Yazar "Babur, Sebahattin" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Öğe
    Dimensional accuracy analysis of samples printed in delta and cartesian kinematic three dimensional printers
    (Gazi University, 2021) İncekar, Erkan; Kaygısız, Hüseyin; Babur, Sebahattin
    The motion mechanisms of manufacturing and robotic systems are developed in different structures, mainly in cartesian and delta structures having series or parallel movement abilities according to the capacity and construction structure of the system. Different systems are used according to the criteria such as bearing load capacity, sensitivity or cost of the system. In this study, the performances of machines installed in the delta and cartesian kinematic structures, which are mostly used in the kinematic systems of three - dimensional printers, were analyzed. In this context, in two different machines with these two construction structures, the same boundary conditions and 4 pieces of calibration parts especially in manufacturing features were printed. 23 different elements that constituted the calibration part were measured, tabulated, statistically analyzed, and the acceptable measuremental tolerance ranges of the elements were determined and the accuracy values of the machines were compared. As a result of this study, according to T test results, 15 of the 23 measurements on the Cartesian system based three-dimensional printers were obtained as acceptable in terms of tolerance range as well as 9 of the 23 different measurements were obtained as acceptable on Delta system. Consequently, operation accuracy of the Cartesian system based three-dimensional printers were higher than the Delta system under the same working conditions and manufacturing parameters.
  • Küçük Resim
    Öğe
    Makine öğrenmesi teknikleri kullanılarak meme kanseri teşhisinin performans değerlendirmesi
    (IEEE, 2015) Bektaş, Burcu; Babur, Sebahattin
    Meme kanseri, sıklıkla kadınlar arasında görülen ve meme hücrelerinde başlayan bir kanser türüdür. Erken teşhis ve doğru tedavi meme kanseri hastalarının hayatta kalma oranını arttırabilme açısından son derece önemlidir. Mikrodizi teknolojisi ile hastalığın genetik faktörlerinin belirlenmesi teşhis ve tedavi sürecine önemli katkı sağlayabilir. Bu çalışmada, meme kanserinin teşhisi için birçok makine öğrenmesi algoritmaları kullanılmıştır ve bu algoritmaların birbirlerine göre sınıflandırma performansları karşılaştırılmıştır. Bunun yanı sıra öznitelik seçme yöntemleri ile meme kanserinde etkin genler belirlenip yapılan çalışma sonucunda 139 öznitelik ile % 90,72 başarı elde edilmiştir.