This research aims to evaluate the efficiency of nano-type oxygen diffusers at different pump power levels in sea bass nursery ponds. The study examines how varying power levels affect dissolved oxygen distribution in the water and their impact on the health, growth, and survival rates of sea bass. The findings indicate that pump power levels influence dissolved oxygen concentration, with the optimal power level improving oxygen distribution in the pond. This enhancement leads to higher survival and growth rates for sea bass. The results provide valuable insights for selecting appropriate oxygen diffusers and pump power levels in fish nursery pond systems. The experiment consisted of two conditions: 1. Without fish – This condition assessed the oxygenation capacity, oxygen transfer coefficient, oxygen transfer rate, and oxygen transfer efficiency of pumps at three different power levels. 2. With fish – This condition evaluated whether the oxygen supplied by pumps at three power levels was sufficient, based on the growth rate and survival rate of the fish in the pond. Blood counts were conducted to assess the immune response. The collected data were statistically analyzed using the RCBD method for the condition without fish and the CRD method for the condition with fish, employing SPSS software.
ประเทศไทยได้ประสบปัญหาในเรื่องของภัยธรรมชาติ ปัญหาการเปลี่ยนเเปลงสภาพภูมิอากาศ โดยเฉพาะปัญหาอุทกภัยและภัยเเล้ง สภาพอากาศแปรปรวน และยังมีปัญหาในด้านการทำประมงที่จำกัดดังนั้นการทำฟาร์มเลี้ยงสัตว์น้ำเเบบลดความเสี่ยงจึงเป็นทางออกในการรักษาความมั่นคงของอาหาร ในปัจจุบันปลาที่สามารถปรับตัวให้อยู่ในน้ำจืดหรือน้ำกร่อยได้และเป็นที่นิยมในการรับประทานได้เเก่ปลากะพงขาว เนื่องจากเลี้ยงง่ายโตเร็ว เนื้อปลารสชาติดี และมีราคาสูงพอคุ้มค่ากับการลงทุน โดยศึกษาจากการใช้อุปกรณ์สร้างออกซิเจนชนิดหัวนาโนบับเบิ้ลเพื่อศึกษาว่าอุปกรณ์ให้ออกซิเจนชนิดหัวนาโนกับขนาดกำลังปั๊มน้ำที่ต่างกันขนาดใดมีความสามารถทำให้ออกซิเจนละลายในน้ำดีมากที่สุด อัตราการถ่ายเทออกซิเจนในน้ำ ค่าสัมประสิทธิ์ออกซิเจนที่ละลายในน้ำได้มีประสิทธิภาพมากที่สุด วัดความเจริญเติบโต อัตรารอดของปลากะพงและภูมิคุ้มกันของปลากะพง ประสิทธิภาพในการให้ ออกซิเจน ในบ่ออนุบาลปลากะพงได้ดีที่สุดและมีผลกระทบน้อยมากที่สุด
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.
คณะเทคโนโลยีการเกษตร
Soil is home to a diverse array of living organisms that interact within a complex food web, facilitating energy and nutrient cycling essential for sustaining life above ground. Among these organisms, soil microbes play a crucial role in supporting plant growth. Beneficial microorganisms enhance nutrient availability, improve soil structure by increasing porosity, and strengthen plant resistance to diseases. Conversely, harmful microorganisms, such as plant pathogens, can hinder plant growth and reduce crop yields when present in high concentrations. Neutral microorganisms, which naturally inhabit the soil, contribute to the soil ecosystem without directly impacting plants. A single teaspoon of soil contains over a billion microorganisms, yet only about 1% of them can be cultured in laboratory conditions. This highlights soil as one of the richest reservoirs of microbial diversity on Earth.
วิทยาเขตชุมพรเขตรอุดมศักดิ์
Durian is an important economic crop in Thailand that is affected by foliar diseases such as rust, leaf blight, and leaf spot. These diseases reduce the quality of the yield and increase management costs. This research focuses on developing AI software for screening durian leaf diseases by applying deep learning technology to classify different types of leaf lesions.