Scaling and discriminability of perceived gloss

While much attention has been given to understanding biases in gloss perception (e.g., changes in perceived reflectance as a function of lighting, shape, viewpoint and other factors), here we investigated sensitivity to changes in surface reflectance. We tested how visual sensitivity to differences in specular reflectance varies as a function of the magnitude of specular reflectance. Stimuli consisted of renderings of glossy objects under natural illumination. Using Maximum Likelihood Difference Scaling, we created a perceptual scaling of the specular reflectance parameter of the Ward reflectance model. Then, using the Method of Constant Stimuli and a standard 2AFC procedure, we obtained psychometric functions for gloss discrimination across a range of reflectance values derived from the perceptual scale. Both methods demonstrate that discriminability is significantly diminished at high levels of specular reflectance, suggesting that gloss sensitivity depends on the magnitude of change in the image produced by different reflectance values.

Suprathreshold contrast response in normal and anomalous trichromats

Maximum Likelihood Difference Scaling was used to measure suprathreshold contrast response difference scales for low-frequency Gabor patterns modulated along luminance and L-M color directions in normal, protanomalous, and deuteranomalous observers. Based on a signal-detection model, perceptual scale values, parameterized as d′, were estimated by maximum likelihood. The difference scales were well fit by a Michaelis-Menten model, permitting estimates of response and contrast gain parameters for each subject. Anomalous observers showed no significant differences in response or contrast gain from normal observers for luminance contrast. For chromatic modulations, however, anomalous observers displayed higher contrast and lower response gain compared to normal observers. These effects cannot be explained by simple pigment shift models and support a compensation mechanism to optimize the mapping of the input contrast range to the neural response range. A linear relation between response and contrast gain suggests a neural trade-off between them.

Measurement invariance explains the universal law of generalization for psychological perception

The universal law of generalization describes how animals discriminate between alternative sensory stimuli. On an appropriate perceptual scale, the probability that an organism perceives two stimuli as similar typically declines exponentially with the difference on the perceptual scale. Exceptions often follow a Gaussian probability pattern rather than an exponential pattern. Previous explanations have been based on underlying theoretical frameworks such as information theory, Kolmogorov complexity, or empirical multidimensional scaling. This article shows that the few inevitable invariances that must apply to any reasonable perceptual scale provide a sufficient explanation for the universal exponential law of generalization. In particular, reasonable measurement scales of perception must be invariant to shift by a constant value, which by itself leads to the exponential form. Similarly, reasonable measurement scales of perception must be invariant to multiplication, or stretch, by a constant value, which leads to the conservation of the slope of discrimination with perceptual difference. In some cases, an additional assumption about exchangeability or rotation of underlying perceptual dimensions leads to a Gaussian pattern of discrimination, which can be understood as a special case of the more general exponential form. The three measurement invariances of shift, stretch, and rotation provide a sufficient explanation for the universally observed patterns of perceptual generalization. All of the additional assumptions and language associated with information, complexity, and empirical scaling are superfluous with regard to the broad patterns of perception.

Measurement invariance explains the universal law of generalization for psychological perception

The universal law of generalization describes how animals discriminate between alternative sensory stimuli. On an appropriate perceptual scale, the probability that an organism perceives two stimuli as similar typically declines exponentially with the difference on the perceptual scale. Exceptions often follow a Gaussian probability pattern rather than an exponential pattern. Previous explanations have been based on underlying theoretical frameworks such as information theory, Kolmogorov complexity, or empirical multidimensional scaling. This article shows that the few inevitable invariances that must apply to any reasonable perceptual scale provide a sufficient explanation for the universal exponential law of generalization. In particular, reasonable measurement scales of perception must be invariant to shift by a constant value, which by itself leads to the exponential form. Similarly, reasonable measurement scales of perception must be invariant to multiplication, or stretch, by a constant value, which leads to the conservation of the slope of discrimination with perceptual difference. In some cases, an additional assumption about exchangeability or rotation of underlying perceptual dimensions leads to a Gaussian pattern of discrimination, which can be understood as a special case of the more general exponential form. The three measurement invariances of shift, stretch, and rotation provide a sufficient explanation for the universally observed patterns of perceptual generalization. All of the additional assumptions and language associated with information, complexity, and empirical scaling are superfluous with regard to the broad patterns of perception.

Does the competitive orientation really lead to emphasis on different internal capabilities?

Purpose – The purpose of this paper is to investigate if the organization competitive orientation can really make firms emphasize different internal capability. This paper aims to revisit and extend the study proposed by Fleury and Fleury (2003). Design/methodology/approach – The survey instrument was employed to collect the sample composed by 163 companies from different sectors of Brazilian market. Additionally, several statistic techniques were applied such as cluster analysis, ANOVA test and hierarchical regression analysis to investigate the phenomenon. Findings – It was observed that three possible clusters can be built based on cumulative capabilities perspective and the Operation oriented group has no emphasis on production, logistic nether R & D capability, while other two clusters have a distinctive attentions on their internal capabilities. Research limitations/implications – The limitation of this research lies in using perceptual scale for performance and few constructs with one item for measuring. On the other hand, this research has revisited the taxonomy topic based on cumulative capability perspective and discussed the trade-off concepts assumed in past studies. Practical implications – This study has demonstrated the absence of systematic strategy implementation of those that are considered Operational oriented. Additionally, the authors have demonstrated that market share and customer satisfaction performance are impacted by different competitive priority as well as internal capability. Originality/value – The authors reviewed the work proposed by Fleury and Fleury (2003), and went further in proposing a taxonomy complementation suggested by them. Additionally the authors discussed the assumptions of the taxonomies that have been adopted up today and explored this issue using cumulative capabilities concept. This work is based on competitive orientations, internal capability and cumulative capabilities suggested by seminar papers.

Modulation Spectra Morphological Parameters: A New Method to Assess Voice Pathologies according to the GRBAS Scale

Disordered voices are frequently assessed by speech pathologists using perceptual evaluations. This might lead to problems caused by the subjective nature of the process and due to the influence of external factors which compromise the quality of the assessment. In order to increase the reliability of the evaluations, the design of automatic evaluation systems is desirable. With that in mind, this paper presents an automatic system which assesses the Grade and Roughness level of the speech according to the GRBAS perceptual scale. Two parameterization methods are used: one based on the classic Mel-Frequency Cepstral Coefficients, which has already been used successfully in previous works, and other derived from modulation spectra. For the latter, a new group of parameters has been proposed, named Modulation Spectra Morphological Parameters: MSC, DRB, LMR, MSH, MSW, CIL, PALA, and RALA. In methodology, PCA and LDA are employed to reduce the dimensionality of feature space, and GMM classifiers to evaluate the ability of the proposed features on distinguishing the different levels. Efficiencies of 81.6% and 84.7% are obtained for Grade and Roughness, respectively, using modulation spectra parameters, while MFCCs performed 80.5% and 77.7%. The obtained results suggest the usefulness of the proposed Modulation Spectra Morphological Parameters for automatic evaluation of Grade and Roughness in the speech.