Claim Missing Document
Check
Articles

Found 2 Documents
Search

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.
Artificial Intelligence Applications and Digital Finance Development: The Moderating Role of Human Resources and Digital Infrastructure Tuan, Huynh Cao; Phuong, Tran Thanh
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1247

Abstract

The rapid advancement of digital technologies has fundamentally transformed financial systems, particularly in emerging economies, where digital finance plays a critical role in enhancing financial accessibility and efficiency. Among these technologies, artificial intelligence (AI) has emerged as a strategic driver reshaping digital financial services. This study aims to investigate the direct and moderating effects of artificial intelligence applications on the development of digital finance by integrating technological, human, institutional, and innovation perspectives. A sequential mixed-methods design was employed. In the qualitative phase, semi-structured interviews were conducted with 55 experts in banking, finance, and financial technology. The sample size was determined based on theoretical saturation, which was reached when successive interviews yielded no substantially new insights regarding construct dimensions or measurement refinement. Insights from this phase were used to validate constructs and refine the measurement instrument. In the quantitative phase, survey data were collected from 700 digital banking users across 20 commercial banks in Vietnam. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to test the proposed hypotheses. The results indicate that the digital policy framework (β = 0.300) and the digital human resource management (β = 0.279) exhibit the largest direct effects on digital finance development, based on the relative magnitude of standardized path coefficients. Among these factors, digital policy frameworks and digital human resource management demonstrate the strongest direct impacts. More importantly, the findings confirm the moderating role of artificial intelligence applications. AI significantly strengthens the relationships between digital human resource management and digital finance development, as well as between digital technology infrastructure and digital finance development. These results indicate that AI serves not only as an independent technological driver but also as a strategic catalyst, enhancing the effectiveness of digital infrastructure and human capital. This study contributes to the digital finance and information systems literature by empirically demonstrating that artificial intelligence serves as both a determinant and a moderator of digital finance development. From a practical perspective, the findings suggest that policymakers and banking executives should prioritize AI-enabled human resource strategies and the intelligent use of digital infrastructure to accelerate the development of sustainable digital finance in emerging economies.