Chia‐Yu Lin
Biographic Data
| ID | 7924441 |
|---|---|
| NAME | Chia‐Yu Lin |
| GIVEN NAMES | Chia‐Yu |
| FAMILY NAME | Lin |
| SIGNATURE | LIN C Y |
| AFFILIATIONS | National Cheng Kung University |
| ORCID | 0000-0001-9591-9260 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Advancing Sustainable Last-Mile Delivery with Collaborative Governance
This study explores the transformation of a parking area into the Low Carbon and Quiet Consolidation Center (LCQCC) in Daxi, Taoyuan City, demonstrating sustainable last-mile logistics through Business Improvement Districts (BIDs). By employing a collaborative governance framework, the LCQCC integrates diverse stakeholder efforts to address urban freight challenges. This research underscores the potential of BIDs to serve as a collaborative platf…
Improving student learning performance in machine learning curricula
Applying Competition-Based Learning to Stimulate Students’ Practical and Competitive AI Ability in a Machine Learning Curriculum
Contribution: This study incorporates competition-based learning (CBL) into machine learning courses. By engaging students in innovative problem-solving challenges within information competitions, revealing that students’ participation in online problem-solving competitions can improve their information technology, and showcase competitions can enhance their competition ability. Background: The CBL model seamlessly integrates project-based learni…
Modeling of Multilayer Multicontent Latent Tree and Its Applications
Latent tree model (LTM) is a probabilistic tree-structured graphical model, which can reveal the hidden hierarchical causal relations among data contents and play a key role in explainable artificial intelligence. However, because current LTM modeling techniques are only suitable for single-content variable, the applications of LTMs are somewhat limited. Toward this end, a multilayer LTM (ML-LTM) is first presented to deal with the hierarchical c…
Cross-Sectional Study on Relationships Among FoMO, Social Influence, Positive Outcome Expectancy, Refusal Self-Efficacy and SNS Usage
The roles of the three determinants of SCT vary by stage of SNS usage. FoMO and refusal self-efficacy are more strongly related with SNS addiction. Further research, particularly longitudinal and intervention studies, is needed to examine the effects of specific factors on SNS addiction
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Cross-Sectional Study on Relationships Among FoMO, Social Influence, Positive Outcome Expectancy, Refusal Self-Efficacy and SNS Usage
The roles of the three determinants of SCT vary by stage of SNS usage. FoMO and refusal self-efficacy are more strongly related with SNS addiction. Further research, particularly longitudinal and intervention studies, is needed to examine the effects of specific factors on SNS addiction
Modeling of Multilayer Multicontent Latent Tree and Its Applications
Latent tree model (LTM) is a probabilistic tree-structured graphical model, which can reveal the hidden hierarchical causal relations among data contents and play a key role in explainable artificial intelligence. However, because current LTM modeling techniques are only suitable for single-content variable, the applications of LTMs are somewhat limited. Toward this end, a multilayer LTM (ML-LTM) is first presented to deal with the hierarchical c…
Improving student learning performance in machine learning curricula
Applying Competition-Based Learning to Stimulate Students’ Practical and Competitive AI Ability in a Machine Learning Curriculum
Contribution: This study incorporates competition-based learning (CBL) into machine learning courses. By engaging students in innovative problem-solving challenges within information competitions, revealing that students’ participation in online problem-solving competitions can improve their information technology, and showcase competitions can enhance their competition ability. Background: The CBL model seamlessly integrates project-based learni…
Advancing Sustainable Last-Mile Delivery with Collaborative Governance
This study explores the transformation of a parking area into the Low Carbon and Quiet Consolidation Center (LCQCC) in Daxi, Taoyuan City, demonstrating sustainable last-mile logistics through Business Improvement Districts (BIDs). By employing a collaborative governance framework, the LCQCC integrates diverse stakeholder efforts to address urban freight challenges. This research underscores the potential of BIDs to serve as a collaborative platf…
Computer Science (4 works) · Psychology (3 works) · Artificial Intelligence (2 works) · Curriculum (2 works) · Machine learning (2 works) · Mathematics education (2 works) · Online Learning and Analytics (2 works) · Pedagogy (2 works) · Addiction (1 work) · Addictive behavior (1 work)