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Empowering English Learning beyond Borders: Challenges and Benefits of Extracurricular Activities in a Non-Anglosphere Context Le, Thanh Thao; Le, Xuan Mai; Nguyen, Thanh-Tung; Nguyen Thi, Kim-Thanh
FOSTER: Journal of English Language Teaching Vol. 4 No. 3 (2023): FOSTER JELT
Publisher : Faculty of Education and Teacher Training of IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/foster-jelt.v4i3.132

Abstract

English language assumes a pivotal position in the socioeconomic advancement of Vietnam. The adoption of extracurricular mechanisms for English language acquisition is recognized as an innovative and potent overhaul of the pedagogical framework for English learners in Vietnam. This study was executed employing a quantitative methodology to ascertain the perceptions of tertiary level students regarding the advantages and obstacles encountered in their engagement with extracurricular activities directed at English language acquisition. Data was accumulated from 1,032 students pursuing higher education in an institution situated in the Mekong delta, facilitated by a questionnaire. The findings highlighted significant expectations students harbored for these activities. Particularly, they anticipated that engagement in these extracurricular endeavors would yield a positive influence on their linguistic competencies, while also fostering a conducive and collaborative environment for English language acquisition, thereby expanding their social networks with fellow participants. Nevertheless, the participants also acknowledged potential drawbacks. They expressed concern that participation in these activities might be time-consuming and could potentially diminish their motivation to partake, especially if the activities were not in alignment with their individual competencies and areas of interest. The findings of this study propose implications for enhancing the effectiveness of extracurricular activities for English language acquisition. Specifically, adequate financial and human capital investment is crucial, and the activities need to be meticulously planned to avoid an excessive time commitment from the students.
Classification of upper gastrointestinal tract diseases using endoscopic images Tran, Thanh Hai; Nguyen, Van-Tuan; Dao, Viet-Hang; Nguyen, Phuc-Binh; Nguyen, Thanh-Tung; Vu, Hai
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i2.pp833-842

Abstract

Automatic classification and disease detection in medical images, aided by machine learning, provide crucial support to prevent overlooked instances and ensure prompt treatment of diseases. Despite impressive achievements in the field of polyp detection from endoscopic images, classification of other diseases, such as reflux esophagitis, esophageal cancer, gastritis, gastric cancer, and duodenal ulcer, is still subject to significant limitations and remains a challenging area of study because of their different and more challenging characteristics. This paper proposes a method to roughly classify the diseases from the whole images by deep learning. In particular, we focus on identifying hard samples from the training dataset and enriching them with some fundamental augmentation techniques. We then employ a cutting-edge model, specifically ResNet, for the final classification stage. Additionally, we enhance the original ResNet’s loss function by incorporating another loss function called focal loss. These modifications play a crucial role in boosting the accuracy of the ResNet model. Our proposed method outputs the disease category and corresponding heat map showing the area of interest. It achieved very promising accuracy (99.55%) for the classification of five lesions on our self-collected dataset. It serves a dual purpose. Firstly, it aids in the training of novice endoscopists, enabling them to gain valuable experience. Secondly, it offers a rapid solution for annotating extensive volumes of endoscopic image data at the label level.
LQR Controller Based on BAT Algorithm for Rotary Double Parallel Inverted Pendulum Le, Thanh-Tri-Dai; Nguyen, Ngoc-Kien; Le, Phuc-Truong; Bui, Minh-Nguyen-Bao; Nguyen, Trong-Tin; Tran, Chi-Anh; Doan, Phuong-Tu; Dao, Duc-Nhan; Nguyen, Van-Dong-Hai; Nguyen, Thanh-Tung
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.304

Abstract

This paper presents an enhanced approach to stabilizing the Rotary Double Parallel Inverted Pendulum (RDPIP) through a combination of the LQR method and the BAT algorithm. Traditionally, selecting appropriate Q and R matrices relies on designers' intuitions or trial-and-error processes, often resulting in suboptimal performance. By leveraging the BAT algorithm’s swarm intelligence, the proposed method automatically optimizes the cost function to yield improved control performance. Key improvements include shorter stabilization time, reduced overshoot, and minimized oscillations. Simulation results show that the BAT-enhanced LQR controller significantly outperforms traditional design in terms of convergence speed and system damping. These findings underscore the potential of metaheuristic algorithms in refining classical control strategies for complex, nonlinear systems.