Academic Journal of Science and Applied Science

A School Safety System for Detecting Threatening Individuals and Providing Escape Routes via CiRA CORE Platform

2025-04-27T15:08:54+07:00

This research aims to develop and evaluate the effectiveness of a system for detecting dangerous individuals and recommending escape routes within a school environment using the CiRA CORE platform. The system processes images from CCTV cameras with the YOLO V4-tiny model to detect weapons and employs Dijkstra's algorithm to calculate the most suitable escape route. The results are displayed through a real-time notification system. The research findings revealed that: Part 1 The YOLO V4-tiny model has high performance in terms of speed, resource efficiency, and accuracy in detection. Part 2 Dijkstra's algorithm is efficient for calculating the shortest distance for escape routes. Part 3 The collaboration between the CiRA CORE platform and Line Notify can accurately notify the location and escape route with 100 percent precision. Part 4 The collaboration between the CiRA CORE platform and the web application can accurately identify the location and escape route with 100 percent precision.

Health Development Tracking System for Kindergarten Students A Case Study of Ban Khun Sri School

2025-05-19T13:52:19+07:00

The objectives of this research are 1) to analyze and design a health development tracking system for kindergarten students; 2) to develop a health development tracking system for kindergarten students; and 3) to evaluate the satisfaction with the health development tracking system for kindergarten students. The tools used in the system development include Visual Studio Code, Bootstrap, MySQL, as well as JavaScript, CSS, HTML, SQL, and PHP languages. The evaluation includes a performance assessment questionnaire and a satisfaction questionnaire to calculate the mean and standard deviation.

A study found that a health monitoring system for kindergarten students, focusing on the case study of Ban Khun Sri School, was designed with five main functions: 1) recording height and weight, 2) recording health status, 3) recording daily routines, 4) reviewing students' overall development, and 5) monitoring individual student progress. When the system was evaluated for effectiveness, it was rated at a very high level (x ̅ =4.38, S.D. = 0.11) In terms of user satisfaction, it also achieved an excellent (x ̅= 4.54, S.D. = 0.14) This system facilitates teachers’ work and enables parents and administrators to easily monitor students' health development.

Development of a Deep Learning Model for Sugarcane Disease Detection Using Leaf Images

2025-06-26T11:07:09+07:00

This research aims to develop a deep learning model for detecting and classifying four major sugarcane diseases found in Thailand: sugarcane mosaic disease, red rot, rust, and leaf scorch. The study utilizes sugarcane leaf images as input data. The development process includes data preparation, dataset diversification through data augmentation, and training models using EfficientNetB0 and MobileNetV2 to compare performance. The experimental results show that EfficientNetB0 achieved the highest accuracy with an F1-Score of 0.95. Furthermore, an analysis of the effects of image brightness and blur on model performance reveals that these factors do not impact prediction accuracy, demonstrating the model's robustness under varying environmental conditions. This research highlights the potential of applying the developed model for effective sugarcane disease detection and classification, supporting disease management in the agricultural sector.

All positive integer solutions of the Diophantine equation 1/w+1/x+1/y+1/z=1/2

2025-07-01T15:55:04+07:00

In 2018, Bai studied and found all positive integer solutions of the Diophantine equation , where and are positive integers such that . However, it was later found that the solutions were incomplete. In this research, we proceeded to find all positive integer solutions of the equation and there was a total of 108 solutions.