This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.

In 1859, the French invasion of Gia Dinh marked the beginning of their acquisition of Cochinchina. Shortly after their arrival, France brought printers on their ships, along with firearms and artillery. The printers were intended to quickly disseminate the policies of the invading army to the inhabitants of the occupied territory. At the end of 1861, the inaugural official newspaper in Cochinchina, ‘Le Bulletin officiel de l’expédition française de la Cochinchine’, had been published. The Royal Printing House (l’Imprimerie Impériale), the first printing facility in Cochinchina, was also established at the end of 1861 to accommodate printing tasks, particularly the production of gazettes. In 1873, various private printing houses emerged in Saigon-Cho Lon. Printing and publishing efforts gradually assimilated into the social fabric of Cochinchina after serving as a tool of the invaders. They transformed into political and cultural institutions within colonial society, notably in Saigon-Cho Lon. The progression of these activities during the process was observable, at least for those granted permission to participate. The requirements of the colonial environment and the vitality of the private sector fuelled these new activities, although the colonial authorities deemed it necessary to exert control over them. This article offers additional information on the printing and publishing activities in Saigon-Cho Lon, Vietnam, highlighting the accomplishments of some distinguished printers.

In recent years, e-sports, as an emerging form of competition, has been rapidly integrated into the daily life of college students, and with its rich interactivity, instant feedback and teamwork, e-sports provides them with an effective channel for emotional catharsis and psychological regulation. This study takes students from four universities as the survey object and adopts quantitative research method to analyze the relationship between different types of e-sports activities and psychological stress resistance through questionnaire survey method combined with spss. The samples were randomly sampled, and a total of 500 valid questionnaires were collected. The results of the study show that: 1. In terms of participation, the ability of students to withstand academic stress and life stress is significantly improved, and e-sports is an effective way to regulate emotions and relieve stress; 2. the three types of games (First-person Shooter, Multiplayer Online Battle Arena, Real-Time Strategy Game) have different impacts on stress tolerance, of which FPS has the greatest impact on stress tolerance; 3. the frequency of playing e-sports affects your stress tolerance; 4. teamwork and strategy play an important role in e-sports resilience.

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.

South Africa’s border posts are increasingly becoming crucial hubs for organized crime posing serious national and regional security implications with far-reaching consequences. The country’s national security, economic stability, and community safety are significantly jeopardised by organised criminal enterprises at border posts. As a result, the porous borders of South Africa have fostered an environment that is conducive to a variety of unlawful activities, such as the smuggling of drugs into the country and human trafficking. This paper seeks to identify political, economic, and social factors that lead to organised crime, corruption, and weak border management systems. The paper employed a secondary data analysis of existing scholarly articles, government reports as well as relevant case studies. The study found that local communities are most affected by illegal activities at the ports of entry. The findings further emphasize the importance of inclusive approaches in responding to security challenges that address cross-border flow regulation, fight corruption in service delivery, and promote community resilience. The paper concludes with recommendations for strengthening border controls towards enhancing cooperation between countries and curbing transnational crime networks.

The CO₂  heat pump air conditioning system of new energy vehicle is designed, and the vehicle model of CO₂  heat pump module and heat management system is established based on KULI simulation. The effects of refrigerant charge, running time and compressor speed on the heat pump air conditioning system is studied, and the energy consumption is compared with the PTC heating system and the CO₂ heat pump air conditioning system without waste heat recovery. The results show that the optimal charge for full-service operation is 750 g; increasing the compressor speed can increase the cooling capacity, so that the refrigerant temperature in the passenger compartment and battery inlet can quickly reach the appropriate temperature, but the COP_h, COP_c are reduced by 2.5% and 1.8% respectively. By comparing it with PTC heating and CO₂ heat pump air conditioning systems without waste heat recovery, it is found that the energy consumption of this system is only for the PTC heating systems 42.5%, without waste heat recovery carbon dioxide heat pump air conditioning system of 86.6%. It greatly saves energy, but also increased the waste heat recovery function, so that the system supply air temperature increased by 26%, improve passenger cabin comfort. This  provides a reference for the future experimental research of CO₂ heat pump air conditioning and heat management system.