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Data based on capacitive and pressure measurement on physical vascular model developed at out university. We used capacitve sensing for dielectric volume change of artificial arterial segment on two measurement sites. For verification we used pressure sensors commonly used in medical applications to measure blood pressure or fluid pressure within the human body. Overall, your approach combining capacitive sensing and pressure measurements provides a comprehensive analysis of the dielectric volume changes in the artificial arterial segment.

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高频信号恢复图

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For the UNB-GCN  classification model, UNB as the input feature vector to the graph structure node, phenotypic information, such as gender, age and APOE genetic information, as the weight of the edges between nodes.

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For the UNB-GCN  classification model, UNB as the input feature vector to the graph structure node, phenotypic information, such as gender, age and APOE genetic information, as the weight of the edges between nodes.

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Supplementary material to the article "Improving the teaching of real-world software practices by means of course integration"

 

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Image coordinates data of AprilTag's four edges

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The high-precision and long-distance extraction and construction of vehicle trajectory data and microscopic traffic flow characteristics are critical for traffic safety studies. Current research typically relies on a limited number of datasets which suffer from vehicle detection inaccuracy and limitation of the coverage area. Therefore, we establish a high-precision and long-distance vehicle trajectory dataset of urban scenarios.

Last Updated On: 
Wed, 11/30/2022 - 10:46

The extraction and construction of high-precision and long-distance vehicle trajectory data and microscopic traffic flow characteristics are critical for traffic safety studies. Current research typically relies on a limited number of datasets which suffer from vehicle detection inaccuracy and limitation of the coverage area. Therefore, we establish a high-precision and long-distance vehicle trajectory dataset of urban scenarios, which is also named as WUT-NGSIM.

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The data of the AC report are collected from the website JUCHAO(http://www.cninfo.com) through the crawler process of Python.

The text feature data is obtained by computing AC reports with the machine learning and text analysis methods of Python.

The data includes 1349 firms from 2014-2019, with 6987 observations.

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