Default Risk Prediction of Enterprises Based on Convolutional Neural Network in the Age of Big Data: Analysis from the Viewpoint of Different Balance Ratios by Zhe Li, Zhenhao Jiang, Xianyou Pan

“…In the age of big data, machine learning models are globally used to execute default risk prediction. …”
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FINTECH REGULATION IN SCHOLARLY DEBATE: A BIBLIOMETRIC ANALYSIS by Fahmi Ali Hudaefi

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TransTab: A transformer-based approach for table detection and tabular data extraction from scanned document images by Yongzhou Wang, Wenliang Lv, Weijie Wu, Guanheng Xie, BiBo Lu, ChunYang Wang, Chao Zhan, Baishun Su

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A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriers by Pinya Lu, Xiaolu Lin, Xiaofeng Liu, Mingfeng Chen, Caiyan Li, Hongqin Yang, Yuhua Wang, Xuemei Ding

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Study of model construction of fuel production from waste plastic pyrolysis based on machine learning by CHEN Sihan, YUAN Zhilong, WANG Ye, SUN Yifei*

“…A machine-learning approach was applied to utilize data from non-catalytic and molecular sieve catalytic processes and to build a model for analyzing raw material pyrolysis. …”
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Integration of Deep Learning Neural Networks and Feature-Extracted Approach for Estimating Future Regional Precipitation by Shiu-Shin Lin, Kai-Yang Zhu, He-Yang Huang

“…This study proposes a deep neural network (DNN) as a downscaling framework with nonlinear features extracted by kernel principal component analysis (KPCA). KPCA utilizes kernel functions to extract nonlinear features from the source climatic data, reducing dimensionality and denoising. …”
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Data driven modeling of TiO2 PVP nanofiber diameter using LSTM and regression for enhanced functional performance by Harshada Mhetre, Sagar Pande, Babita Singla, Pavan Hiremath, Samriddh Sahu, Sarvesh Sorte, Ketan Kotecha, Nithesh Naik

“…TiO₂ + PVP nanofibers were fabricated under diverse conditions, including changes in applied voltage, solution concentration, and distance between tip to collector. The acquired data underwent analysis using LSTM and regression models to assess their predictive capabilities. …”
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Human Behavior Analysis: A Comprehensive Survey on Techniques, Applications, Challenges, and Future Directions by Siham Essahraui, Ismail Lamaakal, Yassine Maleh, Khalid El Makkaoui, Mouncef Filali Bouami, Ibrahim Ouahbi, Ahmed A. Abd El-Latif, May Almousa, Joel J. P. C. Rodrigues

“…Human Behavior Analysis (HBA) has emerged as a critical interdisciplinary field, combining psychology, sociology, artificial intelligence, and data science to model, understand, and predict human behavior across diverse domains. …”
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Interpretable Multi-Sensor Fusion of Optical and SAR Data for GEDI-Based Canopy Height Mapping in Southeastern North Carolina by Chao Wang, Conghe Song, Todd A. Schroeder, Curtis E. Woodcock, Tamlin M. Pavelsky, Qianqian Han, Fangfang Yao

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Predicting soil organic carbon with ensemble learning techniques by using satellite images for precision farming by Shyamal Mundada, Pooja Jain

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The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure by Nima Kianfar, Benn Sartorius, Colleen L. Lau, Robert Bergquist, Behzad Kiani

“…Traditional spatial techniques, including spatial autocorrelation using global Moran’s I, Geary’s C (Amgalan et al., 2022), and Ripley’s K Function (Kan et al., 2022), Local Indicators of Spatial Association (LISA) (Sansuk et al., 2023), hotspot analysis by Getis-Ord Gi* (Lun et al., 2022), spatial lag models (Rey & Franklin, 2022), and Geographically Weighted Regression (GWR) (Kiani et al., 2024) are designed to explicitly incorporate the spatial structure of data into spatial modelling, often referred to as spatially aware models (Reich et al., 2021). …”
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Affective Video Content Analysis: Decade Review and New Perspectives by Junxiao Xue, Jie Wang, Xiaozhen Liu, Qian Zhang, Xuecheng Wu

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Measuring Up: Rasch Analysis of Reading Comprehension Test for Informal Education Learners by Arandha May Rachmawati, Agus Widyantoro

“…The Quest program is used to analyze data in this research. The result showed that the instrument tests provided poor quality even if they fit the RASCH model, so they must be reviewed again. …”
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Effectiveness of Problem-Based Learning and Discovery Learning Models on Learning Outcomes of Social Science Students by Walipah Walipah, Riril Mardiana Firdaus, Farida Chasanah

“…Data analysis techniques use the t-test and Manova test. …”
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Efficiently Learning an Encoder That Classifies Token Replacements and Masked Permuted Network-Based BIGRU Attention Classifier for Enhancing Sentiment Classification of Scientific... by Muhammad Inaam Ul Haq, Khalid Mahmood, Qianmu Li, Ashok Kumar Das, Sachin Shetty, Majid Hussain

“…Our model outperforms state-of-the-art models like LSTM-GRU, Bert-BiLSTM, Bert-LSTM-CNN and MPNet, Electra, BiGRU, and machine learning models in terms of accuracy, precision, recall, F1 and kappa measure which further solidifies its superiority in scientific text sentiment analysis tasks.…”
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Innovation in Mathematics Learning Through E-Learning Ethnomathematics: Creative Thinking Skills and Learning Outcomes by Rosidin Rosidin, Rangga Firdaus, Roseleena Anantanukulwong, Johanis Kinda

“…The research sample consisted of 80 students selected through purposive sampling techniques. The data collection instrument was an essay test to measure students’ creative thinking skills and learning outcomes. …”
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Deep Learning Innovations: ResNet Applied to SAR and Sentinel-2 Imagery by Giuliana Bilotta, Luigi Bibbò, Giuseppe M. Meduri, Emanuela Genovese, Vincenzo Barrile

“…Likewise, data from SAR satellites, such Copernicus’ Sentinel-1 and Jaxa’s ALOS PALSAR, provide diverse environmental investigations, allowing different types of spatial information to be analysed thanks to the particular features of analysis based on radar. …”
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Sentiment prediction based on analysis of customers assessments in food serving businesses by Zoltan Geler, Miloš Savić, Brankica Bratić, Vladimir Kurbalija, Mirjana Ivanović, Weihui Dai

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Machine learning based predictive insights into compressive strength and strength retention of magnesium oxychloride cement by Ahmad Nawaz, M. Zohaib Nawaz, Leyang Lv, Yingwu Zhou

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Comparative analysis of writing strategies between Malaysian and Indonesian students by Noor Azli Affendy Lee, Ryani Yulian, Nur Husna Serip Mohamad, Ufi Ruhama', Rofiza Aboo Bakar

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