Currently, urban agriculture is gaining increasing attention as it helps enhance food security and expand green spaces in cities. However, some people remain uninterested in urban farming, possibly due to living in urban areas or having limited space, making them perceive agriculture as something distant from their daily lives. The development of an urban agriculture card game aims to promote learning about urban farming through an engaging and enjoyable gameplay experience.
การทำเกษตรในเมืองได้รับความสนใจอย่างแพร่หลาย โดยใช้พื้นที่ว่างในเมืองเพื่อทำการปลูกพืชหรือเลี้ยงสัตว์เพื่อเพิ่มความมั่นคงทางอาหารและพื้นที่สีเขียว การเรียนรู้ผ่านเกมช่วยให้ผู้เรียนเข้าใจเนื้อหาได้ดีขึ้นและสนุกสนาน ทั้งปัจจุบันบอร์ดเกมหรือการ์ดเกมได้รับความนิยมอย่างมากจึงมีความสนใจและเล็งเห็นวิธีการเรียนรู้ผ่านการเล่นการ์ดเกมที่ได้ทั้งความสนุกสนานและความรู้ผ่านกลไกของเกม เพื่อสร้างความเข้าใจและตระหนักถึงความสำคัญของการเกษตรในชีวิตประจำวัน
คณะวิศวกรรมศาสตร์
Jaundice, a common condition in infants that results from high bilirubin levels in the blood, often requires early diagnosis and monitoring to prevent severe complications, especially in newborns. Traditional diagnostic methods can be time-consuming and subject to human error. This study proposes an approach for real-time jaundice detection using advanced image processing techniques and machine learning algorithms. By analyzing images captured in RGB color spaces, pixel values are extracted and processed through Otsu’s thresholding and morphological operations to detect color patterns indicative of jaundice. A classifier model is then trained to distinguish between normal and jaundiced conditions, offering an automated, accurate, and efficient diagnostic tool. The system’s potential to operate in real-time makes it particularly suited for clinical settings, providing healthcare professionals with timely insights to improve patient outcomes. The proposed method represents a significant innovation in healthcare, combining artificial intelligence and medical imaging to enhance the early detection and management of jaundice, reducing reliance on manual interventions and improving overall healthcare delivery.
คณะวิทยาศาสตร์
Microalgae are rich in bioactive compounds that may contribute to the growth of probiotics, which require appropriate nutrients, known as prebiotics, to thrive. This study aims to evaluate the effectiveness of crude extracts from intracellular components residues of the microalga Chlorella sp. KLSc61 in promoting the growth of the probiotic bacterium Lactiplantibacillus plantarum JCM1149 under simulated gastrointestinal conditions. The intracellular extracts were obtained using 70% (v/v) ethanol, and their effects on probiotic growth were tested at concentrations of 0.1%, 0.75% and 1.5%. The growth of Lactiplantibacillus plantarum JCM1149 was assessed using the drop plate method. The findings of this study will provide insights into the potential of Chlorella sp. KLSc61 extracts in enhancing probiotic growth, which could lead to the development of synbiotic dietary supplements containing both probiotics and prebiotics. Additionally, this study may serve as a foundation for further research on the role of microalgal extracts in gut health and immune system modulation.
คณะวิศวกรรมศาสตร์
This project has been developed to address medical challenges related to the process of counting and classifying blood cells from samples, a task that requires both time and high precision. To reduce the workload of medical personnel, the developers have created a platform and an artificial intelligence (AI) system capable of automatically classifying and counting cells from sample images. This system is designed to assist medical laboratory technicians by enabling them to work more efficiently and accurately, reducing the time required for analysis. Furthermore, it promotes the advancement of medical technology, ensuring effective usability from classrooms and laboratories to hospitals.