Trends in socioeconomic inequalities in full vaccination coverage among vietnamese children aged 12–23 months, 2000–2014: Evidence for mitigating disparities in vaccination

There has been no report on the situation of socioeconomic inequalities in the full vaccination coverage among Vietnamese children. This study aims to assess the trends and changes in the socioeconomic inequalities in the full vaccination coverage among Vietnamese children aged 12–23 months from 2000 to 2014. Data were drawn from Multiple Indicator Cluster Surveys (2000, 2006, 2011, and 2014). Concentration index (CCI) and concentration curve (CC) were applied to quantify the degree of the socioeconomic inequalities in full immunization coverage. The prevalence of children fully receiving recommended vaccines was significantly improved during 2000–2014, yet, was still not being covered. The total CCI of full vaccination coverage gradually decreased from 2000 to 2014 (CCI: from 0.241 to 0.009). The CC increasingly became close to the equality line through the survey period, indicating the increasingly narrow gap in child full immunization amongst the poor and the rich. Vietnam witnessed a sharp decrease in socioeconomic inequality in the full vaccination coverage for over a decade. The next policies towards children from vulnerable populations (ethnic minority groups, living in rural areas, and having a mother with low education) belonging to lower socioeconomic groups may mitigate socioeconomic inequalities in full vaccination coverage. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Huy Nguyen” is provided in this record*

ASSESSMENT OF THE CURRENT SITUATION OF TOURISM DEVELOPMENT IN MANG DEN TOWN, KON PLONG DISTRICT, KON TUM PROVINCE, VIETNAM

This study surveyed 120 domestic tourists in Mang Den Town, using the convenience sampling method. The method used to analyze primary data was descriptive statistics. The research results have proposed six factors to evaluate the current situation of tourism development in Mang Den Town, Kon Plong District, Kon Tum Province, Vietnam including: (1) Quality of tourism services and tourism resources; (2) Perceived prices; (3) Human resources; (4) Security, order, and safety; (5) Quality of tourism services and tourism infrastructure; (6) and Tourism resources and perceived prices, in which "Human resources" is the factor that has the strongest impact on the current situations of tourism development in Mang Den Town. Through research results, the article has proposed some solutions to develop tourism in Mang Den Town more effectively in the future.  Article visualizations

Load Shedding in Microgrid System with Combination of AHP Algorithm and Hybrid ANN-ACO Algorithm

This paper proposes a new load shedding method based on the application of intelligent algorithms, the process of calculating and load shedding is carried out in two stages. Stage-1 uses a backpropagation neural network to classify faults in the system, thereby determining whether or not to shed the load in that particular case. Stage-2 uses an artificial neural network combined with an ant colony algorithm (ANN-ACO) to determine a load shedding strategy. The AHP algorithm is applied to propose load shedding strategies based on ranking the importance of loads in the system. The proposed method in the article helps to solve the integrated problem of load shedding, classifying the fault to determine whether or not to shedding the load and proposing a correct strategy for shedding the load. The IEEE 25-bus 8-generator power system is used to simulate and test the effectiveness of the proposed method, the results show that the frequency of recovery is good in the allowable range

Ranking load in microgrid based on fuzzy analytic hierarchy process and technique for order of preference by similarity to ideal solution algorithm for load shedding problem

This paper proposes a method to rank the loads in the microgrid by means of a weight that combines the criteria together in terms of both technical and economic aspects. The fuzzy analytic hierarchy process technique for order of preference by similarity to ideal solution (fuzzy AHP TOPSIS) algorithm is used to calculate this combined weight. The criteria to be considered are load importance factor (LIF), voltage electrical distance (VED) and voltage sensitivity index (VSI). The fuzzy algorithm helps to fuzzy the judgment matrix of the analytic hierarchy process (AHP) method, making it easier to compare objects with each other and remove the uncertainty of the AHP method. The technique for order of preference by similarity to ideal solution (TOPSIS) algorithm is used to normalize the decision matrix, determine the positive and negative ideal solutions to calculate the index of proximity to the ideal solution, and finally rank all the alternatives. The combination of fuzzy AHP and TOPSIS algorithms is the optimal combination for decision making and ranking problems in a multi-criteria environment. The 19-bus microgrid system is applied to calculate and demonstrate the effectiveness of the proposed method

AdamOptimizer for the optimisation of Use Case Points estimation

Use Case Points is considered to be one of the most popular methods to estimate the size of a developed software project. Many approaches have been proposed to optimise Use Case Points. The Algorithmic Optimisation Method uses the Multiple Least Squares method to improve the accuracy of Use Case Points by finding optimal coefficient regressions, based on the historical data. This paper aims to propose a new approach to optimise the Use Case Points method based on Gradient Descent with the support of the TensorFlow package. The significance of its purpose is to conduct a new approach that might lead to more accurate prediction than that of the Use Case Points and the Algorithmic Optimisation Method. As a result, this new approach outweighs both the Use Case Points and the Algorithmic Optimisation Methods. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

An evaluation of technical and environmental complexity factors for improving use case points estimation

This paper presents a proposed method for improving the prediction ability of the Use Case Points method. Our main goal is to use the Least Absolute Shrinkage and Selection Operator Regression methods to find out which of the technical and environmental complexity factors significantly affect the accuracy of the Use Case Points method. Two regression models were used to calculate the selected significant variables. The results of several evaluation measures show that the proposed estimation method ability is better than the original Use Case Points method. The Sum of Squared Error of the proposed method is better than the results obtained by the original one. The study also enables project managers to understand how to assess the technical and environmental complexity factors better - since they do have an important impact on effort estimation. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

A SURVEY OF STUDENTS’ ABILITY OF IDENTIFYING ERRORS IN WRONG SOLUTIONS FOR THE MATHEMATICAL PROBLEMS RELATED TO THE MONOTONICITY OF FUNCTIONS

The monotonicity of a function plays an important role in the general mathematics curriculum in Vietnam, because it is considered as an effective tool for solving mathematical problems involved with the monotonic intervals of functions, their extreme, absolute maximum value and absolute minimum value. Normally, students commit errors in solving these problems because of their complexity and difficulty. In addition, specific characteristics of knowledge also make children make mistakes. The sample consisted of 362 students, and they had the task of identifying errors in false assumptions. From the results of the survey, it was found that when dealing with the monotonicity of the functions, students were still misled.  Article visualizations

ASSESSING THE SATISFACTION OF DOMESTIC TOURISTS WITH ECO-TOURISM DEVELOPMENT IN MANG DEN TOWN, KON PLONG DISTRICT, KON TUM PROVINCE, VIETNAM

Mang Den town, Kon Plong District, the Central Province of Kon Tum is one of the destinations of recent interest. With the advantage of the climate and unique high mountain ecosystem, eco-tourism development is one of the notable trends in Mang Den. Based on a survey of 130 domestic tourists to Mang Den, the study used SPSS software 20 to analyze domestic tourists' satisfaction with eco-tourism development in Mang Den. The findings of this research demonstrated the potential of ecotourism Mang Den Town as a destination for Vietnamese tourists seeking natural beauty, cultural experiences, and adventure activities. The positive satisfaction levels indicated that efforts have been made to provide a quality tourism experience. However, there is still room for improvement, particularly in infrastructure development and providing more interpretive and accommodation options. These results can guide tourism stakeholders in developing strategies to enhance ecotourism in Mang Den Town, as a Good Practice and ensure sustainable tourism growth in the Kon Plong District, Kon Tum Province.  Article visualizations

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions