Discover the ultimate innovations of the future developed by Thai researchers! Meet the latest technology from KMITL that will transform our way of life and industry.
คณะเทคโนโลยีสารสนเทศ
This research presents a deep learning method for generating automatic captions from the segmentation of car part damage. It analyzes car images using a Unified Framework to accurately and quickly identify and describe the damage. The development is based on the research "GRiT: A Generative Region-to-text Transformer for Object Understanding," which has been adapted for car image analysis. The improvement aims to make the model generate precise descriptions for different areas of the car, from damaged parts to identifying various components. The researchers focuses on developing deep learning techniques for automatic caption generation and damage segmentation in car damage analysis. The aim is to enable precise identification and description of damages on vehicles, there by increasing speed and reducing the work load of experts in damage assessment. Traditionally, damage assessment relies solely on expert evaluations, which are costly and time-consuming. To address this issue, we propose utilizing data generation for training, automatic caption creation, and damage segmentation using an integrated framework. The researchers created a new dataset from CarDD, which is specifically designed for cardamage detection. This dataset includes labeled damages on vehicles, and the researchers have used it to feed into models for segmenting car parts and accurately labeling each part and damage category. Preliminary results from the model demonstrate its capability in automatic caption generation and damage segmentation for car damage analysis to be satisfactory. With these results, the model serves as an essential foundation for future development. This advancement aims not only to enhance performance in damage segmentation and caption generation but also to improve the model’s adaptability to a diversity of damages occurring on various surfaces and parts of vehicles. This will allow the system to be applied more broadly to different vehicle types and conditions of damage inthe future
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
A conceptual model inspired by Art Deco art, using the luxury, elegance, balance and the use of black and gold, which are the characteristics of Art Deco art, to create a conceptual model that is balanced, stable, elegant, sequential to look dynamic and uses black and gold to express Art Deco luxury.
วิทยาเขตชุมพรเขตรอุดมศักดิ์
A sweet made from flour and added to give it a chewy texture similar to chewing gum.
คณะอุตสาหกรรมอาหาร
In the development of high protein jasmine rice products, hydrocolloids, HPMC at 0, 0.25, 0.5 and 1% w/v and MD at 10% w/v were used. This hydrocolloid contained 30% w/v dissolved protein and was coated with raw jasmine rice. It was found that different amounts of HPMC affected the adhesion of proteins in rice. Then, the hydrocolloid with the best adhesion, 0.25% w/v, was used to find the optimum amount for coating rice at ratios of 1:3 and 1:5, which affected protein content, texture, color, water retention and sensory acceptability.
คณะวิทยาศาสตร์
Eco Grow Pellets are high-porosity plant-growing clay pellets made from ceramic industrial sediment, blended with ground chicken bone to enhance calcium and essential minerals, promoting strong and healthy plant growth. They are suitable for all types of plants, especially those requiring well-aerated soil with good water drainage. Eco Grow Pellets are an innovative clay-based growing medium designed to optimize plant cultivation efficiency. Their high porosity structure allows for excellent air and water circulation, reducing soil compaction and waterlogging—common causes of root rot and stunted growth. Additionally, the pellets are enriched with calcium and essential minerals from ground chicken bones, reinforcing plant structure and enhancing root strength, enabling better nutrient absorption. This product is made from 100% recycled ceramic industrial sediment, aligning with the principles of Zero Waste and the BCG Economy Model. It helps minimize industrial waste while transforming discarded materials into high-value, eco-friendly growing media. Eco Grow Pellets are ideal for vegetables, flowers, and potted plants, offering ease of use, cleanliness, and safety. They contribute to sustainable agriculture by improving both crop productivity and environmental health.
วิทยาลัยวิศวกรรมสังคีต
This project studies how to design a portable, sound-confining space that allows users to practice using their voices without disturbing the surroundings.
วิทยาลัยวิศวกรรมสังคีต
Musical stories to enhance thinking skills of children aged 0-3 years using EF skills as a tool to enhance children development by focus on 3 basic skills. 1. Working memory 2. Inhibitory Control 3. Cognitive Flexibility
คณะวิศวกรรมศาสตร์
This thesis presents the application of deep learning for object classification. The selected deep learning architectures studied include Convolutional Neural Networks (CNN) and ResNet18. It covers data preparation, feature extraction, parameter tuning for accuracy comparison, and performance evaluation of the selected models. The aim is to propose an efficient model for use in devices that assist visually impaired individuals in classifying indoor objects and providing sound alerts.
คณะวิศวกรรมศาสตร์
This project aims to propose a design for a red offal processing room in a pork processing plant that processes 500 pigs per day or 80 pigs per hour. Each pig weighs approximately 105 kilograms, with 3.47% of the weight consisting of red offal. The process involves separating liver, gall bladder, heart, lungs, spleen, and kidneys as required. These parts are then chilled in cold water to reduce their temperature to below 7°C before packaging and sealing. Sorting is based on the number of pieces and weight, depending on the type of product. The processing times of sorting chilling and packaging vary depending on the product's type and size. The design was developed using data collected from the current production line and referenced standards. The room layout was planned using Systematic Layout Planning (SLP) principles to analyze activity relationships within the room and define functional areas. Equipment sizes and the required number of operators were calculated to ensure optimal use of space. The red offal processing room was designed with an area of 56 square meters. After the layout design was completed, a 3D model was created using SketchUp 2024, and the workflow and operations were simulated and analyzed using Flexsim 2024