions to understand and reduce tensions, and this can improve the understanding and management of conflict in the classroom, in collaborative projects, and even in non-teaching environments on campuses.

Goat farming plays an important economic role in numerous developing countries, with Africa being a home to a considerable portion of the global goat population. This study examined the socioeconomic determinants affecting goat herd size among smallholder farmers in Lephalale Local Municipality of the Limpopo Province in South Africa. A simple random sampling technique was used to select 61 participants. The socioeconomic characteristics of smallholder goat farmers in Lephalale Local Municipality were identified and described using descriptive statistics on one hand. On the other hand, a Multiple linear regression model was employed to analyse the socioeconomic determinants affecting smallholder goat farmers’ herd sizes. Findings from the Multiple linear regression model highlighted several key determinants, including the age of the farmer, gender of the farmer, education level, and marital status of farmers, along with determinants like distance to the markets, provision of feed supplements, and access to veterinary services. Understanding these determinants is crucial for policymakers and practitioners to develop targeted strategies aimed at promoting sustainable goat farming practices and improving the livelihoods of smallholder farmers in the region.

The article is devoted to formulation of theoretical principles and practical recommendations regarding organization and planning of the investigation of criminal offenses in the field of economic activity, which are committed with the participation (assistance) of law enforcement officers. The methodology for the article is chosen taking into account the purpose and tasks, object and subject matter of the study. The research results were obtained with the help of the following methods: dialectical; formal and logical; formal and legal; comparative and legal; historical and legal, complex analysis; analysis and synthesis; axiomatic; system and structural method. The obtained results of the study indicated that organization and planning of the investigation of criminal acts under consideration is a purposeful activity of the authorized bodies, which is carried out under the guidance of the investigator, detective of the pre-trial investigation body. These activities require systematic, comprehensive approach and must take into account a wide range of circumstances that can affect the process and results of the investigation: the nature of the criminal offense, access to the necessary financial, human and technical resources; the competence of the investigator, the detective; terms and deadlines for investigation and presenting materials to the court, establishing effective cooperation between competent authorities. The study highlights the peculiarities of the organization and planning of the investigation of criminal offenses in economic activities, when law enforcement officers are involved, and suggests directions for improving the effectiveness of their implementation.