Browsing by Subject "Important features"

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    Coupling enhancement of split ring resonators on graphene
    (Pergamon Press, 2014-12) Cakmakyapan, S.; Caglayan, H.; Özbay, Ekmel
    Metallic split ring resonator (SRR) structures are used in nanophotonics applications in order to localize and enhance incident electromagnetic field. Electrically controllable sheet carrier concentration of graphene provides a platform where the resonance of the SRRs fabricated on graphene can be tuned. The reflectivity spectra of SRR arrays shift by applying gate voltage, which modulates the sheet carrier concentration, and thereby the optical conductivity of monolayer graphene. We experimentally and numerically demonstrated that the tuning range can be increased by tailoring the effective mode area of the SRR and enhancing the interaction with graphene. The tuning capability is one of the important features of graphene based tunable sensors, optical switches, and modulator applications. © 2014 Elsevier Ltd. All rights reserved.
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    Density functional theory investigation of two-dimensional dipolar fermions in a harmonic trap
    (IOP, 2014) Üstünel, H.; Abedinpour, S. H.; Tanatar, Bilal
    We investigate the behavior of polarized dipolar fermions in a two-dimensional harmonic trap in the framework of the density functional theory (DFT) formalism using the local density approximation. We treat only a few particles interacting moderately. Important results were deduced concerning key characteristics of the system such as total energy and particle density. Our results indicate that, at variance with Coulombic systems, the exchange- correlation component was found to provide a large contribution to the total energy for a large range of interaction strengths and particle numbers. In addition, the density profiles of the dipoles are shown to display important features around the origin that is not possible to capture by earlier, simpler treatments of such systems.
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    Separating nut-shell pieces from hazelnuts and pistachio kernels using impact vibration analysis
    (IEEE, 2013) Habiboǧlu, Yusuf Hakan; Sevimli, Rasim Akın; Çetin, A. Enis; Pearson, T.C.
    In this article nut-shell pieces are separated from pistachio kernels and hazelnut kernels using impact vibration analysis. Vibration signals are recorded and analyzed in real-time. Mel-kepstral feature parameters and line spectral frequency values are extracted from the vibration signals. Feature parameters are classified using a Support Vector Machine (SVM) which was trained a priori using a manually classified data set. An average classification rate of 96:3% and 98:3%was achieved with Antepstyle Turkish pistachio nuts and hazelnuts. An important feature of the method is that it is easily trainable for other kinds of pistachio nuts and other nuts including walnuts. © 2013 IEEE.