{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T21:13:18Z","timestamp":1778101998157,"version":"3.51.4"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T00:00:00Z","timestamp":1777852800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.engappai.2026.114778","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T09:17:53Z","timestamp":1776417473000},"page":"114778","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P2","title":["Probabilistic reliability modeling and soft-error tolerance for neuromorphic spiking neural networks in high-flux radiation environments"],"prefix":"10.1016","volume":"176","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0393-228X","authenticated-orcid":false,"given":"Sylvester","family":"Kaczmarek","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.engappai.2026.114778_b1","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1109\/TDSC.2004.2","article-title":"Basic concepts and taxonomy of dependable and secure computing","volume":"1","author":"Avizienis","year":"2004","journal-title":"IEEE Trans. Dependable Secur. Comput."},{"key":"10.1016\/j.engappai.2026.114778_b2","series-title":"BrainChip Second-Generation Platform Brief","author":"BrainChip Inc","year":"2023"},{"issue":"1","key":"10.1016\/j.engappai.2026.114778_b3","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/MM.2018.112130359","article-title":"Loihi: A neuromorphic manycore processor with on-chip learning","volume":"38","author":"Davies","year":"2018","journal-title":"IEEE Micro"},{"issue":"3","key":"10.1016\/j.engappai.2026.114778_b4","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1109\/TNS.2003.813129","article-title":"Basic mechanisms and modeling of single-event upset in digital microelectronics","volume":"50","author":"Dodd","year":"2003","journal-title":"IEEE Trans. Nucl. Sci."},{"key":"10.1016\/j.engappai.2026.114778_b5","series-title":"Spiking Neuron Models: Single Neurons, Populations, Plasticity","author":"Gerstner","year":"2002"},{"key":"10.1016\/j.engappai.2026.114778_b6","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1007\/s11214-013-9964-y","article-title":"AE9, AP9 and SPM: New models for specifying the trapped energetic particle and space plasma environment","volume":"179","author":"Ginet","year":"2013","journal-title":"Space Sci. Rev."},{"key":"10.1016\/j.engappai.2026.114778_b7","series-title":"Proceedings of the 33rd ACM International Conference on Multimedia","first-page":"5461","article-title":"Motion matters: Motion-guided modulation network for skeleton-based micro-action recognition","author":"Gu","year":"2025"},{"key":"10.1016\/j.engappai.2026.114778_b8","series-title":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"387","article-title":"Detecting spacecraft anomalies using LSTMs and nonparametric dynamic thresholding","author":"Hundman","year":"2018"},{"key":"10.1016\/j.engappai.2026.114778_b9","series-title":"Implementing spiking neural networks on neuromorphic architectures: A review","author":"Huynh","year":"2022"},{"key":"10.1016\/j.engappai.2026.114778_b10","series-title":"Neuromorphic computing and sensing in space","author":"Izzo","year":"2022"},{"key":"10.1016\/j.engappai.2026.114778_b11","unstructured":"Kaczmarek, S., 2025a. A Bio-Inspired Hierarchical Temporal Defense for Securing Spiking Neural Networks Against Physical and Adversarial Perturbations. In: Workshop on Machine Learning and the Physical Sciences At NeurIPS 2025."},{"key":"10.1016\/j.engappai.2026.114778_b12","series-title":"Cislunar anomaly and risk dataset (CARD) for spacecraft threats","author":"Kaczmarek","year":"2025"},{"key":"10.1016\/j.engappai.2026.114778_b13","series-title":"2015 IEEE 14th International Conference on Machine Learning and Applications","first-page":"38","article-title":"Evaluating real-time anomaly detection algorithms \u2013 The numenta anomaly benchmark","author":"Lavin","year":"2015"},{"key":"10.1016\/j.engappai.2026.114778_b14","doi-asserted-by":"crossref","unstructured":"Li, K., Liu, P., Guo, D., Wang, F., Wu, Z., Fan, H., Wang, M., 2025. MMAD: Multi-label Micro-Action Detection in Videos. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. ICCV, pp. 13225\u201313236.","DOI":"10.1109\/ICCV51701.2025.01229"},{"key":"10.1016\/j.engappai.2026.114778_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2026.102315","article-title":"Integrated scheduling of cargo vessels, research vessels, and marine experiments in multifunctional ports using Q-learning enhanced PSO","volume":"102","author":"Li","year":"2026","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.engappai.2026.114778_b16","series-title":"Advances in Neural Information Processing Systems 35","article-title":"Toward robust spiking neural network against adversarial perturbation","author":"Liang","year":"2022"},{"issue":"9","key":"10.1016\/j.engappai.2026.114778_b17","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.1016\/S0893-6080(97)00011-7","article-title":"Networks of spiking neurons: The third generation of neural network models","volume":"10","author":"Maass","year":"1997","journal-title":"Neural Netw."},{"key":"10.1016\/j.engappai.2026.114778_b18","series-title":"A survey examining neuromorphic architecture in space and challenges from radiation","author":"Naoukin","year":"2023"},{"key":"10.1016\/j.engappai.2026.114778_b19","series-title":"Mitigating In-Space Charging Effects: NASA Handbook (NASA-HDBK-4002B)","author":"National Aeronautics and Space Administration","year":"2022"},{"key":"10.1016\/j.engappai.2026.114778_b20","series-title":"Badhwar\u2013O\u2019Neill 2014 Galactic Cosmic Ray Flux Model Description","author":"O\u2019Neill","year":"2015"},{"key":"10.1016\/j.engappai.2026.114778_b21","series-title":"Proceedings of the 59th ACM\/IEEE Design Automation Conference","first-page":"151","article-title":"SoftSNN: Low-cost fault tolerance for spiking neural network accelerators under soft errors","author":"Putra","year":"2022"},{"key":"10.1016\/j.engappai.2026.114778_b22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2024\/3616902","article-title":"Overview on radiation damage effects and protection techniques in microelectronic devices","volume":"2024","author":"Ren","year":"2024","journal-title":"Sci. Technol. Nucl. Installations"},{"key":"10.1016\/j.engappai.2026.114778_b23","doi-asserted-by":"crossref","first-page":"85748","DOI":"10.1109\/ACCESS.2021.3085136","article-title":"Neutron-induced, single-event effects on neuromorphic event-based vision sensor: A first step and tools to space applications","volume":"9","author":"Roffe","year":"2021","journal-title":"IEEE Access"},{"issue":"12","key":"10.1016\/j.engappai.2026.114778_b24","doi-asserted-by":"crossref","first-page":"2205","DOI":"10.2514\/1.G004862","article-title":"Runtime assurance for autonomous aerospace systems","volume":"43","author":"Schierman","year":"2020","journal-title":"J. Guid. Control Dyn."},{"key":"10.1016\/j.engappai.2026.114778_b25","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1038\/s43588-021-00184-y","article-title":"Opportunities for neuromorphic computing algorithms and applications","volume":"2","author":"Schuman","year":"2022","journal-title":"Nat. Comput. Sci."},{"issue":"6","key":"10.1016\/j.engappai.2026.114778_b26","doi-asserted-by":"crossref","first-page":"2570","DOI":"10.1109\/TNS.2015.2495130","article-title":"Soft error rate improvements in 14-nm technology featuring second-generation 3D tri-gate transistors","volume":"62","author":"Seifert","year":"2015","journal-title":"IEEE Trans. Nucl. Sci."},{"key":"10.1016\/j.engappai.2026.114778_b27","series-title":"Computer Vision \u2013 ECCV 2020","first-page":"399","article-title":"Inherent adversarial robustness of deep spiking neural networks: Effects of discrete input encoding and non-linear activations","author":"Sharmin","year":"2020"},{"key":"10.1016\/j.engappai.2026.114778_b28","series-title":"Dynamic reliability management in neuromorphic computing","author":"Song","year":"2021"},{"key":"10.1016\/j.engappai.2026.114778_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.euromechflu.2025.204395","article-title":"Prolonging the life time of underground ice ring formed in the period of the cryogenic gas storage","volume":"115","author":"Turkyilmazoglu","year":"2026","journal-title":"Eur. J. Mech. B Fluids"},{"issue":"6","key":"10.1016\/j.engappai.2026.114778_b30","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.1109\/23.903784","article-title":"Predicting error rate for microprocessor-based digital architectures through C.E.U. (Code Emulating Upsets) injection","volume":"47","author":"Velazco","year":"2000","journal-title":"IEEE Trans. Nucl. Sci."},{"key":"10.1016\/j.engappai.2026.114778_b31","series-title":"2021 International Joint Conference on Neural Networks","article-title":"CarSNN: An efficient spiking neural network for event-based autonomous cars on the Loihi neuromorphic research processor","author":"Viale","year":"2021"},{"key":"10.1016\/j.engappai.2026.114778_b32","series-title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","first-page":"2063","article-title":"Drafting and revision: Advancing high-fidelity video inpainting","author":"Wu","year":"2025"},{"key":"10.1016\/j.engappai.2026.114778_b33","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"6180","article-title":"WaveFormer: Wavelet transformer for noise-robust video inpainting","volume":"Vol. 38","author":"Wu","year":"2024"},{"key":"10.1016\/j.engappai.2026.114778_b34","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121471","article-title":"Applications of chaotic quantum adaptive satin bower bird optimizer algorithm in berth-tugboat-quay crane allocation optimization","volume":"237","author":"Yang","year":"2024","journal-title":"Expert Syst. Appl."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626010602?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626010602?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T20:26:36Z","timestamp":1778099196000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626010602"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":34,"alternative-id":["S0952197626010602"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114778","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Probabilistic reliability modeling and soft-error tolerance for neuromorphic spiking neural networks in high-flux radiation environments","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114778","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"114778"}}