The role of statistics in advancing nitric oxide research in plant biology: from data analysis to mechanistic insights by Halah Fadhil Hussein AL-Hakeem, Murtaza Khan

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Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data by Nikolaos Bakalos, Nikolaos Papadakis, Antonios Litke

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Revealing the Hidden Social Structure of Pigs with AI-Assisted Automated Monitoring Data and Social Network Analysis by Saif Agha, Eric Psota, Simon P. Turner, Craig R. G. Lewis, Juan Pedro Steibel, Andrea Doeschl-Wilson

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Integrative analysis of miRNA expression data reveals a minimal signature for tumour cells classification by Sabrina Napoletano, David Dannhauser, Paolo Antonio Netti, Filippo Causa

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Multidimensional analysis of climate-induced streamflow variability using CMIP6 data and advanced modeling techniques by Phyo Thandar Hlaing, Usa Wannasingha Humphries, Muhammad Waqas

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A Robust Multivariate Time Series Classification Approach Based on Topological Data Analysis for Channel Fault Tolerance by Seong-Yeon Jeung, Jang-Woo Kwon

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Foundations and Innovations in Data Fusion and Ensemble Learning for Effective Consensus by Ke-Lin Du, Rengong Zhang, Bingchun Jiang, Jie Zeng, Jiabin Lu

“…Ensemble learning and data fusion techniques play a crucial role in modern machine learning, enhancing predictive performance, robustness, and generalization. …”
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Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics. by Lisa M Breckels, Sean B Holden, David Wojnar, Claire M Mulvey, Andy Christoforou, Arnoud Groen, Matthew W B Trotter, Oliver Kohlbacher, Kathryn S Lilley, Laurent Gatto

“…The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis.…”
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Evaluating Game-Based Learning in informal contexts with Data Science by Xavier Rubio-Campillo, Kevin Marín-Rubio, Celia Corral-Vázquez

“…The emergence of digital Game-Based Learning (GBL) has sparked interest in assessing its efficacy. …”
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Detection of OSA Through the Application of Deep Learning on Polysomnography Data by Hasan Ulutas, Recep Sinan Arslan, Muhammet Emin Sahin, Halil Ibrahim Cosar, Cagri Arisoy, Ahmet Sertol Koksal, Mehmet Bakir, Bulent Ciftci

“…By employing meticulous data collection, preprocessing, and analysis, the study demonstrates the potential of DNNs to capture intricate and high-dimensional features within complex sleep data, allowing precise and reliable diagnosis. …”
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A data-to-forecast machine learning system for global weather by Xiuyu Sun, Xiaohui Zhong, Xiaoze Xu, Yuanqing Huang, Hao Li, J. David Neelin, Deliang Chen, Jie Feng, Wei Han, Libo Wu, Yuan Qi

“…Here, we introduce FuXi Weather, a machine learning-based global forecasting system that assimilates multi-satellite data and is capable of cycling DA and forecasting. …”
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Leadership for Student Participation in Data-Use Professional Learning Communities by Hilde Forfang, Cindy Louise Poortman, Mette Marit Jenssen, Kim Schildkamp

“…In this study, we aimed to combine the benefits associated with data-informed decision making with those associated with Professional Learning Communities. …”
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Small earthquake location via machine learning with insufficient data by Ji Zhang, Aitaro Kato, Huiyu Zhu, Jie Zhang

“…Traditional seismic location methods based on travel time and waveform analysis may be ineffective for such events, while traditional single-station location methods require high signal-to-noise ratio (SNR) data. …”
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Using Big Data in Labor Market Analysis: Theoretical Approaches and Methodological Tools by A. V. Vankevich, I. N. Kalinouskaya

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Machine Learning with Administrative Data for Energy Poverty Identification in the UK by Lin Zheng, Eoghan McKenna

“…We develop machine learning models using data from the English Housing Survey that serves as a proxy for administrative data. …”
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Explainable machine learning and feature engineering applied to nanoindentation data by C.O.W. Trost, S. Žák, S. Schaffer, L. Walch, J. Zitz, T. Klünsner, H. Leitner, L. Exl, M.J. Cordill

“…The work aims to challenge the hegemony in the literature of clustering nanoindentation data solely relying on elastic modulus and hardness as features, thereby discarding information provided by the full load–displacement curve. …”
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From Machine Learning-Based to LLM-Enhanced: An Application-Focused Analysis of How Social IoT Benefits from LLMs by Lijie Yang, Runbo Su

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Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning by Mahsa Torkaman, Skander Jemaa, Jill Fredrickson, Alexandre Fernandez Coimbra, Alex De Crespigny, Richard A. D. Carano

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EL-MTSA: Stock Prediction Model Based on Ensemble Learning and Multimodal Time Series Analysis by Jianlei Kong, Xueqi Zhao, Wenjuan He, Xiaobo Yang, Xuebo Jin

“…Predicting stock prices is a popular area of study within the realms of data mining and machine learning. Precise forecasting can assist investors in mitigating the risks associated with their investments. …”
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Spatiotemporal Analysis of the Termokarst Lakes Evolution Using Remote Sensing and Randomized Machine Learning and Forecasting by Dubnov Yuri, Popkov Alexey, Popkov Yuri, Kuprianov Matvey, Polyschuk Vladimir, Melnikov Andrey, Polyschuk Yuri

“…The approach proposed in the work is based on the Randomized Machine Learning method for constructing mathematical models of lake area from climate indicators, learning the model on real data and further forecasting. …”
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