This work attempts to spark conversations about the technical and creative aspects of participatory concert settings. It features the results of two interactive research concerts on basis of audience participation quantities, motion analysis and log data clustering. Ultimately, it poses questions how participatory work can help when teaching interactive technology for the arts and beyond.
The integration of interactive technology with art and music has gained increasing attention, particularly in concert settings that allow direct audience participation. Creating performances that foster interaction between the audience and performers not only enhances the artistic experience but also provides opportunities for learning about interactive technology.
คณะเทคโนโลยีการเกษตร
The research aims to develop chili Thai commercial varieties for resistance to anthracnose and Pepper yellow leaf curl virus disease. The varieties allowing farmer to reduce the use of chemical pesticides for disease and pest control, also increases productivity and lowers production costs for farmers. The development new varieties are under studied of undergraduate, master's, and doctoral students by using conventional and molecular plant breeding. The new chili varieties were released to farmer and commercial companies for development for Thai commercial seed industry.
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.
คณะวิทยาศาสตร์
Sugar production from sugarcane is a complex process that requires precise control. One of the major issues is sugar loss, which can result from various factors, particularly "burnt cane," before being sent to the mill. This affects the quality of the sugarcane and the efficiency of sugar extraction, along with the performance of the machinery and the properties of the cane, which impact the amount of sugar extracted. This study aims to analyze the factors that influence sugar loss in the sugar production process, using quantitative data from a sugar factory. Nine variables were examined, including mechanical efficiency, machine downtime per day, cane waiting time per day, sand content in cane juice, pol extraction efficiency, overall working time efficiency, cane juice purity, cane sugar content (C.C.S.), and burnt cane. The data were analyzed using correlation analysis to examine relationships between variables and regression modeling to predict sugar loss. The results showed that mechanical efficiency, cane sugar content, and the amount of sand or impurities in the cane juice were significantly correlated with sugar loss. Mechanical efficiency had a direct relationship with the amount of cane milled, which improved sugar production. On the other hand, burnt cane, or cane that was burnt before harvesting, resulted in reduced sugar extraction and impacted the quality of the sugar. Therefore, reducing sugar loss in the production process can be achieved by improving machine efficiency, reducing impurities in cane juice, and managing burnt cane, which will improve sugar production efficiency in the future.