SURVEYING THE VIETNAMESE YOUTH ON THE NEGATIVE IMPACT OF SOCIAL MEDIA

In the context of globalization and the rapid development of the Internet, social networks have become an indispensable part of the lives of citizens in the 21st century. In addition to helping people communicate and connect, wireless platforms bring benefits to work, study, and entertainment. However, faced with the staggering increase in the use of social networks, many argue that they can have negative impacts on users, particularly those who are studying or working. This study aims to provide readers with an overview of the negative impacts of social networks on Vietnamese youth. The research data was collected by gathering reputable sources and surveying young people born between 1995 and 2010, belonging to Generation Z, who are living, studying, and working in major cities in Vietnam and using social networks. Through statistical analysis and data processing, the results show that the use of communication platforms has a negative impact on the productivity and health of Vietnamese youth. To minimize the negative impacts on daily life, young people should consider the amount of time they spend using social networks and the content they publish. Additionally, protecting personal information and building positive communities is necessary to avoid unnecessary risks

Research on the stability of the 3D frame on coral foundation subjected to impact load

This article presents an application of the finite element method (FEM) for the stability analysis of 3D frame (space bar system) on the coral foundation impacted by collision impulse. One-way joints between the rod and the coral foundation are described by the contact element. Numerical analysis shows the effect of some factors on the stability of the bar system on coral foundation. The results of this study can be used for stability analysis of the bar system on coral foundation subjected to sea wave load

VULNERABLITY OF RURAL LIVELIHOODS IN NINH THUAN PROVINCE TO DROUGHT

The risk of drought poses a significant challenge to agricultural production in Ninh Thuan Province. Therefore, this study aims to identify the factors that influence farmers’ livelihood outcomes due to the impact of drought. Data were collected from a survey of 231 farmers randomly selected from the districts of Thuan Nam, Thuan Bac, and Ninh Hai. In addition to descriptive statistics, a Tobit regression model was used to identify the factors influencing livelihood outcomes during mild and severe droughts. The results showed that farmers’ livelihood outcomes were generally low. The regression identified the financial (β=0.230 and 0.205), social (β=0.200 and 0.291), and human capital (β=0.195 and 0.196) impacts on farmers’ livelihood outcomes from both mild and severe droughts. During mild drought years, seasonal adjustment (β=-0.009) and migration (β=0.013) were found to significantly influence livelihood outcomes. In severe drought years, government support (β=-0.030) negatively affected livelihood outcomes. There is a need to establish an early warning system for climate change and extreme weather events while simultaneously disseminating information widely to farmers so that they can take timely measures to cope. Enhancing human capital by raising awareness and skills in adapting to drought and developing comprehensive abilities to implement drought adaptation strategies is needed

Multi-correlation between nematode communities and environmental variables in mangrove-shrimp ponds, Ca Mau Province, Southern Vietnam

Multi-correlation between bio-indices of nematode communities and ecological parameters in mangrove-shrimp farming ponds in Tam Giang commune, Nam Can District, Ca Mau Province, Vietnam were investigated. In which, diversities of nematode communities and several environmental variables in eight ponds were considered to process. Our findings underlined the high diversity of nematode communities in mangrove-shrimp farming ponds compared to other mangrove habitats. Nematode diversities provided more oppotunity in natural food for shrimp. Single correlation analyses showed that the species richness index correlated significantly to three variables (salinity, total organic carbon, and total nitrogen), the Margalef diversity index correlated to two variables (salinity, total organic carbon), and the expected number of species for 50 individuals index correlated with one variable (salinity). Results of multi-correlation analyses between the nematode bio-indices and the environmental variables were completely different from those of single-correlation analyses. In multi-correlation analyses, the species richness and the Margalef diversity index correlated to two variables (salinity, total organic carbon), Pielou’s evenness index and Hill indices correlated with dissolved oxygen, also the Hurlbert index correlated to total organic carbon. Hence, it is necessary to pay attention to the impact of complex interactions between the multi-environmental variables and nematode communities. This research aims to explain the differences between single- and multi-correlation for evaluation of the effects of environmental factors on nematodes as well as aquatic organisms.

Outage performance analysis and SWIPT optimization in energy-harvesting wireless sensor network deploying NOMA

Thanks to the benefits of non-orthogonal multiple access (NOMA) in wireless communications, we evaluate a wireless sensor network deploying NOMA (WSN-NOMA), where the destination can receive two data symbols in a whole transmission process with two time slots. In this work, two relaying protocols, so-called time-switching-based relaying WSN-NOMA (TSR WSN-NOMA) and power-splitting-based relaying WSN-NOMA (PSR WSN-NOMA) are deployed to study energy-harvesting (EH). Regarding the system performance analysis, we obtain the closed-form expressions for the exact and approximate outage probability (OP) in both protocols, and the delay-limited throughput is also evaluated. We then compare the two protocols theoretically, and two optimization problems are formulated to reduce the impact of OP and optimize the data rate. Our numerical and simulation results are provided to prove the theoretical and analytical analysis. Thanks to these results, a great performance gain can be achieved for both TSR WSN-NOMA and PSR WSN-NOMA if optimal values of TS and PS ratios are found. In addition, the optimized TSR WSN-NOMA outperforms that of PSR WSN-NOMA in terms of OP.Web of Science193art. no. 61

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

Efficient machine learning models for prediction of concrete strengths

In this study, an efficient implementation of machine learning models to predict compressive and tensile strengths of high-performance concrete (HPC) is presented. Four predictive algorithms including support vector regression (SVR), multilayer perceptron (MLP), gradient boosting regressor (GBR), and extreme gradient boosting (XGBoost) are employed. The process of hyperparameter tuning is based on random search that results in trained models with better predictive performances. In addition, the missing data is handled by filling with the mean of the available data which allows more information to be used in the training process. The results on two popular datasets of compressive and tensile strengths of high performance concrete show significant improvement of the current approach in terms of both prediction accuracy and computational effort. The comparative studies reveal that, for this particular prediction problem, the trained models based on GBR and XGBoost perform better than those of SVR and MLP

Dynamic stability analysis of laminated composite plates with piezoelectric layers

Research on the stability to determine the critical value of structures is a complex issue but of real significance. Piezoelectric composite plate is one of the structures which have the ability to control the mechanical behaviors under loads. One of the prominent capabilities of this structure is the ability to control its vibration and stability. Using the finite element method (FEM) and construction calculation program in Matlab, the authors analyzed the elastic stability of piezoelectric composite plates under dynamic in-plane loads, taking into account damping properties of the structure. Critical loads and other factors affecting the stability of the plate are investigated

Using fly ash treated by NaOH and H2SO4 solutions for Hg2+ and Cd2+ ion adsorption.

This paper presents the results of adsorption ability of heavy metal ions (Hg2+ and Cd2+) by fly ash (FA) before and after treatment using NaOH and H2SO4 solutions.  Original- and treated FA were characterized by Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and Scanning Electron Microscope (SEM). Specific surface area of FA before and after treatment was calculated by Brunauer – Emmett – Teller (BET) isotherm equation. The obtained results indicated that the morphology and specific surface area of FA changed clearly after treatment by acid or alkaline solutions. Adsorption capacity the Hg2+ and Cd2+ ion by FA was determined from data of UV-Vis spectra. After treatment, the adsorption capacity of ions by FA increased remarkably in comparison with non-treated FA. The FA treated by NaOH solution has the adsorption capacity higher than FA treated by H2SO4 solution. The maximum adsorption capacity of the FA treated by NaOH solution for Cd2+ and Hg2+ ions at room temperature is 28.97 and 14.60 mg/g, respectively. The equilibrium adsorption data were described by the Langmuir and Freundlich isotherm models. The results showed that equilibrium data were fitted well to the Langmuir isotherm. Keywords. Fly ash, treatment, adsorption capacity, heavy metal, Langmuir isotherm

LBMT team at VLSP2022-Abmusu: Hybrid method with text correlation and generative models for Vietnamese multi-document summarization

Multi-document summarization is challenging because the summaries should not only describe the most important information from all documents but also provide a coherent interpretation of the documents. This paper proposes a method for multi-document summarization based on cluster similarity. In the extractive method we use hybrid model based on a modified version of the PageRank algorithm and a text correlation considerations mechanism. After generating summaries by selecting the most important sentences from each cluster, we apply BARTpho and ViT5 to construct the abstractive models. Both extractive and abstractive approaches were considered in this study. The proposed method achieves competitive results in VLSP 2022 competition.Comment: In Proceedings of the 9th International Workshop on Vietnamese Language and Speech Processing (VLSP 2022