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Defect prediction models can be developed using software metrics in combination with defect data for predicting defective classes.
Life cycle assessment (LCA) offers a framework for inclusion of global environmental "systems-level" decision metrics in combination with technological and cost analysis.
The device performance metrics in combination show significant improvement compared to the state-of-the-art in the sense that lower phase shifter loss and higher bandwidth are achieved for the same Vπ or vice versa.
For this purpose, besides providing visual examples of encrypted imagery, we use objective image quality metrics in combination with a public image database to assess the visual security of encrypted images and we rate the extent of control an encryption scheme provides to generate various levels of content protection.
We employ local as well as global performance metrics in combination with an ensemble approach.
The use of supplementary metrics in combination with the HPO measurement tool will increase the reliability of the output of the internal PO assessment.
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These findings show that an integrated analysis of the two stressor-specific SPEAR-metrics in combination with the metrics of general ecological degradation can help water managers to distinguish between the effects of habitat degradation and pesticide stress, two co-occurring stressors in agricultural landscapes.
The complementary analysis in one single software environment allows for mapping structural damage (DTI metrics differences) in combination to detection of tract connections (DTI-based FT reconstructions) with functional alterations (hyper- or hypoconnectivity) of the corresponding networks.
These two metrics are used in combination to determine the network state which is either congested or not, and how to regulate the data transmission.
To the best of our knowledge, this is the first in vivo study where MRI-derived and immunological metrics have been investigated in combination to readdress these aims.
This was achieved by calculating the vector output (i.e. 165 values per subject) of the most influential metric in the combination of metrics with the highest classification accuracy.
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