Lagrangian or Eulerian; real or Fourier? Not all approaches to large-scale structure are created equal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tassev, Svetlin, E-mail: tassev@astro.princeton.edu

We present a pedagogical systematic investigation of the accuracy of Eulerian and Lagrangian perturbation theories of large-scale structure. We show that significant differences exist between them especially when trying to model the Baryon Acoustic Oscillations (BAO). We find that the best available model of the BAO in real space is the Zel'dovich Approximation (ZA), giving an accuracy of ∼<3% at redshift of z = 0 in modelling the matter 2-pt function around the acoustic peak. All corrections to the ZA around the BAO scale are perfectly perturbative in real space. Any attempt to achieve better precision requires calibrating the theorymore » to simulations because of the need to renormalize those corrections. In contrast, theories which do not fully preserve the ZA as their solution, receive O(1) corrections around the acoustic peak in real space at z = 0, and are thus of suspicious convergence at low redshift around the BAO. As an example, we find that a similar accuracy of 3% for the acoustic peak is achieved by Eulerian Standard Perturbation Theory (SPT) at linear order only at z ≈ 4. Thus even when SPT is perturbative, one needs to include loop corrections for z∼<4 in real space. In Fourier space, all models perform similarly, and are controlled by the overdensity amplitude, thus recovering standard results. However, that comes at a price. Real space cleanly separates the BAO signal from non-linear dynamics. In contrast, Fourier space mixes signal from short mildly non-linear scales with the linear signal from the BAO to the level that non-linear contributions from short scales dominate. Therefore, one has little hope in constructing a systematic theory for the BAO in Fourier space.« less

The one scale that rules them all

NASA Astrophysics Data System (ADS)

Ouellette, Jennifer

2017-05-01

There are very real constraints on how large a complex organism can grow. This is the essence of all modern-day scaling laws, and the subject of Geoffrey West's provocative new book Scale: the Universal Laws of Life and Death in Organisms, Cities and Companies

Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model

PubMed Central

van Albada, Sacha J.; Rowley, Andrew G.; Senk, Johanna; Hopkins, Michael; Schmidt, Maximilian; Stokes, Alan B.; Lester, David R.; Diesmann, Markus; Furber, Steve B.

2018-01-01

The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale neural network simulations in real time and with low power consumption. Real-time performance is achieved with 1 ms integration time steps, and thus applies to neural networks for which faster time scales of the dynamics can be neglected. By slowing down the simulation, shorter integration time steps and hence faster time scales, which are often biologically relevant, can be incorporated. We here describe the first full-scale simulations of a cortical microcircuit with biological time scales on SpiNNaker. Since about half the synapses onto the neurons arise within the microcircuit, larger cortical circuits have only moderately more synapses per neuron. Therefore, the full-scale microcircuit paves the way for simulating cortical circuits of arbitrary size. With approximately 80, 000 neurons and 0.3 billion synapses, this model is the largest simulated on SpiNNaker to date. The scale-up is enabled by recent developments in the SpiNNaker software stack that allow simulations to be spread across multiple boards. Comparison with simulations using the NEST software on a high-performance cluster shows that both simulators can reach a similar accuracy, despite the fixed-point arithmetic of SpiNNaker, demonstrating the usability of SpiNNaker for computational neuroscience applications with biological time scales and large network size. The runtime and power consumption are also assessed for both simulators on the example of the cortical microcircuit model. To obtain an accuracy similar to that of NEST with 0.1 ms time steps, SpiNNaker requires a slowdown factor of around 20 compared to real time. The runtime for NEST saturates around 3 times real time using hybrid parallelization with MPI and multi-threading. However, achieving this runtime comes at the cost of increased power and energy consumption. The lowest total energy consumption for NEST is reached at around 144 parallel threads and 4.6 times slowdown. At this setting, NEST and SpiNNaker have a comparable energy consumption per synaptic event. Our results widen the application domain of SpiNNaker and help guide its development, showing that further optimizations such as synapse-centric network representation are necessary to enable real-time simulation of large biological neural networks. PMID:29875620

HRLSim: a high performance spiking neural network simulator for GPGPU clusters.

PubMed

Minkovich, Kirill; Thibeault, Corey M; O'Brien, Michael John; Nogin, Aleksey; Cho, Youngkwan; Srinivasa, Narayan

2014-02-01

Modeling of large-scale spiking neural models is an important tool in the quest to understand brain function and subsequently create real-world applications. This paper describes a spiking neural network simulator environment called HRL Spiking Simulator (HRLSim). This simulator is suitable for implementation on a cluster of general purpose graphical processing units (GPGPUs). Novel aspects of HRLSim are described and an analysis of its performance is provided for various configurations of the cluster. With the advent of inexpensive GPGPU cards and compute power, HRLSim offers an affordable and scalable tool for design, real-time simulation, and analysis of large-scale spiking neural networks.

A relativistic signature in large-scale structure

NASA Astrophysics Data System (ADS)

Bartolo, Nicola; Bertacca, Daniele; Bruni, Marco; Koyama, Kazuya; Maartens, Roy; Matarrese, Sabino; Sasaki, Misao; Verde, Licia; Wands, David

2016-09-01

In General Relativity, the constraint equation relating metric and density perturbations is inherently nonlinear, leading to an effective non-Gaussianity in the dark matter density field on large scales-even if the primordial metric perturbation is Gaussian. Intrinsic non-Gaussianity in the large-scale dark matter overdensity in GR is real and physical. However, the variance smoothed on a local physical scale is not correlated with the large-scale curvature perturbation, so that there is no relativistic signature in the galaxy bias when using the simplest model of bias. It is an open question whether the observable mass proxies such as luminosity or weak lensing correspond directly to the physical mass in the simple halo bias model. If not, there may be observables that encode this relativistic signature.

Introducing the MCHF/OVRP/SDMP: Multicapacitated/Heterogeneous Fleet/Open Vehicle Routing Problems with Split Deliveries and Multiproducts

PubMed Central

Yilmaz Eroglu, Duygu; Caglar Gencosman, Burcu; Cavdur, Fatih; Ozmutlu, H. Cenk

2014-01-01

In this paper, we analyze a real-world OVRP problem for a production company. Considering real-world constrains, we classify our problem as multicapacitated/heterogeneous fleet/open vehicle routing problem with split deliveries and multiproduct (MCHF/OVRP/SDMP) which is a novel classification of an OVRP. We have developed a mixed integer programming (MIP) model for the problem and generated test problems in different size (10–90 customers) considering real-world parameters. Although MIP is able to find optimal solutions of small size (10 customers) problems, when the number of customers increases, the problem gets harder to solve, and thus MIP could not find optimal solutions for problems that contain more than 10 customers. Moreover, MIP fails to find any feasible solution of large-scale problems (50–90 customers) within time limits (7200 seconds). Therefore, we have developed a genetic algorithm (GA) based solution approach for large-scale problems. The experimental results show that the GA based approach reaches successful solutions with 9.66% gap in 392.8 s on average instead of 7200 s for the problems that contain 10–50 customers. For large-scale problems (50–90 customers), GA reaches feasible solutions of problems within time limits. In conclusion, for the real-world applications, GA is preferable rather than MIP to reach feasible solutions in short time periods. PMID:25045735

Inquiry-Based Educational Design for Large-Scale High School Astronomy Projects Using Real Telescopes

ERIC Educational Resources Information Center

Fitzgerald, Michael; McKinnon, David H.; Danaia, Lena

2015-01-01

In this paper, we outline the theory behind the educational design used to implement a large-scale high school astronomy education project. This design was created in response to the realization of ineffective educational design in the initial early stages of the project. The new design follows an iterative improvement model where the materials…

A ZigBee wireless networking for remote sensing applications in hydrological monitoring system

NASA Astrophysics Data System (ADS)

Weng, Songgan; Zhai, Duo; Yang, Xing; Hu, Xiaodong

2017-01-01

Hydrological monitoring is recognized as one of the most important factors in hydrology. Particularly, investigation of the tempo-spatial variation patterns of water-level and their effect on hydrological research has attracted more and more attention in recent. Because of the limitations in both human costs and existing water-level monitoring devices, however, it is very hard for researchers to collect real-time water-level data from large-scale geographical areas. This paper designs and implements a real-time water-level data monitoring system (MCH) based on ZigBee networking, which explicitly serves as an effective and efficient scientific instrument for domain experts to facilitate the measurement of large-scale and real-time water-level data monitoring. We implement a proof-of-concept prototype of the MCH, which can monitor water-level automatically, real-timely and accurately with low cost and low power consumption. The preliminary laboratory results and analyses demonstrate the feasibility and the efficacy of the MCH.

Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS.

PubMed

Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu

2014-09-01

This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations. Copyright © 2014. Published by Elsevier Ltd.

Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

PubMed Central

Shang, Yizi; Shang, Ling; Gao, Chuanchang; Lu, Guiming; Ye, Yuntao; Jia, Dongdong

2014-01-01

This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications. PMID:24574931

Flexible sampling large-scale social networks by self-adjustable random walk

NASA Astrophysics Data System (ADS)

Xu, Xiao-Ke; Zhu, Jonathan J. H.

2016-12-01

Online social networks (OSNs) have become an increasingly attractive gold mine for academic and commercial researchers. However, research on OSNs faces a number of difficult challenges. One bottleneck lies in the massive quantity and often unavailability of OSN population data. Sampling perhaps becomes the only feasible solution to the problems. How to draw samples that can represent the underlying OSNs has remained a formidable task because of a number of conceptual and methodological reasons. Especially, most of the empirically-driven studies on network sampling are confined to simulated data or sub-graph data, which are fundamentally different from real and complete-graph OSNs. In the current study, we propose a flexible sampling method, called Self-Adjustable Random Walk (SARW), and test it against with the population data of a real large-scale OSN. We evaluate the strengths of the sampling method in comparison with four prevailing methods, including uniform, breadth-first search (BFS), random walk (RW), and revised RW (i.e., MHRW) sampling. We try to mix both induced-edge and external-edge information of sampled nodes together in the same sampling process. Our results show that the SARW sampling method has been able to generate unbiased samples of OSNs with maximal precision and minimal cost. The study is helpful for the practice of OSN research by providing a highly needed sampling tools, for the methodological development of large-scale network sampling by comparative evaluations of existing sampling methods, and for the theoretical understanding of human networks by highlighting discrepancies and contradictions between existing knowledge/assumptions of large-scale real OSN data.

New Fund Allows Colleges to Pool Resources for Large-Scale Real-Estate Investments.

ERIC Educational Resources Information Center

McMillen, Liz

1988-01-01

The Real Estate Investment Trust, a companion organization to the Common Trust, allows colleges to commit as little as $50,000 for investments in commercial properties at minimum risk, which could protect endowments while providing returns comparable to those of the stock market. (MSE)

Teaching Real Science with a Microcomputer.

ERIC Educational Resources Information Center

Naiman, Adeline

1983-01-01

Discusses various ways science can be taught using microcomputers, including simulations/games which allow large-scale or historic experiments to be replicated on a manageable scale in a brief time. Examples of several computer programs are also presented, including "Experiments in Human Physiology,""Health Awareness…

Comparison of Fault Detection Algorithms for Real-time Diagnosis in Large-Scale System. Appendix E

NASA Technical Reports Server (NTRS)

Kirubarajan, Thiagalingam; Malepati, Venkat; Deb, Somnath; Ying, Jie

2001-01-01

In this paper, we present a review of different real-time capable algorithms to detect and isolate component failures in large-scale systems in the presence of inaccurate test results. A sequence of imperfect test results (as a row vector of I's and O's) are available to the algorithms. In this case, the problem is to recover the uncorrupted test result vector and match it to one of the rows in the test dictionary, which in turn will isolate the faults. In order to recover the uncorrupted test result vector, one needs the accuracy of each test. That is, its detection and false alarm probabilities are required. In this problem, their true values are not known and, therefore, have to be estimated online. Other major aspects in this problem are the large-scale nature and the real-time capability requirement. Test dictionaries of sizes up to 1000 x 1000 are to be handled. That is, results from 1000 tests measuring the state of 1000 components are available. However, at any time, only 10-20% of the test results are available. Then, the objective becomes the real-time fault diagnosis using incomplete and inaccurate test results with online estimation of test accuracies. It should also be noted that the test accuracies can vary with time --- one needs a mechanism to update them after processing each test result vector. Using Qualtech's TEAMS-RT (system simulation and real-time diagnosis tool), we test the performances of 1) TEAMSAT's built-in diagnosis algorithm, 2) Hamming distance based diagnosis, 3) Maximum Likelihood based diagnosis, and 4) HidderMarkov Model based diagnosis.

Large-scale road safety programmes in low- and middle-income countries: an opportunity to generate evidence.

PubMed

Hyder, Adnan A; Allen, Katharine A; Peters, David H; Chandran, Aruna; Bishai, David

2013-01-01

The growing burden of road traffic injuries, which kill over 1.2 million people yearly, falls mostly on low- and middle-income countries (LMICs). Despite this, evidence generation on the effectiveness of road safety interventions in LMIC settings remains scarce. This paper explores a scientific approach for evaluating road safety programmes in LMICs and introduces such a road safety multi-country initiative, the Road Safety in 10 Countries Project (RS-10). By building on existing evaluation frameworks, we develop a scientific approach for evaluating large-scale road safety programmes in LMIC settings. This also draws on '13 lessons' of large-scale programme evaluation: defining the evaluation scope; selecting study sites; maintaining objectivity; developing an impact model; utilising multiple data sources; using multiple analytic techniques; maximising external validity; ensuring an appropriate time frame; the importance of flexibility and a stepwise approach; continuous monitoring; providing feedback to implementers, policy-makers; promoting the uptake of evaluation results; and understanding evaluation costs. The use of relatively new approaches for evaluation of real-world programmes allows for the production of relevant knowledge. The RS-10 project affords an important opportunity to scientifically test these approaches for a real-world, large-scale road safety evaluation and generate new knowledge for the field of road safety.

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

PubMed

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.

Contribution of Road Grade to the Energy Use of Modern Automobiles Across Large Datasets of Real-World Drive Cycles: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, E.; Burton, E.; Duran, A.

Understanding the real-world power demand of modern automobiles is of critical importance to engineers using modeling and simulation to inform the intelligent design of increasingly efficient powertrains. Increased use of global positioning system (GPS) devices has made large scale data collection of vehicle speed (and associated power demand) a reality. While the availability of real-world GPS data has improved the industry's understanding of in-use vehicle power demand, relatively little attention has been paid to the incremental power requirements imposed by road grade. This analysis quantifies the incremental efficiency impacts of real-world road grade by appending high fidelity elevation profiles tomore » GPS speed traces and performing a large simulation study. Employing a large real-world dataset from the National Renewable Energy Laboratory's Transportation Secure Data Center, vehicle powertrain simulations are performed with and without road grade under five vehicle models. Aggregate results of this study suggest that road grade could be responsible for 1% to 3% of fuel use in light-duty automobiles.« less

On Predictability of System Anomalies in Real World

DTIC Science & Technology

2011-08-01

distributed system SETI @home [44]. Different from the above work, this work focuses on quantifying the predictability of real-world system anomalies. V...J.-M. Vincent, and D. Anderson, “Mining for statistical models of availability in large-scale distributed systems: An empirical study of seti @home,” in Proc. of MASCOTS, sept. 2009.

Integral criteria for large-scale multiple fingerprint solutions

NASA Astrophysics Data System (ADS)

Ushmaev, Oleg S.; Novikov, Sergey O.

2004-08-01

We propose the definition and analysis of the optimal integral similarity score criterion for large scale multmodal civil ID systems. Firstly, the general properties of score distributions for genuine and impostor matches for different systems and input devices are investigated. The empirical statistics was taken from the real biometric tests. Then we carry out the analysis of simultaneous score distributions for a number of combined biometric tests and primary for ultiple fingerprint solutions. The explicit and approximate relations for optimal integral score, which provides the least value of the FRR while the FAR is predefined, have been obtained. The results of real multiple fingerprint test show good correspondence with the theoretical results in the wide range of the False Acceptance and the False Rejection Rates.

CONSORT to community: translation of an RCT to a large-scale community intervention and learnings from evaluation of the upscaled program.

PubMed

Moores, Carly Jane; Miller, Jacqueline; Perry, Rebecca Anne; Chan, Lily Lai Hang; Daniels, Lynne Allison; Vidgen, Helen Anna; Magarey, Anthea Margaret

2017-11-29

Translation encompasses the continuum from clinical efficacy to widespread adoption within the healthcare service and ultimately routine clinical practice. The Parenting, Eating and Activity for Child Health (PEACH™) program has previously demonstrated clinical effectiveness in the management of child obesity, and has been recently implemented as a large-scale community intervention in Queensland, Australia. This paper aims to describe the translation of the evaluation framework from a randomised controlled trial (RCT) to large-scale community intervention (PEACH™ QLD). Tensions between RCT paradigm and implementation research will be discussed along with lived evaluation challenges, responses to overcome these, and key learnings for future evaluation conducted at scale. The translation of evaluation from PEACH™ RCT to the large-scale community intervention PEACH™ QLD is described. While the CONSORT Statement was used to report findings from two previous RCTs, the REAIM framework was more suitable for the evaluation of upscaled delivery of the PEACH™ program. Evaluation of PEACH™ QLD was undertaken during the project delivery period from 2013 to 2016. Experiential learnings from conducting the evaluation of PEACH™ QLD to the described evaluation framework are presented for the purposes of informing the future evaluation of upscaled programs. Evaluation changes in response to real-time changes in the delivery of the PEACH™ QLD Project were necessary at stages during the project term. Key evaluation challenges encountered included the collection of complete evaluation data from a diverse and geographically dispersed workforce and the systematic collection of process evaluation data in real time to support program changes during the project. Evaluation of large-scale community interventions in the real world is challenging and divergent from RCTs which are rigourously evaluated within a more tightly-controlled clinical research setting. Constructs explored in an RCT are inadequate in describing the enablers and barriers of upscaled community program implementation. Methods for data collection, analysis and reporting also require consideration. We present a number of experiential reflections and suggestions for the successful evaluation of future upscaled community programs which are scarcely reported in the literature. PEACH™ QLD was retrospectively registered with the Australian New Zealand Clinical Trials Registry on 28 February 2017 (ACTRN12617000315314).

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

Measurement of Thunderstorm Cloud-Top Parameters Using High-Frequency Satellite Imagery

DTIC Science & Technology

1978-01-01

short wave was present well to the south of this system approximately 2000 ka west of Baja California. Two distinct flow patterns were present, one...view can be observed in near real time whereas radar observations, although excellent for local purposes, involve substantial errors when composited...on a large scale. The time delay in such large scale compositing is critical when attempting to monitor convective cloud systems for a potential

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob; Gonder, Jeff

New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigationmore » systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.« less

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob; Gonder, Jeffrey D

New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigationmore » systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.« less

Large-Scale Modeling of Wordform Learning and Representation

ERIC Educational Resources Information Center

Sibley, Daragh E.; Kello, Christopher T.; Plaut, David C.; Elman, Jeffrey L.

2008-01-01

The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed the "sequence encoder" is used to learn…

Interactive, graphical processing unitbased evaluation of evacuation scenarios at the state scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Aaby, Brandon G; Yoginath, Srikanth B

2011-01-01

In large-scale scenarios, transportation modeling and simulation is severely constrained by simulation time. For example, few real- time simulators scale to evacuation traffic scenarios at the level of an entire state, such as Louisiana (approximately 1 million links) or Florida (2.5 million links). New simulation approaches are needed to overcome severe computational demands of conventional (microscopic or mesoscopic) modeling techniques. Here, a new modeling and execution methodology is explored that holds the potential to provide a tradeoff among the level of behavioral detail, the scale of transportation network, and real-time execution capabilities. A novel, field-based modeling technique and its implementationmore » on graphical processing units are presented. Although additional research with input from domain experts is needed for refining and validating the models, the techniques reported here afford interactive experience at very large scales of multi-million road segments. Illustrative experiments on a few state-scale net- works are described based on an implementation of this approach in a software system called GARFIELD. Current modeling cap- abilities and implementation limitations are described, along with possible use cases and future research.« less

InfoSymbiotics/DDDAS - The power of Dynamic Data Driven Applications Systems for New Capabilities in Environmental -, Geo-, and Space- Sciences

NASA Astrophysics Data System (ADS)

Darema, F.

2016-12-01

InfoSymbiotics/DDDAS embodies the power of Dynamic Data Driven Applications Systems (DDDAS), a concept whereby an executing application model is dynamically integrated, in a feed-back loop, with the real-time data-acquisition and control components, as well as other data sources of the application system. Advanced capabilities can be created through such new computational approaches in modeling and simulations, and in instrumentation methods, and include: enhancing the accuracy of the application model; speeding-up the computation to allow faster and more comprehensive models of a system, and create decision support systems with the accuracy of full-scale simulations; in addition, the notion of controlling instrumentation processes by the executing application results in more efficient management of application-data and addresses challenges of how to architect and dynamically manage large sets of heterogeneous sensors and controllers, an advance over the static and ad-hoc ways of today - with DDDAS these sets of resources can be managed adaptively and in optimized ways. Large-Scale-Dynamic-Data encompasses the next wave of Big Data, and namely dynamic data arising from ubiquitous sensing and control in engineered, natural, and societal systems, through multitudes of heterogeneous sensors and controllers instrumenting these systems, and where opportunities and challenges at these "large-scales" relate not only to data size but the heterogeneity in data, data collection modalities, fidelities, and timescales, ranging from real-time data to archival data. In tandem with this important dimension of dynamic data, there is an extended view of Big Computing, which includes the collective computing by networked assemblies of multitudes of sensors and controllers, this range from the high-end to the real-time seamlessly integrated and unified, and comprising the Large-Scale-Big-Computing. InfoSymbiotics/DDDAS engenders transformative impact in many application domains, ranging from the nano-scale to the terra-scale and to the extra-terra-scale. The talk will address opportunities for new capabilities together with corresponding research challenges, with illustrative examples from several application areas including environmental sciences, geosciences, and space sciences.

A Necessary Course for the 1990s: The Student-Run Advertising Agency.

ERIC Educational Resources Information Center

Marra, James L.

Current advertising courses and educational practices reflect advertising education's allegiance to the real world, particularly the real world as defined by large advertising agencies. A student-run ad agency provides students with a total learning experience on a small advertising agency scale in line with what they are likely to experience in…

YaQ: an architecture for real-time navigation and rendering of varied crowds.

PubMed

Maïm, Jonathan; Yersin, Barbara; Thalmann, Daniel

2009-01-01

The YaQ software platform is a complete system dedicated to real-time crowd simulation and rendering. Fitting multiple application domains, such as video games and VR, YaQ aims to provide efficient algorithms to generate crowds comprising up to thousands of varied virtual humans navigating in large-scale, global environments.

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

DOE PAGES

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

2017-01-01

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Homogenization of Large-Scale Movement Models in Ecology

USGS Publications Warehouse

Garlick, M.J.; Powell, J.A.; Hooten, M.B.; McFarlane, L.R.

2011-01-01

A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10-100 m) habitat variability on large scale (10-100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models. ?? 2010 Society for Mathematical Biology.

The study of integration about measurable image and 4D production

NASA Astrophysics Data System (ADS)

Zhang, Chunsen; Hu, Pingbo; Niu, Weiyun

2008-12-01

In this paper, we create the geospatial data of three-dimensional (3D) modeling by the combination of digital photogrammetry and digital close-range photogrammetry. For large-scale geographical background, we make the establishment of DEM and DOM combination of three-dimensional landscape model based on the digital photogrammetry which uses aerial image data to make "4D" (DOM: Digital Orthophoto Map, DEM: Digital Elevation Model, DLG: Digital Line Graphic and DRG: Digital Raster Graphic) production. For the range of building and other artificial features which the users are interested in, we realize that the real features of the three-dimensional reconstruction adopting the method of the digital close-range photogrammetry can come true on the basis of following steps : non-metric cameras for data collection, the camera calibration, feature extraction, image matching, and other steps. At last, we combine three-dimensional background and local measurements real images of these large geographic data and realize the integration of measurable real image and the 4D production.The article discussed the way of the whole flow and technology, achieved the three-dimensional reconstruction and the integration of the large-scale threedimensional landscape and the metric building.

An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages.

PubMed

Tuarob, Suppawong; Tucker, Conrad S; Salathe, Marcel; Ram, Nilam

2014-06-01

The role of social media as a source of timely and massive information has become more apparent since the era of Web 2.0.Multiple studies illustrated the use of information in social media to discover biomedical and health-related knowledge.Most methods proposed in the literature employ traditional document classification techniques that represent a document as a bag of words.These techniques work well when documents are rich in text and conform to standard English; however, they are not optimal for social media data where sparsity and noise are norms.This paper aims to address the limitations posed by the traditional bag-of-word based methods and propose to use heterogeneous features in combination with ensemble machine learning techniques to discover health-related information, which could prove to be useful to multiple biomedical applications, especially those needing to discover health-related knowledge in large scale social media data.Furthermore, the proposed methodology could be generalized to discover different types of information in various kinds of textual data. Social media data is characterized by an abundance of short social-oriented messages that do not conform to standard languages, both grammatically and syntactically.The problem of discovering health-related knowledge in social media data streams is then transformed into a text classification problem, where a text is identified as positive if it is health-related and negative otherwise.We first identify the limitations of the traditional methods which train machines with N-gram word features, then propose to overcome such limitations by utilizing the collaboration of machine learning based classifiers, each of which is trained to learn a semantically different aspect of the data.The parameter analysis for tuning each classifier is also reported. Three data sets are used in this research.The first data set comprises of approximately 5000 hand-labeled tweets, and is used for cross validation of the classification models in the small scale experiment, and for training the classifiers in the real-world large scale experiment.The second data set is a random sample of real-world Twitter data in the US.The third data set is a random sample of real-world Facebook Timeline posts. Two sets of evaluations are conducted to investigate the proposed model's ability to discover health-related information in the social media domain: small scale and large scale evaluations.The small scale evaluation employs 10-fold cross validation on the labeled data, and aims to tune parameters of the proposed models, and to compare with the stage-of-the-art method.The large scale evaluation tests the trained classification models on the native, real-world data sets, and is needed to verify the ability of the proposed model to handle the massive heterogeneity in real-world social media. The small scale experiment reveals that the proposed method is able to mitigate the limitations in the well established techniques existing in the literature, resulting in performance improvement of 18.61% (F-measure).The large scale experiment further reveals that the baseline fails to perform well on larger data with higher degrees of heterogeneity, while the proposed method is able to yield reasonably good performance and outperform the baseline by 46.62% (F-Measure) on average. Copyright © 2014 Elsevier Inc. All rights reserved.

Scale-Up of Safe & Civil Schools' Model for School-Wide Positive Behavioral Interventions and Supports

ERIC Educational Resources Information Center

Smolkowski, Keith; Strycker, Lisa; Ward, Bryce

2016-01-01

This study evaluated the scale-up of a Safe & Civil Schools "Foundations: Establishing Positive Discipline Policies" positive behavioral interventions and supports initiative through 4 years of "real-world" implementation in a large urban school district. The study extends results from a previous randomized controlled trial…

Applications of the Theory of Distributed and Real Time Systems to the Development of Large-Scale Timing Based Systems.

DTIC Science & Technology

1996-04-01

time systems . The focus is on the study of ’building-blocks’ for the construction of reliable and efficient systems. Our works falls into three...Members of MIT’s Theory of Distributed Systems group have continued their work on modelling, designing, verifying and analyzing distributed and real

Large-Scale Aerosol Modeling and Analysis

DTIC Science & Technology

2008-09-30

novel method of simultaneous real- time measurements of ice-nucleating particle concentrations and size- resolved chemical composition of individual...is to develop a practical predictive capability for visibility and weather effects of aerosol particles for the entire globe for timely use in...prediction follows that used in numerical weather prediction, namely real- time assessment for initialization of first-principles models. The Naval

Kinota: An Open-Source NoSQL implementation of OGC SensorThings for large-scale high-resolution real-time environmental monitoring

NASA Astrophysics Data System (ADS)

Miles, B.; Chepudira, K.; LaBar, W.

2017-12-01

The Open Geospatial Consortium (OGC) SensorThings API (STA) specification, ratified in 2016, is a next-generation open standard for enabling real-time communication of sensor data. Building on over a decade of OGC Sensor Web Enablement (SWE) Standards, STA offers a rich data model that can represent a range of sensor and phenomena types (e.g. fixed sensors sensing fixed phenomena, fixed sensors sensing moving phenomena, mobile sensors sensing fixed phenomena, and mobile sensors sensing moving phenomena) and is data agnostic. Additionally, and in contrast to previous SWE standards, STA is developer-friendly, as is evident from its convenient JSON serialization, and expressive OData-based query language (with support for geospatial queries); with its Message Queue Telemetry Transport (MQTT), STA is also well-suited to efficient real-time data publishing and discovery. All these attributes make STA potentially useful for use in environmental monitoring sensor networks. Here we present Kinota(TM), an Open-Source NoSQL implementation of OGC SensorThings for large-scale high-resolution real-time environmental monitoring. Kinota, which roughly stands for Knowledge from Internet of Things Analyses, relies on Cassandra its underlying data store, which is a horizontally scalable, fault-tolerant open-source database that is often used to store time-series data for Big Data applications (though integration with other NoSQL or rational databases is possible). With this foundation, Kinota can scale to store data from an arbitrary number of sensors collecting data every 500 milliseconds. Additionally, Kinota architecture is very modular allowing for customization by adopters who can choose to replace parts of the existing implementation when desirable. The architecture is also highly portable providing the flexibility to choose between cloud providers like azure, amazon, google etc. The scalable, flexible and cloud friendly architecture of Kinota makes it ideal for use in next-generation large-scale and high-resolution real-time environmental monitoring networks used in domains such as hydrology, geomorphology, and geophysics, as well as management applications such as flood early warning, and regulatory enforcement.

On the reliable use of satellite-derived surface water products for global flood monitoring

NASA Astrophysics Data System (ADS)

Hirpa, F. A.; Revilla-Romero, B.; Thielen, J.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; de Groeve, T.

2015-12-01

Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response management. To this end, real-time flood forecasting and satellite-based detection systems have been developed at global scale. However, due to the limited availability of up-to-date ground observations, the reliability of these systems for real-time applications have not been assessed in large parts of the globe. In this study, we performed comparative evaluations of the commonly used satellite-based global flood detections and operational flood forecasting system using 10 major flood cases reported over three years (2012-2014). Specially, we assessed the flood detection capabilities of the near real-time global flood maps from the Global Flood Detection System (GFDS), and from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the operational forecasts from the Global Flood Awareness System (GloFAS) for the major flood events recorded in global flood databases. We present the evaluation results of the global flood detection and forecasting systems in terms of correctly indicating the reported flood events and highlight the exiting limitations of each system. Finally, we propose possible ways forward to improve the reliability of large scale flood monitoring tools.

A Hybrid, Large-Scale Wireless Sensor Network for Real-Time Acquisition and Tracking

DTIC Science & Technology

2007-06-01

multicolor, Quantum Well Infrared Photodetector ( QWIP ), step-stare, large-format Focal Plane Array (FPA) is proposed and evaluated through performance...Photodetector ( QWIP ), step-stare, large-format Focal Plane Array (FPA) is proposed and evaluated through performance analysis. The thesis proposes...7 1. Multi-color IR Sensors - Operational Advantages ...........................8 2. Quantum-Well IR Photodetector ( QWIP

Validating Bayesian truth serum in large-scale online human experiments.

PubMed

Frank, Morgan R; Cebrian, Manuel; Pickard, Galen; Rahwan, Iyad

2017-01-01

Bayesian truth serum (BTS) is an exciting new method for improving honesty and information quality in multiple-choice survey, but, despite the method's mathematical reliance on large sample sizes, existing literature about BTS only focuses on small experiments. Combined with the prevalence of online survey platforms, such as Amazon's Mechanical Turk, which facilitate surveys with hundreds or thousands of participants, BTS must be effective in large-scale experiments for BTS to become a readily accepted tool in real-world applications. We demonstrate that BTS quantifiably improves honesty in large-scale online surveys where the "honest" distribution of answers is known in expectation on aggregate. Furthermore, we explore a marketing application where "honest" answers cannot be known, but find that BTS treatment impacts the resulting distributions of answers.

Validating Bayesian truth serum in large-scale online human experiments

PubMed Central

Frank, Morgan R.; Cebrian, Manuel; Pickard, Galen; Rahwan, Iyad

2017-01-01

Bayesian truth serum (BTS) is an exciting new method for improving honesty and information quality in multiple-choice survey, but, despite the method’s mathematical reliance on large sample sizes, existing literature about BTS only focuses on small experiments. Combined with the prevalence of online survey platforms, such as Amazon’s Mechanical Turk, which facilitate surveys with hundreds or thousands of participants, BTS must be effective in large-scale experiments for BTS to become a readily accepted tool in real-world applications. We demonstrate that BTS quantifiably improves honesty in large-scale online surveys where the “honest” distribution of answers is known in expectation on aggregate. Furthermore, we explore a marketing application where “honest” answers cannot be known, but find that BTS treatment impacts the resulting distributions of answers. PMID:28494000

Wafer scale fabrication of carbon nanotube thin film transistors with high yield

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Boyuan; Liang, Xuelei, E-mail: liangxl@pku.edu.cn, E-mail: ssxie@iphy.ac.cn; Yan, Qiuping

Carbon nanotube thin film transistors (CNT-TFTs) are promising candidates for future high performance and low cost macro-electronics. However, most of the reported CNT-TFTs are fabricated in small quantities on a relatively small size substrate. The yield of large scale fabrication and the performance uniformity of devices on large size substrates should be improved before the CNT-TFTs reach real products. In this paper, 25 200 devices, with various geometries (channel width and channel length), were fabricated on 4-in. size ridged and flexible substrates. Almost 100% device yield were obtained on a rigid substrate with high out-put current (>8 μA/μm), high on/off current ratiomore » (>10{sup 5}), and high mobility (>30 cm{sup 2}/V·s). More importantly, uniform performance in 4-in. area was achieved, and the fabrication process can be scaled up. The results give us more confidence for the real application of the CNT-TFT technology in the near future.« less

Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach

PubMed Central

Bigdely-Shamlo, Nima; Makeig, Scott; Robbins, Kay A.

2016-01-01

Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain–computer interface models. However, the absence of standardized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the difficulty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a “containerized” approach and freely available tools we have developed to facilitate the process of annotating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-)analysis. The EEG Study Schema (ESS) comprises three data “Levels,” each with its own XML-document schema and file/folder convention, plus a standardized (PREP) pipeline to move raw (Data Level 1) data to a basic preprocessed state (Data Level 2) suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are increasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at www.eegstudy.org and a central catalog of over 850 GB of existing data in ESS format is available at studycatalog.org. These tools and resources are part of a larger effort to enable data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org). PMID:27014048

N-point statistics of large-scale structure in the Zel'dovich approximation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tassev, Svetlin, E-mail: tassev@astro.princeton.edu

2014-06-01

Motivated by the results presented in a companion paper, here we give a simple analytical expression for the matter n-point functions in the Zel'dovich approximation (ZA) both in real and in redshift space (including the angular case). We present numerical results for the 2-dimensional redshift-space correlation function, as well as for the equilateral configuration for the real-space 3-point function. We compare those to the tree-level results. Our analysis is easily extendable to include Lagrangian bias, as well as higher-order perturbative corrections to the ZA. The results should be especially useful for modelling probes of large-scale structure in the linear regime,more » such as the Baryon Acoustic Oscillations. We make the numerical code used in this paper freely available.« less

Study of Travelling Interplanetary Phenomena Report

NASA Astrophysics Data System (ADS)

Dryer, Murray

1987-09-01

Scientific progress on the topic of energy, mass, and momentum transport from the Sun into the heliosphere is contingent upon interdisciplinary and international cooperative efforts on the part of many workers. Summarized here is a report of some highlights of research carried out during the SMY/SMA by the STIP (Study of Travelling Interplanetary Phenomena) Project that included solar and interplanetary scientists around the world. These highlights are concerned with coronal mass ejections from solar flares or erupting prominences (sometimes together); their large-scale consequences in interplanetary space (such as shocks and magnetic 'bubbles'); and energetic particles and their relationship to these large-scale structures. It is concluded that future progress is contingent upon similar international programs assisted by real-time (or near-real-time) warnings of solar activity by cooperating agencies along the lines experienced during the SMY/SMA.

Molecular diagnosis of malaria by photo-induced electron transfer fluorogenic primers: PET-PCR.

PubMed

Lucchi, Naomi W; Narayanan, Jothikumar; Karell, Mara A; Xayavong, Maniphet; Kariuki, Simon; DaSilva, Alexandre J; Hill, Vincent; Udhayakumar, Venkatachalam

2013-01-01

There is a critical need for developing new malaria diagnostic tools that are sensitive, cost effective and capable of performing large scale diagnosis. The real-time PCR methods are particularly robust for large scale screening and they can be used in malaria control and elimination programs. We have designed novel self-quenching photo-induced electron transfer (PET) fluorogenic primers for the detection of P. falciparum and the Plasmodium genus by real-time PCR. A total of 119 samples consisting of different malaria species and mixed infections were used to test the utility of the novel PET-PCR primers in the diagnosis of clinical samples. The sensitivity and specificity were calculated using a nested PCR as the gold standard and the novel primer sets demonstrated 100% sensitivity and specificity. The limits of detection for P. falciparum was shown to be 3.2 parasites/µl using both Plasmodium genus and P. falciparum-specific primers and 5.8 parasites/µl for P. ovale, 3.5 parasites/µl for P. malariae and 5 parasites/µl for P. vivax using the genus specific primer set. Moreover, the reaction can be duplexed to detect both Plasmodium spp. and P. falciparum in a single reaction. The PET-PCR assay does not require internal probes or intercalating dyes which makes it convenient to use and less expensive than other real-time PCR diagnostic formats. Further validation of this technique in the field will help to assess its utility for large scale screening in malaria control and elimination programs.

Imprint of non-linear effects on HI intensity mapping on large scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Umeh, Obinna, E-mail: umeobinna@gmail.com

Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result and the renormalization prescription for biased tracers to study the impact of nonlinear effects on themore » power spectrum of HI brightness temperature both in real and redshift space. We show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortion terms modulate the power spectrum on large scales. The large scale modulation may be understood to be due to the effective bias parameter and effective shot noise.« less

Imprint of non-linear effects on HI intensity mapping on large scales

NASA Astrophysics Data System (ADS)

Umeh, Obinna

2017-06-01

Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result and the renormalization prescription for biased tracers to study the impact of nonlinear effects on the power spectrum of HI brightness temperature both in real and redshift space. We show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortion terms modulate the power spectrum on large scales. The large scale modulation may be understood to be due to the effective bias parameter and effective shot noise.

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

NASA Astrophysics Data System (ADS)

Zhao, Feng; Huang, Qingming; Wang, Hao; Gao, Wen

2010-12-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.

Sparse Measurement Systems: Applications, Analysis, Algorithms and Design

ERIC Educational Resources Information Center

Narayanaswamy, Balakrishnan

2011-01-01

This thesis deals with "large-scale" detection problems that arise in many real world applications such as sensor networks, mapping with mobile robots and group testing for biological screening and drug discovery. These are problems where the values of a large number of inputs need to be inferred from noisy observations and where the…

Abundance of common species, not species richness, drives delivery of a real-world ecosystem service.

PubMed

Winfree, Rachael; Fox, Jeremy W; Williams, Neal M; Reilly, James R; Cariveau, Daniel P

2015-07-01

Biodiversity-ecosystem functioning experiments have established that species richness and composition are both important determinants of ecosystem function in an experimental context. Determining whether this result holds for real-world ecosystem services has remained elusive, however, largely due to the lack of analytical methods appropriate for large-scale, associational data. Here, we use a novel analytical approach, the Price equation, to partition the contribution to ecosystem services made by species richness, composition and abundance in four large-scale data sets on crop pollination by native bees. We found that abundance fluctuations of dominant species drove ecosystem service delivery, whereas richness changes were relatively unimportant because they primarily involved rare species that contributed little to function. Thus, the mechanism behind our results was the skewed species-abundance distribution. Our finding that a few common species, not species richness, drive ecosystem service delivery could have broad generality given the ubiquity of skewed species-abundance distributions in nature. © 2015 John Wiley & Sons Ltd/CNRS.

An effective online data monitoring and saving strategy for large-scale climate simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

An effective online data monitoring and saving strategy for large-scale climate simulations

DOE PAGES

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin; ...

2018-01-22

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

Wireless in-situ Sensor Network for Agriculture and Water Monitoring on a River Basin Scale in Southern Finland: Evaluation from a Data User’s Perspective

PubMed Central

Kotamäki, Niina; Thessler, Sirpa; Koskiaho, Jari; Hannukkala, Asko O.; Huitu, Hanna; Huttula, Timo; Havento, Jukka; Järvenpää, Markku

2009-01-01

Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In the present paper we describe a river basin scale wireless sensor network for agriculture and water monitoring. The network, called SoilWeather, is unique and the first of this type in Finland. The performance of the network is assessed from the user and maintainer perspectives, concentrating on data quality, network maintenance and applications. The results showed that the SoilWeather network has been functioning in a relatively reliable way, but also that the maintenance and data quality assurance by automatic algorithms and calibration samples requires a lot of effort, especially in continuous water monitoring over large areas. We see great benefits on sensor networks enabling continuous, real-time monitoring, while data quality control and maintenance efforts highlight the need for tight collaboration between sensor and sensor network owners to decrease costs and increase the quality of the sensor data in large scale applications. PMID:22574050

Performance of Grey Wolf Optimizer on large scale problems

NASA Astrophysics Data System (ADS)

Gupta, Shubham; Deep, Kusum

2017-01-01

For solving nonlinear continuous problems of optimization numerous nature inspired optimization techniques are being proposed in literature which can be implemented to solve real life problems wherein the conventional techniques cannot be applied. Grey Wolf Optimizer is one of such technique which is gaining popularity since the last two years. The objective of this paper is to investigate the performance of Grey Wolf Optimization Algorithm on large scale optimization problems. The Algorithm is implemented on 5 common scalable problems appearing in literature namely Sphere, Rosenbrock, Rastrigin, Ackley and Griewank Functions. The dimensions of these problems are varied from 50 to 1000. The results indicate that Grey Wolf Optimizer is a powerful nature inspired Optimization Algorithm for large scale problems, except Rosenbrock which is a unimodal function.

Rapid Modeling of and Response to Large Earthquakes Using Real-Time GPS Networks (Invited)

NASA Astrophysics Data System (ADS)

Crowell, B. W.; Bock, Y.; Squibb, M. B.

2010-12-01

Real-time GPS networks have the advantage of capturing motions throughout the entire earthquake cycle (interseismic, seismic, coseismic, postseismic), and because of this, are ideal for real-time monitoring of fault slip in the region. Real-time GPS networks provide the perfect supplement to seismic networks, which operate with lower noise and higher sampling rates than GPS networks, but only measure accelerations or velocities, putting them at a supreme disadvantage for ascertaining the full extent of slip during a large earthquake in real-time. Here we report on two examples of rapid modeling of recent large earthquakes near large regional real-time GPS networks. The first utilizes Japan’s GEONET consisting of about 1200 stations during the 2003 Mw 8.3 Tokachi-Oki earthquake about 100 km offshore Hokkaido Island and the second investigates the 2010 Mw 7.2 El Mayor-Cucapah earthquake recorded by more than 100 stations in the California Real Time Network. The principal components of strain were computed throughout the networks and utilized as a trigger to initiate earthquake modeling. Total displacement waveforms were then computed in a simulated real-time fashion using a real-time network adjustment algorithm that fixes a station far away from the rupture to obtain a stable reference frame. Initial peak ground displacement measurements can then be used to obtain an initial size through scaling relationships. Finally, a full coseismic model of the event can be run minutes after the event, given predefined fault geometries, allowing emergency first responders and researchers to pinpoint the regions of highest damage. Furthermore, we are also investigating using total displacement waveforms for real-time moment tensor inversions to look at spatiotemporal variations in slip.

Real-time Bayesian anomaly detection in streaming environmental data

NASA Astrophysics Data System (ADS)

Hill, David J.; Minsker, Barbara S.; Amir, Eyal

2009-04-01

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of anomalous data caused by sensor or transmission errors or by infrequent system behaviors. This study develops and evaluates three automated anomaly detection methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation of data as they become available, scale to large quantities of data, and require no a priori information regarding process variables or types of anomalies that may be encountered. This study investigates these methods' abilities to identify anomalies in eight meteorological data streams from Corpus Christi, Texas. The results indicate that DBN-based detectors, using either robust Kalman filtering or Rao-Blackwellized particle filtering, outperform a DBN-based detector using Kalman filtering, with the former having false positive/negative rates of less than 2%. These methods were successful at identifying data anomalies caused by two real events: a sensor failure and a large storm.

Sampling from complex networks using distributed learning automata

NASA Astrophysics Data System (ADS)

Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza

2014-02-01

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

Bundle block adjustment of large-scale remote sensing data with Block-based Sparse Matrix Compression combined with Preconditioned Conjugate Gradient

NASA Astrophysics Data System (ADS)

Zheng, Maoteng; Zhang, Yongjun; Zhou, Shunping; Zhu, Junfeng; Xiong, Xiaodong

2016-07-01

In recent years, new platforms and sensors in photogrammetry, remote sensing and computer vision areas have become available, such as Unmanned Aircraft Vehicles (UAV), oblique camera systems, common digital cameras and even mobile phone cameras. Images collected by all these kinds of sensors could be used as remote sensing data sources. These sensors can obtain large-scale remote sensing data which consist of a great number of images. Bundle block adjustment of large-scale data with conventional algorithm is very time and space (memory) consuming due to the super large normal matrix arising from large-scale data. In this paper, an efficient Block-based Sparse Matrix Compression (BSMC) method combined with the Preconditioned Conjugate Gradient (PCG) algorithm is chosen to develop a stable and efficient bundle block adjustment system in order to deal with the large-scale remote sensing data. The main contribution of this work is the BSMC-based PCG algorithm which is more efficient in time and memory than the traditional algorithm without compromising the accuracy. Totally 8 datasets of real data are used to test our proposed method. Preliminary results have shown that the BSMC method can efficiently decrease the time and memory requirement of large-scale data.

Effect of real-time boundary wind conditions on the air flow and pollutant dispersion in an urban street canyon—Large eddy simulations

NASA Astrophysics Data System (ADS)

Zhang, Yun-Wei; Gu, Zhao-Lin; Cheng, Yan; Lee, Shun-Cheng

2011-07-01

Air flow and pollutant dispersion characteristics in an urban street canyon are studied under the real-time boundary conditions. A new scheme for realizing real-time boundary conditions in simulations is proposed, to keep the upper boundary wind conditions consistent with the measured time series of wind data. The air flow structure and its evolution under real-time boundary wind conditions are simulated by using this new scheme. The induced effect of time series of ambient wind conditions on the flow structures inside and above the street canyon is investigated. The flow shows an obvious intermittent feature in the street canyon and the flapping of the shear layer forms near the roof layer under real-time wind conditions, resulting in the expansion or compression of the air mass in the canyon. The simulations of pollutant dispersion show that the pollutants inside and above the street canyon are transported by different dispersion mechanisms, relying on the time series of air flow structures. Large scale air movements in the processes of the air mass expansion or compression in the canyon exhibit obvious effects on pollutant dispersion. The simulations of pollutant dispersion also show that the transport of pollutants from the canyon to the upper air flow is dominated by the shear layer turbulence near the roof level and the expansion or compression of the air mass in street canyon under real-time boundary wind conditions. Especially, the expansion of the air mass, which features the large scale air movement of the air mass, makes more contribution to the pollutant dispersion in this study. Comparisons of simulated results under different boundary wind conditions indicate that real-time boundary wind conditions produces better condition for pollutant dispersion than the artificially-designed steady boundary wind conditions.

Study on Thermal Decomposition Characteristics of Ammonium Nitrate Emulsion Explosive in Different Scales

NASA Astrophysics Data System (ADS)

Wu, Qiujie; Tan, Liu; Xu, Sen; Liu, Dabin; Min, Li

2018-04-01

Numerous accidents of emulsion explosive (EE) are attributed to uncontrolled thermal decomposition of ammonium nitrate emulsion (ANE, the intermediate of EE) and EE in large scale. In order to study the thermal decomposition characteristics of ANE and EE in different scales, a large-scale test of modified vented pipe test (MVPT), and two laboratory-scale tests of differential scanning calorimeter (DSC) and accelerating rate calorimeter (ARC) were applied in the present study. The scale effect and water effect both play an important role in the thermal stability of ANE and EE. The measured decomposition temperatures of ANE and EE in MVPT are 146°C and 144°C, respectively, much lower than those in DSC and ARC. As the size of the same sample in DSC, ARC, and MVPT successively increases, the onset temperatures decrease. In the same test, the measured onset temperature value of ANE is higher than that of EE. The water composition of the sample stabilizes the sample. The large-scale test of MVPT can provide information for the real-life operations. The large-scale operations have more risks, and continuous overheating should be avoided.

A Web service-based architecture for real-time hydrologic sensor networks

NASA Astrophysics Data System (ADS)

Wong, B. P.; Zhao, Y.; Kerkez, B.

2014-12-01

Recent advances in web services and cloud computing provide new means by which to process and respond to real-time data. This is particularly true of platforms built for the Internet of Things (IoT). These enterprise-scale platforms have been designed to exploit the IP-connectivity of sensors and actuators, providing a robust means by which to route real-time data feeds and respond to events of interest. While powerful and scalable, these platforms have yet to be adopted by the hydrologic community, where the value of real-time data impacts both scientists and decision makers. We discuss the use of one such IoT platform for the purpose of large-scale hydrologic measurements, showing how rapid deployment and ease-of-use allows scientists to focus on their experiment rather than software development. The platform is hardware agnostic, requiring only IP-connectivity of field devices to capture, store, process, and visualize data in real-time. We demonstrate the benefits of real-time data through a real-world use case by showing how our architecture enables the remote control of sensor nodes, thereby permitting the nodes to adaptively change sampling strategies to capture major hydrologic events of interest.

Fragmentation scaling of percolation clusters in two and three dimensions: Large-cell Monte Carlo RG approach

NASA Astrophysics Data System (ADS)

Cheon, M.; Chang, I.

1999-04-01

The scaling behavior for a binary fragmentation of critical percolation clusters is investigated by a large-cell Monte Carlo real-space renormalization group method in two and three dimensions. We obtain accurate values of critical exponents λ and phi describing the scaling of fragmentation rate and the distribution of fragments' masses produced by a binary fragmentation. Our results for λ and phi show that the fragmentation rate is proportional to the size of mother cluster, and the scaling relation σ = 1 + λ - phi conjectured by Edwards et al. to be valid for all dimensions is satisfied in two and three dimensions, where σ is the crossover exponent of the average cluster number in percolation theory, which excludes the other scaling relations.

Rapid group-, serotype-, and vaccine strain-specific identification of poliovirus isolates by real-time reverse transcription-PCR using degenerate primers and probes containing deoxyinosine residues.

PubMed

Kilpatrick, David R; Yang, Chen-Fu; Ching, Karen; Vincent, Annelet; Iber, Jane; Campagnoli, Ray; Mandelbaum, Mark; De, Lina; Yang, Su-Ju; Nix, Allan; Kew, Olen M

2009-06-01

We have adapted our previously described poliovirus diagnostic reverse transcription-PCR (RT-PCR) assays to a real-time RT-PCR (rRT-PCR) format. Our highly specific assays and rRT-PCR reagents are designed for use in the WHO Global Polio Laboratory Network for rapid and large-scale identification of poliovirus field isolates.

COMPUTATIONAL METHODOLOGIES for REAL-SPACE STRUCTURAL REFINEMENT of LARGE MACROMOLECULAR COMPLEXES

PubMed Central

Goh, Boon Chong; Hadden, Jodi A.; Bernardi, Rafael C.; Singharoy, Abhishek; McGreevy, Ryan; Rudack, Till; Cassidy, C. Keith; Schulten, Klaus

2017-01-01

The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed. PMID:27145875

Real-time evolution of a large-scale relativistic jet

NASA Astrophysics Data System (ADS)

Martí, Josep; Luque-Escamilla, Pedro L.; Romero, Gustavo E.; Sánchez-Sutil, Juan R.; Muñoz-Arjonilla, Álvaro J.

2015-06-01

Context. Astrophysical jets are ubiquitous in the Universe on all scales, but their large-scale dynamics and evolution in time are hard to observe since they usually develop at a very slow pace. Aims: We aim to obtain the first observational proof of the expected large-scale evolution and interaction with the environment in an astrophysical jet. Only jets from microquasars offer a chance to witness the real-time, full-jet evolution within a human lifetime, since they combine a "short", few parsec length with relativistic velocities. Methods: The methodology of this work is based on a systematic recalibraton of interferometric radio observations of microquasars available in public archives. In particular, radio observations of the microquasar GRS 1758-258 over less than two decades have provided the most striking results. Results: Significant morphological variations in the extended jet structure of GRS 1758-258 are reported here that were previously missed. Its northern radio lobe underwent a major morphological variation that rendered the hotspot undetectable in 2001 and reappeared again in the following years. The reported changes confirm the Galactic nature of the source. We tentatively interpret them in terms of the growth of instabilities in the jet flow. There is also evidence of surrounding cocoon. These results can provide a testbed for models accounting for the evolution of jets and their interaction with the environment.

Agent-based large-scale emergency evacuation using real-time open government data.

DOT National Transportation Integrated Search

2014-01-01

The open government initiatives have provided tremendous data resources for the : transportation system and emergency services in urban areas. This paper proposes : a traffic simulation framework using high temporal resolution demographic data : and ...

Friction Stir Welding of Large Scale Cryogenic Tanks for Aerospace Applications

NASA Technical Reports Server (NTRS)

Russell, Carolyn; Ding, R. Jeffrey

1998-01-01

The Marshall Space Flight Center (MSFC) has established a facility for the joining of large-scale aluminum cryogenic propellant tanks using the friction stir welding process. Longitudinal welds, approximately five meters in length, have been made by retrofitting an existing vertical fusion weld system, designed to fabricate tank barrel sections ranging from two to ten meters in diameter. The structural design requirements of the tooling, clamping and travel system will be described in this presentation along with process controls and real-time data acquisition developed for this application. The approach to retrofitting other large welding tools at MSFC with the friction stir welding process will also be discussed.

Visualization of nanocrystal breathing modes at extreme strains

NASA Astrophysics Data System (ADS)

Szilagyi, Erzsi; Wittenberg, Joshua S.; Miller, Timothy A.; Lutker, Katie; Quirin, Florian; Lemke, Henrik; Zhu, Diling; Chollet, Matthieu; Robinson, Joseph; Wen, Haidan; Sokolowski-Tinten, Klaus; Lindenberg, Aaron M.

2015-03-01

Nanoscale dimensions in materials lead to unique electronic and structural properties with applications ranging from site-specific drug delivery to anodes for lithium-ion batteries. These functional properties often involve large-amplitude strains and structural modifications, and thus require an understanding of the dynamics of these processes. Here we use femtosecond X-ray scattering techniques to visualize, in real time and with atomic-scale resolution, light-induced anisotropic strains in nanocrystal spheres and rods. Strains at the percent level are observed in CdS and CdSe samples, associated with a rapid expansion followed by contraction along the nanosphere or nanorod radial direction driven by a transient carrier-induced stress. These morphological changes occur simultaneously with the first steps in the melting transition on hundreds of femtosecond timescales. This work represents the first direct real-time probe of the dynamics of these large-amplitude strains and shape changes in few-nanometre-scale particles.

Listening to the Deep: live monitoring of ocean noise and cetacean acoustic signals.

PubMed

André, M; van der Schaar, M; Zaugg, S; Houégnigan, L; Sánchez, A M; Castell, J V

2011-01-01

The development and broad use of passive acoustic monitoring techniques have the potential to help assessing the large-scale influence of artificial noise on marine organisms and ecosystems. Deep-sea observatories have the potential to play a key role in understanding these recent acoustic changes. LIDO (Listening to the Deep Ocean Environment) is an international project that is allowing the real-time long-term monitoring of marine ambient noise as well as marine mammal sounds at cabled and standalone observatories. Here, we present the overall development of the project and the use of passive acoustic monitoring (PAM) techniques to provide the scientific community with real-time data at large spatial and temporal scales. Special attention is given to the extraction and identification of high frequency cetacean echolocation signals given the relevance of detecting target species, e.g. beaked whales, in mitigation processes, e.g. during military exercises. Copyright © 2011. Published by Elsevier Ltd.

Contributions to the understanding of large-scale coherent structures in developing free turbulent shear flows

NASA Technical Reports Server (NTRS)

Liu, J. T. C.

1986-01-01

Advances in the mechanics of boundary layer flow are reported. The physical problems of large scale coherent structures in real, developing free turbulent shear flows, from the nonlinear aspects of hydrodynamic stability are addressed. The presence of fine grained turbulence in the problem, and its absence, lacks a small parameter. The problem is presented on the basis of conservation principles, which are the dynamics of the problem directed towards extracting the most physical information, however, it is emphasized that it must also involve approximations.

HSTDEK: Developing a methodology for construction of large-scale, multi-use knowledge bases

NASA Technical Reports Server (NTRS)

Freeman, Michael S.

1987-01-01

The primary research objectives of the Hubble Space Telescope Design/Engineering Knowledgebase (HSTDEK) are to develop a methodology for constructing and maintaining large scale knowledge bases which can be used to support multiple applications. To insure the validity of its results, this research is being persued in the context of a real world system, the Hubble Space Telescope. The HSTDEK objectives are described in detail. The history and motivation of the project are briefly described. The technical challenges faced by the project are outlined.

A parallel orbital-updating based plane-wave basis method for electronic structure calculations

NASA Astrophysics Data System (ADS)

Pan, Yan; Dai, Xiaoying; de Gironcoli, Stefano; Gong, Xin-Gao; Rignanese, Gian-Marco; Zhou, Aihui

2017-11-01

Motivated by the recently proposed parallel orbital-updating approach in real space method [1], we propose a parallel orbital-updating based plane-wave basis method for electronic structure calculations, for solving the corresponding eigenvalue problems. In addition, we propose two new modified parallel orbital-updating methods. Compared to the traditional plane-wave methods, our methods allow for two-level parallelization, which is particularly interesting for large scale parallelization. Numerical experiments show that these new methods are more reliable and efficient for large scale calculations on modern supercomputers.

The TRMM Multi-Satellite Precipitation Analysis (TMPA)

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Nelkin, Eric J.

2008-01-01

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is intended to provide a "best" estimate of quasi-global precipitation from the wide variety of modern satellite-borne precipitation-related sensors. Estimates are provided at relatively fine scales (0.25degx0.25deg, 3-hourly) in both real and post-real time to accommodate a wide range of researchers. However, the errors inherent in the finest scale estimates are large. The most successful use of the TMPA data is when the analysis takes advantage of the fine-scale data to create time/space averages appropriate to the user s application. We review the conceptual basis for the TMPA, summarize the processing sequence, and focus on two new activities. First, a recent upgrade to the real-time version incorporates several additional satellite data sources and employs monthly climatological adjustments to approximate the bias characteristics of the research quality post-real-time product. Second, an upgrade of the research quality post-real-time TMPA from Version 6 to Version 7 (in beta test at press time) is designed to provide a variety of improvements that increase the list of input data sets and correct several issues. Future enhancements for the TMPA will include improved error estimation, extension to higher latitudes, and a shift to a Lagrangian time interpolation scheme.

The TRMM Multi-Satellite Precipitation Analysis (TMPA)

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Nelkin, Eric J.

2010-01-01

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is intended to provide a "best" estimate of quasi-global precipitation from the wide variety of modern satellite-borne precipitation-related sensors. Estimates are provided at relatively fine scales (0.25 deg x 0.25 deg. 3-h) in both real and post-real time to accommodate a wide range of researchers. However, the errors inherent in the finest scale estimates are large. The most successful use of the TMPA data is when the analysis takes advantage of the fine-scale data to create time/space averages appropriate to the user fs application. We review the conceptual basis for the TMPA, summarize the processing sequence, and focus on two new activities. First, a recent upgrade for the real-time version incorporates several additional satellite data sources and employs monthly climatological adjustments to approximate the bias characteristics of the research quality post-real-time product. Second, an upgrade for the research quality post-real-time TMPA from Versions 6 to 7 (in beta test at press time) is designed to provide a variety of improvements that increase the list of input data sets and correct several issues. Future enhancements for the TMPA will include improved error estimation, extension to higher latitudes, and a shift to a Lagrangian time interpolation scheme.

Molecular Diagnosis of Malaria by Photo-Induced Electron Transfer Fluorogenic Primers: PET-PCR

PubMed Central

Lucchi, Naomi W.; Narayanan, Jothikumar; Karell, Mara A.; Xayavong, Maniphet; Kariuki, Simon; DaSilva, Alexandre J.; Hill, Vincent; Udhayakumar, Venkatachalam

2013-01-01

There is a critical need for developing new malaria diagnostic tools that are sensitive, cost effective and capable of performing large scale diagnosis. The real-time PCR methods are particularly robust for large scale screening and they can be used in malaria control and elimination programs. We have designed novel self-quenching photo-induced electron transfer (PET) fluorogenic primers for the detection of P. falciparum and the Plasmodium genus by real-time PCR. A total of 119 samples consisting of different malaria species and mixed infections were used to test the utility of the novel PET-PCR primers in the diagnosis of clinical samples. The sensitivity and specificity were calculated using a nested PCR as the gold standard and the novel primer sets demonstrated 100% sensitivity and specificity. The limits of detection for P. falciparum was shown to be 3.2 parasites/µl using both Plasmodium genus and P. falciparum-specific primers and 5.8 parasites/µl for P. ovale, 3.5 parasites/µl for P. malariae and 5 parasites/µl for P. vivax using the genus specific primer set. Moreover, the reaction can be duplexed to detect both Plasmodium spp. and P. falciparum in a single reaction. The PET-PCR assay does not require internal probes or intercalating dyes which makes it convenient to use and less expensive than other real-time PCR diagnostic formats. Further validation of this technique in the field will help to assess its utility for large scale screening in malaria control and elimination programs. PMID:23437209

Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology.

PubMed

Cordonnier, Guillaume; Cani, Marie-Paule; Benes, Bedrich; Braun, Jean; Galin, Eric

2018-05-01

Most mountain ranges are formed by the compression and folding of colliding tectonic plates. Subduction of one plate causes large-scale asymmetry while their layered composition (or stratigraphy) explains the multi-scale folded strata observed on real terrains. We introduce a novel interactive modeling technique to generate visually plausible, large scale terrains that capture these phenomena. Our method draws on both geological knowledge for consistency and on sculpting systems for user interaction. The user is provided hands-on control on the shape and motion of tectonic plates, represented using a new geologically-inspired model for the Earth crust. The model captures their volume preserving and complex folding behaviors under collision, causing mountains to grow. It generates a volumetric uplift map representing the growth rate of subsurface layers. Erosion and uplift movement are jointly simulated to generate the terrain. The stratigraphy allows us to render folded strata on eroded cliffs. We validated the usability of our sculpting interface through a user study, and compare the visual consistency of the earth crust model with geological simulation results and real terrains.

Fuzzy adaptive strong tracking scaled unscented Kalman filter for initial alignment of large misalignment angles

NASA Astrophysics Data System (ADS)

Li, Jing; Song, Ningfang; Yang, Gongliu; Jiang, Rui

2016-07-01

In the initial alignment process of strapdown inertial navigation system (SINS), large misalignment angles always bring nonlinear problem, which can usually be processed using the scaled unscented Kalman filter (SUKF). In this paper, the problem of large misalignment angles in SINS alignment is further investigated, and the strong tracking scaled unscented Kalman filter (STSUKF) is proposed with fixed parameters to improve convergence speed, while these parameters are artificially constructed and uncertain in real application. To further improve the alignment stability and reduce the parameters selection, this paper proposes a fuzzy adaptive strategy combined with STSUKF (FUZZY-STSUKF). As a result, initial alignment scheme of large misalignment angles based on FUZZY-STSUKF is designed and verified by simulations and turntable experiment. The results show that the scheme improves the accuracy and convergence speed of SINS initial alignment compared with those based on SUKF and STSUKF.

SLIDE - a web-based tool for interactive visualization of large-scale -omics data.

PubMed

Ghosh, Soumita; Datta, Abhik; Tan, Kaisen; Choi, Hyungwon

2018-06-28

Data visualization is often regarded as a post hoc step for verifying statistically significant results in the analysis of high-throughput data sets. This common practice leaves a large amount of raw data behind, from which more information can be extracted. However, existing solutions do not provide capabilities to explore large-scale raw datasets using biologically sensible queries, nor do they allow user interaction based real-time customization of graphics. To address these drawbacks, we have designed an open-source, web-based tool called Systems-Level Interactive Data Exploration, or SLIDE to visualize large-scale -omics data interactively. SLIDE's interface makes it easier for scientists to explore quantitative expression data in multiple resolutions in a single screen. SLIDE is publicly available under BSD license both as an online version as well as a stand-alone version at https://github.com/soumitag/SLIDE. Supplementary Information are available at Bioinformatics online.

A novel rapid genotyping technique for Collie eye anomaly: SYBR Green-based real-time polymerase chain reaction method applicable to blood and saliva specimens on Flinders Technology Associates filter paper.

PubMed

Chang, Hye-Sook; Mizukami, Keijiro; Yabuki, Akira; Hossain, Mohammad A; Rahman, Mohammad M; Uddin, Mohammad M; Arai, Toshiro; Yamato, Osamu

2010-09-01

Collie eye anomaly (CEA) is a canine inherited ocular disease that shows a wide variety of manifestations and severity of clinical lesions. Recently, a CEA-associated mutation was reported, and a DNA test that uses conventional polymerase chain reaction (PCR) has now become available. The objective of the current study was to develop a novel rapid genotyping technique by using SYBR Green-based real-time PCR for future large-scale surveys as a key part in the strategy to eradicate CEA by selective breeding. First, a SYBR Green-based real-time PCR assay for genotyping of CEA was developed and evaluated by using purified DNA samples from normal, carrier, and affected Border Collies in which genotypes had previously been determined by conventional PCR. This real-time PCR assay demonstrated appropriate amplifications in all genotypes, and the results were consistent with those of conventional PCR. Second, the availability of Flinders Technology Associates filter paper (FTA card) as DNA templates for the real-time PCR assay was evaluated by using blood and saliva specimens to determine suitability for CEA screening. DNA-containing solution prepared from a disc of blood- or saliva-spotted FTA cards was available directly as templates for the real-time PCR assay when the volume of solution was 2.5% of the PCR mixture. In conclusion, SYBR Green-based real-time PCR combined with FTA cards is a rapid genotyping technique for CEA that can markedly shorten the overall time required for genotyping as well as simplify the sample preparation. Therefore, this newly developed technique suits large-scale screening in breeding populations of Collie-related breeds.

Streaming fragment assignment for real-time analysis of sequencing experiments

PubMed Central

Roberts, Adam; Pachter, Lior

2013-01-01

We present eXpress, a software package for highly efficient probabilistic assignment of ambiguously mapping sequenced fragments. eXpress uses a streaming algorithm with linear run time and constant memory use. It can determine abundances of sequenced molecules in real time, and can be applied to ChIP-seq, metagenomics and other large-scale sequencing data. We demonstrate its use on RNA-seq data, showing greater efficiency than other quantification methods. PMID:23160280

A novel combined SLAM based on RBPF-SLAM and EIF-SLAM for mobile system sensing in a large scale environment.

PubMed

He, Bo; Zhang, Shujing; Yan, Tianhong; Zhang, Tao; Liang, Yan; Zhang, Hongjin

2011-01-01

Mobile autonomous systems are very important for marine scientific investigation and military applications. Many algorithms have been studied to deal with the computational efficiency problem required for large scale simultaneous localization and mapping (SLAM) and its related accuracy and consistency. Among these methods, submap-based SLAM is a more effective one. By combining the strength of two popular mapping algorithms, the Rao-Blackwellised particle filter (RBPF) and extended information filter (EIF), this paper presents a combined SLAM-an efficient submap-based solution to the SLAM problem in a large scale environment. RBPF-SLAM is used to produce local maps, which are periodically fused into an EIF-SLAM algorithm. RBPF-SLAM can avoid linearization of the robot model during operating and provide a robust data association, while EIF-SLAM can improve the whole computational speed, and avoid the tendency of RBPF-SLAM to be over-confident. In order to further improve the computational speed in a real time environment, a binary-tree-based decision-making strategy is introduced. Simulation experiments show that the proposed combined SLAM algorithm significantly outperforms currently existing algorithms in terms of accuracy and consistency, as well as the computing efficiency. Finally, the combined SLAM algorithm is experimentally validated in a real environment by using the Victoria Park dataset.

Demonstration of nanoimprinted hyperlens array for high-throughput sub-diffraction imaging

NASA Astrophysics Data System (ADS)

Byun, Minsueop; Lee, Dasol; Kim, Minkyung; Kim, Yangdoo; Kim, Kwan; Ok, Jong G.; Rho, Junsuk; Lee, Heon

2017-04-01

Overcoming the resolution limit of conventional optics is regarded as the most important issue in optical imaging science and technology. Although hyperlenses, super-resolution imaging devices based on highly anisotropic dispersion relations that allow the access of high-wavevector components, have recently achieved far-field sub-diffraction imaging in real-time, the previously demonstrated devices have suffered from the extreme difficulties of both the fabrication process and the non-artificial objects placement. This results in restrictions on the practical applications of the hyperlens devices. While implementing large-scale hyperlens arrays in conventional microscopy is desirable to solve such issues, it has not been feasible to fabricate such large-scale hyperlens array with the previously used nanofabrication methods. Here, we suggest a scalable and reliable fabrication process of a large-scale hyperlens device based on direct pattern transfer techniques. We fabricate a 5 cm × 5 cm size hyperlenses array and experimentally demonstrate that it can resolve sub-diffraction features down to 160 nm under 410 nm wavelength visible light. The array-based hyperlens device will provide a simple solution for much more practical far-field and real-time super-resolution imaging which can be widely used in optics, biology, medical science, nanotechnology and other closely related interdisciplinary fields.

Is There Any Real Observational Contradictoty To The Lcdm Model?

NASA Astrophysics Data System (ADS)

Ma, Yin-Zhe

2011-01-01

In this talk, I am going to question the two apparent observational contradictories to LCDM cosmology---- the lack of large angle correlations in the cosmic microwave background, and the very large bulk flow of galaxy peculiar velocities. On the super-horizon scale, "Copi etal. (2009)” have been arguing that the lack of large angular correlations of the CMB temperature field provides strong evidence against the standard, statistically isotropic, LCDM cosmology. I am going to argue that the "ad-hoc” discrepancy is due to the sub-optimal estimator of the low-l multipoles, and a posteriori statistics, which exaggerates the statistical significance. On Galactic scales, "Watkins et al. (2008)” shows that the very large bulk flow prefers a very large density fluctuation, which seems to contradict to the LCDM model. I am going to show that these results are due to their underestimation of the small scale velocity dispersion, and an arbitrary way of combining catalogues. With the appropriate way of combining catalogue data, as well as the treating the small scale velocity dispersion as a free parameter, the peculiar velocity field provides unconvincing evidence against LCDM cosmology.

Forecasting landscape-scale, cumulative effects of forest management on vegetation and wildlife habitat: a case study of issues, limitations, and opportunities

Treesearch

Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Zhaofei F. Fan

2008-01-01

Forest landscape disturbance and succession models have become practical tools for large-scale, long-term analyses of the cumulative effects of forest management on real landscapes. They can provide essential information in a spatial context to address management and policy issues related to forest planning, wildlife habitat quality, timber harvesting, fire effects,...

Scaling NASA Applications to 1024 CPUs on Origin 3K

NASA Technical Reports Server (NTRS)

Taft, Jim

2002-01-01

The long and highly successful joint SGI-NASA research effort in ever larger SSI systems was to a large degree the result of the successful development of the MLP scalable parallel programming paradigm developed at ARC: 1) MLP scaling in real production codes justified ever larger systems at NAS; 2) MLP scaling on 256p Origin 2000 gave SGl impetus to productize 256p; 3) MLP scaling on 512 gave SGI courage to build 1024p O3K; and 4) History of MLP success resulted in IBM Star Cluster based MLP effort.

REAL TIME CONTROL OF SEWERS: US EPA MANUAL

EPA Science Inventory

The problem of sewage spills and local flooding has traditionally been addressed by large scale capital improvement programs that focus on construction alternatives such as sewer separation or construction of storage facilities. The cost of such projects is often high, especiall...

A study on efficient detection of network-based IP spoofing DDoS and malware-infected Systems.

PubMed

Seo, Jung Woo; Lee, Sang Jin

2016-01-01

Large-scale network environments require effective detection and response methods against DDoS attacks. Depending on the advancement of IT infrastructure such as the server or network equipment, DDoS attack traffic arising from a few malware-infected systems capable of crippling the organization's internal network has become a significant threat. This study calculates the frequency of network-based packet attributes and analyzes the anomalies of the attributes in order to detect IP-spoofed DDoS attacks. Also, a method is proposed for the effective detection of malware infection systems triggering IP-spoofed DDoS attacks on an edge network. Detection accuracy and performance of the collected real-time traffic on a core network is analyzed thru the use of the proposed algorithm, and a prototype was developed to evaluate the performance of the algorithm. As a result, DDoS attacks on the internal network were detected in real-time and whether or not IP addresses were spoofed was confirmed. Detecting hosts infected by malware in real-time allowed the execution of intrusion responses before stoppage of the internal network caused by large-scale attack traffic.

The Cell Collective: Toward an open and collaborative approach to systems biology

PubMed Central

2012-01-01

Background Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. Results The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. Conclusions The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction. PMID:22871178

Modelling energy costs for different operational strategies of a large water resource recovery facility.

PubMed

Póvoa, P; Oehmen, A; Inocêncio, P; Matos, J S; Frazão, A

2017-05-01

The main objective of this paper is to demonstrate the importance of applying dynamic modelling and real energy prices on a full scale water resource recovery facility (WRRF) for the evaluation of control strategies in terms of energy costs with aeration. The Activated Sludge Model No. 1 (ASM1) was coupled with real energy pricing and a power consumption model and applied as a dynamic simulation case study. The model calibration is based on the STOWA protocol. The case study investigates the importance of providing real energy pricing comparing (i) real energy pricing, (ii) weighted arithmetic mean energy pricing and (iii) arithmetic mean energy pricing. The operational strategies evaluated were (i) old versus new air diffusers, (ii) different DO set-points and (iii) implementation of a carbon removal controller based on nitrate sensor readings. The application in a full scale WRRF of the ASM1 model coupled with real energy costs was successful. Dynamic modelling with real energy pricing instead of constant energy pricing enables the wastewater utility to optimize energy consumption according to the real energy price structure. Specific energy cost allows the identification of time periods with potential for linking WRRF with the electric grid to optimize the treatment costs, satisfying operational goals.

Real change in the real world: an achievable goal.

PubMed

Friedman, Robert M

2010-03-01

This commentary builds on the papers presented at the Vanderbilt Conference by emphasizing the importance of better understanding the process of change-making if real change in the real world is to be achieved. The commentary reviews several frameworks and research findings related to achieving large-scale sustainable change that benefits children and families. It calls for the application of systems thinking as a complement to the more micro-level research that was presented at the Vanderbilt conference. Such an approach would have implications for framing of the issue, for the strategies that are taken to try to achieve change, and for research/evaluation methods for studying complex, dynamic, nonlinear systems.

Statistical Analysis of Large Scale Structure by the Discrete Wavelet Transform

NASA Astrophysics Data System (ADS)

Pando, Jesus

1997-10-01

The discrete wavelet transform (DWT) is developed as a general statistical tool for the study of large scale structures (LSS) in astrophysics. The DWT is used in all aspects of structure identification including cluster analysis, spectrum and two-point correlation studies, scale-scale correlation analysis and to measure deviations from Gaussian behavior. The techniques developed are demonstrated on 'academic' signals, on simulated models of the Lymanα (Lyα) forests, and on observational data of the Lyα forests. This technique can detect clustering in the Ly-α clouds where traditional techniques such as the two-point correlation function have failed. The position and strength of these clusters in both real and simulated data is determined and it is shown that clusters exist on scales as large as at least 20 h-1 Mpc at significance levels of 2-4 σ. Furthermore, it is found that the strength distribution of the clusters can be used to distinguish between real data and simulated samples even where other traditional methods have failed to detect differences. Second, a method for measuring the power spectrum of a density field using the DWT is developed. All common features determined by the usual Fourier power spectrum can be calculated by the DWT. These features, such as the index of a power law or typical scales, can be detected even when the samples are geometrically complex, the samples are incomplete, or the mean density on larger scales is not known (the infrared uncertainty). Using this method the spectra of Ly-α forests in both simulated and real samples is calculated. Third, a method for measuring hierarchical clustering is introduced. Because hierarchical evolution is characterized by a set of rules of how larger dark matter halos are formed by the merging of smaller halos, scale-scale correlations of the density field should be one of the most sensitive quantities in determining the merging history. We show that these correlations can be completely determined by the correlations between discrete wavelet coefficients on adjacent scales and at nearly the same spatial position, Cj,j+12/cdot2. Scale-scale correlations on two samples of the QSO Ly-α forests absorption spectra are computed. Lastly, higher order statistics are developed to detect deviations from Gaussian behavior. These higher order statistics are necessary to fully characterize the Ly-α forests because the usual 2nd order statistics, such as the two-point correlation function or power spectrum, give inconclusive results. It is shown how this technique takes advantage of the locality of the DWT to circumvent the central limit theorem. A non-Gaussian spectrum is defined and this spectrum reveals not only the magnitude, but the scales of non-Gaussianity. When applied to simulated and observational samples of the Ly-α clouds, it is found that different popular models of structure formation have different spectra while two, independent observational data sets, have the same spectra. Moreover, the non-Gaussian spectra of real data sets are significantly different from the spectra of various possible random samples. (Abstract shortened by UMI.)

A fiber-optic ice detection system for large-scale wind turbine blades

NASA Astrophysics Data System (ADS)

Kim, Dae-gil; Sampath, Umesh; Kim, Hyunjin; Song, Minho

2017-09-01

Icing causes substantial problems in the integrity of large-scale wind turbines. In this work, a fiber-optic sensor system for detection of icing with an arrayed waveguide grating is presented. The sensor system detects Fresnel reflections from the ends of the fibers. The transition in Fresnel reflection due to icing gives peculiar intensity variations, which categorizes the ice, the water, and the air medium on the wind turbine blades. From the experimental results, with the proposed sensor system, the formation of icing conditions and thickness of ice were identified successfully in real time.

Friction-Stir Welding of Large Scale Cryogenic Fuel Tanks for Aerospace Applications

NASA Technical Reports Server (NTRS)

Jones, Clyde S., III; Venable, Richard A.

1998-01-01

The Marshall Space Flight Center has established a facility for the joining of large-scale aluminum-lithium alloy 2195 cryogenic fuel tanks using the friction-stir welding process. Longitudinal welds, approximately five meters in length, were made possible by retrofitting an existing vertical fusion weld system, designed to fabricate tank barrel sections ranging from two to ten meters in diameter. The structural design requirements of the tooling, clamping and the spindle travel system will be described in this paper. Process controls and real-time data acquisition will also be described, and were critical elements contributing to successful weld operation.

Large-Scale Wireless Temperature Monitoring System for Liquefied Petroleum Gas Storage Tanks.

PubMed

Fan, Guangwen; Shen, Yu; Hao, Xiaowei; Yuan, Zongming; Zhou, Zhi

2015-09-18

Temperature distribution is a critical indicator of the health condition for Liquefied Petroleum Gas (LPG) storage tanks. In this paper, we present a large-scale wireless temperature monitoring system to evaluate the safety of LPG storage tanks. The system includes wireless sensors networks, high temperature fiber-optic sensors, and monitoring software. Finally, a case study on real-world LPG storage tanks proves the feasibility of the system. The unique features of wireless transmission, automatic data acquisition and management, local and remote access make the developed system a good alternative for temperature monitoring of LPG storage tanks in practical applications.

Can compactifications solve the cosmological constant problem?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hertzberg, Mark P.; Center for Theoretical Physics, Department of Physics,Massachusetts Institute of Technology,77 Massachusetts Ave, Cambridge, MA 02139; Masoumi, Ali

2016-06-30

Recently, there have been claims in the literature that the cosmological constant problem can be dynamically solved by specific compactifications of gravity from higher-dimensional toy models. These models have the novel feature that in the four-dimensional theory, the cosmological constant Λ is much smaller than the Planck density and in fact accumulates at Λ=0. Here we show that while these are very interesting models, they do not properly address the real cosmological constant problem. As we explain, the real problem is not simply to obtain Λ that is small in Planck units in a toy model, but to explain whymore » Λ is much smaller than other mass scales (and combinations of scales) in the theory. Instead, in these toy models, all other particle mass scales have been either removed or sent to zero, thus ignoring the real problem. To this end, we provide a general argument that the included moduli masses are generically of order Hubble, so sending them to zero trivially sends the cosmological constant to zero. We also show that the fundamental Planck mass is being sent to zero, and so the central problem is trivially avoided by removing high energy physics altogether. On the other hand, by including various large mass scales from particle physics with a high fundamental Planck mass, one is faced with a real problem, whose only known solution involves accidental cancellations in a landscape.« less

Detection and analysis of part load and full load instabilities in a real Francis turbine prototype

NASA Astrophysics Data System (ADS)

Presas, Alexandre; Valentin, David; Egusquiza, Eduard; Valero, Carme

2017-04-01

Francis turbines operate in many cases out of its best efficiency point, in order to regulate their output power according to the instantaneous energy demand of the grid. Therefore, it is of paramount importance to analyse and determine the unstable operating points for these kind of units. In the framework of the HYPERBOLE project (FP7-ENERGY-2013-1; Project number 608532) a large Francis unit was investigated numerically, experimentally in a reduced scale model and also experimentally and numerically in the real prototype. This paper shows the unstable operating points identified during the experimental tests on the real Francis unit and the analysis of the main characteristics of these instabilities. Finally, it is shown that similar phenomena have been identified on previous research in the LMH (Laboratory for Hydraulic Machines, Lausanne) with the reduced scale model.

Thirty Years of Nonparametric Item Response Theory.

ERIC Educational Resources Information Center

Molenaar, Ivo W.

2001-01-01

Discusses relationships between a mathematical measurement model and its real-world applications. Makes a distinction between large-scale data matrices commonly found in educational measurement and smaller matrices found in attitude and personality measurement. Also evaluates nonparametric methods for estimating item response functions and…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Torcellini, P.; Pless, S.; Lobato, C.

Ongoing work at the National Renewable Energy Laboratory indicates that net-zero energy building (NZEB) status is both achievable and repeatable today. This paper presents a definition framework for classifying NZEBs and a real-life example that demonstrates how a large-scale office building can cost-effectively achieve net-zero energy.

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Welch, Gregory Francis; Zhang, Jinghe

2014-06-10

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuitiesmore » caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.« less

Mitigating Large Fires in Drossel-Schwabl Forest Fire Models

NASA Astrophysics Data System (ADS)

Yoder, M.; Turcotte, D.; Rundle, J.; Morein, G.

2008-12-01

We employ variations of the traditional Drossel-Schwabl cellular automata Forest Fire Models (FFM) to study wildfire dynamics. The traditional FFM produces a very robust power law distribution of events, as a function of size, with frequency-size slope very close to -1. Observed data from Australia, the US and northern Mexico suggest that real wild fires closely follow power laws in frequency size with slopes ranging from close to -2 to -1.3 (B.D. Malamud et al. 2005). We suggest two models that, by fracturing and trimming large clusters, reduce the number of large fires while maintaining scale invariance. These fracturing and trimming processes can be justified in terms of real physical processes. For each model, we achieve slopes in the frequency-size relation ranging from approximately -1.77 to -1.06.

Active Learning in PhysicsTechnology and Research-based Techniques Emphasizing Interactive Lecture Demonstrations

NASA Astrophysics Data System (ADS)

Thornton, Ronald

2010-10-01

Physics education research has shown that learning environments that engage students and allow them to take an active part in their learning can lead to large conceptual gains compared to traditional instruction. Examples of successful curricula and methods include Peer Instruction, Just in Time Teaching, RealTime Physics, Workshop Physics, Scale-Up, and Interactive Lecture Demonstrations (ILDs). An active learning environment is often difficult to achieve in lecture sessions. This presentation will demonstrate the use of sequences of Interactive Lecture Demonstrations (ILDs) that use real experiments often involving real-time data collection and display combined with student interaction to create an active learning environment in large or small lecture classes. Interactive lecture demonstrations will be done in the area of mechanics using real-time motion probes and the Visualizer. A video tape of students involved in interactive lecture demonstrations will be shown. The results of a number of research studies at various institutions (including international) to measure the effectiveness of ILDs and guided inquiry conceptual laboratories will be presented.

Appplication of statistical mechanical methods to the modeling of social networks

NASA Astrophysics Data System (ADS)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob; Gonder, Jeffrey D

The green routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation API route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). The navigation APIs, such Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin-destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption modelsmore » are built by assigning travel from a large number of GPS driving traces to the links in TomTom MultiNet as the underlying road network layer and road grade data from a U.S. Geological Survey elevation data set. Fuel consumption on a link is calculated by the proposed fuel consumption model. This paper envisions two kinds of applications: 1) identifying alternate routes that save fuel, and 2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey GPS trajectory data set is conducted. The fuel consumption and savings of CVs and HEVs are investigated. At the same time, the trade-off between fuel saving and time saving for choosing different routes is also examined for both powertrains.« less

A Java program for LRE-based real-time qPCR that enables large-scale absolute quantification.

PubMed

Rutledge, Robert G

2011-03-02

Linear regression of efficiency (LRE) introduced a new paradigm for real-time qPCR that enables large-scale absolute quantification by eliminating the need for standard curves. Developed through the application of sigmoidal mathematics to SYBR Green I-based assays, target quantity is derived directly from fluorescence readings within the central region of an amplification profile. However, a major challenge of implementing LRE quantification is the labor intensive nature of the analysis. Utilizing the extensive resources that are available for developing Java-based software, the LRE Analyzer was written using the NetBeans IDE, and is built on top of the modular architecture and windowing system provided by the NetBeans Platform. This fully featured desktop application determines the number of target molecules within a sample with little or no intervention by the user, in addition to providing extensive database capabilities. MS Excel is used to import data, allowing LRE quantification to be conducted with any real-time PCR instrument that provides access to the raw fluorescence readings. An extensive help set also provides an in-depth introduction to LRE, in addition to guidelines on how to implement LRE quantification. The LRE Analyzer provides the automated analysis and data storage capabilities required by large-scale qPCR projects wanting to exploit the many advantages of absolute quantification. Foremost is the universal perspective afforded by absolute quantification, which among other attributes, provides the ability to directly compare quantitative data produced by different assays and/or instruments. Furthermore, absolute quantification has important implications for gene expression profiling in that it provides the foundation for comparing transcript quantities produced by any gene with any other gene, within and between samples.

A Java Program for LRE-Based Real-Time qPCR that Enables Large-Scale Absolute Quantification

PubMed Central

Rutledge, Robert G.

2011-01-01

Background Linear regression of efficiency (LRE) introduced a new paradigm for real-time qPCR that enables large-scale absolute quantification by eliminating the need for standard curves. Developed through the application of sigmoidal mathematics to SYBR Green I-based assays, target quantity is derived directly from fluorescence readings within the central region of an amplification profile. However, a major challenge of implementing LRE quantification is the labor intensive nature of the analysis. Findings Utilizing the extensive resources that are available for developing Java-based software, the LRE Analyzer was written using the NetBeans IDE, and is built on top of the modular architecture and windowing system provided by the NetBeans Platform. This fully featured desktop application determines the number of target molecules within a sample with little or no intervention by the user, in addition to providing extensive database capabilities. MS Excel is used to import data, allowing LRE quantification to be conducted with any real-time PCR instrument that provides access to the raw fluorescence readings. An extensive help set also provides an in-depth introduction to LRE, in addition to guidelines on how to implement LRE quantification. Conclusions The LRE Analyzer provides the automated analysis and data storage capabilities required by large-scale qPCR projects wanting to exploit the many advantages of absolute quantification. Foremost is the universal perspective afforded by absolute quantification, which among other attributes, provides the ability to directly compare quantitative data produced by different assays and/or instruments. Furthermore, absolute quantification has important implications for gene expression profiling in that it provides the foundation for comparing transcript quantities produced by any gene with any other gene, within and between samples. PMID:21407812

Removal of Dissolved Silica using Calcinated Hydrotalcite in Real-life Applications.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sasan, Koroush; Brady, Patrick Vane.; Krumhansl, James L.

Water shortages are a growing global problem. Reclamation of industrial and municipal wastewater will be necessary in order to mitigate water scarcity. However, many operational challenges, such as silica scaling, prevent large scale water reuse. Previously, our team at Sandia has demonstrated the use of selective ion exchange materials, such as calcinated hydrotalcite (HTC, (Mg 6 Al 2 (OH) 16 (CO 3 )*4H 2 O)), for the low cost removal of silica from synthetic cooling tower water. However, it is not currently know if calcinated HTC has similar capabilities in realistic applications. The purpose of this study was to investigatemore » the ability of calcinated HTC to remove silica from real cooling tower water. This was investigated under both batch and continuous conditions, and in the presence of competing ions. It was determined that calcinated HTC behaved similarly in real and synthetic cooling tower water; the HTC is highly selective for the silica even in the presence of competing cations. Therefore, the data concludes that calcinated HTC is a viable anti-scaling pretreatment for the reuse of industrial wastewaters.« less

Ultra-Scale Computing for Emergency Evacuation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhaduri, Budhendra L; Nutaro, James J; Liu, Cheng

2010-01-01

Emergency evacuations are carried out in anticipation of a disaster such as hurricane landfall or flooding, and in response to a disaster that strikes without a warning. Existing emergency evacuation modeling and simulation tools are primarily designed for evacuation planning and are of limited value in operational support for real time evacuation management. In order to align with desktop computing, these models reduce the data and computational complexities through simple approximations and representations of real network conditions and traffic behaviors, which rarely represent real-world scenarios. With the emergence of high resolution physiographic, demographic, and socioeconomic data and supercomputing platforms, itmore » is possible to develop micro-simulation based emergency evacuation models that can foster development of novel algorithms for human behavior and traffic assignments, and can simulate evacuation of millions of people over a large geographic area. However, such advances in evacuation modeling and simulations demand computational capacity beyond the desktop scales and can be supported by high performance computing platforms. This paper explores the motivation and feasibility of ultra-scale computing for increasing the speed of high resolution emergency evacuation simulations.« less

Rapid DNA extraction protocol for detection of alpha-1 antitrypsin deficiency from dried blood spots by real-time PCR.

PubMed

Struniawski, R; Szpechcinski, A; Poplawska, B; Skronski, M; Chorostowska-Wynimko, J

2013-01-01

The dried blood spot (DBS) specimens have been successfully employed for the large-scale diagnostics of α1-antitrypsin (AAT) deficiency as an easy to collect and transport alternative to plasma/serum. In the present study we propose a fast, efficient, and cost effective protocol of DNA extraction from dried blood spot (DBS) samples that provides sufficient quantity and quality of DNA and effectively eliminates any natural PCR inhibitors, allowing for successful AAT genotyping by real-time PCR and direct sequencing. DNA extracted from 84 DBS samples from chronic obstructive pulmonary disease patients was genotyped for AAT deficiency variants by real-time PCR. The results of DBS AAT genotyping were validated by serum IEF phenotyping and AAT concentration measurement. The proposed protocol allowed successful DNA extraction from all analyzed DBS samples. Both quantity and quality of DNA were sufficient for further real-time PCR and, if necessary, for genetic sequence analysis. A 100% concordance between AAT DBS genotypes and serum phenotypes in positive detection of two major deficiency S- and Z- alleles was achieved. Both assays, DBS AAT genotyping by real-time PCR and serum AAT phenotyping by IEF, positively identified PI*S and PI*Z allele in 8 out of the 84 (9.5%) and 16 out of 84 (19.0%) patients, respectively. In conclusion, the proposed protocol noticeably reduces the costs and the hand-on-time of DBS samples preparation providing genomic DNA of sufficient quantity and quality for further real-time PCR or genetic sequence analysis. Consequently, it is ideally suited for large-scale AAT deficiency screening programs and should be method of choice.

Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010

NASA Astrophysics Data System (ADS)

García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

This study analyzes the evolution of different hydrological variables, such as soil moisture and real evapotranspiration, for the last 30 years, in the Douro Basin, the most extensive basin in the Iberian Peninsula. The different components of the real evaporation, connected to the soil moisture content, can be important when analyzing the intensity of droughts and heat waves, and particularly relevant for the study of the climate change impacts. The real evapotranspiration and soil moisture data are provided by simulations obtained using the Variable Infiltration Capacity (VIC) hydrological model. This model is a large-scale hydrologic model and allows estimates of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cells and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset are used as input variables for VIC model. The simulations have a spatial resolution of about 9 km, and the analysis is carried out on a seasonal time-scale. Additionally, we compare these results with those obtained from a dynamical downscaling driven by ERA-Interim data using the Weather Research and Forecasting (WRF) model, with the same spatial resolution. The results obtained from Spain02 data show a decrease in soil moisture at different parts of the basin during spring and summer, meanwhile soil moisture seems to be increased for autumn. No significant changes are found for real evapotranspiration. Keywords: real evapotranspiration, soil moisture, Douro Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Mapping the integrated Sachs-Wolfe effect

NASA Astrophysics Data System (ADS)

Manzotti, A.; Dodelson, S.

2014-12-01

On large scales, the anisotropies in the cosmic microwave background (CMB) reflect not only the primordial density field but also the energy gain when photons traverse decaying gravitational potentials of large scale structure, what is called the integrated Sachs-Wolfe (ISW) effect. Decomposing the anisotropy signal into a primordial piece and an ISW component, the main secondary effect on large scales, is more urgent than ever as cosmologists strive to understand the Universe on those scales. We present a likelihood technique for extracting the ISW signal combining measurements of the CMB, the distribution of galaxies, and maps of gravitational lensing. We test this technique with simulated data showing that we can successfully reconstruct the ISW map using all the data sets together. Then we present the ISW map obtained from a combination of real data: the NRAO VLA sky survey (NVSS) galaxy survey, temperature anisotropies, and lensing maps made by the Planck satellite. This map shows that, with the data sets used and assuming linear physics, there is no evidence, from the reconstructed ISW signal in the Cold Spot region, for an entirely ISW origin of this large scale anomaly in the CMB. However a large scale structure origin from low redshift voids outside the NVSS redshift range is still possible. Finally we show that future surveys, thanks to a better large scale lensing reconstruction will be able to improve the reconstruction signal to noise which is now mainly coming from galaxy surveys.

Large Scale Landslide Database System Established for the Reservoirs in Southern Taiwan

NASA Astrophysics Data System (ADS)

Tsai, Tsai-Tsung; Tsai, Kuang-Jung; Shieh, Chjeng-Lun

2017-04-01

Typhoon Morakot seriously attack southern Taiwan awaken the public awareness of large scale landslide disasters. Large scale landslide disasters produce large quantity of sediment due to negative effects on the operating functions of reservoirs. In order to reduce the risk of these disasters within the study area, the establishment of a database for hazard mitigation / disaster prevention is necessary. Real time data and numerous archives of engineering data, environment information, photo, and video, will not only help people make appropriate decisions, but also bring the biggest concern for people to process and value added. The study tried to define some basic data formats / standards from collected various types of data about these reservoirs and then provide a management platform based on these formats / standards. Meanwhile, in order to satisfy the practicality and convenience, the large scale landslide disasters database system is built both provide and receive information abilities, which user can use this large scale landslide disasters database system on different type of devices. IT technology progressed extreme quick, the most modern system might be out of date anytime. In order to provide long term service, the system reserved the possibility of user define data format /standard and user define system structure. The system established by this study was based on HTML5 standard language, and use the responsive web design technology. This will make user can easily handle and develop this large scale landslide disasters database system.

Fixing Teacher Professional Development

ERIC Educational Resources Information Center

Hill, Heather C.

2009-01-01

The professional development "system" for teachers is, by all accounts, broken. Despite evidence that specific programs can improve teacher knowledge and practice and student outcomes, these programs seldom reach real teachers on a large scale. Typically, reformers address such perceptions of failure by discovering and celebrating new formats and…

Quadtree of TIN: a new algorithm of dynamic LOD

NASA Astrophysics Data System (ADS)

Zhang, Junfeng; Fei, Lifan; Chen, Zhen

2009-10-01

Currently, Real-time visualization of large-scale digital elevation model mainly employs the regular structure of GRID based on quadtree and triangle simplification methods based on irregular triangulated network (TIN). TIN is a refined means to express the terrain surface in the computer science, compared with GRID. However, the data structure of TIN model is complex, and is difficult to realize view-dependence representation of level of detail (LOD) quickly. GRID is a simple method to realize the LOD of terrain, but contains more triangle count. A new algorithm, which takes full advantage of the two methods' merit, is presented in this paper. This algorithm combines TIN with quadtree structure to realize the view-dependence LOD controlling over the irregular sampling point sets, and holds the details through the distance of viewpoint and the geometric error of terrain. Experiments indicate that this approach can generate an efficient quadtree triangulation hierarchy over any irregular sampling point sets and achieve dynamic and visual multi-resolution performance of large-scale terrain at real-time.

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications.

PubMed

Sauer, Franz; Xie, Jinrong; Ma, Kwan-Liu

2017-10-01

The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a "unit cell" based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer's needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.

Line segment extraction for large scale unorganized point clouds

NASA Astrophysics Data System (ADS)

Lin, Yangbin; Wang, Cheng; Cheng, Jun; Chen, Bili; Jia, Fukai; Chen, Zhonggui; Li, Jonathan

2015-04-01

Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction.

Generalized Master Equation with Non-Markovian Multichromophoric Förster Resonance Energy Transfer for Modular Exciton Densities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jang, Seogjoo; Hoyer, Stephan; Fleming, Graham

2014-10-31

A generalized master equation (GME) governing quantum evolution of modular exciton density (MED) is derived for large scale light harvesting systems composed of weakly interacting modules of multiple chromophores. The GME-MED offers a practical framework to incorporate real time coherent quantum dynamics calculations of small length scales into dynamics over large length scales, and also provides a non-Markovian generalization and rigorous derivation of the Pauli master equation employing multichromophoric Förster resonance energy transfer rates. A test of the GME-MED for four sites of the Fenna-Matthews-Olson complex demonstrates how coherent dynamics of excitonic populations over coupled chromophores can be accurately describedmore » by transitions between subgroups (modules) of delocalized excitons. Application of the GME-MED to the exciton dynamics between a pair of light harvesting complexes in purple bacteria demonstrates its promise as a computationally efficient tool to investigate large scale exciton dynamics in complex environments.« less

Large-Scale medical image analytics: Recent methodologies, applications and Future directions.

PubMed

Zhang, Shaoting; Metaxas, Dimitris

2016-10-01

Despite the ever-increasing amount and complexity of annotated medical image data, the development of large-scale medical image analysis algorithms has not kept pace with the need for methods that bridge the semantic gap between images and diagnoses. The goal of this position paper is to discuss and explore innovative and large-scale data science techniques in medical image analytics, which will benefit clinical decision-making and facilitate efficient medical data management. Particularly, we advocate that the scale of image retrieval systems should be significantly increased at which interactive systems can be effective for knowledge discovery in potentially large databases of medical images. For clinical relevance, such systems should return results in real-time, incorporate expert feedback, and be able to cope with the size, quality, and variety of the medical images and their associated metadata for a particular domain. The design, development, and testing of the such framework can significantly impact interactive mining in medical image databases that are growing rapidly in size and complexity and enable novel methods of analysis at much larger scales in an efficient, integrated fashion. Copyright © 2016. Published by Elsevier B.V.

Reengineering Real-Time Software Systems

DTIC Science & Technology

1993-09-09

reengineering existing large-scale (or real-time) systems; systems designed prior to or during the advent of applied SE (Parnas 1979, Freeman 1980). Is... Advisor : Yutaka Kanayama Approved for public release; distribution is unlimited. 93-29769 93 12 6 098 Form Appmoved REPORT DOCUMENTATION PAGE 1o No. PI rep...trm b Idn 1o tl# caik t al wdornon s easnated to waere 1how per response. fr4ikcdm the time rem matnodons. siauide exetig da"a siuo a i and mami diqw

Experimental program for real gas flow code validation at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Deiwert, George S.; Strawa, Anthony W.; Sharma, Surendra P.; Park, Chul

1989-01-01

The experimental program for validating real gas hypersonic flow codes at NASA Ames Rsearch Center is described. Ground-based test facilities used include ballistic ranges, shock tubes and shock tunnels, arc jet facilities and heated-air hypersonic wind tunnels. Also included are large-scale computer systems for kinetic theory simulations and benchmark code solutions. Flight tests consist of the Aeroassist Flight Experiment, the Space Shuttle, Project Fire 2, and planetary probes such as Galileo, Pioneer Venus, and PAET.

GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmhan, Yogesh; Kumbhare, Alok; Wickramaarachchi, Charith

2014-08-25

Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally. However, there are limitations to this approach which cause vertex centric algorithms to under-perform due to poor compute to communication overhead ratio and slow convergence of iterative superstep. In this paper we introduce GoFFish a scalable sub-graph centric framework co-designed with a distributed persistent graph storage for large scale graph analytics on commodity clusters. We introduce a sub-graph centric programming abstraction that combines themore » scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation.« less

Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns

NASA Astrophysics Data System (ADS)

Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro

2017-05-01

The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

A PRACTICAL ONTOLOGY FOR THE LARGE-SCALE MODELING OF SCHOLARLY ARTIFACTS AND THEIR USAGE

DOE Office of Scientific and Technical Information (OSTI.GOV)

RODRIGUEZ, MARKO A.; BOLLEN, JOHAN; VAN DE SOMPEL, HERBERT

2007-01-30

The large-scale analysis of scholarly artifact usage is constrained primarily by current practices in usage data archiving, privacy issues concerned with the dissemination of usage data, and the lack of a practical ontology for modeling the usage domain. As a remedy to the third constraint, this article presents a scholarly ontology that was engineered to represent those classes for which large-scale bibliographic and usage data exists, supports usage research, and whose instantiation is scalable to the order of 50 million articles along with their associated artifacts (e.g. authors and journals) and an accompanying 1 billion usage events. The real worldmore » instantiation of the presented abstract ontology is a semantic network model of the scholarly community which lends the scholarly process to statistical analysis and computational support. They present the ontology, discuss its instantiation, and provide some example inference rules for calculating various scholarly artifact metrics.« less

Graph-based real-time fault diagnostics

NASA Technical Reports Server (NTRS)

Padalkar, S.; Karsai, G.; Sztipanovits, J.

1988-01-01

A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components.

Real-time fast physical random number generator with a photonic integrated circuit.

PubMed

Ugajin, Kazusa; Terashima, Yuta; Iwakawa, Kento; Uchida, Atsushi; Harayama, Takahisa; Yoshimura, Kazuyuki; Inubushi, Masanobu

2017-03-20

Random number generators are essential for applications in information security and numerical simulations. Most optical-chaos-based random number generators produce random bit sequences by offline post-processing with large optical components. We demonstrate a real-time hardware implementation of a fast physical random number generator with a photonic integrated circuit and a field programmable gate array (FPGA) electronic board. We generate 1-Tbit random bit sequences and evaluate their statistical randomness using NIST Special Publication 800-22 and TestU01. All of the BigCrush tests in TestU01 are passed using 410-Gbit random bit sequences. A maximum real-time generation rate of 21.1 Gb/s is achieved for random bit sequences in binary format stored in a computer, which can be directly used for applications involving secret keys in cryptography and random seeds in large-scale numerical simulations.

Large-scale frequency- and time-domain quantum entanglement over the optical frequency comb (Conference Presentation)

NASA Astrophysics Data System (ADS)

Pfister, Olivier

2017-05-01

When it comes to practical quantum computing, the two main challenges are circumventing decoherence (devastating quantum errors due to interactions with the environmental bath) and achieving scalability (as many qubits as needed for a real-life, game-changing computation). We show that using, in lieu of qubits, the "qumodes" represented by the resonant fields of the quantum optical frequency comb of an optical parametric oscillator allows one to create bona fide, large scale quantum computing processors, pre-entangled in a cluster state. We detail our recent demonstration of 60-qumode entanglement (out of an estimated 3000) and present an extension to combining this frequency-tagged with time-tagged entanglement, in order to generate an arbitrarily large, universal quantum computing processor.

Particle physics and polyedra proximity calculation for hazard simulations in large-scale industrial plants

NASA Astrophysics Data System (ADS)

Plebe, Alice; Grasso, Giorgio

2016-12-01

This paper describes a system developed for the simulation of flames inside an open-source 3D computer graphic software, Blender, with the aim of analyzing in virtual reality scenarios of hazards in large-scale industrial plants. The advantages of Blender are of rendering at high resolution the very complex structure of large industrial plants, and of embedding a physical engine based on smoothed particle hydrodynamics. This particle system is used to evolve a simulated fire. The interaction of this fire with the components of the plant is computed using polyhedron separation distance, adopting a Voronoi-based strategy that optimizes the number of feature distance computations. Results on a real oil and gas refining industry are presented.

Health-Terrain: Visualizing Large Scale Health Data

DTIC Science & Technology

2014-12-01

systems can only be realized if the quality of emerging large medical databases can be characterized and the meaning of the data understood. For this...Designed and tested an evaluation procedure for health data visualization system. This visualization framework offers a real time and web-based solution...rule is shown in the table, with the quality measures of each rule including the support, confidence, Laplace, Gain, p-s, lift and Conviction. We

Approaching the exa-scale: a real-world evaluation of rendering extremely large data sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patchett, John M; Ahrens, James P; Lo, Li - Ta

2010-10-15

Extremely large scale analysis is becoming increasingly important as supercomputers and their simulations move from petascale to exascale. The lack of dedicated hardware acceleration for rendering on today's supercomputing platforms motivates our detailed evaluation of the possibility of interactive rendering on the supercomputer. In order to facilitate our understanding of rendering on the supercomputing platform, we focus on scalability of rendering algorithms and architecture envisioned for exascale datasets. To understand tradeoffs for dealing with extremely large datasets, we compare three different rendering algorithms for large polygonal data: software based ray tracing, software based rasterization and hardware accelerated rasterization. We presentmore » a case study of strong and weak scaling of rendering extremely large data on both GPU and CPU based parallel supercomputers using Para View, a parallel visualization tool. Wc use three different data sets: two synthetic and one from a scientific application. At an extreme scale, algorithmic rendering choices make a difference and should be considered while approaching exascale computing, visualization, and analysis. We find software based ray-tracing offers a viable approach for scalable rendering of the projected future massive data sizes.« less

An Extended, Problem-Based Learning Laboratory Exercise on the Diagnosis of Infectious Diseases Suitable for Large Level 1 Undergraduate Biology Classes

ERIC Educational Resources Information Center

Tatner, Mary; Tierney, Anne

2016-01-01

The development and evaluation of a two-week laboratory class, based on the diagnosis of human infectious diseases, is described. It can be easily scaled up or down, to suit class sizes from 50 to 600 and completed in a shorter time scale, and to different audiences as desired. Students employ a range of techniques to solve a real-life and…

Clustering in the SDSS Redshift Survey

NASA Astrophysics Data System (ADS)

Zehavi, I.; Blanton, M. R.; Frieman, J. A.; Weinberg, D. H.; SDSS Collaboration

2002-05-01

We present measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our current sample consists of roughly 80,000 galaxies with redshifts in the range 0.02 < z < 0.2, covering about 1200 square degrees. We measure the clustering in redshift space and in real space. The two-dimensional correlation function ξ (rp,π ) shows clear signatures of redshift distortions, both the small-scale ``fingers-of-God'' effect and the large-scale compression. The inferred real-space correlation function is well described by a power law. The SDSS is especially suitable for investigating the dependence of clustering on galaxy properties, due to the wealth of information in the photometric survey. We focus on the dependence of clustering on color and on luminosity.

Interactive graphical computer-aided design system

NASA Technical Reports Server (NTRS)

Edge, T. M.

1975-01-01

System is used for design, layout, and modification of large-scale-integrated (LSI) metal-oxide semiconductor (MOS) arrays. System is structured around small computer which provides real-time support for graphics storage display unit with keyboard, slave display unit, hard copy unit, and graphics tablet for designer/computer interface.

Controlling Inventory: Real-World Mathematical Modeling

ERIC Educational Resources Information Center

Edwards, Thomas G.; Özgün-Koca, S. Asli; Chelst, Kenneth R.

2013-01-01

Amazon, Walmart, and other large-scale retailers owe their success partly to efficient inventory management. For such firms, holding too little inventory risks losing sales, whereas holding idle inventory wastes money. Therefore profits hinge on the inventory level chosen. In this activity, students investigate a simplified inventory-control…

Progress toward a low budget reference grade genome assembly

USDA-ARS?s Scientific Manuscript database

Reference quality de novo genome assemblies were once solely the domain of large, well-funded genome projects. While next-generation short read technology removed some of the cost barriers, accurate chromosome-scale assembly remains a real challenge. Here we present efforts to de novo assemble the...

Emissions of nitrous oxide from biomass burning

NASA Technical Reports Server (NTRS)

Winstead, Edward L.; Cofer, Wesley R., III; Levine, Joel S.

1991-01-01

A study has been conducted which compared N2O results obtained over large prescribed fires or wildfires, in which 'grab-sampling' with storage had been used with N2O measurements made in near-real time. CO2-normalized emission ratios obtained initially from the laboratory fires are substantially lower than those obtained over large-scale biomass fires. Combustion may not be the only source of N2O in large fire smoke plumes; physical, chemical, and biochemical processes in the soil may be altered by large biomass fires, leading to large N2O releases.

Neural Codes for One's Own Position and Direction in a Real-World "Vista" Environment.

PubMed

Sulpizio, Valentina; Boccia, Maddalena; Guariglia, Cecilia; Galati, Gaspare

2018-01-01

Humans, like animals, rely on an accurate knowledge of one's spatial position and facing direction to keep orientated in the surrounding space. Although previous neuroimaging studies demonstrated that scene-selective regions (the parahippocampal place area or PPA, the occipital place area or OPA and the retrosplenial complex or RSC), and the hippocampus (HC) are implicated in coding position and facing direction within small-(room-sized) and large-scale navigational environments, little is known about how these regions represent these spatial quantities in a large open-field environment. Here, we used functional magnetic resonance imaging (fMRI) in humans to explore the neural codes of these navigationally-relevant information while participants viewed images which varied for position and facing direction within a familiar, real-world circular square. We observed neural adaptation for repeated directions in the HC, even if no navigational task was required. Further, we found that the amount of knowledge of the environment interacts with the PPA selectivity in encoding positions: individuals who needed more time to memorize positions in the square during a preliminary training task showed less neural attenuation in this scene-selective region. We also observed adaptation effects, which reflect the real distances between consecutive positions, in scene-selective regions but not in the HC. When examining the multi-voxel patterns of activity we observed that scene-responsive regions and the HC encoded both spatial information and that the RSC classification accuracy for positions was higher in individuals scoring higher to a self-reported questionnaire of spatial abilities. Our findings provide new insight into how the human brain represents a real, large-scale "vista" space, demonstrating the presence of neural codes for position and direction in both scene-selective and hippocampal regions, and revealing the existence, in the former regions, of a map-like spatial representation reflecting real-world distance between consecutive positions.

How large a dataset should be in order to estimate scaling exponents and other statistics correctly in studies of solar wind turbulence

NASA Astrophysics Data System (ADS)

Rowlands, G.; Kiyani, K. H.; Chapman, S. C.; Watkins, N. W.

2009-12-01

Quantitative analysis of solar wind fluctuations are often performed in the context of intermittent turbulence and center around methods to quantify statistical scaling, such as power spectra and structure functions which assume a stationary process. The solar wind exhibits large scale secular changes and so the question arises as to whether the timeseries of the fluctuations is non-stationary. One approach is to seek a local stationarity by parsing the time interval over which statistical analysis is performed. Hence, natural systems such as the solar wind unavoidably provide observations over restricted intervals. Consequently, due to a reduction of sample size leading to poorer estimates, a stationary stochastic process (time series) can yield anomalous time variation in the scaling exponents, suggestive of nonstationarity. The variance in the estimates of scaling exponents computed from an interval of N observations is known for finite variance processes to vary as ~1/N as N becomes large for certain statistical estimators; however, the convergence to this behavior will depend on the details of the process, and may be slow. We study the variation in the scaling of second-order moments of the time-series increments with N for a variety of synthetic and “real world” time series, and we find that in particular for heavy tailed processes, for realizable N, one is far from this ~1/N limiting behavior. We propose a semiempirical estimate for the minimum N needed to make a meaningful estimate of the scaling exponents for model stochastic processes and compare these with some “real world” time series from the solar wind. With fewer datapoints the stationary timeseries becomes indistinguishable from a nonstationary process and we illustrate this with nonstationary synthetic datasets. Reference article: K. H. Kiyani, S. C. Chapman and N. W. Watkins, Phys. Rev. E 79, 036109 (2009).

Grindability measurements on low-rank fuels. [Prediction of large pulverizer performance from small scale test equipment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peipho, R.R.; Dougan, D.R.

1981-01-01

Experience has shown that the grinding characteristics of low rank coals are best determined by testing them in a pulverizer. Test results from a small MPS-32 Babcock and Wilcox pulverizer to predict large, full-scale pulverizer performance are presented. The MPS-32 apparatus, test procedure and evaluation of test results is described. The test data show that the Hardgrove apparatus and the ASTM test method must be used with great caution when considering low-rank fuels. The MPS-32 meets the needs for real-machine simulation but with some disadvantages. A smaller pulverizer is desirable. 1 ref.

Large-Scale Wireless Temperature Monitoring System for Liquefied Petroleum Gas Storage Tanks

PubMed Central

Fan, Guangwen; Shen, Yu; Hao, Xiaowei; Yuan, Zongming; Zhou, Zhi

2015-01-01

Temperature distribution is a critical indicator of the health condition for Liquefied Petroleum Gas (LPG) storage tanks. In this paper, we present a large-scale wireless temperature monitoring system to evaluate the safety of LPG storage tanks. The system includes wireless sensors networks, high temperature fiber-optic sensors, and monitoring software. Finally, a case study on real-world LPG storage tanks proves the feasibility of the system. The unique features of wireless transmission, automatic data acquisition and management, local and remote access make the developed system a good alternative for temperature monitoring of LPG storage tanks in practical applications. PMID:26393596

Using real options to evaluate the flexibility in the deployment of SMR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Locatelli, G.; Mancini, M.; Ruiz, F.

2012-07-01

According to recent estimations the financial gap between Large Reactors (LR) and Small Medium Reactors (SMRs) seems not as huge as the economy of scale would suggest, so the SMRs are going to be important players of the worldwide nuclear renaissance. POLIMIs INCAS model has been developed to compare the investment in SMR with respect to LR. It provides the value of IRR (Internal Rate of Return), NPV (Net Present Value), LUEC (Levelized Unitary Electricity Cost), up-front investment, etc. The aim of this research is to integrate the actual INCAS model, based on discounted cash flows, with the real optionmore » theory to measure flexibility of the investor to expand, defer or abandon a nuclear project, under future uncertainties. The work compares the investment in a large nuclear power plant with a series of smaller, modular nuclear power plants on the same site. As a consequence it compares the benefits of the large power plant, coming from the economy of scale, to the benefit of the modular project (flexibility) concluding that managerial flexibility can be measured and used by an investor to face the investment risks. (authors)« less

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

PubMed

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

A fast time-difference inverse solver for 3D EIT with application to lung imaging.

PubMed

Javaherian, Ashkan; Soleimani, Manuchehr; Moeller, Knut

2016-08-01

A class of sparse optimization techniques that require solely matrix-vector products, rather than an explicit access to the forward matrix and its transpose, has been paid much attention in the recent decade for dealing with large-scale inverse problems. This study tailors application of the so-called Gradient Projection for Sparse Reconstruction (GPSR) to large-scale time-difference three-dimensional electrical impedance tomography (3D EIT). 3D EIT typically suffers from the need for a large number of voxels to cover the whole domain, so its application to real-time imaging, for example monitoring of lung function, remains scarce since the large number of degrees of freedom of the problem extremely increases storage space and reconstruction time. This study shows the great potential of the GPSR for large-size time-difference 3D EIT. Further studies are needed to improve its accuracy for imaging small-size anomalies.

Canopy BRF simulation of forest with different crown shape and height in larger scale based on Radiosity method

NASA Astrophysics Data System (ADS)

Song, Jinling; Qu, Yonghua; Wang, Jindi; Wan, Huawei; Liu, Xiaoqing

2007-06-01

Radiosity method is based on the computer simulation of 3D real structures of vegetations, such as leaves, branches and stems, which are composed by many facets. Using this method we can simulate the canopy reflectance and its bidirectional distribution of the vegetation canopy in visible and NIR regions. But with vegetations are more complex, more facets to compose them, so large memory and lots of time to calculate view factors are required, which are the choke points of using Radiosity method to calculate canopy BRF of lager scale vegetation scenes. We derived a new method to solve the problem, and the main idea is to abstract vegetation crown shapes and to simplify their structures, which can lessen the number of facets. The facets are given optical properties according to the reflectance, transmission and absorption of the real structure canopy. Based on the above work, we can simulate the canopy BRF of the mix scenes with different species vegetation in the large scale. In this study, taking broadleaf trees as an example, based on their structure characteristics, we abstracted their crowns as ellipsoid shells, and simulated the canopy BRF in visible and NIR regions of the large scale scene with different crown shape and different height ellipsoids. Form this study, we can conclude: LAI, LAD the probability gap, the sunlit and shaded surfaces are more important parameter to simulate the simplified vegetation canopy BRF. And the Radiosity method can apply us canopy BRF data in any conditions for our research.

Real-time terrain storage generation from multiple sensors towards mobile robot operation interface.

PubMed

Song, Wei; Cho, Seoungjae; Xi, Yulong; Cho, Kyungeun; Um, Kyhyun

2014-01-01

A mobile robot mounted with multiple sensors is used to rapidly collect 3D point clouds and video images so as to allow accurate terrain modeling. In this study, we develop a real-time terrain storage generation and representation system including a nonground point database (PDB), ground mesh database (MDB), and texture database (TDB). A voxel-based flag map is proposed for incrementally registering large-scale point clouds in a terrain model in real time. We quantize the 3D point clouds into 3D grids of the flag map as a comparative table in order to remove the redundant points. We integrate the large-scale 3D point clouds into a nonground PDB and a node-based terrain mesh using the CPU. Subsequently, we program a graphics processing unit (GPU) to generate the TDB by mapping the triangles in the terrain mesh onto the captured video images. Finally, we produce a nonground voxel map and a ground textured mesh as a terrain reconstruction result. Our proposed methods were tested in an outdoor environment. Our results show that the proposed system was able to rapidly generate terrain storage and provide high resolution terrain representation for mobile mapping services and a graphical user interface between remote operators and mobile robots.

Real-Time Terrain Storage Generation from Multiple Sensors towards Mobile Robot Operation Interface

PubMed Central

Cho, Seoungjae; Xi, Yulong; Cho, Kyungeun

2014-01-01

A mobile robot mounted with multiple sensors is used to rapidly collect 3D point clouds and video images so as to allow accurate terrain modeling. In this study, we develop a real-time terrain storage generation and representation system including a nonground point database (PDB), ground mesh database (MDB), and texture database (TDB). A voxel-based flag map is proposed for incrementally registering large-scale point clouds in a terrain model in real time. We quantize the 3D point clouds into 3D grids of the flag map as a comparative table in order to remove the redundant points. We integrate the large-scale 3D point clouds into a nonground PDB and a node-based terrain mesh using the CPU. Subsequently, we program a graphics processing unit (GPU) to generate the TDB by mapping the triangles in the terrain mesh onto the captured video images. Finally, we produce a nonground voxel map and a ground textured mesh as a terrain reconstruction result. Our proposed methods were tested in an outdoor environment. Our results show that the proposed system was able to rapidly generate terrain storage and provide high resolution terrain representation for mobile mapping services and a graphical user interface between remote operators and mobile robots. PMID:25101321

Invasion complexity at large spatial scales is an emergent property of interactions among landscape characteristics and invader traits

USDA-ARS?s Scientific Manuscript database

Understanding the potential for invasive spread is an important consideration for novel agricultural species that may be translocated or introduced into new regions. However, estimating invasion risks remains a challenging problem, particularly in the context of real, complex landscapes. There is ...

Broad-scale consequences of land management: Columbia basin example.

Treesearch

Richard W. Haynes; Thomas M. Quigley

2001-01-01

Integrating management actions to consistently achieve broad ecological and socioeconomic goals is a challenge largely unmet. The presumed or real conflict between these goals establishes a forum for debate. Broad measures are needed to describe tradeoffs, trends in conditions under varying management scenarios, and a transparent science underpinning. The Interior...

Multiple Streaming and the Probability Distribution of Density in Redshift Space

NASA Astrophysics Data System (ADS)

Hui, Lam; Kofman, Lev; Shandarin, Sergei F.

2000-07-01

We examine several aspects of redshift distortions by expressing the redshift-space density in terms of the eigenvalues and orientation of the local Lagrangian deformation tensor. We explore the importance of multiple streaming using the Zeldovich approximation (ZA), and compute the average number of streams in both real and redshift space. We find that multiple streaming can be significant in redshift space but negligible in real space, even at moderate values of the linear fluctuation amplitude (σl<~1). Moreover, unlike their real-space counterparts, redshift-space multiple streams can flow past each other with minimal interactions. Such nonlinear redshift-space effects, which are physically distinct from the fingers-of-God due to small-scale virialized motions, might in part explain the well-known departure of redshift distortions from the classic linear prediction by Kaiser, even at relatively large scales where the corresponding density field in real space is well described by linear perturbation theory. We also compute, using the ZA, the probability distribution function (PDF) of the density, as well as S3, in real and redshift space, and compare it with the PDF measured from N-body simulations. The role of caustics in defining the character of the high-density tail is examined. We find that (non-Lagrangian) smoothing, due to both finite resolution or discreteness and small-scale velocity dispersions, is very effective in erasing caustic structures, unless the initial power spectrum is sufficiently truncated.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sunayama, Tomomi; Padmanabhan, Nikhil; Heitmann, Katrin

Precision measurements of the large scale structure of the Universe require large numbers of high fidelity mock catalogs to accurately assess, and account for, the presence of systematic effects. We introduce and test a scheme for generating mock catalogs rapidly using suitably derated N-body simulations. Our aim is to reproduce the large scale structure and the gross properties of dark matter halos with high accuracy, while sacrificing the details of the halo's internal structure. By adjusting global and local time-steps in an N-body code, we demonstrate that we recover halo masses to better than 0.5% and the power spectrum tomore » better than 1% both in real and redshift space for k =1 h Mpc{sup −1}, while requiring a factor of 4 less CPU time. We also calibrate the redshift spacing of outputs required to generate simulated light cones. We find that outputs separated by Δ z =0.05 allow us to interpolate particle positions and velocities to reproduce the real and redshift space power spectra to better than 1% (out to k =1 h Mpc{sup −1}). We apply these ideas to generate a suite of simulations spanning a range of cosmologies, motivated by the Baryon Oscillation Spectroscopic Survey (BOSS) but broadly applicable to future large scale structure surveys including eBOSS and DESI. As an initial demonstration of the utility of such simulations, we calibrate the shift in the baryonic acoustic oscillation peak position as a function of galaxy bias with higher precision than has been possible so far. This paper also serves to document the simulations, which we make publicly available.« less

Multiscale unfolding of real networks by geometric renormalization

NASA Astrophysics Data System (ADS)

García-Pérez, Guillermo; Boguñá, Marián; Serrano, M. Ángeles

2018-06-01

Symmetries in physical theories denote invariance under some transformation, such as self-similarity under a change of scale. The renormalization group provides a powerful framework to study these symmetries, leading to a better understanding of the universal properties of phase transitions. However, the small-world property of complex networks complicates application of the renormalization group by introducing correlations between coexisting scales. Here, we provide a framework for the investigation of complex networks at different resolutions. The approach is based on geometric representations, which have been shown to sustain network navigability and to reveal the mechanisms that govern network structure and evolution. We define a geometric renormalization group for networks by embedding them into an underlying hidden metric space. We find that real scale-free networks show geometric scaling under this renormalization group transformation. We unfold the networks in a self-similar multilayer shell that distinguishes the coexisting scales and their interactions. This in turn offers a basis for exploring critical phenomena and universality in complex networks. It also affords us immediate practical applications, including high-fidelity smaller-scale replicas of large networks and a multiscale navigation protocol in hyperbolic space, which betters those on single layers.

Scaling Effects on Materials Tribology: From Macro to Micro Scale.

PubMed

Stoyanov, Pantcho; Chromik, Richard R

2017-05-18

The tribological study of materials inherently involves the interaction of surface asperities at the micro to nanoscopic length scales. This is the case for large scale engineering applications with sliding contacts, where the real area of contact is made up of small contacting asperities that make up only a fraction of the apparent area of contact. This is why researchers have sought to create idealized experiments of single asperity contacts in the field of nanotribology. At the same time, small scale engineering structures known as micro- and nano-electromechanical systems (MEMS and NEMS) have been developed, where the apparent area of contact approaches the length scale of the asperities, meaning the real area of contact for these devices may be only a few asperities. This is essentially the field of microtribology, where the contact size and/or forces involved have pushed the nature of the interaction between two surfaces towards the regime where the scale of the interaction approaches that of the natural length scale of the features on the surface. This paper provides a review of microtribology with the purpose to understand how tribological processes are different at the smaller length scales compared to macrotribology. Studies of the interfacial phenomena at the macroscopic length scales (e.g., using in situ tribometry) will be discussed and correlated with new findings and methodologies at the micro-length scale.

Scaling Effects on Materials Tribology: From Macro to Micro Scale

PubMed Central

Stoyanov, Pantcho; Chromik, Richard R.

2017-01-01

The tribological study of materials inherently involves the interaction of surface asperities at the micro to nanoscopic length scales. This is the case for large scale engineering applications with sliding contacts, where the real area of contact is made up of small contacting asperities that make up only a fraction of the apparent area of contact. This is why researchers have sought to create idealized experiments of single asperity contacts in the field of nanotribology. At the same time, small scale engineering structures known as micro- and nano-electromechanical systems (MEMS and NEMS) have been developed, where the apparent area of contact approaches the length scale of the asperities, meaning the real area of contact for these devices may be only a few asperities. This is essentially the field of microtribology, where the contact size and/or forces involved have pushed the nature of the interaction between two surfaces towards the regime where the scale of the interaction approaches that of the natural length scale of the features on the surface. This paper provides a review of microtribology with the purpose to understand how tribological processes are different at the smaller length scales compared to macrotribology. Studies of the interfacial phenomena at the macroscopic length scales (e.g., using in situ tribometry) will be discussed and correlated with new findings and methodologies at the micro-length scale. PMID:28772909

GW/Bethe-Salpeter calculations for charged and model systems from real-space DFT

NASA Astrophysics Data System (ADS)

Strubbe, David A.

GW and Bethe-Salpeter (GW/BSE) calculations use mean-field input from density-functional theory (DFT) calculations to compute excited states of a condensed-matter system. Many parts of a GW/BSE calculation are efficiently performed in a plane-wave basis, and extensive effort has gone into optimizing and parallelizing plane-wave GW/BSE codes for large-scale computations. Most straightforwardly, plane-wave DFT can be used as a starting point, but real-space DFT is also an attractive starting point: it is systematically convergeable like plane waves, can take advantage of efficient domain parallelization for large systems, and is well suited physically for finite and especially charged systems. The flexibility of a real-space grid also allows convenient calculations on non-atomic model systems. I will discuss the interfacing of a real-space (TD)DFT code (Octopus, www.tddft.org/programs/octopus) with a plane-wave GW/BSE code (BerkeleyGW, www.berkeleygw.org), consider performance issues and accuracy, and present some applications to simple and paradigmatic systems that illuminate fundamental properties of these approximations in many-body perturbation theory.

Rapid Large Earthquake and Run-up Characterization in Quasi Real Time

NASA Astrophysics Data System (ADS)

Bravo, F. J.; Riquelme, S.; Koch, P.; Cararo, S.

2017-12-01

Several test in quasi real time have been conducted by the rapid response group at CSN (National Seismological Center) to characterize earthquakes in Real Time. These methods are known for its robustness and realibility to create Finite Fault Models. The W-phase FFM Inversion, The Wavelet Domain FFM and The Body Wave and FFM have been implemented in real time at CSN, all these algorithms are running automatically and triggered by the W-phase Point Source Inversion. Dimensions (Large and Width ) are predefined by adopting scaling laws for earthquakes in subduction zones. We tested the last four major earthquakes occurred in Chile using this scheme: The 2010 Mw 8.8 Maule Earthquake, The 2014 Mw 8.2 Iquique Earthquake, The 2015 Mw 8.3 Illapel Earthquake and The 7.6 Melinka Earthquake. We obtain many solutions as time elapses, for each one of those we calculate the run-up using an analytical formula. Our results are in agreements with some FFM already accepted by the sicentific comunnity aswell as run-up observations in the field.

Quasi-real-time end-to-end simulations of ELT-scale adaptive optics systems on GPUs

NASA Astrophysics Data System (ADS)

Gratadour, Damien

2011-09-01

Our team has started the development of a code dedicated to GPUs for the simulation of AO systems at the E-ELT scale. It uses the CUDA toolkit and an original binding to Yorick (an open source interpreted language) to provide the user with a comprehensive interface. In this paper we present the first performance analysis of our simulation code, showing its ability to provide Shack-Hartmann (SH) images and measurements at the kHz scale for VLT-sized AO system and in quasi-real-time (up to 70 Hz) for ELT-sized systems on a single top-end GPU. The simulation code includes multiple layers atmospheric turbulence generation, ray tracing through these layers, image formation at the focal plane of every sub-apertures of a SH sensor using either natural or laser guide stars and centroiding on these images using various algorithms. Turbulence is generated on-the-fly giving the ability to simulate hours of observations without the need of loading extremely large phase screens in the global memory. Because of its performance this code additionally provides the unique ability to test real-time controllers for future AO systems under nominal conditions.

Laboratory-Scale Simulation and Real-Time Tracking of a Microbial Contamination Event and Subsequent Shock-Chlorination in Drinking Water

PubMed Central

Besmer, Michael D.; Sigrist, Jürg A.; Props, Ruben; Buysschaert, Benjamin; Mao, Guannan; Boon, Nico; Hammes, Frederik

2017-01-01

Rapid contamination of drinking water in distribution and storage systems can occur due to pressure drop, backflow, cross-connections, accidents, and bio-terrorism. Small volumes of a concentrated contaminant (e.g., wastewater) can contaminate large volumes of water in a very short time with potentially severe negative health impacts. The technical limitations of conventional, cultivation-based microbial detection methods neither allow for timely detection of such contaminations, nor for the real-time monitoring of subsequent emergency remediation measures (e.g., shock-chlorination). Here we applied a newly developed continuous, ultra high-frequency flow cytometry approach to track a rapid pollution event and subsequent disinfection of drinking water in an 80-min laboratory scale simulation. We quantified total (TCC) and intact (ICC) cell concentrations as well as flow cytometric fingerprints in parallel in real-time with two different staining methods. The ingress of wastewater was detectable almost immediately (i.e., after 0.6% volume change), significantly changing TCC, ICC, and the flow cytometric fingerprint. Shock chlorination was rapid and detected in real time, causing membrane damage in the vast majority of bacteria (i.e., drop of ICC from more than 380 cells μl-1 to less than 30 cells μl-1 within 4 min). Both of these effects as well as the final wash-in of fresh tap water followed calculated predictions well. Detailed and highly quantitative tracking of microbial dynamics at very short time scales and for different characteristics (e.g., concentration, membrane integrity) is feasible. This opens up multiple possibilities for targeted investigation of a myriad of bacterial short-term dynamics (e.g., disinfection, growth, detachment, operational changes) both in laboratory-scale research and full-scale system investigations in practice. PMID:29085343

Real-Time Reed-Solomon Decoder

NASA Technical Reports Server (NTRS)

Maki, Gary K.; Cameron, Kelly B.; Owsley, Patrick A.

1994-01-01

Generic Reed-Solomon decoder fast enough to correct errors in real time in practical applications designed to be implemented in fewer and smaller very-large-scale integrated, VLSI, circuit chips. Configured to operate in pipelined manner. One outstanding aspect of decoder design is that Euclid multiplier and divider modules contain Galoisfield multipliers configured as combinational-logic cells. Operates at speeds greater than older multipliers. Cellular configuration highly regular and requires little interconnection area, making it ideal for implementation in extraordinarily dense VLSI circuitry. Flight electronics single chip version of this technology implemented and available.

Towards physics responsible for large-scale Lyman-α forest bias parameters

DOE PAGES

Agnieszka M. Cieplak; Slosar, Anze

2016-03-08

Using a series of carefully constructed numerical experiments based on hydrodynamic cosmological SPH simulations, we attempt to build an intuition for the relevant physics behind the large scale density (b δ) and velocity gradient (b η) biases of the Lyman-α forest. Starting with the fluctuating Gunn-Peterson approximation applied to the smoothed total density field in real-space, and progressing through redshift-space with no thermal broadening, redshift-space with thermal broadening and hydrodynamically simulated baryon fields, we investigate how approximations found in the literature fare. We find that Seljak's 2012 analytical formulae for these bias parameters work surprisingly well in the limit ofmore » no thermal broadening and linear redshift-space distortions. We also show that his b η formula is exact in the limit of no thermal broadening. Since introduction of thermal broadening significantly affects its value, we speculate that a combination of large-scale measurements of b η and the small scale flux PDF might be a sensitive probe of the thermal state of the IGM. Lastly, we find that large-scale biases derived from the smoothed total matter field are within 10–20% to those based on hydrodynamical quantities, in line with other measurements in the literature.« less

Towards physics responsible for large-scale Lyman-α forest bias parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agnieszka M. Cieplak; Slosar, Anze

Using a series of carefully constructed numerical experiments based on hydrodynamic cosmological SPH simulations, we attempt to build an intuition for the relevant physics behind the large scale density (b δ) and velocity gradient (b η) biases of the Lyman-α forest. Starting with the fluctuating Gunn-Peterson approximation applied to the smoothed total density field in real-space, and progressing through redshift-space with no thermal broadening, redshift-space with thermal broadening and hydrodynamically simulated baryon fields, we investigate how approximations found in the literature fare. We find that Seljak's 2012 analytical formulae for these bias parameters work surprisingly well in the limit ofmore » no thermal broadening and linear redshift-space distortions. We also show that his b η formula is exact in the limit of no thermal broadening. Since introduction of thermal broadening significantly affects its value, we speculate that a combination of large-scale measurements of b η and the small scale flux PDF might be a sensitive probe of the thermal state of the IGM. Lastly, we find that large-scale biases derived from the smoothed total matter field are within 10–20% to those based on hydrodynamical quantities, in line with other measurements in the literature.« less

Mass dependence of Higgs boson production at large transverse momentum through a bottom-quark loop

NASA Astrophysics Data System (ADS)

Braaten, Eric; Zhang, Hong; Zhang, Jia-Wei

2018-05-01

In the production of the Higgs through a bottom-quark loop, the transverse momentum distribution of the Higgs at large PT is complicated by its dependence on two other important scales: the bottom quark mass mb and the Higgs mass mH. A strategy for simplifying the calculation of the cross section at large PT is to calculate only the leading terms in its expansion in mb2/PT2. In this paper, we consider the bottom-quark-loop contribution to the parton process q q ¯→H +g at leading order in αs. We show that the leading power of 1 /PT2 can be expressed in the form of a factorization formula that separates the large scale PT from the scale of the masses. All the dependence on mb and mH can be factorized into a distribution amplitude for b b ¯ in the Higgs, a distribution amplitude for b b ¯ in a real gluon, and an end point contribution. The factorization formula can be used to organize the calculation of the leading terms in the expansion in mb2/PT2 so that every calculation involves at most two scales.

Highly Efficient Large-Scale Lentiviral Vector Concentration by Tandem Tangential Flow Filtration

PubMed Central

Cooper, Aaron R.; Patel, Sanjeet; Senadheera, Shantha; Plath, Kathrin; Kohn, Donald B.; Hollis, Roger P.

2014-01-01

Large-scale lentiviral vector (LV) concentration can be inefficient and time consuming, often involving multiple rounds of filtration and centrifugation. This report describes a simpler method using two tangential flow filtration (TFF) steps to concentrate liter-scale volumes of LV supernatant, achieving in excess of 2000-fold concentration in less than 3 hours with very high recovery (>97%). Large volumes of LV supernatant can be produced easily through the use of multi-layer flasks, each having 1720 cm2 surface area and producing ~560 mL of supernatant per flask. Combining the use of such flasks and TFF greatly simplifies large-scale production of LV. As a demonstration, the method is used to produce a very high titer LV (>1010 TU/mL) and transduce primary human CD34+ hematopoietic stem/progenitor cells at high final vector concentrations with no overt toxicity. A complex LV (STEMCCA) for induced pluripotent stem cell generation is also concentrated from low initial titer and used to transduce and reprogram primary human fibroblasts with no overt toxicity. Additionally, a generalized and simple multiplexed real- time PCR assay is described for lentiviral vector titer and copy number determination. PMID:21784103

True gender ratios and stereotype rating norms

PubMed Central

Garnham, Alan; Doehren, Sam; Gygax, Pascal

2015-01-01

We present a study comparing, in English, perceived distributions of men and women in 422 named occupations with actual real world distributions. The first set of data was obtained from previous a large-scale norming study, whereas the second set was mostly drawn from UK governmental sources. In total, real world ratios for 290 occupations were obtained for our perceive vs. real world comparison, of which 205 were deemed to be unproblematic. The means for the two sources were similar and the correlation between them was high, suggesting that people are generally accurate at judging real gender ratios, though there were some notable exceptions. Beside this correlation, some interesting patterns emerged from the two sources, suggesting some response strategies when people complete norming studies. We discuss these patterns in terms of the way real world data might complement norming studies in determining gender stereotypicality. PMID:26257681

A real-world size organization of object responses in occipito-temporal cortex

PubMed Central

Konkle, Talia; Oliva, Aude

2012-01-01

SUMMARY While there are selective regions of occipito-temporal cortex that respond to faces, letters, and bodies, the large-scale neural organization of most object categories remains unknown. Here we find that object representations can be differentiated along the ventral temporal cortex by their real-world size. In a functional neuroimaging experiment, observers were shown pictures of big and small real-world objects (e.g. table, bathtub; paperclip, cup), presented at the same retinal size. We observed a consistent medial-to-lateral organization of big and small object preferences in the ventral temporal cortex, mirrored along the lateral surface. Regions in the lateral-occipital, infero-temporal, and parahippocampal cortices showed strong peaks of differential real-world size selectivity, and maintained these preferences over changes in retinal size and in mental imagery. These data demonstrate that the real-world size of objects can provide insight into the spatial topography of object representation. PMID:22726840

Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains

NASA Astrophysics Data System (ADS)

Stoop, Ralph; Saase, Victor; Wagner, Clemens; Stoop, Britta; Stoop, Ruedi

2013-03-01

We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic—intercolumnar—scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks.

Cryogenic Selective Surface - How Cold Can We Go?

NASA Technical Reports Server (NTRS)

Youngquist, Robert; Nurge, Mark

2015-01-01

Selective surfaces have wavelength dependent emissivitya bsorption. These surfaces can be designed to reflect solar radiation, while maximizing infrared emittance, yielding a cooling effect even in sunlight. On earth cooling to -50 C below ambient has been achieved, but in space, outside of the atmosphere, theory using ideal materials has predicted a maximum cooling to 40 K! If this result holds up for real world materials and conditions, then superconducting systems and cryogenic storage can be achieved in space without active cooling. Such a result would enable long term cryogenic storage in deep space and the use of large scale superconducting systems for such applications as galactic cosmic radiation (GCR) shielding and large scale energy storage.

Efficient estimation and large-scale evaluation of lateral chromatic aberration for digital image forensics

NASA Astrophysics Data System (ADS)

Gloe, Thomas; Borowka, Karsten; Winkler, Antje

2010-01-01

The analysis of lateral chromatic aberration forms another ingredient for a well equipped toolbox of an image forensic investigator. Previous work proposed its application to forgery detection1 and image source identification.2 This paper takes a closer look on the current state-of-the-art method to analyse lateral chromatic aberration and presents a new approach to estimate lateral chromatic aberration in a runtime-efficient way. Employing a set of 11 different camera models including 43 devices, the characteristic of lateral chromatic aberration is investigated in a large-scale. The reported results point to general difficulties that have to be considered in real world investigations.

Grid sensitivity capability for large scale structures

NASA Technical Reports Server (NTRS)

Nagendra, Gopal K.; Wallerstein, David V.

1989-01-01

The considerations and the resultant approach used to implement design sensitivity capability for grids into a large scale, general purpose finite element system (MSC/NASTRAN) are presented. The design variables are grid perturbations with a rather general linking capability. Moreover, shape and sizing variables may be linked together. The design is general enough to facilitate geometric modeling techniques for generating design variable linking schemes in an easy and straightforward manner. Test cases have been run and validated by comparison with the overall finite difference method. The linking of a design sensitivity capability for shape variables in MSC/NASTRAN with an optimizer would give designers a powerful, automated tool to carry out practical optimization design of real life, complicated structures.

Tuneable diode laser gas analyser for methane measurements on a large scale solid oxide fuel cell

NASA Astrophysics Data System (ADS)

Lengden, Michael; Cunningham, Robert; Johnstone, Walter

2011-10-01

A new in-line, real time gas analyser is described that uses tuneable diode laser spectroscopy (TDLS) for the measurement of methane in solid oxide fuel cells. The sensor has been tested on an operating solid oxide fuel cell (SOFC) in order to prove the fast response and accuracy of the technology as compared to a gas chromatograph. The advantages of using a TDLS system for process control in a large-scale, distributed power SOFC unit are described. In future work, the addition of new laser sources and wavelength modulation will allow the simultaneous measurement of methane, water vapour, carbon-dioxide and carbon-monoxide concentrations.

DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals

DTIC Science & Technology

2014-09-30

repeating pulse-like signals were investigated. Software prototypes were developed and integrated into distinct streams of reseach ; projects...to study complex sound archives spanning large spatial and temporal scales. A new post processing method for detection and classifcation was also...false positive rates. HK-ANN was successfully tested for a large minke whale dataset, but could easily be used on other signal types. Various

Bringing Abstract Academic Integrity and Ethical Concepts into Real-Life Situations

ERIC Educational Resources Information Center

Kwong, Theresa; Wong, Eva; Yue, Kevin

2017-01-01

This paper reports the learning analytics on the initial stages of a large-scale, government-funded project which inducts university students in Hong Kong into consideration of academic integrity and ethics through mobile Augmented Reality (AR) learning trails--Trails of Integrity and Ethics (TIEs)--accessed on smart devices. The trails immerse…

A CMOS VLSI IC for Real-Time Opto-Electronic Two-Dimensional Histogram Generation

DTIC Science & Technology

1993-12-01

large scale integration) design; MAGIC ; CMOS; optics; image processing; 93 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATiON 19...1. Sun SPARCstation ............. .............. 6 2. Magic .................. ................... 6 a. Peg ................. .................. 7 b...38 v APPENDIX B. MAGIC CELL LAYOUTS .... ............ .. 39 APPENDIX C: SIMULATION DATA ....... ............. .. 56 A. FINITE STATE MACHINE

Educational Research with Real-World Data: Reducing Selection Bias with Propensity Scores

ERIC Educational Resources Information Center

Adelson, Jill L.

2013-01-01

Often it is infeasible or unethical to use random assignment in educational settings to study important constructs and questions. Hence, educational research often uses observational data, such as large-scale secondary data sets and state and school district data, and quasi-experimental designs. One method of reducing selection bias in estimations…

Evaluating real-time Java for mission-critical large-scale embedded systems

NASA Technical Reports Server (NTRS)

Sharp, D. C.; Pla, E.; Luecke, K. R.; Hassan, R. J.

2003-01-01

This paper describes benchmarking results on an RT JVM. This paper extends previously published results by including additional tests, by being run on a recently available pre-release version of the first commercially supported RTSJ implementation, and by assessing results based on our experience with avionics systems in other languages.

Is Game Behavior Related to Behavior in Any Other Situation?

ERIC Educational Resources Information Center

McTavish, Jeanne

This paper begins by reviewing previous research concerning the external validity of mixed-motive games as models of international conflict, interpersonal behavior, and behavior in large-scale social dilemmas. Two further experiments are then described, both of which cast further doubt upon the usefulness of such games as models of any real-world…

An Empirical Generative Framework for Computational Modeling of Language Acquisition

ERIC Educational Resources Information Center

Waterfall, Heidi R.; Sandbank, Ben; Onnis, Luca; Edelman, Shimon

2010-01-01

This paper reports progress in developing a computer model of language acquisition in the form of (1) a generative grammar that is (2) algorithmically learnable from realistic corpus data, (3) viable in its large-scale quantitative performance and (4) psychologically real. First, we describe new algorithmic methods for unsupervised learning of…

Virtual Environments Supporting Learning and Communication in Special Needs Education

ERIC Educational Resources Information Center

Cobb, Sue V. G.

2007-01-01

Virtual reality (VR) describes a set of technologies that allow users to explore and experience 3-dimensional computer-generated "worlds" or "environments." These virtual environments can contain representations of real or imaginary objects on a small or large scale (from modeling of molecular structures to buildings, streets, and scenery of a…

Research to Real Life, 2006: Innovations in Deaf-Blindness

ERIC Educational Resources Information Center

Leslie, Gail, Ed.

2006-01-01

This publication presents several projects that support children who are deaf-blind. These projects are: (1) Learning To Learn; (2) Project SALUTE; (3) Project SPARKLE; (4) Bringing It All Back Home; (5) Project PRIIDE; and (6) Including Students With Deafblindness In Large Scale Assessment Systems. Each project lists components, key practices,…

The Design and Evaluation of a Large-Scale Real-Walking Locomotion Interface

PubMed Central

Peck, Tabitha C.; Fuchs, Henry; Whitton, Mary C.

2014-01-01

Redirected Free Exploration with Distractors (RFED) is a large-scale real-walking locomotion interface developed to enable people to walk freely in virtual environments that are larger than the tracked space in their facility. This paper describes the RFED system in detail and reports on a user study that evaluated RFED by comparing it to walking-in-place and joystick interfaces. The RFED system is composed of two major components, redirection and distractors. This paper discusses design challenges, implementation details, and lessons learned during the development of two working RFED systems. The evaluation study examined the effect of the locomotion interface on users’ cognitive performance on navigation and wayfinding measures. The results suggest that participants using RFED were significantly better at navigating and wayfinding through virtual mazes than participants using walking-in-place and joystick interfaces. Participants traveled shorter distances, made fewer wrong turns, pointed to hidden targets more accurately and more quickly, and were able to place and label targets on maps more accurately, and more accurately estimate the virtual environment size. PMID:22184262

SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

PubMed

Sripad, Athul; Sanchez, Giovanny; Zapata, Mireya; Pirrone, Vito; Dorta, Taho; Cambria, Salvatore; Marti, Albert; Krishnamourthy, Karthikeyan; Madrenas, Jordi

2018-01-01

Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. This has been achieved by using a special-purpose Processing Elements (PEs) for computing SNNs, and analyzing and customizing the instruction set according to the processing needs to achieve maximum performance with minimum resources. The parallel architecture is interfaced with customized Graphical User Interfaces (GUIs) to configure the SNN's connectivity, to compile the neuron-synapse model and to monitor SNN's activity. Our contribution intends to provide a tool that allows to prototype SNNs faster than on CPU/GPU architectures but significantly cheaper than fabricating a customized neuromorphic chip. This could be potentially valuable to the computational neuroscience and neuromorphic engineering communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing Embryos.

PubMed

Stegmaier, Johannes; Amat, Fernando; Lemon, William C; McDole, Katie; Wan, Yinan; Teodoro, George; Mikut, Ralf; Keller, Philipp J

2016-01-25

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55-330 times faster and 2-5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS. Copyright © 2016 Elsevier Inc. All rights reserved.

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE PAGES

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

2016-07-26

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

TaqMan Real-Time PCR Assays To Assess Arbuscular Mycorrhizal Responses to Field Manipulation of Grassland Biodiversity: Effects of Soil Characteristics, Plant Species Richness, and Functional Traits▿ †

PubMed Central

König, Stephan; Wubet, Tesfaye; Dormann, Carsten F.; Hempel, Stefan; Renker, Carsten; Buscot, François

2010-01-01

Large-scale (temporal and/or spatial) molecular investigations of the diversity and distribution of arbuscular mycorrhizal fungi (AMF) require considerable sampling efforts and high-throughput analysis. To facilitate such efforts, we have developed a TaqMan real-time PCR assay to detect and identify AMF in environmental samples. First, we screened the diversity in clone libraries, generated by nested PCR, of the nuclear ribosomal DNA internal transcribed spacer (ITS) of AMF in environmental samples. We then generated probes and forward primers based on the detected sequences, enabling AMF sequence type-specific detection in TaqMan multiplex real-time PCR assays. In comparisons to conventional clone library screening and Sanger sequencing, the TaqMan assay approach provided similar accuracy but higher sensitivity with cost and time savings. The TaqMan assays were applied to analyze the AMF community composition within plots of a large-scale plant biodiversity manipulation experiment, the Jena Experiment, primarily designed to investigate the interactive effects of plant biodiversity on element cycling and trophic interactions. The results show that environmental variables hierarchically shape AMF communities and that the sequence type spectrum is strongly affected by previous land use and disturbance, which appears to favor disturbance-tolerant members of the genus Glomus. The AMF species richness of disturbance-associated communities can be largely explained by richness of plant species and plant functional groups, while plant productivity and soil parameters appear to have only weak effects on the AMF community. PMID:20418424

Panoptes: web-based exploration of large scale genome variation data.

PubMed

Vauterin, Paul; Jeffery, Ben; Miles, Alistair; Amato, Roberto; Hart, Lee; Wright, Ian; Kwiatkowski, Dominic

2017-10-15

The size and complexity of modern large-scale genome variation studies demand novel approaches for exploring and sharing the data. In order to unlock the potential of these data for a broad audience of scientists with various areas of expertise, a unified exploration framework is required that is accessible, coherent and user-friendly. Panoptes is an open-source software framework for collaborative visual exploration of large-scale genome variation data and associated metadata in a web browser. It relies on technology choices that allow it to operate in near real-time on very large datasets. It can be used to browse rich, hybrid content in a coherent way, and offers interactive visual analytics approaches to assist the exploration. We illustrate its application using genome variation data of Anopheles gambiae, Plasmodium falciparum and Plasmodium vivax. Freely available at https://github.com/cggh/panoptes, under the GNU Affero General Public License. paul.vauterin@gmail.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Energy Spectral Behaviors of Communication Networks of Open-Source Communities

PubMed Central

Yang, Jianmei; Yang, Huijie; Liao, Hao; Wang, Jiangtao; Zeng, Jinqun

2015-01-01

Large-scale online collaborative production activities in open-source communities must be accompanied by large-scale communication activities. Nowadays, the production activities of open-source communities, especially their communication activities, have been more and more concerned. Take CodePlex C # community for example, this paper constructs the complex network models of 12 periods of communication structures of the community based on real data; then discusses the basic concepts of quantum mapping of complex networks, and points out that the purpose of the mapping is to study the structures of complex networks according to the idea of quantum mechanism in studying the structures of large molecules; finally, according to this idea, analyzes and compares the fractal features of the spectra in different quantum mappings of the networks, and concludes that there are multiple self-similarity and criticality in the communication structures of the community. In addition, this paper discusses the insights and application conditions of different quantum mappings in revealing the characteristics of the structures. The proposed quantum mapping method can also be applied to the structural studies of other large-scale organizations. PMID:26047331

Mahanaxar: quality of service guarantees in high-bandwidth, real-time streaming data storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bigelow, David; Bent, John; Chen, Hsing-Bung

2010-04-05

Large radio telescopes, cyber-security systems monitoring real-time network traffic, and others have specialized data storage needs: guaranteed capture of an ultra-high-bandwidth data stream, retention of the data long enough to determine what is 'interesting,' retention of interesting data indefinitely, and concurrent read/write access to determine what data is interesting, without interrupting the ongoing capture of incoming data. Mahanaxar addresses this problem. Mahanaxar guarantees streaming real-time data capture at (nearly) the full rate of the raw device, allows concurrent read and write access to the device on a best-effort basis without interrupting the data capture, and retains data as long asmore » possible given the available storage. It has built in mechanisms for reliability and indexing, can scale to meet arbitrary bandwidth requirements, and handles both small and large data elements equally well. Results from our prototype implementation shows that Mahanaxar provides both better guarantees and better performance than traditional file systems.« less

Multiple Streaming and the Probability Distribution of Density in Redshift Space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hui, Lam; Kofman, Lev; Shandarin, Sergei F.

2000-07-01

We examine several aspects of redshift distortions by expressing the redshift-space density in terms of the eigenvalues and orientation of the local Lagrangian deformation tensor. We explore the importance of multiple streaming using the Zeldovich approximation (ZA), and compute the average number of streams in both real and redshift space. We find that multiple streaming can be significant in redshift space but negligible in real space, even at moderate values of the linear fluctuation amplitude ({sigma}{sub l}(less-or-similar sign)1). Moreover, unlike their real-space counterparts, redshift-space multiple streams can flow past each other with minimal interactions. Such nonlinear redshift-space effects, which aremore » physically distinct from the fingers-of-God due to small-scale virialized motions, might in part explain the well-known departure of redshift distortions from the classic linear prediction by Kaiser, even at relatively large scales where the corresponding density field in real space is well described by linear perturbation theory. We also compute, using the ZA, the probability distribution function (PDF) of the density, as well as S{sub 3}, in real and redshift space, and compare it with the PDF measured from N-body simulations. The role of caustics in defining the character of the high-density tail is examined. We find that (non-Lagrangian) smoothing, due to both finite resolution or discreteness and small-scale velocity dispersions, is very effective in erasing caustic structures, unless the initial power spectrum is sufficiently truncated. (c) 2000 The American Astronomical Society.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pratapa, Phanisri P.; Suryanarayana, Phanish; Pask, John E.

We present the Clenshaw–Curtis Spectral Quadrature (SQ) method for real-space O(N) Density Functional Theory (DFT) calculations. In this approach, all quantities of interest are expressed as bilinear forms or sums over bilinear forms, which are then approximated by spatially localized Clenshaw–Curtis quadrature rules. This technique is identically applicable to both insulating and metallic systems, and in conjunction with local reformulation of the electrostatics, enables the O(N) evaluation of the electronic density, energy, and atomic forces. The SQ approach also permits infinite-cell calculations without recourse to Brillouin zone integration or large supercells. We employ a finite difference representation in order tomore » exploit the locality of electronic interactions in real space, enable systematic convergence, and facilitate large-scale parallel implementation. In particular, we derive expressions for the electronic density, total energy, and atomic forces that can be evaluated in O(N) operations. We demonstrate the systematic convergence of energies and forces with respect to quadrature order as well as truncation radius to the exact diagonalization result. In addition, we show convergence with respect to mesh size to established O(N 3) planewave results. In conclusion, we establish the efficiency of the proposed approach for high temperature calculations and discuss its particular suitability for large-scale parallel computation.« less

Spectral Quadrature method for accurate O ( N ) electronic structure calculations of metals and insulators

DOE PAGES

Pratapa, Phanisri P.; Suryanarayana, Phanish; Pask, John E.

2015-12-02

We present the Clenshaw–Curtis Spectral Quadrature (SQ) method for real-space O(N) Density Functional Theory (DFT) calculations. In this approach, all quantities of interest are expressed as bilinear forms or sums over bilinear forms, which are then approximated by spatially localized Clenshaw–Curtis quadrature rules. This technique is identically applicable to both insulating and metallic systems, and in conjunction with local reformulation of the electrostatics, enables the O(N) evaluation of the electronic density, energy, and atomic forces. The SQ approach also permits infinite-cell calculations without recourse to Brillouin zone integration or large supercells. We employ a finite difference representation in order tomore » exploit the locality of electronic interactions in real space, enable systematic convergence, and facilitate large-scale parallel implementation. In particular, we derive expressions for the electronic density, total energy, and atomic forces that can be evaluated in O(N) operations. We demonstrate the systematic convergence of energies and forces with respect to quadrature order as well as truncation radius to the exact diagonalization result. In addition, we show convergence with respect to mesh size to established O(N 3) planewave results. In conclusion, we establish the efficiency of the proposed approach for high temperature calculations and discuss its particular suitability for large-scale parallel computation.« less

Real-Time Large-Scale Dense Mapping with Surfels

PubMed Central

Fu, Xingyin; Zhu, Feng; Wu, Qingxiao; Sun, Yunlei; Lu, Rongrong; Yang, Ruigang

2018-01-01

Real-time dense mapping systems have been developed since the birth of consumer RGB-D cameras. Currently, there are two commonly used models in dense mapping systems: truncated signed distance function (TSDF) and surfel. The state-of-the-art dense mapping systems usually work fine with small-sized regions. The generated dense surface may be unsatisfactory around the loop closures when the system tracking drift grows large. In addition, the efficiency of the system with surfel model slows down when the number of the model points in the map becomes large. In this paper, we propose to use two maps in the dense mapping system. The RGB-D images are integrated into a local surfel map. The old surfels that reconstructed in former times and far away from the camera frustum are moved from the local map to the global map. The updated surfels in the local map when every frame arrives are kept bounded. Therefore, in our system, the scene that can be reconstructed is very large, and the frame rate of our system remains high. We detect loop closures and optimize the pose graph to distribute system tracking drift. The positions and normals of the surfels in the map are also corrected using an embedded deformation graph so that they are consistent with the updated poses. In order to deal with large surface deformations, we propose a new method for constructing constraints with system trajectories and loop closure keyframes. The proposed new method stabilizes large-scale surface deformation. Experimental results show that our novel system behaves better than the prior state-of-the-art dense mapping systems. PMID:29747450

Utilizing Maximal Independent Sets as Dominating Sets in Scale-Free Networks

NASA Astrophysics Data System (ADS)

Derzsy, N.; Molnar, F., Jr.; Szymanski, B. K.; Korniss, G.

Dominating sets provide key solution to various critical problems in networked systems, such as detecting, monitoring, or controlling the behavior of nodes. Motivated by graph theory literature [Erdos, Israel J. Math. 4, 233 (1966)], we studied maximal independent sets (MIS) as dominating sets in scale-free networks. We investigated the scaling behavior of the size of MIS in artificial scale-free networks with respect to multiple topological properties (size, average degree, power-law exponent, assortativity), evaluated its resilience to network damage resulting from random failure or targeted attack [Molnar et al., Sci. Rep. 5, 8321 (2015)], and compared its efficiency to previously proposed dominating set selection strategies. We showed that, despite its small set size, MIS provides very high resilience against network damage. Using extensive numerical analysis on both synthetic and real-world (social, biological, technological) network samples, we demonstrate that our method effectively satisfies four essential requirements of dominating sets for their practical applicability on large-scale real-world systems: 1.) small set size, 2.) minimal network information required for their construction scheme, 3.) fast and easy computational implementation, and 4.) resiliency to network damage. Supported by DARPA, DTRA, and NSF.

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Gu, Guojun; Nelkin, Eric J.; Bowman, Kenneth P.; Stocker, Erich; Wolff, David B.

2006-01-01

The TRMM Multi-satellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining multiple precipitation estimates from satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3-hourly). It is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The data set covers the latitude band 50 degrees N-S for the period 1998 to the delayed present. Early validation results are as follows: The TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate dependent low bias due to lack of sensitivity to low precipitation rates in one of the input products (based on AMSU-B). At finer scales the TMPA is successful at approximately reproducing the surface-observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other fine-scale estimators. Examples are provided of a flood event and diurnal cycle determination.

Evaluating large-scale propensity score performance through real-world and synthetic data experiments.

PubMed

Tian, Yuxi; Schuemie, Martijn J; Suchard, Marc A

2018-06-22

Propensity score adjustment is a popular approach for confounding control in observational studies. Reliable frameworks are needed to determine relative propensity score performance in large-scale studies, and to establish optimal propensity score model selection methods. We detail a propensity score evaluation framework that includes synthetic and real-world data experiments. Our synthetic experimental design extends the 'plasmode' framework and simulates survival data under known effect sizes, and our real-world experiments use a set of negative control outcomes with presumed null effect sizes. In reproductions of two published cohort studies, we compare two propensity score estimation methods that contrast in their model selection approach: L1-regularized regression that conducts a penalized likelihood regression, and the 'high-dimensional propensity score' (hdPS) that employs a univariate covariate screen. We evaluate methods on a range of outcome-dependent and outcome-independent metrics. L1-regularization propensity score methods achieve superior model fit, covariate balance and negative control bias reduction compared with the hdPS. Simulation results are mixed and fluctuate with simulation parameters, revealing a limitation of simulation under the proportional hazards framework. Including regularization with the hdPS reduces commonly reported non-convergence issues but has little effect on propensity score performance. L1-regularization incorporates all covariates simultaneously into the propensity score model and offers propensity score performance superior to the hdPS marginal screen.

Intensity of Territorial Marking Predicts Wolf Reproduction: Implications for Wolf Monitoring

PubMed Central

García, Emilio J.

2014-01-01

Background The implementation of intensive and complex approaches to monitor large carnivores is resource demanding, restricted to endangered species, small populations, or small distribution ranges. Wolf monitoring over large spatial scales is difficult, but the management of such contentious species requires regular estimations of abundance to guide decision-makers. The integration of wolf marking behaviour with simple sign counts may offer a cost-effective alternative to monitor the status of wolf populations over large spatial scales. Methodology/Principal Findings We used a multi-sampling approach, based on the collection of visual and scent wolf marks (faeces and ground scratching) and the assessment of wolf reproduction using howling and observation points, to test whether the intensity of marking behaviour around the pup-rearing period (summer-autumn) could reflect wolf reproduction. Between 1994 and 2007 we collected 1,964 wolf marks in a total of 1,877 km surveyed and we searched for the pups' presence (1,497 howling and 307 observations points) in 42 sampling sites with a regular presence of wolves (120 sampling sites/year). The number of wolf marks was ca. 3 times higher in sites with a confirmed presence of pups (20.3 vs. 7.2 marks). We found a significant relationship between the number of wolf marks (mean and maximum relative abundance index) and the probability of wolf reproduction. Conclusions/Significance This research establishes a real-time relationship between the intensity of wolf marking behaviour and wolf reproduction. We suggest a conservative cutting point of 0.60 for the probability of wolf reproduction to monitor wolves on a regional scale combined with the use of the mean relative abundance index of wolf marks in a given area. We show how the integration of wolf behaviour with simple sampling procedures permit rapid, real-time, and cost-effective assessments of the breeding status of wolf packs with substantial implications to monitor wolves at large spatial scales. PMID:24663068

Exploring network operations for data and information networks

NASA Astrophysics Data System (ADS)

Yao, Bing; Su, Jing; Ma, Fei; Wang, Xiaomin; Zhao, Xiyang; Yao, Ming

2017-01-01

Barabási and Albert, in 1999, formulated scale-free models based on some real networks: World-Wide Web, Internet, metabolic and protein networks, language or sexual networks. Scale-free networks not only appear around us, but also have high qualities in the world. As known, high quality information networks can transfer feasibly and efficiently data, clearly, their topological structures are very important for data safety. We build up network operations for constructing large scale of dynamic networks from smaller scale of network models having good property and high quality. We focus on the simplest operators to formulate complex operations, and are interesting on the closeness of operations to desired network properties.

Environmentally induced amplitude death and firing provocation in large-scale networks of neuronal systems

NASA Astrophysics Data System (ADS)

Pankratova, Evgeniya V.; Kalyakulina, Alena I.

2016-12-01

We study the dynamics of multielement neuronal systems taking into account both the direct interaction between the cells via linear coupling and nondiffusive cell-to-cell communication via common environment. For the cells exhibiting individual bursting behavior, we have revealed the dependence of the network activity on its scale. Particularly, we show that small-scale networks demonstrate the inability to maintain complicated oscillations: for a small number of elements in an ensemble, the phenomenon of amplitude death is observed. The existence of threshold network scales and mechanisms causing firing in artificial and real multielement neural networks, as well as their significance for biological applications, are discussed.

Omega from the anisotropy of the redshift correlation function

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.

1993-01-01

Peculiar velocities distort the correlation function of galaxies observed in redshift space. In the large scale, linear regime, the distortion takes a characteristic quadrupole plus hexadecapole form, with the amplitude of the distortion depending on the cosmological density parameter omega. Preliminary measurements are reported here of the harmonics of the correlation function in the CfA, SSRS, and IRAS 2 Jansky redshift surveys. The observed behavior of the harmonics agrees qualitatively with the predictions of linear theory on large scales in every survey. However, real anisotropy in the galaxy distribution induces large fluctuations in samples which do not yet probe a sufficiently fair volume of the Universe. In the CfA 14.5 sample in particular, the Great Wall induces a large negative quadrupole, which taken at face value implies an unrealistically large omega 20. The IRAS 2 Jy survey, which covers a substantially larger volume than the optical surveys and is less affected by fingers-of-god, yields a more reliable and believable value, omega = 0.5 sup +.5 sub -.25.

Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

PubMed

Demirkus, Meltem; Precup, Doina; Clark, James J; Arbel, Tal

2016-06-01

Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

Large Eddy Simulation of Flame-Turbulence Interactions in a LOX-CH4 Shear Coaxial Injector

DTIC Science & Technology

2012-01-01

heat transfer from dense to light fluids.A previous study on LOX/H2 flames39,40 have pointed the limitations of central scheme to predict such large...pp. 151–169. 39Masquelet, M., Simulations of a Sub-scale Liquid Rocket Engine: Transient Heat Transfer in a Real Gas Environment , Master’s thesis...Eddy Simulation of a cryogenic flame issued from a LOX-CH4 shear coaxial injector. The operating pressure is above the critical pressure for both

The role of ocean climate data in operational Naval oceanography

NASA Technical Reports Server (NTRS)

Chesbrough, Radm G.

1992-01-01

Local application of global-scale models describes the U.S. Navy's basic philosophy for operational oceanography in support of fleet operations. Real-time data, climatologies, coupled air/ocean models, and large scale computers are the essential components of the Navy's system for providing the war fighters with the performance predictions and tactical decision aids they need to operate safely and efficiently. In peacetime, these oceanographic predictions are important for safety of navigation and flight. The paucity and uneven distribution of real-time data mean we have to fall back on climatology to provide the basic data to operate our models. The Navy is both a producer and user of climatologies; it provides observations to the national archives and in turn employs data from these archives to establish data bases. Suggestions for future improvements to ocean climate data are offered.

Applicability of Taylor's hypothesis in thermally driven turbulence

PubMed Central

Verma, Mahendra K.

2018-01-01

In this paper, we show that, in the presence of large-scale circulation (LSC), Taylor’s hypothesis can be invoked to deduce the energy spectrum in thermal convection using real-space probes, a popular experimental tool. We perform numerical simulation of turbulent convection in a cube and observe that the velocity field follows Kolmogorov’s spectrum (k−5/3). We also record the velocity time series using real-space probes near the lateral walls. The corresponding frequency spectrum exhibits Kolmogorov’s spectrum (f−5/3), thus validating Taylor’s hypothesis with the steady LSC playing the role of a mean velocity field. The aforementioned findings based on real-space probes provide valuable inputs for experimental measurements used for studying the spectrum of convective turbulence. PMID:29765668

Applicability of Taylor's hypothesis in thermally driven turbulence

NASA Astrophysics Data System (ADS)

Kumar, Abhishek; Verma, Mahendra K.

2018-04-01

In this paper, we show that, in the presence of large-scale circulation (LSC), Taylor's hypothesis can be invoked to deduce the energy spectrum in thermal convection using real-space probes, a popular experimental tool. We perform numerical simulation of turbulent convection in a cube and observe that the velocity field follows Kolmogorov's spectrum (k-5/3). We also record the velocity time series using real-space probes near the lateral walls. The corresponding frequency spectrum exhibits Kolmogorov's spectrum (f-5/3), thus validating Taylor's hypothesis with the steady LSC playing the role of a mean velocity field. The aforementioned findings based on real-space probes provide valuable inputs for experimental measurements used for studying the spectrum of convective turbulence.

Real-time micro-modelling of city evacuations

NASA Astrophysics Data System (ADS)

Löhner, Rainald; Haug, Eberhard; Zinggerling, Claudio; Oñate, Eugenio

2018-01-01

A methodology to integrate geographical information system (GIS) data with large-scale pedestrian simulations has been developed. Advances in automatic data acquisition and archiving from GIS databases, automatic input for pedestrian simulations, as well as scalable pedestrian simulation tools have made it possible to simulate pedestrians at the individual level for complete cities in real time. An example that simulates the evacuation of the city of Barcelona demonstrates that this is now possible. This is the first step towards a fully integrated crowd prediction and management tool that takes into account not only data gathered in real time from cameras, cell phones or other sensors, but also merges these with advanced simulation tools to predict the future state of the crowd.

Conjugate-Gradient Algorithms For Dynamics Of Manipulators

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1993-01-01

Algorithms for serial and parallel computation of forward dynamics of multiple-link robotic manipulators by conjugate-gradient method developed. Parallel algorithms have potential for speedup of computations on multiple linked, specialized processors implemented in very-large-scale integrated circuits. Such processors used to stimulate dynamics, possibly faster than in real time, for purposes of planning and control.

Institutionalizing Large-Scale Curricular Change: The Top 25 Project at Miami University

ERIC Educational Resources Information Center

Hodge, David C.; Nadler, Marjorie Keeshan; Shore, Cecilia; Taylor, Beverley A. P.

2011-01-01

Now more than ever, it is urgent that colleges and universities mobilize themselves to produce graduates who are capable of being productive, creative, and responsible members of a global society. Employers want clear communicators who are strong critical thinkers and who can solve real-world problems in an ethical way. To achieve these outcomes,…

Embedded Electro-Optic Sensor Network for the On-Site Calibration and Real-Time Performance Monitoring of Large-Scale Phased Arrays

DTIC Science & Technology

2005-07-09

This final report summarizes the progress during the Phase I SBIR project entitled Embedded Electro - Optic Sensor Network for the On-Site Calibration...network based on an electro - optic field-detection technique (the Electro - optic Sensor Network, or ESN) for the performance evaluation of phased

Improving Real World Performance of Vision Aided Navigation in a Flight Environment

DTIC Science & Technology

2016-09-15

Introduction . . . . . . . 63 4.2 Wide Area Search Extent . . . . . . . . . . . . . . . . . 64 4.3 Large-Scale Image Navigation Histogram Filter ...65 4.3.1 Location Model . . . . . . . . . . . . . . . . . . 66 4.3.2 Measurement Model . . . . . . . . . . . . . . . 66 4.3.3 Histogram Filter ...Iteration of Histogram Filter . . . . . . . . . . . 70 4.4 Implementation and Flight Test Campaign . . . . . . . . 71 4.4.1 Software Implementation

System and Method for Dynamic Aeroelastic Control

NASA Technical Reports Server (NTRS)

Suh, Peter M. (Inventor)

2015-01-01

The present invention proposes a hardware and software architecture for dynamic modal structural monitoring that uses a robust modal filter to monitor a potentially very large-scale array of sensors in real time, and tolerant of asymmetric sensor noise and sensor failures, to achieve aircraft performance optimization such as minimizing aircraft flutter, drag and maximizing fuel efficiency.

From Chebyshev to Bernstein: A Tour of Polynomials Small and Large

ERIC Educational Resources Information Center

Boelkins, Matthew; Miller, Jennifer; Vugteveen, Benjamin

2006-01-01

Consider the family of monic polynomials of degree n having zeros at -1 and +1 and all their other real zeros in between these two values. This article explores the size of these polynomials using the supremum of the absolute value on [-1, 1], showing that scaled Chebyshev and Bernstein polynomials give the extremes.

Toward server-side, high performance climate change data analytics in the Earth System Grid Federation (ESGF) eco-system

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Williams, Dean; Aloisio, Giovanni

2016-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated (e.g., the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Most of the tools currently available for scientific data analysis in the climate domain fail at large scale since they: (1) are desktop based and need the data locally; (2) are sequential, so do not benefit from available multicore/parallel machines; (3) do not provide declarative languages to express scientific data analysis tasks; (4) are domain-specific, which ties their adoption to a specific domain; and (5) do not provide a workflow support, to enable the definition of complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes ("datacubes"). The project relies on a strong background of high performance database management and OLAP systems to manage large scientific data sets. It also provides a native workflow management support, to define processing chains and workflows with tens to hundreds of data analytics operators to build real scientific use cases. With regard to interoperability aspects, the talk will present the contribution provided both to the RDA Working Group on Array Databases, and the Earth System Grid Federation (ESGF) Compute Working Team. Also highlighted will be the results of large scale climate model intercomparison data analysis experiments, for example: (1) defined in the context of the EU H2020 INDIGO-DataCloud project; (2) implemented in a real geographically distributed environment involving CMCC (Italy) and LLNL (US) sites; (3) exploiting Ophidia as server-side, parallel analytics engine; and (4) applied on real CMIP5 data sets available through ESGF.

Multi-scale Visualization of Molecular Architecture Using Real-Time Ambient Occlusion in Sculptor.

PubMed

Wahle, Manuel; Wriggers, Willy

2015-10-01

The modeling of large biomolecular assemblies relies on an efficient rendering of their hierarchical architecture across a wide range of spatial level of detail. We describe a paradigm shift currently under way in computer graphics towards the use of more realistic global illumination models, and we apply the so-called ambient occlusion approach to our open-source multi-scale modeling program, Sculptor. While there are many other higher quality global illumination approaches going all the way up to full GPU-accelerated ray tracing, they do not provide size-specificity of the features they shade. Ambient occlusion is an aspect of global lighting that offers great visual benefits and powerful user customization. By estimating how other molecular shape features affect the reception of light at some surface point, it effectively simulates indirect shadowing. This effect occurs between molecular surfaces that are close to each other, or in pockets such as protein or ligand binding sites. By adding ambient occlusion, large macromolecular systems look much more natural, and the perception of characteristic surface features is strongly enhanced. In this work, we present a real-time implementation of screen space ambient occlusion that delivers realistic cues about tunable spatial scale characteristics of macromolecular architecture. Heretofore, the visualization of large biomolecular systems, comprising e.g. hundreds of thousands of atoms or Mega-Dalton size electron microscopy maps, did not take into account the length scales of interest or the spatial resolution of the data. Our approach has been uniquely customized with shading that is tuned for pockets and cavities of a user-defined size, making it useful for visualizing molecular features at multiple scales of interest. This is a feature that none of the conventional ambient occlusion approaches provide. Actual Sculptor screen shots illustrate how our implementation supports the size-dependent rendering of molecular surface features.

Digital CODEC for real-time processing of broadcast quality video signals at 1.8 bits/pixel

NASA Technical Reports Server (NTRS)

Shalkhauser, Mary JO; Whyte, Wayne A., Jr.

1989-01-01

Advances in very large-scale integration and recent work in the field of bandwidth efficient digital modulation techniques have combined to make digital video processing technically feasible and potentially cost competitive for broadcast quality television transmission. A hardware implementation was developed for a DPCM-based digital television bandwidth compression algorithm which processes standard NTSC composite color television signals and produces broadcast quality video in real time at an average of 1.8 bits/pixel. The data compression algorithm and the hardware implementation of the CODEC are described, and performance results are provided.

Digital CODEC for real-time processing of broadcast quality video signals at 1.8 bits/pixel

NASA Technical Reports Server (NTRS)

Shalkhauser, Mary JO; Whyte, Wayne A.

1991-01-01

Advances in very large scale integration and recent work in the field of bandwidth efficient digital modulation techniques have combined to make digital video processing technically feasible an potentially cost competitive for broadcast quality television transmission. A hardware implementation was developed for DPCM (differential pulse code midulation)-based digital television bandwidth compression algorithm which processes standard NTSC composite color television signals and produces broadcast quality video in real time at an average of 1.8 bits/pixel. The data compression algorithm and the hardware implementation of the codec are described, and performance results are provided.

Large Terrain Modeling and Visualization for Planets

NASA Technical Reports Server (NTRS)

Myint, Steven; Jain, Abhinandan; Cameron, Jonathan; Lim, Christopher

2011-01-01

Physics-based simulations are actively used in the design, testing, and operations phases of surface and near-surface planetary space missions. One of the challenges in realtime simulations is the ability to handle large multi-resolution terrain data sets within models as well as for visualization. In this paper, we describe special techniques that we have developed for visualization, paging, and data storage for dealing with these large data sets. The visualization technique uses a real-time GPU-based continuous level-of-detail technique that delivers multiple frames a second performance even for planetary scale terrain model sizes.

Non-negative Tensor Factorization for Robust Exploratory Big-Data Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexandrov, Boian; Vesselinov, Velimir Valentinov; Djidjev, Hristo Nikolov

Currently, large multidimensional datasets are being accumulated in almost every field. Data are: (1) collected by distributed sensor networks in real-time all over the globe, (2) produced by large-scale experimental measurements or engineering activities, (3) generated by high-performance simulations, and (4) gathered by electronic communications and socialnetwork activities, etc. Simultaneous analysis of these ultra-large heterogeneous multidimensional datasets is often critical for scientific discoveries, decision-making, emergency response, and national and global security. The importance of such analyses mandates the development of the next-generation of robust machine learning (ML) methods and tools for bigdata exploratory analysis.

Resolving the Circumstellar Environment of the Galactic B[e] Supergiant Star MWC 137 from Large to Small Scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kraus, Michaela; Nickeler, Dieter H.; Liimets, Tiina

The Galactic object MWC 137 has been suggested to belong to the group of B[e] supergiants. However, with its large-scale optical bipolar ring nebula and high-velocity jet and knots, it is a rather atypical representative of this class. We performed multiwavelength observations spreading from the optical to the radio regimes. Based on optical imaging and long-slit spectroscopic data, we found that the northern parts of the large-scale nebula are predominantly blueshifted, while the southern regions appear mostly redshifted. We developed a geometrical model consisting of two double cones. Although various observational features can be approximated with such a scenario, themore » observed velocity pattern is more complex. Using near-infrared integral-field unit spectroscopy, we studied the hot molecular gas in the vicinity of the star. The emission from the hot CO gas arises in a small-scale disk revolving around the star on Keplerian orbits. Although the disk itself cannot be spatially resolved, its emission is reflected by the dust arranged in arc-like structures and the clumps surrounding MWC 137 on small scales. In the radio regime, we mapped the cold molecular gas in the outskirts of the optical nebula. We found that large amounts of cool molecular gas and warm dust embrace the optical nebula in the east, south, and west. No cold gas or dust was detected in the north and northwestern regions. Despite the new insights into the nebula kinematics gained from our studies, the real formation scenario of the large-scale nebula remains an open issue.« less

The Newport Button: The Large Scale Replication Of Combined Three-And Two-Dimensional Holographic Images

NASA Astrophysics Data System (ADS)

Cowan, James J.

1984-05-01

A unique type of holographic imagery and its large scale replication are described. The "Newport Button", which was designed as an advertising premium item for the Newport Corporation, incorporates a complex overlay of holographic diffraction gratings surrounding a three-dimensional holographic image of a real object. The combined pattern is recorded onto a photosensitive medium from which a metal master is made. The master is subsequently used to repeatedly emboss the pattern into a thin plastic sheet. Individual patterns are then die cut from the metallized plastic and mounted onto buttons. A discussion is given of the diffraction efficiencies of holograms made in this particular fashion and of the special requirements of the replication process.

Computational solutions to large-scale data management and analysis

PubMed Central

Schadt, Eric E.; Linderman, Michael D.; Sorenson, Jon; Lee, Lawrence; Nolan, Garry P.

2011-01-01

Today we can generate hundreds of gigabases of DNA and RNA sequencing data in a week for less than US$5,000. The astonishing rate of data generation by these low-cost, high-throughput technologies in genomics is being matched by that of other technologies, such as real-time imaging and mass spectrometry-based flow cytometry. Success in the life sciences will depend on our ability to properly interpret the large-scale, high-dimensional data sets that are generated by these technologies, which in turn requires us to adopt advances in informatics. Here we discuss how we can master the different types of computational environments that exist — such as cloud and heterogeneous computing — to successfully tackle our big data problems. PMID:20717155

Towards Online Multiresolution Community Detection in Large-Scale Networks

PubMed Central

Huang, Jianbin; Sun, Heli; Liu, Yaguang; Song, Qinbao; Weninger, Tim

2011-01-01

The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks. PMID:21887325

Laser prospects for SPS and restoration of the ozone layer

NASA Technical Reports Server (NTRS)

Kruzhilin, Yuri

1992-01-01

Large-scale applications of high-power lasers are considered (special experiments are described to confirm the feasibility of these applications) to achieve also large-scale environmental advantages. The possibility of producing electric energy by Laser-Solar Power Satellites in the near future is discussed. A full-scale experimental L-SPS satellite is suggested as a module of a global space energy network. Electric power of about 10 MW at the surface of the Earth is achievable as a result of energy conversion of laser radiation. L-SPS is based on the greatest advantages of present optics and laser techniques. Specialized-scale experiments are carried out and described. L-SPS project could provide real electricity for consumers not later than by highly developed fusion techniques, and the environmental aftereffects are quite favorable. A new method of power supply for satellites is suggested, based on the connection of an on-board electric circuit directly with the ground-based power grid by means of laser beams.

Effectiveness and tolerability of second-line therapy with vildagliptin vs. other oral agents in type 2 diabetes: A real-life worldwide observational study (EDGE)

PubMed Central

Mathieu, C; Barnett, A H; Brath, H; Conget, I; de Castro, J J; Göke, R; Márquez Rodriguez, E; Nilsson, P M; Pagkalos, E; Penfornis, A; Schaper, NC; Wangnoo, S K; Kothny, W; Bader, G

2013-01-01

Aim Real-life studies are needed to confirm the clinical relevance of findings from randomised controlled trials (RCTs). This study aimed to assess the effectiveness and tolerability of vildagliptin add-on vs. other oral antihyperglycaemic drugs (OADs) added to OAD monotherapy in a real-life setting, and to explore the advantages and limitations of large-scale ‘pragmatic’ trials. Methods EDGE was a prospective, 1-year, worldwide, real-life observational study in which 2957 physicians reported on the effects of second-line OADs in 45,868 patients with T2DM not reaching glycaemic targets with monotherapy. Physicians could add any OAD, and patients entered either vildagliptin or (pooled) comparator cohort. The primary effectiveness and tolerability end-point (PEP) evaluated proportions of patients decreasing HbA1c > 0.3%, without hypoglycaemia, weight gain, peripheral oedema or gastrointestinal side effects. The most clinically relevant secondary end-point (SEP 3) was attainment of end-point HbA1c < 7% without hypoglycaemia or ≥ 3% increase in body weight. Results In this large group of T2DM patients, a second OAD was added at mean HbA1c of 8.2 ± 1.3%, with no baseline HbA1c difference between cohorts. Second-line OAD therapy attained the PEP in the majority of patients, with higher attainment in those prescribed a vildagliptin-based regimen. The adjusted odds ratio was 1.49 (95% CI: 1.42, 1.55; p < 0.001). In patients with baseline HbA1c ≥ 7%, SEP 3 was achieved by 35% of patients on a vildagliptin-based combination and by 23% of those receiving comparator combinations. The adjusted odds ratio was 1.96 (95% CI: 1.85, 2.07; p < 0.001). Safety events were reported infrequently and safety profiles of vildagliptin and other OADs were consistent with previous data. Conclusion EDGE demonstrates that in a ‘real-life’ setting, vildagliptin as second OAD can lower HbA1c to target without well-recognised OAD side effects, more frequently than comparator OADs. In addition, EDGE illustrates that conducting large-scale, prospective, real-life studies poses challenges but yields valuable clinical information complementary to RCTs. PMID:23961850

A large-scale initiative to disseminate an evidence-based drug abuse prevention program in Italy: Lessons learned for practitioners and researchers.

PubMed

Velasco, Veronica; Griffin, Kenneth W; Antichi, Mariella; Celata, Corrado

2015-10-01

Across developed countries, experimentation with alcohol, tobacco, and other drugs often begins in the early adolescent years. Several evidence-based programs have been developed to prevent adolescent substance use. Many of the most rigorously tested and empirically supported prevention programs were initially developed and tested in the United States. Increasingly, these interventions are being adopted for use in Europe and throughout the world. This paper reports on a large-scale comprehensive initiative designed to select, adapt, implement, and sustain an evidence-based drug abuse prevention program in Italy. As part of a large-scale regionally funded collaboration in the Lombardy region of Italy, we report on processes through which a team of stakeholders selected, translated and culturally adapted, planned, implemented and evaluated the Life Skills Training (LST) school-based drug abuse prevention program, an evidence-based intervention developed in the United States. We discuss several challenges and lessons learned and implications for prevention practitioners and researchers attempting to undertake similar international dissemination projects. We review several published conceptual models designed to promote the replication and widespread dissemination of effective programs, and discuss their strengths and limitations in the context of planning and implementing a complex, large-scale real-world dissemination effort. Copyright © 2015 Elsevier Ltd. All rights reserved.

Active Self-Testing Noise Measurement Sensors for Large-Scale Environmental Sensor Networks

PubMed Central

Domínguez, Federico; Cuong, Nguyen The; Reinoso, Felipe; Touhafi, Abdellah; Steenhaut, Kris

2013-01-01

Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10. PMID:24351634

Wayfinding in Social Networks

NASA Astrophysics Data System (ADS)

Liben-Nowell, David

With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon - the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends - and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.

New methods for state estimation and adaptive observation of environmental flow systems leveraging coordinated swarms of sensor vehicles

NASA Astrophysics Data System (ADS)

Bewley, Thomas

2015-11-01

Accurate long-term forecasts of the path and intensity of hurricanes are imperative to protect property and save lives. Accurate estimations and forecasts of the spread of large-scale contaminant plumes, such as those from Deepwater Horizon, Fukushima, and recent volcanic eruptions in Iceland, are essential for assessing environment impact, coordinating remediation efforts, and in certain cases moving folks out of harm's way. The challenges in estimating and forecasting such systems include: (a) environmental flow modeling, (b) high-performance real-time computing, (c) assimilating measured data into numerical simulations, and (d) acquiring in-situ data, beyond what can be measured from satellites, that is maximally relevant for reducing forecast uncertainty. This talk will focus on new techniques for addressing (c) and (d), namely, data assimilation and adaptive observation, in both hurricanes and large-scale environmental plumes. In particular, we will present a new technique for the energy-efficient coordination of swarms of sensor-laden balloons for persistent, in-situ, distributed, real-time measurement of developing hurricanes, leveraging buoyancy control only (coupled with the predictable and strongly stratified flowfield within the hurricane). Animations of these results are available at http://flowcontrol.ucsd.edu/3dhurricane.mp4 and http://flowcontrol.ucsd.edu/katrina.mp4. We also will survey our unique hybridization of the venerable Ensemble Kalman and Variational approaches to large-scale data assimilation in environmental flow systems, and how essentially the dual of this hybrid approach may be used to solve the adaptive observation problem in a uniquely effective and rigorous fashion.

Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree

NASA Astrophysics Data System (ADS)

Chen, Qiyu; Liu, Gang; Ma, Xiaogang; Mariethoz, Gregoire; He, Zhenwen; Tian, Yiping; Weng, Zhengping

2018-05-01

Large scale 3D digital terrain modeling is a crucial part of many real-time applications in geoinformatics. In recent years, the improved speed and precision in spatial data collection make the original terrain data more complex and bigger, which poses challenges for data management, visualization and analysis. In this work, we presented an effective and comprehensive 3D terrain representation based on local curvature entropy and a dynamic Quadtree. The Level-of-detail (LOD) models of significant terrain features were employed to generate hierarchical terrain surfaces. In order to reduce the radical changes of grid density between adjacent LODs, local entropy of terrain curvature was regarded as a measure of subdividing terrain grid cells. Then, an efficient approach was presented to eliminate the cracks among the different LODs by directly updating the Quadtree due to an edge-based structure proposed in this work. Furthermore, we utilized a threshold of local entropy stored in each parent node of this Quadtree to flexibly control the depth of the Quadtree and dynamically schedule large-scale LOD terrain. Several experiments were implemented to test the performance of the proposed method. The results demonstrate that our method can be applied to construct LOD 3D terrain models with good performance in terms of computational cost and the maintenance of terrain features. Our method has already been deployed in a geographic information system (GIS) for practical uses, and it is able to support the real-time dynamic scheduling of large scale terrain models more easily and efficiently.

Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data.

PubMed

Ibrahim, Mohamed; Wickenhauser, Patrick; Rautek, Peter; Reina, Guido; Hadwiger, Markus

2018-01-01

Molecular dynamics (MD) simulations are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulations with 10 million particles or more, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry. Excessive super-sampling can alleviate this problem, but is prohibitively expensive. This paper presents a novel visualization method for large-scale particle data that addresses aliasing while enabling interactive high-quality rendering. We introduce the novel concept of screen-space normal distribution functions (S-NDFs) for particle data. S-NDFs represent the distribution of surface normals that map to a given pixel in screen space, which enables high-quality re-lighting without re-rendering particles. In order to facilitate interactive zooming, we cache S-NDFs in a screen-space mipmap (S-MIP). Together, these two concepts enable interactive, scale-consistent re-lighting and shading changes, as well as zooming, without having to re-sample the particle data. We show how our method facilitates the interactive exploration of real-world large-scale MD simulation data in different scenarios.

The up-scaling of ecosystem functions in a heterogeneous world

NASA Astrophysics Data System (ADS)

Lohrer, Andrew M.; Thrush, Simon F.; Hewitt, Judi E.; Kraan, Casper

2015-05-01

Earth is in the midst of a biodiversity crisis that is impacting the functioning of ecosystems and the delivery of valued goods and services. However, the implications of large scale species losses are often inferred from small scale ecosystem functioning experiments with little knowledge of how the dominant drivers of functioning shift across scales. Here, by integrating observational and manipulative experimental field data, we reveal scale-dependent influences on primary productivity in shallow marine habitats, thus demonstrating the scalability of complex ecological relationships contributing to coastal marine ecosystem functioning. Positive effects of key consumers (burrowing urchins, Echinocardium cordatum) on seafloor net primary productivity (NPP) elucidated by short-term, single-site experiments persisted across multiple sites and years. Additional experimentation illustrated how these effects amplified over time, resulting in greater primary producer biomass sediment chlorophyll a content (Chla) in the longer term, depending on climatic context and habitat factors affecting the strengths of mutually reinforcing feedbacks. The remarkable coherence of results from small and large scales is evidence of real-world ecosystem function scalability and ecological self-organisation. This discovery provides greater insights into the range of responses to broad-scale anthropogenic stressors in naturally heterogeneous environmental settings.

The up-scaling of ecosystem functions in a heterogeneous world

PubMed Central

Lohrer, Andrew M.; Thrush, Simon F.; Hewitt, Judi E.; Kraan, Casper

2015-01-01

Earth is in the midst of a biodiversity crisis that is impacting the functioning of ecosystems and the delivery of valued goods and services. However, the implications of large scale species losses are often inferred from small scale ecosystem functioning experiments with little knowledge of how the dominant drivers of functioning shift across scales. Here, by integrating observational and manipulative experimental field data, we reveal scale-dependent influences on primary productivity in shallow marine habitats, thus demonstrating the scalability of complex ecological relationships contributing to coastal marine ecosystem functioning. Positive effects of key consumers (burrowing urchins, Echinocardium cordatum) on seafloor net primary productivity (NPP) elucidated by short-term, single-site experiments persisted across multiple sites and years. Additional experimentation illustrated how these effects amplified over time, resulting in greater primary producer biomass sediment chlorophyll a content (Chla) in the longer term, depending on climatic context and habitat factors affecting the strengths of mutually reinforcing feedbacks. The remarkable coherence of results from small and large scales is evidence of real-world ecosystem function scalability and ecological self-organisation. This discovery provides greater insights into the range of responses to broad-scale anthropogenic stressors in naturally heterogeneous environmental settings. PMID:25993477

JPL's GNSS Real-Time Earthquake and Tsunami (GREAT) Alert System

NASA Astrophysics Data System (ADS)

Bar-Sever, Yoaz; Miller, Mark; Vallisneri, Michele; Khachikyan, Robert; Meyer, Robert

2017-04-01

We describe recent developments to the GREAT Alert natural hazard monitoring service from JPL's Global Differential GPS (GDGPS) System. GREAT Alert provides real-time, 1 Hz positioning solutions for hundreds of GNSS tracking sites, from both global and regional networks, aiming to monitor ground motion in the immediate aftermath of earthquakes. We take advantage of the centralized data processing, which is collocated with the GNSS orbit determination operations of the GDGPS System, to combine orbit determination with large-scale point-positioning in a grand estimation scheme, and as a result realize significant improvement to the positioning accuracy compared to conventional stand-alone point positioning techniques. For example, the measured median site (over all sites) real-time horizontal positioning accuracy is 2 cm 1DRMS, and the median real-time vertical accuracy is 4 cm RMS. The GREAT Alert positioning service is integrated with automated global earthquake notices from the United States Geodetic Survey (USGS) to support near-real-time calculations of co-seismic displacements with attendant formal errors based both short-term and long-term error analysis for each individual site. We will show the millimeter-level resolution of co-seismic displacement can be achieved by this system. The co-seismic displacements, in turn, are fed into a JPL geodynamics and ocean models, that estimate the Earthquake magnitude and predict the potential tsunami scale.

Use of ruthenium dyes for subnanosecond detector fidelity testing in real time transient absorption

NASA Astrophysics Data System (ADS)

Byrdin, Martin; Thiagarajan, Viruthachalam; Villette, Sandrine; Espagne, Agathe; Brettel, Klaus

2009-04-01

Transient absorption spectroscopy is a powerful tool for the study of photoreactions on time scales from femtoseconds to seconds. Typically, reactions slower than ˜1 ns are recorded by the "classical" technique; the reaction is triggered by an excitation flash, and absorption changes accompanying the reaction are recorded in real time using a continuous monitoring light beam and a detection system with sufficiently fast response. The pico- and femtosecond region can be accessed by the more recent "pump-probe" technique, which circumvents the difficulties of real time detection on a subnanosecond time scale. This is paid for by accumulation of an excessively large number of shots to sample the reaction kinetics. Hence, it is of interest to extend the classical real time technique as far as possible to the subnanosecond range. In order to identify and minimize detection artifacts common on a subnanosecond scale, like overshoot, ringing, and signal reflections, rigorous testing is required of how the detection system responds to fast changes of the monitoring light intensity. Here, we introduce a novel method to create standard signals for detector fidelity testing on a time scale from a few picoseconds to tens of nanoseconds. The signals result from polarized measurements of absorption changes upon excitation of ruthenium complexes {[Ru(bpy)3]2+ and a less symmetric derivative} by a short laser flash. Two types of signals can be created depending on the polarization of the monitoring light with respect to that of the excitation flash: a fast steplike bleaching at magic angle and a monoexponentially decaying bleaching for parallel polarizations. The lifetime of the decay can be easily varied via temperature and viscosity of the solvent. The method is applied to test the performance of a newly developed real time transient absorption setup with 300 ps time resolution and high sensitivity.

An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator

PubMed Central

Wang, Runchun M.; Thakur, Chetan S.; van Schaik, André

2018-01-01

This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF) neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons). This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks. PMID:29692702

An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator.

PubMed

Wang, Runchun M; Thakur, Chetan S; van Schaik, André

2018-01-01

This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF) neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons). This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

Deep learning-based fine-grained car make/model classification for visual surveillance

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Parıldı, Enes Sinan; Solmaz, Berkan; Yücesoy, Veysel; Koç, Aykut

2017-10-01

Fine-grained object recognition is a potential computer vision problem that has been recently addressed by utilizing deep Convolutional Neural Networks (CNNs). Nevertheless, the main disadvantage of classification methods relying on deep CNN models is the need for considerably large amount of data. In addition, there exists relatively less amount of annotated data for a real world application, such as the recognition of car models in a traffic surveillance system. To this end, we mainly concentrate on the classification of fine-grained car make and/or models for visual scenarios by the help of two different domains. First, a large-scale dataset including approximately 900K images is constructed from a website which includes fine-grained car models. According to their labels, a state-of-the-art CNN model is trained on the constructed dataset. The second domain that is dealt with is the set of images collected from a camera integrated to a traffic surveillance system. These images, which are over 260K, are gathered by a special license plate detection method on top of a motion detection algorithm. An appropriately selected size of the image is cropped from the region of interest provided by the detected license plate location. These sets of images and their provided labels for more than 30 classes are employed to fine-tune the CNN model which is already trained on the large scale dataset described above. To fine-tune the network, the last two fully-connected layers are randomly initialized and the remaining layers are fine-tuned in the second dataset. In this work, the transfer of a learned model on a large dataset to a smaller one has been successfully performed by utilizing both the limited annotated data of the traffic field and a large scale dataset with available annotations. Our experimental results both in the validation dataset and the real field show that the proposed methodology performs favorably against the training of the CNN model from scratch.

Development of a flash flood warning system based on real-time radar data and process-based erosion modelling

NASA Astrophysics Data System (ADS)

Schindewolf, Marcus; Kaiser, Andreas; Buchholtz, Arno; Schmidt, Jürgen

2017-04-01

Extreme rainfall events and resulting flash floods led to massive devastations in Germany during spring 2016. The study presented aims on the development of a early warning system, which allows the simulation and assessment of negative effects on infrastructure by radar-based heavy rainfall predictions, serving as input data for the process-based soil loss and deposition model EROSION 3D. Our approach enables a detailed identification of runoff and sediment fluxes in agricultural used landscapes. In a first step, documented historical events were analyzed concerning the accordance of measured radar rainfall and large scale erosion risk maps. A second step focused on a small scale erosion monitoring via UAV of source areas of heavy flooding events and a model reconstruction of the processes involved. In all examples damages were caused to local infrastructure. Both analyses are promising in order to detect runoff and sediment delivering areas even in a high temporal and spatial resolution. Results prove the important role of late-covering crops such as maize, sugar beet or potatoes in runoff generation. While e.g. winter wheat positively affects extensive runoff generation on undulating landscapes, massive soil loss and thus muddy flows are observed and depicted in model results. Future research aims on large scale model parameterization and application in real time, uncertainty estimation of precipitation forecast and interface developments.

AirSTAR: A UAV Platform for Flight Dynamics and Control System Testing

NASA Technical Reports Server (NTRS)

Jordan, Thomas L.; Foster, John V.; Bailey, Roger M.; Belcastro, Christine M.

2006-01-01

As part of the NASA Aviation Safety Program at Langley Research Center, a dynamically scaled unmanned aerial vehicle (UAV) and associated ground based control system are being developed to investigate dynamics modeling and control of large transport vehicles in upset conditions. The UAV is a 5.5% (seven foot wingspan), twin turbine, generic transport aircraft with a sophisticated instrumentation and telemetry package. A ground based, real-time control system is located inside an operations vehicle for the research pilot and associated support personnel. The telemetry system supports over 70 channels of data plus video for the downlink and 30 channels for the control uplink. Data rates are in excess of 200 Hz. Dynamic scaling of the UAV, which includes dimensional, weight, inertial, actuation, and control system scaling, is required so that the sub-scale vehicle will realistically simulate the flight characteristics of the full-scale aircraft. This testbed will be utilized to validate modeling methods, flight dynamics characteristics, and control system designs for large transport aircraft, with the end goal being the development of technologies to reduce the fatal accident rate due to loss-of-control.

Virtual Patterson Experiment - A Way to Access the Rheology of Aggregates and Melanges

NASA Astrophysics Data System (ADS)

Delannoy, Thomas; Burov, Evgueni; Wolf, Sylvie

2014-05-01

Understanding the mechanisms of lithospheric deformation requires bridging the gap between human-scale laboratory experiments and the huge geological objects they represent. Those experiments are limited in spatial and time scale as well as in choice of materials (e.g., mono-phase minerals, exaggerated temperatures and strain rates), which means that the resulting constitutive laws may not fully represent real rocks at geological spatial and temporal scales. We use the thermo-mechanical numerical modelling approach as a tool to link both experiments and nature and hence better understand the rheology of the lithosphere, by enabling us to study the behavior of polymineralic aggregates and their impact on the localization of the deformation. We have adapted the large strain visco-elasto-plastic Flamar code to allow it to operate at all spatial and temporal scales, from sub-grain to geodynamic scale, and from seismic time scales to millions of years. Our first goal was to reproduce real rock mechanics experiments on deformation of mono and polymineralic aggregates in Patterson's load machine in order to deepen our understanding of the rheology of polymineralic rocks. In particular, we studied in detail the deformation of a 15x15 mm mica-quartz sample at 750 °C and 300 MPa. This mixture includes a molten phase and a solid phase in which shear bands develop as a result of interactions between ductile and brittle deformation and stress concentration at the boundaries between weak and strong phases. We used digitized x-ray scans of real samples as initial configuration for the numerical models so the model-predicted deformation and stress-strain behavior can match those observed in the laboratory experiment. Analyzing the numerical experiments providing the best match with the press experiments and making other complementary models by changing different parameters in the initial state (strength contrast between the phases, proportions, microstructure, etc.) provides a number of new elements of understanding of the mechanisms governing the localization of the deformation across the aggregates. We next used stress-strain curves derived from the numerical experiments to study in detail the evolution of the rheological behavior of each mineral phase as well as that of the mixtures in order to formulate constitutive relations for mélanges and polymineralic aggregates. The next step of our approach would be to link the constitutive laws obtained at small scale (laws that govern the rheology of a polymineralic aggregate, the effect of the presence of a molten phase, etc.) to the large-scale behavior of the Earth by implementing them in lithosphere-scale models.

Quantum error correction in crossbar architectures

NASA Astrophysics Data System (ADS)

Helsen, Jonas; Steudtner, Mark; Veldhorst, Menno; Wehner, Stephanie

2018-07-01

A central challenge for the scaling of quantum computing systems is the need to control all qubits in the system without a large overhead. A solution for this problem in classical computing comes in the form of so-called crossbar architectures. Recently we made a proposal for a large-scale quantum processor (Li et al arXiv:1711.03807 (2017)) to be implemented in silicon quantum dots. This system features a crossbar control architecture which limits parallel single-qubit control, but allows the scheme to overcome control scaling issues that form a major hurdle to large-scale quantum computing systems. In this work, we develop a language that makes it possible to easily map quantum circuits to crossbar systems, taking into account their architecture and control limitations. Using this language we show how to map well known quantum error correction codes such as the planar surface and color codes in this limited control setting with only a small overhead in time. We analyze the logical error behavior of this surface code mapping for estimated experimental parameters of the crossbar system and conclude that logical error suppression to a level useful for real quantum computation is feasible.

A novel heuristic algorithm for capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre

2017-09-01

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

Controllability of multiplex, multi-time-scale networks

NASA Astrophysics Data System (ADS)

Pósfai, Márton; Gao, Jianxi; Cornelius, Sean P.; Barabási, Albert-László; D'Souza, Raissa M.

2016-09-01

The paradigm of layered networks is used to describe many real-world systems, from biological networks to social organizations and transportation systems. While recently there has been much progress in understanding the general properties of multilayer networks, our understanding of how to control such systems remains limited. One fundamental aspect that makes this endeavor challenging is that each layer can operate at a different time scale; thus, we cannot directly apply standard ideas from structural control theory of individual networks. Here we address the problem of controlling multilayer and multi-time-scale networks focusing on two-layer multiplex networks with one-to-one interlayer coupling. We investigate the practically relevant case when the control signal is applied to the nodes of one layer. We develop a theory based on disjoint path covers to determine the minimum number of inputs (Ni) necessary for full control. We show that if both layers operate on the same time scale, then the network structure of both layers equally affect controllability. In the presence of time-scale separation, controllability is enhanced if the controller interacts with the faster layer: Ni decreases as the time-scale difference increases up to a critical time-scale difference, above which Ni remains constant and is completely determined by the faster layer. We show that the critical time-scale difference is large if layer I is easy and layer II is hard to control in isolation. In contrast, control becomes increasingly difficult if the controller interacts with the layer operating on the slower time scale and increasing time-scale separation leads to increased Ni, again up to a critical value, above which Ni still depends on the structure of both layers. This critical value is largely determined by the longest path in the faster layer that does not involve cycles. By identifying the underlying mechanisms that connect time-scale difference and controllability for a simplified model, we provide crucial insight into disentangling how our ability to control real interacting complex systems is affected by a variety of sources of complexity.

Boys, Girls and Communication: Their Views, Confidence and Why These Skills Matter

ERIC Educational Resources Information Center

Clark, Christina

2011-01-01

This is the first large-scale survey of young people's views on communication skills in the UK. The purpose of this survey was three-fold. Since a search of the published literature had highlighted real gaps in knowledge, the author and her colleagues wanted answers to the following questions: What do young people think about communication skills?…

On initial Brain Activity Mapping of episodic and semantic memory code in the hippocampus.

PubMed

Tsien, Joe Z; Li, Meng; Osan, Remus; Chen, Guifen; Lin, Longian; Wang, Phillip Lei; Frey, Sabine; Frey, Julietta; Zhu, Dajiang; Liu, Tianming; Zhao, Fang; Kuang, Hui

2013-10-01

It has been widely recognized that the understanding of the brain code would require large-scale recording and decoding of brain activity patterns. In 2007 with support from Georgia Research Alliance, we have launched the Brain Decoding Project Initiative with the basic idea which is now similarly advocated by BRAIN project or Brain Activity Map proposal. As the planning of the BRAIN project is currently underway, we share our insights and lessons from our efforts in mapping real-time episodic memory traces in the hippocampus of freely behaving mice. We show that appropriate large-scale statistical methods are essential to decipher and measure real-time memory traces and neural dynamics. We also provide an example of how the carefully designed, sometime thinking-outside-the-box, behavioral paradigms can be highly instrumental to the unraveling of memory-coding cell assembly organizing principle in the hippocampus. Our observations to date have led us to conclude that the specific-to-general categorical and combinatorial feature-coding cell assembly mechanism represents an emergent property for enabling the neural networks to generate and organize not only episodic memory, but also semantic knowledge and imagination. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies

PubMed Central

Bidargaddi, N; Musiat, P; Makinen, V-P; Ermes, M; Schrader, G; Licinio, J

2017-01-01

Digital footprints, the automatically accumulated by-products of our technology-saturated lives, offer an exciting opportunity for psychiatric research. The commercial sector has already embraced the electronic trails of customers as an enabling tool for guiding consumer behaviour, and analogous efforts are ongoing to monitor and improve the mental health of psychiatric patients. The untargeted collection of digital footprints that may or may not be health orientated comprises a large untapped information resource for epidemiological scale research into psychiatric disorders. Real-time monitoring of mood, sleep and physical and social activity in a substantial portion of the affected population in a naturalistic setting is unprecedented in psychiatry. We propose that digital footprints can provide these measurements from real world setting unobtrusively and in a longitudinal fashion. In this perspective article, we outline the concept of digital footprints and the services and devices that create them, and present examples where digital footprints have been successfully used in research. We then critically discuss the opportunities and fundamental challenges associated digital footprints in psychiatric research, such as collecting data from different sources, analysis, ethical and research design challenges. PMID:27922603

On Initial Brain Activity Mapping of Associative Memory Code in the Hippocampus

PubMed Central

Tsien, Joe Z.; Li, Meng; Osan, Remus; Chen, Guifen; Lin, Longian; Lei Wang, Phillip; Frey, Sabine; Frey, Julietta; Zhu, Dajiang; Liu, Tianming; Zhao, Fang; Kuang, Hui

2013-01-01

It has been widely recognized that the understanding of the brain code would require large-scale recording and decoding of brain activity patterns. In 2007 with support from Georgia Research Alliance, we have launched the Brain Decoding Project Initiative with the basic idea which is now similarly advocated by BRAIN project or Brain Activity Map proposal. As the planning of the BRAIN project is currently underway, we share our insights and lessons from our efforts in mapping real-time episodic memory traces in the hippocampus of freely behaving mice. We show that appropriate large-scale statistical methods are essential to decipher and measure real-time memory traces and neural dynamics. We also provide an example of how the carefully designed, sometime thinking-outside-the-box, behavioral paradigms can be highly instrumental to the unraveling of memory-coding cell assembly organizing principle in the hippocampus. Our observations to date have led us to conclude that the specific-to-general categorical and combinatorial feature-coding cell assembly mechanism represents an emergent property for enabling the neural networks to generate and organize not only episodic memory, but also semantic knowledge and imagination. PMID:23838072

TopicLens: Efficient Multi-Level Visual Topic Exploration of Large-Scale Document Collections.

PubMed

Kim, Minjeong; Kang, Kyeongpil; Park, Deokgun; Choo, Jaegul; Elmqvist, Niklas

2017-01-01

Topic modeling, which reveals underlying topics of a document corpus, has been actively adopted in visual analytics for large-scale document collections. However, due to its significant processing time and non-interactive nature, topic modeling has so far not been tightly integrated into a visual analytics workflow. Instead, most such systems are limited to utilizing a fixed, initial set of topics. Motivated by this gap in the literature, we propose a novel interaction technique called TopicLens that allows a user to dynamically explore data through a lens interface where topic modeling and the corresponding 2D embedding are efficiently computed on the fly. To support this interaction in real time while maintaining view consistency, we propose a novel efficient topic modeling method and a semi-supervised 2D embedding algorithm. Our work is based on improving state-of-the-art methods such as nonnegative matrix factorization and t-distributed stochastic neighbor embedding. Furthermore, we have built a web-based visual analytics system integrated with TopicLens. We use this system to measure the performance and the visualization quality of our proposed methods. We provide several scenarios showcasing the capability of TopicLens using real-world datasets.

Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies.

PubMed

Bidargaddi, N; Musiat, P; Makinen, V-P; Ermes, M; Schrader, G; Licinio, J

2017-02-01

Digital footprints, the automatically accumulated by-products of our technology-saturated lives, offer an exciting opportunity for psychiatric research. The commercial sector has already embraced the electronic trails of customers as an enabling tool for guiding consumer behaviour, and analogous efforts are ongoing to monitor and improve the mental health of psychiatric patients. The untargeted collection of digital footprints that may or may not be health orientated comprises a large untapped information resource for epidemiological scale research into psychiatric disorders. Real-time monitoring of mood, sleep and physical and social activity in a substantial portion of the affected population in a naturalistic setting is unprecedented in psychiatry. We propose that digital footprints can provide these measurements from real world setting unobtrusively and in a longitudinal fashion. In this perspective article, we outline the concept of digital footprints and the services and devices that create them, and present examples where digital footprints have been successfully used in research. We then critically discuss the opportunities and fundamental challenges associated digital footprints in psychiatric research, such as collecting data from different sources, analysis, ethical and research design challenges.

From random microstructures to representative volume elements

NASA Astrophysics Data System (ADS)

Zeman, J.; Šejnoha, M.

2007-06-01

A unified treatment of random microstructures proposed in this contribution opens the way to efficient solutions of large-scale real world problems. The paper introduces a notion of statistically equivalent periodic unit cell (SEPUC) that replaces in a computational step the actual complex geometries on an arbitrary scale. A SEPUC is constructed such that its morphology conforms with images of real microstructures. Here, the appreciated two-point probability function and the lineal path function are employed to classify, from the statistical point of view, the geometrical arrangement of various material systems. Examples of statistically equivalent unit cells constructed for a unidirectional fibre tow, a plain weave textile composite and an irregular-coursed masonry wall are given. A specific result promoting the applicability of the SEPUC as a tool for the derivation of homogenized effective properties that are subsequently used in an independent macroscopic analysis is also presented.

From bioterrorism exercise to real-life public health crisis: lessons for emergency hotline operations.

PubMed

Uscher-Pines, Lori; Bookbinder, Sylvia H; Miro, Suzanne; Burke, Thomas

2007-01-01

Although public health agencies routinely operate hotlines to communicate key messages to the public, they are rarely evaluated to improve hotline management. Since its creation in 2003, the New Jersey Department of Health & Senior Services' Emergency Communications Center has confronted two large-scale incidents that have tested its capabilities in this area. The influenza vaccine shortage of 2004 and the April 2005 TOPOFF 3 full-scale bioterrorism exercise provided both real-life and simulated crisis situations from which to derive general insights into the strengths and weaknesses of hotline administration. This article identifies problems in the areas of staff and message management by analyzing call volume data and the qualitative observations of group feedback sessions and semistructured interviews with hotline staff. It also makes recommendations based on lessons learned to improve future hotline operations in public health emergencies.

Iterative initial condition reconstruction

NASA Astrophysics Data System (ADS)

Schmittfull, Marcel; Baldauf, Tobias; Zaldarriaga, Matias

2017-07-01

Motivated by recent developments in perturbative calculations of the nonlinear evolution of large-scale structure, we present an iterative algorithm to reconstruct the initial conditions in a given volume starting from the dark matter distribution in real space. In our algorithm, objects are first moved back iteratively along estimated potential gradients, with a progressively reduced smoothing scale, until a nearly uniform catalog is obtained. The linear initial density is then estimated as the divergence of the cumulative displacement, with an optional second-order correction. This algorithm should undo nonlinear effects up to one-loop order, including the higher-order infrared resummation piece. We test the method using dark matter simulations in real space. At redshift z =0 , we find that after eight iterations the reconstructed density is more than 95% correlated with the initial density at k ≤0.35 h Mpc-1 . The reconstruction also reduces the power in the difference between reconstructed and initial fields by more than 2 orders of magnitude at k ≤0.2 h Mpc-1 , and it extends the range of scales where the full broadband shape of the power spectrum matches linear theory by a factor of 2-3. As a specific application, we consider measurements of the baryonic acoustic oscillation (BAO) scale that can be improved by reducing the degradation effects of large-scale flows. In our idealized dark matter simulations, the method improves the BAO signal-to-noise ratio by a factor of 2.7 at z =0 and by a factor of 2.5 at z =0.6 , improving standard BAO reconstruction by 70% at z =0 and 30% at z =0.6 , and matching the optimal BAO signal and signal-to-noise ratio of the linear density in the same volume. For BAO, the iterative nature of the reconstruction is the most important aspect.

Symphony: A Framework for Accurate and Holistic WSN Simulation

PubMed Central

Riliskis, Laurynas; Osipov, Evgeny

2015-01-01

Research on wireless sensor networks has progressed rapidly over the last decade, and these technologies have been widely adopted for both industrial and domestic uses. Several operating systems have been developed, along with a multitude of network protocols for all layers of the communication stack. Industrial Wireless Sensor Network (WSN) systems must satisfy strict criteria and are typically more complex and larger in scale than domestic systems. Together with the non-deterministic behavior of network hardware in real settings, this greatly complicates the debugging and testing of WSN functionality. To facilitate the testing, validation, and debugging of large-scale WSN systems, we have developed a simulation framework that accurately reproduces the processes that occur inside real equipment, including both hardware- and software-induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform that is integrated with the general purpose network simulator ns-3. Our framework enables the user to adjust the real code base as would be done in real deployments and also to test the boundary effects of different hardware components on the performance of distributed applications and protocols. Additionally we have developed a clock emulator with several different skew models and a component that handles sensory data feeds. The new framework should substantially shorten WSN application development cycles. PMID:25723144

A real-space stochastic density matrix approach for density functional electronic structure.

PubMed

Beck, Thomas L

2015-12-21

The recent development of real-space grid methods has led to more efficient, accurate, and adaptable approaches for large-scale electrostatics and density functional electronic structure modeling. With the incorporation of multiscale techniques, linear-scaling real-space solvers are possible for density functional problems if localized orbitals are used to represent the Kohn-Sham energy functional. These methods still suffer from high computational and storage overheads, however, due to extensive matrix operations related to the underlying wave function grid representation. In this paper, an alternative stochastic method is outlined that aims to solve directly for the one-electron density matrix in real space. In order to illustrate aspects of the method, model calculations are performed for simple one-dimensional problems that display some features of the more general problem, such as spatial nodes in the density matrix. This orbital-free approach may prove helpful considering a future involving increasingly parallel computing architectures. Its primary advantage is the near-locality of the random walks, allowing for simultaneous updates of the density matrix in different regions of space partitioned across the processors. In addition, it allows for testing and enforcement of the particle number and idempotency constraints through stabilization of a Feynman-Kac functional integral as opposed to the extensive matrix operations in traditional approaches.

Pilot-scale electrokinetic movement of HCB and Zn in real contaminated sediments enhanced with hydroxypropyl-beta-cyclodextrin.

PubMed

Li, Taiping; Yuan, Songhu; Wan, Jinzhong; Lin, Li; Long, Huayun; Wu, Xiaofeng; Lu, Xiaohua

2009-08-01

This study deals with the efficiency of a pilot-scale electrokinetic (EK) treatment on real aged sediments contaminated with hexachlorobenzene (HCB) and Zn. A total of 0.5m(3) of sediments were treated under a constant voltage in a polyvinyl chloride reactor. The changes of sediment pH, electrical conductivity (EC), organic content (OC), the transport of contaminants in sediments and the consumption of electric energy were evaluated. After 100 d processing, sediment pH slightly increased compared with the initial values, particularly in the bottom layer close to cathodic section, while sediment EC in most sections significantly decreased. Sediment OC in all sections increased, which implied that hydroxypropyl-beta-cyclodextrin (HPCD) was successfully penetrated across sediments by electroosmosis. Significant movement of contaminants was observed across sediments with negligible removals. Both HCB and Zn generally moved from sections near anode and accumulated near cathode. Upon the completion of treatment, the electric energy consumption was calculated as 563 kWhm(-3). This pilot-scale EK test indicates that it is difficult to achieve great removal of hydrophobic organic compounds (HOCs), or HOCs and heavy metal mixed contaminants, by EK treatment in large scale with the use of HPCD.

Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.

NASA Astrophysics Data System (ADS)

Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.

2017-12-01

Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the MizuRoute channel routing tool) but also distributed model states such as soil moisture and snow water equivalent. We also describe challenges in distributed model-based forecasting, including the application and early results of real-time hydrologic data assimilation.

Real-time field programmable gate array architecture for computer vision

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Torres-Huitzil, Cesar

2001-01-01

This paper presents an architecture for real-time generic convolution of a mask and an image. The architecture is intended for fast low-level image processing. The field programmable gate array (FPGA)-based architecture takes advantage of the availability of registers in FPGAs to implement an efficient and compact module to process the convolutions. The architecture is designed to minimize the number of accesses to the image memory and it is based on parallel modules with internal pipeline operation in order to improve its performance. The architecture is prototyped in a FPGA, but it can be implemented on dedicated very- large-scale-integrated devices to reach higher clock frequencies. Complexity issues, FPGA resources utilization, FPGA limitations, and real-time performance are discussed. Some results are presented and discussed.

Evolution of the Contact Area with Normal Load for Rough Surfaces: from Atomic to Macroscopic Scales.

PubMed

Huang, Shiping

2017-11-13

The evolution of the contact area with normal load for rough surfaces has great fundamental and practical importance, ranging from earthquake dynamics to machine wear. This work bridges the gap between the atomic scale and the macroscopic scale for normal contact behavior. The real contact area, which is formed by a large ensemble of discrete contacts (clusters), is proven to be much smaller than the apparent surface area. The distribution of the discrete contact clusters and the interaction between them are key to revealing the mechanism of the contacting solids. To this end, Green's function molecular dynamics (GFMD) is used to study both how the contact cluster evolves from the atomic scale to the macroscopic scale and the interaction between clusters. It is found that the interaction between clusters has a strong effect on their formation. The formation and distribution of the contact clusters is far more complicated than that predicted by the asperity model. Ignorance of the interaction between them leads to overestimating the contacting force. In real contact, contacting clusters are smaller and more discrete due to the interaction between the asperities. Understanding the exact nature of the contact area with the normal load is essential to the following research on friction.

Evolution of the Contact Area with Normal Load for Rough Surfaces: from Atomic to Macroscopic Scales

NASA Astrophysics Data System (ADS)

Huang, Shiping

2017-11-01

The evolution of the contact area with normal load for rough surfaces has great fundamental and practical importance, ranging from earthquake dynamics to machine wear. This work bridges the gap between the atomic scale and the macroscopic scale for normal contact behavior. The real contact area, which is formed by a large ensemble of discrete contacts (clusters), is proven to be much smaller than the apparent surface area. The distribution of the discrete contact clusters and the interaction between them are key to revealing the mechanism of the contacting solids. To this end, Green's function molecular dynamics (GFMD) is used to study both how the contact cluster evolves from the atomic scale to the macroscopic scale and the interaction between clusters. It is found that the interaction between clusters has a strong effect on their formation. The formation and distribution of the contact clusters is far more complicated than that predicted by the asperity model. Ignorance of the interaction between them leads to overestimating the contacting force. In real contact, contacting clusters are smaller and more discrete due to the interaction between the asperities. Understanding the exact nature of the contact area with the normal load is essential to the following research on friction.

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

PubMed

Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

2017-04-10

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

Topographically Engineered Large Scale Nanostructures for Plasmonic Biosensing

NASA Astrophysics Data System (ADS)

Xiao, Bo; Pradhan, Sangram K.; Santiago, Kevin C.; Rutherford, Gugu N.; Pradhan, Aswini K.

2016-04-01

We demonstrate that a nanostructured metal thin film can achieve enhanced transmission efficiency and sharp resonances and use a large-scale and high-throughput nanofabrication technique for the plasmonic structures. The fabrication technique combines the features of nanoimprint and soft lithography to topographically construct metal thin films with nanoscale patterns. Metal nanogratings developed using this method show significantly enhanced optical transmission (up to a one-order-of-magnitude enhancement) and sharp resonances with full width at half maximum (FWHM) of ~15nm in the zero-order transmission using an incoherent white light source. These nanostructures are sensitive to the surrounding environment, and the resonance can shift as the refractive index changes. We derive an analytical method using a spatial Fourier transformation to understand the enhancement phenomenon and the sensing mechanism. The use of real-time monitoring of protein-protein interactions in microfluidic cells integrated with these nanostructures is demonstrated to be effective for biosensing. The perpendicular transmission configuration and large-scale structures provide a feasible platform without sophisticated optical instrumentation to realize label-free surface plasmon resonance (SPR) sensing.

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

PubMed Central

Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

2017-01-01

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks. PMID:28394270

Dynamic structural disorder in supported nanoscale catalysts

NASA Astrophysics Data System (ADS)

Rehr, J. J.; Vila, F. D.

2014-04-01

We investigate the origin and physical effects of "dynamic structural disorder" (DSD) in supported nano-scale catalysts. DSD refers to the intrinsic fluctuating, inhomogeneous structure of such nano-scale systems. In contrast to bulk materials, nano-scale systems exhibit substantial fluctuations in structure, charge, temperature, and other quantities, as well as large surface effects. The DSD is driven largely by the stochastic librational motion of the center of mass and fluxional bonding at the nanoparticle surface due to thermal coupling with the substrate. Our approach for calculating and understanding DSD is based on a combination of real-time density functional theory/molecular dynamics simulations, transient coupled-oscillator models, and statistical mechanics. This approach treats thermal and dynamic effects over multiple time-scales, and includes bond-stretching and -bending vibrations, and transient tethering to the substrate at longer ps time-scales. Potential effects on the catalytic properties of these clusters are briefly explored. Model calculations of molecule-cluster interactions and molecular dissociation reaction paths are presented in which the reactant molecules are adsorbed on the surface of dynamically sampled clusters. This model suggests that DSD can affect both the prefactors and distribution of energy barriers in reaction rates, and thus can significantly affect catalytic activity at the nano-scale.

Learning binary code via PCA of angle projection for image retrieval

NASA Astrophysics Data System (ADS)

Yang, Fumeng; Ye, Zhiqiang; Wei, Xueqi; Wu, Congzhong

2018-01-01

With benefits of low storage costs and high query speeds, binary code representation methods are widely researched for efficiently retrieving large-scale data. In image hashing method, learning hashing function to embed highdimensions feature to Hamming space is a key step for accuracy retrieval. Principal component analysis (PCA) technical is widely used in compact hashing methods, and most these hashing methods adopt PCA projection functions to project the original data into several dimensions of real values, and then each of these projected dimensions is quantized into one bit by thresholding. The variances of different projected dimensions are different, and with real-valued projection produced more quantization error. To avoid the real-valued projection with large quantization error, in this paper we proposed to use Cosine similarity projection for each dimensions, the angle projection can keep the original structure and more compact with the Cosine-valued. We used our method combined the ITQ hashing algorithm, and the extensive experiments on the public CIFAR-10 and Caltech-256 datasets validate the effectiveness of the proposed method.

Near-Real Time Monitoring of TEC Over Japan at NICT (RWC Tokyo OF ISES)

NASA Astrophysics Data System (ADS)

Miyake, W.; Jin, H.

2010-05-01

The world wide use of global navigation satellite systems such as GPS offers unique opportunities for a permanent monitoring of the total electron content (TEC) of the ionosphere. We have developed a system of the rapid derivation of TEC from GEONET (a dense GPS receiver network in Japan). In addition to a previous plot of TEC temporal variation over Japan, we have recently developed a near-real-time two-dimensional TEC map and have used it for the daily operation of Space Weather Forecast Center at NICT (Regional Warning Center Tokyo of International Space Environment Service). The TEC map can be used to continuously monitor the ionospheric disturbances over Japan, including spatial and temporal development of ionospheric storms, large-amplitude traveling ionospheric disturbances, and plasma bubbles intruding over Japan, with high time resolution. The development of the real-time monitoring system of TEC enables us to monitor large ionospheric disturbances, ranging from global- to small-scale disturbances, expected in the next solar maximum. The plot and maps are open to the public and are available on http://wdc.nict.go.jp/IONO/index_E.html.

Iterative User-Centered Design of a Next Generation Patient Monitoring System for Emergency Medical Response

PubMed Central

Gao, Tia; Kim, Matthew I.; White, David; Alm, Alexander M.

2006-01-01

We have developed a system for real-time patient monitoring during large-scale disasters. Our system is designed with scalable algorithms to monitor large numbers of patients, an intuitive interface to support the overwhelmed responders, and ad-hoc mesh networking capabilities to maintain connectivity to patients in the chaotic settings. This paper describes an iterative approach to user-centered design adopted to guide development of our system. This system is a part of the Advanced Health and Disaster Aid Network (AID-N) architecture. PMID:17238348

Large-Scale Distributed Computational Fluid Dynamics on the Information Power Grid Using Globus

NASA Technical Reports Server (NTRS)

Barnard, Stephen; Biswas, Rupak; Saini, Subhash; VanderWijngaart, Robertus; Yarrow, Maurice; Zechtzer, Lou; Foster, Ian; Larsson, Olle

1999-01-01

This paper describes an experiment in which a large-scale scientific application development for tightly-coupled parallel machines is adapted to the distributed execution environment of the Information Power Grid (IPG). A brief overview of the IPG and a description of the computational fluid dynamics (CFD) algorithm are given. The Globus metacomputing toolkit is used as the enabling device for the geographically-distributed computation. Modifications related to latency hiding and Load balancing were required for an efficient implementation of the CFD application in the IPG environment. Performance results on a pair of SGI Origin 2000 machines indicate that real scientific applications can be effectively implemented on the IPG; however, a significant amount of continued effort is required to make such an environment useful and accessible to scientists and engineers.

The need for harmonization of methods for finding locations and magnitudes of air pollution sources using observations of concentrations and wind fields

NASA Astrophysics Data System (ADS)

Hanna, Steven R.; Young, George S.

2017-01-01

What do the terms "top-down", "inverse", "backwards", "adjoint", "sensor data fusion", "receptor", "source term estimation (STE)", to name several appearing in the current literature, have in common? These varied terms are used by different disciplines to describe the same general methodology - the use of observations of air pollutant concentrations and knowledge of wind fields to identify air pollutant source locations and/or magnitudes. Academic journals are publishing increasing numbers of papers on this topic. Examples of scenarios related to this growing interest, ordered from small scale to large scale, are: use of real-time samplers to quickly estimate the location of a toxic gas release by a terrorist at a large public gathering (e.g., Haupt et al., 2009);

Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

3D fast adaptive correlation imaging for large-scale gravity data based on GPU computation

NASA Astrophysics Data System (ADS)

Chen, Z.; Meng, X.; Guo, L.; Liu, G.

2011-12-01

In recent years, large scale gravity data sets have been collected and employed to enhance gravity problem-solving abilities of tectonics studies in China. Aiming at the large scale data and the requirement of rapid interpretation, previous authors have carried out a lot of work, including the fast gradient module inversion and Euler deconvolution depth inversion ,3-D physical property inversion using stochastic subspaces and equivalent storage, fast inversion using wavelet transforms and a logarithmic barrier method. So it can be say that 3-D gravity inversion has been greatly improved in the last decade. Many authors added many different kinds of priori information and constraints to deal with nonuniqueness using models composed of a large number of contiguous cells of unknown property and obtained good results. However, due to long computation time, instability and other shortcomings, 3-D physical property inversion has not been widely applied to large-scale data yet. In order to achieve 3-D interpretation with high efficiency and precision for geological and ore bodies and obtain their subsurface distribution, there is an urgent need to find a fast and efficient inversion method for large scale gravity data. As an entirely new geophysical inversion method, 3D correlation has a rapid development thanks to the advantage of requiring no a priori information and demanding small amount of computer memory. This method was proposed to image the distribution of equivalent excess masses of anomalous geological bodies with high resolution both longitudinally and transversely. In order to tranform the equivalence excess masses into real density contrasts, we adopt the adaptive correlation imaging for gravity data. After each 3D correlation imaging, we change the equivalence into density contrasts according to the linear relationship, and then carry out forward gravity calculation for each rectangle cells. Next, we compare the forward gravity data with real data, and comtinue to perform 3D correlation imaging for the redisual gravity data. After several iterations, we can obtain a satisfactoy results. Newly developed general purpose computing technology from Nvidia GPU (Graphics Processing Unit) has been put into practice and received widespread attention in many areas. Based on the GPU programming mode and two parallel levels, five CPU loops for the main computation of 3D correlation imaging are converted into three loops in GPU kernel functions, thus achieving GPU/CPU collaborative computing. The two inner loops are defined as the dimensions of blocks and the three outer loops are defined as the dimensions of threads, thus realizing the double loop block calculation. Theoretical and real gravity data tests show that results are reliable and the computing time is greatly reduced. Acknowledgments We acknowledge the financial support of Sinoprobe project (201011039 and 201011049-03), the Fundamental Research Funds for the Central Universities (2010ZY26 and 2011PY0183), the National Natural Science Foundation of China (41074095) and the Open Project of State Key Laboratory of Geological Processes and Mineral Resources (GPMR0945).

Pedestrian detection in crowded scenes with the histogram of gradients principle

NASA Astrophysics Data System (ADS)

Sidla, O.; Rosner, M.; Lypetskyy, Y.

2006-10-01

This paper describes a close to real-time scale invariant implementation of a pedestrian detector system which is based on the Histogram of Oriented Gradients (HOG) principle. Salient HOG features are first selected from a manually created very large database of samples with an evolutionary optimization procedure that directly trains a polynomial Support Vector Machine (SVM). Real-time operation is achieved by a cascaded 2-step classifier which uses first a very fast linear SVM (with the same features as the polynomial SVM) to reject most of the irrelevant detections and then computes the decision function with a polynomial SVM on the remaining set of candidate detections. Scale invariance is achieved by running the detector of constant size on scaled versions of the original input images and by clustering the results over all resolutions. The pedestrian detection system has been implemented in two versions: i) fully body detection, and ii) upper body only detection. The latter is especially suited for very busy and crowded scenarios. On a state-of-the-art PC it is able to run at a frequency of 8 - 20 frames/sec.

The research and realization of multi-platform real-time message-oriented middleware in large-scale air traffic control system

NASA Astrophysics Data System (ADS)

Liang, Haijun; Ren, Jialong; Song, Tao

2017-05-01

Operating requirement of air traffic control system, the multi-platform real-time message-oriented middleware was studied and realized, which is composed of CDCC and CDCS. The former provides application process interface, while the latter realizes data synchronism of CDCC and data exchange. MQM, as one important part of it, provides message queue management and, encrypt and compress data during transmitting procedure. The practical system application verifies that the middleware can simplify the development of air traffic control system, enhance its stability, improve its systematic function and make it convenient for maintenance and reuse.

Research on e-commerce transaction networks using multi-agent modelling and open application programming interface

NASA Astrophysics Data System (ADS)

Piao, Chunhui; Han, Xufang; Wu, Harris

2010-08-01

We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.

Fidelity Study of Superconductivity in Extended Hubbard Models

NASA Astrophysics Data System (ADS)

Plonka, Nachum; Jia, Chunjing; Moritz, Brian; Wang, Yao; Devereaux, Thomas

2015-03-01

The role of strong electronic correlations on unconventional superconductivity remains an important open question. Here, we explore the influence of long-range Coulomb interactions, present in real material systems, through nearest and next-nearest neighbor extended Hubbard interactions in addition to the usual on-site terms. Utilizing large scale, numerical exact diagonalization, we analyze the signatures of superconductivity in the ground states through the fidelity metric of quantum information theory. We find that these extended interactions enhance charge fluctuations with various wave vectors. These suppress superconductivity in general, but in certain parameter regimes superconductivity is sustained. This has implications for tuning extended interactions in real materials.

Development of a database system for mapping insertional mutations onto the mouse genome with large-scale experimental data

PubMed Central

2009-01-01

Background Insertional mutagenesis is an effective method for functional genomic studies in various organisms. It can rapidly generate easily tractable mutations. A large-scale insertional mutagenesis with the piggyBac (PB) transposon is currently performed in mice at the Institute of Developmental Biology and Molecular Medicine (IDM), Fudan University in Shanghai, China. This project is carried out via collaborations among multiple groups overseeing interconnected experimental steps and generates a large volume of experimental data continuously. Therefore, the project calls for an efficient database system for recording, management, statistical analysis, and information exchange. Results This paper presents a database application called MP-PBmice (insertional mutation mapping system of PB Mutagenesis Information Center), which is developed to serve the on-going large-scale PB insertional mutagenesis project. A lightweight enterprise-level development framework Struts-Spring-Hibernate is used here to ensure constructive and flexible support to the application. The MP-PBmice database system has three major features: strict access-control, efficient workflow control, and good expandability. It supports the collaboration among different groups that enter data and exchange information on daily basis, and is capable of providing real time progress reports for the whole project. MP-PBmice can be easily adapted for other large-scale insertional mutation mapping projects and the source code of this software is freely available at http://www.idmshanghai.cn/PBmice. Conclusion MP-PBmice is a web-based application for large-scale insertional mutation mapping onto the mouse genome, implemented with the widely used framework Struts-Spring-Hibernate. This system is already in use by the on-going genome-wide PB insertional mutation mapping project at IDM, Fudan University. PMID:19958505

Defining biotypes for depression and anxiety based on large-scale circuit dysfunction: A theoretical review of the evidence and future directions for clinical translation

PubMed Central

Williams, Leanne M

2016-01-01

Complex emotional, cognitive and self-reflective functions rely on the activation and connectivity of large-scale neural circuits. These circuits offer a relevant scale of focus for conceptualizing a taxonomy for depression and anxiety based on specific profiles (or biotypes) of neural circuit dysfunction. Here, the theoretical review first outlined the current consensus as to what constitutes the organization of large-scale circuits in the human brain identified using parcellation and meta-analysis. The focus is on neural circuits implicated in resting reflection (“default mode”), detection of “salience”, affective processing (“threat” and “reward”), “attention” and “cognitive control”. Next, the current evidence regarding which type of dysfunctions in these circuits characterize depression and anxiety disorders was reviewed, with an emphasis on published meta-analyses and reviews of circuit dysfunctions that have been identified in at least two well-powered case:control studies. Grounded in the review of these topics, a conceptual framework is proposed for considering neural circuit-defined “biotypes”. In this framework, biotypes are defined by profiles of extent of dysfunction on each large-scale circuit. The clinical implications of a biotype approach for guiding classification and treatment of depression and anxiety is considered. Future research directions will develop the validity and clinical utility of a neural circuit biotype model that spans diagnostic categories and helps to translate neuroscience into clinical practice in the real world. PMID:27653321

On The Evidence For Large-Scale Galactic Conformity In The Local Universe

NASA Astrophysics Data System (ADS)

Sin, Larry P. T.; Lilly, Simon J.; Henriques, Bruno M. B.

2017-10-01

We re-examine the observational evidence for large-scale (4 Mpc) galactic conformity in the local Universe, as presented in Kauffmann et al. We show that a number of methodological features of their analysis act to produce a misleadingly high amplitude of the conformity signal. These include a weighting in favour of central galaxies in very high density regions, the likely misclassification of satellite galaxies as centrals in the same high-density regions and the use of medians to characterize bimodal distributions. We show that the large-scale conformity signal in Kauffmann et al. clearly originates from a very small number of central galaxies in the vicinity of just a few very massive clusters, whose effect is strongly amplified by the methodological issues that we have identified. Some of these 'centrals' are likely misclassified satellites, but some may be genuine centrals showing a real conformity effect. Regardless, this analysis suggests that conformity on 4 Mpc scales is best viewed as a relatively short-range effect (at the virial radius) associated with these very large neighbouring haloes, rather than a very long-range effect (at tens of virial radii) associated with the relatively low-mass haloes that host the nominal central galaxies in the analysis. A mock catalogue constructed from a recent semi-analytic model shows very similar conformity effects to the data when analysed in the same way, suggesting that there is no need to introduce new physical processes to explain galactic conformity on 4 Mpc scales.

High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flueck, Alex

The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform formore » modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator’s ability to model three­phase and single­ phase networks and devices.« less

Real-time monitoring of CO2 storage sites: Application to Illinois Basin-Decatur Project

USGS Publications Warehouse

Picard, G.; Berard, T.; Chabora, E.; Marsteller, S.; Greenberg, S.; Finley, R.J.; Rinck, U.; Greenaway, R.; Champagnon, C.; Davard, J.

2011-01-01

Optimization of carbon dioxide (CO2) storage operations for efficiency and safety requires use of monitoring techniques and implementation of control protocols. The monitoring techniques consist of permanent sensors and tools deployed for measurement campaigns. Large amounts of data are thus generated. These data must be managed and integrated for interpretation at different time scales. A fast interpretation loop involves combining continuous measurements from permanent sensors as they are collected to enable a rapid response to detected events; a slower loop requires combining large datasets gathered over longer operational periods from all techniques. The purpose of this paper is twofold. First, it presents an analysis of the monitoring objectives to be performed in the slow and fast interpretation loops. Second, it describes the implementation of the fast interpretation loop with a real-time monitoring system at the Illinois Basin-Decatur Project (IBDP) in Illinois, USA. ?? 2011 Published by Elsevier Ltd.

Simulating anomalous transport and multiphase segregation in porous media with the Lattice Boltzmann Method

NASA Astrophysics Data System (ADS)

Matin, Rastin; Hernandez, Anier; Misztal, Marek; Mathiesen, Joachim

2015-04-01

Many hydrodynamic phenomena ranging from flows at micron scale in porous media, large Reynolds numbers flows, non-Newtonian and multiphase flows have been simulated on computers using the lattice Boltzmann (LB) method. By solving the Lattice Boltzmann Equation on unstructured meshes in three dimensions, we have developed methods to efficiently model the fluid flow in real rock samples. We use this model to study the spatio-temporal statistics of the velocity field inside three-dimensional real geometries and investigate its relation to the, in general, anomalous transport of passive tracers for a wide range of Peclet and Reynolds numbers. We extend this model by free-energy based method, which allows us to simulate binary systems with large-density ratios in a thermodynamically consistent way and track the interface explicitly. In this presentation we will present our recent results on both anomalous transport and multiphase segregation.

Big Data and Health Economics: Strengths, Weaknesses, Opportunities and Threats.

PubMed

Collins, Brendan

2016-02-01

'Big data' is the collective name for the increasing capacity of information systems to collect and store large volumes of data, which are often unstructured and time stamped, and to analyse these data by using regression and other statistical techniques. This is a review of the potential applications of big data and health economics, using a SWOT (strengths, weaknesses, opportunities, threats) approach. In health economics, large pseudonymized databases, such as the planned care.data programme in the UK, have the potential to increase understanding of how drugs work in the real world, taking into account adherence, co-morbidities, interactions and side effects. This 'real-world evidence' has applications in individualized medicine. More routine and larger-scale cost and outcomes data collection will make health economic analyses more disease specific and population specific but may require new skill sets. There is potential for biomonitoring and lifestyle data to inform health economic analyses and public health policy.

Determination of real-time predictors of the wind turbine wake meandering

NASA Astrophysics Data System (ADS)

Muller, Yann-Aël; Aubrun, Sandrine; Masson, Christian

2015-03-01

The present work proposes an experimental methodology to characterize the unsteady properties of a wind turbine wake, called meandering, and particularly its ability to follow the large-scale motions induced by large turbulent eddies contained in the approach flow. The measurements were made in an atmospheric boundary layer wind tunnel. The wind turbine model is based on the actuator disc concept. One part of the work has been dedicated to the development of a methodology for horizontal wake tracking by mean of a transverse hot wire rake, whose dynamic response is adequate for spectral analysis. Spectral coherence analysis shows that the horizontal position of the wake correlates well with the upstream transverse velocity, especially for wavelength larger than three times the diameter of the disc but less so for smaller scales. Therefore, it is concluded that the wake is actually a rather passive tracer of the large surrounding turbulent structures. The influence of the rotor size and downstream distance on the wake meandering is studied. The fluctuations of the lateral force and the yawing torque affecting the wind turbine model are also measured and correlated with the wake meandering. Two approach flow configurations are then tested: an undisturbed incoming flow (modelled atmospheric boundary layer) and a disturbed incoming flow, with a wind turbine model located upstream. Results showed that the meandering process is amplified by the presence of the upstream wake. It is shown that the coherence between the lateral force fluctuations and the horizontal wake position is significant up to length scales larger than twice the wind turbine model diameter. This leads to the conclusion that the lateral force is a better candidate than the upstream transverse velocity to predict in real time the meandering process, for either undisturbed (wake free) or disturbed incoming atmospheric flows.

Efficient spiking neural network model of pattern motion selectivity in visual cortex.

PubMed

Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

2014-07-01

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

THUIR at TREC 2009 Web Track: Finding Relevant and Diverse Results for Large Scale Web Search

DTIC Science & Technology

2009-11-01

Porn words‟ filtering is also one of the anti-spam techniques in real world search engines. A list of porn words was found from the internet [2...When the numbers of the porn words in the page is larger than α, then the page is taken as the spam. In our experiments, the threshold is set to 16

Improving health aid for a better planet: The planning, monitoring and evaluation tool (PLANET).

PubMed

Sridhar, Devi; Car, Josip; Chopra, Mickey; Campbell, Harry; Woods, Ngaire; Rudan, Igor

2015-12-01

International development assistance for health (DAH) quadrupled between 1990 and 2012, from US$ 5.6 billion to US$ 28.1 billion. This generates an increasing need for transparent and replicable tools that could be used to set investment priorities, monitor the distribution of funding in real time, and evaluate the impact of those investments. In this paper we present a methodology that addresses these three challenges. We call this approach PLANET, which stands for planning, monitoring and evaluation tool. Fundamentally, PLANET is based on crowdsourcing approach to obtaining information relevant to deployment of large-scale programs. Information is contributed in real time by a diverse group of participants involved in the program delivery. PLANET relies on real-time information from three levels of participants in large-scale programs: funders, managers and recipients. At each level, information is solicited to assess five key risks that are most relevant to each level of operations. The risks at the level of funders involve systematic neglect of certain areas, focus on donor's interests over that of program recipients, ineffective co-ordination between donors, questionable mechanisms of delivery and excessive loss of funding to "middle men". At the level of managers, the risks are corruption, lack of capacity and/or competence, lack of information and /or communication, undue avoidance of governmental structures / preference to non-governmental organizations and exclusion of local expertise. At the level of primary recipients, the risks are corruption, parallel operations / "verticalization", misalignment with local priorities and lack of community involvement, issues with ethics, equity and/or acceptability, and low likelihood of sustainability beyond the end of the program's implementation. PLANET is intended as an additional tool available to policy-makers to prioritize, monitor and evaluate large-scale development programs. In this, it should complement tools such as LiST (for health care/interventions), EQUIST (for health care/interventions) and CHNRI (for health research), which also rely on information from local experts and on local context to set priorities in a transparent, user-friendly, replicable, quantifiable and specific, algorithmic-like manner.

Community-based native seed production for restoration in Brazil - the role of science and policy.

PubMed

Schmidt, I B; de Urzedo, D I; Piña-Rodrigues, F C M; Vieira, D L M; de Rezende, G M; Sampaio, A B; Junqueira, R G P

2018-05-20

Large-scale restoration programmes in the tropics require large volumes of high quality, genetically diverse and locally adapted seeds from a large number of species. However, scarcity of native seeds is a critical restriction to achieve restoration targets. In this paper, we analyse three successful community-based networks that supply native seeds and seedlings for Brazilian Amazon and Cerrado restoration projects. In addition, we propose directions to promote local participation, legal, technical and commercialisation issues for up-scaling the market of native seeds for restoration with high quality and social justice. We argue that effective community-based restoration arrangements should follow some principles: (i) seed production must be based on real market demand; (ii) non-governmental and governmental organisations have a key role in supporting local organisation, legal requirements and selling processes; (iii) local ecological knowledge and labour should be valued, enabling local communities to promote large-scale seed production; (iv) applied research can help develop appropriate techniques and solve technical issues. The case studies from Brazil and principles presented here can be useful for the up-scaling restoration ecology efforts in many other parts of the world and especially in tropical countries where improving rural community income is a strategy for biodiversity conservation and restoration. © 2018 German Society for Plant Sciences and The Royal Botanical Society of the Netherlands.

Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

NASA Astrophysics Data System (ADS)

Abdeljaber, Osama; Avci, Onur; Kiranyaz, Serkan; Gabbouj, Moncef; Inman, Daniel J.

2017-02-01

Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has always been one of the principal objectives of SHM applications. The performance of a classical damage detection system predominantly depends on the choice of the features and the classifier. While the fixed and hand-crafted features may either be a sub-optimal choice for a particular structure or fail to achieve the same level of performance on another structure, they usually require a large computation power which may hinder their usage for real-time structural damage detection. This paper presents a novel, fast and accurate structural damage detection system using 1D Convolutional Neural Networks (CNNs) that has an inherent adaptive design to fuse both feature extraction and classification blocks into a single and compact learning body. The proposed method performs vibration-based damage detection and localization of the damage in real-time. The advantage of this approach is its ability to extract optimal damage-sensitive features automatically from the raw acceleration signals. Large-scale experiments conducted on a grandstand simulator revealed an outstanding performance and verified the computational efficiency of the proposed real-time damage detection method.

One in the Dance: Musical Correlates of Group Synchrony in a Real-World Club Environment

PubMed Central

Ellamil, Melissa; Berson, Joshua; Wong, Jen; Buckley, Louis; Margulies, Daniel S.

2016-01-01

Previous research on interpersonal synchrony has mainly investigated small groups in isolated laboratory settings, which may not fully reflect the complex and dynamic interactions of real-life social situations. The present study expands on this by examining group synchrony across a large number of individuals in a naturalistic environment. Smartphone acceleration measures were recorded from participants during a music set in a dance club and assessed to identify how group movement synchrony covaried with various features of the music. In an evaluation of different preprocessing and analysis methods, giving more weight to front-back movement provided the most sensitive and reliable measure of group synchrony. During the club music set, group synchrony of torso movement was most strongly associated with pulsations that approximate walking rhythm (100–150 beats per minute). Songs with higher real-world play counts were also correlated with greater group synchrony. Group synchrony thus appears to be constrained by familiarity of the movement (walking action and rhythm) and of the music (song popularity). These findings from a real-world, large-scale social and musical setting can guide the development of methods for capturing and examining collective experiences in the laboratory and for effectively linking them to synchrony across people in daily life. PMID:27764167

One in the Dance: Musical Correlates of Group Synchrony in a Real-World Club Environment.

PubMed

Ellamil, Melissa; Berson, Joshua; Wong, Jen; Buckley, Louis; Margulies, Daniel S

2016-01-01

Previous research on interpersonal synchrony has mainly investigated small groups in isolated laboratory settings, which may not fully reflect the complex and dynamic interactions of real-life social situations. The present study expands on this by examining group synchrony across a large number of individuals in a naturalistic environment. Smartphone acceleration measures were recorded from participants during a music set in a dance club and assessed to identify how group movement synchrony covaried with various features of the music. In an evaluation of different preprocessing and analysis methods, giving more weight to front-back movement provided the most sensitive and reliable measure of group synchrony. During the club music set, group synchrony of torso movement was most strongly associated with pulsations that approximate walking rhythm (100-150 beats per minute). Songs with higher real-world play counts were also correlated with greater group synchrony. Group synchrony thus appears to be constrained by familiarity of the movement (walking action and rhythm) and of the music (song popularity). These findings from a real-world, large-scale social and musical setting can guide the development of methods for capturing and examining collective experiences in the laboratory and for effectively linking them to synchrony across people in daily life.

Monitoring scale scores over time via quality control charts, model-based approaches, and time series techniques.

PubMed

Lee, Yi-Hsuan; von Davier, Alina A

2013-07-01

Maintaining a stable score scale over time is critical for all standardized educational assessments. Traditional quality control tools and approaches for assessing scale drift either require special equating designs, or may be too time-consuming to be considered on a regular basis with an operational test that has a short time window between an administration and its score reporting. Thus, the traditional methods are not sufficient to catch unusual testing outcomes in a timely manner. This paper presents a new approach for score monitoring and assessment of scale drift. It involves quality control charts, model-based approaches, and time series techniques to accommodate the following needs of monitoring scale scores: continuous monitoring, adjustment of customary variations, identification of abrupt shifts, and assessment of autocorrelation. Performance of the methodologies is evaluated using manipulated data based on real responses from 71 administrations of a large-scale high-stakes language assessment.

Estimating forest structural characteristics using the airborne LiDAR scanning system and a near-real time profiling laser system

NASA Astrophysics Data System (ADS)

Zhao, Kaiguang

LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatially-explicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for real-time remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real-time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real-time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for real-time forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of airborne scanning or profiling laser systems for remotely measuring various forest structural attributes at a range of scales, i.e., from individual tree, plot, stand and up to regional levels. The system not only provides a regional assessment tool, one that can be used to repeatedly, remotely measure hundreds or thousands of square kilometers with little/no analyst interaction or interpretation, but also serves as a paradigm for future efforts in building more advanced airborne laser systems such as real-time laser scanners.

Design and application of a web-based real-time personal PM2.5 exposure monitoring system.

PubMed

Sun, Qinghua; Zhuang, Jia; Du, Yanjun; Xu, Dandan; Li, Tiantian

2018-06-15

Growing demand from public health research for conduct large-scale epidemiological studies to explore health effect of PM 2.5 was well-documented. To address this need, we design a web-based real-time personal PM 2.5 exposure monitoring system (RPPM2.5 system) which can help researcher to get big data of personal PM 2.5 exposure with low-cost, low labor requirement, and low operating technical requirements. RPPM2.5 system can provide relative accurate real-time personal exposure data for individuals, researches, and decision maker. And this system has been used in a survey of PM 2.5 personal exposure level conducted in 5 cities of China and has provided mass of valuable data for epidemiological research. Copyright © 2018 Elsevier B.V. All rights reserved.

Implementation of Fiber Optic Sensing System on Sandwich Composite Cylinder Buckling Test

NASA Technical Reports Server (NTRS)

Pena, Francisco; Richards, W. Lance; Parker, Allen R.; Piazza, Anthony; Schultz, Marc R.; Rudd, Michelle T.; Gardner, Nathaniel W.; Hilburger, Mark W.

2018-01-01

The National Aeronautics and Space Administration (NASA) Engineering and Safety Center Shell Buckling Knockdown Factor Project is a multicenter project tasked with developing new analysis-based shell buckling design guidelines and design factors (i.e., knockdown factors) through high-fidelity buckling simulations and advanced test technologies. To validate these new buckling knockdown factors for future launch vehicles, the Shell Buckling Knockdown Factor Project is carrying out structural testing on a series of large-scale metallic and composite cylindrical shells at the NASA Marshall Space Flight Center (Marshall Space Flight Center, Alabama). A fiber optic sensor system was used to measure strain on a large-scale sandwich composite cylinder that was tested under multiple axial compressive loads up to more than 850,000 lb, and equivalent bending loads over 22 million in-lb. During the structural testing of the composite cylinder, strain data were collected from optical cables containing distributed fiber Bragg gratings using a custom fiber optic sensor system interrogator developed at the NASA Armstrong Flight Research Center. A total of 16 fiber-optic strands, each containing nearly 1,000 fiber Bragg gratings, measuring strain, were installed on the inner and outer cylinder surfaces to monitor the test article global structural response through high-density real-time and post test strain measurements. The distributed sensing system provided evidence of local epoxy failure at the attachment-ring-to-barrel interface that would not have been detected with conventional instrumentation. Results from the fiber optic sensor system were used to further refine and validate structural models for buckling of the large-scale composite structures. This paper discusses the techniques employed for real-time structural monitoring of the composite cylinder for structural load introduction and distributed bending-strain measurements over a large section of the cylinder by utilizing unique sensing capabilities of fiber optic sensors.

Development of an Efficient Binaural Simulation for the Analysis of Structural Acoustic Data

NASA Technical Reports Server (NTRS)

Johnson, Marty E.; Lalime, Aimee L.; Grosveld, Ferdinand W.; Rizzi, Stephen A.; Sullivan, Brenda M.

2003-01-01

Applying binaural simulation techniques to structural acoustic data can be very computationally intensive as the number of discrete noise sources can be very large. Typically, Head Related Transfer Functions (HRTFs) are used to individually filter the signals from each of the sources in the acoustic field. Therefore, creating a binaural simulation implies the use of potentially hundreds of real time filters. This paper details two methods of reducing the number of real-time computations required by: (i) using the singular value decomposition (SVD) to reduce the complexity of the HRTFs by breaking them into dominant singular values and vectors and (ii) by using equivalent source reduction (ESR) to reduce the number of sources to be analyzed in real-time by replacing sources on the scale of a structural wavelength with sources on the scale of an acoustic wavelength. The ESR and SVD reduction methods can be combined to provide an estimated computation time reduction of 99.4% for the structural acoustic data tested. In addition, preliminary tests have shown that there is a 97% correlation between the results of the combined reduction methods and the results found with the current binaural simulation techniques

Full-scale testing and progressive damage modeling of sandwich composite aircraft fuselage structure

NASA Astrophysics Data System (ADS)

Leone, Frank A., Jr.

A comprehensive experimental and computational investigation was conducted to characterize the fracture behavior and structural response of large sandwich composite aircraft fuselage panels containing artificial damage in the form of holes and notches. Full-scale tests were conducted where panels were subjected to quasi-static combined pressure, hoop, and axial loading up to failure. The panels were constructed using plain-weave carbon/epoxy prepreg face sheets and a Nomex honeycomb core. Panel deformation and notch tip damage development were monitored during the tests using several techniques, including optical observations, strain gages, digital image correlation (DIC), acoustic emission (AE), and frequency response (FR). Additional pretest and posttest inspections were performed via thermography, computer-aided tap tests, ultrasound, x-radiography, and scanning electron microscopy. The framework to simulate damage progression and to predict residual strength through use of the finite element (FE) method was developed. The DIC provided local and full-field strain fields corresponding to changes in the state-of-damage and identified the strain components driving damage progression. AE was monitored during loading of all panels and data analysis methodologies were developed to enable real-time determination of damage initiation, progression, and severity in large composite structures. The FR technique has been developed, evaluating its potential as a real-time nondestructive inspection technique applicable to large composite structures. Due to the large disparity in scale between the fuselage panels and the artificial damage, a global/local analysis was performed. The global FE models fully represented the specific geometries, composite lay-ups, and loading mechanisms of the full-scale tests. A progressive damage model was implemented in the local FE models, allowing the gradual failure of elements in the vicinity of the artificial damage. A set of modifications to the definitions of the local FE model boundary conditions is proposed and developed to address several issues related to the scalability of progressive damage modeling concepts, especially in regards to full-scale fuselage structures. Notable improvements were observed in the ability of the FE models to predict the strength of damaged composite fuselage structures. Excellent agreement has been established between the FE model predictions and the experimental results recorded by DIC, AE, FR, and visual observations.

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2015-04-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

A multi-scale hybrid neural network retrieval model for dust storm detection, a study in Asia

NASA Astrophysics Data System (ADS)

Wong, Man Sing; Xiao, Fei; Nichol, Janet; Fung, Jimmy; Kim, Jhoon; Campbell, James; Chan, P. W.

2015-05-01

Dust storms are known to have adverse effects on human health and significant impact on weather, air quality, hydrological cycle, and ecosystem. Atmospheric dust loading is also one of the large uncertainties in global climate modeling, due to its significant impact on the radiation budget and atmospheric stability. Observations of dust storms in humid tropical south China (e.g. Hong Kong), are challenging due to high industrial pollution from the nearby Pearl River Delta region. This study develops a method for dust storm detection by combining ground station observations (PM10 concentration, AERONET data), geostationary satellite images (MTSAT), and numerical weather and climatic forecasting products (WRF/Chem). The method is based on a hybrid neural network (NN) retrieval model for two scales: (i) a NN model for near real-time detection of dust storms at broader regional scale; (ii) a NN model for detailed dust storm mapping for Hong Kong and Taiwan. A feed-forward multilayer perceptron (MLP) NN, trained using back propagation (BP) algorithm, was developed and validated by the k-fold cross validation approach. The accuracy of the near real-time detection MLP-BP network is 96.6%, and the accuracies for the detailed MLP-BP neural network for Hong Kong and Taiwan is 74.8%. This newly automated multi-scale hybrid method can be used to give advance near real-time mapping of dust storms for environmental authorities and the public. It is also beneficial for identifying spatial locations of adverse air quality conditions, and estimates of low visibility associated with dust events for port and airport authorities.

Earthquakes in the Laboratory: Continuum-Granular Interactions

NASA Astrophysics Data System (ADS)

Ecke, Robert; Geller, Drew; Ward, Carl; Backhaus, Scott

2013-03-01

Earthquakes in nature feature large tectonic plate motion at large scales of 10-100 km and local properties of the earth on the scale of the rupture width, of the order of meters. Fault gouge often fills the gap between the large slipping plates and may play an important role in the nature and dynamics of earthquake events. We have constructed a laboratory scale experiment that represents a similitude scale model of this general earthquake description. Two photo-elastic plates (50 cm x 25 cm x 1 cm) confine approximately 3000 bi-disperse nylon rods (diameters 0.12 and 0.16 cm, height 1 cm) in a gap of approximately 1 cm. The plates are held rigidly along their outer edges with one held fixed while the other edge is driven at constant speed over a range of about 5 cm. The local stresses exerted on the plates are measured using their photo-elastic response, the local relative motions of the plates, i.e., the local strains, are determined by the relative motion of small ball bearings attached to the top surface, and the configurations of the nylon rods are investigated using particle tracking tools. We find that this system has properties similar to real earthquakes and are exploring these ``lab-quake'' events with the quantitative tools we have developed.

Self-similar solutions of stationary Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Shi, Zuoshunhua

2018-02-01

In this paper, we mainly study the existence of self-similar solutions of stationary Navier-Stokes equations for dimension n = 3 , 4. For n = 3, if the external force is axisymmetric, scaling invariant, C 1 , α continuous away from the origin and small enough on the sphere S2, we shall prove that there exists a family of axisymmetric self-similar solutions which can be arbitrarily large in the class Cloc3 , α (R3 0). Moreover, for axisymmetric external forces without swirl, corresponding to this family, the momentum flux of the flow along the symmetry axis can take any real number. However, there are no regular (U ∈ Cloc3 , α (R3 0)) axisymmetric self-similar solutions provided that the external force is a large multiple of some scaling invariant axisymmetric F which cannot be driven by a potential. In the case of dimension 4, there always exists at least one self-similar solution to the stationary Navier-Stokes equations with any scaling invariant external force in L 4 / 3 , ∞ (R4).

Tracking a head-mounted display in a room-sized environment with head-mounted cameras

NASA Astrophysics Data System (ADS)

Wang, Jih-Fang; Azuma, Ronald T.; Bishop, Gary; Chi, Vernon; Eyles, John; Fuchs, Henry

1990-10-01

This paper presents our efforts to accurately track a Head-Mounted Display (HMD) in a large environment. We review our current benchtop prototype (introduced in {WCF9O]), then describe our plans for building the full-scale system. Both systems use an inside-oui optical tracking scheme, where lateraleffect photodiodes mounted on the user's helmet view flashing infrared beacons placed in the environment. Church's method uses the measured 2D image positions and the known 3D beacon locations to recover the 3D position and orientation of the helmet in real-time. We discuss the implementation and performance of the benchtop prototype. The full-scale system design includes ceiling panels that hold the infrared beacons and a new sensor arrangement of two photodiodes with holographic lenses. In the full-scale system, the user can walk almost anywhere under the grid of ceiling panels, making the working volume nearly as large as the room.

Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

Cloud Computing: A model Construct of Real-Time Monitoring for Big Dataset Analytics Using Apache Spark

NASA Astrophysics Data System (ADS)

Alkasem, Ameen; Liu, Hongwei; Zuo, Decheng; Algarash, Basheer

2018-01-01

The volume of data being collected, analyzed, and stored has exploded in recent years, in particular in relation to the activity on the cloud computing. While large-scale data processing, analysis, storage, and platform model such as cloud computing were previously and currently are increasingly. Today, the major challenge is it address how to monitor and control these massive amounts of data and perform analysis in real-time at scale. The traditional methods and model systems are unable to cope with these quantities of data in real-time. Here we present a new methodology for constructing a model for optimizing the performance of real-time monitoring of big datasets, which includes a machine learning algorithms and Apache Spark Streaming to accomplish fine-grained fault diagnosis and repair of big dataset. As a case study, we use the failure of Virtual Machines (VMs) to start-up. The methodology proposition ensures that the most sensible action is carried out during the procedure of fine-grained monitoring and generates the highest efficacy and cost-saving fault repair through three construction control steps: (I) data collection; (II) analysis engine and (III) decision engine. We found that running this novel methodology can save a considerate amount of time compared to the Hadoop model, without sacrificing the classification accuracy or optimization of performance. The accuracy of the proposed method (92.13%) is an improvement on traditional approaches.

Large Scale Simulation Platform for NODES Validation Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sotorrio, P.; Qin, Y.; Min, L.

2017-04-27

This report summarizes the Large Scale (LS) simulation platform created for the Eaton NODES project. The simulation environment consists of both wholesale market simulator and distribution simulator and includes the CAISO wholesale market model and a PG&E footprint of 25-75 feeders to validate the scalability under a scenario of 33% RPS in California with additional 17% of DERS coming from distribution and customers. The simulator can generate hourly unit commitment, 5-minute economic dispatch, and 4-second AGC regulation signals. The simulator is also capable of simulating greater than 10k individual controllable devices. Simulated DERs include water heaters, EVs, residential and lightmore » commercial HVAC/buildings, and residential-level battery storage. Feeder-level voltage regulators and capacitor banks are also simulated for feeder-level real and reactive power management and Vol/Var control.« less

Trickle-Down Preferences: Preferential Conformity to High Status Peers in Fashion Choices.

PubMed

Galak, Jeff; Gray, Kurt; Elbert, Igor; Strohminger, Nina

2016-01-01

How much do our choices represent stable inner preferences versus social conformity? We examine conformity and consistency in sartorial choices surrounding a common life event of new norm exposure: relocation. A large-scale dataset of individual purchases of women's shoes (16,236 transactions) across five years and 2,007 women reveals a balance of conformity and consistency, moderated by changes in location socioeconomic status. Women conform to new local norms (i.e., average heel size) when moving to relatively higher status locations, but mostly ignore new local norms when moving to relatively lower status locations. In short, at periods of transition, it is the fashion norms of the rich that trickle down to consumers. These analyses provide the first naturalistic large-scale demonstration of the tension between psychological conformity and consistency, with real decisions in a highly visible context.

REVIEWS OF TOPICAL PROBLEMS: The hydromagnetic dynamo as the source of planetary, solar, and galactic magnetism

NASA Astrophysics Data System (ADS)

Zeldovich, Ya B.; Ruzmaĭkin, A. A.

1987-06-01

The magnetism of most celestial bodies, i.e., planets, stars, and galaxies, is of hydromagnetic origin. The turbulent hydromagnetic dynamo is the principal mechanism whereby the magnetic field is amplified and maintained, and the theory of this phenomenon has advanced significantly in recent years. This review discusses applications of the theory of the turbulent dynamo to real objects, taking the Sun, the Earth, and the Galaxy as examples. Most of the discussion is concentrated on the large-scale magnetic field averaged over turbulent fluctuations. The average field is amplified and maintained by the average helicity of turbulent motion and large-scale shear flows such as differential rotation. The dynamo theory explains striking phenomena such as geomagnetic field reversal, the solar cycle, and the ring and bisymmetric structure of spiral galaxies.

Efficient conformational space exploration in ab initio protein folding simulation.

PubMed

Ullah, Ahammed; Ahmed, Nasif; Pappu, Subrata Dey; Shatabda, Swakkhar; Ullah, A Z M Dayem; Rahman, M Sohel

2015-08-01

Ab initio protein folding simulation largely depends on knowledge-based energy functions that are derived from known protein structures using statistical methods. These knowledge-based energy functions provide us with a good approximation of real protein energetics. However, these energy functions are not very informative for search algorithms and fail to distinguish the types of amino acid interactions that contribute largely to the energy function from those that do not. As a result, search algorithms frequently get trapped into the local minima. On the other hand, the hydrophobic-polar (HP) model considers hydrophobic interactions only. The simplified nature of HP energy function makes it limited only to a low-resolution model. In this paper, we present a strategy to derive a non-uniform scaled version of the real 20×20 pairwise energy function. The non-uniform scaling helps tackle the difficulty faced by a real energy function, whereas the integration of 20×20 pairwise information overcomes the limitations faced by the HP energy function. Here, we have applied a derived energy function with a genetic algorithm on discrete lattices. On a standard set of benchmark protein sequences, our approach significantly outperforms the state-of-the-art methods for similar models. Our approach has been able to explore regions of the conformational space which all the previous methods have failed to explore. Effectiveness of the derived energy function is presented by showing qualitative differences and similarities of the sampled structures to the native structures. Number of objective function evaluation in a single run of the algorithm is used as a comparison metric to demonstrate efficiency.

Evolution of real contact area under shear and the value of static friction of soft materials.

PubMed

Sahli, R; Pallares, G; Ducottet, C; Ben Ali, I E; Al Akhrass, S; Guibert, M; Scheibert, J

2018-01-16

The frictional properties of a rough contact interface are controlled by its area of real contact, the dynamical variations of which underlie our modern understanding of the ubiquitous rate-and-state friction law. In particular, the real contact area is proportional to the normal load, slowly increases at rest through aging, and drops at slip inception. Here, through direct measurements on various contacts involving elastomers or human fingertips, we show that the real contact area also decreases under shear, with reductions as large as 30[Formula: see text], starting well before macroscopic sliding. All data are captured by a single reduction law enabling excellent predictions of the static friction force. In elastomers, the area-reduction rate of individual contacts obeys a scaling law valid from micrometer-sized junctions in rough contacts to millimeter-sized smooth sphere/plane contacts. For the class of soft materials used here, our results should motivate first-order improvements of current contact mechanics models and prompt reinterpretation of the rate-and-state parameters.

Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images

NASA Astrophysics Data System (ADS)

Yang, Bo; Wang, Mi; Xu, Wen; Li, Deren; Gong, Jianya; Pi, Yingdong

2017-12-01

The potential of large-scale block adjustment (BA) without ground control points (GCPs) has long been a concern among photogrammetric researchers, which is of effective guiding significance for global mapping. However, significant problems with the accuracy and efficiency of this method remain to be solved. In this study, we analyzed the effects of geometric errors on BA, and then developed a step-wise BA method to conduct integrated processing of large-scale ZY-3 satellite images without GCPs. We first pre-processed the BA data, by adopting a geometric calibration (GC) method based on the viewing-angle model to compensate for systematic errors, such that the BA input images were of good initial geometric quality. The second step was integrated BA without GCPs, in which a series of technical methods were used to solve bottleneck problems and ensure accuracy and efficiency. The BA model, based on virtual control points (VCPs), was constructed to address the rank deficiency problem caused by lack of absolute constraints. We then developed a parallel matching strategy to improve the efficiency of tie points (TPs) matching, and adopted a three-array data structure based on sparsity to relieve the storage and calculation burden of the high-order modified equation. Finally, we used the conjugate gradient method to improve the speed of solving the high-order equations. To evaluate the feasibility of the presented large-scale BA method, we conducted three experiments on real data collected by the ZY-3 satellite. The experimental results indicate that the presented method can effectively improve the geometric accuracies of ZY-3 satellite images. This study demonstrates the feasibility of large-scale mapping without GCPs.

Attacking Software Crisis: A Macro Approach.

DTIC Science & Technology

1985-03-01

Advisor X0774R.. Dyns, Second Reader W.R. Greer r. armn, Department of AAministrative Sciences Kneale rf. mrh- Dean of Information and Policy siences ...was at least originally intended to have practical value, that is, to satisfy some real need. Even the recent wave of game software for microcomputer...Comparing Online an" Offline Programming Performance, Communications of the ACM, January, 1968. 31. Schwartz, ,J. "Analyzing Large-Scale System

APPLICATION OF CDNA MICROARRAY TECHNOLOGY TO IN VITRO TOXICOLOGY AND THE SELECTION OF GENES FOR A REAL TIME RT-PCR-BASED SCREEN FOR OXIDATIVE STRESS IN HEP-G2 CELLS

EPA Science Inventory

Large-scale analysis of gene expression using cDNA microarrays promises the
rapid detection of the mode of toxicity for drugs and other chemicals. cDNA
microarrays were used to examine chemically-induced alterations of gene
expression in HepG2 cells exposed to oxidative ...

Full-color large-scaled computer-generated holograms for physical and non-physical objects

NASA Astrophysics Data System (ADS)

Matsushima, Kyoji; Tsuchiyama, Yasuhiro; Sonobe, Noriaki; Masuji, Shoya; Yamaguchi, Masahiro; Sakamoto, Yuji

2017-05-01

Several full-color high-definition CGHs are created for reconstructing 3D scenes including real-existing physical objects. The field of the physical objects are generated or captured by employing three techniques; 3D scanner, synthetic aperture digital holography, and multi-viewpoint images. Full-color reconstruction of high-definition CGHs is realized by RGB color filters. The optical reconstructions are presented for verifying these techniques.

Designing for Data with Ask Dr. Discovery: Design Approaches for Facilitating Museum Evaluation with Real-Time Data Mining

ERIC Educational Resources Information Center

Nelson, Brian C.; Bowman, Cassie; Bowman, Judd

2017-01-01

Ask Dr. Discovery is an NSF-funded study addressing the need for ongoing, large-scale museum evaluation while investigating new ways to encourage museum visitors to engage deeply with museum content. To realize these aims, we are developing and implementing a mobile app with two parts: (1) a front-end virtual scientist called Dr. Discovery (Dr. D)…

Emissions of CO2 and criteria air pollutants from mobile sources: Insights from integrating real-time traffic data into local air quality models

NASA Astrophysics Data System (ADS)

Gately, Conor; Hutyra, Lucy

2016-04-01

In 2013, on-road mobile sources were responsible for over 26% of U.S. fossil fuel carbon dioxide (ffCO2) emissions, and over 34% of both CO and NOx emissions. However, accurate representations of these emissions at the scale of urban areas remains a difficult challenge. Quantifying emissions at the scale of local streets and highways is critical to provide policymakers with the information needed to develop appropriate mitigation strategies and to guide research into the underlying process that drive mobile emissions. Quantification of vehicle ffCO2 emissions at high spatial and temporal resolutions requires a detailed synthesis of data on traffic activity, roadway attributes, fleet characteristics and vehicle speeds. To accurately characterize criteria air pollutant emissions, information on local meteorology is also critical, as the temperature and relative humidity can affect emissions rates of these pollutants by as much as 400%. As the health impacts of air pollutants are more severe for residents living in close proximity (<500m) to road sources, it is critical that inventories of these emissions rely on highly resolved source data to locate potential hot-spots of exposure. In this study we utilize real-time GPS estimates of vehicle speeds to estimate ffCO2 and criteria air pollutant emissions at multiple spatial and temporal scales across a large metropolitan area. We observe large variations in emissions associated with diurnal activity patterns, congestion, sporting and civic events, and weather anomalies. We discuss the advantages and challenges of using highly-resolved source data to quantify emissions at a roadway scale, and the potential of this methodology for forecasting the air quality impacts of changes in infrastructure, urban planning policies, and regional climate.

Emissions of CO2 and criteria air pollutants from mobile sources: Insights from integrating real-time traffic data into local air quality models

NASA Astrophysics Data System (ADS)

Gately, C.; Hutyra, L.; Sue Wing, I.; Peterson, S.; Janetos, A.

2015-12-01

In 2013, on-road mobile sources were responsible for over 26% of U.S. fossil fuel carbon dioxide (ffCO2) emissions, and over 34% of both CO and NOx emissions. However, accurate representations of these emissions at the scale of urban areas remains a difficult challenge. Quantifying emissions at the scale of local streets and highways is critical to provide policymakers with the information needed to develop appropriate mitigation strategies and to guide research into the underlying process that drive mobile emissions. Quantification of vehicle ffCO2 emissions at high spatial and temporal resolutions requires a detailed synthesis of data on traffic activity, roadway attributes, fleet characteristics and vehicle speeds. To accurately characterize criteria air pollutant emissions, information on local meteorology is also critical, as the temperature and relative humidity can affect emissions rates of these pollutants by as much as 400%. As the health impacts of air pollutants are more severe for residents living in close proximity (<500m) to road sources, it is critical that inventories of these emissions rely on highly resolved source data to locate potential hot-spots of exposure. In this study we utilize real-time GPS estimates of vehicle speeds to estimate ffCO2 and criteria air pollutant emissions at multiple spatial and temporal scales across a large metropolitan area. We observe large variations in emissions associated with diurnal activity patterns, congestion, sporting and civic events, and weather anomalies. We discuss the advantages and challenges of using highly-resolved source data to quantify emissions at a roadway scale, and the potential of this methodology for forecasting the air quality impacts of changes in infrastructure, urban planning policies, and regional climate.

Leveraging Large-Scale Semantic Networks for Adaptive Robot Task Learning and Execution.

PubMed

Boteanu, Adrian; St Clair, Aaron; Mohseni-Kabir, Anahita; Saldanha, Carl; Chernova, Sonia

2016-12-01

This work seeks to leverage semantic networks containing millions of entries encoding assertions of commonsense knowledge to enable improvements in robot task execution and learning. The specific application we explore in this project is object substitution in the context of task adaptation. Humans easily adapt their plans to compensate for missing items in day-to-day tasks, substituting a wrap for bread when making a sandwich, or stirring pasta with a fork when out of spoons. Robot plan execution, however, is far less robust, with missing objects typically leading to failure if the robot is not aware of alternatives. In this article, we contribute a context-aware algorithm that leverages the linguistic information embedded in the task description to identify candidate substitution objects without reliance on explicit object affordance information. Specifically, we show that the task context provided by the task labels within the action structure of a task plan can be leveraged to disambiguate information within a noisy large-scale semantic network containing hundreds of potential object candidates to identify successful object substitutions with high accuracy. We present two extensive evaluations of our work on both abstract and real-world robot tasks, showing that the substitutions made by our system are valid, accepted by users, and lead to a statistically significant reduction in robot learning time. In addition, we report the outcomes of testing our approach with a large number of crowd workers interacting with a robot in real time.

Statistical Mechanics of Turbulent Dynamos

NASA Technical Reports Server (NTRS)

Shebalin, John V.

2014-01-01

Incompressible magnetohydrodynamic (MHD) turbulence and magnetic dynamos, which occur in magnetofluids with large fluid and magnetic Reynolds numbers, will be discussed. When Reynolds numbers are large and energy decays slowly, the distribution of energy with respect to length scale becomes quasi-stationary and MHD turbulence can be described statistically. In the limit of infinite Reynolds numbers, viscosity and resistivity become zero and if these values are used in the MHD equations ab initio, a model system called ideal MHD turbulence results. This model system is typically confined in simple geometries with some form of homogeneous boundary conditions, allowing for velocity and magnetic field to be represented by orthogonal function expansions. One advantage to this is that the coefficients of the expansions form a set of nonlinearly interacting variables whose behavior can be described by equilibrium statistical mechanics, i.e., by a canonical ensemble theory based on the global invariants (energy, cross helicity and magnetic helicity) of ideal MHD turbulence. Another advantage is that truncated expansions provide a finite dynamical system whose time evolution can be numerically simulated to test the predictions of the associated statistical mechanics. If ensemble predictions are the same as time averages, then the system is said to be ergodic; if not, the system is nonergodic. Although it had been implicitly assumed in the early days of ideal MHD statistical theory development that these finite dynamical systems were ergodic, numerical simulations provided sufficient evidence that they were, in fact, nonergodic. Specifically, while canonical ensemble theory predicted that expansion coefficients would be (i) zero-mean random variables with (ii) energy that decreased with length scale, it was found that although (ii) was correct, (i) was not and the expected ergodicity was broken. The exact cause of this broken ergodicity was explained, after much investigation, by greatly extending the statistical theory of ideal MHD turbulence. The mathematical details of broken ergodicity, in fact, give a quantitative explanation of how coherent structure, dynamic alignment and force-free states appear in turbulent magnetofluids. The relevance of these ideal results to real MHD turbulence occurs because broken ergodicity is most manifest in the ideal case at the largest length scales and it is in these largest scales that a real magnetofluid has the least dissipation, i.e., most closely approaches the behavior of an ideal magnetofluid. Furthermore, the effects grow stronger when cross and magnetic helicities grow large with respect to energy, and this is exactly what occurs with time in a real magnetofluid, where it is called selective decay. The relevance of these results found in ideal MHD turbulence theory to the real world is that they provide at least a qualitative explanation of why confined turbulent magnetofluids, such as the liquid iron that fills the Earth's outer core, produce stationary, large-scale magnetic fields, i.e., the geomagnetic field. These results should also apply to other planets as well as to plasma confinement devices on Earth and in space, and the effects should be manifest if Reynolds numbers are high enough and there is enough time for stationarity to occur, at least approximately. In the presentation, details will be given for both theoretical and numerical results, and references will be provided.

Partition-of-unity finite-element method for large scale quantum molecular dynamics on massively parallel computational platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pask, J E; Sukumar, N; Guney, M

2011-02-28

Over the course of the past two decades, quantum mechanical calculations have emerged as a key component of modern materials research. However, the solution of the required quantum mechanical equations is a formidable task and this has severely limited the range of materials systems which can be investigated by such accurate, quantum mechanical means. The current state of the art for large-scale quantum simulations is the planewave (PW) method, as implemented in now ubiquitous VASP, ABINIT, and QBox codes, among many others. However, since the PW method uses a global Fourier basis, with strictly uniform resolution at all points inmore » space, and in which every basis function overlaps every other at every point, it suffers from substantial inefficiencies in calculations involving atoms with localized states, such as first-row and transition-metal atoms, and requires substantial nonlocal communications in parallel implementations, placing critical limits on scalability. In recent years, real-space methods such as finite-differences (FD) and finite-elements (FE) have been developed to address these deficiencies by reformulating the required quantum mechanical equations in a strictly local representation. However, while addressing both resolution and parallel-communications problems, such local real-space approaches have been plagued by one key disadvantage relative to planewaves: excessive degrees of freedom (grid points, basis functions) needed to achieve the required accuracies. And so, despite critical limitations, the PW method remains the standard today. In this work, we show for the first time that this key remaining disadvantage of real-space methods can in fact be overcome: by building known atomic physics into the solution process using modern partition-of-unity (PU) techniques in finite element analysis. Indeed, our results show order-of-magnitude reductions in basis size relative to state-of-the-art planewave based methods. The method developed here is completely general, applicable to any crystal symmetry and to both metals and insulators alike. We have developed and implemented a full self-consistent Kohn-Sham method, including both total energies and forces for molecular dynamics, and developed a full MPI parallel implementation for large-scale calculations. We have applied the method to the gamut of physical systems, from simple insulating systems with light atoms to complex d- and f-electron systems, requiring large numbers of atomic-orbital enrichments. In every case, the new PU FE method attained the required accuracies with substantially fewer degrees of freedom, typically by an order of magnitude or more, than the current state-of-the-art PW method. Finally, our initial MPI implementation has shown excellent parallel scaling of the most time-critical parts of the code up to 1728 processors, with clear indications of what will be required to achieve comparable scaling for the rest. Having shown that the key remaining disadvantage of real-space methods can in fact be overcome, the work has attracted significant attention: with sixteen invited talks, both domestic and international, so far; two papers published and another in preparation; and three new university and/or national laboratory collaborations, securing external funding to pursue a number of related research directions. Having demonstrated the proof of principle, work now centers on the necessary extensions and optimizations required to bring the prototype method and code delivered here to production applications.« less

MHD Turbulence and Magnetic Dynamos

NASA Technical Reports Server (NTRS)

Shebalin, John V

2014-01-01

Incompressible magnetohydrodynamic (MHD) turbulence and magnetic dynamos, which occur in magnetofluids with large fluid and magnetic Reynolds numbers, will be discussed. When Reynolds numbers are large and energy decays slowly, the distribution of energy with respect to length scale becomes quasi-stationary and MHD turbulence can be described statistically. In the limit of infinite Reynolds numbers, viscosity and resistivity become zero and if these values are used in the MHD equations ab initio, a model system called ideal MHD turbulence results. This model system is typically confined in simple geometries with some form of homogeneous boundary conditions, allowing for velocity and magnetic field to be represented by orthogonal function expansions. One advantage to this is that the coefficients of the expansions form a set of nonlinearly interacting variables whose behavior can be described by equilibrium statistical mechanics, i.e., by a canonical ensemble theory based on the global invariants (energy, cross helicity and magnetic helicity) of ideal MHD turbulence. Another advantage is that truncated expansions provide a finite dynamical system whose time evolution can be numerically simulated to test the predictions of the associated statistical mechanics. If ensemble predictions are the same as time averages, then the system is said to be ergodic; if not, the system is nonergodic. Although it had been implicitly assumed in the early days of ideal MHD statistical theory development that these finite dynamical systems were ergodic, numerical simulations provided sufficient evidence that they were, in fact, nonergodic. Specifically, while canonical ensemble theory predicted that expansion coefficients would be (i) zero-mean random variables with (ii) energy that decreased with length scale, it was found that although (ii) was correct, (i) was not and the expected ergodicity was broken. The exact cause of this broken ergodicity was explained, after much investigation, by greatly extending the statistical theory of ideal MHD turbulence. The mathematical details of broken ergodicity, in fact, give a quantitative explanation of how coherent structure, dynamic alignment and force-free states appear in turbulent magnetofluids. The relevance of these ideal results to real MHD turbulence occurs because broken ergodicity is most manifest in the ideal case at the largest length scales and it is in these largest scales that a real magnetofluid has the least dissipation, i.e., most closely approaches the behavior of an ideal magnetofluid. Furthermore, the effects grow stronger when cross and magnetic helicities grow large with respect to energy, and this is exactly what occurs with time in a real magnetofluid, where it is called selective decay. The relevance of these results found in ideal MHD turbulence theory to the real world is that they provide at least a qualitative explanation of why confined turbulent magnetofluids, such as the liquid iron that fills the Earth's outer core, produce stationary, large-scale magnetic fields, i.e., the geomagnetic field. These results should also apply to other planets as well as to plasma confinement devices on Earth and in space, and the effects should be manifest if Reynolds numbers are high enough and there is enough time for stationarity to occur, at least approximately. In the presentation, details will be given for both theoretical and numerical results, and references will be provided.

Decentralized Optimal Dispatch of Photovoltaic Inverters in Residential Distribution Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Dhople, Sairaj V.; Johnson, Brian B.

Summary form only given. Decentralized methods for computing optimal real and reactive power setpoints for residential photovoltaic (PV) inverters are developed in this paper. It is known that conventional PV inverter controllers, which are designed to extract maximum power at unity power factor, cannot address secondary performance objectives such as voltage regulation and network loss minimization. Optimal power flow techniques can be utilized to select which inverters will provide ancillary services, and to compute their optimal real and reactive power setpoints according to well-defined performance criteria and economic objectives. Leveraging advances in sparsity-promoting regularization techniques and semidefinite relaxation, this papermore » shows how such problems can be solved with reduced computational burden and optimality guarantees. To enable large-scale implementation, a novel algorithmic framework is introduced - based on the so-called alternating direction method of multipliers - by which optimal power flow-type problems in this setting can be systematically decomposed into sub-problems that can be solved in a decentralized fashion by the utility and customer-owned PV systems with limited exchanges of information. Since the computational burden is shared among multiple devices and the requirement of all-to-all communication can be circumvented, the proposed optimization approach scales favorably to large distribution networks.« less

Powering up with indirect reciprocity in a large-scale field experiment.

PubMed

Yoeli, Erez; Hoffman, Moshe; Rand, David G; Nowak, Martin A

2013-06-18

A defining aspect of human cooperation is the use of sophisticated indirect reciprocity. We observe others, talk about others, and act accordingly. We help those who help others, and we cooperate expecting that others will cooperate in return. Indirect reciprocity is based on reputation, which spreads by communication. A crucial aspect of indirect reciprocity is observability: reputation effects can support cooperation as long as peoples' actions can be observed by others. In evolutionary models of indirect reciprocity, natural selection favors cooperation when observability is sufficiently high. Complimenting this theoretical work are experiments where observability promotes cooperation among small groups playing games in the laboratory. Until now, however, there has been little evidence of observability's power to promote large-scale cooperation in real world settings. Here we provide such evidence using a field study involving 2413 subjects. We collaborated with a utility company to study participation in a program designed to prevent blackouts. We show that observability triples participation in this public goods game. The effect is over four times larger than offering a $25 monetary incentive, the company's previous policy. Furthermore, as predicted by indirect reciprocity, we provide evidence that reputational concerns are driving our observability effect. In sum, we show how indirect reciprocity can be harnessed to increase cooperation in a relevant, real-world public goods game.

A community detection algorithm using network topologies and rule-based hierarchical arc-merging strategies

PubMed Central

2017-01-01

The authors use four criteria to examine a novel community detection algorithm: (a) effectiveness in terms of producing high values of normalized mutual information (NMI) and modularity, using well-known social networks for testing; (b) examination, meaning the ability to examine mitigating resolution limit problems using NMI values and synthetic networks; (c) correctness, meaning the ability to identify useful community structure results in terms of NMI values and Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks; and (d) scalability, or the ability to produce comparable modularity values with fast execution times when working with large-scale real-world networks. In addition to describing a simple hierarchical arc-merging (HAM) algorithm that uses network topology information, we introduce rule-based arc-merging strategies for identifying community structures. Five well-studied social network datasets and eight sets of LFR benchmark networks were employed to validate the correctness of a ground-truth community, eight large-scale real-world complex networks were used to measure its efficiency, and two synthetic networks were used to determine its susceptibility to two resolution limit problems. Our experimental results indicate that the proposed HAM algorithm exhibited satisfactory performance efficiency, and that HAM-identified and ground-truth communities were comparable in terms of social and LFR benchmark networks, while mitigating resolution limit problems. PMID:29121100

Listeriolysin O Membrane Damaging Activity Involves Arc Formation and Lineaction -- Implication for Listeria monocytogenes Escape from Phagocytic Vacuole

PubMed Central

Ruan, Yi; Rezelj, Saša; Bedina Zavec, Apolonija; Anderluh, Gregor; Scheuring, Simon

2016-01-01

Listeriolysin-O (LLO) plays a crucial role during infection by Listeria monocytogenes. It enables escape of bacteria from phagocytic vacuole, which is the basis for its spread to other cells and tissues. It is not clear how LLO acts at phagosomal membranes to allow bacterial escape. The mechanism of action of LLO remains poorly understood, probably due to unavailability of suitable experimental tools that could monitor LLO membrane disruptive activity in real time. Here, we used high-speed atomic force microscopy (HS-AFM) featuring high spatio-temporal resolution on model membranes and optical microscopy on giant unilamellar vesicles (GUVs) to investigate LLO activity. We analyze the assembly kinetics of toxin oligomers, the prepore-to-pore transition dynamics and the membrane disruption in real time. We reveal that LLO toxin efficiency and mode of action as a membrane-disrupting agent varies strongly depending on the membrane cholesterol concentration and the environmental pH. We discovered that LLO is able to form arc pores as well as damage lipid membranes as a lineactant, and this leads to large-scale membrane defects. These results altogether provide a mechanistic basis of how large-scale membrane disruption leads to release of Listeria from the phagocytic vacuole in the cellular context. PMID:27104344

A study of the spreading scheme for viral marketing based on a complex network model

NASA Astrophysics Data System (ADS)

Yang, Jianmei; Yao, Canzhong; Ma, Weicheng; Chen, Guanrong

2010-02-01

Buzzword-based viral marketing, known also as digital word-of-mouth marketing, is a marketing mode attached to some carriers on the Internet, which can rapidly copy marketing information at a low cost. Viral marketing actually uses a pre-existing social network where, however, the scale of the pre-existing network is believed to be so large and so random, so that its theoretical analysis is intractable and unmanageable. There are very few reports in the literature on how to design a spreading scheme for viral marketing on real social networks according to the traditional marketing theory or the relatively new network marketing theory. Complex network theory provides a new model for the study of large-scale complex systems, using the latest developments of graph theory and computing techniques. From this perspective, the present paper extends the complex network theory and modeling into the research of general viral marketing and develops a specific spreading scheme for viral marking and an approach to design the scheme based on a real complex network on the QQ instant messaging system. This approach is shown to be rather universal and can be further extended to the design of various spreading schemes for viral marketing based on different instant messaging systems.

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System.

PubMed

Liu, Youda; Wang, Xue; Liu, Yanchi; Cui, Sujin

2016-08-18

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems.

Integrated situational awareness for cyber attack detection, analysis, and mitigation

NASA Astrophysics Data System (ADS)

Cheng, Yi; Sagduyu, Yalin; Deng, Julia; Li, Jason; Liu, Peng

2012-06-01

Real-time cyberspace situational awareness is critical for securing and protecting today's enterprise networks from various cyber threats. When a security incident occurs, network administrators and security analysts need to know what exactly has happened in the network, why it happened, and what actions or countermeasures should be taken to quickly mitigate the potential impacts. In this paper, we propose an integrated cyberspace situational awareness system for efficient cyber attack detection, analysis and mitigation in large-scale enterprise networks. Essentially, a cyberspace common operational picture will be developed, which is a multi-layer graphical model and can efficiently capture and represent the statuses, relationships, and interdependencies of various entities and elements within and among different levels of a network. Once shared among authorized users, this cyberspace common operational picture can provide an integrated view of the logical, physical, and cyber domains, and a unique visualization of disparate data sets to support decision makers. In addition, advanced analyses, such as Bayesian Network analysis, will be explored to address the information uncertainty, dynamic and complex cyber attack detection, and optimal impact mitigation issues. All the developed technologies will be further integrated into an automatic software toolkit to achieve near real-time cyberspace situational awareness and impact mitigation in large-scale computer networks.

Multifractal analysis and topological properties of a new family of weighted Koch networks

NASA Astrophysics Data System (ADS)

Huang, Da-Wen; Yu, Zu-Guo; Anh, Vo

2017-03-01

Weighted complex networks, especially scale-free networks, which characterize real-life systems better than non-weighted networks, have attracted considerable interest in recent years. Studies on the multifractality of weighted complex networks are still to be undertaken. In this paper, inspired by the concepts of Koch networks and Koch island, we propose a new family of weighted Koch networks, and investigate their multifractal behavior and topological properties. We find some key topological properties of the new networks: their vertex cumulative strength has a power-law distribution; there is a power-law relationship between their topological degree and weight strength; the networks have a high weighted clustering coefficient of 0.41004 (which is independent of the scaling factor c) in the limit of large generation t; the second smallest eigenvalue μ2 and the maximum eigenvalue μn are approximated by quartic polynomials of the scaling factor c for the general Laplacian operator, while μ2 is approximately a quartic polynomial of c and μn= 1.5 for the normalized Laplacian operator. Then, we find that weighted koch networks are both fractal and multifractal, their fractal dimension is influenced by the scaling factor c. We also apply these analyses to six real-world networks, and find that the multifractality in three of them are strong.

Robust real-time cell analysis method for determining viral infectious titers during development of a viral vaccine production process.

PubMed

Charretier, Cédric; Saulnier, Aure; Benair, Loïc; Armanet, Corinne; Bassard, Isabelle; Daulon, Sandra; Bernigaud, Bertrand; Rodrigues de Sousa, Emanuel; Gonthier, Clémence; Zorn, Edouard; Vetter, Emmanuelle; Saintpierre, Claire; Riou, Patrice; Gaillac, David

2018-02-01

The classical cell-culture methods, such as cell culture infectious dose 50% (CCID 50 ) assays, are time-consuming, end-point assays currently used during the development of a viral vaccine production process to measure viral infectious titers. However, they are not suitable for handling the large number of tests required for high-throughput and large-scale screening analyses. Impedance-based bio-sensing techniques used in real-time cell analysis (RTCA) to assess cell layer biological status in vitro, provide real-time data. In this proof-of-concept study, we assessed the correlation between the results from CCID 50 and RTCA assays and compared time and costs using monovalent and tetravalent chimeric yellow fever dengue (CYD) vaccine strains. For the RTCA assay, Vero cells were infected with the CYD sample and real-time impedance was recorded, using the dimensionless cell index (CI). The CI peaked just after infection and decreased as the viral cytopathic effect occurred in a dose-dependent manner. The time to the median CI (CIT med ) was correlated with viral titers determined by CCID 50 over a range of about 4-5log 10 CCID 50 /ml. This in-house RTCA virus-titration assay was shown to be a robust method for determining real-time viral infectious titers, and could be an alternative to the classical CCID 50 assay during the development of viral vaccine production process. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Classification of Large-Scale Remote Sensing Images for Automatic Identification of Health Hazards: Smoke Detection Using an Autologistic Regression Classifier.

PubMed

Wolters, Mark A; Dean, C B

2017-01-01

Remote sensing images from Earth-orbiting satellites are a potentially rich data source for monitoring and cataloguing atmospheric health hazards that cover large geographic regions. A method is proposed for classifying such images into hazard and nonhazard regions using the autologistic regression model, which may be viewed as a spatial extension of logistic regression. The method includes a novel and simple approach to parameter estimation that makes it well suited to handling the large and high-dimensional datasets arising from satellite-borne instruments. The methodology is demonstrated on both simulated images and a real application to the identification of forest fire smoke.

Towards Scalable Graph Computation on Mobile Devices.

PubMed

Chen, Yiqi; Lin, Zhiyuan; Pienta, Robert; Kahng, Minsuk; Chau, Duen Horng

2014-10-01

Mobile devices have become increasingly central to our everyday activities, due to their portability, multi-touch capabilities, and ever-improving computational power. Such attractive features have spurred research interest in leveraging mobile devices for computation. We explore a novel approach that aims to use a single mobile device to perform scalable graph computation on large graphs that do not fit in the device's limited main memory, opening up the possibility of performing on-device analysis of large datasets, without relying on the cloud. Based on the familiar memory mapping capability provided by today's mobile operating systems, our approach to scale up computation is powerful and intentionally kept simple to maximize its applicability across the iOS and Android platforms. Our experiments demonstrate that an iPad mini can perform fast computation on large real graphs with as many as 272 million edges (Google+ social graph), at a speed that is only a few times slower than a 13″ Macbook Pro. Through creating a real world iOS app with this technique, we demonstrate the strong potential application for scalable graph computation on a single mobile device using our approach.

SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data.

PubMed

Salehi, Ali; Jimenez-Berni, Jose; Deery, David M; Palmer, Doug; Holland, Edward; Rozas-Larraondo, Pablo; Chapman, Scott C; Georgakopoulos, Dimitrios; Furbank, Robert T

2015-01-01

To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au.

Atomic displacements in the charge ice pyrochlore Bi2Ti2O6O' studied by neutron total scattering

NASA Astrophysics Data System (ADS)

Shoemaker, Daniel P.; Seshadri, Ram; Hector, Andrew L.; Llobet, Anna; Proffen, Thomas; Fennie, Craig J.

2010-04-01

The oxide pyrochlore Bi2Ti2O6O' is known to be associated with large displacements of Bi and O' atoms from their ideal crystallographic positions. Neutron total scattering, analyzed in both reciprocal and real space, is employed here to understand the nature of these displacements. Rietveld analysis and maximum entropy methods are used to produce an average picture of the structural nonideality. Local structure is modeled via large-box reverse Monte Carlo simulations constrained simultaneously by the Bragg profile and real-space pair distribution function. Direct visualization and statistical analyses of these models show the precise nature of the static Bi and O' displacements. Correlations between neighboring Bi displacements are analyzed using coordinates from the large-box simulations. The framework of continuous symmetry measures has been applied to distributions of O'Bi4 tetrahedra to examine deviations from ideality. Bi displacements from ideal positions appear correlated over local length scales. The results are consistent with the idea that these nonmagnetic lone-pair containing pyrochlore compounds can be regarded as highly structurally frustrated systems.

Towards Scalable Graph Computation on Mobile Devices

PubMed Central

Chen, Yiqi; Lin, Zhiyuan; Pienta, Robert; Kahng, Minsuk; Chau, Duen Horng

2015-01-01

Mobile devices have become increasingly central to our everyday activities, due to their portability, multi-touch capabilities, and ever-improving computational power. Such attractive features have spurred research interest in leveraging mobile devices for computation. We explore a novel approach that aims to use a single mobile device to perform scalable graph computation on large graphs that do not fit in the device's limited main memory, opening up the possibility of performing on-device analysis of large datasets, without relying on the cloud. Based on the familiar memory mapping capability provided by today's mobile operating systems, our approach to scale up computation is powerful and intentionally kept simple to maximize its applicability across the iOS and Android platforms. Our experiments demonstrate that an iPad mini can perform fast computation on large real graphs with as many as 272 million edges (Google+ social graph), at a speed that is only a few times slower than a 13″ Macbook Pro. Through creating a real world iOS app with this technique, we demonstrate the strong potential application for scalable graph computation on a single mobile device using our approach. PMID:25859564

Optical power transfer and communication methods for wireless implantable sensing platforms.

PubMed

Mujeeb-U-Rahman, Muhammad; Adalian, Dvin; Chang, Chieh-Feng; Scherer, Axel

2015-09-01

Ultrasmall scale implants have recently attracted focus as valuable tools for monitoring both acute and chronic diseases. Semiconductor optical technologies are the key to miniaturizing these devices to the long-sought sub-mm scale, which will enable long-term use of these devices for medical applications. This can also enable the use of multiple implantable devices concurrently to form a true body area network of sensors. We demonstrate optical power transfer techniques and methods to effectively harness this power for implantable devices. Furthermore, we also present methods for optical data transfer from such implants. Simultaneous use of these technologies can result in miniaturized sensing platforms that can allow for large-scale use of such systems in real world applications.

A scanning tunneling microscope with a scanning range from hundreds of micrometers down to nanometer resolution.

PubMed

Kalkan, Fatih; Zaum, Christopher; Morgenstern, Karina

2012-10-01

A beetle type stage and a flexure scanning stage are combined to form a two stages scanning tunneling microscope (STM). It operates at room temperature in ultrahigh vacuum and is capable of scanning areas up to 300 μm × 450 μm down to resolution on the nanometer scale. This multi-scale STM has been designed and constructed in order to investigate prestructured metallic or semiconducting micro- and nano-structures in real space from atomic-sized structures up to the large-scale environment. The principle of the instrument is demonstrated on two different systems. Gallium nitride based micropillars demonstrate scan areas up to hundreds of micrometers; a Au(111) surface demonstrates nanometer resolution.

Optical power transfer and communication methods for wireless implantable sensing platforms

NASA Astrophysics Data System (ADS)

Mujeeb-U-Rahman, Muhammad; Adalian, Dvin; Chang, Chieh-Feng; Scherer, Axel

2015-09-01

Ultrasmall scale implants have recently attracted focus as valuable tools for monitoring both acute and chronic diseases. Semiconductor optical technologies are the key to miniaturizing these devices to the long-sought sub-mm scale, which will enable long-term use of these devices for medical applications. This can also enable the use of multiple implantable devices concurrently to form a true body area network of sensors. We demonstrate optical power transfer techniques and methods to effectively harness this power for implantable devices. Furthermore, we also present methods for optical data transfer from such implants. Simultaneous use of these technologies can result in miniaturized sensing platforms that can allow for large-scale use of such systems in real world applications.

Method of Real-Time Principal-Component Analysis

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu

2005-01-01

Dominant-element-based gradient descent and dynamic initial learning rate (DOGEDYN) is a method of sequential principal-component analysis (PCA) that is well suited for such applications as data compression and extraction of features from sets of data. In comparison with a prior method of gradient-descent-based sequential PCA, this method offers a greater rate of learning convergence. Like the prior method, DOGEDYN can be implemented in software. However, the main advantage of DOGEDYN over the prior method lies in the facts that it requires less computation and can be implemented in simpler hardware. It should be possible to implement DOGEDYN in compact, low-power, very-large-scale integrated (VLSI) circuitry that could process data in real time.

Application of computational aero-acoustics to real world problems

NASA Technical Reports Server (NTRS)

Hardin, Jay C.

1996-01-01

The application of computational aeroacoustics (CAA) to real problems is discussed in relation to the analysis performed with the aim of assessing the application of the various techniques. It is considered that the applications are limited by the inability of the computational resources to resolve the large range of scales involved in high Reynolds number flows. Possible simplifications are discussed. It is considered that problems remain to be solved in relation to the efficient use of the power of parallel computers and in the development of turbulent modeling schemes. The goal of CAA is stated as being the implementation of acoustic design studies on a computer terminal with reasonable run times.

Cascading failures and the emergence of cooperation in evolutionary-game based models of social and economical networks.

PubMed

Wang, Wen-Xu; Lai, Ying-Cheng; Armbruster, Dieter

2011-09-01

We study catastrophic behaviors in large networked systems in the paradigm of evolutionary games by incorporating a realistic "death" or "bankruptcy" mechanism. We find that a cascading bankruptcy process can arise when defection strategies exist and individuals are vulnerable to deficit. Strikingly, we observe that, after the catastrophic cascading process terminates, cooperators are the sole survivors, regardless of the game types and of the connection patterns among individuals as determined by the topology of the underlying network. It is necessary that individuals cooperate with each other to survive the catastrophic failures. Cooperation thus becomes the optimal strategy and absolutely outperforms defection in the game evolution with respect to the "death" mechanism. Our results can be useful for understanding large-scale catastrophe in real-world systems and in particular, they may yield insights into significant social and economical phenomena such as large-scale failures of financial institutions and corporations during an economic recession.

Cascading failures and the emergence of cooperation in evolutionary-game based models of social and economical networks

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Armbruster, Dieter

2011-09-01

We study catastrophic behaviors in large networked systems in the paradigm of evolutionary games by incorporating a realistic "death" or "bankruptcy" mechanism. We find that a cascading bankruptcy process can arise when defection strategies exist and individuals are vulnerable to deficit. Strikingly, we observe that, after the catastrophic cascading process terminates, cooperators are the sole survivors, regardless of the game types and of the connection patterns among individuals as determined by the topology of the underlying network. It is necessary that individuals cooperate with each other to survive the catastrophic failures. Cooperation thus becomes the optimal strategy and absolutely outperforms defection in the game evolution with respect to the "death" mechanism. Our results can be useful for understanding large-scale catastrophe in real-world systems and in particular, they may yield insights into significant social and economical phenomena such as large-scale failures of financial institutions and corporations during an economic recession.

Collective behavior of large-scale neural networks with GPU acceleration.

PubMed

Qu, Jingyi; Wang, Rubin

2017-12-01

In this paper, the collective behaviors of a small-world neuronal network motivated by the anatomy of a mammalian cortex based on both Izhikevich model and Rulkov model are studied. The Izhikevich model can not only reproduce the rich behaviors of biological neurons but also has only two equations and one nonlinear term. Rulkov model is in the form of difference equations that generate a sequence of membrane potential samples in discrete moments of time to improve computational efficiency. These two models are suitable for the construction of large scale neural networks. By varying some key parameters, such as the connection probability and the number of nearest neighbor of each node, the coupled neurons will exhibit types of temporal and spatial characteristics. It is demonstrated that the implementation of GPU can achieve more and more acceleration than CPU with the increasing of neuron number and iterations. These two small-world network models and GPU acceleration give us a new opportunity to reproduce the real biological network containing a large number of neurons.

Reconstructing high-dimensional two-photon entangled states via compressive sensing

PubMed Central

Tonolini, Francesco; Chan, Susan; Agnew, Megan; Lindsay, Alan; Leach, Jonathan

2014-01-01

Accurately establishing the state of large-scale quantum systems is an important tool in quantum information science; however, the large number of unknown parameters hinders the rapid characterisation of such states, and reconstruction procedures can become prohibitively time-consuming. Compressive sensing, a procedure for solving inverse problems by incorporating prior knowledge about the form of the solution, provides an attractive alternative to the problem of high-dimensional quantum state characterisation. Using a modified version of compressive sensing that incorporates the principles of singular value thresholding, we reconstruct the density matrix of a high-dimensional two-photon entangled system. The dimension of each photon is equal to d = 17, corresponding to a system of 83521 unknown real parameters. Accurate reconstruction is achieved with approximately 2500 measurements, only 3% of the total number of unknown parameters in the state. The algorithm we develop is fast, computationally inexpensive, and applicable to a wide range of quantum states, thus demonstrating compressive sensing as an effective technique for measuring the state of large-scale quantum systems. PMID:25306850

Neural encoding of large-scale three-dimensional space-properties and constraints.

PubMed

Jeffery, Kate J; Wilson, Jonathan J; Casali, Giulio; Hayman, Robin M

2015-01-01

How the brain represents represent large-scale, navigable space has been the topic of intensive investigation for several decades, resulting in the discovery that neurons in a complex network of cortical and subcortical brain regions co-operatively encode distance, direction, place, movement etc. using a variety of different sensory inputs. However, such studies have mainly been conducted in simple laboratory settings in which animals explore small, two-dimensional (i.e., flat) arenas. The real world, by contrast, is complex and three dimensional with hills, valleys, tunnels, branches, and-for species that can swim or fly-large volumetric spaces. Adding an additional dimension to space adds coding challenges, a primary reason for which is that several basic geometric properties are different in three dimensions. This article will explore the consequences of these challenges for the establishment of a functional three-dimensional metric map of space, one of which is that the brains of some species might have evolved to reduce the dimensionality of the representational space and thus sidestep some of these problems.

Experimental Quantification of Pore-Scale Flow Phenomena in 2D Heterogeneous Porous Micromodels: Multiphase Flow Towards Coupled Solid-Liquid Interactions

NASA Astrophysics Data System (ADS)

Li, Y.; Kazemifar, F.; Blois, G.; Christensen, K. T.

2017-12-01

Geological sequestration of CO2 within saline aquifers is a viable technology for reducing CO2 emissions. Central to this goal is accurately predicting both the fidelity of candidate sites pre-injection of CO2 and its post-injection migration. Moreover, local fluid pressure buildup may cause activation of small pre-existing unidentified faults, leading to micro-seismic events, which could prove disastrous for societal acceptance of CCS, and possibly compromise seal integrity. Recent evidence shows that large-scale events are coupled with pore-scale phenomena, which necessitates the representation of pore-scale stress, strain, and multiphase flow processes in large-scale modeling. To this end, the pore-scale flow of water and liquid/supercritical CO2 is investigated under reservoir-relevant conditions, over a range of wettability conditions in 2D heterogeneous micromodels that reflect the complexity of a real sandstone. High-speed fluorescent microscopy, complemented by a fast differential pressure transmitter, allows for simultaneous measurement of the flow field within and the instantaneous pressure drop across the micromodels. A flexible micromodel is also designed and fabricated, to be used in conjunction with the micro-PIV technique, enabling the quantification of coupled solid-liquid interactions.

Studies into the averaging problem: Macroscopic gravity and precision cosmology

NASA Astrophysics Data System (ADS)

Wijenayake, Tharake S.

2016-08-01

With the tremendous improvement in the precision of available astrophysical data in the recent past, it becomes increasingly important to examine some of the underlying assumptions behind the standard model of cosmology and take into consideration nonlinear and relativistic corrections which may affect it at percent precision level. Due to its mathematical rigor and fully covariant and exact nature, Zalaletdinov's macroscopic gravity (MG) is arguably one of the most promising frameworks to explore nonlinearities due to inhomogeneities in the real Universe. We study the application of MG to precision cosmology, focusing on developing a self-consistent cosmology model built on the averaging framework that adequately describes the large-scale Universe and can be used to study real data sets. We first implement an algorithmic procedure using computer algebra systems to explore new exact solutions to the MG field equations. After validating the process with an existing isotropic solution, we derive a new homogeneous, anisotropic and exact solution. Next, we use the simplest (and currently only) solvable homogeneous and isotropic model of MG and obtain an observable function for cosmological expansion using some reasonable assumptions on light propagation. We find that the principal modification to the angular diameter distance is through the change in the expansion history. We then linearize the MG field equations and derive a framework that contains large-scale structure, but the small scale inhomogeneities have been smoothed out and encapsulated into an additional cosmological parameter representing the averaging effect. We derive an expression for the evolution of the density contrast and peculiar velocities and integrate them to study the growth rate of large-scale structure. We find that increasing the magnitude of the averaging term leads to enhanced growth at late times. Thus, for the same matter content, the growth rate of large scale structure in the MG model is stronger than that of the standard model. Finally, we constrain the MG model using Cosmic Microwave Background temperature anisotropy data, the distance to supernovae data, the galaxy power spectrum, the weak lensing tomography shear-shear cross-correlations and the baryonic acoustic oscillations. We find that for this model the averaging density parameter is very small and does not cause any significant shift in the other cosmological parameters. However, it can lead to increased errors on some cosmological parameters such as the Hubble constant and the amplitude of the linear matter spectrum at the scale of 8h. {-1}Mpc. Further studiesare needed to explore other solutions and models of MG as well as their effects on precision cosmology.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

PubMed Central

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

Oak Ridge Bio-surveillance Toolkit (ORBiT): Integrating Big-Data Analytics with Visual Analysis for Public Health Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramanathan, Arvind; Pullum, Laura L; Steed, Chad A

In this position paper, we describe the design and implementation of the Oak Ridge Bio-surveillance Toolkit (ORBiT): a collection of novel statistical and machine learning tools implemented for (1) integrating heterogeneous traditional (e.g. emergency room visits, prescription sales data, etc.) and non-traditional (social media such as Twitter and Instagram) data sources, (2) analyzing large-scale datasets and (3) presenting the results from the analytics as a visual interface for the end-user to interact and provide feedback. We present examples of how ORBiT can be used to summarize ex- tremely large-scale datasets effectively and how user interactions can translate into the datamore » analytics process for bio-surveillance. We also present a strategy to estimate parameters relevant to dis- ease spread models from near real time data feeds and show how these estimates can be integrated with disease spread models for large-scale populations. We conclude with a perspective on how integrating data and visual analytics could lead to better forecasting and prediction of disease spread as well as improved awareness of disease susceptible regions.« less

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specifically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. (See CASI ID 20100021910 for supplemental data disk.)

On supervised graph Laplacian embedding CA model & kernel construction and its application

NASA Astrophysics Data System (ADS)

Zeng, Junwei; Qian, Yongsheng; Wang, Min; Yang, Yongzhong

2017-01-01

There are many methods to construct kernel with given data attribute information. Gaussian radial basis function (RBF) kernel is one of the most popular ways to construct a kernel. The key observation is that in real-world data, besides the data attribute information, data label information also exists, which indicates the data class. In order to make use of both data attribute information and data label information, in this work, we propose a supervised kernel construction method. Supervised information from training data is integrated into standard kernel construction process to improve the discriminative property of resulting kernel. A supervised Laplacian embedding cellular automaton model is another key application developed for two-lane heterogeneous traffic flow with the safe distance and large-scale truck. Based on the properties of traffic flow in China, we re-calibrate the cell length, velocity, random slowing mechanism and lane-change conditions and use simulation tests to study the relationships among the speed, density and flux. The numerical results show that the large-scale trucks will have great effects on the traffic flow, which are relevant to the proportion of the large-scale trucks, random slowing rate and the times of the lane space change.

Decomposition method for fast computation of gigapixel-sized Fresnel holograms on a graphics processing unit cluster.

PubMed

Jackin, Boaz Jessie; Watanabe, Shinpei; Ootsu, Kanemitsu; Ohkawa, Takeshi; Yokota, Takashi; Hayasaki, Yoshio; Yatagai, Toyohiko; Baba, Takanobu

2018-04-20

A parallel computation method for large-size Fresnel computer-generated hologram (CGH) is reported. The method was introduced by us in an earlier report as a technique for calculating Fourier CGH from 2D object data. In this paper we extend the method to compute Fresnel CGH from 3D object data. The scale of the computation problem is also expanded to 2 gigapixels, making it closer to real application requirements. The significant feature of the reported method is its ability to avoid communication overhead and thereby fully utilize the computing power of parallel devices. The method exhibits three layers of parallelism that favor small to large scale parallel computing machines. Simulation and optical experiments were conducted to demonstrate the workability and to evaluate the efficiency of the proposed technique. A two-times improvement in computation speed has been achieved compared to the conventional method, on a 16-node cluster (one GPU per node) utilizing only one layer of parallelism. A 20-times improvement in computation speed has been estimated utilizing two layers of parallelism on a very large-scale parallel machine with 16 nodes, where each node has 16 GPUs.

New Probe of Departures from General Relativity Using Minkowski Functionals.

PubMed

Fang, Wenjuan; Li, Baojiu; Zhao, Gong-Bo

2017-05-05

The morphological properties of the large scale structure of the Universe can be fully described by four Minkowski functionals (MFs), which provide important complementary information to other statistical observables such as the widely used 2-point statistics in configuration and Fourier spaces. In this work, for the first time, we present the differences in the morphology of the large scale structure caused by modifications to general relativity (to address the cosmic acceleration problem), by measuring the MFs from N-body simulations of modified gravity and general relativity. We find strong statistical power when using the MFs to constrain modified theories of gravity: with a galaxy survey that has survey volume ∼0.125(h^{-1}  Gpc)^{3} and galaxy number density ∼1/(h^{-1}  Mpc)^{3}, the two normal-branch Dvali-Gabadadze-Porrati models and the F5 f(R) model that we simulated can be discriminated from the ΛCDM model at a significance level ≳5σ with an individual MF measurement. Therefore, the MF of the large scale structure is potentially a powerful probe of gravity, and its application to real data deserves active exploration.

High Accuracy Monocular SFM and Scale Correction for Autonomous Driving.

PubMed

Song, Shiyu; Chandraker, Manmohan; Guest, Clark C

2016-04-01

We present a real-time monocular visual odometry system that achieves high accuracy in real-world autonomous driving applications. First, we demonstrate robust monocular SFM that exploits multithreading to handle driving scenes with large motions and rapidly changing imagery. To correct for scale drift, we use known height of the camera from the ground plane. Our second contribution is a novel data-driven mechanism for cue combination that allows highly accurate ground plane estimation by adapting observation covariances of multiple cues, such as sparse feature matching and dense inter-frame stereo, based on their relative confidences inferred from visual data on a per-frame basis. Finally, we demonstrate extensive benchmark performance and comparisons on the challenging KITTI dataset, achieving accuracy comparable to stereo and exceeding prior monocular systems. Our SFM system is optimized to output pose within 50 ms in the worst case, while average case operation is over 30 fps. Our framework also significantly boosts the accuracy of applications like object localization that rely on the ground plane.

Scalable DB+IR Technology: Processing Probabilistic Datalog with HySpirit.

PubMed

Frommholz, Ingo; Roelleke, Thomas

2016-01-01

Probabilistic Datalog (PDatalog, proposed in 1995) is a probabilistic variant of Datalog and a nice conceptual idea to model Information Retrieval in a logical, rule-based programming paradigm. Making PDatalog work in real-world applications requires more than probabilistic facts and rules, and the semantics associated with the evaluation of the programs. We report in this paper some of the key features of the HySpirit system required to scale the execution of PDatalog programs. Firstly, there is the requirement to express probability estimation in PDatalog. Secondly, fuzzy-like predicates are required to model vague predicates (e.g. vague match of attributes such as age or price). Thirdly, to handle large data sets there are scalability issues to be addressed, and therefore, HySpirit provides probabilistic relational indexes and parallel and distributed processing . The main contribution of this paper is a consolidated view on the methods of the HySpirit system to make PDatalog applicable in real-scale applications that involve a wide range of requirements typical for data (information) management and analysis.

Convective aggregation in idealised models and realistic equatorial cases

NASA Astrophysics Data System (ADS)

Holloway, Chris

2015-04-01

Idealised explicit convection simulations of the Met Office Unified Model are shown to exhibit spontaneous self-aggregation in radiative-convective equilibrium, as seen previously in other models in several recent studies. This self-aggregation is linked to feedbacks between radiation, surface fluxes, and convection, and the organization is intimately related to the evolution of the column water vapour (CWV) field. To investigate the relevance of this behaviour to the real world, these idealized simulations are compared with five 15-day cases of real organized convection in the tropics, including multiple simulations of each case testing sensitivities of the convective organization and mean states to interactive radiation, interactive surface fluxes, and evaporation of rain. Despite similar large-scale forcing via lateral boundary conditions, systematic differences in mean CWV, CWV distribution shape, and the length scale of CWV features are found between the different sensitivity runs, showing that there are at least some similarities in sensitivities to these feedbacks in both idealized and realistic simulations.

Convective aggregation in idealised models and realistic equatorial cases

NASA Astrophysics Data System (ADS)

Holloway, C. E.

2014-12-01

Idealised explicit convection simulations of the Met Office Unified Model are shown to exhibit spontaneous self-aggregation in radiative-convective equilibrium, as seen previously in other models in several recent studies. This self-aggregation is linked to feedbacks between radiation, surface fluxes, and convection, and the organization is intimately related to the evolution of the column water vapor (CWV) field. To investigate the relevance of this behavior to the real world, these idealized simulations are compared with five 15-day cases of real organized convection in the tropics, including multiple simulations of each case testing sensitivities of the convective organization and mean states to interactive radiation, interactive surface fluxes, and evaporation of rain. Despite similar large-scale forcing via lateral boundary conditions, systematic differences in mean CWV, CWV distribution shape, and the length scale of CWV features are found between the different sensitivity runs, showing that there are at least some similarities in sensitivities to these feedbacks in both idealized and realistic simulations.

A neurorobotic platform for locomotor prosthetic development in rats and mice

NASA Astrophysics Data System (ADS)

von Zitzewitz, Joachim; Asboth, Leonie; Fumeaux, Nicolas; Hasse, Alexander; Baud, Laetitia; Vallery, Heike; Courtine, Grégoire

2016-04-01

Objectives. We aimed to develop a robotic interface capable of providing finely-tuned, multidirectional trunk assistance adjusted in real-time during unconstrained locomotion in rats and mice. Approach. We interfaced a large-scale robotic structure actuated in four degrees of freedom to exchangeable attachment modules exhibiting selective compliance along distinct directions. This combination allowed high-precision force and torque control in multiple directions over a large workspace. We next designed a neurorobotic platform wherein real-time kinematics and physiological signals directly adjust robotic actuation and prosthetic actions. We tested the performance of this platform in both rats and mice with spinal cord injury. Main Results. Kinematic analyses showed that the robotic interface did not impede locomotor movements of lightweight mice that walked freely along paths with changing directions and height profiles. Personalized trunk assistance instantly enabled coordinated locomotion in mice and rats with severe hindlimb motor deficits. Closed-loop control of robotic actuation based on ongoing movement features enabled real-time control of electromyographic activity in anti-gravity muscles during locomotion. Significance. This neurorobotic platform will support the study of the mechanisms underlying the therapeutic effects of locomotor prosthetics and rehabilitation using high-resolution genetic tools in rodent models.

A neurorobotic platform for locomotor prosthetic development in rats and mice.

PubMed

von Zitzewitz, Joachim; Asboth, Leonie; Fumeaux, Nicolas; Hasse, Alexander; Baud, Laetitia; Vallery, Heike; Courtine, Grégoire

2016-04-01

We aimed to develop a robotic interface capable of providing finely-tuned, multidirectional trunk assistance adjusted in real-time during unconstrained locomotion in rats and mice. We interfaced a large-scale robotic structure actuated in four degrees of freedom to exchangeable attachment modules exhibiting selective compliance along distinct directions. This combination allowed high-precision force and torque control in multiple directions over a large workspace. We next designed a neurorobotic platform wherein real-time kinematics and physiological signals directly adjust robotic actuation and prosthetic actions. We tested the performance of this platform in both rats and mice with spinal cord injury. Kinematic analyses showed that the robotic interface did not impede locomotor movements of lightweight mice that walked freely along paths with changing directions and height profiles. Personalized trunk assistance instantly enabled coordinated locomotion in mice and rats with severe hindlimb motor deficits. Closed-loop control of robotic actuation based on ongoing movement features enabled real-time control of electromyographic activity in anti-gravity muscles during locomotion. This neurorobotic platform will support the study of the mechanisms underlying the therapeutic effects of locomotor prosthetics and rehabilitation using high-resolution genetic tools in rodent models.

Thirty Meter Telescope narrow-field infrared adaptive optics system real-time controller prototyping results

NASA Astrophysics Data System (ADS)

Smith, Malcolm; Kerley, Dan; Chapin, Edward L.; Dunn, Jennifer; Herriot, Glen; Véran, Jean-Pierre; Boyer, Corinne; Ellerbroek, Brent; Gilles, Luc; Wang, Lianqi

2016-07-01

Prototyping and benchmarking was performed for the Real-Time Controller (RTC) of the Narrow Field InfraRed Adaptive Optics System (NFIRAOS). To perform wavefront correction, NFIRAOS utilizes two deformable mirrors (DM) and one tip/tilt stage (TTS). The RTC receives wavefront information from six Laser Guide Star (LGS) Shack- Hartmann WaveFront Sensors (WFS), one high-order Natural Guide Star Pyramid WaveFront Sensor (PWFS) and multiple low-order instrument detectors. The RTC uses this information to determine the commands to send to the wavefront correctors. NFIRAOS is the first light AO system for the Thirty Meter Telescope (TMT). The prototyping was performed using dual-socket high performance Linux servers with the real-time (PREEMPT_RT) patch and demonstrated the viability of a commercial off-the-shelf (COTS) hardware approach to large scale AO reconstruction. In particular, a large custom matrix vector multiplication (MVM) was benchmarked which met the required latency requirements. In addition all major inter-machine communication was verified to be adequate using 10Gb and 40Gb Ethernet. The results of this prototyping has enabled a CPU-based NFIRAOS RTC design to proceed with confidence and that COTS hardware can be used to meet the demanding performance requirements.

Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications.

PubMed

Minor, Bryan; Doppa, Janardhan Rao; Cook, Diane J

2017-12-01

Recent progress in Internet of Things (IoT) platforms has allowed us to collect large amounts of sensing data. However, there are significant challenges in converting this large-scale sensing data into decisions for real-world applications. Motivated by applications like health monitoring and intervention and home automation we consider a novel problem called Activity Prediction , where the goal is to predict future activity occurrence times from sensor data. In this paper, we make three main contributions. First, we formulate and solve the activity prediction problem in the framework of imitation learning and reduce it to a simple regression learning problem. This approach allows us to leverage powerful regression learners that can reason about the relational structure of the problem with negligible computational overhead. Second, we present several metrics to evaluate activity predictors in the context of real-world applications. Third, we evaluate our approach using real sensor data collected from 24 smart home testbeds. We also embed the learned predictor into a mobile-device-based activity prompter and evaluate the app for 9 participants living in smart homes. Our results indicate that our activity predictor performs better than the baseline methods, and offers a simple approach for predicting activities from sensor data.

Big Data Analytics for Demand Response: Clustering Over Space and Time

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chelmis, Charalampos; Kolte, Jahanvi; Prasanna, Viktor K.

The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval. Time-series data can be valuable for data mining and analytics tasks such as identifying the “right” customers among a diverse population, to target for Demand Response programs. However, time series are challenging to mine due to their high dimensionality. Inmore » this paper, we motivate this problem using a real application from the smart grid domain. We explore novel representations of time-series data for BigData analytics, and propose a clustering technique for determining natural segmentation of customers and identification of temporal consumption patterns. Our method is generizable to large-scale, real-world scenarios, without making any assumptions about the data. We evaluate our technique using real datasets from smart meters, totaling ~ 18,200,000 data points, and show the efficacy of our technique in efficiency detecting the number of optimal number of clusters.« less

Rotation and scale change invariant point pattern relaxation matching by the Hopfield neural network

NASA Astrophysics Data System (ADS)

Sang, Nong; Zhang, Tianxu

1997-12-01

Relaxation matching is one of the most relevant methods for image matching. The original relaxation matching technique using point patterns is sensitive to rotations and scale changes. We improve the original point pattern relaxation matching technique to be invariant to rotations and scale changes. A method that makes the Hopfield neural network perform this matching process is discussed. An advantage of this is that the relaxation matching process can be performed in real time with the neural network's massively parallel capability to process information. Experimental results with large simulated images demonstrate the effectiveness and feasibility of the method to perform point patten relaxation matching invariant to rotations and scale changes and the method to perform this matching by the Hopfield neural network. In addition, we show that the method presented can be tolerant to small random error.

AsterAnts: A Concept for Large-Scale Meteoroid Return and Processing using the International Space Station

NASA Technical Reports Server (NTRS)

Globus, Al; Biegel, Bryan A.; Traugott, Steve

2004-01-01

AsterAnts is a concept calling for a fleet of solar sail powered spacecraft to retrieve large numbers of small (1/2-1 meter diameter) Near Earth Objects (NEOs) for orbital processing. AsterAnts could use the International Space Station (ISS) for NEO processing, solar sail construction, and to test NEO capture hardware. Solar sails constructed on orbit are expected to have substantially better performance than their ground built counterparts [Wright 1992]. Furthermore, solar sails may be used to hold geosynchronous communication satellites out-of-plane [Forward 1981] increasing the total number of slots by at least a factor of three. potentially generating $2 billion worth of orbital real estate over North America alone. NEOs are believed to contain large quantities of water, carbon, other life-support materials and metals. Thus. with proper processing, NEO materials could in principle be used to resupply the ISS, produce rocket propellant, manufacture tools, and build additional ISS working space. Unlike proposals requiring massive facilities, such as lunar bases, before returning any extraterrestrial larger than a typical inter-planetary mission. Furthermore, AsterAnts could be scaled up to deliver large amounts of material by building many copies of the same spacecraft, thereby achieving manufacturing economies of scale. Because AsterAnts would capture NEOs whole, NEO composition details, which are generally poorly characterized, are relatively unimportant and no complex extraction equipment is necessary. In combination with a materials processing facility at the ISS, AsterAnts might inaugurate an era of large-scale orbital construction using extraterrestrial materials.

Concurrent heterogeneous neural model simulation on real-time neuromimetic hardware.

PubMed

Rast, Alexander; Galluppi, Francesco; Davies, Sergio; Plana, Luis; Patterson, Cameron; Sharp, Thomas; Lester, David; Furber, Steve

2011-11-01

Dedicated hardware is becoming increasingly essential to simulate emerging very-large-scale neural models. Equally, however, it needs to be able to support multiple models of the neural dynamics, possibly operating simultaneously within the same system. This may be necessary either to simulate large models with heterogeneous neural types, or to simplify simulation and analysis of detailed, complex models in a large simulation by isolating the new model to a small subpopulation of a larger overall network. The SpiNNaker neuromimetic chip is a dedicated neural processor able to support such heterogeneous simulations. Implementing these models on-chip uses an integrated library-based tool chain incorporating the emerging PyNN interface that allows a modeller to input a high-level description and use an automated process to generate an on-chip simulation. Simulations using both LIF and Izhikevich models demonstrate the ability of the SpiNNaker system to generate and simulate heterogeneous networks on-chip, while illustrating, through the network-scale effects of wavefront synchronisation and burst gating, methods that can provide effective behavioural abstractions for large-scale hardware modelling. SpiNNaker's asynchronous virtual architecture permits greater scope for model exploration, with scalable levels of functional and temporal abstraction, than conventional (or neuromorphic) computing platforms. The complete system illustrates a potential path to understanding the neural model of computation, by building (and breaking) neural models at various scales, connecting the blocks, then comparing them against the biology: computational cognitive neuroscience. Copyright © 2011 Elsevier Ltd. All rights reserved.

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

PubMed

Li, Jian-Feng; Bush, Jenifer; Xiong, Yan; Li, Lei; McCormack, Matthew

2011-01-01

Protein-protein interactions (PPIs) constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC) as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs) and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

RT-Syn: A real-time software system generator

NASA Technical Reports Server (NTRS)

Setliff, Dorothy E.

1992-01-01

This paper presents research into providing highly reusable and maintainable components by using automatic software synthesis techniques. This proposal uses domain knowledge combined with automatic software synthesis techniques to engineer large-scale mission-critical real-time software. The hypothesis centers on a software synthesis architecture that specifically incorporates application-specific (in this case real-time) knowledge. This architecture synthesizes complex system software to meet a behavioral specification and external interaction design constraints. Some examples of these external constraints are communication protocols, precisions, timing, and space limitations. The incorporation of application-specific knowledge facilitates the generation of mathematical software metrics which are used to narrow the design space, thereby making software synthesis tractable. Success has the potential to dramatically reduce mission-critical system life-cycle costs not only by reducing development time, but more importantly facilitating maintenance, modifications, and extensions of complex mission-critical software systems, which are currently dominating life cycle costs.

Complex networks as an emerging property of hierarchical preferential attachment.

PubMed

Hébert-Dufresne, Laurent; Laurence, Edward; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J

2015-12-01

Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. We give examples of such hierarchy in real systems, for instance, in the pyramid of production entities of the film industry. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality, and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature.

Complex networks as an emerging property of hierarchical preferential attachment

NASA Astrophysics Data System (ADS)

Hébert-Dufresne, Laurent; Laurence, Edward; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J.

2015-12-01

Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. We give examples of such hierarchy in real systems, for instance, in the pyramid of production entities of the film industry. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality, and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature.

A Framework of Simple Event Detection in Surveillance Video

NASA Astrophysics Data System (ADS)

Xu, Weiguang; Zhang, Yafei; Lu, Jianjiang; Tian, Yulong; Wang, Jiabao

Video surveillance is playing more and more important role in people's social life. Real-time alerting of threaten events and searching interesting content in stored large scale video footage needs human operator to pay full attention on monitor for long time. The labor intensive mode has limit the effectiveness and efficiency of the system. A framework of simple event detection is presented advance the automation of video surveillance. An improved inner key point matching approach is used to compensate motion of background in real-time; frame difference are used to detect foreground; HOG based classifiers are used to classify foreground object into people and car; mean-shift is used to tracking the recognized objects. Events are detected based on predefined rules. The maturity of the algorithms guarantee the robustness of the framework, and the improved approach and the easily checked rules enable the framework to work in real-time. Future works to be done are also discussed.

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Power in the loop real time simulation platform for renewable energy generation

NASA Astrophysics Data System (ADS)

Li, Yang; Shi, Wenhui; Zhang, Xing; He, Guoqing

2018-02-01

Nowadays, a large scale of renewable energy sources has been connecting to power system and the real time simulation platform is widely used to carry out research on integration control algorithm, power system stability etc. Compared to traditional pure digital simulation and hardware in the loop simulation, power in the loop simulation has higher accuracy and degree of reliability. In this paper, a power in the loop analog digital hybrid simulation platform has been built and it can be used not only for the single generation unit connecting to grid, but also for multiple new energy generation units connecting to grid. A wind generator inertia control experiment was carried out on the platform. The structure of the inertia control platform was researched and the results verify that the platform is up to need for renewable power in the loop real time simulation.

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2014-10-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

Recovering the fine structures in solar images

NASA Technical Reports Server (NTRS)

Karovska, Margarita; Habbal, S. R.; Golub, L.; Deluca, E.; Hudson, Hugh S.

1994-01-01

Several examples of the capability of the blind iterative deconvolution (BID) technique to recover the real point spread function, when limited a priori information is available about its characteristics. To demonstrate the potential of image post-processing for probing the fine scale and temporal variability of the solar atmosphere, the BID technique is applied to different samples of solar observations from space. The BID technique was originally proposed for correction of the effects of atmospheric turbulence on optical images. The processed images provide a detailed view of the spatial structure of the solar atmosphere at different heights in regions with different large-scale magnetic field structures.

An ultrasensitive strain sensor with a wide strain range based on graphene armour scales.

PubMed

Yang, Yi-Fan; Tao, Lu-Qi; Pang, Yu; Tian, He; Ju, Zhen-Yi; Wu, Xiao-Ming; Yang, Yi; Ren, Tian-Ling

2018-06-12

An ultrasensitive strain sensor with a wide strain range based on graphene armour scales is demonstrated in this paper. The sensor shows an ultra-high gauge factor (GF, up to 1054) and a wide strain range (ε = 26%), both of which present an advantage compared to most other flexible sensors. Moreover, the sensor is developed by a simple fabrication process. Due to the excellent performance, this strain sensor can meet the demands of subtle, large and complex human motion monitoring, which indicates its tremendous application potential in health monitoring, mechanical control, real-time motion monitoring and so on.

Time Hierarchies and Model Reduction in Canonical Non-linear Models

PubMed Central

Löwe, Hannes; Kremling, Andreas; Marin-Sanguino, Alberto

2016-01-01

The time-scale hierarchies of a very general class of models in differential equations is analyzed. Classical methods for model reduction and time-scale analysis have been adapted to this formalism and a complementary method is proposed. A unified theoretical treatment shows how the structure of the system can be much better understood by inspection of two sets of singular values: one related to the stoichiometric structure of the system and another to its kinetics. The methods are exemplified first through a toy model, then a large synthetic network and finally with numeric simulations of three classical benchmark models of real biological systems. PMID:27708665

Telescopic multi-resolution augmented reality

NASA Astrophysics Data System (ADS)

Jenkins, Jeffrey; Frenchi, Christopher; Szu, Harold

2014-05-01

To ensure a self-consistent scaling approximation, the underlying microscopic fluctuation components can naturally influence macroscopic means, which may give rise to emergent observable phenomena. In this paper, we describe a consistent macroscopic (cm-scale), mesoscopic (micron-scale), and microscopic (nano-scale) approach to introduce Telescopic Multi-Resolution (TMR) into current Augmented Reality (AR) visualization technology. We propose to couple TMR-AR by introducing an energy-matter interaction engine framework that is based on known Physics, Biology, Chemistry principles. An immediate payoff of TMR-AR is a self-consistent approximation of the interaction between microscopic observables and their direct effect on the macroscopic system that is driven by real-world measurements. Such an interdisciplinary approach enables us to achieve more than multiple scale, telescopic visualization of real and virtual information but also conducting thought experiments through AR. As a result of the consistency, this framework allows us to explore a large dimensionality parameter space of measured and unmeasured regions. Towards this direction, we explore how to build learnable libraries of biological, physical, and chemical mechanisms. Fusing analytical sensors with TMR-AR libraries provides a robust framework to optimize testing and evaluation through data-driven or virtual synthetic simulations. Visualizing mechanisms of interactions requires identification of observable image features that can indicate the presence of information in multiple spatial and temporal scales of analog data. The AR methodology was originally developed to enhance pilot-training as well as `make believe' entertainment industries in a user-friendly digital environment We believe TMR-AR can someday help us conduct thought experiments scientifically, to be pedagogically visualized in a zoom-in-and-out, consistent, multi-scale approximations.

Airborne Camera System for Real-Time Applications - Support of a National Civil Protection Exercise

NASA Astrophysics Data System (ADS)

Gstaiger, V.; Romer, H.; Rosenbaum, D.; Henkel, F.

2015-04-01

In the VABENE++ project of the German Aerospace Center (DLR), powerful tools are being developed to aid public authorities and organizations with security responsibilities as well as traffic authorities when dealing with disasters and large public events. One focus lies on the acquisition of high resolution aerial imagery, its fully automatic processing, analysis and near real-time provision to decision makers in emergency situations. For this purpose a camera system was developed to be operated from a helicopter with light-weight processing units and microwave link for fast data transfer. In order to meet end-users' requirements DLR works close together with the German Federal Office of Civil Protection and Disaster Assistance (BBK) within this project. One task of BBK is to establish, maintain and train the German Medical Task Force (MTF), which gets deployed nationwide in case of large-scale disasters. In October 2014, several units of the MTF were deployed for the first time in the framework of a national civil protection exercise in Brandenburg. The VABENE++ team joined the exercise and provided near real-time aerial imagery, videos and derived traffic information to support the direction of the MTF and to identify needs for further improvements and developments. In this contribution the authors introduce the new airborne camera system together with its near real-time processing components and share experiences gained during the national civil protection exercise.

Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

PubMed

Wei, Yawei; Venayagamoorthy, Ganesh Kumar

2017-09-01

To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hydrological characterization of Guadalquivir River Basin for the period 1980-2010 using VIC model

NASA Astrophysics Data System (ADS)

García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

This study analyzes the changes of soil moisture and real evapotranspiration (ETR), during the last 30 years, in the Guadalquivir River Basin, located in the south of the Iberian Peninsula. Soil moisture content is related with the different components of the real evaporation, it is a relevant factor when analyzing the intensity of droughts and heat waves, and particularly, for the impact study of the climate change. The soil moisture and real evapotranspiration data consist of simulations obtained by using the Variable Infiltration Capacity (VIC) hydrological model. This is a large-scale hydrologic model and allows the estimations of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cell and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset have been used as input variables for VIC model. Additionally, estimates of actual evapotranspiration and soil moisture are also analyzed using temperature, precipitation, wind, humidity and radiation as input variables for VIC. These variables are obtained from a dynamical downscaling from ERA-Interim data by the Weather Research and Forecasting (WRF) model. The simulations have a spatial resolution about 9 km and the analysis is done on a seasonal time-scale. Preliminary results show that ETR presents very low values for autumn from WRF simulations compared with VIC simulations. Only significant positive trends are found during autumn for the western part of the basin for the ETR obtained with VIC model, meanwhile no significant trends are found for the ETR WRF simulations. Keywords: Soil moisture, Real evapotranspiration, Guadalquivir Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Large Scale Data Analysis and Knowledge Extraction in Communication Data

DTIC Science & Technology

2017-03-31

this purpose, we developed a novel method the " Correlation Density Ran!C’ which finds probability density distribution of related frequent event on all...which is called " Correlation Density Rank", is developed to derive the community tree from the network. As in the real world, where a network is...Community Structure in Dynamic Social Networks using the Correlation Density Rank," 2014 ASE BigData/SocialCom/Cybersecurity Conference, Stanford

What Are Student Inservice Teachers Talking about in Their Online Communities of Practice? Investigating Student Inservice Teachers' Experiences in a Double-Layered CoP

ERIC Educational Resources Information Center

Lee, Kyungmee; Brett, Clare

2013-01-01

This qualitative case study is the first phase of a large-scale design-based research project to implement a theoretically derived double-layered CoP model within real-world teacher development practices. The main goal of this first iteration is to evaluate the courses and test and refine the CoP model for future implementations. This paper…

SIRT-FILTER v1.0.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

PELT, DANIEL

2017-04-21

Small Python package to compute tomographic reconstructions using a reconstruction method published in: Pelt, D.M., & De Andrade, V. (2017). Improved tomographic reconstruction of large-scale real-world data by filter optimization. Advanced Structural and Chemical Imaging 2: 17; and Pelt, D. M., & Batenburg, K. J. (2015). Accurately approximating algebraic tomographic reconstruction by filtered backprojection. In Proceedings of The 13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (pp. 158-161).

Report of the Working Group on Large-Scale Computing in Aeronautics.

DTIC Science & Technology

1984-06-01

incompressible approximations that are presently made in the lifting line or lifting surface representations of rotor blades. Finally, viscous effects in the forms... Effects of Rotor Model Degradation in the Accuracy of Rotocraft Real-Time Simulation, NASA TN D-8378;1977. 20. Gullen, R. K., Cattell, C. S., and Overton...assistance to member nations for the purpose of increasing their scientific and technical potential; - Recommending effective ways for the member nations

NEMS (Nanoelectromechanicsl Systems) Networks: A Novel Validation Platform for Controlling Interconnected Dynamical Networks

DTIC Science & Technology

2015-08-01

power   power  grids  to...both  an   ultralow  intrinsic  dissipation   (high  Q)  and  a  low  threshold  onset  of  nonlinear  dynamics.  Q...of   nodes,   we  will   have   in   effect   a   powerful   simulator   for   large-­‐scale   real   world  

Continuous, Large-Scale Processing of Seismic Archives for High-Resolution Monitoring of Seismic Activity and Seismogenic Properties

NASA Astrophysics Data System (ADS)

Waldhauser, F.; Schaff, D. P.

2012-12-01

Archives of digital seismic data recorded by seismometer networks around the world have grown tremendously over the last several decades helped by the deployment of seismic stations and their continued operation within the framework of monitoring earthquake activity and verification of the Nuclear Test-Ban Treaty. We show results from our continuing effort in developing efficient waveform cross-correlation and double-difference analysis methods for the large-scale processing of regional and global seismic archives to improve existing earthquake parameter estimates, detect seismic events with magnitudes below current detection thresholds, and improve real-time monitoring procedures. We demonstrate the performance of these algorithms as applied to the 28-year long seismic archive of the Northern California Seismic Network. The tools enable the computation of periodic updates of a high-resolution earthquake catalog of currently over 500,000 earthquakes using simultaneous double-difference inversions, achieving up to three orders of magnitude resolution improvement over existing hypocenter locations. This catalog, together with associated metadata, form the underlying relational database for a real-time double-difference scheme, DDRT, which rapidly computes high-precision correlation times and hypocenter locations of new events with respect to the background archive (http://ddrt.ldeo.columbia.edu). The DDRT system facilitates near-real-time seismicity analysis, including the ability to search at an unprecedented resolution for spatio-temporal changes in seismogenic properties. In areas with continuously recording stations, we show that a detector built around a scaled cross-correlation function can lower the detection threshold by one magnitude unit compared to the STA/LTA based detector employed at the network. This leads to increased event density, which in turn pushes the resolution capability of our location algorithms. On a global scale, we are currently building the computational framework for double-difference processing the combined parametric and waveform archives of the ISC, NEIC, and IRIS with over three million recorded earthquakes worldwide. Since our methods are scalable and run on inexpensive Beowulf clusters, periodic re-analysis of such archives may thus become a routine procedure to continuously improve resolution in existing global earthquake catalogs. Results from subduction zones and aftershock sequences of recent great earthquakes demonstrate the considerable social and economic impact that high-resolution images of active faults, when available in real-time, will have in the prompt evaluation and mitigation of seismic hazards. These results also highlight the need for consistent long-term seismic monitoring and archiving of records.

Exhaustive identification of steady state cycles in large stoichiometric networks

PubMed Central

Wright, Jeremiah; Wagner, Andreas

2008-01-01

Background Identifying cyclic pathways in chemical reaction networks is important, because such cycles may indicate in silico violation of energy conservation, or the existence of feedback in vivo. Unfortunately, our ability to identify cycles in stoichiometric networks, such as signal transduction and genome-scale metabolic networks, has been hampered by the computational complexity of the methods currently used. Results We describe a new algorithm for the identification of cycles in stoichiometric networks, and we compare its performance to two others by exhaustively identifying the cycles contained in the genome-scale metabolic networks of H. pylori, M. barkeri, E. coli, and S. cerevisiae. Our algorithm can substantially decrease both the execution time and maximum memory usage in comparison to the two previous algorithms. Conclusion The algorithm we describe improves our ability to study large, real-world, biochemical reaction networks, although additional methodological improvements are desirable. PMID:18616835

Trickle-Down Preferences: Preferential Conformity to High Status Peers in Fashion Choices

PubMed Central

Galak, Jeff; Gray, Kurt; Elbert, Igor; Strohminger, Nina

2016-01-01

How much do our choices represent stable inner preferences versus social conformity? We examine conformity and consistency in sartorial choices surrounding a common life event of new norm exposure: relocation. A large-scale dataset of individual purchases of women’s shoes (16,236 transactions) across five years and 2,007 women reveals a balance of conformity and consistency, moderated by changes in location socioeconomic status. Women conform to new local norms (i.e., average heel size) when moving to relatively higher status locations, but mostly ignore new local norms when moving to relatively lower status locations. In short, at periods of transition, it is the fashion norms of the rich that trickle down to consumers. These analyses provide the first naturalistic large-scale demonstration of the tension between psychological conformity and consistency, with real decisions in a highly visible context. PMID:27144595

Scalable methodology for large scale building energy improvement: Relevance of calibration in model-based retrofit analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane

2015-05-01

The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less

Impact of tissue atrophy on high-pass filtered MRI signal phase-based assessment in large-scale group-comparison studies: A simulation study

NASA Astrophysics Data System (ADS)

Schweser, Ferdinand; Dwyer, Michael G.; Deistung, Andreas; Reichenbach, Jürgen R.; Zivadinov, Robert

2013-10-01

The assessment of abnormal accumulation of tissue iron in the basal ganglia nuclei and in white matter plaques using the gradient echo magnetic resonance signal phase has become a research focus in many neurodegenerative diseases such as multiple sclerosis or Parkinson’s disease. A common and natural approach is to calculate the mean high-pass-filtered phase of previously delineated brain structures. Unfortunately, the interpretation of such an analysis requires caution: in this paper we demonstrate that regional gray matter atrophy, which is concomitant with many neurodegenerative diseases, may itself directly result in a phase shift seemingly indicative of increased iron concentration even without any real change in the tissue iron concentration. Although this effect is relatively small results of large-scale group comparisons may be driven by anatomical changes rather than by changes of the iron concentration.

Scalable parallel distance field construction for large-scale applications

DOE PAGES

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan -Liu; ...

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate itsmore » efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.« less

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

PubMed Central

Berényi, Antal; Somogyvári, Zoltán; Nagy, Anett J.; Roux, Lisa; Long, John D.; Fujisawa, Shigeyoshi; Stark, Eran; Leonardo, Anthony; Harris, Timothy D.

2013-01-01

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function. PMID:24353300

Possible implications of large scale radiation processing of food

NASA Astrophysics Data System (ADS)

Zagórski, Z. P.

Large scale irradiation has been discussed in terms of the participation of processing cost in the final value of the improved product. Another factor has been taken into account and that is the saturation of the market with the new product. In the case of succesful projects the participation of irradiation cost is low, and the demand for the better product is covered. A limited availability of sources makes the modest saturation of the market difficult with all food subjected to correct radiation treatment. The implementation of the preservation of food needs a decided selection of these kinds of food which comply to all conditions i.e. of acceptance by regulatory bodies, real improvement of quality and economy. The last condition prefers the possibility of use of electron beams of low energy. The best fullfilment of conditions for succesful processing is observed in the group of dry food, in expensive spices in particular.

Petri Net controller synthesis based on decomposed manufacturing models.

PubMed

Dideban, Abbas; Zeraatkar, Hashem

2018-06-01

Utilizing of supervisory control theory on the real systems in many modeling tools such as Petri Net (PN) becomes challenging in recent years due to the significant states in the automata models or uncontrollable events. The uncontrollable events initiate the forbidden states which might be removed by employing some linear constraints. Although there are many methods which have been proposed to reduce these constraints, enforcing them to a large-scale system is very difficult and complicated. This paper proposes a new method for controller synthesis based on PN modeling. In this approach, the original PN model is broken down into some smaller models in which the computational cost reduces significantly. Using this method, it is easy to reduce and enforce the constraints to a Petri net model. The appropriate results of our proposed method on the PN models denote worthy controller synthesis for the large scale systems. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.

PubMed

Haghverdi, Laleh; Lun, Aaron T L; Morgan, Michael D; Marioni, John C

2018-06-01

Large-scale single-cell RNA sequencing (scRNA-seq) data sets that are produced in different laboratories and at different times contain batch effects that may compromise the integration and interpretation of the data. Existing scRNA-seq analysis methods incorrectly assume that the composition of cell populations is either known or identical across batches. We present a strategy for batch correction based on the detection of mutual nearest neighbors (MNNs) in the high-dimensional expression space. Our approach does not rely on predefined or equal population compositions across batches; instead, it requires only that a subset of the population be shared between batches. We demonstrate the superiority of our approach compared with existing methods by using both simulated and real scRNA-seq data sets. Using multiple droplet-based scRNA-seq data sets, we demonstrate that our MNN batch-effect-correction method can be scaled to large numbers of cells.

Scalable Parallel Distance Field Construction for Large-Scale Applications.

PubMed

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.

Reconstructing a Large-Scale Population for Social Simulation

NASA Astrophysics Data System (ADS)

Fan, Zongchen; Meng, Rongqing; Ge, Yuanzheng; Qiu, Xiaogang

The advent of social simulation has provided an opportunity to research on social systems. More and more researchers tend to describe the components of social systems in a more detailed level. Any simulation needs the support of population data to initialize and implement the simulation systems. However, it's impossible to get the data which provide full information about individuals and households. We propose a two-step method to reconstruct a large-scale population for a Chinese city according to Chinese culture. Firstly, a baseline population is generated through gathering individuals into households one by one; secondly, social relationships such as friendship are assigned to the baseline population. Through a case study, a population of 3,112,559 individuals gathered in 1,133,835 households is reconstructed for Urumqi city, and the results show that the generated data can respect the real data quite well. The generated data can be applied to support modeling of some social phenomenon.

Simulation of the Vortex Dynamics in a Real Pinning Landscape of YBa 2 Cu 3 O 7 - δ Coated Conductors

DOE PAGES

Sadovskyy, I. A.; Koshelev, A. E.; Glatz, A.; ...

2016-01-01

The ability of high-temperature superconductors (HTSs) to carry very large currents with almost no dissipation makes them irreplaceable for high-power applications. The development and further improvement of HTS-based cables require an in-depth understanding of the superconducting vortex dynamics in the presence of complex pinning landscapes. We present a critical current analysis of a real HTS sample in a magnetic field by combining state-of-the-art large-scale Ginzburg-Landau simulations with reconstructive three-dimensional scanning-transmission-electron-microscopy tomography of the pinning landscape in Dy-doped YBa 2Cu 3O 7-δ. This methodology provides a unique look at the vortex dynamics in the presence of a complex pinning landscape responsiblemore » for the high-current-carrying-capacity characteristic of commercial HTS wires. Finally, our method demonstrates very good functional and quantitative agreement of the critical current between simulation and experiment, providing a new predictive tool for HTS wire designs.« less

Stereoscopic applications for design visualization

NASA Astrophysics Data System (ADS)

Gilson, Kevin J.

2007-02-01

Advances in display technology and 3D design visualization applications have made real-time stereoscopic visualization of architectural and engineering projects a reality. Parsons Brinkerhoff (PB) is a transportation consulting firm that has used digital visualization tools from their inception and has helped pioneer the application of those tools to large scale infrastructure projects. PB is one of the first Architecture/Engineering/Construction (AEC) firms to implement a CAVE- an immersive presentation environment that includes stereoscopic rear-projection capability. The firm also employs a portable stereoscopic front-projection system, and shutter-glass systems for smaller groups. PB is using commercial real-time 3D applications in combination with traditional 3D modeling programs to visualize and present large AEC projects to planners, clients and decision makers in stereo. These presentations create more immersive and spatially realistic presentations of the proposed designs. This paper will present the basic display tools and applications, and the 3D modeling techniques PB is using to produce interactive stereoscopic content. The paper will discuss several architectural and engineering design visualizations we have produced.

Simulation of the Vortex Dynamics in a Real Pinning Landscape of YBa 2 Cu 3 O 7 - δ Coated Conductors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadovskyy, I. A.; Koshelev, A. E.; Glatz, A.

The ability of high-temperature superconductors (HTSs) to carry very large currents with almost no dissipation makes them irreplaceable for high-power applications. The development and further improvement of HTS-based cables require an in-depth understanding of the superconducting vortex dynamics in the presence of complex pinning landscapes. We present a critical current analysis of a real HTS sample in a magnetic field by combining state-of-the-art large-scale Ginzburg-Landau simulations with reconstructive three-dimensional scanning-transmission-electron-microscopy tomography of the pinning landscape in Dy-doped YBa 2Cu 3O 7-δ. This methodology provides a unique look at the vortex dynamics in the presence of a complex pinning landscape responsiblemore » for the high-current-carrying-capacity characteristic of commercial HTS wires. Finally, our method demonstrates very good functional and quantitative agreement of the critical current between simulation and experiment, providing a new predictive tool for HTS wire designs.« less

Simulation of the Vortex Dynamics in a Real Pinning Landscape of YBa 2 Cu 3 O 7 - δ Coated Conductors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadovskyy, I. A.; Koshelev, A. E.; Glatz, A.

Tmore » he ability of high-temperature superconductors (HSs) to carry very large currents with almost no dissipation makes them irreplaceable for high-power applications. he development and further improvement of HS-based cables require an in-depth understanding of the superconducting vortex dynamics in the presence of complex pinning landscapes. Here, we present a critical current analysis of a real HS sample in a magnetic field by combining state-of-the-art large-scale Ginzburg-Landau simulations with reconstructive three-dimensional scanning-transmission-electron-microscopy tomography of the pinning landscape in Dy-doped YBa 2 Cu 3 O 7 - δ . his methodology provides a unique look at the vortex dynamics in the presence of a complex pinning landscape responsible for the high-current-carrying-capacity characteristic of commercial HS wires. Our method demonstrates very good functional and quantitative agreement of the critical current between simulation and experiment, providing a new predictive tool for HS wire designs.« less

Learning directed acyclic graphs from large-scale genomics data.

PubMed

Nikolay, Fabio; Pesavento, Marius; Kritikos, George; Typas, Nassos

2017-09-20

In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best. Furthermore, we extend the GENIE program by incorporating genetic interaction profile (GI-profile) data to further enhance the detection performance. In addition, we propose a sequential scalability technique for large sets of genes under study, in order to provide statistically significant results for real measurement data. Finally, we show via numeric simulations that the GENIE program and the GI-profile data extended GENIE (GI-GENIE) program clearly outperform the conventional techniques and present real data results for our proposed sequential scalability technique.

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

NASA Astrophysics Data System (ADS)

Chaves-González, José M.; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.

2011-08-01

This article analyses the use of a novel parallel evolutionary strategy to solve complex optimization problems. The work developed here has been focused on a relevant real-world problem from the telecommunication domain to verify the effectiveness of the approach. The problem, known as frequency assignment problem (FAP), basically consists of assigning a very small number of frequencies to a very large set of transceivers used in a cellular phone network. Real data FAP instances are very difficult to solve due to the NP-hard nature of the problem, therefore using an efficient parallel approach which makes the most of different evolutionary strategies can be considered as a good way to obtain high-quality solutions in short periods of time. Specifically, a parallel hyper-heuristic based on several meta-heuristics has been developed. After a complete experimental evaluation, results prove that the proposed approach obtains very high-quality solutions for the FAP and beats any other result published.

LANDPLANER (LANDscape, Plants, LANdslide and ERosion): a model to describe the dynamic response of slopes (or basins) under different changing scenarios

NASA Astrophysics Data System (ADS)

Rossi, Mauro; Torri, Dino; Santi, Elisa; Bacaro, Giovanni; Marchesini, Ivan

2014-05-01

Landslide phenomena and erosion processes are widespread and cause every year extensive damages to the environment and sensible reduction of ecosystem services. These processes are in competition among them, and their complex interaction control the landscapes evolution. Landslide phenomena and erosion processes can be strongly influenced by land use, vegetation, soil characteristics and anthropic actions. Such type of phenomena are mainly model separately using empirical and physically based approaches. The former rely upon the identification of simple empirical laws correlating/relating the occurrence of instability processes to some of their potential causes. The latter are based on physical descriptions of the processes, and depending on the degree of complexity they can integrate different variables characterizing the process and their trigger. Those model often couple an hydrological model with an erosion or a landslide model. The spatial modeling schemas are heterogeneous, but mostly the raster (i.e. matrices of data) or the conceptual (i.e. cascading planes and channels) description of the terrain are used. The two model types are generally designed and applied at different scales. Empirical models, less demanding in terms of input data cannot consider explicitly the real process triggering mechanisms and commonly they are exploited to assess the potential occurrence of instability phenomena over large areas (small scale assessment). Physically-based models are high-demanding in term of input data, difficult to obtain over large areas if not with large uncertainty, and their applicability is often limited to small catchments or single slopes (large scale assessment). More those models, even if physically-based, are simplified description of the instability processes and can neglect significant issues of the real triggering mechanisms. For instance the influence of vegetation has been considered just partially. Although in the literature a variety of model approaches have been proposed to model separately landslide and erosion processes, only few attempts were made to model both jointly, mostly integrating pre-existing models. To overcome this limitation we develop a new model called LANDPLANER (LANDscape, Plants, LANdslide and ERosion), specifically design to describe the dynamic response of slopes (or basins) under different changing scenarios including: (i) changes of meteorological factors, (ii) changes of vegetation or land-use, (iii) and changes of slope morphology. The was applied in different study area in order to check its basic assumptions, and to test its general operability and applicability. Results show a reasonable model behaviors and confirm its easy applicability in real cases.

High performance cellular level agent-based simulation with FLAME for the GPU.

PubMed

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

Simulation-optimization of large agro-hydrosystems using a decomposition approach

NASA Astrophysics Data System (ADS)

Schuetze, Niels; Grundmann, Jens

2014-05-01

In this contribution a stochastic simulation-optimization framework for decision support for optimal planning and operation of water supply of large agro-hydrosystems is presented. It is based on a decomposition solution strategy which allows for (i) the usage of numerical process models together with efficient Monte Carlo simulations for a reliable estimation of higher quantiles of the minimum agricultural water demand for full and deficit irrigation strategies at small scale (farm level), and (ii) the utilization of the optimization results at small scale for solving water resources management problems at regional scale. As a secondary result of several simulation-optimization runs at the smaller scale stochastic crop-water production functions (SCWPF) for different crops are derived which can be used as a basic tool for assessing the impact of climate variability on risk for potential yield. In addition, microeconomic impacts of climate change and the vulnerability of the agro-ecological systems are evaluated. The developed methodology is demonstrated through its application on a real-world case study for the South Al-Batinah region in the Sultanate of Oman where a coastal aquifer is affected by saltwater intrusion due to excessive groundwater withdrawal for irrigated agriculture.

The wireless networking system of Earthquake precursor mobile field observation

NASA Astrophysics Data System (ADS)

Wang, C.; Teng, Y.; Wang, X.; Fan, X.; Wang, X.

2012-12-01

The mobile field observation network could be real-time, reliably record and transmit large amounts of data, strengthen the physical signal observations in specific regions and specific period, it can improve the monitoring capacity and abnormal tracking capability. According to the features of scatter everywhere, a large number of current earthquake precursor observation measuring points, networking technology is based on wireless broadband accessing McWILL system, the communication system of earthquake precursor mobile field observation would real-time, reliably transmit large amounts of data to the monitoring center from measuring points through the connection about equipment and wireless accessing system, broadband wireless access system and precursor mobile observation management center system, thereby implementing remote instrument monitoring and data transmition. At present, the earthquake precursor field mobile observation network technology has been applied to fluxgate magnetometer array geomagnetic observations of Tianzhu, Xichang,and Xinjiang, it can be real-time monitoring the working status of the observational instruments of large area laid after the last two or three years, large scale field operation. Therefore, it can get geomagnetic field data of the local refinement regions and provide high-quality observational data for impending earthquake tracking forecast. Although, wireless networking technology is very suitable for mobile field observation with the features of simple, flexible networking etc, it also has the phenomenon of packet loss etc when transmitting a large number of observational data due to the wireless relatively weak signal and narrow bandwidth. In view of high sampling rate instruments, this project uses data compression and effectively solves the problem of data transmission packet loss; Control commands, status data and observational data transmission use different priorities and means, which control the packet loss rate within an acceptable range and do not affect real-time observation curve. After field running test and earthquake tracking project applications, the field mobile observation wireless networking system is operate normally, various function have good operability and show good performance, the quality of data transmission meet the system design requirements and play a significant role in practical applications.

A map overlay error model based on boundary geometry

USGS Publications Warehouse

Gaeuman, D.; Symanzik, J.; Schmidt, J.C.

2005-01-01

An error model for quantifying the magnitudes and variability of errors generated in the areas of polygons during spatial overlay of vector geographic information system layers is presented. Numerical simulation of polygon boundary displacements was used to propagate coordinate errors to spatial overlays. The model departs from most previous error models in that it incorporates spatial dependence of coordinate errors at the scale of the boundary segment. It can be readily adapted to match the scale of error-boundary interactions responsible for error generation on a given overlay. The area of error generated by overlay depends on the sinuosity of polygon boundaries, as well as the magnitude of the coordinate errors on the input layers. Asymmetry in boundary shape has relatively little effect on error generation. Overlay errors are affected by real differences in boundary positions on the input layers, as well as errors in the boundary positions. Real differences between input layers tend to compensate for much of the error generated by coordinate errors. Thus, the area of change measured on an overlay layer produced by the XOR overlay operation will be more accurate if the area of real change depicted on the overlay is large. The model presented here considers these interactions, making it especially useful for estimating errors studies of landscape change over time. ?? 2005 The Ohio State University.

Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models

PubMed Central

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

2016-01-01

Traffic and environmental conditions (e.g., weather conditions), which frequently change with time, have a significant impact on crash occurrence. Traditional crash frequency models with large temporal scales and aggregated variables are not sufficient to capture the time-varying nature of driving environmental factors, causing significant loss of critical information on crash frequency modeling. This paper aims at developing crash frequency models with refined temporal scales for complex driving environments, with such an effort providing more detailed and accurate crash risk information which can allow for more effective and proactive traffic management and law enforcement intervention. Zero-inflated, negative binomial (ZINB) models with site-specific random effects are developed with unbalanced panel data to analyze hourly crash frequency on highway segments. The real-time driving environment information, including traffic, weather and road surface condition data, sourced primarily from the Road Weather Information System, is incorporated into the models along with site-specific road characteristics. The estimation results of unbalanced panel data ZINB models suggest there are a number of factors influencing crash frequency, including time-varying factors (e.g., visibility and hourly traffic volume) and site-varying factors (e.g., speed limit). The study confirms the unique significance of the real-time weather, road surface condition and traffic data to crash frequency modeling. PMID:27322306

Incremental k-core decomposition: Algorithms and evaluation

DOE PAGES

Sariyuce, Ahmet Erdem; Gedik, Bugra; Jacques-SIlva, Gabriela; ...

2016-02-01

A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, protein function prediction, visualization, and solving NP-hard problems on real networks efficiently, like maximal clique finding. In many real-world applications, networks change over time. As a result, it is essential to develop efficient incremental algorithms for dynamic graph data. In this paper, we propose a suite of incremental k-core decomposition algorithms for dynamic graph data. These algorithms locate a small subgraph that ismore » guaranteed to contain the list of vertices whose maximum k-core values have changed and efficiently process this subgraph to update the k-core decomposition. We present incremental algorithms for both insertion and deletion operations, and propose auxiliary vertex state maintenance techniques that can further accelerate these operations. Our results show a significant reduction in runtime compared to non-incremental alternatives. We illustrate the efficiency of our algorithms on different types of real and synthetic graphs, at varying scales. Furthermore, for a graph of 16 million vertices, we observe relative throughputs reaching a million times, relative to the non-incremental algorithms.« less

Scaling Theory of Entanglement at the Many-Body Localization Transition.

PubMed

Dumitrescu, Philipp T; Vasseur, Romain; Potter, Andrew C

2017-09-15

We study the universal properties of eigenstate entanglement entropy across the transition between many-body localized (MBL) and thermal phases. We develop an improved real space renormalization group approach that enables numerical simulation of large system sizes and systematic extrapolation to the infinite system size limit. For systems smaller than the correlation length, the average entanglement follows a subthermal volume law, whose coefficient is a universal scaling function. The full distribution of entanglement follows a universal scaling form, and exhibits a bimodal structure that produces universal subleading power-law corrections to the leading volume law. For systems larger than the correlation length, the short interval entanglement exhibits a discontinuous jump at the transition from fully thermal volume law on the thermal side, to pure area law on the MBL side.

Variations of trends of indicators describing complex systems: Change of scaling precursory to extreme events

NASA Astrophysics Data System (ADS)

Keilis-Borok, V. I.; Soloviev, A. A.

2010-09-01

Socioeconomic and natural complex systems persistently generate extreme events also known as disasters, crises, or critical transitions. Here we analyze patterns of background activity preceding extreme events in four complex systems: economic recessions, surges in homicides in a megacity, magnetic storms, and strong earthquakes. We use as a starting point the indicators describing the system's behavior and identify changes in an indicator's trend. Those changes constitute our background events (BEs). We demonstrate a premonitory pattern common to all four systems considered: relatively large magnitude BEs become more frequent before extreme event. A premonitory change of scaling has been found in various models and observations. Here we demonstrate this change in scaling of uniformly defined BEs in four real complex systems, their enormous differences notwithstanding.

Energy scaling and reduction in controlling complex networks

PubMed Central

Chen, Yu-Zhong; Wang, Le-Zhi; Wang, Wen-Xu; Lai, Ying-Cheng

2016-01-01

Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as determined by the structural controllability theory, there is a high probability that the energy will diverge. We develop a physical theory to explain the scaling behaviour through identification of the fundamental structural elements, the longest control chains (LCCs), that dominate the control energy. Based on the LCCs, we articulate a strategy to drastically reduce the control energy (e.g. in a large number of real-world networks). Owing to their structural nature, the LCCs may shed light on energy issues associated with control of nonlinear dynamical networks. PMID:27152220

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

DOE PAGES

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.; ...

2016-11-07

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Real-time hydrological early warning system at national scale for surface water and groundwater with stakeholder involvement

NASA Astrophysics Data System (ADS)

He, X.; Stisen, S.; Henriksen, H. J.

2015-12-01

Hydrological models are important tools to support decision making in water resource management in the past few decades. Nowadays, frequent occurrence of extreme hydrological events has put focus on development of real-time hydrological modeling and forecasting systems. Among the various types of hydrological models, it is only the rainfall-runoff models for surface water that are commonly used in the online real-time fashion; and there is never a tradition to use integrated hydrological models for both surface water and groundwater with large scale perspective. At the Geological Survey of Denmark and Greenland (GEUS), we have setup and calibrated an integrated hydrological model that covers the entire nation, namely the DK-model. So far, the DK-model has only been used in offline mode for historical and future scenario simulations. Therefore, challenges arise when operating the DK-model in real-time mode due to lack of technical experiences and stakeholder awareness. In the present study, we try to demonstrate the process of bringing the DK-model online while actively involving the opinions of the stakeholders. Although the system is not yet fully operational, a prototype has been finished and presented to the stakeholders which can simulate groundwater levels, streamflow and water content in the root zone with a lead time of 48 hours and refreshed every 6 hours. The active involvement of stakeholders has provided very valuable insights and feedbacks for future improvements.

How Well Can a Footpoint Tracking Method Estimate the Magnetic Helicity Influx during Flux Emergence?

NASA Astrophysics Data System (ADS)

Choe, Gwangson; Kim, Sunjung; Kim, Kap-Sung; No, Jincheol

2015-08-01

As shown by Démoulin and Berger (2003), the magnetic helicity flux through the solar surface into the solar atmosphere can be exactly calculated if we can trace the motion of footpoints with infinite temporal and spatial resolutions. When there is a magnetic flux transport across the solar surface, the horizontal velocity of footpoints becomes infinite at the polarity inversion line, although the surface integral yielding the helicity flux does not diverge. In practical application, a finite temporal and spatial resolution causes an underestimate of the magnetic helicity flux when a magnetic flux emerges from below the surface, because there is an observational blackout area near a polarity inversion line whether it is pre-existing or newly formed. In this paper, we consider emergence of simple magnetic flux ropes and calculate the supremum of the magnitude of the helicity influx that can be estimated from footpoint tracking. The results depend on the ratio of the resolvable length scale and the flux rope diameter. For a Gold-Hoyle flux rope, in which all field lines are uniformly twisted, the observationally estimated helicity influx would be about 90% of the real influx when the flux rope diameter is one hundred times the spatial resolution (for a large flux rope), and about 45% when it is ten times (for a small flux rope). For Lundquist flux ropes, the errors incurred by observational estimation are smaller than the case of the Gold-Hoyle flux rope, but could be as large as 30% of the real influx. Our calculation suggests that the error in the helicity influx estimate is at least half of the real influx or even larger when small scale magnetic structures (less than 10,000 km) emerge into the solar atmosphere.

Visually Exploring Transportation Schedules.

PubMed

Palomo, Cesar; Guo, Zhan; Silva, Cláudio T; Freire, Juliana

2016-01-01

Public transportation schedules are designed by agencies to optimize service quality under multiple constraints. However, real service usually deviates from the plan. Therefore, transportation analysts need to identify, compare and explain both eventual and systemic performance issues that must be addressed so that better timetables can be created. The purely statistical tools commonly used by analysts pose many difficulties due to the large number of attributes at trip- and station-level for planned and real service. Also challenging is the need for models at multiple scales to search for patterns at different times and stations, since analysts do not know exactly where or when relevant patterns might emerge and need to compute statistical summaries for multiple attributes at different granularities. To aid in this analysis, we worked in close collaboration with a transportation expert to design TR-EX, a visual exploration tool developed to identify, inspect and compare spatio-temporal patterns for planned and real transportation service. TR-EX combines two new visual encodings inspired by Marey's Train Schedule: Trips Explorer for trip-level analysis of frequency, deviation and speed; and Stops Explorer for station-level study of delay, wait time, reliability and performance deficiencies such as bunching. To tackle overplotting and to provide a robust representation for a large numbers of trips and stops at multiple scales, the system supports variable kernel bandwidths to achieve the level of detail required by users for different tasks. We justify our design decisions based on specific analysis needs of transportation analysts. We provide anecdotal evidence of the efficacy of TR-EX through a series of case studies that explore NYC subway service, which illustrate how TR-EX can be used to confirm hypotheses and derive new insights through visual exploration.

Tackling some of the most intricate geophysical challenges via high-performance computing

NASA Astrophysics Data System (ADS)

Khosronejad, A.

2016-12-01

Recently, world has been witnessing significant enhancements in computing power of supercomputers. Computer clusters in conjunction with the advanced mathematical algorithms has set the stage for developing and applying powerful numerical tools to tackle some of the most intricate geophysical challenges that today`s engineers face. One such challenge is to understand how turbulent flows, in real-world settings, interact with (a) rigid and/or mobile complex bed bathymetry of waterways and sea-beds in the coastal areas; (b) objects with complex geometry that are fully or partially immersed; and (c) free-surface of waterways and water surface waves in the coastal area. This understanding is especially important because the turbulent flows in real-world environments are often bounded by geometrically complex boundaries, which dynamically deform and give rise to multi-scale and multi-physics transport phenomena, and characterized by multi-lateral interactions among various phases (e.g. air/water/sediment phases). Herein, I present some of the multi-scale and multi-physics geophysical fluid mechanics processes that I have attempted to study using an in-house high-performance computational model, the so-called VFS-Geophysics. More specifically, I will present the simulation results of turbulence/sediment/solute/turbine interactions in real-world settings. Parts of the simulations I present are performed to gain scientific insights into the processes such as sand wave formation (A. Khosronejad, and F. Sotiropoulos, (2014), Numerical simulation of sand waves in a turbulent open channel flow, Journal of Fluid Mechanics, 753:150-216), while others are carried out to predict the effects of climate change and large flood events on societal infrastructures ( A. Khosronejad, et al., (2016), Large eddy simulation of turbulence and solute transport in a forested headwater stream, Journal of Geophysical Research:, doi: 10.1002/2014JF003423).

Servo-hydraulic actuator in controllable canonical form: Identification and experimental validation

NASA Astrophysics Data System (ADS)

Maghareh, Amin; Silva, Christian E.; Dyke, Shirley J.

2018-02-01

Hydraulic actuators have been widely used to experimentally examine structural behavior at multiple scales. Real-time hybrid simulation (RTHS) is one innovative testing method that largely relies on such servo-hydraulic actuators. In RTHS, interface conditions must be enforced in real time, and controllers are often used to achieve tracking of the desired displacements. Thus, neglecting the dynamics of hydraulic transfer system may result either in system instability or sub-optimal performance. Herein, we propose a nonlinear dynamical model for a servo-hydraulic actuator (a.k.a. hydraulic transfer system) coupled with a nonlinear physical specimen. The nonlinear dynamical model is transformed into controllable canonical form for further tracking control design purposes. Through a number of experiments, the controllable canonical model is validated.

P-REx: The Piston Reconstruction Experiment for infrared interferometry

NASA Astrophysics Data System (ADS)

Widmann, Felix; Pott, Jörg-Uwe; Velasco, Sergio

2018-03-01

For sensitive infrared interferometry, it is crucial to control the differential piston evolution between the used telescopes. This is classically done by the use of a fringe tracker. In this work, we develop a new method to reconstruct the temporal piston variation from the atmosphere, by using real-time data from adaptive optics (AO) wavefront sensing: the Piston Reconstruction Experiment (P-REx). In order to understand the principle performance of the system in a realistic multilayer atmosphere, it is first extensively tested in simulations. The gained insights are then used to apply P-REx to real data, in order to demonstrate the benefit of using P-REx as an auxiliary system in a real interferometer. All tests show positive results, which encourages further research and eventually a real implementation. Especially, the tests on on-sky data showed that the atmosphere is, under decent observing conditions, sufficiently well structured and stable, in order to apply P-REx. It was possible to conveniently reconstruct the piston evolution in two-thirds of the data sets from good observing conditions (r0 ˜ 30 cm). The main conclusion is that applying the piston reconstruction in a real system would reduce the piston variation from around 10 μm down to 1-2 μm over time-scales of up to two seconds. This suggests an application for mid-infrared interferometry, for example for MATISSE at the very large telescope interferometer or the large binocular telescope interferometer. P-REx therefore provides the possibility to improve interferometric measurements without the need for more complex AO systems than already in regular use at 8-m-class telescopes.

A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks

PubMed Central

Yin, Junming; Ho, Qirong; Xing, Eric P.

2014-01-01

We propose a scalable approach for making inference about latent spaces of large networks. With a succinct representation of networks as a bag of triangular motifs, a parsimonious statistical model, and an efficient stochastic variational inference algorithm, we are able to analyze real networks with over a million vertices and hundreds of latent roles on a single machine in a matter of hours, a setting that is out of reach for many existing methods. When compared to the state-of-the-art probabilistic approaches, our method is several orders of magnitude faster, with competitive or improved accuracy for latent space recovery and link prediction. PMID:25400487

Stream computing for biomedical signal processing: A QRS complex detection case-study.

PubMed

Murphy, B M; O'Driscoll, C; Boylan, G B; Lightbody, G; Marnane, W P

2015-01-01

Recent developments in "Big Data" have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data.

Dynamic ruptures on faults of complex geometry: insights from numerical simulations, from large-scale curvature to small-scale fractal roughness

NASA Astrophysics Data System (ADS)

Ulrich, T.; Gabriel, A. A.

2016-12-01

The geometry of faults is subject to a large degree of uncertainty. As buried structures being not directly observable, their complex shapes may only be inferred from surface traces, if available, or through geophysical methods, such as reflection seismology. As a consequence, most studies aiming at assessing the potential hazard of faults rely on idealized fault models, based on observable large-scale features. Yet, real faults are known to be wavy at all scales, their geometric features presenting similar statistical properties from the micro to the regional scale. The influence of roughness on the earthquake rupture process is currently a driving topic in the computational seismology community. From the numerical point of view, rough faults problems are challenging problems that require optimized codes able to run efficiently on high-performance computing infrastructure and simultaneously handle complex geometries. Physically, simulated ruptures hosted by rough faults appear to be much closer to source models inverted from observation in terms of complexity. Incorporating fault geometry on all scales may thus be crucial to model realistic earthquake source processes and to estimate more accurately seismic hazard. In this study, we use the software package SeisSol, based on an ADER-Discontinuous Galerkin scheme, to run our numerical simulations. SeisSol allows solving the spontaneous dynamic earthquake rupture problem and the wave propagation problem with high-order accuracy in space and time efficiently on large-scale machines. In this study, the influence of fault roughness on dynamic rupture style (e.g. onset of supershear transition, rupture front coherence, propagation of self-healing pulses, etc) at different length scales is investigated by analyzing ruptures on faults of varying roughness spectral content. In particular, we investigate the existence of a minimum roughness length scale in terms of rupture inherent length scales below which the rupture ceases to be sensible. Finally, the effect of fault geometry on ground-motions, in the near-field, is considered. Our simulations feature a classical linear slip weakening on the fault and a viscoplastic constitutive model off the fault. The benefits of using a more elaborate fast velocity-weakening friction law will also be considered.

Impact vaporization: Late time phenomena from experiments

NASA Technical Reports Server (NTRS)

Schultz, P. H.; Gault, D. E.

1987-01-01

While simple airflow produced by the outward movement of the ejecta curtain can be scaled to large dimensions, the interaction between an impact-vaporized component and the ejecta curtain is more complicated. The goal of these experiments was to examine such interaction in a real system involving crater growth, ejection of material, two phased mixtures of gas and dust, and strong pressure gradients. The results will be complemented by theoretical studies at laboratory scales in order to separate the various parameters for planetary scale processes. These experiments prompt, however, the following conclusions that may have relevance at broader scales. First, under near vacuum or low atmospheric pressures, an expanding vapor cloud scours the surrounding surface in advance of arriving ejecta. Second, the effect of early-time vaporization is relatively unimportant at late-times. Third, the overpressure created within the crater cavity by significant vaporization results in increased cratering efficiency and larger aspect ratios.

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has tomore » gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a scaling study that compares instrumented ROSS simulations with their noninstrumented counterparts in order to determine the amount of perturbation when running at different simulation scales.« less

Scale-invariant structure of energy fluctuations in real earthquakes

NASA Astrophysics Data System (ADS)

Wang, Ping; Chang, Zhe; Wang, Huanyu; Lu, Hong

2017-11-01

Earthquakes are obviously complex phenomena associated with complicated spatiotemporal correlations, and they are generally characterized by two power laws: the Gutenberg-Richter (GR) and the Omori-Utsu laws. However, an important challenge has been to explain two apparently contrasting features: the GR and Omori-Utsu laws are scale-invariant and unaffected by energy or time scales, whereas earthquakes occasionally exhibit a characteristic energy or time scale, such as with asperity events. In this paper, three high-quality datasets on earthquakes were used to calculate the earthquake energy fluctuations at various spatiotemporal scales, and the results reveal the correlations between seismic events regardless of their critical or characteristic features. The probability density functions (PDFs) of the fluctuations exhibit evidence of another scaling that behaves as a q-Gaussian rather than random process. The scaling behaviors are observed for scales spanning three orders of magnitude. Considering the spatial heterogeneities in a real earthquake fault, we propose an inhomogeneous Olami-Feder-Christensen (OFC) model to describe the statistical properties of real earthquakes. The numerical simulations show that the inhomogeneous OFC model shares the same statistical properties with real earthquakes.

Development and validation of a real-time PCR assay for the detection of Toxoplasma gondii DNA in animal and meat samples.

PubMed

Marino, Anna Maria Fausta; Percipalle, Maurizio; Giunta, Renato Paolo; Salvaggio, Antonio; Caracappa, Giulia; Alfonzetti, Tiziana; Aparo, Alessandra; Reale, Stefano

2017-03-01

We report a rapid and reliable method for the detection of Toxoplasma gondii in meat and animal tissues based on real-time polymerase chain reaction (PCR). Samples were collected from cattle, small ruminants, horses, and pigs raised or imported into Sicily, Italy. All DNA preparations were assayed by real-time PCR tests targeted to a 98-bp long fragment in the AF 529-bp repeat element and to the B1 gene using specific primers. Diagnostic sensitivity (100%), diagnostic specificity (100%), limit of detection (0.01 pg), efficiency (92-109%), and precision (mean coefficient of variation = 0.60%), repeatability (100%), reproducibility (100%), and robustness were evaluated using 240 DNA extracted samples (120 positives and 120 negative as per the OIE nested PCR method) from different matrices. Positive results were confirmed by the repetition of both real-time and nested PCR assays. Our study demonstrates the viability of a reliable, rapid, and specific real-time PCR on a large scale to monitor contamination with Toxoplasma cysts in meat and animal specimens. This validated method can be used for postmortem detection in domestic and wild animals and for food safety purposes.

Simulated convective systems using a cloud resolving model: Impact of large-scale temperature and moisture forcing using observations and GEOS-3 reanalysis

NASA Technical Reports Server (NTRS)

Shie, C.-L.; Tao, W.-K.; Hou, A.; Lin, X.

2006-01-01

The GCE (Goddard Cumulus Ensemble) model, which has been developed and improved at NASA Goddard Space Flight Center over the past two decades, is considered as one of the finer and state-of-the-art CRMs (Cloud Resolving Models) in the research community. As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, GCE has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability. By basically using the large-scale temperature and moisture advective forcing, as well as the temperature, water vapor and wind fields obtained from TRMM (Tropical Rainfall Measuring Mission) field experiments such as SCSMEX (South China Sea Monsoon Experiment) and KWAJEX (Kwajalein Experiment), our recent 2-D and 3-D GCE simulations were able to capture detailed convective systems typical of the targeted (simulated) regions. The GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis data have also been proposed and successfully implemented for usage in the proposed/performed GCE long-term simulations (i.e., aiming at producing massive simulated cloud data -- Cloud Library) in compensating the scarcity of real field experimental data in both time and space (location). Preliminary 2-D or 3-D pilot results using GEOS-3 data have generally showed good qualitative agreement (yet some quantitative difference) with the respective numerical results using the SCSMEX observations. The first objective of this paper is to ensure the GEOS-3 data quality by comparing the model results obtained from several pairs of simulations using the real observations and GEOS-3 reanalysis data. The different large-scale advective forcing obtained from these two kinds of resources (i.e., sounding observations and GEOS-3 reanalysis) has been considered as a major critical factor in producing various model results. The second objective of this paper is therefore to investigate and present such an impact of large-scale forcing on various modeled quantities (such as hydrometeors, rainfall, and etc.). A third objective is to validate the overall GCE 3-D model performance by comparing the numerical results with sounding observations, as well as available satellite retrievals.

International land deals, local people's livelihood, and environment nexus (How to create win-win land deals in Ethiopia?)

NASA Astrophysics Data System (ADS)

Teklemariam Gebremeskel, Dereje; Witlox, Frank; Azadi, Hossein; Haile, Mitiku; Nyssen, Jan

2013-04-01

Following the global raise in demand for food and biofuel production, transnational companies are acquiring large scale agricultural land in developing countries such as Ethiopia. Considering land as one of the factors to be outsourced for development, the government of Ethiopia is supplying millions of hectares of land to transnational companies in the form of longterm lease. Many of the companies which engage in large scale land acquisition are of Indian, Chinese, Ethiopian diaspora, German, Malaysian, Italian, British, Dutch, Turkish, and Saudi-Arabian origin. The boom in the acquisition of farm land in the country has sparked an all-rounded debate among civil society groups, international institutions, nongovernmental organizations and independent development experts. The common reflections concerning the land deals in Ethiopia and elsewhere contain much rhetoric and hype which lack analysis of the real situation "on the ground" giving different connotations such as 'land grabbing', 'agricultural outsourcing', 'neo-colonialism', 'agrarian colonialism', and 'land underdevelopment'. However, deforestation, soil degradation, marginalization of local indigenous communities, and minimally unfair gains from investment by the host country are among the real points of concern arising out of the long term land lease contracts. Scientific evidence is lacking concerning the pragmatic impacts of large scale agricultural land acquisitions by transnational companies upon the natural environment (forest and land), local peoples' livelihood, and the contacting parties (the host country and the companies). The major objective of this study is to investigate the impacts in the context of Ethiopia, orienting to reinvent win-win land use models which constitute sustainable land use, local peoples' livelihood and the company-host country interests. To achieve this overall objective, the study employs a number of methods and methodologies constituting both qualitative and quantitative data analyses at different levels of focus ranging from household and farm levels to national and transnational. The study focuses on the western lowlands of Ethiopia where there are many companies engaged in large scale commercial farming, where 75% of it is below 1500 m a.s.l with average annual temperature of 20-25°C and annual rainfall of 500-1800 mm. Some preliminary exploratory findings indicate that there is massive land use conversion (deforestation) and 'voluntary' displacement of indigenous communities, which requires further triangulation. Key words: agricultural outsourcing; environmental services; land grabbing; sustainable livelihood; soil conservation

Portals for Real-Time Earthquake Data and Forecasting: Challenge and Promise (Invited)

NASA Astrophysics Data System (ADS)

Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Feltstykket, R.; Donnellan, A.; Glasscoe, M. T.

2013-12-01

Earthquake forecasts have been computed by a variety of countries world-wide for over two decades. For the most part, forecasts have been computed for insurance, reinsurance and underwriters of catastrophe bonds. However, recent events clearly demonstrate that mitigating personal risk is becoming the responsibility of individual members of the public. Open access to a variety of web-based forecasts, tools, utilities and information is therefore required. Portals for data and forecasts present particular challenges, and require the development of both apps and the client/server architecture to deliver the basic information in real time. The basic forecast model we consider is the Natural Time Weibull (NTW) method (JBR et al., Phys. Rev. E, 86, 021106, 2012). This model uses small earthquakes (';seismicity-based models') to forecast the occurrence of large earthquakes, via data-mining algorithms combined with the ANSS earthquake catalog. This method computes large earthquake probabilities using the number of small earthquakes that have occurred in a region since the last large earthquake. Localizing these forecasts in space so that global forecasts can be computed in real time presents special algorithmic challenges, which we describe in this talk. Using 25 years of data from the ANSS California-Nevada catalog of earthquakes, we compute real-time global forecasts at a grid scale of 0.1o. We analyze and monitor the performance of these models using the standard tests, which include the Reliability/Attributes and Receiver Operating Characteristic (ROC) tests. It is clear from much of the analysis that data quality is a major limitation on the accurate computation of earthquake probabilities. We discuss the challenges of serving up these datasets over the web on web-based platforms such as those at www.quakesim.org , www.e-decider.org , and www.openhazards.com.

Evidence for pollinator cost and farming benefits of neonicotinoid seed coatings on oilseed rape.

PubMed

Budge, G E; Garthwaite, D; Crowe, A; Boatman, N D; Delaplane, K S; Brown, M A; Thygesen, H H; Pietravalle, S

2015-08-13

Chronic exposure to neonicotinoid insecticides has been linked to reduced survival of pollinating insects at both the individual and colony level, but so far only experimentally. Analyses of large-scale datasets to investigate the real-world links between the use of neonicotinoids and pollinator mortality are lacking. Moreover, the impacts of neonicotinoid seed coatings in reducing subsequent applications of foliar insecticide sprays and increasing crop yield are not known, despite the supposed benefits of this practice driving widespread use. Here, we combine large-scale pesticide usage and yield observations from oilseed rape with those detailing honey bee colony losses over an 11 year period, and reveal a correlation between honey bee colony losses and national-scale imidacloprid (a neonicotinoid) usage patterns across England and Wales. We also provide the first evidence that farmers who use neonicotinoid seed coatings reduce the number of subsequent applications of foliar insecticide sprays and may derive an economic return. Our results inform the societal discussion on the pollinator costs and farming benefits of prophylactic neonicotinoid usage on a mass flowering crop.

Evidence for pollinator cost and farming benefits of neonicotinoid seed coatings on oilseed rape

NASA Astrophysics Data System (ADS)

Budge, G. E.; Garthwaite, D.; Crowe, A.; Boatman, N. D.; Delaplane, K. S.; Brown, M. A.; Thygesen, H. H.; Pietravalle, S.

2015-08-01

Chronic exposure to neonicotinoid insecticides has been linked to reduced survival of pollinating insects at both the individual and colony level, but so far only experimentally. Analyses of large-scale datasets to investigate the real-world links between the use of neonicotinoids and pollinator mortality are lacking. Moreover, the impacts of neonicotinoid seed coatings in reducing subsequent applications of foliar insecticide sprays and increasing crop yield are not known, despite the supposed benefits of this practice driving widespread use. Here, we combine large-scale pesticide usage and yield observations from oilseed rape with those detailing honey bee colony losses over an 11 year period, and reveal a correlation between honey bee colony losses and national-scale imidacloprid (a neonicotinoid) usage patterns across England and Wales. We also provide the first evidence that farmers who use neonicotinoid seed coatings reduce the number of subsequent applications of foliar insecticide sprays and may derive an economic return. Our results inform the societal discussion on the pollinator costs and farming benefits of prophylactic neonicotinoid usage on a mass flowering crop.

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Maximizing algebraic connectivity in air transportation networks

NASA Astrophysics Data System (ADS)

Wei, Peng

In air transportation networks the robustness of a network regarding node and link failures is a key factor for its design. An experiment based on the real air transportation network is performed to show that the algebraic connectivity is a good measure for network robustness. Three optimization problems of algebraic connectivity maximization are then formulated in order to find the most robust network design under different constraints. The algebraic connectivity maximization problem with flight routes addition or deletion is first formulated. Three methods to optimize and analyze the network algebraic connectivity are proposed. The Modified Greedy Perturbation Algorithm (MGP) provides a sub-optimal solution in a fast iterative manner. The Weighted Tabu Search (WTS) is designed to offer a near optimal solution with longer running time. The relaxed semi-definite programming (SDP) is used to set a performance upper bound and three rounding techniques are discussed to find the feasible solution. The simulation results present the trade-off among the three methods. The case study on two air transportation networks of Virgin America and Southwest Airlines show that the developed methods can be applied in real world large scale networks. The algebraic connectivity maximization problem is extended by adding the leg number constraint, which considers the traveler's tolerance for the total connecting stops. The Binary Semi-Definite Programming (BSDP) with cutting plane method provides the optimal solution. The tabu search and 2-opt search heuristics can find the optimal solution in small scale networks and the near optimal solution in large scale networks. The third algebraic connectivity maximization problem with operating cost constraint is formulated. When the total operating cost budget is given, the number of the edges to be added is not fixed. Each edge weight needs to be calculated instead of being pre-determined. It is illustrated that the edge addition and the weight assignment can not be studied separately for the problem with operating cost constraint. Therefore a relaxed SDP method with golden section search is developed to solve both at the same time. The cluster decomposition is utilized to solve large scale networks.

Long-term wave measurements in a climate change perspective.

NASA Astrophysics Data System (ADS)

Pomaro, Angela; Bertotti, Luciana; Cavaleri, Luigi; Lionello, Piero; Portilla-Yandun, Jesus

2017-04-01

At present multi-decadal time series of wave data needed for climate studies are generally provided by long term model simulations (hindcasts) covering the area of interest. Examples, among many, at different scales are wave hindcasts adopting the wind fields of the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF, Reading, U.K.) at the global level and by regional re-analysis as for the Mediterranean Sea (Lionello and Sanna, 2006). Valuable as they are, these estimates are necessarily affected by the approximations involved, the more so because of the problems encountered within modelling processes in small basins using coarse resolution wind fields (Cavaleri and Bertotti, 2004). On the contrary, multi-decadal observed time series are rare. They have the evident advantage of somehow representing the real evolution of the waves, without the shortcomings associated with the limitation of models in reproducing the actual processes and the real variability within the wave fields. Obviously, observed wave time series are not exempt of problems. They represent a very local information, hence their use to describe the wave evolution at large scale is sometimes arguable and, in general, it needs the support of model simulations assessing to which extent the local value is representative of a large scale evolution. Local effects may prevent the identification of trends that are indeed present at large scale. Moreover, a regular maintenance, accurate monitoring and metadata information are crucial issues when considering the reliability of a time series for climate applications. Of course, where available, especially if for several decades, measured data are of great value for a number of reasons and can be valuable clues to delve further into the physics of the processes of interest, especially if considering that waves, as an integrated product of the local climate, if available in an area sensitive to even limited changes of the large scale pattern, can provide related compact and meaningful information. In addition, the availability for the area of interest of a 20-year long dataset of directional spectra (in frequency and direction) offers an independent, but theoretically corresponding and significantly long dataset, allowing to penetrate the wave problem through different perspectives. In particular, we investigate the contribution of the individual wave systems that modulate the variability of waves in the Adriatic Sea. A characterization of wave conditions based on wave spectra in fact brings out a more detailed description of the different wave regimes, their associated meteorological conditions and their variation in time and geographical space.

Simulating large atmospheric phase screens using a woofer-tweeter algorithm.

PubMed

Buscher, David F

2016-10-03

We describe an algorithm for simulating atmospheric wavefront perturbations over ranges of spatial and temporal scales spanning more than 4 orders of magnitude. An open-source implementation of the algorithm written in Python can simulate the evolution of the perturbations more than an order-of-magnitude faster than real time. Testing of the implementation using metrics appropriate to adaptive optics systems and long-baseline interferometers show accuracies at the few percent level or better.

Incorporation of Outcome-Based Contract Requirements in a Real Options Approach for Maintenance Planning

DTIC Science & Technology

2016-04-30

focus on novel onshore/offshore and small/large scale wind turbine designs for expanding their operational range and increasing their efficiency at...of maintenance options created by the implementation of PHM in wind turbines . When an RUL is predicted for a subsystem, there are multiple choices...The section titled Example— Wind Turbine With an Outcome-Based Contract presents a case study for a PHM enabled wind turbine with and without an

The workshop. [use and application of remotely sensed data

NASA Technical Reports Server (NTRS)

Wake, W. H.

1981-01-01

The plan is presented for a two day workshop held to provide educational and training experience in the reading, interpretation, and application of LANDSAT and correlated larger scale imagery, digital printout maps, and other collateral material for a large number of participants with widely diverse levels of expertise, backgrounds, and occupations in government, industry, and education. The need for using surface truth field studies with correlated aerial imagery in solving real world problems was demonstrated.

Large-Scale Exploratory Analysis, Cleaning, and Modeling for Event Detection in Real-World Power Systems Data

DTIC Science & Technology

2013-11-01

big data with R is relatively new. RHadoop is a mature product from Revolution Analytics that uses R with Hadoop Streaming [15] and provides...agnostic all- data summaries or computations, in which case we use MapReduce directly. 2.3 D&R Software Environment In this work, we use the Hadoop ...job scheduling and tracking, data distribu- tion, system architecture, heterogeneity, and fault-tolerance. Hadoop also provides a distributed key-value

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System

PubMed Central

Liu, Youda; Wang, Xue; Liu, Yanchi; Cui, Sujin

2016-01-01

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems. PMID:27548171

Real-time PCR genotyping assay for canine progressive rod-cone degeneration and mutant allele frequency in Toy Poodles, Chihuahuas and Miniature Dachshunds in Japan.

PubMed

Kohyama, Moeko; Tada, Naomi; Mitsui, Hiroko; Tomioka, Hitomi; Tsutsui, Toshihiko; Yabuki, Akira; Rahman, Mohammad Mahbubur; Kushida, Kazuya; Mizukami, Keijiro; Yamato, Osamu

2016-03-01

Canine progressive rod-cone degeneration (PRCD) is a middle- to late-onset, autosomal recessive, inherited retinal disorder caused by a substitution (c.5G>A) in the canine PRCD gene that has been identified in 29 or more purebred dogs. In the present study, a TaqMan probe-based real-time PCR assay was developed and evaluated for rapid genotyping and large-scale screening of the mutation. Furthermore, a genotyping survey was carried out in a population of the three most popular breeds in Japan (Toy Poodles, Chihuahuas and Miniature Dachshunds) to determine the current mutant allele frequency. The assay separated all the genotypes of canine PRCD rapidly, indicating its suitability for large-scale surveys. The results of the survey showed that the mutant allele frequency in Toy Poodles was high enough (approximately 0.09) to allow the establishment of measures for the prevention and control of this disorder in breeding kennels. The mutant allele was detected in Chihuahuas for the first time, but the frequency was lower (approximately 0.02) than that in Toy Poodles. The mutant allele was not detected in Miniature Dachshunds. This assay will allow the selective breeding of dogs from the two most popular breeds (Toy Poodle and Chihuahua) in Japan and effective prevention or control of the disorder.

Powering up with indirect reciprocity in a large-scale field experiment

PubMed Central

Yoeli, Erez; Hoffman, Moshe; Rand, David G.; Nowak, Martin A.

2013-01-01

A defining aspect of human cooperation is the use of sophisticated indirect reciprocity. We observe others, talk about others, and act accordingly. We help those who help others, and we cooperate expecting that others will cooperate in return. Indirect reciprocity is based on reputation, which spreads by communication. A crucial aspect of indirect reciprocity is observability: reputation effects can support cooperation as long as peoples’ actions can be observed by others. In evolutionary models of indirect reciprocity, natural selection favors cooperation when observability is sufficiently high. Complimenting this theoretical work are experiments where observability promotes cooperation among small groups playing games in the laboratory. Until now, however, there has been little evidence of observability’s power to promote large-scale cooperation in real world settings. Here we provide such evidence using a field study involving 2413 subjects. We collaborated with a utility company to study participation in a program designed to prevent blackouts. We show that observability triples participation in this public goods game. The effect is over four times larger than offering a $25 monetary incentive, the company’s previous policy. Furthermore, as predicted by indirect reciprocity, we provide evidence that reputational concerns are driving our observability effect. In sum, we show how indirect reciprocity can be harnessed to increase cooperation in a relevant, real-world public goods game. PMID:23754399

Real-time PCR genotyping assay for canine progressive rod-cone degeneration and mutant allele frequency in Toy Poodles, Chihuahuas and Miniature Dachshunds in Japan

PubMed Central

KOHYAMA, Moeko; TADA, Naomi; MITSUI, Hiroko; TOMIOKA, Hitomi; TSUTSUI, Toshihiko; YABUKI, Akira; RAHMAN, Mohammad Mahbubur; KUSHIDA, Kazuya; MIZUKAMI, Keijiro; YAMATO, Osamu

2015-01-01

Canine progressive rod-cone degeneration (PRCD) is a middle- to late-onset, autosomal recessive, inherited retinal disorder caused by a substitution (c.5G>A) in the canine PRCD gene that has been identified in 29 or more purebred dogs. In the present study, a TaqMan probe-based real-time PCR assay was developed and evaluated for rapid genotyping and large-scale screening of the mutation. Furthermore, a genotyping survey was carried out in a population of the three most popular breeds in Japan (Toy Poodles, Chihuahuas and Miniature Dachshunds) to determine the current mutant allele frequency. The assay separated all the genotypes of canine PRCD rapidly, indicating its suitability for large-scale surveys. The results of the survey showed that the mutant allele frequency in Toy Poodles was high enough (approximately 0.09) to allow the establishment of measures for the prevention and control of this disorder in breeding kennels. The mutant allele was detected in Chihuahuas for the first time, but the frequency was lower (approximately 0.02) than that in Toy Poodles. The mutant allele was not detected in Miniature Dachshunds. This assay will allow the selective breeding of dogs from the two most popular breeds (Toy Poodle and Chihuahua) in Japan and effective prevention or control of the disorder. PMID:26549343

Multiwavelength active-optics Shack-Hartmann sensor for monitoring seeing and turbulence outer scale

NASA Astrophysics Data System (ADS)

Martinez, P.

2014-12-01

Context. Real-time seeing and outer-scale estimation at the location of the focus of a telescope is fundamental for predicting the adaptive-optics system's dimensioning and performance, as well as for the operational aspects of instruments. Aims: This study attempts to take advantage of multiwavelength long-exposure images to instantaneously and simultaneously derive the turbulence outer scale and seeing from the full width at half maximum (FWHM) of seeing-limited images taken at the focus of a telescope. These atmospheric parameters are commonly measured in most observatories by different methods located away from the telescope platform, thus differing from the effective estimates at the focus of a telescope, mainly because of differences in pointing orientation, height above the ground, or local seeing bias (dome contribution). Methods: Long-exposure images can either be provided directly by any multiwavelength scientific imager or spectrograph or, alternatively from a modified active-optics Shack-Hartmann sensor (AOSH). From measuring the AOSH sensor spot point spread function FWHMs simultaneously at different wavelengths, one can estimate the instantaneous outer scale in addition to seeing. Results: Multiwavelength long-exposure images provide access to accurate estimates of r0 and L0 by adequate means as long as precise FWHMs can be obtained. Although AOSH sensors are specified to measure not spot sizes but slopes, real-time r0, and L0 measurements from spot FWHMs can be obtained at the critical location where they are needed with major advantages over scientific instrument images: insensitivity to the telescope field stabilization, and continuous availability. Conclusions: Assuming an alternative optical design that allows simultaneous multiwavelength images, the AOSH sensor benefits from all the advantages of real-time seeing and outer scale monitoring. With the substantial interest in the design of extremely large telescopes, such a system could be of considerable importance.

Real-Time Quantum Dynamics of Long-Range Electronic Excitation Transfer in Plasmonic Nanoantennas.

PubMed

Ilawe, Niranjan V; Oviedo, M Belén; Wong, Bryan M

2017-08-08

Using large-scale, real-time, quantum dynamics calculations, we present a detailed analysis of electronic excitation transfer (EET) mechanisms in a multiparticle plasmonic nanoantenna system. Specifically, we utilize real-time, time-dependent, density functional tight binding (RT-TDDFTB) to provide a quantum-mechanical description (at an electronic/atomistic level of detail) for characterizing and analyzing these systems, without recourse to classical approximations. We also demonstrate highly long-range electronic couplings in these complex systems and find that the range of these couplings is more than twice the conventional cutoff limit considered by Förster resonance energy transfer (FRET)-based approaches. Furthermore, we attribute these unusually long-ranged electronic couplings to the coherent oscillations of conduction electrons in plasmonic nanoparticles. This long-range nature of plasmonic interactions has important ramifications for EET; in particular, we show that the commonly used "nearest-neighbor" FRET model is inadequate for accurately characterizing EET even in simple plasmonic antenna systems. These findings provide a real-time, quantum-mechanical perspective for understanding EET mechanisms and provide guidance in enhancing plasmonic properties in artificial light-harvesting systems.

Reconstruction of real-space linear matter power spectrum from multipoles of BOSS DR12 results

NASA Astrophysics Data System (ADS)

Lee, Seokcheon

2018-02-01

Recently, the power spectrum (PS) multipoles using the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 (DR12) sample are analyzed [1]. The based model for the analysis is the so-called TNS quasi-linear model and the analysis provides the multipoles up to the hexadecapole [2]. Thus, one might be able to recover the real-space linear matter PS by using the combinations of multipoles to investigate the cosmology [3]. We provide the analytic form of the ratio of quadrupole (hexadecapole) to monopole moments of the quasi-linear PS including the Fingers-of-God (FoG) effect to recover the real-space PS in the linear regime. One expects that observed values of the ratios of multipoles should be consistent with those of the linear theory at large scales. Thus, we compare the ratios of multipoles of the linear theory, including the FoG effect with the measured values. From these, we recover the linear matter power spectra in real-space. These recovered power spectra are consistent with the linear matter power spectra.

Real-time measurement of dust in the workplace using video exposure monitoring: Farming to pharmaceuticals

NASA Astrophysics Data System (ADS)

Walsh, P. T.; Forth, A. R.; Clark, R. D. R.; Dowker, K. P.; Thorpe, A.

2009-02-01

Real-time, photometric, portable dust monitors have been employed for video exposure monitoring (VEM) to measure and highlight dust levels generated by work activities, illustrate dust control techniques, and demonstrate good practice. Two workplaces, presenting different challenges for measurement, were used to illustrate the capabilities of VEM: (a) poultry farming activities and (b) powder transfer operations in a pharmaceutical company. For the poultry farm work, the real-time monitors were calibrated with respect to the respirable and inhalable dust concentrations using cyclone and IOM reference samplers respectively. Different rankings of exposure for typical activities were found on the small farm studied here compared to previous exposure measurements at larger poultry farms: these were mainly attributed to the different scales of operation. Large variations in the ratios of respirable, inhalable and real-time monitor TWA concentrations of poultry farm dust for various activities were found. This has implications for the calibration of light-scattering dust monitors with respect to inhalable dust concentration. In the pharmaceutical application, the effectiveness of a curtain barrier for dust control when dispensing powder in a downflow booth was rapidly demonstrated.

An efficient ASIC implementation of 16-channel on-line recursive ICA processor for real-time EEG system.

PubMed

Fang, Wai-Chi; Huang, Kuan-Ju; Chou, Chia-Ching; Chang, Jui-Chung; Cauwenberghs, Gert; Jung, Tzyy-Ping

2014-01-01

This is a proposal for an efficient very-large-scale integration (VLSI) design, 16-channel on-line recursive independent component analysis (ORICA) processor ASIC for real-time EEG system, implemented with TSMC 40 nm CMOS technology. ORICA is appropriate to be used in real-time EEG system to separate artifacts because of its highly efficient and real-time process features. The proposed ORICA processor is composed of an ORICA processing unit and a singular value decomposition (SVD) processing unit. Compared with previous work [1], this proposed ORICA processor has enhanced effectiveness and reduced hardware complexity by utilizing a deeper pipeline architecture, shared arithmetic processing unit, and shared registers. The 16-channel random signals which contain 8-channel super-Gaussian and 8-channel sub-Gaussian components are used to analyze the dependence of the source components, and the average correlation coefficient is 0.95452 between the original source signals and extracted ORICA signals. Finally, the proposed ORICA processor ASIC is implemented with TSMC 40 nm CMOS technology, and it consumes 15.72 mW at 100 MHz operating frequency.

A brief historical introduction to Euler's formula for polyhedra, topology, graph theory and networks

NASA Astrophysics Data System (ADS)

Debnath, Lokenath

2010-09-01

This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Königsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real physical systems are included. We also mention some important and modern applications of graph theory or network problems from transportation to telecommunications. Graphs or networks are effectively used as powerful tools in industrial, electrical and civil engineering, communication networks in the planning of business and industry. Graph theory and combinatorics can be used to understand the changes that occur in many large and complex scientific, technical and medical systems. With the advent of fast large computers and the ubiquitous Internet consisting of a very large network of computers, large-scale complex optimization problems can be modelled in terms of graphs or networks and then solved by algorithms available in graph theory. Many large and more complex combinatorial problems dealing with the possible arrangements of situations of various kinds, and computing the number and properties of such arrangements can be formulated in terms of networks. The Knight's tour problem, Hamilton's tour problem, problem of magic squares, the Euler Graeco-Latin squares problem and their modern developments in the twentieth century are also included.

Large-scale circulation patterns, instability factors and global precipitation modeling as influenced by external forcing

NASA Astrophysics Data System (ADS)

Bundel, A.; Kulikova, I.; Kruglova, E.; Muravev, A.

2003-04-01

The scope of the study is to estimate the relationship between large-scale circulation regimes, various instability indices and global precipitation with different boundary conditions, considered as external forcing. The experiments were carried out in the ensemble-prediction framework of the dynamic-statistical monthly forecast scheme run in the Hydrometeorological Research Center of Russia every ten days. The extension to seasonal intervals makes it necessary to investigate the role of slowly changing boundary conditions among which the sea surface temperature (SST) may be defined as the most effective factor. Continuous integrations of the global spectral T41L15 model for the whole year 2000 (starting from January 1) were performed with the climatic SST and the Reynolds Archive SSTs. Monthly values of the SST were projected on the year days using spline interpolation technique. First, the global precipitation values in experiments were compared to the GPCP (Global Precipitation Climate Program) daily observation data. Although the global mean precipitation is underestimated by the model, some large-scale regional amounts correspond to the real ones (e.g. for Europe) fairly well. On the whole, however, anomaly phases failed to be reproduced. The precipitation averaged over the whole land revealed a greater sensitivity to the SSTs than that over the oceans. The wavelet analysis was applied to separate the low- and high-frequency signal of the SST influence on the large-scale circulation and precipitation. A derivative of the Wallace-Gutzler teleconnection index for the East-Atlantic oscillation was taken as the circulation characteristic. The daily oscillation index values and precipitation amounts averaged over Europe were decomposed using wavelet approach with different “mother wavelets” up to approximation level 3. It was demonstrated that an increase in the precipitation amount over Europe was associated with the zonal flow intensification over the Northern Atlantic when the real SSTs were used. Blocking structures in the circulation caused decreasing precipitation amounts. The wavelet approach gave a more distinctive discrimination in the modeled circulation and precipitation patterns versus different external forcing than a number of other statistical techniques. Several atmospheric instability indices (e.g. the Phillips like parameters, Richardson number etc) were additionally used in post-processing for a more detailed validation of the modeled large-scale and total precipitation amounts. It was shown that a reasonable variety of instability indices must be used for such validations and for precipitation output corrections. Their statistical stability may be substantiated only on the ensemble modeling basis. This work was performed with the financial support of the Russian Foundation for Basic Research (02-05-64655).

Polar firn air reveals large-scale impact of anthropogenic mercury emissions during the 1970s.

PubMed

Faïn, Xavier; Ferrari, Christophe P; Dommergue, Aurélien; Albert, Mary R; Battle, Mark; Severinghaus, Jeff; Arnaud, Laurent; Barnola, Jean-Marc; Cairns, Warren; Barbante, Carlo; Boutron, Claude

2009-09-22

Mercury (Hg) is an extremely toxic pollutant, and its biogeochemical cycle has been perturbed by anthropogenic emissions during recent centuries. In the atmosphere, gaseous elemental mercury (GEM; Hg degrees ) is the predominant form of mercury (up to 95%). Here we report the evolution of atmospheric levels of GEM in mid- to high-northern latitudes inferred from the interstitial air of firn (perennial snowpack) at Summit, Greenland. GEM concentrations increased rapidly after World War II from approximately 1.5 ng m(-3) reaching a maximum of approximately 3 ng m(-3) around 1970 and decreased until stabilizing at approximately 1.7 ng m(-3) around 1995. This reconstruction reproduces real-time measurements available from the Arctic since 1995 and exhibits the same general trend observed in Europe since 1990. Anthropogenic emissions caused a two-fold rise in boreal atmospheric GEM concentrations before the 1970s, which likely contributed to higher deposition of mercury in both industrialized and remotes areas. Once deposited, this toxin becomes available for methylation and, subsequently, the contamination of ecosystems. Implementation of air pollution regulations, however, enabled a large-scale decline in atmospheric mercury levels during the 1980s. The results shown here suggest that potential increases in emissions in the coming decades could have a similar large-scale impact on atmospheric Hg levels.

General relativistic description of the observed galaxy power spectrum: Do we understand what we measure?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, Jaiyul

2010-10-15

We extend the general relativistic description of galaxy clustering developed in Yoo, Fitzpatrick, and Zaldarriaga (2009). For the first time we provide a fully general relativistic description of the observed matter power spectrum and the observed galaxy power spectrum with the linear bias ansatz. It is significantly different from the standard Newtonian description on large scales and especially its measurements on large scales can be misinterpreted as the detection of the primordial non-Gaussianity even in the absence thereof. The key difference in the observed galaxy power spectrum arises from the real-space matter fluctuation defined as the matter fluctuation at themore » hypersurface of the observed redshift. As opposed to the standard description, the shape of the observed galaxy power spectrum evolves in redshift, providing additional cosmological information. While the systematic errors in the standard Newtonian description are negligible in the current galaxy surveys at low redshift, correct general relativistic description is essential for understanding the galaxy power spectrum measurements on large scales in future surveys with redshift depth z{>=}3. We discuss ways to improve the detection significance in the current galaxy surveys and comment on applications of our general relativistic formalism in future surveys.« less

Molecular diagnosis of Plasmodium ovale by photo-induced electron transfer fluorogenic primers: PET-PCR

PubMed Central

Akerele, David; Ljolje, Dragan; Talundzic, Eldin; Udhayakumar, Venkatachalam

2017-01-01

Accurate diagnosis of malaria infections continues to be challenging and elusive, especially in the detection of submicroscopic infections. Developing new malaria diagnostic tools that are sensitive enough to detect low-level infections, user friendly, cost effective and capable of performing large scale diagnosis, remains critical. We have designed novel self-quenching photo-induced electron transfer (PET) fluorogenic primers for the detection of P. ovale by real-time PCR. In our study, a total of 173 clinical samples, consisting of different malaria species, were utilized to test this novel PET-PCR primer. The sensitivity and specificity were calculated using nested-PCR as the reference test. The novel primer set demonstrated a sensitivity of 97.5% and a specificity of 99.2% (95% CI 85.2–99.8% and 95.2–99.9% respectively). Furthermore, the limit of detection for P. ovale was found to be 1 parasite/μl. The PET-PCR assay is a new molecular diagnostic tool with comparable performance to other commonly used PCR methods. It is relatively easy to perform, and amiable to large scale malaria surveillance studies and malaria control and elimination programs. Further field validation of this novel primer will be helpful to ascertain the utility for large scale malaria screening programs. PMID:28640824

Molecular diagnosis of Plasmodium ovale by photo-induced electron transfer fluorogenic primers: PET-PCR.

PubMed

Akerele, David; Ljolje, Dragan; Talundzic, Eldin; Udhayakumar, Venkatachalam; Lucchi, Naomi W

2017-01-01

Accurate diagnosis of malaria infections continues to be challenging and elusive, especially in the detection of submicroscopic infections. Developing new malaria diagnostic tools that are sensitive enough to detect low-level infections, user friendly, cost effective and capable of performing large scale diagnosis, remains critical. We have designed novel self-quenching photo-induced electron transfer (PET) fluorogenic primers for the detection of P. ovale by real-time PCR. In our study, a total of 173 clinical samples, consisting of different malaria species, were utilized to test this novel PET-PCR primer. The sensitivity and specificity were calculated using nested-PCR as the reference test. The novel primer set demonstrated a sensitivity of 97.5% and a specificity of 99.2% (95% CI 85.2-99.8% and 95.2-99.9% respectively). Furthermore, the limit of detection for P. ovale was found to be 1 parasite/μl. The PET-PCR assay is a new molecular diagnostic tool with comparable performance to other commonly used PCR methods. It is relatively easy to perform, and amiable to large scale malaria surveillance studies and malaria control and elimination programs. Further field validation of this novel primer will be helpful to ascertain the utility for large scale malaria screening programs.

Dynamic displacement measurement of large-scale structures based on the Lucas-Kanade template tracking algorithm

NASA Astrophysics Data System (ADS)

Guo, Jie; Zhu, Chang`an

2016-01-01

The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.

Shortwave radiation parameterization scheme for subgrid topography

NASA Astrophysics Data System (ADS)

Helbig, N.; LöWe, H.

2012-02-01

Topography is well known to alter the shortwave radiation balance at the surface. A detailed radiation balance is therefore required in mountainous terrain. In order to maintain the computational performance of large-scale models while at the same time increasing grid resolutions, subgrid parameterizations are gaining more importance. A complete radiation parameterization scheme for subgrid topography accounting for shading, limited sky view, and terrain reflections is presented. Each radiative flux is parameterized individually as a function of sky view factor, slope and sun elevation angle, and albedo. We validated the parameterization with domain-averaged values computed from a distributed radiation model which includes a detailed shortwave radiation balance. Furthermore, we quantify the individual topographic impacts on the shortwave radiation balance. Rather than using a limited set of real topographies we used a large ensemble of simulated topographies with a wide range of typical terrain characteristics to study all topographic influences on the radiation balance. To this end slopes and partial derivatives of seven real topographies from Switzerland and the United States were analyzed and Gaussian statistics were found to best approximate real topographies. Parameterized direct beam radiation presented previously compared well with modeled values over the entire range of slope angles. The approximation of multiple, anisotropic terrain reflections with single, isotropic terrain reflections was confirmed as long as domain-averaged values are considered. The validation of all parameterized radiative fluxes showed that it is indeed not necessary to compute subgrid fluxes in order to account for all topographic influences in large grid sizes.

Numerical and Experimental Studies of Particle Settling in Real Fracture Geometries

NASA Astrophysics Data System (ADS)

Roy, Pratanu; Du Frane, Wyatt L.; Kanarska, Yuliya; Walsh, Stuart D. C.

2016-11-01

Proppant is a vital component of hydraulic stimulation operations, improving conductivity by maintaining fracture aperture. While correct placement is a necessary part of ensuring that proppant performs efficiently, the transport behavior of proppant in natural rock fractures is poorly understood. In particular, as companies pursue new propping strategies involving new types of proppant, more accurate models of proppant behavior are needed to help guide their deployment. A major difficulty with simulating reservoir-scale proppant behavior is that continuum models traditionally used to represent large-scale slurry behavior loose applicability in fracture geometries. Particle transport models are often based on representative volumes that are at the same scale or larger than fractures found in hydraulic fracturing operations, making them inappropriate for modeling these types of flows. In the absence of a first-principles approach, empirical closure relations are needed. However, even such empirical closure relationships are difficult to derive without an accurate understanding of proppant behavior on the particle level. Thus, there is a need for experiments and simulations capable of probing phenomena at the sub-fracture scale. In this paper, we present results from experimental and numerical studies investigating proppant behavior at the sub-fracture level, in particular, the role of particle dispersion during proppant settling. In the experimental study, three-dimensional printing techniques are used to accurately reproduce the topology of a fractured Marcellus shale sample inside a particle-flow cell. By recreating the surface in clear plastic resin, proppant movement within the fracture can be tracked directly in real time without the need for X-ray imaging. Particle tracking is further enhanced through the use of mixtures of transparent and opaque proppant analogues. The accompanying numerical studies employ a high-fidelity three-dimensional particle-flow model, capable of explicitly representing the particles, the fracture surface and the interstitial fluid flow. Both studies reveal large-scale vortex motion during particle settling. For the most part, this behavior is independent of the fracture topology, instead driven by interactions between the sinking particles and the upwelling interstitial fluid. This motion results in large amounts of particle dispersion, significantly greater than might be expected from traditional slurry models. The competition between the particles and the fluid also results in a redistribution of particles toward the fracture walls, which has significant implications for the transport of proppant along the fracture.

Real Time Large Memory Optical Pattern Recognition.

DTIC Science & Technology

1984-06-01

AD-Ri58 023 REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION(U) - h ARMY MISSILE COMMAND REDSTONE ARSENAL AL RESEARCH DIRECTORATE D A GREGORY JUN...TECHNICAL REPORT RR-84-9 Ln REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION Don A. Gregory Research Directorate US Army Missile Laboratory JUNE 1984 L...RR-84-9 , ___/_ _ __ _ __ _ __ _ __"__ _ 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED Real Time Large Memory Optical Pattern Technical

High Resolution Imaging of the Sun with CORONAS-1

NASA Technical Reports Server (NTRS)

Karovska, Margarita

1998-01-01

We applied several image restoration and enhancement techniques, to CORONAS-I images. We carried out the characterization of the Point Spread Function (PSF) using the unique capability of the Blind Iterative Deconvolution (BID) technique, which recovers the real PSF at a given location and time of observation, when limited a priori information is available on its characteristics. We also applied image enhancement technique to extract the small scale structure imbeded in bright large scale structures on the disk and on the limb. The results demonstrate the capability of the image post-processing to substantially increase the yield from the space observations by improving the resolution and reducing noise in the images.

An ignition key for atomic-scale engines

NASA Astrophysics Data System (ADS)

Dundas, Daniel; Cunningham, Brian; Buchanan, Claire; Terasawa, Asako; Paxton, Anthony T.; Todorov, Tchavdar N.

2012-10-01

A current-carrying resonant nanoscale device, simulated by non-adiabatic molecular dynamics, exhibits sharp activation of non-conservative current-induced forces with bias. The result, above the critical bias, is generalized rotational atomic motion with a large gain in kinetic energy. The activation exploits sharp features in the electronic structure, and constitutes, in effect, an ignition key for atomic-scale motors. A controlling factor for the effect is the non-equilibrium dynamical response matrix for small-amplitude atomic motion under current. This matrix can be found from the steady-state electronic structure by a simpler static calculation, providing a way to detect the likely appearance, or otherwise, of non-conservative dynamics, in advance of real-time modelling.

Landau damping of electrostatic waves in arbitrarily degenerate quantum plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rightley, Shane, E-mail: shane.rightley@colorado.edu; Uzdensky, Dmitri, E-mail: uzdensky@colorado.edu

2016-03-15

We carry out a systematic study of the dispersion relation for linear electrostatic waves in an arbitrarily degenerate quantum electron plasma. We solve for the complex frequency spectrum for arbitrary values of wavenumber k and level of degeneracy μ. Our finding is that for large k and high μ the real part of the frequency ω{sub r} grows linearly with k and scales with μ, only because of the scaling of the Fermi energy. In this regime, the relative Landau damping rate γ/ω{sub r} becomes independent of k and varies inversely with μ. Thus, damping is weak but finite atmore » moderate levels of degeneracy for short wavelengths.« less

The Large Local Hole in the Galaxy Distribution: The 2MASS Galaxy Angular Power Spectrum

NASA Astrophysics Data System (ADS)

Frith, W. J.; Outram, P. J.; Shanks, T.

2005-06-01

We present new evidence for a large deficiency in the local galaxy distribution situated in the ˜4000 deg2 APM survey area. We use models guided by the 2dF Galaxy Redshift Survey (2dFGRS) n(z) as a probe of the underlying large-scale structure. We first check the usefulness of this technique by comparing the 2dFGRS n(z) model prediction with the K-band and B-band number counts extracted from the 2MASS and 2dFGRS parent catalogues over the 2dFGRS Northern and Southern declination strips, before turning to a comparison with the APM counts. We find that the APM counts in both the B and K-bands indicate a deficiency in the local galaxy distribution of ˜30% to z ≈ 0.1 over the entire APM survey area. We examine the implied significance of such a large local hole, considering several possible forms for the real-space correlation function. We find that such a deficiency in the APM survey area indicates an excess of power at large scales over what is expected from the correlation function observed in 2dFGRS correlation function or predicted from ΛCDM Hubble Volume mock catalogues. In order to check further the clustering at large scales in the 2MASS data, we have calculated the angular power spectrum for 2MASS galaxies. Although in the linear regime (l<30), ΛCDM models can give a good fit to the 2MASS angular power spectrum, over a wider range (l<100) the power spectrum from Hubble Volume mock catalogues suggests that scale-dependent bias may be needed for ΛCDM to fit. However, the modest increase in large-scale power observed in the 2MASS angular power spectrum is still not enough to explain the local hole. If the APM survey area really is 25% deficient in galaxies out to z≈0.1, explanations for the disagreement with observed galaxy clustering statistics include the possibilities that the galaxy clustering is non-Gaussian on large scales or that the 2MASS volume is still too small to represent a `fair sample' of the Universe. Extending the 2dFGRS redshift survey over the whole APM area would resolve many of the remaining questions about the existence and interpretation of this local hole.

Neutron Spectrometer Prospecting During the Mojave Volatiles Project Analog Field Test

NASA Technical Reports Server (NTRS)

Elphic, R. C.; Heldmann, J. L.; Colaprete, A.; Hunt, D. R.; Deans, M C.; Lim, D. S.; Foil, G.; Fong, T.

2015-01-01

We know there are volatiles sequestered at the poles of the Moon. While we have evidence of water ice and a number of other compounds based on remote sensing, the detailed distribution, and physical and chemical form are largely unknown. Additional orbital studies of lunar polar volatiles may yield further insights, but the most important next step is to use landed assets to fully characterize the volatile composition and distribution at scales of tens to hundreds of meters. To achieve this range of scales, mobility is needed. Because of the proximity of the Moon, near real-time operation of the surface assets is possible, with an associated reduction in risk and cost. This concept of operations is very different from that of rovers on Mars, and new operational approaches are required to carry out such real-time robotic exploration. The Mojave Volatiles Project (MVP) is a Moon- Mars Analog Mission Activities (MMAMA) program effort aimed at (1) determining effective approaches to operating a real-time but short-duration lunar surface robotic mission, and (2) performing prospecting science in a natural setting, as a test of these approaches. We know there are volatiles sequestered at the poles of the Moon. While we have evidence of water ice and a number of other compounds based on remote sensing, the detailed distribution, and physical and chemical form are largely unknown. Additional orbital studies of lunar polar volatiles may yield further insights, but the most important next step is to use landed assets to fully characterize the volatile composition and distribution at scales of tens to hundreds of meters. To achieve this range of scales, mobility is needed. Because of the proximity of the Moon, near real-time operation of the surface assets is possible, with an associated reduction in risk and cost. This concept of operations is very different from that of rovers on Mars, and new operational approaches are required to carry out such robotic exploration. The Mojave Volatiles Project (MVP) is a Moon- Mars Analog Mission Activities (MMAMA) program effort aimed at (1) determining effective approaches to operating a real-time but short-duration lunar surface robotic mission, and (2) performing prospecting science in a natural setting, as a test of these approaches. Here we describe some results from the first such test, carried out in the Mojave Desert between 16 and 24 October, 2014. The test site was an alluvial fan just E of the Soda Mountains, SW of Baker, California. This site contains desert pavements, ranging from the late Pleistocene to early-Holocene in age. These pavements are undergoing dissection by the ongoing development of washes. A principal objective was to determine the hydration state of different types of desert pavement and bare ground features. The mobility element of the test was provided by the KREX-2 rover, designed and operated by the Intelligent Robotics Group at NASA Ames Research Center.

The PREP pipeline: standardized preprocessing for large-scale EEG analysis.

PubMed

Bigdely-Shamlo, Nima; Mullen, Tim; Kothe, Christian; Su, Kyung-Min; Robbins, Kay A

2015-01-01

The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP) and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode.

Multi-granularity Bandwidth Allocation for Large-Scale WDM/TDM PON

NASA Astrophysics Data System (ADS)

Gao, Ziyue; Gan, Chaoqin; Ni, Cuiping; Shi, Qiongling

2017-12-01

WDM (wavelength-division multiplexing)/TDM (time-division multiplexing) PON (passive optical network) is being viewed as a promising solution for delivering multiple services and applications, such as high-definition video, video conference and data traffic. Considering the real-time transmission, QoS (quality of services) requirements and differentiated services model, a multi-granularity dynamic bandwidth allocation (DBA) in both domains of wavelengths and time for large-scale hybrid WDM/TDM PON is proposed in this paper. The proposed scheme achieves load balance by using the bandwidth prediction. Based on the bandwidth prediction, the wavelength assignment can be realized fairly and effectively to satisfy the different demands of various classes. Specially, the allocation of residual bandwidth further augments the DBA and makes full use of bandwidth resources in the network. To further improve the network performance, two schemes named extending the cycle of one free wavelength (ECoFW) and large bandwidth shrinkage (LBS) are proposed, which can prevent transmission from interruption when the user employs more than one wavelength. The simulation results show the effectiveness of the proposed scheme.

Are Superplumes a Myth?

NASA Astrophysics Data System (ADS)

Steinberger, Bernhard; Conrad, Clinton

2017-04-01

Two large seismically slow lower mantle regions beneath the Pacific and Africa are sometimes referred to as "superplumes". This names evokes associations of large-scale active upwellings, however it is not clear whether these are real, or rather just regular mantle plumes occur more frequently in these regions. Here we study the implications of new results on dynamic topography, which would be associated with active upwellings, on this question. Recently, Hoggard et al. (2016) developed a detailed model of marine residual topography, after subtracting isostatic crustal topography. Combining this with results from continents, a global model can be expanded in spherical harmonics. Comparison with dynamic topography derived from mantle flow models inferred from seismic tomography (Steinberger, 2016) yields overall good agreement and similar power spectra, except at spherical harmonic degree two where mantle flow models predict about six times as much power as is inferred from observations: Mantle flow models feature two large-scale antipodal upwellings at the seismically slow regions, whereas the actual topography gives only little indication of these. We will discuss here what this discrepancy could possibly mean and how it could be resolved.

Plate motions and deformations from geologic and geodetic data

NASA Technical Reports Server (NTRS)

Jordan, Thomas H.

1990-01-01

An analysis of geodetic data in the vicinity of the Crustal Dynamics Program (CDP) site at Vandenberg Air Force Base (VNDN) is presented. The utility of space-geodetic data in the monitoring of transient strains associated with earthquakes in tectonically active areas like California is investigated. Particular interest is in the possibility that space-geodetic methods may be able to provide critical new data on deformations precursory to large seismic events. Although earthquake precursory phenomena are not well understood, the monitoring of small strains in the vicinity of active faults is a promising technique for studying the mechanisms that nucleate large earthquakes and, ultimately, for earthquake prediction. Space-geodetic techniques are now capable of measuring baselines of tens to hundreds of kilometers with a precision of a few parts in 108. Within the next few years, it will be possible to record and analyze large-scale strain variations with this precision continuously in real time. Thus, space-geodetic techniques may become tools for earthquake prediction. In anticipation of this capability, several questions related to the temporal and spatial scales associated with subseismic deformation transients are examined.

Highly multiplexed targeted proteomics using precise control of peptide retention time.

PubMed

Gallien, Sebastien; Peterman, Scott; Kiyonami, Reiko; Souady, Jamal; Duriez, Elodie; Schoen, Alan; Domon, Bruno

2012-04-01

Large-scale proteomics applications using SRM analysis on triple quadrupole mass spectrometers present new challenges to LC-MS/MS experimental design. Despite the automation of building large-scale LC-SRM methods, the increased numbers of targeted peptides can compromise the balance between sensitivity and selectivity. To facilitate large target numbers, time-scheduled SRM transition acquisition is performed. Previously published results have demonstrated incorporation of a well-characterized set of synthetic peptides enabled chromatographic characterization of the elution profile for most endogenous peptides. We have extended this application of peptide trainer kits to not only build SRM methods but to facilitate real-time elution profile characterization that enables automated adjustment of the scheduled detection windows. Incorporation of dynamic retention time adjustments better facilitate targeted assays lasting several days without the need for constant supervision. This paper provides an overview of how the dynamic retention correction approach identifies and corrects for commonly observed LC variations. This adjustment dramatically improves robustness in targeted discovery experiments as well as routine quantification experiments. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of a GNSS-Enhanced Tsunami Early Warning System

NASA Astrophysics Data System (ADS)

Bawden, G. W.; Melbourne, T. I.; Bock, Y.; Song, Y. T.; Komjathy, A.

2015-12-01

The past decade has witnessed a terrible loss of life and economic disruption caused by large earthquakes and resultant tsunamis impacting coastal communities and infrastructure across the Indo-Pacific region. NASA has funded the early development of a prototype real-time Global Navigation Satellite System (RT-GNSS) based rapid earthquake and tsunami early warning (GNSS-TEW) system that may be used to enhance seismic tsunami early warning systems for large earthquakes. This prototype GNSS-TEW system geodetically estimates fault parameters (earthquake magnitude, location, strike, dip, and slip magnitude/direction on a gridded fault plane both along strike and at depth) and tsunami source parameters (seafloor displacement, tsunami energy scale, and 3D tsunami initials) within minutes after the mainshock based on dynamic numerical inversions/regressions of the real-time measured displacements within a spatially distributed real-time GNSS network(s) spanning the epicentral region. It is also possible to measure fluctuations in the ionosphere's total electron content (TEC) in the RT-GNSS data caused by the pressure wave from the tsunami. This TEC approach can detect if a tsunami has been triggered by an earthquake, track its waves as they propagate through the oceanic basins, and provide upwards of 45 minutes early warning. These combined real-time geodetic approaches will very quickly address a number of important questions in the immediate minutes following a major earthquake: How big was the earthquake and what are its fault parameters? Could the earthquake have produced a tsunami and was a tsunami generated?

Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments.

PubMed

Ionescu, Catalin; Papava, Dragos; Olaru, Vlad; Sminchisescu, Cristian

2014-07-01

We introduce a new dataset, Human3.6M, of 3.6 Million accurate 3D Human poses, acquired by recording the performance of 5 female and 6 male subjects, under 4 different viewpoints, for training realistic human sensing systems and for evaluating the next generation of human pose estimation models and algorithms. Besides increasing the size of the datasets in the current state-of-the-art by several orders of magnitude, we also aim to complement such datasets with a diverse set of motions and poses encountered as part of typical human activities (taking photos, talking on the phone, posing, greeting, eating, etc.), with additional synchronized image, human motion capture, and time of flight (depth) data, and with accurate 3D body scans of all the subject actors involved. We also provide controlled mixed reality evaluation scenarios where 3D human models are animated using motion capture and inserted using correct 3D geometry, in complex real environments, viewed with moving cameras, and under occlusion. Finally, we provide a set of large-scale statistical models and detailed evaluation baselines for the dataset illustrating its diversity and the scope for improvement by future work in the research community. Our experiments show that our best large-scale model can leverage our full training set to obtain a 20% improvement in performance compared to a training set of the scale of the largest existing public dataset for this problem. Yet the potential for improvement by leveraging higher capacity, more complex models with our large dataset, is substantially vaster and should stimulate future research. The dataset together with code for the associated large-scale learning models, features, visualization tools, as well as the evaluation server, is available online at http://vision.imar.ro/human3.6m.

Development of an Efficient Binaural Simulation for the Analysis of Structural Acoustic Data

NASA Technical Reports Server (NTRS)

Lalime, Aimee L.; Johnson, Marty E.; Rizzi, Stephen A. (Technical Monitor)

2002-01-01

Binaural or "virtual acoustic" representation has been proposed as a method of analyzing acoustic and vibroacoustic data. Unfortunately, this binaural representation can require extensive computer power to apply the Head Related Transfer Functions (HRTFs) to a large number of sources, as with a vibrating structure. This work focuses on reducing the number of real-time computations required in this binaural analysis through the use of Singular Value Decomposition (SVD) and Equivalent Source Reduction (ESR). The SVD method reduces the complexity of the HRTF computations by breaking the HRTFs into dominant singular values (and vectors). The ESR method reduces the number of sources to be analyzed in real-time computation by replacing sources on the scale of a structural wavelength with sources on the scale of an acoustic wavelength. It is shown that the effectiveness of the SVD and ESR methods improves as the complexity of the source increases. In addition, preliminary auralization tests have shown that the results from both the SVD and ESR methods are indistinguishable from the results found with the exhaustive method.

Graph processing platforms at scale: practices and experiences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, Seung-Hwan; Lee, Sangkeun; Brown, Tyler C

2015-01-01

Graph analysis unveils hidden associations of data in many phenomena and artifacts, such as road network, social networks, genomic information, and scientific collaboration. Unfortunately, a wide diversity in the characteristics of graphs and graph operations make it challenging to find a right combination of tools and implementation of algorithms to discover desired knowledge from the target data set. This study presents an extensive empirical study of three representative graph processing platforms: Pegasus, GraphX, and Urika. Each system represents a combination of options in data model, processing paradigm, and infrastructure. We benchmarked each platform using three popular graph operations, degree distribution,more » connected components, and PageRank over a variety of real-world graphs. Our experiments show that each graph processing platform shows different strength, depending the type of graph operations. While Urika performs the best in non-iterative operations like degree distribution, GraphX outputforms iterative operations like connected components and PageRank. In addition, we discuss challenges to optimize the performance of each platform over large scale real world graphs.« less

Detecting the Influence of Spreading in Social Networks with Excitable Sensor Networks

PubMed Central

Pei, Sen; Tang, Shaoting; Zheng, Zhiming

2015-01-01

Detecting spreading outbreaks in social networks with sensors is of great significance in applications. Inspired by the formation mechanism of humans’ physical sensations to external stimuli, we propose a new method to detect the influence of spreading by constructing excitable sensor networks. Exploiting the amplifying effect of excitable sensor networks, our method can better detect small-scale spreading processes. At the same time, it can also distinguish large-scale diffusion instances due to the self-inhibition effect of excitable elements. Through simulations of diverse spreading dynamics on typical real-world social networks (Facebook, coauthor, and email social networks), we find that the excitable sensor networks are capable of detecting and ranking spreading processes in a much wider range of influence than other commonly used sensor placement methods, such as random, targeted, acquaintance and distance strategies. In addition, we validate the efficacy of our method with diffusion data from a real-world online social system, Twitter. We find that our method can detect more spreading topics in practice. Our approach provides a new direction in spreading detection and should be useful for designing effective detection methods. PMID:25950181

A multi-frequency receiver function inversion approach for crustal velocity structure

NASA Astrophysics Data System (ADS)

Li, Xuelei; Li, Zhiwei; Hao, Tianyao; Wang, Sheng; Xing, Jian

2017-05-01

In order to constrain the crustal velocity structures better, we developed a new nonlinear inversion approach based on multi-frequency receiver function waveforms. With the global optimizing algorithm of Differential Evolution (DE), low-frequency receiver function waveforms can primarily constrain large-scale velocity structures, while high-frequency receiver function waveforms show the advantages in recovering small-scale velocity structures. Based on the synthetic tests with multi-frequency receiver function waveforms, the proposed approach can constrain both long- and short-wavelength characteristics of the crustal velocity structures simultaneously. Inversions with real data are also conducted for the seismic stations of KMNB in southeast China and HYB in Indian continent, where crustal structures have been well studied by former researchers. Comparisons of inverted velocity models from previous and our studies suggest good consistency, but better waveform fitness with fewer model parameters are achieved by our proposed approach. Comprehensive tests with synthetic and real data suggest that the proposed inversion approach with multi-frequency receiver function is effective and robust in inverting the crustal velocity structures.

Real-time distribution of pelagic fish: combining hydroacoustics, GIS and spatial modelling at a fine spatial scale.

PubMed

Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan

2018-03-29

Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.

Fast Updating National Geo-Spatial Databases with High Resolution Imagery: China's Methodology and Experience

NASA Astrophysics Data System (ADS)

Chen, J.; Wang, D.; Zhao, R. L.; Zhang, H.; Liao, A.; Jiu, J.

2014-04-01

Geospatial databases are irreplaceable national treasure of immense importance. Their up-to-dateness referring to its consistency with respect to the real world plays a critical role in its value and applications. The continuous updating of map databases at 1:50,000 scales is a massive and difficult task for larger countries of the size of more than several million's kilometer squares. This paper presents the research and technological development to support the national map updating at 1:50,000 scales in China, including the development of updating models and methods, production tools and systems for large-scale and rapid updating, as well as the design and implementation of the continuous updating workflow. The use of many data sources and the integration of these data to form a high accuracy, quality checked product were required. It had in turn required up to date techniques of image matching, semantic integration, generalization, data base management and conflict resolution. Design and develop specific software tools and packages to support the large-scale updating production with high resolution imagery and large-scale data generalization, such as map generalization, GIS-supported change interpretation from imagery, DEM interpolation, image matching-based orthophoto generation, data control at different levels. A national 1:50,000 databases updating strategy and its production workflow were designed, including a full coverage updating pattern characterized by all element topographic data modeling, change detection in all related areas, and whole process data quality controlling, a series of technical production specifications, and a network of updating production units in different geographic places in the country.

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Evolutionary dynamics of social dilemmas in structured heterogeneous populations.

PubMed

Santos, F C; Pacheco, J M; Lenaerts, Tom

2006-02-28

Real populations have been shown to be heterogeneous, in which some individuals have many more contacts than others. This fact contrasts with the traditional homogeneous setting used in studies of evolutionary game dynamics. We incorporate heterogeneity in the population by studying games on graphs, in which the variability in connectivity ranges from single-scale graphs, for which heterogeneity is small and associated degree distributions exhibit a Gaussian tale, to scale-free graphs, for which heterogeneity is large with degree distributions exhibiting a power-law behavior. We study the evolution of cooperation, modeled in terms of the most popular dilemmas of cooperation. We show that, for all dilemmas, increasing heterogeneity favors the emergence of cooperation, such that long-term cooperative behavior easily resists short-term noncooperative behavior. Moreover, we show how cooperation depends on the intricate ties between individuals in scale-free populations.

Real-time gray-scale photolithography for fabrication of continuous microstructure

NASA Astrophysics Data System (ADS)

Peng, Qinjun; Guo, Yongkang; Liu, Shijie; Cui, Zheng

2002-10-01

A novel real-time gray-scale photolithography technique for the fabrication of continuous microstructures that uses a LCD panel as a real-time gray-scale mask is presented. The principle of design of the technique is explained, and computer simulation results based on partially coherent imaging theory are given for the patterning of a microlens array and a zigzag grating. An experiment is set up, and a microlens array and a zigzag grating on panchromatic silver halide sensitized gelatin with trypsinase etching are obtained.