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
คณะวิศวกรรมศาสตร์
Artificial intelligence for agriculture and environment is a collection of significant models for enviromental friendly Thailand development. The models create with machine learning and deep learning by Near infrared spectroscopy research center for agricultural and food products, including: Determining the nutrient needs (N P K) of durian trees by measuring durian leaves using a non-destructive technique using artificial intelligence, Identification of combustion properties of biomass from fast-growing trees and agricultural residues using non-destructive techniques combined with artificial intelligence, and Evaluation of global warming due to biomass combustion using non-destructive techniques using artificial intelligence. The basic technology used is Near infrared Fourier transform spectroscopy technology which measurement and output display can be done quickly without chemical, no requirement for special expert, and measurement price per sample is very low. But the instrument cannot be produced in Thailand.
คณะเทคโนโลยีการเกษตร
Durian is a crucial economic crop of Thailand and one of the most exported agricultural products in the world. However, producing high-quality durian requires maintaining the health of durian trees, ensuring they remain strong and disease-free to optimize productivity and minimize potential damage to both the tree and its fruit. Among the various diseases affecting durian, foliar diseases are among the most common and rapidly spreading, directly impacting tree growth and fruit quality. Therefore, monitoring and controlling leaf diseases is essential for preserving durian quality. This study aims to apply image analysis technology combined with artificial intelligence (AI) to classify diseases in durian leaves, enabling farmers to diagnose diseases independently without relying on experts. The classification includes three categories: healthy leaves (H), leaves infected with anthracnose (A), and leaves affected by algal spot (S). To develop the classification model, convolutional neural network (CNN) algorithms—ResNet-50, GoogleNet, and AlexNet—were employed. Experimental results indicate that the classification accuracy of ResNet-50, GoogleNet, and AlexNet is 93.57%, 93.95%, and 68.69%, respectively.
คณะเทคโนโลยีการเกษตร
-