Unsupervised Learning
To download this dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13896353
Please cite the following paper when using this dataset:
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To download the dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13738598
Please cite the following paper when using this dataset:
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This dataset contains simulation values from thermo-mechanical finite element analysis simulations using ABAQUS. Each simulation is one of 192 unique process parameter settings which includes varying laser power, scan speed, layer height and cooling assumptions. The geometry for each simulation is a hollow rectangluar box with rounded corners such that they form semi-circles. The wall thickness of each simulation is exactly the width of the focused laser.
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A commonly used definition of spatial disorientation (SD) in aviation is "an erroneous sense of one’s position and motion relative to the plane of the earth’s surface". There exists a wide range of SD use-cases dictated by situational factors, therefore SD has been predominantly studied using reduced motion detection experimental contexts in isolation. The study of SD by use-case makes it difficult to understand general SD occurrence and thus provide viable solutions. To investigate SD in a generalized manner, a two-part Human Activity Recognition (HAR) study was performed.
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