{"id":"https://openalex.org/W4414097037","doi":"https://doi.org/10.3390/make7030096","title":"Leveraging DNA-Based Computing to Improve the Performance of Artificial Neural Networks in Smart Manufacturing","display_name":"Leveraging DNA-Based Computing to Improve the Performance of Artificial Neural Networks in Smart Manufacturing","publication_year":2025,"publication_date":"2025-09-09","ids":{"openalex":"https://openalex.org/W4414097037","doi":"https://doi.org/10.3390/make7030096"},"language":"en","primary_location":{"id":"doi:10.3390/make7030096","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7030096","pdf_url":"https://www.mdpi.com/2504-4990/7/3/96/pdf?version=1757477163","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/7/3/96/pdf?version=1757477163","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042786988","display_name":"Angkush Kumar Ghosh","orcid":"https://orcid.org/0000-0002-9644-177X"},"institutions":[{"id":"https://openalex.org/I98957242","display_name":"Kitami Institute of Technology","ror":"https://ror.org/05wks2t16","country_code":"JP","type":"education","lineage":["https://openalex.org/I98957242"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Angkush Kumar Ghosh","raw_affiliation_strings":["Division of Mechanical and Electrical Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Japan"],"raw_orcid":"https://orcid.org/0000-0002-9644-177X","affiliations":[{"raw_affiliation_string":"Division of Mechanical and Electrical Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Japan","institution_ids":["https://openalex.org/I98957242"]}]},{"author_position":"last","author":{"id":null,"display_name":"Sharifu Ura","orcid":"https://orcid.org/0000-0003-4584-5288"},"institutions":[{"id":"https://openalex.org/I98957242","display_name":"Kitami Institute of Technology","ror":"https://ror.org/05wks2t16","country_code":"JP","type":"education","lineage":["https://openalex.org/I98957242"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Sharifu Ura","raw_affiliation_strings":["Division of Mechanical and Electrical Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Japan"],"raw_orcid":"https://orcid.org/0000-0003-4584-5288","affiliations":[{"raw_affiliation_string":"Division of Mechanical and Electrical Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Japan","institution_ids":["https://openalex.org/I98957242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042786988"],"corresponding_institution_ids":["https://openalex.org/I98957242"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":2.0883,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87988941,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"7","issue":"3","first_page":"96","last_page":"96"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7095999717712402},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4514999985694885},{"id":"https://openalex.org/keywords/dbc","display_name":"dBc","score":0.44429999589920044},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.40799999237060547},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3734999895095825},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.36390000581741333}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7153000235557556},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7095999717712402},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6352999806404114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6274999976158142},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4514999985694885},{"id":"https://openalex.org/C193523891","wikidata":"https://www.wikidata.org/wiki/Q1771950","display_name":"dBc","level":3,"score":0.44429999589920044},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40799999237060547},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3345000147819519},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C2988642114","wikidata":"https://www.wikidata.org/wiki/Q25112020","display_name":"Smart manufacturing","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2752000093460083},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27459999918937683},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.273499995470047},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make7030096","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7030096","pdf_url":"https://www.mdpi.com/2504-4990/7/3/96/pdf?version=1757477163","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:18d91fe1c96e42909e333b505e63f996","is_oa":true,"landing_page_url":"https://doaj.org/article/18d91fe1c96e42909e333b505e63f996","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 7, Iss 3, p 96 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make7030096","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7030096","pdf_url":"https://www.mdpi.com/2504-4990/7/3/96/pdf?version=1757477163","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414097037.pdf","grobid_xml":"https://content.openalex.org/works/W4414097037.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W835977602","https://openalex.org/W1420395521","https://openalex.org/W1952294081","https://openalex.org/W2019826771","https://openalex.org/W2031874234","https://openalex.org/W2055214702","https://openalex.org/W2086463518","https://openalex.org/W2156627912","https://openalex.org/W2493990996","https://openalex.org/W2519054182","https://openalex.org/W2552166615","https://openalex.org/W2604520637","https://openalex.org/W2775835322","https://openalex.org/W2790661307","https://openalex.org/W2796481342","https://openalex.org/W2799434389","https://openalex.org/W2803610836","https://openalex.org/W2883908928","https://openalex.org/W2901112046","https://openalex.org/W2946787920","https://openalex.org/W2981365036","https://openalex.org/W2997516327","https://openalex.org/W3002626238","https://openalex.org/W3095800599","https://openalex.org/W3112130234","https://openalex.org/W3119558728","https://openalex.org/W3138535992","https://openalex.org/W3181328872","https://openalex.org/W3185457359","https://openalex.org/W3186548779","https://openalex.org/W3203083747","https://openalex.org/W3210392192","https://openalex.org/W3214248876","https://openalex.org/W3214564282","https://openalex.org/W4206013430","https://openalex.org/W4220943905","https://openalex.org/W4256613398","https://openalex.org/W4296627109","https://openalex.org/W4300782289","https://openalex.org/W4306407818","https://openalex.org/W4308986157","https://openalex.org/W4379653935","https://openalex.org/W4384655840","https://openalex.org/W4385299089","https://openalex.org/W4385566824","https://openalex.org/W4386134686","https://openalex.org/W4388272972","https://openalex.org/W4393210560","https://openalex.org/W4394866263","https://openalex.org/W4402195243","https://openalex.org/W4405624156","https://openalex.org/W4405850794"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Bioinspired":[0],"computing":[1],"methods,":[2],"such":[3,248],"as":[4,68,235,249],"Artificial":[5],"Neural":[6],"Networks":[7],"(ANNs),":[8],"play":[9],"a":[10,69,176,236],"significant":[11],"role":[12],"in":[13,20,80,166],"machine":[14,76,101,238],"learning.":[15],"This":[16,208],"is":[17,73],"particularly":[18],"evident":[19],"smart":[21,245],"manufacturing,":[22],"where":[23],"ANNs":[24,41],"and":[25,37,114,123,204,217],"their":[26],"derivatives,":[27],"like":[28],"deep":[29],"learning,":[30],"are":[31,104],"widely":[32],"used":[33,201],"for":[34,158,214,241],"pattern":[35],"recognition":[36],"adaptive":[38],"control.":[39],"However,":[40,161],"sometimes":[42],"fail":[43],"to":[44,95,202,224],"achieve":[45],"the":[46,62,81,90,107,130,154,167,173,185,190,206,226],"desired":[47],"results,":[48],"especially":[49],"when":[50],"working":[51],"with":[52,89,126,184,229],"small":[53],"datasets.":[54,160,171,219],"To":[55],"address":[56],"this":[57,59,98,188],"limitation,":[58],"article":[60],"presents":[61],"effectiveness":[63],"of":[64,84,93,169,222],"DNA-Based":[65],"Computing":[66],"(DBC)":[67],"complementary":[70],"approach.":[71],"DBC":[72,183,223],"an":[74,110],"innovative":[75],"learning":[77,102,239],"method":[78],"rooted":[79],"central":[82],"dogma":[83],"molecular":[85],"biology":[86],"that":[87,153],"deals":[88],"genetic":[91],"information":[92],"DNA/RNA":[94],"protein.":[96],"In":[97,106,172,187],"article,":[99],"two":[100],"approaches":[103],"considered.":[105],"first":[108,193],"approach,":[109,175],"ANN":[111,155],"was":[112,179],"trained":[113],"tested":[115],"using":[116,195],"time":[117,131],"series":[118],"datasets":[119,231],"driven":[120],"by":[121,181],"long":[122],"short":[124],"windows,":[125],"features":[127,191,199],"extracted":[128,194,198],"from":[129],"domain.":[132],"Each":[133],"long-window-driven":[134,159],"dataset":[135,144],"contained":[136],"approximately":[137,146],"150":[138],"data":[139,148],"points,":[140],"while":[141],"each":[142],"short-window-driven":[143,170,218,230],"had":[145],"10":[147],"points.":[149],"The":[150,197,220],"results":[151],"showed":[152],"performed":[156],"well":[157],"its":[162,233],"performance":[163,213],"declined":[164],"significantly":[165],"case":[168],"last":[174],"hybrid":[177,209],"model":[178],"developed":[180],"integrating":[182],"ANN.":[186,207],"case,":[189],"were":[192,200],"DBC.":[196],"train":[203],"test":[205],"approach":[210],"demonstrated":[211],"robust":[212],"both":[215],"long-":[216],"ability":[221],"overcome":[225],"ANN\u2019s":[227],"limitations":[228],"underscores":[232],"potential":[234],"pragmatic":[237],"solution":[240],"developing":[242],"more":[243],"effective":[244],"manufacturing":[246],"systems,":[247],"digital":[250],"twins.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}