822 resultados para distance-metrics


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Our aim in this study was to compare intermolar widths after alignment of crowded mandibular dental arches in nonextraction adolescent patients between conventional and self-ligating brackets.

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The occupant impact velocity (OIV) and acceleration severity index (ASI) are competing measures of crash severity used to assess occupant injury risk in full-scale crash tests involving roadside safety hardware, e.g. guardrail. Delta-V, or the maximum change in vehicle velocity, is the traditional metric of crash severity for real world crashes. This study compares the ability of the OIV, ASI, and delta-V to discriminate between serious and non-serious occupant injury in real world frontal collisions. Vehicle kinematics data from event data recorders (EDRs) were matched with detailed occupant injury information for 180 real world crashes. Cumulative probability of injury risk curves were generated using binary logistic regression for belted and unbelted data subsets. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV and ASI were found to offer no significant predictive advantage over the simpler delta-V.

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Purpose – The purpose of the present analysis is to show that HR systems are not always designed in ways that consider the well-being of employees. In particular, performance metric methods seem to be designed with organizational goals in mind while focusing less on what employees need and desire. Design/methodology/approach – A literature review and multiple case-study method was utilized. Findings – The analysis showed that performance metrics should be revaluated by executives and HR professionals if they seek to develop socially responsible organizational cultures which care about the well-being of employees. Originality/value – The paper exposes the fact that performance appraisal techniques can be rooted in methodologies that ignore or deemphasize the value of employee well-being. The analysis provides a context in which all HR practices can be questioned in relation to meeting the standards of a social justice agenda in the area of corporate social responsibility.

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The task considered in this paper is performance evaluation of region segmentation algorithms in the ground-truth-based paradigm. Given a machine segmentation and a ground-truth segmentation, performance measures are needed. We propose to consider the image segmentation problem as one of data clustering and, as a consequence, to use measures for comparing clusterings developed in statistics and machine learning. By doing so, we obtain a variety of performance measures which have not been used before in image processing. In particular, some of these measures have the highly desired property of being a metric. Experimental results are reported on both synthetic and real data to validate the measures and compare them with others.