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KIRCI, PINAR

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KIRCI

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PINAR

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2020 - 20213
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Now showing 1 - 3 of 3
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    Publication
    Determination of the fractal dimension of the active fault data along the east anatolian fault zone
    (Inst Geology & Geography, 2021-01-01) Bayrak, Ebru Aydındağ; Kırcı, Pınar; KIRCI, PINAR; Bursa Uludağ Üniversitesi/Bilgisayar Mühendisliği Bölümü; CZK-0182-2022
    The current study has analyzed active fault data along the East Anatolian Fault Zone (EAFZ) apply ing both manual (classic) and modem versions of the box counting method. The EAFZ active fault datasct used for analysis was taken from the Geoscience Map Viewer and the Drawing Editor from the website of the General Directorate of Mineral Research and Exploration. The study covered an area stretching from Karhova in the north to Kinkhan in the south. The fractal analysis of the earthquake surface rupture and the Holocene fault data was performed. Fractal dimensions of the EAFZ active-fault data were calculated for 15 boxes and compared with correlation coefficient values. The calculated fractal dimension values were found to vary with the density of the active-fault data falling into the boxes. The maximum fractal dimension value D-1 was determined for Karliova and its surroundings, which can be associated with the fault density due to the branching geometry.
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    Analyzing blood donation probabilities and number of possible donors
    (Ieee, 2020-01-01) Kırcı, Pınar; KIRCI, PINAR; Aktaş, Şeyma; Sevinç, Burcu; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü.
    In the paper, many critical data of donors were used. A donor's blood donation frequency and the last donation time were included in the utilized data. The utilization of these data types were very important for providing a solution to determine blood donation probabilities. By using many machine learning approaches on blood transfusion data, it is tried to be estimated, if a possible donor will provide blood donation again. Used algorithms were compared by computing their classification performances.
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    Publication
    Multicellular 4G and load balancing over cloud computing
    (Wiley, 2021-06-06) Hamd, Ravyar Jasim; Ali Yahiya, Tara; Kırcı, Pınar; KIRCI, PINAR; CZK-0182-2022
    LTE-based Multicellular 4G is nowadays gaining an enormous success thanks to its flexible core network features and its large data rate. As the number of users increases, along with the different services provided by the telcos, it is becoming a challenging issue to cope with the contextual increase in the backhaul traffic size: a congestion problem. In this perspective, when combining multicellular LTE with Cloud Computing (CC), this would increase the core network load and the subsequent load on the servers located in the CC that delivers services to the LTE users. To address this issue, we introduce an architecture combining both multicellular LTE and CC, and we investigate the performance of different load balancer mechanisms, namely static and semi-dynamic. Extensive simulation scenarios using different algorithms were set up. The obtained results were analyzed considering the Quality of Service (QoS) and computational resources for a deployed Web application.