Technology Affecting the Service Quality of Commercial Banks in Vietnam

Purpose: The study studies the factors affecting the quality of banking services of commercial banks, commercial bank branches operating in Vietnam. The authors proposed policy implications based on research results that improve the quality of commercial banking services.   Theoretical framework: Service quality measurement is difficult because of its characteristics: intangibility, heterogeneity, and inseparability. The concept of service quality has been researched and developed in many recent decades through customer satisfaction.   Design/methodology/approach: The authors conducted quantitative research in 2 phases. Phase 1 is a preliminary quantitative study: collecting data to check the reliability of the scales in the research model and completed in October 2022. Phase 2 is the official quantitative research: collecting data on a large scale after building and perfecting the appropriate scales, to be carried out from November to February 2023. Processing data by statistical methods, analyzing EFA and CFA, using the structural equation model analysis (SEM) method to test the fit of models and hypotheses with SPSS 20.0 software and Amos.   Findings: The article’s findings showed that technology factors affect commercial banks’ service quality in Vietnam. At the same time, it introduces some changes in Vietnamese banks in the context of current technological breakthroughs.   Research, Practical & Social implications: Practical implications enhanced the service quality of commercial banks in the context of digital technology breakthroughs. The amount of information that can be encoded and the tools were available to process it has increased dramatically.   Originality/value: The paper’s originality and value help bank managers invest in digital technology as the way forward to better serve their customers. Besides, the article has systematized the theory of service quality and factors affecting the quality of commercial banking services

Banking Relationship Ties to Firm Performance: Evidence from Food and Beverage Firms in Vietnam

This paper is aimed at analyzing the effects of banking relationship on performance of Vietnamese firms in Food and Beverage (F&B), one of the highest potential sectors. Panel data of 170 observations covers 34 F&B firms listed in the Vietnam stock exchanges in the period 2014-2018. The fixed effect model (FEM) is applied. The key findings are: First, short-term loan financing, leverage, and fixed asset ratios all negatively impacted on F&B firm performance, while firm size and net profit margin had positive impacts. These findings were consistent with previous studies. Second, the opposite results with previous studies were: (i) negative corelation of ROE and number of banks firms working with, as F&B firms were inefficient in selecting bank partners; (ii) positive relation of short-term liabilities ratio and ROA/ROE, as F&B firms utilize other non-bank liabilities shortly; (iii) foreign ownership had negative relationship with ROA& ROE. Foreign investors did not have significant roles in most F&B firms. Third, long-term borrowing from banks, state ownership and ages all insignificantly correlated with firm performance. Recommendations to F&B firms include: (1) Reduce the short- term loans and fixed assets investment, while increase the cheap equity funding sources via shareholders (2) Be selective in working with banks to have better fees and interest saved with banks. (3) Utilize other short-term liabilities, including payables and advances – the low-cost funding sources. F&B firms have good bargaining powers in requesting advances from their clients. (4) Have smart buy-in strategies on foreign ownership

Water and Sanitation in Schools: A Systematic Review of the Health and Educational Outcomes

A systematic review of the literature on the effects of water and sanitation in schools was performed. The goal was to characterize the impacts of water and sanitation inadequacies in the academic environment. Published peer reviewed literature was screened and articles that documented the provision of water and sanitation at schools were considered. Forty-one peer-reviewed papers met the criteria of exploring the effects of the availability of water and/or sanitation facilities in educational establishments. Chosen studies were divided into six fields based on their specific foci: water for drinking, water for handwashing, water for drinking and handwashing, water for sanitation, sanitation for menstruation and combined water and sanitation. The studies provide evidence for an increase in water intake with increased provision of water and increased access to water facilities. Articles also report an increase in absenteeism from schools in developing countries during menses due to inadequate sanitation facilities. Lastly, there is a reported decrease in diarrheal and gastrointestinal diseases with increased access to adequate sanitation facilities in schools. Ensuring ready access to safe drinking water, and hygienic toilets that offer privacy to users has great potential to beneficially impact children’s health. Additional studies that examine the relationship between sanitation provisions in schools are needed to more adequately characterize the impact of water and sanitation on educational achievements

Few-Shot Object Detection via Synthetic Features with Optimal Transport

Few-shot object detection aims to simultaneously localize and classify the objects in an image with limited training samples. However, most existing few-shot object detection methods focus on extracting the features of a few samples of novel classes that lack diversity. Hence, they may not be sufficient to capture the data distribution. To address that limitation, in this paper, we propose a novel approach in which we train a generator to generate synthetic data for novel classes. Still, directly training a generator on the novel class is not effective due to the lack of novel data. To overcome that issue, we leverage the large-scale dataset of base classes. Our overarching goal is to train a generator that captures the data variations of the base dataset. We then transform the captured variations into novel classes by generating synthetic data with the trained generator. To encourage the generator to capture data variations on base classes, we propose to train the generator with an optimal transport loss that minimizes the optimal transport distance between the distributions of real and synthetic data. Extensive experiments on two benchmark datasets demonstrate that the proposed method outperforms the state of the art. Source code will be available

Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Prediction

Advances in deep neural network (DNN) architectures have enabled new prediction techniques for stock market data. Unlike other multivariate time-series data, stock markets show two unique characteristics: (i) \emph{multi-order dynamics}, as stock prices are affected by strong non-pairwise correlations (e.g., within the same industry); and (ii) \emph{internal dynamics}, as each individual stock shows some particular behaviour. Recent DNN-based methods capture multi-order dynamics using hypergraphs, but rely on the Fourier basis in the convolution, which is both inefficient and ineffective. In addition, they largely ignore internal dynamics by adopting the same model for each stock, which implies a severe information loss. In this paper, we propose a framework for stock movement prediction to overcome the above issues. Specifically, the framework includes temporal generative filters that implement a memory-based mechanism onto an LSTM network in an attempt to learn individual patterns per stock. Moreover, we employ hypergraph attentions to capture the non-pairwise correlations. Here, using the wavelet basis instead of the Fourier basis, enables us to simplify the message passing and focus on the localized convolution. Experiments with US market data over six years show that our framework outperforms state-of-the-art methods in terms of profit and stability. Our source code and data are available at \url{https://github.com/thanhtrunghuynh93/estimate}.Comment: Technical report for accepted paper at WSDM 202

SLBQT-DSR: SOURCE-BASED LOAD BALANCING ROUTING ALGORITHM UNDER CONSTRAINTS OF QUALITY OF TRANSMISION FOR MANET

The routing technique under the constraints of the quality of transmision (QoT) in mobile ad hoc networks (MANET) has been studied widely recently. For this routing technique, QoT of the data transmission routes is improved. However, for the network models with mesh topologies such as MANET, The routing technique under the constraints of QoT can increase the bottlenecks due to the unbalanced traffic load. In this paper, we improve the DSR protocol by using the source-based load balancing in combined with the QoT constraint. The simulation results have shown that, the proposed algorithm outperforms the original algorithms in terms of the signal to noise ratio, bit error rate, blocking probability of the data packets and throughput.The routing technique under the constraints of the quality of transmision (QoT) inmobile ad hoc networks (MANET) has been studied widely recently. For this routing technique, QoTof the data transmission routes is improved. However, for the network models with mesh topologiessuch as MANET, The routing technique under the constraints of QoT can increase the bottlenecksdue to the unbalanced trac load. In this paper, we improve the DSR protocol by using the source-based load balancing in combined with the QoT constraint. The simulation results have shown that,the proposed algorithm outperforms the original algorithms in terms of the signal to noise ratio, biterror rate, blocking probability of the data packets and throughput

QUALITY OF TRANSMISSION AWARE ROUTING IN AD HOC NETWORKS BASED ON CROSS-LAYER MODEL COMBINED WITH THE STATIC AGENT

The physical effects happening on the transmission routes in ad hoc networks influence the network performance seriously. These impacts decrease the quality of transmission, especially ad hoc networks with the wide area and high node density. This paper focused on investigating the routing techniques in ad hoc networks taking into account the quality of transmission. Thence, we proposed an improved routing algorithm of DSR based on the cross-layer model in combined with the static agent. The objective of the proposed algorithm is to improve the quality of the transmission signal, reduce the blocking probability of the data packets due to the unguaranteed quality of transmission

Antimicrobial and antioxidant activity of bacterial endophytes isolated from leaves of the mangrove plant Rhizophora stylosa

Mangroves are the most productive ecosystems and contain highly diverse plants and microbial communities. Mangrove endophytes are proved to be a rich source of bioactive secondary metabolites. The biological molecules produced by endophytes play an important role in protection of mangrove plants against herbivores, insects as well as pathogens. The present study aimed to isolate the endophytic bacteria from the mangrove plant Rhizophora stylosa and screen antimicrobial and antioxidant activity of ethyl acetate extracts from the isolated endophytic bacteria. A total of 64 endophytic bacterial strains from R. stylosa leaves were isolated, of which ethyl acetate extracts of 14 isolated endophytic strains showed antimicrobial activity against at least one of reference microorganisms Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 25923, Bacillus subtilis ATCC 27212, Staphylococcus aureus ATCC 12222 and Candida albicans ATCC 7754 with MIC values from 32 to 512 µg/ml. Among them, four strains showed activity against one reference microorganism, five strains showed activity against two reference microorganisms, four strains showed activity against three reference microorganisms, and one strain showed activity against four reference microorganisms. Additionally, the ethyl acetate extracts of 12 isolated endophytic bacteria showed ATBS and DPPH radical scavenging activity with scavenging values from 36.27 ± 2.6% to 71.46 ± 6.6% and from 26.22 ± 3.3% to 57.38 ± 5.8%, respectively. The identification of the five most active endophytic bacteria by 16S rRNA sequences revealed that the endophytes belonged to four genera, including Bacillus, Streptomyces, Pseudovibrio and Pseudomonas. The obtained results suggest that the endophytic bacteria from mangrove plants are a promising reservoir of antimicrobial and antioxidant agents.      

Investigation of the potential of Brevibacillus spp. for the biosynthesis of nonribosomally produced bioactive compounds by combination of genome mining with MALDI-TOF mass spectrometry

The biosynthetic potential of 11 Brevibacillus spp. strains was investigated by combination of genome mining with mass spectrometric analysis using MALDI-TOF mass spectrometry. These endophytic, plant associated Brevibacillus strains were isolated from crop plants, such as coffee and black pepper, in Vietnam. Draft genomes of these strains were available. They were classified (a) by comparison with type strains and a collection of genome-sequenced Brevibacillus spp. deposited in the NCBI data base as well as (b) by construction of a phylogenetic tree from the core sequences of publicly available genomes of Brevibacillus strains. They were identified as Brevibacillus brevis (1 strain); parabrevis (2 strains); porteri (3 strains); and 5 novel Brevibacillus genomospecies. Our work was specifically focused on the detection and characterization of nonribosomal peptides produced by these strains. Structural characterization of these compounds was performed by LIFT-MALDI-TOF/TOF mass spectrometric sequence analysis. The highlights of our work were the demonstration of the tyrocidines, a well-known family of cyclodecapeptides of great structural variability, as the main products of all investigated strains and the identification of a novel class of pentapeptides produced by B. brevis; B. schisleri; and B. porteri which we designate as brevipentins. Our biosynthetic studies demonstrate that knowledge of their biosynthetic capacity can efficiently assist classification of Brevibacillus species.Peer Reviewe