Matematik ve Bilgisayar Bölümü / Department of Mathematics and Computer Science
Permanent URI for this collectionhttps://hdl.handle.net/11413/6787
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Browsing Matematik ve Bilgisayar Bölümü / Department of Mathematics and Computer Science by Type "conferenceObject"
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Publication A certain class of harmonic mappings related to functions of bounded radius rotation(2018) Kahramaner, Yasemin; Yemişçi Şen, Arzu; POLATOĞLU, YAŞARLet R-k be the class of functions with bounded radius rotation and let S-H be the class of sense-preserving harmonic mappings. In the present paper we investigate a certain class of harmonic mappings related to the function of bounded radius rotation.Publication A combinatorial discussion on finite dimensional leavitt path algebras(2012) Esin, Songül; Güloğlu, İsmail; Kanuni, Müge; KOÇ, AYTEN; 112205; 145213Publication A microsoft visual Basic software for B-Spline solution of the one-dimensional heat equation(2008) Çağlar, Hatice Nazan; Çağlar, Süleyman Hikmet; Özer, Mehmet; CUHACI, LEVENT; 110809; 114368; 2509; 112369Publication A non polynomial spline solution of the one-dimensional wave equation subject to an integral conservation condition(2010) Çağlar, Hatice Nazan; Çağlar, Süleyman Hikmet; Yılmaz, Serhat; İşeri, Müge; 110809; 114368Hyperbolic partial differential equations with an integral condition serve as models in many branches of physics and technology. Recently,much attention has been expended in studying these equations and there has been a considerable mathematical interest in them. In this work, the solution of the one-dimensional nonlocal hyperbolic equation is presented by the method of non-polynomial cubic splines. Numerical results reveal that present method based on non-polynomial spline is implemented and effective.Publication A solution to a problem of Abramovich Aliprantis and Burkinshaw(2007) Mısırlıoğlu, Remzi Tunç; 108824Publication A Systematic Mapping Study on Software Architecture Recovery(2016-11) Çatal, Çağatay; BAYDOĞMUŞ, GÖZDE KARATAŞ; ; 108363; 110942In this study, we investigated the approaches used in software architecture recovery papers, identify the current status of paper distributions in terms of year, publication channel, electronic databases, and journals. We executed a mapping study to cluster the software architecture recovery research papers. Papers published since 2000 have been used for this study. The following databases were investigated: Wiley, IEEE, ACM, Science Direct. Our search accessed 250 papers, but after in-depth analysis, 60 papers were found to be related to the software architecture recovery area. Our study shows that there exist many architecture recovery approaches in the literature, with machine learning-based techniques dominating the field. On the basis of this study, we suggest researchers develop more model centric software architecture recovery approaches because of model driven development’s popularity in software engineering field.Publication Average Vector Field Method of The Strongly Coupled Nonlinear Schrodinger Equation(2019-07) akkoyunlu, canan; 113376In this work, average vector field method (AVF) is derived for strongly coupled Schrodinger equation (SCNLS). The SCNLS equation is discretized in space by finite differences and is solved in time by structure preserving AVF method. Numerical results for different paremeter compare with the Lobatto IIIA-IIIB method.The results indicate that AVF method are effective to preserve global energy and momentum.Publication B-Spline solition of linear hyperbolic partial differential equations(2010) Çağlar, Hatice Nazan; Çağlar, Süleyman Hikmet; 110809; 114368Publication B-Spline Solution and the Chaotic Dynamics of Troesch's Problem(Polish Acad Sciences Inst Physics, Al Lotnikow 32-46, Pl-02-668 Warsaw, Poland, 2014-02) Çağlar, Süleyman Hikmet; Çağlar, Hatice Nazan; Özer, Mehmet; 114368; 110809; 2509A B-spline method is presented for solving the Troesch problem. The numerical approximations to the solution are calculated and then their behavior is studied and commenced. The chaotic dynamics exhibited by the solutions of Troesch's problem as they were derived by the decomposition method approximation are examined and an approximate critical value for the parameter lambda is introduced also in this study. For the parameter value slightly less than lambda approximate to 2.2, the solutions begin to show successive bifurcations, finally entering chaotic regimes at higher lambda values. The effectiveness and accuracy of the B-spline method is verified for different values of the parameter, below its critical value, where the first bifurcation occurs.Publication B-Spline Solution for a Convection-Diffusion Equation(Polish Acad Sciences Inst Physics, Al Lotnikow 32-46, Pl-02-668 Warsaw, Poland, 2014-02) Çağlar, Süleyman Hikmet; Çağlar, Hatice Nazan; Özer, Mehmet; 114368; 110809; 2509This paper is concerned with the numerical solution of the convection diffusion problems. A family of B-spline methods has been considered for the numerical solution of the problems. The results showed that the present method is an applicable technique and approximates the exact solution.Publication B-Spline solution of linear hyperbolic partial differential equations(2011) Çağlar, Hatice Nazan; Çağlar, Süleyman Hikmet; Dündar, Durmuş; 110809; 114368Second-order linear hyperbolic equations are solved by using B-spline method . The numerical solution of the equations are discussed and illustrated with an example. Numerical results reveal that B-spline method is implemented and effective.Publication Berger Wang Formula holds for collectively compact sets of linear operators(2011) Mısırlıoğlu, Remzi Tunç; 108824Publication Çakışma Cebirlerinin Singüler olmayan Kasch ve Ikeda Nakayama Halka Olma Koşulları(2008) Kanuni, Müge; Esin, Songül; KOÇ, AYTEN; 112205; 145213Publication Cemal Koc ve Matematik(2010) Esin, Songül; Güloğlu, İsmail; Kanuni, Müge; KOÇ, AYTEN; 112205; 145213Publication Characterization of Some Ring Properties in Incidence Algebras(2008) Esin, Songül; Kanuni, Müge; KOÇ, AYTEN; 145213; 112205Publication Classifications of Representations of Leavitt Path Algebras(2018) KOÇ, AYTEN; 112205Publication Covid-19 Disease Detection with Improved Deep Learning Algorithms on X-Ray Data(Institute of Electrical and Electronics Engineers Inc., 2022) ÇİÇEKLİ, NAHİDE ZEYNEP; BAYDOĞMUŞ, GÖZDE KARATAŞThe COVID-19 pandemic has brought human life to a startling halt around the world from the moment it emerged and took thousands of lives. The health system has come to the point of collapse, many people in the world have died from being infected, and many people who have survived the disease have had permanent lung damage with the spread of COVID-19 in 212 countries and regions. In this study, an answer is sought to diagnose the disease-causing virus through Artificial Intelligence Algorithms. The aim of the study is to accelerate the diagnosis and treatment process of COVID-19 disease. Enhancements were made using Deep Learning methods, including CNN, VGG16, DenseNet121, and ResNet50. For this study, the disease was detected by using X-Ray images of patients with and without COVID-19 disease, and then it was evaluated how to increase the accuracy rate with the limited available data. To increase the accuracy rate, the results of data augmentation on the image data were examined and the time complexity of the algorithms with different layers was evaluated. As a result of the study, it was seen that data augmentation increased the performance rate in all algorithms and the ResNet50 algorithm was more successful than other algorithms. © 2022 IEEE.Publication Deep Learning in Intrusion Detection Systems(2018) Demir, Önder; BAYDOĞMUŞ, GÖZDE KARATAŞ; ŞAHİNGÖZ, ÖZGÜR KORAY; 110942; 170651; 214903Publication The Effect of Loss and Optimization Functions on Bitcoin Rate Prediction in LSTM(Institute of Electrical and Electronics Engineers Inc., 2022) KIRCI, BERKE KAAN; BAYDOĞMUŞ, GÖZDE KARATAŞIn recent years, Bitcoin cryptocurrency has become a growing trend in the world. For this reason, researchers from many fields are examining various artificial intelligence models to predict Bitcoin rates. In particular, Deep Learning algorithms have been shown to outperform traditional models in predicting cryptocurrency rates. However, very few studies have examined the effect of parameters used in deep learning algorithms on the algorithm. Optimization and loss functions are very important, which affect the algorithm's ability to make a successful prediction. In this study, Long-Short Term Memory, a deep learning algorithm, is used to predict daily Bitcoin prices and the effect of optimization/loss functions on the accuracy rate is evaluated. Experimental results showed that the Long-Short Term Memory model made the best predictions as a result of working with the Adam optimization function and the Mean Square Error loss function. © 2022 IEEE.Publication Energy preserving integration of the strongly coupled nonlinear Schrodinger equation(Amer Inst Physics, 2 Huntington Quadrangle, Ste 1No1, Melville, Ny 11747-4501 USA, 2015) Akkoyunlu, Canan; 113376In this paper, average vector field method (AVF) is derived for strongly coupled Schrodinger equation (SCNLS). The SCNLS equation is discretized in space by finite differences and is solved in time by structure preserving AVF method. Numerical results for different paremeter compare with the Lobatto IIIA-IIIB method. The results indicate that AVF method are effective to preserve global energy and momentum.