Anantavrasilp, Isara
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Item type:Publication, Robust image encryption method with cipher stream chaining process(2019-02-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The effect of sizes of the feature sets on intrusion detection performances(2017-12-28) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Hybrid Multi-Model Fuzzy Ensemble Approach for Cardiovascular Diseases Detection(2023-01-01); Thiemjarus, SurapaTimely detection of cardiovascular diseases (CVDs) is crucial to reducing mortality rates. Recent advances in artificial intelligence (AI) and machine learning (ML) models for CVD detection often suffer from low model performance and hence lower accuracy and practicality of early CVD detection. In this study, we propose a novel hybrid ensemble learning framework that combines multiple ML algorithms and a fuzzy expert system to improve CVD diagnosis and prediction accuracy. We evaluate our proposed method on two standard datasets, namely the UCI Cleveland and Framingham, and compare it with four popular ensemble algorithms, namely Random Forest, Gradient Boosting, eXtreme Gradient Boosting, and Adaptive Boosting. Our results demonstrate that the proposed ensemble learning framework achieves higher accuracies of 91.2% (UCI Cleveland) and 91.7% (Framingham), surpassing existing algorithms by 3.3% and 8.8%, respectively. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Locally Designed Campus Smart Bike Sharing System: Lessons Learned and Design Optimization for Thailand(2020-04-01); Bike-sharing systems have been widely implemented in around 700 cities worldwide since the 2000s. The quick expansion is due to the growing concerns over environmental impacts and climate change problems. Bicycles are deemed to be a promising mode of transportation for achieving urban sustainability and sustainability in higher education. Sustainable transportation is an important factor in achieving the UN's Sustainable Development Goals. In Thailand, a bike-sharing service was first launched in Bangkok in 2012. However, bike-sharing in Thailand heavily relied on systems designed and operated by international companies. Many systems have not been very successful and some were discontinued. We discuss lessons learned from a locally designed bike-sharing system and its optimization for a Thai university. A pilot-scale of public bicycles was launched and over 24,000 trips were observed in six months. Most trips were 0-10 minutes and peak hours were in the morning, which means most students picked up the public bike on the last-mile based on study timetable. From heat maps of bicycle usage, nearly educational buildings and connecting transit points had the highest departure and arrival rates. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Development of locally designed smart bike-sharing system on Thai campus: Lessons learnt of a pilot-scale study(2020-01-01); Campus-wide bike-sharing program is one of the solutions for achieving sustainability in higher education. It also contributes to the UN's Sustainable Development Goals (SDGs). Smart bike-sharing systems have been implemented in some Thai cities and Thai universities since 2012. The systems were provided by foreign companies and developers. A locally designed smart bike-sharing system have been developed and pilot-scale tested at a Thai university. Many problems were found throughout the test-period, while design changes and application modifications were conducted to address the issues. The changes were done to make the system appropriate for the context of Thai university and users' demands. This paper discusses the development process and lessons learnt from this locally designed system. The results can be used by developers and software designers of bike-sharing industry to provide better design and implementation for Thailand market.