A commercial architecture consists of a community mall and home offices. The project’s main concept concerns the lack of activities around the given site. The project tackles the main issues of underdevelopment by aiming to bring back the liveliness of the local people back by integrating work-life symbolism and natural spaces, resulting in an interesting design.
โปรเจคตามหลักสูตรออกแบบสถาปัตยกรรม 4 ชั้นปีที่ 3 เพื่อเปิดโอกาสให้นักศึกษาได้แสดงความรู้ ความสามารถ รวมถึงความคิดสร้างสรรค์ด้านการออกแบบ สําหรับการลงทุนเพื่อการพัฒนาที่ดิน ให้เป็น พื้นที่เชิงพาณิชย์พร้อมบ้านพักอาศัย ให้มีความพิเศษและน่าสนใจ ตามแนวคิด Concept Green & Digital
คณะเทคโนโลยีสารสนเทศ
Currently, the issue of developmental writing disabilities in children is a matter of great importance for school-age children. Diagnosing whether a child has developmental writing disabilities relies on writing skill assessments, which are administered to those seeking diagnosis and evaluated by medical professionals or experts. However, there are still limitations in the diagnostic process, which depends heavily on expert physicians, leading to a high demand for human resources. To address this, we have developed a method for scoring writing skill assessments using image processing technology, based on existing scoring criteria. Currently, three criteria are used for scoring: writing position, article format, and copying speed. We have also created a web application to make the system more accessible and easier to use.
วิทยาลัยนวัตกรรมการผลิตขั้นสูง
A child manikin for Cardiopulmonary Resuscitation (CPR) training includes the trachea mechanism, neck mechanism, lung mechanism, heart pump mechanism, artificial skin, and sensor system. All components work together to function similar to a real child. It can be used to practice heart pumping and resuscitation. The manikin has been designed and verified by resuscitation experts. It has a system to evaluate the accuracy of the training and display the results on the computer for real-time monitoring.
คณะวิศวกรรมศาสตร์
This thesis presents the application of deep learning for object classification. The selected deep learning architectures studied include Convolutional Neural Networks (CNN) and ResNet18. It covers data preparation, feature extraction, parameter tuning for accuracy comparison, and performance evaluation of the selected models. The aim is to propose an efficient model for use in devices that assist visually impaired individuals in classifying indoor objects and providing sound alerts.