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All Journal International Journal of Electrical and Computer Engineering Journal of Applied Data Sciences
Hien, Lam Thanh
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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An algorithm for decomposing variations of 3D model Phuong, Tran Thanh; Hien, Lam Thanh; Duc Vinh, Ngo; Manh Toan, Ha; Nang Toan, Do
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1928-1936

Abstract

In recent times, there has been an increasing number of people who are concerned about the virtual reality field. Parameterization of deformations of 3D models is a meaningful problem in theoretical research and application development of virtual reality. This paper proposes a technique for conditional decomposition of 3D model variations based on a given set of 3D observations of an object, along with a set of input strain weights. The proposed algorithm is conducted through an optimal iterative process with solving the non-negative least squares problem. The output of the technique is a set of base models corresponding to different types of strain. The result of the proposed technique allows the creation of a new 3D model variant of the object in a simple and visually observable way. The algorithm has been tested and proven effective on data that are 3D face models created from the Japanese Female Facial Expression (JAFFE) dataset with labeled expression weights.
A framework for 3D radiotherapy dose prediction using the deep learning approach Hien, Lam Thanh; Toan, Ha Manh; Toan, Do Nang
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5524-5533

Abstract

Cancer is known as a dangerous disease to humans with a very high death rate. There are a lot of cancer treatment methods that have been studied and applied in the world. One of the main methods is using radiation beams to kill cancer cells. This method, also known as radiotherapy, requires experts having a high level of skill and experience. Our work focuses on the 3D dose prediction problem in radiotherapy by proposing a framework aiming to create a medical intelligent system for this problem. To do that, we created a convolutional neural network based on ResNet and U-Net to generate the predicted radiation dose. To improve the quality of the training phase, we also applied some data processing techniques based on the characteristics of the 3D computed tomography (CT) data. The experiment used the dataset from patients who were cancer-treated with radiotherapy in the OpenKBP competition. The results achieved good evaluating metrics, the first is by the Dose-score and the second is by the dose-volume histogram (DVH) score. From the training result, we built the medical system supporting 3D dose prediction and visualizing the result as slices in heatmap form.
Applied Structure Equation Model for Policy Suggestions to Develop the Digital Economy in Vietnam Hien, Lam Thanh; Tam, Phan Thanh
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.525

Abstract

In the current context, promoting innovation in digital economic growth models associated with economic restructuring is a prerequisite for sustainable development. Therefore, the article aims to explore the critical factors influencing the digital economy and proposes policy recommendations for developing the digital economy. The study applies quantitative research methods mainly through actual data surveying of economic experts to evaluate factors affecting the digital economy based on the structural equation model to measure the digital economy in five big cities of Vietnam, including Hanoi, Hai Phong City, Da Nang City, Ho Chi Minh City, and Can Tho City. The data collection strategy involves direct interviews via a structured questionnaire, with a sample size of 800 economic experts, and analysis using SPSS version 20.0 and Amos software. The study's novelty identifies eight critical factors influencing the digital economy at a significance level of 0.01 and eight accepted hypotheses, including (1) Information technology and digital infrastructure, (2) Digital transformation capacity in businesses, (3) Government policies and laws, (4) Human resources, (5) Digital consumer needs and behavior, (6) E-commerce and financial technology, (7) International economic integration, and (8) Market. The findings highlight the significant influence of information technology and telecommunications infrastructure on Vietnam's digital economy. Finally, the authors proposed policy recommendations to enhance the digital economy; moreover, the digital economy is a way of doing business that relies on digital technology and data as its main inputs, operates mainly in a digital environment, and employs information and communication technologies to boost labor productivity, create new business models, and optimize economic structures. This model can be used by agencies, researchers, experts, and economic managers.
Impacting Technology on Employees' Job Performance: A Case Study of Commercial Banks in Vietnam Hien, Lam Thanh; Tam, Phan Thanh
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.630

Abstract

Technology is driving rapid transformation in the way people work. Many banks have caught up by introducing technology into their operations and training their personnel to use technology to optimize work productivity. Besides, employee technology competency is one of the most critical issues for organizations, helping them maintain a competitive position in the market. Therefore, the research aimed to measure critical factors impacting on bank employees' job performance and policy recommendations. The methodology of this study applied a structural equation model consisting of five factors: knowledge, attitude, hard skills, soft skills, and technology, and examined the impact of the above factors on tasks, context, and job performance. Data were collected from 900 employees working for 40 branches at 15 commercial banks in Vietnam and processed using SPSS 20.0 and Amos software. After testing the scale’s reliability, convergence, and discrimination, the study's findings showed that the critical factors of knowledge, attitude, skills, and technology positively impact task, contextual, and job performance. In addition, the originality of this research includes the introduction of technological factors into the model, a new factor of the banking industry in the digital transformation period in Vietnam. Based on the results of testing the research model, the authors provided empirical evidence that the career competency framework includes critical factors: knowledge, attitude, skills, and technology that positively impact task performance, contextual performance, and employee job performance. The practical implications of the article proposed management implications to help employees, managers, and policymakers improve employees' knowledge, attitudes, and skills, which play an essential role in performing their duties, and improving job performance in digital competency is one of the required skills in the banking industry.
Applied Data Science for Exploring Human Resource Management Affecting the Competitiveness of Commercial Banks in Vietnam Hien, Lam Thanh; Tam, Phan Thanh
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.710

Abstract

Human resource management is crucial in banking operations and is fundamental for maintaining sustainable development and enhancing the competitiveness of commercial banks. The current challenges in human resource management within banking operations provide notable limits that adversely impact competitiveness. This study seeks to identify the elements impacting human resource management in commercial banks in Vietnam and assess their degree of impact. Considering these issues and their influence on human resource management, the authors suggested strategies to enhance human resource management and bolster the competitiveness of banks. This research employs a blend of qualitative and quantitative methodologies. The study included qualitative approaches, utilizing expert techniques and in-depth interviews with 10 bank directors, supplemented by primary data gathered via 350 questionnaires distributed to staff across 10 commercial banks in 10 regions in Vietnam. SPSS 20.0 and Amos software were utilized to measure the extent of influence of the components. The research found six factors: leadership support, training and development of human resources, workplace environment, employee perks and policies, incentive strategies, monitoring, and assessment. The study finds that control and evaluation have the strongest impact on human resource management. Ultimately, the tool assists banks in maintaining adequate human resource management and enhancing competitive positioning. The novelty of this study showed that human resource management affects the competitiveness of commercial banks with a significance of 0.05. Finally, commercial banks should improve digital human resource development software to provide comprehensive management solutions such as AI-driven recruitment platforms, automated performance evaluations, and human resource analytics tools to enhance efficiency, reducing costs and time to perform tasks. Especially helping bank leaders quickly make the right decisions about human resources. Furthermore, human resources management also contributes to the crystallization of corporate cultural values, building and preserving the bank's brand and identity, and is the driving force and goal for the bank's sustainable development.
Detecting lung nodules in computed tomography images based on deep learning Hien, Lam Thanh; Tu, Le Anh; Hieu, Pham Trung; Duc, Pham Minh; Nang, Nguyen Van; Toan, Do Nang
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5604-5615

Abstract

Lung cancer is currently recognized as one of the most dangerous cancers, with high mortality rate. In order to deal with lung cancer, an important task is to detect lung nodules early to improve patient survival rates, and computed tomography (CT) scans are crucial data for this. In this research, we propose a deep learning-based method for detecting lung nodules in the CT images with the goal of increasing the likelihood of nodule appearance in the input data of the network, making it easier for the model to focus on relevant areas while reducing noise from areas unrelated to the result. Specifically, we propose a simple lung region segmentation process and optimize the hyperparameters of the faster region-based convolutional neural networks (faster R-CNN) model based on the analysis of nodule characteristics in CT image data. In our experiments, to evaluate the effectiveness of our proposals, we conducted tests on the standard LUNA16 dataset with different backbone configurations for the model, namely ResNet50, ResNet50v2, and MobileNet. The best results achieved were 0.86 mAP50 and 0.91 Recall for the Resnet50, and 0.84 mAP50 and 0.94 Recall for the ResNet50v2. These impressive outcomes underscore the success of our method and establish a robust basis for future studies to further integrate AI into healthcare solutions.
Co-Authors Duc Vinh, Ngo Duc, Pham Minh Hieu, Pham Trung Manh Toan, Ha Nang Toan, Do Nang, Nguyen Van Phan Thanh Tam, Phan Thanh Phuong, Tran Thanh Toan, Do Nang Toan, Ha Manh Tu, Le Anh