DIFFICULTIES WITH WORD CHOICE IN ACADEMIC WRITING AND SOLUTIONS: A RESEARCH ON ENGLISH-MAJORED STUDENTS AT CAN THO UNIVERSITY, VIETNAM

Writing, especially academic writing, is highly valued in foreign language acquisition, particularly for English majors. Nevertheless, using academic terminology might be difficult for students still developing their academic language abilities. The purpose of this research is to understand students' difficulties in selecting appropriate words in academic writing and offer solutions to overcome such difficulties. The participants were 78 English majors (high-quality program, course 45) and three lecturers at the Department of English Language and Culture, School of Foreign Languages, Can Tho University. Questionnaires were used to measure their difficulties in word choice in academic writing and semi-structured interviews were utilized to find solutions. The results show that most participants had a basic knowledge of academic vocabulary, which was demonstrated through their ability to select the appropriate word choice. However, students found it difficult to choose the right words in their academic writing. The reasons are that academic words are not easy to remember and not successfully used in the context of the meaning of the word and do not have an effective method of learning academic vocabulary. Based on the results, several specific approaches have been proposed to help students find the most suitable strategies for learning and using academic vocabulary for their writing.  Article visualizations

Structured Light-Based 3D Reconstruction System for Plants.

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance

ANTIBACTERIAL AND PHOTOCATALYTIC ABILITY OF THE Ag/TiO2 COATING ON THE GLASS SURFACE.

The coating on the glass surface was made by heating the mixture of resinate Ag and tetra-n-butyl orthotitanate (TBO) at 570 oC for 1 hour. The characteristics and structure of the mixture Ag/TiO2 with the content of Ag : TiO2 from 0 – 8 (% mol) were studied by the methods such as XRD, FTIR, UV-viz, SEM, EDS. The research results of antibacterial ability and the degradation of blue methylene (MB) were shown that this coating can be used for antibacterial and photocatalytic abilit

Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera.

This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images

Buckling of the initial imperfect rectangular thin plate with variable thickness

This paper analyzes the stability of the rectangular thin plate with sinusoidal changes in the plate thickness combined with initial curvature based on the large deflection theory. The buckling load for simply supported plates is defined using the energy method. The influence of the thickness variation parameter and the initial curvature parameter on the critical loads is investigated

A Multiple Choices Reading Comprehension Corpus for Vietnamese Language Education

Machine reading comprehension has been an interesting and challenging task in recent years, with the purpose of extracting useful information from texts. To attain the computer ability to understand the reading text and answer relevant information, we introduce ViMMRC 2.0 - an extension of the previous ViMMRC for the task of multiple-choice reading comprehension in Vietnamese Textbooks which contain the reading articles for students from Grade 1 to Grade 12. This dataset has 699 reading passages which are prose and poems, and 5,273 questions. The questions in the new dataset are not fixed with four options as in the previous version. Moreover, the difficulty of questions is increased, which challenges the models to find the correct choice. The computer must understand the whole context of the reading passage, the question, and the content of each choice to extract the right answers. Hence, we propose the multi-stage approach that combines the multi-step attention network (MAN) with the natural language inference (NLI) task to enhance the performance of the reading comprehension model. Then, we compare the proposed methodology with the baseline BERTology models on the new dataset and the ViMMRC 1.0. Our multi-stage models achieved 58.81% by Accuracy on the test set, which is 5.34% better than the highest BERTology models. From the results of the error analysis, we found the challenge of the reading comprehension models is understanding the implicit context in texts and linking them together in order to find the correct answers. Finally, we hope our new dataset will motivate further research in enhancing the language understanding ability of computers in the Vietnamese language

The Relationship Between Corporate Social Responsibility and Employee Organizational Commitment in Multinational Corporations in Ho Chi Minh City

Based on the theoretical background of previous studies and the increasing context of personnel turnover in multinational companies, the authors conduct this study with the research objective to test and measure the impact of Corporate Social Responsibility (CSR) on employee’s organizational commitment through the effect of organizational identification and organizational trust. The combined qualitative and quantitative research methods were used to process and analyse the data. Research data was collected from 271 employees working in multinational corporations in Ho Chi Minh City. The study also discusses and provides some governance implications to help MNCs improve their social responsibility towards social and non-social stakeholders, employees, customers and the government as well as increase employee organizational engagement through identification and trust in the organization. Keywords: corporate social responsibility, employee organizational commitment, organizational identification, organizational trus

Lax Compliance of Goodwill Impairment Accounting in the Early Year after IFRS Implementation

After some decades of discussing in recognizing, measuring and reporting goodwill in the financial reports, Hong Kong finally has promulgated HKAS 36 - Impairment of Assets, for the convergence of IFRS including IAS 36. This is absolutely applicable to all transactions of business combinations beginning on or after 1st January, 2005. The adoption of HKAS 36 has resulted in significant changes and more complexity in terms of techniques and in the nature of disclosures relating to goodwill and its impairment to the reporting first-time adopters. The traditional method by adopting “capitalize and amortize” has been replaced by impairment testing regime based on subjective assumptions. Therefore, it is more likely to have inconsistent compliance by the first-time adopters in their transition period under the new reporting approach. Thus, this study has the purpose of examining the compliance levels under a variety of provisions of HKAS 36. By using the data of annual reports of Hong Kong listed firms, first-time adopters, the research found the material levels of non-compliance and substantial changes in the quality of note-form disclosures bearing on impairment testing process. Further study on post transition period is identified and discussed. Keywords: Goodwill, Impairment, Financial Reporting Standard, Hong Kon

Chemical diversity of essential oils of rhizomes of six species of Zingiberaceae family

In this study, the essential oils from the rhizomes of six species belonging to the Zingiberaceae family, including Zingiber zerumbet, Curcuma pierreana, Globba macrocarpa, Alpinia conchigera, Stahlianthus campanulatus and Amomum sp., collected in Binh Chau-Phuoc Buu Nature Reserve were isolated using hydrodistillation, and their constituents were identified via Gas Chromatography-Mass Spectrometry. A total of 91 constituents have been identified from essential oils. These compounds were classified into 4 clusters by Agglomerative Hierarchical Clustering (AHC) and Principal Component Analysis (PCA) analysis. The principal constituents of the essential oils isolated from four species, C. pierreana, S. campanulatus, A. conchigera, and Z. zerumbet contained camphene (18.82%), α-copaene (11.75%), p-xylene (21.86%), and α-santalene (17.91%), which were significantly different from those in previous reports. Furthermore, this study revealed the chemical constituents of essential oils of G. macrocarpa and Amomum sp. for the first time. Accordingly, artemisia triene (22.21%), β-pinene (13.57%), 4,6,8-trimethylazulene (11.1%), 2-tert-butylquinoline (9.86%), β-patchoulene (7.06%), α-elemene (6.93%), and β-ocimene (6.0%) were the major compounds in essential oils of G. macrocarpa rhizomes whereas the oil of Amomum sp. was found to be rich in 2-carene (21.82%), fenchyl acetate (14.26%), 3-carene (8.28%), bornyl acetate (7.7%), and D-limonene (7.13%)