Online Programming Judge System (UOJ)

This research conducts a study to build an Online Programming Judge system with a mechanism to generate test cases automatically using Particle Swarm Optimization (PSO) algorithm. The system has the function to judge programming code by evaluating the output that the program produced. Based on the problem that it is time consuming for lecturers to manually compile, run and verify every student programs for judging. Moreover, they also need to define test cases for different programming exercises in order to judge student‘s code. The system is built on the purpose to assist lecturers in Universiti Teknologi PETRONAS in judging code submitted from students and generate test cases for every programming exercise automatically. It also helps UTP students practice and enhancing their programming skills. In this research, details of judging process are explored. Moreover, the mechanism of test cases generation using PSO algorithm is deeply analyzed. The study would focus on the primary structure of PSO and the proposed fitness function to calculate fitness value for each generated test case. There are comparisons between manual and automatic PSO test case generation results that would be conducted to evaluate the efficiency of the proposed method. Finally, conclusion of current results and recommendation for future development are also stated

Online Programming Judge System (UOJ)

This research conducts a study to build an Online Programming Judge system with a mechanism to generate test cases automatically using Particle Swarm Optimization (PSO) algorithm. The system has the function to judge programming code by evaluating the output that the program produced. Based on the problem that it is time consuming for lecturers to manually compile, run and verify every student programs for judging. Moreover, they also need to define test cases for different programming exercises in order to judge student‘s code. The system is built on the purpose to assist lecturers in Universiti Teknologi PETRONAS in judging code submitted from students and generate test cases for every programming exercise automatically. It also helps UTP students practice and enhancing their programming skills. In this research, details of judging process are explored. Moreover, the mechanism of test cases generation using PSO algorithm is deeply analyzed. The study would focus on the primary structure of PSO and the proposed fitness function to calculate fitness value for each generated test case. There are comparisons between manual and automatic PSO test case generation results that would be conducted to evaluate the efficiency of the proposed method. Finally, conclusion of current results and recommendation for future development are also stated

Rural investment climate and business activities of agro-enterprise: Evidence from northern area of Vietnam

2013東京農業大

Income diversification and poverty in the Northern Uplands of Vietnam:

Poverty, income diversification,

A cross-sectional study of the antibiotic resistant prevalence of ESBL-producing Enterobacteriaceae in Vietnam

Introduction: Antibiotic resistance in Enterobacteriaceae producing extended spectrum beta-lactamase (ESBL) is increasing. Accurate evaluation of antibiotic resistance rates in various categories of bacteria assists medical physicians in recommending suitable indications for their medical problems, improving treatment efficiency, and minimizing dangers for patients. As a result, we undertook this research to assess the prevalence of ESBL-producing Enterobacteriaceae as well as the rate of antibiotic resistance in ESBL-producing Enterobacteriaceae. Methods: A cross-sectional study was conducted on 2716 patients at the An Giang Central General Hospital from June 2020 to June 2021. Data collection was based on interviews and used SPSS 18.0 and GraphPad Prism 9 for data analysis and presentation. Samples included urine, blood, sputum, and pus. Samples were treated with the Phoenix 100 automated machine to separate and identify samples. Results: The highest rate was 64.8% for Escherichia coli, followed by 30.2% for Klebsiella pneumoniae. Proteus mirabilis and Klebsiella oxytoca were found in 4.5% and 0.6% of the samples, respectively. Ampicillin resistance was greatest in E. coli (96.5%), K. pneumonia (92.4%), and K oxytoca (83.3%). The frequency of resistance to the other antibiotics was likewise extremely high, approaching 60%. Tobramycin, Amoxicillin/Clavulanate, Cefoxitin, and Nitrofurantoin were totally resistant to K. oxytoca in the ESBL-producing group. E. coli and K. pneumoniae with ESBL-producing genes also have a high antibiotic resistance rate of more than 50%. Conclusion: E. coli was the most common pathogenic bacteria. Most of the species of bacteria resisted Ampicillin