Gülay Tohumoğlu

Designing simulated annealing and subtractive clustering based fuzzy classifier

A new systematic way in order to obtain optimized fuzzy inference system for classification task is developed. The proposed algorithm, Simulated Annealing (SA) and Subtractive Clustering (SC) based Fuzzy Classifier (SASCFC) is a cooperation of the SA and the SC methods. The SA is used in order to optimize the SC parameters, feature subspace and output threshold value of fuzzy based classifier. A hybrid feature selection strategy which combines filter and wrapper type approaches is also proposed. In order to demonstrate the effects of these optimizations, we proposed four different SASCFC classifiers which are called as the SASCFC-Type1, Type2, Type3 and Type4. The performance and rule base complexity of proposed classifiers are compared with each other and also some classifier tools on some well known classification tasks. The results show that the proposed classifiers have a satisfactory performance in comparison with its counterparts.

Formulation of ELF magnetic fields' effects on malondialdehyde level and myeloperoxidase activity in kidney using genetic programming

In vivo exposure effects of electromagnetic fields (EMFs) on various tissues of experiment animals have been investigated. In this sense, modeling and formulation of these biological effects have been of significant importance. In this study extremely low frequency (ELF) EMFs effects on malondialdehyde (MDA) level and myeloperoxidase (MPO) activity in kidney of guinea pigs exposed to 50 Hz magnetic fields of 1 mT, 2 mT and 3 mT have been presented. It has been planned to determine whether genetic programming (GP) is appropriate to analyze and formulate these biological effects. Consequently, it has been observed that GP can be effectively used to model MDA level and MPO activity. The performances of prediction of the proposed GP formulation versus actual experimental values are found to be quite satisfactory in terms of standard deviation and correlation coefficient. It is concluded that the GP application serves to form a database for the researchers in this field, without exposing tissues to EMF and without using too many guinea pigs.

Analysis of periodically time-varying discrete-time systems in spectral domain

It is well known the concept of the steady-state response in the theory of linear time invariant systems. In this paper, the method called spectral analysis is newly adopted for periodically time varying (PTV) discrete time systems from the theory of the spectral analysis of linear PTV continuous time systems. Shortly, it describes the steady-state analysis of PTV discrete time systems. It leads to a simple algebraic relations in the frequency domain that minimizes calculations in the time domain. In order to show the generality and usefulness of this method, an illustrative examples are chosen. The comparison of the results with the exact solution concludes that the systems having smooth variation-less number of harmonics with respect to strongly varying systems are rapidly convergent with the high accuracy. The error analysis has being done by computing the root-mean-square error.

Formulation of Low Intensity Direct Current Effects on Wound Healing of Skin using Genetic Programming

This study has two main purposes: Firstly, the effect of electrical stimulation was studied on experimental wound healing of skin. It investigates whether a triggering was possible on collagen synthesis in wound healing before the 3rd day of wounding, via measurements of hydroxyproline, a measure of collagen concentration in the wound tissue. Wound tissue hydroxyproline contents were determined with the effects of two different electric current intensities of 200 muA and 400 muA at 48 and 72 hours after wounding by Woessners Method. For both of the current intensities, statistically significant increases were found in hydroxyproline contents of current applied wounds with respect to their controls for 72 hours whereas decreased hydroxyproline content was found for 400 muA of current intensities at 48 hours. Secondly, it was aimed to model and formulate how electric current effects wound healing using Genetic Programming (GP) based on experimental results. The accuracy of the proposed GP formulation is defined quantiatively by standard deviation (SD=0.39) and correlation coefficient (R=0.85), which is found to be high.