Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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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: 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.Editorial Guest Editorial for Signal Processing Aspects of Molecular Communications(Elsevier, 2022) Atakan, Barış; Galmés, Sebastià; Haselmayr, Werner; Farsad, Nariman; Nakano, TadashiMolecular communication is the most widespread communication mechanism on the Earth since it is fundamental for all living entities from unicellular organisms to multicellular animals and plants to maintain their vital functionalities. For example, many unicellular organisms sense and react to molecular signals from their surroundings to control their life cycles. Some signaling molecules called pheromone are also extensively employed by a variety of insects to send and receive information to coordinate colony activities. Moreover, in the neuronal system, signaling molecules known as neurotransmitters are used in junction points of neuron cells to carry out many mental activities. In addition to the various molecular communication mechanisms in nature, the recent advances in nano- and biotechnology have shown that molecular communication is one of the most favorable choices to enable the interconnection of nanomachines such as engineered cells and bionanorobots. The network of such nanomachines, i.e., nanonetwork, is considered to make frontier biomedical applications a reality. In these applications, molecular communication can enable the nanomachines to share information so as to provide reliability and controllability. Furthermore, this can also allow different nanomachine populations to be coordinated to reach highly sophisticated behavior and increase the number of design possibilities.Article Citation - WoS: 1Maximum Average Entropy-Based Quantization of Local Observations for Distributed Detection(Elsevier, 2022) Wahdan, Muath A.; Altınkaya, Mustafa AzizIn a wireless sensor network, multilevel quantization is necessary to find a compromise between minimizing the power consumption of sensors and maximizing the detection performance at the fusion center (FC). The previous methods have been using distance measures such as J-divergence and Bhattacharyya distance in this quantization. This work proposes a different approach based on the maximum average entropy of the output of the sensors under both hypotheses and utilizes it in a Neyman-Pearson criterion-based distributed detection scheme to detect a point source. The receiver operating characteristics of the proposed maximum average entropy (MAE) method in quantizing sensor outputs have been evaluated for multilevel quantization both when the sensor outputs are available error-free at the FC and when non-coherent M-ary frequency shift keying communication is used for transmitting MAE based multilevel quantized sensor outputs over a Rayleigh fading channel. The simulation studies show the success of the MAE in the cases of both error-free fusion and where the effect of the wireless channel has been incorporated. As expected, the performance improves as the level of quantization increases and with six-level quantization approaches the performance of non-quantized data transmission.Article Citation - WoS: 7Citation - Scopus: 9Fluid dynamics-based distance estimation algorithm for macroscale molecular communication(Elsevier, 2021) Güleç, Fatih; Atakan, BarışMany species, from single-cell bacteria to advanced animals, use molecular communication (MC) to share information with each other via chemical signals. Although MC is mostly studied in microscale, new practical applications emerge in macroscale. It is essential to derive an estimation method for channel parameters such as distance for practical macroscale MC systems which include a sprayer emitting molecules as a transmitter (TX) and a sensor as the receiver (RX). Due to the similarity between sneezing/coughing and spraying mechanisms, these practical systems have the potential to be applied in modeling airborne pathogen (viruses, bacteria, etc.) transmission with a MC perspective where an infected human emitting pathogen-laden droplets is considered as a TX. In this paper, a novel approach based on fluid dynamics is proposed for the derivation of the distance estimation in practical MC systems. According to this approach, transmitted molecules are considered as moving and evaporating droplets in the MC channel. With this approach, the Fluid Dynamics-based Distance Estimation (FDDE) algorithm which predicts the propagation distance of the transmitted droplets by updating the diameter of evaporating droplets at each time step is proposed. FDDE algorithm is validated by experimental data. The results reveal that the distance can be estimated by the fluid dynamics approach which introduces novel parameters such as the volume fraction of droplets in a mixture of air and liquid droplets and the beamwidth of the TX. Furthermore, the effect of the evaporation is shown with the numerical results. (C) 2021 Elsevier B.V. All rights reserved.Article Citation - WoS: 7Citation - Scopus: 8Implementation and Experimental Verifications of Microstrip Antennas for Angular Scanning of a Doppler Radar(Elsevier, 2019) Karatay, Anıl; Orcan, Durmuş; Özkal, Ceren; Yaman, FatihThe aim of this study is to improve operational capabilities and range of the MIT-Coffee Can Doppler radar via aperture coupled Vivaldi type transmitter antenna, patch array receiver antenna, and an unequal power divider. Accordingly, a mechanical angular scanning feature for tracking multi-targets and the system integration of lightweight microstrip structures are realized for the radar. A narrow beamwidth in the receiver and a well impedance matching on the overall system to reduce return losses are achieved for the considered application. Good agreements between simulations and measurements for the fabricated antennas/divider and a successful integration of the antennas to the existing system for finding a moving target angular location is reported. It is shown that through wall identification and target velocity at scanned regions can be obtained with the proposed hardware configuration. Simulation results of antenna parameters for various number of array elements are listed which could be a useful tool for different engineering applications. (C) 2019 Elsevier GmbH. All rights reserved.