Can Tho Journal of Science and Technology

BUILDING A MODEL TO CONTROL ELECTRIC DEVICES BY HAND GESTURES USING OPENCV-PYTHON LIBRARY

Dương Ngọc Đoàn — 2025-11-27

Nowadays, the application of artificial intelligence and image processing technology has helped develop the method of communication between humans and devices in an intuitive and vivid way. This study aims to built a model to control electrical devices using hand gestures by combining the OpenCV-Python library, mediapipe with the Arduino microcontroller board to control peripheral devices. Through the computer's camera, the system uses the image processing library OpenCV-Python, mediapipe to track the user's hand gestures. In good enough lighting conditions, the system was tested and can recognize hand gestures well within a distance of 100 cm and execute the commands to control the Arduino to turn on and off lights, fans, and doors.

NONLINEAR DAMPED SEISMIC RESPONSE ANALYSIS OF PLANE SOLID STRUCTURES USING AN IMPLICIT DYNAMIC FINITE ELEMENT ALGORITHM

Nguyễn Thanh Tuấn — 2025-11-27

An implicit dynamic finite element algorithm with decoupled equations is proposed to simulate the nonlinear damped behavior of plane solid structures subjected to strong earthquake excitations. The approach employs equivalent nodal secant stiffness and damping coefficients to decouple the dynamic equilibrium equations, thereby eliminating the need for triangular factorization of the coefficient matrix. Additionally, an efficient method is introduced to rapidly evaluate stiffness-proportional damping forces at the element level when the structure undergoes highly nonlinear dynamic responses. In this approach, the rigid body motion of the plane element is accurately identified, and the pure deformation velocity is then used to compute the nodal damping forces. Compared to conventional finite element dynamic analysis methods, the proposed algorithm demonstrates both high accuracy and computational efficiency in simulating nonlinear damped responses of plane solid structures under seismic loading.

REALTIME ROAD DAMAGE DETECTION

Châu Nhật Phúc — 2025-11-27

A real-time road damage detection system is introduced for mobile deployment using deep learning techniques. Two object detection models Faster R-CNN and YOLOv12m are trained and evaluated on the RDD2022 dataset to determine their suitability for practical application. While Faster R-CNN achieves higher accuracy, its slower inference speed limits responsiveness. YOLOv12m, enhanced with architectural improvements such as R-ELAN, Area Attention, and FlashAttention, offers a better trade-off between speed and accuracy. Based on evaluation results, YOLOv12m is selected and integrated into an Android system, the system integrates the YOLOv12m model into a backend server and connects to the Android application via WebSocket, enabling real-time display of detection results on the user interface.

USING CIRCULATING FLUIDIZED BED FLY ASH TO REPLACE FINE AGGREGATE FOR CLSM

Đường Hoàng Trung Hiếu — 2025-11-27

This study investigates the potential of fly ash (FA) to replace fine aggregates in concrete as part of a laboratory evaluation of Controlled Low Strength Material (CLSM). After conducting tests on the basic physical properties of FA, fly ash from fluidized bed combustion (CFB) was used to replace fine aggregates in mortar and concrete at replacement ratios of 0, 25, 50, 75, and 100%. The experimental results indicate that both the compressive strength and Ultrasonic Pulse Velocity (UPV) of the concrete samples decreased as the replacement ratio increased. In addition, based on CLSM mixtures with a cement content of 150 kg/m³, where FA replaced fine aggregates at the same ratios (0, 25, 50, 75, and 100%), the results revealed that replacing more than 50% of the fine aggregate with FA significantly reduced key performance parameters such as compressive strength, density, and UPV. Based on these findings, FA shows potential as a substitute for fine aggregates in CLSM; however, the replacement level should not exceed 50%.

EFFECTS OF BLENDING RATIOS AND STERILIZATION TIME ON THE PHYSICOCHEMICAL AND SENSORY PROPERTIES OF CANNED STEAMED SNAKEHEAD FISH PASTE

Nguyễn Thị Tròn — 2025-11-27

The study was conducted to investigate the effects of mixing ratios and sterilization time on the physicochemical and sensory properties of canned steamed snakehead fish paste. The experiment was designed with two factors: (i) mixing ratios, including duck egg to fish paste (30%, 50%, and 70%) and minced pork to fish paste (50%, 75%, 100%, and 125%); and (ii) sterilization at 121°C for 10, 15, 20, and 25 minutes. The results indicated that the formulation containing 70% duck egg and 100% minced pork yielded superior physicochemical characteristics and higher sensory scores. Sterilization at 121°C for 15 minutes was identified as the most effective treatment, ensuring microbiological safety while maintaining the physicochemical properties and sensory quality of the product.

STRATEGIC SOLUTIONS TO ENHANCE THE COMPETITIVE CAPACITY OF CAN THO COLLEGE OF ECONOMICS AND TECHNOLOGY

Trần Thảo Vy — 2025-11-27

This study analyzes the competitive capacity of Can Tho College of Economics and Technology in the context of digital transformation in vocational education and regional integration. The theoretical framework integrates the Resource-Based View, core competence theory, and Porter’s competitive model to evaluate internal and external factors through the Internal Factor Evaluation (IFE) matrix, the External Factor Evaluation (EFE) matrix, and the SWOT matrix. Data were collected from secondary sources during 2022–2024 and from a survey of 145 respondents, including lecturers, administrators, industry partners, and alumni. The findings indicate that the College’s overall competitive capacity is relatively high (4.02 points), with an IFE score of 2.91 and an EFE score of 2.85. Key strengths include faculty quality, enterprise-linked training programs, and increasing levels of digital transformation. However, limitations in financial capacity and brand communication continue to hinder the enhancement of competitive advantages. The novelty of this study lies in the integration of the RBV, core competence theory, and Porter’s competitive framework to assess the competitiveness of a public college in the Mekong Delta-an empirical context that remains underexplored.
remains underexplored.

APPLICATION OF THE ARMA MODEL IN THE TIME SERIES ANALYSIS OF VIETNAM'S RICE EXPORTS

Nguyễn Thị Ngọc Thứ — 2025-11-27

This study focuses on time series analysis of Vietnam's rice export volume during the period from January 2020 to April 2025. The research was conducted through four main stages: (i) data exploration, (ii) model estimation and selection, (iii) model validation, and (iv) forecasting. The results show that the ARMA(1,12) model best fits the observed data and provides highly accurate forecasts, with predicted values closely matching actual outcomes. The study contributes important scientific grounds for selecting appropriate forecasting models in time series analysis, thereby supporting the planning and management of rice export activities in a more proactive and efficient manner.

DESIGNING A REVERSE LOGISTICS MODEL: A CASE STUDY OF PLASTIC, PAPER, AND METAL WASTE COLLECTION IN CAN THO CITY

Mai Chí Anh — 2025-11-27

This study focuses on developing a recovery chain model for plastic, paper, and metal waste, determining the location of a central warehouse, and applying simulation through AnyLogic-GIS software in the recovery process. Identifying appropriate collection volumes, optimizing transportation routes, and determining the required number of transport vehicles are essential to enhance the efficiency and performance of the recovery operations. The research methodology is implemented using a multi-method approach, including data collection, field observation, and non-experimental research. Unlike traditional models that focus on individual stages, this study constructs a unified and closed-loop recovery chain from collection to recycling. It integrates operational simulation software and smart waste bins to analyze and optimize the collection process, effectively utilize the supply of plastic, paper, and metal waste, and ensure sustainability in recovery activities.

OPTIMIZING LOGISTICS COSTS AND DIGITAL MARKETING STRATEGY IN DEVELOPING ONLINE DISTRIBUTION CHANNELS

Nguyễn Vĩnh Khang — 2025-11-27

This study assesses the feasibility of developing an online distribution channel for Company B in Can Tho, focusing on four key factors: logistics costs, marketing, information systems, and customer demand. Utilising analytical methods such as Cronbach’s Alpha, EFA, multiple linear regression, and the Dupont model, findings reveal that logistics costs substantially impact operational efficiency. Implementing the Vehicle Routing Problem (VRP) model results in a 46% reduction in delivery time and a 40% cut in transportation costs. An integrated marketing strategy across TikTok, Shopee, and Facebook is proposed to enhance brand visibility. The study confirms the project's feasibility, provided that operations, technology, and communications are optimised for the fast-moving consumer goods sector.

ANALYSIS OF ADVANTAGES AND DIFFICULTIES OF ENGINEERING STUDENTS WHEN PARTICIPATING IN SCIENTIFIC RESEARCH ACTIVITIES: A CASE STUDY OF STUDENTS AT CAN THO UNIVERSITY OF TECHNOLOGY

Lê Hoàng Minh — 2025-11-27

This study aims to investigate the advantages and disadvantages of engineering students at Can Tho University of Technology (CTUT) when participating in scientific research activities. The results showed that engineering students at CTUT have good skills in using scientific literature search tools, identifying research questions and conducting experiments. However, many students have difficulty in publishing research results, transferring and applying research results into practice; at the same time, students also have difficulty due to lack of funding and equipment for research activities. Based on these results, the authors have proposed solutions to promote research skills training; provide financial support, facilities and create favorable conditions for students to participate in publishing and applying research results. The research findings serve as a foundation for advising the development of training and support policies that encourage student participation in scientific research, tailored to specific academic disciplines, thereby contributing to the improvement of high-quality technical human resource training.

FACTORS INFLUENCING STUDENTS' INTENTION TO PURSUE GRADUATE STUDIES AT CAN THO UNIVERSITY OF TECHNOLOGY

Nguyễn Minh Tân — 2025-11-27

This study analyzes the factors influencing students’ intention to pursue postgraduate education at Can Tho University of Technology. Research data were collected from a survey of 240 current students. The Partial Least Squares Structural Equation Modeling (PLS-SEM) approach was employed for analysis. The results indicate that the model is statistically significant with R² = 0.737, confirming that the examined factors exert considerable influence on students’ postgraduate study intentions. The significant factors include social environment, cost and time, labor market requirements, and program quality. Among these, cost and time emerged as the most influential determinant, while labor market demands are increasingly recognized as a key driving force. In addition, program quality and social environment exert moderate impacts, whereas personal motivation, although relevant, is not the primary determinant. These findings provide a scientific basis for policy and managerial implications, including setting reasonable tuition fees, offering flexible study schedules, and improving program quality and teaching effectiveness to attract more students to postgraduate education.

DEVELOPMENT OF AN AI CHATBOT MODEL FOR STUDENT ADVISING AT A CENTER FOR FOREIGN LANGUAGE AND INFORMATICS

Nguyễn Bá Duy — 2025-11-27

At present, chatbots are widely adopted across various sectors, particularly in educational institutions. Nevertheless, those relying on large language models often demand high-performance computing resources, which pose cost challenges for many local education centers. This study introduces an AI-based student advising chatbot that has been designed and piloted at the Center for Foreign Languages and Informatics, Can Tho University of Technology. The system aims to deliver academic advising services under limited-resource conditions, employing the Rasa framework in combination with LaBSE and PostgreSQL. A distinctive contribution of this work lies in building a CPU pipeline that does not depend on GPUs or commercial APIs, together with a detailed preprocessing procedure for Vietnamese text. The dataset includes 1,712 questions collected from students, advisors, and the Center’s Facebook page, categorized into 56 intents and 55 dialogue scenarios. Ten-fold cross-validation results indicate that the chatbot achieves 98.1% accuracy for intent classification and 99.9% for entity recognition. Experimental deployment further validates the feasibility of the proposed model in providing student advising services at educational institutions with constrained infrastructure.