{"id":"https://openalex.org/W4401164153","doi":"https://doi.org/10.1109/eit60633.2024.10609937","title":"Machine Learning Models for Prediction of Metal Ion Concentrations in Drinking Water","display_name":"Machine Learning Models for Prediction of Metal Ion Concentrations in Drinking Water","publication_year":2024,"publication_date":"2024-05-30","ids":{"openalex":"https://openalex.org/W4401164153","doi":"https://doi.org/10.1109/eit60633.2024.10609937"},"language":"en","primary_location":{"id":"doi:10.1109/eit60633.2024.10609937","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/eit60633.2024.10609937","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Electro Information Technology (eIT)","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/A5106015166","display_name":"Nehpal S. Shekhawat","orcid":null},"institutions":[{"id":"https://openalex.org/I102461120","display_name":"Marquette University","ror":"https://ror.org/04gr4te78","country_code":"US","type":"education","lineage":["https://openalex.org/I102461120"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nehpal S. Shekhawat","raw_affiliation_strings":["Marquette University,Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Marquette University,Electrical and Computer Engineering","institution_ids":["https://openalex.org/I102461120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101539621","display_name":"Sangmin Oh","orcid":"https://orcid.org/0000-0001-7019-3117"},"institutions":[{"id":"https://openalex.org/I102461120","display_name":"Marquette University","ror":"https://ror.org/04gr4te78","country_code":"US","type":"education","lineage":["https://openalex.org/I102461120"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sangmin Oh","raw_affiliation_strings":["Marquette University,Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Marquette University,Electrical and Computer Engineering","institution_ids":["https://openalex.org/I102461120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086561910","display_name":"Cristinel Ababei","orcid":"https://orcid.org/0000-0002-7609-5304"},"institutions":[{"id":"https://openalex.org/I102461120","display_name":"Marquette University","ror":"https://ror.org/04gr4te78","country_code":"US","type":"education","lineage":["https://openalex.org/I102461120"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cristinel Ababei","raw_affiliation_strings":["Marquette University,Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Marquette University,Electrical and Computer Engineering","institution_ids":["https://openalex.org/I102461120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041592299","display_name":"Chung Hoon Lee","orcid":"https://orcid.org/0000-0002-5313-1050"},"institutions":[{"id":"https://openalex.org/I102461120","display_name":"Marquette University","ror":"https://ror.org/04gr4te78","country_code":"US","type":"education","lineage":["https://openalex.org/I102461120"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chung Hoon Lee","raw_affiliation_strings":["Marquette University,Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Marquette University,Electrical and Computer Engineering","institution_ids":["https://openalex.org/I102461120"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068927047","display_name":"Dong Hye Ye","orcid":"https://orcid.org/0000-0002-9186-4095"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Hye Ye","raw_affiliation_strings":["Georgia State University,Computer Science"],"affiliations":[{"raw_affiliation_string":"Georgia State University,Computer Science","institution_ids":["https://openalex.org/I181565077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5106015166"],"corresponding_institution_ids":["https://openalex.org/I102461120"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13542368,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"099","last_page":"105"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9340000152587891,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9340000152587891,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5169410109519958},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37208065390586853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3534022569656372}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5169410109519958},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37208065390586853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3534022569656372}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eit60633.2024.10609937","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/eit60633.2024.10609937","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Electro Information Technology (eIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8799999952316284,"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2891262528","https://openalex.org/W2947038911","https://openalex.org/W3164290413","https://openalex.org/W3168970012","https://openalex.org/W3202034776","https://openalex.org/W4226210580","https://openalex.org/W4365801672","https://openalex.org/W4383751302","https://openalex.org/W4385153885","https://openalex.org/W6784225549"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2],"investigation":[3,102],"of":[4,156],"several":[5],"machine":[6],"learning":[7],"(ML)":[8],"models":[9,115,118,138,158],"developed":[10],"to":[11,56,154],"predict":[12],"the":[13,98],"copper":[14],"(Cu)":[15],"and":[16,110,165],"lead":[17],"(Pb)":[18],"ion":[19],"concentrations":[20],"in":[21,82],"drinking":[22,47],"water.":[23],"The":[24,52],"system":[25],"where":[26],"this":[27],"prediction":[28],"is":[29,31,54,78],"employed":[30],"based":[32],"on":[33,123],"a":[34,43,57,69],"microwave":[35],"block":[36],"loop":[37],"gap":[38],"resonator":[39,53],"(BLGR),":[40],"which":[41,62],"surrounds":[42],"glass":[44],"tube":[45],"with":[46],"water":[48],"passing":[49],"through":[50],"it.":[51],"coupled":[55],"vector":[58],"network":[59],"analyzer":[60],"(VNA),":[61],"collects":[63],"reflection":[64],"coefficient":[65],"(S11)":[66],"measurements":[67],"over":[68],"100":[70],"MHz":[71],"-":[72],"6":[73],"GHz":[74],"frequency":[75],"range.":[76],"It":[77],"these":[79],"S11":[80,149],"measurements,":[81],"raw":[83],"format":[84],"or":[85],"compressed":[86],"using":[87,127,132],"various":[88],"signal":[89],"processing":[90],"techniques,":[91],"that":[92,136,139,155],"are":[93],"used":[94],"as":[95,141],"input":[96,142],"into":[97],"ML":[99],"models.":[100],"Our":[101],"looks":[103],"at":[104,160],"new":[105],"convolutional":[106],"neural":[107,112],"networks":[108,113],"(CNN)":[109],"deep":[111],"(DNN)":[114],"because":[116],"such":[117],"can":[119],"easily":[120],"be":[121],"deployed":[122],"IoT":[124],"microcontroller":[125],"devices":[126],"tinyML":[128],"technologies.":[129],"Extensive":[130],"simulations":[131],"real":[133],"data":[134],"demonstrate":[135],"DNN":[137],"use":[140],"features":[143],"essential":[144],"spectral":[145],"information":[146],"created":[147],"from":[148],"traces":[150],"provide":[151],"performance":[152],"comparable":[153],"CNN":[157],"but":[159],"much":[161],"shorter":[162],"training":[163],"times":[164],"significantly":[166],"smaller":[167],"model":[168],"sizes.":[169]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}