{"id":"https://openalex.org/W3047844190","doi":"https://doi.org/10.1109/mdm48529.2020.00041","title":"STIMULATE: A System for Real-time Information Acquisition and Learning for Disaster Management","display_name":"STIMULATE: A System for Real-time Information Acquisition and Learning for Disaster Management","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3047844190","doi":"https://doi.org/10.1109/mdm48529.2020.00041","mag":"3047844190"},"language":"en","primary_location":{"id":"doi:10.1109/mdm48529.2020.00041","doi":"https://doi.org/10.1109/mdm48529.2020.00041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mdm48529.2020.00041","pdf_url":null,"source":{"id":"https://openalex.org/S4393917546","display_name":"IEEE International Conference on Mobile Data Management (MDM)","issn_l":"1551-6245","issn":["1551-6245"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 21st IEEE International Conference on Mobile Data Management (MDM)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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":"https://openalex.org/A5011716917","display_name":"Md. Yasin Kabir","orcid":"https://orcid.org/0000-0002-2449-4872","observed_orcids":["https://orcid.org/0000-0002-2449-4872"]},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Yasin Kabir","raw_affiliation_strings":["Department of Computer Science, Missouri S&T, Rolla, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Missouri S&T, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011789698","display_name":"Sergey Gruzdev","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergey Gruzdev","raw_affiliation_strings":["Department of Computer Science, Missouri S&T, Rolla, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Missouri S&T, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012569039","display_name":"Sanjay Madria","orcid":"https://orcid.org/0000-0002-2768-3660","observed_orcids":["https://orcid.org/0000-0002-2768-3660"]},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanjay Madria","raw_affiliation_strings":["Department of Computer Science, Missouri S&T, Rolla, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Missouri S&T, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20382870"],"apc_list":null,"apc_paid":null,"fwci":9.9689,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.98419301,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"186","last_page":"193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11121","display_name":"Public Relations and Crisis Communication","score":0.5713000297546387,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11121","display_name":"Public Relations and Crisis Communication","score":0.5713000297546387,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10747","display_name":"Disaster Management and Resilience","score":0.33399999141693115,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.039799999445676804,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/disaster-management","display_name":"disaster management","score":0.9589999914169312},{"id":"https://openalex.org/keywords/social-media","display_name":"social media","score":0.6990000009536743},{"id":"https://openalex.org/keywords/twitter","display_name":"Twitter","score":0.9670000076293945},{"id":"https://openalex.org/keywords/situational-awareness","display_name":"situational awareness","score":0.9049999713897705},{"id":"https://openalex.org/keywords/tweet-classification","display_name":"tweet classification","score":0.9160000085830688},{"id":"https://openalex.org/keywords/hurricane-harvey","display_name":"Hurricane Harvey","score":0.5400000214576721},{"id":"https://openalex.org/keywords/hurricane-irma","display_name":"Hurricane Irma","score":0.8849999904632568},{"id":"https://openalex.org/keywords/bidirectional-long-short-term-memory","display_name":"bidirectional long short-term memory","score":0.6639999747276306},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8399999737739563},{"id":"https://openalex.org/keywords/websocket","display_name":"WebSocket","score":0.4480000138282776},{"id":"https://openalex.org/keywords/cloud-deployment","display_name":"cloud deployment","score":0.593999981880188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234068155288696},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.7199283242225647},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.5513666272163391},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5281802415847778},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5265322327613831},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5046638250350952},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4827653467655182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48247888684272766},{"id":"https://openalex.org/C62555980","wikidata":"https://www.wikidata.org/wiki/Q1460420","display_name":"Emergency management","level":2,"score":0.41193607449531555},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.411827027797699},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.361409455537796},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.22954770922660828},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.14371395111083984},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mdm48529.2020.00041","doi":"https://doi.org/10.1109/mdm48529.2020.00041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mdm48529.2020.00041","pdf_url":null,"source":{"id":"https://openalex.org/S4393917546","display_name":"IEEE International Conference on Mobile Data Management (MDM)","issn_l":"1551-6245","issn":["1551-6245"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 21st IEEE International Conference on Mobile Data Management (MDM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W255593144","https://openalex.org/W1513897899","https://openalex.org/W1972594216","https://openalex.org/W2114050095","https://openalex.org/W2128721751","https://openalex.org/W2143430537","https://openalex.org/W2151098288","https://openalex.org/W2181558140","https://openalex.org/W2283621191","https://openalex.org/W2588949631","https://openalex.org/W2782616001","https://openalex.org/W2964250510","https://openalex.org/W2964905055","https://openalex.org/W6679820032"],"related_works":["https://openalex.org/W2964905055","https://openalex.org/W3196814640","https://openalex.org/W3007033558","https://openalex.org/W3205129064","https://openalex.org/W4321787895","https://openalex.org/W4386363254","https://openalex.org/W4361214443","https://openalex.org/W4361019058","https://openalex.org/W4407585397","https://openalex.org/W2985745535"],"abstract_inverted_index":{"Real-time":[0,63],"information":[1],"sharing":[2],"and":[3,38,66,75,96,112,150,155,175,186,218,250,256],"propagation":[4],"using":[5,91,132,148,227,240],"social":[6,161],"media":[7,162],"such":[8],"as":[9,14],"Twitter":[10],"has":[11],"proven":[12],"itself":[13],"a":[15,23,60,210],"potential":[16],"resource":[17],"to":[18,246],"improve":[19],"situational":[20],"awareness":[21],"in":[22,53,78,144,168],"timely":[24],"manner":[25],"for":[26,35,62,68,88,106,119,137,152,158,191,204],"disaster":[27,30,230],"management.":[28],"Traditional":[29],"management":[31,121],"systems":[32],"work":[33],"well":[34],"analyzing":[36],"static":[37],"historical":[39],"information.":[40],"However,":[41],"they":[42],"cannot":[43],"process":[44,76],"dynamic":[45],"streams":[46],"of":[47,109,237,252],"data":[48,242],"that":[49,71],"are":[50],"being":[51],"generated":[52],"real-time.":[54],"This":[55],"paper":[56],"presents":[57],"STIMULATE":[58,127,170],"-":[59],"System":[61],"Information":[64],"Acquisition":[65],"Learning":[67],"Disaster":[69],"Management":[70],"can":[72],"(1)":[73],"fetch":[74],"tweets":[77,83,254],"real-time,":[79],"(2)":[80],"classify":[81],"those":[82],"into":[84],"FEMA":[85,102],"defined":[86,103],"categories":[87],"rescue":[89,107,120,205,257],"priorities":[90],"pre-trained":[92],"deep":[93,165,211],"learning":[94,166,212],"models":[95,167],"generate":[97],"useful":[98],"insights,":[99],"(3)":[100],"find":[101],"stranded":[104],"people":[105],"missions":[108],"varying":[110],"priorities,":[111],"(4)":[113],"provide":[114],"an":[115],"interactive":[116],"web":[117,138],"interface":[118],"given":[122],"the":[123,133,145,169,176,193,199,235,248,253],"available":[124],"resources.":[125],"The":[126,164,222],"prototype":[128,171],"is":[129,142,225],"primarily":[130],"built":[131],"Python":[134,173,200],"Flask":[135],"framework":[136],"interaction.":[139],"Additionally,":[140],"it":[141],"deployed":[143],"cloud":[146],"environment":[147],"Hadoop":[149],"MongoDB":[151],"scalable":[153],"storage,":[154],"on-demand":[156],"computing":[157],"processing":[159],"extensive":[160],"data.":[163],"use":[172,180,198],"Keras":[174],"TensorFlow":[177],"library.":[178],"We":[179,208],"Bi-directional":[181],"Long":[182],"Short-Term":[183],"Memory":[184],"(BLSTM)":[185],"Convolutional":[187],"Neural":[188],"Network":[189],"(CNN)":[190],"developing":[192],"tweet":[194,223],"classifier.":[195],"Further,":[196],"we":[197,233],"PyWSGI":[201],"WebSocket":[202],"server":[203],"scheduling":[206,258],"operations.":[207],"present":[209,234],"system":[213],"trained":[214],"on":[215],"hurricane":[216],"Harvey":[217],"Irma":[219],"datasets":[220],"only.":[221],"classifier":[224],"evaluated":[226],"15":[228],"different":[229,244],"datasets.":[231],"Finally,":[232],"results":[236],"multiple":[238],"simulations":[239],"synthetic":[241],"with":[243],"sizes":[245],"measure":[247],"performance":[249],"effectiveness":[251],"processor":[255],"algorithm.":[259]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2020-08-13T00:00:00"}