In this study, artificial neural network was used to predict the surface tension of 20 hydrocarbon mixtures. Experimental data was divided into two parts (70% for training and 30% for testing). Optimal configuration of the network was obtained with minimization of prediction error on testing data. The accuracy of our proposed model was compared with four well-known empirical equations. The arti...

The landmark experiments by Posner in the late 1970s have shown that reaction time (RT) is faster when the stimulus appears in an expected location, as indicated by a cue; since then, the so-called Posner task has been considered a "gold standard" test of spatial attention. It is thus fundamental to understand the neural mechanisms involved in performing it. To this end, we have developed a Bay...

We introduce a novel genotype-phenotype mapping based on the relation between RNA sequence and its secondary structure for the use in evolutionary studies. Various extensive studies concerning RNA folding in the context of neutral theory yielded insights about properties of the structure space and the mapping itself. We intend to get a better understanding of some of these properties and especi...

In this paper we present a new structure capable of characterizing hand posture, as well as its movement. Topology of a self-organizing neural network determines posture, whereas its adaptation dynamics throughout time determines gesture. This adaptive character of the network allows us to avoid the correspondence problem of other methods, so that the gestures are modelled by the movement of th...

A new scheme to enhance the solution of the problems associated with Transmission line protection with Statcom connected is presented in this paper. The fault detection is carried out by using energy of the detail coefficients of the phase signals and artificial neutral network algorithm used for fault type classification and fault distance location for all the types of faults for 220 KV transm...

background: the purpose of this investigation was to compare empirically predictive ability of an artificial neu­ral network with a logistic regression in prediction of low back pain. methods: data from the second national health survey were considered in this investigation. this data in­cludes the information of low back pain and its associated risk factors among iranian people aged 15 years a...

The ability to learn from interaction with the exterior world as well as variability are two main features of living organisms. The aim of this study is to present and discuss the property of a stochastic reinforcement learning-based model of upper limb posture generation that exhibits both properties. The capacity of the model to discover suitable postures satisfying task and obstacle avoidanc...

Kim, Keehoon, "An artificial neutral network fault-diagnostic adviser for a nuclear power plant with error prediction" (1992). _he Government reserves for itself and others acting (m its behalf a ruyalty free, nonemclusive, irrew_e, worldwide license for governmental purposes to publish, the uontxacto_.

This paper presents a review of the literature on the use of artificial neutral networks in digital watermarking. Digital watermarking is a recent technology evolved to prevent illegal copy or reproduction of digital content. Different neural network based approaches have been categorized based on their applications for embedding and extracting components of watermarking.