Factors Affecting E-Commerce Customer Satisfaction in Hanoi, Vietnam

The escalating ubiquity and cost-effectiveness of internet facilities have precipitated a notable surge in the adoption of e-commerce among Vietnamese inhabitants, particularly those residing in urban areas. This research endeavours to enhance comprehension of factors affecting e-commerce customer satisfaction in Hanoi, Vietnam. A quantitative survey of this research was conducted in which online questionnaires were distributed to 382 respondents through social media. The amassed data underwent meticulous analysis utilizing Microsoft Excel. The findings of this investigation underscore that information quality, system quality, service quality and price simultaneously influence e-commerce customer satisfaction. Keywords: factors, e-commerce customers, satisfaction DOI: 10.7176/EJBM/16-2-03 Publication date:March 31st 202

HYBRID END-TO-END APPROACH INTEGRATING ONLINE LEARNING WITH FACE-IDENTIFICATION SYSTEM

To date, facial recognition has been one of the most intriguing, interesting research topics over years. It requires some specific face-based algorithms such as facial detection, facial alignment, facial representation, and facial recognition as well; however, all of these algorithms derive from heavy deep learning architectures that cause limitations for development, scalability, flawed accuracy, and deployment into publicity with mere CPU servers. It also calls for large datasets containing hundreds of thousands of records for training purposes. In this paper, we propose a full pipeline for an effective face recognition application which only uses a small Vietnamese celebrity dataset and CPU for training that can solve the leakage of data and the need for GPU devices. It is based on a face vector-to-string tokens algorithm then saves face’s properties into Elasticsearch for future retrieval, so the problem of online learning in Facial Recognition is also tackled. Comparison with another popular algorithm on the dataset, our proposed pipeline not only outweighs the accuracy counterpart, but it also achieves a very speedy time inference for a real-time face recognition application

Biocontrol of Alternaria alternata YZU, a causal of stem end rot disease on pitaya, with soil phosphate solubilizing bacteria

Stem end rot is the most destructive disease caused by Alternaria alternata YZU in pitaya-growing regions of Vietnam. This study was conducted to characterize antagonistic phosphate-solubilizing bacteria (PSB) from rhizosphere soil for their biocontrol activities against A. alternata YZU and evaluate the effect of temperature, pH, and water activity on that antagonism. Among seven PSB isolated from 45 rhizosphere soil samples, PSB31 (identified as Bacillus sp. strain IMAU61039, Accession number: MF803700.1) exhibited the highest antagonistic activity against A. alternata YZU with an average inhibition diameter of 0.65 ± 0.05 cm. The results also show that the strain PSB31 controlled the mycelial growth of A. alternata YZU by secreting antifungal metabolites. The most potent inhibitory activity was identified under in vitro conditions of 25 °C, pH 7, and aw 1. The isolated PSB31 could be a potential biological control agent against A. alternata YZU

NeCo@ALQAC 2023: Legal Domain Knowledge Acquisition for Low-Resource Languages through Data Enrichment

In recent years, natural language processing has gained significant popularity in various sectors, including the legal domain. This paper presents NeCo Team's solutions to the Vietnamese text processing tasks provided in the Automated Legal Question Answering Competition 2023 (ALQAC 2023), focusing on legal domain knowledge acquisition for low-resource languages through data enrichment. Our methods for the legal document retrieval task employ a combination of similarity ranking and deep learning models, while for the second task, which requires extracting an answer from a relevant legal article in response to a question, we propose a range of adaptive techniques to handle different question types. Our approaches achieve outstanding results on both tasks of the competition, demonstrating the potential benefits and effectiveness of question answering systems in the legal field, particularly for low-resource languages.Comment: ISAILD@KSE 202

Indoor PM₀.₁ and PM₂.₅ in Hanoi: Chemical characterization, source identification, and health risk assessment

This study attempted to provide comprehensive insights into the chemical composition, source identification, and health risk assessment of indoor particulate matter (PM) in urban areas of Vietnam. Three hundred and twenty daily samples of PM₀.₁ and PM₂.₅ were collected at three different types of dwellings in Hanoi in two seasons, namely summer and winter. The samples were analyzed for 10 trace elements (TEs), namely Cr, Mn, Co, Cu, Ni, Zn, As, Cd, Sn, and Pb. The daily average concentrations of indoor PM₀.₁ and PM₂.₅ in the city were in the ranges of 7.0–8.9 μg/m³ and 43.3–106 μg/m³, respectively. The average concentrations of TEs bound to indoor PM ranged from 66.2 ng/m³ to 216 ng/m³ for PM₀.₁ and 391 ng/m³ to 2360 ng/m³ for PM₂.₅. Principle component analysis and enrichment factor were applied to identify the possible sources of indoor PM. Results showed that indoor PM₂.₅ was mainly derived from outdoor sources, whereas indoor PM₀.₁ was derived from indoor and outdoor sources. Domestic coal burning, industrial and traffic emissions were observed as outdoor sources, whereas household dust and indoor combustion were found as indoor sources. 80% of PM₂.₅ was deposited in the head airways, whereas 75% of PM₀.₁ was deposited in alveolar region. Monte Carlo simulation indicated that the intake of TEs in PM₂.₅ can lead to high carcinogenic risk for people over 60 years old and unacceptable non-carcinogenic risks for all ages at the roadside house in winter

Acidifiers as Alternatives for Antibiotics Reduction and Gut Health Improvement for Poultry and Swine

Using antibiotics of low doses as feed additives could support to improve poultry and swine performances. However, these applications have caused resistance of bacteria and antibiotic residues in foods of animal origins. Therefore, efforts were focused on solutions to replace antibiotics as growth promoters (AGPs). There are many alternatives for AGPs, in which organic acids are one of the important alternatives. The aim of this chapter is to review publications on these acids and their other forms namely as acidifiers using as feed additives including their names and forms, mode of actions, spectrum against bacteria, combinations among them, and latest updates on their effects on swine and poultry production. The scientific findings show that acidifiers can inhibit pathogenic bacteria growth, improve nutrient digestibility, enhance immunity and overall gut health, consequently increase performances of poultry and swine. Several acids and their salts in both liquid and solid forms have been studied and applied as poultry and swine feed additives; however, the efficacy levels and the mode of actions are dependent on the single acidifiers, their salts, and combinations among them. The uses of acidifiers in their salts and derivative forms and mixtures of different acidifiers seem to be more favorable

HYBRID END-TO-END APPROACH INTEGRATING ONLINE LEARNING WITH FACE-IDENTIFICATION SYSTEM

peer reviewedFacial recognition has been one of the most intriguing and exciting research topics over the last few years. It involves multiple face-based algorithms such as facial detection, facial alignment, facial representation, and facial recognition. However, all of these algorithms are derived from large deep-learning architectures, leading to limitations in development, scalability, accuracy, and deployment for public use with mere CPU servers. Also, large data sets that contain hundreds of thousands of records are often required for training purposes. In this paper, we propose a complete pipeline for an effective face-recognition application that requires only a small dataset of Vietnamese celebrities and a CPU for training, solving the problem of data leakage, and the need for GPU devices.The pipeline is based on the combination of a conversion algorithm from face vectors to string tokens and the indexing & retrieval process by Elasticsearch, thereby tackling the problem of online learning in facial recognition. Compared with other popular algorithms on the same data set, our proposed pipeline not only outperforms the counterpart in terms of accuracy but also delivers faster inference, which is essential to real-time applications

CORROSION PROTECTION OF CARBON STEEL USING ZIRCONIUM OXIDE/SILANE PRETREATMENT AND POWDER COATING

Surface pretreatment plays important role in improvement of corrosion resistance and adhesion of organic coatings. A new generation of metal pretreatments based on nanosize zirconium oxide or ogranosilane film has been investigated recently as an alternative method to phosphatation. In this paper, ZrO2/silane composite film on carbon steel was prepared and characterised by field emission scanning electron microscopy, energy dispersive X-ray spectrum and electrochemical measurements. The effect of ZrO2/silane surface treatment on the protection properties of powder coating was studied by salt spray test and adhesion measurement. The results obtained showed that ZrO2 was rapidly precipitated on the steel surface after first 1 minute immersion and ZrO2/silane film formed after 4 minutes immersion give best protective properties. Powder coating on carbon steel with ZrO2/silane pretreatement has equivalent protection performance like powder coating with  phosphate pretreatment

Assessment of aflatoxin B1 contamination in rice and maize

Introduction: Aflatoxins B1 are among the most common poisonous mycotoxins produced by certain fungi that harm animals and crops. Mycotoxins can cause a variety of adverse health effects and pose a serious health threat to humans. The Maximum Residue Limits of aflatoxin B1 in processed cereals and ingredients are 2 parts per billion (ppb) and 5 ppb, respectively. Objectives: To evaluate the status of aflatoxin B 1 contamination in rice, corn and staple food produced in Ha Giang province compared with the maximum permitted levels. Methods: A total of 210 rice and maize samples were analyzed to quantify the level of aflatoxin B1. Analysis of mycotoxins was conducted by High Performance Liquid Chromatography using a fluorescence detector. Results: It was found that rice, rice products, maize, and maize products had a mean aflatoxin B1 content of 1.79 ppb, 2.55 ppb, 2.19 ppb, and 6.35 ppb, respectively. The results also showed that 71.9% of samples were contaminated with mycotoxins, and 14.28% of samples exceeded the maximum allowable limit. Conclusion: The concentration of aflatoxin B1 in 14.28% of the samples are over permissible limits by nationwide regulations