Development of Hand Cream from Murraya Extract Using an Eco-Friendly Extraction Process. This research focuses on extracting active compounds from Murraya paniculata using a water-based, environmentally friendly method. The extract exhibits outstanding antibacterial properties and anti-oxidant. It is incorporated into a hand cream formulation.
ต้นแก้ว (Murraya paniculata) เป็นพืชสมุนไพรที่มีการใช้ประโยชน์ในด้านการแพทย์พื้นบ้านและมีรายงานถึงคุณสมบัติทางชีวภาพ เช่น ฤทธิ์ต้านแบคทีเรียและต้านอนุมูลอิสระ อย่างไรก็ตาม การนำสารสกัดจากต้นแก้วมาใช้ในผลิตภัณฑ์เครื่องสำอางยังมีข้อจำกัดด้านวิธีการสกัดที่ปลอดภัยและเป็นมิตรต่อสิ่งแวดล้อม โครงการนี้จึงมุ่งเน้นการพัฒนากระบวนการสกัดด้วยน้ำ และศึกษาคุณสมบัติเพื่อนำไปพัฒนาเป็นครีมบำรุงมือที่มีประสิทธิภาพและปลอดภัยต่อผู้ใช้
คณะเทคโนโลยีการเกษตร
Currently, Thailand is facing the issue of an aging agricultural workforce and a shortage of labor. The hiring process for agricultural workers is primarily based on word-of-mouth within a limited, narrow area. This may have indirect negative effects in various aspects, such as the lack of basic selection criteria (experience, skills), budget control, and hiring processes. As a result, the idea of creating a job platform specifically for farmers was conceived.Currently, Thailand is facing the issue of an aging agricultural workforce and a shortage of labor. The hiring process for agricultural workers is primarily based on word-of-mouth within a limited, narrow area. This may have indirect negative effects in various aspects, such as the lack of basic selection criteria (experience, skills), budget control, and hiring processes. As a result, the idea of creating a job platform specifically for farmers was conceived.
คณะครุศาสตร์อุตสาหกรรมและเทคโนโลยี
This project presents the development of a single-frequency GPS-based total electron content measurement tool. It applies theories related to total electron content in the ionospheric layer and the measurement of total electron content using GPS time delay to design the single-frequency GPS total electron content measurement tool. The tool consists of an antenna, a single-frequency GPS satellite receiver, a data processing unit for evaluating and calculating total electron content, and a display unit for showing total electron content data. The performance of the single-frequency GPS total electron content measurement tool is tested by comparing it with total electron content data obtained from the International Reference Ionosphere (IRI) model, which is a global reference model for electron content. The tool is also put to practical use. The results of the comparison and practical applications conclude that the single-frequency GPS-based total electron content measurement tool can be effectively utilized, with the difference from the IRI model being 50 TECU
วิทยาลัยอุตสาหกรรมการบินนานาชาติ
The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires an accurate, reliable, and robust object recognition algorithm. Vision-based guided spacecraft relative motion during close-proximity maneuvers has been consecutively applied using dynamic modeling as a spacecraft on-orbit service system. This research constructs a vision-based pose estimation model that performs image processing via a deep convolutional neural network. The pose estimation model was constructed by repurposing a modified pretrained GoogLeNet model with the available Unreal Engine 4 rendered dataset of the Soyuz spacecraft. In the implementation, the convolutional neural network learns from the data samples to create correlations between the images and the spacecraft’s six degrees-of-freedom parameters. The experiment has compared an exponential-based loss function and a weighted Euclidean-based loss function. Using the weighted Euclidean-based loss function, the implemented pose estimation model achieved moderately high performance with a position accuracy of 92.53 percent and an error of 1.2 m. The in-attitude prediction accuracy can reach 87.93 percent, and the errors in the three Euler angles do not exceed 7.6 degrees. This research can contribute to spacecraft detection and tracking problems. Although the finished vision-based model is specific to the environment of synthetic dataset, the model could be trained further to address actual docking operations in the future.