With the current cost of living situation in Thailand continuously rising, many recent graduates face challenges in managing their expenses in alignment with the increasing living costs. Food expenses, even for common street food, continue to surge with no sign of decreasing, despite improvements in raw material costs. Pay-Attention is a website platform designed to help recent graduates gain insights into managing and optimizing their food expenses effectively. It provides guidance on how to spend wisely, ensuring cost-effectiveness while maintaining adequate daily nutritional intake, without falling into monotonous eating habits.
ด้วยสถานการณ์ “ค่าครองชีพ” ของประเทศไทยในปัจจุบันมีแนวโน้มพุ่งขึ้นสูงเรื่อยๆ นับตั้งแต่ ยุคหลังโควิด-19 แต่ฐานเงินเดือนและรายได้ของนักศึกษาจบใหม่ ก็ยังคงมีฐานเริ่มต้นเหมือนเดิม ไม่ต่างจากหลายปีก่อน เป็นผลทำให้ประชากรที่พึ่งสำเร็จการศึกษา ในประเทศไทยจำนวนไม่น้อย ประสบกับปัญหาเรื่องการจัดการค่าใช้จ่าย ให้สอดคล้องกับค่าครองชีพอย่างเหมาะสมในปัจจุบัน ทั้งค่าใช้จ่ายคงที่ และค่าใช้จ่ายผันแปร ที่แปรเปลี่ยนไปตามวิถีชีวิตของแต่ละคน มากน้อย ตามความต้องการและรสนิยม ซึ่งเป็นค่าใช้จ่ายที่ต้องระวังและควบคุมการใช้จ่ายอย่างมีสติเสมอโดยเฉพาะค่าใช้จ่ายเรื่องอาหารที่แม้แต่ตามสั่งทั่วไปก็พุ่งสูงขึ้นเรื่อยเรื่อยไม่มีท่าทีจะลดลงแม้ต้นทุนวัตถุดิบจะปรับปรุงก็ตาม
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.
คณะเทคโนโลยีการเกษตร
The project focuses on designing and creating Art Toy Mascots that reflect the identities of the 12 departments in the Faculty of Agricultural Technology. It combines the concepts of art and agricultural technology to promote better understanding and easy recognition of each department. The project utilizes creative design and artistic toy production techniques.
คณะเทคโนโลยีการเกษตร
Durian is a crucial economic crop of Thailand and one of the most exported agricultural products in the world. However, producing high-quality durian requires maintaining the health of durian trees, ensuring they remain strong and disease-free to optimize productivity and minimize potential damage to both the tree and its fruit. Among the various diseases affecting durian, foliar diseases are among the most common and rapidly spreading, directly impacting tree growth and fruit quality. Therefore, monitoring and controlling leaf diseases is essential for preserving durian quality. This study aims to apply image analysis technology combined with artificial intelligence (AI) to classify diseases in durian leaves, enabling farmers to diagnose diseases independently without relying on experts. The classification includes three categories: healthy leaves (H), leaves infected with anthracnose (A), and leaves affected by algal spot (S). To develop the classification model, convolutional neural network (CNN) algorithms—ResNet-50, GoogleNet, and AlexNet—were employed. Experimental results indicate that the classification accuracy of ResNet-50, GoogleNet, and AlexNet is 93.57%, 93.95%, and 68.69%, respectively.