An efficient and novel computation method for simulating diffraction patterns from large-scale coded apertures on large-scale focal plane arrays

Science.gov (United States)

Shrekenhamer, Abraham; Gottesman, Stephen R.

2012-10-01

A novel and memory efficient method for computing diffraction patterns produced on large-scale focal planes by largescale Coded Apertures at wavelengths where diffraction effects are significant has been developed and tested. The scheme, readily implementable on portable computers, overcomes the memory limitations of present state-of-the-art simulation codes such as Zemax. The method consists of first calculating a set of reference complex field (amplitude and phase) patterns on the focal plane produced by a single (reference) central hole, extending to twice the focal plane array size, with one such pattern for each Line-of-Sight (LOS) direction and wavelength in the scene, and with the pattern amplitude corresponding to the square-root of the spectral irradiance from each such LOS direction in the scene at selected wavelengths. Next the set of reference patterns is transformed to generate pattern sets for other holes. The transformation consists of a translational pattern shift corresponding to each hole's position offset and an electrical phase shift corresponding to each hole's position offset and incoming radiance's direction and wavelength. The set of complex patterns for each direction and wavelength is then summed coherently and squared for each detector to yield a set of power patterns unique for each direction and wavelength. Finally the set of power patterns is summed to produce the full waveband diffraction pattern from the scene. With this tool researchers can now efficiently simulate diffraction patterns produced from scenes by large-scale Coded Apertures onto large-scale focal plane arrays to support the development and optimization of coded aperture masks and image reconstruction algorithms.

The Large-Scale Structure of Scientific Method

Science.gov (United States)

Kosso, Peter

2009-01-01

The standard textbook description of the nature of science describes the proposal, testing, and acceptance of a theoretical idea almost entirely in isolation from other theories. The resulting model of science is a kind of piecemeal empiricism that misses the important network structure of scientific knowledge. Only the large-scale description of…

3D large-scale calculations using the method of characteristics

International Nuclear Information System (INIS)

Dahmani, M.; Roy, R.; Koclas, J.

2004-01-01

An overview of the computational requirements and the numerical developments made in order to be able to solve 3D large-scale problems using the characteristics method will be presented. To accelerate the MCI solver, efficient acceleration techniques were implemented and parallelization was performed. However, for the very large problems, the size of the tracking file used to store the tracks can still become prohibitive and exceed the capacity of the machine. The new 3D characteristics solver MCG will now be introduced. This methodology is dedicated to solve very large 3D problems (a part or a whole core) without spatial homogenization. In order to eliminate the input/output problems occurring when solving these large problems, we define a new computing scheme that requires more CPU resources than the usual one, based on sweeps over large tracking files. The huge capacity of storage needed in some problems and the related I/O queries needed by the characteristics solver are replaced by on-the-fly recalculation of tracks at each iteration step. Using this technique, large 3D problems are no longer I/O-bound, and distributed CPU resources can be efficiently used. (author)

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.

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)

New Distributed Multipole Methods for Accurate Electrostatics for Large-Scale Biomolecular Simultations

Science.gov (United States)

Sagui, Celeste

2006-03-01

An accurate and numerically efficient treatment of electrostatics is essential for biomolecular simulations, as this stabilizes much of the delicate 3-d structure associated with biomolecules. Currently, force fields such as AMBER and CHARMM assign ``partial charges'' to every atom in a simulation in order to model the interatomic electrostatic forces, so that the calculation of the electrostatics rapidly becomes the computational bottleneck in large-scale simulations. There are two main issues associated with the current treatment of classical electrostatics: (i) how does one eliminate the artifacts associated with the point-charges (e.g., the underdetermined nature of the current RESP fitting procedure for large, flexible molecules) used in the force fields in a physically meaningful way? (ii) how does one efficiently simulate the very costly long-range electrostatic interactions? Recently, we have dealt with both of these challenges as follows. In order to improve the description of the molecular electrostatic potentials (MEPs), a new distributed multipole analysis based on localized functions -- Wannier, Boys, and Edminston-Ruedenberg -- was introduced, which allows for a first principles calculation of the partial charges and multipoles. Through a suitable generalization of the particle mesh Ewald (PME) and multigrid method, one can treat electrostatic multipoles all the way to hexadecapoles all without prohibitive extra costs. The importance of these methods for large-scale simulations will be discussed, and examplified by simulations from polarizable DNA models.

Methods Dealing with Complexity in Selecting Joint Venture Contractors for Large-Scale Infrastructure Projects

Directory of Open Access Journals (Sweden)

Ru Liang

2018-01-01

Full Text Available The magnitude of business dynamics has increased rapidly due to increased complexity, uncertainty, and risk of large-scale infrastructure projects. This fact made it increasingly tough to “go alone” into a contractor. As a consequence, joint venture contractors with diverse strengths and weaknesses cooperatively bid for bidding. Understanding project complexity and making decision on the optimal joint venture contractor is challenging. This paper is to study how to select joint venture contractors for undertaking large-scale infrastructure projects based on a multiattribute mathematical model. Two different methods are developed to solve the problem. One is based on ideal points and the other one is based on balanced ideal advantages. Both of the two methods consider individual difference in expert judgment and contractor attributes. A case study of Hong Kong-Zhuhai-Macao-Bridge (HZMB project in China is used to demonstrate how to apply these two methods and their advantages.

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

OpenAIRE

Wang Hao; Gao Wen; Huang Qingming; Zhao Feng

2010-01-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matchin...

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

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

Science.gov (United States)

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

2010-12-01

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

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

Directory of Open Access Journals (Sweden)

Wang Hao

2010-01-01

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

Parallel supercomputing: Advanced methods, algorithms, and software for large-scale linear and nonlinear problems

Energy Technology Data Exchange (ETDEWEB)

Carey, G.F.; Young, D.M.

1993-12-31

The program outlined here is directed to research on methods, algorithms, and software for distributed parallel supercomputers. Of particular interest are finite element methods and finite difference methods together with sparse iterative solution schemes for scientific and engineering computations of very large-scale systems. Both linear and nonlinear problems will be investigated. In the nonlinear case, applications with bifurcation to multiple solutions will be considered using continuation strategies. The parallelizable numerical methods of particular interest are a family of partitioning schemes embracing domain decomposition, element-by-element strategies, and multi-level techniques. The methods will be further developed incorporating parallel iterative solution algorithms with associated preconditioners in parallel computer software. The schemes will be implemented on distributed memory parallel architectures such as the CRAY MPP, Intel Paragon, the NCUBE3, and the Connection Machine. We will also consider other new architectures such as the Kendall-Square (KSQ) and proposed machines such as the TERA. The applications will focus on large-scale three-dimensional nonlinear flow and reservoir problems with strong convective transport contributions. These are legitimate grand challenge class computational fluid dynamics (CFD) problems of significant practical interest to DOE. The methods developed and algorithms will, however, be of wider interest.

The Roles of Sparse Direct Methods in Large-scale Simulations

Energy Technology Data Exchange (ETDEWEB)

Li, Xiaoye S.; Gao, Weiguo; Husbands, Parry J.R.; Yang, Chao; Ng, Esmond G.

2005-06-27

Sparse systems of linear equations and eigen-equations arise at the heart of many large-scale, vital simulations in DOE. Examples include the Accelerator Science and Technology SciDAC (Omega3P code, electromagnetic problem), the Center for Extended Magnetohydrodynamic Modeling SciDAC(NIMROD and M3D-C1 codes, fusion plasma simulation). The Terascale Optimal PDE Simulations (TOPS)is providing high-performance sparse direct solvers, which have had significant impacts on these applications. Over the past several years, we have been working closely with the other SciDAC teams to solve their large, sparse matrix problems arising from discretization of the partial differential equations. Most of these systems are very ill-conditioned, resulting in extremely poor convergence deployed our direct methods techniques in these applications, which achieved significant scientific results as well as performance gains. These successes were made possible through the SciDAC model of computer scientists and application scientists working together to take full advantage of terascale computing systems and new algorithms research.

The Roles of Sparse Direct Methods in Large-scale Simulations

International Nuclear Information System (INIS)

Li, Xiaoye S.; Gao, Weiguo; Husbands, Parry J.R.; Yang, Chao; Ng, Esmond G.

2005-01-01

Sparse systems of linear equations and eigen-equations arise at the heart of many large-scale, vital simulations in DOE. Examples include the Accelerator Science and Technology SciDAC (Omega3P code, electromagnetic problem), the Center for Extended Magnetohydrodynamic Modeling SciDAC(NIMROD and M3D-C1 codes, fusion plasma simulation). The Terascale Optimal PDE Simulations (TOPS)is providing high-performance sparse direct solvers, which have had significant impacts on these applications. Over the past several years, we have been working closely with the other SciDAC teams to solve their large, sparse matrix problems arising from discretization of the partial differential equations. Most of these systems are very ill-conditioned, resulting in extremely poor convergence deployed our direct methods techniques in these applications, which achieved significant scientific results as well as performance gains. These successes were made possible through the SciDAC model of computer scientists and application scientists working together to take full advantage of terascale computing systems and new algorithms research

Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.

Science.gov (United States)

Gilles, Luc; Vogel, Curtis R; Ellerbroek, Brent L

2002-09-01

We introduce a multigrid preconditioned conjugate-gradient (MGCG) iterative scheme for computing open-loop wave-front reconstructors for extreme adaptive optics systems. We present numerical simulations for a 17-m class telescope with n = 48756 sensor measurement grid points within the aperture, which indicate that our MGCG method has a rapid convergence rate for a wide range of subaperture average slope measurement signal-to-noise ratios. The total computational cost is of order n log n. Hence our scheme provides for fast wave-front simulation and control in large-scale adaptive optics systems.

Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval

Directory of Open Access Journals (Sweden)

Lijuan Duan

2017-01-01

Full Text Available Hashing has been widely deployed to perform the Approximate Nearest Neighbor (ANN search for the large-scale image retrieval to solve the problem of storage and retrieval efficiency. Recently, deep hashing methods have been proposed to perform the simultaneous feature learning and the hash code learning with deep neural networks. Even though deep hashing has shown the better performance than traditional hashing methods with handcrafted features, the learned compact hash code from one deep hashing network may not provide the full representation of an image. In this paper, we propose a novel hashing indexing method, called the Deep Hashing based Fusing Index (DHFI, to generate a more compact hash code which has stronger expression ability and distinction capability. In our method, we train two different architecture’s deep hashing subnetworks and fuse the hash codes generated by the two subnetworks together to unify images. Experiments on two real datasets show that our method can outperform state-of-the-art image retrieval applications.

Test methods of total dose effects in very large scale integrated circuits

International Nuclear Information System (INIS)

He Chaohui; Geng Bin; He Baoping; Yao Yujuan; Li Yonghong; Peng Honglun; Lin Dongsheng; Zhou Hui; Chen Yusheng

2004-01-01

A kind of test method of total dose effects (TDE) is presented for very large scale integrated circuits (VLSI). The consumption current of devices is measured while function parameters of devices (or circuits) are measured. Then the relation between data errors and consumption current can be analyzed and mechanism of TDE in VLSI can be proposed. Experimental results of 60 Co γ TDEs are given for SRAMs, EEPROMs, FLASH ROMs and a kind of CPU

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.

Multilevel method for modeling large-scale networks.

Energy Technology Data Exchange (ETDEWEB)

Safro, I. M. (Mathematics and Computer Science)

2012-02-24

Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from

Large Scale Leach Test Facility: Development of equipment and methods, and comparison to MCC-1 leach tests

International Nuclear Information System (INIS)

Pellarin, D.J.; Bickford, D.F.

1985-01-01

This report describes the test equipment and methods, and documents the results of the first large-scale MCC-1 experiments in the Large Scale Leach Test Facility (LSLTF). Two experiments were performed using 1-ft-long samples sectioned from the middle of canister MS-11. The leachant used in the experiments was ultrapure deionized water - an aggressive and well characterized leachant providing high sensitivity for liquid sample analyses. All the original test plan objectives have been successfully met. Equipment and procedures have been developed for large-sample-size leach testing. The statistical reliability of the method has been determined, and ''bench mark'' data developed to relate small scale leach testing to full size waste forms. The facility is unique, and provides sampling reliability and flexibility not possible in smaller laboratory scale tests. Future use of this facility should simplify and accelerate the development of leaching models and repository specific data. The factor of less than 3 for leachability, corresponding to a 200,000/1 increase in sample volume, enhances the credibility of small scale test data which precedes this work, and supports the ability of the DWPF waste form to meet repository criteria

Synthesis of Large-Scale Single-Crystalline Monolayer WS2 Using a Semi-Sealed Method

Directory of Open Access Journals (Sweden)

Feifei Lan

2018-02-01

Full Text Available As a two-dimensional semiconductor, WS2 has attracted great attention due to its rich physical properties and potential applications. However, it is still difficult to synthesize monolayer single-crystalline WS2 at larger scale. Here, we report the growth of large-scale triangular single-crystalline WS2 with a semi-sealed installation by chemical vapor deposition (CVD. Through this method, triangular single-crystalline WS2 with an average length of more than 300 µm was obtained. The largest one was about 405 μm in length. WS2 triangles with different sizes and thicknesses were analyzed by optical microscope and atomic force microscope (AFM. Their optical properties were evaluated by Raman and photoluminescence (PL spectra. This report paves the way to fabricating large-scale single-crystalline monolayer WS2, which is useful for the growth of high-quality WS2 and its potential applications in the future.

An easy, low-cost method to transfer large-scale graphene onto polyethylene terephthalate as a transparent conductive flexible substrate

International Nuclear Information System (INIS)

Chen, Chih-Sheng; Hsieh, Chien-Kuo

2014-01-01

In this study, we develop a low-cost method for transferring a large-scale graphene film onto a flexible transparent substrate. An easily accessible method for home-made chemical vapor deposition (CVD) and a commercial photograph laminator were utilized to fabricate the low-cost graphene-based transparent conductive flexible substrate. The graphene was developed based on CVD growth on nickel foil using a carbon gas source, and the graphene thin film was easily transferred onto the laminating film via a heated photograph laminator. Field emission scanning electron microscopy and atomic force microscopy were utilized to examine the morphological characteristics of the graphene surface. Raman spectroscopy and transmission electron microscopy were utilized to examine the microstructure of the graphene. The optical–electronic properties of the transferred graphene flexible thin film were measured by ultraviolet–visible spectrometry and a four-point probe. The advantage of this method is that large-scale graphene-based thin films can be easily obtained. We provide an economical method for fabricating a graphene-based transparent conductive flexible substrate. - Highlight: • We synthesized the large-scale graphene by thermal CVD method. • A low-cost commercial photograph laminator was used to transfer graphene. • A large-scale transparent and flexible graphene substrate was obtained easily

An easy, low-cost method to transfer large-scale graphene onto polyethylene terephthalate as a transparent conductive flexible substrate

Energy Technology Data Exchange (ETDEWEB)

Chen, Chih-Sheng; Hsieh, Chien-Kuo, E-mail: jack_hsieh@mail.mcut.edu.tw

2014-11-03

In this study, we develop a low-cost method for transferring a large-scale graphene film onto a flexible transparent substrate. An easily accessible method for home-made chemical vapor deposition (CVD) and a commercial photograph laminator were utilized to fabricate the low-cost graphene-based transparent conductive flexible substrate. The graphene was developed based on CVD growth on nickel foil using a carbon gas source, and the graphene thin film was easily transferred onto the laminating film via a heated photograph laminator. Field emission scanning electron microscopy and atomic force microscopy were utilized to examine the morphological characteristics of the graphene surface. Raman spectroscopy and transmission electron microscopy were utilized to examine the microstructure of the graphene. The optical–electronic properties of the transferred graphene flexible thin film were measured by ultraviolet–visible spectrometry and a four-point probe. The advantage of this method is that large-scale graphene-based thin films can be easily obtained. We provide an economical method for fabricating a graphene-based transparent conductive flexible substrate. - Highlight: • We synthesized the large-scale graphene by thermal CVD method. • A low-cost commercial photograph laminator was used to transfer graphene. • A large-scale transparent and flexible graphene substrate was obtained easily.

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

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.

An algebraic sub-structuring method for large-scale eigenvalue calculation

International Nuclear Information System (INIS)

Yang, C.; Gao, W.; Bai, Z.; Li, X.; Lee, L.; Husbands, P.; Ng, E.

2004-01-01

We examine sub-structuring methods for solving large-scale generalized eigenvalue problems from a purely algebraic point of view. We use the term 'algebraic sub-structuring' to refer to the process of applying matrix reordering and partitioning algorithms to divide a large sparse matrix into smaller submatrices from which a subset of spectral components are extracted and combined to provide approximate solutions to the original problem. We are interested in the question of which spectral components one should extract from each sub-structure in order to produce an approximate solution to the original problem with a desired level of accuracy. Error estimate for the approximation to the smallest eigenpair is developed. The estimate leads to a simple heuristic for choosing spectral components (modes) from each sub-structure. The effectiveness of such a heuristic is demonstrated with numerical examples. We show that algebraic sub-structuring can be effectively used to solve a generalized eigenvalue problem arising from the simulation of an accelerator structure. One interesting characteristic of this application is that the stiffness matrix produced by a hierarchical vector finite elements scheme contains a null space of large dimension. We present an efficient scheme to deflate this null space in the algebraic sub-structuring process

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...

Real-time simulation of large-scale floods

Science.gov (United States)

Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.

2016-08-01

According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.

The method of arbitrarily large moments to calculate single scale processes in quantum field theory

Energy Technology Data Exchange (ETDEWEB)

Bluemlein, Johannes [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Schneider, Carsten [Johannes Kepler Univ., Linz (Austria). Research Inst. for Symbolic Computation (RISC)

2017-01-15

We device a new method to calculate a large number of Mellin moments of single scale quantities using the systems of differential and/or difference equations obtained by integration-by-parts identities between the corresponding Feynman integrals of loop corrections to physical quantities. These scalar quantities have a much simpler mathematical structure than the complete quantity. A sufficiently large set of moments may even allow the analytic reconstruction of the whole quantity considered, holding in case of first order factorizing systems. In any case, one may derive highly precise numerical representations in general using this method, which is otherwise completely analytic.

Newton Methods for Large Scale Problems in Machine Learning

Science.gov (United States)

Hansen, Samantha Leigh

2014-01-01

The focus of this thesis is on practical ways of designing optimization algorithms for minimizing large-scale nonlinear functions with applications in machine learning. Chapter 1 introduces the overarching ideas in the thesis. Chapters 2 and 3 are geared towards supervised machine learning applications that involve minimizing a sum of loss…

Deterministic methods for sensitivity and uncertainty analysis in large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Oblow, E.M.; Pin, F.G.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.; Lucius, J.L.

1987-01-01

The fields of sensitivity and uncertainty analysis are dominated by statistical techniques when large-scale modeling codes are being analyzed. This paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. The paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. The paper demonstrates the deterministic approach to sensitivity and uncertainty analysis as applied to a sample problem that models the flow of water through a borehole. The sample problem is used as a basis to compare the cumulative distribution function of the flow rate as calculated by the standard statistical methods and the DUA method. The DUA method gives a more accurate result based upon only two model executions compared to fifty executions in the statistical case

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 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...

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.)

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)

Application of spectral Lanczos decomposition method to large scale problems arising geophysics

Energy Technology Data Exchange (ETDEWEB)

Tamarchenko, T. [Western Atlas Logging Services, Houston, TX (United States)

1996-12-31

This paper presents an application of Spectral Lanczos Decomposition Method (SLDM) to numerical modeling of electromagnetic diffusion and elastic waves propagation in inhomogeneous media. SLDM approximates an action of a matrix function as a linear combination of basis vectors in Krylov subspace. I applied the method to model electromagnetic fields in three-dimensions and elastic waves in two dimensions. The finite-difference approximation of the spatial part of differential operator reduces the initial boundary-value problem to a system of ordinary differential equations with respect to time. The solution to this system requires calculating exponential and sine/cosine functions of the stiffness matrices. Large scale numerical examples are in a good agreement with the theoretical error bounds and stability estimates given by Druskin, Knizhnerman, 1987.

Workshop report on large-scale matrix diagonalization methods in chemistry theory institute

Energy Technology Data Exchange (ETDEWEB)

Bischof, C.H.; Shepard, R.L.; Huss-Lederman, S. [eds.

1996-10-01

The Large-Scale Matrix Diagonalization Methods in Chemistry theory institute brought together 41 computational chemists and numerical analysts. The goal was to understand the needs of the computational chemistry community in problems that utilize matrix diagonalization techniques. This was accomplished by reviewing the current state of the art and looking toward future directions in matrix diagonalization techniques. This institute occurred about 20 years after a related meeting of similar size. During those 20 years the Davidson method continued to dominate the problem of finding a few extremal eigenvalues for many computational chemistry problems. Work on non-diagonally dominant and non-Hermitian problems as well as parallel computing has also brought new methods to bear. The changes and similarities in problems and methods over the past two decades offered an interesting viewpoint for the success in this area. One important area covered by the talks was overviews of the source and nature of the chemistry problems. The numerical analysts were uniformly grateful for the efforts to convey a better understanding of the problems and issues faced in computational chemistry. An important outcome was an understanding of the wide range of eigenproblems encountered in computational chemistry. The workshop covered problems involving self- consistent-field (SCF), configuration interaction (CI), intramolecular vibrational relaxation (IVR), and scattering problems. In atomic structure calculations using the Hartree-Fock method (SCF), the symmetric matrices can range from order hundreds to thousands. These matrices often include large clusters of eigenvalues which can be as much as 25% of the spectrum. However, if Cl methods are also used, the matrix size can be between 10{sup 4} and 10{sup 9} where only one or a few extremal eigenvalues and eigenvectors are needed. Working with very large matrices has lead to the development of

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)

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...

The method of arbitrarily large moments to calculate single scale processes in quantum field theory

Directory of Open Access Journals (Sweden)

Johannes Blümlein

2017-08-01

Full Text Available We devise a new method to calculate a large number of Mellin moments of single scale quantities using the systems of differential and/or difference equations obtained by integration-by-parts identities between the corresponding Feynman integrals of loop corrections to physical quantities. These scalar quantities have a much simpler mathematical structure than the complete quantity. A sufficiently large set of moments may even allow the analytic reconstruction of the whole quantity considered, holding in case of first order factorizing systems. In any case, one may derive highly precise numerical representations in general using this method, which is otherwise completely analytic.

Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends.

Science.gov (United States)

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2017-07-01

Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed.

Two methods for estimating limits to large-scale wind power generation.

Science.gov (United States)

Miller, Lee M; Brunsell, Nathaniel A; Mechem, David B; Gans, Fabian; Monaghan, Andrew J; Vautard, Robert; Keith, David W; Kleidon, Axel

2015-09-08

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 10(5) km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m(-2), whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m(-2), with VKE capturing this combination in a comparatively simple way.

Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data

Directory of Open Access Journals (Sweden)

Sungho Won

2015-01-01

Full Text Available Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases. However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model. Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called “large P and small N” problem. Penalized regressions including least absolute selection and shrinkage operator (LASSO and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs. Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases. Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration.

Robust large-scale parallel nonlinear solvers for simulations.

Energy Technology Data Exchange (ETDEWEB)

Bader, Brett William; Pawlowski, Roger Patrick; Kolda, Tamara Gibson (Sandia National Laboratories, Livermore, CA)

2005-11-01

This report documents research to develop robust and efficient solution techniques for solving large-scale systems of nonlinear equations. The most widely used method for solving systems of nonlinear equations is Newton's method. While much research has been devoted to augmenting Newton-based solvers (usually with globalization techniques), little has been devoted to exploring the application of different models. Our research has been directed at evaluating techniques using different models than Newton's method: a lower order model, Broyden's method, and a higher order model, the tensor method. We have developed large-scale versions of each of these models and have demonstrated their use in important applications at Sandia. Broyden's method replaces the Jacobian with an approximation, allowing codes that cannot evaluate a Jacobian or have an inaccurate Jacobian to converge to a solution. Limited-memory methods, which have been successful in optimization, allow us to extend this approach to large-scale problems. We compare the robustness and efficiency of Newton's method, modified Newton's method, Jacobian-free Newton-Krylov method, and our limited-memory Broyden method. Comparisons are carried out for large-scale applications of fluid flow simulations and electronic circuit simulations. Results show that, in cases where the Jacobian was inaccurate or could not be computed, Broyden's method converged in some cases where Newton's method failed to converge. We identify conditions where Broyden's method can be more efficient than Newton's method. We also present modifications to a large-scale tensor method, originally proposed by Bouaricha, for greater efficiency, better robustness, and wider applicability. Tensor methods are an alternative to Newton-based methods and are based on computing a step based on a local quadratic model rather than a linear model. The advantage of Bouaricha's method is that it can use any

A novel bonding method for large scale poly(methyl methacrylate) micro- and nanofluidic chip fabrication

Science.gov (United States)

Qu, Xingtian; Li, Jinlai; Yin, Zhifu

2018-04-01

Micro- and nanofluidic chips are becoming increasing significance for biological and medical applications. Future advances in micro- and nanofluidics and its utilization in commercial applications depend on the development and fabrication of low cost and high fidelity large scale plastic micro- and nanofluidic chips. However, the majority of the present fabrication methods suffer from a low bonding rate of the chip during thermal bonding process due to air trapping between the substrate and the cover plate. In the present work, a novel bonding technique based on Ar plasma and water treatment was proposed to fully bond the large scale micro- and nanofluidic chips. The influence of Ar plasma parameters on the water contact angle and the effect of bonding conditions on the bonding rate and the bonding strength of the chip were studied. The fluorescence tests demonstrate that the 5 × 5 cm2 poly(methyl methacrylate) chip with 180 nm wide and 180 nm deep nanochannels can be fabricated without any block and leakage by our newly developed method.

SQDFT: Spectral Quadrature method for large-scale parallel O(N) Kohn-Sham calculations at high temperature

Science.gov (United States)

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

2018-03-01

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method for O(N) Kohn-Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw-Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw-Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. We further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect O(N) scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.

Large-eddy simulation with accurate implicit subgrid-scale diffusion

NARCIS (Netherlands)

B. Koren (Barry); C. Beets

1996-01-01

textabstractA method for large-eddy simulation is presented that does not use an explicit subgrid-scale diffusion term. Subgrid-scale effects are modelled implicitly through an appropriate monotone (in the sense of Spekreijse 1987) discretization method for the advective terms. Special attention is

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.

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.

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.

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.

Accelerating large-scale phase-field simulations with GPU

Directory of Open Access Journals (Sweden)

Xiaoming Shi

2017-10-01

Full Text Available A new package for accelerating large-scale phase-field simulations was developed by using GPU based on the semi-implicit Fourier method. The package can solve a variety of equilibrium equations with different inhomogeneity including long-range elastic, magnetostatic, and electrostatic interactions. Through using specific algorithm in Compute Unified Device Architecture (CUDA, Fourier spectral iterative perturbation method was integrated in GPU package. The Allen-Cahn equation, Cahn-Hilliard equation, and phase-field model with long-range interaction were solved based on the algorithm running on GPU respectively to test the performance of the package. From the comparison of the calculation results between the solver executed in single CPU and the one on GPU, it was found that the speed on GPU is enormously elevated to 50 times faster. The present study therefore contributes to the acceleration of large-scale phase-field simulations and provides guidance for experiments to design large-scale functional devices.

Particle generation methods applied in large-scale experiments on aerosol behaviour and source term studies

International Nuclear Information System (INIS)

Swiderska-Kowalczyk, M.; Gomez, F.J.; Martin, M.

1997-01-01

In aerosol research aerosols of known size, shape, and density are highly desirable because most aerosols properties depend strongly on particle size. However, such constant and reproducible generation of those aerosol particles whose size and concentration can be easily controlled, can be achieved only in laboratory-scale tests. In large scale experiments, different generation methods for various elements and compounds have been applied. This work presents, in a brief from, a review of applications of these methods used in large scale experiments on aerosol behaviour and source term. Description of generation method and generated aerosol transport conditions is followed by properties of obtained aerosol, aerosol instrumentation used, and the scheme of aerosol generation system-wherever it was available. An information concerning aerosol generation particular purposes and reference number(s) is given at the end of a particular case. These methods reviewed are: evaporation-condensation, using a furnace heating and using a plasma torch; atomization of liquid, using compressed air nebulizers, ultrasonic nebulizers and atomization of liquid suspension; and dispersion of powders. Among the projects included in this worked are: ACE, LACE, GE Experiments, EPRI Experiments, LACE-Spain. UKAEA Experiments, BNWL Experiments, ORNL Experiments, MARVIKEN, SPARTA and DEMONA. The aim chemical compounds studied are: Ba, Cs, CsOH, CsI, Ni, Cr, NaI, TeO 2 , UO 2 Al 2 O 3 , Al 2 SiO 5 , B 2 O 3 , Cd, CdO, Fe 2 O 3 , MnO, SiO 2 , AgO, SnO 2 , Te, U 3 O 8 , BaO, CsCl, CsNO 3 , Urania, RuO 2 , TiO 2 , Al(OH) 3 , BaSO 4 , Eu 2 O 3 and Sn. (Author)

Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment

Directory of Open Access Journals (Sweden)

S. Ebrahimnejad

2012-04-01

Full Text Available The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment.

Gamma Ray Tomographic Scan Method for Large Scale Industrial Plants

International Nuclear Information System (INIS)

Moon, Jin Ho; Jung, Sung Hee; Kim, Jong Bum; Park, Jang Geun

2011-01-01

The gamma ray tomography systems have been used to investigate a chemical process for last decade. There have been many cases of gamma ray tomography for laboratory scale work but not many cases for industrial scale work. Non-tomographic equipment with gamma-ray sources is often used in process diagnosis. Gamma radiography, gamma column scanning and the radioisotope tracer technique are examples of gamma ray application in industries. In spite of many outdoor non-gamma ray tomographic equipment, the most of gamma ray tomographic systems still remained as indoor equipment. But, as the gamma tomography has developed, the demand on gamma tomography for real scale plants also increased. To develop the industrial scale system, we introduced the gamma-ray tomographic system with fixed detectors and rotating source. The general system configuration is similar to 4 th generation geometry. But the main effort has been made to actualize the instant installation of the system for real scale industrial plant. This work would be a first attempt to apply the 4th generation industrial gamma tomographic scanning by experimental method. The individual 0.5-inch NaI detector was used for gamma ray detection by configuring circular shape around industrial plant. This tomographic scan method can reduce mechanical complexity and require a much smaller space than a conventional CT. Those properties make it easy to get measurement data for a real scale plant

The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.

Science.gov (United States)

Yuan, Gonglin; Sheng, Zhou; Liu, Wenjie

2016-01-01

In this paper, the Hager and Zhang (HZ) conjugate gradient (CG) method and the modified HZ (MHZ) CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables).

The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.

Directory of Open Access Journals (Sweden)

Gonglin Yuan

Full Text Available In this paper, the Hager and Zhang (HZ conjugate gradient (CG method and the modified HZ (MHZ CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables.

Progresses in application of computational ?uid dynamic methods to large scale wind turbine aerodynamics?

Institute of Scientific and Technical Information of China (English)

Zhenyu ZHANG; Ning ZHAO; Wei ZHONG; Long WANG; Bofeng XU

2016-01-01

The computational ?uid dynamics (CFD) methods are applied to aerody-namic problems for large scale wind turbines. The progresses including the aerodynamic analyses of wind turbine pro?les, numerical ?ow simulation of wind turbine blades, evalu-ation of aerodynamic performance, and multi-objective blade optimization are discussed. Based on the CFD methods, signi?cant improvements are obtained to predict two/three-dimensional aerodynamic characteristics of wind turbine airfoils and blades, and the vorti-cal structure in their wake ?ows is accurately captured. Combining with a multi-objective genetic algorithm, a 1.5 MW NH-1500 optimized blade is designed with high e?ciency in wind energy conversion.

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

Decentralised stabilising controllers for a class of large-scale linear ...

Indian Academy of Sciences (India)

subsystems resulting from a new aggregation-decomposition technique. The method has been illustrated through a numerical example of a large-scale linear system consisting of three subsystems each of the fourth order. Keywords. Decentralised stabilisation; large-scale linear systems; optimal feedback control; algebraic ...

Large-Scale Portfolio Optimization Using Multiobjective Evolutionary Algorithms and Preselection Methods

Directory of Open Access Journals (Sweden)

B. Y. Qu

2017-01-01

Full Text Available Portfolio optimization problems involve selection of different assets to invest in order to maximize the overall return and minimize the overall risk simultaneously. The complexity of the optimal asset allocation problem increases with an increase in the number of assets available to select from for investing. The optimization problem becomes computationally challenging when there are more than a few hundreds of assets to select from. To reduce the complexity of large-scale portfolio optimization, two asset preselection procedures that consider return and risk of individual asset and pairwise correlation to remove assets that may not potentially be selected into any portfolio are proposed in this paper. With these asset preselection methods, the number of assets considered to be included in a portfolio can be increased to thousands. To test the effectiveness of the proposed methods, a Normalized Multiobjective Evolutionary Algorithm based on Decomposition (NMOEA/D algorithm and several other commonly used multiobjective evolutionary algorithms are applied and compared. Six experiments with different settings are carried out. The experimental results show that with the proposed methods the simulation time is reduced while return-risk trade-off performances are significantly improved. Meanwhile, the NMOEA/D is able to outperform other compared algorithms on all experiments according to the comparative analysis.

DGDFT: A massively parallel method for large scale density functional theory calculations.

Science.gov (United States)

Hu, Wei; Lin, Lin; Yang, Chao

2015-09-28

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10(-4) Hartree/atom in terms of the error of energy and 6.2 × 10(-4) Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.

DGDFT: A massively parallel method for large scale density functional theory calculations

International Nuclear Information System (INIS)

Hu, Wei; Yang, Chao; Lin, Lin

2015-01-01

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10 −4 Hartree/atom in terms of the error of energy and 6.2 × 10 −4 Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail

DGDFT: A massively parallel method for large scale density functional theory calculations

Energy Technology Data Exchange (ETDEWEB)

Hu, Wei, E-mail: whu@lbl.gov; Yang, Chao, E-mail: cyang@lbl.gov [Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Lin, Lin, E-mail: linlin@math.berkeley.edu [Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Department of Mathematics, University of California, Berkeley, California 94720 (United States)

2015-09-28

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10{sup −4} Hartree/atom in terms of the error of energy and 6.2 × 10{sup −4} Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.

An eigenfunction method for reconstruction of large-scale and high-contrast objects.

Science.gov (United States)

Waag, Robert C; Lin, Feng; Varslot, Trond K; Astheimer, Jeffrey P

2007-07-01

A multiple-frequency inverse scattering method that uses eigenfunctions of a scattering operator is extended to image large-scale and high-contrast objects. The extension uses an estimate of the scattering object to form the difference between the scattering by the object and the scattering by the estimate of the object. The scattering potential defined by this difference is expanded in a basis of products of acoustic fields. These fields are defined by eigenfunctions of the scattering operator associated with the estimate. In the case of scattering objects for which the estimate is radial, symmetries in the expressions used to reconstruct the scattering potential greatly reduce the amount of computation. The range of parameters over which the reconstruction method works well is illustrated using calculated scattering by different objects. The method is applied to experimental data from a 48-mm diameter scattering object with tissue-like properties. The image reconstructed from measurements has, relative to a conventional B-scan formed using a low f-number at the same center frequency, significantly higher resolution and less speckle, implying that small, high-contrast structures can be demonstrated clearly using the extended method.

Novel algorithm of large-scale simultaneous linear equations

International Nuclear Information System (INIS)

Fujiwara, T; Hoshi, T; Yamamoto, S; Sogabe, T; Zhang, S-L

2010-01-01

We review our recently developed methods of solving large-scale simultaneous linear equations and applications to electronic structure calculations both in one-electron theory and many-electron theory. This is the shifted COCG (conjugate orthogonal conjugate gradient) method based on the Krylov subspace, and the most important issue for applications is the shift equation and the seed switching method, which greatly reduce the computational cost. The applications to nano-scale Si crystals and the double orbital extended Hubbard model are presented.

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

Highly Scalable Trip Grouping for Large Scale Collective Transportation Systems

DEFF Research Database (Denmark)

Gidofalvi, Gyozo; Pedersen, Torben Bach; Risch, Tore

2008-01-01

Transportation-related problems, like road congestion, parking, and pollution, are increasing in most cities. In order to reduce traffic, recent work has proposed methods for vehicle sharing, for example for sharing cabs by grouping "closeby" cab requests and thus minimizing transportation cost...... and utilizing cab space. However, the methods published so far do not scale to large data volumes, which is necessary to facilitate large-scale collective transportation systems, e.g., ride-sharing systems for large cities. This paper presents highly scalable trip grouping algorithms, which generalize previous...

A high-speed transmission method for large-scale marine seismic prospecting systems

International Nuclear Information System (INIS)

KeZhu, Song; Ping, Cao; JunFeng, Yang; FuMing, Ruan

2012-01-01

A marine seismic prospecting system is a kind of data acquisition and transmission system with large-scale coverage and synchronous multi-node acquisition. In this kind of system, data transmission is a fundamental and difficult technique. In this paper, a high-speed data-transmission method is proposed, its implications and limitations are discussed, and conclusions are drawn. The method we propose has obvious advantages over traditional techniques with respect to long-distance operation, high speed, and real-time transmission. A marine seismic system with four streamers, each 6000 m long and capable of supporting up to 1920 channels, was designed and built based on this method. The effective transmission baud rate of this system was found to reach up to 240 Mbps, while the minimum sampling interval time was as short as 0.25 ms. This system was found to achieve a good synchronization: 83 ns. Laboratory and in situ experiments showed that this marine-prospecting system could work correctly and robustly, which verifies the feasibility and validity of the method proposed in this paper. In addition to the marine seismic applications, this method can also be used in land seismic applications and certain other transmission applications such as environmental or engineering monitoring systems. (paper)

A high-speed transmission method for large-scale marine seismic prospecting systems

Science.gov (United States)

KeZhu, Song; Ping, Cao; JunFeng, Yang; FuMing, Ruan

2012-12-01

A marine seismic prospecting system is a kind of data acquisition and transmission system with large-scale coverage and synchronous multi-node acquisition. In this kind of system, data transmission is a fundamental and difficult technique. In this paper, a high-speed data-transmission method is proposed, its implications and limitations are discussed, and conclusions are drawn. The method we propose has obvious advantages over traditional techniques with respect to long-distance operation, high speed, and real-time transmission. A marine seismic system with four streamers, each 6000 m long and capable of supporting up to 1920 channels, was designed and built based on this method. The effective transmission baud rate of this system was found to reach up to 240 Mbps, while the minimum sampling interval time was as short as 0.25 ms. This system was found to achieve a good synchronization: 83 ns. Laboratory and in situ experiments showed that this marine-prospecting system could work correctly and robustly, which verifies the feasibility and validity of the method proposed in this paper. In addition to the marine seismic applications, this method can also be used in land seismic applications and certain other transmission applications such as environmental or engineering monitoring systems.

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

Fast Bound Methods for Large Scale Simulation with Application for Engineering Optimization

Science.gov (United States)

Patera, Anthony T.; Peraire, Jaime; Zang, Thomas A. (Technical Monitor)

2002-01-01

In this work, we have focused on fast bound methods for large scale simulation with application for engineering optimization. The emphasis is on the development of techniques that provide both very fast turnaround and a certificate of Fidelity; these attributes ensure that the results are indeed relevant to - and trustworthy within - the engineering context. The bound methodology which underlies this work has many different instantiations: finite element approximation; iterative solution techniques; and reduced-basis (parameter) approximation. In this grant we have, in fact, treated all three, but most of our effort has been concentrated on the first and third. We describe these below briefly - but with a pointer to an Appendix which describes, in some detail, the current "state of the art."

Seismic safety in conducting large-scale blasts

Science.gov (United States)

Mashukov, I. V.; Chaplygin, V. V.; Domanov, V. P.; Semin, A. A.; Klimkin, M. A.

2017-09-01

In mining enterprises to prepare hard rocks for excavation a drilling and blasting method is used. With the approach of mining operations to settlements the negative effect of large-scale blasts increases. To assess the level of seismic impact of large-scale blasts the scientific staff of Siberian State Industrial University carried out expertise for coal mines and iron ore enterprises. Determination of the magnitude of surface seismic vibrations caused by mass explosions was performed using seismic receivers, an analog-digital converter with recording on a laptop. The registration results of surface seismic vibrations during production of more than 280 large-scale blasts at 17 mining enterprises in 22 settlements are presented. The maximum velocity values of the Earth’s surface vibrations are determined. The safety evaluation of seismic effect was carried out according to the permissible value of vibration velocity. For cases with exceedance of permissible values recommendations were developed to reduce the level of seismic impact.

Large Scale Simulation of Hydrogen Dispersion by a Stabilized Balancing Domain Decomposition Method

Directory of Open Access Journals (Sweden)

Qing-He Yao

2014-01-01

Full Text Available The dispersion behaviour of leaking hydrogen in a partially open space is simulated by a balancing domain decomposition method in this work. An analogy of the Boussinesq approximation is employed to describe the connection between the flow field and the concentration field. The linear systems of Navier-Stokes equations and the convection diffusion equation are symmetrized by a pressure stabilized Lagrange-Galerkin method, and thus a balancing domain decomposition method is enabled to solve the interface problem of the domain decomposition system. Numerical results are validated by comparing with the experimental data and available numerical results. The dilution effect of ventilation is investigated, especially at the doors, where flow pattern is complicated and oscillations appear in the past research reported by other researchers. The transient behaviour of hydrogen and the process of accumulation in the partially open space are discussed, and more details are revealed by large scale computation.

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...

Fatigue Analysis of Large-scale Wind turbine

Directory of Open Access Journals (Sweden)

Zhu Yongli

2017-01-01

Full Text Available The paper does research on top flange fatigue damage of large-scale wind turbine generator. It establishes finite element model of top flange connection system with finite element analysis software MSC. Marc/Mentat, analyzes its fatigue strain, implements load simulation of flange fatigue working condition with Bladed software, acquires flange fatigue load spectrum with rain-flow counting method, finally, it realizes fatigue analysis of top flange with fatigue analysis software MSC. Fatigue and Palmgren-Miner linear cumulative damage theory. The analysis result indicates that its result provides new thinking for flange fatigue analysis of large-scale wind turbine generator, and possesses some practical engineering value.

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.

Preface: Introductory Remarks: Linear Scaling Methods

Science.gov (United States)

Bowler, D. R.; Fattebert, J.-L.; Gillan, M. J.; Haynes, P. D.; Skylaris, C.-K.

2008-07-01

It has been just over twenty years since the publication of the seminal paper on molecular dynamics with ab initio methods by Car and Parrinello [1], and the contribution of density functional theory (DFT) and the related techniques to physics, chemistry, materials science, earth science and biochemistry has been huge. Nevertheless, significant improvements are still being made to the performance of these standard techniques; recent work suggests that speed improvements of one or even two orders of magnitude are possible [2]. One of the areas where major progress has long been expected is in O(N), or linear scaling, DFT, in which the computer effort is proportional to the number of atoms. Linear scaling DFT methods have been in development for over ten years [3] but we are now in an exciting period where more and more research groups are working on these methods. Naturally there is a strong and continuing effort to improve the efficiency of the methods and to make them more robust. But there is also a growing ambition to apply them to challenging real-life problems. This special issue contains papers submitted following the CECAM Workshop 'Linear-scaling ab initio calculations: applications and future directions', held in Lyon from 3-6 September 2007. A noteworthy feature of the workshop is that it included a significant number of presentations involving real applications of O(N) methods, as well as work to extend O(N) methods into areas of greater accuracy (correlated wavefunction methods, quantum Monte Carlo, TDDFT) and large scale computer architectures. As well as explicitly linear scaling methods, the conference included presentations on techniques designed to accelerate and improve the efficiency of standard (that is non-linear-scaling) methods; this highlights the important question of crossover—that is, at what size of system does it become more efficient to use a linear-scaling method? As well as fundamental algorithmic questions, this brings up

Large Scale Processes and Extreme Floods in Brazil

Science.gov (United States)

Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

Solving large scale structure in ten easy steps with COLA

Energy Technology Data Exchange (ETDEWEB)

Tassev, Svetlin [Department of Astrophysical Sciences, Princeton University, 4 Ivy Lane, Princeton, NJ 08544 (United States); Zaldarriaga, Matias [School of Natural Sciences, Institute for Advanced Study, Olden Lane, Princeton, NJ 08540 (United States); Eisenstein, Daniel J., E-mail: stassev@cfa.harvard.edu, E-mail: matiasz@ias.edu, E-mail: deisenstein@cfa.harvard.edu [Center for Astrophysics, Harvard University, 60 Garden Street, Cambridge, MA 02138 (United States)

2013-06-01

We present the COmoving Lagrangian Acceleration (COLA) method: an N-body method for solving for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). Unlike standard N-body methods, the COLA method can straightforwardly trade accuracy at small-scales in order to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing, as those catalogs are essential for performing detailed error analysis for ongoing and future surveys of LSS. As an illustration, we ran a COLA-based N-body code on a box of size 100 Mpc/h with particles of mass ≈ 5 × 10{sup 9}M{sub s}un/h. Running the code with only 10 timesteps was sufficient to obtain an accurate description of halo statistics down to halo masses of at least 10{sup 11}M{sub s}un/h. This is only at a modest speed penalty when compared to mocks obtained with LPT. A standard detailed N-body run is orders of magnitude slower than our COLA-based code. The speed-up we obtain with COLA is due to the fact that we calculate the large-scale dynamics exactly using LPT, while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos. Achieving a similar level of accuracy in halo statistics without the COLA method requires at least 3 times more timesteps than when COLA is employed.

Kernel methods for large-scale genomic data analysis

Science.gov (United States)

Xing, Eric P.; Schaid, Daniel J.

2015-01-01

Machine learning, particularly kernel methods, has been demonstrated as a promising new tool to tackle the challenges imposed by today’s explosive data growth in genomics. They provide a practical and principled approach to learning how a large number of genetic variants are associated with complex phenotypes, to help reveal the complexity in the relationship between the genetic markers and the outcome of interest. In this review, we highlight the potential key role it will have in modern genomic data processing, especially with regard to integration with classical methods for gene prioritizing, prediction and data fusion. PMID:25053743

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

Science.gov (United States)

Tučník, Petr; Bureš, Vladimír

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

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

Science.gov (United States)

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

2014-04-15

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

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

Science.gov (United States)

Dednam, W.; Botha, A. E.

2015-01-01

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

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

International Nuclear Information System (INIS)

Dednam, W; Botha, A E

2015-01-01

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

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

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

Two-Level Chebyshev Filter Based Complementary Subspace Method: Pushing the Envelope of Large-Scale Electronic Structure Calculations.

Science.gov (United States)

Banerjee, Amartya S; Lin, Lin; Suryanarayana, Phanish; Yang, Chao; Pask, John E

2018-06-12

We describe a novel iterative strategy for Kohn-Sham density functional theory calculations aimed at large systems (>1,000 electrons), applicable to metals and insulators alike. In lieu of explicit diagonalization of the Kohn-Sham Hamiltonian on every self-consistent field (SCF) iteration, we employ a two-level Chebyshev polynomial filter based complementary subspace strategy to (1) compute a set of vectors that span the occupied subspace of the Hamiltonian; (2) reduce subspace diagonalization to just partially occupied states; and (3) obtain those states in an efficient, scalable manner via an inner Chebyshev filter iteration. By reducing the necessary computation to just partially occupied states and obtaining these through an inner Chebyshev iteration, our approach reduces the cost of large metallic calculations significantly, while eliminating subspace diagonalization for insulating systems altogether. We describe the implementation of the method within the framework of the discontinuous Galerkin (DG) electronic structure method and show that this results in a computational scheme that can effectively tackle bulk and nano systems containing tens of thousands of electrons, with chemical accuracy, within a few minutes or less of wall clock time per SCF iteration on large-scale computing platforms. We anticipate that our method will be instrumental in pushing the envelope of large-scale ab initio molecular dynamics. As a demonstration of this, we simulate a bulk silicon system containing 8,000 atoms at finite temperature, and obtain an average SCF step wall time of 51 s on 34,560 processors; thus allowing us to carry out 1.0 ps of ab initio molecular dynamics in approximately 28 h (of wall time).

A fast learning method for large scale and multi-class samples of SVM

Science.gov (United States)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.

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.

A new method of presentation the large-scale magnetic field structure on the Sun and solar corona

Science.gov (United States)

Ponyavin, D. I.

1995-01-01

The large-scale photospheric magnetic field, measured at Stanford, has been analyzed in terms of surface harmonics. Changes of the photospheric field which occur within whole solar rotation period can be resolved by this analysis. For this reason we used daily magnetograms of the line-of-sight magnetic field component observed from Earth over solar disc. We have estimated the period during which day-to-day full disc magnetograms must be collected. An original algorithm was applied to resolve time variations of spherical harmonics that reflect time evolution of large-scale magnetic field within solar rotation period. This method of magnetic field presentation can be useful enough in lack of direct magnetograph observations due to sometimes bad weather conditions. We have used the calculated surface harmonics to reconstruct the large-scale magnetic field structure on the source surface near the sun - the origin of heliospheric current sheet and solar wind streams. The obtained results have been compared with spacecraft in situ observations and geomagnetic activity. We tried to show that proposed technique can trace shon-time variations of heliospheric current sheet and short-lived solar wind streams. We have compared also our results with those obtained traditionally from potential field approximation and extrapolation using synoptic charts as initial boundary conditions.

Efficient numerical methods for the large-scale, parallel solution of elastoplastic contact problems

KAUST Repository

Frohne, Jö rg; Heister, Timo; Bangerth, Wolfgang

2015-01-01

© 2016 John Wiley & Sons, Ltd. Quasi-static elastoplastic contact problems are ubiquitous in many industrial processes and other contexts, and their numerical simulation is consequently of great interest in accurately describing and optimizing production processes. The key component in these simulations is the solution of a single load step of a time iteration. From a mathematical perspective, the problems to be solved in each time step are characterized by the difficulties of variational inequalities for both the plastic behavior and the contact problem. Computationally, they also often lead to very large problems. In this paper, we present and evaluate a complete set of methods that are (1) designed to work well together and (2) allow for the efficient solution of such problems. In particular, we use adaptive finite element meshes with linear and quadratic elements, a Newton linearization of the plasticity, active set methods for the contact problem, and multigrid-preconditioned linear solvers. Through a sequence of numerical experiments, we show the performance of these methods. This includes highly accurate solutions of a three-dimensional benchmark problem and scaling our methods in parallel to 1024 cores and more than a billion unknowns.

Efficient numerical methods for the large-scale, parallel solution of elastoplastic contact problems

KAUST Repository

Frohne, Jörg

2015-08-06

© 2016 John Wiley & Sons, Ltd. Quasi-static elastoplastic contact problems are ubiquitous in many industrial processes and other contexts, and their numerical simulation is consequently of great interest in accurately describing and optimizing production processes. The key component in these simulations is the solution of a single load step of a time iteration. From a mathematical perspective, the problems to be solved in each time step are characterized by the difficulties of variational inequalities for both the plastic behavior and the contact problem. Computationally, they also often lead to very large problems. In this paper, we present and evaluate a complete set of methods that are (1) designed to work well together and (2) allow for the efficient solution of such problems. In particular, we use adaptive finite element meshes with linear and quadratic elements, a Newton linearization of the plasticity, active set methods for the contact problem, and multigrid-preconditioned linear solvers. Through a sequence of numerical experiments, we show the performance of these methods. This includes highly accurate solutions of a three-dimensional benchmark problem and scaling our methods in parallel to 1024 cores and more than a billion unknowns.

Research on Large-Scale Road Network Partition and Route Search Method Combined with Traveler Preferences

Directory of Open Access Journals (Sweden)

De-Xin Yu

2013-01-01

Full Text Available Combined with improved Pallottino parallel algorithm, this paper proposes a large-scale route search method, which considers travelers’ route choice preferences. And urban road network is decomposed into multilayers effectively. Utilizing generalized travel time as road impedance function, the method builds a new multilayer and multitasking road network data storage structure with object-oriented class definition. Then, the proposed path search algorithm is verified by using the real road network of Guangzhou city as an example. By the sensitive experiments, we make a comparative analysis of the proposed path search method with the current advanced optimal path algorithms. The results demonstrate that the proposed method can increase the road network search efficiency by more than 16% under different search proportion requests, node numbers, and computing process numbers, respectively. Therefore, this method is a great breakthrough in the guidance field of urban road network.

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.

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.

Stabilization Algorithms for Large-Scale Problems

DEFF Research Database (Denmark)

Jensen, Toke Koldborg

2006-01-01

The focus of the project is on stabilization of large-scale inverse problems where structured models and iterative algorithms are necessary for computing approximate solutions. For this purpose, we study various iterative Krylov methods and their abilities to produce regularized solutions. Some......-curve. This heuristic is implemented as a part of a larger algorithm which is developed in collaboration with G. Rodriguez and P. C. Hansen. Last, but not least, a large part of the project has, in different ways, revolved around the object-oriented Matlab toolbox MOORe Tools developed by PhD Michael Jacobsen. New...

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

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.

Stability of large scale interconnected dynamical systems

International Nuclear Information System (INIS)

Akpan, E.P.

1993-07-01

Large scale systems modelled by a system of ordinary differential equations are considered and necessary and sufficient conditions are obtained for the uniform asymptotic connective stability of the systems using the method of cone-valued Lyapunov functions. It is shown that this model significantly improves the existing models. (author). 9 refs

Symplectic integrators for large scale molecular dynamics simulations: A comparison of several explicit methods

International Nuclear Information System (INIS)

Gray, S.K.; Noid, D.W.; Sumpter, B.G.

1994-01-01

We test the suitability of a variety of explicit symplectic integrators for molecular dynamics calculations on Hamiltonian systems. These integrators are extremely simple algorithms with low memory requirements, and appear to be well suited for large scale simulations. We first apply all the methods to a simple test case using the ideas of Berendsen and van Gunsteren. We then use the integrators to generate long time trajectories of a 1000 unit polyethylene chain. Calculations are also performed with two popular but nonsymplectic integrators. The most efficient integrators of the set investigated are deduced. We also discuss certain variations on the basic symplectic integration technique

Multiresolution comparison of precipitation datasets for large-scale models

Science.gov (United States)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

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.

Image-based Exploration of Large-Scale Pathline Fields

KAUST Repository

Nagoor, Omniah H.

2014-01-01

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

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.

Updating Geospatial Data from Large Scale Data Sources

Science.gov (United States)

Zhao, R.; Chen, J.; Wang, D.; Shang, Y.; Wang, Z.; Li, X.; Ai, T.

2011-08-01

In the past decades, many geospatial databases have been established at national, regional and municipal levels over the world. Nowadays, it has been widely recognized that how to update these established geo-spatial database and keep them up to date is most critical for the value of geo-spatial database. So, more and more efforts have been devoted to the continuous updating of these geospatial databases. Currently, there exist two main types of methods for Geo-spatial database updating: directly updating with remote sensing images or field surveying materials, and indirectly updating with other updated data result such as larger scale newly updated data. The former method is the basis because the update data sources in the two methods finally root from field surveying and remote sensing. The later method is often more economical and faster than the former. Therefore, after the larger scale database is updated, the smaller scale database should be updated correspondingly in order to keep the consistency of multi-scale geo-spatial database. In this situation, it is very reasonable to apply map generalization technology into the process of geo-spatial database updating. The latter is recognized as one of most promising methods of geo-spatial database updating, especially in collaborative updating environment in terms of map scale, i.e , different scale database are produced and maintained separately by different level organizations such as in China. This paper is focused on applying digital map generalization into the updating of geo-spatial database from large scale in the collaborative updating environment for SDI. The requirements of the application of map generalization into spatial database updating are analyzed firstly. A brief review on geospatial data updating based digital map generalization is then given. Based on the requirements analysis and review, we analyze the key factors for implementing updating geospatial data from large scale including technical

III. FROM SMALL TO BIG: METHODS FOR INCORPORATING LARGE SCALE DATA INTO DEVELOPMENTAL SCIENCE.

Science.gov (United States)

Davis-Kean, Pamela E; Jager, Justin

2017-06-01

For decades, developmental science has been based primarily on relatively small-scale data collections with children and families. Part of the reason for the dominance of this type of data collection is the complexity of collecting cognitive and social data on infants and small children. These small data sets are limited in both power to detect differences and the demographic diversity to generalize clearly and broadly. Thus, in this chapter we will discuss the value of using existing large-scale data sets to tests the complex questions of child development and how to develop future large-scale data sets that are both representative and can answer the important questions of developmental scientists. © 2017 The Society for Research in Child Development, Inc.

Technologies and challenges in large-scale phosphoproteomics

DEFF Research Database (Denmark)

Engholm-Keller, Kasper; Larsen, Martin Røssel

2013-01-01

become the main technique for discovery and characterization of phosphoproteins in a nonhypothesis driven fashion. In this review, we describe methods for state-of-the-art MS-based analysis of protein phosphorylation as well as the strategies employed in large-scale phosphoproteomic experiments...... with focus on the various challenges and limitations this field currently faces....

Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods, in large scale nonconvex optimization

Directory of Open Access Journals (Sweden)

Andrea Caliciotti

2018-04-01

Full Text Available In this paper, we report data and experiments related to the research article entitled “An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization” by Caliciotti et al. [1]. In particular, in Caliciotti et al. [1], large scale unconstrained optimization problems are considered by applying linesearch-based truncated Newton methods. In this framework, a key point is the reduction of the number of inner iterations needed, at each outer iteration, to approximately solving the Newton equation. A novel adaptive truncation criterion is introduced in Caliciotti et al. [1] to this aim. Here, we report the details concerning numerical experiences over a commonly used test set, namely CUTEst (Gould et al., 2015 [2]. Moreover, comparisons are reported in terms of performance profiles (Dolan and Moré, 2002 [3], adopting different parameters settings. Finally, our linesearch-based scheme is compared with a renowned trust region method, namely TRON (Lin and Moré, 1999 [4].

Large scale study of tooth enamel

International Nuclear Information System (INIS)

Bodart, F.; Deconninck, G.; Martin, M.T.

Human tooth enamel contains traces of foreign elements. The presence of these elements is related to the history and the environment of the human body and can be considered as the signature of perturbations which occur during the growth of a tooth. A map of the distribution of these traces on a large scale sample of the population will constitute a reference for further investigations of environmental effects. On hundred eighty samples of teeth were first analyzed using PIXE, backscattering and nuclear reaction techniques. The results were analyzed using statistical methods. Correlations between O, F, Na, P, Ca, Mn, Fe, Cu, Zn, Pb and Sr were observed and cluster analysis was in progress. The techniques described in the present work have been developed in order to establish a method for the exploration of very large samples of the Belgian population. (author)

Large Scale Self-Organizing Information Distribution System

National Research Council Canada - National Science Library

Low, Steven

2005-01-01

This project investigates issues in "large-scale" networks. Here "large-scale" refers to networks with large number of high capacity nodes and transmission links, and shared by a large number of users...

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.

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.

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)

Large-scale Comparative Study of Hi-C-based Chromatin 3D Structure Modeling Methods

KAUST Repository

Wang, Cheng

2018-05-17

Chromatin is a complex polymer molecule in eukaryotic cells, primarily consisting of DNA and histones. Many works have shown that the 3D folding of chromatin structure plays an important role in DNA expression. The recently proposed Chro- mosome Conformation Capture technologies, especially the Hi-C assays, provide us an opportunity to study how the 3D structures of the chromatin are organized. Based on the data from Hi-C experiments, many chromatin 3D structure modeling methods have been proposed. However, there is limited ground truth to validate these methods and no robust chromatin structure alignment algorithms to evaluate the performance of these methods. In our work, we first made a thorough literature review of 25 publicly available population Hi-C-based chromatin 3D structure modeling methods. Furthermore, to evaluate and to compare the performance of these methods, we proposed a novel data simulation method, which combined the population Hi-C data and single-cell Hi-C data without ad hoc parameters. Also, we designed a global and a local alignment algorithms to measure the similarity between the templates and the chromatin struc- tures predicted by different modeling methods. Finally, the results from large-scale comparative tests indicated that our alignment algorithms significantly outperform the algorithms in literature.

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)

Parallel Dynamic Analysis of a Large-Scale Water Conveyance Tunnel under Seismic Excitation Using ALE Finite-Element Method

Directory of Open Access Journals (Sweden)

Xiaoqing Wang

2016-01-01

Full Text Available Parallel analyses about the dynamic responses of a large-scale water conveyance tunnel under seismic excitation are presented in this paper. A full three-dimensional numerical model considering the water-tunnel-soil coupling is established and adopted to investigate the tunnel’s dynamic responses. The movement and sloshing of the internal water are simulated using the multi-material Arbitrary Lagrangian Eulerian (ALE method. Nonlinear fluid–structure interaction (FSI between tunnel and inner water is treated by using the penalty method. Nonlinear soil-structure interaction (SSI between soil and tunnel is dealt with by using the surface to surface contact algorithm. To overcome computing power limitations and to deal with such a large-scale calculation, a parallel algorithm based on the modified recursive coordinate bisection (MRCB considering the balance of SSI and FSI loads is proposed and used. The whole simulation is accomplished on Dawning 5000 A using the proposed MRCB based parallel algorithm optimized to run on supercomputers. The simulation model and the proposed approaches are validated by comparison with the added mass method. Dynamic responses of the tunnel are analyzed and the parallelism is discussed. Besides, factors affecting the dynamic responses are investigated. Better speedup and parallel efficiency show the scalability of the parallel method and the analysis results can be used to aid in the design of water conveyance tunnels.

A mixed-methods study of system-level sustainability of evidence-based practices in 12 large-scale implementation initiatives.

Science.gov (United States)

Scudder, Ashley T; Taber-Thomas, Sarah M; Schaffner, Kristen; Pemberton, Joy R; Hunter, Leah; Herschell, Amy D

2017-12-07

In recent decades, evidence-based practices (EBPs) have been broadly promoted in community behavioural health systems in the United States of America, yet reported EBP penetration rates remain low. Determining how to systematically sustain EBPs in complex, multi-level service systems has important implications for public health. This study examined factors impacting the sustainability of parent-child interaction therapy (PCIT) in large-scale initiatives in order to identify potential predictors of sustainment. A mixed-methods approach to data collection was used. Qualitative interviews and quantitative surveys examining sustainability processes and outcomes were completed by participants from 12 large-scale initiatives. Sustainment strategies fell into nine categories, including infrastructure, training, marketing, integration and building partnerships. Strategies involving integration of PCIT into existing practices and quality monitoring predicted sustainment, while financing also emerged as a key factor. The reported factors and strategies impacting sustainability varied across initiatives; however, integration into existing practices, monitoring quality and financing appear central to high levels of sustainability of PCIT in community-based systems. More detailed examination of the progression of specific activities related to these strategies may aide in identifying priorities to include in strategic planning of future large-scale initiatives. ClinicalTrials.gov ID NCT02543359 ; Protocol number PRO12060529.

Prospective and Retrospective Studies of Substance Abuse Treatment Outcomes: Methods and Results of Four Large-Scale Follow-Up Studies.

Science.gov (United States)

Gerstein, Dean R.; Johnson, Robert A.

This report compares the research methods, provider and patient characteristics, and outcome results from four large-scale followup studies of drug treatment during the 1990s: (1) the California Drug and Alcohol Treatment Assessment (CALDATA); (2) Services Research Outcomes Study (SROS); (3) National Treatment Improvement Evaluation Study (NTIES);…

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).

Topographic mapping on large-scale tidal flats with an iterative approach on the waterline method

Science.gov (United States)

Kang, Yanyan; Ding, Xianrong; Xu, Fan; Zhang, Changkuan; Ge, Xiaoping

2017-05-01

Tidal flats, which are both a natural ecosystem and a type of landscape, are of significant importance to ecosystem function and land resource potential. Morphologic monitoring of tidal flats has become increasingly important with respect to achieving sustainable development targets. Remote sensing is an established technique for the measurement of topography over tidal flats; of the available methods, the waterline method is particularly effective for constructing a digital elevation model (DEM) of intertidal areas. However, application of the waterline method is more limited in large-scale, shifting tidal flats areas, where the tides are not synchronized and the waterline is not a quasi-contour line. For this study, a topographical map of the intertidal regions within the Radial Sand Ridges (RSR) along the Jiangsu Coast, China, was generated using an iterative approach on the waterline method. A series of 21 multi-temporal satellite images (18 HJ-1A/B CCD and three Landsat TM/OLI) of the RSR area collected at different water levels within a five month period (31 December 2013-28 May 2014) was used to extract waterlines based on feature extraction techniques and artificial further modification. These 'remotely-sensed waterlines' were combined with the corresponding water levels from the 'model waterlines' simulated by a hydrodynamic model with an initial generalized DEM of exposed tidal flats. Based on the 21 heighted 'remotely-sensed waterlines', a DEM was constructed using the ANUDEM interpolation method. Using this new DEM as the input data, it was re-entered into the hydrodynamic model, and a new round of water level assignment of waterlines was performed. A third and final output DEM was generated covering an area of approximately 1900 km2 of tidal flats in the RSR. The water level simulation accuracy of the hydrodynamic model was within 0.15 m based on five real-time tide stations, and the height accuracy (root mean square error) of the final DEM was 0.182 m

A New Method Based On Modified Shuffled Frog Leaping Algorithm In Order To Solve Nonlinear Large Scale Problem

Directory of Open Access Journals (Sweden)

Aliasghar Baziar

2015-03-01

Full Text Available Abstract In order to handle large scale problems this study has used shuffled frog leaping algorithm. This algorithm is an optimization method based on natural memetics that uses a new two-phase modification to it to have a better search in the problem space. The suggested algorithm is evaluated by comparing to some well known algorithms using several benchmark optimization problems. The simulation results have clearly shown the superiority of this algorithm over other well-known methods in the area.

Advances in a framework to compare bio-dosimetry methods for triage in large-scale radiation events

International Nuclear Information System (INIS)

Flood, Ann Barry; Boyle, Holly K.; Du, Gaixin; Demidenko, Eugene; Williams, Benjamin B.; Swartz, Harold M.; Nicolalde, Roberto J.

2014-01-01

Planning and preparation for a large-scale nuclear event would be advanced by assessing the applicability of potentially available bio-dosimetry methods. Using an updated comparative framework the performance of six bio-dosimetry methods was compared for five different population sizes (100-1 000 000) and two rates for initiating processing of the marker (15 or 15 000 people per hour) with four additional time windows. These updated factors are extrinsic to the bio-dosimetry methods themselves but have direct effects on each method's ability to begin processing individuals and the size of the population that can be accommodated. The results indicate that increased population size, along with severely compromised infrastructure, increases the time needed to triage, which decreases the usefulness of many time intensive dosimetry methods. This framework and model for evaluating bio-dosimetry provides important information for policy-makers and response planners to facilitate evaluation of each method and should advance coordination of these methods into effective triage plans. (authors)

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

Sensitivity of the scale partition for variational multiscale large-eddy simulation of channel flow

NARCIS (Netherlands)

Holmen, J.; Hughes, T.J.R.; Oberai, A.A.; Wells, G.N.

2004-01-01

The variational multiscale method has been shown to perform well for large-eddy simulation (LES) of turbulent flows. The method relies upon a partition of the resolved velocity field into large- and small-scale components. The subgrid model then acts only on the small scales of motion, unlike

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.

Comparison of Conjugate Gradient Density Matrix Search and Chebyshev Expansion Methods for Avoiding Diagonalization in Large-Scale Electronic Structure Calculations

Science.gov (United States)

Bates, Kevin R.; Daniels, Andrew D.; Scuseria, Gustavo E.

1998-01-01

We report a comparison of two linear-scaling methods which avoid the diagonalization bottleneck of traditional electronic structure algorithms. The Chebyshev expansion method (CEM) is implemented for carbon tight-binding calculations of large systems and its memory and timing requirements compared to those of our previously implemented conjugate gradient density matrix search (CG-DMS). Benchmark calculations are carried out on icosahedral fullerenes from C60 to C8640 and the linear scaling memory and CPU requirements of the CEM demonstrated. We show that the CPU requisites of the CEM and CG-DMS are similar for calculations with comparable accuracy.

Algorithm 873: LSTRS: MATLAB Software for Large-Scale Trust-Region Subproblems and Regularization

DEFF Research Database (Denmark)

Rojas Larrazabal, Marielba de la Caridad; Santos, Sandra A.; Sorensen, Danny C.

2008-01-01

A MATLAB 6.0 implementation of the LSTRS method is resented. LSTRS was described in Rojas, M., Santos, S.A., and Sorensen, D.C., A new matrix-free method for the large-scale trust-region subproblem, SIAM J. Optim., 11(3):611-646, 2000. LSTRS is designed for large-scale quadratic problems with one...... at each step. LSTRS relies on matrix-vector products only and has low and fixed storage requirements, features that make it suitable for large-scale computations. In the MATLAB implementation, the Hessian matrix of the quadratic objective function can be specified either explicitly, or in the form...... of a matrix-vector multiplication routine. Therefore, the implementation preserves the matrix-free nature of the method. A description of the LSTRS method and of the MATLAB software, version 1.2, is presented. Comparisons with other techniques and applications of the method are also included. A guide...

Facile Large-scale synthesis of stable CuO nanoparticles

Science.gov (United States)

Nazari, P.; Abdollahi-Nejand, B.; Eskandari, M.; Kohnehpoushi, S.

2018-04-01

In this work, a novel approach in synthesizing the CuO nanoparticles was introduced. A sequential corrosion and detaching was proposed in the growth and dispersion of CuO nanoparticles in the optimum pH value of eight. The produced CuO nanoparticles showed six nm (±2 nm) in diameter and spherical feather with a high crystallinity and uniformity in size. In this method, a large-scale production of CuO nanoparticles (120 grams in an experimental batch) from Cu micro-particles was achieved which may met the market criteria for large-scale production of CuO nanoparticles.

PathlinesExplorer — Image-based exploration of large-scale pathline fields

KAUST Repository

Nagoor, Omniah H.

2015-10-25

PathlinesExplorer is a novel image-based tool, which has been designed to visualize large scale pathline fields on a single computer [7]. PathlinesExplorer integrates explorable images (EI) technique [4] with order-independent transparency (OIT) method [2]. What makes this method different is that it allows users to handle large data on a single workstation. Although it is a view-dependent method, PathlinesExplorer combines both exploration and modification of visual aspects without re-accessing the original huge data. Our approach is based on constructing a per-pixel linked list data structure in which each pixel contains a list of pathline 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.

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.

Non-smooth optimization methods for large-scale problems: applications to mid-term power generation planning

International Nuclear Information System (INIS)

Emiel, G.

2008-01-01

This manuscript deals with large-scale non-smooth optimization that may typically arise when performing Lagrangian relaxation of difficult problems. This technique is commonly used to tackle mixed-integer linear programming - or large-scale convex problems. For example, a classical approach when dealing with power generation planning problems in a stochastic environment is to perform a Lagrangian relaxation of the coupling constraints of demand. In this approach, a master problem coordinates local subproblems, specific to each generation unit. The master problem deals with a separable non-smooth dual function which can be maximized with, for example, bundle algorithms. In chapter 2, we introduce basic tools of non-smooth analysis and some recent results regarding incremental or inexact instances of non-smooth algorithms. However, in some situations, the dual problem may still be very hard to solve. For instance, when the number of dualized constraints is very large (exponential in the dimension of the primal problem), explicit dualization may no longer be possible or the update of dual variables may fail. In order to reduce the dual dimension, different heuristics were proposed. They involve a separation procedure to dynamically select a restricted set of constraints to be dualized along the iterations. This relax-and-cut type approach has shown its numerical efficiency in many combinatorial problems. In chapter 3, we show Primal-dual convergence of such strategy when using an adapted sub-gradient method for the dual step and under minimal assumptions on the separation procedure. Another limit of Lagrangian relaxation may appear when the dual function is separable in highly numerous or complex sub-functions. In such situation, the computational burden of solving all local subproblems may be preponderant in the whole iterative process. A natural strategy would be here to take full advantage of the dual separable structure, performing a dual iteration after having

A new method for large-scale assessment of change in ecosystem functioning in relation to land degradation

Science.gov (United States)

Horion, Stephanie; Ivits, Eva; Verzandvoort, Simone; Fensholt, Rasmus

2017-04-01

Ongoing pressures on European land are manifold with extreme climate events and non-sustainable use of land resources being amongst the most important drivers altering the functioning of the ecosystems. The protection and conservation of European natural capital is one of the key objectives of the 7th Environmental Action Plan (EAP). The EAP stipulates that European land must be managed in a sustainable way by 2020 and the UN Sustainable development goals define a Land Degradation Neutral world as one of the targets. This implies that land degradation (LD) assessment of European ecosystems must be performed repeatedly allowing for the assessment of the current state of LD as well as changes compared to a baseline adopted by the UNCCD for the objective of land degradation neutrality. However, scientifically robust methods are still lacking for large-scale assessment of LD and repeated consistent mapping of the state of terrestrial ecosystems. Historical land degradation assessments based on various methods exist, but methods are generally non-replicable or difficult to apply at continental scale (Allan et al. 2007). The current lack of research methods applicable at large spatial scales is notably caused by the non-robust definition of LD, the scarcity of field data on LD, as well as the complex inter-play of the processes driving LD (Vogt et al., 2011). Moreover, the link between LD and changes in land use (how land use changes relates to change in vegetation productivity and ecosystem functioning) is not straightforward. In this study we used the segmented trend method developed by Horion et al. (2016) for large-scale systematic assessment of hotspots of change in ecosystem functioning in relation to LD. This method alleviates shortcomings of widely used linear trend model that does not account for abrupt change, nor adequately captures the actual changes in ecosystem functioning (de Jong et al. 2013; Horion et al. 2016). Here we present a new methodology for

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.

Fabrication of Fe-6.5wt%Si Ribbons by Melt Spinning Method on Large Scale

Directory of Open Access Journals (Sweden)

Y. F. Liang

2015-01-01

Full Text Available Melt spinning method has been widely applied for fabrication of Fe-based amorphous/nanocrystalline ribbons in industry. Compared with Fe-based amorphous/nanocrystalline alloys, Fe-6.5wt%Si high silicon steel is of low cost and has comparable excellent soft magnetic properties. Due to higher melting point and absence of supercooled liquid region, fabrication of Fe-6.5wt%Si ribbons is very hard and is only on lab scale. In this paper, we report that large scale fabrication of Fe-6.5wt%Si ribbons was successful and microstructures, ordered structures, and mechanical and soft magnetic properties of the ribbons were investigated. Due to rapid solidification rate, the ribbons were of ultrafine grains, and low degree of order and exhibited some extent of bending and tensile ductility. After heat treatment, excellent soft magnetic properties were obtained. Due to near-zero magnetostriction, the ribbons are promising to be used in electric devices with high frequencies where low noises are required.

Large scale inverse problems computational methods and applications in the earth sciences

CERN Document Server

Scheichl, Robert; Freitag, Melina A; Kindermann, Stefan

2013-01-01

This book is thesecond volume of three volume series recording the ""Radon Special Semester 2011 on Multiscale Simulation & Analysis in Energy and the Environment"" taking place in Linz, Austria, October 3-7, 2011. The volume addresses the common ground in the mathematical and computational procedures required for large-scale inverse problems and data assimilation in forefront applications.

Concepts for Large Scale Hydrogen Production

OpenAIRE

Jakobsen, Daniel; Åtland, Vegar

2016-01-01

The objective of this thesis is to perform a techno-economic analysis of large-scale, carbon-lean hydrogen production in Norway, in order to evaluate various production methods and estimate a breakeven price level. Norway possesses vast energy resources and the export of oil and gas is vital to the country s economy. The results of this thesis indicate that hydrogen represents a viable, carbon-lean opportunity to utilize these resources, which can prove key in the future of Norwegian energy e...

The Hamburg large scale geostrophic ocean general circulation model. Cycle 1

International Nuclear Information System (INIS)

Maier-Reimer, E.; Mikolajewicz, U.

1992-02-01

The rationale for the Large Scale Geostrophic ocean circulation model (LSG-OGCM) is based on the observations that for a large scale ocean circulation model designed for climate studies, the relevant characteristic spatial scales are large compared with the internal Rossby radius throughout most of the ocean, while the characteristic time scales are large compared with the periods of gravity modes and barotropic Rossby wave modes. In the present version of the model, the fast modes have been filtered out by a conventional technique of integrating the full primitive equations, including all terms except the nonlinear advection of momentum, by an implicit time integration method. The free surface is also treated prognostically, without invoking a rigid lid approximation. The numerical scheme is unconditionally stable and has the additional advantage that it can be applied uniformly to the entire globe, including the equatorial and coastal current regions. (orig.)

A quasi-Newton algorithm for large-scale nonlinear equations

Directory of Open Access Journals (Sweden)

Linghua Huang

2017-02-01

Full Text Available Abstract In this paper, the algorithm for large-scale nonlinear equations is designed by the following steps: (i a conjugate gradient (CG algorithm is designed as a sub-algorithm to obtain the initial points of the main algorithm, where the sub-algorithm’s initial point does not have any restrictions; (ii a quasi-Newton algorithm with the initial points given by sub-algorithm is defined as main algorithm, where a new nonmonotone line search technique is presented to get the step length α k $\\alpha_{k}$ . The given nonmonotone line search technique can avoid computing the Jacobian matrix. The global convergence and the 1 + q $1+q$ -order convergent rate of the main algorithm are established under suitable conditions. Numerical results show that the proposed method is competitive with a similar method for large-scale problems.

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

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.

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.

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.)

Fast, large-scale hologram calculation in wavelet domain

Science.gov (United States)

Shimobaba, Tomoyoshi; Matsushima, Kyoji; Takahashi, Takayuki; Nagahama, Yuki; Hasegawa, Satoki; Sano, Marie; Hirayama, Ryuji; Kakue, Takashi; Ito, Tomoyoshi

2018-04-01

We propose a large-scale hologram calculation using WAvelet ShrinkAge-Based superpositIon (WASABI), a wavelet transform-based algorithm. An image-type hologram calculated using the WASABI method is printed on a glass substrate with the resolution of 65 , 536 × 65 , 536 pixels and a pixel pitch of 1 μm. The hologram calculation time amounts to approximately 354 s on a commercial CPU, which is approximately 30 times faster than conventional methods.

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.)

Stability and Control of Large-Scale Dynamical Systems A Vector Dissipative Systems Approach

CERN Document Server

Haddad, Wassim M

2011-01-01

Modern complex large-scale dynamical systems exist in virtually every aspect of science and engineering, and are associated with a wide variety of physical, technological, environmental, and social phenomena, including aerospace, power, communications, and network systems, to name just a few. This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, and presents the most complete treatment on vector Lyapunov function methods, vector dissipativity theory, and decentralized control architectures. Large-scale dynami

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)

Large Scale GW Calculations on the Cori System

Science.gov (United States)

Deslippe, Jack; Del Ben, Mauro; da Jornada, Felipe; Canning, Andrew; Louie, Steven

The NERSC Cori system, powered by 9000+ Intel Xeon-Phi processors, represents one of the largest HPC systems for open-science in the United States and the world. We discuss the optimization of the GW methodology for this system, including both node level and system-scale optimizations. We highlight multiple large scale (thousands of atoms) case studies and discuss both absolute application performance and comparison to calculations on more traditional HPC architectures. We find that the GW method is particularly well suited for many-core architectures due to the ability to exploit a large amount of parallelism across many layers of the system. This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program.

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.

Multiple time scale methods in tokamak magnetohydrodynamics

International Nuclear Information System (INIS)

Jardin, S.C.

1984-01-01

Several methods are discussed for integrating the magnetohydrodynamic (MHD) equations in tokamak systems on other than the fastest time scale. The dynamical grid method for simulating ideal MHD instabilities utilizes a natural nonorthogonal time-dependent coordinate transformation based on the magnetic field lines. The coordinate transformation is chosen to be free of the fast time scale motion itself, and to yield a relatively simple scalar equation for the total pressure, P = p + B 2 /2μ 0 , which can be integrated implicitly to average over the fast time scale oscillations. Two methods are described for the resistive time scale. The zero-mass method uses a reduced set of two-fluid transport equations obtained by expanding in the inverse magnetic Reynolds number, and in the small ratio of perpendicular to parallel mobilities and thermal conductivities. The momentum equation becomes a constraint equation that forces the pressure and magnetic fields and currents to remain in force balance equilibrium as they evolve. The large mass method artificially scales up the ion mass and viscosity, thereby reducing the severe time scale disparity between wavelike and diffusionlike phenomena, but not changing the resistive time scale behavior. Other methods addressing the intermediate time scales are discussed

An interactive display system for large-scale 3D models

Science.gov (United States)

Liu, Zijian; Sun, Kun; Tao, Wenbing; Liu, Liman

2018-04-01

With the improvement of 3D reconstruction theory and the rapid development of computer hardware technology, the reconstructed 3D models are enlarging in scale and increasing in complexity. Models with tens of thousands of 3D points or triangular meshes are common in practical applications. Due to storage and computing power limitation, it is difficult to achieve real-time display and interaction with large scale 3D models for some common 3D display software, such as MeshLab. In this paper, we propose a display system for large-scale 3D scene models. We construct the LOD (Levels of Detail) model of the reconstructed 3D scene in advance, and then use an out-of-core view-dependent multi-resolution rendering scheme to realize the real-time display of the large-scale 3D model. With the proposed method, our display system is able to render in real time while roaming in the reconstructed scene and 3D camera poses can also be displayed. Furthermore, the memory consumption can be significantly decreased via internal and external memory exchange mechanism, so that it is possible to display a large scale reconstructed scene with over millions of 3D points or triangular meshes in a regular PC with only 4GB RAM.

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.

Topographically Engineered Large Scale Nanostructures for Plasmonic Biosensing

Science.gov (United States)

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

2016-04-01

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

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

Science.gov (United States)

Zhang, Shaoting; Metaxas, Dimitris

2016-10-01

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

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.

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.

Engineering large-scale agent-based systems with consensus

Science.gov (United States)

Bokma, A.; Slade, A.; Kerridge, S.; Johnson, K.

1994-01-01

The paper presents the consensus method for the development of large-scale agent-based systems. Systems can be developed as networks of knowledge based agents (KBA) which engage in a collaborative problem solving effort. The method provides a comprehensive and integrated approach to the development of this type of system. This includes a systematic analysis of user requirements as well as a structured approach to generating a system design which exhibits the desired functionality. There is a direct correspondence between system requirements and design components. The benefits of this approach are that requirements are traceable into design components and code thus facilitating verification. The use of the consensus method with two major test applications showed it to be successful and also provided valuable insight into problems typically associated with the development of large systems.

Features of the method of large-scale paleolandscape reconstructions

Science.gov (United States)

Nizovtsev, Vyacheslav; Erman, Natalia; Graves, Irina

2017-04-01

The method of paleolandscape reconstructions was tested in the key area of the basin of the Central Dubna, located at the junction of the Taldom and Sergiev Posad districts of the Moscow region. A series of maps was created which shows paleoreconstructions of the original (indigenous) living environment of initial settlers during main time periods of the Holocene age and features of human interaction with landscapes at the early stages of economic development of the territory (in the early and middle Holocene). The sequence of these works is as follows. 1. Comprehensive analysis of topographic maps of different scales and aerial and satellite images, stock materials of geological and hydrological surveys and prospecting of peat deposits, archaeological evidence on ancient settlements, palynological and osteological analysis, analysis of complex landscape and archaeological studies. 2. Mapping of factual material and analyzing of the spatial distribution of archaeological sites were performed. 3. Running of a large-scale field landscape mapping (sample areas) and compiling of maps of the modern landscape structure. On this basis, edaphic properties of the main types of natural boundaries were analyzed and their resource base was determined. 4. Reconstruction of lake-river system during the main periods of the Holocene. The boundaries of restored paleolakes were determined based on power and territorial confinement of decay ooze. 5. On the basis of landscape and edaphic method the actual paleolandscape reconstructions for the main periods of the Holocene were performed. During the reconstructions of the original, indigenous flora we relied on data of palynological studies conducted on the studied area or in similar landscape conditions. 6. The result was a retrospective analysis and periodization of the settlement process, economic development and the formation of the first anthropogenically transformed landscape complexes. The reconstruction of the dynamics of the

Large-scale Homogenization of Bulk Materials in Mammoth Silos

NARCIS (Netherlands)

Schott, D.L.

2004-01-01

This doctoral thesis concerns the large-scale homogenization of bulk materials in mammoth silos. The objective of this research was to determine the best stacking and reclaiming method for homogenization in mammoth silos. For this purpose a simulation program was developed to estimate the

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

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

A new method to determine large scale structure from the luminosity distance

International Nuclear Information System (INIS)

Romano, Antonio Enea; Chiang, Hsu-Wen; Chen, Pisin

2014-01-01

The luminosity distance can be used to determine the properties of large scale structure around the observer. To this purpose we develop a new inversion method to map luminosity distance to a Lemaitre–Tolman–Bondi (LTB) metric based on the use of the exact analytical solution for Einstein equations. The main advantages of this approach are an improved numerical accuracy and stability, an exact analytical setting of the initial conditions for the differential equations which need to be solved and the validity for any sign of the functions determining the LTB geometry. Given the fully analytical form of the differential equations, this method also simplifies the calculation of the red-shift expansion around the apparent horizon point where the numerical solution becomes unstable. We test the method by inverting the supernovae Ia luminosity distance function corresponding to the best fit ΛCDM model. We find that only a limited range of initial conditions is compatible with observations, or a transition from red to blue-shift can occur at relatively low red-shift. Despite LTB solutions without a cosmological constant have been shown not to be compatible with all different set of available observational data, those studies normally fit data assuming a special functional ansatz for the inhomogeneity profile, which often depend only on few parameters. Inversion methods on the contrary are able to fully explore the freedom in fixing the functions which determine a LTB solution. Another important possible application is not about LTB solutions as cosmological models, but rather as tools to study the effects on the observations made by a generic observer located in an inhomogeneous region of the Universe where a fully non perturbative treatment involving exact solutions of Einstein equations is required. (paper)

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

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.

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

An Ensemble Three-Dimensional Constrained Variational Analysis Method to Derive Large-Scale Forcing Data for Single-Column Models

Science.gov (United States)

Tang, Shuaiqi

Atmospheric vertical velocities and advective tendencies are essential as large-scale forcing data to drive single-column models (SCM), cloud-resolving models (CRM) and large-eddy simulations (LES). They cannot be directly measured or easily calculated with great accuracy from field measurements. In the Atmospheric Radiation Measurement (ARM) program, a constrained variational algorithm (1DCVA) has been used to derive large-scale forcing data over a sounding network domain with the aid of flux measurements at the surface and top of the atmosphere (TOA). We extend the 1DCVA algorithm into three dimensions (3DCVA) along with other improvements to calculate gridded large-scale forcing data. We also introduce an ensemble framework using different background data, error covariance matrices and constraint variables to quantify the uncertainties of the large-scale forcing data. The results of sensitivity study show that the derived forcing data and SCM simulated clouds are more sensitive to the background data than to the error covariance matrices and constraint variables, while horizontal moisture advection has relatively large sensitivities to the precipitation, the dominate constraint variable. Using a mid-latitude cyclone case study in March 3rd, 2000 at the ARM Southern Great Plains (SGP) site, we investigate the spatial distribution of diabatic heating sources (Q1) and moisture sinks (Q2), and show that they are consistent with the satellite clouds and intuitive structure of the mid-latitude cyclone. We also evaluate the Q1 and Q2 in analysis/reanalysis, finding that the regional analysis/reanalysis all tend to underestimate the sub-grid scale upward transport of moist static energy in the lower troposphere. With the uncertainties from large-scale forcing data and observation specified, we compare SCM results and observations and find that models have large biases on cloud properties which could not be fully explained by the uncertainty from the large-scale forcing

Large scale anisotropy studies with the Auger Observatory

International Nuclear Information System (INIS)

Santos, E.M.; Letessier-Selvon, A.

2006-01-01

With the increasing Auger surface array data sample of the highest energy cosmic rays, large scale anisotropy studies at this part of the spectrum become a promising path towards the understanding of the origin of ultra-high energy cosmic particles. We describe the methods underlying the search for distortions in the cosmic rays arrival directions over large angular scales, that is, bigger than those commonly employed in the search for correlations with point-like sources. The widely used tools, known as coverage maps, are described and some of the issues involved in their calculations are presented through Monte Carlo based studies. Coverage computation requires a deep knowledge on the local detection efficiency, including the influence of weather parameters like temperature and pressure. Particular attention is devoted to a new proposed method to extract the coverage, based upon the assumption of time factorization of an extensive air shower detector acceptance. We use Auger monitoring data to test the goodness of such a hypothesis. We finally show the necessity of using more than one coverage to extract any possible anisotropic pattern on the sky, by pointing to some of the biases present in commonly used methods based, for example, on the scrambling of the UTC arrival times for each event. (author)

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.

Facile Large-Scale Synthesis of 5- and 6-Carboxyfluoresceins

DEFF Research Database (Denmark)

Hammershøj, Peter; Ek, Pramod Kumar; Harris, Pernille

2015-01-01

A series of fluorescein dyes have been prepared from a common precursor through a very simple synthetic procedure, giving access to important precursors for fluorescent probes. The method has proven an efficient access to regioisomerically pure 5- and 6-carboxyfluoresceins on a large scale, in good...

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.

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 scale organized motion in isothermal swirling flow through an axisymmetric dump combustor

International Nuclear Information System (INIS)

Daddis, E.D.; Lieber, B.B.; Nejad, A.S.; Ahmed, S.A.

1990-01-01

This paper reports on velocity measurements that were obtained in a model axisymmetric dump combustor which included a coaxial swirler by means of a two component laser Doppler velocimeter (LDV) at a Reynolds number of 125,000. The frequency spectrum of the velocity fluctuations is obtained via the Fast Fourier Transform (FFT). The velocity field downstream of the dump plane is characterized, in addition to background turbulence, by large scale organized structures which are manifested as sharp spikes of the spectrum at relatively low frequencies. The decomposition of velocity disturbances to background turbulence and large scale structures can then be achieved through spectral methods which include matched filters and spectral factorization. These methods are demonstrated here for axial velocity obtained one step height downstream of the dump plane. Subsequent analysis of the various velocity disturbances shows that large scale structures account for about 25% of the apparent normal stresses at this particular location. Naturally, large scale structures evolve spatially and their contribution to the apparent stress tensor may vary depending on the location in the flow field

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.

Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs

Directory of Open Access Journals (Sweden)

Andrew J Reagan

2017-10-01

Full Text Available Abstract The emergence and global adoption of social media has rendered possible the real-time estimation of population-scale sentiment, an extraordinary capacity which has profound implications for our understanding of human behavior. Given the growing assortment of sentiment-measuring instruments, it is imperative to understand which aspects of sentiment dictionaries contribute to both their classification accuracy and their ability to provide richer understanding of texts. Here, we perform detailed, quantitative tests and qualitative assessments of 6 dictionary-based methods applied to 4 different corpora, and briefly examine a further 20 methods. We show that while inappropriate for sentences, dictionary-based methods are generally robust in their classification accuracy for longer texts. Most importantly they can aid understanding of texts with reliable and meaningful word shift graphs if (1 the dictionary covers a sufficiently large portion of a given text’s lexicon when weighted by word usage frequency; and (2 words are scored on a continuous scale.

Dynamic Reactive Power Compensation of Large Scale Wind Integrated Power System

DEFF Research Database (Denmark)

Rather, Zakir Hussain; Chen, Zhe; Thøgersen, Paul

2015-01-01

wind turbines especially wind farms with additional grid support functionalities like dynamic support (e,g dynamic reactive power support etc.) and ii) refurbishment of existing conventional central power plants to synchronous condensers could be one of the efficient, reliable and cost effective option......Due to progressive displacement of conventional power plants by wind turbines, dynamic security of large scale wind integrated power systems gets significantly compromised. In this paper we first highlight the importance of dynamic reactive power support/voltage security in large scale wind...... integrated power systems with least presence of conventional power plants. Then we propose a mixed integer dynamic optimization based method for optimal dynamic reactive power allocation in large scale wind integrated power systems. One of the important aspects of the proposed methodology is that unlike...

Large scale Brownian dynamics of confined suspensions of rigid particles

Science.gov (United States)

Sprinkle, Brennan; Balboa Usabiaga, Florencio; Patankar, Neelesh A.; Donev, Aleksandar

2017-12-01

We introduce methods for large-scale Brownian Dynamics (BD) simulation of many rigid particles of arbitrary shape suspended in a fluctuating fluid. Our method adds Brownian motion to the rigid multiblob method [F. Balboa Usabiaga et al., Commun. Appl. Math. Comput. Sci. 11(2), 217-296 (2016)] at a cost comparable to the cost of deterministic simulations. We demonstrate that we can efficiently generate deterministic and random displacements for many particles using preconditioned Krylov iterative methods, if kernel methods to efficiently compute the action of the Rotne-Prager-Yamakawa (RPY) mobility matrix and its "square" root are available for the given boundary conditions. These kernel operations can be computed with near linear scaling for periodic domains using the positively split Ewald method. Here we study particles partially confined by gravity above a no-slip bottom wall using a graphical processing unit implementation of the mobility matrix-vector product, combined with a preconditioned Lanczos iteration for generating Brownian displacements. We address a major challenge in large-scale BD simulations, capturing the stochastic drift term that arises because of the configuration-dependent mobility. Unlike the widely used Fixman midpoint scheme, our methods utilize random finite differences and do not require the solution of resistance problems or the computation of the action of the inverse square root of the RPY mobility matrix. We construct two temporal schemes which are viable for large-scale simulations, an Euler-Maruyama traction scheme and a trapezoidal slip scheme, which minimize the number of mobility problems to be solved per time step while capturing the required stochastic drift terms. We validate and compare these schemes numerically by modeling suspensions of boomerang-shaped particles sedimented near a bottom wall. Using the trapezoidal scheme, we investigate the steady-state active motion in dense suspensions of confined microrollers, whose

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

Science.gov (United States)

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

2016-04-01

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

Tile-Based Semisupervised Classification of Large-Scale VHR Remote Sensing Images

Directory of Open Access Journals (Sweden)

Haikel Alhichri

2018-01-01

Full Text Available This paper deals with the problem of the classification of large-scale very high-resolution (VHR remote sensing (RS images in a semisupervised scenario, where we have a limited training set (less than ten training samples per class. Typical pixel-based classification methods are unfeasible for large-scale VHR images. Thus, as a practical and efficient solution, we propose to subdivide the large image into a grid of tiles and then classify the tiles instead of classifying pixels. Our proposed method uses the power of a pretrained convolutional neural network (CNN to first extract descriptive features from each tile. Next, a neural network classifier (composed of 2 fully connected layers is trained in a semisupervised fashion and used to classify all remaining tiles in the image. This basically presents a coarse classification of the image, which is sufficient for many RS application. The second contribution deals with the employment of the semisupervised learning to improve the classification accuracy. We present a novel semisupervised approach which exploits both the spectral and spatial relationships embedded in the remaining unlabelled tiles. In particular, we embed a spectral graph Laplacian in the hidden layer of the neural network. In addition, we apply regularization of the output labels using a spatial graph Laplacian and the random Walker algorithm. Experimental results obtained by testing the method on two large-scale images acquired by the IKONOS2 sensor reveal promising capabilities of this method in terms of classification accuracy even with less than ten training samples per class.

Disinformative data in large-scale hydrological modelling

Directory of Open Access Journals (Sweden)

A. Kauffeldt

2013-07-01

Full Text Available Large-scale hydrological modelling has become an important tool for the study of global and regional water resources, climate impacts, and water-resources management. However, modelling efforts over large spatial domains are fraught with problems of data scarcity, uncertainties and inconsistencies between model forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aimed at identifying data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. The consistency between (i basin areas for different hydrographic datasets, and (ii between climate data (precipitation and potential evaporation and discharge data, was examined in terms of how well basin areas were represented in the flow networks and the possibility of water-balance closure. It was found that (i most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between flow-network datasets and archived basin areas, (ii basins exhibiting too-high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and (iii the occurrence of basins exhibiting losses exceeding the potential-evaporation limit was strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. Some inconsistencies may be resolved by considering sub-grid variability in climate data, surface-dependent potential-evaporation estimates, etc., but further studies are needed to determine the reasons for the inconsistencies found. Our results emphasise the need for pre-modelling data analysis to identify dataset inconsistencies as an important first step in any large-scale study. Applying data-screening methods before modelling should also increase our chances to draw robust conclusions from subsequent

Large Scale Metric Learning for Distance-Based Image Classification on Open Ended Data Sets

NARCIS (Netherlands)

Mensink, T.; Verbeek, J.; Perronnin, F.; Csurka, G.; Farinella, G.M.; Battiato, S.; Cipolla, R,

2013-01-01

Many real-life large-scale datasets are open-ended and dynamic: new images are continuously added to existing classes, new classes appear over time, and the semantics of existing classes might evolve too. Therefore, we study large-scale image classification methods that can incorporate new classes

Mathematical methods in material science and large scale optimization workshops: Final report, June 1, 1995-November 30, 1996

Energy Technology Data Exchange (ETDEWEB)

Friedman, A. [Minnesota Univ., Minneapolis, MN (United States). Inst. for Mathematics and Its Applications

1996-12-01

The summer program in Large Scale Optimization concentrated largely on process engineering, aerospace engineering, inverse problems and optimal design, and molecular structure and protein folding. The program brought together application people, optimizers, and mathematicians with interest in learning about these topics. Three proceedings volumes are being prepared. The year in Materials Sciences deals with disordered media and percolation, phase transformations, composite materials, microstructure; topological and geometric methods as well as statistical mechanics approach to polymers (included were Monte Carlo simulation for polymers); miscellaneous other topics such as nonlinear optical material, particulate flow, and thin film. All these activities saw strong interaction among material scientists, mathematicians, physicists, and engineers. About 8 proceedings volumes are being prepared.

Role of optometry school in single day large scale school vision testing

Science.gov (United States)

Anuradha, N; Ramani, Krishnakumar

2015-01-01

Background: School vision testing aims at identification and management of refractive errors. Large-scale school vision testing using conventional methods is time-consuming and demands a lot of chair time from the eye care professionals. A new strategy involving a school of optometry in single day large scale school vision testing is discussed. Aim: The aim was to describe a new approach of performing vision testing of school children on a large scale in a single day. Materials and Methods: A single day vision testing strategy was implemented wherein 123 members (20 teams comprising optometry students and headed by optometrists) conducted vision testing for children in 51 schools. School vision testing included basic vision screening, refraction, frame measurements, frame choice and referrals for other ocular problems. Results: A total of 12448 children were screened, among whom 420 (3.37%) were identified to have refractive errors. 28 (1.26%) children belonged to the primary, 163 to middle (9.80%), 129 (4.67%) to secondary and 100 (1.73%) to the higher secondary levels of education respectively. 265 (2.12%) children were referred for further evaluation. Conclusion: Single day large scale school vision testing can be adopted by schools of optometry to reach a higher number of children within a short span. PMID:25709271

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...

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

Automatic Measurement in Large-Scale Space with the Laser Theodolite and Vision Guiding Technology

Directory of Open Access Journals (Sweden)

Bin Wu

2013-01-01

Full Text Available The multitheodolite intersection measurement is a traditional approach to the coordinate measurement in large-scale space. However, the procedure of manual labeling and aiming results in the low automation level and the low measuring efficiency, and the measurement accuracy is affected easily by the manual aiming error. Based on the traditional theodolite measuring methods, this paper introduces the mechanism of vision measurement principle and presents a novel automatic measurement method for large-scale space and large workpieces (equipment combined with the laser theodolite measuring and vision guiding technologies. The measuring mark is established on the surface of the measured workpiece by the collimating laser which is coaxial with the sight-axis of theodolite, so the cooperation targets or manual marks are no longer needed. With the theoretical model data and the multiresolution visual imaging and tracking technology, it can realize the automatic, quick, and accurate measurement of large workpieces in large-scale space. Meanwhile, the impact of artificial error is reduced and the measuring efficiency is improved. Therefore, this method has significant ramification for the measurement of large workpieces, such as the geometry appearance characteristics measuring of ships, large aircraft, and spacecraft, and deformation monitoring for large building, dams.

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.

Constructing sites on a large scale

DEFF Research Database (Denmark)

Braae, Ellen Marie; Tietjen, Anne

2011-01-01

Since the 1990s, the regional scale has regained importance in urban and landscape design. In parallel, the focus in design tasks has shifted from master plans for urban extension to strategic urban transformation projects. A prominent example of a contemporary spatial development approach...... for setting the design brief in a large scale urban landscape in Norway, the Jaeren region around the city of Stavanger. In this paper, we first outline the methodological challenges and then present and discuss the proposed method based on our teaching experiences. On this basis, we discuss aspects...... is the IBA Emscher Park in the Ruhr area in Germany. Over a 10 years period (1988-1998), more than a 100 local transformation projects contributed to the transformation from an industrial to a post-industrial region. The current paradigm of planning by projects reinforces the role of the design disciplines...

Large-Scale Parallel Finite Element Analysis of the Stress Singular Problems

International Nuclear Information System (INIS)

Noriyuki Kushida; Hiroshi Okuda; Genki Yagawa

2002-01-01

In this paper, the convergence behavior of large-scale parallel finite element method for the stress singular problems was investigated. The convergence behavior of iterative solvers depends on the efficiency of the pre-conditioners. However, efficiency of pre-conditioners may be influenced by the domain decomposition that is necessary for parallel FEM. In this study the following results were obtained: Conjugate gradient method without preconditioning and the diagonal scaling preconditioned conjugate gradient method were not influenced by the domain decomposition as expected. symmetric successive over relaxation method preconditioned conjugate gradient method converged 6% faster as maximum if the stress singular area was contained in one sub-domain. (authors)

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 ...

Canonical symplectic particle-in-cell method for long-term large-scale simulations of the Vlasov–Maxwell equations

Energy Technology Data Exchange (ETDEWEB)

Qin, Hong; Liu, Jian; Xiao, Jianyuan; Zhang, Ruili; He, Yang; Wang, Yulei; Sun, Yajuan; Burby, Joshua W.; Ellison, Leland; Zhou, Yao

2015-12-14

Particle-in-cell (PIC) simulation is the most important numerical tool in plasma physics. However, its long-term accuracy has not been established. To overcome this difficulty, we developed a canonical symplectic PIC method for the Vlasov-Maxwell system by discretising its canonical Poisson bracket. A fast local algorithm to solve the symplectic implicit time advance is discovered without root searching or global matrix inversion, enabling applications of the proposed method to very large-scale plasma simulations with many, e.g. 10(9), degrees of freedom. The long-term accuracy and fidelity of the algorithm enables us to numerically confirm Mouhot and Villani's theory and conjecture on nonlinear Landau damping over several orders of magnitude using the PIC method, and to calculate the nonlinear evolution of the reflectivity during the mode conversion process from extraordinary waves to Bernstein waves.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

Science.gov (United States)

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant

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.

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

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.

``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.

Improvement of methods for large scale sequencing; application to human Xq28

Energy Technology Data Exchange (ETDEWEB)

Gibbs, R.A.; Andersson, B.; Wentland, M.A. [Baylor College of Medicine, Houston, TX (United States)] [and others

1994-09-01

Sequencing of a one-metabase region of Xq28, spanning the FRAXA and IDS loci has been undertaken in order to investigate the practicality of the shotgun approach for large scale sequencing and as a platform to develop improved methods. The efficiency of several steps in the shotgun sequencing strategy has been increased using PCR-based approaches. An improved method for preparation of M13 libraries has been developed. This protocol combines a previously described adaptor-based protocol with the uracil DNA glycosylase (UDG)-cloning procedure. The efficiency of this procedure has been found to be up to 100-fold higher than that of previously used protocols. In addition the novel protocol is more reliable and thus easy to establish in a laboratory. The method has also been adapted for the simultaneous shotgun sequencing of multiple short fragments by concentrating them before library construction is presented. This protocol is suitable for rapid characterization of cDNA clones. A library was constructed from 15 PCR-amplified and concentrated human cDNA inserts, and the insert sequences could easily be identified as separate contigs during the assembly process and the sequence coverage was even along each fragment. Using this strategy, the fine structures of the FraxA and IDS loci have been revealed and several EST homologies indicating novel expressed sequences have been identified. Use of PCR to close repetitive regions that are difficult to clone was tested by determination of the sequence of a cosmid mapping DXS455 in Xq28, containing a polymorphic VNTR. The region containing the VNTR was not represented in the shotgun library, but by designing PCR primers in the sequences flanking the gap and by cloning and sequencing the PCR product, the fine structure of the VNTR has been determined. It was found to be an AT-rich VNTR with a repeated 25-mer at the center.

Analysis of environmental impact assessment for large-scale X-ray medical equipments

International Nuclear Information System (INIS)

Fu Jin; Pei Chengkai

2011-01-01

Based on an Environmental Impact Assessment (EIA) project, this paper elaborates the basic analysis essentials of EIA for the sales project of large-scale X-ray medical equipment, and provides the analysis procedure of environmental impact and dose estimation method under normal and accident conditions. The key points of EIA for the sales project of large-scale X-ray medical equipment include the determination of pollution factor and management limit value according to the project's actual situation, the utilization of various methods of assessment and prediction such as analogy, actual measurement and calculation to analyze, monitor, calculate and predict the pollution during normal and accident condition. (authors)

Less is more: regularization perspectives on large scale machine learning

CERN Multimedia

CERN. Geneva

2017-01-01

Deep learning based techniques provide a possible solution at the expanse of theoretical guidance and, especially, of computational requirements. It is then a key challenge for large scale machine learning to devise approaches guaranteed to be accurate and yet computationally efficient. In this talk, we will consider a regularization perspectives on machine learning appealing to classical ideas in linear algebra and inverse problems to scale-up dramatically nonparametric methods such as kernel methods, often dismissed because of prohibitive costs. Our analysis derives optimal theoretical guarantees while providing experimental results at par or out-performing state of the art approaches.

Methods for assessing the socioeconomic impacts of large-scale resource developments: implications for nuclear repository siting

International Nuclear Information System (INIS)

Murdock, S.H.; Leistritz, F.L.

1983-03-01

An overview of the major methods presently available for assessing the socioeconomic impacts of large-scale resource developments and includes discussion of the implications and applications of such methods for nuclear-waste-repository siting are provided. The report: (1) summarizes conceptual approaches underlying, and methodological alternatives for, the conduct of impact assessments in each substantive area, and then enumerates advantages and disadvantages of each alternative; (2) describes factors related to the impact-assessment process, impact events, and the characteristics of rural areas that affect the magnitude and distribution of impacts and the assessment of impacts in each area; (3) provides a detailed review of those methodologies actually used in impact assessment for each area, describes advantages and problems encountered in the use of each method, and identifies the frequency of use and the general level of acceptance of each technique; and (4) summarizes the implications of each area of projection for the repository-siting process, the applicability of the methods for each area to the special and standard features of repositories, and makes general recommendations concerning specific methods and procedures that should be incorporated in assessments for siting areas

Large Scale Simulations of the Euler Equations on GPU Clusters

KAUST Repository

Liebmann, Manfred; Douglas, Craig C.; Haase, Gundolf; Horvá th, Zoltá n

2010-01-01

The paper investigates the scalability of a parallel Euler solver, using the Vijayasundaram method, on a GPU cluster with 32 Nvidia Geforce GTX 295 boards. The aim of this research is to enable large scale fluid dynamics simulations with up to one

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)

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.

Large scale simulation of liquid water transport in a gas diffusion layer of polymer electrolyte membrane fuel cells using the lattice Boltzmann method

Science.gov (United States)

Sakaida, Satoshi; Tabe, Yutaka; Chikahisa, Takemi

2017-09-01

A method for the large-scale simulation with the lattice Boltzmann method (LBM) is proposed for liquid water movement in a gas diffusion layer (GDL) of polymer electrolyte membrane fuel cells. The LBM is able to analyze two-phase flows in complex structures, however the simulation domain is limited due to heavy computational loads. This study investigates a variety means to reduce computational loads and increase the simulation areas. One is applying an LBM treating two-phases as having the same density, together with keeping numerical stability with large time steps. The applicability of this approach is confirmed by comparing the results with rigorous simulations using actual density. The second is establishing the maximum limit of the Capillary number that maintains flow patterns similar to the precise simulation; this is attempted as the computational load is inversely proportional to the Capillary number. The results show that the Capillary number can be increased to 3.0 × 10-3, where the actual operation corresponds to Ca = 10-5∼10-8. The limit is also investigated experimentally using an enlarged scale model satisfying similarity conditions for the flow. Finally, a demonstration is made of the effects of pore uniformity in GDL as an example of a large-scale simulation covering a channel.

Incipient multiple fault diagnosis in real time with applications to large-scale systems

International Nuclear Information System (INIS)

Chung, H.Y.; Bien, Z.; Park, J.H.; Seon, P.H.

1994-01-01

By using a modified signed directed graph (SDG) together with the distributed artificial neutral networks and a knowledge-based system, a method of incipient multi-fault diagnosis is presented for large-scale physical systems with complex pipes and instrumentations such as valves, actuators, sensors, and controllers. The proposed method is designed so as to (1) make a real-time incipient fault diagnosis possible for large-scale systems, (2) perform the fault diagnosis not only in the steady-state case but also in the transient case as well by using a concept of fault propagation time, which is newly adopted in the SDG model, (3) provide with highly reliable diagnosis results and explanation capability of faults diagnosed as in an expert system, and (4) diagnose the pipe damage such as leaking, break, or throttling. This method is applied for diagnosis of a pressurizer in the Kori Nuclear Power Plant (NPP) unit 2 in Korea under a transient condition, and its result is reported to show satisfactory performance of the method for the incipient multi-fault diagnosis of such a large-scale system in a real-time manner

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.

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

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.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

Science.gov (United States)

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

Dynamical links between small- and large-scale mantle heterogeneity: Seismological evidence

Science.gov (United States)

Frost, Daniel A.; Garnero, Edward J.; Rost, Sebastian

2018-01-01

We identify PKP • PKP scattered waves (also known as P‧ •P‧) from earthquakes recorded at small-aperture seismic arrays at distances less than 65°. P‧ •P‧ energy travels as a PKP wave through the core, up into the mantle, then scatters back down through the core to the receiver as a second PKP. P‧ •P‧ waves are unique in that they allow scattering heterogeneities throughout the mantle to be imaged. We use array-processing methods to amplify low amplitude, coherent scattered energy signals and resolve their incoming direction. We deterministically map scattering heterogeneity locations from the core-mantle boundary to the surface. We use an extensive dataset with sensitivity to a large volume of the mantle and a location method allowing us to resolve and map more heterogeneities than have previously been possible, representing a significant increase in our understanding of small-scale structure within the mantle. Our results demonstrate that the distribution of scattering heterogeneities varies both radially and laterally. Scattering is most abundant in the uppermost and lowermost mantle, and a minimum in the mid-mantle, resembling the radial distribution of tomographically derived whole-mantle velocity heterogeneity. We investigate the spatial correlation of scattering heterogeneities with large-scale tomographic velocities, lateral velocity gradients, the locations of deep-seated hotspots and subducted slabs. In the lowermost 1500 km of the mantle, small-scale heterogeneities correlate with regions of low seismic velocity, high lateral seismic gradient, and proximity to hotspots. In the upper 1000 km of the mantle there is no significant correlation between scattering heterogeneity location and subducted slabs. Between 600 and 900 km depth, scattering heterogeneities are more common in the regions most remote from slabs, and close to hotspots. Scattering heterogeneities show an affinity for regions close to slabs within the upper 200 km of the

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.

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.

Localization Algorithm Based on a Spring Model (LASM for Large Scale Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Shuai Li

2008-03-01

Full Text Available A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1 for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

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.

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)

Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction

Science.gov (United States)

Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng

2017-01-01

Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.

A Simple but Powerful Heuristic Method for Accelerating k-Means Clustering of Large-Scale Data in Life Science.

Science.gov (United States)

Ichikawa, Kazuki; Morishita, Shinichi

2014-01-01

K-means clustering has been widely used to gain insight into biological systems from large-scale life science data. To quantify the similarities among biological data sets, Pearson correlation distance and standardized Euclidean distance are used most frequently; however, optimization methods have been largely unexplored. These two distance measurements are equivalent in the sense that they yield the same k-means clustering result for identical sets of k initial centroids. Thus, an efficient algorithm used for one is applicable to the other. Several optimization methods are available for the Euclidean distance and can be used for processing the standardized Euclidean distance; however, they are not customized for this context. We instead approached the problem by studying the properties of the Pearson correlation distance, and we invented a simple but powerful heuristic method for markedly pruning unnecessary computation while retaining the final solution. Tests using real biological data sets with 50-60K vectors of dimensions 10-2001 (~400 MB in size) demonstrated marked reduction in computation time for k = 10-500 in comparison with other state-of-the-art pruning methods such as Elkan's and Hamerly's algorithms. The BoostKCP software is available at http://mlab.cb.k.u-tokyo.ac.jp/~ichikawa/boostKCP/.

Large-scale production of lentiviral vector in a closed system hollow fiber bioreactor

Directory of Open Access Journals (Sweden)

Jonathan Sheu

Full Text Available Lentiviral vectors are widely used in the field of gene therapy as an effective method for permanent gene delivery. While current methods of producing small scale vector batches for research purposes depend largely on culture flasks, the emergence and popularity of lentiviral vectors in translational, preclinical and clinical research has demanded their production on a much larger scale, a task that can be difficult to manage with the numbers of producer cell culture flasks required for large volumes of vector. To generate a large scale, partially closed system method for the manufacturing of clinical grade lentiviral vector suitable for the generation of induced pluripotent stem cells (iPSCs, we developed a method employing a hollow fiber bioreactor traditionally used for cell expansion. We have demonstrated the growth, transfection, and vector-producing capability of 293T producer cells in this system. Vector particle RNA titers after subsequent vector concentration yielded values comparable to lentiviral iPSC induction vector batches produced using traditional culture methods in 225 cm2 flasks (T225s and in 10-layer cell factories (CF10s, while yielding a volume nearly 145 times larger than the yield from a T225 flask and nearly three times larger than the yield from a CF10. Employing a closed system hollow fiber bioreactor for vector production offers the possibility of manufacturing large quantities of gene therapy vector while minimizing reagent usage, equipment footprint, and open system manipulation.

Implicit solvers for large-scale nonlinear problems

International Nuclear Information System (INIS)

Keyes, David E; Reynolds, Daniel R; Woodward, Carol S

2006-01-01

Computational scientists are grappling with increasingly complex, multi-rate applications that couple such physical phenomena as fluid dynamics, electromagnetics, radiation transport, chemical and nuclear reactions, and wave and material propagation in inhomogeneous media. Parallel computers with large storage capacities are paving the way for high-resolution simulations of coupled problems; however, hardware improvements alone will not prove enough to enable simulations based on brute-force algorithmic approaches. To accurately capture nonlinear couplings between dynamically relevant phenomena, often while stepping over rapid adjustments to quasi-equilibria, simulation scientists are increasingly turning to implicit formulations that require a discrete nonlinear system to be solved for each time step or steady state solution. Recent advances in iterative methods have made fully implicit formulations a viable option for solution of these large-scale problems. In this paper, we overview one of the most effective iterative methods, Newton-Krylov, for nonlinear systems and point to software packages with its implementation. We illustrate the method with an example from magnetically confined plasma fusion and briefly survey other areas in which implicit methods have bestowed important advantages, such as allowing high-order temporal integration and providing a pathway to sensitivity analyses and optimization. Lastly, we overview algorithm extensions under development motivated by current SciDAC applications

A convex optimization approach for solving large scale linear systems

Directory of Open Access Journals (Sweden)

Debora Cores

2017-01-01

Full Text Available The well-known Conjugate Gradient (CG method minimizes a strictly convex quadratic function for solving large-scale linear system of equations when the coefficient matrix is symmetric and positive definite. In this work we present and analyze a non-quadratic convex function for solving any large-scale linear system of equations regardless of the characteristics of the coefficient matrix. For finding the global minimizers, of this new convex function, any low-cost iterative optimization technique could be applied. In particular, we propose to use the low-cost globally convergent Spectral Projected Gradient (SPG method, which allow us to extend this optimization approach for solving consistent square and rectangular linear system, as well as linear feasibility problem, with and without convex constraints and with and without preconditioning strategies. Our numerical results indicate that the new scheme outperforms state-of-the-art iterative techniques for solving linear systems when the symmetric part of the coefficient matrix is indefinite, and also for solving linear feasibility problems.

Large scale phononic metamaterials for seismic isolation

International Nuclear Information System (INIS)

Aravantinos-Zafiris, N.; Sigalas, M. M.

2015-01-01

In this work, we numerically examine structures that could be characterized as large scale phononic metamaterials. These novel structures could have band gaps in the frequency spectrum of seismic waves when their dimensions are chosen appropriately, thus raising the belief that they could be serious candidates for seismic isolation structures. Different and easy to fabricate structures were examined made from construction materials such as concrete and steel. The well-known finite difference time domain method is used in our calculations in order to calculate the band structures of the proposed metamaterials

Restoring Eelgrass (Zostera marina) from Seed: A Comparison of Planting Methods for Large-Scale Projects

National Research Council Canada - National Science Library

Orth, Robert; Marion, Scott; Granger, Steven; Traber, Michael

2008-01-01

Eelgrass (Zostera marina) seeds are being used in a variety of both small- and large-scale restoration activities and have been successfully used to initiate recovery of eelgrass in the Virginia seaside coastal lagoons...

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.

Modelling across bioreactor scales: methods, challenges and limitations

DEFF Research Database (Denmark)

Gernaey, Krist

that it is challenging and expensive to acquire experimental data of good quality that can be used for characterizing gradients occurring inside a large industrial scale bioreactor. But which model building methods are available? And how can one ensure that the parameters in such a model are properly estimated? And what......Scale-up and scale-down of bioreactors are very important in industrial biotechnology, especially with the currently available knowledge on the occurrence of gradients in industrial-scale bioreactors. Moreover, it becomes increasingly appealing to model such industrial scale systems, considering...

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

Solving Large Scale Nonlinear Eigenvalue Problem in Next-Generation Accelerator Design

Energy Technology Data Exchange (ETDEWEB)

Liao, Ben-Shan; Bai, Zhaojun; /UC, Davis; Lee, Lie-Quan; Ko, Kwok; /SLAC

2006-09-28

A number of numerical methods, including inverse iteration, method of successive linear problem and nonlinear Arnoldi algorithm, are studied in this paper to solve a large scale nonlinear eigenvalue problem arising from finite element analysis of resonant frequencies and external Q{sub e} values of a waveguide loaded cavity in the next-generation accelerator design. They present a nonlinear Rayleigh-Ritz iterative projection algorithm, NRRIT in short and demonstrate that it is the most promising approach for a model scale cavity design. The NRRIT algorithm is an extension of the nonlinear Arnoldi algorithm due to Voss. Computational challenges of solving such a nonlinear eigenvalue problem for a full scale cavity design are outlined.

Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.

Science.gov (United States)

Penas, David R; González, Patricia; Egea, Jose A; Doallo, Ramón; Banga, Julio R

2017-01-21

The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.

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

Large scale and big data processing and management

CERN Document Server

Sakr, Sherif

2014-01-01

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments.The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-bas

Reconstructing Information in Large-Scale Structure via Logarithmic Mapping

Science.gov (United States)

Szapudi, Istvan

We propose to develop a new method to extract information from large-scale structure data combining two-point statistics and non-linear transformations; before, this information was available only with substantially more complex higher-order statistical methods. Initially, most of the cosmological information in large-scale structure lies in two-point statistics. With non- linear evolution, some of that useful information leaks into higher-order statistics. The PI and group has shown in a series of theoretical investigations how that leakage occurs, and explained the Fisher information plateau at smaller scales. This plateau means that even as more modes are added to the measurement of the power spectrum, the total cumulative information (loosely speaking the inverse errorbar) is not increasing. Recently we have shown in Neyrinck et al. (2009, 2010) that a logarithmic (and a related Gaussianization or Box-Cox) transformation on the non-linear Dark Matter or galaxy field reconstructs a surprisingly large fraction of this missing Fisher information of the initial conditions. This was predicted by the earlier wave mechanical formulation of gravitational dynamics by Szapudi & Kaiser (2003). The present proposal is focused on working out the theoretical underpinning of the method to a point that it can be used in practice to analyze data. In particular, one needs to deal with the usual real-life issues of galaxy surveys, such as complex geometry, discrete sam- pling (Poisson or sub-Poisson noise), bias (linear, or non-linear, deterministic, or stochastic), redshift distortions, pro jection effects for 2D samples, and the effects of photometric redshift errors. We will develop methods for weak lensing and Sunyaev-Zeldovich power spectra as well, the latter specifically targetting Planck. In addition, we plan to investigate the question of residual higher- order information after the non-linear mapping, and possible applications for cosmology. Our aim will be to work out

Large scale mapping: an empirical comparison of pixel-based and ...

African Journals Online (AJOL)

In the past, large scale mapping was carried using precise ground survey methods. Later, paradigm shift in data collection using medium to low resolution and, recently, high resolution images brought to bear the problem of accurate data analysis and fitness-for-purpose challenges. Using high resolution satellite images ...

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

An optimal beam alignment method for large-scale distributed space surveillance radar system

Science.gov (United States)

Huang, Jian; Wang, Dongya; Xia, Shuangzhi

2018-06-01

Large-scale distributed space surveillance radar is a very important ground-based equipment to maintain a complete catalogue for Low Earth Orbit (LEO) space debris. However, due to the thousands of kilometers distance between each sites of the distributed radar system, how to optimally implement the Transmitting/Receiving (T/R) beams alignment in a great space using the narrow beam, which proposed a special and considerable technical challenge in the space surveillance area. According to the common coordinate transformation model and the radar beam space model, we presented a two dimensional projection algorithm for T/R beam using the direction angles, which could visually describe and assess the beam alignment performance. Subsequently, the optimal mathematical models for the orientation angle of the antenna array, the site location and the T/R beam coverage are constructed, and also the beam alignment parameters are precisely solved. At last, we conducted the optimal beam alignment experiments base on the site parameters of Air Force Space Surveillance System (AFSSS). The simulation results demonstrate the correctness and effectiveness of our novel method, which can significantly stimulate the construction for the LEO space debris surveillance equipment.

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...

Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

DEFF Research Database (Denmark)

Darkner, Sune; Dahl, Anders Lindbjerg; Larsen, Rasmus

2010-01-01

a microscope and we show how the method can handle transparent particles with significant glare point. The method generalizes to other problems. THis is illustrated by applying the method to camera calibration images and MRI of the midsagittal plane for gray and white matter separation and segmentation......We propose a novel and efficient way of performing local image segmentation. For many applications a threshold of pixel intensities is sufficient but determine the appropriate threshold value can be difficult. In cases with large global intensity variation the threshold value has to be adapted...... locally. We propose a method based on large scale hypothesis testing with a consistent method for selecting an appropriate threshold for the given data. By estimating the background distribution we characterize the segment of interest as a set of outliers with a certain probability based on the estimated...

Systematic methods for defining coarse-grained maps in large biomolecules.

Science.gov (United States)

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

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.

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

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.)

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

Large-scale photochemical reactions of nanocrystalline suspensions: a promising green chemistry method.

Science.gov (United States)

Veerman, Marcel; Resendiz, Marino J E; Garcia-Garibay, Miguel A

2006-06-08

Photochemical reactions in the solid state can be scaled up from a few milligrams to 10 grams by using colloidal suspensions of a photoactive molecular crystal prepared by the solvent shift method. Pure products are recovered by filtration, and the use of H(2)O as a suspension medium makes this method a very attractive one from a green chemistry perspective. Using the photodecarbonylation of dicumyl ketone (DCK) as a test system, we show that reaction efficiencies in colloidal suspensions rival those observed in solution. [reaction: see text

Large scale analysis of signal reachability.

Science.gov (United States)

Todor, Andrei; Gabr, Haitham; Dobra, Alin; Kahveci, Tamer

2014-06-15

Major disorders, such as leukemia, have been shown to alter the transcription of genes. Understanding how gene regulation is affected by such aberrations is of utmost importance. One promising strategy toward this objective is to compute whether signals can reach to the transcription factors through the transcription regulatory network (TRN). Due to the uncertainty of the regulatory interactions, this is a #P-complete problem and thus solving it for very large TRNs remains to be a challenge. We develop a novel and scalable method to compute the probability that a signal originating at any given set of source genes can arrive at any given set of target genes (i.e., transcription factors) when the topology of the underlying signaling network is uncertain. Our method tackles this problem for large networks while providing a provably accurate result. Our method follows a divide-and-conquer strategy. We break down the given network into a sequence of non-overlapping subnetworks such that reachability can be computed autonomously and sequentially on each subnetwork. We represent each interaction using a small polynomial. The product of these polynomials express different scenarios when a signal can or cannot reach to target genes from the source genes. We introduce polynomial collapsing operators for each subnetwork. These operators reduce the size of the resulting polynomial and thus the computational complexity dramatically. We show that our method scales to entire human regulatory networks in only seconds, while the existing methods fail beyond a few tens of genes and interactions. We demonstrate that our method can successfully characterize key reachability characteristics of the entire transcriptions regulatory networks of patients affected by eight different subtypes of leukemia, as well as those from healthy control samples. All the datasets and code used in this article are available at bioinformatics.cise.ufl.edu/PReach/scalable.htm. © The Author 2014

Potential climatic impacts and reliability of large-scale offshore wind farms

International Nuclear Information System (INIS)

Wang Chien; Prinn, Ronald G

2011-01-01

-based installations. However, the intermittency caused by the significant seasonal wind variations over several major offshore sites is substantial, and demands further options to ensure the reliability of large-scale offshore wind power. The method that we used to simulate the offshore wind turbine effect on the lower atmosphere involved simply increasing the ocean surface drag coefficient. While this method is consistent with several detailed fine-scale simulations of wind turbines, it still needs further study to ensure its validity. New field observations of actual wind turbine arrays are definitely required to provide ultimate validation of the model predictions presented here.

Prospects for large scale electricity storage in Denmark

DEFF Research Database (Denmark)

Krog Ekman, Claus; Jensen, Søren Højgaard

2010-01-01

In a future power systems with additional wind power capacity there will be an increased need for large scale power management as well as reliable balancing and reserve capabilities. Different technologies for large scale electricity storage provide solutions to the different challenges arising w...

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.

Large-Scale Structure and Hyperuniformity of Amorphous Ices

Science.gov (United States)

Martelli, Fausto; Torquato, Salvatore; Giovambattista, Nicolas; Car, Roberto

2017-09-01

We investigate the large-scale structure of amorphous ices and transitions between their different forms by quantifying their large-scale density fluctuations. Specifically, we simulate the isothermal compression of low-density amorphous ice (LDA) and hexagonal ice to produce high-density amorphous ice (HDA). Both HDA and LDA are nearly hyperuniform; i.e., they are characterized by an anomalous suppression of large-scale density fluctuations. By contrast, in correspondence with the nonequilibrium phase transitions to HDA, the presence of structural heterogeneities strongly suppresses the hyperuniformity and the system becomes hyposurficial (devoid of "surface-area fluctuations"). Our investigation challenges the largely accepted "frozen-liquid" picture, which views glasses as structurally arrested liquids. Beyond implications for water, our findings enrich our understanding of pressure-induced structural transformations in glasses.

Large-scale biophysical evaluation of protein PEGylation effects

DEFF Research Database (Denmark)

Vernet, Erik; Popa, Gina; Pozdnyakova, Irina

2016-01-01

PEGylation is the most widely used method to chemically modify protein biopharmaceuticals, but surprisingly limited public data is available on the biophysical effects of protein PEGylation. Here we report the first large-scale study, with site-specific mono-PEGylation of 15 different proteins...... of PEGylation on the thermal stability of a protein based on data generated by circular dichroism (CD), differential scanning calorimetry (DSC), or differential scanning fluorimetry (DSF). In addition, DSF was validated as a fast and inexpensive screening method for thermal unfolding studies of PEGylated...... proteins. Multivariate data analysis revealed clear trends in biophysical properties upon PEGylation for a subset of proteins, although no universal trends were found. Taken together, these findings are important in the consideration of biophysical methods and evaluation of second...

Parallel Quasi Newton Algorithms for Large Scale Non Linear Unconstrained Optimization

International Nuclear Information System (INIS)

Rahman, M. A.; Basarudin, T.

1997-01-01

This paper discusses about Quasi Newton (QN) method to solve non-linear unconstrained minimization problems. One of many important of QN method is choice of matrix Hk. to be positive definite and satisfies to QN method. Our interest here is the parallel QN methods which will suite for the solution of large-scale optimization problems. The QN methods became less attractive in large-scale problems because of the storage and computational requirements. How ever, it is often the case that the Hessian is space matrix. In this paper we include the mechanism of how to reduce the Hessian update and hold the Hessian properties.One major reason of our research is that the QN method may be good in solving certain type of minimization problems, but it is efficiency degenerate when is it applied to solve other category of problems. For this reason, we use an algorithm containing several direction strategies which are processed in parallel. We shall attempt to parallelized algorithm by exploring different search directions which are generated by various QN update during the minimization process. The different line search strategies will be employed simultaneously in the process of locating the minimum along each direction.The code of algorithm will be written in Occam language 2 which is run on the transputer machine

VLSI scaling methods and low power CMOS buffer circuit

International Nuclear Information System (INIS)

Sharma Vijay Kumar; Pattanaik Manisha

2013-01-01

Device scaling is an important part of the very large scale integration (VLSI) design to boost up the success path of VLSI industry, which results in denser and faster integration of the devices. As technology node moves towards the very deep submicron region, leakage current and circuit reliability become the key issues. Both are increasing with the new technology generation and affecting the performance of the overall logic circuit. The VLSI designers must keep the balance in power dissipation and the circuit's performance with scaling of the devices. In this paper, different scaling methods are studied first. These scaling methods are used to identify the effects of those scaling methods on the power dissipation and propagation delay of the CMOS buffer circuit. For mitigating the power dissipation in scaled devices, we have proposed a reliable leakage reduction low power transmission gate (LPTG) approach and tested it on complementary metal oxide semiconductor (CMOS) buffer circuit. All simulation results are taken on HSPICE tool with Berkeley predictive technology model (BPTM) BSIM4 bulk CMOS files. The LPTG CMOS buffer reduces 95.16% power dissipation with 84.20% improvement in figure of merit at 32 nm technology node. Various process, voltage and temperature variations are analyzed for proving the robustness of the proposed approach. Leakage current uncertainty decreases from 0.91 to 0.43 in the CMOS buffer circuit that causes large circuit reliability. (semiconductor integrated circuits)

Predictability of the recent slowdown and subsequent recovery of large-scale surface warming using statistical methods

Science.gov (United States)

Mann, Michael E.; Steinman, Byron A.; Miller, Sonya K.; Frankcombe, Leela M.; England, Matthew H.; Cheung, Anson H.

2016-04-01

The temporary slowdown in large-scale surface warming during the early 2000s has been attributed to both external and internal sources of climate variability. Using semiempirical estimates of the internal low-frequency variability component in Northern Hemisphere, Atlantic, and Pacific surface temperatures in concert with statistical hindcast experiments, we investigate whether the slowdown and its recent recovery were predictable. We conclude that the internal variability of the North Pacific, which played a critical role in the slowdown, does not appear to have been predictable using statistical forecast methods. An additional minor contribution from the North Atlantic, by contrast, appears to exhibit some predictability. While our analyses focus on combining semiempirical estimates of internal climatic variability with statistical hindcast experiments, possible implications for initialized model predictions are also discussed.

Comparison of zero-sequence injection methods in cascaded H-bridge multilevel converters for large-scale photovoltaic integration

DEFF Research Database (Denmark)

Yu, Yifan; Konstantinou, Georgios; Townsend, Christopher David

2017-01-01

to maintain three-phase balanced grid currents with unbalanced power generation. This study theoretically compares power balance capabilities of various zero-sequence injection methods based on two metrics which can be easily generalised for all CHB applications to PV systems. Experimental results based......Photovoltaic (PV) power generation levels in the three phases of a multilevel cascaded H-bridge (CHB) converter can be significantly unbalanced, owing to different irradiance levels and ambient temperatures over a large-scale solar PV power plant. Injection of a zero-sequence voltage is required...... on a 430 V, 10 kW, three-phase, seven-level cascaded H-bridge converter prototype confirm superior performance of the optimal zero-sequence injection technique....

A Normalization-Free and Nonparametric Method Sharpens Large-Scale Transcriptome Analysis and Reveals Common Gene Alteration Patterns in Cancers.

Science.gov (United States)

Li, Qi-Gang; He, Yong-Han; Wu, Huan; Yang, Cui-Ping; Pu, Shao-Yan; Fan, Song-Qing; Jiang, Li-Ping; Shen, Qiu-Shuo; Wang, Xiao-Xiong; Chen, Xiao-Qiong; Yu, Qin; Li, Ying; Sun, Chang; Wang, Xiangting; Zhou, Jumin; Li, Hai-Peng; Chen, Yong-Bin; Kong, Qing-Peng

2017-01-01

Heterogeneity in transcriptional data hampers the identification of differentially expressed genes (DEGs) and understanding of cancer, essentially because current methods rely on cross-sample normalization and/or distribution assumption-both sensitive to heterogeneous values. Here, we developed a new method, Cross-Value Association Analysis (CVAA), which overcomes the limitation and is more robust to heterogeneous data than the other methods. Applying CVAA to a more complex pan-cancer dataset containing 5,540 transcriptomes discovered numerous new DEGs and many previously rarely explored pathways/processes; some of them were validated, both in vitro and in vivo , to be crucial in tumorigenesis, e.g., alcohol metabolism ( ADH1B ), chromosome remodeling ( NCAPH ) and complement system ( Adipsin ). Together, we present a sharper tool to navigate large-scale expression data and gain new mechanistic insights into tumorigenesis.

Efficient Topology Estimation for Large Scale Optical Mapping

CERN Document Server

Elibol, Armagan; Garcia, Rafael

2013-01-01

Large scale optical mapping methods are in great demand among scientists who study different aspects of the seabed, and have been fostered by impressive advances in the capabilities of underwater robots in gathering optical data from the seafloor. Cost and weight constraints mean that low-cost ROVs usually have a very limited number of sensors. When a low-cost robot carries out a seafloor survey using a down-looking camera, it usually follows a predefined trajectory that provides several non time-consecutive overlapping image pairs. Finding these pairs (a process known as topology estimation) is indispensable to obtaining globally consistent mosaics and accurate trajectory estimates, which are necessary for a global view of the surveyed area, especially when optical sensors are the only data source. This book contributes to the state-of-art in large area image mosaicing methods for underwater surveys using low-cost vehicles equipped with a very limited sensor suite. The main focus has been on global alignment...

Dynamic subgrid scale model used in a deep bundle turbulence prediction using the large eddy simulation method

International Nuclear Information System (INIS)

Barsamian, H.R.; Hassan, Y.A.

1996-01-01

Turbulence is one of the most commonly occurring phenomena of engineering interest in the field of fluid mechanics. Since most flows are turbulent, there is a significant payoff for improved predictive models of turbulence. One area of concern is the turbulent buffeting forces experienced by the tubes in steam generators of nuclear power plants. Although the Navier-Stokes equations are able to describe turbulent flow fields, the large number of scales of turbulence limit practical flow field calculations with current computing power. The dynamic subgrid scale closure model of Germano et. al (1991) is used in the large eddy simulation code GUST for incompressible isothermal flows. Tube bundle geometries of staggered and non-staggered arrays are considered in deep bundle simulations. The advantage of the dynamic subgrid scale model is the exclusion of an input model coefficient. The model coefficient is evaluated dynamically for each nodal location in the flow domain. Dynamic subgrid scale results are obtained in the form of power spectral densities and flow visualization of turbulent characteristics. Comparisons are performed among the dynamic subgrid scale model, the Smagorinsky eddy viscosity model (Smagorinsky, 1963) (that is used as the base model for the dynamic subgrid scale model) and available experimental data. Spectral results of the dynamic subgrid scale model correlate better with experimental data. Satisfactory turbulence characteristics are observed through flow visualization

Solving Large-Scale TSP Using a Fast Wedging Insertion Partitioning Approach

Directory of Open Access Journals (Sweden)

Zuoyong Xiang

2015-01-01

Full Text Available A new partitioning method, called Wedging Insertion, is proposed for solving large-scale symmetric Traveling Salesman Problem (TSP. The idea of our proposed algorithm is to cut a TSP tour into four segments by nodes’ coordinate (not by rectangle, such as Strip, FRP, and Karp. Each node is located in one of their segments, which excludes four particular nodes, and each segment does not twist with other segments. After the partitioning process, this algorithm utilizes traditional construction method, that is, the insertion method, for each segment to improve the quality of tour, and then connects the starting node and the ending node of each segment to obtain the complete tour. In order to test the performance of our proposed algorithm, we conduct the experiments on various TSPLIB instances. The experimental results show that our proposed algorithm in this paper is more efficient for solving large-scale TSPs. Specifically, our approach is able to obviously reduce the time complexity for running the algorithm; meanwhile, it will lose only about 10% of the algorithm’s performance.

LARGE SCALE METHOD FOR THE PRODUCTION AND PURIFICATION OF CURIUM

Science.gov (United States)

Higgins, G.H.; Crane, W.W.T.

1959-05-19

A large-scale process for production and purification of Cm/sup 242/ is described. Aluminum slugs containing Am are irradiated and declad in a NaOH-- NaHO/sub 3/ solution at 85 to 100 deg C. The resulting slurry filtered and washed with NaOH, NH/sub 4/OH, and H/sub 2/O. Recovery of Cm from filtrate and washings is effected by an Fe(OH)/sub 3/ precipitation. The precipitates are then combined and dissolved ln HCl and refractory oxides centrifuged out. These oxides are then fused with Na/sub 2/CO/sub 3/ and dissolved in HCl. The solution is evaporated and LiCl solution added. The Cm, rare earths, and anionic impurities are adsorbed on a strong-base anfon exchange resin. Impurities are eluted with LiCl--HCl solution, rare earths and Cm are eluted by HCl. Other ion exchange steps further purify the Cm. The Cm is then precipitated as fluoride and used in this form or further purified and processed. (T.R.H.)

The large-scale blast score ratio (LS-BSR pipeline: a method to rapidly compare genetic content between bacterial genomes

Directory of Open Access Journals (Sweden)

Jason W. Sahl

2014-04-01

Full Text Available Background. As whole genome sequence data from bacterial isolates becomes cheaper to generate, computational methods are needed to correlate sequence data with biological observations. Here we present the large-scale BLAST score ratio (LS-BSR pipeline, which rapidly compares the genetic content of hundreds to thousands of bacterial genomes, and returns a matrix that describes the relatedness of all coding sequences (CDSs in all genomes surveyed. This matrix can be easily parsed in order to identify genetic relationships between bacterial genomes. Although pipelines have been published that group peptides by sequence similarity, no other software performs the rapid, large-scale, full-genome comparative analyses carried out by LS-BSR.Results. To demonstrate the utility of the method, the LS-BSR pipeline was tested on 96 Escherichia coli and Shigella genomes; the pipeline ran in 163 min using 16 processors, which is a greater than 7-fold speedup compared to using a single processor. The BSR values for each CDS, which indicate a relative level of relatedness, were then mapped to each genome on an independent core genome single nucleotide polymorphism (SNP based phylogeny. Comparisons were then used to identify clade specific CDS markers and validate the LS-BSR pipeline based on molecular markers that delineate between classical E. coli pathogenic variant (pathovar designations. Scalability tests demonstrated that the LS-BSR pipeline can process 1,000 E. coli genomes in 27–57 h, depending upon the alignment method, using 16 processors.Conclusions. LS-BSR is an open-source, parallel implementation of the BSR algorithm, enabling rapid comparison of the genetic content of large numbers of genomes. The results of the pipeline can be used to identify specific markers between user-defined phylogenetic groups, and to identify the loss and/or acquisition of genetic information between bacterial isolates. Taxa-specific genetic markers can then be translated

Large scale nuclear structure studies

International Nuclear Information System (INIS)

Faessler, A.

1985-01-01

Results of large scale nuclear structure studies are reported. The starting point is the Hartree-Fock-Bogoliubov solution with angular momentum and proton and neutron number projection after variation. This model for number and spin projected two-quasiparticle excitations with realistic forces yields in sd-shell nuclei similar good results as the 'exact' shell-model calculations. Here the authors present results for a pf-shell nucleus 46 Ti and results for the A=130 mass region where they studied 58 different nuclei with the same single-particle energies and the same effective force derived from a meson exchange potential. They carried out a Hartree-Fock-Bogoliubov variation after mean field projection in realistic model spaces. In this way, they determine for each yrast state the optimal mean Hartree-Fock-Bogoliubov field. They apply this method to 130 Ce and 128 Ba using the same effective nucleon-nucleon interaction. (Auth.)

Sample preparation for large-scale bioanalytical studies based on liquid chromatographic techniques.

Science.gov (United States)

Medvedovici, Andrei; Bacalum, Elena; David, Victor

2018-01-01

Quality of the analytical data obtained for large-scale and long term bioanalytical studies based on liquid chromatography depends on a number of experimental factors including the choice of sample preparation method. This review discusses this tedious part of bioanalytical studies, applied to large-scale samples and using liquid chromatography coupled with different detector types as core analytical technique. The main sample preparation methods included in this paper are protein precipitation, liquid-liquid extraction, solid-phase extraction, derivatization and their versions. They are discussed by analytical performances, fields of applications, advantages and disadvantages. The cited literature covers mainly the analytical achievements during the last decade, although several previous papers became more valuable in time and they are included in this review. Copyright © 2017 John Wiley & Sons, Ltd.

PathlinesExplorer — Image-based exploration of large-scale pathline fields

KAUST Repository

Nagoor, Omniah H.; Hadwiger, Markus; Srinivasan, Madhusudhanan

2015-01-01

-accessing the original huge data. Our approach is based on constructing a per-pixel linked list data structure in which each pixel contains a list of pathline segments. With this view-dependent method, it is possible to filter, color-code, and explore large-scale flow

Google Street View as an alternative method to car surveys in large-scale vegetation assessments.

Science.gov (United States)

Deus, Ernesto; Silva, Joaquim S; Catry, Filipe X; Rocha, Miguel; Moreira, Francisco

2015-10-01

Car surveys (CS) are a common method for assessing the distribution of alien invasive plants. Google Street View (GSV), a free-access web technology where users may experience a virtual travel along roads, has been suggested as a cost-effective alternative to car surveys. We tested if we could replicate the results from a countrywide survey conducted by car in Portugal using GSV as a remote sensing tool, aiming at assessing the distribution of Eucalyptus globulus Labill. wildlings on roadsides adjacent to eucalypt stands. Georeferenced points gathered along CS were used to create road transects visible as lines overlapping the road in GSV environment, allowing surveying the same sampling areas using both methods. This paper presents the results of the comparison between the two methods. Both methods produced similar models of plant abundance, selecting the same explanatory variables, in the same hierarchical order of importance and depicting a similar influence on plant abundance. Even though the GSV model had a lower performance and the GSV survey detected fewer plants, additional variables collected exclusively with GSV improved model performance and provided a new insight into additional factors influencing plant abundance. The survey using GSV required ca. 9 % of the funds and 62 % of the time needed to accomplish the CS. We conclude that GSV may be a cost-effective alternative to CS. We discuss some advantages and limitations of GSV as a survey method. We forecast that GSV may become a widespread tool in road ecology, particularly in large-scale vegetation assessments.

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

International Nuclear Information System (INIS)

Turner, M.S.; Villumsen, J.V.; Vittorio, N.; Silk, J.; Juszkiewicz, R.

1986-11-01

A model is presented for the large-scale structure of the universe in which two successive inflationary phases resulted in large small-scale and small large-scale density fluctuations. This bimodal density fluctuation spectrum in an Ω = 1 universe dominated by hot dark matter leads to large-scale structure of the galaxy distribution that is consistent with recent observational results. In particular, large, nearly empty voids and significant large-scale peculiar velocity fields are produced over scales of ∼100 Mpc, while the small-scale structure over ≤ 10 Mpc resembles that in a low density universe, as observed. Detailed analytical calculations and numerical simulations are given of the spatial and velocity correlations. 38 refs., 6 figs

Large-scale innovation and change in UK higher education

Directory of Open Access Journals (Sweden)

Stephen Brown

2013-09-01

Full Text Available This paper reflects on challenges universities face as they respond to change. It reviews current theories and models of change management, discusses why universities are particularly difficult environments in which to achieve large scale, lasting change and reports on a recent attempt by the UK JISC to enable a range of UK universities to employ technology to deliver such changes. Key lessons that emerged from these experiences are reviewed covering themes of pervasiveness, unofficial systems, project creep, opposition, pressure to deliver, personnel changes and technology issues. The paper argues that collaborative approaches to project management offer greater prospects of effective large-scale change in universities than either management-driven top-down or more champion-led bottom-up methods. It also argues that while some diminution of control over project outcomes is inherent in this approach, this is outweighed by potential benefits of lasting and widespread adoption of agreed changes.

Large-scale fracture mechancis testing -- requirements and possibilities

International Nuclear Information System (INIS)

Brumovsky, M.

1993-01-01

Application of fracture mechanics to very important and/or complicated structures, like reactor pressure vessels, brings also some questions about the reliability and precision of such calculations. These problems become more pronounced in cases of elastic-plastic conditions of loading and/or in parts with non-homogeneous materials (base metal and austenitic cladding, property gradient changes through material thickness) or with non-homogeneous stress fields (nozzles, bolt threads, residual stresses etc.). For such special cases some verification by large-scale testing is necessary and valuable. This paper discusses problems connected with planning of such experiments with respect to their limitations, requirements to a good transfer of received results to an actual vessel. At the same time, an analysis of possibilities of small-scale model experiments is also shown, mostly in connection with application of results between standard, small-scale and large-scale experiments. Experience from 30 years of large-scale testing in SKODA is used as an example to support this analysis. 1 fig

Ethics of large-scale change

DEFF Research Database (Denmark)

Arler, Finn

2006-01-01

, 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, the neoclassical economists' approach, and finally the so-called Concentric Circle Theories approach...

Multidimensional scaling for large genomic data sets

Directory of Open Access Journals (Sweden)

Lu Henry

2008-04-01

Full Text Available Abstract Background Multi-dimensional scaling (MDS is aimed to represent high dimensional data in a low dimensional space with preservation of the similarities between data points. This reduction in dimensionality is crucial for analyzing and revealing the genuine structure hidden in the data. For noisy data, dimension reduction can effectively reduce the effect of noise on the embedded structure. For large data set, dimension reduction can effectively reduce information retrieval complexity. Thus, MDS techniques are used in many applications of data mining and gene network research. However, although there have been a number of studies that applied MDS techniques to genomics research, the number of analyzed data points was restricted by the high computational complexity of MDS. In general, a non-metric MDS method is faster than a metric MDS, but it does not preserve the true relationships. The computational complexity of most metric MDS methods is over O(N2, so that it is difficult to process a data set of a large number of genes N, such as in the case of whole genome microarray data. Results We developed a new rapid metric MDS method with a low computational complexity, making metric MDS applicable for large data sets. Computer simulation showed that the new method of split-and-combine MDS (SC-MDS is fast, accurate and efficient. Our empirical studies using microarray data on the yeast cell cycle showed that the performance of K-means in the reduced dimensional space is similar to or slightly better than that of K-means in the original space, but about three times faster to obtain the clustering results. Our clustering results using SC-MDS are more stable than those in the original space. Hence, the proposed SC-MDS is useful for analyzing whole genome data. Conclusion Our new method reduces the computational complexity from O(N3 to O(N when the dimension of the feature space is far less than the number of genes N, and it successfully

Investigation on the integral output power model of a large-scale wind farm

Institute of Scientific and Technical Information of China (English)

BAO Nengsheng; MA Xiuqian; NI Weidou

2007-01-01

The integral output power model of a large-scale wind farm is needed when estimating the wind farm's output over a period of time in the future.The actual wind speed power model and calculation method of a wind farm made up of many wind turbine units are discussed.After analyzing the incoming wind flow characteristics and their energy distributions,and after considering the multi-effects among the wind turbine units and certain assumptions,the incoming wind flow model of multi-units is built.The calculation algorithms and steps of the integral output power model of a large-scale wind farm are provided.Finally,an actual power output of the wind farm is calculated and analyzed by using the practical measurement wind speed data.The characteristics of a large-scale wind farm are also discussed.

On distributed wavefront reconstruction for large-scale adaptive optics systems.

Science.gov (United States)

de Visser, Cornelis C; Brunner, Elisabeth; Verhaegen, Michel

2016-05-01

The distributed-spline-based aberration reconstruction (D-SABRE) method is proposed for distributed wavefront reconstruction with applications to large-scale adaptive optics systems. D-SABRE decomposes the wavefront sensor domain into any number of partitions and solves a local wavefront reconstruction problem on each partition using multivariate splines. D-SABRE accuracy is within 1% of a global approach with a speedup that scales quadratically with the number of partitions. The D-SABRE is compared to the distributed cumulative reconstruction (CuRe-D) method in open-loop and closed-loop simulations using the YAO adaptive optics simulation tool. D-SABRE accuracy exceeds CuRe-D for low levels of decomposition, and D-SABRE proved to be more robust to variations in the loop gain.

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.

Comparison Between Overtopping Discharge in Small and Large Scale Models

DEFF Research Database (Denmark)

Helgason, Einar; Burcharth, Hans F.

2006-01-01

The present paper presents overtopping measurements from small scale model test performed at the Haudraulic & Coastal Engineering Laboratory, Aalborg University, Denmark and large scale model tests performed at the Largde Wave Channel,Hannover, Germany. Comparison between results obtained from...... small and large scale model tests show no clear evidence of scale effects for overtopping above a threshold value. In the large scale model no overtopping was measured for waveheights below Hs = 0.5m as the water sunk into the voids between the stones on the crest. For low overtopping scale effects...

Research on large-scale wind farm modeling

Science.gov (United States)

Ma, Longfei; Zhang, Baoqun; Gong, Cheng; Jiao, Ran; Shi, Rui; Chi, Zhongjun; Ding, Yifeng

2017-01-01

Due to intermittent and adulatory properties of wind energy, when large-scale wind farm connected to the grid, it will have much impact on the power system, which is different from traditional power plants. Therefore it is necessary to establish an effective wind farm model to simulate and analyze the influence wind farms have on the grid as well as the transient characteristics of the wind turbines when the grid is at fault. However we must first establish an effective WTGs model. As the doubly-fed VSCF wind turbine has become the mainstream wind turbine model currently, this article first investigates the research progress of doubly-fed VSCF wind turbine, and then describes the detailed building process of the model. After that investigating the common wind farm modeling methods and pointing out the problems encountered. As WAMS is widely used in the power system, which makes online parameter identification of the wind farm model based on off-output characteristics of wind farm be possible, with a focus on interpretation of the new idea of identification-based modeling of large wind farms, which can be realized by two concrete methods.

Improved decomposition–coordination and discrete differential dynamic programming for optimization of large-scale hydropower system

International Nuclear Information System (INIS)

Li, Chunlong; Zhou, Jianzhong; Ouyang, Shuo; Ding, Xiaoling; Chen, Lu

2014-01-01

Highlights: • Optimization of large-scale hydropower system in the Yangtze River basin. • Improved decomposition–coordination and discrete differential dynamic programming. • Generating initial solution randomly to reduce generation time. • Proposing relative coefficient for more power generation. • Proposing adaptive bias corridor technology to enhance convergence speed. - Abstract: With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition–coordination and discrete differential dynamic programming (IDC–DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC–DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem

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

Science.gov (United States)

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

2018-01-01

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

Studies of Sub-Synchronous Oscillations in Large-Scale Wind Farm Integrated System

Science.gov (United States)

Yue, Liu; Hang, Mend

2018-01-01

With the rapid development and construction of large-scale wind farms and grid-connected operation, the series compensation wind power AC transmission is gradually becoming the main way of power usage and improvement of wind power availability and grid stability, but the integration of wind farm will change the SSO (Sub-Synchronous oscillation) damping characteristics of synchronous generator system. Regarding the above SSO problem caused by integration of large-scale wind farms, this paper focusing on doubly fed induction generator (DFIG) based wind farms, aim to summarize the SSO mechanism in large-scale wind power integrated system with series compensation, which can be classified as three types: sub-synchronous control interaction (SSCI), sub-synchronous torsional interaction (SSTI), sub-synchronous resonance (SSR). Then, SSO modelling and analysis methods are categorized and compared by its applicable areas. Furthermore, this paper summarizes the suppression measures of actual SSO projects based on different control objectives. Finally, the research prospect on this field is explored.

Semi-Automated Air-Coupled Impact-Echo Method for Large-Scale Parkade Structure

Directory of Open Access Journals (Sweden)

Tyler Epp

2018-03-01

Full Text Available Structural Health Monitoring (SHM has moved to data-dense systems, utilizing numerous sensor types to monitor infrastructure, such as bridges and dams, more regularly. One of the issues faced in this endeavour is the scale of the inspected structures and the time it takes to carry out testing. Installing automated systems that can provide measurements in a timely manner is one way of overcoming these obstacles. This study proposes an Artificial Neural Network (ANN application that determines intact and damaged locations from a small training sample of impact-echo data, using air-coupled microphones from a reinforced concrete beam in lab conditions and data collected from a field experiment in a parking garage. The impact-echo testing in the field is carried out in a semi-autonomous manner to expedite the front end of the in situ damage detection testing. The use of an ANN removes the need for a user-defined cutoff value for the classification of intact and damaged locations when a least-square distance approach is used. It is postulated that this may contribute significantly to testing time reduction when monitoring large-scale civil Reinforced Concrete (RC structures.

Needs, opportunities, and options for large scale systems research

Energy Technology Data Exchange (ETDEWEB)

Thompson, G.L.

1984-10-01

The Office of Energy Research was recently asked to perform a study of Large Scale Systems in order to facilitate the development of a true large systems theory. It was decided to ask experts in the fields of electrical engineering, chemical engineering and manufacturing/operations research for their ideas concerning large scale systems research. The author was asked to distribute a questionnaire among these experts to find out their opinions concerning recent accomplishments and future research directions in large scale systems research. He was also requested to convene a conference which included three experts in each area as panel members to discuss the general area of large scale systems research. The conference was held on March 26--27, 1984 in Pittsburgh with nine panel members, and 15 other attendees. The present report is a summary of the ideas presented and the recommendations proposed by the attendees.

Development of a transverse mixing model for large scale impulsion phenomenon in tight lattice

International Nuclear Information System (INIS)

Liu, Xiaojing; Ren, Shuo; Cheng, Xu

2017-01-01

Highlights: • Experiment data of Krauss is used to validate the feasibility of CFD simulation method. • CFD simulation is performed to simulate the large scale impulsion phenomenon for tight-lattice bundle. • A mixing model to simulate the large scale impulsion phenomenon is proposed based on CFD result fitting. • The new developed mixing model has been added in the subchannel code. - Abstract: Tight-lattice is widely adopted in the innovative reactor fuel bundles design since it can increase the conversion ratio and improve the heat transfer between fuel bundles and coolant. It has been noticed that a large scale impulsion of cross-velocity exists in the gap region, which plays an important role on the transverse mixing flow and heat transfer. Although many experiments and numerical simulation have been carried out to study the impulsion of velocity, a model to describe the wave length, amplitude and frequency of mixing coefficient is still missing. This research work takes advantage of the CFD method to simulate the experiment of Krauss and to compare experiment data and simulation result in order to demonstrate the feasibility of simulation method and turbulence model. Then, based on this verified method and model, several simulations are performed with different Reynolds number and different Pitch-to-Diameter ratio. By fitting the CFD results achieved, a mixing model to simulate the large scale impulsion phenomenon is proposed and adopted in the current subchannel code. The new mixing model is applied to some fuel assembly analysis by subchannel calculation, it can be noticed that the new developed mixing model can reduce the hot channel factor and contribute to a uniform distribution of outlet temperature.

A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.

Directory of Open Access Journals (Sweden)

Xiangyun Xiao

Full Text Available The reconstruction of gene regulatory networks (GRNs from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM, experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.

A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.

Science.gov (United States)

Xiao, Xiangyun; Zhang, Wei; Zou, Xiufen

2015-01-01

The reconstruction of gene regulatory networks (GRNs) from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE)-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM), experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.

A Classification Framework for Large-Scale Face Recognition Systems

OpenAIRE

Zhou, Ziheng; Deravi, Farzin

2009-01-01

This paper presents a generic classification framework for large-scale face recognition systems. Within the framework, a data sampling strategy is proposed to tackle the data imbalance when image pairs are sampled from thousands of face images for preparing a training dataset. A modified kernel Fisher discriminant classifier is proposed to make it computationally feasible to train the kernel-based classification method using tens of thousands of training samples. The framework is tested in an...

A 3D Sphere Culture System Containing Functional Polymers for Large-Scale Human Pluripotent Stem Cell Production

Directory of Open Access Journals (Sweden)

Tomomi G. Otsuji

2014-05-01

Full Text Available Utilizing human pluripotent stem cells (hPSCs in cell-based therapy and drug discovery requires large-scale cell production. However, scaling up conventional adherent cultures presents challenges of maintaining a uniform high quality at low cost. In this regard, suspension cultures are a viable alternative, because they are scalable and do not require adhesion surfaces. 3D culture systems such as bioreactors can be exploited for large-scale production. However, the limitations of current suspension culture methods include spontaneous fusion between cell aggregates and suboptimal passaging methods by dissociation and reaggregation. 3D culture systems that dynamically stir carrier beads or cell aggregates should be refined to reduce shearing forces that damage hPSCs. Here, we report a simple 3D sphere culture system that incorporates mechanical passaging and functional polymers. This setup resolves major problems associated with suspension culture methods and dynamic stirring systems and may be optimal for applications involving large-scale hPSC production.

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

Status: Large-scale subatmospheric cryogenic systems

International Nuclear Information System (INIS)

Peterson, T.

1989-01-01

In the late 1960's and early 1970's an interest in testing and operating RF cavities at 1.8K motivated the development and construction of four large (300 Watt) 1.8K refrigeration systems. in the past decade, development of successful superconducting RF cavities and interest in obtaining higher magnetic fields with the improved Niobium-Titanium superconductors has once again created interest in large-scale 1.8K refrigeration systems. The L'Air Liquide plant for Tore Supra is a recently commissioned 300 Watt 1.8K system which incorporates new technology, cold compressors, to obtain the low vapor pressure for low temperature cooling. CEBAF proposes to use cold compressors to obtain 5KW at 2.0K. Magnetic refrigerators of 10 Watt capacity or higher at 1.8K are now being developed. The state of the art of large-scale refrigeration in the range under 4K will be reviewed. 28 refs., 4 figs., 7 tabs

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...

Spatio-temporal spike train analysis for large scale networks using the maximum entropy principle and Monte Carlo method

International Nuclear Information System (INIS)

Nasser, Hassan; Cessac, Bruno; Marre, Olivier

2013-01-01

Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In the first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have focused on modelling synchronous spike patterns, leaving aside the temporal dynamics of the neural activity. However, the maximum entropy principle can be generalized to the temporal case, leading to Markovian models where memory effects and time correlations in the dynamics are properly taken into account. In the second part, we present a new method based on Monte Carlo sampling which is suited for the fitting of large-scale spatio-temporal MaxEnt models. The formalism and the tools presented here will be essential to fit MaxEnt spatio-temporal models to large neural ensembles. (paper)

Traffic assignment models in large-scale applications

DEFF Research Database (Denmark)

Rasmussen, Thomas Kjær

the potential of the method proposed and the possibility to use individual-based GPS units for travel surveys in real-life large-scale multi-modal networks. Congestion is known to highly influence the way we act in the transportation network (and organise our lives), because of longer travel times...... of observations of actual behaviour to obtain estimates of the (monetary) value of different travel time components, thereby increasing the behavioural realism of largescale models. vii The generation of choice sets is a vital component in route choice models. This is, however, not a straight-forward task in real......, but the reliability of the travel time also has a large impact on our travel choices. Consequently, in order to improve the realism of transport models, correct understanding and representation of two values that are related to the value of time (VoT) are essential: (i) the value of congestion (VoC), as the Vo...

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

Science.gov (United States)

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Gene prediction in metagenomic fragments: A large scale machine learning approach

Directory of Open Access Journals (Sweden)

Morgenstern Burkhard

2008-04-01

Full Text Available Abstract Background Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions. Results We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability. Conclusion Large scale machine learning methods are well-suited for gene

Benefits of transactive memory systems in large-scale development

OpenAIRE

Aivars, Sablis

2016-01-01

Context. Large-scale software development projects are those consisting of a large number of teams, maybe even spread across multiple locations, and working on large and complex software tasks. That means that neither a team member individually nor an entire team holds all the knowledge about the software being developed and teams have to communicate and coordinate their knowledge. Therefore, teams and team members in large-scale software development projects must acquire and manage expertise...

Analysis using large-scale ringing data

Directory of Open Access Journals (Sweden)

Baillie, S. R.

2004-06-01

]; Peach et al., 1998; DeSante et al., 2001 are generally co–ordinated by ringing centres such as those that make up the membership of EURING. In some countries volunteer census work (often called Breeding Bird Surveys is undertaken by the same organizations while in others different bodies may co–ordinate this aspect of the work. This session was concerned with the analysis of such extensive data sets and the approaches that are being developed to address the key theoretical and applied issues outlined above. The papers reflect the development of more spatially explicit approaches to analyses of data gathered at large spatial scales. They show that while the statistical tools that have been developed in recent years can be used to derive useful biological conclusions from such data, there is additional need for further developments. Future work should also consider how to best implement such analytical developments within future study designs. In his plenary paper Andy Royle (Royle, 2004 addresses this theme directly by describing a general framework for modelling spatially replicated abundance data. The approach is based on the idea that a set of spatially referenced local populations constitutes a metapopulation, within which local abundance is determined as a random process. This provides an elegant and general approach in which the metapopulation model as described above is combined with a data–generating model specific to the type of data being analysed to define a simple hierarchical model that can be analysed using conventional methods. It should be noted, however, that further software development will be needed if the approach is to be made readily available to biologists. The approach is well suited to dealing with sparse data and avoids the need for data aggregation prior to analysis. Spatial synchrony has received most attention in studies of species whose populations show cyclic fluctuations, particularly certain game birds and small mammals. However

Capabilities of the Large-Scale Sediment Transport Facility

Science.gov (United States)

2016-04-01

pump flow meters, sediment trap weigh tanks , and beach profiling lidar. A detailed discussion of the original LSTF features and capabilities can be...ERDC/CHL CHETN-I-88 April 2016 Approved for public release; distribution is unlimited. Capabilities of the Large-Scale Sediment Transport...describes the Large-Scale Sediment Transport Facility (LSTF) and recent upgrades to the measurement systems. The purpose of these upgrades was to increase

Development of large scale production of Nd-doped phosphate glasses for megajoule-scale laser systems

International Nuclear Information System (INIS)

Ficini, G.; Campbell, J.H.

1996-01-01

Nd-doped phosphate glasses are the preferred gain medium for high-peak-power lasers used for Inertial Confinement Fusion research because they have excellent energy storage and extraction characteristics. In addition, these glasses can be manufactured defect-free in large sizes and at relatively low cost. To meet the requirements of the future mega-joule size lasers, advanced laser glass manufacturing methods are being developed that would enable laser glass to be continuously produced at the rate of several thousand large (790 x 440 x 44 mm 3 ) plates of glass per year. This represents more than a 10 to 100-fold improvement in the scale of the present manufacturing technology

Spatiotemporal property and predictability of large-scale human mobility

Science.gov (United States)

Zhang, Hai-Tao; Zhu, Tao; Fu, Dongfei; Xu, Bowen; Han, Xiao-Pu; Chen, Duxin

2018-04-01

Spatiotemporal characteristics of human mobility emerging from complexity on individual scale have been extensively studied due to the application potential on human behavior prediction and recommendation, and control of epidemic spreading. We collect and investigate a comprehensive data set of human activities on large geographical scales, including both websites browse and mobile towers visit. Numerical results show that the degree of activity decays as a power law, indicating that human behaviors are reminiscent of scale-free random walks known as Lévy flight. More significantly, this study suggests that human activities on large geographical scales have specific non-Markovian characteristics, such as a two-segment power-law distribution of dwelling time and a high possibility for prediction. Furthermore, a scale-free featured mobility model with two essential ingredients, i.e., preferential return and exploration, and a Gaussian distribution assumption on the exploration tendency parameter is proposed, which outperforms existing human mobility models under scenarios of large geographical scales.

On soft limits of large-scale structure correlation functions

International Nuclear Information System (INIS)

Sagunski, Laura

2016-08-01

Large-scale structure surveys have the potential to become the leading probe for precision cosmology in the next decade. To extract valuable information on the cosmological evolution of the Universe from the observational data, it is of major importance to derive accurate theoretical predictions for the statistical large-scale structure observables, such as the power spectrum and the bispectrum of (dark) matter density perturbations. Hence, one of the greatest challenges of modern cosmology is to theoretically understand the non-linear dynamics of large-scale structure formation in the Universe from first principles. While analytic approaches to describe the large-scale structure formation are usually based on the framework of non-relativistic cosmological perturbation theory, we pursue another road in this thesis and develop methods to derive generic, non-perturbative statements about large-scale structure correlation functions. We study unequal- and equal-time correlation functions of density and velocity perturbations in the limit where one of their wavenumbers becomes small, that is, in the soft limit. In the soft limit, it is possible to link (N+1)-point and N-point correlation functions to non-perturbative 'consistency conditions'. These provide in turn a powerful tool to test fundamental aspects of the underlying theory at hand. In this work, we first rederive the (resummed) consistency conditions at unequal times by using the so-called eikonal approximation. The main appeal of the unequal-time consistency conditions is that they are solely based on symmetry arguments and thus are universal. Proceeding from this, we direct our attention to consistency conditions at equal times, which, on the other hand, depend on the interplay between soft and hard modes. We explore the existence and validity of equal-time consistency conditions within and beyond perturbation theory. For this purpose, we investigate the predictions for the soft limit of the

On soft limits of large-scale structure correlation functions

Energy Technology Data Exchange (ETDEWEB)

Sagunski, Laura

2016-08-15

Large-scale structure surveys have the potential to become the leading probe for precision cosmology in the next decade. To extract valuable information on the cosmological evolution of the Universe from the observational data, it is of major importance to derive accurate theoretical predictions for the statistical large-scale structure observables, such as the power spectrum and the bispectrum of (dark) matter density perturbations. Hence, one of the greatest challenges of modern cosmology is to theoretically understand the non-linear dynamics of large-scale structure formation in the Universe from first principles. While analytic approaches to describe the large-scale structure formation are usually based on the framework of non-relativistic cosmological perturbation theory, we pursue another road in this thesis and develop methods to derive generic, non-perturbative statements about large-scale structure correlation functions. We study unequal- and equal-time correlation functions of density and velocity perturbations in the limit where one of their wavenumbers becomes small, that is, in the soft limit. In the soft limit, it is possible to link (N+1)-point and N-point correlation functions to non-perturbative 'consistency conditions'. These provide in turn a powerful tool to test fundamental aspects of the underlying theory at hand. In this work, we first rederive the (resummed) consistency conditions at unequal times by using the so-called eikonal approximation. The main appeal of the unequal-time consistency conditions is that they are solely based on symmetry arguments and thus are universal. Proceeding from this, we direct our attention to consistency conditions at equal times, which, on the other hand, depend on the interplay between soft and hard modes. We explore the existence and validity of equal-time consistency conditions within and beyond perturbation theory. For this purpose, we investigate the predictions for the soft limit of the

Temperature scaling method for Markov chains.

Science.gov (United States)

Crosby, Lonnie D; Windus, Theresa L

2009-01-22

The use of ab initio potentials in Monte Carlo simulations aimed at investigating the nucleation kinetics of water clusters is complicated by the computational expense of the potential energy determinations. Furthermore, the common desire to investigate the temperature dependence of kinetic properties leads to an urgent need to reduce the expense of performing simulations at many different temperatures. A method is detailed that allows a Markov chain (obtained via Monte Carlo) at one temperature to be scaled to other temperatures of interest without the need to perform additional large simulations. This Markov chain temperature-scaling (TeS) can be generally applied to simulations geared for numerous applications. This paper shows the quality of results which can be obtained by TeS and the possible quantities which may be extracted from scaled Markov chains. Results are obtained for a 1-D analytical potential for which the exact solutions are known. Also, this method is applied to water clusters consisting of between 2 and 5 monomers, using Dynamical Nucleation Theory to determine the evaporation rate constant for monomer loss. Although ab initio potentials are not utilized in this paper, the benefit of this method is made apparent by using the Dang-Chang polarizable classical potential for water to obtain statistical properties at various temperatures.

Probing cosmology with the homogeneity scale of the Universe through large scale structure surveys

International Nuclear Information System (INIS)

Ntelis, Pierros

2017-01-01

. It is thus possible to reconstruct the distribution of matter in 3 dimensions in gigantic volumes. We can then extract various statistical observables to measure the BAO scale and the scale of homogeneity of the universe. Using Data Release 12 CMASS galaxy catalogs, we obtained precision on the homogeneity scale reduced by 5 times compared to Wiggle Z measurement. At large scales, the universe is remarkably well described in linear order by the ΛCDM-model, the standard model of cosmology. In general, it is not necessary to take into account the nonlinear effects which complicate the model at small scales. On the other hand, at large scales, the measurement of our observables becomes very sensitive to the systematic effects. This is particularly true for the analysis of cosmic homogeneity, which requires an observational method so as not to bias the measurement. In order to study the homogeneity principle in a model independent way, we explore a new way to infer distances using cosmic clocks and type Ia Supernovae. This establishes the Cosmological Principle using only a small number of a priori assumption, i.e. the theory of General Relativity and astrophysical assumptions that are independent from Friedmann Universes and in extend the homogeneity assumption. This manuscript is as follows. After a short presentation of the knowledge in cosmology necessary for the understanding of this manuscript, presented in Chapter 1, Chapter 2 will deal with the challenges of the Cosmological Principle as well as how to overcome those. In Chapter 3, we will discuss the technical characteristics of the large scale structure surveys, in particular focusing on BOSS and eBOSS galaxy surveys. Chapter 4 presents the detailed analysis of the measurement of cosmic homogeneity and the various systematic effects likely to impact our observables. Chapter 5 will discuss how to use the cosmic homogeneity as a standard ruler to constrain dark energy models from current and future surveys. In

Problems of large-scale vertically-integrated aquaculture

Energy Technology Data Exchange (ETDEWEB)

Webber, H H; Riordan, P F

1976-01-01

The problems of vertically-integrated aquaculture are outlined; they are concerned with: species limitations (in the market, biological and technological); site selection, feed, manpower needs, and legal, institutional and financial requirements. The gaps in understanding of, and the constraints limiting, large-scale aquaculture are listed. Future action is recommended with respect to: types and diversity of species to be cultivated, marketing, biotechnology (seed supply, disease control, water quality and concerted effort), siting, feed, manpower, legal and institutional aids (granting of water rights, grants, tax breaks, duty-free imports, etc.), and adequate financing. The last of hard data based on experience suggests that large-scale vertically-integrated aquaculture is a high risk enterprise, and with the high capital investment required, banks and funding institutions are wary of supporting it. Investment in pilot projects is suggested to demonstrate that large-scale aquaculture can be a fully functional and successful business. Construction and operation of such pilot farms is judged to be in the interests of both the public and private sector.

Surface-roughness-assisted formation of large-scale vertically aligned CdS nanorod arrays via solvothermal method

Energy Technology Data Exchange (ETDEWEB)

Zhou, Minmin [National Laboratory of Solid State Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093 (China); Yan, Shancheng, E-mail: yansc@njupt.edu.cn [National Laboratory of Solid State Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093 (China); School of Geography and Biological Information, Nanjing University of Posts and Telecommunications, Nanjing 210046 (China); Shi, Yi, E-mail: yshi@nju.edu.cn [National Laboratory of Solid State Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093 (China); Yang, Meng; Sun, Huabin; Wang, Jianyu; Yin, Yao; Gao, Fan [National Laboratory of Solid State Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093 (China)

2013-05-15

Large-scale cadmium sulfide (CdS) nanorod arrays were successfully synthesized on several different substrates through solvothermal reaction. During the growth experiments, we observed that the adhesion strength of the CdS nanorod arrays to different substrates differed dramatically, causing some of the CdS coating being easily flushed away by deionized water (DI water). With doubts and suspicions, we seriously investigate the original morphology of all the substrates by using atomic force microscopy (AFM). The phase, morphology, crystal structure and photoelectric property of all the products were characterized by X-ray diffractometer (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy and current–voltage (I–V) probe station. The growth mechanism of solvothermal reaction was proposed on the basis of all the characterizations. Our approach presents a universal method of liquid phase epitaxy of 1D material on a wide range of substrates of any shape.

A primal-dual interior point method for large-scale free material optimization

DEFF Research Database (Denmark)

Weldeyesus, Alemseged Gebrehiwot; Stolpe, Mathias

2015-01-01

Free Material Optimization (FMO) is a branch of structural optimization in which the design variable is the elastic material tensor that is allowed to vary over the design domain. The requirements are that the material tensor is symmetric positive semidefinite with bounded trace. The resulting...... optimization problem is a nonlinear semidefinite program with many small matrix inequalities for which a special-purpose optimization method should be developed. The objective of this article is to propose an efficient primal-dual interior point method for FMO that can robustly and accurately solve large...... of iterations the interior point method requires is modest and increases only marginally with problem size. The computed optimal solutions obtain a higher precision than other available special-purpose methods for FMO. The efficiency and robustness of the method is demonstrated by numerical experiments on a set...

Large-scale computing with Quantum Espresso

International Nuclear Information System (INIS)

Giannozzi, P.; Cavazzoni, C.

2009-01-01

This paper gives a short introduction to Quantum Espresso: a distribution of software for atomistic simulations in condensed-matter physics, chemical physics, materials science, and to its usage in large-scale parallel computing.

BILGO: Bilateral greedy optimization for large scale semidefinite programming

KAUST Repository

Hao, Zhifeng; Yuan, Ganzhao; Ghanem, Bernard

2013-01-01

Many machine learning tasks (e.g. metric and manifold learning problems) can be formulated as convex semidefinite programs. To enable the application of these tasks on a large-scale, scalability and computational efficiency are considered as desirable properties for a practical semidefinite programming algorithm. In this paper, we theoretically analyze a new bilateral greedy optimization (denoted BILGO) strategy in solving general semidefinite programs on large-scale datasets. As compared to existing methods, BILGO employs a bilateral search strategy during each optimization iteration. In such an iteration, the current semidefinite matrix solution is updated as a bilateral linear combination of the previous solution and a suitable rank-1 matrix, which can be efficiently computed from the leading eigenvector of the descent direction at this iteration. By optimizing for the coefficients of the bilateral combination, BILGO reduces the cost function in every iteration until the KKT conditions are fully satisfied, thus, it tends to converge to a global optimum. In fact, we prove that BILGO converges to the global optimal solution at a rate of O(1/k), where k is the iteration counter. The algorithm thus successfully combines the efficiency of conventional rank-1 update algorithms and the effectiveness of gradient descent. Moreover, BILGO can be easily extended to handle low rank constraints. To validate the effectiveness and efficiency of BILGO, we apply it to two important machine learning tasks, namely Mahalanobis metric learning and maximum variance unfolding. Extensive experimental results clearly demonstrate that BILGO can solve large-scale semidefinite programs efficiently.

BILGO: Bilateral greedy optimization for large scale semidefinite programming

KAUST Repository

Hao, Zhifeng

2013-10-03

Many machine learning tasks (e.g. metric and manifold learning problems) can be formulated as convex semidefinite programs. To enable the application of these tasks on a large-scale, scalability and computational efficiency are considered as desirable properties for a practical semidefinite programming algorithm. In this paper, we theoretically analyze a new bilateral greedy optimization (denoted BILGO) strategy in solving general semidefinite programs on large-scale datasets. As compared to existing methods, BILGO employs a bilateral search strategy during each optimization iteration. In such an iteration, the current semidefinite matrix solution is updated as a bilateral linear combination of the previous solution and a suitable rank-1 matrix, which can be efficiently computed from the leading eigenvector of the descent direction at this iteration. By optimizing for the coefficients of the bilateral combination, BILGO reduces the cost function in every iteration until the KKT conditions are fully satisfied, thus, it tends to converge to a global optimum. In fact, we prove that BILGO converges to the global optimal solution at a rate of O(1/k), where k is the iteration counter. The algorithm thus successfully combines the efficiency of conventional rank-1 update algorithms and the effectiveness of gradient descent. Moreover, BILGO can be easily extended to handle low rank constraints. To validate the effectiveness and efficiency of BILGO, we apply it to two important machine learning tasks, namely Mahalanobis metric learning and maximum variance unfolding. Extensive experimental results clearly demonstrate that BILGO can solve large-scale semidefinite programs efficiently.

Grid sensitivity capability for large scale structures

Science.gov (United States)

Nagendra, Gopal K.; Wallerstein, David V.

1989-01-01

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

Ship detection using STFT sea background statistical modeling for large-scale oceansat remote sensing image

Science.gov (United States)

Wang, Lixia; Pei, Jihong; Xie, Weixin; Liu, Jinyuan

2018-03-01

Large-scale oceansat remote sensing images cover a big area sea surface, which fluctuation can be considered as a non-stationary process. Short-Time Fourier Transform (STFT) is a suitable analysis tool for the time varying nonstationary signal. In this paper, a novel ship detection method using 2-D STFT sea background statistical modeling for large-scale oceansat remote sensing images is proposed. First, the paper divides the large-scale oceansat remote sensing image into small sub-blocks, and 2-D STFT is applied to each sub-block individually. Second, the 2-D STFT spectrum of sub-blocks is studied and the obvious different characteristic between sea background and non-sea background is found. Finally, the statistical model for all valid frequency points in the STFT spectrum of sea background is given, and the ship detection method based on the 2-D STFT spectrum modeling is proposed. The experimental result shows that the proposed algorithm can detect ship targets with high recall rate and low missing rate.

Deterministic sensitivity and uncertainty analysis for large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

1988-01-01

The fields of sensitivity and uncertainty analysis have traditionally been dominated by statistical techniques when large-scale modeling codes are being analyzed. These methods are able to estimate sensitivities, generate response surfaces, and estimate response probability distributions given the input parameter probability distributions. Because the statistical methods are computationally costly, they are usually applied only to problems with relatively small parameter sets. Deterministic methods, on the other hand, are very efficient and can handle large data sets, but generally require simpler models because of the considerable programming effort required for their implementation. The first part of this paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. This second part of the paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. This paper is applicable to low-level radioactive waste disposal system performance assessment

Large-scale computation in solid state physics - Recent developments and prospects

International Nuclear Information System (INIS)

DeVreese, J.T.

1985-01-01

During the past few years an increasing interest in large-scale computation is developing. Several initiatives were taken to evaluate and exploit the potential of ''supercomputers'' like the CRAY-1 (or XMP) or the CYBER-205. In the U.S.A., there first appeared the Lax report in 1982 and subsequently (1984) the National Science Foundation in the U.S.A. announced a program to promote large-scale computation at the universities. Also, in Europe several CRAY- and CYBER-205 systems have been installed. Although the presently available mainframes are the result of a continuous growth in speed and memory, they might have induced a discontinuous transition in the evolution of the scientific method; between theory and experiment a third methodology, ''computational science'', has become or is becoming operational

Exploiting large-scale correlations to detect continuous gravitational waves.

Science.gov (United States)

Pletsch, Holger J; Allen, Bruce

2009-10-30

Fully coherent searches (over realistic ranges of parameter space and year-long observation times) for unknown sources of continuous gravitational waves are computationally prohibitive. Less expensive hierarchical searches divide the data into shorter segments which are analyzed coherently, then detection statistics from different segments are combined incoherently. The novel method presented here solves the long-standing problem of how best to do the incoherent combination. The optimal solution exploits large-scale parameter-space correlations in the coherent detection statistic. Application to simulated data shows dramatic sensitivity improvements compared with previously available (ad hoc) methods, increasing the spatial volume probed by more than 2 orders of magnitude at lower computational cost.

Primal Interior-Point Method for Large Sparse Minimax Optimization

Czech Academy of Sciences Publication Activity Database

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan

2009-01-01

Roč. 45, č. 5 (2009), s. 841-864 ISSN 0023-5954 R&D Projects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : unconstrained optimization * large-scale optimization * minimax optimization * nonsmooth optimization * interior-point methods * modified Newton methods * variable metric methods * computational experiments Subject RIV: BA - General Mathematics Impact factor: 0.445, year: 2009 http://dml.cz/handle/10338.dmlcz/140034

The Ownership Structure Dilemma and its Implications on the Transition from Small-Scale to Large-Scale Electric Road Systems

OpenAIRE

BEDNARCIK ABDULHADI, EMMA; VITEZ, MARINA

2016-01-01

This master thesis is written on behalf of KTH Royal Institute of Technology and the Swedish National Road and Transport Research Institute (VTI). The study investigates how infrastructure ownership could affect the transition from small-scale to large-scale electric road systems (ERS) and how infrastructure ownership affects the foreseen future roles of the ERS stakeholders. The authors have used a qualitative research method, including a literature study within the areas of infrastructure t...

RESTRUCTURING OF THE LARGE-SCALE SPRINKLERS

Directory of Open Access Journals (Sweden)

Paweł Kozaczyk

2016-09-01

Full Text Available One of the best ways for agriculture to become independent from shortages of precipitation is irrigation. In the seventies and eighties of the last century a number of large-scale sprinklers in Wielkopolska was built. At the end of 1970’s in the Poznan province 67 sprinklers with a total area of 6400 ha were installed. The average size of the sprinkler reached 95 ha. In 1989 there were 98 sprinklers, and the area which was armed with them was more than 10 130 ha. The study was conducted on 7 large sprinklers with the area ranging from 230 to 520 hectares in 1986÷1998. After the introduction of the market economy in the early 90’s and ownership changes in agriculture, large-scale sprinklers have gone under a significant or total devastation. Land on the State Farms of the State Agricultural Property Agency has leased or sold and the new owners used the existing sprinklers to a very small extent. This involved a change in crop structure, demand structure and an increase in operating costs. There has also been a threefold increase in electricity prices. Operation of large-scale irrigation encountered all kinds of barriers in practice and limitations of system solutions, supply difficulties, high levels of equipment failure which is not inclined to rational use of available sprinklers. An effect of a vision of the local area was to show the current status of the remaining irrigation infrastructure. The adopted scheme for the restructuring of Polish agriculture was not the best solution, causing massive destruction of assets previously invested in the sprinkler system.

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...

The Phoenix series large scale LNG pool fire experiments.

Energy Technology Data Exchange (ETDEWEB)

Simpson, Richard B.; Jensen, Richard Pearson; Demosthenous, Byron; Luketa, Anay Josephine; Ricks, Allen Joseph; Hightower, Marion Michael; Blanchat, Thomas K.; Helmick, Paul H.; Tieszen, Sheldon Robert; Deola, Regina Anne; Mercier, Jeffrey Alan; Suo-Anttila, Jill Marie; Miller, Timothy J.

2010-12-01

The increasing demand for natural gas could increase the number and frequency of Liquefied Natural Gas (LNG) tanker deliveries to ports across the United States. Because of the increasing number of shipments and the number of possible new facilities, concerns about the potential safety of the public and property from an accidental, and even more importantly intentional spills, have increased. While improvements have been made over the past decade in assessing hazards from LNG spills, the existing experimental data is much smaller in size and scale than many postulated large accidental and intentional spills. Since the physics and hazards from a fire change with fire size, there are concerns about the adequacy of current hazard prediction techniques for large LNG spills and fires. To address these concerns, Congress funded the Department of Energy (DOE) in 2008 to conduct a series of laboratory and large-scale LNG pool fire experiments at Sandia National Laboratories (Sandia) in Albuquerque, New Mexico. This report presents the test data and results of both sets of fire experiments. A series of five reduced-scale (gas burner) tests (yielding 27 sets of data) were conducted in 2007 and 2008 at Sandia's Thermal Test Complex (TTC) to assess flame height to fire diameter ratios as a function of nondimensional heat release rates for extrapolation to large-scale LNG fires. The large-scale LNG pool fire experiments were conducted in a 120 m diameter pond specially designed and constructed in Sandia's Area III large-scale test complex. Two fire tests of LNG spills of 21 and 81 m in diameter were conducted in 2009 to improve the understanding of flame height, smoke production, and burn rate and therefore the physics and hazards of large LNG spills and fires.

Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks.

Science.gov (United States)

Lee, Seungseob; Lee, SuKyoung; Kim, Kyungsoo; Kim, Yoon Hyuk

2015-01-01

Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators' careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system

Modeling and control of a large nuclear reactor. A three-time-scale approach

Energy Technology Data Exchange (ETDEWEB)

Shimjith, S.R. [Indian Institute of Technology Bombay, Mumbai (India); Bhabha Atomic Research Centre, Mumbai (India); Tiwari, A.P. [Bhabha Atomic Research Centre, Mumbai (India); Bandyopadhyay, B. [Indian Institute of Technology Bombay, Mumbai (India). IDP in Systems and Control Engineering

2013-07-01

Recent research on Modeling and Control of a Large Nuclear Reactor. Presents a three-time-scale approach. Written by leading experts in the field. Control analysis and design of large nuclear reactors requires a suitable mathematical model representing the steady state and dynamic behavior of the reactor with reasonable accuracy. This task is, however, quite challenging because of several complex dynamic phenomena existing in a reactor. Quite often, the models developed would be of prohibitively large order, non-linear and of complex structure not readily amenable for control studies. Moreover, the existence of simultaneously occurring dynamic variations at different speeds makes the mathematical model susceptible to numerical ill-conditioning, inhibiting direct application of standard control techniques. This monograph introduces a technique for mathematical modeling of large nuclear reactors in the framework of multi-point kinetics, to obtain a comparatively smaller order model in standard state space form thus overcoming these difficulties. It further brings in innovative methods for controller design for systems exhibiting multi-time-scale property, with emphasis on three-time-scale systems.

Applications of Data Assimilation to Analysis of the Ocean on Large Scales

Science.gov (United States)

Miller, Robert N.; Busalacchi, Antonio J.; Hackert, Eric C.

1997-01-01

It is commonplace to begin talks on this topic by noting that oceanographic data are too scarce and sparse to provide complete initial and boundary conditions for large-scale ocean models. Even considering the availability of remotely-sensed data such as radar altimetry from the TOPEX and ERS-1 satellites, a glance at a map of available subsurface data should convince most observers that this is still the case. Data are still too sparse for comprehensive treatment of interannual to interdecadal climate change through the use of models, since the new data sets have not been around for very long. In view of the dearth of data, we must note that the overall picture is changing rapidly. Recently, there have been a number of large scale ocean analysis and prediction efforts, some of which now run on an operational or at least quasi-operational basis, most notably the model based analyses of the tropical oceans. These programs are modeled on numerical weather prediction. Aside from the success of the global tide models, assimilation of data in the tropics, in support of prediction and analysis of seasonal to interannual climate change, is probably the area of large scale ocean modeling and data assimilation in which the most progress has been made. Climate change is a problem which is particularly suited to advanced data assimilation methods. Linear models are useful, and the linear theory can be exploited. For the most part, the data are sufficiently sparse that implementation of advanced methods is worthwhile. As an example of a large scale data assimilation experiment with a recent extensive data set, we present results of a tropical ocean experiment in which the Kalman filter was used to assimilate three years of altimetric data from Geosat into a coarsely resolved linearized long wave shallow water model. Since nonlinear processes dominate the local dynamic signal outside the tropics, subsurface dynamical quantities cannot be reliably inferred from surface height

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

Energy Technology Data Exchange (ETDEWEB)

Blas, Diego; Garny, Mathias; Sibiryakov, Sergey [Theory Division, CERN, CH-1211 Genève 23 (Switzerland); Ivanov, Mikhail M., E-mail: diego.blas@cern.ch, E-mail: mathias.garny@cern.ch, E-mail: mikhail.ivanov@cern.ch, E-mail: sergey.sibiryakov@cern.ch [FSB/ITP/LPPC, École Polytechnique Fédérale de Lausanne, CH-1015, Lausanne (Switzerland)

2016-07-01

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

Large-scale Agricultural Land Acquisitions in West Africa | IDRC ...

International Development Research Centre (IDRC) Digital Library (Canada)

This project will examine large-scale agricultural land acquisitions in nine West African countries -Burkina Faso, Guinea-Bissau, Guinea, Benin, Mali, Togo, Senegal, Niger, and Côte d'Ivoire. ... They will use the results to increase public awareness and knowledge about the consequences of large-scale land acquisitions.

Large-scale uniform ZnO tetrapods on catalyst free glass substrate by thermal evaporation method

Energy Technology Data Exchange (ETDEWEB)

Alsultany, Forat H., E-mail: foratusm@gmail.com [School of Physics, USM, 11800 Penang (Malaysia); Hassan, Z. [Institute of Nano-Optoelectronics Research and Technology Laboratory (INOR), USM, 11800 Penang (Malaysia); Ahmed, Naser M. [School of Physics, USM, 11800 Penang (Malaysia)

2016-07-15

Highlights: • Investigate the growth of ZnO-Ts on glass substrate by thermal evaporation method. • Glass substrate without any catalyst or a seed layer. • The morphology was controlled by adjusting the temperature of the material and the substrate. • Glass substrate was placed vertically in the quartz tube. - Abstract: Here, we report for the first time the catalyst-free growth of large-scale uniform shape and size ZnO tetrapods on a glass substrate via thermal evaporation method. Three-dimensional networks of ZnO tetrapods have needle–wire junctions, an average leg length of 2.1–2.6 μm, and a diameter of 35–240 nm. The morphology and structure of ZnO tetrapods were investigated by controlling the preparation temperature of each of the Zn powder and the glass substrate under O{sub 2} and Ar gases. Studies were carried out on ZnO tetrapods using X-ray diffraction, field emission scanning electron microscopy, UV–vis spectrophotometer, and a photoluminescence. The results showed that the sample grow in the hexagonal wurtzite structure with preferentially oriented along (002) direction, good crystallinity and high transmittance. The band gap value is about 3.27 eV. Photoluminescence spectrum exhibits a very sharp peak at 378 nm and a weak broad green emission.

Large-scale motions in the universe: a review

International Nuclear Information System (INIS)

Burstein, D.

1990-01-01

The expansion of the universe can be retarded in localised regions within the universe both by the presence of gravity and by non-gravitational motions generated in the post-recombination universe. The motions of galaxies thus generated are called 'peculiar motions', and the amplitudes, size scales and coherence of these peculiar motions are among the most direct records of the structure of the universe. As such, measurements of these properties of the present-day universe provide some of the severest tests of cosmological theories. This is a review of the current evidence for large-scale motions of galaxies out to a distance of ∼5000 km s -1 (in an expanding universe, distance is proportional to radial velocity). 'Large-scale' in this context refers to motions that are correlated over size scales larger than the typical sizes of groups of galaxies, up to and including the size of the volume surveyed. To orient the reader into this relatively new field of study, a short modern history is given together with an explanation of the terminology. Careful consideration is given to the data used to measure the distances, and hence the peculiar motions, of galaxies. The evidence for large-scale motions is presented in a graphical fashion, using only the most reliable data for galaxies spanning a wide range in optical properties and over the complete range of galactic environments. The kinds of systematic errors that can affect this analysis are discussed, and the reliability of these motions is assessed. The predictions of two models of large-scale motion are compared to the observations, and special emphasis is placed on those motions in which our own Galaxy directly partakes. (author)

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.;

A Novel Yeast Surface Display Method for Large-Scale Screen Inhibitors of Sortase A.

Science.gov (United States)

Wu, Lin; Li, Huijun; Tang, Tianle

2017-01-24

high-throughput analysis, but the conventional method is much more sensitive. The method described in this paper is expected to lead to large-scale screening of sortase A inhibitors which can be used to decrease the risk of drug resistance development.

A Novel Yeast Surface Display Method for Large-Scale Screen Inhibitors of Sortase A

Directory of Open Access Journals (Sweden)

Lin Wu

2017-01-01

suitable for high-throughput analysis, but the conventional method is much more sensitive. The method described in this paper is expected to lead to large-scale screening of sortase A inhibitors which can be used to decrease the risk of drug resistance development.

Solution approach for a large scale personnel transport system for a large company in Latin America

Energy Technology Data Exchange (ETDEWEB)

Garzón-Garnica, Eduardo-Arturo; Caballero-Morales, Santiago-Omar; Martínez-Flores, José-Luis

2017-07-01

The present paper focuses on the modelling and solution of a large-scale personnel transportation system in Mexico where many routes and vehicles are currently used to service 525 points. The routing system proposed can be applied to many cities in the Latin-American region. Design/methodology/approach: This system was modelled as a VRP model considering the use of real-world transit times, and the fact that routes start at the farthest point from the destination center. Experiments were performed on different sized sets of service points. As the size of the instances was increased, the performance of the heuristic method was assessed in comparison with the results of an exact algorithm, the results remaining very close between both. When the size of the instance was full-scale and the exact algorithm took too much time to solve the problem, then the heuristic algorithm provided a feasible solution. Supported by the validation with smaller scale instances, where the difference between both solutions was close to a 6%, the full –scale solution obtained with the heuristic algorithm was considered to be within that same range. Findings: The proposed modelling and solving method provided a solution that would produce significant savings in the daily operation of the routes. Originality/value: The urban distribution of the cities in Latin America is unique to other regions in the world. The general layout of the large cities in this region includes a small town center, usually antique, and a somewhat disordered outer region. The lack of a vehicle-centered urban planning poses distinct challenges for vehicle routing problems in the region. The use of a heuristic VRP combined with the results of an exact VRP, allowed the obtention of an improved routing plan specific to the requirements of the region.

Solution approach for a large scale personnel transport system for a large company in Latin America

International Nuclear Information System (INIS)

Garzón-Garnica, Eduardo-Arturo; Caballero-Morales, Santiago-Omar; Martínez-Flores, José-Luis

2017-01-01

The present paper focuses on the modelling and solution of a large-scale personnel transportation system in Mexico where many routes and vehicles are currently used to service 525 points. The routing system proposed can be applied to many cities in the Latin-American region. Design/methodology/approach: This system was modelled as a VRP model considering the use of real-world transit times, and the fact that routes start at the farthest point from the destination center. Experiments were performed on different sized sets of service points. As the size of the instances was increased, the performance of the heuristic method was assessed in comparison with the results of an exact algorithm, the results remaining very close between both. When the size of the instance was full-scale and the exact algorithm took too much time to solve the problem, then the heuristic algorithm provided a feasible solution. Supported by the validation with smaller scale instances, where the difference between both solutions was close to a 6%, the full –scale solution obtained with the heuristic algorithm was considered to be within that same range. Findings: The proposed modelling and solving method provided a solution that would produce significant savings in the daily operation of the routes. Originality/value: The urban distribution of the cities in Latin America is unique to other regions in the world. The general layout of the large cities in this region includes a small town center, usually antique, and a somewhat disordered outer region. The lack of a vehicle-centered urban planning poses distinct challenges for vehicle routing problems in the region. The use of a heuristic VRP combined with the results of an exact VRP, allowed the obtention of an improved routing plan specific to the requirements of the region.

Solution approach for a large scale personnel transport system for a large company in Latin America

Directory of Open Access Journals (Sweden)

Eduardo-Arturo Garzón-Garnica

2017-10-01

Full Text Available Purpose: The present paper focuses on the modelling and solution of a large-scale personnel transportation system in Mexico where many routes and vehicles are currently used to service 525 points. The routing system proposed can be applied to many cities in the Latin-American region. Design/methodology/approach: This system was modelled as a VRP model considering the use of real-world transit times, and the fact that routes start at the farthest point from the destination center. Experiments were performed on different sized sets of service points. As the size of the instances was increased, the performance of the heuristic method was assessed in comparison with the results of an exact algorithm, the results remaining very close between both.  When the size of the instance was full-scale and the exact algorithm took too much time to solve the problem, then the heuristic algorithm provided a feasible solution. Supported by the validation with smaller scale instances, where the difference between both solutions was close to a 6%, the full –scale solution obtained with the heuristic algorithm was considered to be within that same range. Findings: The proposed modelling and solving method provided a solution that would produce significant savings in the daily operation of the routes. Originality/value: The urban distribution of the cities in Latin America is unique to other regions in the world. The general layout of the large cities in this region includes a small town center, usually antique, and a somewhat disordered outer region. The lack of a vehicle-centered urban planning poses distinct challenges for vehicle routing problems in the region. The use of a heuristic VRP combined with the results of an exact VRP, allowed the obtention of an improved routing plan specific to the requirements of the region.

Sensitivity technologies for large scale simulation

International Nuclear Information System (INIS)

Collis, Samuel Scott; Bartlett, Roscoe Ainsworth; Smith, Thomas Michael; Heinkenschloss, Matthias; Wilcox, Lucas C.; Hill, Judith C.; Ghattas, Omar; Berggren, Martin Olof; Akcelik, Volkan; Ober, Curtis Curry; van Bloemen Waanders, Bart Gustaaf; Keiter, Eric Richard

2005-01-01

Sensitivity analysis is critically important to numerous analysis algorithms, including large scale optimization, uncertainty quantification,reduced order modeling, and error estimation. Our research focused on developing tools, algorithms and standard interfaces to facilitate the implementation of sensitivity type analysis into existing code and equally important, the work was focused on ways to increase the visibility of sensitivity analysis. We attempt to accomplish the first objective through the development of hybrid automatic differentiation tools, standard linear algebra interfaces for numerical algorithms, time domain decomposition algorithms and two level Newton methods. We attempt to accomplish the second goal by presenting the results of several case studies in which direct sensitivities and adjoint methods have been effectively applied, in addition to an investigation of h-p adaptivity using adjoint based a posteriori error estimation. A mathematical overview is provided of direct sensitivities and adjoint methods for both steady state and transient simulations. Two case studies are presented to demonstrate the utility of these methods. A direct sensitivity method is implemented to solve a source inversion problem for steady state internal flows subject to convection diffusion. Real time performance is achieved using novel decomposition into offline and online calculations. Adjoint methods are used to reconstruct initial conditions of a contamination event in an external flow. We demonstrate an adjoint based transient solution. In addition, we investigated time domain decomposition algorithms in an attempt to improve the efficiency of transient simulations. Because derivative calculations are at the root of sensitivity calculations, we have developed hybrid automatic differentiation methods and implemented this approach for shape optimization for gas dynamics using the Euler equations. The hybrid automatic differentiation method was applied to a first

Constructing sites at a large scale - towards new design (education) methods

DEFF Research Database (Denmark)

Braae, Ellen Marie; Tietjen, Anne

2010-01-01

of the design disciplines within the development of our urban landscapes. At the same time, urban and landscape designers are confronted with new methodological problems. Within a strategic transformation perspective the formulation of the design problem or brief becomes an integrated part of the design process......Since the 1990s the regional scale has regained importance in urban and landscape design. In parallel, the focus in design tasks has shifted from master plans for urban extension to strategic urban transformation projects. The current paradigm of planning by projects reinforces the role....... This paper discusses new design (education) methods based on a relational concept of urban sites and design processes using the actor-network-theory as theoretical frame....

A route to explosive large-scale magnetic reconnection in a super-ion-scale current sheet

Directory of Open Access Journals (Sweden)

K. G. Tanaka

2009-01-01

Full Text Available How to trigger magnetic reconnection is one of the most interesting and important problems in space plasma physics. Recently, electron temperature anisotropy (αeo=Te⊥/Te|| at the center of a current sheet and non-local effect of the lower-hybrid drift instability (LHDI that develops at the current sheet edges have attracted attention in this context. In addition to these effects, here we also study the effects of ion temperature anisotropy (αio=Ti⊥/Ti||. Electron anisotropy effects are known to be helpless in a current sheet whose thickness is of ion-scale. In this range of current sheet thickness, the LHDI effects are shown to weaken substantially with a small increase in thickness and the obtained saturation level is too low for a large-scale reconnection to be achieved. Then we investigate whether introduction of electron and ion temperature anisotropies in the initial stage would couple with the LHDI effects to revive quick triggering of large-scale reconnection in a super-ion-scale current sheet. The results are as follows. (1 The initial electron temperature anisotropy is consumed very quickly when a number of minuscule magnetic islands (each lateral length is 1.5~3 times the ion inertial length form. These minuscule islands do not coalesce into a large-scale island to enable large-scale reconnection. (2 The subsequent LHDI effects disturb the current sheet filled with the small islands. This makes the triggering time scale to be accelerated substantially but does not enhance the saturation level of reconnected flux. (3 When the ion temperature anisotropy is added, it survives through the small island formation stage and makes even quicker triggering to happen when the LHDI effects set-in. Furthermore the saturation level is seen to be elevated by a factor of ~2 and large-scale reconnection is achieved only in this case. Comparison with two-dimensional simulations that exclude the LHDI effects confirms that the saturation level

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.

LARGE-SCALE MAGNETIC HELICITY FLUXES ESTIMATED FROM MDI MAGNETIC SYNOPTIC CHARTS OVER THE SOLAR CYCLE 23

Energy Technology Data Exchange (ETDEWEB)

Yang Shangbin; Zhang Hongqi, E-mail: yangshb@nao.cas.cn [Key Laboratory of Solar Activity, National Astronomical Observatories, Chinese Academy of Sciences, 100012 Beijing (China)

2012-10-10

To investigate the characteristics of large-scale and long-term evolution of magnetic helicity with solar cycles, we use the method of Local Correlation Tracking to estimate the magnetic helicity evolution over solar cycle 23 from 1996 to 2009 using 795 MDI magnetic synoptic charts. The main results are as follows: the hemispheric helicity rule still holds in general, i.e., the large-scale negative (positive) magnetic helicity dominates the northern (southern) hemisphere. However, the large-scale magnetic helicity fluxes show the same sign in both hemispheres around 2001 and 2005. The global, large-scale magnetic helicity flux over the solar disk changes from a negative value at the beginning of solar cycle 23 to a positive value at the end of the cycle, while the net accumulated magnetic helicity is negative in the period between 1996 and 2009.

LARGE-SCALE MAGNETIC HELICITY FLUXES ESTIMATED FROM MDI MAGNETIC SYNOPTIC CHARTS OVER THE SOLAR CYCLE 23

International Nuclear Information System (INIS)

Yang Shangbin; Zhang Hongqi

2012-01-01

To investigate the characteristics of large-scale and long-term evolution of magnetic helicity with solar cycles, we use the method of Local Correlation Tracking to estimate the magnetic helicity evolution over solar cycle 23 from 1996 to 2009 using 795 MDI magnetic synoptic charts. The main results are as follows: the hemispheric helicity rule still holds in general, i.e., the large-scale negative (positive) magnetic helicity dominates the northern (southern) hemisphere. However, the large-scale magnetic helicity fluxes show the same sign in both hemispheres around 2001 and 2005. The global, large-scale magnetic helicity flux over the solar disk changes from a negative value at the beginning of solar cycle 23 to a positive value at the end of the cycle, while the net accumulated magnetic helicity is negative in the period between 1996 and 2009.

Large scale computing in theoretical physics: Example QCD

International Nuclear Information System (INIS)

Schilling, K.

1986-01-01

The limitations of the classical mathematical analysis of Newton and Leibniz appear to be more and more overcome by the power of modern computers. Large scale computing techniques - which resemble closely the methods used in simulations within statistical mechanics - allow to treat nonlinear systems with many degrees of freedom such as field theories in nonperturbative situations, where analytical methods do fail. The computation of the hadron spectrum within the framework of lattice QCD sets a demanding goal for the application of supercomputers in basic science. It requires both big computer capacities and clever algorithms to fight all the numerical evils that one encounters in the Euclidean world. The talk will attempt to describe both the computer aspects and the present state of the art of spectrum calculations within lattice QCD. (orig.)

Application of the PSA method to decay heat removal systems in a large scale FBR design

International Nuclear Information System (INIS)

Kotake, S.; Satoh, K.; Matsumoto, H.; Sugawara, M.; Sakata, K.; Okabe, A.

1993-01-01

The Probabilistic Safety Assessment (PSA) method is applied to a large scale loop-type FBR in its conceptual design stage in order to establish a well-balanced safety. Both the reactor shut down and decay heat removal systems are designed to be highly reliable, e.g. 10 -7 /d. In this paper the results of several reliability analyses concerning the DHRS have been discussed, where the effects of the analytical assumptions, design options, accident managements on the reliability are examined. The reliability is evaluated small enough, since DRACSs consists of four independent loops with sufficient heat removal capacity and both forced and natural circulation capabilities are designed. It is found that the common mode failures for the active components in the DRACS dominate the reliability. The design diversity concerning these components can be effective for the improvements and the accident managements on BOP are also possible by making use of the long grace period in FBR. (author)

Application of the PSA method to decay heat removal systems in a large scale FBR design

Energy Technology Data Exchange (ETDEWEB)

Kotake, S; Satoh, K [Japan Atomic Power Company, Otemachi, Chiyoda-ku, Tokyo (Japan); Matsumoto, H; Sugawara, M [Toshiba Corporation (Japan); Sakata, K [Mitsubishi Atomic Power Industries Inc. (Japan); Okabe, A [Hitachi Engineering Co., Ltd. (Japan)

1993-02-01

The Probabilistic Safety Assessment (PSA) method is applied to a large scale loop-type FBR in its conceptual design stage in order to establish a well-balanced safety. Both the reactor shut down and decay heat removal systems are designed to be highly reliable, e.g. 10{sup -7}/d. In this paper the results of several reliability analyses concerning the DHRS have been discussed, where the effects of the analytical assumptions, design options, accident managements on the reliability are examined. The reliability is evaluated small enough, since DRACSs consists of four independent loops with sufficient heat removal capacity and both forced and natural circulation capabilities are designed. It is found that the common mode failures for the active components in the DRACS dominate the reliability. The design diversity concerning these components can be effective for the improvements and the accident managements on BOP are also possible by making use of the long grace period in FBR. (author)

A small-scale, rolled-membrane microfluidic artificial lung designed towards future large area manufacturing.

Science.gov (United States)

Thompson, A J; Marks, L H; Goudie, M J; Rojas-Pena, A; Handa, H; Potkay, J A

2017-03-01

Artificial lungs have been used in the clinic for multiple decades to supplement patient pulmonary function. Recently, small-scale microfluidic artificial lungs (μAL) have been demonstrated with large surface area to blood volume ratios, biomimetic blood flow paths, and pressure drops compatible with pumpless operation. Initial small-scale microfluidic devices with blood flow rates in the μ l/min to ml/min range have exhibited excellent gas transfer efficiencies; however, current manufacturing techniques may not be suitable for scaling up to human applications. Here, we present a new manufacturing technology for a microfluidic artificial lung in which the structure is assembled via a continuous "rolling" and bonding procedure from a single, patterned layer of polydimethyl siloxane (PDMS). This method is demonstrated in a small-scale four-layer device, but is expected to easily scale to larger area devices. The presented devices have a biomimetic branching blood flow network, 10  μ m tall artificial capillaries, and a 66  μ m thick gas transfer membrane. Gas transfer efficiency in blood was evaluated over a range of blood flow rates (0.1-1.25 ml/min) for two different sweep gases (pure O 2 , atmospheric air). The achieved gas transfer data closely follow predicted theoretical values for oxygenation and CO 2 removal, while pressure drop is marginally higher than predicted. This work is the first step in developing a scalable method for creating large area microfluidic artificial lungs. Although designed for microfluidic artificial lungs, the presented technique is expected to result in the first manufacturing method capable of simply and easily creating large area microfluidic devices from PDMS.

Estimation of turbulence dissipation rate by Large eddy PIV method in an agitated vessel

Directory of Open Access Journals (Sweden)

Kysela Bohuš

2015-01-01

Full Text Available The distribution of turbulent kinetic energy dissipation rate is important for design of mixing apparatuses in chemical industry. Generally used experimental methods of velocity measurements for measurement in complex geometries of an agitated vessel disallow measurement in resolution of small scales close to turbulence dissipation ones. Therefore, Particle image velocity (PIV measurement method improved by large eddy Ply approach was used. Large eddy PIV method is based on modeling of smallest eddies by a sub grid scale (SGS model. This method is similar to numerical calculations using Large Eddy Simulation (LES and the same SGS models are used. In this work the basic Smagorinsky model was employed and compared with power law approximation. Time resolved PIV data were processed by Large Eddy PIV approach and the obtained results of turbulent kinetic dissipation rate were compared in selected points for several operating conditions (impeller speed, operating liquid viscosity.

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.

Finite-Time Stability of Large-Scale Systems with Interval Time-Varying Delay in Interconnection

Directory of Open Access Journals (Sweden)

T. La-inchua

2017-01-01

Full Text Available We investigate finite-time stability of a class of nonlinear large-scale systems with interval time-varying delays in interconnection. Time-delay functions are continuous but not necessarily differentiable. Based on Lyapunov stability theory and new integral bounding technique, finite-time stability of large-scale systems with interval time-varying delays in interconnection is derived. The finite-time stability criteria are delays-dependent and are given in terms of linear matrix inequalities which can be solved by various available algorithms. Numerical examples are given to illustrate effectiveness of the proposed method.

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...

How do the multiple large-scale climate oscillations trigger extreme precipitation?

Science.gov (United States)

Shi, Pengfei; Yang, Tao; Xu, Chong-Yu; Yong, Bin; Shao, Quanxi; Li, Zhenya; Wang, Xiaoyan; Zhou, Xudong; Li, Shu

2017-10-01

Identifying the links between variations in large-scale climate patterns and precipitation is of tremendous assistance in characterizing surplus or deficit of precipitation, which is especially important for evaluation of local water resources and ecosystems in semi-humid and semi-arid regions. Restricted by current limited knowledge on underlying mechanisms, statistical correlation methods are often used rather than physical based model to characterize the connections. Nevertheless, available correlation methods are generally unable to reveal the interactions among a wide range of climate oscillations and associated effects on precipitation, especially on extreme precipitation. In this work, a probabilistic analysis approach by means of a state-of-the-art Copula-based joint probability distribution is developed to characterize the aggregated behaviors for large-scale climate patterns and their connections to precipitation. This method is employed to identify the complex connections between climate patterns (Atlantic Multidecadal Oscillation (AMO), El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO)) and seasonal precipitation over a typical semi-humid and semi-arid region, the Haihe River Basin in China. Results show that the interactions among multiple climate oscillations are non-uniform in most seasons and phases. Certain joint extreme phases can significantly trigger extreme precipitation (flood and drought) owing to the amplification effect among climate oscillations.

Large-scale structure observables in general relativity

International Nuclear Information System (INIS)

Jeong, Donghui; Schmidt, Fabian

2015-01-01

We review recent studies that rigorously define several key observables of the large-scale structure of the Universe in a general relativistic context. Specifically, we consider (i) redshift perturbation of cosmic clock events; (ii) distortion of cosmic rulers, including weak lensing shear and magnification; and (iii) observed number density of tracers of the large-scale structure. We provide covariant and gauge-invariant expressions of these observables. Our expressions are given for a linearly perturbed flat Friedmann–Robertson–Walker metric including scalar, vector, and tensor metric perturbations. While we restrict ourselves to linear order in perturbation theory, the approach can be straightforwardly generalized to higher order. (paper)

Large scale tracking of stem cells using sparse coding and coupled graphs

DEFF Research Database (Denmark)

Vestergaard, Jacob Schack; Dahl, Anders Lindbjerg; Holm, Peter

Stem cell tracking is an inherently large scale problem. The challenge is to identify and track hundreds or thousands of cells over a time period of several weeks. This requires robust methods that can leverage the knowledge of specialists on the field. The tracking pipeline presented here consists...

Output Control Technologies for a Large-scale PV System Considering Impacts on a Power Grid

Science.gov (United States)

Kuwayama, Akira

The mega-solar demonstration project named “Verification of Grid Stabilization with Large-scale PV Power Generation systems” had been completed in March 2011 at Wakkanai, the northernmost city of Japan. The major objectives of this project were to evaluate adverse impacts of large-scale PV power generation systems connected to the power grid and develop output control technologies with integrated battery storage system. This paper describes the outline and results of this project. These results show the effectiveness of battery storage system and also proposed output control methods for a large-scale PV system to ensure stable operation of power grids. NEDO, New Energy and Industrial Technology Development Organization of Japan conducted this project and HEPCO, Hokkaido Electric Power Co., Inc managed the overall project.

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)

A semiparametric graphical modelling approach for large-scale equity selection.

Science.gov (United States)

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.

Nearly incompressible fluids: Hydrodynamics and large scale inhomogeneity

International Nuclear Information System (INIS)

Hunana, P.; Zank, G. P.; Shaikh, D.

2006-01-01

A system of hydrodynamic equations in the presence of large-scale inhomogeneities for a high plasma beta solar wind is derived. The theory is derived under the assumption of low turbulent Mach number and is developed for the flows where the usual incompressible description is not satisfactory and a full compressible treatment is too complex for any analytical studies. When the effects of compressibility are incorporated only weakly, a new description, referred to as 'nearly incompressible hydrodynamics', is obtained. The nearly incompressible theory, was originally applied to homogeneous flows. However, large-scale gradients in density, pressure, temperature, etc., are typical in the solar wind and it was unclear how inhomogeneities would affect the usual incompressible and nearly incompressible descriptions. In the homogeneous case, the lowest order expansion of the fully compressible equations leads to the usual incompressible equations, followed at higher orders by the nearly incompressible equations, as introduced by Zank and Matthaeus. With this work we show that the inclusion of large-scale inhomogeneities (in this case time-independent and radially symmetric background solar wind) modifies the leading-order incompressible description of solar wind flow. We find, for example, that the divergence of velocity fluctuations is nonsolenoidal and that density fluctuations can be described to leading order as a passive scalar. Locally (for small lengthscales), this system of equations converges to the usual incompressible equations and we therefore use the term 'locally incompressible' to describe the equations. This term should be distinguished from the term 'nearly incompressible', which is reserved for higher-order corrections. Furthermore, we find that density fluctuations scale with Mach number linearly, in contrast to the original homogeneous nearly incompressible theory, in which density fluctuations scale with the square of Mach number. Inhomogeneous nearly

Large-scale synthesis of bismuth sulfide nanorods by microwave irradiation

International Nuclear Information System (INIS)

Wu Jiliang; Qin Fan; Cheng Gang; Li Hui; Zhang Jiuhong; Xie Yaoping; Yang Haijian; Lu Zhong; Yu Xianglin; Chen Rong

2011-01-01

Graphical abstract: Display Omitted Research highlights: → Large-scale Bi 2 S 3 nanorods have been prepared by microwave irradiation methods. → CTAB and β-CD are beneficial to the formation of Bi 2 S 3 nanorods. → DMF, EG and DEG were favorable solvents. → Bismuth and sulfur precursors influenced the size and morphology. → A proposed formation mechanism of Bi 2 S 3 nanorods was summarized. - Abstract: Bismuth sulfide (Bi 2 S 3 ) has attracted considerable interest due to its potential applications in thermoelectric and electronic devices, optoelectronic devices, and biomedicine. In this study, large-scale highly crystalline Bi 2 S 3 nanorods were successfully prepared from bismuth citrate and thiourea (Tu) by microwave irradiation methods. The products were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM, HRTEM) and selected area electron diffraction (SAED). The influences of reaction time, surfactants, solvents, and precursors on the formation of Bi 2 S 3 nanorods were discussed. The microwave irradiation method reduced reaction time by at least 80% in the synthesis of Bi 2 S 3 nanorods compared with the refluxing method. Cetyltrimethylammonium bromide (CTAB) and β-cyclodextrin (β-CD) were found to be beneficial to the formation of Bi 2 S 3 nanorods. N,N-dimethylformamide, ethylene glycol, and diethylene glycol were the favorable solvents in the fabrication of these nanorods. It was found that different bismuth and sulfur precursors influenced the sizes and morphologies of the Bi 2 S 3 nanorods. The proposed growth mechanism of Bi 2 S 3 nanorods was also discussed.

Distributed system for large-scale remote research

International Nuclear Information System (INIS)

Ueshima, Yutaka

2002-01-01

In advanced photon research, large-scale simulations and high-resolution observations are powerfull tools. In numerical and real experiments, the real-time visualization and steering system is considered as a hopeful method of data analysis. This approach is valid in the typical analysis at one time or low cost experiment and simulation. In research of an unknown problem, it is necessary that the output data be analyzed many times because conclusive analysis is difficult at one time. Consequently, output data should be filed to refer and analyze at any time. To support research, we need the automatic functions, transporting data files from data generator to data storage, analyzing data, tracking history of data handling, and so on. The supporting system will be a functionally distributed system. (author)

Performance Health Monitoring of Large-Scale Systems

Energy Technology Data Exchange (ETDEWEB)

Rajamony, Ram [IBM Research, Austin, TX (United States)

2014-11-20

This report details the progress made on the ASCR funded project Performance Health Monitoring for Large Scale Systems. A large-­scale application may not achieve its full performance potential due to degraded performance of even a single subsystem. Detecting performance faults, isolating them, and taking remedial action is critical for the scale of systems on the horizon. PHM aims to develop techniques and tools that can be used to identify and mitigate such performance problems. We accomplish this through two main aspects. The PHM framework encompasses diagnostics, system monitoring, fault isolation, and performance evaluation capabilities that indicates when a performance fault has been detected, either due to an anomaly present in the system itself or due to contention for shared resources between concurrently executing jobs. Software components called the PHM Control system then build upon the capabilities provided by the PHM framework to mitigate degradation caused by performance problems.

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

Learning from large scale neural simulations

DEFF Research Database (Denmark)

Serban, Maria

2017-01-01

Large-scale neural simulations have the marks of a distinct methodology which can be fruitfully deployed to advance scientific understanding of the human brain. Computer simulation studies can be used to produce surrogate observational data for better conceptual models and new how...

Phenomenology of two-dimensional stably stratified turbulence under large-scale forcing

KAUST Repository

Kumar, Abhishek; Verma, Mahendra K.; Sukhatme, Jai

2017-01-01

In this paper, we characterise the scaling of energy spectra, and the interscale transfer of energy and enstrophy, for strongly, moderately and weakly stably stratified two-dimensional (2D) turbulence, restricted in a vertical plane, under large-scale random forcing. In the strongly stratified case, a large-scale vertically sheared horizontal flow (VSHF) coexists with small scale turbulence. The VSHF consists of internal gravity waves and the turbulent flow has a kinetic energy (KE) spectrum that follows an approximate k−3 scaling with zero KE flux and a robust positive enstrophy flux. The spectrum of the turbulent potential energy (PE) also approximately follows a k−3 power-law and its flux is directed to small scales. For moderate stratification, there is no VSHF and the KE of the turbulent flow exhibits Bolgiano–Obukhov scaling that transitions from a shallow k−11/5 form at large scales, to a steeper approximate k−3 scaling at small scales. The entire range of scales shows a strong forward enstrophy flux, and interestingly, large (small) scales show an inverse (forward) KE flux. The PE flux in this regime is directed to small scales, and the PE spectrum is characterised by an approximate k−1.64 scaling. Finally, for weak stratification, KE is transferred upscale and its spectrum closely follows a k−2.5 scaling, while PE exhibits a forward transfer and its spectrum shows an approximate k−1.6 power-law. For all stratification strengths, the total energy always flows from large to small scales and almost all the spectral indicies are well explained by accounting for the scale-dependent nature of the corresponding flux.

Phenomenology of two-dimensional stably stratified turbulence under large-scale forcing

KAUST Repository

Kumar, Abhishek

2017-01-11

In this paper, we characterise the scaling of energy spectra, and the interscale transfer of energy and enstrophy, for strongly, moderately and weakly stably stratified two-dimensional (2D) turbulence, restricted in a vertical plane, under large-scale random forcing. In the strongly stratified case, a large-scale vertically sheared horizontal flow (VSHF) coexists with small scale turbulence. The VSHF consists of internal gravity waves and the turbulent flow has a kinetic energy (KE) spectrum that follows an approximate k−3 scaling with zero KE flux and a robust positive enstrophy flux. The spectrum of the turbulent potential energy (PE) also approximately follows a k−3 power-law and its flux is directed to small scales. For moderate stratification, there is no VSHF and the KE of the turbulent flow exhibits Bolgiano–Obukhov scaling that transitions from a shallow k−11/5 form at large scales, to a steeper approximate k−3 scaling at small scales. The entire range of scales shows a strong forward enstrophy flux, and interestingly, large (small) scales show an inverse (forward) KE flux. The PE flux in this regime is directed to small scales, and the PE spectrum is characterised by an approximate k−1.64 scaling. Finally, for weak stratification, KE is transferred upscale and its spectrum closely follows a k−2.5 scaling, while PE exhibits a forward transfer and its spectrum shows an approximate k−1.6 power-law. For all stratification strengths, the total energy always flows from large to small scales and almost all the spectral indicies are well explained by accounting for the scale-dependent nature of the corresponding flux.

Large-scale straw supplies to existing coal-fired power stations

International Nuclear Information System (INIS)

Gylling, M.; Parsby, M.; Thellesen, H.Z.; Keller, P.

1992-08-01

It is considered that large-scale supply of straw to power stations and decentral cogeneration plants could open up new economical systems and methods of organization of straw supply in Denmark. This thesis is elucidated and involved constraints are pointed out. The aim is to describe to what extent large-scale straw supply is interesting with regard to monetary savings and available resources. Analyses of models, systems and techniques described in a foregoing project are carried out. It is reckoned that the annual total amount of surplus straw in Denmark is 3.6 million tons. At present, use of straw which is not agricultural is limited to district heating plants with an annual consumption of 2-12 thousand tons. A prerequisite for a significant increase in the use of straw is an annual consumption by power and cogeneration plants of more than 100.000 tons. All aspects of straw management are examined in detail, also in relation to two actual Danish coal-fired plants. The reliability of straw supply is considered. It is concluded that very significant resources of straw are available in Denmark but there remain a number of constraints. Price competitiveness must be considered in relation to other fuels. It is suggested that the use of corn harvests, with whole stems attached (handled as large bales or in the same way as sliced straw alone) as fuel, would result in significant monetary savings in transport and storage especially. An equal status for whole-harvested corn with other forms of biomass fuels, with following changes in taxes and subsidies could possibly reduce constraints on large scale straw fuel supply. (AB) (13 refs.)

Preparation of a large-scale and multi-layer molybdenum crystal and its characteristics

International Nuclear Information System (INIS)

Fujii, Tadayuki

1989-01-01

In the present work, the secondary recrystallization method was applied to obtain a large-scale and multi-layer crystal from a hot-rolled multi-laminated molybdenum sheet doped and stacked alternately with different amounts of dopant. It was found that the time and/or temperature at which secondary recrystallization commence from the multi- layer sheet is strongly dependent on the amounts of dopants. Therefore the potential nucleus of the secondary grain from layers with different amounts of dopant occurred first at the layer with a small amount of dopant and then grew into the layer with a large amount of dopant after an anneal at 1800 0 C-2000 0 C. Consequently a large -scale and multi-layer molybdenum crystal can easily be obtained. 12 refs., 9 figs., 2 tabs. (Author)

Hydraulic method of working large super-drift pillars

Energy Technology Data Exchange (ETDEWEB)

Rad' ko, B.V.; Syroezhkin, P.V.; Durov, V.S.

1987-03-01

Describes the method of hydraulic coal extraction introduced in the Pioneer mine belonging to the Dobropol'eugol' coal association. This method was found to reduce the number of collection and ventilation roadways needed significantly, increase their stability, reduce coal loss and increase safety, particularly when mining pillars up to 80 m high. Large scale diagram of hydraulic mining layout shows: ventilation gate, hydraulic monitors, mine roadway, cross-cut, and collection roadways. A table shows pillar dimensions and depth and economic savings for different seams in the mine.

Exploring the large-scale structure of Taylor–Couette turbulence through Large-Eddy Simulations

Science.gov (United States)

Ostilla-Mónico, Rodolfo; Zhu, Xiaojue; Verzicco, Roberto

2018-04-01

Large eddy simulations (LES) of Taylor-Couette (TC) flow, the flow between two co-axial and independently rotating cylinders are performed in an attempt to explore the large-scale axially-pinned structures seen in experiments and simulations. Both static and dynamic LES models are used. The Reynolds number is kept fixed at Re = 3.4 · 104, and the radius ratio η = ri /ro is set to η = 0.909, limiting the effects of curvature and resulting in frictional Reynolds numbers of around Re τ ≈ 500. Four rotation ratios from Rot = ‑0.0909 to Rot = 0.3 are simulated. First, the LES of TC is benchmarked for different rotation ratios. Both the Smagorinsky model with a constant of cs = 0.1 and the dynamic model are found to produce reasonable results for no mean rotation and cyclonic rotation, but deviations increase for increasing rotation. This is attributed to the increasing anisotropic character of the fluctuations. Second, “over-damped” LES, i.e. LES with a large Smagorinsky constant is performed and is shown to reproduce some features of the large-scale structures, even when the near-wall region is not adequately modeled. This shows the potential for using over-damped LES for fast explorations of the parameter space where large-scale structures are found.

Large-scale preparation of hollow graphitic carbon nanospheres

International Nuclear Information System (INIS)

Feng, Jun; Li, Fu; Bai, Yu-Jun; Han, Fu-Dong; Qi, Yong-Xin; Lun, Ning; Lu, Xi-Feng

2013-01-01

Hollow graphitic carbon nanospheres (HGCNSs) were synthesized on large scale by a simple reaction between glucose and Mg at 550 °C in an autoclave. Characterization by X-ray diffraction, Raman spectroscopy and transmission electron microscopy demonstrates the formation of HGCNSs with an average diameter of 10 nm or so and a wall thickness of a few graphenes. The HGCNSs exhibit a reversible capacity of 391 mAh g −1 after 60 cycles when used as anode materials for Li-ion batteries. -- Graphical abstract: Hollow graphitic carbon nanospheres could be prepared on large scale by the simple reaction between glucose and Mg at 550 °C, which exhibit superior electrochemical performance to graphite. Highlights: ► Hollow graphitic carbon nanospheres (HGCNSs) were prepared on large scale at 550 °C ► The preparation is simple, effective and eco-friendly. ► The in situ yielded MgO nanocrystals promote the graphitization. ► The HGCNSs exhibit superior electrochemical performance to graphite.

First Mile Challenges for Large-Scale IoT

KAUST Repository

Bader, Ahmed

2017-03-16

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, cellular networks are indeed a strong first mile candidate to accommodate the data tsunami to be generated by the IoT. However, IoT devices are required in the cellular paradigm to undergo random access procedures as a precursor to resource allocation. Such procedures impose a major bottleneck that hinders cellular networks\\' ability to support large-scale IoT. In this article, we shed light on the random access dilemma and present a case study based on experimental data as well as system-level simulations. Accordingly, a case is built for the latent need to revisit random access procedures. A call for action is motivated by listing a few potential remedies and recommendations.

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)

Thermal power generation projects ``Large Scale Solar Heating``; EU-Thermie-Projekte ``Large Scale Solar Heating``

Energy Technology Data Exchange (ETDEWEB)

Kuebler, R.; Fisch, M.N. [Steinbeis-Transferzentrum Energie-, Gebaeude- und Solartechnik, Stuttgart (Germany)

1998-12-31

The aim of this project is the preparation of the ``Large-Scale Solar Heating`` programme for an Europe-wide development of subject technology. The following demonstration programme was judged well by the experts but was not immediately (1996) accepted for financial subsidies. In November 1997 the EU-commission provided 1,5 million ECU which allowed the realisation of an updated project proposal. By mid 1997 a small project was approved, that had been requested under the lead of Chalmes Industriteteknik (CIT) in Sweden and is mainly carried out for the transfer of technology. (orig.) [Deutsch] Ziel dieses Vorhabens ist die Vorbereitung eines Schwerpunktprogramms `Large Scale Solar Heating`, mit dem die Technologie europaweit weiterentwickelt werden sollte. Das daraus entwickelte Demonstrationsprogramm wurde von den Gutachtern positiv bewertet, konnte jedoch nicht auf Anhieb (1996) in die Foerderung aufgenommen werden. Im November 1997 wurden von der EU-Kommission dann kurzfristig noch 1,5 Mio ECU an Foerderung bewilligt, mit denen ein aktualisierter Projektvorschlag realisiert werden kann. Bereits Mitte 1997 wurde ein kleineres Vorhaben bewilligt, das unter Federfuehrung von Chalmers Industriteknik (CIT) in Schweden beantragt worden war und das vor allem dem Technologietransfer dient. (orig.)

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.

SIMON: Remote collaboration system based on large scale simulation

International Nuclear Information System (INIS)

Sugawara, Akihiro; Kishimoto, Yasuaki

2003-01-01

Development of SIMON (SImulation MONitoring) system is described. SIMON aims to investigate many physical phenomena of tokamak type nuclear fusion plasma by simulation and to exchange information and to carry out joint researches with scientists in the world using internet. The characteristics of SIMON are followings; 1) decrease load of simulation by trigger sending method, 2) visualization of simulation results and hierarchical structure of analysis, 3) decrease of number of license by using command line when software is used, 4) improvement of support for using network of simulation data output by use of HTML (Hyper Text Markup Language), 5) avoidance of complex built-in work in client part and 6) small-sized and portable software. The visualization method of large scale simulation, remote collaboration system by HTML, trigger sending method, hierarchical analytical method, introduction into three-dimensional electromagnetic transportation code and technologies of SIMON system are explained. (S.Y.)

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.

The European Union Solidarity Fund: An Important Tool in the Recovery After Large-Scale Natural Disasters

Directory of Open Access Journals (Sweden)

Maria IONCICĂ

2016-03-01

Full Text Available This paper analyses the situation of the European Union Solidarity Fund, as an important tool in the recovery after large-scale natural disasters. In the last millennium, the European Union countries have faced climate change, which lead to events with disastrous consequences. There are several ex-post financial ways to respond to the challenges posed by large-scale natural disasters, among which EU Solidarity Fund, government funds, budget reallocation, donor assistance, domestic and/or external credit. The EU Solidarity Fund was created in 2002 after the massive floods from the Central Europe as the expression of the solidarity of EU countries. Romania has received financial assistance from the EU Solidarity Fund after the occurrence of major natural disasters, regional and neighbouring country disasters. The assessment of large-scale natural disasters in EU is very important and in order to analyse if there is a concentration of large-scale natural disasters in EU we used the Gini coefficient. In the paper, the method of the statistical analysis and the correlation between several indicators were used to study the financial impacts of large-scale natural disasters in Europe, and especially in Romania.

Protein homology model refinement by large-scale energy optimization.

Science.gov (United States)

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

Data management strategies for multinational large-scale systems biology projects.

Science.gov (United States)

Wruck, Wasco; Peuker, Martin; Regenbrecht, Christian R A

2014-01-01

Good accessibility of publicly funded research data is essential to secure an open scientific system and eventually becomes mandatory [Wellcome Trust will Penalise Scientists Who Don't Embrace Open Access. The Guardian 2012]. By the use of high-throughput methods in many research areas from physics to systems biology, large data collections are increasingly important as raw material for research. Here, we present strategies worked out by international and national institutions targeting open access to publicly funded research data via incentives or obligations to share data. Funding organizations such as the British Wellcome Trust therefore have developed data sharing policies and request commitment to data management and sharing in grant applications. Increased citation rates are a profound argument for sharing publication data. Pre-publication sharing might be rewarded by a data citation credit system via digital object identifiers (DOIs) which have initially been in use for data objects. Besides policies and incentives, good practice in data management is indispensable. However, appropriate systems for data management of large-scale projects for example in systems biology are hard to find. Here, we give an overview of a selection of open-source data management systems proved to be employed successfully in large-scale projects.

Bayesian hierarchical model for large-scale covariance matrix estimation.

Science.gov (United States)

Zhu, Dongxiao; Hero, Alfred O

2007-12-01

Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.

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.

Sodium-immersed self-cooled electromagnetic pump design and development of a large-scale coil for high temperature

International Nuclear Information System (INIS)

Oto, Akihiro; Naohara, Nobuyuki; Ishida, Masayoshi; Katsuki, Kenji; Kumazawa, Ryouji

1995-01-01

A sodium-immersed, self-cooled electromagnetic (EM) pump was recently studied as a prospective innovative technology to simplify a fast breeder reactor plant system. The EM pump for a primary pump, a pump type, was designed, and the structural concept and the system performance were clarified. For the flow control method, a constant voltage/frequency method was preferable from the point of view of pump performance and efficiency. The insulation life was tested on a large-scale coil at high temperature as part of the development of a large-capacity EM pump. Mechanical and electrical damage were not observed, and the insulation performance was quite good. The insulation system could also be applied to large-scale coils

Creating Large Scale Database Servers

International Nuclear Information System (INIS)

Becla, Jacek

2001-01-01

The BaBar experiment at the Stanford Linear Accelerator Center (SLAC) is designed to perform a high precision investigation of the decays of the B-meson produced from electron-positron interactions. The experiment, started in May 1999, will generate approximately 300TB/year of data for 10 years. All of the data will reside in Objectivity databases accessible via the Advanced Multi-threaded Server (AMS). To date, over 70TB of data have been placed in Objectivity/DB, making it one of the largest databases in the world. Providing access to such a large quantity of data through a database server is a daunting task. A full-scale testbed environment had to be developed to tune various software parameters and a fundamental change had to occur in the AMS architecture to allow it to scale past several hundred terabytes of data. Additionally, several protocol extensions had to be implemented to provide practical access to large quantities of data. This paper will describe the design of the database and the changes that we needed to make in the AMS for scalability reasons and how the lessons we learned would be applicable to virtually any kind of database server seeking to operate in the Petabyte region

Creating Large Scale Database Servers

Energy Technology Data Exchange (ETDEWEB)

Becla, Jacek

2001-12-14

The BaBar experiment at the Stanford Linear Accelerator Center (SLAC) is designed to perform a high precision investigation of the decays of the B-meson produced from electron-positron interactions. The experiment, started in May 1999, will generate approximately 300TB/year of data for 10 years. All of the data will reside in Objectivity databases accessible via the Advanced Multi-threaded Server (AMS). To date, over 70TB of data have been placed in Objectivity/DB, making it one of the largest databases in the world. Providing access to such a large quantity of data through a database server is a daunting task. A full-scale testbed environment had to be developed to tune various software parameters and a fundamental change had to occur in the AMS architecture to allow it to scale past several hundred terabytes of data. Additionally, several protocol extensions had to be implemented to provide practical access to large quantities of data. This paper will describe the design of the database and the changes that we needed to make in the AMS for scalability reasons and how the lessons we learned would be applicable to virtually any kind of database server seeking to operate in the Petabyte region.

Large-scale pool fires

Directory of Open Access Journals (Sweden)

Steinhaus Thomas

2007-01-01

Full Text Available A review of research into the burning behavior of large pool fires and fuel spill fires is presented. The features which distinguish such fires from smaller pool fires are mainly associated with the fire dynamics at low source Froude numbers and the radiative interaction with the fire source. In hydrocarbon fires, higher soot levels at increased diameters result in radiation blockage effects around the perimeter of large fire plumes; this yields lower emissive powers and a drastic reduction in the radiative loss fraction; whilst there are simplifying factors with these phenomena, arising from the fact that soot yield can saturate, there are other complications deriving from the intermittency of the behavior, with luminous regions of efficient combustion appearing randomly in the outer surface of the fire according the turbulent fluctuations in the fire plume. Knowledge of the fluid flow instabilities, which lead to the formation of large eddies, is also key to understanding the behavior of large-scale fires. Here modeling tools can be effectively exploited in order to investigate the fluid flow phenomena, including RANS- and LES-based computational fluid dynamics codes. The latter are well-suited to representation of the turbulent motions, but a number of challenges remain with their practical application. Massively-parallel computational resources are likely to be necessary in order to be able to adequately address the complex coupled phenomena to the level of detail that is necessary.

Development of a vacuum leak test method for large-scale superconducting magnet test facilities

International Nuclear Information System (INIS)

Kawano, Katsumi; Hamada, Kazuya; Okuno, Kiyoshi; Kato, Takashi

2006-01-01

Japan Atomic Energy Agency (JAEA) has developed leak detection technology for liquid helium temperature experiments in large-scale superconducting magnet test facilities. In JAEA, a cryosorption pump that uses an absorbent cooled by liquid nitrogen with a conventional helium leak detector, is used to detect helium gas that is leaking from pressurized welded joints of pipes and valves in a vacuum chamber. The cryosorption pump plays the role of decreasing aerial components, such as water, nitrogen and oxygen, to increase the sensitivity of helium leak detection. The established detection sensitivity for helium leak testing is 10 -10 to 10 -9 Pam 3 /s. A total of 850 welded and mechanical joints inside the cryogenic test facility for the ITER Central Solenoid Model Coil (CSMC) experiments have been tested. In the test facility, 73 units of glass fiber-reinforced plastic (GFRP) insulation break are used. The amount of helium permeation through the GFRP was recorded during helium leak testing. To distinguish helium leaks from insulation-break permeation, the helium permeation characteristic of the GFRP part was measured as a function of the time of helium charging. Helium permeation was absorbed at 6 h after helium charging, and the detected permeation is around 10 -7 Pam 3 /s. Using the helium leak test method developed, CSMC experiments have been successfully completed. (author)

Large Scale Survey Data in Career Development Research

Science.gov (United States)

Diemer, Matthew A.

2008-01-01

Large scale survey datasets have been underutilized but offer numerous advantages for career development scholars, as they contain numerous career development constructs with large and diverse samples that are followed longitudinally. Constructs such as work salience, vocational expectations, educational expectations, work satisfaction, and…

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.

Similitude and scaling of large structural elements: Case study

Directory of Open Access Journals (Sweden)

M. Shehadeh

2015-06-01

Full Text Available Scaled down models are widely used for experimental investigations of large structures due to the limitation in the capacities of testing facilities along with the expenses of the experimentation. The modeling accuracy depends upon the model material properties, fabrication accuracy and loading techniques. In the present work the Buckingham π theorem is used to develop the relations (i.e. geometry, loading and properties between the model and a large structural element as that is present in the huge existing petroleum oil drilling rigs. The model is to be designed, loaded and treated according to a set of similitude requirements that relate the model to the large structural element. Three independent scale factors which represent three fundamental dimensions, namely mass, length and time need to be selected for designing the scaled down model. Numerical prediction of the stress distribution within the model and its elastic deformation under steady loading is to be made. The results are compared with those obtained from the full scale structure numerical computations. The effect of scaled down model size and material on the accuracy of the modeling technique is thoroughly examined.

Large-scale preparation of hollow graphitic carbon nanospheres

Energy Technology Data Exchange (ETDEWEB)

Feng, Jun; Li, Fu [Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, Ministry of Education, Shandong University, Jinan 250061 (China); Bai, Yu-Jun, E-mail: byj97@126.com [Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, Ministry of Education, Shandong University, Jinan 250061 (China); State Key laboratory of Crystal Materials, Shandong University, Jinan 250100 (China); Han, Fu-Dong; Qi, Yong-Xin; Lun, Ning [Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, Ministry of Education, Shandong University, Jinan 250061 (China); Lu, Xi-Feng [Lunan Institute of Coal Chemical Engineering, Jining 272000 (China)

2013-01-15

Hollow graphitic carbon nanospheres (HGCNSs) were synthesized on large scale by a simple reaction between glucose and Mg at 550 Degree-Sign C in an autoclave. Characterization by X-ray diffraction, Raman spectroscopy and transmission electron microscopy demonstrates the formation of HGCNSs with an average diameter of 10 nm or so and a wall thickness of a few graphenes. The HGCNSs exhibit a reversible capacity of 391 mAh g{sup -1} after 60 cycles when used as anode materials for Li-ion batteries. -- Graphical abstract: Hollow graphitic carbon nanospheres could be prepared on large scale by the simple reaction between glucose and Mg at 550 Degree-Sign C, which exhibit superior electrochemical performance to graphite. Highlights: Black-Right-Pointing-Pointer Hollow graphitic carbon nanospheres (HGCNSs) were prepared on large scale at 550 Degree-Sign C Black-Right-Pointing-Pointer The preparation is simple, effective and eco-friendly. Black-Right-Pointing-Pointer The in situ yielded MgO nanocrystals promote the graphitization. Black-Right-Pointing-Pointer The HGCNSs exhibit superior electrochemical performance to graphite.

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

Optical interconnect for large-scale systems

Science.gov (United States)

Dress, William

2013-02-01

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

Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems

Science.gov (United States)

Koch, Patrick Nathan

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.

Large-scale chromosome folding versus genomic DNA sequences: A discrete double Fourier transform technique.

Science.gov (United States)

Chechetkin, V R; Lobzin, V V

2017-08-07

Using state-of-the-art techniques combining imaging methods and high-throughput genomic mapping tools leaded to the significant progress in detailing chromosome architecture of various organisms. However, a gap still remains between the rapidly growing structural data on the chromosome folding and the large-scale genome organization. Could a part of information on the chromosome folding be obtained directly from underlying genomic DNA sequences abundantly stored in the databanks? To answer this question, we developed an original discrete double Fourier transform (DDFT). DDFT serves for the detection of large-scale genome regularities associated with domains/units at the different levels of hierarchical chromosome folding. The method is versatile and can be applied to both genomic DNA sequences and corresponding physico-chemical parameters such as base-pairing free energy. The latter characteristic is closely related to the replication and transcription and can also be used for the assessment of temperature or supercoiling effects on the chromosome folding. We tested the method on the genome of E. coli K-12 and found good correspondence with the annotated domains/units established experimentally. As a brief illustration of further abilities of DDFT, the study of large-scale genome organization for bacteriophage PHIX174 and bacterium Caulobacter crescentus was also added. The combined experimental, modeling, and bioinformatic DDFT analysis should yield more complete knowledge on the chromosome architecture and genome organization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Complex modular structure of large-scale brain networks

Science.gov (United States)

Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.

2009-06-01

Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

Large-scale Ising-machines composed of magnetic neurons

Science.gov (United States)

Mizushima, Koichi; Goto, Hayato; Sato, Rie

2017-10-01

We propose Ising-machines composed of magnetic neurons, that is, magnetic bits in a recording track. In large-scale machines, the sizes of both neurons and synapses need to be reduced, and neat and smart connections among neurons are also required to achieve all-to-all connectivity among them. These requirements can be fulfilled by adopting magnetic recording technologies such as race-track memories and skyrmion tracks because the area of a magnetic bit is almost two orders of magnitude smaller than that of static random access memory, which has normally been used as a semiconductor neuron, and the smart connections among neurons are realized by using the read and write methods of these technologies.

REIONIZATION ON LARGE SCALES. I. A PARAMETRIC MODEL CONSTRUCTED FROM RADIATION-HYDRODYNAMIC SIMULATIONS

International Nuclear Information System (INIS)

Battaglia, N.; Trac, H.; Cen, R.; Loeb, A.

2013-01-01

We present a new method for modeling inhomogeneous cosmic reionization on large scales. Utilizing high-resolution radiation-hydrodynamic simulations with 2048 3 dark matter particles, 2048 3 gas cells, and 17 billion adaptive rays in a L = 100 Mpc h –1 box, we show that the density and reionization redshift fields are highly correlated on large scales (∼> 1 Mpc h –1 ). This correlation can be statistically represented by a scale-dependent linear bias. We construct a parametric function for the bias, which is then used to filter any large-scale density field to derive the corresponding spatially varying reionization redshift field. The parametric model has three free parameters that can be reduced to one free parameter when we fit the two bias parameters to simulation results. We can differentiate degenerate combinations of the bias parameters by combining results for the global ionization histories and correlation length between ionized regions. Unlike previous semi-analytic models, the evolution of the reionization redshift field in our model is directly compared cell by cell against simulations and performs well in all tests. Our model maps the high-resolution, intermediate-volume radiation-hydrodynamic simulations onto lower-resolution, larger-volume N-body simulations (∼> 2 Gpc h –1 ) in order to make mock observations and theoretical predictions

[A large-scale accident in Alpine terrain].

Science.gov (United States)

Wildner, M; Paal, P

2015-02-01

Due to the geographical conditions, large-scale accidents amounting to mass casualty incidents (MCI) in Alpine terrain regularly present rescue teams with huge challenges. Using an example incident, specific conditions and typical problems associated with such a situation are presented. The first rescue team members to arrive have the elementary tasks of qualified triage and communication to the control room, which is required to dispatch the necessary additional support. Only with a clear "concept", to which all have to adhere, can the subsequent chaos phase be limited. In this respect, a time factor confounded by adverse weather conditions or darkness represents enormous pressure. Additional hazards are frostbite and hypothermia. If priorities can be established in terms of urgency, then treatment and procedure algorithms have proven successful. For evacuation of causalities, a helicopter should be strived for. Due to the low density of hospitals in Alpine regions, it is often necessary to distribute the patients over a wide area. Rescue operations in Alpine terrain have to be performed according to the particular conditions and require rescue teams to have specific knowledge and expertise. The possibility of a large-scale accident should be considered when planning events. With respect to optimization of rescue measures, regular training and exercises are rational, as is the analysis of previous large-scale Alpine accidents.

Knowledge Guided Disambiguation for Large-Scale Scene Classification With Multi-Resolution CNNs

Science.gov (United States)

Wang, Limin; Guo, Sheng; Huang, Weilin; Xiong, Yuanjun; Qiao, Yu

2017-04-01

Convolutional Neural Networks (CNNs) have made remarkable progress on scene recognition, partially due to these recent large-scale scene datasets, such as the Places and Places2. Scene categories are often defined by multi-level information, including local objects, global layout, and background environment, thus leading to large intra-class variations. In addition, with the increasing number of scene categories, label ambiguity has become another crucial issue in large-scale classification. This paper focuses on large-scale scene recognition and makes two major contributions to tackle these issues. First, we propose a multi-resolution CNN architecture that captures visual content and structure at multiple levels. The multi-resolution CNNs are composed of coarse resolution CNNs and fine resolution CNNs, which are complementary to each other. Second, we design two knowledge guided disambiguation techniques to deal with the problem of label ambiguity. (i) We exploit the knowledge from the confusion matrix computed on validation data to merge ambiguous classes into a super category. (ii) We utilize the knowledge of extra networks to produce a soft label for each image. Then the super categories or soft labels are employed to guide CNN training on the Places2. We conduct extensive experiments on three large-scale image datasets (ImageNet, Places, and Places2), demonstrating the effectiveness of our approach. Furthermore, our method takes part in two major scene recognition challenges, and achieves the second place at the Places2 challenge in ILSVRC 2015, and the first place at the LSUN challenge in CVPR 2016. Finally, we directly test the learned representations on other scene benchmarks, and obtain the new state-of-the-art results on the MIT Indoor67 (86.7\\%) and SUN397 (72.0\\%). We release the code and models at~\\url{https://github.com/wanglimin/MRCNN-Scene-Recognition}.

Hierarchical Cantor set in the large scale structure with torus geometry

Energy Technology Data Exchange (ETDEWEB)

Murdzek, R. [Physics Department, ' Al. I. Cuza' University, Blvd. Carol I, Nr. 11, Iassy 700506 (Romania)], E-mail: rmurdzek@yahoo.com

2008-12-15

The formation of large scale structures is considered within a model with string on toroidal space-time. Firstly, the space-time geometry is presented. In this geometry, the Universe is represented by a string describing a torus surface. Thereafter, the large scale structure of the Universe is derived from the string oscillations. The results are in agreement with the cellular structure of the large scale distribution and with the theory of a Cantorian space-time.

Analysis of Utilization of Fecal Resources in Large-scale Livestock and Poultry Breeding in China

Directory of Open Access Journals (Sweden)

XUAN Meng

2018-02-01

Full Text Available The purpose of this paper is to develop a systematic investigation for the serious problems of livestock and poultry breeding in China and the technical demand of promoting the utilization of manure. Based on the status quo of large-scale livestock and poultry farming in typical areas in China, the work had been done beared on statistics and analysis of the modes and proportions of utilization of manure resources. Such a statistical method had been applied to the country -identified large -scale farm, which the total amount of pollutants reduction was in accordance with the "12th Five-Year Plan" standards. The results showed that there were some differences in the modes of resource utilization due to livestock and poultry manure at different scales and types:(1 Hogs, dairy cattle and beef cattle in total accounted for more than 75% of the agricultural manure storage;(2 Laying hens and broiler chickens accounted for about 65% of the total production of the organic manure produced by fecal production. It is demonstrated that the major modes of resource utilization of dung and urine were related to the natural characteristics, agricultural production methods, farming scale and economic development level in the area. It was concluded that the unreasonable planning, lacking of cleansing during breeding, false selection of manure utilizing modes were the major problems in China忆s large-scale livestock and poultry fecal resources utilization.

Experimental study on dynamic behavior of large scale foundation, 1

International Nuclear Information System (INIS)

Hanada, Kazufumi; Sawada, Yoshihiro; Esashi, Yasuyuki; Ueshima, Teruyuki; Nakamura, Hideharu

1983-01-01

The large-sized, high performance vibrating table in the Nuclear Power Engineering Test Center is installed on a large-scale concrete foundation of length 90.9 m, width 44.8 m and maximum thickness 21 m, weighing 150,000 tons. Through the experimental study on the behavior of the foundation, which is set on gravel ground, useful information should be obtained on the siting of a nuclear power plant on the Quaternary stratum ground. The objective of research is to grasp the vibration characteristics of the foundation during the vibration of the table to evaluate the interaction between the foundation and the ground, and to evaluate an analytical method for numerically simulating the vibration behavior. In the present study, the vibration behavior of the foundation was clarified by measurement, and in order to predict the vibration behavior, the semi-infinite theory of elasticity was applied. The accuracy of this analytical method was demonstrated by comparison with the measured results. (Mori, K.)

A simple method to fabricate an NIR detector by PbTe nanowires in a large scale

International Nuclear Information System (INIS)

Baghchesara, Mohammad Amin; Yousefi, Ramin; Cheraghizade, Mohsen; Jamali-Sheini, Farid; Saáedi, Abdolhossein; Mahmmoudian, M.R.

2016-01-01

Highlights: • PbTe nanowires were grown by tellurization of the Pb sheets for the first time. • It was observed a band gap value for the PbTe nanostructures in the NIR region. • NIR detector was fabricated in a large scale using a simple method. • Effect of Te concentration on morphology of PbTe nanostructures was investigated. - Abstract: A simple method was used to fabricate a near-infrared (NIR) detector using PbTe nanostructures. Samples were synthesized by tellurization of lead sheets in a tube furnace. PbTe nanostructures with wires and flakes shapes were grown on the lead sheets that were placed at 300 and 330 °C, respectively, while, PbTe nanoporous were grown at 360 and 390 °C. X-ray diffraction patterns and X-ray photoelectron spectra results indicated that, the PbTe phase was formed in all samples. UV–vis diffuse reflectance spectra measurements showed a band gap for the PbTe nanostructures in the near-infrared region of the electromagnetic spectrum. Actually, the results indicated that, the band gap values of the PbTe nanowires and nanoporous were 1.54 eV and 1.61 eV, respectively. Finally, the PbTe nanostructures were used as a simple photoresponse device under a red light source. The photoresponse results revealed, PbTe nanowires are promising for photoelectrical applications in the NIR region.

Research on fatigue behavior and residual stress of large-scale cruciform welding joint with groove

International Nuclear Information System (INIS)

Zhao, Xiaohui; Liu, Yu; Liu, Yong; Gao, Yuan

2014-01-01

Highlights: • The fatigue behavior of the large-scale cruciform welding joint with groove was studied. • The longitudinal residual stress of the large-scale cruciform welding joint was tested by contour method. • The fatigue fracture mechanism of the large-scale cruciform welding joint with groove was analyzed. - Abstract: Fatigue fracture behavior of the 30 mm thick Q460C-Z steel cruciform welded joint with groove was investigated. The fatigue test results indicated that fatigue strength of 30 mm thick Q460C-Z steel cruciform welded joint with groove can reach fatigue level of 80 MPa (FAT80). Fatigue crack source of the failure specimen initiated from weld toe. Meanwhile, the microcrack was also found in the fusion zones of the fatigue failure specimen, which was caused by weld quality and weld metal integrity resulting from the multi-pass welds. Two-dimensional map of the longitudinal residual stress of 30 mm thick Q460C-Z steel cruciform welded joint with groove was obtained by using the contour method. The stress nephogram of Two-dimensional map indicated that longitudinal residual stress in the welding center is the largest

Parallel Framework for Dimensionality Reduction of Large-Scale Datasets

Directory of Open Access Journals (Sweden)

Sai Kiranmayee Samudrala

2015-01-01

Full Text Available Dimensionality reduction refers to a set of mathematical techniques used to reduce complexity of the original high-dimensional data, while preserving its selected properties. Improvements in simulation strategies and experimental data collection methods are resulting in a deluge of heterogeneous and high-dimensional data, which often makes dimensionality reduction the only viable way to gain qualitative and quantitative understanding of the data. However, existing dimensionality reduction software often does not scale to datasets arising in real-life applications, which may consist of thousands of points with millions of dimensions. In this paper, we propose a parallel framework for dimensionality reduction of large-scale data. We identify key components underlying the spectral dimensionality reduction techniques, and propose their efficient parallel implementation. We show that the resulting framework can be used to process datasets consisting of millions of points when executed on a 16,000-core cluster, which is beyond the reach of currently available methods. To further demonstrate applicability of our framework we perform dimensionality reduction of 75,000 images representing morphology evolution during manufacturing of organic solar cells in order to identify how processing parameters affect morphology evolution.

Large-scale Motion of Solar Filaments

Indian Academy of Sciences (India)

tribpo

Large-scale Motion of Solar Filaments. Pavel Ambrož, Astronomical Institute of the Acad. Sci. of the Czech Republic, CZ-25165. Ondrejov, The Czech Republic. e-mail: pambroz@asu.cas.cz. Alfred Schroll, Kanzelhöehe Solar Observatory of the University of Graz, A-9521 Treffen,. Austria. e-mail: schroll@solobskh.ac.at.

Sensitivity analysis for large-scale problems

Science.gov (United States)

Noor, Ahmed K.; Whitworth, Sandra L.

1987-01-01

The development of efficient techniques for calculating sensitivity derivatives is studied. The objective is to present a computational procedure for calculating sensitivity derivatives as part of performing structural reanalysis for large-scale problems. The scope is limited to framed type structures. Both linear static analysis and free-vibration eigenvalue problems are considered.

Topology Optimization of Large Scale Stokes Flow Problems

DEFF Research Database (Denmark)

Aage, Niels; Poulsen, Thomas Harpsøe; Gersborg-Hansen, Allan

2008-01-01

This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs.......This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs....

A large-scale soil-structure interaction experiment: Design and construction

International Nuclear Information System (INIS)

Tang, H.T.; Tang, Y.K.; Stepp, J.C.; Wall, I.B.; Lin, E.; Cheng, S.C.; Lee, S.K.

1989-01-01

This paper describes the design and construction phase of the Large-Scale Soil-Structure Interaction Experiment project jointly sponsored by EPRI and Taipower. The project has two objectives: 1. to obtain an earthquake database which can be used to substantiate soil-structure interaction (SSI) models and analysis methods; and 2. to quantify nuclear power plant reactor containment and internal components seismic margin based on earthquake experience data. These objectives were accomplished by recording and analyzing data from two instrumented, scaled down, reinforced concrete containment structures during seismic events. The two model structures are sited in a high seismic region in Taiwan (SMART-1). A strong-motion seismic array network is located at the site. The containment models (1/4- and 1/12-scale) were constructed and instrumented specially for this experiment. Construction was completed and data recording began in September 1985. By November 1986, 18 strong motion earthquakes ranging from Richter magnitude 4.5 to 7.0 were recorded. (orig./HP)

The Cosmology Large Angular Scale Surveyor

Science.gov (United States)

Harrington, Kathleen; Marriage, Tobias; Ali, Aamir; Appel, John; Bennett, Charles; Boone, Fletcher; Brewer, Michael; Chan, Manwei; Chuss, David T.; Colazo, Felipe;

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

Science.gov (United States)

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Optimal Wind Energy Integration in Large-Scale Electric Grids

Science.gov (United States)

Albaijat, Mohammad H.

The major concern in electric grid operation is operating under the most economical and reliable fashion to ensure affordability and continuity of electricity supply. This dissertation investigates the effects of such challenges, which affect electric grid reliability and economic operations. These challenges are: 1. Congestion of transmission lines, 2. Transmission lines expansion, 3. Large-scale wind energy integration, and 4. Phaser Measurement Units (PMUs) optimal placement for highest electric grid observability. Performing congestion analysis aids in evaluating the required increase of transmission line capacity in electric grids. However, it is necessary to evaluate expansion of transmission line capacity on methods to ensure optimal electric grid operation. Therefore, the expansion of transmission line capacity must enable grid operators to provide low-cost electricity while maintaining reliable operation of the electric grid. Because congestion affects the reliability of delivering power and increases its cost, the congestion analysis in electric grid networks is an important subject. Consequently, next-generation electric grids require novel methodologies for studying and managing congestion in electric grids. We suggest a novel method of long-term congestion management in large-scale electric grids. Owing to the complication and size of transmission line systems and the competitive nature of current grid operation, it is important for electric grid operators to determine how many transmission lines capacity to add. Traditional questions requiring answers are "Where" to add, "How much of transmission line capacity" to add, and "Which voltage level". Because of electric grid deregulation, transmission lines expansion is more complicated as it is now open to investors, whose main interest is to generate revenue, to build new transmission lines. Adding a new transmission capacity will help the system to relieve the transmission system congestion, create

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality.

Science.gov (United States)

Li, Zhongyu; Butler, Erik; Li, Kang; Lu, Aidong; Ji, Shuiwang; Zhang, Shaoting

2018-02-12

Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i.e., stacked convolutional autoencoders (SCAEs). The deep features are subsequently fused with the hand-crafted features for more accurate representation. Considering the exhaustive search is usually very time-consuming in large-scale databases, we employ a novel binary coding method to compress feature vectors into short binary codes. Our framework is validated on a public data set including 58,000 neurons, showing promising retrieval precision and efficiency compared with state-of-the-art methods. In addition, we develop a novel neuron visualization program based on the techniques of augmented reality (AR), which can help users take a deep exploration of neuron morphologies in an interactive and immersive manner.

Large-scale assembly bias of dark matter halos

Energy Technology Data Exchange (ETDEWEB)

Lazeyras, Titouan; Musso, Marcello; Schmidt, Fabian, E-mail: titouan@mpa-garching.mpg.de, E-mail: mmusso@sas.upenn.edu, E-mail: fabians@mpa-garching.mpg.de [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching (Germany)

2017-03-01

We present precise measurements of the assembly bias of dark matter halos, i.e. the dependence of halo bias on other properties than the mass, using curved 'separate universe' N-body simulations which effectively incorporate an infinite-wavelength matter overdensity into the background density. This method measures the LIMD (local-in-matter-density) bias parameters b {sub n} in the large-scale limit. We focus on the dependence of the first two Eulerian biases b {sup E} {sup {sub 1}} and b {sup E} {sup {sub 2}} on four halo properties: the concentration, spin, mass accretion rate, and ellipticity. We quantitatively compare our results with previous works in which assembly bias was measured on fairly small scales. Despite this difference, our findings are in good agreement with previous results. We also look at the joint dependence of bias on two halo properties in addition to the mass. Finally, using the excursion set peaks model, we attempt to shed new insights on how assembly bias arises in this analytical model.

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

OpenAIRE

Qiang Liu; Yi Qin; Guodong Li

2018-01-01

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...

Managing Risk and Uncertainty in Large-Scale University Research Projects

Science.gov (United States)

Moore, Sharlissa; Shangraw, R. F., Jr.

2011-01-01

Both publicly and privately funded research projects managed by universities are growing in size and scope. Complex, large-scale projects (over $50 million) pose new management challenges and risks for universities. This paper explores the relationship between project success and a variety of factors in large-scale university projects. First, we…

Large Scale Skill in Regional Climate Modeling and the Lateral Boundary Condition Scheme

Science.gov (United States)

Veljović, K.; Rajković, B.; Mesinger, F.

2009-04-01

Several points are made concerning the somewhat controversial issue of regional climate modeling: should a regional climate model (RCM) be expected to maintain the large scale skill of the driver global model that is supplying its lateral boundary condition (LBC)? Given that this is normally desired, is it able to do so without help via the fairly popular large scale nudging? Specifically, without such nudging, will the RCM kinetic energy necessarily decrease with time compared to that of the driver model or analysis data as suggested by a study using the Regional Atmospheric Modeling System (RAMS)? Finally, can the lateral boundary condition scheme make a difference: is the almost universally used but somewhat costly relaxation scheme necessary for a desirable RCM performance? Experiments are made to explore these questions running the Eta model in two versions differing in the lateral boundary scheme used. One of these schemes is the traditional relaxation scheme, and the other the Eta model scheme in which information is used at the outermost boundary only, and not all variables are prescribed at the outflow boundary. Forecast lateral boundary conditions are used, and results are verified against the analyses. Thus, skill of the two RCM forecasts can be and is compared not only against each other but also against that of the driver global forecast. A novel verification method is used in the manner of customary precipitation verification in that forecast spatial wind speed distribution is verified against analyses by calculating bias adjusted equitable threat scores and bias scores for wind speeds greater than chosen wind speed thresholds. In this way, focusing on a high wind speed value in the upper troposphere, verification of large scale features we suggest can be done in a manner that may be more physically meaningful than verifications via spectral decomposition that are a standard RCM verification method. The results we have at this point are somewhat

A real-scale helical coil winding trial of the Large Helical Device

International Nuclear Information System (INIS)

Senba, T.; Yamamoto, T.; Tamaki, T.; Asano, K.; Suzuki, S.; Yamauchi, T.; Uchida, K.; Nakanishi, K.; Yamagiwa, T.; Suzuki, S.; Miyoshi, R.; Sasa, H.; Watanabe, S.; Tatemura, M.; Hatada, N.; Yamaguchi, S.; Imagawa, S.; Yanagi, N.; Satow, T.; Yamamoto, J.; Motojima, O.

1995-01-01

A real-scale helical coil winding trial of the Large Helical Device (LHD) has been conducted for a study of coil winding configuration and winding methods and for exhibiting the state of the art. It includes construction and test run of a specifically designed winding machine and development of various manufacturing methods for accurate coil winding. It has been carried out in Hitachi Works before in situ winding, and has provided much needed engineering data for construction of the LHD. (orig.)

Large scale oil lease automation and electronic custody transfer

International Nuclear Information System (INIS)

Price, C.R.; Elmer, D.C.

1995-01-01

Typically, oil field production operations have only been automated at fields with long term production profiles and enhanced recovery. The automation generally consists of monitoring and control at the wellhead and centralized facilities. However, Union Pacific Resources Co. (UPRC) has successfully implemented a large scale automation program for rapid-decline primary recovery Austin Chalk wells where purchasers buy and transport oil from each individual wellsite. This project has resulted in two significant benefits. First, operators are using the system to re-engineer their work processes. Second, an inter-company team created a new electronic custody transfer method. This paper will describe: the progression of the company's automation objectives in the area; the field operator's interaction with the system, and the related benefits; the research and development of the new electronic custody transfer method