The forest firefighting suit consists of the following components and uses: The forest firefighting suit is designed and developed to be suitable for the behavior of the officers and the conditions of the work area, consisting of a shirt and pants. The material used in the sewing of the suit is aramid fabric, which has the property of being able to prevent the spread of fire, to prevent the officers from burning while performing their duties in the event that the forest fire spreads close to them, which is different from the current suits that cannot prevent fires. The shirt is designed with a mesh on the side of the body to release internal heat so that air can circulate well. The sleeves at the elbows have a support point to prevent contact with the ground or obstacles. The collar has a slot for a portable fan and a fan air circulation channel on the back, which can be turned on while performing forest firefighting duties, helping to prevent the body temperature from getting too hot, reducing the risk of heatstroke. When the fan battery runs out, it can be removed for charging and put back in when needed. The pants are designed with mesh on the inside or in blind spots to release internal heat so that air can circulate well. The pants at the knees have a support point to prevent contact with the ground or obstacles. The forest firefighting suit, consisting of a shirt and pants, has been designed and developed to be able to be produced domestically, reducing imports from abroad
ปัญหาไฟป่าที่ทวีความรุนแรงขึ้นเรื่อย ๆ ส่งผลกระทบในหลายๆด้านโดยเฉพาะผู้ที่พักอาศัยบริเวณใกล้ไฟป่าต้องเผชิญกับปัญหาด้านสุขภาพที่เกิดจากฝุ่น PM2.5 ประกอบกับทางภาครัฐยังขาดแคลนบุคลากรเจ้าหน้าที่ ที่มีความชำนาญในการดับไฟป่า รวมถึงยังขาดชุดดับไฟป่าที่เป็นชุดสามารถกันไฟได้เหมาะสมต่อการดับไฟ เนื่องจากในปัจจุบันชุดที่เจ้าหน้าที่อุทยาน และเจ้าหน้าที่ศูนย์ดับไฟป่า สวมใส่ในการปฏิบัติหน้าที่นั้นเป็นชุดลายพลาง กางเกงกับเสื้อแบบทั่วไป ไม่สามารถปกป้อง หรือกันไฟเมื่อไฟมาถึงระยะประชิดตัวได้ในระดับที่เหมาะสม ซึ่งสาเหตุนี้ส่งผลให้เจ้าหน้าที่บางรายได้รับอันตรายถึงขั้นไฟคลอกได้ ผู้วิจัยจึงได้เล็งเห็นถึงความสำคัญในการออกแบบและพัฒนาชุดดับไฟป่า เพื่อให้เจ้าหน้าที่อุทยาน และเจ้าหน้าที่ศูนย์ดับไฟป่า สามารถสวมใส่ปฏิบัติหน้าที่ได้อย่างปลอดภัย ช่วยลดอุปสรรคในการดับไฟป่าและปฏิบัติหน้าที่ได้อย่างเต็มประสิทธิภาพมากยิ่งขึ้น
คณะบริหารธุรกิจ
Evenly Distributed Temperature Controlled Medical Refrigerator is the medical refrigerator which equipped with specialized control system to control the cold air distribution within the chamber to have the same temperature along the different height within the chamber.
คณะวิศวกรรมศาสตร์
Stirling engine is the external heated engine that heat is sup-plied externally to the heater part of the engine. Thus, Stirling cycle engine can be employed with various sources of renewable energy such as biomass, biofuel, solar energy, geothermal energy, recovery heat, and waste. The integration of gasifier, burner, and heat engine as a power system offers more fuel choices of each local area with potential resources resulting independent from shortage and cost fluctuation of fossil fuel. This research aims to investigate the integration of the Stirling engine with a wood pellet gasifier for electric power generation. Biomass can be controlled to have continuously combustion with ultra-low toxic emission. Stirling engine, therefore, is a promising alternative in small-scale-electricity production. Even though many biomass-powered Stirling engines were successfully constructed and marketed but these engines and the use of biomass resources as fuel for power generation are quite new concepts in some developing countries. Especially, the capital cost of this engine is high and unaffordable for installation compared to other power systems. Therefore, this research aims to the study attractive and feasibility of the compact Stirling engine with green energy.
คณะวิทยาศาสตร์
With the development of space technology, wide-field sky surveys using telescopes have expanded the range of new data available for time-domain astronomical research. Traditional data analysis methods can no longer respond quickly and accurately enough to the growing volume of data. Thus, classifying time-series data, such as light curves, has become a significant challenge in the era of big data. In modern times, analyzing light curves has become essential for using machine learning techniques to handle and filter through massive amounts of data. Machine learning algorithms can be divided into two categories: shallow learning and deep learning. Numerous researchers have proposed and developed a variety of algorithms for light curve classification. In this study, we experimented with Support Vector Machine (SVM) and XGBoost, which are shallow machine learning algorithms, as well as 1D-CNN and Long Short-Term Memory (LSTM), which are deep learning algorithms, which are branches of deep machine learning, to classify variable stars. The training and testing data used in this study were from the Optical Gravitational Lensing Experiment-III (OGLE-III), consisting of variable star data from the Large Magellanic Cloud (LMC), categorized into five main classes: Classical Cepheids, δ Scutis, eclipsing binaries, RR Lyrae stars, and Long-period variables. The results demonstrate the performance analysis of each machine learning algorithm type applied to light curve data, while also highlighting the accuracy and statistical metrics of the algorithms used in the experiments.