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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Robust speech recognition using adaptively denoised wavelet coefficients(IEEE, 2004) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; N/A; Tekalp, Ahmet Murat; Erzin, Engin; Akyol, Emrah; Faculty Member; Faculty Member; Master Student; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 26207; 34503; N/AThe existence of additive noise affects the performance of speech recognition in real environments. We propose a new set of feature vectors for robust speech recognition using denoised wavelet coefficients. The use of wavelet coefficients in speech processing is motivated by the ability of the wavelet transform to capture both time and frequency information and the non-stationary behaviour of speech signals. We use one set of noisy data, such as data with car noise, and we use hard thresholding in the best basis for denoising. We use isolated digits as our database in our HMM based speech recognition system. A performance comparison of hard thresholding denoised wavelet coefficients and MFCC feature vectors is presented.Publication Metadata only A support function based algorithm for optimization with eigenvalue constraints(Siam Publications, 2017) N/A; Department of Mathematics; Mengi, Emre; Faculty Member; Department of Mathematics; College of Sciences; 113760Optimization of convex functions subject to eigenvalue constraints is intriguing because of peculiar analytical properties of eigenvalue functions and is of practical interest because of a wide range of applications in fields such as structural design and control theory. Here we focus on the optimization of a linear objective subject to a constraint on the smallest eigenvalue of an analytic and Hermitian matrix-valued function. We propose a numerical approach based on quadratic support functions that overestimate the smallest eigenvalue function globally. the quadratic support functions are derived by employing variational properties of the smallest eigenvalue function over a set of Hermitian matrices. We establish the local convergence of the algorithm under mild assumptions and deduce a precise rate of convergence result by viewing the algorithm as a fixed point iteration. the convergence analysis reveals that the algorithm is immune to the nonsmooth nature of the smallest eigenvalue. We illustrate the practical applicability of the algorithm on the pseudospectral functions.Publication Metadata only Characterization of finite photonic crystals with defects(Institute of Electrical and Electronics Engineers (IEEE), 2011) N/A; Department of Electrical and Electronics Engineering; Karabulut, Emine Pınar; Aksun, M. İrşadi; Reseacher; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; N/A; 28358A simple computational approach is proposed to obtain the dispersion characteristics that could be observed outside of general finite-extent photonic crystals with defects. Since introducing and tailoring defects in photonic crystals are crucial for designing practical devices, the proposed method may play an important role in characterization and optimization of such defects. The method uses reflection data, due to an incident plane wave at a given frequency, collected at the front interface of a photonic crystal. It is simple and applicable for general photonic crystals, that is, photonic crystals with any periodicity, 1D, 2D, and 3D, and even with any kind of defects. The validity of the method was tested and verified on 1D and 2D finite photonic crystals, for which the reflection coefficient data at the front interface can be easily obtained by analytical means and numerical simulations, respectively. In addition, different types of defects, like random and periodic defects, were studied and it has been shown that the method is capable of providing information pertinent to the outside world on the defect modes.Publication Metadata only Object placement for high bandwidth memory augmented with high capacity memory(IEEE, 2017) N/A; N/A; Department of Computer Engineering; Laghari, Mohammad; Erten, Didem Unat; Master Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 219274High bandwidth memory (HBM) is a new emerging technology that aims to improve the performance of bandwidth limited applications. Even though it provides high bandwidth, it must be augmented with DRAM to meet the memory capacity requirement of any applications. Due to this limitation, objects in an application should be optimally placed on the heterogeneous memory subsystems. In this study, we propose an object placement algorithm that places program objects to fast or slow memories in case the capacity of fast memory is insufficient to hold all the objects to increase the overall application performance. Our algorithm uses the reference counts and type of references (read or write) to make an initial placement of data. In addition, we perform various memory bandwidth benchmarks to be used in our placement algorithm on Intel Knights Landing (KNL) architecture. Not surprisingly high bandwidth memory sustains higher read bandwidth than write bandwidth, however, placing write-intensive data on HBM results in better overall performance because write-intensive data is punished by the DRAM speed more severely compared to read intensive data. Moreover, our benchmarks demonstrate that if a basic block makes references to both types of memories, it performs worse than if it makes references to only one type of memory in some cases. We test our proposed placement algorithm with 6 applications under various system configurations. By allocating objects according to our placement scheme, we are able to achieve a speedup of up to 2x.Publication Metadata only Effect of preservation period on the viscoelastic material properties of soft tissues with implications for liver transplantation(Asme, 2010) N/A; N/A; N/A; Department of Mechanical Engineering; Department of Mechanical Engineering; Öcal, Sina; Özcan, Mustafa Umut; Başdoğan, İpek; Başdoğan, Çağatay; Master Student; Master Student; Faculty Member; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; 179940; 125489The liver harvested from a donor must be preserved and transported to a suitable recipient immediately for a successful liver transplantation. In this process, the preservation period is the most critical, since it is the longest and most tissue damage occurs during this period due to the reduced blood supply to the harvested liver and the change in its temperature. We investigate the effect of preservation period on the dynamic material properties of bovine liver using a viscoelastic model derived from both impact and ramp and hold experiments. First, we measure the storage and loss moduli of bovine liver as a function of excitation frequency using an impact hammer. Second, its time-dependent relaxation modulus is measured separately through ramp and hold experiments performed by a compression device. Third, a Maxwell solid model that successfully imitates the frequency- and time-dependent dynamic responses of bovine liver is developed to estimate the optimum viscoelastic material coefficients by minimizing the error between the experimental data and the corresponding values generated by the model. Finally, the variation in the viscoelastic material coefficients of bovine liver are investigated as a function of preservation period for the liver samples tested 1 h, 2 h, 4 h, 8 h, 12 h, 24 h, 36 h, and 48 h after harvesting. The results of our experiments performed with three animals show that the liver tissue becomes stiffer and more viscous as it spends more time in the preservation cycle.Publication Metadata only Affect burst detection using multi-modal cues(IEEE, 2015) Department of Computer Engineering; Department of Computer Engineering; N/A; Department of Computer Engineering; N/A; Sezgin, Tevfik Metin; Yemez, Yücel; Türker, Bekir Berker; Erzin, Engin; Marzban, Shabbir; Faculty Member; Faculty Member; PhD Student; Faculty Member; Master Student; Department of Computer Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; Graduate School of Sciences and Engineering; 18632; 107907; N/A; 34503; N/ARecently, affect bursts have gained significant importance in the field of emotion recognition since they can serve as prior in recognising underlying affect bursts. In this paper we propose a data driven approach for detecting affect bursts using multimodal streams of input such as audio and facial landmark points. The proposed Gaussian Mixture Model based method learns each modality independently followed by combining the probabilistic outputs to form a decision. This gives us an edge over feature fusion based methods as it allows us to handle events when one of the modalities is too noisy or not available. We demonstrate robustness of the proposed approach on 'Interactive emotional dyadic motion capture database' (IEMOCAP) which contains realistic and natural dyadic conversations. This database is annotated by three annotators to segment and label affect bursts to be used for training and testing purposes. We also present performance comparison between SVM based methods and GMM based methods for the same configuration of experiments.Publication Metadata only Multi-vehicle synchronized arc routing problem to restore post-disaster network connectivity(Elsevier Science Bv, 2017) Department of Industrial Engineering; Department of Industrial Engineering; Akbari, Vahid; Salman, Fatma Sibel; Teaching Faculty; Faculty Member; Department of Industrial Engineering; College of Engineering; College of Engineering; N/A; 178838After a natural disaster roads can be damaged or blocked by debris, while bridges and viaducts may collapse. This commonly observed hazard causes some road sections to be closed and may even disconnect the road network. In the immediate disaster response phase work teams are dispatched to open a subset of roads to reconnect the network. Closed roads are traversable only after they are unblocked/cleared by one of the teams. The main objective of this research is to provide an efficient solution method to generate a synchronized work schedule for the road clearing teams. The solution should specify the synchronized routes of each clearing team so that: 1) connectivity of the network is regained, and 2) none of the closed roads are traversed unless their unblocking/clearing procedure is finished. In this study we develop an exact Mixed Integer Programming (MIP) formulation to solve this problem. Furthermore, we propose a matheuristic that is based on an MIP-relaxation and a local search algorithm. We prove that the optimality gap of the relaxation solution is bounded by K times the lower bound obtained from the relaxed model, where K is the number of teams. We show computationally that the matheuristic obtains optimal or near-optimal solutions. (C) 2016 Elsevier B.V. All rights reserved.Publication Metadata only On the anticyclotomic Iwasawa theory of CM forms at supersingular primes(European Mathematical Soc, 2015) Department of Mathematics; Büyükboduk, Kazım; Faculty Member; Department of Mathematics; College of Sciences; N/AIn this paper, we study the anticyclotomic Iwasawa theory of a CM form f of even weight w >= 2 at a supersingular prime, generalizing the results in weight 2, due to Agboola and Howard. In due course, we are naturally lead to a conjecture on universal norms that generalizes a theorem of Perrin-Riou and Berger and another that generalizes a conjecture of Rubin (the latter seems linked to the local divisibility of Heegner points). Assuming the truth of these conjectures, we establish a formula for the variation of the sizes of the Selmer groups attached to the central critical twist of f as one climbs up the anticyclotomic tower. We also prove a statement which may be regarded as a form of the anticyclotomic main conjecture (without p-adic L-functions) for the central critical twist of f.Publication Metadata only Optimal rate and input format control for content and context adaptive video streaming(IEEE, 2004) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; N/A; Tekalp, Ahmet Murat; Civanlar, Mehmet Reha; Özçelebi, Tanır; Faculty Member; Faculty Member; PhD Student; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 26207; 16372; N/AA novel dynamic programming based technique for optimal selection of input video format and compression rate for video streaming based on "relevancy" of the content and user context is presented. The technique uses context dependent content analysis to divide the input video into temporal segments. User selected relevance levels assigned to these segments are used in formulating a constrained optimization problem, which is solved using dynamic programming. The technique minimizes a weighted distortion measure and the initial waiting time for continuous playback under maximum acceptable distortion constraints. Spatial resolution and frame rate of input video and the DCT quantization parameters are used as optimization variables. The technique is applied to encoding of soccer videos using an H.264 [1] encoder. The improvements obtained over a standard H.264 implementation are demonstrated by experimental results.Publication Metadata only An extended family of bounded component analysis algorithms(IEEE Computer Society, 2015) Department of Electrical and Electronics Engineering; N/A; Erdoğan, Alper Tunga; İnan, Hüseyin Atahan; Faculty Member; Master Student; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 41624; N/ABounded Component Analysis (BCA) is a recent concept proposed as an alternative method for Blind Source Separation problem. BCA enables the separation of dependent as well as independent sources from their mixtures under the practical assumption on source boundedness. This article extends the optimization setting of a recent BCA approach which can be used to produce a variety of BCA algorithms. The article also provides examples of objective functions and the corresponding iterative algorithms. The numerical examples illustrate the advantages of proposed BCA examples regarding the correlated source separation capability over the state of the art ICA based approaches. 1 © 2014 IEEE.