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In this research, a computational model that simulates the mental function of multicolor aesthetic evaluation through backpropagation neural networks was constructed. Helmut Leder's psychological model served as the theoretical framework. We determined the macro‐architecture of the computational model through two psychological experiments using the semantic differential (SD) method. The aesthetic score of a multicolor stimulus is defined as the inverse of its factor score on the factor “Pleasure” extracted in the first experiment, and each of the three factors extracted in the second experiment—i.e., “Stability,” “Heaviness,” and “Presence”—is regarded as a simple perceptual feature. The genetic algorithm was then employed to optimize the hidden layer node number, the learning rate, and the momentum constant of each neural network. In two simulation tests, this computational model exhibited some predictive power, implying that the model can be regarded as a relatively successful approximation of the psychological mechanism of multicolor aesthetic evaluation. In addition, the results of the second simulation also show that the perceptual feature “Heaviness” possesses the principal impact on the aesthetic evaluation of multicolor objects, whereas the other two perceptual features “Stability” and “Presence” have a minor influence. The heavier and/or more stable a multicolor object is perceived to be, the less aesthetically pleasing it is. Conversely, the stronger the sense of matter presence a multicolor object elicits, the more aesthetically appealing it is. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 216–235, 2017

This research aims to clarify the universal rules of the sense of beauty to multi-color stimuli by establishing a computational model specifying the relationships between the initial color information of multi-color stimuli and the aesthetic evaluation. In order to obtain the empirical data based on which the future computational system can be established, two psychological experiments have been conducted using Semantic Differential method. The design of the experiments is based on Leder's psychological model. In Experiment I, three factors, namely "Pleasure", "Activity" and "Potency", are extracted. The aesthetic evaluation values for every stimulus are defined as their factor scores (inverse) on Pleasure factor. In Experiment II, five factors, namely "Vividness", "Complexity", "Gentleness", "Strength" and "Wetness", are extracted. Each of them is regarded as corresponding to a simple visual feature.

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Shearography is a coherent optical technique that allows the identification of the first derivative of deformation in the shearing direction. Due to direct measuring strain information, shearography is suited for non-destructive testing and evaluation (NDT/NDE). However, if there is a small defect parallel to the shearing direction, the first derivative of deformation in the direction has no noticeable change, and the defect is not visible. Therefore, the development of a shearography system with dual-directional simultaneous measurement of the first derivatives of deformation both in x- and y-directions is highly demanded in the field of NDT/NDE. It is suited to inspect complicated defects, such as long and narrow slots, microcracks, etc. This paper presents a review of shearography for different dual-directional systems developed in the last two decades. After a brief overview of shearography, the paper will display two dual-directional shearographic techniques—temporal phase-shift (TPS) and spatial phase-shift (SPS) methods. TPS dual-shearing systems are suited for static measurements, while the SPS dual-shearing systems are useful for dynamic measurements. The basic theories, optical layouts, and comparisons are presented. The advantages and disadvantages of practical applications are discussed.