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
With the development of space technology, wide-field sky surveys using telescopes have expanded the range of new data available for time-domain astronomical research. Traditional data analysis methods can no longer respond quickly and accurately enough to the growing volume of data. Thus, classifying time-series data, such as light curves, has become a significant challenge in the era of big data. In modern times, analyzing light curves has become essential for using machine learning techniques to handle and filter through massive amounts of data. Machine learning algorithms can be divided into two categories: shallow learning and deep learning. Numerous researchers have proposed and developed a variety of algorithms for light curve classification. In this study, we experimented with Support Vector Machine (SVM) and XGBoost, which are shallow machine learning algorithms, as well as 1D-CNN and Long Short-Term Memory (LSTM), which are deep learning algorithms, which are branches of deep machine learning, to classify variable stars. The training and testing data used in this study were from the Optical Gravitational Lensing Experiment-III (OGLE-III), consisting of variable star data from the Large Magellanic Cloud (LMC), categorized into five main classes: Classical Cepheids, δ Scutis, eclipsing binaries, RR Lyrae stars, and Long-period variables. The results demonstrate the performance analysis of each machine learning algorithm type applied to light curve data, while also highlighting the accuracy and statistical metrics of the algorithms used in the experiments.
คณะบริหารธุรกิจ
This research aimed to develop the mixed tea from longan peels and seeds. Population studied were longan farmers who planted longan and preserved the longan product in Ampur Wang Nam Yen, Sa Kaeo Province. From the results, it was found that from By-product in the production of dehydrated longan, longan peels and seeds, which can be processed into ready-to-drink powdered tea. This not only helps reduce waste from the production process but also contributes to generating additional income from these by-products.
คณะเทคโนโลยีสารสนเทศ
Traditional methods of public relations and learning often lack engagement and fail to provide users with a deep and immersive experience. Additionally, these methods struggle to reach a wide audience, especially those unable to visit the physical location. This project aims to solve the issues of accessibility and awareness regarding the institution’s Chalermphrakiat Hall and historical exhibition. Utilizing metaverse technology to simulate important locations allows users to explore the site and view key information in a virtual format, thereby enhancing the engagement of students staff alumni and the general public. The metaverse system is developed using Unity, a powerful game engine capable of supporting the creation of metaverse environments. This allows for the creation of an interactive and realistic virtual space. Unity also supports the management of physics, lighting, and sound, further enhancing realism. Additionally, the system is integrated with web browsers using WebGL technology, enabling the project developed in Unity to be accessed directly through a browser. Users can visit and interact with the metaverse environment from anywhere without the need to install additional software. The developers have thus created the metaverse system to provide a realistic and engaging learning experience, enhancing public relations efforts and fostering a strong connection with the institution efficiently.