National Technology & Engineering Solutions of Sandia, LLC

Andrew T Wilson

Mark Daniel Rintoul

Judith Maria Lavin

Michael Joseph Haass

Christopher G Valicka

Yongkun Sui

Alfred J Thibodeaux

A method for direct write printing of an electrical or optical element based upon a generated master actual position map and a master expected position map is disclosed. The generated master actual position map is generated by efficiently stitching together a number of images using a hierarchical stitching process. Once the desired location of the electrical or optical element is determined by comparing the master actual position map with the master expected position map, a corresponding toolpath for a direct write printer is generated. The direct write printer then direct write prints the electrical or optical element using the generated toolpath. By using different types of inks, the electrical element may be a trace, a resistor, an inductor, a transformer, a capacitor, or some combination thereof. In like manner, the optical element may be a waveguide, a beam-splitter, a phase shifter, an optical attenuator, an interferometer, or some combination thereof.

Part position recognition for printing electrical or optical interconnects

Described herein are various technologies pertaining to extracting one or more features from trajectory data recorded during motion of a body, and further, generating a n-dimensional feature vector based upon the one or more extracted features. The n-dimensional feature vector enables expedited analysis of the trajectory data from which the feature vector was generated. For example, rather than having to analyze a trajectory curve comprising a large number of time-position data points, the n-dimensional feature vector can be compared with one or more search parameters to facilitate clustering of the trajectory data associated with the n-dimensional feature vector with other trajectory data which also satisfies the search request. The trajectory data can be plotted on a screen in combination with the n-dimensional feature vector, and other pertinent information. The trajectory data, etc., can be displayed using heat maps or other graphical representation.

Trajectory prediction via a feature vector approach

Trajectory analysis with geometric features

Described herein are various technologies pertaining to analysis of eye tracking data. A head and/or eyes of an observer who is viewing a visual stimulus is monitored, and eye tracking data that is representative of the path of the eyes of the observer over time (a scanpath) is generated. The eye tracking data is time-series data that defines the location of the focal point, or other measurable characteristics, of the eyes of the observer on the visual stimulus over time. A feature vector is constructed based upon the eye tracking data, where the feature vector is representative of the eye tracking data, and is thus representative of the scanpath. The feature vector is compared with other feature vectors to identify scanpaths that correspond to the scanpath represented by the feature vector.

Analysis and categorization of eye tracking data describing scanpaths

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Albuquerque, NM, United States of America

Andrew T Wilson