Physical properties and structure of fine core-shell particles used as packing materials for chromatography Relationships between particle characteristics and column performance.

Science.gov (United States)

Gritti, Fabrice; Leonardis, Irene; Abia, Jude; Guiochon, Georges

2010-06-11

The recent development of new brands of packing materials made of fine porous-shell particles, e.g., Halo and Kinetex, has brought great improvements in potential column efficiency, demanding considerable progress in the design of chromatographic instruments. Columns packed with Halo and Kinetex particles provide minimum values of their reduced plate heights of nearly 1.5 and 1.2, respectively. These packing materials have physical properties that set them apart from conventional porous particles. The kinetic performance of 4.6mm I.D. columns packed with these two new materials is analyzed based on the results of a series of nine independent and complementary experiments: low-temperature nitrogen adsorption (LTNA), scanning electron microscopy (SEM), inverse size-exclusion chromatography (ISEC), Coulter counter particle size distributions, pycnometry, height equivalent to a theoretical plate (HETP), peak parking method (PP), total pore blocking method (TPB), and local electrochemical detection across the column exit section (LED). The results of this work establish links between the physical properties of these superficially porous particles and the excellent kinetic performance of columns packed with them. It clarifies the fundamental origin of the difference in the chromatographic performances of the Halo and the Kinetex columns. Copyright 2010 Elsevier B.V. All rights reserved.

Reference book for design of valve packings, sealing high temperature water

International Nuclear Information System (INIS)

Doubt, G.L.

1976-01-01

Mockups of stuffing boxes for valves in the 1/4 to 1 in. (0.6-2.54cm) pipe size range and ASA 900 and up pressure class were tested to determine how temperature, stuffing box dimensions, packing compressive stress and stem surface finish affect water leak rate, packing friction torque and packing volume loss (creep). One brand of wire-reinforced asbestos braid on graphite-and-asbestos core packing was used in all tests. The theory of leakage through porous media was reviewed with emphasis on application to packed stuffing boxes, and a mathematical framework for relating leakage and packing friction to stuffing box dimensions and compressive stress was developed. The tests gave empirical relationships (1) for leak rate vs temperature, packing compressive stress, stem diameter and packing size, (2) for packing friction torque vs the above variables and (3) for packing creep vs temperature and stress. Packing stress affected leakage far more than any other variable, the leak rate being inversely proportional to stress to the 7.3 power at a packing temperature of 350 deg F (175 deg C). Factors which increase packing compression (density) have a strong reducing effect on leakage and a moderate to zero effect on packing friction torque. Surface finish had no visible effect on leakage, torque or creep. Empirical results and theory have been combined to show how stuffing boxes can be designed for a given leakage rate. Suggestions for decreasing leakage from existing high temperature stuffing boxes are included. (author)

Simulation of turbulent flow in a packed bed

Energy Technology Data Exchange (ETDEWEB)

Guo, B.; Yu, A. [Centre for Simulation and Modelling of Particulate Systems and School of Material Science and Engineering, The University of New South Wales, Sydney 2052 (Australia); Wright, B.; Zulli, P. [BlueScope Steel Research Laboratories, P.O. Box 202, Port Kembla, NSW 2505 (Australia)

2006-05-15

Numerous models for simulating the flow and transport in packed beds have been proposed in the literature with few reported applications. In this paper, several turbulence models for porous media are applied to the gas flow through a randomly packed bed and are examined by means of a parametric study against some published experimental data. These models predict widely different turbulent eddy viscosity. The analysis also indicates that deficiencies exist in the formulation of some model equations and selection of a suitable turbulence model is important. With this realization, residence time distribution and velocity distribution are then simulated by considering a radial profile of porosity and turbulence induced dispersion, and the results are in good agreement with the available experimental data. (Abstract Copyright [2006], Wiley Periodicals, Inc.)

Method for immobilizing particulate materials in a packed bed

Science.gov (United States)

Even, Jr., William R.; Guthrie, Stephen E.; Raber, Thomas N.; Wally, Karl; Whinnery, LeRoy L.; Zifer, Thomas

1999-01-01

The present invention pertains generally to immobilizing particulate matter contained in a "packed" bed reactor so as to prevent powder migration, compaction, coalescence, or the like. More specifically, this invention relates to a technique for immobilizing particulate materials using a microporous foam-like polymer such that a) the particulate retains its essential chemical nature, b) the local movement of the particulate particles is not unduly restricted, c) bulk powder migration and is prevented, d) physical and chemical access to the particulate is unchanged over time, and e) very high particulate densities are achieved. The immobilized bed of the present invention comprises a vessel for holding particulate matter, inlet and an outlet ports or fittings, a loosely packed bed of particulate material contained within the vessel, and a three dimensional porous matrix for surrounding and confining the particles thereby fixing the movement of individual particle to a limited local position. The established matrix is composed of a series of cells or chambers comprising walls surrounding void space, each wall forming the wall of an adjacent cell; each wall containing many holes penetrating through the wall yielding an overall porous structure and allowing useful levels of gas transport.

Model's sparse representation based on reduced mixed GMsFE basis methods

Energy Technology Data Exchange (ETDEWEB)

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn [Institute of Mathematics, Hunan University, Changsha 410082 (China); Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn [College of Mathematics and Econometrics, Hunan University, Changsha 410082 (China)

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in

SparseM: A Sparse Matrix Package for R *

Directory of Open Access Journals (Sweden)

Roger Koenker

2003-02-01

Full Text Available SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the package is illustrated by a family of linear model fitting functions that implement least squares methods for problems with sparse design matrices. Significant performance improvements in memory utilization and computational speed are possible for applications involving large sparse matrices.

The influence of bamboo-packed configuration to mixing characteristics in a fixed-bed reactor

Science.gov (United States)

Detalina, M.; Pradanawati, S. A.; Widyarani; Mamat; Nilawati, D.; Sintawardani, N.

2018-03-01

Fixed-bed reactors are commonly used as bioreactors for various applications, including chemicals production and organic wastewater treatment. Bioreactors are fixed with packing materials for attaching microorganisms. Packing materials should have high surface area and enable sufficient fluid flow in the reactor. Natural materials e.g. rocks and fibres are often used as packing materials. Commercially, packing materials are also produced from polymer with the advantage of customizable shapes. The objective of this research was to study the mixing pattern in a packed-bed reactor using bamboo as packing material. Bamboo was selected for its pipe-like and porous form, as well as its abundant availability in Indonesia. The cut bamboo sticks were installed in a reactor in different configurations namely vertical, horizontal, and random. Textile dye was used as a tracer. Our results show that the vertical configuration gave the least liquid resistant flow. Yet, the random configuration was the best configuration during mixing process.

High-performance supercapacitors based on hierarchically porous graphite particles

Energy Technology Data Exchange (ETDEWEB)

Chen, Zheng; Wen, Jing; Yan, Chunzhu; Rice, Lynn; Sohn, Hiesang; Lu, Yunfeng [Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA 90095 (United States); Shen, Meiqing [School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072 (China); Cai, Mei [General Motor R and D Center, Warren, MI 48090 (United States); Dunn, Bruce [Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095 (United States)

2011-07-15

Hierarchically porous graphite particles are synthesized using a continuous, scalable aerosol approach. The unique porous graphite architecture provides the particles with high surface area, fast ion transportation, and good electronic conductivity, which endows the resulting supercapacitors with high energy and power densities. This work provides a new material platform for high-performance supercapacitors with high packing density, and is adaptable to battery electrodes, fuel-cell catalyst supports, and other applications. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Comparison of NMR simulations of porous media derived from analytical and voxelized representations.

Science.gov (United States)

Jin, Guodong; Torres-Verdín, Carlos; Toumelin, Emmanuel

2009-10-01

We develop and compare two formulations of the random-walk method, grain-based and voxel-based, to simulate the nuclear-magnetic-resonance (NMR) response of fluids contained in various models of porous media. The grain-based approach uses a spherical grain pack as input, where the solid surface is analytically defined without an approximation. In the voxel-based approach, the input is a computer-tomography or computer-generated image of reconstructed porous media. Implementation of the two approaches is largely the same, except for the representation of porous media. For comparison, both approaches are applied to various analytical and digitized models of porous media: isolated spherical pore, simple cubic packing of spheres, and random packings of monodisperse and polydisperse spheres. We find that spin magnetization decays much faster in the digitized models than in their analytical counterparts. The difference in decay rate relates to the overestimation of surface area due to the discretization of the sample; it cannot be eliminated even if the voxel size decreases. However, once considering the effect of surface-area increase in the simulation of surface relaxation, good quantitative agreement is found between the two approaches. Different grain or pore shapes entail different rates of increase of surface area, whereupon we emphasize that the value of the "surface-area-corrected" coefficient may not be universal. Using an example of X-ray-CT image of Fontainebleau rock sample, we show that voxel size has a significant effect on the calculated surface area and, therefore, on the numerically simulated magnetization response.

Retardation characteristics of radionuclides in geologic media through batch and packed column experiments

International Nuclear Information System (INIS)

Park, Hun Hwee; Han, Kyung Won; Han, Pil Soo; Lee, Jae Owan; Park, Chung Kyun; Yang, Ho Yeon

1988-03-01

Batch and packed column experiments are performed to investigate the retardation characteristics of radionuclide,i.e, Cs-137 in geologic media. In batch experiment, the effects of important parameters on the sorption of radionuclide in geologic media, such as nuclide concentration, pH, and particle size are examined. The Kd value obtained from breakthrough curve was compared with that from the batch sorption experiment to investigate the applicability of the Kd value from batch experiment to prediction of radionuclide migration in dynamic flow through porous media. The proposed model of radionuclide migration in porous media is also verified using the experimental results. (Author)

Application of aerobic porous fixed packed towers for biological treatment of canned food industrial wastewater; Utilizacion de la arcilla expandida como relleno en lechos sumergidos aireados para el tratamiento de aguas residuales procedentes de la industria conservera

Energy Technology Data Exchange (ETDEWEB)

Garrido Escudero, A.; Torres Rojo, J. C.; Tejera de Torres, M.; Hontaria, E.; Osorio Robles, F.; Sabater Redondo, C.

2005-07-01

The main objective is to check the performance of aerobic porous fixed packed towers technology heavy COD duty in canned food industrial wastewater among the Murcia Region (South East Spain). The porous media used was an expanded clay manufactured by Optiroc-Filtralite with grain sizes form 2-5 mm and 3-7 mm. Waste water used for experiments was a COD content of 4.300 mg/l. A pilot plants was built to treat wastewater flows from 101/h to 80 l/h. The volumetric loads checked were from 7 to 140 COD kg/m''3/day. Different tower configurations were tested. Process was designed with different steps (up to 8 different). The results obtained in the phase with better yields shows to a mean performance of 83.05% for COD elimination. The obtained results indicated clearly the feasibility of the treatment for the application of aerobic porous fixed packet with expanded clay media for these heavy duty waste water. (Author) 11 refs.

Computational fluid dynamics (CFD) using porous media modeling predicts recurrence after coiling of cerebral aneurysms.

Science.gov (United States)

Umeda, Yasuyuki; Ishida, Fujimaro; Tsuji, Masanori; Furukawa, Kazuhiro; Shiba, Masato; Yasuda, Ryuta; Toma, Naoki; Sakaida, Hiroshi; Suzuki, Hidenori

2017-01-01

This study aimed to predict recurrence after coil embolization of unruptured cerebral aneurysms with computational fluid dynamics (CFD) using porous media modeling (porous media CFD). A total of 37 unruptured cerebral aneurysms treated with coiling were analyzed using follow-up angiograms, simulated CFD prior to coiling (control CFD), and porous media CFD. Coiled aneurysms were classified into stable or recurrence groups according to follow-up angiogram findings. Morphological parameters, coil packing density, and hemodynamic variables were evaluated for their correlations with aneurysmal recurrence. We also calculated residual flow volumes (RFVs), a novel hemodynamic parameter used to quantify the residual aneurysm volume after simulated coiling, which has a mean fluid domain > 1.0 cm/s. Follow-up angiograms showed 24 aneurysms in the stable group and 13 in the recurrence group. Mann-Whitney U test demonstrated that maximum size, dome volume, neck width, neck area, and coil packing density were significantly different between the two groups (P CFD and larger RFVs in the porous media CFD. Multivariate logistic regression analyses demonstrated that RFV was the only independently significant factor (odds ratio, 1.06; 95% confidence interval, 1.01-1.11; P = 0.016). The study findings suggest that RFV collected under porous media modeling predicts the recurrence of coiled aneurysms.

Measuring adsorption, diffusion and flow in chemical engineering: applications of magnetic resonance to porous media

International Nuclear Information System (INIS)

Gladden, Lynn F; Mitchell, Jonathan

2011-01-01

Magnetic resonance (MR) techniques are increasingly used to improve our understanding of the multi-component, multi-phase processes encountered in chemical engineering. This review brings together many of the MR techniques used, and often developed specifically, to study chemical engineering systems and, in particular, processes occurring within porous media. Pulse sequences for relaxometry, pulsed field gradient measurements of diffusion, imaging and velocimetry measurements are described. Recent applications of these MR pulse sequences to microporous, mesoporous and macroporous structures are then reviewed. Considering the microporous and mesoporous systems, we focus attention on studies of rock cores, manufactured materials such as cement and gypsum plaster, and catalysts. When considering macroporous structures, the transport through packed beds of particles typical of fixed-bed catalytic reactors is reviewed; a brief overview of the increasing research interest in gas-solid fluidized beds is also presented. We highlight the field of sparse k-space sampling as an area that is in its infancy and suggest that, combined with Bayesian methods, it will offer new opportunities in both extending the application of high-field MR techniques to chemical engineering and increasing the range of measurements that can be carried out using low-field hardware.

Semi-supervised sparse coding

KAUST Repository

Wang, Jim Jing-Yan; Gao, Xin

2014-01-01

Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled. By using the manifold structure spanned by the data set of both labeled and unlabeled samples and the constraints provided by the labels of the labeled samples, we learn the variable class labels for all the samples. Furthermore, to improve the discriminative ability of the learned sparse codes, we assume that the class labels could be predicted from the sparse codes directly using a linear classifier. By solving the codebook, sparse codes, class labels and classifier parameters simultaneously in a unified objective function, we develop a semi-supervised sparse coding algorithm. Experiments on two real-world pattern recognition problems demonstrate the advantage of the proposed methods over supervised sparse coding methods on partially labeled data sets.

Semi-supervised sparse coding

KAUST Repository

Wang, Jim Jing-Yan

2014-07-06

Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled. By using the manifold structure spanned by the data set of both labeled and unlabeled samples and the constraints provided by the labels of the labeled samples, we learn the variable class labels for all the samples. Furthermore, to improve the discriminative ability of the learned sparse codes, we assume that the class labels could be predicted from the sparse codes directly using a linear classifier. By solving the codebook, sparse codes, class labels and classifier parameters simultaneously in a unified objective function, we develop a semi-supervised sparse coding algorithm. Experiments on two real-world pattern recognition problems demonstrate the advantage of the proposed methods over supervised sparse coding methods on partially labeled data sets.

In Defense of Sparse Tracking: Circulant Sparse Tracker

KAUST Repository

Zhang, Tianzhu; Bibi, Adel Aamer; Ghanem, Bernard

2016-01-01

Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework. However, most sparse representation based trackers have high computational cost, less than promising tracking performance, and limited feature representation. To deal with the above issues, we propose a novel circulant sparse tracker (CST), which exploits circulant target templates. Because of the circulant structure property, CST has the following advantages: (1) It can refine and reduce particles using circular shifts of target templates. (2) The optimization can be efficiently solved entirely in the Fourier domain. (3) High dimensional features can be embedded into CST to significantly improve tracking performance without sacrificing much computation time. Both qualitative and quantitative evaluations on challenging benchmark sequences demonstrate that CST performs better than all other sparse trackers and favorably against state-of-the-art methods.

In Defense of Sparse Tracking: Circulant Sparse Tracker

KAUST Repository

Zhang, Tianzhu

2016-12-13

Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework. However, most sparse representation based trackers have high computational cost, less than promising tracking performance, and limited feature representation. To deal with the above issues, we propose a novel circulant sparse tracker (CST), which exploits circulant target templates. Because of the circulant structure property, CST has the following advantages: (1) It can refine and reduce particles using circular shifts of target templates. (2) The optimization can be efficiently solved entirely in the Fourier domain. (3) High dimensional features can be embedded into CST to significantly improve tracking performance without sacrificing much computation time. Both qualitative and quantitative evaluations on challenging benchmark sequences demonstrate that CST performs better than all other sparse trackers and favorably against state-of-the-art methods.

A new affinity-HPLC packing for protein separation: Cibacron blue attached uniform porous poly(HEMA-co-EDM) beads.

Science.gov (United States)

Unsal, Ender; Durdu, Aysun; Elmas, Begum; Tuncel, Murvet; Tuncel, Ali

2005-11-01

In this study, a new affinity high-performance liquid chromatography (HPLC) stationary phase suitable for protein separation was synthesized. In the first stage of the synthesis, uniform porous poly(2-hydroxyethyl methacrylate-co-ethylene dimethacrylate), poly(HEMA-co-EDM), beads 6.2 mum in size were obtained. Homogeneous distribution of hydroxyl groups in the bead interior was confirmed by confocal laser scanning microscopy. The plain poly(HEMA-co-EDM) particles gave very low non-specific protein adsorption with albumin. The selected dye ligand Cibacron blue F3G-A (CB F3G-A) was covalently linked onto the beads via hydroxyl groups. In the batch experiments, albumin adsorption up to 60 mg BSA/g particles was obtained with the CB F3G-A carrying poly(HEMA-co-EDM) beads. The affinity-HPLC of selected proteins (albumin and lysozyme) was investigated in a 25 mm x 4.0-mm inner diameter column packed with CB F3G-A carrying beads and both proteins were successfully resolved. By a single injection, 200 mug of protein was loaded and quantitatively eluted from the column. The protein recovery increased with increasing flow rate and salt concentration of the elution buffer and decreased with the increasing protein feed concentration. During the albumin elution, theoretical plate numbers up to 30,000 plates/m were achieved by increasing the salt concentration.

Process for the exchange of hydrogen isotopes using a catalyst packed bed assembly

International Nuclear Information System (INIS)

Butler, J.P.; den Hartog, J.; Molson, F.W.R.

1978-01-01

A process for the exchange of hydrogen isotopes between streams of gaseous hydrogen and liquid water is described, wherein the streams of liquid water and gaseous hydrogen are simultaneously brought into contact with one another and a catalyst packed bed assembly while at a temperature in the range 273 0 to 573 0 K. The catalyst packed bed assembly may be composed of discrete carrier bodies of e.g. ceramics, metals, fibrous materials or synthetic plastics with catalytically active metal crystallites selected from Group VIII of the Periodic Table, partially enclosed in and bonded to the carrier bodies by a water repellent, water vapor and hydrogen gas permeable, porous, polymeric material, and discrete packing bodies having an exterior surface which is substantially hydrophilic and relatively noncatalytically active with regard to hydrogen isotope exchange between hydrogen gas and water vapor to that of the catalyst bodies

Effects of specific surface area and porosity on cube counting fractal dimension, lacunarity, configurational entropy, and permeability of model porous networks: Random packing simulations and NMR micro-imaging study

Science.gov (United States)

Lee, Bum Han; Lee, Sung Keun

2013-07-01

Despite the importance of understanding and quantifying the microstructure of porous networks in diverse geologic settings, the effects of the specific surface area and porosity on the key structural parameters of the networks have not been fully understood. We performed cube-counting fractal dimension (Dcc) and lacunarity analyses of 3D porous networks of model sands and configurational entropy analysis of 2D cross sections of model sands using random packing simulations and nuclear magnetic resonance (NMR) micro-imaging. We established relationships among porosity, specific surface area, structural parameters (Dcc and lacunarity), and the corresponding macroscopic properties (configurational entropy and permeability). The Dcc of the 3D porous networks increases with increasing specific surface area at a constant porosity and with increasing porosity at a constant specific surface area. Predictive relationships correlating Dcc, specific surface area, and porosity were also obtained. The lacunarity at the minimum box size decreases with increasing porosity, and that at the intermediate box size (∼0.469 mm in the current model sands) was reproduced well with specific surface area. The maximum configurational entropy increases with increasing porosity, and the entropy length of the pores decreases with increasing specific surface area and was used to calculate the average connectivity among the pores. The correlation among porosity, specific surface area, and permeability is consistent with the prediction from the Kozeny-Carman equation. From the relationship between the permeability and the Dcc of pores, the permeability can be expressed as a function of the Dcc of pores and porosity. The current methods and these newly identified correlations among structural parameters and properties provide improved insights into the nature of porous media and have useful geophysical and hydrological implications for elasticity and shear viscosity of complex composites of rock

Homotopic non-local regularized reconstruction from sparse positron emission tomography measurements

International Nuclear Information System (INIS)

Wong, Alexander; Liu, Chenyi; Wang, Xiao Yu; Fieguth, Paul; Bie, Hongxia

2015-01-01

Positron emission tomography scanners collect measurements of a patient’s in vivo radiotracer distribution. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radionuclide (tracer), which is introduced into the body on a biologically active molecule, and the tomograms must be reconstructed from projections. The reconstruction of tomograms from the acquired PET data is an inverse problem that requires regularization. The use of tightly packed discrete detector rings, although improves signal-to-noise ratio, are often associated with high costs of positron emission tomography systems. Thus a sparse reconstruction, which would be capable of overcoming the noise effect while allowing for a reduced number of detectors, would have a great deal to offer. In this study, we introduce and investigate the potential of a homotopic non-local regularization reconstruction framework for effectively reconstructing positron emission tomograms from such sparse measurements. Results obtained using the proposed approach are compared with traditional filtered back-projection as well as expectation maximization reconstruction with total variation regularization. A new reconstruction method was developed for the purpose of improving the quality of positron emission tomography reconstruction from sparse measurements. We illustrate that promising reconstruction performance can be achieved for the proposed approach even at low sampling fractions, which allows for the use of significantly fewer detectors and have the potential to reduce scanner costs

Lattice Boltzmann simulations for wall-flow dynamics in porous ceramic diesel particulate filters

Science.gov (United States)

Lee, Da Young; Lee, Gi Wook; Yoon, Kyu; Chun, Byoungjin; Jung, Hyun Wook

2018-01-01

Flows through porous filter walls of wall-flow diesel particulate filter are investigated using the lattice Boltzmann method (LBM). The microscopic model of the realistic filter wall is represented by randomly overlapped arrays of solid spheres. The LB simulation results are first validated by comparison to those from previous hydrodynamic theories and constitutive models for flows in porous media with simple regular and random solid-wall configurations. We demonstrate that the newly designed randomly overlapped array structures of porous walls allow reliable and accurate simulations for the porous wall-flow dynamics in a wide range of solid volume fractions from 0.01 to about 0.8, which is beyond the maximum random packing limit of 0.625. The permeable performance of porous media is scrutinized by changing the solid volume fraction and particle Reynolds number using Darcy's law and Forchheimer's extension in the laminar flow region.

Nasal packing with ventilated nasal packs; a comparison with traditional vaseline nasal pack

International Nuclear Information System (INIS)

Alam, J.; Siddiqui, M.W.; Abbas, A.; Sami, M.; Ayub, Z.

2017-01-01

To compare the benefits of ventilated nasal packing with traditional vaseline guaze nasal packing. Study Design: Randomized controlled trial. Place and Duration of Study: This study was conducted at CMH Multan, from Jun 2014 to Dec 2014. Material and Methods: In this study, sample size of 80 patients was calculated using WHO calculator. Patients were divided in two groups using lottery method endotracheal tube and piece of surgical glove filled with ribbon guaze was utilized for fabricated ventilated nasal pack and compared with traditional nasal packs. Nasal obstruction and sleep disturbance were studied at eight hours and twenty-four hours following surgery using visual analog scale. Results: Mean nasal obstruction with ventilated nasal pack was 45.62 +- 6.17 and with Vaseline nasal pack was 77.67 +- 4.85 which was statistically significant (p=0.001) in both the groups. Mean sleep disturbance in both the groups was 46.32 +- 5.23 and 68.75 +- 2.70 respectively which was statistically significant (p=0.001) in both the groups. Conclusion: Patients with ventilated nasal packs were found to have better tolerance to nasal packs due to less nasal obstruction and sleep disturbance

Thermal-hydraulic modeling of porous bed reactors

International Nuclear Information System (INIS)

Araj, K.J.; Nourbakhsh, H.P.

1987-01-01

Optimum design of nuclear reactor core requires an iterative approach between the thermal-hydraulic, neutronic and operational analysis. This paper concentrates on the thermal-hydraulic behavior of a hydrogen cooled, small particle bed reactor (PBR). The PBR core, modeled here, consists of a hexagonal array of fuel elements embedded in a moderator matrix. The fuel elements are annular packed beds of fuel particles held between two porous cylindrical frits. These particles, 500 to 600 μm in diameter, have a uranium carbide core, which is coated by two layers of graphite and an outer coating of zirconium carbide. Coolant flow, radially inward, from the cold frit through the packed bed and hot frit and axially out the channel, formed by the hot frit, to a common plenum. 5 refs., 1 fig., 2 tabs

Cumulative effects of using pin fin heat sink and porous metal foam on thermal management of lithium-ion batteries

International Nuclear Information System (INIS)

Mohammadian, Shahabeddin K.; Zhang, Yuwen

2017-01-01

Highlights: • 3D transient thermal analysis of a pouch Li-ion cell has been carried out. • Using pin fin heat sink improves the temperature reduction at low pumping powers. • Using pin fin heat sink enhances the temperature uniformity at low air flow rates. • Porous aluminum foam insertion with pin fins improves temperature reduction. • Porous aluminum foam insertion with pin fins enhances temperature uniformity. - Abstract: Three-dimensional transient thermal analysis of an air-cooled module was carried out to investigate cumulative effects of using pin fin heat sink and porous metal foam on thermal management of a Li-ion (lithium-ion) battery pack. Five different cases were designed as Case 1: flow channel without any pin fin or porous metal foam insertion, Case 2: flow channel with aluminum pin fins, Case 3: flow channel with porous aluminum foam pin fins, Case 4: fully inserted flow channel with porous aluminum foam, and Case 5: fully inserted flow channel with porous aluminum foam and aluminum pin fins. The effects of porous aluminum insertions, pin fin types, air flow inlet temperature, and air flow inlet velocity on the temperature uniformity and maximum temperature inside the battery pack were systematically investigated. The results showed that using pin fin heat sink (Case 2) is appropriate only for low air flow velocities. In addition, the use of porous aluminum pin fins or embedding porous aluminum foam inside the air flow channel (Cases 3 and 4) are not beneficial for thermal management improvement. The combination of aluminum pin fins and porous aluminum foam insertion inside the air flow channel (Case 5) is a proper option that improves both temperature reduction and temperature uniformity inside the battery cell.

To Pack or Not to Pack? A Randomized Trial of Vaginal Packing After Vaginal Reconstructive Surgery.

Science.gov (United States)

Westermann, Lauren B; Crisp, Catrina C; Oakley, Susan H; Mazloomdoost, Donna; Kleeman, Steven D; Benbouajili, Janine M; Ghodsi, Vivian; Pauls, Rachel N

2016-01-01

Placement of vaginal packing after pelvic reconstructive surgery is common; however, little evidence exists to support the practice. Furthermore, patients have reported discomfort from the packs. We describe pain and satisfaction in women treated with and without vaginal packing. This institutional review board-approved randomized-controlled trial enrolled patients undergoing vaginal hysterectomy with prolapse repairs. The primary outcome was visual analog scales (VASs) for pain on postoperative day 1. Allocation to "packing" ("P") or "no-packing" ("NP") arms occurred intraoperatively at the end of surgery. Visual analog scales regarding pain and satisfaction were completed early on postoperative day 1 before packing removal. Visual analog scale scores for pain, satisfaction, and bother attributable to packing were recorded before discharge. All packing and perineal pads were weighed to calculate a "postoperative vaginal blood loss." Perioperative data were collected from the hospital record. Our sample size estimation required 74 subjects. Ninety-three women were enrolled. After exclusions, 77 were randomized (P, 37; NP, 40). No differences were found in surgical information, hemoglobin levels, or narcotic use between groups. However, "postoperative vaginal blood loss" was greater in packed subjects (P discharge (P, 35.0 vs NP, 40.0; P = 0.43] were not significantly different between treatment arms. Likewise, VAS scores for satisfaction before removal of packing (P, 81.0 vs NP, 90.0; P = 0.08] and before discharge (P, 90.0 vs NP, 90.5; P = 0.60] were not significantly different. Packed patients noted lower nursing verbal pain scores (P = 0.04) and used less ketorolac (P = 0.01). Bother from packing was low overall. Although there was no difference based on VAS, women receiving vaginal packing had lower nursing documented pain and used less ketorolac than packed women. Vaginal packing may provide benefit and can remain part of the surgical practice.

Infill Optimization for Additive Manufacturing-Approaching Bone-Like Porous Structures.

Science.gov (United States)

Wu, Jun; Aage, Niels; Westermann, Rudiger; Sigmund, Ole

2018-02-01

Porous structures such as trabecular bone are widely seen in nature. These structures are lightweight and exhibit strong mechanical properties. In this paper, we present a method to generate bone-like porous structures as lightweight infill for additive manufacturing. Our method builds upon and extends voxel-wise topology optimization. In particular, for the purpose of generating sparse yet stable structures distributed in the interior of a given shape, we propose upper bounds on the localized material volume in the proximity of each voxel in the design domain. We then aggregate the local per-voxel constraints by their p-norm into an equivalent global constraint, in order to facilitate an efficient optimization process. Implemented on a high-resolution topology optimization framework, our results demonstrate mechanically optimized, detailed porous structures which mimic those found in nature. We further show variants of the optimized structures subject to different design specifications, and we analyze the optimality and robustness of the obtained structures.

Structural Sparse Tracking

KAUST Repository

Zhang, Tianzhu

2015-06-01

Sparse representation has been applied to visual tracking by finding the best target candidate with minimal reconstruction error by use of target templates. However, most sparse representation based trackers only consider holistic or local representations and do not make full use of the intrinsic structure among and inside target candidates, thereby making the representation less effective when similar objects appear or under occlusion. In this paper, we propose a novel Structural Sparse Tracking (SST) algorithm, which not only exploits the intrinsic relationship among target candidates and their local patches to learn their sparse representations jointly, but also preserves the spatial layout structure among the local patches inside each target candidate. We show that our SST algorithm accommodates most existing sparse trackers with the respective merits. Both qualitative and quantitative evaluations on challenging benchmark image sequences demonstrate that the proposed SST algorithm performs favorably against several state-of-the-art methods.

Freezing process in unsaturated packed beds; Fuhowa ryushi sonai ni okeru suibun toketsu

Energy Technology Data Exchange (ETDEWEB)

Akahori, M; Aoki, K; Hattori, M [Nagaoka University of Technology, Niigata (Japan); Tani, T [Oji Paper Co. Ltd., Tokyo (Japan)

1998-04-25

The freezing process in unsaturated packed beds has been investigated experimentally and theoretically. Water transport to the frozen front plays an important part on freezing. The rate of the absorption of water into frozen layer depended on the freezing heat flux and the water saturation at the freezing front. As a result, ice content in the frozen layer was related to the rate of the absorption of water and the freezing heat flux. A one-dimensional freezing model in unsaturated packed beds has been presented, accounting for the water transport. The predicted water saturation and temperature distributions in the body and the thickness of frozen layer were compared with the experimental results using a porous bed composed of glass beads. 12 refs., 10 figs., 1 tab.

Twinning in fcc lattice creates low-coordinated catalytically active sites in porous gold

Energy Technology Data Exchange (ETDEWEB)

Krajčí, Marian [Institute of Physics, Slovak Academy of Sciences, Dúbravská cesta 9, SK-84511 Bratislava (Slovakia); Kameoka, Satoshi; Tsai, An-Pang [Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, Sendai 980-8577 (Japan)

2016-08-28

We describe a new mechanism for creation of catalytically active sites in porous gold. Samples of porous gold prepared by de-alloying Al{sub 2}Au exhibit a clear correlation between the catalytic reactivity towards CO oxidation and structural defects in the fcc lattice of Au. We have found that on the stepped (211) surfaces quite common twin boundary defects in the bulk structure of porous gold can form long close-packed rows of atoms with the coordination number CN = 6. DFT calculations confirm that on these low-coordinated Au sites dioxygen chemisorbs and CO oxidation can proceed via the Langmuir–Hinshelwood mechanism with the activation energy of 37 kJ/mol or via the CO–OO intermediate with the energy barrier of 19 kJ/mol. The existence of the twins in porous gold is stabilized by the surface energy.

Characterising gas behaviour during gas-liquid co-current up-flow in packed beds using magnetic resonance imaging

OpenAIRE

Collins, James HP; Sederman, Andrew John; Gladden, Lynn Faith; Afeworki, Mobae; Kushnerick, J Douglas; Thomann, Hans

2016-01-01

Magnetic resonance (MR) imaging techniques have been used to study gas phase dynamics during co-current up-flow in a column of inner diameter 43 mm, packed with spherical non-porous elements of diameters of 1.8, 3 and 5 mm. MR measurements of gas hold-up, bubble-size distribution, and bubble-rise velocities were made as a function of flow rate and packing size. Gas and liquid flow rates were studied in the range of 20–250 cm3 s−1 and 0–200 cm3 min−1, respectively. The gas hold-up within the b...

Porous structure analysis of large-scale randomly packed pebble bed in high temperature gas-cooled reactor

Energy Technology Data Exchange (ETDEWEB)

Ren, Cheng; Yang, Xingtuan; Liu, Zhiyong; Sun, Yanfei; Jiang, Shengyao [Tsinghua Univ., Beijing (China). Key Laboratory of Advanced Reactor Engineering and Safety; Li, Congxin [Ministry of Environmental Protection of the People' s Republic of China, Beijing (China). Nuclear and Radiation Safety Center

2015-02-15

A three-dimensional pebble bed corresponding to the randomly packed bed in the heat transfer test facility built for the High Temperature Reactor Pebble bed Modules (HTR-PM) in Shandong Shidaowan is simulated via discrete element method. Based on the simulation, we make a detailed analysis on the packing structure of the pebble bed from several aspects, such as transverse section image, longitudinal section image, radial and axial porosity distributions, two-dimensional porosity distribution and coordination number distribution. The calculation results show that radial distribution of porosity is uniform in the center and oscillates near the wall; axial distribution of porosity oscillates near the bottom and linearly varies along height due to effect of gravity; the average coordination number is about seven and equals to the maximum coordination number frequency. The fully established three-dimensional packing structure analysis of the pebble bed in this work is of fundamental significance to understand the flow and heat transfer characteristics throughout the pebble-bed type structure.

A CFD model for biomass combustion in a packed bed furnace

Energy Technology Data Exchange (ETDEWEB)

Karim, Md. Rezwanul [Faculty of Science, Engineering and Technology, Swinburne University of Technology, VIC 3122 (Australia); Department of Mechanical & Chemical Engineering, Islamic University of Technology, Gazipur 1704 (Bangladesh); Ovi, Ifat Rabbil Qudrat [Department of Mechanical & Chemical Engineering, Islamic University of Technology, Gazipur 1704 (Bangladesh); Naser, Jamal, E-mail: jnaser@swin.edu.au [Faculty of Science, Engineering and Technology, Swinburne University of Technology, VIC 3122 (Australia)

2016-07-12

Climate change has now become an important issue which is affecting environment and people around the world. Global warming is the main reason of climate change which is increasing day by day due to the growing demand of energy in developed countries. Use of renewable energy is now an established technique to decrease the adverse effect of global warming. Biomass is a widely accessible renewable energy source which reduces CO{sub 2} emissions for producing thermal energy or electricity. But the combustion of biomass is complex due its large variations and physical structures. Packed bed or fixed bed combustion is the most common method for the energy conversion of biomass. Experimental investigation of packed bed biomass combustion is difficult as the data collection inside the bed is challenging. CFD simulation of these combustion systems can be helpful to investigate different operational conditions and to evaluate the local values inside the investigation area. Available CFD codes can model the gas phase combustion but it can’t model the solid phase of biomass conversion. In this work, a complete three-dimensional CFD model is presented for numerical investigation of packed bed biomass combustion. The model describes the solid phase along with the interface between solid and gas phase. It also includes the bed shrinkage due to the continuous movement of the bed during solid fuel combustion. Several variables are employed to represent different parameters of solid mass. Packed bed is considered as a porous bed and User Defined Functions (UDFs) platform is used to introduce solid phase user defined variables in the CFD. Modified standard discrete transfer radiation method (DTRM) is applied to model the radiation heat transfer. Preliminary results of gas phase velocity and pressure drop over packed bed have been shown. The model can be useful for investigation of movement of the packed bed during solid fuel combustion.

Light scattering in porous materials: Geometrical optics and stereological approach

International Nuclear Information System (INIS)

Malinka, Aleksey V.

2014-01-01

Porous material has been considered from the point of view of stereology (geometrical statistics), as a two-phase random mixture of solid material and air. Considered are the materials having the refractive index with the real part that differs notably from unit and the imaginary part much less than unit. Light scattering in such materials has been described using geometrical optics. These two – the geometrical optics laws and the stereological approach – allow one to obtain the inherent optical properties of such a porous material, which are basic in the radiative transfer theory: the photon survival probability, the scattering phase function, and the polarization properties (Mueller matrix). In this work these characteristics are expressed through the refractive index of the material and the random chord length distribution. The obtained results are compared with the traditional approach, modeling the porous material as a pack of particles of different shapes. - Highlights: • Porous material has been considered from the point of view of stereology. • Properties of a two-phase random mixture of solid material and air are considered. • Light scattering in such materials has been described using geometrical optics. • The inherent optical properties of such a porous material have been obtained

Local description of the energy transfer process in a packed bed heat exchanger

International Nuclear Information System (INIS)

Costa, M.L.M.; Sampaio, R.; Gama, R.M.S. da.

1990-01-01

The energy transfer process in a packed-bed heat exchanger, in counter0flow arrangement is considered. The phenomenon is described through a Continuum Theory of Mixtures approach, in which fluid and solid (porous matrix) are regarded as continuous constituents possessing, each one, its own temperature and velocity fields. The heat 'exchangers consists of two channels, separated by an impermeable wall without thermal resistence, in which there exists a saturated flow. Some particular cases are simulated. (author)

Longitudinal dispersion coefficient depending on superficial velocity of hydrogen isotopes flowing in column packed with zeolite pellets at 77.4 K

Energy Technology Data Exchange (ETDEWEB)

Kotoh, K. [Faculty of Engineering, Kyushu University, Nishi-ku, Fukuoka (Japan); Graduate School of Engineering, Kyushu University, Nishi-ku, Fukuoka (Japan); Kubo, K.; Takashima, S.; Moriyama, S.T. [Graduate School of Engineering, Kyushu University, Nishi-ku, Fukuoka (Japan); Tanaka, M. [National Institute for Fusion Science, Oroshi-cho, Toki, Gifu (Japan); Sugiyama, T. [Faculty of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya (Japan)

2015-03-15

Authors have been developing a cryogenic pressure swing adsorption system for hydrogen isotope separation. In the problem of its design and operation, it is necessary to predict the concentration profiles developing in packed beds of adsorbent pellets. The profiling is affected by the longitudinal dispersion of gas flowing in packed beds, in addition to the mass transfer resistance in porous media of adsorbent pellets. In this work, an equation is derived for estimating the packed-bed dispersion coefficient of hydrogen isotopes, by analyzing the breakthrough curves of trace D{sub 2} or HD replacing H{sub 2} adsorbed in synthetic zeolite particles packed columns at the liquefied nitrogen temperature 77.4 K. Since specialized for hydrogen isotopes, this equation can be considered to estimate the dispersion coefficients more reliable for the cryogenic hydrogen isotope adsorption process, than the existing equations. (authors)

Experimental study of gas–liquid two-phase flow through packed bed under natural circulation conditions

International Nuclear Information System (INIS)

Chen, Shao-Wen; Miwa, Shuichiro; Griffiths, Matt

2016-01-01

Dry-out phenomena in packed beds or porous media may cause a significant digression of cooling/reaction performance in heat transfer/chemical reactor systems. One of the phenomena responsible for the dry-out in packed beds is known as the counter-current flow limitation (CCFL). In order to investigate the CCFL phenomena induced by gas–liquid two-phase flow in packed beds inside a pool, a natural circulation packed bed test facility was designed and constructed. A total of 27 experimental conditions covering various packing media sizes (sphere diameters: 3.0, 6.4 and 9.5 mm), packed bed heights (15, 35 and 50 cm) and water level heights (1.0, 1.5 and 2.0 m) were tested to examine the CCFL criteria with adiabatic air–water two-phase flow under natural circulation conditions. Both CCFL and flow reversal phenomena were observed, and the experimental data including instantaneous and time-averaged void fraction, differential pressure and superficial gas–liquid velocities were collected. The CCFL criteria were determined when periodical oscillations of void fraction and differential pressure appear. In addition, the Wallis correlation for CCFL was utilized for data analysis, and the Wallis coefficient, C, was determined experimentally from the packed bed CCFL tests. Compared to the existing data-sets in literature, the higher C values obtained in the present experiment suggest a possibly higher dry-out heat flux for natural circulation debris systems, which may be due to the water supply from both top and bottom surfaces of the packed beds. Considering the effects of bed height and hydraulic diameter of the packing media, a newly developed model for the Wallis coefficient, C, under natural circulation CCFL is presented. The present model can predict the experimental data with an averaged absolute error of ±7.9%. (author)

Adsorption of zinc ions on bone char using helical coil-packed bed columns and its mass transfer modeling

DEFF Research Database (Denmark)

Moreno-Pérez, J.; Bonilla-Petriciolet, A.; Rojas-Mayorga, C. K.

2016-01-01

This study reports the assessment of helical coil-packed bed columns for Zn2+ adsorption on bone char. Zn2+ adsorption breakthrough curves have been obtained using helical coil columns with different characteristics and a comparison has been conducted with respect to the results of straight fixed-bed...... columns. Results showed that the helical coil adsorption columns may offer an equivalent removal performance than that obtained for the traditional packed bed columns but using a compact structure. However, the coil diameter, number of turns, and feed flow appear to be crucial parameters for obtaining...... the best performance in this packed-bed geometry. A mass transfer model for a mobile fluid flowing through a porous media was used for fitting and predicting the Zn2+ breakthrough curves in helical coil bed columns. Results of adsorbent physicochemical characterization showed that Zn2+ adsorption on bone...

Micropore engineering of carbonized porous aromatic framework (PAF-1) for supercapacitors application.

Science.gov (United States)

Li, Yanqiang; Roy, Soumyajit; Ben, Teng; Xu, Shixian; Qiu, Shilun

2014-07-07

Micropore engineering of porous carbons on the effect of capacitance was explored using a carbonized porous aromatic framework (PAF-1). The porous carbons obtained through different carbonization methods show different pore structures enabling us to do this. The capacitance was measured both in aqueous electrolyte and different organic electrolytes. The porous carbons prepared by KOH activation show both high microporous volume, which is beneficial for charge storage, and mesoporous volume, which is devoted to fast ion diffusion in the pores; properties which are highly desirable. It shows a capacitance as high as 280 F g(-1) and 203 F g(-1) at a current density of 1 A g(-1) in 6.0 M KOH and 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMImTFSI), respectively. We also demonstrate the effect of diffusion and that of geometric packing of the electrolyte ions in the pores, where a commensurate match of the electrolyte ions with the pores of carbonized materials control and influence significantly the capacitance of these materials.

Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint

Directory of Open Access Journals (Sweden)

Zhi Gao

2018-05-01

Full Text Available Light detection and ranging (LiDAR sensors have been widely deployed on intelligent systems such as unmanned ground vehicles (UGVs and unmanned aerial vehicles (UAVs to perform localization, obstacle detection, and navigation tasks. Thus, research into range data processing with competitive performance in terms of both accuracy and efficiency has attracted increasing attention. Sparse coding has revolutionized signal processing and led to state-of-the-art performance in a variety of applications. However, dictionary learning, which plays the central role in sparse coding techniques, is computationally demanding, resulting in its limited applicability in real-time systems. In this study, we propose sparse coding algorithms with a fixed pre-learned ridge dictionary to realize range data denoising via leveraging the regularity of laser range measurements in man-made environments. Experiments on both synthesized data and real data demonstrate that our method obtains accuracy comparable to that of sophisticated sparse coding methods, but with much higher computational efficiency.

Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint.

Science.gov (United States)

Gao, Zhi; Lao, Mingjie; Sang, Yongsheng; Wen, Fei; Ramesh, Bharath; Zhai, Ruifang

2018-05-06

Light detection and ranging (LiDAR) sensors have been widely deployed on intelligent systems such as unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) to perform localization, obstacle detection, and navigation tasks. Thus, research into range data processing with competitive performance in terms of both accuracy and efficiency has attracted increasing attention. Sparse coding has revolutionized signal processing and led to state-of-the-art performance in a variety of applications. However, dictionary learning, which plays the central role in sparse coding techniques, is computationally demanding, resulting in its limited applicability in real-time systems. In this study, we propose sparse coding algorithms with a fixed pre-learned ridge dictionary to realize range data denoising via leveraging the regularity of laser range measurements in man-made environments. Experiments on both synthesized data and real data demonstrate that our method obtains accuracy comparable to that of sophisticated sparse coding methods, but with much higher computational efficiency.

When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

KAUST Repository

Wang, Jim Jing-Yan

2017-06-28

Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been considered separately, assuming that data coding and ranking are two independent and irrelevant problems. However, is there any internal relationship between sparse coding and ranking score learning? If yes, how to explore and make use of this internal relationship? In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm. To explore the local distribution in the sparse code space, and also to bridge coding and ranking problems, we assume that in the neighborhood of each data point, the ranking scores can be approximated from the corresponding sparse codes by a local linear function. By considering the local approximation error of ranking scores, the reconstruction error and sparsity of sparse coding, and the query information provided by the user, we construct a unified objective function for learning of sparse codes, the dictionary and ranking scores. We further develop an iterative algorithm to solve this optimization problem.

Investigation of mixing enhancement in porous media under helical flow conditions: 3-D bench-scale experiments

DEFF Research Database (Denmark)

Chiogna, Gabriele; Ye, Yu; Cirpka, Olaf A.

2017-01-01

us to quantify spreading and dilution of the solute plumes at the outlet cross section. Moreover, we collected direct evidence of plume spiraling and visual proof of helical flow by freezing and slicing the porous medium at different cross sections and observing the dye-tracer distribution. Model...... performed steady-state conservative tracer experiments in a fully three-dimensional flow-through chamber to investigate the effects of helical flow on plume spiraling and deformation, as well as on its dilution [4]. Helical flow was created by packing the porous medium in angled stripes of materials...

Humic acid transport in saturated porous media: influence of flow velocity and influent concentration.

Science.gov (United States)

Wei, Xiaorong; Shao, Mingan; Du, Lina; Horton, Robert

2014-12-01

Understanding the transport of humic acids (HAs) in porous media can provide important and practical evidence needed for accurate prediction of organic/inorganic contaminant transport in different environmental media and interfaces. A series of column transport experiments was conducted to evaluate the transport of HA in different porous media at different flow velocities and influent HA concentrations. Low flow velocity and influent concentration were found to favor the adsorption and deposition of HA onto sand grains packed into columns and to give higher equilibrium distribution coefficients and deposition rate coefficients, which resulted in an increased fraction of HA being retained in columns. Consequently, retardation factors were increased and the transport of HA through the columns was delayed. These results suggest that the transport of HA in porous media is primarily controlled by the attachment of HA to the solid matrix. Accordingly, this attachment should be considered in studies of HA behavior in porous media. Copyright © 2014. Published by Elsevier B.V.

Using crosslinkable diacetylene phospholipids to construct two-dimensional packed beds in supported lipid bilayer separation platforms

Directory of Open Access Journals (Sweden)

Shu-Kai Hu, Sheng-Wen Hsiao, Hsun-Yen Mao, Ya-Ming Chen, Yung Chang and Ling Chao

2013-01-01

Full Text Available Separating and purifying cell membrane-associated biomolecules has been a challenge owing to their amphiphilic property. Taking these species out of their native lipid membrane environment usually results in biomolecule degradation. One of the new directions is to use supported lipid bilayer (SLB platforms to separate the membrane species while they are protected in their native environment. Here we used a type of crosslinkable diacetylene phospholipids, diynePC (1,2-bis(10,12-tricosadiynoyl-sn-glycero-3-phosphocholine, as a packed material to create a 'two-dimensional (2D packed bed' in a SLB platform. After the diynePC SLB is exposed to UV light, some of the diynePC lipids in the SLB can crosslink and the non-crosslinked monomer lipids can be washed away, leaving a 2D porous solid matrix. We incorporated the lipid vesicle deposition method with a microfluidic device to pattern the location of the packed-bed region and the feed region with species to be separated in a SLB platform. Our atomic force microscopy result shows that the nano-scaled structure density of the '2D packed bed' can be tuned by the UV dose applied to the diynePC membrane. When the model membrane biomolecules were forced to transport through the packed-bed region, their concentration front velocities were found to decrease linearly with the UV dose, indicating the successful creation of packed obstacles in these 2D lipid membrane separation platforms.

Waste-to-resource preparation of a porous ceramic membrane support featuring elongated mullite whiskers with enhanced porosity and permeance

NARCIS (Netherlands)

Zhu, Li; Dong, Yingchao; Hampshire, Stuart; Cerneaux, Sophie; Winnubst, Aloysius J.A.

2015-01-01

Different from traditional particle packing structure, a porous structure of ceramic membrane support was fabricated, featuring elongated mullitewhiskers with enhanced porosity, permeance and sufficient mechanical strength. The effect of additives (MoO3and AlF3) and sintering procedureon open

Biomass plug development and propagation in porous media.

Science.gov (United States)

Stewart, T L; Fogler, H S

2001-02-05

Exopolymer-producing bacteria can be used to modify soil profiles for enhanced oil recovery or bioremediation. Understanding the mechanisms associated with biomass plug development and propagation is needed for successful application of this technology. These mechanisms were determined from packed-bed and micromodel experiments that simulate plugging in porous media. Leuconostoc mesenteroides was used, because production of dextran, a water-insoluble exopolymer, can be controlled by using different carbon sources. As dextran was produced, the pressure drop across the porous media increased and began to oscillate. Three pressure phases were identified under exopolymer-producing conditions: the exopolymer-induction phase, the plugging phase, and the plug-propagation phase. The exopolymer-induction phase extended from the time that exopolymer-producing conditions were induced until there was a measurable increase in pressure drop across the porous media. The plugging phase extended from the first increase in pressure drop until a maximum pressure drop was reached. Changes in pressure drop in these two phases were directly related to biomass distribution. Specifically, flow channels within the porous media filled with biomass creating a plugged region where convective flow occurred only in water channels within the biofilm. These water channels were more restrictive to flow causing the pressure drop to increase. At a maximum pressure drop across the porous media, the biomass yielded much like a Bingham plastic, and a flow channel was formed. This behavior marked the onset of the plug-propagation phase which was characterized by sequential development and breakthrough of biomass plugs. This development and breakthrough propagated the biomass plug in the direction of nutrient flow. The dominant mechanism associated with all three phases of plugging in porous media was exopolymer production; yield stress is an additional mechanism in the plug-propagation phase. Copyright

Tunable random packings

International Nuclear Information System (INIS)

Lumay, G; Vandewalle, N

2007-01-01

We present an experimental protocol that allows one to tune the packing fraction η of a random pile of ferromagnetic spheres from a value close to the lower limit of random loose packing η RLP ≅0.56 to the upper limit of random close packing η RCP ≅0.64. This broad range of packing fraction values is obtained under normal gravity in air, by adjusting a magnetic cohesion between the grains during the formation of the pile. Attractive and repulsive magnetic interactions are found to affect stongly the internal structure and the stability of sphere packing. After the formation of the pile, the induced cohesion is decreased continuously along a linear decreasing ramp. The controlled collapse of the pile is found to generate various and reproducible values of the random packing fraction η

Novel porous fly-ash containing geopolymer monoliths for lead adsorption from wastewaters

Energy Technology Data Exchange (ETDEWEB)

Novais, Rui M., E-mail: ruimnovais@ua.pt; Buruberri, L.H.; Seabra, M.P.; Labrincha, J.A.

2016-11-15

Highlights: • Porous fly ash containing-geopolymer monoliths for lead adsorption were developed. • Geopolymers’ porosity and pH of the ion solution controls the adsorption capacity. • Lead adsorption by the geopolymer monoliths up to 6.34 mg/g was observed. • These novel adsorbents can be used in packed beds that are easily collected. • The reuse of biomass fly ash wastes as raw material ensures waste valorization. - Abstract: In this study novel porous biomass fly ash-containing geopolymer monoliths were produced using a simple and flexible procedure. Geopolymers exhibiting distinct total porosities (ranging from 41.0 to 78.4%) and low apparent density (between 1.21 and 0.44 g/cm{sup 3}) were fabricated. Afterwards, the possibility of using these innovative materials as lead adsorbents under distinct conditions was evaluated. Results demonstrate that the geopolymers’ porosity and the pH of the ion solution strongly affect the lead adsorption capacity. Lead adsorption by the geopolymer monoliths ranged between 0.95 and 6.34 mg{sub lead}/g{sub geopolymer}. More porous geopolymers presented better lead removal efficiency, while higher pH in the solution reduced their removal ability, since metal precipitation is enhanced. These novel geopolymeric monoliths can be used in packed beds that are easily collected when exhausted, which is a major advantage in comparison with the use of powdered adsorbents. Furthermore, their production encompasses the reuse of biomass fly-ash, mitigating the environmental impact associated with this waste disposal, while decreasing the adsorbents production costs.

Permeability model of sintered porous media: analysis and experiments

Science.gov (United States)

Flórez Mera, Juan Pablo; Chiamulera, Maria E.; Mantelli, Marcia B. H.

2017-11-01

In this paper, the permeability of porous media fabricated from copper powder sintering process was modeled and measured, aiming the use of the porosity as input parameter for the prediction of the permeability of sintering porous media. An expression relating the powder particle mean diameter with the permeability was obtained, based on an elementary porous media cell, which is physically represented by a duct formed by the arrangement of spherical particles forming a simple or orthorhombic packing. A circular duct with variable section was used to model the fluid flow within the porous media, where the concept of the hydraulic diameter was applied. Thus, the porous is modeled as a converging-diverging duct. The electrical circuit analogy was employed to determine two hydraulic resistances of the cell: based on the Navier-Stokes equation and on the Darcýs law. The hydraulic resistances are compared between themselves and an expression to determine the permeability as function of average particle diameter is obtained. The atomized copper powder was sifted to reduce the size dispersion of the particles. The porosities and permeabilities of sintered media fabricated from powders with particle mean diameters ranging from 20 to 200 microns were measured, by means of the image analysis method and using an experimental apparatus. The permeability data of a porous media, made of copper powder and saturated with distilled water, was used to compare with the permeability model. Permeability literature models, which considers that powder particles have the same diameter and include porosity data as input parameter, were compared with the present model and experimental data. This comparison showed to be quite good.

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

2014-01-01

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan

2014-04-17

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

Turbulent flows over sparse canopies

Science.gov (United States)

Sharma, Akshath; García-Mayoral, Ricardo

2018-04-01

Turbulent flows over sparse and dense canopies exerting a similar drag force on the flow are investigated using Direct Numerical Simulations. The dense canopies are modelled using a homogeneous drag force, while for the sparse canopy, the geometry of the canopy elements is represented. It is found that on using the friction velocity based on the local shear at each height, the streamwise velocity fluctuations and the Reynolds stress within the sparse canopy are similar to those from a comparable smooth-wall case. In addition, when scaled with the local friction velocity, the intensity of the off-wall peak in the streamwise vorticity for sparse canopies also recovers a value similar to a smooth-wall. This indicates that the sparse canopy does not significantly disturb the near-wall turbulence cycle, but causes its rescaling to an intensity consistent with a lower friction velocity within the canopy. In comparison, the dense canopy is found to have a higher damping effect on the turbulent fluctuations. For the case of the sparse canopy, a peak in the spectral energy density of the wall-normal velocity, and Reynolds stress is observed, which may indicate the formation of Kelvin-Helmholtz-like instabilities. It is also found that a sparse canopy is better modelled by a homogeneous drag applied on the mean flow alone, and not the turbulent fluctuations.

Mass transfer in porous media with heterogeneous chemical reaction

Directory of Open Access Journals (Sweden)

Souza S.M.A.G.Ulson de

2003-01-01

Full Text Available In this paper, the modeling of the mass transfer process in packed-bed reactors is presented and takes into account dispersion in the main fluid phase, internal diffusion of the reactant in the pores of the catalyst, and surface reaction inside the catalyst. The method of volume averaging is applied to obtain the governing equation for use on a small scale. The local mass equilibrium is assumed for obtaining the one-equation model for use on a large scale. The closure problems are developed subject to the length-scale constraints and the model of a spatially periodic porous medium. The expressions for effective diffusivity, hydrodynamic dispersion, total dispersion and the Darcy's law permeability tensors are presented. Solution of the set of final equations permits the variations of velocity and concentration of the chemical species along the packed-bed reactors to be obtained.

Discriminative sparse coding on multi-manifolds

KAUST Repository

Wang, J.J.-Y.; Bensmail, H.; Yao, N.; Gao, Xin

2013-01-01

Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.

Discriminative sparse coding on multi-manifolds

KAUST Repository

Wang, J.J.-Y.

2013-09-26

Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.

Thermal-hydraulic modeling of porous bed reactors

International Nuclear Information System (INIS)

Araj, K.J.; Nourbakhsh, H.P.

1987-01-01

Optimum design of nuclear reactor cores requires an iterative approach between the thermal-hydraulic, neutronic, and operational analysis. This paper will concentrate on the thermal-hydraulic behavior of a hydrogen-cooled small particle bed reactor (PBR). The PBR core modeled here consists of a hexagonal array of fuel elements embedded in a moderator matrix. The fuel elements are annular packed beds of fuel particles held between two porous cylindrical frits. These particles, 500 to 600 μm in diameter, have a uranium carbide core, which is coated by two layers of graphite and an outer coating of zirconium carbide. Coolant flows, radially inward, from the cold frit through the packed bed and hot frit and axially out the channel, formed by the hot frit to a common plenum. A fast running one-dimensional lumped-parameter steady-state code (FTHP) was developed to evaluate the effects of design changes in fuel assembly and power distribution. Another objective for the code was to investigate various methods of coolant control to minimize hot channel effects and maximize outlet temperatures

Study of Co-Current and Counter-Current Gas-Liquid Two-Phase Flow Through Packed Bed in Microgravity

Science.gov (United States)

Revankar, Shripad T.

2002-11-01

The main goal of the project is to obtain new experimental data and development of models on the co-current and counter-current gas-liquid two-phase flow through a packed bed in microgravity and characterize the flow regime transition, pressure drop, void and interfacial area distribution, and liquid hold up. Experimental data will be obtained for earth gravity and microgravity conditions. Models will be developed for the prediction of flow regime transition, void fraction distribution and interfacial area concentration, which are key parameters to characterize the packed bed performance. Thus the specific objectives of the proposed research are to: (1) Develop experiments for the study of the gas liquid two-phase flow through the packed bed with three different flow combinations: co-current down flow, co-current upflow and counter current flow. (2) Develop pore scale and bed scale two-phase instrumentation for measurement of flow regime transition, void distribution and gas-liquid interfacial area concentration in the packed bed. (3) Obtain database on flow regime transition, pressure drop, void distribution, interfacial area concentration and liquid hold up as a function of bed characteristics such as bed particle size, porosity, and liquid properties such as viscosity and surface tension. (4) Develop mathematical model for flow regime transition, void fraction distribution and interfacial area concentration for co-current gas-liquid flow through the porous bed in gravity and micro gravity conditions.(4) Develop mathematical model for the flooding phenomena in counter-current gas-liquid flow through the porous bed in gravity and micro gravity conditions. The present proposal addresses the most important topic of HEDS-specific microgravity fluid physics research identified by NASA 's one of the strategic enterprises, OBPR Enterprise. The proposed project is well defined and makes efficient use of the ground-based parabolic flight research aircraft facility. The

Sparse Regression by Projection and Sparse Discriminant Analysis

KAUST Repository

Qi, Xin

2015-04-03

© 2015, © American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross-validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares, and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared with the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplementary materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.

Sparse distributed memory overview

Science.gov (United States)

Raugh, Mike

1990-01-01

The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.

Pore-scale simulation of fluid flow and solute dispersion in three-dimensional porous media

KAUST Repository

Icardi, Matteo

2014-07-31

In the present work fluid flow and solute transport through porous media are described by solving the governing equations at the pore scale with finite-volume discretization. Instead of solving the simplified Stokes equation (very often employed in this context) the full Navier-Stokes equation is used here. The realistic three-dimensional porous medium is created in this work by packing together, with standard ballistic physics, irregular and polydisperse objects. Emphasis is placed on numerical issues related to mesh generation and spatial discretization, which play an important role in determining the final accuracy of the finite-volume scheme and are often overlooked. The simulations performed are then analyzed in terms of velocity distributions and dispersion rates in a wider range of operating conditions, when compared with other works carried out by solving the Stokes equation. Results show that dispersion within the analyzed porous medium is adequately described by classical power laws obtained by analytic homogenization. Eventually the validity of Fickian diffusion to treat dispersion in porous media is also assessed. © 2014 American Physical Society.

Effect of capillary condensation on gas transport properties in porous media

Science.gov (United States)

Yoshimoto, Yuta; Hori, Takuma; Kinefuchi, Ikuya; Takagi, Shu

2017-10-01

We investigate the effect of capillary condensation on gas diffusivity in porous media composed of randomly packed spheres with moderate wettability. To simulate capillary phenomena at the pore scale while retaining complex pore networks of the porous media, we employ density functional theory (DFT) for coarse-grained lattice gas models. The lattice DFT simulations reveal that capillary condensations preferentially occur at confined pores surrounded by solid walls, leading to the occlusion of narrow pores. Consequently, the characteristic lengths of the partially wet structures are larger than those of the corresponding dry structures with the same porosities. Subsequent gas diffusion simulations exploiting the mean-square displacement method indicate that while the effective diffusion coefficients significantly decrease in the presence of partially condensed liquids, they are larger than those in the dry structures with the same porosities. Moreover, we find that the ratio of the porosity to the tortuosity factor, which is a crucial parameter that determines an effective diffusion coefficient, can be reasonably related to the porosity even for the partially wet porous media.

In-place sparse suffix sorting

DEFF Research Database (Denmark)

Prezza, Nicola

2018-01-01

information regarding the lexicographical order of a size-b subset of all n text suffixes is often needed. Such information can be stored space-efficiently (in b words) in the sparse suffix array (SSA). The SSA and its relative sparse LCP array (SLCP) can be used as a space-efficient substitute of the sparse...... suffix tree. Very recently, Gawrychowski and Kociumaka [11] showed that the sparse suffix tree (and therefore SSA and SLCP) can be built in asymptotically optimal O(b) space with a Monte Carlo algorithm running in O(n) time. The main reason for using the SSA and SLCP arrays in place of the sparse suffix...... tree is, however, their reduced space of b words each. This leads naturally to the quest for in-place algorithms building these arrays. Franceschini and Muthukrishnan [8] showed that the full suffix array can be built in-place and in optimal running time. On the other hand, finding sub-quadratic in...

Separative analyses of a chromatographic column packed with a core-shell adsorbent for lithium isotope separation

International Nuclear Information System (INIS)

Sugiyama, T.; Sugura, K.; Enokida, Y.; Yamamoto, I.

2015-01-01

Lithium-6 is used as a blanket material for sufficient tritium production in DT fueled fusion reactors. A core-shell type adsorbent was proposed for lithium isotope separation by chromatography. The mass transfer model in a chromatographic column consisted of 4 steps, such as convection and dispersion in the column, transfer through liquid films, intra-particle diffusion and and adsorption or desorption at the local adsorption sites. A model was developed and concentration profiles and time variation in the column were numerically simulated. It became clear that core-shell type adsorbents with thin porous shell were saturated rapidly relatively to fully porous one and established a sharp edge of adsorption band. This is very important feature because lithium isotope separation requires long-distance development of adsorption band. The values of HETP (Height Equivalent of a Theoretical Plate) for core-shell adsorbent packed column were estimated by statistical moments of the step response curve. The value of HETP decreased with the thickness of the porous shell. A core-shell type adsorbent is, then, useful for lithium isotope separation. (authors)

Characterization of nanoparticle and porous ultra low-k using positron beam

International Nuclear Information System (INIS)

Xu, Jun; Moxom, J.; Suzuki, R.; Ohdaira, T.; Mills, A.P. Jr.

2003-01-01

Nanoparticle materials are important because they exhibit unique properties due to size effects, quantum tunneling, and quantum confinement. As particle sizes are reduced to the nanometer scale, presence of vacancy clusters is expected to affect properties of nanomaterials. A combination of positron lifetime spectroscopy, which tells size of vacancy clusters, and coincidence Doppler broadening of annihilation radiation, which tell where vacancy clusters are located was used to study defect structures on nanomaterials of Au nanoparticles embedded in MgO. Vacancy clusters were found on the surfaces of Au nanoparticles. When the packing density between multilevel interconnects in microelectronic devices increases, a low dielectric constant material is needed to minimize RC delay. Porous oxide films are some of these new low-k materials that have been actively studied by the microelectronics industry. An ideal porous material would consist of a network of closed, small pores with narrow size distribution. However, large and interconnected pores, so called 'killer pores', result in high current leakage and poor mechanical strength. Clearly, characterization and understanding of pore size and interconnectivity are important to optimize the design of porous materials. Using positron beam, we have found that pore percolation in porous methyl-silsesquioxane (MSQ) films strongly depends on the molecular mass of pore generators. (author)

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

Science.gov (United States)

Moody, Daniela; Wohlberg, Brendt

2018-01-02

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Discrete Sparse Coding.

Science.gov (United States)

Exarchakis, Georgios; Lücke, Jörg

2017-11-01

Sparse coding algorithms with continuous latent variables have been the subject of a large number of studies. However, discrete latent spaces for sparse coding have been largely ignored. In this work, we study sparse coding with latents described by discrete instead of continuous prior distributions. We consider the general case in which the latents (while being sparse) can take on any value of a finite set of possible values and in which we learn the prior probability of any value from data. This approach can be applied to any data generated by discrete causes, and it can be applied as an approximation of continuous causes. As the prior probabilities are learned, the approach then allows for estimating the prior shape without assuming specific functional forms. To efficiently train the parameters of our probabilistic generative model, we apply a truncated expectation-maximization approach (expectation truncation) that we modify to work with a general discrete prior. We evaluate the performance of the algorithm by applying it to a variety of tasks: (1) we use artificial data to verify that the algorithm can recover the generating parameters from a random initialization, (2) use image patches of natural images and discuss the role of the prior for the extraction of image components, (3) use extracellular recordings of neurons to present a novel method of analysis for spiking neurons that includes an intuitive discretization strategy, and (4) apply the algorithm on the task of encoding audio waveforms of human speech. The diverse set of numerical experiments presented in this letter suggests that discrete sparse coding algorithms can scale efficiently to work with realistic data sets and provide novel statistical quantities to describe the structure of the data.

Solving Sparse Polynomial Optimization Problems with Chordal Structure Using the Sparse, Bounded-Degree Sum-of-Squares Hierarchy

NARCIS (Netherlands)

Marandi, Ahmadreza; de Klerk, Etienne; Dahl, Joachim

The sparse bounded degree sum-of-squares (sparse-BSOS) hierarchy of Weisser, Lasserre and Toh [arXiv:1607.01151,2016] constructs a sequence of lower bounds for a sparse polynomial optimization problem. Under some assumptions, it is proven by the authors that the sequence converges to the optimal

Application of X-ray CT investigation of CO{sub 2}-brine flow in porous media

Energy Technology Data Exchange (ETDEWEB)

Jiang, Lanlan; Liu, Yu; Song, Yongchen; Yang, Mingjun; Zhao, Yuechao; Zhao, Jiafei; Zhang, Yi; Shen, Zijian [Dalian University of Technology, Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian (China); Xue, Ziqiu [Research Institute of Innovative Technology for the Earth, Kizugawa City, Kyoto (Japan); Suekane, Tetsuya [Tokyo Institute Technology, Department of Energy Sciences, Nagatsuta, Yokohama (Japan)

2015-05-15

A clear understanding of two-phase flows in porous media is important for investigating CO{sub 2} geological storage. In this study, we conducted an experiment of CO{sub 2}/brine flow process in porous media under sequestration conditions using X-ray CT technique. The flow properties of relative permeability, porosity heterogeneity, and CO{sub 2} saturation were observed in this experiment. The porous media was packed with glass beads having a diameter of 0.2 mm. The porosity distribution along the flow direction is heterogeneous owing to the diameter and shape of glass beads along the flow direction. There is a relationship between CO{sub 2} saturation and porosity distribution, which changes with different flow rates and fractional flows. The heterogeneity of the porous media influences the distribution of CO{sub 2}; moreover, gravity, fractional flows, and flow rates influence CO{sub 2} distribution and saturation. The relative permeability curve was constructed using the steady-state method. The results agreed well with the relative permeability curve simulated using pore-network model. (orig.)

Numerical analyses on the effect of capillary condensation on gas diffusivities in porous media

Science.gov (United States)

Yoshimoto, Yuta; Hori, Takuma; Kinefuchi, Ikuya; Takagi, Shu

2017-11-01

We investigate the effect of capillary condensation on gas diffusivities in porous media composed of randomly packed spheres with moderate wettability. Lattice density functional theory simulations successfully reproduce realistic adsorption/desorption isotherms and provide fluid density distributions inside the porous media. We find that capillary condensations lead to the occlusion of narrow pores because they preferentially occur at confined spaces surrounded by the solid walls. Consequently, the characteristic lengths of the partially wet structures are larger than those of the corresponding dry structures with the same porosities. Subsequent gas diffusion simulations exploiting the mean-square displacement method indicate that while effective diffusion coefficients significantly decrease in the presence of partially condensed liquids, they are larger than those in the dry structures with the same porosities. Most importantly, we find that the porosity-to-tortuosity ratio, which is a crucial parameter that determines the effective diffusion coefficient, can be reasonably related to the porosity even for the partially wet porous media.

Synthesis of Rh/Macro-Porous Alumina Over Micro-Channel Plate and Its Catalytic Activity Tests for Diesel Reforming.

Science.gov (United States)

Seong, Yeon Baek; Kim, Yong Sul; Park, No-Kuk; Lee, Tae Jin

2015-11-01

Macro-porous Al2O3 as the catalytic support material was synthesized using colloidal polystyrene spheres over a micro-channel plate. The colloidal polystyrene spheres were used as a template for the production of an ordered macro porous material using an alumina nitrate solution as the precursor for Al2O3. The close-packed colloidal crystal array template method was applied to the formulation of ordered macro-porous Al2O3 used as a catalytic support material over a micro-channel plate. The solvent in the mixture solution, which also contained the colloidal polystyrene solution, aluminum nitrate solution and the precursor of the catalytic active materials (Rh), was evaporated in a vacuum oven at 50 degrees C. The ordered polystyrene spheres and aluminum salt of the solid state were deposited over a micro channel plate, and macro-porous Al2O3 was formed after calcination at 600 degrees C to remove the polystyrene spheres. The catalytic activity of the Rh/macro-porous alumina supported over the micro-channel plate was tested for diesel reforming.

Bayesian Inference Methods for Sparse Channel Estimation

DEFF Research Database (Denmark)

Pedersen, Niels Lovmand

2013-01-01

This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...

When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

KAUST Repository

Wang, Jim Jing-Yan; Cui, Xuefeng; Yu, Ge; Guo, Lili; Gao, Xin

2017-01-01

Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays

Experimental Study of Heat Energy Absorber with Porous Medium for Thermoelectric Conversion System

Directory of Open Access Journals (Sweden)

Tzer-Ming Jeng

2013-12-01

Full Text Available The thermoelectric conversion system usually consists of the heat absorber, the thermoelectric generator (TEG and the heat sink, while the heat absorber collects the heat to increase the temperature on the hot surface of TEG and enhances the generating electricity. This study experimentally investigated the performance of the brass-beads packed-bed heat absorber for the thermoelectric conversion system. The packed-bed heat absorber is installed in a square channel with the various flow orientation systems and the small ratio of channel width to bead diameter. The flow orientation systems included the straight flow and jet flow systems. This study showed the local and average heat transfer characteristics for various parameters. The experimental results can be the base of designs for the novel porous heat absorber of the thermoelectric conversion system.

Improved Sparse Channel Estimation for Cooperative Communication Systems

Directory of Open Access Journals (Sweden)

Guan Gui

2012-01-01

Full Text Available Accurate channel state information (CSI is necessary at receiver for coherent detection in amplify-and-forward (AF cooperative communication systems. To estimate the channel, traditional methods, that is, least squares (LS and least absolute shrinkage and selection operator (LASSO, are based on assumptions of either dense channel or global sparse channel. However, LS-based linear method neglects the inherent sparse structure information while LASSO-based sparse channel method cannot take full advantage of the prior information. Based on the partial sparse assumption of the cooperative channel model, we propose an improved channel estimation method with partial sparse constraint. At first, by using sparse decomposition theory, channel estimation is formulated as a compressive sensing problem. Secondly, the cooperative channel is reconstructed by LASSO with partial sparse constraint. Finally, numerical simulations are carried out to confirm the superiority of proposed methods over global sparse channel estimation methods.

Sparse Image Reconstruction in Computed Tomography

DEFF Research Database (Denmark)

Jørgensen, Jakob Sauer

In recent years, increased focus on the potentially harmful effects of x-ray computed tomography (CT) scans, such as radiation-induced cancer, has motivated research on new low-dose imaging techniques. Sparse image reconstruction methods, as studied for instance in the field of compressed sensing...... applications. This thesis takes a systematic approach toward establishing quantitative understanding of conditions for sparse reconstruction to work well in CT. A general framework for analyzing sparse reconstruction methods in CT is introduced and two sets of computational tools are proposed: 1...... contributions to a general set of computational characterization tools. Thus, the thesis contributions help advance sparse reconstruction methods toward routine use in...

Sparse Regression by Projection and Sparse Discriminant Analysis

KAUST Repository

Qi, Xin; Luo, Ruiyan; Carroll, Raymond J.; Zhao, Hongyu

2015-01-01

predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths

Reduced-Order Direct Numerical Simulation of Solute Transport in Porous Media

Science.gov (United States)

Mehmani, Yashar; Tchelepi, Hamdi

2017-11-01

Pore-scale models are an important tool for analyzing fluid dynamics in porous materials (e.g., rocks, soils, fuel cells). Current direct numerical simulation (DNS) techniques, while very accurate, are computationally prohibitive for sample sizes that are statistically representative of the porous structure. Reduced-order approaches such as pore-network models (PNM) aim to approximate the pore-space geometry and physics to remedy this problem. Predictions from current techniques, however, have not always been successful. This work focuses on single-phase transport of a passive solute under advection-dominated regimes and delineates the minimum set of approximations that consistently produce accurate PNM predictions. Novel network extraction (discretization) and particle simulation techniques are developed and compared to high-fidelity DNS simulations for a wide range of micromodel heterogeneities and a single sphere pack. Moreover, common modeling assumptions in the literature are analyzed and shown that they can lead to first-order errors under advection-dominated regimes. This work has implications for optimizing material design and operations in manufactured (electrodes) and natural (rocks) porous media pertaining to energy systems. This work was supported by the Stanford University Petroleum Research Institute for Reservoir Simulation (SUPRI-B).

Fluid dynamics of air in a packed bed: velocity profiles and the continuum model assumption

Directory of Open Access Journals (Sweden)

NEGRINI A. L.

1999-01-01

Full Text Available Air flow through packed beds was analyzed experimentally under conditions ranging from those that reinforce the effect of the wall on the void fraction to those that minimize it. The packing was spherical particles, with a tube-to-particle diameter ratio (D/dp between 3 and 60. Air flow rates were maintained between 1.3 and 4.44 m3/min, and gas velocity was measured with a Pitot tube positioned above the bed exit. Measurements were made at various radial and angular coordinate values, allowing the distribution of air flow across the bed to be described in detail. Comparison of the experimentally observed radial profiles with those derived from published equations revealed that at high D/dp ratios the measured and calculated velocity profiles behaved similarly. At low ratios, oscillations in the velocity profiles agreed with those in the voidage profiles, signifying that treating the porous medium as a continuum medium is questionable in these cases.

Comparing the efficacy of mature mud pack and hot pack treatments for knee osteoarthritis.

Science.gov (United States)

Sarsan, Ayşe; Akkaya, Nuray; Ozgen, Merih; Yildiz, Necmettin; Atalay, Nilgun Simsir; Ardic, Fusun

2012-01-01

The objective of this study is to compare the efficacy of mature mud pack and hot pack therapies on patients with knee osteoarthritis. This study was designed as a prospective, randomized-controlled, and single-blinded clinical trial. Twenty-seven patients with clinical and radiologic evidence of knee osteoarthritis were randomly assigned into two groups and were treated with mature mud packs (n 15) or hot packs (n=12). Patients were evaluated for pain [based on the visual analog scale (VAS)], function (WOMAC, 6 min walking distance), quality of life [Short Form-36 (SF-36)], and serum levels of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and insulin-like growth factor-1 (IGF-1) at baseline, post-treatment, and 3 and 6~months after treatment. The mud pack group shows a significant improvement in VAS, pain, stifness, and physical function domains of WOMAC. The difference between groups of pain and physical activity domains is significant at post-treatment in favor of mud pack. For a 6 min walking distance, mud pack shows significant improvement, and the difference is significant between groups in favor of mud pack at post-treatment and 3 and 6 months after treatment. Mud pack shows significant improvement in the pain subscale of SF-36 at the third month continuing until the sixth month after the treatment. Significant improvements are found for the social function, vitality/energy, physical role disability, and general health subscales of SF-36 in favor of the mud pack compared with the hot pack group at post-treatment. A significant increase is detected for IGF-1 in the mud pack group 3 months after treatment compared with the baseline, and the difference is significant between groups 3 months after the treatment. Mud pack is a favorable option compared with hotpack for pain relief and for the improvement of functional conditions in treating patients with knee osteoarthritis.

Sparse decompositions in 'incoherent' dictionaries

DEFF Research Database (Denmark)

Gribonval, R.; Nielsen, Morten

2003-01-01

a unique sparse representation in such a dictionary. In particular, it is proved that the result of Donoho and Huo, concerning the replacement of a combinatorial optimization problem with a linear programming problem when searching for sparse representations, has an analog for dictionaries that may...

Argo packing friction research update

International Nuclear Information System (INIS)

VanTassell, D.M.

1994-01-01

This paper focuses on the issue of valve packing friction and its affect on the operability of motor- and air-operated valves (MOVs and AOVs). At this time, most nuclear power plants are required to perform postmaintenance testing following a packing adjustment or replacement. In many cases, the friction generated by the packing does not impact the operability window of a valve. However, to date there has not been a concerted effort to substantiate this claim. To quantify the effects of packing friction, it has become necessary to develop a formula to predict the friction effects accurately. This formula provides a much more accurate method of predicting packing friction than previously used factors based strictly on stem diameter. Over the past 5 years, Argo Packing Company has been developing and testing improved graphite packing systems at research facilities, such as AECL Chalk River and Wyle Laboratories. Much of this testing has centered around reducing and predicting friction that is related to packing. In addition, diagnostic testing for Generic Letter 89-10 MOVs and AOVs has created a significant data base. In July 1992 Argo asked several utilities to provide running load data that could be used to quantify packing friction repeatability and predictability. This technical paper provides the basis to predict packing friction, which will improve calculations for thrust requirements for Generic Leter 89-10 and future AOV programs. In addition, having an accurate packing friction formula will improve packing performance when low running loads are identified that would indicate insufficient sealing force

Column-to-column packing variation of disposable pre-packed columns for protein chromatography.

Science.gov (United States)

Schweiger, Susanne; Hinterberger, Stephan; Jungbauer, Alois

2017-12-08

In the biopharmaceutical industry, pre-packed columns are the standard for process development, but they must be qualified before use in experimental studies to confirm the required performance of the packed bed. Column qualification is commonly done by pulse response experiments and depends highly on the experimental testing conditions. Additionally, the peak analysis method, the variation in the 3D packing structure of the bed, and the measurement precision of the workstation influence the outcome of qualification runs. While a full body of literature on these factors is available for HPLC columns, no comparable studies exist for preparative columns for protein chromatography. We quantified the influence of these parameters for commercially available pre-packed and self-packed columns of disposable and non-disposable design. Pulse response experiments were performed on 105 preparative chromatography columns with volumes of 0.2-20ml. The analyte acetone was studied at six different superficial velocities (30, 60, 100, 150, 250 and 500cm/h). The column-to-column packing variation between disposable pre-packed columns of different diameter-length combinations varied by 10-15%, which was acceptable for the intended use. The column-to-column variation cannot be explained by the packing density, but is interpreted as a difference in particle arrangement in the column. Since it was possible to determine differences in the column-to-column performance, we concluded that the columns were well-packed. The measurement precision of the chromatography workstation was independent of the column volume and was in a range of±0.01ml for the first peak moment and±0.007 ml 2 for the second moment. The measurement precision must be considered for small columns in the range of 2ml or less. The efficiency of disposable pre-packed columns was equal or better than that of self-packed columns. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Data analysis in high-dimensional sparse spaces

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder

classification techniques for high-dimensional problems are presented: Sparse discriminant analysis, sparse mixture discriminant analysis and orthogonality constrained support vector machines. The first two introduces sparseness to the well known linear and mixture discriminant analysis and thereby provide low...... are applied to classifications of fish species, ear canal impressions used in the hearing aid industry, microbiological fungi species, and various cancerous tissues and healthy tissues. In addition, novel applications of sparse regressions (also called the elastic net) to the medical, concrete, and food...

A sparse-grid isogeometric solver

KAUST Repository

Beck, Joakim; Sangalli, Giancarlo; Tamellini, Lorenzo

2018-01-01

Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90’s in the context of the approximation of high-dimensional PDEs.The tests that we report show that, in accordance to the literature, a sparse-grid construction can indeed be useful if the solution of the PDE at hand is sufficiently smooth. Sparse grids can also be useful in the case of non-smooth solutions when some a-priori knowledge on the location of the singularities of the solution can be exploited to devise suitable non-equispaced meshes. Finally, we remark that sparse grids can be seen as a simple way to parallelize pre-existing serial IGA solvers in a straightforward fashion, which can be beneficial in many practical situations.

A sparse-grid isogeometric solver

KAUST Repository

Beck, Joakim

2018-02-28

Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90’s in the context of the approximation of high-dimensional PDEs.The tests that we report show that, in accordance to the literature, a sparse-grid construction can indeed be useful if the solution of the PDE at hand is sufficiently smooth. Sparse grids can also be useful in the case of non-smooth solutions when some a-priori knowledge on the location of the singularities of the solution can be exploited to devise suitable non-equispaced meshes. Finally, we remark that sparse grids can be seen as a simple way to parallelize pre-existing serial IGA solvers in a straightforward fashion, which can be beneficial in many practical situations.

SparseBeads data: benchmarking sparsity-regularized computed tomography

Science.gov (United States)

Jørgensen, Jakob S.; Coban, Sophia B.; Lionheart, William R. B.; McDonald, Samuel A.; Withers, Philip J.

2017-12-01

Sparsity regularization (SR) such as total variation (TV) minimization allows accurate image reconstruction in x-ray computed tomography (CT) from fewer projections than analytical methods. Exactly how few projections suffice and how this number may depend on the image remain poorly understood. Compressive sensing connects the critical number of projections to the image sparsity, but does not cover CT, however empirical results suggest a similar connection. The present work establishes for real CT data a connection between gradient sparsity and the sufficient number of projections for accurate TV-regularized reconstruction. A collection of 48 x-ray CT datasets called SparseBeads was designed for benchmarking SR reconstruction algorithms. Beadpacks comprising glass beads of five different sizes as well as mixtures were scanned in a micro-CT scanner to provide structured datasets with variable image sparsity levels, number of projections and noise levels to allow the systematic assessment of parameters affecting performance of SR reconstruction algorithms6. Using the SparseBeads data, TV-regularized reconstruction quality was assessed as a function of numbers of projections and gradient sparsity. The critical number of projections for satisfactory TV-regularized reconstruction increased almost linearly with the gradient sparsity. This establishes a quantitative guideline from which one may predict how few projections to acquire based on expected sample sparsity level as an aid in planning of dose- or time-critical experiments. The results are expected to hold for samples of similar characteristics, i.e. consisting of few, distinct phases with relatively simple structure. Such cases are plentiful in porous media, composite materials, foams, as well as non-destructive testing and metrology. For samples of other characteristics the proposed methodology may be used to investigate similar relations.

Packing force data correlations

International Nuclear Information System (INIS)

Heiman, S.M.

1994-01-01

One of the issues facing valve maintenance personnel today deals with an appropriate methodology for installing and setting valve packing that will minimize leak rates, yet ensure functionality of the the valve under all anticipated operating conditions. Several variables can affect a valve packing's ability to seal, such as packing bolt torque, stem finish, and lubrication. Stem frictional force can be an excellent overall indicator of some of the underlying conditions that affect the sealing characteristics of the packing and the best parameter to use when adjusting the packing. This paper addresses stem friction forces, analytically derives the equations related to these forces, presents a methodology for measuring these forces on valve stems, and attempts to correlate the data directly to the underlying variables

Multiple and dependent scattering by densely packed discrete spheres: Comparison of radiative transfer and Maxwell theory

International Nuclear Information System (INIS)

Ma, L.X.; Tan, J.Y.; Zhao, J.M.; Wang, F.Q.; Wang, C.A.

2017-01-01

The radiative transfer equation (RTE) has been widely used to deal with multiple scattering of light by sparsely and randomly distributed discrete particles. However, for densely packed particles, the RTE becomes questionable due to strong dependent scattering effects. This paper examines the accuracy of RTE by comparing with the exact electromagnetic theory. For an imaginary spherical volume filled with randomly distributed, densely packed spheres, the RTE is solved by the Monte Carlo method combined with the Percus–Yevick hard model to consider the dependent scattering effect, while the electromagnetic calculation is based on the multi-sphere superposition T-matrix method. The Mueller matrix elements of the system with different size parameters and volume fractions of spheres are obtained using both methods. The results verify that the RTE fails to deal with the systems with a high-volume fraction due to the dependent scattering effects. Apart from the effects of forward interference scattering and coherent backscattering, the Percus–Yevick hard sphere model shows good accuracy in accounting for the far-field interference effects for medium or smaller size parameters (up to 6.964 in this study). For densely packed discrete spheres with large size parameters (equals 13.928 in this study), the improvement of dependent scattering correction tends to deteriorate. The observations indicate that caution must be taken when using RTE in dealing with the radiative transfer in dense discrete random media even though the dependent scattering correction is applied. - Highlights: • The Muller matrix of randomly distributed, densely packed spheres are investigated. • The effects of multiple scattering and dependent scattering are analyzed. • The accuracy of radiative transfer theory for densely packed spheres is discussed. • Dependent scattering correction takes effect at medium size parameter or smaller. • Performance of dependent scattering correction

Supervised Transfer Sparse Coding

KAUST Repository

Al-Shedivat, Maruan

2014-07-27

A combination of the sparse coding and transfer learn- ing techniques was shown to be accurate and robust in classification tasks where training and testing objects have a shared feature space but are sampled from differ- ent underlying distributions, i.e., belong to different do- mains. The key assumption in such case is that in spite of the domain disparity, samples from different domains share some common hidden factors. Previous methods often assumed that all the objects in the target domain are unlabeled, and thus the training set solely comprised objects from the source domain. However, in real world applications, the target domain often has some labeled objects, or one can always manually label a small num- ber of them. In this paper, we explore such possibil- ity and show how a small number of labeled data in the target domain can significantly leverage classifica- tion accuracy of the state-of-the-art transfer sparse cod- ing methods. We further propose a unified framework named supervised transfer sparse coding (STSC) which simultaneously optimizes sparse representation, domain transfer and classification. Experimental results on three applications demonstrate that a little manual labeling and then learning the model in a supervised fashion can significantly improve classification accuracy.

Joint Group Sparse PCA for Compressed Hyperspectral Imaging.

Science.gov (United States)

Khan, Zohaib; Shafait, Faisal; Mian, Ajmal

2015-12-01

A sparse principal component analysis (PCA) seeks a sparse linear combination of input features (variables), so that the derived features still explain most of the variations in the data. A group sparse PCA introduces structural constraints on the features in seeking such a linear combination. Collectively, the derived principal components may still require measuring all the input features. We present a joint group sparse PCA (JGSPCA) algorithm, which forces the basic coefficients corresponding to a group of features to be jointly sparse. Joint sparsity ensures that the complete basis involves only a sparse set of input features, whereas the group sparsity ensures that the structural integrity of the features is maximally preserved. We evaluate the JGSPCA algorithm on the problems of compressed hyperspectral imaging and face recognition. Compressed sensing results show that the proposed method consistently outperforms sparse PCA and group sparse PCA in reconstructing the hyperspectral scenes of natural and man-made objects. The efficacy of the proposed compressed sensing method is further demonstrated in band selection for face recognition.

Upcycling of Packing-Peanuts into Carbon Microsheet Anodes for Lithium-Ion Batteries.

Science.gov (United States)

Etacheri, Vinodkumar; Hong, Chulgi Nathan; Pol, Vilas G

2015-09-15

Porous carbon microsheet anodes with Li-ion storage capacity exceeding the theoretical limit are for the first time derived from waste packing-peanuts. Crystallinity, surface area, and porosity of these 1 μm thick carbon sheets were tuned by varying the processing temperature. Anodes composed of the carbon sheets outperformed the electrochemical properties of commercial graphitic anode in Li-ion batteries. At a current density of 0.1 C, carbon microsheet anodes exhibited a specific capacity of 420 mAh/g, which is slightly higher than the theoretical capacity of graphite (372 mAh/g) in Li-ion half-cell configurations. At a higher rate of 1 C, carbon sheets retained 4-fold higher specific capacity (220 mAh/g) compared to those of commercial graphitic anode. After 100 charge-discharge cycles at current densities of 0.1 and 0.2 C, optimized carbon sheet anodes retained stable specific capacities of 460 and 370 mAh/g, respectively. Spectroscopic and microscopic investigations proved the structural integrity of these high-performance carbon anodes during numerous charge-discharge cycles. Considerably higher electrochemical performance of the porous carbon microsheets are endorsed to their disorderness that facilitate to store more Li-ions than the theoretical limit, and porous 2-D microstructure enabling fast solid-state Li-ion diffusion and superior interfacial kinetics. The work demonstrated here illustrates an inexpensive and environmentally benign method for the upcycling of packaging materials into functional carbon materials for electrochemical energy storage.

Parallel Sparse Matrix - Vector Product

DEFF Research Database (Denmark)

Alexandersen, Joe; Lazarov, Boyan Stefanov; Dammann, Bernd

This technical report contains a case study of a sparse matrix-vector product routine, implemented for parallel execution on a compute cluster with both pure MPI and hybrid MPI-OpenMP solutions. C++ classes for sparse data types were developed and the report shows how these class can be used...

Multi-threaded Sparse Matrix Sparse Matrix Multiplication for Many-Core and GPU Architectures.

Energy Technology Data Exchange (ETDEWEB)

Deveci, Mehmet [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trott, Christian Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rajamanickam, Sivasankaran [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2018-01-01

Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix- matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and data structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.

Ozo-Dyes mixture degradation in a fixed bed biofilm reactor packed with volcanic porous rock

International Nuclear Information System (INIS)

Contreras-Blancas, E.; Cobos-Vasconcelos, D. de los; Juarez-Ramirez, C.; Poggi-Varaldo, H. M.; Ruiz-Ordaz, N.; Galindez-Mayer, J.

2009-01-01

Textile industries discharge great amounts of dyes and dyeing-process auxiliaries, which pollute streams and water bodies. Several dyes, especially the ones containing the azo group, can cause harmful effects to different organisms including humans. Through bacterial and mammalian tests, azo dyes or their derived aromatic amines have shown cell genotoxicity. The purpose of this work was to evaluate the effect of air flow rate on azo-dyes mixture biodegradation by a microbial community immobilized in a packed bed reactor. (Author)

Ozo-Dyes mixture degradation in a fixed bed biofilm reactor packed with volcanic porous rock

Energy Technology Data Exchange (ETDEWEB)

Contreras-Blancas, E.; Cobos-Vasconcelos, D. de los; Juarez-Ramirez, C.; Poggi-Varaldo, H. M.; Ruiz-Ordaz, N.; Galindez-Mayer, J.

2009-07-01

Textile industries discharge great amounts of dyes and dyeing-process auxiliaries, which pollute streams and water bodies. Several dyes, especially the ones containing the azo group, can cause harmful effects to different organisms including humans. Through bacterial and mammalian tests, azo dyes or their derived aromatic amines have shown cell genotoxicity. The purpose of this work was to evaluate the effect of air flow rate on azo-dyes mixture biodegradation by a microbial community immobilized in a packed bed reactor. (Author)

Tritium sorption behavior on the percolation of tritiated water into a soil packed bed

Energy Technology Data Exchange (ETDEWEB)

Furuichi, Kazuya, E-mail: kfuruichi@aees.kyushu-u.ac.jp [Department of Advanced Energy Engineering, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580 (Japan); Katayama, Kazunari; Date, Hiroyuki [Department of Advanced Energy Engineering, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580 (Japan); Takeishi, Toshiharu [Factory of Engineering, Kyushu University, 744 Motooka Nishi-ku, Fukuoka 819-0395 (Japan); Fukada, Satoshi [Department of Advanced Energy Engineering, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580 (Japan)

2016-11-01

Highlights: • We establish the permeation model of tritiated water in the soil layer. • Saturated hydraulic conductivity of water in soil was gained by using the model. • The isotope exchange reaction coefficient was good agreement with experimental data. - Abstract: Development of tritium transport model in natural soil is an important issue from a viewpoint of safety of fusion reactors. The spill of a large amount of tritiated water to the environment is a concern accident because huge tritiated water is handled in a fusion plant. In this work, a simple tritium transport model was proposed based on the tritium transport model in porous materials. The overall mass transfer coefficient representing isotope exchange reaction between tritiated water and structural water in soil particles was obtained by numerically analyzing the result of the percolation experiment of tritiated water into the soil packed bed. Saturated hydraulic conductivity in the natural soil packed bed was obtained to be 0.033 mm/s. By using this value, the overall mass transfer capacity coefficients representing the isotope exchange reaction between tritiated water percolating through the packed bed and overall structural water on soil particles was determined to be 6.0 × 10{sup −4} 1/s. This value is much smaller than the mass transfer capacity coefficient between tritiated water vapor and water on concrete material and metals.

Sparse approximation with bases

CERN Document Server

2015-01-01

This book systematically presents recent fundamental results on greedy approximation with respect to bases. Motivated by numerous applications, the last decade has seen great successes in studying nonlinear sparse approximation. Recent findings have established that greedy-type algorithms are suitable methods of nonlinear approximation in both sparse approximation with respect to bases and sparse approximation with respect to redundant systems. These insights, combined with some previous fundamental results, form the basis for constructing the theory of greedy approximation. Taking into account the theoretical and practical demand for this kind of theory, the book systematically elaborates a theoretical framework for greedy approximation and its applications.  The book addresses the needs of researchers working in numerical mathematics, harmonic analysis, and functional analysis. It quickly takes the reader from classical results to the latest frontier, but is written at the level of a graduate course and do...

Efficient convolutional sparse coding

Science.gov (United States)

Wohlberg, Brendt

2017-06-20

Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.

Hyperspectral Unmixing with Robust Collaborative Sparse Regression

Directory of Open Access Journals (Sweden)

Chang Li

2016-07-01

Full Text Available Recently, sparse unmixing (SU of hyperspectral data has received particular attention for analyzing remote sensing images. However, most SU methods are based on the commonly admitted linear mixing model (LMM, which ignores the possible nonlinear effects (i.e., nonlinearity. In this paper, we propose a new method named robust collaborative sparse regression (RCSR based on the robust LMM (rLMM for hyperspectral unmixing. The rLMM takes the nonlinearity into consideration, and the nonlinearity is merely treated as outlier, which has the underlying sparse property. The RCSR simultaneously takes the collaborative sparse property of the abundance and sparsely distributed additive property of the outlier into consideration, which can be formed as a robust joint sparse regression problem. The inexact augmented Lagrangian method (IALM is used to optimize the proposed RCSR. The qualitative and quantitative experiments on synthetic datasets and real hyperspectral images demonstrate that the proposed RCSR is efficient for solving the hyperspectral SU problem compared with the other four state-of-the-art algorithms.

Entropy generation of viscous dissipative flow in thermal non-equilibrium porous media with thermal asymmetries

International Nuclear Information System (INIS)

Chee, Yi Shen; Ting, Tiew Wei; Hung, Yew Mun

2015-01-01

The effect of thermal asymmetrical boundaries on entropy generation of viscous dissipative flow of forced convection in thermal non-equilibrium porous media is analytically studied. The two-dimensional temperature, Nusselt number and entropy generation contours are analysed comprehensively to provide insights into the underlying physical significance of the effect on entropy generation. By incorporating the effects of viscous dissipation and thermal non-equilibrium, the first-law and second-law characteristics of porous-medium flow are investigated via various pertinent parameters, i.e. heat flux ratio, effective thermal conductivity ratio, Darcy number, Biot number and averaged fluid velocity. For the case of symmetrical wall heat flux, an optimum condition with a high Nusselt number and a low entropy generation is identified at a Darcy number of 10 −4 , providing an ideal operating condition from the second-law aspect. This type of heat and fluid transport in porous media covers a wide range of engineering applications, involving porous insulation, packed-bed catalytic process in nuclear reactors, filtration transpiration cooling, and modelling of transport phenomena of microchannel heat sinks. - Highlights: • Effects of thermal asymmetries on convection in porous-medium are studied. • Exergetic effectiveness of porous media with thermal asymmetries is investigated. • 2-D temperature, Nusselt number and entropy generation contours are analyzed. • Significance of viscous dissipation in entropy generation is scrutinized. • Significance of thermal non-equilibrium in entropy generation is studied

Magnetic resonance velocity imaging of liquid and gas two-phase flow in packed beds.

Science.gov (United States)

Sankey, M H; Holland, D J; Sederman, A J; Gladden, L F

2009-02-01

Single-phase liquid flow in porous media such as bead packs and model fixed bed reactors has been well studied by MRI. To some extent this early work represents the necessary preliminary research to address the more challenging problem of two-phase flow of gas and liquid within these systems. In this paper, we present images of both the gas and liquid velocities during stable liquid-gas flow of water and SF(6) within a packing of 5mm spheres contained within columns of diameter 40 and 27 mm; images being acquired using (1)H and (19)F observation for the water and SF(6), respectively. Liquid and gas flow rates calculated from the velocity images are in agreement with macroscopic flow rate measurements to within 7% and 5%, respectively. In addition to the information obtained directly from these images, the ability to measure liquid and gas flow fields within the same sample environment will enable us to explore the validity of assumptions used in numerical modelling of two-phase flows.

On the Effective Thermal Conductivity of Porous Packed Beds with Uniform Spherical Particles

Science.gov (United States)

Kandula, Max

2010-01-01

Point contact models for the effective thermal conductivity of porous media with uniform spherical inclusions have been briefly reviewed. The model of Zehner and Schlunder (1970) has been further validated with recent experimental data over a broad range of conductivity ratio from 8 to 1200 and over a range of solids fraction up to about 0.8. The comparisons further confirm the validity of Zehner-Schlunder model, known to be applicable for conductivity ratios less than about 2000, above which area contact between the particles becomes significant. This validation of the Zehner-Schlunder model has implications for its use in the prediction of the effective thermal conductivity of water frost (with conductivity ratio around 100) which arises in many important areas of technology.

Transport of titanium dioxide nanoparticles in saturated porous media under various solution chemistry conditions

International Nuclear Information System (INIS)

Wang Yu; Gao Bin; Morales, Verónica L.; Tian Yuan; Wu Lei; Gao Jie; Bai Wei; Yang Liuyan

2012-01-01

Because of its wide applications, nanosized titanium dioxide may become a potential environmental risk to soil and groundwater system. It is therefore important to improve current understanding of the environmental fate and transport of titanium oxides nanoparticles (TONPs). In this work, the effect of solution chemistry (i.e., pH, ionic strength, and natural organic matter (NOM) concentration) on the deposition and transport of TONPs in saturated porous media was examined in detail. Laboratory columns packed with acid-cleaned quartz sand were used in the experiment as porous media. Transport experiments were conducted with various chemistry combinations, including four ionic strengths, three pH levels, and two NOM concentrations. The results showed that TONP mobility increased with increasing solution pH, but decreased with increasing solution ionic strength. It is also found that the presence of NOM in the system enhanced the mobility of TONPs in the saturated porous media. The Derjaguin–Landau–Verwey–Overbeek (DLVO) theory was used to justify the mobility trends observed in the experimental data. Predictions from the theory agreed excellently with the experimental data.

Image fusion using sparse overcomplete feature dictionaries

Science.gov (United States)

Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

2015-10-06

Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

American Spirit Pack Descriptors and Perceptions of Harm: A Crowdsourced Comparison of Modified Packs.

Science.gov (United States)

Pearson, Jennifer L; Richardson, Amanda; Feirman, Shari P; Villanti, Andrea C; Cantrell, Jennifer; Cohn, Amy; Tacelosky, Michael; Kirchner, Thomas R

2016-08-01

In 2015, the Food and Drug Administration issued warnings to three tobacco manufacturers who label their cigarettes as "additive-free" and/or "natural" on the grounds that they make unauthorized reduced risk claims. The goal of this study was to examine US adults' perceptions of three American Spirit (AS) pack descriptors ("Made with Organic Tobacco," "100% Additive-Free," and "100% US Grown Tobacco") to assess if they communicate reduced risk. In September 2012, three cross-sectional surveys were posted on Amazon Mechanical Turk. Adult participants evaluated the relative harm of a Marlboro Red pack versus three different AS packs with the descriptors "Made with Organic Tobacco," "100% Additive-Free," or "100% US Grown Tobacco" (Survey 1; n = 461); a Marlboro Red pack versus these AS packs modified to exclude descriptors (Survey 2; n = 857); and unmodified versus modified AS pack images (Survey 3; n = 1001). The majority of Survey 1 participants rated the unmodified AS packs as less harmful than the Marlboro Red pack; 35.4%-58.8% of Survey 2 participants also rated the modified (no claims) packs as less harmful than Marlboro Red. In these surveys, prior use of AS cigarettes was associated with reduced perceptions of risk (adjusted odds ratio [AOR] 1.59-2.40). "Made with Organic Tobacco" and "100% Additive-Free" were associated with reduced perceptions of risk when comparing the modified versus the unmodified AS packs (Survey 3). Data suggest that these AS pack descriptors communicate reduced harm messages to consumers. Findings have implications for regulatory actions related to product labeling and packaging. These findings provide additional evidence that the "Made with Organic Tobacco," "100% Additive-Free," and "100% US Grown" descriptors, as well as other aspects of the AS pack design, communicate reduced harm to non-, current, and former smokers. Additionally, they provide support for the importance of FDA's 2015 warning to Santa Fe Natural Tobacco Company on

Retention and effective diffusion of model metabolites on porous graphitic carbon.

Science.gov (United States)

Lunn, Daniel B; Yun, Young J; Jorgenson, James W

2017-12-29

The study of metabolites in biological samples is of high interest for a wide range of biological and pharmaceutical applications. Reversed phase liquid chromatography is a common technique used for the separation of metabolites, but it provides little retention for polar metabolites. An alternative to C18 bonded phases, porous graphitic carbon has the ability to provide significant retention for both non-polar and polar analytes. The goal of this work is to study the retention and effective diffusion properties of porous graphitic carbon, to see if it is suitable for the wide injection bands and long run times associated with long, packed capillary-scale separations. The retention of a set of standard metabolites was studied for both stationary phases over a wide range of mobile phase conditions. This data showed that porous graphitic carbon benefits from significantly increased retention (often >100 fold) under initial gradient conditions for these metabolites, suggesting much improved ability to focus a wide injection band at the column inlet. The effective diffusion properties of these columns were studied using peak-parking experiments with the standard metabolites under a wide range of retention conditions. Under the high retention conditions, which can be associated with retention after injection loading for gradient separations, D eff /D m ∼0.1 for both the C18-bonded and porous graphitic carbon columns. As C18 bonded particles are widely, and successfully utilized for long gradient separations without issue of increasing peak width from longitudinal diffusion, this suggests that porous graphitic carbon should be amenable for long runtime gradient separations as well. Copyright © 2017 Elsevier B.V. All rights reserved.

Manifold regularization for sparse unmixing of hyperspectral images.

Science.gov (United States)

Liu, Junmin; Zhang, Chunxia; Zhang, Jiangshe; Li, Huirong; Gao, Yuelin

2016-01-01

Recently, sparse unmixing has been successfully applied to spectral mixture analysis of remotely sensed hyperspectral images. Based on the assumption that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures known in advance, unmixing of each mixed pixel in the scene is to find an optimal subset of signatures in a very large spectral library, which is cast into the framework of sparse regression. However, traditional sparse regression models, such as collaborative sparse regression , ignore the intrinsic geometric structure in the hyperspectral data. In this paper, we propose a novel model, called manifold regularized collaborative sparse regression , by introducing a manifold regularization to the collaborative sparse regression model. The manifold regularization utilizes a graph Laplacian to incorporate the locally geometrical structure of the hyperspectral data. An algorithm based on alternating direction method of multipliers has been developed for the manifold regularized collaborative sparse regression model. Experimental results on both the simulated and real hyperspectral data sets have demonstrated the effectiveness of our proposed model.

Enhancing Scalability of Sparse Direct Methods

International Nuclear Information System (INIS)

Li, Xiaoye S.; Demmel, James; Grigori, Laura; Gu, Ming; Xia, Jianlin; Jardin, Steve; Sovinec, Carl; Lee, Lie-Quan

2007-01-01

TOPS is providing high-performance, scalable sparse direct solvers, which have had significant impacts on the SciDAC applications, including fusion simulation (CEMM), accelerator modeling (COMPASS), as well as many other mission-critical applications in DOE and elsewhere. Our recent developments have been focusing on new techniques to overcome scalability bottleneck of direct methods, in both time and memory. These include parallelizing symbolic analysis phase and developing linear-complexity sparse factorization methods. The new techniques will make sparse direct methods more widely usable in large 3D simulations on highly-parallel petascale computers

Regression with Sparse Approximations of Data

DEFF Research Database (Denmark)

Noorzad, Pardis; Sturm, Bob L.

2012-01-01

We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...

Sparse adaptive filters for echo cancellation

CERN Document Server

Paleologu, Constantin

2011-01-01

Adaptive filters with a large number of coefficients are usually involved in both network and acoustic echo cancellation. Consequently, it is important to improve the convergence rate and tracking of the conventional algorithms used for these applications. This can be achieved by exploiting the sparseness character of the echo paths. Identification of sparse impulse responses was addressed mainly in the last decade with the development of the so-called ``proportionate''-type algorithms. The goal of this book is to present the most important sparse adaptive filters developed for echo cancellati

Magnetohydraulic flow through a packed bed of electrically conducting spheres

International Nuclear Information System (INIS)

Sanders, T.L.

1985-01-01

The flow of an electrically conducting fluid through a packed bed of electrically conducting spheres in the presence of a strong magnetic field constitutes a very complex flow situation due to the constant turning of the fluid in and out of magnetic field lines. The interaction of the orthogonal components of the velocity and magnetic field will induce electric fields that are orthogonal to both and the electric fields in turn can cause currents that interact with the magnetic field to generate forces against the direction of flow. The strengths of these generated forces depend primarily upon the closure paths taken by the induced currents which, in turn, depend upon the relative ratio of the electrical resistance of the solid spheres to that of the fluid. Both experimental and analytical analyses of the slow flow of a eutectic mixture of sodium and potassium (NaK) through packed cylinders containing stainless steel spheres in the presence of a strong transverse magnetic field were completed. A theory of magnetohydraulic flow is developed by analogy with the development of hydraulic radius theories of flow through porous media. An exact regional analysis is successfully applied to an infinite bed of electrically conducting spheres with a conducting or non-conducting constraining wall on one side. The equations derived are solved for many different combinations of flowrate, magnetic field strength, porosity, and electrical resistance ratio

Hardness of approximation for strip packing

DEFF Research Database (Denmark)

Adamaszek, Anna Maria; Kociumaka, Tomasz; Pilipczuk, Marcin

2017-01-01

Strip packing is a classical packing problem, where the goal is to pack a set of rectangular objects into a strip of a given width, while minimizing the total height of the packing. The problem has multiple applications, for example, in scheduling and stock-cutting, and has been studied extensively......)-approximation by two independent research groups [FSTTCS 2016,WALCOM 2017]. This raises a questionwhether strip packing with polynomially bounded input data admits a quasi-polynomial time approximation scheme, as is the case for related twodimensional packing problems like maximum independent set of rectangles or two...

Parallel sparse direct solver for integrated circuit simulation

CERN Document Server

Chen, Xiaoming; Yang, Huazhong

2017-01-01

This book describes algorithmic methods and parallelization techniques to design a parallel sparse direct solver which is specifically targeted at integrated circuit simulation problems. The authors describe a complete flow and detailed parallel algorithms of the sparse direct solver. They also show how to improve the performance by simple but effective numerical techniques. The sparse direct solver techniques described can be applied to any SPICE-like integrated circuit simulator and have been proven to be high-performance in actual circuit simulation. Readers will benefit from the state-of-the-art parallel integrated circuit simulation techniques described in this book, especially the latest parallel sparse matrix solution techniques. · Introduces complicated algorithms of sparse linear solvers, using concise principles and simple examples, without complex theory or lengthy derivations; · Describes a parallel sparse direct solver that can be adopted to accelerate any SPICE-like integrated circuit simulato...

Modified strip packing heuristics for the rectangular variable-sized bin packing problem

Directory of Open Access Journals (Sweden)

FG Ortmann

2010-06-01

Full Text Available Two packing problems are considered in this paper, namely the well-known strip packing problem (SPP and the variable-sized bin packing problem (VSBPP. A total of 252 strip packing heuristics (and variations thereof from the literature, as well as novel heuristics proposed by the authors, are compared statistically by means of 1170 SPP benchmark instances in order to identify the best heuristics in various classes. A combination of new heuristics with a new sorting method yields the best results. These heuristics are combined with a previous heuristic for the VSBPP by the authors to find good feasible solutions to 1357 VSBPP benchmark instances. This is the largest statistical comparison of algorithms for the SPP and the VSBPP to the best knowledge of the authors.

Biclustering via Sparse Singular Value Decomposition

KAUST Repository

Lee, Mihee

2010-02-16

Sparse singular value decomposition (SSVD) is proposed as a new exploratory analysis tool for biclustering or identifying interpretable row-column associations within high-dimensional data matrices. SSVD seeks a low-rank, checkerboard structured matrix approximation to data matrices. The desired checkerboard structure is achieved by forcing both the left- and right-singular vectors to be sparse, that is, having many zero entries. By interpreting singular vectors as regression coefficient vectors for certain linear regressions, sparsity-inducing regularization penalties are imposed to the least squares regression to produce sparse singular vectors. An efficient iterative algorithm is proposed for computing the sparse singular vectors, along with some discussion of penalty parameter selection. A lung cancer microarray dataset and a food nutrition dataset are used to illustrate SSVD as a biclustering method. SSVD is also compared with some existing biclustering methods using simulated datasets. © 2010, The International Biometric Society.

Effect of gravity on colloid transport through water-saturated columns packed with glass beads: modeling and experiments.

Science.gov (United States)

Chrysikopoulos, Constantinos V; Syngouna, Vasiliki I

2014-06-17

The role of gravitational force on colloid transport in water-saturated columns packed with glass beads was investigated. Transport experiments were performed with colloids (clays: kaolinite KGa-1b, montmorillonite STx-1b). The packed columns were placed in various orientations (horizontal, vertical, and diagonal) and a steady flow rate of Q = 1.5 mL/min was applied in both up-flow and down-flow modes. All experiments were conducted under electrostatically unfavorable conditions. The experimental data were fitted with a newly developed, analytical, one-dimensional, colloid transport model. The effect of gravity is incorporated in the mathematical model by combining the interstitial velocity (advection) with the settling velocity (gravity effect). The results revealed that flow direction influences colloid transport in porous media. The rate of particle deposition was shown to be greater for up-flow than for down-flow direction, suggesting that gravity was a significant driving force for colloid deposition.

Modelling the growth process of porous aluminum oxide film during anodization

International Nuclear Information System (INIS)

Aryslanova, E M; Alfimov, A V; Chivilikhin, S A

2015-01-01

Currently it has become important for the development of metamaterials and nanotechnology to obtain regular self-assembled structures. One such structure is porous anodic alumina film that consists of hexagonally packed cylindrical pores. In this work we consider the anodization process, our model takes into account the influence of layers of aluminum and electrolyte on the rate of growth of aluminum oxide, as well as the effect of surface diffusion. In present work we consider those effects. And as a result of our model we obtain the minimum distance between centers of alumina pores in the beginning of anodizing process. (paper)

Modelling the growth process of porous aluminum oxide film during anodization

Science.gov (United States)

Aryslanova, E. M.; Alfimov, A. V.; Chivilikhin, S. A.

2015-11-01

Currently it has become important for the development of metamaterials and nanotechnology to obtain regular self-assembled structures. One such structure is porous anodic alumina film that consists of hexagonally packed cylindrical pores. In this work we consider the anodization process, our model takes into account the influence of layers of aluminum and electrolyte on the rate of growth of aluminum oxide, as well as the effect of surface diffusion. In present work we consider those effects. And as a result of our model we obtain the minimum distance between centers of alumina pores in the beginning of anodizing process.

Flooding characteristics of Goodloe packing

International Nuclear Information System (INIS)

Begovich, J.M.; Watson, J.S.

1976-08-01

Experimental flooding data for the countercurrent flow of air and water in a 7.62-cm-diam glass column filled with Goodloe packing were compared with a correlation reported by the packing manufacturer. Flooding rates observed in this study were as low as one-half those predicted by the correlation. Rearranging the packing by inverting the column and removing some packing segments yielded results similar to the correlation for liquid-to-gas (L/G) mass flow rate ratios greater than 10, but the experimental flooding curve fell significantly below the correlation at lower L/G ratios. When the column was repacked with new packing, the results were essentially the same as those obtained in the inverted column. Thus, it is believed that a carefully packed column is more likely to yield flooding rates similar to those obtained in the new or inverted columns rather than rates predicted by the original correlation

The advantages of hydraulic packing extraction

International Nuclear Information System (INIS)

Baker, R.S.

1991-01-01

Today's competitive environment, coupled with industry's desire to improve the efficiency of plant maintenance and operations, has management continually seeking ways to save time, money, and, at nuclear plants, radiation exposure. One area where a tremendous improvement in efficiency can be realized is valve packing removal. For example, industry experience indicates that up to 70% of the time it takes to repack a valve can be spent just removing the old packing. In some case, the bonnets of small valves are removed to facilitate packing removal and prevent stem and stuffing box damage that can occur when using packing removal picks. In other cases, small valves are simply removed and discarded because it costs less to replace the valves than to remove the packing using conventional methods. Hydraulic packing extraction greatly reduces packing removal time and will not damage the stem nor stuffing box, thus eliminating the need for bonnet removal or valve replacement. This paper will review some of the more common problems associated with manual packing extraction techniques. It will explain how hydraulic packing extraction eliminates or greatly reduces the impact of each of the problem areas. A discussion will be provided of some actual industry operating experiences related to success stories using hydraulic packing extraction. The paper will also briefly describe the operating parameters associated with hydraulic packing extraction tools. Throughout the paper, actual operating experiences from the nuclear power, fossil power, petrochemical, and refinery industries will be used to support the conclusion that hydraulic packing extraction is an alternative that can save time, money, and exposure

The Maximum Resource Bin Packing Problem

DEFF Research Database (Denmark)

Boyar, J.; Epstein, L.; Favrholdt, L.M.

2006-01-01

Usually, for bin packing problems, we try to minimize the number of bins used or in the case of the dual bin packing problem, maximize the number or total size of accepted items. This paper presents results for the opposite problems, where we would like to maximize the number of bins used...... algorithms, First-Fit-Increasing and First-Fit-Decreasing for the maximum resource variant of classical bin packing. For the on-line variant, we define maximum resource variants of classical and dual bin packing. For dual bin packing, no on-line algorithm is competitive. For classical bin packing, we find...

Robust Face Recognition Via Gabor Feature and Sparse Representation

Directory of Open Access Journals (Sweden)

Hao Yu-Juan

2016-01-01

Full Text Available Sparse representation based on compressed sensing theory has been widely used in the field of face recognition, and has achieved good recognition results. but the face feature extraction based on sparse representation is too simple, and the sparse coefficient is not sparse. In this paper, we improve the classification algorithm based on the fusion of sparse representation and Gabor feature, and then improved algorithm for Gabor feature which overcomes the problem of large dimension of the vector dimension, reduces the computation and storage cost, and enhances the robustness of the algorithm to the changes of the environment.The classification efficiency of sparse representation is determined by the collaborative representation,we simplify the sparse constraint based on L1 norm to the least square constraint, which makes the sparse coefficients both positive and reduce the complexity of the algorithm. Experimental results show that the proposed method is robust to illumination, facial expression and pose variations of face recognition, and the recognition rate of the algorithm is improved.

Sparse Learning with Stochastic Composite Optimization.

Science.gov (United States)

Zhang, Weizhong; Zhang, Lijun; Jin, Zhongming; Jin, Rong; Cai, Deng; Li, Xuelong; Liang, Ronghua; He, Xiaofei

2017-06-01

In this paper, we study Stochastic Composite Optimization (SCO) for sparse learning that aims to learn a sparse solution from a composite function. Most of the recent SCO algorithms have already reached the optimal expected convergence rate O(1/λT), but they often fail to deliver sparse solutions at the end either due to the limited sparsity regularization during stochastic optimization (SO) or due to the limitation in online-to-batch conversion. Even when the objective function is strongly convex, their high probability bounds can only attain O(√{log(1/δ)/T}) with δ is the failure probability, which is much worse than the expected convergence rate. To address these limitations, we propose a simple yet effective two-phase Stochastic Composite Optimization scheme by adding a novel powerful sparse online-to-batch conversion to the general Stochastic Optimization algorithms. We further develop three concrete algorithms, OptimalSL, LastSL and AverageSL, directly under our scheme to prove the effectiveness of the proposed scheme. Both the theoretical analysis and the experiment results show that our methods can really outperform the existing methods at the ability of sparse learning and at the meantime we can improve the high probability bound to approximately O(log(log(T)/δ)/λT).

Shearlets and Optimally Sparse Approximations

DEFF Research Database (Denmark)

Kutyniok, Gitta; Lemvig, Jakob; Lim, Wang-Q

2012-01-01

Multivariate functions are typically governed by anisotropic features such as edges in images or shock fronts in solutions of transport-dominated equations. One major goal both for the purpose of compression as well as for an efficient analysis is the provision of optimally sparse approximations...... optimally sparse approximations of this model class in 2D as well as 3D. Even more, in contrast to all other directional representation systems, a theory for compactly supported shearlet frames was derived which moreover also satisfy this optimality benchmark. This chapter shall serve as an introduction...... to and a survey about sparse approximations of cartoon-like images by band-limited and also compactly supported shearlet frames as well as a reference for the state-of-the-art of this research field....

Transport of vanadium (V in saturated porous media: effects of pH, ionic-strength and clay mineral

Directory of Open Access Journals (Sweden)

Yulu Wang

2016-10-01

Full Text Available Vanadium, a hazardous pollutant, has been frequently detected in soil and groundwater, however, its transport behavior in porous media were not clearly understood. In this study, the effects of solution pH, ionic strength (IS and the effect of clay mineral on the transport of vanadium in saturated porous media were investigated. Laboratory experiments using a series of columns packed with quartz sand were carried out to explore the retention and transport of vanadium with a range of ionic-strength (0.001–0.1 M and pH (4–8 and two different types of clay minerals montmorillonite and kaolinite. Results of the breakthrough experiments showed that vanadium was highly mobile in the saturated porous media. The increase in pH rendered a higher transport of vanadium in saturated porous media. The study also indicated an easier transfer of vanadium with an increase in IS. Montmorillonite enhanced the mobility of vanadium in the column when compared to kaolinite. A mathematical model based on advection-dispersion equation coupled with equilibrium and kinetic reactions was used to describe the retention and transport of vanadium in the columns very well.

Multilevel sparse functional principal component analysis.

Science.gov (United States)

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

A sparse version of IGA solvers

KAUST Repository

Beck, Joakim; Sangalli, Giancarlo; Tamellini, Lorenzo

2017-01-01

Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90s in the context of the approximation of high-dimensional PDEs. The tests that we report show that, in accordance to the literature, a sparse grids construction can indeed be useful if the solution of the PDE at hand is sufficiently smooth. Sparse grids can also be useful in the case of non-smooth solutions when some a-priori knowledge on the location of the singularities of the solution can be exploited to devise suitable non-equispaced meshes. Finally, we remark that sparse grids can be seen as a simple way to parallelize pre-existing serial IGA solvers in a straightforward fashion, which can be beneficial in many practical situations.

A sparse version of IGA solvers

KAUST Repository

Beck, Joakim

2017-07-30

Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90s in the context of the approximation of high-dimensional PDEs. The tests that we report show that, in accordance to the literature, a sparse grids construction can indeed be useful if the solution of the PDE at hand is sufficiently smooth. Sparse grids can also be useful in the case of non-smooth solutions when some a-priori knowledge on the location of the singularities of the solution can be exploited to devise suitable non-equispaced meshes. Finally, we remark that sparse grids can be seen as a simple way to parallelize pre-existing serial IGA solvers in a straightforward fashion, which can be beneficial in many practical situations.

Language Recognition via Sparse Coding

Science.gov (United States)

2016-09-08

explanation is that sparse coding can achieve a near-optimal approximation of much complicated nonlinear relationship through local and piecewise linear...training examples, where x(i) ∈ RN is the ith example in the batch. Optionally, X can be normalized and whitened before sparse coding for better result...normalized input vectors are then ZCA- whitened [20]. Em- pirically, we choose ZCA- whitening over PCA- whitening , and there is no dimensionality reduction

Valve packing manual. A maintenance application guide

International Nuclear Information System (INIS)

Aikin, J.A.; McCutcheon, R.G.; Cumming, D.

1997-01-01

Since 1970, AECL Chalk River Mechanical Equipment Development (MED) branch has invested over 175 person years in testing related to improving valve packing performance. Successful developments, including, 'live-loading', reduced packing heights, and performance-based packing qualification testing have been implemented. Since 1986, MED and the Integrated Valve Actuator Program Task Force - Valve Packing Steering Committee (IVAP-VPSC) have been involved in the development of combination die-formed graphite packing for use in CANDU plants. Many reports, articles, and specifications have been issued. Due to the large amount of test data and reports, a more user-friendly document has been prepared for everyday use. The Valve Packing Manual is based on many years of MED research and testing, as well as operating experience from CANDU nuclear generating stations (NGS). Since 1986, packing research and testing has been funded by the CANDU Owners Group (COG), the Electric Power Research Institute (EPRI), and participating valve packing manufacturers. The Valve Packing Manual (VPM) provides topical summaries of all work related to valve packing done since 1985. It includes advances in configuration design, stem packing friction, materials specifications, and installation procedures. This paper provides an overview on the application of the VPM with a focus on qualification testing, packing configuration, and stem packing friction. (author)

Sparse seismic imaging using variable projection

NARCIS (Netherlands)

Aravkin, Aleksandr Y.; Tu, Ning; van Leeuwen, Tristan

2013-01-01

We consider an important class of signal processing problems where the signal of interest is known to be sparse, and can be recovered from data given auxiliary information about how the data was generated. For example, a sparse Green's function may be recovered from seismic experimental data using

Tunable Sparse Network Coding for Multicast Networks

DEFF Research Database (Denmark)

Feizi, Soheil; Roetter, Daniel Enrique Lucani; Sørensen, Chres Wiant

2014-01-01

This paper shows the potential and key enabling mechanisms for tunable sparse network coding, a scheme in which the density of network coded packets varies during a transmission session. At the beginning of a transmission session, sparsely coded packets are transmitted, which benefits decoding...... complexity. At the end of a transmission, when receivers have accumulated degrees of freedom, coding density is increased. We propose a family of tunable sparse network codes (TSNCs) for multicast erasure networks with a controllable trade-off between completion time performance to decoding complexity...... a mechanism to perform efficient Gaussian elimination over sparse matrices going beyond belief propagation but maintaining low decoding complexity. Supporting simulation results are provided showing the trade-off between decoding complexity and completion time....

Influence of the ammonium hydroxide concentration in morphological control of meso porous silica particles

International Nuclear Information System (INIS)

Yoon, Sukbon; Jung, Chonghun; Yoon, Inho; Kim, Changki; Choi, Wangkyu; Moon, Jeikwon

2012-01-01

The discovery of new M41S meso porous silica families in 1992 extended the applications into much wider pore ranges, bringing in a new prosperous era in porous material research. The synthesis of these meso porous silicas has been mainly accomplished through a self-assembly between surfactant molecules and inorganic species under various pH conditions. Meanwhile, many studies have been conducted on the application as catalysts, adsorbents, and packing materials for separation columns due to their unique properties such as high specific surface area, large pore volume, tuneable pore size, and narrow pore size distribution. The pore sizes of these materials can be easily controlled by changing the alkyl-chain length of the surfactant used. However, the control of the morphology and the pore structure is not so common. The morphological control of these materials in particular is one of the major challenges for their industrial application. Recently, the meso porous silica materials with various shapes such as fibers, films, polyhedral particles, and spheres have been reported. In our previous study, the core-shell nanoparticles with a silica core and a meso porous shell under basic conditions were synthesized using the silica nanoparticles as a core and tetraethyl orthosilicate (TEOS)-cetyltrimethylammonium bromide (CTABr)-NH 4 OH-H 2 O-C 2 H 5 OH system. In this work, we report the synthesis of the most well known hexagonal MCM-41 among three main mesophases in the M41S families using TEOS-CTABr-NH 4 OH-H 2 O system. Also, in the control of the morphology and pore structure of the meso porous silica materials, the influence of the NH 4 OH concentration was investigated

Sparse PCA with Oracle Property.

Science.gov (United States)

Gu, Quanquan; Wang, Zhaoran; Liu, Han

In this paper, we study the estimation of the k -dimensional sparse principal subspace of covariance matrix Σ in the high-dimensional setting. We aim to recover the oracle principal subspace solution, i.e., the principal subspace estimator obtained assuming the true support is known a priori. To this end, we propose a family of estimators based on the semidefinite relaxation of sparse PCA with novel regularizations. In particular, under a weak assumption on the magnitude of the population projection matrix, one estimator within this family exactly recovers the true support with high probability, has exact rank- k , and attains a [Formula: see text] statistical rate of convergence with s being the subspace sparsity level and n the sample size. Compared to existing support recovery results for sparse PCA, our approach does not hinge on the spiked covariance model or the limited correlation condition. As a complement to the first estimator that enjoys the oracle property, we prove that, another estimator within the family achieves a sharper statistical rate of convergence than the standard semidefinite relaxation of sparse PCA, even when the previous assumption on the magnitude of the projection matrix is violated. We validate the theoretical results by numerical experiments on synthetic datasets.

Structural Sparse Tracking

KAUST Repository

Zhang, Tianzhu; Yang, Ming-Hsuan; Ahuja, Narendra; Ghanem, Bernard; Yan, Shuicheng; Xu, Changsheng; Liu, Si

2015-01-01

candidate. We show that our SST algorithm accommodates most existing sparse trackers with the respective merits. Both qualitative and quantitative evaluations on challenging benchmark image sequences demonstrate that the proposed SST algorithm performs

Technique detection software for Sparse Matrices

Directory of Open Access Journals (Sweden)

KHAN Muhammad Taimoor

2009-12-01

Full Text Available Sparse storage formats are techniques for storing and processing the sparse matrix data efficiently. The performance of these storage formats depend upon the distribution of non-zeros, within the matrix in different dimensions. In order to have better results we need a technique that suits best the organization of data in a particular matrix. So the decision of selecting a better technique is the main step towards improving the system's results otherwise the efficiency can be decreased. The purpose of this research is to help identify the best storage format in case of reduced storage size and high processing efficiency for a sparse matrix.

Sparse Representations of Hyperspectral Images

KAUST Repository

Swanson, Robin J.

2015-11-23

Hyperspectral image data has long been an important tool for many areas of sci- ence. The addition of spectral data yields significant improvements in areas such as object and image classification, chemical and mineral composition detection, and astronomy. Traditional capture methods for hyperspectral data often require each wavelength to be captured individually, or by sacrificing spatial resolution. Recently there have been significant improvements in snapshot hyperspectral captures using, in particular, compressed sensing methods. As we move to a compressed sensing image formation model the need for strong image priors to shape our reconstruction, as well as sparse basis become more important. Here we compare several several methods for representing hyperspectral images including learned three dimensional dictionaries, sparse convolutional coding, and decomposable nonlocal tensor dictionaries. Addi- tionally, we further explore their parameter space to identify which parameters provide the most faithful and sparse representations.

Sparse Representations of Hyperspectral Images

KAUST Repository

Swanson, Robin J.

2015-01-01

Hyperspectral image data has long been an important tool for many areas of sci- ence. The addition of spectral data yields significant improvements in areas such as object and image classification, chemical and mineral composition detection, and astronomy. Traditional capture methods for hyperspectral data often require each wavelength to be captured individually, or by sacrificing spatial resolution. Recently there have been significant improvements in snapshot hyperspectral captures using, in particular, compressed sensing methods. As we move to a compressed sensing image formation model the need for strong image priors to shape our reconstruction, as well as sparse basis become more important. Here we compare several several methods for representing hyperspectral images including learned three dimensional dictionaries, sparse convolutional coding, and decomposable nonlocal tensor dictionaries. Addi- tionally, we further explore their parameter space to identify which parameters provide the most faithful and sparse representations.

Reconstruction of three-dimensional porous media using generative adversarial neural networks

Science.gov (United States)

Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J.

2017-10-01

To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.

Supervised Convolutional Sparse Coding

KAUST Repository

Affara, Lama Ahmed

2018-04-08

Convolutional Sparse Coding (CSC) is a well-established image representation model especially suited for image restoration tasks. In this work, we extend the applicability of this model by proposing a supervised approach to convolutional sparse coding, which aims at learning discriminative dictionaries instead of purely reconstructive ones. We incorporate a supervised regularization term into the traditional unsupervised CSC objective to encourage the final dictionary elements to be discriminative. Experimental results show that using supervised convolutional learning results in two key advantages. First, we learn more semantically relevant filters in the dictionary and second, we achieve improved image reconstruction on unseen data.

Experimental studies on the coolability of packed beds. Flooding of hot dry packed beds

International Nuclear Information System (INIS)

Leininger, S.; Kulenovic, R.; Laurien, E.

2013-01-01

In case of a severe accident in a nuclear power plant meltdown of the reactor core can occur and form a packed bed in the lower plenum of the reactor pressure vessel (RPV) after solidification due to contact with water. The removal of after-heat and the long-term coolability is of essential interest. The efficient injection of cooling water into the packed bed has to be assured without endangering the structural integrity of the reactor pressure vessel. The experiments performed aimed to study the dry-out and the quenching (flooding) of hot dry packed beds. Two different inflow variants, bottom- and top-flooding including the variation of the starting temperature of the packed bed and the injection rate were studied. In case of bottom flooding the quenching time increases with increasing packed bed temperature and decreasing injection rate. In case of top flooding the flow pattern is more complex, in a first phase the water flows preferentially toward the RPV wall, the flow paths conduct the water downwards. The flow resistance of the packed bed increases with increasing bed temperatures. The quenching temperatures increase significantly above average.

Porous Media and Immersed Boundary Hybrid-Modelling for Simulating Flow in Stone Cover-Layers

DEFF Research Database (Denmark)

Jensen, Bjarne; Liu, Xiaofeng; Christensen, Erik Damgaard

In this paper we present a new numerical modelling approach for coastal and marine applications where a porous media conceptual model was combined with a free surface volume-of-fluid (VOF) model and an immersed boundary method (IBM). The immersed boundary model covers the method of describing....... In this paper, the model is applied to investigate two practical cases in terms of a cover layer of stones on a flat bed under oscillatory flow at different packing densities, and a rock toe structure at a breakwater....

Structure-aware Local Sparse Coding for Visual Tracking

KAUST Repository

Qi, Yuankai

2018-01-24

Sparse coding has been applied to visual tracking and related vision problems with demonstrated success in recent years. Existing tracking methods based on local sparse coding sample patches from a target candidate and sparsely encode these using a dictionary consisting of patches sampled from target template images. The discriminative strength of existing methods based on local sparse coding is limited as spatial structure constraints among the template patches are not exploited. To address this problem, we propose a structure-aware local sparse coding algorithm which encodes a target candidate using templates with both global and local sparsity constraints. For robust tracking, we show local regions of a candidate region should be encoded only with the corresponding local regions of the target templates that are the most similar from the global view. Thus, a more precise and discriminative sparse representation is obtained to account for appearance changes. To alleviate the issues with tracking drifts, we design an effective template update scheme. Extensive experiments on challenging image sequences demonstrate the effectiveness of the proposed algorithm against numerous stateof- the-art methods.

Major factors influencing the generation of natural gas hydrate in porous media

Directory of Open Access Journals (Sweden)

V.N. Khlebnikov

2017-11-01

Full Text Available Current researches related to natural gas hydrate mainly focus on its physical and chemical properties, as well as the approaches to the production (decomposition of hydrate. Physical modeling of the flow process in hydrate deposits is critical to the study on the exploitation or decomposition of hydrate. However, investigation of the dynamic hydrate process by virtue of porous media like sand-packed tubes which are widely used in petroleum production research is rarely reported in literature. In this paper, physical simulation of methane hydrate generation process was conducted using river sand-packed tubes in the core displacement apparatus. During the simulation, the influences of parameters such as reservoir temperature, methane pressure and reservoir model properties on the process of hydrate generation were investigated. The following results are revealed. First, the use of ice-melted water as the immobile water in the reservoir model can significantly enhance the rate of methane hydrate generation. Second, the process driving force in porous media (i.e., extents to which the experimental pressure or temperature deviating those corresponding to the hydrate phase equilibrium plays a key role in the generation of methane hydrate. Third, the induction period of methane hydrate generation almost does not change with temperature or pressure when the methane pressure is above 1.4 folds of the hydrate phase equilibrium pressure or the laboratory temperature is lower than the phase equilibrium temperature by 3 °C or more. Fourth, the parameters such as permeability, water saturation and wettability don't have much influence on the generation of methane hydrate.

Simulation of capillary infiltration into packing structures for the optimization of ceramic materials using the lattice Boltzmann method

Directory of Open Access Journals (Sweden)

Danilo Sergi

2016-01-01

Full Text Available This study uses the lattice Boltzmann method (LBM to simulate in 2D the capillary infiltration into porous structures obtained from the packing of particles. The experimental problem motivating the work is the densification of carbon preforms by reactive melt infiltration. The aim is to determine the optimization principles for the manufacturing of high-performance ceramics. Simulations are performed for packings with varying structural properties. The results suggest that the observed slow infiltrations can be ascribed to interface dynamics. Pinning represents the primary factor retarding fluid penetration. The mechanism responsible for this phenomenon is analyzed in detail. When surface growth is allowed, it is found that the phenomenon of pinning becomes stronger. Systems trying to reproduce typical experimental conditions are also investigated. It turns out that the standard for accurate simulations is challenging. The primary obstacle to overcome for enhanced accuracy seems to be the over-occurrence of pinning.

Sparse Frequency Waveform Design for Radar-Embedded Communication

Directory of Open Access Journals (Sweden)

Chaoyun Mai

2016-01-01

Full Text Available According to the Tag application with function of covert communication, a method for sparse frequency waveform design based on radar-embedded communication is proposed. Firstly, sparse frequency waveforms are designed based on power spectral density fitting and quasi-Newton method. Secondly, the eigenvalue decomposition of the sparse frequency waveform sequence is used to get the dominant space. Finally the communication waveforms are designed through the projection of orthogonal pseudorandom vectors in the vertical subspace. Compared with the linear frequency modulation waveform, the sparse frequency waveform can further improve the bandwidth occupation of communication signals, thus achieving higher communication rate. A certain correlation exists between the reciprocally orthogonal communication signals samples and the sparse frequency waveform, which guarantees the low SER (signal error rate and LPI (low probability of intercept. The simulation results verify the effectiveness of this method.

Optimized packings with applications

CERN Document Server

Pintér, János

2015-01-01

This volume presents a selection of case studies that address a substantial range of optimized object packings (OOP) and their applications. The contributing authors are well-recognized researchers and practitioners. The mathematical modelling and numerical solution aspects of each application case study are presented in sufficient detail. A broad range of OOP problems are discussed: these include various specific and non-standard container loading and object packing problems, as well as the stowing of hazardous and other materials on container ships, data centre resource management, automotive engineering design, space station logistic support, cutting and packing problems with placement constraints, the optimal design of LED street lighting, robust sensor deployment strategies, spatial scheduling problems, and graph coloring models and metaheuristics for packing applications. Novel points of view related to model development and to computational nonlinear, global, mixed integer optimization and heuristic st...

An on-line estimation of battery pack parameters and state-of-charge using dual filters based on pack model

International Nuclear Information System (INIS)

Zhang, Xu; Wang, Yujie; Yang, Duo; Chen, Zonghai

2016-01-01

Accurate estimation of battery pack state-of-charge plays a very important role for electric vehicles, which directly reflects the behavior of battery pack usage. However, the inconsistency of battery makes the estimation of battery pack state-of-charge different from single cell. In this paper, to estimate the battery pack state-of-charge on-line, the definition of battery pack is proposed, and the relationship between the total available capacity of battery pack and single cell is put forward to analyze the energy efficiency influenced by battery inconsistency, then a lumped parameter battery model is built up to describe the dynamic behavior of battery pack. Furthermore, the extend Kalman filter-unscented Kalman filter algorithm is developed to identify the parameters of battery pack and forecast state-of-charge concurrently. The extend Kalman filter is applied to update the battery pack parameters by real-time measured data, while the unscented Kalman filter is employed to estimate the battery pack state-of-charge. Finally, the proposed approach is verified by experiments operated on the lithium-ion battery under constant current condition and the dynamic stress test profiles. Experimental results indicate that the proposed method can estimate the battery pack state-of-charge with high accuracy. - Highlights: • A novel space state equation is built to describe the pack dynamic behavior. • The dual filters method is used to estimate the pack state-of-charge. • Battery inconsistency is considered to analyze the pack usage efficiency. • The accuracy of the proposed method is verified under different conditions.

Massive Asynchronous Parallelization of Sparse Matrix Factorizations

Energy Technology Data Exchange (ETDEWEB)

Chow, Edmond [Georgia Inst. of Technology, Atlanta, GA (United States)

2018-01-08

Solving sparse problems is at the core of many DOE computational science applications. We focus on the challenge of developing sparse algorithms that can fully exploit the parallelism in extreme-scale computing systems, in particular systems with massive numbers of cores per node. Our approach is to express a sparse matrix factorization as a large number of bilinear constraint equations, and then solving these equations via an asynchronous iterative method. The unknowns in these equations are the matrix entries of the factorization that is desired.

Packing Degenerate Graphs Greedily

Czech Academy of Sciences Publication Activity Database

Allen, P.; Böttcher, J.; Hladký, J.; Piguet, Diana

2017-01-01

Roč. 61, August (2017), s. 45-51 ISSN 1571-0653 R&D Projects: GA ČR GJ16-07822Y Institutional support: RVO:67985807 Keywords : tree packing conjecture * graph packing * graph processes Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics

Heuristics for Multidimensional Packing Problems

DEFF Research Database (Denmark)

Egeblad, Jens

for a minimum height container required for the items. The main contributions of the thesis are three new heuristics for strip-packing and knapsack packing problems where items are both rectangular and irregular. In the two first papers we describe a heuristic for the multidimensional strip-packing problem...... that is based on a relaxed placement principle. The heuristic starts with a random overlapping placement of items and large container dimensions. From the overlapping placement overlap is reduced iteratively until a non-overlapping placement is found and a new problem is solved with a smaller container size...... of this heuristic are among the best published in the literature both for two- and three-dimensional strip-packing problems for irregular shapes. In the third paper, we introduce a heuristic for two- and three-dimensional rectangular knapsack packing problems. The two-dimensional heuristic uses the sequence pair...

3D hierarchically porous Cu-BiOCl nanocomposite films: one-step electrochemical synthesis, structural characterization and nanomechanical and photoluminescent properties

Science.gov (United States)

Guerrero, Miguel; Pané, Salvador; Nelson, Bradley J.; Baró, Maria Dolors; Roldán, Mònica; Sort, Jordi; Pellicer, Eva

2013-11-01

Three-dimensional (3D) hierarchically porous composite Cu-BiOCl films have been prepared by a facile one-step galvanostatic electrodeposition process from acidic electrolytic solutions containing Cu(ii) and Bi(iii) chloride salts and Triton X-100. The films show spherical, micron-sized pores that spread over the whole film thickness. In turn, the pore walls are made of randomly packed BiOCl nanoplates that are assembled leaving micro-nanopore voids beneath. It is believed that Cu grows within the interstitial spaces between the hydrogen bubbles produced from the reduction of H+ ions. Then, the BiOCl sheets accommodate in the porous network defined by the Cu building blocks. The presence of Cu tends to enhance the mechanical stability of the composite material. The resulting porous Cu-BiOCl films exhibit homogeneous and stable-in-time photoluminescent response arising from the BiOCl component that spreads over the entire 3D porous structure, as demonstrated by confocal scanning laser microscopy. A broad-band emission covering the entire visible range, in the wavelength interval 450-750 nm, is obtained. The present work paves the way for the facile and controlled preparation of a new generation of photoluminescent membranes.Three-dimensional (3D) hierarchically porous composite Cu-BiOCl films have been prepared by a facile one-step galvanostatic electrodeposition process from acidic electrolytic solutions containing Cu(ii) and Bi(iii) chloride salts and Triton X-100. The films show spherical, micron-sized pores that spread over the whole film thickness. In turn, the pore walls are made of randomly packed BiOCl nanoplates that are assembled leaving micro-nanopore voids beneath. It is believed that Cu grows within the interstitial spaces between the hydrogen bubbles produced from the reduction of H+ ions. Then, the BiOCl sheets accommodate in the porous network defined by the Cu building blocks. The presence of Cu tends to enhance the mechanical stability of the

Valve-stem-packing improvement study. Final report

International Nuclear Information System (INIS)

Adey, C.W.; Klein, J.J.

1982-08-01

By employing questionnaires and face-to-face interviews with valve and valve packing manufacturers, as well as nuclear plant personnel, an understanding of valve stem packing leakage problems from each of the three viewpoints was developed. This information, in-house experience, and available technical literature were used to develop specific recommendations for valve manufacturers, valve packing manufacturers, and nuclear plant valve users. It was generally recommended that each these groups make better use of graphite packing. The questionnaires and interviews indicated that increased usage of graphite packing over the last few years has reduced the incidence of valve packing problems. To confirm this, a survey of Licensee Event Reports (LERs) from 1972 to 1980 was undertaken using the keywords Valve and Packing. A statistical analysis of the LER data confirms that the adoption of graphite packing has significantly reduced valve stem leakage

Optical performance of hybrid porous silicon-porous alumina multilayers

Science.gov (United States)

Cencha, L. G.; Antonio Hernández, C.; Forzani, L.; Urteaga, R.; Koropecki, R. R.

2018-05-01

In this work, we study the optical response of structures involving porous silicon and porous alumina in a multi-layered hybrid structure. We performed a rational design of the optimal sequence necessary to produce a high transmission and selective filter, with potential applications in chemical and biosensors. The combination of these porous materials can be used to exploit its distinguishing features, i.e., high transparency of alumina and high refractive index of porous silicon. We assembled hybrid microcavities with a central porous alumina layer between two porous silicon Bragg reflectors. In this way, we constructed a Fabry-Perot resonator with high reflectivity and low absorption that improves the quality of the filter compared to a microcavity built only with porous silicon or porous alumina. We explored a simpler design in which one of the Bragg reflectors is replaced by the aluminium that remains bound to the alumina after its fabrication. We theoretically explored the potential of the proposal and its limitations when considering the roughness of the layers. We found that the quality of a microcavity made entirely with porous silicon shows a limit in the visible range due to light absorption. This limitation is overcome in the hybrid scheme, with the roughness of the layers determining the ultimate quality. Q-factors of 220 are experimentally obtained for microcavities supported on aluminium, while Q-factors around 600 are reached for microcavities with double Bragg reflectors, centred at 560 nm. This represents a four-fold increase with respect to the optimal porous silicon microcavity at this wavelength.

Co-current descending two-phase flows in inclined packed beds : experiments versus simulations

Energy Technology Data Exchange (ETDEWEB)

Atta, A.; Nigam, K.D.P.; Roy, S. [Inst. of Technology, New Delhi (India). Dept. of Chemical Engineering; Schubert, M.; Larachi, F. [Laval Univ., Quebec City, PQ (Canada). Dept. of Chemical Engineering

2010-10-15

This paper presented a numerical simulation for an inclined packed bed configuration for two-phase co-current downward flow. A two-phase Eulerian computational fluid dynamics (CFD) model was used to predict the hydrodynamic behaviour. Two different modelling strategies were compared, notably a straight tube with an artificially inclined gravity, and an inclined geometry with straight gravity. The effect of inclination angle of a packed bed on its gas-liquid flow segregation and liquid saturation spatial distribution was measured for varying inclinations and fluid velocities. The CFD model was adapted from a trickle-bed vertical configuration and based on the porous media concept. The predicted pressure drops for the inclined gravity were found to be insensitive to inclination. Therefore, simulations to study the parameters that influence the reduced liquid saturation were performed only with the inclined geometry case. Experimental data obtained using electrical capacitance tomography was used to validate the model predictions. The study showed that a trickle bed CFD model for vertically straight reactors can be effectively implemented in inclined reactor geometries. However, additional research is needed to formulate appropriate drag force closures which should be incorporated in the CFD model for improved quantitative estimation of inclined bed hydrodynamics. 22 refs., 10 figs.

Storage of sparse files using parallel log-structured file system

Science.gov (United States)

Bent, John M.; Faibish, Sorin; Grider, Gary; Torres, Aaron

2017-11-07

A sparse file is stored without holes by storing a data portion of the sparse file using a parallel log-structured file system; and generating an index entry for the data portion, the index entry comprising a logical offset, physical offset and length of the data portion. The holes can be restored to the sparse file upon a reading of the sparse file. The data portion can be stored at a logical end of the sparse file. Additional storage efficiency can optionally be achieved by (i) detecting a write pattern for a plurality of the data portions and generating a single patterned index entry for the plurality of the patterned data portions; and/or (ii) storing the patterned index entries for a plurality of the sparse files in a single directory, wherein each entry in the single directory comprises an identifier of a corresponding sparse file.

Sparse reconstruction using distribution agnostic bayesian matching pursuit

KAUST Repository

Masood, Mudassir

2013-11-01

A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data if not available. The method utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean-square error (MMSE) estimate of the sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.

Image understanding using sparse representations

CERN Document Server

Thiagarajan, Jayaraman J; Turaga, Pavan; Spanias, Andreas

2014-01-01

Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blin

Sparse regularization for force identification using dictionaries

Science.gov (United States)

Qiao, Baijie; Zhang, Xingwu; Wang, Chenxi; Zhang, Hang; Chen, Xuefeng

2016-04-01

The classical function expansion method based on minimizing l2-norm of the response residual employs various basis functions to represent the unknown force. Its difficulty lies in determining the optimum number of basis functions. Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions. The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process. First, according to the profile of the unknown force, the dictionary composed of basis functions is determined. Second, a sparsity convex optimization model for force identification is constructed. Third, given the transfer function and the operational response, Sparse reconstruction by separable approximation (SpaRSA) is developed to solve the sparse regularization problem of force identification. Finally, experiments including identification of impact and harmonic forces are conducted on a cantilever thin plate structure to illustrate the effectiveness and applicability of SpaRSA. Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame. The discrete cosine functions can also successfully reconstruct the harmonic forces including the sinusoidal, square and triangular forces. Conversely, the traditional Tikhonov regularization method with the L-curve criterion fails to identify both the impact and harmonic forces in these cases.

Complications of balloon packing in epistaxis

NARCIS (Netherlands)

Vermeeren, Lenka; Derks, Wynia; Fokkens, Wytske; Menger, Dirk Jan

2015-01-01

Although balloon packing appears to be efficient to control epistaxis, severe local complications can occur. We describe four patients with local lesions after balloon packing. Prolonged balloon packing can cause damage to nasal mucosa, septum and alar skin (nasal mucosa, the cartilaginous skeleton

High-Throughput Image Analysis of Fibrillar Materials: A Case Study on Polymer Nanofiber Packing, Alignment, and Defects in Organic Field Effect Transistors.

Science.gov (United States)

Persson, Nils E; Rafshoon, Joshua; Naghshpour, Kaylie; Fast, Tony; Chu, Ping-Hsun; McBride, Michael; Risteen, Bailey; Grover, Martha; Reichmanis, Elsa

2017-10-18

High-throughput discovery of process-structure-property relationships in materials through an informatics-enabled empirical approach is an increasingly utilized technique in materials research due to the rapidly expanding availability of data. Here, process-structure-property relationships are extracted for the nucleation, growth, and deposition of semiconducting poly(3-hexylthiophene) (P3HT) nanofibers used in organic field effect transistors, via high-throughput image analysis. This study is performed using an automated image analysis pipeline combining existing open-source software and new algorithms, enabling the rapid evaluation of structural metrics for images of fibrillar materials, including local orientational order, fiber length density, and fiber length distributions. We observe that microfluidic processing leads to fibers that pack with unusually high density, while sonication yields fibers that pack sparsely with low alignment. This is attributed to differences in their crystallization mechanisms. P3HT nanofiber packing during thin film deposition exhibits behavior suggesting that fibers are confined to packing in two-dimensional layers. We find that fiber alignment, a feature correlated with charge carrier mobility, is driven by increasing fiber length, and that shorter fibers tend to segregate to the buried dielectric interface during deposition, creating potentially performance-limiting defects in alignment. Another barrier to perfect alignment is the curvature of P3HT fibers; we propose a mechanistic simulation of fiber growth that reconciles both this curvature and the log-normal distribution of fiber lengths inherent to the fiber populations under consideration.

Hypostatic jammed packings of frictionless nonspherical particles

Science.gov (United States)

VanderWerf, Kyle; Jin, Weiwei; Shattuck, Mark D.; O'Hern, Corey S.

2018-01-01

We perform computational studies of static packings of a variety of nonspherical particles including circulo-lines, circulo-polygons, ellipses, asymmetric dimers, dumbbells, and others to determine which shapes form packings with fewer contacts than degrees of freedom (hypostatic packings) and which have equal numbers of contacts and degrees of freedom (isostatic packings), and to understand why hypostatic packings of nonspherical particles can be mechanically stable despite having fewer contacts than that predicted from naive constraint counting. To generate highly accurate force- and torque-balanced packings of circulo-lines and cir-polygons, we developed an interparticle potential that gives continuous forces and torques as a function of the particle coordinates. We show that the packing fraction and coordination number at jamming onset obey a masterlike form for all of the nonspherical particle packings we studied when plotted versus the particle asphericity A , which is proportional to the ratio of the squared perimeter to the area of the particle. Further, the eigenvalue spectra of the dynamical matrix for packings of different particle shapes collapse when plotted at the same A . For hypostatic packings of nonspherical particles, we verify that the number of "quartic" modes along which the potential energy increases as the fourth power of the perturbation amplitude matches the number of missing contacts relative to the isostatic value. We show that the fourth derivatives of the total potential energy in the directions of the quartic modes remain nonzero as the pressure of the packings is decreased to zero. In addition, we calculate the principal curvatures of the inequality constraints for each contact in circulo-line packings and identify specific types of contacts with inequality constraints that possess convex curvature. These contacts can constrain multiple degrees of freedom and allow hypostatic packings of nonspherical particles to be mechanically

Sparse inpainting and isotropy

Energy Technology Data Exchange (ETDEWEB)

Feeney, Stephen M.; McEwen, Jason D.; Peiris, Hiranya V. [Department of Physics and Astronomy, University College London, Gower Street, London, WC1E 6BT (United Kingdom); Marinucci, Domenico; Cammarota, Valentina [Department of Mathematics, University of Rome Tor Vergata, via della Ricerca Scientifica 1, Roma, 00133 (Italy); Wandelt, Benjamin D., E-mail: s.feeney@imperial.ac.uk, E-mail: marinucc@axp.mat.uniroma2.it, E-mail: jason.mcewen@ucl.ac.uk, E-mail: h.peiris@ucl.ac.uk, E-mail: wandelt@iap.fr, E-mail: cammarot@axp.mat.uniroma2.it [Kavli Institute for Theoretical Physics, Kohn Hall, University of California, 552 University Road, Santa Barbara, CA, 93106 (United States)

2014-01-01

Sparse inpainting techniques are gaining in popularity as a tool for cosmological data analysis, in particular for handling data which present masked regions and missing observations. We investigate here the relationship between sparse inpainting techniques using the spherical harmonic basis as a dictionary and the isotropy properties of cosmological maps, as for instance those arising from cosmic microwave background (CMB) experiments. In particular, we investigate the possibility that inpainted maps may exhibit anisotropies in the behaviour of higher-order angular polyspectra. We provide analytic computations and simulations of inpainted maps for a Gaussian isotropic model of CMB data, suggesting that the resulting angular trispectrum may exhibit small but non-negligible deviations from isotropy.

Object tracking by occlusion detection via structured sparse learning

KAUST Repository

Zhang, Tianzhu

2013-06-01

Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object\\'s track. This is the case when significant occlusion occurs. To accommodate for non-sparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker consistently outperforms the state-of-the-art. © 2013 IEEE.

Sparse Vector Distributions and Recovery from Compressed Sensing

DEFF Research Database (Denmark)

Sturm, Bob L.

It is well known that the performance of sparse vector recovery algorithms from compressive measurements can depend on the distribution underlying the non-zero elements of a sparse vector. However, the extent of these effects has yet to be explored, and formally presented. In this paper, I...... empirically investigate this dependence for seven distributions and fifteen recovery algorithms. The two morals of this work are: 1) any judgement of the recovery performance of one algorithm over that of another must be prefaced by the conditions for which this is observed to be true, including sparse vector...... distributions, and the criterion for exact recovery; and 2) a recovery algorithm must be selected carefully based on what distribution one expects to underlie the sensed sparse signal....

Exhaustive Search for Sparse Variable Selection in Linear Regression

Science.gov (United States)

Igarashi, Yasuhiko; Takenaka, Hikaru; Nakanishi-Ohno, Yoshinori; Uemura, Makoto; Ikeda, Shiro; Okada, Masato

2018-04-01

We propose a K-sparse exhaustive search (ES-K) method and a K-sparse approximate exhaustive search method (AES-K) for selecting variables in linear regression. With these methods, K-sparse combinations of variables are tested exhaustively assuming that the optimal combination of explanatory variables is K-sparse. By collecting the results of exhaustively computing ES-K, various approximate methods for selecting sparse variables can be summarized as density of states. With this density of states, we can compare different methods for selecting sparse variables such as relaxation and sampling. For large problems where the combinatorial explosion of explanatory variables is crucial, the AES-K method enables density of states to be effectively reconstructed by using the replica-exchange Monte Carlo method and the multiple histogram method. Applying the ES-K and AES-K methods to type Ia supernova data, we confirmed the conventional understanding in astronomy when an appropriate K is given beforehand. However, we found the difficulty to determine K from the data. Using virtual measurement and analysis, we argue that this is caused by data shortage.

A Sparse Approximate Inverse Preconditioner for Nonsymmetric Linear Systems

Czech Academy of Sciences Publication Activity Database

Benzi, M.; Tůma, Miroslav

1998-01-01

Roč. 19, č. 3 (1998), s. 968-994 ISSN 1064-8275 R&D Projects: GA ČR GA201/93/0067; GA AV ČR IAA230401 Keywords : large sparse systems * interative methods * preconditioning * approximate inverse * sparse linear systems * sparse matrices * incomplete factorizations * conjugate gradient -type methods Subject RIV: BA - General Mathematics Impact factor: 1.378, year: 1998

Geometric Models for Isotropic Random Porous Media: A Review

Directory of Open Access Journals (Sweden)

Helmut Hermann

2014-01-01

Full Text Available Models for random porous media are considered. The models are isotropic both from the local and the macroscopic point of view; that is, the pores have spherical shape or their surface shows piecewise spherical curvature, and there is no macroscopic gradient of any geometrical feature. Both closed-pore and open-pore systems are discussed. The Poisson grain model, the model of hard spheres packing, and the penetrable sphere model are used; variable size distribution of the pores is included. A parameter is introduced which controls the degree of open-porosity. Besides systems built up by a single solid phase, models for porous media with the internal surface coated by a second phase are treated. Volume fraction, surface area, and correlation functions are given explicitly where applicable; otherwise numerical methods for determination are described. Effective medium theory is applied to calculate physical properties for the models such as isotropic elastic moduli, thermal and electrical conductivity, and static dielectric constant. The methods presented are exemplified by applications: small-angle scattering of systems showing fractal-like behavior in limited ranges of linear dimension, optimization of nanoporous insulating materials, and improvement of properties of open-pore systems by atomic layer deposition of a second phase on the internal surface.

HPLC-CUPRAC post-column derivatization method for the determination of antioxidants: a performance comparison between porous silica and core-shell column packing.

Science.gov (United States)

Haque, Syed A; Cañete, Socrates Jose P

2018-01-01

An HPLC method employing a post-column derivatization strategy using the cupric reducing antioxidant capacity reagent (CUPRAC reagent) for the determining antioxidants in plant-based materials leverages the separation capability of regular HPLC approaches while allowing for detection specificity for antioxidants. Three different column types, namely core-shell and porous silica including two chemically different core-shell materials (namely phenyl-hexyl and C18), were evaluated to assess potential improvements that could be attained by changing from a porous silica matrix to a core-shell matrix. Tea extracts were used as sample matrices for the evaluation specifically looking at catechin and epigallocatechin gallate (EGCG). Both the C18 and phenyl-hexyl core-shell columns showed better performance compared to the C18 porous silica one in terms of separation, peak shape, and retention time. Among the two core-shell materials, the phenyl-hexyl column showed better resolving power compared to the C18 column. The CUPRAC post-column derivatization method can be improved using core-shell columns and suitable for quantifying antioxidants, exemplified by catechin and EGCG, in tea samples.

Development of Numerical Technique to Analyze the Flow Characteristics of Porous Media Using Lattice Boltzmann Method

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyung Min [Kyonggi Univ., Suwon (Korea, Republic of)

2016-11-15

The performance of proton exchange membrane fuel cells (PEMFC) is strongly related to the water flow and accumulation in the gas diffusion layer (GDL) and catalyst layer. Understanding the behavior of fluid from the characteristics of the media is crucial for the improvement of the performance and design of the GDL. In this paper, a numerical method is proposed to calculate the design parameters of the GDL, i.e., permeability, tortuosity, and effective diffusivity. The fluid flow in a channel filled with randomly packed hard spheres is simulated to validate the method. The flow simulation was performed by lattice Boltzmann method with bounce back condition for the solid volume fraction in the porous media, with different values of porosities. Permeability, which affects the flow, was calculated from the average pressure drop and the velocity in the porous media. Tortuosity, calculated by the ratio the average path length of the randomly injected massless particles to the thickness of the porous media, and the resultant effective diffusivity were in good agreement with the theoretical model. The suggested method can be used to calculate the parameters of real GDL accurately without any modification.

Development of a leadership resource pack

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-07-01

The pack contains notes and presentation material for OSD inspectors to help them prepare for health and safety discussions with senior managers. The successful application of the leadership resource pack depends on an inspector gaining familiarity with the contents of the pack. Flexibility and adaptability were considered crucial factors in developing the contents. The pack is not considered a substitute for an inspector's own experience, knowledge or substitute for prior research. The leadership resource pack is intended as a source of knowledge and good practice that demonstrates how positive leadership can drive a health and safety agenda alongside business considerations. The benefits of the leadership resource pack include: the creation of a flexible tool that inspectors can use to highlight key leadership messages in health and safety; the development of a seven-stage model for characterising senior management commitment; practical examples of how leadership in health and safety management was felt throughout nine organisations; ideas for devising an aide memoire for specific discussions with senior managers. (author)

Structure-based bayesian sparse reconstruction

KAUST Repository

Quadeer, Ahmed Abdul

2012-12-01

Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical information (Gaussian or otherwise) to obtain near optimal estimates. In addition, we make use of the rich structure of the sensing matrix encountered in many signal processing applications to develop a fast sparse recovery algorithm. The computational complexity of the proposed algorithm is very low compared with the widely used convex relaxation methods as well as greedy matching pursuit techniques, especially at high sparsity. © 1991-2012 IEEE.

Greedy vs. L1 convex optimization in sparse coding

DEFF Research Database (Denmark)

Ren, Huamin; Pan, Hong; Olsen, Søren Ingvor

2015-01-01

Sparse representation has been applied successfully in many image analysis applications, including abnormal event detection, in which a baseline is to learn a dictionary from the training data and detect anomalies from its sparse codes. During this procedure, sparse codes which can be achieved...... solutions. Considering the property of abnormal event detection, i.e., only normal videos are used as training data due to practical reasons, effective codes in classification application may not perform well in abnormality detection. Therefore, we compare the sparse codes and comprehensively evaluate...... their performance from various aspects to better understand their applicability, including computation time, reconstruction error, sparsity, detection...

Migration study of americium in porous medium

International Nuclear Information System (INIS)

Tanaka, Tadao; Ogawa, Hiromichi

1999-01-01

Migration experiments of 241 Am 3+ had been performed by a column system, to investigate migration behavior of 241 Am through a column packed porous sedimentary materials: a coastal sandy soil and a reddish soil. Most 241 Am loaded into the column packed the reddish soil sorbed on the influent edge of the column. In the case of the sandy soil, however, considerable amount of 241 Am was passed through the column. This shows that there is colloidal 241 Am species which may move without effective interaction with the sandy soil. Such a migration behavior of colloidal 241 Am in the sandy soil column could be evaluated by a sorption model based on filtration theory. Sorption mechanisms of 241 Am on the sedimentary materials were examined by a chemical extraction method, for 241 Am sorbed on the sandy soil and the reddish soil at any sections in the column. The 241 Am sorbed on the reddish soil was mainly controlled by a reversible ion exchange reaction. On the other hand, the 241 Am sorbed on the sandy soil ws controlled by irreversible reactions, such as the selective chemical sorptions onto Fe and Mn oxyhydroxide/oxide. The experimental results support that the migration of 241 Am in the reddish soil layer can be estimated by using the K d , whereas that in the sandy soil can not be explained by the K d concept. (author)

A sparse matrix based full-configuration interaction algorithm

International Nuclear Information System (INIS)

Rolik, Zoltan; Szabados, Agnes; Surjan, Peter R.

2008-01-01

We present an algorithm related to the full-configuration interaction (FCI) method that makes complete use of the sparse nature of the coefficient vector representing the many-electron wave function in a determinantal basis. Main achievements of the presented sparse FCI (SFCI) algorithm are (i) development of an iteration procedure that avoids the storage of FCI size vectors; (ii) development of an efficient algorithm to evaluate the effect of the Hamiltonian when both the initial and the product vectors are sparse. As a result of point (i) large disk operations can be skipped which otherwise may be a bottleneck of the procedure. At point (ii) we progress by adopting the implementation of the linear transformation by Olsen et al. [J. Chem Phys. 89, 2185 (1988)] for the sparse case, getting the algorithm applicable to larger systems and faster at the same time. The error of a SFCI calculation depends only on the dropout thresholds for the sparse vectors, and can be tuned by controlling the amount of system memory passed to the procedure. The algorithm permits to perform FCI calculations on single node workstations for systems previously accessible only by supercomputers

Porous organic cages

Science.gov (United States)

Tozawa, Tomokazu; Jones, James T. A.; Swamy, Shashikala I.; Jiang, Shan; Adams, Dave J.; Shakespeare, Stephen; Clowes, Rob; Bradshaw, Darren; Hasell, Tom; Chong, Samantha Y.; Tang, Chiu; Thompson, Stephen; Parker, Julia; Trewin, Abbie; Bacsa, John; Slawin, Alexandra M. Z.; Steiner, Alexander; Cooper, Andrew I.

2009-12-01

Porous materials are important in a wide range of applications including molecular separations and catalysis. We demonstrate that covalently bonded organic cages can assemble into crystalline microporous materials. The porosity is prefabricated and intrinsic to the molecular cage structure, as opposed to being formed by non-covalent self-assembly of non-porous sub-units. The three-dimensional connectivity between the cage windows is controlled by varying the chemical functionality such that either non-porous or permanently porous assemblies can be produced. Surface areas and gas uptakes for the latter exceed comparable molecular solids. One of the cages can be converted by recrystallization to produce either porous or non-porous polymorphs with apparent Brunauer-Emmett-Teller surface areas of 550 and 23m2g-1, respectively. These results suggest design principles for responsive porous organic solids and for the modular construction of extended materials from prefabricated molecular pores.

Mechanised packing for longwall coal faces. Monolithic packing and powered supports for the packhole

Energy Technology Data Exchange (ETDEWEB)

Carr, F; Kitching, F

1978-11-01

If full advantage is to be taken of the great advances that have taken place in power loading and powered support at the coalface, other operations in that vicinity must be similarly mechanised and automated. The gateside packing is one of the most important of these ancillary operations on the longwall face, and in previous articles F. Carr and F. Kitching, National Coal Board Headquarters, Coalface Operations Mining Engineers have given a very comprehensive resume of the present situation. Subjects covered include the requirements of mechanised packing, the parameters involved, the various working arrangements, the different systems of gate-ends, the types of equipment that are being used, their characteristics, the spread of their application, and the results obtained from them. In this article the authors conclude their survey by dealing with dirt/cement and anhydrite packing, by taking a hard look at powered supports for the packhole, and by expressing their views on the way mechanised packing may be expected to develop in the future.

An in-depth study of sparse codes on abnormality detection

DEFF Research Database (Denmark)

Ren, Huamin; Pan, Hong; Olsen, Søren Ingvor

2016-01-01

Sparse representation has been applied successfully in abnormal event detection, in which the baseline is to learn a dictionary accompanied by sparse codes. While much emphasis is put on discriminative dictionary construction, there are no comparative studies of sparse codes regarding abnormality...... are carried out from various angles to better understand the applicability of sparse codes, including computation time, reconstruction error, sparsity, detection accuracy, and their performance combining various detection methods. The experiment results show that combining OMP codes with maximum coordinate...

Sparse Principal Component Analysis in Medical Shape Modeling

DEFF Research Database (Denmark)

Sjöstrand, Karl; Stegmann, Mikkel Bille; Larsen, Rasmus

2006-01-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims...... analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of sufficiently small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA...

Sparse reconstruction using distribution agnostic bayesian matching pursuit

KAUST Repository

Masood, Mudassir; Al-Naffouri, Tareq Y.

2013-01-01

A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics

Electrochemical performance of porous diamond-like carbon electrodes for sensing hormones, neurotransmitters, and endocrine disruptors.

Science.gov (United States)

Silva, Tiago A; Zanin, Hudson; May, Paul W; Corat, Evaldo J; Fatibello-Filho, Orlando

2014-12-10

Porous diamond-like carbon (DLC) electrodes have been prepared, and their electrochemical performance was explored. For electrode preparation, a thin DLC film was deposited onto a densely packed forest of highly porous, vertically aligned multiwalled carbon nanotubes (VACNT). DLC deposition caused the tips of the carbon nanotubes to clump together to form a microstructured surface with an enlarged surface area. DLC:VACNT electrodes show fast charge transfer, which is promising for several electrochemical applications, including electroanalysis. DLC:VACNT electrodes were applied to the determination of targeted molecules such as dopamine (DA) and epinephrine (EP), which are neurotransmitters/hormones, and acetaminophen (AC), an endocrine disruptor. Using simple and low-cost techniques, such as cyclic voltammetry, analytical curves in the concentration range from 10 to 100 μmol L(-1) were obtained and excellent analytical parameters achieved, including high analytical sensitivity, good response stability, and low limits of detection of 2.9, 4.5, and 2.3 μmol L(-1) for DA, EP, and AC, respectively.

Hypostatic jammed packings of frictionless nonspherical particles

OpenAIRE

VanderWerf, Kyle; Jin, Weiwei; Shattuck, Mark D.; O'Hern, Corey S.

2017-01-01

We perform computational studies of static packings of a variety of nonspherical particles including circulo-lines, circulo-polygons, ellipses, asymmetric dimers, and dumbbells to determine which shapes form hypostatic versus isostatic packings and to understand why hypostatic packings of nonspherical particles can be mechanically stable despite having fewer contacts than that predicted from na\\"ive constraint counting. To generate highly accurate force- and torque-balanced packings of circul...

Activity behavior of a HPLC column including α-chymotrypsin immobilized monosized-porous particles

International Nuclear Information System (INIS)

Bilici, Z.; Camli, S.T.; Unsal, E.; Tuncel, A.

2004-01-01

In this study, a polymer-based, α-chymotrypsin (CT) immobilized HPLC column was prepared as a potential material for affinity-HPLC and chiral separation applications. Monosized-macroporous particles were synthesized as the support material by a relatively new polymerization protocol, the so-called, 'modified seeded polymerization'. The particles were obtained in the form of styrene-glycidyl methacrylate- divinylbenzene terpolymer approximately 11 μm in size. The particles were treated with aqueous ammonia to have primary amine groups on the porous surface. The amine functionalized particles were reacted by glutaraldehyde and the enzyme, CT, was covalently attached. CT carrying monosized-porous particles were slurry packed into the HPLC column 50 mmx4.6 mm in size. Since the activity behavior of immobilized CT played an important role in the enantiomeric separations performed by similar columns, the enzymatic activity behavior of the column produced by our protocol was determined. For this purpose, HPLC column was used as a packed bed reactor and the enzymatic reaction was continuously followed by measuring the absorbance of the output flow by the UV-detector of HPLC. S-shaped absorbance-time curves were obtained by monitoring the reactor output both in dynamic and steady-state periods. The columns with relatively lower immobilized enzyme content were more sensitive to the changes in the operating conditions and responded with more appreciable substrate conversion changes. The maximum reaction rate of the immobilized enzyme was estimated as approximately 25% of the free one by the mathematical model describing the activity behavior of the column. No significant loss was observed in the activity of the immobilized enzyme during the course of the experiments

Photocatalytic activity of self-assembled porous TiO2 nano-columns array fabricated by oblique angle sputter deposition

Science.gov (United States)

Shi, Pengjun; Li, Xibo; Zhang, Qiuju; Yi, Zao; Luo, Jiangshan

2018-04-01

A well-separated and oriented TiO2 nano-columns arrays with porous structure were fabricated by the oblique angle sputter deposition technique and subsequently annealing at 450 °C in Ar/O2 mixed atmosphere. The deposited substrate was firstly modified by a template of self-assembled close-packed arrays of 500 nm-diameter silica (SiO2) spheres. Scanning electronic microscopic (SEM) images show that the porous columnar nanostructure is formed as a result of the geometric shadowing effect and surface diffusion of the adatoms in oblique angle deposition (OAD). X-ray diffraction (XRD) measurements reveal that the physically OAD film with annealing treatment are generally mixed phase of rutile and anatase TiO2 polymorphic forms. The morphology induced absorbance and band gap tuning by different substrates was demonstrated by the UV–vis spectroscopy. The well-separated one-dimensional (1D) nano-columns array with specific large porous surface area is beneficial for charge separation in photocatalytic degradation. Compared with compact thin film, such self-assembled porous TiO2 nano-columns array fabricated by oblique angle sputter deposition performed an enhanced visible light induced photocatalytic activity by decomposing methyl orange (MO) solution. The well-designed periodic array-structured porous TiO2 films by using modified patterned substrates has been demonstrated significantly increased absorption edge in the UV-visible light region with a narrower optical band gap, which are expected to be favorable for application in photovoltaic, lithium-ion insertion and photocatalytic, etc.

Transport of surface-modified iron nanoparticle in porous media and application to arsenic(III) remediation

International Nuclear Information System (INIS)

Kanel, Sushil Raj; Nepal, Dhriti; Manning, Bruce; Choi, Heechul

2007-01-01

The surface-modified iron nanoparticles (S-INP) were synthesized, characterized and tested for the remediation of arsenite (As(III)), a well known toxic groundwater contaminant of concern. The S-INP material was fully dispersed in the aqueous phase with a particle size distribution of 2-10 nm estimated from high-resolution transmission electron microscopy (HR-TEM). X-ray photoelectron spectroscopy (XPS) revealed that an Fe(III) oxide surface film was present on S-INP in addition to the bulk zero-valent Fe 0 oxidation state. Transport of S-INP through porous media packed in 10 cm length column showed particle breakthroughs of 22.1, 47.4 and 60 pore volumes in glass beads, unbaked sand, and baked sand, respectively. Un-modified INP was immobile and aggregated on porous media surfaces in the column inlet area. Results using S-INP pretreated 10 cm sand-packed columns containing ∼2 g of S-INP showed that 100 % of As(III) was removed from influent solutions (flow rate 1.8 mL min -1 ) containing 0.2, 0.5 and 1.0 mg L -1 As(III) for 9, 7 and 4 days providing 23.3, 20.7 and 10.4 L of arsenic free water, respectively. In addition, it was found that 100% of As(III) in 0.5 mg/L solution (flow rate 1.8 mL min -1 ) was removed by S-INP pretreated 50 cm sand packed column containing 12 g of S-INP for more than 2.5 months providing 194.4 L of arsenic free water. Field emission scanning electron microscopy (FE-SEM) showed S-INP had transformed to elongated, rod-like shaped corrosion product particles after reaction with As(III) in the presence of sand. These results suggest that S-INP has great potential to be used as a mobile, injectable reactive material for in-situ sandy groundwater aquifer treatment of As(III)

New Structured Packing CUB for Purification of Exhaust Gases

Directory of Open Access Journals (Sweden)

Irina Novikova

2016-10-01

Full Text Available New structured packing for heat and mass transfer processes named CUB is presented in our article. The packing can be applied in packed towers for exhaust gas cleaning instead random packing, for example, rings type that are the most used in such processes. The advantages of the new packing over random packing are lower pressure drop, capability of purification and as a consequence long-term service of the packing. The researches of intensity of liquid-phase mass-transfer in packed bed depending on liquid spray rate and gas velocity were carried out. Obtained data show that packing CUB is more effective than the most popular type of structured packing under all other conditions being equal. As experimental data shown heat transfer coefficient was up by 17% and mass transfer coefficient was up by 51%. We found out optimal geometry of cross section of the new packing, namely, number of elements and parameters of one element. The new construction of structured packing is applicable for both type of column cross-section round and square.

Development of an effective valve packing program

Energy Technology Data Exchange (ETDEWEB)

Hart, K.A.

1996-12-01

Current data now shows that graphite valve packing installed within the guidance of a controlled program produces not only reliable stem sealing but predictable running loads. By utilizing recent technological developments in valve performance monitoring for both MOV`s and AOV`s, valve packing performance can be enhanced while reducing maintenance costs. Once known, values are established for acceptable valve packing loads, the measurement of actual valve running loads via the current MOV/AOV diagnostic techniques can provide indication of future valve stem sealing problems, improper valve packing installation or identify the opportunity for valve packing program improvements. At times the full benefit of these advances in material and predictive technology remain under utilized due to simple past misconceptions associated with valve packing. This paper will explore the basis for these misconceptions, provide general insight into the current understanding of valve packing and demonstrate how with this new understanding and current valve diagnostic equipment the key aspects required to develop an effective, quality valve packing program fit together. The cost and operational benefits provided by this approach can be significant impact by the: elimination of periodic valve repacking, reduction of maintenance costs, benefits of leak-free valve operation, justification for reduced Post Maintenance Test Requirements, reduced radiation exposure, improved plant appearance.

User's Manual for PCSMS (Parallel Complex Sparse Matrix Solver). Version 1.

Science.gov (United States)

Reddy, C. J.

2000-01-01

PCSMS (Parallel Complex Sparse Matrix Solver) is a computer code written to make use of the existing real sparse direct solvers to solve complex, sparse matrix linear equations. PCSMS converts complex matrices into real matrices and use real, sparse direct matrix solvers to factor and solve the real matrices. The solution vector is reconverted to complex numbers. Though, this utility is written for Silicon Graphics (SGI) real sparse matrix solution routines, it is general in nature and can be easily modified to work with any real sparse matrix solver. The User's Manual is written to make the user acquainted with the installation and operation of the code. Driver routines are given to aid the users to integrate PCSMS routines in their own codes.

Single-source gamma radiation procedures for improved calibration and measurements in porous media

International Nuclear Information System (INIS)

Oostrom, M.; Hofstee, C.; Dane, H.; Lenhard, R.J.

1998-01-01

When dual-energy gamma radiation systems are employed for measurements in porous media, count rates from both sources are often used to compute parameter values. However, for several applications, the count rates of just one source are insufficient. These applications include the determination of volumetric liquid content values in two-liquid systems and salt concentration values in water-saturated porous media. Single-energy gamma radiation procedures for three applications are described in this paper. Through an error analysis, single-source procedures are shown to reduce the probable error in the determinations considerably. Example calculations and simple column experiments were conducted for each application to compare the performance of the new single-source and standard dual-source methods. In all cases, the single-source methods provided more reliable data than the traditional dual-source methods. In addition, a single-source calibration procedure is proposed to determine incident count rates indirectly. This procedure, which requires packing under saturated conditions, can be used in all single- and dual-source applications and yields accurate porosity and dry bulk density values

Influence of the starch content and sintering temperature on the processing of porous zirconia substrates

International Nuclear Information System (INIS)

Albano, Maria P; Garrido, Liliana B

2008-01-01

Porous ceramics are used as electrodes in fuel cells, separators in batteries, filters, etc. Thin porous substrates of zirconium stabilized with yttrium oxide (ZSY) are used as anodes in solid oxide fuel cells. One way to obtain a porous band is to mix starch particles during the preparation stage of the ZSY suspension. The starch burns during the removal of the binder and leaves stable pores that are not eliminated in the subsequent sintering stage. This work used the band pouring process to produce porous bands of ZSY with porosities of 29% to 53% using starch as a transitory additive. Concentrated aqueous suspensions of ZSY were prepared with different contents of starch and of an acrylic latex binder. The influence of the fraction of starch volume and of the temperature on the sintering behavior and on the final micro structure of the bands was studied. The total porosity of the bands was higher than the fractions in volume of added starch, due to the presence of closed porosity in the matrix. The deviations compared to the porosity predicted based on the fractions in the volume of starch, were greater as the starch content increased. The percentage of open porosity in the sintered bands depended on the fraction in the volume of added starch and on the sintering temperature. When the fraction in volume of starch increased from 17.6% to 37.8% a gradual increase occurred in the opening of the porous structure. The contraction of the bands during sintering at a given temperature correlated with the density of the packing of ZSY (au)

Incoherent and coherent backscattering of light by a layer of densely packed random medium

Energy Technology Data Exchange (ETDEWEB)

Tishkovets, Victor P. [Institute of Radio Astronomy of NASU, 4 Chervonopraporna Street, Kharkiv 61002 (Ukraine)], E-mail: tishkovets@ira.kharkov.ua

2007-12-15

The problem of light scattering by a layer of densely packed discrete random medium is considered. The theory of light scattering by systems of nonspherical particles is applied to derive equations corresponding to incoherent (diffuse) and interference parts of radiation reflected from the medium. A solution of the system of linear equations describing light scattering by a system of particles is represented by iteration. It is shown that the symmetry properties of the T-matrices and of the translation coefficients for the vector Helmholtz harmonics lead to the reciprocity relation for an arbitrary iteration. This relation is applied to consider the backscattering enhancement phenomenon. Equations expressing the incoherent and interference parts of reflected light from statistically homogeneous and isotropic plane-parallel layer of medium are given. In the exact backscattering direction the relation between incoherent and interference parts is identical to that of sparse media.

Random packing of digitized particles

NARCIS (Netherlands)

Korte, de A.C.J.; Brouwers, H.J.H.

2013-01-01

The random packing of regularly and irregularly shaped particles has been studied extensively. Within this paper, packing is studied from the perspective of digitized particles. These digitized particles are developed for and used in cellular automata systems, which are employed for the simple

Random packing of digitized particles

NARCIS (Netherlands)

de Korte, A.C.J.; Brouwers, Jos

2012-01-01

The random packing of regularly and irregularly shaped particles has been studied extensively. Within this paper, packing is studied from the perspective of digitized particles. These digitized particles are developed for and used in cellular automata systems, which are employed for the simple

BNGS B valve packing program

International Nuclear Information System (INIS)

Cumming, D.

1995-01-01

The Bruce B Valve Packing Program began in 1987. The early history and development were presented at the 1992 International CANDU Maintenance conference. This presentation covers the evolution of the Bruce B Valve Packing Program over the period 1992 to 1995. (author)

Parallel transposition of sparse data structures

DEFF Research Database (Denmark)

Wang, Hao; Liu, Weifeng; Hou, Kaixi

2016-01-01

Many applications in computational sciences and social sciences exploit sparsity and connectivity of acquired data. Even though many parallel sparse primitives such as sparse matrix-vector (SpMV) multiplication have been extensively studied, some other important building blocks, e.g., parallel tr...... transposition in the latest vendor-supplied library on an Intel multicore CPU platform, and the MergeTrans approach achieves on average of 3.4-fold (up to 11.7-fold) speedup on an Intel Xeon Phi many-core processor....

The pursuit of perfect packing

CERN Document Server

Weaire, Denis

2008-01-01

Coauthored by one of the creators of the most efficient space packing solution, the Weaire-Phelan structure, The Pursuit of Perfect Packing, Second Edition explores a problem of importance in physics, mathematics, chemistry, biology, and engineering: the packing of structures. Maintaining its mathematical core, this edition continues and revises some of the stories from its predecessor while adding several new examples and applications. The book focuses on both scientific and everyday problems ranging from atoms to honeycombs. It describes packing models, such as the Kepler conjecture, Voronoï decomposition, and Delaunay decomposition, as well as actual structure models, such as the Kelvin cell and the Weaire-Phelan structure. The authors discuss numerous historical aspects and provide biographical details on influential contributors to the field, including emails from Thomas Hales and Ken Brakke. With examples from physics, crystallography, engineering, and biology, this accessible and whimsical bo...

Numerical solution of large sparse linear systems

International Nuclear Information System (INIS)

Meurant, Gerard; Golub, Gene.

1982-02-01

This note is based on one of the lectures given at the 1980 CEA-EDF-INRIA Numerical Analysis Summer School whose aim is the study of large sparse linear systems. The main topics are solving least squares problems by orthogonal transformation, fast Poisson solvers and solution of sparse linear system by iterative methods with a special emphasis on preconditioned conjuguate gradient method [fr

Effective conductivity by fluid analogy for a porous insulator filled with a conductor

International Nuclear Information System (INIS)

Berryman, J.G.

1983-01-01

By combining of identities relating effective conductivity to tortuosity and tortuosity to induced mass, a general formula for the effective (electrical or thermal) conductivity of a porous insulator filled with a conductor is obtained. This formula depends on an induced-mass factor which arises by treating of the conducting material as an inviscid fluid. This induced-mass factor can be estimated with the use of an effective-medium theory. For random arrays of equal spheres, the estimates of conductivity obtained with the use of this fluid analogy are in good agreement with recent exact values derived for periodic arrays of insulating spheres to closest packing

Battery Pack Thermal Design

Energy Technology Data Exchange (ETDEWEB)

Pesaran, Ahmad

2016-06-14

This presentation describes the thermal design of battery packs at the National Renewable Energy Laboratory. A battery thermal management system essential for xEVs for both normal operation during daily driving (achieving life and performance) and off-normal operation during abuse conditions (achieving safety). The battery thermal management system needs to be optimized with the right tools for the lowest cost. Experimental tools such as NREL's isothermal battery calorimeter, thermal imaging, and heat transfer setups are needed. Thermal models and computer-aided engineering tools are useful for robust designs. During abuse conditions, designs should prevent cell-to-cell propagation in a module/pack (i.e., keep the fire small and manageable). NREL's battery ISC device can be used for evaluating the robustness of a module/pack to cell-to-cell propagation.

7 CFR 982.11 - Pack.

Science.gov (United States)

2010-01-01

... according to size, internal quality, and external appearance and condition of hazelnuts packed in accordance... 7 Agriculture 8 2010-01-01 2010-01-01 false Pack. 982.11 Section 982.11 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and...

3D printing of porous hydroxyapatite scaffolds intended for use in bone tissue engineering applications

Energy Technology Data Exchange (ETDEWEB)

Cox, Sophie C.; Thornby, John A.; Gibbons, Gregory J., E-mail: G.J.Gibbons@warwick.ac.uk; Williams, Mark A.; Mallick, Kajal K.

2015-02-01

A systematic characterisation of bone tissue scaffolds fabricated via 3D printing from hydroxyapatite (HA) and poly(vinyl)alcohol (PVOH) composite powders is presented. Flowability of HA:PVOH precursor materials was observed to affect mechanical stability, microstructure and porosity of 3D printed scaffolds. Anisotropic behaviour of constructs and part failure at the boundaries of interlayer bonds was highlighted by compressive strength testing. A trade-off between the ability to facilitate removal of PVOH thermal degradation products during sintering and the compressive strength of green parts was revealed. The ultimate compressive strength of 55% porous green scaffolds printed along the Y-axis and dried in a vacuum oven for 6 h was 0.88 ± 0.02 MPa. Critically, the pores of 3D printed constructs could be user designed, ensuring bulk interconnectivity, and the imperfect packing of powder particles created an inherent surface roughness and non-designed porosity within the scaffold. These features are considered promising since they are known to facilitate osteoconduction and osteointegration in-vivo. Characterisation techniques utilised in this study include two funnel flow tests, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), compressive strength testing and computed tomography (CT). - Highlights: • Flowability of HA and PVOH powders corresponded to scaffold printability. • Anisotropic behaviour of 3D printed scaffolds was highlighted by compressive tests. • Maximum compressive strength of 3D printed 55% porous scaffolds was 0.88 MPa. • Imperfect packing of precursors resulted in a rough surface and microporosity. • A CT method was designed and used to quantify designed and non-designed porosity.

3D printing of porous hydroxyapatite scaffolds intended for use in bone tissue engineering applications

International Nuclear Information System (INIS)

Cox, Sophie C.; Thornby, John A.; Gibbons, Gregory J.; Williams, Mark A.; Mallick, Kajal K.

2015-01-01

A systematic characterisation of bone tissue scaffolds fabricated via 3D printing from hydroxyapatite (HA) and poly(vinyl)alcohol (PVOH) composite powders is presented. Flowability of HA:PVOH precursor materials was observed to affect mechanical stability, microstructure and porosity of 3D printed scaffolds. Anisotropic behaviour of constructs and part failure at the boundaries of interlayer bonds was highlighted by compressive strength testing. A trade-off between the ability to facilitate removal of PVOH thermal degradation products during sintering and the compressive strength of green parts was revealed. The ultimate compressive strength of 55% porous green scaffolds printed along the Y-axis and dried in a vacuum oven for 6 h was 0.88 ± 0.02 MPa. Critically, the pores of 3D printed constructs could be user designed, ensuring bulk interconnectivity, and the imperfect packing of powder particles created an inherent surface roughness and non-designed porosity within the scaffold. These features are considered promising since they are known to facilitate osteoconduction and osteointegration in-vivo. Characterisation techniques utilised in this study include two funnel flow tests, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), compressive strength testing and computed tomography (CT). - Highlights: • Flowability of HA and PVOH powders corresponded to scaffold printability. • Anisotropic behaviour of 3D printed scaffolds was highlighted by compressive tests. • Maximum compressive strength of 3D printed 55% porous scaffolds was 0.88 MPa. • Imperfect packing of precursors resulted in a rough surface and microporosity. • A CT method was designed and used to quantify designed and non-designed porosity

Sparse Source EEG Imaging with the Variational Garrote

DEFF Research Database (Denmark)

Hansen, Sofie Therese; Stahlhut, Carsten; Hansen, Lars Kai

2013-01-01

EEG imaging, the estimation of the cortical source distribution from scalp electrode measurements, poses an extremely ill-posed inverse problem. Recent work by Delorme et al. (2012) supports the hypothesis that distributed source solutions are sparse. We show that direct search for sparse solutions...

Deterministic indexing for packed strings

DEFF Research Database (Denmark)

Bille, Philip; Gørtz, Inge Li; Skjoldjensen, Frederik Rye

2017-01-01

Given a string S of length n, the classic string indexing problem is to preprocess S into a compact data structure that supports efficient subsequent pattern queries. In the deterministic variant the goal is to solve the string indexing problem without any randomization (at preprocessing time...... or query time). In the packed variant the strings are stored with several character in a single word, giving us the opportunity to read multiple characters simultaneously. Our main result is a new string index in the deterministic and packed setting. Given a packed string S of length n over an alphabet σ...

Low-count PET image restoration using sparse representation

Science.gov (United States)

Li, Tao; Jiang, Changhui; Gao, Juan; Yang, Yongfeng; Liang, Dong; Liu, Xin; Zheng, Hairong; Hu, Zhanli

2018-04-01

In the field of positron emission tomography (PET), reconstructed images are often blurry and contain noise. These problems are primarily caused by the low resolution of projection data. Solving this problem by improving hardware is an expensive solution, and therefore, we attempted to develop a solution based on optimizing several related algorithms in both the reconstruction and image post-processing domains. As sparse technology is widely used, sparse prediction is increasingly applied to solve this problem. In this paper, we propose a new sparse method to process low-resolution PET images. Two dictionaries (D1 for low-resolution PET images and D2 for high-resolution PET images) are learned from a group real PET image data sets. Among these two dictionaries, D1 is used to obtain a sparse representation for each patch of the input PET image. Then, a high-resolution PET image is generated from this sparse representation using D2. Experimental results indicate that the proposed method exhibits a stable and superior ability to enhance image resolution and recover image details. Quantitatively, this method achieves better performance than traditional methods. This proposed strategy is a new and efficient approach for improving the quality of PET images.

X-ray computed tomography using curvelet sparse regularization.

Science.gov (United States)

Wieczorek, Matthias; Frikel, Jürgen; Vogel, Jakob; Eggl, Elena; Kopp, Felix; Noël, Peter B; Pfeiffer, Franz; Demaret, Laurent; Lasser, Tobias

2015-04-01

Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method's strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.

Random packing of colloids and granular matter

NARCIS (Netherlands)

Wouterse, A.

2008-01-01

This thesis deals with the random packing of colloids and granular matter. A random packing is a stable disordered collection of touching particles, without long-range positional and orientational order. Experimental random packings of particles with the same shape but made of different materials

Packing circles and spheres on surfaces

KAUST Repository

Schiftner, Alexander; Hö binger, Mathias; Wallner, Johannes; Pottmann, Helmut

2009-01-01

Inspired by freeform designs in architecture which involve circles and spheres, we introduce a new kind of triangle mesh whose faces' incircles form a packing. As it turns out, such meshes have a rich geometry and allow us to cover surfaces with circle patterns, sphere packings, approximate circle packings, hexagonal meshes which carry a torsion-free support structure, hybrid tri-hex meshes, and others. We show how triangle meshes can be optimized so as to have the incircle packing property. We explain their relation to conformal geometry and implications on solvability of optimization. The examples we give confirm that this kind of meshes is a rich source of geometric structures relevant to architectural geometry. © 2009 ACM.

Packing circles and spheres on surfaces

KAUST Repository

Schiftner, Alexander

2009-12-01

Inspired by freeform designs in architecture which involve circles and spheres, we introduce a new kind of triangle mesh whose faces\\' incircles form a packing. As it turns out, such meshes have a rich geometry and allow us to cover surfaces with circle patterns, sphere packings, approximate circle packings, hexagonal meshes which carry a torsion-free support structure, hybrid tri-hex meshes, and others. We show how triangle meshes can be optimized so as to have the incircle packing property. We explain their relation to conformal geometry and implications on solvability of optimization. The examples we give confirm that this kind of meshes is a rich source of geometric structures relevant to architectural geometry.

Packing circles and spheres on surfaces

KAUST Repository

Schiftner, Alexander

2009-01-01

Inspired by freeform designs in architecture which involve circles and spheres, we introduce a new kind of triangle mesh whose faces\\' incircles form a packing. As it turns out, such meshes have a rich geometry and allow us to cover surfaces with circle patterns, sphere packings, approximate circle packings, hexagonal meshes which carry a torsion-free support structure, hybrid tri-hex meshes, and others. We show how triangle meshes can be optimized so as to have the incircle packing property. We explain their relation to conformal geometry and implications on solvability of optimization. The examples we give confirm that this kind of meshes is a rich source of geometric structures relevant to architectural geometry. © 2009 ACM.

Packing circles and spheres on surfaces

KAUST Repository

Schiftner, Alexander; Hö binger, Mathias; Wallner, Johannes; Pottmann, Helmut

2009-01-01

Inspired by freeform designs in architecture which involve circles and spheres, we introduce a new kind of triangle mesh whose faces' incircles form a packing. As it turns out, such meshes have a rich geometry and allow us to cover surfaces with circle patterns, sphere packings, approximate circle packings, hexagonal meshes which carry a torsion-free support structure, hybrid tri-hex meshes, and others. We show how triangle meshes can be optimized so as to have the incircle packing property. We explain their relation to conformal geometry and implications on solvability of optimization. The examples we give confirm that this kind of meshes is a rich source of geometric structures relevant to architectural geometry.

Imaging biofilm in porous media using X-ray computed microtomography.

Science.gov (United States)

Davit, Y; Iltis, G; Debenest, G; Veran-Tissoires, S; Wildenschild, D; Gerino, M; Quintard, M

2011-04-01

In this study, a new technique for three-dimensional imaging of biofilm within porous media using X-ray computed microtomography is presented. Due to the similarity in X-ray absorption coefficients for the porous media (plastic), biofilm and aqueous phase, an X-ray contrast agent is required to image biofilm within the experimental matrix using X-ray computed tomography. The presented technique utilizes a medical suspension of barium sulphate to differentiate between the aqueous phase and the biofilm. Potassium iodide is added to the suspension to aid in delineation between the biofilm and the experimental porous medium. The iodide readily diffuses into the biofilm while the barium sulphate suspension remains in the aqueous phase. This allows for effective differentiation of the three phases within the experimental systems utilized in this study. The behaviour of the two contrast agents, in particular of the barium sulphate, is addressed by comparing two-dimensional images of biofilm within a pore network obtained by (1) optical visualization and (2) X-ray absorption radiography. We show that the contrast mixture provides contrast between the biofilm, the aqueous-phase and the solid-phase (beads). The imaging method is then applied to two three-dimensional packed-bead columns within which biofilm was grown. Examples of reconstructed images are provided to illustrate the effectiveness of the method. Limitations and applications of the technique are discussed. A key benefit, associated with the presented method, is that it captures a substantial amount of information regarding the topology of the pore-scale transport processes. For example, the quantification of changes in porous media effective parameters, such as dispersion or permeability, induced by biofilm growth, is possible using specific upscaling techniques and numerical analysis. We emphasize that the results presented here serve as a first test of this novel approach; issues with accurate segmentation of

Packing configuration performance for small stem diameters

International Nuclear Information System (INIS)

Aikin, J.A.; Spence, C.G.; Cumming, D.

1997-01-01

The extensive use of graphite packing and its excellent track record for large isolating valves in CANDU, Primary Heat Transfer (PHT) systems has resulted in an increased application of graphite packing on the conventional side. Many of these applications are in air operated valves (AOVs) where the packing sets are used on small stem diameters (<1 inch) with frequent short-cycling strokes (± 10% of full stroke). The direct application of the proven packing configurations for large isolated valves to control valve application has generated problems such as stiction, packing wear and, in isolated cases, stem stall. To address this issue, a test program was conducted at AECL, CRL by MED branch. The testing showed that by reconfiguring the packing sets and using PTFE wafers reductions in stem friction of 50% at ambient conditions, a 3 fold at hot conditions are achievable. The test program also demonstrated benefits gained in packing wear with different stem roughness finishes and the potential need to exercise small stems valves that see less than full stroke cycling. The paper describes the tests results and provides field support experience. (author)

Bidispersed Sphere Packing on Spherical Surfaces

Science.gov (United States)

Atherton, Timothy; Mascioli, Andrew; Burke, Christopher

Packing problems on spherical surfaces have a long history, originating in the classic Thompson problem of finding the ground state configuration of charges on a sphere. Such packings contain a minimal number of defects needed to accommodate the curvature; this is predictable using the Gauss-Bonnet theorem from knowledge of the topology of the surface and the local symmetry of the ordering. Famously, the packing of spherical particles on a sphere contains a 'scar' transition, where additional defects over those required by topology appear above a certain critical number of particles and self-organize into chains or scars. In this work, we study the packing of bidispersed packings on a sphere, and hence determine the interaction of bidispersity and curvature. The resultant configurations are nearly crystalline for low values of bidispersity and retain scar-like structures; these rapidly become disordered for intermediate values and approach a so-called Appollonian limit at the point where smaller particles can be entirely accommodated within the voids left by the larger particles. We connect our results with studies of bidispersed packings in the bulk and on flat surfaces from the literature on glassy systems and jamming. Supported by a Cottrell Award from the Research Corporation for Science Advancement.

Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.

Science.gov (United States)

Wang, Ping; Jiang, Jin-Yang; Li, Na; Luo, Han-Wu; Li, Fang; Cui, Shi-Gang

2017-07-01

It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.

Influence of γ-ray radiation on mechanical character of packing

International Nuclear Information System (INIS)

Tashiro, Hisao; Sakuma, Toshio

1989-01-01

This paper describes the results of investigation on coefficient of friction, normal to axial pressure-ratio and compressed strain of packings influenced by γ-ray irradiation, which are necessary to evaluate the mechanical characteristics of packing, using packings made of seven kinds of new materials and conventional asbestos packing A. It resulted that graphite packing was less influenced by the γ-ray exposure, whereas carbon-fiber (pitch) packing, tefron-fiber packing and alamid-fiber packing were much influenced as compared with the graphite packing. (author)

A sparse electromagnetic imaging scheme using nonlinear landweber iterations

KAUST Repository

Desmal, Abdulla; Bagci, Hakan

2015-01-01

Development and use of electromagnetic inverse scattering techniques for imagining sparse domains have been on the rise following the recent advancements in solving sparse optimization problems. Existing techniques rely on iteratively converting

Scalable group level probabilistic sparse factor analysis

DEFF Research Database (Denmark)

Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard

2017-01-01

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...

Fast wavelet based sparse approximate inverse preconditioner

Energy Technology Data Exchange (ETDEWEB)

Wan, W.L. [Univ. of California, Los Angeles, CA (United States)

1996-12-31

Incomplete LU factorization is a robust preconditioner for both general and PDE problems but unfortunately not easy to parallelize. Recent study of Huckle and Grote and Chow and Saad showed that sparse approximate inverse could be a potential alternative while readily parallelizable. However, for special class of matrix A that comes from elliptic PDE problems, their preconditioners are not optimal in the sense that independent of mesh size. A reason may be that no good sparse approximate inverse exists for the dense inverse matrix. Our observation is that for this kind of matrices, its inverse entries typically have piecewise smooth changes. We can take advantage of this fact and use wavelet compression techniques to construct a better sparse approximate inverse preconditioner. We shall show numerically that our approach is effective for this kind of matrices.

Local posterior concentration rate for multilevel sparse sequences

NARCIS (Netherlands)

Belitser, E.N.; Nurushev, N.

2017-01-01

We consider empirical Bayesian inference in the many normal means model in the situation when the high-dimensional mean vector is multilevel sparse, that is,most of the entries of the parameter vector are some fixed values. For instance, the traditional sparse signal is a particular case (with one

Bacterial transport in heterogeneous porous media: Observations from laboratory experiments

Science.gov (United States)

Silliman, S. E.; Dunlap, R.; Fletcher, M.; Schneegurt, M. A.

2001-11-01

Transport of bacteria through heterogeneous porous media was investigated in small-scale columns packed with sand and in a tank designed to allow the hydraulic conductivity to vary as a two-dimensional, lognormally distributed, second-order stationary, exponentially correlated random field. The bacteria were Pseudomonas ftuorescens R8, a strain demonstrating appreciable attachment to surfaces, and strain Ml, a transposon mutant of strain R8 with reduced attachment ability. In bench top, sand-filled columns, transport was determined by measuring intensity of fluorescence of stained cells in the effluent or by measuring radiolabeled cells that were retained in the sand columns. Results demonstrated that strain Ml was transported more efficiently than strain R8 through columns packed with either a homogeneous silica sand or a more heterogeneous sand with iron oxide coatings. Two experiments conducted in the tank involved monitoring transport of bacteria to wells via sampling from wells and sample ports in the tank. Bacterial numbers were determined by direct plate count. At the end of the first experiment, the distribution of the bacteria in the sediment was determined by destructive sampling and plating. The two experiments produced bacterial breakthrough curves that were quite similar even though the similarity between the two porous media was limited to first- and second-order statistical moments. This result appears consistent with the concept of large-scale, average behavior such as has been observed for the transport of conservative chemical tracers. The transported bacteria arrived simultaneously with a conservative chemical tracer (although at significantly lower normalized concentration than the tracer). However, the bacterial breakthrough curves showed significant late time tailing. The concentrations of bacteria attached to the sediment surfaces showed considerably more spatial variation than did the concentrations of bacteria in the fluid phase. This

Sparse modeling of spatial environmental variables associated with asthma.

Science.gov (United States)

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Analog system for computing sparse codes

Science.gov (United States)

Rozell, Christopher John; Johnson, Don Herrick; Baraniuk, Richard Gordon; Olshausen, Bruno A.; Ortman, Robert Lowell

2010-08-24

A parallel dynamical system for computing sparse representations of data, i.e., where the data can be fully represented in terms of a small number of non-zero code elements, and for reconstructing compressively sensed images. The system is based on the principles of thresholding and local competition that solves a family of sparse approximation problems corresponding to various sparsity metrics. The system utilizes Locally Competitive Algorithms (LCAs), nodes in a population continually compete with neighboring units using (usually one-way) lateral inhibition to calculate coefficients representing an input in an over complete dictionary.

Model of porous aluminium oxide growth during initial stage of anodization

Science.gov (United States)

Aryslanova, E. M.; Alfimov, A. V.; Chivilikhin, S. A.

2014-10-01

Currently, the development of nanotechnology and metamaterials requires the ability to obtain regular self-assembled structures with different parameters. One such structure is porous alumina in which the pores grow perpendicular to the substrate and are hexagonally packed. Pore size and the distance between them can be varied depending on the anodization voltage, the electrolyte and the anodization time (pore diameter - from 2 to 350 nm, the distance between the pores - from 5 to 50 nm). At the moment, there are different models describing the process of anodizing aluminum, in this paper we propose a model that takes into account the effect of layers of aluminum, aluminum oxide, and the electrolyte, as well as the influence of the effect of surface diffusion.

Quasi-human seniority-order algorithm for unequal circles packing

International Nuclear Information System (INIS)

Zhu, Dingju

2016-01-01

In the existing methods for solving unequal circles packing problems, the initial configuration is given arbitrarily or randomly, but the impact of different initial configurations for existing packing algorithm to the speed of existing packing algorithm solving unequal circles packing problems is very large. The quasi-human seniority-order algorithm proposed in this paper can generate a better initial configuration for existing packing algorithm to accelerate the speed of existing packing algorithm solving unequal circles packing problems. In experiments, the quasi-human seniority-order algorithm is applied to generate better initial configurations for quasi-physical elasticity methods to solve the unequal circles packing problems, and the experimental results show that the proposed quasi-human seniority-order algorithm can greatly improve the speed of solving the problem.

Film condensation on a porous vertical surface in a porous media

International Nuclear Information System (INIS)

Ebinuma, C.D.; Liu, C.Y.; Ismail, K.A.R.

1983-01-01

The problem of dry saturated steam film condensation by natural convection on a porous surface in a porous medium is presented. Through the classical Darcy law for flow in porous medium and the approximations considered in the Boundary layer theory, it is shown that the analytical solution exists only when the normal velocity to the porous wall is inversly proportional to the square root of the distance along the plate. (E.G.) [pt

48 CFR 552.211-87 - Export packing.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Export packing. 552.211-87... FORMS SOLICITATION PROVISIONS AND CONTRACT CLAUSES Text of Provisions and Clauses 552.211-87 Export packing. As prescribed in 511.204(b)(7), insert the following clause: Export Packing (JAN 2010) (a...

Efficient Pseudorecursive Evaluation Schemes for Non-adaptive Sparse Grids

KAUST Repository

Buse, Gerrit; Pflü ger, Dirk; Jacob, Riko

2014-01-01

In this work we propose novel algorithms for storing and evaluating sparse grid functions, operating on regular (not spatially adaptive), yet potentially dimensionally adaptive grid types. Besides regular sparse grids our approach includes truncated

Tailored Porous Materials

Energy Technology Data Exchange (ETDEWEB)

BARTON,THOMAS J.; BULL,LUCY M.; KLEMPERER,WALTER G.; LOY,DOUGLAS A.; MCENANEY,BRIAN; MISONO,MAKOTO; MONSON,PETER A.; PEZ,GUIDO; SCHERER,GEORGE W.; VARTULI,JAMES C.; YAGHI,OMAR M.

1999-11-09

Tailoring of porous materials involves not only chemical synthetic techniques for tailoring microscopic properties such as pore size, pore shape, pore connectivity, and pore surface reactivity, but also materials processing techniques for tailoring the meso- and the macroscopic properties of bulk materials in the form of fibers, thin films and monoliths. These issues are addressed in the context of five specific classes of porous materials: oxide molecular sieves, porous coordination solids, porous carbons, sol-gel derived oxides, and porous heteropolyanion salts. Reviews of these specific areas are preceded by a presentation of background material and review of current theoretical approaches to adsorption phenomena. A concluding section outlines current research needs and opportunities.

Graded/Gradient Porous Biomaterials

Directory of Open Access Journals (Sweden)

Xigeng Miao

2009-12-01

Full Text Available Biomaterials include bioceramics, biometals, biopolymers and biocomposites and they play important roles in the replacement and regeneration of human tissues. However, dense bioceramics and dense biometals pose the problem of stress shielding due to their high Young’s moduli compared to those of bones. On the other hand, porous biomaterials exhibit the potential of bone ingrowth, which will depend on porous parameters such as pore size, pore interconnectivity, and porosity. Unfortunately, a highly porous biomaterial results in poor mechanical properties. To optimise the mechanical and the biological properties, porous biomaterials with graded/gradient porosity, pores size, and/or composition have been developed. Graded/gradient porous biomaterials have many advantages over graded/gradient dense biomaterials and uniform or homogenous porous biomaterials. The internal pore surfaces of graded/gradient porous biomaterials can be modified with organic, inorganic, or biological coatings and the internal pores themselves can also be filled with biocompatible and biodegradable materials or living cells. However, graded/gradient porous biomaterials are generally more difficult to fabricate than uniform or homogenous porous biomaterials. With the development of cost-effective processing techniques, graded/gradient porous biomaterials can find wide applications in bone defect filling, implant fixation, bone replacement, drug delivery, and tissue engineering.

Electrohydrodynamic bubbling: an alternative route to fabricate porous structures of silk fibroin based materials.

Science.gov (United States)

Ekemen, Zeynep; Ahmad, Zeeshan; Stride, Eleanor; Kaplan, David; Edirisinghe, Mohan

2013-05-13

Conventional fabrication techniques and structures employed in the design of silk fibroin (SF) based porous materials provide only limited control over pore size and require several processing stages. In this study, it is shown that, by utilizing electrohydrodynamic bubbling, not only can new hollow spherical structures of SF be formed in a single step by means of bubbles, but the resulting bubbles can serve as pore generators when dehydrated. The bubble characteristics can be controlled through simple adjustments to the processing parameters. Bubbles with diameters in the range of 240-1000 μm were fabricated in controlled fashion. FT-IR characterization confirmed that the rate of air infused during processing enhanced β-sheet packing in SF at higher flow rates. Dynamic mechanical analysis also demonstrated a correlation between air flow rate and film tensile strength. Results indicate that electrohydrodynamically generated SF and their composite bubbles can be employed as new tools to generate porous structures in a controlled manner with a range of potential applications in biocoatings and tissue engineering scaffolds.

Pore-scale dynamics of salt transport and distribution in drying porous media

International Nuclear Information System (INIS)

Shokri, Nima

2014-01-01

Understanding the physics of water evaporation from saline porous media is important in many natural and engineering applications such as durability of building materials and preservation of monuments, water quality, and mineral-fluid interactions. We applied synchrotron x-ray micro-tomography to investigate the pore-scale dynamics of dissolved salt distribution in a three dimensional drying saline porous media using a cylindrical plastic column (15 mm in height and 8 mm in diameter) packed with sand particles saturated with CaI 2 solution (5% concentration by mass) with a spatial and temporal resolution of 12 μm and 30 min, respectively. Every time the drying sand column was set to be imaged, two different images were recorded using distinct synchrotron x-rays energies immediately above and below the K-edge value of Iodine. Taking the difference between pixel gray values enabled us to delineate the spatial and temporal distribution of CaI 2 concentration at pore scale. Results indicate that during early stages of evaporation, air preferentially invades large pores at the surface while finer pores remain saturated and connected to the wet zone at bottom via capillary-induced liquid flow acting as evaporating spots. Consequently, the salt concentration increases preferentially in finer pores where evaporation occurs. Higher salt concentration was observed close to the evaporating surface indicating a convection-driven process. The obtained salt profiles were used to evaluate the numerical solution of the convection-diffusion equation (CDE). Results show that the macro-scale CDE could capture the overall trend of the measured salt profiles but fail to produce the exact slope of the profiles. Our results shed new insight on the physics of salt transport and its complex dynamics in drying porous media and establish synchrotron x-ray tomography as an effective tool to investigate the dynamics of salt transport in porous media at high spatial and temporal resolution

Anaerobic acidogenic digestion of olive mill wastewaters in biofilm reactors packed with ceramic filters or granular activated carbon.

Science.gov (United States)

Bertin, Lorenzo; Lampis, Silvia; Todaro, Daniela; Scoma, Alberto; Vallini, Giovanni; Marchetti, Leonardo; Majone, Mauro; Fava, Fabio

2010-08-01

Four identically configured anaerobic packed bed biofilm reactors were developed and employed in the continuous acidogenic digestion of olive mill wastewaters to produce volatile fatty acids (VFAs), which can be exploited in the biotechnological production of polyhydroxyalkanoates. Ceramic porous cubes or granular activated carbon were used as biofilm supports. Aside packing material, the role of temperature and organic loading rate (OLR) on VFA production yield and mixture composition were also studied. The process was monitored through a chemical, microbiological and molecular biology integrated procedure. The highest wastewater acidification yield was achieved with the ceramic-based technology at 25 degrees C, with an inlet COD and an OLR of about 17 g/L and 13 g/L/day, respectively. Under these conditions, about the 66% of the influent COD (not including its VFA content) was converted into VFAs, whose final amount represented more than 82% of the influent COD. In particular, acetic, propionic and butyric acids were the main VFAs by composing the 55.7, 21.5 and 14.4%, respectively, of the whole VFA mixture. Importantly, the relative concentrations of acetate and propionate were affected by the OLR parameter. The nature of the packing material remarkable influenced the process performances, by greatly affecting the biofilm bacterial community structure. In particular, ceramic cubes favoured the immobilization of Firmicutes of the genera Bacillus, Paenibacillus and Clostridium, which were probably involved in the VFA producing process. (c) 2010 Elsevier Ltd. All rights reserved.

Occlusion detection via structured sparse learning for robust object tracking

KAUST Repository

Zhang, Tianzhu

2014-01-01

Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios, these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object’s track. This is the case when significant occlusion occurs. To accommodate for nonsparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our proposed tracker consistently outperforms the state-of-the-art trackers.

Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

Directory of Open Access Journals (Sweden)

Xiangwei Xing

2014-01-01

Full Text Available As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC has attracted much attention in synthetic aperture radar (SAR automatic target recognition (ATR recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA, in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Shelving 6 pack crisps

OpenAIRE

Garriga Torrecillas, Núria; Otrubova, Natalie; Worm, Robert; Larroque, Thibaut

2017-01-01

6-Pack crisps are one of the main products sold by PepsiCo using the standard shelf storage options offered by Tesco PLC. While presenting specific packaging involves a multitude of variables. This report focusses on cognitive recognition, brand confusion and product attractiveness. PepsiCo asked the research team to investigate innovative ways of presenting the crisp 6-pack variant on instore displays. research shows that attraction is crucial in the form of expected rewards. The combination...

Bioclogging in Porous Media: Preferential Flow Paths and Anomalous Transport

Science.gov (United States)

Holzner, M.; Carrel, M.; Morales, V.; Derlon, N.; Beltran, M. A.; Morgenroth, E.; Kaufmann, R.

2016-12-01

Biofilms are sessile communities of microorganisms held together by an extracellular polymeric substance that enables surface colonization. In porous media (e.g. soils, trickling filters etc.) biofilm growth has been shown to affect the hydrodynamics in a complex fashion at the pore-scale by clogging individual pores and enhancing preferential flow pathways and anomalous transport. These phenomena are a direct consequence of microbial growth and metabolism, mass transfer processes and complex flow velocity fields possibly exhibiting pronounced three-dimensional features. Despite considerable past work, however, it is not fully understood how bioclogging interacts with flow and mass transport processes in porous media. In this work we use imaging techniques to determine the flow velocities and the distribution of biofilm in a porous medium. Three-dimensional millimodels are packed with a transparent porous medium and a glucose solution to match the optical refractive index. The models are inoculated with planktonic wildtype bacteria and biofilm cultivated for 60 h under a constant flow and nutrient conditions. The pore flow velocities in the increasingly bioclogged medium are measured using 3D particle tracking velocimetry (3D-PTV). The three-dimensional spatial distribution of the biofilm within the pore space is assessed by imaging the model with X-Ray microtomography. We find that biofilm growth increases the complexity of the pore space, leading to the formation of preferential flow pathways and "dead" pore zones. The probability of persistent high and low velocity regions (within preferential paths resp. stagnant flow regions) thus increases upon biofilm growth, leading to an enhancement of anomalous transport. The structural data seems to indicate that the largest pores are not getting clogged and carry the preferential flow, whereas intricated structures develop in the smallest pores, where the flow becomes almost stagnant. These findings may be relevant for

Learning sparse generative models of audiovisual signals

OpenAIRE

Monaci, Gianluca; Sommer, Friedrich T.; Vandergheynst, Pierre

2008-01-01

This paper presents a novel framework to learn sparse represen- tations for audiovisual signals. An audiovisual signal is modeled as a sparse sum of audiovisual kernels. The kernels are bimodal functions made of synchronous audio and video components that can be positioned independently and arbitrarily in space and time. We design an algorithm capable of learning sets of such audiovi- sual, synchronous, shift-invariant functions by alternatingly solving a coding and a learning pr...

Does Post Septoplasty Nasal Packing Reduce Complications?

Directory of Open Access Journals (Sweden)

Bijan Naghibzadeh

2011-01-01

Full Text Available The main issues in nasal surgery are to stabilize the nose in the good position after surgery and preserve the cartilages and bones in the favorable situation and reduce the risk of deviation recurrence. Also it is necessary to avoid the synechia formation, nasal valve narrowing, hematoma and bleeding. Due to the above mentioned problems and in order to solve and minimize them nasal packing, nasal splint and nasal mold have been advised. Patients for whom the nasal packing used may faced to some problems like naso-pulmonary reflex, intractable pain, sleep disorder, post operation infection and very dangerous complication like toxic shock syndrome. We have two groups of patients and three surgeons (one of the surgeons used post operative nasal packing in his patients and the two others surgeons did not.Complications and morbidities were compared in these two groups. Comparing the two groups showed that the rate of complication and morbidities between these two groups were same and the differences were not valuable, except the pain and discomfort post operatively and at the time of its removal. Nasal packing has several risks for the patients while its effects are not studied. Septoplasty can be safely performed without postoperative nasal packing. Nasal packing had no main findings that compensated its usage. Septal suture is one of the procedures that can be used as alternative method to nasal packing. Therefore the nasal packing after septoplasty should be reserved for the patients with increased risk of bleeding.

Support agnostic Bayesian matching pursuit for block sparse signals

KAUST Repository

Masood, Mudassir

2013-05-01

A fast matching pursuit method using a Bayesian approach is introduced for block-sparse signal recovery. This method performs Bayesian estimates of block-sparse signals even when the distribution of active blocks is non-Gaussian or unknown. It is agnostic to the distribution of active blocks in the signal and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data and no user intervention is required. The method requires a priori knowledge of block partition and utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE) estimate of the block-sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.

To compare efficacy & discomfort in posterior nasal packing with foley's catheters versus bipp gauze packing in cases of posterior epistaxis

International Nuclear Information System (INIS)

Khan, M.A.; Ahmed, A.

2015-01-01

To compare efficacy and discomfort in posterior nasal packing with Foley's catheters versus BIPP gauze packing in cases of posterior epistaxis. Study Design: Randomized controlled trial. Place and Duration of Study: Combined Military Hospital (CMH) Kharian from October 2011 to October 2013. Material and Methods: A total of 206 patients of posterior epistaxis were included in the study through non-probability convenience sampling and randomly divided in two groups of 103 each. In group A patients were treated by posterior nasal packing with Foley's catheter and in group B patients were treated by posterior nasal packing with BIPP gauze and results in terms of control of epistaxis and discomfort during pack insertion, while the packs were in situ and pack removal, based on VAS (Visual Analogue Scale) were observed. Results: Average age in group A was 52.64 years (SD=9.57) and in group B it was 50.27 years (SD ± 10.13). There were 71 (68.9%) males in group A while 67 (65%) males in group B. During posterior nasal pack insertion, the mean pain score in Group A was 6.21 (SD ± I.13) and in Group B was 7.43 (SD ± 1.19). The mean pain score with the pack in situ was 4.27 (SD ± 0.08) in Group A versus 4.76 (SD ± 0.09) Group B. Similarly pack removal was also more painful in group B than group A (6.14 ± 0.91 vs 6.89 ± 1.09) (p =0.000). In the group A, 31 (30.1%) patients had rebleeding after pack removal, out of which 9 (8.7%) had significant bleeding requiring repacking. In 22 (21.4%) cases there was mild bleeding which settled without repacking. In group B 22 (21.4%) patients had rebleeding after pack removal, out of which 5 (4.7%) had significant bleeding requiring repacking. Conclusion: It is concluded that posterior nasal packing with BIPP gauze pack is effective for controlling posterior epistaxis but causes more discomfort to the patients as compared to Foley's catheter packing. (author)

Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging

KAUST Repository

Desmal, Abdulla

2014-05-04

Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.

Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging

KAUST Repository

Desmal, Abdulla

2014-01-06

Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.

Electromagnetic Formation Flight (EMFF) for Sparse Aperture Arrays

Science.gov (United States)

Kwon, Daniel W.; Miller, David W.; Sedwick, Raymond J.

2004-01-01

Traditional methods of actuating spacecraft in sparse aperture arrays use propellant as a reaction mass. For formation flying systems, propellant becomes a critical consumable which can be quickly exhausted while maintaining relative orientation. Additional problems posed by propellant include optical contamination, plume impingement, thermal emission, and vibration excitation. For these missions where control of relative degrees of freedom is important, we consider using a system of electromagnets, in concert with reaction wheels, to replace the consumables. Electromagnetic Formation Flight sparse apertures, powered by solar energy, are designed differently from traditional propulsion systems, which are based on V. This paper investigates the design of sparse apertures both inside and outside the Earth's gravity field.

Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging

KAUST Repository

Desmal, Abdulla; Bagci, Hakan

2014-01-01

Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.

A comprehensive study of sparse codes on abnormality detection

DEFF Research Database (Denmark)

Ren, Huamin; Pan, Hong; Olsen, Søren Ingvor

2017-01-01

Sparse representation has been applied successfully in abnor-mal event detection, in which the baseline is to learn a dic-tionary accompanied by sparse codes. While much empha-sis is put on discriminative dictionary construction, there areno comparative studies of sparse codes regarding abnormal-ity...... detection. We comprehensively study two types of sparsecodes solutions - greedy algorithms and convex L1-norm so-lutions - and their impact on abnormality detection perfor-mance. We also propose our framework of combining sparsecodes with different detection methods. Our comparative ex-periments are carried...

Support agnostic Bayesian matching pursuit for block sparse signals

KAUST Repository

Masood, Mudassir; Al-Naffouri, Tareq Y.

2013-01-01

priori knowledge of block partition and utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE) estimate of the block-sparse signal

Suppression of the green photoluminescence band in ZnO embedded into porous opal by spray pyrolysis

International Nuclear Information System (INIS)

Abrarov, S.M.; Yuldashev, Sh.U.; Lee, S.B.; Kang, T.W.

2004-01-01

The photoluminescence (PL) and transmittance characteristics of the zinc oxide embedded into voids of FCC sub-micron packed silicon dioxide spheres by using technologically simple and inexpensive spray pyrolysis are reported. The uniform formation of ZnO nanocrystalline particles inside of the porous opal takes place after deposition in aqueous solution with zinc nitrite hexahydride precursor followed by thermal annealing. The decrease of green PL is observed due to the inhibition of spontaneous emission through oxygen vacancies in ZnO. The strong red shift of the transmittance characteristics signifies the essential filling of voids in the opal matrix

A Quantitative Study on Packing Density and Pozzolanic Activity of Cementitious Materials Based on the Compaction Packing Model

International Nuclear Information System (INIS)

Gong, Jianqing; Chou, Kai; Huang, Zheng Yu; Zhao, Minghua

2014-01-01

A brief introduction to the theoretical basis of compaction packing model (CPM) and an over-view of the principle of the specific strength method provided the starting point of this study. Then, research on quantitative relations was carried out to find the correlation between the contribution rate of the pozzolanic activity and the contribution value of packing density when CPM was applied to fine powder mixture systems. The concept of the contribution value of the packing density being in direct correspondence with the contribution rate was proved by the compressive strength results and SEM images. The results indicated that the variation rule of the contribution rate of the pozzolanic activity is similar to that of the contribution value of packing density as calculated by CPM. This means the contribution value of the packing density could approximately simulate the change tendency of the contribution rate of the pozzolanic activity, which is of significant value for the future of mix designs for high and ultra-high performance concrete

Selectivity and sparseness in randomly connected balanced networks.

Directory of Open Access Journals (Sweden)

Cengiz Pehlevan

Full Text Available Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.

SPARSE ELECTROMAGNETIC IMAGING USING NONLINEAR LANDWEBER ITERATIONS

KAUST Repository

Desmal, Abdulla

2015-07-29

A scheme for efficiently solving the nonlinear electromagnetic inverse scattering problem on sparse investigation domains is described. The proposed scheme reconstructs the (complex) dielectric permittivity of an investigation domain from fields measured away from the domain itself. Least-squares data misfit between the computed scattered fields, which are expressed as a nonlinear function of the permittivity, and the measured fields is constrained by the L0/L1-norm of the solution. The resulting minimization problem is solved using nonlinear Landweber iterations, where at each iteration a thresholding function is applied to enforce the sparseness-promoting L0/L1-norm constraint. The thresholded nonlinear Landweber iterations are applied to several two-dimensional problems, where the ``measured\\'\\' fields are synthetically generated or obtained from actual experiments. These numerical experiments demonstrate the accuracy, efficiency, and applicability of the proposed scheme in reconstructing sparse profiles with high permittivity values.

Vector sparse representation of color image using quaternion matrix analysis.

Science.gov (United States)

Xu, Yi; Yu, Licheng; Xu, Hongteng; Zhang, Hao; Nguyen, Truong

2015-04-01

Traditional sparse image models treat color image pixel as a scalar, which represents color channels separately or concatenate color channels as a monochrome image. In this paper, we propose a vector sparse representation model for color images using quaternion matrix analysis. As a new tool for color image representation, its potential applications in several image-processing tasks are presented, including color image reconstruction, denoising, inpainting, and super-resolution. The proposed model represents the color image as a quaternion matrix, where a quaternion-based dictionary learning algorithm is presented using the K-quaternion singular value decomposition (QSVD) (generalized K-means clustering for QSVD) method. It conducts the sparse basis selection in quaternion space, which uniformly transforms the channel images to an orthogonal color space. In this new color space, it is significant that the inherent color structures can be completely preserved during vector reconstruction. Moreover, the proposed sparse model is more efficient comparing with the current sparse models for image restoration tasks due to lower redundancy between the atoms of different color channels. The experimental results demonstrate that the proposed sparse image model avoids the hue bias issue successfully and shows its potential as a general and powerful tool in color image analysis and processing domain.

Power Packing

Centers for Disease Control (CDC) Podcasts

2011-08-16

In this podcast for kids, the Kidtastics talk about how to pack a lunch safely, to help keep you from getting sick.  Created: 8/16/2011 by National Center for Emerging and Zoonotic Infectious Diseases (NCEZID).   Date Released: 8/16/2011.

Capillary pressure-saturation relationships for porous granular materials: Pore morphology method vs. pore unit assembly method

Science.gov (United States)

Sweijen, Thomas; Aslannejad, Hamed; Hassanizadeh, S. Majid

2017-09-01

In studies of two-phase flow in complex porous media it is often desirable to have an estimation of the capillary pressure-saturation curve prior to measurements. Therefore, we compare in this research the capability of three pore-scale approaches in reproducing experimentally measured capillary pressure-saturation curves. To do so, we have generated 12 packings of spheres that are representative of four different glass-bead packings and eight different sand packings, for which we have found experimental data on the capillary pressure-saturation curve in the literature. In generating the packings, we matched the particle size distributions and porosity values of the granular materials. We have used three different pore-scale approaches for generating the capillary pressure-saturation curves of each packing: i) the Pore Unit Assembly (PUA) method in combination with the Mayer and Stowe-Princen (MS-P) approximation for estimating the entry pressures of pore throats, ii) the PUA method in combination with the hemisphere approximation, and iii) the Pore Morphology Method (PMM) in combination with the hemisphere approximation. The three approaches were also used to produce capillary pressure-saturation curves for the coating layer of paper, used in inkjet printing. Curves for such layers are extremely difficult to determine experimentally, due to their very small thickness and the presence of extremely small pores (less than one micrometer in size). Results indicate that the PMM and PUA-hemisphere method give similar capillary pressure-saturation curves, because both methods rely on a hemisphere to represent the air-water interface. The ability of the hemisphere approximation and the MS-P approximation to reproduce correct capillary pressure seems to depend on the type of particle size distribution, with the hemisphere approximation working well for narrowly distributed granular materials.

Decontamination of pesticide packing using ionizing radiation

International Nuclear Information System (INIS)

Duarte, C.L.; Mori, M.N.; Kodama, Yasko; Oikawa, H.; Sampa, M.H.O.

2007-01-01

The Brazilian agriculture activities have consumed about 288,000 tons of pesticides per year conditioned in about 107,000,000 packing with weight of approximately 23,000 tons. The discharge of empty plastic packing of pesticides can be an environmental concern causing problems to human health, animals, and plants if done without inspection and monitoring. The objective of this work is to study the ionizing radiation effect in the main pesticides used in Brazil for plastic packing decontamination. Among the commercial pesticides, chlorpyrifos has significant importance because of its wide distribution and extensive use and persistence. The radiation-induced degradation of chlorpyrifos in liquid samples and in polyethylene pack was studied by gamma radiolysis. Packing of high-density polyethylene (HDPE) three layer coextruded, named COEX, contaminated with chlorpyrifos, were irradiated using both a multipurpose Co-60 gamma irradiator and a gamma source with 5000 Ci total activity Gamma cell type. The chemical analysis of the chlorpyrifos was made using a gas chromatography associated to the Mass Spectrometry-GCMS from Shimadzu Model QP 5000. Gamma radiation was efficient for removing chlorpyrifos from the plastic packing, in all studied cases

Decontamination of pesticide packing using ionizing radiation

Energy Technology Data Exchange (ETDEWEB)

Duarte, C.L. [Instituto de Pesquisas Energeticas e Nucleares-IPEN-CNEN/SP Av. Lineu Prestes 2.242, 05508-900, Sao Paulo, SP (Brazil)], E-mail: clduarte@ipen.br; Mori, M.N.; Kodama, Yasko; Oikawa, H.; Sampa, M.H.O. [Instituto de Pesquisas Energeticas e Nucleares-IPEN-CNEN/SP Av. Lineu Prestes 2.242, 05508-900, Sao Paulo, SP (Brazil)

2007-11-15

The Brazilian agriculture activities have consumed about 288,000 tons of pesticides per year conditioned in about 107,000,000 packing with weight of approximately 23,000 tons. The discharge of empty plastic packing of pesticides can be an environmental concern causing problems to human health, animals, and plants if done without inspection and monitoring. The objective of this work is to study the ionizing radiation effect in the main pesticides used in Brazil for plastic packing decontamination. Among the commercial pesticides, chlorpyrifos has significant importance because of its wide distribution and extensive use and persistence. The radiation-induced degradation of chlorpyrifos in liquid samples and in polyethylene pack was studied by gamma radiolysis. Packing of high-density polyethylene (HDPE) three layer coextruded, named COEX, contaminated with chlorpyrifos, were irradiated using both a multipurpose Co-60 gamma irradiator and a gamma source with 5000 Ci total activity Gamma cell type. The chemical analysis of the chlorpyrifos was made using a gas chromatography associated to the Mass Spectrometry-GCMS from Shimadzu Model QP 5000. Gamma radiation was efficient for removing chlorpyrifos from the plastic packing, in all studied cases.

Structured packing: an opportunity for energy savings

International Nuclear Information System (INIS)

Chavez T, R.H.; Guadarrama G, J.J.

1996-01-01

This work emphasizes the advantages about the use of structured packing. This type of packings allows by its geometry to reduce the processing time giving energy savings and throw down the production costs in several industries such as heavy water production plants, petrochemical industry and all industries involved with separation processes. There is a comparative results of energy consumption utilizing the structured vs. Raschig packings. (Author)

Fast convolutional sparse coding using matrix inversion lemma

Czech Academy of Sciences Publication Activity Database

Šorel, Michal; Šroubek, Filip

2016-01-01

Roč. 55, č. 1 (2016), s. 44-51 ISSN 1051-2004 R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : Convolutional sparse coding * Feature learning * Deconvolution networks * Shift-invariant sparse coding Subject RIV: JD - Computer Applications, Robotics Impact factor: 2.337, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/sorel-0459332.pdf

Structure-based bayesian sparse reconstruction

KAUST Repository

Quadeer, Ahmed Abdul; Al-Naffouri, Tareq Y.

2012-01-01

Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical

Pore-Scale Investigation of Micron-Size Polyacrylamide Elastic Microspheres (MPEMs) Transport and Retention in Saturated Porous Media

KAUST Repository

Yao, Chuanjin

2014-05-06

Knowledge of micrometer-size polyacrylamide elastic microsphere (MPEM) transport and retention mechanisms in porous media is essential for the application of MPEMs as a smart sweep improvement and profile modification agent in improving oil recovery. A transparent micromodel packed with translucent quartz sand was constructed and used to investigate the pore-scale transport, surface deposition-release, and plugging deposition-remigration mechanisms of MPEMs in porous media. The results indicate that the combination of colloidal and hydrodynamic forces controls the deposition and release of MPEMs on pore-surfaces; the reduction of fluid salinity and the increase of Darcy velocity are beneficial to the MPEM release from pore-surfaces; the hydrodynamic forces also influence the remigration of MPEMs in pore-throats. MPEMs can plug pore-throats through the mechanisms of capture-plugging, superposition-plugging, and bridge-plugging, which produces resistance to water flow; the interception with MPEM particulate filters occurring in the interior of porous media can enhance the plugging effect of MPEMs; while the interception with MPEM particulate filters occurring at the surface of low-permeability layer can prevent the low-permeability layer from being damaged by MPEMs. MPEMs can remigrate in pore-throats depending on their elasticity through four steps of capture-plugging, elastic deformation, steady migration, and deformation recovery. © 2014 American Chemical Society.

Binary Sparse Phase Retrieval via Simulated Annealing

Directory of Open Access Journals (Sweden)

Wei Peng

2016-01-01

Full Text Available This paper presents the Simulated Annealing Sparse PhAse Recovery (SASPAR algorithm for reconstructing sparse binary signals from their phaseless magnitudes of the Fourier transform. The greedy strategy version is also proposed for a comparison, which is a parameter-free algorithm. Sufficient numeric simulations indicate that our method is quite effective and suggest the binary model is robust. The SASPAR algorithm seems competitive to the existing methods for its efficiency and high recovery rate even with fewer Fourier measurements.

27 CFR 24.308 - Bottled or packed wine record.

Science.gov (United States)

2010-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Bottled or packed wine... BUREAU, DEPARTMENT OF THE TREASURY LIQUORS WINE Records and Reports § 24.308 Bottled or packed wine record. A proprietor who bottles, packs, or receives bottled or packed beverage wine in bond shall...

Confidence of model based shape reconstruction from sparse data

DEFF Research Database (Denmark)

Baka, N.; de Bruijne, Marleen; Reiber, J. H. C.

2010-01-01

Statistical shape models (SSM) are commonly applied for plausible interpolation of missing data in medical imaging. However, when fitting a shape model to sparse information, many solutions may fit the available data. In this paper we derive a constrained SSM to fit noisy sparse input landmarks...

Proportionate Minimum Error Entropy Algorithm for Sparse System Identification

Directory of Open Access Journals (Sweden)

Zongze Wu

2015-08-01

Full Text Available Sparse system identification has received a great deal of attention due to its broad applicability. The proportionate normalized least mean square (PNLMS algorithm, as a popular tool, achieves excellent performance for sparse system identification. In previous studies, most of the cost functions used in proportionate-type sparse adaptive algorithms are based on the mean square error (MSE criterion, which is optimal only when the measurement noise is Gaussian. However, this condition does not hold in most real-world environments. In this work, we use the minimum error entropy (MEE criterion, an alternative to the conventional MSE criterion, to develop the proportionate minimum error entropy (PMEE algorithm for sparse system identification, which may achieve much better performance than the MSE based methods especially in heavy-tailed non-Gaussian situations. Moreover, we analyze the convergence of the proposed algorithm and derive a sufficient condition that ensures the mean square convergence. Simulation results confirm the excellent performance of the new algorithm.

Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering

KAUST Repository

Sicat, Ronell Barrera

2014-12-31

This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined in the 4D domain jointly comprising the 3D volume and its 1D intensity range. Crucially, the computation of sparse pdf volumes exploits data coherence in 4D, resulting in a sparse representation with surprisingly low storage requirements. At run time, we dynamically apply transfer functions to the pdfs using simple and fast convolutions. Whereas standard low-pass filtering and down-sampling incur visible differences between resolution levels, the use of pdfs facilitates consistent results independent of the resolution level used. We describe the efficient out-of-core computation of large-scale sparse pdf volumes, using a novel iterative simplification procedure of a mixture of 4D Gaussians. Finally, our data structure is optimized to facilitate interactive multi-resolution volume rendering on GPUs.

Hashish Body Packing: A Case Report

Directory of Open Access Journals (Sweden)

Manuel Jesus Soriano-Perez

2009-01-01

Full Text Available A 42-year-old African male was brought by the police to the emergency department under suspicion of drug smuggling by body-packing. Plain abdominal radiograph showed multiple foreign bodies within the gastrointestinal tract. Contrast-enhanced abdominal CT confirmed the findings, and the patient admitted to have swallowed “balls” of hashish. Body-packing is a recognized method of smuggling drugs across international borders. Body packers may present to the emergency department because of drug toxicity, intestinal obstruction, or more commonly, requested by law-enforcement officers for medical confirmation or exclusion of suspected body packing.

36 CFR 34.10 - Saddle and pack animals.

Science.gov (United States)

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Saddle and pack animals. 34... INTERIOR EL PORTAL ADMINISTRATIVE SITE REGULATIONS § 34.10 Saddle and pack animals. The use of saddle and pack animals is prohibited without a permit from the Superintendent. ...

CoolPack – Simulation tools for refrigeration systems

DEFF Research Database (Denmark)

Jakobsen, Arne; Rasmussen, Bjarne D.; Andersen, Simon Engedal

1999-01-01

CoolPack is a collection of programs used for energy analysis and optimisation of refrigeration systems. CoolPack is developed at the Department of Energy Engineering at the Technical University of Denmark. The Danish Energy Agency finances the project. CoolPack is freeware and can be downloaded...

Simulation of abuse tolerance of lithium-ion battery packs

Energy Technology Data Exchange (ETDEWEB)

Spotnitz, Robert M.; Weaver, James; Yeduvaka, Gowri [Battery Design LLC, 2277 DeLucchi Drive, Pleasanton, CA 94588 (United States); Doughty, D.H.; Roth, E.P. [Lithium Battery Department, Sandia National Laboratories, Albuquerque, NM 87185 (United States)

2007-01-01

A simple approach for using accelerating rate calorimetry data to simulate the thermal abuse resistance of battery packs is described. The thermal abuse tolerance of battery packs is estimated based on the exothermic behavior of a single cell and an energy balance than accounts for radiative, conductive, and convective heat transfer modes of the pack. For the specific example of a notebook computer pack containing eight 18650-size cells, the effects of cell position, heat of reaction, and heat-transfer coefficient are explored. Thermal runaway of the pack is more likely to be induced by thermal runaway of a single cell when that cell is in good contact with other cells and is close to the pack wall. (author)

Hardfacing and packings for improved valve performance

International Nuclear Information System (INIS)

Aikin, J.A.; Patrick, J.N.F.; Inglis, I.

2003-01-01

The CANDU Owners Group (COG), Chemistry, Materials and Components (CMC) Program has supported an ongoing program on valve maintenance and performance for several years. An overview is presented of recent work on iron-based hardfacing, packing qualification, friction testing of polytetrafluoroethylene (PTFE) packings, and an investigation of re-torquing valve packing. Based on this program, two new valve-packing materials have been qualified for use in CANDU stations. By doing this, CANDU maintenance can avoid having only one packing qualified for station use, as well as assess the potential impact of the industry trend towards using lower gland loads. The results from corrosion tests by AECL and the coefficient of friction studies at Battelle' s tribology testing facilities on Delcrome 910, an iron-based hardfacing alloy, indicate it is an acceptable replacement for Stellite 6 under certain conditions. This information can be used to update in-line valve purchasing specifications. The renewed interest in friction characteristics, and environmental qualification (EQ) of packing containing PTFE has resulted in a new test program in these areas. The COG-funded valve programs have resulted in modifications to design specifications for nuclear station in-line valves and have led to better maintenance practices and valve reliability. In the end, this means lower costs and cheaper electricity. (author)

Ordering sparse matrices for cache-based systems

International Nuclear Information System (INIS)

Biswas, Rupak; Oliker, Leonid

2001-01-01

The Conjugate Gradient (CG) algorithm is the oldest and best-known Krylov subspace method used to solve sparse linear systems. Most of the coating-point operations within each CG iteration is spent performing sparse matrix-vector multiplication (SPMV). We examine how various ordering and partitioning strategies affect the performance of CG and SPMV when different programming paradigms are used on current commercial cache-based computers. However, a multithreaded implementation on the cacheless Cray MTA demonstrates high efficiency and scalability without any special ordering or partitioning

A flexible framework for sparse simultaneous component based data integration

Directory of Open Access Journals (Sweden)

Van Deun Katrijn

2011-11-01

Full Text Available Abstract 1 Background High throughput data are complex and methods that reveal structure underlying the data are most useful. Principal component analysis, frequently implemented as a singular value decomposition, is a popular technique in this respect. Nowadays often the challenge is to reveal structure in several sources of information (e.g., transcriptomics, proteomics that are available for the same biological entities under study. Simultaneous component methods are most promising in this respect. However, the interpretation of the principal and simultaneous components is often daunting because contributions of each of the biomolecules (transcripts, proteins have to be taken into account. 2 Results We propose a sparse simultaneous component method that makes many of the parameters redundant by shrinking them to zero. It includes principal component analysis, sparse principal component analysis, and ordinary simultaneous component analysis as special cases. Several penalties can be tuned that account in different ways for the block structure present in the integrated data. This yields known sparse approaches as the lasso, the ridge penalty, the elastic net, the group lasso, sparse group lasso, and elitist lasso. In addition, the algorithmic results can be easily transposed to the context of regression. Metabolomics data obtained with two measurement platforms for the same set of Escherichia coli samples are used to illustrate the proposed methodology and the properties of different penalties with respect to sparseness across and within data blocks. 3 Conclusion Sparse simultaneous component analysis is a useful method for data integration: First, simultaneous analyses of multiple blocks offer advantages over sequential and separate analyses and second, interpretation of the results is highly facilitated by their sparseness. The approach offered is flexible and allows to take the block structure in different ways into account. As such

A flexible framework for sparse simultaneous component based data integration.

Science.gov (United States)

Van Deun, Katrijn; Wilderjans, Tom F; van den Berg, Robert A; Antoniadis, Anestis; Van Mechelen, Iven

2011-11-15

High throughput data are complex and methods that reveal structure underlying the data are most useful. Principal component analysis, frequently implemented as a singular value decomposition, is a popular technique in this respect. Nowadays often the challenge is to reveal structure in several sources of information (e.g., transcriptomics, proteomics) that are available for the same biological entities under study. Simultaneous component methods are most promising in this respect. However, the interpretation of the principal and simultaneous components is often daunting because contributions of each of the biomolecules (transcripts, proteins) have to be taken into account. We propose a sparse simultaneous component method that makes many of the parameters redundant by shrinking them to zero. It includes principal component analysis, sparse principal component analysis, and ordinary simultaneous component analysis as special cases. Several penalties can be tuned that account in different ways for the block structure present in the integrated data. This yields known sparse approaches as the lasso, the ridge penalty, the elastic net, the group lasso, sparse group lasso, and elitist lasso. In addition, the algorithmic results can be easily transposed to the context of regression. Metabolomics data obtained with two measurement platforms for the same set of Escherichia coli samples are used to illustrate the proposed methodology and the properties of different penalties with respect to sparseness across and within data blocks. Sparse simultaneous component analysis is a useful method for data integration: First, simultaneous analyses of multiple blocks offer advantages over sequential and separate analyses and second, interpretation of the results is highly facilitated by their sparseness. The approach offered is flexible and allows to take the block structure in different ways into account. As such, structures can be found that are exclusively tied to one data platform

Experimental, kinetic and numerical modeling of hydrogen production by catalytic reforming of crude ethanol over a commercial catalyst in packed bed tubular reactor and packed bed membrane reactor

International Nuclear Information System (INIS)

Aboudheir, Ahmed; Akande, Abayomi; Idem, Raphael

2006-01-01

reactor. The model was based on the coupling of mass, momentum and energy balance equations as well as our new kinetic model developed for this process.The simulation results for crude ethanol conversion were found to be in accordance with the experimental data obtained at various operating conditions. In addition, the predicted variations of the concentration and temperature profiles for our process. In the radial direction indicate that the assumption of plug flow and isothermal behaviour is justified within certain kinetics operating conditions. However, even within these operating conditions, our results have proven that the axial dispersion terms in the balance equations (mass, momentum and energy) cannot be neglected, especially in the hypothetical industrial case presented in this work for the reforming of crude ethanol. In addition, in the experimental study of the application of a porous membrane reactor for the crude ethanol reforming process conducted to compare with that for the packed bed tubular reactor, it was found that the membrane reactor outperformed the packed bed tubular reactor in terms of crude ethanol conversion and hydrogen production. This is due to the function of the membrane reactor to shift the thermodynamic equilibrium in favour of the conversion of crude ethanol to hydrogen according to Le Catelier-Braun's law.(Author)

P-SPARSLIB: A parallel sparse iterative solution package

Energy Technology Data Exchange (ETDEWEB)

Saad, Y. [Univ. of Minnesota, Minneapolis, MN (United States)

1994-12-31

Iterative methods are gaining popularity in engineering and sciences at a time where the computational environment is changing rapidly. P-SPARSLIB is a project to build a software library for sparse matrix computations on parallel computers. The emphasis is on iterative methods and the use of distributed sparse matrices, an extension of the domain decomposition approach to general sparse matrices. One of the goals of this project is to develop a software package geared towards specific applications. For example, the author will test the performance and usefulness of P-SPARSLIB modules on linear systems arising from CFD applications. Equally important is the goal of portability. In the long run, the author wishes to ensure that this package is portable on a variety of platforms, including SIMD environments and shared memory environments.

Structural characterization of the packings of granular regular polygons.

Science.gov (United States)

Wang, Chuncheng; Dong, Kejun; Yu, Aibing

2015-12-01

By using a recently developed method for discrete modeling of nonspherical particles, we simulate the random packings of granular regular polygons with three to 11 edges under gravity. The effects of shape and friction on the packing structures are investigated by various structural parameters, including packing fraction, the radial distribution function, coordination number, Voronoi tessellation, and bond-orientational order. We find that packing fraction is generally higher for geometrically nonfrustrated regular polygons, and can be increased by the increase of edge number and decrease of friction. The changes of packing fraction are linked with those of the microstructures, such as the variations of the translational and orientational orders and local configurations. In particular, the free areas of Voronoi tessellations (which are related to local packing fractions) can be described by log-normal distributions for all polygons. The quantitative analyses establish a clearer picture for the packings of regular polygons.

Particle and solute migration in porous media. Modeling of simultaneous transport of clay particles and radionuclides in a salinity gradient

International Nuclear Information System (INIS)

Faure, M.H.

1994-03-01

Understanding the mechanisms which control the transient transport of particles and radionuclides in natural and artificial porous media is a key problem for the assessment of safety of radioactive waste disposals. An experimental study has been performed to characterize the clayey particle mobility in porous media: a laboratory- made column, packed with an unconsolidated sand bentonite (5% weight) sample, is flushed with a salt solution. An original method of salinity gradient allowed us to show and to quantify some typical behaviours of this system: threshold effects in the peptization of particles, creation of preferential pathways, formation of immobile water zones induce solute-transfer limitation. The mathematical modelling accounts for a phenomenological law, where the distribution of particles between the stagnant water zone and the porous medium is a function of sodium chloride concentration. This distribution function is associated with a radionuclide adsorption model, and is included in a convective dispersive transport model with stagnant water zones. It allowed us to simulate the particle and solute transport when the salt environment is modified. The complete model has been validated with experiments involving cesium, calcium and neptunium in a sodium chloride gradient. (author). refs., figs., tabs

Max–min Bin Packing Algorithm and its application in nano-particles filling

International Nuclear Information System (INIS)

Zhu, Dingju

2016-01-01

With regard to existing bin packing algorithms, higher packing efficiency often leads to lower packing speed while higher packing speed leads to lower packing efficiency. Packing speed and packing efficiency of existing bin packing algorithms including NFD, NF, FF, FFD, BF and BFD correlates negatively with each other, thus resulting in the failure of existing bin packing algorithms to satisfy the demand of nano-particles filling for both high speed and high efficiency. The paper provides a new bin packing algorithm, Max–min Bin Packing Algorithm (MM), which realizes both high packing speed and high packing efficiency. MM has the same packing speed as NFD (whose packing speed ranks no. 1 among existing bin packing algorithms); in case that the size repetition rate of objects to be packed is over 5, MM can realize almost the same packing efficiency as BFD (whose packing efficiency ranks No. 1 among existing bin packing algorithms), and in case that the size repetition rate of objects to be packed is over 500, MM can achieve exactly the same packing efficiency as BFD. With respect to application of nano-particles filling, the size repetition rate of nano particles to be packed is usually in thousands or ten thousands, far higher than 5 or 500. Consequently, in application of nano-particles filling, the packing efficiency of MM is exactly equal to that of BFD. Thus the irreconcilable conflict between packing speed and packing efficiency is successfully removed by MM, which leads to MM having better packing effect than any existing bin packing algorithm. In practice, there are few cases when the size repetition of objects to be packed is lower than 5. Therefore the MM is not necessarily limited to nano-particles filling, and can also be widely used in other applications besides nano-particles filling. Especially, MM has significant value in application of nano-particles filling such as nano printing and nano tooth filling.

Focused Flow During Infiltration Into Ethanol-Contaminated Unsaturated Porous Media

Science.gov (United States)

Jazwiec, A.; Smith, J. E.

2017-12-01

The increasing commercial and industrial use of ethanol, e.g. in biofuels, has generated increased incidents of vadose zone contamination by way of ethanol spills and releases. This has increased the interest in better understanding behaviors of ethanol in unsaturated porous media and it's multiphase interactions in the vadose zone. This study uses highly controlled laboratory experiments in a 2-D (0.6mx0.6mx0.01m) flow cell to investigate water infiltration behaviors into ethanol-contaminated porous media. Ethanol and water were applied by either constant head or constant flux methods onto the surface of sands homogenously packed into the flow cell. The constant flux experiments at both low and high application rates were conducted using a rainulator with a row of hypodermic needles connected to a peristaltic pump. The constant head experiments were conducted using an 8cm diameter tension disk infiltrometer set to both low and high tensions. The presence of ethanol contamination generated solute-dependent capillarity induced focused flow (SCIFF) of water infiltration, which was primarily due to decreases in interfacial tensions at the air-liquid interfaces in the unsaturated sands as a function of ethanol concentration. SCIFF was clearly expressed as an unsaturated water flow phenomenon comprised of narrowly focused vertical flow fingers of water within the initially ethanol contaminated porous media. Using analyses of photos and video, comparisons were made between constant flux and constant head application methods. Further comparisons were made between low and high infiltration rates and the two sand textures used. A high degree of sensitivity to minor heterogeneity in relatively homogeneous sands was also observed. The results of this research have implications for rainfall infiltration into ethanol contaminated vadose zones expressing SCIFF, including implications for associated mass fluxes and the nature of flushing of ethanol from the unsaturated zone to

Feature selection and multi-kernel learning for sparse representation on a manifold

KAUST Repository

Wang, Jim Jing-Yan

2014-03-01

Sparse representation has been widely studied as a part-based data representation method and applied in many scientific and engineering fields, such as bioinformatics and medical imaging. It seeks to represent a data sample as a sparse linear combination of some basic items in a dictionary. Gao etal. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity graph constructed directly from the original feature space is not necessarily a reliable reflection of the intrinsic manifold of the data samples. To overcome this problem, we integrate feature selection and multiple kernel learning into the sparse coding on the manifold. To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization. By optimizing the objective functions iteratively, we develop novel data representation algorithms with feature selection and multiple kernel learning respectively. Experimental results on two challenging tasks, N-linked glycosylation prediction and mammogram retrieval, demonstrate that the proposed algorithms outperform the traditional sparse coding methods. © 2013 Elsevier Ltd.

Feature selection and multi-kernel learning for sparse representation on a manifold.

Science.gov (United States)

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2014-03-01

Sparse representation has been widely studied as a part-based data representation method and applied in many scientific and engineering fields, such as bioinformatics and medical imaging. It seeks to represent a data sample as a sparse linear combination of some basic items in a dictionary. Gao et al. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity graph constructed directly from the original feature space is not necessarily a reliable reflection of the intrinsic manifold of the data samples. To overcome this problem, we integrate feature selection and multiple kernel learning into the sparse coding on the manifold. To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization. By optimizing the objective functions iteratively, we develop novel data representation algorithms with feature selection and multiple kernel learning respectively. Experimental results on two challenging tasks, N-linked glycosylation prediction and mammogram retrieval, demonstrate that the proposed algorithms outperform the traditional sparse coding methods. Copyright © 2013 Elsevier Ltd. All rights reserved.

Sparse representation, modeling and learning in visual recognition theory, algorithms and applications

CERN Document Server

Cheng, Hong

2015-01-01

This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: provides a thorough introduction to the fundamentals of sparse representation, modeling and learning, and the application of these techniques in visual recognition; describes sparse recovery approaches, robust and efficient sparse represen

Design Patterns for Sparse-Matrix Computations on Hybrid CPU/GPU Platforms

Directory of Open Access Journals (Sweden)

Valeria Cardellini

2014-01-01

Full Text Available We apply object-oriented software design patterns to develop code for scientific software involving sparse matrices. Design patterns arise when multiple independent developments produce similar designs which converge onto a generic solution. We demonstrate how to use design patterns to implement an interface for sparse matrix computations on NVIDIA GPUs starting from PSBLAS, an existing sparse matrix library, and from existing sets of GPU kernels for sparse matrices. We also compare the throughput of the PSBLAS sparse matrix–vector multiplication on two platforms exploiting the GPU with that obtained by a CPU-only PSBLAS implementation. Our experiments exhibit encouraging results regarding the comparison between CPU and GPU executions in double precision, obtaining a speedup of up to 35.35 on NVIDIA GTX 285 with respect to AMD Athlon 7750, and up to 10.15 on NVIDIA Tesla C2050 with respect to Intel Xeon X5650.

An Efficient GPU General Sparse Matrix-Matrix Multiplication for Irregular Data

DEFF Research Database (Denmark)

Liu, Weifeng; Vinter, Brian

2014-01-01

General sparse matrix-matrix multiplication (SpGEMM) is a fundamental building block for numerous applications such as algebraic multigrid method, breadth first search and shortest path problem. Compared to other sparse BLAS routines, an efficient parallel SpGEMM algorithm has to handle extra...... irregularity from three aspects: (1) the number of the nonzero entries in the result sparse matrix is unknown in advance, (2) very expensive parallel insert operations at random positions in the result sparse matrix dominate the execution time, and (3) load balancing must account for sparse data in both input....... Load balancing builds on the number of the necessary arithmetic operations on the nonzero entries and is guaranteed in all stages. Compared with the state-of-the-art GPU SpGEMM methods in the CUSPARSE library and the CUSP library and the latest CPU SpGEMM method in the Intel Math Kernel Library, our...

Comparison of Methods for Sparse Representation of Musical Signals

DEFF Research Database (Denmark)

Endelt, Line Ørtoft; la Cour-Harbo, Anders

2005-01-01

by a number of sparseness measures and results are shown on the ℓ1 norm of the coefficients, using a dictionary containing a Dirac basis, a Discrete Cosine Transform, and a Wavelet Packet. Evaluated only on the sparseness Matching Pursuit is the best method, and it is also relatively fast....

Joint-2D-SL0 Algorithm for Joint Sparse Matrix Reconstruction

Directory of Open Access Journals (Sweden)

Dong Zhang

2017-01-01

Full Text Available Sparse matrix reconstruction has a wide application such as DOA estimation and STAP. However, its performance is usually restricted by the grid mismatch problem. In this paper, we revise the sparse matrix reconstruction model and propose the joint sparse matrix reconstruction model based on one-order Taylor expansion. And it can overcome the grid mismatch problem. Then, we put forward the Joint-2D-SL0 algorithm which can solve the joint sparse matrix reconstruction problem efficiently. Compared with the Kronecker compressive sensing method, our proposed method has a higher computational efficiency and acceptable reconstruction accuracy. Finally, simulation results validate the superiority of the proposed method.

Forced Convection Heat Transfer of a sphere in Packed Bed Arrangement

International Nuclear Information System (INIS)

Lee, Dong-Young; Chung, Bum-Jin

2016-01-01

This paper analysis and discuss the forced convective heat transfer from heated single sphere, which is buried in unheated packed bed, depending on Re d with porosity. The present work determines the test matrix for the packed bed experiment. And this study discuss difference of heat transfer according to the location of heated sphere and compared heated bed with heated sphere in packed bed and compared FCC (Face Centered Cubic), HCP (Hexagonal Closed Packed) structured packed bed with random packed. This paper is to discuss and make the plan to experiment the heat transfer for depending on location of heated single sphere in unheated packed bed, to compare single sphere in packed bed with heated packed bed and to compare the structured packed bed with random packed bed. The Nu d increase as heated single sphere is close to the wall and bottom because of increasing porosity and enhancing eddy motion respectively. The existing experiment of heated sphere in packed bed do not consider the preheating effect which decrease heat transfer on downstream. The heat transfer rate of structured packed bed is different from random packed bed because of unsteady flow in random packed bed. In this study, mass transfer experiments will replace heat transfer experiments based on analogy concept. An electroplating system is adopted using limiting current technique

Forced Convection Heat Transfer of a sphere in Packed Bed Arrangement

Energy Technology Data Exchange (ETDEWEB)

Lee, Dong-Young; Chung, Bum-Jin [Kyung Hee University, Yongin (Korea, Republic of)

2016-10-15

This paper analysis and discuss the forced convective heat transfer from heated single sphere, which is buried in unheated packed bed, depending on Re{sub d} with porosity. The present work determines the test matrix for the packed bed experiment. And this study discuss difference of heat transfer according to the location of heated sphere and compared heated bed with heated sphere in packed bed and compared FCC (Face Centered Cubic), HCP (Hexagonal Closed Packed) structured packed bed with random packed. This paper is to discuss and make the plan to experiment the heat transfer for depending on location of heated single sphere in unheated packed bed, to compare single sphere in packed bed with heated packed bed and to compare the structured packed bed with random packed bed. The Nu{sub d} increase as heated single sphere is close to the wall and bottom because of increasing porosity and enhancing eddy motion respectively. The existing experiment of heated sphere in packed bed do not consider the preheating effect which decrease heat transfer on downstream. The heat transfer rate of structured packed bed is different from random packed bed because of unsteady flow in random packed bed. In this study, mass transfer experiments will replace heat transfer experiments based on analogy concept. An electroplating system is adopted using limiting current technique.

Discussion of CoSA: Clustering of Sparse Approximations

Energy Technology Data Exchange (ETDEWEB)

Armstrong, Derek Elswick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-03-07

The purpose of this talk is to discuss the possible applications of CoSA (Clustering of Sparse Approximations) to the exploitation of HSI (HyperSpectral Imagery) data. CoSA is presented by Moody et al. in the Journal of Applied Remote Sensing (“Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries”, Vol. 8, 2014) and is based on machine learning techniques.

Prevention and suppression of metal packing fires.

Science.gov (United States)

Roberts, Mark; Rogers, William J; Sam Mannan, M; Ostrowski, Scott W

2003-11-14

Structured packing has been widely used because of large surface area that makes possible columns with high capacity and efficiency. The large surface area also contributes to fire hazards because of hydrocarbon deposits that can easily combust and promote combustion of the thin metal packing materials. Materials of high surface area that can fuel fires include reactive metals, such as titanium, and materials that are not considered combustible, such as stainless steel. Column design and material selection for packing construction is discussed together with employee training and practices for safe column maintenance and operations. Presented also are methods and agents for suppression of metal fires. Guidance for prevention and suppression of metal fires is related to incidents involving packing fires in columns.

Gas anti-solvent precipitation assisted salt leaching for generation of micro- and nano-porous wall in bio-polymeric 3D scaffolds.

Science.gov (United States)

Flaibani, Marina; Elvassore, Nicola

2012-08-01

The mass transport through biocompatible and biodegradable polymeric 3D porous scaffolds may be depleted by non-porous impermeable internal walls. As consequence the concentration of metabolites and growth factors within the scaffold may be heterogeneous leading to different cell fate depending on spatial cell location, and in some cases it may compromise cell survival. In this work, we fabricated polymeric scaffolds with micro- and nano-scale porosity by developing a new technique that couples two conventional scaffold production methods: solvent casting-salt leaching and gas antisolvent precipitation. 10-15 w/w solutions of a hyaluronic benzyl esters (HYAFF11) and poly-(lactic acid) (PLA) were used to fill packed beds of 0.177-0.425 mm NaCl crystals. The polymer precipitation in micro and nano-porous structures between the salt crystals was induced by high-pressure gas, then its flushing extracted the residual solvent. The salt was removed by water-wash. Morphological analysis by scanning electron microscopy showed a uniform porosity (~70%) and a high interconnectivity between porous. The polymeric walls were porous themselves counting for 30% of the total porosity. This wall porosity did not lead to a remarkable change in compressive modulus, deformation, and rupture pressure. Scaffold biocompatibility was tested with murine muscle cell line C2C12 for 4 and 7 days. Viability analysis and histology showed that micro- and nano-porous scaffolds are biocompatible and suitable for 3D cell culture promoting cell adhesion on the polymeric wall and allowing their proliferation in layers. Micro- and nano-scale porosities enhance cell migration and growth in the inner part of the scaffold. Copyright © 2012 Elsevier B.V. All rights reserved.

Domain Discretization and Circle Packings

DEFF Research Database (Denmark)

Dias, Kealey

A circle packing is a configuration of circles which are tangent with one another in a prescribed pattern determined by a combinatorial triangulation, where the configuration fills a planar domain or a two-dimensional surface. The vertices in the triangulation correspond to centers of circles...... to domain discretization problems such as triangulation and unstructured mesh generation techniques. We wish to ask ourselves the question: given a cloud of points in the plane (we restrict ourselves to planar domains), is it possible to construct a circle packing preserving the positions of the vertices...... and constrained meshes having predefined vertices as constraints. A standard method of two-dimensional mesh generation involves conformal mapping of the surface or domain to standardized shapes, such as a disk. Since circle packing is a new technique for constructing discrete conformal mappings, it is possible...

The pursuit of perfect packing

CERN Document Server

Weaire, Denis

2000-01-01

In 1998 Thomas Hales dramatically announced the solution of a problem that has long teased eminent mathematicians: what is the densest possible arrangement of identical spheres? The Pursuit of Perfect Packing recounts the story of this problem and many others that have to do with packing things together. The examples are taken from mathematics, physics, biology, and engineering, including the arrangement of soap bubbles in foam, atoms in a crystal, the architecture of the bee''s honeycomb, and the structure of the Giant''s Causeway. Using an informal style and with key references, the book also includes brief accounts of the lives of many of the scientists who devoted themselves to problems of packing over many centuries, together with wry comments on their efforts. It is an entertaining introduction to the field for both specialists and the more general public.

Random close packing of hard spheres and disks

International Nuclear Information System (INIS)

Berryman, J.G.

1983-01-01

A simple definition of random close packing of hard spheres is presented, and the consequences of this definition are explored. According to this definition, random close packing occurs at the minimum packing fraction eta for which the median nearest-neighbor radius equals the diameter of the spheres. Using the radial distribution function at more dilute concentrations to estimate median nearest-neighbor radii, lower bounds on the critical packing fraction eta/sub RCP/ are obtained and the value of eta/sub RCP/ is estimated by extrapolation. Random close packing is predicted to occur for eta/sub RCP/ = 0.64 +- 0.02 in three dimensions and eta/sub RCP/ = 0.82 +- 0.02 in two dimensions. Both of these predictions are shown to be consistent with the available experimental data

Gas-liquid Relative Permeability Estimation in 2D Porous Media by Lattice Boltzmann Method: Low Viscosity Ratio 2D LBM Relative Permeability

Directory of Open Access Journals (Sweden)

Sadegh Mahmoudi

2013-04-01

Full Text Available This work is a primary achievement in studying the CO2 and N2–oil systems. To predict gas-liquid relative permeability curves, a Shan-Chen type multicomponent multiphase lattice Boltzmann model for two-phase flow through 2D porous media is developed. Periodic and bounce back boundary conditions are applied to the model with the Guo scheme for the external body force (i.e., the pressure gradient. The influence of relationship between cohesion and adsorption parameters and the interfacial tension values in Young's equation, pore structure (micro scan image derived porous media response is compared with corresponding porosity and permeability ideal sphere pack structure, and saturation distribution on relative permeability curves are studied with the aim to achieve the realistic stable condition for the simulation of gas-liquid systems with a low viscosity ratio.

Enabling Microliquid Chromatography by Microbead Packing of Microchannels

Science.gov (United States)

Balvin, Manuel; Zheng, Yun

2014-01-01

The microbead packing is the critical element required in the success of on-chip microfabrication of critical microfluidic components for in-situ analysis and detection of chiral amino acids. In order for microliquid chromatography to occur, there must be a stationary phase medium within the microchannel that interacts with the analytes present within flowing fluid. The stationary phase media are the microbeads packed by the process discussed in this work. The purpose of the microliquid chromatography is to provide a lightweight, low-volume, and low-power element to separate amino acids and their chiral partners efficiently to understand better the origin of life. In order to densely pack microbeads into the microchannels, a liquid slurry of microbeads was created. Microbeads were extracted from a commercially available high-performance liquid chromatography column. The silica beads extracted were 5 microns in diameter, and had surface coating of phenyl-hexyl. These microbeads were mixed with a 200- proof ethanol solution to create a microbead slurry with the right viscosity for packing. A microfilter is placed at the outlet via of the microchannel and the slurry is injected, then withdrawn across a filter using modified syringes. After each injection, the channel is flushed with ethanol to enhance packing. This cycle is repeated numerous times to allow for a tightly packed channel of microbeads. Typical microbead packing occurs in the macroscale into tubes or channels by using highly pressurized systems. Moreover, these channels are typically long and straight without any turns or curves. On the other hand, this method of microbead packing is completed within a microchannel 75 micrometers in diameter. Moreover, the microbead packing is completed into a serpentine type microchannel, such that it maximizes microchannel length within a microchip. Doing so enhances the interactions of the analytes with the microbeads to separate efficiently amino acids and amino acid

New iodine filter pack design

International Nuclear Information System (INIS)

Blackbee, B.A.

1977-10-01

To enable Naval Emergency Monitoring Teams to fulfil their role in the field it was necessary to locate or design a replacement filter pack for the collection of radioactive iodine air samples. Collaboration with the Berkeley Laboratories of the Central Electricity Generating Board provided the necessary starting point for a suitable type of package. Further development by NGTE (West Drayton) yielded the improved filter pack which is the subject of this memorandum. (author)

36 CFR 1002.16 - Horses and pack animals.

Science.gov (United States)

2010-07-01

... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Horses and pack animals. 1002... AND RECREATION § 1002.16 Horses and pack animals. The following are prohibited: (a) The use of animals other than those designated as “pack animals” for purposes of transporting equipment. (b) The use of...

36 CFR 2.16 - Horses and pack animals.

Science.gov (United States)

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Horses and pack animals. 2.16... RESOURCE PROTECTION, PUBLIC USE AND RECREATION § 2.16 Horses and pack animals. The following are prohibited: (a) The use of animals other than those designated as “pack animals” for purposes of transporting...

Facial Expression Recognition via Non-Negative Least-Squares Sparse Coding

Directory of Open Access Journals (Sweden)

Ying Chen

2014-05-01

Full Text Available Sparse coding is an active research subject in signal processing, computer vision, and pattern recognition. A novel method of facial expression recognition via non-negative least squares (NNLS sparse coding is presented in this paper. The NNLS sparse coding is used to form a facial expression classifier. To testify the performance of the presented method, local binary patterns (LBP and the raw pixels are extracted for facial feature representation. Facial expression recognition experiments are conducted on the Japanese Female Facial Expression (JAFFE database. Compared with other widely used methods such as linear support vector machines (SVM, sparse representation-based classifier (SRC, nearest subspace classifier (NSC, K-nearest neighbor (KNN and radial basis function neural networks (RBFNN, the experiment results indicate that the presented NNLS method performs better than other used methods on facial expression recognition tasks.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification

Directory of Open Access Journals (Sweden)

Lu Bing

2017-01-01

Full Text Available We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL. After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM. Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.

Science.gov (United States)

Bing, Lu; Wang, Wei

2017-01-01

We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM). Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Joint sparse representation for robust multimodal biometrics recognition.

Science.gov (United States)

Shekhar, Sumit; Patel, Vishal M; Nasrabadi, Nasser M; Chellappa, Rama

2014-01-01

Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing fusion-based methods.

Colloidal Photoluminescent Amorphous Porous Silicon, Methods Of Making Colloidal Photoluminescent Amorphous Porous Silicon, And Methods Of Using Colloidal Photoluminescent Amorphous Porous Silicon

KAUST Repository

Chaieb, Sahraoui

2015-04-09

Embodiments of the present disclosure provide for a colloidal photoluminescent amorphous porous silicon particle suspension, methods of making a colloidal photoluminescent amorphous porous silicon particle suspension, methods of using a colloidal photoluminescent amorphous porous silicon particle suspension, and the like.

Colloidal Photoluminescent Amorphous Porous Silicon, Methods Of Making Colloidal Photoluminescent Amorphous Porous Silicon, And Methods Of Using Colloidal Photoluminescent Amorphous Porous Silicon

KAUST Repository

Chaieb, Saharoui; Mughal, Asad Jahangir

2015-01-01

Embodiments of the present disclosure provide for a colloidal photoluminescent amorphous porous silicon particle suspension, methods of making a colloidal photoluminescent amorphous porous silicon particle suspension, methods of using a colloidal photoluminescent amorphous porous silicon particle suspension, and the like.

Experimental study on local heat transfer characteristics of porous media with internal heat source

International Nuclear Information System (INIS)

Zan Yuanfeng; Wang Taotao; Xiao Zejun; Wang Fei; Huang Yanping

2008-01-01

Model of porous media with internal heat source is established. The model uses water as flowing media, and the stainless steel test section is packed with steel spheres in manner of regular triangle, respectively. The armoured resistance wire is inserted inside the steel sphere. On the basis of the experimental model, many parameters of the local heat transfer characteristics including current velocity and wall temperature of steel sphere are measured. The experimental results show that the coefficient of heat transfer scarcely changes with pressure. The coefficient of heat transfer increases with the surface heat flux of steel sphere. When raising the inlet temperature of the cooling water, the coefficient of heat transfer presents the descending trend. In addition, the influence of entrance effect on heat transfer is discovered in the experiment, which is much less than the liquid flow in the light tube. After experiment data are analyzed and processed, the relation model of heat transfer on local heat transfer characteristic of porous media with internal heat source was described with a power-law-equation. The deviations between calculation and experimental values are within ±10%. (authors)

Numerical modeling of pyrolysis of sawdust in a packed bed

Energy Technology Data Exchange (ETDEWEB)

Meng, Qingmin; Chen, Xiaoping [Southeast Univ., Nanjing (China). School of Energy and Environment

2013-07-01

An unsteady, one-dimensional mathematical model has been developed to describe the pyrolysis of sawdust in a packed bed. The sawdust bed was pyrolyzed using the hot gas and an electric heater outside the bed as the source of energy. The developed model includes mass, momentum and energy conservations of gas and solid within the bed. The gas flow in the bed is modeled using Darcy's law for fluid through a porous medium. The heat transfer model includes heat conduction inside the bed and convection between the bed and the hot gas. The kinetic model consists of primary pyrolysis reaction. A finite volume fully implicit scheme is employed for solving the heat and mass transfer model equations. A Runge-Kutta fourth order method is used for the chemical kinetics model equations. The model predictions of mass loss history and temperature were validated with published experimental results, showing a good agreement. The effects of inlet temperature on the pyrolysis process have been analyzed with model simulation. A sensitivity analysis using the model suggests that the predictions could be improved by considering the second reaction which could generate volatile flowing in the void.

Robust Visual Tracking Via Consistent Low-Rank Sparse Learning

KAUST Repository

Zhang, Tianzhu

2014-06-19

Object tracking is the process of determining the states of a target in consecutive video frames based on properties of motion and appearance consistency. In this paper, we propose a consistent low-rank sparse tracker (CLRST) that builds upon the particle filter framework for tracking. By exploiting temporal consistency, the proposed CLRST algorithm adaptively prunes and selects candidate particles. By using linear sparse combinations of dictionary templates, the proposed method learns the sparse representations of image regions corresponding to candidate particles jointly by exploiting the underlying low-rank constraints. In addition, the proposed CLRST algorithm is computationally attractive since temporal consistency property helps prune particles and the low-rank minimization problem for learning joint sparse representations can be efficiently solved by a sequence of closed form update operations. We evaluate the proposed CLRST algorithm against 14 state-of-the-art tracking methods on a set of 25 challenging image sequences. Experimental results show that the CLRST algorithm performs favorably against state-of-the-art tracking methods in terms of accuracy and execution time.

Packing Smart

Centers for Disease Control (CDC) Podcasts

2011-08-22

In this podcast for kids, the Kidtastics talk about packing a lunch that's not boring and is full of the power and energy kids need to make it through the day.  Created: 8/22/2011 by National Center for Emerging and Zoonotic Infectious Diseases (NCEZID).   Date Released: 8/22/2011.

21 CFR 133.124 - Cold-pack cheese food.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Cold-pack cheese food. 133.124 Section 133.124 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) FOOD... Cheese and Related Products § 133.124 Cold-pack cheese food. (a)(1) Cold-pack cheese food is the food...

PENGARUH POROSITAS PACKING STEEL WOOL TERHADAP PRESSURE DROP DIDALAM PACKED BED COLUMN PADA DISTILASI CAMPURAN ETANOL-AMIL-ALKOHOL-AIR

Directory of Open Access Journals (Sweden)

Trisna Kumala Dhaniswara

2016-08-01

Full Text Available Inventories of petroleum fuels are increasingly depleted and will someday run out. These shortcomings can be overcome by using alternative fuels, such as ethanol. Based on this, it is necessary to research and development of ethanol as a fuel. One way is with a separation in a packed distillation column. This study aims to assess the mass transfer phenomena that occur in the process of distilling a mixture of ethanol-water-amyl alcohol packed in column. In addition, this study aims to optimize temperature and reflux to obtain the highest levels of ethanol. This research method uses packed bed distillation system with the batch process. Feed used is synthetic ethanol, water, and solvent. Solvent used were amyl alcohol. Doing distillation with heating temperature is maintained. Distillation is done in the packing of stainless steel wool. Research carried out in a batch process with a variable temperature of  79°C; 84°C; 91°C; and porosity packing 20%; 30%; 40%; 50%; 60%; 70%; 80%.

Efficient collaborative sparse channel estimation in massive MIMO

KAUST Repository

Masood, Mudassir

2015-08-12

We propose a method for estimation of sparse frequency selective channels within MIMO-OFDM systems. These channels are independently sparse and share a common support. The method estimates the impulse response for each channel observed by the antennas at the receiver. Estimation is performed in a coordinated manner by sharing minimal information among neighboring antennas to achieve results better than many contemporary methods. Simulations demonstrate the superior performance of the proposed method.

Efficient collaborative sparse channel estimation in massive MIMO

KAUST Repository

Masood, Mudassir; Afify, Laila H.; Al-Naffouri, Tareq Y.

2015-01-01

We propose a method for estimation of sparse frequency selective channels within MIMO-OFDM systems. These channels are independently sparse and share a common support. The method estimates the impulse response for each channel observed by the antennas at the receiver. Estimation is performed in a coordinated manner by sharing minimal information among neighboring antennas to achieve results better than many contemporary methods. Simulations demonstrate the superior performance of the proposed method.

Sparse dictionary learning of resting state fMRI networks.

Science.gov (United States)

Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

2012-07-02

Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

Porous carbons

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

Abstract. Carbon in dense as well as porous solid form is used in a variety of applications. Activated porous carbons are made through pyrolysis and activation of carbonaceous natural as well as synthetic precursors. Pyrolysed woods replicate the structure of original wood but as such possess very low surface areas and ...

Low-Rank Sparse Coding for Image Classification

KAUST Repository

Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Xu, Changsheng; Ahuja, Narendra

2013-01-01

In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local structure information among features in an image for the purpose of image-level classification. LRSC represents densely sampled SIFT descriptors, in a spatial neighborhood, collectively as low-rank, sparse linear combinations of code words. As such, it casts the feature coding problem as a low-rank matrix learning problem, which is different from previous methods that encode features independently. This LRSC has a number of attractive properties. (1) It encourages sparsity in feature codes, locality in codebook construction, and low-rankness for spatial consistency. (2) LRSC encodes local features jointly by considering their low-rank structure information, and is computationally attractive. We evaluate the LRSC by comparing its performance on a set of challenging benchmarks with that of 7 popular coding and other state-of-the-art methods. Our experiments show that by representing local features jointly, LRSC not only outperforms the state-of-the-art in classification accuracy but also improves the time complexity of methods that use a similar sparse linear representation model for feature coding.

Low-Rank Sparse Coding for Image Classification

KAUST Repository

Zhang, Tianzhu

2013-12-01

In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local structure information among features in an image for the purpose of image-level classification. LRSC represents densely sampled SIFT descriptors, in a spatial neighborhood, collectively as low-rank, sparse linear combinations of code words. As such, it casts the feature coding problem as a low-rank matrix learning problem, which is different from previous methods that encode features independently. This LRSC has a number of attractive properties. (1) It encourages sparsity in feature codes, locality in codebook construction, and low-rankness for spatial consistency. (2) LRSC encodes local features jointly by considering their low-rank structure information, and is computationally attractive. We evaluate the LRSC by comparing its performance on a set of challenging benchmarks with that of 7 popular coding and other state-of-the-art methods. Our experiments show that by representing local features jointly, LRSC not only outperforms the state-of-the-art in classification accuracy but also improves the time complexity of methods that use a similar sparse linear representation model for feature coding.

Cell packing structures

KAUST Repository

Pottmann, Helmut; Jiang, Caigui; Hö binger, Mathias; Wang, Jun; Bompas, Philippe; Wallner, Johannes

2015-01-01

optimization schemes for the computation of quad-based support structures. Hex-dominant structures may be designed via Voronoi tessellations, power diagrams, sphere packings and various extensions of these concepts. Apart from the obvious application as load

Regularized generalized eigen-decomposition with applications to sparse supervised feature extraction and sparse discriminant analysis

DEFF Research Database (Denmark)

Han, Xixuan; Clemmensen, Line Katrine Harder

2015-01-01

We propose a general technique for obtaining sparse solutions to generalized eigenvalue problems, and call it Regularized Generalized Eigen-Decomposition (RGED). For decades, Fisher's discriminant criterion has been applied in supervised feature extraction and discriminant analysis, and it is for...

Numerical simulation of heat and mass transfer in unsteady nanofluid between two orthogonally moving porous coaxial disks

International Nuclear Information System (INIS)

Ali, Kashif; Iqbal, Muhammad Farooq; Ashraf, Muhammad; Akbar, Muhammad Zubair

2014-01-01

The paper deals with the study of heat and mass transfer in an unsteady viscous incompressible water-based nanofluid (containing Titanium dioxide nanoparticles) between two orthogonally moving porous coaxial disks with suction. A combination of iterative (successive over relaxation) and a direct method is employed for solving the sparse systems of linear algebraic equations arising from the FD discretization of the linearized self similar ODEs. It has been noticed that the rate of mass transfer at the disks decreases with the permeability Reynolds number whether the disks are approaching or receding. The findings of the present investigation may be beneficial for the electronic industry in maintaining the electronic components under effective and safe operational conditions

A performance study of sparse Cholesky factorization on INTEL iPSC/860

Science.gov (United States)

Zubair, M.; Ghose, M.

1992-01-01

The problem of Cholesky factorization of a sparse matrix has been very well investigated on sequential machines. A number of efficient codes exist for factorizing large unstructured sparse matrices. However, there is a lack of such efficient codes on parallel machines in general, and distributed machines in particular. Some of the issues that are critical to the implementation of sparse Cholesky factorization on a distributed memory parallel machine are ordering, partitioning and mapping, load balancing, and ordering of various tasks within a processor. Here, we focus on the effect of various partitioning schemes on the performance of sparse Cholesky factorization on the Intel iPSC/860. Also, a new partitioning heuristic for structured as well as unstructured sparse matrices is proposed, and its performance is compared with other schemes.

Fast sparsely synchronized brain rhythms in a scale-free neural network.

Science.gov (United States)

Kim, Sang-Yoon; Lim, Woochang

2015-08-01

We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D. For small D, full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp>〈fi〉 (〈fi〉: ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4〈fi〉 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For Dsparse synchronization do contributions of individual neuronal dynamics to population synchronization change depending on their degrees, unlike in the case of full synchronization. Consequently, dynamics of individual neurons reveal the inhomogeneous network structure for the case of partial and sparse synchronization, which is in contrast to the case of

Fast sparsely synchronized brain rhythms in a scale-free neural network

Science.gov (United States)

Kim, Sang-Yoon; Lim, Woochang

2015-08-01

We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D . For small D , full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp> ( : ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For D sparse synchronization do contributions of individual neuronal dynamics to population synchronization change depending on their degrees, unlike in the case of full synchronization. Consequently, dynamics of individual neurons reveal the inhomogeneous network structure for the case of partial and sparse synchronization, which is in contrast to the case of statistically homogeneous

SEPTOPLASTY WITH AND WITHOUT NASAL PACKING: A COMPARATIVE STUDY

Directory of Open Access Journals (Sweden)

Mitta

2016-05-01

Full Text Available Septoplasty is one of the most commonly performed surgeries in rhinology to relieve nasal obstruction of patients with distortion in the midline cartilage or septum of the nose to relieve nasal obstruction of patient and findings consistent with nasal endoscopy. The anterior nasal packing routinely done following septoplasty is usually conventional and not evidence based. The purpose of nasal packing is to obtain haemostasis, enhance opposition of septal flaps, avoid septal haematoma formation, close the dead space, avoid synechiae formation, provide support to septal cartilage and prevent its displacement. OBJECTIVE This study intends to evaluate the effects of nasal packing on surgical success and related complications in septoplasty. MATERIALS AND METHODS The present clinical prospective and randomised study was carried out on patients attending Otorhinolaryngology Department of Santhiram Medical College & General Hospital between March 2012 and March 2015. Patients undergoing septoplasty were randomised either to receive anterior nasal packing or to not receive nasal packing postoperatively. RESULTS Levels of pain experienced by patients with nasal packing postoperatively during the initial 24 hours postoperatively and during the removal of the pack were significantly more. Post-operative headache, epiphora, swallowing discomfort and sleep disturbance were more in patients with nasal packing and statistically (p.05. Septal haematoma, adhesions and local infections in both groups were statistically insignificant (p>.05. CONCLUSION Septoplasty enhances the standard of living of patients with septal deviation and nasal obstruction. Our study results suggest that nasal packing after septoplasty is not obligatory. Nasal packing causes considerably more pain and complications, and it should be reserved only for those who have bleeding predisposition.

Characterization of metallic surfaces in phosphorous-bronze ordered packings

International Nuclear Information System (INIS)

Sandru, Claudia; Titescu, Gh.

1997-01-01

Copper and its alloys, particularly the phosphorous bronze, are characterized by a high water wettability as compared with other materials. This feature led to utilization of phosphorous bronze in fabrication of contact elements, a packing type equipping the distillation columns. For heavy water separation by isotopic distillation under vacuum, ordered packings of phosphorous bronze networks were fabricated. The superior performances of these packings are determined by the material and also by the geometrical form and the state of the metallic surface. Thus, a procedure of evaluating the wettability has been developed, based on tests of the network material. The results of the tests constitute a criterion of rating the functional performances of packings, particularly of their efficiencies. Also, investigation techniques of the chemical composition and of the thickness of superficial layer on the packing were developed. It was found that the packing surface presents a layer of about 5-20 μm formed mainly by oxides of copper, tin, and, depending on the packing treatment, of oxides of other elements coming from the treatment agent. The paper presents characterization of phosphorous bronze treated with potassium permanganate, a specific treatment for improving the functional performances of the packings used in the heavy water concentration and re-concentration installations

Fast charge implications: Pack and cell analysis and comparison

Science.gov (United States)

Tanim, Tanvir R.; Shirk, Matthew G.; Bewley, Randy L.; Dufek, Eric J.; Liaw, Bor Yann

2018-03-01

This study investigates the effect of 50-kW (about 2C) direct current fast charging on a full-size battery electric vehicle's battery pack in comparison to a pack exclusively charged at 3.3 kW, which is the common alternating current Level 2 charging power level. Comparable scaled charging protocols are also independently applied to individual cells at three different temperatures, 20 °C, 30 °C, and 40 °C, to perform a comparative analysis with the packs. Dominant cell-level aging modes were identified through incremental capacity analysis and compared with full packs to gain a clear understanding of additional key factors that affect pack aging. While the cell-level study showed a minor impact on performance due to direct current fast charging, the packs showed a significantly higher rate of capacity fade under similar charging protocols. This indicates that pack-level aging cannot be directly extrapolated from cell evaluation. Delayed fast charging, completing shortly before discharge, was found to have less of an impact on battery degradation than conventional alternating current Level 2 charging.

l1- and l2-Norm Joint Regularization Based Sparse Signal Reconstruction Scheme

Directory of Open Access Journals (Sweden)

Chanzi Liu

2016-01-01

Full Text Available Many problems in signal processing and statistical inference involve finding sparse solution to some underdetermined linear system of equations. This is also the application condition of compressive sensing (CS which can find the sparse solution from the measurements far less than the original signal. In this paper, we propose l1- and l2-norm joint regularization based reconstruction framework to approach the original l0-norm based sparseness-inducing constrained sparse signal reconstruction problem. Firstly, it is shown that, by employing the simple conjugate gradient algorithm, the new formulation provides an effective framework to deduce the solution as the original sparse signal reconstruction problem with l0-norm regularization item. Secondly, the upper reconstruction error limit is presented for the proposed sparse signal reconstruction framework, and it is unveiled that a smaller reconstruction error than l1-norm relaxation approaches can be realized by using the proposed scheme in most cases. Finally, simulation results are presented to validate the proposed sparse signal reconstruction approach.

Image fusion via nonlocal sparse K-SVD dictionary learning.

Science.gov (United States)

Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang

2016-03-01

Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.

The synthesis of porous Co3O4 micro cuboid structures by solvothermal approach and investigation of its gas sensing properties and catalytic activity

International Nuclear Information System (INIS)

Jamil, Saba; Jing, Xiaoyan; Wang, Jun; Li, Songnan; Liu, Jingyuan; Zhang, Milin

2013-01-01

Graphical abstract: - Highlights: • Micro cuboid Co 3 O 4 particle prepared by solvothermal method. • Study of morphology of synthesized cuboids before and after calcinations. • Investigation of formation mechanism of porous Co 3 O 4 from cuboid CoCO 3 . • Investigation of gas sensing properties of porous Co 3 O 4 . • Study of catalytic activity of product. - Abstract: The cobalt carbonate cuboids are prepared by adopting a simple solvothermal approach by using diethylene glycol and water in specific ratio as solvent. The prepared cobalt carbonate is subjected to different instrumentation to investigate its morphology and other properties. It is clear from the scanning electron microscopy (SEM) and transmission electron microscopy (TEM) that the product is distinct cuboid in shape with a size of approximately 3 μm from each face of the cube. Each particle of cuboid cobalt carbonate seems to comprise of layer by layer assembly of unit cells that consequently leads to a cuboid geometry. The cuboid cobalt carbonate was calcined at 700 °C in a furnace under argon atmosphere that decompose cobalt carbonate into porous Co 3 O 4 with the loosely packed arrangement of nano architectures. The gas sensing properties and catalytic activity of porous cuboids Co 3 O 4 are also investigated

Detection of Pitting in Gears Using a Deep Sparse Autoencoder

Directory of Open Access Journals (Sweden)

Yongzhi Qu

2017-05-01

Full Text Available In this paper; a new method for gear pitting fault detection is presented. The presented method is developed based on a deep sparse autoencoder. The method integrates dictionary learning in sparse coding into a stacked autoencoder network. Sparse coding with dictionary learning is viewed as an adaptive feature extraction method for machinery fault diagnosis. An autoencoder is an unsupervised machine learning technique. A stacked autoencoder network with multiple hidden layers is considered to be a deep learning network. The presented method uses a stacked autoencoder network to perform the dictionary learning in sparse coding and extract features from raw vibration data automatically. These features are then used to perform gear pitting fault detection. The presented method is validated with vibration data collected from gear tests with pitting faults in a gearbox test rig and compared with an existing deep learning-based approach.

In-Storage Embedded Accelerator for Sparse Pattern Processing

OpenAIRE

Jun, Sang-Woo; Nguyen, Huy T.; Gadepally, Vijay N.; Arvind

2016-01-01

We present a novel architecture for sparse pattern processing, using flash storage with embedded accelerators. Sparse pattern processing on large data sets is the essence of applications such as document search, natural language processing, bioinformatics, subgraph matching, machine learning, and graph processing. One slice of our prototype accelerator is capable of handling up to 1TB of data, and experiments show that it can outperform C/C++ software solutions on a 16-core system at a fracti...

Process Knowledge Discovery Using Sparse Principal Component Analysis

DEFF Research Database (Denmark)

Gao, Huihui; Gajjar, Shriram; Kulahci, Murat

2016-01-01

As the goals of ensuring process safety and energy efficiency become ever more challenging, engineers increasingly rely on data collected from such processes for informed decision making. During recent decades, extracting and interpreting valuable process information from large historical data sets...... SPCA approach that helps uncover the underlying process knowledge regarding variable relations. This approach systematically determines the optimal sparse loadings for each sparse PC while improving interpretability and minimizing information loss. The salient features of the proposed approach...

Massively parallel sparse matrix function calculations with NTPoly

Science.gov (United States)

Dawson, William; Nakajima, Takahito

2018-04-01

We present NTPoly, a massively parallel library for computing the functions of sparse, symmetric matrices. The theory of matrix functions is a well developed framework with a wide range of applications including differential equations, graph theory, and electronic structure calculations. One particularly important application area is diagonalization free methods in quantum chemistry. When the input and output of the matrix function are sparse, methods based on polynomial expansions can be used to compute matrix functions in linear time. We present a library based on these methods that can compute a variety of matrix functions. Distributed memory parallelization is based on a communication avoiding sparse matrix multiplication algorithm. OpenMP task parallellization is utilized to implement hybrid parallelization. We describe NTPoly's interface and show how it can be integrated with programs written in many different programming languages. We demonstrate the merits of NTPoly by performing large scale calculations on the K computer.

SPH Modelling of Sea-ice Pack Dynamics

Science.gov (United States)

Staroszczyk, Ryszard

2017-12-01

The paper is concerned with the problem of sea-ice pack motion and deformation under the action of wind and water currents. Differential equations describing the dynamics of ice, with its very distinct mateFfigrial responses in converging and diverging flows, express the mass and linear momentum balances on the horizontal plane (the free surface of the ocean). These equations are solved by the fully Lagrangian method of smoothed particle hydrodynamics (SPH). Assuming that the ice behaviour can be approximated by a non-linearly viscous rheology, the proposed SPH model has been used to simulate the evolution of a sea-ice pack driven by wind drag stresses. The results of numerical simulations illustrate the evolution of an ice pack, including variations in ice thickness and ice area fraction in space and time. The effects of different initial ice pack configurations and of different conditions assumed at the coast-ice interface are examined. In particular, the SPH model is applied to a pack flow driven by a vortex wind to demonstrate how well the Lagrangian formulation can capture large deformations and displacements of sea ice.

Deformable segmentation via sparse representation and dictionary learning.

Science.gov (United States)

Zhang, Shaoting; Zhan, Yiqiang; Metaxas, Dimitris N

2012-10-01

"Shape" and "appearance", the two pillars of a deformable model, complement each other in object segmentation. In many medical imaging applications, while the low-level appearance information is weak or mis-leading, shape priors play a more important role to guide a correct segmentation, thanks to the strong shape characteristics of biological structures. Recently a novel shape prior modeling method has been proposed based on sparse learning theory. Instead of learning a generative shape model, shape priors are incorporated on-the-fly through the sparse shape composition (SSC). SSC is robust to non-Gaussian errors and still preserves individual shape characteristics even when such characteristics is not statistically significant. Although it seems straightforward to incorporate SSC into a deformable segmentation framework as shape priors, the large-scale sparse optimization of SSC has low runtime efficiency, which cannot satisfy clinical requirements. In this paper, we design two strategies to decrease the computational complexity of SSC, making a robust, accurate and efficient deformable segmentation system. (1) When the shape repository contains a large number of instances, which is often the case in 2D problems, K-SVD is used to learn a more compact but still informative shape dictionary. (2) If the derived shape instance has a large number of vertices, which often appears in 3D problems, an affinity propagation method is used to partition the surface into small sub-regions, on which the sparse shape composition is performed locally. Both strategies dramatically decrease the scale of the sparse optimization problem and hence speed up the algorithm. Our method is applied on a diverse set of biomedical image analysis problems. Compared to the original SSC, these two newly-proposed modules not only significant reduce the computational complexity, but also improve the overall accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.

Sparseness- and continuity-constrained seismic imaging

Science.gov (United States)

Herrmann, Felix J.

2005-04-01

Non-linear solution strategies to the least-squares seismic inverse-scattering problem with sparseness and continuity constraints are proposed. Our approach is designed to (i) deal with substantial amounts of additive noise (SNR formulating the solution of the seismic inverse problem in terms of an optimization problem. During the optimization, sparseness on the basis and continuity along the reflectors are imposed by jointly minimizing the l1- and anisotropic diffusion/total-variation norms on the coefficients and reflectivity, respectively. [Joint work with Peyman P. Moghaddam was carried out as part of the SINBAD project, with financial support secured through ITF (the Industry Technology Facilitator) from the following organizations: BG Group, BP, ExxonMobil, and SHELL. Additional funding came from the NSERC Discovery Grants 22R81254.

Combinatorial Algorithms for Computing Column Space Bases ThatHave Sparse Inverses

Energy Technology Data Exchange (ETDEWEB)

Pinar, Ali; Chow, Edmond; Pothen, Alex

2005-03-18

This paper presents a combinatorial study on the problem ofconstructing a sparse basis forthe null-space of a sparse, underdetermined, full rank matrix, A. Such a null-space is suitable forsolving solving many saddle point problems. Our approach is to form acolumn space basis of A that has a sparse inverse, by selecting suitablecolumns of A. This basis is then used to form a sparse null-space basisin fundamental form. We investigate three different algorithms forcomputing the column space basis: Two greedy approaches that rely onmatching, and a third employing a divide and conquer strategy implementedwith hypergraph partitioning followed by the greedy approach. We alsodiscuss the complexity of selecting a column basis when it is known thata block diagonal basis exists with a small given block size.

Direct contact condensation in packed beds

Energy Technology Data Exchange (ETDEWEB)

Li, Yi; Klausner, James F.; Mei, Renwei; Knight, Jessica [Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611 (United States)

2006-12-15

A diffusion driven desalination process was recently described where a very effective direct contact condenser with a packed bed is used to condense water vapor out of an air/vapor mixture. A laboratory scale direct contact condenser has been fabricated as a twin tower structure with two stages, co-current and countercurrent. Experiments have been operated in each stage with respective saturated air inlet temperatures of 36, 40 and 43{sup o}C. The temperature and humidity data have been collected at the inlet and exit of the packed bed for different water to air mass flow ratios that vary between 0 and 2.5. A one-dimensional model based on conservation principles has been developed, which predicts the variation of temperature, humidity, and condensation rate through the condenser stages. Agreement between the model and experiments is very good. It is observed that the countercurrent flow stage condensation effectiveness is significantly higher than that for the co-current stage. The condensation heat and mass transfer rates were found to decrease when water blockages occur within the packed bed. Using high-speed digital cinematography, it was observed that this problem can occur at any operating condition, and is dependent on the packing surface wetting characteristics. This observation is used to explain the requirement for two different empirical constants, depending on packing diameter, suggested by Onda for the air side mass transfer coefficient correlation. (author)

Effect of deformation on the thermal conductivity of granular porous media with rough grain surface

Science.gov (United States)

Askari, Roohollah; Hejazi, S. Hossein; Sahimi, Muhammad

2017-08-01

Heat transfer in granular porous media is an important phenomenon that is relevant to a wide variety of problems, including geothermal reservoirs and enhanced oil recovery by thermal methods. Resistance to flow of heat in the contact area between the grains strongly influences the effective thermal conductivity of such porous media. Extensive experiments have indicated that the roughness of the grains' surface follows self-affine fractal stochastic functions, and thus, the contact resistance cannot be accounted for by models based on smooth surfaces. Despite the significance of rough contact area, the resistance has been accounted for by a fitting parameter in the models of heat transfer. In this Letter we report on a study of conduction in a packing of particles that contains a fluid of a given conductivity, with each grain having a rough self-affine surface, and is under an external compressive pressure. The deformation of the contact area depends on the fractal dimension that characterizes the grains' rough surface, as well as their Young's modulus. Excellent qualitative agreement is obtained with experimental data. Deformation of granular porous media with grains that have rough self-affine fractal surface is simulated. Thermal contact resistance between grains with rough surfaces is incorporated into the numerical simulation of heat conduction under compressive pressure. By increasing compressive pressure, thermal conductivity is enhanced more in the grains with smoother surfaces and lower Young's modulus. Excellent qualitative agreement is obtained with the experimental data.

Modi ed strip packing heuristics for the rectangular variable-sized ...

African Journals Online (AJOL)

Two packing problems are considered in this paper, namely the well-known strip packing problem (SPP) and the variable-sized bin packing problem (VSBPP). A total of 252 strip packing heuristics (and variations thereof) from the literature, as well as novel heuristics proposed by the authors, are compared statistically by ...

Image Super-Resolution Algorithm Based on an Improved Sparse Autoencoder

Directory of Open Access Journals (Sweden)

Detian Huang

2018-01-01

Full Text Available Due to the limitations of the resolution of the imaging system and the influence of scene changes and other factors, sometimes only low-resolution images can be acquired, which cannot satisfy the practical application’s requirements. To improve the quality of low-resolution images, a novel super-resolution algorithm based on an improved sparse autoencoder is proposed. Firstly, in the training set preprocessing stage, the high- and low-resolution image training sets are constructed, respectively, by using high-frequency information of the training samples as the characterization, and then the zero-phase component analysis whitening technique is utilized to decorrelate the formed joint training set to reduce its redundancy. Secondly, a constructed sparse regularization term is added to the cost function of the traditional sparse autoencoder to further strengthen the sparseness constraint on the hidden layer. Finally, in the dictionary learning stage, the improved sparse autoencoder is adopted to achieve unsupervised dictionary learning to improve the accuracy and stability of the dictionary. Experimental results validate that the proposed algorithm outperforms the existing algorithms both in terms of the subjective visual perception and the objective evaluation indices, including the peak signal-to-noise ratio and the structural similarity measure.

Diagnosis and prognosis of Ostheoarthritis by texture analysis using sparse linear models

DEFF Research Database (Denmark)

Marques, Joselene; Clemmensen, Line Katrine Harder; Dam, Erik

We present a texture analysis methodology that combines uncommitted machine-learning techniques and sparse feature transformation methods in a fully automatic framework. We compare the performances of a partial least squares (PLS) forward feature selection strategy to a hard threshold sparse PLS...... algorithm and a sparse linear discriminant model. The texture analysis framework was applied to diagnosis of knee osteoarthritis (OA) and prognosis of cartilage loss. For this investigation, a generic texture feature bank was extracted from magnetic resonance images of tibial knee bone. The features were...... used as input to the sparse algorithms, which dened the best features to retain in the model. To cope with the limited number of samples, the data was evaluated using 10 fold cross validation (CV). The diagnosis evaluation using sparse PLS reached a generalization area-under-the-ROC curve (AUC) of 0...

Efficient implementations of block sparse matrix operations on shared memory vector machines

International Nuclear Information System (INIS)

Washio, T.; Maruyama, K.; Osoda, T.; Doi, S.; Shimizu, F.

2000-01-01

In this paper, we propose vectorization and shared memory-parallelization techniques for block-type random sparse matrix operations in finite element (FEM) applications. Here, a block corresponds to unknowns on one node in the FEM mesh and we assume that the block size is constant over the mesh. First, we discuss some basic vectorization ideas (the jagged diagonal (JAD) format and the segmented scan algorithm) for the sparse matrix-vector product. Then, we extend these ideas to the shared memory parallelization. After that, we show that the techniques can be applied not only to the sparse matrix-vector product but also to the sparse matrix-matrix product, the incomplete or complete sparse LU factorization and preconditioning. Finally, we report the performance evaluation results obtained on an NEC SX-4 shared memory vector machine for linear systems in some FEM applications. (author)

A Projected Conjugate Gradient Method for Sparse Minimax Problems

DEFF Research Database (Denmark)

Madsen, Kaj; Jonasson, Kristjan

1993-01-01

A new method for nonlinear minimax problems is presented. The method is of the trust region type and based on sequential linear programming. It is a first order method that only uses first derivatives and does not approximate Hessians. The new method is well suited for large sparse problems...... as it only requires that software for sparse linear programming and a sparse symmetric positive definite equation solver are available. On each iteration a special linear/quadratic model of the function is minimized, but contrary to the usual practice in trust region methods the quadratic model is only...... with the method are presented. In fact, we find that the number of iterations required is comparable to that of state-of-the-art quasi-Newton codes....

Identification of MIMO systems with sparse transfer function coefficients

Science.gov (United States)

Qiu, Wanzhi; Saleem, Syed Khusro; Skafidas, Efstratios

2012-12-01

We study the problem of estimating transfer functions of multivariable (multiple-input multiple-output--MIMO) systems with sparse coefficients. We note that subspace identification methods are powerful and convenient tools in dealing with MIMO systems since they neither require nonlinear optimization nor impose any canonical form on the systems. However, subspace-based methods are inefficient for systems with sparse transfer function coefficients since they work on state space models. We propose a two-step algorithm where the first step identifies the system order using the subspace principle in a state space format, while the second step estimates coefficients of the transfer functions via L1-norm convex optimization. The proposed algorithm retains good features of subspace methods with improved noise-robustness for sparse systems.

MULTISCALE SPARSE APPEARANCE MODELING AND SIMULATION OF PATHOLOGICAL DEFORMATIONS

Directory of Open Access Journals (Sweden)

Rami Zewail

2017-08-01

Full Text Available Machine learning and statistical modeling techniques has drawn much interest within the medical imaging research community. However, clinically-relevant modeling of anatomical structures continues to be a challenging task. This paper presents a novel method for multiscale sparse appearance modeling in medical images with application to simulation of pathological deformations in X-ray images of human spine. The proposed appearance model benefits from the non-linear approximation power of Contourlets and its ability to capture higher order singularities to achieve a sparse representation while preserving the accuracy of the statistical model. Independent Component Analysis is used to extract statistical independent modes of variations from the sparse Contourlet-based domain. The new model is then used to simulate clinically-relevant pathological deformations in radiographic images.

An Adaptive Sparse Grid Algorithm for Elliptic PDEs with Lognormal Diffusion Coefficient

KAUST Repository

Nobile, Fabio

2016-03-18

In this work we build on the classical adaptive sparse grid algorithm (T. Gerstner and M. Griebel, Dimension-adaptive tensor-product quadrature), obtaining an enhanced version capable of using non-nested collocation points, and supporting quadrature and interpolation on unbounded sets. We also consider several profit indicators that are suitable to drive the adaptation process. We then use such algorithm to solve an important test case in Uncertainty Quantification problem, namely the Darcy equation with lognormal permeability random field, and compare the results with those obtained with the quasi-optimal sparse grids based on profit estimates, which we have proposed in our previous works (cf. e.g. Convergence of quasi-optimal sparse grids approximation of Hilbert-valued functions: application to random elliptic PDEs). To treat the case of rough permeability fields, in which a sparse grid approach may not be suitable, we propose to use the adaptive sparse grid quadrature as a control variate in a Monte Carlo simulation. Numerical results show that the adaptive sparse grids have performances similar to those of the quasi-optimal sparse grids and are very effective in the case of smooth permeability fields. Moreover, their use as control variate in a Monte Carlo simulation allows to tackle efficiently also problems with rough coefficients, significantly improving the performances of a standard Monte Carlo scheme.

Sparse principal component analysis in medical shape modeling

Science.gov (United States)

Sjöstrand, Karl; Stegmann, Mikkel B.; Larsen, Rasmus

2006-03-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combination of a subset of the original variables. One of the aims of using SPCA is the possible separation of the results into isolated and easily identifiable effects. This article introduces SPCA for shape analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA algorithm has been implemented using Matlab and is available for download. The general behavior of the algorithm is investigated, and strengths and weaknesses are discussed. The original report on the SPCA algorithm argues that the ordering of modes is not an issue. We disagree on this point and propose several approaches to establish sensible orderings. A method that orders modes by decreasing variance and maximizes the sum of variances for all modes is presented and investigated in detail.

Pack stability in dip faces fitted with scraper conveyors

Energy Technology Data Exchange (ETDEWEB)

Schwartzmann, R

1978-01-01

This paper presents an account of an investigation conducted by CERCHAR, at the request of HBNPC, into the problems of goafside pack stability. Winning method and support and stowing techniques are described. Sets out the study methods used: systematic measurement (by direct or remote means) using an instrument developed by CERCHAR to investigate all aspects of in situ pack behaviour: settling, stresses, pressure on supports, etc. Gives the results of the investigation (tables and graphs) load-bearing capacity of the supports, deformation of the surrounding rock, convergence and stresses in the pack (figures, graphs), resistance of support-timber screen, model of in situ pack behaviour. Detailed conclusions (potential techniques, detailed study, practical improvements in packing techniques) are presented.

A comparison between CFD simulation and experimental investigation of a packed-bed thermal energy storage system

International Nuclear Information System (INIS)

Cascetta, Mario; Cau, Giorgio; Puddu, Pierpaolo; Serra, Fabio

2016-01-01

Highlights: • Thermocline formation inside a sensible type packed bed during a complete cycle. • Thermal properties of both phases must be temperature-dependent in the simulation. • Bed porosity increases from the center to the container wall. • Thermal dispersion and solid conduction must be considered in the model. • The wall influences the radial temperature profile and the amount of energy stored. - Abstract: This work presents the comparison between CFD and experimental results obtained on a sensible thermal energy storage system based on alumina beads freely poured into a carbon steel tank. Experimental investigations of charging and discharging phases were carried out at a constant mass flow rate using air as heat transfer fluid. The experimental set-up was instrumented with several thermocouples to detect axial and radial temperature distribution as well as reservoir wall temperature. The experimental results were compared with those obtained from CFD simulations carried out with the FLUENT software. The computational domain consists of an axisymmetric tank of cylindrical shape filled with a porous bed coupled with the wall. The governing equations are solved for incompressible turbulent flow and fully developed forced convection, based on the two-phase transient model equation (LTNE-local thermal non-equilibrium) to calculate the temperature of fluid and solid phases. The porosity of the bed is considered variable in the radial direction, while the thermodynamic properties of both phases are temperature-dependent. The influence of the thermal dispersion within the porous bed, as well as the effective conductivity between the beads was considered. The heat transfer coefficient was calculated according to correlation for forced convection within porous media. Numerical results show a good agreement with experimental ones if thermal properties are considered temperature-dependent and the experimental temperature profile at the inlet of the bed is

Inference algorithms and learning theory for Bayesian sparse factor analysis

International Nuclear Information System (INIS)

Rattray, Magnus; Sharp, Kevin; Stegle, Oliver; Winn, John

2009-01-01

Bayesian sparse factor analysis has many applications; for example, it has been applied to the problem of inferring a sparse regulatory network from gene expression data. We describe a number of inference algorithms for Bayesian sparse factor analysis using a slab and spike mixture prior. These include well-established Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms as well as a novel hybrid of VB and Expectation Propagation (EP). For the case of a single latent factor we derive a theory for learning performance using the replica method. We compare the MCMC and VB/EP algorithm results with simulated data to the theoretical prediction. The results for MCMC agree closely with the theory as expected. Results for VB/EP are slightly sub-optimal but show that the new algorithm is effective for sparse inference. In large-scale problems MCMC is infeasible due to computational limitations and the VB/EP algorithm then provides a very useful computationally efficient alternative.

Inference algorithms and learning theory for Bayesian sparse factor analysis

Energy Technology Data Exchange (ETDEWEB)

Rattray, Magnus; Sharp, Kevin [School of Computer Science, University of Manchester, Manchester M13 9PL (United Kingdom); Stegle, Oliver [Max-Planck-Institute for Biological Cybernetics, Tuebingen (Germany); Winn, John, E-mail: magnus.rattray@manchester.ac.u [Microsoft Research Cambridge, Roger Needham Building, Cambridge, CB3 0FB (United Kingdom)

2009-12-01

Bayesian sparse factor analysis has many applications; for example, it has been applied to the problem of inferring a sparse regulatory network from gene expression data. We describe a number of inference algorithms for Bayesian sparse factor analysis using a slab and spike mixture prior. These include well-established Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms as well as a novel hybrid of VB and Expectation Propagation (EP). For the case of a single latent factor we derive a theory for learning performance using the replica method. We compare the MCMC and VB/EP algorithm results with simulated data to the theoretical prediction. The results for MCMC agree closely with the theory as expected. Results for VB/EP are slightly sub-optimal but show that the new algorithm is effective for sparse inference. In large-scale problems MCMC is infeasible due to computational limitations and the VB/EP algorithm then provides a very useful computationally efficient alternative.

Scandinavian consumer preference for beef steaks packed with or without oxygen.

Science.gov (United States)

Aaslyng, M D; Tørngren, M A; Madsen, N T

2010-07-01

Beef steaks retail-packed with (80% O(2), 20% CO(2)) or without oxygen (either skin-packed or gas-packed (69.6% N(2), 30% CO(2), 0.04% CO or 70% N(2), 30% CO(2))) were compared by consumers in Denmark (n=382), Norway (n=316) and Sweden (n=374). Two pairs of two steaks - one steak packed in a high oxygen atmosphere and one packed without oxygen - were given to the consumers. They were instructed to prepare the steaks at home on two consecutive days, and two persons had to taste each steak. In Denmark, the oxygen-free packing was either gas packing with CO (69.6% N(2), 30% CO(2), 0.04% CO) or without CO (70% N(2), 30% CO(2)), in Norway it was either gas packing with CO (69.6% N(2), 30% CO(2), 0.04% CO) or skin packing, and in Sweden it was either skin packing or gas packing without CO (70% N(2), 30% CO(2)). The meat represented animals that were between 17 and 80 months old (Denmark) and young bulls (Norway and Sweden). Consumers in all three countries clearly preferred steaks packed without oxygen, in terms of overall liking, willingness to pay and their preferred choice of one steak. Furthermore, they preferred the oxygen-free steaks in terms of both overall liking and liking of tenderness, juiciness and flavour. In Sweden, many consumers would pay more than usual for the skin-packed steak, and it was more often chosen as the preferred steak out of the four compared with gas-packed without oxygen. No difference was seen between the two oxygen-free packing methods in Denmark and Norway. Copyright 2010 Elsevier Ltd. All rights reserved.

Universal Regularizers For Robust Sparse Coding and Modeling

OpenAIRE

Ramirez, Ignacio; Sapiro, Guillermo

2010-01-01

Sparse data models, where data is assumed to be well represented as a linear combination of a few elements from a dictionary, have gained considerable attention in recent years, and their use has led to state-of-the-art results in many signal and image processing tasks. It is now well understood that the choice of the sparsity regularization term is critical in the success of such models. Based on a codelength minimization interpretation of sparse coding, and using tools from universal coding...

Deep ensemble learning of sparse regression models for brain disease diagnosis.

Science.gov (United States)

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2017-04-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer's disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call 'Deep Ensemble Sparse Regression Network.' To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Hierarchical Bayesian sparse image reconstruction with application to MRFM.

Science.gov (United States)

Dobigeon, Nicolas; Hero, Alfred O; Tourneret, Jean-Yves

2009-09-01

This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hierarchical Bayes model is well suited to such naturally sparse image applications as it seamlessly accounts for properties such as sparsity and positivity of the image via appropriate Bayes priors. We propose a prior that is based on a weighted mixture of a positive exponential distribution and a mass at zero. The prior has hyperparameters that are tuned automatically by marginalization over the hierarchical Bayesian model. To overcome the complexity of the posterior distribution, a Gibbs sampling strategy is proposed. The Gibbs samples can be used to estimate the image to be recovered, e.g., by maximizing the estimated posterior distribution. In our fully Bayesian approach, the posteriors of all the parameters are available. Thus, our algorithm provides more information than other previously proposed sparse reconstruction methods that only give a point estimate. The performance of the proposed hierarchical Bayesian sparse reconstruction method is illustrated on synthetic data and real data collected from a tobacco virus sample using a prototype MRFM instrument.

Efficient coordinated recovery of sparse channels in massive MIMO

KAUST Repository

Masood, Mudassir

2015-01-01

This paper addresses the problem of estimating sparse channels in massive MIMO-OFDM systems. Most wireless channels are sparse in nature with large delay spread. In addition, these channels as observed by multiple antennas in a neighborhood have approximately common support. The sparsity and common support properties are attractive when it comes to the efficient estimation of large number of channels in massive MIMO systems. Moreover, to avoid pilot contamination and to achieve better spectral efficiency, it is important to use a small number of pilots. We present a novel channel estimation approach which utilizes the sparsity and common support properties to estimate sparse channels and requires a small number of pilots. Two algorithms based on this approach have been developed that perform Bayesian estimates of sparse channels even when the prior is non-Gaussian or unknown. Neighboring antennas share among each other their beliefs about the locations of active channel taps to perform estimation. The coordinated approach improves channel estimates and also reduces the required number of pilots. Further improvement is achieved by the data-aided version of the algorithm. Extensive simulation results are provided to demonstrate the performance of the proposed algorithms.

On contact numbers in random rod packings

NARCIS (Netherlands)

Wouterse, A.; Luding, Stefan; Philipse, A.P.

2009-01-01

Random packings of non-spherical granular particles are simulated by combining mechanical contraction and molecular dynamics, to determine contact numbers as a function of density. Particle shapes are varied from spheres to thin rods. The observed contact numbers (and packing densities) agree well

Packing of ganglioside-phospholipid monolayers

DEFF Research Database (Denmark)

Majewski, J.; Kuhl, T.L.; Kjær, K.

2001-01-01

Using synchrotron grazing-incidence x-ray diffraction (GIXD) and reflectivity, the in-plane and out-of-plane structure of mixed ganglioside-phospholipid monolayers was investigated at the air-water interface. Mixed monolayers of 0, 5, 10, 20, and 100 mol% ganglioside GM, and the phospholipid...... monolayers did not affect hydrocarbon tail packing (fluidization or condensation of the hydrocarbon region). This is in contrast to previous investigations of lipopolymer-lipid mixtures, where the packing structure of phospholipid monolayers was greatly altered by the inclusion of lipids bearing hydrophilic...

Boiling in porous media

International Nuclear Information System (INIS)

1998-01-01

This conference day of the French society of thermal engineers was devoted to the analysis of heat transfers and fluid flows during boiling phenomena in porous media. This book of proceedings comprises 8 communications entitled: 'boiling in porous medium: effect of natural convection in the liquid zone'; 'numerical modeling of boiling in porous media using a 'dual-fluid' approach: asymmetrical characteristic of the phenomenon'; 'boiling during fluid flow in an induction heated porous column'; 'cooling of corium fragment beds during a severe accident. State of the art and the SILFIDE experimental project'; 'state of knowledge about the cooling of a particulates bed during a reactor accident'; 'mass transfer analysis inside a concrete slab during fire resistance tests'; 'heat transfers and boiling in porous media. Experimental analysis and modeling'; 'concrete in accidental situation - influence of boundary conditions (thermal, hydric) - case studies'. (J.S.)

Porous-shaped silicon carbide ultraviolet photodetectors on porous silicon substrates

Energy Technology Data Exchange (ETDEWEB)

Naderi, N., E-mail: naderi.phd@gmail.com [Nano-Optoelectronics Research Laboratory, School of Physics, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia); Hashim, M.R. [Nano-Optoelectronics Research Laboratory, School of Physics, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia)

2013-03-05

Highlights: ► Porous-shaped silicon carbide thin film was deposited on porous silicon substrate. ► Thermal annealing was followed to enhance the physical properties of samples. ► Metal–semiconductor-metal ultraviolet detectors were fabricated on samples. ► The effect of annealing temperature on electrical performance of devices was studied. ► The efficiency of photodetectors was enhanced by annealing at elevated temperatures. -- Abstract: A metal–semiconductor-metal (MSM) ultraviolet photodetector was fabricated based on a porous-shaped structure of silicon carbide (SiC). For increasing the surface roughness of SiC and hence enhancing the light absorption effect in fabricated devices, porous silicon (PS) was chosen as a template; SiC was deposited on PS substrates via radio frequency magnetron sputtering. Therefore, the deposited layers followed the structural pattern of PS skeleton and formed a porous-shaped SiC layer on PS substrate. The structural properties of samples showed that the as-deposited SiC was amorphous. Thus, a post-deposition annealing process with elevated temperatures was required to convert its amorphous phase to crystalline phase. The morphology of the sputtered samples was examined via scanning electron and atomic force microscopies. The grain size and roughness of the deposited layers clearly increased upon an increase in the annealing temperature. The optical properties of sputtered SiC were enhanced due to applying high temperatures. The most intense photoluminescence peak was observed for the sample with 1200 °C of annealing temperature. For the metallization of the SiC substrates to fabricate MSM photodetectors, two interdigitated Schottky contacts of Ni with four fingers for each electrode were deposited onto all the porous substrates. The optoelectronic characteristics of MSM UV photodetectors with porous-shaped SiC substrates were studied in the dark and under UV illumination. The electrical characteristics of fabricated

Porous-shaped silicon carbide ultraviolet photodetectors on porous silicon substrates

International Nuclear Information System (INIS)

Naderi, N.; Hashim, M.R.

2013-01-01

Highlights: ► Porous-shaped silicon carbide thin film was deposited on porous silicon substrate. ► Thermal annealing was followed to enhance the physical properties of samples. ► Metal–semiconductor-metal ultraviolet detectors were fabricated on samples. ► The effect of annealing temperature on electrical performance of devices was studied. ► The efficiency of photodetectors was enhanced by annealing at elevated temperatures. -- Abstract: A metal–semiconductor-metal (MSM) ultraviolet photodetector was fabricated based on a porous-shaped structure of silicon carbide (SiC). For increasing the surface roughness of SiC and hence enhancing the light absorption effect in fabricated devices, porous silicon (PS) was chosen as a template; SiC was deposited on PS substrates via radio frequency magnetron sputtering. Therefore, the deposited layers followed the structural pattern of PS skeleton and formed a porous-shaped SiC layer on PS substrate. The structural properties of samples showed that the as-deposited SiC was amorphous. Thus, a post-deposition annealing process with elevated temperatures was required to convert its amorphous phase to crystalline phase. The morphology of the sputtered samples was examined via scanning electron and atomic force microscopies. The grain size and roughness of the deposited layers clearly increased upon an increase in the annealing temperature. The optical properties of sputtered SiC were enhanced due to applying high temperatures. The most intense photoluminescence peak was observed for the sample with 1200 °C of annealing temperature. For the metallization of the SiC substrates to fabricate MSM photodetectors, two interdigitated Schottky contacts of Ni with four fingers for each electrode were deposited onto all the porous substrates. The optoelectronic characteristics of MSM UV photodetectors with porous-shaped SiC substrates were studied in the dark and under UV illumination. The electrical characteristics of fabricated

Robust Fringe Projection Profilometry via Sparse Representation.

Science.gov (United States)

Budianto; Lun, Daniel P K

2016-04-01

In this paper, a robust fringe projection profilometry (FPP) algorithm using the sparse dictionary learning and sparse coding techniques is proposed. When reconstructing the 3D model of objects, traditional FPP systems often fail to perform if the captured fringe images have a complex scene, such as having multiple and occluded objects. It introduces great difficulty to the phase unwrapping process of an FPP system that can result in serious distortion in the final reconstructed 3D model. For the proposed algorithm, it encodes the period order information, which is essential to phase unwrapping, into some texture patterns and embeds them to the projected fringe patterns. When the encoded fringe image is captured, a modified morphological component analysis and a sparse classification procedure are performed to decode and identify the embedded period order information. It is then used to assist the phase unwrapping process to deal with the different artifacts in the fringe images. Experimental results show that the proposed algorithm can significantly improve the robustness of an FPP system. It performs equally well no matter the fringe images have a simple or complex scene, or are affected due to the ambient lighting of the working environment.

Multilayer DNA Origami Packed on Hexagonal and Hybrid Lattices

DEFF Research Database (Denmark)

Ke, Yonggang; Voigt, Niels Vinther; Shih, William M.

2012-01-01

“Scaffolded DNA origami” has been proven to be a powerful and efficient approach to construct two-dimensional or three-dimensional objects with great complexity. Multilayer DNA origami has been demonstrated with helices packing along either honeycomb-lattice geometry or square-lattice geometry....... Here we report successful folding of multilayer DNA origami with helices arranged on a close-packed hexagonal lattice. This arrangement yields a higher density of helical packing and therefore higher resolution of spatial addressing than has been shown previously. We also demonstrate hybrid multilayer...... DNA origami with honeycomb-lattice, square-lattice, and hexagonal-lattice packing of helices all in one design. The availability of hexagonal close-packing of helices extends our ability to build complex structures using DNA nanotechnology....

Multilayer DNA origami packed on hexagonal and hybrid lattices.

Science.gov (United States)

Ke, Yonggang; Voigt, Niels V; Gothelf, Kurt V; Shih, William M

2012-01-25

"Scaffolded DNA origami" has been proven to be a powerful and efficient approach to construct two-dimensional or three-dimensional objects with great complexity. Multilayer DNA origami has been demonstrated with helices packing along either honeycomb-lattice geometry or square-lattice geometry. Here we report successful folding of multilayer DNA origami with helices arranged on a close-packed hexagonal lattice. This arrangement yields a higher density of helical packing and therefore higher resolution of spatial addressing than has been shown previously. We also demonstrate hybrid multilayer DNA origami with honeycomb-lattice, square-lattice, and hexagonal-lattice packing of helices all in one design. The availability of hexagonal close-packing of helices extends our ability to build complex structures using DNA nanotechnology. © 2011 American Chemical Society

Sparse DOA estimation with polynomial rooting

DEFF Research Database (Denmark)

Xenaki, Angeliki; Gerstoft, Peter; Fernandez Grande, Efren

2015-01-01

Direction-of-arrival (DOA) estimation involves the localization of a few sources from a limited number of observations on an array of sensors. Thus, DOA estimation can be formulated as a sparse signal reconstruction problem and solved efficiently with compressive sensing (CS) to achieve highresol......Direction-of-arrival (DOA) estimation involves the localization of a few sources from a limited number of observations on an array of sensors. Thus, DOA estimation can be formulated as a sparse signal reconstruction problem and solved efficiently with compressive sensing (CS) to achieve...... highresolution imaging. Utilizing the dual optimal variables of the CS optimization problem, it is shown with Monte Carlo simulations that the DOAs are accurately reconstructed through polynomial rooting (Root-CS). Polynomial rooting is known to improve the resolution in several other DOA estimation methods...

Coalescence preference in dense packing of bubbles

Science.gov (United States)

Kim, Yeseul; Gim, Bopil; Gim, Bopil; Weon, Byung Mook

2015-11-01

Coalescence preference is the tendency that a merged bubble from the contact of two original bubbles (parent) tends to be near to the bigger parent. Here, we show that the coalescence preference can be blocked by densely packing of neighbor bubbles. We use high-speed high-resolution X-ray microscopy to clearly visualize individual coalescence phenomenon which occurs in micro scale seconds and inside dense packing of microbubbles with a local packing fraction of ~40%. Previous theory and experimental evidence predict a power of -5 between the relative coalescence position and the parent size. However, our new observation for coalescence preference in densely packed microbubbles shows a different power of -2. We believe that this result may be important to understand coalescence dynamics in dense packing of soft matter. This work (NRF-2013R1A22A04008115) was supported by Mid-career Researcher Program through NRF grant funded by the MEST and also was supported by Ministry of Science, ICT and Future Planning (2009-0082580) and by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry and Education, Science and Technology (NRF-2012R1A6A3A04039257).

A General Sparse Tensor Framework for Electronic Structure Theory.

Science.gov (United States)

Manzer, Samuel; Epifanovsky, Evgeny; Krylov, Anna I; Head-Gordon, Martin

2017-03-14

Linear-scaling algorithms must be developed in order to extend the domain of applicability of electronic structure theory to molecules of any desired size. However, the increasing complexity of modern linear-scaling methods makes code development and maintenance a significant challenge. A major contributor to this difficulty is the lack of robust software abstractions for handling block-sparse tensor operations. We therefore report the development of a highly efficient symbolic block-sparse tensor library in order to provide access to high-level software constructs to treat such problems. Our implementation supports arbitrary multi-dimensional sparsity in all input and output tensors. We avoid cumbersome machine-generated code by implementing all functionality as a high-level symbolic C++ language library and demonstrate that our implementation attains very high performance for linear-scaling sparse tensor contractions.

Granular packing as model glass formers

International Nuclear Information System (INIS)

Wang Yujie

2017-01-01

Static granular packings are model hard-sphere glass formers. The nature of glass transition has remained a hotly debated issue. We review recent experimental progresses in using granular materials to study glass transitions. We focus on the growth of glass order with five-fold symmetry in granular packings and relate the findings to both geometric frustration and random first-order phase transition theories. (paper)

A Harmonic Algorithm for the 3D Strip Packing Problem

NARCIS (Netherlands)

N. Bansal (Nikhil); X. Han; K. Iwama; M. Sviridenko; G. Zhang (Guochuan)

2013-01-01

htmlabstractIn the three-dimensional (3D) strip packing problem, we are given a set of 3D rectangular items and a 3D box $B$. The goal is to pack all the items in $B$ such that the height of the packing is minimized. We consider the most basic version of the problem, where the items must be packed

Evaluation of Packed Distillation Columns I - Atmospheric Pressure

National Research Council Canada - National Science Library

Reynolds, Thaine

1951-01-01

.... Four column-packing combinations of the glass columns and four column-packing combinations of the steel columns were investigated at atmospheric pressure using a test mixture of methylcyclohexane...

Low-rank and sparse modeling for visual analysis

CERN Document Server

Fu, Yun

2014-01-01

This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applic

Duration of Nasal Packs in the Management of Epistaxis

International Nuclear Information System (INIS)

Kundi, N. A.; Raza, M.

2015-01-01

Objective:To compare the efficacy of nasal packs for 12 and 24 hours in the management of epistaxis. Study Design: Quasi experimental study. Place and Duration of Study: Combined Military Hospital, Nowshera and Heavy Industries Taxilla Hospital, from October 2012 to April 2013. Methodology: A total of 60 patients presenting with epistaxis were selected and were divided into two groups of 30 patients each. Patients in both the groups were managed by nasal packs. In group-A packs were removed after 12 hours while in group-B after 24 hours. Symptoms of headache, lacrimation and recurrence of bleeding were recorded. SPSS 20 was used for data analysis and p-value less than 0.01 was considered significant. Results: There was significant difference for headache between removal of nasal packs after 12 hours and 24 hours (p < 0.001). There was significant difference for excessive lacrimation at 12 and 24 hours (p = 0.001). No significant difference was observed for recurrence of bleed when nasal packs were removed at 12 and 24 hours (p = 0.317). Conclusion: Duration in removal of nasal packs after 12 or 24 hours made a difference in the management of epistaxis. Symptoms of headache and excessive lacrimation were significantly higher when nasal packs were removed after 24 hours. It is recommended that patient could be managed with lesser duration of packs after episode of epistaxis to avoid inconvenience. (author)

Sparse BLIP: BLind Iterative Parallel imaging reconstruction using compressed sensing.

Science.gov (United States)

She, Huajun; Chen, Rong-Rong; Liang, Dong; DiBella, Edward V R; Ying, Leslie

2014-02-01

To develop a sensitivity-based parallel imaging reconstruction method to reconstruct iteratively both the coil sensitivities and MR image simultaneously based on their prior information. Parallel magnetic resonance imaging reconstruction problem can be formulated as a multichannel sampling problem where solutions are sought analytically. However, the channel functions given by the coil sensitivities in parallel imaging are not known exactly and the estimation error usually leads to artifacts. In this study, we propose a new reconstruction algorithm, termed Sparse BLind Iterative Parallel, for blind iterative parallel imaging reconstruction using compressed sensing. The proposed algorithm reconstructs both the sensitivity functions and the image simultaneously from undersampled data. It enforces the sparseness constraint in the image as done in compressed sensing, but is different from compressed sensing in that the sensing matrix is unknown and additional constraint is enforced on the sensitivities as well. Both phantom and in vivo imaging experiments were carried out with retrospective undersampling to evaluate the performance of the proposed method. Experiments show improvement in Sparse BLind Iterative Parallel reconstruction when compared with Sparse SENSE, JSENSE, IRGN-TV, and L1-SPIRiT reconstructions with the same number of measurements. The proposed Sparse BLind Iterative Parallel algorithm reduces the reconstruction errors when compared to the state-of-the-art parallel imaging methods. Copyright © 2013 Wiley Periodicals, Inc.

Effect of packing fraction variations on reactivity in pebble-bed reactor

International Nuclear Information System (INIS)

Snoj, L.; Ravnik, M.

2004-01-01

The pebble-bed reactor (PBR) core consists of large number of randomly packed spherical fuel elements. The effect of fuel element packing density variations on multiplication factor in a typical PBR is studied using WIMS code. It is observed that at normal conditions the k-eff increases with packing fraction. Effects of secondary coolant ingress (water or molten lead) in the core at accidental conditions are studied at various packing densities. The effect of water ingress on reactivity depends strongly on water density and packing fraction and is prevailingly positive, while the lead ingress reduces multiplication factor regardless of lead effective density and packing fraction. Both effects are stronger at lower packing fractions. (author)

Real-time SPARSE-SENSE cardiac cine MR imaging: optimization of image reconstruction and sequence validation.

Science.gov (United States)

Goebel, Juliane; Nensa, Felix; Bomas, Bettina; Schemuth, Haemi P; Maderwald, Stefan; Gratz, Marcel; Quick, Harald H; Schlosser, Thomas; Nassenstein, Kai

2016-12-01

Improved real-time cardiac magnetic resonance (CMR) sequences have currently been introduced, but so far only limited practical experience exists. This study aimed at image reconstruction optimization and clinical validation of a new highly accelerated real-time cine SPARSE-SENSE sequence. Left ventricular (LV) short-axis stacks of a real-time free-breathing SPARSE-SENSE sequence with high spatiotemporal resolution and of a standard segmented cine SSFP sequence were acquired at 1.5 T in 11 volunteers and 15 patients. To determine the optimal iterations, all volunteers' SPARSE-SENSE images were reconstructed using 10-200 iterations, and contrast ratios, image entropies, and reconstruction times were assessed. Subsequently, the patients' SPARSE-SENSE images were reconstructed with the clinically optimal iterations. LV volumetric values were evaluated and compared between both sequences. Sufficient image quality and acceptable reconstruction times were achieved when using 80 iterations. Bland-Altman plots and Passing-Bablok regression showed good agreement for all volumetric parameters. 80 iterations are recommended for iterative SPARSE-SENSE image reconstruction in clinical routine. Real-time cine SPARSE-SENSE yielded comparable volumetric results as the current standard SSFP sequence. Due to its intrinsic low image acquisition times, real-time cine SPARSE-SENSE imaging with iterative image reconstruction seems to be an attractive alternative for LV function analysis. • A highly accelerated real-time CMR sequence using SPARSE-SENSE was evaluated. • SPARSE-SENSE allows free breathing in real-time cardiac cine imaging. • For clinically optimal SPARSE-SENSE image reconstruction, 80 iterations are recommended. • Real-time SPARSE-SENSE imaging yielded comparable volumetric results as the reference SSFP sequence. • The fast SPARSE-SENSE sequence is an attractive alternative to standard SSFP sequences.

Solvent-assisted microstructural evolution and enhanced performance of porous ZnO films for plastic dye-sensitized solar cells

Science.gov (United States)

Ohashi, Hitomi; Hagiwara, Manabu; Fujihara, Shinobu

2017-02-01

A low-temperature process for fabricating porous ZnO films on plastic, indium tin oxide-coated polyethylene naphthalate substrates is developed for their use in dye-sensitized solar cells. A special attention is paid to modification of microscopic morphologies for enhancing interparticle connection. ZnO films having two kinds of macroscopic morphologies (flower-like particles and densely packed nanoparticles) are fabricated at temperatures below the heatproof temperature of the substrate, and subsequently immersed in mixed solvents composed of water and ethanol at 90 °C. The immersion leads to the growth of constituting ZnO particles and also the evolution of interparticle connection, depending on solvent compositions. The cell performance is largely improved especially in a short-circuit current density and a power conversion efficiency. The immersion effect is more remarkable for the cell using the densely packed ZnO film, with a 62% increase in the current density and an 84% increase in the conversion efficiency. In consequence, our plastic N719-sensitized ZnO cell shows the conversion efficiency as high as 4.1%.

Cylinder valve packing nut studies

Energy Technology Data Exchange (ETDEWEB)

Blue, S.C. [Martin Marietta Energy Systems, Inc., Paducah, KY (United States)

1991-12-31

The design, manufacture, and use of cylinder valve packing nuts have been studied to improve their resistance to failure from stress corrosion cracking. Stress frozen photoelastic models have been analyzed to measure the stress concentrations at observed points of failure. The load effects induced by assembly torque and thermal expansion of stem packing were observed by strain gaging nuts. The effects of finishing operations and heat treatment were studied by the strain gage hole boring and X-ray methods. Modifications of manufacturing and operation practices are reducing the frequency of stress corrosion failures.

Methodology for using prompt gamma activation analysis to measure the binary diffusion coefficient of a gas in a porous medium

International Nuclear Information System (INIS)

Rios Perez, Carlos A.; Biegalski, Steve R.; Deinert, Mark R.

2012-01-01

Highlights: ► Prompt gamma activation analysis is used to study gas diffusion in a porous system. ► Diffusion coefficients are determined using prompt gamma activation analysis. ► Predictions concentrations fit experimental measurements with an R 2 of 0.98. - Abstract: Diffusion plays a critical role in determining the rate at which gases migrate through porous systems. Accurate estimates of diffusion coefficients are essential if gas transport is to be accurately modeled and better techniques are needed that can be used to measure these coefficients non-invasively. Here we present a novel method for using prompt gamma activation analysis to determine the binary diffusion coefficients of a gas in a porous system. Argon diffusion experiments were conducted in a 1 m long, 10 cm diameter, horizontal column packed with a SiO 2 sand. The temporal variation of argon concentration within the system was measured using prompt gamma activation analysis. The binary diffusion coefficient was obtained by comparing the experimental data with the predictions from a numerical model in which the diffusion coefficient was varied until the sum of square errors between experiment and model data was minimized. Predictions of argon concentration using the optimal diffusivity fit experimental measurements with an R 2 of 0.983.

The general packed column : an analytical solution

NARCIS (Netherlands)

Gielen, J.L.W.

2000-01-01

The transient behaviour of a packed column is considered. The column, uniformly packed on a macroscopic scale, is multi-structured on the microscopic level: the solid phase consists of particles, which may differ in incidence, shape or size, and other relevant physical properties. Transport in the

Characteristics of illegal and legal cigarette packs sold in Guatemala.

Science.gov (United States)

Arevalo, Rodrigo; Corral, Juan E; Monzon, Diego; Yoon, Mira; Barnoya, Joaquin

2016-11-25

Guatemala, as a party to the Framework Convention on Tobacco Control (FCTC), is required to regulate cigarette packaging and labeling and eliminate illicit tobacco trade. Current packaging and labeling characteristics (of legal and illegal cigarettes) and their compliance with the FCTC is unknown. We sought to analyze package and label characteristics of illegal and legal cigarettes sold in Guatemala. We visited the 22 largest traditional markets in the country to purchase illegal cigarettes. All brands registered on tobacco industry websites were purchased as legal cigarettes. Analysis compared labeling characteristics of illegal and legal packs. Most (95%) markets and street vendors sold illegal cigarettes; 104 packs were purchased (79 illegal and 25 legal). Ten percent of illegal and none of the legal packs had misleading terms. Half of the illegal packs had a warning label covering 26 to 50% of the pack surface. All legal packs had a label covering 25% of the surface. Illegal packs were more likely to have information on constituents and emissions (85% vs. 45%, p Guatemala, neither illegal nor legal cigarette packs comply with FCTC labeling mandates. Urgent implementation and enforcement of the FCTC is necessary to halt the tobacco epidemic.

Generalized network improvement and packing problems

CERN Document Server

Holzhauser, Michael

2016-01-01

Michael Holzhauser discusses generalizations of well-known network flow and packing problems by additional or modified side constraints. By exploiting the inherent connection between the two problem classes, the author investigates the complexity and approximability of several novel network flow and packing problems and presents combinatorial solution and approximation algorithms. Contents Fractional Packing and Parametric Search Frameworks Budget-Constrained Minimum Cost Flows: The Continuous Case Budget-Constrained Minimum Cost Flows: The Discrete Case Generalized Processing Networks Convex Generalized Flows Target Groups Researchers and students in the fields of mathematics, computer science, and economics Practitioners in operations research and logistics The Author Dr. Michael Holzhauser studied computer science at the University of Kaiserslautern and is now a research fellow in the Optimization Research Group at the Department of Mathematics of the University of Kaiserslautern.

Security-enhanced phase encryption assisted by nonlinear optical correlation via sparse phase

International Nuclear Information System (INIS)

Chen, Wen; Chen, Xudong; Wang, Xiaogang

2015-01-01

We propose a method for security-enhanced phase encryption assisted by a nonlinear optical correlation via a sparse phase. Optical configurations are established based on a phase retrieval algorithm for embedding an input image and the secret data into phase-only masks. We found that when one or a few phase-only masks generated during data hiding are sparse, it is possible to integrate these sparse masks into those phase-only masks generated during the encoding of the input image. Synthesized phase-only masks are used for the recovery, and sparse distributions (i.e., binary maps) for generating the incomplete phase-only masks are considered as additional parameters for the recovery of secret data. It is difficult for unauthorized receivers to know that a useful phase has been sparsely distributed in the finally generated phase-only masks for secret-data recovery. Only when the secret data are correctly verified can the input image obtained with valid keys be claimed as targeted information. (paper)

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

Science.gov (United States)

Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

Low-rank sparse learning for robust visual tracking

KAUST Repository

Zhang, Tianzhu

2012-01-01

In this paper, we propose a new particle-filter based tracking algorithm that exploits the relationship between particles (candidate targets). By representing particles as sparse linear combinations of dictionary templates, this algorithm capitalizes on the inherent low-rank structure of particle representations that are learned jointly. As such, it casts the tracking problem as a low-rank matrix learning problem. This low-rank sparse tracker (LRST) has a number of attractive properties. (1) Since LRST adaptively updates dictionary templates, it can handle significant changes in appearance due to variations in illumination, pose, scale, etc. (2) The linear representation in LRST explicitly incorporates background templates in the dictionary and a sparse error term, which enables LRST to address the tracking drift problem and to be robust against occlusion respectively. (3) LRST is computationally attractive, since the low-rank learning problem can be efficiently solved as a sequence of closed form update operations, which yield a time complexity that is linear in the number of particles and the template size. We evaluate the performance of LRST by applying it to a set of challenging video sequences and comparing it to 6 popular tracking methods. Our experiments show that by representing particles jointly, LRST not only outperforms the state-of-the-art in tracking accuracy but also significantly improves the time complexity of methods that use a similar sparse linear representation model for particles [1]. © 2012 Springer-Verlag.

Porous Hydrogen-Bonded Organic Frameworks

Directory of Open Access Journals (Sweden)

Yi-Fei Han

2017-02-01

Full Text Available Ordered porous solid-state architectures constructed via non-covalent supramolecular self-assembly have attracted increasing interest due to their unique advantages and potential applications. Porous metal-coordination organic frameworks (MOFs are generated by the assembly of metal coordination centers and organic linkers. Compared to MOFs, porous hydrogen-bonded organic frameworks (HOFs are readily purified and recovered via simple recrystallization. However, due to lacking of sufficiently ability to orientate self-aggregation of building motifs in predictable manners, rational design and preparation of porous HOFs are still challenging. Herein, we summarize recent developments about porous HOFs and attempt to gain deeper insights into the design strategies of basic building motifs.

Sodium Silicate Behavior in Porous Media Applied for In-Depth Profile Modifications

Directory of Open Access Journals (Sweden)

Hossein A. Akhlaghi Amiri

2014-03-01

Full Text Available This paper addresses alkaline sodium silicate (Na-silicate behavior in porous media. One of the advantages of the Na-silicate system is its water-like injectivity during the placement stage. Mixing Na-silicate with saline water results in metal silicate precipitation as well as immediate gelation. This work demonstrated that low salinity water (LSW, sea water diluted 25 times could be used as a pre-flush in flooding operations. A water override phenomenon was observed during gel formation which is caused by gravity segregation. Dynamic adsorption tests in the sand-packed tubes showed inconsiderable adsorbed silicon density (about 8.5 × 10−10 kg/cm3 for a solution with 33 mg/L silicon content, which is less than the estimated mono-layer adsorption density of 1.4 × 10−8 kg/cm3. Na-silicate enhanced water sweep efficiency after application in a dual-permeability sand-pack system, without leak off into the oil-bearing low permeability (LP zone. Field-scale numerical sensitivity studies in a layered reservoir demonstrated that higher permeability and viscosity contrasts and lower vertical/horizontal permeability ratio result in lower Na-silicate leakoff into the matrix. The length of the mixing zone between reservoir water and the injected Na-silicate solution, which is formed by low salinity pre-flush, acts as a buffer zone.

Multi-Node Thermal System Model for Lithium-Ion Battery Packs: Preprint

Energy Technology Data Exchange (ETDEWEB)

Shi, Ying; Smith, Kandler; Wood, Eric; Pesaran, Ahmad

2015-09-14

Temperature is one of the main factors that controls the degradation in lithium ion batteries. Accurate knowledge and control of cell temperatures in a pack helps the battery management system (BMS) to maximize cell utilization and ensure pack safety and service life. In a pack with arrays of cells, a cells temperature is not only affected by its own thermal characteristics but also by its neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs. neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs.

Glottotecnologie didattiche per i migranti L’italiano fra le altre lingue nel progetto L-Pack (Citizenship Language Pack for Migrants in Europe

Directory of Open Access Journals (Sweden)

Pierangela Diadori

2017-01-01

Full Text Available Teaching languages to migrants through ICT L-Pack Project for Italian and other languages (Citizenship Language Pack for Migrants in EuropeThe most recent trends in technology and the internet, commonly called Web 2.0., have determined new concepts in teaching and learning that involve autonomy, multimodality and flexibility. New approaches to ‘knowledge by technology’ are changing both teachers’ and learners’ roles, responding to their different aims and needs. At the same time, nearly 4 million people are presently involved in massive migration processes all over Europe, coming either from outside Europe or from another EU member state. The EU policies on migrants state the importance of a basic knowledge of the host country’s language, history and institutions for an effective integration process, and EU governments are expected to contribute to this aim. This paper describes the European Project ‘L-PACK: Citizenship Language Pack For Migrants in Europe’ (2011-2016, whose main aim consisted in developing a series of internet video texts, accompanied with materials and resources to lead adult migrants to A2 level (according to QCER levels scale in different EU languages. The project has been developed in two main stages. In the first part of the programme, called L-Pack 1, from 2011 to 2013, the languages were Italian, Spanish, German, Lithuanian, Greek and Czech. In the second part, called L-Pack 2 extended, from 2014 to 2016, the project added English and French and was integrated with new resources and tools. The L-PACK course, which consists of 60 short video dialogues from everyday life, supported by comprehension activities and linguistic explanation and rules, is totally free and available through Youtube, Wikibooks and Soundcloud. The dedicated website http://www.l-pack.eu was visited by 120.000 users from 146 countries in the period 2011-2016. L-Pack teaching materials have also been used by teachers in classroom

Prediction of radionuclide migration in the geosphere: is the porous-flow model adequate

International Nuclear Information System (INIS)

Neretnieks, I.

1982-01-01

Practically all models used today to describe radionuclide migration in geologic media are based on the concept of flow in porous media. Recently it has been questioned if Fickian dispersion is the most important dispersion mechanism. Field observations of dispersion indicate that the dispersion coefficient increases with observation distance. This should not be the case in a homogeneous porous medium. For a medium with essentially independent channels, on the other hand, such an effect can be predicted. In some calculated examples it is shown that the use of the Fickian dispersion mechanism will very seriously underestimate the radionuclide concentration at a point downstream if the spreading mechanism in reality is channelling. The consequences of the often-used assumption that the interaction between the radionuclides and the rock is instantaneous is also discussed. It has been shown that in sparsely fissured crystalline rock the whole rock mass will not be able to participate in the sorption reactions, because the radionuclides will not have time to penetrate all through the large blocks. On the other hand, the assumption that only the surface of the fissures interacts with the radionuclides is likely to be an extremely conservative assumption in view of some recent diffusion experiments in crystalline rocks performed in our laboratories and at the Canadian Geologic Survey. Some experimental results on radionuclide migration in a single natural fissure under well-controlled conditions in the laboratory are also presented and interpreted using a model which includes channelling, surface sorption, diffusion in the rock matrix and sorption in the rock matrix. Some implications of these mechanisms in predicting radionuclide migration in the geosphere are discussed and compared with what a porous-flow model would predict

Stress concentrations in an impregnated fibre bundle with random fibre packing

OpenAIRE

Swolfs, Y.; Gorbatikh, L.; Romanov, V.; Orlova, S.; Lomov, S. V.; Verpoest, I.

2013-01-01

The stress redistribution after a single fibre break is a fundamental issue in longitudinal strength models for unidirectional composites. Current models assume hexagonal or square fibre packings. In the present work, random fibre packings were modelled using 3D finite element analysis and compared to ordered fibre packings. Significant differences in the stress redistribution are found. Compared to square and hexagonal packings, random fibre packings result in smaller stress concentration fa...

Group-sparse representation with dictionary learning for medical image denoising and fusion.

Science.gov (United States)

Li, Shutao; Yin, Haitao; Fang, Leyuan

2012-12-01

Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.

Development of porous structure simulator for multi-scale simulation of irregular porous catalysts

International Nuclear Information System (INIS)

Koyama, Michihisa; Suzuki, Ai; Sahnoun, Riadh; Tsuboi, Hideyuki; Hatakeyama, Nozomu; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A.; Miyamoto, Akira

2008-01-01

Efficient development of highly functional porous materials, used as catalysts in the automobile industry, demands a meticulous knowledge of the nano-scale interface at the electronic and atomistic scale. However, it is often difficult to correlate the microscopic interfacial interactions with macroscopic characteristics of the materials; for instance, the interaction between a precious metal and its support oxide with long-term sintering properties of the catalyst. Multi-scale computational chemistry approaches can contribute to bridge the gap between micro- and macroscopic characteristics of these materials; however this type of multi-scale simulations has been difficult to apply especially to porous materials. To overcome this problem, we have developed a novel mesoscopic approach based on a porous structure simulator. This simulator can construct automatically irregular porous structures on a computer, enabling simulations with complex meso-scale structures. Moreover, in this work we have developed a new method to simulate long-term sintering properties of metal particles on porous catalysts. Finally, we have applied the method to the simulation of sintering properties of Pt on alumina support. This newly developed method has enabled us to propose a multi-scale simulation approach for porous catalysts

Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

KAUST Repository

Desmal, Abdulla; Bagci, Hakan

2015-01-01

A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.

Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

KAUST Repository

Desmal, Abdulla

2015-04-13

A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.

Microbiological Quality of Blister Pack Tablets in Community ...

African Journals Online (AJOL)

Keywords: Blister pack, Community pharmacy, Good Manufacturing Practice, Microbial contamination,. Quality control ... High levels of microbial contamination in blister-packed tablets ... and their drugs approved by the Jordan Food and Drug ...

Gas anti-solvent precipitation assisted salt leaching for generation of micro- and nano-porous wall in bio-polymeric 3D scaffolds

Energy Technology Data Exchange (ETDEWEB)

Flaibani, Marina; Elvassore, Nicola, E-mail: nicola.elvassore@unipd.it

2012-08-01

The mass transport through biocompatible and biodegradable polymeric 3D porous scaffolds may be depleted by non-porous impermeable internal walls. As consequence the concentration of metabolites and growth factors within the scaffold may be heterogeneous leading to different cell fate depending on spatial cell location, and in some cases it may compromise cell survival. In this work, we fabricated polymeric scaffolds with micro- and nano-scale porosity by developing a new technique that couples two conventional scaffold production methods: solvent casting-salt leaching and gas antisolvent precipitation. 10-15 w/w solutions of a hyaluronic benzyl esters (HYAFF11) and poly-(lactic acid) (PLA) were used to fill packed beds of 0.177-0.425 mm NaCl crystals. The polymer precipitation in micro and nano-porous structures between the salt crystals was induced by high-pressure gas, then its flushing extracted the residual solvent. The salt was removed by water-wash. Morphological analysis by scanning electron microscopy showed a uniform porosity ({approx} 70%) and a high interconnectivity between porous. The polymeric walls were porous themselves counting for 30% of the total porosity. This wall porosity did not lead to a remarkable change in compressive modulus, deformation, and rupture pressure. Scaffold biocompatibility was tested with murine muscle cell line C2C12 for 4 and 7 days. Viability analysis and histology showed that micro- and nano-porous scaffolds are biocompatible and suitable for 3D cell culture promoting cell adhesion on the polymeric wall and allowing their proliferation in layers. Micro- and nano-scale porosities enhance cell migration and growth in the inner part of the scaffold. - Highlights: Black-Right-Pointing-Pointer Gas anti-solvent precipitation and salt leaching for scaffold fabrication. Black-Right-Pointing-Pointer Hyaluronic benzyl esters (HYAFF11) and poly-(lactic acid) (PLA) sponges. Black-Right-Pointing-Pointer Gas anti-solvent precipitation

Gas anti-solvent precipitation assisted salt leaching for generation of micro- and nano-porous wall in bio-polymeric 3D scaffolds

International Nuclear Information System (INIS)

Flaibani, Marina; Elvassore, Nicola

2012-01-01

The mass transport through biocompatible and biodegradable polymeric 3D porous scaffolds may be depleted by non-porous impermeable internal walls. As consequence the concentration of metabolites and growth factors within the scaffold may be heterogeneous leading to different cell fate depending on spatial cell location, and in some cases it may compromise cell survival. In this work, we fabricated polymeric scaffolds with micro- and nano-scale porosity by developing a new technique that couples two conventional scaffold production methods: solvent casting-salt leaching and gas antisolvent precipitation. 10–15 w/w solutions of a hyaluronic benzyl esters (HYAFF11) and poly-(lactic acid) (PLA) were used to fill packed beds of 0.177–0.425 mm NaCl crystals. The polymer precipitation in micro and nano-porous structures between the salt crystals was induced by high-pressure gas, then its flushing extracted the residual solvent. The salt was removed by water-wash. Morphological analysis by scanning electron microscopy showed a uniform porosity (∼ 70%) and a high interconnectivity between porous. The polymeric walls were porous themselves counting for 30% of the total porosity. This wall porosity did not lead to a remarkable change in compressive modulus, deformation, and rupture pressure. Scaffold biocompatibility was tested with murine muscle cell line C2C12 for 4 and 7 days. Viability analysis and histology showed that micro- and nano-porous scaffolds are biocompatible and suitable for 3D cell culture promoting cell adhesion on the polymeric wall and allowing their proliferation in layers. Micro- and nano-scale porosities enhance cell migration and growth in the inner part of the scaffold. - Highlights: ► Gas anti-solvent precipitation and salt leaching for scaffold fabrication. ► Hyaluronic benzyl esters (HYAFF11) and poly-(lactic acid) (PLA) sponges. ► Gas anti-solvent precipitation induces nano-porous structures. ► Scaffolds are biocompatible and

Improved Taxation Rate for Bin Packing Games

Science.gov (United States)

Kern, Walter; Qiu, Xian

A cooperative bin packing game is a N-person game, where the player set N consists of k bins of capacity 1 each and n items of sizes a 1, ⋯ ,a n . The value of a coalition of players is defined to be the maximum total size of items in the coalition that can be packed into the bins of the coalition. We present an alternative proof for the non-emptiness of the 1/3-core for all bin packing games and show how to improve this bound ɛ= 1/3 (slightly). We conjecture that the true best possible value is ɛ= 1/7.

On the Automatic Parallelization of Sparse and Irregular Fortran Programs

Directory of Open Access Journals (Sweden)

Yuan Lin

1999-01-01

Full Text Available Automatic parallelization is usually believed to be less effective at exploiting implicit parallelism in sparse/irregular programs than in their dense/regular counterparts. However, not much is really known because there have been few research reports on this topic. In this work, we have studied the possibility of using an automatic parallelizing compiler to detect the parallelism in sparse/irregular programs. The study with a collection of sparse/irregular programs led us to some common loop patterns. Based on these patterns new techniques were derived that produced good speedups when manually applied to our benchmark codes. More importantly, these parallelization methods can be implemented in a parallelizing compiler and can be applied automatically.

Investigation of Factors Influencing Dispersion of Liquid Hydrocarbons in Porous Media

Directory of Open Access Journals (Sweden)

Hussain Ali Baker

2016-08-01

Full Text Available An experimental work has been done to study the major factors that affect the axial dispersion of some hydrocarbons during liquid-liquid miscible displacement. Kerosene and gas oil are used as displacing phase while seven liquid hydrocarbons of high purity represent the displaced phase, three of the liquids are aromatics and the rest are of paraffinic base. In conducting the experiments, two packed beds of different porosity and permeability are used as porous media. The results showed that the displacement process is not a piston flow, breakthrough of displacing fluids are shown before one pore volume has been injected. The processes are stable with no evidence of viscous fingering. Dispersion model as adapted by Brigham et.al (1961 is used to determine the axial dispersion coefficient of displacing fluid. The results show an increasing in dispersion coefficient as the interstitial velocity and viscosity ratio increases.

New series of paper pack vending machines; Paper pack jido hanbaiki no shin series

Energy Technology Data Exchange (ETDEWEB)

Ohashi, M. [Fuji Denki Reiki Co. Ltd., Tokyo (Japan); Umino, S. [Fuji Electric Co. Ltd., Tokyo (Japan)

1996-07-10

This paper presents series of paper pack vending machines. These machines may be broadly classified into those of cold drinks and of hot and cold drinks depending on the storage temperature of products. The former is the machine for cooling dairy products at 10{degree}C with a combined stacking by direct-stacked racks and chain-multiracks. The latter is provided with divided storing chambers with each chamber selectively cooled or heated. Products in the hot chamber are canned coffee and the like set at 55{degree}C. The temperature control is performed by a microcomputer. The chain-multiracks are provided with advantages such as capability of handling various kinds of container shapes, storing drinks and foods vertically, replacing products by the change of a shelf attachment with one operation, and storing one liter packs by setting pair columns. The direct-stacked racks are provided with advantages such as versatility of handling various kinds of containers and miniaturization of the mechanism other than the storage part. The installation space was reduced by devising the opening and closing of the door. The control part is capable of setting temperatures differently for cans and paper packs. 7 figs., 1 tab.

Random close packing in protein cores.

Science.gov (United States)

Gaines, Jennifer C; Smith, W Wendell; Regan, Lynne; O'Hern, Corey S

2016-03-01

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ ≈ 0.75, a value that is similar to close packing of equal-sized spheres. A limitation of these analyses was the use of extended atom models, rather than the more physically accurate explicit hydrogen model. The validity of the explicit hydrogen model was proved in our previous studies by its ability to predict the side chain dihedral angle distributions observed in proteins. In contrast, the extended atom model is not able to recapitulate the side chain dihedral angle distributions, and gives rise to large atomic clashes at side chain dihedral angle combinations that are highly probable in protein crystal structures. Here, we employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high-resolution protein structures. We find that these protein cores have ϕ ≈ 0.56, which is similar to results obtained from simulations of random packings of individual amino acids. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations to protein cores and interfaces of known structure.

Minimal packing duration in close reduction for nasal bone fracture treatment.

Science.gov (United States)

Choi, Dong Sik; Lee, Jeong Woo; Yang, Jung Dug; Chung, Ho Yun; Cho, Byung Chae; Choi, Kang Young

2015-04-15

Nasal bone fracture is the most common type of facial bone fracture. The optimal duration of the packing after closed reduction has been a controversial issue. The packing has several disadvantages such as blocking the nasal airway, causing infection and a headache, which is the most common immediate complication. The present study investigated the minimal and optimal duration of the nasal packing following reduction surgery of nasal bone fracture. A prospective study was performed for the patients undergoing reduction surgery following nasal bone fracture between July 2010 and June 2012. The patients were categorised into three groups according to the duration of nasal packing. For the patients treated between July 2010 and June 2011, nasal packing was maintained for 5 days. For those between July 2011 and December 2011, packing was maintained for 3 days. For those between January 2012 and June 2012, the packing was removed after 1 day. The computed tomography scan and the cephalolateral X-ray were checked at immediate postoperative period after packing removal and 6 months postoperatively. The alteration of heights, deviations, and nasal bone contours with time passage were compared among three groups. The patient satisfaction survey was also performed and compared. A total of 530 patients including 322 of the 5-days packing group, 102 of the 3-days group, and 106 of the 1-day group were enrolled. There was no statistically significant difference between the groups in terms of heights, deviations, and nasal bone contours (p-value ≥ 0.05). In the patient satisfaction survey, the 1-day packing group complained of discomfort related to nasal packing and headache symptoms much less, compared to the other two groups. The present study demonstrated that 1-day packing had comparable postoperative outcome with reducing the patients' discomfort. As such, a longer packing duration was not needed to achieve stable results one day is a reasonable packing time for most

Split-Bregman-based sparse-view CT reconstruction

Energy Technology Data Exchange (ETDEWEB)

Vandeghinste, Bert; Vandenberghe, Stefaan [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Goossens, Bart; Pizurica, Aleksandra; Philips, Wilfried [Ghent Univ. (Belgium). Image Processing and Interpretation Research Group (IPI); Beenhouwer, Jan de [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Antwerp Univ., Wilrijk (Belgium). The Vision Lab; Staelens, Steven [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Antwerp Univ., Edegem (Belgium). Molecular Imaging Centre Antwerp

2011-07-01

Total variation minimization has been extensively researched for image denoising and sparse view reconstruction. These methods show superior denoising performance for simple images with little texture, but result in texture information loss when applied to more complex images. It could thus be beneficial to use other regularizers within medical imaging. We propose a general regularization method, based on a split-Bregman approach. We show results for this framework combined with a total variation denoising operator, in comparison to ASD-POCS. We show that sparse-view reconstruction and noise regularization is possible. This general method will allow us to investigate other regularizers in the context of regularized CT reconstruction, and decrease the acquisition times in {mu}CT. (orig.)

Economics Action Pack.

Science.gov (United States)

McDonald's Corp., Oak Brook, IL.

One of five McDonald's Action Packs, this learning package introduces intermediate grade students to basic economic concepts. The fourteen activities include the topics of consumption (4 activities), production (5), the market system (3), a pretest, and a posttest. Specific titles under consumption include The Wonderful Treasure Tree (introduction…

A framework for general sparse matrix-matrix multiplication on GPUs and heterogeneous processors

DEFF Research Database (Denmark)

Liu, Weifeng; Vinter, Brian

2015-01-01

General sparse matrix-matrix multiplication (SpGEMM) is a fundamental building block for numerous applications such as algebraic multigrid method (AMG), breadth first search and shortest path problem. Compared to other sparse BLAS routines, an efficient parallel SpGEMM implementation has to handle...... extra irregularity from three aspects: (1) the number of nonzero entries in the resulting sparse matrix is unknown in advance, (2) very expensive parallel insert operations at random positions in the resulting sparse matrix dominate the execution time, and (3) load balancing must account for sparse data...... memory space and efficiently utilizes the very limited on-chip scratchpad memory. Parallel insert operations of the nonzero entries are implemented through the GPU merge path algorithm that is experimentally found to be the fastest GPU merge approach. Load balancing builds on the number of necessary...

Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.

Science.gov (United States)

Zhang, Guoqing; Sun, Huaijiang; Porikli, Fatih; Liu, Yazhou; Sun, Quansen

2017-08-29

In recent years, sparse representation based classification (SRC) is one of the most successful methods and has been shown impressive performance in various classification tasks. However, when the training data has a different distribution than the testing data, the learned sparse representation may not be optimal, and the performance of SRC will be degraded significantly. To address this problem, in this paper, we propose an optimal couple projections for domain-adaptive sparse representation-based classification (OCPD-SRC) method, in which the discriminative features of data in the two domains are simultaneously learned with the dictionary that can succinctly represent the training and testing data in the projected space. OCPD-SRC is designed based on the decision rule of SRC, with the objective to learn coupled projection matrices and a common discriminative dictionary such that the between-class sparse reconstruction residuals of data from both domains are maximized, and the within-class sparse reconstruction residuals of data are minimized in the projected low-dimensional space. Thus, the resulting representations can well fit SRC and simultaneously have a better discriminant ability. In addition, our method can be easily extended to multiple domains and can be kernelized to deal with the nonlinear structure of data. The optimal solution for the proposed method can be efficiently obtained following the alternative optimization method. Extensive experimental results on a series of benchmark databases show that our method is better or comparable to many state-of-the-art methods.

Frequency-Dependent Streaming Potential of Porous Media—Part 2: Experimental Measurement of Unconsolidated Materials

Directory of Open Access Journals (Sweden)

P. W. J. Glover

2012-01-01

Full Text Available Frequency-dependent streaming potential coefficient measurements have been made upon Ottawa sand and glass bead packs using a new apparatus that is based on an electromagnetic drive. The apparatus operates in the range 1 Hz to 1 kHz with samples of 25.4 mm diameter up to 150 mm long. The results have been analysed using theoretical models that are either (i based upon vibrational mechanics, (ii treat the geological material as a bundle of capillary tubes, or (iii treat the material as a porous medium. The best fit was provided by the Pride model and its simplification, which is satisfying as this model was conceived for porous media rather than capillary tube bundles. Values for the transition frequency were derived from each of the models for each sample and were found to be in good agreement with those expected from the independently measured effective pore radius of each material. The fit to the Pride model for all four samples was also found to be consistent with the independently measured steady-state permeability, while the value of the streaming potential coefficient in the low-frequency limit was found to be in good agreement with other steady-state streaming potential coefficient data.

Two-dimensional sparse wavenumber recovery for guided wavefields

Science.gov (United States)

Sabeti, Soroosh; Harley, Joel B.

2018-04-01

The multi-modal and dispersive behavior of guided waves is often characterized by their dispersion curves, which describe their frequency-wavenumber behavior. In prior work, compressive sensing based techniques, such as sparse wavenumber analysis (SWA), have been capable of recovering dispersion curves from limited data samples. A major limitation of SWA, however, is the assumption that the structure is isotropic. As a result, SWA fails when applied to composites and other anisotropic structures. There have been efforts to address this issue in the literature, but they either are not easily generalizable or do not sufficiently express the data. In this paper, we enhance the existing approaches by employing a two-dimensional wavenumber model to account for direction-dependent velocities in anisotropic media. We integrate this model with tools from compressive sensing to reconstruct a wavefield from incomplete data. Specifically, we create a modified two-dimensional orthogonal matching pursuit algorithm that takes an undersampled wavefield image, with specified unknown elements, and determines its sparse wavenumber characteristics. We then recover the entire wavefield from the sparse representations obtained with our small number of data samples.

Sparse matrix test collections

Energy Technology Data Exchange (ETDEWEB)

Duff, I.

1996-12-31

This workshop will discuss plans for coordinating and developing sets of test matrices for the comparison and testing of sparse linear algebra software. We will talk of plans for the next release (Release 2) of the Harwell-Boeing Collection and recent work on improving the accessibility of this Collection and others through the World Wide Web. There will only be three talks of about 15 to 20 minutes followed by a discussion from the floor.

Porous silicon: X-rays sensitivity

International Nuclear Information System (INIS)

Gerstenmayer, J.L.; Vibert, Patrick; Mercier, Patrick; Rayer, Claude; Hyvernage, Michel; Herino, Roland; Bsiesy, Ahmad

1994-01-01

We demonstrate that high porosity anodically porous silicon is radioluminescent. Interests of this study are double. Firstly: is the construction of porous silicon X-rays detectors (imagers) possible? Secondly: is it necessary to protect silicon porous based optoelectronic systems from ionising radiations effects (spatial environment)? ((orig.))

Packing parameters effect on injection molding of polypropylene nanostructured surfaces

DEFF Research Database (Denmark)

Calaon, Matteo; Tosello, Guido; Hansen, Hans Nørgaard

2012-01-01

having a diameter of 500 nm was employed. The tool insert surface was produced using chemical-based-batch techniques such aluminum anodization and nickel electroplating. During the injection molding process, polypropylene (PP) was employed as material and packing phase parameters (packing time, packing...

JiTTree: A Just-in-Time Compiled Sparse GPU Volume Data Structure

KAUST Repository

Labschutz, Matthias

2015-08-12

Sparse volume data structures enable the efficient representation of large but sparse volumes in GPU memory for computation and visualization. However, the choice of a specific data structure for a given data set depends on several factors, such as the memory budget, the sparsity of the data, and data access patterns. In general, there is no single optimal sparse data structure, but a set of several candidates with individual strengths and drawbacks. One solution to this problem are hybrid data structures which locally adapt themselves to the sparsity. However, they typically suffer from increased traversal overhead which limits their utility in many applications. This paper presents JiTTree, a novel sparse hybrid volume data structure that uses just-in-time compilation to overcome these problems. By combining multiple sparse data structures and reducing traversal overhead we leverage their individual advantages. We demonstrate that hybrid data structures adapt well to a large range of data sets. They are especially superior to other sparse data structures for data sets that locally vary in sparsity. Possible optimization criteria are memory, performance and a combination thereof. Through just-in-time (JIT) compilation, JiTTree reduces the traversal overhead of the resulting optimal data structure. As a result, our hybrid volume data structure enables efficient computations on the GPU, while being superior in terms of memory usage when compared to non-hybrid data structures.

JiTTree: A Just-in-Time Compiled Sparse GPU Volume Data Structure

KAUST Repository

Labschutz, Matthias; Bruckner, Stefan; Groller, M. Eduard; Hadwiger, Markus; Rautek, Peter

2015-01-01

Sparse volume data structures enable the efficient representation of large but sparse volumes in GPU memory for computation and visualization. However, the choice of a specific data structure for a given data set depends on several factors, such as the memory budget, the sparsity of the data, and data access patterns. In general, there is no single optimal sparse data structure, but a set of several candidates with individual strengths and drawbacks. One solution to this problem are hybrid data structures which locally adapt themselves to the sparsity. However, they typically suffer from increased traversal overhead which limits their utility in many applications. This paper presents JiTTree, a novel sparse hybrid volume data structure that uses just-in-time compilation to overcome these problems. By combining multiple sparse data structures and reducing traversal overhead we leverage their individual advantages. We demonstrate that hybrid data structures adapt well to a large range of data sets. They are especially superior to other sparse data structures for data sets that locally vary in sparsity. Possible optimization criteria are memory, performance and a combination thereof. Through just-in-time (JIT) compilation, JiTTree reduces the traversal overhead of the resulting optimal data structure. As a result, our hybrid volume data structure enables efficient computations on the GPU, while being superior in terms of memory usage when compared to non-hybrid data structures.

JiTTree: A Just-in-Time Compiled Sparse GPU Volume Data Structure.

Science.gov (United States)

Labschütz, Matthias; Bruckner, Stefan; Gröller, M Eduard; Hadwiger, Markus; Rautek, Peter

2016-01-01

Sparse volume data structures enable the efficient representation of large but sparse volumes in GPU memory for computation and visualization. However, the choice of a specific data structure for a given data set depends on several factors, such as the memory budget, the sparsity of the data, and data access patterns. In general, there is no single optimal sparse data structure, but a set of several candidates with individual strengths and drawbacks. One solution to this problem are hybrid data structures which locally adapt themselves to the sparsity. However, they typically suffer from increased traversal overhead which limits their utility in many applications. This paper presents JiTTree, a novel sparse hybrid volume data structure that uses just-in-time compilation to overcome these problems. By combining multiple sparse data structures and reducing traversal overhead we leverage their individual advantages. We demonstrate that hybrid data structures adapt well to a large range of data sets. They are especially superior to other sparse data structures for data sets that locally vary in sparsity. Possible optimization criteria are memory, performance and a combination thereof. Through just-in-time (JIT) compilation, JiTTree reduces the traversal overhead of the resulting optimal data structure. As a result, our hybrid volume data structure enables efficient computations on the GPU, while being superior in terms of memory usage when compared to non-hybrid data structures.

Performance of high-rate gravel-packed oil wells

Energy Technology Data Exchange (ETDEWEB)

Unneland, Trond

2001-05-01

Improved methods for the prediction, evaluation, and monitoring of performance in high-rate cased-hole gravel-packed oil wells are presented in this thesis. The ability to predict well performance prior to the gravel-pack operations, evaluate the results after the operation, and monitor well performance over time has been improved. This lifetime approach to performance analysis of gravel-packed oil wells contributes to increase oil production and field profitability. First, analytical models available for prediction of performance in gravel-packed oil wells are reviewed, with particular emphasis on high-velocity flow effects. From the analysis of field data from three North Sea oil fields, improved and calibrated cased-hole gravel-pack performance prediction models are presented. The recommended model is based on serial flow through formation sand and gravel in the perforation tunnels. In addition, new correlations for high-velocity flow in high-rate gravel-packed oil wells are introduced. Combined, this improves the performance prediction for gravel-packed oil wells, and specific areas can be targeted for optimized well design. Next, limitations in the current methods and alternative methods for evaluation and comparison of well performance are presented. The most widely used parameter, the skin factor, remains a convenient and important parameter. However, using the skin concept in direct comparisons between wells with different reservoir properties may result in misleading or even invalid conclusions. A discussion of the parameters affecting the skin value, with a clarification of limitations, is included. A methodology for evaluation and comparison of gravel-packed well performance is presented, and this includes the use of results from production logs and the use of effective perforation tunnel permeability as a parameter. This contributes to optimized operational procedures from well to well and from field to field. Finally, the data sources available for

Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model

Directory of Open Access Journals (Sweden)

Qi Yuan(Alan

2010-01-01

Full Text Available Abstract The problem of uncovering transcriptional regulation by transcription factors (TFs based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes. The model admits prior knowledge from existing database regarding TF-regulated target genes based on a sparse prior and through a developed Gibbs sampling algorithm, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the Gibbs sampling algorithm were evaluated on the simulated systems, and results demonstrated the validity and effectiveness of the proposed approach. The proposed model was then applied to the breast cancer microarray data of patients with Estrogen Receptor positive ( status and Estrogen Receptor negative ( status, respectively.

From porous gold nanocups to porous nanospheres and solid particles - A new synthetic approach

KAUST Repository

Ihsan, Ayesha

2015-05-01

We report a versatile approach for the synthesis of porous gold nanocups, porous gold nanospheres and solid gold nanoparticles. Gold nanocups are formed by the slow reduction of gold salt (HAuCl4{dot operator}3H2O) using aminoantipyrene (AAP) as a reducing agent. Adding polyvinylpyrrolidone (PVP) to the gold salt followed by reduction with AAP resulted in the formation of porous gold nanospheres. Microwave irradiation of both of these porous gold particles resulted in the formation of slightly smaller but solid gold particles. All these nanoparticles are thoroughly characterized by UV-visible spectroscopy, scanning electron microscopy (SEM), high resolution transmission electron microscopy (HR-TEM) and bright-field tomography. Due to the larger size, porous nature, low density and higher surface area, these nanomaterials may have interesting applications in catalysis, drug delivery, phototherapy and sensing.

From porous gold nanocups to porous nanospheres and solid particles - A new synthetic approach

KAUST Repository

Ihsan, Ayesha; Katsiev, Habib; AlYami, Noktan; Anjum, Dalaver H.; Khan, Waheed S.; Hussain, Irshad

2015-01-01

We report a versatile approach for the synthesis of porous gold nanocups, porous gold nanospheres and solid gold nanoparticles. Gold nanocups are formed by the slow reduction of gold salt (HAuCl4{dot operator}3H2O) using aminoantipyrene (AAP) as a reducing agent. Adding polyvinylpyrrolidone (PVP) to the gold salt followed by reduction with AAP resulted in the formation of porous gold nanospheres. Microwave irradiation of both of these porous gold particles resulted in the formation of slightly smaller but solid gold particles. All these nanoparticles are thoroughly characterized by UV-visible spectroscopy, scanning electron microscopy (SEM), high resolution transmission electron microscopy (HR-TEM) and bright-field tomography. Due to the larger size, porous nature, low density and higher surface area, these nanomaterials may have interesting applications in catalysis, drug delivery, phototherapy and sensing.

Stochastic porous media equations

CERN Document Server

Barbu, Viorel; Röckner, Michael

2016-01-01

Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup. Stochastic perturbations of the porous media equation have reviously been considered by physicists, but rigorous mathematical existence results have only recently been found. The porous media equation models a number of different physical phenomena, including the flow of an ideal gas and the diffusion of a compressible fluid through porous media, and also thermal propagation in plasma and plasma radiation. Another important application is to a model of the standard self-organized criticality process, called the "sand-pile model" or the "Bak-Tang-Wiesenfeld model". The book will be of interest to PhD students and researchers in mathematics, physics and biology.

Random close packing in protein cores

OpenAIRE

Gaines, Jennifer C.; Smith, W. Wendell; Regan, Lynne; O'Hern, Corey S.

2015-01-01

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions $\\phi \\approx 0.75$, a value that is similar to close packing equal-sized spheres. A limitation of these analyses was the use of `extended atom' models, rather than the more physically accurate `explicit hydrogen' model. The validity of using the explicit hydrogen model is proved by its ability to predict the side chain dihedral angle distributions obs...

Packing Density Approach for Sustainable Development of Concrete

Directory of Open Access Journals (Sweden)

Sudarshan Dattatraya KORE

2017-12-01

Full Text Available This paper deals with the details of optimized mix design for normal strength concrete using particle packing density method. Also the concrete mixes were designed as per BIS: 10262-2009. Different water-cement ratios were used and kept same in both design methods. An attempt has been made to obtain sustainable and cost effective concrete product by use of particle packing density method. The parameters such as workability, compressive strength, cost analysis and carbon di oxide emission were discussed. The results of the study showed that, the compressive strength of the concrete produced by packing density method are closer to that of design compressive strength of BIS code method. By adopting the packing density method for design of concrete mixes, resulted in 11% cost saving with 12% reduction in carbon di oxide emission.

Amine Functionalized Porous Network

KAUST Repository

Eddaoudi, Mohamed; Guillerm, Vincent; Weselinski, Lukasz Jan; Alkordi, Mohamed H.; Mohideen, Mohamed Infas Haja; Belmabkhout, Youssef

2015-01-01

Amine groups can be introduced in porous materials by a direct (one pot) or post-synthetic modification (PSM) process on aldehyde groups, and the resulting porous materials have increased gas affinity.

Amine Functionalized Porous Network

KAUST Repository

Eddaoudi, Mohamed

2015-05-28

Amine groups can be introduced in porous materials by a direct (one pot) or post-synthetic modification (PSM) process on aldehyde groups, and the resulting porous materials have increased gas affinity.

Magnetic Resonance Super-resolution Imaging Measurement with Dictionary-optimized Sparse Learning

Directory of Open Access Journals (Sweden)

Li Jun-Bao

2017-06-01

Full Text Available Magnetic Resonance Super-resolution Imaging Measurement (MRIM is an effective way of measuring materials. MRIM has wide applications in physics, chemistry, biology, geology, medical and material science, especially in medical diagnosis. It is feasible to improve the resolution of MR imaging through increasing radiation intensity, but the high radiation intensity and the longtime of magnetic field harm the human body. Thus, in the practical applications the resolution of hardware imaging reaches the limitation of resolution. Software-based super-resolution technology is effective to improve the resolution of image. This work proposes a framework of dictionary-optimized sparse learning based MR super-resolution method. The framework is to solve the problem of sample selection for dictionary learning of sparse reconstruction. The textural complexity-based image quality representation is proposed to choose the optimal samples for dictionary learning. Comprehensive experiments show that the dictionary-optimized sparse learning improves the performance of sparse representation.

Compact data structure and scalable algorithms for the sparse grid technique

KAUST Repository

Murarasu, Alin

2011-01-01

The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data structures, thus being far from well-suited for GPUs. In this paper, we describe optimizations that enable us to implement compression and decompression, the crucial sparse grid algorithms for our application, on Nvidia GPUs. The main idea consists of a bijective mapping between the set of points in a multi-dimensional sparse grid and a set of consecutive natural numbers. The resulting data structure consumes a minimum amount of memory. For a 10-dimensional sparse grid with approximately 127 million points, it consumes up to 30 times less memory than trees or hash tables which are typically used. Compared to a sequential CPU implementation, the speedups achieved on GPU are up to 17 for compression and up to 70 for decompression, respectively. We show that the optimizations are also applicable to multicore CPUs. Copyright © 2011 ACM.

Multisnapshot Sparse Bayesian Learning for DOA

DEFF Research Database (Denmark)

Gerstoft, Peter; Mecklenbrauker, Christoph F.; Xenaki, Angeliki

2016-01-01

The directions of arrival (DOA) of plane waves are estimated from multisnapshot sensor array data using sparse Bayesian learning (SBL). The prior for the source amplitudes is assumed independent zero-mean complex Gaussian distributed with hyperparameters, the unknown variances (i.e., the source...

Continuous speech recognition with sparse coding

CSIR Research Space (South Africa)

Smit, WJ

2009-04-01

Full Text Available generative model. The spike train is classified by making use of a spike train model and dynamic programming. It is computationally expensive to find a sparse code. We use an iterative subset selection algorithm with quadratic programming for this process...

Porous silicon carbide (SIC) semiconductor device

Science.gov (United States)

Shor, Joseph S. (Inventor); Kurtz, Anthony D. (Inventor)

1996-01-01

Porous silicon carbide is fabricated according to techniques which result in a significant portion of nanocrystallites within the material in a sub 10 nanometer regime. There is described techniques for passivating porous silicon carbide which result in the fabrication of optoelectronic devices which exhibit brighter blue luminescence and exhibit improved qualities. Based on certain of the techniques described porous silicon carbide is used as a sacrificial layer for the patterning of silicon carbide. Porous silicon carbide is then removed from the bulk substrate by oxidation and other methods. The techniques described employ a two-step process which is used to pattern bulk silicon carbide where selected areas of the wafer are then made porous and then the porous layer is subsequently removed. The process to form porous silicon carbide exhibits dopant selectivity and a two-step etching procedure is implemented for silicon carbide multilayers.

A density functional for sparse matter

DEFF Research Database (Denmark)

Langreth, D.C.; Lundqvist, Bengt; Chakarova-Kack, S.D.

2009-01-01

forces in molecules, to adsorbed molecules, like benzene, naphthalene, phenol and adenine on graphite, alumina and metals, to polymer and carbon nanotube (CNT) crystals, and hydrogen storage in graphite and metal-organic frameworks (MOFs), and to the structure of DNA and of DNA with intercalators......Sparse matter is abundant and has both strong local bonds and weak nonbonding forces, in particular nonlocal van der Waals (vdW) forces between atoms separated by empty space. It encompasses a broad spectrum of systems, like soft matter, adsorption systems and biostructures. Density-functional...... theory (DFT), long since proven successful for dense matter, seems now to have come to a point, where useful extensions to sparse matter are available. In particular, a functional form, vdW-DF (Dion et al 2004 Phys. Rev. Lett. 92 246401; Thonhauser et al 2007 Phys. Rev. B 76 125112), has been proposed...

Sparse learning of stochastic dynamical equations

Science.gov (United States)

Boninsegna, Lorenzo; Nüske, Feliks; Clementi, Cecilia

2018-06-01

With the rapid increase of available data for complex systems, there is great interest in the extraction of physically relevant information from massive datasets. Recently, a framework called Sparse Identification of Nonlinear Dynamics (SINDy) has been introduced to identify the governing equations of dynamical systems from simulation data. In this study, we extend SINDy to stochastic dynamical systems which are frequently used to model biophysical processes. We prove the asymptotic correctness of stochastic SINDy in the infinite data limit, both in the original and projected variables. We discuss algorithms to solve the sparse regression problem arising from the practical implementation of SINDy and show that cross validation is an essential tool to determine the right level of sparsity. We demonstrate the proposed methodology on two test systems, namely, the diffusion in a one-dimensional potential and the projected dynamics of a two-dimensional diffusion process.

Packing Nonspherical Particles: All Shapes Are Not Created Equal

Science.gov (United States)

Torquato, Salvatore

2012-02-01

Over the past decade there has been increasing interest in the effects of particle shape on the characteristics of dense particle packings, since deviations from sphericity can lead to more realistic models of granular media, nanostructured materials, and tissue architecture. It is clear the that the broken rotational symmetry of a nonspherical particle is a crucial aspect in determining its resulting packing characteristics, but given the infinite variety of possible shapes (ellipsoids, superballs, regular and irregular polyhedra, etc.) it is desirable to formulate packing organizing principles based the particle shape. Such principles are beginning to be elucidated; see Refs. 1 and 2 and references therein. Depending upon whether the particle has central symmetry, inequivalent principle axes, and smooth or flat surfaces, we can describe the nature of its densest packing (which is typically periodic) as well as its disordered jammed states (which may or may not be isostatic). Changing the shape of a particle can dramatically alter its packing attributes. This tunability capability via particle shape could be used to tailor many-particle systems (e.g., colloids and granular media) to have designed crystal, liquid and glassy states. [4pt] [1] S. Torquato and F. H. Stillinger, ``Jammed Hard-Particle Packings: From Kepler to Bernal and Beyond," Rev. Modern Phys. 82, 2633 (2010). [0pt] [2] Y. Jiao and S. Torquato, Communication: ``A Packing of Truncated Tetrahedra That Nearly Fills All of Space and its Melting Properties," J. Chem. Phys. 135, 151101 (2011).

Porous ceramics out of oxides

International Nuclear Information System (INIS)

Bakunov, V.S.; Balkevich, V.L.; Vlasov, A.S.; Guzman, I.Ya.; Lukin, E.S.; Poluboyarinov, D.N.; Poliskij, R.Ya.

1977-01-01

A review is made of manufacturing procedures and properties of oxide ceramics intended for high-temperature thermal insulation and thermal protection applications. Presented are structural characteristics of porous oxide refractories and their properties. Strength and thermal conductivity was shown to depend upon porosity. Described is a procedure for manufacturing porous ceramic materials from aluminium oxide, zirconium dioxide, magnesium oxide, beryllium oxide. The thermal resistance of porous ceramics from BeO is considerably greater than that of other high-refractoriness oxides. Listed are areas of application for porous materials based on oxides

Selective formation of porous silicon

Science.gov (United States)

Fathauer, Robert W. (Inventor); Jones, Eric W. (Inventor)

1993-01-01

A pattern of porous silicon is produced in the surface of a silicon substrate by forming a pattern of crystal defects in said surface, preferably by applying an ion milling beam through openings in a photoresist layer to the surface, and then exposing said surface to a stain etchant, such as HF:HNO3:H2O. The defected crystal will preferentially etch to form a pattern of porous silicon. When the amorphous content of the porous silicon exceeds 70 percent, the porous silicon pattern emits visible light at room temperature.

A novel method to design sparse linear arrays for ultrasonic phased array.

Science.gov (United States)

Yang, Ping; Chen, Bin; Shi, Ke-Ren

2006-12-22

In ultrasonic phased array testing, a sparse array can increase the resolution by enlarging the aperture without adding system complexity. Designing a sparse array involves choosing the best or a better configuration from a large number of candidate arrays. We firstly designed sparse arrays by using a genetic algorithm, but found that the arrays have poor performance and poor consistency. So, a method based on the Minimum Redundancy Linear Array was then adopted. Some elements are determined by the minimum-redundancy array firstly in order to ensure spatial resolution and then a genetic algorithm is used to optimize the remaining elements. Sparse arrays designed by this method have much better performance and consistency compared to the arrays designed only by a genetic algorithm. Both simulation and experiment confirm the effectiveness.

Multiple instance learning tracking method with local sparse representation

KAUST Repository

Xie, Chengjun

2013-10-01

When objects undergo large pose change, illumination variation or partial occlusion, most existed visual tracking algorithms tend to drift away from targets and even fail in tracking them. To address this issue, in this study, the authors propose an online algorithm by combining multiple instance learning (MIL) and local sparse representation for tracking an object in a video system. The key idea in our method is to model the appearance of an object by local sparse codes that can be formed as training data for the MIL framework. First, local image patches of a target object are represented as sparse codes with an overcomplete dictionary, where the adaptive representation can be helpful in overcoming partial occlusion in object tracking. Then MIL learns the sparse codes by a classifier to discriminate the target from the background. Finally, results from the trained classifier are input into a particle filter framework to sequentially estimate the target state over time in visual tracking. In addition, to decrease the visual drift because of the accumulative errors when updating the dictionary and classifier, a two-step object tracking method combining a static MIL classifier with a dynamical MIL classifier is proposed. Experiments on some publicly available benchmarks of video sequences show that our proposed tracker is more robust and effective than others. © The Institution of Engineering and Technology 2013.

The benefits of hypopharyngeal packing in nasal surgery: a pilot study.

LENUS (Irish Health Repository)

Fennessy, B G

2012-02-01

BACKGROUND: Hypopharyngeal packs are used in nasal surgery to reduce the risk of aspiration and postoperative nausea and vomiting. Side effects associated with their use range from throat pain to retained packs postoperatively. AIM: To evaluate, as a pilot study, postoperative nausea\\/vomiting and throat pain scores for patients undergoing nasal surgery in whom a wet or dry hypopharyngeal pack was placed compared with patients who received no packing. METHODS: A randomized, double-blind prospective trial in a general ENT unit. RESULTS: The study failed to show a statistically significant difference between the three groups in terms of their postoperative nausea\\/vomiting and throat pain scores at 2 and 6 h postoperatively. This is the first study in which dry packs have been compared with wet and absent packs. CONCLUSION: Based on our findings, the authors recommend against placing hypopharyngeal packs for the purpose of preventing postoperative nausea and vomiting.

Properties of Ni and Ni–Fe nanowires electrochemically deposited into a porous alumina template

Directory of Open Access Journals (Sweden)

Alla I. Vorobjova

2016-11-01

Full Text Available The comparative analysis of the electrochemical deposition of Ni and Ni–Fe nanowires (NWs into ordered porous alumina templates is presented. The method developed allows for obtaining NWs of 50 ± 5 nm in diameter and 25 μm in length, i.e., with an aspect ratio of 500. XRD data demonstrate the polycrystalline nature of Ni and Ni–Fe in a face-centered cubic close-packed lattice. Both fabricated materials, Ni and Ni–Fe, have shown ferromagnetic properties. The specific magnetization value of Ni–Fe NWs in the alumina template is higher than that of the Ni sample and bulk Ni, also the Curie temperature of the Ni–Fe sample (790 K is higher than that of the Ni sample one or bulk Ni.

Sparse linear models: Variational approximate inference and Bayesian experimental design

International Nuclear Information System (INIS)

Seeger, Matthias W

2009-01-01

A wide range of problems such as signal reconstruction, denoising, source separation, feature selection, and graphical model search are addressed today by posterior maximization for linear models with sparsity-favouring prior distributions. The Bayesian posterior contains useful information far beyond its mode, which can be used to drive methods for sampling optimization (active learning), feature relevance ranking, or hyperparameter estimation, if only this representation of uncertainty can be approximated in a tractable manner. In this paper, we review recent results for variational sparse inference, and show that they share underlying computational primitives. We discuss how sampling optimization can be implemented as sequential Bayesian experimental design. While there has been tremendous recent activity to develop sparse estimation, little attendance has been given to sparse approximate inference. In this paper, we argue that many problems in practice, such as compressive sensing for real-world image reconstruction, are served much better by proper uncertainty approximations than by ever more aggressive sparse estimation algorithms. Moreover, since some variational inference methods have been given strong convex optimization characterizations recently, theoretical analysis may become possible, promising new insights into nonlinear experimental design.

Sparse linear models: Variational approximate inference and Bayesian experimental design

Energy Technology Data Exchange (ETDEWEB)

Seeger, Matthias W [Saarland University and Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbruecken (Germany)

2009-12-01

A wide range of problems such as signal reconstruction, denoising, source separation, feature selection, and graphical model search are addressed today by posterior maximization for linear models with sparsity-favouring prior distributions. The Bayesian posterior contains useful information far beyond its mode, which can be used to drive methods for sampling optimization (active learning), feature relevance ranking, or hyperparameter estimation, if only this representation of uncertainty can be approximated in a tractable manner. In this paper, we review recent results for variational sparse inference, and show that they share underlying computational primitives. We discuss how sampling optimization can be implemented as sequential Bayesian experimental design. While there has been tremendous recent activity to develop sparse estimation, little attendance has been given to sparse approximate inference. In this paper, we argue that many problems in practice, such as compressive sensing for real-world image reconstruction, are served much better by proper uncertainty approximations than by ever more aggressive sparse estimation algorithms. Moreover, since some variational inference methods have been given strong convex optimization characterizations recently, theoretical analysis may become possible, promising new insights into nonlinear experimental design.

Discriminative object tracking via sparse representation and online dictionary learning.

Science.gov (United States)

Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

2014-04-01

We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

Granular packings with moving side walls

International Nuclear Information System (INIS)

Landry, James W.; Grest, Gary Stephen

2004-01-01

The effects of movement of the side walls of a confined granular packing are studied by discrete element, molecular dynamics simulations. The dynamical evolution of the stress is studied as a function of wall movement both in the direction of gravity as well as opposite to it. For all wall velocities explored, the stress in the final state of the system after wall movement is fundamentally different from the original state obtained by pouring particles into the container and letting them settle under the influence of gravity. The original packing possesses a hydrostaticlike region at the top of the container which crosses over to a depth-independent stress. As the walls are moved in the direction opposite to gravity, the saturation stress first reaches a minimum value independent of the wall velocity, then increases to a steady-state value dependent on the wall velocity. After wall movement ceases and the packing reaches equilibrium, the stress profile fits the classic Janssen form for high wall velocities, while some deviations remain for low wall velocities. The wall movement greatly increases the number of particle-wall and particle-particle forces at the Coulomb criterion. Varying the wall velocity has only small effects on the particle structure of the final packing so long as the walls travel a similar distance.

Building Input Adaptive Parallel Applications: A Case Study of Sparse Grid Interpolation

KAUST Repository

Murarasu, Alin; Weidendorfer, Josef

2012-01-01

bring a substantial contribution to the speedup. By identifying common patterns in the input data, we propose new algorithms for sparse grid interpolation that accelerate the state-of-the-art non-specialized version. Sparse grid interpolation

7 CFR 906.340 - Container, pack, and container marking regulations.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Container, pack, and container marking regulations... AGRICULTURE ORANGES AND GRAPEFRUIT GROWN IN LOWER RIO GRANDE VALLEY IN TEXAS Container and Pack Requirements § 906.340 Container, pack, and container marking regulations. (a) No handler shall handle any variety of...

cellPACK: a virtual mesoscope to model and visualize structural systems biology.

Science.gov (United States)

Johnson, Graham T; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

2015-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

Jointly-check iterative decoding algorithm for quantum sparse graph codes

International Nuclear Information System (INIS)

Jun-Hu, Shao; Bao-Ming, Bai; Wei, Lin; Lin, Zhou

2010-01-01

For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with a standard belief-propagation (BP) algorithm. In this paper, we present a jointly-check iterative algorithm suitable for decoding quantum sparse graph codes efficiently. Numerical simulations show that this modified method outperforms the standard BP algorithm with an obvious performance improvement. (general)

Rotational image deblurring with sparse matrices

DEFF Research Database (Denmark)

Hansen, Per Christian; Nagy, James G.; Tigkos, Konstantinos

2014-01-01

We describe iterative deblurring algorithms that can handle blur caused by a rotation along an arbitrary axis (including the common case of pure rotation). Our algorithms use a sparse-matrix representation of the blurring operation, which allows us to easily handle several different boundary...

Porous Silicon Nanowires

Science.gov (United States)

Qu, Yongquan; Zhou, Hailong; Duan, Xiangfeng

2011-01-01

In this minreview, we summarize recent progress in the synthesis, properties and applications of a new type of one-dimensional nanostructures — single crystalline porous silicon nanowires. The growth of porous silicon nanowires starting from both p- and n-type Si wafers with a variety of dopant concentrations can be achieved through either one-step or two-step reactions. The mechanistic studies indicate the dopant concentration of Si wafers, oxidizer concentration, etching time and temperature can affect the morphology of the as-etched silicon nanowires. The porous silicon nanowires are both optically and electronically active and have been explored for potential applications in diverse areas including photocatalysis, lithium ion battery, gas sensor and drug delivery. PMID:21869999

Homometrism in close-packed structures

International Nuclear Information System (INIS)

Mardix, S.

1990-01-01

Homometric structures are non-congruent structures having identical X-ray intensity distributions. It has so far been assumed that such structures, while theoretically interesting, would not be realized in practice. Homometrism in close-packed structures is shown to be a realistic possibility. Some general rules applicable to homometric pairs are presented; it is shown that an infinite number of them can be derived from one-dimensional homometric pairs. An exhaustive search of close-packed structures with periods of up to 26 reveals that the smallest period of a homometric pair is 15 and that their number increases rapidly with the period. Homometrism in polytypic structures is further discussed. (orig.)

Avoidance of cigarette pack health warnings among regular cigarette smokers.

Science.gov (United States)

Maynard, Olivia M; Attwood, Angela; O'Brien, Laura; Brooks, Sabrina; Hedge, Craig; Leonards, Ute; Munafò, Marcus R

2014-03-01

Previous research with adults and adolescents indicates that plain cigarette packs increase visual attention to health warnings among non-smokers and non-regular smokers, but not among regular smokers. This may be because regular smokers: (1) are familiar with the health warnings, (2) preferentially attend to branding, or (3) actively avoid health warnings. We sought to distinguish between these explanations using eye-tracking technology. A convenience sample of 30 adult dependent smokers participated in an eye-tracking study. Participants viewed branded, plain and blank packs of cigarettes with familiar and unfamiliar health warnings. The number of fixations to health warnings and branding on the different pack types were recorded. Analysis of variance indicated that regular smokers were biased towards fixating the branding rather than the health warning on all three pack types. This bias was smaller, but still evident, for blank packs, where smokers preferentially attended the blank region over the health warnings. Time-course analysis showed that for branded and plain packs, attention was preferentially directed to the branding location for the entire 10s of the stimulus presentation, while for blank packs this occurred for the last 8s of the stimulus presentation. Familiarity with health warnings had no effect on eye gaze location. Smokers actively avoid cigarette pack health warnings, and this remains the case even in the absence of salient branding information. Smokers may have learned to divert their attention away from cigarette pack health warnings. These findings have implications for cigarette packaging and health warning policy. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Normalization for sparse encoding of odors by a wide-field interneuron.

Science.gov (United States)

Papadopoulou, Maria; Cassenaer, Stijn; Nowotny, Thomas; Laurent, Gilles

2011-05-06

Sparse coding presents practical advantages for sensory representations and memory storage. In the insect olfactory system, the representation of general odors is dense in the antennal lobes but sparse in the mushroom bodies, only one synapse downstream. In locusts, this transformation relies on the oscillatory structure of antennal lobe output, feed-forward inhibitory circuits, intrinsic properties of mushroom body neurons, and connectivity between antennal lobe and mushroom bodies. Here we show the existence of a normalizing negative-feedback loop within the mushroom body to maintain sparse output over a wide range of input conditions. This loop consists of an identifiable "giant" nonspiking inhibitory interneuron with ubiquitous connectivity and graded release properties.

The investigation of cooling tower packing in various arrangements

International Nuclear Information System (INIS)

Golshayshi, H.R.; Missenden, J.F.

1998-01-01

The effect of form with corrugated packing on heat transfer and pressure drop characteristics in atmospheric cooling towers has been studied experimentally. The results showed that the heat transfer coefficient decreased with increase in packing pitch and increase in the ratio of rib pitch to rib height. Friction factors were expressed by a dimensional equation which included pitch and distance between the packings, for both smooth and rough surface. From these results, the relationship between packing heat transfer coefficient and pressure drop was deduced. The correlations were verified with additional experimental data taken with 1.1,P/D p /e 5 . This provides a useful semi experimental relation, in the area generally lacking in design and performance data. (author)

Integrality gap analysis for bin packing games

NARCIS (Netherlands)

Kern, Walter; Qui, X.

A cooperative bin packing game is an $N$-person game, where the player set $N$ consists of $k$ bins of capacity 1 each and $n$ items of sizes $a_1,\\dots,a_n$. The value $v(S)$ of a coalition $S$ of players is defined to be the maximum total size of items in $S$ that can be packed into the bins of

Sparse Representation Denoising for Radar High Resolution Range Profiling

Directory of Open Access Journals (Sweden)

Min Li

2014-01-01

Full Text Available Radar high resolution range profile has attracted considerable attention in radar automatic target recognition. In practice, radar return is usually contaminated by noise, which results in profile distortion and recognition performance degradation. To deal with this problem, in this paper, a novel denoising method based on sparse representation is proposed to remove the Gaussian white additive noise. The return is sparsely described in the Fourier redundant dictionary and the denoising problem is described as a sparse representation model. Noise level of the return, which is crucial to the denoising performance but often unknown, is estimated by performing subspace method on the sliding subsequence correlation matrix. Sliding window process enables noise level estimation using only one observation sequence, not only guaranteeing estimation efficiency but also avoiding the influence of profile time-shift sensitivity. Experimental results show that the proposed method can effectively improve the signal-to-noise ratio of the return, leading to a high-quality profile.

Tracer transfer in consolidated porous medium and fractured porous medium: experimentations and modelling

International Nuclear Information System (INIS)

Dalla Costa, C.

2007-07-01

We try to identify and model physical and chemical mechanisms governing the water flow and the solute transport in fractured consolidated porous medium. An original experimental device was built. The 'cube' consists of an idealized fractured medium reproduced by piling up consolidated porous cubes of 5 cm edge. Meanwhile, columns of the homogeneous consolidated porous medium are studied. The same anionic tracing technique is used in both cases. Using a system analysis approach, we inject concentration pulses in the device to obtain breakthrough curves. After identifying the mass balance and the residence time, we fit the CD and the MIM models to the experimental data. The MIM model is able to reproduce experimental curves of the homogeneous consolidated porous medium better than the CD model. The mobile water fraction is in accordance with the porous medium geometry. The study of the flow rate influence highlights an interference dispersion regime. It was not possible to highlight the observation length influence in this case. On the contrary, we highlight the effect of the observation scale on the fractured and porous medium, comparing the results obtained on a small 'cube' and a big 'cube'. The CD model is not satisfactory in this case. Even if the MIM model can fit the experimental breakthrough curves, it was not possible to obtain unique parameters for the set of experiments. (author)

The Real-Valued Sparse Direction of Arrival (DOA Estimation Based on the Khatri-Rao Product

Directory of Open Access Journals (Sweden)

Tao Chen

2016-05-01

Full Text Available There is a problem that complex operation which leads to a heavy calculation burden is required when the direction of arrival (DOA of a sparse signal is estimated by using the array covariance matrix. The solution of the multiple measurement vectors (MMV model is difficult. In this paper, a real-valued sparse DOA estimation algorithm based on the Khatri-Rao (KR product called the L1-RVSKR is proposed. The proposed algorithm is based on the sparse representation of the array covariance matrix. The array covariance matrix is transformed to a real-valued matrix via a unitary transformation so that a real-valued sparse model is achieved. The real-valued sparse model is vectorized for transforming to a single measurement vector (SMV model, and a new virtual overcomplete dictionary is constructed according to the KR product’s property. Finally, the sparse DOA estimation is solved by utilizing the idea of a sparse representation of array covariance vectors (SRACV. The simulation results demonstrate the superior performance and the low computational complexity of the proposed algorithm.

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.

Porous metal for orthopedics implants

OpenAIRE

Matassi, Fabrizio; Botti, Alessandra; Sirleo, Luigi; Carulli, Christian; Innocenti, Massimo

2013-01-01

Porous metal has been introduced to obtain biological fixation and improve longevity of orthopedic implants. The new generation of porous metal has intriguing characteristics that allows bone healing and high osteointegration of the metallic implants. This article gives an overview about biomaterials properties of the contemporary class of highly porous metals and about the clinical use in orthopaedic surgery.