Abstract: A bundle of roofing shingles, including at least four rows of roofing shingles, where the at least four rows of roofing shingles includes a first roofing shingle row, a second roofing shingle row, a third roofing shingle row, and a fourth roofing shingle row, where the first roofing shingle row includes a first roofing shingle having a first length; and where the second roofing shingle row includes: a second roofing shingle having a second length, and a third roofing shingle having a third length, where the second roofing shingle is adjacent the third roofing shingle, where the second length is greater than the third length, and where the second row is located above the first row.

Abstract: A pathway identification system includes processor and memory hardware. The memory hardware stores a pathway database including pathways corresponding to at least one pathway parameter, a framework database including a set of framework transformation models, and instructions. The instructions include, in response to receiving a first pathway parameter corresponding to a user, identifying a subset of pathways of the pathways corresponding to the first pathway parameter. The instructions include obtaining a first set of framework transformation models from the framework database, determining a pathway value for each pathway of the subset of pathways using the first set of framework transformation models, and selecting at least one pathway of the subset of pathways based on the corresponding pathway value. The instructions include transmitting information encoding the at least one pathway to the operator device and transforming a user interface of the operator device to display the at least one pathway.

Abstract: A system and method for determining if a first image and a second image are correlated images includes partitioning a first image and a second image into a plurality of corresponding pixel partitions, calculating an average luminance value for each of the plurality of pixel partitions, determining if each of the plurality of pixel partitions of the first image is correlated with each of the corresponding plurality of pixel partitions of the second image, calculating a percentage of correlated pixel partitions of the first image and the corresponding plurality of pixel partitions of the second image and determining that the first image and the second image are correlated images if the percentage of correlated pixel partitions exceeds a predetermined pixel partition correlation threshold. The objective metric of the present invention determines whether two static rendered images are correlated enough to be undetectable by a human observer.

Abstract: A system and method for determining if a first image and a second image are correlated images includes partitioning a first image and a second image into a plurality of corresponding pixel partitions, calculating an average luminance value for each of the plurality of pixel partitions, determining if each of the plurality of pixel partitions of the first image is correlated with each of the corresponding plurality of pixel partitions of the second image, calculating a percentage of correlated pixel partitions of the first image and the corresponding plurality of pixel partitions of the second image and determining that the first image and the second image are correlated images if the percentage of correlated pixel partitions exceeds a predetermined pixel partition correlation threshold. The objective metric of the present invention determines whether two static rendered images are correlated enough to be undetectable by a human observer.

Abstract: The present invention provides a quantitative, automated system and method for assessing the correlation level of two rendered images, thereby removing subjectivity from such evaluation. The objective metric of the present invention determines whether two static images are correlated enough to be undetectable by a human observer. The performance of this method is optimized based upon the capabilities and limitations of the human visual system. Therefore, the resulting assessments are not overly sensitive and reduce the resources required to assess rendered images within a networked simulation environment. Additionally, the simplicity of the method lends itself to implementation within existing and emerging simulation systems with relatively little effort compared to current assessment methods. The system and method of the present invention provide benefits to multiple organizations, such as those engaged in human-in-the-loop simulators, distributed learning, and training applications.