Optimization for threat classification of various data types-based on ML model and LLM by Chaerim Hong, Taeyeon Oh

“…It is designed to be applied to both ML models and LLM by systematizing data labeling and data formats. The results showed that the constructed learning model performed well in both text analysis and source code analysis. …”
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Data-Driven Decision Support for Smart and Efficient Building Energy Retrofits: A Review by Amjad Baset, Muhyiddine Jradi

“…This review explores the novel integration of data-driven approaches, including artificial intelligence (AI) and machine learning (ML), in advancing building energy retrofits. …”
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Adaptive Differential Privacy Cox-MLP Model Based on Federated Learning by Jie Niu, Runqi He, Qiyao Zhou, Wenjing Li, Ruxian Jiang, Huimin Li, Dan Chen

“…This paper enhances accuracy and reliability in survival analysis by integrating differential privacy, deep learning, and the Cox proportional hazards model within a federated learning framework. …”
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Impact of Learning Motivation and Physical Condition on Physical Education Learning Outcomes in Junior High School Students Aged 13-15 Years: A Analysis studies by Muhammad Fikri, Dedi Nofrizal, Agung Nugroho, Hafiz Yazid Lubis

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Portfolio selection based on market states acquired via price and non-price data by Andy Chung, Kumiko Tanaka-Ishii, Takehisa Yairi

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Evaluating ensemble models for fair and interpretable prediction in higher education using multimodal data by Felipe Emiliano Arévalo-Cordovilla, Marta Peña

“…However, existing models often lack comprehensive data integration and comparison with state-of-the-art techniques. …”
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Learning Analytics in a Non-Linear Virtual Course by Jhon Mercado, Carlos Mendoza-Cardenas, Luis Fletscher, Natalia Gaviria-Gomez

“…In addition to performance prediction, we conducted a clustering analysis that identified four distinct online learning patterns recurring across various cumulative weight assessments. …”
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Application of data query robots based on large language models in the medical field by QUAN Xiaoxiao, XIONG Wenju, PAN Junjie, ZENG Huatang

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Robust confinement state classification with uncertainty quantification through ensembled data-driven methods by Yoeri Poels, Cristina Venturini, Alessandro Pau, Olivier Sauter, Vlado Menkovski, the TCV Team, the WPTE Team

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Assessing Teaching Effectiveness in Journalism and Communication: A Data-Driven Perspective Using HyperSoft Set by Xiaoxi Zhang

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Biological age prediction in schizophrenia using brain MRI, gut microbiome and blood data by Rui Han, Wei Wang, Jianhao Liao, Runlin Peng, Liqin Liang, Wenhao Li, Shixuan Feng, Yuanyuan Huang, Lam Mei Fong, Jing Zhou, Xiaobo Li, Yuping Ning, Fengchun Wu, Kai Wu

“…Here we evaluated the performance of machine learning models for biological age prediction by using the integrated features from multi-biological data of 140 healthy controls and 43 patients with schizophrenia, including brain MRI, gut microbiome, and blood data. …”
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Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning by Sangwoo Park, Osvaldo Simeone

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Synergistic hyperspectral and SAR imagery retrieval of mangrove leaf area index using adaptive ensemble learning and deep learning algorithms by Jun Sun, Weiguo Jiang, Bolin Fu, Hang Yao, Huajian Li

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Influence of Parenting Styles on Students’ Performance under Modular Distance Learning by Leomarich F Casinillo, Nicolle Agravante, Athena Claire N. Baldevia, Erin Chanelle O. Tang

“…The data gathered were analyzed through standard descriptive measures and correlational analysis. …”
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Arabic Opinion Classification of Customer Service Conversations Using Data Augmentation and Artificial Intelligence by Rihab Fahd Al-Mutawa, Arwa Yousuf Al-Aama

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Evolution, topics and relevant research methodologies in business intelligence and data analysis in the academic management of higher education institutions. A literature review by M. Correa-Peralta, J. Vinueza-Martínez, L. Castillo-Heredia

“…Thematic analysis revealed ten clusters emphasizing predictive modeling, educational innovation, and online learning. …”
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Machine learning-based estimation of crude oil-nitrogen interfacial tension by Safia Obaidur Rab, Subhash Chandra, Abhinav Kumar, Pinank Patel, Mohammed Al-Farouni, Soumya V. Menon, Bandar R. Alsehli, Mamata Chahar, Manmeet Singh, Mahmood Kiani

“…In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil – nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs. …”
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Short-term Power Load Forecasting Method of Data Center Considering PUE by WU Jin-song, ZHANG Shao feng, XU Xiang-min, LI Shu-tao, HUANG Yong, LIAO Xiao

“…Therefore, the influence of PUE is considered in the prediction model, and the adaptive moment estimation algorithm is used for deep learning. Finally, by predicting the actual power load of the data center computer room of a certain electric power design institute in Guangzhou, introducing the PUE value into the model can effectively improve the accuracy of the short-term load forecast of the data center.…”
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Machine Learning System for Predicting Cardiovascular Disorders in Diabetic Patients by A. Mayya, H. Solieman

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Comparing Different Machine Learning Techniques in Predicting Diabetes on Early Stage by Shweta Yadu, Rashmi Chandra, Vivek Kumar Sinha

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