Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…This study developed an advanced bankruptcy prediction model using Support Vector Machines (SVM), Random Forest (RF), and Artificial Neural Network (ANN) algorithms based on datasets from the UCI machine learning repository. …”
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Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models by Yaoyao Ren, Xing Li, Fangyuqing Jin, Chunmei Li, Wei Liu, Erzhu Li, Lianpeng Zhang

“…Extensive experiments conducted on datasets from Nanjing and Wuhan demonstrate the remarkable accuracy of our approach. …”
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Refined Urban Functional Zones Identification via Empirical Bayesian Kriging: A POI-Weighted Scoring Innovation by Xuan Du, Yisha Pan, Xiaoyan Yang, Longgao Chen, Liangchen Liu, Ying Lin

“…The rapid proliferation and open accessibility of multi-source data, such as remote sensing imagery and socio-economic datasets, have introduced new opportunities for the dynamic identification of UFZs. …”
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New Evaluation Method for Fuzzy Cluster Validity Indices by Ismay Perez-Sanchez, Miguel Angel Medina-Perez, Raul Monroy, Octavio Loyola-Gonzalez, Andres Eduardo Gutierrez-Rodriguez

“…The experiments are conducted evaluating the partitions generated by the fuzzy c-means clustering algorithm over 84 UCI datasets with 31 fuzzy CVIs. Experimental results evidenced the need for bigger experimental setups compared to previous studies. …”
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Unraveling the interplay between NDVI, soil moisture, and snowmelt: A comprehensive analysis of the Tibetan Plateau agroecosystem by Di Wei, Lin Yan, Ziqi Zhang, Jia Yu, Xue’er Luo, Yun Zhang, Bo Wang

“…This study integrates MODIS remote sensing images and ERA5-Land meteorological reanalysis datasets to establish a ternary system encompassing NDVI, soil moisture, and snowmelt. …”
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A proposed methodology for the definition of background and reference values for trace elements in fluvial sediments by F. Barrio-Parra, R. Álvarez, H. Serrano-García, M. Izquierdo-Díaz, A. Ordóñez, C.C. García-Fernández, E. De Miguel

“…The methodology proved particularly effective in datasets with a limited sample size and highly skewed data distributions. …”
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Forecasting insect abundance using time series embedding and machine learning by Gabriel R. Palma, Rodrigo F. Mello, Wesley A.C. Godoy, Eduardo Engel, Douglas Lau, Charles Markham, Rafael A. Moral

“…Therefore, we propose a new approach to address this problem by combining statistics, machine learning, and time series embedding. We used two datasets containing a time series of aphids and climate data collected weekly in two municipalities in Southern Brazil for eight years. …”
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Complementary Non‐invasive Fish Monitoring Distinguishes Depth‐Dependent Fish Communities by Ewan Burns, Vijini Mallawaarachchi, Thomas M. Clarke, Belinda Martin, Joseph D. DiBattista, Jamie Hicks, Danny Brock, Elizabeth A. Dinsdale, Charlie Huveneers, Michael P. Doane

“…Only 17 of the 102 species recorded were detected by both methods and combining these two datasets resulted in a 40% increase in species‐level detections compared to either method alone. …”
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Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines by Zhina Wang, Zhina Wang, Yangyuan Chen, Hongming Ma, Hongming Ma, Hong Gao, Hong Gao, Yangbin Zhu, Hongwu Wang, Nan Zhang, Nan Zhang

“…However, existing methods face challenges such as imbalanced datasets and the dominance of high-degree nodes in graph neural networks (GNNs), which compromise the accuracy of node representations. …”
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Integrating social narratives of flood events into a text network analysis-based decision support framework to reduce vulnerability to climate change in Africa by Thomas E. O’Shea, Lena C. Grobusch, Mary Zhang, Jeff Neal, Joseph Daron, Richard G. Jones, Christopher Jack, Alice McClure, Gilbert Siame, Dorothy Ndhlovu, Sukaina Bharwani

“…Local flood inundation maps were created using global rainfall and GIS datasets and then analysed across two interactive “Learning Labs” with local stakeholders. …”
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Multiscale Adaptively Spatial Feature Fusion Network for Spacecraft Component Recognition by Wuxia Zhang, Xiaoxiao Shao, Chao Mei, Xiaoying Pan, Xiaoqiang Lu

“…The proposed method has been validated on the UESD and URSO datasets, and the experimental results demonstrate the superiority of MASFFN over existing spacecraft component recognition methods.…”
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CBGS-YOLO: A Lightweight Network for Detecting Small Targets in Remote Sensing Images Based on a Double Attention Mechanism by Zhenyuan Wu, Di Wu, Ning Li, Wanru Chen, Jie Yuan, Xiangyue Yu, Yongqiang Guo

“…The experimental outcomes demonstrate that CBGS-YOLO outperforms other models when applied to the DB_Licenta and USOD datasets, significantly enhancing detection performance for small targets. …”
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Endoplasmic reticulum stress-related super enhancer promotes epithelial-mesenchymal transformation in hepatocellular carcinoma through CREB5 mediated activation of TNC by Anqi Wang, Sitong Yan, Jiatao Liu, Xiang Chen, Mengyao Hu, Xiao Du, Weijia Jiang, Zhipeng Pan, Lulu Fan, Guoping Sun

“…CRISPR-Cas9 and RT-qPCR identified CAMP responsive element binding protein 5 (CREB5) as a key target of ERS-related SE. Analyses of TCGA datasets and tissue arrays showed that CREB5 mRNA and protein expression levels were higher in liver cancer tissues than in paired normal tissues. …”
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Prognostic prediction for inflammatory breast cancer patients using random survival forest modeling by Yiwei Jia, Chaofan Li, Cong Feng, Shiyu Sun, Yifan Cai, Peizhuo Yao, Xinyu Wei, Zeyao Feng, Yanbin Liu, Wei Lv, Huizi Wu, Fei Wu, Lu Zhang, Shuqun Zhang, Xingcong Ma

“…The C-index of RSF model was 0.7704 and the area under curve (AUC) values for 1, 3, 5 years in training and validation datasets were 0.879–0.955, suggesting the excellent predictive performance of RSF model. …”
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End-to-End Mandarin Speech Reconstruction Based on Ultrasound Tongue Images Using Deep Learning by Fengji Li, Fei Shen, Ding Ma, Jie Zhou, Shaochuan Zhang, Li Wang, Fan Fan, Tao Liu, Xiaohong Chen, Tomoki Toda, Haijun Niu

“…This will be achieved by enlarging training datasets, investigating the impact of ultrasound tongue imaging parameters, and further refining this method.…”
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Multifeature Alignment and Matching Network for SAR and Optical Image Registration by Xin Hu, Yan Wu, Zhikang Li, Zhifei Yang, Ming Li

“…Experiments on three publicly available SAR and optical datasets indicate that our proposed MFAM-RegNet outperforms the existing state-of-the-art algorithms.…”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…Deep learning-based approaches are robust to these artifacts but need extensive training datasets and suffer from generalization to unseen data. …”
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A Secure and Robust Machine Learning Model for Intrusion Detection in Internet of Vehicles by Pradeep Kumar Tiwari, Shiv Prakash, Animesh Tripathi, Tiansheng Yang, Rajkumar Singh Rathore, Manish Aggarwal, Narendra Kumar Shukla

“…The proposed fine tree-based model can be validated by conducting extensive experiments with benchmark real-world datasets which can simulate emerging IoV scenarios. …”
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Decoding Gestures in Electromyography: Spatiotemporal Graph Neural Networks for Generalizable and Interpretable Classification by Hunmin Lee, Ming Jiang, Jinhui Yang, Zhi Yang, Qi Zhao

“…Our methodology exhibits remarkable efficacy, achieving state-of-the-art performance across five publicly available datasets, thus underscoring its prowess in gesture recognition tasks. …”
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Measuring above-ground carbon stock using spatial analysis and the InVEST model: application in the Thoria Watershed, India by Zhe Guo, Himani Sharma, Mahesh Jadav, Upeksha Hettiarachchi, Chiranjit Guha, Wei Zhang, Pratiti Priyadarshini, Ruth S Meinzen-Dick

“…This study introduces a novel methodology for evaluating above-ground carbon storage and sequestration in the Thoria watershed, India, using time-series open-access remotely sensed datasets and the InVEST (Integrated Valuation of Environmental Services and Tradeoffs) carbon model. …”
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