{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:OPDUQJTFPLNSMGYIWZZH6MVFWG","short_pith_number":"pith:OPDUQJTF","canonical_record":{"source":{"id":"1812.07737","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-12-19T02:46:06Z","cross_cats_sorted":[],"title_canon_sha256":"deb9d7197dd7861774d229c247139957cb510503e52c2a67c6dac9c51dbe9a7a","abstract_canon_sha256":"68a478c9bd7afeac4ede0d4da1e78176a88f5c2de2241288bcb80cf2f8957227"},"schema_version":"1.0"},"canonical_sha256":"73c74826657adb261b08b6727f32a5b1b33fe3e8370dceaf36189a632f5f8acc","source":{"kind":"arxiv","id":"1812.07737","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.07737","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"arxiv_version","alias_value":"1812.07737v1","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.07737","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"pith_short_12","alias_value":"OPDUQJTFPLNS","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OPDUQJTFPLNSMGYI","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OPDUQJTF","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:OPDUQJTFPLNSMGYIWZZH6MVFWG","target":"record","payload":{"canonical_record":{"source":{"id":"1812.07737","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-12-19T02:46:06Z","cross_cats_sorted":[],"title_canon_sha256":"deb9d7197dd7861774d229c247139957cb510503e52c2a67c6dac9c51dbe9a7a","abstract_canon_sha256":"68a478c9bd7afeac4ede0d4da1e78176a88f5c2de2241288bcb80cf2f8957227"},"schema_version":"1.0"},"canonical_sha256":"73c74826657adb261b08b6727f32a5b1b33fe3e8370dceaf36189a632f5f8acc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:57:56.174085Z","signature_b64":"FefPn+K66qlJeCoh/SWw68YEAXSLVKNZgPvli+L/oMH+dWwewrQER6+KAtdwhCp/597FneZkwVXZi8gqZ3o+Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"73c74826657adb261b08b6727f32a5b1b33fe3e8370dceaf36189a632f5f8acc","last_reissued_at":"2026-05-17T23:57:56.173453Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:57:56.173453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.07737","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":"2026-05-17T23:57:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mrD0iddKj49wiBg8bEzaYvGoaCSZ2RmoONrN1QR1Pw13tg+mwghDLTKms3KDDJw5LUjYQ34028+Fo7hFK4IQCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T01:39:18.130989Z"},"content_sha256":"7c67fe3d0f63bb631a79c053e5f2eac229ef995dd9530079d4bd42661741a1bf","schema_version":"1.0","event_id":"sha256:7c67fe3d0f63bb631a79c053e5f2eac229ef995dd9530079d4bd42661741a1bf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:OPDUQJTFPLNSMGYIWZZH6MVFWG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimized Feedforward Neural Network Training for Efficient Brillouin Frequency Shift Retrieval in Fiber","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Chongyu Lu, Jialin Jiang, Richeng Zhu, Yongxiang Chen, Yongxin Liang, Zinan Wang","submitted_at":"2018-12-19T02:46:06Z","abstract_excerpt":"Artificial neural networks (ANNs) can be used to replace traditional methods in various fields, making signal processing more efficient and meeting the real-time processing requirements of the Internet of Things (IoT). As a special type of ANN, recently the feedforward neural network (FNN) has been used to replace the time-consuming Lorentzian curve fitting (LCF) method in Brillouin optical time-domain analysis (BOTDA) to retrieve the Brillouin frequency shift (BFS), which could be used as the indicator in temperature/strain sensing, etc. However, FNN needs to be re-trained if the generalizati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.07737","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":"2026-05-17T23:57:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JwtmWlTwCz/He2jrh8PulAyEd9FBVCoGbM4w4XyHoOb7I0fQtKkawSFDLOoE1qDCkFzJbb+LA2zbypO+KmcWAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T01:39:18.131371Z"},"content_sha256":"d286caef4bd35a6c548e2766feb7b10b037d81f8d7b8ca3f96cfe8c1b125775a","schema_version":"1.0","event_id":"sha256:d286caef4bd35a6c548e2766feb7b10b037d81f8d7b8ca3f96cfe8c1b125775a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OPDUQJTFPLNSMGYIWZZH6MVFWG/bundle.json","state_url":"https://pith.science/pith/OPDUQJTFPLNSMGYIWZZH6MVFWG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OPDUQJTFPLNSMGYIWZZH6MVFWG/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":"2026-06-03T01:39:18Z","links":{"resolver":"https://pith.science/pith/OPDUQJTFPLNSMGYIWZZH6MVFWG","bundle":"https://pith.science/pith/OPDUQJTFPLNSMGYIWZZH6MVFWG/bundle.json","state":"https://pith.science/pith/OPDUQJTFPLNSMGYIWZZH6MVFWG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OPDUQJTFPLNSMGYIWZZH6MVFWG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:OPDUQJTFPLNSMGYIWZZH6MVFWG","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":"68a478c9bd7afeac4ede0d4da1e78176a88f5c2de2241288bcb80cf2f8957227","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-12-19T02:46:06Z","title_canon_sha256":"deb9d7197dd7861774d229c247139957cb510503e52c2a67c6dac9c51dbe9a7a"},"schema_version":"1.0","source":{"id":"1812.07737","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.07737","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"arxiv_version","alias_value":"1812.07737v1","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.07737","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"pith_short_12","alias_value":"OPDUQJTFPLNS","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OPDUQJTFPLNSMGYI","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OPDUQJTF","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:d286caef4bd35a6c548e2766feb7b10b037d81f8d7b8ca3f96cfe8c1b125775a","target":"graph","created_at":"2026-05-17T23:57:56Z","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":"Artificial neural networks (ANNs) can be used to replace traditional methods in various fields, making signal processing more efficient and meeting the real-time processing requirements of the Internet of Things (IoT). As a special type of ANN, recently the feedforward neural network (FNN) has been used to replace the time-consuming Lorentzian curve fitting (LCF) method in Brillouin optical time-domain analysis (BOTDA) to retrieve the Brillouin frequency shift (BFS), which could be used as the indicator in temperature/strain sensing, etc. However, FNN needs to be re-trained if the generalizati","authors_text":"Chongyu Lu, Jialin Jiang, Richeng Zhu, Yongxiang Chen, Yongxin Liang, Zinan Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-12-19T02:46:06Z","title":"Optimized Feedforward Neural Network Training for Efficient Brillouin Frequency Shift Retrieval in Fiber"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.07737","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":"sha256:7c67fe3d0f63bb631a79c053e5f2eac229ef995dd9530079d4bd42661741a1bf","target":"record","created_at":"2026-05-17T23:57:56Z","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":"68a478c9bd7afeac4ede0d4da1e78176a88f5c2de2241288bcb80cf2f8957227","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-12-19T02:46:06Z","title_canon_sha256":"deb9d7197dd7861774d229c247139957cb510503e52c2a67c6dac9c51dbe9a7a"},"schema_version":"1.0","source":{"id":"1812.07737","kind":"arxiv","version":1}},"canonical_sha256":"73c74826657adb261b08b6727f32a5b1b33fe3e8370dceaf36189a632f5f8acc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"73c74826657adb261b08b6727f32a5b1b33fe3e8370dceaf36189a632f5f8acc","first_computed_at":"2026-05-17T23:57:56.173453Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:56.173453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FefPn+K66qlJeCoh/SWw68YEAXSLVKNZgPvli+L/oMH+dWwewrQER6+KAtdwhCp/597FneZkwVXZi8gqZ3o+Aw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:56.174085Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.07737","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c67fe3d0f63bb631a79c053e5f2eac229ef995dd9530079d4bd42661741a1bf","sha256:d286caef4bd35a6c548e2766feb7b10b037d81f8d7b8ca3f96cfe8c1b125775a"],"state_sha256":"517bbeaa8a89df7972b74faae540c9eed5567b8a3e479563428a02cc9264ddeb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JYN419eLI5aszz/tC+ksDCa9Cb+Rw/2wqDsxZLYvxMaNcwTCSiIlkbFsABKFYxCFit9o/f5126e7vbUcBKu5AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T01:39:18.133496Z","bundle_sha256":"747b10b72761c970b9e86971b5e4e0c78dbb584fc315926f79594b7d584e302d"}}