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.
ประเทศไทยยังขาดพริกต้านทานต่อโรคแอนแทรกโนสและโรคไวรัสใบหงิกเหลือง และ เพื่อให้เกษตรได้ลดการใช้สารเคมีเพื่อป้องกันและกำจัดโรคและแมลง และเป็นการเพิ่มผลผลิตและลดต้นทุนให้แก่เกษตรกร โดยการพัฒนาพันธุ์พริกผ่านกระบวนการเรียนการสอนทั้งระดับปริญญาตรี โท และเอก ซึ่งถือได้ว่าเป็นการสร้างนักปรับปรุงพันธุ์รุ่นใหม่ ที่มีทั้งความรู้ด้านการปรับปรุงพันธุ์พืชโดยใช้วิธีมาตรฐานร่วมกับการใช้เทคโนโลยีชีวภาพ และงานวิจัยนี้ยังได้เผยแพร่สายพันธู์เพื่อให้เกษตรกร และบริษัทเมล็ดนำไปต่อยอดใช้ในเชิงพานิชย์ และช่วยเสริมความเข้มแข็งให้กับธุรกิจเมล็ดพันธุ์ของประเทศไทยได้
วิทยาลัยอุตสาหกรรมการบินนานาชาติ
The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires an accurate, reliable, and robust object recognition algorithm. Vision-based guided spacecraft relative motion during close-proximity maneuvers has been consecutively applied using dynamic modeling as a spacecraft on-orbit service system. This research constructs a vision-based pose estimation model that performs image processing via a deep convolutional neural network. The pose estimation model was constructed by repurposing a modified pretrained GoogLeNet model with the available Unreal Engine 4 rendered dataset of the Soyuz spacecraft. In the implementation, the convolutional neural network learns from the data samples to create correlations between the images and the spacecraft’s six degrees-of-freedom parameters. The experiment has compared an exponential-based loss function and a weighted Euclidean-based loss function. Using the weighted Euclidean-based loss function, the implemented pose estimation model achieved moderately high performance with a position accuracy of 92.53 percent and an error of 1.2 m. The in-attitude prediction accuracy can reach 87.93 percent, and the errors in the three Euler angles do not exceed 7.6 degrees. This research can contribute to spacecraft detection and tracking problems. Although the finished vision-based model is specific to the environment of synthetic dataset, the model could be trained further to address actual docking operations in the future.
วิทยาลัยนวัตกรรมการผลิตขั้นสูง
The objective of this research is to utilize waste slag in industrial applications and help mitigate flooding, water accumulation, and ponding issues. Currently, slag from the steel smelting or refining process is commonly used as a component in construction materials, such as road surfaces. However, slag has properties that make it difficult for water to permeate, leading to poor drainage and increased flooding problems. This study focuses on improving the properties of pavement materials to enhance their strength and water permeability. This can be achieved through physical structural modifications or the addition of chemical agents such as HPMC, which increases void spaces to facilitate water absorption and drainage according to required standards. The utilization of waste slag not only helps reduce production costs and improve material performance but also minimizes environmental impacts and promotes the sustainable use of resources.
คณะวิศวกรรมศาสตร์
This project aims to develop an AI-powered system for detecting and classifying wall cracks using image processing. It identifies different crack types, assesses severity, and ensures accuracy across various image conditions. The goal is to support preventive maintenance by enabling early detection of structural issues, reducing repair costs, and improving safety.