In the era where information technology plays a significant role in various fields, the use of website to support education has become essential. This case study focuses on the development of a website for the Object Oriented Programming (OOP) course at King Mongkut's Institute of Technology Ladkrabang (KMITL) to facilitate instructors and teaching assistants in grading, assessing student work, and tracking student progress. The developed system helps reduce grading errors, ensures accurate and timely assessments, and enables efficient monitoring of students' academic performance. Additionally, the platform allows students to schedule project submissions and track their grades, while providing statistical data on student performance. This development aims to modernize and enhance the quality of teaching and learning.
ในปัจจุบันคณะเทคโนโลยีสารสนเทศ สถาบันเทคโนโลยีพระจอมเกล้าเจ้าคุณทหารลาดกระบัง ได้เปิดการเรียนการสอนวิชา object oriented programming และให้บริการเว็บไซต์ สำหรับรายวิชา เพื่ออำนวยความสะดวกให้แก่ผู้สอน และ ผู้เรียน โดยทางทีมผู้พัฒนาได้เล็งเห็นว่า ขั้นตอนในกรอกคะแนนเก็บของนักศึกษาว่าอาจเกิดปัญหาจากการกรอกคะแนนจากการส่งงานหรือการส่งโปรเจคผิดอาจส่งผลกระทบถึงเกรดของนักศึกษา ปัญหาต่อที่ผู้สอนได้พบเจอคือผู้ช่วยสอนเดินตรวจงานของนักศึกษาได้ลำบากเพราะตำแหน่งการแสดงผลในระบบไม่ชัดเจนจึงทำให้เกิดความล่าช้าในการตรวจงาน
คณะบริหารธุรกิจ
This book introduces basic management concepts that are applicable to technological innovation development. It encompasses various tech settings like Agro & Health tech, in addition to the more commonly referred digital sector.
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.
คณะแพทยศาสตร์
Background: The RGL3 gene plays a role in key signal transduction pathways and has been implicated in hypertension risk through the identification of a copy number variant deletion in exon 6. Genome-wide association studies have highlighted RGL3 as associated with hypertension, providing insights into the genetic underpinnings of the condition and its protective effects on cardiovascular health. Despite these findings, there is a lack of data that confirms the precise role of RGL3 in hypertension. Additionally, the functional impact of certain variants, particularly those classified as variants of uncertain significance, remains poorly understood. Objectives: This study aims to analyze alterations in the RGL3 protein structure caused by mutations and validate the location of the ligand binding sites. Methods: Clinical variants of the RGL3 gene were obtained from NCBI ClinVar. Variants of uncertain significance and likely benign were analyzed. Multiple sequence alignment was conducted using BioEdit v7.7.1. AlphaFold 2 predicted the wild-type and mutant 3D structures, followed by quality assessment via PROCHECK. Functional domain analysis of RasGEF, RASGEF_NTER, and RA domains was performed, and BIOVIA Discovery Studio Visualizer 2024 was used to evaluate structural and physicochemical changes. Results: The analysis of 81 RGL3 variants identified 5 likely benign and 76 variants of uncertain significance (VUS), all of which were missense mutations. Structural modeling using AlphaFold 2 revealed three key domains: RasGEF_NTER, RasGEF, and RA, where mutations induced conformational changes. Ramachandran plot validation confirmed 79.7% of residues in favored regions, indicating an overall reliable structure. Moreover, mutations within RasGEF and RA domains altered polarity, charge, and stability, suggesting potential functional disruptions. These findings provide insight into the structural consequences of RGL3 mutations, contributing to further functional assessments. Discussion & Conclusion: The identified RGL3 mutations induced physicochemical alterations in key domains, affecting charge, polarity, hydrophobicity, and flexibility. These changes likely disrupt interactions with Ras-like GTPases, impairing GDP-GTP exchange and cellular signaling. Structural analysis highlighted mutations in RasGEF and RA domains that may interfere with activation states, potentially affecting protein function and stability. These findings suggest that mutations in RGL3 could have functional consequences, emphasizing the need for further molecular and functional studies to explore their pathogenic potential.