توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱A Novel Hybrid Genetic–neural Approach for Breast Cancer Diagnosis on Dynamic Magnetic Resonance Imaging
نویسنده(ها): ، ،
اطلاعات انتشار: چهارمین کنفرانس ماشین بینایی و پردازش تصویر، سال
تعداد صفحات: ۸
A hybrid genetic–neural (GA–ANN) model was designed to differentiate malignant from benign in a group of patients with histopathologically proved breast lesions on the base of BI–RADS descriptors and data derived independently from time–intensity curve. We used a database with 117 patients' records each of which consisted of 27 quantitative parameters mostly derived from time–intensity curve, 4 BI–RADS qualitative data which determined by expert radiologist and patient age. These findings were encoded as features for a genetic algorithm (GA) as a preprocessor
for feature selection and classified with a three–layered neural network to predict the outcome of biopsy. The network was trained and tested using the jackknife method and its performance was then compared to that of the experienced radiologist in terms of sensitivity, specificity, accuracy and receiver operating characteristic curve (ROC) analysis. The network was able to classify correctly 107 of 117 original cases and
yielded a good diagnostic accuracy (91%), sensitivity (95%) and specificity (78%) compared to that of the radiologist (92%), (96%) and (78%).<\div>

۲Modeling of Anaerobic Digestion of Complex Substrates
نویسنده(ها): ، ، ، ، ، ، ،
اطلاعات انتشار: Iranian Journal of Chemistry and Chemical Engineering (IJCCE)، بيست و دوم،شماره۲(پياپي ۳۰)، ۲۰۰۳، سال
تعداد صفحات: ۱۱
A structured mathematical model of anaerobic conversion of complex organic materials in non–ideally cyclic–batch reactors for biogas production has been developed. The model is based on multiple–reaction stoichiometry (enzymatic hydrolysis, acidogenesis, acetogenesis and methanogenesis), microbial growth kinetics, conventional material balances in the liquid and gas phases for a cyclic–batch reactor, liquid–gas interactions, liquid–phase equilibrium reactions and a simple mixing model which considers the reactor volume in two separate sections: the flow–through and the retention regions. The dynamic model describes the effects of reactant’s distribution resulting from the mixing conditions, time interval of feeding, hydraulic retention time and mixing parameters on the process performance. The model is applied in the simulation of anaerobic digestion of cattle manure under different operating conditions. The model is compared with experimental data and good correlations are obtained.
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