WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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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.Conference Object Citation - WoS: 1Citation - Scopus: 1Microgrid Environmental Impact(Institute of Electrical and Electronics Engineers Inc., 2020-09-28) Al-Agtash, Salem Y.; al-Hashem, Mohammad; Batarseh, Mohanad; Bintoudi, Angelina D.; Tsolakis, Apostolos Charalampos; Tzovaras, Dimitrios K.; Hadjidemetriou, Lenos; Khiat, MounirPower plants have bad impacts on the environment. One of these impacts is Carbon Dioxide (CO2) emission resulted from power plants that depend on fossil fuel, oil and natural gas. Renewable energy is considered as an important solution for this problem since it is classified as clean and environmentally friendly source of energy and helps reducing the dependency on conventional power plants. High renewable energy penetration into power systems is a big challenge that can be solved by deploying the concept of smart Micro-Grids. This paper presents a study on how much reduction of CO2 emission can be resulted from deploying smart micro-grid concept on a university campus, German Jordanian University (GJU) campus was taken as a pilot. The micro-grid is meant to operate according to an optimum resource scheduling framework that guarantee a minimum operational cost while achieving high local power availability. © 2020 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 17Citation - Scopus: 37Channel Model of Molecular Communication Via Diffusion in a Vessel-Like Environment Considering a Partially Covering Receiver(Institute of Electrical and Electronics Engineers Inc., 2018-06) Turan, Meric; Kuran, Mehmet Şükrü; Yilmaz, Huseyin Birkan; Demirkol, Ilker; Tuǧcu, Tuna; Birkan Yilmaz, H.By considering potential health problems that a fully covering receiver may cause in vessel-like environments, the implementation of a partially covering receiver is needed. To this end, distribution of hitting location of messenger molecules (MM) is analyzed within the context of molecular communication via diffusion with the aim of channel modeling. The distribution of these MMs for a fully covering receiver is analyzed in two parts: angular and radial dimensions. For the angular distribution analysis, the receiver is divided into 180 slices to analyze the mean, standard deviation, and coefficient of variation of these slices. For the axial distance distribution analysis, Kolmogorov-Smirnov test is applied for different significance levels. Also, two different implementations of the reflection from the vessel surface (i.e., rollback and elastic reflection) are compared and mathematical representation of elastic reflection is given. The results show that MMs have tendency to spread uniformly beyond a certain ratio of the distance to the vessel radius. By utilizing the uniformity, we propose a channel model for the partially covering receiver in vessel-like environments and validate the proposed model by simulations. © 2018 Elsevier B.V., All rights reserved.Article Citation - Scopus: 1A Laser-Assisted Cellular Electrophysiology Measurement System(Institute of Electrical and Electronics Engineers Inc., 2021-02-01) Seymen, A.A.; Özgür, E.; Soran-Erdem, Z.; Ortaç, B.Patch-clamp technique is the gold standard for cellular electrophysiological measurements, which is capable of measuring single ion transport events across the cell membrane. However, the measurement possesses significant complexities, and it requires a high level of expertise, while its experimental throughput is nevertheless considerably low. Here, we suggest and experimentally demonstrate a laser-Assisted method for performing cellular electrophysiological measurements. Femtosecond laser pulses, coupled to an optical microscope, are used to form a sub-micrometer hole on a thin polymer membrane separating two electrodes, where a nearby cell is subsequently placed onto the hole by negative pressure. Afterwards, the cell is punctured using subsequent laser exposure, revealing the cell membrane over the hole for electrophysiological recording. This system could be used to increase the output amount of the electrophysiological measurements substantially. © 2021 Elsevier B.V., All rights reserved.
