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IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI)

作者： Kyle E. Benson Qing Han Kyungbaek Kim Phu Nguyen Nalini Venkatasubramanian Donald Bren School of Information and Computer Science UC Irvine Department of Electronics and Computer Engineering Chonnam National University The Henry Samueli School of Engineering UC Irvine

This paper considers the reliable delivery of sensor data from Internet of Things (IoT) devices to distributed cloud service instances in the face of localized failures for event detection, community infrastructure management, and emergency response. We develop and explore the notion of GEOgraphically Correlated Resilient Overlay Networks (GeoCRON) to capture the localized nature of community IoT deployments and their impact/vulnerability in the context of small failures and massive disruptions such as that caused by a large seismic event. As a focus use case, we study the viability and utility of GeoCRON in two different community sensor networks. The first, a large participatory sensing-style network of small inexpensive seismic sensors, reports ground motion in homes and businesses to a cloud service for detecting and characterizing earthquakes. The second, a smaller infrastructure-based network of wireless devices embedded in the water distribution network, reports water pressure changes at pipe junctions that may be indicative of leaks that require human intervention. Using realistic topologies derived from experiences with real world community scale deployments, we study the impact of geo-correlated failures on the combined network infrastructure and evaluate a range of GeoCRON heuristics to improve commnunications resilience in this context. We validate the promise of the proposed GeoCRON-based approach using extensive simulations and an initial prototype system implementation.

关键词： Cloud computing Resilience Routing Reliability Wireless sensor networks Wireless communication

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System Design for a Synergistic, Low Power Mote/BLE Embedded Platform

System Design for a Synergistic, Low Power Mote/BLE Embedded...

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International Symposium on Information Processing in Sensor Networks (IPSN)

作者： Michael P. Andersen Gabe Fierro David E. Culler Electrical Engineering and Computer Science Berkeley UC University of California Berkeley Berkeley CA US

Modern IoT prototyping platforms fall short in terms of energy efficiency, connectivity and software programming practices. We present the design of a new hardware and software platform that addresses these shortcomings by bringing together Mobile, Wearable, Maker and Wireless Sensor Network technologies to enable rapid prototyping with a high degree of synergy and energy efficiency. This is achieved in part by leveraging the Memory Protection Unit on modern microcontrollers along with a novel syscall interface to provide kernel / user isolation and a clean concurrency model. Such a design allows a wide range of languages to be used for application development without significant adaptation. We demonstrate how careful choice of application language allows the naturally asynchronous nature of embedded programming to be expressed cleanly and powerfully. Finally we evaluate the platform in several integrated use cases, providing examples of the capabilities introduced by Synergy.

关键词： Wireless sensor networks Storms Hardware Microcontrollers Software Technological innovation IEEE 802.15 Standard

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Gradient descent only converges to minimizers 29

Gradient descent only converges to minimizers

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29th Conference on Learning Theory, COLT 2016

作者： Lee, Jason D. Simchowitz, Max Jordan, Michael I. Recht, Benjamin Data Sciences and Operations Department Marshall School of Business University of Southern California Los AngelesCA90089 United States Department of Electrical Engineering and Computer Science UC Berkeley BerkeleyCA94720 United States

We show that gradient descent converges to a local minimizer, almost surely with random initialization. This is proved by applying the Stable Manifold Theorem from dynamical systems theory. © 2016 J.D. Lee, M. Si... 详细信息

关键词： Dynamical systems

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Touch based active user authentication using Deep Belief Networks and Random Forests

Touch based active user authentication using Deep Belief Net...

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International Conference on Information Communication and Management (ICICM)

作者： Ye Seon Lee William Hetchily Joseph Shelton Dylan Gunn Kaushik Roy Albert Esterline Xiaohong Yuan Department of Electrical Engineering and Computer Science UC Berkeley Berkeley CA Department of Computer Science North Carolina A & T State University Greensboro NC

ISBN: (纸本)9781509034963

While mobile devices traditionally use authentication methods such as passwords that define a single point of entry, active authentication can provide greater security by continuously authenticating users while they use the device. By extracting features based on users' interaction with the touchscreen, we can distinguish between different users. In this research, we investigate the performances of Deep Belief Networks (DBN) and Random Forest (RF), a more traditional classification algorithm, to classify users using a dataset extracted from the touch patterns of 41 users. The dataset is separated into strokes, which are then grouped into sessions. The preliminary results show that DBNs are outperformed by the RF.

关键词： Feature extraction Authentication Mobile handsets Radio frequency Data mining Performance evaluation Error analysis

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WILD: A workload-based learning model to predict dynamic delay of functional units

WILD: A workload-based learning model to predict dynamic del...

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IEEE International Conference on computer Design: VLSI in computers and Processors, (ICCD)

作者： Xun Jiao Yu Jiang Abbas Rahimi Rajesh K. Gupta Department of Computer Science and Engineering UC San Diego La Jolla CA USA School of Software Tsinghua University Beijing China Department of Electrical Engineering and Computer Sciences UC Berkeley Berkeley CA USA

Dynamic critical path analysis in modern processors is needed to reduce margins typically determined by the static timing analysis. Dynamic path analysis, however, is cost-prohibitive. In this paper, we propose WILD, a supervised learning model to predict dynamic delay of functional units (FUs) based on the input workload during execution. We measure the dynamic delay using switching activity generated through gate-level simulation of a post place-and-route design in TSMC 45nm process. We then look for `features' in the input data that influence dynamic path sensitization. Using these features we apply a logistic regression (LR) method to construct a predictive model trained and tested using three datasets: random, Sobel filter and Gaussian filter. We classify dynamic delay into five distinct classes. For a given test input, WILD predicts the class of output dynamic delay. On average across several FUs, 98.0% of WILD predictions are consistent with gate-level simulation. Using WILD-directed dynamic frequency scaling can improve instruction-level performance by 13%-44% compared to the state-of-the-art instruction-level timing model.

关键词： Delays Integrated circuit modeling Computational modeling Predictive models Feature extraction Data models

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The impact of observing strategy on cosmological constraints with LSST

arXiv

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arXiv 2021年

作者： Lochner, Michelle Scolnic, Dan Almoubayyed, Husni Anguita, Timo Awan, Humna Gawiser, Eric Gontcho, Satya Gontcho A. Gris, Philippe Huber, Simon Jha, Saurabh W. Jones, R. Lynne Kim, Alex G. Mandelbaum, Rachel Marshall, Phil Petrushevska, Tanja Regnault, Nicolas Setzer, Christian N. Suyu, Sherry H. Yoachim, Peter Biswas, Rahul Blaineau, Tristan Hook, Isobel Moniez, Marc Neilsen, Eric Peiris, Hiranya Rothchild, Daniel Stubbs, Christopher Department of Physics and Astronomy University of the Western Cape Bellville Cape Town7535 South Africa The Park Park Road Pinelands Cape Town7405 South Africa Department of Physics Duke University 120 Science Drive DurhamNC27708 United States McWilliams Center for Cosmology Department of Physics Carnegie Mellon University PittsburghPA15213 United States Departamento de Ciencias Fisicas Universidad Andres Bello Fernandez Concha 700 Las Condes Santiago Chile Millennium Institute of Astrophysics Nuncio Monsenor Sotero Sanz 100 Of. 104 Providencia Santiago Chile Leinweber Center for Theoretical Physics Department of Physics University of Michigan Ann ArborMI48109 United States Department of Physics and Astronomy Rutgers The State University PiscatawayNJ08854 United States Department of Physics & Astronomy University of Rochester 500 Wilson Blvd. RochesterNY14627 United States Laboratoire de Physique de Clermont IN2P3 CNRS Université Clermont Auvergne Clermont-FerrandF-63000 France Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Str. 1 Garching85748 Germany Physik-Department Technische Universität München James-Franck-Straße 1 Garching85748 Germany Department of Astronomy University of Washington SeattleWA98195 United States DiRAC Institute University of Washington SeattleWA98195 United States Lawrence Berkeley National Laboratory 1 Cyclotron Rd. BerkeleyCA94720 United States Kavli Institute for Particle Astrophysics and Cosmology P.O. Box 20450 MS29 StanfordCA94309 United States Centre for Astrophysics and Cosmology University of Nova Gorica Vipavska 11c Ajdovšcina5270 Slovenia Laboratoire de Physique Nucleaire et de Hautes-Energies Barre 12-22 1er etage 4 place Jussieu Paris75005 France The Oskar Klein Centre for Cosmoparticle Physics Department of Physics Stockholm University AlbaNova StockholmSE-106 91 Sweden 11F of ASMAB No.1 Section 4 Roosevelt Road Taipei10617 Taiwan Université Paris-Saclay C

The generation-defining Vera C. Rubin Observatory will make state-of-the-art measurements of both the static and transient universe through its Legacy Survey for Space and Time (LSST). With such capabilities, it is immensely challenging to optimize the LSST observing strategy across the survey's wide range of science drivers. Many aspects of the LSST observing strategy relevant to the LSST Dark Energy science Collaboration, such as survey footprint definition, single visit exposure time and the cadence of repeat visits in different filters, are yet to be finalized. Here, we present metrics used to assess the impact of observing strategy on the cosmological probes considered most sensitive to survey design;these are large-scale structure, weak lensing, type Ia supernovae, kilonovae and strong lens systems (as well as photometric redshifts, which enable many of these probes). We evaluate these metrics for over 100 different simulated potential survey designs. Our results show that multiple observing strategy decisions can profoundly impact cosmological constraints with LSST;these include adjusting the survey footprint, ensuring repeat nightly visits are taken in different filters and enforcing regular cadence. We provide public code for our metrics, which makes them readily available for evaluating further modifications to the survey design. We conclude with a set of recommendations and highlight observing strategy factors that require further research. © 2021, CC BY.

关键词： Surveys

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Complexity classification of conjugated Clifford circuits

arXiv

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arXiv 2017年

作者： Bouland, Adam Fitzsimons, Joseph F. Koh, Dax Enshan Department of Electrical Engineering and Computer Sciences UC Berkeley BerkeleyCA United States Singapore University of Technology and Design 8 Somapah Road Singapore487372 Singapore Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 Singapore117543 Singapore Department of Mathematics Massachusetts Institute of Technology CambridgeMA02139 United States

Clifford circuits - i.e. circuits composed of only CNOT, Hadamard, and π/4 phase gates - play a central role in the study of quantum computation. However, their computational power is limited: a well-known result of Gottesman and Knill [Got99] states that Clifford circuits are efficiently classically simulable. We show that in contrast, "conjugated Clifford circuits" (CCCs) - where one additionally conjugates every qubit by the same one-qubit gate U - can perform hard sampling tasks. In particular, we fully classify the computational power of CCCs by showing that essentially any non-Clifford conjugating unitary U can give rise to sampling tasks which cannot be efficiently classically simulated to constant multiplicative error, unless the polynomial hierarchy collapses. Furthermore, by standard techniques, this hardness result can be extended to allow for the more realistic model of constant additive error, under a plausible complexity-theoretic conjecture. This work can be seen as progress towards classifying the computational power of all restricted quantum gate sets. Copyright © 2017, The Authors. All rights reserved.

关键词： Timing circuits

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Publisher Correction: The genome of the stable fly, Stomoxys calcitrans, reveals potential mechanisms underlying reproduction, host interactions, and novel targets for pest control

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BMC biology 2021年第1期19卷 150页

作者： Pia U Olafson Serap Aksoy Geoffrey M Attardo Greta Buckmeier Xiaoting Chen Craig J Coates Megan Davis Justin Dykema Scott J Emrich Markus Friedrich Christopher J Holmes Panagiotis Ioannidis Evan N Jansen Emily C Jennings Daniel Lawson Ellen O Martinson Gareth L Maslen Richard P Meisel Terence D Murphy Dana Nayduch David R Nelson Kennan J Oyen Tyler J Raszick José M C Ribeiro Hugh M Robertson Andrew J Rosendale Timothy B Sackton Perot Saelao Sonja L Swiger Sing-Hoi Sze Aaron M Tarone David B Taylor Wesley C Warren Robert M Waterhouse Matthew T Weirauch John H Werren Richard K Wilson Evgeny M Zdobnov Joshua B Benoit Livestock Arthropod Pests Research Unit USDA-ARS Kerrville TX USA. pia.olafson@usda.gov. Department of Epidemiology of Microbial Diseases Yale School of Public Health New Haven CT USA. Department of Entomology and Nematology University of California - Davis Davis CA USA. Livestock Arthropod Pests Research Unit USDA-ARS Kerrville TX USA. The Center for Autoimmune Genomics and Etiology Cincinnati Children's Hospital Medical Center Cincinnati OH USA. Department of Entomology Texas A & M University College Station TX USA. Department of Biological Sciences Wayne State University Detroit MI USA. Department of Electrical Engineering & Computer Science University of Tennessee Knoxville TN USA. Department of Biological Sciences University of Cincinnati Cincinnati OH USA. Department of Genetic Medicine and Development University of Geneva Medical School and Swiss Institute of Bioinformatics 1211 Geneva Switzerland. The European Molecular Biology Laboratory The European Bioinformatics Institute The Wellcome Genome Campus Hinxton CB10 1SD UK. Department of Entomology University of Georgia Athens GA USA. Department of Biology and Biochemistry University of Houston Houston TX USA. National Center for Biotechnology Information National Library of Medicine National Institutes of Health Bethesda MD USA. Arthropod-borne Animal Diseases Research Unit USDA-ARS Manhattan KS USA. Department of Microbiology Immunology and Biochemistry University of Tennessee Health Science Center Memphis TN USA. Section of Vector Biology Laboratory of Malaria and Vector Research National Institute of Allergy and Infectious Diseases Rockville MD USA. Department of Entomology University of Illinois at Urbana-Champaign Urbana IL USA. Department of Biology Mount St. Joseph University Cincinnati OH USA. Informatics Group Faculty of Arts and Sciences Harvard University Cambridge MA USA. Department of Entomology Texas A&M AgriLife Research and Extension Center Stephenville

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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Stochastic optimal control navigation with the avoidance of unsafe configurations

Stochastic optimal control navigation with the avoidance of ...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Alexey A. Munishkin Dejan Milutinović David W. Casbeer UC Santa Cruz CA Computer Engineering Department UC Santa Cruz CA Control Science Center of Excellence Air Force Research Laboratory Wright-Patterson AFB OH

ISBN: (纸本)9781467393355

Long-time planning horizons are required to safely navigate one vehicle in the presence of another, possibly non-cooperative vehicle. They give rise to computational issues preventing the real-time implementation of safe navigation algorithms. In this paper, we consider two nonholonomic vehicles, of which one (blue) has the goal to enter the “tail” of the other (red). Neither the goal nor the navigation strategy of the red vehicle is known by the blue vehicle. To anticipate this uncertainty, the blue vehicle uses infinite horizon stochastic optimal control. Using the stochastic optimal control and backward Kolmogorov equation, the blue is navigated to avoid unsafe configurations from which the red can enter the “tail” of the blue and gain advantage over it. Our results are illustrated by numerical simulations and the feasibility of the control for the real-time implementation is tested with small-scale robot experiments.

关键词： Vehicles Optimal control Stochastic processes Aircraft navigation Real-time systems Uncertainty

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