Matches in SemOpenAlex for { <https://semopenalex.org/work/W4379616005> ?p ?o ?g. }
Showing items 1 to 88 of
88
with 100 items per page.
- W4379616005 endingPage "106552" @default.
- W4379616005 startingPage "106552" @default.
- W4379616005 abstract "Infrared video (in mathematics terms, tensor) has been widely used in the tensile testing of metallic materials, such as titanium alloy and steel. The infrared video of the tensile testing process can effectively and efficiently determine the properties of metallic materials, e.g., Young’s modulus, Poisson’s ratio, yield strength, etc. The infrared video with structural properties, such as smoothness and sparsity, can be used to characterize the tensile testing process. To extract the features in the infrared video with structural properties, we propose a multi-layer additive tensor decomposition (MLATD) method based on regularization tensor regression for tensile testing. It decomposes a tensor into three classes of components: the multi-smooth layers (including background and foreground), the sparse layers (including between-tensor and in-tensor), and the noise layer. The scree plot is proposed to determine the number of multi-smooth layers, which is a downward curve of the difference between the smooth layers and the sparse layer. The alternating direction method of multipliers (ADMM) algorithm is proposed to solve the proposed method. The decomposition results of the simulation data and real-world case study revealed that the proposed method outperforms the existing state-of-the-art methods." @default.
- W4379616005 created "2023-06-08" @default.
- W4379616005 creator A5008245852 @default.
- W4379616005 creator A5060165452 @default.
- W4379616005 creator A5077025758 @default.
- W4379616005 creator A5078245071 @default.
- W4379616005 date "2023-09-01" @default.
- W4379616005 modified "2023-09-26" @default.
- W4379616005 title "Multi-layer additive tensor decomposition of infrared video for titanium alloy tensile testing" @default.
- W4379616005 cites W1963826206 @default.
- W4379616005 cites W1988637231 @default.
- W4379616005 cites W2000752749 @default.
- W4379616005 cites W2024165284 @default.
- W4379616005 cites W2089468765 @default.
- W4379616005 cites W2133665775 @default.
- W4379616005 cites W2142234851 @default.
- W4379616005 cites W2145962650 @default.
- W4379616005 cites W2342910067 @default.
- W4379616005 cites W2588612844 @default.
- W4379616005 cites W2617488912 @default.
- W4379616005 cites W2734129016 @default.
- W4379616005 cites W2898713328 @default.
- W4379616005 cites W2964214749 @default.
- W4379616005 cites W3021020015 @default.
- W4379616005 cites W3024295828 @default.
- W4379616005 cites W3083836106 @default.
- W4379616005 cites W3096244810 @default.
- W4379616005 cites W3123204155 @default.
- W4379616005 cites W3216343031 @default.
- W4379616005 cites W4244393449 @default.
- W4379616005 doi "https://doi.org/10.1016/j.engappai.2023.106552" @default.
- W4379616005 hasPublicationYear "2023" @default.
- W4379616005 type Work @default.
- W4379616005 citedByCount "0" @default.
- W4379616005 crossrefType "journal-article" @default.
- W4379616005 hasAuthorship W4379616005A5008245852 @default.
- W4379616005 hasAuthorship W4379616005A5060165452 @default.
- W4379616005 hasAuthorship W4379616005A5077025758 @default.
- W4379616005 hasAuthorship W4379616005A5078245071 @default.
- W4379616005 hasConcept C100906024 @default.
- W4379616005 hasConcept C105795698 @default.
- W4379616005 hasConcept C112950240 @default.
- W4379616005 hasConcept C120665830 @default.
- W4379616005 hasConcept C121332964 @default.
- W4379616005 hasConcept C149505630 @default.
- W4379616005 hasConcept C155281189 @default.
- W4379616005 hasConcept C158355884 @default.
- W4379616005 hasConcept C159985019 @default.
- W4379616005 hasConcept C192562407 @default.
- W4379616005 hasConcept C2524010 @default.
- W4379616005 hasConcept C2986737658 @default.
- W4379616005 hasConcept C33923547 @default.
- W4379616005 hasConcept C41008148 @default.
- W4379616005 hasConceptScore W4379616005C100906024 @default.
- W4379616005 hasConceptScore W4379616005C105795698 @default.
- W4379616005 hasConceptScore W4379616005C112950240 @default.
- W4379616005 hasConceptScore W4379616005C120665830 @default.
- W4379616005 hasConceptScore W4379616005C121332964 @default.
- W4379616005 hasConceptScore W4379616005C149505630 @default.
- W4379616005 hasConceptScore W4379616005C155281189 @default.
- W4379616005 hasConceptScore W4379616005C158355884 @default.
- W4379616005 hasConceptScore W4379616005C159985019 @default.
- W4379616005 hasConceptScore W4379616005C192562407 @default.
- W4379616005 hasConceptScore W4379616005C2524010 @default.
- W4379616005 hasConceptScore W4379616005C2986737658 @default.
- W4379616005 hasConceptScore W4379616005C33923547 @default.
- W4379616005 hasConceptScore W4379616005C41008148 @default.
- W4379616005 hasFunder F4320321540 @default.
- W4379616005 hasFunder F4320335777 @default.
- W4379616005 hasLocation W43796160051 @default.
- W4379616005 hasOpenAccess W4379616005 @default.
- W4379616005 hasPrimaryLocation W43796160051 @default.
- W4379616005 hasRelatedWork W2067778584 @default.
- W4379616005 hasRelatedWork W2079143197 @default.
- W4379616005 hasRelatedWork W2236011088 @default.
- W4379616005 hasRelatedWork W2354203570 @default.
- W4379616005 hasRelatedWork W2376099902 @default.
- W4379616005 hasRelatedWork W2385554864 @default.
- W4379616005 hasRelatedWork W2795266391 @default.
- W4379616005 hasRelatedWork W2899084033 @default.
- W4379616005 hasRelatedWork W3032645088 @default.
- W4379616005 hasRelatedWork W4285005749 @default.
- W4379616005 hasVolume "124" @default.
- W4379616005 isParatext "false" @default.
- W4379616005 isRetracted "false" @default.
- W4379616005 workType "article" @default.