Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Correction Corrections To “massive Mimo-Noma Based Mec in Task Offloading for Delay Minimization”(IEEE, 2023) Yılmaz, Saadet Simay; Özbek, Berna[No abstract available]Article Citation - WoS: 2Citation - Scopus: 2A Non-Resonant Approach for Dielectric Constant Reconstructions Via Newton Iterations(Elsevier, 2023) Özkal, Ceren; Yaman, FatihIn this study, a Newton–Raphson-based iterative method has been proposed to obtain dielectric constants accurately from measurements. The originalities of the approach lie in its applicability at non-resonant frequencies, which brings a significant experimental simplicity by avoiding critical coupling, expansion of available frequencies in different bands with the same cost-efficient low-Q (?60) cavity. The direct problem involves either measuring power values inside a cavity (14.6 × 5 × 20.6) cm via a spectrum analyzer or simulating the complete setup via CST-MWS software at one of the non-resonant modes, 1.5 GHz. The solution to the inverse problem provides fastly converging results with an error rate of 1% for the unknown permittivities. The experiments were carried out using five different liquid samples even though the proposed technique does not have a limitation on solid materials. Applicability and the effectiveness of the introduced method is illustrated in detail and comparisons with the perturbation method is provided. © 2023 Elsevier GmbHArticle Citation - WoS: 6Citation - Scopus: 7Time-Resolved Eeg Signal Analysis for Motor Imagery Activity Recognition(Elsevier, 2023) Olcay, Bilal Orkan; Karaçalı, BilgeAccurately characterizing brain activity requires detailed feature analysis in the temporal, spatial, and spectral domains. While previous research has proposed various spatial and spectral feature extraction methods to distinguish between different cognitive tasks, temporal feature analysis for each separate brain region and frequency band has been largely overlooked. This study introduces two novel approaches for recognizing cognitive activity: temporal entropic profiling and time-aligned common spatio-spectral patterns analysis. These approaches capture and use discriminative short-lived signal segments for motor imagery activity recognition. In Approach-1, we evaluated nine different measures to determine timing parameters that showed altered behavior associated with maximal inter-activity differences, which we then used in a machine-learning framework. In Approach-2, we used the best-performing signal characteristic measures from Approach-1 to determine the optimum latency of each channel at each frequency band for a CSP-based activity recognition strategy. We evaluated both approaches on two online available motor imagery EEG datasets and achieved average recognition accuracy levels of 86%. We compared our methods with four established BCI methods. The performance results show that our approaches exceeded the benchmark methods' performances, with notable improvements in the proposed time-aligned common spatio-spectral patterns approach. This study demonstrates that motor imagery recognition performance is improved when a temporal analysis is adopted alongside spatio-spectral neural feature analysis and that timing parameters associated with the maximal entropic difference of EEG segments to the cognitive tasks varied between different brain regions and subjects. © 2023 Elsevier LtdArticle Citation - WoS: 1Citation - Scopus: 1Experimental Demonstration of a Transient Grating Controlled All-Optical Switch(IOP Publishing, 2023) Akın, Osman; Dinleyici, Mehmet SalihWe demonstrate an on-fiber all-optical switching device based on a transient grating formed by the interference of control laser pulses in a Kerr-type nonlinear material placed in the evanescent region of the fiber. The device can operate in two distinctive modes. First, switching/coupling among the fiber modes using bulk index modulation was investigated and an efficiency of about %0.55 @852 nm was measured. Second, by exploiting Four Wave Mixing (FWM), an all-optical switching that transfers power among light signals with wavelengths of λ 1 = 440 nm and λ 2 = 663 nm was achieved by quasi-phase-matching and fRequency matching in a nonlinear thin polymeric film. The results prove that the introduced switching structure may have the potential to be used in integrated photonic applications such as intensity modulators or controllable couplers.Article Citation - WoS: 1Citation - Scopus: 1Resting Electroencephalography Differences Between Eyes-Closed and Eyes-Open Conditions in Children With Subclinical Hypothyroidism(AVES, 2023) Bayazıt, Onur; Kahya, Mehmet Cemal; Çatlı, Gönül; Kocaaslan Atlı, Sibel; Olgaç Dündar, Nihal; Erdoğan, Uğraş; Evirgen Esin, NurObjective: Electroencephalography changes that occur during the transition from eyes-closed to the eyes-open state in resting condition are related to the early phase of sensory processing and are defined as activation. The present study aimed to reveal the potential deteriorations that may occur in the initial period of sensory processing in resting electroencephalography between children with subclinical hypothyroidism and a control group. Materials and Methods: Electroencephalographies of 15 children with subclinical hypothy-roidism and 15 healthy children aged 10 to 17 years were recorded for 2 minutes for EC and 2 minutes for eyes-open conditions in resting state. Absolute electroencephalography band powers (μV2) within the delta, theta, alpha, and beta frequency bands were calculated in Fz, Cz, Pz, and Oz electrodes, respectively, for eyes-closed and eyes-open conditions. Results: The results show that, although there was no noteworthy difference between the powers of the electroencephalography frequency bands of children with subclinical hypothyroidism and healthy children during the eyes-open condition, the alpha powers of the control group were significantly higher in all electrodes during the eyes-closed condition. Furthermore, the powers of all frequency bands were observed to decrease in the eyes-open condition in the control group. However, the same net decrease was not observed in the frequency powers of children with subclinical hypothyroidism. Conclusion: According to the results of this study, children with subclinical hypothyroidism may experience information processing impairments starting in the early stages of sensory processing. © 2023, AVES. All rights reserved.Article Citation - WoS: 15Citation - Scopus: 17Massive Mimo-Noma Based Mec in Task Offloading for Delay Minimization(IEEE, 2023) Yilmaz, Saadet Simay; Özbek, BernaMobile edge computing (MEC) has been considered a promising technology to reduce task offloading and computing delay by enabling mobile devices to offload their computation-intensive tasks. Non-orthogonal multiple access (NOMA) is regarded as a promising method of increasing spectrum efficiency, while Massive multiple-input multiple-output (MIMO) can support a larger number of users for simultaneous offloading. These two technologies can effectively facilitate offloading and further improve the performance of MEC systems. In this work, we propose a NOMA and Massive MIMO assisted MEC system for delay-sensitive applications. Our objective is to minimize the overall computing and transmission delay under users' transmit power and MEC computing capability. Through the pairing scheme for Massive MIMO-NOMA, the users with the higher channel gain can offload all their data, while the users with the lower channel gain can offload a portion of their data to the MEC. Performance results are provided regarding to the sum data rate and overall system delay compared with the orthogonal multiple access (OMA)-MIMO based and Massive MIMO (M-MIMO) based MEC systems.Article Citation - WoS: 7Citation - Scopus: 10Analysis of Crosstalk Effects in Phase-Otdr System Using Fiber Bragg Grating Array(Elsevier, 2023) Koçal, Ertunga Burak; Yüksel, Kıvılcım; Wuilpart, MarcIn this paper, the parasitic components (i.e., multi-reflections, Rayleigh scattering, photodetector noise, and phase variations due to external perturbations) are analysed and based on this analysis, a new signal to noise ratio (SNR) definition is provided suitable for the FBG-assisted Phase-OTDR system. A detailed analysis of performance parameters in the presence of multi reflection crosstalk (including its first- and second-order components) and spectral shadowing crosstalk is presented. SNR was calculated for different reflectivity and spacing lengths showing that the maximum number of cascaded FBGs can be significantly increased by using lower FBG reflectivity. It was also observed that the spacing length distance does not have a significant impact on the maximum number of FBGs that can be interrogated. By comparing single-pulse and double-pulse configurations, the use of double pulse was shown to provide higher SNR values when the number of FBGs is around 100 FBGs. The multi-reflection crosstalk when combined with the spectral-shadowing effect was demonstrated to create secondary crosstalk components making the interpretation of spectral analysis more difficult.Article Citation - WoS: 3Citation - Scopus: 3Current Sensing Using a Phase-Sensitive Optical Time Domain Reflectometer: Feasibility Study(Elsevier, 2022) Wuilpart, Marc; Şirin, Şamil; Yüksel Aldoğan, KıvılcımA novel method for distributed current sensing using an FBG-assisted Phase-OTDR with Mach-Zehnder Interferometer is proposed. The detrimental effect of the intrinsic linear birefringence of the sensing fiber is solved by calibration. An FBG pair is written at the two ends of the spun fiber coil to eliminate phase fading and increase the measurement accuracy. A simulation tool was developed to reveal the feasibility of the approach by investigating the impact of the detector noise as well as the effects of bending- and FBG-induced linear birefringence on the sensing performance.Article Citation - WoS: 4Citation - Scopus: 4Mobile human ad hoc networks: A communication engineering viewpoint on interhuman airborne pathogen transmission(Elsevier, 2022) Güleç, Fatih; Atakan, Barış; Dressler, FalkoA number of transmission models for airborne pathogens transmission, as required to understand airborne infectious diseases such as COVID-19, have been proposed independently from each other, at different scales, and by researchers from various disciplines. We propose a communication engineering approach that blends different disciplines such as epidemiology, biology, medicine, and fluid dynamics. The aim is to present a unified framework using communication engineering, and to highlight future research directions for modeling the spread of infectious diseases through airborne transmission. We introduce the concept of mobile human ad hoc networks (MoHANETs), which exploits the similarity of airborne transmission-driven human groups with mobile ad hoc networks and uses molecular communication as the enabling paradigm. In the MoHANET architecture, a layered structure is employed where the infectious human emitting pathogen-laden droplets and the exposed human to these droplets are considered as the transmitter and receiver, respectively. Our proof-of-concept results, which we validated using empirical COVID-19 data, clearly demonstrate the ability of our MoHANET architecture to predict the dynamics of infectious diseases by considering the propagation of pathogen-laden droplets, their reception and mobility of humans.Article Citation - WoS: 22Citation - Scopus: 26Adaptive Sign Algorithm for Graph Signal Processing(Elsevier, 2022) Yan, Yi; Kuruoğlu, Ercan Engin; Altınkaya, Mustafa AzizEfficient and robust online processing techniques for irregularly structured data are crucial in the current era of data abundance. In this paper, we propose a graph/network version of the classical adaptive Sign algorithm for online graph signal estimation under impulsive noise. The recently introduced graph adaptive least mean squares algorithm is unstable under non-Gaussian impulsive noise and has high computational complexity. The Graph-Sign algorithm proposed in this work is based on the minimum dispersion criterion and therefore impulsive noise does not hinder its estimation quality. Unlike the recently proposed graph adaptive least mean pth power algorithm, our Graph-Sign algorithm can operate without prior knowledge of the noise distribution. The proposed Graph-Sign algorithm has a faster run time because of its low computational complexity compared to the existing adaptive graph signal processing algorithms. Experimenting on steady-state and time-varying graph signals estimation utilizing spectral properties of bandlimitedness and sampling, the Graph-Sign algorithm demonstrates fast, stable, and robust graph signal estimation performance under impulsive noise modeled by alpha stable, Cauchy, Student's t, or Laplace distributions.