{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:2KMQJSJRIKSJDIWWRYLESI772W","short_pith_number":"pith:2KMQJSJR","schema_version":"1.0","canonical_sha256":"d29904c93142a491a2d68e164923ffd5a35f7398bc1a6c5f0f8ec62fcea1adf4","source":{"kind":"arxiv","id":"2102.01158","version":1},"attestation_state":"computed","paper":{"title":"System-reliability based multi-ensemble of GAN and one-class joint Gaussian distributions for unsupervised real-time structural health monitoring","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Kourosh Nasrollahzadeh, Mohammad Hesam Soleimani-Babakamali, Reza Sepasdar, Rodrigo Sarlo","submitted_at":"2021-02-01T20:50:55Z","abstract_excerpt":"Unsupervised health monitoring has gained much attention in the last decade as the most practical real-time structural health monitoring (SHM) approach. Among the proposed unsupervised techniques in the literature, there are still obstacles to robust and real-time health monitoring. These barriers include loss of information from dimensionality reduction in feature extraction steps, case-dependency of those steps, lack of a dynamic clustering, and detection results' sensitivity to user-defined parameters. This study introduces an unsupervised real-time SHM method with a mixture of low- and hig"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2102.01158","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-01T20:50:55Z","cross_cats_sorted":[],"title_canon_sha256":"9edabed2fbab921774b40088f3eda0f6de16e07d51ce277ed41fb60b5c1bd431","abstract_canon_sha256":"7157713a0272a834f16e6df6f83e3296f569647869a39f7c036b34c0eecdee4b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:58:46.228885Z","signature_b64":"e5EmPcHJ4OK634Q/HzG4pTCGcvSHFlMLHEzx1Jp24zJnnRKyNZpBqZqYdIDATbLuyQsTedOQBByBtC96McNFAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d29904c93142a491a2d68e164923ffd5a35f7398bc1a6c5f0f8ec62fcea1adf4","last_reissued_at":"2026-07-05T03:58:46.228450Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:58:46.228450Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"System-reliability based multi-ensemble of GAN and one-class joint Gaussian distributions for unsupervised real-time structural health monitoring","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Kourosh Nasrollahzadeh, Mohammad Hesam Soleimani-Babakamali, Reza Sepasdar, Rodrigo Sarlo","submitted_at":"2021-02-01T20:50:55Z","abstract_excerpt":"Unsupervised health monitoring has gained much attention in the last decade as the most practical real-time structural health monitoring (SHM) approach. Among the proposed unsupervised techniques in the literature, there are still obstacles to robust and real-time health monitoring. These barriers include loss of information from dimensionality reduction in feature extraction steps, case-dependency of those steps, lack of a dynamic clustering, and detection results' sensitivity to user-defined parameters. This study introduces an unsupervised real-time SHM method with a mixture of low- and hig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.01158","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2102.01158/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2102.01158","created_at":"2026-07-05T03:58:46.228506+00:00"},{"alias_kind":"arxiv_version","alias_value":"2102.01158v1","created_at":"2026-07-05T03:58:46.228506+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.01158","created_at":"2026-07-05T03:58:46.228506+00:00"},{"alias_kind":"pith_short_12","alias_value":"2KMQJSJRIKSJ","created_at":"2026-07-05T03:58:46.228506+00:00"},{"alias_kind":"pith_short_16","alias_value":"2KMQJSJRIKSJDIWW","created_at":"2026-07-05T03:58:46.228506+00:00"},{"alias_kind":"pith_short_8","alias_value":"2KMQJSJR","created_at":"2026-07-05T03:58:46.228506+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W","json":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W.json","graph_json":"https://pith.science/api/pith-number/2KMQJSJRIKSJDIWWRYLESI772W/graph.json","events_json":"https://pith.science/api/pith-number/2KMQJSJRIKSJDIWWRYLESI772W/events.json","paper":"https://pith.science/paper/2KMQJSJR"},"agent_actions":{"view_html":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W","download_json":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W.json","view_paper":"https://pith.science/paper/2KMQJSJR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2102.01158&json=true","fetch_graph":"https://pith.science/api/pith-number/2KMQJSJRIKSJDIWWRYLESI772W/graph.json","fetch_events":"https://pith.science/api/pith-number/2KMQJSJRIKSJDIWWRYLESI772W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W/action/storage_attestation","attest_author":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W/action/author_attestation","sign_citation":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W/action/citation_signature","submit_replication":"https://pith.science/pith/2KMQJSJRIKSJDIWWRYLESI772W/action/replication_record"}},"created_at":"2026-07-05T03:58:46.228506+00:00","updated_at":"2026-07-05T03:58:46.228506+00:00"}