Phd Degree / Doktora

Permanent URI for this collectionhttps://hdl.handle.net/11147/2869

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COAR Access Rights: search.filters.coarAccessRights.open accessDepartment: search.filters.department.Thesis (Doctoral)--İzmir Institute of Technology, Electrical and Electronics Engineering

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Now showing 1 - 10 of 24
  • Doctoral Thesis
    Effects of Electromagnetic Fields on the Performance of Molecular Communications
    (01. Izmir Institute of Technology, 2022) Taşçı, Aslı; Atakan, Barış
    This thesis analyzes molecular communication (MC) systems’ performance under electromagnetic fields. The aim of the thesis is to model and study molecular behavior under electromagnetic fields (EMF). The thesis starts with the theoretical explanation of classic electromagnetism. The directional and thermal changes are the main effects of EMF on particles. The directional effects of EMF are studied with regard to electromagnetic forces. The applied electromagnetic forces are presented for different types of particles. The effect of EMF on magnetically susceptible particles is analyzed in particular. Furthermore, molecular movement is analyzed by considering four fundamental forces on diffusing molecules under EMF. The energy transfer between EMF and particles is studied to understand the thermal effects of EMF. AnMCscheme that transmits information with magnetically susceptible molecules is studied in the second part of the thesis. The molecular type and the configuration of EMF are studied to understand the effect of EMF on the diffusion rate. The effects of magnetic field gradient (MFG) and concentration gradient magnetic force (CGMF) are analyzed to model the change in the diffusion rate and concentration of magnetically susceptible molecules. The last part of the thesis focuses on molecular dynamics under EMF. The effect of thermal changes on the molecular reaction rate and binding kinetics is modeled with reaction-diffusion systems. The specific reaction rate constant is analyzed to determine the effect of temperature change caused by the EMF. The movement of molecules is modeled by Langevin’s diffusion model. The probability distribution functions of the molecule’s velocity and displacement are studied to understand and model the molecular behavior under EMF. Moreover, the mean-squared displacement is employed to analyze the diffusion type under EMF.
  • Doctoral Thesis
    Modeling and Analysis of Molecular Signals in Multiscale Molecular Communication
    (01. Izmir Institute of Technology, 2021) Güleç, Fatih; Atakan, Barış
    This thesis focuses on modeling, analysis, and novel experimental techniques in molecular communication (MC). The objective of this thesis is to develop novel engineering solutions and modeling approaches to enable MC applications. The first part of the thesis is about microscale MC studies. In this part, a model of how a receiver nanomachine measures and reconstructs a molecular signal is proposed with a probabilistic approach. In the second part, macroscale MC studies with active transmitters are given. An experimental setup which includes a sprayer emitting alcohol molecules as a transmitter and an alcohol sensor as the receiver is employed. Using the data collected by this setup, five statistical methods, a feature extraction algorithm and the fluid dynamics-based distance estimation algorithm are proposed for distance estimation. Furthermore, a novel droplet-based signal reconstruction approach to channel modeling is proposed. Moreover, MC is utilized to propose an end-to-end system model which considers pathogen-laden cough/sneeze droplets as the input and the infection state of the human as the output. In addition, the concept of mobile human ad hoc network which exploits the similarity of airborne transmission-driven human groups with mobile ad hoc networks and uses MC as the enabling paradigm is introduced. Finally, macroscale MC studies with passive transmitters are detailed in the third part. A novel experimental platform which consists of an evaporating alcohol source and a sensor network is proposed. A sensor network based clustered localization algorithm is proposed to estimate the location of the passive transmitter.
  • Doctoral Thesis
    On the Characterization of Motor Imagery Functions Based on Systematic Timing Organization of the Human Brain
    (01. Izmir Institute of Technology, 2021) Olcay, Bilal Orkan; Karaçalı, Bilge
    The main objective of this thesis is to analyze the timing organization of the brain. The human brain is known to adjust its localized and also the reciprocal operations for each different cognitive task adaptively. This flexibility of the brain has attracted considerable interest in neuroscience. Elucidation of timing adaptation property of brain, however, remains as unresolved due to dynamically changing and nonlinear nature of the brain. In this thesis, we characterize the timing organization of the brain during motor imagery activity using electroencephalography signals. First, we propose a novel motor imagery activity recognition method that relies on the activity-specific time-lag between electroencephalography signals obtained from different brain regions. Next, we generalize this approach into three-parameter formulation to determine the timing profiles of activity-specific short-lived synchronization. The identification of activity-specific timing parameters was carried out using a heuristic approach that maximizes the average pairwise channel synchronizations during associated activity periods. Thereafter, we propose a novel BCI framework that find and use the timings of electroencephalography signals of localized brain regions that elicit localized activity-specific features. We identify the timings for each different brain regions by adopting a heuristic-probabilistic method. Finally, we propose a novel autoregressive modeling framework that finds a representative model for each different cognitive activity. We demonstrated the efficacy of the proposed methods on publicly available brain-computer interfacing datasets on motor imagery. The performance results indicate that considering the timing organization of the brain is crucial for accurate characterization of cognitive activity. In addition, it may also account for the inconsistency of brain computer interfacing performance obtained from different subjects.
  • Doctoral Thesis
    A Study on Entangled Photon Pairs in Graded-Index Optical Fibers
    (Izmir Institute of Technology, 2021) Ekici, Çağın; Dinleyici, Mehmet Salih
    Quantum optics offer new possibilities, new approaches, and potentially groundbreaking new technologies whose backbone is based on creation, manipulation, and detection of special quantum states of light. The main objective of the thesis is to present a study of spontaneously arisen heralded entangled photon-pairs which play crucial role in emerging quantum enhanced technologies. We have mainly investigated discrete transverse-spatial-mode entangled photon-pairs in waveguide, because it intrinsically offers infinite dimension. Entangled states of higher dimensional systems enable realization of quantum information schemes that can offer higher information density coding and show more error resilience than can be achieved with lower dimensional systems. In this context, we have exploited a graded-index optical fiber as photon-pair-generation platform via nonlinear intermodal-four-wave mixing (FWM), since the fiber may allow different FWM processes to overlap in spectral domain, resulting in an entangled pair of spatial qubits. We have also probed joint spectral properties of the generated photons to show capability of hyperentanglement in frequency and transverse mode. We have discussed spatial Wigner function and its realization to characterize spatial properties of the quantum state. We have shown that entanglement can be verified through a violation of the Clauser - Horne - Shimony - Holt (CHSH) inequality based on spatial Wigner function and coupled-mode theory. This thesis also includes basic analysis of transverse-mode entangled photon-pair distribution in a lossy-dispersive medium. Finally, the ways to follow and the quantities to measure are touched upon. Thus, we have explained the generation and four different detection schemes, relying on a combination of photon-number statistics, joint spectral properties, and spatial entanglement measurements.
  • Doctoral Thesis
    Medium-Aware Inference for Wireless Sensor Networks
    (Izmir Institute of Technology, 2020) Wahdan, Muath Abed Alrauf; Altınkaya, Mustafa Aziz
    In a wireless sensor network, multilevel quantization is necessary in order to find a compromise between the smallest possible power consumption of the sensors and the detection performance at the fusion center (FC). The general methodology is using distance measures such as J-divergence (JD) and Bhattacharyya distance in this quantization. This thesis proposes a different approach which is based on maximizing the average output entropy of the sensors under both hypotheses of a binary hypothesis test and utilizes it in a Neyman-Pearson (NP) criterion based distributed detection scheme in order to detect a point source. Firstly, a deterministic signal and isotropic propagation model is considered. The receiver operating characteristics of the proposed maximum average entropy (MAE) meth\-od in quantizing sensor outputs was obtained 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. Secondly, the sequential testing version of the first problem is considered for both unquantized and quantized data transmissions. MAE and maximum JD (MJD) quantization methods for $M$-levels were applied in the sequential probability ratio test of Wald. The average sample number (ASN) required for the target probabilities of detection and a false alarm was the performance criterion: the smaller, the better. The performance of this test improves monotonically with the number of local sensors. Lastly, spatial correlation of the sensors is taken into the account. For this case, a Gaussian isotropic event source was applied. The computational requirements in evaluating multidimensional cumulative densities necessitated proposing a rectangular grid model of sensor deployment and block-diagonal approximations of covariance matrix related to the event signal at the sensors without losing generality. The simulation studies show the success of the MAE both in the cases of fusing error-free sensor outputs and in the case where the effect of the wireless channel is incorporated. As expected the performance gets better as the level of quantization increases and with six-level quantization, it approaches the performance of non-quantized data transmission. In the sequential tests again MAE was more successful compared to MJD resulting in smaller ASNs. It was observed that spatial correlation degrades system performance.
  • Doctoral Thesis
    Stability Analysis and Control of Stochastic Power Systems
    (Izmir Institute of Technology, 2019) Yılmaz, Serpil; Savacı, Ferit Acar
    Increase of the electricity generation and the growth of global electricity consumption lead to an increase in the power fluctuations. In this dissertation, we have proposed a novel approach by modeling these fluctuations as alpha-stable Levy processes. We have focused on the stability analysis and control for stochastic single machine infinite bus system with an emphasis on (1) understanding the effect of impulsive and asymmetric power fluctuations on the rotor angle stability, and (2) developing control rule for synchronism in the presence of Wiener and alpha-stable Levy type power fluctuations. We have investigated the basin stability over the parameter space of mechanical power and damping parameters in the presence of alpha-stable Levy type load fluctuations. The probabilities of returning to the stable equilibrium point have been calculated for different characteristic exponent and skewness parameters of alpha-stable Levy motion to see the effect of impulsive and asymmetric load fluctuations. It has been shown that the impulsiveness and/or asymmetry in the distributions of the load fluctuations can cause the instability of the rotor angle. Hence, the synchronism is lost and the rotor angle despite being stable in the sense of probability, might not be stable in the mean square sense. Furthermore, we have studied the control of the rotor angle stability of single machine infinite bus power system in the presence of Wiener type stochastic fluctuations by minimizing the stochastic sensitivity function. We have also derived an analytical expression for the rotor angle dispersion of single machine infinite bus system in the presence of alpha-stable Levy type power fluctuations. The control rule for the minimization of the rotor angle dispersion has been achieved.
  • Doctoral Thesis
    Random Communication Systems Based on Alpha-Stable Processes
    (Izmir Institute of Technology, 2018) Ahmed, Areeb; Savacı, Ferit Acar; Ahmed, Areeb; Savacı, Ferit Acar
    This thesis presents alpha-stable carrier based random communication systems (RCSs) as an alternate way to perform covert transmission. The first objective is to develop an optimized model of RCS which consists of a receiver that requires less computational complexity and outperforms the previously proposed receivers. Next, in order to solve the existing synchronization issue in RCSs, the general behavior of fractional lower-order covariance method in α-stable noise environments has been evaluated to establish synchronization in RCSs. An optimized range of values for the associated parameters of α-stable carrier has also been presented to optimize the proposed synchronization method. The second objective is to establish criteria for evaluating and quantifying the security and covertness of RCSs. Therefore, the first security performance tradeoff characteristics (SPTC) have been proposed to compare the security of different RCSs. Moreover, the proposed optimized model of RCS has also been analyzed with respect to the developed security scale, i.e. SPTC. Secondly, the criterion to quantify the covertness of RCSs has also been developed to analyze the proposed RCS. Thirdly, an attack for RCS has also been proposed which highlights the potential vulnerabilities of RCSs. However, the counter-measure guidelines have been prescribed to further enhance the security of RCSs. An inverse system approach has been adopted to propose α-stable noise driven linear time invariant system based transmitter and its corresponding inverse system based receiver as a third objective. It can be considered as the most secure model for αstable noise carrier based RCS till now.
  • Doctoral Thesis
    Generalized Bayesian model selection using reversible jump Markov chain Monte Carlo
    (Izmir Institute of Technology, 2017) Karakuş, Oktay; Altınkaya, Mustafa Aziz; Kuruoğlu, Ercan Engin
    The main objective of this thesis is to suggest a general Bayesian framework for model selection based on reversible jump Markov chain Monte Carlo (RJMCMC) algorithm. In particular, we aim to reveal the undiscovered potentials of RJMCMC in model selection applications by exploiting the original formulation to explore spaces of di erent classes or structures and thus, to show that RJMCMC o ers a wider interpretation than just being a trans-dimensional model selection algorithm. The general practice is to use RJMCMC in a trans-dimensional framework e.g. in model estimation studies of linear time series, such as AR and ARMA and mixture processes, etc. In this thesis, we propose a new interpretation on RJMCMC which reveals the undiscovered potentials of the algorithm. This new interpretation, firstly, extends the classical trans-dimensional approach to a much wider meaning by exploring the spaces of linear and nonlinear models in terms of the nonlinear (polynomial) time series models. Polynomial process modelling is followed by the definition of a new type of RJMCMC move that performs transitions between various generic model spaces irrespective of model sizes. Then, we apply this new framework to the identification of Volterra systems with an application of nonlinear channel estimation of an OFDM communication system. The proposed RJMCMC move has been adjusted to explore the spaces of di erent distribution families by matching the common properties of the model spaces such as norm, and this leads us to perform a distribution estimation study of the observed real-life data sets including, impulsive noise in power-line communications, seismic acceleration time series, remote sensing images, etc. Simulation results demonstrate the remarkable performance of the proposed method in nonlinearity degree estimation and in transitions between di erent classes of models. The proposed method uses RJMCMC in an unorthodox way and reveals its potential to be a general estimation method by performing the reversible jump mechanism between spaces of di erent model classes.
  • Doctoral Thesis
    Development of a Unified Analysis Framework for Multicolor Flow Cytometry Data Based on Quasi-Supervised Learning
    (Izmir Institute of Technology, 2017) Köktürk Güzel, Başak Esin; Karaçalı, Bilge
    In this dissertation, automatic compensation and gating strategies are investigated for multi-color flow cytometry data analysis. We propose two clustering algorithms that combine the quasi-supervised learning algorithm with an expectation-maximization routine for automatic gating. The quasi-supervised learning algorithm estimates the posterior probabilities of the different cell populations at each sample in a dataset in a manner that does not involve fitting a parametric model to the data. We have developed two different binary divisive clustering algorithms based on expectation maximization with responsibility values calculated using the quasi-supervised learning algorithm instead of the probabilistic models used in conventional expectation maximization applications. Our clustering algorithms determine the number of clusters in run-time by measuring the overlap between the estimated clusters in each provisional division and comparing it with the previous one to determine whether the division is warranted or not. Since this type of clustering is indifferent to the underlying distribution of dataset, it is well suited to automatic flow cytometry gating. The second clustering algorithm improves upon the first one using a simulated annealing approach. Its iterative structure allows finding the global minimum of a cost functional that achieves the best separation point by gradually smoothing the decision regions in each iteration. Finally, we have developed a joint diagonalization and clustering method for automatic compensation of flow data based on the methods above. The proposed method identifies cell sub groups using the annealing-based model-free expectation-maximization algorithm and finds a data transformation matrix that achieves orthogonality of the covariance structure of each identified cell cluster using fast Frobenius diagonalization. We have tested all proposed algortihms on both synthetically created datasets and real multi-color flow cytometry datasets. The results show that our automated gating algorithms are very successful in identifying the distinct cell groups so long as there is enough statistical evidence for their presence. In addition, the automated compensation procedure was also successfully applied on the synthetically created dataset and real multi-color flow cytometry data of lymphocytes that are a low autofluorescence cell group. However, the automated compensation algorithm needs further study to be generalized to high autofluorescence cell types where proper compensation does not necessarily coincide with an orthogonal covariance structure.
  • Doctoral Thesis
    Control of Redundant Robot Manipulators With Telerobotic Applications
    (Izmir Institute of Technology, 2016) Çetin, Kamil; Tatlıcıoğlu, Enver
    This thesis focuses on task-space control of kinematically redundant robot manipulators with telerobotic applications. The first aim is to design asymptotically stable sub-task controllers for kinematically redundant robot manipulators subject to parametric uncertainties in their dynamics. Initially, a novel combined analysis of the task-space tracking and sub-task controllers is performed for redundant robots having only one extra degree of freedom. Next, an extended task-space controller is designed by integrating manipulator Jacobian with the sub-task Jacobian. Both controllers ensure task-space tracking and sub-task objectives at the amount of redundant degree of freedom. As the second aim, two robust control methods are proposed for task-space tracking of robot manipulators. First, a novel continuous robust controller is designed despite dynamic model and Jacobian uncertainties to ensure asymptotic task-space tracking while requiring measurements of joint positions and velocities. Then, a robust output feedback controller is proposed to ensure ultimately bounded task-space tracking requiring neither measurements of joint positions or velocities nor accurate knowledge of kinematic and dynamic models. The third aim is to develop a passive decomposition method for task-space control of bilateral teleoperation systems. The proposed method ensures coordination of master and slave robots while achieving a desired overall motion for the bilateral teleoperation system. The proposed method is firstly considered for teleoperation systems consisting of kinematically similar master and slave robots, then extended to be applicable to kinematically redundant teleoperation systems. Simulation and experimental studies are performed to present the viability of the proposed methods.