{"id":"https://openalex.org/W4403723937","doi":"https://doi.org/10.1109/dsaa61799.2024.10722784","title":"PAW: A Deep Learning Model for Predicting Amplitude Windows in Seismic Signals","display_name":"PAW: A Deep Learning Model for Predicting Amplitude Windows in Seismic Signals","publication_year":2024,"publication_date":"2024-10-06","ids":{"openalex":"https://openalex.org/W4403723937","doi":"https://doi.org/10.1109/dsaa61799.2024.10722784"},"language":"en","primary_location":{"id":"doi:10.1109/dsaa61799.2024.10722784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa61799.2024.10722784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ariana M. Villegas Suarez","orcid":null},"institutions":[{"id":"https://openalex.org/I169521973","display_name":"University of New Mexico","ror":"https://ror.org/05fs6jp91","country_code":"US","type":"education","lineage":["https://openalex.org/I169521973"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ariana M. Villegas Suarez","raw_affiliation_strings":["Department of Computer Science, University of New Mexico, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of New Mexico, USA","institution_ids":["https://openalex.org/I169521973"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Delaine Reiter","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144946","display_name":"Applied Research Associates (United States)","ror":"https://ror.org/04vpnmr86","country_code":"US","type":"company","lineage":["https://openalex.org/I4210144946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Delaine Reiter","raw_affiliation_strings":["Applied Research Associates, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Research Associates, USA","institution_ids":["https://openalex.org/I4210144946"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jonathan Rolfs","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144946","display_name":"Applied Research Associates (United States)","ror":"https://ror.org/04vpnmr86","country_code":"US","type":"company","lineage":["https://openalex.org/I4210144946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Rolfs","raw_affiliation_strings":["Applied Research Associates, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Research Associates, USA","institution_ids":["https://openalex.org/I4210144946"]}]},{"author_position":"last","author":{"id":null,"display_name":"Abdullah Mueen","orcid":null},"institutions":[{"id":"https://openalex.org/I169521973","display_name":"University of New Mexico","ror":"https://ror.org/05fs6jp91","country_code":"US","type":"education","lineage":["https://openalex.org/I169521973"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdullah Mueen","raw_affiliation_strings":["Department of Computer Science, University of New Mexico, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of New Mexico, USA","institution_ids":["https://openalex.org/I169521973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3556,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57009997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13018","display_name":"Seismology and Earthquake Studies","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13018","display_name":"Seismology and Earthquake Studies","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11757","display_name":"Seismic Waves and Analysis","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.5445859432220459},{"id":"https://openalex.org/keywords/amplitude","display_name":"Amplitude","score":0.5412291288375854},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5191706418991089},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5036486983299255},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.3861594796180725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3358922600746155},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.05672118067741394},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.0530627965927124}],"concepts":[{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.5445859432220459},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.5412291288375854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5191706418991089},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5036486983299255},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.3861594796180725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3358922600746155},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.05672118067741394},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0530627965927124}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa61799.2024.10722784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa61799.2024.10722784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1980658796","https://openalex.org/W1993912260","https://openalex.org/W2009959139","https://openalex.org/W2155780245","https://openalex.org/W2510651935","https://openalex.org/W2608847424","https://openalex.org/W2755481501","https://openalex.org/W2784540332","https://openalex.org/W2785826471","https://openalex.org/W2793536256","https://openalex.org/W2798961812","https://openalex.org/W2802586787","https://openalex.org/W2806777472","https://openalex.org/W2895546528","https://openalex.org/W2895790973","https://openalex.org/W2896827527","https://openalex.org/W2909899137","https://openalex.org/W2954731415","https://openalex.org/W2971724044","https://openalex.org/W2994733056","https://openalex.org/W2995015263","https://openalex.org/W3002709689","https://openalex.org/W3004999940","https://openalex.org/W3043084043","https://openalex.org/W3047855151","https://openalex.org/W3087724869","https://openalex.org/W3100137627","https://openalex.org/W3121383166","https://openalex.org/W3172307969","https://openalex.org/W3199040194","https://openalex.org/W3207556990","https://openalex.org/W4214894402","https://openalex.org/W4225526013","https://openalex.org/W4285233421","https://openalex.org/W4290647997","https://openalex.org/W4292969185","https://openalex.org/W4301401999","https://openalex.org/W4309395887","https://openalex.org/W4317940035","https://openalex.org/W4392309198","https://openalex.org/W6743908518","https://openalex.org/W6771687900"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W4321369474","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"Subsurface":[0],"earthquakes":[1],"and":[2,34,43,57,102,120],"explosions":[3],"generate":[4],"seismic":[5,29,40,54],"wavefields":[6],"that":[7,89],"are":[8],"recorded":[9],"as":[10,24],"time-domain":[11],"signals":[12],"on":[13,117,122],"sensor":[14],"networks":[15],"around":[16],"the":[17,25,36,70,92,100,118],"world.":[18],"To":[19,78],"compute":[20],"key":[21],"characteristics":[22],"such":[23],"magnitude":[26],"of":[27,39,72,94,99],"these":[28],"events,":[30],"analysts":[31],"must":[32],"detect":[33],"select":[35],"cleanest":[37],"indicators":[38],"phase":[41,55],"amplitudes":[42,56],"periods":[44,58],"in":[45],"noisy":[46],"signals.":[47],"Existing":[48],"automated":[49],"systems":[50],"designed":[51],"to":[52,74,126],"pick":[53],"require":[59],"frequent":[60],"adjustments":[61],"by":[62,109],"human":[63,96],"analysts,":[64],"which":[65],"becomes":[66],"a":[67,85,95],"nuisance":[68],"when":[69],"volume":[71],"data":[73],"process":[75],"grows":[76],"large.":[77],"address":[79],"this":[80],"problem,":[81],"we":[82],"have":[83,113],"developed":[84],"neural":[86],"network":[87],"model":[88,119],"accurately":[90],"replicates":[91],"performance":[93,124],"analyst":[97,107],"80%":[98],"time":[101],"shows":[103],"potential":[104],"for":[105],"decreasing":[106],"burden":[108],"over":[110],"40%.":[111],"We":[112],"performed":[114],"multiple":[115],"tests":[116],"report":[121],"its":[123],"compared":[125],"existing":[127],"deep":[128],"learning":[129],"techniques.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2024-10-25T00:00:00"}
