{"id":"https://openalex.org/W1994738042","doi":"https://doi.org/10.1109/vitae.2014.6934396","title":"Neural modeling of link occupancy for wireless transmissions using Markov reward models","display_name":"Neural modeling of link occupancy for wireless transmissions using Markov reward models","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W1994738042","doi":"https://doi.org/10.1109/vitae.2014.6934396","mag":"1994738042"},"language":"en","primary_location":{"id":"doi:10.1109/vitae.2014.6934396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vitae.2014.6934396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems (VITAE)","raw_type":"proceedings-article"},"type":"article","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/A5073553331","display_name":"Izabella Lokshina","orcid":"https://orcid.org/0000-0002-8719-9651"},"institutions":[{"id":"https://openalex.org/I122713931","display_name":"SUNY Oneonta","ror":"https://ror.org/02r3ym141","country_code":"US","type":"education","lineage":["https://openalex.org/I122713931"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Izabella Lokshina","raw_affiliation_strings":["Management, Marketing and Information Systems, SUNY at Oneonta, Oneonta, NY, US","Management, Marketing and Information Systems SUNY at Oneonta, Oneonta, NY, US"],"affiliations":[{"raw_affiliation_string":"Management, Marketing and Information Systems, SUNY at Oneonta, Oneonta, NY, US","institution_ids":["https://openalex.org/I122713931"]},{"raw_affiliation_string":"Management, Marketing and Information Systems SUNY at Oneonta, Oneonta, NY, US","institution_ids":["https://openalex.org/I122713931"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025253057","display_name":"Michael R. Bartolacci","orcid":"https://orcid.org/0000-0002-0817-4270"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Bartolacci","raw_affiliation_strings":["Information Science and Technology, Penn State University-Berks, Reading, PA, US","Information Science and Technology Penn State University - Berks, Reading, PA, US"],"affiliations":[{"raw_affiliation_string":"Information Science and Technology, Penn State University-Berks, Reading, PA, US","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"Information Science and Technology Penn State University - Berks, Reading, PA, US","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5073553331"],"corresponding_institution_ids":["https://openalex.org/I122713931"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09186553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10138","display_name":"Network Traffic and Congestion Control","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9146000146865845,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9018999934196472,"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/markov-chain","display_name":"Markov chain","score":0.7404962778091431},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.698314368724823},{"id":"https://openalex.org/keywords/occupancy","display_name":"Occupancy","score":0.5434037446975708},{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.4927203953266144},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4622257947921753},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.4263971745967865},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.417179673910141},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.37240737676620483},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36283206939697266},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3255253732204437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24871838092803955},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18814808130264282},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15095248818397522},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13916704058647156},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0668419897556305}],"concepts":[{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.7404962778091431},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.698314368724823},{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.5434037446975708},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.4927203953266144},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4622257947921753},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.4263971745967865},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.417179673910141},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.37240737676620483},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36283206939697266},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3255253732204437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24871838092803955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18814808130264282},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15095248818397522},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13916704058647156},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0668419897556305},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vitae.2014.6934396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vitae.2014.6934396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems (VITAE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2036426733","https://openalex.org/W2083164452","https://openalex.org/W2156607018","https://openalex.org/W4299326032"],"related_works":["https://openalex.org/W4282043467","https://openalex.org/W2105697914","https://openalex.org/W3093197249","https://openalex.org/W1968324288","https://openalex.org/W1540010871","https://openalex.org/W3023979140","https://openalex.org/W2904068067","https://openalex.org/W1565491139","https://openalex.org/W3177545769","https://openalex.org/W2202433167"],"abstract_inverted_index":{"The":[0],"paper":[1],"is":[2,43,58,82],"devoted":[3],"to":[4],"neural":[5,91],"modeling":[6],"of":[7,20,63,69],"link":[8,26],"occupancy":[9,41,56,79],"distribution.":[10],"Multi-service":[11],"(i.e.,":[12],"bandwidth":[13],"sharing":[14],"between":[15],"different":[16],"traffic":[17,32],"classes)":[18],"models":[19],"a":[21,61,89],"single,":[22],"possibly":[23],"wireless":[24],"transmission":[25],"for":[27],"rigid,":[28],"adaptive":[29],"and":[30,72,94],"elastic":[31],"are":[33,97],"developed":[34],"based":[35],"on":[36],"Markov":[37,49],"reward":[38],"models.":[39],"Link":[40,55,78],"distribution":[42],"introduced":[44],"as":[45,60],"embedded,":[46],"discrete":[47],"time":[48],"chain":[50],"researched":[51],"with":[52,66],"vector":[53,86],"quantization.":[54],"performance":[57],"simulated":[59],"combination":[62],"single":[64],"queues":[65],"random":[67],"distributions":[68],"arrival":[70],"processes":[71],"holding":[73],"times":[74],"in":[75,88],"service":[76],"phases.":[77],"probability":[80],"density":[81],"determined":[83],"using":[84],"learning":[85],"quantization":[87],"two-layered":[90],"structure.":[92],"Simulation":[93],"numerical":[95],"results":[96],"shown.":[98]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}