The forest firefighting suit consists of the following components and uses: The forest firefighting suit is designed and developed to be suitable for the behavior of the officers and the conditions of the work area, consisting of a shirt and pants. The material used in the sewing of the suit is aramid fabric, which has the property of being able to prevent the spread of fire, to prevent the officers from burning while performing their duties in the event that the forest fire spreads close to them, which is different from the current suits that cannot prevent fires. The shirt is designed with a mesh on the side of the body to release internal heat so that air can circulate well. The sleeves at the elbows have a support point to prevent contact with the ground or obstacles. The collar has a slot for a portable fan and a fan air circulation channel on the back, which can be turned on while performing forest firefighting duties, helping to prevent the body temperature from getting too hot, reducing the risk of heatstroke. When the fan battery runs out, it can be removed for charging and put back in when needed. The pants are designed with mesh on the inside or in blind spots to release internal heat so that air can circulate well. The pants at the knees have a support point to prevent contact with the ground or obstacles. The forest firefighting suit, consisting of a shirt and pants, has been designed and developed to be able to be produced domestically, reducing imports from abroad
ปัญหาไฟป่าที่ทวีความรุนแรงขึ้นเรื่อย ๆ ส่งผลกระทบในหลายๆด้านโดยเฉพาะผู้ที่พักอาศัยบริเวณใกล้ไฟป่าต้องเผชิญกับปัญหาด้านสุขภาพที่เกิดจากฝุ่น PM2.5 ประกอบกับทางภาครัฐยังขาดแคลนบุคลากรเจ้าหน้าที่ ที่มีความชำนาญในการดับไฟป่า รวมถึงยังขาดชุดดับไฟป่าที่เป็นชุดสามารถกันไฟได้เหมาะสมต่อการดับไฟ เนื่องจากในปัจจุบันชุดที่เจ้าหน้าที่อุทยาน และเจ้าหน้าที่ศูนย์ดับไฟป่า สวมใส่ในการปฏิบัติหน้าที่นั้นเป็นชุดลายพลาง กางเกงกับเสื้อแบบทั่วไป ไม่สามารถปกป้อง หรือกันไฟเมื่อไฟมาถึงระยะประชิดตัวได้ในระดับที่เหมาะสม ซึ่งสาเหตุนี้ส่งผลให้เจ้าหน้าที่บางรายได้รับอันตรายถึงขั้นไฟคลอกได้ ผู้วิจัยจึงได้เล็งเห็นถึงความสำคัญในการออกแบบและพัฒนาชุดดับไฟป่า เพื่อให้เจ้าหน้าที่อุทยาน และเจ้าหน้าที่ศูนย์ดับไฟป่า สามารถสวมใส่ปฏิบัติหน้าที่ได้อย่างปลอดภัย ช่วยลดอุปสรรคในการดับไฟป่าและปฏิบัติหน้าที่ได้อย่างเต็มประสิทธิภาพมากยิ่งขึ้น
คณะเทคโนโลยีสารสนเทศ
Facial Expression Recognition (FER) has attracted considerable attention in fields such as healthcare, customer service, and behavior analysis. However, challenges remain in developing a robust system capable of adapting to various environments and dynamic situations. In this study, the researchers introduced an Ensemble Learning approach to merge outputs from multiple models trained in specific conditions, allowing the system to retain old information while efficiently learning new data. This technique is advantageous in terms of training time and resource usage, as it reduces the need to retrain a new model entirely when faced with new conditions. Instead, new specialized models can be added to the Ensemble system with minimal resource requirements. The study explores two main approaches to Ensemble Learning: averaging outputs from dedicated models trained under specific scenarios and using Mixture of Experts (MoE), a technique that combines multiple models each specialized in different situations. Experimental results showed that Mixture of Experts (MoE) performs more effectively than the Averaging Ensemble method for emotion classification in all scenarios. The MoE system achieved an average accuracy of 84.41% on the CK+ dataset, 54.20% on Oulu-CASIA, and 61.66% on RAVDESS, surpassing the 71.64%, 44.99%, and 57.60% achieved by Averaging Ensemble in these datasets, respectively. These results demonstrate MoE’s ability to accurately select the model specialized for each specific scenario, enhancing the system’s capacity to handle more complex environments.
คณะวิศวกรรมศาสตร์
This research suggested natural hemp fiber-reinforced ropes (FRR) polymer usage to reinforce recycled aggregate square concrete columns that contain fired-clay solid brick aggregates in order to reduce the high costs associated with synthetic fiber-reinforced polymers (FRPs). A total of 24 square columns of concrete were fabricated to conduct this study. The samples were tested under a monotonic axial compression load. The variables of interest were the strength of unconfined concrete and the number of FRRlayers. According to the results, the strengthened specimens demonstrated an increased compressive strength and ductility. Notably, the specimens with the smallest unconfined strength demonstrated the largest improvement in compressive strength and ductility. Particularly, the compressive strength and strain were enhanced by up to 181% and 564%, respectively. In order to predict the ultimate confined compressive stress and strain, this study investigated a number of analytical stress–strain models. A comparison of experimental and theoretical findings deduced that only a limited number of strength models resulted in close predictions, whereas an even larger scatter was observed for strain prediction. Machine learning was employed by using neural networks to predict the compressive strength. A dataset comprising 142 specimens strengthened with hemp FRP was extracted from the literature. The neural network was trained on the extracted dataset, and its performance was evaluated for the experimental results of this study, which demonstrated a close agreement.
คณะเทคโนโลยีสารสนเทศ
This research presents the development of an AI-powered system designed to automate the identification and quantification of dental surgical instruments. By leveraging deep learning-based object detection, the system ensures the completeness of instrument sets post-procedure. The system's ability to process multiple images simultaneously streamlines the inventory process, reducing manual effort and potential errors. The extracted data on instrument quantity and type can be seamlessly integrated into a database for various downstream applications.