Factors affecting the flipped classroom in the educational context of Vietnam

In the context of the implementation of the 2018 General Education Program, teachers are required to implement a teaching model oriented to the development of students’ quality and competence. Teachers are encouraged to adapt the flipped classroom model of teaching in schools as its advantages are suitable for novel teaching strategies. This study focuses on analyzing factors affecting the application of this model in the teaching and learning process by collecting feedback from 351 teachers from various cities in Vietnam. The questionnaire included Likert-type questions analyzed by IBM SPSS Statistics version 20 for quantitative analysis and an open question for qualitative analysis with context and personal information. The research-oriented factors focus on the group of potential internal factors (perception, proficiency, desire and readiness of teachers) and the group of external factors (infrastructure, facilities and support resources, training programs). The results showed that those factors include the school’s infrastructure and information communication technology (ICT) condition, the teacher’s ICT competence as well as competence-related teaching and assessment methodologies and the students’ internet access conditions. Finally, the study offers suggestions on how to apply this model in teaching practice to meet the requirements of educational innovation in Vietnam

APPLICATION OF DATA ENVELOPMENT ANALYSIS FOR MEASURING SERVICE QUALITY FROM DISTRIBUTORS’ PERSPECTIVE IN SUPPLY CHAIN

Abstract: Vietnam’s textile and apparel sector has achieved fast and sustainable growth over the past years and played an important role in national socio-economic development. The export value of textile and garment products in recent years has ranked number two in the country’s total export revenue. In this scenario, an attempt was made to examine the service quality at the manufacturer – distributor interface of the textile supply chain and provide clear guidelines for benchmarking of service quality in multi-unit services. A sample of 144 distributors from Small and Medium Enterprises (SMEs) in major regions of South Vietnam was selected. Exploratory Factor Analysis was used to identify the critical factors of service quality. This research applies the data envelopment analysis (DEA) approach to the computation of a measure of overall service quality and benchmarking when measuring service quality with the Service Performance model. Dealing with the five dimensions of Service Performance (SERVPERF) as outputs, the proposed approach uses DEA as a tool for multiple criteria decision making (MCDM), in particular, the pure output DEA model without inputs. Data envelopment analysis measures the relative efficiency of decision-making units (DMUs) and identifies a set of corresponding efficient DMUs that can be used as benchmarks for the improvement of inefficient DMUs. The findings shed valuable insights on measures and critical underlying dimensions of service quality in the context of the supply chain in the textile industry, specifically from the distributor perspective. The results also give the best performer in textile SMEs and set the benchmarking guideline within each group among SEMsKeywords: service quality, data envelopment analysis, SERVPER

An Improved MobileNet for Disease Detection on Tomato Leaves

Tomatoes are widely grown vegetables, and farmers face challenges in caring for them, particularly regarding plant diseases. The MobileNet architecture is renowned for its simplicity and compatibility with mobile devices. This study introduces MobileNet as a deep learning model to enhance disease detection efficiency in tomato plants. The model is evaluated on a dataset of 2,064 tomato leaf images, encompassing early blight, leaf spot, yellow curl, and healthy leaves. Results demonstrate promising accuracy, exceeding 0.980 for disease classification and 0.975 for distinguishing between diseases and healthy cases. Moreover, the proposed model outperforms existing approaches in terms of accuracy and training time for plant leaf disease detection

Ecpoc: an evolutionary computation-based proof of criteria consensus protocol

Recently, blockchain technology has been applied in many domains in our life. Blockchain networks typically utilize a consensus protocol to achieve consistency among network nodes in a decentralized environment. Delegated Proof of Stake (DPoS) is a popular mechanism adopted in many networks such as BitShares, EOS, and Cardano because of its speed and scalability advantages. However, votes that come from nodes on a DPoS network tend to support a set of specific nodes that have a greater chance of becoming block producers after voting rounds. Therefore, only a small group of nodes can be selected to become block producers. To address this issue, we propose a new protocol called Evolutionary Computation-based Proof of Criteria (ECPoC), which uses ten criteria to evaluate and select a new block procedure in each round. Next, a set of optimal weights used for maximizing the network’s decentralization level is identified through the use of evolutionary computation algorithms. The experimental results show that our consensus significantly enhances the degree of decentralization in the selection process of witness nodes compared to DPoS. As a result, ECPoC facilitates fairness between nodes and creates momentum for blockchain network developmen

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

Influence Of Fabrication Condition on the Microstructural and Optical Properties of Lead-Free Ferroelectric Bi0.5_{0.5}Na0.5_{0.5}TiO3_{3} Materials

Lead-free ferroelectric materials have attracted considerable attention due to the increasing potential application in environmental benign materials. Among lead-free ferroelectric materials, the Bi0.5Na0.5TiO3 (BNT) materials were more studied because it exhibited the good ferroelectric and piezoelectric properties which could be promising candidate materials replacing Pb(Zr,Ti)O3. In this work, the lead-free ferroelectric BNT materials were synthesized by sol-gel method. The effects of fabrication process to microstructural and optical properties were studied which includes Na precursor concentration and calcining temperature. The result indicated that the Na precursor concentration were higher 40 mol.% and the calcining temperature

Depression and its associated factors among pregnant women in central Vietnam.

To date, little attention has been given to prenatal depression, especially in low and middle-income countries. The aim of this research was to assess the prevalence of depression and its associated factors amongst pregnant women in a central Vietnamese city. This cross-sectional study included 150 pregnant women from 29 to 40 weeks of gestation, from eight wards of Hue city, via quota sampling from February to May 2019. We employed the Patient Health Questionnaire (PHQ-9) to assess depression. Findings suggest the need to provide routine screening of pregnant women in primary care for depressive symptoms and other mental health problems.This is part of the EBLS proejct of which Prof Eisner is PI. Botnar Fondation is the sponso

Stimulation of shoot regeneration through leaf thin cell layer culture of Passiflora edulis Sims.

Passiflora edulis Sims. belonged to the genus Passiflora, is one of the important economic crops of the world as well as Vietnam. Nowadays, the commercial P. edulis is mainly propagated by seeds, cuttings and grafting; however, these methods still have some limitations such as genetic degradation and heterogeneity and the spread of pathogenic viruses. Micro-propagation has been used for clonal breeding and disease-free plant breeding, as well as providing a source of materials for Passiflora breeding. In this study, leaf explants of P. edulis Sims. (2.0-month-old) excised from the in vitro culture of ex vitro axillary buds cut longitudinally and transversally into thin cell layers (lTCL and tTCL) were used as plant materials to evaluate the shoot regeneration. In addition, the effects of explant age and lighting condition on shoot regeneration were also investigated. After 8 weeks of culture, the results showed that shoot regeneration rate (100%) and shoot multiplication coefficient (13.33) of the in vitro leaf-tTCL-4 were higher than those of other treatments and control. The shoot regeneration rate of P. edulis Sims. also varied with the change of explant age. The highest shoot regeneration rate (100%) was obtained from leaf explants of 1.5-month-old shoots after 8 weeks of culture. Moreover, the light (fluorescent lamps with photoperiod of 16 hours/day and lighting intensity of 40 - 45 μmol.m-2.s-1) improved not only morphogenesis rate, but also shoot regeneration rate (100%) of leaf explants after 8 weeks of culture. This study provided a novel method for rapid micro-propagation of P. edulis Sims

Long short-term memory (LSTM) neural networks for short-term water level prediction in Mekong river estuaries

This study firstly adopts a state-of-the-art deep learning approach based on a Long Short-Term Memory (LSTM) neural network for predicting the hourly water level of Mekong estuaries in Vietnam. The LSTM models were developed from around 8,760 hourly data points within 2018 and were evaluated using the Nash-Sutcliffe efficiency coefficient (NSE), mean absolute error (MAE), and root mean square error (RMSE). The results showed that the NSE values for the training and testing steps were both above 0.98, which can be regarded as very good performance. Furthermore, the RMSE were between 0.09 and 0.11 m for the training and between 0.10 and 0.12 m for the testing, while MAE for the training ranged from 0.07 to 0.08 m and varied from 0.08 to 0.10 m for the testing. The LSTM networks appear to enable high precision and robustness in water level time series prediction. The outcomes of this research have crucial implications in river water level predictions, especially from the viewpoint of employing deep learning algorithms

Influence of foliar application with Moringa oleifera residue fertilizer on growth, and yield quality of leafy vegetables

Biofertilizers produced from organic materials help to promote the growth, and yield quality of crops and is more environmentally friendly than chemical fertilizers. Moringa oleifera is a leafy vegetable whose leaves are also used to make biofertilizers. The use of moringa non-edible parts in biofertilizer preparation remains under-explored. In this study, a procedure to produce moringa foliar biofertilizer (MFB) from non-edible parts was developed. The effect of composting time (3 to 4 months) on the quality of MFB was investigated, and four-month incubation was found suitable for biofertilizers yield with the highest nitrogen content and optimal pH. Furthermore, the influences of MFB doses (20 to 100 mL per Litre) on the growth of lettuce and mustard spinach were studied. The yield of these leafy vegetables was the highest at 100 mL per Litre of MFB spray. Finally, MFB was compared with other commercial foliar sprays, including chitosan fertilizer and seaweed fertilizer. Each foliar treatment was applied every five days until five days before harvest. Plant height, the number of leaves, canopy diameter, leaf area index, actual yield, ascorbic acid content, and Brix were found to be similar in lettuce sprayed with MFB, chitosan, and seaweed fertilizers. In conclusion, the application of MFB promoted the growth and yield of mustard spinach