Abstract: Banana French Fries This project aimed to study and develop the product Banana French Fries, which is a snack made by frying bananas in a form similar to French fries, in order to add value to bananas and create new choices for consumers. The experiment consisted of selecting suitable banana varieties, developing a coating formula, and testing the taste of samples. The results of the study found that Nam Wa bananas are the most suitable for making banana French fries because they have a firm texture and naturally sweet taste. The best coating formula consists of wheat flour, eggs, and milk, which provide longer crispiness. The taste test found that most consumers gave a very good response and were satisfied with the taste and texture. This project shows that banana French fries are a product with potential to be developed as a healthy snack and can be further developed into a commercial product in the future.
เปลี่ยนจากการบริโภคมันฝรั่งจากเดิมให้มีความแตกต่างจากปกติให้ลูกค้ากลุ่มใหม่ได้รับประทานผลิตภัณฑ์รูปแบบใหม่จากล้วยและได้ช่วยให้เกษตรกรได้มีรายได้ในส่วนนี้ด้วย
คณะวิทยาศาสตร์
This project presents the development of an automatic recycling machine for plastic bottles and cans, utilizing Machine Learning for packaging classification through image processing, integrated with smart sensor systems for quality inspection and operation control. The system connects to a Web Application for real-time monitoring and control. Once the packaging type is verified, the system automatically calculates the refund value and processes payment through e-wallet or issues cash vouchers. The system can be installed in public spaces to promote waste segregation at source, reduce contamination, and increase recycling efficiency. It also provides financial incentives to encourage public participation in waste management. This project demonstrates the potential of combining Machine Learning and smart sensor systems in developing accurate, convenient, and sustainable waste management solutions.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
This project is a carbon safe haven of Bangkok, aspiring to be the prototypal gateway of the future's carbon net zero ambitions. The project aims to answer the fundamental "flaw" of the existing urban fabric, still being extremely inefficient and highly polluting. Conversely, Carbon Oasis would not only create its own energy, but look to provide its excess energy and water surplus' back to the city and its surroundings. Taking parts of the existing city and implementing new concepts to inspire a change in the urban fabric and its people.
คณะเทคโนโลยีสารสนเทศ
This report is part of applying the knowledge gained from studying machine learning models and methods for developing a predictive model to identify customers likely to cancel their credit card services with a bank. The project was carried out during an internship at a financial institution, where the creator developed a model to predict customers likely to churn from their credit card services using real customer data through the organization's system. The focus was on building a model that can accurately predict customer churn by selecting features that are appropriate for the prediction model and the unique characteristics of the credit card industry data to ensure the highest possible accuracy and efficiency. This report also covers the integration of the model into the development of a website, which allows related departments to conveniently use the prediction model. Users can upload data for prediction and receive model results instantly. In addition, a dashboard has been created to present insights from the model's predictions, such as identifying high-risk customers likely to cancel services, as well as other important analytical information for strategic decision-making. This will help support more efficient marketing planning and customer retention efforts within the organization.