Using New York City’s Geographic Data in an Innovative Application of Generative Adversarial Networks (GANs) to Produce Cooling Comparisons of Urban Design by Yuanyuan Li, Lina Zhao, Hao Zheng, Xiaozhou Yang

“…We utilize multi-source geographic data, including LiDAR derived land cover, OpenStreetMap data, and building footprint data, together with LST data retrieved from Landsat imagery, to develop a prediction model based on generative adversarial networks (GANs). …”
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Areas simultaneously susceptible and (dis-)connected to debris flows in the Dolomites (Italy): regional-scale application of a novel data-driven approach by Felix Pitscheider, Stefan Steger, Marco Cavalli, Francesco Comiti, Vittoria Scorpio

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Study protocol for developing an urban deprivation index in Nepal: Data review, measurement, visualization and real-world application in urban poverty alleviation. by Sampurna Kakchapati, Sitashma Mainali, Noemia Teixeira de Siqueira-Filha, Helen Elsey, Joseph Paul Hicks, Andrew Clark, Farzana Sehrin, Zahidul Quayyum, Bassey Ebenso, Sushil Chandra Baral

“…<h4>Method</h4>The research will commence with a review of the availability of data covering the urban domains listed in the Urban Deprivation Framework within routine data collected in Nepal at the province, district, and municipal levels. …”
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Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study by Xiaolei Lu, Chenye Qiao, Hujun Wang, Yingqi Li, Jingxuan Wang, Congxiao Wang, Yingpeng Wang, Shuyan Qie

“…Conclusions: This study highlights the potential of integrating advanced sensor technology with machine learning techniques in the analysis of complex clinical data. The developed GDI prediction model, based on sensor-acquired isokinetic dynamometry data, offers a novel, streamlined, and effective tool for assessing rehabilitation progress in post-stroke hemiplegic patients, with promising implications for broader clinical application.…”
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Current trends in the application of causal inference methods to pooled longitudinal non-randomised data: a protocol for a methodological systematic review by Lauren Maxwell, Till Bärnighausen, Paul Gustafson, Ellicott C Matthay, Thomas Debray, Valentijn M T de Jong, Edmund Yeboah, Nicole Sibilla Mauer, Heather Hufstedler, Sinclair Carr, Sabahat Rahman, Harlan Campbell, Thomas Jänisch

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Data-Driven Analysis of Ocean Fronts’ Impact on Acoustic Propagation: Process Understanding and Machine Learning Applications, Focusing on the Kuroshio Extension Front by Weishuai Xu, Lei Zhang, Ming Li, Xiaodong Ma, Maolin Li

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Data Assimilation Informed Model Structure Improvement (DAISI) for Robust Prediction Under Climate Change: Application to 201 Catchments in Southeastern Australia by Julien Lerat, Francis Chiew, David Robertson, Vazken Andréassian, Hongxing Zheng

“…The method, which we have called “Data Assimilation Informed model Structure Improvement” (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South‐East Australia. …”
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APPLICATION OF THE SUPPORT VECTOR MACHINE, LIGHT GRADIENT BOOSTING MACHINE, ADAPTIVE BOOSTING, AND HYBRID ADABOOST-SVM MODEL ON CUSTOMERS CHURN DATA by Felice Elena, Robyn Irawan, Benny Yong

“…The models will be implemented using airlines and telecommunication customers churn data. The usage of oversampling technique is required to balance the number of observations in both classes of training data. …”
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Application of Machine Learning Algorithms in Nitrous Oxide (N₂O) Emission Estimation in Data-Sparse Agricultural Landscapes by Uttam Ghimire, Waqar Ashiq, Asim Biswas, Wanhong Yang, Prasad Daggupati

“…The results indicated that MLR was inapplicable as the data did not satisfy its fundamental assumptions. …”
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Inference for Two-Parameter Birnbaum–Saunders Distribution Based on Type-II Censored Data with Application to the Fatigue Life of Aluminum Coupon Cuts by Omar M. Bdair

“…Accurate estimation and prediction are crucial in many fields where censored data frequently appear, such as material science, medical studies and industrial applications. …”
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Application of ConvNeXt with transfer learning and data augmentation for malaria parasite detection in resource-limited settings using microscopic images by Outlwile Pako Mmileng, Albert Whata, Micheal Olusanya, Siyabonga Mhlongo

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Corrections to &#x201C;A Study on the Feasibility of LiFi in an Intra-Vehicular Data Transmission Application&#x201D; by Hongyu Guan, Manolo Dulva Hina

“…Presents corrections to the paper, (Corrections to &#x201C;A Study on the Feasibility of LiFi in an Intra-Vehicular Data Transmission Application&#x201D;).…”
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Application of flexible sensor multimodal data fusion system based on artificial synapse and machine learning in athletic injury prevention and health monitoring by XiaoLan Gai

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Applications of machine learning algorithms in lithological mapping of Saint Katherine Neoproterozoic rocks in the South Sinai of Egypt using hyperspectral PRISMA data by Mohamed W. Ali-Bik, Tehseen Zafar, Safaa M. Hassan, Mohamed F. Sadek, Saif M. Abo Khashaba

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Applicability of ERA5 Reanalysis Data in Simulating Water Level of Medium and Small-Scale Reservoirs:a Case Study of Changjiang Reservoir by CHEN Junlai, ZHANG Zhouwen, CHEN Weihua, HU Xubao

“…The water level in front of the reservoir is important observation data for medium and small-scale reservoir basins.The reanalysis of this data provides optional schemes for the simulation of water levels in medium and small-scale reservoirs,but its applicability still needs to be evaluated.This study took the Changjiang Reservoir Basin in Zhongshan City as an example to assess the accuracy of ERA5,ERA5-Land reanalysis precipitation,and potential evapotranspiration data under different time scales.Based on the three-source Xinanjiang model coupled with reservoir water management,this study set up different input scenarios and analyzed the applicability of ERA5,ERA5-Land precipitation,and potential evapotranspiration data in water level simulation of the reservoir.The results show that at the annual,monthly,and daily scales,the two reanalysis precipitation data in the study area are consistent with the observed precipitation,while the consistency of the reanalysis potential evapotranspiration data with the observed evaporation is weaker.In the seven scenarios of water level simulation,the rate-periodic NSE can all reach 0.6 or more,and there are differences in the input during the validation period.The adaptability of ERA5 reanalysis data is better than that of ERA5-Land,and the reanalysis potential evapotranspiration data can be used as an alternative input for the model evaporation data,but the reanalysis precipitation data is not suitable for direct use in the model input.This study can provide a reference for the application of ERA5 and ERA5-Land data in the simulation and forecasting of reservoir water levels with insufficient data and provide a feasible scheme for the construction of reliable hydrological models in medium and small-scale reservoir basins.…”
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Retracted: Application of the Stratified Nursing Mode of the Prediction Model Constructed Based on Case System Data in the Nursing of Patients with Acute Renal Failure by Emergency Medicine International

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Topologically associating domains of chromatin on single-cell Hi-C data: a survey of bioinformatic tools and applications in the light of artificial intelligence by Hongqiang Lyu, Yao Li, Xinran Chen, Yuan Liu, Erhu Liu, Xiaoliang Cheng

“…Herein, conduct a survey of bioinformatic tools and applications for TAD structures at the single-cell level in the light of artificial intelligence, including imputation of scHi-C data, identification of TAD boundaries and hierarchy, and differential analysis of TAD structures. …”
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The application of population data linkage to capture sibling health outcomes among children and young adults with neurodevelopmental conditions.... by Caitlin Gray, Helen Leonard, Matthew N. Cooper, Dheeraj Rai, Emma J. Glasson

“…Objective To explore the application of population data linkage as a research method to capture health outcomes of siblings of children with neurodevelopmental conditions. …”
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A framework for performance analysis of OpenStreetMap data in navigation applications: the case of a well-developed road network in Australia by Reza Hosseini, Daoqin Tong, Samsung Lim, Gunho Sohn, Győző Gidófalvi

“…Although much effort has been put into assessing and improving OpenStreetMap (OSM) data quality, further research is required to determine its reliability and robustness for real-world applications. …”
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Data Analysis in Newly Developed Milk Sensor Platforms: Good Practices, Common Pitfalls, and Hard-Earned Lessons from Field Application by Francesco Martelli, Claudia Giacomozzi, Roberto Dragone, Chiara Frazzoli, Gerardo Grasso

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