Coffee is a critical agricultural commodity to be used to produce a premium beverage to serve people worldwide. Coffee microbiome turned to be an essential tool to improve the bean quality through the natural fermentation. Therefore, understanding the microbial diversities could create the final product's better quality. This study investigated the natural microbial consortium during the wet process fermentation of coffee onsite in Thailand to characterize the microorganisms involved in correlation toward the biochemical characteristics and metabolic attributes. Roasting is another important step in developing the complex flavor/ aroma that make coffee to be enjoyable. During the roasting process, the beans undergo many complex and alternatively change in the physicochemical properties from the gained substances in the fermentation process. The changing in the formation of the substances responsible for the sensory qualities, physicochemical/ aroma attributes as well as the health benefits of the final product. Using the starter culture could also develop the distinguished characteristics of coffee (Research collaboration with Van Hart company)
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คณะวิศวกรรมศาสตร์
The Thai Sign Language Generation System aims to create a comprehensive 3D modeling and animation platform that translates Thai sentences into dynamic and accurate representations of Thai Sign Language (TSL) gestures. This project enhances communication for the Thai deaf community by leveraging a landmark-based approach using a Vector Quantized Variational Autoencoder (VQVAE) and a Large Language Model (LLM) for sign language generation. The system first trains a VQVAE encoder using landmark data extracted from sign videos, allowing it to learn compact latent representations of TSL gestures. These encoded representations are then used to generate additional landmark-based sign sequences, effectively expanding the training dataset using the BigSign ThaiPBS dataset. Once the dataset is augmented, an LLM is trained to output accurate landmark sequences from Thai text inputs, which are then used to animate a 3D model in Blender, ensuring fluid and natural TSL gestures. The project is implemented using Python, incorporating MediaPipe for landmark extraction, OpenCV for real-time image processing, and Blender’s Python API for 3D animation. By integrating AI, VQVAE-based encoding, and LLM-driven landmark generation, this system aspires to bridge the communication gap between written Thai text and expressive TSL gestures, providing the Thai deaf community with an interactive, real-time sign language animation platform.
วิทยาลัยเทคโนโลยีและนวัตกรรมวัสดุ
The development of skin-on-a-chip models plays a crucial role in research for drug and cosmetic development. Traditional approaches often utilize two-dimensional (2D) methods that rely on culturing cells on flat surfaces, resulting in a lack of complexity in skin structure and realistic cell interactions. Moreover, traditional methods have limitations in mimicking fluid flow and nutrient circulation, which affects the accuracy of pharmaceutical testing and the prediction of drug effects. This has led to the advancement of three-dimensional (3D) skin models using new microfluidic technology, enhancing the realism of skin structure by replicating both the epidermis and dermis layers, as well as simulating fluid flow similar to physiological conditions in the human body. The design of 3D systems allows for more realistic cell arrangement and interactions, enabling better simulation of skin functions and increasing the accuracy in evaluating the effects of various substances on cell responses, including absorption, inflammation, and wound healing. Therefore, the development of three-dimensional (3D) skin models not only addresses the limitations of traditional methods but also represents a significant step forward in creating models that can be effectively applied in drug testing and pharmaceutical product development.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
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