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Integration of Graphical, Physics-Based, and Machine Learning Methods for Assessment of Impact and Recovery of The Built Environment from Wind Hazards
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Copyright Title

Integration of Graphical, Physics-Based, and Machine Learning Methods for Assessment of Impact and Recovery of The Built Environment from Wind Hazards

Status

Published

on 7 Nov 2019
Year of Creation
2019
Registration Number
TX0008810965
on 7 Nov 2019

Copyright Summary


The U.S. Copyright record (Registration Number: TX0008810965) dated 7 Nov 2019, pertains to an electronic file (eService) titled "Integration of Graphical, Physics-Based, and Machine Learning Methods for Assessment of Impact and Recovery of The Built Environment from Wind Hazards" created in 2019. The copyright holder is Stephanie Frances Pilkington, known for their creative contributions in text registration. For any inquiries concerning this copyrighted material, kindly reach out to Stephanie Frances Pilkington.

Copyright Details


Application Details


Registration Number
TX0008810965
Registration Date
11/7/2019
Year of Creation
2019
Agency Marc Code
DLC-CO
Record Status
New
Physical Description
Electronic file (eService)
First Publication Nation
United States

Notes


Rights Note: Mark Dill, ProQuest, LLC, 789 E. Eisenhower Parkway, Ann Arbor, MI, 48108-3218, United States, (800) 521-0600, disspub@proquest.com

Statements


Application Title Statement: Integration of Graphical, Physics-Based, and Machine Learning Methods for Assessment of Impact and Recovery of The Built Environment from Wind Hazards
Author Statement: Stephanie Frances Pilkington Citizenship: not known Authorship: text
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