Enhancing root-zone soil moisture estimation using Richards' equation and dynamic surface soil moisture data by Xizhuoma Zha, Wenbin Zhu, Yan Han, Aifeng Lv

“…However, due to its high sensitivity to input parameters, its application in large-scale spatial domains remains a significant challenge, particularly in regions with sparse meteorological data. …”
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Resolution enhanced sea ice concentration: a new algorithm applied to AMSR2 microwave radiometry data by Jozef Rusin, Thomas Lavergne, Anthony P. Doulgeris, K. Andrea Scott

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Ridge Regressive Data Preprocessed Quantum Deep Belief Neural Network for Effective Trajectory Planning in Autonomous Vehicles by S. Nirmala Devi, Rajesh Natarajan, Gururaj H. L., Francesco Flammini, Badria Sulaiman Alfurhood, Sujatha Krishna

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Learner stimulus intent: a framework for eye tracking data collection and feature extraction in computer programming education by K. R. Chandrika, J. Amudha

“…These datasets are outcomes of the framework’s application, embodying its potential to revolutionize the way we understand and assess learning in computer science education. …”
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Designing a Model for Implementing Digital Banking Policy Based on Using Big Data in Iranian Banking Industry by Rahmatollah Gholipour Souteh, Hamed Esmaeili Rad

“…Conclusion The findings underscore a significant gap in the attention and application of big data technology within banks. Despite the availability of rich information and data resources in state banks, this valuable capital remains underutilized. …”
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Convolutional neural networks for sea surface data assimilation in operational ocean models: test case in the Gulf of Mexico by O. Zavala-Romero, O. Zavala-Romero, A. Bozec, E. P. Chassignet, J. R. Miranda, J. R. Miranda

“…This work explores the application of convolutional neural networks (CNNs) in data assimilation within the context of the HYbrid Coordinate Ocean Model (HYCOM) in the Gulf of Mexico. …”
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A Data-Driven Decision-Making Support Method for Priority Determination for an Intelligent Road Problem Reporting System by Woohoon Jeon, Jinguk Kim, Joyoung Lee

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A Case Study of Sensor Data Collection and Analysis in Smart City: Provenance in Smart Food Supply Chain by Qiannan Zhang, Tian Huang, Yongxin Zhu, Meikang Qiu

“…In this paper, a smart sensor data collection strategy for IoT is proposed, which would improve the efficiency and accuracy of provenance with the minimized size of data set at the same time. …”
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Study on spatial distribution characteristics of marine habitat in the Beibu Gulf based on GIS and existing environmental and vegetation data by Haiyan Huang, Wenhai Lu, Chang Liu, Yijun Tao, Linchong Kang, Guocheng Zuo, Lu Yang, Yan Xu, Yujia Zhang, Zhaoyang Liu, Yong Ma

“…The study highlights the significant application potential of habitat mapping in coastal and marine management.…”
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Large Language Model and Digital Twins Empowered Asynchronous Federated Learning for Secure Data Sharing in Intelligent Labeling by Xuanzhu Sheng, Chao Yu, Xiaolong Cui, Yang Zhou

“…Big models are inseparable from high-quality, specialized scene data, from training to deploying application iterations to landing generation. …”
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Monitoring and Forecasting Air Pollution Levels by Exploiting Satellite, Ground-Based, and Synoptic Data, Elaborated with Regression Models by Silas Michaelides, Dimitris Paronis, Adrianos Retalis, Filippos Tymvios

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Data-Driven-Based Attribution of Runoff Changes in Tuwei River Basin in the Northern Windy-Sandy Region of Shaanxi by YU Huanghao, LI Binquan

“…The key point in analyzing the attribution of runoff changes is whether the natural runoff process of the basin can be accurately simulated.However,the application accuracy of hydrological models in arid and semi-arid regions of the Loess Plateau is generally not high.Taking the Tuwei River basin in the northern windy-sandy region of Shaanxi in the middle reach of the Yellow River as an example,this paper proposed an improved natural runoff simulation method based on the data-driven approach,so as to quantitatively analyze the effects of climate changes and human activities on runoff changes in the Tuwei River basin.The results show that the annual runoff series in the basin decreased significantly from 1961 to 2015,and there were two abrupt changes in 1979 and 1996,respectively.The annual runoff of the two periods (1980—1996 and 1997—2015) is 25.8% and 47.1% lower than that of the natural period (1961—1979),respectively.The runoff simulation accuracy of the three data-driven methods after improvement rises significantly.Specifically,the improved method proposed by Zhao Wenlin has the highest accuracy,and the Nash-Sutcliffe efficiency coefficient of annual runoff simulation in the natural period is 0.77.Climate change is the main reason for the significant decrease in the runoff between 1980 and 1996 (with a contribution of up to 80.9%).However,from 1997 to 2015,the contribution of climate change and human activities to the decrease in the runoff changed,with the influence of human activities increasing to a proportion of 58.8%.…”
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A research on wireless sensor networks’ node positioning mechanism based on Narrowband Internet of Things data linking by Xiaojun Wu, Qiying Cao, Yuanjie Li

“…It pushes wireless sensor networks to be applied in more application fields. NB-IoT Release 14 has got the ability of positioning from cellular network service. …”
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Conduction Abnormalities after Transcatheter Aortic Valve Implantation: Incidence, Impact and Management Using CT Data Interpretation by Rutger-Jan Nuis, Mark van den Dorpel, Rik Adrichem, Joost Daemen, Nicolas Van Mieghem

“…Moreover, leveraging MSCT data for computational 3D simulations to predict device-anatomy interactions may help guide procedural strategy to mitigate conduction abnormalities. …”
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A new data science trajectory for analysing multiple studies: a case study in physical activity research by Simone Catharina Maria Wilhelmina Tummers, Arjen Hommersom, Catherine Bolman, Lilian Lechner, Roger Bemelmans

“…Because of the complexity of this kind of research, it is valuable to provide more specific guidelines for such analyses than given in standard data science methodologies. Thereto, we propose a generic procedure for applied data science research in which the data from multiple studies are included. …”
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scaDA: A novel statistical method for differential analysis of single-cell chromatin accessibility sequencing data. by Fengdi Zhao, Xin Ma, Bing Yao, Qing Lu, Li Chen

“…One important application of scATAC-seq data analysis is differential chromatin accessibility (DA) analysis. …”
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A systematic review of machine learning-based remote sensing data analysis for geological and mined materials characterisation by Sureka Thiruchittampalam, Bikram Pratap Banerjee, Nancy F Glenn, Simit Raval

“…To explore current practices and the application of machine learning in interpreting complex imaging data for mine material characterisation, a review of 92 studies from 2004 to 2024 was conducted. …”
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Optimizing Metro Passenger Flow Prediction: Integrating Machine Learning and Time-Series Analysis with Multimodal Data Fusion by Li Wan, Wenzhi Cheng, Jie Yang

“…Subsequently, the decomposed data from STL and EEMD are partitioned into training and test sets and normalized. …”
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How big data development influences enterprise green technology innovation? The moderating role of digital inclusive finance by Kaiming Cheng, Shucheng Liu

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Exploring technological evolution of AIED field using topic modelling and link prediction analysis based on patent data by Hüseyin Özçınar, Aylin Sabancı Bayramoğlu

“…This study aims to analyze the artificial intelligence in education (AIED) field using patent data to identify the key actors, main themes, and their evolution over time. …”
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