Large-scale methanol plants. [Based on Japanese-developed process

Energy Technology Data Exchange (ETDEWEB)

Tado, Y

1978-02-01

A study was made on how to produce methanol economically which is expected as a growth item for use as a material for pollution-free energy or for chemical use, centering on the following subjects: (1) Improvement of thermal economy, (2) Improvement of process, and (3) Problems of hardware attending the expansion of scale. The results of this study were already adopted in actual plants, obtaining good results, and large-scale methanol plants are going to be realized.

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

Science.gov (United States)

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

Informational support of the investment process in a large city economy

Directory of Open Access Journals (Sweden)

Tamara Zurabovna Chargazia

2016-12-01

Full Text Available Large cities possess a sufficient potential to participate in the investment processes both at the national and international levels. A potential investor’s awareness of the possibilities and prospects of a city development is of a great importance for him or her to make a decision. So, providing a potential investor with relevant, laconic and reliable information, the local authorities increase the intensity of the investment process in the city economy and vice-versa. As a hypothesis, there is a proposition that a large city administration can sufficiently activate the investment processes in the economy of a corresponding territorial entity using the tools of the information providing. The purpose of this article is to develop measures for the improvement of the investment portal of a large city as an important instrument of the information providing, which will make it possible to brisk up the investment processes at the level under analysis. The reasons of the unsatisfactory information providing on the investment process in a large city economy are deeply analyzed; the national and international experience in this sphere is studied; advantages and disadvantages of the information providing of the investment process in the economy of the city of Makeyevka are considered; the investment portals of different cities are compared. There are suggested technical approaches for improving the investment portal of a large city. The research results can be used to improve the investment policy of large cities.

Foundations of Large-Scale Multimedia Information Management and Retrieval

CERN Document Server

Chang, Edward Y

2011-01-01

"Foundations of Large-Scale Multimedia Information Management and Retrieval - Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and

Constructing large scale SCI-based processing systems by switch elements

International Nuclear Information System (INIS)

Wu, B.; Kristiansen, E.; Skaali, B.; Bogaerts, A.; Divia, R.; Mueller, H.

1993-05-01

The goal of this paper is to study some of the design criteria for the switch elements to form the interconnection of large scale SCI-based processing systems. The approved IEEE standard 1596 makes it possible to couple up to 64K nodes together. In order to connect thousands of nodes to construct large scale SCI-based processing systems, one has to interconnect these nodes by switch elements to form different topologies. A summary of the requirements and key points of interconnection networks and switches is presented. Two models of the SCI switch elements are proposed. The authors investigate several examples of systems constructed for 4-switches with simulations and the results are analyzed. Some issues and enhancements are discussed to provide the ideas behind the switch design that can improve performance and reduce latency. 29 refs., 11 figs., 3 tabs

The role of categorization and scale endpoint comparisons in numerical information processing: A two-process model.

Science.gov (United States)

Tao, Tao; Wyer, Robert S; Zheng, Yuhuang

2017-03-01

We propose a two-process conceptualization of numerical information processing to describe how people form impressions of a score that is described along a bounded scale. According to the model, people spontaneously categorize a score as high or low. Furthermore, they compare the numerical discrepancy between the score and the endpoint of the scale to which it is closer, if they are not confident of their categorization, and use implications of this comparison as a basis for judgment. As a result, their evaluation of the score is less extreme when the range of numbers along the scale is large (e.g., from 0 to 100) than when it is small (from 0 to 10). Six experiments support this two-process model and demonstrate its generalizability. Specifically, the magnitude of numbers composing the scale has less impact on judgments (a) when the score being evaluated is extreme, (b) when individuals are unmotivated to engage in endpoint comparison processes (i.e., they are low in need for cognition), and (c) when they are unable to do so (i.e., they are under cognitive load). Moreover, the endpoint to which individuals compare the score can depend on their regulatory focus. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Visual analysis of inter-process communication for large-scale parallel computing.

Science.gov (United States)

Muelder, Chris; Gygi, Francois; Ma, Kwan-Liu

2009-01-01

In serial computation, program profiling is often helpful for optimization of key sections of code. When moving to parallel computation, not only does the code execution need to be considered but also communication between the different processes which can induce delays that are detrimental to performance. As the number of processes increases, so does the impact of the communication delays on performance. For large-scale parallel applications, it is critical to understand how the communication impacts performance in order to make the code more efficient. There are several tools available for visualizing program execution and communications on parallel systems. These tools generally provide either views which statistically summarize the entire program execution or process-centric views. However, process-centric visualizations do not scale well as the number of processes gets very large. In particular, the most common representation of parallel processes is a Gantt char t with a row for each process. As the number of processes increases, these charts can become difficult to work with and can even exceed screen resolution. We propose a new visualization approach that affords more scalability and then demonstrate it on systems running with up to 16,384 processes.

Implementation of a large-scale hospital information infrastructure for multi-unit health-care services.

Science.gov (United States)

Yoo, Sun K; Kim, Dong Keun; Kim, Jung C; Park, Youn Jung; Chang, Byung Chul

2008-01-01

With the increase in demand for high quality medical services, the need for an innovative hospital information system has become essential. An improved system has been implemented in all hospital units of the Yonsei University Health System. Interoperability between multi-units required appropriate hardware infrastructure and software architecture. This large-scale hospital information system encompassed PACS (Picture Archiving and Communications Systems), EMR (Electronic Medical Records) and ERP (Enterprise Resource Planning). It involved two tertiary hospitals and 50 community hospitals. The monthly data production rate by the integrated hospital information system is about 1.8 TByte and the total quantity of data produced so far is about 60 TByte. Large scale information exchange and sharing will be particularly useful for telemedicine applications.

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

Science.gov (United States)

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.

Information contained within the large scale gas injection test (Lasgit) dataset exposed using a bespoke data analysis tool-kit

International Nuclear Information System (INIS)

Bennett, D.P.; Thomas, H.R.; Cuss, R.J.; Harrington, J.F.; Vardon, P.J.

2012-01-01

Document available in extended abstract form only. The Large Scale Gas Injection Test (Lasgit) is a field scale experiment run by the British Geological Survey (BGS) and is located approximately 420 m underground at SKB's Aespoe Hard Rock Laboratory (HRL) in Sweden. It has been designed to study the impact on safety of gas build up within a KBS-3V concept high level radioactive waste repository. Lasgit has been in almost continuous operation for approximately seven years and is still underway. An analysis of the dataset arising from the Lasgit experiment with particular attention to the smaller scale features and phenomenon recorded has been undertaken in parallel to the macro scale analysis performed by the BGS. Lasgit is a highly instrumented, frequently sampled and long-lived experiment leading to a substantial dataset containing in excess of 14.7 million datum points. The data is anticipated to include a wealth of information, including information regarding overall processes as well as smaller scale or 'second order' features. Due to the size of the dataset coupled with the detailed analysis of the dataset required and the reduction in subjectivity associated with measurement compared to observation, computational analysis is essential. Moreover, due to the length of operation and complexity of experimental activity, the Lasgit dataset is not typically suited to 'out of the box' time series analysis algorithms. In particular, the features that are not suited to standard algorithms include non-uniformities due to (deliberate) changes in sample rate at various points in the experimental history and missing data due to hardware malfunction/failure causing interruption of logging cycles. To address these features a computational tool-kit capable of performing an Exploratory Data Analysis (EDA) on long-term, large-scale datasets with non-uniformities has been developed. Particular tool-kit abilities include: the parameterization of signal variation in the dataset

Large-scale Health Information Database and Privacy Protection.

Science.gov (United States)

Yamamoto, Ryuichi

2016-09-01

Japan was once progressive in the digitalization of healthcare fields but unfortunately has fallen behind in terms of the secondary use of data for public interest. There has recently been a trend to establish large-scale health databases in the nation, and a conflict between data use for public interest and privacy protection has surfaced as this trend has progressed. Databases for health insurance claims or for specific health checkups and guidance services were created according to the law that aims to ensure healthcare for the elderly; however, there is no mention in the act about using these databases for public interest in general. Thus, an initiative for such use must proceed carefully and attentively. The PMDA projects that collect a large amount of medical record information from large hospitals and the health database development project that the Ministry of Health, Labour and Welfare (MHLW) is working on will soon begin to operate according to a general consensus; however, the validity of this consensus can be questioned if issues of anonymity arise. The likelihood that researchers conducting a study for public interest would intentionally invade the privacy of their subjects is slim. However, patients could develop a sense of distrust about their data being used since legal requirements are ambiguous. Nevertheless, without using patients' medical records for public interest, progress in medicine will grind to a halt. Proper legislation that is clear for both researchers and patients will therefore be highly desirable. A revision of the Act on the Protection of Personal Information is currently in progress. In reality, however, privacy is not something that laws alone can protect; it will also require guidelines and self-discipline. We now live in an information capitalization age. I will introduce the trends in legal reform regarding healthcare information and discuss some basics to help people properly face the issue of health big data and privacy

Challenges and opportunities : One stop processing of automatic large-scale base map production using airborne lidar data within gis environment case study: Makassar City, Indonesia

NARCIS (Netherlands)

Widyaningrum, E.; Gorte, B.G.H.

2017-01-01

LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

Science.gov (United States)

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

Some Examples of Residence-Time Distribution Studies in Large-Scale Chemical Processes by Using Radiotracer Techniques

Energy Technology Data Exchange (ETDEWEB)

Bullock, R. M.; Johnson, P.; Whiston, J. [Imperial Chemical Industries Ltd., Billingham, Co., Durham (United Kingdom)

1967-06-15

The application of radiotracers to determine flow patterns in chemical processes is discussed with particular reference to the derivation of design data from model reactors for translation to large-scale units, the study of operating efficiency and design attainment in established plant and the rapid identification of various types of process malfunction. The requirements governing the selection of tracers for various types of media are considered and an example is given of the testing of the behaviour of a typical tracer before use in a particular large-scale process operating at 250 atm and 200 Degree-Sign C. Information which may be derived from flow patterns is discussed including the determination of mixing parameters, gas hold-up in gas/liquid reactions and the detection of channelling and stagnant regions. Practical results and their interpretation are given in relation to an define hydroformylation reaction system, a process for the conversion of propylene to isopropanol, a moving bed catalyst system for the isomerization of xylenes and a three-stage gas-liquid reaction system. The use of mean residence-time data for the detection of leakage between reaction vessels and a heat interchanger system is given as an example of the identification of process malfunction. (author)

Large-scale membrane transfer process: its application to single-crystal-silicon continuous membrane deformable mirror

International Nuclear Information System (INIS)

Wu, Tong; Sasaki, Takashi; Hane, Kazuhiro; Akiyama, Masayuki

2013-01-01

This paper describes a large-scale membrane transfer process developed for the construction of large-scale membrane devices via the transfer of continuous single-crystal-silicon membranes from one substrate to another. This technique is applied for fabricating a large stroke deformable mirror. A bimorph spring array is used to generate a large air gap between the mirror membrane and the electrode. A 1.9 mm × 1.9 mm × 2 µm single-crystal-silicon membrane is successfully transferred to the electrode substrate by Au–Si eutectic bonding and the subsequent all-dry release process. This process provides an effective approach for transferring a free-standing large continuous single-crystal-silicon to a flexible suspension spring array with a large air gap. (paper)

NASA's Information Power Grid: Large Scale Distributed Computing and Data Management

Science.gov (United States)

Johnston, William E.; Vaziri, Arsi; Hinke, Tom; Tanner, Leigh Ann; Feiereisen, William J.; Thigpen, William; Tang, Harry (Technical Monitor)

2001-01-01

Large-scale science and engineering are done through the interaction of people, heterogeneous computing resources, information systems, and instruments, all of which are geographically and organizationally dispersed. The overall motivation for Grids is to facilitate the routine interactions of these resources in order to support large-scale science and engineering. Multi-disciplinary simulations provide a good example of a class of applications that are very likely to require aggregation of widely distributed computing, data, and intellectual resources. Such simulations - e.g. whole system aircraft simulation and whole system living cell simulation - require integrating applications and data that are developed by different teams of researchers frequently in different locations. The research team's are the only ones that have the expertise to maintain and improve the simulation code and/or the body of experimental data that drives the simulations. This results in an inherently distributed computing and data management environment.

Direction of information flow in large-scale resting-state networks is frequency-dependent.

Science.gov (United States)

Hillebrand, Arjan; Tewarie, Prejaas; van Dellen, Edwin; Yu, Meichen; Carbo, Ellen W S; Douw, Linda; Gouw, Alida A; van Straaten, Elisabeth C W; Stam, Cornelis J

2016-04-05

Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.

High-Resiliency and Auto-Scaling of Large-Scale Cloud Computing for OCO-2 L2 Full Physics Processing

Science.gov (United States)

Hua, H.; Manipon, G.; Starch, M.; Dang, L. B.; Southam, P.; Wilson, B. D.; Avis, C.; Chang, A.; Cheng, C.; Smyth, M.; McDuffie, J. L.; Ramirez, P.

2015-12-01

Next generation science data systems are needed to address the incoming flood of data from new missions such as SWOT and NISAR where data volumes and data throughput rates are order of magnitude larger than present day missions. Additionally, traditional means of procuring hardware on-premise are already limited due to facilities capacity constraints for these new missions. Existing missions, such as OCO-2, may also require high turn-around time for processing different science scenarios where on-premise and even traditional HPC computing environments may not meet the high processing needs. We present our experiences on deploying a hybrid-cloud computing science data system (HySDS) for the OCO-2 Science Computing Facility to support large-scale processing of their Level-2 full physics data products. We will explore optimization approaches to getting best performance out of hybrid-cloud computing as well as common issues that will arise when dealing with large-scale computing. Novel approaches were utilized to do processing on Amazon's spot market, which can potentially offer ~10X costs savings but with an unpredictable computing environment based on market forces. We will present how we enabled high-tolerance computing in order to achieve large-scale computing as well as operational cost savings.

Moditored unsaturated soil transport processes as a support for large scale soil and water management

Science.gov (United States)

Vanclooster, Marnik

2010-05-01

The current societal demand for sustainable soil and water management is very large. The drivers of global and climate change exert many pressures on the soil and water ecosystems, endangering appropriate ecosystem functioning. The unsaturated soil transport processes play a key role in soil-water system functioning as it controls the fluxes of water and nutrients from the soil to plants (the pedo-biosphere link), the infiltration flux of precipitated water to groundwater and the evaporative flux, and hence the feed back from the soil to the climate system. Yet, unsaturated soil transport processes are difficult to quantify since they are affected by huge variability of the governing properties at different space-time scales and the intrinsic non-linearity of the transport processes. The incompatibility of the scales between the scale at which processes reasonably can be characterized, the scale at which the theoretical process correctly can be described and the scale at which the soil and water system need to be managed, calls for further development of scaling procedures in unsaturated zone science. It also calls for a better integration of theoretical and modelling approaches to elucidate transport processes at the appropriate scales, compatible with the sustainable soil and water management objective. Moditoring science, i.e the interdisciplinary research domain where modelling and monitoring science are linked, is currently evolving significantly in the unsaturated zone hydrology area. In this presentation, a review of current moditoring strategies/techniques will be given and illustrated for solving large scale soil and water management problems. This will also allow identifying research needs in the interdisciplinary domain of modelling and monitoring and to improve the integration of unsaturated zone science in solving soil and water management issues. A focus will be given on examples of large scale soil and water management problems in Europe.

Large-scale Health Information Database and Privacy Protection*1

Science.gov (United States)

YAMAMOTO, Ryuichi

2016-01-01

Japan was once progressive in the digitalization of healthcare fields but unfortunately has fallen behind in terms of the secondary use of data for public interest. There has recently been a trend to establish large-scale health databases in the nation, and a conflict between data use for public interest and privacy protection has surfaced as this trend has progressed. Databases for health insurance claims or for specific health checkups and guidance services were created according to the law that aims to ensure healthcare for the elderly; however, there is no mention in the act about using these databases for public interest in general. Thus, an initiative for such use must proceed carefully and attentively. The PMDA*2 projects that collect a large amount of medical record information from large hospitals and the health database development project that the Ministry of Health, Labour and Welfare (MHLW) is working on will soon begin to operate according to a general consensus; however, the validity of this consensus can be questioned if issues of anonymity arise. The likelihood that researchers conducting a study for public interest would intentionally invade the privacy of their subjects is slim. However, patients could develop a sense of distrust about their data being used since legal requirements are ambiguous. Nevertheless, without using patients’ medical records for public interest, progress in medicine will grind to a halt. Proper legislation that is clear for both researchers and patients will therefore be highly desirable. A revision of the Act on the Protection of Personal Information is currently in progress. In reality, however, privacy is not something that laws alone can protect; it will also require guidelines and self-discipline. We now live in an information capitalization age. I will introduce the trends in legal reform regarding healthcare information and discuss some basics to help people properly face the issue of health big data and privacy

Requirements and principles for the implementation and construction of large-scale geographic information systems

Science.gov (United States)

Smith, Terence R.; Menon, Sudhakar; Star, Jeffrey L.; Estes, John E.

1987-01-01

This paper provides a brief survey of the history, structure and functions of 'traditional' geographic information systems (GIS), and then suggests a set of requirements that large-scale GIS should satisfy, together with a set of principles for their satisfaction. These principles, which include the systematic application of techniques from several subfields of computer science to the design and implementation of GIS and the integration of techniques from computer vision and image processing into standard GIS technology, are discussed in some detail. In particular, the paper provides a detailed discussion of questions relating to appropriate data models, data structures and computational procedures for the efficient storage, retrieval and analysis of spatially-indexed data.

A large-scale forest landscape model incorporating multi-scale processes and utilizing forest inventory data

Science.gov (United States)

Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson III; David R. Larsen; Jacob S. Fraser; Jian. Yang

2013-01-01

Two challenges confronting forest landscape models (FLMs) are how to simulate fine, standscale processes while making large-scale (i.e., .107 ha) simulation possible, and how to take advantage of extensive forest inventory data such as U.S. Forest Inventory and Analysis (FIA) data to initialize and constrain model parameters. We present the LANDIS PRO model that...

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

Science.gov (United States)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we

Large scale production and downstream processing of a recombinant porcine parvovirus vaccine

NARCIS (Netherlands)

Maranga, L.; Rueda, P.; Antonis, A.F.G.; Vela, C.; Langeveld, J.P.M.; Casal, J.I.; Carrondo, M.J.T.

2002-01-01

Porcine parvovirus (PPV) virus-like particles (VLPs) constitute a potential vaccine for prevention of parvovirus-induced reproductive failure in gilts. Here we report the development of a large scale (25 l) production process for PPV-VLPs with baculovirus-infected insect cells. A low multiplicity of

Simulation research on the process of large scale ship plane segmentation intelligent workshop

Science.gov (United States)

Xu, Peng; Liao, Liangchuang; Zhou, Chao; Xue, Rui; Fu, Wei

2017-04-01

Large scale ship plane segmentation intelligent workshop is a new thing, and there is no research work in related fields at home and abroad. The mode of production should be transformed by the existing industry 2.0 or part of industry 3.0, also transformed from "human brain analysis and judgment + machine manufacturing" to "machine analysis and judgment + machine manufacturing". In this transforming process, there are a great deal of tasks need to be determined on the aspects of management and technology, such as workshop structure evolution, development of intelligent equipment and changes in business model. Along with them is the reformation of the whole workshop. Process simulation in this project would verify general layout and process flow of large scale ship plane section intelligent workshop, also would analyze intelligent workshop working efficiency, which is significant to the next step of the transformation of plane segmentation intelligent workshop.

Data-driven process decomposition and robust online distributed modelling for large-scale processes

Science.gov (United States)

Shu, Zhang; Lijuan, Li; Lijuan, Yao; Shipin, Yang; Tao, Zou

2018-02-01

With the increasing attention of networked control, system decomposition and distributed models show significant importance in the implementation of model-based control strategy. In this paper, a data-driven system decomposition and online distributed subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering algorithm into several clusters. Each cluster can be regarded as a subsystem. Then the inputs of each subsystem are selected by offline canonical correlation analysis between all process variables and its controlled variables. Process decomposition is then realised after the screening of input and output variables. When the system decomposition is finished, the online subsystem modelling can be carried out by recursively block-wise renewing the samples. The proposed algorithm was applied in the Tennessee Eastman process and the validity was verified.

A large scale analysis of information-theoretic network complexity measures using chemical structures.

Directory of Open Access Journals (Sweden)

Matthias Dehmer

Full Text Available This paper aims to investigate information-theoretic network complexity measures which have already been intensely used in mathematical- and medicinal chemistry including drug design. Numerous such measures have been developed so far but many of them lack a meaningful interpretation, e.g., we want to examine which kind of structural information they detect. Therefore, our main contribution is to shed light on the relatedness between some selected information measures for graphs by performing a large scale analysis using chemical networks. Starting from several sets containing real and synthetic chemical structures represented by graphs, we study the relatedness between a classical (partition-based complexity measure called the topological information content of a graph and some others inferred by a different paradigm leading to partition-independent measures. Moreover, we evaluate the uniqueness of network complexity measures numerically. Generally, a high uniqueness is an important and desirable property when designing novel topological descriptors having the potential to be applied to large chemical databases.

Large Scale Gaussian Processes for Atmospheric Parameter Retrieval and Cloud Screening

Science.gov (United States)

Camps-Valls, G.; Gomez-Chova, L.; Mateo, G.; Laparra, V.; Perez-Suay, A.; Munoz-Mari, J.

2017-12-01

Current Earth-observation (EO) applications for image classification have to deal with an unprecedented big amount of heterogeneous and complex data sources. Spatio-temporally explicit classification methods are a requirement in a variety of Earth system data processing applications. Upcoming missions such as the super-spectral Copernicus Sentinels EnMAP and FLEX will soon provide unprecedented data streams. Very high resolution (VHR) sensors like Worldview-3 also pose big challenges to data processing. The challenge is not only attached to optical sensors but also to infrared sounders and radar images which increased in spectral, spatial and temporal resolution. Besides, we should not forget the availability of the extremely large remote sensing data archives already collected by several past missions, such ENVISAT, Cosmo-SkyMED, Landsat, SPOT, or Seviri/MSG. These large-scale data problems require enhanced processing techniques that should be accurate, robust and fast. Standard parameter retrieval and classification algorithms cannot cope with this new scenario efficiently. In this work, we review the field of large scale kernel methods for both atmospheric parameter retrieval and cloud detection using infrared sounding IASI data and optical Seviri/MSG imagery. We propose novel Gaussian Processes (GPs) to train problems with millions of instances and high number of input features. Algorithms can cope with non-linearities efficiently, accommodate multi-output problems, and provide confidence intervals for the predictions. Several strategies to speed up algorithms are devised: random Fourier features and variational approaches for cloud classification using IASI data and Seviri/MSG, and engineered randomized kernel functions and emulation in temperature, moisture and ozone atmospheric profile retrieval from IASI as a proxy to the upcoming MTG-IRS sensor. Excellent compromise between accuracy and scalability are obtained in all applications.

Process optimization of large-scale production of recombinant adeno-associated vectors using dielectric spectroscopy.

Science.gov (United States)

Negrete, Alejandro; Esteban, Geoffrey; Kotin, Robert M

2007-09-01

A well-characterized manufacturing process for the large-scale production of recombinant adeno-associated vectors (rAAV) for gene therapy applications is required to meet current and future demands for pre-clinical and clinical studies and potential commercialization. Economic considerations argue in favor of suspension culture-based production. Currently, the only feasible method for large-scale rAAV production utilizes baculovirus expression vectors and insect cells in suspension cultures. To maximize yields and achieve reproducibility between batches, online monitoring of various metabolic and physical parameters is useful for characterizing early stages of baculovirus-infected insect cells. In this study, rAAVs were produced at 40-l scale yielding ~1 x 10(15) particles. During the process, dielectric spectroscopy was performed by real time scanning in radio frequencies between 300 kHz and 10 MHz. The corresponding permittivity values were correlated with the rAAV production. Both infected and uninfected reached a maximum value; however, only infected cell cultures permittivity profile reached a second maximum value. This effect was correlated with the optimal harvest time for rAAV production. Analysis of rAAV indicated the harvesting time around 48 h post-infection (hpi), and 72 hpi produced similar quantities of biologically active rAAV. Thus, if operated continuously, the 24-h reduction in the production process of rAAV gives sufficient time for additional 18 runs a year corresponding to an extra production of ~2 x 10(16) particles. As part of large-scale optimization studies, this new finding will facilitate the bioprocessing scale-up of rAAV and other bioproducts.

Risk Management Challenges in Large-scale Energy PSS

DEFF Research Database (Denmark)

Tegeltija, Miroslava; Oehmen, Josef; Kozin, Igor

2017-01-01

Probabilistic risk management approaches have a long tradition in engineering. A large variety of tools and techniques based on the probabilistic view of risk is available and applied in PSS practice. However, uncertainties that arise due to lack of knowledge and information are still missing...... adequate representations. We focus on a large-scale energy company in Denmark as one case of current product/servicesystems risk management best practices. We analyze their risk management process and investigate the tools they use in order to support decision making processes within the company. First, we...... identify the following challenges in the current risk management practices that are in line with literature: (1) current methods are not appropriate for the situations dominated by weak knowledge and information; (2) quality of traditional models in such situations is open to debate; (3) quality of input...

Performance evaluation of the DCMD desalination process under bench scale and large scale module operating conditions

KAUST Repository

Francis, Lijo

2014-04-01

The flux performance of different hydrophobic microporous flat sheet commercial membranes made of poly tetrafluoroethylene (PTFE) and poly propylene (PP) was tested for Red Sea water desalination using the direct contact membrane distillation (DCMD) process, under bench scale (high δT) and large scale module (low δT) operating conditions. Membranes were characterized for their surface morphology, water contact angle, thickness, porosity, pore size and pore size distribution. The DCMD process performance was optimized using a locally designed and fabricated module aiming to maximize the flux at different levels of operating parameters, mainly feed water and coolant inlet temperatures at different temperature differences across the membrane (δT). Water vapor flux of 88.8kg/m2h was obtained using a PTFE membrane at high δT (60°C). In addition, the flux performance was compared to the first generation of a new locally synthesized and fabricated membrane made of a different class of polymer under the same conditions. A total salt rejection of 99.99% and boron rejection of 99.41% were achieved under extreme operating conditions. On the other hand, a detailed water characterization revealed that low molecular weight non-ionic molecules (ppb level) were transported with the water vapor molecules through the membrane structure. The membrane which provided the highest flux was then tested under large scale module operating conditions. The average flux of the latter study (low δT) was found to be eight times lower than that of the bench scale (high δT) operating conditions.

Performance evaluation of the DCMD desalination process under bench scale and large scale module operating conditions

KAUST Repository

Francis, Lijo; Ghaffour, NorEddine; Alsaadi, Ahmad Salem; Nunes, Suzana Pereira; Amy, Gary L.

2014-01-01

The flux performance of different hydrophobic microporous flat sheet commercial membranes made of poly tetrafluoroethylene (PTFE) and poly propylene (PP) was tested for Red Sea water desalination using the direct contact membrane distillation (DCMD) process, under bench scale (high δT) and large scale module (low δT) operating conditions. Membranes were characterized for their surface morphology, water contact angle, thickness, porosity, pore size and pore size distribution. The DCMD process performance was optimized using a locally designed and fabricated module aiming to maximize the flux at different levels of operating parameters, mainly feed water and coolant inlet temperatures at different temperature differences across the membrane (δT). Water vapor flux of 88.8kg/m2h was obtained using a PTFE membrane at high δT (60°C). In addition, the flux performance was compared to the first generation of a new locally synthesized and fabricated membrane made of a different class of polymer under the same conditions. A total salt rejection of 99.99% and boron rejection of 99.41% were achieved under extreme operating conditions. On the other hand, a detailed water characterization revealed that low molecular weight non-ionic molecules (ppb level) were transported with the water vapor molecules through the membrane structure. The membrane which provided the highest flux was then tested under large scale module operating conditions. The average flux of the latter study (low δT) was found to be eight times lower than that of the bench scale (high δT) operating conditions.

Modeling of large-scale oxy-fuel combustion processes

DEFF Research Database (Denmark)

Yin, Chungen

2012-01-01

Quite some studies have been conducted in order to implement oxy-fuel combustion with flue gas recycle in conventional utility boilers as an effective effort of carbon capture and storage. However, combustion under oxy-fuel conditions is significantly different from conventional air-fuel firing......, among which radiative heat transfer under oxy-fuel conditions is one of the fundamental issues. This paper demonstrates the nongray-gas effects in modeling of large-scale oxy-fuel combustion processes. Oxy-fuel combustion of natural gas in a 609MW utility boiler is numerically studied, in which...... calculation of the oxy-fuel WSGGM remarkably over-predicts the radiative heat transfer to the furnace walls and under-predicts the gas temperature at the furnace exit plane, which also result in a higher incomplete combustion in the gray calculation. Moreover, the gray and non-gray calculations of the same...

Analysis Methods for Extracting Knowledge from Large-Scale WiFi Monitoring to Inform Building Facility Planning

DEFF Research Database (Denmark)

Ruiz-Ruiz, Antonio; Blunck, Henrik; Prentow, Thor Siiger

2014-01-01

realistic data to inform facility planning. In this paper, we propose analysis methods to extract knowledge from large sets of network collected WiFi traces to better inform facility management and planning in large building complexes. The analysis methods, which build on a rich set of temporal and spatial......The optimization of logistics in large building com- plexes with many resources, such as hospitals, require realistic facility management and planning. Current planning practices rely foremost on manual observations or coarse unverified as- sumptions and therefore do not properly scale or provide....... Spatio-temporal visualization tools built on top of these methods enable planners to inspect and explore extracted information to inform facility-planning activities. To evaluate the methods, we present results for a large hospital complex covering more than 10 hectares. The evaluation is based on Wi...

Large scale chromatographic separations using continuous displacement chromatography (CDC)

International Nuclear Information System (INIS)

Taniguchi, V.T.; Doty, A.W.; Byers, C.H.

1988-01-01

A process for large scale chromatographic separations using a continuous chromatography technique is described. The process combines the advantages of large scale batch fixed column displacement chromatography with conventional analytical or elution continuous annular chromatography (CAC) to enable large scale displacement chromatography to be performed on a continuous basis (CDC). Such large scale, continuous displacement chromatography separations have not been reported in the literature. The process is demonstrated with the ion exchange separation of a binary lanthanide (Nd/Pr) mixture. The process is, however, applicable to any displacement chromatography separation that can be performed using conventional batch, fixed column chromatography

Applicability of vector processing to large-scale nuclear codes

International Nuclear Information System (INIS)

Ishiguro, Misako; Harada, Hiroo; Matsuura, Toshihiko; Okuda, Motoi; Ohta, Fumio; Umeya, Makoto.

1982-03-01

To meet the growing trend of computational requirements in JAERI, introduction of a high-speed computer with vector processing faculty (a vector processor) is desirable in the near future. To make effective use of a vector processor, appropriate optimization of nuclear codes to pipelined-vector architecture is vital, which will pose new problems concerning code development and maintenance. In this report, vector processing efficiency is assessed with respect to large-scale nuclear codes by examining the following items: 1) The present feature of computational load in JAERI is analyzed by compiling the computer utilization statistics. 2) Vector processing efficiency is estimated for the ten heavily-used nuclear codes by analyzing their dynamic behaviors run on a scalar machine. 3) Vector processing efficiency is measured for the other five nuclear codes by using the current vector processors, FACOM 230-75 APU and CRAY-1. 4) Effectiveness of applying a high-speed vector processor to nuclear codes is evaluated by taking account of the characteristics in JAERI jobs. Problems of vector processors are also discussed from the view points of code performance and ease of use. (author)

Development of polymers for large scale roll-to-roll processing of polymer solar cells

DEFF Research Database (Denmark)

Carlé, Jon Eggert

Development of polymers for large scale roll-to-roll processing of polymer solar cells Conjugated polymers potential to both absorb light and transport current as well as the perspective of low cost and large scale production has made these kinds of material attractive in solar cell research....... The research field of polymer solar cells (PSCs) is rapidly progressing along three lines: Improvement of efficiency and stability together with the introduction of large scale production methods. All three lines are explored in this work. The thesis describes low band gap polymers and why these are needed....... Polymer of this type display broader absorption resulting in better overlap with the solar spectrum and potentially higher current density. Synthesis, characterization and device performance of three series of polymers illustrating how the absorption spectrum of polymers can be manipulated synthetically...

Analogue scale modelling of extensional tectonic processes using a large state-of-the-art centrifuge

Science.gov (United States)

Park, Heon-Joon; Lee, Changyeol

2017-04-01

Analogue scale modelling of extensional tectonic processes such as rifting and basin opening has been numerously conducted. Among the controlling factors, gravitational acceleration (g) on the scale models was regarded as a constant (Earth's gravity) in the most of the analogue model studies, and only a few model studies considered larger gravitational acceleration by using a centrifuge (an apparatus generating large centrifugal force by rotating the model at a high speed). Although analogue models using a centrifuge allow large scale-down and accelerated deformation that is derived by density differences such as salt diapir, the possible model size is mostly limited up to 10 cm. A state-of-the-art centrifuge installed at the KOCED Geotechnical Centrifuge Testing Center, Korea Advanced Institute of Science and Technology (KAIST) allows a large surface area of the scale-models up to 70 by 70 cm under the maximum capacity of 240 g-tons. Using the centrifuge, we will conduct analogue scale modelling of the extensional tectonic processes such as opening of the back-arc basin. Acknowledgement This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (grant number 2014R1A6A3A04056405).

A Proactive Complex Event Processing Method for Large-Scale Transportation Internet of Things

OpenAIRE

Wang, Yongheng; Cao, Kening

2014-01-01

The Internet of Things (IoT) provides a new way to improve the transportation system. The key issue is how to process the numerous events generated by IoT. In this paper, a proactive complex event processing method is proposed for large-scale transportation IoT. Based on a multilayered adaptive dynamic Bayesian model, a Bayesian network structure learning algorithm using search-and-score is proposed to support accurate predictive analytics. A parallel Markov decision processes model is design...

Towards the understanding of network information processing in biology

Science.gov (United States)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

Hierarchical optimal control of large-scale nonlinear chemical processes.

Science.gov (United States)

Ramezani, Mohammad Hossein; Sadati, Nasser

2009-01-01

In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear chemical stirred tank reactor (CSTR), where its solution is also compared with the ones obtained using the centralized approach. The simulation results show the efficiency and the capability of the proposed hierarchical approach, in finding the optimal solution, over the centralized method.

Possible implications of large scale radiation processing of food

International Nuclear Information System (INIS)

Zagorski, Z.P.

1990-01-01

Large scale irradiation has been discussed in terms of the participation of processing cost in the final value of the improved product. Another factor has been taken into account and that is the saturation of the market with the new product. In the case of successful projects the participation of irradiation cost is low, and the demand for the better product is covered. A limited availability of sources makes the modest saturation of the market difficult with all food subjected to correct radiation treatment. The implementation of the preservation of food needs a decided selection of these kinds of food which comply to all conditions i.e. of acceptance by regulatory bodies, real improvement of quality and economy. The last condition prefers the possibility of use of electron beams of low energy. The best fulfilment of conditions for successful processing is observed in the group of dry food, in expensive spices in particular. (author)

Possible implications of large scale radiation processing of food

Science.gov (United States)

Zagórski, Z. P.

Large scale irradiation has been discussed in terms of the participation of processing cost in the final value of the improved product. Another factor has been taken into account and that is the saturation of the market with the new product. In the case of succesful projects the participation of irradiation cost is low, and the demand for the better product is covered. A limited availability of sources makes the modest saturation of the market difficult with all food subjected to correct radiation treatment. The implementation of the preservation of food needs a decided selection of these kinds of food which comply to all conditions i.e. of acceptance by regulatory bodies, real improvement of quality and economy. The last condition prefers the possibility of use of electron beams of low energy. The best fullfilment of conditions for succesful processing is observed in the group of dry food, in expensive spices in particular.

The large-scale process of microbial carbonate precipitation for nickel remediation from an industrial soil.

Science.gov (United States)

Zhu, Xuejiao; Li, Weila; Zhan, Lu; Huang, Minsheng; Zhang, Qiuzhuo; Achal, Varenyam

2016-12-01

Microbial carbonate precipitation is known as an efficient process for the remediation of heavy metals from contaminated soils. In the present study, a urease positive bacterial isolate, identified as Bacillus cereus NS4 through 16S rDNA sequencing, was utilized on a large scale to remove nickel from industrial soil contaminated by the battery industry. The soil was highly contaminated with an initial total nickel concentration of approximately 900 mg kg -1 . The soluble-exchangeable fraction was reduced to 38 mg kg -1 after treatment. The primary objective of metal stabilization was achieved by reducing the bioavailability through immobilizing the nickel in the urease-driven carbonate precipitation. The nickel removal in the soils contributed to the transformation of nickel from mobile species into stable biominerals identified as calcite, vaterite, aragonite and nickelous carbonate when analyzed under XRD. It was proven that during precipitation of calcite, Ni 2+ with an ion radius close to Ca 2+ was incorporated into the CaCO 3 crystal. The biominerals were also characterized by using SEM-EDS to observe the crystal shape and Raman-FTIR spectroscopy to predict responsible bonding during bioremediation with respect to Ni immobilization. The electronic structure and chemical-state information of the detected elements during MICP bioremediation process was studied by XPS. This is the first study in which microbial carbonate precipitation was used for the large-scale remediation of metal-contaminated industrial soil. Copyright © 2016 Elsevier Ltd. All rights reserved.

Extending SME to Handle Large-Scale Cognitive Modeling.

Science.gov (United States)

Forbus, Kenneth D; Ferguson, Ronald W; Lovett, Andrew; Gentner, Dedre

2017-07-01

Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine (SME) since its inception in 1986 that have increased its scope of operation. We first review the basic SME algorithm, describe psychological evidence for SME as a process model, and summarize its role in simulating similarity-based retrieval and generalization. Then we describe five techniques now incorporated into the SME that have enabled it to tackle large-scale modeling tasks: (a) Greedy merging rapidly constructs one or more best interpretations of a match in polynomial time: O(n 2 log(n)); (b) Incremental operation enables mappings to be extended as new information is retrieved or derived about the base or target, to model situations where information in a task is updated over time; (c) Ubiquitous predicates model the varying degrees to which items may suggest alignment; (d) Structural evaluation of analogical inferences models aspects of plausibility judgments; (e) Match filters enable large-scale task models to communicate constraints to SME to influence the mapping process. We illustrate via examples from published studies how these enable it to capture a broader range of psychological phenomena than before. Copyright © 2016 Cognitive Science Society, Inc.

Accelerating large-scale protein structure alignments with graphics processing units

Directory of Open Access Journals (Sweden)

Pang Bin

2012-02-01

Full Text Available Abstract Background Large-scale protein structure alignment, an indispensable tool to structural bioinformatics, poses a tremendous challenge on computational resources. To ensure structure alignment accuracy and efficiency, efforts have been made to parallelize traditional alignment algorithms in grid environments. However, these solutions are costly and of limited accessibility. Others trade alignment quality for speedup by using high-level characteristics of structure fragments for structure comparisons. Findings We present ppsAlign, a parallel protein structure Alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs. As a general-purpose GPU platform, ppsAlign could take many concurrent methods, such as TM-align and Fr-TM-align, into the parallelized algorithm design. We evaluated ppsAlign on an NVIDIA Tesla C2050 GPU card, and compared it with existing software solutions running on an AMD dual-core CPU. We observed a 36-fold speedup over TM-align, a 65-fold speedup over Fr-TM-align, and a 40-fold speedup over MAMMOTH. Conclusions ppsAlign is a high-performance protein structure alignment tool designed to tackle the computational complexity issues from protein structural data. The solution presented in this paper allows large-scale structure comparisons to be performed using massive parallel computing power of GPU.

Large-scale retrieval for medical image analytics: A comprehensive review.

Science.gov (United States)

Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

2018-01-01

Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Cloud-enabled large-scale land surface model simulations with the NASA Land Information System

Science.gov (United States)

Duffy, D.; Vaughan, G.; Clark, M. P.; Peters-Lidard, C. D.; Nijssen, B.; Nearing, G. S.; Rheingrover, S.; Kumar, S.; Geiger, J. V.

2017-12-01

Developed by the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC), the Land Information System (LIS) is a high-performance software framework for terrestrial hydrology modeling and data assimilation. LIS provides the ability to integrate satellite and ground-based observational products and advanced modeling algorithms to extract land surface states and fluxes. Through a partnership with the National Center for Atmospheric Research (NCAR) and the University of Washington, the LIS model is currently being extended to include the Structure for Unifying Multiple Modeling Alternatives (SUMMA). With the addition of SUMMA in LIS, meaningful simulations containing a large multi-model ensemble will be enabled and can provide advanced probabilistic continental-domain modeling capabilities at spatial scales relevant for water managers. The resulting LIS/SUMMA application framework is difficult for non-experts to install due to the large amount of dependencies on specific versions of operating systems, libraries, and compilers. This has created a significant barrier to entry for domain scientists that are interested in using the software on their own systems or in the cloud. In addition, the requirement to support multiple run time environments across the LIS community has created a significant burden on the NASA team. To overcome these challenges, LIS/SUMMA has been deployed using Linux containers, which allows for an entire software package along with all dependences to be installed within a working runtime environment, and Kubernetes, which orchestrates the deployment of a cluster of containers. Within a cloud environment, users can now easily create a cluster of virtual machines and run large-scale LIS/SUMMA simulations. Installations that have taken weeks and months can now be performed in minutes of time. This presentation will discuss the steps required to create a cloud-enabled large-scale simulation, present examples of its use, and

Large scale electrolysers

International Nuclear Information System (INIS)

B Bello; M Junker

2006-01-01

Hydrogen production by water electrolysis represents nearly 4 % of the world hydrogen production. Future development of hydrogen vehicles will require large quantities of hydrogen. Installation of large scale hydrogen production plants will be needed. In this context, development of low cost large scale electrolysers that could use 'clean power' seems necessary. ALPHEA HYDROGEN, an European network and center of expertise on hydrogen and fuel cells, has performed for its members a study in 2005 to evaluate the potential of large scale electrolysers to produce hydrogen in the future. The different electrolysis technologies were compared. Then, a state of art of the electrolysis modules currently available was made. A review of the large scale electrolysis plants that have been installed in the world was also realized. The main projects related to large scale electrolysis were also listed. Economy of large scale electrolysers has been discussed. The influence of energy prices on the hydrogen production cost by large scale electrolysis was evaluated. (authors)

Operational experinece with large scale biogas production at the promest manure processing plant in Helmond, the Netherlands

International Nuclear Information System (INIS)

Schomaker, A.H.H.M.

1992-01-01

In The Netherlands a surplus of 15 million tons of liquid pig manure is produced yearly on intensive pig breeding farms. The dutch government has set a three-way policy to reduce this excess of manure: 1. conversion of animal fodder into a product with less and better ingestible nutrients; 2. distribution of the surplus to regions with a shortage of animal manure; 3. processing of the remainder of the surplus in large scale processing plants. The first large scale plant for the processing of liquid pig manure was put in operation in 1988 as a demonstration plant at Promest in Helmond. The design capacity of this plant is 100,000 tons of pig manure per year. The plant was initiated by the Manure Steering Committee of the province Noord-Brabant in order to prove at short notice whether large scale manure processing might contribute to the solution of the problem of the manure surplus in The Netherlands. This steering committee is a corporation of the national and provincial government and the agricultural industrial life. (au)

Large scale processing of dielectric electroactive polymers

DEFF Research Database (Denmark)

Vudayagiri, Sindhu

Efficient processing techniques are vital to the success of any manufacturing industry. The processing techniques determine the quality of the products and thus to a large extent the performance and reliability of the products that are manufactured. The dielectric electroactive polymer (DEAP...

Large-scale simulation of ductile fracture process of microstructured materials

International Nuclear Information System (INIS)

Tian Rong; Wang Chaowei

2011-01-01

The promise of computational science in the extreme-scale computing era is to reduce and decompose macroscopic complexities into microscopic simplicities with the expense of high spatial and temporal resolution of computing. In materials science and engineering, the direct combination of 3D microstructure data sets and 3D large-scale simulations provides unique opportunity for the development of a comprehensive understanding of nano/microstructure-property relationships in order to systematically design materials with specific desired properties. In the paper, we present a framework simulating the ductile fracture process zone in microstructural detail. The experimentally reconstructed microstructural data set is directly embedded into a FE mesh model to improve the simulation fidelity of microstructure effects on fracture toughness. To the best of our knowledge, it is for the first time that the linking of fracture toughness to multiscale microstructures in a realistic 3D numerical model in a direct manner is accomplished. (author)

Scalable Networked Information Processing Environment (SNIPE)

Energy Technology Data Exchange (ETDEWEB)

Fagg, G.E.; Moore, K. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Computer Science; Dongarra, J.J. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Computer Science]|[Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.; Geist, A. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.

1997-11-01

SNIPE is a metacomputing system that aims to provide a reliable, secure, fault tolerant environment for long term distributed computing applications and data stores across the global Internet. This system combines global naming and replication of both processing and data to support large scale information processing applications leading to better availability and reliability than currently available with typical cluster computing and/or distributed computer environments.

Large transverse momentum processes in a non-scaling parton model

International Nuclear Information System (INIS)

Stirling, W.J.

1977-01-01

The production of large transverse momentum mesons in hadronic collisions by the quark fusion mechanism is discussed in a parton model which gives logarithmic corrections to Bjorken scaling. It is found that the moments of the large transverse momentum structure function exhibit a simple scale breaking behaviour similar to the behaviour of the Drell-Yan and deep inelastic structure functions of the model. An estimate of corresponding experimental consequences is made and the extent to which analogous results can be expected in an asymptotically free gauge theory is discussed. A simple set of rules is presented for incorporating the logarithmic corrections to scaling into all covariant parton model calculations. (Auth.)

Large-scale continuous process to vitrify nuclear defense waste: operating experience with nonradioactive waste

International Nuclear Information System (INIS)

Cosper, M.B.; Randall, C.T.; Traverso, G.M.

1982-01-01

The developmental program underway at SRL has demonstrated the vitrification process proposed for the sludge processing facility of the DWPF on a large scale. DWPF design criteria for production rate, equipment lifetime, and operability have all been met. The expected authorization and construction of the DWPF will result in the safe and permanent immobilization of a major quantity of existing high level waste. 11 figures, 4 tables

Large-scale calculations of the beta-decay rates and r-process nucleosynthesis

Energy Technology Data Exchange (ETDEWEB)

Borzov, I N; Goriely, S [Inst. d` Astronomie et d` Astrophysique, Univ. Libre de Bruxelles, Campus Plaine, Bruxelles (Belgium); Pearson, J M [Inst. d` Astronomie et d` Astrophysique, Univ. Libre de Bruxelles, Campus Plaine, Bruxelles (Belgium); [Lab. de Physique Nucleaire, Univ. de Montreal, Montreal (Canada)

1998-06-01

An approximation to a self-consistent model of the ground state and {beta}-decay properties of neutron-rich nuclei is outlined. The structure of the {beta}-strength functions in stable and short-lived nuclei is discussed. The results of large-scale calculations of the {beta}-decay rates for spherical and slightly deformed nuclides of relevance to the r-process are analysed and compared with the results of existing global calculations and recent experimental data. (orig.)

An industrial perspective on bioreactor scale-down: what we can learn from combined large-scale bioprocess and model fluid studies.

Science.gov (United States)

Noorman, Henk

2011-08-01

For industrial bioreactor design, operation, control and optimization, the scale-down approach is often advocated to efficiently generate data on a small scale, and effectively apply suggested improvements to the industrial scale. In all cases it is important to ensure that the scale-down conditions are representative of the real large-scale bioprocess. Progress is hampered by limited detailed and local information from large-scale bioprocesses. Complementary to real fermentation studies, physical aspects of model fluids such as air-water in large bioreactors provide useful information with limited effort and cost. Still, in industrial practice, investments of time, capital and resources often prohibit systematic work, although, in the end, savings obtained in this way are trivial compared to the expenses that result from real process disturbances, batch failures, and non-flyers with loss of business opportunity. Here we try to highlight what can be learned from real large-scale bioprocess in combination with model fluid studies, and to provide suitable computation tools to overcome data restrictions. Focus is on a specific well-documented case for a 30-m(3) bioreactor. Areas for further research from an industrial perspective are also indicated. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large-scale patterns in Rayleigh-Benard convection

International Nuclear Information System (INIS)

Hardenberg, J. von; Parodi, A.; Passoni, G.; Provenzale, A.; Spiegel, E.A.

2008-01-01

Rayleigh-Benard convection at large Rayleigh number is characterized by the presence of intense, vertically moving plumes. Both laboratory and numerical experiments reveal that the rising and descending plumes aggregate into separate clusters so as to produce large-scale updrafts and downdrafts. The horizontal scales of the aggregates reported so far have been comparable to the horizontal extent of the containers, but it has not been clear whether that represents a limitation imposed by domain size. In this work, we present numerical simulations of convection at sufficiently large aspect ratio to ascertain whether there is an intrinsic saturation scale for the clustering process when that ratio is large enough. From a series of simulations of Rayleigh-Benard convection with Rayleigh numbers between 10 5 and 10 8 and with aspect ratios up to 12π, we conclude that the clustering process has a finite horizontal saturation scale with at most a weak dependence on Rayleigh number in the range studied

Unpackaging residential segregation: the importance of scale and informal market processes

Directory of Open Access Journals (Sweden)

Peter M. Ward

2010-06-01

Full Text Available This paper addresses two principal issues: a the scale at which one examines urban segregation; and b how informality, specifically accessibility to land markets and the process of land appropriation by low-income groups in Latin American cities, influences segregation patterns. Using Mexico City as a case study for Latin America, it shows that macro residential segregation levels are not becoming more polarized as many believe, due to informality of the market place and the weak state intervention through planning and zoning. However, there is a hardening of boundaries between adjacent neighborhoods as people turn to gated communities, largely for security reasons. Case study material from three Mexican cities are presented to examine how the nature of residential land costs and market segmentation contributes to segregation in Latin American cities. In a second case study, data from peri-urban low-income self-build settlements (colonias in Texas cities demonstrate how existing inequality patterns can be reproduced by differential access to land markets. They further argue a case that such isolated (rural settlements serving nearby urban labor market, should also be included in any analysis of urban segregation patterns, even if they do not form part of the contiguous urban area.

PLANNING QUALITY ASSURANCE PROCESSES IN A LARGE SCALE GEOGRAPHICALLY SPREAD HYBRID SOFTWARE DEVELOPMENT PROJECT

Directory of Open Access Journals (Sweden)

Святослав Аркадійович МУРАВЕЦЬКИЙ

2016-02-01

Full Text Available There have been discussed key points of operational activates in a large scale geographically spread software development projects. A look taken at required QA processes structure in such project. There have been given up to date methods of integration quality assurance processes into software development processes. There have been reviewed existing groups of software development methodologies. Such as sequential, agile and based on RPINCE2. There have been given a condensed overview of quality assurance processes in each group. There have been given a review of common challenges that sequential and agile models are having in case of large geographically spread hybrid software development project. Recommendations were given in order to tackle those challenges.  The conclusions about the best methodology choice and appliance to the particular project have been made.

Challenges in Managing Trustworthy Large-scale Digital Science

Science.gov (United States)

Evans, B. J. K.

2017-12-01

The increased use of large-scale international digital science has opened a number of challenges for managing, handling, using and preserving scientific information. The large volumes of information are driven by three main categories - model outputs including coupled models and ensembles, data products that have been processing to a level of usability, and increasingly heuristically driven data analysis. These data products are increasingly the ones that are usable by the broad communities, and far in excess of the raw instruments data outputs. The data, software and workflows are then shared and replicated to allow broad use at an international scale, which places further demands of infrastructure to support how the information is managed reliably across distributed resources. Users necessarily rely on these underlying "black boxes" so that they are productive to produce new scientific outcomes. The software for these systems depend on computational infrastructure, software interconnected systems, and information capture systems. This ranges from the fundamentals of the reliability of the compute hardware, system software stacks and libraries, and the model software. Due to these complexities and capacity of the infrastructure, there is an increased emphasis of transparency of the approach and robustness of the methods over the full reproducibility. Furthermore, with large volume data management, it is increasingly difficult to store the historical versions of all model and derived data. Instead, the emphasis is on the ability to access the updated products and the reliability by which both previous outcomes are still relevant and can be updated for the new information. We will discuss these challenges and some of the approaches underway that are being used to address these issues.

Building Participation in Large-scale Conservation: Lessons from Belize and Panama

Directory of Open Access Journals (Sweden)

Jesse Guite Hastings

2015-01-01

Full Text Available Motivated by biogeography and a desire for alignment with the funding priorities of donors, the twenty-first century has seen big international NGOs shifting towards a large-scale conservation approach. This shift has meant that even before stakeholders at the national and local scale are involved, conservation programmes often have their objectives defined and funding allocated. This paper uses the experiences of Conservation International′s Marine Management Area Science (MMAS programme in Belize and Panama to explore how to build participation at the national and local scale while working within the bounds of the current conservation paradigm. Qualitative data about MMAS was gathered through a multi-sited ethnographic research process, utilising document review, direct observation, and semi-structured interviews with 82 informants in Belize, Panama, and the United States of America. Results indicate that while a large-scale approach to conservation disadvantages early national and local stakeholder participation, this effect can be mediated through focusing engagement efforts, paying attention to context, building horizontal and vertical partnerships, and using deliberative processes that promote learning. While explicit consideration of geopolitics and local complexity alongside biogeography in the planning phase of a large-scale conservation programme is ideal, actions taken by programme managers during implementation can still have a substantial impact on conservation outcomes.

Study of a large scale neutron measurement channel

International Nuclear Information System (INIS)

Amarouayache, Anissa; Ben Hadid, Hayet.

1982-12-01

A large scale measurement channel allows the processing of the signal coming from an unique neutronic sensor, during three different running modes: impulses, fluctuations and current. The study described in this note includes three parts: - A theoretical study of the large scale channel and its brief description are given. The results obtained till now in that domain are presented. - The fluctuation mode is thoroughly studied and the improvements to be done are defined. The study of a fluctuation linear channel with an automatic commutation of scales is described and the results of the tests are given. In this large scale channel, the method of data processing is analogical. - To become independent of the problems generated by the use of a an analogical processing of the fluctuation signal, a digital method of data processing is tested. The validity of that method is improved. The results obtained on a test system realized according to this method are given and a preliminary plan for further research is defined [fr

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

CERN Multimedia

CERN. Geneva; Marques, Paulo

2011-01-01

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...

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

Science.gov (United States)

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

2017-04-01

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

The use of production management techniques in the construction of large scale physics detectors

CERN Document Server

Bazan, A; Estrella, F; Kovács, Z; Le Flour, T; Le Goff, J M; Lieunard, S; McClatchey, R; Murray, S; Varga, L Z; Vialle, J P; Zsenei, M

1999-01-01

The construction process of detectors for the Large Hadron Collider (LHC) experiments is large scale, heavily constrained by resource availability and evolves with time. As a consequence, changes in detector component design need to be tracked and quickly reflected in the construction process. With similar problems in industry engineers employ so-called Product Data Management (PDM) systems to control access to documented versions of designs and managers employ so- called Workflow Management software (WfMS) to coordinate production work processes. However, PDM and WfMS software are not generally integrated in industry. The scale of LHC experiments, like CMS, demands that industrial production techniques be applied in detector construction. This paper outlines the major functions and applications of the CRISTAL system (Cooperating Repositories and an information System for Tracking Assembly Lifecycles) in use in CMS which successfully integrates PDM and WfMS techniques in managing large scale physics detector ...

LASSIE: the large analogue signal and scaling information environment for FAIR

International Nuclear Information System (INIS)

Hoffmann, T.; Braeuning, H.; Haseitl, R.

2012-01-01

At FAIR, the Facility for Antiproton and Ion Research, several new accelerators and storage rings such as the SIS-100, HESR, CR, the inter-connecting HEBT beam lines, S-FRS and experiments will be built. All of these installations are equipped with beam diagnostic devices and other components, which deliver time-resolved analogue signals to show status, quality and performance of the accelerators. These signals can originate from particle detectors such as ionization chambers and plastic scintillators, but also from adapted output signals of transformers, collimators, magnet functions, RF cavities and others. To visualize and precisely correlate the time axis of all input signals a dedicated FESA based data acquisition and analysis system named LASSIE, the Large Analogue Signal and Scaling Information Environment, is currently being developed. The main operation mode of LASSIE is currently pulse counting with latching VME scaler boards. Later enhancements for ADC, QDC, or TDC digitization in the future are foreseen. The concept, features and challenges of this large distributed data acquisition system are presented. (authors)

Large-scale production of diesel-like biofuels - process design as an inherent part of microorganism development.

Science.gov (United States)

Cuellar, Maria C; Heijnen, Joseph J; van der Wielen, Luuk A M

2013-06-01

Industrial biotechnology is playing an important role in the transition to a bio-based economy. Currently, however, industrial implementation is still modest, despite the advances made in microorganism development. Given that the fuels and commodity chemicals sectors are characterized by tight economic margins, we propose to address overall process design and efficiency at the start of bioprocess development. While current microorganism development is targeted at product formation and product yield, addressing process design at the start of bioprocess development means that microorganism selection can also be extended to other critical targets for process technology and process scale implementation, such as enhancing cell separation or increasing cell robustness at operating conditions that favor the overall process. In this paper we follow this approach for the microbial production of diesel-like biofuels. We review current microbial routes with both oleaginous and engineered microorganisms. For the routes leading to extracellular production, we identify the process conditions for large scale operation. The process conditions identified are finally translated to microorganism development targets. We show that microorganism development should be directed at anaerobic production, increasing robustness at extreme process conditions and tailoring cell surface properties. All the same time, novel process configurations integrating fermentation and product recovery, cell reuse and low-cost technologies for product separation are mandatory. This review provides a state-of-the-art summary of the latest challenges in large-scale production of diesel-like biofuels. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Scaling the Information Processing Demands of Occupations

Science.gov (United States)

Haase, Richard F.; Jome, LaRae M.; Ferreira, Joaquim Armando; Santos, Eduardo J. R.; Connacher, Christopher C.; Sendrowitz, Kerrin

2011-01-01

The purpose of this study was to provide additional validity evidence for a model of person-environment fit based on polychronicity, stimulus load, and information processing capacities. In this line of research the confluence of polychronicity and information processing (e.g., the ability of individuals to process stimuli from the environment…

The role of large-scale, extratropical dynamics in climate change

Energy Technology Data Exchange (ETDEWEB)

Shepherd, T.G. [ed.

1994-02-01

The climate modeling community has focused recently on improving our understanding of certain processes, such as cloud feedbacks and ocean circulation, that are deemed critical to climate-change prediction. Although attention to such processes is warranted, emphasis on these areas has diminished a general appreciation of the role played by the large-scale dynamics of the extratropical atmosphere. Lack of interest in extratropical dynamics may reflect the assumption that these dynamical processes are a non-problem as far as climate modeling is concerned, since general circulation models (GCMs) calculate motions on this scale from first principles. Nevertheless, serious shortcomings in our ability to understand and simulate large-scale dynamics exist. Partly due to a paucity of standard GCM diagnostic calculations of large-scale motions and their transports of heat, momentum, potential vorticity, and moisture, a comprehensive understanding of the role of large-scale dynamics in GCM climate simulations has not been developed. Uncertainties remain in our understanding and simulation of large-scale extratropical dynamics and their interaction with other climatic processes, such as cloud feedbacks, large-scale ocean circulation, moist convection, air-sea interaction and land-surface processes. To address some of these issues, the 17th Stanstead Seminar was convened at Bishop`s University in Lennoxville, Quebec. The purpose of the Seminar was to promote discussion of the role of large-scale extratropical dynamics in global climate change. Abstracts of the talks are included in this volume. On the basis of these talks, several key issues emerged concerning large-scale extratropical dynamics and their climatic role. Individual records are indexed separately for the database.

The role of large-scale, extratropical dynamics in climate change

International Nuclear Information System (INIS)

Shepherd, T.G.

1994-02-01

The climate modeling community has focused recently on improving our understanding of certain processes, such as cloud feedbacks and ocean circulation, that are deemed critical to climate-change prediction. Although attention to such processes is warranted, emphasis on these areas has diminished a general appreciation of the role played by the large-scale dynamics of the extratropical atmosphere. Lack of interest in extratropical dynamics may reflect the assumption that these dynamical processes are a non-problem as far as climate modeling is concerned, since general circulation models (GCMs) calculate motions on this scale from first principles. Nevertheless, serious shortcomings in our ability to understand and simulate large-scale dynamics exist. Partly due to a paucity of standard GCM diagnostic calculations of large-scale motions and their transports of heat, momentum, potential vorticity, and moisture, a comprehensive understanding of the role of large-scale dynamics in GCM climate simulations has not been developed. Uncertainties remain in our understanding and simulation of large-scale extratropical dynamics and their interaction with other climatic processes, such as cloud feedbacks, large-scale ocean circulation, moist convection, air-sea interaction and land-surface processes. To address some of these issues, the 17th Stanstead Seminar was convened at Bishop's University in Lennoxville, Quebec. The purpose of the Seminar was to promote discussion of the role of large-scale extratropical dynamics in global climate change. Abstracts of the talks are included in this volume. On the basis of these talks, several key issues emerged concerning large-scale extratropical dynamics and their climatic role. Individual records are indexed separately for the database

Towards scaling up trapped ion quantum information processing

International Nuclear Information System (INIS)

Leibfried, D.; Wineland, D. J.; Blakestad, R. B.; Bollinger, J. J.; Britton, J.; Chiaverini, J.; Epstein, R. J.; Itano, W. M.; Jost, J. D.; Knill, E.; Langer, C.; Ozeri, R.; Reichle, R.; Seidelin, S.; Shiga, N.; Wesenberg, J. H.

2007-01-01

Recent theoretical advances have identified several computational algorithms that can be implemented utilizing quantum information processing (QIP), which gives an exponential speedup over the corresponding (known) algorithms on conventional computers. QIP makes use of the counter-intuitive properties of quantum mechanics, such as entanglement and the superposition principle. Unfortunately it has so far been impossible to build a practical QIP system that outperforms conventional computers. Atomic ions confined in an array of interconnected traps represent a potentially scalable approach to QIP. All basic requirements have been experimentally demonstrated in one and two qubit experiments. The remaining task is to scale the system to many qubits while minimizing and correcting errors in the system. While this requires extremely challenging technological improvements, no fundamental roadblocks are currently foreseen.

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

OpenAIRE

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-makin...

Large-scale numerical simulations of plasmas

International Nuclear Information System (INIS)

Hamaguchi, Satoshi

2004-01-01

The recent trend of large scales simulations of fusion plasma and processing plasmas is briefly summarized. Many advanced simulation techniques have been developed for fusion plasmas and some of these techniques are now applied to analyses of processing plasmas. (author)

Large-Scale Sentinel-1 Processing for Solid Earth Science and Urgent Response using Cloud Computing and Machine Learning

Science.gov (United States)

Hua, H.; Owen, S. E.; Yun, S. H.; Agram, P. S.; Manipon, G.; Starch, M.; Sacco, G. F.; Bue, B. D.; Dang, L. B.; Linick, J. P.; Malarout, N.; Rosen, P. A.; Fielding, E. J.; Lundgren, P.; Moore, A. W.; Liu, Z.; Farr, T.; Webb, F.; Simons, M.; Gurrola, E. M.

2017-12-01

With the increased availability of open SAR data (e.g. Sentinel-1 A/B), new challenges are being faced with processing and analyzing the voluminous SAR datasets to make geodetic measurements. Upcoming SAR missions such as NISAR are expected to generate close to 100TB per day. The Advanced Rapid Imaging and Analysis (ARIA) project can now generate geocoded unwrapped phase and coherence products from Sentinel-1 TOPS mode data in an automated fashion, using the ISCE software. This capability is currently being exercised on various study sites across the United States and around the globe, including Hawaii, Central California, Iceland and South America. The automated and large-scale SAR data processing and analysis capabilities use cloud computing techniques to speed the computations and provide scalable processing power and storage. Aspects such as how to processing these voluminous SLCs and interferograms at global scales, keeping up with the large daily SAR data volumes, and how to handle the voluminous data rates are being explored. Scene-partitioning approaches in the processing pipeline help in handling global-scale processing up to unwrapped interferograms with stitching done at a late stage. We have built an advanced science data system with rapid search functions to enable access to the derived data products. Rapid image processing of Sentinel-1 data to interferograms and time series is already being applied to natural hazards including earthquakes, floods, volcanic eruptions, and land subsidence due to fluid withdrawal. We will present the status of the ARIA science data system for generating science-ready data products and challenges that arise from being able to process SAR datasets to derived time series data products at large scales. For example, how do we perform large-scale data quality screening on interferograms? What approaches can be used to minimize compute, storage, and data movement costs for time series analysis in the cloud? We will also

Economically viable large-scale hydrogen liquefaction

Science.gov (United States)

Cardella, U.; Decker, L.; Klein, H.

2017-02-01

The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.

Manufacturing test of large scale hollow capsule and long length cladding in the large scale oxide dispersion strengthened (ODS) martensitic steel

International Nuclear Information System (INIS)

Narita, Takeshi; Ukai, Shigeharu; Kaito, Takeji; Ohtsuka, Satoshi; Fujiwara, Masayuki

2004-04-01

Mass production capability of oxide dispersion strengthened (ODS) martensitic steel cladding (9Cr) has being evaluated in the Phase II of the Feasibility Studies on Commercialized Fast Reactor Cycle System. The cost for manufacturing mother tube (raw materials powder production, mechanical alloying (MA) by ball mill, canning, hot extrusion, and machining) is a dominant factor in the total cost for manufacturing ODS ferritic steel cladding. In this study, the large-sale 9Cr-ODS martensitic steel mother tube which is made with a large-scale hollow capsule, and long length claddings were manufactured, and the applicability of these processes was evaluated. Following results were obtained in this study. (1) Manufacturing the large scale mother tube in the dimension of 32 mm OD, 21 mm ID, and 2 m length has been successfully carried out using large scale hollow capsule. This mother tube has a high degree of accuracy in size. (2) The chemical composition and the micro structure of the manufactured mother tube are similar to the existing mother tube manufactured by a small scale can. And the remarkable difference between the bottom and top sides in the manufactured mother tube has not been observed. (3) The long length cladding has been successfully manufactured from the large scale mother tube which was made using a large scale hollow capsule. (4) For reducing the manufacturing cost of the ODS steel claddings, manufacturing process of the mother tubes using a large scale hollow capsules is promising. (author)

Ensuring Adequate Health and Safety Information for Decision Makers during Large-Scale Chemical Releases

Science.gov (United States)

Petropoulos, Z.; Clavin, C.; Zuckerman, B.

2015-12-01

The 2014 4-Methylcyclohexanemethanol (MCHM) spill in the Elk River of West Virginia highlighted existing gaps in emergency planning for, and response to, large-scale chemical releases in the United States. The Emergency Planning and Community Right-to-Know Act requires that facilities with hazardous substances provide Material Safety Data Sheets (MSDSs), which contain health and safety information on the hazardous substances. The MSDS produced by Eastman Chemical Company, the manufacturer of MCHM, listed "no data available" for various human toxicity subcategories, such as reproductive toxicity and carcinogenicity. As a result of incomplete toxicity data, the public and media received conflicting messages on the safety of the contaminated water from government officials, industry, and the public health community. Two days after the governor lifted the ban on water use, the health department partially retracted the ban by warning pregnant women to continue avoiding the contaminated water, which the Centers for Disease Control and Prevention deemed safe three weeks later. The response in West Virginia represents a failure in risk communication and calls to question if government officials have sufficient information to support evidence-based decisions during future incidents. Research capabilities, like the National Science Foundation RAPID funding, can provide a solution to some of the data gaps, such as information on environmental fate in the case of the MCHM spill. In order to inform policy discussions on this issue, a methodology for assessing the outcomes of RAPID and similar National Institutes of Health grants in the context of emergency response is employed to examine the efficacy of research-based capabilities in enhancing public health decision making capacity. The results of this assessment highlight potential roles rapid scientific research can fill in ensuring adequate health and safety data is readily available for decision makers during large-scale

Sustainable Manufacturing via Multi-Scale, Physics-Based Process Modeling and Manufacturing-Informed Design

Energy Technology Data Exchange (ETDEWEB)

None

2017-04-01

This factsheet describes a project that developed and demonstrated a new manufacturing-informed design framework that utilizes advanced multi-scale, physics-based process modeling to dramatically improve manufacturing productivity and quality in machining operations while reducing the cost of machined components.

Large-scale climatic anomalies affect marine predator foraging behaviour and demography

Science.gov (United States)

Bost, Charles A.; Cotté, Cedric; Terray, Pascal; Barbraud, Christophe; Bon, Cécile; Delord, Karine; Gimenez, Olivier; Handrich, Yves; Naito, Yasuhiko; Guinet, Christophe; Weimerskirch, Henri

2015-10-01

Determining the links between the behavioural and population responses of wild species to environmental variations is critical for understanding the impact of climate variability on ecosystems. Using long-term data sets, we show how large-scale climatic anomalies in the Southern Hemisphere affect the foraging behaviour and population dynamics of a key marine predator, the king penguin. When large-scale subtropical dipole events occur simultaneously in both subtropical Southern Indian and Atlantic Oceans, they generate tropical anomalies that shift the foraging zone southward. Consequently the distances that penguins foraged from the colony and their feeding depths increased and the population size decreased. This represents an example of a robust and fast impact of large-scale climatic anomalies affecting a marine predator through changes in its at-sea behaviour and demography, despite lack of information on prey availability. Our results highlight a possible behavioural mechanism through which climate variability may affect population processes.

Detection of large-scale concentric gravity waves from a Chinese airglow imager network

Science.gov (United States)

Lai, Chang; Yue, Jia; Xu, Jiyao; Yuan, Wei; Li, Qinzeng; Liu, Xiao

2018-06-01

Concentric gravity waves (CGWs) contain a broad spectrum of horizontal wavelengths and periods due to their instantaneous localized sources (e.g., deep convection, volcanic eruptions, or earthquake, etc.). However, it is difficult to observe large-scale gravity waves of >100 km wavelength from the ground for the limited field of view of a single camera and local bad weather. Previously, complete large-scale CGW imagery could only be captured by satellite observations. In the present study, we developed a novel method that uses assembling separate images and applying low-pass filtering to obtain temporal and spatial information about complete large-scale CGWs from a network of all-sky airglow imagers. Coordinated observations from five all-sky airglow imagers in Northern China were assembled and processed to study large-scale CGWs over a wide area (1800 km × 1 400 km), focusing on the same two CGW events as Xu et al. (2015). Our algorithms yielded images of large-scale CGWs by filtering out the small-scale CGWs. The wavelengths, wave speeds, and periods of CGWs were measured from a sequence of consecutive assembled images. Overall, the assembling and low-pass filtering algorithms can expand the airglow imager network to its full capacity regarding the detection of large-scale gravity waves.

Quantum Information Processing with Trapped Ions

International Nuclear Information System (INIS)

Barrett, M.D.; Schaetz, T.; Chiaverini, J.; Leibfried, D.; Britton, J.; Itano, W.M.; Jost, J.D.; Langer, C.; Ozeri, R.; Wineland, D.J.; Knill, E.

2005-01-01

We summarize two experiments on the creation and manipulation of multi-particle entangled states of trapped atomic ions - quantum dense coding and quantum teleportation. The techniques used in these experiments constitute an important step toward performing large-scale quantum information processing. The techniques also have application in other areas of physics, providing improvement in quantum-limited measurement and fundamental tests of quantum mechanical principles, for example

Geospatial Optimization of Siting Large-Scale Solar Projects

Energy Technology Data Exchange (ETDEWEB)

Macknick, Jordan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Quinby, Ted [National Renewable Energy Lab. (NREL), Golden, CO (United States); Caulfield, Emmet [Stanford Univ., CA (United States); Gerritsen, Margot [Stanford Univ., CA (United States); Diffendorfer, Jay [U.S. Geological Survey, Boulder, CO (United States); Haines, Seth [U.S. Geological Survey, Boulder, CO (United States)

2014-03-01

Recent policy and economic conditions have encouraged a renewed interest in developing large-scale solar projects in the U.S. Southwest. However, siting large-scale solar projects is complex. In addition to the quality of the solar resource, solar developers must take into consideration many environmental, social, and economic factors when evaluating a potential site. This report describes a proof-of-concept, Web-based Geographical Information Systems (GIS) tool that evaluates multiple user-defined criteria in an optimization algorithm to inform discussions and decisions regarding the locations of utility-scale solar projects. Existing siting recommendations for large-scale solar projects from governmental and non-governmental organizations are not consistent with each other, are often not transparent in methods, and do not take into consideration the differing priorities of stakeholders. The siting assistance GIS tool we have developed improves upon the existing siting guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.

Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

Science.gov (United States)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach

Using Large Scale Test Results for Pedagogical Purposes

DEFF Research Database (Denmark)

Dolin, Jens

2012-01-01

The use and influence of large scale tests (LST), both national and international, has increased dramatically within the last decade. This process has revealed a tension between the legitimate need for information about the performance of the educational system and teachers to inform policy......, and the teachers’ and students’ use of this information for pedagogical purposes in the classroom. We know well how the policy makers interpret and use the outcomes of such tests, but we know less about how teachers make use of LSTs to inform their pedagogical practice. An important question is whether...... there is a contradiction between the political system’s use of LST and teachers’ (possible) pedagogical use of LST. And if yes: What is a contradiction based on? This presentation will give some results from a systematic review on how tests have influenced the pedagogical practice. The research revealed many of the fatal...

Large-scale weakly supervised object localization via latent category learning.

Science.gov (United States)

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

Large-scale structure of the Universe

International Nuclear Information System (INIS)

Doroshkevich, A.G.

1978-01-01

The problems, discussed at the ''Large-scale Structure of the Universe'' symposium are considered on a popular level. Described are the cell structure of galaxy distribution in the Universe, principles of mathematical galaxy distribution modelling. The images of cell structures, obtained after reprocessing with the computer are given. Discussed are three hypothesis - vortical, entropic, adiabatic, suggesting various processes of galaxy and galaxy clusters origin. A considerable advantage of the adiabatic hypothesis is recognized. The relict radiation, as a method of direct studying the processes taking place in the Universe is considered. The large-scale peculiarities and small-scale fluctuations of the relict radiation temperature enable one to estimate the turbance properties at the pre-galaxy stage. The discussion of problems, pertaining to studying the hot gas, contained in galaxy clusters, the interactions within galaxy clusters and with the inter-galaxy medium, is recognized to be a notable contribution into the development of theoretical and observational cosmology

Influence of Extrinsic Information Scaling Coefficient on Double-Iterative Decoding Algorithm for Space-Time Turbo Codes with Large Number of Antennas

Directory of Open Access Journals (Sweden)

TRIFINA, L.

2011-02-01

Full Text Available This paper analyzes the extrinsic information scaling coefficient influence on double-iterative decoding algorithm for space-time turbo codes with large number of antennas. The max-log-APP algorithm is used, scaling both the extrinsic information in the turbo decoder and the one used at the input of the interference-canceling block. Scaling coefficients of 0.7 or 0.75 lead to a 0.5 dB coding gain compared to the no-scaling case, for one or more iterations to cancel the spatial interferences.

The Development and Validation of Scores on the Mathematics Information Processing Scale (MIPS).

Science.gov (United States)

Bessant, Kenneth C.

1997-01-01

This study reports on the development and psychometric properties of a new 87-item Mathematics Information Processing Scale that explores learning strategies, metacognitive problem-solving skills, and attentional deployment. Results with 340 college students support the use of the instrument, for which factor analysis identified five theoretically…

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

Science.gov (United States)

Maly, K.

1998-01-01

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated

Informational and emotional elements in online support groups: a Bayesian approach to large-scale content analysis.

Science.gov (United States)

Deetjen, Ulrike; Powell, John A

2016-05-01

This research examines the extent to which informational and emotional elements are employed in online support forums for 14 purposively sampled chronic medical conditions and the factors that influence whether posts are of a more informational or emotional nature. Large-scale qualitative data were obtained from Dailystrength.org. Based on a hand-coded training dataset, all posts were classified into informational or emotional using a Bayesian classification algorithm to generalize the findings. Posts that could not be classified with a probability of at least 75% were excluded. The overall tendency toward emotional posts differs by condition: mental health (depression, schizophrenia) and Alzheimer's disease consist of more emotional posts, while informational posts relate more to nonterminal physical conditions (irritable bowel syndrome, diabetes, asthma). There is no gender difference across conditions, although prostate cancer forums are oriented toward informational support, whereas breast cancer forums rather feature emotional support. Across diseases, the best predictors for emotional content are lower age and a higher number of overall posts by the support group member. The results are in line with previous empirical research and unify empirical findings from single/2-condition research. Limitations include the analytical restriction to predefined categories (informational, emotional) through the chosen machine-learning approach. Our findings provide an empirical foundation for building theory on informational versus emotional support across conditions, give insights for practitioners to better understand the role of online support groups for different patients, and show the usefulness of machine-learning approaches to analyze large-scale qualitative health data from online settings. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An Novel Architecture of Large-scale Communication in IOT

Science.gov (United States)

Ma, Wubin; Deng, Su; Huang, Hongbin

2018-03-01

In recent years, many scholars have done a great deal of research on the development of Internet of Things and networked physical systems. However, few people have made the detailed visualization of the large-scale communications architecture in the IOT. In fact, the non-uniform technology between IPv6 and access points has led to a lack of broad principles of large-scale communications architectures. Therefore, this paper presents the Uni-IPv6 Access and Information Exchange Method (UAIEM), a new architecture and algorithm that addresses large-scale communications in the IOT.

Are large-scale flow experiments informing the science and management of freshwater ecosystems?

Science.gov (United States)

Olden, Julian D.; Konrad, Christopher P.; Melis, Theodore S.; Kennard, Mark J.; Freeman, Mary C.; Mims, Meryl C.; Bray, Erin N.; Gido, Keith B.; Hemphill, Nina P.; Lytle, David A.; McMullen, Laura E.; Pyron, Mark; Robinson, Christopher T.; Schmidt, John C.; Williams, John G.

2013-01-01

Greater scientific knowledge, changing societal values, and legislative mandates have emphasized the importance of implementing large-scale flow experiments (FEs) downstream of dams. We provide the first global assessment of FEs to evaluate their success in advancing science and informing management decisions. Systematic review of 113 FEs across 20 countries revealed that clear articulation of experimental objectives, while not universally practiced, was crucial for achieving management outcomes and changing dam-operating policies. Furthermore, changes to dam operations were three times less likely when FEs were conducted primarily for scientific purposes. Despite the recognized importance of riverine flow regimes, four-fifths of FEs involved only discrete flow events. Over three-quarters of FEs documented both abiotic and biotic outcomes, but only one-third examined multiple taxonomic responses, thus limiting how FE results can inform holistic dam management. Future FEs will present new opportunities to advance scientifically credible water policies.

Large scale tracking algorithms

Energy Technology Data Exchange (ETDEWEB)

Hansen, Ross L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Love, Joshua Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melgaard, David Kennett [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Karelitz, David B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pitts, Todd Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zollweg, Joshua David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Anderson, Dylan Z. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nandy, Prabal [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Whitlow, Gary L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bender, Daniel A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Byrne, Raymond Harry [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.

Quantum information processing with atoms and photons

International Nuclear Information System (INIS)

Monroe, C.

2003-01-01

Quantum information processors exploit the quantum features of superposition and entanglement for applications not possible in classical devices, offering the potential for significant improvements in the communication and processing of information. Experimental realization of large-scale quantum information processors remains a long term vision, as the required nearly pure quantum behaviour is observed only in exotic hardware such as individual laser-cooled atoms and isolated photons. But recent theoretical and experimental advances suggest that cold atoms and individual photons may lead the way towards bigger and better quantum information processors, effectively building mesoscopic versions of Schroedinger's cat' from the bottom up. (author)

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

Energy Technology Data Exchange (ETDEWEB)

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah; Carns, Philip; Ross, Robert; Li, Jianping Kelvin; Ma, Kwan-Liu

2016-11-13

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has to gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a

Evolution of scaling emergence in large-scale spatial epidemic spreading.

Science.gov (United States)

Wang, Lin; Li, Xiang; Zhang, Yi-Qing; Zhang, Yan; Zhang, Kan

2011-01-01

Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which has still hardly been clarified. In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.

Modeling of a Large-Scale High Temperature Regenerative Sulfur Removal Process

DEFF Research Database (Denmark)

Konttinen, Jukka T.; Johnsson, Jan Erik

1999-01-01

model that does not account for bed hydrodynamics. The pilot-scale test run results, obtained in the test runs of the sulfur removal process with real coal gasifier gas, have been used for parameter estimation. The validity of the reactor model for commercial-scale design applications is discussed.......Regenerable mixed metal oxide sorbents are prime candidates for the removal of hydrogen sulfide from hot gasifier gas in the simplified integrated gasification combined cycle (IGCC) process. As part of the regenerative sulfur removal process development, reactor models are needed for scale......-up. Steady-state kinetic reactor models are needed for reactor sizing, and dynamic models can be used for process control design and operator training. The regenerative sulfur removal process to be studied in this paper consists of two side-by-side fluidized bed reactors operating at temperatures of 400...

Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

Science.gov (United States)

Ellwanger, Daniel Christian; Leonhardt, Jörn Florian; Mewes, Hans-Werner

2014-12-01

Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Scaling of an information system in a public healthcare market--infrastructuring from the vendor's perspective.

Science.gov (United States)

Johannessen, Liv Karen; Obstfelder, Aud; Lotherington, Ann Therese

2013-05-01

The purpose of this paper is to explore the making and scaling of information infrastructures, as well as how the conditions for scaling a component may change for the vendor. The first research question is how the making and scaling of a healthcare information infrastructure can be done and by whom. The second question is what scope for manoeuvre there might be for vendors aiming to expand their market. This case study is based on an interpretive approach, whereby data is gathered through participant observation and semi-structured interviews. A case study of the making and scaling of an electronic system for general practitioners ordering laboratory services from hospitals is described as comprising two distinct phases. The first may be characterized as an evolving phase, when development, integration and implementation were achieved in small steps, and the vendor, together with end users, had considerable freedom to create the solution according to the users' needs. The second phase was characterized by a large-scale procurement process over which regional healthcare authorities exercised much more control and the needs of groups other than the end users influenced the design. The making and scaling of healthcare information infrastructures is not simply a process of evolution, in which the end users use and change the technology. It also consists of large steps, during which different actors, including vendors and healthcare authorities, may make substantial contributions. This process requires work, negotiation and strategies. The conditions for the vendor may change dramatically, from considerable freedom and close relationships with users and customers in the small-scale development, to losing control of the product and being required to engage in more formal relations with customers in the wider public healthcare market. Onerous procurement processes may be one of the reasons why large-scale implementation of information projects in healthcare is difficult

Emergent Semantics Interoperability in Large-Scale Decentralized Information Systems

CERN Document Server

Cudré-Mauroux, Philippe

2008-01-01

Peer-to-peer systems are evolving with new information-system architectures, leading to the idea that the principles of decentralization and self-organization will offer new approaches in informatics, especially for systems that scale with the number of users or for which central authorities do not prevail. This book describes a new way of building global agreements (semantic interoperability) based only on decentralized, self-organizing interactions.

Mapping spatial patterns of denitrifiers at large scales (Invited)

Science.gov (United States)

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.

Large-scale Health Information Database and Privacy Protection*1

OpenAIRE

YAMAMOTO, Ryuichi

2016-01-01

Japan was once progressive in the digitalization of healthcare fields but unfortunately has fallen behind in terms of the secondary use of data for public interest. There has recently been a trend to establish large-scale health databases in the nation, and a conflict between data use for public interest and privacy protection has surfaced as this trend has progressed. Databases for health insurance claims or for specific health checkups and guidance services were created according to the law...

Innovation Processes in Large-Scale Public Foodservice-Case Findings from the Implementation of Organic Foods in a Danish County

DEFF Research Database (Denmark)

Mikkelsen, Bent Egberg; Nielsen, Thorkild; Kristensen, Niels Heine

2005-01-01

is the idea that the large-scale foodservice such as hospital food service should adopt a buy organic policy due to their large buying volume. But whereas implementation of organic foods has developed quite unproblematically in smaller institutions such as kindergartens and nurseries, introduction of organic...... foods into large-scale foodservice such as that taking place in hospitals and larger homes for the elderly, has proven to be quite difficult. The very complex planning, procurement and processing procedures used in such facilities are among reasons for this. Against this background an evaluation...

Large-scale solar purchasing

International Nuclear Information System (INIS)

1999-01-01

The principal objective of the project was to participate in the definition of a new IEA task concerning solar procurement (''the Task'') and to assess whether involvement in the task would be in the interest of the UK active solar heating industry. The project also aimed to assess the importance of large scale solar purchasing to UK active solar heating market development and to evaluate the level of interest in large scale solar purchasing amongst potential large scale purchasers (in particular housing associations and housing developers). A further aim of the project was to consider means of stimulating large scale active solar heating purchasing activity within the UK. (author)

Photorealistic large-scale urban city model reconstruction.

Science.gov (United States)

Poullis, Charalambos; You, Suya

2009-01-01

The rapid and efficient creation of virtual environments has become a crucial part of virtual reality applications. In particular, civil and defense applications often require and employ detailed models of operations areas for training, simulations of different scenarios, planning for natural or man-made events, monitoring, surveillance, games, and films. A realistic representation of the large-scale environments is therefore imperative for the success of such applications since it increases the immersive experience of its users and helps reduce the difference between physical and virtual reality. However, the task of creating such large-scale virtual environments still remains a time-consuming and manual work. In this work, we propose a novel method for the rapid reconstruction of photorealistic large-scale virtual environments. First, a novel, extendible, parameterized geometric primitive is presented for the automatic building identification and reconstruction of building structures. In addition, buildings with complex roofs containing complex linear and nonlinear surfaces are reconstructed interactively using a linear polygonal and a nonlinear primitive, respectively. Second, we present a rendering pipeline for the composition of photorealistic textures, which unlike existing techniques, can recover missing or occluded texture information by integrating multiple information captured from different optical sensors (ground, aerial, and satellite).

Large-scale visualization system for grid environment

International Nuclear Information System (INIS)

Suzuki, Yoshio

2007-01-01

Center for Computational Science and E-systems of Japan Atomic Energy Agency (CCSE/JAEA) has been conducting R and Ds of distributed computing (grid computing) environments: Seamless Thinking Aid (STA), Information Technology Based Laboratory (ITBL) and Atomic Energy Grid InfraStructure (AEGIS). In these R and Ds, we have developed the visualization technology suitable for the distributed computing environment. As one of the visualization tools, we have developed the Parallel Support Toolkit (PST) which can execute the visualization process parallely on a computer. Now, we improve PST to be executable simultaneously on multiple heterogeneous computers using Seamless Thinking Aid Message Passing Interface (STAMPI). STAMPI, we have developed in these R and Ds, is the MPI library executable on a heterogeneous computing environment. The improvement realizes the visualization of extremely large-scale data and enables more efficient visualization processes in a distributed computing environment. (author)

The use of production management techniques in the construction of large scale physics detectors

International Nuclear Information System (INIS)

Bazan, A.; Chevenier, G.; Estrella, F.

1999-01-01

The construction process of detectors for the Large Hadron Collider (LHC) experiments is large scale, heavily constrained by resource availability and evolves with time. As a consequence, changes in detector component design need to be tracked and quickly reflected in the construction process. With similar problems in industry engineers employ so-called Product Data Management (PDM) systems to control access to documented versions of designs and managers employ so-called Product Data Management (PDM) systems to control access to documented versions of designs and managers employ so-called Workflow Management Software (WfMS) to coordinate production work processes. However, PDM and WfMS software are not generally integrated in industry. The scale of LHC experiments, like CMS, demands that industrial production techniques be applied in detector construction. This paper outlines the major functions and applications of the CRISTAL system (Cooperating Repositories and an Information System for Tracking Assembly Lifecycles) in use in CMS which successfully integrates PDM and WfMS techniques in managing large scale physics detector construction. This is the first time industrial production techniques have been deployed to this extent in detector construction

Photonic Architecture for Scalable Quantum Information Processing in Diamond

Directory of Open Access Journals (Sweden)

Kae Nemoto

2014-08-01

Full Text Available Physics and information are intimately connected, and the ultimate information processing devices will be those that harness the principles of quantum mechanics. Many physical systems have been identified as candidates for quantum information processing, but none of them are immune from errors. The challenge remains to find a path from the experiments of today to a reliable and scalable quantum computer. Here, we develop an architecture based on a simple module comprising an optical cavity containing a single negatively charged nitrogen vacancy center in diamond. Modules are connected by photons propagating in a fiber-optical network and collectively used to generate a topological cluster state, a robust substrate for quantum information processing. In principle, all processes in the architecture can be deterministic, but current limitations lead to processes that are probabilistic but heralded. We find that the architecture enables large-scale quantum information processing with existing technology.

Safeguarding of large scale reprocessing and MOX plants

International Nuclear Information System (INIS)

Howsley, R.; Burrows, B.; Longevialle, H. de; Kuroi, H.; Izumi, A.

1997-01-01

In May 97, the IAEA Board of Governors approved the final measures of the ''93+2'' safeguards strengthening programme, thus improving the international non-proliferation regime by enhancing the effectiveness and efficiency of safeguards verification. These enhancements are not however, a revolution in current practices, but rather an important step in the continuous evolution of the safeguards system. The principles embodied in 93+2, for broader access to information and increased physical access already apply, in a pragmatic way, to large scale reprocessing and MOX fabrication plants. In these plants, qualitative measures and process monitoring play an important role in addition to accountancy and material balance evaluations in attaining the safeguard's goals. This paper will reflect on the safeguards approaches adopted for these large bulk handling facilities and draw analogies, conclusions and lessons for the forthcoming implementation of the 93+2 Programme. (author)

Forest landscape models, a tool for understanding the effect of the large-scale and long-term landscape processes

Science.gov (United States)

Hong S. He; Robert E. Keane; Louis R. Iverson

2008-01-01

Forest landscape models have become important tools for understanding large-scale and long-term landscape (spatial) processes such as climate change, fire, windthrow, seed dispersal, insect outbreak, disease propagation, forest harvest, and fuel treatment, because controlled field experiments designed to study the effects of these processes are often not possible (...

Consultancy on Large-Scale Submerged Aerobic Cultivation Process Design - Final Technical Report: February 1, 2016 -- June 30, 2016

Energy Technology Data Exchange (ETDEWEB)

Crater, Jason [Gemomatica, Inc., San Diego, CA (United States); Galleher, Connor [Gemomatica, Inc., San Diego, CA (United States); Lievense, Jeff [Gemomatica, Inc., San Diego, CA (United States)

2017-05-12

NREL is developing an advanced aerobic bubble column model using Aspen Custom Modeler (ACM). The objective of this work is to integrate the new fermentor model with existing techno-economic models in Aspen Plus and Excel to establish a new methodology for guiding process design. To assist this effort, NREL has contracted Genomatica to critique and make recommendations for improving NREL's bioreactor model and large scale aerobic bioreactor design for biologically producing lipids at commercial scale. Genomatica has highlighted a few areas for improving the functionality and effectiveness of the model. Genomatica recommends using a compartment model approach with an integrated black-box kinetic model of the production microbe. We also suggest including calculations for stirred tank reactors to extend the models functionality and adaptability for future process designs. Genomatica also suggests making several modifications to NREL's large-scale lipid production process design. The recommended process modifications are based on Genomatica's internal techno-economic assessment experience and are focused primarily on minimizing capital and operating costs. These recommendations include selecting/engineering a thermotolerant yeast strain with lipid excretion; using bubble column fermentors; increasing the size of production fermentors; reducing the number of vessels; employing semi-continuous operation; and recycling cell mass.

Curbing variations in packaging process through Six Sigma way in a large-scale food-processing industry

Science.gov (United States)

Desai, Darshak A.; Kotadiya, Parth; Makwana, Nikheel; Patel, Sonalinkumar

2015-03-01

Indian industries need overall operational excellence for sustainable profitability and growth in the present age of global competitiveness. Among different quality and productivity improvement techniques, Six Sigma has emerged as one of the most effective breakthrough improvement strategies. Though Indian industries are exploring this improvement methodology to their advantage and reaping the benefits, not much has been presented and published regarding experience of Six Sigma in the food-processing industries. This paper is an effort to exemplify the application of Six Sigma quality improvement drive to one of the large-scale food-processing sectors in India. The paper discusses the phase wiz implementation of define, measure, analyze, improve, and control (DMAIC) on one of the chronic problems, variations in the weight of milk powder pouch. The paper wraps up with the improvements achieved and projected bottom-line gain to the unit by application of Six Sigma methodology.

Design Methodology of Process Layout considering Various Equipment Types for Large scale Pyro processing Facility

International Nuclear Information System (INIS)

Yu, Seung Nam; Lee, Jong Kwang; Lee, Hyo Jik

2016-01-01

At present, each item of process equipment required for integrated processing is being examined, based on experience acquired during the Pyropocess Integrated Inactive Demonstration Facility (PRIDE) project, and considering the requirements and desired performance enhancement of KAPF as a new facility beyond PRIDE. Essentially, KAPF will be required to handle hazardous materials such as spent nuclear fuel, which must be processed in an isolated and shielded area separate from the operator location. Moreover, an inert-gas atmosphere must be maintained, because of the radiation and deliquescence of the materials. KAPF must also achieve the goal of significantly increased yearly production beyond that of the previous facility; therefore, several parts of the production line must be automated. This article presents the method considered for the conceptual design of both the production line and the overall layout of the KAPF process equipment. This study has proposed a design methodology that can be utilized as a preliminary step for the design of a hot-cell-type, large-scale facility, in which the various types of processing equipment operated by the remote handling system are integrated. The proposed methodology applies to part of the overall design procedure and contains various weaknesses. However, if the designer is required to maximize the efficiency of the installed material-handling system while considering operation restrictions and maintenance conditions, this kind of design process can accommodate the essential components that must be employed simultaneously in a general hot-cell system

Homogenization of Large-Scale Movement Models in Ecology

Science.gov (United States)

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

2011-01-01

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

Large-scale hydrogen production using nuclear reactors

Energy Technology Data Exchange (ETDEWEB)

Ryland, D.; Stolberg, L.; Kettner, A.; Gnanapragasam, N.; Suppiah, S. [Atomic Energy of Canada Limited, Chalk River, ON (Canada)

2014-07-01

For many years, Atomic Energy of Canada Limited (AECL) has been studying the feasibility of using nuclear reactors, such as the Supercritical Water-cooled Reactor, as an energy source for large scale hydrogen production processes such as High Temperature Steam Electrolysis and the Copper-Chlorine thermochemical cycle. Recent progress includes the augmentation of AECL's experimental capabilities by the construction of experimental systems to test high temperature steam electrolysis button cells at ambient pressure and temperatures up to 850{sup o}C and CuCl/HCl electrolysis cells at pressures up to 7 bar and temperatures up to 100{sup o}C. In parallel, detailed models of solid oxide electrolysis cells and the CuCl/HCl electrolysis cell are being refined and validated using experimental data. Process models are also under development to assess options for economic integration of these hydrogen production processes with nuclear reactors. Options for large-scale energy storage, including hydrogen storage, are also under study. (author)

Energy transfers in large-scale and small-scale dynamos

Science.gov (United States)

Samtaney, Ravi; Kumar, Rohit; Verma, Mahendra

2015-11-01

We present the energy transfers, mainly energy fluxes and shell-to-shell energy transfers in small-scale dynamo (SSD) and large-scale dynamo (LSD) using numerical simulations of MHD turbulence for Pm = 20 (SSD) and for Pm = 0.2 on 10243 grid. For SSD, we demonstrate that the magnetic energy growth is caused by nonlocal energy transfers from the large-scale or forcing-scale velocity field to small-scale magnetic field. The peak of these energy transfers move towards lower wavenumbers as dynamo evolves, which is the reason for the growth of the magnetic fields at the large scales. The energy transfers U2U (velocity to velocity) and B2B (magnetic to magnetic) are forward and local. For LSD, we show that the magnetic energy growth takes place via energy transfers from large-scale velocity field to large-scale magnetic field. We observe forward U2U and B2B energy flux, similar to SSD.

Internationalization Measures in Large Scale Research Projects

Science.gov (United States)

Soeding, Emanuel; Smith, Nancy

2017-04-01

Internationalization measures in Large Scale Research Projects Large scale research projects (LSRP) often serve as flagships used by universities or research institutions to demonstrate their performance and capability to stakeholders and other interested parties. As the global competition among universities for the recruitment of the brightest brains has increased, effective internationalization measures have become hot topics for universities and LSRP alike. Nevertheless, most projects and universities are challenged with little experience on how to conduct these measures and make internationalization an cost efficient and useful activity. Furthermore, those undertakings permanently have to be justified with the Project PIs as important, valuable tools to improve the capacity of the project and the research location. There are a variety of measures, suited to support universities in international recruitment. These include e.g. institutional partnerships, research marketing, a welcome culture, support for science mobility and an effective alumni strategy. These activities, although often conducted by different university entities, are interlocked and can be very powerful measures if interfaced in an effective way. On this poster we display a number of internationalization measures for various target groups, identify interfaces between project management, university administration, researchers and international partners to work together, exchange information and improve processes in order to be able to recruit, support and keep the brightest heads to your project.

Large-scale impact cratering on the terrestrial planets

International Nuclear Information System (INIS)

Grieve, R.A.F.

1982-01-01

The crater densities on the earth and moon form the basis for a standard flux-time curve that can be used in dating unsampled planetary surfaces and constraining the temporal history of endogenic geologic processes. Abundant evidence is seen not only that impact cratering was an important surface process in planetary history but also that large imapact events produced effects that were crucial in scale. By way of example, it is noted that the formation of multiring basins on the early moon was as important in defining the planetary tectonic framework as plate tectonics is on the earth. Evidence from several planets suggests that the effects of very-large-scale impacts go beyond the simple formation of an impact structure and serve to localize increased endogenic activity over an extended period of geologic time. Even though no longer occurring with the frequency and magnitude of early solar system history, it is noted that large scale impact events continue to affect the local geology of the planets. 92 references

State of the Art in Large-Scale Soil Moisture Monitoring

Science.gov (United States)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Massive Cloud Computing Processing of P-SBAS Time Series for Displacement Analyses at Large Spatial Scale

Science.gov (United States)

Casu, F.; de Luca, C.; Lanari, R.; Manunta, M.; Zinno, I.

2016-12-01

A methodology for computing surface deformation time series and mean velocity maps of large areas is presented. Our approach relies on the availability of a multi-temporal set of Synthetic Aperture Radar (SAR) data collected from ascending and descending orbits over an area of interest, and also permits to estimate the vertical and horizontal (East-West) displacement components of the Earth's surface. The adopted methodology is based on an advanced Cloud Computing implementation of the Differential SAR Interferometry (DInSAR) Parallel Small Baseline Subset (P-SBAS) processing chain which allows the unsupervised processing of large SAR data volumes, from the raw data (level-0) imagery up to the generation of DInSAR time series and maps. The presented solution, which is highly scalable, has been tested on the ascending and descending ENVISAT SAR archives, which have been acquired over a large area of Southern California (US) that extends for about 90.000 km2. Such an input dataset has been processed in parallel by exploiting 280 computing nodes of the Amazon Web Services Cloud environment. Moreover, to produce the final mean deformation velocity maps of the vertical and East-West displacement components of the whole investigated area, we took also advantage of the information available from external GPS measurements that permit to account for possible regional trends not easily detectable by DInSAR and to refer the P-SBAS measurements to an external geodetic datum. The presented results clearly demonstrate the effectiveness of the proposed approach that paves the way to the extensive use of the available ERS and ENVISAT SAR data archives. Furthermore, the proposed methodology can be particularly suitable to deal with the very huge data flow provided by the Sentinel-1 constellation, thus permitting to extend the DInSAR analyses at a nearly global scale. This work is partially supported by: the DPC-CNR agreement, the EPOS-IP project and the ESA GEP project.

Challenges for Large Scale Structure Theory

CERN Multimedia

CERN. Geneva

2018-01-01

I will describe some of the outstanding questions in Cosmology where answers could be provided by observations of the Large Scale Structure of the Universe at late times.I will discuss some of the theoretical challenges which will have to be overcome to extract this information from the observations. I will describe some of the theoretical tools that might be useful to achieve this goal. 

Large-Scale Optimization for Bayesian Inference in Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Willcox, Karen [MIT; Marzouk, Youssef [MIT

2013-11-12

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of the SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

Science.gov (United States)

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

Third generation participatory design in health informatics--making user participation applicable to large-scale information system projects.

Science.gov (United States)

Pilemalm, Sofie; Timpka, Toomas

2008-04-01

Participatory Design (PD) methods in the field of health informatics have mainly been applied to the development of small-scale systems with homogeneous user groups in local settings. Meanwhile, health service organizations are becoming increasingly large and complex in character, making it necessary to extend the scope of the systems that are used for managing data, information and knowledge. This study reports participatory action research on the development of a PD framework for large-scale system design. The research was conducted in a public health informatics project aimed at developing a system for 175,000 users. A renewed PD framework was developed in response to six major limitations experienced to be associated with the existing methods. The resulting framework preserves the theoretical grounding, but extends the toolbox to suit applications in networked health service organizations. Future research should involve evaluations of the framework in other health service settings where comprehensive HISs are developed.

The effects of large scale processing on caesium leaching from cemented simulant sodium nitrate waste

International Nuclear Information System (INIS)

Lee, D.J.; Brown, D.J.

1982-01-01

The effects of large scale processing on the properties of cemented simulant sodium nitrate waste have been investigated. Leach tests have been performed on full-size drums, cores and laboratory samples of cement formulations containing Ordinary Portland Cement (OPC), Sulphate Resisting Portland Cement (SRPC) and a blended cement (90% ground granulated blast furnace slag/10% OPC). In addition, development of the cement hydration exotherms with time and the temperature distribution in 220 dm 3 samples have been followed. (author)

Large-scale networks in engineering and life sciences

CERN Document Server

Findeisen, Rolf; Flockerzi, Dietrich; Reichl, Udo; Sundmacher, Kai

2014-01-01

This edited volume provides insights into and tools for the modeling, analysis, optimization, and control of large-scale networks in the life sciences and in engineering. Large-scale systems are often the result of networked interactions between a large number of subsystems, and their analysis and control are becoming increasingly important. The chapters of this book present the basic concepts and theoretical foundations of network theory and discuss its applications in different scientific areas such as biochemical reactions, chemical production processes, systems biology, electrical circuits, and mobile agents. The aim is to identify common concepts, to understand the underlying mathematical ideas, and to inspire discussions across the borders of the various disciplines.  The book originates from the interdisciplinary summer school “Large Scale Networks in Engineering and Life Sciences” hosted by the International Max Planck Research School Magdeburg, September 26-30, 2011, and will therefore be of int...

Preparing laboratory and real-world EEG data for large-scale analysis: A containerized approach

Directory of Open Access Journals (Sweden)

Nima eBigdely-Shamlo

2016-03-01

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

Modelling aggregation on the large scale and regularity on the small scale in spatial point pattern datasets

DEFF Research Database (Denmark)

Lavancier, Frédéric; Møller, Jesper

We consider a dependent thinning of a regular point process with the aim of obtaining aggregation on the large scale and regularity on the small scale in the resulting target point process of retained points. Various parametric models for the underlying processes are suggested and the properties...

Large-scale data analytics

CERN Document Server

Gkoulalas-Divanis, Aris

2014-01-01

Provides cutting-edge research in large-scale data analytics from diverse scientific areas Surveys varied subject areas and reports on individual results of research in the field Shares many tips and insights into large-scale data analytics from authors and editors with long-term experience and specialization in the field

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

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.

Rank Order Coding: a Retinal Information Decoding Strategy Revealed by Large-Scale Multielectrode Array Retinal Recordings.

Science.gov (United States)

Portelli, Geoffrey; Barrett, John M; Hilgen, Gerrit; Masquelier, Timothée; Maccione, Alessandro; Di Marco, Stefano; Berdondini, Luca; Kornprobst, Pierre; Sernagor, Evelyne

2016-01-01

How a population of retinal ganglion cells (RGCs) encodes the visual scene remains an open question. Going beyond individual RGC coding strategies, results in salamander suggest that the relative latencies of a RGC pair encode spatial information. Thus, a population code based on this concerted spiking could be a powerful mechanism to transmit visual information rapidly and efficiently. Here, we tested this hypothesis in mouse by recording simultaneous light-evoked responses from hundreds of RGCs, at pan-retinal level, using a new generation of large-scale, high-density multielectrode array consisting of 4096 electrodes. Interestingly, we did not find any RGCs exhibiting a clear latency tuning to the stimuli, suggesting that in mouse, individual RGC pairs may not provide sufficient information. We show that a significant amount of information is encoded synergistically in the concerted spiking of large RGC populations. Thus, the RGC population response described with relative activities, or ranks, provides more relevant information than classical independent spike count- or latency- based codes. In particular, we report for the first time that when considering the relative activities across the whole population, the wave of first stimulus-evoked spikes is an accurate indicator of stimulus content. We show that this coding strategy coexists with classical neural codes, and that it is more efficient and faster. Overall, these novel observations suggest that already at the level of the retina, concerted spiking provides a reliable and fast strategy to rapidly transmit new visual scenes.

The impact of new forms of large-scale general practice provider collaborations on England's NHS: a systematic review.

Science.gov (United States)

Pettigrew, Luisa M; Kumpunen, Stephanie; Mays, Nicholas; Rosen, Rebecca; Posaner, Rachel

2018-03-01

Over the past decade, collaboration between general practices in England to form new provider networks and large-scale organisations has been driven largely by grassroots action among GPs. However, it is now being increasingly advocated for by national policymakers. Expectations of what scaling up general practice in England will achieve are significant. To review the evidence of the impact of new forms of large-scale general practice provider collaborations in England. Systematic review. Embase, MEDLINE, Health Management Information Consortium, and Social Sciences Citation Index were searched for studies reporting the impact on clinical processes and outcomes, patient experience, workforce satisfaction, or costs of new forms of provider collaborations between general practices in England. A total of 1782 publications were screened. Five studies met the inclusion criteria and four examined the same general practice networks, limiting generalisability. Substantial financial investment was required to establish the networks and the associated interventions that were targeted at four clinical areas. Quality improvements were achieved through standardised processes, incentives at network level, information technology-enabled performance dashboards, and local network management. The fifth study of a large-scale multisite general practice organisation showed that it may be better placed to implement safety and quality processes than conventional practices. However, unintended consequences may arise, such as perceptions of disenfranchisement among staff and reductions in continuity of care. Good-quality evidence of the impacts of scaling up general practice provider organisations in England is scarce. As more general practice collaborations emerge, evaluation of their impacts will be important to understand which work, in which settings, how, and why. © British Journal of General Practice 2018.

Prototype Vector Machine for Large Scale Semi-Supervised Learning

Energy Technology Data Exchange (ETDEWEB)

Zhang, Kai; Kwok, James T.; Parvin, Bahram

2009-04-29

Practicaldataminingrarelyfalls exactlyinto the supervisedlearning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised learning (SSL). We note that the computationalintensivenessofgraph-based SSLarises largely from the manifold or graph regularization, which in turn lead to large models that are dificult to handle. To alleviate this, we proposed the prototype vector machine (PVM), a highlyscalable,graph-based algorithm for large-scale SSL. Our key innovation is the use of"prototypes vectors" for effcient approximation on both the graph-based regularizer and model representation. The choice of prototypes are grounded upon two important criteria: they not only perform effective low-rank approximation of the kernel matrix, but also span a model suffering the minimum information loss compared with the complete model. We demonstrate encouraging performance and appealing scaling properties of the PVM on a number of machine learning benchmark data sets.

Large-scale grid management

International Nuclear Information System (INIS)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-01-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series

Large-scale experiments for the vulnerability analysis of buildings impacted and intruded by fluviatile torrential hazard processes

Science.gov (United States)

Sturm, Michael; Gems, Bernhard; Fuchs, Sven; Mazzorana, Bruno; Papathoma-Köhle, Maria; Aufleger, Markus

2016-04-01

In European mountain regions, losses due to torrential hazards are still considerable high despite the ongoing debate on an overall increasing or decreasing trend. Recent events in Austria severely revealed that due to technical and economic reasons, an overall protection of settlements in the alpine environment against torrential hazards is not feasible. On the side of the hazard process, events with unpredictable intensities may represent overload scenarios for existent protection structures in the torrent catchments. They bear a particular risk of significant losses in the living space. Although the importance of vulnerability is widely recognised, there is still a research gap concerning its assessment. Currently, potential losses at buildings due to torrential hazards and their comparison with reinstatement costs are determined by the use of empirical functions. Hence, relations of process intensities and the extent of losses, gathered by the analysis of historic hazard events and the information of object-specific restoration values, are used. This approach does not represent a physics-based and integral concept since relevant and often crucial processes, as the intrusion of the fluid-sediment-mixture into elements at risk, are not considered. Based on these findings, our work is targeted at extending these findings and models of present risk research in the context of an integral, more physics-based vulnerability analysis concept. Fluviatile torrential hazard processes and their impacts on the building envelope are experimentally modelled. Material intrusion processes are thereby explicitly considered. Dynamic impacts are gathered quantitatively and spatially distributed by the use of a large set of force transducers. The experimental tests are accomplished with artificial, vertical and skewed plates, including also openings for material intrusion. Further, the impacts on specific buildings within the test site of the work, the fan apex of the Schnannerbach

Analysis using large-scale ringing data

Directory of Open Access Journals (Sweden)

Baillie, S. R.

2004-06-01

Full Text Available Birds are highly mobile organisms and there is increasing evidence that studies at large spatial scales are needed if we are to properly understand their population dynamics. While classical metapopulation models have rarely proved useful for birds, more general metapopulation ideas involving collections of populations interacting within spatially structured landscapes are highly relevant (Harrison, 1994. There is increasing interest in understanding patterns of synchrony, or lack of synchrony, between populations and the environmental and dispersal mechanisms that bring about these patterns (Paradis et al., 2000. To investigate these processes we need to measure abundance, demographic rates and dispersal at large spatial scales, in addition to gathering data on relevant environmental variables. There is an increasing realisation that conservation needs to address rapid declines of common and widespread species (they will not remain so if such trends continue as well as the management of small populations that are at risk of extinction. While the knowledge needed to support the management of small populations can often be obtained from intensive studies in a few restricted areas, conservation of widespread species often requires information on population trends and processes measured at regional, national and continental scales (Baillie, 2001. While management prescriptions for widespread populations may initially be developed from a small number of local studies or experiments, there is an increasing need to understand how such results will scale up when applied across wider areas. There is also a vital role for monitoring at large spatial scales both in identifying such population declines and in assessing population recovery. Gathering data on avian abundance and demography at large spatial scales usually relies on the efforts of large numbers of skilled volunteers. Volunteer studies based on ringing (for example Constant Effort Sites [CES

On the use of Cloud Computing and Machine Learning for Large-Scale SAR Science Data Processing and Quality Assessment Analysi

Science.gov (United States)

Hua, H.

2016-12-01

Geodetic imaging is revolutionizing geophysics, but the scope of discovery has been limited by labor-intensive technological implementation of the analyses. The Advanced Rapid Imaging and Analysis (ARIA) project has proven capability to automate SAR data processing and analysis. Existing and upcoming SAR missions such as Sentinel-1A/B and NISAR are also expected to generate massive amounts of SAR data. This has brought to the forefront the need for analytical tools for SAR quality assessment (QA) on the large volumes of SAR data-a critical step before higher-level time series and velocity products can be reliably generated. Initially leveraging an advanced hybrid-cloud computing science data system for performing large-scale processing, machine learning approaches were augmented for automated analysis of various quality metrics. Machine learning-based user-training of features, cross-validation, prediction models were integrated into our cloud-based science data processing flow to enable large-scale and high-throughput QA analytics for enabling improvements to the production quality of geodetic data products.

Ethics of large-scale change

OpenAIRE

Arler, Finn

2006-01-01

  The subject of this paper is long-term large-scale changes in human society. Some very significant examples of large-scale change are presented: human population growth, human appropriation of land and primary production, the human use of fossil fuels, and climate change. The question is posed, which kind of attitude is appropriate when dealing with large-scale changes like these from an ethical point of view. Three kinds of approaches are discussed: Aldo Leopold's mountain thinking, th...

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

Science.gov (United States)

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.

Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems

CERN Document Server

Kołodziej, Joanna

2012-01-01

One of the most challenging issues in modelling today's large-scale computational systems is to effectively manage highly parametrised distributed environments such as computational grids, clouds, ad hoc networks and P2P networks. Next-generation computational grids must provide a wide range of services and high performance computing infrastructures. Various types of information and data processed in the large-scale dynamic grid environment may be incomplete, imprecise, and fragmented, which complicates the specification of proper evaluation criteria and which affects both the availability of resources and the final collective decisions of users. The complexity of grid architectures and grid management may also contribute towards higher energy consumption. All of these issues necessitate the development of intelligent resource management techniques, which are capable of capturing all of this complexity and optimising meaningful metrics for a wide range of grid applications.   This book covers hot topics in t...

Presenting an Approach for Conducting Knowledge Architecture within Large-Scale Organizations.

Science.gov (United States)

Varaee, Touraj; Habibi, Jafar; Mohaghar, Ali

2015-01-01

Knowledge architecture (KA) establishes the basic groundwork for the successful implementation of a short-term or long-term knowledge management (KM) program. An example of KA is the design of a prototype before a new vehicle is manufactured. Due to a transformation to large-scale organizations, the traditional architecture of organizations is undergoing fundamental changes. This paper explores the main strengths and weaknesses in the field of KA within large-scale organizations and provides a suitable methodology and supervising framework to overcome specific limitations. This objective was achieved by applying and updating the concepts from the Zachman information architectural framework and the information architectural methodology of enterprise architecture planning (EAP). The proposed solution may be beneficial for architects in knowledge-related areas to successfully accomplish KM within large-scale organizations. The research method is descriptive; its validity is confirmed by performing a case study and polling the opinions of KA experts.

Image-based Exploration of Large-Scale Pathline Fields

KAUST Repository

Nagoor, Omniah H.

2014-05-27

While real-time applications are nowadays routinely used in visualizing large nu- merical simulations and volumes, handling these large-scale datasets requires high-end graphics clusters or supercomputers to process and visualize them. However, not all users have access to powerful clusters. Therefore, it is challenging to come up with a visualization approach that provides insight to large-scale datasets on a single com- puter. Explorable images (EI) is one of the methods that allows users to handle large data on a single workstation. Although it is a view-dependent method, it combines both exploration and modification of visual aspects without re-accessing the original huge data. In this thesis, we propose a novel image-based method that applies the concept of EI in visualizing large flow-field pathlines data. The goal of our work is to provide an optimized image-based method, which scales well with the dataset size. Our approach is based on constructing a per-pixel linked list data structure in which each pixel contains a list of pathlines segments. With this view-dependent method it is possible to filter, color-code and explore large-scale flow data in real-time. In addition, optimization techniques such as early-ray termination and deferred shading are applied, which further improves the performance and scalability of our approach.

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

Science.gov (United States)

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.

Multi-format all-optical processing based on a large-scale, hybridly integrated photonic circuit.

Science.gov (United States)

Bougioukos, M; Kouloumentas, Ch; Spyropoulou, M; Giannoulis, G; Kalavrouziotis, D; Maziotis, A; Bakopoulos, P; Harmon, R; Rogers, D; Harrison, J; Poustie, A; Maxwell, G; Avramopoulos, H

2011-06-06

We investigate through numerical studies and experiments the performance of a large scale, silica-on-silicon photonic integrated circuit for multi-format regeneration and wavelength-conversion. The circuit encompasses a monolithically integrated array of four SOAs inside two parallel Mach-Zehnder structures, four delay interferometers and a large number of silica waveguides and couplers. Exploiting phase-incoherent techniques, the circuit is capable of processing OOK signals at variable bit rates, DPSK signals at 22 or 44 Gb/s and DQPSK signals at 44 Gbaud. Simulation studies reveal the wavelength-conversion potential of the circuit with enhanced regenerative capabilities for OOK and DPSK modulation formats and acceptable quality degradation for DQPSK format. Regeneration of 22 Gb/s OOK signals with amplified spontaneous emission (ASE) noise and DPSK data signals degraded with amplitude, phase and ASE noise is experimentally validated demonstrating a power penalty improvement up to 1.5 dB.

Information Management for a Large Multidisciplinary Project

Science.gov (United States)

Jones, Kennie H.; Randall, Donald P.; Cronin, Catherine K.

1992-01-01

In 1989, NASA's Langley Research Center (LaRC) initiated the High-Speed Airframe Integration Research (HiSAIR) Program to develop and demonstrate an integrated environment for high-speed aircraft design using advanced multidisciplinary analysis and optimization procedures. The major goals of this program were to evolve the interactions among disciplines and promote sharing of information, to provide a timely exchange of information among aeronautical disciplines, and to increase the awareness of the effects each discipline has upon other disciplines. LaRC historically has emphasized the advancement of analysis techniques. HiSAIR was founded to synthesize these advanced methods into a multidisciplinary design process emphasizing information feedback among disciplines and optimization. Crucial to the development of such an environment are the definition of the required data exchanges and the methodology for both recording the information and providing the exchanges in a timely manner. These requirements demand extensive use of data management techniques, graphic visualization, and interactive computing. HiSAIR represents the first attempt at LaRC to promote interdisciplinary information exchange on a large scale using advanced data management methodologies combined with state-of-the-art, scientific visualization techniques on graphics workstations in a distributed computing environment. The subject of this paper is the development of the data management system for HiSAIR.

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

Science.gov (United States)

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

2017-10-01

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

An improved method to characterise the modulation of small-scale turbulent by large-scale structures

Science.gov (United States)

Agostini, Lionel; Leschziner, Michael; Gaitonde, Datta

2015-11-01

A key aspect of turbulent boundary layer dynamics is ``modulation,'' which refers to degree to which the intensity of coherent large-scale structures (LS) cause an amplification or attenuation of the intensity of the small-scale structures (SS) through large-scale-linkage. In order to identify the variation of the amplitude of the SS motion, the envelope of the fluctuations needs to be determined. Mathis et al. (2009) proposed to define this latter by low-pass filtering the modulus of the analytic signal built from the Hilbert transform of SS. The validity of this definition, as a basis for quantifying the modulated SS signal, is re-examined on the basis of DNS data for a channel flow. The analysis shows that the modulus of the analytic signal is very sensitive to the skewness of its PDF, which is dependent, in turn, on the sign of the LS fluctuation and thus of whether these fluctuations are associated with sweeps or ejections. The conclusion is that generating an envelope by use of a low-pass filtering step leads to an important loss of information associated with the effects of the local skewness of the PDF of the SS on the modulation process. An improved Hilbert-transform-based method is proposed to characterize the modulation of SS turbulence by LS structures

Efficient algorithms for collaborative decision making for large scale settings

DEFF Research Database (Denmark)

Assent, Ira

2011-01-01

to bring about more effective and more efficient retrieval systems that support the users' decision making process. We sketch promising research directions for more efficient algorithms for collaborative decision making, especially for large scale systems.......Collaborative decision making is a successful approach in settings where data analysis and querying can be done interactively. In large scale systems with huge data volumes or many users, collaboration is often hindered by impractical runtimes. Existing work on improving collaboration focuses...... on avoiding redundancy for users working on the same task. While this improves the effectiveness of the user work process, the underlying query processing engine is typically considered a "black box" and left unchanged. Research in multiple query processing, on the other hand, ignores the application...

A Process Mining Based Service Composition Approach for Mobile Information Systems

Directory of Open Access Journals (Sweden)

Chengxi Huang

2017-01-01

Full Text Available Due to the growing trend in applying big data and cloud computing technologies in information systems, it is becoming an important issue to handle the connection between large scale of data and the associated business processes in the Internet of Everything (IoE environment. Service composition as a widely used phase in system development has some limits when the complexity of relationship among data increases. Considering the expanding scale and the variety of devices in mobile information systems, a process mining based service composition approach is proposed in this paper in order to improve the adaptiveness and efficiency of compositions. Firstly, a preprocessing is conducted to extract existing service execution information from server-side logs. Then process mining algorithms are applied to discover the overall event sequence with preprocessed data. After that, a scene-based service composition is applied to aggregate scene information and relocate services of the system. Finally, a case study that applied the work in mobile medical application proves that the approach is practical and valuable in improving service composition adaptiveness and efficiency.

Integrating weather and geotechnical monitoring data for assessing the stability of large scale surface mining operations

Directory of Open Access Journals (Sweden)

Steiakakis Chrysanthos

2016-01-01

Full Text Available The geotechnical challenges for safe slope design in large scale surface mining operations are enormous. Sometimes one degree of slope inclination can significantly reduce the overburden to ore ratio and therefore dramatically improve the economics of the operation, while large scale slope failures may have a significant impact on human lives. Furthermore, adverse weather conditions, such as high precipitation rates, may unfavorably affect the already delicate balance between operations and safety. Geotechnical, weather and production parameters should be systematically monitored and evaluated in order to safely operate such pits. Appropriate data management, processing and storage are critical to ensure timely and informed decisions.

Parallelizing Gene Expression Programming Algorithm in Enabling Large-Scale Classification

Directory of Open Access Journals (Sweden)

Lixiong Xu

2017-01-01

Full Text Available As one of the most effective function mining algorithms, Gene Expression Programming (GEP algorithm has been widely used in classification, pattern recognition, prediction, and other research fields. Based on the self-evolution, GEP is able to mine an optimal function for dealing with further complicated tasks. However, in big data researches, GEP encounters low efficiency issue due to its long time mining processes. To improve the efficiency of GEP in big data researches especially for processing large-scale classification tasks, this paper presents a parallelized GEP algorithm using MapReduce computing model. The experimental results show that the presented algorithm is scalable and efficient for processing large-scale classification tasks.

Large-scale hydrology in Europe : observed patterns and model performance

Energy Technology Data Exchange (ETDEWEB)

Gudmundsson, Lukas

2011-06-15

In a changing climate, terrestrial water storages are of great interest as water availability impacts key aspects of ecosystem functioning. Thus, a better understanding of the variations of wet and dry periods will contribute to fully grasp processes of the earth system such as nutrient cycling and vegetation dynamics. Currently, river runoff from small, nearly natural, catchments is one of the few variables of the terrestrial water balance that is regularly monitored with detailed spatial and temporal coverage on large scales. River runoff, therefore, provides a foundation to approach European hydrology with respect to observed patterns on large scales, with regard to the ability of models to capture these.The analysis of observed river flow from small catchments, focused on the identification and description of spatial patterns of simultaneous temporal variations of runoff. These are dominated by large-scale variations of climatic variables but also altered by catchment processes. It was shown that time series of annual low, mean and high flows follow the same atmospheric drivers. The observation that high flows are more closely coupled to large scale atmospheric drivers than low flows, indicates the increasing influence of catchment properties on runoff under dry conditions. Further, it was shown that the low-frequency variability of European runoff is dominated by two opposing centres of simultaneous variations, such that dry years in the north are accompanied by wet years in the south.Large-scale hydrological models are simplified representations of our current perception of the terrestrial water balance on large scales. Quantification of the models strengths and weaknesses is the prerequisite for a reliable interpretation of simulation results. Model evaluations may also enable to detect shortcomings with model assumptions and thus enable a refinement of the current perception of hydrological systems. The ability of a multi model ensemble of nine large-scale

New Visions for Large Scale Networks: Research and Applications

Data.gov (United States)

Networking and Information Technology Research and Development, Executive Office of the President — This paper documents the findings of the March 12-14, 2001 Workshop on New Visions for Large-Scale Networks: Research and Applications. The workshops objectives were...

Presenting an Approach for Conducting Knowledge Architecture within Large-Scale Organizations

Science.gov (United States)

Varaee, Touraj; Habibi, Jafar; Mohaghar, Ali

2015-01-01

Knowledge architecture (KA) establishes the basic groundwork for the successful implementation of a short-term or long-term knowledge management (KM) program. An example of KA is the design of a prototype before a new vehicle is manufactured. Due to a transformation to large-scale organizations, the traditional architecture of organizations is undergoing fundamental changes. This paper explores the main strengths and weaknesses in the field of KA within large-scale organizations and provides a suitable methodology and supervising framework to overcome specific limitations. This objective was achieved by applying and updating the concepts from the Zachman information architectural framework and the information architectural methodology of enterprise architecture planning (EAP). The proposed solution may be beneficial for architects in knowledge-related areas to successfully accomplish KM within large-scale organizations. The research method is descriptive; its validity is confirmed by performing a case study and polling the opinions of KA experts. PMID:25993414

VESPA: Very large-scale Evolutionary and Selective Pressure Analyses

Directory of Open Access Journals (Sweden)

Andrew E. Webb

2017-06-01

Full Text Available Background Large-scale molecular evolutionary analyses of protein coding sequences requires a number of preparatory inter-related steps from finding gene families, to generating alignments and phylogenetic trees and assessing selective pressure variation. Each phase of these analyses can represent significant challenges, particularly when working with entire proteomes (all protein coding sequences in a genome from a large number of species. Methods We present VESPA, software capable of automating a selective pressure analysis using codeML in addition to the preparatory analyses and summary statistics. VESPA is written in python and Perl and is designed to run within a UNIX environment. Results We have benchmarked VESPA and our results show that the method is consistent, performs well on both large scale and smaller scale datasets, and produces results in line with previously published datasets. Discussion Large-scale gene family identification, sequence alignment, and phylogeny reconstruction are all important aspects of large-scale molecular evolutionary analyses. VESPA provides flexible software for simplifying these processes along with downstream selective pressure variation analyses. The software automatically interprets results from codeML and produces simplified summary files to assist the user in better understanding the results. VESPA may be found at the following website: http://www.mol-evol.org/VESPA.

The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data.

Science.gov (United States)

Stucky, Brian J; Guralnick, Rob; Deck, John; Denny, Ellen G; Bolmgren, Kjell; Walls, Ramona

2018-01-01

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

Recent Advances in Understanding Large Scale Vapour Explosions

International Nuclear Information System (INIS)

Board, S.J.; Hall, R.W.

1976-01-01

description of efficient large scale explosions it will be necessary to consider three stages: a) the setting up of a quasi-stable initial configuration; b) the triggering of this configuration; c) the propagation of the explosion. In this paper we consider each stage in turn, reviewing the relevant experimental information and theory to see to what extent the requirements for energetic explosions, and the physical processes that can satisfy these requirements, are understood. We pay particular attention to an attractively simple criterion for explosiveness, suggested by Fauske, that the contact temperature should exceed the temperature for spontaneous nucleation of the coolant, because on this criterion, sodium and UO 2 in particular are not explosive

Reducing Plug and Process Loads for a Large Scale, Low Energy Office Building: NREL's Research Support Facility; Preprint

Energy Technology Data Exchange (ETDEWEB)

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

2011-02-01

This paper documents the design and operational plug and process load energy efficiency measures needed to allow a large scale office building to reach ultra high efficiency building goals. The appendices of this document contain a wealth of documentation pertaining to plug and process load design in the RSF, including a list of equipment was selected for use.

Political consultation and large-scale research

International Nuclear Information System (INIS)

Bechmann, G.; Folkers, H.

1977-01-01

Large-scale research and policy consulting have an intermediary position between sociological sub-systems. While large-scale research coordinates science, policy, and production, policy consulting coordinates science, policy and political spheres. In this very position, large-scale research and policy consulting lack of institutional guarantees and rational back-ground guarantee which are characteristic for their sociological environment. This large-scale research can neither deal with the production of innovative goods under consideration of rentability, nor can it hope for full recognition by the basis-oriented scientific community. Policy consulting knows neither the competence assignment of the political system to make decisions nor can it judge succesfully by the critical standards of the established social science, at least as far as the present situation is concerned. This intermediary position of large-scale research and policy consulting has, in three points, a consequence supporting the thesis which states that this is a new form of institutionalization of science: These are: 1) external control, 2) the organization form, 3) the theoretical conception of large-scale research and policy consulting. (orig.) [de

Validation of the process control system of an automated large scale manufacturing plant.

Science.gov (United States)

Neuhaus, H; Kremers, H; Karrer, T; Traut, R H

1998-02-01

The validation procedure for the process control system of a plant for the large scale production of human albumin from plasma fractions is described. A validation master plan is developed, defining the system and elements to be validated, the interfaces with other systems with the validation limits, a general validation concept and supporting documentation. Based on this master plan, the validation protocols are developed. For the validation, the system is subdivided into a field level, which is the equipment part, and an automation level. The automation level is further subdivided into sections according to the different software modules. Based on a risk categorization of the modules, the qualification activities are defined. The test scripts for the different qualification levels (installation, operational and performance qualification) are developed according to a previously performed risk analysis.

Large-Scale Transit Signal Priority Implementation

OpenAIRE

Lee, Kevin S.; Lozner, Bailey

2018-01-01

In 2016, the District Department of Transportation (DDOT) deployed Transit Signal Priority (TSP) at 195 intersections in highly urbanized areas of Washington, DC. In collaboration with a broader regional implementation, and in partnership with the Washington Metropolitan Area Transit Authority (WMATA), DDOT set out to apply a systems engineering–driven process to identify, design, test, and accept a large-scale TSP system. This presentation will highlight project successes and lessons learned.

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

Science.gov (United States)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach

Large-scale multimedia modeling applications

International Nuclear Information System (INIS)

Droppo, J.G. Jr.; Buck, J.W.; Whelan, G.; Strenge, D.L.; Castleton, K.J.; Gelston, G.M.

1995-08-01

Over the past decade, the US Department of Energy (DOE) and other agencies have faced increasing scrutiny for a wide range of environmental issues related to past and current practices. A number of large-scale applications have been undertaken that required analysis of large numbers of potential environmental issues over a wide range of environmental conditions and contaminants. Several of these applications, referred to here as large-scale applications, have addressed long-term public health risks using a holistic approach for assessing impacts from potential waterborne and airborne transport pathways. Multimedia models such as the Multimedia Environmental Pollutant Assessment System (MEPAS) were designed for use in such applications. MEPAS integrates radioactive and hazardous contaminants impact computations for major exposure routes via air, surface water, ground water, and overland flow transport. A number of large-scale applications of MEPAS have been conducted to assess various endpoints for environmental and human health impacts. These applications are described in terms of lessons learned in the development of an effective approach for large-scale applications

Inverse problem to constrain the controlling parameters of large-scale heat transport processes: The Tiberias Basin example

Science.gov (United States)

Goretzki, Nora; Inbar, Nimrod; Siebert, Christian; Möller, Peter; Rosenthal, Eliyahu; Schneider, Michael; Magri, Fabien

2015-04-01

Salty and thermal springs exist along the lakeshore of the Sea of Galilee, which covers most of the Tiberias Basin (TB) in the northern Jordan- Dead Sea Transform, Israel/Jordan. As it is the only freshwater reservoir of the entire area, it is important to study the salinisation processes that pollute the lake. Simulations of thermohaline flow along a 35 km NW-SE profile show that meteoric and relic brines are flushed by the regional flow from the surrounding heights and thermally induced groundwater flow within the faults (Magri et al., 2015). Several model runs with trial and error were necessary to calibrate the hydraulic conductivity of both faults and major aquifers in order to fit temperature logs and spring salinity. It turned out that the hydraulic conductivity of the faults ranges between 30 and 140 m/yr whereas the hydraulic conductivity of the Upper Cenomanian aquifer is as high as 200 m/yr. However, large-scale transport processes are also dependent on other physical parameters such as thermal conductivity, porosity and fluid thermal expansion coefficient, which are hardly known. Here, inverse problems (IP) are solved along the NW-SE profile to better constrain the physical parameters (a) hydraulic conductivity, (b) thermal conductivity and (c) thermal expansion coefficient. The PEST code (Doherty, 2010) is applied via the graphical interface FePEST in FEFLOW (Diersch, 2014). The results show that both thermal and hydraulic conductivity are consistent with the values determined with the trial and error calibrations. Besides being an automatic approach that speeds up the calibration process, the IP allows to cover a wide range of parameter values, providing additional solutions not found with the trial and error method. Our study shows that geothermal systems like TB are more comprehensively understood when inverse models are applied to constrain coupled fluid flow processes over large spatial scales. References Diersch, H.-J.G., 2014. FEFLOW Finite

Innovation Processes in Large-Scale Public Foodservice-Case Findings from the Implementation of Organic Foods in a Danish County

DEFF Research Database (Denmark)

Mikkelsen, Bent Egberg; Nielsen, Thorkild; Kristensen, Niels Heine

2005-01-01

was carried out of the change process related implementation of organic foods in large-scale foodservice facilities in Greater Copenhagen county in order to study the effects of such a change. Based on the findings, a set of guidelines has been developed for the successful implementation of organic foods...

Importance of regional species pools and functional traits in colonization processes: predicting re-colonization after large-scale destruction of ecosystems

NARCIS (Netherlands)

Kirmer, A.; Tischew, S.; Ozinga, W.A.; Lampe, von M.; Baasch, A.; Groenendael, van J.M.

2008-01-01

Large-scale destruction of ecosystems caused by surface mining provides an opportunity for the study of colonization processes starting with primary succession. Surprisingly, over several decades and without any restoration measures, most of these sites spontaneously developed into valuable biotope

Formation and fate of marine snow: small-scale processes with large- scale implications

Directory of Open Access Journals (Sweden)

Thomas Kiørboe

2001-12-01

Full Text Available Marine snow aggregates are believed to be the main vehicles for vertical material transport in the ocean. However, aggregates are also sites of elevated heterotrophic activity, which may rather cause enhanced retention of aggregated material in the upper ocean. Small-scale biological-physical interactions govern the formation and fate of marine snow. Aggregates may form by physical coagulation: fluid motion causes collisions between small primary particles (e.g. phytoplankton that may then stick together to form aggregates with enhanced sinking velocities. Bacteria may subsequently solubilise and remineralise aggregated particles. Because the solubilization rate exceeds the remineralization rate, organic solutes leak out of sinking aggregates. The leaking solutes spread by diffusion and advection and form a chemical trail in the wake of the sinking aggregate that may guide small zooplankters to the aggregate. Also, suspended bacteria may enjoy the elevated concentration of organic solutes in the plume. I explore these small-scale formation and degradation processes by means of models, experiments and field observations. The larger scale implications for the structure and functioning of pelagic food chains of export vs. retention of material will be discussed.

Upscaling of Large-Scale Transport in Spatially Heterogeneous Porous Media Using Wavelet Transformation

Science.gov (United States)

Moslehi, M.; de Barros, F.; Ebrahimi, F.; Sahimi, M.

2015-12-01

Modeling flow and solute transport in large-scale heterogeneous porous media involves substantial computational burdens. A common approach to alleviate this complexity is to utilize upscaling methods. These processes generate upscaled models with less complexity while attempting to preserve the hydrogeological properties comparable to the original fine-scale model. We use Wavelet Transformations (WT) of the spatial distribution of aquifer's property to upscale the hydrogeological models and consequently transport processes. In particular, we apply the technique to a porous formation with broadly distributed and correlated transmissivity to verify the performance of the WT. First, transmissivity fields are coarsened using WT in such a way that the high transmissivity zones, in which more important information is embedded, mostly remain the same, while the low transmissivity zones are averaged out since they contain less information about the hydrogeological formation. Next, flow and non-reactive transport are simulated in both fine-scale and upscaled models to predict both the concentration breakthrough curves at a control location and the large-scale spreading of the plume around its centroid. The results reveal that the WT of the fields generates non-uniform grids with an average of 2.1% of the number of grid blocks in the original fine-scale models, which eventually leads to a significant reduction in the computational costs. We show that the upscaled model obtained through the WT reconstructs the concentration breakthrough curves and the spreading of the plume at different times accurately. Furthermore, the impacts of the Hurst coefficient, size of the flow domain and the orders of magnitude difference in transmissivity values on the results have been investigated. It is observed that as the heterogeneity and the size of the domain increase, better agreement between the results of fine-scale and upscaled models can be achieved. Having this framework at hand aids

Report of the Workshop on Petascale Systems Integration for LargeScale Facilities

Energy Technology Data Exchange (ETDEWEB)

Kramer, William T.C.; Walter, Howard; New, Gary; Engle, Tom; Pennington, Rob; Comes, Brad; Bland, Buddy; Tomlison, Bob; Kasdorf, Jim; Skinner, David; Regimbal, Kevin

2007-10-01

There are significant issues regarding Large Scale System integration that are not being addressed in other forums such as current research portfolios or vendor user groups. Unfortunately, the issues in the area of large-scale system integration often fall into a netherworld; not research, not facilities, not procurement, not operations, not user services. Taken together, these issues along with the impact of sub-optimal integration technology means the time required to deploy, integrate and stabilize large scale system may consume up to 20 percent of the useful life of such systems. Improving the state of the art for large scale systems integration has potential to increase the scientific productivity of these systems. Sites have significant expertise, but there are no easy ways to leverage this expertise among them . Many issues inhibit the sharing of information, including available time and effort, as well as issues with sharing proprietary information. Vendors also benefit in the long run from the solutions to issues detected during site testing and integration. There is a great deal of enthusiasm for making large scale system integration a full-fledged partner along with the other major thrusts supported by funding agencies in the definition, design, and use of a petascale systems. Integration technology and issues should have a full 'seat at the table' as petascale and exascale initiatives and programs are planned. The workshop attendees identified a wide range of issues and suggested paths forward. Pursuing these with funding opportunities and innovation offers the opportunity to dramatically improve the state of large scale system integration.

Direction of information flow in large-scale resting-state networks is frequency-dependent

NARCIS (Netherlands)

Hillebrand, Arjan; Tewarie, Prejaas; Van Dellen, Edwin; Yu, Meichen; Carbo, Ellen W S; Douw, Linda; Gouw, Alida A.; Van Straaten, Elisabeth C W; Stam, Cornelis J.

2016-01-01

Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these

Large-scale self-assembled zirconium phosphate smectic layers via a simple spray-coating process

Science.gov (United States)

Wong, Minhao; Ishige, Ryohei; White, Kevin L.; Li, Peng; Kim, Daehak; Krishnamoorti, Ramanan; Gunther, Robert; Higuchi, Takeshi; Jinnai, Hiroshi; Takahara, Atsushi; Nishimura, Riichi; Sue, Hung-Jue

2014-04-01

The large-scale assembly of asymmetric colloidal particles is used in creating high-performance fibres. A similar concept is extended to the manufacturing of thin films of self-assembled two-dimensional crystal-type materials with enhanced and tunable properties. Here we present a spray-coating method to manufacture thin, flexible and transparent epoxy films containing zirconium phosphate nanoplatelets self-assembled into a lamellar arrangement aligned parallel to the substrate. The self-assembled mesophase of zirconium phosphate nanoplatelets is stabilized by epoxy pre-polymer and exhibits rheology favourable towards large-scale manufacturing. The thermally cured film forms a mechanically robust coating and shows excellent gas barrier properties at both low- and high humidity levels as a result of the highly aligned and overlapping arrangement of nanoplatelets. This work shows that the large-scale ordering of high aspect ratio nanoplatelets is easier to achieve than previously thought and may have implications in the technological applications for similar materials.

Comparative Analysis of Different Protocols to Manage Large Scale Networks

OpenAIRE

Anil Rao Pimplapure; Dr Jayant Dubey; Prashant Sen

2013-01-01

In recent year the numbers, complexity and size is increased in Large Scale Network. The best example of Large Scale Network is Internet, and recently once are Data-centers in Cloud Environment. In this process, involvement of several management tasks such as traffic monitoring, security and performance optimization is big task for Network Administrator. This research reports study the different protocols i.e. conventional protocols like Simple Network Management Protocol and newly Gossip bas...

Report of the LASCAR forum: Large scale reprocessing plant safeguards

International Nuclear Information System (INIS)

1992-01-01

This report has been prepared to provide information on the studies which were carried out from 1988 to 1992 under the auspices of the multinational forum known as Large Scale Reprocessing Plant Safeguards (LASCAR) on safeguards for four large scale reprocessing plants operated or planned to be operated in the 1990s. The report summarizes all of the essential results of these studies. The participants in LASCAR were from France, Germany, Japan, the United Kingdom, the United States of America, the Commission of the European Communities - Euratom, and the International Atomic Energy Agency

Subgrid-scale models for large-eddy simulation of rotating turbulent channel flows

Science.gov (United States)

Silvis, Maurits H.; Bae, Hyunji Jane; Trias, F. Xavier; Abkar, Mahdi; Moin, Parviz; Verstappen, Roel

2017-11-01

We aim to design subgrid-scale models for large-eddy simulation of rotating turbulent flows. Rotating turbulent flows form a challenging test case for large-eddy simulation due to the presence of the Coriolis force. The Coriolis force conserves the total kinetic energy while transporting it from small to large scales of motion, leading to the formation of large-scale anisotropic flow structures. The Coriolis force may also cause partial flow laminarization and the occurrence of turbulent bursts. Many subgrid-scale models for large-eddy simulation are, however, primarily designed to parametrize the dissipative nature of turbulent flows, ignoring the specific characteristics of transport processes. We, therefore, propose a new subgrid-scale model that, in addition to the usual dissipative eddy viscosity term, contains a nondissipative nonlinear model term designed to capture transport processes, such as those due to rotation. We show that the addition of this nonlinear model term leads to improved predictions of the energy spectra of rotating homogeneous isotropic turbulence as well as of the Reynolds stress anisotropy in spanwise-rotating plane-channel flows. This work is financed by the Netherlands Organisation for Scientific Research (NWO) under Project Number 613.001.212.

Decentralized Large-Scale Power Balancing

DEFF Research Database (Denmark)

Halvgaard, Rasmus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad

2013-01-01

problem is formulated as a centralized large-scale optimization problem but is then decomposed into smaller subproblems that are solved locally by each unit connected to an aggregator. For large-scale systems the method is faster than solving the full problem and can be distributed to include an arbitrary...

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

Science.gov (United States)

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

Towards large-scale production of solution-processed organic tandem modules based on ternary composites: Design of the intermediate layer, device optimization and laser based module processing

DEFF Research Database (Denmark)

Li, Ning; Kubis, Peter; Forberich, Karen

2014-01-01

on commercially available materials, which enhances the absorption of poly(3-hexylthiophene) (P3HT) and as a result increase the PCE of the P3HT-based large-scale OPV devices; 3. laser-based module processing, which provides an excellent processing resolution and as a result can bring the power conversion...... efficiency (PCE) of mass-produced organic photovoltaic (OPV) devices close to the highest PCE values achieved for lab-scale solar cells through a significant increase in the geometrical fill factor. We believe that the combination of the above mentioned concepts provides a clear roadmap to push OPV towards...

Leveraging human oversight and intervention in large-scale parallel processing of open-source data

Science.gov (United States)

Casini, Enrico; Suri, Niranjan; Bradshaw, Jeffrey M.

2015-05-01

The popularity of cloud computing along with the increased availability of cheap storage have led to the necessity of elaboration and transformation of large volumes of open-source data, all in parallel. One way to handle such extensive volumes of information properly is to take advantage of distributed computing frameworks like Map-Reduce. Unfortunately, an entirely automated approach that excludes human intervention is often unpredictable and error prone. Highly accurate data processing and decision-making can be achieved by supporting an automatic process through human collaboration, in a variety of environments such as warfare, cyber security and threat monitoring. Although this mutual participation seems easily exploitable, human-machine collaboration in the field of data analysis presents several challenges. First, due to the asynchronous nature of human intervention, it is necessary to verify that once a correction is made, all the necessary reprocessing is done in chain. Second, it is often needed to minimize the amount of reprocessing in order to optimize the usage of resources due to limited availability. In order to improve on these strict requirements, this paper introduces improvements to an innovative approach for human-machine collaboration in the processing of large amounts of open-source data in parallel.

Automating large-scale reactor systems

International Nuclear Information System (INIS)

Kisner, R.A.

1985-01-01

This paper conveys a philosophy for developing automated large-scale control systems that behave in an integrated, intelligent, flexible manner. Methods for operating large-scale systems under varying degrees of equipment degradation are discussed, and a design approach that separates the effort into phases is suggested. 5 refs., 1 fig

Large-Scale Spray Releases: Additional Aerosol Test Results

Energy Technology Data Exchange (ETDEWEB)

Daniel, Richard C.; Gauglitz, Phillip A.; Burns, Carolyn A.; Fountain, Matthew S.; Shimskey, Rick W.; Billing, Justin M.; Bontha, Jagannadha R.; Kurath, Dean E.; Jenks, Jeromy WJ; MacFarlan, Paul J.; Mahoney, Lenna A.

2013-08-01

One of the events postulated in the hazard analysis for the Waste Treatment and Immobilization Plant (WTP) and other U.S. Department of Energy (DOE) nuclear facilities is a breach in process piping that produces aerosols with droplet sizes in the respirable range. The current approach for predicting the size and concentration of aerosols produced in a spray leak event involves extrapolating from correlations reported in the literature. These correlations are based on results obtained from small engineered spray nozzles using pure liquids that behave as a Newtonian fluid. The narrow ranges of physical properties on which the correlations are based do not cover the wide range of slurries and viscous materials that will be processed in the WTP and in processing facilities across the DOE complex. To expand the data set upon which the WTP accident and safety analyses were based, an aerosol spray leak testing program was conducted by Pacific Northwest National Laboratory (PNNL). PNNL’s test program addressed two key technical areas to improve the WTP methodology (Larson and Allen 2010). The first technical area was to quantify the role of slurry particles in small breaches where slurry particles may plug the hole and prevent high-pressure sprays. The results from an effort to address this first technical area can be found in Mahoney et al. (2012a). The second technical area was to determine aerosol droplet size distribution and total droplet volume from prototypic breaches and fluids, including sprays from larger breaches and sprays of slurries for which literature data are mostly absent. To address the second technical area, the testing program collected aerosol generation data at two scales, commonly referred to as small-scale and large-scale testing. The small-scale testing and resultant data are described in Mahoney et al. (2012b), and the large-scale testing and resultant data are presented in Schonewill et al. (2012). In tests at both scales, simulants were used

Accelerating Relevance Vector Machine for Large-Scale Data on Spark

Directory of Open Access Journals (Sweden)

Liu Fang

2017-01-01

Full Text Available Relevance vector machine (RVM is a machine learning algorithm based on a sparse Bayesian framework, which performs well when running classification and regression tasks on small-scale datasets. However, RVM also has certain drawbacks which restricts its practical applications such as (1 slow training process, (2 poor performance on training large-scale datasets. In order to solve these problem, we propose Discrete AdaBoost RVM (DAB-RVM which incorporate ensemble learning in RVM at first. This method performs well with large-scale low-dimensional datasets. However, as the number of features increases, the training time of DAB-RVM increases as well. To avoid this phenomenon, we utilize the sufficient training samples of large-scale datasets and propose all features boosting RVM (AFB-RVM, which modifies the way of obtaining weak classifiers. In our experiments we study the differences between various boosting techniques with RVM, demonstrating the performance of the proposed approaches on Spark. As a result of this paper, two proposed approaches on Spark for different types of large-scale datasets are available.

Aligning Business Process Quality and Information System Quality

OpenAIRE

Heinrich, Robert

2013-01-01

Business processes and information systems mutually affect each other in non-trivial ways. Frequently, the business process design and the information system design are not well aligned. This means that business processes are designed without taking the information system impact into account, and vice versa. Missing alignment at design time often results in quality problems at runtime, such as large response times of information systems, large process execution times, overloaded information s...

A fast approach to generate large-scale topographic maps based on new Chinese vehicle-borne Lidar system

International Nuclear Information System (INIS)

Youmei, Han; Bogang, Yang

2014-01-01

Large -scale topographic maps are important basic information for city and regional planning and management. Traditional large- scale mapping methods are mostly based on artificial mapping and photogrammetry. The traditional mapping method is inefficient and limited by the environments. While the photogrammetry methods(such as low-altitude aerial mapping) is an economical and effective way to map wide and regulate range of large scale topographic map but doesn't work well in the small area due to the high cost of manpower and resources. Recent years, the vehicle-borne LIDAR technology has a rapid development, and its application in surveying and mapping is becoming a new topic. The main objective of this investigation is to explore the potential of vehicle-borne LIDAR technology to be used to fast mapping large scale topographic maps based on new Chinese vehicle-borne LIDAR system. It studied how to use the new Chinese vehicle-borne LIDAR system measurement technology to map large scale topographic maps. After the field data capture, it can be mapped in the office based on the LIDAR data (point cloud) by software which programmed by ourselves. In addition, the detailed process and accuracy analysis were proposed by an actual case. The result show that this new technology provides a new fast method to generate large scale topographic maps, which is high efficient and accuracy compared to traditional methods

Application of simplified models to CO2 migration and immobilization in large-scale geological systems

KAUST Repository

Gasda, Sarah E.

2012-07-01

Long-term stabilization of injected carbon dioxide (CO 2) is an essential component of risk management for geological carbon sequestration operations. However, migration and trapping phenomena are inherently complex, involving processes that act over multiple spatial and temporal scales. One example involves centimeter-scale density instabilities in the dissolved CO 2 region leading to large-scale convective mixing that can be a significant driver for CO 2 dissolution. Another example is the potentially important effect of capillary forces, in addition to buoyancy and viscous forces, on the evolution of mobile CO 2. Local capillary effects lead to a capillary transition zone, or capillary fringe, where both fluids are present in the mobile state. This small-scale effect may have a significant impact on large-scale plume migration as well as long-term residual and dissolution trapping. Computational models that can capture both large and small-scale effects are essential to predict the role of these processes on the long-term storage security of CO 2 sequestration operations. Conventional modeling tools are unable to resolve sufficiently all of these relevant processes when modeling CO 2 migration in large-scale geological systems. Herein, we present a vertically-integrated approach to CO 2 modeling that employs upscaled representations of these subgrid processes. We apply the model to the Johansen formation, a prospective site for sequestration of Norwegian CO 2 emissions, and explore the sensitivity of CO 2 migration and trapping to subscale physics. Model results show the relative importance of different physical processes in large-scale simulations. The ability of models such as this to capture the relevant physical processes at large spatial and temporal scales is important for prediction and analysis of CO 2 storage sites. © 2012 Elsevier Ltd.

Scale up risk of developing oil shale processing units

International Nuclear Information System (INIS)

Oepik, I.

1991-01-01

The experiences in oil shale processing in three large countries, China, the U.S.A. and the U.S.S.R. have demonstrated, that the relative scale up risk of developing oil shale processing units is related to the scale up factor. On the background of large programmes for developing the oil shale industry branch, i.e. the $30 billion investments in colorado and Utah or 50 million t/year oil shale processing in Estonia and Leningrad Region planned in the late seventies, the absolute scope of the scale up risk of developing single retorting plants, seems to be justified. But under the conditions of low crude oil prices, when the large-scale development of oil shale processing industry is stopped, the absolute scope of the scale up risk is to be divided between a small number of units. Therefore, it is reasonable to build the new commercial oil shale processing plants with a minimum scale up risk. For example, in Estonia a new oil shale processing plant with gas combustion retorts projected to start in the early nineties will be equipped with four units of 1500 t/day enriched oil shale throughput each, designed with scale up factor M=1.5 and with a minimum scale up risk, only r=2.5-4.5%. The oil shale retorting unit for the PAMA plant in Israel [1] is planned to develop in three steps, also with minimum scale up risk: feasibility studies in Colorado with Israel's shale at Paraho 250 t/day retort and other tests, demonstration retort of 700 t/day and M=2.8 in Israel, and commercial retorts in the early nineties with the capacity of about 1000 t/day with M=1.4. The scale up risk of the PAMA project r=2-4% is approximately the same as that in Estonia. the knowledge of the scope of the scale up risk of developing oil shale processing retorts assists on the calculation of production costs in erecting new units. (author). 9 refs., 2 tabs

GAIA: A WINDOW TO LARGE-SCALE MOTIONS

Energy Technology Data Exchange (ETDEWEB)

Nusser, Adi [Physics Department and the Asher Space Science Institute-Technion, Haifa 32000 (Israel); Branchini, Enzo [Department of Physics, Universita Roma Tre, Via della Vasca Navale 84, 00146 Rome (Italy); Davis, Marc, E-mail: adi@physics.technion.ac.il, E-mail: branchin@fis.uniroma3.it, E-mail: mdavis@berkeley.edu [Departments of Astronomy and Physics, University of California, Berkeley, CA 94720 (United States)

2012-08-10

Using redshifts as a proxy for galaxy distances, estimates of the two-dimensional (2D) transverse peculiar velocities of distant galaxies could be obtained from future measurements of proper motions. We provide the mathematical framework for analyzing 2D transverse motions and show that they offer several advantages over traditional probes of large-scale motions. They are completely independent of any intrinsic relations between galaxy properties; hence, they are essentially free of selection biases. They are free from homogeneous and inhomogeneous Malmquist biases that typically plague distance indicator catalogs. They provide additional information to traditional probes that yield line-of-sight peculiar velocities only. Further, because of their 2D nature, fundamental questions regarding vorticity of large-scale flows can be addressed. Gaia, for example, is expected to provide proper motions of at least bright galaxies with high central surface brightness, making proper motions a likely contender for traditional probes based on current and future distance indicator measurements.

Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks.

Science.gov (United States)

Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A

2016-10-26

Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called "Collective Influence (CI)" has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes' significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct "virtual" information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes' importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community.

Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Ghattas, Omar [The University of Texas at Austin

2013-10-15

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUARO Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.

Large Spatial Scale Ground Displacement Mapping through the P-SBAS Processing of Sentinel-1 Data on a Cloud Computing Environment

Science.gov (United States)

Casu, F.; Bonano, M.; de Luca, C.; Lanari, R.; Manunta, M.; Manzo, M.; Zinno, I.

2017-12-01

Since its launch in 2014, the Sentinel-1 (S1) constellation has played a key role on SAR data availability and dissemination all over the World. Indeed, the free and open access data policy adopted by the European Copernicus program together with the global coverage acquisition strategy, make the Sentinel constellation as a game changer in the Earth Observation scenario. Being the SAR data become ubiquitous, the technological and scientific challenge is focused on maximizing the exploitation of such huge data flow. In this direction, the use of innovative processing algorithms and distributed computing infrastructures, such as the Cloud Computing platforms, can play a crucial role. In this work we present a Cloud Computing solution for the advanced interferometric (DInSAR) processing chain based on the Parallel SBAS (P-SBAS) approach, aimed at processing S1 Interferometric Wide Swath (IWS) data for the generation of large spatial scale deformation time series in efficient, automatic and systematic way. Such a DInSAR chain ingests Sentinel 1 SLC images and carries out several processing steps, to finally compute deformation time series and mean deformation velocity maps. Different parallel strategies have been designed ad hoc for each processing step of the P-SBAS S1 chain, encompassing both multi-core and multi-node programming techniques, in order to maximize the computational efficiency achieved within a Cloud Computing environment and cut down the relevant processing times. The presented P-SBAS S1 processing chain has been implemented on the Amazon Web Services platform and a thorough analysis of the attained parallel performances has been performed to identify and overcome the major bottlenecks to the scalability. The presented approach is used to perform national-scale DInSAR analyses over Italy, involving the processing of more than 3000 S1 IWS images acquired from both ascending and descending orbits. Such an experiment confirms the big advantage of

GPU-based large-scale visualization

KAUST Repository

Hadwiger, Markus

2013-11-19

Recent advances in image and volume acquisition as well as computational advances in simulation have led to an explosion of the amount of data that must be visualized and analyzed. Modern techniques combine the parallel processing power of GPUs with out-of-core methods and data streaming to enable the interactive visualization of giga- and terabytes of image and volume data. A major enabler for interactivity is making both the computational and the visualization effort proportional to the amount of data that is actually visible on screen, decoupling it from the full data size. This leads to powerful display-aware multi-resolution techniques that enable the visualization of data of almost arbitrary size. The course consists of two major parts: An introductory part that progresses from fundamentals to modern techniques, and a more advanced part that discusses details of ray-guided volume rendering, novel data structures for display-aware visualization and processing, and the remote visualization of large online data collections. You will learn how to develop efficient GPU data structures and large-scale visualizations, implement out-of-core strategies and concepts such as virtual texturing that have only been employed recently, as well as how to use modern multi-resolution representations. These approaches reduce the GPU memory requirements of extremely large data to a working set size that fits into current GPUs. You will learn how to perform ray-casting of volume data of almost arbitrary size and how to render and process gigapixel images using scalable, display-aware techniques. We will describe custom virtual texturing architectures as well as recent hardware developments in this area. We will also describe client/server systems for distributed visualization, on-demand data processing and streaming, and remote visualization. We will describe implementations using OpenGL as well as CUDA, exploiting parallelism on GPUs combined with additional asynchronous

Parallel Index and Query for Large Scale Data Analysis

Energy Technology Data Exchange (ETDEWEB)

Chou, Jerry; Wu, Kesheng; Ruebel, Oliver; Howison, Mark; Qiang, Ji; Prabhat,; Austin, Brian; Bethel, E. Wes; Ryne, Rob D.; Shoshani, Arie

2011-07-18

Modern scientific datasets present numerous data management and analysis challenges. State-of-the-art index and query technologies are critical for facilitating interactive exploration of large datasets, but numerous challenges remain in terms of designing a system for process- ing general scientific datasets. The system needs to be able to run on distributed multi-core platforms, efficiently utilize underlying I/O infrastructure, and scale to massive datasets. We present FastQuery, a novel software framework that address these challenges. FastQuery utilizes a state-of-the-art index and query technology (FastBit) and is designed to process mas- sive datasets on modern supercomputing platforms. We apply FastQuery to processing of a massive 50TB dataset generated by a large scale accelerator modeling code. We demonstrate the scalability of the tool to 11,520 cores. Motivated by the scientific need to search for inter- esting particles in this dataset, we use our framework to reduce search time from hours to tens of seconds.

The Software Reliability of Large Scale Integration Circuit and Very Large Scale Integration Circuit

OpenAIRE

Artem Ganiyev; Jan Vitasek

2010-01-01

This article describes evaluation method of faultless function of large scale integration circuits (LSI) and very large scale integration circuits (VLSI). In the article there is a comparative analysis of factors which determine faultless of integrated circuits, analysis of already existing methods and model of faultless function evaluation of LSI and VLSI. The main part describes a proposed algorithm and program for analysis of fault rate in LSI and VLSI circuits.

Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

Directory of Open Access Journals (Sweden)

A. F. Van Loon

2012-11-01

underestimation of wet-to-dry-season droughts and snow-related droughts. Furthermore, almost no composite droughts were simulated for slowly responding areas, while many multi-year drought events were expected in these systems.

We conclude that most drought propagation processes are reasonably well reproduced by the ensemble mean of large-scale models in contrasting catchments in Europe. Challenges, however, remain in catchments with cold and semi-arid climates and catchments with large storage in aquifers or lakes. This leads to a high uncertainty in hydrological drought simulation at large scales. Improvement of drought simulation in large-scale models should focus on a better representation of hydrological processes that are important for drought development, such as evapotranspiration, snow accumulation and melt, and especially storage. Besides the more explicit inclusion of storage in large-scale models, also parametrisation of storage processes requires attention, for example through a global-scale dataset on aquifer characteristics, improved large-scale datasets on other land characteristics (e.g. soils, land cover, and calibration/evaluation of the models against observations of storage (e.g. in snow, groundwater.

Large Deviations for Two-Time-Scale Diffusions, with Delays

International Nuclear Information System (INIS)

Kushner, Harold J.

2010-01-01

We consider the problem of large deviations for a two-time-scale reflected diffusion process, possibly with delays in the dynamical terms. The Dupuis-Ellis weak convergence approach is used. It is perhaps the most intuitive and simplest for the problems of concern. The results have applications to the problem of approximating optimal controls for two-time-scale systems via use of the averaged equation.

Large-Scale Consumption and Zero-Waste Recycling Method of Red Mud in Steel Making Process

Directory of Open Access Journals (Sweden)

Guoshan Ning

2018-03-01

Full Text Available To release the environmental pressure from the massive discharge of bauxite residue (red mud, a novel recycling method of red mud in steel making process was investigated through high-temperature experiments and thermodynamic analysis. The results showed that after the reduction roasting of the carbon-bearing red mud pellets at 1100–1200 °C for 12–20 min, the metallic pellets were obtained with the metallization ratio of ≥88%. Then, the separation of slag and iron achieved from the metallic pellets at 1550 °C, after composition adjustment targeting the primary crystal region of the 12CaO·7Al2O3 phase. After iron removal and composition adjustment, the smelting-separation slag had good smelting performance and desulfurization capability, which meets the demand of sulfurization flux in steel making process. The pig iron quality meets the requirements of the high-quality raw material for steel making. In virtue of the huge scale and output of steel industry, the large-scale consumption and zero-waste recycling method of red mud was proposed, which comprised of the carbon-bearing red mud pellets roasting in the rotary hearth furnace and smelting separation in the electric arc furnace after composition adjustment.

How the Internet Will Help Large-Scale Assessment Reinvent Itself

Directory of Open Access Journals (Sweden)

Randy Elliot Bennett

2001-02-01

Full Text Available Large-scale assessment in the United States is undergoing enormous pressure to change. That pressure stems from many causes. Depending upon the type of test, the issues precipitating change include an outmoded cognitive-scientific basis for test design; a mismatch with curriculum; the differential performance of population groups; a lack of information to help individuals improve; and inefficiency. These issues provide a strong motivation to reconceptualize both the substance and the business of large-scale assessment. At the same time, advances in technology, measurement, and cognitive science are providing the means to make that reconceptualization a reality. The thesis of this paper is that the largest facilitating factor will be technological, in particular the Internet. In the same way that it is already helping to revolutionize commerce, education, and even social interaction, the Internet will help revolutionize the business and substance of large-scale assessment.

Phylogenetic distribution of large-scale genome patchiness

Directory of Open Access Journals (Sweden)

Hackenberg Michael

2008-04-01

Full Text Available Abstract Background The phylogenetic distribution of large-scale genome structure (i.e. mosaic compositional patchiness has been explored mainly by analytical ultracentrifugation of bulk DNA. However, with the availability of large, good-quality chromosome sequences, and the recently developed computational methods to directly analyze patchiness on the genome sequence, an evolutionary comparative analysis can be carried out at the sequence level. Results The local variations in the scaling exponent of the Detrended Fluctuation Analysis are used here to analyze large-scale genome structure and directly uncover the characteristic scales present in genome sequences. Furthermore, through shuffling experiments of selected genome regions, computationally-identified, isochore-like regions were identified as the biological source for the uncovered large-scale genome structure. The phylogenetic distribution of short- and large-scale patchiness was determined in the best-sequenced genome assemblies from eleven eukaryotic genomes: mammals (Homo sapiens, Pan troglodytes, Mus musculus, Rattus norvegicus, and Canis familiaris, birds (Gallus gallus, fishes (Danio rerio, invertebrates (Drosophila melanogaster and Caenorhabditis elegans, plants (Arabidopsis thaliana and yeasts (Saccharomyces cerevisiae. We found large-scale patchiness of genome structure, associated with in silico determined, isochore-like regions, throughout this wide phylogenetic range. Conclusion Large-scale genome structure is detected by directly analyzing DNA sequences in a wide range of eukaryotic chromosome sequences, from human to yeast. In all these genomes, large-scale patchiness can be associated with the isochore-like regions, as directly detected in silico at the sequence level.

Managing large-scale models: DBS

International Nuclear Information System (INIS)

1981-05-01

A set of fundamental management tools for developing and operating a large scale model and data base system is presented. Based on experience in operating and developing a large scale computerized system, the only reasonable way to gain strong management control of such a system is to implement appropriate controls and procedures. Chapter I discusses the purpose of the book. Chapter II classifies a broad range of generic management problems into three groups: documentation, operations, and maintenance. First, system problems are identified then solutions for gaining management control are disucssed. Chapters III, IV, and V present practical methods for dealing with these problems. These methods were developed for managing SEAS but have general application for large scale models and data bases

Automation of Survey Data Processing, Documentation and Dissemination: An Application to Large-Scale Self-Reported Educational Survey.

Science.gov (United States)

Shim, Eunjae; Shim, Minsuk K.; Felner, Robert D.

Automation of the survey process has proved successful in many industries, yet it is still underused in educational research. This is largely due to the facts (1) that number crunching is usually carried out using software that was developed before information technology existed, and (2) that the educational research is to a great extent trapped…

On the Large-Scaling Issues of Cloud-based Applications for Earth Science Dat

Science.gov (United States)

Hua, H.

2016-12-01

Next generation science data systems are needed to address the incoming flood of data from new missions such as NASA's SWOT and NISAR where its SAR data volumes and data throughput rates are order of magnitude larger than present day missions. Existing missions, such as OCO-2, may also require high turn-around time for processing different science scenarios where on-premise and even traditional HPC computing environments may not meet the high processing needs. Additionally, traditional means of procuring hardware on-premise are already limited due to facilities capacity constraints for these new missions. Experiences have shown that to embrace efficient cloud computing approaches for large-scale science data systems requires more than just moving existing code to cloud environments. At large cloud scales, we need to deal with scaling and cost issues. We present our experiences on deploying multiple instances of our hybrid-cloud computing science data system (HySDS) to support large-scale processing of Earth Science data products. We will explore optimization approaches to getting best performance out of hybrid-cloud computing as well as common issues that will arise when dealing with large-scale computing. Novel approaches were utilized to do processing on Amazon's spot market, which can potentially offer 75%-90% costs savings but with an unpredictable computing environment based on market forces.

Risk perception and information processing: the development and validation of a questionnaire to assess self-reported information processing.

Science.gov (United States)

Smerecnik, Chris M R; Mesters, Ilse; Candel, Math J J M; De Vries, Hein; De Vries, Nanne K

2012-01-01

The role of information processing in understanding people's responses to risk information has recently received substantial attention. One limitation of this research concerns the unavailability of a validated questionnaire of information processing. This article presents two studies in which we describe the development and validation of the Information-Processing Questionnaire to meet that need. Study 1 describes the development and initial validation of the questionnaire. Participants were randomized to either a systematic processing or a heuristic processing condition after which they completed a manipulation check and the initial 15-item questionnaire and again two weeks later. The questionnaire was subjected to factor reliability and validity analyses on both measurement times for purposes of cross-validation of the results. A two-factor solution was observed representing a systematic processing and a heuristic processing subscale. The resulting scale showed good reliability and validity, with the systematic condition scoring significantly higher on the systematic subscale and the heuristic processing condition significantly higher on the heuristic subscale. Study 2 sought to further validate the questionnaire in a field study. Results of the second study corresponded with those of Study 1 and provided further evidence of the validity of the Information-Processing Questionnaire. The availability of this information-processing scale will be a valuable asset for future research and may provide researchers with new research opportunities. © 2011 Society for Risk Analysis.

Cell therapy-processing economics: small-scale microfactories as a stepping stone toward large-scale macrofactories.

Science.gov (United States)

Harrison, Richard P; Medcalf, Nicholas; Rafiq, Qasim A

2018-03-01

Manufacturing methods for cell-based therapies differ markedly from those established for noncellular pharmaceuticals and biologics. Attempts to 'shoehorn' these into existing frameworks have yielded poor outcomes. Some excellent clinical results have been realized, yet emergence of a 'blockbuster' cell-based therapy has so far proved elusive.  The pressure to provide these innovative therapies, even at a smaller scale, remains. In this process, economics research paper, we utilize cell expansion research data combined with operational cost modeling in a case study to demonstrate the alternative ways in which a novel mesenchymal stem cell-based therapy could be provided at small scale. This research outlines the feasibility of cell microfactories but highlighted that there is a strong pressure to automate processes and split the quality control cost-burden over larger production batches. The study explores one potential paradigm of cell-based therapy provisioning as a potential exemplar on which to base manufacturing strategy.

Technical data summary: Uranium(IV) production using a large scale electrochemical cell

International Nuclear Information System (INIS)

Hsu, T.C.

1984-05-01

This Technical Data Summary outlines an electrochemical process to produce U(IV), in the form of uranous nitrate, from U(VI), as uranyl nitrate. U(IV) with hydrazine could then be used as an alternative plutonium reductant to substantially reduce the waste volume from the Purex solvent extraction process. This TDS is divided into three parts. The first part (Chapters I to IV) generally describes the electrochemical production of U(IV). The second part (Chapters V to VII) describes a pilot scale U(IV) production facility that was constructed and operated at an engineering semiworks area of SRP, referred to as TNX. The lst part (Chapter VIII) describes a preliminary design for a full-scale facility that would meet the projected need for U(IV) as a reductant in SRP's separations processes. The preliminary design was described in a Basic Data Summary for the U(IV) production facility, and a Venture Guidance Appraisal (VGA) was prepared from the Basic Data Summary. The VGA for the U(IV) process showed that because of the large capital investment required, this approach to waste reduction was not economically competitive with another alternative that required only modifying the ongoing Purex process at no additional capital cost. However, implementing he U(IV) process as part of an overall canyon renovation, presently scheduled for the 1990's, may be economically attractive. The purpose of this TDS is therefore to bring together the information and experience obtained thus far in the U(IV) program so that a useful body of information will be available to support any future development of this process

Participatory Design and the Challenges of Large-Scale Systems

DEFF Research Database (Denmark)

Simonsen, Jesper; Hertzum, Morten

2008-01-01

With its 10th biannual anniversary conference, Participatory Design (PD) is leaving its teens and must now be considered ready to join the adult world. In this article we encourage the PD community to think big: PD should engage in large-scale information-systems development and opt for a PD...

Lessons from a large-scale assessment: Results from conceptual inventories

Directory of Open Access Journals (Sweden)

Beth Thacker

2014-07-01

Full Text Available We report conceptual inventory results of a large-scale assessment project at a large university. We studied the introduction of materials and instructional methods informed by physics education research (PER (physics education research-informed materials into a department where most instruction has previously been traditional and a significant number of faculty are hesitant, ambivalent, or even resistant to the introduction of such reforms. Data were collected in all of the sections of both the large algebra- and calculus-based introductory courses for a number of years employing commonly used conceptual inventories. Results from a small PER-informed, inquiry-based, laboratory-based class are also reported. Results suggest that when PER-informed materials are introduced in the labs and recitations, independent of the lecture style, there is an increase in students’ conceptual inventory gains. There is also an increase in the results on conceptual inventories if PER-informed instruction is used in the lecture. The highest conceptual inventory gains were achieved by the combination of PER-informed lectures and laboratories in large class settings and by the hands-on, laboratory-based, inquiry-based course taught in a small class setting.

Improved Large-Scale Inundation Modelling by 1D-2D Coupling and Consideration of Hydrologic and Hydrodynamic Processes - a Case Study in the Amazon

Science.gov (United States)

Hoch, J. M.; Bierkens, M. F.; Van Beek, R.; Winsemius, H.; Haag, A.

2015-12-01

Understanding the dynamics of fluvial floods is paramount to accurate flood hazard and risk modeling. Currently, economic losses due to flooding constitute about one third of all damage resulting from natural hazards. Given future projections of climate change, the anticipated increase in the World's population and the associated implications, sound knowledge of flood hazard and related risk is crucial. Fluvial floods are cross-border phenomena that need to be addressed accordingly. Yet, only few studies model floods at the large-scale which is preferable to tiling the output of small-scale models. Most models cannot realistically model flood wave propagation due to a lack of either detailed channel and floodplain geometry or the absence of hydrologic processes. This study aims to develop a large-scale modeling tool that accounts for both hydrologic and hydrodynamic processes, to find and understand possible sources of errors and improvements and to assess how the added hydrodynamics affect flood wave propagation. Flood wave propagation is simulated by DELFT3D-FM (FM), a hydrodynamic model using a flexible mesh to schematize the study area. It is coupled to PCR-GLOBWB (PCR), a macro-scale hydrological model, that has its own simpler 1D routing scheme (DynRout) which has already been used for global inundation modeling and flood risk assessments (GLOFRIS; Winsemius et al., 2013). A number of model set-ups are compared and benchmarked for the simulation period 1986-1996: (0) PCR with DynRout; (1) using a FM 2D flexible mesh forced with PCR output and (2) as in (1) but discriminating between 1D channels and 2D floodplains, and, for comparison, (3) and (4) the same set-ups as (1) and (2) but forced with observed GRDC discharge values. Outputs are subsequently validated against observed GRDC data at Óbidos and flood extent maps from the Dartmouth Flood Observatory. The present research constitutes a first step into a globally applicable approach to fully couple

Large scale structure and baryogenesis

International Nuclear Information System (INIS)

Kirilova, D.P.; Chizhov, M.V.

2001-08-01

We discuss a possible connection between the large scale structure formation and the baryogenesis in the universe. An update review of the observational indications for the presence of a very large scale 120h -1 Mpc in the distribution of the visible matter of the universe is provided. The possibility to generate a periodic distribution with the characteristic scale 120h -1 Mpc through a mechanism producing quasi-periodic baryon density perturbations during inflationary stage, is discussed. The evolution of the baryon charge density distribution is explored in the framework of a low temperature boson condensate baryogenesis scenario. Both the observed very large scale of a the visible matter distribution in the universe and the observed baryon asymmetry value could naturally appear as a result of the evolution of a complex scalar field condensate, formed at the inflationary stage. Moreover, for some model's parameters a natural separation of matter superclusters from antimatter ones can be achieved. (author)

Automatic management software for large-scale cluster system

International Nuclear Information System (INIS)

Weng Yunjian; Chinese Academy of Sciences, Beijing; Sun Gongxing

2007-01-01

At present, the large-scale cluster system faces to the difficult management. For example the manager has large work load. It needs to cost much time on the management and the maintenance of large-scale cluster system. The nodes in large-scale cluster system are very easy to be chaotic. Thousands of nodes are put in big rooms so that some managers are very easy to make the confusion with machines. How do effectively carry on accurate management under the large-scale cluster system? The article introduces ELFms in the large-scale cluster system. Furthermore, it is proposed to realize the large-scale cluster system automatic management. (authors)

On the universal character of the large scale structure of the universe

International Nuclear Information System (INIS)

Demianski, M.; International Center for Relativistic Astrophysics; Rome Univ.; Doroshkevich, A.G.

1991-01-01

We review different theories of formation of the large scale structure of the Universe. Special emphasis is put on the theory of inertial instability. We show that for a large class of initial spectra the resulting two point correlation functions are similar. We discuss also the adhesion theory which uses the Burgers equation, Navier-Stokes equation or coagulation process. We review the Zeldovich theory of gravitational instability and discuss the internal structure of pancakes. Finally we discuss the role of the velocity potential in determining the global characteristics of large scale structures (distribution of caustics, scale of voids, etc.). In the last chapter we list the main unsolved problems and main successes of the theory of formation of large scale structure. (orig.)

Utilization of Large Scale Surface Models for Detailed Visibility Analyses

Science.gov (United States)

Caha, J.; Kačmařík, M.

2017-11-01

This article demonstrates utilization of large scale surface models with small spatial resolution and high accuracy, acquired from Unmanned Aerial Vehicle scanning, for visibility analyses. The importance of large scale data for visibility analyses on the local scale, where the detail of the surface model is the most defining factor, is described. The focus is not only the classic Boolean visibility, that is usually determined within GIS, but also on so called extended viewsheds that aims to provide more information about visibility. The case study with examples of visibility analyses was performed on river Opava, near the Ostrava city (Czech Republic). The multiple Boolean viewshed analysis and global horizon viewshed were calculated to determine most prominent features and visibility barriers of the surface. Besides that, the extended viewshed showing angle difference above the local horizon, which describes angular height of the target area above the barrier, is shown. The case study proved that large scale models are appropriate data source for visibility analyses on local level. The discussion summarizes possible future applications and further development directions of visibility analyses.

Survey of large-scale solar water heaters installed in Taiwan, China

Energy Technology Data Exchange (ETDEWEB)

Chang Keh-Chin; Lee Tsong-Sheng; Chung Kung-Ming [Cheng Kung Univ., Tainan (China); Lien Ya-Feng; Lee Chine-An [Cheng Kung Univ. Research and Development Foundation, Tainan (China)

2008-07-01

Almost all the solar collectors installed in Taiwan, China were used for production of hot water for homeowners (residential systems), in which the area of solar collectors is less than 10 square meters. From 2001 to 2006, there were only 39 large-scale systems (defined as the area of solar collectors being over 100 m{sup 2}) installed. Their utilization purposes are for rooming house (dormitory), swimming pool, restaurant, and manufacturing process. A comprehensive survey of those large-scale solar water heaters was conducted in 2006. The objectives of the survey were to asses the systems' performance and to have the feedback from the individual users. It is found that lack of experience in system design and maintenance are the key factors for reliable operation of a system. For further promotion of large-scale solar water heaters in Taiwan, a more compressive program on a system design for manufacturing process should be conducted. (orig.)

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

Science.gov (United States)

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

2017-01-01

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

Optimization of large-scale heterogeneous system-of-systems models.

Energy Technology Data Exchange (ETDEWEB)

Parekh, Ojas; Watson, Jean-Paul; Phillips, Cynthia Ann; Siirola, John; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Lee, Herbert K. H. (University of California, Santa Cruz, Santa Cruz, CA); Hart, William Eugene; Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Woodruff, David L. (University of California, Davis, Davis, CA)

2012-01-01

Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.

Prehospital Acute Stroke Severity Scale to Predict Large Artery Occlusion: Design and Comparison With Other Scales.

Science.gov (United States)

Hastrup, Sidsel; Damgaard, Dorte; Johnsen, Søren Paaske; Andersen, Grethe

2016-07-01

We designed and validated a simple prehospital stroke scale to identify emergent large vessel occlusion (ELVO) in patients with acute ischemic stroke and compared the scale to other published scales for prediction of ELVO. A national historical test cohort of 3127 patients with information on intracranial vessel status (angiography) before reperfusion therapy was identified. National Institutes of Health Stroke Scale (NIHSS) items with the highest predictive value of occlusion of a large intracranial artery were identified, and the most optimal combination meeting predefined criteria to ensure usefulness in the prehospital phase was determined. The predictive performance of Prehospital Acute Stroke Severity (PASS) scale was compared with other published scales for ELVO. The PASS scale was composed of 3 NIHSS scores: level of consciousness (month/age), gaze palsy/deviation, and arm weakness. In derivation of PASS 2/3 of the test cohort was used and showed accuracy (area under the curve) of 0.76 for detecting large arterial occlusion. Optimal cut point ≥2 abnormal scores showed: sensitivity=0.66 (95% CI, 0.62-0.69), specificity=0.83 (0.81-0.85), and area under the curve=0.74 (0.72-0.76). Validation on 1/3 of the test cohort showed similar performance. Patients with a large artery occlusion on angiography with PASS ≥2 had a median NIHSS score of 17 (interquartile range=6) as opposed to PASS <2 with a median NIHSS score of 6 (interquartile range=5). The PASS scale showed equal performance although more simple when compared with other scales predicting ELVO. The PASS scale is simple and has promising accuracy for prediction of ELVO in the field. © 2016 American Heart Association, Inc.

Decoupling processes and scales of shoreline morphodynamics

Science.gov (United States)

Hapke, Cheryl J.; Plant, Nathaniel G.; Henderson, Rachel E.; Schwab, William C.; Nelson, Timothy R.

2016-01-01

Behavior of coastal systems on time scales ranging from single storm events to years and decades is controlled by both small-scale sediment transport processes and large-scale geologic, oceanographic, and morphologic processes. Improved understanding of coastal behavior at multiple time scales is required for refining models that predict potential erosion hazards and for coastal management planning and decision-making. Here we investigate the primary controls on shoreline response along a geologically-variable barrier island on time scales resolving extreme storms and decadal variations over a period of nearly one century. An empirical orthogonal function analysis is applied to a time series of shoreline positions at Fire Island, NY to identify patterns of shoreline variance along the length of the island. We establish that there are separable patterns of shoreline behavior that represent response to oceanographic forcing as well as patterns that are not explained by this forcing. The dominant shoreline behavior occurs over large length scales in the form of alternating episodes of shoreline retreat and advance, presumably in response to storms cycles. Two secondary responses include long-term response that is correlated to known geologic variations of the island and the other reflects geomorphic patterns with medium length scale. Our study also includes the response to Hurricane Sandy and a period of post-storm recovery. It was expected that the impacts from Hurricane Sandy would disrupt long-term trends and spatial patterns. We found that the response to Sandy at Fire Island is not notable or distinguishable from several other large storms of the prior decade.

Karhunen-Loève (PCA) based detection of multiple oscillations in multiple measurement signals from large-scale process plants

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Wickerhauser, M.V.

2007-01-01

 In the perspective of optimizing the control and operation of large scale process plants, it is important to detect and to locate oscillations in the plants. This paper presents a scheme for detecting and localizing multiple oscillations in multiple measurements from such a large-scale power plant....... The scheme is based on a Karhunen-Lo\\`{e}ve analysis of the data from the plant. The proposed scheme is subsequently tested on two sets of data: a set of synthetic data and a set of data from a coal-fired power plant. In both cases the scheme detects the beginning of the oscillation within only a few samples....... In addition the oscillation localization has also shown its potential by localizing the oscillations in both data sets....

Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks

Science.gov (United States)

Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A.

2016-01-01

Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called “Collective Influence (CI)” has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes’ significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct “virtual” information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes’ importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community. PMID:27782207

Large-scale Lurgi plant would be uneconomic: study group

Energy Technology Data Exchange (ETDEWEB)

1964-03-21

Gas Council and National Coal Board agreed that building of large scale Lurgi plant on the basis of study is not at present acceptable on economic grounds. The committee considered that new processes based on naphtha offered more economic sources of base and peak load production. Tables listing data provided in contractors' design studies and summary of contractors' process designs are included.

Large scale network-centric distributed systems

CERN Document Server

Sarbazi-Azad, Hamid

2014-01-01

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

Large-Scale Outflows in Seyfert Galaxies

Science.gov (United States)

Colbert, E. J. M.; Baum, S. A.

1995-12-01

\\catcode`\\@=11 \\ialign{m @th#1hfil ##hfil \\crcr#2\\crcr\\sim\\crcr}}} \\catcode`\\@=12 Highly collimated outflows extend out to Mpc scales in many radio-loud active galaxies. In Seyfert galaxies, which are radio-quiet, the outflows extend out to kpc scales and do not appear to be as highly collimated. In order to study the nature of large-scale (>~1 kpc) outflows in Seyferts, we have conducted optical, radio and X-ray surveys of a distance-limited sample of 22 edge-on Seyfert galaxies. Results of the optical emission-line imaging and spectroscopic survey imply that large-scale outflows are present in >~{{1} /{4}} of all Seyferts. The radio (VLA) and X-ray (ROSAT) surveys show that large-scale radio and X-ray emission is present at about the same frequency. Kinetic luminosities of the outflows in Seyferts are comparable to those in starburst-driven superwinds. Large-scale radio sources in Seyferts appear diffuse, but do not resemble radio halos found in some edge-on starburst galaxies (e.g. M82). We discuss the feasibility of the outflows being powered by the active nucleus (e.g. a jet) or a circumnuclear starburst.

Large-scale melting and impact mixing on early-formed asteroids

DEFF Research Database (Denmark)

Greenwood, Richard; Barrat, J.-A.; Scott, Edward Robert Dalton

Large-scale melting of asteroids and planetesimals is now known to have taken place ex-tremely early in solar system history [1]. The first-generation bodies produced by this process would have been subject to rapid collisional reprocessing, leading in most cases to fragmentation and/or accretion...... the relationship between the different groups of achondrites [3, 4]. Here we present new oxygen isotope evidence con-cerning the role of large-scale melting and subsequent impact mixing in the evolution of three important achondrite groups: the main-group pallasites, meso-siderites and HEDs....

Survey of high-voltage pulse technology suitable for large-scale plasma source ion implantation processes

International Nuclear Information System (INIS)

Reass, W.A.

1994-01-01

Many new plasma processes ideas are finding their way from the research lab to the manufacturing plant floor. These require high voltage (HV) pulse power equipment, which must be optimized for application, system efficiency, and reliability. Although no single HV pulse technology is suitable for all plasma processes, various classes of high voltage pulsers may offer a greater versatility and economy to the manufacturer. Technology developed for existing radar and particle accelerator modulator power systems can be utilized to develop a modern large scale plasma source ion implantation (PSII) system. The HV pulse networks can be broadly defined by two classes of systems, those that generate the voltage directly, and those that use some type of pulse forming network and step-up transformer. This article will examine these HV pulse technologies and discuss their applicability to the specific PSII process. Typical systems that will be reviewed will include high power solid state, hard tube systems such as crossed-field ''hollow beam'' switch tubes and planar tetrodes, and ''soft'' tube systems with crossatrons and thyratrons. Results will be tabulated and suggestions provided for a particular PSII process

Assessing Human Modifications to Floodplains using Large-Scale Hydrogeomorphic Floodplain Modeling

Science.gov (United States)

Morrison, R. R.; Scheel, K.; Nardi, F.; Annis, A.

2017-12-01

Human modifications to floodplains for water resource and flood management purposes have significantly transformed river-floodplain connectivity dynamics in many watersheds. Bridges, levees, reservoirs, shifts in land use, and other hydraulic engineering works have altered flow patterns and caused changes in the timing and extent of floodplain inundation processes. These hydrogeomorphic changes have likely resulted in negative impacts to aquatic habitat and ecological processes. The availability of large-scale topographic datasets at high resolution provide an opportunity for detecting anthropogenic impacts by means of geomorphic mapping. We have developed and are implementing a methodology for comparing a hydrogeomorphic floodplain mapping technique to hydraulically-modeled floodplain boundaries to estimate floodplain loss due to human activities. Our hydrogeomorphic mapping methodology assumes that river valley morphology intrinsically includes information on flood-driven erosion and depositional phenomena. We use a digital elevation model-based algorithm to identify the floodplain as the area of the fluvial corridor laying below water reference levels, which are estimated using a simplified hydrologic model. Results from our hydrogeomorphic method are compared to hydraulically-derived flood zone maps and spatial datasets of levee protected-areas to explore where water management features, such as levees, have changed floodplain dynamics and landscape features. Parameters associated with commonly used F-index functions are quantified and analyzed to better understand how floodplain areas have been reduced within a basin. Preliminary results indicate that the hydrogeomorphic floodplain model is useful for quickly delineating floodplains at large watershed scales, but further analyses are needed to understand the caveats for using the model in determining floodplain loss due to levees. We plan to continue this work by exploring the spatial dependencies of the F

SCALE INTERACTION IN A MIXING LAYER. THE ROLE OF THE LARGE-SCALE GRADIENTS

KAUST Repository

Fiscaletti, Daniele

2015-08-23

The interaction between scales is investigated in a turbulent mixing layer. The large-scale amplitude modulation of the small scales already observed in other works depends on the crosswise location. Large-scale positive fluctuations correlate with a stronger activity of the small scales on the low speed-side of the mixing layer, and a reduced activity on the high speed-side. However, from physical considerations we would expect the scales to interact in a qualitatively similar way within the flow and across different turbulent flows. Therefore, instead of the large-scale fluctuations, the large-scale gradients modulation of the small scales has been additionally investigated.

Integration, Provenance, and Temporal Queries for Large-Scale Knowledge Bases

OpenAIRE

Gao, Shi

2016-01-01

Knowledge bases that summarize web information in RDF triples deliver many benefits, including support for natural language question answering and powerful structured queries that extract encyclopedic knowledge via SPARQL. Large scale knowledge bases grow rapidly in terms of scale and significance, and undergo frequent changes in both schema and content. Two critical problems have thus emerged: (i) how to support temporal queries that explore the history of knowledge bases or flash-back to th...

Evolutionary leap in large-scale flood risk assessment needed

OpenAIRE

Vorogushyn, Sergiy; Bates, Paul D.; de Bruijn, Karin; Castellarin, Attilio; Kreibich, Heidi; Priest, Sally J.; Schröter, Kai; Bagli, Stefano; Blöschl, Günter; Domeneghetti, Alessio; Gouldby, Ben; Klijn, Frans; Lammersen, Rita; Neal, Jeffrey C.; Ridder, Nina

2018-01-01

Current approaches for assessing large-scale flood risks contravene the fundamental principles of the flood risk system functioning because they largely ignore basic interactions and feedbacks between atmosphere, catchments, river-floodplain systems and socio-economic processes. As a consequence, risk analyses are uncertain and might be biased. However, reliable risk estimates are required for prioritizing national investments in flood risk mitigation or for appraisal and management of insura...

Low-Complexity Transmit Antenna Selection and Beamforming for Large-Scale MIMO Communications

Directory of Open Access Journals (Sweden)

Kun Qian

2014-01-01

Full Text Available Transmit antenna selection plays an important role in large-scale multiple-input multiple-output (MIMO communications, but optimal large-scale MIMO antenna selection is a technical challenge. Exhaustive search is often employed in antenna selection, but it cannot be efficiently implemented in large-scale MIMO communication systems due to its prohibitive high computation complexity. This paper proposes a low-complexity interactive multiple-parameter optimization method for joint transmit antenna selection and beamforming in large-scale MIMO communication systems. The objective is to jointly maximize the channel outrage capacity and signal-to-noise (SNR performance and minimize the mean square error in transmit antenna selection and minimum variance distortionless response (MVDR beamforming without exhaustive search. The effectiveness of all the proposed methods is verified by extensive simulation results. It is shown that the required antenna selection processing time of the proposed method does not increase along with the increase of selected antennas, but the computation complexity of conventional exhaustive search method will significantly increase when large-scale antennas are employed in the system. This is particularly useful in antenna selection for large-scale MIMO communication systems.

Best Practices in the Evaluation of Large-scale STEM-focused Events: A Review of Recent Literature

Science.gov (United States)

Shebby, S.; Cobb, W. H.; Buxner, S.; Shipp, S. S.

2015-12-01

Each year, the National Aeronautics and Space Administration (NASA) sponsors a variety of educational events to share information with educators, students, and the general public. Intended outcomes of these events include increased interest in and awareness of the mission and goals of NASA. Events range in size from relatively small family science nights at a local school to large-scale mission and celestial event celebrations involving thousands of members of the general public. To support community members in designing event evaluations, the Science Mission Directorate (SMD) Planetary Science Forum sponsored the creation of a Best Practices Guide. The guide was generated by reviewing published large-scale event evaluation reports; however, the best practices described within are pertinent for all event organizers and evaluators regardless of event size. Each source included in the guide identified numerous challenges to conducting their event evaluation. These included difficulty in identifying extant instruments or items, collecting representative data, and disaggregating data to inform different evaluation questions. Overall, the guide demonstrates that evaluations of the large-scale events are generally done at a very basic level, with the types of data collected limited to observable demographic information and participant reactions collected via online survey. In addition to these findings, this presentation will describe evaluation best practices that will help practitioners move beyond these basic indicators and examine how to make the evaluation process an integral—and valuable—element of event planning, ultimately informing event outcomes and impacts. It will provide detailed information on five recommendations presented in the guide: 1) consider evaluation methodology, including data analysis, in advance; 2) design data collection instruments well in advance of the event; 3) collect data at different times and from multiple sources; 4) use

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

Science.gov (United States)

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.

Large-scale silviculture experiments of western Oregon and Washington.

Science.gov (United States)

Nathan J. Poage; Paul D. Anderson

2007-01-01

We review 12 large-scale silviculture experiments (LSSEs) in western Washington and Oregon with which the Pacific Northwest Research Station of the USDA Forest Service is substantially involved. We compiled and arrayed information about the LSSEs as a series of matrices in a relational database, which is included on the compact disc published with this report and...

Dissecting the large-scale galactic conformity

Science.gov (United States)

Seo, Seongu

2018-01-01

Galactic conformity is an observed phenomenon that galaxies located in the same region have similar properties such as star formation rate, color, gas fraction, and so on. The conformity was first observed among galaxies within in the same halos (“one-halo conformity”). The one-halo conformity can be readily explained by mutual interactions among galaxies within a halo. Recent observations however further witnessed a puzzling connection among galaxies with no direct interaction. In particular, galaxies located within a sphere of ~5 Mpc radius tend to show similarities, even though the galaxies do not share common halos with each other ("two-halo conformity" or “large-scale conformity”). Using a cosmological hydrodynamic simulation, Illustris, we investigate the physical origin of the two-halo conformity and put forward two scenarios. First, back-splash galaxies are likely responsible for the large-scale conformity. They have evolved into red galaxies due to ram-pressure stripping in a given galaxy cluster and happen to reside now within a ~5 Mpc sphere. Second, galaxies in strong tidal field induced by large-scale structure also seem to give rise to the large-scale conformity. The strong tides suppress star formation in the galaxies. We discuss the importance of the large-scale conformity in the context of galaxy evolution.

Innovative Techniques for Large-Scale Collection, Processing, and Storage of Eelgrass (Zostera marina) Seeds

National Research Council Canada - National Science Library

Orth, Robert J; Marion, Scott R

2007-01-01

.... Although methods for hand-collecting, processing and storing eelgrass seeds have advanced to match the scale of collections, the number of seeds collected has limited the scale of restoration efforts...

Identifying influential nodes in large-scale directed networks: the role of clustering.

Science.gov (United States)

Chen, Duan-Bing; Gao, Hui; Lü, Linyuan; Zhou, Tao

2013-01-01

Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node's neighbors but do not directly make use of the interactions among it's neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors' influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR) spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about [Formula: see text] nodes, more than 15 times faster than PageRank.

Identifying influential nodes in large-scale directed networks: the role of clustering.

Directory of Open Access Journals (Sweden)

Duan-Bing Chen

Full Text Available Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node's neighbors but do not directly make use of the interactions among it's neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors' influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about [Formula: see text] nodes, more than 15 times faster than PageRank.

Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering

Science.gov (United States)

Chen, Duan-Bing; Gao, Hui; Lü, Linyuan; Zhou, Tao

2013-01-01

Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node’s neighbors but do not directly make use of the interactions among it’s neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors’ influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR) spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about nodes, more than 15 times faster than PageRank. PMID:24204833

Parameter and State Estimation of Large-Scale Complex Systems Using Python Tools

Directory of Open Access Journals (Sweden)

M. Anushka S. Perera

2015-07-01

Full Text Available This paper discusses the topics related to automating parameter, disturbance and state estimation analysis of large-scale complex nonlinear dynamic systems using free programming tools. For large-scale complex systems, before implementing any state estimator, the system should be analyzed for structural observability and the structural observability analysis can be automated using Modelica and Python. As a result of structural observability analysis, the system may be decomposed into subsystems where some of them may be observable --- with respect to parameter, disturbances, and states --- while some may not. The state estimation process is carried out for those observable subsystems and the optimum number of additional measurements are prescribed for unobservable subsystems to make them observable. In this paper, an industrial case study is considered: the copper production process at Glencore Nikkelverk, Kristiansand, Norway. The copper production process is a large-scale complex system. It is shown how to implement various state estimators, in Python, to estimate parameters and disturbances, in addition to states, based on available measurements.

Parallel clustering algorithm for large-scale biological data sets.

Science.gov (United States)

Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang

2014-01-01

Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies.

Large-scale Intelligent Transporation Systems simulation

Energy Technology Data Exchange (ETDEWEB)

Ewing, T.; Canfield, T.; Hannebutte, U.; Levine, D.; Tentner, A.

1995-06-01

A prototype computer system has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS) capable of running on massively parallel computers and distributed (networked) computer systems. The prototype includes the modelling of instrumented ``smart`` vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces to support human-factors studies. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of our design is that vehicles will be represented by autonomus computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.

GATECloud.net: a platform for large-scale, open-source text processing on the cloud.

Science.gov (United States)

Tablan, Valentin; Roberts, Ian; Cunningham, Hamish; Bontcheva, Kalina

2013-01-28

Cloud computing is increasingly being regarded as a key enabler of the 'democratization of science', because on-demand, highly scalable cloud computing facilities enable researchers anywhere to carry out data-intensive experiments. In the context of natural language processing (NLP), algorithms tend to be complex, which makes their parallelization and deployment on cloud platforms a non-trivial task. This study presents a new, unique, cloud-based platform for large-scale NLP research--GATECloud. net. It enables researchers to carry out data-intensive NLP experiments by harnessing the vast, on-demand compute power of the Amazon cloud. Important infrastructural issues are dealt with by the platform, completely transparently for the researcher: load balancing, efficient data upload and storage, deployment on the virtual machines, security and fault tolerance. We also include a cost-benefit analysis and usage evaluation.

Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

Directory of Open Access Journals (Sweden)

Qiang Liu

2018-05-01

Full Text Available Computing speed is a significant issue of large-scale flood simulations for real-time response to disaster prevention and mitigation. Even today, most of the large-scale flood simulations are generally run on supercomputers due to the massive amounts of data and computations necessary. In this work, a two-dimensional shallow water model based on an unstructured Godunov-type finite volume scheme was proposed for flood simulation. To realize a fast simulation of large-scale floods on a personal computer, a Graphics Processing Unit (GPU-based, high-performance computing method using the OpenACC application was adopted to parallelize the shallow water model. An unstructured data management method was presented to control the data transportation between the GPU and CPU (Central Processing Unit with minimum overhead, and then both computation and data were offloaded from the CPU to the GPU, which exploited the computational capability of the GPU as much as possible. The parallel model was validated using various benchmarks and real-world case studies. The results demonstrate that speed-ups of up to one order of magnitude can be achieved in comparison with the serial model. The proposed parallel model provides a fast and reliable tool with which to quickly assess flood hazards in large-scale areas and, thus, has a bright application prospect for dynamic inundation risk identification and disaster assessment.

Large-scale perspective as a challenge

NARCIS (Netherlands)

Plomp, M.G.A.

2012-01-01

1. Scale forms a challenge for chain researchers: when exactly is something ‘large-scale’? What are the underlying factors (e.g. number of parties, data, objects in the chain, complexity) that determine this? It appears to be a continuum between small- and large-scale, where positioning on that

Algorithm 896: LSA: Algorithms for Large-Scale Optimization

Czech Academy of Sciences Publication Activity Database

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan

2009-01-01

Roč. 36, č. 3 (2009), 16-1-16-29 ISSN 0098-3500 R&D Pro jects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : algorithms * design * large-scale optimization * large-scale nonsmooth optimization * large-scale nonlinear least squares * large-scale nonlinear minimax * large-scale systems of nonlinear equations * sparse pro blems * partially separable pro blems * limited-memory methods * discrete Newton methods * quasi-Newton methods * primal interior-point methods Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.904, year: 2009

Scale interactions in a mixing layer – the role of the large-scale gradients

KAUST Repository

Fiscaletti, D.

2016-02-15

© 2016 Cambridge University Press. The interaction between the large and the small scales of turbulence is investigated in a mixing layer, at a Reynolds number based on the Taylor microscale of , via direct numerical simulations. The analysis is performed in physical space, and the local vorticity root-mean-square (r.m.s.) is taken as a measure of the small-scale activity. It is found that positive large-scale velocity fluctuations correspond to large vorticity r.m.s. on the low-speed side of the mixing layer, whereas, they correspond to low vorticity r.m.s. on the high-speed side. The relationship between large and small scales thus depends on position if the vorticity r.m.s. is correlated with the large-scale velocity fluctuations. On the contrary, the correlation coefficient is nearly constant throughout the mixing layer and close to unity if the vorticity r.m.s. is correlated with the large-scale velocity gradients. Therefore, the small-scale activity appears closely related to large-scale gradients, while the correlation between the small-scale activity and the large-scale velocity fluctuations is shown to reflect a property of the large scales. Furthermore, the vorticity from unfiltered (small scales) and from low pass filtered (large scales) velocity fields tend to be aligned when examined within vortical tubes. These results provide evidence for the so-called \\'scale invariance\\' (Meneveau & Katz, Annu. Rev. Fluid Mech., vol. 32, 2000, pp. 1-32), and suggest that some of the large-scale characteristics are not lost at the small scales, at least at the Reynolds number achieved in the present simulation.

Information collection and processing of dam distortion in digital reservoir system

Science.gov (United States)

Liang, Yong; Zhang, Chengming; Li, Yanling; Wu, Qiulan; Ge, Pingju

2007-06-01

The "digital reservoir" is usually understood as describing the whole reservoir with digital information technology to make it serve the human existence and development furthest. Strictly speaking, the "digital reservoir" is referred to describing vast information of the reservoir in different dimension and space-time by RS, GPS, GIS, telemetry, remote-control and virtual reality technology based on computer, multi-media, large-scale memory and wide-band networks technology for the human existence, development and daily work, life and entertainment. The core of "digital reservoir" is to realize the intelligence and visibility of vast information of the reservoir through computers and networks. The dam is main building of reservoir, whose safety concerns reservoir and people's safety. Safety monitoring is important way guaranteeing the dam's safety, which controls the dam's running through collecting the dam's information concerned and developing trend. Safety monitoring of the dam is the process from collection and processing of initial safety information to forming safety concept in the brain. The paper mainly researches information collection and processing of the dam by digital means.

Large Scale EOF Analysis of Climate Data

Science.gov (United States)

Prabhat, M.; Gittens, A.; Kashinath, K.; Cavanaugh, N. R.; Mahoney, M.

2016-12-01

We present a distributed approach towards extracting EOFs from 3D climate data. We implement the method in Apache Spark, and process multi-TB sized datasets on O(1000-10,000) cores. We apply this method to latitude-weighted ocean temperature data from CSFR, a 2.2 terabyte-sized data set comprising ocean and subsurface reanalysis measurements collected at 41 levels in the ocean, at 6 hour intervals over 31 years. We extract the first 100 EOFs of this full data set and compare to the EOFs computed simply on the surface temperature field. Our analyses provide evidence of Kelvin and Rossy waves and components of large-scale modes of oscillation including the ENSO and PDO that are not visible in the usual SST EOFs. Further, they provide information on the the most influential parts of the ocean, such as the thermocline, that exist below the surface. Work is ongoing to understand the factors determining the depth-varying spatial patterns observed in the EOFs. We will experiment with weighting schemes to appropriately account for the differing depths of the observations. We also plan to apply the same distributed approach to analysis of analysis of 3D atmospheric climatic data sets, including multiple variables. Because the atmosphere changes on a quicker time-scale than the ocean, we expect that the results will demonstrate an even greater advantage to computing 3D EOFs in lieu of 2D EOFs.

Large-scale matrix-handling subroutines 'ATLAS'

International Nuclear Information System (INIS)

Tsunematsu, Toshihide; Takeda, Tatsuoki; Fujita, Keiichi; Matsuura, Toshihiko; Tahara, Nobuo

1978-03-01

Subroutine package ''ATLAS'' has been developed for handling large-scale matrices. The package is composed of four kinds of subroutines, i.e., basic arithmetic routines, routines for solving linear simultaneous equations and for solving general eigenvalue problems and utility routines. The subroutines are useful in large scale plasma-fluid simulations. (auth.)

Integration and segregation of large-scale brain networks during short-term task automatization.

Science.gov (United States)

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-11-03

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

Large-scale solar heat

Energy Technology Data Exchange (ETDEWEB)

Tolonen, J.; Konttinen, P.; Lund, P. [Helsinki Univ. of Technology, Otaniemi (Finland). Dept. of Engineering Physics and Mathematics

1998-12-31

In this project a large domestic solar heating system was built and a solar district heating system was modelled and simulated. Objectives were to improve the performance and reduce costs of a large-scale solar heating system. As a result of the project the benefit/cost ratio can be increased by 40 % through dimensioning and optimising the system at the designing stage. (orig.)

On BLM scale fixing in exclusive processes

International Nuclear Information System (INIS)

Anikin, I.V.; Pire, B.; Szymanowski, L.; Teryaev, O.V.; Wallon, S.

2005-01-01

We discuss the BLM scale fixing procedure in exclusive electroproduction processes in the Bjorken regime with rather large x B . We show that in the case of vector meson production dominated in this case by quark exchange the usual way to apply the BLM method fails due to singularities present in the equations fixing the BLM scale. We argue that the BLM scale should be extracted from the squared amplitudes which are directly related to observables. (orig.)

On BLM scale fixing in exclusive processes

Energy Technology Data Exchange (ETDEWEB)

Anikin, I.V. [JINR, Bogoliubov Laboratory of Theoretical Physics, Dubna (Russian Federation); Universite Paris-Sud, LPT, Orsay (France); Pire, B. [Ecole Polytechnique, CPHT, Palaiseau (France); Szymanowski, L. [Soltan Institute for Nuclear Studies, Warsaw (Poland); Univ. de Liege, Inst. de Physique, Liege (Belgium); Teryaev, O.V. [JINR, Bogoliubov Laboratory of Theoretical Physics, Dubna (Russian Federation); Wallon, S. [Universite Paris-Sud, LPT, Orsay (France)

2005-07-01

We discuss the BLM scale fixing procedure in exclusive electroproduction processes in the Bjorken regime with rather large x{sub B}. We show that in the case of vector meson production dominated in this case by quark exchange the usual way to apply the BLM method fails due to singularities present in the equations fixing the BLM scale. We argue that the BLM scale should be extracted from the squared amplitudes which are directly related to observables. (orig.)

Large-scale multielectrode recording and stimulation of neural activity

International Nuclear Information System (INIS)

Sher, A.; Chichilnisky, E.J.; Dabrowski, W.; Grillo, A.A.; Grivich, M.; Gunning, D.; Hottowy, P.; Kachiguine, S.; Litke, A.M.; Mathieson, K.; Petrusca, D.

2007-01-01

Large circuits of neurons are employed by the brain to encode and process information. How this encoding and processing is carried out is one of the central questions in neuroscience. Since individual neurons communicate with each other through electrical signals (action potentials), the recording of neural activity with arrays of extracellular electrodes is uniquely suited for the investigation of this question. Such recordings provide the combination of the best spatial (individual neurons) and temporal (individual action-potentials) resolutions compared to other large-scale imaging methods. Electrical stimulation of neural activity in turn has two very important applications: it enhances our understanding of neural circuits by allowing active interactions with them, and it is a basis for a large variety of neural prosthetic devices. Until recently, the state-of-the-art in neural activity recording systems consisted of several dozen electrodes with inter-electrode spacing ranging from tens to hundreds of microns. Using silicon microstrip detector expertise acquired in the field of high-energy physics, we created a unique neural activity readout and stimulation framework that consists of high-density electrode arrays, multi-channel custom-designed integrated circuits, a data acquisition system, and data-processing software. Using this framework we developed a number of neural readout and stimulation systems: (1) a 512-electrode system for recording the simultaneous activity of as many as hundreds of neurons, (2) a 61-electrode system for electrical stimulation and readout of neural activity in retinas and brain-tissue slices, and (3) a system with telemetry capabilities for recording neural activity in the intact brain of awake, naturally behaving animals. We will report on these systems, their various applications to the field of neurobiology, and novel scientific results obtained with some of them. We will also outline future directions

Probes of large-scale structure in the Universe

International Nuclear Information System (INIS)

Suto, Yasushi; Gorski, K.; Juszkiewicz, R.; Silk, J.

1988-01-01

Recent progress in observational techniques has made it possible to confront quantitatively various models for the large-scale structure of the Universe with detailed observational data. We develop a general formalism to show that the gravitational instability theory for the origin of large-scale structure is now capable of critically confronting observational results on cosmic microwave background radiation angular anisotropies, large-scale bulk motions and large-scale clumpiness in the galaxy counts. (author)

Contribution of large scale coherence to wind turbine power: A large eddy simulation study in periodic wind farms

Science.gov (United States)

Chatterjee, Tanmoy; Peet, Yulia T.

2018-03-01

Length scales of eddies involved in the power generation of infinite wind farms are studied by analyzing the spectra of the turbulent flux of mean kinetic energy (MKE) from large eddy simulations (LES). Large-scale structures with an order of magnitude bigger than the turbine rotor diameter (D ) are shown to have substantial contribution to wind power. Varying dynamics in the intermediate scales (D -10 D ) are also observed from a parametric study involving interturbine distances and hub height of the turbines. Further insight about the eddies responsible for the power generation have been provided from the scaling analysis of two-dimensional premultiplied spectra of MKE flux. The LES code is developed in a high Reynolds number near-wall modeling framework, using an open-source spectral element code Nek5000, and the wind turbines have been modelled using a state-of-the-art actuator line model. The LES of infinite wind farms have been validated against the statistical results from the previous literature. The study is expected to improve our understanding of the complex multiscale dynamics in the domain of large wind farms and identify the length scales that contribute to the power. This information can be useful for design of wind farm layout and turbine placement that take advantage of the large-scale structures contributing to wind turbine power.

Gauging policy-driven large-scale vegetation restoration programmes under a changing environment: Their effectiveness and socio-economic relationships.

Science.gov (United States)

Li, Ting; Lü, Yihe; Fu, Bojie; Comber, Alexis J; Harris, Paul; Wu, Lianhai

2017-12-31

Large-scale ecological restoration has been widely accepted globally as an effective strategy for combating environmental crises and to facilitate sustainability. Assessing the effectiveness of ecological restoration is vital for researchers, practitioners, and policy-makers. However, few practical tools are available to perform such tasks, particularly for large-scale restoration programmes in complex socio-ecological systems. By taking a "before and after" design, this paper formulates a composite index (E j ) based on comparing the trends of vegetation cover and vegetation productivity to assess ecological restoration effectiveness. The index reveals the dynamic and spatially heterogenic process of vegetation restoration across different time periods, which can be informative for ecological restoration management at regional scales. Effectiveness together with its relationship to socio-economic factors is explored via structural equation modeling for three time periods. The results indicate that the temporal scale is a crucial factor in representing restoration effectiveness, and that the effects of socio-economic factors can also vary with time providing insight for improving restoration effectiveness. A dual-track strategy, which promotes the development of tertiary industry in absorbing the rural labor force together with improvements in agricultural practices, is proposed as a promising strategy for enhancing restoration effectiveness. In this process, timely and long-term ecological restoration monitoring is advocated, so that the success and sustainability of such programmes is ensured, together with more informative decision making where socio-ecological interactions at differing temporal scales are key concerns. Copyright © 2017 Elsevier B.V. All rights reserved.

Large-scale production of UO2 kernels by sol–gel process at INET

International Nuclear Information System (INIS)

Hao, Shaochang; Ma, Jingtao; Zhao, Xingyu; Wang, Yang; Zhou, Xiangwen; Deng, Changsheng

2014-01-01

In order to supply elements (300,000 elements per year) for the Chinese pebble bed modular high temperature gas cooled reactor (HTR-PM), it is necessary to scale up the production of UO 2 kernels to 3–6 kgU per batch. The sol–gel process for preparation of UO 2 kernels have been improved and optimized at Institute of Nuclear and New Energy Technology (INET), Tsinghua University, PR China, and a whole set of facility was designed and constructed based on the process. This report briefly describes the main steps of the process, the key equipment and the production capacities of every step. Six batches of kernels for scale-up verification and four batches of kernels for fuel elements for in-pile irradiation tests have been successfully produced, respectively. The quality of the produced kernels meets the design requirements. The production capacity of the process reaches 3–6 kgU per batch

Large-scale grid management; Storskala Nettforvaltning

Energy Technology Data Exchange (ETDEWEB)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-07-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series.

The influence of control parameter estimation on large scale geomorphological interpretation of pointclouds

Science.gov (United States)

Dorninger, P.; Koma, Z.; Székely, B.

2012-04-01

In recent years, laser scanning, also referred to as LiDAR, has proved to be an important tool for topographic data acquisition. Basically, laser scanning acquires a more or less homogeneously distributed point cloud. These points represent all natural objects like terrain and vegetation as well as man-made objects such as buildings, streets, powerlines, or other constructions. Due to the enormous amount of data provided by current scanning systems capturing up to several hundred thousands of points per second, the immediate application of such point clouds for large scale interpretation and analysis is often prohibitive due to restrictions of the hard- and software infrastructure. To overcome this, numerous methods for the determination of derived products do exist. Commonly, Digital Terrain Models (DTM) or Digital Surface Models (DSM) are derived to represent the topography using a regular grid as datastructure. The obvious advantages are a significant reduction of the amount of data and the introduction of an implicit neighborhood topology enabling the application of efficient post processing methods. The major disadvantages are the loss of 3D information (i.e. overhangs) as well as the loss of information due to the interpolation approach used. We introduced a segmentation approach enabling the determination of planar structures within a given point cloud. It was originally developed for the purpose of building modeling but has proven to be well suited for large scale geomorphological analysis as well. The result is an assignment of the original points to a set of planes. Each plane is represented by its plane parameters. Additionally, numerous quality and quantity parameters are determined (e.g. aspect, slope, local roughness, etc.). In this contribution, we investigate the influence of the control parameters required for the plane segmentation on the geomorphological interpretation of the derived product. The respective control parameters may be determined

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

Science.gov (United States)

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.

Japanese large-scale interferometers

CERN Document Server

Kuroda, K; Miyoki, S; Ishizuka, H; Taylor, C T; Yamamoto, K; Miyakawa, O; Fujimoto, M K; Kawamura, S; Takahashi, R; Yamazaki, T; Arai, K; Tatsumi, D; Ueda, A; Fukushima, M; Sato, S; Shintomi, T; Yamamoto, A; Suzuki, T; Saitô, Y; Haruyama, T; Sato, N; Higashi, Y; Uchiyama, T; Tomaru, T; Tsubono, K; Ando, M; Takamori, A; Numata, K; Ueda, K I; Yoneda, H; Nakagawa, K; Musha, M; Mio, N; Moriwaki, S; Somiya, K; Araya, A; Kanda, N; Telada, S; Sasaki, M; Tagoshi, H; Nakamura, T; Tanaka, T; Ohara, K

2002-01-01

The objective of the TAMA 300 interferometer was to develop advanced technologies for kilometre scale interferometers and to observe gravitational wave events in nearby galaxies. It was designed as a power-recycled Fabry-Perot-Michelson interferometer and was intended as a step towards a final interferometer in Japan. The present successful status of TAMA is presented. TAMA forms a basis for LCGT (large-scale cryogenic gravitational wave telescope), a 3 km scale cryogenic interferometer to be built in the Kamioka mine in Japan, implementing cryogenic mirror techniques. The plan of LCGT is schematically described along with its associated R and D.

Two-scale large deviations for chemical reaction kinetics through second quantization path integral

International Nuclear Information System (INIS)

Li, Tiejun; Lin, Feng

2016-01-01

Motivated by the study of rare events for a typical genetic switching model in systems biology, in this paper we aim to establish the general two-scale large deviations for chemical reaction systems. We build a formal approach to explicitly obtain the large deviation rate functionals for the considered two-scale processes based upon the second quantization path integral technique. We get three important types of large deviation results when the underlying two timescales are in three different regimes. This is realized by singular perturbation analysis to the rate functionals obtained by the path integral. We find that the three regimes possess the same deterministic mean-field limit but completely different chemical Langevin approximations. The obtained results are natural extensions of the classical large volume limit for chemical reactions. We also discuss its implication on the single-molecule Michaelis–Menten kinetics. Our framework and results can be applied to understand general multi-scale systems including diffusion processes. (paper)

Large-scale exact diagonalizations reveal low-momentum scales of nuclei

Science.gov (United States)

Forssén, C.; Carlsson, B. D.; Johansson, H. T.; Sääf, D.; Bansal, A.; Hagen, G.; Papenbrock, T.

2018-03-01

Ab initio methods aim to solve the nuclear many-body problem with controlled approximations. Virtually exact numerical solutions for realistic interactions can only be obtained for certain special cases such as few-nucleon systems. Here we extend the reach of exact diagonalization methods to handle model spaces with dimension exceeding 1010 on a single compute node. This allows us to perform no-core shell model (NCSM) calculations for 6Li in model spaces up to Nmax=22 and to reveal the 4He+d halo structure of this nucleus. Still, the use of a finite harmonic-oscillator basis implies truncations in both infrared (IR) and ultraviolet (UV) length scales. These truncations impose finite-size corrections on observables computed in this basis. We perform IR extrapolations of energies and radii computed in the NCSM and with the coupled-cluster method at several fixed UV cutoffs. It is shown that this strategy enables information gain also from data that is not fully UV converged. IR extrapolations improve the accuracy of relevant bound-state observables for a range of UV cutoffs, thus making them profitable tools. We relate the momentum scale that governs the exponential IR convergence to the threshold energy for the first open decay channel. Using large-scale NCSM calculations we numerically verify this small-momentum scale of finite nuclei.

Success Factors of Large Scale ERP Implementation in Thailand

OpenAIRE

Rotchanakitumnuai; Siriluck

2010-01-01

The objectives of the study are to examine the determinants of ERP implementation success factors of ERP implementation. The result indicates that large scale ERP implementation success consist of eight factors: project management competence, knowledge sharing, ERP system quality , understanding, user involvement, business process re-engineering, top management support, organization readiness.

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

Science.gov (United States)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

Methods for large-scale international studies on ICT in education

NARCIS (Netherlands)

Pelgrum, W.J.; Plomp, T.; Voogt, Joke; Knezek, G.A.

2008-01-01

International comparative assessment is a research method applied for describing and analyzing educational processes and outcomes. They are used to ‘describe the status quo’ in educational systems from an international comparative perspective. This chapter reviews different large scale international

The influence of teacher perceived administration of self-regulated learning on students' motivation and information-processing

NARCIS (Netherlands)

Rozendaal, JS; Minnaert, A; Boekaerts, M

This study investigates the influence of teacher perceived administration of self-regulated learning on students' motivation and information-processing over time. This was done in the context of the Interactive Learning group System (ILS (R)): a large-scale innovation program in Dutch vocational

Local, distributed topology control for large-scale wireless ad-hoc networks

NARCIS (Netherlands)

Nieberg, T.; Hurink, Johann L.

In this document, topology control of a large-scale, wireless network by a distributed algorithm that uses only locally available information is presented. Topology control algorithms adjust the transmission power of wireless nodes to create a desired topology. The algorithm, named local power

Scaling Health Information Systems in Developing Countries

DEFF Research Database (Denmark)

Mengiste, Shegaw Anagaw; Neilsen, Petter

2006-01-01

This article addresses the issues of scaling health information system in the context of developing countries by taking a case study from Ethiopia. Concepts of information infrastructure have been used as an analytical lens to better understand scaling of Health Information systems. More...... specifically, we question the fruitfulness of focusing on not being installed base hostile and suggest focusing on how to be installed base “friendly” by underscoring how the installed base can also be draw upon and shaped by human agents. The paper conceptualizes health information infrastructure (HII......) building as an intertwined process of the evolution of the installed base and the construction activities of human agents. Overall, we argue that it is not only the adverse situation that determines how things develop, but HII builders need to navigate and take into account a wide range of issues related...

Large-scale simulations with distributed computing: Asymptotic scaling of ballistic deposition

International Nuclear Information System (INIS)

Farnudi, Bahman; Vvedensky, Dimitri D

2011-01-01

Extensive kinetic Monte Carlo simulations are reported for ballistic deposition (BD) in (1 + 1) dimensions. The large system sizes L observed for the onset of asymptotic scaling (L ≅ 2 12 ) explains the widespread discrepancies in previous reports for exponents of BD in one and likely in higher dimensions. The exponents obtained directly from our simulations, α = 0.499 ± 0.004 and β = 0.336 ± 0.004, capture the exact values α = 1/2 and β = 1/3 for the one-dimensional Kardar-Parisi-Zhang equation. An analysis of our simulations suggests a criterion for identifying the onset of true asymptotic scaling, which enables a more informed evaluation of exponents for BD in higher dimensions. These simulations were made possible by the Simulation through Social Networking project at the Institute for Advanced Studies in Basic Sciences in 2007, which was re-launched in November 2010.

Adaptive Texture Synthesis for Large Scale City Modeling

Science.gov (United States)

Despine, G.; Colleu, T.

2015-02-01

Large scale city models textured with aerial images are well suited for bird-eye navigation but generally the image resolution does not allow pedestrian navigation. One solution to face this problem is to use high resolution terrestrial photos but it requires huge amount of manual work to remove occlusions. Another solution is to synthesize generic textures with a set of procedural rules and elementary patterns like bricks, roof tiles, doors and windows. This solution may give realistic textures but with no correlation to the ground truth. Instead of using pure procedural modelling we present a method to extract information from aerial images and adapt the texture synthesis to each building. We describe a workflow allowing the user to drive the information extraction and to select the appropriate texture patterns. We also emphasize the importance to organize the knowledge about elementary pattern in a texture catalogue allowing attaching physical information, semantic attributes and to execute selection requests. Roofs are processed according to the detected building material. Façades are first described in terms of principal colours, then opening positions are detected and some window features are computed. These features allow selecting the most appropriate patterns from the texture catalogue. We experimented this workflow on two samples with 20 cm and 5 cm resolution images. The roof texture synthesis and opening detection were successfully conducted on hundreds of buildings. The window characterization is still sensitive to the distortions inherent to the projection of aerial images onto the facades.

Secure Data Aggregation with Fully Homomorphic Encryption in Large-Scale Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Xing Li

2015-07-01

Full Text Available With the rapid development of wireless communication technology, sensor technology, information acquisition and processing technology, sensor networks will finally have a deep influence on all aspects of people’s lives. The battery resources of sensor nodes should be managed efficiently in order to prolong network lifetime in large-scale wireless sensor networks (LWSNs. Data aggregation represents an important method to remove redundancy as well as unnecessary data transmission and hence cut down the energy used in communication. As sensor nodes are deployed in hostile environments, the security of the sensitive information such as confidentiality and integrity should be considered. This paper proposes Fully homomorphic Encryption based Secure data Aggregation (FESA in LWSNs which can protect end-to-end data confidentiality and support arbitrary aggregation operations over encrypted data. In addition, by utilizing message authentication codes (MACs, this scheme can also verify data integrity during data aggregation and forwarding processes so that false data can be detected as early as possible. Although the FHE increase the computation overhead due to its large public key size, simulation results show that it is implementable in LWSNs and performs well. Compared with other protocols, the transmitted data and network overhead are reduced in our scheme.

Secure Data Aggregation with Fully Homomorphic Encryption in Large-Scale Wireless Sensor Networks.

Science.gov (United States)

Li, Xing; Chen, Dexin; Li, Chunyan; Wang, Liangmin

2015-07-03

With the rapid development of wireless communication technology, sensor technology, information acquisition and processing technology, sensor networks will finally have a deep influence on all aspects of people's lives. The battery resources of sensor nodes should be managed efficiently in order to prolong network lifetime in large-scale wireless sensor networks (LWSNs). Data aggregation represents an important method to remove redundancy as well as unnecessary data transmission and hence cut down the energy used in communication. As sensor nodes are deployed in hostile environments, the security of the sensitive information such as confidentiality and integrity should be considered. This paper proposes Fully homomorphic Encryption based Secure data Aggregation (FESA) in LWSNs which can protect end-to-end data confidentiality and support arbitrary aggregation operations over encrypted data. In addition, by utilizing message authentication codes (MACs), this scheme can also verify data integrity during data aggregation and forwarding processes so that false data can be detected as early as possible. Although the FHE increase the computation overhead due to its large public key size, simulation results show that it is implementable in LWSNs and performs well. Compared with other protocols, the transmitted data and network overhead are reduced in our scheme.

Large scale model testing

International Nuclear Information System (INIS)

Brumovsky, M.; Filip, R.; Polachova, H.; Stepanek, S.

1989-01-01

Fracture mechanics and fatigue calculations for WWER reactor pressure vessels were checked by large scale model testing performed using large testing machine ZZ 8000 (with a maximum load of 80 MN) at the SKODA WORKS. The results are described from testing the material resistance to fracture (non-ductile). The testing included the base materials and welded joints. The rated specimen thickness was 150 mm with defects of a depth between 15 and 100 mm. The results are also presented of nozzles of 850 mm inner diameter in a scale of 1:3; static, cyclic, and dynamic tests were performed without and with surface defects (15, 30 and 45 mm deep). During cyclic tests the crack growth rate in the elastic-plastic region was also determined. (author). 6 figs., 2 tabs., 5 refs

Scaling of Health Information Systems in Nigeria and Ethiopia

DEFF Research Database (Denmark)

Mengiste, Shegaw Anagaw; Shaw, Vincent; Braa, Jørn

2007-01-01

Systems Programme in Nigeria and Ethiopia, the interdependencies between three spheres are identified as being important in scaling health information systems. The three spheres that are explored are the volume of data collected, human resource factors and access to technology. We draw on concepts from...... the balance. Three flexible standards are identified as being critical strategies to global health information scaling initiatives, namely an essential data set, a scalable process of information systems collection and collation consisting of gateways between paper based systems and hardware and software...

Why small-scale cannabis growers stay small: five mechanisms that prevent small-scale growers from going large scale.

Science.gov (United States)

Hammersvik, Eirik; Sandberg, Sveinung; Pedersen, Willy

2012-11-01

Over the past 15-20 years, domestic cultivation of cannabis has been established in a number of European countries. New techniques have made such cultivation easier; however, the bulk of growers remain small-scale. In this study, we explore the factors that prevent small-scale growers from increasing their production. The study is based on 1 year of ethnographic fieldwork and qualitative interviews conducted with 45 Norwegian cannabis growers, 10 of whom were growing on a large-scale and 35 on a small-scale. The study identifies five mechanisms that prevent small-scale indoor growers from going large-scale. First, large-scale operations involve a number of people, large sums of money, a high work-load and a high risk of detection, and thus demand a higher level of organizational skills than for small growing operations. Second, financial assets are needed to start a large 'grow-site'. Housing rent, electricity, equipment and nutrients are expensive. Third, to be able to sell large quantities of cannabis, growers need access to an illegal distribution network and knowledge of how to act according to black market norms and structures. Fourth, large-scale operations require advanced horticultural skills to maximize yield and quality, which demands greater skills and knowledge than does small-scale cultivation. Fifth, small-scale growers are often embedded in the 'cannabis culture', which emphasizes anti-commercialism, anti-violence and ecological and community values. Hence, starting up large-scale production will imply having to renegotiate or abandon these values. Going from small- to large-scale cannabis production is a demanding task-ideologically, technically, economically and personally. The many obstacles that small-scale growers face and the lack of interest and motivation for going large-scale suggest that the risk of a 'slippery slope' from small-scale to large-scale growing is limited. Possible political implications of the findings are discussed. Copyright

Distributed large-scale dimensional metrology new insights

CERN Document Server

Franceschini, Fiorenzo; Maisano, Domenico

2011-01-01

Focuses on the latest insights into and challenges of distributed large scale dimensional metrology Enables practitioners to study distributed large scale dimensional metrology independently Includes specific examples of the development of new system prototypes

Design of a Large-scale Three-dimensional Flexible Arrayed Tactile Sensor

Directory of Open Access Journals (Sweden)

Junxiang Ding

2011-01-01

Full Text Available This paper proposes a new type of large-scale three-dimensional flexible arrayed tactile sensor based on conductive rubber. It can be used to detect three-dimensional force information on the continuous surface of the sensor, which realizes a true skin type tactile sensor. The widely used method of liquid rubber injection molding (LIMS method is used for "the overall injection molding" sample preparation. The structure details of staggered nodes and a new decoupling algorithm of force analysis are given. Simulation results show that the sensor based on this structure can achieve flexible measurement of large-scale 3-D tactile sensor arrays.

Development of Best Practices for Large-scale Data Management Infrastructure

NARCIS (Netherlands)

S. Stadtmüller; H.F. Mühleisen (Hannes); C. Bizer; M.L. Kersten (Martin); J.A. de Rijke (Arjen); F.E. Groffen (Fabian); Y. Zhang (Ying); G. Ladwig; A. Harth; M Trampus

2012-01-01

htmlabstractThe amount of available data for processing is constantly increasing and becomes more diverse. We collect our experiences on deploying large-scale data management tools on local-area clusters or cloud infrastructures and provide guidance to use these computing and storage

A new large-scale manufacturing platform for complex biopharmaceuticals.

Science.gov (United States)

Vogel, Jens H; Nguyen, Huong; Giovannini, Roberto; Ignowski, Jolene; Garger, Steve; Salgotra, Anil; Tom, Jennifer

2012-12-01

Complex biopharmaceuticals, such as recombinant blood coagulation factors, are addressing critical medical needs and represent a growing multibillion-dollar market. For commercial manufacturing of such, sometimes inherently unstable, molecules it is important to minimize product residence time in non-ideal milieu in order to obtain acceptable yields and consistently high product quality. Continuous perfusion cell culture allows minimization of residence time in the bioreactor, but also brings unique challenges in product recovery, which requires innovative solutions. In order to maximize yield, process efficiency, facility and equipment utilization, we have developed, scaled-up and successfully implemented a new integrated manufacturing platform in commercial scale. This platform consists of a (semi-)continuous cell separation process based on a disposable flow path and integrated with the upstream perfusion operation, followed by membrane chromatography on large-scale adsorber capsules in rapid cycling mode. Implementation of the platform at commercial scale for a new product candidate led to a yield improvement of 40% compared to the conventional process technology, while product quality has been shown to be more consistently high. Over 1,000,000 L of cell culture harvest have been processed with 100% success rate to date, demonstrating the robustness of the new platform process in GMP manufacturing. While membrane chromatography is well established for polishing in flow-through mode, this is its first commercial-scale application for bind/elute chromatography in the biopharmaceutical industry and demonstrates its potential in particular for manufacturing of potent, low-dose biopharmaceuticals. Copyright © 2012 Wiley Periodicals, Inc.

SCALE INTERACTION IN A MIXING LAYER. THE ROLE OF THE LARGE-SCALE GRADIENTS

KAUST Repository

Fiscaletti, Daniele; Attili, Antonio; Bisetti, Fabrizio; Elsinga, Gerrit E.

2015-01-01

from physical considerations we would expect the scales to interact in a qualitatively similar way within the flow and across different turbulent flows. Therefore, instead of the large-scale fluctuations, the large-scale gradients modulation of the small scales has been additionally investigated.

THE IMPORTANCE OF INFORMATION SYSTEMS IN THE MANAGEMENT AND PROCESSING OF LARGE DATA VOLUMES IN PUBLIC INSTITUTIONS

Directory of Open Access Journals (Sweden)

CARINA-ELENA STEGĂROIU

2016-12-01

Full Text Available Under a computerized society, technological resources become a source of identification for any community, institution or country. Globalization of information becomes a reality, all the resources having entered into a relationship of subordination with the World Wide Web, the information highways and the Internet. "Information technology - with its most important branch, data management computer science - enters a new era, in which the computer leads to the benefit of a navigable and transparent communication space, focusing on information". Therefore, in an information-based economy, information systems have been established which, based on management systems through the methods of algebra, with applications in economic engineering, have come to manage and process large volumes of data, especially in public institutions. Consequently, the Ministry of Public Affairs has implemented the “Increasing the public administration’s responsibility by modernising the information systems for generating the reports of the financial situations of public institutions” project (FOREXEBUG”, cod SMIS 34952, for which it received in 2012 non-refundable financing from the European Social Fund through the Operational Program for Developing the Administrative Capacity 2007-2013, based on which this paper will analyse the usefulness of implementing such a program in public institutions. Such a system aims to achieve a new form of reporting of budget execution and financial statements (including information related to legal commitments submitted monthly by each public institution in electronic, standardized, secure form, with increasing the reliability of data collected by cross-checking data from the treasury and providing reliable information for use by the Ministry of Finance, public institutions, other relevant institutions and the public, both at the level of detail and the consolidation possibilities at various levels, in parallel with their use for

Large transverse momentum hadronic processes

International Nuclear Information System (INIS)

Darriulat, P.

1977-01-01

The possible relations between deep inelastic leptoproduction and large transverse momentum (psub(t)) processes in hadronic collisions are usually considered in the framework of the quark-parton picture. Experiments observing the structure of the final state in proton-proton collisions producing at least one large transverse momentum particle have led to the following conclusions: a large fraction of produced particles are uneffected by the large psub(t) process. The other products are correlated to the large psub(t) particle. Depending upon the sign of scalar product they can be separated into two groups of ''towards-movers'' and ''away-movers''. The experimental evidence are reviewed favouring such a picture and the properties are discussed of each of three groups (underlying normal event, towards-movers and away-movers). Some phenomenological interpretations are presented. The exact nature of away- and towards-movers must be further investigated. Their apparent jet structure has to be confirmed. Angular correlations between leading away and towards movers are very informative. Quantum number flow, both within the set of away and towards-movers, and between it and the underlying normal event, are predicted to behave very differently in different models

How Did the Information Flow in the #AlphaGo Hashtag Network? A Social Network Analysis of the Large-Scale Information Network on Twitter.

Science.gov (United States)

Kim, Jinyoung

2017-12-01

As it becomes common for Internet users to use hashtags when posting and searching information on social media, it is important to understand who builds a hashtag network and how information is circulated within the network. This article focused on unlocking the potential of the #AlphaGo hashtag network by addressing the following questions. First, the current study examined whether traditional opinion leadership (i.e., the influentials hypothesis) or grassroot participation by the public (i.e., the interpersonal hypothesis) drove dissemination of information in the hashtag network. Second, several unique patterns of information distribution by key users were identified. Finally, the association between attributes of key users who exerted great influence on information distribution (i.e., the number of followers and follows) and their central status in the network was tested. To answer the proffered research questions, a social network analysis was conducted using a large-scale hashtag network data set from Twitter (n = 21,870). The results showed that the leading actors in the network were actively receiving information from their followers rather than serving as intermediaries between the original information sources and the public. Moreover, the leading actors played several roles (i.e., conversation starters, influencers, and active engagers) in the network. Furthermore, the number of their follows and followers were significantly associated with their central status in the hashtag network. Based on the results, the current research explained how the information was exchanged in the hashtag network by proposing the reciprocal model of information flow.

Large-Scale Production of Nanographite by Tube-Shear Exfoliation in Water.

Directory of Open Access Journals (Sweden)

Nicklas Blomquist

Full Text Available The number of applications based on graphene, few-layer graphene, and nanographite is rapidly increasing. A large-scale process for production of these materials is critically needed to achieve cost-effective commercial products. Here, we present a novel process to mechanically exfoliate industrial quantities of nanographite from graphite in an aqueous environment with low energy consumption and at controlled shear conditions. This process, based on hydrodynamic tube shearing, produced nanometer-thick and micrometer-wide flakes of nanographite with a production rate exceeding 500 gh-1 with an energy consumption about 10 Whg-1. In addition, to facilitate large-area coating, we show that the nanographite can be mixed with nanofibrillated cellulose in the process to form highly conductive, robust and environmentally friendly composites. This composite has a sheet resistance below 1.75 Ω/sq and an electrical resistivity of 1.39×10-4 Ωm and may find use in several applications, from supercapacitors and batteries to printed electronics and solar cells. A batch of 100 liter was processed in less than 4 hours. The design of the process allow scaling to even larger volumes and the low energy consumption indicates a low-cost process.

SHAPE FROM TEXTURE USING LOCALLY SCALED POINT PROCESSES

Directory of Open Access Journals (Sweden)

Eva-Maria Didden

2015-09-01

Full Text Available Shape from texture refers to the extraction of 3D information from 2D images with irregular texture. This paper introduces a statistical framework to learn shape from texture where convex texture elements in a 2D image are represented through a point process. In a first step, the 2D image is preprocessed to generate a probability map corresponding to an estimate of the unnormalized intensity of the latent point process underlying the texture elements. The latent point process is subsequently inferred from the probability map in a non-parametric, model free manner. Finally, the 3D information is extracted from the point pattern by applying a locally scaled point process model where the local scaling function represents the deformation caused by the projection of a 3D surface onto a 2D image.

``Large''- vs Small-scale friction control in turbulent channel flow

Science.gov (United States)

Canton, Jacopo; Örlü, Ramis; Chin, Cheng; Schlatter, Philipp

2017-11-01

We reconsider the ``large-scale'' control scheme proposed by Hussain and co-workers (Phys. Fluids 10, 1049-1051 1998 and Phys. Rev. Fluids, 2, 62601 2017), using new direct numerical simulations (DNS). The DNS are performed in a turbulent channel at friction Reynolds number Reτ of up to 550 in order to eliminate low-Reynolds-number effects. The purpose of the present contribution is to re-assess this control method in the light of more modern developments in the field, in particular also related to the discovery of (very) large-scale motions. The goals of the paper are as follows: First, we want to better characterise the physics of the control, and assess what external contribution (vortices, forcing, wall motion) are actually needed. Then, we investigate the optimal parameters and, finally, determine which aspects of this control technique actually scale in outer units and can therefore be of use in practical applications. In addition to discussing the mentioned drag-reduction effects, the present contribution will also address the potential effect of the naturally occurring large-scale motions on frictional drag, and give indications on the physical processes for potential drag reduction possible at all Reynolds numbers.

Semihard processes with BLM renormalization scale setting

Energy Technology Data Exchange (ETDEWEB)

Caporale, Francesco [Instituto de Física Teórica UAM/CSIC, Nicolás Cabrera 15 and U. Autónoma de Madrid, E-28049 Madrid (Spain); Ivanov, Dmitry Yu. [Sobolev Institute of Mathematics and Novosibirsk State University, 630090 Novosibirsk (Russian Federation); Murdaca, Beatrice; Papa, Alessandro [Dipartimento di Fisica, Università della Calabria, and Istituto Nazionale di Fisica Nucleare, Gruppo collegato di Cosenza, Arcavacata di Rende, I-87036 Cosenza (Italy)

2015-04-10

We apply the BLM scale setting procedure directly to amplitudes (cross sections) of several semihard processes. It is shown that, due to the presence of β{sub 0}-terms in the NLA results for the impact factors, the obtained optimal renormalization scale is not universal, but depends both on the energy and on the process in question. We illustrate this general conclusion considering the following semihard processes: (i) inclusive production of two forward high-p{sub T} jets separated by large interval in rapidity (Mueller-Navelet jets); (ii) high-energy behavior of the total cross section for highly virtual photons; (iii) forward amplitude of the production of two light vector mesons in the collision of two virtual photons.

Large-scale grain growth in the solid-state process: From "Abnormal" to "Normal"

Science.gov (United States)

Jiang, Minhong; Han, Shengnan; Zhang, Jingwei; Song, Jiageng; Hao, Chongyan; Deng, Manjiao; Ge, Lingjing; Gu, Zhengfei; Liu, Xinyu

2018-02-01

Abnormal grain growth (AGG) has been a common phenomenon during the ceramic or metallurgy processing since prehistoric times. However, usually it had been very difficult to grow big single crystal (centimeter scale over) by using the AGG method due to its so-called occasionality. Based on the AGG, a solid-state crystal growth (SSCG) method was developed. The greatest advantages of the SSCG technology are the simplicity and cost-effectiveness of the technique. But the traditional SSCG technology is still uncontrollable. This article first summarizes the history and current status of AGG, and then reports recent technical developments from AGG to SSCG, and further introduces a new seed-free, solid-state crystal growth (SFSSCG) technology. This SFSSCG method allows us to repeatedly and controllably fabricate large-scale single crystals with appreciable high quality and relatively stable chemical composition at a relatively low temperature, at least in (K0.5Na0.5)NbO3(KNN) and Cu-Al-Mn systems. In this sense, the exaggerated grain growth is no longer 'Abnormal' but 'Normal' since it is able to be artificially controllable and repeated now. This article also provides a crystal growth model to qualitatively explain the mechanism of SFSSCG for KNN system. Compared with the traditional melt and high temperature solution growth methods, the SFSSCG method has the advantages of low energy consumption, low investment, simple technique, composition homogeneity overcoming the issues with incongruent melting and high volatility. This SFSSCG could be helpful for improving the mechanical and physical properties of single crystals, which should be promising for industrial applications.

Trends in large-scale testing of reactor structures

International Nuclear Information System (INIS)

Blejwas, T.E.

2003-01-01

Large-scale tests of reactor structures have been conducted at Sandia National Laboratories since the late 1970s. This paper describes a number of different large-scale impact tests, pressurization tests of models of containment structures, and thermal-pressure tests of models of reactor pressure vessels. The advantages of large-scale testing are evident, but cost, in particular limits its use. As computer models have grown in size, such as number of degrees of freedom, the advent of computer graphics has made possible very realistic representation of results - results that may not accurately represent reality. A necessary condition to avoiding this pitfall is the validation of the analytical methods and underlying physical representations. Ironically, the immensely larger computer models sometimes increase the need for large-scale testing, because the modeling is applied to increasing more complex structural systems and/or more complex physical phenomena. Unfortunately, the cost of large-scale tests is a disadvantage that will likely severely limit similar testing in the future. International collaborations may provide the best mechanism for funding future programs with large-scale tests. (author)

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study.

Science.gov (United States)

Dolz, Jose; Desrosiers, Christian; Ben Ayed, Ismail

2018-04-15

This study investigates a 3D and fully convolutional neural network (CNN) for subcortical brain structure segmentation in MRI. 3D CNN architectures have been generally avoided due to their computational and memory requirements during inference. We address the problem via small kernels, allowing deeper architectures. We further model both local and global context by embedding intermediate-layer outputs in the final prediction, which encourages consistency between features extracted at different scales and embeds fine-grained information directly in the segmentation process. Our model is efficiently trained end-to-end on a graphics processing unit (GPU), in a single stage, exploiting the dense inference capabilities of fully CNNs. We performed comprehensive experiments over two publicly available datasets. First, we demonstrate a state-of-the-art performance on the ISBR dataset. Then, we report a large-scale multi-site evaluation over 1112 unregistered subject datasets acquired from 17 different sites (ABIDE dataset), with ages ranging from 7 to 64 years, showing that our method is robust to various acquisition protocols, demographics and clinical factors. Our method yielded segmentations that are highly consistent with a standard atlas-based approach, while running in a fraction of the time needed by atlas-based methods and avoiding registration/normalization steps. This makes it convenient for massive multi-site neuroanatomical imaging studies. To the best of our knowledge, our work is the first to study subcortical structure segmentation on such large-scale and heterogeneous data. Copyright © 2017 Elsevier Inc. All rights reserved.

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

Science.gov (United States)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Large - scale Rectangular Ruler Automated Verification Device

Science.gov (United States)

Chen, Hao; Chang, Luping; Xing, Minjian; Xie, Xie

2018-03-01

This paper introduces a large-scale rectangular ruler automated verification device, which consists of photoelectric autocollimator and self-designed mechanical drive car and data automatic acquisition system. The design of mechanical structure part of the device refer to optical axis design, drive part, fixture device and wheel design. The design of control system of the device refer to hardware design and software design, and the hardware mainly uses singlechip system, and the software design is the process of the photoelectric autocollimator and the automatic data acquisition process. This devices can automated achieve vertical measurement data. The reliability of the device is verified by experimental comparison. The conclusion meets the requirement of the right angle test procedure.

Idealised modelling of storm surges in large-scale coastal basins

NARCIS (Netherlands)

Chen, Wenlong

2015-01-01

Coastal areas around the world are frequently attacked by various types of storms, threatening human life and property. This study aims to understand storm surge processes in large-scale coastal basins, particularly focusing on the influences of geometry, topography and storm characteristics on the

Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles

Directory of Open Access Journals (Sweden)

Ming Lei

2012-01-01

Full Text Available A new formation framework of large-scale intelligent autonomous vehicles is developed, which can realize complex formations while reducing data exchange. Using the proposed hierarchy formation method and the automatic dividing algorithm, vehicles are automatically divided into leaders and followers by exchanging information via wireless network at initial time. Then, leaders form formation geometric shape by global formation information and followers track their own virtual leaders to form line formation by local information. The formation control laws of leaders and followers are designed based on consensus algorithms. Moreover, collision-avoiding problems are considered and solved using artificial potential functions. Finally, a simulation example that consists of 25 vehicles shows the effectiveness of theory.

An efficient method based on the uniformity principle for synthesis of large-scale heat exchanger networks

International Nuclear Information System (INIS)

Zhang, Chunwei; Cui, Guomin; Chen, Shang

2016-01-01

Highlights: • Two dimensionless uniformity factors are presented to heat exchange network. • The grouping of process streams reduces the computational complexity of large-scale HENS problems. • The optimal sub-network can be obtained by Powell particle swarm optimization algorithm. • The method is illustrated by a case study involving 39 process streams, with a better solution. - Abstract: The optimal design of large-scale heat exchanger networks is a difficult task due to the inherent non-linear characteristics and the combinatorial nature of heat exchangers. To solve large-scale heat exchanger network synthesis (HENS) problems, two dimensionless uniformity factors to describe the heat exchanger network (HEN) uniformity in terms of the temperature difference and the accuracy of process stream grouping are deduced. Additionally, a novel algorithm that combines deterministic and stochastic optimizations to obtain an optimal sub-network with a suitable heat load for a given group of streams is proposed, and is named the Powell particle swarm optimization (PPSO). As a result, the synthesis of large-scale heat exchanger networks is divided into two corresponding sub-parts, namely, the grouping of process streams and the optimization of sub-networks. This approach reduces the computational complexity and increases the efficiency of the proposed method. The robustness and effectiveness of the proposed method are demonstrated by solving a large-scale HENS problem involving 39 process streams, and the results obtained are better than those previously published in the literature.

Evaluating Unmanned Aerial Platforms for Cultural Heritage Large Scale Mapping

Science.gov (United States)

Georgopoulos, A.; Oikonomou, C.; Adamopoulos, E.; Stathopoulou, E. K.

2016-06-01

When it comes to large scale mapping of limited areas especially for cultural heritage sites, things become critical. Optical and non-optical sensors are developed to such sizes and weights that can be lifted by such platforms, like e.g. LiDAR units. At the same time there is an increase in emphasis on solutions that enable users to get access to 3D information faster and cheaper. Considering the multitude of platforms, cameras and the advancement of algorithms in conjunction with the increase of available computing power this challenge should and indeed is further investigated. In this paper a short review of the UAS technologies today is attempted. A discussion follows as to their applicability and advantages, depending on their specifications, which vary immensely. The on-board cameras available are also compared and evaluated for large scale mapping. Furthermore a thorough analysis, review and experimentation with different software implementations of Structure from Motion and Multiple View Stereo algorithms, able to process such dense and mostly unordered sequence of digital images is also conducted and presented. As test data set, we use a rich optical and thermal data set from both fixed wing and multi-rotor platforms over an archaeological excavation with adverse height variations and using different cameras. Dense 3D point clouds, digital terrain models and orthophotos have been produced and evaluated for their radiometric as well as metric qualities.

Mirror dark matter and large scale structure

International Nuclear Information System (INIS)

Ignatiev, A.Yu.; Volkas, R.R.

2003-01-01

Mirror matter is a dark matter candidate. In this paper, we reexamine the linear regime of density perturbation growth in a universe containing mirror dark matter. Taking adiabatic scale-invariant perturbations as the input, we confirm that the resulting processed power spectrum is richer than for the more familiar cases of cold, warm and hot dark matter. The new features include a maximum at a certain scale λ max , collisional damping below a smaller characteristic scale λ S ' , with oscillatory perturbations between the two. These scales are functions of the fundamental parameters of the theory. In particular, they decrease for decreasing x, the ratio of the mirror plasma temperature to that of the ordinary. For x∼0.2, the scale λ max becomes galactic. Mirror dark matter therefore leads to bottom-up large scale structure formation, similar to conventional cold dark matter, for x(less-or-similar sign)0.2. Indeed, the smaller the value of x, the closer mirror dark matter resembles standard cold dark matter during the linear regime. The differences pertain to scales smaller than λ S ' in the linear regime, and generally in the nonlinear regime because mirror dark matter is chemically complex and to some extent dissipative. Lyman-α forest data and the early reionization epoch established by WMAP may hold the key to distinguishing mirror dark matter from WIMP-style cold dark matter

Dose monitoring in large-scale flowing aqueous media

International Nuclear Information System (INIS)

Kuruca, C.N.

1995-01-01

The Miami Electron Beam Research Facility (EBRF) has been in operation for six years. The EBRF houses a 1.5 MV, 75 KW DC scanned electron beam. Experiments have been conducted to evaluate the effectiveness of high-energy electron irradiation in the removal of toxic organic chemicals from contaminated water and the disinfection of various wastewater streams. The large-scale plant operates at approximately 450 L/min (120 gal/min). The radiation dose absorbed by the flowing aqueous streams is estimated by measuring the difference in water temperature before and after it passes in front of the beam. Temperature measurements are made using resistance temperature devices (RTDs) and recorded by computer along with other operating parameters. Estimated dose is obtained from the measured temperature differences using the specific heat of water. This presentation will discuss experience with this measurement system, its application to different water presentation devices, sources of error, and the advantages and disadvantages of its use in large-scale process applications

Charm production and mass scales in deep inelastic processes

International Nuclear Information System (INIS)

Close, F.E.; Scott, D.M.; Sivers, D.

1976-07-01

Because of their large mass, the production of charmed particles offers the possibility of new insight into fundamental dynamics. An approach to deep inelastic processes is discussed in which Generalized Vector Meson Dominance is used to extend parton model results away from the strict Bjorken scaling limit into regions where mass scales play an important role. The processes e + e - annihilation, photoproduction, deep inelastic leptoproduction, photon-photon scattering and the production of lepton pairs in hadronic collisions are discussed. The GCMD approach provides a reasonably unified framework and makes specific predictions concerning the way in which these reactions reflect an underlying flavour symmetry, broken by large mass differences. (author)

Numerical and experimental simulation of accident processes using KMS large-scale test facility under the program of training university students for nuclear power industry

International Nuclear Information System (INIS)

Aniskevich, Yu.N.

2005-01-01

The KMS large-scale test facility is being constructed at NITI site and designed to model accident processes in VVER reactor plants and provide experimental data for safety analysis of both existing and future NPPs. The KMS phase I is at the completion stage. This is a containment model of 2000 m3 volume intended for experimentally simulating heat and mass transfers of steam-gas mixtures and aerosols inside containment. The KMS phase II will incorporate a reactor model (1:27 scale) and be used for analysing a number of events including primary and secondary LOCA. The KMS program for background training of university students in the nuclear field will include preparation and conduction of experiments, analysis of experiment data. The KMS program for background training of university students in nuclear will include: participation in the development and application of experiment procedures, preparation and carrying out experiments; carrying out pretest and post-test calculations with different computer codes; on-the-job training as operators of experiment scenarios; training of specialists in measurement and information acquisition technologies. (author)

Inducing a health-promoting change process within an organization: the effectiveness of a large-scale intervention on social capital, openness, and autonomous motivation toward health.

Science.gov (United States)

van Scheppingen, Arjella R; de Vroome, Ernest M M; Ten Have, Kristin C J M; Bos, Ellen H; Zwetsloot, Gerard I J M; van Mechelen, W

2014-11-01

To examine the effectiveness of an organizational large-scale intervention applied to induce a health-promoting organizational change process. A quasi-experimental, "as-treated" design was used. Regression analyses on data of employees of a Dutch dairy company (n = 324) were used to examine the effects on bonding social capital, openness, and autonomous motivation toward health and on employees' lifestyle, health, vitality, and sustainable employability. Also, the sensitivity of the intervention components was examined. Intervention effects were found for bonding social capital, openness toward health, smoking, healthy eating, and sustainable employability. The effects were primarily attributable to the intervention's dialogue component. The change process initiated by the large-scale intervention contributed to a social climate in the workplace that promoted health and ownership toward health. The study confirms the relevance of collective change processes for health promotion.

Towards large-scale plasma-assisted synthesis of nanowires

Science.gov (United States)

Cvelbar, U.

2011-05-01

Large quantities of nanomaterials, e.g. nanowires (NWs), are needed to overcome the high market price of nanomaterials and make nanotechnology widely available for general public use and applications to numerous devices. Therefore, there is an enormous need for new methods or routes for synthesis of those nanostructures. Here plasma technologies for synthesis of NWs, nanotubes, nanoparticles or other nanostructures might play a key role in the near future. This paper presents a three-dimensional problem of large-scale synthesis connected with the time, quantity and quality of nanostructures. Herein, four different plasma methods for NW synthesis are presented in contrast to other methods, e.g. thermal processes, chemical vapour deposition or wet chemical processes. The pros and cons are discussed in detail for the case of two metal oxides: iron oxide and zinc oxide NWs, which are important for many applications.

Large Scale Computations in Air Pollution Modelling

DEFF Research Database (Denmark)

Zlatev, Z.; Brandt, J.; Builtjes, P. J. H.

Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...

Large-scale digitizer system, analog converters

International Nuclear Information System (INIS)

Althaus, R.F.; Lee, K.L.; Kirsten, F.A.; Wagner, L.J.

1976-10-01

Analog to digital converter circuits that are based on the sharing of common resources, including those which are critical to the linearity and stability of the individual channels, are described. Simplicity of circuit composition is valued over other more costly approaches. These are intended to be applied in a large-scale processing and digitizing system for use with high-energy physics detectors such as drift-chambers or phototube-scintillator arrays. Signal distribution techniques are of paramount importance in maintaining adequate signal-to-noise ratio. Noise in both amplitude and time-jitter senses is held sufficiently low so that conversions with 10-bit charge resolution and 12-bit time resolution are achieved

Restoring large-scale brain networks in PTSD and related disorders: a proposal for neuroscientifically-informed treatment interventions

Directory of Open Access Journals (Sweden)

Ruth A. Lanius

2015-03-01

Full Text Available Background: Three intrinsic connectivity networks in the brain, namely the central executive, salience, and default mode networks, have been identified as crucial to the understanding of higher cognitive functioning, and the functioning of these networks has been suggested to be impaired in psychopathology, including posttraumatic stress disorder (PTSD. Objective: 1 To describe three main large-scale networks of the human brain; 2 to discuss the functioning of these neural networks in PTSD and related symptoms; and 3 to offer hypotheses for neuroscientifically-informed interventions based on treating the abnormalities observed in these neural networks in PTSD and related disorders. Method: Literature relevant to this commentary was reviewed. Results: Increasing evidence for altered functioning of the central executive, salience, and default mode networks in PTSD has been demonstrated. We suggest that each network is associated with specific clinical symptoms observed in PTSD, including cognitive dysfunction (central executive network, increased and decreased arousal/interoception (salience network, and an altered sense of self (default mode network. Specific testable neuroscientifically-informed treatments aimed to restore each of these neural networks and related clinical dysfunction are proposed. Conclusions: Neuroscientifically-informed treatment interventions will be essential to future research agendas aimed at targeting specific PTSD and related symptoms.

Formation of Large-scale Coronal Loops Interconnecting Two Active Regions through Gradual Magnetic Reconnection and an Associated Heating Process

Science.gov (United States)

Du, Guohui; Chen, Yao; Zhu, Chunming; Liu, Chang; Ge, Lili; Wang, Bing; Li, Chuanyang; Wang, Haimin

2018-06-01

Coronal loops interconnecting two active regions (ARs), called interconnecting loops (ILs), are prominent large-scale structures in the solar atmosphere. They carry a significant amount of magnetic flux and therefore are considered to be an important element of the solar dynamo process. Earlier observations showed that eruptions of ILs are an important source of CMEs. It is generally believed that ILs are formed through magnetic reconnection in the high corona (>150″–200″), and several scenarios have been proposed to explain their brightening in soft X-rays (SXRs). However, the detailed IL formation process has not been fully explored, and the associated energy release in the corona still remains unresolved. Here, we report the complete formation process of a set of ILs connecting two nearby ARs, with successive observations by STEREO-A on the far side of the Sun and by SDO and Hinode on the Earth side. We conclude that ILs are formed by gradual reconnection high in the corona, in line with earlier postulations. In addition, we show evidence that ILs brighten in SXRs and EUVs through heating at or close to the reconnection site in the corona (i.e., through the direct heating process of reconnection), a process that has been largely overlooked in earlier studies of ILs.

Large-Scale 3D Printing: The Way Forward

Science.gov (United States)

Jassmi, Hamad Al; Najjar, Fady Al; Ismail Mourad, Abdel-Hamid

2018-03-01

Research on small-scale 3D printing has rapidly evolved, where numerous industrial products have been tested and successfully applied. Nonetheless, research on large-scale 3D printing, directed to large-scale applications such as construction and automotive manufacturing, yet demands a great a great deal of efforts. Large-scale 3D printing is considered an interdisciplinary topic and requires establishing a blended knowledge base from numerous research fields including structural engineering, materials science, mechatronics, software engineering, artificial intelligence and architectural engineering. This review article summarizes key topics of relevance to new research trends on large-scale 3D printing, particularly pertaining (1) technological solutions of additive construction (i.e. the 3D printers themselves), (2) materials science challenges, and (3) new design opportunities.

Graph processing platforms at scale: practices and experiences

Energy Technology Data Exchange (ETDEWEB)

Lim, Seung-Hwan [ORNL; Lee, Sangkeun (Matt) [ORNL; Brown, Tyler C [ORNL; Sukumar, Sreenivas R [ORNL; Ganesh, Gautam [ORNL

2015-01-01

Graph analysis unveils hidden associations of data in many phenomena and artifacts, such as road network, social networks, genomic information, and scientific collaboration. Unfortunately, a wide diversity in the characteristics of graphs and graph operations make it challenging to find a right combination of tools and implementation of algorithms to discover desired knowledge from the target data set. This study presents an extensive empirical study of three representative graph processing platforms: Pegasus, GraphX, and Urika. Each system represents a combination of options in data model, processing paradigm, and infrastructure. We benchmarked each platform using three popular graph operations, degree distribution, connected components, and PageRank over a variety of real-world graphs. Our experiments show that each graph processing platform shows different strength, depending the type of graph operations. While Urika performs the best in non-iterative operations like degree distribution, GraphX outputforms iterative operations like connected components and PageRank. In addition, we discuss challenges to optimize the performance of each platform over large scale real world graphs.

Advances in Large-Scale Solar Heating and Long Term Storage in Denmark

DEFF Research Database (Denmark)

Heller, Alfred

2000-01-01

According to (the) information from the European Large-Scale Solar Heating Network, (See http://www.hvac.chalmers.se/cshp/), the area of installed solar collectors for large-scale application is in Europe, approximately 8 mill m2, corresponding to about 4000 MW thermal power. The 11 plants...... the last 10 years and the corresponding cost per collector area for the final installed plant is kept constant, even so the solar production is increased. Unfortunately large-scale seasonal storage was not able to keep up with the advances in solar technology, at least for pit water and gravel storage...... of the total 51 plants are equipped with long-term storage. In Denmark, 7 plants are installed, comprising of approx. 18,000-m2 collector area with new plants planned. The development of these plants and the involved technologies will be presented in this paper, with a focus on the improvements for Danish...

Growth Limits in Large Scale Networks

DEFF Research Database (Denmark)

Knudsen, Thomas Phillip

limitations. The rising complexity of network management with the convergence of communications platforms is shown as problematic for both automatic management feasibility and for manpower resource management. In the fourth step the scope is extended to include the present society with the DDN project as its......The Subject of large scale networks is approached from the perspective of the network planner. An analysis of the long term planning problems is presented with the main focus on the changing requirements for large scale networks and the potential problems in meeting these requirements. The problems...... the fundamental technological resources in network technologies are analysed for scalability. Here several technological limits to continued growth are presented. The third step involves a survey of major problems in managing large scale networks given the growth of user requirements and the technological...

Accelerating sustainability in large-scale facilities

CERN Multimedia

Marina Giampietro

2011-01-01

Scientific research centres and large-scale facilities are intrinsically energy intensive, but how can big science improve its energy management and eventually contribute to the environmental cause with new cleantech? CERN’s commitment to providing tangible answers to these questions was sealed in the first workshop on energy management for large scale scientific infrastructures held in Lund, Sweden, on the 13-14 October.   Participants at the energy management for large scale scientific infrastructures workshop. The workshop, co-organised with the European Spallation Source (ESS) and  the European Association of National Research Facilities (ERF), tackled a recognised need for addressing energy issues in relation with science and technology policies. It brought together more than 150 representatives of Research Infrastrutures (RIs) and energy experts from Europe and North America. “Without compromising our scientific projects, we can ...

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

Science.gov (United States)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

GPU-accelerated brain connectivity reconstruction and visualization in large-scale electron micrographs

KAUST Repository

Jeong, Wonki

2011-01-01

This chapter introduces a GPU-accelerated interactive, semiautomatic axon segmentation and visualization system. Two challenging problems have been addressed: the interactive 3D axon segmentation and the interactive 3D image filtering and rendering of implicit surfaces. The reconstruction of neural connections to understand the function of the brain is an emerging and active research area in neuroscience. With the advent of high-resolution scanning technologies, such as 3D light microscopy and electron microscopy (EM), reconstruction of complex 3D neural circuits from large volumes of neural tissues has become feasible. Among them, only EM data can provide sufficient resolution to identify synapses and to resolve extremely narrow neural processes. These high-resolution, large-scale datasets pose challenging problems, for example, how to process and manipulate large datasets to extract scientifically meaningful information using a compact representation in a reasonable processing time. The running time of the multiphase level set segmentation method has been measured on the CPU and GPU. The CPU version is implemented using the ITK image class and the ITK distance transform filter. The numerical part of the CPU implementation is similar to the GPU implementation for fair comparison. The main focus of this chapter is introducing the GPU algorithms and their implementation details, which are the core components of the interactive segmentation and visualization system. © 2011 Copyright © 2011 NVIDIA Corporation and Wen-mei W. Hwu Published by Elsevier Inc. All rights reserved..

Large scale reflood test

International Nuclear Information System (INIS)

Hirano, Kemmei; Murao, Yoshio

1980-01-01

The large-scale reflood test with a view to ensuring the safety of light water reactors was started in fiscal 1976 based on the special account act for power source development promotion measures by the entrustment from the Science and Technology Agency. Thereafter, to establish the safety of PWRs in loss-of-coolant accidents by joint international efforts, the Japan-West Germany-U.S. research cooperation program was started in April, 1980. Thereupon, the large-scale reflood test is now included in this program. It consists of two tests using a cylindrical core testing apparatus for examining the overall system effect and a plate core testing apparatus for testing individual effects. Each apparatus is composed of the mock-ups of pressure vessel, primary loop, containment vessel and ECCS. The testing method, the test results and the research cooperation program are described. (J.P.N.)

Choosing the best partition of the output from a large-scale simulation

Energy Technology Data Exchange (ETDEWEB)

Challacombe, Chelsea Jordan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Casleton, Emily Michele [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-09-26

Data partitioning becomes necessary when a large-scale simulation produces more data than can be feasibly stored. The goal is to partition the data, typically so that every element belongs to one and only one partition, and store summary information about the partition, either a representative value plus an estimate of the error or a distribution. Once the partitions are determined and the summary information stored, the raw data is discarded. This process can be performed in-situ; meaning while the simulation is running. When creating the partitions there are many decisions that researchers must make. For instance, how to determine once an adequate number of partitions have been created, how are the partitions created with respect to dividing the data, or how many variables should be considered simultaneously. In addition, decisions must be made for how to summarize the information within each partition. Because of the combinatorial number of possible ways to partition and summarize the data, a method of comparing the different possibilities will help guide researchers into choosing a good partitioning and summarization scheme for their application.

Large Scale Cosmological Anomalies and Inhomogeneous Dark Energy

Directory of Open Access Journals (Sweden)

Leandros Perivolaropoulos

2014-01-01

Full Text Available A wide range of large scale observations hint towards possible modifications on the standard cosmological model which is based on a homogeneous and isotropic universe with a small cosmological constant and matter. These observations, also known as “cosmic anomalies” include unexpected Cosmic Microwave Background perturbations on large angular scales, large dipolar peculiar velocity flows of galaxies (“bulk flows”, the measurement of inhomogenous values of the fine structure constant on cosmological scales (“alpha dipole” and other effects. The presence of the observational anomalies could either be a large statistical fluctuation in the context of ΛCDM or it could indicate a non-trivial departure from the cosmological principle on Hubble scales. Such a departure is very much constrained by cosmological observations for matter. For dark energy however there are no significant observational constraints for Hubble scale inhomogeneities. In this brief review I discuss some of the theoretical models that can naturally lead to inhomogeneous dark energy, their observational constraints and their potential to explain the large scale cosmic anomalies.

A conceptual analysis of standard setting in large-scale assessments

NARCIS (Netherlands)

van der Linden, Willem J.

1994-01-01

Elements of arbitrariness in the standard setting process are explored, and an alternative to the use of cut scores is presented. The first part of the paper analyzes the use of cut scores in large-scale assessments, discussing three different functions: (1) cut scores define the qualifications used

ADAPTIVE TEXTURE SYNTHESIS FOR LARGE SCALE CITY MODELING

Directory of Open Access Journals (Sweden)

G. Despine

2015-02-01

Full Text Available Large scale city models textured with aerial images are well suited for bird-eye navigation but generally the image resolution does not allow pedestrian navigation. One solution to face this problem is to use high resolution terrestrial photos but it requires huge amount of manual work to remove occlusions. Another solution is to synthesize generic textures with a set of procedural rules and elementary patterns like bricks, roof tiles, doors and windows. This solution may give realistic textures but with no correlation to the ground truth. Instead of using pure procedural modelling we present a method to extract information from aerial images and adapt the texture synthesis to each building. We describe a workflow allowing the user to drive the information extraction and to select the appropriate texture patterns. We also emphasize the importance to organize the knowledge about elementary pattern in a texture catalogue allowing attaching physical information, semantic attributes and to execute selection requests. Roofs are processed according to the detected building material. Façades are first described in terms of principal colours, then opening positions are detected and some window features are computed. These features allow selecting the most appropriate patterns from the texture catalogue. We experimented this workflow on two samples with 20 cm and 5 cm resolution images. The roof texture synthesis and opening detection were successfully conducted on hundreds of buildings. The window characterization is still sensitive to the distortions inherent to the projection of aerial images onto the facades.

Large-scale event extraction from literature with multi-level gene normalization.

Directory of Open Access Journals (Sweden)

Sofie Van Landeghem

Full Text Available Text mining for the life sciences aims to aid database curation, knowledge summarization and information retrieval through the automated processing of biomedical texts. To provide comprehensive coverage and enable full integration with existing biomolecular database records, it is crucial that text mining tools scale up to millions of articles and that their analyses can be unambiguously linked to information recorded in resources such as UniProt, KEGG, BioGRID and NCBI databases. In this study, we investigate how fully automated text mining of complex biomolecular events can be augmented with a normalization strategy that identifies biological concepts in text, mapping them to identifiers at varying levels of granularity, ranging from canonicalized symbols to unique gene and proteins and broad gene families. To this end, we have combined two state-of-the-art text mining components, previously evaluated on two community-wide challenges, and have extended and improved upon these methods by exploiting their complementary nature. Using these systems, we perform normalization and event extraction to create a large-scale resource that is publicly available, unique in semantic scope, and covers all 21.9 million PubMed abstracts and 460 thousand PubMed Central open access full-text articles. This dataset contains 40 million biomolecular events involving 76 million gene/protein mentions, linked to 122 thousand distinct genes from 5032 species across the full taxonomic tree. Detailed evaluations and analyses reveal promising results for application of this data in database and pathway curation efforts. The main software components used in this study are released under an open-source license. Further, the resulting dataset is freely accessible through a novel API, providing programmatic and customized access (http://www.evexdb.org/api/v001/. Finally, to allow for large-scale bioinformatic analyses, the entire resource is available for bulk download from

Large-scale gas dynamical processes affecting the origin and evolution of gaseous galactic halos

Science.gov (United States)

Shapiro, Paul R.

1991-01-01

Observations of galactic halo gas are consistent with an interpretation in terms of the galactic fountain model in which supernova heated gas in the galactic disk escapes into the halo, radiatively cools and forms clouds which fall back to the disk. The results of a new study of several large-scale gas dynamical effects which are expected to occur in such a model for the origin and evolution of galactic halo gas will be summarized, including the following: (1) nonequilibrium absorption line and emission spectrum diagnostics for radiatively cooling halo gas in our own galaxy, as well the implications of such absorption line diagnostics for the origin of quasar absorption lines in galactic halo clouds of high redshift galaxies; (2) numerical MHD simulations and analytical analysis of large-scale explosions ad superbubbles in the galactic disk and halo; (3) numerical MHD simulations of halo cloud formation by thermal instability, with and without magnetic field; and (4) the effect of the galactic fountain on the galactic dynamo.

FFTLasso: Large-Scale LASSO in the Fourier Domain

KAUST Repository

Bibi, Adel Aamer

2017-11-09

In this paper, we revisit the LASSO sparse representation problem, which has been studied and used in a variety of different areas, ranging from signal processing and information theory to computer vision and machine learning. In the vision community, it found its way into many important applications, including face recognition, tracking, super resolution, image denoising, to name a few. Despite advances in efficient sparse algorithms, solving large-scale LASSO problems remains a challenge. To circumvent this difficulty, people tend to downsample and subsample the problem (e.g. via dimensionality reduction) to maintain a manageable sized LASSO, which usually comes at the cost of losing solution accuracy. This paper proposes a novel circulant reformulation of the LASSO that lifts the problem to a higher dimension, where ADMM can be efficiently applied to its dual form. Because of this lifting, all optimization variables are updated using only basic element-wise operations, the most computationally expensive of which is a 1D FFT. In this way, there is no need for a linear system solver nor matrix-vector multiplication. Since all operations in our FFTLasso method are element-wise, the subproblems are completely independent and can be trivially parallelized (e.g. on a GPU). The attractive computational properties of FFTLasso are verified by extensive experiments on synthetic and real data and on the face recognition task. They demonstrate that FFTLasso scales much more effectively than a state-of-the-art solver.

FFTLasso: Large-Scale LASSO in the Fourier Domain

KAUST Repository

Bibi, Adel Aamer; Itani, Hani; Ghanem, Bernard

2017-01-01

In this paper, we revisit the LASSO sparse representation problem, which has been studied and used in a variety of different areas, ranging from signal processing and information theory to computer vision and machine learning. In the vision community, it found its way into many important applications, including face recognition, tracking, super resolution, image denoising, to name a few. Despite advances in efficient sparse algorithms, solving large-scale LASSO problems remains a challenge. To circumvent this difficulty, people tend to downsample and subsample the problem (e.g. via dimensionality reduction) to maintain a manageable sized LASSO, which usually comes at the cost of losing solution accuracy. This paper proposes a novel circulant reformulation of the LASSO that lifts the problem to a higher dimension, where ADMM can be efficiently applied to its dual form. Because of this lifting, all optimization variables are updated using only basic element-wise operations, the most computationally expensive of which is a 1D FFT. In this way, there is no need for a linear system solver nor matrix-vector multiplication. Since all operations in our FFTLasso method are element-wise, the subproblems are completely independent and can be trivially parallelized (e.g. on a GPU). The attractive computational properties of FFTLasso are verified by extensive experiments on synthetic and real data and on the face recognition task. They demonstrate that FFTLasso scales much more effectively than a state-of-the-art solver.

Modelling financial markets with agents competing on different time scales and with different amount of information

Science.gov (United States)

Wohlmuth, Johannes; Andersen, Jørgen Vitting

2006-05-01

We use agent-based models to study the competition among investors who use trading strategies with different amount of information and with different time scales. We find that mixing agents that trade on the same time scale but with different amount of information has a stabilizing impact on the large and extreme fluctuations of the market. Traders with the most information are found to be more likely to arbitrage traders who use less information in the decision making. On the other hand, introducing investors who act on two different time scales has a destabilizing effect on the large and extreme price movements, increasing the volatility of the market. Closeness in time scale used in the decision making is found to facilitate the creation of local trends. The larger the overlap in commonly shared information the more the traders in a mixed system with different time scales are found to profit from the presence of traders acting at another time scale than themselves.

Applications of Neutron Scattering in the Chemical Industry: Proton Dynamics of Highly Dispersed Materials, Characterization of Fuel Cell Catalysts, and Catalysts from Large-Scale Chemical Processes

Science.gov (United States)

Albers, Peter W.; Parker, Stewart F.

The attractiveness of neutron scattering techniques for the detailed characterization of materials of high degrees of dispersity and structural complexity as encountered in the chemical industry is discussed. Neutron scattering picks up where other analytical methods leave off because of the physico-chemical properties of finely divided products and materials whose absorption behavior toward electromagnetic radiation and electrical conductivity causes serious problems. This is demonstrated by presenting typical applications from large-scale production technology and industrial catalysis. These include the determination of the proton-related surface chemistry of advanced materials that are used as reinforcing fillers in the manufacture of tires, where interrelations between surface chemistry, rheological properties, improved safety, and significant reduction of fuel consumption are the focus of recent developments. Neutron scattering allows surface science studies of the dissociative adsorption of hydrogen on nanodispersed, supported precious metal particles of fuel cell catalysts under in situ loading at realistic gas pressures of about 1 bar. Insight into the occupation of catalytically relevant surface sites provides valuable information about the catalyst in the working state and supplies essential scientific input for tailoring better catalysts by technologists. The impact of deactivation phenomena on industrial catalysts by coke deposition, chemical transformation of carbonaceous deposits, and other processes in catalytic hydrogenation processes that result in significant shortening of the time of useful operation in large-scale plants can often be traced back in detail to surface or bulk properties of catalysts or materials of catalytic relevance. A better understanding of avoidable or unavoidable aspects of catalyst deactivation phenomena under certain in-process conditions and the development of effective means for reducing deactivation leads to more energy

A large-scale forest fragmentation experiment: the Stability of Altered Forest Ecosystems Project

Science.gov (United States)

Ewers, Robert M.; Didham, Raphael K.; Fahrig, Lenore; Ferraz, Gonçalo; Hector, Andy; Holt, Robert D.; Kapos, Valerie; Reynolds, Glen; Sinun, Waidi; Snaddon, Jake L.; Turner, Edgar C.

2011-01-01

Opportunities to conduct large-scale field experiments are rare, but provide a unique opportunity to reveal the complex processes that operate within natural ecosystems. Here, we review the design of existing, large-scale forest fragmentation experiments. Based on this review, we develop a design for the Stability of Altered Forest Ecosystems (SAFE) Project, a new forest fragmentation experiment to be located in the lowland tropical forests of Borneo (Sabah, Malaysia). The SAFE Project represents an advance on existing experiments in that it: (i) allows discrimination of the effects of landscape-level forest cover from patch-level processes; (ii) is designed to facilitate the unification of a wide range of data types on ecological patterns and processes that operate over a wide range of spatial scales; (iii) has greater replication than existing experiments; (iv) incorporates an experimental manipulation of riparian corridors; and (v) embeds the experimentally fragmented landscape within a wider gradient of land-use intensity than do existing projects. The SAFE Project represents an opportunity for ecologists across disciplines to participate in a large initiative designed to generate a broad understanding of the ecological impacts of tropical forest modification. PMID:22006969

A large-scale forest fragmentation experiment: the Stability of Altered Forest Ecosystems Project.

Science.gov (United States)

Ewers, Robert M; Didham, Raphael K; Fahrig, Lenore; Ferraz, Gonçalo; Hector, Andy; Holt, Robert D; Kapos, Valerie; Reynolds, Glen; Sinun, Waidi; Snaddon, Jake L; Turner, Edgar C

2011-11-27

Opportunities to conduct large-scale field experiments are rare, but provide a unique opportunity to reveal the complex processes that operate within natural ecosystems. Here, we review the design of existing, large-scale forest fragmentation experiments. Based on this review, we develop a design for the Stability of Altered Forest Ecosystems (SAFE) Project, a new forest fragmentation experiment to be located in the lowland tropical forests of Borneo (Sabah, Malaysia). The SAFE Project represents an advance on existing experiments in that it: (i) allows discrimination of the effects of landscape-level forest cover from patch-level processes; (ii) is designed to facilitate the unification of a wide range of data types on ecological patterns and processes that operate over a wide range of spatial scales; (iii) has greater replication than existing experiments; (iv) incorporates an experimental manipulation of riparian corridors; and (v) embeds the experimentally fragmented landscape within a wider gradient of land-use intensity than do existing projects. The SAFE Project represents an opportunity for ecologists across disciplines to participate in a large initiative designed to generate a broad understanding of the ecological impacts of tropical forest modification.

Collaborative mining and interpretation of large-scale data for biomedical research insights.

Directory of Open Access Journals (Sweden)

Georgia Tsiliki

Full Text Available Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence.

Individual differences influence two-digit number processing, but not their analog magnitude processing: a large-scale online study.

Science.gov (United States)

Huber, Stefan; Nuerk, Hans-Christoph; Reips, Ulf-Dietrich; Soltanlou, Mojtaba

2017-12-23

Symbolic magnitude comparison is one of the most well-studied cognitive processes in research on numerical cognition. However, while the cognitive mechanisms of symbolic magnitude processing have been intensively studied, previous studies have paid less attention to individual differences influencing symbolic magnitude comparison. Employing a two-digit number comparison task in an online setting, we replicated previous effects, including the distance effect, the unit-decade compatibility effect, and the effect of cognitive control on the adaptation to filler items, in a large-scale study in 452 adults. Additionally, we observed that the most influential individual differences were participants' first language, time spent playing computer games and gender, followed by reported alcohol consumption, age and mathematical ability. Participants who used a first language with a left-to-right reading/writing direction were faster than those who read and wrote in the right-to-left direction. Reported playing time for computer games was correlated with faster reaction times. Female participants showed slower reaction times and a larger unit-decade compatibility effect than male participants. Participants who reported never consuming alcohol showed overall slower response times than others. Older participants were slower, but more accurate. Finally, higher grades in mathematics were associated with faster reaction times. We conclude that typical experiments on numerical cognition that employ a keyboard as an input device can also be run in an online setting. Moreover, while individual differences have no influence on domain-specific magnitude processing-apart from age, which increases the decade distance effect-they generally influence performance on a two-digit number comparison task.

Amplification of large-scale magnetic field in nonhelical magnetohydrodynamics

KAUST Repository

Kumar, Rohit

2017-08-11

It is typically assumed that the kinetic and magnetic helicities play a crucial role in the growth of large-scale dynamo. In this paper, we demonstrate that helicity is not essential for the amplification of large-scale magnetic field. For this purpose, we perform nonhelical magnetohydrodynamic (MHD) simulation, and show that the large-scale magnetic field can grow in nonhelical MHD when random external forcing is employed at scale 1/10 the box size. The energy fluxes and shell-to-shell transfer rates computed using the numerical data show that the large-scale magnetic energy grows due to the energy transfers from the velocity field at the forcing scales.

Detecting differential protein expression in large-scale population proteomics

Energy Technology Data Exchange (ETDEWEB)

Ryu, Soyoung; Qian, Weijun; Camp, David G.; Smith, Richard D.; Tompkins, Ronald G.; Davis, Ronald W.; Xiao, Wenzhong

2014-06-17

Mass spectrometry-based high-throughput quantitative proteomics shows great potential in clinical biomarker studies, identifying and quantifying thousands of proteins in biological samples. However, methods are needed to appropriately handle issues/challenges unique to mass spectrometry data in order to detect as many biomarker proteins as possible. One issue is that different mass spectrometry experiments generate quite different total numbers of quantified peptides, which can result in more missing peptide abundances in an experiment with a smaller total number of quantified peptides. Another issue is that the quantification of peptides is sometimes absent, especially for less abundant peptides and such missing values contain the information about the peptide abundance. Here, we propose a Significance Analysis for Large-scale Proteomics Studies (SALPS) that handles missing peptide intensity values caused by the two mechanisms mentioned above. Our model has a robust performance in both simulated data and proteomics data from a large clinical study. Because varying patients’ sample qualities and deviating instrument performances are not avoidable for clinical studies performed over the course of several years, we believe that our approach will be useful to analyze large-scale clinical proteomics data.

Large-scale information flow in conscious and unconscious states: an ECoG study in monkeys.

Directory of Open Access Journals (Sweden)

Toru Yanagawa

Full Text Available Consciousness is an emergent property of the complex brain network. In order to understand how consciousness is constructed, neural interactions within this network must be elucidated. Previous studies have shown that specific neural interactions between the thalamus and frontoparietal cortices; frontal and parietal cortices; and parietal and temporal cortices are correlated with levels of consciousness. However, due to technical limitations, the network underlying consciousness has not been investigated in terms of large-scale interactions with high temporal and spectral resolution. In this study, we recorded neural activity with dense electrocorticogram (ECoG arrays and used the spectral Granger causality to generate a more comprehensive network that relates to consciousness in monkeys. We found that neural interactions were significantly different between conscious and unconscious states in all combinations of cortical region pairs. Furthermore, the difference in neural interactions between conscious and unconscious states could be represented in 4 frequency-specific large-scale networks with unique interaction patterns: 2 networks were related to consciousness and showed peaks in alpha and beta bands, while the other 2 networks were related to unconsciousness and showed peaks in theta and gamma bands. Moreover, networks in the unconscious state were shared amongst 3 different unconscious conditions, which were induced either by ketamine and medetomidine, propofol, or sleep. Our results provide a novel picture that the difference between conscious and unconscious states is characterized by a switch in frequency-specific modes of large-scale communications across the entire cortex, rather than the cessation of interactions between specific cortical regions.

Unraveling The Connectome: Visualizing and Abstracting Large-Scale Connectomics Data

KAUST Repository

Al-Awami, Ali K.

2017-04-30

We explore visualization and abstraction approaches to represent neuronal data. Neuroscientists acquire electron microscopy volumes to reconstruct a complete wiring diagram of the neurons in the brain, called the connectome. This will be crucial to understanding brains and their development. However, the resulting data is complex and large, posing a big challenge to existing visualization techniques in terms of clarity and scalability. We describe solutions to tackle the problems of scalability and cluttered presentation. We first show how a query-guided interactive approach to visual exploration can reduce the clutter and help neuroscientists explore their data dynamically. We use a knowledge-based query algebra that facilitates the interactive creation of queries. This allows neuroscientists to pose domain-specific questions related to their research. Simple queries can be combined to form complex queries to answer more sophisticated questions. We then show how visual abstractions from 3D to 2D can significantly reduce the visual clutter and add clarity to the visualization so that scientists can focus more on the analysis. We abstract the topology of 3D neurons into a multi-scale, relative distance-preserving subway map visualization that allows scientists to interactively explore the morphological and connectivity features of neuronal cells. We then focus on the process of acquisition, where neuroscientists segment electron microscopy images to reconstruct neurons. The segmentation process of such data is tedious, time-intensive, and usually performed using a diverse set of tools. We present a novel web-based visualization system for tracking the state, progress, and evolution of segmentation data in neuroscience. Our multi-user system seamlessly integrates a diverse set of tools. Our system provides support for the management, provenance, accountability, and auditing of large-scale segmentations. Finally, we present a novel architecture to render very large

Algorithm of search and track of static and moving large-scale objects

Directory of Open Access Journals (Sweden)

Kalyaev Anatoly

2017-01-01

Full Text Available We suggest an algorithm for processing of a sequence, which contains images of search and track of static and moving large-scale objects. The possible software implementation of the algorithm, based on multithread CUDA processing, is suggested. Experimental analysis of the suggested algorithm implementation is performed.

Superconducting materials for large scale applications

International Nuclear Information System (INIS)

Dew-Hughes, D.

1975-01-01

Applications of superconductors capable of carrying large current densities in large-scale electrical devices are examined. Discussions are included on critical current density, superconducting materials available, and future prospects for improved superconducting materials. (JRD)

Large-scale influences in near-wall turbulence.

Science.gov (United States)

Hutchins, Nicholas; Marusic, Ivan

2007-03-15

Hot-wire data acquired in a high Reynolds number facility are used to illustrate the need for adequate scale separation when considering the coherent structure in wall-bounded turbulence. It is found that a large-scale motion in the log region becomes increasingly comparable in energy to the near-wall cycle as the Reynolds number increases. Through decomposition of fluctuating velocity signals, it is shown that this large-scale motion has a distinct modulating influence on the small-scale energy (akin to amplitude modulation). Reassessment of DNS data, in light of these results, shows similar trends, with the rate and intensity of production due to the near-wall cycle subject to a modulating influence from the largest-scale motions.

Workshop Report on Additive Manufacturing for Large-Scale Metal Components - Development and Deployment of Metal Big-Area-Additive-Manufacturing (Large-Scale Metals AM) System

Energy Technology Data Exchange (ETDEWEB)

Babu, Sudarsanam Suresh [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Manufacturing Demonstration Facility; Love, Lonnie J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Manufacturing Demonstration Facility; Peter, William H. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Manufacturing Demonstration Facility; Dehoff, Ryan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Manufacturing Demonstration Facility

2016-05-01

Additive manufacturing (AM) is considered an emerging technology that is expected to transform the way industry can make low-volume, high value complex structures. This disruptive technology promises to replace legacy manufacturing methods for the fabrication of existing components in addition to bringing new innovation for new components with increased functional and mechanical properties. This report outlines the outcome of a workshop on large-scale metal additive manufacturing held at Oak Ridge National Laboratory (ORNL) on March 11, 2016. The charter for the workshop was outlined by the Department of Energy (DOE) Advanced Manufacturing Office program manager. The status and impact of the Big Area Additive Manufacturing (BAAM) for polymer matrix composites was presented as the background motivation for the workshop. Following, the extension of underlying technology to low-cost metals was proposed with the following goals: (i) High deposition rates (approaching 100 lbs/h); (ii) Low cost (<$10/lbs) for steel, iron, aluminum, nickel, as well as, higher cost titanium, (iii) large components (major axis greater than 6 ft) and (iv) compliance of property requirements. The above concept was discussed in depth by representatives from different industrial sectors including welding, metal fabrication machinery, energy, construction, aerospace and heavy manufacturing. In addition, DOE’s newly launched High Performance Computing for Manufacturing (HPC4MFG) program was reviewed. This program will apply thermo-mechanical models to elucidate deeper understanding of the interactions between design, process, and materials during additive manufacturing. Following these presentations, all the attendees took part in a brainstorming session where everyone identified the top 10 challenges in large-scale metal AM from their own perspective. The feedback was analyzed and grouped in different categories including, (i) CAD to PART software, (ii) selection of energy source, (iii

Sub-surface laser nanostructuring in stratified metal/dielectric media: a versatile platform towards flexible, durable and large-scale plasmonic writing

International Nuclear Information System (INIS)

Siozios, A; Bellas, D V; Lidorikis, E; Patsalas, P; Kalfagiannis, N; Cranton, W M; Koutsogeorgis, D C; Bazioti, C; Dimitrakopulos, G P; Vourlias, G

2015-01-01

Laser nanostructuring of pure ultrathin metal layers or ceramic/metal composite thin films has emerged as a promising route for the fabrication of plasmonic patterns with applications in information storage, cryptography, and security tagging. However, the environmental sensitivity of pure Ag layers and the complexity of ceramic/metal composite film growth hinder the implementation of this technology to large-scale production, as well as its combination with flexible substrates. In the present work we investigate an alternative pathway, namely, starting from non-plasmonic multilayer metal/dielectric layers, whose growth is compatible with large scale production such as in-line sputtering and roll-to-roll deposition, which are then transformed into plasmonic templates by single-shot UV-laser annealing (LA). This entirely cold, large-scale process leads to a subsurface nanoconstruction involving plasmonic Ag nanoparticles (NPs) embedded in a hard and inert dielectric matrix on top of both rigid and flexible substrates. The subsurface encapsulation of Ag NPs provides durability and long-term stability, while the cold character of LA suits the use of sensitive flexible substrates. The morphology of the final composite film depends primarily on the nanocrystalline character of the dielectric host and its thermal conductivity. We demonstrate the emergence of a localized surface plasmon resonance, and its tunability depending on the applied fluence and environmental pressure. The results are well explained by theoretical photothermal modeling. Overall, our findings qualify the proposed process as an excellent candidate for versatile, large-scale optical encoding applications. (paper)

Achieving online consent to participation in large-scale gene-environment studies: a tangible destination

NARCIS (Netherlands)

Wood, F.; Kowalczuk, J.; Elwyn, G.; Mitchell, C.; Gallacher, J.

2011-01-01

BACKGROUND: Population based genetics studies are dependent on large numbers of individuals in the pursuit of small effect sizes. Recruiting and consenting a large number of participants is both costly and time consuming. We explored whether an online consent process for large-scale genetics studies

Sensory information in local field potentials and spikes from visual and auditory cortices: time scales and frequency bands.

Science.gov (United States)

Belitski, Andrei; Panzeri, Stefano; Magri, Cesare; Logothetis, Nikos K; Kayser, Christoph

2010-12-01

Studies analyzing sensory cortical processing or trying to decode brain activity often rely on a combination of different electrophysiological signals, such as local field potentials (LFPs) and spiking activity. Understanding the relation between these signals and sensory stimuli and between different components of these signals is hence of great interest. We here provide an analysis of LFPs and spiking activity recorded from visual and auditory cortex during stimulation with natural stimuli. In particular, we focus on the time scales on which different components of these signals are informative about the stimulus, and on the dependencies between different components of these signals. Addressing the first question, we find that stimulus information in low frequency bands (50 Hz), in contrast, is scale dependent, and is larger when the energy is averaged over several hundreds of milliseconds. Indeed, combined analysis of signal reliability and information revealed that the energy of slow LFP fluctuations is well related to the stimulus even when considering individual or few cycles, while the energy of fast LFP oscillations carries information only when averaged over many cycles. Addressing the second question, we find that stimulus information in different LFP bands, and in different LFP bands and spiking activity, is largely independent regardless of time scale or sensory system. Taken together, these findings suggest that different LFP bands represent dynamic natural stimuli on distinct time scales and together provide a potentially rich source of information for sensory processing or decoding brain activity.

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

Science.gov (United States)

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

PKI security in large-scale healthcare networks.

Science.gov (United States)

Mantas, Georgios; Lymberopoulos, Dimitrios; Komninos, Nikos

2012-06-01

During the past few years a lot of PKI (Public Key Infrastructures) infrastructures have been proposed for healthcare networks in order to ensure secure communication services and exchange of data among healthcare professionals. However, there is a plethora of challenges in these healthcare PKI infrastructures. Especially, there are a lot of challenges for PKI infrastructures deployed over large-scale healthcare networks. In this paper, we propose a PKI infrastructure to ensure security in a large-scale Internet-based healthcare network connecting a wide spectrum of healthcare units geographically distributed within a wide region. Furthermore, the proposed PKI infrastructure facilitates the trust issues that arise in a large-scale healthcare network including multi-domain PKI infrastructures.

Hydrogen combustion modelling in large-scale geometries

International Nuclear Information System (INIS)

Studer, E.; Beccantini, A.; Kudriakov, S.; Velikorodny, A.

2014-01-01

Hydrogen risk mitigation issues based on catalytic recombiners cannot exclude flammable clouds to be formed during the course of a severe accident in a Nuclear Power Plant. Consequences of combustion processes have to be assessed based on existing knowledge and state of the art in CFD combustion modelling. The Fukushima accidents have also revealed the need for taking into account the hydrogen explosion phenomena in risk management. Thus combustion modelling in a large-scale geometry is one of the remaining severe accident safety issues. At present day there doesn't exist a combustion model which can accurately describe a combustion process inside a geometrical configuration typical of the Nuclear Power Plant (NPP) environment. Therefore the major attention in model development has to be paid on the adoption of existing approaches or creation of the new ones capable of reliably predicting the possibility of the flame acceleration in the geometries of that type. A set of experiments performed previously in RUT facility and Heiss Dampf Reactor (HDR) facility is used as a validation database for development of three-dimensional gas dynamic model for the simulation of hydrogen-air-steam combustion in large-scale geometries. The combustion regimes include slow deflagration, fast deflagration, and detonation. Modelling is based on Reactive Discrete Equation Method (RDEM) where flame is represented as an interface separating reactants and combustion products. The transport of the progress variable is governed by different flame surface wrinkling factors. The results of numerical simulation are presented together with the comparisons, critical discussions and conclusions. (authors)

A large-scale perspective on stress-induced alterations in resting-state networks

Science.gov (United States)

Maron-Katz, Adi; Vaisvaser, Sharon; Lin, Tamar; Hendler, Talma; Shamir, Ron

2016-02-01

Stress is known to induce large-scale neural modulations. However, its neural effect once the stressor is removed and how it relates to subjective experience are not fully understood. Here we used a statistically sound data-driven approach to investigate alterations in large-scale resting-state functional connectivity (rsFC) induced by acute social stress. We compared rsfMRI profiles of 57 healthy male subjects before and after stress induction. Using a parcellation-based univariate statistical analysis, we identified a large-scale rsFC change, involving 490 parcel-pairs. Aiming to characterize this change, we employed statistical enrichment analysis, identifying anatomic structures that were significantly interconnected by these pairs. This analysis revealed strengthening of thalamo-cortical connectivity and weakening of cross-hemispheral parieto-temporal connectivity. These alterations were further found to be associated with change in subjective stress reports. Integrating report-based information on stress sustainment 20 minutes post induction, revealed a single significant rsFC change between the right amygdala and the precuneus, which inversely correlated with the level of subjective recovery. Our study demonstrates the value of enrichment analysis for exploring large-scale network reorganization patterns, and provides new insight on stress-induced neural modulations and their relation to subjective experience.

Inference of functional properties from large-scale analysis of enzyme superfamilies.

Science.gov (United States)

Brown, Shoshana D; Babbitt, Patricia C

2012-01-02

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies.

Emerging large-scale solar heating applications

International Nuclear Information System (INIS)

Wong, W.P.; McClung, J.L.

2009-01-01

Currently the market for solar heating applications in Canada is dominated by outdoor swimming pool heating, make-up air pre-heating and domestic water heating in homes, commercial and institutional buildings. All of these involve relatively small systems, except for a few air pre-heating systems on very large buildings. Together these applications make up well over 90% of the solar thermal collectors installed in Canada during 2007. These three applications, along with the recent re-emergence of large-scale concentrated solar thermal for generating electricity, also dominate the world markets. This paper examines some emerging markets for large scale solar heating applications, with a focus on the Canadian climate and market. (author)

Emerging large-scale solar heating applications

Energy Technology Data Exchange (ETDEWEB)

Wong, W.P.; McClung, J.L. [Science Applications International Corporation (SAIC Canada), Ottawa, Ontario (Canada)

2009-07-01

Currently the market for solar heating applications in Canada is dominated by outdoor swimming pool heating, make-up air pre-heating and domestic water heating in homes, commercial and institutional buildings. All of these involve relatively small systems, except for a few air pre-heating systems on very large buildings. Together these applications make up well over 90% of the solar thermal collectors installed in Canada during 2007. These three applications, along with the recent re-emergence of large-scale concentrated solar thermal for generating electricity, also dominate the world markets. This paper examines some emerging markets for large scale solar heating applications, with a focus on the Canadian climate and market. (author)

Environment and host as large-scale controls of ectomycorrhizal fungi.

Science.gov (United States)

van der Linde, Sietse; Suz, Laura M; Orme, C David L; Cox, Filipa; Andreae, Henning; Asi, Endla; Atkinson, Bonnie; Benham, Sue; Carroll, Christopher; Cools, Nathalie; De Vos, Bruno; Dietrich, Hans-Peter; Eichhorn, Johannes; Gehrmann, Joachim; Grebenc, Tine; Gweon, Hyun S; Hansen, Karin; Jacob, Frank; Kristöfel, Ferdinand; Lech, Paweł; Manninger, Miklós; Martin, Jan; Meesenburg, Henning; Merilä, Päivi; Nicolas, Manuel; Pavlenda, Pavel; Rautio, Pasi; Schaub, Marcus; Schröck, Hans-Werner; Seidling, Walter; Šrámek, Vít; Thimonier, Anne; Thomsen, Iben Margrete; Titeux, Hugues; Vanguelova, Elena; Verstraeten, Arne; Vesterdal, Lars; Waldner, Peter; Wijk, Sture; Zhang, Yuxin; Žlindra, Daniel; Bidartondo, Martin I

2018-06-06

Explaining the large-scale diversity of soil organisms that drive biogeochemical processes-and their responses to environmental change-is critical. However, identifying consistent drivers of belowground diversity and abundance for some soil organisms at large spatial scales remains problematic. Here we investigate a major guild, the ectomycorrhizal fungi, across European forests at a spatial scale and resolution that is-to our knowledge-unprecedented, to explore key biotic and abiotic predictors of ectomycorrhizal diversity and to identify dominant responses and thresholds for change across complex environmental gradients. We show the effect of 38 host, environment, climate and geographical variables on ectomycorrhizal diversity, and define thresholds of community change for key variables. We quantify host specificity and reveal plasticity in functional traits involved in soil foraging across gradients. We conclude that environmental and host factors explain most of the variation in ectomycorrhizal diversity, that the environmental thresholds used as major ecosystem assessment tools need adjustment and that the importance of belowground specificity and plasticity has previously been underappreciated.

Large-scale inverse model analyses employing fast randomized data reduction

Science.gov (United States)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

Cross-section library and processing techniques within the SCALE system

International Nuclear Information System (INIS)

Westfall, R.M.

1986-01-01

A summary of each of the SCALE system features involved in problem-dependent cross section processing is presented. These features include criticality libraries, shielding libraries, the Standard Composition Library, the SCALE functional modules: BONAMI-S, NITAWL-S, XSDRNPM-S, ICE-S, and the Material Information Processor. The automated procedure for cross-section processing is described with examples. 15 refs

[Information processing speed and influential factors in multiple sclerosis].

Science.gov (United States)

Zhang, M L; Xu, E H; Dong, H Q; Zhang, J W

2016-04-19

To study the information processing speed and the influential factors in multiple sclerosis (MS) patients. A total of 36 patients with relapsing-remitting MS (RRMS), 21 patients with secondary progressive MS (SPMS), and 50 healthy control subjects from Xuanwu Hospital of Capital Medical University between April 2010 and April 2012 were included into this cross-sectional study.Neuropsychological tests was conducted after the disease had been stable for 8 weeks, including information processing speed, memory, executive functions, language and visual perception.Correlation between information processing speed and depression, fatigue, Expanded Disability Status Scale (EDSS) were studied. (1)MS patient groups demonstrated cognitive deficits compared to healthy controls.The Symbol Digit Modalities Test (SDMT) (control group 57±12; RRMS group 46±17; SPMS group 35±10, Pinformation processing (Pinformation processing speed, verbal memory and executive functioning are seen in MS patients, especially in SPMS subtype, while visual-spatial function is relatively reserved.Age, white matter change scales, EDSS scores, depression are negatively associated with information processing speed.

Large-scale regions of antimatter

International Nuclear Information System (INIS)

Grobov, A. V.; Rubin, S. G.

2015-01-01

Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era

Large-scale regions of antimatter

Energy Technology Data Exchange (ETDEWEB)

Grobov, A. V., E-mail: alexey.grobov@gmail.com; Rubin, S. G., E-mail: sgrubin@mephi.ru [National Research Nuclear University MEPhI (Russian Federation)

2015-07-15

Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era.

Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data.

Science.gov (United States)

Narimani, Zahra; Beigy, Hamid; Ahmad, Ashar; Masoudi-Nejad, Ali; Fröhlich, Holger

2017-01-01

Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. We devise a novel Bayesian network reverse engineering approach using ordinary differential equations with the ability to include non-linearity. Besides modeling arbitrary, possibly combinatorial and time dependent perturbations with unknown targets, one of our main contributions is the use of Expectation Propagation, an algorithm for approximate Bayesian inference over large scale network structures in short computation time. We further explore the possibility of integrating prior knowledge into network inference. We evaluate the proposed model on DREAM4 and DREAM8 data and find it competitive against several state-of-the-art existing network inference methods.

Scalable and Fully Distributed Localization in Large-Scale Sensor Networks

Directory of Open Access Journals (Sweden)

Miao Jin

2017-06-01

Full Text Available This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and a non-uniform nodal distribution. In contrast to current state-of-the-art connectivity-based localization methods, the proposed algorithm is highly scalable with linear computation and communication costs with respect to the size of the network; and fully distributed where each node only needs the information of its neighbors without cumbersome partitioning and merging process. The algorithm is theoretically guaranteed and numerically stable. Moreover, the algorithm can be readily extended to the localization of networks with a one-hop transmission range distance measurement, and the propagation of the measurement error at one sensor node is limited within a small area of the network around the node. Extensive simulations and comparison with other methods under various representative network settings are carried out, showing the superior performance of the proposed algorithm.

Timing of Formal Phase Safety Reviews for Large-Scale Integrated Hazard Analysis

Science.gov (United States)

Massie, Michael J.; Morris, A. Terry

2010-01-01

Integrated hazard analysis (IHA) is a process used to identify and control unacceptable risk. As such, it does not occur in a vacuum. IHA approaches must be tailored to fit the system being analyzed. Physical, resource, organizational and temporal constraints on large-scale integrated systems impose additional direct or derived requirements on the IHA. The timing and interaction between engineering and safety organizations can provide either benefits or hindrances to the overall end product. The traditional approach for formal phase safety review timing and content, which generally works well for small- to moderate-scale systems, does not work well for very large-scale integrated systems. This paper proposes a modified approach to timing and content of formal phase safety reviews for IHA. Details of the tailoring process for IHA will describe how to avoid temporary disconnects in major milestone reviews and how to maintain a cohesive end-to-end integration story particularly for systems where the integrator inherently has little to no insight into lower level systems. The proposal has the advantage of allowing the hazard analysis development process to occur as technical data normally matures.

Hypersingular integral equations, waveguiding effects in Cantorian Universe and genesis of large scale structures

International Nuclear Information System (INIS)

Iovane, G.; Giordano, P.

2005-01-01

In this work we introduce the hypersingular integral equations and analyze a realistic model of gravitational waveguides on a cantorian space-time. A waveguiding effect is considered with respect to the large scale structure of the Universe, where the structure formation appears as if it were a classically self-similar random process at all astrophysical scales. The result is that it seems we live in an El Naschie's o (∞) Cantorian space-time, where gravitational lensing and waveguiding effects can explain the appearing Universe. In particular, we consider filamentary and planar large scale structures as possible refraction channels for electromagnetic radiation coming from cosmological structures. From this vision the Universe appears like a large self-similar adaptive mirrors set, thanks to three numerical simulations. Consequently, an infinite Universe is just an optical illusion that is produced by mirroring effects connected with the large scale structure of a finite and not a large Universe

Calculating Soil Wetness, Evapotranspiration and Carbon Cycle Processes Over Large Grid Areas Using a New Scaling Technique

Science.gov (United States)

Sellers, Piers

2012-01-01

Soil wetness typically shows great spatial variability over the length scales of general circulation model (GCM) grid areas (approx 100 km ), and the functions relating evapotranspiration and photosynthetic rate to local-scale (approx 1 m) soil wetness are highly non-linear. Soil respiration is also highly dependent on very small-scale variations in soil wetness. We therefore expect significant inaccuracies whenever we insert a single grid area-average soil wetness value into a function to calculate any of these rates for the grid area. For the particular case of evapotranspiration., this method - use of a grid-averaged soil wetness value - can also provoke severe oscillations in the evapotranspiration rate and soil wetness under some conditions. A method is presented whereby the probability distribution timction(pdf) for soil wetness within a grid area is represented by binning. and numerical integration of the binned pdf is performed to provide a spatially-integrated wetness stress term for the whole grid area, which then permits calculation of grid area fluxes in a single operation. The method is very accurate when 10 or more bins are used, can deal realistically with spatially variable precipitation, conserves moisture exactly and allows for precise modification of the soil wetness pdf after every time step. The method could also be applied to other ecological problems where small-scale processes must be area-integrated, or upscaled, to estimate fluxes over large areas, for example in treatments of the terrestrial carbon budget or trace gas generation.

Information paths within the new product development process

DEFF Research Database (Denmark)

Jespersen, Kristina Risom

2007-01-01

collection platform to obtain measurements from within the NPD process. 42 large, international companies participated in the data collecting simulation. Results revealed five different information paths that were not connecting all stages of the NPD process. Moreover, results show that the front......-end is not driving the information acquisition through the stages of the NPD process, and that environmental turbulence disconnects stages from the information paths in the NPD process. This implies that information is at the same time a key to success and a key to entrapment in the NPD process....

Towards Device-Independent Information Processing on General Quantum Networks

Science.gov (United States)

Lee, Ciarán M.; Hoban, Matty J.

2018-01-01

The violation of certain Bell inequalities allows for device-independent information processing secure against nonsignaling eavesdroppers. However, this only holds for the Bell network, in which two or more agents perform local measurements on a single shared source of entanglement. To overcome the practical constraints that entangled systems can only be transmitted over relatively short distances, large-scale multisource networks have been employed. Do there exist analogs of Bell inequalities for such networks, whose violation is a resource for device independence? In this Letter, the violation of recently derived polynomial Bell inequalities will be shown to allow for device independence on multisource networks, secure against nonsignaling eavesdroppers.

Information processing and routing in wireless sensor networks

CERN Document Server

Yu, Yang; Krishnamachari, Bhaskar

2006-01-01

This book presents state-of-the-art cross-layer optimization techniques for energy-efficient information processing and routing in wireless sensor networks. Besides providing a survey on this important research area, three specific topics are discussed in detail - information processing in a collocated cluster, information transport over a tree substrate, and information routing for computationally intensive applications. The book covers several important system knobs for cross-layer optimization, including voltage scaling, rate adaptation, and tunable compression. By exploring tradeoffs of en

Large-Scale Analysis of Art Proportions

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2014-01-01

While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square) and with majo......While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square...

The Expanded Large Scale Gap Test

Science.gov (United States)

1987-03-01

NSWC TR 86-32 DTIC THE EXPANDED LARGE SCALE GAP TEST BY T. P. LIDDIARD D. PRICE RESEARCH AND TECHNOLOGY DEPARTMENT ’ ~MARCH 1987 Ap~proved for public...arises, to reduce the spread in the LSGT 50% gap value.) The worst charges, such as those with the highest or lowest densities, the largest re-pressed...Arlington, VA 22217 PE 62314N INS3A 1 RJ14E31 7R4TBK 11 TITLE (Include Security CIlmsilficatiorn The Expanded Large Scale Gap Test . 12. PEIRSONAL AUTHOR() T

The relationship between large-scale and convective states in the tropics - Towards an improved representation of convection in large-scale models

Energy Technology Data Exchange (ETDEWEB)

Jakob, Christian [Monash Univ., Melbourne, VIC (Australia)

2015-02-26

This report summarises an investigation into the relationship of tropical thunderstorms to the atmospheric conditions they are embedded in. The study is based on the use of radar observations at the Atmospheric Radiation Measurement site in Darwin run under the auspices of the DOE Atmospheric Systems Research program. Linking the larger scales of the atmosphere with the smaller scales of thunderstorms is crucial for the development of the representation of thunderstorms in weather and climate models, which is carried out by a process termed parametrisation. Through the analysis of radar and wind profiler observations the project made several fundamental discoveries about tropical storms and quantified the relationship of the occurrence and intensity of these storms to the large-scale atmosphere. We were able to show that the rainfall averaged over an area the size of a typical climate model grid-box is largely controlled by the number of storms in the area, and less so by the storm intensity. This allows us to completely rethink the way we represent such storms in climate models. We also found that storms occur in three distinct categories based on their depth and that the transition between these categories is strongly related to the larger scale dynamical features of the atmosphere more so than its thermodynamic state. Finally, we used our observational findings to test and refine a new approach to cumulus parametrisation which relies on the stochastic modelling of the area covered by different convective cloud types.

A full scale approximation of covariance functions for large spatial data sets

KAUST Repository

Sang, Huiyan

2011-10-10

Gaussian process models have been widely used in spatial statistics but face tremendous computational challenges for very large data sets. The model fitting and spatial prediction of such models typically require O(n 3) operations for a data set of size n. Various approximations of the covariance functions have been introduced to reduce the computational cost. However, most existing approximations cannot simultaneously capture both the large- and the small-scale spatial dependence. A new approximation scheme is developed to provide a high quality approximation to the covariance function at both the large and the small spatial scales. The new approximation is the summation of two parts: a reduced rank covariance and a compactly supported covariance obtained by tapering the covariance of the residual of the reduced rank approximation. Whereas the former part mainly captures the large-scale spatial variation, the latter part captures the small-scale, local variation that is unexplained by the former part. By combining the reduced rank representation and sparse matrix techniques, our approach allows for efficient computation for maximum likelihood estimation, spatial prediction and Bayesian inference. We illustrate the new approach with simulated and real data sets. © 2011 Royal Statistical Society.

A full scale approximation of covariance functions for large spatial data sets

KAUST Repository

Sang, Huiyan; Huang, Jianhua Z.

2011-01-01

Gaussian process models have been widely used in spatial statistics but face tremendous computational challenges for very large data sets. The model fitting and spatial prediction of such models typically require O(n 3) operations for a data set of size n. Various approximations of the covariance functions have been introduced to reduce the computational cost. However, most existing approximations cannot simultaneously capture both the large- and the small-scale spatial dependence. A new approximation scheme is developed to provide a high quality approximation to the covariance function at both the large and the small spatial scales. The new approximation is the summation of two parts: a reduced rank covariance and a compactly supported covariance obtained by tapering the covariance of the residual of the reduced rank approximation. Whereas the former part mainly captures the large-scale spatial variation, the latter part captures the small-scale, local variation that is unexplained by the former part. By combining the reduced rank representation and sparse matrix techniques, our approach allows for efficient computation for maximum likelihood estimation, spatial prediction and Bayesian inference. We illustrate the new approach with simulated and real data sets. © 2011 Royal Statistical Society.

Centralized manure digestion. Selection of locations and estimation of costs of large-scale manure storage application

International Nuclear Information System (INIS)

1995-03-01

A study to assess the possibilities and the consequences of the use of existing Dutch large scale manure silos at centralised anaerobic digestion plants (CAD-plants) for manure and energy-rich organic wastes is carried out. Reconstruction of these large scale manure silos into digesters for a CAD-plant is not self-evident due to the high height/diameter ratio of these silos and the extra investments that have to be made for additional facilities for roofing, insulation, mixing and heating. From the results of an inventory and selection of large scale manure silos with a storage capacity above 1,500 m 3 it appeared that there are 21 locations in The Netherlands that can be qualified for realisation of a CAD plant with a processing capacity of 100 m 3 biomass (80% manure, 20% additives) per day. These locations are found in particular at the 'shortage-areas' for manure fertilisation in the Dutch provinces Groningen and Drenthe. Three of these 21 locations with large scale silos are considered to be the most suitable for realisation of a large scale CAD-plant. The selection is based on an optimal scale for a CAD-plant of 300 m 3 material (80% manure, 20% additives) to be processed per day and the most suitable consuming markets for the biogas produced at the CAD-plant. The three locations are at Middelharnis, Veendam, and Klazinaveen. Applying the conditions as used in this study and accounting for all costs for transport of manure, additives and end-product including the costs for the storage facilities, a break-even operation might be realised at a minimum income for the additives of approximately 50 Dutch guilders per m 3 (including TAV). This income price is considerably lower than the prevailing costs for tipping or processing of organic wastes in The Netherlands. This study revealed that a break-even exploitation of a large scale CAD-plant for the processing of manure with energy-rich additives is possible. (Abstract Truncated)

Human visual system automatically represents large-scale sequential regularities.

Science.gov (United States)

Kimura, Motohiro; Widmann, Andreas; Schröger, Erich

2010-03-04

Our brain recordings reveal that large-scale sequential regularities defined across non-adjacent stimuli can be automatically represented in visual sensory memory. To show that, we adopted an auditory paradigm developed by Sussman, E., Ritter, W., and Vaughan, H. G. Jr. (1998). Predictability of stimulus deviance and the mismatch negativity. NeuroReport, 9, 4167-4170, Sussman, E., and Gumenyuk, V. (2005). Organization of sequential sounds in auditory memory. NeuroReport, 16, 1519-1523 to the visual domain by presenting task-irrelevant infrequent luminance-deviant stimuli (D, 20%) inserted among task-irrelevant frequent stimuli being of standard luminance (S, 80%) in randomized (randomized condition, SSSDSSSSSDSSSSD...) and fixed manners (fixed condition, SSSSDSSSSDSSSSD...). Comparing the visual mismatch negativity (visual MMN), an event-related brain potential (ERP) index of memory-mismatch processes in human visual sensory system, revealed that visual MMN elicited by deviant stimuli was reduced in the fixed compared to the randomized condition. Thus, the large-scale sequential regularity being present in the fixed condition (SSSSD) must have been represented in visual sensory memory. Interestingly, this effect did not occur in conditions with stimulus-onset asynchronies (SOAs) of 480 and 800 ms but was confined to the 160-ms SOA condition supporting the hypothesis that large-scale regularity extraction was based on perceptual grouping of the five successive stimuli defining the regularity. 2010 Elsevier B.V. All rights reserved.

original papers : Returns to scale in one-shot information processing when hours count

OpenAIRE

Catherine de Fontenay; Kieron J. Meagher

2001-01-01

The decentralized information processing approach pioneered by Radner and Van Zandt endogenously determines the optimal hierarchy for decision making within an organization. The simplest information processing model is the one-shot problem (one set of information to process) which serves as the testing ground for ever richer descriptions of managers and their tasks. Meagher and Van Zandt observed that an hours-based measure should be used for calculating managerial costs rather than the fixed...

Non-destructive measurement methods for large scale gaseous diffusion process equipment

International Nuclear Information System (INIS)

Mayer, R.L.; Hagenauer, R.C.; McGinnis, B.R.

1994-01-01

Two measurement methods have been developed to measure non-destructively uranium hold-up in gaseous diffusion plants. These methods include passive neutron and passive γ ray measurements. An additional method, high resolution γ ray spectroscopy, provides supplementary information about additional γ ray emitting isotopes, γ ray correction factors, 235 U/ 234 U ratios and 235 U enrichment. Many of these methods can be used as a general purpose measurement technique for large containers of uranium. Measurement applications for these methods include uranium hold-up, waste measurements, criticality safety and nuclear accountability

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

Science.gov (United States)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Inflationary tensor fossils in large-scale structure

Energy Technology Data Exchange (ETDEWEB)

Dimastrogiovanni, Emanuela [School of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455 (United States); Fasiello, Matteo [Department of Physics, Case Western Reserve University, Cleveland, OH 44106 (United States); Jeong, Donghui [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States); Kamionkowski, Marc, E-mail: ema@physics.umn.edu, E-mail: mrf65@case.edu, E-mail: duj13@psu.edu, E-mail: kamion@jhu.edu [Department of Physics and Astronomy, 3400 N. Charles St., Johns Hopkins University, Baltimore, MD 21218 (United States)

2014-12-01

Inflation models make specific predictions for a tensor-scalar-scalar three-point correlation, or bispectrum, between one gravitational-wave (tensor) mode and two density-perturbation (scalar) modes. This tensor-scalar-scalar correlation leads to a local power quadrupole, an apparent departure from statistical isotropy in our Universe, as well as characteristic four-point correlations in the current mass distribution in the Universe. So far, the predictions for these observables have been worked out only for single-clock models in which certain consistency conditions between the tensor-scalar-scalar correlation and tensor and scalar power spectra are satisfied. Here we review the requirements on inflation models for these consistency conditions to be satisfied. We then consider several examples of inflation models, such as non-attractor and solid-inflation models, in which these conditions are put to the test. In solid inflation the simplest consistency conditions are already violated whilst in the non-attractor model we find that, contrary to the standard scenario, the tensor-scalar-scalar correlator probes directly relevant model-dependent information. We work out the predictions for observables in these models. For non-attractor inflation we find an apparent local quadrupolar departure from statistical isotropy in large-scale structure but that this power quadrupole decreases very rapidly at smaller scales. The consistency of the CMB quadrupole with statistical isotropy then constrains the distance scale that corresponds to the transition from the non-attractor to attractor phase of inflation to be larger than the currently observable horizon. Solid inflation predicts clustering fossils signatures in the current galaxy distribution that may be large enough to be detectable with forthcoming, and possibly even current, galaxy surveys.

Large scale cluster computing workshop

International Nuclear Information System (INIS)

Dane Skow; Alan Silverman

2002-01-01

Recent revolutions in computer hardware and software technologies have paved the way for the large-scale deployment of clusters of commodity computers to address problems heretofore the domain of tightly coupled SMP processors. Near term projects within High Energy Physics and other computing communities will deploy clusters of scale 1000s of processors and be used by 100s to 1000s of independent users. This will expand the reach in both dimensions by an order of magnitude from the current successful production facilities. The goals of this workshop were: (1) to determine what tools exist which can scale up to the cluster sizes foreseen for the next generation of HENP experiments (several thousand nodes) and by implication to identify areas where some investment of money or effort is likely to be needed. (2) To compare and record experimences gained with such tools. (3) To produce a practical guide to all stages of planning, installing, building and operating a large computing cluster in HENP. (4) To identify and connect groups with similar interest within HENP and the larger clustering community

Information and processes underlying semantic and episodic memory across tasks, items, and individuals.

Science.gov (United States)

Cox, Gregory E; Hemmer, Pernille; Aue, William R; Criss, Amy H

2018-04-01

The development of memory theory has been constrained by a focus on isolated tasks rather than the processes and information that are common to situations in which memory is engaged. We present results from a study in which 453 participants took part in five different memory tasks: single-item recognition, associative recognition, cued recall, free recall, and lexical decision. Using hierarchical Bayesian techniques, we jointly analyzed the correlations between tasks within individuals-reflecting the degree to which tasks rely on shared cognitive processes-and within items-reflecting the degree to which tasks rely on the same information conveyed by the item. Among other things, we find that (a) the processes involved in lexical access and episodic memory are largely separate and rely on different kinds of information, (b) access to lexical memory is driven primarily by perceptual aspects of a word, (c) all episodic memory tasks rely to an extent on a set of shared processes which make use of semantic features to encode both single words and associations between words, and (d) recall involves additional processes likely related to contextual cuing and response production. These results provide a large-scale picture of memory across different tasks which can serve to drive the development of comprehensive theories of memory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Detonation and fragmentation modeling for the description of large scale vapor explosions

International Nuclear Information System (INIS)

Buerger, M.; Carachalios, C.; Unger, H.

1985-01-01

The thermal detonation modeling of large-scale vapor explosions is shown to be indispensable for realistic safety evaluations. A steady-state as well as transient detonation model have been developed including detailed descriptions of the dynamics as well as the fragmentation processes inside a detonation wave. Strong restrictions for large-scale vapor explosions are obtained from this modeling and they indicate that the reactor pressure vessel would even withstand explosions with unrealistically high masses of corium involved. The modeling is supported by comparisons with a detonation experiment and - concerning its key part - hydronamic fragmentation experiments. (orig.) [de

Large-Scale Agriculture and Outgrower Schemes in Ethiopia

DEFF Research Database (Denmark)

Wendimu, Mengistu Assefa

, the impact of large-scale agriculture and outgrower schemes on productivity, household welfare and wages in developing countries is highly contentious. Chapter 1 of this thesis provides an introduction to the study, while also reviewing the key debate in the contemporary land ‘grabbing’ and historical large...... sugarcane outgrower scheme on household income and asset stocks. Chapter 5 examines the wages and working conditions in ‘formal’ large-scale and ‘informal’ small-scale irrigated agriculture. The results in Chapter 2 show that moisture stress, the use of untested planting materials, and conflict over land...... commands a higher wage than ‘formal’ large-scale agriculture, while rather different wage determination mechanisms exist in the two sectors. Human capital characteristics (education and experience) partly explain the differences in wages within the formal sector, but play no significant role...

Cerebral methodology based computing to estimate real phenomena from large-scale nuclear simulation

International Nuclear Information System (INIS)

Suzuki, Yoshio

2011-01-01

Our final goal is to estimate real phenomena from large-scale nuclear simulations by using computing processes. Large-scale simulations mean that they include scale variety and physical complexity so that corresponding experiments and/or theories do not exist. In nuclear field, it is indispensable to estimate real phenomena from simulations in order to improve the safety and security of nuclear power plants. Here, the analysis of uncertainty included in simulations is needed to reveal sensitivity of uncertainty due to randomness, to reduce the uncertainty due to lack of knowledge and to lead a degree of certainty by verification and validation (V and V) and uncertainty quantification (UQ) processes. To realize this, we propose 'Cerebral Methodology based Computing (CMC)' as computing processes with deductive and inductive approaches by referring human reasoning processes. Our idea is to execute deductive and inductive simulations contrasted with deductive and inductive approaches. We have established its prototype system and applied it to a thermal displacement analysis of a nuclear power plant. The result shows that our idea is effective to reduce the uncertainty and to get the degree of certainty. (author)

THE DECAY OF A WEAK LARGE-SCALE MAGNETIC FIELD IN TWO-DIMENSIONAL TURBULENCE

Energy Technology Data Exchange (ETDEWEB)

Kondić, Todor; Hughes, David W.; Tobias, Steven M., E-mail: t.kondic@leeds.ac.uk [Department of Applied Mathematics, University of Leeds, Leeds LS2 9JT (United Kingdom)

2016-06-01

We investigate the decay of a large-scale magnetic field in the context of incompressible, two-dimensional magnetohydrodynamic turbulence. It is well established that a very weak mean field, of strength significantly below equipartition value, induces a small-scale field strong enough to inhibit the process of turbulent magnetic diffusion. In light of ever-increasing computer power, we revisit this problem to investigate fluids and magnetic Reynolds numbers that were previously inaccessible. Furthermore, by exploiting the relation between the turbulent diffusion of the magnetic potential and that of the magnetic field, we are able to calculate the turbulent magnetic diffusivity extremely accurately through the imposition of a uniform mean magnetic field. We confirm the strong dependence of the turbulent diffusivity on the product of the magnetic Reynolds number and the energy of the large-scale magnetic field. We compare our findings with various theoretical descriptions of this process.

In situ vitrification large-scale operational acceptance test analysis

International Nuclear Information System (INIS)

Buelt, J.L.; Carter, J.G.

1986-05-01

A thermal treatment process is currently under study to provide possible enhancement of in-place stabilization of transuranic and chemically contaminated soil sites. The process is known as in situ vitrification (ISV). In situ vitrification is a remedial action process that destroys solid and liquid organic contaminants and incorporates radionuclides into a glass-like material that renders contaminants substantially less mobile and less likely to impact the environment. A large-scale operational acceptance test (LSOAT) was recently completed in which more than 180 t of vitrified soil were produced in each of three adjacent settings. The LSOAT demonstrated that the process conforms to the functional design criteria necessary for the large-scale radioactive test (LSRT) to be conducted following verification of the performance capabilities of the process. The energy requirements and vitrified block size, shape, and mass are sufficiently equivalent to those predicted by the ISV mathematical model to confirm its usefulness as a predictive tool. The LSOAT demonstrated an electrode replacement technique, which can be used if an electrode fails, and techniques have been identified to minimize air oxidation, thereby extending electrode life. A statistical analysis was employed during the LSOAT to identify graphite collars and an insulative surface as successful cold cap subsidence techniques. The LSOAT also showed that even under worst-case conditions, the off-gas system exceeds the flow requirements necessary to maintain a negative pressure on the hood covering the area being vitrified. The retention of simulated radionuclides and chemicals in the soil and off-gas system exceeds requirements so that projected emissions are one to two orders of magnitude below the maximum permissible concentrations of contaminants at the stack

Magnetic Properties of Large-Scale Nanostructured Graphene Systems

DEFF Research Database (Denmark)

Gregersen, Søren Schou

The on-going progress in two-dimensional (2D) materials and nanostructure fabrication motivates the study of altered and combined materials. Graphene—the most studied material of the 2D family—displays unique electronic and spintronic properties. Exceptionally high electron mobilities, that surpass...... those in conventional materials such as silicon, make graphene a very interesting material for high-speed electronics. Simultaneously, long spin-diffusion lengths and spin-life times makes graphene an eligible spin-transport channel. In this thesis, we explore fundamental features of nanostructured...... graphene systems using large-scale modeling techniques. Graphene perforations, or antidots, have received substantial interest in the prospect of opening large band gaps in the otherwise gapless graphene. Motivated by recent improvements of fabrication processes, such as forming graphene antidots and layer...

A Configurable Surface-Electrode Ion Trap Design for Quantum Information Processing

International Nuclear Information System (INIS)

Liu Wei; Chen Shu-Ming; Chen Ping-Xing; Wu Wei

2013-01-01

We propose a configurable surface-electrode ion trap design to alleviate the poor reusability of the existing traps. It can architecturally and electrically support 5 mainstream modes by design reuse, thus enhancing the trap reusability and reducing the experiment setup overhead. We also develop a corresponding simulation suite which can optimize trap geometries and calculate trap parameters to control the trapped ion's classic motion. According to our analytical and simulated results, the configurable design can serve as a unified platform for basic research of large-scale quantum information processing

Computing in Large-Scale Dynamic Systems

NARCIS (Netherlands)

Pruteanu, A.S.

2013-01-01

Software applications developed for large-scale systems have always been difficult to de- velop due to problems caused by the large number of computing devices involved. Above a certain network size (roughly one hundred), necessary services such as code updating, topol- ogy discovery and data

Fires in large scale ventilation systems

International Nuclear Information System (INIS)

Gregory, W.S.; Martin, R.A.; White, B.W.; Nichols, B.D.; Smith, P.R.; Leslie, I.H.; Fenton, D.L.; Gunaji, M.V.; Blythe, J.P.

1991-01-01

This paper summarizes the experience gained simulating fires in large scale ventilation systems patterned after ventilation systems found in nuclear fuel cycle facilities. The series of experiments discussed included: (1) combustion aerosol loading of 0.61x0.61 m HEPA filters with the combustion products of two organic fuels, polystyrene and polymethylemethacrylate; (2) gas dynamic and heat transport through a large scale ventilation system consisting of a 0.61x0.61 m duct 90 m in length, with dampers, HEPA filters, blowers, etc.; (3) gas dynamic and simultaneous transport of heat and solid particulate (consisting of glass beads with a mean aerodynamic diameter of 10μ) through the large scale ventilation system; and (4) the transport of heat and soot, generated by kerosene pool fires, through the large scale ventilation system. The FIRAC computer code, designed to predict fire-induced transients in nuclear fuel cycle facility ventilation systems, was used to predict the results of experiments (2) through (4). In general, the results of the predictions were satisfactory. The code predictions for the gas dynamics, heat transport, and particulate transport and deposition were within 10% of the experimentally measured values. However, the code was less successful in predicting the amount of soot generation from kerosene pool fires, probably due to the fire module of the code being a one-dimensional zone model. The experiments revealed a complicated three-dimensional combustion pattern within the fire room of the ventilation system. Further refinement of the fire module within FIRAC is needed. (orig.)

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

Directory of Open Access Journals (Sweden)

Yingni Zhai

2014-10-01

Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the

Risk Management of Large RC Structures within Spatial Information System

DEFF Research Database (Denmark)

Qin, Jianjun; Faber, Michael Havbro

2012-01-01

Abstract: The present article addresses the development of a spatial information system (SIS), which aims to facilitate risk management of large‐scale concrete structures. The formulation of the SIS is based on ideas developed in the context of indicator‐based risk modeling for concrete structures...... subject to corrosion and geographical information system based risk modeling concerning large‐scale risk management. The term “risk management” here refers in particular to the process of condition assessment and optimization of the inspection and repair activities. The SIS facilitates the storage...... and handling of all relevant information to the risk management. The probabilistic modeling utilized in the condition assessment takes basis in a Bayesian hierarchical modeling philosophy. It facilitates the updating of risks as well as optimizing inspection plans whenever new information about the condition...

Inference of Functional Properties from Large-scale Analysis of Enzyme Superfamilies*

Science.gov (United States)

Brown, Shoshana D.; Babbitt, Patricia C.

2012-01-01

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies. PMID:22069325

Research and development of safeguards measures for the large scale reprocessing plant

Energy Technology Data Exchange (ETDEWEB)

Kikuchi, Masahiro; Sato, Yuji; Yokota, Yasuhiro; Masuda, Shoichiro; Kobayashi, Isao; Uchikoshi, Seiji; Tsutaki, Yasuhiro; Nidaira, Kazuo [Nuclear Material Control Center, Tokyo (Japan)

1994-12-31

The Government of Japan agreed on the safeguards concepts of commercial size reprocessing plant under the bilateral agreement for cooperation between the Japan and the United States. In addition, the LASCAR, that is the forum of large scale reprocessing plant safeguards, could obtain the fruitful results in the spring of 1992. The research and development of safeguards measures for the Rokkasho Reprocessing Plant should be progressed with every regard to the concepts described in both documents. Basically, the material accountancy and monitoring system should be established, based on the NRTA and other measures in order to obtain the timeliness goal for plutonium, and the un-attended mode inspection approach based on the integrated containment/surveillance system coupled with radiation monitoring in order to reduce the inspection efforts. NMCC has been studying on the following measures for a large scale reprocessing plant safeguards (1) A radiation gate monitor and integrated surveillance system (2) A near real time Shipper and Receiver Difference monitoring (3) A near real time material accountancy system operated for the bulk handling area (4) A volume measurement technique in a large scale input accountancy vessel (5) An in-process inventory estimation technique applied to the process equipment such as the pulse column and evaporator (6) Solution transfer monitoring approach applied to buffer tanks in the chemical process (7) A timely analysis technique such as a hybrid K edge densitometer operated in the on-site laboratory (J.P.N.).

Information processing in micro and meso-scale neural circuits during normal and disease states

Science.gov (United States)

Luongo, Francisco

Neural computation can occur at multiple spatial and temporal timescales. The sum total of all of these processes is to guide optimal behaviors within the context of the constraints imposed by the physical world. How the circuits of the brain achieves this goal represents a central question in systems neuroscience. Here I explore the many ways in which the circuits of the brain can process information at both the micro and meso scale. Understanding the way information is represented and processed in the brain could shed light on the neuropathology underlying complex neuropsychiatric diseases such as autism and schizophrenia. Chapter 2 establishes an experimental paradigm for assaying patterns of microcircuit activity and examines the role of dopaminergic modulation on prefrontal microcircuits. We find that dopamine type 2 (D2) receptor activation results in an increase in spontaneous activity while dopamine type 1 (D1) activation does not. Chapter 3 of this dissertation presents a study that illustrates how cholingergic activation normally produces what has been suggested as a neural substrate of attention; pairwise decorrelation in microcircuit activity. This study also shows that in two etiologicall distinct mouse models of autism, FMR1 knockout mice and Valproic Acid exposed mice, this ability to decorrelate in the presence of cholinergic activation is lost. This represents a putative microcircuit level biomarker of autism. Chapter 4 examines the structure/function relationship within the prefrontal microcircuit. Spontaneous activity in prefrontal microcircuits is shown to be organized according to a small world architecture. Interestingly, this architecture is important for one concrete function of neuronal microcircuits; the ability to produce temporally stereotyped patterns of activation. In the final chapter, we identify subnetworks in chronic intracranial electrocorticographic (ECoG) recordings using pairwise electrode coherence and dimensionality reduction

Large-scale Complex IT Systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2011-01-01

This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

Large-scale complex IT systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2012-01-01

12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

First Mile Challenges for Large-Scale IoT

KAUST Repository

Bader, Ahmed; Elsawy, Hesham; Gharbieh, Mohammad; Alouini, Mohamed-Slim; Adinoyi, Abdulkareem; Alshaalan, Furaih

2017-01-01

The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end

In situ vitrification: Preliminary results from the first large-scale radioactive test

International Nuclear Information System (INIS)

Buelt, J.L.; Westsik, J.H.

1988-02-01

The first large-scale radioactive test (LSRT) of In Situ Vitrification (ISV) has been completed. In Situ Vitrification is a process whereby joule heating immobilizes contaminated soil in place by converting it to a durable glass and crystalline waste form. The LSRT was conducted at an actual transuranic contaminated soil site on the Department of Energy's Hanford Site. The test had two objectives: (1) determine large-scale processing performance and (2) produce a waste form that can be fully evaluated as a potential technique for the final disposal of transuranic-contaminated soil sites at Hanford. This accomplishment has provided technical data to evaluate the ISV process for its potential in the final disposition of transuranic-contaminated soil sites at Hanford. Because of the test's successful completion, within a year technical data on the vitrified soil will be available to determine how well the process incorporates transuranics into the waste form and how well the form resists leaching of transuranics. Preliminary results available include retention of transuranics and other elements within the waste form during processing and the efficiency of the off-gas treatment system in removing contaminants from the gaseous effluents. 13 refs., 10 figs., 5 tabs

Using value stream mapping technique through the lean production transformation process: An implementation in a large-scaled tractor company

Directory of Open Access Journals (Sweden)

Mehmet Rıza Adalı

2017-04-01

Full Text Available Today’s world, manufacturing industries have to continue their development and continuity in more competitive environment via decreasing their costs. As a first step in the lean production process transformation is to analyze the value added activities and non-value adding activities. This study aims at applying the concepts of Value Stream Mapping (VSM in a large-scaled tractor company in Sakarya. Waste and process time are identified by mapping the current state in the production line of platform. The future state was suggested with improvements for elimination of waste and reduction of lead time, which went from 13,08 to 4,35 days. Analysis are made using current and future states to support the suggested improvements and cycle time of the production line of platform is improved 8%. Results showed that VSM is a good alternative in the decision-making for change in production process.

BigSUR: large-scale structured urban reconstruction

KAUST Repository

Kelly, Tom

2017-11-22

The creation of high-quality semantically parsed 3D models for dense metropolitan areas is a fundamental urban modeling problem. Although recent advances in acquisition techniques and processing algorithms have resulted in large-scale imagery or 3D polygonal reconstructions, such data-sources are typically noisy, and incomplete, with no semantic structure. In this paper, we present an automatic data fusion technique that produces high-quality structured models of city blocks. From coarse polygonal meshes, street-level imagery, and GIS footprints, we formulate a binary integer program that globally balances sources of error to produce semantically parsed mass models with associated facade elements. We demonstrate our system on four city regions of varying complexity; our examples typically contain densely built urban blocks spanning hundreds of buildings. In our largest example, we produce a structured model of 37 city blocks spanning a total of 1,011 buildings at a scale and quality previously impossible to achieve automatically.

BigSUR: large-scale structured urban reconstruction

KAUST Repository

Kelly, Tom; Femiani, John; Wonka, Peter; Mitra, Niloy J.

2017-01-01

The creation of high-quality semantically parsed 3D models for dense metropolitan areas is a fundamental urban modeling problem. Although recent advances in acquisition techniques and processing algorithms have resulted in large-scale imagery or 3D polygonal reconstructions, such data-sources are typically noisy, and incomplete, with no semantic structure. In this paper, we present an automatic data fusion technique that produces high-quality structured models of city blocks. From coarse polygonal meshes, street-level imagery, and GIS footprints, we formulate a binary integer program that globally balances sources of error to produce semantically parsed mass models with associated facade elements. We demonstrate our system on four city regions of varying complexity; our examples typically contain densely built urban blocks spanning hundreds of buildings. In our largest example, we produce a structured model of 37 city blocks spanning a total of 1,011 buildings at a scale and quality previously impossible to achieve automatically.

TensorFlow: A system for large-scale machine learning

OpenAIRE

Abadi, Martín; Barham, Paul; Chen, Jianmin; Chen, Zhifeng; Davis, Andy; Dean, Jeffrey; Devin, Matthieu; Ghemawat, Sanjay; Irving, Geoffrey; Isard, Michael; Kudlur, Manjunath; Levenberg, Josh; Monga, Rajat; Moore, Sherry; Murray, Derek G.

2016-01-01

TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general-purpose GPUs, and custom designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexib...

Large-scale sequential quadratic programming algorithms

Energy Technology Data Exchange (ETDEWEB)

Eldersveld, S.K.

1992-09-01

The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.

Prospects for large scale electricity storage in Denmark