Brian J Alexander

US Patent:

7810055, Oct 5, 2010

Filed:

Dec 5, 2006

Appl. No.:

11/633962

Inventors:

Brian J. Alexander - Erie CO, US
Jaime D. Lujan - Louisville CO, US

Assignee:

Xilinx, Inc. - San Jose CA

International Classification:

G06F 17/50

US Classification:

716 3, 716 4, 716 17

Abstract:

A method of managing correlation data for a design implementation process can include identifying correlation data from each of a plurality of design applications. Each of the design applications can generate a circuit description and the correlation data can specify associations between circuit elements of different ones of the circuit descriptions. The method also can include storing the circuit descriptions and the correlation data independently of one another and determining a relationship among circuit elements of the circuit descriptions according to the correlation data.

US Patent:

20140188442, Jul 3, 2014

Filed:

Dec 27, 2012

Appl. No.:

13/727901

Inventors:

- Upper Saddle River NJ, US
Andrew J. Sannier - Denver CO, US
Brian Alexander - Greenwood Village CO, US

Assignee:

PEARSON EDUCATION, INC. - Upper Saddle River NJ

International Classification:

G06F 17/50

US Classification:

703 2

Abstract:

Systems and methods may automatically generate institution-specific, program-specific or course-specific student risk assessment models from an arbitrary set of potential risk predictors. Student data from previously completed courses are collected and used to create a design matrix of predictor values and an outcome vector. The system determines the coefficients for the model using an automated predictor selection method, such as lasso logistic regression. The system uses the model with current student data to assess an outcome probability, such as the risk of a current student from failing or dropping a course. In addition to an overall risk assessment model, component models focused on particular components of risk, such as performance, participation, attendance, timeliness, or student profile, can be generated. The component models may be used along with the overall risk assessment model to help explain the reasons behind the risk assessment.