Midyat Meslek Yüksekokulu

Permanent URI for this communityhttps://hdl.handle.net/20.500.12514/29

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Analysis of Feature Selection Approaches in Large Scale Cyber Intelligence Data with Deep Learning
(IEEE, 2020) Ahmetoğlu, Hüseyin; Daş, Resul
Ağ sistemlerinin her geçen gün katlanarak büyüyen boyutu, saldırı yoğunluğunun ve türlerinin de artmasına neden olmaktadır. Ağ içerisinde bu saldırıların tespiti, ağ güvenliğinin başlıca problemlerindendir. Saldırı tespit sistemleri, bu problemle başa çıkmak için geliştirilen bir yaklaşımdır. Saldırı tespit sistemlerinde işlenen büyük boyutlu veriler beraberinde karmaşıklığ da getirmektedir. Bu çalışma, veri kümelerindeki karmaşıklığı gidermek için 6 farklı öznitelik seçme algoritmasının incelenmesini ve bu algoritmaların sınıflandırma modellerindeki performanslarının karşılaştırılmasını içermektedir. Bu performanslar, açık erişimli olarak sunulan CICIDS2017 veri seti üzerinde uygulanan Derin Öğrenme modelleri ile analiz edilmiştir. Bu işlem sırasında algoritmaların test sonuçları hem kendi aralarında hem de veri setinin orijinal haliyle karşılaştırılmıştır. Uygulama sırasında veri kümesindeki öznitelik sayıları çoklu sınıflandırma için 78’den 25’e, ikili sınıflandırma için 8’e düşürülmüştür. Elde edilen başarı oranları bütün uygulamalarda %92’nin üzerindedir.
Analysis of Open Circuit Voltage MPPT Method with Analytical Analysis with Perturb and Observe (P&O) MPPT Method in PV Systems
(Taylor and Francis Ltd., 2023) Çakmak, Fevzi; Tür, Mehmet Rıda; Tür, Mehmet Rıda
This study conducts a comprehensive comparison between two prominent Maximum Power Point Tracking (MPPT) techniques employed in solar energy systems: the Perturb and Observe (P&O) method and the Analytical Solution Fractional Open Circuit Voltage (ASFOCV) method. To assess the effectiveness of these MPPT approaches, a simulation study was conducted using four SHARP NDQ295 model photovoltaic panels, configured as two panels in series and two in parallel. Both the P&O and ASFOCV MPPT methods were evaluated under various scenarios of radiation levels and temperature changes. The results unequivocally demonstrate the superior performance of the ASFOCV MPPT method over the P&O MPPT method. The ASFOCV method notably enhanced converter output power by up to 5% when compared to the P&O method, leading to more efficient energy production. Furthermore, the ASFOCV method exhibited rapid stabilization of output voltage during abrupt weather changes, outperforming the P&O method in this regard. This study underscores the potential of the ASFOCV MPPT method to enhance the efficiency of solar energy systems and its adaptability to fluctuating environmental conditions. Future research endeavors could focus on mitigating the ASFOCV method’s sensitivity to temperature variations and conducting real-world applications to further investigate its performance under practical circumstances.
How do family influence on career choices and perceived social support affect students’ life satisfaction in Turkey? The role of vocational outcome expectations as mediator
(SpringerLink, 2023) Aslan, Yavuz; Koçak, Orhan
This study aimed to examine the relationships between family infuence on career choices with perceived social support, vocational outcome expectations, and life satisfaction of university students. Correlational research method was used in the study. The results showed that family infuence on career choices and perceived social support were positive and signifcant predictors of vocational outcome expectations and life satisfaction. In addition, vocational outcome expectations was a positive and signifcant predictor of life satisfaction. Vocational outcome expectations partially mediated the relationship between family infuence on career choices, perceived social support, and life satisfaction.
Mppt Control for PV Systems with Analytical Analysis Fractional Open Circuit Voltage Method
(IEEE, 2022) Çakmak, Fevzi; Tür, Mehmet Rıda; Tür, Mehmet Rıda
Abstract— In this study, analytical resolved fractional open circuit voltage (FOCV) maximum power point tracking (MPPT) method is presented. The proposed method is obtained by calculating it by utilizing the single diode circuit of the PV module, while measuring the open circuit voltage (Voc) by interrupting the power of other open circuit voltage methods. Vmpp is obtained by multiplying the obtained Voc voltage with the coefficient. The voltage variation (E) is obtained by the subtraction between the panel voltage (Vpv) and the Vmpp voltage. It is applied as an input to the PI controller by multiplying the Ki factor to limit the voltage variation (E). The PI Controller generates the required duty cycle for the DC-DC converter. The most important advantage of this method is acquaring open circuit voltage without power interruption. The proposed method operated effectively at different radiation and temperature values. For the proposed method, it has simulated in Matlab/Simulink program using SHARP NDQ295 model PV panel.

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