Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 6Citation - Scopus: 10Using Chemosensory-Induced Eeg Signals To Identify Patients With <i>de Novo</I> Parkinson's Disease(Elsevier Sci Ltd, 2024) Olcay, Orkan; Onay, Fatih; Ozturk, Guliz Akin; Oniz, Adile; Ozgoren, Murat; Hummel, Thomas; Guducu, CagdasObjective: Parkinson's disease (PD) patients generally exhibit an olfactory loss. Hence, psychophysical or electrophysiological tests are used for diagnosis. However, these tests are susceptible to the subjects' behavioral response bias and require advanced techniques for an accurate analysis. Proposed Approach: Using well-known feature extraction methods, we characterized chemosensory-induced EEG responses of the participants to classify whether they have PD. The classification was performed for different time intervals after chemosensory stimulation to see which temporal segment better separates healthy controls and subjects with de novo PD. Results: The performances show that entropy and connectivity features discriminate effectively PD and HC participants when olfactory-induced EEG signals were used. For these methods, discrimination is over 80% for segments 100-700 and 200-800 milliseconds after stimulus onset. Comparison with Existing Methods: We compared the performance of our framework with linear predictive coding, bispectrum, wavelet entropy-based methods, and TDI score-based classification. While the entropy- and connectivity-based methods elicited the highest classification performances for olfactory stimuli, the linear predictive coding-based method elicited slightly higher performance than our framework when the trigeminal stimuli were used. Conclusion: This is one of the first studies that use chemosensory-induced EEG signals along with different feature extraction methods to classify healthy subjects and subjects with de novo PD. Our results show that entropy and functional connectivity methods unravel the chemosensory-induced neural dynamics encapsulating critical information about the subjects' olfactory performance. Furthermore, time- and frequency-resolved feature analysis is beneficial for capturing disease-affected neural patterns.Article 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 Power transmission entropy(Inderscience Enterprises Ltd., 2008) Özdemir, SerhanMechanical transmissions have been characterised traditionally by their transmission efficiencies. This is given by the ratio of the output to the input of the transmitted power. Unfortunately, the power transmission phenomenon is slightly more complex than that. As any designer would agree, each of these transmission localities is a source of uncertainty. Once formulated, this statement of uncertainty would reflect the designer's trust in the transmission. By virtue of the proposed approach, power transmission is no longer a deterministic entity but becomes a probabilistic one. This paper discusses the overlooked uncertainty inherent in every transmission.Article Citation - WoS: 10Citation - Scopus: 12Statistical Approach To Tunneling Time in Attosecond Experiments(Academic Press Inc., 2017) Demir, Durmuş Ali; Güner, TuğrulTunneling, transport of particles through classically forbidden regions, is a pure quantum phenomenon. It governs numerous phenomena ranging from single-molecule electronics to donor–acceptor transition reactions. The main problem is the absence of a universal method to compute tunneling time. This problem has been attacked in various ways in the literature. Here, in the present work, we show that a statistical approach to the problem, motivated by the imaginary nature of time in the forbidden regions, lead to a novel tunneling time formula which is real and subluminal (in contrast to various known time definitions implying superluminal tunneling). In addition to this, we show explicitly that the entropic time formula is in good agreement with the tunneling time measurements in laser-driven He ionization. Moreover, it sets an accurate range for long-range electron transfer reactions. The entropic time formula is general enough to extend to the photon and phonon tunneling phenomena.Conference Object Citation - Scopus: 3Entropik Kümeleme Kullanılarak Beyin Aktivitesi Karakterizasyonu(IEEE, 2017) Olcay, Bilal Orkan; Karacali, Bilge; Ozgoren, Murat; Guducu, CagdaIn this study, two novel entropy and mutual information based algorithms have been proposed to characterize the stimulus specific brain activity. In the first method, inter channel mutual information of electroencephalography signals has been calculated and the channels that exhibit synchronized behaivour during stimulus. In the second method, the responsiveness of the individual channels has been characterized in an entropic manner and then, the channels which demonstrates stimulus specific entropic behavior have been obtained. The performance of the proposed methods has been simulated on a real dataset obtained from Dokuz Eylul University Brain Biophysics laboratory. The results demonstrate that different regions of the brain exhibit a coherent activity during stimulus.Article Citation - WoS: 2Citation - Scopus: 2Estimating Probability Density Functions and Entropies of Chua's Circuit Using B-Spline Functions(World Scientific Publishing Co. Pte Ltd, 2012) Savacı, Ferit Acar; Güngör, Mesutn this paper, first the probability density functions (PDFs) of the states of Chua's circuit have been estimated using B-spline functions and then the state entropies of Chua's circuit with respect to the bifurcation parameter have been obtained. The results of the proposed B-spline density estimator have been compared with the results obtained from the Parzen density estimator. © 2012 World Scientific Publishing Company.Article Citation - WoS: 6Citation - Scopus: 7Classification of Manipulators of the Same Origin by Virtue of Compactness and Complexity(Elsevier Ltd., 2011) Gezgin, Erkin; Özdemir, SerhanThis work deals with a classification method that employs concepts such as complexity and compactness. The idea is to classify manipulators, or any other mechanism for that matter, of the same origin, based on the geometry of the joints, the tasks performed by the joints, the efficiency and the manufacturing cost to generate the specified efficiency. It is known that successive units on a single branch create individual uncertainties that affect the eventual quality of the performed operation [1]. An entropic expression quantifies this uncertainty in terms of the number of links and the unit effectiveness. The concepts of compactness and complexity have been formulated, and these concepts are explained through serial and parallel manipulators with varying parameters. Eventually, a cost function is created which is a function of complexity, uncertainty and the manufacturing cost. A worked example on M = 6 Stewart-Gough platform is given how this cost function could be taken advantage of when deciding an initial manipulator. A genetic algorithm is used for the optimization of the cost function, where the results are tabulated.Article Citation - WoS: 36Citation - Scopus: 44Continuous Time Wavelet Entropy of Auditory Evoked Potentials(Elsevier Ltd., 2010) Çek, Mehmet Emre; Özgören, Murat; Savacı, Ferit AcarIn this paper, the continuous time wavelet entropy (CTWE) of auditory evoked potentials (AEP) has been characterized by evaluating the relative wavelet energies (RWE) in specified EEG frequency bands. Thus, the rapid variations of CTWE due to the auditory stimulation could be detected in post-stimulus time interval. This approach removes the probability of missing the information hidden in short time intervals. The discrete time and continuous time wavelet based wavelet entropy variations were compared on non-target and target AEP data. It was observed that CTWE can also be an alternative method to analyze entropy as a function of time. © 2009 Elsevier Ltd. All rights reserved.Article Citation - WoS: 8Citation - Scopus: 8Measures of Uncertainty in Power Split Systems(Elsevier Ltd., 2007) Özdemir, SerhanThis paper discusses the overlooked uncertainty inherent in every transmission. The uncertainty aspect has been often, for the sake of clarity, ignored. Instead, mechanical transmissions have been characterized traditionally by their transmission efficacies. It is known that transmission localities are sources of power loss, depending on many factors, hence sources of uncertainty. Thus each transmission of power should not only be designated by a constant of efficiency but also by an expression of uncertainty, reflecting the probability of transmission. Furthermore, Shannon's and Renyi's expressions of entropy have been used to quantify this so-called transmission uncertainty. The entropy of a transmitting unit is given in these two forms and then compared. Practical formulations for flow optimization are given.Article Citation - WoS: 13Citation - Scopus: 16Thermochromism in Oligothiophenes: the Role of the Internal Rotation(American Chemical Society, 2002) Elmacı, Nuran; Yurtsever, ErsinThe relation between thermochromism in polythiophenes and the internal rotation is studied by density-functional theory (DFT). For head-to-tail methyl-substituted thiophenes, rotational potential maps of dimer and trimer are calculated. With time-dependent-DFT methodology the absorption spectra of these oligomers in UV-vis region are calculated as functions of the torsional angles. Theoretical temperature-dependent UV-vis spectra are generated from the distribution of torsional angles. The results show that the internal rotation alone is not sufficient to explain the mechanism of thermochromism.