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.
ปัจจุบันการควบคุมน้ำหนักและสุขภาพเป็นเรื่องที่สำคัญสำหรับหลายคนแต่บ่อยครั้งที่การเลือกกินของหวานหรือขนมทำให้เรารู้สึกว่ากำลังละเมิดแผนควบคุมน้ำหนักของเราและกลัวว่าจะอ้วนหรือมีปัญหาสุขภาพตามมา เพื่อตอบโจทย์นี้ เราจึงได้แรงบันดาลใจในการพัฒนาเครื่องดื่มสมุนไพรในรูปแบบเยลลี่ที่ไม่เพียงแต่มีสรรพคุณในการช่วยควบคุมน้ำหนักและลดความอ้วน แต่ยังช่วยทำให้ร่างกายมีสุขภาพดีขึ้นด้วย โดยไม่ต้องพึ่งผลิตภัณฑ์เสริมหรือยาลดน้ำหนักที่อาจมีผลข้างเคียงที่เป็นอันตราย โดยผลิตภัณฑ์ของเราจะไม่เป็นเพียงแค่เครื่องดื่มสมุนไพรธรรมดา แต่จะถูกพัฒนาให้อยู่ในรูปแบบเครื่องดื่มเยลลี่ที่มีเม็ดสเฟียร์เป็นองค์ประกอบในเครื่องดื่มเพื่อสร้างความเพลิดเพลินในการรับประทาน และสามารถทานได้ง่ายเหมือนกินขนมที่ชื่นชอบ
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.
คณะวิทยาศาสตร์
The current residential solar panels lack an adequate monitoring system, which hinders their optimal utilization. This research aims to design an Internet of Things (IoT) monitoring system and employ machine learning techniques to predict the current and voltage generated by solar panels. Experimental studies have revealed a correlation between dust accumulation and the current output of solar panels. The proposed system facilitates the prediction of the optimal time for cleaning solar panels.
คณะวิทยาศาสตร์
This research will begin with a review of literature and related studies to examine existing technologies and methods for hand gesture recognition and their applications in controlling electronic devices such as drones, robots, and gaming systems. Subsequently, a hand gesture recognition system will be designed and developed using machine learning and computer vision techniques, with a focus on creating an algorithm that operates quickly and accurately, making it suitable for real-time control. The developed system will be tested and refined using various simulated scenarios to evaluate its efficiency and accuracy in diverse environments. Additionally, a user-friendly interface will be developed to ensure accessibility for all user groups. The research will also incorporate qualitative studies to gather feedback from both novice users and experts, which will contribute to further system improvements, ensuring it effectively meets user needs. Ultimately, the findings of this research will lead to the development of a functional prototype for gesture-based control, which can be applied in industries and entertainment. This will contribute to advancements in innovation and new technologies in the future.