
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.
In one, docking is defined as “when one incoming spacecraft rendezvous with another spacecraft and flies a controlled collision trajectory in such a manner to align and mesh the interface mechanisms”, and defined docking as an on-orbital service to connect two free-flying man-made space objects. The service should be supported by an accurate, reliable, and robust positioning and orientation (pose) estimation system. Therefore, pose estimation is an essential process in an on-orbit spacecraft docking operation. The position estimation can be obtained by the most well-known cooperative measurement, a Global Positioning System (GPS), while the spacecraft attitude can be measured by an installed Inertial Measurement Unit (IMU). However, these methods are not applicable to non-cooperative targets. Many studies and missions have been performed by focusing on mutually cooperative satellites. However, the demand for non-cooperative satellites may increase in the future. Therefore, determining the attitude of non-cooperative spacecrafts is a challenging technological research problem that can improve spacecraft docking operations. One traditional method, which is based on spacecraft control principles, is to estimate the position and attitude of a spacecraft using the equations of motion, which are a function of time. However, the prediction using a spacecraft equation of motion needs support from the sensor fusion to achieve the highest accuracy of the state estimation algorithm. For non-cooperative spacecraft, a vision-based pose estimator is currently developing for space application with a faster and more powerful computational resource.

คณะสถาปัตยกรรม ศิลปะและการออกแบบ
When it comes to the general perception of death, it is often seen as something negative or inauspicious. However, the end or death of someone can sometimes be the beginning of change, influencing thoughts, lifestyles, and attitudes in a positive way for those around them. For students aged 13-18, accessing and understanding this topic remains a challenge. Most available information is often presented in complex forms that are difficult for young people to grasp. Moreover, teaching materials in schools often lack creativity and engagement, leading to a decline in students’ interest in this subject. To address this issue, a website has been designed as an accessible and creative resource. It aims to deepen young people's understanding of the impact of actions and the death of individuals on the world they live in, while inspiring them to become part of creating positive change for the future.

คณะอุตสาหกรรมอาหาร
The "PRIVARY" product is an innovative herbal jelly beverage designed to support weight management and promote health through the benefits of four Thai herbs: roselle, safflower, chrysanthemum, and bitter melon. These herbs are rich in active compounds such as flavonoids, beta-carotene, and anthocyanins, which help reduce blood lipids, prevent inflammation, and exhibit antioxidant properties. The product emphasizes convenience and caters to health-conscious consumers using advanced production techniques like Inverse and External Gelation to create spheres encapsulating key bioactive compounds. Additionally, the product aligns with sustainability goals by enhancing the value of Thai herbs and supporting local communities.

คณะเทคโนโลยีสารสนเทศ
The process of treating cancer patients in the chemotherapy department at Chonburi Cancer Hospital is complicated and inconvenient due to the procedure of submitting blood test results through the personal LINE application of medical staff, which hinders workflow efficiency. Therefore, the researcher has developed a cancer patient management and tracking program in the form of a web-based application and LINE LIFF (LINE Front-end Framework) application to facilitate both medical personnel and patients. The web-based application is designed for medical personnel to monitor, schedule, and collect patient data, while the LINE application is designed for patients to submit blood test results, view appointment schedules, record symptoms after chemotherapy, log their weekly weight, and access a chatbot for consultation. This system is developed based on client-server technology, which enhances data analysis efficiency and supports automated treatment planning. As a result, the cancer treatment process becomes faster, more modern, and more efficient.