Extending Human Perception of Electromagnetic Radiation to the UV Region through Biologically Inspired Photochromic Fuzzy Logic (BIPFUL) Systems.

Photochromic Fuzzy Logic Systems have been designed that extend human visual perception into the UV region. The systems are founded on a detailed knowledge of the activation wavelengths and quantum yields of a series of thermally reversible photochromic compounds. By appropriate matching of the photochromic behaviour unique colour signatures are generated in response differing UV activation frequencies

What is Computational Intelligence and where is it going?

What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with ``computational intelligence'' in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary), their applications, and selected fashionable pattern recognition methods. At present CI has no comprehensive foundations and is more a bag of tricks than a solid branch of science. The change of focus from methods to challenging problems is advocated, with CI defined as a part of computer and engineering sciences devoted to solution of non-algoritmizable problems. In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions. Grand challenges on both sides of this spectrum are addressed

EMPATH: A Neural Network that Categorizes Facial Expressions

There are two competing theories of facial expression recognition. Some researchers have suggested that it is an example of "categorical perception." In this view, expression categories are considered to be discrete entities with sharp boundaries, and discrimination of nearby pairs of expressive faces is enhanced near those boundaries. Other researchers, however, suggest that facial expression perception is more graded and that facial expressions are best thought of as points in a continuous, low-dimensional space, where, for instance, "surprise" expressions lie between "happiness" and "fear" expressions due to their perceptual similarity. In this article, we show that a simple yet biologically plausible neural network model, trained to classify facial expressions into six basic emotions, predicts data used to support both of these theories. Without any parameter tuning, the model matches a variety of psychological data on categorization, similarity, reaction times, discrimination, and recognition difficulty, both qualitatively and quantitatively. We thus explain many of the seemingly complex psychological phenomena related to facial expression perception as natural consequences of the tasks' implementations in the brain

Dynamic mapping strategies for interactive art installations: an embodied combined HCI HRI HHI approach

This paper proposes a theoretical framework for dealing with the paradigm of interactivity in new media art, and how the broad use of the term in different research fields can lead to some misunderstandings. The paper addresses a conceptual view on how we can implement interaction in new media art from an embodied approach that unites views from HCI, HRI and HHI. The focus is on an intuitive mapping of a multitude of sensor data and to extend upon this using the paradigm of (1) finite state machines (FSM) to address dynamic mapping strategies, (2) mediality to address aisthesis and (3) embodiment to address valid mapping strategies originated from natural body movements. The theory put forward is illustrated by a case study