Apply deep learning to improve the question analysis model in the Vietnamese question answering system

Question answering (QA) system nowadays is quite popular for automated answering purposes, the meaning analysis of the question plays an important role, directly affecting the accuracy of the system. In this article, we propose an improvement for question-answering models by adding more specific question analysis steps, including contextual characteristic analysis, pos-tag analysis, and question-type analysis built on deep learning network architecture. Weights of extracted words through question analysis steps are combined with the best matching 25 (BM25) algorithm to find the best relevant paragraph of text and incorporated into the QA model to find the best and least noisy answer. The dataset for the question analysis step consists of 19,339 labeled questions covering a variety of topics. Results of the question analysis model are combined to train the question-answering model on the data set related to the learning regulations of Industrial University of Ho Chi Minh City. It includes 17,405 pairs of questions and answers for the training set and 1,600 pairs for the test set, where the robustly optimized BERT pre-training approach (RoBERTa) model has an F1-score accuracy of 74%. The model has improved significantly. For long and complex questions, the mode has extracted weights and correctly provided answers based on the question’s contents

Enriching Biomedical Knowledge for Vietnamese Low-resource Language Through Large-Scale Translation

Biomedical data and benchmarks are highly valuable yet very limited in low-resource languages other than English such as Vietnamese. In this paper, we make use of a state-of-the-art translation model in English-Vietnamese to translate and produce both pretrained as well as supervised data in the biomedical domains. Thanks to such large-scale translation, we introduce ViPubmedT5, a pretrained Encoder-Decoder Transformer model trained on 20 million translated abstracts from the high-quality public PubMed corpus. ViPubMedT5 demonstrates state-of-the-art results on two different biomedical benchmarks in summarization and acronym disambiguation. Further, we release ViMedNLI - a new NLP task in Vietnamese translated from MedNLI using the recently public En-vi translation model and carefully refined by human experts, with evaluations of existing methods against ViPubmedT5

A Study on Employment for Rural Laborers in the Process of Industrialization and Modernization of Vietnam

Employment and job creation are global socio-economic issues and concern every country in the world and Vietnam is no exception. Today, the concept of development is comprehensively understood and economic growth is associated with progress, social justice, poverty reduction, on the basis of creating sustainable jobs for workers. At different times, employments for workers also have different characteristics. In the dimension of this study, employment for rural laborers with the case study of Nam Dinh of Vietnam have been investigated, then some recommendations are proposed for creating more jobs for rural people. Keywords: Employment, job creation, rural employment, rural labor. DOI: 10.7176/EJBM/12-21-13 Publication date:July 31st 202

Limonene and eucalyptol rich essential oils with their antimicrobial activity from the leaves and rhizomes of Conamomum vietnamense N.S. Lý & T.S. Hoang (Zingiberaceae)

Conamomum vietnamense, a new species of Zingiberaceae family, has been discovered and described from Tay Nguyen (Central Highlands, Vietnam) in 2022. The present study described the preparation of essential oil from leaves and rhizomes of the plant by hydrodistillation process. Then, the chemical composition of these essential oils was analyzed by Gas Chromatography-Mass Spectrometry (GC-MS), which indicated that limonene (18.74 and 26.20%) and eucalyptol (40.47 and 49.49%) were the main components, respectively. The essential oils also showed moderate antimicrobial activities against Gram-positive bacterial strains (Enterococcus faecalis ATCC 299212, Staphylococcus aureus ATCC 25923, Bacillus cereus ATCC 14579), Gram-negative bacterial strains (Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, Salmonella enterica ATCC 13076), and a pathogenic yeast (Candida albicans ATCC 10231) in the MIC range of 32–256 μg/mL, which was comparable to those of positive controls, streptomycin and cycloheximide. For the first time, the chemical composition and antimicrobial activity of the essential oil of C. vietnamense were studied

Community perceptions of social, economic and environmental impacts of flooding in central districts of Hanoi, Vietnam

The impacts of flooding on road infrastructure in Hanoi are highly disruptive, despite recent progress by the Vietnamese authorities in improving the city’s drainage systems. The GCRF–OSIRIS Project aims to optimise investment strategies to minimise the impacts of flood disasters, making disaster risk reduction more effective, by introducing operational research methods. In support of this objective, the project carried out an impact assessment in four of the city’s central districts. The assessment considered locally perceived social, economic and environmental impacts on residents, local entrepreneurs, and on visiting street vendors and transport service providers. Impacts of flooding were found to be highly gender-differentiated. When roads are flooded, women—both resident and visiting—face greater conflicts between the need to maintain their incomes and the responsibilities of caring for vulnerable family members, resulting in increased stress and increasing risks to their health. The assessment suggests that such disproportionate impacts on women could be mitigated through public education and pre-emptive planning measures

M^2UNet: MetaFormer Multi-scale Upsampling Network for Polyp Segmentation

Polyp segmentation has recently garnered significant attention, and multiple methods have been formulated to achieve commendable outcomes. However, these techniques often confront difficulty when working with the complex polyp foreground and their surrounding regions because of the nature of convolution operation. Besides, most existing methods forget to exploit the potential information from multiple decoder stages. To address this challenge, we suggest combining MetaFormer, introduced as a baseline for integrating CNN and Transformer, with UNet framework and incorporating our Multi-scale Upsampling block (MU). This simple module makes it possible to combine multi-level information by exploring multiple receptive field paths of the shallow decoder stage and then adding with the higher stage to aggregate better feature representation, which is essential in medical image segmentation. Taken all together, we propose MetaFormer Multi-scale Upsampling Network (M$^2$UNet) for the polyp segmentation task. Extensive experiments on five benchmark datasets demonstrate that our method achieved competitive performance compared with several previous methods

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

Class based Influence Functions for Error Detection

Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we provide an explanation for the instability of IFs and develop a solution to this problem. We show that IFs are unreliable when the two data points belong to two different classes. Our solution leverages class information to improve the stability of IFs. Extensive experiments show that our modification significantly improves the performance and stability of IFs while incurring no additional computational cost.Comment: Thang Nguyen-Duc, Hoang Thanh-Tung, and Quan Hung Tran are co-first authors of this paper. 12 pages, 12 figures. Accepted to ACL 202

Fabrication of Electrochemical Electrodes Based on Platinum and ZnO\text{ZnO} Nanofibers for Biosensing Applications

Platinum (Pt) electrodes were designed in imitation of screen-printed electrodes, and prepared by microelectronic techniques. These electrodes were then modified with zinc oxide (ZnO) nanofibers for biosensing applications. ZnO nanofibers with average length $\sim 20-30\; \mu$ m and diameter $\sim 150$ nm in hexagonal crystalline structure are prepared using electrospinning method. Their surface characteristics were analyzed by field emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Electrochemical properties of modified Pt electrodes were investigated in comparison with commercial carbon screen-printed electrodes. The results showed that the cyclic voltammogram of modified Pt electrodes was stable, but has much lower resistance compared to that of carbon screen-printed electrodes