Optimal control of switched capacitor banks in Vietnam distribution network using integer genetic algorithm

In distribution network, power and energy losses can be reduced by using switched capacitor banks. The capacitor banks can be switched on or off based on voltage profile or power factor or using timers. Due to variation of load, it is necessary to control the capacitor banks switching in function of load curve. This paper presents the application of an integer genetic algorithm to determine the optimal number of banks corresponding with hourly load to minimize total active power losses of distribution feeders. The problem constraints include voltage profile and heat conditions which are taken into account to the objective function by a penalty function. In this application, the structure of chromosomes is a set of numbers of the capacitor banks hourly connected to the grid. The proposed formulation is validated by a feeder. The result shows that in some cases, the active power losses at maximum compensation are greater than the ones of optimal control compensation, and the voltage reaches a higher level than the maximum voltage limit. The optimal control of switched capacitor banks can reduce power and energy losses as well as ensure maximum voltage profile within the limit

CHARACTERISTICS OF QUATERNARY SEDIMENTARY FACIES IN RELATION TO WATER BEARING CAPACITY OF AQUIFERS AND AQUICLUDES IN RED RIVER DELTA, VIETNAM

Joint Research on Environmental Science and Technology for the Eart

THE STATUS OF PARTICIPATION IN EXTRACURRICULAR SPORT TRAINING OF STUDENTS IN SOC TRANG PROVINCE, VIETNAM

The method of sociological investigation is used in the article to survey students' opinions at colleges in Soc Trang province and provided information on the status of participation in extracurricular sports of students at colleges in Soc Trang province by gender, ethnicity and purpose.  Article visualizations

Assessment of High School Students’ Learning and Development of Qualities and Competencies: A Case Study

This study aims to assess high school students' learning outcomes, their achievement of goals and fulfilling academic requirements and how the entire teaching and learning process takes place. The study, consisting of an experimental group and a control group was conducted for pre-test and post-test comparisons of the academic performance of 88 10th grade students. 44 students were selected as the experimental group that underwent a specific teaching strategy to monitor their development of qualities and competencies in one semester, and the remaining 44 students acted as the control group. The data collected after the tests were analyzed using SPSS software (V20). The results showed that the students in the experimental group had better academic results than those in the control group. The findings of this study have implications for policy, further research as well as approaches for the assessment of students’ development of qualities and competencies in Vietnam

Grid search of multilayer perceptron based on the walk-forward validation methodology

Multilayer perceptron neural network is one of the widely used method for load forecasting. There are hyperparameters which can be used to determine the network structure and used to train the multilayer perceptron neural network model. This paper aims to propose a framework for grid search model based on the walk-forward validation methodology. The training process will specify the optimal models which satisfy requirement for minimum of accuracy scores of root mean square error, mean absolute percentage error and mean absolute error. The testing process will evaluate the optimal models along with the other ones. The results indicated that the optimal models have accuracy scores near the minimum values. The US airline passenger and Ho Chi Minh city load demand data were used to verify the accuracy and reliability of the grid search framework

Combining content and social features in a deep learning approach to Vietnamese email prioritization

The email overload problem has been discussed in numerous email-related studies. One of the possible solutions to this problem is email prioritization, which is the act of automatically predicting the importance levels of received emails and sorting the user’s inbox accordingly. Several learning-based methods have been proposed to address the email prioritization problem using content features as well as social features. Although these methods have laid the foundation works in this field of study, the reported performance is far from being practical. Recent works on deep neural networks have achieved good results in various tasks. In this paper, the authors propose a novel email prioritization model which incorporates several deep learning techniques and uses a combination of both content features and social features from email data. This method targets Vietnamese emails and is tested against a self-built Vietnamese email corpus. Conducted experiments explored the effects of different model configurations and compared the effectiveness of the new method to that of a previous work

CHOOSE REMEMBERSHIP REMEDIES TO IMPROVE THE HAPPINESS OF FEMALE OFFICERS AND OFFICERS UNIVERSITY OF FITNESS AND SPORTS DA NANG, VIETNAM

Happiness has long been a veritable area of scientific research in most industrialized countries. Using the method of synthesis of documents and interview method, the study investigates the current state of happiness of 30 female officers and employees of Danang University of Physical Education and Sports using the author's happiness scale. Michael Argyle and Peter Hills (2002) have shown: 30.0% less are happy; 43.33% are happy on average; 26.67% are moderately happy; the most important factor in happiness is health. Subject-selected measures that can increase happiness are finding moments with loved ones in the family; practising more positive thinking; accepting the reality of the situation; join arts and sports clubs

SEASONAL VARIATION OF PHYTOPLANKTON FUNCTIONAL GROUPS IN TUYEN LAM RESERVOIR, CENTRAL HIGHLANDS, VIETNAM

Seasonal changes in freshwater phytoplankton assemblages at Tuyen Lam Reservoir in the Central Highlands of Vietnam were classified into 23 functional groups based on physiological, morphological, and ecological characteristics. A total of 168 species were recorded during 10 surveys from 2015 to 2019 at 7 sampling sites, with Chlorophyta dominating in number of species. Phytoplankton abundance varied from 0.18×105 to 21.2×105 cells/L during the study period, mainly due to cyanobacteria. Seven of the 23 functional groups were considered to be dominant (relative density > 5%).  The dominant functional groups were groups M and G in the dry season and groups M, G, P, and E in the rainy season. Group M (Microcystis aeruginosa) was the most common in both seasons, while group P (Closterium, Staurastrum, Aulacoseira), group E (Dinobryon, Synura), and group G (Sphaerocystis, Eudorina) were more common in the rainy season. The Shannon diversity index (H¢) showed that phytoplankton communities were relatively diverse and that most of the study sites were lightly polluted. However, the ecological status has deteriorated at some locations due to the overgrowth of group M, leading to eutrophication in this reservoir. This study highlights the usefulness of functional groups in the study of seasonal changes in phytoplankton dynamics. Functional groups are applied for the first time at Tuyen Lam Reservoir and can be used to predict early-stage cyanobacterial blooms in future studies

EVALUATION OF THE VULNERABILITY OF THE COASTAL SOCIO-NATURAL SYSTEMS (EXAMPLE FROM KHANH HOA COASTAL ZONE)

Joint Research on Environmental Science and Technology for the Eart