In welded tubular joints, when the fatigue crack depth is less than 20% of chord wall thickness, the crack growing process is highly affected by weld geometry.&#10 Hence, T-butt solution and weld magnification factor (Mk) are applicable tools for evaluating the crack growth rate in this domain. In this research, the capability of Artificial Neural Network (ANN) for estimating the Mk of weld toe...

In welded tubular joints, when the fatigue crack depth is less than 20% of chord wall thickness, the crack growing process is highly affected by weld geometry. Hence, T-butt solution and weld magnification factor (Mk) are applicable tools for evaluating the crack growth rate in this domain. In this research, the capability of Artificial Neural Network (ANN) for estimating the Mk of weld toe c...

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...

hardware-implemented ANN presented framework realization: ! 2 ANN ASICs with binary neurons and analog synapses ! implementing a recurrent Perceptron model ! controlled by an FPGA (framework controller) ! trained by an evolutionary algorithm ! capabale of scaling mapping to resources desired network topology We propose a framework for hardware artificial neural networks (ANN) that allows to map...

We have investigated the use of an Artificial Neural Network (ANN) for the assessment of fall-risk (FR) in patients with different neural pathologies. The assessment integrates a clinical tool based on a wearable device (WD) with accelerometers (ACCs) and rate gyroscopes (GYROs) properly suited to identify trunk kinematic parameters that can be measured during a posturography test with differen...

background and objectives: rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. materials and met...

Procedures using Artificial Neural Networks (ANN) are developed for characterizing square microstrip antennas. A Multi-Layer Perceptron (MLP) is used to find out the resonant frequency of the antennas. Same ANN is used to accomplish the task of obtaining different important antenna characteristics like gain, return loss and bandwidth of operation at once. The developed ANN is tested experimenta...

background: although experiments on water quality are time consuming and expensive, models are often employed as supplement to simulate water quality. artificial neural network (ann) is an efficient tool in hydrologic studies, yet it cannot predetermine its results in the forms of maps and geo-referenced data. methods: in this study, ann was applied to simulate groundwater quality and geographi...