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, we see that under each type of prior inputs,
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PRNI 2015 paper, to appear in IEEE proceedings (image processing)
Micro-expressions are unconscious, faint, short-lived expressions that appear on the faces. It can make people's understanding of psychological state and emotion more accurate. Therefore, micro-expression recognition is particularly important in psychotherapy and clinical diagnosis, which has been widely studied by researchers for the past decades....
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... ∆L ν < 2) the simplest model is chosen according to the principle of parsimony. Formulas to calculate the L ν − measure for SEM with ordinal data can be found in Li and Yang (2011);Song et al. (2011). ...
Even in well-studied organisms, it is often challenging to uncover the social and environmental determinants of fitness. Typically, fitness is determined by a variety of factors that act in concert, thus forming complex networks of causal relationships. Moreover, even strong correlations between social and environmental conditions and fitness components may not be indicative of direct causal links, as the measured variables may be driven by unmeasured (or unmeasurable) causal factors. Standard statistical approaches, like multiple regression analyses, are not suited for disentangling such complex causal relationships. Here, we apply structural equation modeling (SEM), a technique that is specifically designed to reveal causal relationships between variables, and which also allows to include hypothetical causal factors. Therefore, SEM seems ideally suited for comparing alternative hypotheses on how fitness differences arise from differences in social and environmental factors. We apply SEM to a rich data set collected in a long-term study on the Seychelles warbler (Acrocephalus sechellensis), a bird species with facultatively cooperative breeding and a high rate of extra-group paternity. Our analysis reveals that the presence of helpers has a positive effect on the reproductive output of both female and male breeders. In contrast, per capita food availability does not affect reproductive output. Our analysis does not confirm earlier suggestions on other species that the presence of helpers has a negative effect on the reproductive output of male breeders. As such, both female and male breeders should tolerate helpers in their territories, irrespective of food availability.
... The values in this approach, nevertheless, are based on a userdefined threshold. By examining the largest relative variation value of the center variables inside a window, Li and Yang [10] employed a location-based high selection methodology to effectively identify those kinds of data inputs that are probable to integrate important data. Even though this technique has been shown to be superior to the pyramid-based approach, it has the drawback of treating the wavelet transform of both the low-and high-frequency regions in the same manner. ...
This research focuses of the efficacious wavelet-based methodology for clinical image fusion that is established by considering the human visual system, including the physical effects of the wavelet coefficients. Once the clinical images that have to be fused have been decomposed via the transforms of wavelet, different systems of fusion for integrating these coefficients are projected. The coefficients in the lower frequencies are chosen with the visibility-centered system, and those coefficients with the highest frequency bands are chosen using the variance-oriented approach. To effective mitigate the issue of noise and guarantee homogeneity of an image, which is being fused, coefficients are typically done based on the application of the window-centered verification process. The images are lastly structured using the inverse wavelet transforms with the composite coefficient. To effectively assess and effectively prove the effective applicability of the proposed methodology, experimentation series and comparison of the fusion approaches are done. The results of the experimentation on the real and simulated clinical images show that the projected approach is effective and is capable of yielding the proposed results of the fusion process.
This paper is designed to give a complete overview of the literature that is available, as it relates to application of the Bayesian analysis model to investigate multiple group nonlinear structural equation models, also known as SEMs, including those having ordered categorical, dichotomous and categorical-dichotomous mixed variables. It will also work to summarize Bayesian multiple group nonlinear SEMs with nonlinear covariate variables, and latent variables in the structural model and both linear covariant and latent variable sin the measurement models. More specifically, it will be suggested that using hidden continuous normal distribution, including both right and left censoring and truncation, and interval censoring and truncation, can improve the Bayesian approach to multiple group nonlinear structural equation models when solving problems using ordered categorical and dichotomous data.
In this paper, dichotomous variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical inferences, which involve estimation of parameters and their standard deviations, and residuals analysis for testing the selected model, are discussed. Hidden continuous normal distribution (censored normal distribution) is used to solve the problem of dichotomous variables. The proposed procedure is illustrated by a simulation data obtained from R program. Analyses are done by using R2WinBUGS package in R-program.
