Evaluating Groundwater Quality Using Multivariate Statistical Analysis and Groundwater Quality Index

Under pressure from surface water pollution and climate change, groundwater becomes a critical water source. Information on groundwater quality could contribute to effective groundwater management. This study was carried out to utilize multivariate statistical analysis and the groundwater quality index (GWQI) to evaluate groundwater quality in Ca Mau Province, Vietnam. Twenty-five groundwater samples from residential-urban areas, cemetery areas, landfill areas, and saline intrusion areas were collected for this study. Groundwater quality was evaluated using the National Technical Regulation on Groundwater Quality (QCVN 09-MT:2015/BTNMT) and GWQI. Principal component analysis (PCA) was used to identify potential polluting sources and key variables influencing groundwater quality. Cluster analysis (CA) was applied to cluster groundwater quality, and the sites were recommended for future monitoring. The results revealed that NH4+-N contaminated groundwater in the landfill area, while the saline intrusion area was polluted by TDS and NH4+-N. The groundwater quality classified as excellent, good, poor, and very poor accounted for 44, 40%, 12%, and 4%, respectively. Cluster analysis divided groundwater quality into four groups, mainly based on the presence of NH4+-N and TDS. Nine groundwater sampling locations could be removed from the current groundwater quality program but still ensuring representativeness as a result of CA. PCA proposed two main sources of variation in groundwater quality at each residential-urban area: the cemetery area, the landfilling area, and the saline intrusion area. The groundwater parameters (i.e., pH, TDS, permanganate index, NH4+-N, NO3--N, and Fe) should be continued to monitor. Domestic and industrial wastewater discharge, leachate from cemeteries and landfills, the nature of groundwater aquifers, and seawater intrusion could be potential sources of groundwater variation. The current findings provide scientific information for local environmental authorities to manage and monitor groundwater quality in the study area. Doi: 10.28991/CEJ-2024-010-03-03 Full Text: PD

Assessing Air Quality Using Multivariate Statistical Approaches

The purpose of the current study was to evaluate air quality in Dong Thap province, Vietnam. The air quality data was collected during 2019–2020, representing the time of pre- and mid-COVID-19. Twenty-seven air quality samples (in the areas of urban, residential-administrative, hospital-schools, and industry-craft village areas) were used for the evaluation. Air quality was evaluated using national technical regulations on air quality, including QCVN 26:2010/BTNMT and QCVN 05:2013/BTNMT. The difference of mean air quality between the areas was examined using a one-way ANOVA followed by the Duncan test at a significant level of 5%. The relationship between air quality parameters and microclimate factors was tested using Pearson correlation. Principal component analysis (PCA) was utilized to identify critical variables and potential sources of air variation. Cluster analysis (CA) was applied to group similar air quality sites, thus recommending air monitoring site selection. The results show that the air quality in the study area is not polluted. The concentrations of noise, TSP, SO2, and NO2in the mid-COVID-19 pandemic were significantly lower than those in the pre-COVID-19 pandemic due to the social distancing policy. There was a close correlation among air quality parameters, except for air humidity. PCA identified two to four potential sources of air variation, explaining 84.3%, 100%, 100% and 89.7% of the total air quality variance at urban, residential–administrative, hospital-schools, and industry-craft villages, respectively. CA divided the 27 sampling sites into eight groups by the differences, mainly in humidity, wind speed noise, TSP, and CO. Eight sampling sites could be potentially reduced from the current monitoring program for representativeness and cost-effectiveness purposes. All air parameters in the current study are significant for monitoring, and the potential sources of air quality variation are traffic activities, industrial production, craft village activities, and daily life using fuels in residential areas. The results of the current study provide useful information for air quality monitoring and management. Future monitoring programs should include toxic air pollutants in air quality monitoring programs. Doi: 10.28991/CEJ-2024-010-02-012 Full Text: PD

Sentiment classification on polarity reviews: an empirical study using rating-based features

We present a new feature type named rating-based feature and evaluate the contribution of this feature to the task of document-level sentiment analysis. We achieve state-of-the-art results on two publicly available standard polarity movie datasets: on the dataset consisting of 2000 reviews produced by Pang and Lee (2004) we obtain an accuracy of 91.6% while it is 89.87% evaluated on the dataset of 50000 reviews created by Maas et al. (2011). We also get a performance at 93.24% on our own dataset consisting of 233600 movie reviews, and we aim to share this dataset for further research in sentiment polarity analysis task

Developing high-quality human resources to meet the requirements of rapid and sustainable development: Realities and solutions

The world is undergoing rapid and transformative changes, with high-quality resources playing a pivotal role in driving significant economic and social advancements. Today, the competition among nations and businesses increasingly revolves around intellectual capacity and the knowledge embedded in products, commodities, and services factors that are underpinned by superior human resources. To achieve both swift and sustainable progress, countries globally are prioritizing the development of human resources, recognizing it as a strategic and pressing necessity amidst the backdrop of global economic integration. For Vietnam, developing high-quality human resources is crucial to enhancing its competitive edge and meeting the demands of the modern digital economy. This article delves into the challenges associated with cultivating high-quality human resources needed for rapid and sustainable development. It also offers solutions to nurture these resources in Vietnam for the near future. Theoretical research is conducted from both United Nations and Vietnamese perspectives within the framework of international economic integration. This research provides both theoretical and practical foundations for advancing high-quality human resources to support sustainable development goals in Vietnam

Real-time Damper Force Estimation for Automotive Suspension: A Generalized H2/LPV Approach

The real-time knowledge of the damper force is of paramount importance in controlling and diagnosing automotive suspension systems. This study presents a generalized H2/LPV observer for damper force estimation of a semi-active electro-rheological (ER) suspension system. First, an extended quarter-car model augmented with the nonlinear and dynamical model of the semi-active suspension system is written into the quasi-LPV formulation. Then, the damper force estimation method is developed through a generalized H2/LPV observer whose objective is to handle the impact of unknown road disturbances and sensor noise on the estimation errors of the state variables thanks to the H2 norm. The measured sprung and unsprung mass accelerations of the quarter-car system are used as inputs for the observer. The proposed approach is simulated with validated model of the 1/5-scaled real vehicle testbed of GIPSA-lab. Simulation results show the performance of the estimation method against unknown disturbances, emphasizing the effectiveness of the damper force estimation in real time

State-ownership and bank risk: A case of Vietnamese commercial banks

The paper aims to verify the impact of state-ownership on banks’ risks at Vietnamese commercial banks. Based on the survey data of 31 commercial banks in Vietnam from 2007 to 2018, the empirical result shows that the state-ownership in the Vietnamese commercial banks has a decrease in the banks’ risks. Besides, the research result is shown that the lower Vietnamese commercial banks’ risks at the previous time lead to the lower ones at present. Furthermore, this evidence contributes to the debate of state-ownership for the Vietnamese commercial banks which gives policy-makers to pay more attention to the efficiency of joint-stock state-ownership

Academic Staffs’ Participation in University Governance Towards Autonomy: Practice at Two University Models in Vietnam

Vietnamese universities are now in a state of “diverse governing bodies” and the Ministry of Education and Training is responsible for their expertise. This model can cause overlapping or loosened management by many agencies simultaneously managing. Vietnamese universities need to promote autonomy and accountability in management. This study was conducted in 2018-2019 with 322 lecturers and educational managers working at two Vietnamese public universities governed by different autonomy policies. This research analyses the academic staff’ s participation in university governance toward autonomy. The research results show that (i) there is no difference between the two universities in the level of participation in governance activities; (ii) The academic staff’ s participation levels are positively correlated from low to moderate levels according to the effectiveness of participating in activities; (iii) The higher the participation level, the higher the scientific research results are for domestic publication. However, it is not a significant case for international publication

Design of an LMI-based Polytopic LQR Cruise Controller for an Autonomous Vehicle towards Riding Comfort

In this paper, we present an LMI-based approach for comfort-oriented cruise control of an autonomous vehicle. First, vehicle longitudinal dynamics and a corresponding parameter-dependent state-space representation are explained and discussed. An LMI-based polytopic LQR controller is then designed for the vehicle speed to track the reference value in the presence of noise and disturbances, where the scheduling parameters are functions of the vehicle mass and the speed itself. An appropriate disturbance force compensation term is also included in the designed controller to provide a smoother response. Then we detail how the reference speed is calculated online, using polynomial functions of the given desired comfort level (quantified by the vertical acceleration absorbed by the human body) and of the road type characterized by road roughness. Finally, time-domain simulations illustrate the method’s effectiveness

Revisiting LARS for Large Batch Training Generalization of Neural Networks

LARS and LAMB have emerged as prominent techniques in Large Batch Learning (LBL), ensuring the stability of AI training. One of the primary challenges in LBL is convergence stability, where the AI agent usually gets trapped into the sharp minimizer. Addressing this challenge, a relatively recent technique, known as warm-up, has been employed. However, warm-up lacks a strong theoretical foundation, leaving the door open for further exploration of more efficacious algorithms. In light of this situation, we conduct empirical experiments to analyze the behaviors of the two most popular optimizers in the LARS family: LARS and LAMB, with and without a warm-up strategy. Our analyses give us a comprehension of the novel LARS, LAMB, and the necessity of a warm-up technique in LBL. Building upon these insights, we propose a novel algorithm called Time Varying LARS (TVLARS), which facilitates robust training in the initial phase without the need for warm-up. Experimental evaluation demonstrates that TVLARS achieves competitive results with LARS and LAMB when warm-up is utilized while surpassing their performance without the warm-up technique