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Christopher R Rosati, 4241467 Fremont Blvd, Fremont, CA 94538

Christopher Rosati Phones & Addresses

41467 Fremont Blvd, Fremont, CA 94538   

106 Fairfax Ct, Centerville, GA 31028    478-9531272   

6004 Susan Cir, Valdosta, GA 31605    229-2421649   

Moody AFB, GA   

Plainfield, CT   

Danielson, CT   

Mentions for Christopher R Rosati

Career records & work history

License Records

Christopher Rosati

Licenses:
License #: 009204 - Expired
Category: WELDER
Issued Date: Sep 4, 2009
Expiration Date: Aug 31, 2010

Christopher Richard Rosati

Address:
41467 Fremont Blvd, Fremont, CA 94538
Licenses:
License #: A4794266
Category: Airmen

Christopher Rosati resumes & CV records

Resumes

Christopher Rosati Photo 31

Enroute Air Traffic Controller

Location:
Danville, CA
Industry:
Aviation & Aerospace
Work:
Faa
Enroute Air Traffic Controller
United States Air Force Sep 2001 - Sep 2007
Flying Crew Chief
Education:
Embry - Riddle Aeronautical University 2007 - 2010
Bachelors, Bachelor of Science
Skills:
Aviation, Aircraft, Aerospace, Flights, Flight Safety, Commercial Aviation, Airports, Airlines, Aircraft Maintenance, Avionics, Civil Aviation, Airworthiness, Military, Systems Engineering, Aeronautics
Christopher Rosati Photo 32

Christopher Rosati

Publications & IP owners

Us Patents

Methods And Systems For Using Sound Data To Analyze Health Condition And Welfare States In Collections Of Farm Animals

US Patent:
2021028, Sep 23, 2021
Filed:
Jun 3, 2021
Appl. No.:
17/337750
Inventors:
- Peachtree Corners GA, US
Joseph Marcel Sarzen - Sandy Springs GA, US
Christopher G. Rosati - Duluth GA, US
International Classification:
A01K 29/00
G10L 25/66
G06N 20/00
G06N 5/04
Abstract:
Systems and methods are described for selecting a sound type of interest from a first (e.g., master/global) machine learning library comprising information derived from reference audio stream data acquired from a plurality of farm animal operation reference sound monitoring events, including from a first farm animal operation monitoring event of a first farm animal operation, wherein the sound type of interest is associated with a condition state of interest of a first collection of farm animals. Further, information associated with the selected sound type of interest can be included a second machine learning library, wherein the second machine learning library is operational on an edge computing device located in proximity to a second farm animal operation. Audio stream data can be acquired from the second farm animal operation in a second farm animal operation monitoring event, and processed using the second machine learning library information to determine whether the sound type of interest is present in the acquired audio stream data, thereby generating information associated with the presence or absence of the condition during the second farm animal operation monitoring event.

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