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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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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GIS partial discharge diagnosis method under sample imbalance conditions by Tianyu Hu, Hongzhong Ma, Dawei Duan, Yuan Dong

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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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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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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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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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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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A Comprehensive Feature Extraction Network for Deep-Learning-Based Wildfire Detection in Remote Sensing Imagery by Haiyan Pan, Die Luo, Yuewei Zhang

“…To mitigate these challenges, this study proposes a deep-learning-based fire point detection method that integrates Swin Transformer and BiLSTM for the extraction of the multi-dimensional features associated with fire points. …”
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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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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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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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Design of an Efficient Deep Learning-Based Diagnostic Model for Wind Turbine Gearboxes Using SCADA Data by Xuan-Kien Mai, Jun-Yeop Lee, Jae-In Lee, Byeong-Soo Go, Seok-Ju Lee, Minh-Chau Dinh

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How does interactive case-based learning improve students' complex mathematical problem-solving abilities? by Ramdani Miftah, Jarnawi Afghani Dahlan, Lia Kurniawati, Tatang Herman, Lutfiana Lutfiana

“…The study's findings are that students instructed using the ICBL model demonstrated superior CMPS abilities compared to those instructed using traditional methods, and students responded positively to the ICBL instructional model in mathematics learning. …”
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Metabolomic machine learning-based model predicts efficacy of chemoimmunotherapy for advanced lung squamous cell carcinoma by Liang Zheng, Wei Nie, Shuyuan Wang, Ling Yang, Fang Hu, Fang Hu, Meili Ma, Lei Cheng, Jun Lu, Bo Zhang, Jianlin Xu, Ying Li, Yinchen Shen, Wei Zhang, Runbo Zhong, Tianqing Chu, Baohui Han, Xiaoxuan Zheng, Xiaoxuan Zheng, Hua Zhong, Xueyan Zhang

“…Patients were divided into non-response (NR) and response (R) groups according to overall survival (OS), and prognostic models were constructed and validated using different machine learning methods. The patients were further categorized into high-risk and low-risk groups based on the median risk score, to assess the model's predictive performance.ResultsThere were significant differences in metabolites and metabolic pathways between NR and R groups, and 117 differential metabolites were preliminarily screened (p &lt; 0.05, VIP &gt; 1). …”
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Surface-Related Multiple Suppression Based on Field-Parameter-Guided Semi-Supervised Learning for Marine Data by Jiao Qi, Siyuan Cao, Zhiyong Wang, Yankai Xu, Qiqi Zhang

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Machine learning model based on survey assessment of sleep quality in chronic obstructive pulmonary disease patients. by Miraç Öz, Banu Eriş Gülbay, Barış Bulut, Elif Akıncı Aydınlı, Aslıhan Gürün Kaya, Öznur Yıldız, Turan Acıcan, Sevgi Saryal

“…<h4>Purpose</h4>The aim is to develop a learning model based on clinical and survey data to assess sleep quality and identify determining factors affecting sleep quality in chronic obstructive pulmonary disease (COPD) patients.…”
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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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Development of a machine learning-based prediction model for serious bacterial infections in febrile young infants by Jina Lee, Jong Seung Lee, Seak Hee Oh, Jun Sung Park, Reenar Yoo, Soo-young Lim, Dahyun Kim, Min Kyo Chun, Jeeho Han, Jeong-Yong Lee, Seung Jun Choi

“…Background To develop and validate machine learning (ML)-based models to predict serious bacterial infections (SBIs) in febrile infants aged ≤90 days.Methods This retrospective study analysed data from febrile infants (≥38.0℃) aged ≤90 days. …”
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