Evaluasi Curah Hujan Berbasis Data Global pada DAS Wae Mese, Labuan Bajo by Maria Kalista Hadia Sabu, Doddi Yudianto, Obaja Triputera Wijaya

“…Accuracy of rainfall data is very important in hydrological analysis, especially in areas with limited data such as Labuan Bajo City, Indonesia. …”
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Predictive modeling of rapid glaucoma progression based on systemic data from electronic medical records by Richul Oh, Hyunjoong Kim, Tae-Woo Kim, Eun Ji Lee

“…The rate of change in global RNFL thickness for each eye was determined by linear regression analysis over time. Systemic data obtained within 6 months from the time of glaucoma diagnosis were extracted from the EMRs and incorporated into a model to predict the rate of progressive RNFL thinning. …”
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Data processing capability of polarization dynamics in ferroelectric-gate transistor-based physical reservoir computing by Yu Ukezeki, Sota Inoue, Norifumi Fujimura, Tokuji Yokomatsu, Kensuke Kanda, Kazusuke Maenaka, Kasidit Toprasertpong, Shinichi Takagi, Takeshi Yoshimura

“…The voltage applied to the ferroelectric layers was theoretically calculated using load line analysis and determined experimentally. In a time-series prediction task, the FeFETs showed low error rates under conditions that produced multiple hysteresis loops in dynamic transfer waveforms. …”
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Short-Term Building Electrical Load Prediction by Peak Data Clustering and Transfer Learning Strategy by Kangji Li, Shiyi Zhou, Mengtao Zhao, Borui Wei

“…Results show that the data clustering and transfer learning method reduces the error by 49.22% (MAE) compared to the Elman model. …”
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Predicting laboratory solution kit accuracy using artificial intelligence: a data-driven approach by Abdulwahab AL-Deib, Eshraq Alsherif, Husameddin Abuzgaia, Amel Rabti, Ruwaida Rtemi, Salem Elfard, Sheren Njaim

“…Abstract This study developed and validated an artificial intelligence (AI)-based computational tool for standardizing glucose and urea measurements across different clinical laboratory systems (Biolabo and BioScien) using Biomagreb as the reference standard. Through empirical analysis of parallel-tested blood samples, four linear regression models were established, demonstrating excellent predictive accuracy (R2 > 0.99, mean absolute error < 1.2%). …”
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TransformerPayne: Enhancing Spectral Emulation Accuracy and Data Efficiency by Capturing Long-range Correlations by Tomasz Różański, Yuan-Sen Ting, Maja Jabłońska

“…The newly introduced TransformerPayne emulator outperformed all other tested models, achieving a mean absolute error (MAE) of approximately 0.15% when trained on the full grid. …”
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Development of a Model for Soil Salinity Segmentation Based on Remote Sensing Data and Climate Parameters by Gulzira Abdikerimova, Dana Khamitova, Akmaral Kassymova, Assyl Bissengaliyeva, Gulsara Nurova, Murat Aitimov, Yerlan Alimzhanovich Shynbergenov, Moldir Yessenova, Roza Bekbayeva

“…The classification accuracy was 99.99%, with only one error in more than 10,000 test objects. The results confirmed the proposed method’s high efficiency and applicability for remote monitoring, environmental analysis, and sustainable land management.…”
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An investigation of inversion method to measure the radial velocity of Kuroshio from Sentinel-1 SAR data by Benhua Tan, Lihua Wang, Dechen Ge, Zhen Fang, Weiwei Sun, Tian Feng

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Monitoring water quality parameters using multi-source data-driven machine learning models by Yubo Zhao, Mo Chen, Jinyu He, Yanping Ma

“…Remote sensing technology, as an effective monitoring tool, provided real-time water quality data. Currently, most research primarily relied on reflectance analysis of remote sensing data, often overlooking the impact of environmental factors on aquatic environments. …”
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Assessing the Role of Intrinsic Variability in Black Hole Parameter Inference Using Multiepoch EHT Data by Dominic O. Chang, Michael D. Johnson, Paul Tiede

“…Our findings highlight both the promise and challenges of multiepoch EHT observations: while they can refine parameter constraints, they also reveal the limitations of simple parametric models in capturing the full source complexity. Our analysis—the first to fit semianalytic emission models to 2018 EHT observations—underscores the importance of quantifying data contributions from intrinsic variability in future high-resolution imaging studies of black hole environments and the role of repeated observations in quantifying these uncertainties.…”
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Estimating Seafloor Topography of the South China Sea Using SWOT Wide-Swath Altimetry Data by Fengshun Zhu, Jinbo Li, Yang Li, Jianqiao Xu, Jinyun Guo, Jiangcun Zhou, Heping Sun

“…This study utilized 15 cycles of SWOT Level-3 product to construct seafloor topography model of the South China Sea by linear regression analysis. The root mean square error of the difference between the model and shipborne bathymetry at checkpoints is about 120 m, which is 20 m better than topo_27.1 and DTU18BAT, and 40 m better than ETOPO1. …”
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SPA-Net: An Offset-Free Proposal Network for Individual Tree Segmentation from TLS Data by Yunjie Zhu, Zhihao Wang, Qiaolin Ye, Lifeng Pang, Qian Wang, Xiaolong Zheng, Chunhua Hu

“…Unlike methods heavily reliant on potentially error-prone global offset vector predictions, SPA-Net employs a novel sampling-shifting-grouping paradigm within its sparse geometric proposal (SGP) module to directly generate initial proposal candidates from raw point data, aiming to reduce dependence on the offset branch. …”
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Enhancing County-Level GDP Estimation Accuracy With Downscaled NPP-VIIRS Nighttime Light Data by Weihua Lin, Weixing Xu, Zhaocong Wu, Jiaheng Cao

“…Additionally, the downscaled NTL data improve the accuracy of GDP estimates by reducing the relative error between estimated and statistical GDP compared to NPP-VIIRS NTL data. …”
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Enhancing Immunoglobulin G Goat Colostrum Determination Using Color-Based Techniques and Data Science by Manuel Betancor-Sánchez, Marta González-Cabrera, Antonio Morales-delaNuez, Lorenzo E. Hernández-Castellano, Anastasio Argüello, Noemí Castro

“…This study proposes a more accessible alternative for farmers to predict IgG concentration in goat colostrum by integrating color-based techniques with machine learning models, specifically decision trees and neural networks, through the development of two regression models based on colostrum color data from Majorera dairy goats. A total of 813 colostrum samples were collected in a previous study (June 1997–April 2003) that utilized multiple regression analysis as a reference to verify that applying data science techniques improves accuracy and reliability. …”
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An Improved Size and Direction Adaptive Filtering Method for Bathymetry Using ATLAS ATL03 Data by Lei Kuang, Mingquan Liu, Dongfang Zhang, Chengjun Li, Lihe Wu

“…After applying refraction correction, the high accuracy of bathymetry was evidenced by a strong coefficient of determination (R<sup data-eusoft-scrollable-element="1">2</sup>) and a low root mean square error (RMSE) between the ICESat-2 bathymetry data and ALB data. …”
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Monitoring and Evaluation of High Temperature and Heat Damage of Summer Maize Based on Remote Sensing Data by Yang Lei, Han Lijuan, Song Jinling, Li Sen

“…Combined with MOD/MYD11A1 land surface temperature products and ground measured temperature data, based on linear correlation between land surface temperature and air temperature, a method of combining multiple stepwise regression and principal component analysis is used to construct a high-temperature damage evaluation model for the Huang-Huai-Hai summer maize production area. …”
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Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapy by Takuya Sakamoto, Hiroto Koma, Ayane Kuwano, Tetsuhiro Horie, Atsushi Fuku, Hironori Kitajima, Yuka Nakamura, Ikuhiro Tanida, Yujiro Nakade, Hiroaki Hirata, Yoshiyuki Tachi, Hiroshi Sunami, Daisuke Sakamoto, Sohsuke Yamada, Naoki Yamamoto, Yusuke Shimizu, Yasuhito Ishigaki, Toru Ichiseki, Ayumi Kaneuji, Satoshi Osawa, Norio Kawahara

“…Measurement accuracy was validated using Bland–Altman analysis and scatter plot correlation coefficients.Results ChatGPT Data Analyst was consistent with ImageJ for all parameters. …”
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Aided Greenway Design Approach Based on Internet Big Data and AIGC Fine-Tuning Model by Yifan WU, Lu MENG, Liang LI

“…Consequently, these three categories of images are chosen as data samples for subsequent analysis and model training. …”
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Spatial analysis of annual precipitation of Khuzestan province; An approach of spatial regressions analysis by Saeed balyani

“…In order to determine of precipitation model and forecasting it, there are different models, but given that the precipitation data have a spatial autocorrelation, the spatial statistic is a powerful tool to recognition of spatial behaviors. …”
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Outreach eye camps: Providing comprehensive vision care in underserved areas of North India: Meeting the unmet by Asma Jabeen

“…Data analysis was done through descriptive statistical analysis, comparative analysis, and thematic analysis of qualitative data. …”
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