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Opportunity++ is a precisely annotated dataset designed to support AI and machine learning research focused on the multimodal perception and learning of human activities (e.g. short actions, gestures, modes of locomotion, higher-level behavior).

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The growth of the need for quantum computers in many domains such as machine learning, numerical scientific simulation and finance has necessitated that quantum computers produce stable results. However, mitigating the impact of the noise inside each quantum device presents an immediate challenge. In this paper, we investigate the temporal behavior of noisy intermediate-scale quantum (NISQ) computers based on calibration data and the characteristics of individual devices.

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The UBFC-Phys dataset is a public multimodal dataset dedicated to psychophysiological studies. 56 participants followed a three-step experience where they lived social stress through a rest task T1, a speech task T2 and an arithmetic task T3. During the experience, the participants were filmed and were wearing a wristband that measured their Blood Volume Pulse (BVP) and ElectroDermal Activity (EDA) signals. Before the experience started and once it finished, the participants filled a form allowing to compute their self-reported anxiety scores.

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