Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

A multidisciplinary approach to the development of low-cost high-performance lightwave networks

NASA Technical Reports Server (NTRS)

Maitan, Jacek; Harwit, Alex

1991-01-01

Our research focuses on high-speed distributed systems. We anticipate that our results will allow the fabrication of low-cost networks employing multi-gigabit-per-second data links for space and military applications. The recent development of high-speed low-cost photonic components and new generations of microprocessors creates an opportunity to develop advanced large-scale distributed information systems. These systems currently involve hundreds of thousands of nodes and are made up of components and communications links that may fail during operation. In order to realize these systems, research is needed into technologies that foster adaptability and scaleability. Self-organizing mechanisms are needed to integrate a working fabric of large-scale distributed systems. The challenge is to fuse theory, technology, and development methodologies to construct a cost-effective, efficient, large-scale system.

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

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.

Designing and developing portable large-scale JavaScript web applications within the Experiment Dashboard framework

NASA Astrophysics Data System (ADS)

Andreeva, J.; Dzhunov, I.; Karavakis, E.; Kokoszkiewicz, L.; Nowotka, M.; Saiz, P.; Tuckett, D.

2012-12-01

Improvements in web browser performance and web standards compliance, as well as the availability of comprehensive JavaScript libraries, provides an opportunity to develop functionally rich yet intuitive web applications that allow users to access, render and analyse data in novel ways. However, the development of such large-scale JavaScript web applications presents new challenges, in particular with regard to code sustainability and team-based work. We present an approach that meets the challenges of large-scale JavaScript web application design and development, including client-side model-view-controller architecture, design patterns, and JavaScript libraries. Furthermore, we show how the approach leads naturally to the encapsulation of the data source as a web API, allowing applications to be easily ported to new data sources. The Experiment Dashboard framework is used for the development of applications for monitoring the distributed computing activities of virtual organisations on the Worldwide LHC Computing Grid. We demonstrate the benefits of the approach for large-scale JavaScript web applications in this context by examining the design of several Experiment Dashboard applications for data processing, data transfer and site status monitoring, and by showing how they have been ported for different virtual organisations and technologies.

Network placement optimization for large-scale distributed system

NASA Astrophysics Data System (ADS)

Ren, Yu; Liu, Fangfang; Fu, Yunxia; Zhou, Zheng

2018-01-01

The network geometry strongly influences the performance of the distributed system, i.e., the coverage capability, measurement accuracy and overall cost. Therefore the network placement optimization represents an urgent issue in the distributed measurement, even in large-scale metrology. This paper presents an effective computer-assisted network placement optimization procedure for the large-scale distributed system and illustrates it with the example of the multi-tracker system. To get an optimal placement, the coverage capability and the coordinate uncertainty of the network are quantified. Then a placement optimization objective function is developed in terms of coverage capabilities, measurement accuracy and overall cost. And a novel grid-based encoding approach for Genetic algorithm is proposed. So the network placement is optimized by a global rough search and a local detailed search. Its obvious advantage is that there is no need for a specific initial placement. At last, a specific application illustrates this placement optimization procedure can simulate the measurement results of a specific network and design the optimal placement efficiently.

"Tactic": Traffic Aware Cloud for Tiered Infrastructure Consolidation

ERIC Educational Resources Information Center

Sangpetch, Akkarit

2013-01-01

Large-scale enterprise applications are deployed as distributed applications. These applications consist of many inter-connected components with heterogeneous roles and complex dependencies. Each component typically consumes 5-15% of the server capacity. Deploying each component as a separate virtual machine (VM) allows us to consolidate the…

Conditional sampling technique to test the applicability of the Taylor hypothesis for the large-scale coherent structures

NASA Technical Reports Server (NTRS)

Hussain, A. K. M. F.

1980-01-01

Comparisons of the distributions of large scale structures in turbulent flow with distributions based on time dependent signals from stationary probes and the Taylor hypothesis are presented. The study investigated an area in the near field of a 7.62 cm circular air jet at a Re of 32,000, specifically having coherent structures through small-amplitude controlled excitation and stable vortex pairing in the jet column mode. Hot-wire and X-wire anemometry were employed to establish phase averaged spatial distributions of longitudinal and lateral velocities, coherent Reynolds stress and vorticity, background turbulent intensities, streamlines and pseudo-stream functions. The Taylor hypothesis was used to calculate spatial distributions of the phase-averaged properties, with results indicating that the usage of the local time-average velocity or streamwise velocity produces large distortions.

Secure and Robust Overlay Content Distribution

ERIC Educational Resources Information Center

Kang, Hun Jeong

2010-01-01

With the success of applications spurring the tremendous increase in the volume of data transfer, efficient and reliable content distribution has become a key issue. Peer-to-peer (P2P) technology has gained popularity as a promising approach to large-scale content distribution due to its benefits including self-organizing, load-balancing, and…

A distributed parallel storage architecture and its potential application within EOSDIS

NASA Technical Reports Server (NTRS)

Johnston, William E.; Tierney, Brian; Feuquay, Jay; Butzer, Tony

1994-01-01

We describe the architecture, implementation, use of a scalable, high performance, distributed-parallel data storage system developed in the ARPA funded MAGIC gigabit testbed. A collection of wide area distributed disk servers operate in parallel to provide logical block level access to large data sets. Operated primarily as a network-based cache, the architecture supports cooperation among independently owned resources to provide fast, large-scale, on-demand storage to support data handling, simulation, and computation.

Mapping the universe in three dimensions

PubMed Central

Haynes, Martha P.

1996-01-01

The determination of the three-dimensional layout of galaxies is critical to our understanding of the evolution of galaxies and the structures in which they lie, to our determination of the fundamental parameters of cosmology, and to our understanding of both the past and future histories of the universe at large. The mapping of the large scale structure in the universe via the determination of galaxy red shifts (Doppler shifts) is a rapidly growing industry thanks to technological developments in detectors and spectrometers at radio and optical wavelengths. First-order application of the red shift-distance relation (Hubble’s law) allows the analysis of the large-scale distribution of galaxies on scales of hundreds of megaparsecs. Locally, the large-scale structure is very complex but the overall topology is not yet clear. Comparison of the observed red shifts with ones expected on the basis of other distance estimates allows mapping of the gravitational field and the underlying total density distribution. The next decade holds great promise for our understanding of the character of large-scale structure and its origin. PMID:11607714

Mapping the universe in three dimensions.

PubMed

Haynes, M P

1996-12-10

The determination of the three-dimensional layout of galaxies is critical to our understanding of the evolution of galaxies and the structures in which they lie, to our determination of the fundamental parameters of cosmology, and to our understanding of both the past and future histories of the universe at large. The mapping of the large scale structure in the universe via the determination of galaxy red shifts (Doppler shifts) is a rapidly growing industry thanks to technological developments in detectors and spectrometers at radio and optical wavelengths. First-order application of the red shift-distance relation (Hubble's law) allows the analysis of the large-scale distribution of galaxies on scales of hundreds of megaparsecs. Locally, the large-scale structure is very complex but the overall topology is not yet clear. Comparison of the observed red shifts with ones expected on the basis of other distance estimates allows mapping of the gravitational field and the underlying total density distribution. The next decade holds great promise for our understanding of the character of large-scale structure and its origin.

Generation of dense granular deposits for porosity analysis: assessment and application of large-scale non-smooth granular dynamics

NASA Astrophysics Data System (ADS)

Schruff, T.; Liang, R.; Rüde, U.; Schüttrumpf, H.; Frings, R. M.

2018-01-01

The knowledge of structural properties of granular materials such as porosity is highly important in many application-oriented and scientific fields. In this paper we present new results of computer-based packing simulations where we use the non-smooth granular dynamics (NSGD) method to simulate gravitational random dense packing of spherical particles with various particle size distributions and two types of depositional conditions. A bin packing scenario was used to compare simulation results to laboratory porosity measurements and to quantify the sensitivity of the NSGD regarding critical simulation parameters such as time step size. The results of the bin packing simulations agree well with laboratory measurements across all particle size distributions with all absolute errors below 1%. A large-scale packing scenario with periodic side walls was used to simulate the packing of up to 855,600 spherical particles with various particle size distributions (PSD). Simulation outcomes are used to quantify the effect of particle-domain-size ratio on the packing compaction. A simple correction model, based on the coordination number, is employed to compensate for this effect on the porosity and to determine the relationship between PSD and porosity. Promising accuracy and stability results paired with excellent computational performance recommend the application of NSGD for large-scale packing simulations, e.g. to further enhance the generation of representative granular deposits.

Laser-induced plasmonic colours on metals

NASA Astrophysics Data System (ADS)

Guay, Jean-Michel; Calà Lesina, Antonino; Côté, Guillaume; Charron, Martin; Poitras, Daniel; Ramunno, Lora; Berini, Pierre; Weck, Arnaud

2017-07-01

Plasmonic resonances in metallic nanoparticles have been used since antiquity to colour glasses. The use of metal nanostructures for surface colourization has attracted considerable interest following recent developments in plasmonics. However, current top-down colourization methods are not ideally suited to large-scale industrial applications. Here we use a bottom-up approach where picosecond laser pulses can produce a full palette of non-iridescent colours on silver, gold, copper and aluminium. We demonstrate the process on silver coins weighing up to 5 kg and bearing large topographic variations (~1.5 cm). We find that colours are related to a single parameter, the total accumulated fluence, making the process suitable for high-throughput industrial applications. Statistical image analyses of laser-irradiated surfaces reveal various nanoparticle size distributions. Large-scale finite-difference time-domain computations based on these nanoparticle distributions reproduce trends seen in reflectance measurements, and demonstrate the key role of plasmonic resonances in colour formation.

Laser-induced plasmonic colours on metals

PubMed Central

Guay, Jean-Michel; Calà Lesina, Antonino; Côté, Guillaume; Charron, Martin; Poitras, Daniel; Ramunno, Lora; Berini, Pierre; Weck, Arnaud

2017-01-01

Plasmonic resonances in metallic nanoparticles have been used since antiquity to colour glasses. The use of metal nanostructures for surface colourization has attracted considerable interest following recent developments in plasmonics. However, current top-down colourization methods are not ideally suited to large-scale industrial applications. Here we use a bottom-up approach where picosecond laser pulses can produce a full palette of non-iridescent colours on silver, gold, copper and aluminium. We demonstrate the process on silver coins weighing up to 5 kg and bearing large topographic variations (∼1.5 cm). We find that colours are related to a single parameter, the total accumulated fluence, making the process suitable for high-throughput industrial applications. Statistical image analyses of laser-irradiated surfaces reveal various nanoparticle size distributions. Large-scale finite-difference time-domain computations based on these nanoparticle distributions reproduce trends seen in reflectance measurements, and demonstrate the key role of plasmonic resonances in colour formation. PMID:28719576

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

NASA Astrophysics Data System (ADS)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Backscattering from a Gaussian distributed, perfectly conducting, rough surface

NASA Technical Reports Server (NTRS)

Brown, G. S.

1977-01-01

The problem of scattering by random surfaces possessing many scales of roughness is analyzed. The approach is applicable to bistatic scattering from dielectric surfaces, however, this specific analysis is restricted to backscattering from a perfectly conducting surface in order to more clearly illustrate the method. The surface is assumed to be Gaussian distributed so that the surface height can be split into large and small scale components, relative to the electromagnetic wavelength. A first order perturbation approach is employed wherein the scattering solution for the large scale structure is perturbed by the small scale diffraction effects. The scattering from the large scale structure is treated via geometrical optics techniques. The effect of the large scale surface structure is shown to be equivalent to a convolution in k-space of the height spectrum with the following: the shadowing function, a polarization and surface slope dependent function, and a Gaussian factor resulting from the unperturbed geometrical optics solution. This solution provides a continuous transition between the near normal incidence geometrical optics and wide angle Bragg scattering results.

Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.

A watershed scale spatially-distributed model for streambank erosion rate driven by channel curvature

NASA Astrophysics Data System (ADS)

McMillan, Mitchell; Hu, Zhiyong

2017-10-01

Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.

Particle Acceleration in Mildly Relativistic Shearing Flows: The Interplay of Systematic and Stochastic Effects, and the Origin of the Extended High-energy Emission in AGN Jets

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

Liu, Ruo-Yu; Rieger, F. M.; Aharonian, F. A., E-mail: ruoyu@mpi-hd.mpg.de, E-mail: frank.rieger@mpi-hd.mpg.de, E-mail: aharon@mpi-hd.mpg.de

The origin of the extended X-ray emission in the large-scale jets of active galactic nuclei (AGNs) poses challenges to conventional models of acceleration and emission. Although electron synchrotron radiation is considered the most feasible radiation mechanism, the formation of the continuous large-scale X-ray structure remains an open issue. As astrophysical jets are expected to exhibit some turbulence and shearing motion, we here investigate the potential of shearing flows to facilitate an extended acceleration of particles and evaluate its impact on the resultant particle distribution. Our treatment incorporates systematic shear and stochastic second-order Fermi effects. We show that for typical parametersmore » applicable to large-scale AGN jets, stochastic second-order Fermi acceleration, which always accompanies shear particle acceleration, can play an important role in facilitating the whole process of particle energization. We study the time-dependent evolution of the resultant particle distribution in the presence of second-order Fermi acceleration, shear acceleration, and synchrotron losses using a simple Fokker–Planck approach and provide illustrations for the possible emergence of a complex (multicomponent) particle energy distribution with different spectral branches. We present examples for typical parameters applicable to large-scale AGN jets, indicating the relevance of the underlying processes for understanding the extended X-ray emission and the origin of ultrahigh-energy cosmic rays.« less

Semantics-based distributed I/O with the ParaMEDIC framework.

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

Balaji, P.; Feng, W.; Lin, H.

2008-01-01

Many large-scale applications simultaneously rely on multiple resources for efficient execution. For example, such applications may require both large compute and storage resources; however, very few supercomputing centers can provide large quantities of both. Thus, data generated at the compute site oftentimes has to be moved to a remote storage site for either storage or visualization and analysis. Clearly, this is not an efficient model, especially when the two sites are distributed over a wide-area network. Thus, we present a framework called 'ParaMEDIC: Parallel Metadata Environment for Distributed I/O and Computing' which uses application-specific semantic information to convert the generatedmore » data to orders-of-magnitude smaller metadata at the compute site, transfer the metadata to the storage site, and re-process the metadata at the storage site to regenerate the output. Specifically, ParaMEDIC trades a small amount of additional computation (in the form of data post-processing) for a potentially significant reduction in data that needs to be transferred in distributed environments.« less

IP-Based Video Modem Extender Requirements

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

Pierson, L G; Boorman, T M; Howe, R E

2003-12-16

Visualization is one of the keys to understanding large complex data sets such as those generated by the large computing resources purchased and developed by the Advanced Simulation and Computing program (aka ASCI). In order to be convenient to researchers, visualization data must be distributed to offices and large complex visualization theaters. Currently, local distribution of the visual data is accomplished by distance limited modems and RGB switches that simply do not scale to hundreds of users across the local, metropolitan, and WAN distances without incurring large costs in fiber plant installation and maintenance. Wide Area application over the DOEmore » Complex is infeasible using these limited distance RGB extenders. On the other hand, Internet Protocols (IP) over Ethernet is a scalable well-proven technology that can distribute large volumes of data over these distances. Visual data has been distributed at lower resolutions over IP in industrial applications. This document describes requirements of the ASCI program in visual signal distribution for the purpose of identifying industrial partners willing to develop products to meet ASCI's needs.« less

Distributed chemical computing using ChemStar: an open source java remote method invocation architecture applied to large scale molecular data from PubChem.

PubMed

Karthikeyan, M; Krishnan, S; Pandey, Anil Kumar; Bender, Andreas; Tropsha, Alexander

2008-04-01

We present the application of a Java remote method invocation (RMI) based open source architecture to distributed chemical computing. This architecture was previously employed for distributed data harvesting of chemical information from the Internet via the Google application programming interface (API; ChemXtreme). Due to its open source character and its flexibility, the underlying server/client framework can be quickly adopted to virtually every computational task that can be parallelized. Here, we present the server/client communication framework as well as an application to distributed computing of chemical properties on a large scale (currently the size of PubChem; about 18 million compounds), using both the Marvin toolkit as well as the open source JOELib package. As an application, for this set of compounds, the agreement of log P and TPSA between the packages was compared. Outliers were found to be mostly non-druglike compounds and differences could usually be explained by differences in the underlying algorithms. ChemStar is the first open source distributed chemical computing environment built on Java RMI, which is also easily adaptable to user demands due to its "plug-in architecture". The complete source codes as well as calculated properties along with links to PubChem resources are available on the Internet via a graphical user interface at http://moltable.ncl.res.in/chemstar/.

ISIS and META projects

NASA Technical Reports Server (NTRS)

Birman, Kenneth; Cooper, Robert; Marzullo, Keith

1990-01-01

The ISIS project has developed a new methodology, virtual synchony, for writing robust distributed software. High performance multicast, large scale applications, and wide area networks are the focus of interest. Several interesting applications that exploit the strengths of ISIS, including an NFS-compatible replicated file system, are being developed. The META project is distributed control in a soft real-time environment incorporating feedback. This domain encompasses examples as diverse as monitoring inventory and consumption on a factory floor, and performing load-balancing on a distributed computing system. One of the first uses of META is for distributed application management: the tasks of configuring a distributed program, dynamically adapting to failures, and monitoring its performance. Recent progress and current plans are reported.

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 expensive black-box function optimization

NASA Astrophysics Data System (ADS)

Rashid, Kashif; Bailey, William; Couët, Benoît

2012-09-01

This paper presents the application of an adaptive radial basis function method to a computationally expensive black-box reservoir simulation model of many variables. An iterative proxy-based scheme is used to tune the control variables, distributed for finer control over a varying number of intervals covering the total simulation period, to maximize asset NPV. The method shows that large-scale simulation-based function optimization of several hundred variables is practical and effective.

Turbulent pipe flow at extreme Reynolds numbers.

PubMed

Hultmark, M; Vallikivi, M; Bailey, S C C; Smits, A J

2012-03-02

Both the inherent intractability and complex beauty of turbulence reside in its large range of physical and temporal scales. This range of scales is captured by the Reynolds number, which in nature and in many engineering applications can be as large as 10(5)-10(6). Here, we report turbulence measurements over an unprecedented range of Reynolds numbers using a unique combination of a high-pressure air facility and a new nanoscale anemometry probe. The results reveal previously unknown universal scaling behavior for the turbulent velocity fluctuations, which is remarkably similar to the well-known scaling behavior of the mean velocity distribution.

On the Fidelity of Semi-distributed Hydrologic Model Simulations for Large Scale Catchment Applications

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.; Lakshmi, V.

2017-12-01

Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

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

Wu, Chase Qishi; Zhu, Michelle Mengxia

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models featuremore » diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.« less

Visualization, documentation, analysis, and communication of large scale gene regulatory networks

PubMed Central

Longabaugh, William J.R.; Davidson, Eric H.; Bolouri, Hamid

2009-01-01

Summary Genetic regulatory networks (GRNs) are complex, large-scale, and spatially and temporally distributed. These characteristics impose challenging demands on computational GRN modeling tools, and there is a need for custom modeling tools. In this paper, we report on our ongoing development of BioTapestry, an open source, freely available computational tool designed specifically for GRN modeling. We also outline our future development plans, and give some examples of current applications of BioTapestry. PMID:18757046

Non-Gaussian Nature of Fracture and the Survival of Fat-Tail Exponents

NASA Astrophysics Data System (ADS)

Tallakstad, Ken Tore; Toussaint, Renaud; Santucci, Stephane; Måløy, Knut Jørgen

2013-04-01

We study the fluctuations of the global velocity Vl(t), computed at various length scales l, during the intermittent mode-I propagation of a crack front. The statistics converge to a non-Gaussian distribution, with an asymmetric shape and a fat tail. This breakdown of the central limit theorem (CLT) is due to the diverging variance of the underlying local crack front velocity distribution, displaying a power law tail. Indeed, by the application of a generalized CLT, the full shape of our experimental velocity distribution at large scale is shown to follow the stable Levy distribution, which preserves the power law tail exponent under upscaling. This study aims to demonstrate in general for crackling noise systems how one can infer the complete scale dependence of the activity—and extreme event distributions—by measuring only at a global scale.

Large-scale machine learning and evaluation platform for real-time traffic surveillance

NASA Astrophysics Data System (ADS)

Eichel, Justin A.; Mishra, Akshaya; Miller, Nicholas; Jankovic, Nicholas; Thomas, Mohan A.; Abbott, Tyler; Swanson, Douglas; Keller, Joel

2016-09-01

In traffic engineering, vehicle detectors are trained on limited datasets, resulting in poor accuracy when deployed in real-world surveillance applications. Annotating large-scale high-quality datasets is challenging. Typically, these datasets have limited diversity; they do not reflect the real-world operating environment. There is a need for a large-scale, cloud-based positive and negative mining process and a large-scale learning and evaluation system for the application of automatic traffic measurements and classification. The proposed positive and negative mining process addresses the quality of crowd sourced ground truth data through machine learning review and human feedback mechanisms. The proposed learning and evaluation system uses a distributed cloud computing framework to handle data-scaling issues associated with large numbers of samples and a high-dimensional feature space. The system is trained using AdaBoost on 1,000,000 Haar-like features extracted from 70,000 annotated video frames. The trained real-time vehicle detector achieves an accuracy of at least 95% for 1/2 and about 78% for 19/20 of the time when tested on ˜7,500,000 video frames. At the end of 2016, the dataset is expected to have over 1 billion annotated video frames.

Development and Application of the Collaborative Optimization Architecture in a Multidisciplinary Design Environment

NASA Technical Reports Server (NTRS)

Braun, R. D.; Kroo, I. M.

1995-01-01

Collaborative optimization is a design architecture applicable in any multidisciplinary analysis environment but specifically intended for large-scale distributed analysis applications. In this approach, a complex problem is hierarchically de- composed along disciplinary boundaries into a number of subproblems which are brought into multidisciplinary agreement by a system-level coordination process. When applied to problems in a multidisciplinary design environment, this scheme has several advantages over traditional solution strategies. These advantageous features include reducing the amount of information transferred between disciplines, the removal of large iteration-loops, allowing the use of different subspace optimizers among the various analysis groups, an analysis framework which is easily parallelized and can operate on heterogenous equipment, and a structural framework that is well-suited for conventional disciplinary organizations. In this article, the collaborative architecture is developed and its mathematical foundation is presented. An example application is also presented which highlights the potential of this method for use in large-scale design applications.

Software environment for implementing engineering applications on MIMD computers

NASA Technical Reports Server (NTRS)

Lopez, L. A.; Valimohamed, K. A.; Schiff, S.

1990-01-01

In this paper the concept for a software environment for developing engineering application systems for multiprocessor hardware (MIMD) is presented. The philosophy employed is to solve the largest problems possible in a reasonable amount of time, rather than solve existing problems faster. In the proposed environment most of the problems concerning parallel computation and handling of large distributed data spaces are hidden from the application program developer, thereby facilitating the development of large-scale software applications. Applications developed under the environment can be executed on a variety of MIMD hardware; it protects the application software from the effects of a rapidly changing MIMD hardware technology.

Application of LANDSAT data to delimitation of avalanche hazards in Montane Colorado

NASA Technical Reports Server (NTRS)

Knepper, D. H. (Principal Investigator); Ives, J. D.; Summer, R.

1975-01-01

The author has identified the following significant results. Interpretation of small scale LANDSAT imagery provides a means for determining the general location and distribution of avalanche paths. The accuracy and completeness of small scale mapping is less than is obtained from the interpretation of large scale color infrared photos. Interpretation of enlargement prints (18X) of LANDSAT imagery is superior to small scale imagery, because more detailed information can be extracted and annotated.

High quality uniform YBCO film growth by the metalorganic deposition using trifluoroacetates

NASA Astrophysics Data System (ADS)

Wang, S. S.; Zhang, Z. L.; Wang, L.; Gao, L. K.; Liu, J.

2017-03-01

A need exists for the large-area superconducting YBa2Cu3O7-x (YBCO) films with high critical current density for microwave communication and/or electric power applications. Trifluoroacetic metalorganic (TFA-MOD) method is a promising low cost technique for large-scale production of YBCO films, because it does not need high vacuum device and is easily applicable to substrates of various shape and size. In this paper, double-sided YBCO films with maximum 2 in diameter were prepared on LaAlO3 substrates by TFA-MOD method. Inductive critical current densitiy Jc, microwave surface resistance Rs, as well as the microstructure were characterized. A newly homemade furnace system was used to epitaxially grown YBCO films, which can improve the uniformity of YBCO film significantly by gas supply and temperature distribution proper design. Results showed that the large area YBCO films were very uniform in microstructure and thickness distribution, an average inductive Jc in excess of 6 MA/cm2 with uniform distribution, and low Rs (10 GHz) below 0.3 mΩ at 77 K were obtained. Andthe film filter may be prepared to work at temperatures lower than 74 K. These results are very close to the highest value of YBCO films made by conventional vacuum method, so we show a very promising route for large-scale production of high quality large-area YBCO superconducting films at a lower cost.

Scale-dependent coupling of hysteretic capillary pressure, trapping, and fluid mobilities

NASA Astrophysics Data System (ADS)

Doster, F.; Celia, M. A.; Nordbotten, J. M.

2012-12-01

Many applications of multiphase flow in porous media, including CO2-storage and enhanced oil recovery, require mathematical models that span a large range of length scales. In the context of numerical simulations, practical grid sizes are often on the order of tens of meters, thereby de facto defining a coarse model scale. Under particular conditions, it is possible to approximate the sub-grid-scale distribution of the fluid saturation within a grid cell; that reconstructed saturation can then be used to compute effective properties at the coarse scale. If both the density difference between the fluids and the vertical extend of the grid cell are large, and buoyant segregation within the cell on a sufficiently shorte time scale, then the phase pressure distributions are essentially hydrostatic and the saturation profile can be reconstructed from the inferred capillary pressures. However, the saturation reconstruction may not be unique because the parameters and parameter functions of classical formulations of two-phase flow in porous media - the relative permeability functions, the capillary pressure -saturation relationship, and the residual saturations - show path dependence, i.e. their values depend not only on the state variables but also on their drainage and imbibition histories. In this study we focus on capillary pressure hysteresis and trapping and show that the contribution of hysteresis to effective quantities is dependent on the vertical length scale. By studying the transition from the two extreme cases - the homogeneous saturation distribution for small vertical extents and the completely segregated distribution for large extents - we identify how hysteretic capillary pressure at the local scale induces hysteresis in all coarse-scale quantities for medium vertical extents and finally vanishes for large vertical extents. Our results allow for more accurate vertically integrated modeling while improving our understanding of the coupling of capillary pressure and relative permeabilities over larger length scales.

Predictive Anomaly Management for Resilient Virtualized Computing Infrastructures

DTIC Science & Technology

2015-05-27

PREC: Practical Root Exploit Containment for Android Devices, ACM Conference on Data and Application Security and Privacy (CODASPY) . 03-MAR-14...05-OCT-11, . : , Hiep Nguyen, Yongmin Tan, Xiaohui Gu. Propagation-aware Anomaly Localization for Cloud Hosted Distributed Applications , ACM...Workshop on Managing Large-Scale Systems via the Analysis of System Logs and the Application of Machine Learning Techniques (SLAML) in conjunction with SOSP

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Extraction of drainage networks from large terrain datasets using high throughput computing

NASA Astrophysics Data System (ADS)

Gong, Jianya; Xie, Jibo

2009-02-01

Advanced digital photogrammetry and remote sensing technology produces large terrain datasets (LTD). How to process and use these LTD has become a big challenge for GIS users. Extracting drainage networks, which are basic for hydrological applications, from LTD is one of the typical applications of digital terrain analysis (DTA) in geographical information applications. Existing serial drainage algorithms cannot deal with large data volumes in a timely fashion, and few GIS platforms can process LTD beyond the GB size. High throughput computing (HTC), a distributed parallel computing mode, is proposed to improve the efficiency of drainage networks extraction from LTD. Drainage network extraction using HTC involves two key issues: (1) how to decompose the large DEM datasets into independent computing units and (2) how to merge the separate outputs into a final result. A new decomposition method is presented in which the large datasets are partitioned into independent computing units using natural watershed boundaries instead of using regular 1-dimensional (strip-wise) and 2-dimensional (block-wise) decomposition. Because the distribution of drainage networks is strongly related to watershed boundaries, the new decomposition method is more effective and natural. The method to extract natural watershed boundaries was improved by using multi-scale DEMs instead of single-scale DEMs. A HTC environment is employed to test the proposed methods with real datasets.

Coalescence computations for large samples drawn from populations of time-varying sizes

PubMed Central

Polanski, Andrzej; Szczesna, Agnieszka; Garbulowski, Mateusz; Kimmel, Marek

2017-01-01

We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset. PMID:28170404

Distributed intelligent urban environment monitoring system

NASA Astrophysics Data System (ADS)

Du, Jinsong; Wang, Wei; Gao, Jie; Cong, Rigang

2018-02-01

The current environmental pollution and destruction have developed into a world-wide major social problem that threatens human survival and development. Environmental monitoring is the prerequisite and basis of environmental governance, but overall, the current environmental monitoring system is facing a series of problems. Based on the electrochemical sensor, this paper designs a small, low-cost, easy to layout urban environmental quality monitoring terminal, and multi-terminal constitutes a distributed network. The system has been small-scale demonstration applications and has confirmed that the system is suitable for large-scale promotion

Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

NASA Astrophysics Data System (ADS)

Zhang, Daili

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

DOE PAGES

Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

2010-01-01

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads tomore » minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution function method.

Nearest neighbor density ratio estimation for large-scale applications in astronomy

NASA Astrophysics Data System (ADS)

Kremer, J.; Gieseke, F.; Steenstrup Pedersen, K.; Igel, C.

2015-09-01

In astronomical applications of machine learning, the distribution of objects used for building a model is often different from the distribution of the objects the model is later applied to. This is known as sample selection bias, which is a major challenge for statistical inference as one can no longer assume that the labeled training data are representative. To address this issue, one can re-weight the labeled training patterns to match the distribution of unlabeled data that are available already in the training phase. There are many examples in practice where this strategy yielded good results, but estimating the weights reliably from a finite sample is challenging. We consider an efficient nearest neighbor density ratio estimator that can exploit large samples to increase the accuracy of the weight estimates. To solve the problem of choosing the right neighborhood size, we propose to use cross-validation on a model selection criterion that is unbiased under covariate shift. The resulting algorithm is our method of choice for density ratio estimation when the feature space dimensionality is small and sample sizes are large. The approach is simple and, because of the model selection, robust. We empirically find that it is on a par with established kernel-based methods on relatively small regression benchmark datasets. However, when applied to large-scale photometric redshift estimation, our approach outperforms the state-of-the-art.

Distributed Large Data-Object Environments: End-to-End Performance Analysis of High Speed Distributed Storage Systems in Wide Area ATM Networks

NASA Technical Reports Server (NTRS)

Johnston, William; Tierney, Brian; Lee, Jason; Hoo, Gary; Thompson, Mary

1996-01-01

We have developed and deployed a distributed-parallel storage system (DPSS) in several high speed asynchronous transfer mode (ATM) wide area networks (WAN) testbeds to support several different types of data-intensive applications. Architecturally, the DPSS is a network striped disk array, but is fairly unique in that its implementation allows applications complete freedom to determine optimal data layout, replication and/or coding redundancy strategy, security policy, and dynamic reconfiguration. In conjunction with the DPSS, we have developed a 'top-to-bottom, end-to-end' performance monitoring and analysis methodology that has allowed us to characterize all aspects of the DPSS operating in high speed ATM networks. In particular, we have run a variety of performance monitoring experiments involving the DPSS in the MAGIC testbed, which is a large scale, high speed, ATM network and we describe our experience using the monitoring methodology to identify and correct problems that limit the performance of high speed distributed applications. Finally, the DPSS is part of an overall architecture for using high speed, WAN's for enabling the routine, location independent use of large data-objects. Since this is part of the motivation for a distributed storage system, we describe this architecture.

A uniform approach for programming distributed heterogeneous computing systems

PubMed Central

Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas

2014-01-01

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater’s performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations. PMID:25844015

A uniform approach for programming distributed heterogeneous computing systems.

PubMed

Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas

2014-12-01

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater's performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations.

Large Scale System Defense

DTIC Science & Technology

2008-10-01

AD); Aeolos, a distributed intrusion detection and event correlation infrastructure; STAND, a training-set sanitization technique applicable to ADs...UU 18. NUMBER OF PAGES 25 19a. NAME OF RESPONSIBLE PERSON Frank H. Born a. REPORT U b. ABSTRACT U c . THIS PAGE U 19b. TELEPHONE...Summary of findings 2 (a) Automatic Patch Generation 2 (b) Better Patch Management 2 ( c ) Artificial Diversity 3 (d) Distributed Anomaly Detection 3

Globus | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Globus software services provide secure cancer research data transfer, synchronization, and sharing in distributed environments at large scale. These services can be integrated into applications and research data gateways, leveraging Globus identity management, single sign-on, search, and authorization capabilities. Globus Genomics integrates Globus with the Galaxy genomics workflow engine and Amazon Web Services to enable cancer genomics analysis that can elastically scale compute resources with demand.

On the Relevancy of Efficient, Integrated Computer and Network Monitoring in HEP Distributed Online Environment

NASA Astrophysics Data System (ADS)

Carvalho, D.; Gavillet, Ph.; Delgado, V.; Albert, J. N.; Bellas, N.; Javello, J.; Miere, Y.; Ruffinoni, D.; Smith, G.

Large Scientific Equipments are controlled by Computer Systems whose complexity is growing driven, on the one hand by the volume and variety of the information, its distributed nature, the sophistication of its treatment and, on the other hand by the fast evolution of the computer and network market. Some people call them genetically Large-Scale Distributed Data Intensive Information Systems or Distributed Computer Control Systems (DCCS) for those systems dealing more with real time control. Taking advantage of (or forced by) the distributed architecture, the tasks are more and more often implemented as Client-Server applications. In this framework the monitoring of the computer nodes, the communications network and the applications becomes of primary importance for ensuring the safe running and guaranteed performance of the system. With the future generation of HEP experiments, such as those at the LHC in view, it is proposed to integrate the various functions of DCCS monitoring into one general purpose Multi-layer System.

A two-scale scattering model with application to the JONSWAP '75 aircraft microwave scatterometer experiment

NASA Technical Reports Server (NTRS)

Wentz, F. J.

1977-01-01

The general problem of bistatic scattering from a two scale surface was evaluated. The treatment was entirely two-dimensional and in a vector formulation independent of any particular coordinate system. The two scale scattering model was then applied to backscattering from the sea surface. In particular, the model was used in conjunction with the JONSWAP 1975 aircraft scatterometer measurements to determine the sea surface's two scale roughness distributions, namely the probability density of the large scale surface slope and the capillary wavenumber spectrum. Best fits yield, on the average, a 0.7 dB rms difference between the model computations and the vertical polarization measurements of the normalized radar cross section. Correlations between the distribution parameters and the wind speed were established from linear, least squares regressions.

SmallTool - a toolkit for realizing shared virtual environments on the Internet

NASA Astrophysics Data System (ADS)

Broll, Wolfgang

1998-09-01

With increasing graphics capabilities of computers and higher network communication speed, networked virtual environments have become available to a large number of people. While the virtual reality modelling language (VRML) provides users with the ability to exchange 3D data, there is still a lack of appropriate support to realize large-scale multi-user applications on the Internet. In this paper we will present SmallTool, a toolkit to support shared virtual environments on the Internet. The toolkit consists of a VRML-based parsing and rendering library, a device library, and a network library. This paper will focus on the networking architecture, provided by the network library - the distributed worlds transfer and communication protocol (DWTP). DWTP provides an application-independent network architecture to support large-scale multi-user environments on the Internet.

Investigation of the near subsurface using acoustic to seismic coupling

USDA-ARS?s Scientific Manuscript database

Agricultural, hydrological and civil engineering applications have realized a need for information of the near subsurface over large areas. In order to obtain this spatially distributed data over such scales, the measurement technique must be highly mobile with a short acquisition time. Therefore, s...

Nowcasting Earthquakes: A Comparison of Induced Earthquakes in Oklahoma and at the Geysers, California

NASA Astrophysics Data System (ADS)

Luginbuhl, Molly; Rundle, John B.; Hawkins, Angela; Turcotte, Donald L.

2018-01-01

Nowcasting is a new method of statistically classifying seismicity and seismic risk (Rundle et al. 2016). In this paper, the method is applied to the induced seismicity at the Geysers geothermal region in California and the induced seismicity due to fluid injection in Oklahoma. Nowcasting utilizes the catalogs of seismicity in these regions. Two earthquake magnitudes are selected, one large say M_{λ } ≥ 4, and one small say M_{σ } ≥ 2. The method utilizes the number of small earthquakes that occurs between pairs of large earthquakes. The cumulative probability distribution of these values is obtained. The earthquake potential score (EPS) is defined by the number of small earthquakes that has occurred since the last large earthquake, the point where this number falls on the cumulative probability distribution of interevent counts defines the EPS. A major advantage of nowcasting is that it utilizes "natural time", earthquake counts, between events rather than clock time. Thus, it is not necessary to decluster aftershocks and the results are applicable if the level of induced seismicity varies in time. The application of natural time to the accumulation of the seismic hazard depends on the applicability of Gutenberg-Richter (GR) scaling. The increasing number of small earthquakes that occur after a large earthquake can be scaled to give the risk of a large earthquake occurring. To illustrate our approach, we utilize the number of M_{σ } ≥ 2.75 earthquakes in Oklahoma to nowcast the number of M_{λ } ≥ 4.0 earthquakes in Oklahoma. The applicability of the scaling is illustrated during the rapid build-up of injection-induced seismicity between 2012 and 2016, and the subsequent reduction in seismicity associated with a reduction in fluid injections. The same method is applied to the geothermal-induced seismicity at the Geysers, California, for comparison.

Fragmentation under the Scaling Symmetry and Turbulent Cascade with Intermittency

NASA Technical Reports Server (NTRS)

Gorokhovski, M.

2003-01-01

Fragmentation plays an important role in a variety of physical, chemical, and geological processes. Examples include atomization in sprays, crushing of rocks, explosion and impact of solids, polymer degradation, etc. Although each individual action of fragmentation is a complex process, the number of these elementary actions is large. It is natural to abstract a simple 'effective' scenario of fragmentation and to represent its essential features. One of the models is the fragmentation under the scaling symmetry: each breakup action reduces the typical length of fragments, r (right arrow) alpha r, by an independent random multiplier alpha (0 < alpha < 1), which is governed by the fragmentation intensity spectrum q(alpha), integral(sup 1)(sub 0) q(alpha)d alpha = 1. This scenario has been proposed by Kolmogorov (1941), when he considered the breakup of solid carbon particle. Describing the breakup as a random discrete process, Kolmogorov stated that at latest times, such a process leads to the log-normal distribution. In Gorokhovski & Saveliev, the fragmentation under the scaling symmetry has been reviewed as a continuous evolution process with new features established. The objective of this paper is twofold. First, the paper synthesizes and completes theoretical part of Gorokhovski & Saveliev. Second, the paper shows a new application of the fragmentation theory under the scale invariance. This application concerns the turbulent cascade with intermittency. We formulate here a model describing the evolution of the velocity increment distribution along the progressively decreasing length scale. The model shows that when the turbulent length scale gets smaller, the velocity increment distribution has central growing peak and develops stretched tails. The intermittency in turbulence is manifested in the same way: large fluctuations of velocity provoke highest strain in narrow (dissipative) regions of flow.

The Universe at Moderate Redshift

NASA Technical Reports Server (NTRS)

Cen, Renyue; Ostriker, Jeremiah P.

1997-01-01

The report covers the work done in the past year and a wide range of fields including properties of clusters of galaxies; topological properties of galaxy distributions in terms of galaxy types; patterns of gravitational nonlinear clustering process; development of a ray tracing algorithm to study the gravitational lensing phenomenon by galaxies, clusters and large-scale structure, one of whose applications being the effects of weak gravitational lensing by large-scale structure on the determination of q(0); the origin of magnetic fields on the galactic and cluster scales; the topological properties of Ly(alpha) clouds the Ly(alpha) optical depth distribution; clustering properties of Ly(alpha) clouds; and a determination (lower bound) of Omega(b) based on the observed Ly(alpha) forest flux distribution. In the coming year, we plan to continue the investigation of Ly(alpha) clouds using larger dynamic range (about a factor of two) and better simulations (with more input physics included) than what we have now. We will study the properties of galaxies on 1 - 100h(sup -1) Mpc scales using our state-of-the-art large scale galaxy formation simulations of various cosmological models, which will have a resolution about a factor of 5 (in each dimension) better than our current, best simulations. We will plan to study the properties of X-ray clusters using unprecedented, very high dynamic range (20,000) simulations which will enable us to resolve the cores of clusters while keeping the simulation volume sufficiently large to ensure a statistically fair sample of the objects of interest. The details of the last year's works are now described.

Scale-free Graphs for General Aviation Flight Schedules

NASA Technical Reports Server (NTRS)

Alexandov, Natalia M. (Technical Monitor); Kincaid, Rex K.

2003-01-01

In the late 1990s a number of researchers noticed that networks in biology, sociology, and telecommunications exhibited similar characteristics unlike standard random networks. In particular, they found that the cummulative degree distributions of these graphs followed a power law rather than a binomial distribution and that their clustering coefficients tended to a nonzero constant as the number of nodes, n, became large rather than O(1/n). Moreover, these networks shared an important property with traditional random graphs as n becomes large the average shortest path length scales with log n. This latter property has been coined the small-world property. When taken together these three properties small-world, power law, and constant clustering coefficient describe what are now most commonly referred to as scale-free networks. Since 1997 at least six books and over 400 articles have been written about scale-free networks. In this manuscript an overview of the salient characteristics of scale-free networks. Computational experience will be provided for two mechanisms that grow (dynamic) scale-free graphs. Additional computational experience will be given for constructing (static) scale-free graphs via a tabu search optimization approach. Finally, a discussion of potential applications to general aviation networks is given.

General calibration methodology for a combined Horton-SCS infiltration scheme in flash flood modeling

NASA Astrophysics Data System (ADS)

Gabellani, S.; Silvestro, F.; Rudari, R.; Boni, G.

2008-12-01

Flood forecasting undergoes a constant evolution, becoming more and more demanding about the models used for hydrologic simulations. The advantages of developing distributed or semi-distributed models have currently been made clear. Now the importance of using continuous distributed modeling emerges. A proper schematization of the infiltration process is vital to these types of models. Many popular infiltration schemes, reliable and easy to implement, are too simplistic for the development of continuous hydrologic models. On the other hand, the unavailability of detailed and descriptive information on soil properties often limits the implementation of complete infiltration schemes. In this work, a combination between the Soil Conservation Service Curve Number method (SCS-CN) and a method derived from Horton equation is proposed in order to overcome the inherent limits of the two schemes. The SCS-CN method is easily applicable on large areas, but has structural limitations. The Horton-like methods present parameters that, though measurable to a point, are difficult to achieve a reliable estimate at catchment scale. The objective of this work is to overcome these limits by proposing a calibration procedure which maintains the large applicability of the SCS-CN method as well as the continuous description of the infiltration process given by the Horton's equation suitably modified. The estimation of the parameters of the modified Horton method is carried out using a formal analogy with the SCS-CN method under specific conditions. Some applications, at catchment scale within a distributed model, are presented.

A scaling theory for number-flux distributions generated during steady-state coagulation and settling and application to particles in Lake Zurich, Switzerland.

PubMed

Boehm, Alexandria B

2002-10-15

In this study, we extend the established scaling theory for cluster size distributions generated during unsteady coagulation to number-flux distributions that arise during steady-state coagulation and settling in an unmixed water mass. The scaling theory predicts self-similar number-flux distributions and power-law decay of total number flux with depth. The shape of the number-flux distributions and the power-law exponent describing the decay of the total number flux are shown to depend on the homogeneity and small i/j limit of the coagulation kernel and the exponent kappa, which describes the variation in settling velocity with cluster volume. Particle field measurements from Lake Zurich, collected by U. Weilenmann and co-workers (Limnol. Oceanogr.34, 1 (1989)), are used to illustrate how the scaling predictions can be applied to a natural system. This effort indicates that within the mid-depth region of Lake Zurich, clusters of the same size preferentially interact and large clusters react with one another more quickly than small ones, indicative of clusters coagulating in a reaction-limited regime.

Data Sharing in DHT Based P2P Systems

NASA Astrophysics Data System (ADS)

Roncancio, Claudia; Del Pilar Villamil, María; Labbé, Cyril; Serrano-Alvarado, Patricia

The evolution of peer-to-peer (P2P) systems triggered the building of large scale distributed applications. The main application domain is data sharing across a very large number of highly autonomous participants. Building such data sharing systems is particularly challenging because of the “extreme” characteristics of P2P infrastructures: massive distribution, high churn rate, no global control, potentially untrusted participants... This article focuses on declarative querying support, query optimization and data privacy on a major class of P2P systems, that based on Distributed Hash Table (P2P DHT). The usual approaches and the algorithms used by classic distributed systems and databases for providing data privacy and querying services are not well suited to P2P DHT systems. A considerable amount of work was required to adapt them for the new challenges such systems present. This paper describes the most important solutions found. It also identifies important future research trends in data management in P2P DHT systems.

Functionalized Nanodiamonds for Biological and Medical Applications.

PubMed

Lai, Lin; Barnard, Amanda S

2015-02-01

Nanodiamond is a promising material for biological and medical applications, owning to its relatively inexpensive and large-scale synthesis, unique structure, and superior optical properties. However, most biomedical applications, such as drug delivery and bio-imaging, are dependent upon the precise control of the surfaces, and can be significantly affected by the type, distribution and stability of chemical funtionalisations of the nanodiamond surface. In this paper, recent studies on nanodiamonds and their biomedical applications by conjugating with different chemicals are reviewed, while highlighting the critical importance of surface chemical states for various applications.

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.

The accurate particle tracer code

NASA Astrophysics Data System (ADS)

Wang, Yulei; Liu, Jian; Qin, Hong; Yu, Zhi; Yao, Yicun

2017-11-01

The Accurate Particle Tracer (APT) code is designed for systematic large-scale applications of geometric algorithms for particle dynamical simulations. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and nonlinear problems. To provide a flexible and convenient I/O interface, the libraries of Lua and Hdf5 are used. Following a three-step procedure, users can efficiently extend the libraries of electromagnetic configurations, external non-electromagnetic forces, particle pushers, and initialization approaches by use of the extendible module. APT has been used in simulations of key physical problems, such as runaway electrons in tokamaks and energetic particles in Van Allen belt. As an important realization, the APT-SW version has been successfully distributed on the world's fastest computer, the Sunway TaihuLight supercomputer, by supporting master-slave architecture of Sunway many-core processors. Based on large-scale simulations of a runaway beam under parameters of the ITER tokamak, it is revealed that the magnetic ripple field can disperse the pitch-angle distribution significantly and improve the confinement of energetic runaway beam on the same time.

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

Kim, Junghyun; Gangwon, Jo; Jaehoon, Jung

Applications written solely in OpenCL or CUDA cannot execute on a cluster as a whole. Most previous approaches that extend these programming models to clusters are based on a common idea: designating a centralized host node and coordinating the other nodes with the host for computation. However, the centralized host node is a serious performance bottleneck when the number of nodes is large. In this paper, we propose a scalable and distributed OpenCL framework called SnuCL-D for large-scale clusters. SnuCL-D's remote device virtualization provides an OpenCL application with an illusion that all compute devices in a cluster are confined inmore » a single node. To reduce the amount of control-message and data communication between nodes, SnuCL-D replicates the OpenCL host program execution and data in each node. We also propose a new OpenCL host API function and a queueing optimization technique that significantly reduce the overhead incurred by the previous centralized approaches. To show the effectiveness of SnuCL-D, we evaluate SnuCL-D with a microbenchmark and eleven benchmark applications on a large-scale CPU cluster and a medium-scale GPU cluster.« less

Response of deep and shallow tropical maritime cumuli to large-scale processes

NASA Technical Reports Server (NTRS)

Yanai, M.; Chu, J.-H.; Stark, T. E.; Nitta, T.

1976-01-01

The bulk diagnostic method of Yanai et al. (1973) and a simplified version of the spectral diagnostic method of Nitta (1975) are used for a more quantitative evaluation of the response of various types of cumuliform clouds to large-scale processes, using the same data set in the Marshall Islands area for a 100-day period in 1956. The dependence of the cloud mass flux distribution on radiative cooling, large-scale vertical motion, and evaporation from the sea is examined. It is shown that typical radiative cooling rates in the tropics tend to produce a bimodal distribution of mass spectrum exhibiting deep and shallow clouds. The bimodal distribution is further enhanced when the large-scale vertical motion is upward, and a nearly unimodal distribution of shallow clouds prevails when the relative cooling is compensated by the heating due to the large-scale subsidence. Both deep and shallow clouds are modulated by large-scale disturbances. The primary role of surface evaporation is to maintain the moisture flux at the cloud base.

A study of residence time distribution using radiotracer technique in the large scale plant facility

NASA Astrophysics Data System (ADS)

Wetchagarun, S.; Tippayakul, C.; Petchrak, A.; Sukrod, K.; Khoonkamjorn, P.

2017-06-01

As the demand for troubleshooting of large industrial plants increases, radiotracer techniques, which have capability to provide fast, online and effective detections to plant problems, have been continually developed. One of the good potential applications of the radiotracer for troubleshooting in a process plant is the analysis of Residence Time Distribution (RTD). In this paper, the study of RTD in a large scale plant facility using radiotracer technique was presented. The objective of this work is to gain experience on the RTD analysis using radiotracer technique in a “larger than laboratory” scale plant setup which can be comparable to the real industrial application. The experiment was carried out at the sedimentation tank in the water treatment facility of Thailand Institute of Nuclear Technology (Public Organization). Br-82 was selected to use in this work due to its chemical property, its suitable half-life and its on-site availability. NH4Br in the form of aqueous solution was injected into the system as the radiotracer. Six NaI detectors were placed along the pipelines and at the tank in order to determine the RTD of the system. The RTD and the Mean Residence Time (MRT) of the tank was analysed and calculated from the measured data. The experience and knowledge attained from this study is important for extending this technique to be applied to industrial facilities in the future.

Advances toward field application of 3D hydraulic tomography

NASA Astrophysics Data System (ADS)

Cardiff, M. A.; Barrash, W.; Kitanidis, P. K.

2011-12-01

Hydraulic tomography (HT) is a technique that shows great potential for aquifer characterization and one that holds the promise of producing 3D hydraulic property distributions, given suitable equipment. First suggested over 15 years ago, HT assimilates distributed aquifer pressure (head) response data collected during a series of multiple pumping tests to produce estimates of aquifer property variability. Unlike traditional curve-matching analyses, which assume homogeneity or "effective" parameters within the radius of influence of a hydrologic test, HT analysis relies on numerical models with detailed heterogeneity in order to invert for the highly resolved 3D parameter distribution that jointly fits all data. Several numerical and laboratory investigations of characterization using HT have shown that property distributions can be accurately estimated between observation locations when experiments are correctly designed - a property not always shared by other, simpler 1D characterization approaches such as partially-penetrating slug tests. HT may represent one of the best methods available for obtaining detailed 3D aquifer property descriptions, especially in deep or "hard" aquifer materials, where direct-push methods may not be feasible. However, to date HT has not yet been widely adopted at contaminated field sites. We believe that current perceived impediments to HT adoption center around four key issues: 1) A paucity in the scientific literature of proven, cross-validated 3D field applications 2) A lack of guidelines and best practices for performing field 3D HT experiments; 3) Practical difficulty and time commitment associated with the installation of a large number of high-accuracy sampling locations, and the running of a large number of pumping tests; and 4) Computational difficulty associated with solving large-scale inverse problems for parameter identification. In this talk, we present current results in 3D HT research that addresses these four issues, and thus bring HT closer to field practice. Topics to be discussed include: -Improving field efficiency through design and implementation of new modular, easily-installed equipment for 3D HT. -Validating field-scale 3D HT through application and cross-validation at the Boise Hydrogeophysical Research Site. -Developing guidelines for HT implementation based on field experience, numerical modeling, and a comprehensive literature review of the past 15 years of HT research. -Application of novel, fast numerical methods for large-scale HT data analysis. The results presented will focus on the application of 3D HT, but in general we also hope to provide insights on aquifer characterization that stimulate thought on the issue of continually updating aquifer characteristics estimates while recognizing uncertainties and providing guidance for future data collection.

Fire extinguishing tests -80 with methyl alcohol gasoline

NASA Astrophysics Data System (ADS)

Holmstedt, G.; Ryderman, A.; Carlsson, B.; Lennmalm, B.

1980-10-01

Large scale tests and laboratory experiments were carried out for estimating the extinguishing effectiveness of three alcohol resistant aqueous film forming foams (AFFF), two alcohol resistant fluoroprotein foams and two detergent foams in various poolfires: gasoline, isopropyl alcohol, acetone, methyl-ethyl ketone, methyl alcohol and M15 (a gasoline, methyl alcohol, isobutene mixture). The scaling down of large scale tests for developing a reliable laboratory method was especially examined. The tests were performed with semidirect foam application, in pools of 50, 11, 4, 0.6, and 0.25 sq m. Burning time, temperature distribution in the liquid, and thermal radiation were determined. An M15 fire can be extinguished with a detergent foam, but it is impossible to extinguish fires in polar solvents, such as methyl alcohol, acetone, and isopropyl alcohol with detergent foams, AFFF give the best results; and performances with small pools can hardly be correlated with results from large scale fires.

Micron-scale mapping of megagauss magnetic fields using optical polarimetry to probe hot electron transport in petawatt-class laser-solid interactions.

PubMed

Chatterjee, Gourab; Singh, Prashant Kumar; Robinson, A P L; Blackman, D; Booth, N; Culfa, O; Dance, R J; Gizzi, L A; Gray, R J; Green, J S; Koester, P; Kumar, G Ravindra; Labate, L; Lad, Amit D; Lancaster, K L; Pasley, J; Woolsey, N C; Rajeev, P P

2017-08-21

The transport of hot, relativistic electrons produced by the interaction of an intense petawatt laser pulse with a solid has garnered interest due to its potential application in the development of innovative x-ray sources and ion-acceleration schemes. We report on spatially and temporally resolved measurements of megagauss magnetic fields at the rear of a 50-μm thick plastic target, irradiated by a multi-picosecond petawatt laser pulse at an incident intensity of ~10 20 W/cm 2 . The pump-probe polarimetric measurements with micron-scale spatial resolution reveal the dynamics of the magnetic fields generated by the hot electron distribution at the target rear. An annular magnetic field profile was observed ~5 ps after the interaction, indicating a relatively smooth hot electron distribution at the rear-side of the plastic target. This is contrary to previous time-integrated measurements, which infer that such targets will produce highly structured hot electron transport. We measured large-scale filamentation of the hot electron distribution at the target rear only at later time-scales of ~10 ps, resulting in a commensurate large-scale filamentation of the magnetic field profile. Three-dimensional hybrid simulations corroborate our experimental observations and demonstrate a beam-like hot electron transport at initial time-scales that may be attributed to the local resistivity profile at the target rear.

A simple method for the production of large volume 3D macroporous hydrogels for advanced biotechnological, medical and environmental applications

NASA Astrophysics Data System (ADS)

Savina, Irina N.; Ingavle, Ganesh C.; Cundy, Andrew B.; Mikhalovsky, Sergey V.

2016-02-01

The development of bulk, three-dimensional (3D), macroporous polymers with high permeability, large surface area and large volume is highly desirable for a range of applications in the biomedical, biotechnological and environmental areas. The experimental techniques currently used are limited to the production of small size and volume cryogel material. In this work we propose a novel, versatile, simple and reproducible method for the synthesis of large volume porous polymer hydrogels by cryogelation. By controlling the freezing process of the reagent/polymer solution, large-scale 3D macroporous gels with wide interconnected pores (up to 200 μm in diameter) and large accessible surface area have been synthesized. For the first time, macroporous gels (of up to 400 ml bulk volume) with controlled porous structure were manufactured, with potential for scale up to much larger gel dimensions. This method can be used for production of novel 3D multi-component macroporous composite materials with a uniform distribution of embedded particles. The proposed method provides better control of freezing conditions and thus overcomes existing drawbacks limiting production of large gel-based devices and matrices. The proposed method could serve as a new design concept for functional 3D macroporous gels and composites preparation for biomedical, biotechnological and environmental applications.

Design for Run-Time Monitor on Cloud Computing

NASA Astrophysics Data System (ADS)

Kang, Mikyung; Kang, Dong-In; Yun, Mira; Park, Gyung-Leen; Lee, Junghoon

Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well as infrastructure. A cloud is the type of a parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a cloud require adaptive service-based software, which has the capability of monitoring the system status change, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize resources on cloud computing. RTM monitors application software through library instrumentation as well as underlying hardware through performance counter optimizing its computing configuration based on the analyzed data.

Scalable Performance Measurement and Analysis

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

Gamblin, Todd

2009-01-01

Concurrency levels in large-scale, distributed-memory supercomputers are rising exponentially. Modern machines may contain 100,000 or more microprocessor cores, and the largest of these, IBM's Blue Gene/L, contains over 200,000 cores. Future systems are expected to support millions of concurrent tasks. In this dissertation, we focus on efficient techniques for measuring and analyzing the performance of applications running on very large parallel machines. Tuning the performance of large-scale applications can be a subtle and time-consuming task because application developers must measure and interpret data from many independent processes. While the volume of the raw data scales linearly with the number ofmore » tasks in the running system, the number of tasks is growing exponentially, and data for even small systems quickly becomes unmanageable. Transporting performance data from so many processes over a network can perturb application performance and make measurements inaccurate, and storing such data would require a prohibitive amount of space. Moreover, even if it were stored, analyzing the data would be extremely time-consuming. In this dissertation, we present novel methods for reducing performance data volume. The first draws on multi-scale wavelet techniques from signal processing to compress systemwide, time-varying load-balance data. The second uses statistical sampling to select a small subset of running processes to generate low-volume traces. A third approach combines sampling and wavelet compression to stratify performance data adaptively at run-time and to reduce further the cost of sampled tracing. We have integrated these approaches into Libra, a toolset for scalable load-balance analysis. We present Libra and show how it can be used to analyze data from large scientific applications scalably.« less

Low-Cost, Disposable, Flexible and Highly Reproducible Screen Printed SERS Substrates for the Detection of Various Chemicals

PubMed Central

Wu, Wei; Liu, Li; Dai, Zhigao; Liu, Juhua; Yang, Shuanglei; Zhou, Li; Xiao, Xiangheng; Jiang, Changzhong; Roy, Vellaisamy A.L.

2015-01-01

Ideal SERS substrates for sensing applications should exhibit strong signal enhancement, generate a reproducible and uniform response, and should be able to fabricate in large-scale and low-cost. Herein, we demonstrate low-cost, highly sensitive, disposable and reproducible SERS substrates by means of screen printing Ag nanoparticles (NPs) on a plastic PET (Polyethylene terephthalate) substrates. While there are many complex methods for the fabrication of SERS substrates, screen printing is suitable for large-area fabrication and overcomes the uneven radial distribution. Using as-printed Ag substrates as the SERS platform, detection of various commonly known chemicals have been done. The SERS detection limit of Rhodamine 6G (R6G) is higher than the concentration of 1 × 10−10 M. The relative standard deviation (RSD) value for 784 points on the detection of R6G and Malachite green (MG) is less than 20% revealing a homogeneous SERS distribution and high reproducibility. Moreover, melamine (MA) is detected in fresh liquid-milk without additional pretreatment, which may accelerate the application of rapid on-line detection of MA in liquid milk. Our screen printing method highlights the use of large-scale printing strategies for the fabrication of well-defined functional nanostructures with applications well beyond the field of SERS sensing. PMID:25974125

Data Intensive Systems (DIS) Benchmark Performance Summary

DTIC Science & Technology

2003-08-01

models assumed by today’s conventional architectures. Such applications include model- based Automatic Target Recognition (ATR), synthetic aperture...radar (SAR) codes, large scale dynamic databases/battlefield integration, dynamic sensor- based processing, high-speed cryptanalysis, high speed...distributed interactive and data intensive simulations, data-oriented problems characterized by pointer- based and other highly irregular data structures

Distributed 3D Information Visualization - Towards Integration of the Dynamic 3D Graphics and Web Services

NASA Astrophysics Data System (ADS)

Vucinic, Dean; Deen, Danny; Oanta, Emil; Batarilo, Zvonimir; Lacor, Chris

This paper focuses on visualization and manipulation of graphical content in distributed network environments. The developed graphical middleware and 3D desktop prototypes were specialized for situational awareness. This research was done in the LArge Scale COllaborative decision support Technology (LASCOT) project, which explored and combined software technologies to support human-centred decision support system for crisis management (earthquake, tsunami, flooding, airplane or oil-tanker incidents, chemical, radio-active or other pollutants spreading, etc.). The performed state-of-the-art review did not identify any publicly available large scale distributed application of this kind. Existing proprietary solutions rely on the conventional technologies and 2D representations. Our challenge was to apply the "latest" available technologies, such Java3D, X3D and SOAP, compatible with average computer graphics hardware. The selected technologies are integrated and we demonstrate: the flow of data, which originates from heterogeneous data sources; interoperability across different operating systems and 3D visual representations to enhance the end-users interactions.

An evaluation of multi-probe locality sensitive hashing for computing similarities over web-scale query logs.

PubMed

Cormode, Graham; Dasgupta, Anirban; Goyal, Amit; Lee, Chi Hoon

2018-01-01

Many modern applications of AI such as web search, mobile browsing, image processing, and natural language processing rely on finding similar items from a large database of complex objects. Due to the very large scale of data involved (e.g., users' queries from commercial search engines), computing such near or nearest neighbors is a non-trivial task, as the computational cost grows significantly with the number of items. To address this challenge, we adopt Locality Sensitive Hashing (a.k.a, LSH) methods and evaluate four variants in a distributed computing environment (specifically, Hadoop). We identify several optimizations which improve performance, suitable for deployment in very large scale settings. The experimental results demonstrate our variants of LSH achieve the robust performance with better recall compared with "vanilla" LSH, even when using the same amount of space.

Should we trust build-up/wash-off water quality models at the scale of urban catchments?

PubMed

Bonhomme, Céline; Petrucci, Guido

2017-01-01

Models of runoff water quality at the scale of an urban catchment usually rely on build-up/wash-off formulations obtained through small-scale experiments. Often, the physical interpretation of the model parameters, valid at the small-scale, is transposed to large-scale applications. Testing different levels of spatial variability, the parameter distributions of a water quality model are obtained in this paper through a Monte Carlo Markov Chain algorithm and analyzed. The simulated variable is the total suspended solid concentration at the outlet of a periurban catchment in the Paris region (2.3 km 2 ), for which high-frequency turbidity measurements are available. This application suggests that build-up/wash-off models applied at the catchment-scale do not maintain their physical meaning, but should be considered as "black-box" models. Copyright © 2016 Elsevier Ltd. All rights reserved.

A topology visualization early warning distribution algorithm for large-scale network security incidents.

PubMed

He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

2013-01-01

It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.

Large scale synthesis of α-Si3N4 nanowires through a kinetically favored chemical vapour deposition process

NASA Astrophysics Data System (ADS)

Liu, Haitao; Huang, Zhaohui; Zhang, Xiaoguang; Fang, Minghao; Liu, Yan-gai; Wu, Xiaowen; Min, Xin

2018-01-01

Understanding the kinetic barrier and driving force for crystal nucleation and growth is decisive for the synthesis of nanowires with controllable yield and morphology. In this research, we developed an effective reaction system to synthesize very large scale α-Si3N4 nanowires (hundreds of milligrams) and carried out a comparative study to characterize the kinetic influence of gas precursor supersaturation and liquid metal catalyst. The phase composition, morphology, microstructure and photoluminescence properties of the as-synthesized products were characterized by X-ray diffraction, fourier-transform infrared spectroscopy, field emission scanning electron microscopy, transmission electron microscopy and room temperature photoluminescence measurement. The yield of the products not only relates to the reaction temperature (thermodynamic condition) but also to the distribution of gas precursors (kinetic condition). As revealed in this research, by controlling the gas diffusion process, the yield of the nanowire products could be greatly improved. The experimental results indicate that the supersaturation is the dominant factor in the as-designed system rather than the catalyst. With excellent non-flammability and high thermal stability, the large scale α-Si3N4 products would have potential applications to the improvement of strength of high temperature ceramic composites. The photoluminescence spectrum of the α-Si3N4 shows a blue shift which could be valued for future applications in blue-green emitting devices. There is no doubt that the large scale products are the base of these applications.

Beowulf Distributed Processing and the United States Geological Survey

USGS Publications Warehouse

Maddox, Brian G.

2002-01-01

Introduction In recent years, the United States Geological Survey's (USGS) National Mapping Discipline (NMD) has expanded its scientific and research activities. Work is being conducted in areas such as emergency response research, scientific visualization, urban prediction, and other simulation activities. Custom-produced digital data have become essential for these types of activities. High-resolution, remotely sensed datasets are also seeing increased use. Unfortunately, the NMD is also finding that it lacks the resources required to perform some of these activities. Many of these projects require large amounts of computer processing resources. Complex urban-prediction simulations, for example, involve large amounts of processor-intensive calculations on large amounts of input data. This project was undertaken to learn and understand the concepts of distributed processing. Experience was needed in developing these types of applications. The idea was that this type of technology could significantly aid the needs of the NMD scientific and research programs. Porting a numerically intensive application currently being used by an NMD science program to run in a distributed fashion would demonstrate the usefulness of this technology. There are several benefits that this type of technology can bring to the USGS's research programs. Projects can be performed that were previously impossible due to a lack of computing resources. Other projects can be performed on a larger scale than previously possible. For example, distributed processing can enable urban dynamics research to perform simulations on larger areas without making huge sacrifices in resolution. The processing can also be done in a more reasonable amount of time than with traditional single-threaded methods (a scaled version of Chester County, Pennsylvania, took about fifty days to finish its first calibration phase with a single-threaded program). This paper has several goals regarding distributed processing technology. It will describe the benefits of the technology. Real data about a distributed application will be presented as an example of the benefits that this technology can bring to USGS scientific programs. Finally, some of the issues with distributed processing that relate to USGS work will be discussed.

Autonomous management of a recursive area hierarchy for large scale wireless sensor networks using multiple parents

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

Cree, Johnathan Vee; Delgado-Frias, Jose

Large scale wireless sensor networks have been proposed for applications ranging from anomaly detection in an environment to vehicle tracking. Many of these applications require the networks to be distributed across a large geographic area while supporting three to five year network lifetimes. In order to support these requirements large scale wireless sensor networks of duty-cycled devices need a method of efficient and effective autonomous configuration/maintenance. This method should gracefully handle the synchronization tasks duty-cycled networks. Further, an effective configuration solution needs to recognize that in-network data aggregation and analysis presents significant benefits to wireless sensor network and should configuremore » the network in a way such that said higher level functions benefit from the logically imposed structure. NOA, the proposed configuration and maintenance protocol, provides a multi-parent hierarchical logical structure for the network that reduces the synchronization workload. It also provides higher level functions with significant inherent benefits such as but not limited to: removing network divisions that are created by single-parent hierarchies, guarantees for when data will be compared in the hierarchy, and redundancies for communication as well as in-network data aggregation/analysis/storage.« less

Three-dimensional constrained variational analysis: Approach and application to analysis of atmospheric diabatic heating and derivative fields during an ARM SGP intensive observational period

NASA Astrophysics Data System (ADS)

Tang, Shuaiqi; Zhang, Minghua

2015-08-01

Atmospheric vertical velocities and advective tendencies are essential large-scale forcing data to drive single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulations (LESs). However, they cannot be directly measured from field measurements or easily calculated with great accuracy. In the Atmospheric Radiation Measurement Program (ARM), a constrained variational algorithm (1-D constrained variational analysis (1DCVA)) has been used to derive large-scale forcing data over a sounding network domain with the aid of flux measurements at the surface and top of the atmosphere (TOA). The 1DCVA algorithm is now extended into three dimensions (3DCVA) along with other improvements to calculate gridded large-scale forcing data, diabatic heating sources (Q1), and moisture sinks (Q2). Results are presented for a midlatitude cyclone case study on 3 March 2000 at the ARM Southern Great Plains site. These results are used to evaluate the diabatic heating fields in the available products such as Rapid Update Cycle, ERA-Interim, National Centers for Environmental Prediction Climate Forecast System Reanalysis, Modern-Era Retrospective Analysis for Research and Applications, Japanese 55-year Reanalysis, and North American Regional Reanalysis. We show that although the analysis/reanalysis generally captures the atmospheric state of the cyclone, their biases in the derivative terms (Q1 and Q2) at regional scale of a few hundred kilometers are large and all analyses/reanalyses tend to underestimate the subgrid-scale upward transport of moist static energy in the lower troposphere. The 3DCVA-gridded large-scale forcing data are physically consistent with the spatial distribution of surface and TOA measurements of radiation, precipitation, latent and sensible heat fluxes, and clouds that are better suited to force SCMs, CRMs, and LESs. Possible applications of the 3DCVA are discussed.

Exploiting multi-scale parallelism for large scale numerical modelling of laser wakefield accelerators

NASA Astrophysics Data System (ADS)

Fonseca, R. A.; Vieira, J.; Fiuza, F.; Davidson, A.; Tsung, F. S.; Mori, W. B.; Silva, L. O.

2013-12-01

A new generation of laser wakefield accelerators (LWFA), supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances for multiple applications. Achieving this goal will rely heavily on numerical modelling to further understand the underlying physics and identify optimal regimes, but large scale modelling of these scenarios is computationally heavy and requires the efficient use of state-of-the-art petascale supercomputing systems. We discuss the main difficulties involved in running these simulations and the new developments implemented in the OSIRIS framework to address these issues, ranging from multi-dimensional dynamic load balancing and hybrid distributed/shared memory parallelism to the vectorization of the PIC algorithm. We present the results of the OASCR Joule Metric program on the issue of large scale modelling of LWFA, demonstrating speedups of over 1 order of magnitude on the same hardware. Finally, scalability to over ˜106 cores and sustained performance over ˜2 P Flops is demonstrated, opening the way for large scale modelling of LWFA scenarios.

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

Building and measuring a high performance network architecture

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

Kramer, William T.C.; Toole, Timothy; Fisher, Chuck

2001-04-20

Once a year, the SC conferences present a unique opportunity to create and build one of the most complex and highest performance networks in the world. At SC2000, large-scale and complex local and wide area networking connections were demonstrated, including large-scale distributed applications running on different architectures. This project was designed to use the unique opportunity presented at SC2000 to create a testbed network environment and then use that network to demonstrate and evaluate high performance computational and communication applications. This testbed was designed to incorporate many interoperable systems and services and was designed for measurement from the very beginning.more » The end results were key insights into how to use novel, high performance networking technologies and to accumulate measurements that will give insights into the networks of the future.« less

Transverse momentum dependent (TMD) parton distribution functions: Status and prospects*

DOE PAGES

Angeles-Martinez, R.; Bacchetta, A.; Balitsky, Ian I.; ...

2015-01-01

In this study, we review transverse momentum dependent (TMD) parton distribution functions, their application to topical issues in high-energy physics phenomenology, and their theoretical connections with QCD resummation, evolution and factorization theorems. We illustrate the use of TMDs via examples of multi-scale problems in hadronic collisions. These include transverse momentum q T spectra of Higgs and vector bosons for low q T, and azimuthal correlations in the production of multiple jets associated with heavy bosons at large jet masses. We discuss computational tools for TMDs, and present the application of a new tool, TMD LIB, to parton density fits andmore » parameterizations.« less

Extensions of Island Biogeography Theory predict the scaling of functional trait composition with habitat area and isolation.

PubMed

Jacquet, Claire; Mouillot, David; Kulbicki, Michel; Gravel, Dominique

2017-02-01

The Theory of Island Biogeography (TIB) predicts how area and isolation influence species richness equilibrium on insular habitats. However, the TIB remains silent about functional trait composition and provides no information on the scaling of functional diversity with area, an observation that is now documented in many systems. To fill this gap, we develop a probabilistic approach to predict the distribution of a trait as a function of habitat area and isolation, extending the TIB beyond the traditional species-area relationship. We compare model predictions to the body-size distribution of piscivorous and herbivorous fishes found on tropical reefs worldwide. We find that small and isolated reefs have a higher proportion of large-sized species than large and connected reefs. We also find that knowledge of species body-size and trophic position improves the predictions of fish occupancy on tropical reefs, supporting both the allometric and trophic theory of island biogeography. The integration of functional ecology to island biogeography is broadly applicable to any functional traits and provides a general probabilistic approach to study the scaling of trait distribution with habitat area and isolation. © 2016 John Wiley & Sons Ltd/CNRS.

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge

PubMed Central

Gallicchio, Emilio; Deng, Nanjie; He, Peng; Wickstrom, Lauren; Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Olson, Arthur J.; Levy, Ronald M.

2014-01-01

As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization. PMID:24504704

Scientific Services on the Cloud

NASA Astrophysics Data System (ADS)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

Analyzing large scale genomic data on the cloud with Sparkhit

PubMed Central

Huang, Liren; Krüger, Jan

2018-01-01

Abstract Motivation The increasing amount of next-generation sequencing data poses a fundamental challenge on large scale genomic analytics. Existing tools use different distributed computational platforms to scale-out bioinformatics workloads. However, the scalability of these tools is not efficient. Moreover, they have heavy run time overheads when pre-processing large amounts of data. To address these limitations, we have developed Sparkhit: a distributed bioinformatics framework built on top of the Apache Spark platform. Results Sparkhit integrates a variety of analytical methods. It is implemented in the Spark extended MapReduce model. It runs 92–157 times faster than MetaSpark on metagenomic fragment recruitment and 18–32 times faster than Crossbow on data pre-processing. We analyzed 100 terabytes of data across four genomic projects in the cloud in 21 h, which includes the run times of cluster deployment and data downloading. Furthermore, our application on the entire Human Microbiome Project shotgun sequencing data was completed in 2 h, presenting an approach to easily associate large amounts of public datasets with reference data. Availability and implementation Sparkhit is freely available at: https://rhinempi.github.io/sparkhit/. Contact asczyrba@cebitec.uni-bielefeld.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:29253074

GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

NASA Astrophysics Data System (ADS)

Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

2016-12-01

Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We tested the performance of the platform based on taxi trajectory analysis. Results suggested that GISpark achieves excellent run time performance in spatiotemporal big data applications.

Applied Distributed Model Predictive Control for Energy Efficient Buildings and Ramp Metering

NASA Astrophysics Data System (ADS)

Koehler, Sarah Muraoka

Industrial large-scale control problems present an interesting algorithmic design challenge. A number of controllers must cooperate in real-time on a network of embedded hardware with limited computing power in order to maximize system efficiency while respecting constraints and despite communication delays. Model predictive control (MPC) can automatically synthesize a centralized controller which optimizes an objective function subject to a system model, constraints, and predictions of disturbance. Unfortunately, the computations required by model predictive controllers for large-scale systems often limit its industrial implementation only to medium-scale slow processes. Distributed model predictive control (DMPC) enters the picture as a way to decentralize a large-scale model predictive control problem. The main idea of DMPC is to split the computations required by the MPC problem amongst distributed processors that can compute in parallel and communicate iteratively to find a solution. Some popularly proposed solutions are distributed optimization algorithms such as dual decomposition and the alternating direction method of multipliers (ADMM). However, these algorithms ignore two practical challenges: substantial communication delays present in control systems and also problem non-convexity. This thesis presents two novel and practically effective DMPC algorithms. The first DMPC algorithm is based on a primal-dual active-set method which achieves fast convergence, making it suitable for large-scale control applications which have a large communication delay across its communication network. In particular, this algorithm is suited for MPC problems with a quadratic cost, linear dynamics, forecasted demand, and box constraints. We measure the performance of this algorithm and show that it significantly outperforms both dual decomposition and ADMM in the presence of communication delay. The second DMPC algorithm is based on an inexact interior point method which is suited for nonlinear optimization problems. The parallel computation of the algorithm exploits iterative linear algebra methods for the main linear algebra computations in the algorithm. We show that the splitting of the algorithm is flexible and can thus be applied to various distributed platform configurations. The two proposed algorithms are applied to two main energy and transportation control problems. The first application is energy efficient building control. Buildings represent 40% of energy consumption in the United States. Thus, it is significant to improve the energy efficiency of buildings. The goal is to minimize energy consumption subject to the physics of the building (e.g. heat transfer laws), the constraints of the actuators as well as the desired operating constraints (thermal comfort of the occupants), and heat load on the system. In this thesis, we describe the control systems of forced air building systems in practice. We discuss the "Trim and Respond" algorithm which is a distributed control algorithm that is used in practice, and show that it performs similarly to a one-step explicit DMPC algorithm. Then, we apply the novel distributed primal-dual active-set method and provide extensive numerical results for the building MPC problem. The second main application is the control of ramp metering signals to optimize traffic flow through a freeway system. This application is particularly important since urban congestion has more than doubled in the past few decades. The ramp metering problem is to maximize freeway throughput subject to freeway dynamics (derived from mass conservation), actuation constraints, freeway capacity constraints, and predicted traffic demand. In this thesis, we develop a hybrid model predictive controller for ramp metering that is guaranteed to be persistently feasible and stable. This contrasts to previous work on MPC for ramp metering where such guarantees are absent. We apply a smoothing method to the hybrid model predictive controller and apply the inexact interior point method to this nonlinear non-convex ramp metering problem.

The accurate particle tracer code

DOE PAGES

Wang, Yulei; Liu, Jian; Qin, Hong; ...

2017-07-20

The Accurate Particle Tracer (APT) code is designed for systematic large-scale applications of geometric algorithms for particle dynamical simulations. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and nonlinear problems. To provide a flexible and convenient I/O interface, the libraries of Lua and Hdf5 are used. Following a three-step procedure, users can efficiently extend the libraries of electromagnetic configurations, external non-electromagnetic forces, particle pushers, and initialization approaches by use of the extendible module. APT has been used in simulations of key physical problems, such as runawaymore » electrons in tokamaks and energetic particles in Van Allen belt. As an important realization, the APT-SW version has been successfully distributed on the world’s fastest computer, the Sunway TaihuLight supercomputer, by supporting master–slave architecture of Sunway many-core processors. Here, based on large-scale simulations of a runaway beam under parameters of the ITER tokamak, it is revealed that the magnetic ripple field can disperse the pitch-angle distribution significantly and improve the confinement of energetic runaway beam on the same time.« less

The accurate particle tracer code

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

Wang, Yulei; Liu, Jian; Qin, Hong

The Accurate Particle Tracer (APT) code is designed for systematic large-scale applications of geometric algorithms for particle dynamical simulations. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and nonlinear problems. To provide a flexible and convenient I/O interface, the libraries of Lua and Hdf5 are used. Following a three-step procedure, users can efficiently extend the libraries of electromagnetic configurations, external non-electromagnetic forces, particle pushers, and initialization approaches by use of the extendible module. APT has been used in simulations of key physical problems, such as runawaymore » electrons in tokamaks and energetic particles in Van Allen belt. As an important realization, the APT-SW version has been successfully distributed on the world’s fastest computer, the Sunway TaihuLight supercomputer, by supporting master–slave architecture of Sunway many-core processors. Here, based on large-scale simulations of a runaway beam under parameters of the ITER tokamak, it is revealed that the magnetic ripple field can disperse the pitch-angle distribution significantly and improve the confinement of energetic runaway beam on the same time.« less

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

NASA Technical Reports Server (NTRS)

Johnston, William E.

2002-01-01

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System.

PubMed

Passerat-Palmbach, Jonathan; Reuillon, Romain; Leclaire, Mathieu; Makropoulos, Antonios; Robinson, Emma C; Parisot, Sarah; Rueckert, Daniel

2017-01-01

OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition. The construction of the pipeline itself is decoupled from the execution context. The high-level DSL abstracts the underlying execution environment, contrary to classic shell-script based pipelines. These two aspects allow pipelines to be shared and studies to be replicated across different computing environments. Workflows can be run as traditional batch pipelines or coupled with OpenMOLE's advanced exploration methods in order to study the behavior of an application, or perform automatic parameter tuning. In this work, we briefly present the strong assets of OpenMOLE and detail recent improvements targeting re-executability of workflows across various Linux platforms. We have tightly coupled OpenMOLE with CARE, a standalone containerization solution that allows re-executing on a Linux host any application that has been packaged on another Linux host previously. The solution is evaluated against a Python-based pipeline involving packages such as scikit-learn as well as binary dependencies. All were packaged and re-executed successfully on various HPC environments, with identical numerical results (here prediction scores) obtained on each environment. Our results show that the pair formed by OpenMOLE and CARE is a reliable solution to generate reproducible results and re-executable pipelines. A demonstration of the flexibility of our solution showcases three neuroimaging pipelines harnessing distributed computing environments as heterogeneous as local clusters or the European Grid Infrastructure (EGI).

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System

PubMed Central

Passerat-Palmbach, Jonathan; Reuillon, Romain; Leclaire, Mathieu; Makropoulos, Antonios; Robinson, Emma C.; Parisot, Sarah; Rueckert, Daniel

2017-01-01

OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition. The construction of the pipeline itself is decoupled from the execution context. The high-level DSL abstracts the underlying execution environment, contrary to classic shell-script based pipelines. These two aspects allow pipelines to be shared and studies to be replicated across different computing environments. Workflows can be run as traditional batch pipelines or coupled with OpenMOLE's advanced exploration methods in order to study the behavior of an application, or perform automatic parameter tuning. In this work, we briefly present the strong assets of OpenMOLE and detail recent improvements targeting re-executability of workflows across various Linux platforms. We have tightly coupled OpenMOLE with CARE, a standalone containerization solution that allows re-executing on a Linux host any application that has been packaged on another Linux host previously. The solution is evaluated against a Python-based pipeline involving packages such as scikit-learn as well as binary dependencies. All were packaged and re-executed successfully on various HPC environments, with identical numerical results (here prediction scores) obtained on each environment. Our results show that the pair formed by OpenMOLE and CARE is a reliable solution to generate reproducible results and re-executable pipelines. A demonstration of the flexibility of our solution showcases three neuroimaging pipelines harnessing distributed computing environments as heterogeneous as local clusters or the European Grid Infrastructure (EGI). PMID:28381997

Comparison of prestellar core elongations and large-scale molecular cloud structures in the Lupus I region

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

Poidevin, Frédérick; Ade, Peter A. R.; Hargrave, Peter C.

2014-08-10

Turbulence and magnetic fields are expected to be important for regulating molecular cloud formation and evolution. However, their effects on sub-parsec to 100 parsec scales, leading to the formation of starless cores, are not well understood. We investigate the prestellar core structure morphologies obtained from analysis of the Herschel-SPIRE 350 μm maps of the Lupus I cloud. This distribution is first compared on a statistical basis to the large-scale shape of the main filament. We find the distribution of the elongation position angle of the cores to be consistent with a random distribution, which means no specific orientation of themore » morphology of the cores is observed with respect to the mean orientation of the large-scale filament in Lupus I, nor relative to a large-scale bent filament model. This distribution is also compared to the mean orientation of the large-scale magnetic fields probed at 350 μm with the Balloon-borne Large Aperture Telescope for Polarimetry during its 2010 campaign. Here again we do not find any correlation between the core morphology distribution and the average orientation of the magnetic fields on parsec scales. Our main conclusion is that the local filament dynamics—including secondary filaments that often run orthogonally to the primary filament—and possibly small-scale variations in the local magnetic field direction, could be the dominant factors for explaining the final orientation of each core.« less

An evaluation of multi-probe locality sensitive hashing for computing similarities over web-scale query logs

PubMed Central

2018-01-01

Many modern applications of AI such as web search, mobile browsing, image processing, and natural language processing rely on finding similar items from a large database of complex objects. Due to the very large scale of data involved (e.g., users’ queries from commercial search engines), computing such near or nearest neighbors is a non-trivial task, as the computational cost grows significantly with the number of items. To address this challenge, we adopt Locality Sensitive Hashing (a.k.a, LSH) methods and evaluate four variants in a distributed computing environment (specifically, Hadoop). We identify several optimizations which improve performance, suitable for deployment in very large scale settings. The experimental results demonstrate our variants of LSH achieve the robust performance with better recall compared with “vanilla” LSH, even when using the same amount of space. PMID:29346410

Large-scale anisotropy of the cosmic microwave background radiation

NASA Technical Reports Server (NTRS)

Silk, J.; Wilson, M. L.

1981-01-01

Inhomogeneities in the large-scale distribution of matter inevitably lead to the generation of large-scale anisotropy in the cosmic background radiation. The dipole, quadrupole, and higher order fluctuations expected in an Einstein-de Sitter cosmological model have been computed. The dipole and quadrupole anisotropies are comparable to the measured values, and impose important constraints on the allowable spectrum of large-scale matter density fluctuations. A significant dipole anisotropy is generated by the matter distribution on scales greater than approximately 100 Mpc. The large-scale anisotropy is insensitive to the ionization history of the universe since decoupling, and cannot easily be reconciled with a galaxy formation theory that is based on primordial adiabatic density fluctuations.

A simple method for the production of large volume 3D macroporous hydrogels for advanced biotechnological, medical and environmental applications

PubMed Central

Savina, Irina N.; Ingavle, Ganesh C.; Cundy, Andrew B.; Mikhalovsky, Sergey V.

2016-01-01

The development of bulk, three-dimensional (3D), macroporous polymers with high permeability, large surface area and large volume is highly desirable for a range of applications in the biomedical, biotechnological and environmental areas. The experimental techniques currently used are limited to the production of small size and volume cryogel material. In this work we propose a novel, versatile, simple and reproducible method for the synthesis of large volume porous polymer hydrogels by cryogelation. By controlling the freezing process of the reagent/polymer solution, large-scale 3D macroporous gels with wide interconnected pores (up to 200 μm in diameter) and large accessible surface area have been synthesized. For the first time, macroporous gels (of up to 400 ml bulk volume) with controlled porous structure were manufactured, with potential for scale up to much larger gel dimensions. This method can be used for production of novel 3D multi-component macroporous composite materials with a uniform distribution of embedded particles. The proposed method provides better control of freezing conditions and thus overcomes existing drawbacks limiting production of large gel-based devices and matrices. The proposed method could serve as a new design concept for functional 3D macroporous gels and composites preparation for biomedical, biotechnological and environmental applications. PMID:26883390

The Large -scale Distribution of Galaxies

NASA Astrophysics Data System (ADS)

Flin, Piotr

A review of the Large-scale structure of the Universe is given. A connection is made with the titanic work by Johannes Kepler in many areas of astronomy and cosmology. A special concern is made to spatial distribution of Galaxies, voids and walls (cellular structure of the Universe). Finaly, the author is concluding that the large scale structure of the Universe can be observed in much greater scale that it was thought twenty years ago.

Male group size, female distribution and changes in sexual segregation by Roosevelt elk

PubMed Central

Peterson, Leah M.

2017-01-01

Sexual segregation, or the differential use of space by males and females, is hypothesized to be a function of body size dimorphism. Sexual segregation can also manifest at small (social segregation) and large (habitat segregation) spatial scales for a variety of reasons. Furthermore, the connection between small- and large-scale sexual segregation has rarely been addressed. We studied a population of Roosevelt elk (Cervus elaphus roosevelti) across 21 years in north coastal California, USA, to assess small- and large-scale sexual segregation in winter. We hypothesized that male group size would associate with small-scale segregation and that a change in female distribution would associate with large-scale segregation. Variation in forage biomass might also be coupled to small and large-scale sexual segregation. Our findings were consistent with male group size associating with small-scale segregation and a change in female distribution associating with large-scale segregation. Females appeared to avoid large groups comprised of socially dominant males. Males appeared to occupy a habitat vacated by females because of a wider forage niche, greater tolerance to lethal risks, and, perhaps, to reduce encounters with other elk. Sexual segregation at both spatial scales was a poor predictor of forage biomass. Size dimorphism was coupled to change in sexual segregation at small and large spatial scales. Small scale segregation can seemingly manifest when all forage habitat is occupied by females and large scale segregation might happen when some forage habitat is not occupied by females. PMID:29121076

Integration of climatic water deficit and fine-scale physiography in process-based modeling of forest landscape resilience to large-scale tree mortality

NASA Astrophysics Data System (ADS)

Yang, J.; Weisberg, P.; Dilts, T.

2016-12-01

Climate warming can lead to large-scale drought-induced tree mortality events and greatly affect forest landscape resilience. Climatic water deficit (CWD) and its physiographic variations provide a key mechanism in driving landscape dynamics in response to climate change. Although CWD has been successfully applied in niche-based species distribution models, its application in process-based forest landscape models is still scarce. Here we present a framework incorporating fine-scale influence of terrain on ecohydrology in modeling forest landscape dynamics. We integrated CWD with a forest landscape succession and disturbance model (LANDIS-II) to evaluate how tree species distribution might shift in response to different climate-fire scenarios across an elevation-aspect gradient in a semi-arid montane landscape of northeastern Nevada, USA. Our simulations indicated that drought-intolerant tree species such as quaking aspen could experience greatly reduced distributions in the more arid portions of their existing ranges due to water stress limitations under future climate warming scenarios. However, even at the most xeric portions of its range, aspen is likely to persist in certain environmental settings due to unique and often fine-scale combinations of resource availability, species interactions and disturbance regime. The modeling approach presented here allowed identification of these refugia. In addition, this approach helped quantify how the direction and magnitude of fire influences on species distribution would vary across topoclimatic gradients, as well as furthers our understanding on the role of environmental conditions, fire, and inter-specific competition in shaping potential responses of landscape resilience to climate change.

2012 Market Report on U.S. Wind Technologies in Distributed Applications

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

Orrell, Alice C.; Flowers, L. T.; Gagne, M. N.

2013-08-06

At the end of 2012, U.S. wind turbines in distributed applications reached a 10-year cumulative installed capacity of more than 812 MW from more than 69,000 units across all 50 states. In 2012 alone, nearly 3,800 wind turbines totaling 175 MW of distributed wind capacity were documented in 40 states and in the U.S. Virgin Islands, with 138 MW using utility-scale turbines (i.e., greater than 1 MW in size), 19 MW using mid-size turbines (i.e., 101 kW to 1 MW in size), and 18.4 MW using small turbines (i.e., up to 100 kW in size). Distributed wind is defined inmore » terms of technology application based on a wind project’s location relative to end-use and power-distribution infrastructure, rather than on technology size or project size. Distributed wind systems are either connected on the customer side of the meter (to meet the onsite load) or directly to distribution or micro grids (to support grid operations or offset large loads nearby). Estimated capacity-weighted average costs for 2012 U.S. distributed wind installations was $2,540/kW for utility-scale wind turbines, $2,810/kW for mid-sized wind turbines, and $6,960/kW for newly manufactured (domestic and imported) small wind turbines. An emerging trend observed in 2012 was an increased use of refurbished turbines. The estimated capacity-weighted average cost of refurbished small wind turbines installed in 2012 was $4,080/kW. As a result of multiple projects using utility-scale turbines, Iowa deployed the most new overall distributed wind capacity, 37 MW, in 2012. Nevada deployed the most small wind capacity in 2012, with nearly 8 MW of small wind turbines installed in distributed applications. In the case of mid-size turbines, Ohio led all states in 2012 with 4.9 MW installed in distributed applications. State and federal policies and incentives continued to play a substantial role in the development of distributed wind projects. In 2012, U.S. Treasury Section 1603 payments and grants and loans from the U.S. Department of Agriculture’s Rural Energy for America Program were the main sources of federal funding for distributed wind projects. State and local funding varied across the country, from rebates to loans, tax credits, and other incentives. Reducing utility bills and hedging against potentially rising electricity rates remain drivers of distributed wind installations. In 2012, other drivers included taking advantage of the expiring U.S. Treasury Section 1603 program and a prosperous year for farmers. While 2012 saw a large addition of distributed wind capacity, considerable barriers and challenges remain, such as a weak domestic economy, inconsistent state incentives, and very competitive solar photovoltaic and natural gas prices. The industry remains committed to improving the distributed wind marketplace by advancing the third-party certification process and introducing alternative financing models, such as third-party power purchase agreements and lease-to-own agreements more typical in the solar photovoltaic market. Continued growth is expected in 2013.« less

Architectural Optimization of Digital Libraries

NASA Technical Reports Server (NTRS)

Biser, Aileen O.

1998-01-01

This work investigates performance and scaling issues relevant to large scale distributed digital libraries. Presently, performance and scaling studies focus on specific implementations of production or prototype digital libraries. Although useful information is gained to aid these designers and other researchers with insights to performance and scaling issues, the broader issues relevant to very large scale distributed libraries are not addressed. Specifically, no current studies look at the extreme or worst case possibilities in digital library implementations. A survey of digital library research issues is presented. Scaling and performance issues are mentioned frequently in the digital library literature but are generally not the focus of much of the current research. In this thesis a model for a Generic Distributed Digital Library (GDDL) and nine cases of typical user activities are defined. This model is used to facilitate some basic analysis of scaling issues. Specifically, the calculation of Internet traffic generated for different configurations of the study parameters and an estimate of the future bandwidth needed for a large scale distributed digital library implementation. This analysis demonstrates the potential impact a future distributed digital library implementation would have on the Internet traffic load and raises questions concerning the architecture decisions being made for future distributed digital library designs.

Evolution of the Busbar Structure in Large-Scale Aluminum Reduction Cells

NASA Astrophysics Data System (ADS)

Zhang, Hongliang; Liang, Jinding; Li, Jie; Sun, Kena; Xiao, Jin

2017-02-01

Studies of magnetic field and magneto-hydro-dynamics are regarded as the foundation for the development of large-scale aluminum reduction cells, while due to the direct relationship between the busbar configuration and magnetic compensation, the actual key content is the configuration of the busbar. As the line current has been increased from 160 kA to 600 kA, the configuration of the busbar was becoming more complex. To summarize and explore the evolution of busbar configuration in aluminum reduction cells, this paper has reviewed various representative large-scale pre-baked aluminum reduction cell busbar structures, such as end-to-end potlines, side-by-side potlines and external compensation current. The advantages and disadvantages in the magnetic distribution or technical specifications have also been introduced separately, especially for the configurations of the mainstream 400-kA potlines. In the end, the development trends of the bus structure configuration were prospected, based on the recent successful applications of super-scale cell busbar structures in China (500-600 kA).

Fire extinguishing tests -80 with methyl alcohol gasoline (in MIXED)

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

Holmstedt, G.; Ryderman, A.; Carlsson, B.

1980-01-01

Large scale tests and laboratory experiments were carried out for estimating the extinguishing effectiveness of three alcohol resistant aqueous film forming foams (AFFF), two alcohol resistant fluoroprotein foams and two detergent foams in various poolfires: gasoline, isopropyl alcohol, acetone, methyl-ethyl ketone, methyl alcohol and M15 (a gasoline, methyl alcohol, isobutene mixture). The scaling down of large scale tests for developing a reliable laboratory method was especially examined. The tests were performed with semidirect foam application, in pools of 50, 11, 4, 0.6, and 0.25 sq m. Burning time, temperature distribution in the liquid, and thermal radiation were determined. An M15more » fire can be extinguished with a detergent foam, but it is impossible to extinguish fires in polar solvents, such as methyl alcohol, acetone, and isopropyl alcohol with detergent foams, AFFF give the best results, and performances with small pools can hardly be correlated with results from large scale fires.« less

Comparison of the Frontier Distributed Database Caching System to NoSQL Databases

NASA Astrophysics Data System (ADS)

Dykstra, Dave

2012-12-01

One of the main attractions of non-relational “NoSQL” databases is their ability to scale to large numbers of readers, including readers spread over a wide area. The Frontier distributed database caching system, used in production by the Large Hadron Collider CMS and ATLAS detector projects for Conditions data, is based on traditional SQL databases but also adds high scalability and the ability to be distributed over a wide-area for an important subset of applications. This paper compares the major characteristics of the two different approaches and identifies the criteria for choosing which approach to prefer over the other. It also compares in some detail the NoSQL databases used by CMS and ATLAS: MongoDB, CouchDB, HBase, and Cassandra.

Comparison of the Frontier Distributed Database Caching System to NoSQL Databases

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

Dykstra, Dave

One of the main attractions of non-relational NoSQL databases is their ability to scale to large numbers of readers, including readers spread over a wide area. The Frontier distributed database caching system, used in production by the Large Hadron Collider CMS and ATLAS detector projects for Conditions data, is based on traditional SQL databases but also adds high scalability and the ability to be distributed over a wide-area for an important subset of applications. This paper compares the major characteristics of the two different approaches and identifies the criteria for choosing which approach to prefer over the other. It alsomore » compares in some detail the NoSQL databases used by CMS and ATLAS: MongoDB, CouchDB, HBase, and Cassandra.« less

Estimating large carnivore populations at global scale based on spatial predictions of density and distribution – Application to the jaguar (Panthera onca)

PubMed Central

Robinson, Hugh S.; Abarca, Maria; Zeller, Katherine A.; Velasquez, Grisel; Paemelaere, Evi A. D.; Goldberg, Joshua F.; Payan, Esteban; Hoogesteijn, Rafael; Boede, Ernesto O.; Schmidt, Krzysztof; Lampo, Margarita; Viloria, Ángel L.; Carreño, Rafael; Robinson, Nathaniel; Lukacs, Paul M.; Nowak, J. Joshua; Salom-Pérez, Roberto; Castañeda, Franklin; Boron, Valeria; Quigley, Howard

2018-01-01

Broad scale population estimates of declining species are desired for conservation efforts. However, for many secretive species including large carnivores, such estimates are often difficult. Based on published density estimates obtained through camera trapping, presence/absence data, and globally available predictive variables derived from satellite imagery, we modelled density and occurrence of a large carnivore, the jaguar, across the species’ entire range. We then combined these models in a hierarchical framework to estimate the total population. Our models indicate that potential jaguar density is best predicted by measures of primary productivity, with the highest densities in the most productive tropical habitats and a clear declining gradient with distance from the equator. Jaguar distribution, in contrast, is determined by the combined effects of human impacts and environmental factors: probability of jaguar occurrence increased with forest cover, mean temperature, and annual precipitation and declined with increases in human foot print index and human density. Probability of occurrence was also significantly higher for protected areas than outside of them. We estimated the world’s jaguar population at 173,000 (95% CI: 138,000–208,000) individuals, mostly concentrated in the Amazon Basin; elsewhere, populations tend to be small and fragmented. The high number of jaguars results from the large total area still occupied (almost 9 million km2) and low human densities (< 1 person/km2) coinciding with high primary productivity in the core area of jaguar range. Our results show the importance of protected areas for jaguar persistence. We conclude that combining modelling of density and distribution can reveal ecological patterns and processes at global scales, can provide robust estimates for use in species assessments, and can guide broad-scale conservation actions. PMID:29579129

Design of Availability-Dependent Distributed Services in Large-Scale Uncooperative Settings

ERIC Educational Resources Information Center

Morales, Ramses Victor

2009-01-01

Thesis Statement: "Availability-dependent global predicates can be efficiently and scalably realized for a class of distributed services, in spite of specific selfish and colluding behaviors, using local and decentralized protocols". Several types of large-scale distributed systems spanning the Internet have to deal with availability variations…

Design and Development of a Run-Time Monitor for Multi-Core Architectures in Cloud Computing

PubMed Central

Kang, Mikyung; Kang, Dong-In; Crago, Stephen P.; Park, Gyung-Leen; Lee, Junghoon

2011-01-01

Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well as infrastructure. A cloud is a type of parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a cloud require adaptive service-based software, which has the capability of monitoring system status changes, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design and develop a Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize cloud computing resources for multi-core architectures. RTM monitors application software through library instrumentation as well as underlying hardware through a performance counter optimizing its computing configuration based on the analyzed data. PMID:22163811

Design and development of a run-time monitor for multi-core architectures in cloud computing.

PubMed

Kang, Mikyung; Kang, Dong-In; Crago, Stephen P; Park, Gyung-Leen; Lee, Junghoon

2011-01-01

Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well as infrastructure. A cloud is a type of parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a cloud require adaptive service-based software, which has the capability of monitoring system status changes, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design and develop a Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize cloud computing resources for multi-core architectures. RTM monitors application software through library instrumentation as well as underlying hardware through a performance counter optimizing its computing configuration based on the analyzed data.

Wireless Technology Infrastructures for Authentication of Patients: PKI that Rings

PubMed Central

Sax, Ulrich; Kohane, Isaac; Mandl, Kenneth D.

2005-01-01

As the public interest in consumer-driven electronic health care applications rises, so do concerns about the privacy and security of these applications. Achieving a balance between providing the necessary security while promoting user acceptance is a major obstacle in large-scale deployment of applications such as personal health records (PHRs). Robust and reliable forms of authentication are needed for PHRs, as the record will often contain sensitive and protected health information, including the patient's own annotations. Since the health care industry per se is unlikely to succeed at single-handedly developing and deploying a large scale, national authentication infrastructure, it makes sense to leverage existing hardware, software, and networks. This report proposes a new model for authentication of users to health care information applications, leveraging wireless mobile devices. Cell phones are widely distributed, have high user acceptance, and offer advanced security protocols. The authors propose harnessing this technology for the strong authentication of individuals by creating a registration authority and an authentication service, and examine the problems and promise of such a system. PMID:15684133

Wireless technology infrastructures for authentication of patients: PKI that rings.

PubMed

Sax, Ulrich; Kohane, Isaac; Mandl, Kenneth D

2005-01-01

As the public interest in consumer-driven electronic health care applications rises, so do concerns about the privacy and security of these applications. Achieving a balance between providing the necessary security while promoting user acceptance is a major obstacle in large-scale deployment of applications such as personal health records (PHRs). Robust and reliable forms of authentication are needed for PHRs, as the record will often contain sensitive and protected health information, including the patient's own annotations. Since the health care industry per se is unlikely to succeed at single-handedly developing and deploying a large scale, national authentication infrastructure, it makes sense to leverage existing hardware, software, and networks. This report proposes a new model for authentication of users to health care information applications, leveraging wireless mobile devices. Cell phones are widely distributed, have high user acceptance, and offer advanced security protocols. The authors propose harnessing this technology for the strong authentication of individuals by creating a registration authority and an authentication service, and examine the problems and promise of such a system.

Validation of large-scale, monochromatic UV disinfection systems for drinking water using dyed microspheres.

PubMed

Blatchley, E R; Shen, C; Scheible, O K; Robinson, J P; Ragheb, K; Bergstrom, D E; Rokjer, D

2008-02-01

Dyed microspheres have been developed as a new method for validation of ultraviolet (UV) reactor systems. When properly applied, dyed microspheres allow measurement of the UV dose distribution delivered by a photochemical reactor for a given operating condition. Prior to this research, dyed microspheres had only been applied to a bench-scale UV reactor. The goal of this research was to extend the application of dyed microspheres to large-scale reactors. Dyed microsphere tests were conducted on two prototype large-scale UV reactors at the UV Validation and Research Center of New York (UV Center) in Johnstown, NY. All microsphere tests were conducted under conditions that had been used previously in biodosimetry experiments involving two challenge bacteriophage: MS2 and Qbeta. Numerical simulations based on computational fluid dynamics and irradiance field modeling were also performed for the same set of operating conditions used in the microspheres assays. Microsphere tests on the first reactor illustrated difficulties in sample collection and discrimination of microspheres against ambient particles. Changes in sample collection and work-up were implemented in tests conducted on the second reactor that allowed for improvements in microsphere capture and discrimination against the background. Under these conditions, estimates of the UV dose distribution from the microspheres assay were consistent with numerical simulations and the results of biodosimetry, using both challenge organisms. The combined application of dyed microspheres, biodosimetry, and numerical simulation offers the potential to provide a more in-depth description of reactor performance than any of these methods individually, or in combination. This approach also has the potential to substantially reduce uncertainties in reactor validation, thereby leading to better understanding of reactor performance, improvements in reactor design, and decreases in reactor capital and operating costs.

Landscape-scale distribution and persistence of genetically modified oilseed rape (Brassica napus) in Manitoba, Canada.

PubMed

Knispel, Alexis L; McLachlan, Stéphane M

2010-01-01

Genetically modified herbicide-tolerant (GMHT) oilseed rape (OSR; Brassica napus L.) was approved for commercial cultivation in Canada in 1995 and currently represents over 95% of the OSR grown in western Canada. After a decade of widespread cultivation, GMHT volunteers represent an increasing management problem in cultivated fields and are ubiquitous in adjacent ruderal habitats, where they contribute to the spread of transgenes. However, few studies have considered escaped GMHT OSR populations in North America, and even fewer have been conducted at large spatial scales (i.e. landscape scales). In particular, the contribution of landscape structure and large-scale anthropogenic dispersal processes to the persistence and spread of escaped GMHT OSR remains poorly understood. We conducted a multi-year survey of the landscape-scale distribution of escaped OSR plants adjacent to roads and cultivated fields. Our objective was to examine the long-term dynamics of escaped OSR at large spatial scales and to assess the relative importance of landscape and localised factors to the persistence and spread of these plants outside of cultivation. From 2005 to 2007, we surveyed escaped OSR plants along roadsides and field edges at 12 locations in three agricultural landscapes in southern Manitoba where GMHT OSR is widely grown. Data were analysed to examine temporal changes at large spatial scales and to determine factors affecting the distribution of escaped OSR plants in roadside and field edge habitats within agricultural landscapes. Additionally, we assessed the potential for seed dispersal between escaped populations by comparing the relative spatial distribution of roadside and field edge OSR. Densities of escaped OSR fluctuated over space and time in both roadside and field edge habitats, though the proportion of GMHT plants was high (93-100%). Escaped OSR was positively affected by agricultural landscape (indicative of cropping intensity) and by the presence of an adjacent field planted to OSR. Within roadside habitats, escaped OSR was also strongly associated with large-scale variables, including road surface (indicative of traffic intensity) and distance to the nearest grain elevator. Conversely, within field edges, OSR density was affected by localised crop management practices such as mowing, soil disturbance and herbicide application. Despite the proximity of roadsides and field edges, there was little evidence of spatial aggregation among escaped OSR populations in these two habitats, especially at very fine spatial scales (i.e. <100 m), suggesting that natural propagule exchange is infrequent. Escaped OSR populations were persistent at large spatial and temporal scales, and low density in a given landscape or year was not indicative of overall extinction. As a result of ongoing cultivation and transport of OSR crops, escaped GMHT traits will likely remain predominant in agricultural landscapes. While escaped OSR in field edge habitats generally results from local seeding and management activities occurring at the field-scale, distribution patterns within roadside habitats are determined in large part by seed transport occurring at the landscape scale and at even larger regional scales. Our findings suggest that these large-scale anthropogenic dispersal processes are sufficient to enable persistence despite limited natural seed dispersal. This widespread dispersal is likely to undermine field-scale management practices aimed at eliminating escaped and in-field GMHT OSR populations. Agricultural transport and landscape-scale cropping patterns are important determinants of the distribution of escaped GM crops. At the regional level, these factors ensure ongoing establishment and spread of escaped GMHT OSR despite limited local seed dispersal. Escaped populations thus play an important role in the spread of transgenes and have substantial implications for the coexistence of GM and non-GM production systems. Given the large-scale factors driving the spread of escaped transgenes, localised co-existence measures may be impracticable where they are not commensurate with regional dispersal mechanisms. To be effective, strategies aimed at reducing contamination from GM crops should be multi-scale in approach and be developed and implemented at both farm and landscape levels of organisation. Multiple stakeholders should thus be consulted, including both GM and non-GM farmers, as well as seed developers, processors, transporters and suppliers. Decisions to adopt GM crops require thoughtful and inclusive consideration of the risks and responsibilities inherent in this new technology.

Access control and privacy in large distributed systems

NASA Technical Reports Server (NTRS)

Leiner, B. M.; Bishop, M.

1986-01-01

Large scale distributed systems consists of workstations, mainframe computers, supercomputers and other types of servers, all connected by a computer network. These systems are being used in a variety of applications including the support of collaborative scientific research. In such an environment, issues of access control and privacy arise. Access control is required for several reasons, including the protection of sensitive resources and cost control. Privacy is also required for similar reasons, including the protection of a researcher's proprietary results. A possible architecture for integrating available computer and communications security technologies into a system that meet these requirements is described. This architecture is meant as a starting point for discussion, rather that the final answer.

Towards Noise Tomography and Passive Monitoring Using Distributed Acoustic Sensing

NASA Astrophysics Data System (ADS)

Paitz, P.; Fichtner, A.

2017-12-01

Distributed Acoustic Sensing (DAS) has the potential to revolutionize the field of seismic data acquisition. Thanks to their cost-effectiveness, fiber-optic cables may have the capability of complementing conventional geophones and seismometers by filling a niche of applications utilizing large amounts of data. Therefore, DAS may serve as an additional tool to investigate the internal structure of the Earth and its changes over time; on scales ranging from hydrocarbon or geothermal reservoirs to the entire globe. An additional potential may be in the existence of large fibre networks deployed already for telecommunication purposes. These networks that already exist today could serve as distributed seismic antennas. We investigate theoretically how ambient noise tomography may be used with DAS data. For this we extend the theory of seismic interferometry to the measurement of strain. With numerical, 2D finite-difference examples we investigate the impact of source and receiver effects. We study the effect of heterogeneous source distributions and the cable orientation by assessing similarities and differences to the Green's function. We also compare the obtained interferometric waveforms from strain interferometry to displacement interferometric wave fields obtained with existing methods. Intermediate results show that the obtained interferometric waveforms can be connected to the Green's Functions and provide consistent information about the propagation medium. These simulations will be extended to reservoir scale subsurface structures. Future work will include the application of the theory to real-data examples. The presented research depicts the early stage of a combination of theoretical investigations, numerical simulations and real-world data applications. We will therefore evaluate the potentials and shortcomings of DAS in reservoir monitoring and seismology at the current state, with a long-term vision of global seismic tomography utilizing DAS data from existing fiber-optic cable networks.

Semihierarchical quantum repeaters based on moderate lifetime quantum memories

NASA Astrophysics Data System (ADS)

Liu, Xiao; Zhou, Zong-Quan; Hua, Yi-Lin; Li, Chuan-Feng; Guo, Guang-Can

2017-01-01

The construction of large-scale quantum networks relies on the development of practical quantum repeaters. Many approaches have been proposed with the goal of outperforming the direct transmission of photons, but most of them are inefficient or difficult to implement with current technology. Here, we present a protocol that uses a semihierarchical structure to improve the entanglement distribution rate while reducing the requirement of memory time to a range of tens of milliseconds. This protocol can be implemented with a fixed distance of elementary links and fixed requirements on quantum memories, which are independent of the total distance. This configuration is especially suitable for scalable applications in large-scale quantum networks.

Investigations of grain size dependent sediment transport phenomena on multiple scales

NASA Astrophysics Data System (ADS)

Thaxton, Christopher S.

Sediment transport processes in coastal and fluvial environments resulting from disturbances such as urbanization, mining, agriculture, military operations, and climatic change have significant impact on local, regional, and global environments. Primarily, these impacts include the erosion and deposition of sediment, channel network modification, reduction in downstream water quality, and the delivery of chemical contaminants. The scale and spatial distribution of these effects are largely attributable to the size distribution of the sediment grains that become eligible for transport. An improved understanding of advective and diffusive grain-size dependent sediment transport phenomena will lead to the development of more accurate predictive models and more effective control measures. To this end, three studies were performed that investigated grain-size dependent sediment transport on three different scales. Discrete particle computer simulations of sheet flow bedload transport on the scale of 0.1--100 millimeters were performed on a heterogeneous population of grains of various grain sizes. The relative transport rates and diffusivities of grains under both oscillatory and uniform, steady flow conditions were quantified. These findings suggest that boundary layer formalisms should describe surface roughness through a representative grain size that is functionally dependent on the applied flow parameters. On the scale of 1--10m, experiments were performed to quantify the hydrodynamics and sediment capture efficiency of various baffles installed in a sediment retention pond, a commonly used sedimentation control measure in watershed applications. Analysis indicates that an optimum sediment capture effectiveness may be achieved based on baffle permeability, pond geometry and flow rate. Finally, on the scale of 10--1,000m, a distributed, bivariate watershed terain evolution module was developed within GRASS GIS. Simulation results for variable grain sizes and for distributed rainfall infiltration and land cover matched observations. Although a unique set of governing equations applies to each scale, an improved physics-based understanding of small and medium scale behavior may yield more accurate parameterization of key variables used in large scale predictive models.

Detecting Potentially Compromised Credentials in a Large-Scale Production Single-Signon System

DTIC Science & Technology

2014-06-01

Attention Deficit Hyperactivity Disorder ( ADHD ), Post-Traumatic Stress Disorder (PTSD), anxiety, they are neurotic, and have memory issues. They... Deficit Hyperactivity Disorder API Application Programming Interface CAC Common Access Card CBL Composite Blocking List CDF Cumulative Distribution...Service Logons (DSLs) system . . . . . . . . . . . . . . . . 49 xi THIS PAGE INTENTIONALLY LEFT BLANK xii List of Acronyms and Abbreviations ADHD Attention

Large-scale P2P network based distributed virtual geographic environment (DVGE)

NASA Astrophysics Data System (ADS)

Tan, Xicheng; Yu, Liang; Bian, Fuling

2007-06-01

Virtual Geographic Environment has raised full concern as a kind of software information system that helps us understand and analyze the real geographic environment, and it has also expanded to application service system in distributed environment--distributed virtual geographic environment system (DVGE), and gets some achievements. However, limited by the factor of the mass data of VGE, the band width of network, as well as numerous requests and economic, etc. DVGE still faces some challenges and problems which directly cause the current DVGE could not provide the public with high-quality service under current network mode. The Rapid development of peer-to-peer network technology has offered new ideas of solutions to the current challenges and problems of DVGE. Peer-to-peer network technology is able to effectively release and search network resources so as to realize efficient share of information. Accordingly, this paper brings forth a research subject on Large-scale peer-to-peer network extension of DVGE as well as a deep study on network framework, routing mechanism, and DVGE data management on P2P network.

On the improvement for charging large-scale flexible electrostatic actuators

NASA Astrophysics Data System (ADS)

Liao, Hsu-Ching; Chen, Han-Long; Su, Yu-Hao; Chen, Yu-Chi; Ko, Wen-Ching; Liou, Chang-Ho; Wu, Wen-Jong; Lee, Chih-Kung

2011-04-01

Recently, the development of flexible electret based electrostatic actuator has been widely discussed. The devices was shown to have high sound quality, energy saving, flexible structure and can be cut to any shape. However, achieving uniform charge on the electret diaphragm is one of the most critical processes needed to have the speaker ready for large-scale production. In this paper, corona discharge equipment contains multi-corona probes and grid bias was set up to inject spatial charges within the electret diaphragm. The optimal multi-corona probes system was adjusted to achieve uniform charge distribution of electret diaphragm. The processing conditions include the distance between the corona probes, the voltages of corona probe and grid bias, etc. We assembled the flexible electret loudspeakers first and then measured their sound pressure and beam pattern. The uniform charge distribution within the electret diaphragm based flexible electret loudspeaker provided us with the opportunity to shape the loudspeaker arbitrarily and to tailor the sound distribution per specifications request. Some of the potential futuristic applications for this device such as sound poster, smart clothes, and sound wallpaper, etc. were discussed as well.

Lateral distribution of the radio signal in extensive air showers measured with LOPES

NASA Astrophysics Data System (ADS)

Apel, W. D.; Arteaga, J. C.; Asch, T.; Badea, A. F.; Bähren, L.; Bekk, K.; Bertaina, M.; Biermann, P. L.; Blümer, J.; Bozdog, H.; Brancus, I. M.; Brüggemann, M.; Buchholz, P.; Buitink, S.; Cantoni, E.; Chiavassa, A.; Cossavella, F.; Daumiller, K.; de Souza, V.; di Pierro, F.; Doll, P.; Engel, R.; Falcke, H.; Finger, M.; Fuhrmann, D.; Gemmeke, H.; Ghia, P. L.; Glasstetter, R.; Grupen, C.; Haungs, A.; Heck, D.; Hörandel, J. R.; Horneffer, A.; Huege, T.; Isar, P. G.; Kampert, K.-H.; Kang, D.; Kickelbick, D.; Krömer, O.; Kuijpers, J.; Lafebre, S.; Łuczak, P.; Ludwig, M.; Mathes, H. J.; Mayer, H. J.; Melissas, M.; Mitrica, B.; Morello, C.; Navarra, G.; Nehls, S.; Nigl, A.; Oehlschläger, J.; Over, S.; Palmieri, N.; Petcu, M.; Pierog, T.; Rautenberg, J.; Rebel, H.; Roth, M.; Saftoiu, A.; Schieler, H.; Schmidt, A.; Schröder, F.; Sima, O.; Singh, K.; Toma, G.; Trinchero, G. C.; Ulrich, H.; Weindl, A.; Wochele, J.; Wommer, M.; Zabierowski, J.; Zensus, J. A.; LOPES Collaboration

2010-01-01

The antenna array LOPES is set up at the location of the KASCADE-Grande extensive air shower experiment in Karlsruhe, Germany and aims to measure and investigate radio pulses from extensive air showers. The coincident measurements allow us to reconstruct the electric field strength at observation level in dependence of general EAS parameters. In the present work, the lateral distribution of the radio signal in air showers is studied in detail. It is found that the lateral distributions of the electric field strengths in individual EAS can be described by an exponential function. For about 20% of the events a flattening towards the shower axis is observed, preferentially for showers with large inclination angle. The estimated scale parameters R0, describing the slope of the lateral profiles range between 100 and 200 m. No evidence for a direct correlation of R0 with shower parameters like azimuth angle, geomagnetic angle, or primary energy can be found. This indicates that the lateral profile is an intrinsic property of the radio emission during the shower development which makes the radio detection technique suitable for large scale applications.

A rapid local singularity analysis algorithm with applications

NASA Astrophysics Data System (ADS)

Chen, Zhijun; Cheng, Qiuming; Agterberg, Frits

2015-04-01

The local singularity model developed by Cheng is fast gaining popularity in characterizing mineralization and detecting anomalies of geochemical, geophysical and remote sensing data. However in one of the conventional algorithms involving the moving average values with different scales is time-consuming especially while analyzing a large dataset. Summed area table (SAT), also called as integral image, is a fast algorithm used within the Viola-Jones object detection framework in computer vision area. Historically, the principle of SAT is well-known in the study of multi-dimensional probability distribution functions, namely in computing 2D (or ND) probabilities (area under the probability distribution) from the respective cumulative distribution functions. We introduce SAT and it's variation Rotated Summed Area Table in the isotropic, anisotropic or directional local singularity mapping in this study. Once computed using SAT, any one of the rectangular sum can be computed at any scale or location in constant time. The area for any rectangular region in the image can be computed by using only 4 array accesses in constant time independently of the size of the region; effectively reducing the time complexity from O(n) to O(1). New programs using Python, Julia, matlab and C++ are implemented respectively to satisfy different applications, especially to the big data analysis. Several large geochemical and remote sensing datasets are tested. A wide variety of scale changes (linear spacing or log spacing) for non-iterative or iterative approach are adopted to calculate the singularity index values and compare the results. The results indicate that the local singularity analysis with SAT is more robust and superior to traditional approach in identifying anomalies.

Squid - a simple bioinformatics grid.

PubMed

Carvalho, Paulo C; Glória, Rafael V; de Miranda, Antonio B; Degrave, Wim M

2005-08-03

BLAST is a widely used genetic research tool for analysis of similarity between nucleotide and protein sequences. This paper presents a software application entitled "Squid" that makes use of grid technology. The current version, as an example, is configured for BLAST applications, but adaptation for other computing intensive repetitive tasks can be easily accomplished in the open source version. This enables the allocation of remote resources to perform distributed computing, making large BLAST queries viable without the need of high-end computers. Most distributed computing / grid solutions have complex installation procedures requiring a computer specialist, or have limitations regarding operating systems. Squid is a multi-platform, open-source program designed to "keep things simple" while offering high-end computing power for large scale applications. Squid also has an efficient fault tolerance and crash recovery system against data loss, being able to re-route jobs upon node failure and recover even if the master machine fails. Our results show that a Squid application, working with N nodes and proper network resources, can process BLAST queries almost N times faster than if working with only one computer. Squid offers high-end computing, even for the non-specialist, and is freely available at the project web site. Its open-source and binary Windows distributions contain detailed instructions and a "plug-n-play" instalation containing a pre-configured example.

Redshift surveys

NASA Technical Reports Server (NTRS)

Geller, Margaret J.; Huchra, J. P.

1991-01-01

Present-day understanding of the large-scale galaxy distribution is reviewed. The statistics of the CfA redshift survey are briefly discussed. The need for deeper surveys to clarify the issues raised by recent studies of large-scale galactic distribution is addressed.

Augmented Reality 2.0

NASA Astrophysics Data System (ADS)

Schmalstieg, Dieter; Langlotz, Tobias; Billinghurst, Mark

Augmented Reality (AR) was first demonstrated in the 1960s, but only recently have technologies emerged that can be used to easily deploy AR applications to many users. Camera-equipped cell phones with significant processing power and graphics abilities provide an inexpensive and versatile platform for AR applications, while the social networking technology of Web 2.0 provides a large-scale infrastructure for collaboratively producing and distributing geo-referenced AR content. This combination of widely used mobile hardware and Web 2.0 software allows the development of a new type of AR platform that can be used on a global scale. In this paper we describe the Augmented Reality 2.0 concept and present existing work on mobile AR and web technologies that could be used to create AR 2.0 applications.

A Latency-Tolerant Partitioner for Distributed Computing on the Information Power Grid

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Harvey, Daniel J.; Biwas, Rupak; Kwak, Dochan (Technical Monitor)

2001-01-01

NASA's Information Power Grid (IPG) is an infrastructure designed to harness the power of graphically distributed computers, databases, and human expertise, in order to solve large-scale realistic computational problems. This type of a meta-computing environment is necessary to present a unified virtual machine to application developers that hides the intricacies of a highly heterogeneous environment and yet maintains adequate security. In this paper, we present a novel partitioning scheme. called MinEX, that dynamically balances processor workloads while minimizing data movement and runtime communication, for applications that are executed in a parallel distributed fashion on the IPG. We also analyze the conditions that are required for the IPG to be an effective tool for such distributed computations. Our results show that MinEX is a viable load balancer provided the nodes of the IPG are connected by a high-speed asynchronous interconnection network.

Large Scale Density Estimation of Blue and Fin Whales (LSD)

DTIC Science & Technology

2014-09-30

172. McDonald, MA, Hildebrand, JA, and Mesnick, S (2009). Worldwide decline in tonal frequencies of blue whale songs . Endangered Species Research 9...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...estimating blue and fin whale density that is effective over large spatial scales and is designed to cope with spatial variation in animal density utilizing

Framing Innovation: The Role of Distributed Leadership in Gaining Acceptance of Large-Scale Technology Initiatives

ERIC Educational Resources Information Center

Turner, Henry J.

2014-01-01

This dissertation of practice utilized a multiple case-study approach to examine distributed leadership within five school districts that were attempting to gain acceptance of a large-scale 1:1 technology initiative. Using frame theory and distributed leadership theory as theoretical frameworks, this study interviewed each district's…

Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

NASA Astrophysics Data System (ADS)

Maskey, M.; Ramachandran, R.; Miller, J.

2017-12-01

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

Responses of Cloud Type Distributions to the Large-Scale Dynamical Circulation: Water Budget-Related Dynamical Phase Space and Dynamical Regimes

NASA Technical Reports Server (NTRS)

Wong, Sun; Del Genio, Anthony; Wang, Tao; Kahn, Brian; Fetzer, Eric J.; L'Ecuyer, Tristan S.

2015-01-01

Goals: Water budget-related dynamical phase space; Connect large-scale dynamical conditions to atmospheric water budget (including precipitation); Connect atmospheric water budget to cloud type distributions.

Implications of the IRAS data for galactic gamma-ray astronomy and EGRET

NASA Technical Reports Server (NTRS)

Stecker, F. W.

1990-01-01

Using the results of gamma-ray, millimeter wave and far infrared surveys of the galaxy, one can derive a logically consistent picture of the large scale distribution of galactic gas and cosmic rays, one tied to the overall processes of stellar birth and destruction on a galactic scale. Using the results of the IRAS far-infrared survey of the galaxy, the large scale radial distribution of galactic far-infrared emission were obtained independently for both the Northern and Southern Hemisphere sides of the Galaxy. It was found that the dominant feature in these distributions to be a broad peak coincident with the 5 kpc molecular gas cloud ring. Also found was evidence of spiral arm features. Strong correlations are evident between the large scale galactic distributions of far infrared emission, gamma-ray emission and total CO emission. There is a particularly tight correlation between the distribution of warm molecular clouds and far-infrared emission on a galactic scale.

Large scale air pollution estimation method combining land use regression and chemical transport modeling in a geostatistical framework.

PubMed

Akita, Yasuyuki; Baldasano, Jose M; Beelen, Rob; Cirach, Marta; de Hoogh, Kees; Hoek, Gerard; Nieuwenhuijsen, Mark; Serre, Marc L; de Nazelle, Audrey

2014-04-15

In recognition that intraurban exposure gradients may be as large as between-city variations, recent air pollution epidemiologic studies have become increasingly interested in capturing within-city exposure gradients. In addition, because of the rapidly accumulating health data, recent studies also need to handle large study populations distributed over large geographic domains. Even though several modeling approaches have been introduced, a consistent modeling framework capturing within-city exposure variability and applicable to large geographic domains is still missing. To address these needs, we proposed a modeling framework based on the Bayesian Maximum Entropy method that integrates monitoring data and outputs from existing air quality models based on Land Use Regression (LUR) and Chemical Transport Models (CTM). The framework was applied to estimate the yearly average NO2 concentrations over the region of Catalunya in Spain. By jointly accounting for the global scale variability in the concentration from the output of CTM and the intraurban scale variability through LUR model output, the proposed framework outperformed more conventional approaches.

Identification of Curie temperature distributions in magnetic particulate systems

NASA Astrophysics Data System (ADS)

Waters, J.; Berger, A.; Kramer, D.; Fangohr, H.; Hovorka, O.

2017-09-01

This paper develops a methodology for extracting the Curie temperature distribution from magnetisation versus temperature measurements which are realizable by standard laboratory magnetometry. The method is integral in nature, robust against various sources of measurement noise, and can be adopted to a wide range of granular magnetic materials and magnetic particle systems. The validity and practicality of the method is demonstrated using large-scale Monte-Carlo simulations of an Ising-like model as a proof of concept, and general conclusions are drawn about its applicability to different classes of systems and experimental conditions.

Workflow based framework for life science informatics.

PubMed

Tiwari, Abhishek; Sekhar, Arvind K T

2007-10-01

Workflow technology is a generic mechanism to integrate diverse types of available resources (databases, servers, software applications and different services) which facilitate knowledge exchange within traditionally divergent fields such as molecular biology, clinical research, computational science, physics, chemistry and statistics. Researchers can easily incorporate and access diverse, distributed tools and data to develop their own research protocols for scientific analysis. Application of workflow technology has been reported in areas like drug discovery, genomics, large-scale gene expression analysis, proteomics, and system biology. In this article, we have discussed the existing workflow systems and the trends in applications of workflow based systems.

The distribution of free electrons in the inner galaxy from pulsar dispersion measures

NASA Technical Reports Server (NTRS)

Harding, D. S.; Harding, A. K.

1981-01-01

The dispersion measures of a sample of 149 pulsars in the inner Galaxy (absolute value of l 50 deg) were statistically analyzed to deduce the large-scale distribution of free thermal electrons in this region. The dispersion measure distribution of these pulsars shows significant evidence for a decrease in the electron scale height from a local value greater than the pulsar scale height to a value less than the pulsar scale height at galactocentric radii inside of approximately 7 kpc. An increase in the electron density (to a value around .15/cu cm at 4 to 5 kpc) must accompany such a decrease in scale height. There is also evidence for a large-scale warp in the electron distribution below the b + 0 deg plane inside the Solar circle. A model is proposed for the electron distribution which incorporates these features and Monte Carlo generated dispersion measure distributions are presented for parameters which best reproduce the observed pulsar distributions.

Formation of large-scale structure from cosmic strings and massive neutrinos

NASA Technical Reports Server (NTRS)

Scherrer, Robert J.; Melott, Adrian L.; Bertschinger, Edmund

1989-01-01

Numerical simulations of large-scale structure formation from cosmic strings and massive neutrinos are described. The linear power spectrum in this model resembles the cold-dark-matter power spectrum. Galaxy formation begins early, and the final distribution consists of isolated density peaks embedded in a smooth background, leading to a natural bias in the distribution of luminous matter. The distribution of clustered matter has a filamentary appearance with large voids.

A study of the viability of exploiting memory content similarity to improve resilience to memory errors

DOE PAGES

Levy, Scott; Ferreira, Kurt B.; Bridges, Patrick G.; ...

2014-12-09

Building the next-generation of extreme-scale distributed systems will require overcoming several challenges related to system resilience. As the number of processors in these systems grow, the failure rate increases proportionally. One of the most common sources of failure in large-scale systems is memory. In this paper, we propose a novel runtime for transparently exploiting memory content similarity to improve system resilience by reducing the rate at which memory errors lead to node failure. We evaluate the viability of this approach by examining memory snapshots collected from eight high-performance computing (HPC) applications and two important HPC operating systems. Based on themore » characteristics of the similarity uncovered, we conclude that our proposed approach shows promise for addressing system resilience in large-scale systems.« less

Investigating Darcy-scale assumptions by means of a multiphysics algorithm

NASA Astrophysics Data System (ADS)

Tomin, Pavel; Lunati, Ivan

2016-09-01

Multiphysics (or hybrid) algorithms, which couple Darcy and pore-scale descriptions of flow through porous media in a single numerical framework, are usually employed to decrease the computational cost of full pore-scale simulations or to increase the accuracy of pure Darcy-scale simulations when a simple macroscopic description breaks down. Despite the massive increase in available computational power, the application of these techniques remains limited to core-size problems and upscaling remains crucial for practical large-scale applications. In this context, the Hybrid Multiscale Finite Volume (HMsFV) method, which constructs the macroscopic (Darcy-scale) problem directly by numerical averaging of pore-scale flow, offers not only a flexible framework to efficiently deal with multiphysics problems, but also a tool to investigate the assumptions used to derive macroscopic models and to better understand the relationship between pore-scale quantities and the corresponding macroscale variables. Indeed, by direct comparison of the multiphysics solution with a reference pore-scale simulation, we can assess the validity of the closure assumptions inherent to the multiphysics algorithm and infer the consequences for macroscopic models at the Darcy scale. We show that the definition of the scale ratio based on the geometric properties of the porous medium is well justified only for single-phase flow, whereas in case of unstable multiphase flow the nonlinear interplay between different forces creates complex fluid patterns characterized by new spatial scales, which emerge dynamically and weaken the scale-separation assumption. In general, the multiphysics solution proves very robust even when the characteristic size of the fluid-distribution patterns is comparable with the observation length, provided that all relevant physical processes affecting the fluid distribution are considered. This suggests that macroscopic constitutive relationships (e.g., the relative permeability) should account for the fact that they depend not only on the saturation but also on the actual characteristics of the fluid distribution.

Intrapixel measurement techniques on large focal plane arrays for astronomical applications: a comparative study

NASA Astrophysics Data System (ADS)

Ketchazo, C.; Viale, T.; Boulade, O.; de la Barrière, F.; Dubreuil, D.; Mugnier, L.; Moreau, V.; Guérineau, N.; Mulet, P.; Druart, G.; Delisle, C.

2017-09-01

The intrapixel response is the signal detected by a single pixel illuminated by a Dirac distribution as a function of the position of this Dirac inside this pixel. It is also known as the pixel response function (PRF). This function measures the sensitivity variation at the subpixel scale and gives a spatial map of the sensitivity across a pixel.

Resurrecting hot dark matter - Large-scale structure from cosmic strings and massive neutrinos

NASA Technical Reports Server (NTRS)

Scherrer, Robert J.

1988-01-01

These are the results of a numerical simulation of the formation of large-scale structure from cosmic-string loops in a universe dominated by massive neutrinos (hot dark matter). This model has several desirable features. The final matter distribution contains isolated density peaks embedded in a smooth background, producing a natural bias in the distribution of luminous matter. Because baryons can accrete onto the cosmic strings before the neutrinos, the galaxies will have baryon cores and dark neutrino halos. Galaxy formation in this model begins much earlier than in random-phase models. On large scales the distribution of clustered matter visually resembles the CfA survey, with large voids and filaments.

Nonextensive Entropy Approach to Space Plasma Fluctuations and Turbulence

NASA Astrophysics Data System (ADS)

Leubner, M. P.; Vörös, Z.; Baumjohann, W.

Spatial intermittency in fully developed turbulence is an established feature of astrophysical plasma fluctuations and in particular apparent in the interplanetary medium by in situ observations. In this situation, the classical Boltzmann— Gibbs extensive thermo-statistics, applicable when microscopic interactions and memory are short ranged and the environment is a continuous and differentiable manifold, fails. Upon generalization of the entropy function to nonextensivity, accounting for long-range interactions and thus for correlations in the system, it is demonstrated that the corresponding probability distribution functions (PDFs) are members of a family of specific power-law distributions. In particular, the resulting theoretical bi-κ functional reproduces accurately the observed global leptokurtic, non-Gaussian shape of the increment PDFs of characteristic solar wind variables on all scales, where nonlocality in turbulence is controlled via a multiscale coupling parameter. Gradual decoupling is obtained by enhancing the spatial separation scale corresponding to increasing κ-values in case of slow solar wind conditions where a Gaussian is approached in the limit of large scales. Contrary, the scaling properties in the high speed solar wind are predominantly governed by the mean energy or variance of the distribution, appearing as second parameter in the theory. The PDFs of solar wind scalar field differences are computed from WIND and ACE data for different time-lags and bulk speeds and analyzed within the nonextensive theory, where also a particular nonlinear dependence of the coupling parameter and variance with scale arises for best fitting theoretical PDFs. Consequently, nonlocality in fluctuations, related to both, turbulence and its large scale driving, should be related to long-range interactions in the context of nonextensive entropy generalization, providing fundamentally the physical background of the observed scale dependence of fluctuations in intermittent space plasmas.

Domain-area distribution anomaly in segregating multicomponent superfluids

NASA Astrophysics Data System (ADS)

Takeuchi, Hiromitsu

2018-01-01

The domain-area distribution in the phase transition dynamics of Z2 symmetry breaking is studied theoretically and numerically for segregating binary Bose-Einstein condensates in quasi-two-dimensional systems. Due to the dynamic-scaling law of the phase ordering kinetics, the domain-area distribution is described by a universal function of the domain area, rescaled by the mean distance between domain walls. The scaling theory for general coarsening dynamics in two dimensions hypothesizes that the distribution during the coarsening dynamics has a hierarchy with the two scaling regimes, the microscopic and macroscopic regimes with distinct power-law exponents. The power law in the macroscopic regime, where the domain size is larger than the mean distance, is universally represented with the Fisher's exponent of the percolation theory in two dimensions. On the other hand, the power-law exponent in the microscopic regime is sensitive to the microscopic dynamics of the system. This conjecture is confirmed by large-scale numerical simulations of the coupled Gross-Pitaevskii equation for binary condensates. In the numerical experiments of the superfluid system, the exponent in the microscopic regime anomalously reaches to its theoretical upper limit of the general scaling theory. The anomaly comes from the quantum-fluid effect in the presence of circular vortex sheets, described by the hydrodynamic approximation neglecting the fluid compressibility. It is also found that the distribution of superfluid circulation along vortex sheets obeys a dynamic-scaling law with different power-law exponents in the two regimes. An analogy to quantum turbulence on the hierarchy of vorticity distribution and the applicability to chiral superfluid 3He in a slab are also discussed.

Distributed Fiber-Optic Sensors for Vibration Detection

PubMed Central

Liu, Xin; Jin, Baoquan; Bai, Qing; Wang, Yu; Wang, Dong; Wang, Yuncai

2016-01-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach–Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications. PMID:27472334

Distributed Fiber-Optic Sensors for Vibration Detection.

PubMed

Liu, Xin; Jin, Baoquan; Bai, Qing; Wang, Yu; Wang, Dong; Wang, Yuncai

2016-07-26

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach-Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications.

Multi-scale Material Appearance

NASA Astrophysics Data System (ADS)

Wu, Hongzhi

Modeling and rendering the appearance of materials is important for a diverse range of applications of computer graphics - from automobile design to movies and cultural heritage. The appearance of materials varies considerably at different scales, posing significant challenges due to the sheer complexity of the data, as well the need to maintain inter-scale consistency constraints. This thesis presents a series of studies around the modeling, rendering and editing of multi-scale material appearance. To efficiently render material appearance at multiple scales, we develop an object-space precomputed adaptive sampling method, which precomputes a hierarchy of view-independent points that preserve multi-level appearance. To support bi-scale material appearance design, we propose a novel reflectance filtering algorithm, which rapidly computes the large-scale appearance from small-scale details, by exploiting the low-rank structures of Bidirectional Visible Normal Distribution Functions and pre-rotated Bidirectional Reflectance Distribution Functions in the matrix formulation of the rendering algorithm. This approach can guide the physical realization of appearance, as well as the modeling of real-world materials using very sparse measurements. Finally, we present a bi-scale-inspired high-quality general representation for material appearance described by Bidirectional Texture Functions. Our representation is at once compact, easily editable, and amenable to efficient rendering.

Nowcasting Induced Seismicity at the Groningen Gas Field in the Netherlands

NASA Astrophysics Data System (ADS)

Luginbuhl, M.; Rundle, J. B.; Turcotte, D. L.

2017-12-01

The Groningen natural gas field in the Netherlands has recently been a topic of controversy for many residents in the surrounding area. The gas field provides energy for the majority of the country; however, for a minority of Dutch citizens who live nearby, the seismicity induced by the gas field is a cause for major concern. Since the early 2000's, the region has seen an increase in both number and magnitude of events, the largest of which was a magnitude 3.6 in 2012. Earthquakes of this size and smaller easily cause infrastructural damage to older houses and farms built with single brick walls. Nowcasting is a new method of statistically classifying seismicity and seismic risk. In this paper, the method is applied to the induced seismicity at the natural gas fields in Groningen, Netherlands. Nowcasting utilizes the catalogs of seismicity in these regions. Two earthquake magnitudes are selected, one large say , and one small say . The method utilizes the number of small earthquakes that occur between pairs of large earthquakes. The cumulative probability distribution of these values is obtained. The earthquake potential score (EPS) is defined by the number of small earthquakes that have occurred since the last large earthquake, the point where this number falls on the cumulative probability distribution of interevent counts defines the EPS. A major advantage of nowcasting is that it utilizes "natural time", earthquake counts, between events rather than clock time. Thus, it is not necessary to decluster aftershocks and the results are applicable if the level of induced seismicity varies in time, which it does in this case. The application of natural time to the accumulation of the seismic hazard depends on the applicability of Gutenberg-Richter (GR) scaling. The increasing number of small earthquakes that occur after a large earthquake can be scaled to give the risk of a large earthquake occurring. To illustrate our approach, we utilize the number of earthquakes in Groningen to nowcast the number of earthquakes in Groningen. The applicability of the scaling is illustrated during the rapid build up of seismicity between 2004 and 2016. It can now be used to forecast the expected reduction in seismicity associated with reduction in gas production.

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

Latency Hiding in Dynamic Partitioning and Load Balancing of Grid Computing Applications

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Harvey, Daniel J.; Biswas, Rupak

2001-01-01

The Information Power Grid (IPG) concept developed by NASA is aimed to provide a metacomputing platform for large-scale distributed computations, by hiding the intricacies of highly heterogeneous environment and yet maintaining adequate security. In this paper, we propose a latency-tolerant partitioning scheme that dynamically balances processor workloads on the.IPG, and minimizes data movement and runtime communication. By simulating an unsteady adaptive mesh application on a wide area network, we study the performance of our load balancer under the Globus environment. The number of IPG nodes, the number of processors per node, and the interconnected speeds are parameterized to derive conditions under which the IPG would be suitable for parallel distributed processing of such applications. Experimental results demonstrate that effective solution are achieved when the IPG nodes are connected by a high-speed asynchronous interconnection network.

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

Schauder, C.

This subcontract report was completed under the auspices of the NREL/SCE High-Penetration Photovoltaic (PV) Integration Project, which is co-funded by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) and the California Solar Initiative (CSI) Research, Development, Demonstration, and Deployment (RD&D) program funded by the California Public Utility Commission (CPUC) and managed by Itron. This project is focused on modeling, quantifying, and mitigating the impacts of large utility-scale PV systems (generally 1-5 MW in size) that are interconnected to the distribution system. This report discusses the concerns utilities have when interconnecting large PV systems thatmore » interconnect using PV inverters (a specific application of frequency converters). Additionally, a number of capabilities of PV inverters are described that could be implemented to mitigate the distribution system-level impacts of high-penetration PV integration. Finally, the main issues that need to be addressed to ease the interconnection of large PV systems to the distribution system are presented.« less

An Application of Hydraulic Tomography to a Large-Scale Fractured Granite Site, Mizunami, Japan.

PubMed

Zha, Yuanyuan; Yeh, Tian-Chyi J; Illman, Walter A; Tanaka, Tatsuya; Bruines, Patrick; Onoe, Hironori; Saegusa, Hiromitsu; Mao, Deqiang; Takeuchi, Shinji; Wen, Jet-Chau

2016-11-01

While hydraulic tomography (HT) is a mature aquifer characterization technology, its applications to characterize hydrogeology of kilometer-scale fault and fracture zones are rare. This paper sequentially analyzes datasets from two new pumping tests as well as those from two previous pumping tests analyzed by Illman et al. (2009) at a fractured granite site in Mizunami, Japan. Results of this analysis show that datasets from two previous pumping tests at one side of a fault zone as used in the previous study led to inaccurate mapping of fracture and fault zones. Inclusion of the datasets from the two new pumping tests (one of which was conducted on the other side of the fault) yields locations of the fault zone consistent with those based on geological mapping. The new datasets also produce a detailed image of the irregular fault zone, which is not available from geological investigation alone and the previous study. As a result, we conclude that if prior knowledge about geological structures at a field site is considered during the design of HT surveys, valuable non-redundant datasets about the fracture and fault zones can be collected. Only with these non-redundant data sets, can HT then be a viable and robust tool for delineating fracture and fault distributions over kilometer scales, even when only a limited number of boreholes are available. In essence, this paper proves that HT is a new tool for geologists, geophysicists, and engineers for mapping large-scale fracture and fault zone distributions. © 2016, National Ground Water Association.

Performance of a Heterogeneous Grid Partitioner for N-body Applications

NASA Technical Reports Server (NTRS)

Harvey, Daniel J.; Das, Sajal K.; Biswas, Rupak

2003-01-01

An important characteristic of distributed grids is that they allow geographically separated multicomputers to be tied together in a transparent virtual environment to solve large-scale computational problems. However, many of these applications require effective runtime load balancing for the resulting solutions to be viable. Recently, we developed a latency tolerant partitioner, called MinEX, specifically for use in distributed grid environments. This paper compares the performance of MinEX to that of METIS, a popular multilevel family of partitioners, using simulated heterogeneous grid configurations. A solver for the classical N-body problem is implemented to provide a framework for the comparisons. Experimental results show that MinEX provides superior quality partitions while being competitive to METIS in speed of execution.

Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts.

PubMed

Bellamy, Chloe; Altringham, John

2015-01-01

Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m - 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the potential to become a standard tool for supporting landscape-scale decision-making as relevant data and open source, user-friendly, and peer-reviewed software become widely available.

Modeling relief demands in an emergency supply chain system under large-scale disasters based on a queuing network.

PubMed

He, Xinhua; Hu, Wenfa

2014-01-01

This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model.

Modeling Relief Demands in an Emergency Supply Chain System under Large-Scale Disasters Based on a Queuing Network

PubMed Central

He, Xinhua

2014-01-01

This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

PubMed

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Scaling Irregular Applications through Data Aggregation and Software Multithreading

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

Morari, Alessandro; Tumeo, Antonino; Chavarría-Miranda, Daniel

Bioinformatics, data analytics, semantic databases, knowledge discovery are emerging high performance application areas that exploit dynamic, linked data structures such as graphs, unbalanced trees or unstructured grids. These data structures usually are very large, requiring significantly more memory than available on single shared memory systems. Additionally, these data structures are difficult to partition on distributed memory systems. They also present poor spatial and temporal locality, thus generating unpredictable memory and network accesses. The Partitioned Global Address Space (PGAS) programming model seems suitable for these applications, because it allows using a shared memory abstraction across distributed-memory clusters. However, current PGAS languagesmore » and libraries are built to target regular remote data accesses and block transfers. Furthermore, they usually rely on the Single Program Multiple Data (SPMD) parallel control model, which is not well suited to the fine grained, dynamic and unbalanced parallelism of irregular applications. In this paper we present {\\bf GMT} (Global Memory and Threading library), a custom runtime library that enables efficient execution of irregular applications on commodity clusters. GMT integrates a PGAS data substrate with simple fork/join parallelism and provides automatic load balancing on a per node basis. It implements multi-level aggregation and lightweight multithreading to maximize memory and network bandwidth with fine-grained data accesses and tolerate long data access latencies. A key innovation in the GMT runtime is its thread specialization (workers, helpers and communication threads) that realize the overall functionality. We compare our approach with other PGAS models, such as UPC running using GASNet, and hand-optimized MPI code on a set of typical large-scale irregular applications, demonstrating speedups of an order of magnitude.« less

Possibility of the market expansion of large capacity optical cold archive

NASA Astrophysics Data System (ADS)

Matsumoto, Ikuo; Sakata, Emiko

2017-08-01

The field, IoT and Big data, which is activated by the revolution of ICT, has caused rapid increase of distribution data of various business application. As a result, data with low access frequency has been rapidly increasing into a huge scale that human has never experienced before. This data with low access frequency is called "cold data", and the storage for cold data is called "cold storage". In this situation, the specifications of storage including access frequency, response speed and cost is determined by the application's request.

A Weibull distribution accrual failure detector for cloud computing.

PubMed

Liu, Jiaxi; Wu, Zhibo; Wu, Jin; Dong, Jian; Zhao, Yao; Wen, Dongxin

2017-01-01

Failure detectors are used to build high availability distributed systems as the fundamental component. To meet the requirement of a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. However, several implementations of accrual failure detectors do not adapt well to the cloud service environment. To solve this problem, a new accrual failure detector based on Weibull Distribution, called the Weibull Distribution Failure Detector, has been proposed specifically for cloud computing. It can adapt to the dynamic and unexpected network conditions in cloud computing. The performance of the Weibull Distribution Failure Detector is evaluated and compared based on public classical experiment data and cloud computing experiment data. The results show that the Weibull Distribution Failure Detector has better performance in terms of speed and accuracy in unstable scenarios, especially in cloud computing.

Spatial distribution of GRBs and large scale structure of the Universe

NASA Astrophysics Data System (ADS)

Bagoly, Zsolt; Rácz, István I.; Balázs, Lajos G.; Tóth, L. Viktor; Horváth, István

We studied the space distribution of the starburst galaxies from Millennium XXL database at z = 0.82. We examined the starburst distribution in the classical Millennium I (De Lucia et al. (2006)) using a semi-analytical model for the genesis of the galaxies. We simulated a starburst galaxies sample with Markov Chain Monte Carlo method. The connection between the large scale structures homogenous and starburst groups distribution (Kofman and Shandarin 1998), Suhhonenko et al. (2011), Liivamägi et al. (2012), Park et al. (2012), Horvath et al. (2014), Horvath et al. (2015)) on a defined scale were checked too.

The large-scale distribution of galaxies

NASA Technical Reports Server (NTRS)

Geller, Margaret J.

1989-01-01

The spatial distribution of galaxies in the universe is characterized on the basis of the six completed strips of the Harvard-Smithsonian Center for Astrophysics redshift-survey extension. The design of the survey is briefly reviewed, and the results are presented graphically. Vast low-density voids similar to the void in Bootes are found, almost completely surrounded by thin sheets of galaxies. Also discussed are the implications of the results for the survey sampling problem, the two-point correlation function of the galaxy distribution, the possibility of detecting large-scale coherent flows, theoretical models of large-scale structure, and the identification of groups and clusters of galaxies.

The Applications of Model-Based Geostatistics in Helminth Epidemiology and Control

PubMed Central

Magalhães, Ricardo J. Soares; Clements, Archie C.A.; Patil, Anand P.; Gething, Peter W.; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. PMID:21295680

Performance of intraclass correlation coefficient (ICC) as a reliability index under various distributions in scale reliability studies.

PubMed

Mehta, Shraddha; Bastero-Caballero, Rowena F; Sun, Yijun; Zhu, Ray; Murphy, Diane K; Hardas, Bhushan; Koch, Gary

2018-04-29

Many published scale validation studies determine inter-rater reliability using the intra-class correlation coefficient (ICC). However, the use of this statistic must consider its advantages, limitations, and applicability. This paper evaluates how interaction of subject distribution, sample size, and levels of rater disagreement affects ICC and provides an approach for obtaining relevant ICC estimates under suboptimal conditions. Simulation results suggest that for a fixed number of subjects, ICC from the convex distribution is smaller than ICC for the uniform distribution, which in turn is smaller than ICC for the concave distribution. The variance component estimates also show that the dissimilarity of ICC among distributions is attributed to the study design (ie, distribution of subjects) component of subject variability and not the scale quality component of rater error variability. The dependency of ICC on the distribution of subjects makes it difficult to compare results across reliability studies. Hence, it is proposed that reliability studies should be designed using a uniform distribution of subjects because of the standardization it provides for representing objective disagreement. In the absence of uniform distribution, a sampling method is proposed to reduce the non-uniformity. In addition, as expected, high levels of disagreement result in low ICC, and when the type of distribution is fixed, any increase in the number of subjects beyond a moderately large specification such as n = 80 does not have a major impact on ICC. Copyright © 2018 John Wiley & Sons, Ltd.

Applications of picosecond lasers and pulse-bursts in precision manufacturing

NASA Astrophysics Data System (ADS)

Knappe, Ralf

2012-03-01

Just as CW and quasi-CW lasers have revolutionized the materials processing world, picosecond lasers are poised to change the world of micromachining, where lasers outperform mechanical tools due to their flexibility, reliability, reproducibility, ease of programming, and lack of mechanical force or contamination to the part. Picosecond lasers are established as powerful tools for micromachining. Industrial processes like micro drilling, surface structuring and thin film ablation benefit from a process, which provides highest precision and minimal thermal impact for all materials. Applications such as microelectronics, semiconductor, and photovoltaic industries use picosecond lasers for maximum quality, flexibility, and cost efficiency. The range of parts, manufactured with ps lasers spans from microscopic diamond tools over large printing cylinders with square feet of structured surface. Cutting glass for display and PV is a large application, as well. With a smart distribution of energy into groups of ps-pulses at ns-scale separation (known as burst mode) ablation rates can be increased by one order of magnitude or more for some materials, also providing a better surface quality under certain conditions. The paper reports on the latest results of the laser technology, scaling of ablation rates, and various applications in ps-laser micromachining.

A Functional Model for Management of Large Scale Assessments.

ERIC Educational Resources Information Center

Banta, Trudy W.; And Others

This functional model for managing large-scale program evaluations was developed and validated in connection with the assessment of Tennessee's Nutrition Education and Training Program. Management of such a large-scale assessment requires the development of a structure for the organization; distribution and recovery of large quantities of…

Deformation of leaky-dielectric fluid globules under strong electric fields: Boundary layers and jets at large Reynolds numbers

NASA Astrophysics Data System (ADS)

Schnitzer, Ory; Frankel, Itzchak; Yariv, Ehud

2013-11-01

In Taylor's theory of electrohydrodynamic drop deformation (Proc. R. Soc. Lond. A, vol. 291, 1966, pp. 159-166), inertia is neglected at the outset, resulting in fluid velocity that scales as the square of the applied-field magnitude. For large drops, with increasing field strength the Reynolds number predicted by this scaling may actually become large, suggesting the need for a complementary large-Reynolds-number investigation. Balancing viscous stresses and electrical shear forces in this limit reveals a different velocity scaling, with the 4/3-power of the applied-field magnitude. We focus here on the flow over a gas bubble. It is essentially confined to two boundary layers propagating from the poles to the equator, where they collide to form a radial jet. At leading order in the Capillary number, the bubble deforms due to (i) Maxwell stresses; (ii) the hydrodynamic boundary-layer pressure associated with centripetal acceleration; and (iii) the intense pressure distribution acting over the narrow equatorial deflection zone, appearing as a concentrated load. Remarkably, the unique flow topology and associated scalings allow to obtain a closed-form expression for this deformation through application of integral mass and momentum balances. On the bubble scale, the concentrated pressure load is manifested in the appearance of a non-smooth equatorial dimple.

Space Flight Middleware: Remote AMS over DTN for Delay-Tolerant Messaging

NASA Technical Reports Server (NTRS)

Burleigh, Scott

2011-01-01

This paper describes a technique for implementing scalable, reliable, multi-source multipoint data distribution in space flight communications -- Delay-Tolerant Reliable Multicast (DTRM) -- that is fully supported by the "Remote AMS" (RAMS) protocol of the Asynchronous Message Service (AMS) proposed for standardization within the Consultative Committee for Space Data Systems (CCSDS). The DTRM architecture enables applications to easily "publish" messages that will be reliably and efficiently delivered to an arbitrary number of "subscribing" applications residing anywhere in the space network, whether in the same subnet or in a subnet on a remote planet or vehicle separated by many light minutes of interplanetary space. The architecture comprises multiple levels of protocol, each included for a specific purpose and allocated specific responsibilities: "application AMS" traffic performs end-system data introduction and delivery subject to access control; underlying "remote AMS" directs this application traffic to populations of recipients at remote locations in a multicast distribution tree, enabling the architecture to scale up to large networks; further underlying Delay-Tolerant Networking (DTN) Bundle Protocol (BP) advances RAMS protocol data units through the distribution tree using delay-tolerant storeand- forward methods; and further underlying reliable "convergence-layer" protocols ensure successful data transfer over each segment of the end-to-end route. The result is scalable, reliable, delay-tolerant multi-source multicast that is largely self-configuring.

Ecological niche modeling as a new paradigm for large-scale investigations of diversity and distribution of birds

Treesearch

A. Townsend Peterson; Daniel A. Kluza

2005-01-01

Large-scale assessments of the distribution and diversity of birds have been challenged by the need for a robust methodology for summarizing or predicting species' geographic distributions (e.g. Beard et al. 1999, Manel et al. 1999, Saveraid et al. 2001). Methodologies used in such studies have at times been inappropriate, or even more frequently limited in their...

Influence of savanna fire on Australian monsoon season precipitation and circulation as simulated using a distributed computing environment

NASA Astrophysics Data System (ADS)

Lynch, Amanda H.; Abramson, David; Görgen, Klaus; Beringer, Jason; Uotila, Petteri

2007-10-01

Fires in the Australian savanna have been hypothesized to affect monsoon evolution, but the hypothesis is controversial and the effects have not been quantified. A distributed computing approach allows the development of a challenging experimental design that permits simultaneous variation of all fire attributes. The climate model simulations are distributed around multiple independent computer clusters in six countries, an approach that has potential for a range of other large simulation applications in the earth sciences. The experiment clarifies that savanna burning can shape the monsoon through two mechanisms. Boundary-layer circulation and large-scale convergence is intensified monotonically through increasing fire intensity and area burned. However, thresholds of fire timing and area are evident in the consequent influence on monsoon rainfall. In the optimal band of late, high intensity fires with a somewhat limited extent, it is possible for the wet season to be significantly enhanced.

Numerical Simulations of Vortical Mode Stirring: Effects of Large Scale Shear and Strain

DTIC Science & Technology

2015-09-30

Numerical Simulations of Vortical Mode Stirring: Effects of Large-Scale Shear and Strain M.-Pascale Lelong NorthWest Research Associates...can be implemented in larger-scale ocean models. These parameterizations will incorporate the effects of local ambient conditions including latitude...talk at the 1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Nonlinear Effects in Internal Waves Conference held

Miniaturized integration of a fluorescence microscope

PubMed Central

Ghosh, Kunal K.; Burns, Laurie D.; Cocker, Eric D.; Nimmerjahn, Axel; Ziv, Yaniv; Gamal, Abbas El; Schnitzer, Mark J.

2013-01-01

The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals towards relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including semiconductor light source and sensor. This device enables high-speed cellular-level imaging across ∼0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens. PMID:21909102

Miniaturized integration of a fluorescence microscope.

PubMed

Ghosh, Kunal K; Burns, Laurie D; Cocker, Eric D; Nimmerjahn, Axel; Ziv, Yaniv; Gamal, Abbas El; Schnitzer, Mark J

2011-09-11

The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals for relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including a semiconductor light source and sensor. This device enables high-speed cellular imaging across ∼0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens.

Improving Air Quality (and Weather) Predictions using Advanced Data Assimilation Techniques Applied to Coupled Models during KORUS-AQ

NASA Astrophysics Data System (ADS)

Carmichael, G. R.; Saide, P. E.; Gao, M.; Streets, D. G.; Kim, J.; Woo, J. H.

2017-12-01

Ambient aerosols are important air pollutants with direct impacts on human health and on the Earth's weather and climate systems through their interactions with radiation and clouds. Their role is dependent on their distributions of size, number, phase and composition, which vary significantly in space and time. There remain large uncertainties in simulated aerosol distributions due to uncertainties in emission estimates and in chemical and physical processes associated with their formation and removal. These uncertainties lead to large uncertainties in weather and air quality predictions and in estimates of health and climate change impacts. Despite these uncertainties and challenges, regional-scale coupled chemistry-meteorological models such as WRF-Chem have significant capabilities in predicting aerosol distributions and explaining aerosol-weather interactions. We explore the hypothesis that new advances in on-line, coupled atmospheric chemistry/meteorological models, and new emission inversion and data assimilation techniques applicable to such coupled models, can be applied in innovative ways using current and evolving observation systems to improve predictions of aerosol distributions at regional scales. We investigate the impacts of assimilating AOD from geostationary satellite (GOCI) and surface PM2.5 measurements on predictions of AOD and PM in Korea during KORUS-AQ through a series of experiments. The results suggest assimilating datasets from multiple platforms can improve the predictions of aerosol temporal and spatial distributions.

A case for ZnO nanowire field emitter arrays in advanced x-ray source applications

NASA Astrophysics Data System (ADS)

Robinson, Vance S.; Bergkvist, Magnus; Chen, Daokun; Chen, Jun; Huang, Mengbing

2016-09-01

Reviewing current efforts in X-ray source miniaturization reveals a broad spectrum of applications: Portable and/or remote nondestructive evaluation, high throughput protein crystallography, invasive radiotherapy, monitoring fluid flow and particulate generation in situ, and portable radiography devices for battle-front or large scale disaster triage scenarios. For the most part, all of these applications are being addressed with a top-down approach aimed at improving portability, weight and size. That is, the existing system or a critical sub-component is shrunk in some manner in order to miniaturize the overall package. In parallel to top-down x-ray source miniaturization, more recent efforts leverage field emission and semiconductor device fabrication techniques to achieve small scale x-ray sources via a bottom-up approach where phenomena effective at a micro/nanoscale are coordinated for macro-scale effect. The bottom-up approach holds potential to address all the applications previously mentioned but its entitlement extends into new applications with much more ground-breaking potential. One such bottom-up application is the distributed x-ray source platform. In the medical space, using an array of microscale x-ray sources instead of a single source promises significant reductions in patient dose as well as smaller feature detectability and fewer image artifacts. Cold cathode field emitters are ideal for this application because they can be gated electrostatically or via photonic excitation, they do not generate excessive heat like other common electron emitters, they have higher brightness and they are relatively compact. This document describes how ZnO nanowire field emitter arrays are well suited for distributed x-ray source applications because they hold promise in each of the following critical areas: emission stability, simple scalable fabrication, performance, radiation resistance and photonic coupling.

Porting the AVS/Express scientific visualization software to Cray XT4.

PubMed

Leaver, George W; Turner, Martin J; Perrin, James S; Mummery, Paul M; Withers, Philip J

2011-08-28

Remote scientific visualization, where rendering services are provided by larger scale systems than are available on the desktop, is becoming increasingly important as dataset sizes increase beyond the capabilities of desktop workstations. Uptake of such services relies on access to suitable visualization applications and the ability to view the resulting visualization in a convenient form. We consider five rules from the e-Science community to meet these goals with the porting of a commercial visualization package to a large-scale system. The application uses message-passing interface (MPI) to distribute data among data processing and rendering processes. The use of MPI in such an interactive application is not compatible with restrictions imposed by the Cray system being considered. We present details, and performance analysis, of a new MPI proxy method that allows the application to run within the Cray environment yet still support MPI communication required by the application. Example use cases from materials science are considered.

Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

NASA Technical Reports Server (NTRS)

Avissar, Roni; Chen, Fei

1993-01-01

Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes generated by such subgrid-scale landscape discontinuities in large-scale atmospheric models.

Coupling a basin erosion and river sediment transport model into a large scale hydrological model: an application in the Amazon basin

NASA Astrophysics Data System (ADS)

Buarque, D. C.; Collischonn, W.; Paiva, R. C. D.

2012-04-01

This study presents the first application and preliminary results of the large scale hydrodynamic/hydrological model MGB-IPH with a new module to predict the spatial distribution of the basin erosion and river sediment transport in a daily time step. The MGB-IPH is a large-scale, distributed and process based hydrological model that uses a catchment based discretization and the Hydrological Response Units (HRU) approach. It uses physical based equations to simulate the hydrological processes, such as the Penman Monteith model for evapotranspiration, and uses the Muskingum Cunge approach and a full 1D hydrodynamic model for river routing; including backwater effects and seasonal flooding. The sediment module of the MGB-IPH model is divided into two components: 1) prediction of erosion over the basin and sediment yield to river network; 2) sediment transport along the river channels. Both MGB-IPH and the sediment module use GIS tools to display relevant maps and to extract parameters from SRTM DEM (a 15" resolution was adopted). Using the catchment discretization the sediment module applies the Modified Universal Soil Loss Equation to predict soil loss from each HRU considering three sediment classes defined according to the soil texture: sand, silt and clay. The effects of topography on soil erosion are estimated by a two-dimensional slope length (LS) factor which using the contributing area approach and a local slope steepness (S), both estimated for each DEM pixel using GIS algorithms. The amount of sediment releasing to the catchment river reach in each day is calculated using a linear reservoir. Once the sediment reaches the river they are transported into the river channel using an advection equation for silt and clay and a sediment continuity equation for sand. A sediment balance based on the Yang sediment transport capacity, allowing to compute the amount of erosion and deposition along the rivers, is performed for sand particles as bed load, whilst no erosion or deposition is allowed for silt and clay. The model was first applied on the Madeira River basin, one of the major tributaries of the Amazon River (~1.4*106 km2) accounting for 35% of the suspended sediment amount annually transported for the Amazon river to the ocean. Model results agree with observed data, mainly for monthly and annual time scales. The spatial distribution of soil erosion within the basin showed a large amount of sediment being delivered from the Andean regions of Bolivia and Peru. Spatial distribution of mean annual sediment along the river showed that Madre de Dios, Mamoré and Beni rivers transport the major amount of sediment. Simulated daily suspended solid discharge agree with observed data. The model is able to provide temporaly and spatialy distributed estimates of soil loss source over the basin, locations with tendency for erosion or deposition along the rivers, and to reproduce long term sediment yield at several locations. Despite model results are encouraging, further effort is needed to validate the model considering the scarcity of data at large scale.

Simulating statistics of lightning-induced and man made fires

NASA Astrophysics Data System (ADS)

Krenn, R.; Hergarten, S.

2009-04-01

The frequency-area distributions of forest fires show power-law behavior with scaling exponents α in a quite narrow range, relating wildfire research to the theoretical framework of self-organized criticality. Examples of self-organized critical behavior can be found in computer simulations of simple cellular automata. The established self-organized critical Drossel-Schwabl forest fire model (DS-FFM) is one of the most widespread models in this context. Despite its qualitative agreement with event-size statistics from nature, its applicability is still questioned. Apart from general concerns that the DS-FFM apparently oversimplifies the complex nature of forest dynamics, it significantly overestimates the frequency of large fires. We present a straightforward modification of the model rules that increases the scaling exponent α by approximately 1•3 and brings the simulated event-size statistics close to those observed in nature. In addition, combined simulations of both the original and the modified model predict a dependence of the overall distribution on the ratio of lightning induced and man made fires as well as a difference between their respective event-size statistics. The increase of the scaling exponent with decreasing lightning probability as well as the splitting of the partial distributions are confirmed by the analysis of the Canadian Large Fire Database. As a consequence, lightning induced and man made forest fires cannot be treated separately in wildfire modeling, hazard assessment and forest management.

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

Friar, James Lewis; Goldman, Terrance J.; Pérez-Mercader, J.

In this paper, we apply the Law of Total Probability to the construction of scale-invariant probability distribution functions (pdf's), and require that probability measures be dimensionless and unitless under a continuous change of scales. If the scale-change distribution function is scale invariant then the constructed distribution will also be scale invariant. Repeated application of this construction on an arbitrary set of (normalizable) pdf's results again in scale-invariant distributions. The invariant function of this procedure is given uniquely by the reciprocal distribution, suggesting a kind of universality. Finally, we separately demonstrate that the reciprocal distribution results uniquely from requiring maximum entropymore » for size-class distributions with uniform bin sizes.« less

Distributions of the Kullback-Leibler divergence with applications.

PubMed

Belov, Dmitry I; Armstrong, Ronald D

2011-05-01

The Kullback-Leibler divergence (KLD) is a widely used method for measuring the fit of two distributions. In general, the distribution of the KLD is unknown. Under reasonable assumptions, common in psychometrics, the distribution of the KLD is shown to be asymptotically distributed as a scaled (non-central) chi-square with one degree of freedom or a scaled (doubly non-central) F. Applications of the KLD for detecting heterogeneous response data are discussed with particular emphasis on test security. © The British Psychological Society.

Large-scale additive manufacturing with bioinspired cellulosic materials.

PubMed

Sanandiya, Naresh D; Vijay, Yadunund; Dimopoulou, Marina; Dritsas, Stylianos; Fernandez, Javier G

2018-06-05

Cellulose is the most abundant and broadly distributed organic compound and industrial by-product on Earth. However, despite decades of extensive research, the bottom-up use of cellulose to fabricate 3D objects is still plagued with problems that restrict its practical applications: derivatives with vast polluting effects, use in combination with plastics, lack of scalability and high production cost. Here we demonstrate the general use of cellulose to manufacture large 3D objects. Our approach diverges from the common association of cellulose with green plants and it is inspired by the wall of the fungus-like oomycetes, which is reproduced introducing small amounts of chitin between cellulose fibers. The resulting fungal-like adhesive material(s) (FLAM) are strong, lightweight and inexpensive, and can be molded or processed using woodworking techniques. We believe this first large-scale additive manufacture with ubiquitous biological polymers will be the catalyst for the transition to environmentally benign and circular manufacturing models.

Large-scale structure non-Gaussianities with modal methods

NASA Astrophysics Data System (ADS)

Schmittfull, Marcel

2016-10-01

Relying on a separable modal expansion of the bispectrum, the implementation of a fast estimator for the full bispectrum of a 3d particle distribution is presented. The computational cost of accurate bispectrum estimation is negligible relative to simulation evolution, so the bispectrum can be used as a standard diagnostic whenever the power spectrum is evaluated. As an application, the time evolution of gravitational and primordial dark matter bispectra was measured in a large suite of N-body simulations. The bispectrum shape changes characteristically when the cosmic web becomes dominated by filaments and halos, therefore providing a quantitative probe of 3d structure formation. Our measured bispectra are determined by ~ 50 coefficients, which can be used as fitting formulae in the nonlinear regime and for non-Gaussian initial conditions. We also compare the measured bispectra with predictions from the Effective Field Theory of Large Scale Structures (EFTofLSS).

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

NASA Technical Reports Server (NTRS)

Ott, L.; Pawson, S.; Zhu, Z.; Nielsen, J. E.; Collatz, G. J.; Gregg, W. W.

2012-01-01

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Supervised Outlier Detection in Large-Scale Mvs Point Clouds for 3d City Modeling Applications

NASA Astrophysics Data System (ADS)

Stucker, C.; Richard, A.; Wegner, J. D.; Schindler, K.

2018-05-01

We propose to use a discriminative classifier for outlier detection in large-scale point clouds of cities generated via multi-view stereo (MVS) from densely acquired images. What makes outlier removal hard are varying distributions of inliers and outliers across a scene. Heuristic outlier removal using a specific feature that encodes point distribution often delivers unsatisfying results. Although most outliers can be identified correctly (high recall), many inliers are erroneously removed (low precision), too. This aggravates object 3D reconstruction due to missing data. We thus propose to discriminatively learn class-specific distributions directly from the data to achieve high precision. We apply a standard Random Forest classifier that infers a binary label (inlier or outlier) for each 3D point in the raw, unfiltered point cloud and test two approaches for training. In the first, non-semantic approach, features are extracted without considering the semantic interpretation of the 3D points. The trained model approximates the average distribution of inliers and outliers across all semantic classes. Second, semantic interpretation is incorporated into the learning process, i.e. we train separate inlieroutlier classifiers per semantic class (building facades, roof, ground, vegetation, fields, and water). Performance of learned filtering is evaluated on several large SfM point clouds of cities. We find that results confirm our underlying assumption that discriminatively learning inlier-outlier distributions does improve precision over global heuristics by up to ≍ 12 percent points. Moreover, semantically informed filtering that models class-specific distributions further improves precision by up to ≍ 10 percent points, being able to remove very isolated building, roof, and water points while preserving inliers on building facades and vegetation.

A Comparative Study of Point Cloud Data Collection and Processing

NASA Astrophysics Data System (ADS)

Pippin, J. E.; Matheney, M.; Gentle, J. N., Jr.; Pierce, S. A.; Fuentes-Pineda, G.

2016-12-01

Over the past decade, there has been dramatic growth in the acquisition of publicly funded high-resolution topographic data for scientific, environmental, engineering and planning purposes. These data sets are valuable for applications of interest across a large and varied user community. However, because of the large volumes of data produced by high-resolution mapping technologies and expense of aerial data collection, it is often difficult to collect and distribute these datasets. Furthermore, the data can be technically challenging to process, requiring software and computing resources not readily available to many users. This study presents a comparison of advanced computing hardware and software that is used to collect and process point cloud datasets, such as LIDAR scans. Activities included implementation and testing of open source libraries and applications for point cloud data processing such as, Meshlab, Blender, PDAL, and PCL. Additionally, a suite of commercial scale applications, Skanect and Cloudcompare, were applied to raw datasets. Handheld hardware solutions, a Structure Scanner and Xbox 360 Kinect V1, were tested for their ability to scan at three field locations. The resultant data projects successfully scanned and processed subsurface karst features ranging from small stalactites to large rooms, as well as a surface waterfall feature. Outcomes support the feasibility of rapid sensing in 3D at field scales.

Multi-level structure in the large scale distribution of optically luminous galaxies

NASA Astrophysics Data System (ADS)

Deng, Xin-fa; Deng, Zu-gan; Liu, Yong-zhen

1992-04-01

Fractal dimensions in the large scale distribution of galaxies have been calculated with the method given by Wen et al. [1] Samples are taken from CfA redshift survey in northern and southern galactic [2] hemisphere in our analysis respectively. Results from these two regions are compared with each other. There are significant differences between the distributions in these two regions. However, our analyses do show some common features of the distributions in these two regions. All subsamples show multi-level fractal character distinctly. Combining it with the results from analyses of samples given by IRAS galaxies and results from samples given by redshift survey in pencil-beam fields, [3,4] we suggest that multi-level fractal structure is most likely to be a general and important character in the large scale distribution of galaxies. The possible implications of this character are discussed.

Autonomous smart sensor network for full-scale structural health monitoring

NASA Astrophysics Data System (ADS)

Rice, Jennifer A.; Mechitov, Kirill A.; Spencer, B. F., Jr.; Agha, Gul A.

2010-04-01

The demands of aging infrastructure require effective methods for structural monitoring and maintenance. Wireless smart sensor networks offer the ability to enhance structural health monitoring (SHM) practices through the utilization of onboard computation to achieve distributed data management. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While smart sensor technology is not new, the number of full-scale SHM applications has been limited. This slow progress is due, in part, to the complex network management issues that arise when moving from a laboratory setting to a full-scale monitoring implementation. This paper presents flexible network management software that enables continuous and autonomous operation of wireless smart sensor networks for full-scale SHM applications. The software components combine sleep/wake cycling for enhanced power management with threshold detection for triggering network wide tasks, such as synchronized sensing or decentralized modal analysis, during periods of critical structural response.

Probing the statistics of primordial fluctuations and their evolution

NASA Technical Reports Server (NTRS)

Gaztanaga, Enrique; Yokoyama, Jun'ichi

1993-01-01

The statistical distribution of fluctuations on various scales is analyzed in terms of the counts in cells of smoothed density fields, using volume-limited samples of galaxy redshift catalogs. It is shown that the distribution on large scales, with volume average of the two-point correlation function of the smoothed field less than about 0.05, is consistent with Gaussian. Statistics are shown to agree remarkably well with the negative binomial distribution, which has hierarchial correlations and a Gaussian behavior at large scales. If these observed properties correspond to the matter distribution, they suggest that our universe started with Gaussian fluctuations and evolved keeping hierarchial form.

Ubiquity of Benford's law and emergence of the reciprocal distribution

DOE PAGES

Friar, James Lewis; Goldman, Terrance J.; Pérez-Mercader, J.

2016-04-07

In this paper, we apply the Law of Total Probability to the construction of scale-invariant probability distribution functions (pdf's), and require that probability measures be dimensionless and unitless under a continuous change of scales. If the scale-change distribution function is scale invariant then the constructed distribution will also be scale invariant. Repeated application of this construction on an arbitrary set of (normalizable) pdf's results again in scale-invariant distributions. The invariant function of this procedure is given uniquely by the reciprocal distribution, suggesting a kind of universality. Finally, we separately demonstrate that the reciprocal distribution results uniquely from requiring maximum entropymore » for size-class distributions with uniform bin sizes.« less

Developing science gateways for drug discovery in a grid environment.

PubMed

Pérez-Sánchez, Horacio; Rezaei, Vahid; Mezhuyev, Vitaliy; Man, Duhu; Peña-García, Jorge; den-Haan, Helena; Gesing, Sandra

2016-01-01

Methods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources. To this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows. Our implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.

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

Marrinan, Thomas; Leigh, Jason; Renambot, Luc

Mixed presence collaboration involves remote collaboration between multiple collocated groups. This paper presents the design and results of a user study that focused on mixed presence collaboration using large-scale tiled display walls. The research was conducted in order to compare data synchronization schemes for multi-user visualization applications. Our study compared three techniques for sharing data between display spaces with varying constraints and affordances. The results provide empirical evidence that using data sharing techniques with continuous synchronization between the sites lead to improved collaboration for a search and analysis task between remotely located groups. We have also identified aspects of synchronizedmore » sessions that result in increased remote collaborator awareness and parallel task coordination. It is believed that this research will lead to better utilization of large-scale tiled display walls for distributed group work.« less

'Fracking', Induced Seismicity and the Critical Earth

NASA Astrophysics Data System (ADS)

Leary, P.; Malin, P. E.

2012-12-01

Issues of 'fracking' and induced seismicity are reverse-analogous to the equally complex issues of well productivity in hydrocarbon, geothermal and ore reservoirs. In low hazard reservoir economics, poorly producing wells and low grade ore bodies are many while highly producing wells and high grade ores are rare but high pay. With induced seismicity factored in, however, the same distribution physics reverses the high/low pay economics: large fracture-connectivity systems are hazardous hence low pay, while high probability small fracture-connectivity systems are non-hazardous hence high pay. Put differently, an economic risk abatement tactic for well productivity and ore body pay is to encounter large-scale fracture systems, while an economic risk abatement tactic for 'fracking'-induced seismicity is to avoid large-scale fracture systems. Well productivity and ore body grade distributions arise from three empirical rules for fluid flow in crustal rock: (i) power-law scaling of grain-scale fracture density fluctuations; (ii) spatial correlation between spatial fluctuations in well-core porosity and the logarithm of well-core permeability; (iii) frequency distributions of permeability governed by a lognormality skewness parameter. The physical origin of rules (i)-(iii) is the universal existence of a critical-state-percolation grain-scale fracture-density threshold for crustal rock. Crustal fractures are effectively long-range spatially-correlated distributions of grain-scale defects permitting fluid percolation on mm to km scales. The rule is, the larger the fracture system the more intense the percolation throughput. As percolation pathways are spatially erratic and unpredictable on all scales, they are difficult to model with sparsely sampled well data. Phenomena such as well productivity, induced seismicity, and ore body fossil fracture distributions are collectively extremely difficult to predict. Risk associated with unpredictable reservoir well productivity and ore body distributions can be managed by operating in a context which affords many small failures for a few large successes. In reverse view, 'fracking' and induced seismicity could be rationally managed in a context in which many small successes can afford a few large failures. However, just as there is every incentive to acquire information leading to higher rates of productive well drilling and ore body exploration, there are equal incentives for acquiring information leading to lower rates of 'fracking'-induced seismicity. Current industry practice of using an effective medium approach to reservoir rock creates an uncritical sense that property distributions in rock are essentially uniform. Well-log data show that the reverse is true: the larger the length scale the greater the deviation from uniformity. Applying the effective medium approach to large-scale rock formations thus appears to be unnecessarily hazardous. It promotes the notion that large scale fluid pressurization acts against weakly cohesive but essentially uniform rock to produce large-scale quasi-uniform tensile discontinuities. Indiscriminate hydrofacturing appears to be vastly more problematic in reality than as pictured by the effective medium hypothesis. The spatial complexity of rock, especially at large scales, provides ample reason to find more controlled pressurization strategies for enhancing in situ flow.

Application of the actor model to large scale NDE data analysis

NASA Astrophysics Data System (ADS)

Coughlin, Chris

2018-03-01

The Actor model of concurrent computation discretizes a problem into a series of independent units or actors that interact only through the exchange of messages. Without direct coupling between individual components, an Actor-based system is inherently concurrent and fault-tolerant. These traits lend themselves to so-called "Big Data" applications in which the volume of data to analyze requires a distributed multi-system design. For a practical demonstration of the Actor computational model, a system was developed to assist with the automated analysis of Nondestructive Evaluation (NDE) datasets using the open source Myriad Data Reduction Framework. A machine learning model trained to detect damage in two-dimensional slices of C-Scan data was deployed in a streaming data processing pipeline. To demonstrate the flexibility of the Actor model, the pipeline was deployed on a local system and re-deployed as a distributed system without recompiling, reconfiguring, or restarting the running application.

Fast Generation of Ensembles of Cosmological N-Body Simulations via Mode-Resampling

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

Schneider, M D; Cole, S; Frenk, C S

2011-02-14

We present an algorithm for quickly generating multiple realizations of N-body simulations to be used, for example, for cosmological parameter estimation from surveys of large-scale structure. Our algorithm uses a new method to resample the large-scale (Gaussian-distributed) Fourier modes in a periodic N-body simulation box in a manner that properly accounts for the nonlinear mode-coupling between large and small scales. We find that our method for adding new large-scale mode realizations recovers the nonlinear power spectrum to sub-percent accuracy on scales larger than about half the Nyquist frequency of the simulation box. Using 20 N-body simulations, we obtain a powermore » spectrum covariance matrix estimate that matches the estimator from Takahashi et al. (from 5000 simulations) with < 20% errors in all matrix elements. Comparing the rates of convergence, we determine that our algorithm requires {approx}8 times fewer simulations to achieve a given error tolerance in estimates of the power spectrum covariance matrix. The degree of success of our algorithm indicates that we understand the main physical processes that give rise to the correlations in the matter power spectrum. Namely, the large-scale Fourier modes modulate both the degree of structure growth through the variation in the effective local matter density and also the spatial frequency of small-scale perturbations through large-scale displacements. We expect our algorithm to be useful for noise modeling when constraining cosmological parameters from weak lensing (cosmic shear) and galaxy surveys, rescaling summary statistics of N-body simulations for new cosmological parameter values, and any applications where the influence of Fourier modes larger than the simulation size must be accounted for.« less

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size.

PubMed

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics.

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size

PubMed Central

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E.

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics. PMID:26381745

Large Scale Density Estimation of Blue and Fin Whales: Utilizing Sparse Array Data to Develop and Implement a New Method for Estimating Blue and Fin Whale Density

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...Utilizing Sparse Array Data to Develop and Implement a New Method for Estimating Blue and Fin Whale Density Len Thomas & Danielle Harris Centre...to develop and implement a new method for estimating blue and fin whale density that is effective over large spatial scales and is designed to cope

A Weibull distribution accrual failure detector for cloud computing

PubMed Central

Wu, Zhibo; Wu, Jin; Zhao, Yao; Wen, Dongxin

2017-01-01

Failure detectors are used to build high availability distributed systems as the fundamental component. To meet the requirement of a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. However, several implementations of accrual failure detectors do not adapt well to the cloud service environment. To solve this problem, a new accrual failure detector based on Weibull Distribution, called the Weibull Distribution Failure Detector, has been proposed specifically for cloud computing. It can adapt to the dynamic and unexpected network conditions in cloud computing. The performance of the Weibull Distribution Failure Detector is evaluated and compared based on public classical experiment data and cloud computing experiment data. The results show that the Weibull Distribution Failure Detector has better performance in terms of speed and accuracy in unstable scenarios, especially in cloud computing. PMID:28278229

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

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

WarpIV: In situ visualization and analysis of ion accelerator simulations

DOE PAGES

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc; ...

2016-05-09

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

Scale Mixture Models with Applications to Bayesian Inference

NASA Astrophysics Data System (ADS)

Qin, Zhaohui S.; Damien, Paul; Walker, Stephen

2003-11-01

Scale mixtures of uniform distributions are used to model non-normal data in time series and econometrics in a Bayesian framework. Heteroscedastic and skewed data models are also tackled using scale mixture of uniform distributions.

Large-scale geographic variation in distribution and abundance of Australian deep-water kelp forests.

PubMed

Marzinelli, Ezequiel M; Williams, Stefan B; Babcock, Russell C; Barrett, Neville S; Johnson, Craig R; Jordan, Alan; Kendrick, Gary A; Pizarro, Oscar R; Smale, Dan A; Steinberg, Peter D

2015-01-01

Despite the significance of marine habitat-forming organisms, little is known about their large-scale distribution and abundance in deeper waters, where they are difficult to access. Such information is necessary to develop sound conservation and management strategies. Kelps are main habitat-formers in temperate reefs worldwide; however, these habitats are highly sensitive to environmental change. The kelp Ecklonia radiate is the major habitat-forming organism on subtidal reefs in temperate Australia. Here, we provide large-scale ecological data encompassing the latitudinal distribution along the continent of these kelp forests, which is a necessary first step towards quantitative inferences about the effects of climatic change and other stressors on these valuable habitats. We used the Autonomous Underwater Vehicle (AUV) facility of Australia's Integrated Marine Observing System (IMOS) to survey 157,000 m2 of seabed, of which ca 13,000 m2 were used to quantify kelp covers at multiple spatial scales (10-100 m to 100-1,000 km) and depths (15-60 m) across several regions ca 2-6° latitude apart along the East and West coast of Australia. We investigated the large-scale geographic variation in distribution and abundance of deep-water kelp (>15 m depth) and their relationships with physical variables. Kelp cover generally increased with latitude despite great variability at smaller spatial scales. Maximum depth of kelp occurrence was 40-50 m. Kelp latitudinal distribution along the continent was most strongly related to water temperature and substratum availability. This extensive survey data, coupled with ongoing AUV missions, will allow for the detection of long-term shifts in the distribution and abundance of habitat-forming kelp and the organisms they support on a continental scale, and provide information necessary for successful implementation and management of conservation reserves.

Implications of the IRAS data for galactic gamma ray astronomy and EGRET

NASA Technical Reports Server (NTRS)

Stecker, Floyd W.

1990-01-01

Using the results of gamma-ray, millimeter wave and far surveys of the galaxy, logically consistent picture of the large scale distribution of galactic gas and cosmic rays was derived, tied to the overall processes of stellar birth and destruction on a galactic scale. Using the results of the IRAS far-infrared survey of te galaxy, the large scale radial distributions of galactic far-infrared emission independently was obtained for both the Northern and Southern Hemisphere sides of the Galaxy. The dominant feature in these distributions was found to be a broad peak coincident with the 5 kpc molecular gas cloud ring. Evidence was found for spiral arm features. Strong correlations are evident between the large scale galactic distributions of far-infrared emission, gamma-ray emission and total CO emission. There is particularly tight correlation between the distribution of warm molecular clouds and far-infrared emission on a galactic scale. The 5 kpc ring was evident in existing galactic gamma-ray data. The extent to which the more detailed spiral arm features are evident in the more resolved EGRET (Energetic Gamma-Ray Experimental Telescope) data will help to determine more precisely the propagation characteristics of cosmic rays.

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Fractals in geology and geophysics

NASA Technical Reports Server (NTRS)

Turcotte, Donald L.

1989-01-01

The definition of a fractal distribution is that the number of objects N with a characteristic size greater than r scales with the relation N of about r exp -D. The frequency-size distributions for islands, earthquakes, fragments, ore deposits, and oil fields often satisfy this relation. This application illustrates a fundamental aspect of fractal distributions, scale invariance. The requirement of an object to define a scale in photograhs of many geological features is one indication of the wide applicability of scale invariance to geological problems; scale invariance can lead to fractal clustering. Geophysical spectra can also be related to fractals; these are self-affine fractals rather than self-similar fractals. Examples include the earth's topography and geoid.

Mapping the distribution of the denitrifier community at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Bru, D.; Ramette, A.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 740 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Network Theory: A Primer and Questions for Air Transportation Systems Applications

NASA Technical Reports Server (NTRS)

Holmes, Bruce J.

2004-01-01

A new understanding (with potential applications to air transportation systems) has emerged in the past five years in the scientific field of networks. This development emerges in large part because we now have a new laboratory for developing theories about complex networks: The Internet. The premise of this new understanding is that most complex networks of interest, both of nature and of human contrivance, exhibit a fundamentally different behavior than thought for over two hundred years under classical graph theory. Classical theory held that networks exhibited random behavior, characterized by normal, (e.g., Gaussian or Poisson) degree distributions of the connectivity between nodes by links. The new understanding turns this idea on its head: networks of interest exhibit scale-free (or small world) degree distributions of connectivity, characterized by power law distributions. The implications of scale-free behavior for air transportation systems include the potential that some behaviors of complex system architectures might be analyzed through relatively simple approximations of local elements of the system. For air transportation applications, this presentation proposes a framework for constructing topologies (architectures) that represent the relationships between mobility, flight operations, aircraft requirements, and airspace capacity, and the related externalities in airspace procedures and architectures. The proposed architectures or topologies may serve as a framework for posing comparative and combinative analyses of performance, cost, security, environmental, and related metrics.

Shifts in Summertime Precipitation Accumulation Distributions over the US

NASA Astrophysics Data System (ADS)

Martinez-Villalobos, C.; Neelin, J. D.

2016-12-01

Precipitation accumulations, i.e., the amount of precipitation integrated over the course of an event, is a variable with both important physical and societal implications. Previous observational studies show that accumulation distributions have a characteristic shape, with an approximately power law decrease at first, followed by a sharp decrease at a characteristic large event cutoff scale. This cutoff scale is important as it limits the biggest accumulation events. Stochastic prototypes show that the resulting distributions, and importantly the large event cutoff scale, can be understood as a result of the interplay between moisture loss by precipitation and changes in moisture sinks/sources due to fluctuations in moisture divergence over the course of a precipitation event. The strength of this fluctuating moisture sink/source term is expected to increase under global warming, with both theory and climate model simulations predicting a concomitant increase in the large event cutoff scale. This cutoff scale increase has important consequences as it implies an approximately exponential increase for the largest accumulation events. Given its importance, in this study we characterize and track changes in the distribution of precipitation events accumulations over the contiguous US. Accumulation distributions are calculated using hourly precipitation data from 1700 stations, covering the 1974-2013 period over May-October. The resulting distributions largely follow the aforementioned shape, with individual cutoff scales depending on the local climate. An increase in the large event cutoff scale over this period is observed over several regions over the US, most notably over the eastern third of the US. In agreement with the increase in the cutoff, almost exponential increases in the highest accumulation percentiles occur over these regions, with increases in the 99.9 percentile in the Northeast of 70% for example. The relationship to changes in daily precipitation that have previously been noted and to changes in the moisture budget over this period are examined.

Shifts in Summertime Precipitation Accumulation Distributions over the US

NASA Astrophysics Data System (ADS)

Martinez-Villalobos, C.; Neelin, J. D.

2017-12-01

Precipitation accumulations, i.e., the amount of precipitation integrated over the course of an event, is a variable with both important physical and societal implications. Previous observational studies show that accumulation distributions have a characteristic shape, with an approximately power law decrease at first, followed by a sharp decrease at a characteristic large event cutoff scale. This cutoff scale is important as it limits the biggest accumulation events. Stochastic prototypes show that the resulting distributions, and importantly the large event cutoff scale, can be understood as a result of the interplay between moisture loss by precipitation and changes in moisture sinks/sources due to fluctuations in moisture divergence over the course of a precipitation event. The strength of this fluctuating moisture sink/source term is expected to increase under global warming, with both theory and climate model simulations predicting a concomitant increase in the large event cutoff scale. This cutoff scale increase has important consequences as it implies an approximately exponential increase for the largest accumulation events. Given its importance, in this study we characterize and track changes in the distribution of precipitation events accumulations over the contiguous US. Accumulation distributions are calculated using hourly precipitation data from 1700 stations, covering the 1974-2013 period over May-October. The resulting distributions largely follow the aforementioned shape, with individual cutoff scales depending on the local climate. An increase in the large event cutoff scale over this period is observed over several regions over the US, most notably over the eastern third of the US. In agreement with the increase in the cutoff, almost exponential increases in the highest accumulation percentiles occur over these regions, with increases in the 99.9 percentile in the Northeast of 70% for example. The relationship to changes in daily precipitation that have previously been noted and to changes in the moisture budget over this period are examined.

The consequences of landscape change on ecological resources: An assessment of the United States mid-Atlantic region, 1973-1993

USGS Publications Warehouse

Jones, K.B.; Neale, A.C.; Wade, T.G.; Wickham, J.D.; Cross, C.L.; Edmonds, C.M.; Loveland, Thomas R.; Nash, M.S.; Riitters, K.H.; Smith, E.R.

2001-01-01

Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the development of methods to conduct such broad-scale assessments. Field-based methods have proven to be too costly and too inconsistent in their application to make estimates of ecological conditions over large areas. New spatial data derived from satellite imagery and other sources, the development of statistical models relating landscape composition and pattern to ecological endpoints, and geographic information systems (GIS) make it possible to evaluate ecological conditions at multiple scales over broad geographic regions. In this study, we demonstrate the application of spatially distributed models for bird habitat quality and nitrogen yield to streams to assess the consequences of landcover change across the mid-Atlantic region between the 1970s and 1990s. Moreover, we present a way to evaluate spatial concordance between models related to different environmental endpoints. Results of this study should help environmental managers in the mid-Atlantic region target those areas in need of conservation and protection.

Double inflation - A possible resolution of the large-scale structure problem

NASA Technical Reports Server (NTRS)

Turner, Michael S.; Villumsen, Jens V.; Vittorio, Nicola; Silk, Joseph; Juszkiewicz, Roman

1987-01-01

A model is presented for the large-scale structure of the universe in which two successive inflationary phases resulted in large small-scale and small large-scale density fluctuations. This bimodal density fluctuation spectrum in an Omega = 1 universe dominated by hot dark matter leads to large-scale structure of the galaxy distribution that is consistent with recent observational results. In particular, large, nearly empty voids and significant large-scale peculiar velocity fields are produced over scales of about 100 Mpc, while the small-scale structure over less than about 10 Mpc resembles that in a low-density universe, as observed. Detailed analytical calculations and numerical simulations are given of the spatial and velocity correlations.

Steps Towards Understanding Large-scale Deformation of Gas Hydrate-bearing Sediments

NASA Astrophysics Data System (ADS)

Gupta, S.; Deusner, C.; Haeckel, M.; Kossel, E.

2016-12-01

Marine sediments bearing gas hydrates are typically characterized by heterogeneity in the gas hydrate distribution and anisotropy in the sediment-gas hydrate fabric properties. Gas hydrates also contribute to the strength and stiffness of the marine sediment, and any disturbance in the thermodynamic stability of the gas hydrates is likely to affect the geomechanical stability of the sediment. Understanding mechanisms and triggers of large-strain deformation and failure of marine gas hydrate-bearing sediments is an area of extensive research, particularly in the context of marine slope-stability and industrial gas production. The ultimate objective is to predict severe deformation events such as regional-scale slope failure or excessive sand production by using numerical simulation tools. The development of such tools essentially requires a careful analysis of thermo-hydro-chemo-mechanical behavior of gas hydrate-bearing sediments at lab-scale, and its stepwise integration into reservoir-scale simulators through definition of effective variables, use of suitable constitutive relations, and application of scaling laws. One of the focus areas of our research is to understand the bulk coupled behavior of marine gas hydrate systems with contributions from micro-scale characteristics, transport-reaction dynamics, and structural heterogeneity through experimental flow-through studies using high-pressure triaxial test systems and advanced tomographical tools (CT, ERT, MRI). We combine these studies to develop mathematical model and numerical simulation tools which could be used to predict the coupled hydro-geomechanical behavior of marine gas hydrate reservoirs in a large-strain framework. Here we will present some of our recent results from closely co-ordinated experimental and numerical simulation studies with an objective to capture the large-deformation behavior relevant to different gas production scenarios. We will also report on a variety of mechanically relevant test scenarios focusing on effects of dynamic changes in gas hydrate saturation, highly uneven gas hydrate distributions, focused fluid migration and gas hydrate production through depressurization and CO2 injection.

Relative importance of time, land use and lithology on determining aquifer-scale denitrification

NASA Astrophysics Data System (ADS)

Kolbe, Tamara; de Dreuzy, Jean-Raynald; Abbott, Benjamin W.; Marçais, Jean; Babey, Tristan; Thomas, Zahra; Peiffer, Stefan; Aquilina, Luc; Labasque, Thierry; Laverman, Anniet; Fleckenstein, Jan; Boulvais, Philippe; Pinay, Gilles

2017-04-01

Unconfined shallow aquifers are commonly contaminated by nitrate in agricultural regions, because of excess fertilizer application over the last decades. Watershed studies have indicated that 1) changes in agricultural practices have caused changes in nitrate input over time, 2) denitrification occurs in localized hotspots within the aquifer, and 3) heterogeneous groundwater flow circulation has led to strong nitrate gradients in aquifers that are not yet well understood. In this study we investigated the respective influence of land use, groundwater transit time distribution, and hotspot distribution on groundwater denitrification with a particular interest on how a detailed understanding of transit time distributions could be used to upscale the point denitrification measurements to the aquifer-scale. We measured CFC-based groundwater age, oxygen, nitrate, and dinitrogen gas excess in 16 agricultural wells of an unconfined crystalline aquifer in Brittany, France. Groundwater age data was used to calibrate a mechanistic groundwater flow model of the study site. Historical nitrate inputs were reconstructed by using measured nitrate concentrations, dinitrogen gas excess and transit time distributions of the wells. Field data showed large differences in denitrification activity among wells, strongly associated with differences in transit time distribution. This suggests that knowing groundwater flow dynamics and consequent transit time distributions at the catchment-scale could be used to estimate the overall denitrification capacity of agricultural aquifers.

Nanoparticles from renewable polymers

PubMed Central

Wurm, Frederik R.; Weiss, Clemens K.

2014-01-01

The use of polymers from natural resources can bring many benefits for novel polymeric nanoparticle systems. Such polymers have a variety of beneficial properties such as biodegradability and biocompatibility, they are readily available on large scale and at low cost. As the amount of fossil fuels decrease, their application becomes more interesting even if characterization is in many cases more challenging due to structural complexity, either by broad distribution of their molecular weights (polysaccharides, polyesters, lignin) or by complex structure (proteins, lignin). This review summarizes different sources and methods for the preparation of biopolymer-based nanoparticle systems for various applications. PMID:25101259

Towards Portable Large-Scale Image Processing with High-Performance Computing.

PubMed

Huo, Yuankai; Blaber, Justin; Damon, Stephen M; Boyd, Brian D; Bao, Shunxing; Parvathaneni, Prasanna; Noguera, Camilo Bermudez; Chaganti, Shikha; Nath, Vishwesh; Greer, Jasmine M; Lyu, Ilwoo; French, William R; Newton, Allen T; Rogers, Baxter P; Landman, Bennett A

2018-05-03

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.

Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data

PubMed Central

Detwiler, Landon T.; Suciu, Dan; Franklin, Joshua D.; Moore, Eider B.; Poliakov, Andrew V.; Lee, Eunjung S.; Corina, David P.; Ojemann, George A.; Brinkley, James F.

2008-01-01

This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too “heavyweight” for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a “lightweight” distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP) accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts. PMID:19198662

From ratites to rats: the size of fleshy fruits shapes species' distributions and continental rainforest assembly

PubMed Central

Rossetto, Maurizio; Kooyman, Robert; Yap, Jia-Yee S.; Laffan, Shawn W.

2015-01-01

Seed dispersal is a key process in plant spatial dynamics. However, consistently applicable generalizations about dispersal across scales are mostly absent because of the constraints on measuring propagule dispersal distances for many species. Here, we focus on fleshy-fruited taxa, specifically taxa with large fleshy fruits and their dispersers across an entire continental rainforest biome. We compare species-level results of whole-chloroplast DNA analyses in sister taxa with large and small fruits, to regional plot-based samples (310 plots), and whole-continent patterns for the distribution of woody species with either large (more than 30 mm) or smaller fleshy fruits (1093 taxa). The pairwise genomic comparison found higher genetic distances between populations and between regions in the large-fruited species (Endiandra globosa), but higher overall diversity within the small-fruited species (Endiandra discolor). Floristic comparisons among plots confirmed lower numbers of large-fruited species in areas where more extreme rainforest contraction occurred, and re-colonization by small-fruited species readily dispersed by the available fauna. Species' distribution patterns showed that larger-fruited species had smaller geographical ranges than smaller-fruited species and locations with stable refugia (and high endemism) aligned with concentrations of large fleshy-fruited taxa, making them a potentially valuable conservation-planning indicator. PMID:26645199

From ratites to rats: the size of fleshy fruits shapes species' distributions and continental rainforest assembly.

PubMed

Rossetto, Maurizio; Kooyman, Robert; Yap, Jia-Yee S; Laffan, Shawn W

2015-12-07

Seed dispersal is a key process in plant spatial dynamics. However, consistently applicable generalizations about dispersal across scales are mostly absent because of the constraints on measuring propagule dispersal distances for many species. Here, we focus on fleshy-fruited taxa, specifically taxa with large fleshy fruits and their dispersers across an entire continental rainforest biome. We compare species-level results of whole-chloroplast DNA analyses in sister taxa with large and small fruits, to regional plot-based samples (310 plots), and whole-continent patterns for the distribution of woody species with either large (more than 30 mm) or smaller fleshy fruits (1093 taxa). The pairwise genomic comparison found higher genetic distances between populations and between regions in the large-fruited species (Endiandra globosa), but higher overall diversity within the small-fruited species (Endiandra discolor). Floristic comparisons among plots confirmed lower numbers of large-fruited species in areas where more extreme rainforest contraction occurred, and re-colonization by small-fruited species readily dispersed by the available fauna. Species' distribution patterns showed that larger-fruited species had smaller geographical ranges than smaller-fruited species and locations with stable refugia (and high endemism) aligned with concentrations of large fleshy-fruited taxa, making them a potentially valuable conservation-planning indicator. © 2015 The Author(s).

Design and Verification of Remote Sensing Image Data Center Storage Architecture Based on Hadoop

NASA Astrophysics Data System (ADS)

Tang, D.; Zhou, X.; Jing, Y.; Cong, W.; Li, C.

2018-04-01

The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.

Quantifying Stock Return Distributions in Financial Markets

PubMed Central

Botta, Federico; Moat, Helen Susannah; Stanley, H. Eugene; Preis, Tobias

2015-01-01

Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales. PMID:26327593

Quantifying Stock Return Distributions in Financial Markets.

PubMed

Botta, Federico; Moat, Helen Susannah; Stanley, H Eugene; Preis, Tobias

2015-01-01

Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales.

STRIDE: Species Tree Root Inference from Gene Duplication Events.

PubMed

Emms, David M; Kelly, Steven

2017-12-01

The correct interpretation of any phylogenetic tree is dependent on that tree being correctly rooted. We present STRIDE, a fast, effective, and outgroup-free method for identification of gene duplication events and species tree root inference in large-scale molecular phylogenetic analyses. STRIDE identifies sets of well-supported in-group gene duplication events from a set of unrooted gene trees, and analyses these events to infer a probability distribution over an unrooted species tree for the location of its root. We show that STRIDE correctly identifies the root of the species tree in multiple large-scale molecular phylogenetic data sets spanning a wide range of timescales and taxonomic groups. We demonstrate that the novel probability model implemented in STRIDE can accurately represent the ambiguity in species tree root assignment for data sets where information is limited. Furthermore, application of STRIDE to outgroup-free inference of the origin of the eukaryotic tree resulted in a root probability distribution that provides additional support for leading hypotheses for the origin of the eukaryotes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

INFN, IT the GENIUS grid portal and the robot certificates to perform phylogenetic analysis on large scale: a success story from the International LIBI project

NASA Astrophysics Data System (ADS)

Barbera, Roberto; Donvit, Giacinto; Falzone, Alberto; Rocca, Giuseppe La; Maggi, Giorgio Pietro; Milanesi, Luciano; Vicarioicario, Saverio

This paper depicts the solution proposed by INFN to allow users, not owning a personal digital certificate and therefore not belonging to any specific Virtual Organization (VO), to access Grid infrastructures via the GENIUS Grid portal enabled with robot certificates. Robot certificates, also known as portal certificates, are associated with a specific application that the user wants to share with the whole Grid community and have recently been introduced by the EUGridPMA (European Policy Management Authority for Grid Authentication) to perform automated tasks on Grids on behalf of users. They are proven to be extremely useful to automate grid service monitoring, data processing production, distributed data collection systems, etc. In this paper, robot certificates have been used to allow bioinformaticians involved in the Italian LIBI project to perform large scale phylogenetic analyses. The distributed environment set up in this work strongly simplify the grid access of occasional users and represents a valuable step forward to wide the communities of users.

Large-scale velocities and primordial non-Gaussianity

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

Schmidt, Fabian

2010-09-15

We study the peculiar velocities of density peaks in the presence of primordial non-Gaussianity. Rare, high-density peaks in the initial density field can be identified with tracers such as galaxies and clusters in the evolved matter distribution. The distribution of relative velocities of peaks is derived in the large-scale limit using two different approaches based on a local biasing scheme. Both approaches agree, and show that halos still stream with the dark matter locally as well as statistically, i.e. they do not acquire a velocity bias. Nonetheless, even a moderate degree of (not necessarily local) non-Gaussianity induces a significant skewnessmore » ({approx}0.1-0.2) in the relative velocity distribution, making it a potentially interesting probe of non-Gaussianity on intermediate to large scales. We also study two-point correlations in redshift space. The well-known Kaiser formula is still a good approximation on large scales, if the Gaussian halo bias is replaced with its (scale-dependent) non-Gaussian generalization. However, there are additional terms not encompassed by this simple formula which become relevant on smaller scales (k > or approx. 0.01h/Mpc). Depending on the allowed level of non-Gaussianity, these could be of relevance for future large spectroscopic surveys.« less

Statistical Analysis of Big Data on Pharmacogenomics

PubMed Central

Fan, Jianqing; Liu, Han

2013-01-01

This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

Distributed Optimization of Multi-Agent Systems: Framework, Local Optimizer, and Applications

NASA Astrophysics Data System (ADS)

Zu, Yue

Convex optimization problem can be solved in a centralized or distributed manner. Compared with centralized methods based on single-agent system, distributed algorithms rely on multi-agent systems with information exchanging among connected neighbors, which leads to great improvement on the system fault tolerance. Thus, a task within multi-agent system can be completed with presence of partial agent failures. By problem decomposition, a large-scale problem can be divided into a set of small-scale sub-problems that can be solved in sequence/parallel. Hence, the computational complexity is greatly reduced by distributed algorithm in multi-agent system. Moreover, distributed algorithm allows data collected and stored in a distributed fashion, which successfully overcomes the drawbacks of using multicast due to the bandwidth limitation. Distributed algorithm has been applied in solving a variety of real-world problems. Our research focuses on the framework and local optimizer design in practical engineering applications. In the first one, we propose a multi-sensor and multi-agent scheme for spatial motion estimation of a rigid body. Estimation performance is improved in terms of accuracy and convergence speed. Second, we develop a cyber-physical system and implement distributed computation devices to optimize the in-building evacuation path when hazard occurs. The proposed Bellman-Ford Dual-Subgradient path planning method relieves the congestion in corridor and the exit areas. At last, highway traffic flow is managed by adjusting speed limits to minimize the fuel consumption and travel time in the third project. Optimal control strategy is designed through both centralized and distributed algorithm based on convex problem formulation. Moreover, a hybrid control scheme is presented for highway network travel time minimization. Compared with no controlled case or conventional highway traffic control strategy, the proposed hybrid control strategy greatly reduces total travel time on test highway network.

Population distributions of time to collision at brake application during car following from naturalistic driving data.

PubMed

Kusano, Kristofer D; Chen, Rong; Montgomery, Jade; Gabler, Hampton C

2015-09-01

Forward collision warning (FCW) systems are designed to mitigate the effects of rear-end collisions. Driver acceptance of these systems is crucial to their success, as perceived "nuisance" alarms may cause drivers to disable the systems. In order to make customizable FCW thresholds, system designers need to quantify the variation in braking behavior in the driving population. The objective of this study was to quantify the time to collision (TTC) that drivers applied the brakes during car following scenarios from a large scale naturalistic driving study (NDS). Because of the large amount of data generated by NDS, an automated algorithm was developed to identify lead vehicles using radar data recorded as part of the study. Using the search algorithm, all trips from 64 drivers from the 100-Car NDS were analyzed. A comparison of the algorithm to 7135 brake applications where the presence of a lead vehicle was manually identified found that the algorithm agreed with the human review 90.6% of the time. This study examined 72,123 trips that resulted in 2.6 million brake applications. Population distributions of the minimum, 1st, and 10th percentiles were computed for each driver in speed ranges between 3 and 60 mph in 10 mph increments. As speed increased, so did the minimum TTC experience by drivers as well as variance in TTC. Younger drivers (18-30) had lower TTC at brake application compared to older drivers (30-51+), especially at speeds between 40 mph and 60 mph. This is one of the first studies to use large scale NDS data to quantify braking behavior during car following. The results of this study can be used to design and evaluate FCW systems and calibrate traffic simulation models. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Extending large-scale forest inventories to assess urban forests.

PubMed

Corona, Piermaria; Agrimi, Mariagrazia; Baffetta, Federica; Barbati, Anna; Chiriacò, Maria Vincenza; Fattorini, Lorenzo; Pompei, Enrico; Valentini, Riccardo; Mattioli, Walter

2012-03-01

Urban areas are continuously expanding today, extending their influence on an increasingly large proportion of woods and trees located in or nearby urban and urbanizing areas, the so-called urban forests. Although these forests have the potential for significantly improving the quality the urban environment and the well-being of the urban population, data to quantify the extent and characteristics of urban forests are still lacking or fragmentary on a large scale. In this regard, an expansion of the domain of multipurpose forest inventories like National Forest Inventories (NFIs) towards urban forests would be required. To this end, it would be convenient to exploit the same sampling scheme applied in NFIs to assess the basic features of urban forests. This paper considers approximately unbiased estimators of abundance and coverage of urban forests, together with estimators of the corresponding variances, which can be achieved from the first phase of most large-scale forest inventories. A simulation study is carried out in order to check the performance of the considered estimators under various situations involving the spatial distribution of the urban forests over the study area. An application is worked out on the data from the Italian NFI.

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

Zhai, Y.; D'Hauthuille, L.; Barth, C.

High-field superconducting magnets play a very important role in many large-scale physics experiments, particularly particle colliders and fusion confinement devices such as Large Hadron Collider (LHC) and International Thermonuclear Experimental Reactor (ITER). The two most common superconductors used in these applications are NbTi and Nb 3Sn. Nb 3Sn wires are favored because of their significantly higher J c (critical current density) for higher field applications. The main disadvantage of Nb 3Sn is that the superconducting performance of the wire is highly strain sensitive and it is very brittle. This strain sensitivity is strongly influenced by two factors: plasticity and crackedmore » filaments. Cracks are induced by large stress concentrators that can be traced to the presence of voids in the wire. We develop detailed 2-D and 3-D finite-element models containing wire filaments and different possible distributions of voids in a bronze-route Nb 3Sn wire. We apply compressive transverse loads for various cases of void distributions to simulate the stress and strain response of a Nb 3Sn wire under the Lorentz force. Furthermore, this paper improves our understanding of the effect voids have on the Nb 3Sn wire's mechanical properties, and in so, the connection between the distribution of voids and performance degradation such as the correlation between irreversible strain limit and the void-induced local stress concentrations.« less

A study on the required performance of a 2G HTS wire for HTS wind power generators

NASA Astrophysics Data System (ADS)

Sung, Hae-Jin; Park, Minwon; Go, Byeong-Soo; Yu, In-Keun

2016-05-01

YBCO or REBCO coated conductor (2G) materials are developed for their superior performance at high magnetic field and temperature. Power system applications based on high temperature superconducting (HTS) 2G wire technology are attracting attention, including large-scale wind power generators. In particular, to solve problems associated with the foundations and mechanical structure of offshore wind turbines, due to the large diameter and heavy weight of the generator, an HTS generator is suggested as one of the key technologies. Many researchers have tried to develop feasible large-scale HTS wind power generator technologies. In this paper, a study on the required performance of a 2G HTS wire for large-scale wind power generators is discussed. A 12 MW class large-scale wind turbine and an HTS generator are designed using 2G HTS wire. The total length of the 2G HTS wire for the 12 MW HTS generator is estimated, and the essential prerequisites of the 2G HTS wire based generator are described. The magnetic field distributions of a pole module are illustrated, and the mechanical stress and strain of the pole module are analysed. Finally, a reasonable price for 2G HTS wire for commercialization of the HTS generator is suggested, reflecting the results of electromagnetic and mechanical analyses of the generator.

Impact of potential large-scale and medium-scale irrigation on the West African Monsoon and its dependence on location of irrigated area

NASA Astrophysics Data System (ADS)

Eltahir, E. A. B.; IM, E. S.

2014-12-01

This study investigates the impact of potential large-scale (about 400,000 km2) and medium-scale (about 60,000 km2) irrigation on the climate of West Africa using the MIT Regional Climate Model. A new irrigation module is implemented to assess the impact of location and scheduling of irrigation on rainfall distribution over West Africa. A control simulation (without irrigation) and various sensitivity experiments (with irrigation) are performed and compared to discern the effects of irrigation location, size and scheduling. In general, the irrigation-induced surface cooling due to anomalously wet soil tends to suppress moist convection and rainfall, which in turn induces local subsidence and low level anti-cyclonic circulation. These local effects are dominated by a consistent reduction of local rainfall over the irrigated land, irrespective of its location. However, the remote response of rainfall distribution to irrigation exhibits a significant sensitivity to the latitudinal position of irrigation. The low-level northeasterly flow associated with anti-cyclonic circulation centered over the irrigation area can enhance the extent of low level convergence through interaction with the prevailing monsoon flow, leading to significant increase in rainfall. Despite much reduced forcing of irrigation water, the medium-scale irrigation seems to draw the same response as large-scale irrigation, which supports the robustness of the response to irrigation in our modeling system. Both large-scale and medium-scale irrigation experiments show that an optimal irrigation location and scheduling exists that would lead to a more efficient use of irrigation water. The approach of using a regional climate model to investigate the impact of location and size of irrigation schemes may be the first step in incorporating land-atmosphere interactions in the design of location and size of irrigation projects. However, this theoretical approach is still in early stages of development and further research is needed before any practical application in water resources planning. Acknowledgements.This research was supported by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling interdisciplinary research program.

Design and implementation of distributed multimedia surveillance system based on object-oriented middleware

NASA Astrophysics Data System (ADS)

Cao, Xuesong; Jiang, Ling; Hu, Ruimin

2006-10-01

Currently, the applications of surveillance system have been increasingly widespread. But there are few surveillance platforms that can meet the requirement of large-scale, cross-regional, and flexible surveillance business. In the paper, we present a distributed surveillance system platform to improve safety and security of the society. The system is constructed by an object-oriented middleware called as Internet Communications Engine (ICE). This middleware helps our platform to integrate a lot of surveillance resource of the society and accommodate diverse range of surveillance industry requirements. In the follow sections, we will describe in detail the design concepts of system and introduce traits of ICE.

Large-scale motions in the universe: Using clusters of galaxies as tracers

NASA Technical Reports Server (NTRS)

Gramann, Mirt; Bahcall, Neta A.; Cen, Renyue; Gott, J. Richard

1995-01-01

Can clusters of galaxies be used to trace the large-scale peculiar velocity field of the universe? We answer this question by using large-scale cosmological simulations to compare the motions of rich clusters of galaxies with the motion of the underlying matter distribution. Three models are investigated: Omega = 1 and Omega = 0.3 cold dark matter (CDM), and Omega = 0.3 primeval baryonic isocurvature (PBI) models, all normalized to the Cosmic Background Explorer (COBE) background fluctuations. We compare the cluster and mass distribution of peculiar velocities, bulk motions, velocity dispersions, and Mach numbers as a function of scale for R greater than or = 50/h Mpc. We also present the large-scale velocity and potential maps of clusters and of the matter. We find that clusters of galaxies trace well the large-scale velocity field and can serve as an efficient tool to constrain cosmological models. The recently reported bulk motion of clusters 689 +/- 178 km/s on approximately 150/h Mpc scale (Lauer & Postman 1994) is larger than expected in any of the models studied (less than or = 190 +/- 78 km/s).

Corridor One:An Integrated Distance Visualization Enuronments for SSI+ASCI Applications

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

Christopher R. Johnson, Charles D. Hansen

2001-10-29

The goal of Corridor One: An Integrated Distance Visualization Environment for ASCI and SSI Application was to combine the forces of six leading edge laboratories working in the areas of visualization and distributed computing and high performance networking (Argonne National Laboratory, Lawrence Berkeley National Laboratory, Los Alamos National Laboratory, University of Illinois, University of Utah and Princeton University) to develop and deploy the most advanced integrated distance visualization environment for large-scale scientific visualization and demonstrate it on applications relevant to the DOE SSI and ASCI programs. The Corridor One team brought world class expertise in parallel rendering, deep image basedmore » rendering, immersive environment technology, large-format multi-projector wall based displays, volume and surface visualization algorithms, collaboration tools and streaming media technology, network protocols for image transmission, high-performance networking, quality of service technology and distributed computing middleware. Our strategy was to build on the very successful teams that produced the I-WAY, ''Computational Grids'' and CAVE technology and to add these to the teams that have developed the fastest parallel visualizations systems and the most widely used networking infrastructure for multicast and distributed media. Unfortunately, just as we were getting going on the Corridor One project, DOE cut the program after the first year. As such, our final report consists of our progress during year one of the grant.« less

The applications of model-based geostatistics in helminth epidemiology and control.

PubMed

Magalhães, Ricardo J Soares; Clements, Archie C A; Patil, Anand P; Gething, Peter W; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Phytoextraction of Cd-Contaminated Soils: Current Status and Future Challenges.

PubMed

Li, Jin-Tian; Baker, Alan J M; Ye, Zhi-Hong; Wang, Hong-Bin; Shu, Wen-Sheng

2012-10-01

Cadmium (Cd) is one of the most toxic and widely distributed pollutants in the environment. Cadmium contamination of soils has posed a serious threat to safe food production in many parts of the world. The authors present a comprehensive review of present status of phytoextraction technology for cleaning up Cd-contaminated soils, based primarily on the data resulting from both laboratory and field-scale studies that have been conducted to assess or improve the Cd phytoextraction potential of various plant species in the past decade. The encouraging results of field-scale studies have provided a fundamental basis to usher phytoextraction technology into practical use to remediate slightly to moderately Cd-contaminated soils in Europe and Asia, although this technology is not yet ready for widespread application. Chelators and microorganisms tested so far seem not to contribute to the applicability of Cd phytoextraction. The major challenges for the large-scale application of Cd phytoextraction are (a) how to further improve the efficiency of Cd phytoextraction, (b) how to cut the overall costs of Cd phytoextraction, and (c) how to get greater stakeholders' acceptance of Cd phytoextraction as a reliable option.

Simple Statistical Model to Quantify Maximum Expected EMC in Spacecraft and Avionics Boxes

NASA Technical Reports Server (NTRS)

Trout, Dawn H.; Bremner, Paul

2014-01-01

This study shows cumulative distribution function (CDF) comparisons of composite a fairing electromagnetic field data obtained by computational electromagnetic 3D full wave modeling and laboratory testing. Test and model data correlation is shown. In addition, this presentation shows application of the power balance and extention of this method to predict the variance and maximum exptected mean of the E-field data. This is valuable for large scale evaluations of transmission inside cavities.

A distributed microcomputer-controlled system for data acquisition and power spectral analysis of EEG.

PubMed

Vo, T D; Dwyer, G; Szeto, H H

1986-04-01

A relatively powerful and inexpensive microcomputer-based system for the spectral analysis of the EEG is presented. High resolution and speed is achieved with the use of recently available large-scale integrated circuit technology with enhanced functionality (INTEL Math co-processors 8087) which can perform transcendental functions rapidly. The versatility of the system is achieved with a hardware organization that has distributed data acquisition capability performed by the use of a microprocessor-based analog to digital converter with large resident memory (Cyborg ISAAC-2000). Compiled BASIC programs and assembly language subroutines perform on-line or off-line the fast Fourier transform and spectral analysis of the EEG which is stored as soft as well as hard copy. Some results obtained from test application of the entire system in animal studies are presented.

Analyzing big data with the hybrid interval regression methods.

PubMed

Huang, Chia-Hui; Yang, Keng-Chieh; Kao, Han-Ying

2014-01-01

Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth support vector machine (SSVM) to analyze big data. Recently, the smooth support vector machine (SSVM) was proposed as an alternative of the standard SVM that has been proved more efficient than the traditional SVM in processing large-scale data. In addition the soft margin method is proposed to modify the excursion of separation margin and to be effective in the gray zone that the distribution of data becomes hard to be described and the separation margin between classes.

Analyzing Big Data with the Hybrid Interval Regression Methods

PubMed Central

Kao, Han-Ying

2014-01-01

Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth support vector machine (SSVM) to analyze big data. Recently, the smooth support vector machine (SSVM) was proposed as an alternative of the standard SVM that has been proved more efficient than the traditional SVM in processing large-scale data. In addition the soft margin method is proposed to modify the excursion of separation margin and to be effective in the gray zone that the distribution of data becomes hard to be described and the separation margin between classes. PMID:25143968

Power Supply for Variable Frequency Induction Heating Using MERS Soft-Switching High Frequency Inverter

NASA Astrophysics Data System (ADS)

Isobe, Takanori; Kitahara, Tadayuki; Fukutani, Kazuhiko; Shimada, Ryuichi

Variable frequency induction heating has great potential for industrial heating applications due to the possibility of achieving heating distribution control; however, large-scale induction heating with variable frequency has not yet been introduced for practical use. This paper proposes a high frequency soft-switching inverter for induction heating that can achieve variable frequency operation. One challenge of variable frequency induction heating is increasing power electronics ratings. This paper indicates that its current source type dc-link configuration and soft-switching characteristics can make it possible to build a large-scale system with variable frequency capability. A 90-kVA 150-1000Hz variable frequency experimental power supply for steel strip induction heating was developed. Experiments confirmed the feasibility of variable frequency induction heating with proposed converter and the advantages of variable frequency operation.

Gravitational lenses and large scale structure

NASA Technical Reports Server (NTRS)

Turner, Edwin L.

1987-01-01

Four possible statistical tests of the large scale distribution of cosmic material are described. Each is based on gravitational lensing effects. The current observational status of these tests is also summarized.

Three Dimensional Distribution of Sensitive Field and Stress Field Inversion of Force Sensitive Materials under Constant Current Excitation.

PubMed

Zhao, Shuanfeng; Liu, Min; Guo, Wei; Zhang, Chuanwei

2018-02-28

Force sensitive conductive composite materials are functional materials which can be used as the sensitive material of force sensors. However, the existing sensors only use one-dimensional electrical properties of force sensitive conductive materials. Even in tactile sensors, the measurement of contact pressure is achieved by large-scale arrays and the units of a large-scale array are also based on the one-dimensional electrical properties of force sensitive materials. The main contribution of this work is to study the three-dimensional electrical properties and the inversion method of three-dimensional stress field of a force sensitive material (conductive rubber), which pushes the application of force sensitive material from one dimensional to three-dimensional. First, the mathematical model of the conductive rubber current field distribution under a constant force is established by the effective medium theory, and the current field distribution model of conductive rubber with different geometry, conductive rubber content and conductive rubber relaxation parameters is deduced. Secondly, the inversion method of the three-dimensional stress field of conductive rubber is established, which provides a theoretical basis for the design of a new tactile sensor, three-dimensional stress field and space force based on force sensitive materials.

Hexabromocyclododecanes (HBCDDs) in surface soils from coastal cities in North China: Correlation between diastereoisomer profiles and industrial activities.

PubMed

Zhang, Yueqing; Li, Qifeng; Lu, Yonglong; Jones, Kevin; Sweetman, Andrew J

2016-04-01

Hexabromocyclododecane (HBCDD) is a brominated flame retardant with a wide range of industrial applications, although little is known about its patterns of spatial distribution in soils in relation to industrial emissions. This study has undertaken a large-scale investigation around an industrialized coastal area of China, exploring the concentrations, spatial distribution and diastereoisomer profiles of HBCDD in 188 surface soils from 21 coastal cities in North China. The detection frequency was 100% and concentrations of total HBCDD in the surface soils ranged from 0.123 to 363 ng g(-1) and averaged 7.20 ng g(-1), showing its ubiquitous existence at low levels. The spatial distribution of HBCDD exhibited a correlation with the location of known manufacturing facilities in Weifang, suggesting the production of HBCDD as major emission source. Diastereoisomer profiles varied in different cities. Diastereoisomer compositions in soils were compared with emissions from HBCDD industrial activities, and correlations were found between them, which has the potential for source identification. Although the contemporary concentrations of HBCDD in soils from the study were relatively low, HBCDD-containing products (expanded/extruded polystyrene insulation boards) would be a potential source after its service life, and attention needs to be paid to prioritizing large-scale waste management efforts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Scalable subsurface inverse modeling of huge data sets with an application to tracer concentration breakthrough data from magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Lee, Jonghyun; Yoon, Hongkyu; Kitanidis, Peter K.; Werth, Charles J.; Valocchi, Albert J.

2016-07-01

Characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydrogeophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with "big data" processing and numerous large-scale numerical simulations. To tackle such difficulties, the principal component geostatistical approach (PCGA) has been proposed as a "Jacobian-free" inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed in the traditional inversion methods. PCGA can be conveniently linked to any multiphysics simulation software with independent parallel executions. In this paper, we extend PCGA to handle a large number of measurements (e.g., 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data were compressed by the zeroth temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Only about 2000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method.

Large Scale Traffic Simulations

DOT National Transportation Integrated Search

1997-01-01

Large scale microscopic (i.e. vehicle-based) traffic simulations pose high demands on computation speed in at least two application areas: (i) real-time traffic forecasting, and (ii) long-term planning applications (where repeated "looping" between t...

Enterprise PACS and image distribution.

PubMed

Huang, H K

2003-01-01

Around the world now, because of the need to improve operation efficiency and better cost effective healthcare, many large-scale healthcare enterprises have been formed. Each of these enterprises groups hospitals, medical centers, and clinics together as one enterprise healthcare network. The management of these enterprises recognizes the importance of using PACS and image distribution as a key technology in cost-effective healthcare delivery in the enterprise level. As a result, many large-scale enterprise level PACS/image distribution pilot studies, full design and implementation, are underway. The purpose of this paper is to provide readers an overall view of the current status of enterprise PACS and image distribution. reviews three large-scale enterprise PACS/image distribution systems in USA, Germany, and South Korean. The concept of enterprise level PACS/image distribution, its characteristics and ingredients are then discussed. Business models for enterprise level implementation available by the private medical imaging and system integration industry are highlighted. One current system under development in designing a healthcare enterprise level chest tuberculosis (TB) screening in Hong Kong is described in detail. Copyright 2002 Elsevier Science Ltd.

Solar microclimatology. [tables (data) on insolation for application to solar energy conversion by electric power plants

NASA Technical Reports Server (NTRS)

Mckenney, D. B.; Beauchamp, W. T.

1975-01-01

It has become apparent in recent years that solar energy can be used for electric power production by several methods. Because of the diffuse nature of the solar insolation, the area involved in any central power plant design can encompass several square miles. A detailed design of these large area collection systems will require precise knowledge of the local solar insolation. Detailed information will also be needed concerning the temporal nature of the insolation and the local spatial distribution. Therefore, insolation data was collected and analyzed for a network of sensors distributed over an area of several square kilometers in Arizona. The analyses of this data yielded probability distributions of cloud size, velocity, and direction of motion which were compared with data obtained from the National Weather Service. Microclimatological analyses were also performed for suitable modeling parameters pertinent to large scale electric power plant design. Instrumentation used to collect the data is described.

A self-scaling, distributed information architecture for public health, research, and clinical care.

PubMed

McMurry, Andrew J; Gilbert, Clint A; Reis, Ben Y; Chueh, Henry C; Kohane, Isaac S; Mandl, Kenneth D

2007-01-01

This study sought to define a scalable architecture to support the National Health Information Network (NHIN). This architecture must concurrently support a wide range of public health, research, and clinical care activities. The architecture fulfils five desiderata: (1) adopt a distributed approach to data storage to protect privacy, (2) enable strong institutional autonomy to engender participation, (3) provide oversight and transparency to ensure patient trust, (4) allow variable levels of access according to investigator needs and institutional policies, (5) define a self-scaling architecture that encourages voluntary regional collaborations that coalesce to form a nationwide network. Our model has been validated by a large-scale, multi-institution study involving seven medical centers for cancer research. It is the basis of one of four open architectures developed under funding from the Office of the National Coordinator of Health Information Technology, fulfilling the biosurveillance use case defined by the American Health Information Community. The model supports broad applicability for regional and national clinical information exchanges. This model shows the feasibility of an architecture wherein the requirements of care providers, investigators, and public health authorities are served by a distributed model that grants autonomy, protects privacy, and promotes participation.

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.

Lightweight and Statistical Techniques for Petascale Debugging: Correctness on Petascale Systems (CoPS) Preliminry Report

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

de Supinski, B R; Miller, B P; Liblit, B

2011-09-13

Petascale platforms with O(10{sup 5}) and O(10{sup 6}) processing cores are driving advancements in a wide range of scientific disciplines. These large systems create unprecedented application development challenges. Scalable correctness tools are critical to shorten the time-to-solution on these systems. Currently, many DOE application developers use primitive manual debugging based on printf or traditional debuggers such as TotalView or DDT. This paradigm breaks down beyond a few thousand cores, yet bugs often arise above that scale. Programmers must reproduce problems in smaller runs to analyze them with traditional tools, or else perform repeated runs at scale using only primitive techniques.more » Even when traditional tools run at scale, the approach wastes substantial effort and computation cycles. Continued scientific progress demands new paradigms for debugging large-scale applications. The Correctness on Petascale Systems (CoPS) project is developing a revolutionary debugging scheme that will reduce the debugging problem to a scale that human developers can comprehend. The scheme can provide precise diagnoses of the root causes of failure, including suggestions of the location and the type of errors down to the level of code regions or even a single execution point. Our fundamentally new strategy combines and expands three relatively new complementary debugging approaches. The Stack Trace Analysis Tool (STAT), a 2011 R&D 100 Award Winner, identifies behavior equivalence classes in MPI jobs and highlights behavior when elements of the class demonstrate divergent behavior, often the first indicator of an error. The Cooperative Bug Isolation (CBI) project has developed statistical techniques for isolating programming errors in widely deployed code that we will adapt to large-scale parallel applications. Finally, we are developing a new approach to parallelizing expensive correctness analyses, such as analysis of memory usage in the Memgrind tool. In the first two years of the project, we have successfully extended STAT to determine the relative progress of different MPI processes. We have shown that the STAT, which is now included in the debugging tools distributed by Cray with their large-scale systems, substantially reduces the scale at which traditional debugging techniques are applied. We have extended CBI to large-scale systems and developed new compiler based analyses that reduce its instrumentation overhead. Our results demonstrate that CBI can identify the source of errors in large-scale applications. Finally, we have developed MPIecho, a new technique that will reduce the time required to perform key correctness analyses, such as the detection of writes to unallocated memory. Overall, our research results are the foundations for new debugging paradigms that will improve application scientist productivity by reducing the time to determine which package or module contains the root cause of a problem that arises at all scales of our high end systems. While we have made substantial progress in the first two years of CoPS research, significant work remains. While STAT provides scalable debugging assistance for incorrect application runs, we could apply its techniques to assertions in order to observe deviations from expected behavior. Further, we must continue to refine STAT's techniques to represent behavioral equivalence classes efficiently as we expect systems with millions of threads in the next year. We are exploring new CBI techniques that can assess the likelihood that execution deviations from past behavior are the source of erroneous execution. Finally, we must develop usable correctness analyses that apply the MPIecho parallelization strategy in order to locate coding errors. We expect to make substantial progress on these directions in the next year but anticipate that significant work will remain to provide usable, scalable debugging paradigms.« less

Silver hake tracks changes in Northwest Atlantic circulation.

PubMed

Nye, Janet A; Joyce, Terrence M; Kwon, Young-Oh; Link, Jason S

2011-08-02

Recent studies documenting shifts in spatial distribution of many organisms in response to a warming climate highlight the need to understand the mechanisms underlying species distribution at large spatial scales. Here we present one noteworthy example of remote oceanographic processes governing the spatial distribution of adult silver hake, Merluccius bilinearis, a commercially important fish in the Northeast US shelf region. Changes in spatial distribution of silver hake over the last 40 years are highly correlated with the position of the Gulf Stream. These changes in distribution are in direct response to local changes in bottom temperature on the continental shelf that are responding to the same large scale circulation change affecting the Gulf Stream path, namely changes in the Atlantic meridional overturning circulation (AMOC). If the AMOC weakens, as is suggested by global climate models, silver hake distribution will remain in a poleward position, the extent to which could be forecast at both decadal and multidecadal scales.

A decentralized training algorithm for Echo State Networks in distributed big data applications.

PubMed

Scardapane, Simone; Wang, Dianhui; Panella, Massimo

2016-06-01

The current big data deluge requires innovative solutions for performing efficient inference on large, heterogeneous amounts of information. Apart from the known challenges deriving from high volume and velocity, real-world big data applications may impose additional technological constraints, including the need for a fully decentralized training architecture. While several alternatives exist for training feed-forward neural networks in such a distributed setting, less attention has been devoted to the case of decentralized training of recurrent neural networks (RNNs). In this paper, we propose such an algorithm for a class of RNNs known as Echo State Networks. The algorithm is based on the well-known Alternating Direction Method of Multipliers optimization procedure. It is formulated only in terms of local exchanges between neighboring agents, without reliance on a coordinating node. Additionally, it does not require the communication of training patterns, which is a crucial component in realistic big data implementations. Experimental results on large scale artificial datasets show that it compares favorably with a fully centralized implementation, in terms of speed, efficiency and generalization accuracy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Turbulent Channel Flow Measurements with a Nano-scale Thermal Anemometry Probe

NASA Astrophysics Data System (ADS)

Bailey, Sean; Witte, Brandon

2014-11-01

Using a Nano-scale Thermal Anemometry Probe (NSTAP), streamwise velocity was measured in a turbulent channel flow wind tunnel at Reynolds numbers ranging from Reτ = 500 to Reτ = 4000 . Use of these probes results in the a sensing-length-to-viscous-length-scale ratio of just 5 at the highest Reynolds number measured. Thus measured results can be considered free of spatial filtering effects. Point statistics are compared to recently published DNS and LDV data at similar Reynolds numbers and the results are found to be in good agreement. However, comparison of the measured spectra provide further evidence of aliasing at long wavelengths due to application of Taylor's frozen flow hypothesis, with increased aliasing evident with increasing Reynolds numbers. In addition to conventional point statistics, the dissipative scales of turbulence are investigated with focus on the wall-dependent scaling. Results support the existence of a universal pdf distribution of these scales once scaled to account for large-scale anisotropy. This research is supported by KSEF Award KSEF-2685-RDE-015.

Effect of extreme data loss on heart rate signals quantified by entropy analysis

NASA Astrophysics Data System (ADS)

Li, Yu; Wang, Jun; Li, Jin; Liu, Dazhao

2015-02-01

The phenomenon of data loss always occurs in the analysis of large databases. Maintaining the stability of analysis results in the event of data loss is very important. In this paper, we used a segmentation approach to generate a synthetic signal that is randomly wiped from data according to the Gaussian distribution and the exponential distribution of the original signal. Then, the logistic map is used as verification. Finally, two methods of measuring entropy-base-scale entropy and approximate entropy-are comparatively analyzed. Our results show the following: (1) Two key parameters-the percentage and the average length of removed data segments-can change the sequence complexity according to logistic map testing. (2) The calculation results have preferable stability for base-scale entropy analysis, which is not sensitive to data loss. (3) The loss percentage of HRV signals should be controlled below the range (p = 30 %), which can provide useful information in clinical applications.

The Search for Efficiency in Arboreal Ray Tracing Applications

NASA Astrophysics Data System (ADS)

van Leeuwen, M.; Disney, M.; Chen, J. M.; Gomez-Dans, J.; Kelbe, D.; van Aardt, J. A.; Lewis, P.

2016-12-01

Forest structure significantly impacts a range of abiotic conditions, including humidity and the radiation regime, all of which affect the rate of net and gross primary productivity. Current forest productivity models typically consider abstract media to represent the transfer of radiation within the canopy. Examples include the representation forest structure via a layered canopy model, where leaf area and inclination angles are stratified with canopy depth, or as turbid media where leaves are randomly distributed within space or within confined geometric solids such as blocks, spheres or cones. While these abstract models are known to produce accurate estimates of primary productivity at the stand level, their limited geometric resolution restricts applicability at fine spatial scales, such as the cell, leaf or shoot levels, thereby not addressing the full potential of assimilation of data from laboratory and field measurements with that of remote sensing technology. Recent research efforts have explored the use of laser scanning to capture detailed tree morphology at millimeter accuracy. These data can subsequently be used to combine ray tracing with primary productivity models, providing an ability to explore trade-offs among different morphological traits or assimilate data from spatial scales, spanning the leaf- to the stand level. Ray tracing has a major advantage of allowing the most accurate structural description of the canopy, and can directly exploit new 3D structural measurements, e.g., from laser scanning. However, the biggest limitation of ray tracing models is their high computational cost, which currently limits their use for large-scale applications. In this talk, we explore ways to more efficiently exploit ray tracing simulations and capture this information in a readily computable form for future evaluation, thus potentially enabling large-scale first-principles forest growth modelling applications.

Three-Phase Time-Multiplexed Planar Power Transmission to Distributed Implants.

PubMed

Lee, Byunghun; Ahn, Dukju; Ghovanloo, Maysam

2016-03-01

A platform has been presented for wireless powering of receivers (Rx's) that are arbitrarily distributed over a large area. A potential application could be powering of small Rx implants, distributed over large areas of the brain. The transmitter (Tx) consists of three overlapping layers of hexagonal planar spiral coils (hex-PSC) that are horizontally shifted to provide the strongest and most homogeneous electromagnetic flux coverage. The three-layer hex-PSC array is driven by a three-phase time-division-multiplexed power Tx that takes the advantage of the carrier phase shift, coil geometries, and Rx time constant to homogeneously power the arbitrarily distributed Rx's regardless of their misalignments. The functionality of the proposed three-phase power transmission concept has been verified in a detailed scaled-up high-frequency structure simulator Advanced Design System simulation model and measurement setup, and compared with a conventional Tx. The new Tx delivers 5.4 mW to each Rx and achieves, on average, 5.8% power transfer efficiency to the Rx at the worst case 90° angular misalignment, compared with 1.4% by the conventional Tx.

Improving Assimilated Global Data Sets using TMI Rainfall and Columnar Moisture Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.

1999-01-01

A global analysis that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. In this study, we show that assimilating precipitation and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). In particular, assimilating TMI rain improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. The improved analysis also improves short-range forecasts in the tropics. Ensemble forecasts initialized with the GEOS analysis incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day and better 500 hPa geopotential height forecasts up to 5 days. Results of this study demonstrate the potential of using high-quality space-borne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications

A Development of Lightweight Grid Interface

NASA Astrophysics Data System (ADS)

Iwai, G.; Kawai, Y.; Sasaki, T.; Watase, Y.

2011-12-01

In order to help a rapid development of Grid/Cloud aware applications, we have developed API to abstract the distributed computing infrastructures based on SAGA (A Simple API for Grid Applications). SAGA, which is standardized in the OGF (Open Grid Forum), defines API specifications to access distributed computing infrastructures, such as Grid, Cloud and local computing resources. The Universal Grid API (UGAPI), which is a set of command line interfaces (CLI) and APIs, aims to offer simpler API to combine several SAGA interfaces with richer functionalities. These CLIs of the UGAPI offer typical functionalities required by end users for job management and file access to the different distributed computing infrastructures as well as local computing resources. We have also built a web interface for the particle therapy simulation and demonstrated the large scale calculation using the different infrastructures at the same time. In this paper, we would like to present how the web interface based on UGAPI and SAGA achieve more efficient utilization of computing resources over the different infrastructures with technical details and practical experiences.

Analysis of labor productivity using large-scale data of firm's financial statements

NASA Astrophysics Data System (ADS)

Ikeda, Y.; Souma, W.; Aoyama, H.; Fujiwara, Y.; Iyetomi, H.

2010-08-01

We investigated labor productivity distribution by analyzing large-scale financial statement data consisting of listed and unlisted Japanese firms to clarify the characteristics of the Japanese labor market. Both high and low productivity sides of the labor productivity distribution follows the power-law distribution. Large inequality in the low productivity side was observed only for the manufacturing sectors in Japan fiscal year (JFY) 1999 and observed for both the manufacturing and non-manufacturing sectors in JFY 2002. The decline in the Japanese GDP in JFY 1999 and JFY 2002 were coincided with the large inequality in the low productivity side of the distribution. A lower peak was found for all non-manufacturing sectors. This might be the origin of the low productivity of the non-manufacturing sectors reported in recent economic studies.

Large-Scale Geographic Variation in Distribution and Abundance of Australian Deep-Water Kelp Forests

PubMed Central

Marzinelli, Ezequiel M.; Williams, Stefan B.; Babcock, Russell C.; Barrett, Neville S.; Johnson, Craig R.; Jordan, Alan; Kendrick, Gary A.; Pizarro, Oscar R.; Smale, Dan A.; Steinberg, Peter D.

2015-01-01

Despite the significance of marine habitat-forming organisms, little is known about their large-scale distribution and abundance in deeper waters, where they are difficult to access. Such information is necessary to develop sound conservation and management strategies. Kelps are main habitat-formers in temperate reefs worldwide; however, these habitats are highly sensitive to environmental change. The kelp Ecklonia radiate is the major habitat-forming organism on subtidal reefs in temperate Australia. Here, we provide large-scale ecological data encompassing the latitudinal distribution along the continent of these kelp forests, which is a necessary first step towards quantitative inferences about the effects of climatic change and other stressors on these valuable habitats. We used the Autonomous Underwater Vehicle (AUV) facility of Australia’s Integrated Marine Observing System (IMOS) to survey 157,000 m2 of seabed, of which ca 13,000 m2 were used to quantify kelp covers at multiple spatial scales (10–100 m to 100–1,000 km) and depths (15–60 m) across several regions ca 2–6° latitude apart along the East and West coast of Australia. We investigated the large-scale geographic variation in distribution and abundance of deep-water kelp (>15 m depth) and their relationships with physical variables. Kelp cover generally increased with latitude despite great variability at smaller spatial scales. Maximum depth of kelp occurrence was 40–50 m. Kelp latitudinal distribution along the continent was most strongly related to water temperature and substratum availability. This extensive survey data, coupled with ongoing AUV missions, will allow for the detection of long-term shifts in the distribution and abundance of habitat-forming kelp and the organisms they support on a continental scale, and provide information necessary for successful implementation and management of conservation reserves. PMID:25693066

Task Assignment Heuristics for Distributed CFD Applications

NASA Technical Reports Server (NTRS)

Lopez-Benitez, N.; Djomehri, M. J.; Biswas, R.; Biegel, Bryan (Technical Monitor)

2001-01-01

CFD applications require high-performance computational platforms: 1. Complex physics and domain configuration demand strongly coupled solutions; 2. Applications are CPU and memory intensive; and 3. Huge resource requirements can only be satisfied by teraflop-scale machines or distributed computing.

Requirements for migration of NSSD code systems from LTSS to NLTSS

NASA Technical Reports Server (NTRS)

Pratt, M.

1984-01-01

The purpose of this document is to address the requirements necessary for a successful conversion of the Nuclear Design (ND) application code systems to the NLTSS environment. The ND application code system community can be characterized as large-scale scientific computation carried out on supercomputers. NLTSS is a distributed operating system being developed at LLNL to replace the LTSS system currently in use. The implications of change are examined including a description of the computational environment and users in ND. The discussion then turns to requirements, first in a general way, followed by specific requirements, including a proposal for managing the transition.

Large-scale atomistic simulations of helium-3 bubble growth in complex palladium alloys

DOE PAGES

Hale, Lucas M.; Zimmerman, Jonathan A.; Wong, Bryan M.

2016-05-18

Palladium is an attractive material for hydrogen and hydrogen-isotope storage applications due to its properties of large storage density and high diffusion of lattice hydrogen. When considering tritium storage, the material’s structural and mechanical integrity is threatened by both the embrittlement effect of hydrogen and the creation and evolution of additional crystal defects (e.g., dislocations, stacking faults) caused by the formation and growth of helium-3 bubbles. Using recently developed inter-atomic potentials for the palladium-silver-hydrogen system, we perform large-scale atomistic simulations to examine the defect-mediated mechanisms that govern helium bubble growth. Our simulations show the evolution of a distribution of materialmore » defects, and we compare the material behavior displayed with expectations from experiment and theory. In conclusion, we also present density functional theory calculations to characterize ideal tensile and shear strengths for these materials, which enable the understanding of how and why our developed potentials either meet or confound these expectations.« less

Data-Driven Simulation-Enhanced Optimization of People-Based Print Production Service

NASA Astrophysics Data System (ADS)

Rai, Sudhendu

This paper describes a systematic six-step data-driven simulation-based methodology for optimizing people-based service systems on a large distributed scale that exhibit high variety and variability. The methodology is exemplified through its application within the printing services industry where it has been successfully deployed by Xerox Corporation across small, mid-sized and large print shops generating over 250 million in profits across the customer value chain. Each step of the methodology consisting of innovative concepts co-development and testing in partnership with customers, development of software and hardware tools to implement the innovative concepts, establishment of work-process and practices for customer-engagement and service implementation, creation of training and infrastructure for large scale deployment, integration of the innovative offering within the framework of existing corporate offerings and lastly the monitoring and deployment of the financial and operational metrics for estimating the return-on-investment and the continual renewal of the offering are described in detail.

Advanced Optical Burst Switched Network Concepts

NASA Astrophysics Data System (ADS)

Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

In recent years, as the bandwidth and the speed of networks have increased significantly, a new generation of network-based applications using the concept of distributed computing and collaborative services is emerging (e.g., Grid computing applications). The use of the available fiber and DWDM infrastructure for these applications is a logical choice offering huge amounts of cheap bandwidth and ensuring global reach of computing resources [230]. Currently, there is a great deal of interest in deploying optical circuit (wavelength) switched network infrastructure for distributed computing applications that require long-lived wavelength paths and address the specific needs of a small number of well-known users. Typical users are particle physicists who, due to their international collaborations and experiments, generate enormous amounts of data (Petabytes per year). These users require a network infrastructures that can support processing and analysis of large datasets through globally distributed computing resources [230]. However, providing wavelength granularity bandwidth services is not an efficient and scalable solution for applications and services that address a wider base of user communities with different traffic profiles and connectivity requirements. Examples of such applications may be: scientific collaboration in smaller scale (e.g., bioinformatics, environmental research), distributed virtual laboratories (e.g., remote instrumentation), e-health, national security and defense, personalized learning environments and digital libraries, evolving broadband user services (i.e., high resolution home video editing, real-time rendering, high definition interactive TV). As a specific example, in e-health services and in particular mammography applications due to the size and quantity of images produced by remote mammography, stringent network requirements are necessary. Initial calculations have shown that for 100 patients to be screened remotely, the network would have to securely transport 1.2 GB of data every 30 s [230]. According to the above explanation it is clear that these types of applications need a new network infrastructure and transport technology that makes large amounts of bandwidth at subwavelength granularity, storage, computation, and visualization resources potentially available to a wide user base for specified time durations. As these types of collaborative and network-based applications evolve addressing a wide range and large number of users, it is infeasible to build dedicated networks for each application type or category. Consequently, there should be an adaptive network infrastructure able to support all application types, each with their own access, network, and resource usage patterns. This infrastructure should offer flexible and intelligent network elements and control mechanism able to deploy new applications quickly and efficiently.

A Computational framework for telemedicine.

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

Foster, I.; von Laszewski, G.; Thiruvathukal, G. K.

1998-07-01

Emerging telemedicine applications require the ability to exploit diverse and geographically distributed resources. Highspeed networks are used to integrate advanced visualization devices, sophisticated instruments, large databases, archival storage devices, PCs, workstations, and supercomputers. This form of telemedical environment is similar to networked virtual supercomputers, also known as metacomputers. Metacomputers are already being used in many scientific application areas. In this article, we analyze requirements necessary for a telemedical computing infrastructure and compare them with requirements found in a typical metacomputing environment. We will show that metacomputing environments can be used to enable a more powerful and unified computational infrastructure formore » telemedicine. The Globus metacomputing toolkit can provide the necessary low level mechanisms to enable a large scale telemedical infrastructure. The Globus toolkit components are designed in a modular fashion and can be extended to support the specific requirements for telemedicine.« less

Mapping Submarine Groundwater Discharge - how to investigate spatial discharge variability on coastal and beach scales

NASA Astrophysics Data System (ADS)

Stieglitz, T. C.; Burnett, W. C.; Rapaglia, J.

2008-12-01

Submarine groundwater discharge (SGD) is now increasingly recognized as an important component in the water balance, water quality and ecology of the coastal zone. A multitude of methods are currently employed to study SGD, ranging from point flux measurements with seepage meters to methods integrating over various spatial and temporal scales such as hydrological models, geophysical techniques or surface water tracer approaches. From studies in a large variety of hydrogeological settings, researchers in this field have come to expect that SGD is rarely uniformly distributed. Here we discuss the application of: (a) the mapping of subsurface electrical conductivity in a discharge zone on a beach; and (b) the large-scale mapping of radon in coastal surface water to improving our understanding of SGD and its spatial variability. On a beach scale, as part of intercomparison studies of a UNESCO/IAEA working group, mapping of subsurface electrical conductivity in a beach face have elucidated the non-uniform distribution of SGD associated with rock fractures, volcanic settings and man-made structures (e.g., piers, jetties). Variations in direct point measurements of SGD flux with seepage meters were linked to the subsurface conductivity distribution. We demonstrate how the combination of these two techniques may complement one another to better constrain SGD measurements. On kilometer to hundred kilometer scales, the spatial distribution and regional importance of SGD can be investigated by mapping relevant tracers in the coastal ocean. The radon isotope Rn-222 is a commonly used tracer for SGD investigations due to its significant enrichment in groundwater, and continuous mapping of this tracer, in combination with ocean water salinity, can be used to efficiently infer locations of SGD along a coastline on large scales. We use a surface-towed, continuously recording multi-detector setup installed on a moving vessel. This tool was used in various coastal environments, e.g. in Florida, Brazil, Mauritius and Australia's Great Barrier Reef lagoon. From shore-parallel transects along the Central Great Barrier Reef coastline, numerous processes and locations of SGD were identified, including terrestrially-derived fresh SGD and the recirculation of seawater in mangrove forests, as well as riverine sources. From variations in the inverse relationship of the two tracers radon and salinity, some aspects of regional freshwater input into the lagoon during the tropical wet season could be assessed. Such surveys on coastal scales can be a useful tool to obtain an overview of locations and processes of SGD on an unknown coastline.

Portable parallel stochastic optimization for the design of aeropropulsion components

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Rhodes, G. S.

1994-01-01

This report presents the results of Phase 1 research to develop a methodology for performing large-scale Multi-disciplinary Stochastic Optimization (MSO) for the design of aerospace systems ranging from aeropropulsion components to complete aircraft configurations. The current research recognizes that such design optimization problems are computationally expensive, and require the use of either massively parallel or multiple-processor computers. The methodology also recognizes that many operational and performance parameters are uncertain, and that uncertainty must be considered explicitly to achieve optimum performance and cost. The objective of this Phase 1 research was to initialize the development of an MSO methodology that is portable to a wide variety of hardware platforms, while achieving efficient, large-scale parallelism when multiple processors are available. The first effort in the project was a literature review of available computer hardware, as well as review of portable, parallel programming environments. The first effort was to implement the MSO methodology for a problem using the portable parallel programming language, Parallel Virtual Machine (PVM). The third and final effort was to demonstrate the example on a variety of computers, including a distributed-memory multiprocessor, a distributed-memory network of workstations, and a single-processor workstation. Results indicate the MSO methodology can be well-applied towards large-scale aerospace design problems. Nearly perfect linear speedup was demonstrated for computation of optimization sensitivity coefficients on both a 128-node distributed-memory multiprocessor (the Intel iPSC/860) and a network of workstations (speedups of almost 19 times achieved for 20 workstations). Very high parallel efficiencies (75 percent for 31 processors and 60 percent for 50 processors) were also achieved for computation of aerodynamic influence coefficients on the Intel. Finally, the multi-level parallelization strategy that will be needed for large-scale MSO problems was demonstrated to be highly efficient. The same parallel code instructions were used on both platforms, demonstrating portability. There are many applications for which MSO can be applied, including NASA's High-Speed-Civil Transport, and advanced propulsion systems. The use of MSO will reduce design and development time and testing costs dramatically.

Laser SRS tracker for reverse prototyping tasks

NASA Astrophysics Data System (ADS)

Kolmakov, Egor; Redka, Dmitriy; Grishkanich, Aleksandr; Tsvetkov, Konstantin

2017-10-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of chip and microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

Ceramic Integration Technologies for Advanced Energy Systems: Critical Needs, Technical Challenges, and Opportunities

NASA Technical Reports Server (NTRS)

Singh, Mrityunjay

2010-01-01

Advanced ceramic integration technologies dramatically impact the energy landscape due to wide scale application of ceramics in all aspects of alternative energy production, storage, distribution, conservation, and efficiency. Examples include fuel cells, thermoelectrics, photovoltaics, gas turbine propulsion systems, distribution and transmission systems based on superconductors, nuclear power generation and waste disposal. Ceramic integration technologies play a key role in fabrication and manufacturing of large and complex shaped parts with multifunctional properties. However, the development of robust and reliable integrated systems with optimum performance requires the understanding of many thermochemical and thermomechanical factors, particularly for high temperature applications. In this presentation, various needs, challenges, and opportunities in design, fabrication, and testing of integrated similar (ceramic ceramic) and dissimilar (ceramic metal) material www.nasa.gov 45 ceramic-ceramic-systems have been discussed. Experimental results for bonding and integration of SiC based Micro-Electro-Mechanical-Systems (MEMS) LDI fuel injector and advanced ceramics and composites for gas turbine applications are presented.

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.

Scaling laws and fluctuations in the statistics of word frequencies

NASA Astrophysics Data System (ADS)

Gerlach, Martin; Altmann, Eduardo G.

2014-11-01

In this paper, we combine statistical analysis of written texts and simple stochastic models to explain the appearance of scaling laws in the statistics of word frequencies. The average vocabulary of an ensemble of fixed-length texts is known to scale sublinearly with the total number of words (Heaps’ law). Analyzing the fluctuations around this average in three large databases (Google-ngram, English Wikipedia, and a collection of scientific articles), we find that the standard deviation scales linearly with the average (Taylor's law), in contrast to the prediction of decaying fluctuations obtained using simple sampling arguments. We explain both scaling laws (Heaps’ and Taylor) by modeling the usage of words using a Poisson process with a fat-tailed distribution of word frequencies (Zipf's law) and topic-dependent frequencies of individual words (as in topic models). Considering topical variations lead to quenched averages, turn the vocabulary size a non-self-averaging quantity, and explain the empirical observations. For the numerous practical applications relying on estimations of vocabulary size, our results show that uncertainties remain large even for long texts. We show how to account for these uncertainties in measurements of lexical richness of texts with different lengths.

Landscape-scale distribution and density of raptor populations wintering in anthropogenic-dominated desert landscapes

Treesearch

Adam E. Duerr; Tricia A. Miller; Kerri L. Cornell Duerr; Michael J. Lanzone; Amy Fesnock; Todd E. Katzner

2015-01-01

Anthropogenic development has great potential to affect fragile desert environments. Large-scale development of renewable energy infrastructure is planned for many desert ecosystems. Development plans should account for anthropogenic effects to distributions and abundance of rare or sensitive wildlife; however, baseline data on abundance and distribution of such...

Large Scale Density Estimation of Blue and Fin Whales (LSD)

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...sensors, or both. The goal of this research is to develop and implement a new method for estimating blue and fin whale density that is effective over...develop and implement a density estimation methodology for quantifying blue and fin whale abundance from passive acoustic data recorded on sparse

VisIO: enabling interactive visualization of ultra-scale, time-series data via high-bandwidth distributed I/O systems

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

Mitchell, Christopher J; Ahrens, James P; Wang, Jun

2010-10-15

Petascale simulations compute at resolutions ranging into billions of cells and write terabytes of data for visualization and analysis. Interactive visuaUzation of this time series is a desired step before starting a new run. The I/O subsystem and associated network often are a significant impediment to interactive visualization of time-varying data; as they are not configured or provisioned to provide necessary I/O read rates. In this paper, we propose a new I/O library for visualization applications: VisIO. Visualization applications commonly use N-to-N reads within their parallel enabled readers which provides an incentive for a shared-nothing approach to I/O, similar tomore » other data-intensive approaches such as Hadoop. However, unlike other data-intensive applications, visualization requires: (1) interactive performance for large data volumes, (2) compatibility with MPI and POSIX file system semantics for compatibility with existing infrastructure, and (3) use of existing file formats and their stipulated data partitioning rules. VisIO, provides a mechanism for using a non-POSIX distributed file system to provide linear scaling of 110 bandwidth. In addition, we introduce a novel scheduling algorithm that helps to co-locate visualization processes on nodes with the requested data. Testing using VisIO integrated into Para View was conducted using the Hadoop Distributed File System (HDFS) on TACC's Longhorn cluster. A representative dataset, VPIC, across 128 nodes showed a 64.4% read performance improvement compared to the provided Lustre installation. Also tested, was a dataset representing a global ocean salinity simulation that showed a 51.4% improvement in read performance over Lustre when using our VisIO system. VisIO, provides powerful high-performance I/O services to visualization applications, allowing for interactive performance with ultra-scale, time-series data.« less

Efficient feature extraction from wide-area motion imagery by MapReduce in Hadoop

NASA Astrophysics Data System (ADS)

Cheng, Erkang; Ma, Liya; Blaisse, Adam; Blasch, Erik; Sheaff, Carolyn; Chen, Genshe; Wu, Jie; Ling, Haibin

2014-06-01

Wide-Area Motion Imagery (WAMI) feature extraction is important for applications such as target tracking, traffic management and accident discovery. With the increasing amount of WAMI collections and feature extraction from the data, a scalable framework is needed to handle the large amount of information. Cloud computing is one of the approaches recently applied in large scale or big data. In this paper, MapReduce in Hadoop is investigated for large scale feature extraction tasks for WAMI. Specifically, a large dataset of WAMI images is divided into several splits. Each split has a small subset of WAMI images. The feature extractions of WAMI images in each split are distributed to slave nodes in the Hadoop system. Feature extraction of each image is performed individually in the assigned slave node. Finally, the feature extraction results are sent to the Hadoop File System (HDFS) to aggregate the feature information over the collected imagery. Experiments of feature extraction with and without MapReduce are conducted to illustrate the effectiveness of our proposed Cloud-Enabled WAMI Exploitation (CAWE) approach.

Optical interconnect for large-scale systems

NASA Astrophysics Data System (ADS)

Dress, William

2013-02-01

This paper presents a switchless, optical interconnect module that serves as a node in a network of identical distribution modules for large-scale systems. Thousands to millions of hosts or endpoints may be interconnected by a network of such modules, avoiding the need for multi-level switches. Several common network topologies are reviewed and their scaling properties assessed. The concept of message-flow routing is discussed in conjunction with the unique properties enabled by the optical distribution module where it is shown how top-down software control (global routing tables, spanning-tree algorithms) may be avoided.

On-board B-ISDN fast packet switching architectures. Phase 2: Development. Proof-of-concept architecture definition report

NASA Technical Reports Server (NTRS)

Shyy, Dong-Jye; Redman, Wayne

1993-01-01

For the next-generation packet switched communications satellite system with onboard processing and spot-beam operation, a reliable onboard fast packet switch is essential to route packets from different uplink beams to different downlink beams. The rapid emergence of point-to-point services such as video distribution, and the large demand for video conference, distributed data processing, and network management makes the multicast function essential to a fast packet switch (FPS). The satellite's inherent broadcast features gives the satellite network an advantage over the terrestrial network in providing multicast services. This report evaluates alternate multicast FPS architectures for onboard baseband switching applications and selects a candidate for subsequent breadboard development. Architecture evaluation and selection will be based on the study performed in phase 1, 'Onboard B-ISDN Fast Packet Switching Architectures', and other switch architectures which have become commercially available as large scale integration (LSI) devices.

Tail-scope: Using friends to estimate heavy tails of degree distributions in large-scale complex networks

NASA Astrophysics Data System (ADS)

Eom, Young-Ho; Jo, Hang-Hyun

2015-05-01

Many complex networks in natural and social phenomena have often been characterized by heavy-tailed degree distributions. However, due to rapidly growing size of network data and concerns on privacy issues about using these data, it becomes more difficult to analyze complete data sets. Thus, it is crucial to devise effective and efficient estimation methods for heavy tails of degree distributions in large-scale networks only using local information of a small fraction of sampled nodes. Here we propose a tail-scope method based on local observational bias of the friendship paradox. We show that the tail-scope method outperforms the uniform node sampling for estimating heavy tails of degree distributions, while the opposite tendency is observed in the range of small degrees. In order to take advantages of both sampling methods, we devise the hybrid method that successfully recovers the whole range of degree distributions. Our tail-scope method shows how structural heterogeneities of large-scale complex networks can be used to effectively reveal the network structure only with limited local information.

Uncertainty in determining extreme precipitation thresholds

NASA Astrophysics Data System (ADS)

Liu, Bingjun; Chen, Junfan; Chen, Xiaohong; Lian, Yanqing; Wu, Lili

2013-10-01

Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method are more reasonable and applicable for the Pearl River Basin.

An interactive web-based system using cloud for large-scale visual analytics

NASA Astrophysics Data System (ADS)

Kaseb, Ahmed S.; Berry, Everett; Rozolis, Erik; McNulty, Kyle; Bontrager, Seth; Koh, Youngsol; Lu, Yung-Hsiang; Delp, Edward J.

2015-03-01

Network cameras have been growing rapidly in recent years. Thousands of public network cameras provide tremendous amount of visual information about the environment. There is a need to analyze this valuable information for a better understanding of the world around us. This paper presents an interactive web-based system that enables users to execute image analysis and computer vision techniques on a large scale to analyze the data from more than 65,000 worldwide cameras. This paper focuses on how to use both the system's website and Application Programming Interface (API). Given a computer program that analyzes a single frame, the user needs to make only slight changes to the existing program and choose the cameras to analyze. The system handles the heterogeneity of the geographically distributed cameras, e.g. different brands, resolutions. The system allocates and manages Amazon EC2 and Windows Azure cloud resources to meet the analysis requirements.

Molecular clouds and the large-scale structure of the galaxy

NASA Technical Reports Server (NTRS)

Thaddeus, Patrick; Stacy, J. Gregory

1990-01-01

The application of molecular radio astronomy to the study of the large-scale structure of the Galaxy is reviewed and the distribution and characteristic properties of the Galactic population of Giant Molecular Clouds (GMCs), derived primarily from analysis of the Columbia CO survey, and their relation to tracers of Population 1 and major spiral features are described. The properties of the local molecular interstellar gas are summarized. The CO observing programs currently underway with the Center for Astrophysics 1.2 m radio telescope are described, with an emphasis on projects relevant to future comparison with high-energy gamma-ray observations. Several areas are discussed in which high-energy gamma-ray observations by the EGRET (Energetic Gamma-Ray Experiment Telescope) experiment aboard the Gamma Ray Observatory will directly complement radio studies of the Milky Way, with the prospect of significant progress on fundamental issues related to the structure and content of the Galaxy.

Application of Time Series Insar Technique for Deformation Monitoring of Large-Scale Landslides in Mountainous Areas of Western China

NASA Astrophysics Data System (ADS)

Qu, T.; Lu, P.; Liu, C.; Wan, H.

2016-06-01

Western China is very susceptible to landslide hazards. As a result, landslide detection and early warning are of great importance. This work employs the SBAS (Small Baseline Subset) InSAR Technique for detection and monitoring of large-scale landslides that occurred in Li County, Sichuan Province, Western China. The time series INSAR is performed using descending scenes acquired from TerraSAR-X StripMap mode since 2014 to get the spatial distribution of surface displacements of this giant landslide. The time series results identify the distinct deformation zone on the landslide body with a rate of up to 150mm/yr. The deformation acquired by SBAS technique is validated by inclinometers from diverse boreholes of in-situ monitoring. The integration of InSAR time series displacements and ground-based monitoring data helps to provide reliable data support for the forecasting and monitoring of largescale landslide.

Non-classical photon correlation in a two-dimensional photonic lattice.

PubMed

Gao, Jun; Qiao, Lu-Feng; Lin, Xiao-Feng; Jiao, Zhi-Qiang; Feng, Zhen; Zhou, Zheng; Gao, Zhen-Wei; Xu, Xiao-Yun; Chen, Yuan; Tang, Hao; Jin, Xian-Min

2016-06-13

Quantum interference and quantum correlation, as two main features of quantum optics, play an essential role in quantum information applications, such as multi-particle quantum walk and boson sampling. While many experimental demonstrations have been done in one-dimensional waveguide arrays, it remains unexplored in higher dimensions due to tight requirement of manipulating and detecting photons in large-scale. Here, we experimentally observe non-classical correlation of two identical photons in a fully coupled two-dimensional structure, i.e. photonic lattice manufactured by three-dimensional femtosecond laser writing. Photon interference consists of 36 Hong-Ou-Mandel interference and 9 bunching. The overlap between measured and simulated distribution is up to 0.890 ± 0.001. Clear photon correlation is observed in the two-dimensional photonic lattice. Combining with controllably engineered disorder, our results open new perspectives towards large-scale implementation of quantum simulation on integrated photonic chips.

The topology of large-scale structure. I - Topology and the random phase hypothesis. [galactic formation models

NASA Technical Reports Server (NTRS)

Weinberg, David H.; Gott, J. Richard, III; Melott, Adrian L.

1987-01-01

Many models for the formation of galaxies and large-scale structure assume a spectrum of random phase (Gaussian), small-amplitude density fluctuations as initial conditions. In such scenarios, the topology of the galaxy distribution on large scales relates directly to the topology of the initial density fluctuations. Here a quantitative measure of topology - the genus of contours in a smoothed density distribution - is described and applied to numerical simulations of galaxy clustering, to a variety of three-dimensional toy models, and to a volume-limited sample of the CfA redshift survey. For random phase distributions the genus of density contours exhibits a universal dependence on threshold density. The clustering simulations show that a smoothing length of 2-3 times the mass correlation length is sufficient to recover the topology of the initial fluctuations from the evolved galaxy distribution. Cold dark matter and white noise models retain a random phase topology at shorter smoothing lengths, but massive neutrino models develop a cellular topology.

States of mind: Emotions, body feelings, and thoughts share distributed neural networks

PubMed Central

Oosterwijk, Suzanne; Lindquist, Kristen A.; Anderson, Eric; Dautoff, Rebecca; Moriguchi, Yoshiya; Barrett, Lisa Feldman

2012-01-01

Scientists have traditionally assumed that different kinds of mental states (e.g., fear, disgust, love, memory, planning, concentration, etc.) correspond to different psychological faculties that have domain-specific correlates in the brain. Yet, growing evidence points to the constructionist hypothesis that mental states emerge from the combination of domain-general psychological processes that map to large-scale distributed brain networks. In this paper, we report a novel study testing a constructionist model of the mind in which participants generated three kinds of mental states (emotions, body feelings, or thoughts) while we measured activity within large-scale distributed brain networks using fMRI. We examined the similarity and differences in the pattern of network activity across these three classes of mental states. Consistent with a constructionist hypothesis, a combination of large-scale distributed networks contributed to emotions, thoughts, and body feelings, although these mental states differed in the relative contribution of those networks. Implications for a constructionist functional architecture of diverse mental states are discussed. PMID:22677148

A Grid Infrastructure for Supporting Space-based Science Operations

NASA Technical Reports Server (NTRS)

Bradford, Robert N.; Redman, Sandra H.; McNair, Ann R. (Technical Monitor)

2002-01-01

Emerging technologies for computational grid infrastructures have the potential for revolutionizing the way computers are used in all aspects of our lives. Computational grids are currently being implemented to provide a large-scale, dynamic, and secure research and engineering environments based on standards and next-generation reusable software, enabling greater science and engineering productivity through shared resources and distributed computing for less cost than traditional architectures. Combined with the emerging technologies of high-performance networks, grids provide researchers, scientists and engineers the first real opportunity for an effective distributed collaborative environment with access to resources such as computational and storage systems, instruments, and software tools and services for the most computationally challenging applications.

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

DOE PAGES

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De; ...

2017-01-28

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

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

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Snow stratigraphic heterogeneity within ground-based passive microwave radiometer footprints: Implications for emission modeling

NASA Astrophysics Data System (ADS)

Rutter, Nick; Sandells, Mel; Derksen, Chris; Toose, Peter; Royer, Alain; Montpetit, Benoit; Langlois, Alex; Lemmetyinen, Juha; Pulliainen, Jouni

2014-03-01

Two-dimensional measurements of snowpack properties (stratigraphic layering, density, grain size, and temperature) were used as inputs to the multilayer Helsinki University of Technology (HUT) microwave emission model at a centimeter-scale horizontal resolution, across a 4.5 m transect of ground-based passive microwave radiometer footprints near Churchill, Manitoba, Canada. Snowpack stratigraphy was complex (between six and eight layers) with only three layers extending continuously throughout the length of the transect. Distributions of one-dimensional simulations, accurately representing complex stratigraphic layering, were evaluated using measured brightness temperatures. Large biases (36 to 68 K) between simulated and measured brightness temperatures were minimized (-0.5 to 0.6 K), within measurement accuracy, through application of grain scaling factors (2.6 to 5.3) at different combinations of frequencies, polarizations, and model extinction coefficients. Grain scaling factors compensated for uncertainty relating optical specific surface area to HUT effective grain size inputs and quantified relative differences in scattering and absorption properties of various extinction coefficients. The HUT model required accurate representation of ice lenses, particularly at horizontal polarization, and large grain scaling factors highlighted the need to consider microstructure beyond the size of individual grains. As variability of extinction coefficients was strongly influenced by the proportion of large (hoar) grains in a vertical profile, it is important to consider simulations from distributions of one-dimensional profiles rather than single profiles, especially in sub-Arctic snowpacks where stratigraphic variability can be high. Model sensitivity experiments suggested that the level of error in field measurements and the new methodological framework used to apply them in a snow emission model were satisfactory. Layer amalgamation showed that a three-layer representation of snowpack stratigraphy reduced the bias of a one-layer representation by about 50%.

Selectivity by host plants affects the distribution of arbuscular mycorrhizal fungi: evidence from ITS rDNA sequence metadata.

PubMed

Yang, Haishui; Zang, Yanyan; Yuan, Yongge; Tang, Jianjun; Chen, Xin

2012-04-12

Arbuscular mycorrhizal fungi (AMF) can form obligate symbioses with the vast majority of land plants, and AMF distribution patterns have received increasing attention from researchers. At the local scale, the distribution of AMF is well documented. Studies at large scales, however, are limited because intensive sampling is difficult. Here, we used ITS rDNA sequence metadata obtained from public databases to study the distribution of AMF at continental and global scales. We also used these sequence metadata to investigate whether host plant is the main factor that affects the distribution of AMF at large scales. We defined 305 ITS virtual taxa (ITS-VTs) among all sequences of the Glomeromycota by using a comprehensive maximum likelihood phylogenetic analysis. Each host taxonomic order averaged about 53% specific ITS-VTs, and approximately 60% of the ITS-VTs were host specific. Those ITS-VTs with wide host range showed wide geographic distribution. Most ITS-VTs occurred in only one type of host functional group. The distributions of most ITS-VTs were limited across ecosystem, across continent, across biogeographical realm, and across climatic zone. Non-metric multidimensional scaling analysis (NMDS) showed that AMF community composition differed among functional groups of hosts, and among ecosystem, continent, biogeographical realm, and climatic zone. The Mantel test showed that AMF community composition was significantly correlated with plant community composition among ecosystem, among continent, among biogeographical realm, and among climatic zone. The structural equation modeling (SEM) showed that the effects of ecosystem, continent, biogeographical realm, and climatic zone were mainly indirect on AMF distribution, but plant had strongly direct effects on AMF. The distribution of AMF as indicated by ITS rDNA sequences showed a pattern of high endemism at large scales. This pattern indicates high specificity of AMF for host at different scales (plant taxonomic order and functional group) and high selectivity from host plants for AMF. The effects of ecosystemic, biogeographical, continental and climatic factors on AMF distribution might be mediated by host plants.

Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network.

PubMed

Yoon, Young; Kim, Beom Heyn

2016-01-01

Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users.

Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network

PubMed Central

Kim, Beom Heyn

2016-01-01

Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users. PMID:27367610

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2011-08-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3" (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2010-09-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting a very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TGR only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3'' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Finite-element analysis of transverse compressive and thermal loads on Nb 3Sn wires with voids

DOE PAGES

Zhai, Y.; D'Hauthuille, L.; Barth, C.; ...

2016-02-29

High-field superconducting magnets play a very important role in many large-scale physics experiments, particularly particle colliders and fusion confinement devices such as Large Hadron Collider (LHC) and International Thermonuclear Experimental Reactor (ITER). The two most common superconductors used in these applications are NbTi and Nb 3Sn. Nb 3Sn wires are favored because of their significantly higher J c (critical current density) for higher field applications. The main disadvantage of Nb 3Sn is that the superconducting performance of the wire is highly strain sensitive and it is very brittle. This strain sensitivity is strongly influenced by two factors: plasticity and crackedmore » filaments. Cracks are induced by large stress concentrators that can be traced to the presence of voids in the wire. We develop detailed 2-D and 3-D finite-element models containing wire filaments and different possible distributions of voids in a bronze-route Nb 3Sn wire. We apply compressive transverse loads for various cases of void distributions to simulate the stress and strain response of a Nb 3Sn wire under the Lorentz force. Furthermore, this paper improves our understanding of the effect voids have on the Nb 3Sn wire's mechanical properties, and in so, the connection between the distribution of voids and performance degradation such as the correlation between irreversible strain limit and the void-induced local stress concentrations.« less

THE VIRTUAL INSTRUMENT: SUPPORT FOR GRID-ENABLED MCELL SIMULATIONS

PubMed Central

Casanova, Henri; Berman, Francine; Bartol, Thomas; Gokcay, Erhan; Sejnowski, Terry; Birnbaum, Adam; Dongarra, Jack; Miller, Michelle; Ellisman, Mark; Faerman, Marcio; Obertelli, Graziano; Wolski, Rich; Pomerantz, Stuart; Stiles, Joel

2010-01-01

Ensembles of widely distributed, heterogeneous resources, or Grids, have emerged as popular platforms for large-scale scientific applications. In this paper we present the Virtual Instrument project, which provides an integrated application execution environment that enables end-users to run and interact with running scientific simulations on Grids. This work is performed in the specific context of MCell, a computational biology application. While MCell provides the basis for running simulations, its capabilities are currently limited in terms of scale, ease-of-use, and interactivity. These limitations preclude usage scenarios that are critical for scientific advances. Our goal is to create a scientific “Virtual Instrument” from MCell by allowing its users to transparently access Grid resources while being able to steer running simulations. In this paper, we motivate the Virtual Instrument project and discuss a number of relevant issues and accomplishments in the area of Grid software development and application scheduling. We then describe our software design and report on the current implementation. We verify and evaluate our design via experiments with MCell on a real-world Grid testbed. PMID:20689618

MHD Modeling of the Solar Wind with Turbulence Transport and Heating

NASA Technical Reports Server (NTRS)

Goldstein, M. L.; Usmanov, A. V.; Matthaeus, W. H.; Breech, B.

2009-01-01

We have developed a magnetohydrodynamic model that describes the global axisymmetric steady-state structure of the solar wind near solar minimum with account for transport of small-scale turbulence associated heating. The Reynolds-averaged mass, momentum, induction, and energy equations for the large-scale solar wind flow are solved simultaneously with the turbulence transport equations in the region from 0.3 to 100 AU. The large-scale equations include subgrid-scale terms due to turbulence and the turbulence (small-scale) equations describe the effects of transport and (phenomenologically) dissipation of the MHD turbulence based on a few statistical parameters (turbulence energy, normalized cross-helicity, and correlation scale). The coupled set of equations is integrated numerically for a source dipole field on the Sun by a time-relaxation method in the corotating frame of reference. We present results on the plasma, magnetic field, and turbulence distributions throughout the heliosphere and on the role of the turbulence in the large-scale structure and temperature distribution in the solar wind.

Information Power Grid Posters

NASA Technical Reports Server (NTRS)

Vaziri, Arsi

2003-01-01

This document is a summary of the accomplishments of the Information Power Grid (IPG). Grids are an emerging technology that provide seamless and uniform access to the geographically dispersed, computational, data storage, networking, instruments, and software resources needed for solving large-scale scientific and engineering problems. The goal of the NASA IPG is to use NASA's remotely located computing and data system resources to build distributed systems that can address problems that are too large or complex for a single site. The accomplishments outlined in this poster presentation are: access to distributed data, IPG heterogeneous computing, integration of large-scale computing node into distributed environment, remote access to high data rate instruments,and exploratory grid environment.

Groups of galaxies in the Center for Astrophysics redshift survey

NASA Technical Reports Server (NTRS)

Ramella, Massimo; Geller, Margaret J.; Huchra, John P.

1989-01-01

By applying the Huchra and Geller (1982) objective group identification algorithm to the Center for Astrophysics' redshift survey, a catalog of 128 groups with three or more members is extracted, and 92 of these are used as a statistical sample. A comparison of the distribution of group centers with the distribution of all galaxies in the survey indicates qualitatively that groups trace the large-scale structure of the region. The physical properties of groups may be related to the details of large-scale structure, and it is concluded that differences among group catalogs may be due to the properties of large-scale structures and their location relative to the survey limits.

The effects of Reynolds number, rotor incidence angle and surface roughness on the heat transfer distribution in a large-scale turbine rotor passage

NASA Technical Reports Server (NTRS)

Blair, M. F.

1991-01-01

A combined experimental and computational program was conducted to examine the heat transfer distribution in a turbine rotor passage geometrically similar to the Space Shuttle Main Engine (SSME) High Pressure Fuel Turbopump (HPFTP). Heat transfer was measured and computed for both the full span suction and pressure surfaces of the rotor airfoil as well as for the hub endwall surface. The objective of the program was to provide a benchmark-quality database for the assessment of rotor heat transfer computational techniques. The experimental portion of the study was conducted in a large scale, ambient temperature, rotating turbine model. The computational portion consisted of the application of a well-posed parabolized Navier-Stokes analysis of the calculation of the three-dimensional viscous flow through ducts simulating a gas turbine package. The results of this assessment indicate that the procedure has the potential to predict the aerodynamics and the heat transfer in a gas turbine passage and can be used to develop detailed three dimensional turbulence models for the prediction of skin friction and heat transfer in complex three dimensional flow passages.

Hierarchical Data Distribution Scheme for Peer-to-Peer Networks

NASA Astrophysics Data System (ADS)

Bhushan, Shashi; Dave, M.; Patel, R. B.

2010-11-01

In the past few years, peer-to-peer (P2P) networks have become an extremely popular mechanism for large-scale content sharing. P2P systems have focused on specific application domains (e.g. music files, video files) or on providing file system like capabilities. P2P is a powerful paradigm, which provides a large-scale and cost-effective mechanism for data sharing. P2P system may be used for storing data globally. Can we implement a conventional database on P2P system? But successful implementation of conventional databases on the P2P systems is yet to be reported. In this paper we have presented the mathematical model for the replication of the partitions and presented a hierarchical based data distribution scheme for the P2P networks. We have also analyzed the resource utilization and throughput of the P2P system with respect to the availability, when a conventional database is implemented over the P2P system with variable query rate. Simulation results show that database partitions placed on the peers with higher availability factor perform better. Degradation index, throughput, resource utilization are the parameters evaluated with respect to the availability factor.

Ensemble averaged structure–function relationship for nanocrystals: effective superparamagnetic Fe clusters with catalytically active Pt skin

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

Petkov, Valeri; Prasai, Binay; Shastri, Sarvjit

2017-09-12

Practical applications require the production and usage of metallic nanocrystals (NCs) in large ensembles. Besides, due to their cluster-bulk solid duality, metallic NCs exhibit a large degree of structural diversity. This poses the question as to what atomic-scale basis is to be used when the structure–function relationship for metallic NCs is to be quantified precisely. In this paper, we address the question by studying bi-functional Fe core-Pt skin type NCs optimized for practical applications. In particular, the cluster-like Fe core and skin-like Pt surface of the NCs exhibit superparamagnetic properties and a superb catalytic activity for the oxygen reduction reaction,more » respectively. We determine the atomic-scale structure of the NCs by non-traditional resonant high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Using the experimental structure data we explain the observed magnetic and catalytic behavior of the NCs in a quantitative manner. Lastly, we demonstrate that NC ensemble-averaged 3D positions of atoms obtained by advanced X-ray scattering techniques are a very proper basis for not only establishing but also quantifying the structure–function relationship for the increasingly complex metallic NCs explored for practical applications.« less

Monitoring Local Changes in Granite Rock Under Biaxial Test: A Spatiotemporal Imaging Application With Diffuse Waves

NASA Astrophysics Data System (ADS)

Xie, Fan; Ren, Yaqiong; Zhou, Yongsheng; Larose, Eric; Baillet, Laurent

2018-03-01

Diffuse acoustic or seismic waves are highly sensitive to detect changes of mechanical properties in heterogeneous geological materials. In particular, thanks to acoustoelasticity, we can quantify stress changes by tracking acoustic or seismic relative velocity changes in the material at test. In this paper, we report on a small-scale laboratory application of an innovative time-lapse tomography technique named Locadiff to image spatiotemporal mechanical changes on a granite sample under biaxial loading, using diffuse waves at ultrasonic frequencies (300 kHz to 900 kHz). We demonstrate the ability of the method to image reversible stress evolution and deformation process, together with the development of reversible and irreversible localized microdamage in the specimen at an early stage. Using full-field infrared thermography, we visualize stress-induced temperature changes and validate stress images obtained from diffuse ultrasound. We demonstrate that the inversion with a good resolution can be achieved with only a limited number of receivers distributed around a single source, all located at the free surface of the specimen. This small-scale experiment is a proof of concept for frictional earthquake-like failure (e.g., stick-slip) research at laboratory scale as well as large-scale seismic applications, potentially including active fault monitoring.

Scalable subsurface inverse modeling of huge data sets with an application to tracer concentration breakthrough data from magnetic resonance imaging

DOE PAGES

Lee, Jonghyun; Yoon, Hongkyu; Kitanidis, Peter K.; ...

2016-06-09

When characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydro-geophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with “big data” processing and numerous large-scale numerical simulations. To tackle such difficulties, the Principal Component Geostatistical Approach (PCGA) has been proposed as a “Jacobian-free” inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed inmore » the traditional inversion methods. PCGA can be conveniently linked to any multi-physics simulation software with independent parallel executions. In our paper, we extend PCGA to handle a large number of measurements (e.g. 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data was compressed by the zero-th temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Moreover, only about 2,000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method. This article is protected by copyright. All rights reserved.« less

Large-Scale Ichthyoplankton and Water Mass Distribution along the South Brazil Shelf

PubMed Central

de Macedo-Soares, Luis Carlos Pinto; Garcia, Carlos Alberto Eiras; Freire, Andrea Santarosa; Muelbert, José Henrique

2014-01-01

Ichthyoplankton is an essential component of pelagic ecosystems, and environmental factors play an important role in determining its distribution. We have investigated simultaneous latitudinal and cross-shelf gradients in ichthyoplankton abundance to test the hypothesis that the large-scale distribution of fish larvae in the South Brazil Shelf is associated with water mass composition. Vertical plankton tows were collected between 21°27′ and 34°51′S at 107 stations, in austral late spring and early summer seasons. Samples were taken with a conical-cylindrical plankton net from the depth of chlorophyll maxima to the surface in deep stations, or from 10 m from the bottom to the surface in shallow waters. Salinity and temperature were obtained with a CTD/rosette system, which provided seawater for chlorophyll-a and nutrient concentrations. The influence of water mass on larval fish species was studied using Indicator Species Analysis, whereas environmental effects on the distribution of larval fish species were analyzed by Distance-based Redundancy Analysis. Larval fish species were associated with specific water masses: in the north, Sardinella brasiliensis was found in Shelf Water; whereas in the south, Engraulis anchoita inhabited the Plata Plume Water. At the slope, Tropical Water was characterized by the bristlemouth Cyclothone acclinidens. The concurrent analysis showed the importance of both cross-shelf and latitudinal gradients on the large-scale distribution of larval fish species. Our findings reveal that ichthyoplankton composition and large-scale spatial distribution are determined by water mass composition in both latitudinal and cross-shelf gradients. PMID:24614798

Large-scale ichthyoplankton and water mass distribution along the South Brazil Shelf.

PubMed

de Macedo-Soares, Luis Carlos Pinto; Garcia, Carlos Alberto Eiras; Freire, Andrea Santarosa; Muelbert, José Henrique

2014-01-01

Ichthyoplankton is an essential component of pelagic ecosystems, and environmental factors play an important role in determining its distribution. We have investigated simultaneous latitudinal and cross-shelf gradients in ichthyoplankton abundance to test the hypothesis that the large-scale distribution of fish larvae in the South Brazil Shelf is associated with water mass composition. Vertical plankton tows were collected between 21°27' and 34°51'S at 107 stations, in austral late spring and early summer seasons. Samples were taken with a conical-cylindrical plankton net from the depth of chlorophyll maxima to the surface in deep stations, or from 10 m from the bottom to the surface in shallow waters. Salinity and temperature were obtained with a CTD/rosette system, which provided seawater for chlorophyll-a and nutrient concentrations. The influence of water mass on larval fish species was studied using Indicator Species Analysis, whereas environmental effects on the distribution of larval fish species were analyzed by Distance-based Redundancy Analysis. Larval fish species were associated with specific water masses: in the north, Sardinella brasiliensis was found in Shelf Water; whereas in the south, Engraulis anchoita inhabited the Plata Plume Water. At the slope, Tropical Water was characterized by the bristlemouth Cyclothone acclinidens. The concurrent analysis showed the importance of both cross-shelf and latitudinal gradients on the large-scale distribution of larval fish species. Our findings reveal that ichthyoplankton composition and large-scale spatial distribution are determined by water mass composition in both latitudinal and cross-shelf gradients.

Identifying unproven cancer treatments on the health web: addressing accuracy, generalizability and scalability.

PubMed

Aphinyanaphongs, Yin; Fu, Lawrence D; Aliferis, Constantin F

2013-01-01

Building machine learning models that identify unproven cancer treatments on the Health Web is a promising approach for dealing with the dissemination of false and dangerous information to vulnerable health consumers. Aside from the obvious requirement of accuracy, two issues are of practical importance in deploying these models in real world applications. (a) Generalizability: The models must generalize to all treatments (not just the ones used in the training of the models). (b) Scalability: The models can be applied efficiently to billions of documents on the Health Web. First, we provide methods and related empirical data demonstrating strong accuracy and generalizability. Second, by combining the MapReduce distributed architecture and high dimensionality compression via Markov Boundary feature selection, we show how to scale the application of the models to WWW-scale corpora. The present work provides evidence that (a) a very small subset of unproven cancer treatments is sufficient to build a model to identify unproven treatments on the web; (b) unproven treatments use distinct language to market their claims and this language is learnable; (c) through distributed parallelization and state of the art feature selection, it is possible to prepare the corpora and build and apply models with large scalability.

Comparisons of ionospheric electron density distributions reconstructed by GPS computerized tomography, backscatter ionograms, and vertical ionograms

NASA Astrophysics Data System (ADS)

Zhou, Chen; Lei, Yong; Li, Bofeng; An, Jiachun; Zhu, Peng; Jiang, Chunhua; Zhao, Zhengyu; Zhang, Yuannong; Ni, Binbin; Wang, Zemin; Zhou, Xuhua

2015-12-01

Global Positioning System (GPS) computerized ionosphere tomography (CIT) and ionospheric sky wave ground backscatter radar are both capable of measuring the large-scale, two-dimensional (2-D) distributions of ionospheric electron density (IED). Here we report the spatial and temporal electron density results obtained by GPS CIT and backscatter ionogram (BSI) inversion for three individual experiments. Both the GPS CIT and BSI inversion techniques demonstrate the capability and the consistency of reconstructing large-scale IED distributions. To validate the results, electron density profiles obtained from GPS CIT and BSI inversion are quantitatively compared to the vertical ionosonde data, which clearly manifests that both methods output accurate information of ionopsheric electron density and thereby provide reliable approaches to ionospheric soundings. Our study can improve current understanding of the capability and insufficiency of these two methods on the large-scale IED reconstruction.

Large-scale budget applications of mathematical programming in the Forest Service

Treesearch

Malcolm Kirby

1978-01-01

Mathematical programming applications in the Forest Service, U.S. Department of Agriculture, are growing. They are being used for widely varying problems: budgeting, lane use planning, timber transport, road maintenance and timber harvest planning. Large-scale applications are being mace in budgeting. The model that is described can be used by developing economies....

Efficient On-Demand Operations in Large-Scale Infrastructures

ERIC Educational Resources Information Center

Ko, Steven Y.

2009-01-01

In large-scale distributed infrastructures such as clouds, Grids, peer-to-peer systems, and wide-area testbeds, users and administrators typically desire to perform "on-demand operations" that deal with the most up-to-date state of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to…

Role of Hydrodynamic and Mineralogical Heterogeneities on Reactive Transport Processes.

NASA Astrophysics Data System (ADS)

Luquot, L.; Garcia-Rios, M.; soler Sagarra, J.; Gouze, P.; Martinez-Perez, L.; Carrera, J.

2017-12-01

Predicting reactive transport at large scale, i.e., Darcy- and field- scale, is still challenging considering the number of heterogeneities that may be present from nm- to pore-scale. It is well documented that conventional continuum-scale approaches oversimplify and/or ignore many important aspects of rock structure, chemical reactions, fluid displacement and transport, which, as a consequence, results in uncertainties when applied to field-scale operations. The changes in flow and reactive transport across the different spatial and temporal scales are of central concern in many geological applications such as groundwater systems, geo-energy, rock building heritage and geological storage... In this presentation, we will discuss some laboratory and numerical results on how local heterogeneities (structural, hydrodynamic and mineralogical) can affect the localization and the rate of the reaction processes. Different flow through laboratory experiments using various rock samples will be presented, from simple monomineral rocks such as limestone samples, and more complex rocks composed of different minerals with a large range of kinetic reactions. A new numerical approach based on multirate water mixing approach will be presented and applied to one of the laboratory experiment in order to analyze and distinguish the effect of the mineralogy distribution and the hydrodynamic heterogeneity on the total reaction rate.

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

NASA Technical Reports Server (NTRS)

Johnston, William E.; Gannon, Dennis; Nitzberg, Bill

2000-01-01

We use the term "Grid" to refer to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. This infrastructure includes: (1) Tools for constructing collaborative, application oriented Problem Solving Environments / Frameworks (the primary user interfaces for Grids); (2) Programming environments, tools, and services providing various approaches for building applications that use aggregated computing and storage resources, and federated data sources; (3) Comprehensive and consistent set of location independent tools and services for accessing and managing dynamic collections of widely distributed resources: heterogeneous computing systems, storage systems, real-time data sources and instruments, human collaborators, and communications systems; (4) Operational infrastructure including management tools for distributed systems and distributed resources, user services, accounting and auditing, strong and location independent user authentication and authorization, and overall system security services The vision for NASA's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks. Such Grids will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. Examples of these problems include: (1) Coupled, multidisciplinary simulations too large for single systems (e.g., multi-component NPSS turbomachine simulation); (2) Use of widely distributed, federated data archives (e.g., simultaneous access to metrological, topological, aircraft performance, and flight path scheduling databases supporting a National Air Space Simulation systems}; (3) Coupling large-scale computing and data systems to scientific and engineering instruments (e.g., realtime interaction with experiments through real-time data analysis and interpretation presented to the experimentalist in ways that allow direct interaction with the experiment (instead of just with instrument control); (5) Highly interactive, augmented reality and virtual reality remote collaborations (e.g., Ames / Boeing Remote Help Desk providing field maintenance use of coupled video and NDI to a remote, on-line airframe structures expert who uses this data to index into detailed design databases, and returns 3D internal aircraft geometry to the field); (5) Single computational problems too large for any single system (e.g. the rotocraft reference calculation). Grids also have the potential to provide pools of resources that could be called on in extraordinary / rapid response situations (such as disaster response) because they can provide common interfaces and access mechanisms, standardized management, and uniform user authentication and authorization, for large collections of distributed resources (whether or not they normally function in concert). IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: the scientist / design engineer whose primary interest is problem solving (e.g. determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user is the tool designer: the computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. The results of the analysis of the needs of these two types of users provides a broad set of requirements that gives rise to a general set of required capabilities. The IPG project is intended to address all of these requirements. In some cases the required computing technology exists, and in some cases it must be researched and developed. The project is using available technology to provide a prototype set of capabilities in a persistent distributed computing testbed. Beyond this, there are required capabilities that are not immediately available, and whose development spans the range from near-term engineering development (one to two years) to much longer term R&D (three to six years). Additional information is contained in the original.

Distributed analysis functional testing using GangaRobot in the ATLAS experiment

NASA Astrophysics Data System (ADS)

Legger, Federica; ATLAS Collaboration

2011-12-01

Automated distributed analysis tests are necessary to ensure smooth operations of the ATLAS grid resources. The HammerCloud framework allows for easy definition, submission and monitoring of grid test applications. Both functional and stress test applications can be defined in HammerCloud. Stress tests are large-scale tests meant to verify the behaviour of sites under heavy load. Functional tests are light user applications running at each site with high frequency, to ensure that the site functionalities are available at all times. Success or failure rates of these tests jobs are individually monitored. Test definitions and results are stored in a database and made available to users and site administrators through a web interface. In this work we present the recent developments of the GangaRobot framework. GangaRobot monitors the outcome of functional tests, creates a blacklist of sites failing the tests, and exports the results to the ATLAS Site Status Board (SSB) and to the Service Availability Monitor (SAM), providing on the one hand a fast way to identify systematic or temporary site failures, and on the other hand allowing for an effective distribution of the work load on the available resources.

Phytoextraction of Cd-Contaminated Soils: Current Status and Future Challenges

PubMed Central

Li, Jin-Tian; Baker, Alan J. M.; Ye, Zhi-Hong; Wang, Hong-Bin; Shu, Wen-Sheng

2012-01-01

Cadmium (Cd) is one of the most toxic and widely distributed pollutants in the environment. Cadmium contamination of soils has posed a serious threat to safe food production in many parts of the world. The authors present a comprehensive review of present status of phytoextraction technology for cleaning up Cd-contaminated soils, based primarily on the data resulting from both laboratory and field-scale studies that have been conducted to assess or improve the Cd phytoextraction potential of various plant species in the past decade. The encouraging results of field-scale studies have provided a fundamental basis to usher phytoextraction technology into practical use to remediate slightly to moderately Cd-contaminated soils in Europe and Asia, although this technology is not yet ready for widespread application. Chelators and microorganisms tested so far seem not to contribute to the applicability of Cd phytoextraction. The major challenges for the large-scale application of Cd phytoextraction are (a) how to further improve the efficiency of Cd phytoextraction, (b) how to cut the overall costs of Cd phytoextraction, and (c) how to get greater stakeholders’ acceptance of Cd phytoextraction as a reliable option. PMID:23335842

Large-scale horizontally aligned ZnO microrod arrays with controlled orientation, periodic distribution as building blocks for chip-in piezo-phototronic LEDs.

PubMed

Guo, Zhen; Li, Haiwen; Zhou, Lianqun; Zhao, Dongxu; Wu, Yihui; Zhang, Zhiqiang; Zhang, Wei; Li, Chuanyu; Yao, Jia

2015-01-27

A novel method of fabricating large-scale horizontally aligned ZnO microrod arrays with controlled orientation and periodic distribution via combing technology is introduced. Horizontally aligned ZnO microrod arrays with uniform orientation and periodic distribution can be realized based on the conventional bottom-up method prepared vertically aligned ZnO microrod matrix via the combing method. When the combing parameters are changed, the orientation of horizontally aligned ZnO microrod arrays can be adjusted (θ = 90° or 45°) in a plane and a misalignment angle of the microrods (0.3° to 2.3°) with low-growth density can be obtained. To explore the potential applications based on the vertically and horizontally aligned ZnO microrods on p-GaN layer, piezo-phototronic devices such as heterojunction LEDs are built. Electroluminescence (EL) emission patterns can be adjusted for the vertically and horizontally aligned ZnO microrods/p-GaN heterojunction LEDs by applying forward bias. Moreover, the emission color from UV-blue to yellow-green can be tuned by investigating the piezoelectric properties of the materials. The EL emission mechanisms of the LEDs are discussed in terms of band diagrams of the heterojunctions and carrier recombination processes. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An evaluation of semi-automated methods for collecting ecosystem-level data in temperate marine systems.

PubMed

Griffin, Kingsley J; Hedge, Luke H; González-Rivero, Manuel; Hoegh-Guldberg, Ove I; Johnston, Emma L

2017-07-01

Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high-resolution imaging and associated machine-learning image-scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free-to-use machine-learning software to semi-automatically generate dense and widespread abundance records of a habitat-forming algae over ~5,000 m 2 of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver-based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10-20 transects (50 × 1 m) were required to obtain reliable results. This represents 2-20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine-resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi-automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.

Boosting Bayesian parameter inference of nonlinear stochastic differential equation models by Hamiltonian scale separation.

PubMed

Albert, Carlo; Ulzega, Simone; Stoop, Ruedi

2016-04-01

Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In many situations, the dominant sources of uncertainty must be included into the model for making reliable predictions. This naturally leads to stochastic models. Stochastic models render parameter inference much harder, as the aim then is to find a distribution of likely parameter values. In Bayesian statistics, which is a consistent framework for data-driven learning, this so-called posterior distribution can be used to make probabilistic predictions. We propose a novel, exact, and very efficient approach for generating posterior parameter distributions for stochastic differential equation models calibrated to measured time series. The algorithm is inspired by reinterpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, where the measurements are mapped on heavier beads compared to those of the simulated data. To arrive at distribution samples, we employ a Hamiltonian Monte Carlo approach combined with a multiple time-scale integration. A separation of time scales naturally arises if either the number of measurement points or the number of simulation points becomes large. Furthermore, at least for one-dimensional problems, we can decouple the harmonic modes between measurement points and solve the fastest part of their dynamics analytically. Our approach is applicable to a wide range of inference problems and is highly parallelizable.

The power of event-driven analytics in Large Scale Data Processing

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

Sebastiao, Nuno; Marques, Paulo

2011-02-24

FeedZai is a software company specialized in creating high-­‐throughput low-­‐latency data processing solutions. FeedZai develops a product called "FeedZai Pulse" for continuous event-­‐driven analytics that makes application development easier for end users. It automatically calculates key performance indicators and baselines, showing how current performance differ from previous history, creating timely business intelligence updated to the second. The tool does predictive analytics and trend analysis, displaying data on real-­‐time web-­‐based graphics. In 2010 FeedZai won the European EBN Smart Entrepreneurship Competition, in the Digital Models category, being considered one of the "top-­‐20 smart companies in Europe". The main objective of thismore » seminar/workshop is to explore the topic for large-­‐scale data processing using Complex Event Processing and, in particular, the possible uses of Pulse in the scope of the data processing needs of CERN. Pulse is available as open-­‐source and can be licensed both for non-­‐commercial and commercial applications. FeedZai is interested in exploring possible synergies with CERN in high-­‐volume low-­‐latency data processing applications. The seminar will be structured in two sessions, the first one being aimed to expose the general scope of FeedZai's activities, and the second focused on Pulse itself: 10:00-11:00 FeedZai and Large Scale Data Processing; Introduction to FeedZai; FeedZai Pulse and Complex Event Processing; Demonstration; Use-Cases and Applications; Conclusion and Q&A. 11:00-11:15 Coffee break 11:15-12:30 FeedZai Pulse Under the Hood; A First FeedZai Pulse Application; PulseQL overview; Defining KPIs and Baselines; Conclusion and Q&A. About the speakers Nuno Sebastião is the CEO of FeedZai. Having worked for many years for the European Space Agency (ESA), he was responsible the overall design and development of Satellite Simulation Infrastructure of the agency. Having left ESA to found FeedZai, Nuno is currently responsible for the whole operations of the company. Nuno holds an M.Eng. in Informatics Engineering for the University of Coimbra, and an MBA from the London Business School. Paulo Marques is the CTO of FeedZai, being responsible for product development. Paulo is an Assistant Professor at the University of Coimbra, in the area of Distributed Data Processing, and an Adjunct Associated Professor at Carnegie Mellon, in the US. In the past Paulo lead a large number of projects for institutions like the ESA, Microsoft Research, SciSys, Siemens, among others, being now fully dedicated to FeedZai. Paulo holds a Ph.D. in Distributed Systems from the University of Coimbra.« less

The power of event-driven analytics in Large Scale Data Processing

ScienceCinema

None

2017-12-09

FeedZai is a software company specialized in creating high-­-throughput low-­-latency data processing solutions. FeedZai develops a product called "FeedZai Pulse" for continuous event-­-driven analytics that makes application development easier for end users. It automatically calculates key performance indicators and baselines, showing how current performance differ from previous history, creating timely business intelligence updated to the second. The tool does predictive analytics and trend analysis, displaying data on real-­-time web-­-based graphics. In 2010 FeedZai won the European EBN Smart Entrepreneurship Competition, in the Digital Models category, being considered one of the "top-­-20 smart companies in Europe". The main objective of this seminar/workshop is to explore the topic for large-­-scale data processing using Complex Event Processing and, in particular, the possible uses of Pulse in the scope of the data processing needs of CERN. Pulse is available as open-­-source and can be licensed both for non-­-commercial and commercial applications. FeedZai is interested in exploring possible synergies with CERN in high-­-volume low-­-latency data processing applications. The seminar will be structured in two sessions, the first one being aimed to expose the general scope of FeedZai's activities, and the second focused on Pulse itself: 10:00-11:00 FeedZai and Large Scale Data Processing Introduction to FeedZai FeedZai Pulse and Complex Event Processing Demonstration Use-Cases and Applications Conclusion and Q&A 11:00-11:15 Coffee break 11:15-12:30 FeedZai Pulse Under the Hood A First FeedZai Pulse Application PulseQL overview Defining KPIs and Baselines Conclusion and Q&A About the speakers Nuno Sebastião is the CEO of FeedZai. Having worked for many years for the European Space Agency (ESA), he was responsible the overall design and development of Satellite Simulation Infrastructure of the agency. Having left ESA to found FeedZai, Nuno is currently responsible for the whole operations of the company. Nuno holds an M.Eng. in Informatics Engineering for the University of Coimbra, and an MBA from the London Business School. Paulo Marques is the CTO of FeedZai, being responsible for product development. Paulo is an Assistant Professor at the University of Coimbra, in the area of Distributed Data Processing, and an Adjunct Associated Professor at Carnegie Mellon, in the US. In the past Paulo lead a large number of projects for institutions like the ESA, Microsoft Research, SciSys, Siemens, among others, being now fully dedicated to FeedZai. Paulo holds a Ph.D. in Distributed Systems from the University of Coimbra.

Application of Physics Based Distributed Hydrologic Models to Assess Anthropologic Land Disturbance in Watersheds

NASA Astrophysics Data System (ADS)

Downer, C. W.; Ogden, F. L.; Byrd, A. R.

2008-12-01

The Department of Defense (DoD) manages approximately 200,000 km2 of land within the United States on military installations and flood control and river improvement projects. The Watershed Systems Group (WSG) within the Coastal and Hydraulics Laboratory of the Engineer Research and Development Center (ERDC) supports the US Army and the US Army Corps of Engineers in both military and civil operations through the development, modification and application of surface and sub-surface hydrologic models. The US Army has a long history of land management and the development of analytical tools to assist with the management of US Army lands. The US Army has invested heavily in the distributed hydrologic model GSSHA and its predecessor CASC2D. These tools have been applied at numerous military and civil sites to analyze the effects of landscape alteration on hydrologic response and related consequences, changes in erosion and sediment transport, along with associated contaminants. Examples include: impacts of military training and land management activities, impact of changing land use (urbanization or environmental restoration), as well as impacts of management practices employed to abate problems, i.e. Best Management Practices (BMPs). Traditional models such as HSPF and SWAT, are largely conceptual in nature. GSSHA attempts to simulate the physical processes actually occurring in the watershed allowing the user to explicitly simulate changing parameter values in response to changes in land use, land cover, elevation, etc. Issues of scale raise questions: How do we best include fine-scale land use or management features in models of large watersheds? Do these features have to be represented explicitly through physical processes in the watershed domain? Can a point model, physical or empirical, suffice? Can these features be lumped into coarsely resolved numerical grids or sub-watersheds? In this presentation we will discuss the US Army's distributed hydrologic models in terms of how they simulate the relevant processes and present multiple applications of the models used for analyzing land management and land use change. Using these applications as a basis we will discuss issues related to the analysis of anthropogenic alterations in the landscape.

Anomalies in the GRBs' distribution

NASA Astrophysics Data System (ADS)

Bagoly, Zsolt; Horvath, Istvan; Hakkila, Jon; Toth, Viktor

2015-08-01

Gamma-ray bursts (GRBs) are the most luminous objects known: they outshine their host galaxies making them ideal candidates for probing large-scale structure. Earlier, the angular distribution of different GRBs (long, intermediate and short) has been studied in detail with different methods and it has been found that the short and intermediate groups showed deviation from the full randomness at different levels (e.g. Vavrek, R., et al. 2008). However these result based only angular measurements of the BATSE experiment, without any spatial distance indicator involved.Currently we have more than 361 GRBs with measured precise position, optical afterglow and redshift, mainly due to the observations of the Swift mission. This sample is getting large enough that it its homogeneous and isotropic distribution a large scale can be checked. We have recently (Horvath, I. et al., 2014) identified a large clustering of gamma-ray bursts at redshift z ~ 2 in the general direction of the constellations of Hercules and Corona Borealis. This angular excess cannot be entirely attributed to known selection biases, making its existence due to chance unlikely. The scale on which the clustering occurs is disturbingly large, about 2-3 Gpc: the underlying distribution of matter suggested by this cluster is big enough to question standard assumptions about Universal homogeneity and isotropy.

A randomized approach to speed up the analysis of large-scale read-count data in the application of CNV detection.

PubMed

Wang, WeiBo; Sun, Wei; Wang, Wei; Szatkiewicz, Jin

2018-03-01

The application of high-throughput sequencing in a broad range of quantitative genomic assays (e.g., DNA-seq, ChIP-seq) has created a high demand for the analysis of large-scale read-count data. Typically, the genome is divided into tiling windows and windowed read-count data is generated for the entire genome from which genomic signals are detected (e.g. copy number changes in DNA-seq, enrichment peaks in ChIP-seq). For accurate analysis of read-count data, many state-of-the-art statistical methods use generalized linear models (GLM) coupled with the negative-binomial (NB) distribution by leveraging its ability for simultaneous bias correction and signal detection. However, although statistically powerful, the GLM+NB method has a quadratic computational complexity and therefore suffers from slow running time when applied to large-scale windowed read-count data. In this study, we aimed to speed up substantially the GLM+NB method by using a randomized algorithm and we demonstrate here the utility of our approach in the application of detecting copy number variants (CNVs) using a real example. We propose an efficient estimator, the randomized GLM+NB coefficients estimator (RGE), for speeding up the GLM+NB method. RGE samples the read-count data and solves the estimation problem on a smaller scale. We first theoretically validated the consistency and the variance properties of RGE. We then applied RGE to GENSENG, a GLM+NB based method for detecting CNVs. We named the resulting method as "R-GENSENG". Based on extensive evaluation using both simulated and empirical data, we concluded that R-GENSENG is ten times faster than the original GENSENG while maintaining GENSENG's accuracy in CNV detection. Our results suggest that RGE strategy developed here could be applied to other GLM+NB based read-count analyses, i.e. ChIP-seq data analysis, to substantially improve their computational efficiency while preserving the analytic power.

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.

2012 Market Report on Wind Technologies in Distributed Applications

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

Orrell, Alice C.

2013-08-01

An annual report on U.S. wind power in distributed applications – expanded to include small, mid-size, and utility-scale installations – including key statistics, economic data, installation, capacity, and generation statistics, and more.

Facile large-scale synthesis of brain-like mesoporous silica nanocomposites via a selective etching process

NASA Astrophysics Data System (ADS)

Chen, Yu; Wang, Qihua; Wang, Tingmei

2015-10-01

The core-shell structured mesoporous silica nanomaterials (MSNs) are experiencing rapid development in many applications such as heterogeneous catalysis, bio-imaging and drug delivery wherein a large pore volume is desirable. We develop a one-pot method for large-scale synthesis of brain-like mesoporous silica nanocomposites based on the reasonable change of the intrinsic nature of the -Si-O-Si- framework of silica nanoparticles together with a selective etching strategy. The as-synthesized products show good monodispersion and a large pore volume of 1.0 cm3 g-1. The novelty of this approach lies in the use of an inorganic-organic hybrid layer to assist the creation of large-pore morphology on the outermost shell thereby promoting efficient mass transfer or storage. Importantly, the method is reliable and grams of products can be easily prepared. The morphology on the outermost silica shell can be controlled by simply adjusting the VTES-to-TEOS molar ratio (VTES: triethoxyvinylsilane, TEOS: tetraethyl orthosilicate) as well as the etching time. The as-synthesized products exhibit fluorescence performance by incorporating rhodamine B isothiocyanate (RITC) covalently into the inner silica walls, which provide potential application in bioimaging. We also demonstrate the applications of as-synthesized large-pore structured nanocomposites in drug delivery systems and stimuli-responsive nanoreactors for heterogeneous catalysis.The core-shell structured mesoporous silica nanomaterials (MSNs) are experiencing rapid development in many applications such as heterogeneous catalysis, bio-imaging and drug delivery wherein a large pore volume is desirable. We develop a one-pot method for large-scale synthesis of brain-like mesoporous silica nanocomposites based on the reasonable change of the intrinsic nature of the -Si-O-Si- framework of silica nanoparticles together with a selective etching strategy. The as-synthesized products show good monodispersion and a large pore volume of 1.0 cm3 g-1. The novelty of this approach lies in the use of an inorganic-organic hybrid layer to assist the creation of large-pore morphology on the outermost shell thereby promoting efficient mass transfer or storage. Importantly, the method is reliable and grams of products can be easily prepared. The morphology on the outermost silica shell can be controlled by simply adjusting the VTES-to-TEOS molar ratio (VTES: triethoxyvinylsilane, TEOS: tetraethyl orthosilicate) as well as the etching time. The as-synthesized products exhibit fluorescence performance by incorporating rhodamine B isothiocyanate (RITC) covalently into the inner silica walls, which provide potential application in bioimaging. We also demonstrate the applications of as-synthesized large-pore structured nanocomposites in drug delivery systems and stimuli-responsive nanoreactors for heterogeneous catalysis. Electronic supplementary information (ESI) available: The average particle size distribution of LPASN-1, LPASN-2 and LPASN-3; the wide-angle XRD pattern of LPASN-2/LPASN-3/LPASN-4; the catalytic properties of LPASN-PNIPAM at different temperatures (15 °C and 33 °C). See DOI: 10.1039/c5nr04123f

FROM FINANCE TO COSMOLOGY: THE COPULA OF LARGE-SCALE STRUCTURE

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

Scherrer, Robert J.; Berlind, Andreas A.; Mao, Qingqing

2010-01-01

Any multivariate distribution can be uniquely decomposed into marginal (one-point) distributions, and a function called the copula, which contains all of the information on correlations between the distributions. The copula provides an important new methodology for analyzing the density field in large-scale structure. We derive the empirical two-point copula for the evolved dark matter density field. We find that this empirical copula is well approximated by a Gaussian copula. We consider the possibility that the full n-point copula is also Gaussian and describe some of the consequences of this hypothesis. Future directions for investigation are discussed.

Transitioning Active Flow Control to Applications

NASA Technical Reports Server (NTRS)

Joslin, Ronald D.; Horta, Lucas G.; Chen, Fang-Jenq

1999-01-01

Active Flow Control Programs at NASA, the U.S. Air Force, and DARPA have been initiated with the goals of obtaining revolutionary advances in aerodynamic performance and maneuvering compared to conventional approaches. These programs envision the use of actuators, sensors, and controllers on applications such as aircraft wings/tails, engine nacelles, internal ducts, nozzles, projectiles, weapons bays, and hydrodynamic vehicles. Anticipated benefits of flow control include reduced weight, part count, and operating cost and reduced fuel burn (and emissions), noise and enhanced safety if the sensors serve a dual role of flow control and health monitoring. To get from the bench-top or laboratory test to adaptive distributed control systems on realistic applications, reliable validated design tools are needed in addition to sub- and large-scale wind-tunnel and flight experiments. This paper will focus on the development of tools for active flow control applications.

Large-Scale Cooperative Task Distribution on Peer-to-Peer Networks

DTIC Science & Technology

2012-01-01

SUBTITLE Large-scale cooperative task distribution on peer-to-peer networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...of agents, and each agent attempts to form a coalition with its most profitable partner. The second algorithm builds upon the Shapley for- mula [37...ters at the second layer. These Category Layer clusters each represent a single resource, and agents join one or more clusters based on their

Asymptotic stability and instability of large-scale systems. [using vector Liapunov functions

NASA Technical Reports Server (NTRS)

Grujic, L. T.; Siljak, D. D.

1973-01-01

The purpose of this paper is to develop new methods for constructing vector Lyapunov functions and broaden the application of Lyapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. By redefining interconnection functions among the subsystems according to interconnection matrices, the same mathematical machinery can be used to determine connective asymptotic stability of large-scale systems under arbitrary structural perturbations.

Quasi-linear regime of gravitational instability: Implication to density-velocity relation

NASA Technical Reports Server (NTRS)

Shandarin, Sergei F.

1993-01-01

The well known linear relation between density and peculiar velocity distributions is a powerful tool for studying the large-scale structure in the Universe. Potentially it can test the gravitational instability theory and measure Omega. At present it is used in both ways: the velocity is reconstructed, provided the density is given, and vice versa. Reconstructing the density from the velocity field usually makes use of the Zel'dovich approximation. However, the standard linear approximation in Eulerian space is used when the velocity is reconstructed from the density distribution. I show that the linearized Zel'dovich approximation, in other words the linear approximation in the Lagrangian space, is more accurate for reconstructing velocity. In principle, a simple iteration technique can recover both the density and velocity distributions in Lagrangian space, but its practical application may need an additional study.

Implementation of a multi-threaded framework for large-scale scientific applications

DOE PAGES

Sexton-Kennedy, E.; Gartung, Patrick; Jones, C. D.; ...

2015-05-22

The CMS experiment has recently completed the development of a multi-threaded capable application framework. In this paper, we will discuss the design, implementation and application of this framework to production applications in CMS. For the 2015 LHC run, this functionality is particularly critical for both our online and offline production applications, which depend on faster turn-around times and a reduced memory footprint relative to before. These applications are complex codes, each including a large number of physics-driven algorithms. While the framework is capable of running a mix of thread-safe and 'legacy' modules, algorithms running in our production applications need tomore » be thread-safe for optimal use of this multi-threaded framework at a large scale. Towards this end, we discuss the types of changes, which were necessary for our algorithms to achieve good performance of our multithreaded applications in a full-scale application. Lastly performance numbers for what has been achieved for the 2015 run are presented.« less

Facile synthesis of concentrated gold nanoparticles with low size-distribution in water: temperature and pH controls

NASA Astrophysics Data System (ADS)

Li, Chunfang; Li, Dongxiang; Wan, Gangqiang; Xu, Jie; Hou, Wanguo

2011-07-01

The citrate reduction method for the synthesis of gold nanoparticles (GNPs) has known advantages but usually provides the products with low nanoparticle concentration and limits its application. Herein, we report a facile method to synthesize GNPs from concentrated chloroauric acid (2.5 mM) via adding sodium hydroxide and controlling the temperature. It was found that adding a proper amount of sodium hydroxide can produce uniform concentrated GNPs with low size distribution; otherwise, the largely distributed nanoparticles or instable colloids were obtained. The low reaction temperature is helpful to control the nanoparticle formation rate, and uniform GNPs can be obtained in presence of optimized NaOH concentrations. The pH values of the obtained uniform GNPs were found to be very near to neutral, and the pH influence on the particle size distribution may reveal the different formation mechanism of GNPs at high or low pH condition. Moreover, this modified synthesis method can save more than 90% energy in the heating step. Such environmental-friendly synthesis method for gold nanoparticles may have a great potential in large-scale manufacturing for commercial and industrial demand.

A bibliographical surveys of large-scale systems

NASA Technical Reports Server (NTRS)

Corliss, W. R.

1970-01-01

A limited, partly annotated bibliography was prepared on the subject of large-scale system control. Approximately 400 references are divided into thirteen application areas, such as large societal systems and large communication systems. A first-author index is provided.

Time-sliced perturbation theory for large scale structure I: general formalism

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

Blas, Diego; Garny, Mathias; Sibiryakov, Sergey

2016-07-01

We present a new analytic approach to describe large scale structure formation in the mildly non-linear regime. The central object of the method is the time-dependent probability distribution function generating correlators of the cosmological observables at a given moment of time. Expanding the distribution function around the Gaussian weight we formulate a perturbative technique to calculate non-linear corrections to cosmological correlators, similar to the diagrammatic expansion in a three-dimensional Euclidean quantum field theory, with time playing the role of an external parameter. For the physically relevant case of cold dark matter in an Einstein-de Sitter universe, the time evolution ofmore » the distribution function can be found exactly and is encapsulated by a time-dependent coupling constant controlling the perturbative expansion. We show that all building blocks of the expansion are free from spurious infrared enhanced contributions that plague the standard cosmological perturbation theory. This paves the way towards the systematic resummation of infrared effects in large scale structure formation. We also argue that the approach proposed here provides a natural framework to account for the influence of short-scale dynamics on larger scales along the lines of effective field theory.« less

SDN-NGenIA, a software defined next generation integrated architecture for HEP and data intensive science

NASA Astrophysics Data System (ADS)

Balcas, J.; Hendricks, T. W.; Kcira, D.; Mughal, A.; Newman, H.; Spiropulu, M.; Vlimant, J. R.

2017-10-01

The SDN Next Generation Integrated Architecture (SDN-NGeNIA) project addresses some of the key challenges facing the present and next generations of science programs in HEP, astrophysics, and other fields, whose potential discoveries depend on their ability to distribute, process and analyze globally distributed Petascale to Exascale datasets. The SDN-NGenIA system under development by Caltech and partner HEP and network teams is focused on the coordinated use of network, computing and storage infrastructures, through a set of developments that build on the experience gained in recently completed and previous projects that use dynamic circuits with bandwidth guarantees to support major network flows, as demonstrated across LHC Open Network Environment [1] and in large scale demonstrations over the last three years, and recently integrated with PhEDEx and Asynchronous Stage Out data management applications of the CMS experiment at the Large Hadron Collider. In addition to the general program goals of supporting the network needs of the LHC and other science programs with similar needs, a recent focus is the use of the Leadership HPC facility at Argonne National Lab (ALCF) for data intensive applications.

Annual Rainfall Maxima: Theoretical Estimation of the GEV Shape Parameter k Using Multifractal Models

NASA Astrophysics Data System (ADS)

Veneziano, D.; Langousis, A.; Lepore, C.

2009-12-01

The annual maximum of the average rainfall intensity in a period of duration d, Iyear(d), is typically assumed to have generalized extreme value (GEV) distribution. The shape parameter k of that distribution is especially difficult to estimate from either at-site or regional data, making it important to constraint k using theoretical arguments. In the context of multifractal representations of rainfall, we observe that standard theoretical estimates of k from extreme value (EV) and extreme excess (EE) theories do not apply, while estimates from large deviation (LD) theory hold only for very small d. We then propose a new theoretical estimator based on fitting GEV models to the numerically calculated distribution of Iyear(d). A standard result from EV and EE theories is that k depends on the tail behavior of the average rainfall in d, I(d). This result holds if Iyear(d) is the maximum of a sufficiently large number n of variables, all distributed like I(d); therefore its applicability hinges on whether n = 1yr/d is large enough and the tail of I(d) is sufficiently well known. One typically assumes that at least for small d the former condition is met, but poor knowledge of the upper tail of I(d) remains an obstacle for all d. In fact, in the case of multifractal rainfall, also the first condition is not met because, irrespective of d, 1yr/d is too small (Veneziano et al., 2009, WRR, in press). Applying large deviation (LD) theory to this multifractal case, we find that, as d → 0, Iyear(d) approaches a GEV distribution whose shape parameter kLD depends on a region of the distribution of I(d) well below the upper tail, is always positive (in the EV2 range), is much larger than the value predicted by EV and EE theories, and can be readily found from the scaling properties of I(d). The scaling properties of rainfall can be inferred also from short records, but the limitation remains that the result holds under d → 0 not for finite d. Therefore, for different reasons, none of the above asymptotic theories applies to Iyear(d). In practice, one is interested in the distribution of Iyear(d) over a finite range of averaging durations d and return periods T. Using multifractal representations of rainfall, we have numerically calculated the distribution of Iyear(d) and found that, although not GEV, the distribution can be accurately approximated by a GEV model. The best-fitting parameter k depends on d, but is insensitive to the scaling properties of rainfall and the range of return periods T used for fitting. We have obtained a default expression for k(d) and compared it with estimates from historical rainfall records. The theoretical function tracks well the empirical dependence on d, although it generally overestimates the empirical k values, possibly due to deviations of rainfall from perfect scaling. This issue is under investigation.

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: Earth System Modeling Software Framework Survey

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn; Zukor, Dorothy (Technical Monitor)

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task, both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation. while maintaining high performance across numerous supercomputer and workstation architectures. This document surveys numerous software frameworks for potential use in Earth science modeling. Several frameworks are evaluated in depth, including Parallel Object-Oriented Methods and Applications (POOMA), Cactus (from (he relativistic physics community), Overture, Goddard Earth Modeling System (GEMS), the National Center for Atmospheric Research Flux Coupler, and UCLA/UCB Distributed Data Broker (DDB). Frameworks evaluated in less detail include ROOT, Parallel Application Workspace (PAWS), and Advanced Large-Scale Integrated Computational Environment (ALICE). A host of other frameworks and related tools are referenced in this context. The frameworks are evaluated individually and also compared with each other.

Distributed Parallel Processing and Dynamic Load Balancing Techniques for Multidisciplinary High Speed Aircraft Design

NASA Technical Reports Server (NTRS)

Krasteva, Denitza T.

1998-01-01

Multidisciplinary design optimization (MDO) for large-scale engineering problems poses many challenges (e.g., the design of an efficient concurrent paradigm for global optimization based on disciplinary analyses, expensive computations over vast data sets, etc.) This work focuses on the application of distributed schemes for massively parallel architectures to MDO problems, as a tool for reducing computation time and solving larger problems. The specific problem considered here is configuration optimization of a high speed civil transport (HSCT), and the efficient parallelization of the embedded paradigm for reasonable design space identification. Two distributed dynamic load balancing techniques (random polling and global round robin with message combining) and two necessary termination detection schemes (global task count and token passing) were implemented and evaluated in terms of effectiveness and scalability to large problem sizes and a thousand processors. The effect of certain parameters on execution time was also inspected. Empirical results demonstrated stable performance and effectiveness for all schemes, and the parametric study showed that the selected algorithmic parameters have a negligible effect on performance.

Mechanisation of large-scale agricultural fields in developing countries - a review.

PubMed

Onwude, Daniel I; Abdulstter, Rafia; Gomes, Chandima; Hashim, Norhashila

2016-09-01

Mechanisation of large-scale agricultural fields often requires the application of modern technologies such as mechanical power, automation, control and robotics. These technologies are generally associated with relatively well developed economies. The application of these technologies in some developing countries in Africa and Asia is limited by factors such as technology compatibility with the environment, availability of resources to facilitate the technology adoption, cost of technology purchase, government policies, adequacy of technology and appropriateness in addressing the needs of the population. As a result, many of the available resources have been used inadequately by farmers, who continue to rely mostly on conventional means of agricultural production, using traditional tools and equipment in most cases. This has led to low productivity and high cost of production among others. Therefore this paper attempts to evaluate the application of present day technology and its limitations to the advancement of large-scale mechanisation in developing countries of Africa and Asia. Particular emphasis is given to a general understanding of the various levels of mechanisation, present day technology, its management and application to large-scale agricultural fields. This review also focuses on/gives emphasis to future outlook that will enable a gradual, evolutionary and sustainable technological change. The study concludes that large-scale-agricultural farm mechanisation for sustainable food production in Africa and Asia must be anchored on a coherent strategy based on the actual needs and priorities of the large-scale farmers. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, Alexey; Belov, Sergey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

2012-12-01

ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, A.; Di Girolamo, A.; Klimentov, A.; Oleynik, D.; Petrosyan, A.; Atlas Collaboration

2014-06-01

ATLAS, a particle physics experiment at the Large Hadron Collider at CERN, produced petabytes of data annually through simulation production and tens of petabytes of data per year from the detector itself. The ATLAS computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we describe the ATLAS Grid Information System (AGIS), designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by the ATLAS Distributed Computing applications and services.

Compiling for Application Specific Computational Acceleration in Reconfigurable Architectures Final Report CRADA No. TSB-2033-01

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

De Supinski, B.; Caliga, D.

2017-09-28

The primary objective of this project was to develop memory optimization technology to efficiently deliver data to, and distribute data within, the SRC-6's Field Programmable Gate Array- ("FPGA") based Multi-Adaptive Processors (MAPs). The hardware/software approach was to explore efficient MAP configurations and generate the compiler technology to exploit those configurations. This memory accessing technology represents an important step towards making reconfigurable symmetric multi-processor (SMP) architectures that will be a costeffective solution for large-scale scientific computing.

The two-point correlation function for groups of galaxies in the Center for Astrophysics redshift survey

NASA Technical Reports Server (NTRS)

Ramella, Massimo; Geller, Margaret J.; Huchra, John P.

1990-01-01

The large-scale distribution of groups of galaxies selected from complete slices of the CfA redshift survey extension is examined. The survey is used to reexamine the contribution of group members to the galaxy correlation function. The relationship between the correlation function for groups and those calculated for rich clusters is discussed, and the results for groups are examined as an extension of the relation between correlation function amplitude and richness. The group correlation function indicates that groups and individual galaxies are equivalent tracers of the large-scale matter distribution. The distribution of group centers is equivalent to random sampling of the galaxy distribution. The amplitude of the correlation function for groups is consistent with an extrapolation of the amplitude-richness relation for clusters. The amplitude scaled by the mean intersystem separation is also consistent with results for richer clusters.

States of mind: emotions, body feelings, and thoughts share distributed neural networks.

PubMed

Oosterwijk, Suzanne; Lindquist, Kristen A; Anderson, Eric; Dautoff, Rebecca; Moriguchi, Yoshiya; Barrett, Lisa Feldman

2012-09-01

Scientists have traditionally assumed that different kinds of mental states (e.g., fear, disgust, love, memory, planning, concentration, etc.) correspond to different psychological faculties that have domain-specific correlates in the brain. Yet, growing evidence points to the constructionist hypothesis that mental states emerge from the combination of domain-general psychological processes that map to large-scale distributed brain networks. In this paper, we report a novel study testing a constructionist model of the mind in which participants generated three kinds of mental states (emotions, body feelings, or thoughts) while we measured activity within large-scale distributed brain networks using fMRI. We examined the similarity and differences in the pattern of network activity across these three classes of mental states. Consistent with a constructionist hypothesis, a combination of large-scale distributed networks contributed to emotions, thoughts, and body feelings, although these mental states differed in the relative contribution of those networks. Implications for a constructionist functional architecture of diverse mental states are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

A quantitative approach to the topology of large-scale structure. [for galactic clustering computation

NASA Technical Reports Server (NTRS)

Gott, J. Richard, III; Weinberg, David H.; Melott, Adrian L.

1987-01-01

A quantitative measure of the topology of large-scale structure: the genus of density contours in a smoothed density distribution, is described and applied. For random phase (Gaussian) density fields, the mean genus per unit volume exhibits a universal dependence on threshold density, with a normalizing factor that can be calculated from the power spectrum. If large-scale structure formed from the gravitational instability of small-amplitude density fluctuations, the topology observed today on suitable scales should follow the topology in the initial conditions. The technique is illustrated by applying it to simulations of galaxy clustering in a flat universe dominated by cold dark matter. The technique is also applied to a volume-limited sample of the CfA redshift survey and to a model in which galaxies reside on the surfaces of polyhedral 'bubbles'. The topology of the evolved mass distribution and 'biased' galaxy distribution in the cold dark matter models closely matches the topology of the density fluctuations in the initial conditions. The topology of the observational sample is consistent with the random phase, cold dark matter model.

Disappearance of Anisotropic Intermittency in Large-amplitude MHD Turbulence and Its Comparison with Small-amplitude MHD Turbulence

NASA Astrophysics Data System (ADS)

Yang, Liping; Zhang, Lei; He, Jiansen; Tu, Chuanyi; Li, Shengtai; Wang, Xin; Wang, Linghua

2018-03-01

Multi-order structure functions in the solar wind are reported to display a monofractal scaling when sampled parallel to the local magnetic field and a multifractal scaling when measured perpendicularly. Whether and to what extent will the scaling anisotropy be weakened by the enhancement of turbulence amplitude relative to the background magnetic strength? In this study, based on two runs of the magnetohydrodynamic (MHD) turbulence simulation with different relative levels of turbulence amplitude, we investigate and compare the scaling of multi-order magnetic structure functions and magnetic probability distribution functions (PDFs) as well as their dependence on the direction of the local field. The numerical results show that for the case of large-amplitude MHD turbulence, the multi-order structure functions display a multifractal scaling at all angles to the local magnetic field, with PDFs deviating significantly from the Gaussian distribution and a flatness larger than 3 at all angles. In contrast, for the case of small-amplitude MHD turbulence, the multi-order structure functions and PDFs have different features in the quasi-parallel and quasi-perpendicular directions: a monofractal scaling and Gaussian-like distribution in the former, and a conversion of a monofractal scaling and Gaussian-like distribution into a multifractal scaling and non-Gaussian tail distribution in the latter. These results hint that when intermittencies are abundant and intense, the multifractal scaling in the structure functions can appear even if it is in the quasi-parallel direction; otherwise, the monofractal scaling in the structure functions remains even if it is in the quasi-perpendicular direction.

Impact of Utility-Scale Distributed Wind on Transmission-Level System Operations

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

Brancucci Martinez-Anido, C.; Hodge, B. M.

2014-09-01

This report presents a new renewable integration study that aims to assess the potential for adding distributed wind to the current power system with minimal or no upgrades to the distribution or transmission electricity systems. It investigates the impacts of integrating large amounts of utility-scale distributed wind power on bulk system operations by performing a case study on the power system of the Independent System Operator-New England (ISO-NE).

Regimes of Flow over Complex Structures of Endothelial Glycocalyx: A Molecular Dynamics Simulation Study.

PubMed

Jiang, Xi Zhuo; Feng, Muye; Ventikos, Yiannis; Luo, Kai H

2018-04-10

Flow patterns on surfaces grafted with complex structures play a pivotal role in many engineering and biomedical applications. In this research, large-scale molecular dynamics (MD) simulations are conducted to study the flow over complex surface structures of an endothelial glycocalyx layer. A detailed structure of glycocalyx has been adopted and the flow/glycocalyx system comprises about 5,800,000 atoms. Four cases involving varying external forces and modified glycocalyx configurations are constructed to reveal intricate fluid behaviour. Flow profiles including temporal evolutions and spatial distributions of velocity are illustrated. Moreover, streamline length and vorticity distributions under the four scenarios are compared and discussed to elucidate the effects of external forces and glycocalyx configurations on flow patterns. Results show that sugar chain configurations affect streamline length distributions but their impact on vorticity distributions is statistically insignificant, whilst the influence of the external forces on both streamline length and vorticity distributions are trivial. Finally, a regime diagram for flow over complex surface structures is proposed to categorise flow patterns.

Large-scale modeling of rain fields from a rain cell deterministic model

NASA Astrophysics Data System (ADS)

FéRal, Laurent; Sauvageot, Henri; Castanet, Laurent; Lemorton, JoëL.; Cornet, FréDéRic; Leconte, Katia

2006-04-01

A methodology to simulate two-dimensional rain rate fields at large scale (1000 × 1000 km2, the scale of a satellite telecommunication beam or a terrestrial fixed broadband wireless access network) is proposed. It relies on a rain rate field cellular decomposition. At small scale (˜20 × 20 km2), the rain field is split up into its macroscopic components, the rain cells, described by the Hybrid Cell (HYCELL) cellular model. At midscale (˜150 × 150 km2), the rain field results from the conglomeration of rain cells modeled by HYCELL. To account for the rain cell spatial distribution at midscale, the latter is modeled by a doubly aggregative isotropic random walk, the optimal parameterization of which is derived from radar observations at midscale. The extension of the simulation area from the midscale to the large scale (1000 × 1000 km2) requires the modeling of the weather frontal area. The latter is first modeled by a Gaussian field with anisotropic covariance function. The Gaussian field is then turned into a binary field, giving the large-scale locations over which it is raining. This transformation requires the definition of the rain occupation rate over large-scale areas. Its probability distribution is determined from observations by the French operational radar network ARAMIS. The coupling with the rain field modeling at midscale is immediate whenever the large-scale field is split up into midscale subareas. The rain field thus generated accounts for the local CDF at each point, defining a structure spatially correlated at small scale, midscale, and large scale. It is then suggested that this approach be used by system designers to evaluate diversity gain, terrestrial path attenuation, or slant path attenuation for different azimuth and elevation angle directions.

A Composite Network Approach for Assessing Multi-Species Connectivity: An Application to Road Defragmentation Prioritisation

PubMed Central

Saura, Santiago; Rondinini, Carlo

2016-01-01

One of the biggest challenges in large-scale conservation is quantifying connectivity at broad geographic scales and for a large set of species. Because connectivity analyses can be computationally intensive, and the planning process quite complex when multiple taxa are involved, assessing connectivity at large spatial extents for many species turns to be often intractable. Such limitation results in that conducted assessments are often partial by focusing on a few key species only, or are generic by considering a range of dispersal distances and a fixed set of areas to connect that are not directly linked to the actual spatial distribution or mobility of particular species. By using a graph theory framework, here we propose an approach to reduce computational effort and effectively consider large assemblages of species in obtaining multi-species connectivity priorities. We demonstrate the potential of the approach by identifying defragmentation priorities in the Italian road network focusing on medium and large terrestrial mammals. We show that by combining probabilistic species graphs prior to conducting the network analysis (i) it is possible to analyse connectivity once for all species simultaneously, obtaining conservation or restoration priorities that apply for the entire species assemblage; and that (ii) those priorities are well aligned with the ones that would be obtained by aggregating the results of separate connectivity analysis for each of the individual species. This approach offers great opportunities to extend connectivity assessments to large assemblages of species and broad geographic scales. PMID:27768718

Eddington's demon: inferring galaxy mass functions and other distributions from uncertain data

NASA Astrophysics Data System (ADS)

Obreschkow, D.; Murray, S. G.; Robotham, A. S. G.; Westmeier, T.

2018-03-01

We present a general modified maximum likelihood (MML) method for inferring generative distribution functions from uncertain and biased data. The MML estimator is identical to, but easier and many orders of magnitude faster to compute than the solution of the exact Bayesian hierarchical modelling of all measurement errors. As a key application, this method can accurately recover the mass function (MF) of galaxies, while simultaneously dealing with observational uncertainties (Eddington bias), complex selection functions and unknown cosmic large-scale structure. The MML method is free of binning and natively accounts for small number statistics and non-detections. Its fast implementation in the R-package dftools is equally applicable to other objects, such as haloes, groups, and clusters, as well as observables other than mass. The formalism readily extends to multidimensional distribution functions, e.g. a Choloniewski function for the galaxy mass-angular momentum distribution, also handled by dftools. The code provides uncertainties and covariances for the fitted model parameters and approximate Bayesian evidences. We use numerous mock surveys to illustrate and test the MML method, as well as to emphasize the necessity of accounting for observational uncertainties in MFs of modern galaxy surveys.

Void probability as a function of the void's shape and scale-invariant models. [in studies of spacial galactic distribution

NASA Technical Reports Server (NTRS)

Elizalde, E.; Gaztanaga, E.

1992-01-01

The dependence of counts in cells on the shape of the cell for the large scale galaxy distribution is studied. A very concrete prediction can be done concerning the void distribution for scale invariant models. The prediction is tested on a sample of the CfA catalog, and good agreement is found. It is observed that the probability of a cell to be occupied is bigger for some elongated cells. A phenomenological scale invariant model for the observed distribution of the counts in cells, an extension of the negative binomial distribution, is presented in order to illustrate how this dependence can be quantitatively determined. An original, intuitive derivation of this model is presented.

The cosmological principle is not in the sky

NASA Astrophysics Data System (ADS)

Park, Chan-Gyung; Hyun, Hwasu; Noh, Hyerim; Hwang, Jai-chan

2017-08-01

The homogeneity of matter distribution at large scales, known as the cosmological principle, is a central assumption in the standard cosmological model. The case is testable though, thus no longer needs to be a principle. Here we perform a test for spatial homogeneity using the Sloan Digital Sky Survey Luminous Red Galaxies (LRG) sample by counting galaxies within a specified volume with the radius scale varying up to 300 h-1 Mpc. We directly confront the large-scale structure data with the definition of spatial homogeneity by comparing the averages and dispersions of galaxy number counts with allowed ranges of the random distribution with homogeneity. The LRG sample shows significantly larger dispersions of number counts than the random catalogues up to 300 h-1 Mpc scale, and even the average is located far outside the range allowed in the random distribution; the deviations are statistically impossible to be realized in the random distribution. This implies that the cosmological principle does not hold even at such large scales. The same analysis of mock galaxies derived from the N-body simulation, however, suggests that the LRG sample is consistent with the current paradigm of cosmology, thus the simulation is also not homogeneous in that scale. We conclude that the cosmological principle is neither in the observed sky nor demanded to be there by the standard cosmological world model. This reveals the nature of the cosmological principle adopted in the modern cosmology paradigm, and opens a new field of research in theoretical cosmology.

Extreme Mean and Its Applications

NASA Technical Reports Server (NTRS)

Swaroop, R.; Brownlow, J. D.

1979-01-01

Extreme value statistics obtained from normally distributed data are considered. An extreme mean is defined as the mean of p-th probability truncated normal distribution. An unbiased estimate of this extreme mean and its large sample distribution are derived. The distribution of this estimate even for very large samples is found to be nonnormal. Further, as the sample size increases, the variance of the unbiased estimate converges to the Cramer-Rao lower bound. The computer program used to obtain the density and distribution functions of the standardized unbiased estimate, and the confidence intervals of the extreme mean for any data are included for ready application. An example is included to demonstrate the usefulness of extreme mean application.

Distributed electrochemical sensors: recent advances and barriers to market adoption.

PubMed

Hoekstra, Rafael; Blondeau, Pascal; Andrade, Francisco J

2018-07-01

Despite predictions of their widespread application in healthcare and environmental monitoring, electrochemical sensors are yet to be distributed at scale, instead remaining largely confined to R&D labs. This contrasts sharply with the situation for physical sensors, which are now ubiquitous and seamlessly embedded in the mature ecosystem provided by electronics and connectivity protocols. Although chemical sensors could be integrated into the same ecosystem, there are fundamental issues with these sensors in the three key areas of analytical performance, usability, and affordability. Nevertheless, advances are being made in each of these fields, leading to hope that the deployment of automated and user-friendly low-cost electrochemical sensors is on the horizon. Here, we present a brief survey of key challenges and advances in the development of distributed electrochemical sensors for liquid samples, geared towards applications in healthcare and wellbeing, environmental monitoring, and homeland security. As will be seen, in many cases the analytical performance of the sensor is acceptable; it is usability that is the major barrier to commercial viability at this moment. Were this to be overcome, the issue of affordability could be addressed. Graphical Abstract ᅟ.

Multi-scale connectivity and graph theory highlight critical areas for conservation under climate change

USGS Publications Warehouse

Dilts, Thomas E.; Weisberg, Peter J.; Leitner, Phillip; Matocq, Marjorie D.; Inman, Richard D.; Nussear, Ken E.; Esque, Todd C.

2016-01-01

Conservation planning and biodiversity management require information on landscape connectivity across a range of spatial scales from individual home ranges to large regions. Reduction in landscape connectivity due changes in land-use or development is expected to act synergistically with alterations to habitat mosaic configuration arising from climate change. We illustrate a multi-scale connectivity framework to aid habitat conservation prioritization in the context of changing land use and climate. Our approach, which builds upon the strengths of multiple landscape connectivity methods including graph theory, circuit theory and least-cost path analysis, is here applied to the conservation planning requirements of the Mohave ground squirrel. The distribution of this California threatened species, as for numerous other desert species, overlaps with the proposed placement of several utility-scale renewable energy developments in the American Southwest. Our approach uses information derived at three spatial scales to forecast potential changes in habitat connectivity under various scenarios of energy development and climate change. By disentangling the potential effects of habitat loss and fragmentation across multiple scales, we identify priority conservation areas for both core habitat and critical corridor or stepping stone habitats. This approach is a first step toward applying graph theory to analyze habitat connectivity for species with continuously-distributed habitat, and should be applicable across a broad range of taxa.

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets.

PubMed

Bicer, Tekin; Gürsoy, Doğa; Andrade, Vincent De; Kettimuthu, Rajkumar; Scullin, William; Carlo, Francesco De; Foster, Ian T

2017-01-01

Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

Niches, models, and climate change: Assessing the assumptions and uncertainties

PubMed Central

Wiens, John A.; Stralberg, Diana; Jongsomjit, Dennis; Howell, Christine A.; Snyder, Mark A.

2009-01-01

As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some “hotspots” of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option. PMID:19822750

ATLAS Data Management Accounting with Hadoop Pig and HBase

NASA Astrophysics Data System (ADS)

Lassnig, Mario; Garonne, Vincent; Dimitrov, Gancho; Canali, Luca

2012-12-01

The ATLAS Distributed Data Management system requires accounting of its contents at the metadata layer. This presents a hard problem due to the large scale of the system, the high dimensionality of attributes, and the high rate of concurrent modifications of data. The system must efficiently account more than 90PB of disk and tape that store upwards of 500 million files across 100 sites globally. In this work a generic accounting system is presented, which is able to scale to the requirements of ATLAS. The design and architecture is presented, and the implementation is discussed. An emphasis is placed on the design choices such that the underlying data models are generally applicable to different kinds of accounting, reporting and monitoring.

Extracting Useful Semantic Information from Large Scale Corpora of Text

ERIC Educational Resources Information Center

Mendoza, Ray Padilla, Jr.

2012-01-01

Extracting and representing semantic information from large scale corpora is at the crux of computer-assisted knowledge generation. Semantic information depends on collocation extraction methods, mathematical models used to represent distributional information, and weighting functions which transform the space. This dissertation provides a…

A new method to estimate local pitch angles in spiral galaxies: Application to spiral arms and feathers in M81 and M51

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

Puerari, Ivânio; Elmegreen, Bruce G.; Block, David L., E-mail: puerari@inaoep.mx

2014-12-01

We examine 8 μm IRAC images of the grand design two-arm spiral galaxies M81 and M51 using a new method whereby pitch angles are locally determined as a function of scale and position, in contrast to traditional Fourier transform spectral analyses which fit to average pitch angles for whole galaxies. The new analysis is based on a correlation between pieces of a galaxy in circular windows of (lnR,θ) space and logarithmic spirals with various pitch angles. The diameter of the windows is varied to study different scales. The result is a best-fit pitch angle to the spiral structure as amore » function of position and scale, or a distribution function of pitch angles as a function of scale for a given galactic region or area. We apply the method to determine the distribution of pitch angles in the arm and interarm regions of these two galaxies. In the arms, the method reproduces the known pitch angles for the main spirals on a large scale, but also shows higher pitch angles on smaller scales resulting from dust feathers. For the interarms, there is a broad distribution of pitch angles representing the continuation and evolution of the spiral arm feathers as the flow moves into the interarm regions. Our method shows a multiplicity of spiral structures on different scales, as expected from gas flow processes in a gravitating, turbulent and shearing interstellar medium. We also present results for M81 using classical 1D and 2D Fourier transforms, together with a new correlation method, which shows good agreement with conventional 2D Fourier transforms.« less

Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

PubMed Central

Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.

2017-01-01

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519

The Relevancy of Large-Scale, Quantitative Methodologies in Middle Grades Education Research

ERIC Educational Resources Information Center

Mertens, Steven B.

2006-01-01

This article examines the relevancy of large-scale, quantitative methodologies in middle grades education research. Based on recommendations from national advocacy organizations, the need for more large-scale, quantitative research, combined with the application of more rigorous methodologies, is presented. Subsequent sections describe and discuss…

Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications

NASA Astrophysics Data System (ADS)

Wang, L.-P.; Ochoa-Rodríguez, S.; Onof, C.; Willems, P.

2015-09-01

Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field) that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive) technique and the commonly used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2) (Edinburgh, UK) during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban drainage system's dynamics, particularly of peak runoff flows.

Recurrent patterning in the daily foraging routes of hamadryas baboons (Papio hamadryas): spatial memory in large-scale versus small-scale space.

PubMed

Schreier, Amy L; Grove, Matt

2014-05-01

The benefits of spatial memory for foraging animals can be assessed on two distinct spatial scales: small-scale space (travel within patches) and large-scale space (travel between patches). While the patches themselves may be distributed at low density, within patches resources are likely densely distributed. We propose, therefore, that spatial memory for recalling the particular locations of previously visited feeding sites will be more advantageous during between-patch movement, where it may reduce the distances traveled by animals that possess this ability compared to those that must rely on random search. We address this hypothesis by employing descriptive statistics and spectral analyses to characterize the daily foraging routes of a band of wild hamadryas baboons in Filoha, Ethiopia. The baboons slept on two main cliffs--the Filoha cliff and the Wasaro cliff--and daily travel began and ended on a cliff; thus four daily travel routes exist: Filoha-Filoha, Filoha-Wasaro, Wasaro-Wasaro, Wasaro-Filoha. We use newly developed partial sum methods and distribution-fitting analyses to distinguish periods of area-restricted search from more extensive movements. The results indicate a single peak in travel activity in the Filoha-Filoha and Wasaro-Filoha routes, three peaks of travel activity in the Filoha-Wasaro routes, and two peaks in the Wasaro-Wasaro routes; and are consistent with on-the-ground observations of foraging and ranging behavior of the baboons. In each of the four daily travel routes the "tipping points" identified by the partial sum analyses indicate transitions between travel in small- versus large-scale space. The correspondence between the quantitative analyses and the field observations suggest great utility for using these types of analyses to examine primate travel patterns and especially in distinguishing between movement in small versus large-scale space. Only the distribution-fitting analyses are inconsistent with the field observations, which may be due to the scale at which these analyses were conducted. © 2013 Wiley Periodicals, Inc.

Simulation of a Driven Dense Granular Gas

NASA Astrophysics Data System (ADS)

Bizon, Chris; Shattuck, M. D.; Swift, J. B.; Swinney, Harry L.

1998-11-01

Event driven particle simulations quantitatively reproduce the experimental results on vibrated granular layers, including the formation of standing wave patterns(C. Bizon, M.D. Shattuck, J.B. Swift, W.D. McCormick, and H.L. Swinney, Phys. Rev. Lett. 80), pp. 57-60 (1998). and secondary instabilities(J.R. deBruyn, C. Bizon, M.D. Shattuck, D. Goldman, J.B. Swift, and H.L. Swinney, Phys. Rev. Lett. 81) (1998), to appear. . In these simulations the velocity distributions are nearly Gaussian when scaled with the local fluctuational kinetic energy (granular temperature); this suggests that inelastic dense gas kinetic theory is applicable. We perform simulations of a two-dimensional granular gas that is homogeneously driven with fluctuating forces. We find that the equation of state differs from that of an elastic dense gas and that this difference is due to a change in the distribution of relative velocities at collisions. Granular thermal conductivity and viscosity are measured by allowing the fluctuating forces to have large scale spatial gradients.

Replica and extreme-value analysis of the Jarzynski free-energy estimator

NASA Astrophysics Data System (ADS)

Palassini, Matteo; Ritort, Felix

2008-03-01

We analyze the Jarzynski estimator of free-energy differences from nonequilibrium work measurements. By a simple mapping onto Derrida's Random Energy Model, we obtain a scaling limit for the expectation of the bias of the estimator. We then derive analytical approximations in three different regimes of the scaling parameter x = log(N)/W, where N is the number of measurements and W the mean dissipated work. Our approach is valid for a generic distribution of the dissipated work, and is based on a replica symmetry breaking scheme for x >> 1, the asymptotic theory of extreme value statistics for x << 1, and a direct approach for x near one. The combination of the three analytic approximations describes well Monte Carlo data for the expectation value of the estimator, for a wide range of values of N, from N=1 to large N, and for different work distributions. Based on these results, we introduce improved free-energy estimators and discuss the application to the analysis of experimental data.

Diamond photonics for distributed quantum networks

NASA Astrophysics Data System (ADS)

Johnson, Sam; Dolan, Philip R.; Smith, Jason M.

2017-09-01

The distributed quantum network, in which nodes comprising small but well-controlled quantum states are entangled via photonic channels, has in recent years emerged as a strategy for delivering a range of quantum technologies including secure communications, enhanced sensing and scalable quantum computing. Colour centres in diamond are amongst the most promising candidates for nodes fabricated in the solid-state, offering potential for large scale production and for chip-scale integrated devices. In this review we consider the progress made and the remaining challenges in developing diamond-based nodes for quantum networks. We focus on the nitrogen-vacancy and silicon-vacancy colour centres, which have demonstrated many of the necessary attributes for these applications. We focus in particular on the use of waveguides and other photonic microstructures for increasing the efficiency with which photons emitted from these colour centres can be coupled into a network, and the use of microcavities for increasing the fraction of photons emitted that are suitable for generating entanglement between nodes.

Real Time Text Analysis

NASA Astrophysics Data System (ADS)

Senthilkumar, K.; Ruchika Mehra Vijayan, E.

2017-11-01

This paper aims to illustrate real time analysis of large scale data. For practical implementation we are performing sentiment analysis on live Twitter feeds for each individual tweet. To analyze sentiments we will train our data model on sentiWordNet, a polarity assigned wordNet sample by Princeton University. Our main objective will be to efficiency analyze large scale data on the fly using distributed computation. Apache Spark and Apache Hadoop eco system is used as distributed computation platform with Java as development language

Distributed computing testbed for a remote experimental environment

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

Butner, D.N.; Casper, T.A.; Howard, B.C.

1995-09-18

Collaboration is increasing as physics research becomes concentrated on a few large, expensive facilities, particularly in magnetic fusion energy research, with national and international participation. These facilities are designed for steady state operation and interactive, real-time experimentation. We are developing tools to provide for the establishment of geographically distant centers for interactive operations; such centers would allow scientists to participate in experiments from their home institutions. A testbed is being developed for a Remote Experimental Environment (REE), a ``Collaboratory.`` The testbed will be used to evaluate the ability of a remotely located group of scientists to conduct research on themore » DIII-D Tokamak at General Atomics. The REE will serve as a testing environment for advanced control and collaboration concepts applicable to future experiments. Process-to-process communications over high speed wide area networks provide real-time synchronization and exchange of data among multiple computer networks, while the ability to conduct research is enhanced by adding audio/video communication capabilities. The Open Software Foundation`s Distributed Computing Environment is being used to test concepts in distributed control, security, naming, remote procedure calls and distributed file access using the Distributed File Services. We are exploring the technology and sociology of remotely participating in the operation of a large scale experimental facility.« less

Efficient computation of significance levels for multiple associations in large studies of correlated data, including genomewide association studies.

PubMed

Dudbridge, Frank; Koeleman, Bobby P C

2004-09-01

Large exploratory studies, including candidate-gene-association testing, genomewide linkage-disequilibrium scans, and array-expression experiments, are becoming increasingly common. A serious problem for such studies is that statistical power is compromised by the need to control the false-positive rate for a large family of tests. Because multiple true associations are anticipated, methods have been proposed that combine evidence from the most significant tests, as a more powerful alternative to individually adjusted tests. The practical application of these methods is currently limited by a reliance on permutation testing to account for the correlated nature of single-nucleotide polymorphism (SNP)-association data. On a genomewide scale, this is both very time-consuming and impractical for repeated explorations with standard marker panels. Here, we alleviate these problems by fitting analytic distributions to the empirical distribution of combined evidence. We fit extreme-value distributions for fixed lengths of combined evidence and a beta distribution for the most significant length. An initial phase of permutation sampling is required to fit these distributions, but it can be completed more quickly than a simple permutation test and need be done only once for each panel of tests, after which the fitted parameters give a reusable calibration of the panel. Our approach is also a more efficient alternative to a standard permutation test. We demonstrate the accuracy of our approach and compare its efficiency with that of permutation tests on genomewide SNP data released by the International HapMap Consortium. The estimation of analytic distributions for combined evidence will allow these powerful methods to be applied more widely in large exploratory studies.

The Large Scale Distribution of Water Ice in the Polar Regions of the Moon

NASA Astrophysics Data System (ADS)

Jordan, A.; Wilson, J. K.; Schwadron, N.; Spence, H. E.

2017-12-01

For in situ resource utilization, one must know where water ice is on the Moon. Many datasets have revealed both surface deposits of water ice and subsurface deposits of hydrogen near the lunar poles, but it has proved difficult to resolve the differences among the locations of these deposits. Despite these datasets disagreeing on how deposits are distributed on small scales, we show that most of these datasets do agree on the large scale distribution of water ice. We present data from the Cosmic Ray Telescope for the Effects of Radiation (CRaTER) on the Lunar Reconnaissance Orbiter (LRO), LRO's Lunar Exploration Neutron Detector (LEND), the Neutron Spectrometer on Lunar Prospector (LPNS), LRO's Lyman Alpha Mapping Project (LAMP), LRO's Lunar Orbiter Laser Altimeter (LOLA), and Chandrayaan-1's Moon Mineralogy Mapper (M3). All, including those that show clear evidence for water ice, reveal surprisingly similar trends with latitude, suggesting that both surface and subsurface datasets are measuring ice. All show that water ice increases towards the poles, and most demonstrate that its signature appears at about ±70° latitude and increases poleward. This is consistent with simulations of how surface and subsurface cold traps are distributed with latitude. This large scale agreement constrains the origin of the ice, suggesting that an ancient cometary impact (or impacts) created a large scale deposit that has been rendered locally heterogeneous by subsequent impacts. Furthermore, it also shows that water ice may be available down to ±70°—latitudes that are more accessible than the poles for landing.

Semiconductor nanocrystal quantum dot synthesis approaches towards large-scale industrial production for energy applications

DOE PAGES

Hu, Michael Z.; Zhu, Ting

2015-12-04

This study reviews the experimental synthesis and engineering developments that focused on various green approaches and large-scale process production routes for quantum dots. Fundamental process engineering principles were illustrated. In relation to the small-scale hot injection method, our discussions focus on the non-injection route that could be scaled up with engineering stir-tank reactors. In addition, applications that demand to utilize quantum dots as "commodity" chemicals are discussed, including solar cells and solid-state lightings.

Reconstruction of spatial distributions of sound velocity and absorption in soft biological tissues using model ultrasonic tomographic data

NASA Astrophysics Data System (ADS)

Burov, V. A.; Zotov, D. I.; Rumyantseva, O. D.

2014-07-01

A two-step algorithm is used to reconstruct the spatial distributions of the acoustic characteristics of soft biological tissues-the sound velocity and absorption coefficient. Knowing these distributions is urgent for early detection of benign and malignant neoplasms in biological tissues, primarily in the breast. At the first stage, large-scale distributions are estimated; at the second step, they are refined with a high resolution. Results of reconstruction on the base of model initial data are presented. The principal necessity of preliminary reconstruction of large-scale distributions followed by their being taken into account at the second step is illustrated. The use of CUDA technology for processing makes it possible to obtain final images of 1024 × 1024 samples in only a few minutes.

Linear velocity fields in non-Gaussian models for large-scale structure

NASA Technical Reports Server (NTRS)

Scherrer, Robert J.

1992-01-01

Linear velocity fields in two types of physically motivated non-Gaussian models are examined for large-scale structure: seed models, in which the density field is a convolution of a density profile with a distribution of points, and local non-Gaussian fields, derived from a local nonlinear transformation on a Gaussian field. The distribution of a single component of the velocity is derived for seed models with randomly distributed seeds, and these results are applied to the seeded hot dark matter model and the global texture model with cold dark matter. An expression for the distribution of a single component of the velocity in arbitrary local non-Gaussian models is given, and these results are applied to such fields with chi-squared and lognormal distributions. It is shown that all seed models with randomly distributed seeds and all local non-Guassian models have single-component velocity distributions with positive kurtosis.

Ensemble Kalman filtering in presence of inequality constraints

NASA Astrophysics Data System (ADS)

van Leeuwen, P. J.

2009-04-01

Kalman filtering is presence of constraints is an active area of research. Based on the Gaussian assumption for the probability-density functions, it looks hard to bring in extra constraints in the formalism. On the other hand, in geophysical systems we often encounter constraints related to e.g. the underlying physics or chemistry, which are violated by the Gaussian assumption. For instance, concentrations are always non-negative, model layers have non-negative thickness, and sea-ice concentration is between 0 and 1. Several methods to bring inequality constraints into the Kalman-filter formalism have been proposed. One of them is probability density function (pdf) truncation, in which the Gaussian mass from the non-allowed part of the variables is just equally distributed over the pdf where the variables are alolwed, as proposed by Shimada et al. 1998. However, a problem with this method is that the probability that e.g. the sea-ice concentration is zero, is zero! The new method proposed here does not have this drawback. It assumes that the probability-density function is a truncated Gaussian, but the truncated mass is not distributed equally over all allowed values of the variables, but put into a delta distribution at the truncation point. This delta distribution can easily be handled with in Bayes theorem, leading to posterior probability density functions that are also truncated Gaussians with delta distributions at the truncation location. In this way a much better representation of the system is obtained, while still keeping most of the benefits of the Kalman-filter formalism. In the full Kalman filter the formalism is prohibitively expensive in large-scale systems, but efficient implementation is possible in ensemble variants of the kalman filter. Applications to low-dimensional systems and large-scale systems will be discussed.

High-resolution simulation of deep pencil beam surveys - analysis of quasi-periodicity

NASA Astrophysics Data System (ADS)

Weiss, A. G.; Buchert, T.

1993-07-01

We carry out pencil beam constructions in a high-resolution simulation of the large-scale structure of galaxies. The initial density fluctuations are taken to have a truncated power spectrum. All the models have {OMEGA} = 1. As an example we present the results for the case of "Hot-Dark-Matter" (HDM) initial conditions with scale-free n = 1 power index on large scales as a representative of models with sufficient large-scale power. We use an analytic approximation for particle trajectories of a self-gravitating dust continuum and apply a local dynamical biasing of volume elements to identify luminous matter in the model. Using this method, we are able to resolve formally a simulation box of 1200h^-1^ Mpc (e.g. for HDM initial conditions) down to the scale of galactic halos using 2160^3^ particles. We consider this as the minimal resolution necessary for a sensible simulation of deep pencil beam data. Pencil beam probes are taken for a given epoch using the parameters of observed beams. In particular, our analysis concentrates on the detection of a quasi-periodicity in the beam probes using several different methods. The resulting beam ensembles are analyzed statistically using number distributions, pair-count histograms, unnormalized pair-counts, power spectrum analysis and trial-period folding. Periodicities are classified according to their significance level in the power spectrum of the beams. The simulation is designed for application to parameter studies which prepare future observational projects. We find that a large percentage of the beams show quasi- periodicities with periods which cluster at a certain length scale. The periods found range between one and eight times the cutoff length in the initial fluctuation spectrum. At significance levels similar to those of the data of Broadhurst et al. (1990), we find about 15% of the pencil beams to show periodicities, about 30% of which are around the mean separation of rich clusters, while the distribution of scales reaches values of more than 200h^-1^ Mpc. The detection of periodicities larger than the typical void size must not be due to missing of "walls" (like the so called "Great Wall" seen in the CfA catalogue of galaxies), but can be due to different clustering properties of galaxies along the beams.

The MICE Grand Challenge lightcone simulation - II. Halo and galaxy catalogues

NASA Astrophysics Data System (ADS)

Crocce, M.; Castander, F. J.; Gaztañaga, E.; Fosalba, P.; Carretero, J.

2015-10-01

This is the second in a series of three papers in which we present an end-to-end simulation from the MICE collaboration, the MICE Grand Challenge (MICE-GC) run. The N-body contains about 70 billion dark-matter particles in a (3 h-1 Gpc)3 comoving volume spanning five orders of magnitude in dynamical range. Here, we introduce the halo and galaxy catalogues built upon it, both in a wide (5000 deg2) and deep (z < 1.4) lightcone and in several comoving snapshots. Haloes were resolved down to few 1011 h-1 M⊙. This allowed us to model galaxies down to absolute magnitude Mr < -18.9. We used a new hybrid halo occupation distribution and abundance matching technique for galaxy assignment. The catalogue includes the spectral energy distributions of all galaxies. We describe a variety of halo and galaxy clustering applications. We discuss how mass resolution effects can bias the large-scale two-pt clustering amplitude of poorly resolved haloes at the ≲5 per cent level, and their three-pt correlation function. We find a characteristic scale-dependent bias of ≲6 per cent across the BAO feature for haloes well above M⋆ ˜ 1012 h-1 M⊙ and for luminous red galaxy like galaxies. For haloes well below M⋆ the scale dependence at 100 h-1 Mpc is ≲2 per cent. Lastly, we discuss the validity of the large-scale Kaiser limit across redshift and departures from it towards non-linear scales. We make the current version of the lightcone halo and galaxy catalogue (MICECATv1.0) publicly available through a dedicated web portal to help develop and exploit the new generation of astronomical surveys.

Robopedia: Leveraging Sensorpedia for Web-Enabled Robot Control

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

Resseguie, David R

There is a growing interest in building Internetscale sensor networks that integrate sensors from around the world into a single unified system. In contrast, robotics application development has primarily focused on building specialized systems. These specialized systems take scalability and reliability into consideration, but generally neglect exploring the key components required to build a large scale system. Integrating robotic applications with Internet-scale sensor networks will unify specialized robotics applications and provide answers to large scale implementation concerns. We focus on utilizing Internet-scale sensor network technology to construct a framework for unifying robotic systems. Our framework web-enables a surveillance robot smore » sensor observations and provides a webinterface to the robot s actuators. This lets robots seamlessly integrate into web applications. In addition, the framework eliminates most prerequisite robotics knowledge, allowing for the creation of general web-based robotics applications. The framework also provides mechanisms to create applications that can interface with any robot. Frameworks such as this one are key to solving large scale mobile robotics implementation problems. We provide an overview of previous Internetscale sensor networks, Sensorpedia (an ad-hoc Internet-scale sensor network), our framework for integrating robots with Sensorpedia, two applications which illustrate our frameworks ability to support general web-based robotic control, and offer experimental results that illustrate our framework s scalability, feasibility, and resource requirements.« less

Impact of the Dominant Large-scale Teleconnections on Winter Temperature Variability over East Asia

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Kim, Hae-Dong

2013-01-01

Monthly mean geopotential height for the past 33 DJF seasons archived in Modern Era Retrospective analysis for Research and Applications reanalysis is decomposed into the large-scale teleconnection patterns to explain their impacts on winter temperature variability over East Asia. Following Arctic Oscillation (AO) that explains the largest variance, East Atlantic/West Russia (EA/WR), West Pacific (WP) and El Nino-Southern Oscillation (ENSO) are identified as the first four leading modes that significantly explain East Asian winter temperature variation. While the northern part of East Asia north of 50N is prevailed by AO and EA/WR impacts, temperature in the midlatitudes (30N-50N), which include Mongolia, northeastern China, Shandong area, Korea, and Japan, is influenced by combined effect of the four leading teleconnections. ENSO impact on average over 33 winters is relatively weaker than the impact of the other three teleconnections. WP impact, which has received less attention than ENSO in earlier studies, characterizes winter temperatures over Korea, Japan, and central to southern China region south of 30N mainly by advective process from the Pacific. Upper level wave activity fluxes reveal that, for the AO case, the height and circulation anomalies affecting midlatitude East Asian winter temperature is mainly located at higher latitudes north of East Asia. Distribution of the fluxes also explains that the stationary wave train associated with EA/WR propagates southeastward from the western Russia, affecting the East Asian winter temperature. Investigation on the impact of each teleconnection for the selected years reveals that the most dominant teleconnection over East Asia is not the same at all years, indicating a great deal of interannual variability. Comparison in temperature anomaly distributions between observation and temperature anomaly constructed using the combined effect of four leading teleconnections clearly show a reasonable consistency between them, demonstrating that the seasonal winter temperature distributions over East Asia are substantially explained by these four large-scale circulation impacts.

Statistical Compression of Wind Speed Data

NASA Astrophysics Data System (ADS)

Tagle, F.; Castruccio, S.; Crippa, P.; Genton, M.

2017-12-01

In this work we introduce a lossy compression approach that utilizes a stochastic wind generator based on a non-Gaussian distribution to reproduce the internal climate variability of daily wind speed as represented by the CESM Large Ensemble over Saudi Arabia. Stochastic wind generators, and stochastic weather generators more generally, are statistical models that aim to match certain statistical properties of the data on which they are trained. They have been used extensively in applications ranging from agricultural models to climate impact studies. In this novel context, the parameters of the fitted model can be interpreted as encoding the information contained in the original uncompressed data. The statistical model is fit to only 3 of the 30 ensemble members and it adequately captures the variability of the ensemble in terms of seasonal internannual variability of daily wind speed. To deal with such a large spatial domain, it is partitioned into 9 region, and the model is fit independently to each of these. We further discuss a recent refinement of the model, which relaxes this assumption of regional independence, by introducing a large-scale component that interacts with the fine-scale regional effects.

Mapping cold-water coral habitats at different scales within the Northern Ionian Sea (Central Mediterranean): an assessment of coral coverage and associated vulnerability.

PubMed

Savini, Alessandra; Vertino, Agostina; Marchese, Fabio; Beuck, Lydia; Freiwald, André

2014-01-01

In this study, we mapped the distribution of Cold-Water Coral (CWC) habitats on the northern Ionian Margin (Mediterranean Sea), with an emphasis on assessing coral coverage at various spatial scales over an area of 2,000 km(2) between 120 and 1,400 m of water depth. Our work made use of a set of data obtained from ship-based research surveys. Multi-scale seafloor mapping data, video inspections, and previous results from sediment samples were integrated and analyzed using Geographic Information System (GIS)-based tools. Results obtained from the application of spatial and textural analytical techniques to acoustic meso-scale maps (i.e. a Digital Terrain Model (DTM) of the seafloor at a 40 m grid cell size and associated terrain parameters) and large-scale maps (i.e. Side-Scan Sonar (SSS) mosaics of 1 m in resolution ground-truthed using underwater video observations) were integrated and revealed that, at the meso-scale level, the main morphological pattern (i.e. the aggregation of mound-like features) associated with CWC habitat occurrences was widespread over a total area of 600 km(2). Single coral mounds were isolated from the DTM and represented the geomorphic proxies used to model coral distributions within the investigated area. Coral mounds spanned a total area of 68 km(2) where different coral facies (characterized using video analyses and mapped on SSS mosaics) represent the dominant macro-habitat. We also mapped and classified anthropogenic threats that were identifiable within the examined videos, and, here, discuss their relationship to the mapped distribution of coral habitats and mounds. The combined results (from multi-scale habitat mapping and observations of the distribution of anthropogenic threats) provide the first quantitative assessment of CWC coverage for a Mediterranean province and document the relevant role of seafloor geomorphology in influencing habitat vulnerability to different types of human pressures.

Applications of Magnetic Suspension Technology to Large Scale Facilities: Progress, Problems and Promises

NASA Technical Reports Server (NTRS)

Britcher, Colin P.

1997-01-01

This paper will briefly review previous work in wind tunnel Magnetic Suspension and Balance Systems (MSBS) and will examine the handful of systems around the world currently known to be in operational condition or undergoing recommissioning. Technical developments emerging from research programs at NASA and elsewhere will be reviewed briefly, where there is potential impact on large-scale MSBSS. The likely aerodynamic applications for large MSBSs will be addressed, since these applications should properly drive system designs. A recently proposed application to ultra-high Reynolds number testing will then be addressed in some detail. Finally, some opinions on the technical feasibility and usefulness of a large MSBS will be given.

Bridging the gap between small and large scale sediment budgets? - A scaling challenge in the Upper Rhone Basin, Switzerland

NASA Astrophysics Data System (ADS)

Schoch, Anna; Blöthe, Jan; Hoffmann, Thomas; Schrott, Lothar

2016-04-01

A large number of sediment budgets have been compiled on different temporal and spatial scales in alpine regions. Detailed sediment budgets based on the quantification of a number of sediment storages (e.g. talus cones, moraine deposits) exist only for a few small scale drainage basins (up to 10² km²). In contrast, large scale sediment budgets (> 10³ km²) consider only long term sediment sinks such as valley fills and lakes. Until now, these studies often neglect small scale sediment storages in the headwaters. However, the significance of these sediment storages have been reported. A quantitative verification whether headwaters function as sediment source regions is lacking. Despite substantial transport energy in mountain environments due to steep gradients and high relief, sediment flux in large river systems is frequently disconnected from alpine headwaters. This leads to significant storage of coarse-grained sediment along the flow path from rockwall source regions to large sedimentary sinks in major alpine valleys. To improve the knowledge on sediment budgets in large scale alpine catchments and to bridge the gap between small and large scale sediment budgets, we apply a multi-method approach comprising investigations on different spatial scales in the Upper Rhone Basin (URB). The URB is the largest inneralpine basin in the European Alps with a size of > 5400 km². It is a closed system with Lake Geneva acting as an ultimate sediment sink for suspended and clastic sediment. We examine the spatial pattern and volumes of sediment storages as well as the morphometry on the local and catchment-wide scale. We mapped sediment storages and bedrock in five sub-regions of the study area (Goms, Lötschen valley, Val d'Illiez, Vallée de la Liène, Turtmann valley) in the field and from high-resolution remote sensing imagery to investigate the spatial distribution of different sediment storage types (e.g. talus deposits, debris flow cones, alluvial fans). These sub-regions cover all three litho-tectonic units of the URB (Helvetic nappes, Penninic nappes, External massifs) and different catchment sizes to capture the inherent variability. Different parameters characterizing topography, surface characteristics, and vegetation cover are analyzed for each storage type. The data is then used in geostatistical models (PCA, stepwise logistic regression) to predict the spatial distribution of sediment storage for the whole URB. We further conduct morphometric analyses of the URB to gain information on the varying degree of glacial imprint and postglacial landscape evolution and their control on the spatial distribution of sediment storage in a large scale drainage basin. Geophysical methods (ground penetrating radar and electrical resistivity tomography) are applied on different sediment storage types on the local scale to estimate mean thicknesses. Additional data from published studies are used to complement our dataset. We integrate the local data in the statistical model on the spatial distribution of sediment storages for the whole URB. Hence, we can extrapolate the stored sediment volumes to the regional scale in order to bridge the gap between small and large scale studies.

Void probability as a function of the void's shape and scale-invariant models

NASA Technical Reports Server (NTRS)

Elizalde, E.; Gaztanaga, E.

1991-01-01

The dependence of counts in cells on the shape of the cell for the large scale galaxy distribution is studied. A very concrete prediction can be done concerning the void distribution for scale invariant models. The prediction is tested on a sample of the CfA catalog, and good agreement is found. It is observed that the probability of a cell to be occupied is bigger for some elongated cells. A phenomenological scale invariant model for the observed distribution of the counts in cells, an extension of the negative binomial distribution, is presented in order to illustrate how this dependence can be quantitatively determined. An original, intuitive derivation of this model is presented.

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

"We get by with a little help from our friends": Small-scale informal and large-scale formal peer distribution networks of sterile injecting equipment in Australia.

PubMed

Newland, Jamee; Newman, Christy; Treloar, Carla

2016-08-01

In Australia, sterile needles and syringes are distributed to people who inject drugs (PWID) through formal services for the purposes of preventing blood borne viruses (BBV). Peer distribution involves people acquiring needles from formal services and redistributing them to others. This paper investigates the dynamics of the distribution of sterile injecting equipment among networks of people who inject drugs in four sites in New South Wales (NSW), Australia. Qualitative data exploring the practice of peer distribution were collected through in-depth, semi-structured interviews and participatory social network mapping. These interviews explored injecting equipment demand, access to services, relationship pathways through which peer distribution occurred, an estimate of the size of the different peer distribution roles and participants' understanding of the illegality of peer distribution in NSW. Data were collected from 32 participants, and 31 (98%) reported participating in peer distribution in the months prior to interview. Of those 31 participants, five reported large-scale formal distribution, with an estimated volume of 34,970 needles and syringes annually. Twenty-two participated in reciprocal exchange, where equipment was distributed and received on an informal basis that appeared dependent on context and circumstance and four participants reported recipient peer distribution as their only access to sterile injecting equipment. Most (n=27) were unaware that it was illegal to distribute injecting equipment to their peers. Peer distribution was almost ubiquitous amongst the PWID participating in the study, and although five participants reported taking part in the highly organised, large-scale distribution of injecting equipment for altruistic reasons, peer distribution was more commonly reported to take place in small networks of friends and/or partners for reasons of convenience. The law regarding the illegality of peer distribution needs to change so that NSPs can capitalise on peer distribution to increase the options available to PWID and to acknowledge PWID as essential harm reduction agents in the prevention of BBVs. Copyright © 2016 Elsevier B.V. All rights reserved.

Percolation Analysis as a Tool to Describe the Topology of the Large Scale Structure of the Universe

NASA Astrophysics Data System (ADS)

Yess, Capp D.

1997-09-01

Percolation analysis is the study of the properties of clusters. In cosmology, it is the statistics of the size and number of clusters. This thesis presents a refinement of percolation analysis and its application to astronomical data. An overview of the standard model of the universe and the development of large scale structure is presented in order to place the study in historical and scientific context. Then using percolation statistics we, for the first time, demonstrate the universal character of a network pattern in the real space, mass distributions resulting from nonlinear gravitational instability of initial Gaussian fluctuations. We also find that the maximum of the number of clusters statistic in the evolved, nonlinear distributions is determined by the effective slope of the power spectrum. Next, we present percolation analyses of Wiener Reconstructions of the IRAS 1.2 Jy Redshift Survey. There are ten reconstructions of galaxy density fields in real space spanning the range β = 0.1 to 1.0, where β=Ω0.6/b,/ Ω is the present dimensionless density and b is the linear bias factor. Our method uses the growth of the largest cluster statistic to characterize the topology of a density field, where Gaussian randomized versions of the reconstructions are used as standards for analysis. For the reconstruction volume of radius, R≈100h-1 Mpc, percolation analysis reveals a slight 'meatball' topology for the real space, galaxy distribution of the IRAS survey. Finally, we employ a percolation technique developed for pointwise distributions to analyze two-dimensional projections of the three northern and three southern slices in the Las Campanas Redshift Survey and then give consideration to further study of the methodology, errors and application of percolation. We track the growth of the largest cluster as a topological indicator to a depth of 400 h-1 Mpc, and report an unambiguous signal, with high signal-to-noise ratio, indicating a network topology which in two dimensions is indicative of a filamentary distribution. It is hoped that one day percolation analysis can characterize the structure of the universe to a degree that will aid theorists in confidently describing the nature of our world.

Architectural Visualization of C/C++ Source Code for Program Comprehension

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

Panas, T; Epperly, T W; Quinlan, D

2006-09-01

Structural and behavioral visualization of large-scale legacy systems to aid program comprehension is still a major challenge. The challenge is even greater when applications are implemented in flexible and expressive languages such as C and C++. In this paper, we consider visualization of static and dynamic aspects of large-scale scientific C/C++ applications. For our investigation, we reuse and integrate specialized analysis and visualization tools. Furthermore, we present a novel layout algorithm that permits a compressive architectural view of a large-scale software system. Our layout is unique in that it allows traditional program visualizations, i.e., graph structures, to be seen inmore » relation to the application's file structure.« less

Latitudinal variability of large-scale coronal temperature and its association with the density and the global magnetic field

NASA Technical Reports Server (NTRS)

Guhathakurta, M.; Fisher, R. R.

1994-01-01

In this paper we utilize the latitiude distribution of the coronal temperature during the period 1984-1992 that was derived in a paper by Guhathakurta et al, 1993, utilizing ground-based intensity observations of the green (5303 A Fe XIV) and red (6374 A Fe X) coronal forbidden lines from the National Solar Observatory at Sacramento Peak, and establish it association with the global magnetic field and the density distributions in the corona. A determination of plasma temperature, T, was estimated from the intensity ratio Fe X/Fe XIV (where T is inversely proportional to the ratio), since both emission lines come from ionized states of Fe, and the ratio is only weakly dependent on density. We observe that there is a large-scale organization of the inferred coronal temperature distribution that is associated with the large-scale, weak magnetic field structures and bright coronal features; this organization tends to persist through most of the magnetic activity cycle. These high-temperature structures exhibit time-space characteristics which are similar to those of the polar crown filaments. This distribution differs in spatial and temporal characterization from the traditional picture of sunspot and active region evolution over the range of the sunspot cycle, which are manifestations of the small-scale, strong magnetic field regions.

Large-scale precipitation estimation using Kalpana-1 IR measurements and its validation using GPCP and GPCC data

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mahesh, C.; Gairola, Rakesh M.

2011-12-01

Large-scale precipitation estimation is very important for climate science because precipitation is a major component of the earth's water and energy cycles. In the present study, the GOES precipitation index technique has been applied to the Kalpana-1 satellite infrared (IR) images of every three-hourly, i.e., of 0000, 0300, 0600,…., 2100 hours UTC, for rainfall estimation as a preparatory to the INSAT-3D. After the temperatures of all the pixels in a grid are known, they are distributed to generate a three-hourly 24-class histogram of brightness temperatures of IR (10.5-12.5 μm) images for a 1.0° × 1.0° latitude/longitude box. The daily, monthly, and seasonal rainfall have been estimated using these three-hourly rain estimates for the entire south-west monsoon period of 2009 in the present study. To investigate the potential of these rainfall estimates, the validation of monthly and seasonal rainfall estimates has been carried out using the Global Precipitation Climatology Project and Global Precipitation Climatology Centre data. The validation results show that the present technique works very well for the large-scale precipitation estimation qualitatively as well as quantitatively. The results also suggest that the simple IR-based estimation technique can be used to estimate rainfall for tropical areas at a larger temporal scale for climatological applications.

Mems: Platform for Large-Scale Integrated Vacuum Electronic Circuits

DTIC Science & Technology

2017-03-20

SECURITY CLASSIFICATION OF: The objective of the LIVEC advanced study project was to develop a platform for large-scale integrated vacuum electronic ...Distribution Unlimited UU UU UU UU 20-03-2017 1-Jul-2014 30-Jun-2015 Final Report: MEMS Platform for Large-Scale Integrated Vacuum Electronic ... Electronic Circuits (LIVEC) Contract No: W911NF-14-C-0093 COR Dr. James Harvey U.S. ARO RTP, NC 27709-2211 Phone: 702-696-2533 e-mail

The AppScale Cloud Platform

PubMed Central

Krintz, Chandra

2013-01-01

AppScale is an open source distributed software system that implements a cloud platform as a service (PaaS). AppScale makes cloud applications easy to deploy and scale over disparate cloud fabrics, implementing a set of APIs and architecture that also makes apps portable across the services they employ. AppScale is API-compatible with Google App Engine (GAE) and thus executes GAE applications on-premise or over other cloud infrastructures, without modification. PMID:23828721

Effects of Eddy Viscosity on Time Correlations in Large Eddy Simulation

NASA Technical Reports Server (NTRS)

He, Guowei; Rubinstein, R.; Wang, Lian-Ping; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

Subgrid-scale (SGS) models for large. eddy simulation (LES) have generally been evaluated by their ability to predict single-time statistics of turbulent flows such as kinetic energy and Reynolds stresses. Recent application- of large eddy simulation to the evaluation of sound sources in turbulent flows, a problem in which time, correlations determine the frequency distribution of acoustic radiation, suggest that subgrid models should also be evaluated by their ability to predict time correlations in turbulent flows. This paper compares the two-point, two-time Eulerian velocity correlation evaluated from direct numerical simulation (DNS) with that evaluated from LES, using a spectral eddy viscosity, for isotropic homogeneous turbulence. It is found that the LES fields are too coherent, in the sense that their time correlations decay more slowly than the corresponding time. correlations in the DNS fields. This observation is confirmed by theoretical estimates of time correlations using the Taylor expansion technique. Tile reason for the slower decay is that the eddy viscosity does not include the random backscatter, which decorrelates fluid motion at large scales. An effective eddy viscosity associated with time correlations is formulated, to which the eddy viscosity associated with energy transfer is a leading order approximation.

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.

Assessing the role of mini-applications in predicting key performance characteristics of scientific and engineering applications

DOE PAGES

Barrett, R. F.; Crozier, P. S.; Doerfler, D. W.; ...

2014-09-28

Computational science and engineering application programs are typically large, complex, and dynamic, and are often constrained by distribution limitations. As a means of making tractable rapid explorations of scientific and engineering application programs in the context of new, emerging, and future computing architectures, a suite of miniapps has been created to serve as proxies for full scale applications. Each miniapp is designed to represent a key performance characteristic that does or is expected to significantly impact the runtime performance of an application program. In this paper we introduce a methodology for assessing the ability of these miniapps to effectively representmore » these performance issues. We applied this methodology to four miniapps, examining the linkage between them and an application they are intended to represent. Herein we evaluate the fidelity of that linkage. This work represents the initial steps required to begin to answer the question, ''Under what conditions does a miniapp represent a key performance characteristic in a full app?''« less

Speed scanning system based on solid-state microchip laser for architectural planning

NASA Astrophysics Data System (ADS)

Redka, Dmitriy; Grishkanich, Alexsandr S.; Kolmakov, Egor; Tsvetkov, Konstantin

2017-10-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

Coordinate measuring system based on microchip lasers for reverse prototyping

NASA Astrophysics Data System (ADS)

Iakovlev, Alexey; Grishkanich, Alexsandr S.; Redka, Dmitriy; Tsvetkov, Konstantin

2017-02-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of chip and microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

AMRZone: A Runtime AMR Data Sharing Framework For Scientific Applications

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

Zhang, Wenzhao; Tang, Houjun; Harenberg, Steven

Frameworks that facilitate runtime data sharing across multiple applications are of great importance for scientific data analytics. Although existing frameworks work well over uniform mesh data, they can not effectively handle adaptive mesh refinement (AMR) data. Among the challenges to construct an AMR-capable framework include: (1) designing an architecture that facilitates online AMR data management; (2) achieving a load-balanced AMR data distribution for the data staging space at runtime; and (3) building an effective online index to support the unique spatial data retrieval requirements for AMR data. Towards addressing these challenges to support runtime AMR data sharing across scientific applications,more » we present the AMRZone framework. Experiments over real-world AMR datasets demonstrate AMRZone's effectiveness at achieving a balanced workload distribution, reading/writing large-scale datasets with thousands of parallel processes, and satisfying queries with spatial constraints. Moreover, AMRZone's performance and scalability are even comparable with existing state-of-the-art work when tested over uniform mesh data with up to 16384 cores; in the best case, our framework achieves a 46% performance improvement.« less

An Adaptive Priority Tuning System for Optimized Local CPU Scheduling using BOINC Clients

NASA Astrophysics Data System (ADS)

Mnaouer, Adel B.; Ragoonath, Colin

2010-11-01

Volunteer Computing (VC) is a Distributed Computing model which utilizes idle CPU cycles from computing resources donated by volunteers who are connected through the Internet to form a very large-scale, loosely coupled High Performance Computing environment. Distributed Volunteer Computing environments such as the BOINC framework is concerned mainly with the efficient scheduling of the available resources to the applications which require them. The BOINC framework thus contains a number of scheduling policies/algorithms both on the server-side and on the client which work together to maximize the available resources and to provide a degree of QoS in an environment which is highly volatile. This paper focuses on the BOINC client and introduces an adaptive priority tuning client side middleware application which improves the execution times of Work Units (WUs) while maintaining an acceptable Maximum Response Time (MRT) for the end user. We have conducted extensive experimentation of the proposed system and the results show clear speedup of BOINC applications using our optimized middleware as opposed to running using the original BOINC client.

Exploring Cloud Computing for Large-scale Scientific Applications

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

Lin, Guang; Han, Binh; Yin, Jian

This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

Newton Methods for Large Scale Problems in Machine Learning

ERIC Educational Resources Information Center

Hansen, Samantha Leigh

2014-01-01

The focus of this thesis is on practical ways of designing optimization algorithms for minimizing large-scale nonlinear functions with applications in machine learning. Chapter 1 introduces the overarching ideas in the thesis. Chapters 2 and 3 are geared towards supervised machine learning applications that involve minimizing a sum of loss…

Experience with specifications applicable to certification. [of photovoltaic modules for large-scale application

NASA Technical Reports Server (NTRS)

Ross, R. G., Jr.

1982-01-01

The Jet Propulsion Laboratory has developed a number of photovoltaic test and measurement specifications to guide the development of modules toward the requirements of future large-scale applications. Experience with these specifications and the extensive module measurement and testing that has accompanied their use is examined. Conclusions are drawn relative to three aspects of product certification: performance measurement, endurance testing and safety evaluation.

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

PubMed

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

Developing eThread pipeline using SAGA-pilot abstraction for large-scale structural bioinformatics.

PubMed

Ragothaman, Anjani; Boddu, Sairam Chowdary; Kim, Nayong; Feinstein, Wei; Brylinski, Michal; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread--a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure.

Developing eThread Pipeline Using SAGA-Pilot Abstraction for Large-Scale Structural Bioinformatics

PubMed Central

Ragothaman, Anjani; Feinstein, Wei; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread—a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure. PMID:24995285

Multilevel Item Response Modeling: Applications to Large-Scale Assessment of Academic Achievement

ERIC Educational Resources Information Center

Zheng, Xiaohui

2009-01-01

The call for standards-based reform and educational accountability has led to increased attention to large-scale assessments. Over the past two decades, large-scale assessments have been providing policymakers and educators with timely information about student learning and achievement to facilitate their decisions regarding schools, teachers and…

Advanced Operating System Technologies

NASA Astrophysics Data System (ADS)

Cittolin, Sergio; Riccardi, Fabio; Vascotto, Sandro

In this paper we describe an R&D effort to define an OS architecture suitable for the requirements of the Data Acquisition and Control of an LHC experiment. Large distributed computing systems are foreseen to be the core part of the DAQ and Control system of the future LHC experiments. Neworks of thousands of processors, handling dataflows of several gigaBytes per second, with very strict timing constraints (microseconds), will become a common experience in the following years. Problems like distributyed scheduling, real-time communication protocols, failure-tolerance, distributed monitoring and debugging will have to be faced. A solid software infrastructure will be required to manage this very complicared environment, and at this moment neither CERN has the necessary expertise to build it, nor any similar commercial implementation exists. Fortunately these problems are not unique to the particle and high energy physics experiments, and the current research work in the distributed systems field, especially in the distributed operating systems area, is trying to address many of the above mentioned issues. The world that we are going to face in the next ten years will be quite different and surely much more interconnected than the one we see now. Very ambitious projects exist, planning to link towns, nations and the world in a single "Data Highway". Teleconferencing, Video on Demend, Distributed Multimedia Applications are just a few examples of the very demanding tasks to which the computer industry is committing itself. This projects are triggering a great research effort in the distributed, real-time micro-kernel based operating systems field and in the software enginering areas. The purpose of our group is to collect the outcame of these different research efforts, and to establish a working environment where the different ideas and techniques can be tested, evaluated and possibly extended, to address the requirements of a DAQ and Control System suitable for LHC. Our work started in the second half of 1994, with a research agreement between CERN and Chorus Systemes (France), world leader in the micro-kernel OS technology. The Chorus OS is targeted to distributed real-time applications, and it can very efficiently support different "OS personalities" in the same environment, like Posix, UNIX, and a CORBA compliant distributed object architecture. Projects are being set-up to verify the suitability of our work for LHC applications, we are building a scaled-down prototype of the DAQ system foreseen for the CMS experiment at LHC, where we will directly test our protocols and where we will be able to make measurements and benchmarks, guiding our development and allowing us to build an analytical model of the system, suitable for simulation and large scale verification.

Macroecology of unicellular organisms - patterns and processes.

PubMed

Soininen, Janne

2012-02-01

Macroecology examines the relationship between organisms and their environment at large spatial (and temporal) scales. Typically, macroecologists explain the large-scale patterns of abundance, distribution and diversity. Despite the difficulties in sampling and characterizing microbial diversity, macroecologists have recently also been interested in unicellular organisms. Here, I review the current advances made in microbial macroecology, as well as discuss related ecosystem functions. Overall, it seems that microorganisms suit surprisingly well to known species abundance distributions and show positive relationship between distribution and adundance. Microbial species-area and distance-decay relationships tend to be weaker than for macroorganisms, but nonetheless significant. Few findings on altitudinal gradients in unicellular taxa seem to differ greatly from corresponding findings for larger taxa, whereas latitudinal gradients among microorganisms have either been clearly evident or absent depending on the context. Literature also strongly emphasizes the role of spatial scale for the patterns of diversity and suggests that patterns are affected by species traits as well as ecosystem characteristics. Finally, I discuss the large role of local biotic and abiotic variables driving the community assembly in unicellular taxa and eventually dictating how multiple ecosystem processes are performed. Present review highlights the fact that most microorganisms may not differ fundamentally from larger taxa in their large-scale distribution patterns. Yet, review also shows that many aspects of microbial macroecology are still relatively poorly understood and specific patterns depend on focal taxa and ecosystem concerned. © 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.

Ensemble averaged structure–function relationship for nanocrystals: effective superparamagnetic Fe clusters with catalytically active Pt skin [Ensemble averaged structure-function relationship for composite nanocrystals: magnetic bcc Fe clusters with catalytically active fcc Pt skin

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

Petkov, Valeri; Prasai, Binay; Shastri, Sarvjit

Practical applications require the production and usage of metallic nanocrystals (NCs) in large ensembles. Besides, due to their cluster-bulk solid duality, metallic NCs exhibit a large degree of structural diversity. This poses the question as to what atomic-scale basis is to be used when the structure–function relationship for metallic NCs is to be quantified precisely. In this paper, we address the question by studying bi-functional Fe core-Pt skin type NCs optimized for practical applications. In particular, the cluster-like Fe core and skin-like Pt surface of the NCs exhibit superparamagnetic properties and a superb catalytic activity for the oxygen reduction reaction,more » respectively. We determine the atomic-scale structure of the NCs by non-traditional resonant high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Using the experimental structure data we explain the observed magnetic and catalytic behavior of the NCs in a quantitative manner. Lastly, we demonstrate that NC ensemble-averaged 3D positions of atoms obtained by advanced X-ray scattering techniques are a very proper basis for not only establishing but also quantifying the structure–function relationship for the increasingly complex metallic NCs explored for practical applications.« less

Reynolds number scaling to predict droplet size distribution in dispersed and undispersed subsurface oil releases.

PubMed

Li, Pu; Weng, Linlu; Niu, Haibo; Robinson, Brian; King, Thomas; Conmy, Robyn; Lee, Kenneth; Liu, Lei

2016-12-15

This study was aimed at testing the applicability of modified Weber number scaling with Alaska North Slope (ANS) crude oil, and developing a Reynolds number scaling approach for oil droplet size prediction for high viscosity oils. Dispersant to oil ratio and empirical coefficients were also quantified. Finally, a two-step Rosin-Rammler scheme was introduced for the determination of droplet size distribution. This new approach appeared more advantageous in avoiding the inconsistency in interfacial tension measurements, and consequently delivered concise droplet size prediction. Calculated and observed data correlated well based on Reynolds number scaling. The relation indicated that chemical dispersant played an important role in reducing the droplet size of ANS under different seasonal conditions. The proposed Reynolds number scaling and two-step Rosin-Rammler approaches provide a concise, reliable way to predict droplet size distribution, supporting decision making in chemical dispersant application during an offshore oil spill. Copyright © 2016 Elsevier Ltd. All rights reserved.

Federated learning of predictive models from federated Electronic Health Records.

PubMed

Brisimi, Theodora S; Chen, Ruidi; Mela, Theofanie; Olshevsky, Alex; Paschalidis, Ioannis Ch; Shi, Wei

2018-04-01

In an era of "big data," computationally efficient and privacy-aware solutions for large-scale machine learning problems become crucial, especially in the healthcare domain, where large amounts of data are stored in different locations and owned by different entities. Past research has been focused on centralized algorithms, which assume the existence of a central data repository (database) which stores and can process the data from all participants. Such an architecture, however, can be impractical when data are not centrally located, it does not scale well to very large datasets, and introduces single-point of failure risks which could compromise the integrity and privacy of the data. Given scores of data widely spread across hospitals/individuals, a decentralized computationally scalable methodology is very much in need. We aim at solving a binary supervised classification problem to predict hospitalizations for cardiac events using a distributed algorithm. We seek to develop a general decentralized optimization framework enabling multiple data holders to collaborate and converge to a common predictive model, without explicitly exchanging raw data. We focus on the soft-margin l 1 -regularized sparse Support Vector Machine (sSVM) classifier. We develop an iterative cluster Primal Dual Splitting (cPDS) algorithm for solving the large-scale sSVM problem in a decentralized fashion. Such a distributed learning scheme is relevant for multi-institutional collaborations or peer-to-peer applications, allowing the data holders to collaborate, while keeping every participant's data private. We test cPDS on the problem of predicting hospitalizations due to heart diseases within a calendar year based on information in the patients Electronic Health Records prior to that year. cPDS converges faster than centralized methods at the cost of some communication between agents. It also converges faster and with less communication overhead compared to an alternative distributed algorithm. In both cases, it achieves similar prediction accuracy measured by the Area Under the Receiver Operating Characteristic Curve (AUC) of the classifier. We extract important features discovered by the algorithm that are predictive of future hospitalizations, thus providing a way to interpret the classification results and inform prevention efforts. Copyright © 2018 Elsevier B.V. All rights reserved.

Proceedings of the Workshop on Applications of Distributed System Theory to the Control of Large Space Structures

NASA Technical Reports Server (NTRS)

Rodriguez, G. (Editor)

1983-01-01

Two general themes in the control of large space structures are addressed: control theory for distributed parameter systems and distributed control for systems requiring spatially-distributed multipoint sensing and actuation. Topics include modeling and control, stabilization, and estimation and identification.

Soil moisture and biogeochemical factors influence the distribution of annual Bromus species

Treesearch

Jayne Belnap; John M. Stark; Benjamin M. Rau; Edith B. Allen; Susan Phillips

2016-01-01

Abiotic factors have a strong influence on where annual Bromus species are found. At the large regional scale, temperature and precipitation extremes determine the boundaries of Bromus occurrence. At the more local scale, soil characteristics and climate influence distribution, cover, and performance. In hot, dry, summer-rainfall-dominated deserts (Sonoran, Chihuahuan...

Multi-level discriminative dictionary learning with application to large scale image classification.

PubMed

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

A High-Performance Sintered Iron Electrode for Rechargeable Alkaline Batteries to Enable Large-Scale Energy Storage

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

Yang, Chenguang; Manohar, Aswin K.; Narayanan, S. R.

Iron-based alkaline rechargeable batteries such as iron-air and nickel-iron batteries are particularly attractive for large-scale energy storage because these batteries can be relatively inexpensive, environment- friendly, and also safe. Therefore, our study has focused on achieving the essential electrical performance and cycling properties needed for the widespread use of iron-based alkaline batteries in stationary and distributed energy storage applications.We have demonstrated for the first time, an advanced sintered iron electrode capable of 3500 cycles of repeated charge and discharge at the 1-hour rate and 100% depth of discharge in each cycle, and an average Coulombic efficiency of over 97%. Suchmore » a robust and efficient rechargeable iron electrode is also capable of continuous discharge at rates as high as 3C with no noticeable loss in utilization. We have shown that the porosity, pore size and thickness of the sintered electrode can be selected rationally to optimize specific capacity, rate capability and robustness. As a result, these advances in the electrical performance and durability of the iron electrode enables iron-based alkaline batteries to be a viable technology solution for meeting the dire need for large-scale electrical energy storage.« less

A resource of large-scale molecular markers for monitoring Agropyron cristatum chromatin introgression in wheat background based on transcriptome sequences.

PubMed

Zhang, Jinpeng; Liu, Weihua; Lu, Yuqing; Liu, Qunxing; Yang, Xinming; Li, Xiuquan; Li, Lihui

2017-09-20

Agropyron cristatum is a wild grass of the tribe Triticeae and serves as a gene donor for wheat improvement. However, very few markers can be used to monitor A. cristatum chromatin introgressions in wheat. Here, we reported a resource of large-scale molecular markers for tracking alien introgressions in wheat based on transcriptome sequences. By aligning A. cristatum unigenes with the Chinese Spring reference genome sequences, we designed 9602 A. cristatum expressed sequence tag-sequence-tagged site (EST-STS) markers for PCR amplification and experimental screening. As a result, 6063 polymorphic EST-STS markers were specific for the A. cristatum P genome in the single-receipt wheat background. A total of 4956 randomly selected polymorphic EST-STS markers were further tested in eight wheat variety backgrounds, and 3070 markers displaying stable and polymorphic amplification were validated. These markers covered more than 98% of the A. cristatum genome, and the marker distribution density was approximately 1.28 cM. An application case of all EST-STS markers was validated on the A. cristatum 6 P chromosome. These markers were successfully applied in the tracking of alien A. cristatum chromatin. Altogether, this study provided a universal method of large-scale molecular marker development to monitor wild relative chromatin in wheat.

A High-Performance Sintered Iron Electrode for Rechargeable Alkaline Batteries to Enable Large-Scale Energy Storage

DOE PAGES

Yang, Chenguang; Manohar, Aswin K.; Narayanan, S. R.

2017-01-07

Iron-based alkaline rechargeable batteries such as iron-air and nickel-iron batteries are particularly attractive for large-scale energy storage because these batteries can be relatively inexpensive, environment- friendly, and also safe. Therefore, our study has focused on achieving the essential electrical performance and cycling properties needed for the widespread use of iron-based alkaline batteries in stationary and distributed energy storage applications.We have demonstrated for the first time, an advanced sintered iron electrode capable of 3500 cycles of repeated charge and discharge at the 1-hour rate and 100% depth of discharge in each cycle, and an average Coulombic efficiency of over 97%. Suchmore » a robust and efficient rechargeable iron electrode is also capable of continuous discharge at rates as high as 3C with no noticeable loss in utilization. We have shown that the porosity, pore size and thickness of the sintered electrode can be selected rationally to optimize specific capacity, rate capability and robustness. As a result, these advances in the electrical performance and durability of the iron electrode enables iron-based alkaline batteries to be a viable technology solution for meeting the dire need for large-scale electrical energy storage.« less

The combustion behavior of large scale lithium titanate battery

PubMed Central

Huang, Peifeng; Wang, Qingsong; Li, Ke; Ping, Ping; Sun, Jinhua

2015-01-01

Safety problem is always a big obstacle for lithium battery marching to large scale application. However, the knowledge on the battery combustion behavior is limited. To investigate the combustion behavior of large scale lithium battery, three 50 Ah Li(NixCoyMnz)O2/Li4Ti5O12 batteries under different state of charge (SOC) were heated to fire. The flame size variation is depicted to analyze the combustion behavior directly. The mass loss rate, temperature and heat release rate are used to analyze the combustion behavior in reaction way deeply. Based on the phenomenon, the combustion process is divided into three basic stages, even more complicated at higher SOC with sudden smoke flow ejected. The reason is that a phase change occurs in Li(NixCoyMnz)O2 material from layer structure to spinel structure. The critical temperatures of ignition are at 112–121°C on anode tab and 139 to 147°C on upper surface for all cells. But the heating time and combustion time become shorter with the ascending of SOC. The results indicate that the battery fire hazard increases with the SOC. It is analyzed that the internal short and the Li+ distribution are the main causes that lead to the difference. PMID:25586064

Hydraulic head applications of flow logs in the study of heterogeneous aquifers

USGS Publications Warehouse

Paillet, Frederick L.

2001-01-01

Permeability profiles derived from high-resolution flow logs in heterogeneous aquifers provide a limited sample of the most permeable beds or fractures determining the hydraulic properties of those aquifers. This paper demonstrates that flow logs can also be used to infer the large-scale properties of aquifers surrounding boreholes. The analysis is based on the interpretation of the hydraulic head values estimated from the flow log analysis. Pairs of quasi-steady flow profiles obtained under ambient conditions and while either pumping or injecting are used to estimate the hydraulic head in each water-producing zone. Although the analysis yields localized estimates of transmissivity for a few water-producing zones, the hydraulic head estimates apply to the farfield aquifers to which these zones are connected. The hydraulic head data are combined with information from other sources to identify the large-scale structure of heterogeneous aquifers. More complicated cross-borehole flow experiments are used to characterize the pattern of connection between large-scale aquifer units inferred from the hydraulic head estimates. The interpretation of hydraulic heads in situ under steady and transient conditions is illustrated by several case studies, including an example with heterogeneous permeable beds in an unconsolidated aquifer, and four examples with heterogeneous distributions of bedding planes and/or fractures in bedrock aquifers.

Convex hulls of random walks in higher dimensions: A large-deviation study

NASA Astrophysics Data System (ADS)

Schawe, Hendrik; Hartmann, Alexander K.; Majumdar, Satya N.

2017-12-01

The distribution of the hypervolume V and surface ∂ V of convex hulls of (multiple) random walks in higher dimensions are determined numerically, especially containing probabilities far smaller than P =10-1000 to estimate large deviation properties. For arbitrary dimensions and large walk lengths T , we suggest a scaling behavior of the distribution with the length of the walk T similar to the two-dimensional case and behavior of the distributions in the tails. We underpin both with numerical data in d =3 and d =4 dimensions. Further, we confirm the analytically known means of those distributions and calculate their variances for large T .

New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Geogdzhayev, Igor V.; Tsigaridis, Konstantinos; Marshak, Alexander; Levy, Robert; Cairns, Brian

2016-01-01

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a month-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5deg spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

Nimbus 7 SMMR Derived Seasonal Variations in the Water Vapor, Liquid Water and Surface Winds over the Global Oceans

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Short, D. A.

1984-01-01

Monthly mean distributions of water vapor and liquid water contained in a vertical column of the atmosphere and the surface wind speed were derived from Nimbus Scanning Multichannel Microwave Radiometer (SMMR) observations over the global oceans for the period November 1978 to November 1979. The remote sensing techniques used to estimate these parameters from SMMR are presented to reveal the limitations, accuracies, and applicability of the satellite-derived information for climate studies. On a time scale of the order of a month, the distribution of atmospheric water vapor over the oceans is controlled by the sea surface temperature and the large scale atmospheric circulation. The monthly mean distribution of liquid water content in the atmosphere over the oceans closely reflects the precipitation patterns associated with the convectively and baroclinically active regions. Together with the remotely sensed surface wind speed that is causing the sea surface stress, the data collected reveal the manner in which the ocean-atmosphere system is operating. Prominent differences in the water vapor patterns from one year to the next, or from month to month, are associated with anomalies in the wind and geopotential height fields. In association with such circulation anomalies the precipitation patterns deduced from the meteorological network over adjacent continents also reveal anomalous distributions.

Multiscale connectivity and graph theory highlight critical areas for conservation under climate change.

PubMed

Dilt, Thomas E; Weisberg, Peter J; Leitner, Philip; Matocq, Marjorie D; Inman, Richard D; Nussear, Kenneth E; Esque, Todd C

2016-06-01

Conservation planning and biodiversity management require information on landscape connectivity across a range of spatial scales from individual home ranges to large regions. Reduction in landscape connectivity due changes in land use or development is expected to act synergistically with alterations to habitat mosaic configuration arising from climate change. We illustrate a multiscale connectivity framework to aid habitat conservation prioritization in the context of changing land use and climate. Our approach, which builds upon the strengths of multiple landscape connectivity methods, including graph theory, circuit theory, and least-cost path analysis, is here applied to the conservation planning requirements of the Mohave ground squirrel. The distribution of this threatened Californian species, as for numerous other desert species, overlaps with the proposed placement of several utility-scale renewable energy developments in the American southwest. Our approach uses information derived at three spatial scales to forecast potential changes in habitat connectivity under various scenarios of energy development and climate change. By disentangling the potential effects of habitat loss and fragmentation across multiple scales, we identify priority conservation areas for both core habitat and critical corridor or stepping stone habitats. This approach is a first step toward applying graph theory to analyze habitat connectivity for species with continuously distributed habitat and should be applicable across a broad range of taxa.

Suboptimal distributed control and estimation: application to a four coupled tanks system

NASA Astrophysics Data System (ADS)

Orihuela, Luis; Millán, Pablo; Vivas, Carlos; Rubio, Francisco R.

2016-06-01

The paper proposes an innovative estimation and control scheme that enables the distributed monitoring and control of large-scale processes. The proposed approach considers a discrete linear time-invariant process controlled by a network of agents that may both collect information about the evolution of the plant and apply control actions to drive its behaviour. The problem makes full sense when local observability/controllability is not assumed and the communication between agents can be exploited to reach system-wide goals. Additionally, to reduce agents bandwidth requirements and power consumption, an event-based communication policy is studied. The design procedure guarantees system stability, allowing the designer to trade-off performance, control effort and communication requirements. The obtained controllers and observers are implemented in a fully distributed fashion. To illustrate the performance of the proposed technique, experimental results on a quadruple-tank process are provided.

Design and Realization of Online Monitoring System of Distributed New Energy and Renewable Energy

NASA Astrophysics Data System (ADS)

Tang, Yanfen; Zhou, Tao; Li, Mengwen; Zheng, Guotai; Li, Hao

2018-01-01

Aimed at difficult centralized monitoring and management of current distributed new energy and renewable energy generation projects due to great varieties, different communication protocols and large-scale difference, this paper designs a online monitoring system of new energy and renewable energy characterized by distributed deployment, tailorable functions, extendible applications and fault self-healing performance. This system is designed based on international general standard for grid information data model, formulates unified data acquisition and transmission standard for different types of new energy and renewable energy generation projects, and can realize unified data acquisition and real-time monitoring of new energy and renewable energy generation projects, such as solar energy, wind power, biomass energy, etc. within its jurisdiction. This system has applied in Beijing. At present, 576 projects are connected to the system. Good effect is achieved and stability and reliability of the system have been validated.

Performance analysis on a large scale borehole ground source heat pump in Tianjin cultural centre

NASA Astrophysics Data System (ADS)

Yin, Baoquan; Wu, Xiaoting

2018-02-01

In this paper, the temperature distribution of the geothermal field for the vertical borehole ground-coupled heat pump was tested and analysed. Besides the borehole ground-coupled heat pump, the system composed of the ice storage, heat supply network and cooling tower. According to the operation data for nearly three years, the temperature constant zone is in the ground depth of 40m -120m with a temperature gradient of about 3.0°C/100m. The temperature of the soil dropped significantly in the heating season, increased significantly in the cooling season, and reinstated in the transitional season. With the energy balance design of the heating and cooling and the existence of the soil thermal inertia, the soil temperature stayed in a relative stable range and the ground source heat pump system was operated with a relative high efficiency. The geothermal source heat pump was shown to be applicable for large scale utilization.

High Performance Geostatistical Modeling of Biospheric Resources

NASA Astrophysics Data System (ADS)

Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.

2004-12-01

We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

NASA Technical Reports Server (NTRS)

Johnston, William E.; Gannon, Dennis; Nitzberg, Bill; Feiereisen, William (Technical Monitor)

2000-01-01

The term "Grid" refers to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. The vision for NASN's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks that will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: The scientist / design engineer whose primary interest is problem solving (e.g., determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user if the tool designer: The computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. This paper describes the current state of IPG (the operational testbed), the set of capabilities being put into place for the operational prototype IPG, as well as some of the longer term R&D tasks.

Collective evolution of submicron hillocks during the early stages of anisotropic alkaline wet chemical etching of Si(1 0 0) surfaces

NASA Astrophysics Data System (ADS)

Sana, P.; Vázquez, Luis; Cuerno, Rodolfo; Sarkar, Subhendu

2017-11-01

We address experimentally the large-scale dynamics of Si(1 0 0) surfaces during the initial stages of anisotropic wet (KOH) chemical etching, which are characterized through atomic force microscopy. These systems are known to lead to the formation of characteristic pyramids, or hillocks, of typical sizes in the nanometric/micrometer scales, thus with the potential for a large number of applications that can benefit from the nanotexturing of Si surfaces. The present pattern formation process is very strongly disordered in space. We assess the space correlations in such a type of rough surface and elucidate the existence of a complex and rich morphological evolution, featuring at least three different regimes in just 10 min of etching. Such a complex time behavior cannot be consistently explained within a single formalism for dynamic scaling. The pyramidal structure reveals itself as the basic morphological motif of the surface throughout the dynamics. A detailed analysis of the surface slope distribution with etching time reveals that the texturing process induced by the KOH etching is rather gradual and progressive, which accounts for the dynamic complexity. The various stages of the morphological evolution can be accurately reproduced by computer-generated surfaces composed by uncorrelated pyramidal structures. To reach such an agreement, the key parameters are the average pyramid size, which increases with etching time, its distribution and the surface coverage by the pyramidal structures.

Combined discrete particle and continuum model predicting solid-state fermentation in a drum fermentor.

PubMed

Schutyser, M A I; Briels, W J; Boom, R M; Rinzema, A

2004-05-20

The development of mathematical models facilitates industrial (large-scale) application of solid-state fermentation (SSF). In this study, a two-phase model of a drum fermentor is developed that consists of a discrete particle model (solid phase) and a continuum model (gas phase). The continuum model describes the distribution of air in the bed injected via an aeration pipe. The discrete particle model describes the solid phase. In previous work, mixing during SSF was predicted with the discrete particle model, although mixing simulations were not carried out in the current work. Heat and mass transfer between the two phases and biomass growth were implemented in the two-phase model. Validation experiments were conducted in a 28-dm3 drum fermentor. In this fermentor, sufficient aeration was provided to control the temperatures near the optimum value for growth during the first 45-50 hours. Several simulations were also conducted for different fermentor scales. Forced aeration via a single pipe in the drum fermentors did not provide homogeneous cooling in the substrate bed. Due to large temperature gradients, biomass yield decreased severely with increasing size of the fermentor. Improvement of air distribution would be required to avoid the need for frequent mixing events, during which growth is hampered. From these results, it was concluded that the two-phase model developed is a powerful tool to investigate design and scale-up of aerated (mixed) SSF fermentors. Copyright 2004 Wiley Periodicals, Inc.

Hope for the Forests? Habitat Resiliency Illustrated in the Face of Climate Change Using Fine-Scale Modeling

NASA Astrophysics Data System (ADS)

Flint, L. E.; Flint, A. L.; Weiss, S. B.; Micheli, E. R.

2010-12-01

In the face of rapid climate change, fine-scale predictions of landscape change are of extreme interest to land managers that endeavor to develop long term adaptive strategies for maintaining biodiversity and ecosystem services. Global climate model (GCM) outputs, which generally focus on estimated increases in air temperature, are increasingly applied to species habitat distribution models. For sensitive species subject to climate change, habitat models predict significant migration (either northward or towards higher elevations), or complete extinction. Current studies typically rely on large spatial scale GCM projections (> 10 km) of changes in precipitation and air temperature: at this scale, these models necessarily neglect subtleties of topographic shading, geomorphic expression of the landscape, and fine-scale differences in soil properties - data that is readily available at meaningful local scales. Recent advances in modeling take advantage of available soils, geology, and topographic data to construct watershed-scale scenarios using GCM inputs and result in improved correlations of vegetation distribution with temperature. For this study, future climate projections were downscaled to 270-m and applied to a physically-based hydrologic model to calculate future changes in recharge, runoff, and climatic water deficit (CWD) for basins draining into the northern San Francisco Bay. CWD was analyzed for mapped vegetation types to evaluate the range of CWD for historic time periods in comparison to future time periods. For several forest communities (including blue oak woodlands, montane hardwoods, douglas-fir, and coast redwood) existing landscape area exhibiting suitable CWD diminishes by up 80 percent in the next century, with a trend towards increased CWD throughout the region. However, no forest community loses all suitable habitat, with islands of potential habitat primarily remaining on north facing slopes and deeper soils. Creation of new suitable habitat is also predicted throughout the region. Results have direct application to management issues of habitat connectivity, forest land protection and acquisition, and active management solutions such as transplanting or assisted migration. Although this analysis considers only one driver of forest habitat distribution, consideration of hydrologic derivatives at a fine scale explains current forest community distributions and provides a far more informed perspective on potential future forest distributions. Results demonstrate the utility of fine-scale modeling and provide landscape managers and conservation agencies valuable management tools in fine-scale future forest scenarios and a framework for evaluating forest resiliency in a changing climate.

Nanostructures and functional materials fabricated by interferometric lithography.

PubMed

Xia, Deying; Ku, Zahyun; Lee, S C; Brueck, S R J

2011-01-11

Interferometric lithography (IL) is a powerful technique for the definition of large-area, nanometer-scale, periodically patterned structures. Patterns are recorded in a light-sensitive medium, such as a photoresist, that responds nonlinearly to the intensity distribution associated with the interference of two or more coherent beams of light. The photoresist patterns produced with IL are a platform for further fabrication of nanostructures and growth of functional materials and are building blocks for devices. This article provides a brief review of IL technologies and focuses on various applications for nanostructures and functional materials based on IL including directed self-assembly of colloidal nanoparticles, nanophotonics, semiconductor materials growth, and nanofluidic devices. Perspectives on future directions for IL and emerging applications in other fields are presented.

A Bayesian Hierarchical Modeling Scheme for Estimating Erosion Rates Under Current Climate Conditions

NASA Astrophysics Data System (ADS)

Lowman, L.; Barros, A. P.

2014-12-01

Computational modeling of surface erosion processes is inherently difficult because of the four-dimensional nature of the problem and the multiple temporal and spatial scales that govern individual mechanisms. Landscapes are modified via surface and fluvial erosion and exhumation, each of which takes place over a range of time scales. Traditional field measurements of erosion/exhumation rates are scale dependent, often valid for a single point-wise location or averaging over large aerial extents and periods with intense and mild erosion. We present a method of remotely estimating erosion rates using a Bayesian hierarchical model based upon the stream power erosion law (SPEL). A Bayesian approach allows for estimating erosion rates using the deterministic relationship given by the SPEL and data on channel slopes and precipitation at the basin and sub-basin scale. The spatial scale associated with this framework is the elevation class, where each class is characterized by distinct morphologic behavior observed through different modes in the distribution of basin outlet elevations. Interestingly, the distributions of first-order outlets are similar in shape and extent to the distribution of precipitation events (i.e. individual storms) over a 14-year period between 1998-2011. We demonstrate an application of the Bayesian hierarchical modeling framework for five basins and one intermontane basin located in the central Andes between 5S and 20S. Using remotely sensed data of current annual precipitation rates from the Tropical Rainfall Measuring Mission (TRMM) and topography from a high resolution (3 arc-seconds) digital elevation map (DEM), our erosion rate estimates are consistent with decadal-scale estimates based on landslide mapping and sediment flux observations and 1-2 orders of magnitude larger than most millennial and million year timescale estimates from thermochronology and cosmogenic nuclides.

An Investigation on the Spatial Variability of Manning Roughness Coefficients in Continental-scale River Routing Simulations

NASA Astrophysics Data System (ADS)

Luo, X.; Hong, Y.; Lei, X.; Leung, L. R.; Li, H. Y.; Getirana, A.

2017-12-01

As one essential component of the Earth system modeling, the continental-scale river routing computation plays an important role in applications of Earth system models, such as evaluating the impacts of the global change on water resources and flood hazards. The streamflow timing, which depends on the modeled flow velocities, can be an important aspect of the model results. River flow velocities have been estimated by using the Manning's equation where the Manning roughness coefficient is a key and sensitive parameter. In some early continental-scale studies, the Manning coefficient was determined with simplified methods, such as using a constant value for the entire basin. However, large spatial variability is expected in the Manning coefficients for the numerous channels composing the river network in distributed continental-scale hydrologic modeling. In the application of a continental-scale river routing model in the Amazon Basin, we use spatially varying Manning coefficients dependent on channel sizes and attempt to represent the dominant spatial variability of Manning coefficients. Based on the comparisons of simulation results with in situ streamflow records and remotely sensed river stages, we investigate the comparatively optimal Manning coefficients and explicitly demonstrate the advantages of using spatially varying Manning coefficients. The understanding obtained in this study could be helpful in the modeling of surface hydrology at regional to continental scales.

Advances in snow cover distributed modelling via ensemble simulations and assimilation of satellite data

NASA Astrophysics Data System (ADS)

Revuelto, J.; Dumont, M.; Tuzet, F.; Vionnet, V.; Lafaysse, M.; Lecourt, G.; Vernay, M.; Morin, S.; Cosme, E.; Six, D.; Rabatel, A.

2017-12-01

Nowadays snowpack models show a good capability in simulating the evolution of snow in mountain areas. However singular deviations of meteorological forcing and shortcomings in the modelling of snow physical processes, when accumulated on time along a snow season, could produce large deviations from real snowpack state. The evaluation of these deviations is usually assessed with on-site observations from automatic weather stations. Nevertheless the location of these stations could strongly influence the results of these evaluations since local topography may have a marked influence on snowpack evolution. Despite the evaluation of snowpack models with automatic weather stations usually reveal good results, there exist a lack of large scale evaluations of simulations results on heterogeneous alpine terrain subjected to local topographic effects.This work firstly presents a complete evaluation of the detailed snowpack model Crocus over an extended mountain area, the Arve upper catchment (western European Alps). This catchment has a wide elevation range with a large area above 2000m a.s.l. and/or glaciated. The evaluation compares results obtained with distributed and semi-distributed simulations (the latter nowadays used on the operational forecasting). Daily observations of the snow covered area from MODIS satellite sensor, seasonal glacier surface mass balance evolution measured in more than 65 locations and the galciers annual equilibrium line altitude from Landsat/Spot/Aster satellites, have been used for model evaluation. Additionally the latest advances in producing ensemble snowpack simulations for assimilating satellite reflectance data over extended areas will be presented. These advances comprises the generation of an ensemble of downscaled high-resolution meteorological forcing from meso-scale meteorological models and the application of a particle filter scheme for assimilating satellite observations. Despite the results are prefatory, they show a good potential improving snowpack forecasting capabilities.

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

NASA Astrophysics Data System (ADS)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

Dynamic Control of Facts Devices to Enable Large Scale Penetration of Renewable Energy Resources

NASA Astrophysics Data System (ADS)

Chavan, Govind Sahadeo

This thesis focuses on some of the problems caused by large scale penetration of Renewable Energy Resources within EHV transmission networks, and investigates some approaches in resolving these problems. In chapter 4, a reduced-order model of the 500 kV WECC transmission system is developed by estimating its key parameters from phasor measurement unit (PMU) data. The model was then implemented in RTDS and was investigated for its accuracy with respect to the PMU data. Finally it was tested for observing the effects of various contingencies like transmission line loss, generation loss and large scale penetration of wind farms on EHV transmission systems. Chapter 5 introduces Static Series Synchronous Compensators (SSSC) which are seriesconnected converters that can control real power flow along a transmission line. A new application of SSSCs in mitigating Ferranti effect on unloaded transmission lines was demonstrated on PSCAD. A new control scheme for SSSCs based on the Cascaded H-bridge (CHB) converter configuration was proposed and was demonstrated using PSCAD and RTDS. A new centralized controller was developed for the distributed SSSCs based on some of the concepts used in the CHB-based SSSC. The controller's efficacy was demonstrated using RTDS. Finally chapter 6 introduces the problem of power oscillations induced by renewable sources in a transmission network. A power oscillation damping (POD) controller is designed using distributed SSSCs in NYPA's 345 kV three-bus AC system and its efficacy is demonstrated in PSCAD. A similar POD controller is then designed for the CHB-based SSSC in the IEEE 14 bus system in PSCAD. Both controllers were noted to have significantly damped power oscillations in the transmission networks.

Prospects of Detecting HI using Redshifted 21-cm Radiation at z˜3

NASA Astrophysics Data System (ADS)

Gehlot, Bharat Kumar; Bagla, J. S.

2017-03-01

Distribution of cold gas in the post-reionization era provides an important link between distribution of galaxies and the process of star formation. Redshifted 21-cm radiation from the hyperfine transition of neutral hydrogen allows us to probe the neutral component of cold gas, most of which is to be found in the interstellar medium of galaxies. Existing and upcoming radio telescopes can probe the large scale distribution of neutral hydrogen via HI intensity mapping. In this paper, we use an estimate of the HI power spectrum derived using an ansatz to compute the expected signal from the large scale HI distribution at z˜3. We find that the scale dependence of bias at small scales makes a significant difference to the expected signal even at large angular scales. We compare the predicted signal strength with the sensitivity of radio telescopes that can observe such radiation and calculate the observation time required for detecting neutral hydrogen at these redshifts. We find that OWFA (Ooty Wide Field Array) offers the best possibility to detect neutral hydrogen at z˜3 before the SKA (Square Kilometer Array) becomes operational. We find that the OWFA should be able to make a 3 σ or a more significant detection in 2000 hours of observations at several angular scales. Calculations done using the Fisher matrix approach indicate that a 5 σ detection of the binned HI power spectrum via measurement of the amplitude of the HI power spectrum is possible in 1000 h (Sarkar et al. 2017).

Pynamic: the Python Dynamic Benchmark

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

Lee, G L; Ahn, D H; de Supinksi, B R

2007-07-10

Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, wemore » present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.« less

Healthcare4VideoStorm: Making Smart Decisions Based on Storm Metrics.

PubMed

Zhang, Weishan; Duan, Pengcheng; Chen, Xiufeng; Lu, Qinghua

2016-04-23

Storm-based stream processing is widely used for real-time large-scale distributed processing. Knowing the run-time status and ensuring performance is critical to providing expected dependability for some applications, e.g., continuous video processing for security surveillance. The existing scheduling strategies' granularity is too coarse to have good performance, and mainly considers network resources without computing resources while scheduling. In this paper, we propose Healthcare4Storm, a framework that finds Storm insights based on Storm metrics to gain knowledge from the health status of an application, finally ending up with smart scheduling decisions. It takes into account both network and computing resources and conducts scheduling at a fine-grained level using tuples instead of topologies. The comprehensive evaluation shows that the proposed framework has good performance and can improve the dependability of the Storm-based applications.

Programmable dispersion on a photonic integrated circuit for classical and quantum applications.

PubMed

Notaros, Jelena; Mower, Jacob; Heuck, Mikkel; Lupo, Cosmo; Harris, Nicholas C; Steinbrecher, Gregory R; Bunandar, Darius; Baehr-Jones, Tom; Hochberg, Michael; Lloyd, Seth; Englund, Dirk

2017-09-04

We demonstrate a large-scale tunable-coupling ring resonator array, suitable for high-dimensional classical and quantum transforms, in a CMOS-compatible silicon photonics platform. The device consists of a waveguide coupled to 15 ring-based dispersive elements with programmable linewidths and resonance frequencies. The ability to control both quality factor and frequency of each ring provides an unprecedented 30 degrees of freedom in dispersion control on a single spatial channel. This programmable dispersion control system has a range of applications, including mode-locked lasers, quantum key distribution, and photon-pair generation. We also propose a novel application enabled by this circuit - high-speed quantum communications using temporal-mode-based quantum data locking - and discuss the utility of the system for performing the high-dimensional unitary optical transformations necessary for a quantum data locking demonstration.

Monitoring carnivore populations at the landscape scale: occupancy modelling of tigers from sign surveys

USGS Publications Warehouse

Karanth, Kota Ullas; Gopalaswamy, Arjun M.; Kumar, Narayanarao Samba; Vaidyanathan, Srinivas; Nichols, James D.; MacKenzie, Darryl I.

2011-01-01

1. Assessing spatial distributions of threatened large carnivores at landscape scales poses formidable challenges because of their rarity and elusiveness. As a consequence of logistical constraints, investigators typically rely on sign surveys. Most survey methods, however, do not explicitly address the central problem of imperfect detections of animal signs in the field, leading to underestimates of true habitat occupancy and distribution. 2. We assessed habitat occupancy for a tiger Panthera tigris metapopulation across a c. 38 000-km2 landscape in India, employing a spatially replicated survey to explicitly address imperfect detections. Ecological predictions about tiger presence were confronted with sign detection data generated from occupancy sampling of 205 sites, each of 188 km2. 3. A recent occupancy model that considers Markovian dependency among sign detections on spatial replicates performed better than the standard occupancy model (ΔAIC = 184·9). A formulation of this model that fitted the data best showed that density of ungulate prey and levels of human disturbance were key determinants of local tiger presence. Model averaging resulted in a replicate-level detection probability [inline image] = 0·17 (0·17) for signs and a tiger habitat occupancy estimate of [inline image] = 0·665 (0·0857) or 14 076 (1814) km2 of potential habitat of 21 167 km2. In contrast, a traditional presence-versus-absence approach underestimated occupancy by 47%. Maps of probabilities of local site occupancy clearly identified tiger source populations at higher densities and matched observed tiger density variations, suggesting their potential utility for population assessments at landscape scales. 4. Synthesis and applications. Landscape-scale sign surveys can efficiently assess large carnivore spatial distributions and elucidate the factors governing their local presence, provided ecological and observation processes are both explicitly modelled. Occupancy sampling using spatial replicates can be used to reliably and efficiently identify tiger population sources and help monitor metapopulations. Our results reinforce earlier findings that prey depletion and human disturbance are key drivers of local tiger extinctions and tigers can persist even in human-dominated landscapes through effective protection of source populations. Our approach facilitates efficient targeting of tiger conservation interventions and, more generally, provides a basis for the reliable integration of large carnivore monitoring data between local and landscape scales.

Emergence of scaling in human-interest dynamics.

PubMed

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-12-11

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical "Big Data" sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction.

Distributed Lag Models: Examining Associations between the Built Environment and Health

PubMed Central

Baek, Jonggyu; Sánchez, Brisa N.; Berrocal, Veronica J.; Sanchez-Vaznaugh, Emma V.

2016-01-01

Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, pre-specified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children’s dietary choices both through direct access to junk food and exposure to advertisement, and children’s body mass index z-scores (BMIz). PMID:26414942

Emergence of scaling in human-interest dynamics

NASA Astrophysics Data System (ADS)

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-12-01

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical ``Big Data'' sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction.

Probability density function of non-reactive solute concentration in heterogeneous porous formations.

PubMed

Bellin, Alberto; Tonina, Daniele

2007-10-30

Available models of solute transport in heterogeneous formations lack in providing complete characterization of the predicted concentration. This is a serious drawback especially in risk analysis where confidence intervals and probability of exceeding threshold values are required. Our contribution to fill this gap of knowledge is a probability distribution model for the local concentration of conservative tracers migrating in heterogeneous aquifers. Our model accounts for dilution, mechanical mixing within the sampling volume and spreading due to formation heterogeneity. It is developed by modeling local concentration dynamics with an Ito Stochastic Differential Equation (SDE) that under the hypothesis of statistical stationarity leads to the Beta probability distribution function (pdf) for the solute concentration. This model shows large flexibility in capturing the smoothing effect of the sampling volume and the associated reduction of the probability of exceeding large concentrations. Furthermore, it is fully characterized by the first two moments of the solute concentration, and these are the same pieces of information required for standard geostatistical techniques employing Normal or Log-Normal distributions. Additionally, we show that in the absence of pore-scale dispersion and for point concentrations the pdf model converges to the binary distribution of [Dagan, G., 1982. Stochastic modeling of groundwater flow by unconditional and conditional probabilities, 2, The solute transport. Water Resour. Res. 18 (4), 835-848.], while it approaches the Normal distribution for sampling volumes much larger than the characteristic scale of the aquifer heterogeneity. Furthermore, we demonstrate that the same model with the spatial moments replacing the statistical moments can be applied to estimate the proportion of the plume volume where solute concentrations are above or below critical thresholds. Application of this model to point and vertically averaged bromide concentrations from the first Cape Cod tracer test and to a set of numerical simulations confirms the above findings and for the first time it shows the superiority of the Beta model to both Normal and Log-Normal models in interpreting field data. Furthermore, we show that assuming a-priori that local concentrations are normally or log-normally distributed may result in a severe underestimate of the probability of exceeding large concentrations.

Large-Scale Fabrication of Silicon Nanowires for Solar Energy Applications.

PubMed

Zhang, Bingchang; Jie, Jiansheng; Zhang, Xiujuan; Ou, Xuemei; Zhang, Xiaohong

2017-10-11

The development of silicon (Si) materials during past decades has boosted up the prosperity of the modern semiconductor industry. In comparison with the bulk-Si materials, Si nanowires (SiNWs) possess superior structural, optical, and electrical properties and have attracted increasing attention in solar energy applications. To achieve the practical applications of SiNWs, both large-scale synthesis of SiNWs at low cost and rational design of energy conversion devices with high efficiency are the prerequisite. This review focuses on the recent progresses in large-scale production of SiNWs, as well as the construction of high-efficiency SiNW-based solar energy conversion devices, including photovoltaic devices and photo-electrochemical cells. Finally, the outlook and challenges in this emerging field are presented.

Discriminative Random Field Models for Subsurface Contamination Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Arshadi, M.; Abriola, L. M.; Miller, E. L.; De Paolis Kaluza, C.

2017-12-01

Application of flow and transport simulators for prediction of the release, entrapment, and persistence of dense non-aqueous phase liquids (DNAPLs) and associated contaminant plumes is a computationally intensive process that requires specification of a large number of material properties and hydrologic/chemical parameters. Given its computational burden, this direct simulation approach is particularly ill-suited for quantifying both the expected performance and uncertainty associated with candidate remediation strategies under real field conditions. Prediction uncertainties primarily arise from limited information about contaminant mass distributions, as well as the spatial distribution of subsurface hydrologic properties. Application of direct simulation to quantify uncertainty would, thus, typically require simulating multiphase flow and transport for a large number of permeability and release scenarios to collect statistics associated with remedial effectiveness, a computationally prohibitive process. The primary objective of this work is to develop and demonstrate a methodology that employs measured field data to produce equi-probable stochastic representations of a subsurface source zone that capture the spatial distribution and uncertainty associated with key features that control remediation performance (i.e., permeability and contamination mass). Here we employ probabilistic models known as discriminative random fields (DRFs) to synthesize stochastic realizations of initial mass distributions consistent with known, and typically limited, site characterization data. Using a limited number of full scale simulations as training data, a statistical model is developed for predicting the distribution of contaminant mass (e.g., DNAPL saturation and aqueous concentration) across a heterogeneous domain. Monte-Carlo sampling methods are then employed, in conjunction with the trained statistical model, to generate realizations conditioned on measured borehole data. Performance of the statistical model is illustrated through comparisons of generated realizations with the `true' numerical simulations. Finally, we demonstrate how these realizations can be used to determine statistically optimal locations for further interrogation of the subsurface.

Intra-beam scattering and its application to ERL

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

Fedotov, A.

Treatment of Coulomb collisions within the beam requires consideration of both large and small angle scattering. Such collisions lead to the Touschek effect and Intrabeam Scattering (IBS). The Touschek effect refers to particle loss as a result of a single collision, where only transfer from the transverse direction into longitudinal plays a role. It is important to consider this effect for ERL design to have an appropriate choice of collimation system. The IBS is a diffusion process which leads to changes of beam distribution but does not necessarily result in a beam loss. Evaluation of IBS in ERLs, where beammore » distribution is non-Gaussian, requires special treatment. Here we describe the IBS and Touschek effects with application to ERLs. In circular accelerators both the Touschek effect and IBS were found important. The generalized formulas for Touschek calculations are available and are already being used in advanced tracking simulations of several ERL-based projects. The IBS (which is diffusion due to multiple Coulomb scattering) is not expected to cause any significant effect on beam distribution in ERLs, unless one considers very long transport of high-brightness beams at low energies. Both large and small-angle Coulomb scattering can contribute to halo formation in future ERLs with high-brightness beams, as follows from simple order-of-magnitude estimates. In this report, a test comparison between 'local' and 'sliced' IBS models within the BET ACOOL code was presented for an illustrative ERL distribution. We also presented accumulated current loss distribution due to Touschek scattering for design parameters of ERL proposed for the eRHIC project, as well as scaling for multi-pass ERLs.« less

A Hierarchical and Distributed Approach for Mapping Large Applications to Heterogeneous Grids using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Sanyal, Soumya; Jain, Amit; Das, Sajal K.; Biswas, Rupak

2003-01-01

In this paper, we propose a distributed approach for mapping a single large application to a heterogeneous grid environment. To minimize the execution time of the parallel application, we distribute the mapping overhead to the available nodes of the grid. This approach not only provides a fast mapping of tasks to resources but is also scalable. We adopt a hierarchical grid model and accomplish the job of mapping tasks to this topology using a scheduler tree. Results show that our three-phase algorithm provides high quality mappings, and is fast and scalable.

Soil organic carbon - a large scale paired catchment assessment

NASA Astrophysics Data System (ADS)

Kunkel, V.; Hancock, G. R.; Wells, T.

2016-12-01

Soil organic carbon (SOC) concentration can vary both spatially and temporally driven by differences in soil properties, topography and climate. However most studies have focused on point scale data sets with a paucity of studies examining larger scale catchments. Here we examine the spatial and temporal distribution of SOC for two large catchments. The Krui (575 km2) and Merriwa River (675km2) catchments (New South Wales, Australia). Both have similar shape, soils, topography and orientation. We show that SOC distribution is very similar for both catchments and that elevation (and associated increase in soil moisture) is a major influence on SOC. We also show that there is little change in SOC from the initial assessment in 2006 to 2015 despite a major drought from 2003 to 2010 and extreme rainfall events in 2007 and 2010 -therefore SOC concentration appears robust. However, we found significant relationships between erosion and deposition patterns (as quantified using 137Cs) and SOC for both catchments again demonstrating a strong geomorphic relationship. Vegetation across the catchments was assessed using remote sensing (Landsat and MODIS). Vegetation patterns were temporally consistent with above ground biomass increasing with elevation. SOC could be predicted using both these low and high resolution remote sensing platforms. Results indicate that, although moderate resolution (250 m) allows for reasonable prediction of the spatial distribution of SOC, the higher resolution (30 m) improved the strength of the SOC-NDVI relationship. The relationship between SOC and 137Cs, as a surrogate for the erosion and deposition of SOC, suggested that sediment transport and deposition influences the distribution of SOC within the catchment. The findings demonstrate that over the large catchment scale and at the decadal time scale that SOC is relatively constant and can largely be predicted by topography.

Potential for geophysical experiments in large scale tests.

USGS Publications Warehouse

Dieterich, J.H.

1981-01-01

Potential research applications for large-specimen geophysical experiments include measurements of scale dependence of physical parameters and examination of interactions with heterogeneities, especially flaws such as cracks. In addition, increased specimen size provides opportunities for improved recording resolution and greater control of experimental variables. Large-scale experiments using a special purpose low stress (100MPa).-Author

A process for creating multimetric indices for large-scale aquatic surveys

EPA Science Inventory

Differences in sampling and laboratory protocols, differences in techniques used to evaluate metrics, and differing scales of calibration and application prohibit the use of many existing multimetric indices (MMIs) in large-scale bioassessments. We describe an approach to develop...

Imprinting continuously varying topographical structure onto large-aperture optical surfaces using magnetorheological finishing

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

Menapace, J A; Davis, P J; Dixit, S

2007-03-07

Over the past four years we have advanced Magnetorheological Finishing (MRF) techniques and tools to imprint complex continuously varying topographical structures onto large-aperture (430 x 430 mm) optical surfaces. These optics, known as continuous phase plates (CPPs), are important for high-power laser applications requiring precise manipulation and control of beam-shape, energy distribution, and wavefront profile. MRF's unique deterministic-sub-aperture polishing characteristics make it possible to imprint complex topographical information onto optical surfaces at spatial scale-lengths approaching 1 mm and surface peak-to-valleys as high as 22 {micro}m. During this discussion, we will present the evolution of the MRF imprinting technology and themore » MRF tools designed to manufacture large-aperture 430 x 430 mm CPPs. Our results will show how the MRF removal function impacts and limits imprint fidelity and what must be done to arrive at a high-quality surface. We also present several examples of this imprinting technology for fabrication of phase correction plates and CPPs for use in high-power laser applications.« less

Big Data Approaches for the Analysis of Large-Scale fMRI Data Using Apache Spark and GPU Processing: A Demonstration on Resting-State fMRI Data from the Human Connectome Project

PubMed Central

Boubela, Roland N.; Kalcher, Klaudius; Huf, Wolfgang; Našel, Christian; Moser, Ewald

2016-01-01

Technologies for scalable analysis of very large datasets have emerged in the domain of internet computing, but are still rarely used in neuroimaging despite the existence of data and research questions in need of efficient computation tools especially in fMRI. In this work, we present software tools for the application of Apache Spark and Graphics Processing Units (GPUs) to neuroimaging datasets, in particular providing distributed file input for 4D NIfTI fMRI datasets in Scala for use in an Apache Spark environment. Examples for using this Big Data platform in graph analysis of fMRI datasets are shown to illustrate how processing pipelines employing it can be developed. With more tools for the convenient integration of neuroimaging file formats and typical processing steps, big data technologies could find wider endorsement in the community, leading to a range of potentially useful applications especially in view of the current collaborative creation of a wealth of large data repositories including thousands of individual fMRI datasets. PMID:26778951

A Census of Large-scale (≥10 PC), Velocity-coherent, Dense Filaments in the Northern Galactic Plane: Automated Identification Using Minimum Spanning Tree

NASA Astrophysics Data System (ADS)

Wang, Ke; Testi, Leonardo; Burkert, Andreas; Walmsley, C. Malcolm; Beuther, Henrik; Henning, Thomas

2016-09-01

Large-scale gaseous filaments with lengths up to the order of 100 pc are on the upper end of the filamentary hierarchy of the Galactic interstellar medium (ISM). Their association with respect to the Galactic structure and their role in Galactic star formation are of great interest from both an observational and theoretical point of view. Previous “by-eye” searches, combined together, have started to uncover the Galactic distribution of large filaments, yet inherent bias and small sample size limit conclusive statistical results from being drawn. Here, we present (1) a new, automated method for identifying large-scale velocity-coherent dense filaments, and (2) the first statistics and the Galactic distribution of these filaments. We use a customized minimum spanning tree algorithm to identify filaments by connecting voxels in the position-position-velocity space, using the Bolocam Galactic Plane Survey spectroscopic catalog. In the range of 7\\buildrel{\\circ}\\over{.} 5≤slant l≤slant 194^\\circ , we have identified 54 large-scale filaments and derived mass (˜ {10}3{--}{10}5 {M}⊙ ), length (10-276 pc), linear mass density (54-8625 {M}⊙ pc-1), aspect ratio, linearity, velocity gradient, temperature, fragmentation, Galactic location, and orientation angle. The filaments concentrate along major spiral arms. They are widely distributed across the Galactic disk, with 50% located within ±20 pc from the Galactic mid-plane and 27% run in the center of spiral arms. An order of 1% of the molecular ISM is confined in large filaments. Massive star formation is more favorable in large filaments compared to elsewhere. This is the first comprehensive catalog of large filaments that can be useful for a quantitative comparison with spiral structures and numerical simulations.

Exploring the role of movement in determining the global distribution of marine biomass using a coupled hydrodynamic - Size-based ecosystem model

NASA Astrophysics Data System (ADS)

Watson, James R.; Stock, Charles A.; Sarmiento, Jorge L.

2015-11-01

Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be ∼ 2.84 ×109 tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.

Determining erosion relevant soil characteristics with a small-scale rainfall simulator

NASA Astrophysics Data System (ADS)

Schindewolf, M.; Schmidt, J.

2009-04-01

The use of soil erosion models is of great importance in soil and water conservation. Routine application of these models on the regional scale is not at least limited by the high parameter demands. Although the EROSION 3D simulation model is operating with a comparable low number of parameters, some of the model input variables could only be determined by rainfall simulation experiments. The existing data base of EROSION 3D was created in the mid 90s based on large-scale rainfall simulation experiments on 22x2m sized experimental plots. Up to now this data base does not cover all soil and field conditions adequately. Therefore a new campaign of experiments would be essential to produce additional information especially with respect to the effects of new soil management practices (e.g. long time conservation tillage, non tillage). The rainfall simulator used in the actual campaign consists of 30 identic modules, which are equipped with oscillating rainfall nozzles. Veejet 80/100 (Spraying Systems Co., Wheaton, IL) are used in order to ensure best possible comparability to natural rainfalls with respect to raindrop size distribution and momentum transfer. Central objectives of the small-scale rainfall simulator are - effectively application - provision of comparable results to large-scale rainfall simulation experiments. A crucial problem in using the small scale simulator is the restriction on rather small volume rates of surface runoff. Under this conditions soil detachment is governed by raindrop impact. Thus impact of surface runoff on particle detachment cannot be reproduced adequately by a small-scale rainfall simulator With this problem in mind this paper presents an enhanced small-scale simulator which allows a virtual multiplication of the plot length by feeding additional sediment loaded water to the plot from upstream. Thus is possible to overcome the plot length limited to 3m while reproducing nearly similar flow conditions as in rainfall experiments on standard plots. The simulator is extensively applied to plots of different soil types, crop types and management systems. The comparison with existing data sets obtained by large-scale rainfall simulations show that results can adequately be reproduced by the applied combination of small-scale rainfall simulator and sediment loaded water influx.

Collaborative Distributed Scheduling Approaches for Wireless Sensor Network

PubMed Central

Niu, Jianjun; Deng, Zhidong

2009-01-01

Energy constraints restrict the lifetime of wireless sensor networks (WSNs) with battery-powered nodes, which poses great challenges for their large scale application. In this paper, we propose a family of collaborative distributed scheduling approaches (CDSAs) based on the Markov process to reduce the energy consumption of a WSN. The family of CDSAs comprises of two approaches: a one-step collaborative distributed approach and a two-step collaborative distributed approach. The approaches enable nodes to learn the behavior information of its environment collaboratively and integrate sleep scheduling with transmission scheduling to reduce the energy consumption. We analyze the adaptability and practicality features of the CDSAs. The simulation results show that the two proposed approaches can effectively reduce nodes' energy consumption. Some other characteristics of the CDSAs like buffer occupation and packet delay are also analyzed in this paper. We evaluate CDSAs extensively on a 15-node WSN testbed. The test results show that the CDSAs conserve the energy effectively and are feasible for real WSNs. PMID:22408491

Interaction chromatography for characterization and large-scale fractionation of chemically heterogeneous copolymers

NASA Astrophysics Data System (ADS)

Han, Junwon

The remarkable development of polymer synthesis techniques to make complex polymers with controlled chain architectures has inevitably demanded the advancement of polymer characterization tools to analyze the molecular dispersity in polymeric materials beyond size exclusion chromatography (SEC). In particular, man-made synthetic copolymers that consist of more than one monomer type are disperse mixtures of polymer chains that have distributions in terms of both chemical heterogeneity and chain length (molar mass). While the molecular weight distribution has been quite reliably estimated by the SEC, it is still challenging to properly characterize the chemical composition distribution in the copolymers. Here, I have developed and applied adsorption-based interaction chromatography (IC) techniques as a promising tool to characterize and fractionate polystyrene-based block, random and branched copolymers in terms of their chemical heterogeneity. The first part of this thesis is focused on the adsorption-desorption based purification of PS-b-PMMA diblock copolymers using nanoporous silica. The liquid chromatography analysis and large scale purification are discussed for the PS-b-PMMA block copolymers that have been synthesized by sequential anionic polymerization. SEC and IC are compared to critically analyze the contents of PS homopolymers in the as-synthesized block copolymers. In addition, I have developed an IC technique to provide faster and more reliable information on the chemical heterogeneity in the as-synthesized block copolymers. Finally, a large scale (multi-gram) separation technique is developed to obtain "homopolymer-free" block copolymers via a simple chromatographic filtration technique. By taking advantage of the large specific surface area of nanoporous silica (≈300m 2/g), large scale purification of neat PS-b-PMMA has successfully been achieved by controlling adsorption and desorption of the block copolymers on the silica gel surface using a gravity column. The second part of this thesis is focused on the liquid chromatography analysis and fractionation of RAFT-polymerized PS-b -PMMA diblock copolymers and AFM studies. In this study, PS- b-PMMA block copolymers were synthesized by a RAFT free radical polymerization process---the PMMA block with a phenyldithiobenzoate end group was synthesized first. The contents of unreacted PS and PMMA homopolymers in as-synthesized PS-b-PMMA block copolymers were quantitatively analyzed by solvent gradient interaction chromatography (SGIC) technique employing bare silica and C18-bonded silica columns, respectively. In addition, by 2-dimensional large-scale IC fractionation method, atomic force microscopy (AFM) study of these fractionated samples revealed various morphologies with respect to the chemical composition of each fraction. The third part of this thesis is to analyze random copolymers with tunable monomer sequence distributions using interaction chromatography. Here, IC was used for characterizing the composition and monomer sequence distribution in statistical copolymers of poly(styrene-co-4-bromostyrene) (PBrxS). The PBrS copolymers were synthesized by the bromination of monodisperse polystyrenes; the degree of bromination (x) and the sequence distribution were adjusted by varying the bromination time and the solvent quality, respectively. Both normal-phase (bare silica) and reversed-phase (C18-bonded silica) columns were used at different combinations of solvents and non-solvents to monitor the content of the 4-bromostyrene units in the copolymer and their average monomer sequence distribution. The fourth part of this thesis is to analyze and fractionate highly branched polymers such as dendronized polymers and star-shaped homo and copolymers. I have developed an interaction chromatography technique to separate polymers with nonlinear chain architecture. Specifically, the IC technique has been used to separate dendronized polymers and PS-based highly branched copolymers and to ultimately obtain well-defined dendronized or branched copolymers with a low polydispersity. The effects of excess arm-polymers on (1) the micellar self-assembly of dendronized polymers and (2) the regularity of the pore morphology in the low-k applications by the sol-gel process have been studied.

Distributed data mining on grids: services, tools, and applications.

PubMed

Cannataro, Mario; Congiusta, Antonio; Pugliese, Andrea; Talia, Domenico; Trunfio, Paolo

2004-12-01

Data mining algorithms are widely used today for the analysis of large corporate and scientific datasets stored in databases and data archives. Industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed and parallel systems. The grid can play a significant role in providing an effective computational support for distributed knowledge discovery applications. For the development of data mining applications on grids we designed a system called Knowledge Grid. This paper describes the Knowledge Grid framework and presents the toolset provided by the Knowledge Grid for implementing distributed knowledge discovery. The paper discusses how to design and implement data mining applications by using the Knowledge Grid tools starting from searching grid resources, composing software and data components, and executing the resulting data mining process on a grid. Some performance results are also discussed.

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

Katti, Amogh; Di Fatta, Giuseppe; Naughton, Thomas

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that inmore » all algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.« less

Liter-scale production of uniform gas bubbles via parallelization of flow-focusing generators.

PubMed

Jeong, Heon-Ho; Yadavali, Sagar; Issadore, David; Lee, Daeyeon

2017-07-25

Microscale gas bubbles have demonstrated enormous utility as versatile templates for the synthesis of functional materials in medicine, ultra-lightweight materials and acoustic metamaterials. In many of these applications, high uniformity of the size of the gas bubbles is critical to achieve the desired properties and functionality. While microfluidics have been used with success to create gas bubbles that have a uniformity not achievable using conventional methods, the inherently low volumetric flow rate of microfluidics has limited its use in most applications. Parallelization of liquid droplet generators, in which many droplet generators are incorporated onto a single chip, has shown great promise for the large scale production of monodisperse liquid emulsion droplets. However, the scale-up of monodisperse gas bubbles using such an approach has remained a challenge because of possible coupling between parallel bubbles generators and feedback effects from the downstream channels. In this report, we systematically investigate the effect of factors such as viscosity of the continuous phase, capillary number, and gas pressure as well as the channel uniformity on the size distribution of gas bubbles in a parallelized microfluidic device. We show that, by optimizing the flow conditions, a device with 400 parallel flow focusing generators on a footprint of 5 × 5 cm 2 can be used to generate gas bubbles with a coefficient of variation of less than 5% at a production rate of approximately 1 L h -1 . Our results suggest that the optimization of flow conditions using a device with a small number (e.g., 8) of parallel FFGs can facilitate large-scale bubble production.

Open | SpeedShop: An Open Source Infrastructure for Parallel Performance Analysis

DOE PAGES

Schulz, Martin; Galarowicz, Jim; Maghrak, Don; ...

2008-01-01

Over the last decades a large number of performance tools has been developed to analyze and optimize high performance applications. Their acceptance by end users, however, has been slow: each tool alone is often limited in scope and comes with widely varying interfaces and workflow constraints, requiring different changes in the often complex build and execution infrastructure of the target application. We started the Open | SpeedShop project about 3 years ago to overcome these limitations and provide efficient, easy to apply, and integrated performance analysis for parallel systems. Open | SpeedShop has two different faces: it provides an interoperable tool set covering themore » most common analysis steps as well as a comprehensive plugin infrastructure for building new tools. In both cases, the tools can be deployed to large scale parallel applications using DPCL/Dyninst for distributed binary instrumentation. Further, all tools developed within or on top of Open | SpeedShop are accessible through multiple fully equivalent interfaces including an easy-to-use GUI as well as an interactive command line interface reducing the usage threshold for those tools.« less

The impact of land-surface wetness heterogeneity on mesoscale heat fluxes

NASA Technical Reports Server (NTRS)

Chen, Fei; Avissar, Roni

1994-01-01

Vertical heat fluxes associated with mesoscale circulations generated by land-surface wetness discontinuities are often stronger than turbulent fluxes, especially in the upper part of the atmospheric planetary boundary layer. As a result, they contribute significantly to the subgrid-scale fluxes in large-scale atmospheric models. Yet they are not considered in these models. To provide some insights into the possible parameterization of these fluxes in large-scale models, a state-of-the-art mesoscale numerical model was used to investigate the relationships between mesoscale heat fluxes and atmospheric and land-surface characteristics that play a key role in the generation of mesoscale circulations. The distribution of land-surface wetness, the wavenumber and the wavelength of the land-surface discontinuities, and the large-scale wind speed have a significant impact on the mesoscale heat fluxes. Empirical functions were derived to characterize the relationships between mesoscale heat fluxes and the spatial distribution of land-surface wetness. The strongest mesoscale heat fluxes were obtained for a wavelength of forcing corresponding approximately to the local Rossby deformation radius. The mesoscale heat fluxes are weakened by large-scale background winds but remain significant even with moderate winds.

Assessing actual evapotranspiration via surface energy balance aiming to optimize water and energy consumption in large scale pressurized irrigation systems

NASA Astrophysics Data System (ADS)

Awada, H.; Ciraolo, G.; Maltese, A.; Moreno Hidalgo, M. A.; Provenzano, G.; Còrcoles, J. I.

2017-10-01

Satellite imagery provides a dependable basis for computational models that aimed to determine actual evapotranspiration (ET) by surface energy balance. Satellite-based models enables quantifying ET over large areas for a wide range of applications, such as monitoring water distribution, managing irrigation and assessing irrigation systems' performance. With the aim to evaluate the energy and water consumption of a large scale on-turn pressurized irrigation system in the district of Aguas Nuevas, Albacete, Spain, the satellite-based image-processing model SEBAL was used for calculating actual ET. The model has been applied to quantify instantaneous, daily, and seasonal actual ET over high- resolution Landsat images for the peak water demand season (May to September) and for the years 2006 - 2008. The model provided a direct estimation of the distribution of main energy fluxes, at the instant when the satellite overpassed over each field of the district. The image acquisition day Evapotranspiration (ET24) was obtained from instantaneous values by assuming a constant evaporative fraction (Λ) for the entire day of acquisition; then, monthly and seasonal ET were estimated from the daily evapotranspiration (ETdaily) assuming that ET24 varies in proportion to reference ET (ETr) at the meteorological station, thus accounting for day to day variation in meteorological forcing. The comparison between the hydrants water consumption and the actual evapotranspiration, considering an irrigation efficiency of 85%, showed that a considerable amount of water and energy can be saved at district level.

Discrimination of bed form scales using robust spline filters and wavelet transforms: Methods and application to synthetic signals and bed forms of the Río Paraná, Argentina

NASA Astrophysics Data System (ADS)

Gutierrez, Ronald R.; Abad, Jorge D.; Parsons, Daniel R.; Best, James L.

2013-09-01

There is no standard nomenclature and procedure to systematically identify the scale and magnitude of bed forms such as bars, dunes, and ripples that are commonly present in many sedimentary environments. This paper proposes a standardization of the nomenclature and symbolic representation of bed forms and details the combined application of robust spline filters and continuous wavelet transforms to discriminate these morphodynamic features, allowing the quantitative recognition of bed form hierarchies. Herein the proposed methodology for bed form discrimination is first applied to synthetic bed form profiles, which are sampled at a Nyquist ratio interval of 2.5-50 and a signal-to-noise ratio interval of 1-20 and subsequently applied to a detailed 3-D bed topography from the Río Paraná, Argentina, which exhibits large-scale dunes with superimposed, smaller bed forms. After discriminating the synthetic bed form signals into three-bed form hierarchies that represent bars, dunes, and ripples, the accuracy of the methodology is quantified by estimating the reproducibility, the cross correlation, and the standard deviation ratio of the actual and retrieved signals. For the case of the field measurements, the proposed method is used to discriminate small and large dunes and subsequently obtain and statistically analyze the common morphological descriptors such as wavelength, slope, and amplitude of both stoss and lee sides of these different size bed forms. Analysis of the synthetic signals demonstrates that the Morlet wavelet function is the most efficient in retrieving smaller periodicities such as ripples and smaller dunes and that the proposed methodology effectively discriminates waves of different periods for Nyquist ratios higher than 25 and signal-to-noise ratios higher than 5. The analysis of bed forms in the Río Paraná reveals that, in most cases, a Gamma probability distribution, with a positive skewness, best describes the dimensionless wavelength and amplitude for both the lee and stoss sides of large dunes. For the case of smaller superimposed dunes, the dimensionless wavelength shows a discrete behavior that is governed by the sampling frequency of the data, and the dimensionless amplitude better fits the Gamma probability distribution, again with a positive skewness. This paper thus provides a robust methodology for systematically identifying the scales and magnitudes of bed forms in a range of environments.

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

PubMed

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

PubMed Central

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

Climate-driven C4 plant distributions in China: divergence in C4 taxa

PubMed Central

Wang, Renzhong; Ma, Linna

2016-01-01

There have been debates on the driving factors of C4 plant expansion, such as PCO2 decline in the late Micocene and warmer climate and precipitation at large-scale modern ecosystems. These disputes are mainly due to the lack of direct evidence and extensive data analysis. Here we use mass flora data to explore the driving factors of C4 distribution and divergent patterns for different C4 taxa at continental scale in China. The results display that it is mean annual climate variables driving C4 distribution at present-day vegetation. Mean annual temperature is the critical restriction of total C4 plants and the precipitation gradients seem to have much less impact. Grass and sedge C4 plants are largely restricted to mean annual temperature and precipitation respectively, while Chenopod C4 plants are strongly restricted by aridity in China. Separate regression analysis can succeed to detect divergences of climate distribution patterns of C4 taxa at global scale. PMID:27302686

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.