Examples of Artificial Perceptions in Optical Character Recognition and Iris Recognition

This paper assumes the hypothesis that human learning is perception based, and consequently, the learning process and perceptions should not be represented and investigated independently or modeled in different simulation spaces. In order to keep the analogy between the artificial and human learning, the former is assumed here as being based on the artificial perception. Hence, instead of choosing to apply or develop a Computational Theory of (human) Perceptions, we choose to mirror the human perceptions in a numeric (computational) space as artificial perceptions and to analyze the interdependence between artificial learning and artificial perception in the same numeric space, using one of the simplest tools of Artificial Intelligence and Soft Computing, namely the perceptrons. As practical applications, we choose to work around two examples: Optical Character Recognition and Iris Recognition. In both cases a simple Turing test shows that artificial perceptions of the difference between two characters and between two irides are fuzzy, whereas the corresponding human perceptions are, in fact, crisp.Comment: 5th Int. Conf. on Soft Computing and Applications (Szeged, HU), 22-24 Aug 201

A Behavioural Foundation for Natural Computing and a Programmability Test

What does it mean to claim that a physical or natural system computes? One answer, endorsed here, is that computing is about programming a system to behave in different ways. This paper offers an account of what it means for a physical system to compute based on this notion. It proposes a behavioural characterisation of computing in terms of a measure of programmability, which reflects a system's ability to react to external stimuli. The proposed measure of programmability is useful for classifying computers in terms of the apparent algorithmic complexity of their evolution in time. I make some specific proposals in this connection and discuss this approach in the context of other behavioural approaches, notably Turing's test of machine intelligence. I also anticipate possible objections and consider the applicability of these proposals to the task of relating abstract computation to nature-like computation.Comment: 37 pages, 4 figures. Based on an invited Talk at the Symposium on Natural/Unconventional Computing and its Philosophical Significance, Alan Turing World Congress 2012, Birmingham, UK. http://link.springer.com/article/10.1007/s13347-012-0095-2 Ref. glitch fixed in 2nd. version; Philosophy & Technology (special issue on History and Philosophy of Computing), Springer, 201

Influence of volumetric shrinkage and curing light intensity on proximal contact tightness of class II resin composite restorations: in vitro study.

Item does not contain fulltextBACKGROUND : Proximal contact tightness of class II resin composite restorations is influenced by a myriad of factors. Previous studies investigated the role of matrix band type and thickness, consistency of resin composite, and technique of placement. However, the effect of volumetric shrinkage of resin and intensity of curing light has yet to be determined. Thus, the aim of this study was to identify the influence of these factors on the proximal contact tightness when restoring class II cavity preparations in vitro. METHODS : Sixty artificial molars were restored with either a low-shrinkage (Filtek Silorane, 3M ESPE) or a conventional (Z100, 3M ESPE) composite and polymerized with low-intensity (Smartlite IQ2, Dentsply) or high-intensity light curing units (Demi(TM), Kerr). Proximal contact tightness was measured using the Tooth Pressure Meter. Data were statistically analyzed using one-way analysis of variance and Tukey post hoc test. RESULTS : Use of low-shrinkage composite (Filtek Silorane) resulted in significantly tighter proximal contacts compared to the use of conventional composite (Z100) when cured with the same polymerization unit (p<0.001). Moreover, the low-intensity curing unit (IQ2) resulted in significantly tighter contacts than the high-intensity unit when material is constant (p<0.001). CONCLUSIONS : Low-shrinkage resin composite and low curing light intensity is associated with tighter proximal contact values