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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 Metadata only An audio-driven dancing avatar(Springer, 2008) Balci, Koray; Kizoglu, Idil; Akarun, Lale; Canton-Ferrer, Cristian; Tilmanne, Joelle; Bozkurt, Elif; Erdem, A. Tanju; Department of Computer Engineering; N/A; N/A; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Yemez, Yücel; Ofli, Ferda; Demir, Yasemin; Erzin, Engin; Tekalp, Ahmet Murat; Faculty Member; PhD Student; Master Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 107907; N/A; N/A; 34503; 26207We present a framework for training and synthesis of an audio-driven dancing avatar. The avatar is trained for a given musical genre using the multicamera video recordings of a dance performance. The video is analyzed to capture the time-varying posture of the dancer's body whereas the musical audio signal is processed to extract the beat information. We consider two different marker-based schemes for the motion capture problem. The first scheme uses 3D joint positions to represent the body motion whereas the second uses joint angles. Body movements of the dancer are characterized by a set of recurring semantic motion patterns, i.e., dance figures. Each dance figure is modeled in a supervised manner with a set of HMM (Hidden Markov Model) structures and the associated beat frequency. In the synthesis phase, an audio signal of unknown musical type is first classified, within a time interval, into one of the genres that have been learnt in the analysis phase, based on mel frequency cepstral coefficients (MFCC). The motion parameters of the corresponding dance figures are then synthesized via the trained HMM structures in synchrony with the audio signal based on the estimated tempo information. Finally, the generated motion parameters, either the joint angles or the 3D joint positions of the body, are animated along with the musical audio using two different animation tools that we have developed. Experimental results demonstrate the effectiveness of the proposed framework.Publication Metadata only Anharmonicity, mode-coupling and entropy in a fluctuating native protein(Iop Publishing Ltd, 2010) N/A; Department of Physics; Department of Computer Engineering; N/A; Department of Chemical and Biological Engineering; Kabakçıoğlu, Alkan; Yüret, Deniz; Gür, Mert; Erman, Burak; Faculty Member; Faculty Member; PhD Student; Faculty Member; Department of Physics; Department of Computer Engineering; Department of Chemical and Biological Engineering; College of Sciences; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 49854; 179996; 216930; 179997We develop a general framework for the analysis of residue fluctuations that simultaneously incorporates anharmonicity and mode-coupling in a unified formalism. We show that both deviations from the Gaussian model are important for modeling the multidimensional energy landscape of the protein Crambin (1EJG) in the vicinity of its native state. the effect of anharmonicity and mode-coupling on the fluctuational entropy is in the order of a few percent.Publication Metadata only Arl2-mediated allosteric release of farnesylated kras4b from shuttling factor pde delta(2018) Jang, Hyunbum; Nussinov, Ruth; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Özdemir, E. Sıla; Gürsoy, Attila; Keskin, Özlem; PhD Student; Faculty Member; 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); N/A; College of Engineering; College of Engineering; N/A; 8745; 40548Proper localization of Ras proteins at the plasma membrane (PM) is crucial for their functions. To get to the PM, KRas4B and some other Ras family proteins bind to the PDE delta shuttling protein through their farnesylated hypervariable regions (HVRs). The docking of their famesyl (and to a lesser extent geranylgeranyl) in the hydrophobic pocket of PDE delta's stabilizes the interaction. At the PM, guanosine 5'-triphosphate (GTP)-bound Arf-like protein 2 (Arl2) assists in the release of Ras from the PDE delta. However, exactly how is still unclear. Using all-atom molecular dynamics simulations, we unraveled the detailed mechanism of Arl2-mediated release of KRas4B, the most abundant oncogenic Ras isoform, from PDE delta. We simulated ternary Arl2 PDE delta KRas4B HVR complexes and observed that Arl2 binding weakens the PDE delta farnesylated HVR interaction. Our detailed analysis showed that allosteric changes (involving beta 6 of PDE delta and additional PDE delta residues) compress the hydrophobic PDE delta pocket and push the HVR out. Mutating PDE delta residues that mediate allosteric changes in PDE delta terminates the release process. Mutant Ras proteins are enriched in human cancers, with currently no drugs in the clinics. This mechanistic account may inspire efforts to develop drugs suppressing oncogenic KRas4B release.Publication Metadata only BindMe: a thread binding library with advanced mapping algorithms(Wiley, 2018) N/A; Department of Computer Engineering; Department of Computer Engineering; Soomro, Pirah Noor; Sasongko, Muhammad Aditya; Erten, Didem Unat; PhD Student; Researcher; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; 219274Binding parallel tasks to cores according to a placement policy is one of the key aspects to achieve good performance in multicore machines because it can reduce on-chip communication among parallel threads. Binding also prevents operating system from migrating threads, which improves data locality. However, there is no single mapping policy that works best among all different kinds of applications and platforms because each machine has a different topology and each application exhibits different communication pattern. Determining the best policy for a given application and machine requires extra programming effort. To relieve the programmer from that burden, we introduce BindMe, A thread binding library that assists programmer to bind threads to underlying hardware. BindMe incorporates state-of-the-art mapping algorithms, which use communication pattern in an application to formulate an efficient task placement policy. We also introduce ChoiceMap, A communication aware mapping algorithm that respects mutual priorities of parallel tasks and performs a fair mapping by reducing communication volume among cores. We have tested BindMe and ChoiceMap with various applications from NaS parallel benchmark and Rodinia bechmark. Our results show that choosing a mapping policy that best suits the application behavior can increase its performance and no single policy gives the best performance across different applications.Publication Metadata only Characterization and prediction of protein interfaces to infer protein-protein interaction networks(Bentham Science Publ Ltd, 2008) N/A; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Tunçbağ, Nurcan; Gürsoy, Attila; Faculty Member; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; College of Engineering; College of Engineering; College of Engineering; 26605; 245513; 8745Complex protein-protein interaction networks govern biological processes in cells. Protein interfaces are the sites where proteins physically interact. Identification and characterization of protein interfaces will lead to understanding how proteins interact with each other and how they are involved in protein-protein interaction networks. What makes a given interface bind to different proteins; how similar/different the interactions in proteins are some key questions to be answered. Enormous amount of protein structures and experimental protein-protein interactions data necessitate advanced computational methods for analyzing and inferring new knowledge. Interface prediction methods use a wide range of sequence, structural and physico-chemical characteristics that distinguish interface residues from non-interface surface residues. Here, we present a review focusing on the characteristics of interfaces and the current status of interface prediction methods.Publication Metadata only Classification of semantic relations between nominals(Springer, 2009) Girju, Roxana; Nakov, Preslav; Nastase, Vivi; Szpakowicz, Stan; Turney, Peter; Department of Computer Engineering; Yüret, Deniz; Faculty Member; Department of Computer Engineering; College of Engineering; 179996The NLP community has shown a renewed interest in deeper semantic analyses, among them automatic recognition of semantic relations in text. We present the development and evaluation of a semantic analysis task: automatic recognition of relations between pairs of nominals in a sentence. The task was part of SemEval-2007, the fourth edition of the semantic evaluation event previously known as SensEval. Apart from the observations we have made, the long-lasting effect of this task may be a framework for comparing approaches to the task. We introduce the problem of recognizing relations between nominals, and in particular the process of drafting and refining the definitions of the semantic relations. We show how we created the training and test data, list and briefly describe the 15 participating systems, discuss the results, and conclude with the lessons learned in the course of this exercise.Publication Metadata only Crowdsourcing for information retrieval: introduction to the special issue(2013) Lease, Matthew; Department of Computer Engineering; Yılmaz, Emine; Teaching Faculty; Department of Computer Engineering; College of Engineering; N/AThis introduction to the special issue summarizes and contextualizes six novel research contributions at the intersection of information retrieval (IR) and crowdsourcing (also overlapping crowdsourcing’s closely-related sibling, human computation). Several of the papers included in this special issue represent deeper investigations into research topics for which earlier stages of the authors’ research were disseminated at crowdsourcing workshops at SIGIR and WSDM conferences, as well as at the NIST TREC conference. Since the first proposed use of crowdsourcing for IR in 2008, interest in this area has quickly accelerated and led to three workshops, an ongoing NIST TREC track, and a great variety of published papers, talks, and tutorials. We briefly summarize the area in order to help situate the contributions appearing in this special issue. We also discuss some broader current trends and issues in crowdsourcing which bear upon its use in IR and other fields.Publication Open Access Cryptochrome deletion in p53 mutant mice enhances apoptotic and anti-tumorigenic responses to UV damage at the transcriptome level(Springer, 2019) Korkmaz, Tuba; Özturk, Nuri; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Department of Computer Engineering; N/A; Kavaklı, İbrahim Halil; Keskin, Özlem; Cavga, Ayşe Derya; Gürsoy, Attila; Tardu, Mehmet; Faculty Member; Faculty Member; PhD Student; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; 40319; 26605; N/A; 8745; N/APrevious studies have demonstrated that deletion of cryptochrome (Cry) genes protects p53(-/-) mutant mice from the early onset of cancer and extends their median life-span by about 1.5-fold. Subsequent in vitro studies had revealed that deletion of Crys enhances apoptosis in response to UV damage through activation of p73 and inactivation of GSK3 beta. However, it was not known at the transcriptome-wide level how deletion of Crys delays the onset of cancer in p53(-/-) mutant mice. In this study, the RNA-seq approach was taken to uncover the differentially expressed genes (DEGs) and pathways following UV-induced DNA damage in p53(-/-) and p53(-/-)Cry1(-/-)Cry2(-/-) mouse skin fibroblasts. Gene set enrichment analysis with the DEGs demonstrated enrichment in immune surveillance-associated genes regulated by IFN-gamma and genes involved in TNF alpha signaling via NF-kappa B. Furthermore, protein network analysis enabled identification of DEGs p21, Sirt1, and Jun as key players, along with their interacting partners. It was also observed that the DEGs contained a high ratio of non-coding transcripts. Collectively, the present study suggests new genes in NF-kappa B regulation and IFN-gamma response, as well as non-coding RNAs, may contribute to delaying the onset of cancer in p53(-/-)Cry1(-/-)Cry2(-/-) mice and increasing the life-span of these animals compared to p53(-/-) mice.Publication Open Access Cyberphysical blockchain-enabled peer-to-peer energy trading(Institute of Electrical and Electronics Engineers (IEEE), 2020) Aloqaily, Moayad; Alfandi, Omar; N/A; Department of Computer Engineering; Ali, Faizan Safdar; Özkasap, Öznur; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 113507Scalability and security problems with centralized architecture models in cyberphysical systems have provided opportunities for blockchain-based distributed models. A decentralized energy-trading system takes advantage of various sources and effectively coordinates the energy to ensure the optimal utilization of available resources. Three blockchainbased energy-trading models are proposed to overcome the technical challenges and market barriers as well as enhance the adoption of this disruptive technology.