A Photographic series that expresses the abstract states of myself, towards the question of existence that results from being surrounded by expectations of both surrender and freedom of expression, this series focuses on my own subjectivities in order to bring back memories of almost forgotten feelings and make them clear once more.
การที่เติบโตมาจากครอบครัวที่คาดหวังในตัวเรา ที่สมาชิกคาดหวังในตัวเราไม่เหมือนกัน ถ้าเราทำแบบใดแบบหนึ่งที่คนใดคนหนึ่งต้องการอีกคนจะไม่พอใจ จนเราเกิดสงสัยว่าเราต้องเป็นแบบไหน เมื่อเข้ามาอยู่ในสังคมใหม่ทำให้เราตั้งคำถามกับตนเองเมื่อเข้าหาผู้คนว่าเราต้องเป็นไปแบบที่เขาต้องการหรือเปล่าเราถึงจะเข้าถึงเขาได้ ทำให้เราสับสนกับตัวเองและต้องสร้างตัวตนใหม่ไปตามที่คนคนนั้นพอใจ จนเราเองเริ่มเกิดคำถามว่าจริงๆแล้วตัวตนของเราจริงๆเป็นแบบไหน
วิทยาเขตชุมพรเขตรอุดมศักดิ์
Durian is an important economic crop in Thailand that is affected by foliar diseases such as rust, leaf blight, and leaf spot. These diseases reduce the quality of the yield and increase management costs. This research focuses on developing AI software for screening durian leaf diseases by applying deep learning technology to classify different types of leaf lesions.
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.
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.