Deniz Senturk

US Patent:

7676390, Mar 9, 2010

Filed:

Sep 4, 2003

Appl. No.:

10/654738

Inventors:

Deniz Senturk - Niskayuna NY, US
Christina A. LaComb - Schenectady NY, US
Roger W. Hoerl - Niskayuna NY, US
Snehil Gambhir - Niskayuna NY, US
Peter A. Kalish - Clifton Park NY, US

Assignee:

General Electric Company - Niskayuna NY

International Classification:

G06Q 90/00

US Classification:

705 7, 705 10

Abstract:

Electrical data processing techniques are described for performing business analysis based on datasets that are incomplete (e. g. , contain censored data) and/or based on datasets that are derived from a stage-based business operation. A first technique offsets the effects of error caused by the incomplete dataset by performing a trending operation followed by a de-trending operation. A second technique provides a model containing multiple sub-models, where the output of one sub-model serves as the input to another sub-model in recursive fashion. A third technique determines when a specified event is likely to occur with respect to a given asset by first discriminating whether the event is very unlikely to occur; if the asset does not meet this initial test, it is further processed by a second sub-model, which determines the probability that the specified event will occur for each of a specified series of time intervals.

US Patent:

7729964, Jun 1, 2010

Filed:

Dec 27, 2004

Appl. No.:

11/022402

Inventors:

Deniz Senturk - Niskayuna NY, US
Murat Doganaksoy - Niskayuna NY, US
Christina Ann LaComb - Schenectady NY, US
Bethany Kniffin Hoogs - Niskayuna NY, US
Radu Eugen Neagu - Schenectady NY, US

Assignee:

General Electric Company - Niskayuna NY

International Classification:

G06Q 40/00

US Classification:

705 35, 705 37

Abstract:

A technique for detecting anomalous values in a small set of financial metrics makes use of context data that is determined based upon the characteristics of the target company being evaluated. Context data is selected to represent the historical values of the financial metric for the target company or the simultaneous performance of peer companies. Using the context data, an anomaly score for the financial metric is calculated representing the degree to which the value of the financial metric is an outlier among the context data. This can be done using an exceptional statistical technique. The anomaly score can be used to evaluate the risks associated with business transactions related to the target company.

US Patent:

20040107077, Jun 3, 2004

Filed:

Nov 30, 2002

Appl. No.:

10/307547

Inventors:

Moitreyee Sinha - Clifton Park NY, US
Pratima Rangarajan - Clifton Park NY, US
Martha Gardner - Niskayuna NY, US
Vicki Watkins - Alplaus NY, US
Deniz Senturk - Schenectady NY, US

International Classification:

G06F017/10

US Classification:

703/002000

Abstract:

Statistical models for quantifying and predicting human perception of scratches on automotive components are disclosed. Such models may be created by utilizing quantitative two-step moving scale surveys. Such surveys employ a continuous scale to model human perception and allow response bias and measurement error in survey data to be evaluated. Once survey data is collected, relationships between the visual perception of the scratches and the measurable optical properties associated with the scratches can be determined. Additionally, relationships between the visual perception of the scratches and the actual physical scratch dimensions can be determined. Thereafter, models for predicting the human perception of such scratches can be created therefrom. Since these models predict the results of such surveys, the need for repeatedly collecting survey data is eliminated. These models may also be used for predicting human perception of other items of interest. Furthermore, the two-step moving scale surveys may be used in various kinds of surveys about any items of interest.

US Patent:

20040138933, Jul 15, 2004

Filed:

Apr 18, 2003

Appl. No.:

10/418428

Inventors:

Christina LaComb - Cropseyville NY, US
Amy Aragones - Clifton Park NY, US
Hong Cheng - Niskayuna NY, US
Michael Clark - Glen Ellyn IL, US
Snehil Gambhir - Niskayuna NY, US
Mark Gilder - Clifton Park NY, US
John Interrante - Schenectady NY, US
Christopher Johnson - Clifton Park NY, US
Thomas Repoff - Sprakers NY, US
Deniz Senturk - Schenectady NY, US

International Classification:

G06F017/60

US Classification:

705/007000

Abstract:

A process for developing a model and integrating the model into a business intelligence system includes: (a) defining at least one variable X to serve as an input to the model and at least one output variable Y to serve as an output of the model; (b) assessing whether there is sufficient data of sufficient quality to operate the model in the business intelligence system of the business, and creating a prototype design of the model; (c) further developing the prototype design of the model to produce a final model design, and validating output results provided by the final model design; (d) implementing the final model design to produce an implemented model, and developing an interface that enables a user to interact with the implemented model; and (e) integrating the implemented model and associated interface into the business intelligence system to provide an integrated model, and repetitively monitoring the accuracy of output results provided by the integrated model. A related method and system are also described.

US Patent:

20050125322, Jun 9, 2005

Filed:

Nov 21, 2003

Appl. No.:

10/719953

Inventors:

Christina Ann Lacomb - Schenectady NY, US
Janet Barnett - Pattersonville NY, US
Allen Case - Amsterdam NY, US
Prakash Rao - Niskayuna NY, US
Deniz Senturk - Schenectady NY, US

International Classification:

G06F017/60

US Classification:

705035000, 705001000

Abstract:

System, method and computer product to detect behavioral patterns related to the financial health of a business entity. In this invention, financial data and business data that relate to the business entity is extracted from various data sources. The financial data comprises quantitative financial data and/or qualitative financial data. The business data comprises quantitative business data and/or qualitative business data. The quantitative financial and business data is analyzed using a financial anomaly detection technique to detect the behavioral patterns associated with the business entity.

US Patent:

20060015377, Jan 19, 2006

Filed:

Jul 14, 2004

Appl. No.:

10/890836

Inventors:

Bethany Hoogs - Niskayuna NY, US
Deniz Senturk - Niskayuna NY, US
Christina LaComb - Schenectady NY, US

International Classification:

G06F 9/44

US Classification:

705007000

Abstract:

A method and system for detecting business behavioral patterns related to a business entity is provided. The method comprises determining a model for business behavioral patterns in which the likelihood of a particular business behavioral pattern is associated with the occurrence of a qualitative event and a quantitative metric. The method further comprises extracting a first data set from a first data source and a second data set from a second data source. The first data set represents the occurrence of the qualitative event associated with the business entity. The second data set represents the quantitative metric associated with the business entity. Then a first confidence attribute and a first temporal attribute associated with the qualitative event is determined. Similarly, a second confidence attribute and a second temporal attribute associated with the quantitative metric are determined. Finally, the likelihood of the particular business behavior pattern is evaluated by running the model based on the first data set, the second data set, the first confidence attribute, the first temporal attribute, the second confidence attribute and the second temporal attribute.

US Patent:

6633104, Oct 14, 2003

Filed:

May 31, 2002

Appl. No.:

10/160679

Inventors:

John Erik Hershey - Ballston Lake NY
Brock Estel Osborn - Niskayuna NY
Deniz Senturk - Schenectady NY
Howard Daniel Koontz - Overland Park KS
Brian Joseph McManus - Helendale CA
Edward James Lewandowski - Chardon OH

Assignee:

General Electric Company - Niskayuna NY

International Classification:

H02K 1300

US Classification:

310242, 310239, 310228

Abstract:

An apparatus for estimating DC motor brush wear comprising: a wear element calculator adapted to calculate a plurality of wear elements from at least one environmental variable; a wear element multiplier adapted to multiply the wear elements by respective ones of a plurality of wear coefficients to yield a plurality of weighted wear elements; and a summer adapted to sum the weighted wear elements to yield a brush wear estimate.