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Michael David Cvetanovich

from Charlottesville, VA
Age ~62
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Also known as:
Michael D Cvetanovich, Michael David Cvet, Michael D Cvet, Michael D Czetanovich, Michael D Cvetanoich, Michael H, Mic Cvetanovich, Mike Cvetanovich
Phone and address:
1420 Hazel St, Charlottesville, VA 22902
Related to:
Mark Richard Cvet, 60
Connected to:
Cvetan M Cvetanov, 53Gregory L Cvetanovich, 40Nikola M Cvetanovic, 89Robert A Cvetko, 55Ivaylo P Cvetkov, 38Jane L Cvetkovic, 69Misha Cvetkovic, 40Nellya R Cvetkovs, 38Rita Cvetkovich, 72Snezana Cvetkova, 70

Michael Cvetanovich Phones & Addresses

  • 1420 Hazel St, Charlottesville, VA 22902
  • Charlottesvle, VA
  • Monroe, MI
  • Tulsa, OK

Resumes

Resumes

Michael Cvetanovich Photo 1

Independent Technical Contractor & Certified Dell Field Technician

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Position:
Owner at Independent Contractor - Certified Dell Field Technician
Location:
Charlottesville, Virginia Area
Industry:
Electrical/Electronic Manufacturing
Work:
Independent Contractor - Certified Dell Field Technician - Charlottesville, Virginia Area since Jun 2010
Owner
Northrop Grumman Sperry Marine Apr 2008 - Jul 2010
Test Engineer
Northrop Grumman Sperry Marine Dec 2005 - Apr 2008
Sr. Process Planner - Promoted to Manufacturing Engineer
Acoustic Muse 2000 - 2008
Director
EC LINC, INC. (Formerly Electronic Cable & Assemble, Inc) Jul 2003 - Nov 2005
Technical Documentation /Job Estimator
Education:
PVCC 1993 - 1995
A.A.S, Electronics Tulsa Community College 1987 - 1988
Monroe High School 1981
Skills:
Electronics
Testing
Software Documentation
Automation
Labview
Manufacturing
Engineering
Technical Writing
Troubleshooting
Product Development
Test Equipment
AutoCAD
Aerospace
Interests:
Engineering, Science, Inventions, Music,
Michael Cvetanovich Photo 2

Electronic Access Control And Data Analysis With Uva Hrl It Department

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Location:
Chicago, IL
Industry:
Higher Education
Work:
Independent Contractor - Certified Dell Field Technician - Charlottesville, Virginia Area since Jun 2010
Owner
Northrop Grumman Sperry Marine Apr 2008 - Jul 2010
Test Engineer
Northrop Grumman Sperry Marine Dec 2005 - Apr 2008
Sr. Process Planner - Promoted to Manufacturing Engineer
Acoustic Muse 2000 - 2008
Director
EC LINC, INC. (Formerly Electronic Cable & Assemble, Inc) Jul 2003 - Nov 2005
Technical Documentation /Job Estimator
Education:
PVCC 1993 - 1995
A.A.S, Electronics Tulsa Community College 1987 - 1988
Monroe High School 1981
Skills:
Electronics
Testing
Troubleshooting
Technical Writing
Product Development
Engineering
Manufacturing
Project Management
Engineering Management
Software Documentation
Automation
Management
Microsoft Office
Test Equipment
Autocad
Aerospace
Leadership
Program Management
Public Speaking
Labview
Interests:
Engineering
Science
Music
Inventions
Certifications:
Salesforce Trailhead
Salesforce Platform Basics Badge
Salesforce Trailhead Explorer Rank
Microsoft Dat101X: Data Science Orientation
Cs Access System With Action and Response Management
Certified Ipc Trainer For Ipc/Whma-A-620.
Certification For Step 7 Plc Software Development

Publications

Us Patents

System And Method For The Inference Of Activities Of Daily Living And Instrumental Activities Of Daily Living Automatically

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US Patent:
20050234310, Oct 20, 2005
Filed:
Mar 10, 2005
Appl. No.:
11/076604
Inventors:
Majd Alwan - Charlottesville VA, US
Robin Felder - Charlottesville VA, US
Steven Kell - Keswick VA, US
Sarah Wood - Lovingston VA, US
Michael Cvetanovich - Charlottesville VA, US
Beverly Turner - North Garden VA, US
J. Holman - Earlysville VA, US
International Classification:
A61B005/00
A61B005/103
A61B005/117
US Classification:
600300000, 128920000
Abstract:
A method and related system to, among other things, automatically infer answers to all of the ADL questions and the first four questions of the IADL in the home. The inference methods detect the relevant activities unobtrusively, continuously, accurately, objectively, quantifiably and without relying on the patient's own memory (which may be fading due to aging or an existing health condition, such as Traumatic Brain Injury (TBI)) or on a caregiver's subjective report. The methods rely on the judicious placement of a number of sensors in the subject's place of residence, including motion detection sensors in every room, the decomposition of each relevant activity into the sub-tasks involved, identification of additional sensors required to detect the relevant sub-tasks and spatial-temporal conditions between the signals of sensors to formulate the rules that will detect the occurrence of the specific activities of interest. The sensory data logged on a computing device (computer, data logger etc.), date and time stamped, is analyzed using specialist data analysis software tools that check for the applicable task/activity detection rules. The methods are particularly useful for the continued in-home assessment of subjects living alone to evaluate their progress in response to medical intervention drug or physical therapy or decline in abilities that may be the indicator of the onset of disease over time. Measuring the frequency of each activity, the time required to accomplish an activity or a subtask and the number of activities/subtasks performed continuously over time can add extremely valuable quantification extensions to the existing ADL and IADL evaluation instruments, as it will not only reveal important information setting up a baseline for activity levels for each activity, but will also easily allow the detection of any drift from these personalized norms.

System And Method For The Inference Of Activities Of Daily Living And Instrumental Activities Of Daily Living Automatically

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US Patent:
20150080767, Mar 19, 2015
Filed:
Nov 24, 2014
Appl. No.:
14/551882
Inventors:
- Charlottesville VA, US
Robin A. Felder - Charlottesville VA, US
Steven W. Kell - Keswick VA, US
Sarah G. Wood - Lovingston VA, US
Michael Cvetanovich - Charlottesville VA, US
Beverly L. Turner - North Garden VA, US
J. William Holman - Earlysville VA, US
International Classification:
A61B 5/11
A61B 5/20
A61B 5/00
US Classification:
600595, 600300
Abstract:
A method and related system to, among other things, automatically infer answers to all of the ADL questions and the first four questions of the IADL in the home. The inference methods detect the relevant activities unobtrusively, continuously, accurately, objectively, quantifiably and without relying on the patient's own memory (which may be fading due to aging or an existing health condition, such as Traumatic Brain Injury (TBI)) or on a caregiver's subjective report. The methods rely on the judicious placement of a number of sensors in the subject's place of residence, including motion detection sensors in every room, the decomposition of each relevant activity into the sub-tasks involved, identification of additional sensors required to detect the relevant sub-tasks and spatial-temporal conditions between the signals of sensors to formulate the rules that will detect the occurrence of the specific activities of interest.
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Michael David Cvetanovich from Charlottesville, VA, age ~62 Get Report