
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.
โรงงานผู้ผลิตข้าวพบปัญหาการปลอมปนของข้าวสารที่มีอายุการเก็บรักษาต่างกัน โดยทั่วไปการคัดแยกการปลอมปนจะใช้วิธีมาตรฐานโดยการหุงข้าว จากนั้นนำข้าวหุงสุกไปวัดเนื้อสัมผัสเพื่อแยกอายุของข้าว ซึ่งใช้เวลาและเป็นการทำลายตัวอย่างและเกิดความล่าช้าในการตรวจสอบคุณภาพข้าวสาร งานวิจัยนี้ใช้เทคนิคเนียร์อินฟราเรดสเปกโทรสโกปี (Near-Infrared Spectroscopy, NIRS) ในการตรวจสอบการปลอมปนของข้าวสารพันธุ์ขาวดอกมะลิ 105 (KDML 105) ที่อายุการเก็บรักษาต่างกันเพื่อแก้ไขปัญหาดังกล่าว

คณะวิศวกรรมศาสตร์
SecurionSphere is the penetration testing learning platform that focuses on web application exploitation. This platform is intended to address concerns seen in existing penetration testing platforms, such as resource sharing that may affect other users and the constant environment configuration the permits the same response leading to copy the answer from others. Supervisors can use templates to address various forms of web application vulnerability threats. Users can generate the instance of supervisor's templates machine. The platform also randomly generates the environment configuration for each machine has the difference environment and the answer. This allows the users get more realistic learning experiences without affecting the resources of others.

คณะวิทยาศาสตร์
With the urgent need for rapid screening of Aflatoxin B1 (AFB1) due to its association with increased liver cirrhosis and hepatocellular carcinoma cases from contaminated agricultural foods, we propose a novel electrochemical aptasensor. This aptasensor is based on trimetallic nanoparticles AuPt-Ru supported by reduced graphene oxide (AuPt-Ru/RGO) modified on a low-cost and disposable goldleaf electrode (GLEAuPt-Ru/RGO) for detection of AFB1. The trimetallic nanoparticle AuPt-Ru was synthesized using an ultrasonic-driven chemical reduction method. The synthesized AuPt-Ru exhibited a waxberry-like appearance, with AuPt core-shell structure and ruthenium dispersed over the particles. The average particle size was 57.35 ± 8.24 nm. The AuPt-Ru was integrated into RGO sheets (inner diameter of 0.5 to 1.6 µm) in order to enhance electron transfer efficiency and increase the specific immobilizing surface area of the thiol-5’-terminated modified aptamer (Apt) to target AFB1. With a large electrochemical surface area and low electrochemical impedance, GLEAuPt-Ru/RGO displays ultra-high sensitivity for AFB1 detection. Differential pulse voltammetry (DPV) measurements revealed a linear range for AFB1 detection range from 0.3 to 30.0 pg mL-1 (R2 = 0.9972), with a limit of detection (LOD, S/N = 3) and a limit of quantification (LOQ, S/N = 10) of 0.009 pg mL-1 and 0.031 pg mL-1, respectively. The developed aptasensor also demonstrated excellent accuracy in real agricultural products, including dried red chili, garlic, peanut, pepper, and Thai jasmine rice, achieving recovery rates between 94.6 and 107.9%. The fabricated aptamer-based GLEAuPt-Ru/RGO performance is comparable to that of a modified commercial electrode, which has great potential application prospects for detecting AFB1 in agricultural products.

คณะวิศวกรรมศาสตร์
Stirling engine is the external heated engine that heat is sup-plied externally to the heater part of the engine. Thus, Stirling cycle engine can be employed with various sources of renewable energy such as biomass, biofuel, solar energy, geothermal energy, recovery heat, and waste. The integration of gasifier, burner, and heat engine as a power system offers more fuel choices of each local area with potential resources resulting independent from shortage and cost fluctuation of fossil fuel. This research aims to investigate the integration of the Stirling engine with a wood pellet gasifier for electric power generation. Biomass can be controlled to have continuously combustion with ultra-low toxic emission. Stirling engine, therefore, is a promising alternative in small-scale-electricity production. Even though many biomass-powered Stirling engines were successfully constructed and marketed but these engines and the use of biomass resources as fuel for power generation are quite new concepts in some developing countries. Especially, the capital cost of this engine is high and unaffordable for installation compared to other power systems. Therefore, this research aims to the study attractive and feasibility of the compact Stirling engine with green energy.