School of Applied Digital Technology http://mfuir.mfu.ac.th:80/xmlui/handle/123456789/191 2026-04-19T15:37:08Z 2026-04-19T15:37:08Z Pornthep Phanbua http://mfuir.mfu.ac.th:80/xmlui/handle/123456789/1683 2026-04-09T08:30:53Z 2024-01-01T00:00:00Z

Extra trees model with minority target oversampling for classification of dementia and heart failure in adults Pornthep Phanbua Punnarumol Temdee Thesis (M.Eng.) -- Computer Engineering, School of Applied Digital Technology. Mae Fah Luang University, 2024

2024-01-01T00:00:00Z Wachira Lawpradit http://mfuir.mfu.ac.th:80/xmlui/handle/123456789/1671 2026-04-09T04:52:55Z 2021-01-01T00:00:00Z

A study of brain wave pattern with the touching learning of blinded people Wachira Lawpradit Thongchai Yooyativong Dissertation (Ph.D.) -- Computer Engineering, School of Information Technology. Mae Fah Luang University, 2021

2021-01-01T00:00:00Z Amadou Sanneh http://mfuir.mfu.ac.th:80/xmlui/handle/123456789/1639 2026-03-24T04:51:45Z 2025-01-01T00:00:00Z

Recommended conceptual framework for a community-based flood management system in the Gambia Amadou Sanneh Santichai Wicha Due to its frequency and severe impacts on lives and livelihoods, flooding stands as the primary hazard in the Gambia. This research investigates the standard of the various flood information systems in the Gambia. Both primary and secondary data were used; 385 respondents, including humanitarian workers and community members, administered a questionnaire on the quality of the heterogeneous flood information systems in the Gambia based on the constructs of the Delone and Mclean Information System Success Model (D & M IS Success Model). Data collection was done using Google form and was analysed using SPSS. On average, Humanitarian Workers and Community members were 59% satisfied with the overall quality of the existing flood information Systems. System. Recommendations were made for developing a community-based flood information system, which should empower a multi-sectoral, all-inclusive, and participatory approach for flood risk information management. Based on the findings of this research, a road map was outlined for the development of a Community Centred Flood Information Thesis (M.Sc.) -- Information Technology, School of Applied Digital Technology. Mae Fah Luang University, 2025

2025-01-01T00:00:00Z Mongkhon Sinsirimongkhon http://mfuir.mfu.ac.th:80/xmlui/handle/123456789/1624 2026-02-20T05:56:28Z 2024-01-01T00:00:00Z

Classification model for hypertension with diabetes using gradient boosting and feature engineering Mongkhon Sinsirimongkhon Punnarumol Temdee Hypertension and diabetes present significant global health challenges, impacting individual well-being and economies. Early detection and prevention are pivotal in mitigating their adverse effects. Machine learning is widely applied in various industries and has shown promise in healthcare. While machine learning has shown promise in predicting these conditions separately, limited research has focused on their co-occurrence. This study proposes a novel multiclass-classification approach to predict the coexistence of hypertension and diabetes. The methodology encompasses data collection, preprocessing, model construction, validation, and comparison. Various classifiers were employed, including Decision Tree, Support Vector Machines, Random Forests, Extra Trees, Gradient Boosting, and Long Short-Term Memory. Additionally, CTGAN was utilized to address imbalanced datasets. Results demonstrate the effectiveness of the proposed approach. Gradient Boosting emerged as the most successful among the classifiers, achieving an impressive accuracy of 92.21% and an average AUC-ROC of 96.46%. These findings underscore the potential of machine learning in accurately predicting the concurrent presence of hypertension and diabetes. This study’s significance lies in its contribution to understanding and diabetes. This study’s significance lies in its contribution to understanding and predicting complex health conditions, facilitating early intervention and personalized care strategies. The outcomes suggest a promising avenue for healthcare practitioners to enhance proactive management approaches for individuals with both hypertension and diabetes Thesis (M.Eng.) -- Computer Engineering, School of Applied Digital Technology. Mae Fah Luang University, 2024

2024-01-01T00:00:00Z