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Mark Barglof Phones & Addresses

  • 2807 165Th Ave, Burt, IA 50522 (515) 924-3302
  • Urbandale, IA
  • Altoona, IA
  • Marion, IA
  • 94-213 Lumiaina St, Waipahu, HI 96797 (808) 671-0844
  • Ames, IA
  • Bennett, IA
  • Dallas, IA
  • 94-213 Lumiaina Pl #UNITC104, Waipahu, HI 96797 (808) 671-0844

Work

Position: Food Preparation and Serving Related Occupations

Education

Degree: Bachelor's degree or higher

Resumes

Resumes

Mark Barglof Photo 1

Senior Engineering Manager

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Location:
Burt, IA
Industry:
Electrical/Electronic Manufacturing
Work:
Raven Industries
Senior Engineering Manager

Smart Ag
Co-Founder and Chief Technology Officer

Ag Leader Technology Jul 1, 2015 - Jun 2017
Manager of Software Engineering

Ag Leader Technology Sep 2012 - Jul 2015
Engineering Manager, Ag Leader Displays

John Deere Aug 2011 - Sep 2012
Development Lead
Education:
Iowa State University 2012 - 2015
Master of Science, Masters, Agronomy
Iowa State University
Bachelors, Bachelor of Science, Mechanical Engineering
Skills:
Product Development
Program Management
Engineering Management
Cross Functional Team Leadership
Engineering
Leadership
Management
Systems Engineering
Agile Methodologies
Testing
Dod
Embedded Software
Continuous Improvement
Six Sigma
Project Planning
Process Improvement
Automation
Embedded Systems
Product Management
Scrum
Agile Leadership
Electrical Engineering
Certified Scrum Master Csm
Simulations
Integration
Ms Project
U.s. Department of Defense
Fmea
Root Cause Analysis
Mark Barglof Photo 2

Mark Barglof

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Skills:
Engineering
Mark Barglof Photo 3

Mark Barglof

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Publications

Us Patents

Multi-Dwell Channel Monitoring For Coordinated Frequency Hopped Systems

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US Patent:
8077597, Dec 13, 2011
Filed:
Mar 6, 2008
Appl. No.:
12/074800
Inventors:
Robert J. Frank - Cedar Rapids IA, US
Richard L. Robertson - Cedar Rapids IA, US
Carlos J. Chavez - Marion IA, US
Mark W. Barglof - Marion IA, US
Assignee:
Rockwell Collins, Inc. - Cedar Rapids IA
International Classification:
H04J 11/00
H04B 7/216
US Classification:
370208, 370342, 375132
Abstract:
Spectral environment estimation systems and methods are provided for use with frequency hopped communications systems. A spectral sensor is configured to receive input signals from a signal aperture and to perform spectral estimations on the input signals to generate a frequency domain spectral estimate. Ordinary spectral characterization circuitry is configured to receive the frequency domain spectral estimate as an input and to produce an ordinary frequency domain spectral environment estimate based on the spectral estimate. Frequency hopping translation circuitry is configured to receive the frequency domain spectral estimate from the spectral sensor as an input and to produce a de-hopped channel domain spectral estimate based on the frequency domain spectral estimate. De-hopped spectral characterization circuitry is configured to receive the de-hopped channel domain spectral estimate as an input and to produce a de-hopped channel domain spectral environment estimate based on the de-hopped spectral estimate. Spectral environment integration circuitry is configured to generate an integrated spectral environment estimate, based on the ordinary frequency domain spectral environment estimate and the de-hopped channel domain spectral environment estimate, for use by networked communications systems or devices in controlling frequency hopped communications.

Network Enabled Survival Terminal

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US Patent:
7667620, Feb 23, 2010
Filed:
Feb 2, 2007
Appl. No.:
11/701666
Inventors:
Mark W. Barglof - Marion IA, US
Richard L. Robertson - Cedar Rapids IA, US
Gunther B. Frank - Robins IA, US
Assignee:
Rockwell Collins, Inc. - Cedar Rapids IA
International Classification:
G08B 21/00
US Classification:
340945, 340963, 701 9, 701213
Abstract:
In some embodiments, a search and rescue communication may include one or more of the following features: (a) a rescue terminal, (b) a main terminal operably connected to said rescue terminal across a communication network, said main terminal sends an emergency notification message across said communication network to said rescue terminal, and (c) a survival terminal associated with an ejection seat, said survival terminal being in communication with said main terminal, wherein said emergency notification message is delivered by said main terminal when said ejection seat is ejected.

Safety System For Autonomous Operation Of Off-Road And Agricultural Vehicles Using Machine Learning For Detection And Identification Of Obstacles

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US Patent:
20200326715, Oct 15, 2020
Filed:
Jan 10, 2020
Appl. No.:
16/740109
Inventors:
- Sioux Falls SD, US
Rahul Ramakrishnan - Ames IA, US
Mark William Barglof - Burt IA, US
Quincy Calvin Milloy - Ames IA, US
Thomas Antony - Ames IA, US
International Classification:
G05D 1/02
G05D 1/00
B60W 10/20
B60W 10/18
B60W 10/04
B60W 10/10
G06K 9/00
G06K 9/62
G06N 20/00
Abstract:
A framework for safely operating autonomous machinery, such as vehicles and other heavy equipment, in an in-field or off-road environment, includes detecting, identifying, classifying and tracking objects and/or terrain characteristics from on-board sensors that capture images in front and around the autonomous machinery as it performs agricultural or other activities. The framework generates commands for navigational control of the autonomous machinery in response to perceived objects and terrain impacting safe operation. The framework processes image data and range data in multiple fields of view around the autonomous equipment to discern objects and terrain, and applies artificial intelligence techniques in one or more neural networks to accurately interpret this data for enabling such safe operation.

Integrated Platform And Common Software Structural Architecture For Autonomous Agricultural Vehicle And Machinery Operation

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US Patent:
20200159220, May 21, 2020
Filed:
Nov 15, 2019
Appl. No.:
16/685994
Inventors:
- Sioux Falls SD, US
MARK WILLIAM BARGLOF - BURT IA, US
QUINCY CALVIN MILLOY - AMES IA, US
International Classification:
G05D 1/00
G06Q 10/04
G06Q 50/02
G06N 5/02
G05D 1/02
A01B 79/00
A01B 69/04
H04W 4/40
H04Q 9/02
Abstract:
An integrated technology platform includes multiple hardware and software components that enable any application of autonomous agricultural equipment operation in an agricultural or other off-road setting, within a common software structural architecture. The integrated technology platform represents a technology stack that is a modular architecture that can be leveraged across multiple use cases and vehicle types. The integrated technology platform includes a vehicle interface component responsible for the physical interface to agricultural equipment, a telematics component that enables stable in-field communications between all aspects of the integrated technology platform, and a perception component that operates as a safety mechanism and includes object detection and classification. Additionally, a cloud-side application performs account management and field setup and as well as syncing of field equipment and operating systems in a common operating system. The integrated technology platform also includes an executive control layer that enables rapid porting from one platform to another, so that software applications in the integrated technology platform can work with hardware of any manufacture.

Safety System For Autonomous Operation Of Off-Road And Agricultural Vehicles Using Machine Learning For Detection And Identification Of Obstacles

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US Patent:
20190146511, May 16, 2019
Filed:
Nov 12, 2018
Appl. No.:
16/188114
Inventors:
- Ames IA, US
RAHUL RAMAKRISHNAN - AMES IA, US
MARK WILLIAM BARGLOF - BURT IA, US
QUINCY CALVIN MILLOY - AMES IA, US
THOMAS ANTONY - AMES IA, US
International Classification:
G05D 1/02
G06N 99/00
G05D 1/00
B60W 10/20
B60W 10/18
B60W 10/04
B60W 10/10
G06K 9/00
G06K 9/62
Abstract:
A framework for safely operating autonomous machinery, such as vehicles and other heavy equipment, in an in-field or off-road environment, includes detecting, identifying, classifying and tracking objects and/or terrain characteristics from on-board sensors that capture images in front and around the autonomous machinery as it performs agricultural or other activities. The framework generates commands for navigational control of the autonomous machinery in response to perceived objects and terrain impacting safe operation. The framework processes image data and range data in multiple fields of view around the autonomous equipment to discern objects and terrain, and applies artificial intelligence techniques in one or more neural networks to accurately interpret this data for enabling such safe operation.
Mark William Barglof from Burt, IA, age ~46 Get Report