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Öğe ANALYZING MOBILE PHONE ELECTROMAGNETIC RADIATION(ST JOHN PATRICK PUBL, 2016) Seyfi, Levent; Yaldiz, Ercan; Nacarolu, Can[Abstract not Available]Öğe Cep telefonu ışımasının kullanıcı yönünde ekranlama yöntemiyle zayıflatılması(Selçuk Üniversitesi Fen Bilimleri Enstitüsü, 2006-01-16) Seyfi, Levent; Yaldız, EcanBu tez çalışmasında cep telefonu kullanımının insan sağlığına zarar riskini azaltmak için telefondan yayılan elektromanyetik dalgaların kullanıcı yönünde ekranlanması incelenmiştir. Bu amaçla iki boyutlu FDTD yöntemi ile bilgisayarda elektromanyetik dalga yayılması benzetimi yapılmıştır. Benzetimler için Matlab programlama dili kullanılarak kullanıcı arayüzlü bir program geliştirilmiştir. 900 MHz ve 1800 MHz bandında bilgisayarda yapılan benzetimlerde ve deneysel ölçümlerde uygulamada çok kullanılan ve maliyeti düşük olan iyi iletkenlerden alüminyum ve bakır plakalar ekran olarak kullanılmıştır. Yapılan benzetim çalışmaları sonucunda elektromanyetik ışımanın kullanıcı yönünde mesafeye ve ekran boyutuna bağlı olarak zayıfladığı gözlenmiştir. Pratikteki ölçüm sonuçları cep telefonu ışımasının ekranlanması halinde özel olarak hazırlanan yansımasız odalarda elde edilen ölçüm sonuçlarından farklı değerler verdiğini ve değişik faktörlere bağlı olarak da ışımanın azaltılmasının her zaman düzenli olmadığını göstermiştir. Bu durum, bilgisayar kullanarak benzetim yapılırken cep telefonunun çıkış gücü sabit tutulurken pratikte iyi iletkenler yardımı ile yapılan ekranlama etkisi nedeniyle gücün cep telefonu tarafından artırılabilmesi özelliğine bağlanabilir.Öğe A comparative study on parameters of leaf-shaped patch antenna using hybrid artificial intelligence network models(SPRINGER LONDON LTD, 2018) Ozkaya, Umut; Seyfi, LeventThis study proposes a very compact coaxial-fed planar antenna for X band applications. The antenna design includes a tulip-shaped radiator on the FR4 dielectric substrate. The antenna parameters, such as return losses, bandwidth and operating frequency, have close relationships with patch geometry. In order to obtain desired antenna parameters for X band application, patch dimension is necessary to be optimized. In this article, four different hybrid artificial intelligence network models are suggested for optimization. These are particle swarm optimization, differential evolution, grey wolf optimizer and vortex search algorithm. Also, they are combined with artificial neural network for the purpose of estimating dimension of patch. Therefore, the comparison of different proposed algorithms is analyzed to obtain higher characteristics for antenna design. Their results are compared with each other in HFSS 13.0 software. The antenna with the most suitable return loss, bandwidth and operating frequency is selected to be used in antenna design.Öğe Convolution Kernel Size Effect on Convolutional Neural Network in Histopathological Image Processing Applications(IEEE, 2018) Ozturk, Saban; Ozkaya, Umut; Akdemir, Bayram; Seyfi, LeventIn this study, the change in the classification success of the convolutional neural network (CNN) is investigated when the dimensions of the convolution window are altered. For this purpose, four different linear convolution neural network architectures are constructed. The first architecture includes 4 convolution layers with 3x3 convolution window dimensions. The second architecture includes 4 convolution layers with 5x5 convolution window dimensions. The third architecture includes 4 convolution layers with 7x7 convolution window dimensions. The fourth architecture includes 4 convolution layers with 9x9 convolution window dimensions. A dataset consisting of histopathological image patches is used to test the CNN architects that are created. 2000 training images and 250 validation images on dataset are applied to all architectures with the same order, in order to fair assessment. In conclusion, the effect of convolution dimensions on classification of histopathological images by deep learning methods is determined. The test results of four different linear convolutional neural network architectures are evaluated using sensitivity, specificity and accuracy parameters.Öğe Deep dictionary learning application in GPR B-scan images(SPRINGER LONDON LTD, 2018) Ozkaya, Umut; Seyfi, LeventThis paper introduces GPR B-scan database which contains 180 labelled images to facilitate research in developing presentation algorithm for this challenging scenario. Along with GPR B-scan images, there are several other detections of buried objects that are explored in the literature. The next contribution of this research is a novel multilevel deep dictionary learning-based presentation buried object detection algorithm that can discern different kinds of materials. An efficient layer by layer training approach is formulated to learn the deep dictionaries followed by different classifiers as types of shape for buried objects. By changing the number of layers in proposed algorithm, performances in different classifiers are compared. It is possible to integrate the proposed algorithm with real-time systems because it is supervised and has high classification accuracy with 94.4%.Öğe Dimension Optimization of Microstrip Patch Antenna in X/Ku Band via Artificial Neural Network(ELSEVIER SCIENCE BV, 2015) Ozkaya, Umut; Seyfi, LeventThis paper is aimed at designing the effective shape of a microstrip patch antenna for X Band (8 to 12 GHz) and Ku Band (12 GHz to 18 GHz). Artificial Neural Network is used for optimizing microstrip antenna dimensions. The Network takes the different microstrip antenna parameters as inputs and delivers its dimensions in the X/Ku Band satellite communication. The error and validity analysis of neural network results are carried out in Matlab. Finally, HFSS simulation software results for prototype microstrip antenna, which has the best antenna parameters, is compared with real value. (C) 2015 The Authors. Published by Elsevier Ltd.Öğe Enerji verimli iki boyutlu bir gpr algoritmasının geliştirilmesi(Selçuk Üniversitesi Fen Bilimleri Enstitüsü, 2011-12-16) Seyfi, Levent; Yaldız, ErcanTahribatsız algılama teknikleri sayesinde araştırılacak olan sahada kazı gibi zahmetli bir işlem yapmadan aranılan nesnenin varlığı tespit edilebilmektedir. Böylece en az zaman kaybı ve masraf ile yeraltı hakkında bilgi toplanıp kaydedilebilmektedir. Yere nüfuz eden radar (Ground Penetrating Radar, GPR), tahribatsız algılama için birçok alanda kullanılan önemli bir tekniktir. GPR, elektromanyetik dalga gönderme ve yansıyıp geri gelen dalgaları algılaması prensibiyle tarama yapar. Bu tez çalışmasında GPR çalışmasının nümerik olarak modellenmesi ve benzetim çalışmaları Matlab programlama dili aracılığıyla 2 boyutlu olarak gerçekleştirilmiştir. Benzetimler, zamanda sonlu farklar (Finite Difference Time Domain, FDTD) tekniği kullanılarak gerçekleştirilmiştir. Benzetimlerde yutucu sınır koşulu olarak mükemmel uyumlu tabaka (Perfectly Matched Layer, PML) kullanılmıştır. GPR, portatif bir cihazdır ve şebeke geriliminin olmadığı sahalarda enerjisini pilleri üzerinden sağlamaktadır. Pillerin enerjisi yettiği sürece GPR ile sahada tarama yapılabilmektedir. Pillerin verimli bir şekilde kullanılması GPR'ın etkin kullanımı için oldukça önemlidir. Bu nedenle bu tez çalışmasında enerji tasarruflu yeni bir GPR algoritması geliştirilmiştir. Önerilen algoritma, GPR'ın araştırılan hedefi algılayabileceği minimum elektromanyetik dalga genliğini ayarlamaktadır. Enerji tasarruflu GPR algoritması sayesinde standart algoritmasına kıyasla daha az enerji harcandığı yapılan benzetim çalışmaları ile gösterilmiştir. Önerilen algoritmanın etkinliği, farklı elektriksel özelliklerde düz ve engebeli katmanlar ile farklı boyutta gömülü cisimler için araştırılmıştır.Öğe Mapping of Electromagnetic Pollution at 1800 Mhz GSM (Global System for Mobile Communication) Frequency in Konya(ACADEMIC JOURNALS, 2010) Durduran, S. Savaş; Uygunol, Osman; Seyfi, LeventMobile phones are a vital part of daily life; thus, the rate of usage of mobile phones is increasing on a daily basis. Because they work in connection with base stations, number of base stations has to be boosted as long as the trend in the use of them continues. Because each base station runs by radiating electromagnetic waves, this is a disturbing condition for people from a medical point of view. Thus, it is important to analyze radiation of base stations until we are sure that they are definitely non-harmful in the long term. Mapping of electromagnetic pollution from base stations may be of much importance in this context. This paper aimed at mapping the electromagnetic pollution at 1800 MHz in Konya. To do this, electromagnetic radiation from base stations was measured at 185 points in Konya. Then, electromagnetic pollution maps were accomplished by uniting transactions like database query, statistical analysis with visualization and maps-based spatial analysis. They provide useful information to enable us to analyze and explain some probable health problems, which may be caused by GSM (global system for mobile communication) radiation in future.Öğe Measurement of electromagnetic radiation with respect to the hours and days of a week at 100kHz-3GHz frequency band in a turkish dwelling(ELSEVIER SCI LTD, 2013) Seyfi, LeventIn this paper, the electromagnetic (EM) radiation to which we are exposed in our life is aimed to be observed during a week. The measurements are carried out in a randomly selected apartment during 24 h a day at 4 s sampling period for all days of a week. Due to the result of the study, we can see whether any radiation above specified limits occurs during a day and week or not and also we can determine how an ordinary instantaneous measurement represents the usual radiation level in related area. Measurement results showed that EM radiation levels in 100 kHz-3 GHz frequency band were considerably below specified limit values. There is statistically no difference between measured values in Monday and Saturday with respect to days. However, it is observed that the measured values in other days except for Monday and Saturday are statistically considerably different. (C) 2013 Elsevier Ltd. All rights reserved.Öğe MODELING AND ANALYSIS OF ABSORBING BOUNDARY CONDITION IN ANTENNA DESIGN(CENTRAL BOHEMIA UNIV, 2016) Ozkaya, Umut; Seyfi, LeventIn this study, the absorbing boundary condition is modelled and analyzed by particle swarm optimization for antenna designs. Two pieces of circular and rectangular microstrip patch antennas are designed for results by means of High Frequency Structure Simulator (HFSS) simulation program. These antennas are implemented by printed circuit board technologies. The results of measurements and simulation performed for the antenna determined the optimal absorbing boundary distance.. In order to be closer with simulation and measurement results, data set is generated by varying in absorbing boundary size. Average square error between simulation and measurement data is necessary to be optimized as an objective function. For this reason, optimization algorithm based on swarm intelligence is preferred to be minimized the error function. Thanks to the results of measurements and simulation performed with the antenna, optimal absorbing boundary distance is determined by Particle Swarm Optimization.Öğe A NOVEL FUZZY LOGIC MODEL FOR INTELLIGENT TRAFFIC SYSTEMS(ST JOHN PATRICK PUBL, 2016) Ozkaya, Umut; Seyfi, Levent[Abstract not Available]Öğe Numerical Computing of Reduction of SAR Values in a Homogenous Head Model Using Copper Shield(Int Assoc Engineers-Iaeng, 2010) Seyfi, Levent; Yaldız, ErcanIn this study, variation of the maximum specific absorption rate (SAR) on mobile phone user was researched when mobile phone was shielded with copper at 900 MHz frequency. Simulations were conducted to calculate the maximum SAR values in Matlab programming language using 2D-FDTD (Finite Difference Time Domain) method. Calculations were made separately for 1g and 10g. Head structure was assumed to be uniform.Öğe A simulator based on an energy-efficient GPR algorithm modified for the scanning of all types of regions(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, 2012) Seyfi, Levent; Yaldiz, ErcanAn improved simulator is presented for the simulation of an energy-efficient ground-penetrating radar (GPR) using the 2D finite-difference time-domain method in the MATLAB environment. This simulator is novel in that it improves on previous work that did not involve scanning a buried object or the intermittent sublayer beneath the ground using an energy-efficient algorithm. The present simulator examines the scanned region and automatically chooses either a common algorithm or an energy-efficient algorithm, depending on the region. The simulator provides the possibility of using an energy-efficient GPR without the need for the operator to determine the suitability of the scanned region. Three different models are defined to confirm the validity of the simulator. These models separately include an inclined sublayer, a rough sublayer, and a buried object. The obtained results show that the energy-efficient GPR can be used in all types of regions.Öğe Weighting and Classification of Image Features using Optimization Algorithms(IEEE, 2018) Ozturk, Saban; Ozkaya, Umut; Akdemir, Bayram; Seyfi, LeventIn this study, importance ratios of features extracted from images using feature extraction algorithms are examined. A significance coefficient is determined for each feature parameter. The number of features is reduced according to the weight of the importance calculated for each feature. The classification success is examined for each case. Firstly, six feature extraction algorithms are used for this purpose. The classification success of all these feature extraction algorithms has been examined separately. Then, all properties are combined to form a single property matrix. The obtained property matrix is reduced by using principal component analysis and relieff methods. New feature matrices provide increased classification performance. However, it is inefficient to classify a high number of properties in real-time applications. To overcome this problem, the effect of classifying each parameter in the property matrix is examined and the insignificant properties are discarded. The proposed method is tested using histopathological images. Histopathological images are divided into 4 separate classes. The proposed method reduces the raw feature matrix by 50% with 97.2% classification success.
