Technology
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- Ấn phẩmA new score function of IFSs and it sapplication in the evaluation of software quality(2024) Ngoc, Minh Chau; Nguyen, Xuan Thao; Nguyen, Thi ThaoThe score function is used to compare intutionistic fuzzy numbers. In this paper, a novel score function of intuitionistic fuzzy sets (IFSs) is investigated. The novel score function was constructed by combining the polynomial and exponential functions working on the degree of membership and degree of non-membership of intuitionistic fuzzy sets. Then, the newly obtained measure overcomes the limitations of some existing score functions. Next, we applied the new measure to construct a method to deal with a multi-criteria decision-making (MCDM) problem. Finally, this MCDM model was used to assess the quality of software projects. The results showed that the new measure was well done and better than other score functions in some cases. This demonstrate the effectiveness of the newly proposed method.
- Ấn phẩmGenerative AI in simulation-based SBIRT training: Enhancing content validity and educational impact(2025) Kroll, NicoleBackground: Traditional SBIRT (Screening, Brief Intervention, and Referral to Treatment) training is limited by subjective assessments and resource constraints. Integrating generative AI into simulation offers scalable, consistent, and objective learning for addressing substance use disorders. Method: A web-based AI-enabled SBIRT simulation using large language models was piloted with content experts to evaluate usability, content validity, and educational impact via mixed-methods feedback and survey analysis. Results: Most evaluators rated the simulation as highly relevant and natural, with enhanced consistency and accessibility. The platform was easy to use and improved therapeutic communication skills. Conclusion(s): Generative AI in SBIRT simulation increases training reliability, scalability, and learner engagement for healthcare providers
- Ấn phẩmLegally-aware AI moderation in Vietnam: A cybersecurity law-compliant framework for platform governance(2025) Bui, Vu LuongDigital platforms increasingly mediate fraud, illicit trade, misinformation, and incitement, often under stringent statutory timelines that demand rapid and auditable responses. Conventional moderation pipelines remain tuned to classifier accuracy, leaving them misaligned with legal categories, due-process safeguards, and deterrence goals. This produces costly false positives that chill lawful expression, false negatives that enable social harm, and thin audit trails that weaken accountability. We address this gap by introducing a legally-aware AI moderation framework that integrates law → policy → model label → evidence minima → action tier → appeal path into a single, auditable pipeline with human-in-the-loop review and mandatory rationales. The framework embeds economic criminology by modeling the expected utility of offending and demonstrating how risk thresholds, graduated sanctions, and appeal quality shift incentives while internalizing enforcement externalities. We develop a decision-analytic simulation of 50,000 multi-signal items that calibrates governance choices on a harm–cost frontier. Results show that at matched thresholds, a graduated action menu achieves 2.51 × greater harm reduction per unit enforcement cost compared to binary removal, while sustaining deterrence and lowering appeal overturn rates. This evidence demonstrates that moderation choices function as price signals in a crime market: raising certainty and proportional severity reduces offenders’ expected payoffs while protecting legitimacy through reversibility and transparency. By quantifying deterrence, externality reduction, and enforcement-cost efficiency, the framework reframes moderation as a problem of governance economics, not just technical accuracy. Situated within economic criminology, it operationalizes deterrence (certainty × severity), rational-choice incentives, and capable guardianship via a cost-adjusted harm-reduction frontier. Through open research objects and a jurisdictional portability protocol, it offers a replicable and auditable blueprint for platform governance that is compliant, economically rational, and transferable across sectors and jurisdictions.
- Ấn phẩmDigital transformation for SMEs through an optimized approach to business process management(2025) Nguyen, Thi HangResearch background and purpose: Amidst the rapid digital transformation, small and medium-sized enterprises (SMEs) in Vietnam face numerous challenges in optimizing business processes and enhancing their competitiveness. This study aims to assess the readiness and digital transformation capabilities of SMEs while proposing distribution channel models and business strategies to help enterprises improve customer reach, streamline operations, and enhance business performance. Design/methodology/approach: Research data were collected through an online survey via Google Forms, with participation from 200 managers of SMEs in Vietnam. The questionnaire was designed to evaluate the demand, readiness, and digital transformation capabilities of SMEs. Reliability tests for the measurement scales were conducted to validate the research hypotheses. The collected data were analyzed using quantitative methods to assess the effectiveness of business process redesign through automation and technological adoption. Findings: The study proposes two key models: (1) The parallel distribution channel model, which integrates both traditional and modern channels, enabling SMEs to expand their global customer reach quickly and efficiently; (2) The multi-channel distribution model, which outlines specific tasks necessary for optimizing production management processes and improving customer service. The findings provide a clear roadmap for SMEs to restructure business processes, enhance automation, reduce costs, and optimize data processing, thereby improving their competitive capabilities. Value and limitations: This study offers significant theoretical and practical contributions to the development of distribution strategies and digital transformation for SMEs. However, the research is limited to a small sample within Vietnam, necessitating further studies to validate the findings across different national and industry contexts
- Ấn phẩmModerating the AI revolution: Perceived threat and generative AI implementation in Vietnamese hospitals(2025) Ta, Thi Nguyet Trang; Pham, Chien Thang; Vo, Tam AnGenerative artificial intelligence (AI) has the potential to revolutionize healthcare by improving diagnostic accuracy, streamlining administrative tasks, and enhancing patient communication. However, healthcare professionals often harbor concerns about AI-related job displacement, data security, and ethical implications, creating a perceived AI threat that may impede its widespread adoption. This study integrates the unified theory of acceptance and use of technology with perceived AI threat as both a direct and moderating factor, thereby examining how threat perceptions interact with established adoption drivers in the context of healthcare in Vietnam. A cross-sectional survey was administered to 573 healthcare professionals from major hospitals across Hanoi, Vietnam. Partial least squares structural equation modeling was employed to test the proposed framework, which included performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and perceived AI threat. The results indicate that PE, EE, and SI had significant positive effects on behavioral intention, whereas FC was not a significant predictor. Perceived AI threat demonstrated a strong negative impact on adoption intentions, particularly by moderating and weakening the positive effects of PE and SI. The model explained 79.8 % of the variance in AI adoption intention, suggesting a substantial predictive power. Overall, the findings highlight the importance of addressing existential fears regarding AI in healthcare. Interventions targeting user training, transparent communication, and regulatory support may help mitigate perceived threats and harness AI’s benefits. Interventions targeting user training, transparent communication, and regulatory support may help mitigate perceived threats and harness AI’s benefits.
- Ấn phẩmInformation technology, public audits and the challenges for the state audit office of Vietnam(2025) Nguyen, Thi Phuong; Kend, MichaelPurpose – Information technology (IT) has changed the ways in which state agencies operate in Vietnam. IT audit is a new part of the processes at the State Audit Office in Vietnam, in the wake of both the Viet A corruption scandal and the Vietcombank misstatements case. This exploratory study aims to investigate state auditors’ perceptions related to IT audit in the State Audit Office in Vietnam, focusing on the role that IT audits play in preventing or detecting similar issues to those two cases. Design/methodology/approach – We analyse the perceptions of 22 auditors from the State Audit Office of Vietnam. These 22 auditors participated in semi-structured interviews, and we used the theoretical lens of regulatory spaces in public audits to interpret the data collected. Findings – The resultsindicate that the ITaudit is becoming more relied upon in the State Audit Office of Vietnam after the corruption findings related to Viet A and misstatements in the IT systems of Vietcombank. We find, overall, that more e-services are being provided by government agencies and state-owned enterprises, making IT audits more crucial, given the issuesfrom those two cases. Based on the perceptions of our 22 interviewees, the IT audit at present plays a pivotal role in the public sector of Vietnam. However, there are several challenges auditors currently face in terms of limitations of human resources, infrastructure and audit regulations. Originality/value – The findings of this research may benefit various interested stakeholders, such as regulators, and academic researchers. We discuss how the technology that has emerged in public audits has affected the regulatory space