non-invasive ultrasound surgeries such as high intensity focused ultrasound have been developed to treat tumors or to stop bleeding. in this technique, incorporation of a suitable imaging modality to monitor and control the treatments is essential so several imaging methods such as x-ray, magnetic resonance imaging and ultrasound imaging have been proposed to monitor the induced thermal lesions...

The bulk of water pipes experience major degradation and deterioration problems. This research aims at estimating the condition in Shattora Shaker Al-Bahery’s distribution networks, Egypt. developed models involve training Elman neural network (ENN) feed-forward (FFNN) coupled with particle swarm optimization (PSO), genetic algorithms (GA), sine cosine algorithm (SCA), teaching-learning-based (...

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from inpu...

An artificial neural network has been used to determine the volume flux and rejections of Ca2+ , Na+ and Cl¯, as a function of transmembrane pressure and concentrations of Ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. The feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidde...

In this paper, solution of generalized matrix Riccati differential equation (GMRDE) for indefinite stochastic linear quadratic singular system is obtained using neural networks. The goal is to provide optimal control with reduced calculus effort by comparing the solutions of GMRDE obtained from well known traditional Runge Kutta (RK) method and nontraditional neural network method. To obtain th...

A system that segments and labels tabla strokes from real performances is described. Performance is evaluated on a large database taken from three performers under different recording conditions, containing a total of 16,834 strokes. The current work extends previous work by Gillet and Richard (2003) on categorizing tabla strokes, by using a larger, more diverse database that includes their dat...

Feature extraction methods and subsequent neural network performances are explored in this paper. Object recognition method ‘regionprops’ and moment invariants are used to extract basic characteristics from acquired bloodstain images. The extracted features are in return fed into a neural network for the purpose of pattern recognition. The blood drop in the image is first detected using sobel e...

Monitoring system for induction motor is widely developed to detect the incipient fault. Such system is desirable to detect the fault at the running condition to avoid the motor stop running suddenly. In this paper, a new method for detection system is proposed that emphasizes the fault occurrences as temporary short circuit in induction motor winding. The investigation of fault detection is fo...

In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...