This paper aimed to introduce a real-time reactive power controller based on artificial neural network. A feedforward employing back-propagation was used as training algorithm. The inputs to the ANN were real and reactive power of each load. The targets were to switch ON/OFF the capacitors during normal and abnormal conditions. The network was trained and the weights corresponded to minimum (MS...

Perturbations of the Kerr black hole in the class of axisymmetric artificial black holes. Abstract Artificial black holes (called also acoustic or optical black holes) are the black holes for the linear wave equation describing the wave propagation in a moving medium. They attracted a considerable interest of physicists who study them to better understand the black holes in general relativity. ...

Brain tumor is one of the major reasons of death among people. It is indication that the chances of survival can be greater than before if the tumor is detected correctly at its early stage. This paper classifies the type of tumor using Artificial Neural Network (ANN) in MRI images of different patients with Astrocytoma type of brain tumor. The extraction of texture features in the detected tum...

Artificial talkers and speech synthesis systems have long been used as a means of understanding both speech production and speech perception. The development of an airway modulation model is described that simulates the time-varying changes of the glottis and vocal tract, as well as acoustic wave propagation, during speech production. The result is a type of artificial talker that can be used t...

In this paper propagation properties of a parallel-plate waveguide with tunable artificial impedance surfaces as sidewalls are studied both analytically and numerically. The impedance surfaces comprise an array of patches over a dielectric slab with embedded metallic vias. The tunability of surfaces is achieved with varactors. Simple design equations for tunable artificial impedance surfaces ar...

Resumen. En este trabajo se llevó a cabo una caracterización de sujetos vulnerables en el Sistema de Asistencia Alimentaria del DIF del Estado de Guanajuato, esto aplicando algoritmos de agrupamiento. La segmentación se realizó con la información del Padrón 2013-2014. Se aplicó un proceso de limpieza y normalización de los datos. Además se creó un vector de caracteŕısticas, al cual se le aplica...

Accurate prediction of future stock market prices is of great importance to traders. The process can be automated using artificial neural networks. However, the conventional backward propagation of errors algorithm commonly used for training the networks suffers from the local minima problem. This study investigates whether investing more computational resources into training an artificial neur...

Throughout much of the history of biology, the cell membrane was functionally defined as a semi-permeable barrier separating aqueous compartments, and an anchoring site for proteins. Little attention was devoted to its possible regulatory role in intracellular molecular processes and neuron electrical signaling. This article reviews the history of membrane studies and the current state of the a...

In this paper, we analyze the multi-transmitting formula (MTF) proposed by Liao et al [19]. From the computed reflection coefficients for the fully discrete MTF boundary conditions, we suggest choices for the artificial wave propagation speed, which are different from Liao’s original choice. Theoretical and numerical studies for various incidence angles demonstrate that the suggested choices ef...

In this paper, vapor pressure for pure compounds is estimated using the Artificial Neural Networks and a simple Group Contribution Method (ANN–GCM). For model comprehensiveness, materials were chosen from various families. Most of materials are from 12 families. Vapor pressure data of 100 compounds is used to train, validate and test the ANN-GCM model. Va...