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
A smartphone-based colorimetric sensor for quantitative detection of pyridoxine (Vitamin B6, VB-6) in functional drink samples has been realized by developing double layer hydrogel. Electrostatic interaction initiates the cross-linking and produces double layer hydrogel.
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.
คณะวิศวกรรมศาสตร์
This cooperative education report presents a project for developing a Distributed Control System (DCS) for boilers in a sugar factory. The objective is to enhance the control system for boilers 1-8 to operate cohesively within the DCS framework provided by ABB, utilizing the ABB Ability™ System 800xA software. The overall functionality of the system involves creating a control program that begins with the utilization of bagasse, a byproduct from the sugar extraction process, as fuel for the boiler. The program manages various operations of the boiler, including the intake of air into the combustion chamber, the internal functioning of the boiler, and the treatment of flue gases before their release into the atmosphere. The project encompasses the development of the DCS program, the design and creation of HMI display graphics, the study and design of the boiler control system, the documentation of the project, and the control processes utilizing the ABB Ability™ System 800xA software, culminating in the operational outcomes.