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

Subjects: “…model structure…”
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A dynamic key management and secure data transfer based on m-tree structure with multi-level security framework for Internet of vehicles by Hua Yi Lin, Meng-Yen Hsieh

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PATIENTS WITH ATRIAL FIBRILLATION IN MULTIDISCIPLINARY HOSPITAL: STRUCTURE OF HOSPITALIZATION, CONCOMITANT CARDIOVASCULAR DISEASES AND DRUG TREATMENT (DATA OF RECVASA AF-TULA REGISTRY) by M. N. Valiakhmetov, T. A. Gomova, M. M. Loukianov, S. Yu. Martsevich, K. N. Nadejkina, M. N. Artemova, D. N. Jilin, E. E. Fedotova, A. V. Zagrebelnyy, E. V. Kudryashov, S. A. Boytsov

“…All patients with a diagnosis of AF in the patient's chart (n=1225) were included into the RECVAZA AF-Tula registry; that is 4.2% of 29018 patients hospitalized to the Tula Regional Clinical Hospital in 2013. The structure of the associated cardiovascular diseases, as well as drug therapy, was evaluated on the basis of data in the medical documentation.Results. …”
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Detachment‐Fault Structure Beneath the TAG Hydrothermal Field, Mid‐Atlantic Ridge, Revealed From Dense Wide‐Angle Seismic Data by Szu‐Ying Lai, G. Bayrakci, B. J. Murton, T. A. Minshull

“…We used dense wide‐angle seismic data to define TAG's detachment structure at a finer scale than has previously been possible. …”
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Large language models for data extraction from unstructured and semi-structured electronic health records: a multiple model performance evaluation by Vasileios Ntinopoulos, Hector Rodriguez Cetina Biefer, Igor Tudorache, Nestoras Papadopoulos, Dragan Odavic, Petar Risteski, Achim Haeussler, Omer Dzemali

“…Objectives We aimed to evaluate the performance of multiple large language models (LLMs) in data extraction from unstructured and semi-structured electronic health records.Methods 50 synthetic medical notes in English, containing a structured and an unstructured part, were drafted and evaluated by domain experts, and subsequently used for LLM-prompting. 18 LLMs were evaluated against a baseline transformer-based model. …”
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A comparative study of regression methods to predict forest structure and canopy fuel variables from LiDAR full-waveform data by P. Crespo-Peremarch, L.A. Ruiz, A. Balaguer-Beser

“…Regression methods are widely employed in forestry to predict and map structure and canopy fuel variables. We present a study where several regression models (linear, non-linear, regression trees and ensemble) were assessed. …”
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Structure of snow-­ice dams of the outburst lakes in the Broknes Peninsula (Larsemann Hills, East Antarctica) based on ground­penetrating radar data by S. D. Grigoreva, E. R. Kiniabaeva, M. R. Kuznetsova, S. V. Popov, M. P. Kashkevich

“…During the summer field season of the 65th Russian Antarctic Expedition a research aimed at studying the structure of the snow-­ice dams of the Lakes Progress and Discussion (Larsemann Hills, East Antarctica), which are characterized with annual outburst floods, was carried out. …”
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A nonparametric approach for detecting urban polycentric spatial structure in China using remote sensing nighttime light and point of interest data by Linlin Jiang, Yizhen Wu, Junru Wang, Huiran Han, Kaifang Shi

“…Effectively identifying urban polycentric spatial structure (UPSS) is essential for data-driven evaluation of urban performance, and it serves as a scientific basis for urban spatial planning. …”
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Optimization of Structural Parameters and Mechanical Performance Analysis of a Novel Redundant Actuation Rehabilitation Training Robot by Junyu Wu, He Wang, Yubin Liu, Zhuoqi Man, Xiaofan Yang, Xuanming Cao, Hegao Cai, Jie Zhao

“…The integration of redundant structures into robotic systems enhances the degrees of freedom (DOFs), flexibility, and capability to perform complex tasks. …”
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The Effect of Different Components of the Brainling Model (i.e., Cultuling, Cogling, Sensoling, and Emoling) on their Recall and Retention of Complex Structures: EFL Learners’ Perc... by Mohadese Karimi, Neda Fatehi Rad, Vale Jalali

“…This research used a semi-structured interview with five open-ended questions to collect the data. …”
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Algorithm of athletes’ fitness structure individual features’ determination with the help of multidimensional analysis (on example of basketball) by Zh.L. Kozina, M. Cieslicka, K. Prusik, R. Muszkieta, I.N. Sobko, O.A. Ryepko, T.A. Bazilyuk, S.B. Polishchuk, A.V. Osiptsov, S.A. Korol

“…In every micro-cycle 30% is assigned for athletes’ individual training: athletes received individual tasks; groups on the base of cluster analysis data were formed, if necessary. Conclusions: when working out individual training programs, development of leading factors in individual factorial structure of athletes’ fitness shall be accented. …”
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The influencing factors of newly employed nurses’ adaptation in Malaysia: a structural equation modelling assessment by Hafidza Baharum, Aniza Ismail, Zainudin Awang, Lisa McKenna, Roszita Ibrahim, Zainah Mohamed, Nor Haty Hassan, Abdul Haniff Mohamad Yahaya

“…Questionnaires were distributed through Google Forms. The data were analysed using covariance-based structural equation modelling. …”
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Selection of a Probability Model Adapted to the Current Climate for Annual Maximum Daily Rainfall in the Benin Mono-Couffo Basin (West Africa) by Voltaire Midakpo Alofa, Mathieu B. Hounsou, Grâce-Désirée Houeffa, Yèkambèssoun N’tcha M’po, David Houéwanou Ahoton, Expédit Vissin, Euloge Agbossou

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3D Visualization Method for Surface Defects of Underwater Structures Based on Acoustic and Optical Combination Measurement by Xiang WANG, Jinchao WANG, Houcheng LIU, Wanpeng SONG, Shuqi LI

“…Finally, a three-dimensional visualization system for surface defects of underwater structures is developed by constructing a texture feature image enhancement algorithm, synchronously utilizing sound and light combination data. …”
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A Refinement Reconstruction Method for Indoor Structures Based on 3D Point Cloud Template Matching by B. Cai, S. Tang, W. Wang, L. Xie, X. Li, R. Guo

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Seismic Facies Classification of Salt Structures and Sediments in the Northern Gulf of Mexico Using Self-Organizing Maps by Silas Adeoluwa Samuel, Camelia C. Knapp, James H. Knapp

“…SOM Models 1 and 2, which combined geometric, spectral, and amplitude-based attributes, were shown to delineate potential storage reservoirs, gas hydrates, salt structures, associated radial faults, and areas with poor data quality due to the presence of the salt structures more than SOM Models 3 and 4. …”
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GEOMAPLEARN 1.2: detecting structures from geological maps with machine learning – the case of geological folds by D. Oakley, D. Oakley, C. Loiselet, T. Coowar, T. Coowar, V. Labbe, J.-P. Callot

“…<p>The increasing availability of large geological datasets and modern methods of data analysis facilitate a data science approach to geology in which inferences are drawn from geological data using automated methods based on statistics and machine learning. …”
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Iterative Approach to the Area Collapse Algorithm for 2D Geometric Objects Representing Long Engineering Structures by Michał M. Buczek

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Gold Punning: studying multistable meaning structures using a systematically collected set of lexical blends by Daniel Kjellander

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P- and S-Wave Velocity Structures and the Influence of Volcanic Activities in the East Java Area From Seismic Tomography by Syawaldin Ridha, Sukir Maryanto, Agustya A. Martha, Vanisa Syahra, Muhajir Anshori, Pepen Supendi, Sri Widiyantoro, Sri D. Wuryani, Rendi P. Hab Sari

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