Application of canonical correlation analysis to a sensitivity study of constitutive model parameter fitting

Mandal, Subinay; Gockel, Brian T.; Rollett, Anthony D.

doi:10.1016/j.matdes.2017.06.050

Cited by 21 publications

(8 citation statements)

References 41 publications

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“…Quantitative analysis employed SPSS 25 for the exploration of the relationship between the use of formulaic sequences (frequency, proportion, and variety) and oral fluency (speed fluency, breakdown fluency, and repair fluency). Specifically, the present study employed not only Pearson correlation analysis, but also canonical correlational analysis (CCA), a statistical technique initially developed by Hotelling (1935Hotelling ( , 1936 in the 1930s, which could investigate the relationship between two sets of variables, rather than two variables (Mandel et al, 2017). This technique is comprehensive and crucial, fitting many instances (Sherry and Henson, 2005).…”

Section: Investigating the Relationshipsmentioning

confidence: 99%

The role of psycholinguistics for language learning in teaching based on formulaic sequence use and oral fluency

2022

Front. Psychol.

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Psycholinguistics has provided numerous theories that explain how a person acquires a language, produces and perceives both spoken and written language, including theories of proceduralization. Learners of English as a foreign language (hereafter referred to as EFL learners) often find it difficult to achieve oral fluency, a key construct closely related to the mental state or even mental health of learners. According to previous research, this problem could be addressed by the mastery of formulaic sequences, since the employment of formulaic sequences could often promote oral fluency in the long run, reflected in the positive relationship between formulaic sequence use and oral fluency. However, there are also findings contradicting the abovementioned ones, without adequate explanations. This study aims to explore the roles of formulaic sequences in oral fluency, taking into account the relationship between formulaic sequence use and oral fluency. This study investigated 120 pieces of spoken narratives by Chinese EFL learners, using both quantitative and qualitative methods, combined with artificial intelligence techniques. Results of canonical correlation analysis showed that the frequency of formulaic sequences was significantly related to speed fluency (r = 0.563, p = 0.000) and breakdown fluency (r = 0.360, p = 0.001), while the variety of formulaic sequences was significantly related to repair fluency (r = 0.292, p = 0.035). Case studies further demonstrated that formulaic sequences could contribute to oral fluency development by promoting speed and reducing pausing when retrieved holistically, but they sometimes lost processing advantages when retrieved and processed in a word-by-word manner. The inappropriate use of formulaic sequences also neutralized the facilitative effects of formulaic sequences on repair fluency and could mirror speakers’ occasional tendency to sacrifice repair fluency for the improvement of speed and breakdown fluency when using formulaic sequences. Pedagogical implications were provided accordingly to promote sustainable oral fluency development through the use of formulaic sequences.

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Section: Investigating the Relationshipsmentioning

confidence: 99%

The role of psycholinguistics for language learning in teaching based on formulaic sequence use and oral fluency

2022

Front. Psychol.

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“…To validate the deep learning techniques' capability for feature fusion, the feature fusion was also achieved using the CCA [40][41][42][43]. The CCA combines multiple datasets into a common representation across subjects for denoising and dimensionality reduction.…”

Section: (C) Feature Fusion For Defect Depth and 3d Mappingmentioning

confidence: 99%

Wireless power transfer-based eddy current non-destructive testing using a flexible printed coil array

Daura

Tian

et al. 2020

Phil. Trans. R. Soc. A.

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Eddy current testing (ECT) has been employed as a traditional non-destructive testing and evaluation (NDT&E) tool for many years. It has developed from single frequency to multiple frequencies, and eventually to pulsed and swept-frequency excitation. Recent progression of wireless power transfer (WPT) and flexible printed devices open opportunities to address challenges of defect detection and reconstruction under complex geometric situations. In this paper, a transmitter–receiver (Tx–Rx) flexible printed coil (FPC) array that uses the WPT approach featuring dual resonance responses for the first time has been proposed. The dual resonance responses can provide multiple parameters of samples, such as defect characteristics, lift-offs and material properties, while the flexible coil array allows area mapping of complex structures. To validate the proposed approach, experimental investigations of a single excitation coil with multiple receiving coils using the WPT principle were conducted on a curved pipe surface with a natural dent defect. The FPC array has one single excitation coil and 16 receiving (Rx) coils, which are used to measure the dent by using 21 C-scan points on the dedicated dent sample. The experimental data were then used for training and evaluation of dual resonance responses in terms of multiple feature extraction, selection and fusion for quantitative NDE. Four features, which include resonant magnitudes and principal components of the two resonant areas, were investigated for mapping and reconstructing the defective dent through correlation analysis for feature selection and feature fusion by deep learning. It shows that deep learning-based multiple feature fusion has outstanding performance for 3D defect reconstruction of WPT-based FPC-ECT. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.

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“…In recent years, different methods have been developed to identify the relative contribution of parameters in mathematical models, such as gradient algorithms, numerical methods, knowledgebased systems or artificial intelligence algorithms [e.g., [37][38][39][40][41][42] ]. Among these methods, parameter sensitivity analyzes help identify the relative importance of model parameters, including global and local sensitivity analyzes [e.g., [43][44][45][46] ]. Because the M-M-P model has twice as many parameters as the P-Z-C model, introducing a simple tool that can identify parameter groups which controls more specific aspects of model outputs is convenient.…”

Section: Introductionmentioning

confidence: 99%

Inspection of two sophisticated models for sand based on generalized plasticity: Monotonic loading and Monte Carlo analysis

Yeh

Tafili

Prada-Sarmiento

et al. 2022

Num Anal Meth Geomechanics

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The generalized plasticity theory has evolved in the last decades and attracts the attention of different research groups, because of characteristics like the absence of an explicit flow surface formulation. This paper presents a detailed inspection of two sophisticated constitutive models for granular soils under monotonic loading: the Pastor‐Zienkiewicz‐Chan (P‐Z‐C) model[1] and the Manzanal‐Merodo‐Pastor (M‐M‐P) model.[2] Even though they are similar in mathematical framework, the P‐Z‐C model requires only eight parameters compared to the M‐M‐P model which requires 18 parameters to describe the material behavior under monotonic loading. Parameters of both models were calibrated based on the extensive experimental database available for monotonic triaxial tests performed on Karlsruhe fine sand by Wichtmann et al.[3] An objective discussion addressing the strengths and weaknesses of each model is presented. Finally, a procedure to identify the most relevant parameters that control different elements in the model like the stiffness, the evolution of dilatancy or the hardening variables is introduced, using the Monte Carlo Toolbox (MCAT) for simulations. Some interesting inferences could be obtained, like the conclusion that the MCAT is a helpful tool for identifying material parameters and their interaction, but it cannot replace the human factor, the experience and objective judgement of the modeller for the calibration of constitutive models.

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Application of canonical correlation analysis to a sensitivity study of constitutive model parameter fitting

Cited by 21 publications

References 41 publications

The role of psycholinguistics for language learning in teaching based on formulaic sequence use and oral fluency

The role of psycholinguistics for language learning in teaching based on formulaic sequence use and oral fluency

Wireless power transfer-based eddy current non-destructive testing using a flexible printed coil array

Inspection of two sophisticated models for sand based on generalized plasticity: Monotonic loading and Monte Carlo analysis

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