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
คณะวิทยาศาสตร์
Albumin Smart Test is an innovative device for screening of kidney disease by mobile phone. The device composes of (1) container and testing device with specific reagents for the albumin detection. (2) The mobile phone, installed with "Albumin smart test" application. The test is started by dropping patient urine and the reagent. Color of the product is occurred and is captured by the application with subsequent evaluation of the albumin amount. The results is displayed on screen within 3 mins. This innovative device is simple, rapid and user-friendly.
คณะเทคโนโลยีการเกษตร
The Public Park Project: Bubbledel Park is a new-style public park located at Suan Phra Nakhon in Lat Krabang District, Bangkok. Designed to be modern and entertaining, the park incorporates the concept of using bubbles to add vibrancy and create a unique connection with nature, unlike any other place.
คณะเทคโนโลยีสารสนเทศ
This research presents a deep learning method for generating automatic captions from the segmentation of car part damage. It analyzes car images using a Unified Framework to accurately and quickly identify and describe the damage. The development is based on the research "GRiT: A Generative Region-to-text Transformer for Object Understanding," which has been adapted for car image analysis. The improvement aims to make the model generate precise descriptions for different areas of the car, from damaged parts to identifying various components. The researchers focuses on developing deep learning techniques for automatic caption generation and damage segmentation in car damage analysis. The aim is to enable precise identification and description of damages on vehicles, there by increasing speed and reducing the work load of experts in damage assessment. Traditionally, damage assessment relies solely on expert evaluations, which are costly and time-consuming. To address this issue, we propose utilizing data generation for training, automatic caption creation, and damage segmentation using an integrated framework. The researchers created a new dataset from CarDD, which is specifically designed for cardamage detection. This dataset includes labeled damages on vehicles, and the researchers have used it to feed into models for segmenting car parts and accurately labeling each part and damage category. Preliminary results from the model demonstrate its capability in automatic caption generation and damage segmentation for car damage analysis to be satisfactory. With these results, the model serves as an essential foundation for future development. This advancement aims not only to enhance performance in damage segmentation and caption generation but also to improve the model’s adaptability to a diversity of damages occurring on various surfaces and parts of vehicles. This will allow the system to be applied more broadly to different vehicle types and conditions of damage inthe future