{"id":"https://openalex.org/W7166345537","doi":"https://doi.org/10.5281/zenodo.20966808","title":"Simulation Code: Boolean Differential Analysis with Hybrid Density-Partitioning Clustering for Enhanced Security Risk Assessment","display_name":"Simulation Code: Boolean Differential Analysis with Hybrid Density-Partitioning Clustering for Enhanced Security Risk Assessment","publication_year":2026,"publication_date":"2026-06-27","ids":{"openalex":"https://openalex.org/W7166345537","doi":"https://doi.org/10.5281/zenodo.20966808"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.20966808","doi":"https://doi.org/10.5281/zenodo.20966808","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.20966808","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Software"},"volume":null,"type":"software","is_traditional":false,"indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.20966808","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133036119","display_name":"Rana Amirova","orcid":"https://orcid.org/0009-0005-6412-4736","observed_orcids":["https://orcid.org/0009-0005-6412-4736"]},"institutions":[{"id":"https://openalex.org/I26889942","display_name":"Azerbaijan Technical University","ror":"https://ror.org/01qe1a488","country_code":"AZ","type":"education","lineage":["https://openalex.org/I26889942"]}],"countries":["AZ"],"is_corresponding":false,"raw_author_name":"Amirova, Rana","raw_affiliation_strings":["Azerbaijan Technical University"],"raw_orcid":"https://orcid.org/0009-0005-6412-4736","affiliations":[{"raw_affiliation_string":"Azerbaijan Technical University","institution_ids":["https://openalex.org/I26889942"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139297184","display_name":"Babanli Gunel","orcid":"https://orcid.org/0009-0007-9990-5019","observed_orcids":["https://orcid.org/0009-0007-9990-5019"]},"institutions":[{"id":"https://openalex.org/I26889942","display_name":"Azerbaijan Technical University","ror":"https://ror.org/01qe1a488","country_code":"AZ","type":"education","lineage":["https://openalex.org/I26889942"]}],"countries":["AZ"],"is_corresponding":false,"raw_author_name":"Babanli, Gunel","raw_affiliation_strings":["Azerbaijan Technical University"],"raw_orcid":"https://orcid.org/0009-0007-9990-5019","affiliations":[{"raw_affiliation_string":"Azerbaijan Technical University","institution_ids":["https://openalex.org/I26889942"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I26889942"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13832","display_name":"Advanced Decision-Making Techniques","score":0.8008000254631042,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13832","display_name":"Advanced Decision-Making Techniques","score":0.8008000254631042,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.05900000035762787,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.02669999934732914,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/boolean-functions","display_name":"Boolean functions","score":0.49300000071525574},{"id":"https://openalex.org/keywords/security-risk-assessment","display_name":"security risk assessment","score":0.800000011920929},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"K-means clustering","score":0.8790000081062317},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.8679999709129333},{"id":"https://openalex.org/keywords/hybrid-clustering","display_name":"hybrid clustering","score":0.796999990940094},{"id":"https://openalex.org/keywords/neuro-symbolic-models","display_name":"neuro-symbolic models","score":0.7480000257492065}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7631000280380249},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.7236999869346619},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6922000050544739},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6894000172615051},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6097999811172485},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.5591999888420105},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4246000051498413},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3449000120162964},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.3312999904155731},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.3287999927997589},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.328000009059906},{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C187455244","wikidata":"https://www.wikidata.org/wiki/Q942353","display_name":"Boolean function","level":2,"score":0.2508000135421753},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.20966808","doi":"https://doi.org/10.5281/zenodo.20966808","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.20966808","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Software"},{"id":"doi:10.5281/zenodo.20966809","doi":"https://doi.org/10.5281/zenodo.20966809","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.20966809","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Software"}],"best_oa_location":{"id":"doi:10.5281/zenodo.20966808","doi":"https://doi.org/10.5281/zenodo.20966808","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.20966808","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Software"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7196999972","https://openalex.org/W7167852480","https://openalex.org/W7214966659","https://openalex.org/W7170160542","https://openalex.org/W6958538004","https://openalex.org/W7165851656","https://openalex.org/W7167728939","https://openalex.org/W7203620419","https://openalex.org/W4396655994","https://openalex.org/W2314838732"],"abstract_inverted_index":{"This":[0],"repository":[1],"contains":[2],"the":[3,9,43],"complete":[4],"Python":[5,120],"simulation":[6],"package":[7,33],"accompanying":[8],"paper":[10],"\"Boolean":[11],"Differential":[12],"Analysis":[13],"with":[14,88,103],"Hybrid":[15,98],"Density-Partitioning":[16],"Clustering":[17],"for":[18,52],"Enhanced":[19],"Security":[20],"Risk":[21],"Assessment\"":[22],"by":[23],"Gunel":[24],"Babanli":[25],"and":[26,38,59,70],"Rana":[27],"Amirova":[28],"(Azerbaijan":[29],"Technical":[30],"University).":[31],"The":[32],"reproduces":[34],"all":[35],"figures,":[36],"tables,":[37],"numerical":[39],"results":[40],"presented":[41],"in":[42],"paper:":[44],"-":[45],"Boolean":[46,80],"differential":[47],"operators":[48],"(\u2202f/\u2202x\u1d62,":[49],"max\u2228,":[50],"min\u2227)":[51],"f(x\u2081,x\u2082,x\u2083)":[53],"=":[54],"(x\u2081\u00b7x\u2082)":[55],"\u2295":[56],"x\u2083-":[57],"Linear":[58],"sigmoid":[60],"AI":[61,113],"risk":[62,72],"models":[63],"(Figures":[64,74],"2\u20133)-":[65],"Critical":[66],"variable":[67],"x\u2083":[68],"analysis":[69],"3D":[71],"surfaces":[73],"4\u20135)-":[75],"Preprocessing":[76],"pipeline:":[77],"binarization":[78],"\u2192":[79,83],"feature":[81],"augmentation":[82],"normalization-":[84],"K-Means":[85,99],"clustering":[86,95],"(k=3)":[87],"quantization":[89],"mapping":[90],"(Table":[91,107,117],"2)-":[92],"DBSCAN":[93,101],"density-based":[94],"(\u03b5=0.30,":[96],"minPts=2)-":[97],"+":[100],"method":[102],"Silhouette":[104],"Score":[105],"evaluation":[106],"3)-":[108],"Neuro-symbolic":[109],"training":[110],"comparison:":[111],"Standard":[112],"vs.":[114],"Boolean-guided":[115],"model":[116],"1)":[118],"Requirements:":[119],"3.8+,":[121],"numpy,":[122],"matplotlib,":[123],"scikit-learn,":[124],"scipy":[125],"Run:":[126],"python":[127],"run_all.py":[128]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-06-28T00:00:00"}