WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Enhancing Mode Transition Dynamics in Non-Inverting Buck-Boost Inverters for PV Systems(Institute of Electrical and Electronics Engineers Inc., 2026) Keskinkilic, E.; Tekgun, B.Quasi-single-stage inverters (QSSIs) are notable for their simple structure and bidirectional operation capability in applications such as photovoltaic (PV) systems. Among these QSSI, the non-inverting buck-boost inverter (NIBBI) or four-switch buck-boost inverter (FSBBI) is often preferred due to its ability to perform both step-down and step-up operations. However, when traditional control is used, achieving a smooth transition and efficient conversion becomes challenging as the output voltage approaches the input voltage. The pulse width ratio limitations and non-idealities of active and passive components are the cause of this. In this paper, a comparative analysis of the mode transition techniques in FSBBI is presented using methods available for DC/DC converters. System efficiency and output voltage signal quality are selected as performance metrics. A 2-kW FSBBI is installed and controlled using single, two, modified two, three, and four-mode techniques. Simulation and experimental studies were conducted to validate the results. Based on these studies, the four-mode control technique was observed to be the most effective in eliminating dead zone effects, reducing total harmonic distortion (THD), and achieving the highest system efficiency in a PV system where a battery powers the AC load. Experimental results indicate that the four-mode modulation attained an efficiency of 95.49% with a THD of 2.97%. © 1986-2012 IEEE.Article Citation - WoS: 40Citation - Scopus: 49Spatio-Temporal Rich Model-Based Video Steganalysis on Cross Sections of Motion Vector Planes(Institute of Electrical and Electronics Engineers Inc., 2016-07) Taşdemir, K.; Kurugöllü, F.; Sakir Sezer, S.; Sezer, SakirA rich model-based motion vector (MV) steganalysis benefiting from both temporal and spatial correlations of MVs is proposed in this paper. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this paper. First, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring MVs for longer distances. Therefore, temporal MV dependency alongside the spatial dependency is utilized for rigorous MV steganalysis. Second, unlike the filters previously used, which were heuristically designed against a specific MV steganography, a diverse set of many filters, which can capture aberrations introduced by various MV steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in the previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-Temporal range and provides a better cover model. The proposed method is tested against the most prominent MV steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in MV steganalysis field, including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads. © 2016 Elsevier B.V., All rights reserved.