Prediction of teaching quality in the context of smart education: application of multimodal data fusion and complex network topology structure by Chunzhong Li, Chenglan Liu, Wenliang Ju, Yuanquan Zhong, Yonghui Li

Subjects: “…Complex network topology structure…”
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New data on the structure and motion of the ice sheet in the area of a runway of the Novolazarevskaya Reserch Station (East Antarctica) by A. S. Boronina, M. P. Kashkevich, S. V. Popov, E. M. Mikhailov, A. E. Druzhin

“…The central part of the runway appears to be the most complex in structure, demonstrating relatively high deformations in the marginal parts and characterized by large vertical structures in the glacier. …”
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THE STRUCTURE AND HISTORY OF ABYSSAL HILLS OF THE NORTH-WESTERN PACIFIC PLATE FROM CONTINUOUS SEISMIC PROFILING AND STRATIGRAPHIC DATA by V. L. Lomtev

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Local structure of solid and liquid gold probed by reverse Monte Carlo analysis of X-ray absorption data by Nodoka Hara, Fabio Iesari, Toshihiro Okajima, Andrea Di Cicco

“…The increase in computational capabilities of modern computers has allowed us to develop new accurate methods for EXAFS (extended X-ray absorption fine structure) data-analysis. In particular, the RMC-GNXAS package provides models of the three-dimensional structure applying the reverse Monte Carlo (RMC) method to EXAFS of condensed or molecular systems. …”
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Automated Collection Planning for Civilian and Commercial Satellite Imagery, and Definition and Exploitation of the Collection Asset Specification Data Structure by Jeff Secker, Katerina Biron, Dany Dessureault, Pierre Lamontagne, Rodney Rear

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Data of vegetation structure metrics retrieved from airborne laser scanning surveys for European demonstration sitesZenodo by W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

“…A total of 35 LiDAR metrics were calculated, of which 28 represent vegetation structural attributes. These include vegetation height (seven metrics), vegetation cover (fourteen metrics), and vegetation vertical variability (seven metrics). …”
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Structuring data analysis projects in the Open Science era with Kerblam! [version 1; peer review: 2 approved] by Federico Alessandro Ruffinatti, Luca Munaron, Luca Visentin

“…Background Structuring data analysis projects, that is, defining the layout of files and folders needed to analyze data using existing tools and novel code, largely follows personal preferences. …”
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Debiasing Structure Function Estimates from Sparse Time Series of the Solar Wind: A Data-driven Approach by Daniel Wrench, Tulasi N. Parashar

“…Structure functions (SFs), which quantify the moments of increments of a stochastic process, are essential complementary statistics to power spectra for analyzing the self-similar behavior of a time series. …”
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Grain Protein Function Prediction Based on CNN and Residual Attention Mechanism with AlphaFold2 Structure Data by Jing Liu, Xinping Zhang, Kai Huang, Yuqi Wei, Xiao Guan

“…The experimental results indicate that secondary structure and spatial structure information contribute to improving model performance. …”
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A structured-illumination reflectance imaging dataset for woody breast assessment of broiler meatZenodo by Yuzhen Lu, Hamed Sardari

“…An image dataset was created to assess WB conditions in broiler breast fillets using structured-illumination reflectance imaging (SIRI) as a non-destructive, objective means for WB assessment. …”
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A Semi-Supervised Deep Network Embedding Approach Based on the Neighborhood Structure by Wenmao Wu, Zhizhou Yu, Jieyue He

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Structural and analytical studies on some complexes of Pd2+ ions with asymmetric -dioximes by Daniela Cîrțînă

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Urban Viaduct Structural Health Monitoring: A Review of Wireless Sensor Approaches by Tianli Wang, Tong Cui, Xin Qi, Xintao Huan

“…In this paper, we review the full-chain methods of employing wireless sensor technology for urban viaduct structural health monitoring. By proposing a general wireless structural health monitoring approach as a framework, we first review the sensor types and wireless transmission technologies, then the data processing and modal identification methods, and finally the damage detection methods. …”
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Auxo: A Temporal Graph Management System by Wentao Han, Kaiwei Li, Shimin Chen, Wenguang Chen

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Molecular structure data and modelling roadmap for optimized oxidized graphene quantum dot and epoxy interface and mechanical propertiesMendeley Data by Prathamesh Deshpande, Robert Chan-Jobe, Ozgur Keles

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A Bibliometric Analysis of International Structural Engineering Standards Using VOS Viewer by Andri Irfan Rifai, Darius Angtony, Ade Jaya Saputra, Joewono Prasetijo

“…The outcome indicates that “standards” and “structure” are still trending topics in global discourse. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…ObjectiveStructural parameter identification based on swarm intelligent optimization methods has become one of the popular methods for finite element model modification. …”
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Crashworthiness simulation dataset of re-entrant crash box with combined in-plane and out-of-plane filling structureMendeley Data. by Arif Rochman Fachrudin, Moch. Agus Choiron, Anindito Purnowidodo, Yudy Surya Irawan

“…This article presents a dataset generated from finite element simulations of square aluminum crash box with various re-entrant infill structures. The configurations include in-plane, out-of-plane and combined in-plane and out-of-plane geometries. …”
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DETERMINANTS OF STRUCTURAL DIMENSION OF DAILY BEHAVIOUR IN A TRADITIONAL AFRICAN CITY: A CASE STUDY OF ILORIN, NIGERIA by Moses Olutoyin ADEDOKUN

“…The study also shows clearly that the temporal structure of activity in Ilorin is different from what obtains in Western cities where there is flexibility in the usage of time. …”
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Knowledge and theme discovery across very large biological data sets using distributed queries: a prototype combining unstructured and structured data. by Uma S Mudunuri, Mohamad Khouja, Stephen Repetski, Girish Venkataraman, Anney Che, Brian T Luke, F Pascal Girard, Robert M Stephens

“…As we move towards personalized medicine, the need to combine unstructured data, such as medical literature, with large amounts of highly structured and high-throughput data such as human variation or expression data from very large cohorts, is especially urgent. …”
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