Sentiment and Emotion Network Analysis—SENA: An Analytic Framework and No-Code Software to Integrate Natural Language Processing, Linguistic Analysis, and Data Science with Qualita... by Manuel S. González Canché, Kaiwen Zheng

“…Narrow applicability means that SEA has primarily been employed in market research to understand customers’ satisfaction thus foregoing its applicability in qualitative and mixed methods academic research. …”
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Identifying missing sources and reducing NO_<i>x</i> emissions uncertainty over China using daily satellite data and a mass-conserving method by L. Lu, L. Lu, J. B. Cohen, J. B. Cohen, K. Qin, K. Qin, X. Li, X. Li, Q. He, Q. He

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Enhancing Temperature Data Quality for Agricultural Decision-Making with Emphasis to Evapotranspiration Calculation: A Robust Framework Integrating Dynamic Time Warping, Fuzzy Logi... by Christos Koliopanos, Alexandra Gemitzi, Petros Kofakis, Nikolaos Malamos, Ioannis Tsirogiannis

“…The enhanced temperature data significantly improve the reliability of inputs for applications such as evapotranspiration (ET) estimation and agricultural decision support systems (DSS). …”
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A Study of the Non-Linear Relationship Between Urban Morphology and Vitality in Heritage Areas Based on Multi-Source Data and Machine Learning: A Case Study of Dalian by He Li, Li Miao

“…However, existing research primarily focuses on urban areas, leaving the applicability of urban form elements to heritage sites and their influence mechanisms unclear. …”
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Predictive analysis of total organic carbon (TOC) in shale targets: example from the Lower Cretaceous of the Austral Basin (Patagonia, Argentina) using machine learning on outcrop... by Sebastian M. Richiano, Federico Ares

“…This study explores the potential of machine learning (ML) for predicting Total Organic Carbon (TOC) content using outcrop data, a novel approach compared to traditional subsurface data applications. …”
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Kharif rice crop acreage and yield estimation using microwave and optical remote sensing time series satellite data: A case study of the eastern region of Maharashtra by Pritam Meshram, Kishan Singh Rawat, Gaurav Singh

“…Material and methods: Recent advancements in remote sensing technology, including improvements in image resolution and availability, allowed for timely data collection. The study employs a random forest classifier to identify rice crop using sentinel-1A SAR temporal backscatter satellite images. …”
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CrystalShift: A Versatile Command-Line Tool for Crystallographic Structural Data Analysis, Modification, and Format Conversion Prior to Solid-State DFT Calculations of Organic Crys... by Ilona A. Isupova, Denis A. Rychkov

“…<i>CrystalShift</i> is an open-source computational tool tailored for the analysis, transformation, and conversion of crystallographic data, with a particular emphasis on organic crystal structures. …”
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Extraction of Periodic Characteristics and Long-Term Stock Price Forecasting Using Non-Harmonic Analysis With Over 14 Years of NASDAQ Data Before and After COVID-19 by Yuki Kojima, Li Ma, Keisuke Nomoto, Masaya Hasegawa, Shigeki Hirobayashi

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Evaluation of surface albedo products from ERA5, JRA-55, MERRA-2, and CERES-EBAF on the Tibetan Plateau: insights from in-situ observations and MODIS data by Guojin Pang, Lingzhen Meng, Xuejia Wang, Fei Liu, Mengyao Shu, Chunli Ma, Tao Che

“…However, significant discrepancies exist in various albedo datasets, primarily due to variations in the surface data and simulation models employed. This study assessed the applicability of five surface albedo products (MODIS, ERA5, MERRA-2, JRA-55, and CERES-EBAF) in the Tibetan Plateau using nine in-situ monitoring sites and explored the potential factors of vegetation and snow cover on these products. …”
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Applying Multi-Sensor Satellite Data to Identify Key Natural Factors in Annual Livestock Change and Winter Livestock Disaster (<i>Dzud</i>) in Mongolian Nomadic Pasturelands by Sinkyu Kang, Nanghyun Cho, Amartuvshin Narantsetseg, Bolor-Erdene Lkhamsuren, Otgon Khongorzul, Tumendemberel Tegshdelger, Bumsuk Seo, Keunchang Jang

“…In the present study, we tested the applicability of multi-sensor satellite data to account for key natural factors of annual livestock number changes in county-level <i>soum</i> districts of Mongolia. …”
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Streamflow estimation in the Indus River Basin using a water balance framework and artificial neural networks with satellite- and model-derived global hydro-climatic data sources by Hira Sattar, Tsuyoshi Kinouchi

“…First, the water balance framework was employed to select the best-performing datasets for P and E from various sources, including satellite observations, reanalysis products, and combined satellite-gauge data. These selected datasets, together with terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE), were then used in separate applications of the water balance equation and artificial neural networks (ANN) for streamflow estimation. …”
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Integrating UAS-Based GNSS-R, LiDAR, and Multispectral Data for Soil Moisture Estimation: Summary of Results From a Three-Year-Long Field Campaign by Md Mehedi Farhad, Volkan Senyurek, Mohammad Abdus Shahid Rafi, Sriman Bidhan Baray, Cary McCraine, Lee A. Hathcock, Ardeshir Adeli, Huang Yanbo, Ali C. Gurbuz, Mehmet Kurum

“…The experiment spans three years of data collection over 2.31 hectares of corn and cotton fields, incorporating GNSS-R, multispectral imaging, light detection and ranging, and in situ SM measurements. …”
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Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of... by Ronald P. Dillner, Maria A. Wimmer, Matthias Porten, Thomas Udelhoven, Rebecca Retzlaff

“…Assessing vines’ vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. …”
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Land Surface Temperature Retrieval from Landsat 9 Satellite Data in the Case of Injibara Town and the Surrounding Banja District, Awi Nationality Administrative Zone, Amhara, Ethio... by Minyichil Teshome Kassahun, Nigatu Amsalu Workineh

“…Land surface temperature (LST) is crucial for various applications like agriculture, hydrology, urban planning, and climate analysis. …”
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Prospective external validation of the automated PIPRA multivariable prediction model for postoperative delirium on real-world data from a consecutive cohort of non-cardiac surgery... by Mary-Anne Kedda, Kelly A Reeve, Nayeli Schmutz Gelsomino, Michela Venturini, Felix Buddeberg, Martin Zozman, Reto Stocker, Philipp Meier, Marius Möller, Simone Pascale Wildhaber, Benjamin T Dodsworth

“…This study externally validated the Pre-Interventional Preventive Risk Assessment (PIPRA) algorithm, a CE-certified tool for identifying high-risk patients to enable targeted prevention.Methods A prospective validation study was conducted at a 335-bed Swiss hospital as part of a quality improvement initiative. Data from 866 patients aged ≥60 undergoing non-cardiac, non-intracranial surgery (May–June 2023) were analysed. …”
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A Scalable Data-Driven Surrogate Model for 3D Dynamic Wind Farm Wake Prediction Using Physics-Inspired Neural Networks and Wind Box Decomposition by Qiuyu Lu, Yuqi Cao, Pingping Xie, Ying Chen, Yingming Lin

“…This paper proposes a novel data-driven surrogate modeling framework to bridge this gap, leveraging Neural Networks (NNs) trained on data from the high-fidelity SOWFA (simulator for wind farm applications) tool. …”
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Immigration-specific stress and 24-hour movement behaviors among international nurses in Japan: a network and time-series network analysis using wearable device data by Xinyi Chang, Xiuzhu Gu

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Relações empíricas entre a estrutura da vegetação e dados do sensor TM/LANDSAT Empirical relationship between vegetation structure and TM/LANDSAT data by Luciano J. de O. Accioly, Admilson Pachêco, Thomaz C. e C. da Costa, Osvaldo F. Lopes, Maria A. J. de Oliveira

“…<br>The use of spectral data to estimate the structural parameters of vegetation has been considered as one of the most important applications of the remote sensing of ecosystems. …”
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An Analytical Prior Selection Procedure for Empirical Bayesian Analysis Using Resampling Techniques: A Simulation-Based Approach Using the Pancreatic Adenocarcinoma Data from the S... by Aditya Chakraborty, Mohan D. Pant

“…<b>Results:</b> The most appropriate data distribution was found to be a two-parameter log-normal via GOF tests. …”
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A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and... by Priya Mathur, Hammad Shaikh, Farhan Sheth, Dheeraj Kumar, Amit Kumar Gupta

“…This framework offers a scalable and reliable tool for advancing nanofluid-based applications in thermal engineering and related domains.…”
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