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Showing 1,481 - 1,500 results of 53,535 for search '((structures OR ((unstructures OR structural) OR structural)) OR structured) data', query time: 0.49s Refine Results
  1. 1481
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  3. 1483

    A Deep Learning Method for the Automated Mapping of Archaeological Structures from Geospatial Data: A Case Study of Delos Island by Pavlos Fylaktos, George P. Petropoulos, Ioannis Lemesios

    Published 2025-06-01
    “…By combining these state-of-the-art technologies, this study demonstrates the algorithm’s effectiveness at recognizing and segmenting the ancient structures within the archaeological site of Delos, Greece. …”
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  4. 1484

    Fatigue strength of welded aluminum structures – A re-evaluation of fatigue data of welded aluminum joints with nominal stress approach by Juho Havia, Antti Ahola, Timo Björk

    Published 2025-06-01
    “…This work analyzes the applicability of the nominal stress approach to welded aluminum joints, with respect to the second generation of Eurocode 9: Design of Aluminium Structures and recommendations of International Institute of Welding, utilizing experimental fatigue test data extracted from existing relevant literature. …”
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  5. 1485

    Autoencoder-Augmented Graph Neural Networks for Accurate and Scalable Structure Recognition in Analog/Mixed-Signal Schematics by Mohamed Salem, Witesyavwirwa Vianney Kambale, Ali Deeb, Sergii Tkachov, Anjeza Karaj, Joachim Pichler, Manuel Ludwig Lexer, Kyandoghere Kyamakya

    Published 2025-01-01
    “…The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, where data scarcity and confidentiality constraints limit model training. …”
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  6. 1486
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    Evaluation of Clinical Competencies and Feedback of Senior Dental Students with Objective Structured Clinical Examination (OSCE) by Maryam Basirat, Fatemeh Rahbar Masouleh, Mehran Falahchai, Abtin Heidarzadeh

    Published 2025-01-01
    “…Introduction: The Objective Structured Clinical Examination (OSCE) serves as a scientific evaluation method that effectively enhances clinical assessment techniques and transforms management strategies to solve educational problems. …”
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    Article
  8. 1488

    From Viewing to Structure: A Computational Framework for Modeling and Visualizing Visual Exploration by Kuan-Chen Chen, Chang-Franw Lee, Teng-Wen Chang, Cheng-Gang Wang, Jia-Rong Li

    Published 2025-07-01
    “…This approach opens new possibilities for discovering structural organization within visual exploration data and analyzing goal-directed viewing behaviors. …”
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  9. 1489

    Building a High-Performance Graph Storage on Top of Tree-Structured Key-Value Stores by Heng Lin, Zhiyong Wang, Shipeng Qi, Xiaowei Zhu, Chuntao Hong, Wenguang Chen, Yingwei Luo

    Published 2024-03-01
    “…The present study focuses on the design and implementation of graph storage layout, with a particular emphasis on tree-structured key-value stores. We also examine different design choices in the graph storage layer and present our findings through the development of TuGraph, a highly efficient single-machine graph database that significantly outperforms well-known Graph DataBase Management System (GDBMS). …”
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  10. 1490
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    Graph compression algorithm based on a two-level index structure by Gaochao LI, Ben LI, Yuhai LU, Mengya LIU, Yanbing LIU

    Published 2018-06-01
    “…The demand for the analysis and application of graph data in various fields is increasing day by day.The management of large-scale graph data with complicated structure and high degree of coupling faces two challenges:one is querying speed too slow,the other is space consumption too large.Facing the problems of long query time and large space occupation in graph data management,a two-level index compression algorithm named GComIdx for graph data was proposed.GComIdx algorithm used the ordered Key-Value structure to store the associated nodes and edges as closely as possible,and constructed two-level index and hash node index for efficient attribute query and neighbor query.Furthermore,GComIdx algorithm used a graph data compressed technology to compress the graph data before it directly stored in hard disk,which could effectively reduce the storing space consumption.The experimental results show that GComIdx algorithm can effectively reduce the initialization time of the graph data calculation and the disk space occupancy of the graph data storing,meanwhile,the query time is less than common graph databases and other Key-Value storage solutions.…”
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  13. 1493

    The comparison of islamic and conventional banking in ownership structure and interest rates in Indonesia by Titin Hartini, Rika Lidyah, Nurfala Safitri

    Published 2024-02-01
    “…This study aims to compare the performance of Islamic and conventional banking in ownership structure and interest rates. In study, the author used quantitative methods that emphasize the analysis of numerical data processed using Stata 16. …”
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  14. 1494

    A Few Remarks on the Stochastic Structure of the Unemployment Rate in Poland by Gender by Stanisław Jaworski

    Published 2020-01-01
    “…It appeared that for Polish unemployment data that structure was not as it could have been expected. …”
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  15. 1495

    Mapping topographic structure in white matter pathways with level set trees. by Brian P Kent, Alessandro Rinaldo, Fang-Cheng Yeh, Timothy Verstynen

    Published 2014-01-01
    “…We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. …”
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  16. 1496

    An Ultrafast Optical Imaging System with Anamorphic Transformation Based on STEAM Structure by Guoqing Wang, Yuan Zhou, Rui Min, Fang Zhao, E Du, Xingquan Li, Cong Qiu, Dongrui Xiao, Chao Wang

    Published 2024-12-01
    “…In this paper, we propose an ultrafast optical imaging system with anamorphic transformation (AT) based on the STEAM structure, which has the benefit of data compression and changing group delay-related resolution. …”
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  17. 1497

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

    Published 2025-01-01
    “…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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  18. 1498

    KARAŞAR, AN ALEVI-BEKTASHI SETTLEMENT IN BEYPAZARI (ADMINISTRATIVE, ECONOMIC AND SOCIAL STRUCTURE) by İsmail Yaşayanlar

    Published 2024-12-01
    “…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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  19. 1499

    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

    Published 2018-01-01
    “…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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  20. 1500

    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

    Published 2025-06-01
    “…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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