KMITL Innovation Expo 2025 Logo

Enchancing stability of cooking oils using ultrasound-assisted infusion with Thai herbs

Abstract

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.

Objective

ประเทศไทยมีการใช้น้ำมันพืชเฉลี่ยปีละ 800,000 ตัน ซึ่งการบริโภคอาหารทอดที่เพิ่มขึ้นนำไปสู่ปัญหาน้ำมันใช้แล้วที่เสื่อมสภาพและเกิดสารพิษ เช่น อนุมูลอิสระ อัลดีไฮด์ และไฮโดรเปอร์ออกไซด์ ซึ่งอาจก่อให้เกิดอันตรายต่อสุขภาพ วิธีการบำบัดน้ำมันที่ใช้แล้วในปัจจุบัน เช่น การกรองและการใช้สารดูดซับ เช่น ถ่านกัมมันต์ ยังมีข้อจำกัด ปลีกล้วยเป็นแหล่งของสารฟีนอลิก เช่น แทนนินและฟลาโวนอยด์ ซึ่งมีคุณสมบัติต้านอนุมูลอิสระและสามารถช่วยเพิ่มเสถียรภาพของน้ำมันโดยลดการเกิดออกซิเดชัน การศึกษานี้จึงมุ่งเน้นการใช้เทคโนโลยีคลื่นอัลตราโซนิคร่วมกับปลีกล้วยสายพันธุ์ต่างๆ เพื่อฟื้นฟูน้ำมันปรุงอาหารที่เสื่อมสภาพให้กลับมาใช้งานได้ ลดของเสีย และส่งเสริมการใช้ทรัพยากรอย่างยั่งยืน ซึ่งจะเป็นประโยชน์ต่อสุขภาพและสิ่งแวดล้อมในระยะยาว

Other Innovations

SignGen: An LLM-Based Thai Sign Language Generator

คณะวิศวกรรมศาสตร์

SignGen: An LLM-Based Thai Sign Language Generator

The Thai Sign Language Generation System aims to create a comprehensive 3D modeling and animation platform that translates Thai sentences into dynamic and accurate representations of Thai Sign Language (TSL) gestures. This project enhances communication for the Thai deaf community by leveraging a landmark-based approach using a Vector Quantized Variational Autoencoder (VQVAE) and a Large Language Model (LLM) for sign language generation. The system first trains a VQVAE encoder using landmark data extracted from sign videos, allowing it to learn compact latent representations of TSL gestures. These encoded representations are then used to generate additional landmark-based sign sequences, effectively expanding the training dataset using the BigSign ThaiPBS dataset. Once the dataset is augmented, an LLM is trained to output accurate landmark sequences from Thai text inputs, which are then used to animate a 3D model in Blender, ensuring fluid and natural TSL gestures. The project is implemented using Python, incorporating MediaPipe for landmark extraction, OpenCV for real-time image processing, and Blender’s Python API for 3D animation. By integrating AI, VQVAE-based encoding, and LLM-driven landmark generation, this system aspires to bridge the communication gap between written Thai text and expressive TSL gestures, providing the Thai deaf community with an interactive, real-time sign language animation platform.

Read more
Revolutionizing pill identification by using deep convolutional neural network based on widely-used essential household remedy drugs

คณะแพทยศาสตร์

Revolutionizing pill identification by using deep convolutional neural network based on widely-used essential household remedy drugs

This study explores the application of deep convolutional neural networks (CNNs) for accurate pill identification, addressing the limitations of traditional human-based methods. Using a dataset of 1,250 images across 10 household remedy drugs, various CNN architectures, including YOLO models, were tested under different conditions. Results showed that natural lighting was optimal for imprinted pills, while a lightbox improved detection for plain pills. The YOLOv5-tiny model demonstrated the best detection accuracy, and efficientNet_b0 achieved the highest classification performance. While the model showed strong results, its generalization is limited by sample size and drug variability. Nonetheless, this approach holds promise for enhancing medication safety and reducing errors in outpatient care.

Read more
LOCATION SELECTION OF BEVERAGE DISTRIBUTION CENTER USING A MATHEMATICAL MODELING CONSIDERING TRANSPORTATION LOGISTIC COSTS

คณะวิทยาศาสตร์

LOCATION SELECTION OF BEVERAGE DISTRIBUTION CENTER USING A MATHEMATICAL MODELING CONSIDERING TRANSPORTATION LOGISTIC COSTS

This research aims to select the location of the beverage distribution center of Thai Spirit Industry Co., Ltd. with the lowest total cost of transportation. using a mathematical model by considering the Muang districts of all 76 provinces, excluding Chachoengsao Province, where the factory is located. In the present study, four scenarios were divided: 1) when only one distribution center was required; 2) when more than one distribution center was established; 3) when it was divided into 4 regions. There can only be one distribution center in one region, and 4) when it is divided into four regions, where more than one distribution center can be established in one region. When processed with the program IBM ILOG CPLEX Optimization Studio, the results are summarized as follows: Scenario 1, when only one distribution center is assigned. The total transportation cost is 786,107.75 baht/month. Scenario 2, when more than one distribution center can be established. The total transportation cost is 252,338.98 baht/month. Scenario 3, when divided into 4 regions by requiring only one distribution center in one region. The total transportation cost is 401,499.61 baht/month. Scenario 4, when divided into 4 regions by requiring that there is more than one distribution center in each region. The total transportation cost is 258,666.22 baht/month.

Read more