Telemedicine App is a prototype system that provides basic functions for communicating diagnosis between patients, nurses, and doctors via video conferencing. The system is contains different diagnostic room and it allows recording patient information. It is an open source for others to extend for further development.
เพิ่มประสิทธิภาพในการเข้าถึงการรักษา ผู้ป่วยที่อยู่ห่างไกลจากโรงพยาบาลหรือสถานพยาบาล สามารถเข้าถึงการตรวจรักษาและได้รับการวินิจฉัยจากแพทย์ผู้เชี่ยวชาญได้ทันท่วงที
คณะบริหารธุรกิจ
In a world increasingly focused on sustainability and reducing environmental impact, DreamHigh is pioneering an innovative approach to packaging solutions using mycelium—a natural, biodegradable, and renewable material derived from fungi. Our mission is to revolutionize the packaging industry by offering eco-friendly alternatives that not only reduce waste but also align with global efforts to combat climate change. Mycelium packaging offers a compelling alternative to traditional plastic and Styrofoam packaging, which contribute significantly to environmental pollution. It is fully biodegradable, compostable, and capable of breaking down in natural environments within weeks, leaving no toxic residues behind. Additionally, mycelium-based products are lightweight, durable, and customizable, making them suitable for a wide range of applications, from consumer goods packaging to protective shipping materials. DreamHigh’s business plan outlines a scalable production process leveraging advanced mycelium cultivation techniques and partnerships with local agricultural sectors to utilize agricultural waste as a key raw material. This not only ensures cost-efficiency but also supports a circular economy by repurposing waste that would otherwise be discarded.
คณะเทคโนโลยีการเกษตร
The design of Dreamscape Park, a public park covering an area of 50 rai, is based on the concept of ART. The design focuses on preserving green spaces while enhancing functionality to cater to people of all ages. The park features a landmark in the form of a water pond shaped like a drop of ink and a medium-sized amphitheater for various activities. Additional relaxation areas include a café, chill-out seating, outdoor activity zones, and sports facilities such as a basketball court, a takraw court, and walking/running paths around the park. There are also pet zones, children's play areas, gardens at various points, and accessible pathways throughout the area. Users can enjoy a peaceful environment and engage in activities according to their preferences.
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.