"Niyom Thai" represents health-centric footwear adorned with traditional Thai patterns, embodying an innovative approach to sustainable development tailored to the current needs of local communities. These shoes utilize natural materials to mitigate fatigue and integrate safety technologies, including location tracking via a mobile application and heart rate monitoring. This addresses the aspects of convenience and well-being in both daily life and travel
เนื่องจากปัจจัยผู้คนให้ความสนใจเรื่องสุขภาพมากขึ้นเเละรองเท้านับเป็นอีกหนึ่งเทรนด์สุขภาพที่กำลังได้รับความสนใจในยุคนี้ อีกทั้งผ้าไทยจัดเป็นศิลปะ ที่มีเอกลักษณ์เเละความสวยงาม คณะผู้จัดทำจึงมีเเนวคิดที่จะออกแบบลวดลายไทยให้เข้ากับยุคสมัยเเต่ยังคงความเป็นเป็นไทยและนำเทคโนโลยีมาผสมผสานเข้าด้วยกันให้เกิดนวัตกรรมรองเท้าเพื่อสุขภาพลายไทย
คณะบริหารธุรกิจ
BrushXchange is a toothbrush brand dedicated to reducing plastic waste in Thailand by offering toothbrushes made from recycled plastic with replaceable bristles. These products help minimize waste generated by traditional toothbrushes. The design is modern and user-friendly, emphasizing durability, comfort, and affordability, making it appropriate for health-conscious and environmentally aware consumers. The brand aims to drive change in the oral care industry by providing high-quality products at accessible prices. Its marketing strategy focuses on using social media platforms like Instagram and TikTok and collaborating with organizations that promote sustainability. The product is distributed through retail stores such as Lotus’s and Tops. BrushXchange also prioritizes environmental responsibility by using recycled paper packaging and organizing sustainability campaigns. The brand's long-term goal is to become a widely recognized brand image in the eco-friendly toothbrush market in Thailand while encouraging sustainable living habits within society.
คณะวิศวกรรมศาสตร์
The evaluation of mango yield and consumer behavior reflects an increasing awareness of product origins, with a growing demand for traceability to understand how the produce has been cultivated and managed. This study explores the relationship between mango characteristics and cultivation practices before harvest, using location identification to provide insights into these processes. To achieve this, a model was developed to detect and locate mangoes using 2D images via a Deep Learning approach. The study also investigates techniques to determine the real-world coordinates of mangoes from 2D images. The YOLOv8 model was employed for object detection, integrated with camera calibration and triangulation techniques to estimate the 3D positions of detected mangoes. Experiments involved 125 trials with randomized mango positions and camera placements at varying yaw and pitch angles. Parameters extracted from sequential images were compared to derive the actual 3D positions of the mangoes. The YOLOv8 model demonstrated high performance with prediction metrics of Precision (0.928), Recall (0.901), mAP50 (0.965), mAP50-95 (0.785), and F1-Score (0.914). These results indicate sufficient accuracy for predicting mango positions, with an average positional error of approximately 38 centimeters.
คณะวิทยาศาสตร์
This special project aims to develop and compare the performance of gold price prediction models using quantitative variables and news text data. The study incorporates nine key predictors, including Brent crude oil prices, WTI crude oil prices, silver prices, platinum prices, the U.S. Federal Reserve's policy interest rate, the Nikkei 225 index, the Dow Jones Industrial Average, the S&P 500 index, and daily news articles from Bangkok Business News. Relevant news data will be processed using Natural Language Processing (NLP) techniques and integrated with three predictive models: Gradient Boosting, Machine Learning Models, and Regression Analysis. The model performance will be evaluated using three key metrics: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the Coefficient of Determination (R*). This research aims to develop a predictive model that effectively utilizes both quantitative variables and news data to enhance gold price forecasting, providing valuable insights for investors and analysts.