The designing of mosquitoes counting system instrument is presented in this work. The mosquitoes that were counted died in order not to measure duplicate counting data. As soon as the input source counting machine can detect the mosquito, the single trigger signal is transmitted to the IOT system to interrupt the server immediately. The number of real mosquito is not transmitting to the IOT but only a signal to interrupt the server. The server records the number of the interrupt signal with real-time clock. Then the interrupt information will be further handled. The front end counting machine consist of the high voltage generate with the suitable voltage value and electrode distance for the required mosquitoes size. The low trigger pulse signals of the mosquitoes killed by high voltage are sending to the controller unit. Immediately, interrupt counting signal of the number of mosquitoes is sent to the big stream data collection on IOT system by the time stamp technique. Form the measurement results, 10 live sample mosquitoes in a limited space box to fly though the counting machine show that the count results are 100% correct count.
ประเทศไทยประสบกับปัญหาการแพร่ระบาดของโรคที่มียุงเป็นพาหะนำโรคมานาน เช่น ไข้มาราเลีย โรคไข้เลือดออก โรคเท้าช้าง เป็นต้น โรคไข้เลือดออกถูกพบขึ้นครั้งแรกในประเทศไทยในปี พ.ศ. 2492 ข้อมูลรายงานสถานการณ์โรคไข้เลือดออกตั้งแต่ปี พ.ศ. 2558 ถึงปี พ.ศ. 2563 พบว่ามีผู้ป่วยสูงสุดในปี 2562 ซึ่งพบผู้ป่วยสูงถึง 18,105 รายโดยภาครัฐไม่ได้นิ่งนอนใจเกี่ยวกับปัญหาที่เกิดขึ้นและได้ทำการสนับสนุนนวัตกรรมที่จะเข้ามาช่วยจัดการกับปัญหาดังกล่าว
คณะวิศวกรรมศาสตร์
Given the fact that the equity market contributes a significant amount to Thai economy and increasing participants and interest by Thai companies, these facts inspire and motivate us to establish a study to analyze whether the stock market can indeed be an active booster of company performances and characteristics of companies which will be beneficial from being in the stock market. These results can support higher listing interest from companies, provide actionable ideas to companies aiming to improve their performance in the competitive arena, and suggest improvements for the stock market to further establish a stronger capital market penetration and foundation in Thailand. The main hypothesis driving this project is to examine whether “aging in the market” contributes to measurable improvements in a company’s performance. Specifically, we seek to understand if the presence of Thai companies in the Stock Exchange of Thailand correlates with enhanced operational outcomes, thereby providing insights into the true benefits of public listing on long-term performance.
คณะอุตสาหกรรมอาหาร
This study aimed to develop a formula and production process for snacks made from germinated brown rice flour and banana flour using the extrusion process. The results indicated that both germinated brown rice flour and banana flour could be effectively used as the main raw materials for snack production via extrusion. The proportion of flour in the formula and production conditions, such as moisture content of the raw materials, barrel temperature, and screw speed, significantly influenced the nutritional value, bioactive compound levels, and antioxidant activity of the final products.
คณะวิทยาศาสตร์
Otitis Media is an infection of the middle ear that can occur in individuals of all ages. Diagnosis typically involves analyzing images taken with an otoscope by specialized physicians, which relies heavily on medical experience to expedite the process. This research introduces computer vision technology to assist in the preliminary diagnosis, aiding expert decision-making. By utilizing deep learning techniques and convolutional neural networks, specifically the YOLOv8 and Inception v3 architectures, the study aims to classify the disease and its five characteristics used by physicians: color, transparency, fluid, retraction, and perforation. Additionally, image segmentation and classification methods were employed to analyze and predict the types of Otitis Media, which are categorized into four types: Otitis Media with Effusion, Acute Otitis Media with Effusion, Perforation, and Normal. Experimental results indicate that the classification model performs moderately well in directly classifying Otitis Media, with an accuracy of 65.7%, a recall of 65.7%, and a precision of 67.6%. Moreover, the model provides the best results for classifying the perforation characteristic, with an accuracy of 91.8%, a recall of 91.8%, and a precision of 92.1%. In contrast, the classification model that incorporates image segmentation techniques achieved the best overall performance, with an mAP50-95 of 79.63%, a recall of 100%, and a precision of 99.8%. However, this model has not yet been tested for classifying the different types of Otitis Media.