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
คณะแพทยศาสตร์
This study explores the application of deep convolutional neural networks (CNNs) for accurate pill identification, addressing the limitations of traditional human-based methods. Using a dataset of 1,250 images across 10 household remedy drugs, various CNN architectures, including YOLO models, were tested under different conditions. Results showed that natural lighting was optimal for imprinted pills, while a lightbox improved detection for plain pills. The YOLOv5-tiny model demonstrated the best detection accuracy, and efficientNet_b0 achieved the highest classification performance. While the model showed strong results, its generalization is limited by sample size and drug variability. Nonetheless, this approach holds promise for enhancing medication safety and reducing errors in outpatient care.
คณะวิศวกรรมศาสตร์
Nowadays, consumers may have experienced situations where they don't know which product to use based on their skin problems, the product they use doesn't give the desired results, the product is not worth the price, allergic to certain chemicals in the product ,or use multiple products and have ingredients that should not be used together leading to irritation. For this reason, we develop an application to analyze skin care product ingredients to solve such problems. This allows consumers to correctly understand information about the ingredients in products and know which products they should use according to their skin problems without having to rely on chemical knowledge and get products that are the best value for money. The project has integrated software knowledge to develop an application for analyzing skin care product ingredients. To find and recommend suitable skin care products to consumers. The information on various important ingredients has been collected from reliable articles and research.
คณะเทคโนโลยีการเกษตร
This study aimed to investigate the efficacy of lime containing more than 50% calcium oxide and not less than 29% magnesium oxide in enhancing water alkalinity for Pacific White Shrimp (Litopenaeus vannamei) aquaculture. The experiment was conducted at concentrations of 0, 5, 10, 15, and 20 ppm over a 48-hour period, with data collected at 0, 3, 6, 12, 24, 36, and 48 hours. Results demonstrated that lime exhibited high dissolution efficiency (65-86%) within the first hour and reached complete dissolution (98.5-98.6%) within 6 hours. The pH values initially increased proportionally with lime concentration, gradually decreased during 3-12 hours, before stabilizing. Total alkalinity showed significant increase during the first 3-6 hours and remained stable until the end of the experiment. Statistical analysis revealed that both concentration and time significantly affected all parameters (p < 0.001)