Litho-structural study and depth estimation of Shaki area of Southwestern, Nigeria using high resolution aeromagnetic data by Omonike Adedokun, Olagoke Oladejo, K. O Suleiman, Kehinde Alao, E. O. Adeniyi, H. Otobrise, Oluwaseun Adedokun, Lukman Sunmonu

“…High resolution aeromagnetic data (HRAD) of Shaki (sheet 199) was obtained from the Nigeria Geological Survey Agency; it was processed, enhanced, and interpreted using Geosoft Oasis Montaj 6.4.2 data processing and analysis software package. …”
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Study on Correction Methods for GPM Rainfall Rate and Radar Reflectivity Using Ground-Based Raindrop Spectrometer Data by Lin Chen, Huige Di, Dongdong Chen, Ning Chen, Qinze Chen, Dengxin Hua

“…The Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) mission provides valuable three-dimensional precipitation structure data on a global scale and has been widely used in hydrometeorological research. …”
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Estimating Nurse Workload Using a Predictive Model From Routine Hospital Data: Algorithm Development and Validation by Paul Meredith, Christina Saville, Chiara Dall’Ora, Tom Weeks, Sue Wierzbicki, Peter Griffiths

“…ObjectiveThe objective of this study is to explore whether an algorithm could estimate ward workload using existing routinely recorded data. …”
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Optimization of dual-layer flow field in a water electrolyzer using a data-driven surrogate model by Lizhen Wu, Zhefei Pan, Shu Yuan, Xiaoyu Huo, Qiang Zheng, Xiaohui Yan, Liang An

“…Therefore, machine learning methods are adopted to accelerate the optimization. A data-driven surrogate model based on deep neural network (DNN) is developed and successfully trained using data obtained by the physical VOF method. …”
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A century of Sudd wetland’s water storage dynamics using reconstructed and downscaled GRACE/GRACE-FO Data by Dinuka Kudagama, Joseph Awange, Jielong Wang, Ayalsew Zerihun, Leidy Luna

“…Although the Gravity Recovery And Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions have provided valuable Total Water Storage Anomaly (TWSA) observations for understanding the stored water changes in the Ramser Sudd wetland, their coarse resolution (∼300 km) and relatively short records (<30 years) limit their applicability to study long-term water storage variations over this wetland, one of the largest (tropical) wetlands in the world that has so far received little attention. Random Forest (RF) modeling is used to downscale the Sudd wetland’s TWSA from 0.5°to 0.1°for the period 2003–2023 for the evaluation of the short-term TWSA dynamics, whereas the centenary precipitation-driven TWSA product is employed to elucidate the long-term climate impacts on the Sudd wetland’s TWSA. …”
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Multi-time scale analysis of human activity patterns on the Qinghai–Tibet Plateau using location request data by Minglu Che, Yanyun Nian, Chengyao Wang, Wenhui Zhang, Jie Chen, Bingzhi Liao, Tao Pei

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Assessment of plant diversity index in degraded desert grassland using UAV hyperspectral multimodal data and Encoder-CNN by Zhaohui Tang, Chuanzhong Xuan, Tao Zhang, Xinyu Gao, Suhui Liu, Mengqin Zhang

“…The use of multimodal data combining spatial spectral features with index features, combined with the Encode-CNN model, can provide the most accurate information on community composition. …”
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Enhancing PM2.5 prediction by mitigating annual data drift using wrapped loss and neural networks. by Md Khalid Hossen, Yan-Tsung Peng, Meng Chang Chen

“…In many deep learning tasks, it is assumed that the data used in the training process is sampled from the same distribution. …”
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<italic>PhotonBathymetry</italic>: An Interactive Software for Nearshore Bathymetry Using ICESat-2 Data and Multispectral Images by Shuai Xing, Songtao Guo, Guoping Zhang, Xinlei Zhang, Pengcheng Li, Dandi Wang, Li Chen, Ming Gao, Qing Xu

“…These levels are designed to ensure the efficiency of data loading, browsing, and processing. To cater to the diverse needs of developers, PBathy is built using C++ and provides standardized interfaces for different programming languages. …”
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Analysis of TCGA (The Cancer Genome Atlas) Data for Prognosis, Risk Categorization, and Survival of AML Patients Using Bioinformatics by Bhavika Rishi, Shamsuz Zaman, Fouzia Siraj, Sree Vishmaya, Himanshu Dhanda, Manpreet Kaur, Sandeep Swain, Baseer Noor, Sumita Chaudhry, Ankur Jain, Prashant Prabhakar, Amitabh Singh, Aroonima Misra

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Quantifying impact of correlated predictors on low-cost sensor PM2.5 data using KZ filter by Vijay Kumar, Vijay Kumar, Shantanu Sur, Dinushani Senarathna, Dinushani Senarathna, Supraja Gurajala, Suresh Dhaniyala, Sumona Mondal

“…Recently, the emergence of low-cost air quality sensor networks has enabled the availability of air quality data with higher spatiotemporal resolution, which is more representative of personal exposure. …”
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Development of a midwifery regulatory environment index using data from the Global Midwives’ Associations map survey by Emma Virginia Clark, Marianna LaNoue, Kate Clouse, Alexandra Zuber, Jeremy Neal

“…We aimed to use these data to develop a composite index that represents the midwifery regulatory environment in the countries that participated in the survey. …”
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Mapping landforms of a hilly landscape using machine learning and high-resolution LiDAR topographic data by Netra R. Regmi, Nina D.S. Webb, Jacob I. Walter, Joonghyeok Heo, Nicholas W. Hayman

“…The landform map developed using this approach has several potential applications. …”
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The Impact of Pose Alignment Errors on a Classical Late Infrastructure-Vehicle Collaboration Framework Using Experimental Data by Roshan George, Dara Molloy, Tim Brophy, William O'Grady, Darragh Mullins, Edward Jones, Brian Deegan, Martin Glavin

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Multi-model ensemble mapping of irrigated areas using remote sensing, machine learning, and ground truth data by Muhammad Umar Akbar, Ali Mirchi, Arfan Arshad, Sara Alian, Mukesh Mehata, Saleh Taghvaeian, Kasra Khodkar, Jacob Kettner, Sumon Datta, Kevin Wagner

“…ML classifiers were trained using different input variables including vegetation indices acquired from high-resolution (30 m) Landsat imagery, soil, topography, and climate data. …”
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Cervical Cancer Prediction Based on Imbalanced Data Using Machine Learning Algorithms with a Variety of Sampling Methods by Mădălina Maria Muraru, Zsuzsa Simó, László Barna Iantovics

“…For instance, an experienced medical doctor may diagnose a case but need expert support that related to another medical specialty. Data imbalance is frequent in healthcare data and has a negative influence on predictions made using ML algorithms. …”
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Multi-dimensional dynamic deformation monitoring of long-span railway bridges using GBIR and IVM data fusion by Yuhao Liu, Songbo Wu, Bochen Zhang, Zhen Peng, Jiayuan Zhang, Chisheng Wang, Wei Tu, Zhipeng Chen, Mi Jiang, Xiao Cheng, Jiasong Zhu, Qingquan Li

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Deductively coding psychosocial autopsy interview data using a few-shot learning large language model by Elias Balt, Elias Balt, Salim Salmi, Sandjai Bhulai, Stefan Vrinzen, Merijn Eikelenboom, Merijn Eikelenboom, Renske Gilissen, Renske Gilissen, Daan Creemers, Daan Creemers, Arne Popma, Saskia Mérelle, Saskia Mérelle

“…It typically relies heavily on qualitative data from interviews or medical documentation. However, qualitative research has often been scrutinized for being prone to bias and is notoriously time- and cost-intensive. …”
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High-throughput mesoscopic optical imaging data processing and parsing using differential-guided filtered neural networks by Hong Zhang, Zhikang Lu, Peicong Gong, Shilong Zhang, Xiaoquan Yang, Xiangning Li, Zhao Feng, Anan Li, Chi Xiao

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Perturbation based privacy preservation and classification using Jaya Algorithm and Dragonfly Inspired Algorithm by Dipanwita Sen, Bhupati Bhusan Mishra, Prasant Kumar Pattnaik

“…In this work, the Wisconsin Prognostic Breast Cancer (WBC) dataset has been used. At first, a privacy preserving schema making use of perturbation implementing Jaya Algorithm has been elucidated. …”
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