-
-
คณะบริหารธุรกิจ
In an era where sustainability is at the heart of business operations, eco-friendly packaging is gaining increasing attention. This research explores sustainable business models for alternative packaging, focusing on the case of corn-based paper, an innovation that effectively replaces conventional plastic packaging. The study analyzes key factors that enable businesses using natural raw materials to remain competitive in the market, as well as the growth potential of sustainable packaging compared to plastic-based alternatives. Additionally, it examines the factors influencing consumer behavior in choosing eco-friendly products and evaluates the impact on profitability and social responsibility. This research employs both qualitative and quantitative methods, including case studies of businesses utilizing alternative materials, in-depth interviews with industry experts, and consumer behavior surveys. The findings are expected to provide insights into the business potential of corn-based packaging, strategies for market expansion, and approaches for long-term sustainability. The results of this study will serve as a valuable reference for entrepreneurs seeking to develop green businesses and policymakers aiming to promote sustainable packaging in the market.
คณะอุตสาหกรรมอาหาร
The Ginbanirose project aims to develop herbal extracts for alleviating menstrual pain using key ingredients: roselle, banana inflorescence, and ginger. These ingredients contain bioactive compounds with anti-inflammatory, antioxidant, and pain-relieving properties. The extracts are enhanced through liposome encapsulation technology, which improves absorption and stability. The production process involves herbal extraction, freeze-drying, and liposome formulation using lecithin and stabilizers. Experimental results demonstrate high phenolic content and antioxidant activity via the DPPH method. Ginbanirose addresses women’s quality of life concerns while offering significant business opportunities in the rapidly growing herbal market, particularly in the Asia-Pacific region.
คณะวิศวกรรมศาสตร์
This thesis presents the application of deep learning for object classification. The selected deep learning architectures studied include Convolutional Neural Networks (CNN) and ResNet18. It covers data preparation, feature extraction, parameter tuning for accuracy comparison, and performance evaluation of the selected models. The aim is to propose an efficient model for use in devices that assist visually impaired individuals in classifying indoor objects and providing sound alerts.