{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:XXGTM7YOBXCAG7CYFMALSMOUXV","short_pith_number":"pith:XXGTM7YO","canonical_record":{"source":{"id":"1703.06272","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-18T08:38:51Z","cross_cats_sorted":["cs.NE","stat.ML"],"title_canon_sha256":"01a8eb2fe207d4acf5f54c9a77b8b8d2535343c001b9fb48c65391a569d15df5","abstract_canon_sha256":"4c256231e4166809f5571a6ae3776fb4eb4625a7f0aaec820c771c0c324b9dff"},"schema_version":"1.0"},"canonical_sha256":"bdcd367f0e0dc4037c582b00b931d4bd53757267c72504ce4f3325c1be5d37b9","source":{"kind":"arxiv","id":"1703.06272","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.06272","created_at":"2026-05-18T00:48:23Z"},{"alias_kind":"arxiv_version","alias_value":"1703.06272v1","created_at":"2026-05-18T00:48:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.06272","created_at":"2026-05-18T00:48:23Z"},{"alias_kind":"pith_short_12","alias_value":"XXGTM7YOBXCA","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"XXGTM7YOBXCAG7CY","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"XXGTM7YO","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:XXGTM7YOBXCAG7CYFMALSMOUXV","target":"record","payload":{"canonical_record":{"source":{"id":"1703.06272","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-18T08:38:51Z","cross_cats_sorted":["cs.NE","stat.ML"],"title_canon_sha256":"01a8eb2fe207d4acf5f54c9a77b8b8d2535343c001b9fb48c65391a569d15df5","abstract_canon_sha256":"4c256231e4166809f5571a6ae3776fb4eb4625a7f0aaec820c771c0c324b9dff"},"schema_version":"1.0"},"canonical_sha256":"bdcd367f0e0dc4037c582b00b931d4bd53757267c72504ce4f3325c1be5d37b9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:48:23.410859Z","signature_b64":"8nYnek5/jGY84yVFY5PPcoXOsoX5cKfy67XV1lGLzxoJ7c2jGX3QOrdwqU53VPreNajsSgoXwd2vkogF2REVDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bdcd367f0e0dc4037c582b00b931d4bd53757267c72504ce4f3325c1be5d37b9","last_reissued_at":"2026-05-18T00:48:23.410286Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:48:23.410286Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.06272","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:48:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"peQ72+iXksw1b7MhpMFNhwD1hEklRTq5IFpmKBt+yizD8jMJqV8ivUKCQztxJBN1PuKryj2oEJR38/04kOUkDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T14:41:12.319370Z"},"content_sha256":"fbc0f3958cb2bcdfd0d6cfb947b9cb92f1765005dee4b84e60df6d89c3670db9","schema_version":"1.0","event_id":"sha256:fbc0f3958cb2bcdfd0d6cfb947b9cb92f1765005dee4b84e60df6d89c3670db9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:XXGTM7YOBXCAG7CYFMALSMOUXV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Automated Auto-encoder Correlation-based Health-Monitoring and Prognostic Method for Machine Bearings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE","stat.ML"],"primary_cat":"cs.LG","authors_text":"Guodong Wang, Radu Grosu, Ramin M. Hasani","submitted_at":"2017-03-18T08:38:51Z","abstract_excerpt":"This paper studies an intelligent ultimate technique for health-monitoring and prognostic of common rotary machine components, particularly bearings. During a run-to-failure experiment, rich unsupervised features from vibration sensory data are extracted by a trained sparse auto-encoder. Then, the correlation of the extracted attributes of the initial samples (presumably healthy at the beginning of the test) with the succeeding samples is calculated and passed through a moving-average filter. The normalized output is named auto-encoder correlation-based (AEC) rate which stands for an informati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.06272","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:48:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qGgrJ8KOq1JK7R5g/hNBCozSFufxCj7lL7Z5BOK3Y2Vbml5B6y5G2QY/AHzN4R2M/Uua6mo2BD3jef5J46smCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T14:41:12.319994Z"},"content_sha256":"b769deaa77f7bfc9bbe8dc2ddbbefe7b7f5f06aebc84947bb1d867668debfa21","schema_version":"1.0","event_id":"sha256:b769deaa77f7bfc9bbe8dc2ddbbefe7b7f5f06aebc84947bb1d867668debfa21"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XXGTM7YOBXCAG7CYFMALSMOUXV/bundle.json","state_url":"https://pith.science/pith/XXGTM7YOBXCAG7CYFMALSMOUXV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XXGTM7YOBXCAG7CYFMALSMOUXV/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-27T14:41:12Z","links":{"resolver":"https://pith.science/pith/XXGTM7YOBXCAG7CYFMALSMOUXV","bundle":"https://pith.science/pith/XXGTM7YOBXCAG7CYFMALSMOUXV/bundle.json","state":"https://pith.science/pith/XXGTM7YOBXCAG7CYFMALSMOUXV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XXGTM7YOBXCAG7CYFMALSMOUXV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:XXGTM7YOBXCAG7CYFMALSMOUXV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"4c256231e4166809f5571a6ae3776fb4eb4625a7f0aaec820c771c0c324b9dff","cross_cats_sorted":["cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-18T08:38:51Z","title_canon_sha256":"01a8eb2fe207d4acf5f54c9a77b8b8d2535343c001b9fb48c65391a569d15df5"},"schema_version":"1.0","source":{"id":"1703.06272","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.06272","created_at":"2026-05-18T00:48:23Z"},{"alias_kind":"arxiv_version","alias_value":"1703.06272v1","created_at":"2026-05-18T00:48:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.06272","created_at":"2026-05-18T00:48:23Z"},{"alias_kind":"pith_short_12","alias_value":"XXGTM7YOBXCA","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"XXGTM7YOBXCAG7CY","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"XXGTM7YO","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:b769deaa77f7bfc9bbe8dc2ddbbefe7b7f5f06aebc84947bb1d867668debfa21","target":"graph","created_at":"2026-05-18T00:48:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"This paper studies an intelligent ultimate technique for health-monitoring and prognostic of common rotary machine components, particularly bearings. During a run-to-failure experiment, rich unsupervised features from vibration sensory data are extracted by a trained sparse auto-encoder. Then, the correlation of the extracted attributes of the initial samples (presumably healthy at the beginning of the test) with the succeeding samples is calculated and passed through a moving-average filter. The normalized output is named auto-encoder correlation-based (AEC) rate which stands for an informati","authors_text":"Guodong Wang, Radu Grosu, Ramin M. Hasani","cross_cats":["cs.NE","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-18T08:38:51Z","title":"An Automated Auto-encoder Correlation-based Health-Monitoring and Prognostic Method for Machine Bearings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.06272","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:fbc0f3958cb2bcdfd0d6cfb947b9cb92f1765005dee4b84e60df6d89c3670db9","target":"record","created_at":"2026-05-18T00:48:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"4c256231e4166809f5571a6ae3776fb4eb4625a7f0aaec820c771c0c324b9dff","cross_cats_sorted":["cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-18T08:38:51Z","title_canon_sha256":"01a8eb2fe207d4acf5f54c9a77b8b8d2535343c001b9fb48c65391a569d15df5"},"schema_version":"1.0","source":{"id":"1703.06272","kind":"arxiv","version":1}},"canonical_sha256":"bdcd367f0e0dc4037c582b00b931d4bd53757267c72504ce4f3325c1be5d37b9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bdcd367f0e0dc4037c582b00b931d4bd53757267c72504ce4f3325c1be5d37b9","first_computed_at":"2026-05-18T00:48:23.410286Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:48:23.410286Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8nYnek5/jGY84yVFY5PPcoXOsoX5cKfy67XV1lGLzxoJ7c2jGX3QOrdwqU53VPreNajsSgoXwd2vkogF2REVDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:48:23.410859Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.06272","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fbc0f3958cb2bcdfd0d6cfb947b9cb92f1765005dee4b84e60df6d89c3670db9","sha256:b769deaa77f7bfc9bbe8dc2ddbbefe7b7f5f06aebc84947bb1d867668debfa21"],"state_sha256":"d55baf6073525e0d9e55eb92600e3df274e4fe1ab44243faceaa0165b2f4fbc7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5fvI7SGQLPqh0aJQjvoittPhQpEsZCXZmDt2zSEfuJZ36Tg4SG2SpwPOLJtoXa3btSxDozieDqxtQ+QmOOK9BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T14:41:12.323277Z","bundle_sha256":"ec419a5d6f025d14270f029948f33da4e8893f55c1e4f5c8d4324aa5e019b91b"}}