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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3

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Now showing 1 - 10 of 442
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    Learning deep temporal representations for fMRI brain decoding
    (Springer International Publishing Ag, 2015) Firat, Orhan; Aksan, Emre; Fatos T. Yarman; Department of Psychology; Öztekin, İlke; Faculty Member; Department of Psychology; College of Social Sciences and Humanities; N/A
    Functional magnetic resonance imaging (fMRI) produces low number of samples in high dimensional vector spaces which is hardly adequate for brain decoding tasks. In this study, we propose a combination of autoencoding and temporal convolutional neural network architecture which aims to reduce the feature dimensionality along with improved classification performance. The proposed network learns temporal representations of voxel intensities at each layer of the network by leveraging unlabeled fMRI data with regularized autoencoders. Learned temporal representations capture the temporal regularities of the fMRI data and are observed to be an expressive bank of activation patterns. Then a temporal convolutional neural network with spatial pooling layers reduces the dimensionality of the learned representations. By employing the proposed method, raw input fMRI data is mapped to a low-dimensional feature space where the final classification is conducted. In addition, a simple decorrelated representation approach is proposed for tuning the model hyper-parameters. The proposed method is tested on a ten class recognition memory experiment with nine subjects. Results support the efficiency and potential of the proposed model, compared to the baseline multi-voxel pattern analysis techniques.
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    Exploring projection based mixed reality with tangibles for nonsymbolic preschool math education
    (Assoc Computing Machinery, 2019) N/A; N/A; Department of Psychology; Department of Media and Visual Arts; Department of Electrical and Electronics Engineering; Salman, Elif; Beşevli, Ceylan; Göksun, Tilbe; Özcan, Oğuzhan; Ürey, Hakan; Master Student; Researcher; Faculty Member; Faculty Member; Faculty Member; Department of Psychology; Department of Media and Visual Arts; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Social Sciences and Humanities; College of Social Sciences and Humanities; College of Social Sciences and Humanities; College of Engineering; N/A; N/A; 47278; 12532; 8579
    A child's early math development can stem from interactions with the physical world. Accordingly, current tangible interaction studies focus on preschool children's formal (symbolic) mathematics, i.e. number knowledge. However, recent developmental studies stress the importance of nonsymbolic number representation in math learning, i.e. understanding quantity relations without counting(more/less). To our knowledge, there are no tangible systems based on this math concept. We developed an initial tangible based mixed-reality(MR) setup with a small tabletop projector and depth camera. Our goal was observing children's interaction with the setup to guide our further design process towards developing nonsymbolic math trainings. In this paper we present our observations from sessions with four 3-to-5 year old children and discuss their meaning for future work. Initial clues show that our MR setup leads to exploratory and mindful interactions, which might be generalizable to other tangible MR systems for child education and could inspire interaction design studies.
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    A novel test coverage metric for concurrently-accessed software components (A work-in-progress paper)
    (Springer-Verlag Berlin, 2006) N/A; Department of Computer Engineering; N/A; Department of Computer Engineering; Department of Computer Engineering; Taşıran, Serdar; Elmas, Tayfun; Bölükbaşı, Güven; Keremoğlu, M. Erkan; Faculty Member; PhD Student; Undergraduate Student; Reseacher; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering, College of Engineering; N/A; N/A; N/A; N/A
    We propose a novel, practical coverage metric called "location pairs" (LP) for concurrently-accessed software components. The LP metric captures well common concurrency errors that lead to atomicity or refinement violations. We describe a software tool for measuring LP coverage and outline an inexpensive application of predicate abstraction and model checking for ruling out infeasible coverage targets.
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    Hotspotizer: end-user authoring of mid-air gestural interactions
    (Association for Computing Machinery, 2014) N/A; Department of Computer Engineering; Department of Media and Visual Arts; Baytaş, Mehmet Aydın; Yemez, Yücel; Özcan, Oğuzhan; PhD Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Media and Visual Arts; KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); Graduate School of Social Sciences and Humanities; College of Engineering; College of Social Sciences and Humanities; N/A; 107907; 12532
    Drawing from a user-centered design process and guidelines derived from the literature, we developed a paradigm based on space discretization for declaratively authoring mid-air gestures and implemented it in Hotspotizer, an end-to-end toolkit for mapping custom gestures to keyboard commands. Our implementation empowers diverse user populations - including end-users without domain expertise - to develop custom gestural interfaces within minutes, for use with arbitrary applications.
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    A mixed basis with off-center Gaussian functions for the calculation of the potential energy surfaces for pi-stacking interactions: dimers of benzene and planar C-6
    (Springer, 2015) Department of Chemistry; Yurtsever, İsmail Ersin; Faculty Member; Department of Chemistry; College of Sciences; 7129
    A practical mixed basis set was developed to facilitate accurate calculations of potential energy surfaces for pi-stacking interactions. Correlation consistent basis sets (cc-PVXZ) were augmented by p-type Gaussian functions placed above and below the planes of C-6 moieties. Moller-Plesset (MP2, SCS-MP2) and coupled cluster [CCSD(T)] calculations show that such generated basis sets provide an accurate description of p-stacking systems with favorable computation times compared to the standard augmented basis sets. The addition of these off-center functions eliminates the linear dependence of the augmented basis sets, which is one of the most encountered numerical problems during calculation of the oligomers of polyaromatic hydrocarbons (PAH). In this work, we present a comparative study of the general characteristics of the potential energy surfaces for the parallel stacked and T-shape conformations of benzene and planar C6 clusters, using a combination of cc-PVXZ and our optimized functions. We discuss properties, such as the depth and curvature of the potential functions, short and long distance behavior, and the frictional forces between two model monomers.
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    On the convergence of ICA algorithms with symmetric orthogonalization
    (IEEE, 2008) Department of Electrical and Electronics Engineering; Erdoğan, Alper Tunga; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 41624
    We study the convergence behavior of Independent Component Analysis (ICA) algorithms that are based on the contrast function maximization and that employ symmetric orthogonalization method to guarantee the orthogonality property of the search matrix. In particular, the characterization of the critical points of the corresponding optimization problem and the stationary points of the conventional gradient ascent and fixed point algorithms are obtained. As an interesting and a useful feature of the symmetrical orthogonalization method, we show that the use of symmetric orthogonalization enables the monotonic convergence for the fixed point ICA algorithms that are based on the convex contrast functions.
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    Multicamera audio-visual analysis of dance figures
    (IEEE, 2007) N/A; N/A; Department of Computer Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Ofli, Ferda; Erzin, Engin; Yemez, Yücel; Tekalp, Ahmet Murat; PhD Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; 34503; 107907; 26207
    We present an automated system for multicamera motion capture and audio-visual analysis of dance figures. the multiview video of a dancing actor is acquired using 8 synchronized cameras. the motion capture technique is based on 3D tracking of the markers attached to the person's body in the scene, using stereo color information without need for an explicit 3D model. the resulting set of 3D points is then used to extract the body motion features as 3D displacement vectors whereas MFC coefficients serve as the audio features. in the first stage of multimodal analysis, we perform Hidden Markov Model (HMM) based unsupervised temporal segmentation of the audio and body motion features, separately, to determine the recurrent elementary audio and body motion patterns. then in the second stage, we investigate the correlation of body motion patterns with audio patterns, that can be used for estimation and synthesis of realistic audio-driven body animation.
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    Audio-facial laughter detection in naturalistic dyadic conversations
    (Ieee-Inst Electrical Electronics Engineers Inc, 2017) N/A; N/A; Department of Computer Engineering; Department of Computer Engineering; Department of Computer Engineering; Türker, Bekir Berker; Yemez, Yücel; Sezgin, Tevfik Metin; Erzin, Engin; PhD Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 107907; 18632; 34503
    We address the problem of continuous laughter detection over audio-facial input streams obtained from naturalistic dyadic conversations. We first present meticulous annotation of laughters, cross-talks and environmental noise in an audio-facial database with explicit 3D facial mocap data. Using this annotated database, we rigorously investigate the utility of facial information, head movement and audio features for laughter detection. We identify a set of discriminative features using mutual information-based criteria, and show how they can be used with classifiers based on support vector machines (SVMs) and time delay neural networks (TDNNs). Informed by the analysis of the individual modalities, we propose a multimodal fusion setup for laughter detection using different classifier-feature combinations. We also effectively incorporate bagging into our classification pipeline to address the class imbalance problem caused by the scarcity of positive laughter instances. Our results indicate that a combination of TDNNs and SVMs lead to superior detection performance, and bagging effectively addresses data imbalance. Our experiments show that our multimodal approach supported by bagging compares favorably to the state of the art in presence of detrimental factors such as cross-talk, environmental noise, and data imbalance.
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    Parallel computing in Asian option pricing
    (Elsevier Science Bv, 2007) Sak, Halis; Boduroglu, Ilkay; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631
    We discuss the use of parallel computing in Asian option pricing and evaluate the efficiency of various algorithms. We only focus on "backward-starting fixed strike" Asian options that are continuously averaged. We implement a partial differential equation (PDE) approach that involves a single state variable to price the Asian option, and implement the same methodology to price a standard European option to check for accuracy. A parabolic PDE is solved by using both explicit and Crank-Nicolson's implicit finite-difference methods. In particular, we look for algorithms designed for implementing the computations in massively parallel processors (MPP). We evaluate the performance of the algorithms by comparing the numerical results with respect to accuracy and wall-clock time of code executions. Codes are executed on a Linux PC cluster.
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    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; 219274
    High 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.