Peter P. Bleznyk - Roswell GA, US John Steven Engelmann - Roswell GA, US Hossein Eslambolchi - Los Altos Hills CA, US Charles C. Giddens - Conyers GA, US David H. Lu - Morganville NJ, US Kenneth James Smith - Dacula GA, US Anthony M. Srdar - Alpharetta GA, US Harold Jeffrey Stewart - Alpharetta GA, US John Vincent Wilson - Conyers GA, US
Assignee:
AT&T Corp. - New York NY
International Classification:
G08B019/00
US Classification:
340521, 340506, 340524, 370216
Abstract:
In accordance with the teachings of the present invention, a method is presented for displaying power and heat faults that occur in a network. A server initiates a variety of power alarm display methods. Each method is directed at receiving specific types of power alarm information and displaying or inhibiting the display of this information on a wallboard. The methods operate simultaneously and update the wallboard with power alarm information in near real time. Further, the methods continue to operate and update the display of the power alarm information when tickets associated with the alarms are received or when an operator acknowledges the alarm.
Application Of Statistical Inference To Optical Time Domain Reflectometer Data
Michael Asher - Conyers GA, US Hossein Eslambolchi - Los Altos Hills CA, US Chuck Giddens - Conyers GA, US John Sinclair Huffman - Conyers GA, US Harold Stewart - Alpharetta GA, US
Assignee:
AT&T Corp. - New York NY
International Classification:
G01N 21/00
US Classification:
356 731
Abstract:
The present invention relates to method for interpreting data obtained by measuring a length of optical fiber using an optical time domain reflectometer (OTDR), and comparing that measurement to a reference measurement. The technique uses statistical inference to determine a likely cause for a length measurement to be shorter than a reference length. One technique uses a chi-squared best fit of an array reflectance spike occurrences along the fiber to a historical reference array. In that way, it can be determined whether the missing portion of the tested fiber is at an end or between the ends, providing evidence that the short length measurement results from a fiber break or from the intentional removal of a reserve loop.
Application Of Statistical Inference To Optical Time Domain Reflectometer Data
Michael Asher - Conyers GA, US Hossein Eslambolchi - Los Altos Hills CA, US Chuck Giddens - Conyers GA, US John Sinclair Huffman - Conyers GA, US Harold Stewart - Alpharetta GA, US
International Classification:
G01N 21/00
US Classification:
356 731
Abstract:
The present invention relates to method for interpreting data obtained by measuring a length of optical fiber using an optical time domain reflectometer (OTDR), and comparing that measurement to a reference measurement. The technique uses statistical inference to determine a likely cause for a length measurement to be shorter than a reference length. One technique uses a chi-squared best fit of an array reflectance spike occurrences along the fiber to a historical reference array. In that way, it can be determined whether the missing portion of the tested fiber is at an end or between the ends, providing evidence that the short length measurement results from a fiber break or from the intentional removal of a reserve loop.
Application Of Statistical Inference To Optical Time Domain Reflectometer Data
Michael Asher - Conyers GA, US Hossein Eslambolchi - Los Altos Hills CA, US Chuck Giddens - Conyers GA, US John Sinclair Huffman - Conyers GA, US Harold Stewart - Alpharetta GA, US
Assignee:
AT&T Corp. - New York NY
International Classification:
G01N 21/00
US Classification:
356 731
Abstract:
The present invention relates to a method for interpreting data obtained by measuring a length of optical fiber using an optical time domain reflectometer (OTDR), and comparing that measurement to a reference measurement. The technique uses statistical inference to determine a whether a reference trace is valid by comparing that trace to a more recent test trace. One technique uses a chi-squared best fit of an array reflectance spike occurrences along the fiber to a historical reference array.
Application Of Statistical Inference To Optical Time Domain Reflectometer Data
Michael Asher - Conyers GA, US Hossein Eslambolchi - Los Altos Hills CA, US Chuck Giddens - Conyers GA, US John Sinclair Huffman - Conyers GA, US Harold Stewart - Alpharetta GA, US
Assignee:
AT&T Corp. - New York NY
International Classification:
G01N 21/00
US Classification:
356 731
Abstract:
The present invention relates to a method for interpreting data obtained by measuring a length of optical fiber using an optical time domain reflectometer (OTDR), and comparing that measurement to a reference measurement. The technique uses statistical inference to determine a whether a reference trace is valid by comparing that trace to a more recent test trace. The reference trace may be replaced or an alarm may be transmitted under certain conditions.
Application Of Statistical Inference To Optical Time Domain Reflectometer Data
Michael Asher - Conyers GA, US Hossein Eslambolchi - Los Altos Hills CA, US Chuck Giddens - Conyers GA, US John Sinclair Huffman - Conyers GA, US Harold Stewart - Alpharetta GA, US
Assignee:
AT&T Corp - New York NY
International Classification:
G01N 21/00
US Classification:
356 731
Abstract:
The present invention relates to a method for interpreting data obtained by measuring a length of optical fiber using an optical time domain reflectometer (OTDR), and comparing that measurement to a reference measurement. The technique uses statistical inference to determine a whether a reference trace is valid by comparing that trace to a more recent test trace. The reference trace may be replaced or an alarm may be transmitted under certain conditions.
Michael L. Asher - Green Grove Springs FL, US Charles C. Giddens - Conyers GA, US Harold Jeffrey Stewart - Alpharetta GA, US
Assignee:
AT&T Corp. - New York NY
International Classification:
G06F 12/16
US Classification:
713164, 726 22
Abstract:
For each process a stack data structure that includes two stacks, which are joined at their bases, is created. The two stacks include a normal stack, which grows downward, and an inverse stack, which grows upward. Items on the stack data structure are segregated into protected and unprotected classes. Protected items include frame pointers and return addresses, which are stored on the normal stack. Unprotected items are function parameters and local variables. The unprotected items are stored on the inverse stack.
Michael L. Asher - Green Grove Springs FL, US Charles C. Giddens - Conyers GA, US Harold Jeffrey Stewart - Alpharetta GA, US
Assignee:
AT&T Intellectual Property II, LP - Atlanta GA
International Classification:
G06F 12/16
US Classification:
713164, 726 22
Abstract:
For each process a stack data structure that includes two stacks, which are joined at their bases, is created. The two stacks include a normal stack, which grows downward, and an inverse stack, which grows upward. Items on the stack data structure are segregated into protected and unprotected classes. Protected items include frame pointers and return addresses, which are stored on the normal stack. Unprotected items are function parameters and local variables. The unprotected items are stored on the inverse stack.
Harman/Becker Automotive Systems Jun 2012 - Feb 2013
Area Manager
Ingersoll Rand Feb 2006 - Jun 2012
Manufacturing Supervisor
Ingersoll Rand Mar 2004 - Feb 2006
Warehouse/Supply Chain Supervisor
Jewel Construction Jun 2001 - Mar 2004
Project Manager
Delphi Automotive Systems Jan 2000 - Jun 2001
Maintenance - EHS Manager
Education:
Indiana Wesleyan University 1998 - 2000
MBA, Business Administration
Illinois State University
BS, Industrial Technology
Ncr Corporation
Customer Engineer Ii
Cigna
Data Network Support Technician
Cvs Pharmacy Jun 2016 - Dec 2016
Customer Service Associate
Jcpenney Oct 2011 - Dec 2016
Customer Service Specialist
Ctdi Oct 2011 - Dec 2016
Order Picker
Education:
Savannah State University 2009 - 2016
Bachelors, Computer Science
Cedar Grove High School 2009
Skills:
Data Center Infrastructure Microsoft Office Microsoft Excel Training Powerpoint Customer Service Leadership Microsoft Word Team Leadership Data Entry
Interests:
Any New Technology Children German Shepard Dogs Fashion Education Science and Technology Exercising Arts and Culture Health
Group Health Everett Medical Center 2930 Maple St, Everett, WA 98201 4252611500 (phone), 4252611815 (fax)
Education:
Medical School University of Oklahoma College of Medicine at Oklahoma City Graduated: 1974
Languages:
English Russian Spanish
Description:
Dr. Stewart graduated from the University of Oklahoma College of Medicine at Oklahoma City in 1974. He works in Everett, WA and specializes in Occupational Medicine. Dr. Stewart is affiliated with Providence Regional Medical Center Everett.