Answer: a) Subjective measure of fairness
Explanation:
Subjective measure in terms of fairness is defined as the parameter which is observed and experienced by a person and then stated based on its partiality or impartiality.
According to the question, fairness according to Joe and Paulette's experience is being measured in their marriage. Paulette thinks that has fair relationship whereas Joe thinks the relation is unfair because of division of relationship areas such as housework, decision making etc.This depicts the fairness is being measured through subjective measure.
Other options are incorrect because objective measure is used for measuring a work performed by person. Power in personal and conjugal terms is not displayed .Thus, the correct option is option (a).
Answer: B. amount paid for owned shares
For example, if each share costs $2, and you bought 30 of them, then this means you paid 2*30 = 60 dollars total. If the corporation goes bankrupt, then the most you lose is that 60 dollars.
Your gonna need to look this up on wiki or ask , .com
>.< hope this helps!
Markerless motion capture and understanding of professional non-daily human movements is an important yet unsolved task, which suffers from complex motion patterns and severe self-occlusion, especially for the monocular setting. In this paper, we propose SportsCap -- the first approach for simultaneously capturing 3D human motions and understanding fine-grained actions from monocular challenging sports video input.
About SportCaps :
SportsCap proposes a challenging sports dataset called Sports Motion and Recognition Tasks (SMART) dataset, which contains per-frame action labels, manually annotated pose, and action assessment of various challenging sports video clips from professional referees.
Their approaches :
This is especially prevalent in non-daily action classes like fitness and sports domains. This can be mitigated, for example, by annotating domain-specific datasets , but that requires a considerable amount of manual annotation efforts, financial resources, and 3D annotations can only be obtained in controlled conditions. Therefore, we propose to learn domain-specific pose-sensitive representations from unlabeled videos, which can be fine tuned using only a small labeled dataset. ...
Learn more about Monocular 3 D Human :
brainly.com/question/21602764
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