Dynamic UAV data fusion and deep learning for improved maize phenological-stage tracking by Ziheng Feng, Jiliang Zhao, Liunan Suo, Heguang Sun, Huiling Long, Hao Yang, Xiaoyu Song, Haikuan Feng, Bo Xu, Guijun Yang, Chunjiang Zhao

“…Most phenological monitoring methods are post–seasonal and heavily rely on high–frequency time–series data. These methods are not applicable on the unmanned aerial vehicle (UAV) platform due to the high cost of acquiring time–series UAV images and the shortage of UAV–based phenological monitoring methods. …”
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Summary and Analysis of Digital Pain Manikin Data in Adults With Pain Experience: Scoping Review by Darcy Alex Murphy, Syed Mustafa Ali, Shellie Ann Boudreau, William Dixon, David Wong, Sabine N van der Veer

“…We extracted and synthesized data on how studies summarized and analyzed digital manikin pain data at the individual pain–drawing level as well as across multiple pain drawings. …”
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Industrial data-driven machine learning soft sensing for optimal operation of etching tools by Feiyang Ou, Henrik Wang, Chao Zhang, Matthew Tom, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…This paper examines the applicability of soft sensing methods to the operational data of five industrial etching machines. …”
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NHANES 2005–2018 data reveal high albumin-bilirubin scores are associated with depression by Qing-Zhong Li, Jia-Xin Tan, Guo-Tian Ruan, Quan-Zhi Qin, Teng Deng, Yi-Zhen Gong

“…Trial registration Clinical trial number: not applicable.…”
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Plausible Vehicle Trajectory Augmentation With Hybrid Machine Learning by Junyeop Park, Hyeonsoo Jang, Byeongju Kang, Yunhyoung Hwang

“…To address this issue, this paper proposes a novel data augmentation technique, integrating Chebyshev polynomial fitting with Hierarchical Density-Based Spatial Clustering of Applications with Noise clustering and Gaussian mixture models to generate robust training data. …”
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Obesity Alters the Vascular Morphology and VEGF‐A Signaling in Adipose Tissue by Yunjeong Lee, Keith Lionel Tukei, Yingye Fang, Shobhan Kuila, Xinming Liu, Princess I. Imoukhuede

“…Systems biology approaches have advanced our understanding of VEGF‐A signaling in vascular diseases, but their application to obesity is limited by scattered and sometimes contradictory data. …”
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The Usability of Citizen Science Data for Research on Invasive Plant Species in Urban Cores and Fringes: A Hungarian Case Study by Georgina Veronika Visztra, Péter Szilassi

“…Prior to utilising citizen science data, it is essential to identify its inherent flaws and limitations to develop appropriate strategies for its effective application. …”
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Modeling Population Mobility Flows: A Hybrid Approach Integrating a Gravity Model and Machine Learning by Jingjing Liu, Lei Xu, Le Ma, Nengcheng Chen

“…Traditional population migration models reveal the factors influencing migration, while machine learning methods provide effective tools for creating data-driven models to handle the nonlinear relationships between origin and destination characteristics and migration. …”
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Open Access Datasets for Active Magnetic Bearing High-Speed Machinery by Mohammad Rayhan, Ibrahim Abubakar, Gyan Ranjan, Jussi Sopanen, Tuomo Lindh, Niko Nevaranta

“…Following this, we present a detailed description of the open-access datasets related to one HST application example system, including identification results, operational data, and design data. …”
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National Health Insurance Data as a Research Tool in Korean Medicine: a guide to database utilization and methodological approaches by Chan-Young Kwon, Il-Su Park

“…We examined available data types, access protocols, and methodological approaches, with particular emphasis on their application in KM research. …”
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varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction by Lusiné Nazaretyan, Philipp Rentzsch, Martin Kircher

“…Abstract Background Machine learning and artificial intelligence are increasingly being applied to identify phenotypically causal genetic variation. These data-driven methods require comprehensive training sets to deliver reliable results. …”
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QAAPT: an interoperable web-based open-source tool for antimicrobial resistance data analysis and visualisation by Mohammad Julhas Sujan, Sanjay Gautam, Ahmed Taha Aboushady, Adam Clark, Sooyoung Kwon, Hea Sun Joh, Marianne Holm, John Stelling, Florian Marks, Florian Marks, Florian Marks, Florian Marks, Nimesh Poudyal

“…This open-source web-based tool/application generates statistical and visual outputs of AMR data, offers data curation options, and can be integrated with laboratory information management systems. …”
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STOP: Studying Time-Series of Preeclamptic Emergencies by Franklin Parrales-Bravo, Rosangela Caicedo-Quiroz, Elena Tolozano-Benites, Leonel Vasquez-Cevallos, Lorenzo Cevallos-Torres

“…This work can serve as a basis for future studies on the joint application of all DDPP analyses to univariate time series, providing a step-by-step guide on how to analyze such data and introducing a systematic procedure for their analysis for those who may lack statistical expertise.…”
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Data integration across urban digital twin lifecycle: a comprehensive review of current initiatives by Imane Jeddoub, Gilles-Antoine Nys, Rafika Hajji, Roland Billen

“…Hence, this framework provides a generic and urban application-independent overview of the different levels of data integration based on the UDT lifecycle inspired by the Spatial Data Infrastructure lifecycle. …”
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Application Analysis of Credit Scoring of Financial Institutions Based on Machine Learning Model by Yi Wu, Yuwen Pan

“…Firstly, according to the application scenario of credit evaluation of personal credit data, the experimental dataset is cleaned, the discrete data is one-HOT coded, and the data are standardized. …”
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Maximizing the scientific application of Pandora column observations of HCHO and NO₂ by P. Rawat, J. H. Crawford, K. R. Travis, L. M. Judd, M. A. G. Demetillo, L. C. Valin, J. J. Szykman, A. Whitehill, E. Baumann, T. F. Hanisco

“…These results suggest that Pandora data users should carefully assess data across all quality flags and consider their potential for useful application to scientific analysis. …”
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A Systematic Review on Application of Multimodal Learning and Explainable AI in Tuberculosis Detection by Barbara Nansamba, Joyce Nakatumba-Nabende, Andrew Katumba, David Patrick Kateete

“…Traditionally, the application of machine learning and deep learning in detecting TB has focused more on using single modes of data. …”
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Development and implementation of digital solutions in healthcare: insights from the Australian tertiary hospital landscape by Rudolf J. Schnetler, Venkat N. Vangaveti, Venkat N. Vangaveti, Benjamin J. Crowley, Joshua K. Keogh, Trudie Harris, Dale Parker, Jane Watson, Teresa Edwards, Peter Westwood, Hudson Birden, Marina Daly, Kieran Keyes, Erik Biros, Erik Biros, Andrew J. Mallett, Andrew J. Mallett, Andrew J. Mallett, Andrew J. Mallett

“…The Audit, Quality, and Innovation Review panel simplifies the approval process using digital workflows for quality assurance and audit projects, and the Research Data Laboratory provides secure access to de-identified patient data and supports data analysis.DiscussionUnlike some countries, such as the US and UK, where financial incentives or established networks drive research integration, the Townsville Hospital and Health Service focuses on empowering clinicians to address local healthcare issues through research directly. …”
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Employing the principal components in time series models and selecting the best models with Application by Rizgar Maghded Ahmed, Nida Salim Mala Younis

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DESIGN OF STUDENT SUCCESS PREDICTION APPLICATION IN ONLINE LEARNING USING FUZZY-KNN by Selly Anastassia Amellia Kharis, Gatot Fatwanto Hertono, Endang Wahyuningrum, Yumiati Yumiati, Sam Rizky Irawan, T Ahmad Danial, Dimas Septian Saputra

“…Data mining techniques as known as Educational Data Mining (EDM) collect, process, report and used to find the unseen patterns in the student dataset. …”
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