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.
ในดินมีสิ่งมีชีวิตหลากหลายชนิดซึ่งมีความสัมพันธ์กันเป็นสายใยอาหารขนาดใหญ่ที่ทำให้เกิดการหมุนเวียนพลังงานและสารอาหารไปยังสิ่งมีชีวิตที่อาศัยอยู่บนดิน สิ่งมีชีวิตในดินทำหน้าที่สร้างอาหารสำหรับพืชเพื่อใช้ในการเจริญเติบโต ดินมีลักษณะเป็นรูพรุน มีทั้งน้ำ อากาศ ธาตุอาหารต่างๆ จึงเป็นแหล่งที่อยู่อาศัยของสิ่งมีชีวิตหลากหลายชนิด ซึ่งสิ่งมีชีวิตแต่ละชนิดจะมีบทบาทหลากหลายแตกต่างกันไป กลุ่มสิ่งมีชีวิตที่พบในดินได้แก่
คณะบริหารธุรกิจ
Air Quality Monitoring System with External Device Controlling Capability is the equipment which measures and records the climatic data with the capability to control external devices (e.g. blower fan or air purifier) to rectify the surrounding atmosphere according to the air quality at the moment and other users' pre-defined conditions.
คณะเทคโนโลยีสารสนเทศ
Facial Expression Recognition (FER) has attracted considerable attention in fields such as healthcare, customer service, and behavior analysis. However, challenges remain in developing a robust system capable of adapting to various environments and dynamic situations. In this study, the researchers introduced an Ensemble Learning approach to merge outputs from multiple models trained in specific conditions, allowing the system to retain old information while efficiently learning new data. This technique is advantageous in terms of training time and resource usage, as it reduces the need to retrain a new model entirely when faced with new conditions. Instead, new specialized models can be added to the Ensemble system with minimal resource requirements. The study explores two main approaches to Ensemble Learning: averaging outputs from dedicated models trained under specific scenarios and using Mixture of Experts (MoE), a technique that combines multiple models each specialized in different situations. Experimental results showed that Mixture of Experts (MoE) performs more effectively than the Averaging Ensemble method for emotion classification in all scenarios. The MoE system achieved an average accuracy of 84.41% on the CK+ dataset, 54.20% on Oulu-CASIA, and 61.66% on RAVDESS, surpassing the 71.64%, 44.99%, and 57.60% achieved by Averaging Ensemble in these datasets, respectively. These results demonstrate MoE’s ability to accurately select the model specialized for each specific scenario, enhancing the system’s capacity to handle more complex environments.
คณะเทคโนโลยีสารสนเทศ
The process of treating cancer patients in the chemotherapy department at Chonburi Cancer Hospital is complicated and inconvenient due to the procedure of submitting blood test results through the personal LINE application of medical staff, which hinders workflow efficiency. Therefore, the researcher has developed a cancer patient management and tracking program in the form of a web-based application and LINE LIFF (LINE Front-end Framework) application to facilitate both medical personnel and patients. The web-based application is designed for medical personnel to monitor, schedule, and collect patient data, while the LINE application is designed for patients to submit blood test results, view appointment schedules, record symptoms after chemotherapy, log their weekly weight, and access a chatbot for consultation. This system is developed based on client-server technology, which enhances data analysis efficiency and supports automated treatment planning. As a result, the cancer treatment process becomes faster, more modern, and more efficient.