Tarun K Kumar

US Patent:

7835891, Nov 16, 2010

Filed:

Mar 13, 2008

Appl. No.:

12/047705

Inventors:

Tarun Kumar - Ossining NY, US
Gyana Ranjan Parija - Briarcliff Manor NY, US
Haifeng Xi - Yorktown Heights NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 17/50
G06F 7/60

US Classification:

703 2

Abstract:

A computer implemented method for determining an alternative representation of an optimization model reduces model input through compact representation of model parameters. Model generation is performed at varying levels of complexity (approximation) depending on pre-defined, business approved thresholds. The computer receives a set of functions representing a set of events where each function includes sets of first and second axis coordinate values. Each of the functions are transformed to a compacted function which includes a set of pieces including an anchor point, break points, and slopes. Successive pieces having the same slope value are removed. Alternate optimization models are generated based on the set of pieces representing a compacted function and on a predetermined accuracy value.

US Patent:

7917380, Mar 29, 2011

Filed:

Mar 28, 2008

Appl. No.:

12/058098

Inventors:

Tarun Kumar - Ossining NY, US
Gyana Ranjan Parija - Haryana, IN
Haifeng Xi - Yorktown Heights NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 9/44

US Classification:

705 7, 705 8

Abstract:

The present invention provides a system and method for strategic budgeting of initial response for managing wildfires. According to the present invention, stochastic-integer-programming-based constrained optimization techniques are employed to develop a strategic budget by optimally allocating disaster management resources to disaster events belonging to scenarios associated with occurrence probabilities. According to the invention, certain machine-readable data describing fires may be subjected to computerized data processing, ultimately producing a determination of valid disaster management resources for each fire event, which may be used for strategic budgeting of initial responses for managing wildfires.

US Patent:

8036921, Oct 11, 2011

Filed:

Sep 16, 2004

Appl. No.:

10/942040

Inventors:

Tarun Kumar - Ossining NY, US
Gyana R. Parija - Poughkeepsie NY, US
Haifeng Xi - Yorktown Heights NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06Q 10/00

US Classification:

705 711

Abstract:

A method (and system) of providing optimization repeatability in an on-demand computing environment removes variability in an optimization model instance and can be exemplarily implemented in a service architecture. The method and system receives a plurality of physical data instances, which are different representations of the same logical data model, and transforms the plurality of physical data instances into a normalized physical data instance, which can be combined with an optimization model to form a unique optimization model instance, thereby providing repeatability in solving optimization problems.

US Patent:

20060161467, Jul 20, 2006

Filed:

Jan 14, 2005

Appl. No.:

11/035931

Inventors:

Tarun Kumar - Ossining NY, US
Gyana Parija - South City-1, IN
Haifeng Xi - Yorktown Heights NY, US

International Classification:

G06F 9/46

US Classification:

705008000

Abstract:

The present invention provides a system and method for strategic budgeting of initial response for managing wildfires. According to the present invention, stochastic-integer-programming-based constrained optimization techniques are employed to develop a strategic budget by optimally allocating disaster management resources to disaster events belonging to scenarios associated with occurrence probabilities. According to the invention, certain machine-readable data describing fires may be subjected to computerized data processing, ultimately producing a determination of valid disaster management resources for each fire event, which may be used for strategic budgeting of initial responses for managing wildfires.

US Patent:

20070162162, Jul 12, 2007

Filed:

Jan 9, 2006

Appl. No.:

11/328023

Inventors:

Tarun Kumar - Ossining NY, US
Gyana Parija - Briarcliff Manor NY, US
Haifeng Xi - Yorktown Heights NY, US

International Classification:

G05B 13/02

US Classification:

700029000

Abstract:

A method for determining an alternative representation of an optimization model reduces model input through compact representation of model parameters. Model generation is performed at varying levels of complexity (approximation) depending on pre-defined, business approved thresholds.

US Patent:

20210006469, Jan 7, 2021

Filed:

Sep 14, 2020

Appl. No.:

17/020794

Inventors:

- Valhalla NY, US
Harsh Chaudhary - Ossining NY, US
Yakup Koç - Delft, NL
Younghun Kim - White Plains NY, US
Tarun Kumar - Mohegan Lake NY, US
Abhishek Raman - Mahopac NY, US

International Classification:

H04L 12/24
H04L 12/707

Abstract:

A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.

US Patent:

20200387119, Dec 10, 2020

Filed:

Mar 10, 2020

Appl. No.:

16/814388

Inventors:

- Valhalla NY, US
Younghun Kim - White Plains NY, US
Tarun Kumar - Mohegan Lake NY, US
Abhishek Raman - Santa Clara CA, US
Rui Zhang - Ossining NY, US

Assignee:

Utopus Insights, Inc. - Valhalla NY

International Classification:

G05B 13/02
G01F 22/02
H04L 12/26
H04L 29/08
G01M 3/28
G05D 7/06

Abstract:

Technical solutions are described for predicting linepack delays. An example method includes receiving temporal sensor measurements of a first fluid-delivery pipeline network and generating a causality graph of the first fluid-delivery pipeline network. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies a temporal delay between a pair of stations. The method also includes generating a temporal delay prediction model based on the topological network and predicting the linepack delays of a second fluid-delivery pipeline network based on the temporal delay prediction model, where a compressor station of the second fluid-delivery pipeline network compresses fluid based on the predicted linepack delays to maintain a predetermined pressure.

US Patent:

20200210854, Jul 2, 2020

Filed:

Dec 27, 2018

Appl. No.:

16/234465

Inventors:

- Valhalla NY, US
Younghun Kim - Pleasantville NY, US
Tarun Kumar - Chappaqua NY, US

Assignee:

Utopus Insights, Inc. - Valhalla NY

International Classification:

G06N 5/02
G06N 20/00
G06N 3/08

Abstract:

An example method comprises receiving historical sensor data of a first time period, the historical data including sensor data of a renewable energy asset, extracting features, performing a unsupervised anomaly detection technique on the historical sensor data to generate first labels associated with the historical sensor data, performing at least one dimensionality reduction technique to generate second labels, combining the first labels and the second labels to generate combined labels, generating one or more models based on supervised machine learning and the combined labels, receiving current sensor data of a second time period, the current sensor data including sensor data of the renewable energy asset, extracting features, applying the one or more models to the extracted features of the current sensor data to create a prediction of a future fault in the renewable energy asset, and generating a report including the prediction of the future fault in the energy asset.