Standards Research Data
This dataset presents collisions between a service robot - Qolo - and pedestrian dummies: male adult Hybrid-III (H3) and child model 3-years-old (Q3). We present a set of collision scenarios for the assessment of pedestrian safety, considering possible impacts at the legs for adult pedestrians, and legs, chest and head for children.
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Each record in the dataset includes 7 fields:
UserID, CurrentChannel, NextChannel, Date, TimeSection, StartTime, Duration.
The meanings of them are respectively as follows,
1. UserID : the number of a user, sorted in descending order by the number of channels he/she has switched during the period of time; [1, 13246].
2. CurrentChannel: the channel ID viewed by the user in the current time section.
3. NextChannel: the channel ID which the user would view in the next time section.
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The data are associated with a submitted journal paper.
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Intracellular organelle networks such as the endoplasmic reticulum (ER) network and the mitochondrial network serve crucial physiological functions. Morphology of these networks plays critical roles in mediating their functions.Accurate image segmentation is required for analyzing morphology of these networks for applications such as disease diagnosis and drug discovery. Deep learning models have shown remarkable advantages in accurate and robust segmentation of these complex network structures.
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Image : Image was made by me for other International Contest (held by some Medical Institute,USA in the year 2021), 'An intuitive of electromagnetic radiation flowing over epithelial tissue'.
This is an open-access page. All content can be freely downloaded after sign-up. This webpage contains datasets and models, which are in support of my Research claim/discovery.
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This dataset contains the data associated with the electrically equivalent model of the IEEE Low Voltage (LV) test feeder for use of the distribution network studies. This dataset is for the letter entitled:" A Reduced Electrically-Equivalent Model of the IEEE European Low Voltage Test Feeder".
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This is a large Chinese taxonomic knowledge base, which is translated from Probase by the neural network.
It has 11,292,493 IsA pairs with an accuracy of 86.6%.
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This is a large Chinese commonsense knowledge base, which is translated from ConceptNet 5.6, with around 2 million triples and an accuracy of 89.6%.
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This dataset is created with the usage of Galvanic Skin Response Sensor and Electrocardiogram sensor of MySignals Healthcare Toolkit. MySignals toolkit consists of the Arduino Uno board and different sensor ports. The sensors were connected to the different ports of the hardware kit which was controlled by Arduino SDK.
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