Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Article Citation - WoS: 101Citation - Scopus: 129Scientific Applications of Distributed Acoustic Sensing: State-Of Review and Perspective(MDPI, 2022) Gorshkov, Boris G.; Yüksel, Kıvılcım; Fotiadi, Andrei A.; Wuilpart, Marc; Korobko, Dmitry A.; Zhirnov, Andrey A.; Lobach, Ivan A.This work presents a detailed review of the development of distributed acoustic sensors (DAS) and their newest scientific applications. It covers most areas of human activities, such as the engineering, material, and humanitarian sciences, geophysics, culture, biology, and applied mechanics. It also provides the theoretical basis for most well-known DAS techniques and unveils the features that characterize each particular group of applications. After providing a summary of research achievements, the paper develops an initial perspective of the future work and determines the most promising DAS technologies that should be improved.Article Citation - WoS: 10Citation - Scopus: 13On the Characterization of Cognitive Tasks Using Activity-Specific Short-Lived Synchronization Between Electroencephalography Channels(Elsevier, 2021) Olcay, B. Orkan; Özgören, Murat; Karaçalı, BilgeAccurate characterization of brain activity during a cognitive task is challenging due to the dynamically changing and the complex nature of the brain. The majority of the proposed approaches assume stationarity in brain activity and disregard the systematic timing organization among brain regions during cognitive tasks. In this study, we propose a novel cognitive activity recognition method that captures the activity-specific timing parameters from training data that elicits maximal average short-lived pairwise synchronization between electroencephalography signals. We evaluated the characterization power of the activity-specific timing parameter triplets in a motor imagery activity recognition framework. The activity-specific timing parameter triplets consist of latency of the maximally synchronized signal segments from activity onset Delta t, the time lag between maximally synchronized signal segments t, and the duration of the maximally synchronized signal segments w. We used cosine-based similarity, wavelet bi-coherence, phase-locking value, phase coherence value, linearized mutual information, and cross-correntropy to calculate the channel synchronizations at the specific timing parameters. Recognition performances as well as statistical analyses on both BCI Competition-III dataset IVa and PhysioNet Motor Movement/Imagery dataset, indicate that the interchannel short-lived synchronization calculated using activity-specific timing parameter triplets elicit significantly distinct synchronization profiles for different motor imagery tasks and can thus reliably be used for cognitive task recognition purposes. (C) 2021 Elsevier Ltd. All rights reserved.Article Citation - WoS: 24Citation - Scopus: 26Fiber Bragg Grating Regeneration at 450°c for Improved High Temperature Sensing(The Optical Society, 2019) Chah, Karima; Yüksel, Kıvılcım; Kinet, Damien; Yazd, Nazila Safari; Megret, Patrice; Caucheteur, ChristopheType-I fiber Bragg gratings photo-inscribed in hydrogen-loaded B/Ge co-doped silica single-mode optical fibers have been regenerated efficiently at 450 degrees C, which is the lowest temperature reported so far. The mechanical strength of the annealed fiber is preserved while ensuring temperature sensing of the regenerated gratings up to 900 degrees C. Unlike low temperature cycles (<= 600 degrees C), an annealing process at higher temperatures revealed faster regeneration for strong gratings. Changes in grating strength were also measured before the regeneration cycle. These behaviors suggest the contribution of different mechanisms to the regeneration process with different relative dynamics. (C) 2019 Optical Society of America.Article Citation - WoS: 19Citation - Scopus: 21Spectral Shadowing Suppression Technique in Phase-Otdr Sensing Based on Weak Fiber Bragg Grating Array(The Optical Society, 2019) de Miguel Soto, Veronica; Jason, Johan; Kurtoğlu, Deniz; Lopez-Amo, Manuel; Wuilpart, MarcA postprocessing procedure is presented to suppress spectral shadowing in phase-OTDR sensing systems based on a weak fiber Bragg grating array. A complete theoretical analysis of the interfering signals has been carried out to identify a compensation method. The proposed approach has been applied to simulated and experimental phase-OTDR in the context of vibration measurements. Fast Fourier transform has been employed to analyze the obtained results, which has verified the validity of the proposed method to suppress spectral shadowing. (C) 2019 Optical Society of AmericaArticle Citation - WoS: 18Citation - Scopus: 19Generalized Bayesian Model Selection for Speckle on Remote Sensing Images(Institute of Electrical and Electronics Engineers Inc., 2019) Karakuş, Oktay; Kuruoğlu, Ercan E.; Altınkaya, Mustafa AzizSynthetic aperture radar (SAR) and ultrasound (US) are two important active imaging techniques for remote sensing, both of which are subject to speckle noise caused by coherent summation of back-scattered waves and subsequent nonlinear envelope transformations. Estimating the characteristics of this multiplicative noise is crucial to develop denoising methods and to improve statistical inference from remote sensing images. In this paper, reversible jump Markov chain Monte Carlo (RJMCMC) algorithm has been used with a wider interpretation and a recently proposed RJMCMC-based Bayesian approach, trans-space RJMCMC, has been utilized. The proposed method provides an automatic model class selection mechanism for remote sensing images of SAR and US where the model class space consists of popular envelope distribution families. The proposed method estimates the correct distribution family, as well as the shape and the scale parameters, avoiding performing an exhaustive search. For the experimental analysis, different SAR images of urban, forest and agricultural scenes, and two different US images of a human heart have been used. Simulation results show the efficiency of the proposed method in finding statistical models for speckle.Article Citation - WoS: 14Citation - Scopus: 17Evaluation of Synchronization Measures for Capturing the Lagged Synchronization Between Eeg Channels: a Cognitive Task Recognition Approach(Elsevier, 2019) Olcay, Bilal Orkan; Karaçalı, BilgeDuring cognitive, perceptual and sensory tasks, connectivity profile changes across different regions of the brain. Variations of such connectivity patterns between different cognitive tasks can be evaluated using pairwise synchronization measures applied to electrophysiological signals, such as electroencephalography (EEG). However, connectivity-based task recognition approaches achieving viable recognition performance have been lacking from the literature. By using several synchronization measures, we identify time lags between channel pairs during different cognitive tasks. We employed mutual information, cross correntropy, cross correlation, phase locking value, cosine similarity and nonlinear interdependence measures. In the training phase, for each type of cognitive task, we identify the time lags that maximize the average synchronization between channel pairs. These lags are used to calculate pairwise synchronization values with which we construct the train and test feature vectors for recognition of the cognitive task carried out using Fisher's linear discriminant (FLD) analysis. We tested our framework in a motor imagery activity recognition scenario on PhysioNet Motor Movement/Imagery and BCI Competition-III IVa datasets. For PhysioNet dataset, average performance results ranging between % 51 and % 61 across 20 subjects. For BCI Competition-III dataset, we achieve an average recognition performance of % 76 which is above the minimum reliable communication rate (% 70). We achieved an average accuracy over the minimum reliable communication rate on the BCI Competition-III dataset. Performance levels were lower on the PhysioNet dataset. These results indicate that a viable task recognition system is achievable using pairwise synchronization measures evaluated at the proper task specific lags.Article Citation - WoS: 26Citation - Scopus: 27Implementation of a Mobile Platform Based on Fiber Bragg Grating Sensors for Automotive Traffic Monitoring(MDPI, 2020) Yüksel, Kıvılcım; Kinet, Damien; Chah, Karima; Caucheteur, ChristopheInstrumentation techniques, implementation and installation methods are major concerns in today's distributed and quasi-distributed monitoring applications using fiber optic sensors. Although many successful traffic monitoring experiments have been reported using Fiber Bragg Gratings (FBGs), there has been no standardized solution proposed so far to have FBG seamlessly implemented in roads. In this work, we investigate a mobile platform including FBG sensors that can be positioned on roads for the purpose of vehicle speed measurements. The experimental results prove the efficiency of the proposed platform, providing a perspective toward weigh-in-motion systems.Article Citation - WoS: 59Citation - Scopus: 57Cmos Enabled Microfluidic Systems for Healthcare Based Applications(John Wiley and Sons Inc., 2018) Hussian, Muhammad M.; Khan, Sherjeel M.; Gümüş, Abdurrahman; Nassar, Joanna M.With the increased global population, it is more important than ever to expand accessibility to affordable personalized healthcare. In this context, a seamless integration of microfluidic technology for bioanalysis and drug delivery and complementary metal oxide semiconductor (CMOS) technology enabled data-management circuitry is critical. Therefore, here, the fundamentals, integration aspects, and applications of CMOS-enabled microfluidic systems for affordable personalized healthcare systems are presented. Critical components, like sensors, actuators, and their fabrication and packaging, are discussed and reviewed in detail. With the emergence of the Internet-of-Things and the upcoming Internet-of-Everything for a people–process–data–device connected world, now is the time to take CMOS-enabled microfluidics technology to as many people as possible. There is enormous potential for microfluidic technologies in affordable healthcare for everyone, and CMOS technology will play a major role in making that happen.Article Citation - WoS: 560Citation - Scopus: 607A Community Effort To Assess and Improve Drug Sensitivity Prediction Algorithms(Nature Publishing Group, 2014) Costello, James C.; Heiser, Laura M.; Georgii, Elisabeth; Gönen, Mehmet; Menden, Michael P.; Wang, Nicholas J.; Bansal, Mukesh; Ammad-ud-din, Muhammad; Hintsanen, Petteri; Khan, Suleiman A.; Mpindi, John-Patrick; Kallioniemi, Olli; Honkela, Antti; Aittokallio, Tero; Wennerberg, Krister; NCI-DREAM Community; Karaçalı, Bilge; Collins, James J.; Gallahan, Dan; Singer, Dinah; Saez-Rodriguez, Julio; Kaski, Samuel; Gray, Joe W.; Stolovitzky, GustavoPredicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods.Article Citation - WoS: 240Citation - Scopus: 264A Community Computational Challenge To Predict the Activity of Pairs of Compounds(Nature Publishing Group, 2014) Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P.; Costello, James C.; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M.; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J.; Shen, Yao; NCI-DREAM Community; Karaçalı, Bilge; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, AndreaRecent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.