Hewlett-packard Development Company, L.p.

Hewlett Packard Enterprise Development LP

Hewlett-packard Company

Hitachi, Ltd.

Entit Software LLC

Micro Focus Lcc

Umeshwar Dayal

Ming C Hao

Meichun Hsu

Daniel Keim

Qiming Chen

Chetan Kumar Gupta

Ming-Chien Shan

Maria G Castellanos

Fabio Casati

Harumi Kuno

William Kevin Wilkinson

Halldor Janetzko

Christian Rohrdantz

Manish Marwah

Halldór Janetzko

Ratnesh Kumar Sharma

Bin Zhang

Alkiviadis Simitsis

Abhay Mehta

Janet Lynn Wiener

Martha Lurie Lyons

Ravigopal Vennelakanti

Sebastian Mittelstaedt

Daniel A Keim

Stefan Krompass

Markus H Gross

Alex Xin Zhang

Riddhiman Ghosh

Song Wang

Mehmet Oguz Sayal

Mohamed E Dekhil

Adrian Krug

Parvathi Chundi

Anshuman Sahu

Thomas Holenstein

Peter J Wright

Lars-Erik Haug

Cullen Edwin Bash

Vijay Machiraju

Michael Hund

Pankaj K Garg

Soma Sundaram Santhiveeran

Klaus Wurster

Daniel Cotting

Dominik Morent

Julian Ladisch

Walter Hill

Nimesh Patel

Tobias Schreck

Sabastian Mittelstadt

Chandrakant D Patel

Surajit J Chaudhuri

Alan Hersh Karp

Goetz Graefe

Keith Farkas

Amit Kumar

Hiroshi Yoshikawa

Craig Peter Sayers

Archana Sulochana Ganapathi

Jerry Zhaolin Shan

Krishnamurthy Viswanathan

Weimin Du

Masami Yamasaki

Cheng Chang

Nina Mishra

Ismail Ari

Robert Lovejoy Raymond

Elke Angelika Rundensteiner

Mustazirul Islam

Yue Lu

Marie-Jo Fremont

Iwao Tanuma

Mark S Anspach

Prasun Singh

Lyle H Ramshaw

Bao-Yao Zhou

Hong Su

Jie Deng

Li-Jie Jin

Shouchun Peng

Abbay Mehta

Miguel Durazo

Chandrakat Patel

Chantal Tremblay

Patrick A Autilio

Joem Schneidewind

Ivo Jimenez

Toblas Schreck

Stephany Kalil

Betty Cant

Eric Stammers

Lakshminarayn Choudur

Brian Ono

Pramod Singh

Sabastian Mittelstädt

Tak W Yan

David V Dodd

Rafi Ahmed

Sebastian Mittelstädt

Mark B Misroch

A method for sharing and analyzing information to support execution of multi-party workflows in an electrification ecosystem. The method may include creating or updating shared data schema and data governance rules associated with data to be received from a plurality of parties, wherein the plurality of parties are stakeholders to the multi-party workflows, and the data is associated with a battery system; submitting the shared data schema and the data governance rules for approval to the plurality of parties; creating or updating decision logics associated with the data to be received; submitting the decision logics for approval to the plurality of parties; receiving the data from the plurality of parties; and applying the approved shared data schema, the approved data governance rules, and the approved decision logics to the multi-party workflows and the received data from the plurality of parties to perform automated decision optimization.

Multi-party business collaboration platform for electrification ecosystems

Disclosed herein are techniques for optimizing and managing the execution of hybrid flows. An execution plan is generated for each hybrid flow based at least partially on attributes associated therewith. The execution of each hybrid flow is managed in accordance with the execution plan.

Optimizing and managing execution of hybrid flows

Example implementations disclosed herein are directed to monitoring communications networks in real time to ensure that they are performing in a desired fashion. Metrics such as utilization and latency are monitored to ensure that customer SLAs (Service Level Agreements) are met in a timely fashion. To detect problems in advance, example implementations predict the future values of metrics and detect events if the future value violates certain conditions. Example implementations build models that can predict the future values of metrics and analyze historical, near real time and real time streaming data so as to build predictive models.

Performance monitoring at edge of communication networks using hybrid multi-granular computation with learning feedback

Systems and methods are directed to oil and gas management. In example implementations, data relating to oil and gas management is aggregated and placed in a cube along several cube dimensions, which can include scalar, temporal and spatial dimensions. The dimensions can be structured as a hierarchy, such that output can be generated as a roll up or roll down along the hierarchy.

Automatic method of generating decision cubes from cross dependent data sets

A pattern of geocoded pixels is generated by accessing data point values, where each data point value includes an attribute value and coordinates of a geographic location. Each data point value corresponds to a geocoded pixel that is positioned on the pattern based on the coordinates of the data point value such some geocoded pixels overlap other geocoded pixels. Different levels of the pattern of geocoded pixels correspond to a different degree of overlap between the geocoded pixels. The different levels of the pattern of geocoded pixels are associated with different magnification levels of a geographic map such that changing a magnification level of the geographic map causes a degree of overlap between the geocoded pixels of the pattern to change.

Map with different degrees of overlapping geocoded pixels

Provided is a production amount prediction system including: a storage unit which stores a production amount prediction model which is based on resources information including a resources amount obtained in a previously drilled wellbore and a resources recovery probability in the vicinity thereof; an input unit which receives a trajectory coordinate of a planned wellbore as an input; a production amount prediction unit which calculates a production amount of the planned wellbore based on the production amount prediction model by using a degree of influence of the previous wellbore on the planned wellbore as at least one parameter; and a display unit which displays the production amount of resources of the planned wellbore calculated by the production amount prediction unit.

System for predicting amount of production and method for predicting amount of production

A management server is coupled to a plurality of rig systems by a network, each of the rig systems having a plurality of sensors, a rig and a rig node. The management server stores data received from at least one of the plurality of rig systems, the data including values associated with one or more attributes of the rig. The management server derives a model signature for at least one phase from a timeline for at least one rig system based on analytics of information stored in the database and the data, where the model signature includes a set of attributes for the at least one of the plurality of rig systems. In addition, the management server generates a recommendation including one or more actions for planning rig system management operations corresponding to at least one attribute of the set of attributes.

Oil and gas rig data aggregation and modeling system

A data processing system includes a query progress analyzer. The database processing system comprises a receiver that receives database queries including a target query directed to a database and a query analyzer. The query analyzer is coupled to the receiver and analyzes progress status of the target query based on comparison of measured target query resource usage to resource usage predicted from a query plan of the target query and measured system resource usage.

Progress analyzer for database queries

One embodiment is a method to manage queries in a database. The method identifies a query that executes on the database for an elapsed time that is greater than a threshold and then implements a remedial action when the query executes on the database for an execution time that is greater than an estimated execution time.

Managing execution of database queries

Non-overlapping visualization of data records of a scatter plot is provided by providing rows and columns in a visualization screen containing cells representing respective data records. The rows correspond to value ranges of a first attribute, and the columns correspond to value ranges of a second attribute. The value ranges are automatically generated for the rows and columns from data values of the data records.

Non-overlapping visualization of data records of a scatter plot

An event occurring in a particular geographic region is identified based on disseminated information containing public commentary in the particular geographic region. Attributes that are related to the event are identified, and sentiment words relating to the identified event are extracted from the disseminated information, where the extracted sentiment words are in a local language of the particular geographic region. A sentiment trend visualization is generated that depicts a trend of sentiments of at least a particular one of the identified attributes, wherein the sentiments are based on the sentiment words for at least the particular attribute.

Sentiment trent visualization relating to an event occuring in a particular geographic region

Using a contingency calculation based on a number of events sharing a collection of values of plural attributes, a discriminative metric is computed representing a statistical significance of the events that share the collection of values of the plural attributes. A visualization is generated that includes cells representing respective events, the visualization including a region containing a subset of the cells corresponding to the collection of values of the plural attributes, and the visualization including a significance visual indicator associated with the region to indicate the statistical significance of the events sharing the collection of values of the plural attributes.

Visualization that indicates event significance represented by a discriminative metric computed using a contingency calculation

Color cell-based data placement systems, methods, and computer-readable storage media that visualize large amounts of multidimensional data on an output by rearranging data objects to variably grant more output space to areas with high data density and less output space to areas with low data density, and to variably rearrange overlapping data objects based on a number of data objects already placed at a preferred cell position for the data object.

Generalized scatter plots

A method of processing a stream of raw data from a plurality of distributed data producing devices includes reducing the raw data to a plurality of representative synopsis coefficients, organizing the synopsis coefficients into a data structure with at least three dimensions, including a time window dimension and an accuracy dimension. Responsive to a detected anomaly in the data structure, at least one of a predetermined autonomous action and an action directed by a user is performed.

Data stream processing

Example embodiments relate to providing visual analytics of spatial time series data. In example embodiments, sensors may be located at regions within a building for collecting sensor data at regular time intervals. A sensor hierarchy can be generated including sensor nodes that are hierarchically arranged according to a physical infrastructure of the building, where each of the sensor nodes corresponds to a sensor. Sensor data can be obtained from the sensors, and a pixel calendar tree can be generated based on the sensor data and the sensor hierarchy, where the pixel calendar tree is recursively subdivided into tree portions according to a proportion of the sensor data attributable to each of the sensors. The pixel calendar tree can be displayed, where each of the tree portions includes time series sensor data of a corresponding region that is generated based on the sensor data.

Visual analytics of spatial time series data using a pixel calendar tree

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Saratoga, CA, United States of America

Umeshwar Dayal