Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Enhancing Thickness Determination of Nanoscale Dielectric Films in Phase Diffraction-Based Optical Characterization Systems With Radial Basis Function Neural Networks(IOP Publishing, 2023) Ataç, Enes; Karatay, Anıl; Dinleyici, Mehmet SalihAccurate determination of the optical properties of ultra-thin dielectric films is an essential and challenging task in optical fiber sensor systems. However, nanoscale thickness identification of these films may be laborious due to insufficient and protracted classical curve matching algorithms. Therefore, this experimental study presents an application of a radial basis function neural network in phase diffraction-based optical characterization systems to determine the thickness of nanoscale polymer films. The non-stationary measurement data with environmental and detector noise were subjected to a detailed analysis. The outcomes of this investigation are benchmarked against the linear discriminant analysis method and further verified by means of scanning electron microscopy. The results show that the neural network has reached a remarkable accuracy of 98% and 82.5%, respectively, in tests with simulation and experimental data. In this way, rapid and precise thickness estimation may be realized within the tolerance range of 25 nm, offering a significant improvement over conventional measurement techniques.Article Citation - WoS: 91Citation - Scopus: 105Measurement of the Single-Top T-Channel Cross Section in Pp Collisions at ?s=7 Tev(Springer Verlag, 2012) CMS Collaboration; Karapınar, GülerA measurement of the single-top-quark t-channel production cross section in pp collisions at √s=7 TeV with the CMS detector at the LHC is presented. Two different and complementary approaches have been followed. The first approach exploits the distributions of the pseudorapidity of the recoil jet and reconstructed top-quark mass using background estimates determined from control samples in data. The second approach is based on multivariate analysis techniques that probe the compatibility of the candidate events with the signal. Data have been collected for the muon and electron final states, corresponding to integrated luminosities of 1.17 and 1.56 fb-1, respectively. The single-top-quark production cross section in the t-channel is measured to be 67.2±6.1 pb, in agreement with the approximate next-to-next-to-leading- order standard model prediction. Using the standard model electroweak couplings, the CKM matrix element |V tb| is measured to be 1.020 ± 0.046 (meas.) ± 0.017 (theor.). © 2012 CERN for the benefit of the CMS collaboration.Article Citation - Scopus: 250A Neural Network Approach for Early Cost Estimation of Structural Systems of Buildings(Elsevier Ltd., 2004) Günaydın, Hüsnü Murat; Doğan, Sevgi ZeynepThe importance of decision making in cost estimation for building design processes points to a need for an estimation tool for both designers and project managers. This paper investigates the utility of neural network methodology to overcome cost estimation problems in early phases of building design processes. Cost and design data from thirty projects were used for training and testing our neural network methodology with eight design parameters utilized in estimating the square meter cost of reinforced concrete structural systems of 4-8 storey residential buildings in Turkey, an average cost estimation accuracy of 93% was achieved.