Nowadays, assembling a computer is considered something close to many people. Everyone has a chance to catch it. which knowledge of various components of computers and skills in assembling computers. These 2 things mentioned above are things that the general public should have basic knowledge and understanding about. For the self-assembly of computers, We therefore would like to provide knowledge to the general public who wants to learn how to assemble a computer, including information about its components. Through presentation in the form of learning media using VR technology, which will help reduce the problem of errors. and resources used in assembly Ready to create excitement for users by simulating computer assembly for users to interact within the virtual world. experience and provide knowledge before actually putting it into practice with real equipment This project was therefore created for those interested in assembling computers. Especially for people who have no experience in computer assembly. Including people who would like to have the opportunity to try building a computer by themselves.
ในการประกอบคอมพิวเตอร์หนึ่งเครื่องนั้นจำเป็นต้องมีอุปกรณ์จริงในการประกอบ หากไม่มีก็ไม่สามารถทำได้ อีกทั้งผู้ที่จะประกอบไม่มีความรู้อาจส่งผลให้ต้องใช้เวลานานในการประกอบ และ ในการปฏิบัติจริงในบางกรณีอาจส่งผลเสียกับอุปกรณ์กรณีที่ประกอบผิดขั้นตอน ซึ่งโครงงานนี้จะช่วยให้ผู้ใช้สามารถได้ทดลองประกอบคอมพิวเตอร์ได้ด้วยตนเอง พร้อมกับให้ความรู้เบื้องต้น โดยผ่านการนำเสนอในรูปแบบสื่อการสอนด้วยเทคโนโลยีความจริงเสมือน เพื่อให้ผู้ใช้ได้มีปฏิสัมพันธ์ และ ได้จำลองสถานการณ์ ซึ่งจะช่วยให้ผู้ใช้งานสามารถเข้าใจ และ ได้ความรู้ในการประกอบคอมพิวเตอร์มากยิ่งขึ้น ก่อนที่จะนำความรู้ที่ได้ไปปฏิบัติกับอุปกรณ์จริงได้อย่างถูกต้อง
คณะวิศวกรรมศาสตร์
Jaundice, a common condition in infants that results from high bilirubin levels in the blood, often requires early diagnosis and monitoring to prevent severe complications, especially in newborns. Traditional diagnostic methods can be time-consuming and subject to human error. This study proposes an approach for real-time jaundice detection using advanced image processing techniques and machine learning algorithms. By analyzing images captured in RGB color spaces, pixel values are extracted and processed through Otsu’s thresholding and morphological operations to detect color patterns indicative of jaundice. A classifier model is then trained to distinguish between normal and jaundiced conditions, offering an automated, accurate, and efficient diagnostic tool. The system’s potential to operate in real-time makes it particularly suited for clinical settings, providing healthcare professionals with timely insights to improve patient outcomes. The proposed method represents a significant innovation in healthcare, combining artificial intelligence and medical imaging to enhance the early detection and management of jaundice, reducing reliance on manual interventions and improving overall healthcare delivery.
คณะวิทยาศาสตร์
Development of Hand Cream from Murraya Extract Using an Eco-Friendly Extraction Process. This research focuses on extracting active compounds from Murraya paniculata using a water-based, environmentally friendly method. The extract exhibits outstanding antibacterial properties and anti-oxidant. It is incorporated into a hand cream formulation.
คณะวิทยาศาสตร์
In today’s rapidly expanding e-commerce environment, the massive volume of product reviews makes it crucial to summarize user opinions in a way that is both comprehensible and practically applicable. This research presents a system for analyzing product reviews using Aspect-Based Sentiment Analysis (ABSA), a Natural Language Processing (NLP) technique that identifies key aspects of a review (such as shipping, product quality, and packaging) and evaluates the sentiment (positive, negative, or neutral) associated with each aspect, allowing both consumers and merchants to gain more efficient access to in-depth insights. This project focuses on developing AI for Thai-language ABSA by utilizing WangchanBERTa, a model trained on Thai data, and comparing it with various standard approaches such as TF-IDF + Logistic Regression, Word2Vec + BiLSTM, and Multilingual BERT (mBERT/XLM-R) to assess their performance in terms of accuracy, speed, and resource usage. Additionally, a dashboard visualization is provided to help users quickly grasp review trends. The expected outcome is to create an AI tool that can be practically employed in the e-commerce industry, enabling consumers to make easier purchasing decisions and assisting merchants in effectively improving their products and services.