Evaluation of structured data from electronic health records to identify clinical classification criteria attributes for systemic lupus erythematosus by Rosalind Ramsey-Goldman, Theresa L Walunas, Abel N Kho, Anika S Ghosh, Jennifer A Pacheco, Vesna Mitrovic, Andy Wu, Kathryn L Jackson, Ryan Schusler, Anh Chung, Daniel Erickson, Karen Mancera-Cuevas, Yuan Luo

“…We implemented rule-based algorithms using structured data within the EHR system for each attribute of the three classification criteria. …”
Get full text

Indicator-Type Grey Structure Incidence Analysis Method for Panel Data and Its Application in Identifying Technological Innovation Factors by Shuqin Gu, Yong Liu, Lu Yue

“…There exist many panel data decision problems in real life, and they take on obvious structural similarities and lag effects among decision objects or indicators, which are difficult to solve effectively based on traditional panel data analysis methods. …”
Get full text

Intelligent Computerized Video Analysis for Automated Data Extraction in Wave Structure Interaction; A Wave Basin Case Study by Samuel Hugh Wolrige, Damon Howe, Hamed Majidiyan

“…Despite advancements in direct sensing technologies, accurately capturing complex wave–structure interactions remain a significant challenge in ship and ocean engineering. …”
Get full text

A large-scale dataset of AI-related tweets: Structure and descriptive statisticsGitHubDataverse by Nathalie de Marcellis-Warin, Daniel Kouloukoui, Thierry Warin

“…The final dataset includes structured metadata such as media elements (images, videos, and URLs), user engagement metrics (likes, retweets, replies), hashtags, language codes, and temporal indicators (hour and weekday of posting). …”
Get full text

Graph Neural Networks for Analyzing Trauma-Related Brain Structure in Children and Adolescents: A Pilot Study by Harim Jeong, Minjoo Kang, Shanon McLeay, R. J. R. Blair, Unsun Chung, Soonjo Hwang

Subjects: Get full text

A data-driven spatial-temporal model for prediction of tunnel deformation by Ziyi Zhang, Han Zhang, Cong Du, Mingzhao Wei, Xiaochao Wang, Jianqing Wu

Subjects: “…structural health monitoring…”
Get full text

Networked Microgrid Energy Management Considering Ownership and Control Structures: A Comparison by Guodong Liu, Michael Starke

“…To solve this issue, a complete comparison of networked microgrid energy management under centralized, distributed and decentralized structures are performed. As a novel contribution, the required minimum data exchange of networked microgrid energy management under three control structures are identified, respectively. …”
Get full text

Experimental electronic structures of copper complexes with a biphenyldiimino dithioether – a model for blue copper proteins by Marek Fronc, Martin Breza, Lukáš Bučinský, Ingrid Jelemenská, Jozef Kožíšek

Subjects: “…electronic structures…”
Get full text

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

“…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. …”
Get full text

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

“…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. …”
Get full text

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

“…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. …”
Get full text

Global value chains, technological sophistication and economic complexity: panel data for 58 economies from 2006 to 2015 by Raul Costa Cavalcanti Manso, Camila do Carmo Hermida

Get full text

Constraints on the frontal crustal structure of a continental collision from an integrated geophysical research: The central‐western Betic Cordillera (SW Spain) by A. Ruiz‐Constán, A. Pedrera, J. Galindo‐Zaldívar, J. Pous, J. Arzate, F. J. Roldán‐García, C. Marin‐Lechado, F. Anahnah

Get full text

Design and Validation of the MANTiS-32 Wireless Monitoring System for Real-Time Performance-Based Structural Assessment by Jaehoon Lee, Geonhyeok Bang, Yujae Lee, Gwanghee Heo

Subjects: Get full text

Graph compression algorithm based on a two-level index structure by Gaochao LI, Ben LI, Yuhai LU, Mengya LIU, Yanbing LIU

“…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.…”
Get full text

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

“…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. …”
Get full text

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

“…It appeared that for Polish unemployment data that structure was not as it could have been expected. …”
Get full text

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

“…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. …”
Get full text

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

“…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. …”
Get full text

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. …”
Get full text