This research investigates active packaging films made from polyvinyl alcohol (PVA) and nanocellulose fibers (NFC), incorporating silver nanoparticles (AgNPs) synthesized from Terminalia chebula extract, which possesses antibacterial and antifungal properties. The developed films were tested for their mechanical properties, microbial inhibition, and biodegradability. The results showed that the addition of AgNPs from Terminalia chebula enhanced product protection and effectively extended the shelf life of strawberries while being environmentally friendly.
บรรจุภัณฑ์แอคทีฟถูกพัฒนาเพื่อปกป้องผลิตภัณฑ์และยืดอายุการเก็บรักษา โดยสามารถแลกเปลี่ยนแก๊สได้อย่างมีประสิทธิภาพ ฟิล์มที่ผลิตจากพอลิไวนิลแอลกอฮอล์ (PVA) มีความยืดหยุ่น แข็งแรง และสามารถละลายน้ำได้ อีกทั้งยังสามารถเติมอนุภาคซิลเวอร์นาโน (AgNPs) เพื่อเพิ่มคุณสมบัติในการยับยั้งจุลินทรีย์ สมอไทย (Terminalia chebula) ซึ่งอุดมไปด้วยสารต้านเชื้อแบคทีเรียและเชื้อรา ถูกนำมาใช้ในการสังเคราะห์ AgNPs เพื่อนำไปประยุกต์ใช้กับฟิล์มบรรจุภัณฑ์แอคทีฟ งานวิจัยนี้จึงศึกษาคุณสมบัติของฟิล์มที่พัฒนาขึ้นสำหรับการเคลือบสตรอเบอร์รีเพื่อยืดอายุการเก็บรักษาอย่างมีประสิทธิภาพ
คณะแพทยศาสตร์
This study explores the application of deep convolutional neural networks (CNNs) for accurate pill identification, addressing the limitations of traditional human-based methods. Using a dataset of 1,250 images across 10 household remedy drugs, various CNN architectures, including YOLO models, were tested under different conditions. Results showed that natural lighting was optimal for imprinted pills, while a lightbox improved detection for plain pills. The YOLOv5-tiny model demonstrated the best detection accuracy, and efficientNet_b0 achieved the highest classification performance. While the model showed strong results, its generalization is limited by sample size and drug variability. Nonetheless, this approach holds promise for enhancing medication safety and reducing errors in outpatient care.
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 research focuses on the design and development of a high-power converter to regulate energy supply from solar cells (Photovoltaic: PV) to a hydrogen production unit (Electrolyzer), which is a crucial component in advancing renewable energy in alignment with the RE100 initiative. Specifically, this study targets Green Hydrogen, which is generated through the water electrolysis process using clean energy from solar cells, ensuring zero emissions and environmental sustainability. The proposed converter includes of a Three-Level NPC Inverter, transformer, Full-Bridge Rectifier, and LC filter to enhance the power quality supplied to the electrolyzer. The system's design and simulation were conducted using MATLAB and Simulink to evaluate circuit performance and analyze operational efficiency. Simulation was conducted using MATLAB and Simulink to evaluate circuit performance and analyze operational efficiency. Additionally, a microcontroller-based control system is integrated with a gate driver circuit to optimize the electrolysis process by reducing power losses. This proposed converter effectively converts PV energy into suitable voltage and current levels for the electrolyzer while maintaining high hydrogen production efficiency.