Search results for "Neural Networks"
showing 10 items of 599 documents
Theory of heterogeneous viscoelasticity
2015
We review a new theory of viscoelasticity of a glass-forming viscous liquid near and below the glass transition. In our model we assume that each point in the material has a specific viscosity, which varies randomly in space according to a fluctuating activation free energy. We include a Maxwellian elastic term and assume that the corresponding shear modulus fluctuates as well with the same distribution as that of the activation barriers. The model is solved in coherent-potential approximation (CPA), for which a derivation is given. The theory predicts an Arrhenius-type temperature dependence of the viscosity in the vanishing-frequency limit, independent of the distribution of the activatio…
The red tooth hypothesis: A computational model of predator-prey relations, protean escape behavior and sexual reproduction
2009
This paper presents an extension of the Red Queen Hypothesis (hereafter, RQH) that we call the Red Tooth Hypothesis (RTH). This hypothesis suggests that predator-prey relations may play a role in the maintenance of sexual reproduction in many higher animals. RTH is based on an interaction between learning on the part of predators and evolution on the part of prey. We present a simple predator-prey computer simulation that illustrates the effects of this interaction. This simulation suggests that the optimal escape strategy from the prey's standpoint would be to have a small number of highly reflexive, largely innate (and, therefore, very fast) escape patterns, but that would also be unlearn…
Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising
2017
[EN] The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In add…
'Niche Selection' and the evolution of a complex behavior in a changing environment--a simulation.
2000
One of the key problems in theoretical biology is the identification of the mechanisms underlying the evolution of complexity. This paper suggests that some difficulties in current models could be avoided by taking account of “niche selection” as proposed by Waddington [21] and subsequent authors [2]. Computer simulations, in which an evolving population of artificial organisms “selects” the niche(s) that maximize their fitness, are compared with a Control Model in which “Niche Selection” is absent. In the simulations the Niche Selection Model consistently produced a greater number of “fit” organisms than the Control Model; although the Niche Selection Model tended, in general, to produce o…
Design and Implementation of Deep Learning Based Contactless Authentication System Using Hand Gestures
2021
Hand gestures based sign language digits have several contactless applications. Applications include communication for impaired people, such as elderly and disabled people, health-care applications, automotive user interfaces, and security and surveillance. This work presents the design and implementation of a complete end-to-end deep learning based edge computing system that can verify a user contactlessly using &lsquo
An Embedded Fingerprints Classification System based on Weightless Neural Networks
2009
Automatic fingerprint classification provides an important indexing scheme to facilitate efficient matching in large-scale fingerprint databases in Automatic Fingerprint Identification Systems (AFISs). The paper presents a new fast fingerprint classification module implementing on embedded Weightless Neural Network (RAM-based neural network). The proposed WNN architecture uses directional maps to classify fingerprint images in the five NIST classes (Left Loop, Right Loop, Whorl, Arch and Tented Arch) without anyone enhancement phase. Starting from the directional map, the WNN architecture computes the fingerprint classification rate. The proposed architecture is implemented on Celoxica RC20…
Emotions in a cognitive architecture for human robot interactions
2004
A robot architecture is proposed in which cognitive models of emotions are modelled in terms of conceptual spaces. The architecture has been implemented in a anthropomorphic robotic hand system. Experimental results are described related to an experimental setup in which the robot system plays Rock Paper Scissor against a human opponent Copyright © 2004, American Association for Artificial Intelligence (www.aaai.org).
Empirical mode decomposition and neural network for the classification of electroretinographic data
2013
The processing of biosignals is increasingly being utilized in ambulatory situations in order to extract significant signals' features that can help in clinical diagnosis. However, this task is hampered by the fact that biomedical signals exhibit a complex behaviour characterized by strong non-linear and non-stationary properties that cannot always be perceived by simple visual examination. New processing methods need be considered. In this context, we propose to apply a signal processing method, based on empirical mode decomposition and artificial neural networks, to analyse electroretinograms, i.e. the retinal response to a light flash, with the aim to detect and classify retinal diseases…
Neural based MRAS sensorless techniques for high performance linear induction motor drives.
2010
This paper proposes a neural based MRAS (Model reference Adaptive System) speed observer suited for linear induction motors (LIM). Starting from the dynamical equation of the LIM in the synchronous reference frame in literature, the so-called voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been deduced. Then, while the inductor equations have been used as reference model of the MRAS observer, the induced part equations have been discretized and rearranged so to be represented by a linear neural network (ADALINE). On this basis, the so called TLS EXIN neuron has been used to compute on-line, in recursive form, the machi…
Factors Affecting Attrition among First Year Computer Science Students: the Case of University of Latvia
2015
<p class="R-AbstractKeywords"><span lang="EN-GB">The purpose of our study was to identify reasons for high dropout of students enrolled in the first year of the computer science study program to make it possible to determine students, who are potentially in risk. Several factors that could affect attrition, as it was originally assumed, were studied: high school grades (admission score), compensative course in high school mathematics, intermediate grades for core courses, prior knowledge of programming. However, the results of our study indicate that none of the studied factors is determinant to identify those students, who are going to abandon their studies, with great precisio…