{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:B6ELT3OCP2Z3W6LPDY4SC4NC4Z","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":"c75ef933aadcecb08eb029efdbc96a57be26abf1c220b3ffa74c55baddfece2f","cross_cats_sorted":["cs.NI","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2015-09-12T09:05:44Z","title_canon_sha256":"08c9c0c2ff3ddfb7e0c0ef17db9f9885547e9f8ea91a1467c0df053528c65992"},"schema_version":"1.0","source":{"id":"1509.03723","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1509.03723","created_at":"2026-05-18T01:33:14Z"},{"alias_kind":"arxiv_version","alias_value":"1509.03723v1","created_at":"2026-05-18T01:33:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.03723","created_at":"2026-05-18T01:33:14Z"},{"alias_kind":"pith_short_12","alias_value":"B6ELT3OCP2Z3","created_at":"2026-05-18T12:29:14Z"},{"alias_kind":"pith_short_16","alias_value":"B6ELT3OCP2Z3W6LP","created_at":"2026-05-18T12:29:14Z"},{"alias_kind":"pith_short_8","alias_value":"B6ELT3OC","created_at":"2026-05-18T12:29:14Z"}],"graph_snapshots":[{"event_id":"sha256:adbfe1b97827e3639467067af146a5b0e72e3bd40ac3a54357f1e2ef7eb25ed9","target":"graph","created_at":"2026-05-18T01:33:14Z","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":"Wireless sensor networks are widely adopted in military, civilian and commercial applications, which fuels an exponential explosion of sensory data. However, a major challenge to deploy effective sensing systems is the presence of {\\em massive missing entries, measurement noise, and anomaly readings}. Existing works assume that sensory data matrices have low-rank structures. This does not hold in reality due to anomaly readings, causing serious performance degradation. In this paper, we introduce an {\\em LS-Decomposition} approach for robust sensory data recovery, which decomposes a corrupted ","authors_text":"Linghe Kong, Meikang Qiu, Min-You Wu, Xiaodong Wang, Xiao-Yang Liu","cross_cats":["cs.NI","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2015-09-12T09:05:44Z","title":"An LS-Decomposition Approach for Robust Data Recovery in Wireless Sensor Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.03723","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:a82e7c7eaaf3b282c1cc297f3abdb178455a4b3deb3a9c6f9216123b9d9b6eea","target":"record","created_at":"2026-05-18T01:33:14Z","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":"c75ef933aadcecb08eb029efdbc96a57be26abf1c220b3ffa74c55baddfece2f","cross_cats_sorted":["cs.NI","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2015-09-12T09:05:44Z","title_canon_sha256":"08c9c0c2ff3ddfb7e0c0ef17db9f9885547e9f8ea91a1467c0df053528c65992"},"schema_version":"1.0","source":{"id":"1509.03723","kind":"arxiv","version":1}},"canonical_sha256":"0f88b9edc27eb3bb796f1e392171a2e67c784eb5b843f8818caf936fabdaeeb6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0f88b9edc27eb3bb796f1e392171a2e67c784eb5b843f8818caf936fabdaeeb6","first_computed_at":"2026-05-18T01:33:14.725649Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:33:14.725649Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"T5I+Grnr2ZHVnR2tnmipo7lJlxm6ADEVPfiEqraAgkhbRVqlIvnTfWtUWFE5Sl3rINODwZyKdaliOXUgptT/Dg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:33:14.726238Z","signed_message":"canonical_sha256_bytes"},"source_id":"1509.03723","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a82e7c7eaaf3b282c1cc297f3abdb178455a4b3deb3a9c6f9216123b9d9b6eea","sha256:adbfe1b97827e3639467067af146a5b0e72e3bd40ac3a54357f1e2ef7eb25ed9"],"state_sha256":"6ef2496ca2c6d455e1889fe8839da4551f9b7ed3ab5665b6c1e0bfd88a5bc155"}