Hewlett-packard Development Company, L.p.

Micro Focus Lcc

Entit Software LLC

Hewlett-packard Indigo B.v.

Precognize Ltd.

Hila Nachlieli

Doron Shaked

Ruth Bergman

Carl Staelin

Gitit Ruckenstein

George H Forman

Mani Fischer

Sagi Schein

David Lehavi

Jan Philip Allebach

Renato Keshet

Ron Maurer

Pavel Kisilev

Michal Aharon

Michael Plotkin

Shlomo Harush

Darryl Greig

Shaul Haim Raz

Boris Oicherman

Haim Vladomirski

Hadas Kogan

Zachi Karni

Shai Druckman

Smadar Shiffman

Yaniv Yona

Olga Shain

Raanan Manor

Chen Linchevski

Alexander Berkovich

Maya Shalev

Shai Emanueli

Xiaochen Jing

Gabriel Shaar

The present invention discloses methods and systems for improving asset operation based on identification of significant changes in sensor combinations in related events. Methods include the steps of: providing an asset representation of an asset having an alert-aggregation system; creating a calculated indicator listing having at least one calculated indicator in the asset configured to calculate, predict, or estimate an indicated asset behavior; incorporating the calculated indicator listing into a set of entity connections by associating listing elements in the calculated indicator listing, thereby producing the interconnected representation; associating the identified asset behavior with at least one relevant object and/or at least one relevant process that is impairing the asset from optimally performing, conducting, and/or achieving the identified asset behavior; and generating at least one hint associated with at least one relevant object and/or at least one relevant process that is impairing the identified asset behavior.

Methods and systems for improving asset operation based on identification of significant changes in sensor combinations in related events

An example method comprises performing for each class from a plurality of classes: constructing binary training set for the class, the binary training set including labeled cases for that class from the main training set other labeled cases from the main training set; training classifier for the class on the binary training set; computing a local calibration threshold using scores of the labeled cases in the binary training set; and adjusting all scores of the label cases in the binary training set with the local calibration threshold to meet a global decision threshold. The method also comprises determining, with the processor, a global hierarchical calibration threshold by using the adjusted scores for all classes to optimize a performance measurement of all trained classifiers. The method further comprises classifying, with the processor, a new case by using a previously trained classifier, a local calibration threshold, and the global hierarchical calibration threshold.

System and method for hierarchical classification

An example method is provided in according with one implementation of the present disclosure. The method comprises receiving a training dataset of cases, where each of a plurality of classes is associated with a set of labeled cases in the training dataset. The method also comprises defining a proper subset of classes in the training dataset, and training a first classifier model on the proper subset of classes in the training dataset. The method further comprises testing the first classifier model on at least one class in the training dataset that was excluded from the proper subset, and determining a performance measurement of the first classifier model.

Classifier

An example method is provided in according with one implementation of the present disclosure. The method comprises generating a group of most frequent elements in a dataset, calculating features of each of the most frequent elements in the dataset, applying a trained model to the features of each of the most frequent elements, and generating a list of predicted relevant elements from the list of most frequent elements. The method further comprises determining at least one element-chain group for each predicted relevant element and a group score for the element-chain-group, ordering a plurality of element-chain groups for the dataset based on the group score for each of the element-chain groups, and identifying a predetermined number of element-chain groups to be outputted to a user.

Identifying groups

Examples herein involve generating a spiral visualization of items of a dataset. Dimensions of item indicators corresponding to items of a dataset are analyzed. Starting coordinates for a spiral path for a spiral visualization of the items are determined based on the dimensions of the item indicators and a display area of a display device. A spiral path may be calculated based on the starting coordinates and the dimensions of the item indicators. The spiral visualization may be generated by rendering the item indicators on the spiral path to present a first item indicator of the item indicators from a corresponding first item of the list at the starting coordinates and a last item indicator of the item indicators of a corresponding last item on the list on the spiral path toward the center of the spiral.

Spiral visualization generator

In at least some examples, a system comprises a processor and a memory coupled to the processor. The memory stores an image defect visibility predictor that, when executed by the processor, compares an original image with a defect image and outputs a predicted defect visibility image (PDVI) that accounts for defect masking by the original image.

Image defect visibility predictor

A malfunction diagnosis system of a printer is provided. A printer controller receives malfunction-related input by the user from an input device, which user input specifies a print defect perceptible to the user. It generates image data representing a test print job in response to the user input specifying the perceptible print defect, and forwards the test print job image data to the printing unit to produce a corresponding test printout. Measurement data output from a sensing device as measured on the test printout is received and analyzed, and information indicative of a cause for the print defect based on the analyzed measurement data output from the sensing device is output.

Diagnosing printer malfunction from malfunction-related input

A method includes obtaining, by executing a module stored on a non-transitory computer-readable storage device, approximately-zero polynomials for each of multiple classes. The method further includes evaluating the approximately-zero polynomials for each class on a plurality of points to compute distances from each point to each of the classes. The method also includes scaling the approximately-zero polynomials based on the distances and classifying the points based on the scaled approximately-zero polynomials.

Multiclass classification of points

Method and system embodiments of the present invention are directed to automated identification of regions within digitally-encoded images that correspond to objects and features of scenes captured in the digitally-encoded images, a process referred to as 'perceptual segmentation' of an image. Regions or segments within an image are first identified by any of various region-identifying or segmentation methods. For each region or segment, features of pixels within the region or segment are employed to compute one or more segment features. The segment features are used, in turn, to identify the region or segment as belonging to a particular type of region or segment, and the region is then accordingly labeled or tagged as a region or segment of the determined type.

Perceptual segmentation of images

A component of a color printing system, such as lookup tables for converting requested marking-agent coverages to corresponding half-tone screen sizes, is calibrated. The calibration can be effected off an arbitrary image and involves making reflectance spectrum measures of the printed image at multiple locations. Expected reflectance measures for each measurement location are computed based on the requested coverage value for each of the marking agents printed there. The computed measures may be dependent on a parameter. A value of the parameter is determined that minimizes the aggregate differences between the sensed and expected reflectance-spectrum measures, and this value is then used in calibrating the component.

Color printing system calibration

A method for compressing a plurality of coordinates includes obtaining a plurality of approximately-zero polynomials of dimension dim for a plurality of coordinate parameters. The method further includes selecting dim+1 non-approximately-zero polynomials, and providing a compressed data set that includes the approximately-zero polynomials, the dim+1 non-approximately-zero polynomials, and evaluations of the selected dim+1 non-approximately-zero polynomials based on the coordinates.

Coordinate compression using polynomials

Modification of a digital image includes determining a likelihood of a pixel belonging to a memory color region (). The memory color region has a preferred color. The modification further includes shifting original color of the pixel toward the preferred color (). The original color is shifted by an amount that is a function of the likelihood and that is generally less than the difference between the original and preferred colors.

Modification of memory colors in digital images

An apparatus and method detect defects in a captured image of output from a printing device. The captured image is filtered using a source image for the output, wherein specific defects of interest are detected using the filtered image.

Specific print defect detection

Methods, machines, and computer-readable media for processing an input image with a bi-selective filter in a transform domain are described. In one aspect, a forward transform of an input image is computed. A bi-selective filter smoothes image regions with low magnitude coefficients and sharpens image regions with high magnitude coefficients. An output image is generated from the filtered forward transform.

Bi-selective filtering in transform domain

A method, diagnostic tool and system are provided for evaluating printing defects. A captured image of a printed sheet is received and a profile generated of the printed sheet, this profile being representative of tonal variations in the printed sheet. The profile is analyzed in a plurality of different scales and an assessment made of the significance of one or more features of a printing defect throughout the plurality of different scales. From the assessed significance of the one or more features, an evaluation is carried out, in each of the plurality of different scales, of the severity of the printing defect.

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Haifa, Israel

Hila Nachlieli