The impacts of training data spatial resolution on deep learning in remote sensing by Christopher Ardohain, Songlin Fei

“…We expect that the findings from this study will assist future research in optimizing the development of DL training datasets, selection of source imagery at the proper resolution given training data availability, and application of appropriate model tuning depending on landscape complexity.…”
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Estimation of the average time to failure of the turning steps according to the operation data by M. V. Belousova, V. V. Bulatov

“…For confirmation, a statistical criterion for checking the deviation of the distribution from the normal one was applied.On the basis of carried statistic analysis a histogram of frequencies and a line of the density function of samples of failure time in the data fixation period from 2010 to 2017 were built. …”
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Data-driven prediction of cardiovascular and cerebrovascular diseases in a nationwide study by Sehyun Kim, Beomsang Ryu, Mingee Choi, Sangyon Lee, Jaeyong Shin, Sok Chul Hong

“…Abstract As the importance of the prevention and premanagement of cardiovascular and cerebrovascular diseases continues to emerge, research is being conducted globally to create and compare risk factor prediction models using health examination big data. In this study, health insurance data were used to predict the incidence of cardiocerebrovascular disease using various models and compare the performance of the models on samples with different initial risk levels. …”
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A systematic review of data privacy in Mobility as a Service (MaaS) by Zineb Garroussi, Antoine Legrain, Sébastien Gambs, Vincent Gautrais, Brunilde Sansò

“…Future research should focus on developing scalable privacy frameworks that protect user data without compromising operational efficiency.…”
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Students’ experiences of placements in urban Indigenous health contexts: developing a culturally responsive workforce by Kate Odgers-Jewell, Alison Nelson, Renee Brown, Nicole Hunter, Tiffany Atkins, Kelly Menzel

“…The sign test for matched pairs was used to calculate differences between pre and post surveys, and a one-sided hypothesis test was utilised to determine if the level of agreement increased from pre to post survey. Qualitative data obtained for seven questions were thematically analysed using Groundwater Method, an Indigenous data analysis technique. …”
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Developing a Fatigue Detection Model for Hospital Nurses Using HRV Measures and Machine Learning by Wynona Salsabila Hafiz, Maya Arlini Puspasari, Dewi Yunia Fitriani, Richard Joseph Hanowski, Danu Hadi Syaifullah, Salsabila Annisa Arista

“…Sixty nurses from a hospital in Depok, Indonesia, participated with HRV data collected via Polar H10 monitors before and after shifts alongside SOFI questionnaires. …”
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Optimizing The Financial Domain With Robotic Process Automation: Invoice Data Extraction by Andre Suryaningprang, Yoyo Sudaryo, Riyandi Nur Sumawidjaja, Andhika Mochamad Siddiq, Dedi Supiyadi

“…There are several steps taken to build RPA, namely (1) Problem Analysis and Motivation, (2) Determining Solution Goals, (3) Designing and Developing Solutions (4) performance evaluation. …”
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Harnessing Novel Data‐Driven Techniques for Precise Rainfall–Runoff Modeling by Saad Sh. Sammen, Reza Mohammadpour, Karam AlSafadi, Ali Mokhtar, Shamsuddin Shahid

“…In this study, data‐driven techniques, such as the group method of data handling (GMDH), extreme learning machine (ELM), and two hybrids of artificial neural network (ANN) with Cuckoo search algorithm (ANN + Cuckoo) and genetic algorithm (ANN + GA) were used to model the rainfall–runoff relationship. …”
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Implementing and evaluating a project to enable and encourage Caribbean data-sharing by Selvi M. Jeyaseelan, Natasha P. Sobers, Kayla Grant, Gian Marco Vasquez, Shamar Blenman, Ian R. Hambleton

“…The CaribData project, funded by the Inter-American Development Bank and implemented by The University of the West Indies, aims to enhance data-handling, -sharing and reuse capabilities in the Caribbean. …”
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A Machine Learning-Based Method for Developing the Chinese Symptom Checklist-11 (CSCL-11) by Xuanyi Cai, Yunan Zhang, Meng Su, Fan Chang, Lei Quan, Yixing Liu, Bei Wang

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Experimental and theoretical study of used GFRP I-profile composite columns by Ata El-Kariem Shoeib, Mohammed Salem, Alaa Sheriff, Mohammed Abdel-Rahman M. Khalil

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Assessment of psychosocial factors in juvenile offenders: Developing a context-specific instrument for Latin America by Yamileth Ortiz-Gómez, Laura Daniela Cabrera Muñoz, Clara Inés Torres Sinisterra, Ivette Mejía López, Isabel Cristina Parra Uribe, Daniel Escobar Zamora, Andrés Felipe Muñoz Gómez

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Developing "Multifactor Asset Pricing Models" Using Threshold Regression Approach and Credit Risk Factor by Hadi Gharehbaghii, Mahmoud Botshekan

“…Objective This study aims to develop threshold asset pricing models to enhance the performance of common multi-factor models. …”
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An Integrated Algorithm with Feature Selection, Data Augmentation, and XGBoost for Ovarian Cancer by Jingxun Cai, Zne-Jung Lee, Zhihxian Lin, Chih-Hung Hsu, Yun Lin

“…In recent years, ovarian cancer prediction research has advanced, allowing for the analysis of the likelihood and type of cancer based on patients’ genetic data. …”
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Optimising ensemble streamflow predictions with bias correction and data assimilation techniques by M. Tanguy, M. Tanguy, M. Eastman, M. Eastman, A. Chevuturi, E. Magee, E. Cooper, R. H. B. Johnson, K. Facer-Childs, J. Hannaford, J. Hannaford

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DRomics, a workflow to exploit dose-response omics data in ecotoxicology by Delignette-Muller, Marie Laure, Siberchicot, Aurélie, Larras, Floriane, Billoir, Elise

“…DRomics has been augmented especially to be able to handle varied omics data considering the nature of the measured signal (e.g. counts of reads in RNAseq) and the way data were collected (e.g. batch effect, situation with no experimental replicates). …”
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A Model for Predicting the Risk of Developing Drug-Induced Liver Injury During Therapy with Favipiravir by Yu. V. Shevchuk, I. V. Sychev, A. V. Kryukov, I. I. Temirbulatov, K. B. Mirzaev, N. P. Denisenko, Sh. P. Abdullaev, S. N. Tuchkova, V. I. Vechorko, O. V. Averkov, D. A. Sychev

“…Based on the data obtained, the association of clinical, laboratory, pharmacological, and pharmacogenetic parameters with the development of drug-induced liver injury during favipiravir therapy was studied. …”
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Digital Behavior and Impact on Employee Performance: Evidence from Indonesia by Annisa Nuraini, Harmon Chaniago, Yen Efawati

“…The questionnaire was tested for validity and reliability. Data analysis uses descriptive analysis, factor analysis, and multiple regression. …”
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Developing a Southern Ocean Marine Ecosystem Model Ensemble to Assess Climate Risks and Uncertainties by Kieran Murphy, Denisse Fierro‐Arcos, Tyler Rohr, David Green, Camilla Novaglio, Katherine Baker, Kelly Ortega‐Cisneros, Tyler D. Eddy, Cheryl S. Harrison, Simeon L. Hill, Patrick Eskuche‐Keith, Camila Cataldo‐Mendez, Colleen M. Petrik, Matthew Pinkerton, Paul Spence, Ilaria Stollberg, Roshni C. Subramaniam, Rowan Trebilco, Vivitskaia Tulloch, Juliano Palacios‐Abrantes, Sophie Bestley, Daniele Bianchi, Philip Boyd, Pearse J. Buchanan, Andrea Bryndum‐Buchholz, Marta Coll, Stuart Corney, Samik Datta, Jason D. Everett, Romain Forestier, Elizabeth A. Fulton, Vianney Guibourd de Luzinais, Ryan Heneghan, Julia G. Mason, Olivier Maury, Clive R. McMahon, Eugene Murphy, Anthony J. Richardson, Derek P. Tittensor, Scott Spillias, Jeroen Steenbeek, Devi Veytia, Julia Blanchard

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Machine Learning in the National Economy by Azamjon A. Usmonov

“…Key areas of using this technology in the economy are analyzed, such as market trend forecasting, financial risk management, and economic data analysis. Special attention is given to the advantages of machine learning, including improved decision-making efficiency, process automation, and handling large volumes of data. …”
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