Journal of Computer and Creative Technology

Design and Evaluation of a High-Availability Secure Mail Relay with OAuth2 Authentication for Legacy Systems

2026-04-21T19:54:44+07:00

In an era of escalating cyber threats, the enforcement of Modern Authentication (OAuth 2.0) by Microsoft 365 has created a critical compatibility gap for legacy applications that cannot be modified, posing significant risks to data security and business continuity, particularly in email communication systems. This research proposes High-Availability Secure Mail Relay architecture. The core novelty lies in the development of an “OAuth2 Agent Module” an intermediary mechanism designed to seamlessly translate legacy authentication protocols into OAuth 2.0 standards without requiring source code modifications. This is integrated with a Service-Level High Availability (HA) system capable of detecting internal service failures. Experimental results confirm that (1) The proposed architecture achieves a 100% success rate in relaying emails using OAuth 2.0 standards (2) While the enhanced security processing introduces a slight latency increase to 2.158 seconds compared to traditional Basic Authentication 1.908 seconds, performance remains within acceptable limits and (3) The HA mechanism successfully executes service failover in an average of 1.312 seconds. This study contributes a practical framework for retrofitting legacy systems to comply with modern security mandates while ensuring resilience.

Analysis and Comparison of the Impact of Statistical Feature Reduction for Classification using Machine Learning

2026-04-29T00:08:10+07:00

This study aims to analyze the impact of statistical feature reduction on classification performance and to identify the optimal hyperparameter configurations for predicting medical conditions. Three machine learning algorithms—Support Vector Machine (SVM), Decision Tree (DT) and K-Nearest Neighbors (KNN) were compared using the Healthcare Risk Factors Dataset. Two filter-based feature selection methods, the Kruskal–Wallis test (KW) and Mutual Information (MI), were employed to generate a full feature set and feature subsets at the 25th, 50th, and 75th percentiles. Model performance was evaluated using 5 repeats of 5-fold Stratified K-Fold Cross-Validation, integrated with systematic hyperparameter tuning. The experimental results demonstrated that SVM achieved the highest performance using the full feature set (C = 300), yielding an accuracy of 0.9214 ± 0.0005, precision of 0.9212 ± 0.0005, recall of 0.9214 ± 0.0005, and an F1-Score of 0.9210 ± 0.0005. This accuracy significantly outperformed DT (0.8752 ± 0.0028) and KNN (0.7916 ± 0.0015). Furthermore, reducing the feature set to the 75th percentile using the KW method maintained a high accuracy of 0.9165 ± 0.0006, representing a marginal decline of only 0.49%. These findings indicate that SVM is highly suitable for disease diagnosis within this dataset. Moreover, statistical feature reduction effectively minimizes computational complexity without a significant loss in accuracy.

Optimizing Feature Selection for Multi-Task Prediction of Non-Communicable Diseases on Imbalanced Healthcare Data

2026-04-16T14:01:23+07:00

This research aims to investigate and compare the performance of feature selection techniques, encompassing Filter and Wrapper methods, for multi-task healthcare data characterized by high class imbalance. The primary objective is to develop a predictive model for non-communicable diseases (NCDs) by integrating the most efficient feature selection strategies with machine learning algorithms, evaluated through statistical metrics appropriate for imbalanced datasets. The methodology consists of six key stages: 1) data collection from Kaggle, comprising 253,680 records and 19 features; 2) data preprocessing and multi-target definition for three diseases; 3) feature selection using Filter methods (Information Gain, Gain Ratio, and Chi-Square) and Wrapper methods (Forward Selection and Backward Elimination); 4) class imbalance mitigation via the SMOTE technique; 5) classification model development using XGBoost, Random Forest, and LightGBM; and 6) model evaluation and hyperparameter optimization to identify the most suitable values. The experimental results reveal that the best-performing model, utilizing the Gain Ratio technique, significantly enhances the performance of the XGBoost model, successfully reducing the feature set from 19 to 7 key features—including BMI, Age, Income, Physical Health, General Health, Education, and Mental Health—while achieving a peak accuracy of 0.8768 and a maximum AUC of 0.9300. These findings indicate that the proposed approach is highly suitable for accurate and efficient multi-task prediction of non-communicable diseases.

Information System for Promoting the Marketing of Native Woven Fabrics in Cha‑Uat District, Nakhon Si Thammarat Province

2026-04-28T18:32:48+07:00

This research aims to 1) develop an information system to promote the marketing of local woven fabrics in Cha-uat district, Nakhon Si Thammarat province; 2) evaluate user satisfaction with the information system; and 3) assess the effectiveness of the information system. The system will assist in managing, publicizing, and marketing local woven fabric products in Cha-uat District, Nakhon Si Thammarat Province. The research was conducted using the System Development Life Cycle (SDLC) principles, employing PHP programming and a MySQL database. User satisfaction was assessed using a sample group consisting of 20 general customers interested in local woven fabrics and 5 entrepreneurs from local weaving groups, selected using a combination of accidental and intensified sampling methods. The system's effectiveness was evaluated by three information technology experts. The results showed that user satisfaction with the system's usability was very good ( = 4.72, s.d. = 0.45) and design was also very good ( = 4.68, s.d. = 0.47). The system's effectiveness was evaluated by the experts. It is at a very good level ( = 4.60, s.d. = 0.46), indicating that the system is functional and meets the needs of the system users.

The Development of an Online Hybrid Learning Lesson Incorporating the CIPPA Model to Promote Analytical Thinking Skills on Responsible Use of Information Technology for Mathayomsuksa 2 Students

2026-04-28T13:44:41+07:00

The objectives of this research were to: (1) develop an online hybrid learning lesson with an efficiency of 80/80, (2) study students’analytical thinking skills before and after learning through the online hybrid learning lesson integrated with the CIPPA model on the topic “Using Information Technology Responsibly” for Mathayomsuksa 2 students, (3) compare students’ learning achievement before and after learning with the online hybrid learning lesson, and (4) study students’ satisfaction toward the online hybrid learning lesson. The sample consisted of 39 Mathayomsuksa 2/1 students from Phutthaisong School, Phutthaisong District, Buriram Province, under the Secondary Educational Service Area Office Buriram, in the first semester of the academic year 2025. The research instruments included: (1) an online hybrid learning lesson, (2) five CIPPA-based lesson plans totalling 10 hours, (3) a 20-item multiple-choice analytical thinking test, (4) a 20-item multiple-choice learning achievement test, and (5) a student satisfaction questionnaire. The results revealed that: (1) the efficiency of the online hybrid learning lesson met the 80/80 criterion, achieving 84.13/86.17; (2) students’ analytical thinking skills after learning were significantly higher than before learning at the .05 level; (3) students’ learning achievement after learning was significantly higher than before learning at the .05 level; and (4) students’ satisfaction with the online hybrid learning lesson was at the highest level.

Driving Success Factors of LINE Micro-App Architecture: A Technical Assessment of Information System Quality and Empirical Value

2026-04-29T12:57:20+07:00

This research aimed to (1) study the success drivers of the LINE Front-end Framework (LIFF) architecture that affect information system quality, (2) evaluate the effect of information system quality on user satisfaction, and (3) examine the influence of user satisfaction on the performance of community enterprises by applying the Extended IS Success Model framework. The sample comprised 175 community members from Surin Province, drawn using stratified random sampling. The research instrument used was an online questionnaire. Data were analyzed using multiple regression, path analysis, and mediation analysis. The results showed that the success factors of the LIFF architecture, including ease of use, Integration with platforms, and data security, had a statistically significant positive impact on the information system's quality (p < 0.001). In addition, information quality influenced user satisfaction (β = 0.547, p < 0.001), and user satisfaction directly impacted the business performance of community enterprises (β = 0.654, R² = 0.428, p < 0.001). The study results show that the Extended IS Success Model appropriately describes the success of using micro-applications on the LINE platform and reflects LIFF's potential to support community enterprise operations in a real-world context.

Effects of Violence Reduction in Video Games for Esports Competitions on Policy Acceptance in Educational Institutions in Thailand

2026-01-14T07:07:06+07:00

This study employed a mixed-methods approach integrating quantitative and qualitative data. The objectives were to (1) examine perceptions of violence reduction in esports video games, (2) assess its impacts, (3) compare differences across demographic characteristics, and (4) propose policy recommendations for Thai educational institutions. The quantitative sample comprised 400 participants—200 upper secondary students and 200 undergraduates—from institutions offering esports programs, selected through simple random sampling. Qualitative data were obtained from in-depth interviews with three university lecturers as subject-matter experts. The findings indicated that (1) overall perceptions of violence reduction were moderate, with the highest scores in understanding violent content, while perceptions of actual reduction were low; (2) the overall impact was moderate, with positive effects in social and attitudinal dimensions, but the lowest in behavioral outcomes; (3) no significant gender differences were found overall, although some differences appeared in specific dimensions, and no significant differences were observed between education levels; and (4) policy recommendations emphasized age-appropriate content control systems based on international or local standards, clear institutional policies for game selection, teacher supervision, and training on psychological impacts to enhance emotional intelligence and support students’ ability to distinguish between virtual and real-world contexts sustainably.

Developing an Information System for Minor Program Student Admission through Action Research of Faculty of Humanities and Social Sciences, Prince of Songkla University

2026-02-02T18:09:53+07:00

This research aimed to develop and evaluate the quality of an information system for minor program student admission at the Faculty of Humanities and Social Sciences, Prince of Songkla University, using an action research methodology (PAOR). The study sample comprised 22 academic advisors, program chairs, and academic staff; 12 first-year undergraduate students; and 3 information technology experts. The research instruments included semi-structured interview guides, observation forms, and a system quality evaluation form. Data were analyzed using descriptive statistics. The research results showed that (1) regarding system development, the action research process based on the PAOR cycle was integrated with the System Development Life Cycle (SDLC) utilizing a 3-Tier Architecture and a relational database. It was developed using PHP and a MySQL database management system. The prominent feature of the developed system is its capability to support a Sequential Approval Workflow. It comprises key functions including online application, system-based approval workflow, real-time status tracking, automatic email notifications, and Excel report generation. The system reduced the operational processing time from 10-14 days to 3-5 days and decreased paper usage by 80%. (2) Regarding the system quality evaluation, the overall expert evaluation was at the highest level. When considering each dimension ranked by mean score from highest to lowest, it was found that information security and access control received the highest evaluation score. This was followed by system performance and efficiency, and system usability and user interface design, which were equally rated at the highest level, and finally system functionality and user requirements, which was also at the highest level.

Analysis of Reversibility and Critical Depth in Quantum Computers under Noise via Circuit Simulation

2026-02-03T09:38:46+07:00

This research aims to: 1) simulate the time-reversibility behavior in chaotic quantum systems (Ising model), 2) analyze the quantitative relationship between noise levels (ε) and system sizes (N), and 3) propose the critical depth criterion for evaluating the preliminary limits of quantum computers. The research methodology involves simulating the behavior of quantum systems via circuit simulation using Qiskit to evaluate the return probability under depolarizing error ranging from 0-2%. The results indicate that noise causes a rapid decay in the system's reversibility. Larger systems (N=6) demonstrate approximately 45% higher sensitivity to noise than smaller systems (N=4), based on the relative reduction of the critical depth, which decreases from 15 steps to 11 steps at a 1% noise level. Based on these findings, this study proposes critical depth as a simulation-based index for evaluating noise-induced limitations in NISQ-era quantum computers.

The Competency Development of Analytical Thinking Abilities of Knowledge on Factors Affecting Plant Growth and Response of Grade 11 Students through Learning Management Based on the TPACK Framework Model

2026-04-30T04:48:03+07:00

The purposes of this research were 1) develop lesson plans based on the Technological Pedagogical Content Knowledge (TPACK) framework with an efficiency criterion of 75/75; 2) enhance students’ analytical thinking ability after learning through TPACK-based instruction; 3) compare students’ learning achievement before and after learning through TPACK-based learning management; and 4) to investigate Grade 11 students’ satisfaction toward learning management activities based on the TPACK framework model. The sample consisted of 25 students, Grade 11 students from class 5/2 at Triam Udom Suksa Phatthanakan Ubon Ratchathani School in the second semester academic of 2025 year, selected by cluster random sampling, using the classroom as the sampling unit. The research instruments included: 1) lesson plans, 2) the analytical thinking ability test, 3) a learning achievement test, and 4) a student satisfaction questionnaire. The data were analyzed using mean, percentage, standard deviation, and the t-test analysis (One Sample t-test). The results revealed that 1) the efficiency of the TPACK-based lesson plans was 83.00/75.40, which met the established criterion; 2) students’ analytical thinking abilities after learning were significantly higher than before learning at the 0.05 level; 3) students’ post-test learning achievement was significantly higher than their pre-test achievement at the 0.05 level; and 4) the overall level of students’ satisfaction toward the TPACK-based learning management activities was at the highest level.

A Retrieval-Augmented Generation Framework for Traditional Chinese Medicine Herb Recommendation Using Symptom-Focused and Ingredient-Based Embeddings

2026-03-16T05:17:54+07:00

Traditional Chinese Medicine (TCM) herb recommendation systems face significant challenges in accurately matching complex patient symptoms with appropriate herbal treatments due to the intricate relationships between symptoms, herb properties, and traditional diagnostic principles. This research proposes a retrieval-augmented generation (RAG) framework that leverages specialized symptom-focused and ingredient-based embeddings to explore potential improvements in recommendation accuracy and clinical relevance. We developed three distinct RAG systems: the first focuses exclusively on symptom-herb relationships by utilizing detailed indication and effect data from comprehensive TCM knowledge bases, the second incorporates rich herb properties and meridian information to capture the fundamental characteristics of each medicinal substance, and the third combines both knowledge perspectives through integrated retrieval mechanisms. Our comprehensive experimental evaluation, conducted on a dataset of 15,000 historical TCM prescriptions with 100 test samples, reveals nuanced findings regarding the effectiveness of domain-specific embeddings. The symptom-focused RAG approach achieved modest improvements with 4.76% higher precision@5 (0.1320 vs. 0.1260) and 2.22% higher recall@5 (0.0967 vs. 0.0946) compared to the baseline LLM-only approach, though these differences did not achieve statistical significance (p > 0.05). Notably, the baseline LLM demonstrated robust performance across multiple metrics, including superior overall accuracy (0.1900), Mean Average Precision (0.0803), and NDCG@5 (0.1475), reflecting the substantial pre-trained medical knowledge embedded within modern large language models. The ingredient-focused and combined RAG approaches showed performance decrements relative to baseline, with 7.94% lower precision@5 and 7.29% lower recall@5, suggesting that simple knowledge concatenation strategies may introduce conflicting signals without careful integration design. These findings provide important insights into both the opportunities and challenges of applying retrieval-augmented generation to Traditional Chinese Medicine applications. While specialized domain embeddings show potential for targeted improvements in specific retrieval scenarios, achieving consistent and statistically significant performance gains requires further optimization of embedding construction strategies, retrieval mechanisms, knowledge integration approaches, and potentially larger-scale training datasets. The proposed framework establishes a methodological foundation for future research in TCM recommendation systems and highlights the importance of rigorous experimental validation, careful hyperparameter tuning, and sophisticated knowledge fusion techniques when bridging traditional medical knowledge with modern artificial intelligence capabilities. These results empirically demonstrate that embedding design choices critically determine RAG system performance in TCM applications, where misaligned knowledge integration can degrade rather than improve recommendation quality.

Logfile-Based SQL Injection Detection and Prevention System for PHP Web Applications

2026-03-09T07:34:26+07:00

This research aims to 1) analyze real-world SQL Injection attack patterns from system Logfile, 2) design and develop an automated SQL Injection detection and prevention system using rule-based techniques, and 3) evaluate the system's performance. Methodology The study was conducted in three phases 1) collecting and analyzing 4,649 historical log records to establish detection rules 2) validating the algorithm with a new dataset of 4,312 records and 3) evaluating performance using TP, FP, FN, and TN metrics through a real-world deployment on the Cultural Map Thailand information system over a period of 830 days. The findings demonstrate that the system achieved up to 100% Accuracy and F1-Score across all testing phases under controlled conditions. During the practical implementation, the system successfully detected a total of 25,660 attack attempts. Furthermore, the results indicate a significant decrease in the average daily attack rate post-deployment, illustrating the system's deterrent effect and its capability to effectively identify complex evasion techniques. This approach significantly enhances the long-term security posture of web-based information systems.

Effect of Internal and External Interactive Scenarios Video on Science Problem-Solving Abilities of Grade 9 Students

2026-03-19T16:02:39+07:00

The purposes of this research were: 1) to compare Students’ Problem-Solving Abilities Before and After Learning Through Internal Interactive Scenarios Video; 2) to compare students’ Problem-Solving Abilities Before and After Learning Through External Interactive Scenarios Video; and 3) to Compare Students’ Problem-Solving Abilities After Learning Through Internal and External Interactive Scenarios Video. The research sample consisted of 52 Grade 9 students from the Chom Phra 1 Integrated Educational Network, Chom Phra District, Surin Province. The participants were selected using the matched-pair sampling method. The research instruments included: 1) Internal and External Interactive Scenarios Video, 2) science lesson plans, and 3) a science problem-solving ability assessment test. Data were analyzed using mean, standard deviation (S.D.), and t-test for hypothesis testing. The research findings revealed that: 1) Students who learned using the Internal Interactive Scenarios Video achieved significantly higher post-learning problem-solving scores than their pre-learning scores at the .05 significance level. 2) Students who learned using the External Interactive Scenarios Video achieved significantly higher post-learning problem-solving scores than their pre-learning scores at the .05 significance level. 3) Students using the Internal Interactive Scenarios Video demonstrated significantly higher problem-solving abilities than those using the External Interactive Scenarios Video at the .05 significance level.

Development of a Centralized System for Exchanging Geometric Point Movements in 3D Models for Visual Effects and Computer Animation

2026-03-30T11:11:33+07:00

This study explores techniques for reducing file sizes and processing time of geometric point movements in 3D models, leading to the development of a GPU Cache algorithm. The objectives of the research were: 1) to design and develop a centralized system for exchanging geometric point movement data in 3D models between visual effects and computer animation software, and 2) to examine user satisfaction and compare the usability of the developed system in supporting workflows in visual effects and computer animation. The sample group consisted of 34 undergraduate students majoring in Multimedia Technology at Rajamangala University of Technology Isan, selected based on their prior coursework in visual effects and computer animation. The research employed mean, standard deviation, and t-test statistics. Results indicated that 1) the developed centralized system was highly effective, with an average score of 4.38, and 2) the sample group showed a statistically significant difference in satisfaction levels before and after using the centralized system at the .05 significance level. Satisfaction after using the system was higher than before, with a mean score of 4.157.

A Comparison of Different Guidance Patterns in Interactive Video-Based Online Learning on Mathematics Achievement of Grade 8 Students

2026-03-03T09:48:09+07:00

The purposes of this study were: (1) to compare Grade 8 students’ academic achievement before and after using video guidance in an interactive video-based online mathematics course; (2) to compare their achievement before and after using infographic guidance; and (3) to compare post-test achievement between students using video guidance and those using infographic guidance. The population consisted of 153 Grade 8 students from the Jom Phra 1 Integrated School Network, Jom Phra District, Surin Province. The sample (n = 56) was obtained through a two-stage sampling process. First, simple random sampling (school-level) selected three schools: Ban Phang Udom Sombun Witthaya School (15 students), Ban Khamin (Rueang Rat Rangsan) School (22 students), and Ban Chum Saeng School (19 students). Then, systematic sampling was used to assign students into two experimental groups: 29 students in the video-guidance group and 27 students in the infographic-guidance group. The research instruments included: (1) interactive videos with embedded questions on Statistics, (2) video guidance materials, (3) infographic guidance materials, (4) lesson plans, and (5) an academic achievement test. Data were analyzed using mean, standard deviation, and t-test. The results showed that: (1) students in the video-guidance group had significantly higher post-test scores than pre-test scores at the .05 level; (2) students in the infographic-guidance group also showed significantly higher post-test scores than pre-test scores at the .05 level; and (3) there was no significant difference in post-test achievement between the two groups at the .05 level.

The Illusion of Multimedia Exposure: Predicting Study Engagement in Kuwaiti Undergraduates

2026-03-26T11:01:31+07:00

Amidst the global integration of Technology-Enhanced Learning (TEL), this study investigates the relationship between students' holistic multimedia exposure and their study engagement in the under-researched context of Kuwaiti higher education. Drawing on the Cognitive Theory of Multimedia Learning (CTML), the study examines if increased exposure to multimedia predicts higher levels of study engagement. A quantitative, cross-sectional survey design was employed. A sample of 222 undergraduate students from Kuwait’s Public Authority for Applied Education and Training (PAAET) completed a self-administered online questionnaire. The sample was predominantly female (85.1%) and largely within the 18–21 age range (76.1%), indicating limited demographic diversity. Multimedia exposure was measured using a custom 8-item scale (α = .893), and study engagement was assessed using the 9-item Utrecht Work Engagement Scale (UWES-S) (α = .903). Data were analyzed using t-tests, ANOVA and simple linear regression. The findings indicate that while students report high levels of study engagement, particularly on affective dimensions, their multimedia exposure is dominated by traditional tools like PowerPoint. No significant differences were found across gender or age groups. Crucially, linear regression analysis revealed that multimedia experience is not a statistically significant predictor of study engagement (R² = .002, p = .553). The assumption that frequent multimedia use inherently enhances student engagement is challenged. In the Kuwaiti context, technology functions primarily as a delivery medium rather than a catalyst for engagement. This underscores the critical importance of pedagogical design and instructional quality over mere technological access in fostering meaningful student involvement.

The Design and Development of Learning Management Process using Digital Technology to Enhance the Learning Efficiency of Learners

2026-01-30T10:25:01+07:00

The design and development of a learning management process using digital technology to enhance the learning effectiveness of students is a transformation of teaching methods to be modern and efficient. This involves applying digital technology to create an engaging, challenging learning experience that meets the needs of learners in the digital age, with a focus on creating diverse and interesting learning experiences for students. In this digital age, educators must shift their role from being lecturers to facilitators and creators of learning activities. Learning management is the key to enabling learners to achieve their intended purposes and to advance rapidly in science and technology. Digital technology thus plays a significant role in the daily lives of most people who need to engage with information and news, and it is crucial in designing learning management. Therefore, instructors should consider choosing appropriate learning management techniques, selecting technology media and learning resources that will support learners' learning, using a variety of assessment methods, with an emphasis on the learners themselves, to enable each learner to develop according to their potential and to apply what they have learned in real life. Therefore, managing learning through digital technology and innovative methods requires educators to incorporate new technologies and innovations into their teaching management to enhance efficiency and create a more engaging learning experience, including convenient and borderless learning. Learning management in this digital age encompasses online, on-site, or blended learning, with the goal of developing essential skills for the 21st century and preparing for a changing world.

The Role and Development Approach for Innovative Teachers Competence in Creating Learning Management Innovations with Digital Technology

2026-01-19T07:37:27+07:00

The role and development for innovative teacher competencies in creating learning management innovations with the digital technology era is extremely important, enabling teachers to adapt and apply digital technology effectively and modernly in learning management, with the aim of developing learners to possess the necessary skills and competencies for the 21st century. The development of innovative teacher competencies enhances teachers' abilities to create and apply educational innovations in the learning process to continuously improve the quality of learners, which involves developing knowledge, skills, and attributes essential for being an innovator. The creation of innovative learning management involves the development of new, effective and modern teaching methods to promote creative and sustainable learning among students, focusing on improving the learning process, using technology, and applying new ideas to teaching management, so that students can engage in meaningful learning and apply knowledge in real life. Importantly, learning management in the digital age involves using digital technology and online media as tools for teaching and learning management to enhance effectiveness and create a more diverse and engaging learning experience in the present era.