Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Article Secrecy performance of full-duplex space-air integrated networks in the presence of active/passive eavesdropper, and friendly jammer(Wiley, 2024) Buyuksar, Ayse Betul; Erdoğan, Eylem; Altunbas, IbrahimIn this paper, a full-duplex (FD) space-air ground integrated network (SAGIN) system with passive and active eavesdroppers (PE/AE) and a friendly jammer (FJ) is investigated. The shadowing side information (SSI)-based unmanned aerial vehicle relay node (URN) selection strategy is considered to improve signal-to-interference plus noise power ratio (SINR) at the ground destination unit. To quantify the secrecy performance of the considered scenario, outage probability (OP), interception probability (IP), and transmission secrecy outage probability (TSOP) are investigated in the presence of FJ and PE/AE. The results have shown that aerial AE is an important threat since it can severely degrade the OP of the main transmission link. Furthermore, the FJ can decrease the IP of the eavesdropper by causing interference with the cost of power consumption of URNs. Simulations are performed to verify the theoretical findings.Article Citation - WoS: 5Citation - Scopus: 6A Comparative Study of Metaheuristic Feature Selection Algorithms for Respiratory Disease Classification(MDPI, 2024) Gürkan Kuntalp, D.; Özcan, N.; Düzyel, Okan; Kababulut, F.Y.; Kuntalp, M.The correct diagnosis and early treatment of respiratory diseases can significantly improve the health status of patients, reduce healthcare expenses, and enhance quality of life. Therefore, there has been extensive interest in developing automatic respiratory disease detection systems. Most recent methods for detecting respiratory disease use machine and deep learning algorithms. The success of these machine learning methods depends heavily on the selection of proper features to be used in the classifier. Although metaheuristic-based feature selection methods have been successful in addressing difficulties presented by high-dimensional medical data in various biomedical classification tasks, there is not much research on the utilization of metaheuristic methods in respiratory disease classification. This paper aims to conduct a detailed and comparative analysis of six widely used metaheuristic optimization methods using eight different transfer functions in respiratory disease classification. For this purpose, two different classification cases were examined: binary and multi-class. The findings demonstrate that metaheuristic algorithms using correct transfer functions could effectively reduce data dimensionality while enhancing classification accuracy. © 2024 by the authors.Conference Object Carrier Frequency Offset Based Shared Randomness for Secure Transmission in M-Psk Noma(IEEE, 2023) Göztepe, Caner; Karabulut Kurt, Güneş; Özbek, BernaPower domain non-orthogonal multiple access (NOMA) enhances spectral efficiency by superposing multiple users in the same time-frequency resource block at the expense of exposing the users' data. However, current approaches to improve the secrecy levels of users are limited to rate reduction. This paper proposes a secure NOMA system based on the shared randomness extracted from the reciprocal carrier frequency offsets (CFOs) between the transmitter-receiver pairs for M-ary phase-shift keying. As multiple users will have physically separated oscillators, it will result in independent CFOs among users. This randomness is used to introduce a constellation rotation in the transmitted symbols. We show that under ideal CFO estimates, the proposed approach achieves perfect secrecy among all NOMA users without introducing any rate reduction. We also demonstrate the practical applicability of the proposed approach by using a software-defined radio-based test bed. © 2023 IEEE.Article Citation - WoS: 4Citation - Scopus: 4A New Shapley-Based Feature Selection Method in a Clinical Decision Support System for the Identification of Lung Diseases(MDPI, 2023) Kababulut, Fevzi Yasin; Kuntalp, Damla Gurkan; Düzyel, Okan; Özcan, Nermin; Kuntalp, MehmetThe aim of this study is to propose a new feature selection method based on the class-based contribution of Shapley values. For this purpose, a clinical decision support system was developed to assist doctors in their diagnosis of lung diseases from lung sounds. The developed systems, which are based on the Decision Tree Algorithm (DTA), create a classification for five different cases: healthy and disease (URTI, COPD, Pneumonia, and Bronchiolitis) states. The most important reason for using a Decision Tree Classifier instead of other high-performance classifiers such as CNN and RNN is that the class contributions of Shapley values can be seen with this classifier. The systems developed consist of either a single DTA classifier or five parallel DTA classifiers each of which is optimized to make a binary classification such as healthy vs. others, COPD vs. Others, etc. Feature sets based on Power Spectral Density (PSD), Mel Frequency Cepstral Coefficients (MFCC), and statistical characteristics extracted from lung sound recordings were used in these classifications. The results indicate that employing features selected based on the class-based contribution of Shapley values, along with utilizing an ensemble (parallel) system, leads to improved classification performance compared to performances using either raw features alone or traditional use of Shapley values.Conference Object Citation - Scopus: 2Compact Proton Accelerator in Uhf Band at Kahvelab(JACoW Publishing, 2022) Esen, S.; Adıgüzel, A.; Koçer, O.; Çağlar, A.; Çelebi, E.; Öz, S.; Özcan, V.E.; Karatay, Anıl; Yaman, Fatih; Yılmaz, Hasan ÖnderProton Test Beam at KAHVELab (Kandilli Detector, Accelerator and Instrumentation Laboratory) project aims to design and produce a radio frequency quadrupole (RFQ) operating at 800 MHz in Istanbul, Turkey using the local resources. The beamline consists of a proton source, a low energy beam transport (LEBT) line including the beam diagnostic section and the RFQ cavity itself. This RFQ is 4-vane, 1-meter-long cavity to accelerate the 20 keV beam extracted from plasma ion source to 2 MeV. Its engineering prototype is already produced and subjected to mechanical, low power RF and vacuum tests. In this study, the results of the first test production, especially the bead-pull test setup will be discussed. © 2022 Proceedings - Linear Accelerator Conference, LINAC. All rights reserved.Conference Object Citation - Scopus: 2Rf Measurements and Tuning of the Test Module of 800 Mhz Radio-Frequency Quadrupole(JACoW Publishing, 2022) Kılıçgedik, A.; Adıgüzel, A.; Esen, S.; Baran, B.; Çağlar, A.; Çelebi, E.; Özcan, V. E.; Kaya, U.; Türemen, G.; Ünel, N. G.; Yaman, FatihThe 800 MHz RFQ (radio-frequency quadrupole), developed and built at KAHVElab (Kandilli Detector, Accelerator and Instrumentation Laboratory) at Bogazici University in Istanbul, Turkey, has been designed to provide protons that have an energy of 2 MeV within only 1 m length. The RFQ consists of two modules and the test module of RFQ was constructed. The algorithm developed by CERN, based on the measurements generated by the tuner settings estimated through the response matrix [1, 2, 3], has been optimized for a single module and 16 tuners. The desired field consistent with the simulation was obtained by bead-pull measurements. In this study, we present low-power rf measurements and field tuning of the test module. © 2022 Proceedings - Linear Accelerator Conference, LINAC. All rights reserved.Article Enhancing Thickness Determination of Nanoscale Dielectric Films in Phase Diffraction-Based Optical Characterization Systems With Radial Basis Function Neural Networks(IOP Publishing, 2023) Ataç, Enes; Karatay, Anıl; Dinleyici, Mehmet SalihAccurate determination of the optical properties of ultra-thin dielectric films is an essential and challenging task in optical fiber sensor systems. However, nanoscale thickness identification of these films may be laborious due to insufficient and protracted classical curve matching algorithms. Therefore, this experimental study presents an application of a radial basis function neural network in phase diffraction-based optical characterization systems to determine the thickness of nanoscale polymer films. The non-stationary measurement data with environmental and detector noise were subjected to a detailed analysis. The outcomes of this investigation are benchmarked against the linear discriminant analysis method and further verified by means of scanning electron microscopy. The results show that the neural network has reached a remarkable accuracy of 98% and 82.5%, respectively, in tests with simulation and experimental data. In this way, rapid and precise thickness estimation may be realized within the tolerance range of 25 nm, offering a significant improvement over conventional measurement techniques.Correction Corrections To “massive Mimo-Noma Based Mec in Task Offloading for Delay Minimization”(IEEE, 2023) Yılmaz, Saadet Simay; Özbek, Berna[No abstract available]Conference Object A Framework for Physical Layer Network Coding With Multiple Antennas for Bpsk(IEEE, 2023) İlgüy, Mert; Özbek, BernaPhysical layer network coding (PNC) is combined with multiple antennas to increase the spectral efficiency of wireless communication systems. In this work, we present a PNC framework including both uplink and downlink for binary phase shift keying (BPSK). In the uplink, we propose a scheme for detecting network-coded symbol (NCS) with reduced complexity. For the downlink, we propose a transmission scheme of NCS through maximum ratio transmission (MRT) by defining the precoding vector as an average of users' channels. The bit-error-rate (BER) performances and the comparison results with the conventional scheme in both downlink and uplink are provided for the proposed low-complexity PNC framework.Article Sensory and Sensorimotor Gating in Children With Subclinical Hypothyroidism(2023) Kocaaslan Atlı, Sibel; Olgaç Dündar, Nihal; Erdoğan, Uğraş; Evirgen Esin, Nur; Bayazıt, Turan Onur; Kahya, Mehmet Cemal; Çatlı, Gönül; Gençpınar, Pınar; Dündar, Bumin NuriObjective: Attention and learning problems have been reported in children diagnosed with subclinic hypothyroidism (SH). Sensory gating is an automatic phenomenon that is related to attentional processes. It is known that an impairment in sensory/sensorimotor gating negatively affects the signal processing mechanism and hence attention and learning processes. The aim of the present study was to evaluate the effect of SH on sensory gating processes via P50 suppression and prepulse inhibition (PPI) in children. Methods: Fifteen children aged 8-16 years, diagnosed with SH, and 15 healthy children were included in the study. Auditory P50 suppression and PPI paradigms were applied during the recordings. P50 suppression was examined via auditory brain potentials recorded by electroencephalography. PPI was evaluated via electromyography, in which the blink reflex was recorded by oculomotor muscle activity. Results: No statistical difference was found in P50 suppression and PPI processes between children in the SH and control groups. These findings indicate that the sensory gating processes children with SH are not affected. Conclusion: The findings of this study show that the sensory gating processes of SH children are not affected. However, considering that brain maturation continues until the age of 20s, it may be more useful to scrutinize these processes with a wider age range and a larger number of participants to reveal more clearly how sensory gating is affected by SH.