Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Neuro-symbolic is not enough, we need neuro-*semantic*
Borchardt.poole.majerowicz
1. National Aeronautics and Space Administration
NASA Scheduling:
The Path Forward
NASA PM Challenge 2011
Long Beach California
February 9-10, 2011
Heidemarie Borchardt, PMP NASA Independent Program Assessment Office
Ken Poole, NASA Marshall Space Flight Center
Walt Majerowicz, MBA, PMP ASRC Aerospace Corporation
Used with permission
2. Purpose of Today’s Presentation
The purpose to today’s session is to initiate a dialogue among
NASA project planning & scheduling practitioners and
stakeholders on the challenges and opportunities in the
scheduling discipline at NASA.
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3. Managing Complex Projects
“NASA program and project managers face a variety of
challenges associated with risks introduced by fiscal
constraints, schedule demands, and changing priorities.
To meet these challenges, NASA program and project
managers must adhere to the fundamentals of program
and project management, fully implement acquisition
strategies that share risks and rewards with contractors,
and effectively use earned value management systems to
help Agency managers identify and mitigate risks.”
“Key Issues and Challenges Facing NASA”
Statement of The Honorable Paul K. Martin
Inspector General, National Aeronautics and Space Administration
February 3, 2010
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4. Agenda
• NASA Planning & Scheduling Community of Practice
• Scheduling Resources
• Hot Topics in NASA Project Scheduling
• Continuous Improvement in NASA Scheduling
• Moving Forward
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5. NASA Planning & Scheduling Community of Practice
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6. NASA Planning & Scheduling Community of Practice
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7. NASA Planning & Scheduling Community of Practice
• Instructions for joining the P&S CoP are at:
– http://pmknowledge.gsfc.nasa.gov/docs/PSCoP_Instructions.pdf
• For P&S CoP technical assistance contact:
– Jennifer Poston
– Jennifer.L.Poston@nasa.gov
– (301) 286-7492
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9. NASA Schedule Management Handbook
Chapters
1. Introduction
2. Schedule Management Overview
3. Schedule Management Tool
Considerations
4. Pre-schedule Development
5. Integrated Master Schedule
Development
6. Status Updates & Schedule
Maintenance
7. Schedule Assessments and Analysis
8. Schedule Control
9. Schedule Reporting
10. Schedule Data Archival & Lessons
Learned
Download the NASA Schedule Management Handbook at: http://evm.nasa.gov/handbooks.html
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10. NASA Schedule Test And Assessment Tool (STAT)
CS40 Schedule Health Check
Overall Project Health Status Indicator
Project Name: Project XYZ IMS 1.19a.mpp 2.1 Y 1.35 R
Schedule Status Check for Improvements
Description Current Previous Change (C-P)
Current Start (Note: earliest activity Early Start Date) 4/5/2006 4/5/2006
Current Finish (Note: latest activity Early Finish Date) 7/27/2009 7/5/2009 22 0%
Approximate Remaining Work Days 684 668 16 2%
Is this schedule externally linked to other schedules? N N
Status Date 10/31/2006 8/30/2006 63
Task and Milestone Count (Note: These counts exclude summary tasks) Is the Status Date Current?
Description Count % of Total Count % of Total Change (C-P)
Total Tasks and Milestones 3057 3021 36
Completed Tasks and Milestones 501 16% 387 13% 114 4%
To Go Tasks and Milestones 2556 84% 2634 87% -78 -4%
Logic (Note: These counts exclude summary and started/completed tasks) Missing Interdependencies & Number of Constraints
Tasks and Milestones Without Predecessors 170 7% Y 290 11% R 120 -4%
Tasks and Milestones Without Successors 393 15% R 425 16% R 32 -1%
Constraints (Note: other than ASAP including deadlines) 235 9% G 403 15% R 168 -6%
Summaries with Logic Ties (see note below) 5 0% G 8 0% G 3 0%
Tasks and Milestones Needing Updates Incorrect Status 105 4% Y 235 9% R 130 -5%
Actuals after Status Date 40 2% Y 52 2% Y 12 0%
Tasks marked as Milestones (Note: having a duration of > 0) 0 0% G 3 0% Y 3 0%
Note: The summaries with logic ties number is calculated as a percentage of tasks and milestones.
Additional Schedule Information Additional Key Indicators
Tasks with No Finish Ties 17 1% 25 1%
Recurring Tasks 33 1% 38 1%
Tasks and Milestones with Estimated Duration 1 0% 0 0%
Schedule traceable to WBS (Y/N) Y Y
Realistic Critical Path(s) (Y/N) N N
Schedule Baselined Tasks 2783 91% 2569 85%
Resource Loaded (Y/N) Partially N
Tasks and Milestones with 10 days or less Total Float 724 28% 1533 58% -809 -30%
Tasks with Total Float > 25% of remaining duration 793 31% 910 35% -117 -4%
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11. NASA Schedule Test And Assessment Tool (STAT)
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13. Schedule Training from the NASA Academy of
Program, Project and Engineering Leadership (APPEL)
• Understanding Project Scheduling (1 day)
• Beyond Scheduling Basics: Analysis, Control & Margin Planning (1 day)
• Advanced Earned Value Management Topics: Recognizing EVM and
Scheduling Gaming, Abuse and Data Manipulation (1 day)
• Assessing Project Performance (2 days)
• Training schedule http://pmknowledge.gsfc.nasa.gov/scheduletrain.htm
• Additional schedule tool and process training is also available at most
NASA centers – check with your HR training representative or Satern
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14. Hot Topics in NASA Project Scheduling
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15. Hot Topics in NASA Project Scheduling
• Integrated Master Schedule – Are we really integrated?
• Critical Path – It’s not just a methodology!
• Schedule Margin – Do you have it when you when you need it?
• Activity Constraints – They are not logical!
• Schedule Risk Analysis – This is risky business!
• Resource Loading – Show me the money!
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16. Integrated Master Schedule (IMS)
• The IMS is “an integrated schedule developed by logically
networking all detailed project activities.” NASA Schedule
Management Handbook, 2010.
• IMS is built from the project Work Breakdown Structure, and
captures the scope and known project risks. Time phased plan
allowing for capturing Earned Value Management data.
• Schedule hierarchy: the Master Schedule supported by
intermediate level schedules and by detail-level schedules. If the
IMS is correctly coded, master schedule, system-level, and
subsystem-level schedules can be generated from one database.
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17. Schedule Hierarchy
Integrated Master Schedule (IMS)
INTEGRATED MASTER SCHEDULE (IMS)
Master Schedule
Integration
Vertical
Intermediate Schedule
I
Detailed Schedules
(Work Package Planning)
Network Logic Included Horizontal
Integration
122
•Code the schedule so that the Master Schedule can
easily be extracted from the IMS
•IMS Critical Path
NASA Schedule Management Handbook
NASA/SP-2010-3403, January 2010
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18. Critical Path
• Critical Path: “the sequence of schedule activities that
determines the duration of the project. It is the longest path
through the project.” PMBOK Guide 4th Edition
• There is a difference between the critical path and critical
activities.
• To analyze the critical path, the schedule must have one start and
one finish activity. All other activities, except potential
receivables and deliverables from external sources, must have a
predecessor or successor. Additionally, the schedule should have
minimal constraints.
• Filter for the lowest slack value in the schedule and organize the
data by date. This will help determine the critical path.
• It is important to monitor the top critical paths as paths can
change as the schedule is updated.
• Manage the critical path.
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20. Schedule Margin
• Project Schedule Margin should be inserted into the IMS at strategic
locations so that it satisfies its intended purpose as an overall risk buffer
for project completion. To ensure this, it is recommended that the
largest margin task be inserted at the end of the IMS logic flow, just prior
to hardware delivery or project completion. Other suggested locations
might include prior to PDR, CDR, I&T Complete, ORR, etc.
• Schedule Margin is not the same as schedule Slack. Total Slack is the
available time already included in the project duration based on the
existing task interdependencies. Schedule Margin is a separately planned
quantity of time over and above the planned project duration inserted
into the IMS to reduce the impact of missing overall schedule objectives.
• Schedule Margin is owned by the Project Manager and must be visible and
controlled.
• No known scope is associated with the Schedule Margin task, so no budget
can be assigned. Therefore, an adequate amount of Management Reserve
dollars must be held by the project to cover the cost of Schedule Margin.
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21. Schedule Margin
• The preferred technique for including schedule margin in the IMS is to insert
additional tasks that are specifically identified as “Schedule Margin.” These tasks
should have durations assigned that provide the additional quantity of time deemed
necessary to absorb the impacts of Project Schedule Margin should be inserted into
the IMS at strategic locations so that it satisfies its intended purpose as overall risk
buffer for project completion. To ensure this, it is recommended that the largest
margin task be inserted at the end of the IMS logic flow, just prior to hardware
delivery or project completion. Other suggested locations might include prior to
PDR, CDR, I&T Complete, ORR, etc. (NASA, 2010, p. 45)
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22. Activity Constraints
• An activity constraint “is a fixed date assigned to a task to control
when it starts or finishes”. NASA Schedule Management
Handbook, 2010
– “SNET” can be used for receivables
• Constraints, other than ASAP, will override schedule logic so they
should not be used unless absolutely necessary.
• Consider using resource calendars for facilities.
• Constraints will impact slack calculations and limit the
determination of the critical path.
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23. Schedule with FNLT Constraint
Logic ignored
due to FNLT
constraint
With the MS Project setting “Tasks will always honor their constraints” applied. A “Finish
No Later Than” date of 9/16 has been incorporated for Task 5. Note both forward and
backward pass was affected for the task, and the relationship between Task 1 and Task
5 was Ignored. This is the definition of a hard constraint. Because of the change in
logic, the new forecasted early finish of the project has been advanced to 9/23, but it is
artificial. (Note: a “Must Finish On” would have the same impact).
The longest path above has been manipulated and reflects misleading schedule data.
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24. Logic vs. Constraints
By adding the task, “CDR Preparation” as a successor to all of the subsystem CDRs,
the use of a constraint has been avoided and logic reflects work being done on the project.
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25. Resource Loading
• Assigning resources to a task is called resource loading. Resources
are people (workforce), facilities (equipment), and materials
(consumables).
• Develop a resource pool. Identify all the resources that are
required for the project.
• Determine how many resources are required for a specific task and
then assign them to the schedule tasks.
• Activity durations are affected by resource skill levels.
• Focus on high-risk items and critical path tasks first. Managing
resources is key to completing the project as scheduled.
• Program Analyst and Scheduler need to work together to ensure
that there is consistency in resource planning and management.
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26. Schedule Risk Analysis
• Review schedule and assign duration uncertainty values as
appropriate.
• Monitor schedule risks.
• Map risk id to schedule task that is affected by the risk.
• Run simulations
• Determine if mitigation is required (mitigation tasks, additional
resources, use of margin)
• Risk manager and scheduler work together to closely monitor risks
and schedule impacts.
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27. Risk Analysis Process
Model Project Network* Risk Sensitivity, Cost
Days, Facilities, Parts, People*
WBS
Probability Risk Sensitivity, Schedule
Density
Task 100 Function
Task 101
5 1 3
Likelihood
4 1 4 Task 102
3 1 Task 103
2
Task 104
1 1
1 2 3 4 5 Task 105
Primary Risks
Consequence Planned Launch 9/14/2012
Risk Case Name Mean Difference
Mitigate
Task 106
All Risks 7/8/2013 297
Risk 2 and 7 I&T Failure - Late ISIM 12/31/2012 189
Schedule Map Risks to Risk 2
Risk 7
I&T Failure
Late ISIM
4/3/2013
5/2/2013
96
67
Create Cost & Risk 5 Cryo Cooler 7/2/2013 6
Health Schedule Risk 1 Fail to meet reqt's 7/7/2013 1
Accept
Risk 3 Insufficient Mass Margins 7/7/2013 1
Schedule Risk Analysis Risk 8
Risk 4
Mirror Damage 7/7/2013
TRL for machining mirrors 7/8/2013
1
0
Check Simulation
Risk 6 SS Deployment 7/8/2013 0
Determine
Uncertainty Models
Values Results
• Likelihood of completion
date
• Driver risks
• Findings
• Mitigation
recommendations
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29. Continuous Improvement in NASA Scheduling
NASA Scheduling Requirements: do we need them?
Possibilities ?:
• Documented project schedule management plans
• Total project scope must be included within the IMS – (all WBS
elements)
• Documented schedule baseline and formal control process
• Resource Integration - (resource loading or other approved
integration technique)
• Standard schedule formats
• Complete identification of task/milestone sequence - (open-ends
(danglers) allowed only with approved and documented rationale)
• Document rationale for use of constraints, lags, leads, etc.
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30. Continuous Improvement in NASA Scheduling
GAO Scheduling Best Practices: what do they mean for
NASA?
• Best Practice 1: Capturing all activities
• Best Practice 2: Sequencing all activities
• Best Practice 3: Assigning resources to all activities
• Best Practice 4: Establishing the duration of all activities
• Best Practice 5: Schedule is traceable horizontally and vertically
• Best Practice 6: Establishing the critical path
• Best Practice 7: Reasonable total float
• Best Practice 8: Conducting a schedule risk analysis
• Best Practice 9: Updating the schedule
• Best Practice 10: Creating a Baseline Schedule
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31. Continuous Improvement in NASA Scheduling
Are standard logic templates a possibility in IMS
development for various project efforts that are typical?
For Example:
• Standard logic templates for Individual system and
subsystem developments (ie; structures, Guidance &
Control, software, propulsion, etc.)
• Each template would contain the basic typical tasks and
logic relationships as a starting point, then modify to
project specifics
• Combine completed templates to form project IMS
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32. Continuous Improvement in NASA Scheduling
Would standard Agency scheduling tools and processes
help or hinder NASA project management?
Considerations:
• Multiple scheduling tools and processes are the norm across NASA
centers, programs & projects, and the contractor community
• How much efficiency and accuracy is lost by conversions from one
tool to another when integrating all schedules from responsible
program/project partners?
• How much additional cost is involved in allowing multiple tools
across a program/project?
• How much additional training is required due to the use of
multiple scheduling tools?
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33. Continuous Improvement in NASA Scheduling
NASA Schedule Management Working Group: do we
need one?
Considerations:
• Are we adequately communicating and sharing scheduling
knowledge and information across the Agency?
• Could it be used to enhance consistency in schedule products
and practices across the Agency?
• Could it serve as the owner of all formal schedule guidance
documentation (e.g.; NASA Schedule Management Handbook,
schedule requirements, and pocket guide for scheduling)
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35. Get Involved !
• Fill out the “NASA Scheduling Survey Card” on your chairs and
return them to the Session Coordinator
• Join the NASA P&S Community of Practice
• Any questions?
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36. Thank you !
Heidemarie Borchardt, PMP
Lead Scheduler
NASA Independent Program Assessment Office
Heidemarie.E.Borchardt@nasa.gov
(757) 864-9753
Ken Poole
Senior Project Controls Specialist
NASA Marshall Space Flight Center
Kenneth.W.Poole@nasa.gov
(256) 544-2419
Walt Majerowicz, MBA, PMP
Management Consultant
ASRC Aerospace Corporation
walt.majerowicz@nasa.gov
walt.majerowicz@gmail.com
301-286-5622
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