Ballet dancing requires clear and precise body gestures. To raise standard and motivation for Thai ballet dancers, this testing console is developed such that dancers and beginners are able to learn and keep track of their dancing progress. Their gestures can be compared with internationally recognized ballet dancers without face-to-face learning. This enables self-development according to their purposes and pace. The portable console is easy to use. Connect it to a monitor, turn on, and enjoy.
แม้ว่าบัลเลต์จะเป็นนาฏศิลป์แบบคลาสสิคที่กำเนิดมาตั้งแต่สมัยเรอเนสซองส์ในคริสต์ศตวรรษที่ 15 บัลเลต์ก็ยังเป็นที่นิยมในปัจจุบันทั้งในกลุ่มนักเต้นอาชีพและบุคคลทั่วไป ตลอดจนเป็นรากฐานและนำมาประยุกต์ให้เข้ากับการเต้นในหลายๆรูปแบบ โดยนักเต้นอาชีพที่มีชื่อเสียงมักมีประสบการณ์ในการเต้นบัลเลต์ไม่มากก็น้อย สำหรับในประเทศไทยนั้น แม้ว่าจะมีนักบัลเลต์ที่มีชื่อเสียงในระดับนานาชาติหลายท่าน แต่ก็ยังถือว่ามีจำนวนน้อยเมื่อเทียบกับจำนวนนักเรียน ดังนั้น เพื่อเป็นการสร้างมาตรฐานและแรงบันดาลใจสำหรับนักเรียนหรือนักเต้นชาวไทย ผู้วิจัยจึงสร้างอุปกรณ์นี้ขึ้นมาเพื่อให้นักเต้นและบุคคลทั่วไปสามารถเรียนรู้และตรวจสอบพัฒนาการในการเต้นของตัวเอง โดยเทียบเคียงกับนักบัลเลต์ที่มีชื่อเสียงระดับนานาชาติได้ โดยไม่จำเป็นที่จะต้องเรียนแบบ Face-to-face กับนักบัลเลต์ท่านนั้นโดยตรง เพื่อประโยชน์ในการปรับปรุงตัวเองให้มีความสามารถสูงขึ้นตามจุดประสงค์ของแต่ละคน
คณะวิทยาศาสตร์
The aim of experiment was to study the pyrolysis oil derived from sorted landfill plastic waste that had been buried for 15 years by the Nonthaburi Provincial Administrative Organization. The pyrolysis oil was produced using a Fixed-Bed Reactor at 450 °C for 1.5 hours with LPG as the feedstock, with the goal of using the pyrolysis oil as an alternative fuel. The experiment was conducted under four different conditions : (1) plastic waste buried in a landfill that has not been washed but has been reduced in size, (2) plastic waste buried in a landfill that has been washed and has been reduced in size, (3) plastic waste buried in a landfill that not has been washed and has not been reduced in size, (4) plastic waste buried in a landfill that has not been washed and has been reduced size, with activated carbon used as a catalyst. The experiment revealed that three products were produced : Oil, gas, and char in different quantity. The pyrolysis oil were compared in terms of quality based on pH, Heating value, Moisture content, Functional group, and Chemical Composition. The pyrolysis oil we obtained will be referenced according to the criteria from the Department of Energy Business. The analysis results of the pyrolysis can explain which conditions are suitable for replacing fuel oil in industrial It is therefore one of the approaches that helps manage plastic waste in landfills, reducing the quantity by converting it into usable energy.
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
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.