Cilt:63 Sayı:01 (2021)

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https://dspace.ankara.edu.tr/handle/20.500.12575/76567

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Browsing Cilt:63 Sayı:01 (2021) by Author "Other"

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    A new astronomical parameter from remote sensing data: Astronomical clearness index (ACI)
    (Ankara Üniversitesi Fen Fakültesi, 2021-07-01) Kaba, Kazım; Yaprak, Cahit Yeşil; Şatır, Onur; Other; Other
    Eastern Anatolia Observatory (DAG) project was initiated in Erzurum/Turkey in 2011. DAG will have Turkey’s largest (4 m) and first infrared telescope. The installation process is planned to be by taking its first light in the end of 2021. This study was focused on a new analysis method about the atmospheric properties of DAG site in terms of the cloudiness as known the most vital atmospheric parameter for ground-based astronomical observatories. In this regard, the cloudiness for DAG site is comprehensively examined using the “Cloud Mask” (CMa) and “Cloud Type” (CT) products from Satellite Application Facility on Support to Nowcasting and Very Short-Range Forecasting (NWC SAF). Firstly, the cloudiness and the cloud types over DAG site were determined. Secondly, NWC SAF CMa and CT data have been redefined for astronomical purposes, and the pixel values/meanings in CMa and CT images have been reduced from 6 to 4 and from 21 to 4 pixels, respectively. Thirdly, these new data were used to define a new index named as “Astronomical Clearness Index” (ACI), and finally, the observable days for DAG site were determined using this newly defined index.
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    A new distributed denial-of-service detection system in cloud environment by using deep belief networks
    (Ankara Üniversitesi Fen Fakültesi, 2021-06-30) İbrahim, İbrahim; Kurnaz, Sefer; Other; Other
    This study presents new method to detect DDOS attacks by using Deep Belief Networks (DBN). The input data which represented the DDoS features in cloud environment are first analyzed by using DBN to extracted high level and sensitive features. The output of the DBN wired to the classifier (SoftMax and SVM). The aim of using the DBN is to extracted features that have ability to present the best classification results and to speed up the processing time by reducing the dimension of features. In the last stage, the Classifier trained in supervised method to classify the features into two labels there is attack or not. The obtained results compared with well-known studies presented in this field.
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    Enhanced boost converter with gan based power switches and switched-capacitor
    (Ankara Üniversitesi Fen Fakültesi, 2021-06-30) Cengiz, Korhan; Other; Other
    To increase the voltage gain of power electronic circuits, several voltage converters have been designed by researchers. Especially, the boost based converters are used by designers for numerous devices and systems because of their reliability. Generally, in these studies, researchers propose to use high frequency transformers, silicon based diodes and inductance based sub-circuits. However, the improvement on new generation power transistors should be considered as an alternative way to provide these goals because of their lower inner resistances, lower switching losses and adoptability for new generation devices. Therefore, in this paper, usage of these kinds of semiconductors to improve the voltage gain performance of traditional boost converter is proposed. With this enhanced design and usage of new semiconductor switches, we obtain approximately 70% more output voltage gain than traditional boost converter. The proposed converter provides significant gain, high scalability in duty cycle vs output voltage usage and portability for weight restricted systems. The enhanced boost based converter is modelled in Simulink to verify the analytical voltage gain equations. Finally, the proposed model is compared with traditional boost converter in term of gain performance.
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    Impurity effects on activation energy, structure and physical properties of Ybco superconductor
    (Ankara Üniversitesi Fen Fakültesi, 2021-07-01) Özabacı, Murat; Other; Other
    The influence of separately added 0.3 wt%, CdO, Bi2O3, BeO and SiO2 on the phase formation, microstructure, magnetic and transport properties of Y1Ba2Cu3O(7- δ ) (Y-123 or YBCO) fabricated by conventional solid state reaction method has been analyzed. The results reveal a very low solubility limit for bismuth and silicon in the Y-123 phase, leading to precipitation phases located within intergranular regions. BeO addition suppresses the granular nature of the structure by probably incorporating into the host matrix. CdO does not have a remarkable effect both on structural and superconducting properties of the Y-123 at this doping ratio. Attractive infield transition behavior was obtained in the Bi2O3 added sample with a narrower transition width and an increase of transition temperatures approximately 1 K. The activation energy (U0), a potential energy barrier to prevent flux flow, of the samples was estimated by taking into account Arrhenius law. The best U0 value was computed to be 1.11 eV belonging to the Bi2O3 added sample which implies the contribution of 3-5 µm sized Bi containing precipitation regions on the flux pinning capability of the Y-123.