Dataset and machine learning-based computer-aided tools for modeling working sorption isotherms in dried parchment and green coffee beansMendeley Data by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

“…The dataset also provides computer-aided tools for the mathematical modeling of working sorption isotherms and infrared data of coffee. These tools were developed using MATLAB® R2023a (The MathWorks Inc., Natick, MA, USA) and offer users the ability to model sorption isotherms and analyze infrared spectral data using advanced machine learning techniques. …”
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Prediction of microvascular obstruction from angio-based microvascular resistance and available clinical data in percutaneous coronary intervention: an explainable machine learning... by Zhe Zhang, Yang Dai, Peng Xue, Xue Bao, Xinbo Bai, Shiyang Qiao, Yuan Gao, Xuemei Guo, Yanan Xue, Qing Dai, Biao Xu, Lina Kang

“…This study aimed to validate the correlation between AMR and CMR-derived parameters and to construct an interpretable machine learning (ML) model, incorporating AMR and clinical data, to forecast MVO in ST-segment elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention (PPCI). …”
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Exploring Regional Determinants of Tourism Success in the Eurozone: An Unsupervised Machine Learning Approach by Charalampos Agiropoulos, James Ming Chen, George Galanos, Thomas Poufinas

“…This paper contributes to the literature by demonstrating how machine learning can be applied to regional tourism data to better understand and strategize for tourism development. …”
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Digital Footprints of Academic Success: An Empirical Analysis of Moodle Logs and Traditional Factors for Student Performance by Dalia Abdulkareem Shafiq, Mohsen Marjani, Riyaz Ahamed Ariyaluran Habeeb, David Asirvatham

“…With the wide adoption of Learning Management Systems (LMSs) in educational institutions, ample data have become available demonstrating students’ online behavior. …”
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Public Medical Appeals and Government Online Responses: Big Data Analysis Based on Chinese Digital Governance Platforms by Hebin Li, Zhihan Liu, Ziyan Zhang, Lu Ping, Wenxin Gu, Yuan Yao

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Analysis of two pedagogical approaches to foster discipline integrations in an educational data mining class using communities of practice by Brayan Díaz, Collin Lynch, Cesar Delgado, Kevin Han

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Data Analysis and Forecasting of COVID-19 Pandemic in Kuwait Based on Daily Observation and Basic Reproduction Number Dynamics by Kayode Oshinubi, Fahima Al-Awadhi, Mustapha Rachdi, Jacques Demongeot

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Deep Convolutional Neural Networks in Medical Image Analysis: A Review by Ibomoiye Domor Mienye, Theo G. Swart, George Obaido, Matt Jordan, Philip Ilono

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OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data. by Raga Krishnakumar, Anne M Ruffing

“…We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. …”
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A novel spatiotemporal prediction approach to fill air pollution data gaps using mobile sensors, machine learning and citizen science techniques by Arunik Baruah, Dimitrios Bousiotis, Seny Damayanti, Alessandro Bigi, Grazia Ghermandi, O. Ghaffarpasand, Roy M. Harrison, Francis D. Pope

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A Hierarchical Feature-Based Time Series Clustering Approach for Data-Driven Capacity Planning of Cellular Networks by Vineeta Jain, Anna Richter, Vladimir Fokow, Mathias Schweigel, Ulf Wetzker, Andreas Frotzscher

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Prostate cancer and metabolic syndrome: exploring shared signature genes through integrative analysis of bioinformatics and clinical data by Maomao Guo, Sudong Liang, Zhenghui Guan, Jingcheng Mao, Zhibin Xu, Wenchao Zhao, Hao Bian, Jianfeng Zhu, Jiangping Wang, Xin Jin, Yuan Xia

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Crop classification in Google Earth Engine: leveraging Sentinel-1, Sentinel-2, European CAP data, and object-based machine-learning approaches by Marco Vizzari, Giacomo Lesti, Siham Acharki

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Educational data mining: factors influencing medical student success and the exploration of visualization techniques by Ploywarong Rueangket, Chulaluck Thaebanpakul, Boonsub Sakboonyarat, Akara Prayote

“…Association rules analysis further emphasized the importance of environmental factors, particularly transportation time to school and access to learning resources, in supporting academic success.ConclusionEducational data mining (EDM) provided valuable insights into factors contributing to medical student success. …”
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Quantifying nocturnal thrush migration using sensor data fusion between acoustics and vertical‐looking radar by Silvia Giuntini, Juha Saari, Adriano Martinoli, Damiano G. Preatoni, Birgen Haest, Baptiste Schmid, Nadja Weisshaupt

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Automated detection of submarine pipelines in the Yellow River Estuary: a deep learning approach for side-scan sonar data in dynamic deltaic systems by Min Wei, Min Wei, Yongqing Yu, Xing Du, Yupeng Song, Lifeng Dong, Qikun Zhou, Linfeng Wang, Longying Zhang, Yamei Wang

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Revolutionizing clinical decision making through deep learning and topic modeling for pathway optimization by Liu Tianzhao, He Jinzhi, Zhou Rong, Song Jun, Liu Hailong, Liang Yan

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A Deep Learning Method for Inversing 3D Temperature Fields Using Sea Surface Data in Offshore China and the Northwest Pacific Ocean by Xiangyu Wu, Mengqi Zhang, Qingchang Wang, Xidong Wang, Jian Chen, Yinghao Qin

“…In recent years, with the rapid development of remote sensing data, deep learning methods have provided new ideas for the reconstruction of ocean information. …”
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Estimation of Leaf, Spike, Stem and Total Biomass of Winter Wheat Under Water-Deficit Conditions Using UAV Multimodal Data and Machine Learning by Jinhang Liu, Wenying Zhang, Yongfeng Wu, Juncheng Ma, Yulin Zhang, Binhui Liu

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A novel framework for the assessment of public-transport drivers' well-being and satisfaction based on physiological data by Guy Wachtel, Yuval Hadas

“…This paper presents a novel framework for data collection and fusion, for better analysis and assessment of public transportation (PT) drivers' well-being and satisfaction using physiological data. …”
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