Introduction This study is an effort to diagnose breast cancer by processing the quantitative and qualitative information obtained from medical infrared imaging. The medical infrared imaging is free from any harmful radiation and it is one of the best advantages of the proposed method. By analyzing this information, the best diagnostic parameters among the available parameters are selected and ...

The paper deals with Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN). We believe that solving for the DEA efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. In this paper, a new neural network model is used to estimate the inefficiency of DMUs in large datasets.

background: one issue of concern in water supply is the quality of water. measuring the qualitative parameters of water is time-consuming and costly. predicting these parameters using various models leads to a reduction in related expenses and the presentation of overall and comprehensive statistics for water resource management. methods: the present study used an artificial neural network (ann...

gas hydrates are a costly problem when they plug oil and gas pipelines. the best way to determine the hft and pressure is to measure these conditions experimentally for every gas system. since this is not practical in terms of time and money, correlations are the other alternative tools. there are a small number of correlations for specific gravity method to predict the hydrate formation. as th...

one of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. in this regard, there have many models developed, proposing better management in order to maintain water quality. most of these models require input parameters that are either hardly available or time-consuming and expensive to...

a neural network is developed for the determination of leaky confined aquifer parameters. leakage into the aquifer takes place from the storage in the confining aquitard. the network is trained for the well function of leaky confined aquifers by the back propagation technique and adopting the levenberg–marquardt optimization algorithm. by applying the principal component analysis (pca) on the a...

drying characteristics of green pea (pisum satium) with an initial moisture content of 76% (db) was studied in a fluidized bed dryer assisted by microwave heating. four drying air temperatures (30, 40, 50 and 60ºc) and five microwave powers (180, 360, 540, 720 and 900w) were adopted. several experiments were conducted to obtain data for sample moisture content versus drying time. the results sh...

conclusions lead contamination in the presence of an emf exacerbates the oxidative damage to plasma proteins as well as the conformational changes in hb. an artificial neural network can be used as a predictive tool for the oxidative danger posed to workers in industrial fields, battery manufacturing companies, and power plants. patients and methods in this experimental study, the blood samples...

in this study, an artificial neural network was developed in order to analyze flexible pavement structure anddetermine its critical responses under the influence of standard axle loading. in doing so, more than 10000four-layered flexible pavement sections composed of asphalt concrete layer, base layer, subbase layer, andsubgrade soil were analyzed under the impact of standard axle loading. pave...

objective: social anxiety disorder (sad) is defined as a constant fear of being embarrassed or negatively evaluated in social situations or while doing activities in the presence of others. several studies have examined the role of certain variables that might predict response to treatment and may affect treatment outcome. the purpose of this study was to identify predictive variables of change...