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  • Neuroinformatics
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Zhilin, Zhang; Tzyy-Ping, Jung; Scott, Makeig; Bhaskar D, Rao;

    Telemonitoring of electroencephalogram (EEG) through wireless body-area networks is an evolving direction in personalized medicine. Among various constraints in designing such a system, three important constraints are energy consumption, data compression, and device cost. Conventional data compression methodologies, although effective in data compression, consumes significant energy and cannot reduce device cost. Compressed sensing (CS), as an emerging data compression methodology, is promising in catering to these constraints. However, EEG is non-sparse in the time domain and also non-sparse in transformed domains (such as the wavelet domain). Therefore, it is extremely difficult for current CS algorithms to recover EEG with the quality that satisfies the requirements of clinical diagnosis and engineering applications. Recently, Block Sparse Bayesian Learning (BSBL) was proposed as a new method to the CS problem. This study introduces the technique to the telemonitoring of EEG. Experimental results show that its recovery quality is better than state-of-the-art CS algorithms, and sufficient for practical use. These results suggest that BSBL is very promising for telemonitoring of EEG and other non-sparse physiological signals. Comment: Matlab codes can be downloaded at: http://dsp.ucsd.edu/~zhilin/BSBL.html, or http://sites.google.com/site/researchbyzhang/bsbl

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ IEEE Transactions on...arrow_drop_down
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    IEEE Transactions on Biomedical Engineering
    Article . 2013 . Peer-reviewed
    License: IEEE Copyright
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    https://doi.org/10.48550/arxiv...
    Article . 2012
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      IEEE Transactions on Biomedical Engineering
      Article . 2013 . Peer-reviewed
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      Article . 2012
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ciesielski, Maciej; Askar, Serkan; Gomez-Prado, Daniel; Guillot, Jeremie; +1 Authors

    International audience; An original technique to transform functional representation of the design into a structural representation in form of a data flow graph (DFG) is described. A canonical, word-level data structure, Taylor Expansion Diagram (TED), is used as a vehicle to effect this transformation. The problem is formulated as that of applying a sequence of decomposition cuts to a TED that transforms it into a DFG optimized for a particular objective. A systematic approach to arrive at such a decomposition is described. Experimental results show that such constructed DFG provides a better starting point for architectural synthesis than those extracted directly from HDL specifications.

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    Authors: Sagduyu, Yalin Evren; Berry, Randall A.; Ephremides, Anthony;

    Game-Theoretic Models and Security; International audience; We analyze the effects of dynamic packet traffic on jamming attacks in wireless networks. For random access over collision channels, the jamming problem is formulated as a non-cooperative game in which nodes choose their transmission probabilities under energy and delay constraints. We relax the standard assumption of backlogged nodes and evaluate the Nash equilibrium strategies for random arrivals, which introduces the possibility that jamming attacks fail due to empty packet queues at the transmitters. The maximum feasible throughput is derived depending on whether jammers have the queue state knowledge, or not. We also model the effects of erroneous queue state inference due to random packet traffic and incorporate the channel sensing capability before jamming. The analysis extends from one transmitter-jammer pair transmitting over a single channel at a single access point to multiple transmitters and jammers, and then to an arbitrary number of subchannels at multiple channel access points. In the resulting jamming games, we show that jammers cannot effectively increase the average energy cost and cannot decrease the feasible throughput for transmitters, if they face uncertainty on transmitter queue states. Therefore, medium access is less vulnerable to jamming attacks under increasing traffic uncertainty. This motivates the use of traffic dynamics as a defense mechanism to mitigate denial of service attacks in wireless access.

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    Other literature type . 2010
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    Authors: Ozan Ozdenizci; Ye Wang; Toshiaki Koike-Akino; Deniz Erdogmus;

    Deep learning methods for person identification based on electroencephalographic (EEG) brain activity encounters the problem of exploiting the temporally correlated structures or recording session specific variability within EEG. Furthermore, recent methods have mostly trained and evaluated based on single session EEG data. We address this problem from an invariant representation learning perspective. We propose an adversarial inference approach to extend such deep learning models to learn session-invariant person-discriminative representations that can provide robustness in terms of longitudinal usability. Using adversarial learning within a deep convolutional network, we empirically assess and show improvements with our approach based on longitudinally collected EEG data for person identification from half-second EEG epochs. Comment: Accepted for publication by IEEE Signal Processing Letters

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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    Europe PubMed Central
    Other literature type . 2019
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    IEEE Signal Processing Letters
    Article . 2019 . Peer-reviewed
    License: IEEE Copyright
    https://doi.org/10.48550/arxiv...
    Article . 2019
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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      Europe PubMed Central
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      IEEE Signal Processing Letters
      Article . 2019 . Peer-reviewed
      License: IEEE Copyright
      https://doi.org/10.48550/arxiv...
      Article . 2019
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    Authors: Slavov, Vasil; Rao, Praveen; Barenkala, Dinesh; Paturi, Srivenu;

    Chip makers are envisioning hundreds of cores in future processors for throughput oriented computing. These processors, called manycore processors, require new architectural innovations for scaling to a large number of cores as compared with today's multicore processors. We report an early study on the performance of RDF query processing on a manycore processor. In our study, we use the Intel SCC, an experimental manycore processor from Intel Labs. This processor has new architectural features, namely, 48 Pentium cores, a high speed, on-chip mesh network to communicate between cores and access memory controllers, on-chip message passing buffers for high speed message passing, and software controlled fine-grained power management. We classify queries based on their I/O footprint and study the impact of two standard models, namely, task and data parallel programming models. Based on our experiments with synthetic and real RDF datasets on the SCC, we conclude that the task parallelism model provides an immediate way to boost the performance of RDF query processing.

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    Authors: Haleh Fotowat; Florian Engert;

    AbstractLarval zebrafish that are exposed repeatedly to dark looming stimuli will quickly habituate to these aversive signals and cease to respond with their stereotypical escape swims.A dark looming stimulus can be separated into two independent components: one that is characterized by an overall spatial expansion, where overall luminance is maintained at the same level, and a second, that represents an overall dimming within the whole visual field in the absence of any motion energy. Using specific stimulation patterns that isolate these independent components, we first extracted the behavioral algorithms that dictate how these separate information channels interact with each other and across the two eyes during the habituation process. Concurrent brain wide imaging experiments then permitted the construction of circuit models that suggest the existence of three separate neural pathways. The first is a looming channel which responds specifically to concentrically expanding edges and relays that information to the brain stem escape network to generate directed escapes.The second is a dimming specific channel that serves to support and amplify the looming pathway. While the looming channel operates in a purely monocular fashion where stimuli are relayed exclusively to the contralateral hemisphere, dimming responses are processed in both monocular and binocular pathways. Finally, we identify a third, separate and largely monocular, dimming channel that appears to specifically inhibit escape responses when activated. We propose that, unlike the first two channels, this third channel is under strong contextual modulation and that it is primarily responsible for the incremental silencing of successive dark looming evoked escapes.

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    eLife
    Article . 2022
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    eLife
    Article . 2023 . Peer-reviewed
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      eLife
      Article . 2022
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      eLife
      Article . 2023 . Peer-reviewed
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    Authors: Hemaspaandra, Edith; Schnoor, Henning;

    Modal logics are widely used in computer science. The complexity of modal satisfiability problems has been investigated since the 1970s, usually proving results on a case-by-case basis. We prove a very general classification for a wide class of relevant logics: Many important subclasses of modal logics can be obtained by restricting the allowed models with first-order Horn formulas. We show that the satisfiability problem for each of these logics is either NP-complete or PSPACE-hard, and exhibit a simple classification criterion. Further, we prove matching PSPACE upper bounds for many of the PSPACE-hard logics. Comment: Full version of STACS 2008 paper

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    https://doi.org/10.48550/arxiv...
    Article . 2008
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      https://doi.org/10.48550/arxiv...
      Article . 2008
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Durand-Lose, Jérôme; Hendricks, Jacob; Patitz, Matthew J.; Perkins, Ian; +1 Authors

    International audience; Self-assembly is a process which is ubiquitous in natural, especially biological systems. It occurs when groups of relatively simple components spontaneously combine to form more complex structures. While such systems have inspired a large amount of research into designing theoretical models of self-assembling systems, and even laboratory-based implementations of them, these artificial models and systems often tend to be lacking in one of the powerful features of natural systems (e.g. the assembly and folding of proteins), which is dynamic reconfigurability of structures. In this paper, we present a new mathematical model of self-assembly, based on the abstract Tile Assembly Model (aTAM), called the Flexible Tile Assembly Model (FTAM). In the FTAM, the individual components are 2-dimensional tiles as in the aTAM, but in the FTAM, bonds between the edges of tiles can be flexible, allowing bonds to flex and entire structures to reconfigure, thus allowing 2-dimensional components to form 3-dimensional structures. We analyze the powers and limitations of FTAM systems by (1) demonstrating how flexibility can be controlled to carefully build desired structures, and (2) showing how flexibility can be beneficially harnessed to form structures which can “efficiently” reconfigure into many different configurations and/or greatly varying configurations. We also show that with such power comes a heavy burden in terms of computational complexity of simulation and prediction by proving that for important properties of FTAM systems, determining their existence is intractable, even for properties which are easily computed for systems in less dynamic models.

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    Natural Computing
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    Natural Computing
    Article . 2019 . Peer-reviewed
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      Natural Computing
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      Natural Computing
      Article . 2019 . Peer-reviewed
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    Authors: Jad Dino Raad; Ratna Babu Chinnam; Suzan Arslanturk; Sidhartha Tan; +2 Authors

    AbstractAnalysis of 3D medical imaging data has been a large topic of focus in the area of Machine Learning/Artificial Intelligence, though little work has been done in algorithmic (particularly unsupervised) analysis of neonatal brain MRI’s. A myriad of conditions can manifest at an early age, including neonatal encephalopathy (NE), which can result in lifelong physical consequences. As such, there is a dire need for better biomarkers of NE and other conditions. The objective of the study is to improve identification of anomalies and prognostication of neonatal MRI brain scans. We introduce a framework designed to support the analysis and assessment of neonatal MRI brain scans, the results of which can be used as an aid to neuroradiologists. We explored the efficacy of the framework through iterations of several deep convolutional Autoencoder (AE) unsupervised modeling architectures designed to learn normalcy of the neonatal brain structure. We tested this framework on the developing human connectome project (dHCP) dataset with 97 patients that were previously categorized by severity. Our framework demonstrated the model’s ability to identify and distinguish subtle morphological signatures present in brain structures. Normal and abnormal neonatal brain scans can be distinguished with reasonable accuracy, correctly categorizing them in up to 83% of cases. Most critically, new brain anomalies originally missed during the radiological reading were identified and corroborated by a neuroradiologist. This framework and our modeling approach demonstrate an ability to improve prognostication of neonatal brain conditions and are able to localize new anomalies.

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    Scientific Reports
    Article . 2023 . Peer-reviewed
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      Scientific Reports
      Article . 2023 . Peer-reviewed
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    Authors: Grigoriev, D;

    International audience; The complexity lower bound (log N) is proved for randomized computation trees (over reals with branching signs f ; >g) for recognizing an arrangement or a polyhedron with N faces. A similar lower bound is proved for randomized computation trees over any zero-characteristic eld with branching signs f=; 6 =g for recognizing an arrangement. As consequences, this provides in particular, the randomized lower bound (n 2) for the KNAPSACK problem (which was proved in case of the randomized computation trees over reals in 11]) and also the randomized lower bound (n log n)

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    Hyper Article en Ligne; Hal-Diderot
    Other literature type . Conference object . 1998
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Zhilin, Zhang; Tzyy-Ping, Jung; Scott, Makeig; Bhaskar D, Rao;

    Telemonitoring of electroencephalogram (EEG) through wireless body-area networks is an evolving direction in personalized medicine. Among various constraints in designing such a system, three important constraints are energy consumption, data compression, and device cost. Conventional data compression methodologies, although effective in data compression, consumes significant energy and cannot reduce device cost. Compressed sensing (CS), as an emerging data compression methodology, is promising in catering to these constraints. However, EEG is non-sparse in the time domain and also non-sparse in transformed domains (such as the wavelet domain). Therefore, it is extremely difficult for current CS algorithms to recover EEG with the quality that satisfies the requirements of clinical diagnosis and engineering applications. Recently, Block Sparse Bayesian Learning (BSBL) was proposed as a new method to the CS problem. This study introduces the technique to the telemonitoring of EEG. Experimental results show that its recovery quality is better than state-of-the-art CS algorithms, and sufficient for practical use. These results suggest that BSBL is very promising for telemonitoring of EEG and other non-sparse physiological signals. Comment: Matlab codes can be downloaded at: http://dsp.ucsd.edu/~zhilin/BSBL.html, or http://sites.google.com/site/researchbyzhang/bsbl

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    IEEE Transactions on Biomedical Engineering
    Article . 2013 . Peer-reviewed
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    Article . 2012
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      IEEE Transactions on Biomedical Engineering
      Article . 2013 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ciesielski, Maciej; Askar, Serkan; Gomez-Prado, Daniel; Guillot, Jeremie; +1 Authors

    International audience; An original technique to transform functional representation of the design into a structural representation in form of a data flow graph (DFG) is described. A canonical, word-level data structure, Taylor Expansion Diagram (TED), is used as a vehicle to effect this transformation. The problem is formulated as that of applying a sequence of decomposition cuts to a TED that transforms it into a DFG optimized for a particular objective. A systematic approach to arrive at such a decomposition is described. Experimental results show that such constructed DFG provides a better starting point for architectural synthesis than those extracted directly from HDL specifications.

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    Authors: Sagduyu, Yalin Evren; Berry, Randall A.; Ephremides, Anthony;

    Game-Theoretic Models and Security; International audience; We analyze the effects of dynamic packet traffic on jamming attacks in wireless networks. For random access over collision channels, the jamming problem is formulated as a non-cooperative game in which nodes choose their transmission probabilities under energy and delay constraints. We relax the standard assumption of backlogged nodes and evaluate the Nash equilibrium strategies for random arrivals, which introduces the possibility that jamming attacks fail due to empty packet queues at the transmitters. The maximum feasible throughput is derived depending on whether jammers have the queue state knowledge, or not. We also model the effects of erroneous queue state inference due to random packet traffic and incorporate the channel sensing capability before jamming. The analysis extends from one transmitter-jammer pair transmitting over a single channel at a single access point to multiple transmitters and jammers, and then to an arbitrary number of subchannels at multiple channel access points. In the resulting jamming games, we show that jammers cannot effectively increase the average energy cost and cannot decrease the feasible throughput for transmitters, if they face uncertainty on transmitter queue states. Therefore, medium access is less vulnerable to jamming attacks under increasing traffic uncertainty. This motivates the use of traffic dynamics as a defense mechanism to mitigate denial of service attacks in wireless access.

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    Other literature type . 2010
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      Other literature type . 2010
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    Authors: Ozan Ozdenizci; Ye Wang; Toshiaki Koike-Akino; Deniz Erdogmus;

    Deep learning methods for person identification based on electroencephalographic (EEG) brain activity encounters the problem of exploiting the temporally correlated structures or recording session specific variability within EEG. Furthermore, recent methods have mostly trained and evaluated based on single session EEG data. We address this problem from an invariant representation learning perspective. We propose an adversarial inference approach to extend such deep learning models to learn session-invariant person-discriminative representations that can provide robustness in terms of longitudinal usability. Using adversarial learning within a deep convolutional network, we empirically assess and show improvements with our approach based on longitudinally collected EEG data for person identification from half-second EEG epochs. Comment: Accepted for publication by IEEE Signal Processing Letters

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    Europe PubMed Central
    Other literature type . 2019
    Data sources: PubMed Central
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    IEEE Signal Processing Letters
    Article . 2019 . Peer-reviewed
    License: IEEE Copyright