This research focuses on the fabrication of graphene oxide (GO) composite membranes using the Phase-Inversion Method, which transforms polymers from liquid to solid through phase separation. This process creates a porous membrane structure, making it highly adaptable, cost-effective, and suitable for wastewater treatment, separation processes, and industrial filtration applications. Graphene oxide, with its nano-layered structure, offers excellent molecular sieving properties, high water permeability, and chemical and mechanical stability, making it an ideal additive for membrane fabrication. The GO-based membrane demonstrates efficient removal of nanoparticles, heavy metal ions (Pb²⁺, Cr⁶⁺, Hg²⁺), organic pollutants, and microorganisms while exhibiting antifouling properties and high hydrophilicity due to oxygen-functional groups. Applications of this membrane include industrial wastewater treatment, desalination, and the removal of pharmaceutical contaminants, such as antibiotics and hormones. The incorporation of GO enhances membrane performance, providing a sustainable and energy-efficient solution for water purification.
ปัญหามลพิษทางน้ำจากโลหะหนัก สารอินทรีย์ และจุลินทรีย์ในน้ำเสียอุตสาหกรรมและน้ำธรรมชาติกำลังเป็นปัญหาระดับโลก เทคโนโลยีเมมเบรน ได้รับความสนใจเนื่องจากมีประสิทธิภาพสูงในการกรองและบำบัดน้ำ กราฟีนออกไซด์ (GO) เป็นวัสดุที่มีโครงสร้างระดับนาโนและคุณสมบัติพิเศษ เช่น การซึมผ่านน้ำสูง ความทนทานทางเคมี และการคัดแยกสารปนเปื้อนอย่างมีประสิทธิภาพ ดังนั้น การพัฒนาเมมเบรนกราฟีนออกไซด์ผ่านกระบวนการ Phase-Inversion Method จึงเป็นแนวทางสำคัญในการสร้าง เมมเบรนคุณภาพสูง ราคาประหยัด และเหมาะสำหรับการใช้งานด้านสิ่งแวดล้อม
คณะศิลปศาสตร์
Layla, the hotel robot, is responsible for carrying guests’ luggage and guiding them to their accommodations. It is equipped with an internal map of the hotel, allowing it to navigate various locations efficiently. Additionally, it features an AI-powered system that enables interactive conversations in three major languages: Thai, English, and Chinese.
คณะวิศวกรรมศาสตร์
One of the most important aspects of responding to a medical case is the response time. In general, most fatalities are due to the patient not being able to reach the hands of the doctor in time. This also includes the arrival of medical equipment to the scene. The human brain will start to degrade in function after 3 minutes of oxygen starvation which conventional road transportation method first responders presently use is usually unable to reach the site in this golden 3 minutes, resulting in fatalities during transport or before the arrival of first responders at the scene. Therefore, medical equipment transport by fully autonomous aircraft is explored. This is done through drone deliveries which is much quicker than road methods as the equipment could be flown straight to the site as it is not affected by traffic, road conditions, and navigation. In this project, we will explore an aerial delivery system for medical equipment such as Automatic External Defibrillators (AEDs), First aid equipment, and other small requested medical devices. This will be done through a DJI drone platform and their SDK application. The main goal for this project is to decrease the response time by using an autonomous aerial drone to deliver medical equipment.
คณะวิทยาศาสตร์
Recruitment is a crucial process that enables organizations to select candidates whose qualifications match the requirements of a given position. However, this process often faces challenges related to data management, delays, and human bias. This research aims to design and develop an intelligent web application for employee recruitment using artificial intelligence (AI) technology to evaluate and score candidates' suitability for job positions. The system leverages data analysis techniques on resumes and a qualification-matching process based on predefined criteria. Developed using Agile principles, the system employs Natural Language Processing (NLP) to analyze resumes, assess candidates’ qualifications, skills, and experience, and utilizes Machine Learning to predict and rank suitability. The system consolidates data from multiple sources into a unified database to reduce redundancy and input errors. Additionally, it presents insights through a dashboard, enabling HR teams to make more effective hiring decisions.