Ellett
Benjamin Ellett, Kirkland, WA US
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20110298819 | HARDWARE-ACCELERATED COLOR DATA PROCESSING - Methods for mapping color data having at least one color associated therewith to an output device based on an input-device profile and an output-device profile, each profile having a tone curve and a color matrix, are provided. In one embodiment, the method includes receiving color data from an input device and determining whether the color data is in a linear space. If it is determined that the color data is not in a linear space, the method further includes applying the tone curve of the input device profile to the color data to convert it into a linear space. The method further includes converting the color(s) associated with the color data from the input linear space to an output linear space by applying the color matrix of the input device profile and the inverse color matrix of the output device profile to create color-converted image data. | 12-08-2011 |
Eric Ellett, Chevy Chase, MD US
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20150341379 | NETWORK ANOMALY DETECTION - Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining network related anomaly scores. One of the methods includes generating a network map including at least a plurality of network nodes and a plurality of edges that indicate communications paths between the plurality of network nodes, obtaining first data indicating network activity over the edges and between the plurality of network nodes for a first time period, generating a model of expected network activity over the edges and between the plurality of network nodes for a future time period using the network map and the first data, obtaining second data indicating network activity over the edges and between the plurality of network nodes for a second time period, and determining an anomaly score using a comparison between the second data and the model of expected network activity. | 11-26-2015 |
Eric A. Ellett, Chevy Chase, MD US
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20140283048 | DATA TREND ANALYSIS - According to an example, a method for data trend analysis may include retrieving data from data sources, associating the data with a time, and identifying co-occurrences of terms and concepts within the data. In response to determining that co-occurrences of term and concept pairs reach a predefined threshold, the method may include adding the term and concept pairs to an ontology. The method may include logging occurrences of terms in the ontology within the data with respect to associated data times, identifying a plurality of time periods, and for one of the plurality of time periods and for the logged terms, determining a first score indicative of a weighted term frequency metric for a logged term within the data during the one time period, and determining a second score indicative of a commonality of a presence of the logged term within the data among the plurality of time periods. | 09-18-2014 |