Hewlett-Packard Development Company, L.p.

Micro Focus Lcc

General Electric Company

Hewlett Packard Enterprise Development LP

Hewlett-Packard Company

Entit Software LLC

Renato Keshet

Doron Shaked

Ron Maurer

Mani Fischer

Omer Barkol

Alina Maor

Yaniv Sabo

Manish Marwah

Carl Staelin

Ruth Bergman

Pavel Kisilev

Robert E Sobol

Christopher Andrew Whitman

Sagi Schein

Gitit Ruckenstein

Michael Elad

Andreas Tzanetakis

Barak Raz

Boris Oicherman

Hadas Kogan

Michelle Townshend

Constance Anne Rathke

Olga Shain

Ronny Kimmel

Brent James Miller

Reuth Goldstein

George H Forman

Ming C Hao

Stephen Bernard Pollard

Tomas Sander

Pratyusa Kumar Manadhata

William G Horne

Andrew Arthur Hunter

Gregory William Cook

Jonathan Yen

Michal Aharon

Hila Nachlieli

Nelson L Chang

Kevin Smathers

Riddhiman Ghosh

Casey L Miller

Irwin E Sobel

Lior Shapira

Gregory Braverman

Benjamin D Kimbell

Eigil Samset

Sandeep N Bhatt

Michael Hund

Igor Nor

Ayelet Pnueli

Yacov Hel-Or

Avi Levy

Yohanan Sivan

Arun Kumar Paruchuri

Tomasz Jaroslaw Bania

Eyal Hayun

Elina Sokulin

Danny Barash

Avi Schori

Stephen B Pollard

Morad Awad

Gil Elgrably

Mike Krohn

Reuth Vexler

Ron Mauror

Real-time alerts and transmission of selected signal samples is disclosed. One example is a system including a base facility linked to a production station with an alerting system to perform anomaly analysis utilizing an anomaly model. A receiver at the base facility receives, from the production station, a selection of signal samples based on the anomaly analysis, where the received selection is optimized at the production station to be substantially relevant to an update of a statistical model while adhering to a dynamic capacity limitation of the production station. The statistical model is maintained at the base facility and incorporates features related to the production station. A management system at the base facility updates the statistical model based on the received selection, optionally derives an updated anomaly model based on the statistical model, and optionally transmits the updated anomaly model to the production station.

Real-time alerts and transmission of selected signal samples under a dynamic capacity limitation

Systems and methods are provided for presenting aggregate data in response to a natural language user input. In one example, a system includes a display and a computing device coupled to the display and storing instructions executable to receive a natural language user input, process the natural language user input, in response to determining that the user input includes a request to display two different plots of record data specific to the subject, generate, with the virtual assistant, a single graph including the two different plots of record data based on the processed natural language user input, the two different plots of record data plotted from two different record data sets, one or more aspects of the single graph selected based on an overlapping parameter for each of the two different record data sets, and output, to the display, the single graph as part of a communication thread.

Systems and methods for conversational flexible data presentation

In some examples, an alert relating to an issue in a computing arrangement is received. Contextual information is determined for the alert, the determined contextual information comprising spatial and temporal distributions of previous instances of the alert or similar alerts. The contextual information is communicated for use in addressing the issue in the computing arrangement.

Determining contextual information for alerts

In some examples, a plurality of alerts relating to issues in a computing arrangement are received, where the plurality of alerts generated based on events in the computing arrangement. A subset of the plurality of alerts is grouped into a bundle of alerts, the grouping being based on a criterion. The bundle of alerts is communicated to cause processing of the alerts in the bundle of alerts together.

Grouping alerts into bundles of alerts

Example apparatus, systems, and methods for image data processing are disclosed and described. An example system includes an image capturer to facilitate capture of an image. The example system includes a Doppler spectrum recorder to record a Doppler spectrum. The example system includes a study type inferrer to infer a study type associated with the Doppler spectrum by: processing the Doppler spectrum using at least one neural network to generate a first probability distribution among study type classifications; processing the image using the at least one neural network to generate a second probability distribution among the study type classifications; and combining the first probability distribution and the second probability distribution to infer a study type.

Ultrasound Cardiac Doppler study automation

A unified visualization interface is disclosed. One example is a system including an association module, a multicasting module, a data sharing module, and a unified visualization interface. The association module associates an identified event in a first visualization system with a visualization function. The multicasting module stores event data related to the identified event and the associated visualization function in a shared data source, and multicasts the identified event to a second visualization system. The data sharing module associates the event data with characteristics of the first visualization system, and shares, in response to the multicast of the identified event, the shared data source with the second visualization system. The unified visualization interface automatically invokes, without software changes, the second visualization system in response to the multicast of the identified event, the invoking based on the shared data source including the characteristics of the first visualization system.

Automatically invoked unified visualization interface

Interactive detection of system anomalies is disclosed. One example is a system including a data processor, an anomaly processor, and an interaction processor. Input data related to a series of events and telemetry measurements is received by the data processor. The anomaly processor detects presence of a system anomaly in the input data, the system anomaly indicative of a rare situation that is distant from a norm of a distribution based on the series of events and telemetry measurements. The interaction processor is communicatively linked to the anomaly processor and to an interactive graphical user interface. The interaction processor displays, via the interactive graphical user interface, an output data stream based on the presence of the system anomaly, receives, from the interactive graphical user interface, feedback data associated with the output data stream, and provides the feedback data to the anomaly processor for operations analytics based on the feedback data.

Interactive detection of system anomalies

Examples disclosed herein relate, among other things, to a method. The method may obtain a time series comprising a plurality of data points associated with a sub-segment of a segment, obtaining a plurality of weights associated with a plurality of data point pairs from the plurality of data points, and based on the plurality of weights and the plurality of data point pairs, determine whether the time series comprises a trend. Based on a determination that the time series comprises a trend, the method may calculate a trend score for the trend based on at least one characteristic of at least one of the segment and the sub-segment, and provide the trend for display.

Time series trends

The present disclosure provides a method, system and non-transient computer readable medium for evaluating system behaviour by deriving a statistical distance between each entity in a multi-entity system, and summing the statistical distance to each other entity to create a ranked abnormality score for each entity in the system.

Evaluating system behaviour

In some examples, a plurality of multi-dimensional data samples representing respective behaviors of entities in a computing environment are sorted, where the sorting is based on values of dimensions of each respective multi-dimensional data sample. For a given multi-dimensional data sample, a subset of the plurality of multi-dimensional data samples is selected based on the sorting. An anomaly indication is computed for the given multi-dimensional data sample based on applying a function on the multi-dimensional data samples in the subset. It is determined whether the given multi-dimensional data sample represents an anomalous entity in the computing environment based on the computed anomaly indication.

Multi-dimensional data samples representing anomalous entities

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

The present approach relates to extracting a heart cycle signal from ultrasound sequences (e.g., echocardiograms) without complex spatial image processing and without finding or assuming the knowledge of the position of heart reference points. The present heart cycle signal is computed by determining temporal changes in low-resolution versions of the echocardiographic frames, such as temporal information of the heartbeat.

Extracting a cardiac-cycle signal from echocardiogram data

The present disclosure relates to an interactive system that manages analytics contexts through a series of analytics interactions. The disclosed interactive system receives a selection of an analytics interaction from a user during an interactive analytics session. Then, the system generates a series of analytics interactions by the user during the interactive analytics session. Each analytics interaction represents an analytics context that comprises an analytics interaction, a result, and a reference analytics context. Moreover, the system manages a plurality of analytics contexts by selecting the reference analytics context from previous analytics interactions, or by navigating to a different analytics context, or by deactivating a user-selected analytics context, and presents to the user the series of analytics interactions with the result corresponding to both the selection of the analytics interaction and the reference analytics context. Each analytics interaction in the series of analytics interactions is selectable by the user.

Manage analytics contexts through a series of analytics interactions via a graphical user interface

Growing community of inventors

Haifa, Israel

Renato Keshet