Recent Submissions

  • Ultrasonic array characterization in multiscattering and attenuating media using pin targets 

    Kumru, Y.; Köymen, Hayrettin (Cornell University, 2021-05-31)
    This paper presents an approach to characterize ultrasonic imaging arrays using pin targets in commercial test phantoms. We used a 128-element phased array transducer operating at 7.5 MHz with a fractional bandwidth of ...
  • Coded divergent waves for fast ultrasonic imaging: Optimization and comparative performance analysis 

    Kumru, Y.; Köymen, Hayrettin (Cornell University, 2021-04-21)
    In this paper, we present the optimal use of coded signals in diverging wave transmission for fast ultrasonic imaging. The performance of coded imaging with diverging waves, quantified by SNR, CNR, speckle power and target ...
  • Signal-to-noise ratio of diverging waves in multiscattering media: Effects of signal duration and divergence angle 

    Kumru, Y.; Köymen, Hayrettin (AIP Publishing, 2022-01-18)
    In this paper, SNR maximization in coded diverging waves is studied, and experimental verification of the results is presented. Complementary Golay sequences and binary phase shift keying modulation are used to code the ...
  • Steady-state and first passage time distributions for waiting times in the MAP/M/s+G queueing model with generally distributed patience times 

    Gürsoy, Ömer; Mehr, Kamal Adli; Akar, Nail (AIMS Press, 2021)
    We study the MAP/M/s+G queueing model that arises in various multi-server engineering problems including telephone call centers, under the assumption of MAP (Markovian Arrival Process) arrivals, exponentially distributed ...
  • Author Correction: A robust benchmark for detection of germline large deletions and insertions 

    Zook, J. M.; Hansen, N. F.; Olson, N. D.; Chapman, L.; Mullikin, J. C.; Xiao, C.; Sherry, S.; Koren, S.; Phillippy, A. M.; Boutros, P. C.; Sahraeian, S. M. E.; Huang, V.; Rouette, A.; Alexander, N.; Mason, C. E.; Hajirasouliha, I.; Ricketts, C.; Lee, J.; Tearle, R.; Fiddes, I. T.; Barrio, A. M.; Wala, J.; Carroll, A.; Ghaffari, N.; Rodriguez, O. L.; Bashir, A.; Jackman, S.; Farrell, J. J.; Wenger, A. M.; Alkan, Can; Söylev, A.; Schatz, M. C.; Garg, S.; Church, G.; Marschall, T.; Chen, K.; Fan, X.; English, A. C.; Rosenfeld, J. A.; Zhou, W.; Mills, R. E.; Sage, J. M.; Davis, J. R.; Kaiser, M. D.; Oliver, J. S.; Catalano, A. P.; Chaisson, M. J. P.; Spies, N.; Sedlazeck, F. J.; Salit, M. (Nature Research, 2020)
    New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and ...
  • Exceptional adaptable MWIR thermal emission for ordinary objects covered with thin VO2 film 

    Durna, Yılmaz; Kocer, Hasan; Aydın, Koray; Cakir, Mehmet Cihan; Soydan, Mahmut Can; Odabasi, Oguz; Işık, Halil; Ozbay, Ekmel (Elsevier Ltd, 2021-01-25)
    Monotonous thermal radiation emitted from an ordinary object can be brought into a dynamic and versatile form that can be shaped according to the application area with the ingenious design of the surface coatings. Building ...
  • Adaptive measurement matrix design in compressed sensing based direction of arrival estimation 

    Kılıç, Berkan; Güngör, Alper; Kalfa, Mert; Arıkan, Orhan (IEEE, 2021)
    Design of measurement matrices is an important aspect of compressed sensing (CS) based direction of arrival (DoA) applications that enables reduction in the analog channels to be processed in sparse target environments. ...
  • Combinatorial Gaussian process bandits with probabilistically triggered arms 

    Demirel, İlker; Tekin, Cem (Microtome Publishing, 2021)
    Combinatorial bandit models and algorithms are used in many sequential decision-making tasks ranging from item list recommendation to influence maximization. Typical algorithms proposed for combinatorial bandits, including ...
  • Abstract 207: the cBioPortal for cancer genomics 

    Gao, J.; Mazor, T.; de Bruijn, I.; Abeshouse, A.; Baiceanu, D.; Erkoç, Z.; Gross, B.; Higgins, D.; Jagannathan, P. K.; Kalletla, K.; Kumari, Priti; Kundra, R.; Li, X.; Lindsay, J.; Lisman, A.; Lukasse, P.; Madala, D.; Madupuri, R.; Ochoa, A.; Plantalech, O.; Quach, J.; Rodenburg, S.; Satravada, A.; Schaeffer, F.; Sheridan, R.; Sikina, L.; Sümer, S. O.; Sun, Y.; van Dijk, P.; van Nierop, P.; Wang, A.; Wilson, M.; Zhang, H.; Zhao, G.; van Hagen, S.; van Bochove, K.; Doğrusöz, Uğur; Heath, A.; Resnick, A.; Pugh, T. J.; Sander, C.; Cerami, E.; Schultz, N. (American Association for Cancer Research (AACR), 2021)
    The cBioPortal for Cancer Genomics is an open-source software platform that enables interactive, exploratory analysis of large-scale cancer genomics data sets with a user-friendly interface. It integrates genomic and ...
  • The pulse shape effect on signal-to-noise ratio for φ-OTDR systems 

    Uyar, Faruk; Nehir, Anıl; Kartaloğlu, Tolga; Özbay, Ekmel; Özdur, İ. (Optica Publishing Group, 2021)
    We experimentally investigate the effect of the probe pulse shape on the performance of φ-OTDR based distributed vibration sensors by comparing the SNR values for rectangular, Gaussian and triangular pulses.
  • Spatial resolution analysis of dual-pulse ϕ-OTDR systems 

    Yıldız, Muhammed Kaan; Uyar, Faruk; Kartaloğlu, Tolga; Özbay, Ekmel; Özdur, İ. (Optica Publishing Group, 2021)
    This work analyzes the spatial resolution of the dual-pulse -OTDR systems by changing the dual-pulse parameters and demonstrates that the spatial resolution corresponds to half of the fiber region occupied by the dual-pulse train.
  • State of the art and prospects for Halide Perovskite nanocrystals 

    Dey, A.; Ye, J.; De, A.; Debroye, E.; Ha, S. K.; Bladt, E.; Kshirsagar, A. S.; Wang, Z.; Yin, J.; Wang, Y.; Quan, L. N.; Yan, F.; Gao, M.; Li, X.; Shamsi, J.; Debnath, T.; Cao, M.; Scheel, M. A.; Kumar, S.; Steele, J. A.; Gerhard, M.; Chouhan, L.; Xu, K.; Wu, X-g; Li, Y.; Zhang, Y.; Han, C.; Dutta, A.; Vincon, I.; Rogach, A. L.; Nag, A.; Samanta, A.; Korgel, B. A.; Shih, C.-J.; Gamelin, D. R.; Son, D. H.; Zeng, H.; Zhong, H.; Sun, H.; Demir, Hilmi Volkan; Scheblykin, I. G.; Mora-Seró, I.; Stolarczyk, J. K.; Zhang, J. Z.; Feldmann, J.; Hofkens, J.; Luther, J. M.; Pérez-Prieto, J.; Li, L.; Manna, L.; Bodnarchuk, M. I.; Kovalenko, M. V.; Roeffaers, M. B. J.; Pradhan, N.; Mohammed, O. F.; Bakr, O. M.; Yang, P.; Müller-Buschbaum, P.; Kamat, P. V.; Bao, Q.; Zhang, Q.; Krahne, R.; Galian, R. E.; Stranks, S. D.; Bals, S.; Biju, V.; Tisdale, W. A.; Yan, Y.; Hoye, R. L. Z.; Polavarapu, L. (American Chemical Society, 2021-06-17)
    Metal-halide perovskites have rapidly emerged as one of the most promising materials of the 21st century, with many exciting properties and great potential for a broad range of applications, from photovoltaics to optoelectronics ...
  • Spatiotemporal sequence prediction with point processes and self-organizing decision trees 

    Karaahmetoğlu, Oğuzhan; Serdar Kozat, Süleyman (Institute of Electrical and Electronics Engineers, 2021-09-22)
    We study the spatiotemporal prediction problem and introduce a novel point-process-based prediction algorithm. Spatiotemporal prediction is extensively studied in machine learning literature due to its critical real-life ...
  • Multi-label sentiment analysis on 100 languages with dynamic weighting for label imbalance 

    Yılmaz, Selim Fırat; Kaynak, Ergün Batuhan; Koç, Aykut; Dibeklioğlu, Hamdi; Kozat, Süleyman Serdar (Institute of Electrical and Electronics Engineers, 2021-07-19)
    We investigate cross-lingual sentiment analysis, which has attracted significant attention due to its applications in various areas including market research, politics, and social sciences. In particular, we introduce a ...
  • Achieving online regression performance of LSTMs with simple RNNs 

    Vural, Nuri Mert; İlhan, Fatih; Yılmaz, Selim Fırat; Ergüt, S.; Kozat, Süleyman Serdar (Institute of Electrical and Electronics Engineers, 2021-06-17)
    Recurrent neural networks (RNNs) are widely used for online regression due to their ability to generalize nonlinear temporal dependencies. As an RNN model, long short-term memory networks (LSTMs) are commonly preferred in ...
  • Driver modeling through deep reinforcement learning and behavioral game theory 

    Albaba, Berat Mert; Yıldız, Yıldıray (Institute of Electrical and Electronics Engineers, 2021-05-05)
    In this work, a synergistic combination of deep reinforcement learning and hierarchical game theory is proposed as a modeling framework for behavioral predictions of drivers in highway driving scenarios. The modeling ...
  • Markovian RNN: an adaptive time series prediction network with HMM-based switching for nonstationary environments 

    İlhan, Fatih; Karaahmetoğlu, Oğuzhan; Balaban, İ.; Kozat, Süleyman Serdar (Institute of Electrical and Electronics Engineers, 2021-08-09)
    We investigate nonlinear regression for nonstationary sequential data. In most real-life applications such as business domains including finance, retail, energy, and economy, time series data exhibit nonstationarity due ...

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