Pipeline Inspection using Microwave Nondestructive Testing

A Master of Science thesis in Electrical Engineering by Ahmad Ghattas entitled, “Pipeline Inspection using Microwave Nondestructive Testing”, submitted in January 2025. Thesis advisor is Dr. Nasser Qaddoumi and thesis co-advisor is Dr. Amer Zakaria. Soft copy is available (Thesis, Completion Certifi...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Ghattas, Ahmad (author)
التنسيق: doctoralThesis
منشور في: 2025
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/11073/26140
الوسوم: إضافة وسم
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author Ghattas, Ahmad
author_facet Ghattas, Ahmad
author_role author
dc.contributor.none.fl_str_mv Qaddoumi, Nasser
Zakaria, Amer
dc.creator.none.fl_str_mv Ghattas, Ahmad
dc.date.none.fl_str_mv 2025-06-19T07:07:35Z
2025-06-19T07:07:35Z
2025-01
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2025.02
https://hdl.handle.net/11073/26140
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Pipeline inspection
Ka-band
Microwave non-destructive testing
Artificial neural networks
Machine learning
dc.title.none.fl_str_mv Pipeline Inspection using Microwave Nondestructive Testing
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Electrical Engineering by Ahmad Ghattas entitled, “Pipeline Inspection using Microwave Nondestructive Testing”, submitted in January 2025. Thesis advisor is Dr. Nasser Qaddoumi and thesis co-advisor is Dr. Amer Zakaria. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form)
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identifier_str_mv 35.232-2025.02
language_invalid_str_mv en_US
network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/26140
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling Pipeline Inspection using Microwave Nondestructive TestingGhattas, AhmadPipeline inspectionKa-bandMicrowave non-destructive testingArtificial neural networksMachine learningA Master of Science thesis in Electrical Engineering by Ahmad Ghattas entitled, “Pipeline Inspection using Microwave Nondestructive Testing”, submitted in January 2025. Thesis advisor is Dr. Nasser Qaddoumi and thesis co-advisor is Dr. Amer Zakaria. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form)College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE)Qaddoumi, NasserZakaria, Amer2025-06-19T07:07:35Z2025-06-19T07:07:35Z2025-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2025.02https://hdl.handle.net/11073/26140en_USoai:repository.aus.edu:11073/261402025-06-26T12:23:56Z
spellingShingle Pipeline Inspection using Microwave Nondestructive Testing
Ghattas, Ahmad
Pipeline inspection
Ka-band
Microwave non-destructive testing
Artificial neural networks
Machine learning
status_str publishedVersion
title Pipeline Inspection using Microwave Nondestructive Testing
title_full Pipeline Inspection using Microwave Nondestructive Testing
title_fullStr Pipeline Inspection using Microwave Nondestructive Testing
title_full_unstemmed Pipeline Inspection using Microwave Nondestructive Testing
title_short Pipeline Inspection using Microwave Nondestructive Testing
title_sort Pipeline Inspection using Microwave Nondestructive Testing
topic Pipeline inspection
Ka-band
Microwave non-destructive testing
Artificial neural networks
Machine learning
url https://hdl.handle.net/11073/26140