The paper addresses features extraction of sensor data for robot behavior learning using factor analysis. Redundancies in sensor types and quantities are common in sensing competence of robots. The redundancies cause the high dimensionality of the perceptual space. It is impractical to incorporate all available sensor information in decision-making and learning of robots due to the huge memory ...

The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth...

Traditional and modern vocabulary instruction techniques have been introduced in the past few decades to improve the learners’ performance in reading comprehension. Semantic mapping, which entails drawing learners’ attention to the interrelationships among lexical items through graphic organizers, is claimed to enhance vocabulary learning significantly. However, whether this technique suits all...

Representational views of the mind traditionally face a skeptical challenge on perceptual knowledge: if our experience of the world is mediated by representations built upon perceptual inputs, how can we be certain that our representations are accurate and our perceptual apparatus reliable? J. J. Gibson's ecological approach provides an alternative framework, according to which direct perceptio...

OBJECTIVES To review research on perceptual accuracy in pediatric asthma and diabetes and to provide recommendations for future research efforts and clinical applications of the construct in these populations. METHODS A literature search was conducted using Medline and PsychInfo databases as well as the bibliographies of relevant articles. RESULTS Children and adolescents with asthma or dia...

A new feature extraction model, generalized perceptual linear prediction (gPLP), is developed to calculate a set of perceptually relevant features for digital signal analysis of animal vocalizations. The gPLP model is a generalized adaptation of the perceptual linear prediction model, popular in human speech processing, which incorporates perceptual information such as frequency warping and equ...