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.
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
คณะเทคโนโลยีสารสนเทศ
This research presents a deep learning method for generating automatic captions from the segmentation of car part damage. It analyzes car images using a Unified Framework to accurately and quickly identify and describe the damage. The development is based on the research "GRiT: A Generative Region-to-text Transformer for Object Understanding," which has been adapted for car image analysis. The improvement aims to make the model generate precise descriptions for different areas of the car, from damaged parts to identifying various components. The researchers focuses on developing deep learning techniques for automatic caption generation and damage segmentation in car damage analysis. The aim is to enable precise identification and description of damages on vehicles, there by increasing speed and reducing the work load of experts in damage assessment. Traditionally, damage assessment relies solely on expert evaluations, which are costly and time-consuming. To address this issue, we propose utilizing data generation for training, automatic caption creation, and damage segmentation using an integrated framework. The researchers created a new dataset from CarDD, which is specifically designed for cardamage detection. This dataset includes labeled damages on vehicles, and the researchers have used it to feed into models for segmenting car parts and accurately labeling each part and damage category. Preliminary results from the model demonstrate its capability in automatic caption generation and damage segmentation for car damage analysis to be satisfactory. With these results, the model serves as an essential foundation for future development. This advancement aims not only to enhance performance in damage segmentation and caption generation but also to improve the model’s adaptability to a diversity of damages occurring on various surfaces and parts of vehicles. This will allow the system to be applied more broadly to different vehicle types and conditions of damage inthe future
คณะบริหารธุรกิจ
Parking space shortages in urban areas contribute to traffic congestion, inefficient land use, and environmental challenges. Automated Parking Systems (APS) provide an innovative solution by optimizing space utilization, reducing search times, and minimizing carbon emissions. This research investigates key factors influencing user adoption of APS technology using the UTAUT2 framework, focusing on variables such as Performance Expectancy, Effort Expectancy, Social Influence, Trust in Technology, and Environmental Consciousness. The APS Evolution project presents a smart parking solution that enhances efficiency, minimizes environmental impact, and improves user experience in urban settings. The initiative emphasizes technology-driven urban mobility and sustainable parking management to align with the evolving needs of modern cities.
คณะอุตสาหกรรมอาหาร
This study aims to investigate the co-encapsulation technique of vitamin C and coenzyme Q10 within liposomes to enhance their stability and encapsulation efficiency and evaluate their antioxidant activity and release behavior under simulated gastrointestinal conditions. Liposomes were prepared using the High-Speed Homogenization Method, and their characteristics, including particle size, zeta potential, encapsulation efficiency, and antioxidant activity, were analyzed using DPPH, ABTS, and FRAP assays. The results demonstrated that co-encapsulation significantly improved the stability of vitamin C and coenzyme Q10 compared to single encapsulation. The liposomes exhibited high encapsulation efficiency and maintained strong antioxidant activity. The release profile under simulated gastrointestinal conditions also indicated a sustained and controlled release. These findings highlight the potential of the co-encapsulation technique in enhancing the efficacy of functional bioactive compounds, making it applicable to the food and nutraceutical industries.