Agricultural products and by-products are important raw materials in various industries including cosmetics and pharmaceuticals. Agro-based fibers have the composition, properties and structure that make them suitable for uses as composite-cosmetic industry. Upon microwave digestion, cellulose have been successfully synthesized into nanocrystalline cellulose (NCC) with lengths from 50-1000 nm, widths between 5-70 nm. Nanocrystalline cellulose was grafted with cosmetic active ingredients such as glycerin), sodium hyaluronate), glycolic acid, and nicotinamide. The beauty active ingredients attached nanocelluloses can penetrate through the skin to enhance beauty and youth.
ประเทศไทย เป็นหนึ่งในประเทศที่ผลิตผลิตผลทางการเกษตร และประเทศไทยได้รับการขนานนามว่าเป็น “ครัวของโลก” (Kitchen of the World) เนื่องจากมีความอุดมสมบูรณ์ เป็นแหล่งผลิตสินค้าเกษตรที่สำคัญ ผลผลิตที่มากมายย่อมก่อให้เกิดผลพลอยได้ทางการเกษตรที่ตามมา เพื่อก่อให้เกิดประโยชน์สูงสุดของผลพลอยได้ทางการเกษตร งามวิจัยมุ่งเห็นถึงประโยชน์ของนาโนเซลลูโลส ที่เป็นองค์ประกอบที่สำคัญของพืช นาโนเซลลูโลส มีคุณสมบัติละลายน้ำได้ดี ทำให้เส้นใยนาโนเซลลูโลสมีคุณสมบัติในการอุ้มน้ำได้สูงกว่าน้ำหนักในขณะที่ไม่เปียกน้ำ ถึง 100 เท่า และมีความแข็งแกร่ง ยืดหยุ่นสูง อีกทั้งยังเป็นสารปลอดพิษที่ปราศจากเชื้อ และมีความบริสุทธิ์สูง การนำนาโนเซลลูโลสมายึดตึดด้วยสารสำคัญทางความงาม เช่นกลีเซอรีน (Glycerin), กรดไฮยาลูรอนิก (Sodium Hyaluronate), กรดไกลโคลิก (Glycolic Acid) หรือแม้แต่วิตตามิน เช่น นิโคตินาไมด์ (Nicotinamide) หรือ วิตามินบี 3 ย่อมส่งผลดีต่อการนำส่งสารความงามลงสู่ใบหน้า งานวิจัยนี้จึงมุ่งเน้นสังเคราะห์นาโนเซลลูโลส จากผลิตผล และผลพลอยได้ทางการเกษตร โดยการใช้เทคโนโลยีขั้นสูงไมโครเวฟในการย่อย และต่อกิ่งสารสำคัญทางความงาม เช่นกลีเซอรีน (Glycerin), กรดไฮยาลูรอนิก (Sodium Hyaluronate), กรดไกลโคลิก (Glycolic Acid) หรือแม้แต่วิตตามิน เช่น นิโคตินาไมด์ (Nicotinamide) หรือ วิตามินบี 3 ลงบนนาโนเซลลูโลส เพื่อมุ่งหวังใช้เป็นสารเสริมความงามต่อไป
คณะวิศวกรรมศาสตร์
The integration of intelligent robotic systems into human-centric environments, such as laboratories, hospitals, and educational institutions, has become increasingly important due to the growing demand for accessible and context-aware assistants. However, current solutions often lack scalability—for instance, relying on specialized personnel to repeatedly answer the same questions as administrators for specific departments—and adaptability to dynamic environments that require real-time situational responses. This study introduces a novel framework for an interactive robotic assistant (Beckerle et al. , 2017) designed to assist during laboratory tours and mitigate the challenges posed by limited human resources in providing comprehensive information to visitors. The proposed system operates through multiple modes, including standby mode and recognition mode, to ensure seamless interaction and adaptability in various contexts. In standby mode, the robot signals readiness with a smiling face animation while patrolling predefined paths or conserving energy when stationary. Advanced obstacle detection ensures safe navigation in dynamic environments. Recognition mode activates through gestures or wake words, using advanced computer vision and real-time speech recognition to identify users. Facial recognition further classifies individuals as known or unknown, providing personalized greetings or context-specific guidance to enhance user engagement. The proposed robot and its 3D design are shown in Figure 1. In interactive mode, the system integrates advanced technologies, including advanced speech recognition (ASR Whisper), natural language processing (NLP), and a large language model Ollama 3.2 (LLM Predictor, 2025), to provide a user-friendly, context-aware, and adaptable experience. Motivated by the need to engage students and promote interest in the RAI department, which receives over 1,000 visitors annually, it addresses accessibility gaps where human staff may be unavailable. With wake word detection, face and gesture recognition, and LiDAR-based obstacle detection, the robot ensures seamless communication in English, alongside safe and efficient navigation. The Retrieval-Augmented Generation (RAG) human interaction system communicates with the mobile robot, built on ROS1 Noetic, using the MQTT protocol over Ethernet. It publishes navigation goals to the move_base module in ROS, which autonomously handles navigation and obstacle avoidance. A diagram is explained in Figure 2. The framework includes a robust back-end architecture utilizing a combination of MongoDB for information storage and retrieval and a RAG mechanism (Thüs et al., 2024) to process program curriculum information in the form of PDFs. This ensures that the robot provides accurate and contextually relevant answers to user queries. Furthermore, the inclusion of smiling face animations and text-to-speech (TTS BotNoi) enhanced user engagement metrics were derived through a combination of observational studies and surveys, which highlighted significant improvements in user satisfaction and accessibility. This paper also discusses capability to operate in dynamic environments and human-centric spaces. For example, handling interruptions while navigating during a mission. The modular design allows for easy integration of additional features, such as gesture recognition and hardware upgrades, ensuring long-term scalability. However, limitations such as the need for high initial setup costs and dependency on specific hardware configurations are acknowledged. Future work will focus on enhancing the system’s adaptability to diverse languages, expanding its use cases, and exploring collaborative interactions between multiple robots. In conclusion, the proposed interactive robotic assistant represents a significant step forward in bridging the gap between human needs and technological advancements. By combining cutting-edge AI technologies with practical hardware solutions, this work offers a scalable, efficient, and user-friendly system that enhances accessibility and user engagement in human-centric spaces.
คณะอุตสาหกรรมอาหาร
The growing interest in antioxidant-rich foods is driven by their potential to reduce the risk of chronic diseases such as cancer, cardiovascular conditions, and cellular degeneration. Ginger (Zingiber officinale), banana inflorescence (Musa paradisiaca L.), and roselle (Hibiscus sabdariffa L.) are herbal plants known for their high phenolic content, a crucial component in antioxidant activity. However, the bioactive compounds in these plants are often unstable when exposed to light, temperature, and oxygen, leading to a reduction in their efficacy. This study aims to investigate the optimal ratio of ginger, banana inflorescence, and roselle for encapsulation in liposomes—a technique designed to enhance the stability of bioactive compounds and improve their delivery efficacy. The research evaluates the antioxidant activity of the extracts using DPPH, ABTS, and FRAP methods, alongside total phenolic content (TPC) measurement. The most effective ratio for antioxidant activity will be selected for liposomal encapsulation, employing phospholipids as key structural components. The encapsulation efficiency (EE%) will be calculated to assess the effectiveness of the liposomal delivery system. The findings are expected to identify the optimal combination of ginger, banana inflorescence, and roselle that maximizes antioxidant potency and enhances the stability of bioactive compounds through liposomal encapsulation. This approach offers a promising strategy for developing herbal health supplements that maintain their biological properties over time.
คณะวิศวกรรมศาสตร์
This capstone project develops an AI-powered chatbot to address cybersecurity vulnerabilities, leveraging the Common Vulnerabilities and Exposures (CVE) system and the Common Vulnerability Scoring System (CVSS). The chatbot will provide accessible and informative support for understanding and mitigating these vulnerabilities, potentially leading to significant improvements in cybersecurity practices.