Dynamic graph structure and spatio-temporal representations in wind power forecasting by Zang Peng, Dong Wenqi, Wang Jing, Fu Jianglong

“…However, due to the stochastic and unstable nature of wind, it poses a real challenge to effectively analyze the correlations among multiple time series data for accurate prediction. In our study, an end-to-end framework called Dynamic Graph structure and Spatio-Temporal representation learning (DSTG) framework is proposed to achieve stable power forecasting by constructing graph data to capture the critical features in the data. …”
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KARAŞAR, AN ALEVI-BEKTASHI SETTLEMENT IN BEYPAZARI (ADMINISTRATIVE, ECONOMIC AND SOCIAL STRUCTURE) by İsmail Yaşayanlar

“…This study evaluates the economic and social structure of Karaşar, an Alevi-Bektashi settlement, on the basis of data from tahrir, population and temettuat books in the Ottoman Archives. …”
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Bayesian variable selection with graphical structure learning: Applications in integrative genomics. by Suprateek Kundu, Yichen Cheng, Minsuk Shin, Ganiraju Manyam, Bani K Mallick, Veerabhadran Baladandayuthapani

“…This has motivated systematic data-driven approaches to integrate multi-dimensional structured datasets, since cancer development and progression is driven by numerous co-ordinated molecular alterations and the interactions between them. …”
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Advancing Structural Health Monitoring with Deep Belief Network-Based Classification by Álvaro Presno Vélez, Zulima Fernández Muñiz, Juan Luis Fernández Martínez

“…In recent years, deep learning techniques have emerged as powerful tools for analyzing the complex data generated by SHM systems. This study investigates the use of deep belief networks (DBNs) for classifying structural conditions before and after retrofitting, using both ambient and train-induced acceleration data. …”
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Using the Size Structure of Populations to Infer Range Dynamics and the Frequency of Recruitment by Jenny Ann Sweatman, J. David Aguirre, Adam N. H. Smith, Libby Liggins

“…Our study demonstrates that size‐structure data can be a valuable resource in understanding range dynamics and recruitment in the absence of time‐series data.…”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Abstract Background Gene regulatory network modeling is a complex structure learning problem that involves both observational data analysis and experimental interventions. …”
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Impact of capital structure on financial performance of oil and gas firms in Nigeria by Obumneme Renato Anozie, Taiwo Adewale Muritala, Victor Edet Ininm, Nurudeen Salako Yisau

“…Abstract This study examines the impact of capital structure on the financial performance of Nigerian oil and gas companies. …”
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A Model-Based Substructuring Method for Local Damage Detection of Structure by Eun-Taik Lee, Hee-Chang Eun

“…It is impractical to collect the full set of data in finite element model for investigating the structural performance. …”
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Structural Assessment of Flexible Pavements Based on the Level of Detail of Management Functions by Edwin Antonio Guzmán Suárez, Diego Fernando Gualdrón Alfonso, Jorge Andrés Sarmiento-Rojas

“…Context: Pavement condition data are a fundamental component of pavement management systems (PMS) and play a critical role in structural evaluation. …”
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A Minimalist Analysis of the Subjunctive Mood in the Clausal Structure of Central Kurdish by Azad Hasan Fatah, Rawand Anwar Mahmood

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Structural Health Monitoring of Laminated Composites Using Lightweight Transfer Learning by Muhammad Muzammil Azad, Izaz Raouf, Muhammad Sohail, Heung Soo Kim

“…Therefore, deep learning-based methods that use sensor data to conduct autonomous health monitoring have drawn much interest in structural health monitoring (SHM). …”
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Remote sensing‐based mapping of structural building damage in the Ahr valley by Guilherme Samprogna Mohor, Tobias Sieg, Oliver Koch, Aaron Buhrmann, Holger Maiwald, Jochen Schwarz, Annegret H. Thieken

“…Abstract Flood damage data are needed for various applications. Structural damage of buildings can reflect not only the economic damage but also the life‐threatening condition of a building, which provide crucial information for disaster response and recovery. …”
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An Experimental Technique for Structural Diagnostic Based on Laser Vibrometry and Neural Networks by Paolo Castellini, Gian Marco Revel

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Structural assessment and seismic response of the historic Justinian stone arch bridge by Zeki Özcan

“…The research examines the structural configuration of the bridge and integrates its architectural background with data derived from comprehensive analyses. …”
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Uncovering intention behind the translation of headlines: a thematic structure analysis by Ninuk Sholikhah Akhiroh, Mangatur Nababan, Riyadi Santosa, Djatmika

“…Using a qualitative method, the data was analyzed using Hallidayan concept of Thematic Structure, and Stiles’ Levels of Intention, and applied Spradley model of data analysis. …”
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Discovering structural cis‐regulatory elements by modeling the behaviors of mRNAs by Barrett C Foat, Gary D Stormo

“…We applied our structural cis‐regulatory element detector (StructRED) to microarray and mRNA sequence data from Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens. …”
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From dairy to plant products: Understanding their structural fingerprints with X-rays by Eleonora Olsmats, Adrian R. Rennie

“…The study provides a basis for understanding scattering data where structural fingerprint plots, using colour scales to compare intensity and intensity gradient, allow ready data interpretation that will be beneficial for analysis with artificial intelligence (AI) tools. …”
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Hydrothermal structure of a polythermal glacier in Spitsbergen by measurements and numerical modeling by A. V. Sosnovsky, Yu. Ya. Macheret, A. F. Glazovsky, I. I. Lavrentiev

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Genetic structure of different ethnic populations at the frontotemporal dementia risk loci. by Volodymyr Mavrych, Maryam Alamil, Olena Bolgova, Volodymyr Dvornyk

“…This study aimed to analyze the genetic structure of different ethnic populations at FTD risk loci and provide insights into possible genetic factors underlying the above variation.…”
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Frequency and Structure of Drug Resistance of M. tuberculosis in Pulmonary and Extrapulmonary Tuberculosis by P. K. Yablonskiy, B. I. Vishnevskiy, N. S. Solovyova, V. B. Galkin

“…The objective: to assess changes in the data on drug resistance of M. tuberculosis for 2015-2021 and compare it with data for 2012-2014.Subjects and Methods. …”
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