This project aims to develop a conceptual prototype of a weapon aiming system that simulates an anti-aircraft gun. Utilizing an optical camera, the system detects moving objects and calculates their trajectories in real time. The results are then used to control a motorized laser pointer with two degrees of freedom (DoF) of rotation, enabling it to aim at the predicted position of the target. Our system is built on the Raspberry Pi platform, employing machine vision software. The object motion tracking functionality was developed using the OpenCV library, based on color detection algorithms. Experimental results indicate that the system successfully detects the movement of a tennis ball at a rate of 30 frames per second (fps). The current phase involves designing and integratively testing the mechanical system for precise laser pointer position control. This project exemplifies the integration of knowledge in electronics (computer programming) and mechanical engineering (motor control).
โปรเจคนี้เกิดจากความสนใจในการพัฒนาระบบที่มีการผสมผสานของ Machine Vision และระบบความคุมกลไกมอเตอร์ 2 แกนแบบ Degrees of Freedom(DoF) เพื่อพัฒนาอุปกรณ์ต้นแบบที่สามารถตรวจจับ ติดตาม และเล็งเป้าหมายได้อย่างมีแม่นยำ ซึ่งหวังเป็นอย่างยิ่งว่าโปรเจคนี้จะมีประโยชน์ต่องานในอนาคตต่างๆที่เกี่ยวข้อง ไม่ว่าจะเป็น ทางการทหาร ทางการแพทย์ หรือทางอุตสาหกรรม
คณะทันตแพทยศาสตร์
Aggregatibacter actinomycetemcomitans is a key pathogen in periodontal disease, damaging periodontal ligaments and alveolar bone through biofilm formation. D-LL-31, an engineered antimicrobial peptide, exhibits superior biofilm-killing ability compared to conventional treatments, while DNase I enhances its efficacy by disrupting the biofilm matrix. This study evaluated the combined effects of D-LL-31 and DNase I on A. actinomycetemcomitans biofilms. Results showed that D-LL-31 effectively eradicated biofilms, and its combination with DNase I further enhanced biofilm disruption without cytotoxicity to gingival epithelial cells. The D-LL-31 and DNase I combination shows potential for development as a mouthwash to improve oral health and combat periodontal disease.
คณะเทคโนโลยีการเกษตร
This research aimed 1) to study the problems and needs in the packaging design of the community enterprise group 2) to develop packaging for the community enterprise group 3) to study the satisfaction with the packaging design of the members of the Klong Dan Shrimp Paste Community Enterprise Group 3 Klong Dan Subdistrict, Bang Bo District, Samut Prakan Province, consisting of 9 members The study found that the community enterprise group faced the problem of lacking suitable packaging for souvenirs and had a need to develop packaging that is appropriate for this purpose. The packaging material selected was paper, with a rectangular shape including a handle for portability It can be folded for easy transportation and stacked for storage, while maintaining durability The packaging color used was light brown, and the label color was white The label included the following details: shrimp paste recipe, ingredients, manufacturing and expiration dates, the background of the community enterprise group, a QR code, phone number, a short story, group name, production site, as well as illustrations of the group’s location and red krill. The results of developing packaging for the community enterprise group indicated that the new packaging design increased the credibility of the product, building customer confidence in the product. Regarding the satisfaction with the packaging design among the group members, it was found that Packaging Design 1 had the highest level of satisfaction (x ̅ = 4.57, S.D. = 0.22). Among the aspects, color received the highest satisfaction score (x ̅ = 4.74, S.D. = 0.06), followed by the label (x ̅ = 4.69, S.D. = 0.10), while the lowest was the properties aspect, which was rated at a moderate level of satisfaction (x ̅ = 3.83, S.D. = 1.58), respectively.
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.