Measuring the impact of ChatGPT in enhancing number sense acquisition: A mixed-method study by Kadir, Gita Fajrin Jafar, Benjamin B. Mangila

“…Based on these findings, this study recommends that educators consider incorporating ChatGPT to complement traditional teaching methods to enhance the overall learning experience of number concepts.…”
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The Research on Precise Monitoring Methods for Grain Planting Areas Based on High-precision UAV Remote Sensing Images by XU Chang, WANG Chunxiao, LIU Lu, YAN Xiaobin, LIU Xiaojuan, Chen Hui, CHENG Mingxing, FAN Yewen

“…This method has a more stable training process, and the IoU is 5% $\sim$ 10% higher than that of unsupervised transfer learning models and fully supervised models with a small number of samples.…”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

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Using Machine Learning for Recognition of Alzheimer’s Disease Based on Transcription Information by U. A. Vishniakou, Chu Yue Yu

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Exploring Kampung Inggris Pare: Indonesia's Foremost English Learning Hub by Ruminda Ruminda, Widiati Isana

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Fraud Detection on Crowdfunding Platforms Using Multiple Feature Selection Methods by Seunghun Lee, Heemin Park, Hyun-Chul Kim

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Uncertainty Quantification to Assess the Generalisability of Automated Masonry Joint Segmentation Methods by Jack M. W. Smith, Chrysothemis Paraskevopoulou

“…However, for such methods to be applied in practice to a safety-critical situation, it is necessary to validate their conclusions. …”
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Research Progress on Identification and Extraction Methods of Soil and Water Conservation Measures by TIAN Pei, REN Yiling, CHEN Yan

“…The identification and extraction methods mainly include visual interpretation, traditional machine learning, object-oriented classification methods, and deep learning models. …”
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Predicting soil organic matter using corrected field spectra and stacking ensemble learning by Yu Wang, Xuhui Yan, Rongyanting Huo, Longcai Zhao, Jie Peng, Yongsheng Hong, Jing Liu

“…In the practical application of field spectroscopy, eliminating interference through spectra correction methods is an effective strategy. The field prediction of SOM using spectra correction algorithms in conjunction with ensemble learning remains a significant and unresolved challenge. …”
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Predicting the time to get back to work using statistical models and machine learning approaches by George Bouliotis, M. Underwood, R. Froud

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Integrating Machine Learning, SHAP Interpretability, and Deep Learning Approaches in the Study of Environmental and Economic Factors: A Case Study of Residential Segregation in Las... by Jingyi Liu, Yuxuan Cai, Xiwei Shen

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Malicious Traffic Detection Method for Power Monitoring Systems Based on Multi-Model Fusion Stacking Ensemble Learning by Hao Zhang, Ye Liang, Yuanzhuo Li, Sihan Wang, Huimin Gong, Junkai Zhai, Hua Zhang

“…Current malicious traffic detection methods mostly rely on single machine learning models, which face problems such as poor generalization, low detection accuracy, and instability. …”
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Deep learning-based method for grading histopathological liver fibrosis in rodent models of metabolic dysfunction-associated steatohepatitis by Soo Min Ko, Jae-ik Shin, Jae-ik Shin, Yiyu Hong, Hyunji Kim, Insuk Sohn, Ji-Young Lee, Hyo-Jeong Han, Da Som Jeong, Yerin Lee, Woo-Chan Son

“…This scoring system is part of a standard clinical research network and relies heavily on the expertise of pathologists.MethodsThis study utilized Sirius Red-stained whole slide images of liver tissue obtained from various MASH animal models to develop deep learning (DL) models for scoring liver fibrosis, with a focus on the criteria outlined in Kleiner’s score. …”
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Retracted: Parametric Optimization of Abrasive Water Jet Cutting on AA 5083 through Multiobjective Teaching-Learning Method by Advances in Materials Science and Engineering

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Prediction on Permeability Coefficient of Continuously Graded Coarse-Grained Soils: A Data-Driven Machine Learning Method by Jinhua Wang, Haibin Ding, Lingxiao Guan, Yulin Wang

“…Compared to a traditional empirical model (R² = 0.9031), BPNN improved prediction accuracy by 10.13%, demonstrating the advantage of data-driven methods for evaluating CGS permeability.…”
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Portal Dynamics Learning Method for Renewable-integrated Regional Power Networks Based on Neural Differential-Algebraic Equations by Bin CAO, Ke SU, Shuai YUAN, Tannan XIAO, Ying CHEN

“…Therefore a neural differential-algebraic equations-based portal dynamics learning method is proposed for renewable-integrated regional power networks. …”
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Multi-Attribute Data-Driven Flight Departure Delay Prediction for Airport System Using Deep Learning Method by Yujie Yuan, Yantao Wang, Chun Sing Lai

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Pit Collapse Risk Fusion Early-Warning Method Based on Machine Learning and Improved Cloud Dempster–Shafer by Jiajia Zeng, Bo Wu, Cong Liu

“…A high-accuracy metro pit collapse risk fusion early-warning method is proposed in present study. The main contributions include (1) presenting a new input to the fusion model by optimizing the machine learning model through a multi-step rolling method, and then using the basic probability assignment values obtained from the cloud model as input to the fusion model and (2) developing an improved methodology to address the paradoxical results of the fusion of traditional Dempster–Shafer evidence theory when there is a high level of conflict in multi-source risk prediction data. …”
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Thermal performance analysis of a heat exchanger with a novel turbulator insert by using machine learning method by Jiangbo Wang, Chenzhe Li, Liangcai Zeng, Ting Fu, Kai Liu

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The Use of the Structural Analytic Synthetic Method in Arabic Language Learning: Insights from Islamic Elementary Schools in Indonesia by Ahmad Syadi, suparmanto, Erli Latifah Dayyinati, Nur Sahadah Abdan, Salsabila Khalisah

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