Expanding from a public park design project to a campus design on an area of over 50 rai in Ang Sila Subdistrict, Mueang District, Chonburi Province, to serve as both an educational institution and a place for relaxation and learning for the surrounding people.
การพัฒนาพื้นที่แห่งนี้ให้กลายเป็นCampus Park เพื่อเป็นพื้นที่พักผ่อนและแลกเปลี่ยนความรู้เกี่ยวกับระบบนิเวศชายหาดของจังหวัดชลบุรี
คณะบริหารธุรกิจ
This project is a part of KMITL business student’s thesis. The topic is business plan about blazers and trousers made by recycled fabric
คณะวิทยาศาสตร์
The current residential solar panels lack an adequate monitoring system, which hinders their optimal utilization. This research aims to design an Internet of Things (IoT) monitoring system and employ machine learning techniques to predict the current and voltage generated by solar panels. Experimental studies have revealed a correlation between dust accumulation and the current output of solar panels. The proposed system facilitates the prediction of the optimal time for cleaning solar panels.
คณะวิศวกรรมศาสตร์
This research aims to investigate the adulteration of Khao Dawk Mali 105 rice based on storage age using Near-Infrared Spectroscopy (NIRS) with Fourier Transform Near-Infrared Spectroscopy (FT-NIR) in the wavenumber range of 12,500 – 4,000 cm-1 (800 – 2,500 nm). Storage duration significantly impacts the quality of cooked rice. This research is divided into two parts: 1) to investigate the feasibility of separating rice according to storage age (1, 2, and 3 years) using the best model created by an Ensemble method combined with Second Derivative, which achieved an accuracy of 96.3%. 2) To investigate adulteration based on storage age by adulterating at 0% (all 2- and 3-year-old rice), 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% (all 1-year-old rice). The best model was created using Gaussian Process Regression (GPR) combined with Smoothing + Multiplicative Scatter Correction (MSC), with coefficients of determination (r²), root mean square error of prediction (RMSEP), bias, and prediction ability (RPD) values of 0.92, 8.6%, 0.9%, and 3.6 respectively. This demonstrates that the adulteration model can be applied to separate rice by storage age (1, 2, and 3 years). Additionally, the color values of rice with different storage ages show differences in L* and b* values.