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
This special problem aims to compare the performance of machine learning methods in time series forecasting using lagged time periods as independent variables. The lagged periods are categorized into three groups: lagged by 10 units, lagged by 15 units, and lagged by 20 units. The study employs four machine learning methods: Decision Tree (DT), Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The time series data simulated as independent variables diverse including characteristics: Random Walk data, Trending data, and Non-Linear data, with sample sizes of 100, 300, 500, and 700. The research methodology involves splitting the data into 90% for training and 10% for testing. Simulations and analysis are performed using the R programming language, with 1,000 iterations conducted. The results are evaluated based on the average mean squared error (AMSE) and the average mean absolute percentage error (AMAPE) are calculated to identify the best performing method. The research findings revealed that for Random Walk data, the best performing methods are Random Forest and Support Vector Machine. For Trend data, the best performing methods are Random Forest. For Non-Linear data, the best performing methods are Support Vector Machine. When tested with real-world data, the results show that for the Euro-to-Thai Baht exchange rate, the best methods are Random Forest and Support Vector Machine. For the S&P 500 Index in USD, the best performing methods are Random Forest. For the Bank of America Corp Index in USD, the best performing methods are Support Vector Machine.
วิทยาลัยเทคโนโลยีและนวัตกรรมวัสดุ
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คณะสถาปัตยกรรม ศิลปะและการออกแบบ
Koh Tao, a picturesque island in Thailand, is famous for its breathtaking coral reefs and vibrant marine life, attracting diving enthusiasts from all over the world. Despite its natural beauty, the island currently lacks innovative accommodations that enhance the visitor experience and promote environmental sustainability. This project proposes the development of a unique four-star floating resort with underwater villas, designed to offer an extraordinary lodging experience that fosters a deeper connection with the marine environment. By incorporating sustainable practices into the resort's design and operations, the project addresses the growing demand for eco-friendly tourism in the region. The floating resort concept aims not only to provide guests with an immersive experience but also to raise awareness about marine conservation. Through eco-friendly design and operations, the resort seeks to set a benchmark for sustainable tourism in Koh Tao, showcasing how accommodations can align with environmental stewardship, benefiting both the local ecosystem and tourism.