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Phase-plane analysis for a simplified model of Purkinje cell dendrite

Özer, Mahmut

Proceedings | 2003 | Mathematical and Computational Applications8 ( 1-3 ) , pp.71 - 78

In this study, phase-plane analysis is carried out for a simplified model of Purkinje cell dendrite in terms of voltage-gated ionic channels involved. State variables, nullclines and equilibrium points of the model are determined, and effects of ionic channel conductance and injected current on the shape of nullclines and the equilibrium points are investigated. In this study, phase-plane analysis is carried out for a simplified model of Purkinje cell dendrite in terms of voltage-gated ionic channels involved. State variables, nullclines and equilibrium points of the model are determined, and effects of ionic channel conductance and . . . injected current on the shape of nullclines and the equilibrium points are investigated Daha fazlası Daha az

Determination of fruit health status and yield with unmanned aerial vehicle

Kulu, Nükhet | Başkaya, Merve | Keleş, Aysel | Altan, Aytaç | Hacıoğlu, Rıfat


In this study, it is aimed to determine the number of reference fruits and health status (sturdy, rotten, mottled, non-spotted) by using real-time image or recorded video taken from the autonomous Unmanned Aerial Vehicle (UAV) camera in orchards. In the determinations made by using image processing techniques, sturdy-rotten and mottled-speckless distinction are made for oranges and apricots, respectively. These distinction and determination processes are carried out using highly trained classifiers. Three types of multi-trained classifiers performance have been compared and a highly trained classifier which has high performance has . . .been preferred for object detection. The accuracy of the Haar, local binary pattern (LBP), and histogram of oriented gradients (HOG) classifiers are compared in Python using the open source computer vision library. It has been shown experimentally that Haar classifier achieves high performance in determining real-time reference fruit health status and yield. Daha fazlası Daha az

Early prediction of paroxysmal atrial fibrillation based on short-term heart rate variability

Narin, Ali | İşler, Yalçın | Özer, Mahmut | Perc, Matjaž

Article | 2018 | Physica A: Statistical Mechanics and its Applications509 , pp.56 - 65

Atrial fibrillation (AF) is the most common arrhythmia type and its early stage is paroxysmal atrial fibrillation (PAF). PAF affects negatively the quality of life by causing dyspnea, chest pain, feeling of excessive fatigue, and dizziness. In this study, our aim is to predict the onset of paroxysmal atrial fibrillation (PAF) events so that patients can take precautions to prevent PAF events. We use an open data from Physionet, Atrial Fibrillation Prediction Database. We construct our approach based on the heart rate variability (HRV) analysis. Short-term HRV analysis requires 5-minute data so that each dataset was divided into 5-mi . . .nute data segments. HRV features for each segment are calculated from time-domain measures and frequency-domain measures using power spectral density estimations of fast Fourier transform, Lomb–Scargle, and wavelet transform methods. Different combinations of these HRV features are selected by Genetic Algorithm and then applied to k-nearest neighbors classification algorithm. We compute the classifier performances by the 10-fold cross-validation method. The proposed approach results in 92% sensitivity, 88% specificity and 90% accuracy in the 2.5–7.5 min time interval priors to PAF event. The proposed method results in better classification performance than the similar studies in literature. Comparing the existing studies, we propose that our approach provide better tool to predict PAF events. © 2018 Elsevier B.V Daha fazlası Daha az

Real time detection of alternator failures using intelligent control systems

Uçar, Murat | Bayır, Raif | Özer, Mahmut

Proceedings | 2009 | ELECO 2009 - 6th International Conference on Electrical and Electronics Engineering , pp.56 - 65

On todays vehicles, dynamos are being left gradually and alternators take the turn instead for charging systems. Alternator is an electromechanical device which converts mechanical energy into electrical energy. Superior feature of alternators is that they can be charged on idling epoch and they have more output current. On the other hand by using diodes alternative current can be converted into direct current. Alternators are the main component of the charging system on modern vehicles. In this study, alternator failures are detected using fuzzy logic and artificial neural network. These are double diode failure, excessive current, . . . excessive stretch belt, loose belt, loose brush, regulator failure, short circuits on coils, one broken connection on rotor coil, two broken connection on rotor coil, broken connection on tridiode and tridiode short circuit. For detecting the failures, current, accumulator voltage, alternator voltage and the epoch number of the alternator is measured and alternator failure detection classification is implemented by designing an intelligent system inference according to these measured values Daha fazlası Daha az

Relaxation phenomena in the activation and inactivation gates of ionic channels

Özer, Mahmut

Proceedings | 2003 | Chinese Journal of Physics41 ( 2 ) , pp.206 - 218

The dynamics of a voltage-gated ionic channel is modeled by the conventional Hodgkin-Huxley mathematical formalism. In that formalism, the dynamics of the ionic channel activation and inactivation gates is modeled by a first-order differential equation dependent on the gate variable and the membrane potential. In this study a method, which combines statistical equilibrium theory and the thermodynamics of irreversible processes, is proposed for the study of the relaxation phenomena in the activation and inactivation gates of ionic channels present in the excitable membranes of neurons. In order to study the relaxation phenomena, the . . .assumption is made that the activation and inactivation gate order parameters can be treated as fluxes and forces, in the sense of Onsager's theory of irreversible thermodynamics. The kinetic equations are solved by using the Runge-Kutta method, in order to study the relaxation of the order parameters. It is found that the kinetic equations are characterized by two relaxation times. The kinetic coefficients that relate the fluxes to the forces are determined. Furthermore, it is shown that the obtained relaxation times have the same results as those obtained by using the Hodgkin-Huxley model. These results therefore indicate the validity of the proposed approach Daha fazlası Daha az

Effects of autapse and channel blockage on firing regularity in a biological neuronal network

Uzun, Rukiye | Özer, Mahmut

Proceedings | 2017 | Istanbul University - Journal of Electrical and Electronics Engineering17 , pp.3069 - 3073

In this paper; the effects of autapse (a kind of self-synapse formed between the axon of the soma of a neuron and its own dendrites) and ion channel blockage on the firing regularity of a biological small-world neuronal network, consists of stochastic Hodgkin-Huxley neurons, are studied. In this study, it is assumed that all of the neurons on the network have a chemical autapse and a constant membrane area. Obtained results indicate that there are different effects of channel blockage and parameters of the autapse on the regularity of the network, thus on the temporal coherence of the network. It is found that the firing regularity . . .of the network is decreased with the sodium channel blockage while increased with potassium channel blockage. Besides, it is determined that regularity of the network augments with the conductance of the autapse Daha fazlası Daha az

Epilepsy diagnosis using probability density functions of EEG signals

Orhan, Umut | Hekim, Mahmut | Özer, Mahmut | Provaznik, Ivo

Proceedings | 2011 | INISTA 2011 - 2011 International Symposium on INnovations in Intelligent SysTems and Applications , pp.626 - 630

In this paper, the equal frequency discretization (EFD) based probability density approach was proposed to be used in the diagnosis of epilepsy from electroencephalogram (EEG) signals. For this aim, EEG signals were decomposed by using the discrete wavelet discretization (DWT) method into subbands, the coefficients in each subband were discretized to several intervals by EFD method, and the probability density of each subband of each EEG segment was computed according to the number of coefficients in discrete intervals. Then, two probability density functions were defined by means of the curve fitting over the probability densities . . .of the sets of both healthy subjects and epilepsy patients. EEG signals were classified by applying the mean square error (MSE) criterion to these functions. The result of the classification was evaluated by using the ROC analysis, which indicated 82.50% success in the diagnosis of epilepsy. As a result, the EFD based probability density approach may be considered as an alternative way to diagnose epilepsy disease on EEG signals. © 2011 IEEE Daha fazlası Daha az

Performances of DS-UWB signals over the CM1 channel model

Öztürk, Ertan | Yılmaz, Ergin

Proceedings | 2007 | MobiWac'07 - Proceedings of the 5th ACM International Workshop on Mobility Management and Wireless Access , pp.107 - 111

In this paper, we investigate the probability of error performance of Direct Sequence Ultra Wide Band (DS-UWB) signals using various pulse shapes over the CM1 model of the Standard UWB channel. The considered pulse shapes are the first and second derivatives of Gauss waveform, Rayleigh waveform, and first four orthogonal modified Hermite waveforms. Results reveals that the probability of errors for all available pulse shapes over the considered channel are very similar for few users. However, by increasing the number of users, the performance differences start to appear in favor of Hermite pulses. © 2007 ACM.

Investigation of synchronization in biological neural circuits

Çilli, Salih | Çalım, Ali | Uzuntarla, Muhammet

Proceedings | 2019 | TIPTEKNO 2019 - Tip Teknolojileri Kongresi , pp.107 - 111

Vital functions in living organisms occur through changes in electrical activity. These activities consist of brain rhythms with different frequencies that exhibit oscillatory behavior and can be monitored by local field potentials or EEG recordings. The synchronization of neural activity underlies the emergence of these rhythmic waves, which are of great importance in the nervous system. In this study, the effects of changes in intrinsic mechanisms and intercellular communication, that are constituting neural activity, on the synchronization of neuron pair which is composed of two nerve cells and connected with different types of s . . .ynaptic junction were investigated in a biologically meaningful way. The obtained results showed that the excitability, synaptic and ionic conductivity levels are crucial for neurons to synchronize. It has also been found that the noise caused by the stochastic nature of the ion channels is an auxiliary biological component to achieve synchronization. © 2019 IEEE Daha fazlası Daha az

Effect of the ratio of inhibitory and excitatory conductance on the regularity of spontaneous cortical activity

Özer, Mahmut | Uzuntarla, Muhammet | Graham, Lyle J.

Proceedings | 2008 | ANALYSIS OF BIOMEDICAL SIGNALS AND IMAGES , pp.64 - 68

Cortical neurons in vivo can operate in a continuum between low-conductance (LC) and high-conductance (HC) states. We investigate how changing the ratio, r, of the mean inhibitory conductance to a fixed value of the mean excitatory conductance affects the regularity of spontaneous cortical firing between the two extreme states. We show that, in general, spike regularity becomes smaller for larger r, thus as the neuron approaches the HC state. Furthermore, in the HC state, spike regularity consistently increases with an increase of the synaptic input variability, whereas with small r, thus LC states, regularity first decreases and th . . .en increases with an increase in the input variability. We suggest that this qualitative difference may reflect a state-dependent dominance of spike output driven by the average membrane potential, versus that driven by fluctuations in the membrane potential Daha fazlası Daha az

Prediction of the optimal threshold value in DF relay selection schemes based on artificial neural networks

Kara, Ferdi | Kaya, Hakan | Erkaymaz, Okan | Öztürk, Ertan

Proceedings | 2016 | Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016 , pp.64 - 68

In wireless communications, the cooperative communication (CC) technology promises performance gains compared to traditional Single-Input Single Output (SISO) techniques. Therefore, the CC technique is one of the nominees for 5G networks. In the Decode-And-Forward (DF) relaying scheme which is one of the CC techniques, determination of the threshold value at the relay has a key role for the system performance and power usage. In this paper, we propose prediction of the optimal threshold values for the best relay selection scheme in cooperative communications, based on Artificial Neural Networks (ANNs) for the first time in literatur . . .e. The average link qualities and number of relays have been used as inputs in the prediction of optimal threshold values using Artificial Neural Networks (ANNs): Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) networks. The MLP network has better performance from the RBF network on the prediction of optimal threshold value when the same number of neurons is used at the hidden layer for both networks. Besides, the optimal threshold values obtained using ANNs are verified by the optimal threshold values obtained numerically using the closed form expression derived for the system. The results show that the optimal threshold values obtained by ANNs on the best relay selection scheme provide a minimum Bit-Error-Rate (BER) because of the reduction of the probability that error propagation may occur. Also, for the same BER performance goal, prediction of optimal threshold values provides 2dB less power usage, which is great gain in terms of green communication. © 2016 IEEE Daha fazlası Daha az

Optical signal processing of interference fringes by Hartley transform method

Kaya, Hakan | Saraç, Zehra | Özer, Mahmut | Taşkın, Halit

Proceedings | 2010 | Proceedings of SPIE - The International Society for Optical Engineering7746 , pp.64 - 68

In this paper, the processing of interference fringes is achieved by Hartley transform method. The experimental and simulated interference fringe patterns are used for the signal analysis. Phase results are presented. These are compared with phase obtained by Fourier transform method. Disadvantages and advantages of Hartley transform method used for the evaluation of interference fringe patterns are given. © 2010 SPIE.

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