Multipurpose cleaner from Stemona (Stemonaceae) effectively cleans all surfaces,removes insects and stains, and is safe and eco-friendly
น้ำยาทำความสะอาดในตลาดมักมีสารเคมีที่เป็นอันตราย โครงงานนี้จึงศึกษาและพัฒนาน้ำยาทำความสะอาดอเนกประสงค์ที่ปลอดภัย ใช้งานได้หลากหลาย และเป็นมิตรกับสิ่งแวดล้อม
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.
คณะเทคโนโลยีสารสนเทศ
This report is part of applying the knowledge gained from studying machine learning models and methods for developing a predictive model to identify customers likely to cancel their credit card services with a bank. The project was carried out during an internship at a financial institution, where the creator developed a model to predict customers likely to churn from their credit card services using real customer data through the organization's system. The focus was on building a model that can accurately predict customer churn by selecting features that are appropriate for the prediction model and the unique characteristics of the credit card industry data to ensure the highest possible accuracy and efficiency. This report also covers the integration of the model into the development of a website, which allows related departments to conveniently use the prediction model. Users can upload data for prediction and receive model results instantly. In addition, a dashboard has been created to present insights from the model's predictions, such as identifying high-risk customers likely to cancel services, as well as other important analytical information for strategic decision-making. This will help support more efficient marketing planning and customer retention efforts within the organization.
คณะวิทยาศาสตร์
A new colorimetric assay for the rapid detection of tannic acid in beverage samples based on displacement phenomenon of aggregated gallic acid-modified platinum nanoparticles is developed for the first time. PtNPs were functionalized with gallic acid, promoting the formation of the green-hued aggregated nanoparticles. While colorimetry offers a rapid method for identifying tannic acid, challenges remain in sensitivity and accuracy of detection on the PtNPs colorimetric probe, particularly in the presence of anthocyanin interferences. To address this, we developed a sample preparation method to degrade anthocyanin in beverages. Tannic acid was easily displaced onto the gallic acid-coated PtNPs surfaces, causing dispersion and resulting in a visible color change from green to orange−brown. Under the optimal conditions, the colorimetric sensor exhibited a linear response in the range of 1−2,000 µmol L−1 (R2 = 0.9991). The limit of detection (LOD) and the limit of quantification (LOQ) were found at 0.02 and 0.09 µmol L−1, respectively. The proposed sensor expressed superior selectivity over other interfering substances and demonstrated excellent precision with a relative standard deviation (RSD) of 1.00%−3.36%. More importantly, recoveries ranging from 95.0−104.7% were obtained, indicating the capability of proposed colorimetric sensor to detect tannic acid rapidly and accurately in real beverage samples.