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Vol. 2 No. 1 (2025): Volume 2 Issue 1 (November 2025)

Vol. 2 No. 1 (2025): Volume 2 Issue 1 (November 2025)
Archives
Published: 2025-11-28
Articles
A Study on Anomaly Detection and Hybrid Forecasting Model Using Underground Stormwater Pipe Water Level Time-Series Data for Urban Flood Prediction
Jang-won Lee; Nak Hyun Jung
As urban flooding risks intensify due to climate change, developing accurate and real-time predictive systems has become critical for disaster preparedness and response. This study proposes an AI-based flood prediction model...
Time Series Prediction Anomaly Detection Water Level Prediction Hybrid Model LSTM ConvLSTM Transformer
2-16
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A Hybrid Ensemble Framework for Privilege Anomaly Detection in Multi-Cloud Environments
Chi-Sung Kim
With the rapid expansion of cloud computing, privilege abuse and escalation attacks in multi-cloud environments are emerging as a core security threat for organizations. Existing research shows limitations due to a lack of context from reliance...
Multi-Cloud Security Privilege Anomaly Detection Hybrid Ensemble Explainable AI (XAI) ROC-AUC Precision-Recall Curve
17-29
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Research on how to increase user engagement of Korean AI tutoring service using token economy
Su Choe
While AI tutoring has strengths in personalization, it is limited by a lack of emotional and social interaction to keep learners engaged. To address this issue, this research proposes a new model that fuses AI tutoring with blockchain-based...
30-40
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Causal Policy Analysis in Financial Time Series Using Deep Learning X-Learner
Taeyeon Oh; Joongho Chang
This study employs the X-Learner algorithm with deep learning models (MLP, LSTM, GRU, CNN) to causally estimate performance differences between cyclical (T=1) and defensive (T=0) asset classes in financial time-series data. The results show that...
X-Learner Causal Inference Time-Series Analysis Deep Learning
41-49
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Enhancing Stock Price Prediction using StockGPT: An Empirical Study on the Effectiveness of Macroeconomic Indicators
Jieun Oh
This study explores the enhancement of stock price prediction using StockGPT, a transformer-based generative model, by integrating macroeconomic indicators and feature engineering techniques. Using data from U.S. tech stocks and the S&P 500...
StockGPT stock price prediction macroeconomic indicators transformer model feature engineering Permutation Importance
50-57
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