Standards Research Data
*This datasheet is being updated progressively to provide more details.
This datasheet provides the phasor measurement data in actual power systems.
These PMU data were recorded during a Low Frequency Oscillation incident and a Short Circuit Incident, respectively.
These PMU data are used for the studies in wide-area control systems (WACS) and PMU data compressions.
Please cite this datasheet and the papers in your work if they help.
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The PRIME-FP20 dataset is established for development and evaluation of retinal vessel segmentation algorithms in ultra-widefield (UWF) fundus photography (FP). PRIME-FP20 provides 15 high-resolution UWF FP images acquired using the Optos 200Tx camera (Optos plc, Dunfermline, United Kingdom), the corresponding labeled binary vessel maps, and the corresponding binary masks for the valid data region for the images. For each UWF FP image, a concurrently captured UWF fluorescein angiography (FA) is also included.
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Several pathological phenomena are closely associated with mechanical properties of vessel and interactions of blood flow–wall dynamics. However, conventional techniques cannot easily measure these features. In this study, new deep learning-based simultaneous measurement of flow–wall dynamics (DL-SFW) is proposed by devising integrated neural network for super-resolved localization and vessel wall segmentation and combining with tissue motion measurement technique and flow velocimetry.
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Each voice sample is stored as a .WAV file, which is then pre-processed for acoustic analysis using the specan function from the WarbleR R package. Specan measures 22 acoustic parameters on acoustic signals for which the start and end times are provided.
The output from the pre-processed WAV files were saved into a CSV file, containing 3168 rows and 21 columns (20 columns for each feature and one label column for the classification of male or female).
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This is an example of clustering to replicate OpenNym experiments
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An ontology for the multidisciplinary phenomenon of creating web application ove encrypted data
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Nodes represent personality facets (a description of each facet is provided in Table 3), green lines represent positive connections and red lines represent negative connections. Thicker lines represent stronger connections and thinner lines represent weaker connections. The node placement of all graphs is based on the adaptive LASSO network to facilitate comparison. The width and color are scaled to the strongest edge and are not comparable between graphs; edge strengths in the correlation network are generally stronger than edge strengths in the partial correlation network.
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We develop a general group-based continuous-time Markov epidemic model (GgroupEM) framework for any compartmental epidemic model (e.g., susceptible-infected-susceptible, susceptible-infected-recovered, susceptible-exposed-infected-recovered). Here, a group consists of a collection of individual nodes of a network. This model can be used to understand the critical dynamic characteristics of a stochastic epidemic spreading over large complex networks while being informative about the state of groups.
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This is a file containing the codes for IEEE paper
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