Detection of UAV GPS Spoofing Attacks Using a Stacked Ensemble Method by Ting Ma, Xiaofeng Zhang, Zhexin Miao

“…To address this issue, we propose a detection method based on stacked ensemble learning that combines convolutional neural network (CNN) and extreme gradient boosting (XGBoost) to detect spoofing signals in the GPS data received by UAVs. …”
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Predicting the achievement emotions of elementary and middle school students in online learning based on control-value theory by Yan Yi, Lixiang Gao, Shuang Wang, Mingzhang Zuo, Heng Luo

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The influence of machine learning-based knowledge management model on enterprise organizational capability innovation and industrial development. by Zhigang Zhou, Yanyan Liu, Hao Yu, Lihua Ren

“…The aims are to explore the construction of the knowledge management model for engineering cost consulting enterprises, and to expand the application of data mining techniques and machine learning methods in constructing knowledge management model. …”
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Acute Upper Gastrointestinal Bleeding: A Hands-On Simulation Case for Internal Medicine Residents Improves Knowledge and Confidence by Marni H. Wilkoff, Emily S. Seltzer, Nicholas R. Piniella, Harrindra Seepersaud, Priscilla Loanzon, Susannah Kurtz, James Salonia, Daniela Jodorkovsky

“…Introduction Upper gastrointestinal (GI) bleeding leads to approximately 350,000 hospital admissions annually. Simulation-based training enhances medical education by improving quality care, patient safety, and clinical competency. …”
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Evaluating visitor perception and spatial preferences of various museums based on machine learning from 2016 to 2024. by Yuandi Jiang, Kalyna Pashkevych, Shibo Bi

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Connected and automated vehicle control at unsignalized intersection based on deep reinforcement learning in vehicle-to-infrastructure environment by Juan Chen, Vijayan Sugumaran, Peiyan Qu

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Contrastive Learning-Based Hyperspectral Image Target Detection Using a Gated Dual-Path Network by Jiake Wu, Rong Liu, Nan Wang

“…Deep learning-based hyperspectral target detection (HTD) methods often face the challenge of insufficient prior information and difficulty in distinguishing local and global spectral differences. …”
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On Classification of the Human Emotions from Facial Thermal Images: A Case Study Based on Machine Learning by Marius Sorin Pavel, Simona Moldovanu, Dorel Aiordachioaie

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Design and implementation of classical literature sentiment analysis system based on ensemble learning and graph neural network by Qianru Gao, Jiachen Huang

“…This study is committed to the design and implementation of a classical literature sentiment analysis system based on ensemble learning and graph neural network, with the goal of breaking through the limitations of traditional methods and realizing the refined analysis of classical literature sentiment tendencies. …”
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A deep learning-based image analysis model for automated scoring of horizontal ocular movement disorders by Xiao-lu Jin, Yu-fei Liu, Bing-bing He, Yi-fei Fan, Ling-yun Zhou

“…IntroductionThis study proposes a deep learning–based image analysis method for automated scoring of the severity of horizontal ocular movement disorders and evaluates its performance against traditional manual scoring methods.MethodsA total of 2,565 ocular images were prospectively collected from 164 patients with ocular movement disorders and 121 healthy subjects. …”
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Interdisciplinary problem-based learning model for standardized dental residency training: from theory to practice in dental trauma management by Yang Shuting, Wang Haohao, Wang Shida, Zheng Liwei, Wan Mian

“…To address these issues, West China Hospital of Stomatology, Sichuan University introduced an interdisciplinary problem-based learning (IPBL) model to improve residents’ professional quality and practical abilities.MethodsBased on the specific needs of dental residents, the hospital established a PBL framework supported by an interdisciplinary collaborative teaching team with a focus on dental trauma diagnosis and treatment. …”
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Systematic review of risks hidden in VR-based learning environments: Research frameworks and evidence from the literature by Yu-Ju Lan, Kai-Yu Tang

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Deep Learning for Anomaly Detection in CNC Machine Vibration Data: A RoughLSTM-Based Approach by Rasım Çekik, Abdullah Turan

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Extended Application of Double Machine Learning in Corporate Financial Resilience Research: Based on Data Factor Marketization by Fangzhou Song, Yang Huang, Chengkun Liu

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Integrating phenomenon-based learning and GIS to improve geo-literacy and student engagement: an action research approach by Sutthiphong Meechandee, Nattapon Meekaew

“…Abstract Purpose This study investigated the integration of Phenomenon-Based Learning (PhenoBL) and Geographic Information Systems (GIS) to enhance geo-literacy and student engagement among Grade 8 students in Thailand, addressing the gap in research on their combined impact in secondary geography teaching within the Thai educational context. …”
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Identification of potential biomarkers and mechanisms for keloid disorder based on comprehensive bioinformatics analysis and machine learning algorithms by Bowen Zheng, Jianxiong Qiao, Xiaoping Yu, Hanghang Zhou, Anqi Wang, Xuanfen Zhang

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Deep Reinforcement Learning for CT-Based Non-Invasive Prediction of SOX9 Expression in Hepatocellular Carcinoma by Minghui Liu, Yi Wei, Tianshu Xie, Meiyi Yang, Xuan Cheng, Lifeng Xu, Qian Li, Feng Che, Qing Xu, Bin Song, Ming Liu

“…<b>Results:</b> Our DRL-based model achieved an area under the curve (AUC) of 91.00% (95% confidence interval: 88.64–93.15%), outperforming conventional DL methods by over 10%. …”
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Exploring the Relationship between Lifelong Learning Components and Evidence- Based Medicine Acceptance among Physiopathology Students at Mazandaran University of Medical Sciences,... by Parinaz Talebi, Nassim Ghahrani, Forouzan Sadeghimahalli, Siavash Moradi

“…Among the components of lifelong learning, only the information search skill subscale showed a significant positive correlation with the evidence-based medicine acceptance score. …”
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Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning by Qiqiang Liang, Xin Xu, Shuo Ding, Jin Wu, Man Huang

“…Background Predicting the successful weaning of acute kidney injury (AKI) patients from renal replacement therapy (RRT) has emerged as a research focus, and we successfully built predictive models for RRT withdrawal in patients with severe AKI by machine learning.Methods This retrospective single-center study utilized data from our general intensive care unit (ICU) Database, focusing on patients diagnosed with severe AKI who underwent RRT. …”
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Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning by Jie Huang, Yanli Zhao, Zhanxiao Tian, Wei Qu, Xia Du, Jie Zhang, Meng Zhang, Yunlong Tan, Zhiren Wang, Shuping Tan

“…In this study, a discriminative model of schizophrenic speech based on deep learning is developed, which combines different emotional stimuli and features. …”
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