This work got the idea of bringing the car culture of Thai teenagers to present in a new way through our perspective. Create characters and bring various elements within the culture to combine with what we like. Whether it's stickers, posters and band shirts with acrylic paint techniques.
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คณะแพทยศาสตร์
Migraine, a prevalent neurological disorder, is the third most common disease globally, causing significant health and financial burdens. It has four stages: prodrome, aura, headache, and postdrome. The prodrome (also known as premonitory) stage is crucial as it precedes the headache by up to 72 hours. Taking medication during the premonitory peroid has shown to prevent the headache phase . However, the symptoms of premonitory period lack specificity, making it difficult for patients to know if they’re experiencing premonitory symptoms. Calcitonin-gene related peptide (cGRP),is a protein that plays a key role in migraine pathogenesis and studies found that salivary cGRP levels increase during the premonitory stage. This study aims to develop and evaluate a lateral flow immunoassay kit for detecting salivary cGRP levels in migraine patients during the prodrome stage. It can serve as a confirmation tool for premonitory symptoms.
คณะเทคโนโลยีการเกษตร
The development of a board game to enhance cooking skills focuses on a popular and well-known dish—burgers. This study integrates learning with interactive gameplay, allowing players to gain knowledge about burgers, including their ingredients, preparation methods, and even the basics of running a burger business. Through hands-on activities and engaging game mechanics, players can develop both their culinary skills and entrepreneurial mindset while enjoying the fun and immersive experience of the board game.
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.