Publications with Fulltext
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access 3D face recognition by projection based methods(Society of Photo-optical Instrumentation Engineers (SPIE), 2006) Dutaǧaci, Helin; Sankur, Bülent; Department of Computer Engineering; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of EngineeringIn this paper, we investigate recognition performances of various projection-based features applied on registered 3D scans of faces. Some features are data driven, such as ICA-based features or NNMF-based features. Other features are obtained using DFT or DCT-based schemes. We apply the feature extraction techniques to three different representations of registered faces, namely, 3D point clouds, 2D depth images and 3D voxel. We consider both global and local features. Global features are extracted from the whole face data, whereas local features are computed over the blocks partitioned from 2D depth images. The block-based local features are fused both at feature level and at decision level. The resulting feature vectors are matched using Linear Discriminant Analysis. Experiments using different combinations of representation types and feature vectors are conducted on the 3D-RMA dataset.Publication Open Access 3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients(Public Library of Science, 2019) Dinçer, Cansu; Kaya, Tuğba; Tunçbağ, Nurcan; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Gürsoy, Attila; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; 26605; 8745Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant insights. Approximately 10% of the mutations are located in "patches" which are defined as the set of residues spatially in close proximity that are mutated across multiple patients. Grouping mutations as 3D patches reduces the heterogeneity across patients. There are multiple patches that are relatively small in oncogenes, whereas there are a small number of very large patches in tumor suppressors. Additionally, different patches in the same protein are often located at different domains that can mediate different functions. We stratified the patients into five groups based on their potentially affected pathways, revealed from the patient-specific subnetworks. These subnetworks were constructed by integrating mutation profiles of the patients with the interactome data. Network-guided clustering showed significant association between each group and patient survival (P-value = 0.0408). Also, each group carries a set of signature 3D mutation patches that affect predominant pathways. We integrated drug sensitivity data of GBM cell lines with the mutation patches and the patient groups to analyze the therapeutic outcome of these patches. We found that Pazopanib might be effective in Group 3 by targeting CSF1R. Additionally, inhibiting ATM that is a mediator of PTEN phosphorylation may be ineffective in Group 2. We believe that from mutations to networks and eventually to clinical and therapeutic data, this study provides a novel perspective in the network-guided precision medicine.Publication Open Access A deep learning approach for data driven vocal tract area function estimation(Institute of Electrical and Electronics Engineers (IEEE), 2018) Department of Computer Engineering; Department of Electrical and Electronics Engineering; Erzin, Engin; Asadiabadi, Sasan; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; College of Sciences; Graduate School of Sciences and Engineering; 34503; N/AIn this paper we present a data driven vocal tract area function (VTAF) estimation using Deep Neural Networks (DNN). We approach the VTAF estimation problem based on sequence to sequence learning neural networks, where regression over a sliding window is used to learn arbitrary non-linear one-to-many mapping from the input feature sequence to the target articulatory sequence. We propose two schemes for efficient estimation of the VTAF; (1) a direct estimation of the area function values and (2) an indirect estimation via predicting the vocal tract boundaries. We consider acoustic speech and phone sequence as two possible input modalities for the DNN estimators. Experimental evaluations are performed over a large data comprising acoustic and phonetic features with parallel articulatory information from the USC-TIMIT database. Our results show that the proposed direct and indirect schemes perform the VTAF estimation with mean absolute error (MAE) rates lower than 1.65 mm, where the direct estimation scheme is observed to perform better than the indirect scheme.Publication Open Access A diversity combination model incorporating an inward bias for interaural time-level difference cue integration in sound lateralization(Multidisciplinary Digital Publishing Institute (MDPI), 2020) N/A; Department of Computer Engineering; Mojtahedi, Sina; Erzin, Engin; Ungan, Pekcan; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; 34503; N/AA sound source with non-zero azimuth leads to interaural time level differences (ITD and ILD). Studies on hearing system imply that these cues are encoded in different parts of the brain, but combined to produce a single lateralization percept as evidenced by experiments indicating trading between them. According to the duplex theory of sound lateralization, ITD and ILD play a more significant role in low-frequency and high-frequency stimulations, respectively. In this study, ITD and ILD, which were extracted from a generic head-related transfer functions, were imposed on a complex sound consisting of two low- and seven high-frequency tones. Two-alternative forced-choice behavioral tests were employed to assess the accuracy in identifying a change in lateralization. Based on a diversity combination model and using the error rate data obtained from the tests, the weights of the ITD and ILD cues in their integration were determined by incorporating a bias observed for inward shifts. The weights of the two cues were found to change with the azimuth of the sound source. While the ILD appears to be the optimal cue for the azimuths near the midline, the ITD and ILD weights turn to be balanced for the azimuths far from the midline.Publication Open Access A gated fusion network for dynamic saliency prediction(Institute of Electrical and Electronics Engineers (IEEE), 2022) Kocak, Aysun; Erdem, Erkut; Department of Computer Engineering; Erdem, Aykut; Faculty Member; Department of Computer Engineering; College of Engineering; 20331Predicting saliency in videos is a challenging problem due to complex modeling of interactions between spatial and temporal information, especially when ever-changing, dynamic nature of videos is considered. Recently, researchers have proposed large-scale data sets and models that take advantage of deep learning as a way to understand what is important for video saliency. These approaches, however, learn to combine spatial and temporal features in a static manner and do not adapt themselves much to the changes in the video content. In this article, we introduce the gated fusion network for dynamic saliency (GFSalNet), the first deep saliency model capable of making predictions in a dynamic way via the gated fusion mechanism. Moreover, our model also exploits spatial and channelwise attention within a multiscale architecture that further allows for highly accurate predictions. We evaluate the proposed approach on a number of data sets, and our experimental analysis demonstrates that it outperforms or is highly competitive with the state of the art. Importantly, we show that it has a good generalization ability, and moreover, exploits temporal information more effectively via its adaptive fusion scheme.Publication Open Access A task set proposal for automatic protest information collection across multiple countries(Springer, 2019) Department of Sociology; Department of Computer Engineering; Hürriyetoğlu, Ali; Yörük, Erdem; Yoltar, Çağrı; Yüret, Deniz; Gürel, Burak; Duruşan, Fırat; Mutlu, Osman; Teaching Faculty; Faculty Member; Researcher; Faculty Member; Faculty Member; Researcher; Department of Sociology; Department of Computer Engineering; Graduate School of Social Sciences and Humanities; Graduate School of Sciences and Engineering; N/A; 28982; N/A; 179996; 219277; N/A; N/AWe propose a coherent set of tasks for protest information collection in the context of generalizable natural language processing. The tasks are news article classification, event sentence detection, and event extraction. Having tools for collecting event information from data produced in multiple countries enables comparative sociology and politics studies. We have annotated news articles in English from a source and a target country in order to be able to measure the performance of the tools developed using data from one country on data from a different country. Our preliminary experiments have shown that the performance of the tools developed using English texts from India drops to a level that are not usable when they are applied on English texts from China. We think our setting addresses the challenge of building generalizable NLP tools that perform well independent of the source of the text and will accelerate progress in line of developing generalizable NLP systems.Publication Open Access Adaptive reference levels in a level-crossing analog-to-digital converter(Hindawi, 2008) Guan, Karen M.; Singer, Andrew C.; Department of Computer Engineering; Kozat, Süleyman Serdar; Faculty Member; Department of Computer Engineering; College of EngineeringLevel-crossing analog-to-digital converters (LC ADCs) have been considered in the literature and have been shown to efficiently sample certain classes of signals. One important aspect of their implementation is the placement of reference levels in the converter. The levels need to be appropriately located within the input dynamic range, in order to obtain samples efficiently. In this paper, we study optimization of the performance of such an LC ADC by providing several sequential algorithms that adaptively update the ADC reference levels. The accompanying performance analysis and simulation results show that as the signal length grows, the performance of the sequential algorithms asymptotically approaches that of the best choice that could only have been chosen in hindsight within a family of possible schemes.Publication Open Access AffectON: incorporating affect into dialog generation(Institute of Electrical and Electronics Engineers (IEEE), 2020) Bucinca, Zana; Department of Computer Engineering; Yemez, Yücel; Erzin, Engin; Sezgin, Tevfik Metin; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; College of Engineering; 107907; 34503; 18632Due to its expressivity, natural language is paramount for explicit and implicit affective state communication among humans. The same linguistic inquiry (e.g. How are you ?) might induce responses with different affects depending on the affective state of the conversational partner(s) and the context of the conversation. Yet, most dialog systems do not consider affect as constitutive aspect of response generation. In this paper, we introduce AffectON, an approach for generating affective responses during inference. For generating language in a targeted affect, our approach leverages a probabilistic language model and an affective space. AffectON is language model agnostic, since it can work with probabilities generated by any language model (e.g., sequence-to-sequence models, neural language models, n-grams). Hence, it can be employed for both affective dialog and affective language generation. We experimented with affective dialog generation and evaluated the generated text objectively and subjectively. For the subjective part of the evaluation, we designed a custom user interface for rating and provided recommendations for the design of such interfaces. The results, both subjective and objective demonstrate that our approach is successful in pulling the generated language toward the targeted affect, with little sacrifice in syntactic coherence.Publication Open Access AI-KU: using co-occurrence modeling for semantic similarity(Association for Computational Linguistics (ACL), 2014) Department of Computer Engineering; Başkaya, Osman; Department of Computer Engineering; College of EngineeringIn this paper, we describe our unsupervised method submitted to the Cross-Level Semantic Similarity task in Semeval 2014 that computes semantic similarity between two different sized text fragments. Our method models each text fragment by using the co-occurrence statistics of either occurred words or their substitutes. The co-occurrence modeling step provides dense, low-dimensional embedding for each fragment which allows us to calculate semantic similarity using various similarity metrics. Although our current model avoids the syntactic information, we achieved promising results and outperformed all baselines.Publication Open Access Alpha-beta-conspiracy search(International Computer Games Association (ICGA), 2002) McAllester, David A.; Department of Computer Engineering; Yüret, Deniz; Faculty Member; Department of Computer Engineering; College of Engineering; 179996We introduce a variant of alpha-beta search in which each node is associated with two depths rather than one. The purpose of alpha-beta search is to find strategies for each player that together establish a value for the root position. A max strategy establishes a lower bound and the min strategy establishes an upper bound. It has long been observed that forced moves should be searched more deeply. Here we make the observation that in the max strategy we are only concerned with the forcedness of max moves and in the min strategy we are only concerned with the forcedness of min moves. This leads to two measures of depth - one for each strategy - and to a two-depth variant of alpha-beta called ABC search. The two-depth approach can be formally derived from conspiracy theory and the structure of the ABC procedure is justified by two theorems relating ABC search and conspiracy numbers.Publication Open Access An adversarial approach to protocol analysis and selection in local differential privacy(Institute of Electrical and Electronics Engineers (IEEE), 2022) Liu, L.; Chow, K.H.; Truex, S.; Wei, W.; Department of Computer Engineering; Gürsoy, Mehmet Emre; Faculty Member; Department of Computer Engineering; College of EngineeringLocal Differential Privacy (LDP) is a popular standard for privacy-preserving data collection. Numerous LDP protocols have been proposed in the literature which differ in how they provide higher utility in different settings. Yet, few have engaged in analyzing the privacy relationships of these protocols under varying settings, and consequently, it is non-trivial to select which LDP protocol is best to use in a newly emerging application. In this paper, we present an adversarial approach to protocol analysis and selection and make three original contributions. First, we introduce a Bayesian adversary to analyze the privacy relationships of LDP protocols under varying settings. We show that different protocols have substantially different responses to the attack effectiveness of the Bayesian adversary, measured in terms of Adversarial Success Rate (ASR). Second, we provide a formal and empirical analysis on a set of privacy and utility-critical factors, including encoding parameters, privacy budget, data domain, adversarial knowledge, and statistical distribution. We show that different settings of these factors have significant effects on the ASRs of LDP protocols, and no protocol provides consistently low ASR across all settings. Third, we design and develop LDPLens, a prototype implementation of our proposed framework. Given a data collection scenario with various factors and constraints, LDPLens enables optimized selection of a desirable LDP protocol for the given scenario. We evaluate the effectiveness of LDPLens using three case studies with real-world datasets. Results show that LDPLens recommends a different protocol in each case study, and the protocol recommended by LDPLens can yield up to 1.5-2 fold reduction in utility loss, ASR or privacy budget compared to a randomly selected protocol.Publication Open Access Androgen receptor-binding sites are highly mutated in prostate cancer(Nature Publishing Group (NPG), 2020) McNeill, Daniel R.; Wilson, David M., III; Lallous, Nada; Dalal, Kush; Department of Industrial Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Morova, Tunç; Lack, Nathan Alan; Gönen, Mehmet; Gürsoy, Attila; Keskin, Özlem; Faculty Member; Faculty Member; Department of Industrial Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; College of Engineering; N/A; N/A; 237468; 8745; 26605Androgen receptor (AR) signalling is essential in nearly all prostate cancers. Any alterations to AR-mediated transcription can have a profound effect on carcinogenesis and tumor growth. While mutations of the AR protein have been extensively studied, little is known about those somatic mutations that occur at the non-coding regions where AR binds DNA. Using clinical whole genome sequencing, we show that AR binding sites have a dramatically increased rate of mutations that is greater than any other transcription factor and specific to only prostate cancer. Demonstrating this may be common to lineage-specific transcription factors, estrogen receptor binding sites were also found to have elevated rate of mutations in breast cancer. We provide evidence that these mutations at AR binding sites, and likely other related transcription factors, are caused by faulty repair of abasic sites. Overall, this work demonstrates that non-coding AR binding sites are frequently mutated in prostate cancer and can impact enhancer activity.Publication Open Access Androgen receptor-mediated transcription in prostate cancer(Multidisciplinary Digital Publishing Institute (MDPI), 2022) Morova, Tunç; Department of Computer Engineering; Department of Chemical and Biological Engineering; Lack, Nathan Alan; Özturan, Doğancan; Faculty Member; PhD Student; Department of Computer Engineering; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; 120842; N/AAndrogen receptor (AR)-mediated transcription is critical in almost all stages of prostate cancer (PCa) growth and differentiation. This process involves a complex interplay of coregulatory proteins, chromatin remodeling complexes, and other transcription factors that work with AR at cis-regulatory enhancer regions to induce the spatiotemporal transcription of target genes. This enhancer-driven mechanism is remarkably dynamic and undergoes significant alterations during PCa progression. In this review, we discuss the AR mechanism of action in PCa with a focus on how cis-regulatory elements modulate gene expression. We explore emerging evidence of genetic variants that can impact AR regulatory regions and alter gene transcription in PCa. Finally, we highlight several outstanding questions and discuss potential mechanisms of this critical transcription factor.Publication Open Access Artificial bandwidth extension of spectral envelope along a Viterbi path(Elsevier, 2013) Department of Computer Engineering; Yağlı, Can; Turan, Mehmet Ali Tuğtekin; Erzin, Engin; Master Student; Faculty Member; Department of Computer Engineering; College of Engineering; N/A; N/A; 34503In this paper, we propose a hidden Markov model (HMM)-based wideband spectral envelope estimation method for the artificial bandwidth extension problem. The proposed HMM-based estimator decodes an optimal Viterbi path based on the temporal contour of the narrowband spectral envelope and then performs the minimum mean square error (MMSE) estimation of the wideband spectral envelope on this path. Experimental evaluations are performed to compare the proposed estimator to the state-of-the-art HMM and Gaussian mixture model based estimators using both objective and subjective evaluations. Objective evaluations are performed with the log-spectral distortion (LSD) and the wideband perceptual evaluation of speech quality (PESQ) metrics. Subjective evaluations are performed with the A/B pair comparison listening test. Both objective and subjective evaluations yield that the proposed wideband spectral envelope estimator consistently improves performances over the state-of-the-art estimators. (C) 2012 Elsevier B.V. All rights reserved.Publication Open Access Artificial intelligence approaches to human-microbiome protein-protein interactions(Elsevier, 2022) Lim, Hansaim; Tsai, Chung-Jung; Nussinov, Ruth; Department of Computer Engineering; Department of Chemical and Biological Engineering; Gürsoy, Attila; Keskin, Özlem; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; Graduate School of Sciences and Engineering; 8745; 26605; N/AHost-microbiome interactions play significant roles in human health and disease. Artificial intelligence approaches have been developed to better understand and predict the molecular interplay between the host and its microbiome. Here, we review recent advancements in computational methods to predict microbial effects on human cells with a special focus on protein–protein interactions. We categorize recent methods from traditional ones to more recent deep learning methods, followed by several challenges and potential solutions in structure-based approaches. This review serves as a brief guide to the current status and future directions in the field.Publication Open Access Audiovisual synchronization and fusion using canonical correlation analysis(Institute of Electrical and Electronics Engineers (IEEE), 2007) Department of Computer Engineering; Department of Electrical and Electronics Engineering; Sargın, Mehmet Emre; Yemez, Yücel; Erzin, Engin; Tekalp, Ahmet Murat; 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; N/A; N/A; 34503; 26207It is well-known that early integration (also called data fusion) is effective when the modalities are correlated, and late integration (also called decision or opinion fusion) is optimal when modalities are uncorrelated. In this paper, we propose a new multimodal fusion strategy for open-set speaker identification using a combination of early and late integration following canonical correlation analysis (CCA) of speech and lip texture features. We also propose a method for high precision synchronization of the speech and lip features using CCA prior to the proposed fusion. Experimental results show that i) the proposed fusion strategy yields the best equal error rates (EER), which are used to quantify the performance of the fusion strategy for open-set speaker identification, and ii) precise synchronization prior to fusion improves the EER; hence, the best EER is obtained when the proposed synchronization scheme is employed together with the proposed fusion strategy. We note that the proposed fusion strategy outperforms others because the features used in the late integration are truly uncorrelated, since they are output of the CCA analysis.Publication Open Access Augmented tabletop role-playing game with movement-based gameplay and arm-worn devices(Association for Computing Machinery (ACM), 2017) Department of Computer Engineering; Buruk, Oğuz Turan; Özcan, Oğuzhan; Özbeyli, İsmet Melih; Faculty Member; Department of Computer Engineering; KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); College of Engineering; N/A; 12532; N/AAugmenting table-top role-playing games (TTRPG) is a trending subject in game research. Different objects and interaction modalities such as surface displays, tangible devices or interactive rooms are used for the augmentation of TTRPG. Still, usage of wearable devices and movement-based gameplay in such games is a rather underexplored area although they have a potential for enhancing the player experience according to the previous studies. To delve into this area, we developed a new interactive environment comprised of arm-worn devices and an augmented die. These devices, together with a new role-playing game system, facilitate movement-based gameplay which encourage players to enact their characters with their bodies. In this paper, we explained the specifications of this gaming environment and our demonstration setting.Publication Open Access BlockSim-Net: a network-based blockchain simulator(TÜBİTAK, 2022) Ramachandran, Prashanthi; Agrawal, Nandini; Department of Computer Engineering; Biçer, Osman; Küpçü, Alptekin; Faculty Member; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; N/A; 168060Since its proposal by Eyal and Sirer (CACM '13), selfish mining attacks on proof-of-work blockchains have been studied extensively. The main body of this research aims at both studying the extent of its impact and defending against it. Yet, before any practical defense is deployed in a real world blockchain system, it needs to be tested for security and dependability. However, real blockchain systems are too complex to conduct any test on or benchmark the developed protocols. Instead, some simulation environments have been proposed recently, such as BlockSim (Maher et al., SIGMETRICS Perform. Eval. Rev. '19), which is a modular and easy-to-use blockchain simulator. However, BlockSim's structure is insufficient to capture the essence of a real blockchain network, as the simulation of an entire network happens over a single CPU. Such a lack of decentralization can cause network issues such as propagation delays being simulated in an unrealistic manner. In this work, we propose BlockSim-Net, a modular, efficient, high performance, distributed, network-based blockchain simulator that is parallelized to better reflect reality in a blockchain simulation environment.Publication Open Access Boxlib with tiling: an adaptive mesh refinement software framework(Society for Industrial and Applied Mathematics (SIAM), 2016) Zhang, W.; Almgren, A.; Day, M.; Nguyen, T.; Shalf, J.; Department of Computer Engineering; Erten, Didem Unat; Faculty Member; Department of Computer Engineering; College of Engineering; 219274In this paper we introduce a block-structured adaptive mesh refinement software framework that incorporates tiling, a well-known loop transformation. Because the multiscale, multiphysics codes built in boxlib are designed to solve complex systems at high resolution, performance on current and next generation architectures is essential. With the expectation of many more cores per node on next generation architectures, the ability to effectively utilize threads within a node is essential, and the current model for parallelization will not be sufficient. We describe a new version of boxlib in which the tiling constructs are embedded so that boxlib-based applications can easily realize expected performance gains without extra effort on the part of the application developer. We also discuss a path forward to enable future versions of boxlib to take advantage of NUMA-aware optimizations using the tida portable library.Publication Open Access Building a gold standard for perceptual sketch similarity(The Eurographics Association, 2016) Department of Computer Engineering; Sezgin, Tevfik Metin; Çakmak, Şerike; Faculty Member; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; 18632; N/ASimilarity is among the most basic concepts studied in psychology. Yet, there is no unique way of assessing similarity of two objects. In the sketch recognition domain, many tasks such as classification, detection or clustering require measuring the level of similarity between sketches. In this paper, we propose a carefully designed experiment setup to construct a gold standard for measuring the similarity of sketches. Our setup is based on table scaling, and allows efficient construction of a measure of similarity for large datasets containing hundreds of sketches in reasonable time scales. We report the results of an experiment involving a total of 9 unique assessors, and 8 groups of sketches, each containing 300 drawings. The results show high interrater agreement between the assessors, which makes the constructed gold standard trustworthy.