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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/30165
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DC FieldValueLanguage
dc.contributor.authorAlsadi N-
dc.contributor.authorGadsden SA-
dc.contributor.authorYawney J-
dc.contributor.editorWysocki BT-
dc.contributor.editorHolt J-
dc.contributor.editorBlowers M-
dc.date.accessioned2024-09-08T17:48:02Z-
dc.date.available2024-09-08T17:48:02Z-
dc.date.issued2023-06-15-
dc.identifier.isbn978-1-5106-6200-1-
dc.identifier.issn0277-786X-
dc.identifier.issn1996-756X-
dc.identifier.urihttp://hdl.handle.net/11375/30165-
dc.description.abstractBlockchain technology has gained notoriety as the foundation for cryptocurrencies like Bitcoin. However, its possibilities go well beyond that, enabling the deployment of new applications that were not previously feasible as well as enormous improvements to already existing technological applications. Several factors impacting the consensus mechanism must fall within a specific range for a blockchain network to be efficient, sustainable and secure. The long-term sustainability of current networks, like Bitcoin, is in jeopardy due to their relatively uncompromising reconfiguration, which tends to be inflexible, and somewhat independent of environmental circumstances. To provide a systematic methodology for integrating a sustainable and secure adaptive framework, we propose the amalgamation of cognitive dynamic systems theory with blockchain technology, specifically regarding variant network difficulty. A respective architecture was designed with the employment of Long-Short Term Memory (LSTM) to control the difficulty of a network with Proof-of-Work Consensus.-
dc.publisherSPIE, the international society for optics and photonics-
dc.rights.uri7-
dc.subject40 Engineering-
dc.subject4006 Communications Engineering-
dc.subject4009 Electronics, Sensors and Digital Hardware-
dc.subject51 Physical Sciences-
dc.subject5102 Atomic, Molecular and Optical Physics-
dc.subjectBehavioral and Social Science-
dc.subject8 Decent Work and Economic Growth-
dc.titleA cognitive dynamics framework for practical blockchain applications-
dc.typeArticle-
dc.date.updated2024-09-08T17:48:01Z-
dc.contributor.departmentMechanical Engineering-
dc.rights.licenseAttribution-NonCommercial-NoDerivs - CC BY-NC-ND-
dc.identifier.doihttps://doi.org/10.1117/12.2664067-
Appears in Collections:Mechanical Engineering Publications

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