{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/92861"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/92861","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Radiation source detection from mobile sensor networks using principal component analysis","abstract":"Detecting the presence of possible illicit radioactive materials in large areas is challenging because of changing background radiation, shielding effects and short collection time, especially when the radioactive materials are moving. The concept of mobile sensor networks is put forward to solve this problem. In this thesis, a small mobile sensor network is established using commercially available radiation detectors and cell phones. A spectrum decomposition and reconstruction method based on Principal Component Analysis (PCA) is proposed to work with mobile sensor networks. Two experiments are designed to test this method's performance on real-world data. The PCA-based method's performance is analyzed using receiver operating characteristic, or ROC curves. Further study finds that although the PCA-based method doesn't work well on current mobile sensor networks, its performance can be improved by increasing the radiation spectral quality.","abstract_html":"Detecting the presence of possible illicit radioactive materials in large areas is challenging because of changing background radiation, shielding effects and short collection time, especially when the radioactive materials are moving. The concept of mobile sensor networks is put forward to solve this problem. In this thesis, a small mobile sensor network is established using commercially available radiation detectors and cell phones. A spectrum decomposition and reconstruction method based on Principal Component Analysis (PCA) is proposed to work with mobile sensor networks. Two experiments are designed to test this method's performance on real-world data. The PCA-based method's performance is analyzed using receiver operating characteristic, or ROC curves. Further study finds that although the PCA-based method doesn't work well on current mobile sensor networks, its performance can be improved by increasing the radiation spectral quality.","abstract_has_math":false,"creators":["Zhao, Jifu"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Nuclear, Plasma, Radiolgc Engr","degree_department":null,"school":null,"contributors":["Sullivan, Clair J.","Mohaghegh, Zahra"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-11-10T17:55:16Z","date_published":"2016-11-10T17:55:16Z","updated_at":"2026-07-22T22:26:35Z","subjects":["Radiation detection","mobile sensor networks","principal component analysis"],"languages":["en"],"rights":["Copyright 2016 Jifu Zhao"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/92861","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sullivan, Clair J.","Mohaghegh, Zahra"]},{"key":"dc:creator","label":"Author","values":["Zhao, Jifu"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-11-10T17:55:16Z","2016-07-18","2016-08"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Nuclear, Plasma, Radiolgc Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Radiation detection","mobile sensor networks","principal component analysis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Jifu Zhao"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/92861"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Detecting the presence of possible illicit radioactive materials in large areas is challenging because of changing background radiation, shielding effects and short collection time, especially when the radioactive materials are moving. The concept of mobile sensor networks is put forward to solve this problem. In this thesis, a small mobile sensor network is established using commercially available radiation detectors and cell phones. A spectrum decomposition and reconstruction method based on Principal Component Analysis (PCA) is proposed to work with mobile sensor networks. Two experiments are designed to test this method's performance on real-world data. The PCA-based method's performance is analyzed using receiver operating characteristic, or ROC curves. Further study finds that although the PCA-based method doesn't work well on current mobile sensor networks, its performance can be improved by increasing the radiation spectral quality.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-11-09 without embargo terms","The student, Jifu Zhao, accepted the attached license on 2016-07-18 at 09:17.","The student, Jifu Zhao, submitted this Thesis for approval on 2016-07-18 at 09:31.","This Thesis was approved for publication on 2016-07-18 at 14:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9979 on 2016-11-09 at 10:25:19","Made available in DSpace on 2016-11-10T17:55:16Z (GMT). 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In this thesis, a small mobile sensor network is established using commercially available radiation detectors and cell phones. A spectrum decomposition and reconstruction method based on Principal Component Analysis (PCA) is proposed to work with mobile sensor networks. Two experiments are designed to test this method's performance on real-world data. The PCA-based method's performance is analyzed using receiver operating characteristic, or ROC curves. Further study finds that although the PCA-based method doesn't work well on current mobile sensor networks, its performance can be improved by increasing the radiation spectral quality.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-11-09 without embargo terms","The student, Jifu Zhao, accepted the attached license on 2016-07-18 at 09:17.","The student, Jifu Zhao, submitted this Thesis for approval on 2016-07-18 at 09:31.","This Thesis was approved for publication on 2016-07-18 at 14:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9979 on 2016-11-09 at 10:25:19","Made available in DSpace on 2016-11-10T17:55:16Z (GMT). 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