Yazar "Saritaş I." seçeneğine göre listele

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    Diagnosis modelling of urethral obstructions using fuzzy expert system
    (2008) Zühtüoğulları, Kürşat; Saritaş I.; Arikan N.
    The aim of this study is to help the doctors for diagnosis process of urinary system illnesses that causes obstruction in the urethra and the bladder. There are several reasons that cause obstructions in the urinary system. The common causes of these obstructions are prostate cancers, verimontanum hypertrophies, detrusor instabilities, urinary incontinence, the bladder cancer and malfunctions. This study is to help the specialist doctors about the evaluation process of the uroflowmetric measurements that are made to determine the intensity of the urinary obstructions. The average flowrate (ml) and the residual urine volume measured in the bladder are accepted as the input variables of the fuzzy logic system. The output variable is the urinary obstruction rate of the urethra. When the obstruction reaches the dangerous levels, it means that the severity of the obstruction in the urethra is high and this obstruction can easily give harm to the kidneys and at the advanced stages of the illness it can cause real failure. Matlab 7 Fuzzy Logic Toolbox is used for the simulation of the fuzzy logic urinary obstruction diagnosis system.
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    Prediction of surface roughness using artificial neural network in lathe
    (2008) Taşdemir S.; Neşeli S.; Saritaş I.; Yaldiz S.
    In this study, the effect of tool geometry on surface roughness has been investigated in universal lathe. Machining process has been carried out on AISI 1040 steel in dry cutting condition using various insert geometry at depth of cut off 0.5 mm. At the end of the cutting operation, surface roughness has been measured using MAHR M1 perthometer. After experimental study, to predict the surface roughness, an ANN has been modelled using the data obtained. Modelling of ANN; tool nose radius (r), approach angle (K), rake angle (Y), tool overhang (L) have been used. In this study, surface roughness (Ra) is output data. The ANN has been designed on PC by using Matlab 6.5 software. Comparison of the experimental data and ANN results by means of statistically t test show that there is no significant difference and ANN has been used confidently.