Expanding from a public park design project to a campus design on an area of over 50 rai in Ang Sila Subdistrict, Mueang District, Chonburi Province, to serve as both an educational institution and a place for relaxation and learning for the surrounding people.
การพัฒนาพื้นที่แห่งนี้ให้กลายเป็นCampus Park เพื่อเป็นพื้นที่พักผ่อนและแลกเปลี่ยนความรู้เกี่ยวกับระบบนิเวศชายหาดของจังหวัดชลบุรี
คณะเทคโนโลยีสารสนเทศ
This report is part of applying the knowledge gained from studying machine learning models and methods for developing a predictive model to identify customers likely to cancel their credit card services with a bank. The project was carried out during an internship at a financial institution, where the creator developed a model to predict customers likely to churn from their credit card services using real customer data through the organization's system. The focus was on building a model that can accurately predict customer churn by selecting features that are appropriate for the prediction model and the unique characteristics of the credit card industry data to ensure the highest possible accuracy and efficiency. This report also covers the integration of the model into the development of a website, which allows related departments to conveniently use the prediction model. Users can upload data for prediction and receive model results instantly. In addition, a dashboard has been created to present insights from the model's predictions, such as identifying high-risk customers likely to cancel services, as well as other important analytical information for strategic decision-making. This will help support more efficient marketing planning and customer retention efforts within the organization.
คณะวิศวกรรมศาสตร์
This capstone project develops an AI-powered chatbot to address cybersecurity vulnerabilities, leveraging the Common Vulnerabilities and Exposures (CVE) system and the Common Vulnerability Scoring System (CVSS). The chatbot will provide accessible and informative support for understanding and mitigating these vulnerabilities, potentially leading to significant improvements in cybersecurity practices.
คณะวิทยาศาสตร์
Cancer remains a major global health challenge as the second-leading cause of human death worldwide. The traditional treatments for cancer beyond surgical resection include radiation and chemotherapy; however, these therapies can cause serious adverse side effects due to their high killing potency but low tumor selectivity. The FDA approved monoclonal antibodies (mAbs) that target TIGIT/PVR (T-cell immunoglobulin and ITIM domain/poliovirus receptor) which is an emerging immune checkpoint molecules has been developed; however, the clinical translation of immune checkpoint inhibitors based on antibodies is hampered due to immunogenicity, immunological-related side effects, and high costs, even though these mAbs show promising therapeutic efficacy in clinical trials. To overcome these bottlenecks, small-molecule inhibitors may offer advantages such as better oral bioavailability and tumor penetration compared to mAbs due to their smaller size. Here, we performed structure-based virtual screening of FDA-approved drug repertoires. The 100 screened candidates were further narrowed down to 10 compounds using molecular docking, with binding affinities ranging from -9.152 to -7.643 kcal/mol. These compounds were subsequently evaluated for their pharmacokinetic properties using ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, which demonstrated favorable drug-like characteristics. The lead compounds will be further analyzed for conformational changes and binding stability against TIGIT through molecular dynamics (MD) simulations to ensure that no significant conformational changes occur in the protein structure. Collectively, this study represents the potential of computational methods and drug repurposing as effective strategies for drug discovery, facilitating the accelerated development of novel cancer treatments.