This study aims to identify the toothbrush appearance factors that affect baby boomers purchasing decisions. The research divide into three stages: The first stage is to classify the toothbrush appearance factors through a review of literature, research, and examining toothbrushes currently available on the market, summarizing them as appearance factors. The second stage is to summarize the results of the toothbrush appearance factors to create a multiple-choice questionnaire in three dimensions: purchasing decisions, aesthetics, and functionality. Collecting data from a group of 30 Baby Boomers aged 57-75 years old. The last stage is to summarize the three dimensions of appearance factors affecting baby boomers' toothbrush purchasing decisions and report as percentages and rank them. The research findings indicate that the most significant toothbrush appearance factor is a "Curved handle," accounting for 80%, followed by “Multi-level bristles” at 70%, a "Rubber thumb rest" at 53.3%, "Handle divided into more than two parts" at 50%, and “Offset shape” at 40%, respectively. In terms of the reason for purchasing decision based on various factors are as follows: the curved handle and offset shape give a sense of purchase with its aesthetic, While the selection of multi-level bristles, the Rubber thumb rest, and the handle divided into more than two parts due to functionality.
เทรนด์ผู้สูงอายุเป็นเทรนด์ที่ได้รับความสนใจเป็นอย่างมาก แต่แบรนด์ส่วนใหญ่ยังไม่ปรับตัวเพื่อให้เหมาะกับเทรนด์ผู้สูงอายุอย่างชัดเจน ข้อมูลการออกแบบจากโครงการนี้จึงเป็นประโยชน์ต่อนักออกแบบและธุรกิจที่กำลังสนใจกลุ่มผู้สูงอายุซึ่งกำลังมีสัดส่วนที่มากขึ้นเรื่อยๆในประเทศไทย ผู้วิจัยจึงสนใจทำการเก็บข้อมูลและวิเคราะห์ปัจจัยรูปร่างภายนอกที่มีผลต่อการตัดสินใจซื้อแปรงสีฟันของประชากรกลุ่มเบบี้บูมเมอร์ เพื่อเป็นฐานข้อมูลที่อาจเป็นประโยชน์ต่อผู้ประกอบหรือนักออกแบบต่อไป
คณะวิทยาศาสตร์
In this paper, Vanadium dioxide (VO2) thin-film devices with two different use cases have been redesigned to introduce an asymmetrical resonant cavity structure. The structure is designed with the goal of enhancing the optical performance of the central VO2 layer and has an anti-reflection property in the cold state. The advantages and limitations of such a design are discussed.
คณะวิทยาศาสตร์
Currently, climate change and human activities are causing rapid deterioration of coral reefs worldwide. Monitoring coral health is essential for marine ecosystem conservation. This project focuses on developing an Artificial Intelligence (AI) model to classify coral health into four categories: Healthy, Bleached, Pale, and Dead using Deep Learning techniques. With pre-trained convolutional neural network (CNN) for image classification. To improve accuracy and mitigate overfitting, 5-fold Cross-Validation is employed during training, and the best-performing model is saved. The results of this project can be applied to monitor coral reef conditions and assist marine scientists in analyzing coral health more efficiently and accurately. This contributes to better conservation planning for marine ecosystems in the future.
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.