Crispy Rice-berry Snack is a product made from broken rice-berry rice that has been processed into a snack that is thin and crispy, bite-sized. Broken rice-berry rice is cooked, finely ground, and mixed with other ingredients to increase its nutritional value, such as adding plant seeds, adding plant protein nutrients, and then forming it into sheets using heat. The resulting product is a thin sheet, purple-brown in color, crispy, and has the smell of the ingredients used in the production process. It does not contain sugar or sweeteners. It is used as a snack with tea or coffee. Crispy Rice-berry Waffle is a product that contains complete nutrients, including carbohydrates, protein, and fat, which are derived from the ingredients in the production formula.
เป็นการเพิ่มมูลค่าใหักับข้าวหักไรซ์เบอร์ โดยนำมาแปรรูปเป็นผลิตภัณฑ์อาหารที่รับประทานได้ง่าย
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
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คณะอุตสาหกรรมอาหาร
The reuse of cooking oil in food preparation leads to oil degradation and the formation of harmful compounds due to oxidation. This study focuses on enhancing the stability of used palm oil through ultrasound-assisted infusion with three varieties of banana blossoms: Kluai Khai, Kluai Hom, and Kluai Nam Wa, which are rich in phenolic compounds and antioxidants. The research investigates the restoration of used palm oil by infusing dried and powdered banana blossoms using ultrasonic treatment at different temperatures and durations. The quality of the infused oil was evaluated through physical (water activity, moisture content, and color), chemical (peroxide value, acid value, and Thio barbituric acid reactive substances), and antioxidant activity (DPPH, ABTS, and FRAP) analyses.
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.