Computational error estimates for Monte Carlo finite element approximation with log normal diffusion coefficients

KAUST Repository

Sandberg, Mattias

2015-01-07

The Monte Carlo (and Multi-level Monte Carlo) finite element method can be used to approximate observables of solutions to diffusion equations with log normal distributed diffusion coefficients, e.g. modelling ground water flow. Typical models use log normal diffusion coefficients with H¨older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible and can be larger than the computable low frequency error. This talk will address how the total error can be estimated by the computable error.

Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis

Directory of Open Access Journals (Sweden)

Zhigao Zeng

2016-01-01

Full Text Available This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise.

Binary joint transform correlation using error-diffusion techniques

Science.gov (United States)

Inbar, Hanni; Marom, Emanuel; Konforti, Naim

1993-08-01

Optical pattern recognition techniques based on the optical joint transform correlator (JTC) scheme are attractive due to their simplicity. Recent improvements in spatial light modulators (SLM) increased the popularity of the JTC, providing means for real time operation. Using a binary SLM for the display of the Fourier spectrum, first requires binarization of the joint power spectrum distribution. Although hard-clipping is the simplest and most common binarization method used, we suggest to apply error-diffusion as an improved binarization technique. The performance of a binary JTC, whose input image is considered to contain additive zero-mean white Gaussian noise, is investigated. Various ways for nonlinearly modifying the joint power spectrum prior to the binarization step, which is based on either error-diffusion or hard-clipping techniques, are discussed. These nonlinear modifications aim at increasing the contrast of the interference fringes at the joint power spectrum plane, leading to better definition of the correlation signal. Mathematical analysis, computer simulations and experimental results are presented.

Computable error estimates for Monte Carlo finite element approximation of elliptic PDE with lognormal diffusion coefficients

KAUST Repository

Hall, Eric

2016-01-09

The Monte Carlo (and Multi-level Monte Carlo) finite element method can be used to approximate observables of solutions to diffusion equations with lognormal distributed diffusion coefficients, e.g. modeling ground water flow. Typical models use lognormal diffusion coefficients with H´ older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible and can be larger than the computable low frequency error. We address how the total error can be estimated by the computable error.

The type I error rate for in vivo Comet assay data when the hierarchical structure is disregarded

DEFF Research Database (Denmark)

Hansen, Merete Kjær; Kulahci, Murat

the type I error rate is greater than the nominal _ at 0.05. Closed-form expressions based on scaled F-distributions using the Welch-Satterthwaite approximation are provided to show how the type I error rate is aUected. With this study we hope to motivate researchers to be more precise regarding......, and this imposes considerable impact on the type I error rate. This study aims to demonstrate the implications that result from disregarding the hierarchical structure. DiUerent combinations of the factor levels as they appear in a literature study give type I error rates up to 0.51 and for all combinations...

Residual sweeping errors in turbulent particle pair diffusion in a Lagrangian diffusion model.

Science.gov (United States)

Malik, Nadeem A

2017-01-01

Thomson, D. J. & Devenish, B. J. [J. Fluid Mech. 526, 277 (2005)] and others have suggested that sweeping effects make Lagrangian properties in Kinematic Simulations (KS), Fung et al [Fung J. C. H., Hunt J. C. R., Malik N. A. & Perkins R. J. J. Fluid Mech. 236, 281 (1992)], unreliable. However, such a conclusion can only be drawn under the assumption of locality. The major aim here is to quantify the sweeping errors in KS without assuming locality. Through a novel analysis based upon analysing pairs of particle trajectories in a frame of reference moving with the large energy containing scales of motion it is shown that the normalized integrated error [Formula: see text] in the turbulent pair diffusivity (K) due to the sweeping effect decreases with increasing pair separation (σl), such that [Formula: see text] as σl/η → ∞; and [Formula: see text] as σl/η → 0. η is the Kolmogorov turbulence microscale. There is an intermediate range of separations 1 < σl/η < ∞ in which the error [Formula: see text] remains negligible. Simulations using KS shows that in the swept frame of reference, this intermediate range is large covering almost the entire inertial subrange simulated, 1 < σl/η < 105, implying that the deviation from locality observed in KS cannot be atributed to sweeping errors. This is important for pair diffusion theory and modeling. PACS numbers: 47.27.E?, 47.27.Gs, 47.27.jv, 47.27.Ak, 47.27.tb, 47.27.eb, 47.11.-j.

Error quantification of the axial nodal diffusion kernel of the DeCART code

International Nuclear Information System (INIS)

Cho, J. Y.; Kim, K. S.; Lee, C. C.

2006-01-01

This paper is to quantify the transport effects involved in the axial nodal diffusion kernel of the DeCART code. The transport effects are itemized into three effects, the homogenization, the diffusion, and the nodal effects. A five pin model consisting of four fuel pins and one non-fuel pin is demonstrated to quantify the transport effects. The transport effects are analyzed for three problems, the single pin (SP), guide tube (GT) and control rod (CR) problems by replacing the non-fuel pin with the fuel pin, a guide-tube and a control rod pins, respectively. The homogenization and diffusion effects are estimated to be about -4 and -50 pcm for the eigenvalue, and less than 2 % for the node power. The nodal effect on the eigenvalue is evaluated to be about -50 pcm in the SP and GT problems, and +350 pcm in the CR problem. Regarding the node power, this effect induces about a 3 % error in the SP and GT problems, and about a 20 % error in the CR problem. The large power error in the CR problem is due to the plane thickness, and it can be decreased by using the adaptive plane size. From the error quantification, it is concluded that the homogenization and the diffusion effects are not controllable if DeCART maintains the diffusion kernel for the axial solution, but the nodal effect is controllable by introducing the adaptive plane size scheme. (authors)

Modulated error diffusion CGHs for neural nets

Science.gov (United States)

Vermeulen, Pieter J. E.; Casasent, David P.

1990-05-01

New modulated error diffusion CGHs (computer generated holograms) for optical computing are considered. Specific attention is given to their use in optical matrix-vector, associative processor, neural net and optical interconnection architectures. We consider lensless CGH systems (many CGHs use an external Fourier transform (FT) lens), the Fresnel sampling requirements, the effects of finite CGH apertures (sample and hold inputs), dot size correction (for laser recorders), and new applications for this novel encoding method (that devotes attention to quantization noise effects).

Two-dimensional finite element neutron diffusion analysis using hierarchic shape functions

International Nuclear Information System (INIS)

Carpenter, D.C.

1997-01-01

Recent advances have been made in the use of p-type finite element method (FEM) for structural and fluid dynamics problems that hold promise for reactor physics problems. These advances include using hierarchic shape functions, element-by-element iterative solvers and more powerful mapping techniques. Use of the hierarchic shape functions allows greater flexibility and efficiency in implementing energy-dependent flux expansions and incorporating localized refinement of the solution space. The irregular matrices generated by the p-type FEM can be solved efficiently using element-by-element conjugate gradient iterative solvers. These solvers do not require storage of either the global or local stiffness matrices and can be highly vectorized. Mapping techniques based on blending function interpolation allow exact representation of curved boundaries using coarse element grids. These features were implemented in a developmental two-dimensional neutron diffusion program based on the use of hierarchic shape functions (FEM2DH). Several aspects in the effective use of p-type analysis were explored. Two choices of elemental preconditioning were examined--the proper selection of the polynomial shape functions and the proper number of functions to use. Of the five shape function polynomials tested, the integral Legendre functions were the most effective. The serendipity set of functions is preferable over the full tensor product set. Two global preconditioners were also examined--simple diagonal and incomplete Cholesky. The full effectiveness of the finite element methodology was demonstrated on a two-region, two-group cylindrical problem but solved in the x-y coordinate space, using a non-structured element grid. The exact, analytic eigenvalue solution was achieved with FEM2DH using various combinations of element grids and flux expansions

Computational error estimates for Monte Carlo finite element approximation with log normal diffusion coefficients

KAUST Repository

Sandberg, Mattias

2015-01-01

log normal diffusion coefficients with H¨older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible

Principal distance constraint error diffusion algorithm for homogeneous dot distribution

Science.gov (United States)

Kang, Ki-Min; Kim, Choon-Woo

1999-12-01

The perceived quality of the halftoned image strongly depends on the spatial distribution of the binary dots. Various error diffusion algorithms have been proposed for realizing the homogeneous dot distribution in the highlight and shadow regions. However, they are computationally expensive and/or require large memory space. This paper presents a new threshold modulated error diffusion algorithm for the homogeneous dot distribution. The proposed method is applied exactly same as the Floyd-Steinberg's algorithm except the thresholding process. The threshold value is modulated based on the difference between the distance to the nearest minor pixel, `minor pixel distance', and the principal distance. To do so, calculation of the minor pixel distance is needed for every pixel. But, it is quite time consuming and requires large memory resources. In order to alleviate this problem, `the minor pixel offset array' that transforms the 2D history of minor pixels into the 1D codes is proposed. The proposed algorithm drastically reduces the computational load and memory spaces needed for calculation of the minor pixel distance.

Error estimation for variational nodal calculations

International Nuclear Information System (INIS)

Zhang, H.; Lewis, E.E.

1998-01-01

Adaptive grid methods are widely employed in finite element solutions to both solid and fluid mechanics problems. Either the size of the element is reduced (h refinement) or the order of the trial function is increased (p refinement) locally to improve the accuracy of the solution without a commensurate increase in computational effort. Success of these methods requires effective local error estimates to determine those parts of the problem domain where the solution should be refined. Adaptive methods have recently been applied to the spatial variables of the discrete ordinates equations. As a first step in the development of adaptive methods that are compatible with the variational nodal method, the authors examine error estimates for use in conjunction with spatial variables. The variational nodal method lends itself well to p refinement because the space-angle trial functions are hierarchical. Here they examine an error estimator for use with spatial p refinement for the diffusion approximation. Eventually, angular refinement will also be considered using spherical harmonics approximations

Computable error estimates for Monte Carlo finite element approximation of elliptic PDE with lognormal diffusion coefficients

KAUST Repository

Hall, Eric; Haakon, Hoel; Sandberg, Mattias; Szepessy, Anders; Tempone, Raul

2016-01-01

lognormal diffusion coefficients with H´ older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible

Discontinuous Galerkin methods and a posteriori error analysis for heterogenous diffusion problems; Methodes de Galerkine discontinues et analyse d'erreur a posteriori pour les problemes de diffusion heterogene

Energy Technology Data Exchange (ETDEWEB)

Stephansen, A.F

2007-12-15

In this thesis we analyse a discontinuous Galerkin (DG) method and two computable a posteriori error estimators for the linear and stationary advection-diffusion-reaction equation with heterogeneous diffusion. The DG method considered, the SWIP method, is a variation of the Symmetric Interior Penalty Galerkin method. The difference is that the SWIP method uses weighted averages with weights that depend on the diffusion. The a priori analysis shows optimal convergence with respect to mesh-size and robustness with respect to heterogeneous diffusion, which is confirmed by numerical tests. Both a posteriori error estimators are of the residual type and control the energy (semi-)norm of the error. Local lower bounds are obtained showing that almost all indicators are independent of heterogeneities. The exception is for the non-conforming part of the error, which has been evaluated using the Oswald interpolator. The second error estimator is sharper in its estimate with respect to the first one, but it is slightly more costly. This estimator is based on the construction of an H(div)-conforming Raviart-Thomas-Nedelec flux using the conservativeness of DG methods. Numerical results show that both estimators can be used for mesh-adaptation. (author)

Development of the hierarchical domain decomposition boundary element method for solving the three-dimensional multiregion neutron diffusion equations

International Nuclear Information System (INIS)

Chiba, Gou; Tsuji, Masashi; Shimazu, Yoichiro

2001-01-01

A hierarchical domain decomposition boundary element method (HDD-BEM) that was developed to solve a two-dimensional neutron diffusion equation has been modified to deal with three-dimensional problems. In the HDD-BEM, the domain is decomposed into homogeneous regions. The boundary conditions on the common inner boundaries between decomposed regions and the neutron multiplication factor are initially assumed. With these assumptions, the neutron diffusion equations defined in decomposed homogeneous regions can be solved respectively by applying the boundary element method. This part corresponds to the 'lower level' calculations. At the 'higher level' calculations, the assumed values, the inner boundary conditions and the neutron multiplication factor, are modified so as to satisfy the continuity conditions for the neutron flux and the neutron currents on the inner boundaries. These procedures of the lower and higher levels are executed alternately and iteratively until the continuity conditions are satisfied within a convergence tolerance. With the hierarchical domain decomposition, it is possible to deal with problems composing a large number of regions, something that has been difficult with the conventional BEM. In this paper, it is showed that a three-dimensional problem even with 722 regions can be solved with a fine accuracy and an acceptable computation time. (author)

The speed of memory errors shows the influence of misleading information: Testing the diffusion model and discrete-state models.

Science.gov (United States)

Starns, Jeffrey J; Dubé, Chad; Frelinger, Matthew E

2018-05-01

In this report, we evaluate single-item and forced-choice recognition memory for the same items and use the resulting accuracy and reaction time data to test the predictions of discrete-state and continuous models. For the single-item trials, participants saw a word and indicated whether or not it was studied on a previous list. The forced-choice trials had one studied and one non-studied word that both appeared in the earlier single-item trials and both received the same response. Thus, forced-choice trials always had one word with a previous correct response and one with a previous error. Participants were asked to select the studied word regardless of whether they previously called both words "studied" or "not studied." The diffusion model predicts that forced-choice accuracy should be lower when the word with a previous error had a fast versus a slow single-item RT, because fast errors are associated with more compelling misleading memory retrieval. The two-high-threshold (2HT) model does not share this prediction because all errors are guesses, so error RT is not related to memory strength. A low-threshold version of the discrete state approach predicts an effect similar to the diffusion model, because errors are a mixture of responses based on misleading retrieval and guesses, and the guesses should tend to be slower. Results showed that faster single-trial errors were associated with lower forced-choice accuracy, as predicted by the diffusion and low-threshold models. Copyright © 2018 Elsevier Inc. All rights reserved.

Error analysis of semidiscrete finite element methods for inhomogeneous time-fractional diffusion

KAUST Repository

Jin, B.; Lazarov, R.; Pasciak, J.; Zhou, Z.

2014-01-01

© 2014 Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved. We consider the initial-boundary value problem for an inhomogeneous time-fractional diffusion equation with a homogeneous Dirichlet boundary condition, a vanishing initial data and a nonsmooth right-hand side in a bounded convex polyhedral domain. We analyse two semidiscrete schemes based on the standard Galerkin and lumped mass finite element methods. Almost optimal error estimates are obtained for right-hand side data f (x, t) ε L∞ (0, T; Hq(ω)), ≤1≥ 1, for both semidiscrete schemes. For the lumped mass method, the optimal L2(ω)-norm error estimate requires symmetric meshes. Finally, twodimensional numerical experiments are presented to verify our theoretical results.

Error analysis of semidiscrete finite element methods for inhomogeneous time-fractional diffusion

KAUST Repository

Jin, B.

2014-05-30

© 2014 Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved. We consider the initial-boundary value problem for an inhomogeneous time-fractional diffusion equation with a homogeneous Dirichlet boundary condition, a vanishing initial data and a nonsmooth right-hand side in a bounded convex polyhedral domain. We analyse two semidiscrete schemes based on the standard Galerkin and lumped mass finite element methods. Almost optimal error estimates are obtained for right-hand side data f (x, t) ε L∞ (0, T; Hq(ω)), ≤1≥ 1, for both semidiscrete schemes. For the lumped mass method, the optimal L2(ω)-norm error estimate requires symmetric meshes. Finally, twodimensional numerical experiments are presented to verify our theoretical results.

Magnitude of pseudopotential localization errors in fixed node diffusion quantum Monte Carlo.

Science.gov (United States)

Krogel, Jaron T; Kent, P R C

2017-06-28

Growth in computational resources has lead to the application of real space diffusion quantum Monte Carlo to increasingly heavy elements. Although generally assumed to be small, we find that when using standard techniques, the pseudopotential localization error can be large, on the order of an electron volt for an isolated cerium atom. We formally show that the localization error can be reduced to zero with improvements to the Jastrow factor alone, and we define a metric of Jastrow sensitivity that may be useful in the design of pseudopotentials. We employ an extrapolation scheme to extract the bare fixed node energy and estimate the localization error in both the locality approximation and the T-moves schemes for the Ce atom in charge states 3+ and 4+. The locality approximation exhibits the lowest Jastrow sensitivity and generally smaller localization errors than T-moves although the locality approximation energy approaches the localization free limit from above/below for the 3+/4+ charge state. We find that energy minimized Jastrow factors including three-body electron-electron-ion terms are the most effective at reducing the localization error for both the locality approximation and T-moves for the case of the Ce atom. Less complex or variance minimized Jastrows are generally less effective. Our results suggest that further improvements to Jastrow factors and trial wavefunction forms may be needed to reduce localization errors to chemical accuracy when medium core pseudopotentials are applied to heavy elements such as Ce.

Intensity-based hierarchical elastic registration using approximating splines.

Science.gov (United States)

Serifovic-Trbalic, Amira; Demirovic, Damir; Cattin, Philippe C

2014-01-01

We introduce a new hierarchical approach for elastic medical image registration using approximating splines. In order to obtain the dense deformation field, we employ Gaussian elastic body splines (GEBS) that incorporate anisotropic landmark errors and rotation information. Since the GEBS approach is based on a physical model in form of analytical solutions of the Navier equation, it can very well cope with the local as well as global deformations present in the images by varying the standard deviation of the Gaussian forces. The proposed GEBS approximating model is integrated into the elastic hierarchical image registration framework, which decomposes a nonrigid registration problem into numerous local rigid transformations. The approximating GEBS registration scheme incorporates anisotropic landmark errors as well as rotation information. The anisotropic landmark localization uncertainties can be estimated directly from the image data, and in this case, they represent the minimal stochastic localization error, i.e., the Cramér-Rao bound. The rotation information of each landmark obtained from the hierarchical procedure is transposed in an additional angular landmark, doubling the number of landmarks in the GEBS model. The modified hierarchical registration using the approximating GEBS model is applied to register 161 image pairs from a digital mammogram database. The obtained results are very encouraging, and the proposed approach significantly improved all registrations comparing the mean-square error in relation to approximating TPS with the rotation information. On artificially deformed breast images, the newly proposed method performed better than the state-of-the-art registration algorithm introduced by Rueckert et al. (IEEE Trans Med Imaging 18:712-721, 1999). The average error per breast tissue pixel was less than 2.23 pixels compared to 2.46 pixels for Rueckert's method. The proposed hierarchical elastic image registration approach incorporates the GEBS

Hierarchically Nanoporous Bioactive Glasses for High Efficiency Immobilization of Enzymes

DEFF Research Database (Denmark)

He, W.; Min, D.D.; Zhang, X.D.

2014-01-01

Bioactive glasses with hierarchical nanoporosity and structures have been heavily involved in immobilization of enzymes. Because of meticulous design and ingenious hierarchical nanostructuration of porosities from yeast cell biotemplates, hierarchically nanostructured porous bioactive glasses can...... and products of catalytic reactions can freely diffuse through open mesopores (2–40 nm). The formation mechanism of hierarchically structured porous bioactive glasses, the immobilization mechanism of enzyme and the catalysis mechanism of immobilized enzyme are then discussed. The novel nanostructure...

On the group approximation errors in description of neutron slowing-down at large distances from a source. Diffusion approach

International Nuclear Information System (INIS)

Kulakovskij, M.Ya.; Savitskij, V.I.

1981-01-01

The errors of multigroup calculating the neutron flux spatial and energy distribution in the fast reactor shield caused by using group and age approximations are considered. It is shown that at small distances from a source the age theory rather well describes the distribution of the slowing-down density. With the distance increase the age approximation leads to underestimating the neutron fluxes, and the error quickly increases at that. At small distances from the source (up to 15 lengths of free path in graphite) the multigroup diffusion approximation describes the distribution of slowing down density quite satisfactorily and at that the results almost do not depend on the number of groups. With the distance increase the multigroup diffusion calculations lead to considerable overestimating of the slowing-down density. The conclusion is drawn that the group approximation proper errors are opposite in sign to the error introduced by the age approximation and to some extent compensate each other

Hierarchical matrices algorithms and analysis

CERN Document Server

Hackbusch, Wolfgang

2015-01-01

This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...

Zeolitic materials with hierarchical porous structures.

Science.gov (United States)

Lopez-Orozco, Sofia; Inayat, Amer; Schwab, Andreas; Selvam, Thangaraj; Schwieger, Wilhelm

2011-06-17

During the past several years, different kinds of hierarchical structured zeolitic materials have been synthesized due to their highly attractive properties, such as superior mass/heat transfer characteristics, lower restriction of the diffusion of reactants in the mesopores, and low pressure drop. Our contribution provides general information regarding types and preparation methods of hierarchical zeolitic materials and their relative advantages and disadvantages. Thereafter, recent advances in the preparation and characterization of hierarchical zeolitic structures within the crystallites by post-synthetic treatment methods, such as dealumination or desilication; and structured devices by in situ and ex situ zeolite coatings on open-cellular ceramic foams as (non-reactive as well as reactive) supports are highlighted. Specific advantages of using hierarchical zeolitic catalysts/structures in selected catalytic reactions, such as benzene to phenol (BTOP) and methanol to olefins (MTO) are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of Error Propagation Within Hierarchical Air Combat Models

Science.gov (United States)

2016-06-01

values alone are propagated through layers of combat models, the final results will likely be biased, and risk underestimated. An air-to-air...values alone are propagated through layers of combat models, the final results will likely be biased, and risk underestimated. An air-to-air engagement... PROPAGATION WITHIN HIERARCHICAL AIR COMBAT MODELS by Salih Ilaslan June 2016 Thesis Advisor: Thomas W. Lucas Second Reader: Jeffrey

Drifting through Basic Subprocesses of Reading: A Hierarchical Diffusion Model Analysis of Age Effects on Visual Word Recognition.

Science.gov (United States)

Froehlich, Eva; Liebig, Johanna; Ziegler, Johannes C; Braun, Mario; Lindenberger, Ulman; Heekeren, Hauke R; Jacobs, Arthur M

2016-01-01

Reading is one of the most popular leisure activities and it is routinely performed by most individuals even in old age. Successful reading enables older people to master and actively participate in everyday life and maintain functional independence. Yet, reading comprises a multitude of subprocesses and it is undoubtedly one of the most complex accomplishments of the human brain. Not surprisingly, findings of age-related effects on word recognition and reading have been partly contradictory and are often confined to only one of four central reading subprocesses, i.e., sublexical, orthographic, phonological and lexico-semantic processing. The aim of the present study was therefore to systematically investigate the impact of age on each of these subprocesses. A total of 1,807 participants (young, N = 384; old, N = 1,423) performed four decision tasks specifically designed to tap one of the subprocesses. To account for the behavioral heterogeneity in older adults, this subsample was split into high and low performing readers. Data were analyzed using a hierarchical diffusion modeling approach, which provides more information than standard response time/accuracy analyses. Taking into account incorrect and correct response times, their distributions and accuracy data, hierarchical diffusion modeling allowed us to differentiate between age-related changes in decision threshold, non-decision time and the speed of information uptake. We observed longer non-decision times for older adults and a more conservative decision threshold. More importantly, high-performing older readers outperformed younger adults at the speed of information uptake in orthographic and lexico-semantic processing, whereas a general age-disadvantage was observed at the sublexical and phonological levels. Low-performing older readers were slowest in information uptake in all four subprocesses. Discussing these results in terms of computational models of word recognition, we propose age

When mechanism matters: Bayesian forecasting using models of ecological diffusion

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.; Russell, Robin E.; Walsh, Daniel P.; Powell, James A.

2017-01-01

Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

Two-Phase Diffusion Technique for the Preparation of Ultramacroporous/Mesoporous Silica Microspheres via Interface Hydrolysis, Diffusion, and Gelation of TEOS.

Science.gov (United States)

Ju, Minhua; Li, Yupeng; Yu, Liang; Wang, Chongqing; Zhang, Lixiong

2018-02-06

Honeycombed hierarchical ultramacroporous/mesoporous silica microspheres were prepared via the hydrolysis of TEOS in the oil-water interface, with subsequent diffusion and gelation in the acidic water-phase microdroplets with the assistance of a simple homemade microdevice. The diffusion of furfuryl alcohol (FA) also happened at a relatively high rate during the hydrolysis and diffusion of TEOS. Therefore, plenty of FA will be inside of the water microdroplets and form a decent number of polyfurfuryl alcohol (PFA) microparticles, thereby obtaining honeycombed hierarchical porosity silica microspheres with abundant ultramacroporous cavities and mesopores after calcination. It was found that the concentration of FA, residence time, and reaction temperature have significant effects on the porosity and pore size due to the influence on the diffusion rate and amount of FA in water-phase microdroplets. The honeycombed silica microspheres have obvious microscopic visible ultramacroporous cavities with the submicrometer cavity diameter as high as 85% porosity based on the rough overall volume of microsphere. N 2 adsorption-desorption isotherms show that the honeycombed hierarchical porosity silica microspheres have a high surface area of 602 m 2 g -1 , a mesopore volume of 0.77 cm 3 /g, and a mesopore porosity of 99.6% based on the total pore volume of N 2 adsorption-desorption. On the basis of the experiment results, a rational formation process of the honeycombed hierarchical porosity silica microspheres was deduced.

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

Science.gov (United States)

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep

Drifting through basic subprocesses of reading: A hierarchical diffusion model analysis of age effects on visual word recognition

Directory of Open Access Journals (Sweden)

Eva Froehlich

2016-11-01

Full Text Available Reading is one of the most popular leisure activities and it is routinely performed by most individuals even in old age. Successful reading enables older people to master and actively participate in everyday life and maintain functional independence. Yet, reading comprises a multitude of subprocesses and it is undoubtedly one of the most complex accomplishments of the human brain. Not surprisingly, findings of age-related effects on word recognition and reading have been partly contradictory and are often confined to only one of four central reading subprocesses, i.e., sublexical, orthographic, phonological and lexico-semantic processing. The aim of the present study was therefore to systematically investigate the impact of age on each of these subprocesses. A total of 1,807 participants (young, N = 384; old, N = 1,423 performed four decision tasks specifically designed to tap one of the subprocesses. To account for the behavioral heterogeneity in older adults, this subsample was split into high and low performing readers. Data were analyzed using a hierarchical diffusion modelling approach which provides more information than standard response times/accuracy analyses. Taking into account incorrect and correct response times, their distributions and accuracy data, hierarchical diffusion modelling allowed us to differentiate between age-related changes in decision threshold, non-decision time and the speed of information uptake. We observed longer non-decision times for older adults and a more conservative decision threshold. More importantly, high-performing older readers outperformed younger adults at the speed of information uptake in orthographic and lexico-semantic processing whereas a general age-disadvantage was observed at the sublexical and phonological levels. Low-performing older readers were slowest in information uptake in all four subprocesses. Discussing these results in terms of computational models of word recognition, we propose

Statistical Significance for Hierarchical Clustering

Science.gov (United States)

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Hierarchical modeling and its numerical implementation for layered thin elastic structures

Energy Technology Data Exchange (ETDEWEB)

Cho, Jin-Rae [Hongik University, Sejong (Korea, Republic of)

2017-05-15

Thin elastic structures such as beam- and plate-like structures and laminates are characterized by the small thickness, which lead to classical plate and laminate theories in which the displacement fields through the thickness are assumed linear or higher-order polynomials. These classical theories are either insufficient to represent the complex stress variation through the thickness or may encounter the accuracy-computational cost dilemma. In order to overcome the inherent problem of classical theories, the concept of hierarchical modeling has been emerged. In the hierarchical modeling, the hierarchical models with different model levels are selected and combined within a structure domain, in order to make the modeling error be distributed as uniformly as possible throughout the problem domain. The purpose of current study is to explore the potential of hierarchical modeling for the effective numerical analysis of layered structures such as laminated composite. For this goal, the hierarchical models are constructed and the hierarchical modeling is implemented by selectively adjusting the level of hierarchical models. As well, the major characteristics of hierarchical models are investigated through the numerical experiments.

Impact of errors in experimental parameters on reconstructed breast images using diffuse optical tomography.

Science.gov (United States)

Deng, Bin; Lundqvist, Mats; Fang, Qianqian; Carp, Stefan A

2018-03-01

Near-infrared diffuse optical tomography (NIR-DOT) is an emerging technology that offers hemoglobin based, functional imaging tumor biomarkers for breast cancer management. The most promising clinical translation opportunities are in the differential diagnosis of malignant vs. benign lesions, and in early response assessment and guidance for neoadjuvant chemotherapy. Accurate quantification of the tissue oxy- and deoxy-hemoglobin concentration across the field of view, as well as repeatability during longitudinal imaging in the context of therapy guidance, are essential for the successful translation of NIR-DOT to clinical practice. The ill-posed and ill-condition nature of the DOT inverse problem makes this technique particularly susceptible to model errors that may occur, for example, when the experimental conditions do not fully match the assumptions built into the image reconstruction process. To evaluate the susceptibility of DOT images to experimental errors that might be encountered in practice for a parallel-plate NIR-DOT system, we simulated 7 different types of errors, each with a range of magnitudes. We generated simulated data by using digital breast phantoms derived from five actual mammograms of healthy female volunteers, to which we added a 1-cm tumor. After applying each of the experimental error types and magnitudes to the simulated measurements, we reconstructed optical images with and without structural prior guidance and assessed the overall error in the total hemoglobin concentrations (HbT) and in the HbT contrast between the lesion and surrounding area vs. the best-case scenarios. It is found that slight in-plane probe misalignment and plate rotation did not result in large quantification errors. However, any out-of-plane probe tilting could result in significant deterioration in lesion contrast. Among the error types investigated in this work, optical images were the least likely to be impacted by breast shape inaccuracies but suffered the

Students' errors in solving linear equation word problems: Case ...

African Journals Online (AJOL)

kofi.mereku

the modified Newman Error Hierarchical levels (NEAL), which comprise reading, comprehension, transformation, process skills and encoding errors. The results revealed that majority (60%) of the students attempted most of the questions with a few (2%) arriving at the correct answer which implies students have difficulties ...

Molecular simulation of adsorption and transport in hierarchical porous materials.

Science.gov (United States)

Coasne, Benoit; Galarneau, Anne; Gerardin, Corine; Fajula, François; Villemot, François

2013-06-25

Adsorption and transport in hierarchical porous solids with micro- (~1 nm) and mesoporosities (>2 nm) are investigated by molecular simulation. Two models of hierarchical solids are considered: microporous materials in which mesopores are carved out (model A) and mesoporous materials in which microporous nanoparticles are inserted (model B). Adsorption isotherms for model A can be described as a linear combination of the adsorption isotherms for pure mesoporous and microporous solids. In contrast, adsorption in model B departs from adsorption in pure microporous and mesoporous solids; the inserted microporous particles act as defects, which help nucleate the liquid phase within the mesopore and shift capillary condensation toward lower pressures. As far as transport under a pressure gradient is concerned, the flux in hierarchical materials consisting of microporous solids in which mesopores are carved out obeys the Navier-Stokes equation so that Darcy's law is verified within the mesopore. Moreover, the flow in such materials is larger than in a single mesopore, due to the transfer between micropores and mesopores. This nonzero velocity at the mesopore surface implies that transport in such hierarchical materials involves slippage at the mesopore surface, although the adsorbate has a strong affinity for the surface. In contrast to model A, flux in model B is smaller than in a single mesopore, as the nanoparticles act as constrictions that hinder transport. By a subtle effect arising from fast transport in the mesopores, the presence of mesopores increases the number of molecules in the microporosity in hierarchical materials and, hence, decreases the flow in the micropores (due to mass conservation). As a result, we do not observe faster diffusion in the micropores of hierarchical materials upon flow but slower diffusion, which increases the contact time between the adsorbate and the surface of the microporosity.

Tracking Single DNA Nanodevices in Hierarchically Meso-Macroporous Antimony-Doped Tin Oxide Demonstrates Finite Confinement.

Science.gov (United States)

Mieritz, Daniel; Li, Xiang; Volosin, Alex; Liu, Minghui; Yan, Hao; Walter, Nils G; Seo, Dong-Kyun

2017-06-27

Housing bio-nano guest devices based on DNA nanostructures within porous, conducting, inorganic host materials promise valuable applications in solar energy conversion, chemical catalysis, and analyte sensing. Herein, we report a single-template synthetic development of hierarchically porous, transparent conductive metal oxide coatings whose pores are freely accessible by large biomacromolecules. Their hierarchal pore structure is bimodal with a larger number of closely packed open macropores (∼200 nm) at the higher rank and with the remaining space being filled with a gel network of antimony-doped tin oxide (ATO) nanoparticles that is highly porous with a broad size range of textual pores mainly from 20-100 nm at the lower rank. The employed carbon black template not only creates the large open macropores but also retains the highly structured gel network as holey pore walls. Single molecule fluorescence microscopic studies with fluorophore-labeled DNA nanotweezers reveal a detailed view of multimodal diffusion dynamics of the biomacromolecules inside the hierarchically porous structure. Two diffusion constants were parsed from trajectory analyses that were attributed to free diffusion (diffusion constant D = 2.2 μm 2 /s) and to diffusion within an average confinement length of 210 nm (D = 0.12 μm 2 /s), consistent with the average macropore size of the coating. Despite its holey nature, the ATO gel network acts as an efficient barrier to the diffusion of the DNA nanostructures, which is strongly indicative of physical interactions between the molecules and the pore nanostructure.

HIERARCHICAL ADAPTIVE ROOD PATTERN SEARCH FOR MOTION ESTIMATION AT VIDEO SEQUENCE ANALYSIS

Directory of Open Access Journals (Sweden)

V. T. Nguyen

2016-05-01

Full Text Available Subject of Research.The paper deals with the motion estimation algorithms for the analysis of video sequences in compression standards MPEG-4 Visual and H.264. Anew algorithm has been offered based on the analysis of the advantages and disadvantages of existing algorithms. Method. Thealgorithm is called hierarchical adaptive rood pattern search (Hierarchical ARPS, HARPS. This new algorithm includes the classic adaptive rood pattern search ARPS and hierarchical search MP (Hierarchical search or Mean pyramid. All motion estimation algorithms have been implemented using MATLAB package and tested with several video sequences. Main Results. The criteria for evaluating the algorithms were: speed, peak signal to noise ratio, mean square error and mean absolute deviation. The proposed method showed a much better performance at a comparable error and deviation. The peak signal to noise ratio in different video sequences shows better and worse results than characteristics of known algorithms so it requires further investigation. Practical Relevance. Application of this algorithm in MPEG-4 and H.264 codecs instead of the standard can significantly reduce compression time. This feature enables to recommend it in telecommunication systems for multimedia data storing, transmission and processing.

Hierarchical Neural Regression Models for Customer Churn Prediction

Directory of Open Access Journals (Sweden)

Golshan Mohammadi

2013-01-01

Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

Lattice-Symmetry-Driven Epitaxy of Hierarchical GaN Nanotripods

KAUST Repository

Wang, Ping

2017-01-18

Lattice-symmetry-driven epitaxy of hierarchical GaN nanotripods is demonstrated. The nanotripods emerge on the top of hexagonal GaN nanowires, which are selectively grown on pillar-patterned GaN templates using molecular beam epitaxy. High-resolution transmission electron microscopy confirms that two kinds of lattice-symmetry, wurtzite (wz) and zinc-blende (zb), coexist in the GaN nanotripods. Periodical transformation between wz and zb drives the epitaxy of the hierarchical nanotripods with N-polarity. The zb-GaN is formed by the poor diffusion of adatoms, and it can be suppressed by improving the ability of the Ga adatoms to migrate as the growth temperature increased. This controllable epitaxy of hierarchical GaN nanotripods allows quantum dots to be located at the phase junctions of the nanotripods and nanowires, suggesting a new recipe for multichannel quantum devices.

Structural Group-based Auditing of Missing Hierarchical Relationships in UMLS

Science.gov (United States)

Chen, Yan; Gu, Huanying(Helen); Perl, Yehoshua; Geller, James

2009-01-01

The Metathesaurus of the UMLS was created by integrating various source terminologies. The inter-concept relationships were either integrated into the UMLS from the source terminologies or specially generated. Due to the extensive size and inherent complexity of the Metathesaurus, the accidental omission of some hierarchical relationships was inevitable. We present a recursive procedure which allows a human expert, with the support of an algorithm, to locate missing hierarchical relationships. The procedure starts with a group of concepts with exactly the same (correct) semantic type assignments. It then partitions the concepts, based on child-of hierarchical relationships, into smaller, singly rooted, hierarchically connected subgroups. The auditor only needs to focus on the subgroups with very few concepts and their concepts with semantic type reassignments. The procedure was evaluated by comparing it with a comprehensive manual audit and it exhibits a perfect error recall. PMID:18824248

Semiparametric Bernstein–von Mises for the error standard deviation

OpenAIRE

Jonge, de, R.; Zanten, van, J.H.

2013-01-01

We study Bayes procedures for nonparametric regression problems with Gaussian errors, giving conditions under which a Bernstein–von Mises result holds for the marginal posterior distribution of the error standard deviation. We apply our general results to show that a single Bayes procedure using a hierarchical spline-based prior on the regression function and an independent prior on the error variance, can simultaneously achieve adaptive, rate-optimal estimation of a smooth, multivariate regr...

Hierarchical modeling of molecular energies using a deep neural network

Science.gov (United States)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

Using HET taxonomy to help stop human error

OpenAIRE

Li, Wen-Chin; Harris, Don; Stanton, Neville A.; Hsu, Yueh-Ling; Chang, Danny; Wang, Thomas; Young, Hong-Tsu

2010-01-01

Flight crews make positive contributions to the safety of aviation operations. Pilots have to assess continuously changing situations, evaluate potential risks, and make quick decisions. However, even well-trained and experienced pilots make errors. Accident investigations have identified that pilots’ performance is influenced significantly by the design of the flightdeck interface. This research applies hierarchical task analysis (HTA) and utilizes the Human Error Template (HET) taxonomy to ...

Rhodium SPND's Error Reduction using Extended Kalman Filter combined with Time Dependent Neutron Diffusion Equation

International Nuclear Information System (INIS)

Lee, Jeong Hun; Park, Tong Kyu; Jeon, Seong Su

2014-01-01

The Rhodium SPND is accurate in steady-state conditions but responds slowly to changes in neutron flux. The slow response time of Rhodium SPND precludes its direct use for control and protection purposes specially when nuclear power plant is used for load following. To shorten the response time of Rhodium SPND, there were some acceleration methods but they could not reflect neutron flux distribution in reactor core. On the other hands, some methods for core power distribution monitoring could not consider the slow response time of Rhodium SPND and noise effect. In this paper, time dependent neutron diffusion equation is directly used to estimate reactor power distribution and extended Kalman filter method is used to correct neutron flux with Rhodium SPND's and to shorten the response time of them. Extended Kalman filter is effective tool to reduce measurement error of Rhodium SPND's and even simple FDM to solve time dependent neutron diffusion equation can be an effective measure. This method reduces random errors of detectors and can follow reactor power level without cross-section change. It means monitoring system may not calculate cross-section at every time steps and computing time will be shorten. To minimize delay of Rhodium SPND's conversion function h should be evaluated in next study. Neutron and Rh-103 reaction has several decay chains and half-lives over 40 seconds causing delay of detection. Time dependent neutron diffusion equation will be combined with decay chains. Power level and distribution change corresponding movement of control rod will be tested with more complicated reference code as well as xenon effect. With these efforts, final result is expected to be used as a powerful monitoring tool of nuclear reactor core

Rhodium SPND's Error Reduction using Extended Kalman Filter combined with Time Dependent Neutron Diffusion Equation

Energy Technology Data Exchange (ETDEWEB)

Lee, Jeong Hun; Park, Tong Kyu; Jeon, Seong Su [FNC Technology Co., Ltd., Yongin (Korea, Republic of)

2014-05-15

The Rhodium SPND is accurate in steady-state conditions but responds slowly to changes in neutron flux. The slow response time of Rhodium SPND precludes its direct use for control and protection purposes specially when nuclear power plant is used for load following. To shorten the response time of Rhodium SPND, there were some acceleration methods but they could not reflect neutron flux distribution in reactor core. On the other hands, some methods for core power distribution monitoring could not consider the slow response time of Rhodium SPND and noise effect. In this paper, time dependent neutron diffusion equation is directly used to estimate reactor power distribution and extended Kalman filter method is used to correct neutron flux with Rhodium SPND's and to shorten the response time of them. Extended Kalman filter is effective tool to reduce measurement error of Rhodium SPND's and even simple FDM to solve time dependent neutron diffusion equation can be an effective measure. This method reduces random errors of detectors and can follow reactor power level without cross-section change. It means monitoring system may not calculate cross-section at every time steps and computing time will be shorten. To minimize delay of Rhodium SPND's conversion function h should be evaluated in next study. Neutron and Rh-103 reaction has several decay chains and half-lives over 40 seconds causing delay of detection. Time dependent neutron diffusion equation will be combined with decay chains. Power level and distribution change corresponding movement of control rod will be tested with more complicated reference code as well as xenon effect. With these efforts, final result is expected to be used as a powerful monitoring tool of nuclear reactor core.

A Bayesian Hierarchical Model for Glacial Dynamics Based on the Shallow Ice Approximation and its Evaluation Using Analytical Solutions

Science.gov (United States)

Gopalan, Giri; Hrafnkelsson, Birgir; Aðalgeirsdóttir, Guðfinna; Jarosch, Alexander H.; Pálsson, Finnur

2018-03-01

Bayesian hierarchical modeling can assist the study of glacial dynamics and ice flow properties. This approach will allow glaciologists to make fully probabilistic predictions for the thickness of a glacier at unobserved spatio-temporal coordinates, and it will also allow for the derivation of posterior probability distributions for key physical parameters such as ice viscosity and basal sliding. The goal of this paper is to develop a proof of concept for a Bayesian hierarchical model constructed, which uses exact analytical solutions for the shallow ice approximation (SIA) introduced by Bueler et al. (2005). A suite of test simulations utilizing these exact solutions suggests that this approach is able to adequately model numerical errors and produce useful physical parameter posterior distributions and predictions. A byproduct of the development of the Bayesian hierarchical model is the derivation of a novel finite difference method for solving the SIA partial differential equation (PDE). An additional novelty of this work is the correction of numerical errors induced through a numerical solution using a statistical model. This error correcting process models numerical errors that accumulate forward in time and spatial variation of numerical errors between the dome, interior, and margin of a glacier.

Recent progress in the direct synthesis of hierarchical zeolites: synthetic strategies and characterization methods

KAUST Repository

Liu, Zhaohui; Hua, Yingjie; Wang, Jianjian; Dong, Xinglong; Tian, Qiwei; Han, Yu

2017-01-01

Hierarchically structured zeolites combine the merits of microporous zeolites and mesoporous materials to offer enhanced molecular diffusion and mass transfer without compromising the inherent catalytic activities and selectivity of zeolites

Recent progress in the direct synthesis of hierarchical zeolites: synthetic strategies and characterization methods

KAUST Repository

Liu, Zhaohui

2017-06-16

Hierarchically structured zeolites combine the merits of microporous zeolites and mesoporous materials to offer enhanced molecular diffusion and mass transfer without compromising the inherent catalytic activities and selectivity of zeolites. This short review gives an introduction to the synthesis strategies for hierarchically structured zeolites with emphasis on the latest progress in the route of ‘direct synthesis’ using various templates. Several characterization methods that allow us to evaluate the ‘quality’ of complex porous structures are also introduced. At the end of this review, an outlook is given to discuss some critical issues and challenges regarding the development of novel hierarchically structured zeolites as well as their applications.

Effect of hierarchical meso–macroporous alumina-supported copper catalyst for methanol synthesis from CO2 hydrogenation

International Nuclear Information System (INIS)

Witoon, Thongthai; Bumrungsalee, Sittisut; Chareonpanich, Metta; Limtrakul, Jumras

2015-01-01

Highlights: • CO 2 hydrogenation over Cu-loaded unimodal and hierarchical alumina catalysts. • Cu-loaded hierarchical catalyst exhibited higher methanol selectivity and stability. • The presence of macropores reduced the probability of side reaction. - Abstract: Effects of pore structures of alumina on the catalytic performance of copper catalysts for CO 2 hydrogenation were investigated. Copper-loaded hierarchical meso–macroporous alumina (Cu/HAl) catalyst exhibited no significant difference in terms of CO 2 conversion with copper-loaded unimodal mesoporous alumina (Cu/UAl) catalyst. However, the selectivity to methanol and dimethyl ether of the Cu/HAl catalyst was much higher than that of the Cu/UAl catalyst. This was attributed to the presence of macropores which diminished the occurrence of side reaction by the shortening the mesopores diffusion path length. The Cu/HAl catalyst also exhibited much higher stability than the Cu/UAl catalyst due to the fast diffusion of water out from the catalyst pellets, alleviating the oxidation of metallic copper to CuO

Three-dimensional h-adaptivity for the multigroup neutron diffusion equations

KAUST Repository

Wang, Yaqi

2009-04-01

Adaptive mesh refinement (AMR) has been shown to allow solving partial differential equations to significantly higher accuracy at reduced numerical cost. This paper presents a state-of-the-art AMR algorithm applied to the multigroup neutron diffusion equation for reactor applications. In order to follow the physics closely, energy group-dependent meshes are employed. We present a novel algorithm for assembling the terms coupling shape functions from different meshes and show how it can be made efficient by deriving all meshes from a common coarse mesh by hierarchic refinement. Our methods are formulated using conforming finite elements of any order, for any number of energy groups. The spatial error distribution is assessed with a generalization of an error estimator originally derived for the Poisson equation. Our implementation of this algorithm is based on the widely used Open Source adaptive finite element library deal.II and is made available as part of this library\\'s extensively documented tutorial. We illustrate our methods with results for 2-D and 3-D reactor simulations using 2 and 7 energy groups, and using conforming finite elements of polynomial degree up to 6. © 2008 Elsevier Ltd. All rights reserved.

Simulation and Measurement of the Transmission Distortions of the Digital Television DVB-T/H Part 2: Hierarchical Modulation Performance

Directory of Open Access Journals (Sweden)

R. Stukavec

2010-09-01

Full Text Available The paper deals with the second part of results of the Czech Science Foundation research project that was aimed into the simulation and measurement of the transmission distortions of the digital terrestrial television according to DVB-T/H standards. In this part the hierarchical modulation performance characteristics and its simulation and laboratory measurements are presented. The paper deals with the hierarchical oriented COFDM modulator for the digital terrestrial television transmission and DVB-T/H standards and possible utilization of this technique in real broadcasting scenarios – fixed, portable and mobile digital TV, all in one TV channel. Impact of the hierarchical modulation on Modulation Error Rate from I/Q constellations and Bit Error Rates before and after Viterbi decoding in DVB-T/H signal decoding are evaluated and discussed.

Adaptive hierarchical grid model of water-borne pollutant dispersion

Science.gov (United States)

Borthwick, A. G. L.; Marchant, R. D.; Copeland, G. J. M.

Water pollution by industrial and agricultural waste is an increasingly major public health issue. It is therefore important for water engineers and managers to be able to predict accurately the local behaviour of water-borne pollutants. This paper describes the novel and efficient coupling of dynamically adaptive hierarchical grids with standard solvers of the advection-diffusion equation. Adaptive quadtree grids are able to focus on regions of interest such as pollutant fronts, while retaining economy in the total number of grid elements through selective grid refinement. Advection is treated using Lagrangian particle tracking. Diffusion is solved separately using two grid-based methods; one is by explicit finite differences, the other a diffusion-velocity approach. Results are given in two dimensions for pure diffusion of an initially Gaussian plume, advection-diffusion of the Gaussian plume in the rotating flow field of a forced vortex, and the transport of species in a rectangular channel with side wall boundary layers. Close agreement is achieved with analytical solutions of the advection-diffusion equation and simulations from a Lagrangian random walk model. An application to Sepetiba Bay, Brazil is included to demonstrate the method with complex flows and topography.

Bayesian modeling of measurement error in predictor variables

NARCIS (Netherlands)

Fox, Gerardus J.A.; Glas, Cornelis A.W.

2003-01-01

It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between

Hierarchically Nanostructured Transition Metal Oxides for Lithium‐Ion Batteries

Science.gov (United States)

Zheng, Mingbo; Tang, Hao; Li, Lulu; Hu, Qin; Zhang, Li; Xue, Huaiguo

2018-01-01

Abstract Lithium‐ion batteries (LIBs) have been widely used in the field of portable electric devices because of their high energy density and long cycling life. To further improve the performance of LIBs, it is of great importance to develop new electrode materials. Various transition metal oxides (TMOs) have been extensively investigated as electrode materials for LIBs. According to the reaction mechanism, there are mainly two kinds of TMOs, one is based on conversion reaction and the other is based on intercalation/deintercalation reaction. Recently, hierarchically nanostructured TMOs have become a hot research area in the field of LIBs. Hierarchical architecture can provide numerous accessible electroactive sites for redox reactions, shorten the diffusion distance of Li‐ion during the reaction, and accommodate volume expansion during cycling. With rapid research progress in this field, a timely account of this advanced technology is highly necessary. Here, the research progress on the synthesis methods, morphological characteristics, and electrochemical performances of hierarchically nanostructured TMOs for LIBs is summarized and discussed. Some relevant prospects are also proposed. PMID:29593962

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Clinical time series prediction: towards a hierarchical dynamical system framework

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2014-01-01

Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

A top-down approach for fabricating free-standing bio-carbon supercapacitor electrodes with a hierarchical structure.

Science.gov (United States)

Li, Yingzhi; Zhang, Qinghua; Zhang, Junxian; Jin, Lei; Zhao, Xin; Xu, Ting

2015-09-23

Biomass has delicate hierarchical structures, which inspired us to develop a cost-effective route to prepare electrode materials with rational nanostructures for use in high-performance storage devices. Here, we demonstrate a novel top-down approach for fabricating bio-carbon materials with stable structures and excellent diffusion pathways; this approach is based on carbonization with controlled chemical activation. The developed free-standing bio-carbon electrode exhibits a high specific capacitance of 204 F g(-1) at 1 A g(-1); good rate capability, as indicated by the residual initial capacitance of 85.5% at 10 A g(-1); and a long cycle life. These performance characteristics are attributed to the outstanding hierarchical structures of the electrode material. Appropriate carbonization conditions enable the bio-carbon materials to inherit the inherent hierarchical texture of the original biomass, thereby facilitating effective channels for fast ion transfer. The macropores and mesopores that result from chemical activation significantly increase the specific surface area and also play the role of temporary ion-buffering reservoirs, further shortening the ionic diffusion distance.

Facile preparation of hierarchically porous polymer microspheres for superhydrophobic coating

Science.gov (United States)

Gao, Jiefeng; Wong, Julia Shuk-Ping; Hu, Mingjun; Li, Wan; Li, Robert. K. Y.

2013-12-01

A facile method, i.e., nonsolvent assisted electrospraying, is proposed to fabricate hierarchically porous microspheres. The pore size on the microsphere surface ranges from a few tens to several hundred nanometers. Thermally and nonsolvent induced phase separation as well as breath figure is responsible for the formation of the hierarchical structures with different nano-sized pores. The nonsolvent could not only induce phase separation, but also stabilize the interface between the droplet and air, which can prevent the droplet from strong deformation, and is therefore beneficial to the formation of regular and uniform microspheres. On the other hand, solvent evaporation, polymer diffusion and Coulomb fission during electrospraying influence the morphology of finally obtained products. In this paper, the influence of polymer concentration, the weight ratio between nonsolvent and polymer and the flowing rate on the morphology of the porous microsphere is carefully studied. The hierarchically porous microsphere significantly increases the surface roughness and thus the hydrophobicity, and the contact angle can reach as high as 152.2 +/- 1.2°. This nonsolvent assisted electrospraying opens a new way to fabricate superhydrophobic coating materials.A facile method, i.e., nonsolvent assisted electrospraying, is proposed to fabricate hierarchically porous microspheres. The pore size on the microsphere surface ranges from a few tens to several hundred nanometers. Thermally and nonsolvent induced phase separation as well as breath figure is responsible for the formation of the hierarchical structures with different nano-sized pores. The nonsolvent could not only induce phase separation, but also stabilize the interface between the droplet and air, which can prevent the droplet from strong deformation, and is therefore beneficial to the formation of regular and uniform microspheres. On the other hand, solvent evaporation, polymer diffusion and Coulomb fission during

Diffusion of Zonal Variables Using Node-Centered Diffusion Solver

Energy Technology Data Exchange (ETDEWEB)

Yang, T B

2007-08-06

Tom Kaiser [1] has done some preliminary work to use the node-centered diffusion solver (originally developed by T. Palmer [2]) in Kull for diffusion of zonal variables such as electron temperature. To avoid numerical diffusion, Tom used a scheme developed by Shestakov et al. [3] and found their scheme could, in the vicinity of steep gradients, decouple nearest-neighbor zonal sub-meshes leading to 'alternating-zone' (red-black mode) errors. Tom extended their scheme to couple the sub-meshes with appropriate chosen artificial diffusion and thereby solved the 'alternating-zone' problem. Because the choice of the artificial diffusion coefficient could be very delicate, it is desirable to use a scheme that does not require the artificial diffusion but still able to avoid both numerical diffusion and the 'alternating-zone' problem. In this document we present such a scheme.

Hierarchical models for informing general biomass equations with felled tree data

Science.gov (United States)

Brian J. Clough; Matthew B. Russell; Christopher W. Woodall; Grant M. Domke; Philip J. Radtke

2015-01-01

We present a hierarchical framework that uses a large multispecies felled tree database to inform a set of general models for predicting tree foliage biomass, with accompanying uncertainty, within the FIA database. Results suggest significant prediction uncertainty for individual trees and reveal higher errors when predicting foliage biomass for larger trees and for...

On the Design of Error-Correcting Ciphers

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Mathur Chetan Nanjunda

2006-01-01

Full Text Available Securing transmission over a wireless network is especially challenging, not only because of the inherently insecure nature of the medium, but also because of the highly error-prone nature of the wireless environment. In this paper, we take a joint encryption-error correction approach to ensure secure and robust communication over the wireless link. In particular, we design an error-correcting cipher (called the high diffusion cipher and prove bounds on its error-correcting capacity as well as its security. Towards this end, we propose a new class of error-correcting codes (HD-codes with built-in security features that we use in the diffusion layer of the proposed cipher. We construct an example, 128-bit cipher using the HD-codes, and compare it experimentally with two traditional concatenated systems: (a AES (Rijndael followed by Reed-Solomon codes, (b Rijndael followed by convolutional codes. We show that the HD-cipher is as resistant to linear and differential cryptanalysis as the Rijndael. We also show that any chosen plaintext attack that can be performed on the HD cipher can be transformed into a chosen plaintext attack on the Rijndael cipher. In terms of error correction capacity, the traditional systems using Reed-Solomon codes are comparable to the proposed joint error-correcting cipher and those that use convolutional codes require more data expansion in order to achieve similar error correction as the HD-cipher. The original contributions of this work are (1 design of a new joint error-correction-encryption system, (2 design of a new class of algebraic codes with built-in security criteria, called the high diffusion codes (HD-codes for use in the HD-cipher, (3 mathematical properties of these codes, (4 methods for construction of the codes, (5 bounds on the error-correcting capacity of the HD-cipher, (6 mathematical derivation of the bound on resistance of HD cipher to linear and differential cryptanalysis, (7 experimental comparison

Synthesis of hierarchical porous materials with ZSM-5 structures via template-free sol–gel method

Directory of Open Access Journals (Sweden)

Wei Han et al

2007-01-01

Full Text Available Interests are focused on preparation of hierarchical porous materials with zeolite structures by using soft or rigid templates in order to solve diffusion and mass transfer limitations resulting from the small pore sizes of zeolites. Here we develop a convenient template-free sol–gel method to synthesize hierarchical porous materials with ZSM-5 structures. This method involves hydrothermal recrystallization of the xerogel converted from uniform ZSM-5 sol by a vacuum drying process. By utilizing this method we can manipulate the size of zeolite nanocrystals as building units of porous structures based on controlling temperature of recrystallization, consequently obtain hierarchical porous materials with different intercrystalline pore sizes and ZSM-5 structures.

Diffuse solar radiation estimation models for Turkey's big cities

International Nuclear Information System (INIS)

Ulgen, Koray; Hepbasli, Arif

2009-01-01

literature in terms of the widely used statistical indicators, namely; the relative percentage error (E), coefficient of determination (R 2 ), the mean percentage error (MPE), the mean absolute percentage error (MAPE), the sum of the squares of relative errors (SSRE), the relative standard error (RSE), the mean bias error (MBE), the root mean square error (RMSE), and the t-statistic (t-stat) method combining the last two errors. It may be concluded that the new models predict the values of cloudness index (K d ) and diffuse coefficient (K dd ) as a function of clearness index (K T ) and sunshine fraction (S/S o ) for three big cities in Turkey better than other available models, while all the models tested appear to be location independent models for diffuse radiation predictions, at least for three big cities in Turkey. It is also expected that the models reviewed and developed will be beneficial to everyone involved or interested in the design and study of solar energy

Error Decomposition and Adaptivity for Response Surface Approximations from PDEs with Parametric Uncertainty

KAUST Repository

Bryant, C. M.; Prudhomme, S.; Wildey, T.

2015-01-01

In this work, we investigate adaptive approaches to control errors in response surface approximations computed from numerical approximations of differential equations with uncertain or random data and coefficients. The adaptivity of the response surface approximation is based on a posteriori error estimation, and the approach relies on the ability to decompose the a posteriori error estimate into contributions from the physical discretization and the approximation in parameter space. Errors are evaluated in terms of linear quantities of interest using adjoint-based methodologies. We demonstrate that a significant reduction in the computational cost required to reach a given error tolerance can be achieved by refining the dominant error contributions rather than uniformly refining both the physical and stochastic discretization. Error decomposition is demonstrated for a two-dimensional flow problem, and adaptive procedures are tested on a convection-diffusion problem with discontinuous parameter dependence and a diffusion problem, where the diffusion coefficient is characterized by a 10-dimensional parameter space.

On progress of the solution of the stationary 2-dimensional neutron diffusion equation: a polynomial approximation method with error analysis

International Nuclear Information System (INIS)

Ceolin, C.; Schramm, M.; Bodmann, B.E.J.; Vilhena, M.T.

2015-01-01

Recently the stationary neutron diffusion equation in heterogeneous rectangular geometry was solved by the expansion of the scalar fluxes in polynomials in terms of the spatial variables (x; y), considering the two-group energy model. The focus of the present discussion consists in the study of an error analysis of the aforementioned solution. More specifically we show how the spatial subdomain segmentation is related to the degree of the polynomial and the Lipschitz constant. This relation allows to solve the 2-D neutron diffusion problem for second degree polynomials in each subdomain. This solution is exact at the knots where the Lipschitz cone is centered. Moreover, the solution has an analytical representation in each subdomain with supremum and infimum functions that shows the convergence of the solution. We illustrate the analysis with a selection of numerical case studies. (author)

On progress of the solution of the stationary 2-dimensional neutron diffusion equation: a polynomial approximation method with error analysis

Energy Technology Data Exchange (ETDEWEB)

Ceolin, C., E-mail: celina.ceolin@gmail.com [Universidade Federal de Santa Maria (UFSM), Frederico Westphalen, RS (Brazil). Centro de Educacao Superior Norte; Schramm, M.; Bodmann, B.E.J.; Vilhena, M.T., E-mail: celina.ceolin@gmail.com [Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Engenharia Mecanica

2015-07-01

Recently the stationary neutron diffusion equation in heterogeneous rectangular geometry was solved by the expansion of the scalar fluxes in polynomials in terms of the spatial variables (x; y), considering the two-group energy model. The focus of the present discussion consists in the study of an error analysis of the aforementioned solution. More specifically we show how the spatial subdomain segmentation is related to the degree of the polynomial and the Lipschitz constant. This relation allows to solve the 2-D neutron diffusion problem for second degree polynomials in each subdomain. This solution is exact at the knots where the Lipschitz cone is centered. Moreover, the solution has an analytical representation in each subdomain with supremum and infimum functions that shows the convergence of the solution. We illustrate the analysis with a selection of numerical case studies. (author)

Error diffusion applied to the manipulation of liquid-crystal display subpixels

Science.gov (United States)

Dallas, William J.; Fan, Jiahua; Roehrig, Hans; Krupinski, Elizabeth A.

2004-05-01

Flat-panel displays based on liquid crystal technology are becoming widely used in the medical imaging arena. Despite the impressive capabilities of presently-existing panels, some medical images push their boundaries. We are working with mammograms that contain up to 4800 x 6400 14-bit pixels. Stated differently, these images contain 30 mega-pixels each. In the standard environment, for film viewing, the mammograms are hung four-up, i.e. four images are located side by side. Because many of the LCD panels used for monochrome display of medical images are based on color models, the pixels of the panels are divided into sub-pixels. These sub-pixels vary in their numbers and in the degrees of independence. Manufacturers have used both spatial and temporal modulation of these sub-pixels to improve the quality of images presented by the monitors. In this presentation we show how the sub-pixel structure of some present and future displays can be used to attain higher spatial resolution than the full-pixel resolution specification would suggest while also providing increased contrast resolution. The error diffusion methods we discuss provide a natural way of controlling sub-pixels and implementing trade-offs. In smooth regions of the image contrast resolution can maximized. In rapidly-varying regions of the image spatial resolution can be favored.

[Analysis of intrusion errors in free recall].

Science.gov (United States)

Diesfeldt, H F A

2017-06-01

Extra-list intrusion errors during five trials of the eight-word list-learning task of the Amsterdam Dementia Screening Test (ADST) were investigated in 823 consecutive psychogeriatric patients (87.1% suffering from major neurocognitive disorder). Almost half of the participants (45.9%) produced one or more intrusion errors on the verbal recall test. Correct responses were lower when subjects made intrusion errors, but learning slopes did not differ between subjects who committed intrusion errors and those who did not so. Bivariate regression analyses revealed that participants who committed intrusion errors were more deficient on measures of eight-word recognition memory, delayed visual recognition and tests of executive control (the Behavioral Dyscontrol Scale and the ADST-Graphical Sequences as measures of response inhibition). Using hierarchical multiple regression, only free recall and delayed visual recognition retained an independent effect in the association with intrusion errors, such that deficient scores on tests of episodic memory were sufficient to explain the occurrence of intrusion errors. Measures of inhibitory control did not add significantly to the explanation of intrusion errors in free recall, which makes insufficient strength of memory traces rather than a primary deficit in inhibition the preferred account for intrusion errors in free recall.

A Hierarchical Approach Using Machine Learning Methods in Solar Photovoltaic Energy Production Forecasting

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Zhaoxuan Li

2016-01-01

Full Text Available We evaluate and compare two common methods, artificial neural networks (ANN and support vector regression (SVR, for predicting energy productions from a solar photovoltaic (PV system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used in this work corresponds to 15 min averaged power measurements collected from 2014. The accuracy of the model is determined using computing error statistics such as mean bias error (MBE, mean absolute error (MAE, root mean square error (RMSE, relative MBE (rMBE, mean percentage error (MPE and relative RMSE (rRMSE. This work provides findings on how forecasts from individual inverters will improve the total solar power generation forecast of the PV system.

A reward optimization method based on action subrewards in hierarchical reinforcement learning.

Science.gov (United States)

Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming

2014-01-01

Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.

A Hierarchically Micro-Meso-Macroporous Zeolite CaA for Methanol Conversion to Dimethyl Ether

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Yan Wang

2016-11-01

Full Text Available A hierarchical zeolite CaA with microporous, mesoporous and macroporous structure was hydrothermally synthesized by a ”Bond-Blocking” method using organo-functionalized mesoporous silica (MS as a silica source. The characterization by XRD, SEM/TEM and N2 adsorption/desorption techniques showed that the prepared material had well-crystalline zeolite Linde Type A (LTA topological structure, microspherical particle morphologies, and hierarchically intracrystalline micro-meso-macropores structure. With the Bond-Blocking principle, the external surface area and macro-mesoporosity of the hierarchical zeolite CaA can be adjusted by varying the organo-functionalized degree of the mesoporous silica surface. Similarly, the distribution of the micro-meso-macroporous structure in the zeolite CaA can be controlled purposely. Compared with the conventional microporous zeolite CaA, the hierarchical zeolite CaA as a catalyst in the conversion of methanol to dimethyl ether (DME, exhibited complete DME selectivity and stable catalytic activity with high methanol conversion. The catalytic performances of the hierarchical zeolite CaA results clearly from the micro-meso-macroporous structure, improving diffusion properties, favoring the access to the active surface and avoiding secondary reactions (no hydrocarbon products were detected after 3 h of reaction.

Optimization of Hierarchical Modulation for Use of Scalable Media

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Heneghan Conor

2010-01-01

Full Text Available This paper studies the Hierarchical Modulation, a transmission strategy of the approaching scalable multimedia over frequency-selective fading channel for improving the perceptible quality. An optimization strategy for Hierarchical Modulation and convolutional encoding, which can achieve the target bit error rates with minimum global signal-to-noise ratio in a single-user scenario, is suggested. This strategy allows applications to make a free choice of relationship between Higher Priority (HP and Lower Priority (LP stream delivery. The similar optimization can be used in multiuser scenario. An image transport task and a transport task of an H.264/MPEG4 AVC video embedding both QVGA and VGA resolutions are simulated as the implementation example of this optimization strategy, and demonstrate savings in SNR and improvement in Peak Signal-to-Noise Ratio (PSNR for the particular examples shown.

Anisotropic mesh adaptation for solution of finite element problems using hierarchical edge-based error estimates

Energy Technology Data Exchange (ETDEWEB)

Lipnikov, Konstantin [Los Alamos National Laboratory; Agouzal, Abdellatif [UNIV DE LYON; Vassilevski, Yuri [Los Alamos National Laboratory

2009-01-01

We present a new technology for generating meshes minimizing the interpolation and discretization errors or their gradients. The key element of this methodology is construction of a space metric from edge-based error estimates. For a mesh with N{sub h} triangles, the error is proportional to N{sub h}{sup -1} and the gradient of error is proportional to N{sub h}{sup -1/2} which are optimal asymptotics. The methodology is verified with numerical experiments.

Estimation of diffuse from measured global solar radiation

International Nuclear Information System (INIS)

Moriarty, W.W.

1991-01-01

A data set of quality controlled radiation observations from stations scattered throughout Australia was formed and further screened to remove residual doubtful observations. It was then divided into groups by solar elevation, and used to find average relationships for each elevation group between relative global radiation (clearness index - the measured global radiation expressed as a proportion of the radiation on a horizontal surface at the top of the atmosphere) and relative diffuse radiation. Clear-cut relationships were found, which were then fitted by polynomial expressions giving the relative diffuse radiation as a function of relative global radiation and solar elevation. When these expressions were used to estimate the diffuse radiation from the global, the results had a slightly smaller spread of errors than those from an earlier technique given by Spencer. It was found that the errors were related to cloud amount, and further relationships were developed giving the errors as functions of global radiation, solar elevation, and the fraction of sky obscured by high cloud and by opaque (low and middle level) cloud. When these relationships were used to adjust the first estimates of diffuse radiation, there was a considerable reduction in the number of large errors

Final Report of Optimization Algorithms for Hierarchical Problems, with Applications to Nanoporous Materials

Energy Technology Data Exchange (ETDEWEB)

Nash, Stephen G.

2013-11-11

The research focuses on the modeling and optimization of nanoporous materials. In systems with hierarchical structure that we consider, the physics changes as the scale of the problem is reduced and it can be important to account for physics at the fine level to obtain accurate approximations at coarser levels. For example, nanoporous materials hold promise for energy production and storage. A significant issue is the fabrication of channels within these materials to allow rapid diffusion through the material. One goal of our research is to apply optimization methods to the design of nanoporous materials. Such problems are large and challenging, with hierarchical structure that we believe can be exploited, and with a large range of important scales, down to atomistic. This requires research on large-scale optimization for systems that exhibit different physics at different scales, and the development of algorithms applicable to designing nanoporous materials for many important applications in energy production, storage, distribution, and use. Our research has two major research thrusts. The first is hierarchical modeling. We plan to develop and study hierarchical optimization models for nanoporous materials. The models have hierarchical structure, and attempt to balance the conflicting aims of model fidelity and computational tractability. In addition, we analyze the general hierarchical model, as well as the specific application models, to determine their properties, particularly those properties that are relevant to the hierarchical optimization algorithms. The second thrust was to develop, analyze, and implement a class of hierarchical optimization algorithms, and apply them to the hierarchical models we have developed. We adapted and extended the optimization-based multigrid algorithms of Lewis and Nash to the optimization models exemplified by the hierarchical optimization model. This class of multigrid algorithms has been shown to be a powerful tool for

Improved diffusion coefficients generated from Monte Carlo codes

International Nuclear Information System (INIS)

Herman, B. R.; Forget, B.; Smith, K.; Aviles, B. N.

2013-01-01

Monte Carlo codes are becoming more widely used for reactor analysis. Some of these applications involve the generation of diffusion theory parameters including macroscopic cross sections and diffusion coefficients. Two approximations used to generate diffusion coefficients are assessed using the Monte Carlo code MC21. The first is the method of homogenization; whether to weight either fine-group transport cross sections or fine-group diffusion coefficients when collapsing to few-group diffusion coefficients. The second is a fundamental approximation made to the energy-dependent P1 equations to derive the energy-dependent diffusion equations. Standard Monte Carlo codes usually generate a flux-weighted transport cross section with no correction to the diffusion approximation. Results indicate that this causes noticeable tilting in reconstructed pin powers in simple test lattices with L2 norm error of 3.6%. This error is reduced significantly to 0.27% when weighting fine-group diffusion coefficients by the flux and applying a correction to the diffusion approximation. Noticeable tilting in reconstructed fluxes and pin powers was reduced when applying these corrections. (authors)

Numerical analysis of a neural network with hierarchically organized patterns

International Nuclear Information System (INIS)

Bacci, Silvia; Wiecko, Cristina; Parga, Nestor

1988-01-01

A numerical analysis of the retrieval behaviour of an associative memory model where the memorized patterns are stored hierarchically is performed. It is found that the model is able to categorize errors. For a finite number of categories, these are retrieved correctly even when the stored patterns are not. Instead, when they are allowed to increase with the number of neurons, their retrieval quality deteriorates above a critical category capacity. (Author)

Hierarchical regular small-world networks

International Nuclear Information System (INIS)

Boettcher, Stefan; Goncalves, Bruno; Guclu, Hasan

2008-01-01

Two new networks are introduced that resemble small-world properties. These networks are recursively constructed but retain a fixed, regular degree. They possess a unique one-dimensional lattice backbone overlaid by a hierarchical sequence of long-distance links, mixing real-space and small-world features. Both networks, one 3-regular and the other 4-regular, lead to distinct behaviors, as revealed by renormalization group studies. The 3-regular network is planar, has a diameter growing as √N with system size N, and leads to super-diffusion with an exact, anomalous exponent d w = 1.306..., but possesses only a trivial fixed point T c = 0 for the Ising ferromagnet. In turn, the 4-regular network is non-planar, has a diameter growing as ∼2 √(log 2 N 2 ) , exhibits 'ballistic' diffusion (d w = 1), and a non-trivial ferromagnetic transition, T c > 0. It suggests that the 3-regular network is still quite 'geometric', while the 4-regular network qualifies as a true small world with mean-field properties. As an engineering application we discuss synchronization of processors on these networks. (fast track communication)

Applications of hierarchically structured porous materials from energy storage and conversion, catalysis, photocatalysis, adsorption, separation, and sensing to biomedicine.

Science.gov (United States)

Sun, Ming-Hui; Huang, Shao-Zhuan; Chen, Li-Hua; Li, Yu; Yang, Xiao-Yu; Yuan, Zhong-Yong; Su, Bao-Lian

2016-06-13

Over the last decade, significant effort has been devoted to the applications of hierarchically structured porous materials owing to their outstanding properties such as high surface area, excellent accessibility to active sites, and enhanced mass transport and diffusion. The hierarchy of porosity, structural, morphological and component levels in these materials is key for their high performance in all kinds of applications. The introduction of hierarchical porosity into materials has led to a significant improvement in the performance of materials. Herein, recent progress in the applications of hierarchically structured porous materials from energy conversion and storage, catalysis, photocatalysis, adsorption, separation, and sensing to biomedicine is reviewed. Their potential future applications are also highlighted. We particularly dwell on the relationship between hierarchically porous structures and properties, with examples of each type of hierarchically structured porous material according to its chemical composition and physical characteristics. The present review aims to open up a new avenue to guide the readers to quickly obtain in-depth knowledge of applications of hierarchically porous materials and to have a good idea about selecting and designing suitable hierarchically porous materials for a specific application. In addition to focusing on the applications of hierarchically porous materials, this comprehensive review could stimulate researchers to synthesize new advanced hierarchically porous solids.

Non-Archimedean reaction-ultradiffusion equations and complex hierarchic systems

Science.gov (United States)

Zúñiga-Galindo, W. A.

2018-06-01

We initiate the study of non-Archimedean reaction-ultradiffusion equations and their connections with models of complex hierarchic systems. From a mathematical perspective, the equations studied here are the p-adic counterpart of the integro-differential models for phase separation introduced by Bates and Chmaj. Our equations are also generalizations of the ultradiffusion equations on trees studied in the 1980s by Ogielski, Stein, Bachas, Huberman, among others, and also generalizations of the master equations of the Avetisov et al models, which describe certain complex hierarchic systems. From a physical perspective, our equations are gradient flows of non-Archimedean free energy functionals and their solutions describe the macroscopic density profile of a bistable material whose space of states has an ultrametric structure. Some of our results are p-adic analogs of some well-known results in the Archimedean setting, however, the mechanism of diffusion is completely different due to the fact that it occurs in an ultrametric space.

Towards a systematic assessment of errors in diffusion Monte Carlo calculations of semiconductors: Case study of zinc selenide and zinc oxide

Energy Technology Data Exchange (ETDEWEB)

Yu, Jaehyung [Department of Mechanical Science and Engineering, 1206 W Green Street, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Wagner, Lucas K. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Ertekin, Elif, E-mail: ertekin@illinois.edu [Department of Mechanical Science and Engineering, 1206 W Green Street, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); International Institute for Carbon Neutral Energy Research - WPI-I" 2CNER, Kyushu University, 744 Moto-oka, Nishi-ku, Fukuoka 819-0395 (Japan)

2015-12-14

The fixed node diffusion Monte Carlo (DMC) method has attracted interest in recent years as a way to calculate properties of solid materials with high accuracy. However, the framework for the calculation of properties such as total energies, atomization energies, and excited state energies is not yet fully established. Several outstanding questions remain as to the effect of pseudopotentials, the magnitude of the fixed node error, and the size of supercell finite size effects. Here, we consider in detail the semiconductors ZnSe and ZnO and carry out systematic studies to assess the magnitude of the energy differences arising from controlled and uncontrolled approximations in DMC. The former include time step errors and supercell finite size effects for ground and optically excited states, and the latter include pseudopotentials, the pseudopotential localization approximation, and the fixed node approximation. We find that for these compounds, the errors can be controlled to good precision using modern computational resources and that quantum Monte Carlo calculations using Dirac-Fock pseudopotentials can offer good estimates of both cohesive energy and the gap of these systems. We do however observe differences in calculated optical gaps that arise when different pseudopotentials are used.

Hierarchical Co-based Porous Layered Double Hydroxide Arrays Derived via Alkali Etching for High-performance Supercapacitors

Science.gov (United States)

Abushrenta, Nasser; Wu, Xiaochao; Wang, Junnan; Liu, Junfeng; Sun, Xiaoming

2015-08-01

Hierarchical nanoarchitecture and porous structure can both provide advantages for improving the electrochemical performance in energy storage electrodes. Here we report a novel strategy to synthesize new electrode materials, hierarchical Co-based porous layered double hydroxide (PLDH) arrays derived via alkali etching from Co(OH)2@CoAl LDH nanoarrays. This structure not only has the benefits of hierarchical nanoarrays including short ion diffusion path and good charge transport, but also possesses a large contact surface area owing to its porous structure which lead to a high specific capacitance (23.75 F cm-2 or 1734 F g-1 at 5 mA cm-2) and excellent cycling performance (over 85% after 5000 cycles). The enhanced electrode material is a promising candidate for supercapacitors in future application.

Construction of hierarchically porous metal-organic frameworks through linker labilization

Science.gov (United States)

Yuan, Shuai; Zou, Lanfang; Qin, Jun-Sheng; Li, Jialuo; Huang, Lan; Feng, Liang; Wang, Xuan; Bosch, Mathieu; Alsalme, Ali; Cagin, Tahir; Zhou, Hong-Cai

2017-05-01

A major goal of metal-organic framework (MOF) research is the expansion of pore size and volume. Although many approaches have been attempted to increase the pore size of MOF materials, it is still a challenge to construct MOFs with precisely customized pore apertures for specific applications. Herein, we present a new method, namely linker labilization, to increase the MOF porosity and pore size, giving rise to hierarchical-pore architectures. Microporous MOFs with robust metal nodes and pro-labile linkers were initially synthesized. The mesopores were subsequently created as crystal defects through the splitting of a pro-labile-linker and the removal of the linker fragments by acid treatment. We demonstrate that linker labilization method can create controllable hierarchical porous structures in stable MOFs, which facilitates the diffusion and adsorption process of guest molecules to improve the performances of MOFs in adsorption and catalysis.

Hierarchical Threshold Adaptive for Point Cloud Filter Algorithm of Moving Surface Fitting

Directory of Open Access Journals (Sweden)

ZHU Xiaoxiao

2018-02-01

Full Text Available In order to improve the accuracy,efficiency and adaptability of point cloud filtering algorithm,a hierarchical threshold adaptive for point cloud filter algorithm of moving surface fitting was proposed.Firstly,the noisy points are removed by using a statistic histogram method.Secondly,the grid index is established by grid segmentation,and the surface equation is set up through the lowest point among the neighborhood grids.The real height and fit are calculated.The difference between the elevation and the threshold can be determined.Finally,in order to improve the filtering accuracy,hierarchical filtering is used to change the grid size and automatically set the neighborhood size and threshold until the filtering result reaches the accuracy requirement.The test data provided by the International Photogrammetry and Remote Sensing Society (ISPRS is used to verify the algorithm.The first and second error and the total error are 7.33%,10.64% and 6.34% respectively.The algorithm is compared with the eight classical filtering algorithms published by ISPRS.The experiment results show that the method has well-adapted and it has high accurate filtering result.

Hierarchically structured photonic crystals for integrated chemical separation and colorimetric detection.

Science.gov (United States)

Fu, Qianqian; Zhu, Biting; Ge, Jianping

2017-02-16

A SiO 2 colloidal photonic crystal film with a hierarchical porous structure is fabricated to demonstrate an integrated separation and colorimetric detection of chemical species for the first time. This new photonic crystal based thin layer chromatography process requires no dyeing, developing and UV irradiation compared to the traditional TLC. The assembling of mesoporous SiO 2 particles via a supersaturation-induced-precipitation process forms uniform and hierarchical photonic crystals with micron-scale cracks and mesopores, which accelerate the diffusion of developers and intensify the adsorption/desorption between the analytes and silica for efficient separation. Meanwhile, the chemical substances infiltrated to the voids of photonic crystals cause an increase of the refractive index and a large contrast of structural colors towards the unloaded part, so that the sample spots can be directly recognized with the naked eye before and after separation.

MOF-5 decorated hierarchical ZnO nanorod arrays and its photoluminescence

Science.gov (United States)

Zhang, Yinmin; Lan, Ding; Wang, Yuren; Cao, He; Jiang, Heng

2011-04-01

The strategy to manipulate nanoscale materials into well-organized hierarchical architectures is very important to both material synthesis and nanodevice applications. Here, nanoscale MOF-5 crystallites were successfully fabricated onto ordered hierarchical ZnO arrays based on aqueous chemical synthesis and molecule self-assembly technology guided room temperature diffusion method, which has the advantages of energy saving and simple operation. The structures and morphologies of the samples were performed by X-ray powder diffraction and field emission scanning electronic microscopy. The MOF-5 crystallites have good quality and bind well to the hexagonal-patterned ZnO arrays. The photoluminescence spectrum shows that the emission of hybrid MOF-5-ZnO films displays a blue shift in green emission and intensity reduction in UV emission. This ordered hybrid semiconductor material is expected to exploit the great potentiality in sensors, micro/nanodevices, and screen displays.

Social Influence on Information Technology Adoption and Sustained Use in Healthcare: A Hierarchical Bayesian Learning Method Analysis

Science.gov (United States)

Hao, Haijing

2013-01-01

Information technology adoption and diffusion is currently a significant challenge in the healthcare delivery setting. This thesis includes three papers that explore social influence on information technology adoption and sustained use in the healthcare delivery environment using conventional regression models and novel hierarchical Bayesian…

Hierarchical optimal control of large-scale nonlinear chemical processes.

Science.gov (United States)

Ramezani, Mohammad Hossein; Sadati, Nasser

2009-01-01

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

STP-LWE: A Variant of Learning with Error for a Flexible Encryption

Directory of Open Access Journals (Sweden)

Bo Gao

2014-01-01

Full Text Available We construct a flexible lattice based scheme based on semitensor product learning with errors (STP-LWE, which is a variant of learning with errors problem. We have proved that STP-LWE is hard when LWE is hard. Our scheme is proved to be secure against indistinguishable chosen message attacks, and it can achieve a balance between the security and efficiency in the hierarchical encryption systems. In addition, our scheme is almost as efficient as the dual encryption in GPV08.

Controlled synthesis of three-dimensional hierarchical Bi2WO6 microspheres with optimum photocatalytic activity

International Nuclear Information System (INIS)

Wang, Hong; Song, Jimei; Zhang, Hui; Gao, Fei; Zhao, Shaojuan; Hu, Haiqin

2012-01-01

Highlights: ► The synthesized method is very simple. It can be widely used in the production. ► The morphology is novel and the property is fine. ► The formation of 3D hierarchical microsphere can be induced by changing the concentration of KNO 3 . -- Abstract: Three-dimensional (3D) hierarchical Bi 2 WO 6 microsphere and octahedral Bi 2 WO 6 have been synthesized by a facile hydrothermal method using KNO 3 solution and distilled water as solvent, respectively. The obtained products were characterized by X-ray diffraction, scanning electron microscopy, N 2 adsorption/desorption, and UV–vis diffuse reflectance spectroscopy in detail. The concentration of KNO 3 played a key role in the formation of 3D hierarchical Bi 2 WO 6 microspheres. A possible formation mechanism of Bi 2 WO 6 microsphere was proposed. The photocatalytic activity of the as-synthesized products was evaluated by monitoring the degradation of MB solution under sunlight irradiation. It was found that the photocatalytic activity of the 3D hierarchical Bi 2 WO 6 microsphere was superior to the octahedral Bi 2 WO 6 , which was attributed to the larger surface area and special hierarchical structure of Bi 2 WO 6 microsphere.

An improved procedure for determining grain boundary diffusion coefficients from averaged concentration profiles

Science.gov (United States)

Gryaznov, D.; Fleig, J.; Maier, J.

2008-03-01

Whipple's solution of the problem of grain boundary diffusion and Le Claire's relation, which is often used to determine grain boundary diffusion coefficients, are examined for a broad range of ratios of grain boundary to bulk diffusivities Δ and diffusion times t. Different reasons leading to errors in determining the grain boundary diffusivity (DGB) when using Le Claire's relation are discussed. It is shown that nonlinearities of the diffusion profiles in lnCav-y6/5 plots and deviations from "Le Claire's constant" (-0.78) are the major error sources (Cav=averaged concentration, y =coordinate in diffusion direction). An improved relation (replacing Le Claire's constant) is suggested for analyzing diffusion profiles particularly suited for small diffusion lengths (short times) as often required in diffusion experiments on nanocrystalline materials.

Hierarchical CuO hollow microspheres: Controlled synthesis for enhanced lithium storage performance

International Nuclear Information System (INIS)

Guan Xiangfeng; Li Liping; Li Guangshe; Fu Zhengwei; Zheng Jing; Yan Tingjiang

2011-01-01

Graphical abstract: Hierarchical CuO microspheres with hollow interiors were formed through self-wrapping of a single layer of radically oriented CuO nanorods, and these microspheres showed excellent cycle performance and enhanced lithium storage capacity. Display Omitted Research highlights: → Hierarchical CuO hollow microspheres were prepared by a hydrothermal method. → The CuO hollow microspheres were assembled from radically oriented nanorods. → The growth mechanism was proposed to proceed via self-assembly and Ostwald's ripening. → The microspheres showed good cycle performance and enhanced lithium storage capacity. → Hierarchical microstructures with hollow interiors promote electrochemical property. - Abstract: In this work, hierarchical CuO hollow microspheres were hydrothermally prepared without use of any surfactants or templates. By controlling the formation reaction conditions and monitoring the relevant reaction processes using time-dependent experiments, it is demonstrated that hierarchical CuO microspheres with hollow interiors were formed through self-wrapping of a single layer of radically oriented CuO nanorods, and that hierarchical spheres could be tuned to show different morphologies and microstructures. As a consequence, the formation mechanism was proposed to proceed via a combined process of self-assembly and Ostwald's ripening. Further, these hollow microspheres were initiated as the anode material in lithium ion batteries, which showed excellent cycle performance and enhanced lithium storage capacity, most likely because of the synergetic effect of small diffusion lengths in building blocks of nanorods and proper void space that buffers the volume expansion. The strategy reported in this work is reproducible, which may help to significantly improve the electrochemical performance of transition metal oxide-based anode materials via designing the hollow structures necessary for developing lithium ion batteries and the relevant

Spatial Mapping of Translational Diffusion Coefficients Using Diffusion Tensor Imaging: A Mathematical Description.

Science.gov (United States)

Shetty, Anil N; Chiang, Sharon; Maletic-Savatic, Mirjana; Kasprian, Gregor; Vannucci, Marina; Lee, Wesley

2014-01-01

In this article, we discuss the theoretical background for diffusion weighted imaging and diffusion tensor imaging. Molecular diffusion is a random process involving thermal Brownian motion. In biological tissues, the underlying microstructures restrict the diffusion of water molecules, making diffusion directionally dependent. Water diffusion in tissue is mathematically characterized by the diffusion tensor, the elements of which contain information about the magnitude and direction of diffusion and is a function of the coordinate system. Thus, it is possible to generate contrast in tissue based primarily on diffusion effects. Expressing diffusion in terms of the measured diffusion coefficient (eigenvalue) in any one direction can lead to errors. Nowhere is this more evident than in white matter, due to the preferential orientation of myelin fibers. The directional dependency is removed by diagonalization of the diffusion tensor, which then yields a set of three eigenvalues and eigenvectors, representing the magnitude and direction of the three orthogonal axes of the diffusion ellipsoid, respectively. For example, the eigenvalue corresponding to the eigenvector along the long axis of the fiber corresponds qualitatively to diffusion with least restriction. Determination of the principal values of the diffusion tensor and various anisotropic indices provides structural information. We review the use of diffusion measurements using the modified Stejskal-Tanner diffusion equation. The anisotropy is analyzed by decomposing the diffusion tensor based on symmetrical properties describing the geometry of diffusion tensor. We further describe diffusion tensor properties in visualizing fiber tract organization of the human brain.

Flower-like hierarchical structures consisting of porous single-crystalline ZnO nanosheets and their gas sensing properties to volatile organic compounds (VOCs)

Energy Technology Data Exchange (ETDEWEB)

Meng, Fanli, E-mail: flmeng@iim.ac.cn [Research Center for Biomimetic Functional Materials and Sensing Devices, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 (China); Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095 (United States); Hou, Nannan [Research Center for Biomimetic Functional Materials and Sensing Devices, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 (China); Department of Chemistry, University of Science and Technology of China, Hefei 230026 (China); Ge, Sheng [Department of Mechanical and Automotive Engineering, Anhui Polytechnic University, Wuhu 241000 (China); Sun, Bai [Research Center for Biomimetic Functional Materials and Sensing Devices, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 (China); Jin, Zhen, E-mail: zjin@iim.ac.cn [Research Center for Biomimetic Functional Materials and Sensing Devices, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 (China); Shen, Wei; Kong, Lingtao; Guo, Zheng [Research Center for Biomimetic Functional Materials and Sensing Devices, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 (China); Sun, Yufeng, E-mail: sunyufeng118@126.com [Department of Mechanical and Automotive Engineering, Anhui Polytechnic University, Wuhu 241000 (China); Wu, Hao; Wang, Chen [Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095 (United States); Li, Minqiang [Research Center for Biomimetic Functional Materials and Sensing Devices, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 (China)

2015-03-25

Highlights: • Flower-like hierarchical structures consisting of porous single-crystalline ZnO nanosheets were synthesized. • The flower-like hierarchical structured ZnO exhibited higher response and shorter response and recovery times. • The sensing mechanism of the flower-like hierarchical has been systematically analyzed. - Abstract: Flower-like hierarchical structures consisting of porous single-crystalline ZnO nanosheets (FHPSCZNs) were synthesized by a one-pot wet-chemical method followed by an annealing treatment, which combined the advantages between flower-like hierarchical structure and porous single-crystalline structure. XRD, SEM and HRTEM were used to characterize the synthesized FHPSCZN samples. The sensing properties of the FHPSCZN sensor were also investigated by comparing with ZnO powder sensor, which exhibited higher response and shorter response and recovery times. The sensing mechanism of the FHPSCZN sensor has been further analyzed from the aspects of electronic transport and gas diffusion.

Flower-like hierarchical structures consisting of porous single-crystalline ZnO nanosheets and their gas sensing properties to volatile organic compounds (VOCs)

International Nuclear Information System (INIS)

Meng, Fanli; Hou, Nannan; Ge, Sheng; Sun, Bai; Jin, Zhen; Shen, Wei; Kong, Lingtao; Guo, Zheng; Sun, Yufeng; Wu, Hao; Wang, Chen; Li, Minqiang

2015-01-01

Highlights: • Flower-like hierarchical structures consisting of porous single-crystalline ZnO nanosheets were synthesized. • The flower-like hierarchical structured ZnO exhibited higher response and shorter response and recovery times. • The sensing mechanism of the flower-like hierarchical has been systematically analyzed. - Abstract: Flower-like hierarchical structures consisting of porous single-crystalline ZnO nanosheets (FHPSCZNs) were synthesized by a one-pot wet-chemical method followed by an annealing treatment, which combined the advantages between flower-like hierarchical structure and porous single-crystalline structure. XRD, SEM and HRTEM were used to characterize the synthesized FHPSCZN samples. The sensing properties of the FHPSCZN sensor were also investigated by comparing with ZnO powder sensor, which exhibited higher response and shorter response and recovery times. The sensing mechanism of the FHPSCZN sensor has been further analyzed from the aspects of electronic transport and gas diffusion

High-speed parallel solution of the neutron diffusion equation with the hierarchical domain decomposition boundary element method incorporating parallel communications

International Nuclear Information System (INIS)

Tsuji, Masashi; Chiba, Gou

2000-01-01

A hierarchical domain decomposition boundary element method (HDD-BEM) for solving the multiregion neutron diffusion equation (NDE) has been fully parallelized, both for numerical computations and for data communications, to accomplish a high parallel efficiency on distributed memory message passing parallel computers. Data exchanges between node processors that are repeated during iteration processes of HDD-BEM are implemented, without any intervention of the host processor that was used to supervise parallel processing in the conventional parallelized HDD-BEM (P-HDD-BEM). Thus, the parallel processing can be executed with only cooperative operations of node processors. The communication overhead was even the dominant time consuming part in the conventional P-HDD-BEM, and the parallelization efficiency decreased steeply with the increase of the number of processors. With the parallel data communication, the efficiency is affected only by the number of boundary elements assigned to decomposed subregions, and the communication overhead can be drastically reduced. This feature can be particularly advantageous in the analysis of three-dimensional problems where a large number of processors are required. The proposed P-HDD-BEM offers a promising solution to the deterioration problem of parallel efficiency and opens a new path to parallel computations of NDEs on distributed memory message passing parallel computers. (author)

Easy synthesis of hierarchical carbon spheres with superior capacitive performance in supercapacitors.

Science.gov (United States)

Huang, Xinhua; Kim, Seok; Heo, Min Seon; Kim, Ji Eun; Suh, Hongsuk; Kim, Il

2013-10-01

An easy template-free approach to the fabrication of pure carbon microspheres has been achieved via direct pyrolysis of as-prepared polyaromatic hydrocarbons including polynaphthalene and polypyrene. The polyaromatics were synthesized from aromatic hydrocarbons (AHCs) using anhydrous zinc chloride as the Friedel-Crafts catalyst and chloromethyl methyl ether as a cross-linker. The experimental results show that the methylene bridges between phenyl rings generate a hierarchical porous polyaromatic precursor to form three-dimensionally (3D) interconnected micro-, meso-, and macroporous networks during carbonization. These hierarchical porous carbon aggregates of spherical carbon spheres exhibit faster ion transport/diffusion behavior and increased surface area usage in electric double-layer capacitors. Furthermore, micropores are present in the 3D interconnected network inside the cross-linked AHC-based carbon microspheres, thus imparting an exceptionally large, electrochemically accessible surface area for charge accumulation.

Error characterization for asynchronous computations: Proxy equation approach

Science.gov (United States)

Sallai, Gabriella; Mittal, Ankita; Girimaji, Sharath

2017-11-01

Numerical techniques for asynchronous fluid flow simulations are currently under development to enable efficient utilization of massively parallel computers. These numerical approaches attempt to accurately solve time evolution of transport equations using spatial information at different time levels. The truncation error of asynchronous methods can be divided into two parts: delay dependent (EA) or asynchronous error and delay independent (ES) or synchronous error. The focus of this study is a specific asynchronous error mitigation technique called proxy-equation approach. The aim of this study is to examine these errors as a function of the characteristic wavelength of the solution. Mitigation of asynchronous effects requires that the asynchronous error be smaller than synchronous truncation error. For a simple convection-diffusion equation, proxy-equation error analysis identifies critical initial wave-number, λc. At smaller wave numbers, synchronous error are larger than asynchronous errors. We examine various approaches to increase the value of λc in order to improve the range of applicability of proxy-equation approach.

Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

KAUST Repository

Sang, Huiyan; Jun, Mikyoung; Huang, Jianhua Z.

2011-01-01

This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models

Facile synthesis of TiO2 hierarchical microspheres assembled by ultrathin nanosheets for dye-sensitized solar cells

International Nuclear Information System (INIS)

Xu, Fang; Zhang, Xuyan; Wu, Yao; Wu, Dapeng; Gao, Zhiyong; Jiang, Kai

2013-01-01

Highlights: •TiO 2 hierarchical spheres were prepared via one-pot solvothermal route. •TiO 2 hierarchical spheres based DSSCs shows a conversion efficiency of 5.56%. •The performance of DSSC is dependence of the thickness of photoanode. -- Abstract: TiO 2 hierarchical microspheres assembled by ultrathin nanosheets were prepared via solvothermal route for dye-sensitized solar cells (DSSCs). The performance of cells was investigated by diffuse and reflectance spectra, photocurrent–voltage measurement, incident-photon-to-current conversion efficiency and electrochemical impedance spectra. Photoanodes with different thickness of TiO 2 hierarchical spheres were studied, which proves that the photoanode with thickness of 15.9 μm exhibits higher performance (short-circuit current density of 12.36 mA cm −2 , open-circuit voltage of 0.73 mV, fill factor of 61.95, and conversion efficiency of 5.56%) than that of P25-based DSSC due to the excellent particle interconnections, low electron recombination and high specific surface area (78 m 2 g −1 )

Hierarchical Network Design

DEFF Research Database (Denmark)

Thomadsen, Tommy

2005-01-01

Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

Real depletion in nodal diffusion codes

International Nuclear Information System (INIS)

Petkov, P.T.

2002-01-01

The fuel depletion is described by more than one hundred fuel isotopes in the advanced lattice codes like HELIOS, but only a few fuel isotopes are accounted for even in the advanced steady-state diffusion codes. The general assumption that the number densities of the majority of the fuel isotopes depend only on the fuel burnup is seriously in error if high burnup is considered. The real depletion conditions in the reactor core differ from the asymptotic ones at the stage of lattice depletion calculations. This study reveals which fuel isotopes should be explicitly accounted for in the diffusion codes in order to predict adequately the real depletion effects in the core. A somewhat strange conclusion is that if the real number densities of the main fissionable isotopes are not explicitly accounted for in the diffusion code, then Sm-149 should not be accounted for either, because the net error in k-inf is smaller (Authors)

High-throughput ab-initio dilute solute diffusion database.

Science.gov (United States)

Wu, Henry; Mayeshiba, Tam; Morgan, Dane

2016-07-19

We demonstrate automated generation of diffusion databases from high-throughput density functional theory (DFT) calculations. A total of more than 230 dilute solute diffusion systems in Mg, Al, Cu, Ni, Pd, and Pt host lattices have been determined using multi-frequency diffusion models. We apply a correction method for solute diffusion in alloys using experimental and simulated values of host self-diffusivity. We find good agreement with experimental solute diffusion data, obtaining a weighted activation barrier RMS error of 0.176 eV when excluding magnetic solutes in non-magnetic alloys. The compiled database is the largest collection of consistently calculated ab-initio solute diffusion data in the world.

Two-step growth mechanism of supported Co3O4-based sea-urchin like hierarchical nanostructures

Science.gov (United States)

Maurizio, Chiara; Edla, Raju; Michieli, Niccolo'; Orlandi, Michele; Trapananti, Angela; Mattei, Giovanni; Miotello, Antonio

2018-05-01

Supported 3D hierarchical nanostructures of transition metal oxides exhibit enhanced photocatalytic performances and long-term stability under working conditions. The growth mechanisms crucially determine their intimate structure, that is a key element to optimize their properties. We report on the formation mechanism of supported Co3O4 hierarchical sea urchin-like nanostructured catalyst, starting from Co-O-B layers deposited by Pulsed Laser Deposition (PLD). The particles deposited on the layer surface, that constitute the seeds for the urchin formation, have been investigated after separation from the underneath deposited layer, by X-ray diffraction, X-ray absorption spectroscopy and scanning electron microscopy. The comparison with PLD deposited layers without O and/or B indicates a crucial role of B for the urchin formation that (i) limits Co oxidation during the deposition process and (ii) induces a chemical reduction of Co, especially in the particle core, in the first step of air annealing (2 h, 500 °C). After 2 h heating Co oxidation proceeds and Co atoms outdiffuse from the Co fcc particle core likely through fast diffusion channel present in the shell and form Co3O4 nano-needles. The growth of nano-needles from the layer beneath the particles is prevented by a faster Co oxidation and a minimum fraction of metallic Co. This investigation shows how diffusion mechanisms and chemical effects can be effectively coupled to obtain hierarchical structures of transition metal oxides.

Partitioning,Automation and Error Recovery in the Control and Monitoring System of an LHC Experiment

Institute of Scientific and Technical Information of China (English)

C.Gaspar

2001-01-01

The Joint Controls Project(JCOP)is a collaboration between CERN and the four LHC experiments to find and implement common solutions for their control and monitoring systems.As part of this project and Architecture Working Group was set up in order to study the requirements and devise an architectural model that would suit the four experiments.Many issues were studied by this working group:Alarm handling,Access Control,Hierarchical Control,etc.This paper will report on the specific issue of hierarchical control and in particular partitioning,automation and error recovery.

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

Science.gov (United States)

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

Semiparametric modeling: Correcting low-dimensional model error in parametric models

International Nuclear Information System (INIS)

Berry, Tyrus; Harlim, John

2016-01-01

In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consists of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.

Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates

Science.gov (United States)

Jakeman, J. D.; Wildey, T.

2015-01-01

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.

Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates

International Nuclear Information System (INIS)

Jakeman, J.D.; Wildey, T.

2015-01-01

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation

Rapid fabrication of hierarchically structured supramolecular nanocomposite thin films in one minute

Energy Technology Data Exchange (ETDEWEB)

Xu, Ting; Kao, Joseph

2016-11-08

Functional nanocomposites containing nanoparticles of different chemical compositions may exhibit new properties to meet demands for advanced technology. It is imperative to simultaneously achieve hierarchical structural control and to develop rapid, scalable fabrication to minimize degradation of nanoparticle properties and for compatibility with nanomanufacturing. The assembly kinetics of supramolecular nanocomposite in thin films is governed by the energetic cost arising from defects, the chain mobility, and the activation energy for inter-domain diffusion. By optimizing only one parameter, the solvent fraction in the film, the assembly kinetics can be precisely tailored to produce hierarchically structured thin films of supramolecular nanocomposites in approximately one minute. Moreover, the strong wavelength dependent optical anisotropy in the nanocomposite highlights their potential applications for light manipulation and information transmission. The present invention opens a new avenue in designing manufacture-friendly continuous processing for the fabrication of functional nanocomposite thin films.

In-situ preparation of Fe2O3 hierarchical arrays on stainless steel substrate for high efficient catalysis

International Nuclear Information System (INIS)

Yang, Zeheng; Wang, Kun; Shao, Zongming; Tian, Yuan; Chen, Gongde; Wang, Kai; Chen, Zhangxian; Dou, Yan; Zhang, Weixin

2017-01-01

Hierarchical array catalysts with micro/nano structures on substrates not only possess high reactivity from large surface area and suitable interface, but intensify mass transfer through shortening the diffusion paths of both reactants and products for high catalytic efficiency. Herein, we first demonstrate fabrication of Fe 2 O 3 hierarchical arrays grown on stainless-steel substrates via in-situ hydrothermal chemical oxidation followed by heat treatment in N 2 atmosphere. As a Fenton-like catalyst, Fe 2 O 3 hierarchical arrays exhibit excellent catalytic activity and life cycle performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H 2 O 2 . The Fe 2 O 3 catalyst with unique hierarchical structures and efficient transport channels, effectively activates H 2 O 2 to generate large quantity of • OH radicals and highly promotes reaction kinetics between MB and • OH radicals. Immobilization of hierarchical array catalysts on stainless-steel can prevent particles agglomeration, facilitate the recovery and reuse of the catalysts, which is expected promising applications in wastewater remediation. - Graphical abstract: The in-situ synthesis of Fe 2 O 3 hierarchical arrays on stainless-steel substrates was reported for the first time, which exhibit excellent catalytic activity performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H 2 O 2 . - Highlights: • Fe 2 O 3 hierarchical arrays was prepared by in-situ hydrothermal chemical oxidation. • F − ions play an important role in the formation of the Fe 2 O 3 hierarchical arrays. • Fe 2 O 3 hierarchical arrays show high catalytic activity to methylene blue degradation.

Analysis and correction of gradient nonlinearity bias in apparent diffusion coefficient measurements.

Science.gov (United States)

Malyarenko, Dariya I; Ross, Brian D; Chenevert, Thomas L

2014-03-01

Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10-20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Spatial dependence of nonlinearity correction terms accounts for the bulk (75-95%) of ADC bias for FA = 0.3-0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. Copyright © 2013 Wiley Periodicals, Inc.

Detecting Hierarchical Structure in Networks

DEFF Research Database (Denmark)

Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard

2012-01-01

Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose...... a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

Construction of 3D Arrays of Cylindrically Hierarchical Structures with ZnO Nanorods Hydrothermally Synthesized on Optical Fiber Cores

Directory of Open Access Journals (Sweden)

Weixuan Jing

2014-01-01

Full Text Available With ZnO nanorods hydrothermally synthesized on manually assembled arrays of optical fiber cores, 3D arrays of ZnO nanorod-based cylindrically hierarchical structures with nominal pitch 250 μm or 375 μm were constructed. Based on micrographs of scanning electron microscopy and image processing operators of MATLAB software, the 3D arrays of cylindrically hierarchical structures were quantitatively characterized. The values of the actual diameters, the actual pitches, and the parallelism errors suggest that the process capability of the manual assembling is sufficient and the quality of the 3D arrays of cylindrically hierarchical structures is acceptable. The values of the characteristic parameters such as roughness, skewness, kurtosis, correlation length, and power spectrum density show that the surface morphologies of the cylindrically hierarchical structures not only were affected significantly by Zn2+ concentration of the growth solution but also were anisotropic due to different curvature radii of the optical fiber core at side and front view.

Synthesis of hierarchical conductive C/LiFePO_4/carbon nanotubes composite with less antisite defects for high power lithium-ion batteries

International Nuclear Information System (INIS)

Song, Jianjun; Shao, Guangjie; Ma, Zhipeng; Wang, Guiling; Yang, Jing

2015-01-01

Graphical abstract: The hierarchical conductive C/LiFePO4/CNTs composite with less antisite defects is synthesized by a modified solvothemal process and delivers superior electrochemical performance with high rate capability and good capacity retention. - Abstract: The low electronic conductivity and Li ion diffusion ability are two major obstacles to realize its wide application for LiFePO_4 materials. The material with hierarchical conductive structure and lower antisite defects concentration can effectively enhance the electronic conductivity and Li ion diffusion ability. We firstly report here a modified solvothemal process for the fabrication of hierarchical conductive C/LiFePO_4/CNTs composite with less antisite defects. It is found that the modified solvothemal process is facilitated to decrease Fe_L_i antisite defects and enhance the electronic continuity between LFP and CNTs. In favor of its unique properties, the C/LFP/CNTs composites can deliver superior rate capability and cycling stability. Remarkably, even at a high rate of 20C (3400 mA g"−"1), a high initial discharge capacity of 91.6 mAh g"−"1 and good cycle retention of 95% with almost 100% coulombic efficiency are still obtained after 100 cycles.

Isotropic resolution diffusion tensor imaging of lumbosacral and sciatic nerves using a phase-corrected diffusion-prepared 3D turbo spin echo.

Science.gov (United States)

Cervantes, Barbara; Van, Anh T; Weidlich, Dominik; Kooijman, Hendrick; Hock, Andreas; Rummeny, Ernst J; Gersing, Alexandra; Kirschke, Jan S; Karampinos, Dimitrios C

2018-08-01

To perform in vivo isotropic-resolution diffusion tensor imaging (DTI) of lumbosacral and sciatic nerves with a phase-navigated diffusion-prepared (DP) 3D turbo spin echo (TSE) acquisition and modified reconstruction incorporating intershot phase-error correction and to investigate the improvement on image quality and diffusion quantification with the proposed phase correction. Phase-navigated DP 3D TSE included magnitude stabilizers to minimize motion and eddy-current effects on the signal magnitude. Phase navigation of motion-induced phase errors was introduced before readout in 3D TSE. DTI of lower back nerves was performed in vivo using 3D TSE and single-shot echo planar imaging (ss-EPI) in 13 subjects. Diffusion data were phase-corrected per k z plane with respect to T 2 -weighted data. The effects of motion-induced phase errors on DTI quantification was assessed for 3D TSE and compared with ss-EPI. Non-phase-corrected 3D TSE resulted in artifacts in diffusion-weighted images and overestimated DTI parameters in the sciatic nerve (mean diffusivity [MD] = 2.06 ± 0.45). Phase correction of 3D TSE DTI data resulted in reductions in all DTI parameters (MD = 1.73 ± 0.26) of statistical significance (P ≤ 0.001) and in closer agreement with ss-EPI DTI parameters (MD = 1.62 ± 0.21). DP 3D TSE with phase correction allows distortion-free isotropic diffusion imaging of lower back nerves with robustness to motion-induced artifacts and DTI quantification errors. Magn Reson Med 80:609-618, 2018. © 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2018 The Authors Magnetic Resonance

Functional annotation of hierarchical modularity.

Directory of Open Access Journals (Sweden)

Kanchana Padmanabhan

Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

A Multi-layer, Hierarchical Information Management System for the Smart Grid

Energy Technology Data Exchange (ETDEWEB)

Lu, Ning; Du, Pengwei; Paulson, Patrick R.; Greitzer, Frank L.; Guo, Xinxin; Hadley, Mark D.

2011-10-10

This paper presents the modeling approach, methodologies, and initial results of setting up a multi-layer, hierarchical information management system (IMS) for the smart grid. The IMS allows its users to analyze the data collected by multiple control and communication networks to characterize the states of the smart grid. Abnormal, corrupted, or erroneous measurement data and outliers are detected and analyzed to identify whether they are caused by random equipment failures, unintentional human errors, or deliberate tempering attempts. Data collected from different information networks are crosschecked for data integrity based on redundancy, dependency, correlation, or cross-correlations, which reveal the interdependency between data sets. A hierarchically structured reasoning mechanism is used to rank possible causes of an event to aid the system operators to proactively respond or provide mitigation recommendations to remove or neutralize the threats. The model provides satisfactory performance on identifying the cause of an event and significantly reduces the need of processing myriads of data collected.

Observation of structural universality in disordered systems using bulk diffusion measurement

Science.gov (United States)

Papaioannou, Antonios; Novikov, Dmitry S.; Fieremans, Els; Boutis, Gregory S.

2017-12-01

We report on an experimental observation of classical diffusion distinguishing between structural universality classes of disordered systems in one dimension. Samples of hyperuniform and short-range disorder were designed, characterized by the statistics of the placement of micrometer-thin parallel permeable barriers, and the time-dependent diffusion coefficient was measured by NMR methods over three orders of magnitude in time. The relation between the structural exponent, characterizing disorder universality class, and the dynamical exponent of the diffusion coefficient is experimentally verified. The experimentally established relation between structure and transport exemplifies the hierarchical nature of structural complexity—dynamics are mainly determined by the universality class, whereas microscopic parameters affect the nonuniversal coefficients. These results open the way for noninvasive characterization of structural correlations in porous media, complex materials, and biological tissues via a bulk diffusion measurement.

Enhanced supercapacitor performance using hierarchical TiO2 nanorod/Co(OH)2 nanowall array electrodes

International Nuclear Information System (INIS)

Ramadoss, Ananthakumar; Kim, Sang Jae

2014-01-01

Graphical abstract: - Highlights: • TiO 2 /Co(OH) 2 hierarchical nanostructure was prepared by a combination of hydrothermal and cathodic electrodeposition method. • Hierarchical nanostructure electrode exhibited a maximum capacitance of 274.3 mF cm −2 at a scan rate of 5 mV s −1 . • Combination of Co(OH) 2 nanowall with TiO 2 NR into a single system enhanced the electrochemical behavior of supercapacitor electrode. - Abstract: We report novel hierarchical TiO 2 nanorod (NR)/porous Co(OH) 2 nanowall array electrodes for high-performance supercapacitors fabricated using a two-step process that involves hydrothermal and electrodeposition techniques. Field-emission scanning electron microscope images reveal a bilayer structure consisting of TiO 2 NR arrays with porous Co(OH) 2 nanowalls. Compared with the bare TiO 2 NRs, the hierarchical TiO 2 NRs/Co(OH) 2 electrodes showed improved pseudocapacitive performance in a 2-M KOH electrolyte solution, exhibiting an areal specific capacitance of 274.3 mF cm −2 at a scan rate of 5 mV s −1 . The electrodes exhibited good stability, retaining 82.5% of the initial capacitance after 4000 cycles. The good pseudocapacitive performance of the hierarchical nanostructures is mainly due to the porous structure, which provides fast ion and electron transfer, a large surface area, short ion diffusion paths, and a favourable volume change during the cycling process

A Hierarchical Bayes Error Correction Model to Explain Dynamic Effects of Price Changes

NARCIS (Netherlands)

D. Fok (Dennis); R. Paap (Richard); C. Horváth (Csilla); Ph.H.B.F. Franses (Philip Hans)

2005-01-01

textabstractThe authors put forward a sales response model to explain the differences in immediate and dynamic effects of promotional prices and regular prices on sales. The model consists of a vector autoregression rewritten in error-correction format which allows to disentangle the immediate

Catalysis with hierarchical zeolites

DEFF Research Database (Denmark)

Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

2011-01-01

Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

Identification of the Diffusion Parameter in Nonlocal Steady Diffusion Problems

Energy Technology Data Exchange (ETDEWEB)

D’Elia, M., E-mail: mdelia@fsu.edu, E-mail: mdelia@sandia.gov [Sandia National Laboratories (United States); Gunzburger, M. [Florida State University (United States)

2016-04-15

The problem of identifying the diffusion parameter appearing in a nonlocal steady diffusion equation is considered. The identification problem is formulated as an optimal control problem having a matching functional as the objective of the control and the parameter function as the control variable. The analysis makes use of a nonlocal vector calculus that allows one to define a variational formulation of the nonlocal problem. In a manner analogous to the local partial differential equations counterpart, we demonstrate, for certain kernel functions, the existence of at least one optimal solution in the space of admissible parameters. We introduce a Galerkin finite element discretization of the optimal control problem and derive a priori error estimates for the approximate state and control variables. Using one-dimensional numerical experiments, we illustrate the theoretical results and show that by using nonlocal models it is possible to estimate non-smooth and discontinuous diffusion parameters.

Validating atlas-guided DOT: a comparison of diffuse optical tomography informed by atlas and subject-specific anatomies.

Science.gov (United States)

Cooper, Robert J; Caffini, Matteo; Dubb, Jay; Fang, Qianqian; Custo, Anna; Tsuzuki, Daisuke; Fischl, Bruce; Wells, William; Dan, Ippeita; Boas, David A

2012-09-01

We describe the validation of an anatomical brain atlas approach to the analysis of diffuse optical tomography (DOT). Using MRI data from 32 subjects, we compare the diffuse optical images of simulated cortical activation reconstructed using a registered atlas with those obtained using a subject's true anatomy. The error in localization of the simulated cortical activations when using a registered atlas is due to a combination of imperfect registration, anatomical differences between atlas and subject anatomies and the localization error associated with diffuse optical image reconstruction. When using a subject-specific MRI, any localization error is due to diffuse optical image reconstruction only. In this study we determine that using a registered anatomical brain atlas results in an average localization error of approximately 18 mm in Euclidean space. The corresponding error when the subject's own MRI is employed is 9.1 mm. In general, the cost of using atlas-guided DOT in place of subject-specific MRI-guided DOT is a doubling of the localization error. Our results show that despite this increase in error, reasonable anatomical localization is achievable even in cases where the subject-specific anatomy is unavailable. Copyright © 2012 Elsevier Inc. All rights reserved.

Parallel hierarchical radiosity rendering

Energy Technology Data Exchange (ETDEWEB)

Carter, Michael [Iowa State Univ., Ames, IA (United States)

1993-07-01

In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

Hierarchical prisoner’s dilemma in hierarchical game for resource competition

Science.gov (United States)

Fujimoto, Yuma; Sagawa, Takahiro; Kaneko, Kunihiko

2017-07-01

Dilemmas in cooperation are one of the major concerns in game theory. In a public goods game, each individual cooperates by paying a cost or defecting without paying it, and receives a reward from the group out of the collected cost. Thus, defecting is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individuals also play games. To study such a multi-level game, we introduce a hierarchical game in which multiple groups compete for limited resources by utilizing the collected cost in each group, where the power to appropriate resources increases with the population of the group. Analyzing this hierarchical game, we found a hierarchical prisoner’s dilemma, in which groups choose the defecting policy (say, armament) as a Nash strategy to optimize each group’s benefit, while cooperation optimizes the total benefit. On the other hand, for each individual, refusing to pay the cost (say, tax) is a Nash strategy, which turns out to be a cooperation policy for the group, thus leading to a hierarchical dilemma. Here the group reward increases with the group size. However, we find that there exists an optimal group size that maximizes the individual payoff. Furthermore, when the population asymmetry between two groups is large, the smaller group will choose a cooperation policy (say, disarmament) to avoid excessive response from the larger group, and the prisoner’s dilemma between the groups is resolved. Accordingly, the relevance of this hierarchical game on policy selection in society and the optimal size of human or animal groups are discussed.

Symmetries and modelling functions for diffusion processes

International Nuclear Information System (INIS)

Nikitin, A G; Spichak, S V; Vedula, Yu S; Naumovets, A G

2009-01-01

A constructive approach to the theory of diffusion processes is proposed, which is based on application of both symmetry analysis and the method of modelling functions. An algorithm for construction of the modelling functions is suggested. This algorithm is based on the error function expansion (ERFEX) of experimental concentration profiles. The high-accuracy analytical description of the profiles provided by ERFEX approximation allows a convenient extraction of the concentration dependence of diffusivity from experimental data and prediction of the diffusion process. Our analysis is exemplified by its employment in experimental results obtained for surface diffusion of lithium on the molybdenum (1 1 2) surface precovered with dysprosium. The ERFEX approximation can be directly extended to many other diffusion systems.

Mesh-size errors in diffusion-theory calculations using finite-difference and finite-element methods

International Nuclear Information System (INIS)

Baker, A.R.

1982-07-01

A study has been performed of mesh-size errors in diffusion-theory calculations using finite-difference and finite-element methods. As the objective was to illuminate the issues, the study was performed for a 1D slab model of a reactor with one neutron-energy group for which analytical solutions were possible. A computer code SLAB was specially written to perform the finite-difference and finite-element calculations and also to obtain the analytical solutions. The standard finite-difference equations were obtained by starting with an expansion of the neutron current in powers of the mesh size, h, and keeping terms as far as h 2 . It was confirmed that these equations led to the well-known result that the criticality parameter varied with the square of the mesh size. An improved form of the finite-difference equations was obtained by continuing the expansion for the neutron current as far as the term in h 4 . In this case, the critical parameter varied as the fourth power of the mesh size. The finite-element solutions for 2 and 3 nodes per element revealed that the criticality parameter varied as the square and fourth power of the mesh size, respectively. Numerical results are presented for a bare reactive core of uniform composition with 2 zones of different uniform mesh and for a reactive core with an absorptive reflector. (author)

An Adaptive Approach to Variational Nodal Diffusion Problems

International Nuclear Information System (INIS)

Zhang Hui; Lewis, E.E.

2001-01-01

An adaptive grid method is presented for the solution of neutron diffusion problems in two dimensions. The primal hybrid finite elements employed in the variational nodal method are used to reduce the diffusion equation to a coupled set of elemental response matrices. An a posteriori error estimator is developed to indicate the magnitude of local errors stemming from the low-order elemental interface approximations. An iterative procedure is implemented in which p refinement is applied locally by increasing the polynomial order of the interface approximations. The automated algorithm utilizes the a posteriori estimator to achieve local error reductions until an acceptable level of accuracy is reached throughout the problem domain. Application to a series of X-Y benchmark problems indicates the reduction of computational effort achievable by replacing uniform with adaptive refinement of the spatial approximations

A bio-inspired N-doped porous carbon electrocatalyst with hierarchical superstructure for efficient oxygen reduction reaction

Science.gov (United States)

Miao, Yue-E.; Yan, Jiajie; Ouyang, Yue; Lu, Hengyi; Lai, Feili; Wu, Yue; Liu, Tianxi

2018-06-01

The bio-inspired hierarchical "grape cluster" superstructure provides an effective integration of one-dimensional carbon nanofibers (CNF) with isolated carbonaceous nanoparticles into three-dimensional (3D) conductive frameworks for efficient electron and mass transfer. Herein, a 3D N-doped porous carbon electrocatalyst consisting of carbon nanofibers with grape-like N-doped hollow carbon particles (CNF@NC) has been prepared through a simple electrospinning strategy combined with in-situ growth and carbonization processes. Such a bio-inspired hierarchically organized conductive network largely facilitates both the mass diffusion and electron transfer during the oxygen reduction reactions (ORR). Therefore, the metal-free CNF@NC catalyst demonstrates superior catalytic activity with an absolute four-electron transfer mechanism, strong methanol tolerance and good long-term stability towards ORR in alkaline media.

Micromechanics of hierarchical materials

DEFF Research Database (Denmark)

Mishnaevsky, Leon, Jr.

2012-01-01

A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

Hierarchical Models for Type Ia Supernova Light Curves in the Optical and Near Infrared

Science.gov (United States)

Mandel, Kaisey; Narayan, G.; Kirshner, R. P.

2011-01-01

I have constructed a comprehensive statistical model for Type Ia supernova optical and near infrared light curves. Since the near infrared light curves are excellent standard candles and are less sensitive to dust extinction and reddening, the combination of near infrared and optical data better constrains the host galaxy extinction and improves the precision of distance predictions to SN Ia. A hierarchical probabilistic model coherently accounts for multiple random and uncertain effects, including photometric error, intrinsic supernova light curve variations and correlations across phase and wavelength, dust extinction and reddening, peculiar velocity dispersion and distances. An improved BayeSN MCMC code is implemented for computing probabilistic inferences for individual supernovae and the SN Ia and host galaxy dust populations. I use this hierarchical model to analyze nearby Type Ia supernovae with optical and near infared data from the PAIRITEL, CfA3, and CSP samples and the literature. Using cross-validation to test the robustness of the model predictions, I find that the rms Hubble diagram scatter of predicted distance moduli is 0.11 mag for SN with optical and near infrared data versus 0.15 mag for SN with only optical data. Accounting for the dispersion expected from random peculiar velocities, the rms intrinsic prediction error is 0.08-0.10 mag for SN with both optical and near infrared light curves. I discuss results for the inferred intrinsic correlation structures of the optical-NIR SN Ia light curves and the host galaxy dust distribution captured by the hierarchical model. The continued observation and analysis of Type Ia SN in the optical and near infrared is important for improving their utility as precise and accurate cosmological distance indicators.

Multicollinearity in hierarchical linear models.

Science.gov (United States)

Yu, Han; Jiang, Shanhe; Land, Kenneth C

2015-09-01

This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model. Copyright © 2015 Elsevier Inc. All rights reserved.

A Hierarchical Approach Using Machine Learning Methods in Solar Photovoltaic Energy Production Forecasting

OpenAIRE

Zhaoxuan Li; SM Mahbobur Rahman; Rolando Vega; Bing Dong

2016-01-01

We evaluate and compare two common methods, artificial neural networks (ANN) and support vector regression (SVR), for predicting energy productions from a solar photovoltaic (PV) system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used in this work corresponds to 15 min averaged power measurements collected from 2014. The accuracy of the model is determined using computing error statisti...

How hierarchical is language use?

Science.gov (United States)

Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

2012-01-01

It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

Efficient hierarchical trans-dimensional Bayesian inversion of magnetotelluric data

Science.gov (United States)

Xiang, Enming; Guo, Rongwen; Dosso, Stan E.; Liu, Jianxin; Dong, Hao; Ren, Zhengyong

2018-06-01

This paper develops an efficient hierarchical trans-dimensional (trans-D) Bayesian algorithm to invert magnetotelluric (MT) data for subsurface geoelectrical structure, with unknown geophysical model parameterization (the number of conductivity-layer interfaces) and data-error models parameterized by an auto-regressive (AR) process to account for potential error correlations. The reversible-jump Markov-chain Monte Carlo algorithm, which adds/removes interfaces and AR parameters in birth/death steps, is applied to sample the trans-D posterior probability density for model parameterization, model parameters, error variance and AR parameters, accounting for the uncertainties of model dimension and data-error statistics in the uncertainty estimates of the conductivity profile. To provide efficient sampling over the multiple subspaces of different dimensions, advanced proposal schemes are applied. Parameter perturbations are carried out in principal-component space, defined by eigen-decomposition of the unit-lag model covariance matrix, to minimize the effect of inter-parameter correlations and provide effective perturbation directions and length scales. Parameters of new layers in birth steps are proposed from the prior, instead of focused distributions centred at existing values, to improve birth acceptance rates. Parallel tempering, based on a series of parallel interacting Markov chains with successively relaxed likelihoods, is applied to improve chain mixing over model dimensions. The trans-D inversion is applied in a simulation study to examine the resolution of model structure according to the data information content. The inversion is also applied to a measured MT data set from south-central Australia.

Hierarchical architecture of active knits

International Nuclear Information System (INIS)

Abel, Julianna; Luntz, Jonathan; Brei, Diann

2013-01-01

Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm. (paper)

Nested and Hierarchical Archimax copulas

KAUST Repository

Hofert, Marius

2017-07-03

The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

Nested and Hierarchical Archimax copulas

KAUST Repository

Hofert, Marius; Huser, Raphaë l; Prasad, Avinash

2017-01-01

The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

A top-down approach for fabricating free-standing bio-carbon supercapacitor electrodes with a hierarchical structure

OpenAIRE

Yingzhi Li; Qinghua Zhang; Junxian Zhang; Lei Jin; Xin Zhao; Ting Xu

2015-01-01

Biomass has delicate hierarchical structures, which inspired us to develop a cost-effective route to prepare electrode materials with rational nanostructures for use in high-performance storage devices. Here, we demonstrate a novel top-down approach for fabricating bio-carbon materials with stable structures and excellent diffusion pathways; this approach is based on carbonization with controlled chemical activation. The developed free-standing bio-carbon electrode exhibits a high specific ca...

Gaussian and Affine Approximation of Stochastic Diffusion Models for Interest and Mortality Rates

Directory of Open Access Journals (Sweden)

Marcus C. Christiansen

2013-10-01

Full Text Available In the actuarial literature, it has become common practice to model future capital returns and mortality rates stochastically in order to capture market risk and forecasting risk. Although interest rates often should and mortality rates always have to be non-negative, many authors use stochastic diffusion models with an affine drift term and additive noise. As a result, the diffusion process is Gaussian and, thus, analytically tractable, but negative values occur with positive probability. The argument is that the class of Gaussian diffusions would be a good approximation of the real future development. We challenge that reasoning and study the asymptotics of diffusion processes with affine drift and a general noise term with corresponding diffusion processes with an affine drift term and an affine noise term or additive noise. Our study helps to quantify the error that is made by approximating diffusive interest and mortality rate models with Gaussian diffusions and affine diffusions. In particular, we discuss forward interest and forward mortality rates and the error that approximations cause on the valuation of life insurance claims.

A day in the life of a volunteer incident commander: errors, pressures and mitigating strategies.

Science.gov (United States)

Bearman, Christopher; Bremner, Peter A

2013-05-01

To meet an identified gap in the literature this paper investigates the tasks that a volunteer incident commander needs to carry out during an incident, the errors that can be made and the way that errors are managed. In addition, pressure from goal seduction and situation aversion were also examined. Volunteer incident commanders participated in a two-part interview consisting of a critical decision method interview and discussions about a hierarchical task analysis constructed by the authors. A SHERPA analysis was conducted to further identify potential errors. The results identified the key tasks, errors with extreme risk, pressures from strong situations and mitigating strategies for errors and pressures. The errors and pressures provide a basic set of issues that need to be managed by both volunteer incident commanders and fire agencies. The mitigating strategies identified here suggest some ways that this can be done. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Hierarchical Approach to 'Atomistic' 3-D MOSFET Simulation

Science.gov (United States)

Asenov, Asen; Brown, Andrew R.; Davies, John H.; Saini, Subhash

1999-01-01

We present a hierarchical approach to the 'atomistic' simulation of aggressively scaled sub-0.1 micron MOSFET's. These devices are so small that their characteristics depend on the precise location of dopant atoms within them, not just on their average density. A full-scale three-dimensional drift-diffusion atomistic simulation approach is first described and used to verify more economical, but restricted, options. To reduce processor time and memory requirements at high drain voltage, we have developed a self-consistent option based on a solution of the current continuity equation restricted to a thin slab of the channel. This is coupled to the solution of the Poisson equation in the whole simulation domain in the Gummel iteration cycles. The accuracy of this approach is investigated in comparison to the full self-consistent solution. At low drain voltage, a single solution of the nonlinear Poisson equation is sufficient to extract the current with satisfactory accuracy. In this case, the current is calculated by solving the current continuity equation in a drift approximation only, also in a thin slab containing the MOSFET channel. The regions of applicability for the different components of this hierarchical approach are illustrated in example simulations covering the random dopant-induced threshold voltage fluctuations, threshold voltage lowering, threshold voltage asymmetry, and drain current fluctuations.

Type Ia Supernova Light Curve Inference: Hierarchical Models for Nearby SN Ia in the Optical and Near Infrared

Science.gov (United States)

Mandel, Kaisey; Kirshner, R. P.; Narayan, G.; Wood-Vasey, W. M.; Friedman, A. S.; Hicken, M.

2010-01-01

I have constructed a comprehensive statistical model for Type Ia supernova light curves spanning optical through near infrared data simultaneously. The near infrared light curves are found to be excellent standard candles (sigma(MH) = 0.11 +/- 0.03 mag) that are less vulnerable to systematic error from dust extinction, a major confounding factor for cosmological studies. A hierarchical statistical framework incorporates coherently multiple sources of randomness and uncertainty, including photometric error, intrinsic supernova light curve variations and correlations, dust extinction and reddening, peculiar velocity dispersion and distances, for probabilistic inference with Type Ia SN light curves. Inferences are drawn from the full probability density over individual supernovae and the SN Ia and dust populations, conditioned on a dataset of SN Ia light curves and redshifts. To compute probabilistic inferences with hierarchical models, I have developed BayeSN, a Markov Chain Monte Carlo algorithm based on Gibbs sampling. This code explores and samples the global probability density of parameters describing individual supernovae and the population. I have applied this hierarchical model to optical and near infrared data of over 100 nearby Type Ia SN from PAIRITEL, the CfA3 sample, and the literature. Using this statistical model, I find that SN with optical and NIR data have a smaller residual scatter in the Hubble diagram than SN with only optical data. The continued study of Type Ia SN in the near infrared will be important for improving their utility as precise and accurate cosmological distance indicators.

In-situ preparation of Fe{sub 2}O{sub 3} hierarchical arrays on stainless steel substrate for high efficient catalysis

Energy Technology Data Exchange (ETDEWEB)

Yang, Zeheng, E-mail: zehengyang@hfut.edu.cn [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Wang, Kun; Shao, Zongming; Tian, Yuan [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Chen, Gongde [Department of Chemical and Environmental Engineering, University of California at Riverside, Riverside, CA 92521 (United States); Wang, Kai; Chen, Zhangxian; Dou, Yan [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Zhang, Weixin, E-mail: wxzhang@hfut.edu.cn [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China)

2017-02-15

Hierarchical array catalysts with micro/nano structures on substrates not only possess high reactivity from large surface area and suitable interface, but intensify mass transfer through shortening the diffusion paths of both reactants and products for high catalytic efficiency. Herein, we first demonstrate fabrication of Fe{sub 2}O{sub 3} hierarchical arrays grown on stainless-steel substrates via in-situ hydrothermal chemical oxidation followed by heat treatment in N{sub 2} atmosphere. As a Fenton-like catalyst, Fe{sub 2}O{sub 3} hierarchical arrays exhibit excellent catalytic activity and life cycle performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H{sub 2}O{sub 2}. The Fe{sub 2}O{sub 3} catalyst with unique hierarchical structures and efficient transport channels, effectively activates H{sub 2}O{sub 2} to generate large quantity of • OH radicals and highly promotes reaction kinetics between MB and • OH radicals. Immobilization of hierarchical array catalysts on stainless-steel can prevent particles agglomeration, facilitate the recovery and reuse of the catalysts, which is expected promising applications in wastewater remediation. - Graphical abstract: The in-situ synthesis of Fe{sub 2}O{sub 3} hierarchical arrays on stainless-steel substrates was reported for the first time, which exhibit excellent catalytic activity performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H{sub 2}O{sub 2}. - Highlights: • Fe{sub 2}O{sub 3} hierarchical arrays was prepared by in-situ hydrothermal chemical oxidation. • F{sup −} ions play an important role in the formation of the Fe{sub 2}O{sub 3} hierarchical arrays. • Fe{sub 2}O{sub 3} hierarchical arrays show high catalytic activity to methylene blue degradation.

Diffusion in glass

Energy Technology Data Exchange (ETDEWEB)

Mubarak, A S

1991-12-31

Rutherford backscattering spectromertry technique (RBS) was used to characterize and investigate the depth distribution profiles of Ca-impurities of Ca-doped soda-time glass. The purposely added Ca-impurities were introduced inti the glass matrix by a normal ion exchange diffusion process. The measurements and analysis were performed using 2 MeV {sup 2}He{sup +} ions supplied from the University of Jordan Van de Graff acceierator (JOVAG). The normalized concetration versus depth profile distributions for the Ca-imourities were determined, both theoretically and experimentally. The theoretical treatment was carried out by setting up and soiving the diffusion equation under the conditions of the experiment. The resulting profiles are characterized by a compiementary error function. the theoretical treeatment was extended to include the various methods of enhancing the diffusion process, e.g. using an electric field. The diffusion coefficient, assumed constant, of the Ca-impurities exchanged in the soda-lime glass was determined to be 1.23 x 10{sup 13} cm{sup 2}/s. A comparison between theoretically and experimentally determined profiles is made and commented at, where several conclusions are drawn and suggestions for future work are mentioned. (author). 38 refs., 21 figs., 10 Tabs.

Hydrothermal deposition and photochromic performances of three kinds of hierarchical structure arrays of WO3 thin films

International Nuclear Information System (INIS)

Ding, Defang; Shen, Yi; Ouyang, Yali; Li, Zhen

2012-01-01

Three kinds of tungsten oxide (WO 3 ) thin films have been fabricated by a simple hydrothermal deposition method. Scanning electron microscopy images of the products revealed that the capping agents did impact the microstructure of WO 3 films. Films prepared without capping agents were ordered nanorod arrays, while the ones obtained with ethanol and oxalic acid revealed peeled-orange-like and cauliflower-like hierarchical structure arrays, respectively. Both of the two hierarchical structures were composed of much thinner nanorods compared with the one obtained without capping agents. All the WO 3 films exhibited good photochromic properties and the two with inducers performed even better, which could be due to the changes in the microstructure that increased the amount of photogenerated electron–hole pairs and the proton diffusion rates. - Highlights: ► Ordered WO 3 nanorod arrays were prepared by hydrothermal deposition process. ► Two hierarchical WO 3 structure arrays were obtained with ethanol and oxalic acid. ► Mechanism for the improved photochromic performances of WO 3 films is proposed.

Hierarchical three-dimensional porous SnS{sub 2}/carbon cloth anode for high-performance lithium ion batteries

Energy Technology Data Exchange (ETDEWEB)

Chao, Junfeng, E-mail: chchjjff@163.com [College of Electronic Information and Electric Engineering, Anyang Institute of Technology, Anyang 455000 (China); Zhang, Xiutai [College of Electronic Information and Electric Engineering, Anyang Institute of Technology, Anyang 455000 (China); Xing, Shumin [College of Mathematics and Physics, Anyang Institute of Technology, Anyang 455000 (China); Fan, Qiufeng; Yang, Junping; Zhao, Luhua; Li, Xiang [College of Electronic Information and Electric Engineering, Anyang Institute of Technology, Anyang 455000 (China)

2016-08-15

Graphical abstract: Hierarchical 3D porous SnS{sub 2}/carbon cloth, good electrochemical performance. - Highlights: • Hierarchical 3D porous SnS{sub 2}/carbon cloth has been firstly synthesized. • The SnS{sub 2}/carbon clothes were good candidates for excellent lithium ion batteries. • The SnS{sub 2}/carbon cloth exhibits improved capacity compared to pure SnS{sub 2}. - Abstract: Hierarchical three-dimension (3D) porous SnS{sub 2}/carbon clothes were synthesized via a facile polyol refluxing process. The as-synthesized samples were characterized by X-ray powder diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer–Emmet–Teller (BET) and UV–vis diffuse reflectance spectrometer (UV–vis DRS). The 3D porous SnS{sub 2}/carbon clothes-based lithium ion batteries exhibited high reversible capacity and good rate capability as anode materials. The good electrochemical performance for lithium ion storage could be attributed to the special nanostructure, leading to high-rate transportation of electrolyte ion and electrons throughout the electrode matrix.

Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning

Science.gov (United States)

Fu, QiMing

2016-01-01

To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704

Human error identification for laparoscopic surgery: Development of a motion economy perspective.

Science.gov (United States)

Al-Hakim, Latif; Sevdalis, Nick; Maiping, Tanaphon; Watanachote, Damrongpan; Sengupta, Shomik; Dissaranan, Charuspong

2015-09-01

This study postulates that traditional human error identification techniques fail to consider motion economy principles and, accordingly, their applicability in operating theatres may be limited. This study addresses this gap in the literature with a dual aim. First, it identifies the principles of motion economy that suit the operative environment and second, it develops a new error mode taxonomy for human error identification techniques which recognises motion economy deficiencies affecting the performance of surgeons and predisposing them to errors. A total of 30 principles of motion economy were developed and categorised into five areas. A hierarchical task analysis was used to break down main tasks of a urological laparoscopic surgery (hand-assisted laparoscopic nephrectomy) to their elements and the new taxonomy was used to identify errors and their root causes resulting from violation of motion economy principles. The approach was prospectively tested in 12 observed laparoscopic surgeries performed by 5 experienced surgeons. A total of 86 errors were identified and linked to the motion economy deficiencies. Results indicate the developed methodology is promising. Our methodology allows error prevention in surgery and the developed set of motion economy principles could be useful for training surgeons on motion economy principles. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Dissociable mechanisms of speed-accuracy tradeoff during visual perceptual learning are revealed by a hierarchical drift diffusion model

Directory of Open Access Journals (Sweden)

Jiaxiang eZhang

2014-04-01

Full Text Available Two phenomena are commonly observed in decision-making. First, there is a speed-accuracy tradeoff such that decisions are slower and more accurate when instructions emphasize accuracy over speed, and vice versa. Second, decision performance improves with practice, as a task is learnt. The speed-accuracy tradeoff and learning effects have been explained under a well-established evidence-accumulation framework for decision-making, which suggests that evidence supporting each choice is accumulated over time, and a decision is committed to when the accumulated evidence reaches a decision boundary. This framework suggests that changing the decision boundary creates the tradeoff between decision speed and accuracy, while increasing the rate of accumulation leads to more accurate and faster decisions after learning. However, recent studies challenged the view that speed-accuracy tradeoff and learning are associated with changes in distinct, single decision parameters. Further, the influence of speed-accuracy instructions over the course of learning remains largely unknown. Here, we used a hierarchical drift-diffusion model to examine the speed-accuracy tradeoff during learning of a coherent motion discrimination task across multiple training sessions, and a transfer test session. The influence of speed-accuracy instructions was robust over training and generalized across untrained stimulus features. Emphasizing decision accuracy rather than speed was associated with increased boundary separation, drift rate and non-decision time at the beginning of training. However, after training, an emphasis on decision accuracy was only associated with increased boundary separation. In addition, faster and more accurate decisions after learning were due to a gradual decrease in boundary separation and an increase in drift rate. The results suggest that speed-accuracy instructions and learning differentially shape decision-making processes at different time scales.

Nodal spectrum method for solving neutron diffusion equation

International Nuclear Information System (INIS)

Sanchez, D.; Garcia, C. R.; Barros, R. C. de; Milian, D.E.

1999-01-01

Presented here is a new numerical nodal method for solving static multidimensional neutron diffusion equation in rectangular geometry. Our method is based on a spectral analysis of the nodal diffusion equations. These equations are obtained by integrating the diffusion equation in X, Y directions and then considering flat approximations for the current. These flat approximations are the only approximations that are considered in this method, as a result the numerical solutions are completely free from truncation errors. We show numerical results to illustrate the methods accuracy for coarse mesh calculations

Computable error estimates of a finite difference scheme for option pricing in exponential Lévy models

KAUST Repository

Kiessling, Jonas; Tempone, Raul

2014-01-01

jump activity, then the jumps smaller than some (Formula presented.) are approximated by diffusion. The resulting diffusion approximation error is also estimated, with leading order term in computable form, as well as the dependence of the time

Synthesis of hierarchical mesoporous lithium nickel cobalt manganese oxide spheres with high rate capability for lithium-ion batteries

Science.gov (United States)

Tong, Wei; Huang, Yudai; Cai, Yanjun; Guo, Yong; Wang, Xingchao; Jia, Dianzeng; Sun, Zhipeng; Pang, Weikong; Guo, Zaiping; Zong, Jun

2018-01-01

Hierarchical mesoporous LiNi1/3Co1/3Mn1/3O2 spheres have been synthesized by urea-assisted solvothermal method with adding Triton X-100. The structure and morphology of the as-prepared materials were analyzed by X-ray diffraction and electron microscope. The results show that the as-prepared samples can be indexed as hexagonal layered structure with hierarchical architecture, and the possible formation mechanism is speculated. When evaluated as cathode material, the hierarchical mesoporous LiNi1/3Co1/3Mn1/3O2 spheres show good electrochemical properties with high initial discharge capacity of 129.9 mAh g-1, and remain the discharge capacity of 95.5 mAh g-1 after 160 cycles at 10C. The excellent electrochemical performance of the as-prepared sample can be attributed to its stable hierarchical mesoporous framework in conjunction with large specific surface, low cation mixing and small particle size. They not only provide a large number of reaction sites for surface or interface reaction, but also shorten the diffusion length of Li+ ions. Meanwhile, the mesoporous spheres composed of nanoparticles can contribute to high rate ability and buffer volume changes during charge/discharge process.

Random walk, diffusion and mixing in simulations of scalar transport in fluid flows

International Nuclear Information System (INIS)

Klimenko, A Y

2008-01-01

Physical similarity and mathematical equivalence of continuous diffusion and particle random walk form one of the cornerstones of modern physics and the theory of stochastic processes. In many applied models used in simulation of turbulent transport and turbulent combustion, mixing between particles is used to reflect the influence of the continuous diffusion terms in the transport equations. We show that the continuous scalar transport and diffusion can be accurately specified by means of mixing between randomly walking Lagrangian particles with scalar properties and assess errors associated with this scheme. This gives an alternative formulation for the stochastic process which is selected to represent the continuous diffusion. This paper focuses on statistical errors and deals with relatively simple cases, where one-particle distributions are sufficient for a complete description of the problem.

Models of diffuse solar radiation

Energy Technology Data Exchange (ETDEWEB)

Boland, John; Ridley, Barbara [Centre for Industrial and Applied Mathematics, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, SA 5095 (Australia); Brown, Bruce [Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546 (Singapore)

2008-04-15

For some locations both global and diffuse solar radiation are measured. However, for many locations, only global is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from trigonometry, we need to have diffuse on the horizontal available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse radiation on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia [Spencer JW. A comparison of methods for estimating hourly diffuse solar radiation from global solar radiation. Sol Energy 1982; 29(1): 19-32]. Boland et al. [Modelling the diffuse fraction of global solar radiation on a horizontal surface. Environmetrics 2001; 12: 103-16] developed a validated model for Australian conditions. We detail our recent advances in developing the theoretical framework for the approach reported therein, particularly the use of the logistic function instead of piecewise linear or simple nonlinear functions. Additionally, we have also constructed a method, using quadratic programming, for identifying values that are likely to be erroneous. This allows us to eliminate outliers in diffuse radiation values, the data most prone to errors in measurement. (author)

Co3O4 based non-enzymatic glucose sensor with high sensitivity and reliable stability derived from hollow hierarchical architecture

Science.gov (United States)

Tian, Liangliang; He, Gege; Cai, Yanhua; Wu, Shenping; Su, Yongyao; Yan, Hengqing; Yang, Cong; Chen, Yanling; Li, Lu

2018-02-01

Inspired by kinetics, the design of hollow hierarchical electrocatalysts through large-scale integration of building blocks is recognized as an effective approach to the achievement of superior electrocatalytic performance. In this work, a hollow, hierarchical Co3O4 architecture (Co3O4 HHA) was constructed using a coordinated etching and precipitation (CEP) method followed by calcination. The resulting Co3O4 HHA electrode exhibited excellent electrocatalytic activity in terms of high sensitivity (839.3 μA mM-1 cm-2) and reliable stability in glucose detection. The high sensitivity could be attributed to the large specific surface area (SSA), ample unimpeded penetration diffusion paths and high electron transfer rate originating from the unique two-dimensional (2D) sheet-like character and hollow porous architecture. The hollow hierarchical structure also affords sufficient interspace for accommodation of volume change and structural strain, resulting in enhanced stability. The results indicate that Co3O4 HHA could have potential for application in the design of non-enzymatic glucose sensors, and that the construction of hollow hierarchical architecture provides an efficient way to design highly active, stable electrocatalysts.

Time-discrete higher order ALE formulations: a priori error analysis

KAUST Repository

Bonito, Andrea; Kyza, Irene; Nochetto, Ricardo H.

2013-01-01

We derive optimal a priori error estimates for discontinuous Galerkin (dG) time discrete schemes of any order applied to an advection-diffusion model defined on moving domains and written in the Arbitrary Lagrangian Eulerian (ALE) framework. Our

Hydrothermal deposition and photochromic performances of three kinds of hierarchical structure arrays of WO{sub 3} thin films

Energy Technology Data Exchange (ETDEWEB)

Ding, Defang; Shen, Yi, E-mail: sysy7373@163.com; Ouyang, Yali; Li, Zhen

2012-10-01

Three kinds of tungsten oxide (WO{sub 3}) thin films have been fabricated by a simple hydrothermal deposition method. Scanning electron microscopy images of the products revealed that the capping agents did impact the microstructure of WO{sub 3} films. Films prepared without capping agents were ordered nanorod arrays, while the ones obtained with ethanol and oxalic acid revealed peeled-orange-like and cauliflower-like hierarchical structure arrays, respectively. Both of the two hierarchical structures were composed of much thinner nanorods compared with the one obtained without capping agents. All the WO{sub 3} films exhibited good photochromic properties and the two with inducers performed even better, which could be due to the changes in the microstructure that increased the amount of photogenerated electron-hole pairs and the proton diffusion rates. - Highlights: Black-Right-Pointing-Pointer Ordered WO{sub 3} nanorod arrays were prepared by hydrothermal deposition process. Black-Right-Pointing-Pointer Two hierarchical WO{sub 3} structure arrays were obtained with ethanol and oxalic acid. Black-Right-Pointing-Pointer Mechanism for the improved photochromic performances of WO{sub 3} films is proposed.

Hierarchical time series bottom-up approach for forecast the export value in Central Java

Science.gov (United States)

Mahkya, D. A.; Ulama, B. S.; Suhartono

2017-10-01

The purpose of this study is Getting the best modeling and predicting the export value of Central Java using a Hierarchical Time Series. The export value is one variable injection in the economy of a country, meaning that if the export value of the country increases, the country’s economy will increase even more. Therefore, it is necessary appropriate modeling to predict the export value especially in Central Java. Export Value in Central Java are grouped into 21 commodities with each commodity has a different pattern. One approach that can be used time series is a hierarchical approach. Hierarchical Time Series is used Buttom-up. To Forecast the individual series at all levels using Autoregressive Integrated Moving Average (ARIMA), Radial Basis Function Neural Network (RBFNN), and Hybrid ARIMA-RBFNN. For the selection of the best models used Symmetric Mean Absolute Percentage Error (sMAPE). Results of the analysis showed that for the Export Value of Central Java, Bottom-up approach with Hybrid ARIMA-RBFNN modeling can be used for long-term predictions. As for the short and medium-term predictions, it can be used a bottom-up approach RBFNN modeling. Overall bottom-up approach with RBFNN modeling give the best result.

Neutrosophic Hierarchical Clustering Algoritms

Directory of Open Access Journals (Sweden)

Rıdvan Şahin

2014-03-01

Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

An On-Line Method for Thermal Diffusivity Detection of Thin Films Using Infrared Video

Directory of Open Access Journals (Sweden)

Dong Huilong

2016-03-01

Full Text Available A novel method for thermal diffusivity evolution of thin-film materials with pulsed Gaussian beam and infrared video is reported. Compared with common pulse methods performed in specialized labs, the proposed method implements a rapid on-line measurement without producing the off-centre detection error. Through mathematical deduction of the original heat conduction model, it is discovered that the area s, which is encircled by the maximum temperature curve rTMAX(θ, increases linearly over elapsed time. The thermal diffusivity is acquired from the growth rate of the area s. In this study, the off-centre detection error is avoided by performing the distance regularized level set evolution formulation. The area s was extracted from the binary images of temperature variation rate, without inducing errors from determination of the heat source centre. Thermal diffusivities of three materials, 304 stainless steel, titanium, and zirconium have been measured with the established on-line detection system, and the measurement errors are: −2.26%, −1.07%, and 1.61% respectively.

The Hierarchical Perspective

Directory of Open Access Journals (Sweden)

Daniel Sofron

2015-05-01

Full Text Available This paper is focused on the hierarchical perspective, one of the methods for representing space that was used before the discovery of the Renaissance linear perspective. The hierarchical perspective has a more or less pronounced scientific character and its study offers us a clear image of the way the representatives of the cultures that developed it used to perceive the sensitive reality. This type of perspective is an original method of representing three-dimensional space on a flat surface, which characterises the art of Ancient Egypt and much of the art of the Middle Ages, being identified in the Eastern European Byzantine art, as well as in the Western European Pre-Romanesque and Romanesque art. At the same time, the hierarchical perspective is also present in naive painting and infantile drawing. Reminiscences of this method can be recognised also in the works of some precursors of the Italian Renaissance. The hierarchical perspective can be viewed as a subjective ranking criterion, according to which the elements are visually represented by taking into account their relevance within the image while perception is ignored. This paper aims to show how the main objective of the artists of those times was not to faithfully represent the objective reality, but rather to emphasize the essence of the world and its perennial aspects. This may represent a possible explanation for the refusal of perspective in the Egyptian, Romanesque and Byzantine painting, characterised by a marked two-dimensionality.

Comparisons of Flow Patterns over a Hierarchical and a Non-hierarchical Surface in Relation to Biofouling Control

Directory of Open Access Journals (Sweden)

Bin Ahmad Fawzan Mohammed Ridha

2018-01-01

Full Text Available Biofouling can be defined as unwanted deposition and development of organisms on submerged surfaces. It is a major problem as it causes water contamination, infrastructures damage and increase in maintenance and operational cost especially in the shipping industry. There are a few methods that can prevent this problem. One of the most effective methods which is using chemicals particularly Tributyltin has been banned due to adverse effects on the environment. One of the non-toxic methods found to be effective is surface modification which involves altering the surface topography so that it becomes a low-fouling or a non-stick surface to biofouling organisms. Current literature suggested that non-hierarchical topographies has lower antifouling performance compared to hierarchical topographies. It is still unclear if the effects of the flow on these topographies could have aided in their antifouling properties. This research will use Computational Fluid Dynamics (CFD simulations to study the flow on these two topographies which also involves comparison study of the topographies used. According to the results obtained, it is shown that hierarchical topography has higher antifouling performance compared to non-hierarchical topography. This is because the fluid characteristics at the hierarchical topography is more favorable in controlling biofouling. In addition, hierarchical topography has higher wall shear stress distribution compared to non-hierarchical topography

Adaptive hierarchical multi-agent organizations

NARCIS (Netherlands)

Ghijsen, M.; Jansweijer, W.N.H.; Wielinga, B.J.; Babuška, R.; Groen, F.C.A.

2010-01-01

In this chapter, we discuss the design of adaptive hierarchical organizations for multi-agent systems (MAS). Hierarchical organizations have a number of advantages such as their ability to handle complex problems and their scalability to large organizations. By introducing adaptivity in the

Renewable Wood Pulp Paper Reactor with Hierarchical Micro/Nanopores for Continuous-Flow Nanocatalysis.

Science.gov (United States)

Koga, Hirotaka; Namba, Naoko; Takahashi, Tsukasa; Nogi, Masaya; Nishina, Yuta

2017-06-22

Continuous-flow nanocatalysis based on metal nanoparticle catalyst-anchored flow reactors has recently provided an excellent platform for effective chemical manufacturing. However, there has been limited progress in porous structure design and recycling systems for metal nanoparticle-anchored flow reactors to create more efficient and sustainable catalytic processes. In this study, traditional paper is used for a highly efficient, recyclable, and even renewable flow reactor by tailoring the ultrastructures of wood pulp. The "paper reactor" offers hierarchically interconnected micro- and nanoscale pores, which can act as convective-flow and rapid-diffusion channels, respectively, for efficient access of reactants to metal nanoparticle catalysts. In continuous-flow, aqueous, room-temperature catalytic reduction of 4-nitrophenol to 4-aminophenol, a gold nanoparticle (AuNP)-anchored paper reactor with hierarchical micro/nanopores provided higher reaction efficiency than state-of-the-art AuNP-anchored flow reactors. Inspired by traditional paper materials, successful recycling and renewal of AuNP-anchored paper reactors were also demonstrated while high reaction efficiency was maintained. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Microarray-based classification of diffuse large B-cell lymphoma

DEFF Research Database (Denmark)

Poulsen, Christian Bjørn; Borup, Rehannah; Nielsen, Finn Cilius

2005-01-01

on the Affymetrix HG-U133A oligonucleotide arrays and improve the classification, we determined the expression profiles of pretreatment, diagnostic samples from 52 primary nodal DLBCL. METHODS AND RESULTS: First, three previously published gene lists were converted to the HG-U133A probe sets and used......OBJECTIVE: Hierarchical clusterings of diffuse large B-cell lymphoma (DLBCL) based on gene expression signatures have previously been used to classify DLBCL into Germinal Center B-cell (GCB) and Activated B-cell (ABC) types. To examine if it was feasible to perform a cross-platform validation...... for hierarchical clustering. In this way, three subtypes, including the GCB type (n = 20), the ABC type (n = 25) and an intermediate group, Type-3 (n = 5), were distinguished. The CD10 and Bcl-6 expression as well as t(14;18) translocation were prevalent, but not exclusive to the GCB type. By contrast, MUM1...

An assessment of a model for error processing in the CMS Data Acquisition System

International Nuclear Information System (INIS)

Dustdar, S; Moser, R; Gutleber, J; Orsini, L

2010-01-01

The CMS Data Acquisition System consists of O(20000) interdependent services. A system providing exception and application-specific monitoring data is essential for the operation of such a cluster. Due to the number of involved services the amount of monitoring data is higher than a human operator can handle efficiently. Thus moving the expert-knowledge for error analysis from the operator to a dedicated system is a natural choice. This reduces the number of notifications to the operator for simpler visualization and provides meaningful error cause descriptions and suggestions for possible countermeasures. This paper discusses an architecture of a workflow-based hierarchical error analysis system based on Guardians for the CMS Data Acquisition System. Guardians provide a common interface for error analysis of a specific service or subsystem. To provide effective and complete error analysis, the requirements regarding information sources, monitoring and configuration, are analyzed. Formats for common notification types are defined and a generic Guardian based on Event-Condition-Action rules is presented as a proof-of-concept.

Hierarchical porous carbons prepared by an easy one-step carbonization and activation of phenol-formaldehyde resins with high performance for supercapacitors

Energy Technology Data Exchange (ETDEWEB)

Zheng, Zhoujun [State Key Laboratory of High Performance Ceramics and Superfine Microstructures, Graduate School, Shanghai Institute of Ceramics, Chinese Academy of Science, 1295 Dingxi Road, Shanghai 200050 (China); Gao, Qiuming [State Key Laboratory of High Performance Ceramics and Superfine Microstructures, Graduate School, Shanghai Institute of Ceramics, Chinese Academy of Science, 1295 Dingxi Road, Shanghai 200050 (China); School of Chemistry and Environment, Beihang University, 37 Xueyuan Road, Haidian District, Beijing 100191 (China)

2011-02-01

Hierarchical porous carbons are prepared by an easy one-step process of carbonization and activation derived from phenol-formaldehyde resins, in which potassium hydroxide acts as both the catalyst of polymerization and the activation reagent. The simple one-step preparation saves the cost of carbons and leads to high yield. The porous carbons have high surface areas with abundant pore structures. The plenty of micropores and small mesopores increase the capacitance and make the electrolyte ions diffuse fast into the pores. These hierarchical porous carbons show high performance for supercapacitors possessing of the optimized capacitance of 234 F g{sup -1} in aqueous electrolyte and 137 F g{sup -1} in organic electrolyte with high capacitive retention. (author)

Intravoxel incoherent motion diffusion imaging of the liver: Optimal b-value subsampling and impact on parameter precision and reproducibility

International Nuclear Information System (INIS)

Dyvorne, Hadrien; Jajamovich, Guido; Kakite, Suguru; Kuehn, Bernd; Taouli, Bachir

2014-01-01

Highlights: • We assess the precision and reproducibility of liver IVIM diffusion parameters. • Liver IVIM DWI can be performed with 4 b-values with good parameter precision. • Liver IVIM DWI can be performed with 4 b-values with good parameter reproducibility. - Abstract: Purpose: To increase diffusion sampling efficiency in intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) of the liver by reducing the number of diffusion weightings (b-values). Materials and methods: In this IRB approved HIPAA compliant prospective study, 53 subjects (M/F 38/15, mean age 52 ± 13 y) underwent IVIM DWI at 1.5 T using 16 b-values (0–800 s/mm 2 ), with 14 subjects having repeat exams to assess IVIM parameter reproducibility. A biexponential diffusion model was used to quantify IVIM hepatic parameters (PF: perfusion fraction, D: true diffusion and D*: pseudo diffusion). All possible subsets of the 16 b-values were probed, with number of b values ranging from 4 to 15, and corresponding parameters were quantified for each subset. For each b-value subset, global parameter estimation error was computed against the parameters obtained with all 16 b-values and the subsets providing the lowest error were selected. Interscan estimation error was also evaluated between repeat exams to assess reproducibility of the IVIM technique in the liver. The optimal b-values distribution was selected such that the number of b-values was minimal while keeping parameter estimation error below interscan reproducibility error. Results: As the number of b-values decreased, the estimation error increased for all parameters, reflecting decreased precision of IVIM metrics. Using an optimal set of 4 b-values (0, 15, 150 and 800 s/mm 2 ), the errors were 6.5, 22.8 and 66.1% for D, PF and D* respectively. These values lie within the range of test–retest reproducibility for the corresponding parameters, with errors of 12.0, 32.3 and 193.8% for D, PF and D* respectively. Conclusion: A set

Hierarchical video summarization

Science.gov (United States)

Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

1998-12-01

We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

Global CO2 flux inversions from remote-sensing data with systematic errors using hierarchical statistical models

Science.gov (United States)

Zammit-Mangion, Andrew; Stavert, Ann; Rigby, Matthew; Ganesan, Anita; Rayner, Peter; Cressie, Noel

2017-04-01

The Orbiting Carbon Observatory-2 (OCO-2) satellite was launched on 2 July 2014, and it has been a source of atmospheric CO2 data since September 2014. The OCO-2 dataset contains a number of variables, but the one of most interest for flux inversion has been the column-averaged dry-air mole fraction (in units of ppm). These global level-2 data offer the possibility of inferring CO2 fluxes at Earth's surface and tracking those fluxes over time. However, as well as having a component of random error, the OCO-2 data have a component of systematic error that is dependent on the instrument's mode, namely land nadir, land glint, and ocean glint. Our statistical approach to CO2-flux inversion starts with constructing a statistical model for the random and systematic errors with parameters that can be estimated from the OCO-2 data and possibly in situ sources from flasks, towers, and the Total Column Carbon Observing Network (TCCON). Dimension reduction of the flux field is achieved through the use of physical basis functions, while temporal evolution of the flux is captured by modelling the basis-function coefficients as a vector autoregressive process. For computational efficiency, flux inversion uses only three months of sensitivities of mole fraction to changes in flux, computed using MOZART; any residual variation is captured through the modelling of a stochastic process that varies smoothly as a function of latitude. The second stage of our statistical approach is to simulate from the posterior distribution of the basis-function coefficients and all unknown parameters given the data using a fully Bayesian Markov chain Monte Carlo (MCMC) algorithm. Estimates and posterior variances of the flux field can then be obtained straightforwardly from this distribution. Our statistical approach is different than others, as it simultaneously makes inference (and quantifies uncertainty) on both the error components' parameters and the CO2 fluxes. We compare it to more classical

Chelating agent-free, vapor-assisted crystallization method to synthesize hierarchical microporous/mesoporous MIL-125 (Ti).

Science.gov (United States)

McNamara, Nicholas D; Hicks, Jason C

2015-03-11

Titanium-based microporous heterogeneous catalysts are widely studied but are often limited by the accessibility of reactants to active sites. Metal-organic frameworks (MOFs), such as MIL-125 (Ti), exhibit enhanced surface areas due to their high intrinsic microporosity, but the pore diameters of most microporous MOFs are often too small to allow for the diffusion of larger reactants (>7 Å) relevant to petroleum and biomass upgrading. In this work, hierarchical microporous MIL-125 exhibiting significantly enhanced interparticle mesoporosity was synthesized using a chelating-free, vapor-assisted crystallization method. The resulting hierarchical MOF was examined as an active catalyst for the oxidation of dibenzothiophene (DBT) with tert-butyl hydroperoxide and outperformed the solely microporous analogue. This was attributed to greater access of the substrate to surface active sites, as the pores in the microporous analogues were of inadequate size to accommodate DBT. Moreover, thiophene adsorption studies suggested the mesoporous MOF contained larger amounts of unsaturated metal sites that could enhance the observed catalytic activity.

The awareness and want matrix with adoption gap ratio analysis for e-service diffusion effect.

Science.gov (United States)

Liang, Te-Hsin

2011-03-01

Since the hierarchical stages of a customer purchasing decision or innovation adoption process are interrelated, an analysis of all their stages, including awareness, want, and adoption, in relation to product or service diffusion, is urgently needed. Therefore, this study proposes the use of an awareness and want matrix, together with an adoption gap ratio analysis, to assess the effectiveness of innovation and technology diffusion for e-services. This study also conducts an empirical test on the promotion performance evaluation of 12 e-services promoted by the Taiwanese government.

Rapid and selective detection of acetone using hierarchical ZnO gas sensor for hazardous odor markers application.

Science.gov (United States)

Jia, Qianqian; Ji, Huiming; Zhang, Ying; Chen, Yalu; Sun, Xiaohong; Jin, Zhengguo

2014-07-15

Hierarchical nanostructured ZnO dandelion-like spheres were synthesized via solvothermal reaction at 200°C for 4h. The products were pure hexagonal ZnO with large exposure of (002) polar facet. Side-heating gas sensor based on hierarchical ZnO spheres was prepared to evaluate the acetone gas sensing properties. The detection limit to acetone for the ZnO sensor is 0.25ppm. The response (Ra/Rg) toward 100ppm acetone was 33 operated at 230°C and the response time was as short as 3s. The sensor exhibited remarkable acetone selectivity with negligible response toward other hazardous gases and water vapor. The high proportion of electron depletion region and oxygen vacancies contributed to high gas response sensitivity. The hollow and porous structure of dandelion-like ZnO spheres facilitated the diffusion of gas molecules, leading to a rapid response speed. The largely exposed (002) polar facets could adsorb acetone gas molecules easily and efficiently, resulting in a rapid response speed and good selectivity of hierarchical ZnO spheres gas sensor at low operating temperature. Copyright © 2014 Elsevier B.V. All rights reserved.

Enhancement of diffusers BRDF accuracy

Science.gov (United States)

Otter, Gerard; Bazalgette Courrèges-Lacoste, Gregory; van Brug, Hedser; Schaarsberg, Jos Groote; Delwart, Steven; del Bello, Umberto

2017-11-01

This paper reports the result of an ESA study conducted at TNO to investigate properties of various diffusers. Diffusers are widely used in space instruments as part of the on-board absolute calibration. Knowledge of the behaviour of the diffuser is therefore most important. From measurements of launched instruments in-orbit it has been discovered that when a diffuser is used in the vacuum of space the BRDF can change with respect to the one in ambient conditions. This is called the air/vacuum effect and has been simulated in this study by measuring the BRDF in a laboratory in ambient as well as vacuum conditions. Another studied effect is related to the design parameters of the optical system and the scattering properties of the diffuser. The effect is called Spectral Features and is a noise like structure superimposed on the diffuser BRDF. Modern space spectrometers, which have high spectral resolution and/or a small field of view (high spatial resolution) are suffering from this effect. The choice of diffuser can be very critical with respect to the required absolute radiometric calibration of an instrument. Even if the Spectral Features are small it can influence the error budget of the retrieval algorithms for the level 2 products. in this presentation diffuser trade-off results are presented and the Spectral Features model applied to the optical configuration of the MERIS instrument is compared to in-flight measurements of MERIS.

Error prevention at a radon measurement service laboratory

International Nuclear Information System (INIS)

Cohen, B.L.; Cohen, F.

1989-01-01

This article describes the steps taken at a high volume counting laboratory to avoid human, instrument, and computer errors. The laboratory analyzes diffusion barrier charcoal adsorption canisters which have been used to test homes and commercial buildings. A series of computer and human cross-checks are utilized to assure that accurate results are reported to the correct client

Novel nitrogen-doped hierarchically porous coralloid carbon materials as host matrixes for lithium–sulfur batteries

International Nuclear Information System (INIS)

Yang, Jing; Wang, Shuyuan; Ma, Zhipeng; Du, Zhiling; Li, Chunying; Song, Jianjun; Wang, Guiling; Shao, Guangjie

2015-01-01

Highlights: • Nitrogen-doped hierarchically porous coralloid carbon/sulfur composites were prepared • Nitrogen atoms were introduced to improve electrochemical properties • The intriguing structural features benefited discharge capacity and cycling stability - Abstract: Nitrogen-doped hierarchically porous coralloid carbon/sulfur composites (N-HPCC/S) served as attractive cathode materials for lithium–sulfur (Li–S) batteries were fabricated for the first time. The nitrogen-doped hierarchically porous coralloid carbon (N-HPCC) with an appropriate nitrogen content (1.29 wt%) was synthesized via a facile hydrothermal approach, combined with subsequent carbonization–activation. The N-HPCC/S composites prepared by a simple melt–diffusion method displayed an excellent electrochemical performance. With a high sulfur content (58 wt%) in the total electrode weight, the N-HPCC/S cathode delivered a high initial discharge capacity of 1626.8 mA h g −1 and remained high up to 1086.3 mA h g −1 after 50 cycles at 100 mA g −1 , which is about 1.86 times as that of activated carbon. Particularly, the reversible discharge capacity still maintained 607.2 mA h g −1 after 200 cycles even at a higher rate of 800 mA g −1 . The enhanced electrochemical performance was attributed to the synergetic effect between the intriguing hierarchically porous coralloid structure and appropriate nitrogen doping, which could effectively trap polysulfides, alleviate the volume expansion, enhance the electronic conductivity and improve the surface interaction between the carbon matrix and polysulfides

The Sustained Influence of an Error on Future Decision-Making.

Science.gov (United States)

Schiffler, Björn C; Bengtsson, Sara L; Lundqvist, Daniel

2017-01-01

Post-error slowing (PES) is consistently observed in decision-making tasks after negative feedback. Yet, findings are inconclusive as to whether PES supports performance accuracy. We addressed the role of PES by employing drift diffusion modeling which enabled us to investigate latent processes of reaction times and accuracy on a large-scale dataset (>5,800 participants) of a visual search experiment with emotional face stimuli. In our experiment, post-error trials were characterized by both adaptive and non-adaptive decision processes. An adaptive increase in participants' response threshold was sustained over several trials post-error. Contrarily, an initial decrease in evidence accumulation rate, followed by an increase on the subsequent trials, indicates a momentary distraction of task-relevant attention and resulted in an initial accuracy drop. Higher values of decision threshold and evidence accumulation on the post-error trial were associated with higher accuracy on subsequent trials which further gives credence to these parameters' role in post-error adaptation. Finally, the evidence accumulation rate post-error decreased when the error trial presented angry faces, a finding suggesting that the post-error decision can be influenced by the error context. In conclusion, we demonstrate that error-related response adaptations are multi-component processes that change dynamically over several trials post-error.

The Sustained Influence of an Error on Future Decision-Making

Directory of Open Access Journals (Sweden)

Björn C. Schiffler

2017-06-01

Full Text Available Post-error slowing (PES is consistently observed in decision-making tasks after negative feedback. Yet, findings are inconclusive as to whether PES supports performance accuracy. We addressed the role of PES by employing drift diffusion modeling which enabled us to investigate latent processes of reaction times and accuracy on a large-scale dataset (>5,800 participants of a visual search experiment with emotional face stimuli. In our experiment, post-error trials were characterized by both adaptive and non-adaptive decision processes. An adaptive increase in participants’ response threshold was sustained over several trials post-error. Contrarily, an initial decrease in evidence accumulation rate, followed by an increase on the subsequent trials, indicates a momentary distraction of task-relevant attention and resulted in an initial accuracy drop. Higher values of decision threshold and evidence accumulation on the post-error trial were associated with higher accuracy on subsequent trials which further gives credence to these parameters’ role in post-error adaptation. Finally, the evidence accumulation rate post-error decreased when the error trial presented angry faces, a finding suggesting that the post-error decision can be influenced by the error context. In conclusion, we demonstrate that error-related response adaptations are multi-component processes that change dynamically over several trials post-error.

A method for optimizing the cosine response of solar UV diffusers

Science.gov (United States)

Pulli, Tomi; Kärhä, Petri; Ikonen, Erkki

2013-07-01

Instruments measuring global solar ultraviolet (UV) irradiance at the surface of the Earth need to collect radiation from the entire hemisphere. Entrance optics with angular response as close as possible to the ideal cosine response are necessary to perform these measurements accurately. Typically, the cosine response is obtained using a transmitting diffuser. We have developed an efficient method based on a Monte Carlo algorithm to simulate radiation transport in the solar UV diffuser assembly. The algorithm takes into account propagation, absorption, and scattering of the radiation inside the diffuser material. The effects of the inner sidewalls of the diffuser housing, the shadow ring, and the protective weather dome are also accounted for. The software implementation of the algorithm is highly optimized: a simulation of 109 photons takes approximately 10 to 15 min to complete on a typical high-end PC. The results of the simulations agree well with the measured angular responses, indicating that the algorithm can be used to guide the diffuser design process. Cost savings can be obtained when simulations are carried out before diffuser fabrication as compared to a purely trial-and-error-based diffuser optimization. The algorithm was used to optimize two types of detectors, one with a planar diffuser and the other with a spherically shaped diffuser. The integrated cosine errors—which indicate the relative measurement error caused by the nonideal angular response under isotropic sky radiance—of these two detectors were calculated to be f2=1.4% and 0.66%, respectively.

The drift diffusion model as the choice rule in reinforcement learning.

Science.gov (United States)

Pedersen, Mads Lund; Frank, Michael J; Biele, Guido

2017-08-01

Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyperactivity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups.

Robust and scalable hierarchical matrix-based fast direct solver and preconditioner for the numerical solution of elliptic partial differential equations

KAUST Repository

Chavez, Gustavo Ivan

2017-07-10

This dissertation introduces a novel fast direct solver and preconditioner for the solution of block tridiagonal linear systems that arise from the discretization of elliptic partial differential equations on a Cartesian product mesh, such as the variable-coefficient Poisson equation, the convection-diffusion equation, and the wave Helmholtz equation in heterogeneous media. The algorithm extends the traditional cyclic reduction method with hierarchical matrix techniques. The resulting method exposes substantial concurrency, and its arithmetic operations and memory consumption grow only log-linearly with problem size, assuming bounded rank of off-diagonal matrix blocks, even for problems with arbitrary coefficient structure. The method can be used as a standalone direct solver with tunable accuracy, or as a black-box preconditioner in conjunction with Krylov methods. The challenges that distinguish this work from other thrusts in this active field are the hybrid distributed-shared parallelism that can demonstrate the algorithm at large-scale, full three-dimensionality, and the three stressors of the current state-of-the-art multigrid technology: high wavenumber Helmholtz (indefiniteness), high Reynolds convection (nonsymmetry), and high contrast diffusion (inhomogeneity). Numerical experiments corroborate the robustness, accuracy, and complexity claims and provide a baseline of the performance and memory footprint by comparisons with competing approaches such as the multigrid solver hypre, and the STRUMPACK implementation of the multifrontal factorization with hierarchically semi-separable matrices. The companion implementation can utilize many thousands of cores of Shaheen, KAUST\\'s Haswell-based Cray XC-40 supercomputer, and compares favorably with other implementations of hierarchical solvers in terms of time-to-solution and memory consumption.

Variational Multiscale error estimator for anisotropic adaptive fluid mechanic simulations: application to convection-diffusion problems

OpenAIRE

Bazile , Alban; Hachem , Elie; Larroya-Huguet , Juan-Carlos; Mesri , Youssef

2018-01-01

International audience; In this work, we present a new a posteriori error estimator based on the Variational Multiscale method for anisotropic adaptive fluid mechanics problems. The general idea is to combine the large scale error based on the solved part of the solution with the sub-mesh scale error based on the unresolved part of the solution. We compute the latter with two different methods: one using the stabilizing parameters and the other using bubble functions. We propose two different...

Hierarchically porous carbon with high-speed ion transport channels for high performance supercapacitors

Science.gov (United States)

Lu, Haoyuan; Li, Qingwei; Guo, Jianhui; Song, Aixin; Gong, Chunhong; Zhang, Jiwei; Zhang, Jingwei

2018-01-01

Hierarchically porous carbons (HPC) are considered as promising electrode materials for supercapacitors, due to their outstanding charge/discharge cycling stabilities and high power densities. However, HPC possess a relatively low ion diffusion rate inside the materials, which challenges their application for high performance supercapacitor. Thus tunnel-shaped carbon pores with a size of tens of nanometers were constructed by inducing the self-assembly of lithocholic acid with ammonium chloride, thereby providing high-speed channels for internal ion diffusion. The as-formed one-dimensional pores are beneficial to the activation process by KOH, providing a large specific surface area, and then facilitate rapid transport of electrolyte ions from macropores to the microporous surfaces. Therefore, the HPC achieve an outstanding gravimetric capacitance of 284 F g-1 at a current density of 0.1 A g-1 and a remarkable capacity retention of 64.8% when the current density increases by 1000 times to 100 A g-1.

Computable error estimates of a finite difference scheme for option pricing in exponential Lévy models

KAUST Repository

Kiessling, Jonas

2014-05-06

Option prices in exponential Lévy models solve certain partial integro-differential equations. This work focuses on developing novel, computable error approximations for a finite difference scheme that is suitable for solving such PIDEs. The scheme was introduced in (Cont and Voltchkova, SIAM J. Numer. Anal. 43(4):1596-1626, 2005). The main results of this work are new estimates of the dominating error terms, namely the time and space discretisation errors. In addition, the leading order terms of the error estimates are determined in a form that is more amenable to computations. The payoff is only assumed to satisfy an exponential growth condition, it is not assumed to be Lipschitz continuous as in previous works. If the underlying Lévy process has infinite jump activity, then the jumps smaller than some (Formula presented.) are approximated by diffusion. The resulting diffusion approximation error is also estimated, with leading order term in computable form, as well as the dependence of the time and space discretisation errors on this approximation. Consequently, it is possible to determine how to jointly choose the space and time grid sizes and the cut off parameter (Formula presented.). © 2014 Springer Science+Business Media Dordrecht.

Convergent evidence for hierarchical prediction networks from human electrocorticography and magnetoencephalography.

Science.gov (United States)

Phillips, Holly N; Blenkmann, Alejandro; Hughes, Laura E; Kochen, Silvia; Bekinschtein, Tristan A; Cam-Can; Rowe, James B

2016-09-01

We propose that sensory inputs are processed in terms of optimised predictions and prediction error signals within hierarchical neurocognitive models. The combination of non-invasive brain imaging and generative network models has provided support for hierarchical frontotemporal interactions in oddball tasks, including recent identification of a temporal expectancy signal acting on prefrontal cortex. However, these studies are limited by the need to invert magnetoencephalographic or electroencephalographic sensor signals to localise activity from cortical 'nodes' in the network, or to infer neural responses from indirect measures such as the fMRI BOLD signal. To overcome this limitation, we examined frontotemporal interactions estimated from direct cortical recordings from two human participants with cortical electrode grids (electrocorticography - ECoG). Their frontotemporal network dynamics were compared to those identified by magnetoencephalography (MEG) in forty healthy adults. All participants performed the same auditory oddball task with standard tones interspersed with five deviant tone types. We normalised post-operative electrode locations to standardised anatomic space, to compare across modalities, and inverted the MEG to cortical sources using the estimated lead field from subject-specific head models. A mismatch negativity signal in frontal and temporal cortex was identified in all subjects. Generative models of the electrocorticographic and magnetoencephalographic data were separately compared using the free-energy estimate of the model evidence. Model comparison confirmed the same critical features of hierarchical frontotemporal networks in each patient as in the group-wise MEG analysis. These features included bilateral, feedforward and feedback frontotemporal modulated connectivity, in addition to an asymmetric expectancy driving input on left frontal cortex. The invasive ECoG provides an important step in construct validation of the use of neural

Finite-difference schemes for anisotropic diffusion

Energy Technology Data Exchange (ETDEWEB)

Es, Bram van, E-mail: es@cwi.nl [Centrum Wiskunde and Informatica, P.O. Box 94079, 1090GB Amsterdam (Netherlands); FOM Institute DIFFER, Dutch Institute for Fundamental Energy Research, Association EURATOM-FOM (Netherlands); Koren, Barry [Eindhoven University of Technology (Netherlands); Blank, Hugo J. de [FOM Institute DIFFER, Dutch Institute for Fundamental Energy Research, Association EURATOM-FOM (Netherlands)

2014-09-01

In fusion plasmas diffusion tensors are extremely anisotropic due to the high temperature and large magnetic field strength. This causes diffusion, heat conduction, and viscous momentum loss, to effectively be aligned with the magnetic field lines. This alignment leads to different values for the respective diffusive coefficients in the magnetic field direction and in the perpendicular direction, to the extent that heat diffusion coefficients can be up to 10{sup 12} times larger in the parallel direction than in the perpendicular direction. This anisotropy puts stringent requirements on the numerical methods used to approximate the MHD-equations since any misalignment of the grid may cause the perpendicular diffusion to be polluted by the numerical error in approximating the parallel diffusion. Currently the common approach is to apply magnetic field-aligned coordinates, an approach that automatically takes care of the directionality of the diffusive coefficients. This approach runs into problems at x-points and at points where there is magnetic re-connection, since this causes local non-alignment. It is therefore useful to consider numerical schemes that are tolerant to the misalignment of the grid with the magnetic field lines, both to improve existing methods and to help open the possibility of applying regular non-aligned grids. To investigate this, in this paper several discretization schemes are developed and applied to the anisotropic heat diffusion equation on a non-aligned grid.

Evaluating Hierarchical Structure in Music Annotations.

Science.gov (United States)

McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

2017-01-01

Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

Evaluating Hierarchical Structure in Music Annotations

Directory of Open Access Journals (Sweden)

Brian McFee

2017-08-01

Full Text Available Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR, it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

Fabricating hierarchically porous carbon with well-defined open pores via polymer dehalogenation for high-performance supercapacitor

Science.gov (United States)

Guo, Mei; Li, Yu; Du, Kewen; Qiu, Chaochao; Dou, Gang; Zhang, Guoxin

2018-05-01

Improving specific energy of supercapacitors (SCs) at high power has been intensively investigated as a hot and challengeable topic. In this work, hierarchically porous carbon (HPC) materials with well-defined meso-/macro-pores are reported via the dehalogenation reaction of polyvinyl fluoride (PVDF) by NaNH2. The pore hierarchy is achievable mainly because of the coupled effects of NaNH2 activation and the template/bubbling effects of byproducts of NaF and NH3. Electron microscopy studies and Brunauer-Emmett-Teller (BET) measurements confirm that the structures of HPC samples contain multiple-scale pores assembled in a hierarchical pattern, and most of their volumes are contributed by mesopores. Aqueous symmetric supercapacitors (ASSCs) were fabricated using HPC-M7 materials, achieving an ultrahigh specific energy of 18.8 Wh kg-1 at specific power of 986.8 W kg-1. Remarkably, at the ultrahigh power of 14.3 kW kg-1, the HPC-ASSCs still output a very high specific energy of 16.7 Wh kg-1, which means the ASSCs can be charged or discharged within 4 s. The outstanding rate capacitive performance is mainly benefited from the hierarchical porous structure that allows highly efficient ion diffusion.

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling.

Science.gov (United States)

Cressie, Noel; Calder, Catherine A; Clark, James S; Ver Hoef, Jay M; Wikle, Christopher K

2009-04-01

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Development of advanced methods for analysis of experimental data in diffusion

Science.gov (United States)

Jaques, Alonso V.

There are numerous experimental configurations and data analysis techniques for the characterization of diffusion phenomena. However, the mathematical methods for estimating diffusivities traditionally do not take into account the effects of experimental errors in the data, and often require smooth, noiseless data sets to perform the necessary analysis steps. The current methods used for data smoothing require strong assumptions which can introduce numerical "artifacts" into the data, affecting confidence in the estimated parameters. The Boltzmann-Matano method is used extensively in the determination of concentration - dependent diffusivities, D(C), in alloys. In the course of analyzing experimental data, numerical integrations and differentiations of the concentration profile are performed. These methods require smoothing of the data prior to analysis. We present here an approach to the Boltzmann-Matano method that is based on a regularization method to estimate a differentiation operation on the data, i.e., estimate the concentration gradient term, which is important in the analysis process for determining the diffusivity. This approach, therefore, has the potential to be less subjective, and in numerical simulations shows an increased accuracy in the estimated diffusion coefficients. We present a regression approach to estimate linear multicomponent diffusion coefficients that eliminates the need pre-treat or pre-condition the concentration profile. This approach fits the data to a functional form of the mathematical expression for the concentration profile, and allows us to determine the diffusivity matrix directly from the fitted parameters. Reformulation of the equation for the analytical solution is done in order to reduce the size of the problem and accelerate the convergence. The objective function for the regression can incorporate point estimations for error in the concentration, improving the statistical confidence in the estimated diffusivity matrix

Nonlinear adaptive control system design with asymptotically stable parameter estimation error

Science.gov (United States)

Mishkov, Rumen; Darmonski, Stanislav

2018-01-01

The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

Adaptive solution of the multigroup diffusion equation on irregular structured grids using a conforming finite element method formulation

International Nuclear Information System (INIS)

Ragusa, J. C.

2004-01-01

In this paper, a method for performing spatially adaptive computations in the framework of multigroup diffusion on 2-D and 3-D Cartesian grids is investigated. The numerical error, intrinsic to any computer simulation of physical phenomena, is monitored through an a posteriori error estimator. In a posteriori analysis, the computed solution itself is used to assess the accuracy. By efficiently estimating the spatial error, the entire computational process is controlled through successively adapted grids. Our analysis is based on a finite element solution of the diffusion equation. Bilinear test functions are used. The derived a posteriori error estimator is therefore based on the Hessian of the numerical solution. (authors)

Adaptive weak approximation of reflected and stopped diffusions

KAUST Repository

Bayer, Christian

2010-01-01

We study the weak approximation problem of diffusions, which are reflected at a subset of the boundary of a domain and stopped at the remaining boundary. First, we derive an error representation for the projected Euler method of Costantini, Pacchiarotti and Sartoretto [Costantini et al., SIAM J. Appl. Math., 58(1):73-102, 1998], based on which we introduce two new algorithms. The first one uses a correction term from the representation in order to obtain a higher order of convergence, but the computation of the correction term is, in general, not feasible in dimensions d > 1. The second algorithm is adaptive in the sense of Moon, Szepessy, Tempone and Zouraris [Moon et al., Stoch. Anal. Appl., 23:511-558, 2005], using stochastic refinement of the time grid based on a computable error expansion derived from the representation. Regarding the stopped diffusion, it is based in the adaptive algorithm for purely stopped diffusions presented in Dzougoutov, Moon, von Schwerin, Szepessy and Tempone [Dzougoutov et al., Lect. Notes Comput. Sci. Eng., 44, 59-88, 2005]. We give numerical examples underlining the theoretical results. © de Gruyter 2010.

Analysis of individual brain activation maps using hierarchical description and multiscale detection

International Nuclear Information System (INIS)

Poline, J.B.; Mazoyer, B.M.

1994-01-01

The authors propose a new method for the analysis of brain activation images that aims at detecting activated volumes rather than pixels. The method is based on Poisson process modeling, hierarchical description, and multiscale detection (MSD). Its performances have been assessed using both Monte Carlo simulated images and experimental PET brain activation data. As compared to other methods, the MSD approach shows enhanced sensitivity with a controlled overall type I error, and has the ability to provide an estimate of the spatial limits of the detected signals. It is applicable to any kind of difference image for which the spatial autocorrelation function can be approximated by a stationary Gaussian function

Yearly, seasonal and monthly daily average diffuse sky radiation models

International Nuclear Information System (INIS)

Kassem, A.S.; Mujahid, A.M.; Turner, D.W.

1993-01-01

A daily average diffuse sky radiation regression model based on daily global radiation was developed utilizing two year data taken near Blytheville, Arkansas (Lat. =35.9 0 N, Long. = 89.9 0 W), U.S.A. The model has a determination coefficient of 0.91 and 0.092 standard error of estimate. The data were also analyzed for a seasonal dependence and four seasonal average daily models were developed for the spring, summer, fall and winter seasons. The coefficient of determination is 0.93, 0.81, 0.94 and 0.93, whereas the standard error of estimate is 0.08, 0.102, 0.042 and 0.075 for spring, summer, fall and winter, respectively. A monthly average daily diffuse sky radiation model was also developed. The coefficient of determination is 0.92 and the standard error of estimate is 0.083. A seasonal monthly average model was also developed which has 0.91 coefficient of determination and 0.085 standard error of estimate. The developed monthly daily average and daily models compare well with a selected number of previously developed models. (author). 11 ref., figs., tabs

Hierarchically Nanostructured Materials for Sustainable Environmental Applications

Directory of Open Access Journals (Sweden)

Zheng eRen

2013-11-01

Full Text Available This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

Hierarchically structured, nitrogen-doped carbon membranes

KAUST Repository

Wang, Hong; Wu, Tao

2017-01-01

The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced

Hierarchical Cu precipitation in lamellated steel after multistage heat treatment

Science.gov (United States)

Liu, Qingdong; Gu, Jianfeng

2017-09-01

The hierarchical distribution of Cu-rich precipitates (CRPs) and related partitioning and segregation behaviours of solute atoms were investigated in a 1.54 Cu-3.51 Ni (wt.%) low-carbon high-strength low-alloy (HSLA) steel after multistage heat treatment by using the combination of electron backscatter diffraction (EBSD), transmission electron microscopy (TEM) and atom probe tomography (APT). Intercritical tempering at 725 °C of as-quenched lathlike martensitic structure leads to the coprecipitation of CRPs at the periphery of a carbide precipitate which is possibly in its paraequilibrium state due to distinct solute segregation at the interface. The alloyed carbide and CRPs provide constituent elements for each other and make the coprecipitation thermodynamically favourable. Meanwhile, austenite reversion occurs to form fresh secondary martensite (FSM) zone where is rich in Cu and pertinent Ni and Mn atoms, which gives rise to a different distributional morphology of CRPs with large size and high density. In addition, conventional tempering at 500 °C leads to the formation of nanoscale Cu-rich clusters in α-Fe matrix. As a consequence, three populations of CRPs are hierarchically formed around carbide precipitate, at FSM zone and in α-Fe matrix. The formation of different precipitated features can be turned by controlling diffusion pathways of related solute atoms and further to tailor mechanical properties via proper multistage heat treatments.

Diffusion-Based Trajectory Observers with Variance Constraints

DEFF Research Database (Denmark)

Alcocer, Alex; Jouffroy, Jerome; Oliveira, Paulo

Diffusion-based trajectory observers have been recently proposed as a simple and efficient framework to solve diverse smoothing problems in underwater navigation. For instance, to obtain estimates of the trajectories of an underwater vehicle given position fixes from an acoustic positioning system...... of smoothing and is determined by resorting to trial and error. This paper presents a methodology to choose the observer gain by taking into account a priori information on the variance of the position measurement errors. Experimental results with data from an acoustic positioning system are presented...

Synthesis of hierarchical Ni(OH)(2) and NiO nanosheets and their adsorption kinetics and isotherms to Congo red in water.

Science.gov (United States)

Cheng, Bei; Le, Yao; Cai, Weiquan; Yu, Jiaguo

2011-01-30

Ni(OH)(2) and NiO nanosheets with hierarchical porous structures were synthesized by a simple chemical precipitation method using nickel chloride as precursors and urea as precipitating agent. The as-prepared samples were characterized by X-ray diffraction, scanning electron microscopy and nitrogen adsorption-desorption isotherms. Adsorption of Congo red (CR) onto the as-prepared samples from aqueous solutions was investigated and discussed. The pore structure analyses indicate that Ni(OH)(2) and NiO nanosheets are composed of at least three levels of hierarchical porous organization: small mesopores (ca. 3-5 nm), large mesopores (ca. 10-50 nm) and macropores (100-500 nm). The equilibrium adsorption data of CR on the as-prepared samples were analyzed by Langmuir and Freundlich models, suggesting that the Langmuir model provides the better correlation of the experimental data. The adsorption capacities for removal of CR was determined using the Langmuir equation and found to be 82.9, 151.7 and 39.7 mg/g for Ni(OH)(2) nanosheets, NiO nanosheets and NiO nanoparticles, respectively. Adsorption data were modeled using the pseudo-first-order, pseudo-second-order and intra-particle diffusion kinetics equations. The results indicate that pseudo-second-order kinetic equation and intra-particle diffusion model can better describe the adsorption kinetics. The as-prepared Ni(OH)(2) and NiO nanosheets are found to be effective adsorbents for the removal of Congo red pollutant from wastewater as a result of their unique hierarchical porous structures and high specific surface areas. Copyright © 2010 Elsevier B.V. All rights reserved.

Synthesis of hierarchical Ni(OH)2 and NiO nanosheets and their adsorption kinetics and isotherms to Congo red in water

International Nuclear Information System (INIS)

Cheng Bei; Le Yao; Cai Weiquan; Yu Jiaguo

2011-01-01

Ni(OH) 2 and NiO nanosheets with hierarchical porous structures were synthesized by a simple chemical precipitation method using nickel chloride as precursors and urea as precipitating agent. The as-prepared samples were characterized by X-ray diffraction, scanning electron microscopy and nitrogen adsorption-desorption isotherms. Adsorption of Congo red (CR) onto the as-prepared samples from aqueous solutions was investigated and discussed. The pore structure analyses indicate that Ni(OH) 2 and NiO nanosheets are composed of at least three levels of hierarchical porous organization: small mesopores (ca. 3-5 nm), large mesopores (ca. 10-50 nm) and macropores (100-500 nm). The equilibrium adsorption data of CR on the as-prepared samples were analyzed by Langmuir and Freundlich models, suggesting that the Langmuir model provides the better correlation of the experimental data. The adsorption capacities for removal of CR was determined using the Langmuir equation and found to be 82.9, 151.7 and 39.7 mg/g for Ni(OH) 2 nanosheets, NiO nanosheets and NiO nanoparticles, respectively. Adsorption data were modeled using the pseudo-first-order, pseudo-second-order and intra-particle diffusion kinetics equations. The results indicate that pseudo-second-order kinetic equation and intra-particle diffusion model can better describe the adsorption kinetics. The as-prepared Ni(OH) 2 and NiO nanosheets are found to be effective adsorbents for the removal of Congo red pollutant from wastewater as a result of their unique hierarchical porous structures and high specific surface areas.

Hierarchically organized layout for visualization of biochemical pathways.

Science.gov (United States)

Tsay, Jyh-Jong; Wu, Bo-Liang; Jeng, Yu-Sen

2010-01-01

Many complex pathways are described as hierarchical structures in which a pathway is recursively partitioned into several sub-pathways, and organized hierarchically as a tree. The hierarchical structure provides a natural way to visualize the global structure of a complex pathway. However, none of the previous research on pathway visualization explores the hierarchical structures provided by many complex pathways. In this paper, we aim to develop algorithms that can take advantages of hierarchical structures, and give layouts that explore the global structures as well as local structures of pathways. We present a new hierarchically organized layout algorithm to produce layouts for hierarchically organized pathways. Our algorithm first decomposes a complex pathway into sub-pathway groups along the hierarchical organization, and then partition each sub-pathway group into basic components. It then applies conventional layout algorithms, such as hierarchical layout and force-directed layout, to compute the layout of each basic component. Finally, component layouts are joined to form a final layout of the pathway. Our main contribution is the development of algorithms for decomposing pathways and joining layouts. Experiment shows that our algorithm is able to give comprehensible visualization for pathways with hierarchies, cycles as well as complex structures. It clearly renders the global component structures as well as the local structure in each component. In addition, it runs very fast, and gives better visualization for many examples from previous related research. 2009 Elsevier B.V. All rights reserved.

Mesoporous zeolite single crystal catalysts: Diffusion and catalysis in hierarchical zeolites

DEFF Research Database (Denmark)

Christensen, Christina Hviid; Johannsen, Kim; Toernqvist, Eric

2007-01-01

During the last years, several new routes to produce zeolites with controlled mesoporosity have appeared. Moreover, an improved catalytic performance of the resulting mesoporous zeolites over conventional zeolites has been demonstrated in several reactions. In most cases, the mesoporous zeolites...... exhibit higher catalytic activity, but in some cases also improved selectivity and longer catalyst lifetime has been reported. The beneficial effects of introducing mesopores into the zeolites has in most instances been attributed to improved mass transport to and from the active sites located...... in the zeolite micropores. Here, we briefly discuss the most important ways of introducing mesopores into zeolites and, for the first time, we show experimentally that the presence of mesopores dramatically increases the rate of diffusion in zeolite catalysts. This is done by studying the elution of iso...

Phase correction of MR perfusion/diffusion images

International Nuclear Information System (INIS)

Chenevert, T.L.; Pipe, J.G.; Brunberg, J.A.; Yeung, H.N.

1989-01-01

Apparent diffusion coefficient (ADC) and perfusion MR sequences are exceptionally sensitive to minute motion and, therefore, are prone to bulk motions that hamper ADC/perfusion quantification. The authors have developed a phase correction algorithm to substantially reduce this error. The algorithm uses a diffusion-insensitive data set to correct data that are diffusion sensitive but phase corrupt. An assumption of the algorithm is that bulk motion phase shifts are uniform in one dimension, although they may be arbitrarily large and variable from acquisition to acquisition. This is facilitated by orthogonal section selection. The correction is applied after one Fourier transform of a two-dimensional Fourier transform reconstruction. Imaging experiments on rat and human brain demonstrate significant artifact reduction in ADC and perfusion measurements

Fabrication of hierarchical porous ZnO-Al2O3 microspheres with enhanced adsorption performance

Science.gov (United States)

Lei, Chunsheng; Pi, Meng; Xu, Difa; Jiang, Chuanjia; Cheng, Bei

2017-12-01

Hierarchical porous ZnO-Al2O3 microspheres were fabricated through a simple hydrothermal route. The as-prepared hierarchical porous ZnO-Al2O3 composites were utilized as adsorbents to remove organic dye Congo red (CR) from water. The ZnO-Al2O3 composites had morphology of microspheres with diameters in the range of 12-16 μm, which were assembled by nanosheets with thicknesses of approximately 60 nm. The adsorption kinetics of CR onto the ZnO-Al2O3 composites was properly fitted by the pseudo-second-order kinetic model. The equilibrium adsorption data were perfectly described by the Langmuir isotherm and had a maximum adsorption capacity that reached 397 mg/g, which was significantly higher than the value of the pure alumina (Al2O3) and zinc oxide (ZnO) samples. The superior CR removal efficiency of the ZnO-Al2O3 composites was attributed to its well-developed hierarchical porous structures and larger specific surface area (201 m2/g), which were conducive to the diffusion and adsorption of CR molecules. Moreover, the regeneration study reveals that the ZnO-Al2O3 composites have suitable stability and reusability. The results also indicate that the as-prepared sample can act as a highly effective adsorbent in anionic dye removal from wastewater.

Hierarchical screening for multiple mental disorders.

Science.gov (United States)

Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Christensen, Helen; Mackinnon, Andrew J

2013-10-01

There is a need for brief, accurate screening when assessing multiple mental disorders. Two-stage hierarchical screening, consisting of brief pre-screening followed by a battery of disorder-specific scales for those who meet diagnostic criteria, may increase the efficiency of screening without sacrificing precision. This study tested whether more efficient screening could be gained using two-stage hierarchical screening than by administering multiple separate tests. Two Australian adult samples (N=1990) with high rates of psychopathology were recruited using Facebook advertising to examine four methods of hierarchical screening for four mental disorders: major depressive disorder, generalised anxiety disorder, panic disorder and social phobia. Using K6 scores to determine whether full screening was required did not increase screening efficiency. However, pre-screening based on two decision tree approaches or item gating led to considerable reductions in the mean number of items presented per disorder screened, with estimated item reductions of up to 54%. The sensitivity of these hierarchical methods approached 100% relative to the full screening battery. Further testing of the hierarchical screening approach based on clinical criteria and in other samples is warranted. The results demonstrate that a two-phase hierarchical approach to screening multiple mental disorders leads to considerable increases efficiency gains without reducing accuracy. Screening programs should take advantage of prescreeners based on gating items or decision trees to reduce the burden on respondents. © 2013 Elsevier B.V. All rights reserved.

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

Science.gov (United States)

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Self-assembled biomimetic superhydrophobic hierarchical arrays.

Science.gov (United States)

Yang, Hongta; Dou, Xuan; Fang, Yin; Jiang, Peng

2013-09-01

Here, we report a simple and inexpensive bottom-up technology for fabricating superhydrophobic coatings with hierarchical micro-/nano-structures, which are inspired by the binary periodic structure found on the superhydrophobic compound eyes of some insects (e.g., mosquitoes and moths). Binary colloidal arrays consisting of exemplary large (4 and 30 μm) and small (300 nm) silica spheres are first assembled by a scalable Langmuir-Blodgett (LB) technology in a layer-by-layer manner. After surface modification with fluorosilanes, the self-assembled hierarchical particle arrays become superhydrophobic with an apparent water contact angle (CA) larger than 150°. The throughput of the resulting superhydrophobic coatings with hierarchical structures can be significantly improved by templating the binary periodic structures of the LB-assembled colloidal arrays into UV-curable fluoropolymers by a soft lithography approach. Superhydrophobic perfluoroether acrylate hierarchical arrays with large CAs and small CA hysteresis can be faithfully replicated onto various substrates. Both experiments and theoretical calculations based on the Cassie's dewetting model demonstrate the importance of the hierarchical structure in achieving the final superhydrophobic surface states. Copyright © 2013 Elsevier Inc. All rights reserved.

Enhancement of Unequal Error Protection Properties of LDPC Codes

Directory of Open Access Journals (Sweden)

Poulliat Charly

2007-01-01

Full Text Available It has been widely recognized in the literature that irregular low-density parity-check (LDPC codes exhibit naturally an unequal error protection (UEP behavior. In this paper, we propose a general method to emphasize and control the UEP properties of LDPC codes. The method is based on a hierarchical optimization of the bit node irregularity profile for each sensitivity class within the codeword by maximizing the average bit node degree while guaranteeing a minimum degree as high as possible. We show that this optimization strategy is efficient, since the codes that we optimize show better UEP capabilities than the codes optimized for the additive white Gaussian noise channel.

Hierarchically structured, nitrogen-doped carbon membranes

KAUST Repository

Wang, Hong

2017-08-03

The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced on a large-scale approach. The unique HNDCM holds great promise as components in separation and advanced carbon devices because they could offer unconventional fluidic transport phenomena on the nanoscale. Overall, the invention set forth herein covers a hierarchically structured, nitrogen-doped carbon membranes and methods of making and using such a membranes.

Hierarchical Rhetorical Sentence Categorization for Scientific Papers

Science.gov (United States)

Rachman, G. H.; Khodra, M. L.; Widyantoro, D. H.

2018-03-01

Important information in scientific papers can be composed of rhetorical sentences that is structured from certain categories. To get this information, text categorization should be conducted. Actually, some works in this task have been completed by employing word frequency, semantic similarity words, hierarchical classification, and the others. Therefore, this paper aims to present the rhetorical sentence categorization from scientific paper by employing TF-IDF and Word2Vec to capture word frequency and semantic similarity words and employing hierarchical classification. Every experiment is tested in two classifiers, namely Naïve Bayes and SVM Linear. This paper shows that hierarchical classifier is better than flat classifier employing either TF-IDF or Word2Vec, although it increases only almost 2% from 27.82% when using flat classifier until 29.61% when using hierarchical classifier. It shows also different learning model for child-category can be built by hierarchical classifier.

Comparison of apparent diffusion coefficients (ADCs) between two-point and multi-point analyses using high-B-value diffusion MR imaging

International Nuclear Information System (INIS)

Kubo, Hitoshi; Maeda, Masayuki; Araki, Akinobu

2001-01-01

We evaluated the accuracy of calculating apparent diffusion coefficients (ADCs) using high-B-value diffusion images. Echo planar diffusion-weighted MR images were obtained at 1.5 tesla in five standard locations in six subjects using gradient strengths corresponding to B values from 0 to 3000 s/mm 2 . Estimation of ADCs was made using two methods: a nonlinear regression model using measurements from a full set of B values (multi-point method) and linear estimation using B values of 0 and max only (two-point method). A high correlation between the two methods was noted (r=0.99), and the mean percentage differences were -0.53% and 0.53% in phantom and human brain, respectively. These results suggest there is little error in estimating ADCs calculated by the two-point technique using high-B-value diffusion MR images. (author)

Hierarchical Statistical 3D ' Atomistic' Simulation of Decanano MOSFETs: Drift-Diffusion, Hydrodynamic and Quantum Mechanical Approaches

Science.gov (United States)

Asenov, Asen; Brown, A. R.; Slavcheva, G.; Davies, J. H.

2000-01-01

When MOSFETs are scaled to deep submicron dimensions the discreteness and randomness of the dopant charges in the channel region introduces significant fluctuations in the device characteristics. This effect, predicted 20 year ago, has been confirmed experimentally and in simulation studies. The impact of the fluctuations on the functionality, yield, and reliability of the corresponding systems shifts the paradigm of the numerical device simulation. It becomes insufficient to simulate only one device representing one macroscopical design in a continuous charge approximation. An ensemble of macroscopically identical but microscopically different devices has to be characterized by simulation of statistically significant samples. The aims of the numerical simulations shift from predicting the characteristics of a single device with continuous doping towards estimating the mean values and the standard deviations of basic design parameters such as threshold voltage, subthreshold slope, transconductance, drive current, etc. for the whole ensemble of 'atomistically' different devices in the system. It has to be pointed out that even the mean values obtained from 'atomistic' simulations are not identical to the values obtained from continuous doping simulations. In this paper we present a hierarchical approach to the 'atomistic' simulation of aggressively scaled decanano MOSFETs. A full scale 3D drift-diffusion'atomostic' simulation approach is first described and used for verification of the more economical, but also more restricted, options. To reduce the processor time and memory requirements at high drain voltage we have developed a self-consistent option based on a thin slab solution of the current continuity equation only in the channel region. This is coupled to the Poisson's equation solution in the whole simulation domain in the Gummel iteration cycles. The accuracy of this approach is investigated in comparison with the full self-consistent solution. At low drain

Effective Diffusion Coefficients in Coal Chars

DEFF Research Database (Denmark)

Johnsson, Jan Erik; Jensen, Anker

2001-01-01

Knowledge of effective diffusion coefficients in char particles is important when interpreting experimental reactivity measurements and modeling char combustion or NO and N2O reduction. In this work, NO and N2O reaction with a bituminous coal char was studied in a fixed-bed quartz glass reactor....... In the case of strong pore diffusion limitations, the error in the interpretation of experimental results using the mean pore radius could be a factor of 5 on the intrinsic rate constant. For an average coal char reacting with oxygen at 1300 K, this would be the case for particle sizes larger than about 50...

Instrumentation for thermal diffusivity determination of sintered materials

International Nuclear Information System (INIS)

Turquetti Filho, R.

1990-01-01

A new procedure to measure the sinterized materials thermal diffusivity, using the heat pulse method was developed in this work. The experimental data were performed at room temperature with UO sub(2), ThO sub(2), and Al sub(2)O sub(3) samples with 94%, 95%, and 96% of theoretical densities, respectively. Nondimensional root mean square deviation for theoretical function fitting was found to be on the order, of 10 sup(-3). The total error associated with the measurements for thermal diffusivity was ± 5%. (author)

Arbitrary Dimension Convection-Diffusion Schemes for Space-Time Discretizations

Energy Technology Data Exchange (ETDEWEB)

Bank, Randolph E. [Univ. of California, San Diego, CA (United States); Vassilevski, Panayot S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Zikatanov, Ludmil T. [Bulgarian Academy of Sciences, Sofia (Bulgaria)

2016-01-20

This note proposes embedding a time dependent PDE into a convection-diffusion type PDE (in one space dimension higher) with singularity, for which two discretization schemes, the classical streamline-diffusion and the EAFE (edge average finite element) one, are investigated in terms of stability and error analysis. The EAFE scheme, in particular, is extended to be arbitrary order which is of interest on its own. Numerical results, in combined space-time domain demonstrate the feasibility of the proposed approach.

Processing of hierarchical syntactic structure in music.

Science.gov (United States)

Koelsch, Stefan; Rohrmeier, Martin; Torrecuso, Renzo; Jentschke, Sebastian

2013-09-17

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions in which the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with long-distance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

Hierarchical Nanoceramics for Industrial Process Sensors

Energy Technology Data Exchange (ETDEWEB)

Ruud, James, A.; Brosnan, Kristen, H.; Striker, Todd; Ramaswamy, Vidya; Aceto, Steven, C.; Gao, Yan; Willson, Patrick, D.; Manoharan, Mohan; Armstrong, Eric, N., Wachsman, Eric, D.; Kao, Chi-Chang

2011-07-15

This project developed a robust, tunable, hierarchical nanoceramics materials platform for industrial process sensors in harsh-environments. Control of material structure at multiple length scales from nano to macro increased the sensing response of the materials to combustion gases. These materials operated at relatively high temperatures, enabling detection close to the source of combustion. It is anticipated that these materials can form the basis for a new class of sensors enabling widespread use of efficient combustion processes with closed loop feedback control in the energy-intensive industries. The first phase of the project focused on materials selection and process development, leading to hierarchical nanoceramics that were evaluated for sensing performance. The second phase focused on optimizing the materials processes and microstructures, followed by validation of performance of a prototype sensor in a laboratory combustion environment. The objectives of this project were achieved by: (1) synthesizing and optimizing hierarchical nanostructures; (2) synthesizing and optimizing sensing nanomaterials; (3) integrating sensing functionality into hierarchical nanostructures; (4) demonstrating material performance in a sensing element; and (5) validating material performance in a simulated service environment. The project developed hierarchical nanoceramic electrodes for mixed potential zirconia gas sensors with increased surface area and demonstrated tailored electrocatalytic activity operable at high temperatures enabling detection of products of combustion such as NOx close to the source of combustion. Methods were developed for synthesis of hierarchical nanostructures with high, stable surface area, integrated catalytic functionality within the structures for gas sensing, and demonstrated materials performance in harsh lab and combustion gas environments.

The Case for a Hierarchical Cosmology

Science.gov (United States)

Vaucouleurs, G. de

1970-01-01

The development of modern theoretical cosmology is presented and some questionable assumptions of orthodox cosmology are pointed out. Suggests that recent observations indicate that hierarchical clustering is a basic factor in cosmology. The implications of hierarchical models of the universe are considered. Bibliography. (LC)

Classification using Hierarchical Naive Bayes models

DEFF Research Database (Denmark)

Langseth, Helge; Dyhre Nielsen, Thomas

2006-01-01

Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe......, termed Hierarchical Naïve Bayes models. Hierarchical Naïve Bayes models extend the modeling flexibility of Naïve Bayes models by introducing latent variables to relax some of the independence statements in these models. We propose a simple algorithm for learning Hierarchical Naïve Bayes models...

Hierarchical mesosilicalite nanoformulation integrated with cisplatin exhibits target-specific efficient anticancer activity

Science.gov (United States)

Jermy, B. Rabindran; Acharya, Sadananda; Ravinayagam, Vijaya; Alghamdi, Hajer Saleh; Akhtar, Sultan; Basuwaidan, Rehab S.

2018-04-01

Hierarchically structured zeolitic ZSM-5 and meso MCM-41 interlinked domain had an impeccable use as catalysis in many applications. The aim of the study was to develop a new drug delivery nanoformulation, specifically, cisplatin/mesosilicalite using top-down approach for cancer therapy. Hierarchical mesosilicalite with variable porosity was synthesized using alkaline molar solution (0.2 and 0.7 M NaOH) and was loaded with cisplatin through equilibrium adsorption technique. Physico-chemical properties of the nanoformulation (IAUM-56—Imam Abdulrahman Bin Faisal University Mesosilicalite-56) were characterized using X-ray diffraction, surface area analysis (BET), Fourier transformed infrared spectroscopy (FT-IR), diffuse reflectance UV-Vis spectroscopy, and transmission electron microscopy. Drug release study and anticancer activity were assayed on HeLa and MCF7 cancer cells using MTT assay. X-ray diffraction pattern showed interrelated meso- and microphases, while BET analysis revealed considerable mesoporosity formation with a remodulation of isotherm hysteresis indicating the presence of hierarchical pores. FT-IR showed the presence of nanozeolitic subunits into mesostructure with a band at about 550 cm-1. IAUM-56 demonstrated high cytotoxic activity against HeLa cancer cells with an LC50 of 0.02 mg/ml, MCF7 cancer cells with an LC50 of 0.05 mg/ml, and less toxic to normal fibroblast cells with an LC50 of approximately ten times higher at 0.5 mg/ml. Overall, IAUM-56 showed a high rate of sustained release of cisplatin imparting target specific cytotoxic effect against tumor cells with at least tenfold lower toxicity on normal fibroblast cells. Our nanoformulation has the potential use in cancer therapy as a targeted drug delivery system.

Improved Adhesion and Compliancy of Hierarchical Fibrillar Adhesives.

Science.gov (United States)

Li, Yasong; Gates, Byron D; Menon, Carlo

2015-08-05

The gecko relies on van der Waals forces to cling onto surfaces with a variety of topography and composition. The hierarchical fibrillar structures on their climbing feet, ranging from mesoscale to nanoscale, are hypothesized to be key elements for the animal to conquer both smooth and rough surfaces. An epoxy-based artificial hierarchical fibrillar adhesive was prepared to study the influence of the hierarchical structures on the properties of a dry adhesive. The presented experiments highlight the advantages of a hierarchical structure despite a reduction of overall density and aspect ratio of nanofibrils. In contrast to an adhesive containing only nanometer-size fibrils, the hierarchical fibrillar adhesives exhibited a higher adhesion force and better compliancy when tested on an identical substrate.

One wouldn't expect an expert bowler to hit only two pins: Hierarchical predictive processing of agent-caused events.

Science.gov (United States)

Heil, Lieke; Kwisthout, Johan; van Pelt, Stan; van Rooij, Iris; Bekkering, Harold

2018-01-01

Evidence is accumulating that our brains process incoming information using top-down predictions. If lower level representations are correctly predicted by higher level representations, this enhances processing. However, if they are incorrectly predicted, additional processing is required at higher levels to "explain away" prediction errors. Here, we explored the potential nature of the models generating such predictions. More specifically, we investigated whether a predictive processing model with a hierarchical structure and causal relations between its levels is able to account for the processing of agent-caused events. In Experiment 1, participants watched animated movies of "experienced" and "novice" bowlers. The results are in line with the idea that prediction errors at a lower level of the hierarchy (i.e., the outcome of how many pins fell down) slow down reporting of information at a higher level (i.e., which agent was throwing the ball). Experiments 2 and 3 suggest that this effect is specific to situations in which the predictor is causally related to the outcome. Overall, the study supports the idea that a hierarchical predictive processing model can account for the processing of observed action outcomes and that the predictions involved are specific to cases where action outcomes can be predicted based on causal knowledge.

Class hierarchical test case generation algorithm based on expanded EMDPN model

Institute of Scientific and Technical Information of China (English)

LI Jun-yi; GONG Hong-fang; HU Ji-ping; ZOU Bei-ji; SUN Jia-guang

2006-01-01

A new model of event and message driven Petri network(EMDPN) based on the characteristic of class interaction for messages passing between two objects was extended. Using EMDPN interaction graph, a class hierarchical test-case generation algorithm with cooperated paths (copaths) was proposed, which can be used to solve the problems resulting from the class inheritance mechanism encountered in object-oriented software testing such as oracle, message transfer errors, and unreachable statement. Finally, the testing sufficiency was analyzed with the ordered sequence testing criterion(OSC). The results indicate that the test cases stemmed from newly proposed automatic algorithm of copaths generation satisfies synchronization message sequences testing criteria, therefore the proposed new algorithm of copaths generation has a good coverage rate.

Diffusive Wave Approximation to the Shallow Water Equations: Computational Approach

KAUST Repository

Collier, Nathan; Radwan, Hany; Dalcin, Lisandro; Calo, Victor M.

2011-01-01

We discuss the use of time adaptivity applied to the one dimensional diffusive wave approximation to the shallow water equations. A simple and computationally economical error estimator is discussed which enables time-step size adaptivity

Diffusion of zinc into an unpassivated surface of indium phosphide

International Nuclear Information System (INIS)

Budko, T.O.; Gushchinskaya, E.V.; Emelyanenko, Yu.S.; Malyshev, S.A.

1989-01-01

Peculiarities are studied of the diffusion of Zn into an unpassivated surface of InP in an open gasflow system. In the region where the carrier concentration profile is described by an erfc (error function compliment), the diffusion coefficient and activation energy are determined. It is shown that thermal processes cause changes in the charge state of Zn in InP which result in a variation of the carrier profile in the semiconductor. (author)

Reduction of numerical diffusion in three-dimensional vortical flows using a coupled Eulerian/Lagrangian solution procedure

Science.gov (United States)

Felici, Helene M.; Drela, Mark

1993-01-01

A new approach based on the coupling of an Eulerian and a Lagrangian solver, aimed at reducing the numerical diffusion errors of standard Eulerian time-marching finite-volume solvers, is presented. The approach is applied to the computation of the secondary flow in two bent pipes and the flow around a 3D wing. Using convective point markers the Lagrangian approach provides a correction of the basic Eulerian solution. The Eulerian flow in turn integrates in time the Lagrangian state-vector. A comparison of coarse and fine grid Eulerian solutions makes it possible to identify numerical diffusion. It is shown that the Eulerian/Lagrangian approach is an effective method for reducing numerical diffusion errors.

An adaptive sampling method for variable-fidelity surrogate models using improved hierarchical kriging

Science.gov (United States)

Hu, Jiexiang; Zhou, Qi; Jiang, Ping; Shao, Xinyu; Xie, Tingli

2018-01-01

Variable-fidelity (VF) modelling methods have been widely used in complex engineering system design to mitigate the computational burden. Building a VF model generally includes two parts: design of experiments and metamodel construction. In this article, an adaptive sampling method based on improved hierarchical kriging (ASM-IHK) is proposed to refine the improved VF model. First, an improved hierarchical kriging model is developed as the metamodel, in which the low-fidelity model is varied through a polynomial response surface function to capture the characteristics of a high-fidelity model. Secondly, to reduce local approximation errors, an active learning strategy based on a sequential sampling method is introduced to make full use of the already required information on the current sampling points and to guide the sampling process of the high-fidelity model. Finally, two numerical examples and the modelling of the aerodynamic coefficient for an aircraft are provided to demonstrate the approximation capability of the proposed approach, as well as three other metamodelling methods and two sequential sampling methods. The results show that ASM-IHK provides a more accurate metamodel at the same simulation cost, which is very important in metamodel-based engineering design problems.

Transport equivalent diffusion constants for reflector region in PWRs

International Nuclear Information System (INIS)

Tahara, Yoshihisa; Sekimoto, Hiroshi

2002-01-01

The diffusion-theory-based nodal method is widely used in PWR core designs for reason of its high computing speed in three-dimensional calculations. The baffle/reflector (B/R) constants used in nodal calculations are usually calculated based on a one-dimensional transport calculation. However, to achieve high accuracy of assembly power prediction, two-dimensional model is needed. For this reason, the method for calculating transport equivalent diffusion constants of reflector material was developed so that the neutron currents on the material boundaries could be calculated exactly in diffusion calculations. Two-dimensional B/R constants were calculated using the transport equivalent diffusion constants in the two-dimensional diffusion calculation whose geometry reflected the actual material configuration in the reflector region. The two-dimensional B/R constants enabled us to predict assembly power within an error of 1.5% at hot full power conditions. (author)

Analysis of ligand-protein exchange by Clustering of Ligand Diffusion Coefficient Pairs (CoLD-CoP)

Science.gov (United States)

Snyder, David A.; Chantova, Mihaela; Chaudhry, Saadia

2015-06-01

NMR spectroscopy is a powerful tool in describing protein structures and protein activity for pharmaceutical and biochemical development. This study describes a method to determine weak binding ligands in biological systems by using hierarchic diffusion coefficient clustering of multidimensional data obtained with a 400 MHz Bruker NMR. Comparison of DOSY spectrums of ligands of the chemical library in the presence and absence of target proteins show translational diffusion rates for small molecules upon interaction with macromolecules. For weak binders such as compounds found in fragment libraries, changes in diffusion rates upon macromolecular binding are on the order of the precision of DOSY diffusion measurements, and identifying such subtle shifts in diffusion requires careful statistical analysis. The "CoLD-CoP" (Clustering of Ligand Diffusion Coefficient Pairs) method presented here uses SAHN clustering to identify protein-binders in a chemical library or even a not fully characterized metabolite mixture. We will show how DOSY NMR and the "CoLD-CoP" method complement each other in identifying the most suitable candidates for lysozyme and wheat germ acid phosphatase.

Application of TRIZ Methodology in Diffusion Welding System Optimization

Science.gov (United States)

Ravinder Reddy, N.; Satyanarayana, V. V.; Prashanthi, M.; Suguna, N.

2017-12-01

Welding is tremendously used in metal joining processes in the manufacturing process. In recent years, diffusion welding method has significantly increased the quality of a weld. Nevertheless, diffusion welding has some extent short research and application progress. Therefore, diffusion welding has a lack of relevant information, concerned with the joining of thick and thin materials with or without interlayers, on welding design such as fixture, parameters selection and integrated design. This article intends to combine innovative methods in the application of diffusion welding design. This will help to decrease trial and error or failure risks in the welding process being guided by the theory of inventive problem solving (TRIZ) design method. This article hopes to provide welding design personnel with innovative design ideas under research and for practical application.

Leadership styles across hierarchical levels in nursing departments.

Science.gov (United States)

Stordeur, S; Vandenberghe, C; D'hoore, W

2000-01-01

Some researchers have reported on the cascading effect of transformational leadership across hierarchical levels. One study examined this effect in nursing, but it was limited to a single hospital. To examine the cascading effect of leadership styles across hierarchical levels in a sample of nursing departments and to investigate the effect of hierarchical level on the relationships between leadership styles and various work outcomes. Based on a sample of eight hospitals, the cascading effect was tested using correlation analysis. The main sources of variation among leadership scores were determined with analyses of variance (ANOVA), and the interaction effect of hierarchical level and leadership styles on criterion variables was tested with moderated regression analysis. No support was found for a cascading effect of leadership across hierarchical levels. Rather, the variation of leadership scores was explained primarily by the organizational context. Transformational leadership had a stronger impact on criterion variables than transactional leadership. Interaction effects between leadership styles and hierarchical level were observed only for perceived unit effectiveness. The hospital's structure and culture are major determinants of leadership styles.

Error Concealment using Data Hiding in Wireless Image Transmission

Directory of Open Access Journals (Sweden)

A. Akbari

2016-11-01

Full Text Available The transmission of image/video over unreliable medium like wireless networks generally results in receiving a damaged image/video. In this paper, a novel image error concealment scheme based on the idea of data hiding and Set Partitioning In Hierarchical Trees (SPIHT coding is investigated. In the encoder side, the coefficients of wavelet decomposed image are partitioned into “perfect trees”. The SPIHT coder is applied to encode each per-fect tree independently and generate an efficiently compressed reference code. This code is then embedded into the coefficients of another perfect tree which is located in a different place, using a robust data hiding scheme based on Quantization Index Modulation (QIM. In the decoder side, if a part of the image is lost, the algorithm extracts the embedded code for reference trees related to this part to reconstruct the lost information. Performance results show that for an error prone transmission, the proposed technique is promising to efficiently conceal the lost areas of the transmitted image.

COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.

Science.gov (United States)

Cui, Licong

Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on the knowledge provided within the targeted ontology. This paper proposes a novel cross-ontology analysis method, Cross-Ontology Hierarchical Relation Examination (COHeRE), to detect inconsistencies and possible errors in hierarchical relations across multiple ontologies. COHeRE leverages the Unified Medical Language System (UMLS) knowledge source and the MapReduce cloud computing technique for systematic, large-scale ontology quality assurance work. COHeRE consists of three main steps with the UMLS concepts and relations as the input. First, the relations claimed in source vocabularies are filtered and aggregated for each pair of concepts. Second, inconsistent relations are detected if a concept pair is related by different types of relations in different source vocabularies. Finally, the uncovered inconsistent relations are voted according to their number of occurrences across different source vocabularies. The voting result together with the inconsistent relations serve as the output of COHeRE for possible ontological change. The highest votes provide initial suggestion on how such inconsistencies might be fixed. In UMLS, 138,987 concept pairs were found to have inconsistent relationships across multiple source vocabularies. 40 inconsistent concept pairs involving hierarchical relationships were randomly selected and manually reviewed by a human expert. 95.8% of the inconsistent relations involved in these concept pairs indeed exist in their source vocabularies rather than being introduced by mistake in the UMLS integration process. 73.7% of the concept pairs with suggested relationship were agreed by the human expert. The effectiveness of COHeRE indicates that UMLS provides a promising environment to enhance

Learning with hierarchical-deep models.

Science.gov (United States)

Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

2013-08-01

We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

Facile synthesis of flower-like BiOI hierarchical spheres at room temperature with high visible-light photocatalytic activity

International Nuclear Information System (INIS)

Wang, Xiao-jing; Li, Fa-tang; Li, Dong-yan; Liu, Rui-hong; Liu, Shuang-jun

2015-01-01

Graphical abstract: - Highlights: • Flower-like BiOI hierarchical sphere is obtained in the presence of ethylene glycol. • A template free hydrolysis route is employed at room temperature. • Ethylene glycol plays an important role in assembling BiOI nanoflakes to form spheres. • The BiOI sphere shows high visible-light photocatalytic activity and good stability. - Abstract: Flower-like BiOI hierarchical spheres are prepared at room temperature via a template free route simply by dropping water into ethylene glycol (EG) solution containing reactants based on the hydrolysis and oriented assembly roles of water and EG, respectively. The BiOI samples are characterized by X-ray diffraction (XRD), nitrogen adsorption/desorption, emission scanning electron microscopy (SEM), UV–Vis diffuse reflectance spectra (UV–Vis DRS), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). The photocatalytic reaction rate constant of the as-prepared BiOI hierarchical spheres is 15.8, 13.3, and 2.0 times that of BiOI nanoflakes obtained in the absence of EG in degradation of anionic dye (methyl orange), cationic dye (methylene blue), and colorless target pollutant (phenol), respectively, under the visible-light irradiation, which can be attributed to its unique flower-like structure for utilization of light, small crystal size, and large specific surface area

Novel hollow microspheres of hierarchical zinc-aluminum layered double hydroxides and their enhanced adsorption capacity for phosphate in water

International Nuclear Information System (INIS)

Zhou, Jiabin; Yang, Siliang; Yu, Jiaguo; Shu, Zhan

2011-01-01

Highlights: → Hierarchical Zn-Al LDHs hollow microspheres were first synthesized by a simple hydrothermal method using urea as precipitating agent. → The morphology of Zn-Al LDHs can be tailored from irregular platelet to hollow microspheres by simply varying concentrations of urea. → The as-prepared samples exhibit high adsorption capacity (54.1-232 mg/g) for phosphate from aqueous solution. - Abstract: Hollow microspheres of hierarchical Zn-Al layered double hydroxides (LDHs) were synthesized by a simple hydrothermal method using urea as precipitating agent. The morphology and microstructure of the as-prepared samples were characterized by X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), nitrogen adsorption-desorption isotherms and fourier transform infrared (FTIR) spectroscopy. It was found that the morphology of hierarchical Zn-Al LDHs can be tuned from irregular platelets to hollow microspheres by simply varying concentrations of urea. The effects of initial phosphate concentration and contact time on phosphate adsorption using various Zn-Al LDHs and their calcined products (LDOs) were investigated from batch tests. Our results indicate that the equilibrium adsorption data were best fitted by Langmuir isothermal model, with the maximum adsorption capacity of 54.1-232 mg/g; adsorption kinetics follows the pseudo-second-order kinetic equation and intra-particle diffusion model. In addition, Zn-Al LDOs are shown to be effective adsorbents for removing phosphate from aqueous solutions due to their hierarchical porous structures and high specific surface areas.

Color Histogram Diffusion for Image Enhancement

Science.gov (United States)

Kim, Taemin

2011-01-01

Various color histogram equalization (CHE) methods have been proposed to extend grayscale histogram equalization (GHE) for color images. In this paper a new method called histogram diffusion that extends the GHE method to arbitrary dimensions is proposed. Ranges in a histogram are specified as overlapping bars of uniform heights and variable widths which are proportional to their frequencies. This diagram is called the vistogram. As an alternative approach to GHE, the squared error of the vistogram from the uniform distribution is minimized. Each bar in the vistogram is approximated by a Gaussian function. Gaussian particles in the vistoram diffuse as a nonlinear autonomous system of ordinary differential equations. CHE results of color images showed that the approach is effective.

Hierarchically structured MnO2 nanowires supported on hollow Ni dendrites for high-performance supercapacitors

Science.gov (United States)

Sun, Zhipeng; Firdoz, Shaik; Ying-Xuan Yap, Esther; Li, Lan; Lu, Xianmao

2013-05-01

We report a hierarchical Ni@MnO2 structure consisting of MnO2 nanowires supported on hollow Ni dendrites for high-performance supercapacitors. The Ni@MnO2 structure, which was prepared via a facile electrodeposition method, is highly porous and appears like a forest of pine trees grown vertically on a substrate. At a MnO2 mass loading of 0.35 mg cm-2, the Ni@MnO2 electrode demonstrated a specific capacitance of 1125 F g-1 that is close to the theoretical value. In addition, a remarkable high-rate performance (766 F g-1 at a discharge current density of 100 A g-1) was achieved. Electrochemical tests in a two-electrode configuration for the Ni@MnO2 structure with a high MnO2 loading of 3.6 mg cm-2 showed a low equivalent series resistance (ESR) of 1 Ω and a high specific power of 72 kW kg-1. This superior performance can be attributed to the highly porous and hierarchical structure of Ni@MnO2 that favors rapid diffusion of an electrolyte, highly conductive pathway for electron transport, and efficient material utilization.We report a hierarchical Ni@MnO2 structure consisting of MnO2 nanowires supported on hollow Ni dendrites for high-performance supercapacitors. The Ni@MnO2 structure, which was prepared via a facile electrodeposition method, is highly porous and appears like a forest of pine trees grown vertically on a substrate. At a MnO2 mass loading of 0.35 mg cm-2, the Ni@MnO2 electrode demonstrated a specific capacitance of 1125 F g-1 that is close to the theoretical value. In addition, a remarkable high-rate performance (766 F g-1 at a discharge current density of 100 A g-1) was achieved. Electrochemical tests in a two-electrode configuration for the Ni@MnO2 structure with a high MnO2 loading of 3.6 mg cm-2 showed a low equivalent series resistance (ESR) of 1 Ω and a high specific power of 72 kW kg-1. This superior performance can be attributed to the highly porous and hierarchical structure of Ni@MnO2 that favors rapid diffusion of an electrolyte, highly

Sampling-free Bayesian inversion with adaptive hierarchical tensor representations

Science.gov (United States)

Eigel, Martin; Marschall, Manuel; Schneider, Reinhold

2018-03-01

A sampling-free approach to Bayesian inversion with an explicit polynomial representation of the parameter densities is developed, based on an affine-parametric representation of a linear forward model. This becomes feasible due to the complete treatment in function spaces, which requires an efficient model reduction technique for numerical computations. The advocated perspective yields the crucial benefit that error bounds can be derived for all occuring approximations, leading to provable convergence subject to the discretization parameters. Moreover, it enables a fully adaptive a posteriori control with automatic problem-dependent adjustments of the employed discretizations. The method is discussed in the context of modern hierarchical tensor representations, which are used for the evaluation of a random PDE (the forward model) and the subsequent high-dimensional quadrature of the log-likelihood, alleviating the ‘curse of dimensionality’. Numerical experiments demonstrate the performance and confirm the theoretical results.

Predicting in vivo glioma growth with the reaction diffusion equation constrained by quantitative magnetic resonance imaging data

International Nuclear Information System (INIS)

Hormuth II, David A; Weis, Jared A; Barnes, Stephanie L; Miga, Michael I; Yankeelov, Thomas E; Rericha, Erin C; Quaranta, Vito

2015-01-01

Reaction–diffusion models have been widely used to model glioma growth. However, it has not been shown how accurately this model can predict future tumor status using model parameters (i.e., tumor cell diffusion and proliferation) estimated from quantitative in vivo imaging data. To this end, we used in silico studies to develop the methods needed to accurately estimate tumor specific reaction–diffusion model parameters, and then tested the accuracy with which these parameters can predict future growth. The analogous study was then performed in a murine model of glioma growth. The parameter estimation approach was tested using an in silico tumor ‘grown’ for ten days as dictated by the reaction–diffusion equation. Parameters were estimated from early time points and used to predict subsequent growth. Prediction accuracy was assessed at global (total volume and Dice value) and local (concordance correlation coefficient, CCC) levels. Guided by the in silico study, rats (n = 9) with C6 gliomas, imaged with diffusion weighted magnetic resonance imaging, were used to evaluate the model’s accuracy for predicting in vivo tumor growth. The in silico study resulted in low global (tumor volume error 0.92) and local (CCC values >0.80) level errors for predictions up to six days into the future. The in vivo study showed higher global (tumor volume error >11.7%, Dice <0.81) and higher local (CCC <0.33) level errors over the same time period. The in silico study shows that model parameters can be accurately estimated and used to accurately predict future tumor growth at both the global and local scale. However, the poor predictive accuracy in the experimental study suggests the reaction–diffusion equation is an incomplete description of in vivo C6 glioma biology and may require further modeling of intra-tumor interactions including segmentation of (for example) proliferative and necrotic regions. (paper)

Hierarchical analysis of acceptable use policies

Directory of Open Access Journals (Sweden)

P. A. Laughton

2008-01-01

Full Text Available Acceptable use policies (AUPs are vital tools for organizations to protect themselves and their employees from misuse of computer facilities provided. A well structured, thorough AUP is essential for any organization. It is impossible for an effective AUP to deal with every clause and remain readable. For this reason, some sections of an AUP carry more weight than others, denoting importance. The methodology used to develop the hierarchical analysis is a literature review, where various sources were consulted. This hierarchical approach to AUP analysis attempts to highlight important sections and clauses dealt with in an AUP. The emphasis of the hierarchal analysis is to prioritize the objectives of an AUP.

Maximum likelihood estimation for integrated diffusion processes

DEFF Research Database (Denmark)

Baltazar-Larios, Fernando; Sørensen, Michael

We propose a method for obtaining maximum likelihood estimates of parameters in diffusion models when the data is a discrete time sample of the integral of the process, while no direct observations of the process itself are available. The data are, moreover, assumed to be contaminated...... EM-algorithm to obtain maximum likelihood estimates of the parameters in the diffusion model. As part of the algorithm, we use a recent simple method for approximate simulation of diffusion bridges. In simulation studies for the Ornstein-Uhlenbeck process and the CIR process the proposed method works...... by measurement errors. Integrated volatility is an example of this type of observations. Another example is ice-core data on oxygen isotopes used to investigate paleo-temperatures. The data can be viewed as incomplete observations of a model with a tractable likelihood function. Therefore we propose a simulated...

Error-related brain activity and error awareness in an error classification paradigm.

Science.gov (United States)

Di Gregorio, Francesco; Steinhauser, Marco; Maier, Martin E

2016-10-01

Error-related brain activity has been linked to error detection enabling adaptive behavioral adjustments. However, it is still unclear which role error awareness plays in this process. Here, we show that the error-related negativity (Ne/ERN), an event-related potential reflecting early error monitoring, is dissociable from the degree of error awareness. Participants responded to a target while ignoring two different incongruent distractors. After responding, they indicated whether they had committed an error, and if so, whether they had responded to one or to the other distractor. This error classification paradigm allowed distinguishing partially aware errors, (i.e., errors that were noticed but misclassified) and fully aware errors (i.e., errors that were correctly classified). The Ne/ERN was larger for partially aware errors than for fully aware errors. Whereas this speaks against the idea that the Ne/ERN foreshadows the degree of error awareness, it confirms the prediction of a computational model, which relates the Ne/ERN to post-response conflict. This model predicts that stronger distractor processing - a prerequisite of error classification in our paradigm - leads to lower post-response conflict and thus a smaller Ne/ERN. This implies that the relationship between Ne/ERN and error awareness depends on how error awareness is related to response conflict in a specific task. Our results further indicate that the Ne/ERN but not the degree of error awareness determines adaptive performance adjustments. Taken together, we conclude that the Ne/ERN is dissociable from error awareness and foreshadows adaptive performance adjustments. Our results suggest that the relationship between the Ne/ERN and error awareness is correlative and mediated by response conflict. Copyright © 2016 Elsevier Inc. All rights reserved.

Method of Parallel-Hierarchical Network Self-Training and its Application for Pattern Classification and Recognition

Directory of Open Access Journals (Sweden)

TIMCHENKO, L.

2012-11-01

Full Text Available Propositions necessary for development of parallel-hierarchical (PH network training methods are discussed in this article. Unlike already known structures of the artificial neural network, where non-normalized (absolute similarity criteria are used for comparison, the suggested structure uses a normalized criterion. Based on the analysis of training rules, a conclusion is made that application of two training methods with a teacher is optimal for PH network training: error correction-based training and memory-based training. Mathematical models of training and a combined method of PH network training for recognition of static and dynamic patterns are developed.

Virtual timers in hierarchical real-time systems

NARCIS (Netherlands)

Heuvel, van den M.M.H.P.; Holenderski, M.J.; Cools, W.A.; Bril, R.J.; Lukkien, J.J.; Zhu, D.

2009-01-01

Hierarchical scheduling frameworks (HSFs) provide means for composing complex real-time systems from welldefined subsystems. This paper describes an approach to provide hierarchically scheduled real-time applications with virtual event timers, motivated by the need for integrating priority

Catalytic conversion reactions mediated by single-file diffusion in linear nanopores: hydrodynamic versus stochastic behavior.

Science.gov (United States)

Ackerman, David M; Wang, Jing; Wendel, Joseph H; Liu, Da-Jiang; Pruski, Marek; Evans, James W

2011-03-21

We analyze the spatiotemporal behavior of species concentrations in a diffusion-mediated conversion reaction which occurs at catalytic sites within linear pores of nanometer diameter. Diffusion within the pores is subject to a strict single-file (no passing) constraint. Both transient and steady-state behavior is precisely characterized by kinetic Monte Carlo simulations of a spatially discrete lattice-gas model for this reaction-diffusion process considering various distributions of catalytic sites. Exact hierarchical master equations can also be developed for this model. Their analysis, after application of mean-field type truncation approximations, produces discrete reaction-diffusion type equations (mf-RDE). For slowly varying concentrations, we further develop coarse-grained continuum hydrodynamic reaction-diffusion equations (h-RDE) incorporating a precise treatment of single-file diffusion in this multispecies system. The h-RDE successfully describe nontrivial aspects of transient behavior, in contrast to the mf-RDE, and also correctly capture unreactive steady-state behavior in the pore interior. However, steady-state reactivity, which is localized near the pore ends when those regions are catalytic, is controlled by fluctuations not incorporated into the hydrodynamic treatment. The mf-RDE partly capture these fluctuation effects, but cannot describe scaling behavior of the reactivity.

Error Analysis of Variations on Larsen's Benchmark Problem

International Nuclear Information System (INIS)

Azmy, YY

2001-01-01

Error norms for three variants of Larsen's benchmark problem are evaluated using three numerical methods for solving the discrete ordinates approximation of the neutron transport equation in multidimensional Cartesian geometry. The three variants of Larsen's test problem are concerned with the incoming flux boundary conditions: unit incoming flux on the left and bottom edges (Larsen's configuration); unit, incoming flux only on the left edge; unit incoming flux only on the bottom edge. The three methods considered are the Diamond Difference (DD) method, and the constant-approximation versions of the Arbitrarily High Order Transport method of the Nodal type (AHOT-N), and of the Characteristic (AHOT-C) type. The cell-wise error is computed as the difference between the cell-averaged flux computed by each method and the exact value, then the L 1 , L 2 , and L ∞ error norms are calculated. The results of this study demonstrate that while integral error norms, i.e. L 1 , L 2 , converge to zero with mesh refinement, the pointwise L ∞ norm does not due to solution discontinuity across the singular characteristic. Little difference is observed between the error norm behavior of the three methods considered in spite of the fact that AHOT-C is locally exact, suggesting that numerical diffusion across the singular characteristic as the major source of error on the global scale. However, AHOT-C possesses a given accuracy in a larger fraction of computational cells than DD

Rapid innovation diffusion in social networks.

Science.gov (United States)

Kreindler, Gabriel E; Young, H Peyton

2014-07-22

Social and technological innovations often spread through social networks as people respond to what their neighbors are doing. Previous research has identified specific network structures, such as local clustering, that promote rapid diffusion. Here we derive bounds that are independent of network structure and size, such that diffusion is fast whenever the payoff gain from the innovation is sufficiently high and the agents' responses are sufficiently noisy. We also provide a simple method for computing an upper bound on the expected time it takes for the innovation to become established in any finite network. For example, if agents choose log-linear responses to what their neighbors are doing, it takes on average less than 80 revision periods for the innovation to diffuse widely in any network, provided that the error rate is at least 5% and the payoff gain (relative to the status quo) is at least 150%. Qualitatively similar results hold for other smoothed best-response functions and populations that experience heterogeneous payoff shocks.

Microscopy of hierarchically organized TiO{sub 2} photoelectrode for dye solar cells

Energy Technology Data Exchange (ETDEWEB)

Eskandar, A., E-mail: aeska07@gmail.com [Department of Electrical and Electronics, Universiti Teknologi PETRONAS, Tronoh, Perak (Malaysia); Mohamed, N. M., E-mail: noranimuti-mohamed@petronas.com.my [Centre of Innovative Nanostructures and Nanodevices, Universiti Teknologi PETRONAS, Tronoh, Perak (Malaysia)

2015-07-22

Research on improving the performance of dye solar cells has various aspects of the device being investigated. This paper analyzes the deliberately hierarchized photoelectrode configuration for DSC applications to improve the performance of DSCs. Multiple layers of differently composed TiO{sub 2} particle types namely aggregates and nanoparticles were deposited to form a photoelectrode with thickness of about 12 µm. The photoelectrodes were assembled into working DSCs with an active area of 1 cm{sup 2}. Measurement for solar power conversion performance was measured under 1 sun at AM1.5 spectrum simulated sunlight. Electron microscopy for photoelectrode analysis was conducted using Field Emission Scattering Electron Microscopy with enhanced resolution. External Quantum Efficiency was measured using a purpose built instrument. Kinetics were investigated using the Electrochemical Impedance Spectroscopy (EIS) measurement with a potentiostat. The best performing DSC is of the hierarchically organized photoelectrode with a photoconversion efficiency of 4.58%, an increase of 14% in comparison to the reference samples with fully aggregates configuration. Short circuit current density, Jsc increases by about 2.223 mA cm{sup −2} relative to the blanks. The electron microscopy confirmed expected thickness at around 10 µm and layers forming the photoelectrode being hierarchically deposited with ∼20 nm TiO{sub 2} nanoparticles and 450 nm TiO{sub 2} aggregates mixture composition. EQE improved especially for visible region of 500-550 nm light wavelengths with 12 % increase in the response of in that region. Improvement to the diffusion coefficient as measured by the EIS contributed to the performance increase of the photoelectrode configuration under investigation.

Hierarchical modeling and analysis for spatial data

CERN Document Server

Banerjee, Sudipto; Gelfand, Alan E

2003-01-01

Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

TYPE Ia SUPERNOVA LIGHT-CURVE INFERENCE: HIERARCHICAL BAYESIAN ANALYSIS IN THE NEAR-INFRARED

International Nuclear Information System (INIS)

Mandel, Kaisey S.; Friedman, Andrew S.; Kirshner, Robert P.; Wood-Vasey, W. Michael

2009-01-01

We present a comprehensive statistical analysis of the properties of Type Ia supernova (SN Ia) light curves in the near-infrared using recent data from Peters Automated InfraRed Imaging TELescope and the literature. We construct a hierarchical Bayesian framework, incorporating several uncertainties including photometric error, peculiar velocities, dust extinction, and intrinsic variations, for principled and coherent statistical inference. SN Ia light-curve inferences are drawn from the global posterior probability of parameters describing both individual supernovae and the population conditioned on the entire SN Ia NIR data set. The logical structure of the hierarchical model is represented by a directed acyclic graph. Fully Bayesian analysis of the model and data is enabled by an efficient Markov Chain Monte Carlo algorithm exploiting the conditional probabilistic structure using Gibbs sampling. We apply this framework to the JHK s SN Ia light-curve data. A new light-curve model captures the observed J-band light-curve shape variations. The marginal intrinsic variances in peak absolute magnitudes are σ(M J ) = 0.17 ± 0.03, σ(M H ) = 0.11 ± 0.03, and σ(M Ks ) = 0.19 ± 0.04. We describe the first quantitative evidence for correlations between the NIR absolute magnitudes and J-band light-curve shapes, and demonstrate their utility for distance estimation. The average residual in the Hubble diagram for the training set SNe at cz > 2000kms -1 is 0.10 mag. The new application of bootstrap cross-validation to SN Ia light-curve inference tests the sensitivity of the statistical model fit to the finite sample and estimates the prediction error at 0.15 mag. These results demonstrate that SN Ia NIR light curves are as effective as corrected optical light curves, and, because they are less vulnerable to dust absorption, they have great potential as precise and accurate cosmological distance indicators.

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

Directory of Open Access Journals (Sweden)

Zahra Sharafi

2017-01-01

Full Text Available Background. The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods. The ordinal logistic regression (OLR and hierarchical ordinal logistic regression (HOLR were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™ 4.0 collected from 576 healthy school children were analyzed. Results. Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions. The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

Hierarchical organization versus self-organization

OpenAIRE

Busseniers, Evo

2014-01-01

In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

Dynamic aperture and transverse proton diffusion in HERA

International Nuclear Information System (INIS)

Zimmermann, F.

1994-04-01

The dynamic aperture caused by persistent-current nonlinear field errors is an important concern in the design of superconducting hadron storage rings. The HERA proton ring is the second superconducting accelerator in operation. In this lecture note, its measured dynamic aperture is compared with that inferred from comprehensive trackig studies. To understand the difference between prediction and measurement, a semi-analytical method is developed for evaluating transverse diffusion rates due to various processes, such as modulational diffusion or sweeping diffusion this analysis makes use of parameters for high-order resonances in the transverse phase space, which are obtained by normal-form algorithms using differential-algebra software. This semi-analytical results are consistent wit the measurements, and suggest that the actual dynamic aperture is caused by an interplay of tune modulation and nonlinear magnetic fields

An adaptive algorithm for simulation of stochastic reaction-diffusion processes

International Nuclear Information System (INIS)

Ferm, Lars; Hellander, Andreas; Loetstedt, Per

2010-01-01

We propose an adaptive hybrid method suitable for stochastic simulation of diffusion dominated reaction-diffusion processes. For such systems, simulation of the diffusion requires the predominant part of the computing time. In order to reduce the computational work, the diffusion in parts of the domain is treated macroscopically, in other parts with the tau-leap method and in the remaining parts with Gillespie's stochastic simulation algorithm (SSA) as implemented in the next subvolume method (NSM). The chemical reactions are handled by SSA everywhere in the computational domain. A trajectory of the process is advanced in time by an operator splitting technique and the timesteps are chosen adaptively. The spatial adaptation is based on estimates of the errors in the tau-leap method and the macroscopic diffusion. The accuracy and efficiency of the method are demonstrated in examples from molecular biology where the domain is discretized by unstructured meshes.

Enhanced cycling stability of Li-rich nanotube cathodes by 3D graphene hierarchical architectures for Li-ion batteries

International Nuclear Information System (INIS)

Ma, Dingtao; Li, Yongliang; Wu, Maosheng; Deng, Libo; Ren, Xiangzhong; Zhang, Peixin

2016-01-01

A hybrid composite of Li 1.2 Mn 0.54 Ni 0.13 Co 0.13 O 2 nanotubes (LMNCO NTs) wrapped with reduced graphene oxide (RGO) nanosheets (LMNCO@RGO) was prepared as cathode for lithium-ion batteries. The discharge capacity of the LMNCO@RGO composite is only reducing 3.5% after 100 cycles at 1 C. Such composite which simultaneously combines a high surface area of LMNCO NTs with shorten ionic diffusion pathway and high conductivity of 3D graphene hierarchical architectures as well as structural protection layers, displaying a good cycling stability.

TYPE Ia SUPERNOVA LIGHT CURVE INFERENCE: HIERARCHICAL MODELS IN THE OPTICAL AND NEAR-INFRARED

International Nuclear Information System (INIS)

Mandel, Kaisey S.; Narayan, Gautham; Kirshner, Robert P.

2011-01-01

We have constructed a comprehensive statistical model for Type Ia supernova (SN Ia) light curves spanning optical through near-infrared (NIR) data. A hierarchical framework coherently models multiple random and uncertain effects, including intrinsic supernova (SN) light curve covariances, dust extinction and reddening, and distances. An improved BAYESN Markov Chain Monte Carlo code computes probabilistic inferences for the hierarchical model by sampling the global probability density of parameters describing individual SNe and the population. We have applied this hierarchical model to optical and NIR data of 127 SNe Ia from PAIRITEL, CfA3, Carnegie Supernova Project, and the literature. We find an apparent population correlation between the host galaxy extinction A V and the ratio of total-to-selective dust absorption R V . For SNe with low dust extinction, A V ∼ V ∼ 2.5-2.9, while at high extinctions, A V ∼> 1, low values of R V < 2 are favored. The NIR luminosities are excellent standard candles and are less sensitive to dust extinction. They exhibit low correlation with optical peak luminosities, and thus provide independent information on distances. The combination of NIR and optical data constrains the dust extinction and improves the predictive precision of individual SN Ia distances by about 60%. Using cross-validation, we estimate an rms distance modulus prediction error of 0.11 mag for SNe with optical and NIR data versus 0.15 mag for SNe with optical data alone. Continued study of SNe Ia in the NIR is important for improving their utility as precise and accurate cosmological distance indicators.

Deliberate change without hierarchical influence?

DEFF Research Database (Denmark)

Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

2017-01-01

reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

Multiparty hierarchical quantum-information splitting

International Nuclear Information System (INIS)

Wang Xinwen; Zhang Dengyu; Tang Shiqing; Xie Lijun

2011-01-01

We propose a scheme for multiparty hierarchical quantum-information splitting (QIS) with a multipartite entangled state, where a boss distributes a secret quantum state to two grades of agents asymmetrically. The agents who belong to different grades have different authorities for recovering the boss's secret. Except for the boss's Bell-state measurement, no nonlocal operation is involved. The presented scheme is also shown to be secure against eavesdropping. Such a hierarchical QIS is expected to find useful applications in the field of modern multipartite quantum cryptography.

Biased trapping issue on weighted hierarchical networks

Indian Academy of Sciences (India)

archical networks which are based on the classic scale-free hierarchical networks. ... Weighted hierarchical networks; weight-dependent walks; mean first passage ..... The weighted networks can mimic some real-world natural and social systems to ... the Priority Academic Program Development of Jiangsu Higher Education ...

NQAR: Network Quality Aware Routing in Error-Prone Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jaewon Choi

2010-01-01

Full Text Available We propose a network quality aware routing (NQAR mechanism to provide an enabling method of the delay-sensitive data delivery over error-prone wireless sensor networks. Unlike the existing routing methods that select routes with the shortest arrival latency or the minimum hop count, the proposed scheme adaptively selects the route based on the network qualities including link errors and collisions with minimum additional complexity. It is designed to avoid the paths with potential noise and collision that may cause many non-deterministic backoffs and retransmissions. We propose a generic framework to select a minimum cost route that takes the packet loss rate and collision history into account. NQAR uses a data centric approach to estimate a single-hop delay based on processing time, propagation delay, packet loss rate, number of backoffs, and the retransmission timeout between two neighboring nodes. This enables a source node to choose the shortest expected end-to-end delay path to send a delay-sensitive data. The experiment results show that NQAR reduces the end-to-end transfer delay up to approximately 50% in comparison with the latency-based directed diffusion and the hop count-based directed diffusion under the error-prone network environments. Moreover, NQAR shows better performance than those routing methods in terms of jitter, reachability, and network lifetime.

Anti-hierarchical evolution of the active galactic nucleus space density in a hierarchical universe

International Nuclear Information System (INIS)

Enoki, Motohiro; Ishiyama, Tomoaki; Kobayashi, Masakazu A. R.; Nagashima, Masahiro

2014-01-01

Recent observations show that the space density of luminous active galactic nuclei (AGNs) peaks at higher redshifts than that of faint AGNs. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos, and the AGN lifetime scaling with the dynamical timescale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by star formation and gas cooling is suppressed in massive dark halos, the amount of cold gas accreted onto SMBHs decreases with cosmic time. Moreover, AGN lifetime increases with cosmic time. Thus, at low redshifts, major mergers do not always lead to luminous AGNs. Because the luminosity of AGNs is correlated with the mass of accreted gas onto SMBHs, the space density of luminous AGNs decreases more quickly than that of faint AGNs. We conclude that the anti-hierarchical evolution of the AGN space density is not contradictory to the hierarchical structure formation scenario.

Anti-hierarchical evolution of the active galactic nucleus space density in a hierarchical universe

Energy Technology Data Exchange (ETDEWEB)

Enoki, Motohiro [Faculty of Business Administration, Tokyo Keizai University, Kokubunji, Tokyo 185-8502 (Japan); Ishiyama, Tomoaki [Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8577 (Japan); Kobayashi, Masakazu A. R. [Research Center for Space and Cosmic Evolution, Ehime University, Matsuyama, Ehime 790-8577 (Japan); Nagashima, Masahiro, E-mail: enokimt@tku.ac.jp [Faculty of Education, Nagasaki University, Nagasaki, Nagasaki 852-8521 (Japan)

2014-10-10

Recent observations show that the space density of luminous active galactic nuclei (AGNs) peaks at higher redshifts than that of faint AGNs. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos, and the AGN lifetime scaling with the dynamical timescale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by star formation and gas cooling is suppressed in massive dark halos, the amount of cold gas accreted onto SMBHs decreases with cosmic time. Moreover, AGN lifetime increases with cosmic time. Thus, at low redshifts, major mergers do not always lead to luminous AGNs. Because the luminosity of AGNs is correlated with the mass of accreted gas onto SMBHs, the space density of luminous AGNs decreases more quickly than that of faint AGNs. We conclude that the anti-hierarchical evolution of the AGN space density is not contradictory to the hierarchical structure formation scenario.

Diffusion tensor MR microscopy of tissues with low diffusional anisotropy.

Science.gov (United States)

Bajd, Franci; Mattea, Carlos; Stapf, Siegfried; Sersa, Igor

2016-06-01

Diffusion tensor imaging exploits preferential diffusional motion of water molecules residing within tissue compartments for assessment of tissue structural anisotropy. However, instrumentation and post-processing errors play an important role in determination of diffusion tensor elements. In the study, several experimental factors affecting accuracy of diffusion tensor determination were analyzed. Effects of signal-to-noise ratio and configuration of the applied diffusion-sensitizing gradients on fractional anisotropy bias were analyzed by means of numerical simulations. In addition, diffusion tensor magnetic resonance microscopy experiments were performed on a tap water phantom and bovine articular cartilage-on-bone samples to verify the simulation results. In both, the simulations and the experiments, the multivariate linear regression of the diffusion-tensor analysis yielded overestimated fractional anisotropy with low SNRs and with low numbers of applied diffusion-sensitizing gradients. An increase of the apparent fractional anisotropy due to unfavorable experimental conditions can be overcome by applying a larger number of diffusion sensitizing gradients with small values of the condition number of the transformation matrix. This is in particular relevant in magnetic resonance microscopy, where imaging gradients are high and the signal-to-noise ratio is low.

Electrolyte diffusion in compacted montmorillonite engineered barriers

International Nuclear Information System (INIS)

Jahnke, F.M.; Radke, C.J.

1985-09-01

The bentonite-based engineered barrier or packing is a proposed component of several designs conceived to dispose of high-level nuclear waste in geologic repositories. Once radionuclides escape the waste package, they must first diffuse through the highly impermeable clay-rich barrier before they reach the host repository. To determine the effectiveness of the packing as a sorption barrier in the transient release period and as a mass-transfer barrier in the steady release period over the geologic time scales involved in nuclear waste disposal, a fundamental understanding of the diffusion of electrolytes in compacted clays is required. We present, and compare with laboratory data, a model quantifying the diffusion rates of cationic cesium and uncharged tritium in compacted montmorillonite clay. Neutral tritium characterizes the geometry (i.e., tortuosity) of the particulate gel. After accounting for cation exchange, we find that surface diffusion is the dominant mechanism of cation transport, with an approximate surface diffusion coefficient of 2 x 10 -6 cm 2 /s for cesium. This value increases slightly with increasing background ionic strength. The implications of this work for the packing as a migration barrier are twofold. During the transient release period, K/sub d/ values are of little importance in retarding ion migration. This is because sorption also gives rise to a surface diffusion path, and it is surface diffusion which controls the diffusion rate of highly sorbing cations in compacted montmorillonite. During the steady release period, the presence of surface diffusion leads to a flux through the packing which is greatly enhanced. In either case, if surface diffusion is neglected, the appropriate diffusion coefficient of ions in compacted packing will be in considerable error relative to current design recommendations. 11 refs., 4 figs., 1 tab

The assessment of pore connectivity in hierarchical zeolites using positron annihilation lifetime spectroscopy: instrumental and morphological aspects.

Science.gov (United States)

Zubiaga, Asier; Warringham, Robbie; Boltz, Marilyne; Cooke, David; Crivelli, Paolo; Gidley, David; Pérez-Ramírez, Javier; Mitchell, Sharon

2016-04-07

Recent studies demonstrated the power of positron annihilation lifetime spectroscopy (PALS) to characterise the connectivity and corresponding effectiveness of hierarchical pore networks in zeolites. This was based on the fractional escape of ortho-positronium (Ps), formed within the micropore framework, to vacuum. To further develop this technique, here we assess the impact of the positron implantation energy and of the zeolite crystal size and the particle morphology. Conventional measurements using fast positrons and beam measurements applying moderated positrons both readily distinguish purely microporous ZSM-5 zeolites comprised of single crystals or crystal aggregates. Unlike beam measurements, however, conventional measurements fail to discriminate model hierarchical zeolites with open or constricted mesopore architectures. Several steps are taken to rationalise these observations. The dominant contribution of Ps diffusion to the PALS response is confirmed by capping the external surface of the zeolite crystals with tetraethylorthosilicate, which greatly enhances the sensitivity to the micropore network. A one-dimensional model is constructed to predict the out-diffusion of Ps from a zeolite crystal, which is validated experimentally by comparing coffin-shaped single crystals of varying size. Calculation of the trends expected on the application of fast or moderated positrons indicates that the distinctions in the initial distribution of Ps at the crystal level cannot explain the limited sensitivity of the former to the mesopore architecture. Instead, we propose that the greater penetration of fast positrons within the sample increases the probability of Ps re-entry from intercrystalline voids into mesopores connected with the external surface of zeolite crystals, thereby reducing their fractional escape.

Analysis of the Numerical Diffusion in Anisotropic Mediums: Benchmarks for Magnetic Field Aligned Meshes in Space Propulsion Simulations

Directory of Open Access Journals (Sweden)

Daniel Pérez-Grande

2016-11-01

Full Text Available This manuscript explores numerical errors in highly anisotropic diffusion problems. First, the paper addresses the use of regular structured meshes in numerical solutions versus meshes aligned with the preferential directions of the problem. Numerical diffusion in structured meshes is quantified by solving the classical anisotropic diffusion problem; the analysis is exemplified with the application to a numerical model of conducting fluids under magnetic confinement, where rates of transport in directions parallel and perpendicular to a magnetic field are quite different. Numerical diffusion errors in this problem promote the use of magnetic field aligned meshes (MFAM. The generation of this type of meshes presents some challenges; several meshing strategies are implemented and analyzed in order to provide insight into achieving acceptable mesh regularity. Second, Gradient Reconstruction methods for magnetically aligned meshes are addressed and numerical errors are compared for the structured and magnetically aligned meshes. It is concluded that using the latter provides a more correct and straightforward approach to solving problems where anisotropicity is present, especially, if the anisotropicity level is high or difficult to quantify. The conclusions of the study may be extrapolated to the study of anisotropic flows different from conducting fluids.

Discovering hierarchical structure in normal relational data

DEFF Research Database (Denmark)

Schmidt, Mikkel Nørgaard; Herlau, Tue; Mørup, Morten

2014-01-01

-parametric generative model for hierarchical clustering of similarity based on multifurcating Gibbs fragmentation trees. This allows us to infer and display the posterior distribution of hierarchical structures that comply with the data. We demonstrate the utility of our method on synthetic data and data of functional...

A three-dimensional hierarchical collagen scaffold fabricated by a combined solid freeform fabrication (SFF) and electrospinning process to enhance mesenchymal stem cell (MSC) proliferation

International Nuclear Information System (INIS)

Ahn, SeungHyun; Kim, GeunHyung; Koh, Young Ho

2010-01-01

Collagen has the advantage of being very similar to macromolecular substances that can be recognized and metabolized in the biological environment. Although the natural material has superior property for this purpose, its use to fabricate reproducible and pore-structure-controlled 3D structures, which are designed to allow the entry of sufficient cells and the easy diffusion of nutrients, has been limited due to its low processability. Here, we propose a hybrid technology that combines a cryogenic plotting system with an electrospinning process. Using this technique, an easily pore-size-controllable hierarchical 3D scaffold consisting of micro-sized highly porous collagen strands and micro/nano-sized collagen fibers was fabricated. The pore structure of the collagen scaffold was controlled by the collagen micro/nanofibers, which were layered in the scaffold. The hierarchical scaffolds were characterized with respect to initial cell attachment and proliferation of bone marrow-derived mesenchymal stem cells within the scaffolds. The hierarchical scaffold exhibited incredibly enhanced initial cell attachment and cell compactness between pores of the plotted scaffold relative to the normally designed 3D collagen scaffold.

How well do different tracers constrain the firn diffusivity profile?

Directory of Open Access Journals (Sweden)

C. M. Trudinger

2013-02-01

Full Text Available Firn air transport models are used to interpret measurements of the composition of air in firn and bubbles trapped in ice in order to reconstruct past atmospheric composition. The diffusivity profile in the firn is usually calibrated by comparing modelled and measured concentrations for tracers with known atmospheric history. However, in most cases this is an under-determined inverse problem, often with multiple solutions giving an adequate fit to the data (this is known as equifinality. Here we describe a method to estimate the firn diffusivity profile that allows multiple solutions to be identified, in order to quantify the uncertainty in diffusivity due to equifinality. We then look at how well different combinations of tracers constrain the firn diffusivity profile. Tracers with rapid atmospheric variations like CH₃CCl₃, HFCs and ¹⁴CO₂ are most useful for constraining molecular diffusivity, while &delta:¹⁵N₂ is useful for constraining parameters related to convective mixing near the surface. When errors in the observations are small and Gaussian, three carefully selected tracers are able to constrain the molecular diffusivity profile well with minimal equifinality. However, with realistic data errors or additional processes to constrain, there is benefit to including as many tracers as possible to reduce the uncertainties. We calculate CO₂ age distributions and their spectral widths with uncertainties for five firn sites (NEEM, DE08-2, DSSW20K, South Pole 1995 and South Pole 2001 with quite different characteristics and tracers available for calibration. We recommend moving away from the use of a firn model with one calibrated parameter set to infer atmospheric histories, and instead suggest using multiple parameter sets, preferably with multiple representations of uncertain processes, to assist in quantification of the uncertainties.

Road Network Selection Based on Road Hierarchical Structure Control

Directory of Open Access Journals (Sweden)

HE Haiwei

2015-04-01

Full Text Available A new road network selection method based on hierarchical structure is studied. Firstly, road network is built as strokes which are then classified into hierarchical collections according to the criteria of betweenness centrality value (BC value. Secondly, the hierarchical structure of the strokes is enhanced using structural characteristic identification technique. Thirdly, the importance calculation model was established according to the relationships among the hierarchical structure of the strokes. Finally, the importance values of strokes are got supported with the model's hierarchical calculation, and with which the road network is selected. Tests are done to verify the advantage of this method by comparing it with other common stroke-oriented methods using three kinds of typical road network data. Comparision of the results show that this method had few need to semantic data, and could eliminate the negative influence of edge strokes caused by the criteria of BC value well. So, it is better to maintain the global hierarchical structure of road network, and suitable to meet with the selection of various kinds of road network at the same time.

Hierarchically Structured Electrospun Fibers

Directory of Open Access Journals (Sweden)

Nicole E. Zander

2013-01-01

Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

Hierarchical control of electron-transfer

DEFF Research Database (Denmark)

Westerhoff, Hans V.; Jensen, Peter Ruhdal; Egger, Louis

1997-01-01

In this chapter the role of electron transfer in determining the behaviour of the ATP synthesising enzyme in E. coli is analysed. It is concluded that the latter enzyme lacks control because of special properties of the electron transfer components. These properties range from absence of a strong...... back pressure by the protonmotive force on the rate of electron transfer to hierarchical regulation of the expression of the gens that encode the electron transfer proteins as a response to changes in the bioenergetic properties of the cell.The discussion uses Hierarchical Control Analysis...

Assimilating irregularly spaced sparsely observed turbulent signals with hierarchical Bayesian reduced stochastic filters

International Nuclear Information System (INIS)

Brown, Kristen A.; Harlim, John

2013-01-01

In this paper, we consider a practical filtering approach for assimilating irregularly spaced, sparsely observed turbulent signals through a hierarchical Bayesian reduced stochastic filtering framework. The proposed hierarchical Bayesian approach consists of two steps, blending a data-driven interpolation scheme and the Mean Stochastic Model (MSM) filter. We examine the potential of using the deterministic piecewise linear interpolation scheme and the ordinary kriging scheme in interpolating irregularly spaced raw data to regularly spaced processed data and the importance of dynamical constraint (through MSM) in filtering the processed data on a numerically stiff state estimation problem. In particular, we test this approach on a two-layer quasi-geostrophic model in a two-dimensional domain with a small radius of deformation to mimic ocean turbulence. Our numerical results suggest that the dynamical constraint becomes important when the observation noise variance is large. Second, we find that the filtered estimates with ordinary kriging are superior to those with linear interpolation when observation networks are not too sparse; such robust results are found from numerical simulations with many randomly simulated irregularly spaced observation networks, various observation time intervals, and observation error variances. Third, when the observation network is very sparse, we find that both the kriging and linear interpolations are comparable

WWER radial reflector modeling by diffusion codes

International Nuclear Information System (INIS)

Petkov, P. T.; Mittag, S.

2005-01-01

The two commonly used approaches to describe the WWER radial reflectors in diffusion codes, by albedo on the core-reflector boundary and by a ring of diffusive assembly size nodes, are discussed. The advantages and disadvantages of the first approach are presented first, then the Koebke's equivalence theory is outlined and its implementation for the WWER radial reflectors is discussed. Results for the WWER-1000 reactor are presented. Then the boundary conditions on the outer reflector boundary are discussed. The possibility to divide the library into fuel assembly and reflector parts and to generate each library by a separate code package is discussed. Finally, the homogenization errors for rodded assemblies are presented and discussed (Author)

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

Energy Technology Data Exchange (ETDEWEB)

Kumar, Ranjan [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: ranjan.k@ks3.ecs.kyoto-u.ac.jp; Izui, Kazuhiro [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: izui@prec.kyoto-u.ac.jp; Yoshimura, Masataka [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: yoshimura@prec.kyoto-u.ac.jp; Nishiwaki, Shinji [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: shinji@prec.kyoto-u.ac.jp

2009-04-15

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

International Nuclear Information System (INIS)

Kumar, Ranjan; Izui, Kazuhiro; Yoshimura, Masataka; Nishiwaki, Shinji

2009-01-01

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets

Tracking errors in tractography of the gastrocnemius muscle. A comparison between the transverse and sagittal planes

International Nuclear Information System (INIS)

Aoki, Takako; Tohdoh, Yukihiro; Tawara, Noriyuki; Okuwaki, Toru; Horiuchi, Akira; Itagaki, Takuma; Niitsu, Mamoru

2010-01-01

In scans taken in conventional direction, tracking errors may occur when using a streamline-based algorithm for the tractography of the gastrocnemius muscle. To solve errors in tracking, we applied tractography to the musculotendinous junction and performed fiber tracking on the gastrocnemius muscle of 10 healthy subjects with their written informed consent. We employed a spin-echo diffusion tensor imaging (SE-DTI) sequence with 6-direction diffusion gradient sensitization and acquired DTI images at 1.5 tesla using a body array coil with parallel imaging. We compared tractography obtained in the transverse and sagittal planes using anatomical reference and found that the gastrocnemius muscle and musculotendinous junction were significantly better visualized on sagittal scans and in 3 regions of interest. We utilized Mann-Whitney U-test to determine significant differences between rates of concordance (P 2 value of skeletal muscle is around 50 ms, and TE should be as short as possible. A streamline-based algorithm is based on the continuity of a vector. It is easy to take running of the muscle fiber in sagittal scan. Therefore, tracking error is hard to occur. In conclusion, sagittal scanning may be one way to eliminate tracking errors in the tractography of the gastrocnemius muscle. Tracking errors were smaller with sagittal scans than transverse scans, and sagittal scans allow better fiber tracking. (author)

Hierarchical Traces for Reduced NSM Memory Requirements

Science.gov (United States)

Dahl, Torbjørn S.

This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.

The Rational Relevance of the Diffuse Paradigms

Directory of Open Access Journals (Sweden)

Marin Dinu

2006-01-01

Full Text Available Processes like the globalization consistency and learning about society are screened by diffuse concepts such as those taking the last steps of the industrial civilization and hierarchically ordered world through hegemony. This is why the meaning of globalization is given by deviant trends, like globalism, and the knowledge society is taken for the tools promoted by itself, such as the internet. This does not imply only approximations of meaning but rather the vanity of change, preserving the status quo represented by the pre-global world or the adversity principle. Historicism of paradigm cannot be avoided. Evolvement towards something else, announced by globalization is implacable, and the new ordinating principle, the one of competition, opens the opportunity horizon to global world.

The Rational Relevance of the Diffuse Paradigms

Directory of Open Access Journals (Sweden)

Marin Dinu

2006-03-01

Full Text Available Processes like the globalization consistency and learning about society are screened by diffuse concepts such as those taking the last steps of the industrial civilization and hierarchically ordered world through hegemony. This is why the meaning of globalization is given by deviant trends, like globalism, and the knowledge society is taken for the tools promoted by itself, such as the internet. This does not imply only approximations of meaning but rather the vanity of change, preserving the status quo represented by the pre-global world or the adversity principle. Historicism of paradigm cannot be avoided. Evolvement towards something else, announced by globalization is implacable, and the new ordinating principle, the one of competition, opens the opportunity horizon to global world

Hierarchical subtask discovery with non-negative matrix factorization

CSIR Research Space (South Africa)

Earle, AC

2018-04-01

Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

Hierarchical subtask discovery with non-negative matrix factorization

CSIR Research Space (South Africa)

Earle, AC

2017-08-01

Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

Reflector modelization for neutronic diffusion and parameters identification

International Nuclear Information System (INIS)

Argaud, J.P.

1993-04-01

Physical parameters of neutronic diffusion equations can be adjusted to decrease calculations-measurements errors. The reflector being always difficult to modelize, we choose to elaborate a new reflector model and to use the parameters of this model as adjustment coefficients in the identification procedure. Using theoretical results, and also the physical behaviour of neutronic flux solutions, the reflector model consists then in its replacement by boundary conditions for the diffusion equations on the core only. This theoretical result of non-local operator relations leads then to some discrete approximations by taking into account the multiscaled behaviour, on the core-reflector interface, of neutronic diffusion solutions. The resulting model of this approach is then compared with previous reflector modelizations, and first results indicate that this new model gives the same representation of reflector for the core than previous. (author). 12 refs

Spectral nodal method for one-speed X,Y-geometry Eigenvalue diffusion problems

International Nuclear Information System (INIS)

Dominguez, Dany S.; Lorenzo, Daniel M.; Hernandez, Carlos G.; Barros, Ricardo C.; Silva, Fernando C. da

2001-01-01

Presented here is a new numerical nodal method for steady-state multidimensional neutron diffusion equation in rectangular geometry. Our method is based on a spectral analysis of the transverse-integrated nodal diffusion equations. These equations are obtained by integrating the diffusion equation in X and Y directions, and then considering flat approximations for the transverse leakage terms. These flat approximations are the only approximations that we consider in this method; as a result the numerical solutions are completely free from truncation errors in slab geometry. We show numerical results to illustrate the method's accuracy for coarse mesh calculations in a heterogeneous medium. (author)

Strong influence of periodic boundary conditions on lateral diffusion in lipid bilayer membranes

Energy Technology Data Exchange (ETDEWEB)

Camley, Brian A. [Center for Theoretical Biological Physics and Department of Physics, University of California, San Diego, California 92093 (United States); Department of Physics, University of California, Santa Barbara, California 93106 (United States); Lerner, Michael G. [Department of Physics and Astronomy, Earlham College, Richmond, Indiana 47374 (United States); Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892 (United States); Pastor, Richard W. [Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892 (United States); Brown, Frank L. H. [Department of Physics, University of California, Santa Barbara, California 93106 (United States); Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106 (United States)

2015-12-28

The Saffman-Delbrück hydrodynamic model for lipid-bilayer membranes is modified to account for the periodic boundary conditions commonly imposed in molecular simulations. Predicted lateral diffusion coefficients for membrane-embedded solid bodies are sensitive to box shape and converge slowly to the limit of infinite box size, raising serious doubts for the prospects of using detailed simulations to accurately predict membrane-protein diffusivities and related transport properties. Estimates for the relative error associated with periodic boundary artifacts are 50% and higher for fully atomistic models in currently feasible simulation boxes. MARTINI simulations of LacY membrane protein diffusion and LacY dimer diffusion in DPPC membranes and lipid diffusion in pure DPPC bilayers support the underlying hydrodynamic model.

Strong influence of periodic boundary conditions on lateral diffusion in lipid bilayer membranes

International Nuclear Information System (INIS)

Camley, Brian A.; Lerner, Michael G.; Pastor, Richard W.; Brown, Frank L. H.

2015-01-01

The Saffman-Delbrück hydrodynamic model for lipid-bilayer membranes is modified to account for the periodic boundary conditions commonly imposed in molecular simulations. Predicted lateral diffusion coefficients for membrane-embedded solid bodies are sensitive to box shape and converge slowly to the limit of infinite box size, raising serious doubts for the prospects of using detailed simulations to accurately predict membrane-protein diffusivities and related transport properties. Estimates for the relative error associated with periodic boundary artifacts are 50% and higher for fully atomistic models in currently feasible simulation boxes. MARTINI simulations of LacY membrane protein diffusion and LacY dimer diffusion in DPPC membranes and lipid diffusion in pure DPPC bilayers support the underlying hydrodynamic model

Postural control model interpretation of stabilogram diffusion analysis

Science.gov (United States)

Peterka, R. J.

2000-01-01

Collins and De Luca [Collins JJ. De Luca CJ (1993) Exp Brain Res 95: 308-318] introduced a new method known as stabilogram diffusion analysis that provides a quantitative statistical measure of the apparently random variations of center-of-pressure (COP) trajectories recorded during quiet upright stance in humans. This analysis generates a stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons. SDFs have a characteristic two-part form that suggests the presence of two different control regimes: a short-term open-loop control behavior and a longer-term closed-loop behavior. This paper demonstrates that a very simple closed-loop control model of upright stance can generate realistic SDFs. The model consists of an inverted pendulum body with torque applied at the ankle joint. This torque includes a random disturbance torque and a control torque. The control torque is a function of the deviation (error signal) between the desired upright body position and the actual body position, and is generated in proportion to the error signal, the derivative of the error signal, and the integral of the error signal [i.e. a proportional, integral and derivative (PID) neural controller]. The control torque is applied with a time delay representing conduction, processing, and muscle activation delays. Variations in the PID parameters and the time delay generate variations in SDFs that mimic real experimental SDFs. This model analysis allows one to interpret experimentally observed changes in SDFs in terms of variations in neural controller and time delay parameters rather than in terms of open-loop versus closed-loop behavior.

Particle Simulation of Fractional Diffusion Equations

KAUST Repository

Allouch, Samer

2017-07-12

This work explores different particle-based approaches to the simulation of one-dimensional fractional subdiffusion equations in unbounded domains. We rely on smooth particle approximations, and consider four methods for estimating the fractional diffusion term. The first method is based on direct differentiation of the particle representation, it follows the Riesz definition of the fractional derivative and results in a non-conservative scheme. The other three methods follow the particle strength exchange (PSE) methodology and are by construction conservative, in the sense that the total particle strength is time invariant. The first PSE algorithm is based on using direct differentiation to estimate the fractional diffusion flux, and exploiting the resulting estimates in an integral representation of the divergence operator. Meanwhile, the second one relies on the regularized Riesz representation of the fractional diffusion term to derive a suitable interaction formula acting directly on the particle representation of the diffusing field. A third PSE construction is considered that exploits the Green\\'s function of the fractional diffusion equation. The performance of all four approaches is assessed for the case of a one-dimensional diffusion equation with constant diffusivity. This enables us to take advantage of known analytical solutions, and consequently conduct a detailed analysis of the performance of the methods. This includes a quantitative study of the various sources of error, namely filtering, quadrature, domain truncation, and time integration, as well as a space and time self-convergence analysis. These analyses are conducted for different values of the order of the fractional derivatives, and computational experiences are used to gain insight that can be used for generalization of the present constructions.

Particle Simulation of Fractional Diffusion Equations

KAUST Repository

Allouch, Samer; Lucchesi, Marco; Maî tre, O. P. Le; Mustapha, K. A.; Knio, Omar

2017-01-01

This work explores different particle-based approaches to the simulation of one-dimensional fractional subdiffusion equations in unbounded domains. We rely on smooth particle approximations, and consider four methods for estimating the fractional diffusion term. The first method is based on direct differentiation of the particle representation, it follows the Riesz definition of the fractional derivative and results in a non-conservative scheme. The other three methods follow the particle strength exchange (PSE) methodology and are by construction conservative, in the sense that the total particle strength is time invariant. The first PSE algorithm is based on using direct differentiation to estimate the fractional diffusion flux, and exploiting the resulting estimates in an integral representation of the divergence operator. Meanwhile, the second one relies on the regularized Riesz representation of the fractional diffusion term to derive a suitable interaction formula acting directly on the particle representation of the diffusing field. A third PSE construction is considered that exploits the Green's function of the fractional diffusion equation. The performance of all four approaches is assessed for the case of a one-dimensional diffusion equation with constant diffusivity. This enables us to take advantage of known analytical solutions, and consequently conduct a detailed analysis of the performance of the methods. This includes a quantitative study of the various sources of error, namely filtering, quadrature, domain truncation, and time integration, as well as a space and time self-convergence analysis. These analyses are conducted for different values of the order of the fractional derivatives, and computational experiences are used to gain insight that can be used for generalization of the present constructions.

Action errors, error management, and learning in organizations.

Science.gov (United States)

Frese, Michael; Keith, Nina

2015-01-03

Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.

Filtering and smoothing of stae vector for diffuse state space models

NARCIS (Netherlands)

Koopman, S.J.; Durbin, J.

2003-01-01

This paper presents exact recursions for calculating the mean and mean square error matrix of the state vector given the observations for the multi-variate linear Gaussian state-space model in the case where the initial state vector is (partially) diffuse.

Modeling coherent errors in quantum error correction

Science.gov (United States)

Greenbaum, Daniel; Dutton, Zachary

2018-01-01

Analysis of quantum error correcting codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical data qubits result in both physical and logical error rates that differ significantly from those predicted by a Pauli model. Here we examine the accuracy of the Pauli approximation for noise containing coherent errors (characterized by a rotation angle ɛ) under the repetition code. We derive an analytic expression for the logical error channel as a function of arbitrary code distance d and concatenation level n, in the small error limit. We find that coherent physical errors result in logical errors that are partially coherent and therefore non-Pauli. However, the coherent part of the logical error is negligible at fewer than {ε }-({dn-1)} error correction cycles when the decoder is optimized for independent Pauli errors, thus providing a regime of validity for the Pauli approximation. Above this number of correction cycles, the persistent coherent logical error will cause logical failure more quickly than the Pauli model would predict, and this may need to be combated with coherent suppression methods at the physical level or larger codes.

Reaction-diffusion controlled growth of complex structures

Science.gov (United States)

Noorduin, Willem; Mahadevan, L.; Aizenberg, Joanna

2013-03-01

Understanding how the emergence of complex forms and shapes in biominerals came about is both of fundamental and practical interest. Although biomineralization processes and organization strategies to give higher order architectures have been studied extensively, synthetic approaches to mimic these self-assembled structures are highly complex and have been difficult to emulate, let alone replicate. The emergence of solution patterns has been found in reaction-diffusion systems such as Turing patterns and the BZ reaction. Intrigued by this spontaneous formation of complexity we explored if similar processes can lead to patterns in the solid state. We here identify a reaction-diffusion system in which the shape of the solidified products is a direct readout of the environmental conditions. Based on insights in the underlying mechanism, we developed a toolbox of engineering strategies to deterministically sculpt patterns and shapes, and combine different morphologies to create a landscape of hierarchical multi scale-complex tectonic architectures with unprecedented levels of complexity. These findings may hold profound implications for understanding, mimicking and ultimately expanding upon nature's morphogenesis strategies, allowing the synthesis of advanced highly complex microscale materials and devices. WLN acknowledges the Netherlands Organization for Scientific Research for financial support

Three Ways to Link Merge with Hierarchical Concept-Combination

Directory of Open Access Journals (Sweden)

Chris Thornton

2016-11-01

Full Text Available In the Minimalist Program, language competence is seen to stem from a fundamental ability to construct hierarchical structure, an operation dubbed ‘Merge’. This raises the problem of how to view hierarchical concept-combination. This is a conceptual operation which also builds hierarchical structure. We can conceive of a garden that consists of a lawn and a flower-bed, for example, or a salad consisting of lettuce, fennel and rocket, or a crew consisting of a pilot and engineer. In such cases, concepts are put together in a way that makes one the accommodating element with respect to the others taken in combination. The accommodating element becomes the root of a hierarchical unit. Since this unit is itself a concept, the operation is inherently recursive. Does this mean the mind has two independent systems of hierarchical construction? Or is some form of integration more likely? Following a detailed examination of the operations involved, this paper shows there are three main ways in which Merge might be linked to hierarchical concept-combination. Also examined are the architectural implications that arise in each case.

Application of optimal interation strategies to diffusion theory calculations

International Nuclear Information System (INIS)

Jones, R.B.

1978-01-01

The geometric interpretation of optimal (minimum computational time) iteration strategies is applied to one- and two-group, two-dimensional diffusion-theory calculations. The method is a ''spectral/time balance'' technique which weighs the convergence enhancement of the inner iteration procedure with that of the outer iteration loop and the time required to reconstruct the source. The diffusion-theory option of the discrete-ordinates transport code DOT3.5 was altered to incorporate the theoretical inner/outer decision logic. For the two-dimensional configuration considered, the optimal strategies reduced the total number of iterations performed for a given error criterion

Errors in causal inference: an organizational schema for systematic error and random error.

Science.gov (United States)

Suzuki, Etsuji; Tsuda, Toshihide; Mitsuhashi, Toshiharu; Mansournia, Mohammad Ali; Yamamoto, Eiji

2016-11-01

To provide an organizational schema for systematic error and random error in estimating causal measures, aimed at clarifying the concept of errors from the perspective of causal inference. We propose to divide systematic error into structural error and analytic error. With regard to random error, our schema shows its four major sources: nondeterministic counterfactuals, sampling variability, a mechanism that generates exposure events and measurement variability. Structural error is defined from the perspective of counterfactual reasoning and divided into nonexchangeability bias (which comprises confounding bias and selection bias) and measurement bias. Directed acyclic graphs are useful to illustrate this kind of error. Nonexchangeability bias implies a lack of "exchangeability" between the selected exposed and unexposed groups. A lack of exchangeability is not a primary concern of measurement bias, justifying its separation from confounding bias and selection bias. Many forms of analytic errors result from the small-sample properties of the estimator used and vanish asymptotically. Analytic error also results from wrong (misspecified) statistical models and inappropriate statistical methods. Our organizational schema is helpful for understanding the relationship between systematic error and random error from a previously less investigated aspect, enabling us to better understand the relationship between accuracy, validity, and precision. Copyright © 2016 Elsevier Inc. All rights reserved.

A Hierarchical Bayesian Setting for an Inverse Problem in Linear Parabolic PDEs with Noisy Boundary Conditions

KAUST Repository

Ruggeri, Fabrizio

2016-05-12

In this work we develop a Bayesian setting to infer unknown parameters in initial-boundary value problems related to linear parabolic partial differential equations. We realistically assume that the boundary data are noisy, for a given prescribed initial condition. We show how to derive the joint likelihood function for the forward problem, given some measurements of the solution field subject to Gaussian noise. Given Gaussian priors for the time-dependent Dirichlet boundary values, we analytically marginalize the joint likelihood using the linearity of the equation. Our hierarchical Bayesian approach is fully implemented in an example that involves the heat equation. In this example, the thermal diffusivity is the unknown parameter. We assume that the thermal diffusivity parameter can be modeled a priori through a lognormal random variable or by means of a space-dependent stationary lognormal random field. Synthetic data are used to test the inference. We exploit the behavior of the non-normalized log posterior distribution of the thermal diffusivity. Then, we use the Laplace method to obtain an approximated Gaussian posterior and therefore avoid costly Markov Chain Monte Carlo computations. Expected information gains and predictive posterior densities for observable quantities are numerically estimated using Laplace approximation for different experimental setups.

Hierarchical surfaces for enhanced self-cleaning applications

Science.gov (United States)

Fernández, Ariadna; Francone, Achille; Thamdrup, Lasse H.; Johansson, Alicia; Bilenberg, Brian; Nielsen, Theodor; Guttmann, Markus; Sotomayor Torres, Clivia M.; Kehagias, Nikolaos

2017-04-01

In this study we present a flexible and adaptable fabrication method to create complex hierarchical structures over inherently hydrophobic resist materials. We have tested these surfaces for their superhydrophobic behaviour and successfully verified their self-cleaning properties. The followed approach allow us to design and produce superhydrophobic surfaces in a reproducible manner. We have analysed different combination of hierarchical micro-nanostructures for their application to self-cleaning surfaces. A static contact angle value of 170° with a hysteresis of 4° was achieved without the need of any additional chemical treatment on the fabricated hierarchical structures. Dynamic effects were analysed on these surfaces, obtaining a remarkable self-cleaning effect as well as a good robustness over impacting droplets.

Diffusion-Weighted MRI for the Assessment of Liver Fibrosis: Principles and Applications

Directory of Open Access Journals (Sweden)

Stefano Palmucci

2015-01-01

Full Text Available The importance of an early identification of hepatic fibrosis has been emphasized, in order to start therapy and obtain fibrosis regression. Biopsy is the gold-standard method for the assessment of liver fibrosis in chronic liver diseases, but it is limited by complications, interobserver variability, and sampling errors. Several noninvasive methods have been recently introduced into clinical routine, in order to detect liver fibrosis early. One of the most diffuse approaches is represented by diffusion-weighted liver MRI. In this review, the main technical principles are briefly reported in order to explain the rationale for clinical applications. In addition, roles of apparent diffusion coefficient, intravoxel incoherent motion, and relative apparent diffusion coefficient are also reported, showing their advantages and limits.

Diffusive Wave Approximation to the Shallow Water Equations: Computational Approach

KAUST Repository

Collier, Nathan

2011-05-14

We discuss the use of time adaptivity applied to the one dimensional diffusive wave approximation to the shallow water equations. A simple and computationally economical error estimator is discussed which enables time-step size adaptivity. This robust adaptive time discretization corrects the initial time step size to achieve a user specified bound on the discretization error and allows time step size variations of several orders of magnitude. In particular, in the one dimensional results presented in this work feature a change of four orders of magnitudes for the time step over the entire simulation.

Hierarchical Micro-Nano Coatings by Painting

Science.gov (United States)

Kirveslahti, Anna; Korhonen, Tuulia; Suvanto, Mika; Pakkanen, Tapani A.

2016-03-01

In this paper, the wettability properties of coatings with hierarchical surface structures and low surface energy were studied. Hierarchically structured coatings were produced by using hydrophobic fumed silica nanoparticles and polytetrafluoroethylene (PTFE) microparticles as additives in polyester (PES) and polyvinyldifluoride (PVDF). These particles created hierarchical micro-nano structures on the paint surfaces and lowered or supported the already low surface energy of the paint. Two standard application techniques for paint application were employed and the presented coatings are suitable for mass production and use in large surface areas. By regulating the particle concentrations, it was possible to modify wettability properties gradually. Highly hydrophobic surfaces were achieved with the highest contact angle of 165∘. Dynamic contact angle measurements were carried out for a set of selected samples and low hysteresis was obtained. Produced coatings possessed long lasting durability in the air and in underwater conditions.

Hierarchical virtual screening approaches in small molecule drug discovery.

Science.gov (United States)

Kumar, Ashutosh; Zhang, Kam Y J

2015-01-01

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

Influence of diffuse reflectance measurement accuracy on the scattering coefficient in determination of optical properties with integrating sphere optics (a secondary publication).

Science.gov (United States)

Horibe, Takuro; Ishii, Katsunori; Fukutomi, Daichi; Awazu, Kunio

2015-12-30

An estimation error of the scattering coefficient of hemoglobin in the high absorption wavelength range has been observed in optical property calculations of blood-rich tissues. In this study, the relationship between the accuracy of diffuse reflectance measurement in the integrating sphere and calculated scattering coefficient was evaluated with a system to calculate optical properties combined with an integrating sphere setup and the inverse Monte Carlo simulation. Diffuse reflectance was measured with the integrating sphere using a small incident port diameter and optical properties were calculated. As a result, the estimation error of the scattering coefficient was improved by accurate measurement of diffuse reflectance. In the high absorption wavelength range, the accuracy of diffuse reflectance measurement has an effect on the calculated scattering coefficient.

The cosmic history of the baryon budget in a hierarchical universe

International Nuclear Information System (INIS)

Rasera, Yann

2005-01-01

In the framework of the hierarchical model of galaxy formation, small primordial density fluctuations observed on the cosmological microwave background are amplified by gravitational instability leading to the formation of larger and larger halos. The gas collapses and cools in these dark matter potential wells and forms cold centrifugally supported gas discs. These discs are converted into stellar discs that is to say galaxies. The problem in this scenario is the so-called 'overcooling problem': the resulting amount of stars is greater than the observed one by a factor of four. I have therefore studied the evolution of baryons (hydrogen and helium gas) in the Universe using high resolution hydrodynamic simulations. Based on these results, I have developed a simple analytical model for computing the baryons mass fraction in each of the following phases: stars, cold gas in galactic discs, hot gas in clusters and diffuse gas in the intergalactic medium. The comparison of model results to observations shows us that cosmology controls the cosmic history of star formation. The important cosmological role of galactic winds is also shed to light. They eject the cold gas from discs to hot halos, overcoming the overcooling problem. Finally, I have studied the implication of baryon physics onto the diffuse gamma-ray background from light dark matter particles. (author) [fr

Regularized multivariate regression models with skew-t error distributions

KAUST Repository

Chen, Lianfu

2014-06-01

We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both the regression coefficient and inverse scale matrices simultaneously. The sparsity is introduced through penalizing the negative log-likelihood by adding L1-penalties on the entries of the two matrices. Taking advantage of the hierarchical representation of skew-t distributions, and using the expectation conditional maximization (ECM) algorithm, we reduce the problem to penalized normal likelihood and develop a procedure to minimize the ensuing objective function. Using a simulation study the performance of the method is assessed, and the methodology is illustrated using a real data set with a 24-dimensional response vector. © 2014 Elsevier B.V.

Hierarchical Mesoporous Lithium-Rich Li[Li0.2Ni0.2Mn0.6]O2 Cathode Material Synthesized via Ice Templating for Lithium-Ion Battery.

Science.gov (United States)

Li, Yu; Wu, Chuan; Bai, Ying; Liu, Lu; Wang, Hui; Wu, Feng; Zhang, Na; Zou, Yufeng

2016-07-27

Tuning hierarchical micro/nanostructure of electrode materials is a sought-after means to reinforce their electrochemical performance in the energy storage field. Herein, we introduce a type of hierarchical mesoporous Li[Li0.2Ni0.2Mn0.6]O2 microsphere composed of nanoparticles synthesized via an ice templating combined coprecipitation strategy. It is a low-cost, eco-friendly, and easily operated method using ice as a template to control material with homogeneous morphology and rich porous channels. The as-prepared material exhibits remarkably enhanced electrochemical performances with higher capacity, more excellent cycling stability and more superior rate property, compared with the sample prepared by conventional coprecipitation method. It has satisfactory initial discharge capacities of 280.1 mAh g(-1) at 0.1 C, 207.1 mAh g(-1) at 2 C, and 152.4 mAh g(-1) at 5 C, as well as good cycle performance. The enhanced electrochemical performance can be ascribed to the stable hierarchical microsized structure and the improved lithium-ion diffusion kinetics from the highly porous structure.

Introduction into Hierarchical Matrices

KAUST Repository

Litvinenko, Alexander

2013-01-01

Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

Introduction into Hierarchical Matrices

KAUST Repository

Litvinenko, Alexander

2013-12-05

Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

Robust, Efficient Depth Reconstruction With Hierarchical Confidence-Based Matching.

Science.gov (United States)

Sun, Li; Chen, Ke; Song, Mingli; Tao, Dacheng; Chen, Gang; Chen, Chun

2017-07-01

In recent years, taking photos and capturing videos with mobile devices have become increasingly popular. Emerging applications based on the depth reconstruction technique have been developed, such as Google lens blur. However, depth reconstruction is difficult due to occlusions, non-diffuse surfaces, repetitive patterns, and textureless surfaces, and it has become more difficult due to the unstable image quality and uncontrolled scene condition in the mobile setting. In this paper, we present a novel hierarchical framework with multi-view confidence-based matching for robust, efficient depth reconstruction in uncontrolled scenes. Particularly, the proposed framework combines local cost aggregation with global cost optimization in a complementary manner that increases efficiency and accuracy. A depth map is efficiently obtained in a coarse-to-fine manner by using an image pyramid. Moreover, confidence maps are computed to robustly fuse multi-view matching cues, and to constrain the stereo matching on a finer scale. The proposed framework has been evaluated with challenging indoor and outdoor scenes, and has achieved robust and efficient depth reconstruction.

Hierarchical surfaces for enhanced self-cleaning applications

International Nuclear Information System (INIS)

Fernández, Ariadna; Francone, Achille; Sotomayor Torres, Clivia M; Kehagias, Nikolaos; Thamdrup, Lasse H; Johansson, Alicia; Bilenberg, Brian; Nielsen, Theodor; Guttmann, Markus

2017-01-01

In this study we present a flexible and adaptable fabrication method to create complex hierarchical structures over inherently hydrophobic resist materials. We have tested these surfaces for their superhydrophobic behaviour and successfully verified their self-cleaning properties. The followed approach allow us to design and produce superhydrophobic surfaces in a reproducible manner. We have analysed different combination of hierarchical micro-nanostructures for their application to self-cleaning surfaces. A static contact angle value of 170° with a hysteresis of 4° was achieved without the need of any additional chemical treatment on the fabricated hierarchical structures. Dynamic effects were analysed on these surfaces, obtaining a remarkable self-cleaning effect as well as a good robustness over impacting droplets. (paper)

Hierarchical processing in the prefrontal cortex in a variety of cognitive domains

Directory of Open Access Journals (Sweden)

Hyeon-Ae eJeon

2014-11-01

Full Text Available This review scrutinizes several findings on human hierarchical processing within the prefrontal cortex (PFC in diverse cognitive domains. Converging evidence from previous studies has shown that the PFC, specifically Brodmann area (BA 44, may function as the essential region for hierarchical processing across the domains. In language fMRI studies, BA 44 was significantly activated for the hierarchical processing of center-embedded sentences and this pattern of activations was also observed in artificial grammar. The same pattern was observed in the visuo-spatial domain where BA44 was actively involved in the processing of hierarchy for the visual symbol. Musical syntax, which is the rule-based arrangement of musical sets, has also been construed as hierarchical processing as in the language domain such that the activation in BA44 was observed in a chord sequence paradigm. P600 ERP was also engendered during the processing of musical hierarchy. Along with a longstanding idea that a human’s number faculty is developed as a by-product of language faculty, BA44 was closely involved in hierarchical processing in mental arithmetic. This review extended its discussion of hierarchical processing to hierarchical behavior, that is, human action which has been referred to as being hierarchically composed. Several lesion and TMS studies supported the involvement of BA44 for hierarchical processing in the action domain. Lastly, the hierarchical organization of cognitive controls was discussed within the PFC, forming a cascade of top-down hierarchical processes operating along a posterior-to-anterior axis of the lateral PFC including BA44 within the network. It is proposed that PFC is actively involved in different forms of hierarchical processing and specifically BA44 may play an integral role in the process. Taking levels of proficiency and subcortical areas into consideration may provide further insight into the functional role of BA44 for hierarchical

Model and Reduction of Inactive Times in a Maintenance Workshop Following a Diagnostic Error

Directory of Open Access Journals (Sweden)

T. Beda

2011-04-01

Full Text Available The majority of maintenance workshops in manufacturing factories are hierarchical. This arrangement permits quick response in advent of a breakdown. Reaction of the maintenance workshop is done by evaluating the characteristics of the breakdown. In effect, a diagnostic error at a given level of the process of decision making delays the restoration of normal operating state. The consequences are not just financial loses, but loss in customers’ satisfaction as well. The goal of this paper is to model the inactive time of a maintenance workshop in case that an unpredicted catalectic breakdown has occurred and a diagnostic error has also occurred at a certain level of decision-making, during the treatment process of the breakdown. We show that the expression for the inactive times obtained, is depended only on the characteristics of the workshop. Next, we propose a method to reduce the inactive times.

Hierarchical Ag mesostructures for single particle SERS substrate

Energy Technology Data Exchange (ETDEWEB)

Xu, Minwei, E-mail: xuminwei@xjtu.edu.cn; Zhang, Yin

2017-01-30

Highlights: • Hierarchical Ag mesostructures with the size of 250, 360 and 500 nm are synthesized via a seed-mediated approach. • The Ag mesostructures present the tailorable size and highly roughened surfaces. • The average enhancement factors for individual Ag mesostructures were estimated to be as high as 10{sup 6}. - Abstract: Hierarchical Ag mesostructures with highly rough surface morphology have been synthesized at room temperature through a simple seed-mediated approach. Electron microscopy characterizations indicate that the obtained Ag mesostructures exhibit a textured surface morphology with the flower-like architecture. Moreover, the particle size can be tailored easily in the range of 250–500 nm. For the growth process of the hierarchical Ag mesostructures, it is believed that the self-assembly mechanism is more reasonable rather than the epitaxial overgrowth of Ag seed. The oriented attachment of nanoparticles is revealed during the formation of Ag mesostructures. Single particle surface enhanced Raman spectra (sp-SERS) of crystal violet adsorbed on the hierarchical Ag mesostructures were measured. Results reveal that the hierarchical Ag mesostructures can be highly sensitive sp-SERS substrates with good reproducibility. The average enhancement factors for individual Ag mesostructures are estimated to be about 10{sup 6}.

Which, When, and How: Hierarchical Clustering with Human–Machine Cooperation

Directory of Open Access Journals (Sweden)

Huanyang Zheng

2016-12-01

Full Text Available Human–Machine Cooperations (HMCs can balance the advantages and disadvantages of human computation (accurate but costly and machine computation (cheap but inaccurate. This paper studies HMCs in agglomerative hierarchical clusterings, where the machine can ask the human some questions. The human will return the answers to the machine, and the machine will use these answers to correct errors in its current clustering results. We are interested in the machine’s strategy on handling the question operations, in terms of three problems: (1 Which question should the machine ask? (2 When should the machine ask the question (early or late? (3 How does the machine adjust the clustering result, if the machine’s mistake is found by the human? Based on the insights of these problems, an efficient algorithm is proposed with five implementation variations. Experiments on image clusterings show that the proposed algorithm can improve the clustering accuracy with few question operations.

Hierarchically ordered mesoporous carbon/graphene composites as supercapacitor electrode materials.

Science.gov (United States)

Song, Yanjie; Li, Zhu; Guo, Kunkun; Shao, Ting

2016-08-25

Hierarchically ordered mesoporous carbon/graphene (OMC/G) composites have been fabricated by means of a solvent-evaporation-induced self-assembly (EISA) method. The structures of these composites are characterized by X-ray diffraction, transmission electron microscopy, Raman spectroscopy and nitrogen adsorption-desorption at 77 K. These results indicate that OMC/G composites possess the hierarchically ordered hexagonal p6mm mesostructure with the lattice unit parameter and pore diameter close to 10 nm and 3 nm, respectively. The specific surface area of OMC/G composites after KOH activation is high up to 2109.2 m(2) g(-1), which is significantly greater than OMC after activation (1474.6 m(2) g(-1)). Subsequently, the resulting OMC/G composites as supercapacitor electrode materials exhibit an outstanding capacitance as high as 329.5 F g(-1) in 6 M KOH electrolyte at a current density of 0.5 A g(-1), which is much higher than both OMC (234.2 F g(-1)) and a sample made by mechanical mixing of OMC with graphene (217.7 F g(-1)). In addition, the obtained OMC/G composites display good cyclic stability, and the final capacitance retention is approximately 96% after 5000 cycles. These ordered mesopores in the OMC/G composites are beneficial to the accessibility and rapid diffusion of the electrolyte, while graphene in OMC/G composites can also facilitate the transport of electrons during the processes of charging and discharging owing to its high conductivity, thereby leading to an excellent energy storage performance. The method demonstrated in this work would open up a new route to design and develop graphene-based architectures for supercapacitor applications.

Whisper: Tracing the Spatiotemporal Process of Information Diffusion in Real Time.

Science.gov (United States)

Cao, Nan; Lin, Yu-Ru; Sun, Xiaohua; Lazer, D; Liu, Shixia; Qu, Huamin

2012-12-01

When and where is an idea dispersed? Social media, like Twitter, has been increasingly used for exchanging information, opinions and emotions about events that are happening across the world. Here we propose a novel visualization design, "Whisper", for tracing the process of information diffusion in social media in real time. Our design highlights three major characteristics of diffusion processes in social media: the temporal trend, social-spatial extent, and community response of a topic of interest. Such social, spatiotemporal processes are conveyed based on a sunflower metaphor whose seeds are often dispersed far away. In Whisper, we summarize the collective responses of communities on a given topic based on how tweets were retweeted by groups of users, through representing the sentiments extracted from the tweets, and tracing the pathways of retweets on a spatial hierarchical layout. We use an efficient flux line-drawing algorithm to trace multiple pathways so the temporal and spatial patterns can be identified even for a bursty event. A focused diffusion series highlights key roles such as opinion leaders in the diffusion process. We demonstrate how our design facilitates the understanding of when and where a piece of information is dispersed and what are the social responses of the crowd, for large-scale events including political campaigns and natural disasters. Initial feedback from domain experts suggests promising use for today's information consumption and dispersion in the wild.

Error-related brain activity predicts cocaine use after treatment at 3-month follow-up.

Science.gov (United States)

Marhe, Reshmi; van de Wetering, Ben J M; Franken, Ingmar H A

2013-04-15

Relapse after treatment is one of the most important problems in drug dependency. Several studies suggest that lack of cognitive control is one of the causes of relapse. In this study, a relative new electrophysiologic index of cognitive control, the error-related negativity, is investigated to examine its suitability as a predictor of relapse. The error-related negativity was measured in 57 cocaine-dependent patients during their first week in detoxification treatment. Data from 49 participants were used to predict cocaine use at 3-month follow-up. Cocaine use at follow-up was measured by means of self-reported days of cocaine use in the last month verified by urine screening. A multiple hierarchical regression model was used to examine the predictive value of the error-related negativity while controlling for addiction severity and self-reported craving in the week before treatment. The error-related negativity was the only significant predictor in the model and added 7.4% of explained variance to the control variables, resulting in a total of 33.4% explained variance in the prediction of days of cocaine use at follow-up. A reduced error-related negativity measured during the first week of treatment was associated with more days of cocaine use at 3-month follow-up. Moreover, the error-related negativity was a stronger predictor of recent cocaine use than addiction severity and craving. These results suggest that underactive error-related brain activity might help to identify patients who are at risk of relapse as early as in the first week of detoxification treatment. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Guide to precision calculations in Dyson close-quote s hierarchical scalar field theory

International Nuclear Information System (INIS)

Godina, J.J.; Meurice, Y.; Oktay, M.B.; Niermann, S.

1998-01-01

The goal of this article is to provide a practical method to calculate, in a scalar theory, accurate numerical values of the renormalized quantities which could be used to test any kind of approximate calculation. We use finite truncations of the Fourier transform of the recursion formula for Dyson close-quote s hierarchical model in the symmetric phase to perform high-precision calculations of the unsubtracted Green close-quote s functions at zero momentum in dimension 3, 4, and 5. We use the well-known correspondence between statistical mechanics and field theory in which the large cutoff limit is obtained by letting β reach a critical value β c (with up to 16 significant digits in our actual calculations). We show that the round-off errors on the magnetic susceptibility grow like (β c -β) -1 near criticality. We show that the systematic errors (finite truncations and volume) can be controlled with an exponential precision and reduced to a level lower than the numerical errors. We justify the use of the truncation for calculations of the high-temperature expansion. We calculate the dimensionless renormalized coupling constant corresponding to the 4-point function and show that when β→β c , this quantity tends to a fixed value which can be determined accurately when D=3 (hyperscaling holds), and goes to zero like [Ln(β c -β)] -1 when D=4. copyright 1998 The American Physical Society

Measurement of heat and momentum eddy diffusivities in recirculating LMFBR outlet plenum flows

International Nuclear Information System (INIS)

Manno, V.P.; Golay, M.W.

1978-06-01

An optical technique has been developed for the measurement of the eddy diffusivity of heat in a transparent flowing medium. The method uses a combination of two established measurement tools: a Mach-Zehnder interferometer for the monitoring of turbulently fluctuating temperature and a Laser Doppler Anemometer (LDA) for the measurement of turbulent velocity fluctuations. The technique is applied to the investigation of flow fields characteristic of the LMFBR outlet plenum. The study is accomplished using air as the working fluid in a small scale Plexiglas test section. Lows are introduced into both the 1 / 15 scale FFTF outlet plenum and the 3 / 80 scale CRBR geometry plenum at inlet Reynolds numbers of 22,000. Measurements of the eddy diffusivity of heat and the eddy diffusivity of momentum are performed at a total of 11 measurement stations. Significant differences of the turbulence parameters are found between the two geometries, and the higher chimney structure of the CRBR case is found to be the major cause of the distinction. Spectral intensity studies of the fluctuating electronic analog signals of velocity and temperature are also performed. Error analysis of the overall technique indicates an experimental error of 10% in the determination of the eddy diffusivity of heat and 6% in the evaluation of turbulent momentum viscosity. In general it is seen that the turbulence in the cases observed is not isotropic, and use of isotropic turbulent heat and momentum diffusivities in transport modelling would not be a valid procedure

Analysis hierarchical model for discrete event systems

Science.gov (United States)

Ciortea, E. M.

2015-11-01

The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

Hierarchical effects on target detection and conflict monitoring

Science.gov (United States)

Cao, Bihua; Gao, Feng; Ren, Maofang; Li, Fuhong

2016-01-01

Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220–350 ms) at the frontal sites, and a smaller P3 component (350–500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction. PMID:27561989

Performance Analysis of a Two-Hop MIMO Mobile-to-Mobile via Stratospheric-Relay Link Employing Hierarchical Modulation

Directory of Open Access Journals (Sweden)

Nikolaos Nomikos

2013-01-01

Full Text Available Next generation wireless communication networks intend to take advantage of the integration of terrestrial and aerospace infrastructures. Besides, multiple-input multiple-output (MIMO architecture is the key technology, which has brought the wireless gigabit vision closer to reality. In this direction, high-altitude platforms (HAPs could act as relay stations in the stratosphere transferring information from an uplink to a downlink MIMO channel. This paper investigates the performance of a novel transmission scheme for the delivery of mobile-to-mobile (M-to-M services via a stratospheric relay. It is assumed that the source, relay, and destination nodes are equipped with multiple antennas and that amplify-and-forward (AF relaying is adopted. The performance is analyzed through rigorous simulations in terms of the bit-error rate (BER by using a recently proposed 3D geometry-based reference model in spatially correlated flat-fading MIMO channels, employing a hierarchical broadcast technique and minimum mean square error (MMSE receivers.

Programming with Hierarchical Maps

DEFF Research Database (Denmark)

Ørbæk, Peter

This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

Error begat error: design error analysis and prevention in social infrastructure projects.

Science.gov (United States)

Love, Peter E D; Lopez, Robert; Edwards, David J; Goh, Yang M

2012-09-01

Design errors contribute significantly to cost and schedule growth in social infrastructure projects and to engineering failures, which can result in accidents and loss of life. Despite considerable research that has addressed their error causation in construction projects they still remain prevalent. This paper identifies the underlying conditions that contribute to design errors in social infrastructure projects (e.g. hospitals, education, law and order type buildings). A systemic model of error causation is propagated and subsequently used to develop a learning framework for design error prevention. The research suggests that a multitude of strategies should be adopted in congruence to prevent design errors from occurring and so ensure that safety and project performance are ameliorated. Copyright © 2011. Published by Elsevier Ltd.

Hierarchical Bayesian Spatio Temporal Model Comparison on the Earth Trapped Particle Forecast

International Nuclear Information System (INIS)

Suparta, Wayan; Gusrizal

2014-01-01

We compared two hierarchical Bayesian spatio temporal (HBST) results, Gaussian process (GP) and autoregressive (AR) models, on the Earth trapped particle forecast. Two models were employed on the South Atlantic Anomaly (SAA) region. Electron of >30 keV (mep0e1) from National Oceanic and Atmospheric Administration (NOAA) 15-18 satellites data was chosen as the particle modeled. We used two weeks data to perform the model fitting on a 5°x5° grid of longitude and latitude, and 31 August 2007 was set as the date of forecast. Three statistical validations were performed on the data, i.e. the root mean square error (RMSE), mean absolute percentage error (MAPE) and bias (BIAS). The statistical analysis showed that GP model performed better than AR with the average of RMSE = 0.38 and 0.63, MAPE = 11.98 and 17.30, and BIAS = 0.32 and 0.24, for GP and AR, respectively. Visual validation on both models with the NOAA map's also confirmed the superior of the GP than the AR. The variance of log flux minimum = 0.09 and 1.09, log flux maximum = 1.15 and 1.35, and in successively represents GP and AR

Multiscale stabilization for convection-dominated diffusion in heterogeneous media

KAUST Repository

Calo, Victor M.

2016-02-23

We develop a Petrov-Galerkin stabilization method for multiscale convection-diffusion transport systems. Existing stabilization techniques add a limited number of degrees of freedom in the form of bubble functions or a modified diffusion, which may not be sufficient to stabilize multiscale systems. We seek a local reduced-order model for this kind of multiscale transport problems and thus, develop a systematic approach for finding reduced-order approximations of the solution. We start from a Petrov-Galerkin framework using optimal weighting functions. We introduce an auxiliary variable to a mixed formulation of the problem. The auxiliary variable stands for the optimal weighting function. The problem reduces to finding a test space (a dimensionally reduced space for this auxiliary variable), which guarantees that the error in the primal variable (representing the solution) is close to the projection error of the full solution on the dimensionally reduced space that approximates the solution. To find the test space, we reformulate some recent mixed Generalized Multiscale Finite Element Methods. We introduce snapshots and local spectral problems that appropriately define local weight and trial spaces. In particular, we use energy minimizing snapshots and local spectral decompositions in the natural norm associated with the auxiliary variable. The resulting spectral decomposition adaptively identifies and builds the optimal multiscale space to stabilize the system. We discuss the stability and its relation to the approximation property of the test space. We design online basis functions, which accelerate convergence in the test space, and consequently, improve stability. We present several numerical examples and show that one needs a few test functions to achieve an error similar to the projection error in the primal variable irrespective of the Peclet number.

Oriented diffusion filtering for enhancing low-quality fingerprint images

KAUST Repository

Gottschlich, C.; Schönlieb, C.-B.

2012-01-01

To enhance low-quality fingerprint images, we present a novel method that first estimates the local orientation of the fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast enhancement step. By applying the authors' new approach to low-quality images of the FVC2004 fingerprint databases, the authors are able to show its competitiveness with other state-of-the-art enhancement methods for fingerprints like curved Gabor filtering. A major advantage of oriented diffusion filtering over those is its computational efficiency. Combining oriented diffusion filtering with curved Gabor filters led to additional improvements and, to the best of the authors' knowledge, the lowest equal error rates achieved so far using MINDTCT and BOZORTH3 on the FVC2004 databases. The recognition performance and the computational efficiency of the method suggest to include oriented diffusion filtering as a standard image enhancement add-on module for real-time fingerprint recognition systems. In order to facilitate the reproduction of these results, an implementation of the oriented diffusion filtering for Matlab and GNU Octave is made available for download. © 2012 The Institution of Engineering and Technology.

Oriented diffusion filtering for enhancing low-quality fingerprint images

KAUST Repository

Gottschlich, C.

2012-01-01

To enhance low-quality fingerprint images, we present a novel method that first estimates the local orientation of the fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast enhancement step. By applying the authors\\' new approach to low-quality images of the FVC2004 fingerprint databases, the authors are able to show its competitiveness with other state-of-the-art enhancement methods for fingerprints like curved Gabor filtering. A major advantage of oriented diffusion filtering over those is its computational efficiency. Combining oriented diffusion filtering with curved Gabor filters led to additional improvements and, to the best of the authors\\' knowledge, the lowest equal error rates achieved so far using MINDTCT and BOZORTH3 on the FVC2004 databases. The recognition performance and the computational efficiency of the method suggest to include oriented diffusion filtering as a standard image enhancement add-on module for real-time fingerprint recognition systems. In order to facilitate the reproduction of these results, an implementation of the oriented diffusion filtering for Matlab and GNU Octave is made available for download. © 2012 The Institution of Engineering and Technology.

Hierarchical porous photoanode based on acid boric catalyzed sol for dye sensitized solar cells

Energy Technology Data Exchange (ETDEWEB)

Maleki, Khatereh [School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, P.O. Box: 14395-553, Tehran (Iran, Islamic Republic of); Abdizadeh, Hossein [School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, P.O. Box: 14395-553, Tehran (Iran, Islamic Republic of); Center of Excellence for High Performance Materials, University of Tehran, Tehran (Iran, Islamic Republic of); Golobostanfard, Mohammad Reza, E-mail: Mohammadreza.Golbostanfard@gmail.com [School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, P.O. Box: 14395-553, Tehran (Iran, Islamic Republic of); Adelfar, Razieh [School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, P.O. Box: 14395-553, Tehran (Iran, Islamic Republic of)

2017-02-01

Highlights: • Acid boric can thoroughly leads to the hierarchical porous titania structure. • Boron is introduced into titania lattice which causes slight blueshift of bandgap. • The optimized sol parameters are H{sub 3}BO{sub 3}/TTiP = 0.45, DI/TTiP = 4.5, and 0.17 M. • Optimized paste parameters is not changed compared to conventional pastes. • The DSSC based on H{sub 3}BO{sub 3} catalyzed sol shows promising efficiency of 2.91%. - Abstract: The hierarchical porous photoanode of the dye sensitized solar cell (DSSC) is synthesized through non-aqueous sol-gel method based on H{sub 3}BO{sub 3} as an acid catalyst and the efficiencies of the fabricated DSSC based on these photoanodes are compared. The sol parameters of 0.17 M, water mole ratio of 4.5, acid mole ratio of 0.45, and solvent type of ethanol are introduced as optimum parameters for photoanode formation without any detectable cracks. The optimized hierarchical photoanode mainly contains anatase phase with slight shift toward higher angles, confirming the doping of boron into titania structure. Moreover, the porous structure involves two ranges of average pore sizes of 20 and 635 nm. The diffuse reflectance spectroscopy (DRS) shows the proper scattering and blueshift in band gap. The paste parameters of solid:liquid, TiO{sub 2}:ethyl cellulose, and terpineol:ethanol equal to 11:89, 3.5:7.5, and 25:64, respectively, are assigned as optimized parameters for this novel paste. The photovoltaic properties of short circuit current density, open circuit voltage, fill factor, and efficiency of 5.89 mA/cm{sup 2}, 703 mV, 0.7, and 2.91% are obtained for the optimized sample, respectively. The relatively higher short circuit current of the main sample compared to other samples is mainly due to higher dye adsorption in this sample corresponding to its higher surface area and presumably higher charge transfer confirmed by low R{sub S} and R{sub ct} in electrochemical impedance spectroscopy data. Boric acid as

Modeling of the interplay between single-file diffusion and conversion reaction in mesoporous systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Jing [Iowa State Univ., Ames, IA (United States)

2013-01-11

We analyze the spatiotemporal behavior of species concentrations in a diffusion-mediated conversion reaction which occurs at catalytic sites within linear pores of nanometer diameter. A strict single-file (no passing) constraint occurs in the diffusion within such narrow pores. Both transient and steady-state behavior is precisely characterized by kinetic Monte Carlo simulations of a spatially discrete lattice–gas model for this reaction–diffusion process considering various distributions of catalytic sites. Exact hierarchical master equations can also be developed for this model. Their analysis, after application of mean-field type truncation approximations, produces discrete reaction–diffusion type equations (mf-RDE). For slowly varying concentrations, we further develop coarse-grained continuum hydrodynamic reaction–diffusion equations (h-RDE) incorporating a precise treatment of single-file diffusion (SFD) in this multispecies system. Noting the shortcomings of mf-RDE and h-RDE, we then develop a generalized hydrodynamic (GH) formulation of appropriate gh-RDE which incorporates an unconventional description of chemical diffusion in mixed-component quasi-single-file systems based on a refined picture of tracer diffusion for finite-length pores. The gh-RDE elucidate the non-exponential decay of the steady-state reactant concentration into the pore and the non-mean-field scaling of the reactant penetration depth. Then an extended model of a catalytic conversion reaction within a functionalized nanoporous material is developed to assess the effect of varying the reaction product – pore interior interaction from attractive to repulsive. The analysis is performed utilizing the generalized hydrodynamic formulation of the reaction-diffusion equations which can reliably capture the complex interplay between reaction and restricted transport for both irreversible and reversible reactions.

Hierarchical Porous Structures

Energy Technology Data Exchange (ETDEWEB)

Grote, Christopher John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-06-07

Materials Design is often at the forefront of technological innovation. While there has always been a push to generate increasingly low density materials, such as aero or hydrogels, more recently the idea of bicontinuous structures has gone more into play. This review will cover some of the methods and applications for generating both porous, and hierarchically porous structures.

On an adaptive time stepping strategy for solving nonlinear diffusion equations

International Nuclear Information System (INIS)

Chen, K.; Baines, M.J.; Sweby, P.K.

1993-01-01

A new time step selection procedure is proposed for solving non- linear diffusion equations. It has been implemented in the ASWR finite element code of Lorenz and Svoboda [10] for 2D semiconductor process modelling diffusion equations. The strategy is based on equi-distributing the local truncation errors of the numerical scheme. The use of B-splines for interpolation (as well as for the trial space) results in a banded and diagonally dominant matrix. The approximate inverse of such a matrix can be provided to a high degree of accuracy by another banded matrix, which in turn can be used to work out the approximate finite difference scheme corresponding to the ASWR finite element method, and further to calculate estimates of the local truncation errors of the numerical scheme. Numerical experiments on six full simulation problems arising in semiconductor process modelling have been carried out. Results show that our proposed strategy is more efficient and better conserves the total mass. 18 refs., 6 figs., 2 tabs

Variations in Static Force Control and Motor Unit Behavior with Error Amplification Feedback in the Elderly

Directory of Open Access Journals (Sweden)

Yi-Ching Chen

2017-11-01

Full Text Available Error amplification (EA feedback is a promising approach to advance visuomotor skill. As error detection and visuomotor processing at short time scales decline with age, this study examined whether older adults could benefit from EA feedback that included higher-frequency information to guide a force-tracking task. Fourteen young and 14 older adults performed low-level static isometric force-tracking with visual guidance of typical visual feedback and EA feedback containing augmented high-frequency errors. Stabilogram diffusion analysis was used to characterize force fluctuation dynamics. Also, the discharge behaviors of motor units and pooled motor unit coherence were assessed following the decomposition of multi-channel surface electromyography (EMG. EA produced different behavioral and neurophysiological impacts on young and older adults. Older adults exhibited inferior task accuracy with EA feedback than with typical visual feedback, but not young adults. Although stabilogram diffusion analysis revealed that EA led to a significant decrease in critical time points for both groups, EA potentiated the critical point of force fluctuations <ΔFc2>, short-term effective diffusion coefficients (Ds, and short-term exponent scaling only for the older adults. Moreover, in older adults, EA added to the size of discharge variability of motor units and discharge regularity of cumulative discharge rate, but suppressed the pooled motor unit coherence in the 13–35 Hz band. Virtual EA alters the strategic balance between open-loop and closed-loop controls for force-tracking. Contrary to expectations, the prevailing use of closed-loop control with EA that contained high-frequency error information enhanced the motor unit discharge variability and undermined the force steadiness in the older group, concerning declines in physiological complexity in the neurobehavioral system and the common drive to the motoneuronal pool against force destabilization.

Monte Carlo Finite Volume Element Methods for the Convection-Diffusion Equation with a Random Diffusion Coefficient

Directory of Open Access Journals (Sweden)

Qian Zhang

2014-01-01

Full Text Available The paper presents a framework for the construction of Monte Carlo finite volume element method (MCFVEM for the convection-diffusion equation with a random diffusion coefficient, which is described as a random field. We first approximate the continuous stochastic field by a finite number of random variables via the Karhunen-Loève expansion and transform the initial stochastic problem into a deterministic one with a parameter in high dimensions. Then we generate independent identically distributed approximations of the solution by sampling the coefficient of the equation and employing finite volume element variational formulation. Finally the Monte Carlo (MC method is used to compute corresponding sample averages. Statistic error is estimated analytically and experimentally. A quasi-Monte Carlo (QMC technique with Sobol sequences is also used to accelerate convergence, and experiments indicate that it can improve the efficiency of the Monte Carlo method.

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

Science.gov (United States)

Colas, Jaron T

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

Directory of Open Access Journals (Sweden)

Jaron T Colas

Full Text Available In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation

Science.gov (United States)

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes “winner-take-all” processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans’ value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light. PMID:29077746

Greedy algorithms for diffuse optical tomography reconstruction

Science.gov (United States)

Dileep, B. P. V.; Das, Tapan; Dutta, Pranab K.

2018-03-01

Diffuse optical tomography (DOT) is a noninvasive imaging modality that reconstructs the optical parameters of a highly scattering medium. However, the inverse problem of DOT is ill-posed and highly nonlinear due to the zig-zag propagation of photons that diffuses through the cross section of tissue. The conventional DOT imaging methods iteratively compute the solution of forward diffusion equation solver which makes the problem computationally expensive. Also, these methods fail when the geometry is complex. Recently, the theory of compressive sensing (CS) has received considerable attention because of its efficient use in biomedical imaging applications. The objective of this paper is to solve a given DOT inverse problem by using compressive sensing framework and various Greedy algorithms such as orthogonal matching pursuit (OMP), compressive sampling matching pursuit (CoSaMP), and stagewise orthogonal matching pursuit (StOMP), regularized orthogonal matching pursuit (ROMP) and simultaneous orthogonal matching pursuit (S-OMP) have been studied to reconstruct the change in the absorption parameter i.e, Δα from the boundary data. Also, the Greedy algorithms have been validated experimentally on a paraffin wax rectangular phantom through a well designed experimental set up. We also have studied the conventional DOT methods like least square method and truncated singular value decomposition (TSVD) for comparison. One of the main features of this work is the usage of less number of source-detector pairs, which can facilitate the use of DOT in routine applications of screening. The performance metrics such as mean square error (MSE), normalized mean square error (NMSE), structural similarity index (SSIM), and peak signal to noise ratio (PSNR) have been used to evaluate the performance of the algorithms mentioned in this paper. Extensive simulation results confirm that CS based DOT reconstruction outperforms the conventional DOT imaging methods in terms of

Light diffusion in N-layered turbid media: steady-state domain.

Science.gov (United States)

Liemert, André; Kienle, Alwin

2010-01-01

We deal with light diffusion in N-layered turbid media. The steady-state diffusion equation is solved for N-layered turbid media having a finite or an infinitely thick N'th layer. Different refractive indices are considered in the layers. The Fourier transform formalism is applied to derive analytical solutions of the fluence rate in Fourier space. The inverse Fourier transform is calculated using four different methods to test their performance and accuracy. Further, to avoid numerical errors, approximate formulas in Fourier space are derived. Fast solutions for calculation of the spatially resolved reflectance and transmittance from the N-layered turbid media ( approximately 10 ms) with small relative differences (<10(-7)) are found. Additionally, the solutions of the diffusion equation are compared to Monte Carlo simulations for turbid media having up to 20 layers.

Analyzing security protocols in hierarchical networks

DEFF Research Database (Denmark)

Zhang, Ye; Nielson, Hanne Riis

2006-01-01

Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

Hierarchical Analysis of the Omega Ontology

Energy Technology Data Exchange (ETDEWEB)

Joslyn, Cliff A.; Paulson, Patrick R.

2009-12-01

Initial delivery for mathematical analysis of the Omega Ontology. We provide an analysis of the hierarchical structure of a version of the Omega Ontology currently in use within the US Government. After providing an initial statistical analysis of the distribution of all link types in the ontology, we then provide a detailed order theoretical analysis of each of the four main hierarchical links present. This order theoretical analysis includes the distribution of components and their properties, their parent/child and multiple inheritance structure, and the distribution of their vertical ranks.

Active Power Quality Improvement Strategy for Grid-connected Microgrid Based on Hierarchical Control

DEFF Research Database (Denmark)

Wei, Feng; Sun, Kai; Guan, Yajuan

2018-01-01

proposes an active, unbalanced, and harmonic GCC suppression strategy based on hierarchical theory. The voltage error between the bus of the DCGC-MG and the grid’s PCC was transformed to the dq frame. On the basis of the grid, an additional compensator, which consists of multiple resonant voltage......When connected to a distorted grid utility, droop-controlled grid-connected microgrids (DCGC-MG) exhibit low equivalent impedance. The harmonic and unbalanced voltage at the point of common coupling (PCC) deteriorates the power quality of the grid-connected current (GCC) of DCGC-MG. This work...... regulators, was then added to the original secondary control to generate the negative fundamental and unbalanced harmonic voltage reference. Proportional integral and multiple resonant controllers were adopted as voltage controller at the original primary level to improve the voltage tracking performance...

Diffusion in multicomponent systems: a free energy approach

International Nuclear Information System (INIS)

Emmanuel, Simon; Cortis, Andrea; Berkowitz, Brian

2004-01-01

This work examines diffusion in ternary non-ideal systems and derives coupled non-linear equations based on a non-equilibrium thermodynamic approach in which an explicit expression for the free energy is substituted into standard diffusion equations. For ideal solutions, the equations employ four mobility parameters (M aa , M ab , M ba , and M bb ), and uphill diffusion is predicted for certain initial conditions and combinations of mobilities. For the more complex case of ternary Simple Mixtures, two non-ideality parameters (χ ac and χ bc ) that are directly related to the excess free energy of mixing are introduced. The solution of the equations is carried out by means of two different numerical schemes: (1) spectral collocation and (2) finite element. An error minimization technique is coupled with the spectral collocation method and applied to diffusional profiles to extract the M and χ parameters. The model satisfactorily reproduces diffusional profiles from published data for silicate melts. Further improvements in numerical and experimental techniques are then suggested

Hierarchical composites: Analysis of damage evolution based on fiber bundle model

DEFF Research Database (Denmark)

Mishnaevsky, Leon

2011-01-01

A computational model of multiscale composites is developed on the basis of the fiber bundle model with the hierarchical load sharing rule, and employed to study the effect of the microstructures of hierarchical composites on their damage resistance. Two types of hierarchical materials were consi...

Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

KAUST Repository

Sang, Huiyan

2011-12-01

This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models. Our method allows for a nonseparable and nonstationary cross-covariance structure. We also present a covariance approximation approach to facilitate the computation in the modeling and analysis of very large multivariate spatial data sets. The covariance approximation consists of two parts: a reduced-rank part to capture the large-scale spatial dependence, and a sparse covariance matrix to correct the small-scale dependence error induced by the reduced rank approximation. We pay special attention to the case that the second part of the approximation has a block-diagonal structure. Simulation results of model fitting and prediction show substantial improvement of the proposed approximation over the predictive process approximation and the independent blocks analysis. We then apply our computational approach to the joint statistical modeling of multiple climate model errors. © 2012 Institute of Mathematical Statistics.

Hierarchical cellular designs for load-bearing biocomposite beams and plates

International Nuclear Information System (INIS)

Burgueno, Rigoberto; Quagliata, Mario J.; Mohanty, Amar K.; Mehta, Geeta; Drzal, Lawrence T.; Misra, Manjusri

2005-01-01

Scrutiny into the composition of natural, or biological materials convincingly reveals that high material and structural efficiency can be attained, even with moderate-quality constituents, by hierarchical topologies, i.e., successively organized material levels or layers. The present study demonstrates that biologically inspired hierarchical designs can help improve the moderate properties of natural fiber polymer composites or biocomposites and allow them to compete with conventional materials for load-bearing applications. An overview of the mechanics concepts that allow hierarchical designs to achieve higher performance is presented, followed by observation and results from flexural tests on periodic and hierarchical cellular beams and plates made from industrial hemp fibers and unsaturated polyester resin biocomposites. The experimental data is shown to agree well with performance indices predicted by mechanics models. A procedure for the multi-scale integrated material/structural analysis of hierarchical cellular biocomposite components is presented and its advantages and limitations are discussed

Self-assembled hierarchical carbon/g-C3N4 composite with high photocatalytic activity

Science.gov (United States)

Huang, Ru-Long; Huang, Wei-Qing; Li, Dong-Feng; Ma, Li-Li; Pan, Anlian; Hu, Wangyu; Fan, Xiaoxing; Huang, Gui-Fang

2018-04-01

Hierarchical carbon/g-C3N4 composites consisting of nanosheets are synthesized by a direct thermal diffusion and exfoliation approach with glucose acting as the intercalator and carbon source. This facile protocol not only renders nanosheets with a large surface area, but also carbon intercalation into the interlayer of g-C3N4. Therefore, the synthesized carbon/g-C3N4 composites exhibit superior photocatalytic performance for degrading representative methylene blue (MB) under visible light irradiatuon. Carbon/g-C3N4 composites with an optimal glucose mass ratio of 0.25% show the apparent reaction rate constant of 0.253 h-1, which is 9 times higher than that over bluk g-C3N4. The superior photocatalytic performance of carbon/g-C3N4 hierarchical architectures can be attributed to the synergic effects of large reactive sites, effective visible light adsorption and faster charge transfer owing to the superior electron transfer ability of carbon as verified by the PL and photoelectrochemical measurements. The main reactive species responsible for the photocatalytic degradation are photoinduced holes and ·OH radicals under visible light irradiation. This work provides a facile way to fabricate effecient g-C3N4-based photocatalysts for the potential application in dealing with environmental and energy shortage issues using solar energy.

Methodology for assessment of safety risk due to potential accidents in US gaseous diffusion plants

International Nuclear Information System (INIS)

Turner, J.H.; O'Kain, D.U.

1991-01-01

Gaseous diffusion plants that operate in the United States represent a unique combination of nuclear and chemical hazards. Assessing and controlling the health, safety, and environmental risks that can result from natural phenomena events, process upset conditions, and operator errors require a unique methodology. Such a methodology has been developed for the diffusion plants and is being utilized to assess and control the risk of operating the plants. A summary of the methodology developed to assess the unique safety risks at the US gaseous diffusion plants is presented in this paper

Fabrication of Superhydrophobic Surface with Controlled Wetting Property by Hierarchical Particles.

Science.gov (United States)

Xu, Jianxiong; Liu, Weiwei; Du, Jingjing; Tang, Zengmin; Xu, Lijian; Li, Na

2015-04-01

Hierarchical particles were prepared by synthetically joining appropriately functionalized polystyrene spheres of poly[styrene-co-(3-(4-vinylphenyl)pentane-2,4-dione)] (PS-co-PVPD) nanoparticles and poly(styrene-co-chloromethylstyrene) (PS-co-PCMS) microparticles. The coupling reaction of nucleophilic substitution of pendent β-diketone groups with benzyl chloride was used to form the hierarchical particles. Since the polymeric nanoparticles and microparticles were synthesized by dispersion polymerization and emulsion polymerization, respectively, both the core microparticles and the surface nanoparticles can be different size and chemical composition. By means of changing the size of the PS-co-PVPD surface nanoparticles, a series of hierarchical particles with different scale ratio of the micro/nano surface structure were successfully prepared. Moreover, by employing the PS-co-PVPD microparticles and PS-co-PCMS nanoparticles as building blocks, hierarchical particles with surface nanoaprticles of different composition were made. These as-prepared hierarchical particles were subsequently assembled on glass substrates to form particulate films. Contact angle measurement shows that superhydrophobic surfaces can be obtained and the contact angle of water on the hierarchically structured surface can be adjusted by the scale ratio of the micro/nano surface structure and surface chemical component of hierarchical particles.

Solving the neutron diffusion equation on combinatorial geometry computational cells for reactor physics calculations

International Nuclear Information System (INIS)

Azmy, Y. Y.

2004-01-01

An approach is developed for solving the neutron diffusion equation on combinatorial geometry computational cells, that is computational cells composed by combinatorial operations involving simple-shaped component cells. The only constraint on the component cells from which the combinatorial cells are assembled is that they possess a legitimate discretization of the underlying diffusion equation. We use the Finite Difference (FD) approximation of the x, y-geometry diffusion equation in this work. Performing the same combinatorial operations involved in composing the combinatorial cell on these discrete-variable equations yields equations that employ new discrete variables defined only on the combinatorial cell's volume and faces. The only approximation involved in this process, beyond the truncation error committed in discretizing the diffusion equation over each component cell, is a consistent-order Legendre series expansion. Preliminary results for simple configurations establish the accuracy of the solution to the combinatorial geometry solution compared to straight FD as the system dimensions decrease. Furthermore numerical results validate the consistent Legendre-series expansion order by illustrating the second order accuracy of the combinatorial geometry solution, the same as standard FD. Nevertheless the magnitude of the error for the new approach is larger than FD's since it incorporates the additional truncated series approximation. (authors)

Flux-gradient relationships and soil-water diffusivity from curves of water content versus time

Energy Technology Data Exchange (ETDEWEB)

Nofziger, D.L.; Ahuja, L.R.; Swartzendruber, D.

Direct analysis of a family of curves of soil-water content vs. time at different fixed positions enables assessment of the flux-gradient relationship prior to the calculations of soil-water diffusivity. The method is evaluated on both smooth and random-error data generated from the solution of the horizontal soil-water intake problem with a known diffusivity function. Interpolation, differentiation, and intergration are carried out by least-squares curve fitting based on the 2 recently developed techniques of parabolic splines and sliding parabolas, with all computations performed by computer. Results are excellent for both smooth and random-error input data, whether in terms of recovering the original known diffusivity function, assessing the nature of the flux-gradient relationship, or in making the numerous checks and validations at various intermediate stages of computation. The method applies for any horizontal soil-wetting process independently of the specific boundary conditions, including water entry through a nonzero inlet resistance. It should be adaptable to horizontal dewatering, and extendable to vertical flow. (11 refs.)

Identification and Assessment of Human Errors in Postgraduate Endodontic Students of Kerman University of Medical Sciences by Using the SHERPA Method

Directory of Open Access Journals (Sweden)

Saman Dastaran

2016-03-01

Full Text Available Introduction: Human errors are the cause of many accidents, including industrial and medical, therefore finding out an approach for identifying and reducing them is very important. Since no study has been done about human errors in the dental field, this study aimed to identify and assess human errors in postgraduate endodontic students of Kerman University of Medical Sciences by using the SHERPA Method. Methods: This cross-sectional study was performed during year 2014. Data was collected using task observation and interviewing postgraduate endodontic students. Overall, 10 critical tasks, which were most likely to cause harm to patients were determined. Next, Hierarchical Task Analysis (HTA was conducted and human errors in each task were identified by the Systematic Human Error Reduction Prediction Approach (SHERPA technique worksheets. Results: After analyzing the SHERPA worksheets, 90 human errors were identified including (67.7% action errors, (13.3% checking errors, (8.8% selection errors, (5.5% retrieval errors and (4.4% communication errors. As a result, most of them were action errors and less of them were communication errors. Conclusions: The results of the study showed that the highest percentage of errors and the highest level of risk were associated with action errors, therefore, to reduce the occurrence of such errors and limit their consequences, control measures including periodical training of work procedures, providing work check-lists, development of guidelines and establishment of a systematic and standardized reporting system, should be put in place. Regarding the results of this study, the control of recovery errors with the highest percentage of undesirable risk and action errors with the highest frequency of errors should be in the priority of control

TiO_2 hierarchical hollow microspheres with different size for application as anodes in high-performance lithium storage

International Nuclear Information System (INIS)

Wang, Xiaobing; Meng, Qiuxia; Wang, Yuanyuan; Liang, Huijun; Bai, Zhengyu; Wang, Kui; Lou, Xiangdong; Cai, Bibo; Yang, Lin

2016-01-01

Graphical abstract: In the application of lithium-ion batteries, the influences of microsphere sizes are more significant than the secondary nanoparticles size and crystallinity of TiO_2-HSs for their transfer resistance and cycling performance, so that the bigger sizes of TiO_2-HSs can retain high reversible capacities after 30 recycles. - Highlights: • Hierarchical hollow microspheres have size-effect in the application of lithium ion battery. • The microsphere sizes can significantly affect the cycling capacities of TiO_2. • The nanoparticles size affect the initial discharge capacity and lithium ion diffusion. • Controlled microsphere size is more significant for improving TiO_2 cycling capacities. - Abstract: Nowadays, the safety issue has greatly hindered the development of large capacity lithium-ion batteries (LIBs), especially in electric vehicles applications. TiO_2 is a kind of potential anode candidate for improving the safety of LIBs. However, it still needs to understand how to improve the performance of TiO_2 anode in the practical applications. Herein, we design a contrast experiment by using three sizes of TiO_2 hierarchical hollow microspheres (TiO_2-HSs). The research results indicated that the cycling performance of TiO_2-HSs anode can be affected by the size of microspheres, and the nanoparticles size of microspheres and crystallinity of TiO_2 can affect their initial discharge capacity and lithium ion diffusion. And, the influence of microspheres size is more significant. This may provide a new strategy for improving the lithium-ion storage property of TiO_2 anode material in the practical applications.

Easy fabrication and high electrochemical capacitive performance of hierarchical porous carbon by a method combining liquid-liquid phase separation and pyrolysis process

International Nuclear Information System (INIS)

Fan, Hui-li; Ran, Fen; Zhang, Xuan-xuan; Song, Hai-ming; Jing, Wen-xia; Shen, Kui-wen; Kong, Ling-bin; Kang, Long

2014-01-01

A hierarchical porous carbon membrane was designed and prepared through a method combining liquid-liquid phase separation and then pyrolysis process using polyacrylonitrile (PAN) as precursor. The results of scan electron microscopy, transmission electron microscope and Brunauer-Emmett-Teller characterization reveal that the 3D nanoscaled architecture with hierarchical porous structure was achieved, which not only provide a continuous electron pathway to ensure good electrical contact, but also facilitate ion transport by shortening diffusion pathways. The effect of PAN concentration in casting solution on structure feature of carbon membrane was also studied, indicating that the membrane thickness with different porous structure can be mediated by PAN concentration. As the electrode material for supercapacitor, a high specific capacitance of 277.0 F g −1 was attained at a current density of 5 mA cm −2 and long cycle life of 90.0% capacity retention was obtained after 2000 charge-discharge cycles in 2 mol L −1 KOH solution

Discursive Hierarchical Patterning in Law and Management Cases

Science.gov (United States)

Lung, Jane

2008-01-01

This paper investigates the differences in the discursive patterning of cases in Law and Management. It examines a corpus of 271 Law and Management cases and discusses the kind of information that these two disciplines call for and how discourses are constructed in discursive hierarchical patterns. A discursive hierarchical pattern is a model…

The numerical simulation of convection delayed dominated diffusion equation

Directory of Open Access Journals (Sweden)

Mohan Kumar P. Murali

2016-01-01

Full Text Available In this paper, we propose a fitted numerical method for solving convection delayed dominated diffusion equation. A fitting factor is introduced and the model equation is discretized by cubic spline method. The error analysis is analyzed for the consider problem. The numerical examples are solved using the present method and compared the result with the exact solution.

Hierarchical modularity in human brain functional networks

Directory of Open Access Journals (Sweden)

David Meunier

2009-10-01

Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

Hierarchical Context Modeling for Video Event Recognition.

Science.gov (United States)

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Embedded vision equipment of industrial robot for inline detection of product errors by clustering–classification algorithms

Directory of Open Access Journals (Sweden)

Kamil Zidek

2016-10-01

Full Text Available The article deals with the design of embedded vision equipment of industrial robots for inline diagnosis of product error during manipulation process. The vision equipment can be attached to the end effector of robots or manipulators, and it provides an image snapshot of part surface before grasp, searches for error during manipulation, and separates products with error from the next operation of manufacturing. The new approach is a methodology based on machine teaching for the automated identification, localization, and diagnosis of systematic errors in products of high-volume production. To achieve this, we used two main data mining algorithms: clustering for accumulation of similar errors and classification methods for the prediction of any new error to proposed class. The presented methodology consists of three separate processing levels: image acquisition for fail parameterization, data clustering for categorizing errors to separate classes, and new pattern prediction with a proposed class model. We choose main representatives of clustering algorithms, for example, K-mean from quantization of vectors, fast library for approximate nearest neighbor from hierarchical clustering, and density-based spatial clustering of applications with noise from algorithm based on the density of the data. For machine learning, we selected six major algorithms of classification: support vector machines, normal Bayesian classifier, K-nearest neighbor, gradient boosted trees, random trees, and neural networks. The selected algorithms were compared for speed and reliability and tested on two platforms: desktop-based computer system and embedded system based on System on Chip (SoC with vision equipment.

Bayesian nonparametric hierarchical modeling.

Science.gov (United States)

Dunson, David B

2009-04-01

In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.

Hierarchical species distribution models

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

Hierarchical silica particles by dynamic multicomponent assembly

DEFF Research Database (Denmark)

Wu, Z. W.; Hu, Q. Y.; Pang, J. B.

2005-01-01

Abstract: Aerosol-assisted assembly of mesoporous silica particles with hierarchically controllable pore structure has been prepared using cetyltrimethylammonium bromide (CTAB) and poly(propylene oxide) (PPO, H[OCH(CH3)CH2],OH) as co-templates. Addition of the hydrophobic PPO significantly...... influences the delicate hydrophilic-hydrophobic balance in the well-studied CTAB-silicate co-assembling system, resulting in various mesostructures (such as hexagonal, lamellar, and hierarchical structure). The co-assembly of CTAB, silicate clusters, and a low-molecular-weight PPO (average M-n 425) results...... in a uniform lamellar structure, while the use of a high-molecular-weight PPO (average M-n 2000), which is more hydrophobic, leads to the formation of hierarchical pore structure that contains meso-meso or meso-macro pore structure. The role of PPO additives on the mesostructure evolution in the CTAB...

A multiscale MD-FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure.

Science.gov (United States)

Kojic, M; Milosevic, M; Kojic, N; Kim, K; Ferrari, M; Ziemys, A

2014-02-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts.

Errors, error detection, error correction and hippocampal-region damage: data and theories.

Science.gov (United States)

MacKay, Donald G; Johnson, Laura W

2013-11-01

This review and perspective article outlines 15 observational constraints on theories of errors, error detection, and error correction, and their relation to hippocampal-region (HR) damage. The core observations come from 10 studies with H.M., an amnesic with cerebellar and HR damage but virtually no neocortical damage. Three studies examined the detection of errors planted in visual scenes (e.g., a bird flying in a fish bowl in a school classroom) and sentences (e.g., I helped themselves to the birthday cake). In all three experiments, H.M. detected reliably fewer errors than carefully matched memory-normal controls. Other studies examined the detection and correction of self-produced errors, with controls for comprehension of the instructions, impaired visual acuity, temporal factors, motoric slowing, forgetting, excessive memory load, lack of motivation, and deficits in visual scanning or attention. In these studies, H.M. corrected reliably fewer errors than memory-normal and cerebellar controls, and his uncorrected errors in speech, object naming, and reading aloud exhibited two consistent features: omission and anomaly. For example, in sentence production tasks, H.M. omitted one or more words in uncorrected encoding errors that rendered his sentences anomalous (incoherent, incomplete, or ungrammatical) reliably more often than controls. Besides explaining these core findings, the theoretical principles discussed here explain H.M.'s retrograde amnesia for once familiar episodic and semantic information; his anterograde amnesia for novel information; his deficits in visual cognition, sentence comprehension, sentence production, sentence reading, and object naming; and effects of aging on his ability to read isolated low frequency words aloud. These theoretical principles also explain a wide range of other data on error detection and correction and generate new predictions for future test. Copyright © 2013 Elsevier Ltd. All rights reserved.

Engineering 3D bicontinuous hierarchically macro-mesoporous LiFePO4/C nanocomposite for lithium storage with high rate capability and long cycle stability.

Science.gov (United States)

Zhang, Qian; Huang, Shao-Zhuan; Jin, Jun; Liu, Jing; Li, Yu; Wang, Hong-En; Chen, Li-Hua; Wang, Bin-Jie; Su, Bao-Lian

2016-05-16

A highly crystalline three dimensional (3D) bicontinuous hierarchically macro-mesoporous LiFePO4/C nanocomposite constructed by nanoparticles in the range of 50~100 nm via a rapid microwave assisted solvothermal process followed by carbon coating have been synthesized as cathode material for high performance lithium-ion batteries. The abundant 3D macropores allow better penetration of electrolyte to promote Li(+) diffusion, the mesopores provide more electrochemical reaction sites and the carbon layers outside LiFePO4 nanoparticles increase the electrical conductivity, thus ultimately facilitating reverse reaction of Fe(3+) to Fe(2+) and alleviating electrode polarization. In addition, the particle size in nanoscale can provide short diffusion lengths for the Li(+) intercalation-deintercalation. As a result, the 3D macro-mesoporous nanosized LiFePO4/C electrode exhibits excellent rate capability (129.1 mA h/g at 2 C; 110.9 mA h/g at 10 C) and cycling stability (87.2% capacity retention at 2 C after 1000 cycles, 76.3% at 5 C after 500 cycles and 87.8% at 10 C after 500 cycles, respectively), which are much better than many reported LiFePO4/C structures. Our demonstration here offers the opportunity to develop nanoscaled hierarchically porous LiFePO4/C structures for high performance lithium-ion batteries through microwave assisted solvothermal method.

Hierarchical classification with a competitive evolutionary neural tree.

Science.gov (United States)

Adams, R G.; Butchart, K; Davey, N

1999-04-01

A new, dynamic, tree structured network, the Competitive Evolutionary Neural Tree (CENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage that the CENT offers over other hierarchical competitive networks is its ability to self determine the number, and structure, of the competitive nodes in the network, without the need for externally set parameters. The network produces stable classificatory structures by halting its growth using locally calculated heuristics. The results of network simulations are presented over a range of data sets, including Anderson's IRIS data set. The CENT network demonstrates its ability to produce a representative hierarchical structure to classify a broad range of data sets.

Direct hierarchical assembly of nanoparticles

Science.gov (United States)

Xu, Ting; Zhao, Yue; Thorkelsson, Kari

2014-07-22

The present invention provides hierarchical assemblies of a block copolymer, a bifunctional linking compound and a nanoparticle. The block copolymers form one micro-domain and the nanoparticles another micro-domain.

Band structures of two dimensional solid/air hierarchical phononic crystals

Energy Technology Data Exchange (ETDEWEB)

Xu, Y.L.; Tian, X.G. [State Key Laboratory for Mechanical Structure Strength and Vibration, Xi' an Jiaotong University, Xi' an 710049 (China); Chen, C.Q., E-mail: chencq@tsinghua.edu.cn [Department of Engineering Mechanics, AML and CNMM, Tsinghua University, Beijing 100084 (China)

2012-06-15

The hierarchical phononic crystals to be considered show a two-order 'hierarchical' feature, which consists of square array arranged macroscopic periodic unit cells with each unit cell itself including four sub-units. Propagation of acoustic wave in such two dimensional solid/air phononic crystals is investigated by the finite element method (FEM) with the Bloch theory. Their band structure, wave filtering property, and the physical mechanism responsible for the broadened band gap are explored. The corresponding ordinary phononic crystal without hierarchical feature is used for comparison. Obtained results show that the solid/air hierarchical phononic crystals possess tunable outstanding band gap features, which are favorable for applications such as sound insulation and vibration attenuation.

Nearly Cyclic Pursuit and its Hierarchical variant for Multi-agent Systems

DEFF Research Database (Denmark)

Iqbal, Muhammad; Leth, John-Josef; Ngo, Trung Dung

2015-01-01

The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version of the nea......The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version...

Automatic Hierarchical Color Image Classification

Directory of Open Access Journals (Sweden)

Jing Huang

2003-02-01

Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

Wechsler Adult Intelligence Scale-Revised Block Design broken configuration errors in nonpenetrating traumatic brain injury.

Science.gov (United States)

Wilde, M C; Boake, C; Sherer, M

2000-01-01

Final broken configuration errors on the Wechsler Adult Intelligence Scale-Revised (WAIS-R; Wechsler, 1981) Block Design subtest were examined in 50 moderate and severe nonpenetrating traumatically brain injured adults. Patients were divided into left (n = 15) and right hemisphere (n = 19) groups based on a history of unilateral craniotomy for treatment of an intracranial lesion and were compared to a group with diffuse or negative brain CT scan findings and no history of neurosurgery (n = 16). The percentage of final broken configuration errors was related to injury severity, Benton Visual Form Discrimination Test (VFD; Benton, Hamsher, Varney, & Spreen, 1983) total score and the number of VFD rotation and peripheral errors. The percentage of final broken configuration errors was higher in the patients with right craniotomies than in the left or no craniotomy groups, which did not differ. Broken configuration errors did not occur more frequently on designs without an embedded grid pattern. Right craniotomy patients did not show a greater percentage of broken configuration errors on nongrid designs as compared to grid designs.

Calculating the diffuse solar radiation in regions without solar radiation measurements

International Nuclear Information System (INIS)

Li, Huashan; Bu, Xianbiao; Long, Zhen; Zhao, Liang; Ma, Weibin

2012-01-01

Correlations for calculating diffuse solar radiation can be classified into models with global solar radiation (H-based method) and without it (Non-H method). The objective of the present study is to compare the performance of H-based and Non-H methods for calculating the diffuse solar radiation in regions without solar radiation measurements. The comparison is carried out at eight meteorological stations in China focusing on the monthly average daily diffuse solar radiation. Based on statistical error tests, the results show that the Non-H method that includes other readily available meteorological elements gives better estimates. Therefore, it can be concluded that the Non-H method is more appropriate than the H-based one for calculating the diffuse solar radiation in regions without solar radiation measurements. -- Highlights: ► Methods for calculating diffuse solar radiation in regions without solar radiation measurements are investigated. ► Diffuse solar radiation models can be classified into two groups according to global solar radiation. ► Two approaches are compared at the eight meteorological stations in China. ► The method without global solar radiation is recommended.

Hierarchical clustering using correlation metric and spatial continuity constraint

Science.gov (United States)

Stork, Christopher L.; Brewer, Luke N.

2012-10-02

Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.

Nitrogen-enriched hierarchically porous carbons prepared from polybenzoxazine for high-performance supercapacitors.

Science.gov (United States)

Wan, Liu; Wang, Jianlong; Xie, Lijing; Sun, Yahui; Li, Kaixi

2014-09-10

Nitrogen-enriched hierarchically porous carbons (HPCs) were synthesized from a novel nitrile-functionalized benzoxazine based on benzoxazine chemistry using a soft-templating method and a potassium hydroxide (KOH) chemical activation method and used as electrode materials for supercapacitors. The textural and chemical properties could be easily tuned by adding a soft template and changing the activation temperature. The introduction of the soft-templating agent (surfactant F127) resulted in the formation of mesopores, which facilitated fast ionic diffusion and reduced the internal resistance. The micropores of HPCs were extensively developed by KOH activation to provide large electrochemical double-layer capacitance. As the activation temperature increased from 600 to 800 °C, the specific surface area of nitrogen-enriched carbons increased dramatically, micropores were enlarged, and more meso/macropores were developed, but the nitrogen and oxygen content decreased, which affected the electrochemical performance. The sample HPC-800 activated at 800 °C possesses a high specific surface area (1555.4 m(2) g(-1)), high oxygen (10.61 wt %) and nitrogen (3.64 wt %) contents, a hierarchical pore structure, a high graphitization degree, and good electrical conductivity. It shows great pseudocapacitance and the largest specific capacitance of 641.6 F g(-1) at a current density of 1 A g(-1) in a 6 mol L(-1) KOH aqueous electrolyte when measured in a three-electrode system. Furthermore, the HPC-800 electrode exhibits excellent rate capability (443.0 F g(-1) remained at 40 A g(-1)) and good cycling stability (94.3% capacitance retention over 5000 cycles).

Intrinsic and extrinsic diffusion of phosphorus, arsenic, and antimony in germanium

International Nuclear Information System (INIS)

Brotzmann, Sergej; Bracht, Hartmut

2008-01-01

Diffusion experiments of phosphorus (P), arsenic (As), and antimony (Sb) in high purity germanium (Ge) were performed at temperatures between 600 and 920 deg. C. Secondary ion mass spectrometry and spreading resistance profiling were applied to determine the concentration profiles of the chemically and electrically active dopants. Intrinsic and extrinsic doping conditions result in a complementary error function and box-shaped diffusion profiles, respectively. These profiles demonstrate enhanced dopant diffusion under extrinsic doping. Accurate modeling of dopant diffusion is achieved on the basis of the vacancy mechanism taking into account singly negatively charged dopant-vacancy pairs and doubly negatively charged vacancies. The activation enthalpy and pre-exponential factor for dopant diffusion under intrinsic condition were determined to 2.85 eV and 9.1 cm 2 s -1 for P, 2.71 eV and 32 cm 2 s -1 for As, and 2.55 eV and 16.7 cm 2 s -1 for Sb. With increasing atomic size of the dopants the activation enthalpy decreases. This is attributed to differences in the binding energy of the dopant-vacancy pairs

Static and dynamic friction of hierarchical surfaces.

Science.gov (United States)

Costagliola, Gianluca; Bosia, Federico; Pugno, Nicola M

2016-12-01

Hierarchical structures are very common in nature, but only recently have they been systematically studied in materials science, in order to understand the specific effects they can have on the mechanical properties of various systems. Structural hierarchy provides a way to tune and optimize macroscopic mechanical properties starting from simple base constituents and new materials are nowadays designed exploiting this possibility. This can be true also in the field of tribology. In this paper we study the effect of hierarchical patterned surfaces on the static and dynamic friction coefficients of an elastic material. Our results are obtained by means of numerical simulations using a one-dimensional spring-block model, which has previously been used to investigate various aspects of friction. Despite the simplicity of the model, we highlight some possible mechanisms that explain how hierarchical structures can significantly modify the friction coefficients of a material, providing a means to achieve tunability.

Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

Science.gov (United States)

Broccardo, M.; Mignan, A.; Wiemer, S.; Stojadinovic, B.; Giardini, D.

2017-11-01

In this study, we present a Bayesian hierarchical framework to model fluid-induced seismicity. The framework is based on a nonhomogeneous Poisson process with a fluid-induced seismicity rate proportional to the rate of injected fluid. The fluid-induced seismicity rate model depends upon a set of physically meaningful parameters and has been validated for six fluid-induced case studies. In line with the vision of hierarchical Bayesian modeling, the rate parameters are considered as random variables. We develop both the Bayesian inference and updating rules, which are used to develop a probabilistic forecasting model. We tested the Basel 2006 fluid-induced seismic case study to prove that the hierarchical Bayesian model offers a suitable framework to coherently encode both epistemic uncertainty and aleatory variability. Moreover, it provides a robust and consistent short-term seismic forecasting model suitable for online risk quantification and mitigation.

Deep hierarchical attention network for video description

Science.gov (United States)

Li, Shuohao; Tang, Min; Zhang, Jun

2018-03-01

Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.

Using Directional Diffusion Coefficients for Nonlinear Diffusion Acceleration of the First Order SN Equations in Near-Void Regions

Energy Technology Data Exchange (ETDEWEB)

Schunert, Sebastian; Hammer, Hans; Lou, Jijie; Wang, Yaqi; Ortensi, Javier; Gleicher, Frederick; Baker, Benjamin; DeHart, Mark; Martineau, Richard

2016-11-01

The common definition of the diffusion coeffcient as the inverse of three times the transport cross section is not compat- ible with voids. Morel introduced a non-local tensor diffusion coeffcient that remains finite in voids[1]. It can be obtained by solving an auxiliary transport problem without scattering or fission. Larsen and Trahan successfully applied this diffusion coeffcient for enhancing the accuracy of diffusion solutions of very high temperature reactor (VHTR) problems that feature large, optically thin channels in the z-direction [2]. It is demonstrated that a significant reduction of error can be achieved in particular in the optically thin region. Along the same line of thought, non-local diffusion tensors are applied modeling the TREAT reactor confirming the findings of Larsen and Trahan [3]. Previous work of the authors have introduced a flexible Nonlinear-Diffusion Acceleration (NDA) method for the first order S N equations discretized with the discontinuous finite element method (DFEM), [4], [5], [6]. This NDA method uses a scalar diffusion coeffcient in the low-order system that is obtained as the flux weighted average of the inverse transport cross section. Hence, it su?ers from very large and potentially unbounded diffusion coeffcients in the low order problem. However, it was noted that the choice of the diffusion coeffcient does not influence consistency of the method at convergence and hence the di?usion coeffcient is essentially a free parameter. The choice of the di?usion coeffcient does, however, affect the convergence behavior of the nonlinear di?usion iterations. Within this work we use Morel’s non-local di?usion coef- ficient in the aforementioned NDA formulation in lieu of the flux weighted inverse of three times the transport cross section. The goal of this paper is to demonstrate that significant en- hancement of the spectral properties of NDA can be achieved in near void regions. For testing the spectral properties of the NDA

A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data

Science.gov (United States)

Chen, Chuanfa; Li, Yanyan; Li, Wei; Dai, Honglei

2013-08-01

We presented a multiresolution hierarchical classification (MHC) algorithm for differentiating ground from non-ground LiDAR point cloud based on point residuals from the interpolated raster surface. MHC includes three levels of hierarchy, with the simultaneous increase of cell resolution and residual threshold from the low to the high level of the hierarchy. At each level, the surface is iteratively interpolated towards the ground using thin plate spline (TPS) until no ground points are classified, and the classified ground points are used to update the surface in the next iteration. 15 groups of benchmark dataset, provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) commission, were used to compare the performance of MHC with those of the 17 other publicized filtering methods. Results indicated that MHC with the average total error and average Cohen’s kappa coefficient of 4.11% and 86.27% performs better than all other filtering methods.

Learning time-dependent noise to reduce logical errors: real time error rate estimation in quantum error correction

Science.gov (United States)

Huo, Ming-Xia; Li, Ying

2017-12-01

Quantum error correction is important to quantum information processing, which allows us to reliably process information encoded in quantum error correction codes. Efficient quantum error correction benefits from the knowledge of error rates. We propose a protocol for monitoring error rates in real time without interrupting the quantum error correction. Any adaptation of the quantum error correction code or its implementation circuit is not required. The protocol can be directly applied to the most advanced quantum error correction techniques, e.g. surface code. A Gaussian processes algorithm is used to estimate and predict error rates based on error correction data in the past. We find that using these estimated error rates, the probability of error correction failures can be significantly reduced by a factor increasing with the code distance.

Hierarchical Sets: Analyzing Pangenome Structure through Scalable Set Visualizations

DEFF Research Database (Denmark)

Pedersen, Thomas Lin

2017-01-01

of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https...

[Study on predicting firmness of watermelon by Vis/NIR diffuse transmittance technique].

Science.gov (United States)

Tian, Hai-Qing; Ying, Yi-Bin; Lu, Hui-Shan; Xu, Hui-Rong; Xie, Li-Juan; Fu, Xia-Ping; Yu, Hai-Yan

2007-06-01

Watermelon is a popular fruit in the world and firmness (FM) is one of the major characteristics used for assessing watermelon quality. The objective of the present research was to study the potential of visible/near Infrared (Vis/NIR) diffuse transmittance spectroscopy as a way for the nondestructive measurement of FM of watermelon. Statistical models between the spectra and FM were developed using partial least square (PLS) and principle component regression (PCR) methods. Performance of different models was assessed in terms of correlation coefficients (r) of validation set of samples and root mean square errors of prediction (RMSEP). Models for three kinds of mathematical treatments of spectra (original, first derivative and second derivative) were established. Savitsky-Goaly filter smoothing method was used for spectra data smoothing. The PLS model of the second derivative spectra gave the best prediction of FM, with a correlation coefficient (r) of 0. 974 and root mean square errors of prediction (RMSEP) of 0. 589 N using Savitsky-Goaly filter smoothing method. The results of this study indicate that NIR diffuse transmittance spectroscopy can be used to predict the FM of watermelon. The Vis/NIR diffuse transmittance technique will be valuable for the nandestructive detection large shape and thick peel fruits'.

What are hierarchical models and how do we analyze them?

Science.gov (United States)

Royle, Andy

2016-01-01

In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood and Bayesian perspectives. We go through the mechanics of maximizing the likelihood and characterizing the posterior distribution by Markov chain Monte Carlo (MCMC) methods. We give a general perspective on topics such as model selection and assessment of model fit, although we demonstrate these topics in practice in later chapters (especially Chapters 5, 6, 7, and 10 Chapter 5 Chapter 6 Chapter 7 Chapter 10)

Facile synthesis and photocatalytic activity of zinc oxide hierarchical microcrystals

KAUST Repository

Xu, Xinjiang

2013-04-04

ZnO microcrystals with hierarchical structure have been synthesized by a simple solvothermal approach. The microcrystals were studied by means of X-ray diffraction, transmission electron microscopy, and scanning electron microscopy. Research on the formation mechanism of the hierarchical microstructure shows that the coordination solvent and precursor concentration have considerable influence on the size and morphology of the microstructures. A possible formation mechanism of the hierarchical structure was suggested. Furthermore, the catalytic activity of the ZnO microcrystals was studied by treating low concentration Rhodamine B (RhB) solution under UV light, and research results show the hierarchical microstructures of ZnO display high catalytic activity in photocatalysis, the catalysis process follows first-order reaction kinetics, and the apparent rate constant k = 0.03195 min-1.

Tiny Molybdenites Tell Diffusion Tales

Science.gov (United States)

Stein, H. J.; Hannah, J. L.

2014-12-01

Diffusion invokes micron-scale exchange during crystal growth and dissolution in magma chambers on short time-scales. Fundamental to interpreting such data are assumptions on magma-fluid dynamics at all scales. Nevertheless, elemental diffusion profiles are used to estimate time scales for magma storage, eruption, and recharge. An underutilized timepiece to evaluate diffusion and 3D mobility of magmatic fluids is high-precision Re-Os dating of molybdenite. With spatially unique molybdenite samples from a young ore system (e.g., 1 Ma) and a double Os spike, analytical errors of 1-3 ka unambiguously separate events in time. Re-Os ages show that hydrous shallow magma chambers locally recharge and expel Cu-Mo-Au-silica as superimposed stockwork vein networks at time scales less than a few thousand years [1]. Re-Os ages provide diffusion rates controlled by a dynamic crystal mush, accumulation and expulsion of metalliferous fluid, and magma reorganization after explosive crystallization events. Importantly, this approach has broad application far from ore deposits. Here, we use Re-Os dating of molybdenite to assess time scales for generating and diffusing metals through the deep crust. To maximize opportunity for chemical diffusion, we use a continental-scale Sveconorwegian mylonite zone for the study area. A geologically constrained suite of molybdenite samples was acquired from quarry exposures. Molybdenite, previously unreported, is extremely scarce. Tiny but telling molybdenites include samples from like occurrences to assure geologic accuracy in Re-Os ages. Ages range from mid-Mesoproterozoic to mid-Neoproterozoic, and correspond to early metamorphic dehydration of a regionally widespread biotite-rich gneiss, localized melting of gneiss to form cm-m-scale K-feldspar ± quartz pods, development of vapor-rich, vuggy mm stringers that serve as volatile collection surfaces in felsic leucosomes, and low-angle (relative to foliation) cross-cutting cm-scale quartz veins

INCORPORATING AMBIPOLAR AND OHMIC DIFFUSION IN THE AMR MHD CODE RAMSES

International Nuclear Information System (INIS)

Masson, J.; Mulet-Marquis, C.; Chabrier, G.; Teyssier, R.; Hennebelle, P.

2012-01-01

We have implemented non-ideal magnetohydrodynamics (MHD) effects in the adaptive mesh refinement code RAMSES, namely, ambipolar diffusion and Ohmic dissipation, as additional source terms in the ideal MHD equations. We describe in details how we have discretized these terms using the adaptive Cartesian mesh, and how the time step is diminished with respect to the ideal case, in order to perform a stable time integration. We have performed a large suite of test runs, featuring the Barenblatt diffusion test, the Ohmic diffusion test, the C-shock test, and the Alfvén wave test. For the latter, we have performed a careful truncation error analysis to estimate the magnitude of the numerical diffusion induced by our Godunov scheme, allowing us to estimate the spatial resolution that is required to address non-ideal MHD effects reliably. We show that our scheme is second-order accurate, and is therefore ideally suited to study non-ideal MHD effects in the context of star formation and molecular cloud dynamics.

Hierarchical decision making for flood risk reduction

DEFF Research Database (Denmark)

Custer, Rocco; Nishijima, Kazuyoshi

2013-01-01

. In current practice, structures are often optimized individually without considering benefits of having a hierarchy of protection structures. It is here argued, that the joint consideration of hierarchically integrated protection structures is beneficial. A hierarchical decision model is utilized to analyze...... and compare the benefit of large upstream protection structures and local downstream protection structures in regard to epistemic uncertainty parameters. Results suggest that epistemic uncertainty influences the outcome of the decision model and that, depending on the magnitude of epistemic uncertainty...

Accuracy analysis of the thermal diffusivity measurement of molten salts by stepwise heating method

International Nuclear Information System (INIS)

Kato, Yoshio; Furukawa, Kazuo

1976-11-01

The stepwise heating method for measuring thermal diffusivity of molten salts is based on the electrical heating of a thin metal plate as a plane heat source in the molten salt. In this method, the following estimations on error are of importance: (1) thickness effect of the metal plate, (2) effective length between the plate and a temperature measuring point and (3) effect of the noise on the temperature rise signal. In this report, a measuring apparatus is proposed and measuring conditions are suggested on the basis of error estimations. The measurements for distilled water and glycerine were made first to test the performance; the results agreed well with standard values. The thermal diffusivities of molten NaNO 3 at 320-380 0 C and of molten Li 2 BeF 4 at 470-700 0 C were measured. (auth.)

Ionothermal synthesis of hierarchical BiOBr microspheres for water treatment

Energy Technology Data Exchange (ETDEWEB)

Zhang, Dieqing [The Education Ministry Key Lab of Resource Chemistry and Shanghai Key Laboratory of Rare Earth Functional Materials, Shanghai Normal University, 100 Guilin Road, Shanghai 200231 (China); Department of Chemistry and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong (China); Wen, Meicheng; Jiang, Bo; Li, Guisheng [The Education Ministry Key Lab of Resource Chemistry and Shanghai Key Laboratory of Rare Earth Functional Materials, Shanghai Normal University, 100 Guilin Road, Shanghai 200231 (China); Yu, Jimmy C., E-mail: jimyu@cuhk.edu.hk [Department of Chemistry and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong (China)

2012-04-15

Graphical abstract: Hierarchical BiOBr microspheres were prepared from a bromine-containing ionic liquid. The material was found effective for removing heavy metals, degrading organic pollutants and killing bacteria. Highlight: Black-Right-Pointing-Pointer Ionothermal synthesis of BiOBr microspheres with hierarchical structure. Black-Right-Pointing-Pointer Efficient mass transfer and excellent light-harvesting ability. Black-Right-Pointing-Pointer Suitable for removing heavy metals and treatment of organic dyes. Black-Right-Pointing-Pointer Remarkable photocatalytic bactericidal property. - Abstract: Bismuth oxybromide (BiOBr) micropsheres with hierarchical morphologies have been fabricated via an ionothermal synthesis route. Ionic liquid acts as a unique soft material capable of promoting nucleation and in situ growth of 3D hierarchical BiOBr mesocrystals without the help of surfactants. The as-prepared BiOBr nanomaterials can effectively remove heavy metal ions and organic dyes from wastewater. They can also kill Micrococcus lylae, a Gram positive bacterium, in water under fluorescent light irradiation. Their high adaptability in water treatment may be ascribed to their hierarchical structure, allowing them high surface to volume ratio, facile species transportation and excellent light-harvesting ability.

Ionothermal synthesis of hierarchical BiOBr microspheres for water treatment

International Nuclear Information System (INIS)

Zhang, Dieqing; Wen, Meicheng; Jiang, Bo; Li, Guisheng; Yu, Jimmy C.

2012-01-01

Graphical abstract: Hierarchical BiOBr microspheres were prepared from a bromine-containing ionic liquid. The material was found effective for removing heavy metals, degrading organic pollutants and killing bacteria. Highlight: ► Ionothermal synthesis of BiOBr microspheres with hierarchical structure. ► Efficient mass transfer and excellent light-harvesting ability. ► Suitable for removing heavy metals and treatment of organic dyes. ► Remarkable photocatalytic bactericidal property. - Abstract: Bismuth oxybromide (BiOBr) micropsheres with hierarchical morphologies have been fabricated via an ionothermal synthesis route. Ionic liquid acts as a unique soft material capable of promoting nucleation and in situ growth of 3D hierarchical BiOBr mesocrystals without the help of surfactants. The as-prepared BiOBr nanomaterials can effectively remove heavy metal ions and organic dyes from wastewater. They can also kill Micrococcus lylae, a Gram positive bacterium, in water under fluorescent light irradiation. Their high adaptability in water treatment may be ascribed to their hierarchical structure, allowing them high surface to volume ratio, facile species transportation and excellent light-harvesting ability.

BiOCl nanowire with hierarchical structure and its Raman features

International Nuclear Information System (INIS)

Tian Ye; Guo Chuanfei; Guo Yanjun; Wang Qi; Liu Qian

2012-01-01

BiOCl is a promising V-VI-VII-compound semiconductor with excellent optical and electrical properties, and has great potential applications in photo-catalysis, photoelectric, etc. We successfully synthesize BiOCl nanowire with a hierarchical structure by combining wet etch (top-down) with liquid phase crystal growth (bottom-up) process, opening a novel method to construct ordered bismuth-based nanostructures. The morphology and lattice structures of Bi nanowires, β-Bi 2 O 3 nanowires and BiOCl nanowires with the hierarchical structure are investigated by scanning electron microscope (SEM) and transition electron microscope (TEM). The formation mechanism of such ordered BiOCl hierarchical structure is considered to mainly originate from the highly preferred growth, which is governed by the lattice match between (1 1 0) facet of BiOCl and (2 2 0) or (0 0 2) facet of β-Bi 2 O 3 . A schematic model is also illustrated to depict the formation process of the ordered BiOCl hierarchical structure. In addition, Raman properties of the BiOCl nanowire with the hierarchical structure are investigated deeply.

A metal-organic framework derived hierarchical nickel-cobalt sulfide nanosheet array on Ni foam with enhanced electrochemical performance for supercapacitors.

Science.gov (United States)

Tao, Kai; Han, Xue; Ma, Qingxiang; Han, Lei

2018-03-06

Metal-organic frameworks (MOFs) have emerged as a new platform for the construction of various functional materials for energy related applications. Here, a facile MOF templating method is developed to fabricate a hierarchical nickel-cobalt sulfide nanosheet array on conductive Ni foam (Ni-Co-S/NF) as a binder-free electrode for supercapacitors. A uniform 2D Co-MOF nanowall array is first grown in situ on Ni foam in aqueous solution at room temperature, and then the Co-MOF nanowalls are converted into hierarchical Ni-Co-S nanoarchitectures via an etching and ion-exchange reaction with Ni(NO 3 ) 2 , and a subsequent solvothermal sulfurization. Taking advantage of the compositional and structural merits of the hierarchical Ni-Co-S nanosheet array and conductive Ni foam, such as fast electron transportation, short ion diffusion path, abundant active sites and rich redox reactions, the obtained Ni-Co-S/NF electrode exhibits excellent electrochemical capacitive performance (1406.9 F g -1 at 0.5 A g -1 , 53.9% retention at 10 A g -1 and 88.6% retention over 1000 cycles), which is superior to control CoS/NF. An asymmetric supercapacitor (ASC) assembled by using the as-fabricated Ni-Co-S/NF as the positive electrode and activated carbon (AC) as the negative electrode delivers a high energy density of 24.8 W h kg -1 at a high power density of 849.5 W kg -1 . Even when the power density is as high as 8.5 kW kg -1 , the ASC still exhibits a high energy density of 12.5 W h kg -1 . This facile synthetic strategy can also be extended to fabricate other hierarchical integrated electrodes for high-efficiency electrochemical energy conversion and storage devices.

A mixed-order nonlinear diffusion compressed sensing MR image reconstruction.

Science.gov (United States)

Joy, Ajin; Paul, Joseph Suresh

2018-03-07

Avoid formation of staircase artifacts in nonlinear diffusion-based MR image reconstruction without compromising computational speed. Whereas second-order diffusion encourages the evolution of pixel neighborhood with uniform intensities, fourth-order diffusion considers smooth region to be not necessarily a uniform intensity region but also a planar region. Therefore, a controlled application of fourth-order diffusivity function is used to encourage second-order diffusion to reconstruct the smooth regions of the image as a plane rather than a group of blocks, while not being strong enough to introduce the undesirable speckle effect. Proposed method is compared with second- and fourth-order nonlinear diffusion reconstruction, total variation (TV), total generalized variation, and higher degree TV using in vivo data sets for different undersampling levels with application to dictionary learning-based reconstruction. It is observed that the proposed technique preserves sharp boundaries in the image while preventing the formation of staircase artifacts in the regions of smoothly varying pixel intensities. It also shows reduced error measures compared with second-order nonlinear diffusion reconstruction or TV and converges faster than TV-based methods. Because nonlinear diffusion is known to be an effective alternative to TV for edge-preserving reconstruction, the crucial aspect of staircase artifact removal is addressed. Reconstruction is found to be stable for the experimentally determined range of fourth-order regularization parameter, and therefore not does not introduce a parameter search. Hence, the computational simplicity of second-order diffusion is retained. © 2018 International Society for Magnetic Resonance in Medicine.

Medication errors: prescribing faults and prescription errors.

Science.gov (United States)

Velo, Giampaolo P; Minuz, Pietro

2009-06-01

1. Medication errors are common in general practice and in hospitals. Both errors in the act of writing (prescription errors) and prescribing faults due to erroneous medical decisions can result in harm to patients. 2. Any step in the prescribing process can generate errors. Slips, lapses, or mistakes are sources of errors, as in unintended omissions in the transcription of drugs. Faults in dose selection, omitted transcription, and poor handwriting are common. 3. Inadequate knowledge or competence and incomplete information about clinical characteristics and previous treatment of individual patients can result in prescribing faults, including the use of potentially inappropriate medications. 4. An unsafe working environment, complex or undefined procedures, and inadequate communication among health-care personnel, particularly between doctors and nurses, have been identified as important underlying factors that contribute to prescription errors and prescribing faults. 5. Active interventions aimed at reducing prescription errors and prescribing faults are strongly recommended. These should be focused on the education and training of prescribers and the use of on-line aids. The complexity of the prescribing procedure should be reduced by introducing automated systems or uniform prescribing charts, in order to avoid transcription and omission errors. Feedback control systems and immediate review of prescriptions, which can be performed with the assistance of a hospital pharmacist, are also helpful. Audits should be performed periodically.

Fractional Diffusion Equations and Anomalous Diffusion

Science.gov (United States)

Evangelista, Luiz Roberto; Kaminski Lenzi, Ervin

2018-01-01

Preface; 1. Mathematical preliminaries; 2. A survey of the fractional calculus; 3. From normal to anomalous diffusion; 4. Fractional diffusion equations: elementary applications; 5. Fractional diffusion equations: surface effects; 6. Fractional nonlinear diffusion equation; 7. Anomalous diffusion: anisotropic case; 8. Fractional Schrödinger equations; 9. Anomalous diffusion and impedance spectroscopy; 10. The Poisson–Nernst–Planck anomalous (PNPA) models; References; Index.

On Utmost Multiplicity of Hierarchical Stellar Systems

Directory of Open Access Journals (Sweden)

Gebrehiwot Y. M.

2016-12-01

Full Text Available According to theoretical considerations, multiplicity of hierarchical stellar systems can reach, depending on masses and orbital parameters, several hundred, while observational data confirm the existence of at most septuple (seven-component systems. In this study, we cross-match the stellar systems of very high multiplicity (six and more components in modern catalogues of visual double and multiple stars to find among them the candidates to hierarchical systems. After cross-matching the catalogues of closer binaries (eclipsing, spectroscopic, etc., some of their components were found to be binary/multiple themselves, what increases the system's degree of multiplicity. Optical pairs, known from literature or filtered by the authors, were flagged and excluded from the statistics. We compiled a list of hierarchical systems with potentially very high multiplicity that contains ten objects. Their multiplicity does not exceed 12, and we discuss a number of ways to explain the lack of extremely high multiplicity systems.

Hierarchical capillary adhesion of microcantilevers or hairs

International Nuclear Information System (INIS)

Liu Jianlin; Feng Xiqiao; Xia Re; Zhao Hongping

2007-01-01

As a result of capillary forces, animal hairs, carbon nanotubes or nanowires of a periodically or randomly distributed array often assemble into hierarchical structures. In this paper, the energy method is adopted to analyse the capillary adhesion of microsized hairs, which are modelled as clamped microcantilevers wetted by liquids. The critical conditions for capillary adhesion of two hairs, three hairs or two bundles of hairs are derived in terms of Young's contact angle, elastic modulus and geometric sizes of the beams. Then, the hierarchical capillary adhesion of hairs is addressed. It is found that for multiple hairs or microcantilevers, the system tends to take a hierarchical structure as a result of the minimization of the total potential energy of the system. The level number of structural hierarchy increases with the increase in the number of hairs if they are sufficiently long. Additionally, we performed experiments to verify our theoretical solutions for the adhesion of microbeams

Numerical Solution of the 1D Advection-Diffusion Equation Using Standard and Nonstandard Finite Difference Schemes

Directory of Open Access Journals (Sweden)

A. R. Appadu

2013-01-01

for which the Reynolds number is 2 or 4. Some errors are computed, namely, the error rate with respect to the L1 norm, dispersion, and dissipation errors. We have both dissipative and dispersive errors, and this indicates that the methods generate artificial dispersion, though the partial differential considered is not dispersive. It is seen that the Lax-Wendroff and NSFD are quite good methods to approximate the 1D advection-diffusion equation at some values of k and h. Two optimisation techniques are then implemented to find the optimal values of k when h=0.02 for the Lax-Wendroff and NSFD schemes, and this is validated by numerical experiments.

Advances in Applications of Hierarchical Bayesian Methods with Hydrological Models

Science.gov (United States)

Alexander, R. B.; Schwarz, G. E.; Boyer, E. W.

2017-12-01

Mechanistic and empirical watershed models are increasingly used to inform water resource decisions. Growing access to historical stream measurements and data from in-situ sensor technologies has increased the need for improved techniques for coupling models with hydrological measurements. Techniques that account for the intrinsic uncertainties of both models and measurements are especially needed. Hierarchical Bayesian methods provide an efficient modeling tool for quantifying model and prediction uncertainties, including those associated with measurements. Hierarchical methods can also be used to explore spatial and temporal variations in model parameters and uncertainties that are informed by hydrological measurements. We used hierarchical Bayesian methods to develop a hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow across diverse environmental and climatic drainages in 18 U.S. hydrological regions. Our application illustrates the use of a new generation of Bayesian methods that offer more advanced computational efficiencies than the prior generation. Evaluations of the effects of hierarchical (regional) variations in model coefficients and uncertainties on model accuracy indicates improved prediction accuracies (median of 10-50%) but primarily in humid eastern regions, where model uncertainties are one-third of those in arid western regions. Generally moderate regional variability is observed for most hierarchical coefficients. Accounting for measurement and structural uncertainties, using hierarchical state-space techniques, revealed the effects of spatially-heterogeneous, latent hydrological processes in the "localized" drainages between calibration sites; this improved model precision, with only minor changes in regional coefficients. Our study can inform advances in the use of hierarchical methods with hydrological models to improve their integration with stream

Recommendation based on trust diffusion model.

Science.gov (United States)

Yuan, Jinfeng; Li, Li

2014-01-01

Recommender system is emerging as a powerful and popular tool for online information relevant to a given user. The traditional recommendation system suffers from the cold start problem and the data sparsity problem. Many methods have been proposed to solve these problems, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the trust diffusion (DiffTrust) algorithm and the probabilistic matrix factorization (PMF). DiffTrust is first used to study the possible diffusions of trust between various users. It is able to make use of the implicit relationship of the trust network, thus alleviating the data sparsity problem. The probabilistic matrix factorization (PMF) is then employed to combine the users' tastes with their trusted friends' interests. We evaluate the algorithm on Flixster, Moviedata, and Epinions datasets, respectively. The experimental results show that the recommendation based on our proposed DiffTrust + PMF model achieves high performance in terms of the root mean square error (RMSE), Recall, and F Measure.

A Hierarchical Dispatch Structure for Distribution Network Pricing

OpenAIRE

Yuan, Zhao; Hesamzadeh, Mohammad Reza

2015-01-01

This paper presents a hierarchical dispatch structure for efficient distribution network pricing. The dispatch coordination problem in the context of hierarchical network operators are addressed. We formulate decentralized generation dispatch into a bilevel optimization problem in which main network operator and the connected distribution network operator optimize their costs in two levels. By using Karush-Kuhn-Tucker conditions and Fortuny-Amat McCarl linearization, the bilevel optimization ...

Rapid and selective detection of acetone using hierarchical ZnO gas sensor for hazardous odor markers application

International Nuclear Information System (INIS)

Jia, Qianqian; Ji, Huiming; Zhang, Ying; Chen, Yalu; Sun, Xiaohong; Jin, Zhengguo

2014-01-01

Highlights: • ZnO spheres fabricated via solvothermal method are with (0 0 2) polar facet exposed. • Response time of ZnO sensor for detecting 100 ppm acetone is as short as 3 s. • R a /R g toward 100 ppm acetone is 33 when operated at 230 °C. • ZnO sensor exhibits good selectivity against other toxic gases and water vapor. • Porous structure and exposure of polar facet contribute to good sensing properties. - Abstract: Hierarchical nanostructured ZnO dandelion-like spheres were synthesized via solvothermal reaction at 200 °C for 4 h. The products were pure hexagonal ZnO with large exposure of (0 0 2) polar facet. Side-heating gas sensor based on hierarchical ZnO spheres was prepared to evaluate the acetone gas sensing properties. The detection limit to acetone for the ZnO sensor is 0.25 ppm. The response (R a /R g ) toward 100 ppm acetone was 33 operated at 230 °C and the response time was as short as 3 s. The sensor exhibited remarkable acetone selectivity with negligible response toward other hazardous gases and water vapor. The high proportion of electron depletion region and oxygen vacancies contributed to high gas response sensitivity. The hollow and porous structure of dandelion-like ZnO spheres facilitated the diffusion of gas molecules, leading to a rapid response speed. The largely exposed (0 0 2) polar facets could adsorb acetone gas molecules easily and efficiently, resulting in a rapid response speed and good selectivity of hierarchical ZnO spheres gas sensor at low operating temperature

Automatic relative RPC image model bias compensation through hierarchical image matching for improving DEM quality

Science.gov (United States)

Noh, Myoung-Jong; Howat, Ian M.

2018-02-01

The quality and efficiency of automated Digital Elevation Model (DEM) extraction from stereoscopic satellite imagery is critically dependent on the accuracy of the sensor model used for co-locating pixels between stereo-pair images. In the absence of ground control or manual tie point selection, errors in the sensor models must be compensated with increased matching search-spaces, increasing both the computation time and the likelihood of spurious matches. Here we present an algorithm for automatically determining and compensating the relative bias in Rational Polynomial Coefficients (RPCs) between stereo-pairs utilizing hierarchical, sub-pixel image matching in object space. We demonstrate the algorithm using a suite of image stereo-pairs from multiple satellites over a range stereo-photogrammetrically challenging polar terrains. Besides providing a validation of the effectiveness of the algorithm for improving DEM quality, experiments with prescribed sensor model errors yield insight into the dependence of DEM characteristics and quality on relative sensor model bias. This algorithm is included in the Surface Extraction through TIN-based Search-space Minimization (SETSM) DEM extraction software package, which is the primary software used for the U.S. National Science Foundation ArcticDEM and Reference Elevation Model of Antarctica (REMA) products.

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches.

Science.gov (United States)

Chowdhury, Rasheda Arman; Lina, Jean Marc; Kobayashi, Eliane; Grova, Christophe

2013-01-01

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm(2) to 30 cm(2), whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches.

Directory of Open Access Journals (Sweden)

Rasheda Arman Chowdhury

Full Text Available Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG or Magneto-EncephaloGraphy (MEG signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i brain activity may be modeled using cortical parcels and (ii brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM and the Hierarchical Bayesian (HB source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm(2 to 30 cm(2, whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

Hierarchical materials: Background and perspectives

DEFF Research Database (Denmark)

2016-01-01

Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

Snake velvet black: Hierarchical micro- and nanostructure enhances dark colouration in Bitis rhinoceros

Science.gov (United States)

Spinner, Marlene; Kovalev, Alexander; Gorb, Stanislav N.; Westhoff, Guido

2013-05-01

The West African Gaboon viper (Bitis rhinoceros) is a master of camouflage due to its colouration pattern. Its skin is geometrically patterned and features black spots that purport an exceptional spatial depth due to their velvety surface texture. Our study shades light on micromorphology, optical characteristics and principles behind such a velvet black appearance. We revealed a unique hierarchical pattern of leaf-like microstructures striated with nanoridges on the snake scales that coincides with the distribution of black colouration. Velvet black sites demonstrate four times lower reflectance and higher absorbance than other scales in the UV - near IR spectral range. The combination of surface structures impeding reflectance and absorbing dark pigments, deposited in the skin material, provides reflecting less than 11% of the light reflected by a polytetrafluoroethylene diffuse reflectance standard in any direction. A view-angle independent black structural colour in snakes is reported here for the first time.

Regularized spherical polar fourier diffusion MRI with optimal dictionary learning.

Science.gov (United States)

Cheng, Jian; Jiang, Tianzi; Deriche, Rachid; Shen, Dinggang; Yap, Pew-Thian

2013-01-01

Compressed Sensing (CS) takes advantage of signal sparsity or compressibility and allows superb signal reconstruction from relatively few measurements. Based on CS theory, a suitable dictionary for sparse representation of the signal is required. In diffusion MRI (dMRI), CS methods proposed for reconstruction of diffusion-weighted signal and the Ensemble Average Propagator (EAP) utilize two kinds of Dictionary Learning (DL) methods: 1) Discrete Representation DL (DR-DL), and 2) Continuous Representation DL (CR-DL). DR-DL is susceptible to numerical inaccuracy owing to interpolation and regridding errors in a discretized q-space. In this paper, we propose a novel CR-DL approach, called Dictionary Learning - Spherical Polar Fourier Imaging (DL-SPFI) for effective compressed-sensing reconstruction of the q-space diffusion-weighted signal and the EAP. In DL-SPFI, a dictionary that sparsifies the signal is learned from the space of continuous Gaussian diffusion signals. The learned dictionary is then adaptively applied to different voxels using a weighted LASSO framework for robust signal reconstruction. Compared with the start-of-the-art CR-DL and DR-DL methods proposed by Merlet et al. and Bilgic et al., respectively, our work offers the following advantages. First, the learned dictionary is proved to be optimal for Gaussian diffusion signals. Second, to our knowledge, this is the first work to learn a voxel-adaptive dictionary. The importance of the adaptive dictionary in EAP reconstruction will be demonstrated theoretically and empirically. Third, optimization in DL-SPFI is only performed in a small subspace resided by the SPF coefficients, as opposed to the q-space approach utilized by Merlet et al. We experimentally evaluated DL-SPFI with respect to L1-norm regularized SPFI (L1-SPFI), which uses the original SPF basis, and the DR-DL method proposed by Bilgic et al. The experiment results on synthetic and real data indicate that the learned dictionary produces

Hierarchical Planning Methodology for a Supply Chain Management

Directory of Open Access Journals (Sweden)

Virna ORTIZ-ARAYA

2012-01-01

Full Text Available Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision–making levels of the planning issues on the time horizon considered. This paper presents a hierarchical approach proposed to a company that produces reusable shopping bags in Chile and Perú, to determine the optimal allocation of resources at the tactical level as well as over the most immediate planning horizon to meet customer demands for the next weeks. Starting from an aggregated production planning model, the aggregated decisions are disaggregated into refined decisions in two levels, using a couple of optimization models that impose appropriate constraints to keep coherence of the plan on the production system. The main features of the hierarchical solution approach are presented.

On the implementation of an accurate and efficient solver for convection-diffusion equations

Science.gov (United States)

Wu, Chin-Tien

In this dissertation, we examine several different aspects of computing the numerical solution of the convection-diffusion equation. The solution of this equation often exhibits sharp gradients due to Dirichlet outflow boundaries or discontinuities in boundary conditions. Because of the singular-perturbed nature of the equation, numerical solutions often have severe oscillations when grid sizes are not small enough to resolve sharp gradients. To overcome such difficulties, the streamline diffusion discretization method can be used to obtain an accurate approximate solution in regions where the solution is smooth. To increase accuracy of the solution in the regions containing layers, adaptive mesh refinement and mesh movement based on a posteriori error estimations can be employed. An error-adapted mesh refinement strategy based on a posteriori error estimations is also proposed to resolve layers. For solving the sparse linear systems that arise from discretization, goemetric multigrid (MG) and algebraic multigrid (AMG) are compared. In addition, both methods are also used as preconditioners for Krylov subspace methods. We derive some convergence results for MG with line Gauss-Seidel smoothers and bilinear interpolation. Finally, while considering adaptive mesh refinement as an integral part of the solution process, it is natural to set a stopping tolerance for the iterative linear solvers on each mesh stage so that the difference between the approximate solution obtained from iterative methods and the finite element solution is bounded by an a posteriori error bound. Here, we present two stopping criteria. The first is based on a residual-type a posteriori error estimator developed by Verfurth. The second is based on an a posteriori error estimator, using local solutions, developed by Kay and Silvester. Our numerical results show the refined mesh obtained from the iterative solution which satisfies the second criteria is similar to the refined mesh obtained from

A multiscale MD–FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure

Science.gov (United States)

Kojic, M.; Milosevic, M.; Kojic, N.; Kim, K.; Ferrari, M.; Ziemys, A.

2014-01-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts. PMID:24578582

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

Science.gov (United States)

Stankov, L

1979-07-01

The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

Diffusion in porous structures containing three fluid phases

International Nuclear Information System (INIS)

Galani, A.N.; Kainourgiakis, M.E.; Stubos, A.K.; Kikkinides, E.S.

2005-01-01

In the present study, the tracer diffusion in porous media filled by three fluid phases (a non-wetting, an intermediate wetting and a wetting phase) is investigated. The disordered porous structure of porous systems like random sphere packing and the North Sea chalk, is represented by three-dimensional binary images. The random sphere pack is generated by a standard ballistic deposition procedure, while the chalk matrix by a stochastic reconstruction technique. Physically sound spatial distributions of the three phases filling the pore space are determined by the use of a simulated annealing algorithm, where those phases are initially randomly distributed in the pore space and trial-and-error swaps are performed in order to attain the global minimum of the total interfacial energy. The acceptance rule for a trial move during the annealing is modified properly improving the efficiency of the technique. The diffusivities of the resulting domains are computed by a random walk method. A parametric study with respect to the pore volume fraction occupied by each fluid phase and the ratio of the diffusivities in the fluid phases is performed. (authors)

Ultrafast Hierarchical OTDM/WDM Network

Directory of Open Access Journals (Sweden)

Hideyuki Sotobayashi

2003-12-01

Full Text Available Ultrafast hierarchical OTDM/WDM network is proposed for the future core-network. We review its enabling technologies: C- and L-wavelength-band generation, OTDM-WDM mutual multiplexing format conversions, and ultrafast OTDM wavelengthband conversions.

Traveling and Pinned Fronts in Bistable Reaction-Diffusion Systems on Networks

Science.gov (United States)

Kouvaris, Nikos E.; Kori, Hiroshi; Mikhailov, Alexander S.

2012-01-01

Traveling fronts and stationary localized patterns in bistable reaction-diffusion systems have been broadly studied for classical continuous media and regular lattices. Analogs of such non-equilibrium patterns are also possible in networks. Here, we consider traveling and stationary patterns in bistable one-component systems on random Erdös-Rényi, scale-free and hierarchical tree networks. As revealed through numerical simulations, traveling fronts exist in network-organized systems. They represent waves of transition from one stable state into another, spreading over the entire network. The fronts can furthermore be pinned, thus forming stationary structures. While pinning of fronts has previously been considered for chains of diffusively coupled bistable elements, the network architecture brings about significant differences. An important role is played by the degree (the number of connections) of a node. For regular trees with a fixed branching factor, the pinning conditions are analytically determined. For large Erdös-Rényi and scale-free networks, the mean-field theory for stationary patterns is constructed. PMID:23028746

Facile fabrication of superhydrophobic surfaces with hierarchical structures.

Science.gov (United States)

Lee, Eunyoung; Lee, Kun-Hong

2018-03-06

Hierarchical structures were fabricated on the surfaces of SUS304 plates using a one-step process of direct microwave irradiation under a carbon dioxide atmosphere. The surface nanostructures were composed of chrome-doped hematite single crystals. Superhydrophobic surfaces with a water contact angle up to 169° were obtained by chemical modification of the hierarchical structures. The samples maintained superhydrophobicity under NaCl solution up to 2 weeks.

Rate estimation in partially observed Markov jump processes with measurement errors

OpenAIRE

Amrein, Michael; Kuensch, Hans R.

2010-01-01

We present a simulation methodology for Bayesian estimation of rate parameters in Markov jump processes arising for example in stochastic kinetic models. To handle the problem of missing components and measurement errors in observed data, we embed the Markov jump process into the framework of a general state space model. We do not use diffusion approximations. Markov chain Monte Carlo and particle filter type algorithms are introduced, which allow sampling from the posterior distribution of t...

Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

Science.gov (United States)

Klauer, Karl Christoph

2010-01-01

Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…

Hierarchically nanostructured hydroxyapatite: hydrothermal synthesis, morphology control, growth mechanism, and biological activity

Directory of Open Access Journals (Sweden)

Ma MG

2012-04-01

Full Text Available Ming-Guo MaInstitute of Biomass Chemistry and Technology, College of Materials Science and Technology, Beijing Forestry University, Beijing, People's Republic of ChinaAbstract: Hierarchically nanosized hydroxyapatite (HA with flower-like structure assembled from nanosheets consisting of nanorod building blocks was successfully synthesized by using CaCl2, NaH2PO4, and potassium sodium tartrate via a hydrothermal method at 200°C for 24 hours. The effects of heating time and heating temperature on the products were investigated. As a chelating ligand and template molecule, the potassium sodium tartrate plays a key role in the formation of hierarchically nanostructured HA. On the basis of experimental results, a possible mechanism based on soft-template and self-assembly was proposed for the formation and growth of the hierarchically nanostructured HA. Cytotoxicity experiments indicated that the hierarchically nanostructured HA had good biocompatibility. It was shown by in-vitro experiments that mesenchymal stem cells could attach to the hierarchically nanostructured HA after being cultured for 48 hours.Objective: The purpose of this study was to develop facile and effective methods for the synthesis of novel hydroxyapatite (HA with hierarchical nanostructures assembled from independent and discrete nanobuilding blocks.Methods: A simple hydrothermal approach was applied to synthesize HA by using CaCl2, NaH2PO4, and potassium sodium tartrate at 200°C for 24 hours. The cell cytotoxicity of the hierarchically nanostructured HA was tested by MTT (3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide assay.Results: HA displayed the flower-like structure assembled from nanosheets consisting of nanorod building blocks. The potassium sodium tartrate was used as a chelating ligand, inducing the formation and self-assembly of HA nanorods. The heating time and heating temperature influenced the aggregation and morphology of HA. The cell viability did

Analysis of a HP-refinement method for solving the neutron transport equation using two error estimators

International Nuclear Information System (INIS)

Fournier, D.; Le Tellier, R.; Suteau, C.; Herbin, R.

2011-01-01

The solution of the time-independent neutron transport equation in a deterministic way invariably consists in the successive discretization of the three variables: energy, angle and space. In the SNATCH solver used in this study, the energy and the angle are respectively discretized with a multigroup approach and the discrete ordinate method. A set of spatial coupled transport equations is obtained and solved using the Discontinuous Galerkin Finite Element Method (DGFEM). Within this method, the spatial domain is decomposed into elements and the solution is approximated by a hierarchical polynomial basis in each one. This approach is time and memory consuming when the mesh becomes fine or the basis order high. To improve the computational time and the memory footprint, adaptive algorithms are proposed. These algorithms are based on an error estimation in each cell. If the error is important in a given region, the mesh has to be refined (h−refinement) or the polynomial basis order increased (p−refinement). This paper is related to the choice between the two types of refinement. Two ways to estimate the error are compared on different benchmarks. Analyzing the differences, a hp−refinement method is proposed and tested. (author)

MR-AFS: a global hierarchical file-system

International Nuclear Information System (INIS)

Reuter, H.

2000-01-01

The next generation of fusion experiments will use object-oriented technology creating the need for world wide sharing of an underlying hierarchical file-system. The Andrew file system (AFS) is a well known and widely spread global distributed file-system. Multiple-resident-AFS (MR-AFS) combines the features of AFS with hierarchical storage management systems. Files in MR-AFS therefore may be migrated on secondary storage, such as roboted tape libraries. MR-AFS is in use at IPP for the current experiments and data originating from super-computer applications. Experiences and scalability issues are discussed

Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

Science.gov (United States)

Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

2017-01-01

The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

Hierarchical wave functions revisited

International Nuclear Information System (INIS)

Li Dingping.

1997-11-01

We study the hierarchical wave functions on a sphere and on a torus. We simplify some wave functions on a sphere or a torus using the analytic properties of wave functions. The open question, the construction of the wave function for quasi electron excitation on a torus, is also solved in this paper. (author)

Total variation regularization for a backward time-fractional diffusion problem

International Nuclear Information System (INIS)

Wang, Liyan; Liu, Jijun

2013-01-01

Consider a two-dimensional backward problem for a time-fractional diffusion process, which can be considered as image de-blurring where the blurring process is assumed to be slow diffusion. In order to avoid the over-smoothing effect for object image with edges and to construct a fast reconstruction scheme, the total variation regularizing term and the data residual error in the frequency domain are coupled to construct the cost functional. The well posedness of this optimization problem is studied. The minimizer is sought approximately using the iteration process for a series of optimization problems with Bregman distance as a penalty term. This iteration reconstruction scheme is essentially a new regularizing scheme with coupling parameter in the cost functional and the iteration stopping times as two regularizing parameters. We give the choice strategy for the regularizing parameters in terms of the noise level of measurement data, which yields the optimal error estimate on the iterative solution. The series optimization problems are solved by alternative iteration with explicit exact solution and therefore the amount of computation is much weakened. Numerical implementations are given to support our theoretical analysis on the convergence rate and to show the significant reconstruction improvements. (paper)

Hierarchically nanostructured hydroxyapatite: hydrothermal synthesis, morphology control, growth mechanism, and biological activity

Science.gov (United States)

Ma, Ming-Guo

2012-01-01

Hierarchically nanosized hydroxyapatite (HA) with flower-like structure assembled from nanosheets consisting of nanorod building blocks was successfully synthesized by using CaCl2, NaH2PO4, and potassium sodium tartrate via a hydrothermal method at 200°C for 24 hours. The effects of heating time and heating temperature on the products were investigated. As a chelating ligand and template molecule, the potassium sodium tartrate plays a key role in the formation of hierarchically nanostructured HA. On the basis of experimental results, a possible mechanism based on soft-template and self-assembly was proposed for the formation and growth of the hierarchically nanostructured HA. Cytotoxicity experiments indicated that the hierarchically nanostructured HA had good biocompatibility. It was shown by in-vitro experiments that mesenchymal stem cells could attach to the hierarchically nanostructured HA after being cultured for 48 hours. Objective The purpose of this study was to develop facile and effective methods for the synthesis of novel hydroxyapatite (HA) with hierarchical nanostructures assembled from independent and discrete nanobuilding blocks. Methods A simple hydrothermal approach was applied to synthesize HA by using CaCl2, NaH2PO4, and potassium sodium tartrate at 200°C for 24 hours. The cell cytotoxicity of the hierarchically nanostructured HA was tested by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Results HA displayed the flower-like structure assembled from nanosheets consisting of nanorod building blocks. The potassium sodium tartrate was used as a chelating ligand, inducing the formation and self-assembly of HA nanorods. The heating time and heating temperature influenced the aggregation and morphology of HA. The cell viability did not decrease with the increasing concentration of hierarchically nanostructured HA added. Conclusion A novel, simple and reliable hydrothermal route had been developed for the synthesis of

Hierarchical partial order ranking

International Nuclear Information System (INIS)

Carlsen, Lars

2008-01-01

Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

Hierarchical control of a nuclear reactor using uncertain dynamics techniques

International Nuclear Information System (INIS)

Rovere, L.A.; Otaduy, P.J.; Brittain, C.R.; Perez, R.B.

1988-01-01

Recent advances in the nonlinear optimal control area are opening new possibilities towards its implementation in process control. Algorithms for multivariate control, hierarchical decomposition, parameter tracking, model uncertainties actuator saturation effects and physical limits to state variables can be implemented on the basis of a consistent mathematical formulation. In this paper, good agreement is shown between a centralized and a hierarchical implementation of a controller for a hypothetical nuclear power plant subject to multiple demands. The performance of the hierarchical distributed system in the presence of localized subsystem failures is analyzed. 4 refs., 13 figs

Analytical and numerical studies of creation probabilities of hierarchical trees

Directory of Open Access Journals (Sweden)

S.S. Borysov

2011-03-01

Full Text Available We consider the creation conditions of diverse hierarchical trees both analytically and numerically. A connection between the probabilities to create hierarchical levels and the probability to associate these levels into a united structure is studied. We argue that a consistent probabilistic picture requires the use of deformed algebra. Our consideration is based on the study of the main types of hierarchical trees, among which both regular and degenerate ones are studied analytically, while the creation probabilities of Fibonacci, scale-free and arbitrary trees are determined numerically.

Hierarchical drivers of reef-fish metacommunity structure.

Science.gov (United States)

MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P

2009-01-01

Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at

Prediction of diffuse solar irradiance using machine learning and multivariable regression

International Nuclear Information System (INIS)

Lou, Siwei; Li, Danny H.W.; Lam, Joseph C.; Chan, Wilco W.H.

2016-01-01

Highlights: • 54.9% of the annual global irradiance is composed by its diffuse part in HK. • Hourly diffuse irradiance was predicted by accessible variables. • The importance of variable in prediction was assessed by machine learning. • Simple prediction equations were developed with the knowledge of variable importance. - Abstract: The paper studies the horizontal global, direct-beam and sky-diffuse solar irradiance data measured in Hong Kong from 2008 to 2013. A machine learning algorithm was employed to predict the horizontal sky-diffuse irradiance and conduct sensitivity analysis for the meteorological variables. Apart from the clearness index (horizontal global/extra atmospheric solar irradiance), we found that predictors including solar altitude, air temperature, cloud cover and visibility are also important in predicting the diffuse component. The mean absolute error (MAE) of the logistic regression using the aforementioned predictors was less than 21.5 W/m"2 and 30 W/m"2 for Hong Kong and Denver, USA, respectively. With the systematic recording of the five variables for more than 35 years, the proposed model would be appropriate to estimate of long-term diffuse solar radiation, study climate change and develope typical meteorological year in Hong Kong and places with similar climates.

Efficient analysis of macromolecular rotational diffusion from heteronuclear relaxation data

International Nuclear Information System (INIS)

Dosset, Patrice; Hus, Jean-Christophe; Blackledge, Martin; Marion, Dominique

2000-01-01

A novel program has been developed for the interpretation of 15 N relaxation rates in terms of macromolecular anisotropic rotational diffusion. The program is based on a highly efficient simulated annealing/minimization algorithm, designed specifically to search the parametric space described by the isotropic, axially symmetric and fully anisotropic rotational diffusion tensor models. The high efficiency of this algorithm allows extensive noise-based Monte Carlo error analysis. Relevant statistical tests are systematically applied to provide confidence limits for the proposed tensorial models. The program is illustrated here using the example of the cytochrome c' from Rhodobacter capsulatus, a four-helix bundle heme protein, for which data at three different field strengths were independently analysed and compared

Disparity Map Generation from Illumination Variant Stereo Images Using Efficient Hierarchical Dynamic Programming

Directory of Open Access Journals (Sweden)

Viral H. Borisagar

2014-01-01

Full Text Available A novel hierarchical stereo matching algorithm is presented which gives disparity map as output from illumination variant stereo pair. Illumination difference between two stereo images can lead to undesirable output. Stereo image pair often experience illumination variations due to many factors like real and practical situation, spatially and temporally separated camera positions, environmental illumination fluctuation, and the change in the strength or position of the light sources. Window matching and dynamic programming techniques are employed for disparity map estimation. Good quality disparity map is obtained with the optimized path. Homomorphic filtering is used as a preprocessing step to lessen illumination variation between the stereo images. Anisotropic diffusion is used to refine disparity map to give high quality disparity map as a final output. The robust performance of the proposed approach is suitable for real life circumstances where there will be always illumination variation between the images. The matching is carried out in a sequence of images representing the same scene, however in different resolutions. The hierarchical approach adopted decreases the computation time of the stereo matching problem. This algorithm can be helpful in applications like robot navigation, extraction of information from aerial surveys, 3D scene reconstruction, and military and security applications. Similarity measure SAD is often sensitive to illumination variation. It produces unacceptable disparity map results for illumination variant left and right images. Experimental results show that our proposed algorithm produces quality disparity maps for both wide range of illumination variant and invariant stereo image pair.

A Fully Discrete Galerkin Method for a Nonlinear Space-Fractional Diffusion Equation

Directory of Open Access Journals (Sweden)

Yunying Zheng

2011-01-01

Full Text Available The spatial transport process in fractal media is generally anomalous. The space-fractional advection-diffusion equation can be used to characterize such a process. In this paper, a fully discrete scheme is given for a type of nonlinear space-fractional anomalous advection-diffusion equation. In the spatial direction, we use the finite element method, and in the temporal direction, we use the modified Crank-Nicolson approximation. Here the fractional derivative indicates the Caputo derivative. The error estimate for the fully discrete scheme is derived. And the numerical examples are also included which are in line with the theoretical analysis.

Mathematical modelling of pasta dough dynamic viscosity, thermal conductivity and diffusivity

Directory of Open Access Journals (Sweden)

Andrei Ionuţ SIMION

2015-08-01

Full Text Available This work aimed to study the mathematical variation of three main thermodynamic properties (dynamic viscosity, thermal conductivity and thermal diffusivity of pasta dough obtained by mixing wheat semolina and water with dough humidity and deformation speed (for dynamic viscosity, respectively with dough humidity and temperature (for thermal diffusivity and conductivity. The realized regression analysis of existing graphical data led to the development of mathematical models with a high degree of accuracy. The employed statistical tests (least squares, relative error and analysis of variance revealed that the obtained equations are able to describe and predict the tendency of the dough thermodynamic properties.

Comparison of Experimental Methods for Estimating Matrix Diffusion Coefficients for Contaminant Transport Modeling

Energy Technology Data Exchange (ETDEWEB)

Telfeyan, Katherine Christina [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ware, Stuart Douglas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reimus, Paul William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Birdsell, Kay Hanson [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-06

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

Science.gov (United States)

Telfeyan, Katherine; Ware, S. Doug; Reimus, Paul W.; Birdsell, Kay H.

2018-02-01

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

Science.gov (United States)

Nitta, Tohru

2017-10-01

We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

Challenge and Error: Critical Events and Attention-Related Errors

Science.gov (United States)

Cheyne, James Allan; Carriere, Jonathan S. A.; Solman, Grayden J. F.; Smilek, Daniel

2011-01-01

Attention lapses resulting from reactivity to task challenges and their consequences constitute a pervasive factor affecting everyday performance errors and accidents. A bidirectional model of attention lapses (error [image omitted] attention-lapse: Cheyne, Solman, Carriere, & Smilek, 2009) argues that errors beget errors by generating attention…

Hierarchically structured materials for lithium batteries

International Nuclear Information System (INIS)

Xiao, Jie; Zheng, Jianming; Li, Xiaolin; Shao, Yuyan; Zhang, Ji-Guang

2013-01-01

The lithium-ion battery (LIB) is one of the most promising power sources to be deployed in electric vehicles, including solely battery powered vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. With the increasing demand for devices of high-energy densities (>500 Wh kg −1 ), new energy storage systems, such as lithium–oxygen (Li–O 2 ) batteries and other emerging systems beyond the conventional LIB, have attracted worldwide interest for both transportation and grid energy storage applications in recent years. It is well known that the electrochemical performance of these energy storage systems depends not only on the composition of the materials, but also on the structure of the electrode materials used in the batteries. Although the desired performance characteristics of batteries often have conflicting requirements with the micro/nano-structure of electrodes, hierarchically designed electrodes can be tailored to satisfy these conflicting requirements. This work will review hierarchically structured materials that have been successfully used in LIB and Li–O 2 batteries. Our goal is to elucidate (1) how to realize the full potential of energy materials through the manipulation of morphologies, and (2) how the hierarchical structure benefits the charge transport, promotes the interfacial properties and prolongs the electrode stability and battery lifetime. (paper)

Hierarchically structured graphene-carbon nanotube-cobalt hybrid electrocatalyst for seawater battery

Science.gov (United States)

Suh, Dong Hoon; Park, Sul Ki; Nakhanivej, Puritut; Kim, Youngsik; Hwang, Soo Min; Park, Ho Seok

2017-12-01

The design of cost-effective and highly active catalysts is a critical challenge. Inspired by the strong points of stability and conductivity of carbon nanotubes (CNTs), high catalytic activity of Co nanoparticles, and rapid ion diffusion and large accessible area of three-dimensional (3D) graphene, we demonstrate a novel strategy to construct a hierarchical hybrid structure consisting of Co/CoOx nanoparticles-incorporated CNT branches onto the 3D reduced graphene oxide (rGO) architecture. The surface-modified 3D rGO by steam activation process has a large surface area and abundant defect sites, which serve as active sites to uniformly grow Co/CoOx nanoparticles. Furthermore, the CNTs preserve their performance stably by encapsulating Co nanoparticles, while the uniformly decorated Co/CoOx nanoparticles exhibit superior electrocatalytic activity toward oxygen evolution/reduction reaction due to highly exposed active sites. Employing the hybrid particle electrocatalyst, the seawater battery operates stably at 0.01 mA cm-2 during 50 cycles, owing to the good electrocatalytic ability.

A general solution in the cylindrical coordinates system for the diffusion of a radionuclide in homogeneous and isotropic solids

CERN Document Server

Ribeiro, F B

1999-01-01

Solutions of the diffusion equation in cylindrical coordinates are presented for a radionuclide produced by the decay of a not diffusing parent isotope with arbitrary activity distribution. General initial and Dirichlet boundary conditions are considered and the diffusion equation is solved for a finite cylinder. Solutions corresponding to two particular boundary conditions that can be imposed in laboratory diffusion coefficient measurements are presented. An analysis of the speed of convergence and of the series truncation error is done for these particular solutions. An example of the escape to production ratio derived from one of the solutions is also presented.