Victor K. Y. Chan

Orcid: 0000-0002-3755-4512

According to our database1, Victor K. Y. Chan authored at least 11 papers between 2004 and 2023.

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Bibliography

2023
Legal Risks of E-Learning: A case study of the small jurisdiction Macao versus some major jurisdictions.
Proceedings of the 7th International Conference on Education and Multimedia Technology, 2023

Evaluation of e-learning platforms using artificial intelligence (AI) robots: Are the AI robots consistent.
Proceedings of the 7th International Conference on Education and Multimedia Technology, 2023

2022
Convergent Validity of Non-Invigilated, Formative Online Assessments in Business Mathematics Courses and Students' Comparative Performance in Online and Offline Assessments.
Proceedings of the 2022 6th International Conference on Education and Multimedia Technology, 2022

2021
Strengths and Limitations of Using e-Learning for Chinese Learners on Creative Engagement.
Proceedings of the Advances in Web-Based Learning - ICWL 2021, 2021

2019
A Back-End Method Realizing the Ergonomic Advantage of Modularized Battery Systems: ICT Equipment, Electric Vehicles and Beyond.
Proceedings of the Advances in Artificial Intelligence, Software and Systems Engineering, 2019

2007
A Statistical Methodology to Simplify Software Metric Models Constructed Using Incomplete Data Samples.
Int. J. Softw. Eng. Knowl. Eng., 2007

Outlier elimination in construction of software metric models.
Proceedings of the 2007 ACM Symposium on Applied Computing (SAC), 2007

2006
Applying statistical methodology to optimize and simplify software metric models with missing data.
Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), 2006

Application of a Statistical Methodology to Simplify Software Quality Metric Models Constructed Using Incomplete Data Samples.
Proceedings of the Sixth International Conference on Quality Software (QSIC 2006), 2006

2005
Optimizing and Simplifying Software Metric Models Constructed Using Maximum Likelihood Methods.
Proceedings of the 29th Annual International Computer Software and Applications Conference, 2005

2004
Software Effort Prediction Models Using Maximum Likelihood Methods Require Multivariate Normality of the Software Metrics Data Sample: Can Such a Sample Be Made Multivariate Normal?
Proceedings of the 28th International Computer Software and Applications Conference (COMPSAC 2004), 2004


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