Energy Technology Data Exchange (ETDEWEB)
Pazanin, Igor [Zagreb Univ. (Croatia). Dept. of Mathematics; Siddheshwar, Pradeep G. [Bangalore Univ., Bengaluru (India). Dept. of Mathematics
2017-06-01
In this article we investigate the fluid flow through a thin fracture modelled as a fluid-saturated porous medium. We assume that the fracture has constrictions and that the flow is governed by the prescribed pressure drop between the edges of the fracture. The problem is described by the Darcy-Lapwood-Brinkman model acknowledging the Brinkman extension of the Darcy law as well as the flow inertia. Using asymptotic analysis with respect to the thickness of the fracture, we derive the explicit higher-order approximation for the velocity distribution. We make an error analysis to comment on the order of accuracy of the method used and also to provide rigorous justification for the model.
Diffusion and reaction within porous packing media: a phenomenological model.
Jones, W L; Dockery, J D; Vogel, C R; Sturman, P J
1993-04-25
A phenomenological model has been developed to describe biomass distribution and substrate depletion in porous diatomaceous earth (DE) pellets colonized by Pseudomonas aeruginosa. The essential features of the model are diffusion, attachment and detachment to/from pore walls of the biomass, diffusion of substrate within the pellet, and external mass transfer of both substrate and biomass in the bulk fluid of a packed bed containing the pellets. A bench-scale reactor filled with DE pellets was inoculated with P. aeruginosa and operated in plug flow without recycle using a feed containing glucose as the limiting nutrient. Steady-state effluent glucose concentrations were measured at various residence times, and biomass distribution within the pellet was measured at the lowest residence time. In the model, microorganism/substrate kinetics and mass transfer characteristics were predicted from the literature. Only the attachment and detachment parameters were treated as unknowns, and were determined by fitting biomass distribution data within the pellets to the mathematical model. The rate-limiting step in substrate conversion was determined to be internal mass transfer resistance; external mass transfer resistance and microbial kinetic limitations were found to be nearly negligible. Only the outer 5% of the pellets contributed to substrate conversion.
Boiling phenomenon and heat transfer in bead-packed porous structure
International Nuclear Information System (INIS)
Zhang Xiaojie; ZHu Yanlei; Bai Bofeng; Yan Xiao; Xiao Zejun
2009-01-01
A visual study on pool boiling behavior and phase distribution was conducted on the porous structures made of staggered glass beads at atmospheric pressure. The bead-packed structure was heated on the bottom. The investigations were carried out respectively at different glass bead diameters which were 4 mm, 6 mm and 8 mm. The results show that during subcooled boiling, small isolated bubbles are formed on the heated surface and combine into main-bubbles, the dispersion frequency of the main-bubbles is low and the small bubbles scatter in the bead-packed porous structures. At the initial stage of saturated boiling, the bubble growth rate, the volume of main-bubbles and the range of continuous vapor phase increase. The dispersion frequency of main-bubbles increases with the increasing of heat flux. During film boiling, the heated surface is absolutely covered with vapor film and the porous structure is full of liquid. The larger the diameter of beads is, the higher heat flux is needed for the same phenomenon, and the higher maximum value of heat transfer coefficient will be. During the whole saturated boiling, and the heat transfer enhanced firstly and then weakened. Being opposite to that of the diameters of 4 mm and 8 mm, the heat transfer coefficient in the 6 mm-bead-packed porous structure decreases with the increasing of the heat flux. (authors)
On the modeling of gas flow through porous compression packings used in valve stuffing-boxes
International Nuclear Information System (INIS)
Kazeminia, Mehdi; Bouzid, Abdel-Hakim
2015-01-01
Predicting leak rate through porous compression packing rings is a significant challenge for the design of packed stuffing boxes. Although few studies have been conducted to predict the leak rate through these seals, there is no comprehensive standard procedure to be used to design compression packings for a maximum tolerated leak for a given application. With the ubiquitous use of the yarned packing rings and the strict regulations on fugitive emissions and the new environment protection laws quantification of leak rate through yarned stuffing boxes becomes more than necessary and a tightness criteria based design procedure must be developed. In this study a new approach to predict leak rate through compression packing rings has been developed. It is based on Darcy's model to which Klinkenberg slip effect is incorporated. The predicted leak rates are compared to those measured experimentally using two different graphite-based packing rings subjected to different compression levels and pressures. A good agreement is found between the predicted and the measured leak rates which illustrates the validity of the developed model. (author)
Directory of Open Access Journals (Sweden)
Hardiman M. Y
2008-01-01
Full Text Available is paper presents the comparison of engineering properties between single and double layer porous asphalt (SLPA and DLPA made of packing gradation. Three nominal maximum aggregate sizes (NMAS were tested each made up of 10, 14, and 20 mm for SLPA. While for the DLPA with 30, 20, and 15 mm top layer are made of 10 and 14 mm NMAS, with a base layer of 20 mm NMAS. Total thickness of all mixes is 70 mm. Binders used are 60/70 penetration base bitumen and polymer binder styrene-butadiene-styrene (SBS. The result shows that the properties of SLPA mix namely permeability and resistance to abrasion loss decreases when the NMAS in SLPA decreases. The abrasion loss of DLPA mixes increases when the porous asphalt top layer thickness decreases, while drainage time value decreases. However, SLPA with 20 mm NMAS exhibits higher abrasion loss compared to all DLPA mixes.
Effect of particle size distribution on permeability in the randomly packed porous media
Markicevic, Bojan
2017-11-01
An answer of how porous medium heterogeneity influences the medium permeability is still inconclusive, where both increase and decrease in the permeability value are reported. A numerical procedure is used to generate a randomly packed porous material consisting of spherical particles. Six different particle size distributions are used including mono-, bi- and three-disperse particles, as well as uniform, normal and log-normal particle size distribution with the maximum to minimum particle size ratio ranging from three to eight for different distributions. In all six cases, the average particle size is kept the same. For all media generated, the stochastic homogeneity is checked from distribution of three coordinates of particle centers, where uniform distribution of x-, y- and z- positions is found. The medium surface area remains essentially constant except for bi-modal distribution in which medium area decreases, while no changes in the porosity are observed (around 0.36). The fluid flow is solved in such domain, and after checking for the pressure axial linearity, the permeability is calculated from the Darcy law. The permeability comparison reveals that the permeability of the mono-disperse medium is smallest, and the permeability of all poly-disperse samples is less than ten percent higher. For bi-modal particles, the permeability is for a quarter higher compared to the other media which can be explained by volumetric contribution of larger particles and larger passages for fluid flow to take place.
Supercooling and cold energy storage characteristics of nano-media in ball-packed porous structures
Directory of Open Access Journals (Sweden)
Zhao Qunzhi
2015-04-01
Full Text Available The presented experiments aimed to study the supercooling and cold-energy storage characteristics of nanofluids and water-based nano-media in ball-packed porous structures (BPS. Titanium dioxide nanoparticles (TiO2 NPs measuring 20nm and 80nm were used as additives and sodium dodecyl benzene sulphonate (SDBS was used as anionic surfactant. The experiments used different concentrations of nanofluid, distilled with BPS of different spherical diameter and different concentrations of nano-media, and were conducted 20 times. Experimental results of supercooling were analysed by statistical methods. Results show that the average and peak supercooling degrees of nanofluids and nano-media in BPS are lower than those of distilled water. For the distilled water in BPS, the supercooling degree decreases on the whole with the decrease of the ball diameter. With the same spherical diameter (8mm of BPS, the supercooling degree of TiO2 NPs measuring 20nm is lower than the supercooling degree of distilled water in BPS. Step-cooling experiments of different concentrations of nanofluids and nano-media in BPS were also conducted. Results showed that phase transition time is reduced because of the presence of TiO2 NPs. The BPS substrate and the NPs enhance the heat transfer. Distilled water with a porous solid base and nanoparticles means the amount of cold-energy storage increases and the supercooling degree and the total time are greatly reduced. The phase transition time of distilled water is about 3.5 times that of nano-media in BPS.
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)
On the Effective Thermal Conductivity of Porous Packed Beds with Uniform Spherical Particles
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.
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.
Min, Yi; Jiang, Bo; Wu, Ci; Xia, Simin; Zhang, Xiaodan; Liang, Zhen; Zhang, Lihua; Zhang, Yukui
2014-08-22
In this work, 1.9 μm reversed-phase packing materials with superficially porous structure were prepared to achieve the rapid and high efficient separation of peptides and proteins. The silica particles were synthesized via three steps, nonporous silica particle preparation by a modified seeded growth method, mesoporous shell formation by a one pot templated dissolution and redeposition strategy, and pore size expansion via acid-refluxing. By such a method, 1.9 μm superficially porous materials with 0.18 μm shell thickness and tailored pore diameter (10 nm, 15 nm) were obtained. After pore enlargement, the formerly dense arrays of mesoporous structure changed, the radially oriented pores dominated the superficially porous structure. The chromatographic performance of such particles was investigated after C18 derivatization. For packing materials with 1.9 μm diameter and 10 nm pore size, the column efficiency could reach 211,300 plates per m for naphthalene. To achieve the high resolution separation of peptides and proteins, particles with pore diameter of 15 nm were tailored, by which the baseline separation of 5 peptides and 5 intact proteins could be respectively achieved within 1 min, demonstrating the superiority in the high efficiency and high throughput analysis of biomolecules. Furthermore, BSA digests were well separated with peak capacity of 120 in 30 min on a 15 cm-long column. Finally, we compared our columns with a 1.7 μm Kinetex C18 column under the same conditions, our particles with 10nm pore size demonstrated similar performance for separation of the large intact proteins. Moreover, the particles with 15 nm pore size showed more symmetrical peaks for the separation of large proteins (BSA, OVA and IgG) and provided rapid separation of protein extracts from Escherichia coli in 5 min. All these results indicated that the synthesized 1.9 μm superficially porous silica packing materials would be promising in the ultra-fast and high
Gritti, Fabrice; Omamogho, Jesse; Guiochon, Georges
2011-10-07
The recent successful breakthrough of sub-3 μm shell particles in HPLC has triggered considerable research efforts toward the design of new brands of core-shell particles. We investigated the mass transfer mechanism of a few analytes in narrow-bore columns packed with prototype 1.7 μm shell particles, made of 1.0, 1.2, and 1.4 μm solid nonporous cores surrounded by porous shells 350, 250, and 150 nm thick, respectively. Three probe solutes, uracil, naphthalene, and insulin, were chosen to assess the kinetic performance of these columns. Inverse size exclusion chromatography, peak parking experiments, and the numerical integration of the experimental peak profiles were carried out in order to measure the external, internal, and total column porosities, the true bulk diffusion coefficients of these analytes, the height equivalent to a theoretical plate, the longitudinal diffusion term, and the trans-particle mass transfer resistance term. The residual eddy diffusion term was measured by difference. The results show the existence of important trans-column velocity biases (7%) possibly due to the presence of particle multiplets in the slurry mixture used during the packing process. Our results illustrates some of the difficulties encountered by scientists preparing and packing shell particles into narrow-bore columns. Copyright © 2011 Elsevier B.V. All rights reserved.
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.
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.
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
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.
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.
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.
Sparse structure regularized ranking
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
Mutha, Heena K; Lu, Yuan; Stein, Itai; Cho, H Jeremy; Suss, Matthew; Laoui, Tahar; Thompson, Carl; Wardle, Brian; Wang, Evelyn
2016-12-13
Vertically aligned one-dimensional nanostructure arrays are promising in many applications such as electrochemical systems, solar cells, and electronics, taking advantage of high surface area per unit volume, nanometer length scale packing, and alignment leading to high conductivity. However, many devices need to optimize arrays for device performance by selecting an appropriate morphology. Developing a simple, non-invasive tool for understanding the role of pore volume distribution and interspacing would aid in the optimization of nanostructure morphologies in electrodes. In this work, we combined electrochemical impedance spectroscopy (EIS) with capacitance measurements and porous electrode theory to conduct in situ porosimetry of vertically-aligned carbon nanotubes (VA-CNTs) non-destructively. We utilized the EIS measurements with a pore size distribution model to quantify the average and dispersion of inter-CNT spacing (Γ), stochastically, in carpets that were mechanically densified from 1.7 × 1010 tubes/cm2 to 4.5 × 1011 tubes/cm2. Our analysis predicts that the inter-CNT spacing ranges from over 100 ± 50 nm in sparse carpets to sub 10 ± 5 nm in packed carpets. Our results suggest that waviness of CNTs leads to variations in the inter-CNT spacing, which can be significant in sparse carpets. This methodology can be used to predict the performance of many nanostructured devices, including supercapacitors, batteries, solar cells, and semiconductor electronics. Copyright 2016 IOP Publishing Ltd.
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.
Sparse structure regularized ranking
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.
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
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.
Sparse distributed memory overview
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.
Efficient convolutional sparse coding
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.
Sparse approximation with bases
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...
Supervised Convolutional Sparse Coding
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.
Supervised Transfer Sparse Coding
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.
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.
Mass transfer controlled reactions in packed beds at low Reynolds numbers
Energy Technology Data Exchange (ETDEWEB)
Fedkiw, P.S.
1978-12-01
The a priori prediction and correlation of mass-transfer rates in transport limited, packed-bed reactors at low Reynolds numbers is examined. The solutions to the governing equations for a flow-through porous electrode reactor indicate that these devices must operate at a low space velocity to suppress a large ohmic potential drop. Packed-bed data for the mass-transfer rate at such low Reynolds numbers were examined and found to be sparse, especially in liquid systems. Prior models to simulate the solid-void structure in a bed are reviewed. Here the bed was envisioned as an array of sinusoidal periodically constricted tubes (PCT). Use of this model has not appeared in the literature. The velocity field in such a tube should be a good approximation to the converging-diverging character of the velocity field in an actual bed. The creeping flow velocity profiles were calculated. These results were used in the convective-diffusion equation to find mass transfer rates at high Peclet number for both deep and shallow beds, for low Peclet numbers in a deep bed. All calculations assumed that the reactant concentration at the tube surface is zero. Mass-transfer data were experimentally taken in a transport controlled, flow-through porous electrode to test the theoretical calculations and to provide data resently unavailable for deeper beds. It was found that the sinusoidal PCT model could not fit the data of this work or that available in the literature. However, all data could be adequately described by a model which incorporates a channelingeffect. The bed was successfully modeled as an array of dual sized straight tubes.
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.
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.
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
Compressed sensing & sparse filtering
Carmi, Avishy Y; Godsill, Simon J
2013-01-01
This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary.Â Apart from compressed sensing this book contains other related app
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.
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.
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
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
Denning, Peter J.
1989-01-01
Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs. This memory exhibits behaviors, both in theory and in experiment, that resemble those previously unapproached by machines - e.g., rapid recognition of faces or odors, discovery of new connections between seemingly unrelated ideas, continuation of a sequence of events when given a cue from the middle, knowing that one doesn't know, or getting stuck with an answer on the tip of one's tongue. These behaviors are now within reach of machines that can be incorporated into the computing systems of robots capable of seeing, talking, and manipulating. Kanerva's theory is a break with the Western rationalistic tradition, allowing a new interpretation of learning and cognition that respects biology and the mysteries of individual human beings.
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)
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...
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...
Optimized packings with applications
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...
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
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...
Consensus Convolutional Sparse Coding
Choudhury, Biswarup
2017-12-01
Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high-dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaicing and 4D light field view synthesis.
Consensus Convolutional Sparse Coding
Choudhury, Biswarup
2017-04-11
Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaickingand 4D light field view synthesis.
Consensus Convolutional Sparse Coding
Choudhury, Biswarup; Swanson, Robin; Heide, Felix; Wetzstein, Gordon; Heidrich, Wolfgang
2017-01-01
Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high-dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaicing and 4D light field view synthesis.
Turbulent flows over sparse canopies
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.
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 ...
Sparse Regression by Projection and Sparse Discriminant Analysis
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
In Defense of Sparse Tracking: Circulant Sparse Tracker
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
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.
Modeling approaches to natural convection in porous media
Su, Yan
2015-01-01
This book provides an overview of the field of flow and heat transfer in porous medium and focuses on presentation of a generalized approach to predict drag and convective heat transfer within porous medium of arbitrary microscopic geometry, including reticulated foams and packed beds. Practical numerical methods to solve natural convection problems in porous media will be presented with illustrative applications for filtrations, thermal storage and solar receivers.
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.
Language Recognition via Sparse Coding
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
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…
Optimal Packed String Matching
DEFF Research Database (Denmark)
Ben-Kiki, Oren; Bille, Philip; Breslauer, Dany
2011-01-01
In the packed string matching problem, each machine word accommodates – characters, thus an n-character text occupies n/– memory words. We extend the Crochemore-Perrin constantspace O(n)-time string matching algorithm to run in optimal O(n/–) time and even in real-time, achieving a factor – speed...
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....
Sparse Representations of Hyperspectral Images
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.
Sparse Representations of Hyperspectral Images
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.
DEFF Research Database (Denmark)
Andersen, Henrik; Ritter, Thomas
Ever seen a growth strategies fail because it was not connect ed to the firm’s customer base? Or a customer relationship strategy falters just because it was the wrong thing to do with that given customer? This article presents the six pack model, a tool that makes growth profitable and predictable....... Not all customers can and should grow – thus a firm needs to classify its customers in order to implement the right customer strategy....
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
Image understanding using sparse representations
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
The influence of bamboo-packed configuration to mixing characteristics in a fixed-bed reactor
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.
Sparse PCA with Oracle Property.
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.
To Pack or Not to Pack? A Randomized Trial of Vaginal Packing After Vaginal Reconstructive Surgery.
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.
Sparse Regression by Projection and Sparse Discriminant Analysis
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.
Pottmann, Helmut
2015-03-03
This paper is an overview of architectural structures which are either composed of polyhedral cells or closely related to them. We introduce the concept of a support structure of such a polyhedral cell packing. It is formed by planar quads and obtained by connecting corresponding vertices in two combinatorially equivalent meshes whose corresponding edges are coplanar and thus determine planar quads. Since corresponding triangle meshes only yield trivial structures, we focus on support structures associated with quad meshes or hex-dominant meshes. For the quadrilateral case, we provide a short survey of recent research which reveals beautiful relations to discrete differential geometry. Those are essential for successfully initializing numerical 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-bearing structures, we illustrate here a new application to shading and indirect lighting. On a higher level, our work emphasizes the interplay between geometry, optimization, statics, and manufacturing, with the overall aim of combining form, function and fabrication into novel integrated design tools.
Energy Technology Data Exchange (ETDEWEB)
Singleton, Robert Jr. [Los Alamos National Laboratory; Israel, Daniel M. [Los Alamos National Laboratory; Doebling, Scott William [Los Alamos National Laboratory; Woods, Charles Nathan [Los Alamos National Laboratory; Kaul, Ann [Los Alamos National Laboratory; Walter, John William Jr [Los Alamos National Laboratory; Rogers, Michael Lloyd [Los Alamos National Laboratory
2016-05-09
For code verification, one compares the code output against known exact solutions. There are many standard test problems used in this capacity, such as the Noh and Sedov problems. ExactPack is a utility that integrates many of these exact solution codes into a common API (application program interface), and can be used as a stand-alone code or as a python package. ExactPack consists of python driver scripts that access a library of exact solutions written in Fortran or Python. The spatial profiles of the relevant physical quantities, such as the density, fluid velocity, sound speed, or internal energy, are returned at a time specified by the user. The solution profiles can be viewed and examined by a command line interface or a graphical user interface, and a number of analysis tools and unit tests are also provided. We have documented the physics of each problem in the solution library, and provided complete documentation on how to extend the library to include additional exact solutions. ExactPack’s code architecture makes it easy to extend the solution-code library to include additional exact solutions in a robust, reliable, and maintainable manner.
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
Energy Technology Data Exchange (ETDEWEB)
Chmielewski, A G [Institute of Nuclear Chemistry and Technology, Warsaw (Poland)
2006-07-01
Joint FAO/IAEA/WHO Expert Committee approved the use of radiation treatment of foods. Nowadays food packaging are mostly made of plastics, natural or synthetic, therefore effect of irradiation on these materials is crucial for packing engineering for food irradiation technology. By selecting the right polymer materials for food packaging it can be ensured that the critical elements of material and product performance are not compromised. When packaging materials are in contact with food at the time of irradiation that regulatory approvals sometimes apply. The review of the R-and-D and technical papers regarding material selection, testing and approval is presented in the report. The most information come from the USA where this subject is well elaborated, the International Atomic Energy Agency (IAEA) reports are reviewed as well. The report can be useful for scientists and food irradiation plants operators. (author)
International Nuclear Information System (INIS)
Chmielewski, A.G.
2006-01-01
Joint FAO/IAEA/WHO Expert Committee approved the use of radiation treatment of foods. Nowadays food packaging are mostly made of plastics, natural or synthetic, therefore effect of irradiation on these materials is crucial for packing engineering for food irradiation technology. By selecting the right polymer materials for food packaging it can be ensured that the critical elements of material and product performance are not compromised. When packaging materials are in contact with food at the time of irradiation that regulatory approvals sometimes apply. The review of the R-and-D and technical papers regarding material selection, testing and approval is presented in the report. The most information come from the USA where this subject is well elaborated, the International Atomic Energy Agency (IAEA) reports are reviewed as well. The report can be useful for scientists and food irradiation plants operators. (author)
Ng, Albert H.
2011-01-24
To incorporate protein polarization effects within a protein combinatorial optimization framework, we decompose the polarizable force field AMOEBA into low order terms. Including terms up to the third-order provides a fair approximation to the full energy while maintaining tractability. We represent the polarizable packing problem for protein G as a hypergraph and solve for optimal rotamers with the FASTER combinatorial optimization algorithm. These approximate energy models can be improved to high accuracy [root mean square deviation (rmsd) < 1 kJ mol -1] via ridge regression. The resulting trained approximations are used to efficiently identify new, low-energy solutions. The approach is general and should allow combinatorial optimization of other many-body problems. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011 Copyright © 2011 Wiley Periodicals, Inc.
Using atomic layer deposited tungsten to increase thermal conductivity of a packed bed
Energy Technology Data Exchange (ETDEWEB)
Van Norman, Staci A.; Falconer, John L.; Weimer, Alan W., E-mail: alan.weimer@colorado.edu [Department of Chemical and Biological Engineering, University of Colorado, UCB 596, Boulder, Colorado 80309-0596 (United States); Tringe, Joseph W.; Sain, John D. [Lawrence Livermore National Laboratory, 7000 East Ave, Livermore, California 94550 (United States); Yang, Ronggui [Department of Mechanical Engineering, University of Colorado, UCB 427, Boulder, Colorado 80309-0427 (United States)
2015-04-13
This study investigated the effective thermal conductivity (k{sub eff}) of packed-beds that contained porous particles with nanoscale tungsten (W) films of different thicknesses formed by atomic layer deposition (ALD). A continuous film on the particles is vital towards increasing k{sub eff} of the packed beds. For example, the k{sub eff} of an alumina packed bed was increased by three times after an ∼8-nm continuous W film with 20 cycles of W ALD, whereas k{sub eff} was decreased on a polymer packed bed with discontinuous, evenly dispersed W-islands due to nanoparticle scattering of phonons. For catalysts, understanding the thermal properties of these packed beds is essential for developing thermally conductive supports as alternatives to structured supports.
Random packing of digitized particles
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
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
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)
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...
Disk Density Tuning of a Maximal Random Packing.
Ebeida, Mohamed S; Rushdi, Ahmad A; Awad, Muhammad A; Mahmoud, Ahmed H; Yan, Dong-Ming; English, Shawn A; Owens, John D; Bajaj, Chandrajit L; Mitchell, Scott A
2016-08-01
We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively more-aggressive local operations. We may achieve a user-defined density, either more dense or more sparse, almost up to the theoretical structured limits. The tuned samples are conflict-free, retain coverage maximality, and, except in the extremes, retain the blue noise randomness properties of the input. We change the density of the packing one disk at a time, maintaining the minimum disk separation distance and the maximum domain coverage distance required of any maximal packing. These properties are local, and we can handle spatially-varying sizing functions. Using fewer points to satisfy a sizing function improves the efficiency of some applications. We apply the framework to improve the quality of meshes, removing non-obtuse angles; and to more accurately model fiber reinforced polymers for elastic and failure simulations.
Sparse Matrices in Frame Theory
DEFF Research Database (Denmark)
Lemvig, Jakob; Krahmer, Felix; Kutyniok, Gitta
2014-01-01
Frame theory is closely intertwined with signal processing through a canon of methodologies for the analysis of signals using (redundant) linear measurements. The canonical dual frame associated with a frame provides a means for reconstruction by a least squares approach, but other dual frames...... yield alternative reconstruction procedures. The novel paradigm of sparsity has recently entered the area of frame theory in various ways. Of those different sparsity perspectives, we will focus on the situations where frames and (not necessarily canonical) dual frames can be written as sparse matrices...
Diffusion Indexes with Sparse Loadings
DEFF Research Database (Denmark)
Kristensen, Johannes Tang
The use of large-dimensional factor models in forecasting has received much attention in the literature with the consensus being that improvements on forecasts can be achieved when comparing with standard models. However, recent contributions in the literature have demonstrated that care needs...... to the problem by using the LASSO as a variable selection method to choose between the possible variables and thus obtain sparse loadings from which factors or diffusion indexes can be formed. This allows us to build a more parsimonious factor model which is better suited for forecasting compared...... it to be an important alternative to PC....
Sparse Linear Identifiable Multivariate Modeling
DEFF Research Database (Denmark)
Henao, Ricardo; Winther, Ole
2011-01-01
and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable......In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...
Programming for Sparse Minimax Optimization
DEFF Research Database (Denmark)
Jonasson, K.; Madsen, Kaj
1994-01-01
We present an algorithm for nonlinear minimax optimization which is well suited for large and sparse problems. The method is based on trust regions and sequential linear programming. On each iteration, a linear minimax problem is solved for a basic step. If necessary, this is followed...... by the determination of a minimum norm corrective step based on a first-order Taylor approximation. No Hessian information needs to be stored. Global convergence is proved. This new method has been extensively tested and compared with other methods, including two well known codes for nonlinear programming...
Dynamic Representations of Sparse Graphs
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Fagerberg, Rolf
1999-01-01
We present a linear space data structure for maintaining graphs with bounded arboricity—a large class of sparse graphs containing e.g. planar graphs and graphs of bounded treewidth—under edge insertions, edge deletions, and adjacency queries. The data structure supports adjacency queries in worst...... case O(c) time, and edge insertions and edge deletions in amortized O(1) and O(c+log n) time, respectively, where n is the number of nodes in the graph, and c is the bound on the arboricity....
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
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...
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...
Image fusion using sparse overcomplete feature dictionaries
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.
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...
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.)
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.
The pursuit of perfect packing
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...
When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores
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
Neural Network for Sparse Reconstruction
Directory of Open Access Journals (Sweden)
Qingfa Li
2014-01-01
Full Text Available We construct a neural network based on smoothing approximation techniques and projected gradient method to solve a kind of sparse reconstruction problems. Neural network can be implemented by circuits and can be seen as an important method for solving optimization problems, especially large scale problems. Smoothing approximation is an efficient technique for solving nonsmooth optimization problems. We combine these two techniques to overcome the difficulties of the choices of the step size in discrete algorithms and the item in the set-valued map of differential inclusion. In theory, the proposed network can converge to the optimal solution set of the given problem. Furthermore, some numerical experiments show the effectiveness of the proposed network in this paper.
Diffusion Indexes With Sparse Loadings
DEFF Research Database (Denmark)
Kristensen, Johannes Tang
2017-01-01
The use of large-dimensional factor models in forecasting has received much attention in the literature with the consensus being that improvements on forecasts can be achieved when comparing with standard models. However, recent contributions in the literature have demonstrated that care needs...... to the problem by using the least absolute shrinkage and selection operator (LASSO) as a variable selection method to choose between the possible variables and thus obtain sparse loadings from which factors or diffusion indexes can be formed. This allows us to build a more parsimonious factor model...... in forecasting accuracy and thus find it to be an important alternative to PC. Supplementary materials for this article are available online....
Sparse and stable Markowitz portfolios.
Brodie, Joshua; Daubechies, Ingrid; De Mol, Christine; Giannone, Domenico; Loris, Ignace
2009-07-28
We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e., portfolios with only few active positions), and allows accounting for transaction costs. Our approach recovers as special cases the no-short-positions portfolios, but does allow for short positions in limited number. We implement this methodology on two benchmark data sets constructed by Fama and French. Using only a modest amount of training data, we construct portfolios whose out-of-sample performance, as measured by Sharpe ratio, is consistently and significantly better than that of the naïve evenly weighted portfolio.
SPARSE FARADAY ROTATION MEASURE SYNTHESIS
International Nuclear Information System (INIS)
Andrecut, M.; Stil, J. M.; Taylor, A. R.
2012-01-01
Faraday rotation measure synthesis is a method for analyzing multichannel polarized radio emissions, and it has emerged as an important tool in the study of Galactic and extragalactic magnetic fields. The method requires the recovery of the Faraday dispersion function from measurements restricted to limited wavelength ranges, which is an ill-conditioned deconvolution problem. Here, we discuss a recovery method that assumes a sparse approximation of the Faraday dispersion function in an overcomplete dictionary of functions. We discuss the general case when both thin and thick components are included in the model, and we present the implementation of a greedy deconvolution algorithm. We illustrate the method with several numerical simulations that emphasize the effect of the covered range and sampling resolution in the Faraday depth space, and the effect of noise on the observed data.
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)
Numerical simulation and experimental verification of gas flow through packed beds
International Nuclear Information System (INIS)
Natarajan, S.; Zhang, C.; Briens, C.
2003-01-01
This work is concerned with finding out an effective way of eliminating oxygen from a packed bed of monomer particles. This process finds application in industries involved in the manufacture of Nylon12. In the manufacture of the polymer Nylon12, the polymerization reaction is hindered by the presence of oxygen. Therefore, the main objective of this study is to get rid of the oxygen by injecting nitrogen to displace the oxygen from the voids in-between the monomer particles before they are introduced into the polymerization reactor. This work involves the numerical simulation and experimental verification of the flow in a packed bed. In addition, a parametric study is carried out for the parameters such as the number of injectors, the radial position of injectors, and the position of the injectors along the circumference of the packed bed to find out the best possible combination for effective elimination of the oxygen. Nitrogen does not interact with the monomer particles and hence there is no chemical reaction involved in this process. The nitrogen is introduced into the packed bed at a flow rate which will keep the superficial velocity well below the minimum fluidization velocity of the monomer particles. The packed bed will be modeled using a porous medium approach available in the commercial computational fluid dynamics (CFD) software FLUENT. The fluid flow inside the packed bed will be a multicomponent gas flow through a porous medium. The simulation results are validated by comparing with the experimental results. (author)
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
Sparse seismic imaging using variable projection
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
Efficient packing of patterns in sparse distributed memory by selective weighting of input bits
Kanerva, Pentti
1991-01-01
When a set of patterns is stored in a distributed memory, any given storage location participates in the storage of many patterns. From the perspective of any one stored pattern, the other patterns act as noise, and such noise limits the memory's storage capacity. The more similar the retrieval cues for two patterns are, the more the patterns interfere with each other in memory, and the harder it is to separate them on retrieval. A method is described of weighting the retrieval cues to reduce such interference and thus to improve the separability of patterns that have similar cues.
Orthogonal sparse linear discriminant analysis
Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun
2018-03-01
Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.
Spectra of sparse random matrices
International Nuclear Information System (INIS)
Kuehn, Reimer
2008-01-01
We compute the spectral density for ensembles of sparse symmetric random matrices using replica. Our formulation of the replica-symmetric ansatz shares the symmetries of that suggested in a seminal paper by Rodgers and Bray (symmetry with respect to permutation of replica and rotation symmetry in the space of replica), but uses a different representation in terms of superpositions of Gaussians. It gives rise to a pair of integral equations which can be solved by a stochastic population-dynamics algorithm. Remarkably our representation allows us to identify pure-point contributions to the spectral density related to the existence of normalizable eigenstates. Our approach is not restricted to matrices defined on graphs with Poissonian degree distribution. Matrices defined on regular random graphs or on scale-free graphs, are easily handled. We also look at matrices with row constraints such as discrete graph Laplacians. Our approach naturally allows us to unfold the total density of states into contributions coming from vertices of different local coordinations and an example of such an unfolding is presented. Our results are well corroborated by numerical diagonalization studies of large finite random matrices
The pursuit of perfect packing
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.
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...
Discriminative sparse coding on multi-manifolds
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
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.
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.
Method for immobilizing particulate materials in a packed bed
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.
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
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
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.
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.
Amine Functionalized Porous Network
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
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.
Towards optimal packed string matching
DEFF Research Database (Denmark)
Ben-Kiki, Oren; Bille, Philip; Breslauer, Dany
2014-01-01
-size string-matching instruction wssm is available in contemporary commodity processors. The other word-size maximum-suffix instruction wslm is only required during the pattern pre-processing. Benchmarks show that our solution can be efficiently implemented, unlike some prior theoretical packed string...
Structure-based bayesian sparse reconstruction
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
Biclustering via Sparse Singular Value Decomposition
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.
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....
SPARSE ELECTROMAGNETIC IMAGING USING NONLINEAR LANDWEBER ITERATIONS
Desmal, Abdulla; Bagci, Hakan
2015-01-01
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
Learning sparse generative models of audiovisual signals
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...
Diffusion with condensation and evaporation in porous media
International Nuclear Information System (INIS)
Gu, L.; Plumb, O.A.; Ho, C.K.; Webb, S.W.
1998-03-01
Vapor phase transport in porous media is important in a number of environmental and industrial processes: soil moisture transport, vapor phase transport in the vadose zone, transport in the vicinity of buried nuclear waste, and industrial processes such as drying. The diffusion of water vapor in a packed bed containing residual liquid is examined experimentally. The objective is to quantify the effect of enhanced vapor diffusion resulting from evaporation/condensation in porous media subjected to a temperature gradient. Isothermal diffusion experiments in free-space were conducted to qualify the experimental apparatus and techniques. For these experiments measured diffusion coefficients are within 3.6% of those reported in the literature for the temperature range from 25 C to 40 C. Isothermal experiments in packed beds of glass beads were used to determine the tortuosity coefficient resulting in τ = 0.78 ± 0.028, which is also consistent with previously reported results. Nonisothermal experiments in packed beds in which condensation occurs were conducted to examine enhanced vapor diffusion. The interpretation of the results for these experiments is complicated by a gradual, but continuous, build-up of condensate in the packed beds during the course of the experiment. Results indicate diffusion coefficients which increase as a function of saturation resulting in enhancement of the vapor-phase transport by a factor of approximately four compared to a dry porous medium
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...
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...
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.
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)
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)
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.
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.
Quantification and Control of Wall Effects in Porous Media Experiments
Roth, E. J.; Mays, D. C.; Neupauer, R.; Crimaldi, J. P.
2017-12-01
Fluid flow dynamics in porous media are dominated by media heterogeneity. This heterogeneity can create preferential pathways in which local seepage velocities dwarf system seepage velocities, further complicating an already incomplete understanding of dispersive processes. In physical models of porous media flows, apparatus walls introduce preferential flow paths (i.e., wall effects) that may overwhelm other naturally occurring preferential pathways within the apparatus, leading to deceptive results. We used planar laser-induced fluorescence (PLIF) in conjunction with refractive index matched (RIM) porous media and pore fluid to observe fluid dynamics in the porous media, with particular attention to the region near the apparatus walls in a 17 cm x 8 cm x 7 cm uniform flow cell. Hexagonal close packed spheres were used to create an isotropic, homogenous porous media field in the interior of the apparatus. Visualization of the movement of a fluorescent dye revealed the influence of the wall in creating higher permeability preferential flow paths in an otherwise homogenous media packing. These preferential flow paths extended approximately one half of one sphere diameter from the wall for homogenously packed regions, with a quickly diminishing effect on flow dynamics for homogenous media adjacent to the preferential pathway, but with major influence on flow dynamics for adjoining heterogeneous regions. Multiple approaches to mitigate wall effects were investigated, and a modified wall was created such that the fluid dynamics near the wall mimics the fluid dynamics within the homogenous porous media. This research supports the design of a two-dimensional experimental apparatus that will simulate engineered pumping schemes for use in contaminant remediation. However, this research could benefit the design of fixed bed reactors or other engineering challenges in which vessel walls contribute to unwanted preferential flow.
Hypostatic jammed packings of frictionless nonspherical particles
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...
SparseBeads data: benchmarking sparsity-regularized computed tomography
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.
1996-07-11
The Superior Court of New Jersey, Appellate Division, recognized "a physician's duty to warn those known to be at risk of avoidable harm from a genetically transmissible condition." During the 1950s, Dr. George Pack treated Donna Shafer's father for a cancerous blockage of the colon and multiple polyposis. In 1990, Safer was diagnosed with the same condition, which she claims is inherited, and, if not diagnosed and treated, invariably will lead to metastic colorectal cancer. Safer alleged that Dr. Pack knew the hereditary nature of the disease, yet failed to warn the immediate family, thus breaching his professional duty to warn. The court did not follow the analysis of the trial court, that a physician has no legal duty to warn the child of a patient of the genetic risk of disease because no physician and patient relationship exists between the doctor and the child.
Fast Searching in Packed Strings
DEFF Research Database (Denmark)
Bille, Philip
2009-01-01
Given strings P and Q the (exact) string matching problem is to find all positions of substrings in Q matching P. The classical Knuth-Morris-Pratt algorithm [SIAM J. Comput., 1977] solves the string matching problem in linear time which is optimal if we can only read one character at the time....... However, most strings are stored in a computer in a packed representation with several characters in a single word, giving us the opportunity to read multiple characters simultaneously. In this paper we study the worst-case complexity of string matching on strings given in packed representation. Let m...... word-RAM with logarithmic word size we present an algorithm using time O(n/log(sigma) n + m + occ) Here occ is the number of occurrences of P in Q. For m = o(n) this improves the O(n) bound...
Random packing of colloids and granular matter
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
Complications of balloon packing in epistaxis
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
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)
When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores
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.
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)
Sparse Learning with Stochastic Composite Optimization.
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).
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...
International Nuclear Information System (INIS)
Antwerpen, W. van; Rousseau, P.G.; Toit, C.G. du
2009-01-01
A proper understanding of the mechanisms of heat transfer, flow and pressure drop through a packed bed of spheres is of utmost importance in the design of a high temperature pebble bed reactor. A thorough knowledge of the porous structure within the packed bed is important to any rigorous analysis of the transport phenomena, as all the heat and flow mechanisms are influenced by the porous structure. In this paper a new approach is proposed to simulate the effective thermal conductivity employing a combination of new and existing correlations for randomly packed beds. More attention is given to packing structure based on coordination number and contact angles, resulting in a more rigorous differentiation between the bulk and near-wall regions. The model accounts for solid conduction, gas conduction, contact area, surface roughness as well as radiation. (author)
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...
SPARSE ELECTROMAGNETIC IMAGING USING NONLINEAR LANDWEBER ITERATIONS
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.
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.
Sparse regularization for force identification using dictionaries
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.
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
Analog system for computing sparse codes
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.
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....
Structure-based bayesian sparse reconstruction
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.
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.
Subspace Based Blind Sparse Channel Estimation
DEFF Research Database (Denmark)
Hayashi, Kazunori; Matsushima, Hiroki; Sakai, Hideaki
2012-01-01
The paper proposes a subspace based blind sparse channel estimation method using 1–2 optimization by replacing the 2–norm minimization in the conventional subspace based method by the 1–norm minimization problem. Numerical results confirm that the proposed method can significantly improve...
Multilevel sparse functional principal component analysis.
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.
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...
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...
Better Size Estimation for Sparse Matrix Products
DEFF Research Database (Denmark)
Amossen, Rasmus Resen; Campagna, Andrea; Pagh, Rasmus
2010-01-01
We consider the problem of doing fast and reliable estimation of the number of non-zero entries in a sparse Boolean matrix product. Let n denote the total number of non-zero entries in the input matrices. We show how to compute a 1 ± ε approximation (with small probability of error) in expected t...
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...
Feature based omnidirectional sparse visual path following
Goedemé, Toon; Tuytelaars, Tinne; Van Gool, Luc; Vanacker, Gerolf; Nuttin, Marnix
2005-01-01
Goedemé T., Tuytelaars T., Van Gool L., Vanacker G., Nuttin M., ''Feature based omnidirectional sparse visual path following'', Proceedings IEEE/RSJ international conference on intelligent robots and systems - IROS2005, pp. 1003-1008, August 2-6, 2005, Edmonton, Alberta, Canada.
Comparison of sparse point distribution models
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Vester-Christensen, Martin; Larsen, Rasmus
2010-01-01
This paper compares several methods for obtaining sparse and compact point distribution models suited for data sets containing many variables. These are evaluated on a database consisting of 3D surfaces of a section of the pelvic bone obtained from CT scans of 33 porcine carcasses. The superior m...
A sparse-grid isogeometric solver
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.
A sparse version of IGA solvers
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.
A sparse-grid isogeometric solver
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 version of IGA solvers
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.
New methods for sampling sparse populations
Anna Ringvall
2007-01-01
To improve surveys of sparse objects, methods that use auxiliary information have been suggested. Guided transect sampling uses prior information, e.g., from aerial photographs, for the layout of survey strips. Instead of being laid out straight, the strips will wind between potentially more interesting areas. 3P sampling (probability proportional to prediction) uses...
Hypostatic jammed packings of frictionless nonspherical particles
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
Fast searching in packed strings
DEFF Research Database (Denmark)
Bille, Philip
2011-01-01
Given strings P and Q the (exact) string matching problem is to find all positions of substrings in Q matching P. The classical Knuth–Morris–Pratt algorithm [SIAM J. Comput. 6 (2) (1977) 323–350] solves the string matching problem in linear time which is optimal if we can only read one character...... at the time. However, most strings are stored in a computer in a packed representation with several characters in a single word, giving us the opportunity to read multiple characters simultaneously. In this paper we study the worst-case complexity of string matching on strings given in packed representation....... Let m⩽n be the lengths P and Q, respectively, and let σ denote the size of the alphabet. On a standard unit-cost word-RAM with logarithmic word size we present an algorithm using timeO(nlogσn+m+occ). Here occ is the number of occurrences of P in Q. For m=o(n) this improves the O(n) bound of the Knuth...
CERN Bulletin
2011-01-01
The Particle Zoo is a colourful set of hand-made soft toys representing the particles in the Standard Model and beyond. It includes a “theoreticals” pack where you can find yet undiscovered particles: the best-selling Higgs boson, the graviton, the tachyon, and dark matter. Supersymmetric particle soft toys are also available on demand. But what would happen to the zoo if Nature had prepared some unexpected surprises? Julie Peasley, the zookeeper, is ready to sew new smiling faces… The "Theoreticals" pack in the Particle Zoo. There is only one place in the world where you can buy a smiling Higgs boson and it’s not at CERN, although this is where scientists hope to observe it. The blue star-shaped particle is the best seller of Julie Peasley’s Particle Zoo – a collection of tens of soft toys representing all sorts of particles, including composite and decaying particles. Over the years Julie’s zoo ...
Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint.
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.
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.
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
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.)
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
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)
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
A sparse electromagnetic imaging scheme using nonlinear landweber iterations
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
Efficient Pseudorecursive Evaluation Schemes for Non-adaptive Sparse Grids
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
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 reconstruction using distribution agnostic bayesian matching pursuit
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
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
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...
Sparse learning of stochastic dynamical equations
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.
Sparseness- and continuity-constrained seismic imaging
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.
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...
Lattice Boltzmann simulations for wall-flow dynamics in porous ceramic diesel particulate filters
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.
Robust Fringe Projection Profilometry via Sparse Representation.
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.
Fabricating porous silicon carbide
Shor, Joseph S. (Inventor); Kurtz, Anthony D. (Inventor)
1994-01-01
The formation of porous SiC occurs under electrochemical anodization. A sample of SiC is contacted electrically with nickel and placed into an electrochemical cell which cell includes a counter electrode and a reference electrode. The sample is encapsulated so that only a bare semiconductor surface is exposed. The electrochemical cell is filled with an HF electrolyte which dissolves the SiC electrochemically. A potential is applied to the semiconductor and UV light illuminates the surface of the semiconductor. By controlling the light intensity, the potential and the doping level, a porous layer is formed in the semiconductor and thus one produces porous SiC.
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...
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.
The general packed column : an analytical solution
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
On contact numbers in random rod packings
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
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...
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.
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
Stochastic porous media equations
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.
Condensation in Nanoporous Packed Beds.
Ally, Javed; Molla, Shahnawaz; Mostowfi, Farshid
2016-05-10
In materials with tiny, nanometer-scale pores, liquid condensation is shifted from the bulk saturation pressure observed at larger scales. This effect is called capillary condensation and can block pores, which has major consequences in hydrocarbon production, as well as in fuel cells, catalysis, and powder adhesion. In this study, high pressure nanofluidic condensation studies are performed using propane and carbon dioxide in a colloidal crystal packed bed. Direct visualization allows the extent of condensation to be observed, as well as inference of the pore geometry from Bragg diffraction. We show experimentally that capillary condensation depends on pore geometry and wettability because these factors determine the shape of the menisci that coalesce when pore filling occurs, contrary to the typical assumption that all pore structures can be modeled as cylindrical and perfectly wetting. We also observe capillary condensation at higher pressures than has been done previously, which is important because many applications involving this phenomenon occur well above atmospheric pressure, and there is little, if any, experimental validation of capillary condensation at such pressures, particularly with direct visualization.
Hawking Colloquium Packed CERN Auditoriums
2006-01-01
Stephen Hawking's week long visit to CERN included an 'exceptional CERN colloquium' which filled six auditoriums. Stephen Hawking during his visit to the ATLAS experiment. Stephen Hawking, Lucasian Professor of Cambridge University, visited the Theory Unit of the Physics Department from 24 September to 1 October 2006. As part of his visit, he gave two lectures in the main auditorium - a theoretical seminar on 'The Semi-Classical Birth of The Universe', attended by about 120 specialists; and a colloquium titled 'The Origin of The Universe'. As a key public figure in theoretical physics, his presence was eagerly awaited on both occasions. Those who wanted to attend the colloquium had to arrive early and be equipped with plenty of patience. An hour before it was due to begin, the 400 capacity of the main auditorium was already full. The lecture, simultaneously broadcast to five other fully packed CERN auditoriums, was attended by an estimated total of 850. Stephen Hawking attracted a large CERN crowd, filling ...
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.
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
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.
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)
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)
Noniterative MAP reconstruction using sparse matrix representations.
Cao, Guangzhi; Bouman, Charles A; Webb, Kevin J
2009-09-01
We present a method for noniterative maximum a posteriori (MAP) tomographic reconstruction which is based on the use of sparse matrix representations. Our approach is to precompute and store the inverse matrix required for MAP reconstruction. This approach has generally not been used in the past because the inverse matrix is typically large and fully populated (i.e., not sparse). In order to overcome this problem, we introduce two new ideas. The first idea is a novel theory for the lossy source coding of matrix transformations which we refer to as matrix source coding. This theory is based on a distortion metric that reflects the distortions produced in the final matrix-vector product, rather than the distortions in the coded matrix itself. The resulting algorithms are shown to require orthonormal transformations of both the measurement data and the matrix rows and columns before quantization and coding. The second idea is a method for efficiently storing and computing the required orthonormal transformations, which we call a sparse-matrix transform (SMT). The SMT is a generalization of the classical FFT in that it uses butterflies to compute an orthonormal transform; but unlike an FFT, the SMT uses the butterflies in an irregular pattern, and is numerically designed to best approximate the desired transforms. We demonstrate the potential of the noniterative MAP reconstruction with examples from optical tomography. The method requires offline computation to encode the inverse transform. However, once these offline computations are completed, the noniterative MAP algorithm is shown to reduce both storage and computation by well over two orders of magnitude, as compared to a linear iterative reconstruction methods.
Galaxy redshift surveys with sparse sampling
International Nuclear Information System (INIS)
Chiang, Chi-Ting; Wullstein, Philipp; Komatsu, Eiichiro; Jee, Inh; Jeong, Donghui; Blanc, Guillermo A.; Ciardullo, Robin; Gronwall, Caryl; Hagen, Alex; Schneider, Donald P.; Drory, Niv; Fabricius, Maximilian; Landriau, Martin; Finkelstein, Steven; Jogee, Shardha; Cooper, Erin Mentuch; Tuttle, Sarah; Gebhardt, Karl; Hill, Gary J.
2013-01-01
Survey observations of the three-dimensional locations of galaxies are a powerful approach to measure the distribution of matter in the universe, which can be used to learn about the nature of dark energy, physics of inflation, neutrino masses, etc. A competitive survey, however, requires a large volume (e.g., V survey ∼ 10Gpc 3 ) to be covered, and thus tends to be expensive. A ''sparse sampling'' method offers a more affordable solution to this problem: within a survey footprint covering a given survey volume, V survey , we observe only a fraction of the volume. The distribution of observed regions should be chosen such that their separation is smaller than the length scale corresponding to the wavenumber of interest. Then one can recover the power spectrum of galaxies with precision expected for a survey covering a volume of V survey (rather than the volume of the sum of observed regions) with the number density of galaxies given by the total number of observed galaxies divided by V survey (rather than the number density of galaxies within an observed region). We find that regularly-spaced sampling yields an unbiased power spectrum with no window function effect, and deviations from regularly-spaced sampling, which are unavoidable in realistic surveys, introduce calculable window function effects and increase the uncertainties of the recovered power spectrum. On the other hand, we show that the two-point correlation function (pair counting) is not affected by sparse sampling. While we discuss the sparse sampling method within the context of the forthcoming Hobby-Eberly Telescope Dark Energy Experiment, the method is general and can be applied to other galaxy surveys
A view of Kanerva's sparse distributed memory
Denning, P. J.
1986-01-01
Pentti Kanerva is working on a new class of computers, which are called pattern computers. Pattern computers may close the gap between capabilities of biological organisms to recognize and act on patterns (visual, auditory, tactile, or olfactory) and capabilities of modern computers. Combinations of numeric, symbolic, and pattern computers may one day be capable of sustaining robots. The overview of the requirements for a pattern computer, a summary of Kanerva's Sparse Distributed Memory (SDM), and examples of tasks this computer can be expected to perform well are given.
Wavelets for Sparse Representation of Music
DEFF Research Database (Denmark)
Endelt, Line Ørtoft; Harbo, Anders La-Cour
2004-01-01
We are interested in obtaining a sparse representation of music signals by means of a discrete wavelet transform (DWT). That means we want the energy in the representation to be concentrated in few DWT coefficients. It is well-known that the decay of the DWT coefficients is strongly related...... to the number of vanishing moments of the mother wavelet, and to the smoothness of the signal. In this paper we present the result of applying two classical families of wavelets to a series of musical signals. The purpose is to determine a general relation between the number of vanishing moments of the wavelet...
Sparse dynamics for partial differential equations.
Schaeffer, Hayden; Caflisch, Russel; Hauck, Cory D; Osher, Stanley
2013-04-23
We investigate the approximate dynamics of several differential equations when the solutions are restricted to a sparse subset of a given basis. The restriction is enforced at every time step by simply applying soft thresholding to the coefficients of the basis approximation. By reducing or compressing the information needed to represent the solution at every step, only the essential dynamics are represented. In many cases, there are natural bases derived from the differential equations, which promote sparsity. We find that our method successfully reduces the dynamics of convection equations, diffusion equations, weak shocks, and vorticity equations with high-frequency source terms.
Abnormal Event Detection Using Local Sparse Representation
DEFF Research Database (Denmark)
Ren, Huamin; Moeslund, Thomas B.
2014-01-01
We propose to detect abnormal events via a sparse subspace clustering algorithm. Unlike most existing approaches, which search for optimized normal bases and detect abnormality based on least square error or reconstruction error from the learned normal patterns, we propose an abnormality measurem...... is found that satisfies: the distance between its local space and the normal space is large. We evaluate our method on two public benchmark datasets: UCSD and Subway Entrance datasets. The comparison to the state-of-the-art methods validate our method's effectiveness....
Partitioning sparse rectangular matrices for parallel processing
Energy Technology Data Exchange (ETDEWEB)
Kolda, T.G.
1998-05-01
The authors are interested in partitioning sparse rectangular matrices for parallel processing. The partitioning problem has been well-studied in the square symmetric case, but the rectangular problem has received very little attention. They will formalize the rectangular matrix partitioning problem and discuss several methods for solving it. They will extend the spectral partitioning method for symmetric matrices to the rectangular case and compare this method to three new methods -- the alternating partitioning method and two hybrid methods. The hybrid methods will be shown to be best.
Functional fixedness in a technologically sparse culture.
German, Tim P; Barrett, H Clark
2005-01-01
Problem solving can be inefficient when the solution requires subjects to generate an atypical function for an object and the object's typical function has been primed. Subjects become "fixed" on the design function of the object, and problem solving suffers relative to control conditions in which the object's function is not demonstrated. In the current study, such functional fixedness was demonstrated in a sample of adolescents (mean age of 16 years) among the Shuar of Ecuadorian Amazonia, whose technologically sparse culture provides limited access to large numbers of artifacts with highly specialized functions. This result suggests that design function may universally be the core property of artifact concepts in human semantic memory.
Parallel preconditioning techniques for sparse CG solvers
Energy Technology Data Exchange (ETDEWEB)
Basermann, A.; Reichel, B.; Schelthoff, C. [Central Institute for Applied Mathematics, Juelich (Germany)
1996-12-31
Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role in numerical methods for solving discretized partial differential equations. The large size and the condition of many technical or physical applications in this area result in the need for efficient parallelization and preconditioning techniques of the CG method. In particular for very ill-conditioned matrices, sophisticated preconditioner are necessary to obtain both acceptable convergence and accuracy of CG. Here, we investigate variants of polynomial and incomplete Cholesky preconditioners that markedly reduce the iterations of the simply diagonally scaled CG and are shown to be well suited for massively parallel machines.
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.
Improved Taxation Rate for Bin Packing Games
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.
Comparing the efficacy of mature mud pack and hot pack treatments for knee osteoarthritis.
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.
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.
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.
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...
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.
Interferometric interpolation of sparse marine data
Hanafy, Sherif M.
2013-10-11
We present the theory and numerical results for interferometrically interpolating 2D and 3D marine surface seismic profiles data. For the interpolation of seismic data we use the combination of a recorded Green\\'s function and a model-based Green\\'s function for a water-layer model. Synthetic (2D and 3D) and field (2D) results show that the seismic data with sparse receiver intervals can be accurately interpolated to smaller intervals using multiples in the data. An up- and downgoing separation of both recorded and model-based Green\\'s functions can help in minimizing artefacts in a virtual shot gather. If the up- and downgoing separation is not possible, noticeable artefacts will be generated in the virtual shot gather. As a partial remedy we iteratively use a non-stationary 1D multi-channel matching filter with the interpolated data. Results suggest that a sparse marine seismic survey can yield more information about reflectors if traces are interpolated by interferometry. Comparing our results to those of f-k interpolation shows that the synthetic example gives comparable results while the field example shows better interpolation quality for the interferometric method. © 2013 European Association of Geoscientists & Engineers.
Balanced and sparse Tamo-Barg codes
Halbawi, Wael; Duursma, Iwan; Dau, Hoang; Hassibi, Babak
2017-01-01
We construct balanced and sparse generator matrices for Tamo and Barg's Locally Recoverable Codes (LRCs). More specifically, for a cyclic Tamo-Barg code of length n, dimension k and locality r, we show how to deterministically construct a generator matrix where the number of nonzeros in any two columns differs by at most one, and where the weight of every row is d + r - 1, where d is the minimum distance of the code. Since LRCs are designed mainly for distributed storage systems, the results presented in this work provide a computationally balanced and efficient encoding scheme for these codes. The balanced property ensures that the computational effort exerted by any storage node is essentially the same, whilst the sparse property ensures that this effort is minimal. The work presented in this paper extends a similar result previously established for Reed-Solomon (RS) codes, where it is now known that any cyclic RS code possesses a generator matrix that is balanced as described, but is sparsest, meaning that each row has d nonzeros.
Atmospheric inverse modeling via sparse reconstruction
Hase, Nils; Miller, Scot M.; Maaß, Peter; Notholt, Justus; Palm, Mathias; Warneke, Thorsten
2017-10-01
Many applications in atmospheric science involve ill-posed inverse problems. A crucial component of many inverse problems is the proper formulation of a priori knowledge about the unknown parameters. In most cases, this knowledge is expressed as a Gaussian prior. This formulation often performs well at capturing smoothed, large-scale processes but is often ill equipped to capture localized structures like large point sources or localized hot spots. Over the last decade, scientists from a diverse array of applied mathematics and engineering fields have developed sparse reconstruction techniques to identify localized structures. In this study, we present a new regularization approach for ill-posed inverse problems in atmospheric science. It is based on Tikhonov regularization with sparsity constraint and allows bounds on the parameters. We enforce sparsity using a dictionary representation system. We analyze its performance in an atmospheric inverse modeling scenario by estimating anthropogenic US methane (CH4) emissions from simulated atmospheric measurements. Different measures indicate that our sparse reconstruction approach is better able to capture large point sources or localized hot spots than other methods commonly used in atmospheric inversions. It captures the overall signal equally well but adds details on the grid scale. This feature can be of value for any inverse problem with point or spatially discrete sources. We show an example for source estimation of synthetic methane emissions from the Barnett shale formation.
Balanced and sparse Tamo-Barg codes
Halbawi, Wael
2017-08-29
We construct balanced and sparse generator matrices for Tamo and Barg\\'s Locally Recoverable Codes (LRCs). More specifically, for a cyclic Tamo-Barg code of length n, dimension k and locality r, we show how to deterministically construct a generator matrix where the number of nonzeros in any two columns differs by at most one, and where the weight of every row is d + r - 1, where d is the minimum distance of the code. Since LRCs are designed mainly for distributed storage systems, the results presented in this work provide a computationally balanced and efficient encoding scheme for these codes. The balanced property ensures that the computational effort exerted by any storage node is essentially the same, whilst the sparse property ensures that this effort is minimal. The work presented in this paper extends a similar result previously established for Reed-Solomon (RS) codes, where it is now known that any cyclic RS code possesses a generator matrix that is balanced as described, but is sparsest, meaning that each row has d nonzeros.
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.
Diffusion in porous structures containing three fluid phases
International Nuclear Information System (INIS)
Galani, A.N.; Kainourgiakis, M.E.; Stubos, A.K.; Kikkinides, E.S.
2005-01-01
In the present study, the tracer diffusion in porous media filled by three fluid phases (a non-wetting, an intermediate wetting and a wetting phase) is investigated. The disordered porous structure of porous systems like random sphere packing and the North Sea chalk, is represented by three-dimensional binary images. The random sphere pack is generated by a standard ballistic deposition procedure, while the chalk matrix by a stochastic reconstruction technique. Physically sound spatial distributions of the three phases filling the pore space are determined by the use of a simulated annealing algorithm, where those phases are initially randomly distributed in the pore space and trial-and-error swaps are performed in order to attain the global minimum of the total interfacial energy. The acceptance rule for a trial move during the annealing is modified properly improving the efficiency of the technique. The diffusivities of the resulting domains are computed by a random walk method. A parametric study with respect to the pore volume fraction occupied by each fluid phase and the ratio of the diffusivities in the fluid phases is performed. (authors)
Packing circles and spheres on surfaces
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 in Two and Three Dimensions
National Research Council Canada - National Science Library
Martins, Gustavo H
2003-01-01
...), the Multidimensional Knapsack Problem (MD-KP), and the Multidimensional Bin Packing Problem (MD-BPP). In these problems, there is a set of items, with rectangular dimensions, and a set of large containers, or bins, also with rectangular dimensions...
Prevention and suppression of metal packing fires.
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.
Packing circles and spheres on surfaces
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
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
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.
Random close packing in protein cores
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...
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)
Integrality gap analysis for bin packing games
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
Parallel sparse direct solver for integrated circuit simulation
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...
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)
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.
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)
Bidispersed Sphere Packing on Spherical Surfaces
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.
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...
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
Energy Technology Data Exchange (ETDEWEB)
Marsden, S.S.
1986-07-01
In 1978 a literature search on selective blocking of fluid flow in porous media was done by Professor S.S. Marsden and two of his graduate students, Tom Elson and Kern Huppy. This was presented as SUPRI Report No. TR-3 entitled ''Literature Preview of the Selected Blockage of Fluids in Thermal Recovery Projects.'' Since then a lot of research on foam in porous media has been done on the SUPRI project and a great deal of new information has appeared in the literature. Therefore we believed that a new, up-to-date search should be done on foam alone, one which would be helpful to our students and perhaps of interest to others. This is a chronological survey showing the development of foam flow, blockage and use in porous media, starting with laboratory studies and eventually getting into field tests and demonstrations. It is arbitrarily divided into five-year time periods. 81 refs.
Porous material neutron detector
Diawara, Yacouba [Oak Ridge, TN; Kocsis, Menyhert [Venon, FR
2012-04-10
A neutron detector employs a porous material layer including pores between nanoparticles. The composition of the nanoparticles is selected to cause emission of electrons upon detection of a neutron. The nanoparticles have a maximum dimension that is in the range from 0.1 micron to 1 millimeter, and can be sintered with pores thereamongst. A passing radiation generates electrons at one or more nanoparticles, some of which are scattered into a pore and directed toward a direction opposite to the applied electrical field. These electrons travel through the pore and collide with additional nanoparticles, which generate more electrons. The electrons are amplified in a cascade reaction that occurs along the pores behind the initial detection point. An electron amplification device may be placed behind the porous material layer to further amplify the electrons exiting the porous material layer.
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
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)
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.
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
Dose-shaping using targeted sparse optimization
Energy Technology Data Exchange (ETDEWEB)
Sayre, George A.; Ruan, Dan [Department of Radiation Oncology, University of California - Los Angeles School of Medicine, 200 Medical Plaza, Los Angeles, California 90095 (United States)
2013-07-15
Purpose: Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, the authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method.Methods: In designing the energy minimization objective (E{sub tot}{sup sparse}), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L{sub 1} norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E{sub tot
Dose-shaping using targeted sparse optimization
International Nuclear Information System (INIS)
Sayre, George A.; Ruan, Dan
2013-01-01
Purpose: Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, the authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method.Methods: In designing the energy minimization objective (E tot sparse ), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L 1 norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E tot sparse improves
Dose-shaping using targeted sparse optimization.
Sayre, George A; Ruan, Dan
2013-07-01
Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, the authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method. In designing the energy minimization objective (E tot (sparse)), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L1 norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E tot (sparse) improves tradeoff between
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...
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...
Energy Technology Data Exchange (ETDEWEB)
Tsuo, Y.S.; Menna, P.; Pitts, J.R. [National Renewable Energy Lab., Golden, CO (United States)] [and others
1996-05-01
The authors have studied a novel extrinsic gettering method that uses the large surface areas produced by a porous-silicon etch as gettering sites. The annealing step of the gettering used a high-flux solar furnace. They found that a high density of photons during annealing enhanced the impurity diffusion to the gettering sites. The authors used metallurgical-grade Si (MG-Si) prepared by directional solidification casing as the starting material. They propose to use porous-silicon-gettered MG-Si as a low-cost epitaxial substrate for polycrystalline silicon thin-film growth.
Porous metal for orthopedics implants
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.
Preparation and characterization of nanostructured ZrO2 coatings on dense and porous substrates
International Nuclear Information System (INIS)
Shi Jingyu; Verweij, Henk
2008-01-01
Nanostructured ZrO 2 coatings are prepared on both dense and porous substrates by wet-chemical deposition of non-agglomerated 5 nm precursor particle dispersions, followed by thermal processing. The precursor particle dispersions are made by modified emulsion precipitation and a purification treatment to remove reaction products and additives. The coatings are formed by depositing the precursor nanoparticle dispersion directly onto the substrate, followed by drying and heating at 600 deg. C. Scanning electron microscopy and cross-sectional transmission electron microscopy observations of the heat-treated coatings indicate that the ZrO 2 coating on dense Si wafer substrate has a homogeneous, dense particle packing structure with shallow meniscus-shaped depressions in the surface, and microcracks below the meniscus surface. On the other hand, coatings formed on a meso-porous γ-alumina membrane substrate are free of defects, but with a lower packing density. The mechanism of the substrate effect on the particle packing behavior and defect formation during coating deposition is discussed. It is expected that by using a thin porous substrate with reduced capillary force, a defect-free, homogenously dense-packed coating structure can be achieved
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.
Sparse Bayesian Learning for Nonstationary Data Sources
Fujimaki, Ryohei; Yairi, Takehisa; Machida, Kazuo
This paper proposes an online Sparse Bayesian Learning (SBL) algorithm for modeling nonstationary data sources. Although most learning algorithms implicitly assume that a data source does not change over time (stationary), one in the real world usually does due to such various factors as dynamically changing environments, device degradation, sudden failures, etc (nonstationary). The proposed algorithm can be made useable for stationary online SBL by setting time decay parameters to zero, and as such it can be interpreted as a single unified framework for online SBL for use with stationary and nonstationary data sources. Tests both on four types of benchmark problems and on actual stock price data have shown it to perform well.
Narrowband interference parameterization for sparse Bayesian recovery
Ali, Anum
2015-09-11
This paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosen sub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use tools from stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recovery method for NBI mitigation. © 2015 IEEE.
Modern algorithms for large sparse eigenvalue problems
International Nuclear Information System (INIS)
Meyer, A.
1987-01-01
The volume is written for mathematicians interested in (numerical) linear algebra and in the solution of large sparse eigenvalue problems, as well as for specialists in engineering, who use the considered algorithms in the investigation of eigenoscillations of structures, in reactor physics, etc. Some variants of the algorithms based on the idea of a gradient-type direction of movement are presented and their convergence properties are discussed. From this, a general strategy for the direct use of preconditionings for the eigenvalue problem is derived. In this new approach the necessity of the solution of large linear systems is entirely avoided. Hence, these methods represent a new alternative to some other modern eigenvalue algorithms, as they show a slightly slower convergence on the one hand but essentially lower numerical and data processing problems on the other hand. A brief description and comparison of some well-known methods (i.e. simultaneous iteration, Lanczos algorithm) completes this volume. (author)
Sparse random matrices: The eigenvalue spectrum revisited
International Nuclear Information System (INIS)
Semerjian, Guilhem; Cugliandolo, Leticia F.
2003-08-01
We revisit the derivation of the density of states of sparse random matrices. We derive a recursion relation that allows one to compute the spectrum of the matrix of incidence for finite trees that determines completely the low concentration limit. Using the iterative scheme introduced by Biroli and Monasson [J. Phys. A 32, L255 (1999)] we find an approximate expression for the density of states expected to hold exactly in the opposite limit of large but finite concentration. The combination of the two methods yields a very simple geometric interpretation of the tails of the spectrum. We test the analytic results with numerical simulations and we suggest an indirect numerical method to explore the tails of the spectrum. (author)
ESTIMATION OF FUNCTIONALS OF SPARSE COVARIANCE MATRICES.
Fan, Jianqing; Rigollet, Philippe; Wang, Weichen
High-dimensional statistical tests often ignore correlations to gain simplicity and stability leading to null distributions that depend on functionals of correlation matrices such as their Frobenius norm and other ℓ r norms. Motivated by the computation of critical values of such tests, we investigate the difficulty of estimation the functionals of sparse correlation matrices. Specifically, we show that simple plug-in procedures based on thresholded estimators of correlation matrices are sparsity-adaptive and minimax optimal over a large class of correlation matrices. Akin to previous results on functional estimation, the minimax rates exhibit an elbow phenomenon. Our results are further illustrated in simulated data as well as an empirical study of data arising in financial econometrics.
Miniature Laboratory for Detecting Sparse Biomolecules
Lin, Ying; Yu, Nan
2005-01-01
A miniature laboratory system has been proposed for use in the field to detect sparsely distributed biomolecules. By emphasizing concentration and sorting of specimens prior to detection, the underlying system concept would make it possible to attain high detection sensitivities without the need to develop ever more sensitive biosensors. The original purpose of the proposal is to aid the search for signs of life on a remote planet by enabling the detection of specimens as sparse as a few molecules or microbes in a large amount of soil, dust, rocks, water/ice, or other raw sample material. Some version of the system could prove useful on Earth for remote sensing of biological contamination, including agents of biological warfare. Processing in this system would begin with dissolution of the raw sample material in a sample-separation vessel. The solution in the vessel would contain floating microscopic magnetic beads coated with substances that could engage in chemical reactions with various target functional groups that are parts of target molecules. The chemical reactions would cause the targeted molecules to be captured on the surfaces of the beads. By use of a controlled magnetic field, the beads would be concentrated in a specified location in the vessel. Once the beads were thus concentrated, the rest of the solution would be discarded. This procedure would obviate the filtration steps and thereby also eliminate the filter-clogging difficulties of typical prior sample-concentration schemes. For ferrous dust/soil samples, the dissolution would be done first in a separate vessel before the solution is transferred to the microbead-containing vessel.
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
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.
A Harmonic Algorithm for the 3D Strip Packing Problem
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
27 CFR 24.308 - Bottled or packed wine record.
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...
Electrokinetics in porous media
Luong, D.T.
2014-01-01
This thesis presents the PhD research on electrokinetics in porous media. Electrokinetic phenomena are induced by the relative motion between a fluid and a solid surface and are directly related to the existence of an electric double layer between the fluid and the solid grain surface.
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)
Coalescence preference in dense packing of bubbles
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).
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)
Permeability model of sintered porous media: analysis and experiments
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.
Biomass plug development and propagation in porous media.
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
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.
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.
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...
Support agnostic Bayesian matching pursuit for block sparse signals
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
Local posterior concentration rate for multilevel sparse sequences
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
Joint Group Sparse PCA for Compressed Hyperspectral Imaging.
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.
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...
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....
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.
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
Generalized network improvement and packing problems
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.
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.
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.
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...
Used fuel packing plant for CANDU fuel
Energy Technology Data Exchange (ETDEWEB)
Menzies, I.; Thayer, B.; Bains, N., E-mail: imenzies@atsautomation.com [ATS Automation, Cambridge, ON (Canada); Murchison, A., E-mail: amurchison@nwmo.ca [NWMO, Toronto, ON (Canada)
2015-07-01
Large forgings have been selected to containerize Light Water Reactor used nuclear fuel. CANDU fuel, which is significantly smaller in size, allows novel approaches for containerization. For example, by utilizing commercially available extruded ASME pipe a conceptual design of a Used Fuel Packing Plant for containerization of used CANDU fuel in a long lived metallic container has been developed. The design adopts a modular approach with multiple independent work cells to transfer and containerize the used fuel. Based on current technologies and concepts from proven industrial systems, the Used Fuel Packing Plant can assemble twelve used fuel containers per day considering conservative levels of process availability. (author)
Relaxations to Sparse Optimization Problems and Applications
Skau, Erik West
Parsimony is a fundamental property that is applied to many characteristics in a variety of fields. Of particular interest are optimization problems that apply rank, dimensionality, or support in a parsimonious manner. In this thesis we study some optimization problems and their relaxations, and focus on properties and qualities of the solutions of these problems. The Gramian tensor decomposition problem attempts to decompose a symmetric tensor as a sum of rank one tensors.We approach the Gramian tensor decomposition problem with a relaxation to a semidefinite program. We study conditions which ensure that the solution of the relaxed semidefinite problem gives the minimal Gramian rank decomposition. Sparse representations with learned dictionaries are one of the leading image modeling techniques for image restoration. When learning these dictionaries from a set of training images, the sparsity parameter of the dictionary learning algorithm strongly influences the content of the dictionary atoms.We describe geometrically the content of trained dictionaries and how it changes with the sparsity parameter.We use statistical analysis to characterize how the different content is used in sparse representations. Finally, a method to control the structure of the dictionaries is demonstrated, allowing us to learn a dictionary which can later be tailored for specific applications. Variations of dictionary learning can be broadly applied to a variety of applications.We explore a pansharpening problem with a triple factorization variant of coupled dictionary learning. Another application of dictionary learning is computer vision. Computer vision relies heavily on object detection, which we explore with a hierarchical convolutional dictionary learning model. Data fusion of disparate modalities is a growing topic of interest.We do a case study to demonstrate the benefit of using social media data with satellite imagery to estimate hazard extents. In this case study analysis we
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.
Sparse alignment for robust tensor learning.
Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Zhao, Cairong; Sun, Mingming
2014-10-01
Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods, L1- and L2-norms are introduced to enhance the robustness in the alignment step of the STA. The advantage of the proposed technique is that the difficulty in selecting the size of the local neighborhood can be avoided in the manifold learning based tensor feature extraction algorithms. Although STA is an unsupervised learning method, the sparsity encodes the discriminative information in the alignment step and provides the robustness of STA. Extensive experiments on the well-known image databases as well as action and hand gesture databases by encoding object images as tensors demonstrate that the proposed STA algorithm gives the most competitive performance when compared with the tensor-based unsupervised learning methods.
Regression analysis of sparse asynchronous longitudinal data.
Cao, Hongyuan; Zeng, Donglin; Fine, Jason P
2015-09-01
We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are proposed for generalized linear models with either time invariant or time-dependent coefficients under smoothness assumptions for the covariate processes which are similar to those for synchronous data. For models with either time invariant or time-dependent coefficients, the estimators are consistent and asymptotically normal but converge at slower rates than those achieved with synchronous data. Simulation studies evidence that the methods perform well with realistic sample sizes and may be superior to a naive application of methods for synchronous data based on an ad hoc last value carried forward approach. The practical utility of the methods is illustrated on data from a study on human immunodeficiency virus.
Duplex scanning using sparse data sequences
DEFF Research Database (Denmark)
Møllenbach, S. K.; Jensen, Jørgen Arendt
2008-01-01
reconstruction of the missing samples possible. The periodic pattern has the length T = M + A samples, where M are for B-mode and A for velocity estimation. The missing samples can now be reconstructed using a filter bank. One filter bank reconstructs one missing sample, so the number of filter banks corresponds...... to M. The number of sub filters in every filter bank is the same as A. Every sub filter contains fractional delay (FD) filter and an interpolation function. Many different sequences can be selected to adapt the B-mode frame rate needed. The drawback of the method is that the maximum velocity detectable......, the fprf and the resolution are 15 MHz, 3.5 kHz, and 12 bit sample (8 kHz and 16 bit for the Carotid artery). The resulting data contains 8000 RF lines with 128 samples at a depth of 45 mm for the vein and 50 mm for Aorta. Sparse sequences are constructed from the full data sequences to have both...
Transformer fault diagnosis using continuous sparse autoencoder.
Wang, Lukun; Zhao, Xiaoying; Pei, Jiangnan; Tang, Gongyou
2016-01-01
This paper proposes a novel continuous sparse autoencoder (CSAE) which can be used in unsupervised feature learning. The CSAE adds Gaussian stochastic unit into activation function to extract features of nonlinear data. In this paper, CSAE is applied to solve the problem of transformer fault recognition. Firstly, based on dissolved gas analysis method, IEC three ratios are calculated by the concentrations of dissolved gases. Then IEC three ratios data is normalized to reduce data singularity and improve training speed. Secondly, deep belief network is established by two layers of CSAE and one layer of back propagation (BP) network. Thirdly, CSAE is adopted to unsupervised training and getting features. Then BP network is used for supervised training and getting transformer fault. Finally, the experimental data from IEC TC 10 dataset aims to illustrate the effectiveness of the presented approach. Comparative experiments clearly show that CSAE can extract features from the original data, and achieve a superior correct differentiation rate on transformer fault diagnosis.
Joint Sparse Recovery With Semisupervised MUSIC
Wen, Zaidao; Hou, Biao; Jiao, Licheng
2017-05-01
Discrete multiple signal classification (MUSIC) with its low computational cost and mild condition requirement becomes a significant noniterative algorithm for joint sparse recovery (JSR). However, it fails in rank defective problem caused by coherent or limited amount of multiple measurement vectors (MMVs). In this letter, we provide a novel sight to address this problem by interpreting JSR as a binary classification problem with respect to atoms. Meanwhile, MUSIC essentially constructs a supervised classifier based on the labeled MMVs so that its performance will heavily depend on the quality and quantity of these training samples. From this viewpoint, we develop a semisupervised MUSIC (SS-MUSIC) in the spirit of machine learning, which declares that the insufficient supervised information in the training samples can be compensated from those unlabeled atoms. Instead of constructing a classifier in a fully supervised manner, we iteratively refine a semisupervised classifier by exploiting the labeled MMVs and some reliable unlabeled atoms simultaneously. Through this way, the required conditions and iterations can be greatly relaxed and reduced. Numerical experimental results demonstrate that SS-MUSIC can achieve much better recovery performances than other MUSIC extended algorithms as well as some typical greedy algorithms for JSR in terms of iterations and recovery probability.
SLAP, Large Sparse Linear System Solution Package
International Nuclear Information System (INIS)
Greenbaum, A.
1987-01-01
1 - Description of program or function: SLAP is a set of routines for solving large sparse systems of linear equations. One need not store the entire matrix - only the nonzero elements and their row and column numbers. Any nonzero structure is acceptable, so the linear system solver need not be modified when the structure of the matrix changes. Auxiliary storage space is acquired and released within the routines themselves by use of the LRLTRAN POINTER statement. 2 - Method of solution: SLAP contains one direct solver, a band matrix factorization and solution routine, BAND, and several interactive solvers. The iterative routines are as follows: JACOBI, Jacobi iteration; GS, Gauss-Seidel Iteration; ILUIR, incomplete LU decomposition with iterative refinement; DSCG and ICCG, diagonal scaling and incomplete Cholesky decomposition with conjugate gradient iteration (for symmetric positive definite matrices only); DSCGN and ILUGGN, diagonal scaling and incomplete LU decomposition with conjugate gradient interaction on the normal equations; DSBCG and ILUBCG, diagonal scaling and incomplete LU decomposition with bi-conjugate gradient iteration; and DSOMN and ILUOMN, diagonal scaling and incomplete LU decomposition with ORTHOMIN iteration
Nield, Donald A
2013-01-01
Convection in Porous Media, 4th Edition, provides a user-friendly introduction to the subject, covering a wide range of topics, such as fibrous insulation, geological strata, and catalytic reactors. The presentation is self-contained, requiring only routine mathematics and the basic elements of fluid mechanics and heat transfer. The book will be of use not only to researchers and practicing engineers as a review and reference, but also to graduate students and others entering the field. The new edition features approximately 1,750 new references and covers current research in nanofluids, cellular porous materials, strong heterogeneity, pulsating flow, and more. Recognized as the standard reference in the field Includes a comprehensive, 250-page reference list Cited over 2300 times to date in its various editions Serves as an introduction for those entering the field and as a comprehensive reference for experienced researchers Features new sections on nanofluids, carbon dioxide sequestration, and applications...
Porous electrode preparation method
Arons, R.M.; Dusek, J.T.
1983-10-18
A porous sintered plaque is provided with a bimodal porosity that is especially well suited for use as an electrode within a molten carbonate fuel cell. The coarse porosity is sufficient for admitting gases into contact with the reaction surfaces while the fine porosity is wetted with and retains molten electrolyte on the reaction sites. The electrode structure is prepared by providing a very fine powder of such as nickel oxide and blending the powder with a suitable decomposable binder to form a solid mass. The mass is comminuted into agglomerate size particles substantially larger than the fine oxide particles and formed into a cohesive compact for subsequent sintering. Sintering is carried out at sufficient conditions to bind the agglomerates together into a porous structure having both coarse and fine porosity. Where lithiated nickel oxide cathodes are prepared, the sintering conditions can be moderate enough to retain substantial quantities of lithium within the electrode for adequate conductivity. 2 figs.
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
Energy Technology Data Exchange (ETDEWEB)
Garralaga Rojas, Enrique; Hensen, Jan; Brendel, Rolf [Institut fuer Solarenergieforschung Hameln (ISFH), Emmerthal (Germany); Carstensen, Juergen; Foell, Helmut [Chair for General Materials Science, Faculty of Engineering, Christian-Albrechts-University of Kiel (Germany)
2011-06-15
We present the reproducible fabrication of porous germanium (PGe) single- and multilayers. Mesoporous layers form on heavily doped 4'' p-type Ge wafers by electrochemical etching in highly concentrated HF-based electrolytes with concentrations in a range of 30-50 wt.%. Direct PGe formation is accompanied by a constant dissolution of the already-formed porous layer at the electrolyte/PGe interface, hence yielding a thinner substrate after etching. This effect inhibits multilayer formation as the starting layer is etched while forming the second layer. We avoid dissolution of the porous layer by alternating the etching bias from anodic to cathodic. PGe formation occurs during anodic etching whereas the cathodic step passivates pore walls with H-atoms and avoids electropolishing. The passivation lasts a limited time depending on the etching current density and electrolyte concentration, necessitating a repetition of the cathodic step at suitable intervals. With optimized alternating bias mesoporous multilayer production is possible. We control the porosity of each single layer by varying the etching current density and the electrolyte (copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Random close packing in protein cores.
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.
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.
Importance of packing in spiral defect chaos
Indian Academy of Sciences (India)
We develop two measures to characterize the geometry of patterns exhibited by the state of spiral defect chaos, a weakly turbulent regime of Rayleigh-Bénard convection. These describe the packing of contiguous stripes within the pattern by quantifying their length and nearest-neighbor distributions. The distributions ...
Wrap-Attack Pack: Product Packaging Exercise
Lee, Seung Hwan; Hoffman, K. Douglas
2016-01-01
Although many marketing courses discuss traditional concepts pertaining to product strategy, concepts specifically relating to packaging are often glossed over. This exercise, "Wrap-Attack Pack," teaches students about the utilitarian and hedonic design elements of packaging. More specifically, the primary objective is to creatively…
Simple Cloud Chambers Using Gel Ice Packs
Kamata, Masahiro; Kubota, Miki
2012-01-01
Although cloud chambers are highly regarded as teaching aids for radiation education, school teachers have difficulty in using cloud chambers because they have to prepare dry ice or liquid nitrogen before the experiment. We developed a very simple and inexpensive cloud chamber that uses the contents of gel ice packs which can substitute for dry…
The new generation of packing materials
International Nuclear Information System (INIS)
Malikov, T.S.; Dzhonmurodov, A.S.; Usmanova, S.R.; Teshaev, Kh.I.; Mukhidinov, Z.K.
2016-01-01
Present article is devoted to new generation of packing materials. The methods of extraction and investigation of component composition and properties of whey protein, zein, carboxymethylcellulose, hyaluronic acid and pectins were elaborated in order to further application them in pharmaceutical industry as composite materials and for capsulation of medicines.
Packing frustration in dense confined fluids.
Nygård, Kim; Sarman, Sten; Kjellander, Roland
2014-09-07
Packing frustration for confined fluids, i.e., the incompatibility between the preferred packing of the fluid particles and the packing constraints imposed by the confining surfaces, is studied for a dense hard-sphere fluid confined between planar hard surfaces at short separations. The detailed mechanism for the frustration is investigated via an analysis of the anisotropic pair distributions of the confined fluid, as obtained from integral equation theory for inhomogeneous fluids at pair correlation level within the anisotropic Percus-Yevick approximation. By examining the mean forces that arise from interparticle collisions around the periphery of each particle in the slit, we calculate the principal components of the mean force for the density profile--each component being the sum of collisional forces on a particle's hemisphere facing either surface. The variations of these components with the slit width give rise to rather intricate changes in the layer structure between the surfaces, but, as shown in this paper, the basis of these variations can be easily understood qualitatively and often also semi-quantitatively. It is found that the ordering of the fluid is in essence governed locally by the packing constraints at each single solid-fluid interface. A simple superposition of forces due to the presence of each surface gives surprisingly good estimates of the density profiles, but there remain nontrivial confinement effects that cannot be explained by superposition, most notably the magnitude of the excess adsorption of particles in the slit relative to bulk.
The benefits of using customized procedure packs.
Baines, R; Colquhoun, G; Jones, N; Bateman, R
2001-01-01
Discrete item purchasing is the traditional approach for hospitals to obtain consumable supplies for theatre procedures. Although most items are relatively low cost, the management and co-ordination of the supply chain, raising orders, controlling stock, picking and delivering to each operating theatre can be complex and costly. Customized procedure packs provide a solution.
Object tracking by occlusion detection via structured sparse learning
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.
Manifold regularization for sparse unmixing of hyperspectral images.
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.
Infill Optimization for Additive Manufacturing-Approaching Bone-Like Porous Structures.
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.
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.
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...
Electromagnetic Formation Flight (EMFF) for Sparse Aperture Arrays
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.
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...
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.
Column-to-column packing variation of disposable pre-packed columns for protein chromatography.
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.
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
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.
Gonzalo-Lumbreras, Raquel; Sanz-Landaluze, Jon; Cámara, Carmen
2015-07-01
The behavior of 15 benzimidazoles, including their main metabolites, using several C18 columns with standard or narrow-bore diameters and different particle size and type were evaluated. These commercial columns were selected because their differences could affect separation of benzimidazoles, and so they can be used as alternative columns. A simple screening method for the analysis of benzimidazole residues and their main metabolites was developed. First, the separation of benzimidazoles was optimized using a Kinetex C18 column; later, analytical performances of other columns using the above optimized conditions were compared and then individually re-optimized. Critical pairs resolution, analysis run time, column type and characteristics, and selectivity were considered for chromatographic columns comparison. Kinetex XB was selected because it provides the shortest analysis time and the best resolution of critical pairs. Using this column, the separation conditions were re-optimized using a factorial design. Separations obtained with the different columns tested can be applied to the analysis of specific benzimidazoles residues or other applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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.
High Order Tensor Formulation for Convolutional Sparse Coding
Bibi, Adel Aamer; Ghanem, Bernard
2017-01-01
Convolutional sparse coding (CSC) has gained attention for its successful role as a reconstruction and a classification tool in the computer vision and machine learning community. Current CSC methods can only reconstruct singlefeature 2D images
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
Desmal, Abdulla; Bagci, Hakan
2014-01-01
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
Multiple instance learning tracking method with local sparse representation
Xie, Chengjun; Tan, Jieqing; Chen, Peng; Zhang, Jie; Helg, Lei
2013-01-01
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
Low-rank sparse learning for robust visual tracking
Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra
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
Robust visual tracking via multi-task sparse learning
Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra
2012-01-01
In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates
Sparse Machine Learning Methods for Understanding Large Text Corpora
National Aeronautics and Space Administration — Sparse machine learning has recently emerged as powerful tool to obtain models of high-dimensional data with high degree of interpretability, at low computational...
Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering
Sicat, Ronell Barrera; Kruger, Jens; Moller, Torsten; Hadwiger, Markus
2014-01-01
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
Sparse Linear Solver for Power System Analysis Using FPGA
National Research Council Canada - National Science Library
Johnson, J. R; Nagvajara, P; Nwankpa, C
2005-01-01
.... Numerical solution to load flow equations are typically computed using Newton-Raphson iteration, and the most time consuming component of the computation is the solution of a sparse linear system...
Support agnostic Bayesian matching pursuit for block sparse signals
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.
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.
Sparse logistic principal components analysis for binary data
Lee, Seokho; Huang, Jianhua Z.; Hu, Jianhua
2010-01-01
with a criterion function motivated from a penalized Bernoulli likelihood. A Majorization-Minimization algorithm is developed to efficiently solve the optimization problem. The effectiveness of the proposed sparse logistic PCA method is illustrated
Sparse reconstruction using distribution agnostic bayesian matching pursuit
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.
Occlusion detection via structured sparse learning for robust object tracking
Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra
2014-01-01
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
Object tracking by occlusion detection via structured sparse learning
Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra
2013-01-01
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
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....
Sparse encoding of automatic visual association in hippocampal networks
DEFF Research Database (Denmark)
Hulme, Oliver J; Skov, Martin; Chadwick, Martin J
2014-01-01
Intelligent action entails exploiting predictions about associations between elements of ones environment. The hippocampus and mediotemporal cortex are endowed with the network topology, physiology, and neurochemistry to automatically and sparsely code sensori-cognitive associations that can...
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.
Heavy metals in the snow pack of Semey town
International Nuclear Information System (INIS)
Panin, M.S.; Esenzholova, A.Zh.; Toropov, A.S.
2008-01-01
The data about the maintenance of heavy metals in the snow pack in various zones of Semey and biogeochemical operation factors of snow pack in Semey are presented in this work. Also the correlation connection between elements is calculated.
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...
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
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 ...
Packing of equal discs on a parabolic spiral lattice
International Nuclear Information System (INIS)
Xudong, F.; Bursill, L.A.; Julin, P.
1989-01-01
A contact disc model is investigated to determine the most closely-packed parabolic spiral lattice. The most space-efficient packings have divergence angles in agreement with the priority ranking of natural spiral structures
Efficient collaborative sparse channel estimation in massive MIMO
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.
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
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.
Efficient collaborative sparse channel estimation in massive MIMO
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.
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.
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
In-Storage Embedded Accelerator for Sparse Pattern Processing
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...
Occlusion detection via structured sparse learning for robust object tracking
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.
Exhaustive Search for Sparse Variable Selection in Linear Regression
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.
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.
Structure-aware Local Sparse Coding for Visual Tracking
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.
Vector sparse representation of color image using quaternion matrix analysis.
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.
Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging
Desmal, Abdulla
2016-03-01
synthetically generated or actually measured scattered fields, show that the images recovered by these sparsity-regularized methods are sharper and more accurate than those produced by existing methods. The methods developed in this work have potential application areas ranging from oil/gas reservoir engineering to biological imaging where sparse domains naturally exist.
Imaging of drug smuggling by body packing.
Sica, Giacomo; Guida, Franco; Bocchini, Giorgio; Iaselli, Francesco; Iadevito, Isabella; Scaglione, Mariano
2015-02-01
Body packing, pushing, and stuffing are hazardous practices with complex medicolegal and social implications. A radiologist plays both a social and a medicolegal role in their assessment, and it should not be limited only to the identification of the packages but must also provide accurate information about their number and their exact location so as to prevent any package remains in the body packer. Radiologists must also be able to recognize the complications associated with these risky practices. Imaging assessment of body packing is performed essentially through plain abdominal X-ray and computed tomography scans. Ultrasound and magnetic resonance imaging, although with some advantages, actually have a limited use. Copyright © 2014 Elsevier Inc. All rights reserved.
Packing and Disorder in Substituted Fullerenes
Tummala, Naga Rajesh
2016-07-15
Fullerenes are ubiquitous as electron-acceptor and electron-transport materials in organic solar cells. Recent synthetic strategies to improve the solubility and electronic characteristics of these molecules have translated into a tremendous increase in the variety of derivatives employed in these applications. Here, we use molecular dynamics (MD) simulations to examine the impact of going from mono-adducts to bis- and tris-adducts on the structural, cohesive, and packing characteristics of [6,6]-phenyl-C60-butyric acid methyl ester (PCBM) and indene-C60. The packing configurations obtained at the MD level then serve as input for density functional theory calculations that examine the solid-state energetic disorder (distribution of site energies) as a function of chemical substitution. The variations in structural and site-energy disorders reflect the fundamental materials differences among the derivatives and impact the performance of these materials in thin-film electronic devices.
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.)
School meal sociality or lunch pack individualism?
DEFF Research Database (Denmark)
Andersen, Sidse Schoubye; Holm, Lotte; Baarts, Charlotte
2015-01-01
the social life of a school class, and how these arrangements involve strategies of both inclusion and exclusion. Two types of school meals are compared in the intervention study: a hot meal based on Nordic ingredients and the normal Danish school meal arrangement in which children bring lunch packs...... to school. The study discusses commensality by examining and comparing lunchtime interactions within the same group of children in the two contrasting meal situations. The results fail to confirm the conventional view that shared meals have greater social impacts and benefits than eating individualized...... foods. The article argues that the social entrepreneurship involved in sharing individual lunch packs might even outweigh some of the benefits of shared meals where everyone is served the same food....
Optical performance of hybrid porous silicon-porous alumina multilayers
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.
On the perfect hexagonal packing of rods
International Nuclear Information System (INIS)
Starostin, E L
2006-01-01
In most cases the hexagonal packing of fibrous structures or rods extremizes the energy of interaction between strands. If the strands are not straight, then it is still possible to form a perfect hexatic bundle. Conditions under which the perfect hexagonal packing of curved tubular structures may exist are formulated. Particular attention is given to closed or cycled arrangements of the rods like in the DNA toroids and spools. The closure or return constraints of the bundle result in an allowable group of automorphisms of the cross-sectional hexagonal lattice. The structure of this group is explored. Examples of open helical-like and closed toroidal-like bundles are presented. An expression for the elastic energy of a perfectly packed bundle of thin elastic rods is derived. The energy accounts for both the bending and torsional stiffnesses of the rods. It is shown that equilibria of the bundle correspond to solutions of a variational problem formulated for the curve representing the axis of the bundle. The functional involves a function of the squared curvature under the constraints on the total torsion and the length. The Euler-Lagrange equations are obtained in terms of curvature and torsion and due to the existence of the first integrals the problem is reduced to the quadrature. The three-dimensional shape of the bundle may be readily reconstructed by integration of the Ilyukhin-type equations in special cylindrical coordinates. The results are of universal nature and are applicable to various fibrous structures, in particular, to intramolecular liquid crystals formed by DNA condensed in toroids or packed inside the viral capsids
36 CFR 1002.16 - Horses and pack animals.
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 34.10 - Saddle and pack animals.
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. ...
36 CFR 2.16 - Horses and pack animals.
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...
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.
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...
Evaluation of Type II Fast Packs for Electrostatic Discharge Properties.
1983-08-01
34 x 8" x 1 3/4") consisting of a reclosable cushioned carrier which mates into an outer fiberboard sleeve. A cushioning insert is used consisting of a... RECLOSABLE CUSHIONED CARRIER TEST LOAD FIGURE 1: Cancel Caddy Pack * CONVOLUTED 4* CUSHIONED I FIGURE 2: Type II Fast Pack (PPP-B-1672) TYPE II FAST PACK
21 CFR 133.124 - Cold-pack cheese food.
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...
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...
48 CFR 552.211-87 - Export packing.
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...
Symmetric scrolled packings of multilayered carbon nanoribbons
Savin, A. V.; Korznikova, E. A.; Lobzenko, I. P.; Baimova, Yu. A.; Dmitriev, S. V.
2016-06-01
Scrolled packings of single-layer and multilayer graphene can be used for the creation of supercapacitors, nanopumps, nanofilters, and other nanodevices. The full atomistic simulation of graphene scrolls is restricted to consideration of relatively small systems in small time intervals. To overcome this difficulty, a two-dimensional chain model making possible an efficient calculation of static and dynamic characteristics of nanoribbon scrolls with allowance for the longitudinal and bending stiffness of nanoribbons is proposed. The model is extended to the case of scrolls of multilayer graphene. Possible equilibrium states of symmetric scrolls of multilayer carbon nanotribbons rolled up so that all nanoribbons in the scroll are equivalent are found. Dependences of the number of coils, the inner and outer radii, lowest vibrational eigenfrequencies of rolled packages on the length L of nanoribbons are obtained. It is shown that the lowest vibrational eigenfrequency of a symmetric scroll decreases with a nanoribbon length proportionally to L -1. It is energetically unfavorable for too short nanoribbons to roll up, and their ground state is a stack of plane nanoribbons. With an increasing number k of layers, the nanoribbon length L necessary for creation of symmetric scrolls increases. For a sufficiently small number of layers k and a sufficiently large nanoribbon length L, the scrolled packing has the lowest energy as compared to that of stack of plane nanoribbons and folded structures. The results can be used for development of nanomaterials and nanodevices on the basis of graphene scrolled packings.
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
Numerical analyses on the effect of capillary condensation on gas diffusivities in porous media
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.
New raw materials improve packing sealing efficiency
International Nuclear Information System (INIS)
Igel, B.; McKeague, L.
2012-01-01
End-users and OEM's using or manufacturing on/off and control valves expect a permanent and effective increase in service life together with an increased sealing capability while at the same time minimizing maintenance concerns. Developing materials which provide consistency and repeatability are essential characteristics to optimizing valve performance. “New Generation” materials and yarn allow us to meet this growing demand while complying with the requirements related to chemical purity and an increased level of safety to both plant workers and equipment in the nuclear environment. Through R&D initiatives and developments in new and improved raw materials; a new mechanical packing generation which optimizes friction coefficients and extended life cycle has been introduced to the industry. Lower friction values drastically optimize actuator effort and size improving efficiency for stem operation with significant improvements in flow control of fluids. Combined with new and improved procedures (installation, torque levels and consolidation recommendations), this new packing generation has provided significant improvement in the mechanical behavior of packing materials (independent tests carried out in collaboration with AECL and CETIM) this has provided the opportunity to develop successful Valve Enhancement Programs which offer improved efficiency, valve operation and repeatability. These NEW generation yarns are available with or without wire reinforcement depending on specific operating parameters and conditions. The purpose of this presentation is to demonstrate that new generation material(s). Which are available to the industry for AOV, MOV and Manual valves? - To highlight the steps taken in R&D and manufacturing contributing to the much improved yarns and finished packing products. - Comply and are designed to meet the stringent requirements in the nuclear industry - Simplify valve maintenance without risk to safety or performance - Increase service
The mechanical behaviour of packed particulates
International Nuclear Information System (INIS)
Dutton, R.
1998-01-01
Within the Canadian Nuclear Fuel Waste Management program, the central concept is to package used fuel in containers that would be deposited in an underground vault in a plutonic rock formation. To provide internal mechanical support for the container, the reference design specifies it to be filled with a matrix of compacted particulate material (called 'packed particulate'), such as quartz sand granules. The focus of this report is on the mechanical properties of the packed-particulate material, based on information drawn from the extant literature. We first consider the packing density of particulate matrices to minimize the remnant porosity and maximize mechanical stability under conditions of external pressure. Practical methods, involving vibratory packing, are reviewed and recommendations made to select techniques to achieve optimum packing density. The behaviour of particulates under compressive loading has been of interest to the powder metallurgy industry (i.e., the manufacture of products from pressed/sintered metal and ceramic powders) since the early decades of this century. We review the evidence showing that in short timescales, stress induced compaction occurs by particle shuffling and rearrangement, elastic distortion, plastic yielding and microfracturing. Analytical expressions are available to describe these processes in a semiquantitative fashion. Time-dependent compaction, mainly via creep mechanisms, is more complex. Much of the theoretical and experimental information is confined to higher temperatures (> 500 degrees C), where deformation rates are more rapid. Thus, for the relatively low ambient temperatures of the waste container (∼100 degrees C), we require analytical techniques to extrapolate the collective particulate creep behaviour. This is largely accomplished by employing current theories of creep deformation, particularly in the form of Deformation Mechanism Maps, which allow estimation of creep rates over a wide range of stress
The mechanical behaviour of packed particulates
Energy Technology Data Exchange (ETDEWEB)
Dutton, R
1998-01-01
Within the Canadian Nuclear Fuel Waste Management program, the central concept is to package used fuel in containers that would be deposited in an underground vault in a plutonic rock formation. To provide internal mechanical support for the container, the reference design specifies it to be filled with a matrix of compacted particulate material (called 'packed particulate'), such as quartz sand granules. The focus of this report is on the mechanical properties of the packed-particulate material, based on information drawn from the extant literature. We first consider the packing density of particulate matrices to minimize the remnant porosity and maximize mechanical stability under conditions of external pressure. Practical methods, involving vibratory packing, are reviewed and recommendations made to select techniques to achieve optimum packing density. The behaviour of particulates under compressive loading has been of interest to the powder metallurgy industry (i.e., the manufacture of products from pressed/sintered metal and ceramic powders) since the early decades of this century. We review the evidence showing that in short timescales, stress induced compaction occurs by particle shuffling and rearrangement, elastic distortion, plastic yielding and microfracturing. Analytical expressions are available to describe these processes in a semiquantitative fashion. Time-dependent compaction, mainly via creep mechanisms, is more complex. Much of the theoretical and experimental information is confined to higher temperatures (> 500 degrees C), where deformation rates are more rapid. Thus, for the relatively low ambient temperatures of the waste container ({approx}100 degrees C), we require analytical techniques to extrapolate the collective particulate creep behaviour. This is largely accomplished by employing current theories of creep deformation, particularly in the form of Deformation Mechanism Maps, which allow estimation of creep rates over a wide
HETP evaluation of structured packing distillation column
Directory of Open Access Journals (Sweden)
A. E. Orlando Jr.
2009-09-01
Full Text Available Several tests with a hydrocarbon mixture of known composition (C8-C14, obtained from DETEN Chemistry S.A., have been performed in a laboratory distillation column, having 40mm of nominal diameter and 2.2m high, with internals of Sulzer DX gauze stainless steel structured packing. The main purpose of this work was to evaluate HETP of a structured packing laboratory scale distillation column, operating continuously. Six HETP correlations available in the literature were compared in order to find out which is the most appropriate for structured packing columns working with medium distillates. Prior to the experimental tests, simulation studies using commercial software PRO/II® were performed in order to establish the optimum operational conditions for the distillation, especially concerning operating pressure, top and bottom temperatures, feed location and reflux ratio. The results of PRO/II® were very similar to the analysis of the products obtained during continuous operation, therefore permitting the use of the properties calculated by that software on the theoretical models investigated. The theoretical models chosen for HETP evaluation were: Bravo, Rocha and Fair (1985; Rocha, Bravo and Fair (1993, 1996; Brunazzi and Pagliant (1997; Carlo, Olujić and Pagliant (2006; Olujić et al., (2004. Modifications concerning calculation of specific areas were performed on the correlations in order to fit them for gauze packing HETP evaluation. As the laboratory distillation column was operated continuously, different HETP values were found by the models investigated for each section of the column. The low liquid flow rates in the top section of the column are a source of error for HETP evaluation by the models; therefore, more reliable HETP values were found in the bottom section, in which liquid flow rates were much greater. Among the theoretical models, Olujić et al. (2004 has shown good results relative to the experimental tests. In addition, the
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.
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.
Sparse modeling of spatial environmental variables associated with asthma.
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.
Nanoparticle tracers in calcium carbonate porous media
Li, Yan Vivian
2014-07-15
Tracers are perhaps the most direct way of diagnosing subsurface fluid flow pathways for ground water decontamination and for natural gas and oil production. Nanoparticle tracers could be particularly effective because they do not diffuse away from the fractures or channels where flow occurs and thus take much less time to travel between two points. In combination with a chemical tracer they can measure the degree of flow concentration. A prerequisite for tracer applications is that the particles are not retained in the porous media as the result of aggregation or sticking to mineral surfaces. By screening eight nanoparticles (3-100 nm in diameter) for retention when passed through calcium carbonate packed laboratory columns in artificial oil field brine solutions of variable ionic strength we show that the nanoparticles with the least retention are 3 nm in diameter, nearly uncharged, and decorated with highly hydrophilic polymeric ligands. The details of these column experiments and the tri-modal distribution of zeta potential of the calcite sand particles in the brine used in our tests suggests that parts of the calcite surface have positive zeta potential and the retention of negatively charged nanoparticles occurs at these sites. Only neutral nanoparticles are immune to at least some retention. © 2014 Springer Science+Business Media.
Structural characterization of the packings of granular regular polygons.
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.
Image fusion via nonlocal sparse K-SVD dictionary learning.
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.
Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.
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.
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
X-ray computed tomography using curvelet sparse regularization.
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.
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.
Low-count PET image restoration using sparse representation
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.
Sparse BLIP: BLind Iterative Parallel imaging reconstruction using compressed sensing.
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.
Nield, Donald A
1992-01-01
This book provides a user-friendly introduction to the topic of convection in porous media The authors as- sume that the reader is familiar with the basic elements of fluid mechanics and heat transfer, but otherwise the book is self-contained The book will be useful both as a review (for reference) and as a tutorial work, suitable as a textbook in a graduate course or seminar The book brings into perspective the voluminous research that has been performed during the last two decades The field has recently exploded because of worldwide concern with issues such as energy self-sufficiency and pollution of the environment Areas of application include the insulation of buildings and equipment, energy storage and recovery, geothermal reservoirs, nuclear waste disposal, chemical reactor engineering, and the storage of heat-generating materials such as grain and coal Geophysical applications range from the flow of groundwater around hot intrusions to the stability of snow against avalanches
Optimized manufacturable porous materials
DEFF Research Database (Denmark)
Andreassen, Erik; Andreasen, Casper Schousboe; Jensen, Jakob Søndergaard
Topology optimization has been used to design two-dimensional material structures with specific elastic properties, but optimized designs of three-dimensional material structures are more scarsely seen. Partly because it requires more computational power, and partly because it is a major challenge...... to include manufacturing constraints in the optimization. This work focuses on incorporating the manufacturability into the optimization procedure, allowing the resulting material structure to be manufactured directly using rapid manufacturing techniques, such as selective laser melting/sintering (SLM....../S). The available manufacturing methods are best suited for porous materials (one constituent and void), but the optimization procedure can easily include more constituents. The elasticity tensor is found from one unit cell using the homogenization method together with a standard finite element (FE) discretization...
DEFF Research Database (Denmark)
Yuan, Hao; Shapiro, Alexander
There is a considerable and ongoing effort aimed at understanding the transport and the deposition of suspended particles in porous media, especially non-Fickian transport and non-exponential deposition of particles. In this work, the influential parameters in filtration models are studied...... to understand their effects on the non-Fickian transport and the non-exponential deposition. The filtration models are validated by the comparisons between the modelling results and the experimental data.The elliptic equation with distributed filtration coefficients may be applied to model non-Fickian transport...... and hyperexponential deposition. The filtration model accounting for the migration of surface associated particles may be applied for non-monotonic deposition....
Biogenic Cracks in Porous Rock
Hemmerle, A.; Hartung, J.; Hallatschek, O.; Goehring, L.; Herminghaus, S.
2014-12-01
Microorganisms growing on and inside porous rock may fracture it by various processes. Some of the mechanisms of biofouling and bioweathering are today identified and partially understood but most emphasis is on chemical weathering, while mechanical contributions have been neglected. However, as demonstrated by the perseverance of a seed germinating and cracking up a concrete block, the turgor pressure of living organisms can be very significant. Here, we present results of a systematic study of the effects of the mechanical forces of growing microbial populations on the weathering of porous media. We designed a model porous medium made of glass beads held together by polydimethylsiloxane (PDMS), a curable polymer. The rheological properties of the porous medium, whose shape and size are tunable, can be controlled by the ratio of crosslinker to base used in the PDMS (see Fig. 1). Glass and PDMS being inert to most chemicals, we are able to focus on the mechanical processes of biodeterioration, excluding any chemical weathering. Inspired by recent measurements of the high pressure (~0.5 Mpa) exerted by a growing population of yeasts trapped in a microfluidic device, we show that yeast cells can be cultured homogeneously within porous medium until saturation of the porous space. We investigate then the effects of such an inner pressure on the mechanical properties of the sample. Using the same model system, we study also the complex interplay between biofilms and porous media. We focus in particular on the effects of pore size on the penetration of the biofilm within the porous sample, and on the resulting deformations of the matrix, opening new perspectives into the understanding of life in complex geometry. Figure 1. Left : cell culture growing in a model porous medium. The white spheres represent the grains, bonds are displayed in grey, and microbes in green. Right: microscopy picture of glass beads linked by PDMS bridges, scale bar: 100 μm.
Luminescence of porous silicon doped by erbium
International Nuclear Information System (INIS)
Bondarenko, V.P.; Vorozov, N.N.; Dolgij, L.N.; Dorofeev, A.M.; Kazyuchits, N.M.; Leshok, A.A.; Troyanova, G.N.
1996-01-01
The possibility of the 1.54 μm intensive luminescence in the silicon dense porous layers, doped by erbium, with various structures is shown. Low-porous materials of both porous type on the p-type silicon and porous silicon with wood-like structure on the n + type silicon may be used for formation of light-emitting structures
Viscoelastic gravel-pack carrier fluid
International Nuclear Information System (INIS)
Nehmer, W.L.
1988-01-01
The ability of a fluid to flow adequately into the formation during gravel-pack treatments is critical to achieving a good pack. Recent studies have indicated ''fish-eyes'' and/or ''microgels'' present in many polymer gelled carrier fluids will plug pore throats, leading to impaired leakoff and causing formation damage. Intensive manipulation of the polymer gelled fluid using shear and filter devices will help remove the particles, but it adds to the cost of the treatment in terms of equipment and manpower. Excessive shear will degrade the polymer leading to poor gravel suspension, while too little shear will cause filtration problems. A gelled carried fluid using a viscoelastic surfactant system has been found to leak off very efficiently to the formation, and cause no formation damage, without the use of shear/filter devices. Viscoelastic surfactant-base gelled fluids develop viscosity because of the association of surfactant moloecules into large rod-shaped aggregates. There is no hydration of polymer involved, so fish-eyes and microgels will not be formed in the viscoelastic fluid. A surfactant-base system having a yield point allows the gravel carrying properties to be much better than fluids gelled with conventional polymer systems (hydroxyethylcellulose [HEC]). For example, a gravel carried fluid gelled with 80 lb HEC/1,000 gal has a viscosity of about 400 cp at 170 sec/sup -1/; a viscoelastic surfactant-base system having only one-half the viscosity still flows into cores about four times more efficiently than the HEC-base fluid. The rheology, leakoff, formation damage and mixing properties of a viscoelastic, surfactant-base, gravel-pack carrier fluid are discussed
Porous media geometry and transports
Adler, Pierre
1992-01-01
The goal of ""Porous Media: Geometry and Transports"" is to provide the basis of a rational and modern approach to porous media. This book emphasizes several geometrical structures (spatially periodic, fractal, and random to reconstructed) and the three major single-phase transports (diffusion, convection, and Taylor dispersion).""Porous Media"" serves various purposes. For students it introduces basic information on structure and transports. Engineers will find this book useful as a readily accessible assemblage of al the major experimental results pertaining to single-phase tr
Comparing Online Algorithms for Bin Packing Problems
DEFF Research Database (Denmark)
Epstein, Leah; Favrholdt, Lene Monrad; Kohrt, Jens Svalgaard
2012-01-01
The relative worst-order ratio is a measure of the quality of online algorithms. In contrast to the competitive ratio, this measure compares two online algorithms directly instead of using an intermediate comparison with an optimal offline algorithm. In this paper, we apply the relative worst-ord......-order ratio to online algorithms for several common variants of the bin packing problem. We mainly consider pairs of algorithms that are not distinguished by the competitive ratio and show that the relative worst-order ratio prefers the intuitively better algorithm of each pair....
Packing C60 in Boron Nitride Nanotubes
Mickelson, W.; Aloni, S.; Han, Wei-Qiang; Cumings, John; Zettl, A.
2003-04-01
We have created insulated C60 nanowire by packing C60 molecules into the interior of insulating boron nitride nanotubes (BNNTs). For small-diameter BNNTs, the wire consists of a linear chain of C60 molecules. With increasing BNNT inner diameter, unusual C60 stacking configurations are obtained (including helical, hollow core, and incommensurate) that are unknown for bulk or thin-film forms of C60. C60 in BNNTs thus presents a model system for studying the properties of dimensionally constrained ``silo'' crystal structures. For the linear-chain case, we have fused the C60 molecules to form a single-walled carbon nanotube inside the insulating BNNT.
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.
Joint sparse representation for robust multimodal biometrics recognition.
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.
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.
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....
A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.
Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi
2015-12-01
Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.
Massively parallel sparse matrix function calculations with NTPoly
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.
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
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.
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
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
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.
Identification of MIMO systems with sparse transfer function coefficients
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.
A General Sparse Tensor Framework for Electronic Structure Theory.
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.
Sparse dictionary learning of resting state fMRI networks.
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.
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.
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.
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.
Bioclogging in Porous Media: Preferential Flow Paths and Anomalous Transport
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
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...
Contaminant bacteria in traditional-packed honey
Directory of Open Access Journals (Sweden)
Hening Tjaturina Pramesti
2007-03-01
Full Text Available Honey may be contaminated by microorganisms during its harvesting, processing, and packaging. Honey selected for clinical purposes must safe, sterile, and contain antimicrobial activity, so it must be evaluated using laboratory testing. The aim of this descriptive laboratory study was to isolate and identify the bacterial contaminant in the traditional-packed honey dealing with the use of honey for medical purposes. the colony forming units of honey sample cultured on blood agar were counted using Stuart bacterial colony counter. The suspected bacterial colonies were isolated and identified based on cultural morphology characteristics. The isolates of suspected bacterial colonies were stained according to Gram and Klein method and then were examined by the biochemical reaction. The results showed that there were two contaminant bacteria. Gram-positive cocci which were presumptively identified as coagulase-negative Staphylococci and gram-positive rods which were presumptively identified as Bacillus subtilis. In conclusion, the contaminant bacteria were regarded as low pathogen bacteria. The subtilin enzyme of B subtilis may cause an allergic reaction and coagulase-negative Staphylococci, Staphylococcus epidermidis is also an opportunist pathogen. Inevitably, for medical purposes, traditional-packed honey must be well filtered, water content above 18%, and standardized sterilization without loss of an antibacterial activity or change in properties.
Universal Regularizers For Robust Sparse Coding and Modeling
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...
Uniform sparse bounds for discrete quadratic phase Hilbert transforms
Kesler, Robert; Arias, Darío Mena
2017-09-01
For each α \\in T consider the discrete quadratic phase Hilbert transform acting on finitely supported functions f : Z → C according to H^{α }f(n):= \\sum _{m ≠ 0} e^{iα m^2} f(n - m)/m. We prove that, uniformly in α \\in T , there is a sparse bound for the bilinear form for every pair of finitely supported functions f,g : Z→ C . The sparse bound implies several mapping properties such as weighted inequalities in an intersection of Muckenhoupt and reverse Hölder classes.
Sparse reconstruction by means of the standard Tikhonov regularization
International Nuclear Information System (INIS)
Lu Shuai; Pereverzev, Sergei V
2008-01-01
It is a common belief that Tikhonov scheme with || · ||L 2 -penalty fails in sparse reconstruction. We are going to show, however, that this standard regularization can help if the stability measured in L 1 -norm will be properly taken into account in the choice of the regularization parameter. The crucial point is that now a stability bound may depend on the bases with respect to which the solution of the problem is assumed to be sparse. We discuss how such a stability can be estimated numerically and present the results of computational experiments giving the evidence of the reliability of our approach.
Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding
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
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.
Sparse grid techniques for particle-in-cell schemes
Ricketson, L. F.; Cerfon, A. J.
2017-02-01
We propose the use of sparse grids to accelerate particle-in-cell (PIC) schemes. By using the so-called ‘combination technique’ from the sparse grids literature, we are able to dramatically increase the size of the spatial cells in multi-dimensional PIC schemes while paying only a slight penalty in grid-based error. The resulting increase in cell size allows us to reduce the statistical noise in the simulation without increasing total particle number. We present initial proof-of-principle results from test cases in two and three dimensions that demonstrate the new scheme’s efficiency, both in terms of computation time and memory usage.
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
Sparse Matrix for ECG Identification with Two-Lead Features
Directory of Open Access Journals (Sweden)
Kuo-Kun Tseng
2015-01-01
Full Text Available Electrocardiograph (ECG human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.
Low-rank and sparse modeling for visual analysis
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
Hydrodynamic dispersion within porous biofilms
Davit, Y.; Byrne, H.; Osborne, J.; Pitt-Francis, J.; Gavaghan, D.; Quintard, M.
2013-01-01
Many microorganisms live within surface-associated consortia, termed biofilms, that can form intricate porous structures interspersed with a network of fluid channels. In such systems, transport phenomena, including flow and advection, regulate
Vibrational modes of porous silicon
International Nuclear Information System (INIS)
Sabra, M.; Naddaf, M.
2012-01-01
On the basis of theoretical and experimental investigations, the origin of room temperature photoluminescence (PL) from porous silicon is found to related to chemical complexes constituted the surface, in particular, SiHx, SiOx and SiOH groups. Ab initio atomic and molecular electronic structure calculations on select siloxane compounds were used for imitation of infrared (IR) spectra of porous silicon. These are compared to the IR spectra of porous silicon recorded by using Fourier Transform Infrared Spectroscopy (FTIR). In contrast to linear siloxane, the suggested circular siloxane terminated with linear siloxane structure is found to well-imitate the experimental spectra. These results are augmented with EDX (energy dispersive x-ray spectroscopy) measurements, which showed that the increase of SiOx content in porous silicon due to rapid oxidation process results in considerable decrease in PL peak intensity and a blue shift in the peak position. (author)
Transport phenomena in porous media
Ingham, Derek B
1998-01-01
Research into thermal convection in porous media has substantially increased during recent years due to its numerous practical applications. These problems have attracted the attention of industrialists, engineers and scientists from many very diversified disciplines, such as applied mathematics, chemical, civil, environmental, mechanical and nuclear engineering, geothermal physics and food science. Thus, there is a wealth of information now available on convective processes in porous media and it is therefore appropriate and timely to undertake a new critical evaluation of this contemporary information. Transport Phenomena in Porous Media contains 17 chapters and represents the collective work of 27 of the world's leading experts, from 12 countries, in heat transfer in porous media. The recent intensive research in this area has substantially raised the expectations for numerous new practical applications and this makes the book a most timely addition to the existing literature. It includes recent major deve...
Positronium chemistry in porous materials
International Nuclear Information System (INIS)
Kobayashi, Y.; Ito, K.; Oka, T.; Hirata, K.
2007-01-01
Porous materials have fascinated positron and positronium chemists for over decades. In the early 1970s it was already known that ortho-positronium (o-Ps) exhibits characteristic long lifetimes in silica gels, porous glass and zeolites. Since then, our understanding of Ps formation, diffusion and annihilation has been drastically deepened. Ps is now well recognized as a powerful porosimetric and chemical probe to study the average pore size, pore size distribution, pore connectivity and surface properties of various porous materials including thin films. In this paper, developments of Ps chemistry in porous materials undertaken in the past some 40 yr are surveyed and problems to be addressed in future are briefly discussed
Porous substrates filled with nanomaterials
Worsley, Marcus A.; Baumann, Theodore F.; Satcher, Jr., Joe H.; Stadermann, Michael
2018-04-03
A composition comprising: at least one porous carbon monolith, such as a carbon aerogel, comprising internal pores, and at least one nanomaterial, such as carbon nanotubes, disposed uniformly throughout the internal pores. The nanomaterial can be disposed in the middle of the monolith. In addition, a method for making a monolithic solid with both high surface area and good bulk electrical conductivity is provided. A porous substrate having a thickness of 100 microns or more and comprising macropores throughout its thickness is prepared. At least one catalyst is deposited inside the porous substrate. Subsequently, chemical vapor deposition is used to uniformly deposit a nanomaterial in the macropores throughout the thickness of the porous substrate. Applications include electrical energy storage, such as batteries and capacitors, and hydrogen storage.
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.
Comparison of NMR simulations of porous media derived from analytical and voxelized representations.
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.
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)
International Nuclear Information System (INIS)
Ma Xiang; Zabaras, Nicholas
2009-01-01
A new approach to modeling inverse problems using a Bayesian inference method is introduced. The Bayesian approach considers the unknown parameters as random variables and seeks the probabilistic distribution of the unknowns. By introducing the concept of the stochastic prior state space to the Bayesian formulation, we reformulate the deterministic forward problem as a stochastic one. The adaptive hierarchical sparse grid collocation (ASGC) method is used for constructing an interpolant to the solution of the forward model in this prior space which is large enough to capture all the variability/uncertainty in the posterior distribution of the unknown parameters. This solution can be considered as a function of the random unknowns and serves as a stochastic surrogate model for the likelihood calculation. Hierarchical Bayesian formulation is used to derive the posterior probability density function (PPDF). The spatial model is represented as a convolution of a smooth kernel and a Markov random field. The state space of the PPDF is explored using Markov chain Monte Carlo algorithms to obtain statistics of the unknowns. The likelihood calculation is performed by directly sampling the approximate stochastic solution obtained through the ASGC method. The technique is assessed on two nonlinear inverse problems: source inversion and permeability estimation in flow through porous media
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.
Magnetic resonance velocity imaging of liquid and gas two-phase flow in packed beds.
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.
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.
Multilayer DNA Origami Packed on Hexagonal and Hybrid Lattices
Ke, Yonggang; Voigt, Niels V.; Gothelf, Kurt V.; 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 r...
Energy Technology Data Exchange (ETDEWEB)
Swisdak, M.; Drake, J. F. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, MD 20742 (United States); Opher, M., E-mail: swisdak@umd.edu, E-mail: drake@umd.edu, E-mail: mopher@bu.edu [Department of Astronomy, Boston University, 725 Commonwealth Avenue, Boston, MA 02215 (United States)
2013-09-01
The picture of the heliopause (HP)-the boundary between the domains of the Sun and the local interstellar medium (LISM)-as a pristine interface with a large rotation in the magnetic field fails to describe recent Voyager 1 (V1) data. Magnetohydrodynamic (MHD) simulations of the global heliosphere reveal that the rotation angle of the magnetic field across the HP at V1 is small. Particle-in-cell simulations, based on cuts through the MHD model at V1's location, suggest that the sectored region of the heliosheath (HS) produces large-scale magnetic islands that reconnect with the interstellar magnetic field while mixing LISM and HS plasma. Cuts across the simulation reveal multiple, anti-correlated jumps in the number densities of LISM and HS particles, similar to those observed, at the magnetic separatrices. A model is presented, based on both the observations and simulations, of the HP as a porous, multi-layered structure threaded by magnetic fields. This model further suggests that contrary to the conclusions of recent papers, V1 has already crossed the HP.
Efficient coordinated recovery of sparse channels in massive MIMO
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.
Sparse Generalized Fourier Series via Collocation-based Optimization
2014-11-01
Theory 51, 12 (2005) 4203– 4215. [6] P. CONSTANTINE , M. ELDRED AND E. PHIPPS, Sparse pseu- dospectral approximation method. Comput. Methods Appl. Mech...Visition XVI: Algorithms, Techniques, Active Vision , and Materials Handling, 224 (1997). [15] J. SHEN AND L. WANG, Some recent advances on spectral methods
A Sparse Bayesian Learning Algorithm With Dictionary Parameter Estimation
DEFF Research Database (Denmark)
Hansen, Thomas Lundgaard; Badiu, Mihai Alin; Fleury, Bernard Henri
2014-01-01
This paper concerns sparse decomposition of a noisy signal into atoms which are specified by unknown continuous-valued parameters. An example could be estimation of the model order, frequencies and amplitudes of a superposition of complex sinusoids. The common approach is to reduce the continuous...
Robust visual tracking via structured multi-task sparse learning
Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra
2012-01-01
In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary
Behavior of greedy sparse representation algorithms on nested supports
DEFF Research Database (Denmark)
Mailhé, Boris; Sturm, Bob L.; Plumbley, Mark
2013-01-01
is not locally nested: there is a dictionary and supports Γ ⊃ Γ′ such that OMP can recover all signals with support Γ, but not all signals with support Γ′. We also show that the support recovery optimality of OMP is globally nested: if OMP can recover all s-sparse signals, then it can recover all s...
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.
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.
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.
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.
Efficient coordinated recovery of sparse channels in massive MIMO
Masood, Mudassir; Afify, Laila H.; Al-Naffouri, Tareq Y.
2015-01-01
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
Low-rank sparse learning for robust visual tracking
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.
Structure-aware Local Sparse Coding for Visual Tracking
Qi, Yuankai; Qin, Lei; Zhang, Jian; Zhang, Shengping; Huang, Qingming; Yang, Ming-Hsuan
2018-01-01
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
A Practical View on Tunable Sparse Network Coding
DEFF Research Database (Denmark)
Sørensen, Chres Wiant; Shahbaz Badr, Arash; Cabrera Guerrero, Juan Alberto
2015-01-01
Tunable sparse network coding (TSNC) constitutes a promising concept for trading off computational complexity and delay performance. This paper advocates for the use of judicious feedback as a key not only to make TSNC practical, but also to deliver a highly consistent and controlled delay perfor...
Parallel and Scalable Sparse Basic Linear Algebra Subprograms
DEFF Research Database (Denmark)
Liu, Weifeng
and heterogeneous processors. The thesis compares the proposed methods with state-of-the-art approaches on six homogeneous and five heterogeneous processors from Intel, AMD and nVidia. Using in total 38 sparse matrices as a benchmark suite, the experimental results show that the proposed methods obtain significant...
SparseBeads data: benchmarking sparsity-regularized computed tomography
DEFF Research Database (Denmark)
Jørgensen, Jakob Sauer; Coban, Sophia B.; Lionheart, William R. B.
2017-01-01
-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...
Hierarchical Bayesian sparse image reconstruction with application to MRFM.
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.
Multiple instance learning tracking method with local sparse representation
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.
Fast sparse matrix-vector multiplication by partitioning and reordering
Yzelman, A.N.
2011-01-01
The thesis introduces a cache-oblivious method for the sparse matrix-vector (SpMV) multiplication, which is an important computational kernel in many applications. The method works by permuting rows and columns of the input matrix so that the resulting reordered matrix induces cache-friendly
Sobol indices for dimension adaptivity in sparse grids
Dwight, R.P.; Desmedt, S.G.L.; Shoeibi Omrani, P.
2016-01-01
Propagation of random variables through computer codes of many inputs is primarily limited by computational expense. The use of sparse grids mitigates these costs somewhat; here we show how Sobol indices can be used to perform dimension adaptivity to mitigate them further. The method is compared to
Discriminative object tracking via sparse representation and online dictionary learning.
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.
Fast Estimation of Optimal Sparseness of Music Signals
DEFF Research Database (Denmark)
la Cour-Harbo, Anders
2006-01-01
We want to use a variety of sparseness measured applied to ‘the minimal L1 norm representation' of a music signal in an overcomplete dictionary as features for automatic classification of music. Unfortunately, the process of computing the optimal L1 norm representation is rather slow, and we...
Sparse principal component analysis in medical shape modeling
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.
Robust Visual Tracking Via Consistent Low-Rank Sparse Learning
Zhang, Tianzhu; Liu, Si; Ahuja, Narendra; Yang, Ming-Hsuan; Ghanem, Bernard
2014-01-01
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
Non-Cartesian MRI scan time reduction through sparse sampling
Wajer, F.T.A.W.
2001-01-01
Non-Cartesian MRI Scan-Time Reduction through Sparse Sampling Magnetic resonance imaging (MRI) signals are measured in the Fourier domain, also called k-space. Samples of the MRI signal can not be taken at will, but lie along k-space trajectories determined by the magnetic field gradients. MRI
Sparsely-Packetized Predictive Control by Orthogonal Matching Pursuit
DEFF Research Database (Denmark)
Nagahara, Masaaki; Quevedo, Daniel; Østergaard, Jan
2012-01-01
We study packetized predictive control, known to be robust against packet dropouts in networked systems. To obtain sparse packets for rate-limited networks, we design control packets via an ℓ0 optimization, which can be eectively solved by orthogonal matching pursuit. Our formulation ensures...
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.
Robust Visual Tracking Via Consistent Low-Rank Sparse Learning
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.
Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering
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.
EEG Source Reconstruction using Sparse Basis Function Representations
DEFF Research Database (Denmark)
Hansen, Sofie Therese; Hansen, Lars Kai
2014-01-01
-validation this approach is more automated than competing approaches such as Multiple Sparse Priors (Friston et al., 2008) or Champagne (Wipf et al., 2010) that require manual selection of noise level and auxiliary signal free data, respectively. Finally, we propose an unbiased estimator of the reproducibility...
Aliasing-free wideband beamforming using sparse signal representation
Tang, Z.; Blacquière, G.; Leus, G.
2011-01-01
Sparse signal representation (SSR) is considered to be an appealing alternative to classical beamforming for direction-of-arrival (DOA) estimation. For wideband signals, the SSR-based approach constructs steering matrices, referred to as dictionaries in this paper, corresponding to different
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.
Meromorphic Vector Fields and Circle Packings
DEFF Research Database (Denmark)
Dias, Kealey
The objective of the Ph.D. project is to initiate a classification of bifurcations of meromorphic vector fields and to clarify their relation to circle packings. Technological applications are to image analysis and to effective grid generation using discrete conformal mappings. The two branches...... of dynamical systems, continuous and discrete, correspond to the study of differential equations (vector fields) and iteration of mappings respectively. In holomorphic dynamics, the systems studied are restricted to those described by holomorphic (complex analytic) functions or meromorphic (allowing poles...... as singularities) functions. There already exists a well-developed theory for iterative holomorphic dynamical systems, and successful relations found between iteration theory and flows of vector fields have been one of the main motivations for the recent interest in holomorphic vector fields. Restricting...
Hyperstaticity and loops in frictional granular packings
Tordesillas, Antoinette; Lam, Edward; Metzger, Philip T.
2009-06-01
The hyperstatic nature of granular packings of perfectly rigid disks is analyzed algebraically and through numerical simulation. The elementary loops of grains emerge as a fundamental element in addressing hyperstaticity. Loops consisting of an odd number of grains behave differently than those with an even number. For odd loops, the latent stresses are exterior and are characterized by the sum of frictional forces around each loop. For even loops, the latent stresses are interior and are characterized by the alternating sum of frictional forces around each loop. The statistics of these two types of loop sums are found to be Gibbsian with a "temperature" that is linear with the friction coefficient μ when μ<1.
New Packing Structure of Concentration Solar Receiver
International Nuclear Information System (INIS)
Tsai, Shang-Yu; Lee, Yueh-Mu; Shih, Zun-Hao; Hong, Hwen-Fen; Shin, Hwa-Yuh; Kuo, Cherng-Tsong
2010-01-01
This paper presents a solution to the temperature issue in High Concentration Photovoltaic (HCPV) module device by using different thermal conductive material and packing structure. In general, the open-circuited voltage of a device reduces with the increase of temperature and therefore degrades its efficiency. The thermal conductive material we use in this paper, silicon, has a high thermal conductive coefficient (149 W/m·K) and steady semiconductor properties which are suitable for the application of solar receiver in HCPV module. Solar cell was soldered on a metal-plated Si substrate with a thicker SiO 2 film which acts as an insulating layer. Then it was mounted on an Al-based plate to obtain a better heat dissipating result.
Slow creep in soft granular packings.
Srivastava, Ishan; Fisher, Timothy S
2017-05-14
Transient creep mechanisms in soft granular packings are studied numerically using a constant pressure and constant stress simulation method. Rapid compression followed by slow dilation is predicted on the basis of a logarithmic creep phenomenon. Characteristic scales of creep strain and time exhibit a power-law dependence on jamming pressure, and they diverge at the jamming point. Microscopic analysis indicates the existence of a correlation between rheology and nonaffine fluctuations. Localized regions of large strain appear during creep and grow in magnitude and size at short times. At long times, the spatial structure of highly correlated local deformation becomes time-invariant. Finally, a microscale connection between local rheology and local fluctuations is demonstrated in the form of a linear scaling between granular fluidity and nonaffine velocity.
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)
Upcycling of Packing-Peanuts into Carbon Microsheet Anodes for Lithium-Ion Batteries.
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.
Deformable segmentation via sparse representation and dictionary learning.
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.
Bacterial transport in heterogeneous porous media: Observations from laboratory experiments
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
Directory of Open Access Journals (Sweden)
Joseph P. Abrahamson
2018-05-01
Full Text Available Porous graphite was prepared without the use of template by rapidly heating the carbonization products from mixtures of anthracene, fluorene, and pyrene with a CO2 laser. Rapid CO2 laser heating at a rate of 1.8 × 106 °C/s vaporizes out the fluorene-pyrene derived pitch while annealing the anthracene coke. The resulting structure is that of graphite with 100 nm spherical pores. The graphitizablity of the porous material is the same as pure anthracene coke. Transmission electron microscopy revealed that the interfaces between graphitic layers and the pore walls are unimpeded. Traditional furnace annealing does not result in the porous structure as the heating rates are too slow to vaporize out the pitch, thereby illustrating the advantage of fast thermal processing. The resultant porous graphite was prelithiated and used as an anode in lithium ion capacitors. The porous graphite when lithiated had a specific capacity of 200 mAh/g at 100 mA/g. The assembled lithium ion capacitor demonstrated an energy density as high as 75 Wh/kg when cycled between 2.2 V and 4.2 V.
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.
Energy Technology Data Exchange (ETDEWEB)
Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W.; Cliff, S.S.; Ramanathan, V.
2010-01-12
Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain at a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.
Feature selection and multi-kernel learning for sparse representation on a manifold
Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin
2014-01-01
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
Building Input Adaptive Parallel Applications: A Case Study of Sparse Grid Interpolation
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
A Non-static Data Layout Enhancing Parallelism and Vectorization in Sparse Grid Algorithms
Buse, Gerrit; Pfluger, Dirk; Murarasu, Alin; Jacob, Riko
2012-01-01
performance and facilitate the use of vector registers for our sparse grid benchmark problem hierarchization. Based on the compact data structure proposed for regular sparse grids in [2], we developed a new algorithm that outperforms existing implementations
Packing and Cohesive Properties of Some Locally Extracted Starches
African Journals Online (AJOL)
... properties of the particles affect the packing and cohesive properties of the starches, and are important in predicting the behaviour of the starches during handling and use in pharmaceutical preparations. These properties need to be closely controlled in pre-formulation studies. Keywords: Packing and cohesive properties, ...
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
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)
Hydrodynamics of multi-phase packed bed micro-reactors
Márquez Luzardo, N.M.
2010-01-01
Why to use packed bed micro-reactors for catalyst testing? Miniaturized packed bed reactors have a large surface-to-volume ratio at the reactor and particle level that favors the heat- and mass-transfer processes at all scales (intra-particle, inter-phase and inter-particle or reactor level). If the
The Performance of Structured Packings in Trickle-Bed Reactors
Frank, M.J.W.; Kuipers, J.A.M.; Versteeg, G.F.; Swaaij, W.P.M. van
1999-01-01
An experimental study was carried out to investigate whether the use of structured packings might improve the mass transfer characteristics and the catalyst effectiveness of a trickle-bed reactor. Therefore, the performances of a structured packing, consisting of KATAPAK elements, and a dumped
demonstrating close-packing of atoms using spherical bubble gums
African Journals Online (AJOL)
Admin
chemistry and junior inorganic chemistry courses. However, the subject of three dimen- sional close-packing of atoms has always been difficult for students to understand. In particular, students find it difficult to visualize the packing of atoms in different layers. They cannot clearly identify tetrahedral and octahedral holes, and.
Improved Erythrocyte Osmotic Fragility and Packed Cell Volume ...
African Journals Online (AJOL)
Improved Erythrocyte Osmotic Fragility and Packed Cell Volume following administration of Aloe barbadensis Juice Extract in Rats. ... Abstract. Aloe barbadensis is a popular house plant that has a long history of a multipurpose folk remedy. ... Keywords: osmotic fragility, packed cell volume, haemoglobin, Aloe vera ...
Metallic witness packs for behind-armour debris characterization
Verolme, J.L.; Szymczak, M.; Broos, J.P.F.
1999-01-01
For the experimental characterization of behind-armour debris so-called metallic witness packs can be used. A metallic witness pack consists of an array of metallic plates interspaced by polystyrene foam sheets. To quantify the fragment mass and velocity from the corresponding hole area and position
27 CFR 24.255 - Bottling or packing wine.
2010-04-01
... in the same tax class when that wine is removed from bond, without benefit of tolerance, when the... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Bottling or packing wine..., DEPARTMENT OF THE TREASURY LIQUORS WINE Storage, Treatment and Finishing of Wine Bottling, Packing, and...
Consistency Check for the Bin Packing Constraint Revisited
Dupuis, Julien; Schaus, Pierre; Deville, Yves
The bin packing problem (BP) consists in finding the minimum number of bins necessary to pack a set of items so that the total size of the items in each bin does not exceed the bin capacity C. The bin capacity is common for all the bins.
Characteristics of illegal and legal cigarette packs sold in Guatemala.
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.