Mechanical dispersion in fractured crystalline rock systems
International Nuclear Information System (INIS)
Lafleur, D.W.; Raven, K.G.
1986-12-01
This report compiles and evaluates the hydrogeologic parameters describing the flow of groundwater and transport of solutes in fractured crystalline rocks. This report describes the processes of mechanical dispersion in fractured crystalline rocks, and compiles and evaluates the dispersion parameters determined from both laboratory and field tracer experiments. The compiled data show that extrapolation of the reliable test results performed over intermediate scales (10's of m and 10's to 100's of hours) to larger spatial and temporal scales required for performance assessment of a nuclear waste repository in crystalline rock is not justified. The reliable measures of longitudinal dispersivity of fractured crystalline rock are found to range between 0.4 and 7.8 m
Radionuclide migration in crystalline rock fractures
International Nuclear Information System (INIS)
Hoelttae, P.
2002-01-01
Crystalline rock has been considered as a host medium for the repository of high radioactive spent nuclear fuel in Finland. The geosphere will act as an ultimate barrier retarding the migration of radionuclides to the biosphere if they are released through the technical barriers. Radionuclide transport is assumed to take place along watercarrying fractures, and retardation will occur both in the fracture and within the rock matrix. To be able to predict the transport and retardation of radionuclides in rock fractures and rock matrices, it is essential to understand the different phenomena involved. Matrix diffusion has been indicated to be an important mechanism, which will retard the transport of radionuclides in rock fractures. Both dispersion and matrix diffusion are processes, which can have similar influences on solute breakthrough curves in fractured crystalline rock. In this work, the migration of radionuclides in crystalline rock fractures was studied by means of laboratory scale column methods. The purpose of the research was to gain a better understanding of various phenomena - particularly matrix diffusion - affecting the transport and retardation behaviour of radionuclides in fracture flow. Interaction between radionuclides and the rock matrix was measured in order to test the compatibility of experimental retardation parameters and transport models used in assessing the safety of underground repositories for spent nuclear fuel. Rock samples of mica gneiss and of unaltered, moderately altered and strongly altered tonalite represented different rock features and porosities offering the possibility to determine experimental boundary limit values for parameters describing both the transport and retardation of radionuclides and rock matrix properties. The dominant matrix diffusion behaviour was demonstrated in porous ceramic column and gas diffusion experiments. Demonstration of the effects of matrix diffusion in crystalline rock fracture succeeded for the
Mixing induced reactive transport in fractured crystalline rocks
International Nuclear Information System (INIS)
Martinez-Landa, Lurdes; Carrera, Jesus; Dentz, Marco; Fernàndez-Garcia, Daniel; Nardí, Albert; Saaltink, Maarten W.
2012-01-01
In this paper the solute retention properties of crystalline fractured rocks due to mixing-induced geochemical reactions are studied. While fractured media exhibit paths of fast flow and transport and thus short residence times for conservative solutes, at the same time they promote mixing and dilution due to strong heterogeneity, which leads to sharp concentration contrasts. Enhanced mixing and dilution have a double effect that favors crystalline fractured media as a possible host medium for nuclear waste disposal. Firstly, peak radionuclide concentrations are attenuated and, secondly, mixing-induced precipitation reactions are enhanced significantly, which leads to radionuclide immobilization. An integrated framework is presented for the effective modeling of these flow, transport and reaction phenomena, and the interaction between them. In a simple case study, the enhanced dilution and precipitation potential of fractured crystalline rocks are systematically studied and quantified and contrasted it to retention and attenuation in an equivalent homogeneous formation.
International Nuclear Information System (INIS)
Davison, C.; Brown, A.; Gascoyne, M.; Stevenson, D.; Ophori, D.
2000-01-01
Atomic Energy of Canada Limited (AECL) conducted a ten-year long groundwater flow study of a 1050 km 2 region of fractured crystalline rock in southeastern Manitoba to illustrate how an understanding of large scale groundwater flow can be used to assist in selecting a hydraulically favourable location for the deep geological disposal of nuclear fuel waste. The study involved extensive field investigations that included the drilling testing, sampling and monitoring of twenty deep boreholes distributed at detailed study areas across the region. The surface and borehole geotechnical investigations were used to construct a conceptual model of the main litho-structural features that controlled groundwater flow through the crystalline rocks of the region. Eighty-three large fracture zones and other spatial domains of moderately fractured and sparsely fractured rocks were represented in a finite element model of the area to simulate regional groundwater flow. The groundwater flow model was calibrated to match the observed groundwater recharge rate and the hydraulic heads measured in the network of deep boreholes. Particle tracking was used to determine the pathways and travel times from different depths in the velocity field of the calibrated groundwater flow model. The results were used to identify locations in the regional flow field that maximize the time it takes for groundwater to travel to surface discharge areas through long, slow groundwater pathways. One of these locations was chosen as a good hypothetical location for situating a nuclear fuel waste disposal vault at 750 m depth. (authors)
Black, John H.; Woodman, Nicholas D.; Barker, John A.
2017-03-01
Rethinking an old tracer experiment in fractured crystalline rock suggests a concept of groundwater flow in sparse networks of long channels that is supported by results from an innovative lattice network model. The model, HyperConv, can vary the mean length of `strings' of connected bonds, and the gaps between them, using two independent probability functions. It is found that networks of long channels are able to percolate at lower values of (bond) density than networks of short channels. A general relationship between mean channel length, mean gap length and probability of percolation has been developed which incorporates the well-established result for `classical' lattice network models as a special case. Using parameters appropriate to a 4-m diameter drift located 360 m below surface at Stripa Mine Underground Research Laboratory in Sweden, HyperConv is able to reproduce values of apparent positive skin, as observed in the so-called Macropermeability Experiment, but only when mean channel length exceeds 10 m. This implies that such channel systems must cross many fracture intersections without bifurcating. A general relationship in terms of flow dimension is suggested. Some initial investigations using HyperConv show that the commonly observed feature, `compartmentalization', only occurs when channel density is just above the percolation threshold. Such compartments have been observed at Kamaishi Experimental Mine (Japan) implying a sparse flow network. It is suggested that compartments and skin are observable in the field, indicate sparse channel systems, and could form part of site characterization for deep nuclear waste repositories.
Comparison of pressure transient response in intensely and sparsely fractured reservoirs
Energy Technology Data Exchange (ETDEWEB)
Johns, R.T.
1989-04-01
A comprehensive analytical model is presented to study the pressure transient behavior of a naturally fractured reservoir with a continuous matrix block size distribution. Geologically realistic probability density functions of matrix block size are used to represent reservoirs of varying fracture intensity and uniformity. Transient interporosity flow is assumed and interporosity skin is incorporated. Drawdown and interference pressure transient tests are investigated. The results show distinctions in the pressure response from intensely and sparsely fractured reservoirs in the absence of interporosity skin. Also, uniformly and nonuniformly fractured reservoirs exhibit distinct responses, irrespective of the degree of fracture intensity. The pressure response in a nonuniformly fractured reservoir with large block size variability, approaches a nonfractured (homogeneous) reservoir response. Type curves are developed to estimate matrix block size variability and the degree of fracture intensity from drawdown and interference well tests.
International Nuclear Information System (INIS)
Svensson, Urban
2001-04-01
A particle tracking algorithm, PARTRACK, that simulates transport and dispersion in a sparsely fractured rock is described. The main novel feature of the algorithm is the introduction of multiple particle states. It is demonstrated that the introduction of this feature allows for the simultaneous simulation of Taylor dispersion, sorption and matrix diffusion. A number of test cases are used to verify and demonstrate the features of PARTRACK. It is shown that PARTRACK can simulate the following processes, believed to be important for the problem addressed: the split up of a tracer cloud at a fracture intersection, channeling in a fracture plane, Taylor dispersion and matrix diffusion and sorption. From the results of the test cases, it is concluded that PARTRACK is an adequate framework for simulation of transport and dispersion of a solute in a sparsely fractured rock
Fracture of crystalline silicon nanopillars during electrochemical lithium insertion
Lee, S. W.
2012-02-27
From surface hardening of steels to doping of semiconductors, atom insertion in solids plays an important role in modifying chemical, physical, and electronic properties of materials for a variety of applications. High densities of atomic insertion in a solid can result in dramatic structural transformations and associated changes in mechanical behavior: This is particularly evident during electrochemical cycling of novel battery electrodes, such as alloying anodes, conversion oxides, and sulfur and oxygen cathodes. Silicon, which undergoes 400% volume expansion when alloying with lithium, is an extreme case and represents an excellent model system for study. Here, we show that fracture locations are highly anisotropic for lithiation of crystalline Si nanopillars and that fracture is strongly correlated with previously discovered anisotropic expansion. Contrary to earlier theoretical models based on diffusion-induced stresses where fracture is predicted to occur in the core of the pillars during lithiation, the observed cracks are present only in the amorphous lithiated shell. We also show that the critical fracture size is between about 240 and 360 nm and that it depends on the electrochemical reaction rate.
Fractures inside crystalline rocks. Effects of deformations on fluid circulations
International Nuclear Information System (INIS)
Gentier, S.
2005-01-01
The modeling of fluid flows inside granite massifs is an important task for the evaluation of the feasibility of radioactive waste storage inside such formations. This document makes a synthesis of the works carried out since about 15 years, in particular by the French bureau of geological and mining research (BRGM), about the hydro-mechanical behaviour of a fracture and about the hydrodynamical characterization of fracture networks inside crystalline rocks: 1 - introduction; 2 - hydro-mechanical behaviour under normal stress: experimental results (hydro-mechanical behaviour, flow regimes, mechanical behaviour, test protocol, complementary tests, influence of samples size), geometrical interpretation of experimental results (relation with walls geometry, relation with voids geometry, relation with contacts geometry), hydro-mechanical modeling (hydraulic modeling, mechanical modeling); 3 - from the hydro-mechanical behaviour under normal stress to the coupling with heat transfers and chemistry: experiment for the study of the chemo-thermo-hydro-mechanical coupling (experimental results, relation with walls morphology), thermo-hydro-mechanical experiments, thermo-hydro-chemical experiments with fractures, conclusions; 4 - hydro-mechanical behaviour during shear: experimental results, geometrical interpretation (relation with the geometry of damaged zones, relation with voids geometry, relation with walls geometry), hydro-mechanical modeling (mechanical modeling, hydro-mechanical modeling of the behaviour during shear). (J.S.)
Hyman, J.; Aldrich, G. A.; Viswanathan, H. S.; Makedonska, N.; Karra, S.
2016-12-01
We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semi-correlation, and non-correlation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same.We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.
Predictions of first passage times in sparse discrete fracture networks using graph-based reductions
Hyman, J.; Hagberg, A.; Srinivasan, G.; Mohd-Yusof, J.; Viswanathan, H. S.
2017-12-01
We present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths. First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. Accurate estimates of first passage times are obtained with an order of magnitude reduction of CPU time and mesh size using the proposed method.
Creep in the sparsely fractured rock between a disposal vault and a zone of highly fractured rock
International Nuclear Information System (INIS)
Wilkins, B.J.S.; Rigby, G.L.
1993-08-01
AECL Research is responsible for investigating the feasibility and safety of the disposal of Canada's nuclear fuel waste deep in the plutonic rock of the Canadian Shield. The excavation of the disposal vault, the installation of sealing systems and the heat generated by the fuel waste will all perturb the in situ stress state of the rock mass. This computer codes HOTROK, MCROC and MCDIRC are used to analyze the influence of these stress perturbations on the mechanical behaviour of the rock mass. Time-dependent microcracking of the rock mass will lead to creep around openings in the vault. The analysis specifically estimates the resulting creep strain in the sparsely fractured rock between the edge of the disposal vault and a postulated zone of highly fractured rock. The estimates are extremely conservative. The conclusion reached is that the rock mass more than 3 m beyond the edge of the vault will experience < 0.001 creep strain 100 000 years after the fuel waste is emplaced. (author). 10 refs., 4 tabs., 4 figs
Phononless soliton waves as early forerunners of crystalline material fracture
International Nuclear Information System (INIS)
Dubovskij, O.A.; Orlov, A.V.
2007-01-01
Phononless soliton waves of compression are shown to generate at a critical tension of crystals featuring real Lennard-Jones potential of interatomic interaction just before their fracture. A new method of nonlinear micro dynamics was applied to define the initial atomic displacements at high excitation energies. A solution is found that corresponds to a soliton wave running before the front of fracture. In a bounded crystal, the soliton being reflected from the crystal boundary passes the front of fracture and deforms while moving in the opposite direction. The amplitude and spectral characteristics of that type of soliton waves in crystals with a modified Lennard-Jones potential have been investigated. An approximate analytical solution was found for the soliton waves [ru
Theoretical and laboratory investigations of flow through fractures in crystalline rock
International Nuclear Information System (INIS)
Witherspoon, P.A.; Watkins, D.J.; Tsang, Y.W.
1981-01-01
A theoretical model developed for flow through a deformable fracture subject to stresses was successfully tested against laboratory experiments. The model contains no arbitrary parameters and can be used to predict flow rates through a single fracture if the fractional fracture contact area can be estimated and if stress-deformation data are available. These data can be obtained from laboratory or in situ tests. The model has considerable potential for practical application. The permeability of ultralarge samples of fractured crystalline rock as a function of stresses was measured. Results from tests on a pervasively fractured 1-m-diameter specimen of granitic rock showed that drastically simplifying assumptions must be used to apply theoretical models to this type of rock mass. Simple models successfully reproduce the trend of reduced permeability as stress is applied in a direction normal to the fracture plane. The tests also demonstrated how fracture conductivity increases as a result of dilatancy associated with shear displacements. The effect of specimen size on the hydraulic properties of fractured rock was also investigated. Permeability tests were performed on specimens of charcoal black granite containing a single fracture subjected to normal stress. Results are presented for tests performed on a 0.914-m-diameter specimen and on the same specimen after it had been reduced to 0.764 m in diameter. The data show that fracture conductivity is sensitive to stress history and sample disturbance
Mobilities of radionuclides in fresh and fractured crystalline rock
International Nuclear Information System (INIS)
Torstenfelt, B.; Ittner, T.; Allard, B.; Andersson, K.; Olofsson, U.
1982-12-01
Sorption and migration of technetium, cesium and americium on fracture surfaces and fresh surfaces of granites taken from drilling cores from the Finnsjoen and Studsvik areas and the Stripa mine are reported. The three elements were used as reference elements with different chemistry and behaviour in water; under the conditions used in the experiments technetium exists as the heptavalent TcO -4 -ion, cesium as the non-complexed monovalent cation Cs + and americium as the strongly hydrolysed Am(OH)super (3-x) (x-1-4). The waters used were synthetic groundwaters representative of waters from the drilling holes. After the exposure of the fracture samples to spiked groundwater solutions for a period of three up to six months the penetration depths and concentration profiles were analysed and autoradiographs of cesium and americium distribution vs depth were taken. The sorption of technetium was found to be negligible. The transport of TcO -4 depends on accessibility to fractures and micro-fissures in the rock. Cesium is sorbed through an ion-exchange process. Migration of cesium depends not only on the transport in water into fractures and micro-fissures, but also on migration through mineral veins with a high CEC. Americium is strongly sorbed on most solid surfaces and did not migrate significantly during the contact time of three months. The diffusivity in granite was found to be around 10 - 13 m 2 /s for cesium; preliminary values for technetium and americium were 10 - 12 m 2 /s and less than 10 - 16 m 2 /s, respectively. (Authors)
Study of strontium and cesium migration in fractured crystalline rock
International Nuclear Information System (INIS)
Gustafsson, E.; Klockars, C.E.
1984-01-01
The purpose of this investigation has been to study the retardation and dilution of non-active strontium and cesium relative to a non-absorbing substance (iodide) in a well-defined fracture zone in the Finnsjoen field research area. The investigation was carried out in a previously tracer-tested fracture zone. The study has encompassed two separate test runs with prolonged injection of strontium and iodide and of cesium and iodide. The test have shown that: - Strontium is not retarded, but rather absorbed to about 40% at equilibrium. - At injection stop, 36.3% of the injected mass of strontium has been absorbed and there is no deabsorption. -Cesium is retarded a factor of 2-3 and absorbed to about 30% at equilibrium. - At injection stop, 39.4% of the injected mass of cesium has been absorbed. Cesium is deabsorbed after injection stop (400h) and after 1300 hours, only 22% of the injected mass of cesium is absorbed. (author)
Fracture detection in crystalline rock using ultrasonic shear waves
International Nuclear Information System (INIS)
Waters, K.H.; Palmer, S.P.; Farrell, W.E.
1978-12-01
An ultrasonic shear wave reflection profiling system for use in the detection of water-filled cracks occurring within a crystalline rock mass is being tested in a laboratory environment. Experiments were performed on an irregular tensile crack induced approximately 0.5 m below one circular face of a 1.0-m-dia, 1.8-m-long granite cylinder. Good reflection data were obtained from this irregular crack with the crack either air filled or water filled. Data were collected that suggest a frequency-dependent S/sub H/ wave reflection coefficient for a granite-water interface. Waves that propagate along the free surface of a rock mass (surface waves) can severely hinder the detection of reflected events. Two methods of reducing this surface wave noise were investigated. The first technique uses physical obstructions (such as a slit trench) to scatter the surface waves. The second technique uses a linear array of receivers located on the free surface to cancel waves that are propagating parallel to the array (e.g., surface waves), thus enhancing waves with propagation vectors orthogonal to the linear array (e.g., reflected events). Deconvolution processing was found to be another method useful in surface wave cancellation
Fracturing process and effect of fracturing degree on wave velocity of a crystalline rock
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Charalampos Saroglou
2017-10-01
Full Text Available The present paper investigates the effect of fracturing degree on P- and S-wave velocities in rock. The deformation of intact brittle rocks under loading conditions is characterized by a microcracking procedure, which occurs due to flaws in their microscopic structure and propagates through the intact rock, leading to shear fracture. This fracturing process is of fundamental significance as it affects the mechanical properties of the rock and hence the wave velocities. In order to determine the fracture mechanism and the effect of fracturing degree, samples were loaded at certain percentages of peak strength and ultrasonic wave velocity was recorded after every test. The fracturing degree was recorded on the outer surface of the sample and quantified by the use of the indices P10 (traces of joints/m, P20 (traces of joints/m2 and P21 (length of fractures/m2. It was concluded that the wave velocity decreases exponentially with increasing fracturing degree. Additionally, the fracturing degree is described adequately with the proposed indices. Finally, other parameters concerning the fracture characteristics, rock type and scale influence were found to contribute to the velocity decay and need to be investigated further.
Normani, S. D.; Sykes, J. F.; Jensen, M. R.
2009-04-01
A high resolution sub-regional scale (84 km2) density-dependent, fracture zone network groundwater flow model with hydromechanical coupling and pseudo-permafrost, was developed from a larger 5734 km2 regional scale groundwater flow model of a Canadian Shield setting in fractured crystalline rock. The objective of the work is to illustrate aspects of regional and sub-regional groundwater flow that are relevant to the long-term performance of a hypothetical nuclear fuel repository. The discrete fracture dual continuum numerical model FRAC3DVS-OPG was used for all simulations. A discrete fracture zone network model delineated from surface features was superimposed onto an 789887 element flow domain mesh. Orthogonal fracture faces (between adjacent finite element grid blocks) were used to best represent the irregular discrete fracture zone network. The crystalline rock between these structural discontinuities was assigned properties characteristic of those reported for the Canadian Shield at the Underground Research Laboratory at Pinawa, Manitoba. Interconnectivity of permeable fracture features is an important pathway for the possibly relatively rapid migration of average water particles and subsequent reduction in residence times. The multiple 121000 year North American continental scale paleoclimate simulations are provided by W.R. Peltier using the University of Toronto Glacial Systems Model (UofT GSM). Values of ice sheet normal stress, and proglacial lake depth from the UofT GSM are applied to the sub-regional model as surface boundary conditions, using a freshwater head equivalent to the normal stress imposed by the ice sheet at its base. Permafrost depth is applied as a permeability reduction to both three-dimensional grid blocks and fractures that lie within the time varying permafrost zone. Two different paleoclimate simulations are applied to the sub-regional model to investigate the effect on the depth of glacial meltwater migration into the subsurface. In
VSP in crystalline rocks - from downhole velocity profiling to 3-D fracture mapping
International Nuclear Information System (INIS)
Cosma, C.; Heikkinen, P.; Keskinen, J.; Enescu, N.
1998-01-01
VSP surveys have been carried out at several potential nuclear waste disposal sites in Finland since the mid 80s. To date, more than 200 three-component profiles have been measured. The main purpose of the surveys was to detect fracture zones in the crystalline bedrock and to determine their position. Most seismic events could be linked to zones of increased fracturing observed in the borehole logs. The more pronounced seismic reflectors could be correlated with hydrogeologically significant zones, which have been the main targets in the investigations. Processing and interpretation methods have been developed specifically for VSP surveys in crystalline rocks: Weak reflections from thin fracture zones are enhanced by multi-channel filtering techniques based on the Radon transform. The position and orientation of the fracture zones are determined by polarisation analysis and by combining data from several shot points. The compilation of the results from several boreholes gives a comprehensive image of the fracture zones at the scale of the whole site. The discussion of the methodology is based on examples from the Olkiluoto site, in SW Finland
International Nuclear Information System (INIS)
Marine, I.W.
1975-01-01
J At the Savannah River plant of the Atomic Energy Commission near Aiken, South Carolina, there are three distinct groundwater systems: the coastal plain sediments, the crystalline metamorphic rocks, and a buried Triassic basin. The coastal plain sediments include several Cretaceous and Tertiary granular aquifers and aquicludes, the total thickness being about 305 m. Below these sediments, water occurs in small fractures in crystalline metamorphic rock (hornblende schist and gneiss with lesser amounts of quartzite). Water level fluctuations due to earth tides are recorded in the crystalline metamorphic rock system and in the coastal plain sediments. No water level fluctuations due to earth tides have been observed in wells in the Triassic rock because of the very low permeability. The water level fluctuations due to earth tides in the crystalline rock are about 10 cm, and those in the sediments are about 1.8 cm. The use of water level fluctuations due to earth tides to calculate porosity appears to present practical difficulties both in the crystalline metamorphic rock system and in the coastal plain sediments. In a 1-yr pumping test on a well in the crystalline metamorphic rock the flow was controlled to within 0.1 percent of the total discharge, which was 0.94 1/s. The water level fluctuations due to earth tides in the pumping well were 10 cm, the same as when this well was not being pumped. (U.S.)
Energy Technology Data Exchange (ETDEWEB)
Pharr, M.; Katoh, Y.; Bei, H.
2006-01-01
Along with other desirable properties, the ability of silicon carbide (SiC) to retain high strength after elevated temperature exposures to neutron irradiation renders it potentially applicable in fusion and advanced fission reactors. However, properties of the material such as room temperature fracture toughness must be thoroughly characterized prior to such practical applications. The objective of this work is to investigate the dependence of fracture toughness on crystallographic orientation for single-crystalline β-SiC. X-ray diffraction was first performed on the samples to determine the orientation of the crystal. Nanoindentation was used to determine a hardness of 39.1 and 35.2 GPa and elastic modulus of 474 and 446 GPa for the single-crystalline and polycrystalline samples, respectively. Additionally, crack lengths and indentation diagonals were measured via a Vickers micro-hardness indenter under a load of 100 gf for different crystallographic orientations with indentation diagonals aligned along fundamental cleavage planes. Upon examination of propagation direction of cracks, the cracks usually did not initiate and propagate from the corners of the indentation where the stresses are concentrated but instead from the indentation sides. Such cracks clearly moved along the {1 1 0} family of planes (previously determined to be preferred cleavage plane), demonstrating that the fracture toughness of SiC is comparatively so much lower along this set of planes that the lower energy required to cleave along this plane overpowers the stress-concentration at indentation corners. Additionally, fracture toughness in the <1 1 0> direction was 1.84 MPa·m1/2, lower than the 3.46 MPa·m1/2 measured for polycrystalline SiC (which can serve as an average of a spectrum of orientations), further demonstrating that single-crystalline β-SiC has a strong fracture toughness anisotropy.
Energy Technology Data Exchange (ETDEWEB)
Ramstad, Randi Kalstad
2004-11-01
The use of improved equipment and methodology can result in considerable reductions in the drilling costs for medium- to large sized ground source heat pump system in crystalline bedrock. The main point has been to use special techniques within hydraulic fracturing to create a larger heat exchange area in the bedrock, and thus a greater energy extraction per borehole. The energy extraction is based on circulating groundwater. Stimulation with hydraulic fracturing is a well known technique in order to improve borehole yields for drinking water-, oil-, and geothermal purposes. A procedure for injection of propping agents in selected borehole sections, and custom-made equipment for hydraulic fracturing in crystalline bedrock, a double packer, have been developed in this study. The propping agents are likely to ensure a permanent improvement of the hydraulic conductivity in a long-run perspective. In addition to a pre-test, a comprehensive test programme has been performed at each of the two pilot plants at Bryn and at the former property of Energiselskapet Asker og Baerum (EAB) in Baerum municipality outside Oslo, Norway. A total of 125 stimulations with hydraulic fracturing using water-only and hydraulic fracturing with injection of sand have been performed in 9 boreholes. Test pumping and geophysical logging (temperature, electrical conductivity, gamma radiation, optical televiewer and flow measurements) have been carried out in order to document the effect of the hydraulic fracturing. The pilot plants at Bryn and EAB, where the ground source heat pump systems are based on circulating groundwater, have demonstrated the short-period energy extraction, limitations and opportunities of the concept for hydraulic fracturing and increased energy extraction in different geological and hydrogeological areas. The bedrock at Bryn and EAB is characterized as a low-metamorphic sandstone and a nodular limestone, respectively. At Bryn, the five boreholes were organised with a
Reflection seismic methods applied to locating fracture zones in crystalline rock
International Nuclear Information System (INIS)
Juhlin, C.
1998-01-01
The reflection seismic method is a potentially powerful tool for identifying and localising fracture zones in crystalline rock if used properly. Borehole sonic logs across fracture zones show that they have reduced P-wave velocities compared to the surrounding intact rock. Diagnostically important S-wave velocity log information across the fracture zones is generally lacking. Generation of synthetic reflection seismic data and subsequent processing of these data show that structures dipping up towards 70 degrees from horizontal can be reliably imaged using surface seismic methods. Two real case studies where seismic reflection methods have been used to image fracture zones in crystalline rock are presented. Two examples using reflection seismic are presented. The first is from the 5354 m deep SG-4 borehole in the Middle Urals, Russia where strong seismic reflectors dipping from 25 to 50 degrees are observed on surface seismic reflection data crossing over the borehole. On vertical seismic profile data acquired in the borehole, the observed P-wave reflectivity is weak from these zones, however, strong converted P to S waves are observed. This can be explained by the source of the reflectors being fracture zones with a high P wave to S wave velocity ratio compared to the surrounding rock resulting in a high dependence on the angle of incidence for the reflection coefficient. A high P wave to S wave velocity ratio (high Poisson's ratio) is to be expected in fluid filled fractured rock. The second case is from Aevroe, SE Sweden, where two 1 km long crossing high resolution seismic reflection lines were acquired in October 1996. An E-W line was shot with 5 m geophone and shotpoint spacing and a N-S one with 10 m geophone and shotpoint spacing. An explosive source with a charge size of 100 grams was used along both lines. The data clearly image three major dipping reflectors in the upper 200 ms (600 m). The dipping ones intersect or project to the surface at/or close to
Characterizing fractures and shear zones in crystalline rock using seismic and GPR methods
Doetsch, Joseph; Jordi, Claudio; Laaksonlaita, Niko; Gischig, Valentin; Schmelzbach, Cedric; Maurer, Hansruedi
2016-04-01
Understanding the natural or artificially created hydraulic conductivity of a rock mass is critical for the successful exploitation of enhanced geothermal systems (EGS). The hydraulic response of fractured crystalline rock is largely governed by the spatial organization of permeable fractures. Defining the 3D geometry of these fractures and their connectivity is extremely challenging, because fractures can only be observed directly at their intersections with tunnels or boreholes. Borehole-based and tunnel-based ground-penetrating radar (GPR) and seismic measurements have the potential to image fractures and other heterogeneities between and around boreholes and tunnels, and to monitor subtle time-lapse changes in great detail. We present the analysis of data acquired in the Grimsel rock laboratory as part of the In-situ Stimulation and Circulation (ISC) experiment, in which a series of stimulation experiments have been and will be performed. The experiments in the granitic rock range from hydraulic fracturing to controlled fault-slip experiments. The aim is to obtain a better understanding of coupled seismo-hydro-mechanical processes associated with high-pressure fluid injections in crystalline rocks and their impact on permeability creation and enhancement. GPR and seismic data have been recorded to improve the geological model and characterize permeable fractures and shear zones. The acquired and processed data include reflection GPR profiles measured from tunnel walls, single-borehole GPR images, and borehole-to-borehole and tunnel-to-tunnel seismic and GPR tomograms. The reflection GPR data reveal the geometry of shear zones up to a distance of 30 m from the tunnels and boreholes, but the interpretation is complicated by the geometrical ambiguity around tunnels and boreholes and by spurious reflections from man-made structures such as boreholes. The GPR and seismic traveltime tomography results reveal brittle fractured rock between two ductile shear zones. The
Matrix diffusion of simple cations, anions, and neutral species in fractured crystalline rocks
International Nuclear Information System (INIS)
Sato, Haruo
1999-01-01
The diffusion of radionuclides into the pore spaces of a rock matrix and the pore properties in fractured crystalline rocks were studied. The work concentrated on the predominant water-conducting fracture system in the host granodiorite of the Kamaishi In Situ Test Site, which consists of fracture fillings and altered grandodiorite. Through-diffusion experiments to obtain effective and apparent diffusion coefficients (De and Da, respectively) for Na + , Cs + , HTO, Cl - , and SeO 3 2- as a function of ionic charge were conducted through the fracture fillings and altered and intact granodiorite. The total porosity φ, density, pore-size distribution, and specific surface area of the pores of the rocks were also determined by a water saturation method and Hg porosimetry. The average φ is, in the order from highest to lowest, as follows: fracture fillings (5.6%) greater than altered granodiorite (3.2%) greater than intact granodiorite (2.3%), and gradually it decreases into the matrix. The pore sizes of the intact and altered granodiorite range from 10 nm to 200 microm, and the fracture fillings from 50 nm to 200 microm, but almost all pores are found around 0.1 and 200 microm in the fracture fillings. The De values for all species are in the following order: fracture fillings greater than altered granodiorite greater than intact granodiorite, as with the rock porosity. In addition. no effect of ionic charge on De is found. No significant dependence for Da values on the rock porosity is found. The formation factors FF and geometric factors G of the rocks were evaluated by normalizing the free water diffusion coefficient Do for each species. The FF decreased with decreasing rock porosity, and an empirical equation for the rock porosity was derived to be FF = φ 1.57±0.02 . The G values showed a tendency to slightly decrease with decreasing rock porosity, but they were approximately constant (0.12 to 0.19) in this porosity range. This indicates that accessible pores
The impact of a (hyper)alkaline plume on (fractured) crystalline rock
International Nuclear Information System (INIS)
Alexander, Russell
2012-01-01
Russell Alexander from Bedrock Geosciences, Switzerland, gave a presentation on the possible effects of cement pore waters on a crystalline host rock. Field, laboratory and natural analogue studies as well as geochemical modelling indicate that cement leachates tend to induce the sealing of fractures in the rock. These studies also indicate that strongly alkaline waters might: - Accelerate the dissolution of vitrified waste, but probably not affect the dissolution rate of spent fuel. - Degrade bentonite to some degree. To avoid some of the effects associated with the use of concrete, several approaches may be used: - Minimisation and tracking/monitoring of the concrete masses. - Development and use of low-pH cements and alternative grouting materials. - The selection of less fractured rock volumes for a repository location. The sealing of fractures evidenced in the Maquarin natural analogue study might contribute to limiting the extent of perturbations caused by an alkaline plume and is likely to create a hydraulic barrier that affects groundwater flow. The effects of these processes should be analysed in a safety case since they may support the idea of a self-sealing repository. Uncertainties in the treatment of an alkaline plume in fractured rock include: - The possible formation of colloids. - Thermodynamic data for cement components and secondary mineral stability. - Cement carbonation. - The effects of super-plasticisers. Given these uncertainties, current assessments of perturbations around a HLW or spent fuel repository caused by cementitious materials are often conservative and provide a pessimistic view of disposal system performance. Discussion of the paper included: Will groundwater flows in deep systems be fast enough to cause pervasive sealing of fractures? The process of how a network of fractures may be sealed over time is uncertain. The flow field will be altered as fractures are sealed and this may cause flow rates in other parts of the fracture
Persaud, Elisha; Levison, Jana; Pehme, Peeter; Novakowski, Kentner; Parker, Beth
2018-01-01
In order to continually improve the current understanding of flow and transport in crystalline bedrock environments, developing and improving fracture system characterization techniques is an important area of study. The presented research examines the installation of flexible, impermeable FLUTe™ liners as a means for assessing cross-hole fracture connectivity. FLUTe™ liners are used to generate a new style of hydraulic pulse, with pressure response monitored in a nearby network of open boreholes drilled in gneissic rock of the Canadian Shield in eastern Ontario, Canada. Borehole liners were installed in six existing 10-15 cm diameter boreholes located 10-35 m apart and drilled to depths ranging between 25-45 m. Liner installation tests were completed consecutively with the number of observation wells available for each test ranging between one and six. The collected pressure response data have been analyzed to identify significant groundwater flow paths between source and observation boreholes as well as to estimate inter-well transmissivity and storativity using a conventional type-curve analysis. While the applied solution relies on a number of general assumptions, it has been found that reasonable comparison can be made to previously completed pulse interference and pumping tests. Results of this research indicate areas where method refinement is necessary, but, nonetheless, highlight the potential for use in crystalline bedrock environments. This method may provide value to future site characterization efforts given that it is complementary to, and can be used in conjunction with, other currently employed borehole liner applications, such as the removal of cross-connection at contaminated sites and the assessment of discrete fracture distributions when boreholes are sealed, recreating natural hydraulic gradient conditions.
Sahlstedt, E. K.; Karhu, J.; Pitkänen, P.
2015-12-01
Changes in the geochemical environment in crystalline bedrock fractures were investigated using the stable isotopes of C, O and S in fracture filling minerals as tracers. Of special interest were the possible changes which may occur in the subsurface at low temperatures. Especially, the influence of microbial activity was recognized as a catalyst for inducing changes in the geochemical environment. The study site is the Olkiluoto island located on the western coast of Finland, planned to host a geological repository for nuclear waste. Fracture surfaces were investigated to recognize the latest mineralizations at the site. These fillings were comprised of thin plates or small euhedral crystals of calcite and pyrite. The carbon and sulfur isotope compositions of calcite and pyrite were measured from bulk material by conventional IRMS, and in situ by secondary ion mass spectrometry. A notable feature of the late-stage fillings was high variabilities in the δ13C values of calcite and the δ34S values of pyrite, which ranged from -53.8 ‰ to +31.6 ‰ and from -50.4 ‰ to +77.7 ‰, respectively. Based on the isotopic compositions of the fillings, several features in the past hydrogeochemical environment could be recognized. The isotopic composition of the fracture fillings indicate an environment which was stratified with respect to depth. Characteristic features include bacterial sulfate reduction (BSR) occurring at depths 50 m. It appears that methanic conditions were replaced by sulfate reduction at depths >50 m likely due to infiltration of SO42--rich brackish waters. Sulfate reducing bacteria used mainly surface derived organic carbon as electron donors. Some indication of minor methanotrophic activity was recognized in anomalously low δ13C values of calcite, down to -53.8 ‰, at the depth range of 34-54 m. This methanotrophic activity may have been related to bacteria using CH4 as an electron donor in BSR.
International Nuclear Information System (INIS)
Stevenson, D.R.; Kozak, E.T.; Davison, C.C.; Gascoyne, M.; Broadfoot, R.A.
1996-06-01
The hydrogeologic characteristics of the granitic Lac du Bonnet batholith in southeastern Manitoba have been studied since 1978, as part of AECL's program to assess the concept of disposing of Canada's nuclear fuel waste deep within plutonic rocks of the Canadian Shield (Davison et al. 1994a). These studies have included an extensive program of drilling, logging, testing, sampling and monitoring in 19 deep surface boreholes drilled at Grid areas located across the Lac du Bonnet batholith, at the Whiteshell Laboratory (WL), and in surface and underground boreholes at the Underground Research Laboratory (URL). Based on these investigations domains of low permeability, sparsely fractured rock (SFR) have been identified in the Lac du Bonnet batholith
International Nuclear Information System (INIS)
Olsson, O.; Falk, L.; Forslund, O.; Lundmark, L.; Sandberg, E.
1992-01-01
This paper discusses the borehole radar system, RAMAC, developed within the framework of the International Stripa Project, which can be used in three different measuring modes; single-hole reflection, cross-hole reflection and cross-hole tomography. The reflection modes basically provide geometrical data on features located at some distance from the borehole. In addition the strength of the reflections indicate the contrast in electrical properties. Single-hole reflection data are cylindrically symmetrical with respect to the borehole, which means that a unique fracture orientation cannot be obtained. A method has been devised where absolute orientation of fracture zones is obtained by combining single-hole reflection data from adjacent holes. Similar methods for the analysis of cross-hole reflection data have also been developed and found to be efficient. The radar operates in the frequency range 20-60 MHz which gives a resolution of 1-3 m in crystalline rock. The investigation range obtained in the Stripa granite is approximately 100 m in the single-hole mode and 200-300 m in the cross-hole model. Variations in the arrival time and amplitude of the direct wave between transmitter and receiver have been used for cross-hole tomographic imaging to yield maps of radar velocity and attenuation. The cross-hole measurement configuration coupled with tomographic inversion has less resolution than the reflection methods but provides better quantitative estimates of the values of measured properties. The analysis of the radar data has provided a consistent description of the fracture zones at the Stripa Cross-hole site in agreement with both geological and geophysical observations
Continuum-based DFN-consistent simulations of oxygen ingress in fractured crystalline rocks
Trinchero, P.; Puigdomenech, I.; Molinero, J.; Ebrahimi, H.; Gylling, B.; Svensson, U.; Bosbach, D.; Deissmann, G.
2016-12-01
The potential transient infiltration of oxygenated glacial meltwater into initially anoxic and reducing fractured crystalline rocks during glaciation events is an issue of concern for some of the prospected deep geological repositories for spent nuclear fuel. Here, this problem is assessed using reactive transport calculations. First, a novel parameterisation procedure is presented, where flow, transport and geochemical parameters (i.e. hydraulic conductivity, effective/kinetic porosity, and mineral specific surface and abundance) are defined on a finite volume numerical grid based on the (spatially varying) properties of an underlying Discrete Fracture Network (DFN). Second, using this approach, a realistic reactive transport model of Forsmark, i.e. the selected site for the proposed Swedish spent nuclear fuel repository, is implemented. The model consists of more than 70 million geochemical transport degrees of freedom and simulates the ingress of oxygen-rich water from the recharge area of the domain and its depletion due to reactions with the Fe(II) mineral chlorite. Third, the calculations are solved in the supercomputer JUQUEEN of the Jülich Supercomputing Centre. The results of the simulations show that oxygen infiltrates relatively quickly along fractures and deformation zones until a steady state profile is reached, where geochemical reactions counterbalance advective transport processes. Interestingly, most of the iron-bearing minerals are consumed in the highly conductive zones, where larger mineral surfaces are available for reactions. An analysis based on mineral mass balance shows that the considered rock medium has enough capacity to buffer oxygen infiltration for a long period of time (i.e. some thousand years).
HRL Aespoe - two-phase flow experiment - gas and water flow in fractured crystalline rock
International Nuclear Information System (INIS)
Kull, H.; Liedtke, L.
1998-01-01
(The full text of the contribution follows:) Gas generated from radioactive waste may influence the hydraulic and mechanical properties of the man-made barriers and the immediate surroundings of the repository. Prediction of alteration in fractured crystalline rock is difficult. There is a lack of experimental data, and calibrated models are not yet available. Because of the general importance of this matter the German Federal Ministry for Education, Science, Research and Technology decided to conduct a two-phase flow study at HRL Aespoe within the scope of the co-operation agreement with SKB. Within the presentation an overview of field experiments and modelling studies scheduled until end of '99 are given. Conceptual models for one- and two-phase flow, methodologies and with respect to numerical calculations necessary parameter set-ups are discussed. Common objective of in-situ experiments is to calibrate flow models to improve the reliability of predictions for gas migration through fractured rock mass. Hence, in a defined dipole flow field in niche 2/715 at HRL Aespoe effective hydraulic parameters are evaluated. Numerical modelling of non-isothermal, two-phase, two-component processes is feasible only for two-dimensional representation of a porous medium. To overcome this restriction a computer program will be developed to model three-dimensional, fractured, porous media. Rational aspects of two-phase flow studies are for the designing of geotechnical barriers and for the long-term safety analysis of potential radionuclide transport in a future repository required for the licensing process
International Nuclear Information System (INIS)
Sahlstedt, Elina; Karhu, Juha A.; Pitkänen, Petteri; Whitehouse, Martin
2016-01-01
34–54 m showed evidence of localized methanotrophic activity seen as anomalously 13 C depleted calcite, having δ 13 C values as low as −53.8‰. At depths of ∼60–400 m, positive δ 13 C values of up to +31.6‰ in late-stage calcite of Group 1–2 indicated methanogenesis. In comparison, high CH 4 concentrations in present day groundwaters are found at depths of >300 m. One sample at a depth of 111 m showed a transition from methanogenetic conditions (calcite bearing methanogenetic signature) to sulfate reducing (precipitation of pyrite on calcite surface), however, the timing of this transition is so far unclear. The results from this study gives indications of the complex nature of sulfur and carbon cycling in fractured crystalline environments and highlights the usefulness of in situ stable isotope analysis. - Highlights: • The carbon isotope variation in fracture calcite was measured in situ. • The δ 13 C values were used to investigate carbon sources and cycling in fractured rock. • Information on biogenic processes in the paleogroundwaters was gained.
International Nuclear Information System (INIS)
Marine, I.W.
1975-01-01
At the Savannah River plant of the Atomic Energy Commission near Aiken, South Carolina, there are three distinct groundwater systems: the coastal plain sediments, the crystalline metamorphic rocks, and a buried Triassic basin. The coastal plain sediments include several Cretaceous and Tertiary granular aquifers and aquicludes, the total thickness being about 305 m. Below these sediments, water occurs in small fractures in crystalline metamorphic rock (hornblende schist and gneiss with lesser amounts of quartzite). Water level fluctuations due to earth tides are recorded in the crystalline metamorphic rock system and in the coastal plain sediments. No water level fluctuations due to earth tides have been observed in wells in the Triassic rock because of the very low permeability. The water level fluctuations due to earth tides in the crystalline rock are about 10 cm, and those in the sediments are about 1.8 cm. The use of water level fluctuations due to earth tides to calculate porosity appears to present practical difficulties both in the crystalline metamorphic rock system and in the coastal plain sediments. In a 1-yr pumping test on a well in the crystalline metamorphic rock the flow was controlled to within 0.1 per cent of the total discharge, which was 0.94 l/s. The water level fluctuations due to earth tides in the pumping well were 10 cm, the same as when this well was not being pumped. (U.S.)
Harte, Philip T.; Anderson, Alton; Williams, John H.
2014-01-01
Identifying hydraulically active fractures in low permeability, crystalline-bedrock aquifers requires a variety of geophysical and hydrogeophysical borehole tools and approaches. One such approach is Single Borehole Dilution Tests (SBDT), which in some low flow cases have been shown to provide greater resolution of borehole flow than other logging procedures, such as vertical differential Heat Pulse Flowmeter (HPFM) logging. Because the tools used in SBDT collect continuous profiles of water quality or dye changes, they can identify horizontal flow zones and vertical flow. We used SBDT with a food grade blue dye as a tracer and dual photometer-nephelometer measurements to identify low flow zones.SBDT were conducted at seven wells with open boreholes (exceeding 300 ft). At most of the wells HPFM logs were also collected. The seven wells are set in low-permeability, fractured granite and gneiss rocks underlying a former tetrachloroeythylene (PCE) source area at the Savage Municipal Well Superfund site in Milford, NH. Time series SBDT logs were collected at each of the seven wells under three distinct hydraulic conditions: (1) ambient conditions prior to a pump test at an adjacent well, (2) mid test, after 2-3 days of the start of the pump test, and (3) at the end of the test, after 8-9 days of the pump test. None of the SBDT were conducted under pumping conditions in the logged well. For each condition, wells were initially passively spiked with blue dye once and subsequent time series measurements were made.Measurement accuracy and precision of the photometer tool is important in SBDT when attempting to detect low rates of borehole flow. Tests indicate that under ambient conditions, none of the wells had detectable flow as measured with HPFM logging. With SBDT, 4 of the 7 showed the presence of some very low flow. None of 5 (2 of the 7 wells initially logged with HPFM under ambient conditions were not re-logged) wells logged with the HPFM during the pump test had
International Nuclear Information System (INIS)
Gustafsson, E.; Klockars, C.-E.
1981-04-01
The purpose of the investigation has been study the following parameters along existing fractures between two boreholes: hydraulic properties of rock mass and fractures; adsorptive properties of some selected tracers during transport along fractures; dispersivity and dilution of tracers during transport in fractures; kinematic porosity of fractured bedrock. The procedure has been to determine the hydraulic properties of a rock mass by means of conventional hydraulic testing methods in 100 m deep boreholes, and to study transport mechanisms and properties of selected tracers in a selected fracture zone between two boreholes. (Auth.)
Time dependent fracture growth in intact crystalline rock: new laboratory procedures
International Nuclear Information System (INIS)
Backers, T.; Stephansson, O.
2008-01-01
Short term laboratory tests to determine the strength of rock material are commonly used to assess stability of rock excavations. However, loading the rock below its short term strength may lead to delayed failure due to slow stable fracture growth. This time-dependent phenomenon is called subcritical fracture growth. A fracture mechanics based approach is applied in this study to determine the parameters describing subcritical fracture growth under Mode Ⅰ (tensile) and Mode Ⅱ (in-plane shear) loading in terms of the stress intensity factors of saturated granodiorite from the) Aespoe HRL. A statistical method is applied to data from three-point bending (tension) and Punch-Through Shear with Confining Pressure, PTS/CP, (shear) experiments. One population of each set-up was subjected to rapid loading tests yielding a strength probability distribution. A second population was loaded up to a certain fraction of the statistical percentage for failure and the time-to-failure was determined. From these two populations the subcritical fracture growth parameters were determined successfully. Earlier studies demonstrated subcritical fracture growth under Mode I loading conditions, but this study shows that under a Mode Ⅱ load time-dependent fracture growth exists as well. (authors)
Energy Technology Data Exchange (ETDEWEB)
Gentier, S
2005-07-01
The modeling of fluid flows inside granite massifs is an important task for the evaluation of the feasibility of radioactive waste storage inside such formations. This document makes a synthesis of the works carried out since about 15 years, in particular by the French bureau of geological and mining research (BRGM), about the hydro-mechanical behaviour of a fracture and about the hydrodynamical characterization of fracture networks inside crystalline rocks: 1 - introduction; 2 - hydro-mechanical behaviour under normal stress: experimental results (hydro-mechanical behaviour, flow regimes, mechanical behaviour, test protocol, complementary tests, influence of samples size), geometrical interpretation of experimental results (relation with walls geometry, relation with voids geometry, relation with contacts geometry), hydro-mechanical modeling (hydraulic modeling, mechanical modeling); 3 - from the hydro-mechanical behaviour under normal stress to the coupling with heat transfers and chemistry: experiment for the study of the chemo-thermo-hydro-mechanical coupling (experimental results, relation with walls morphology), thermo-hydro-mechanical experiments, thermo-hydro-chemical experiments with fractures, conclusions; 4 - hydro-mechanical behaviour during shear: experimental results, geometrical interpretation (relation with the geometry of damaged zones, relation with voids geometry, relation with walls geometry), hydro-mechanical modeling (mechanical modeling, hydro-mechanical modeling of the behaviour during shear). (J.S.)
Directory of Open Access Journals (Sweden)
F. Tuba
2014-11-01
Full Text Available The plane-stress ductile fracture of poly(#-caprolactone (PCL has been investigated as a function of molecular weight and related crystalline structure. Because of the interacting effects in semi-crystalline polymers a separate study of a given structural parameter is rather challenging. Nevertheless, this polymer seems to be a good model material to study the effect of molecular weight on the essential work of fracture, as the interactions between the separate parameters, at room temperature, are negligible. The molecular characteristics of PCL were determined by size exclusion chromatography. To confirm the entangled molecular structure of studied polymers rheological measurements were performed. The crystalline morphology has been characterized by differential scanning calorimetry and wide angle X-ray diffraction. Quasi-static tensile tests and essential work of fracture tests were performed to study the mechanical behavior. Based on the experimental observations an empirical model has been proposed to outline the molecular weight and crystallinity dependence of the essential work of fracture in this semi-crystalline polymer.
Frawley, Keara G.; Bakst, Ian; Sypek, John T.; Vijayan, Sriram; Weinberger, Christopher R.; Canfield, Paul C.; Aindow, Mark; Lee, Seok-Woo
2018-04-01
The plastic deformation and fracture mechanisms in single-crystalline CaFe2As2 has been studied using nanoindentation and density functional theory simulations. CaFe2As2 single crystals were grown in a Sn-flux, resulting in homogeneous and nearly defect-free crystals. Nanoindentation along the [001] direction produces strain bursts, radial cracking, and lateral cracking. Ideal cleavage simulations along the [001] and [100] directions using density functional theory calculations revealed that cleavage along the [001] direction requires a much lower stress than cleavage along the [100] direction. This strong anisotropy of cleavage strength implies that CaFe2As2 has an atomic-scale layered structure, which typically exhibits lateral cracking during nanoindentation. This special layered structure results from weak atomic bonding between the (001) Ca and Fe2As2 layers.
Fracture detection in crystalline rock using ultrasonic reflection techniques: Volume 1
International Nuclear Information System (INIS)
Palmer, S.P.
1982-11-01
This research was initiated to investigate using ultrasonic seismic reflection techniques to detect fracture discontinuities in a granitic rock. Initial compressional (P) and shear (SH) wave experiments were performed on a 0.9 x 0.9 x 0.3 meter granite slab in an attempt to detect seismic energy reflected from the opposite face of the slab. It was found that processing techniques such as deconvolution and array synthesis could improve the standout of the reflection event. During the summers of 1979 and 1980 SH reflection experiments were performed at a granite quarry near Knowles, California. The purpose of this study was to use SH reflection methods to detect an in situ fracture located one to three meters behind the quarry face. These SH data were later analyzed using methods similar to those applied in the laboratory. Interpretation of the later-arriving events observed in the SH field data as reflections from a steeply-dipping fracture was inconclusive. 41 refs., 43 figs., 7 tabs
An investigation of 'sparse channel networks'. Characteristic behaviours and their causes
Energy Technology Data Exchange (ETDEWEB)
Black, J.H. (In Situ Solutions, East Bridgford (GB)); Barker, J.A.; Woodman, N.D. (Univ. of Southampton (GB))
2007-09-15
This report represents a third study in a series concerned with groundwater flow in poorly permeable fractured crystalline rocks. The study has brought together three linked, but distinct, elements; a mathematical analysis of the intersection of ellipses, a review of field measurements associated with nuclear waste repository investigations and probabilistic simulations using a lattice network numerical model. We conclude that the model of channels that traverse fracture intersections without necessarily branching is a very likely representation of reality. More generally, assembling all the lines of evidence, it is suggested that groundwater flow systems in fractured crystalline rocks in the environs of underground laboratories have the following characteristics: Groundwater flows within a sparse network of channels just above the percolation limit. The frequency of intersections is low in that individual channels extend considerable distances between significant junctions. Individual channels often extend over many fracture surfaces and the resulting flow system is only weakly related to the density or size of mappable fractures. The sparseness of systems compared to the size of drifts and tunnels means that only a very few flow channels are intersected by drifts and tunnels. Highly convergent flow is required to connect to the rest of the network and this is misinterpreted as a skin of low hydraulic conductivity. Systems are so sparse that they are controlled by a few 'chokes' that give rise to compartments of head, and probably, of groundwater chemistry. Channels occur on all fracture planes, including those within fracture zones, and although the characteristics of the fracture zone channel networks may differ from those in surrounding rocks, they are nonetheless still channel networks. The actively flowing sparse channel network, occurring within any particular rock, is a naturally selected, small sub-set of the available channels. Hence, there are
An investigation of 'sparse channel networks'. Characteristic behaviours and their causes
International Nuclear Information System (INIS)
Black, J.H.; Barker, J.A.; Woodman, N.D.
2007-09-01
This report represents a third study in a series concerned with groundwater flow in poorly permeable fractured crystalline rocks. The study has brought together three linked, but distinct, elements; a mathematical analysis of the intersection of ellipses, a review of field measurements associated with nuclear waste repository investigations and probabilistic simulations using a lattice network numerical model. We conclude that the model of channels that traverse fracture intersections without necessarily branching is a very likely representation of reality. More generally, assembling all the lines of evidence, it is suggested that groundwater flow systems in fractured crystalline rocks in the environs of underground laboratories have the following characteristics: Groundwater flows within a sparse network of channels just above the percolation limit. The frequency of intersections is low in that individual channels extend considerable distances between significant junctions. Individual channels often extend over many fracture surfaces and the resulting flow system is only weakly related to the density or size of mappable fractures. The sparseness of systems compared to the size of drifts and tunnels means that only a very few flow channels are intersected by drifts and tunnels. Highly convergent flow is required to connect to the rest of the network and this is misinterpreted as a skin of low hydraulic conductivity. Systems are so sparse that they are controlled by a few 'chokes' that give rise to compartments of head, and probably, of groundwater chemistry. Channels occur on all fracture planes, including those within fracture zones, and although the characteristics of the fracture zone channel networks may differ from those in surrounding rocks, they are nonetheless still channel networks. The actively flowing sparse channel network, occurring within any particular rock, is a naturally selected, small sub-set of the available channels. Hence, there are many
International Nuclear Information System (INIS)
Backers, Tobias; Stephansson, Ove
2008-01-01
The stability issues of deposition holes of a repository layout according to the KBS-3 concept in the sparsely fractured Forsmark granites are analysed with the emphasis on fracture mechanics. At the start of the project the rock mass is viewed as a continuum. In a second step explicit fracture networks are introduced and included in the numerical rock fracture models. The software Fracod2D was used for the rock fracture mechanics analysis. Assuming deposition holes located in a continuous, homogeneous elastic rock mass and The presented stress state of the rock mass the following results were obtained: For single KBS-3H deposition holes oriented in the direction of the minimum horizontal stress, Sh, bore hole breakouts are introduced for all depth levels. For KBS-3H holes which are oriented in direction of SH, no significant fracturing can be expected. In case of vertical deposition holes according to KBS-3V an increased risk of fracturing at greater depth levels (> 500m) is evident. At shallow depth levels ( 5MPa gives a favourable situation about spalling for the KBS-3H and KBS-3V layouts. To prevent spalling, it is important to build up a swelling pressure soon after excavation, so that the enhanced stresses in the surrounding of the deposition ii holes are reduced. This has a positive impact on other excavation activities and also on time-dependent fracturing. After excavation and filling of the deposition holes with subsequent increase of swelling pressure, the temperature will increase in the vicinity of the excavation. For the range of swelling pressures predicted for the KBS-3 concept, i.e. 5.5MPa to 7.2MPa, no significant fracturing for the KBS-3H concept with the axis parallel SH at depths below about 600m was discovered. The results from other layouts bare the risk of partly significant fracturing. About 60ka from closing the repository an ice cover of approximately 3km is expected over Forsmark. This dead load increases the in-situ stresses and
Gourion-Arsiquaud, Samuel; Lukashova, Lyudmilla; Power, Jon; Loveridge, Nigel; Reeve, Jonathan; Boskey, Adele L.
2012-01-01
After age 60 hip fracture risk strongly increases, but only a fifth of this increase is attributable to reduced mineral density (BMD, measured clinically). Changes in bone quality, specifically bone composition as measured by Fourier Transform Infrared spectroscopic imaging (FTIRI), also contribute to fracture risk. Here, FTIRI was applied to study the femoral neck and provide spatially derived information on its mineral and matrix properties in age-matched fractured and non-fractured bones. Whole femoral neck cross sections, divided into quadrants along the neck’s axis, from 10 women with hip fracture and 10 cadaveric controls were studied using FTIRI and micro-computed Tomography. Although 3-dimensional micro-CT bone mineral densities were similar, the mineral-to-matrix ratio was reduced in the cases of hip fracture, confirming previous reports. New findings were that the FTIRI microscopic variation (heterogeneity) of the mineral-to-matrix ratio was substantially reduced in the fracture group as was the heterogeneity of the carbonate-to-phosphate ratio. Conversely, the heterogeneity of crystallinity was increased. Increased variation of crystallinity was statistically associated with reduced variation of the carbonate-to-phosphate ratio. Anatomical variation in these properties between the different femoral neck quadrants was reduced in the fracture group compared to controls. While our treatment-naïve patients had reduced rather than increased bending resistance, these changes in heterogeneity associated with hip fracture are in another way comparable to the effects of experimental bisphosphonate therapy, which decreases heterogeneity and other indicators of bone’s toughness as a material. PMID:22865771
International Nuclear Information System (INIS)
Ota, Kunio; Alexander, W.R.
2001-01-01
The joint Nagra/JNC radionuclide Retardation Programme has now been ongoing for more thean 10 years with the main aim of direct testing of radionuclide transport models for fractured crystalline rocks in as realistic a manner as possible. A large programme of field, laboratory and natural analogue studies has been carried out at the Grimsel Test Site in the central Swiss Alps. The understanding and modelling of both the processes and the structures influencing radionuclide transport in fractured crystalline rocks have matured as has the experimental technology, which has contributed to develop confidence in the applicability of the underlying research models in a repository performance assessment. In this report, the successes and set-backs of this programme are discussed as is the general approach to the thorough testing of the process models and of model assumptions. (author)
Gourion-Arsiquaud, Samuel; Lukashova, Lyudmilla; Power, Jon; Loveridge, Nigel; Reeve, Jonathan; Boskey, Adele L
2013-01-01
After the age of 60 years, hip fracture risk strongly increases, but only a fifth of this increase is attributable to reduced bone mineral density (BMD, measured clinically). Changes in bone quality, specifically bone composition as measured by Fourier transform infrared spectroscopic imaging (FTIRI), also contribute to fracture risk. Here, FTIRI was applied to study the femoral neck and provide spatially derived information on its mineral and matrix properties in age-matched fractured and nonfractured bones. Whole femoral neck cross sections, divided into quadrants along the neck's axis, from 10 women with hip fracture and 10 cadaveric controls were studied using FTIRI and micro-computed tomography. Although 3-dimensional micro-CT bone mineral densities were similar, the mineral-to-matrix ratio was reduced in the cases of hip fracture, confirming previous reports. New findings were that the FTIRI microscopic variation (heterogeneity) of the mineral-to-matrix ratio was substantially reduced in the fracture group as was the heterogeneity of the carbonate-to-phosphate ratio. Conversely, the heterogeneity of crystallinity was increased. Increased variation of crystallinity was statistically associated with reduced variation of the carbonate-to-phosphate ratio. Anatomical variation in these properties between the different femoral neck quadrants was reduced in the fracture group compared with controls. Although our treatment-naive patients had reduced rather than increased bending resistance, these changes in heterogeneity associated with hip fracture are in another way comparable to the effects of experimental bisphosphonate therapy, which decreases heterogeneity and other indicators of bone's toughness as a material. Copyright © 2013 American Society for Bone and Mineral Research.
Mathurin, Frédéric A.; Drake, Henrik; Tullborg, Eva-Lena; Berger, Tobias; Peltola, Pasi; Kalinowski, Birgitta E.; Åström, Mats E.
2014-05-01
Dissolved and solid phase cesium (Cs) was studied in the upper 1.2 km of a coastal granitoid fracture network on the Baltic Shield (Äspö Hard Rock Laboratory and Laxemar area, SE Sweden). There unusually high Cs concentrations (up to 5-6 μg L-1) occur in the low-temperature (single and primary control of dissolved Cs in these systems. The high Cs concentrations in the saline groundwater is ascribed to long-term weathering of minerals, primarily Cs-enriched fracture coatings dominated by illite and mixed-layer clays and possibly wall rock micaceous minerals. The high Cs concentrations in the groundwater of marine origin are, in contrast, explained by relatively fast cation exchange reactions. As indicated by the field data and predicted by 1D solute transport modeling, alkali cations with low-energy hydration carried by intruding marine water are capable of (NH4+ in particular and K+ to some extent) replacing Cs+ on frayed edge (FES) sites on illite in the fracture coatings. The result is a rapid and persistent (at least in the order of decades) buildup of dissolved Cs concentrations in fractures where marine water flows downward. The identification of high Cs concentrations in young groundwater of marine origin and the predicted capacity of NH4+ to displace Cs from fracture solids are of particular relevance in the disposal of radioactive nuclear waste deep underground in crystalline rock.
Arancibia, G.; Roquer, T.; Sepúlveda, J.; Veloso, E. A.; Morata, D.; Rowland, J. V.
2017-12-01
Fault zones can control the location, emplacement, and evolution of economic mineral deposits and geothermal systems by acting as barriers and/or conduits to crustal fluid flow (e.g. magma, gas, oil, hydro-geothermal and groundwater). The nature of the fault control permeability is critical in the case of fluid flow into low porosity/permeability crystalline rocks, since structural permeability provides the main hydraulic conductivity to generate a natural fractured system. However, several processes accompanying the failure of rocks (i.e. episodic permeability given by cycling ruptures, mineral precipitation from fluids in veins, dissolution of minerals in the vicinity of a fracture) promote a complex time-dependent and enhancing/reducing fault-controlled permeability. We propose the Southern Volcanic Zone (Southern Andes, Chile) as a case study to evaluate the role of the structural permeability in low porosity crystalline rocks belonging to the Miocene North Patagonian Batholith. Recently published studies propose a relatively well-constrained first-order role of two active fault systems, the arc-parallel (NS to NNE trending) Liquiñe Ofqui Fault System and the arc-oblique (NW trending) Andean Transverse Fault Zones, in fluid flow at crustal scales. We now propose to examine the Liquiñe ( 39°S) and Maihue ( 40°S) areas as sites of interaction between these fault systems, in order to evaluate a naturally fractured geothermal system. Preliminary results indicate upwelling of thermal water directly from fractured granite or from fluvial deposits overlying granitoids. Measured temperatures of thermal springs suggest a low- to medium-enthalpy system, which could potentially be harnessed for use in geothermal energy applications (e.g. heating, wood dryer and green house), which are much needed in Southern Chile. Future work will aim to examine the nature of structural permeability from the regional to the microscopic scale connecting the paleo- and current- fluid
de La Bernardie, Jérôme; de Dreuzy, Jean-Raynald; Bour, Olivier; Thierion, Charlotte; Ausseur, Jean-Yves; Lesuer, Hervé; Le Borgne, Tanguy
2016-04-01
Geothermal energy is a renewable energy source particularly attractive due to associated low greenhouse gas emission rates. Crystalline rocks are in general considered of poor interest for geothermal applications at shallow depths (structure, heat exchanges and storage may be highlighted.
Crystalline and Crystalline International Disposal Activities
Energy Technology Data Exchange (ETDEWEB)
Viswanathan, Hari S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chu, Shaoping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dittrich, Timothy M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hyman, Jeffrey De' Haven [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Karra, Satish [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Makedonska, Nataliia [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reimus, Paul William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-03-06
This report presents the results of work conducted between September 2015 and July 2016 at Los Alamos National Laboratory in the crystalline disposal and crystalline international disposal work packages of the Used Fuel Disposition Campaign (UFDC) for DOE-NE’s Fuel Cycle Research and Development program. Los Alamos focused on two main activities during this period: Discrete fracture network (DFN) modeling to describe flow and radionuclide transport in complex fracture networks that are typical of crystalline rock environments, and a comprehensive interpretation of three different colloid-facilitated radionuclide transport experiments conducted in a fractured granodiorite at the Grimsel Test Site in Switzerland between 2002 and 2013. Chapter 1 presents the results of the DFN work and is divided into three main sections: (1) we show results of our recent study on the correlation between fracture size and fracture transmissivity (2) we present an analysis and visualization prototype using the concept of a flow topology graph for characterization of discrete fracture networks, and (3) we describe the Crystalline International work in support of the Swedish Task Force. Chapter 2 presents interpretation of the colloidfacilitated radionuclide transport experiments in the crystalline rock at the Grimsel Test Site.
International Nuclear Information System (INIS)
Alexander, W.R.; MacKenzie, A.B.; Scott, R.D.; McKinley, I.G.
1990-06-01
Current Swiss concepts for the disposal of radioactive waste involve disposal in deep mined repositories to ensure that only insignificant quantities of radionuclides will ever reach the surface and so enter the biosphere. The rock formations presently considered as potential candidates for hosting radwaste repositories have thus been selected on the basis of their capacity to isolate radionuclides from the biosphere. An important factor in ensuring such containment is a very low solute transport rate through the host formation. However, it is considered likely that, in the formations of interest in the Swiss programme (eg. granites, argillaceous sediments, anhydrite), the rocks will be fractured to some extent even at repository depth. In the instance of the cumulative failure of near-field barriers in the repository, these hydraulically connected fractures in the host formation could be very important far-field routes of migration (and possible sites of retardation) of radionuclides dissolved in the groundwaters. In this context, the so-called 'matrix diffusion' mechanism is potentially very important for radionuclide retardation. This report is the culmination of a programme which has attempted to assess the potential influence of these water-bearing fractures on radionuclide transport in a crystalline rock radwaste repository. 162 refs., 36 figs., 16 tabs
International Nuclear Information System (INIS)
Normani, S.D.; Sykes, J.F.
2011-01-01
A high resolution three-dimensional sub-regional scale (104 km 2 ) density-dependent, discretely fractured groundwater flow model with hydro-mechanical coupling and pseudo-permafrost was developed from a larger 5734 km 2 regional-scale groundwater flow model of a Canadian Shield setting. The objective of the work is to determine the sensitivity of modelled groundwater system evolution to the hydro-mechanical parameters. The discrete fracture dual continuum numerical model FRAC3DVS-OPG was used for all simulations. A discrete fracture network model delineated from surface features was superimposed onto an approximate 790 000 element domain mesh with approximately 850 000 nodes. Orthogonal fracture faces (between adjacent finite element grid blocks) were used to best represent the irregular discrete fracture zone network. Interconnectivity of the permeable fracture zones is an important pathway for the possible migration and subsequent reduction in groundwater and contaminant residence times. The crystalline rock matrix between these structural discontinuities was assigned mechanical and flow properties characteristic of those reported for the Canadian Shield. The variation of total dissolved solids with depth was assigned using literature data for the Canadian Shield. Performance measures for the sensitivity analysis include equivalent freshwater heads, environmental heads, linear velocities, and depth of penetration by conservative non-decaying tracers released at the surface. A 121 000 year North American continental scale paleo-climate simulation was applied to the domain with ice-sheet histories estimated by the University of Toronto Glacial Systems Model (UofT GSM). Hydro-mechanical coupling between the rock matrix and the pore fluid, due to the ice sheet normal stress, was included in the simulations. The flow model included the influence of vertical strain and assumed that areal loads were homogeneous. Permafrost depth was applied as a permeability reduction
International Nuclear Information System (INIS)
Yamamoto, Koshi; Yoshida, Hidekazu; Akagawa, Fuminori; Nishimoto, Shoji; Metcalfe, Richard
2013-01-01
Highlights: • Deep redox front developed in orogenic granitic rock have been studied. • The process was controlled by the buffering capacity of minerals. • This is an analogue of redox front penetration into HLW repositories in Japan. - Abstract: Redox buffering is one important factor to be considered when assessing the barrier function of potential host rocks for a deep geological repository for long-lived radioactive waste. If such a repository is to be sited in fractured crystalline host rock it must be demonstrated that waste will be emplaced deeper than the maximum depth to which oxidizing waters can penetrate from the earth’s surface via fractures, during the assessment timeframe (typically 1 Ma). An analogue for penetration of such oxidizing water occurs in the Cretaceous Toki Granite of central Japan. Here, a deep redox front is developed along water-conducting fractures at a depth of 210 m below the ground surface. Detailed petrographical studies and geochemical analyses were carried out on drill core specimens of this redox front. The aim was to determine the buffering processes and behavior of major and minor elements, including rare earth elements (REEs), during redox front development. The results are compared with analytical data from an oxidized zone found along shallow fractures (up to 20 m from the surface) in the same granitic rock, in order to understand differences in elemental migration according to the depth below the ground surface of redox-front formation. Geochemical analyses by XRF and ICP-MS of the oxidized zone at 210 m depth reveal clear changes in Fe(III)/Fe(II) ratios and Ca depletion across the front, while Fe concentrations vary little. In contrast, the redox front identified along shallow fractures shows strong enrichments of Fe, Mn and trace elements in the oxidized zone compared with the fresh rock matrix. The difference can be ascribed to the changing Eh and pH of groundwater as it flows downwards in the granite, due to
International Nuclear Information System (INIS)
Drake, Henrik; Suksi, Juhani; Tullborg, Eva-Lena; Lahaye, Yann
2017-01-01
When planning for long term deep geological repositories for spent nuclear fuel knowledge of processes that will influence and change the sub-surface environment is crucial. For repositories in northern Europe and similar areas, influence from advancing and retreating continental ice sheets must be planned for. Rapid transport of meltwater into the bedrock may introduce oxic conditions at great depth, which may affect the copper canisters planned to encapsulate the spent fuel. The lack of direct observations has led to simplified modelling assumptions not reflecting the complexity of natural systems. As part of a unique field and modelling study, The Greenland Analogue Project, of a continental ice sheet and related sub-surface conditions, we here present mineralogical and U-series data unravelling the Quaternary redox history in the deep bedrock fracture system close to the margin of the Greenland ice sheet. The aim was to increase the understanding of circulation of potentially oxygenated glacial meltwater from the surface down to 650 m depth. Secondary mineral coatings were sampled from open fractures in cored boreholes down to 650 m, within and below the current permafrost. Despite continental ice sheet coverage and/or prevailing permafrost during large parts of the last 1 Ma, measured disequilibrium in the 238 U- 234 U- 230 Th system shows that water has circulated in the bedrock fracture system at various occasions during this time span. In fractures of the upper 60 m, infiltration of oxygenated surface water has resulted in a prominent near-surface ”oxidised zone” with abundant FeOOH precipitation. However, this zone must be relict because it is currently within permafrost and the U-series disequilibrium signatures of most fracture coatings show evidence of deposition of U prior to the Holocene and even prior to the last glaciation maximum which occurred less than 100 ka ago. This U deposition is found both within and below the near surface
Frampton, A.; Hyman, J.; Zou, L.
2017-12-01
Analysing flow and transport in sparsely fractured media is important for understanding how crystalline bedrock environments function as barriers to transport of contaminants, with important applications towards subsurface repositories for storage of spent nuclear fuel. Crystalline bedrocks are particularly favourable due to their geological stability, low advective flow and strong hydrogeochemical retention properties, which can delay transport of radionuclides, allowing decay to limit release to the biosphere. There are however many challenges involved in quantifying and modelling subsurface flow and transport in fractured media, largely due to geological complexity and heterogeneity, where the interplay between advective and dispersive flow strongly impacts both inert and reactive transport. A key to modelling transport in a Lagrangian framework involves quantifying pathway travel times and the hydrodynamic control of retention, and both these quantities strongly depend on heterogeneity of the fracture network at different scales. In this contribution, we present recent analysis of flow and transport considering fracture networks with single-fracture heterogeneity described by different multivariate normal distributions. A coherent triad of fields with identical correlation length and variance are created but which greatly differ in structure, corresponding to textures with well-connected low, medium and high permeability structures. Through numerical modelling of multiple scales in a stochastic setting we quantify the relative impact of texture type and correlation length against network topological measures, and identify key thresholds for cases where flow dispersion is controlled by single-fracture heterogeneity versus network-scale heterogeneity. This is achieved by using a recently developed novel numerical discrete fracture network model. Furthermore, we highlight enhanced flow channelling for cases where correlation structure continues across
Johnson, Carole D.; Kiel, Kristal F.; Joesten, Peter K.; Pappas, Katherine L.
2016-10-04
The U.S. Geological Survey, in cooperation with the Connecticut Department of Energy and Environmental Protection, investigated the characteristics of the bedrock aquifer in the Tylerville section of Haddam, Connecticut, from June to August 2014. As part of this investigation, geophysical logs were collected from six water-supply wells and were analyzed to (1) identify well construction, (2) determine the rock type and orientation of the foliation and layering of the rock, (3) characterize the depth and orientation of fractures, (4) evaluate fluid properties of the water in the well, and (5) determine the relative transmissivity and head of discrete fractures or fracture zones. The logs included the following: caliper, electromagnetic induction, gamma, acoustic and (or) optical televiewer, heat-pulse flowmeter under ambient and pumped conditions, hydraulic head data, fluid electrical conductivity and temperature under postpumping conditions, and borehole-radar reflection collected in single-hole mode. In a seventh borehole, a former water-supply well, only caliper, fluid electrical conductivty, and temperature logs were collected, because of a constriction in the borehole.This report includes a description of the methods used to collect and process the borehole geophysical data, the description of the data collected in each of the wells, and a comparison of the results collected in all of the wells. The data are presented in plots of the borehole geophysical logs, tables, and figures. Collectively these data provide valuable characterizations that can be used to improve or inform site conceptual models of groundwater flow in the study area.
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.
Energy Technology Data Exchange (ETDEWEB)
Pearson, C.
1982-04-01
Using source parameters estimated from seismic spectra and magnitudes estimated from coda lengths, we demonstrate that the log-linear relationship between moment and magnitude holds for events with magnitudes as low as -6. Using, as a data set, events induced by hydraulic fracturing experiments at the Fenton Hill, New Mexico, Hot Dry Rock (HDR) geothermal site, we find that the relationship between magnitude M and seismic moment (Mo) is log (Mo) = 17.27+0.77 M Moreover, the linear relationship between seismic moment and source radius (r) holds for the Fenton Hill microearthquakes. Analyses of the Fenton Hill data yield the following relationship. log (r) = 2.28+0.19 log (Mo)
International Nuclear Information System (INIS)
Vomvoris, S.; Andrews, R.W.; Lanyon, G.W.; Voborny, O.; Wilson, W.
1996-04-01
Switzerland is one of many nations with nuclear power that is seeking to identify rock types and locations that would be suitable for the underground disposal of nuclear waste. A common challenge among these programs is to provide engineering designers and safety analysts with a reasonably representative hydrogeological input dataset that synthesizes the relevant information from direct field observations as well as inferences and model results derived from those observations. Needed are estimates of the volumetric flux through a volume of rock and the distribution of that flux into discrete pathways between the repository zones and the biosphere. These fluxes are not directly measurable but must be derived based on understandings of the range of plausible hydrogeologic conditions expected at the location investigated. The methodology described in this report utilizes conceptual and numerical models at various scales to derive the input dataset. The methodology incorporates an innovative approach, called the geometric approach, in which field observations and their associated uncertainty, together with a conceptual representation of those features that most significantly affect the groundwater flow regime, were rigorously applied to generate alternative possible realizations of hydrogeologic features in the geosphere. In this approach, the ranges in the output values directly reflect uncertainties in the input values. As a demonstration, the methodology is applied to the derivation of the hydrogeological dataset for the crystalline basement of Northern Switzerland. (author) figs., tabs., refs
Dynamic characterisation of the specific surface area for fracture networks
Cvetkovic, V.
2017-12-01
One important application of chemical transport is geological disposal of high-level nuclear waste for which crystalline rock is a prime candidate for instance in Scandinavia. Interconnected heterogeneous fractures of sparsely fractured rock such as granite, act as conduits for transport of dissolved tracers. Fluid flow is known to be highly channelized in such rocks. Channels imply narrow flow paths, adjacent to essentially stagnant water in the fracture and/or the rock matrix. Tracers are transported along channelised flow paths and retained by minerals and/or stagnant water, depending on their sorption properties; this mechanism is critical for rocks to act as a barrier and ultimately provide safety for a geological repository. The sorbing tracers are retained by diffusion and sorption on mineral surfaces, whereas non-sorbing tracers can be retained only by diffusion into stagnant water of fractures. The retention and transport properties of a sparsely fractured rock will primarily depend on the specific surface area (SSA) of the fracture network which is determined by the heterogeneous structure and flow. The main challenge when characterising SSA on the field-scale is its dependence on the flow dynamics. We first define SSA as a physical quantity and clarify its importance for chemical transport. A methodology for dynamic characterisation of SSA in fracture networks is proposed that relies on three sets of data: i) Flow rate data as obtained by a flow logging procedure; ii) transmissivity data as obtained by pumping tests; iii) fracture network data as obtained from outcrop and geophysical observations. The proposed methodology utilises these data directly as well as indirectly through flow and particle tracking simulations in three-dimensional discrete fracture networks. The methodology is exemplified using specific data from the Swedish site Laxemar. The potential impact of uncertainties is of particular significance and is illustrated for radionuclide
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
Dessirier, Benoît; Frampton, Andrew; Jarsjö, Jerker
2015-11-01
Geological disposal of spent nuclear fuel in deep crystalline rock is investigated as a possible long term solution in Sweden and Finland. The fuel rods would be cased in copper canisters and deposited in vertical holes in the floor of deep underground tunnels, embedded within an engineered bentonite buffer. Recent experiments at the Äspö Hard Rock Laboratory (Sweden) showed that the high suction of unsaturated bentonite causes a de-saturation of the adjacent rock at the time of installation, which was also independently predicted in model experiments. Remaining air can affect the flow patterns and alter bio-geochemical conditions, influencing for instance the transport of radionuclides in the case of canister failure. However, thus far, observations and model realizations are limited in number and do not capture the conceivable range and combination of parameter values and boundary conditions that are relevant for the thousands of deposition holes envisioned in an operational final repository. In order to decrease this knowledge gap, we introduce here a formalized, systematic and fully integrated approach to study the combined impact of multiple factors on air saturation and dissolution predictions, investigating the impact of variability in parameter values, geometry and boundary conditions on bentonite buffer saturation times and on occurrences of rock de-saturation. Results showed that four parameters consistently appear in the top six influential factors for all considered output (target) variables: the position of the fracture intersecting the deposition hole, the background rock permeability, the suction representing the relative humidity in the open tunnel and the far field pressure value. The combined influence of these compared to the other parameters increases as one targets a larger fraction of the buffer reaching near-saturation. Strong interaction effects were found, which means that some parameter combinations yielded results (e.g., time to
International Nuclear Information System (INIS)
Drake, Henrik; Tullborg, Eva-Lena
2009-01-01
Fracture minerals calcite, pyrite, gypsum, barite and quartz, formed during several events have been analysed for δ 13 C, δ 18 O, δ 34 S, 87 Sr/ 86 Sr, trace element chemistry and fluid inclusions in order to gain knowledge of the paleohydrogeological evolution of the Simpevarp area, south-eastern Sweden. This area is dominated by Proterozoic crystalline rocks and is currently being investigated by the Swedish Nuclear Fuel and Waste Management Co. (SKB) in order to find a suitable location for a deep-seated repository for spent nuclear fuel. Knowledge of the paleohydrogeological evolution is essential to understand the stability or evolution of the groundwater system over a time scale relevant to the performance assessment for a spent nuclear fuel repository. The ages of the minerals analysed range from the Proterozoic to possibly the Quaternary. The Proterozoic calcite and pyrite show inorganic and hydrothermal-magmatic stable isotope signatures and were probably formed during a long time period as indicated by the large span in temperatures (c. 200-360 deg. C) and salinities (0-24 wt.% eq. CaCl 2 ), obtained from fluid inclusion analyses. The Paleozoic minerals were formed from organically influenced brine-type fluids at temperatures of 80-145 deg. C. The isotopic results indicate that low temperature calcite and pyrite may have formed during different events ranging in time possibly from the end of the Paleozoic until the Quaternary. Formation conditions ranging from fresh to brackish and saline waters have been distinguished based on calcite crystal morphologies. The combination of δ 18 O and crystal morphologies show that the fresh-saline water interface has changed considerably over time, and water similar to the present meteoric water and brackish seawater at the site, have most probably earlier been residing in the bedrock. Organic influence and closed system in situ microbial activity causing disequilibrium are indicated by extremely low δ 13 C (down
Groundwater in crystalline bedrock
International Nuclear Information System (INIS)
Palmqvist, K.
1990-06-01
The aim of this project was to make detailed descriptions of the geological conditions and the different kinds of leakage in some tunnels in Sweden, to be able to describe the presence of ground water in crystalline bedrock. The studies were carried out in TBM tunnels as well as in conventionally drilled and blasted tunnels. Thanks to this, it has been possible to compare the pattern and appearance of ground water leakage in TBM tunnels and in blasted tunnels. On the basis of some experiments in a TBM tunnel, it has been confirmed that a detailed mapping of leakage gives a good picture of the flow paths and their aquiferous qualities in the bedrock. The same picture is found to apply even in cautious blasted tunnels. It is shown that the ground water flow paths in crystalline bedrock are usually restricted to small channels along only small parts of the fractures. This is also true for fracture zones. It has also been found that the number of flow paths generally increases with the degree of tectonisation, up to a given point. With further tectonisation the bedrock is more or less crushed which, along with mineral alteration, leaves only a little space left for the formation of water channels. The largest individual flow paths are usually found in fracture zones. The total amount of ground water leakage per m tunnel is also greater in fracture zones than in the bedrock between the fracture zones. In mapping visible leakage, five classes have been distinguished according to size. Where possible, the individual leak inflow has been measured during the mapping process. The quantification of the leakage classes made in different tunnels are compared, and some quantification standards suggested. A comparison of leakage in different rock types, tectonic zones, fractures etc is also presented. (author)
International Nuclear Information System (INIS)
Stevenson, D.R.; Brown, A.; Davison, C.C.; Gascoyne, M.; McGregor, R.G.; Ophori, D.U.; Scheier, N.W.; Stanchell, F.; Thorne, G.A.; Tomsons, D.K.
1996-04-01
A revised conceptual hydrogeologic model of regional groundwater flow in the crystalline rocks of the Whiteshell Research Area (WRA) has been developed by a team of AECL geoscientists. The revised model updates an earlier model developed in 1985, and has a much broader database. This database was compiled from Landsat and airborne radar images, geophysical surveys and surface mapping, and from analyses of fracture logs, hydraulic tests and water samples collected from a network of deep boreholes drilled across the WRA. The boundaries of the revised conceptual model were selected to coincide with the natural hydraulic boundaries assumed for the regional groundwater flow systems in the WRA. The upper and lower boundaries are the water table and a horizontal plane 4 km below ground surface. For modelling purposes the rocks below 4 km are considered to be impermeable. The rocks of the modelled region were divided on the basis of fracture characteristics into three categories: fractured zones (FZs); moderately fractured rock (MFR); and sparsely fractured rock (SFR). The FZs are regions of intensely fractured rock. Seventy-six FZs were selected to form the fault framework within the revised conceptual model. The physical rock/water properties of the FZs, MFR and SFR were selected by analysis of field data from hydraulic and tracer tests, laboratory test data and water quality data. These properties were used to define a mathematical groundwater flow model of the WRA using AECL's MOTIF finite element code (Ophori et al. 1995, 1996). (author). 29 refs., 4 tabs., 12 figs
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
Boorder, H. de
1982-01-01
A framework of major, deep-reaching fracture zones in western Central Africa is inferred from airborne magnetometric and surface geological observations in Central Angola and Gabon. A correlation is proposed between these observations and the continental negative Bouguer anomaly. The minimum
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.
International Nuclear Information System (INIS)
Capilla, J. E.; Rodrigo, J.; Gomez Hernandez, J. J.
2003-01-01
Characterizing the uncertainty of flow and mass transport models requires the definition of stochastic models to describe hydrodynamic parameters. Porosity and hydraulic conductivity (K) are two of these parameters that exhibit a high degree of spatial variability. K is usually the parameter whose variability influence to a more extended degree solutes movement. In fracture media, it is critical to properly characterize K in the most altered zones where flow and solutes migration tends to be concentrated. However, K measurements use to be scarce and sparse. This fact calls to consider stochastic models that allow quantifying the uncertainty of flow and mass transport predictions. This paper presents a convective transport problem solved in a 3D block of fractured crystalline rock. the case study is defined based on data from a real geological formation. As the scarcity of K data in fractures does not allow supporting classical multi Gaussian assumptions for K in fractures, the non multi Gaussian hypothesis has been explored, comparing mass transport results for alternative Gaussian and non-Gaussian assumptions. The latter hypothesis allows reproducing high spatial connectivity for extreme values of K. This feature is present in nature, might lead to reproduce faster solute pathways, and therefore should be modeled in order to obtain reasonably safe prediction of contaminants migration in a geological formation. The results obtained for the two alternative hypotheses show a remarkable impact of the K random function model in solutes movement. (Author) 9 refs
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.
Energy Technology Data Exchange (ETDEWEB)
Chan, T.; Stanchell, F.W. [Atomic Energy of Canada Ltd, Toronto (Canada); Christiansson, R. [Swedish Nuclear Fuel and Waste Management Co., Figeholm (Sweden); Boulton, G.S. [Univ. of Edinburgh (United Kingdom). School of GeoSciences; Eriksson, L.O.; Vistrand, P.; Wallroth, T. [Chalmers Univ. of Technology, Goeteborg (Sweden). Dept. of Geology; Hartikainen, J. [Helsinki Univ. of Technology (Finland). Inst. of Mathematics; Jensen, M.R. [0ntario Power Generation, Toronto (Canada); Mas lvars, D. [Royal Inst. of Technology, Stockholm (Sweden). Land and Water Resources engineering
2005-02-15
A number of studies related to past and on-going deep repository performance assessments have identified glaciation/deglaciation as major future events in the next few hundred thousand years capable of causing significant impact on the long term performance of the repository system. Benchmark Test 3 (BMT3) of the international DECOVALEX III project has been designed to provide an illustrative example that explores the mechanical and hydraulic response of a fractured crystalline rock mass to a period of glaciation. The primary purpose of this numerical study is to investigate whether transient events associated with a glacial cycle could significantly influence the performance of a deep geological repository in a crystalline shield setting. A conceptual site-scale (tens of kilometres) hydro-mechanical (HM) model was assembled based primarily on site-specific litho-structural, hydrogeological and geomechanical data from the Whiteshell Research Area in the Canadian Shield, with simplification and generalization. Continental glaciological modelling of the Laurentide ice sheet through the last glacial cycle lasting approximately 100,000 years suggests that this site was glaciated at about 60 ka and between about 22.5 ka and 11 ka before present with maximum ice sheet thickness reaching 2,500 m and maximum basal water pressure head reaching 2000 m. The ice-sheet/drainage model was scaled down to generate spatially and temporally variable hydraulic and mechanical glaciated surface boundary conditions for site-scale subsurface HM modelling and permafrost modelling. Under extreme periglacial conditions permafrost was able to develop down to the assumed 500-m repository horizon. Two- and three-dimensional coupled HM finite-element simulations indicate: during ice-sheet advance there is rapid rise in hydraulic head, high transient hydraulic gradients and high groundwater velocities 2-3 orders of magnitude higher than under nonglacial conditions; surface water recharges deeper
International Nuclear Information System (INIS)
Chan, T.; Stanchell, F.W.; Christiansson, R.; Boulton, G.S.; Mas lvars, D.
2005-02-01
A number of studies related to past and on-going deep repository performance assessments have identified glaciation/deglaciation as major future events in the next few hundred thousand years capable of causing significant impact on the long term performance of the repository system. Benchmark Test 3 (BMT3) of the international DECOVALEX III project has been designed to provide an illustrative example that explores the mechanical and hydraulic response of a fractured crystalline rock mass to a period of glaciation. The primary purpose of this numerical study is to investigate whether transient events associated with a glacial cycle could significantly influence the performance of a deep geological repository in a crystalline shield setting. A conceptual site-scale (tens of kilometres) hydro-mechanical (HM) model was assembled based primarily on site-specific litho-structural, hydrogeological and geomechanical data from the Whiteshell Research Area in the Canadian Shield, with simplification and generalization. Continental glaciological modelling of the Laurentide ice sheet through the last glacial cycle lasting approximately 100,000 years suggests that this site was glaciated at about 60 ka and between about 22.5 ka and 11 ka before present with maximum ice sheet thickness reaching 2,500 m and maximum basal water pressure head reaching 2000 m. The ice-sheet/drainage model was scaled down to generate spatially and temporally variable hydraulic and mechanical glaciated surface boundary conditions for site-scale subsurface HM modelling and permafrost modelling. Under extreme periglacial conditions permafrost was able to develop down to the assumed 500-m repository horizon. Two- and three-dimensional coupled HM finite-element simulations indicate: during ice-sheet advance there is rapid rise in hydraulic head, high transient hydraulic gradients and high groundwater velocities 2-3 orders of magnitude higher than under nonglacial conditions; surface water recharges deeper
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.
A new scripting library for modeling flow and transport in fractured rock with channel networks
Dessirier, Benoît; Tsang, Chin-Fu; Niemi, Auli
2018-02-01
Deep crystalline bedrock formations are targeted to host spent nuclear fuel owing to their overall low permeability. They are however highly heterogeneous and only a few preferential paths pertaining to a small set of dominant rock fractures usually carry most of the flow or mass fluxes, a behavior known as channeling that needs to be accounted for in the performance assessment of repositories. Channel network models have been developed and used to investigate the effect of channeling. They are usually simpler than discrete fracture networks based on rock fracture mappings and rely on idealized full or sparsely populated lattices of channels. This study reexamines the fundamental parameter structure required to describe a channel network in terms of groundwater flow and solute transport, leading to an extended description suitable for unstructured arbitrary networks of channels. An implementation of this formalism in a Python scripting library is presented and released along with this article. A new algebraic multigrid preconditioner delivers a significant speedup in the flow solution step compared to previous channel network codes. 3D visualization is readily available for verification and interpretation of the results by exporting the results to an open and free dedicated software. The new code is applied to three example cases to verify its results on full uncorrelated lattices of channels, sparsely populated percolation lattices and to exemplify the use of unstructured networks to accommodate knowledge on local rock fractures.
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.
Generic Crystalline Disposal Reference Case
Energy Technology Data Exchange (ETDEWEB)
Painter, Scott Leroy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chu, Shaoping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Harp, Dylan Robert [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Perry, Frank Vinton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Wang, Yifeng [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-02-20
A generic reference case for disposal of spent nuclear fuel and high-level radioactive waste in crystalline rock is outlined. The generic cases are intended to support development of disposal system modeling capability by establishing relevant baseline conditions and parameters. Establishment of a generic reference case requires that the emplacement concept, waste inventory, waste form, waste package, backfill/buffer properties, EBS failure scenarios, host rock properties, and biosphere be specified. The focus in this report is on those elements that are unique to crystalline disposal, especially the geosphere representation. Three emplacement concepts are suggested for further analyses: a waste packages containing 4 PWR assemblies emplaced in boreholes in the floors of tunnels (KBS-3 concept), a 12-assembly waste package emplaced in tunnels, and a 32-assembly dual purpose canister emplaced in tunnels. In addition, three failure scenarios were suggested for future use: a nominal scenario involving corrosion of the waste package in the tunnel emplacement concepts, a manufacturing defect scenario applicable to the KBS-3 concept, and a disruptive glaciation scenario applicable to both emplacement concepts. The computational approaches required to analyze EBS failure and transport processes in a crystalline rock repository are similar to those of argillite/shale, with the most significant difference being that the EBS in a crystalline rock repository will likely experience highly heterogeneous flow rates, which should be represented in the model. The computational approaches required to analyze radionuclide transport in the natural system are very different because of the highly channelized nature of fracture flow. Computational workflows tailored to crystalline rock based on discrete transport pathways extracted from discrete fracture network models are recommended.
Dessirier, B.; Frampton, A.; Fransson, À.; Jarsjö, J.
2016-08-01
The repository concept for geological disposal of spent nuclear fuel in Sweden and Finland is planned to be constructed in sparsely fractured crystalline bedrock and with an engineered bentonite buffer to embed the waste canisters. An important stage in such a deep repository is the postclosure phase following the deposition and the backfilling operations when the initially unsaturated buffer material gets hydrated by the groundwater delivered by the natural bedrock. We use numerical simulations to interpret observations on buffer wetting gathered during an in situ campaign, the Bentonite Rock Interaction Experiment, in which unsaturated bentonite columns were introduced into deposition holes in the floor of a 417 m deep tunnel at the Äspö Hard Rock Laboratory in Sweden. Our objectives are to assess the performance of state-of-the-art flow models in reproducing the buffer wetting process and to investigate to which extent dependable predictions of buffer wetting times and saturation patterns can be made based on information collected prior to buffer insertion. This would be important for preventing insertion into unsuitable bedrock environments. Field data and modeling results indicate the development of a de-saturated zone in the rock and show that in most cases, the presence or absence of fractures and flow heterogeneity are more important factors for correct wetting predictions than the total inflow. For instance, for an equal open-hole inflow value, homogeneous inflow yields much more rapid buffer wetting than cases where fractures are represented explicitly thus creating heterogeneous inflow distributions.
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.
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...
International Nuclear Information System (INIS)
Jing, L.
2005-02-01
temperature can be predicted accurately without consideration of coupling to hydraulic and mechanical processes. It is also clear that mechanical behaviour, that is, evolution of stress in the buffer-rock system, cannot be appropriately predicted without consideration of temperature effects and effects of fluid pressure. It is not clear at this point whether the hydraulic behaviour (for example resaturation of the buffer and radioactive nuclide transport) can be significantly impacted by T and M processes. For the parameter set adopted in this analysis, the resaturation time is slightly impacted by the effect of temperature whereas the mechanically induced changes in permeability does not significantly impact the resaturation process. The general results of the impact of various THM couplings for sparsely fractured rocks conducted in this paper are in line with those of a homogenous low permeability rock defined as in BMT1B. The main difference is that the hydraulic conducting fractures provide an additional water supply that prevents desaturation of the rock and accelerates the buffer resaturation process
Energy Technology Data Exchange (ETDEWEB)
Jing, L. [Royal Inst. of Technology, Stockholm (Sweden). Engineering Geology; Nguyen, T.S. [Canadian Nuclear Safety Commission, Ottawa, ON (Canada)] (eds.)
2005-02-15
temperature can be predicted accurately without consideration of coupling to hydraulic and mechanical processes. It is also clear that mechanical behaviour, that is, evolution of stress in the buffer-rock system, cannot be appropriately predicted without consideration of temperature effects and effects of fluid pressure. It is not clear at this point whether the hydraulic behaviour (for example resaturation of the buffer and radioactive nuclide transport) can be significantly impacted by T and M processes. For the parameter set adopted in this analysis, the resaturation time is slightly impacted by the effect of temperature whereas the mechanically induced changes in permeability does not significantly impact the resaturation process. The general results of the impact of various THM couplings for sparsely fractured rocks conducted in this paper are in line with those of a homogenous low permeability rock defined as in BMT1B. The main difference is that the hydraulic conducting fractures provide an additional water supply that prevents desaturation of the rock and accelerates the buffer resaturation process.
Site characterization in fractured crystalline rock
International Nuclear Information System (INIS)
Andersson, Peter; Andersson, J.E.; Gustafsson, E.; Nordqvist, R.; Voss, C.
1993-03-01
This report concerns a study which is part of the SKI performance assessment project SITE-94. SITE-94 is a performance assessment of a hypothetical repository at a real site. The main objective of the project is to determine how site specific data should be assimilated into the performance assessment process and to evaluate how uncertainties inherent in site characterization will influence performance assessment results. Other important elements of SITE-94 are the development of a practical and defensible methodology for defining, constructing and analyzing scenarios, the development of approaches for treatment of uncertainties, evaluation of canister integrity, and the development and application of an appropriate Quality Assurance plan for Performance Assessments. (111 refs.)
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.
International Nuclear Information System (INIS)
Jang, Dong Il; Jeong, Gyeong Seop; Han, Min Gu
1992-08-01
This book introduces basic theory and analytical solution of fracture mechanics, linear fracture mechanics, non-linear fracture mechanics, dynamic fracture mechanics, environmental fracture and fatigue fracture, application on design fracture mechanics, application on analysis of structural safety, engineering approach method on fracture mechanics, stochastic fracture mechanics, numerical analysis code and fracture toughness test and fracture toughness data. It gives descriptions of fracture mechanics to theory and analysis from application of engineering.
United States Crystalline Repository Project - key research areas
International Nuclear Information System (INIS)
Patera, E.S.
1986-01-01
The Crystalline Repository Project is responsible for siting the second high-level nuclear waste repository in crystalline rock for the US Department of Energy. A methodology is being developed to define data and information needs and a way to evaluate that information. The areas of research the Crystalline Repository Project is involved in include fluid flow in a fractured network, coupled thermal, chemical and flow processes and cooperation in other nations and OECD research programs
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.
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.
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
Fatigue damage and fracture behavior of tungsten fiber reinforced Zr-based metallic glassy composite
Energy Technology Data Exchange (ETDEWEB)
Zhang, H. [Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang 110016 (China); Zhang, Z.F. [Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang 110016 (China)]. E-mail: zhfzhang@imr.ac.cn; Wang, Z.G. [Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang 110016 (China); Qiu, K.Q. [Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang 110016 (China); Zhang, H.F. [Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang 110016 (China); Zang, Q.S. [Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang 110016 (China); Hu, Z.Q. [Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang 110016 (China)
2006-02-25
The fatigue life, damage and fracture behavior of tungsten fiber reinforced metallic glass Zr{sub 41.25}Ti{sub 13.75}Ni{sub 10}Cu{sub 12.5}Be{sub 22.5} composites are investigated under cyclic push-pull loading. It is found that the fatigue life of the composite increases with increasing the volume fraction of tungsten fibers. Similar to crystalline metals, the regions of crack initiation, propagation and overload fracture can be discerned on the fracture surface of the specimen. Fatigue crack normally initiates in the metallic glass matrix at the outer surface of the composite specimen and propagates predominantly in the matrix. Different crack front profile around the tungsten fibers and fiber pullout demonstrate that fatigue crack may propagate around the fiber, leading to bridging of the crack faces by the unbroken fiber and hence improved fatigue crack-growth resistance. Locally decreased effective stiffness in the region where fiber distribution is sparse may provide preferential crack path in the composite. A proposed model was exercised to elucidate different tungsten fiber fracture morphologies in the fatigue crack propagation and overload fracture regions in the light of Poisson's ratio effect during fatigue loading.
Fatigue damage and fracture behavior of tungsten fiber reinforced Zr-based metallic glassy composite
International Nuclear Information System (INIS)
Zhang, H.; Zhang, Z.F.; Wang, Z.G.; Qiu, K.Q.; Zhang, H.F.; Zang, Q.S.; Hu, Z.Q.
2006-01-01
The fatigue life, damage and fracture behavior of tungsten fiber reinforced metallic glass Zr 41.25 Ti 13.75 Ni 10 Cu 12.5 Be 22.5 composites are investigated under cyclic push-pull loading. It is found that the fatigue life of the composite increases with increasing the volume fraction of tungsten fibers. Similar to crystalline metals, the regions of crack initiation, propagation and overload fracture can be discerned on the fracture surface of the specimen. Fatigue crack normally initiates in the metallic glass matrix at the outer surface of the composite specimen and propagates predominantly in the matrix. Different crack front profile around the tungsten fibers and fiber pullout demonstrate that fatigue crack may propagate around the fiber, leading to bridging of the crack faces by the unbroken fiber and hence improved fatigue crack-growth resistance. Locally decreased effective stiffness in the region where fiber distribution is sparse may provide preferential crack path in the composite. A proposed model was exercised to elucidate different tungsten fiber fracture morphologies in the fatigue crack propagation and overload fracture regions in the light of Poisson's ratio effect during fatigue loading
Crystalline and Crystalline International Disposal Activities
Energy Technology Data Exchange (ETDEWEB)
Viswanathan, Hari S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chu, Shaoping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reimus, Paul William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Makedonska, Nataliia [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hyman, Jeffrey De' Haven [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Karra, Satish [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dittrich, Timothy M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-12-21
This report presents the results of work conducted between September 2014 and July 2015 at Los Alamos National Laboratory in the crystalline disposal and crystalline international disposal work packages of the Used Fuel Disposition Campaign (UFDC) for DOE-NE’s Fuel Cycle Research and Development program.
Becker, M.; Bour, O.; Le Borgne, T.; Longuevergne, L.; Lavenant, N.; Cole, M. C.; Guiheneuf, N.
2017-12-01
Determining hydraulic and transport connectivity in fractured bedrock has long been an important objective in contaminant hydrogeology, petroleum engineering, and geothermal operations. A persistent obstacle to making this determination is that the characteristic length scale is nearly impossible to determine in sparsely fractured networks. Both flow and transport occur through an unknown structure of interconnected fracture and/or fracture zones making the actual length that water or solutes travel undetermined. This poses difficulties for flow and transport models. For, example, hydraulic equations require a separation distance between pumping and observation well to determine hydraulic parameters. When wells pairs are close, the structure of the network can influence the interpretation of well separation and the flow dimension of the tested system. This issue is explored using hydraulic tests conducted in a shallow fractured crystalline rock. Periodic (oscillatory) slug tests were performed at the Ploemeur fractured rock test site located in Brittany, France. Hydraulic connectivity was examined between three zones in one well and four zones in another, located 6 m apart in map view. The wells are sufficiently close, however, that the tangential distance between the tested zones ranges between 6 and 30 m. Using standard periodic formulations of radial flow, estimates of storativity scale inversely with the square of the separation distance and hydraulic diffusivity directly with the square of the separation distance. Uncertainty in the connection paths between the two wells leads to an order of magnitude uncertainty in estimates of storativity and hydraulic diffusivity, although estimates of transmissivity are unaffected. The assumed flow dimension results in alternative estimates of hydraulic parameters. In general, one is faced with the prospect of assuming the hydraulic parameter and inverting the separation distance, or vice versa. Similar uncertainties exist
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.
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
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.
Frederiks, R.; Lowry, C.; Mutiibwa, R.; Moisy, S.; Thapa, L.; Oriba, J.
2017-12-01
In the past two years, Uganda has witnessed an influx of nearly one million refugees who have settled in the sparsely populated northwestern region of the country. This rapid population growth has created high demand for clean water resources. Water supply has been unable to keep pace with demand because the fractured rock aquifers underlying the region often produce low yielding wells. To facilitate management of groundwater resources, it is necessary to quantify the spatial distribution of groundwater. In fractured rock aquifers, there is significant spatial variability in water storage because fractures must be both connected and abundant for water to be extracted in usable quantities. Two conceptual models were evaluated to determine the groundwater storage mechanism in the fractured crystalline bedrock aquifers of northwestern Uganda where by permeability is controlled by faulting, which opens up fractures in the bedrock, or weathering, which occurs when water dissolves components of rock. In order to test these two conceptual models, geologic well logs and available hydrologic data were collected and evaluated using geostatistical and numerical groundwater models. The geostatistical analysis focused on identifying spatially distributed patterns of high and low water yield. The conceptual models were evaluated numerically using four inverse groundwater MODFLOW models based on head and estimated flux targets. The models were based on: (1) the mapped bedrock units using an equivalent porous media approach (2) bedrock units with the addition of known fault zones (3) bedrock units with predicted units of deep weathering based on surface slopes, and (4) bedrock units with discrete faults and simulated weathered zones. Predicting permeable zones is vital for water well drilling in much of East Africa and South America where there is an abundance of both fractured rock and tectonic activity. Given that the population of these developing regions is growing, the demand
,
1992-01-01
Crystalline silica is the scientific name for a group of minerals composed of silicon and oxygen. The term crystalline refers to the fact that the oxygen and silicon atoms are arranged in a threedimensional repeating pattern. This group of minerals has shaped human history since the beginning of civilization. From the sand used for making glass to the piezoelectric quartz crystals used in advanced communication systems, crystalline silica has been a part of our technological development. Crystalline silica's pervasiveness in our technology is matched only by its abundance in nature. It's found in samples from every geologic era and from every location around the globe. Scientists have known for decades that prolonged and excessive exposure to crystalline silica dust in mining environments can cause silicosis, a noncancerous lung disease. During the 1980's, studies were conducted that suggested that crystalline silica also was a carcinogen. As a result of these findings, crystalline silica has been regulated under the Occupational Safety and Health Administration's (OSHA) Hazard Communication Standard (HCS). Under HCS, OSHAregulated businesses that use materials containing 0.1% or more crystalline silica must follow Federal guidelines concerning hazard communication and worker training. Although the HCS does not require that samples be analyzed for crystalline silica, mineral suppliers or OSHAregulated
... and ceramic manufacturing and the tool and die, steel and foundry industries. Crystalline silica is used in manufacturing, household abrasives, adhesives, paints, soaps, and glass. Additionally, ...
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.
Used Fuel Disposal in Crystalline Rocks. FY15 Progress Report
Energy Technology Data Exchange (ETDEWEB)
Wang, Yifeng [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-08-20
The objective of the Crystalline Disposal R&D Work Package is to advance our understanding of long-term disposal of used fuel in crystalline rocks and to develop necessary experimental and computational capabilities to evaluate various disposal concepts in such media. Chapter headings are as follows: Fuel matrix degradation model and its integration with performance assessments, Investigation of thermal effects on the chemical behavior of clays, Investigation of uranium diffusion and retardation in bentonite, Long-term diffusion of U(VI) in bentonite: dependence on density, Sorption and desorption of plutonium by bentonite, Dissolution of plutonium intrinsic colloids in the presence of clay and as a function of temperature, Laboratory investigation of colloid-facilitated transport of cesium by bentonite colloids in a crystalline rock system, Development and demonstration of discrete fracture network model, Fracture continuum model and its comparison with discrete fracture network model.
An evaluation of hydrogeologic data of crystalline rock systems
International Nuclear Information System (INIS)
Raven, K.G.; Lafleur, D.W.
1986-12-01
This report presents a detailed review of hydrogeologic data collected as part of various research programs investigating fractured crystalline rock around the world. Based on the available information describing the test equipment, test methods and analytical techniques, the data have been assessed in terms of their reliability and representativeness, and likely error ranges have been assigned. The data reviewed include both hydrogeologic parameters, such as permeability, storage coefficient components (principally porosity), and fracture characteristic data
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....
Crystalline color superconductivity
International Nuclear Information System (INIS)
Alford, Mark; Bowers, Jeffrey A.; Rajagopal, Krishna
2001-01-01
In any context in which color superconductivity arises in nature, it is likely to involve pairing between species of quarks with differing chemical potentials. For suitable values of the differences between chemical potentials, Cooper pairs with nonzero total momentum are favored, as was first realized by Larkin, Ovchinnikov, Fulde, and Ferrell (LOFF). Condensates of this sort spontaneously break translational and rotational invariance, leading to gaps which vary periodically in a crystalline pattern. Unlike the original LOFF state, these crystalline quark matter condensates include both spin-zero and spin-one Cooper pairs. We explore the range of parameters for which crystalline color superconductivity arises in the QCD phase diagram. If in some shell within the quark matter core of a neutron star (or within a strange quark star) the quark number densities are such that crystalline color superconductivity arises, rotational vortices may be pinned in this shell, making it a locus for glitch phenomena
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...
a significant site for hydrogeological investigation in crystalline ...
Indian Academy of Sciences (India)
Estimating the hydrogeologic control of fractured aquifers in hard crystalline and metamorphosed rocks is challenging due to complexity in the development of secondary porosity. The present study in the Precambrian metamorphic terrain in and around the Balarampur of Purulia district, West Bengal, India, aims to estimate ...
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...
Dissolution of crystalline ceramics
International Nuclear Information System (INIS)
White, W.B.
1982-01-01
The present program objectives are to lay out the fundamentals of crystalline waste form dissolution. Nuclear waste ceramics are polycrystalline. An assumption of the work is that to the first order, the release rate of a particular radionuclide is the surface-weighted sum of the release rates of the radionuclide from each crystalline form that contains it. In the second order, of course, there will be synergistic effects. There will be also grain boundary and other microstructural influences. As a first approximation, we have selected crystalline phases one at a time. The sequence of investigations and measurements is: (i) Identification of the actual chemical reactions of dissolution including identification of the solid reaction products if such occur. (ii) The rates of these reactions are then determined empirically to give what may be called macroscopic kinetics. (iii) Determination of the rate-controlling mechanisms. (iv) If the rate is controlled by surface reactions, the final step would be to determine the atomic kinetics, that is the specific atomic reactions that occur at the dissolving interface. Our concern with the crystalline forms are in two areas: The crystalline components of the reference ceramic waste form and related ceramics and the alumino-silicate phases that appear in some experimental waste forms and as waste-rock interaction products. Specific compounds are: (1) Reference Ceramic Phases (zirconolite, magnetoplumbite, spinel, Tc-bearing spinel and perovskite); (2) Aluminosilicate phases (nepheline, pollucite, CsAlSi 5 O 12 , Sr-feldspar). 5 figures, 1 table
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.
Thermodynamics of Crystalline States
Fujimoto, Minoru
2010-01-01
Thermodynamics is a well-established discipline of physics for properties of matter in thermal equilibrium surroundings. Applying to crystals, however, the laws encounter undefined properties of crystal lattices, which therefore need to be determined for a clear and well-defined description of crystalline states. Thermodynamics of Crystalline States explores the roles played by order variables and dynamic lattices in crystals in a wholly new way. This book is divided into three parts. The book begins by clarifying basic concepts for stable crystals. Next, binary phase transitions are discussed to study collective motion of order variables, as described mostly as classical phenomena. In the third part, the multi-electron system is discussed theoretically, as a quantum-mechanical example, for the superconducting state in metallic crystals. Throughout the book, the role played by the lattice is emphasized and examined in-depth. Thermodynamics of Crystalline States is an introductory treatise and textbook on meso...
Liquid crystalline dihydroazulene photoswitches
DEFF Research Database (Denmark)
Petersen, Anne Ugleholdt; Jevric, Martyn; Mandle, Richard J.
2015-01-01
A large selection of photochromic dihydroazulene (DHA) molecules incorporating various substituents at position 2 of the DHA core was prepared and investigated for their ability to form liquid crystalline phases. Incorporation of an octyloxy-substituted biphenyl substituent resulted in nematic...... phase behavior and it was possible to convert one such compound partly into its vinylheptafulvene (VHF) isomer upon irradiation with light when in the liquid crystalline phase. This conversion resulted in an increase in the molecular alignment of the phase. In time, the meta-stable VHF returns...... to the DHA where the alignment is maintained. The systematic structural variation has revealed that a biaryl spacer between the DHA and the alkyl chain is needed for liquid crystallinity and that the one aromatic ring in the spacer cannot be substituted by a triazole. This work presents an important step...
... hip fractures in people of all ages. In older adults, a hip fracture is most often a result of a fall from a standing height. In people with very weak bones, a hip fracture can occur simply by standing on the leg and twisting. Risk factors The rate of hip fractures increases substantially with ...
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
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
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.
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.
Crystalline structure of metals
International Nuclear Information System (INIS)
Holas, A.
1972-01-01
An attempt is made to find the crystalline structure of metals on the basis of the existing theory of metals. The considerations are limited to the case of free crystals, that is, not subjected to any stresses and with T=0. The energy of the crystal lattice has been defined and the dependence of each term on structures and other properties of metals has been described. The energy has been used to find the values of crystalline structure parameters as the values at which the energy has an absolute minimum. The stability of the structure has been considered in cases of volume changes and shearing deformations. A semiqualitative description has been obtained which explains characteristic properties of one-electron metals. (S.B.)
Thermodynamics of Crystalline States
Fujimoto, Minoru
2013-01-01
Thermodynamics is a well-established discipline of physics for properties of matter in thermal equilibrium with the surroundings. Applying to crystals, however, the laws encounter undefined properties of crystal lattice, which therefore need to be determined for a clear and well-defined description of crystalline states. Thermodynamics of Crystalline States explores the roles played by order variables and dynamic lattices in crystals in a wholly new way. The book begins by clarifying basic concepts for stable crystals. Next, binary phase transitions are discussed to study collective motion of order variables, as described mostly as classical phenomena. New to this edition is the examination of magnetic crystals, where magnetic symmetry is essential for magnetic phase transitions. The multi-electron system is also discussed theoretically, as a quantum-mechanical example, for superconductivity in metallic crystals. Throughout the book, the role played by the lattice is emphasized and studied in-depth. Thermod...
... Video) Achilles Tendon Tear Additional Content Medical News Rib Fractures By Thomas G. Weiser, MD, MPH, Associate Professor, ... Tamponade Hemothorax Injury to the Aorta Pulmonary Contusion Rib Fractures Tension Pneumothorax Traumatic Pneumothorax (See also Introduction to ...
DEFF Research Database (Denmark)
Andreasen, Jens Ove; Christensen, Søren Steno Ahrensburg; Tsilingaridis, Georgios
2012-01-01
The purpose of this study was to analyze tooth loss after root fractures and to assess the influence of the type of healing and the location of the root fracture. Furthermore, the actual cause of tooth loss was analyzed....
International Nuclear Information System (INIS)
Wei, Jie; Li, Xiao-Ping
1993-01-01
In order to employ molecular dynamics (MD) methods, commonly used in condensed matter physics, we have derived the equations of motion for a beam of charged particles in the rotating rest frame of the reference particle. We include in the formalism that the particles are confined by the guiding and focusing magnetic fields, and that they are confined in a conducting vacuum pipe while interacting with each other via a Coulomb force. Numerical simulations using MD methods has been performed to obtain the equilibrium crystalline beam structure. The effect of the shearing force, centrifugal force, and azimuthal variation of the focusing strength are investigated. It is found that a constant gradient storage ring can not give a crystalline beam, but that an alternating-gradient (AG) structure can. In such a machine the ground state is, except for one-dimensional (1-D) crystals, time dependent. The ground state is a zero entropy state, despite the time-dependent, periodic variation of the focusing force. The nature of the ground state, similar to that found by Schiffer et al. depends upon the density and the relative focusing strengths in the transverse directions. At low density, the crystal is 1-D. As the density increases, it transforms into various kinds of 2-D and 3-D crystals. If the energy of the beam is higher than the transition energy of the machine, the crystalline structure can not be formed for lack of radial focusing
Stress fractures Overview Stress fractures are tiny cracks in a bone. They're caused by repetitive force, often from overuse — such as repeatedly jumping up and down or running long distances. Stress fractures can also arise from normal use of ...
Yu, Caixia; Zhao, Jingtao; Wang, Yanfei
2017-02-01
Studying small-scale geologic discontinuities, such as faults, cavities and fractures, plays a vital role in analyzing the inner conditions of reservoirs, as these geologic structures and elements can provide storage spaces and migration pathways for petroleum. However, these geologic discontinuities have weak energy and are easily contaminated with noises, and therefore effectively extracting them from seismic data becomes a challenging problem. In this paper, a method for detecting small-scale discontinuities using dictionary learning and sparse representation is proposed that can dig up high-resolution information by sparse coding. A K-SVD (K-means clustering via Singular Value Decomposition) sparse representation model that contains two stage of iteration procedure: sparse coding and dictionary updating, is suggested for mathematically expressing these seismic small-scale discontinuities. Generally, the orthogonal matching pursuit (OMP) algorithm is employed for sparse coding. However, the method can only update one dictionary atom at one time. In order to improve calculation efficiency, a regularized version of OMP algorithm is presented for simultaneously updating a number of atoms at one time. Two numerical experiments demonstrate the validity of the developed method for clarifying and enhancing small-scale discontinuities. The field example of carbonate reservoirs further demonstrates its effectiveness in revealing masked tiny faults and small-scale cavities.
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...
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)
Anon.
1989-01-01
Following pioneer work by specialists at the Soviet Novosibirsk Laboratory some ten years ago, interest developed in the possibility of 'freezing' ion beams in storage rings by pushing cooling (to smooth out beam behaviour) to its limits, the final goal being to lock the ions into a neat crystal pattern. After advances by groups working on laser cooled ions in traps, and with several cooling rings now in operation, a workshop on crystalline ion beams was organized recently by the GSI (Darmstadt) Laboratory and held at Wertheim in Germany
Taal-van Koppen, J.K.J.
2008-01-01
Fractured reservoirs are notoriously difficult to characterize because the resolution of seismic data is too low to detect fractures whereas borehole data is detailed but sparse. Therefore, outcrops can be of great support in gaining knowledge of the three-dimensional geometry of fracture networks,
Directory of Open Access Journals (Sweden)
Chad Correa
2017-09-01
Full Text Available History of present illness: A 77-year-old female presented to her primary care physician (PCP with right hip pain after a mechanical fall. She did not lose consciousness or have any other traumatic injuries. She was unable to ambulate post-fall, so X-rays were ordered by her PCP. Her X-rays were concerning for a right acetabular fracture (see purple arrows, so the patient was referred to the emergency department where a computed tomography (CT scan was ordered. Significant findings: The non-contrast CT images show a minimally displaced comminuted fracture of the right acetabulum involving the acetabular roof, medial and anterior walls (red arrows, with associated obturator muscle hematoma (blue oval. Discussion: Acetabular fractures are quite rare. There are 37 pelvic fractures per 100,000 people in the United States annually, and only 10% of these involve the acetabulum. They occur more frequently in the elderly totaling an estimated 4,000 per year. High-energy trauma is the primary cause of acetabular fractures in younger individuals and these fractures are commonly associated with other fractures and pelvic ring disruptions. Fractures secondary to moderate or minimal trauma are increasingly of concern in patients of advanced age.1 Classification of acetabular fractures can be challenging. However, the approach can be simplified by remembering the three basic types of acetabular fractures (column, transverse, and wall and their corresponding radiologic views. First, column fractures should be evaluated with coronally oriented CT images. This type of fracture demonstrates a coronal fracture line running caudad to craniad, essentially breaking the acetabulum into two halves: a front half and a back half. Secondly, transverse fractures should be evaluated by sagittally oriented CT images. By definition, a transverse fracture separates the acetabulum into superior and inferior halves with the fracture line extending from anterior to posterior
International Nuclear Information System (INIS)
Wei, Jie; Li, Xiao-Ping; Sessler, A.M.
1993-01-01
In order to employ Molecular Dynamics method, commonly used in condensed matter physics, we have derived the equations of motion for a beam of charged particles in the rotating rest frame of the reference particle. We include in the formalism that the particles are confined by the guiding and focusing magnetic fields, and that they are confined in a conducting vacuum pipe while interacting with each other via a Coulomb force. Numerical simulations has been performed to obtain the equilibrium structure. The effects of the shearing force, centrifugal force, and azimuthal variation of the focusing strength are investigated. It is found that a constant gradient storage ring can not give a crystalline beam, but that an alternating-gradient (AG) structure can. In such a machine the ground state is, except for one-dimensional (1-D) crystals, time-dependent. The ground state is a zero entropy state, despite the time-dependent, periodic variation of the focusing force. The nature of the ground state, similar to that found by Rahman and Schiffer, depends upon the density and the relative focusing strengths in the transverse directions. At low density, the crystal is 1-D. As the density increases, it transforms into various kinds of 2-D and 3-D crystals. If the energy of the beam is higher than the transition energy of the machine, the crystalline structure can not be formed for lack of radial focusing
International Nuclear Information System (INIS)
Wei, J.; Li, X.P.
1993-01-01
In order to employ the Molecular Dynamics method, commonly used in condensed matter physics, the authors have derived the equations of motion for a beam of charged particles in the rotating rest frame of the reference particle. They include in the formalism that the particles are confined by the guiding and focusing magnetic fields, and that they are confined in a conducting vacuum pipe while interacting with each other via a Coulomb force. Numerical simulations has been performed to obtain the equilibrium structure. The effects of the shearing force, centrifugal force, and azimuthal variation of the focusing strength are investigated. It is found that a constant gradient storage ring can not give a crystalline beam, but that an alternating-gradient (AG) structure can. In such a machine the ground state is, except for one-dimensional (1-D) crystals, time-dependent. The ground state is a zero entropy state, despite the time-dependent, periodic variation of the focusing force. The nature of the ground state, similar to that found by Rahman and Schiffer, depends upon the density and the relative focusing strengths in the transverse directions. At low density, the crystal is 1-D. As the density increases, it transforms into various kinds of 2-D and 3-D crystals. If the energy of the beam is higher than the transition energy of the machine, the crystalline structure can not be formed for lack of radial focusing
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.
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...
Dating fractures and fracture movement in the Lac du Bonnet Batholith
International Nuclear Information System (INIS)
Gascoyne, M.; Brown, A.; Ejeckam, R.B.; Everitt, R.A.
1997-04-01
This report examines and summarizes all work that has been done from 1980 to the present in determining the age of rock crystallization, fracture initiation, fracture reactivation and rates of fracture movement in the Lac du Bonnet Batholith to provide information for Atomic Energy of Canada Limited's (AECL) Canadian Nuclear Fuel Waste Management Program. Geological and petrographical indicators of relative age (e.g. cross-cutting relationships, sequences of fracture infilling minerals, P-T characteristics of primary and secondary minerals) are calibrated with radiometric age determinations on minerals and whole rock samples, using 87 Rb- 87 Sr, 40 K- 39 Ar, 40 Ar- 39 Ar and fission track methods. Most fractures and fracture zones inclined at low angles are found to be ancient features, first formed in the Early Proterozoic under conditions of deuteric alteration. Following some movement on fractures in the Late Proterozoic and Early Paleozoic, reactivation of fractures during the Pleistocene is established from uranium-series dating methods and use of stable isotopic contents of fracture infilling minerals (mainly calcite). Some indication of movement on fracture zones during the Pleistocene is given by electron spin resonance dating techniques on fault gouge. The slow rate of propagation of fractures is indicated by mineral infillings, their P-T characteristics and U-series calcite ages in a fracture in sparsely fractured rock, accessible from AECL's Underground Research Laboratory. These results collectively indicate that deep fractures observed in the batholith are ancient features and the fracturing and jointing in the upper 200 m is relatively recent (< 1 Ma) and largely a result of stress release. (author)
Pickrell, Brent B; Serebrakian, Arman T; Maricevich, Renata S
2017-05-01
Mandible fractures account for a significant portion of maxillofacial injuries and the evaluation, diagnosis, and management of these fractures remain challenging despite improved imaging technology and fixation techniques. Understanding appropriate surgical management can prevent complications such as malocclusion, pain, and revision procedures. Depending on the type and location of the fractures, various open and closed surgical reduction techniques can be utilized. In this article, the authors review the diagnostic evaluation, treatment options, and common complications of mandible fractures. Special considerations are described for pediatric and atrophic mandibles.
Liquid crystalline order in polymers
Blumstein, Alexandre
1978-01-01
Liquid Crystalline Order in Polymers examines the topic of liquid crystalline order in systems containing rigid synthetic macromolecular chains. Each chapter of the book provides a review of one important area of the field. Chapter 1 discusses scattering in polymer systems with liquid crystalline order. It also introduces the field of liquid crystals. Chapter 2 treats the origin of liquid crystalline order in macromolecules by describing the in-depth study of conformation of such macromolecules in their unassociated state. The chapters that follow describe successively the liquid crystalli
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.
Crystalline lens radioprotectors
International Nuclear Information System (INIS)
Belkacemi, Y.; Pasquier, D.; Castelain, B.; Lartigau, E.; Warnet, J.M.
2003-01-01
During more than a half of century, numerous compounds have been tested in different models against radiation-induced cataract. In this report, we will review the radioprotectors that have been already tested for non-human crystalline lens protection. We will focus on the most important published studies in this topic and the mechanisms of cyto-protection reported in. vitro and in. vivo from animals. The most frequent mechanisms incriminated in the cyto-protective effect are: free radical scavenging, limitation of lipid peroxidation, modulation of cycle progression increase of intracellular reduced glutathione pool, reduction of DNA strand breaks and limitation of apoptotic cell death. Arnifostine (or Ethyol) and anethole dithiolethione (or Sulfarlem), already used clinically as chemo- and radio-protectants, could be further test?r for ocular radioprotection particularly for radiation-induced cataract. (author)
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.
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.
Ghosh, Rajarshi; Gopalkrishnan, Kulandaswamy
2018-06-01
The aim of this study is to retrospectively analyze the incidence of facial fractures along with age, gender predilection, etiology, commonest site, associated dental injuries, and any complications of patients operated in Craniofacial Unit of SDM College of Dental Sciences and Hospital. This retrospective study was conducted at the Department of OMFS, SDM College of Dental Sciences, Dharwad from January 2003 to December 2013. Data were recorded for the cause of injury, age and gender distribution, frequency and type of injury, localization and frequency of soft tissue injuries, dentoalveolar trauma, facial bone fractures, complications, concomitant injuries, and different treatment protocols.All the data were analyzed using statistical analysis that is chi-squared test. A total of 1146 patients reported at our unit with facial fractures during these 10 years. Males accounted for a higher frequency of facial fractures (88.8%). Mandible was the commonest bone to be fractured among all the facial bones (71.2%). Maxillary central incisors were the most common teeth to be injured (33.8%) and avulsion was the most common type of injury (44.6%). Commonest postoperative complication was plate infection (11%) leading to plate removal. Other injuries associated with facial fractures were rib fractures, head injuries, upper and lower limb fractures, etc., among these rib fractures were seen most frequently (21.6%). This study was performed to compare the different etiologic factors leading to diverse facial fracture patterns. By statistical analysis of this record the authors come to know about the relationship of facial fractures with gender, age, associated comorbidities, etc.
Directory of Open Access Journals (Sweden)
Dogra A
1995-04-01
Full Text Available An extremely rare case of combined transverse and vertical fracture of sacrum with neurological deficit is reported here with a six month follow-up. The patient also had an L1 compression fracture. The patient has recovered significantly with conservative management.
The effects of bacteria on crystalline rock
International Nuclear Information System (INIS)
Brown, D.A.
1994-01-01
Many reactions involving inorganic minerals at water-rock interfaces have now been recognized to be bacterially mediated; these reactions could have a significant effect in the excavation of vaults for toxic and radioactive waste disposal. To investigate the role that bacteria play in the natural aqueous environment of crystalline rock the microbial growth factors of nutrition, energy and environment are described. Microbial activity has been investigated in Atomic Energy of Canada's Underground Research Laboratory (URL), situated in the Archean granitic Lac du Bonnet Batholith, Winnipeg, Manitoba. Faults, initiated in the Early Proterozoic, and later-formed fractures, provide ground-water pathways. Planktonic bacteria, free-swimming in the groundwater, have been observed in over 100 underground borehole samples. The number of bacteria varied from 10 3 to 10 5 mL -1 and appeared to decrease with depth and with increased salinity of the water. However, in the natural environment of deep (100-500 m) crystalline rocks, where nutrition is limited, formation of biofilms by sessile bacteria is a successful survival strategy. Natural biofilms at the URL and biofilms grown in bioreactors have been studied. The biofilms can accumulate different elements, depending upon the local environment. Precipitates of iron have been found in all the biofilms studied, where they are either passively accumulated or utilized as an energy source. Within the biofilm active and extensive biogeochemical immobilization of dissolved elements is controlled by distinct bacterial activities which are sufficiently discrete for hematite and siderite to be precipitated in close proximity
Zehnder, Alan T
2012-01-01
Fracture mechanics is a vast and growing field. This book develops the basic elements needed for both fracture research and engineering practice. The emphasis is on continuum mechanics models for energy flows and crack-tip stress- and deformation fields in elastic and elastic-plastic materials. In addition to a brief discussion of computational fracture methods, the text includes practical sections on fracture criteria, fracture toughness testing, and methods for measuring stress intensity factors and energy release rates. Class-tested at Cornell, this book is designed for students, researchers and practitioners interested in understanding and contributing to a diverse and vital field of knowledge. Alan Zehnder joined the faculty at Cornell University in 1988. Since then he has served in a number of leadership roles including Chair of the Department of Theoretical and Applied Mechanics, and Director of the Sibley School of Mechanical and Aerospace Engineering. He teaches applied mechanics and his research t...
Crystalline Bioceramic Materials
Directory of Open Access Journals (Sweden)
de Aza, P. N.
2005-06-01
Full Text Available A strong interest in the use of ceramics for biomedical engineering applications developed in the late 1960´s. Used initially as alternatives to metallic materials in order to increase the biocompatibility of implants, bioceramics have become a diverse class of biomaterials, presently including three basic types: relatively bioinert ceramics; bioactive or surface reactive bioceramics and bioresorbable ceramics. This review will only refer to bioceramics “sensus stricto”, it is to say, those ceramic materials constituted for nonmetallic inorganic compounds, crystallines and consolidated by thermal treatments of powders to high temperatures. Leaving bioglasses, glass-ceramics and biocements apart, since, although all of them are obtained by thermal treatments to high temperatures, the first are amorphous, the second are obtained by desvitrification of a glass and in them vitreous phase normally prevails on the crystalline phases and the third are consolidated by means of a hydraulic or chemical reaction to room temperature. A review of the composition, physiochemical properties and biological behaviour of the principal types of crystalline bioceramics is given, based on the literature data and on the own experience of the authors.
A finales de los años sesenta se despertó un gran interés por el uso de los materiales cerámicos para aplicaciones biomédicas. Inicialmente utilizados como una alternativa a los materiales metálicos, con el propósito de incrementar la biocompatibilidad de los implantes, las biocerámicas se han convertido en una clase diversa de biomateriales, incluyendo actualmente tres tipos: cerámicas cuasi inertes; cerámicas bioactivas o reactivas superficialmente y cerámicas reabsorbibles o biodegradables. En la presente revisión se hace referencia a las biocerámicas en sentido estricto, es decir, a aquellos materiales constitutitos por compuestos inorgánicos no metálicos, cristalinos y consolidados
Fracture of crystalline silicon nanopillars during electrochemical lithium insertion
Lee, S. W.; McDowell, M. T.; Berla, L. A.; Nix, W. D.; Cui, Y.
2012-01-01
in a solid can result in dramatic structural transformations and associated changes in mechanical behavior: This is particularly evident during electrochemical cycling of novel battery electrodes, such as alloying anodes, conversion oxides, and sulfur
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...
Reaction Front Evolution during Electrochemical Lithiation of Crystalline Silicon Nanopillars
Lee, Seok Woo
2012-12-01
The high theoretical specific capacity of Si as an anode material is attractive in lithium-ion batteries, although the issues caused by large volume changes during cycling have been a major challenge. Efforts have been devoted to understanding how diffusion-induced stresses cause fracture, but recent observations of anisotropic volume expansion in single-crystalline Si nanostructures require new theoretical considerations of expansion behavior during lithiation. Further experimental investigation is also necessary to better understand the anisotropy of the lithiation process. Here, we present a method to reveal the crystalline core of partially lithiated Si nanopillars with three different crystallographic orientations by using methanol to dissolve the Li atoms from the amorphous Li-Si alloy. The exposed crystalline cores have flat {110} surfaces at the pillar sidewalls; these surfaces represent the position of the reaction front between the crystalline core and the amorphous Li-Si alloy. It was also found that an amorphous Si structure remained on the flat surfaces of the crystalline core after dissolution of the Li, which was presumed to be caused by the accumulation of Si atoms left over from the removal of Li from the Li-Si alloy. © 2012 Wiley-VCH Verlag GmbH &Co. KGaA, Weinheim.
Reaction Front Evolution during Electrochemical Lithiation of Crystalline Silicon Nanopillars
Lee, Seok Woo; Berla, Lucas A.; McDowell, Matthew T.; Nix, William D.; Cui, Yi
2012-01-01
The high theoretical specific capacity of Si as an anode material is attractive in lithium-ion batteries, although the issues caused by large volume changes during cycling have been a major challenge. Efforts have been devoted to understanding how diffusion-induced stresses cause fracture, but recent observations of anisotropic volume expansion in single-crystalline Si nanostructures require new theoretical considerations of expansion behavior during lithiation. Further experimental investigation is also necessary to better understand the anisotropy of the lithiation process. Here, we present a method to reveal the crystalline core of partially lithiated Si nanopillars with three different crystallographic orientations by using methanol to dissolve the Li atoms from the amorphous Li-Si alloy. The exposed crystalline cores have flat {110} surfaces at the pillar sidewalls; these surfaces represent the position of the reaction front between the crystalline core and the amorphous Li-Si alloy. It was also found that an amorphous Si structure remained on the flat surfaces of the crystalline core after dissolution of the Li, which was presumed to be caused by the accumulation of Si atoms left over from the removal of Li from the Li-Si alloy. © 2012 Wiley-VCH Verlag GmbH &Co. KGaA, Weinheim.
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.
Microstructurally Based Prediction of High Strain Failure Modes in Crystalline Solids
2016-07-05
interfaces in hcp– fcc systems subjected to high strain-rate deformation and fracture modes, Journal of Materials Research, (8 2015): 0. doi: 10.1557/jmr...rupture • Comparison and validation with experimental observations/ measurements • New dislocation-density crystalline plasticity that accounts for...relationships between coherent interfaces in hcp– fcc systems subjected to high strain-rate deformation and fracture modes, Journal of Materials Research, Vol. 30
Interpretation of field experiments on the flow of water and tracers through crystalline rock
International Nuclear Information System (INIS)
Hodgkinson, D.P.; Lever, D.A.; Robinson, P.C.; Bourke, P.J.
1983-01-01
This paper reviews recent work at Harwell on the interpretation of field experiments on the flow of water and tracers through crystalline rock. First a model for the radial transport of tracers through an isolated fracture is outlined and used to analyse a recent Swedish experiment at Finnsjoen. Secondly, the theoretical and experimental approach that is being used to quantify flow and dispersion through networks of fractures is described
Acidization of shales with calcite cemented fractures
Kwiatkowski, Kamil; Szymczak, Piotr; Jarosiński, Marek
2017-04-01
Investigation of cores drilled from shale formations reveals a relatively large number of calcite-cemented fractures. Usually such fractures are reactivated during fracking and can contribute considerably to the permeability of the resulting fracture network. However, calcite coating on their surfaces effectively excludes them from production. Dissolution of the calcite cement by acidic fluids is investigated numerically with focus on the evolution of fracture morphology. Available surface area, breakthrough time, and reactant penetration length are calculated. Natural fractures in cores from Pomeranian shale formation (northern Poland) were analyzed and classified. Representative fractures are relatively thin (0.1 mm), flat and completely sealed with calcite. Next, the morphology evolution of reactivated natural fractures treated with low-pH fluids has been simulated numerically under various operating conditions. Depth-averaged equations for fracture flow and reactant transport has been solved by finite-difference method coupled with sparse-matrix solver. Transport-limited dissolution has been considered, which corresponds to the treatment with strong acids, such as HCl. Calcite coating in reactivated natural fractures dissolves in a highly non-homogeneous manner - a positive feedback between fluid transport and calcite dissolution leads to the spontaneous formation of wormhole-like patterns, in which most of the flow is focused. The wormholes carry reactive fluids deeper inside the system, which dramatically increases the range of the treatment. Non-uniformity of the dissolution patterns provides a way of retaining the fracture permeability even in the absence of the proppant, since the less dissolved regions will act as supports to keep more dissolved regions open. Evolution of fracture morphology is shown to depend strongly on the thickness of calcite layer - the thicker the coating the more pronounced wormholes are observed. However the interaction between
Neutron transmission through crystalline Fe
International Nuclear Information System (INIS)
Adib, M.; Habib, N.; Kilany, M.; El-Mesiry, M.S.
2004-01-01
The neutron transmission through crystalline Fe has been calculated for neutron energies in the range 10 4 < E<10 eV using an additive formula. The formula permits calculation of the nuclear capture, thermal diffuse and Bragg scattering cross-section as a function of temperature and crystalline form. The obtained agreement between the calculated values and available experimental ones justifies the applicability of the used formula. A feasibility study on using poly-crystalline Fe as a cold neutron filter and a large Fe single crystal as a thermal one is given
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
Perez, Nestor
2017-01-01
The second edition of this textbook includes a refined presentation of concepts in each chapter, additional examples; new problems and sections, such as conformal mapping and mechanical behavior of wood; while retaining all the features of the original book. The material included in this book is based upon the development of analytical and numerical procedures pertinent to particular fields of linear elastic fracture mechanics (LEFM) and plastic fracture mechanics (PFM), including mixed-mode-loading interaction. The mathematical approach undertaken herein is coupled with a brief review of several fracture theories available in cited references, along with many color images and figures. Dynamic fracture mechanics is included through the field of fatigue and Charpy impact testing. Explains computational and engineering approaches for solving crack-related problems using straightforward mathematics that facilitate comprehension of the physical meaning of crack growth processes; Expands computational understandin...
International Nuclear Information System (INIS)
Ueng, Tzoushin; Towse, D.
1991-01-01
Fractures are not only the weak planes of a rock mass, but also the easy passages for the fluid flow. Their spacing, orientation, and aperture will affect the deformability, strength, heat transmittal, and fluid transporting properties of the rock mass. To understand the thermomechanical and hydrological behaviors of the rock surrounding the heater emplacement borehole, the location, orientation, and aperture of the fractures of the rock mass should be known. Borehole television and borescope surveys were performed to map the location, orientation, and aperture of the fractures intersecting the boreholes drilled in the Prototype Engineered Barrier System Field Tests (PEBSFT) at G-Tunnel. Core logging was also performed during drilling. However, because the core was not oriented and the depth of the fracture cannot be accurately determined, the results of the core logging were only used as reference and will not be discussed here
Ricketts, Sophie; Gill, Hameet S; Fialkov, Jeffery A; Matic, Damir B; Antonyshyn, Oleh M
2016-02-01
After reading this article, the participant should be able to: 1. Demonstrate an understanding of some of the changes in aspects of facial fracture management. 2. Assess a patient presenting with facial fractures. 3. Understand indications and timing of surgery. 4. Recognize exposures of the craniomaxillofacial skeleton. 5. Identify methods for repair of typical facial fracture patterns. 6. Discuss the common complications seen with facial fractures. Restoration of the facial skeleton and associated soft tissues after trauma involves accurate clinical and radiologic assessment to effectively plan a management approach for these injuries. When surgical intervention is necessary, timing, exposure, sequencing, and execution of repair are all integral to achieving the best long-term outcomes for these patients.
Representation of fracture networks as grid cell conductivities
International Nuclear Information System (INIS)
Svensson, Urban
1999-12-01
A method to represent fracture networks as grid cell conductivities is described and evaluated. The method is developed for a fracture system of the kind found in the Aespoe area, i.e. a sparsely fractured rock with a conductivity field that is dominated by a set of major fracture zones. For such a fracture system it is believed that an accurate description of the correlation and anisotropy structure is essential. The proposed method will capture these features of the fracture system. The method will be described in two reports. The first one, this report, evaluates the accuracy by comparisons with analytical solutions and established theories. The second report is an application to the Aespoe Hard Rock Laboratory. The general conclusion from this report is that the method is accurate enough for practical groundwater simulations. This statement is based on the results from three test cases with analytical solution and two test cases where results are compared with those from established theories
International Nuclear Information System (INIS)
Fleege, M.A.; Jebson, P.J.; Renfrew, D.L.; El-Khoury, G.Y.; Steyers, C.M. Jr.
1991-01-01
Fractures of the pisiform are often missed due to improper radiographic evaluation and a tendency to focus on other, more obvious injuries. Delayed diagnosis may result in disabling sequelae. A high index of clinical suspicion and appropriate radiographic examination will establish the correct diagnosis. Ten patients with pisiform fracture are presented. The anatomy, mechanism of injury, clinical presentation, radiographic features, and evaluation of this injury are discussed. (orig.)
International Nuclear Information System (INIS)
Berquist, T.H.; Cooper, K.L.; Pritchard, D.J.
1985-01-01
The diagnosis of a stress fracture should be considered in patients presented with pain after a change in activity, especially if the activity is strenuous and the pain is in the lower extremities. Since evidence of the stress fracture may not be apparent for weeks on routine radiographs, proper use of other imaging techniques will allow an earlier diagnosis. Prompt diagnosis is especially important in the femur, where displacement may occur
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...
Directory of Open Access Journals (Sweden)
Esther Kim, BS
2018-04-01
Full Text Available History of present illness: A 25-year-old, right-handed male presented to the emergency department with left wrist pain after falling from a skateboard onto an outstretched hand two-weeks prior. He otherwise had no additional concerns, including no complaints of weakness or loss of sensation. On physical exam, there was tenderness to palpation within the anatomical snuff box. The neurovascular exam was intact. Plain films of the left wrist and hand were obtained. Significant findings: The anteroposterior (AP plain film of this patient demonstrates a full thickness fracture through the middle third of the scaphoid (red arrow, with some apparent displacement (yellow lines and subtle angulation of the fracture fragments (blue line. Discussion: The scaphoid bone is the most commonly fractured carpal bone accounting for 70%-80% of carpal fractures.1 Classically, it is sustained following a fall onto an outstretched hand (FOOSH. Patients should be evaluated for tenderness with palpation over the anatomical snuffbox, which has a sensitivity of 100% and specificity of 40%.2 Plain films are the initial diagnostic modality of choice and have a sensitivity of 70%, but are commonly falsely negative in the first two to six weeks of injury (false negative of 20%.3 The Mayo classification organizes scaphoid fractures as involving the proximal, mid, and distal portions of the scaphoid bone with mid-fractures being the most common.3 The proximal scaphoid is highly susceptible to vascular compromise because it depends on retrograde blood flow from the radial artery. Therefore, disruption can lead to serious sequelae including osteonecrosis, arthrosis, and functional impairment. Thus, a low threshold should be maintained for neurovascular evaluation and surgical referral. Patients with non-displaced scaphoid fractures should be placed in a thumb spica splint.3 Patients with even suspected scaphoid fractures should be placed in a thumb spica splint and re
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.
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
Underground Research Laboratories for Crystalline Rock and Sedimentary Rock in Japan
Energy Technology Data Exchange (ETDEWEB)
Shigeta, N.; Takeda, S.; Matsui, H.; Yamasaki, S.
2003-02-27
The Japan Nuclear Cycle Development Institute (JNC) has started two off-site (generic) underground research laboratory (URL) projects, one for crystalline rock as a fractured media and the other for sedimentary rock as a porous media. This paper introduces an overview and current status of these projects.
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.
The fracture zone project - final report
International Nuclear Information System (INIS)
Andersson, Peter
1993-09-01
This report summarizes the work and the experiences gained during the fracture zone project at the Finnsjoen study site. The project is probably the biggest effort, so far, to characterize a major fracture zone in crystalline bedrock. The project was running between 1984-1990 involving a large number of geological, geohydrological, geochemical, and geomechanical investigation. The methods used for identification and characterization are reviewed and discussed in terms of applicability and possible improvements for future investigations. The discussion is exemplified with results from the investigation within the project. Flow and transport properties of the zone determined from hydraulic tests and tracer tests are discussed. A large number of numerical modelling efforts performed within the fracture zone project, the INTRAVAL project, and the SKB91-study are summarized and reviewed. Finally, occurrence of similar zones and the relevance of major low angle fracture zones in connection to the siting of an underground repository is addressed
A review of numerical techniques approaching microstructures of crystalline rocks
Zhang, Yahui; Wong, Louis Ngai Yuen
2018-06-01
The macro-mechanical behavior of crystalline rocks including strength, deformability and failure pattern are dominantly influenced by their grain-scale structures. Numerical technique is commonly used to assist understanding the complicated mechanisms from a microscopic perspective. Each numerical method has its respective strengths and limitations. This review paper elucidates how numerical techniques take geometrical aspects of the grain into consideration. Four categories of numerical methods are examined: particle-based methods, block-based methods, grain-based methods, and node-based methods. Focusing on the grain-scale characters, specific relevant issues including increasing complexity of micro-structure, deformation and breakage of model elements, fracturing and fragmentation process are described in more detail. Therefore, the intrinsic capabilities and limitations of different numerical approaches in terms of accounting for the micro-mechanics of crystalline rocks and their phenomenal mechanical behavior are explicitly presented.
The make up of crystalline bedrock - crystalline body and blocks
International Nuclear Information System (INIS)
Huber, M.; Huber, A.
1986-01-01
Statements of a geological nature can be made on the basis of investigations of the bedrock exposed in southern Black Forest and these can, in the form of prognoses, be applied to the crystalline Basement of northern Switzerland. Such statements relate to the average proportions of the main lithological groups at the bedrock surface and the surface area of the granite body. Some of the prognoses can be compared and checked with the results from the deep drilling programme in northern Switzerland. Further, analogical interferences from the situation in the southern Black Forest allow predictions to be made on the anticipated block structure of the crystalline Basement. (author)
International Nuclear Information System (INIS)
Herrlin, K.; Stroemberg, T.; Lidgren, L.; Walloee, A.; Pettersson, H.; Lund Univ.
1988-01-01
Four hundred and thirty trochanteric factures operated upon with McLaughlin, Ender or Richard's osteosynthesis were divided into 6 different types based on their radiographic appearance before and immediately after reposition with special reference to the medial cortical support. A significant correlation was found between the fracture type and subsequent mechanical complications where types 1 and 2 gave less, and types 4 and 5 more complications. A comparison of the various osteosyntheses showed that Richard's had significantly fewer complications than either the Ender or McLaughlin types. For Richard's osteosynthesis alone no correlation to fracture type could be made because of the small number of complications in this group. (orig.)
Directory of Open Access Journals (Sweden)
Uebbing, Claire M
2011-02-01
Full Text Available Fracture blisters are a relatively uncommon complication of fractures in locations of the body, such as the ankle, wrist elbow and foot, where skin adheres tightly to bone with little subcutaneous fat cushioning. The blister that results resembles that of a second degree burn.These blisters significantly alter treatment, making it difficult to splint or cast and often overlying ideal surgical incision sites. Review of the literature reveals no consensus on management; however, most authors agree on early treatment prior to blister formation or delay until blister resolution before attempting surgical correction or stabilization. [West J Emerg Med. 2011;12(1;131-133.
neutron transmission through crystalline materials
International Nuclear Information System (INIS)
El Mesiry, M.S.
2011-01-01
The aim of the present work is to study the neutron transmission through crystalline materials. Therefore a study of pyrolytic graphite (PG) as a highly efficient selective thermal neutron filter and Iron single crystal as a whole one, as well as the applicability of using their polycrystalline powders as a selective cold neutron filters is given. Moreover, the use of PG and iron single crystal as an efficient neutron monochromator is also investigated. An additive formula is given which allows calculating the contribution of the total neutron cross-section including the Bragg scattering from different )(hkl planes to the neutron transmission through crystalline iron and graphite. The formula takes into account their crystalline form. A computer CFe program was developed in order to provide the required calculations for both poly- and single-crystalline iron. The validity of the CFe program was approved from the comparison of the calculated iron cross-section data with the available experimental ones. The CFe program was also adapted to calculate the reflectivity from iron single crystal when it used as a neutron monochromator The computer package GRAPHITE, developed in Neutron Physics laboratory, Nuclear Research Center, has been used in order to provide the required calculations for crystalline graphite in the neutron energy range from 0.1 meV to 10 eV. A Mono-PG code was added to the computer package GRAPHITE in order to calculate the reflectivity from PG crystal when it used as a neutron monochromator.
Diverse topics in crystalline beams
International Nuclear Information System (INIS)
Wei, Jie; Draeseke, A.; Sessler, A.M.; Li, Xiao-Ping
1995-01-01
Equations of motion are presented, appropriate to interacting charged particles of diverse charge and mass, subject to the external forces produced by various kinds of magnetic fields and radio-frequency (rf) electric fields in storage rings. These equations are employed in the molecular dynamics simulations to study the properties of crystalline beams. The two necessary conditions for the formation and maintenance of crystalline beams are summarized. The transition from ID to 2D, and from 2D to 3D is explored, and the scaling behavior of the heating rates is discussed especially in the high temperature limit. The effectiveness of various cooling techniques in achieving crystalline states has been investigated. Crystalline beams made of two different species of ions via sympathetic cooling are presented, as well as circulating ''crystal balls'' bunched in all directions by magnetic focusing and rf field. By numerically reconstructing the original experimental conditions of the NAP-M ring, it is found that only at extremely low beam intensities, outside of the range of the original measurement, proton particles can form occasionally-passing disks. The proposed New ASTRID ring is shown to be suitable for the formation and maintenance of crystalline beams of all dimensions
Directory of Open Access Journals (Sweden)
Malin Bomberg
2015-01-01
Full Text Available Active microbial communities of deep crystalline bedrock fracture water were investigated from seven different boreholes in Olkiluoto (Western Finland using bacterial and archaeal 16S rRNA, dsrB, and mcrA gene transcript targeted 454 pyrosequencing. Over a depth range of 296–798 m below ground surface the microbial communities changed according to depth, salinity gradient, and sulphate and methane concentrations. The highest bacterial diversity was observed in the sulphate-methane mixing zone (SMMZ at 250–350 m depth, whereas archaeal diversity was highest in the lowest boundaries of the SMMZ. Sulphide-oxidizing ε-proteobacteria (Sulfurimonas sp. dominated in the SMMZ and γ-proteobacteria (Pseudomonas spp. below the SMMZ. The active archaeal communities consisted mostly of ANME-2D and Thermoplasmatales groups, although Methermicoccaceae, Methanobacteriaceae, and Thermoplasmatales (SAGMEG, TMG were more common at 415–559 m depth. Typical indicator microorganisms for sulphate-methane transition zones in marine sediments, such as ANME-1 archaea, α-, β- and δ-proteobacteria, JS1, Actinomycetes, Planctomycetes, Chloroflexi, and MBGB Crenarchaeota were detected at specific depths. DsrB genes were most numerous and most actively transcribed in the SMMZ while the mcrA gene concentration was highest in the deep methane rich groundwater. Our results demonstrate that active and highly diverse but sparse and stratified microbial communities inhabit the Fennoscandian deep bedrock ecosystems.
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.
... is also an important factor when treating elbow fractures. Casts are used more frequently in children, as their risk of developing elbow stiffness is small; however, in an adult, elbow stiffness is much more likely. Rehabilitation directed by your doctor is often used to ...
... All Topics A-Z Videos Infographics Symptom Picker Anatomy Bones Joints Muscles Nerves Vessels Tendons About Hand Surgery What is a Hand Surgeon? What is a Hand Therapist? Media Find a Hand Surgeon Home Anatomy Wrist Fractures Email to a friend * required fields ...
... All Topics A-Z Videos Infographics Symptom Picker Anatomy Bones Joints Muscles Nerves Vessels Tendons About Hand Surgery What is a Hand Surgeon? What is a Hand Therapist? Media Find a Hand Surgeon Home Anatomy Shoulder Fractures Email to a friend * required fields ...
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.
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...
Glycation precedes lens crystallin aggregation
International Nuclear Information System (INIS)
Swamy, M.S.; Perry, R.E.; Abraham, E.C.
1987-01-01
Non-enzymatic glycosylation (glycation) seems to have the potential to alter the structure of crystallins and make them susceptible to thiol oxidation leading to disulfide-linked high molecular weight (HMW) aggregate formation. They used streptozotocin diabetic rats during precataract and cataract stages and long-term cell-free glycation of bovine lens crystallins to study the relationship between glycation and lens crystallin aggregation. HMW aggregates and other protein components of the water-soluble (WS) and urea-soluble (US) fractions were separated by molecular sieve high performance liquid chromatography. Glycation was estimated by both [ 3 H]NaBH 4 reduction and phenylboronate agarose affinity chromatography. Levels of total glycated protein (GP) in the US fractions were about 2-fold higher than in the WS fractions and there was a linear increase in GP in both WS and US fractions. This increase was parallelled by a corresponding increase in HMW aggregates. Total GP extracted by the affinity method from the US fraction showed a predominance of HMW aggregates and vice versa. Cell-free glycation studies with bovine crystallins confirmed the results of the animals studies. Increasing glycation caused a corresponding increase in protein insolubilization and the insoluble fraction thus formed also contained more glycated protein. It appears that lens protein glycation, HMW aggregate formation, and protein insolubilization are interrelated
Bimalleolar ankle fracture with proximal fibular fracture
Colenbrander, R. J.; Struijs, P. A. A.; Ultee, J. M.
2005-01-01
A 56-year-old female patient suffered a bimalleolar ankle fracture with an additional proximal fibular fracture. This is an unusual fracture type, seldom reported in literature. It was operatively treated by open reduction and internal fixation of the lateral malleolar fracture. The proximal fibular
Steady-state flow in a rock mass intersected by permeable fracture zones
International Nuclear Information System (INIS)
Lindbom, B.
1986-12-01
Level 1 of HYDROCOIN consists of seven well-defined test problems. This paper is concerned with Case 2, which is formulated as a generic groundwater flow situation often found in crystalline rock with highly permeable fracture zones in a less permeable rock mass. The case is two-dimensional and modelled with 8-noded, isoparametric, rectangular elements. According to the case definition, calculations of hydraulic head and particle tracking are performed. The computations are carried out with varying degree of discretisation in order to analyse possible impact on the result with respect to nodal density. Further calculations have been performed mainly devoted to mass balance deviations and how these are affected by permeability contrasts, varying degree of spatial discretisation and distortion of finite elements. The distribution of hydraulic head in the domain is less sensitive to differences in nodal density than the trajectories. The hydraulic heads show similar behaviour for three meshes with varying degrees of discretisation. The particle tracking seems to be more sensitive to the level of discretisation. The results obtained with a coarse and medium mesh indicate completely different solutions for one of the pathlines. The coarse mesh is too sparsely discretised for the specified problem. The local mass balance is evaluated for seven runs. The mass balance deviation seems to be considerably more sensitive to the level of discretisation than to both permeability contrasts and deformation of elements. The permeability contrasts between the rock mass and fracture zones vary from a factor of 1000 to 1 (homogeneous properties) with increments of a factor of 10. These calculations in fact give better mass balance with increasing permeability contrasts, contrary to what could be expected. (orig./HP)
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
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...
International Nuclear Information System (INIS)
Miannay, D.P.
1995-01-01
This book entitle ''Fracture Mechanics'', the first one of the monograph ''Materiologie'' is geared to design engineers, material engineers, non destructive inspectors and safety experts. This book covers fracture mechanics in isotropic homogeneous continuum. Only the monotonic static loading is considered. This book intended to be a reference with the current state of the art gives the fundamental of the issues under concern and avoids the developments too complicated or not yet mastered for not making reading cumbersome. The subject matter is organized as going from an easy to a more complicated level and thus follows the chronological evolution in the field. Similarly the microscopic scale is considered before the macroscopic scale, the physical understanding of phenomena linked to the experimental observation of the material preceded the understanding of the macroscopic behaviour of structures. In this latter field the relatively recent contribution of finite element computations with some analogy with the experimental observation is determining. However more sensitive analysis is not skipped
Experimental study upon the effect of irradiation on callus formation of fracture
International Nuclear Information System (INIS)
Saigusa, Fujio
1981-01-01
Irradiation effects on callus formation after bone fracture were studied in rats with fractured right lower extremity. Follow-up study was continued for 112 days since 3000 rad was irradiated to the fractured site 3 days after bone fracture. Callus formation was noted in both of the outer and inner part (bone marrow) of the diaphysis before 14 days after bone fracture, but it was slow and sparse compared with that of non-irradiated group. Callus formation tended to disappear gradually from the outside of the diaphysis after 28 days after bone fracture. Strong disturbance was found in the surrounding vascular system at this time. Inside of the diaphysis, callus formation was restricted the end of the fracture, where lamellar calluses fused together. Changes in vascular system remained until 56 days after bone fracture. Vascular distribution was most dense 28 days after bone fracture. In many of the calluses which have established fusion, findings suggested excessive calcification in the trabeculae. Vascular distribution at this time was sparse, vascular formation was markedly suppressed in the bone marrow, and very little vascular formation was found in the fractured edges of the bone. (Ueda, J.)
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.
Energy Technology Data Exchange (ETDEWEB)
Eichinger, F. [Hydroisotop GmbH, Schweitenkirchen (Germany); Waber, H. N. [Rock-Water Interaction, Institute of Geological Sciences, University of Bern, Bern (Switzerland); Smellie, J. A.T. [Conterra AB, Stockholm (Sweden)
2013-07-15
Matrix pore water in the connected inter- and intragranular pore space of low permeable crystalline bedrock interacts with flowing fracture groundwater predominately by diffusion. Based on the slow exchange between the two water reservoirs, matrix pore water acts as an archive of past changes in fracture groundwater compositions and thus of the palaeohydrological history of a site. Matrix pore water of crystalline bedrock from the olkiluoto investigation site (SW Finland) was characterised using the stable water isotopes ({delta}{sup 18}O, {delta}{sup 2}H), combined with the concentrations of dissolved chloride and bromide as natural tracers. The comparison of tracer concentrations in pore water and present day fracture groundwater suggest for the pore water the presence of old, dilute meteoric water components that infiltrated into the fractures during various warm climate stages. These different meteoric components can be discerned based on the diffusion distance between the two reservoirs and brought into context with the palaeohydrological evolution of the site. (author)
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.
Grindrod, P.; Peletier, M.A.; Takase, H.
1999-01-01
We consider the interaction between a saturated clay buffer layer and a fractured crystalline rock engineered disturbed zone. Once saturated, the clay extrudes into the available rock fractures, behaving as a compressible non-Newtonian fluid. We discuss the modelling implications of published
Groundwater management in coastal zones and on islands in crystalline bedrock areas of Sweden
Banzhaf, Stefan; Ekström, Linda Louise; Ljungkvist, Andreas; Granberg, Maria; Merisalu, Johanna; Pokorny, Sebastian; Barthel, Roland
2017-04-01
Groundwater problems in coastal regions are usually not associated with the sparsely populated shores of water-rich Scandinavia. However, the combination of geology and the specific conditions of water usage create challenges even there. Along the Swedish coast, much of the groundwater occurs in fractured bedrock or in relatively small, shallow, and isolated quaternary sedimentary formations. Those aquifers cannot provide water to larger permanent settlements and are thus neither useful for the public water supply nor have previously received much attention from water authorities or researchers. However, of the 450,000 private wells in Sweden, many are located in coastal areas or on islands, creating pressure on groundwater resources in summer months as periods with low or no natural groundwater recharge. In view of the increasing water demand, as well as the awareness of environmental impacts and climate change, Swedish municipalities now recognize groundwater usage in coastal areas is a major concern. Here, we present the results of an investigation on the "Koster" archipelago which forms a microcosm of coastal zone groundwater problems in Sweden. Koster's geology is dominated by fractured, crystalline bedrock with occasional shallow quaternary deposits in between. With around 300 permanent residents, and up to 6,000 summer guests in peak holiday season, the existing water supply based on 800 private wells is at its limit. Water availability forms an obstacle to future development and the current mode of operation is unsustainable. Therefore, the municipality must decide how to secure future water supply which involves complex legal problems, as well as social, cultural, economic, hydrogeological, and environmental questions. As there are no observation wells on the islands, we used approximately 220 of the 800 wells (65% dug and shallow, 35% drilled and up to 120m deep) for our monitoring. Additionally, water samples were collected by property owners on four
Ferrofluids in liquid crystalline systems
International Nuclear Information System (INIS)
Figueiredo Neto, A.M.; Liebert, L.
1989-08-01
It is a well-known fact that intermediate or mesomorphic phase may exist between the crystalline and the isotropic liquid phases. The symmetry properties of these mesophases are intermediate between those of a crystal and a liquid. In this paper, some aspects of the use of ferrofluids in thermotropic and lyotropic systems are studied both the experimental difficulties as well as the fundamental phypical phenomena involved. (A.C.A.S.) [pt
EELS from organic crystalline materials
International Nuclear Information System (INIS)
Brydson, R; Seabourne, C R; Hondow, N; Eddleston, M D; Jones, W
2014-01-01
We report the use of the electron energy loss spectroscopy (EELS) for providing light element chemical composition information from organic, crystalline pharmaceutical materials including theophylline and paracetamol and discuss how this type of data can complement transmission electron microscopy (TEM) imaging and electron diffraction when investigating polymorphism. We also discuss the potential for the extraction of bonding information using electron loss near-edge structure (ELNES)
Soliton structure in crystalline acetanilide
International Nuclear Information System (INIS)
Eilbeck, J.C.; Lomdahl, P.S.; Scott, A.C.
1984-01-01
The theory of self-trapping of amide I vibrational energy in crystalline acetanilide is studied in detail. A spectrum of stationary, self-trapped (soliton) solutions is determined and tested for dynamic stability. Only those solutions for which the amide I energy is concentrated near a single molecule were found to be stable. Exciton modes were found to be unstable to decay into solitons
Graphene on insulating crystalline substrates
International Nuclear Information System (INIS)
Akcoeltekin, S; El Kharrazi, M; Koehler, B; Lorke, A; Schleberger, M
2009-01-01
We show that it is possible to prepare and identify ultra-thin sheets of graphene on crystalline substrates such as SrTiO 3 , TiO 2 , Al 2 O 3 and CaF 2 by standard techniques (mechanical exfoliation, optical and atomic force microscopy). On the substrates under consideration we find a similar distribution of single layer, bilayer and few-layer graphene and graphite flakes as with conventional SiO 2 substrates. The optical contrast C of a single graphene layer on any of those substrates is determined by calculating the optical properties of a two-dimensional metallic sheet on the surface of a dielectric, which yields values between C = -1.5% (G/TiO 2 ) and C = -8.8% (G/CaF 2 ). This contrast is in reasonable agreement with experimental data and is sufficient to make identification by an optical microscope possible. The graphene layers cover the crystalline substrate in a carpet-like mode and the height of single layer graphene on any of the crystalline substrates as determined by atomic force microscopy is d SLG = 0.34 nm and thus much smaller than on SiO 2 .
Biocompatibility of crystalline opal nanoparticles.
Hernández-Ortiz, Marlen; Acosta-Torres, Laura S; Hernández-Padrón, Genoveva; Mendieta, Alicia I; Bernal, Rodolfo; Cruz-Vázquez, Catalina; Castaño, Victor M
2012-10-22
Silica nanoparticles are being developed as a host of biomedical and biotechnological applications. For this reason, there are more studies about biocompatibility of silica with amorphous and crystalline structure. Except hydrated silica (opal), despite is presents directly and indirectly in humans. Two sizes of crystalline opal nanoparticles were investigated in this work under criteria of toxicology. In particular, cytotoxic and genotoxic effects caused by opal nanoparticles (80 and 120 nm) were evaluated in cultured mouse cells via a set of bioassays, methylthiazolyldiphenyl-tetrazolium-bromide (MTT) and 5-bromo-2'-deoxyuridine (BrdU). 3T3-NIH cells were incubated for 24 and 72 h in contact with nanocrystalline opal particles, not presented significant statistically difference in the results of cytotoxicity. Genotoxicity tests of crystalline opal nanoparticles were performed by the BrdU assay on the same cultured cells for 24 h incubation. The reduction of BrdU-incorporated cells indicates that nanocrystalline opal exposure did not caused unrepairable damage DNA. There is no relationship between that particles size and MTT reduction, as well as BrdU incorporation, such that the opal particles did not induce cytotoxic effect and genotoxicity in cultured mouse cells.
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.
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.
... neck fracture repair - discharge; Trochanteric fracture repair - discharge; Hip pinning surgery - discharge ... in the hospital for surgery to repair a hip fracture, a break in the upper part of ...
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
Schilcher, Jörg
2015-12-01
Healing of complete, atypical femoral fractures is thought to be impaired, but the evidence is weak and appears to be based on the delayed healing observed in patients with incomplete atypical fractures. Time until fracture healing is difficult to assess, therefore we compared the reoperation rates between women with complete atypical femoral fractures and common femoral shaft fractures. We searched the orthopaedic surgical registry in Östergötland County for patients with subtrochanteric and femoral shaft fractures (ICD-10 diagnosis codes S72.2, S72.3 and M84.3F) between January 1st 2007 and December 31st 2013. Out of 895 patients with surgically treated femoral shaft fractures, 511 were women 50 years of age or older. Among these we identified 24 women with atypical femoral shaft fractures, and 71 with common shaft fractures. Reoperations were performed in 6 and 5 patients, respectively, odds ratio 4.4 (95% CI 1.2 to 16.1). However, 5 reoperations in the atypical fracture group could not be ascribed to poor healing. In 3 patients the reoperation was due to a new fracture proximal to a standard intramedullary nail. In 2 patients the distal locking screws were removed due to callus formation that was deemed incomplete 5 months post-operatively. The one patient with poor healing showed faint callus formation at 5 months when the fracture was dynamised and callus remained sparse at 11 months. Among patients with common shaft fractures, 2 reoperations were performed to remove loose screws, 2 because of peri-implant fractures and 1 reoperation due to infection. Reoperation rates in patients with complete atypical femoral fractures are higher than in patients with common shaft fractures. The main reason for failure was peri-implant fragility fractures which might be prevented with the use of cephalomedullary nails at the index surgery. Fracture healing however, seems generally good. A watchful waiting approach is advocated in patients with fractures that appear to
Webb, Lawrence X
2002-01-01
Fractures of the proximal femur include fractures of the head, neck, intertrochanteric, and subtrochanteric regions. Head fractures commonly accompany dislocations. Neck fractures and intertrochanteric fractures occur with greatest frequency in elderly patients with a low bone mineral density and are produced by low-energy mechanisms. Subtrochanteric fractures occur in a predominantly strong cortical osseous region which is exposed to large compressive stresses. Implants used to address these fractures must be able to accommodate significant loads while the fractures consolidate. Complications secondary to these injuries produce significant morbidity and include infection, nonunion, malunion, decubitus ulcers, fat emboli, deep venous thrombosis, pulmonary embolus, pneumonia, myocardial infarction, stroke, and death.
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
Approach to the fracture hydrology at Stripa: preliminary results
International Nuclear Information System (INIS)
Gale, J.E.; Witherspoon, P.A.
1979-05-01
There are two main problems associated with the concept of geologic storage of radioactive waste in fractured crystalline rock: (1) the thermo-mechanical effects of the heat generated by the waste, and (2) the potential for transport of radioactive materials by the groundwater system. In both problems, fractures play a dominant role. An assessment of the hydraulic and mechanical characteristics of fractued rock requires a careful series of laboratory and field investigations. The complexity of the problem is illustrated by the field studies in a fractured granite that are currently underway in an abandoned iron-ore mine at Stripa, Sweden. Much information is being gathered from an extensive series of boreholes and fracture maps. The approach being taken to integrate these data into an analysis of the fracture hydrology is reviewed and preliminary results from the hydrology program are presented. 13 figures
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.
Saline groundwater in crystalline bedrock
International Nuclear Information System (INIS)
Lampen, P.
1992-11-01
The State-of-art report describes research made on deep saline groundwaters and brines found in crystalline bedrock, mainly in site studies for nuclear waste disposal. The occurrence, definitions and classifications of saline groundwaters are reviewed with a special emphasis on the different theories concerning the origins of saline groundwaters. Studies of the saline groundwaters in Finland and Sweden have been reviewed more thoroughly. Also the mixing of different bodies of groundwaters, observations of the contact of saline groundwaters and permafrost, and the geochemical modelling of saline groundwaters as well as the future trends of research have been discussed. (orig.)
Crystalline beams: The vertical zigzag
International Nuclear Information System (INIS)
Haffmans, A.F.; Maletic, D.; Ruggiero, A.G.
1994-01-01
This note is the continuation of our comprehensive investigation of Crystalline Beams. After having determined the equations of motion and the conditions for the formation of the simplest configuration, i.e. the string, we study the possibility of storing an intense beam of charged particles in a storage ring where they form a vertical zigzag. We define the equilibrium configuration, and examine the confinement conditions. Subsequently, we derive the transfer matrix for motion through various elements of the storage ring. Finally we investigate the stability conditions for such a beam
Crystalline cerium(IV) phosphates
International Nuclear Information System (INIS)
Herman, R.G.; Clearfield, A.
1976-01-01
The ion exchange behaviour of seven crystalline cerium(IV) phosphates towards some of the alkali metal cations is described. Only two of the compounds (A and C) possess ion exchange properties in acidic solutions. Four others show some ion exchange characteristics in basic media with some of the alkali cations. Compound G does not behave as an ion exchanger in solutions of pH + , but show very little Na + uptake. Compound E undergoes ion exchange with Na + and Cs + , but not with Li+. Both Li + and Na + are sorbed by compounds A and C. The results are indicative of structures which show steric exclusion phenomena. (author)
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...
Effect of silicon solar cell processing parameters and crystallinity on mechanical strength
Energy Technology Data Exchange (ETDEWEB)
Popovich, V.A.; Yunus, A.; Janssen, M.; Richardson, I.M. [Delft University of Technology, Department of Materials Science and Engineering, Delft (Netherlands); Bennett, I.J. [Energy Research Centre of the Netherlands, Solar Energy, PV Module Technology, Petten (Netherlands)
2011-01-15
Silicon wafer thickness reduction without increasing the wafer strength leads to a high breakage rate during subsequent handling and processing steps. Cracking of solar cells has become one of the major sources of solar module failure and rejection. Hence, it is important to evaluate the mechanical strength of solar cells and influencing factors. The purpose of this work is to understand the fracture behavior of silicon solar cells and to provide information regarding the bending strength of the cells. Triple junctions, grain size and grain boundaries are considered to investigate the effect of crystallinity features on silicon wafer strength. Significant changes in fracture strength are found as a result of metallization morphology and crystallinity of silicon solar cells. It is observed that aluminum paste type influences the strength of the solar cells. (author)
Lateral topological crystalline insulator heterostructure
Sun, Qilong; Dai, Ying; Niu, Chengwang; Ma, Yandong; Wei, Wei; Yu, Lin; Huang, Baibiao
2017-06-01
The emergence of lateral heterostructures fabricated by two-dimensional building blocks brings many exciting realms in material science and device physics. Enriching available nanomaterials for creating such heterostructures and enabling the underlying new physics is highly coveted for the integration of next-generation devices. Here, we report a breakthrough in lateral heterostructure based on the monolayer square transition-metal dichalcogenides MX2 (M = W, X = S/Se) modules. Our results reveal that the MX2 lateral heterostructure (1S-MX2 LHS) can possess excellent thermal and dynamical stability. Remarkably, the highly desired two-dimensional topological crystalline insulator phase is confirmed by the calculated mirror Chern number {{n}\\text{M}}=-1 . A nontrivial band gap of 65 meV is obtained with SOC, indicating the potential for room-temperature observation and applications. The topologically protected edge states emerge at the edges of two different nanoribbons between the bulk band gap, which is consistent with the mirror Chern number. In addition, a strain-induced topological phase transition in 1S-MX2 LHS is also revealed, endowing the potential utilities in electronics and spintronics. Our predictions not only introduce new member and vitality into the studies of lateral heterostructures, but also highlight the promise of lateral heterostructure as appealing topological crystalline insulator platforms with excellent stability for future devices.
Traumatic thoracolumbar spine fractures
J. Siebenga (Jan)
2013-01-01
textabstractTraumatic spinal fractures have the lowest functional outcomes and the lowest rates of return to work after injury of all major organ systems.1 This thesis will cover traumatic thoracolumbar spine fractures and not osteoporotic spine fractures because of the difference in fracture
Fractures in multiple sclerosis
DEFF Research Database (Denmark)
Stenager, E; Jensen, K
1991-01-01
In a cross-sectional study of 299 MS patients 22 have had fractures and of these 17 after onset of MS. The fractures most frequently involved the femoral neck and trochanter (41%). Three patients had had more than one fracture. Only 1 patient had osteoporosis. The percentage of fractures increase...
Energy Technology Data Exchange (ETDEWEB)
Mei, Kai; Kopp, Felix K.; Schwaiger, Benedikt J.; Gersing, Alexandra S.; Sauter, Andreas; Muenzel, Daniela; Rummeny, Ernst J. [Klinikum rechts der Isar, Technische Universitaet Muenchen, Department of Diagnostic and Interventional Radiology, Munich (Germany); Bippus, Rolf [Research Laboratories, Philips GmbH Innovative Technologies, Hamburg (Germany); Koehler, Thomas [Research Laboratories, Philips GmbH Innovative Technologies, Hamburg (Germany); Technische Universitaet Muenchen, TUM Institute for Advanced Studies, Garching (Germany); Fehringer, Andreas [Technische Universitaet Muenchen, Lehrstuhl fuer Biomedizinische Physik, Garching (Germany); Pfeiffer, Franz [Klinikum rechts der Isar, Technische Universitaet Muenchen, Department of Diagnostic and Interventional Radiology, Munich (Germany); Technische Universitaet Muenchen, TUM Institute for Advanced Studies, Garching (Germany); Technische Universitaet Muenchen, Lehrstuhl fuer Biomedizinische Physik, Garching (Germany); Kirschke, Jan S. [Klinikum rechts der Isar, Technische Universitaet Muenchen, Section of Diagnostic and Interventional Neuroradiology, Munich (Germany); Noel, Peter B. [Klinikum rechts der Isar, Technische Universitaet Muenchen, Department of Diagnostic and Interventional Radiology, Munich (Germany); Technische Universitaet Muenchen, Lehrstuhl fuer Biomedizinische Physik, Garching (Germany); Baum, Thomas [Klinikum rechts der Isar, Technische Universitaet Muenchen, Department of Diagnostic and Interventional Radiology, Munich (Germany); Klinikum rechts der Isar, Technische Universitaet Muenchen, Section of Diagnostic and Interventional Neuroradiology, Munich (Germany)
2017-12-15
Osteoporosis diagnosis using multidetector CT (MDCT) is limited to relatively high radiation exposure. We investigated the effect of simulated ultra-low-dose protocols on in-vivo bone mineral density (BMD) and quantitative trabecular bone assessment. Institutional review board approval was obtained. Twelve subjects with osteoporotic vertebral fractures and 12 age- and gender-matched controls undergoing routine thoracic and abdominal MDCT were included (average effective dose: 10 mSv). Ultra-low radiation examinations were achieved by simulating lower tube currents and sparse samplings at 50%, 25% and 10% of the original dose. BMD and trabecular bone parameters were extracted in T10-L5. Except for BMD measurements in sparse sampling data, absolute values of all parameters derived from ultra-low-dose data were significantly different from those derived from original dose images (p<0.05). BMD, apparent bone fraction and trabecular thickness were still consistently lower in subjects with than in those without fractures (p<0.05). In ultra-low-dose scans, BMD and microstructure parameters were able to differentiate subjects with and without vertebral fractures, suggesting osteoporosis diagnosis is feasible. However, absolute values differed from original values. BMD from sparse sampling appeared to be more robust. This dose-dependency of parameters should be considered for future clinical use. (orig.)
International Nuclear Information System (INIS)
Mei, Kai; Kopp, Felix K.; Schwaiger, Benedikt J.; Gersing, Alexandra S.; Sauter, Andreas; Muenzel, Daniela; Rummeny, Ernst J.; Bippus, Rolf; Koehler, Thomas; Fehringer, Andreas; Pfeiffer, Franz; Kirschke, Jan S.; Noel, Peter B.; Baum, Thomas
2017-01-01
Osteoporosis diagnosis using multidetector CT (MDCT) is limited to relatively high radiation exposure. We investigated the effect of simulated ultra-low-dose protocols on in-vivo bone mineral density (BMD) and quantitative trabecular bone assessment. Institutional review board approval was obtained. Twelve subjects with osteoporotic vertebral fractures and 12 age- and gender-matched controls undergoing routine thoracic and abdominal MDCT were included (average effective dose: 10 mSv). Ultra-low radiation examinations were achieved by simulating lower tube currents and sparse samplings at 50%, 25% and 10% of the original dose. BMD and trabecular bone parameters were extracted in T10-L5. Except for BMD measurements in sparse sampling data, absolute values of all parameters derived from ultra-low-dose data were significantly different from those derived from original dose images (p<0.05). BMD, apparent bone fraction and trabecular thickness were still consistently lower in subjects with than in those without fractures (p<0.05). In ultra-low-dose scans, BMD and microstructure parameters were able to differentiate subjects with and without vertebral fractures, suggesting osteoporosis diagnosis is feasible. However, absolute values differed from original values. BMD from sparse sampling appeared to be more robust. This dose-dependency of parameters should be considered for future clinical use. (orig.)
International Nuclear Information System (INIS)
Kanis, John A.; Johansson, Helena; Oden, Anders; McCloskey, Eugene V.
2009-01-01
Fractures are a common complication of osteoporosis. Although osteoporosis is defined by bone mineral density at the femoral neck, other sites and validated techniques can be used for fracture prediction. Several clinical risk factors contribute to fracture risk independently of BMD. These include age, prior fragility fracture, smoking, excess alcohol, family history of hip fracture, rheumatoid arthritis and the use of oral glucocorticoids. These risk factors in conjunction with BMD can be integrated to provide estimates of fracture probability using the FRAX tool. Fracture probability rather than BMD alone can be used to fashion strategies for the assessment and treatment of osteoporosis.
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...
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.
Energy Technology Data Exchange (ETDEWEB)
Saigusa, F [Nippon Dental Coll., Tokyo
1981-02-01
Irradiation effects on callus formation after bone fracture were studied in rats with fractured right lower extremity. Follow-up study was continued for 112 days since 3000 rad was irradiated to the fractured site 3 days after bone fracture. Callus formation was noted in both of the outer and inner part (bone marrow) of the diaphysis before 14 days after bone fracture, but it was slow and sparse compared with that of non-irradiated group. Callus formation tended to disappear gradually from the outside of the diaphysis after 28 days after bone fracture. Strong disturbance was found in the surrounding vascular system at this time. Inside of the diaphysis, callus formation was restricted the end of the fracture, where lamellar calluses fused together. Changes in vascular system remained until 56 days after bone fracture. Vascular distribution was most dense 28 days after bone fracture. In many of the calluses which have established fusion, findings suggested excessive calcification in the trabeculae. Vascular distribution at this time was sparse, vascular formation was markedly suppressed in the bone marrow, and very little vascular formation was found in the fractured edges of the bone.
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.
Schottky spectra and crystalline beams
International Nuclear Information System (INIS)
Pestrikov, D.V.
1996-01-01
In this paper we revise the current dependence of the Schottky noise power of a cooled proton beam previously measured at NAP-M. More careful study of experimental data indicates a linear decrease in the inverse Schottky noise power with an increase in the beam intensity (N). The root of this function determines a threshold current which occurs at N = N th ≅1.2 x 10 8 particles. The inspection of measured Schottky spectra shows that this threshold does not correspond to some collective instability of the measured harmonic of the linear beam density. The found value of N th does not depend on the longitudinal beam temperature. For the case of NAP-M lattice, the study of the spectral properties of the Schottky noise in the crystalline string predicts the current dependence of the equilibrium momentum spread of the beam, which qualitatively agrees with that, recalculated from the NAP-M data. (orig.)
Bending cyclic load test for crystalline silicon photovoltaic modules
Suzuki, Soh; Doi, Takuya; Masuda, Atsushi; Tanahashi, Tadanori
2018-02-01
The failures induced by thermomechanical fatigue within crystalline silicon photovoltaic modules are a common issue that can occur in any climate. In order to understand these failures, we confirmed the effects of compressive or tensile stresses (which were cyclically loaded on photovoltaic cells and cell interconnect ribbons) at subzero, moderate, and high temperatures. We found that cell cracks were induced predominantly at low temperatures, irrespective of the compression or tension applied to the cells, although the orientation of cell cracks was dependent on the stress applied. The fracture of cell interconnect ribbons was caused by cyclical compressive stress at moderate and high temperatures, and this failure was promoted by the elevation of temperature. On the basis of these results, the causes of these failures are comprehensively discussed in relation to the viscoelasticity of the encapsulant.
A seismic study on cracks in crystalline rock
International Nuclear Information System (INIS)
Israelsson, H.
1981-07-01
This report summarizes results from a field study with in-situ seismic measurements in crystalline rock. It was found that among a few potential seismic techniques the so called cross hole method would probably provide the most powerful capability for detecting cracks and fracture zones. By this method the area between two holes are systematically scanned by seismic raypaths. Seismic signals are generated in one hole by micro explosions and recorded in the other at various combinations of depths. A test sample of scanning data showed a rather dramatic variation of the seismic P-wave velocity (5-6 km/s). Analysis procedures like tomographic imaging was applied to this data set primarily to illustrate the kind of structural mapping such procedures can provide. (Author)
Yenier, E.; Baturan, D.; Karimi, S.
2016-12-01
Monitoring of seismicity related to oil and gas operations is routinely performed nowadays using a number of different surface and downhole seismic array configurations and technologies. Here, we provide a hydraulic fracture (HF) monitoring case study that compares the data set generated by a sparse local surface network of broadband seismometers to a data set generated by a single downhole geophone string. Our data was collected during a 5-day single-well HF operation, by a temporary surface network consisting of 10 stations deployed within 5 km of the production well. The downhole data was recorded by a 20 geophone string deployed in an observation well located 15 m from the production well. Surface network data processing included standard STA/LTA event triggering enhanced by template-matching subspace detection, grid search locations which was improved using the double-differencing re-location technique, as well as Richter (ML) and moment (Mw) magnitude computations for all detected events. In addition, moment tensors were computed from first motion polarities and amplitudes for the subset of highest SNR events. The resulting surface event catalog shows a very weak spatio-temporal correlation to HF operations with only 43% of recorded seismicity occurring during HF stages times. This along with source mechanisms shows that the surface-recorded seismicity delineates the activation of several pre-existing structures striking NNE-SSW and consistent with regional stress conditions as indicated by the orientation of SHmax. Comparison of the sparse-surface and single downhole string datasets allows us to perform a cost-benefit analysis of the two monitoring methods. Our findings show that although the downhole array recorded ten times as many events, the surface network provides a more coherent delineation of the underlying structure and more accurate magnitudes for larger magnitude events. We attribute this to the enhanced focal coverage provided by the surface
Paratrooper's ankle fracture: posterior malleolar fracture.
Young, Ki Won; Kim, Jin-su; Cho, Jae Ho; Kim, Hyung Seuk; Cho, Hun Ki; Lee, Kyung Tai
2015-03-01
We assessed the frequency and types of ankle fractures that frequently occur during parachute landings of special operation unit personnel and analyzed the causes. Fifty-six members of the special force brigade of the military who had sustained ankle fractures during parachute landings between January 2005 and April 2010 were retrospectively analyzed. The injury sites and fracture sites were identified and the fracture types were categorized by the Lauge-Hansen and Weber classifications. Follow-up surveys were performed with respect to the American Orthopedic Foot and Ankle Society ankle-hindfoot score, patient satisfaction, and return to preinjury activity. The patients were all males with a mean age of 23.6 years. There were 28 right and 28 left ankle fractures. Twenty-two patients had simple fractures and 34 patients had comminuted fractures. The average number of injury and fractures sites per person was 2.07 (116 injuries including a syndesmosis injury and a deltoid injury) and 1.75 (98 fracture sites), respectively. Twenty-three cases (41.07%) were accompanied by posterior malleolar fractures. Fifty-five patients underwent surgery; of these, 30 had plate internal fixations. Weber type A, B, and C fractures were found in 4, 38, and 14 cases, respectively. Based on the Lauge-Hansen classification, supination-external rotation injuries were found in 20 cases, supination-adduction injuries in 22 cases, pronation-external rotation injuries in 11 cases, tibiofibular fractures in 2 cases, and simple medial malleolar fractures in 2 cases. The mean follow-up period was 23.8 months, and the average follow-up American Orthopedic Foot and Ankle Society ankle-hindfoot score was 85.42. Forty-five patients (80.36%) reported excellent or good satisfaction with the outcome. Posterior malleolar fractures occurred in 41.07% of ankle fractures sustained in parachute landings. Because most of the ankle fractures in parachute injuries were compound fractures, most cases had to
Fracture mechanical materials characterisation
International Nuclear Information System (INIS)
Wallin, K.; Planman, T.; Nevalainen, M.
1998-01-01
The experimental fracture mechanics development has been focused on the determination of reliable lower-bound fracture toughness estimates from small and miniature specimens, in particular considering the statistical aspects and loading rate effects of fracture mechanical material properties. Additionally, materials aspects in fracture assessment of surface cracks, with emphasis on the transferability of fracture toughness data to structures with surface flaws have been investigated. Further a modified crack-arrest fracture toughness test method, to increase the effectiveness of testing, has been developed. (orig.)
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.
Interaction between clay-based shaft seal components and crystalline host rock
International Nuclear Information System (INIS)
Priyanto, D.; Dixon, D.; Man, A.
2010-01-01
Document available in extended abstract form only. The Government of Canada has accepted the Nuclear Waste Management Organization's (NWMO) recommendation of Adaptive Phased Management (APM) as the long-term management approach for Canada's used nuclear fuel. APM ultimately involves the isolation and containment of used nuclear fuel deep in a Deep Geological Repository (DGR). On completion of waste emplacement operation and during repository closure, shaft seals, comprising clay-based shaft seal components, will be installed at strategic locations, such as where significant fracture zones (FZs) are located. The primary function of a shaft seal is to limit and prevent short-circuiting of the groundwater flow regime via the shaft. Currently, at Atomic Energy of Canada Limited's Underground Research Laboratory (URL) a full-scale shaft seal is being constructed at the intersection of a low dipping thrust fault called FZ 2 as part of the overall URL decommissioning activities. Both crystalline rock and sedimentary rock are considered potentially suitable host rocks formations for a DGR. This paper presents the results of numerical simulation of a shaft seal installed in moderately to sparsely fractured crystalline rock (MFR). The shape and thickness of the shaft seal modelled for a DGR in this exercise are similar to the shaft seal at the URL, but in the modelling exercise it is given a larger diameter (i.e. 7.30 m) equal to the assumed diameter of a production shaft of a repository. The seal consists of a blended bentonite-sand (BS) component that is constrained between two massive concrete seals. Dense backfill (DBF) materials are installed above and below the concrete seals (CS). The concrete seals are keyed into the access shaft to better anchor the concrete units in place and in order to restrain the swelling of the bentonite-sand component of the seal as it hydrates. The reference geosphere in the proposed work is MFR similar to the rock conditions
Fractures (Broken Bones): First Aid
First aid Fractures (broken bones) Fractures (broken bones): First aid By Mayo Clinic Staff A fracture is a ... 10, 2018 Original article: http://www.mayoclinic.org/first-aid/first-aid-fractures/basics/ART-20056641 . Mayo Clinic ...
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.
Crystalline silicotitanate gate review analysis
International Nuclear Information System (INIS)
Schlahta, S.N.; Carreon, R.; Gentilucci, J.A.
1997-11-01
Crystalline silicotitanate (CST) is an ion-exchange method for removing radioactive cesium from tank waste to allow the separation of the waste into high- and low-level fractions. The CST, originally developed Sandia National Laboratories personnel in association with Union Oil Products Corporation, has both a high affinity and selectivity for sorbing cesium-137 from highly alkaline or acidic solutions. For several years now, the U.S. Department of Energy has funded work to investigate applying CST to large-scale removal of cesium-137 from radioactive tank wastes. In January 1997, an expert panel sponsored by the Tanks Focus Area met to review the current state of the technology and to determine whether it was ready for routine use. The review also sought to identify any technical issues that must be resolved or additional CST development that must occur before full implementation by end-users. The CST Gate Review Group concluded that sufficient work has been done to close developmental work on CST and turn the remaining site-specific tasks over to the users. This report documents the review group''s findings, issues, concerns, and recommendations as well as responses from the Tanks Focus Area expert staff to specific pretreatment and immobilization issues
Crystalline lens dislocation secondary to bacterial endogenous endophthalmitis.
Sangave, Amit; Komati, Rahul; Weinmann, Allison; Samuel, Linoj; Desai, Uday
2017-09-01
To present an unusual case of endogenous endophthalmitis secondary to Group A streptococcus (GAS) that resulted in dislocation of the crystalline lens. An immunocompetent 51-year-old man presented to the emergency room (ER) with upper respiratory infection (URI) symptoms and painful right eye. He was diagnosed with URI and viral conjunctivitis and discharged on oral azithromycin and polytrim eyedrops. He returned to the ER 30 h later with sepsis and findings consistent with endophthalmitis, including light perception only vision. Ophthalmology was consulted at this time and an emergent vitreous tap and injection was performed. Both blood and vitreous cultures grew an atypical non-hemolytic variant of GAS ( Streptococcus pyogenes ). The primary source of infection was presumed to be secondary to pharyngitis or cutaneous dissemination. Final vision in the affected eye was no light perception, likely from a combination of anterior segment scarring, posterior segment damage, and hypotony. Interestingly, head computed tomography (CT) at the initial ER presentation showed normal lens position, but repeat CT at re-presentation revealed posterior dislocation of the lens. Endophthalmitis secondary to GAS has been sparsely reported in the literature, and this case highlights a unique clinical presentation. We suspect that this atypical non-hemolytic strain may have evaded detection on initial pharyngeal cultures. Additionally, we hypothesize that GAS-mediated protease release resulted in breakdown of the zonular fibers and subsequent lens dislocation. Ophthalmologists should be aware of GAS and its devastating intraocular manifestations.
Fracture toughness correlations
International Nuclear Information System (INIS)
Wallin, Kim
1986-09-01
In this study existing fracture parameter correlations are reviewed. Their applicability and reliability are discussed in detail. A new K IC -CVN-correlation, based on a theoretical brittle fracture model, is presented
... this page: //medlineplus.gov/ency/patientinstructions/000539.htm Rib fracture - aftercare To use the sharing features on this page, please enable JavaScript. A rib fracture is a crack or break in one or ...
Sprains, Strains and Fractures
... fractures. Many fractures and sprains occur during sports. Football players are particularly vulnerable to foot and ankle ... feet and ankles and take a complete medical history. He or she will also order tests, including ...
Skull fractures may occur with head injuries. Although the skull is both tough and resilient and provides excellent ... or blow can result in fracture of the skull and may be accompanied by injury to the ...
... this page: //medlineplus.gov/ency/patientinstructions/000548.htm Ankle fracture - aftercare To use the sharing features on this page, please enable JavaScript. An ankle fracture is a break in 1 or more ankle ...
Koray Aydogdu
2014-01-01
Rib fractures are usually seen after a trauma, while atraumatic spontaneous rib fractures are quite rare. A first rib fracture identified in our 17 years old female patient who had not a history of trauma except lifting a heavy weight was examined in details in terms of the potential complications and followed-up for a long time. We presented our experience on this case with atraumatic first rib fracture that has different views for the etiology in light of the literature.
Solute transport in fractured rock - applications to radionuclide waste repositories
International Nuclear Information System (INIS)
Neretnieks, I.
1990-12-01
Flow and solute transport in fractured rocks has been intensively studied in the last decade. The increased interest is mainly due to the plans in many countries to site repositories for high level nuclear waste in deep geologic formations. All investigated crystalline rocks have been found to be fractured and most of the water flows in the fractures and fracture zones. The water transports dissolved species and radionuclides. It is thus of interest to be able to understand and to do predictive modelling of the flowrate of water, the flowpaths and the residence times of the water and of the nuclides. The dissolved species including the nuclides will interact with the surrounding rock in different ways and will in many cases be strongly retarded relative to the water velocity. Ionic species may be ion exchanged or sorbed in the mineral surfaces. Charges and neutral species may diffuse into the stagnant waters in the rock matrix and thus be withdrawn from the mobile water. These effects will be strongly dependent on how much rock surface is in contact with the flowing water. It has been found in a set of field experiments and by other observations that not all fractures conduct water. Furthermore it is found that conductive fractures only conduct the water in a small part of the fracture in what is called channels or preferential flowpaths. This report summarizes the present concepts of water flow and solute transport in fractured rocks. The data needs for predictive modelling are discussed and both field and laboratory measurement which have been used to obtain data are described. Several large scale field experiments which have been specially designed to study flow and tracer transport in crystalline rocks are described. In many of the field experients new techniques have been developed and used. (81 refs.) (author)
Metatarsal stress fractures - aftercare
... Metatarsal stress fracture. In: Safran MR, Zachazewski J, Stone DA, eds. Instructions for Sports Medicine Patients . 2nd ed. Elsevier Saunders; 2012:648-652. Smith MS. Metatarsal fractures. In: Eiff PM, Hatch R, eds. Fracture Management for Primary Care . 3rd ed. ...
Relationships between fractures
Peacock, D. C. P.; Sanderson, D. J.; Rotevatn, A.
2018-01-01
Fracture systems comprise many fractures that may be grouped into sets based on their orientation, type and relative age. The fractures are often arranged in a network that involves fracture branches that interact with one another. Interacting fractures are termed geometrically coupled when they share an intersection line and/or kinematically coupled when the displacements, stresses and strains of one fracture influences those of the other. Fracture interactions are characterised in terms of the following. 1) Fracture type: for example, whether they have opening (e.g., joints, veins, dykes), closing (stylolites, compaction bands), shearing (e.g., faults, deformation bands) or mixed-mode displacements. 2) Geometry (e.g., relative orientations) and topology (the arrangement of the fractures, including their connectivity). 3) Chronology: the relative ages of the fractures. 4) Kinematics: the displacement distributions of the interacting fractures. It is also suggested that interaction can be characterised in terms of mechanics, e.g., the effects of the interaction on the stress field. It is insufficient to describe only the components of a fracture network, with fuller understanding coming from determining the interactions between the different components of the network.
Gonnelli, Stefano; Caffarelli, Carla; Nuti, Ranuccio
2014-01-01
Obesity and osteoporosis are two common diseases with an increasing prevalence and a high impact on morbidity and mortality. Obese women have always been considered protected against osteoporosis and osteoporotic fractures. However, several recent studies have challenged the widespread belief that obesity is protective against fracture and have suggested that obesity is a risk factor for certain fractures.
Imaging of insufficiency fractures
Energy Technology Data Exchange (ETDEWEB)
Krestan, Christian [Department of Radiology, Medical University of Vienna, Vienna General Hospital, Waehringerstr. 18-20, 1090 Vienna (Austria)], E-mail: christian.krestan@meduniwien.ac.at; Hojreh, Azadeh [Department of Radiology, Medical University of Vienna, Vienna General Hospital, Waehringerstr. 18-20, 1090 Vienna (Austria)
2009-09-15
This review focuses on the occurrence, imaging and differential diagnosis of insufficiency fractures. Prevalence, the most common sites of insufficiency fractures and their clinical implications are discussed. Insufficiency fractures occur with normal stress exerted on weakened bone. Postmenopausal osteoporosis is the most common cause of insufficiency fractures. Other conditions which affect bone turnover include osteomalacia, hyperparathyroidism, chronic renal failure and high-dose glucocorticoid therapy. It is a challenge for the radiologist to detect and diagnose insufficiency fractures, and to differentiate them from other bone lesions. Radiographs are still the most widely used imaging method for identification of insufficiency fractures, but sensitivity is limited, depending on the location of the fractures. Magnetic resonance imaging (MRI) is a very sensitive tool to visualize bone marrow abnormalities associated with insufficiency fractures. Thin section, multi-detector computed tomography (MDCT) depicts subtle fracture lines allowing direct visualization of cortical and trabecular bone. Bone scintigraphy still plays a role in detecting fractures, with good sensitivity but limited specificity. The most important differential diagnosis is underlying malignant disease leading to pathologic fractures. Bone densitometry and clinical history may also be helpful in confirming the diagnosis of insufficiency fractures.
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.
Brook, Martin; Hebblewhite, Bruce; Mitra, Rudrajit
2016-04-01
The size-scaling of rock fractures is a well-studied problem in geology, especially for permeability quantification. The intensity of fractures may control the economic exploitation of fractured reservoirs because fracture intensity describes the abundance of fractures potentially available for fluid flow. Moreover, in geotechnical engineering, fractures are important for parameterisation of stress models and excavation design. As fracture data is often collected from widely-spaced boreholes where core recovery is often incomplete, accurate interpretation and representation of fracture aperture-frequency relationships from sparse datasets is important. Fracture intensity is the number of fractures encountered per unit length along a sample scanline oriented perpendicular to the fractures in a set. Cumulative frequency of fractures (F) is commonly related to fracture aperture (A) in the form of a power-law (F = aA-b), with variations in the size of the a coefficient between sites interpreted to equate to fracture frequency for a given aperture (A). However, a common flaw in this approach is that even a small change in b can have a large effect on the response of the fracture frequency (F) parameter. We compare fracture data from the Late Permian Rangal Coal Measures from Australia's Bowen Basin, with fracture data from Jurassic carbonates from the Sierra Madre Oriental, northeastern Mexico. Both power-law coefficient a and exponent b control the fracture aperture-frequency relationship in conjunction with each other; that is, power-laws with relatively low a coefficients have relatively high b exponents and vice versa. Hence, any comparison of different power-laws must take both a and b into consideration. The corollary is that different sedimentary beds in the Sierra Madre carbonates do not show ˜8× the fracture frequency for a given fracture aperture, as based solely on the comparison of coefficient a. Rather, power-law "sensitivity factors" developed from both
Hydraulic testing in crystalline rock
International Nuclear Information System (INIS)
Almen, K.E.; Andersson, J.E.; Carlsson, L.; Hansson, K.; Larsson, N.A.
1986-12-01
Swedish Geolocical Company (SGAB) conducted and carried out single-hole hydraulic testing in borehole Fi 6 in the Finnsjoen area of central Sweden. The purpose was to make a comprehensive evaluation of different methods applicable in crystalline rocks and to recommend methods for use in current and scheduled investigations in a range of low hydraulic conductivity rocks. A total of eight different methods of testing were compared using the same equipment. This equipment was thoroughly tested as regards the elasticity of the packers and change in volume of the test section. The use of a hydraulically operated down-hole valve enabled all the tests to be conducted. Twelve different 3-m long sections were tested. The hydraulic conductivity calculated ranged from about 5x10 -14 m/s to 1x10 -6 m/s. The methods used were water injection under constant head and then at a constant rate-of-flow, each of which was followed by a pressure fall-off period. Water loss, pressure pulse, slug and drill stem tests were also performed. Interpretation was carried out using standard transient evaluation methods for flow in porous media. The methods used showed themselves to be best suited to specific conductivity ranges. Among the less time-consuming methods, water loss, slug and drill stem tests usually gave somewhat higher hydraulic conductivity values but still comparable to those obtained using the more time-consuming tests. These latter tests, however, provided supplementary information on hydraulic and physical properties and flow conditions, together with hydraulic conductivity values representing a larger volume of rock. (orig./HP)
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
Groundwater flow and sorption processes in fractured rocks (I)
Energy Technology Data Exchange (ETDEWEB)
Kim, Won Young; Woo, Nam Chul; Yum, Byoung Woo; Choi, Young Sub; Chae, Byoung Kon; Kim, Jung Yul; Kim, Yoo Sung; Hyun, Hye Ja; Lee, Kil Yong; Lee, Seung Gu; Youn, Youn Yul; Choon, Sang Ki [Korea Institute of Geology Mining and Materials, Taejon (Korea, Republic of)
1996-12-01
This study is objected to characterize groundwater flow and sorption processes of the contaminants (ground-water solutes) along the fractured crystalline rocks in Korea. Considering that crystalline rock mass is an essential condition for using underground space cannot be overemphasized the significance of the characterizing fractured crystalline rocks. the behavior of the groundwater contaminants is studied in related to the subsurface structure, and eventually a quantitative technique will be developed to evaluate the impacts of the contaminants on the subsurface environments. The study has been carried at the Samkwang mine area in the Chung-Nam Province. The site has Pre-Cambrian crystalline gneiss as a bedrock and the groundwater flow system through the bedrock fractures seemed to be understandable with the study on the subsurface geologic structure through the mining tunnels. Borehole tests included core logging, televiewer logging, constant pressure fixed interval length tests and tracer tests. The results is summarized as follows; 1) To determine the hydraulic parameters of the fractured rock, the transient flow analysis produce better results than the steady - state flow analysis. 2) Based on the relationship between fracture distribution and transmissivities measured, the shallow part of the system could be considered as a porous and continuous medium due to the well developed fractures and weathering. However, the deeper part shows flow characteristics of the fracture dominant system, satisfying the assumptions of the Cubic law. 3) Transmissivities from the FIL test were averaged to be 6.12 x 10{sup -7}{sub m}{sup 2}{sub /s}. 4) Tracer tests result indicates groundwater flow in the study area is controlled by the connection, extension and geometry of fractures in the bedrock. 5) Hydraulic conductivity of the tracer-test interval was in maximum of 7.2 x 10{sup -6}{sub m/sec}, and the effective porosity of 1.8 %. 6) Composition of the groundwater varies
Liu, Zhiyuan; Wang, Shijie; Zhao, Haiyang; Wang, Lei; Li, Wei; Geng, Yudi; Tao, Shan; Zhang, Guangqing; Chen, Mian
2018-02-01
Natural fractures have a significant influence on the propagation geometry of hydraulic fractures in fractured reservoirs. True triaxial volumetric fracturing experiments, in which random natural fractures are created by placing cement blocks of different dimensions in a cuboid mold and filling the mold with additional cement to create the final test specimen, were used to study the factors that influence the hydraulic fracture propagation geometry. These factors include the presence of natural fractures around the wellbore, the dimension and volumetric density of random natural fractures and the horizontal differential stress. The results show that volumetric fractures preferentially formed when natural fractures occurred around the wellbore, the natural fractures are medium to long and have a volumetric density of 6-9%, and the stress difference is less than 11 MPa. The volumetric fracture geometries are mainly major multi-branch fractures with fracture networks or major multi-branch fractures (2-4 fractures). The angles between the major fractures and the maximum horizontal in situ stress are 30°-45°, and fracture networks are located at the intersections of major multi-branch fractures. Short natural fractures rarely led to the formation of fracture networks. Thus, the interaction between hydraulic fractures and short natural fractures has little engineering significance. The conclusions are important for field applications and for gaining a deeper understanding of the formation process of volumetric fractures.
Role of MRI in hip fractures, including stress fractures, occult fractures, avulsion fractures
International Nuclear Information System (INIS)
Nachtrab, O.; Cassar-Pullicino, V.N.; Lalam, R.; Tins, B.; Tyrrell, P.N.M.; Singh, J.
2012-01-01
MR imaging plays a vital role in the diagnosis and management of hip fractures in all age groups, in a large spectrum of patient groups spanning the elderly and sporting population. It allows a confident exclusion of fracture, differentiation of bony from soft tissue injury and an early confident detection of fractures. There is a spectrum of MR findings which in part is dictated by the type and cause of the fracture which the radiologist needs to be familiar with. Judicious but prompt utilisation of MR in patients with suspected hip fractures has a positive therapeutic impact with healthcare cost benefits as well as social care benefits.
Directory of Open Access Journals (Sweden)
Jeffrey M Joseph
2011-01-01
Full Text Available Jeffrey M Joseph, Ioannis P GlavasDivision of Ophthalmic Plastic and Reconstructive Surgery, Department of Ophthalmology, School of Medicine, New York University, New York, NY, USA; Manhattan Eye, Ear, and Throat Hospital, New York, NY, USAAbstract: This review of orbital fractures has three goals: 1 to understand the clinically relevant orbital anatomy with regard to periorbital trauma and orbital fractures, 2 to explain how to assess and examine a patient after periorbital trauma, and 3 to understand the medical and surgical management of orbital fractures. The article aims to summarize the evaluation and management of commonly encountered orbital fractures from the ophthalmologic perspective and to provide an overview for all practicing ophthalmologists and ophthalmologists in training.Keywords: orbit, trauma, fracture, orbital floor, medial wall, zygomatic, zygomatic complex, zmc fracture, zygomaticomaxillary complex fractures
Mechanics of Hydraulic Fractures
Detournay, Emmanuel
2016-01-01
Hydraulic fractures represent a particular class of tensile fractures that propagate in solid media under pre-existing compressive stresses as a result of internal pressurization by an injected viscous fluid. The main application of engineered hydraulic fractures is the stimulation of oil and gas wells to increase production. Several physical processes affect the propagation of these fractures, including the flow of viscous fluid, creation of solid surfaces, and leak-off of fracturing fluid. The interplay and the competition between these processes lead to multiple length scales and timescales in the system, which reveal the shifting influence of the far-field stress, viscous dissipation, fracture energy, and leak-off as the fracture propagates.
DEFF Research Database (Denmark)
Hassager, Ole
Fracture is a phenomenon that is generally associated with solids. A key element in fracture theory is the so-called weakest link idea that fracture initiates from the largest pre-existing material imperfection. However, recent work has demonstrated that fracture can also happen in liquids, where...... surface tension will act to suppress such imperfections. Therefore, the weakest link idea does not seem immediately applicable to fracture in liquids. This presentation will review fracture in liquids and argue that fracture in soft liquids is a material property independent of pre-existing imperfections....... The following questions then emerge: What is the material description needed to predict crack initiation, crack speed and crack shape in soft materials and liquids....
The quest for crystalline ion beams
Schramm, U; Bussmann, M; Habs, D
2002-01-01
The phase transition of an ion beam into its crystalline state has long been expected to dramatically influence beam dynamics beyond the limitations of standard accelerator physics. Yet, although considerable improvement in beam cooling techniques has been made, strong heating mechanisms inherent to existing high-energy storage rings have prohibited the formation of the crystalline state in these machines up to now. Only recently, laser cooling of low-energy beams in the table-top rf quadrupole storage ring PAaul Laser cooLing Acceleration System (PALLAS) has lead to the experimental realization of crystalline beams. In this article, the quest for crystalline beams as well as their unique properties as experienced in PALLAS will be reviewed.
Excimer fluorescence of liquid crystalline systems
Sakhno, Tamara V.; Khakhel, Oleg A.; Barashkov, Nikolay N.; Korotkova, Irina V.
1996-04-01
The method of synchronous scanning fluorescence spectroscopy shows a presence of dimers of pyrene in a polymeric matrix. The results suggest that excimer formation takes place with dimers in liquid crystalline systems.
Syntheses, molecular and crystalline architectures, and ...
Indian Academy of Sciences (India)
Syntheses, molecular and crystalline architectures, and luminescence behaviour of terephthalate bridged heptacoordinated dinuclear lead(II) complexes containing a pentadentate N-donor Schiff base. SUBHASIS ROYa, SOMNATH CHOUBEYa, SUMITAVA KHANa, KISHALAY BHARa,. PARTHA MITRAb and BARINDRA ...
Electrochemical synthesis of highly crystalline copper nanowires
International Nuclear Information System (INIS)
Kaur, Amandeep; Gupta, Tanish; Kumar, Akshay; Kumar, Sanjeev; Singh, Karamjeet; Thakur, Anup
2015-01-01
Copper nanowires were fabricated within the pores of anodic alumina template (AAT) by template synthesis method at pH = 2.9. X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) were used to investigate the structure, morphology and composition of fabricated nanowires. These characterizations revealed that the deposited copper nanowires were highly crystalline in nature, dense and uniform. The crystalline copper nanowires are promising in application of future nanoelectronic devices and circuits
Irradiation sterilization of semi-crystalline polymers
International Nuclear Information System (INIS)
Williams, J.; Dunn, T.; Stannett, V.
1978-01-01
A semi-crystalline polymer such as polypropylene, is sterilized by high energy irradiation, with the polymer containing a non-crystalline mobilizing additive which increases the free volume of the polymer, to prevent embrittlement of the polymer during and subsequent to the irradiation. The additive has a density of from 0.6 to 1.9 g/cm 3 and a molecular weight from 100 to 10,000 g/mole
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
International Nuclear Information System (INIS)
Sirat, M.
1999-01-01
The > 10,000 fractures documented in the 450 m deep Aespoe Hard Rock Laboratory (HRL) provide a unique opportunity to study brittle deformation of a Swedish bedrock mass. The fracture population consists of six major sets, one sub-horizontal and five sub-vertical. A classical structural analysis explored the interrelations between geometry and frequency of both dry and wet fractures with respect to depth and in-situ stresses. Three main findings are: In-situ stresses govern frequency distributions of dilated, hence water-bearing fractures. About 68.5% of sub-horizontal fractures are dilated in the thrust regime above a depth of ca. 230 m while 53% of sub-vertical fractures are dilated in the underlying wrench regime. Fractures curve both horizontally and vertically, a finding confirmed by the application of artificial neural networks that included Back-Propagation and Self-Organizing (Kohonen) networks. The asymmetry of the total fracture population and tilts of the sub-Cambrian peneplain demonstrates that multiple reactivations of fractures have tilted the Aespoe rock mass 6 deg to the west. The potential space problem raised by this tilt is negated by systematic curvature of steep fractures, some of which sole out to gently dipping fracture zones. Fractures probably developed their curvature when they formed deep in crystalline crust in Precambrian times but have since reactivated at shallow depths. These findings add significantly to the conceptual model of Aespoe and should be taken into account in future studies regarding the isolation of Sweden's high-grade radioactive waste in crystalline bedrock
International Nuclear Information System (INIS)
Liu, L.; Neretnieks, I.
2005-01-01
Full text of publication follows: Canisters with spent fuel will be deposited in fractured crystalline rock in the Swedish concept for a final repository. The fractures intersect the canister holes at different angles and they have variable apertures and therefore locally varying flowrates. Our previous model with fractures with a constant aperture and a 90 deg. intersection angle is now extended to arbitrary intersection angles and stochastically variable apertures. It is shown the previous basic model can be simply amended to account for these effects. The mean and the standard deviation of the water flowrate in the fractures are obtained from the statistics of the aperture variations by a simple formula. Likewise, the statistical form of distribution of the so-called 'equivalent flowrate', which describes the mass transfer of solutes between the canister and the flowing water, is also obtained by a simple relation. These simple statistical relations obviate the need to simulate each fracture that intersects a canister in great detail. The water flowrate and the equivalent flowrate of a fracture are instead taken from the simple distributions presented in this work. This allows the use of complex fractures also in very large fracture network models used in performance assessment. The distributions have been obtained by generating a multitude of fractures and by studying their flow and transport properties. Fractal as well as Gaussian aperture distributions have been studied. It has been found that the distributions of the volumetric and the equivalent flow rates are all close to the Normal for both types of fractures, with the mean of the distribution of the volumetric flow rate being determined solely by the hydraulic aperture, and that of the equivalent flow rate being determined by the mechanical aperture. Moreover, the standard deviation of the volumetric flow rates of the many realizations increases with increasing roughness and spatial correlation length of
Ballistic fractures: indirect fracture to bone.
Dougherty, Paul J; Sherman, Don; Dau, Nathan; Bir, Cynthia
2011-11-01
Two mechanisms of injury, the temporary cavity and the sonic wave, have been proposed to produce indirect fractures as a projectile passes nearby in tissue. The purpose of this study is to evaluate the temporal relationship of pressure waves using strain gauge technology and high-speed video to elucidate whether the sonic wave, the temporary cavity, or both are responsible for the formation of indirect fractures. Twenty-eight fresh frozen cadaveric diaphyseal tibia (2) and femurs (26) were implanted into ordnance gelatin blocks. Shots were fired using 9- and 5.56-mm bullets traversing through the gelatin only, passing close to the edge of the bone, but not touching, to produce an indirect fracture. High-speed video of the impact event was collected at 20,000 frames/s. Acquisition of the strain data were synchronized with the video at 20,000 Hz. The exact time of fracture was determined by analyzing and comparing the strain gauge output and video. Twenty-eight shots were fired, 2 with 9-mm bullets and 26 with 5.56-mm bullets. Eight indirect fractures that occurred were of a simple (oblique or wedge) pattern. Comparison of the average distance of the projectile from the bone was 9.68 mm (range, 3-20 mm) for fractured specimens and 15.15 mm (range, 7-28 mm) for nonfractured specimens (Student's t test, p = 0.036). In this study, indirect fractures were produced after passage of the projectile. Thus, the temporary cavity, not the sonic wave, was responsible for the indirect fractures.
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.
Molecular origins of anisotropic shock propagation in crystalline and amorphous polyethylene
O'Connor, Thomas C.; Elder, Robert M.; Sliozberg, Yelena R.; Sirk, Timothy W.; Andzelm, Jan W.; Robbins, Mark O.
2018-03-01
Molecular dynamics simulations are used to analyze shock propagation in amorphous and crystalline polyethylene. Results for the shock velocity Us are compared to predictions from Pastine's equation of state and hydrostatic theory. The results agree with Pastine at high impact velocities. At low velocities the yield stress becomes important, increasing the shock velocity and leading to anisotropy in the crystalline response. Detailed analysis of changes in atomic order reveals the origin of the anisotropic response. For shock along the polymer backbone, an elastic front is followed by a plastic front where chains buckle with a characteristic wavelength. Shock perpendicular to the chain backbone can produce plastic deformation or transitions to different orthorhombic or monoclinic structures, depending on the impact speed and direction. Tensile loading does not produce stable shocks: Amorphous systems craze and fracture while for crystals the front broadens linearly with time.
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
Directory of Open Access Journals (Sweden)
Koray Aydogdu
2014-12-01
Full Text Available Rib fractures are usually seen after a trauma, while atraumatic spontaneous rib fractures are quite rare. A first rib fracture identified in our 17 years old female patient who had not a history of trauma except lifting a heavy weight was examined in details in terms of the potential complications and followed-up for a long time. We presented our experience on this case with atraumatic first rib fracture that has different views for the etiology in light of the literature.
Fracture mechanics safety approaches
International Nuclear Information System (INIS)
Roos, E.; Schuler, X.; Eisele, U.
2004-01-01
Component integrity assessments require the knowledge of reliable fracture toughness parameters characterising the initiation of the failure process in the whole relevant temperature range. From a large number of fracture mechanics tests a statistically based procedure was derived allowing to quantify the initiation of fracture toughness as a function of temperature as a closed function as well as the temperature dependence of the cleavage instability parameters. Alternatively to the direct experimental determination one also can use a correlation between fracture toughness and notch impact energy. (orig.)
Scaphoid fractures in children
Directory of Open Access Journals (Sweden)
Gajdobranski Đorđe
2014-01-01
Full Text Available Introduction. Scaphoid fractures are rare in childhood. Diagnosis is very difficult to establish because carpal bones are not fully ossified. In suspected cases comparative or delayed radiography is used, as well as computerized tomography, magnetic resonance imaging, ultrasound and bone scintigraphy. Majority of scaphoid fractures are treated conservatively with good results. In case of delayed fracture healing various types of treatment are available. Objective. To determine the mechanism of injury, clinical healing process, types and outcome of treatment of scaphoid fractures in children. Methods. We retrospectively analyzed patients with traumatic closed fracture of the scaphoid bone over a ten-year period (2002-2011. The outcome of the treatment of “acute” scaphoid fracture was evaluated using the Mayo Wrist Score. Results. There were in total 34 patients, of mean age 13.8 years, with traumatic closed fracture of the scaphoid bone, whose bone growth was not finished yet. Most common injury mechanism was fall on outstretched arm - 76% of patients. During the examined period 31 children with “acute” fracture underwent conservative treatment, with average immobilization period of 51 days. Six patients were lost to follow-up. In the remaining 25 patients, after completed rehabilitation, functional results determined by the Mayo Wrist Score were excellent. Conclusion. Conservative therapy of “acute” scaphoid fractures is an acceptable treatment option for pediatric patients with excellent functional results.
Pathological fractures in children
De Mattos, C. B. R.; Binitie, O.; Dormans, J. P.
2012-01-01
Pathological fractures in children can occur as a result of a variety of conditions, ranging from metabolic diseases and infection to tumours. Fractures through benign and malignant bone tumours should be recognised and managed appropriately by the treating orthopaedic surgeon. The most common benign bone tumours that cause pathological fractures in children are unicameral bone cysts, aneurysmal bone cysts, non-ossifying fibromas and fibrous dysplasia. Although pathological fractures through a primary bone malignancy are rare, these should be recognised quickly in order to achieve better outcomes. A thorough history, physical examination and review of plain radiographs are crucial to determine the cause and guide treatment. In most benign cases the fracture will heal and the lesion can be addressed at the time of the fracture, or after the fracture is healed. A step-wise and multidisciplinary approach is necessary in caring for paediatric patients with malignancies. Pathological fractures do not have to be treated by amputation; these fractures can heal and limb salvage can be performed when indicated. PMID:23610658
Group sparse canonical correlation analysis for genomic data integration.
Lin, Dongdong; Zhang, Jigang; Li, Jingyao; Calhoun, Vince D; Deng, Hong-Wen; Wang, Yu-Ping
2013-08-12
The emergence of high-throughput genomic datasets from different sources and platforms (e.g., gene expression, single nucleotide polymorphisms (SNP), and copy number variation (CNV)) has greatly enhanced our understandings of the interplay of these genomic factors as well as their influences on the complex diseases. It is challenging to explore the relationship between these different types of genomic data sets. In this paper, we focus on a multivariate statistical method, canonical correlation analysis (CCA) method for this problem. Conventional CCA method does not work effectively if the number of data samples is significantly less than that of biomarkers, which is a typical case for genomic data (e.g., SNPs). Sparse CCA (sCCA) methods were introduced to overcome such difficulty, mostly using penalizations with l-1 norm (CCA-l1) or the combination of l-1and l-2 norm (CCA-elastic net). However, they overlook the structural or group effect within genomic data in the analysis, which often exist and are important (e.g., SNPs spanning a gene interact and work together as a group). We propose a new group sparse CCA method (CCA-sparse group) along with an effective numerical algorithm to study the mutual relationship between two different types of genomic data (i.e., SNP and gene expression). We then extend the model to a more general formulation that can include the existing sCCA models. We apply the model to feature/variable selection from two data sets and compare our group sparse CCA method with existing sCCA methods on both simulation and two real datasets (human gliomas data and NCI60 data). We use a graphical representation of the samples with a pair of canonical variates to demonstrate the discriminating characteristic of the selected features. Pathway analysis is further performed for biological interpretation of those features. The CCA-sparse group method incorporates group effects of features into the correlation analysis while performs individual feature
Non-Newtonian fluid flow in 2D fracture networks
Zou, L.; Håkansson, U.; Cvetkovic, V.
2017-12-01
Modeling of non-Newtonian fluid (e.g., drilling fluids and cement grouts) flow in fractured rocks is of interest in many geophysical and industrial practices, such as drilling operations, enhanced oil recovery and rock grouting. In fractured rock masses, the flow paths are dominated by fractures, which are often represented as discrete fracture networks (DFN). In the literature, many studies have been devoted to Newtonian fluid (e.g., groundwater) flow in fractured rock using the DFN concept, but few works are dedicated to non-Newtonian fluids.In this study, a generalized flow equation for common non-Newtonian fluids (such as Bingham, power-law and Herschel-Bulkley) in a single fracture is obtained from the analytical solutions for non-Newtonian fluid discharge between smooth parallel plates. Using Monte Carlo sampling based on site characterization data for the distribution of geometrical features (e.g., density, length, aperture and orientations) in crystalline fractured rock, a two dimensional (2D) DFN model is constructed for generic flow simulations. Due to complex properties of non-Newtonian fluids, the relationship between fluid discharge and the pressure gradient is nonlinear. A Galerkin finite element method solver is developed to iteratively solve the obtained nonlinear governing equations for the 2D DFN model. Using DFN realizations, simulation results for different geometrical distributions of the fracture network and different non-Newtonian fluid properties are presented to illustrate the spatial discharge distributions. The impact of geometrical structures and the fluid properties on the non-Newtonian fluid flow in 2D DFN is examined statistically. The results generally show that modeling non-Newtonian fluid flow in fractured rock as a DFN is feasible, and that the discharge distribution may be significantly affected by the geometrical structures as well as by the fluid constitutive properties.
Geometrical properties of tension-induced fractures in granite
International Nuclear Information System (INIS)
Sato, Hisashi; Sawada, Atsushi; Yasuhara, Hideaki
2011-03-01
Considering a safe, long-term sequestration of energy byproducts such as high level radioactive wastes, it is of significant importance to well-constrain the hydraulic and transport behavior of targeted permeants within fractured rocks. Specifically, fluid flow within low-permeability crystalline rock masses (e.g., granite) is often dominated by transport in through-cutting fractures, and thus careful considerations are needed on the behavior. There are three planes along that granites fail most easily under tension, and those may be identified as the rift, grain, and hardway planes. This anisotropic fabric may be attributed to preferentially oriented microcrack sets contained within intact rock. In this research, geometrical properties of tension-induced fractures are evaluated as listed below; (1) Creation of tension-induced fractures considering the anisotropy clarified by elastic wave measurements. (2) Evaluation of geometrical properties in those fractures characterized by the anisotropy. In the item (1), the three planes of rift, grain and hardway were identified by measuring elastic wave. In the item (2), JRC, variogram, fractal dimension and distributions of elevations in the fracture surfaces were evaluated using digitized data of the fracture surfaces measured via a laser profilometry. Results show that rift planes are less rougher than the other planes of grain and hardway, and grain planes are generically rougher than the other planes of rift and hardway. It was also confirmed that the fracture shape anisotropy was correlated with the direction of the slit which constructed during tensile tests. On the other hand, the tendency peculiar to the direction of slit and granites fail about the estimated aperture distribution from fracture shape was not seen. (author)
An in-depth study of sparse codes on abnormality detection
DEFF Research Database (Denmark)
Ren, Huamin; Pan, Hong; Olsen, Søren Ingvor
2016-01-01
Sparse representation has been applied successfully in abnormal event detection, in which the baseline is to learn a dictionary accompanied by sparse codes. While much emphasis is put on discriminative dictionary construction, there are no comparative studies of sparse codes regarding abnormality...... are carried out from various angles to better understand the applicability of sparse codes, including computation time, reconstruction error, sparsity, detection accuracy, and their performance combining various detection methods. The experiment results show that combining OMP codes with maximum coordinate...
Cheng, Hong
2015-01-01
This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: provides a thorough introduction to the fundamentals of sparse representation, modeling and learning, and the application of these techniques in visual recognition; describes sparse recovery approaches, robust and efficient sparse represen
Porting of the DBCSR library for Sparse Matrix-Matrix Multiplications to Intel Xeon Phi systems
Bethune, Iain; Gloess, Andeas; Hutter, Juerg; Lazzaro, Alfio; Pabst, Hans; Reid, Fiona
2017-01-01
Multiplication of two sparse matrices is a key operation in the simulation of the electronic structure of systems containing thousands of atoms and electrons. The highly optimized sparse linear algebra library DBCSR (Distributed Block Compressed Sparse Row) has been specifically designed to efficiently perform such sparse matrix-matrix multiplications. This library is the basic building block for linear scaling electronic structure theory and low scaling correlated methods in CP2K. It is para...
Fracture of the styloid process associated with the mandible fracture
Directory of Open Access Journals (Sweden)
K N Dubey
2013-01-01
Full Text Available Fracture of the styloid process (SP of temporal bone is an uncommon injuries. Fracture of the SP can be associated with the facial injuries including mandible fracture. However, injury to the SP may be concealed and missed diagnosis may lead to the improper or various unnecessary treatments. A rare case of SP fracture associated with the ipsilateral mandibular fracture and also the diagnostic and management considerations of the SP fracture are discussed.
Nanoparticles migration in fractured rocks and affects on contaminant migration
Missana, Tiziana; Garcia-Gutierrez, Miguel; Alonso, Ursula
2014-05-01
In previous studies, the transport behavior of artificial (gold and latex) and natural (smectite clay) colloids, within a planar fracture in crystalline rock, was analyzed. In order to better understand the effects of colloid size, shape and surface charge on nanoparticle migration and especially on filtration processes on natural rock surfaces, different clay colloids and oxide nanoparticles were selected and their transport studied as a function of the residence time. In all the cases, (a fraction of) the nanoparticles travelled in the fracture as fast as or faster than water (with a retardation factor, Rf ≤ 1) and the observed Rf, was related to the Taylor dispersion coefficient, accounting for colloid size, water velocity and fracture width. However, under most of the cases, in contrast to the behavior of a conservative tracer, colloids recovery was much lower than 100 %. Differences in recovery between different nanoparticles, under similar residence times, were analyzed. In order to evaluate the possible consequences, on contaminant migration, of the presence of nanoparticles in the system, transport tests were carried out with both colloids and sorbing radionuclides. The overall capacity for colloids of enhancing radionuclide migration in crystalline rock fractures is discussed. Acknowledgments: The research leading to these results received funding from EU FP7/2007-2011 grant agreement Nº 295487 (BELBAR, Bentonite Erosion: effects on the Long term performance of the engineered Barrier and Radionuclide Transport) and by the Spanish Government under the project NANOBAG (CTM2011-2797).
Geological site selection studies in Precambrian crystalline rocks in Finland
International Nuclear Information System (INIS)
Vuorela, P.
1988-01-01
In general geological investigations made since 1977 the Finnish crystalline bedrock has been determined to be suitable for the final disposal of the spent nuclear fuel. Regional investigations have been mainly based on already existing geological studies. Special attention has been paid on the international geological Finland as the Baltic Shield is stiff and stable and situated far outside the zones of volcanic and seismic activity. The present day crustal movements in Finland are related to landuplift process. Movements and possible faults in the bedrock follow fracture zones which devide the bedrock into mosaiclike blocks. As compared to small scale geological maps the bedrock blocks are often indicated as large granite rock formations which are less broken than the surrounding rocks, though the age of granite formations is at least 1500 millions of years. The large bedrock blocks (20-300 km 2 ) are divided to smaller units by different magnitudes of fractures and these smaller bedrock units (5-20 km 2 ) have been selected for further site selection investigations. At the first stage of investigations 327 suitable regional bedrock blocks have been identified on the basis of Landsat-1 winter and summer mosaics of Finland. After two years of investigations 134 investigation areas were selected inside 61 bedrock blocks and classified to four priority classes, the three first of which were redommended for further investigations. Geological criteries used in classification indicated clear differences between the classes one and three, however all classified areas are situated in large rather homogenous bedrock blocks and more exact three dimensional suitability errors may not be observed until deep bore holes have been made
Bio-based liquid crystalline polyesters
Wilsens, Carolus; Rastogi, Sanjay; Dutch Collaboration
2013-03-01
The reported thin-film polymerization has been used as a screening method in order to find bio-based liquid crystalline polyesters with convenient melting temperatures for melt-processing purposes. An in depth study of the structural, morphological and chemical changes occurring during the ongoing polycondensation reactions of these polymers have been performed. Structural and conformational changes during polymerization for different compositions have been followed by time resolved X-ray and Infrared spectroscopy. In this study, bio-based monomers such as vanillic acid and 2,5-furandicarboxylic acid are successfully incorporated in liquid crystalline polyesters and it is shown that bio-based liquid crystalline polymers with high aromatic content and convenient processing temperatures can be synthesized. Special thanks to the Dutch Polymer Institute for financial support
Irreducible tensor operators and crystalline potentials
International Nuclear Information System (INIS)
Boutron, F.; Saint-James, D.
1961-01-01
It is often accepted that the effects of its neighbourhood on the quantum state of an ion A may be obtained by the model of the crystalline effective field approximation. Within this assumption Stevens has developed a method which provides equivalent operators that facilitate the calculation of the matrix elements of the crystalline field in a given multiplicity. This method has been extended here. We demonstrate that in the expansion of the crystalline field in powers of the electrons coordinates of the ion A - for electrons of the same sub-shell of A - only even terms can contribute. Equivalent operators and matrix elements, in a given multiplicity, are given for these development terms - up to order 6 - and for potential invariant by the operations of one of the thirty-two point-groups. (author) [fr
High-Order Sparse Linear Predictors for Audio Processing
DEFF Research Database (Denmark)
Giacobello, Daniele; van Waterschoot, Toon; Christensen, Mads Græsbøll
2010-01-01
Linear prediction has generally failed to make a breakthrough in audio processing, as it has done in speech processing. This is mostly due to its poor modeling performance, since an audio signal is usually an ensemble of different sources. Nevertheless, linear prediction comes with a whole set...... of interesting features that make the idea of using it in audio processing not far fetched, e.g., the strong ability of modeling the spectral peaks that play a dominant role in perception. In this paper, we provide some preliminary conjectures and experiments on the use of high-order sparse linear predictors...... in audio processing. These predictors, successfully implemented in modeling the short-term and long-term redundancies present in speech signals, will be used to model tonal audio signals, both monophonic and polyphonic. We will show how the sparse predictors are able to model efﬁciently the different...
Sparse Covariance Matrix Estimation by DCA-Based Algorithms.
Phan, Duy Nhat; Le Thi, Hoai An; Dinh, Tao Pham
2017-11-01
This letter proposes a novel approach using the [Formula: see text]-norm regularization for the sparse covariance matrix estimation (SCME) problem. The objective function of SCME problem is composed of a nonconvex part and the [Formula: see text] term, which is discontinuous and difficult to tackle. Appropriate DC (difference of convex functions) approximations of [Formula: see text]-norm are used that result in approximation SCME problems that are still nonconvex. DC programming and DCA (DC algorithm), powerful tools in nonconvex programming framework, are investigated. Two DC formulations are proposed and corresponding DCA schemes developed. Two applications of the SCME problem that are considered are classification via sparse quadratic discriminant analysis and portfolio optimization. A careful empirical experiment is performed through simulated and real data sets to study the performance of the proposed algorithms. Numerical results showed their efficiency and their superiority compared with seven state-of-the-art methods.
Sample size reduction in groundwater surveys via sparse data assimilation
Hussain, Z.
2013-04-01
In this paper, we focus on sparse signal recovery methods for data assimilation in groundwater models. The objective of this work is to exploit the commonly understood spatial sparsity in hydrodynamic models and thereby reduce the number of measurements to image a dynamic groundwater profile. To achieve this we employ a Bayesian compressive sensing framework that lets us adaptively select the next measurement to reduce the estimation error. An extension to the Bayesian compressive sensing framework is also proposed which incorporates the additional model information to estimate system states from even lesser measurements. Instead of using cumulative imaging-like measurements, such as those used in standard compressive sensing, we use sparse binary matrices. This choice of measurements can be interpreted as randomly sampling only a small subset of dug wells at each time step, instead of sampling the entire grid. Therefore, this framework offers groundwater surveyors a significant reduction in surveying effort without compromising the quality of the survey. © 2013 IEEE.
High Order Tensor Formulation for Convolutional Sparse Coding
Bibi, Adel Aamer
2017-12-25
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 independently. However, learning multidimensional dictionaries and sparse codes for the reconstruction of multi-dimensional data is very important, as it examines correlations among all the data jointly. This provides more capacity for the learned dictionaries to better reconstruct data. In this paper, we propose a generic and novel formulation for the CSC problem that can handle an arbitrary order tensor of data. Backed with experimental results, our proposed formulation can not only tackle applications that are not possible with standard CSC solvers, including colored video reconstruction (5D- tensors), but it also performs favorably in reconstruction with much fewer parameters as compared to naive extensions of standard CSC to multiple features/channels.
Sample size reduction in groundwater surveys via sparse data assimilation
Hussain, Z.; Muhammad, A.
2013-01-01
In this paper, we focus on sparse signal recovery methods for data assimilation in groundwater models. The objective of this work is to exploit the commonly understood spatial sparsity in hydrodynamic models and thereby reduce the number of measurements to image a dynamic groundwater profile. To achieve this we employ a Bayesian compressive sensing framework that lets us adaptively select the next measurement to reduce the estimation error. An extension to the Bayesian compressive sensing framework is also proposed which incorporates the additional model information to estimate system states from even lesser measurements. Instead of using cumulative imaging-like measurements, such as those used in standard compressive sensing, we use sparse binary matrices. This choice of measurements can be interpreted as randomly sampling only a small subset of dug wells at each time step, instead of sampling the entire grid. Therefore, this framework offers groundwater surveyors a significant reduction in surveying effort without compromising the quality of the survey. © 2013 IEEE.
Sparse logistic principal components analysis for binary data
Lee, Seokho
2010-09-01
We develop a new principal components analysis (PCA) type dimension reduction method for binary data. Different from the standard PCA which is defined on the observed data, the proposed PCA is defined on the logit transform of the success probabilities of the binary observations. Sparsity is introduced to the principal component (PC) loading vectors for enhanced interpretability and more stable extraction of the principal components. Our sparse PCA is formulated as solving an optimization problem 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 by application to a single nucleotide polymorphism data set and a simulation study. © Institute ol Mathematical Statistics, 2010.
Statistical mechanics of semi-supervised clustering in sparse graphs
International Nuclear Information System (INIS)
Ver Steeg, Greg; Galstyan, Aram; Allahverdyan, Armen E
2011-01-01
We theoretically study semi-supervised clustering in sparse graphs in the presence of pair-wise constraints on the cluster assignments of nodes. We focus on bi-cluster graphs and study the impact of semi-supervision for varying constraint density and overlap between the clusters. Recent results for unsupervised clustering in sparse graphs indicate that there is a critical ratio of within-cluster and between-cluster connectivities below which clusters cannot be recovered with better than random accuracy. The goal of this paper is to examine the impact of pair-wise constraints on the clustering accuracy. Our results suggest that the addition of constraints does not provide automatic improvement over the unsupervised case. When the density of the constraints is sufficiently small, their only impact is to shift the detection threshold while preserving the criticality. Conversely, if the density of (hard) constraints is above the percolation threshold, the criticality is suppressed and the detection threshold disappears
A sparse electromagnetic imaging scheme using nonlinear landweber iterations
Desmal, Abdulla
2015-10-26
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 the nonlinear forward scattering operator into a sequence of linear ill-posed operations (for example using the Born iterative method) and applying sparsity constraints to the linear minimization problem of each iteration through the use of L0/L1-norm penalty term (A. Desmal and H. Bagci, IEEE Trans. Antennas Propag, 7, 3878–3884, 2014, and IEEE Trans. Geosci. Remote Sens., 3, 532–536, 2015). It has been shown that these techniques produce more accurate and sharper images than their counterparts which solve a minimization problem constrained with smoothness promoting L2-norm penalty term. But these existing techniques are only applicable to investigation domains involving weak scatterers because the linearization process breaks down for high values of dielectric permittivity.
Semi-blind sparse image reconstruction with application to MRFM.
Park, Se Un; Dobigeon, Nicolas; Hero, Alfred O
2012-09-01
We propose a solution to the image deconvolution problem where the convolution kernel or point spread function (PSF) is assumed to be only partially known. Small perturbations generated from the model are exploited to produce a few principal components explaining the PSF uncertainty in a high-dimensional space. Unlike recent developments on blind deconvolution of natural images, we assume the image is sparse in the pixel basis, a natural sparsity arising in magnetic resonance force microscopy (MRFM). Our approach adopts a Bayesian Metropolis-within-Gibbs sampling framework. The performance of our Bayesian semi-blind algorithm for sparse images is superior to previously proposed semi-blind algorithms such as the alternating minimization algorithm and blind algorithms developed for natural images. We illustrate our myopic algorithm on real MRFM tobacco virus data.
Sparse data structure design for wavelet-based methods
Directory of Open Access Journals (Sweden)
Latu Guillaume
2011-12-01
Full Text Available This course gives an introduction to the design of efficient datatypes for adaptive wavelet-based applications. It presents some code fragments and benchmark technics useful to learn about the design of sparse data structures and adaptive algorithms. Material and practical examples are given, and they provide good introduction for anyone involved in the development of adaptive applications. An answer will be given to the question: how to implement and efficiently use the discrete wavelet transform in computer applications? A focus will be made on time-evolution problems, and use of wavelet-based scheme for adaptively solving partial differential equations (PDE. One crucial issue is that the benefits of the adaptive method in term of algorithmic cost reduction can not be wasted by overheads associated to sparse data management.
Split-Bregman-based sparse-view CT reconstruction
Energy Technology Data Exchange (ETDEWEB)
Vandeghinste, Bert; Vandenberghe, Stefaan [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Goossens, Bart; Pizurica, Aleksandra; Philips, Wilfried [Ghent Univ. (Belgium). Image Processing and Interpretation Research Group (IPI); Beenhouwer, Jan de [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Antwerp Univ., Wilrijk (Belgium). The Vision Lab; Staelens, Steven [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Antwerp Univ., Edegem (Belgium). Molecular Imaging Centre Antwerp
2011-07-01
Total variation minimization has been extensively researched for image denoising and sparse view reconstruction. These methods show superior denoising performance for simple images with little texture, but result in texture information loss when applied to more complex images. It could thus be beneficial to use other regularizers within medical imaging. We propose a general regularization method, based on a split-Bregman approach. We show results for this framework combined with a total variation denoising operator, in comparison to ASD-POCS. We show that sparse-view reconstruction and noise regularization is possible. This general method will allow us to investigate other regularizers in the context of regularized CT reconstruction, and decrease the acquisition times in {mu}CT. (orig.)
Sparse canonical correlation analysis: new formulation and algorithm.
Chu, Delin; Liao, Li-Zhi; Ng, Michael K; Zhang, Xiaowei
2013-12-01
In this paper, we study canonical correlation analysis (CCA), which is a powerful tool in multivariate data analysis for finding the correlation between two sets of multidimensional variables. The main contributions of the paper are: 1) to reveal the equivalent relationship between a recursive formula and a trace formula for the multiple CCA problem, 2) to obtain the explicit characterization for all solutions of the multiple CCA problem even when the corresponding covariance matrices are singular, 3) to develop a new sparse CCA algorithm, and 4) to establish the equivalent relationship between the uncorrelated linear discriminant analysis and the CCA problem. We test several simulated and real-world datasets in gene classification and cross-language document retrieval to demonstrate the effectiveness of the proposed algorithm. The performance of the proposed method is competitive with the state-of-the-art sparse CCA algorithms.
Sparse Nonlinear Electromagnetic Imaging Accelerated With Projected Steepest Descent Algorithm
Desmal, Abdulla
2017-04-03
An efficient electromagnetic inversion scheme for imaging sparse 3-D domains is proposed. The scheme achieves its efficiency and accuracy by integrating two concepts. First, the nonlinear optimization problem is constrained using L₀ or L₁-norm of the solution as the penalty term to alleviate the ill-posedness of the inverse problem. The resulting Tikhonov minimization problem is solved using nonlinear Landweber iterations (NLW). Second, the efficiency of the NLW is significantly increased using a steepest descent algorithm. The algorithm uses a projection operator to enforce the sparsity constraint by thresholding the solution at every iteration. Thresholding level and iteration step are selected carefully to increase the efficiency without sacrificing the convergence of the algorithm. Numerical results demonstrate the efficiency and accuracy of the proposed imaging scheme in reconstructing sparse 3-D dielectric profiles.
Multi scales based sparse matrix spectral clustering image segmentation
Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin
2018-04-01
In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.
Nonredundant sparse feature extraction using autoencoders with receptive fields clustering.
Ayinde, Babajide O; Zurada, Jacek M
2017-09-01
This paper proposes new techniques for data representation in the context of deep learning using agglomerative clustering. Existing autoencoder-based data representation techniques tend to produce a number of encoding and decoding receptive fields of layered autoencoders that are duplicative, thereby leading to extraction of similar features, thus resulting in filtering redundancy. We propose a way to address this problem and show that such redundancy can be eliminated. This yields smaller networks and produces unique receptive fields that extract distinct features. It is also shown that autoencoders with nonnegativity constraints on weights are capable of extracting fewer redundant features than conventional sparse autoencoders. The concept is illustrated using conventional sparse autoencoder and nonnegativity-constrained autoencoders with MNIST digits recognition, NORB normalized-uniform object data and Yale face dataset. Copyright © 2017 Elsevier Ltd. All rights reserved.
Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse Recovery
Kim, Daeun; Haldar, Justin P.
2016-01-01
This work proposes a family of greedy algorithms to jointly reconstruct a set of vectors that are (i) nonnegative and (ii) simultaneously sparse with a shared support set. The proposed algorithms generalize previous approaches that were designed to impose these constraints individually. Similar to previous greedy algorithms for sparse recovery, the proposed algorithms iteratively identify promising support indices. In contrast to previous approaches, the support index selection procedure has been adapted to prioritize indices that are consistent with both the nonnegativity and shared support constraints. Empirical results demonstrate for the first time that the combined use of simultaneous sparsity and nonnegativity constraints can substantially improve recovery performance relative to existing greedy algorithms that impose less signal structure. PMID:26973368
The Process of Hydraulic Fracturing
Hydraulic fracturing, know as fracking or hydrofracking, produces fractures in a rock formation by pumping fluids (water, proppant, and chemical additives) at high pressure down a wellbore. These fractures stimulate the flow of natural gas or oil.
Limited-memory trust-region methods for sparse relaxation
Adhikari, Lasith; DeGuchy, Omar; Erway, Jennifer B.; Lockhart, Shelby; Marcia, Roummel F.
2017-08-01
In this paper, we solve the l2-l1 sparse recovery problem by transforming the objective function of this problem into an unconstrained differentiable function and applying a limited-memory trust-region method. Unlike gradient projection-type methods, which uses only the current gradient, our approach uses gradients from previous iterations to obtain a more accurate Hessian approximation. Numerical experiments show that our proposed approach eliminates spurious solutions more effectively while improving computational time.
Obtaining sparse distributions in 2D inverse problems
Reci, A; Sederman, Andrew John; Gladden, Lynn Faith
2017-01-01
The mathematics of inverse problems has relevance across numerous estimation problems in science and engineering. L1 regularization has attracted recent attention in reconstructing the system properties in the case of sparse inverse problems; i.e., when the true property sought is not adequately described by a continuous distribution, in particular in Compressed Sensing image reconstruction. In this work, we focus on the application of L1 regularization to a class of inverse problems; relaxat...
Sparse optimization for inverse problems in atmospheric modelling
Czech Academy of Sciences Publication Activity Database
Adam, Lukáš; Branda, Martin
2016-01-01
Roč. 79, č. 3 (2016), s. 256-266 ISSN 1364-8152 R&D Projects: GA MŠk(CZ) 7F14287 Institutional support: RVO:67985556 Keywords : Inverse modelling * Sparse optimization * Integer optimization * Least squares * European tracer experiment * Free Matlab codes Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.404, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/adam-0457037.pdf
Example-Based Image Colorization Using Locality Consistent Sparse Representation.
Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L
2017-11-01
Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.
Reliability of Broadcast Communications Under Sparse Random Linear Network Coding
Brown, Suzie; Johnson, Oliver; Tassi, Andrea
2018-01-01
Ultra-reliable Point-to-Multipoint (PtM) communications are expected to become pivotal in networks offering future dependable services for smart cities. In this regard, sparse Random Linear Network Coding (RLNC) techniques have been widely employed to provide an efficient way to improve the reliability of broadcast and multicast data streams. This paper addresses the pressing concern of providing a tight approximation to the probability of a user recovering a data stream protected by this kin...
Efficient Pseudorecursive Evaluation Schemes for Non-adaptive Sparse Grids
Buse, Gerrit
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 grids, both with and without boundary grid points. Similar to the implicit data structures proposed in Feuersänger (Dünngitterverfahren für hochdimensionale elliptische partielle Differntialgleichungen. Diploma Thesis, Institut für Numerische Simulation, Universität Bonn, 2005) and Murarasu et al. (Proceedings of the 16th ACM Symposium on Principles and Practice of Parallel Programming. Cambridge University Press, New York, 2011, pp. 25–34) we also define a bijective mapping from the multi-dimensional space of grid points to a contiguous index, such that the grid data can be stored in a simple array without overhead. Our approach is especially well-suited to exploit all levels of current commodity hardware, including cache-levels and vector extensions. Furthermore, this kind of data structure is extremely attractive for today’s real-time applications, as it gives direct access to the hierarchical structure of the grids, while outperforming other common sparse grid structures (hash maps, etc.) which do not match with modern compute platforms that well. For dimensionality d ≤ 10 we achieve good speedups on a 12 core Intel Westmere-EP NUMA platform compared to the results presented in Murarasu et al. (Proceedings of the International Conference on Computational Science—ICCS 2012. Procedia Computer Science, 2012). As we show, this also holds for the results obtained on Nvidia Fermi GPUs, for which we observe speedups over our own CPU implementation of up to 4.5 when dealing with moderate dimensionality. In high-dimensional settings, in the order of tens to hundreds of dimensions, our sparse grid evaluation kernels on the CPU outperform any other known implementation.
Iterative algorithms for large sparse linear systems on parallel computers
Adams, L. M.
1982-01-01
Algorithms for assembling in parallel the sparse system of linear equations that result from finite difference or finite element discretizations of elliptic partial differential equations, such as those that arise in structural engineering are developed. Parallel linear stationary iterative algorithms and parallel preconditioned conjugate gradient algorithms are developed for solving these systems. In addition, a model for comparing parallel algorithms on array architectures is developed and results of this model for the algorithms are given.
Distributed coding of multiview sparse sources with joint recovery
DEFF Research Database (Denmark)
Luong, Huynh Van; Deligiannis, Nikos; Forchhammer, Søren
2016-01-01
In support of applications involving multiview sources in distributed object recognition using lightweight cameras, we propose a new method for the distributed coding of sparse sources as visual descriptor histograms extracted from multiview images. The problem is challenging due to the computati...... transform (SIFT) descriptors extracted from multiview images shows that our method leads to bit-rate saving of up to 43% compared to the state-of-the-art distributed compressed sensing method with independent encoding of the sources....
Optimal deep neural networks for sparse recovery via Laplace techniques
Limmer, Steffen; Stanczak, Slawomir
2017-01-01
This paper introduces Laplace techniques for designing a neural network, with the goal of estimating simplex-constraint sparse vectors from compressed measurements. To this end, we recast the problem of MMSE estimation (w.r.t. a pre-defined uniform input distribution) as the problem of computing the centroid of some polytope that results from the intersection of the simplex and an affine subspace determined by the measurements. Owing to the specific structure, it is shown that the centroid ca...
Shape prior modeling using sparse representation and online dictionary learning.
Zhang, Shaoting; Zhan, Yiqiang; Zhou, Yan; Uzunbas, Mustafa; Metaxas, Dimitris N
2012-01-01
The recently proposed sparse shape composition (SSC) opens a new avenue for shape prior modeling. Instead of assuming any parametric model of shape statistics, SSC incorporates shape priors on-the-fly by approximating a shape instance (usually derived from appearance cues) by a sparse combination of shapes in a training repository. Theoretically, one can increase the modeling capability of SSC by including as many training shapes in the repository. However, this strategy confronts two limitations in practice. First, since SSC involves an iterative sparse optimization at run-time, the more shape instances contained in the repository, the less run-time efficiency SSC has. Therefore, a compact and informative shape dictionary is preferred to a large shape repository. Second, in medical imaging applications, training shapes seldom come in one batch. It is very time consuming and sometimes infeasible to reconstruct the shape dictionary every time new training shapes appear. In this paper, we propose an online learning method to address these two limitations. Our method starts from constructing an initial shape dictionary using the K-SVD algorithm. When new training shapes come, instead of re-constructing the dictionary from the ground up, we update the existing one using a block-coordinates descent approach. Using the dynamically updated dictionary, sparse shape composition can be gracefully scaled up to model shape priors from a large number of training shapes without sacrificing run-time efficiency. Our method is validated on lung localization in X-Ray and cardiac segmentation in MRI time series. Compared to the original SSC, it shows comparable performance while being significantly more efficient.
Color normalization of histology slides using graph regularized sparse NMF
Sha, Lingdao; Schonfeld, Dan; Sethi, Amit
2017-03-01
Computer based automatic medical image processing and quantification are becoming popular in digital pathology. However, preparation of histology slides can vary widely due to differences in staining equipment, procedures and reagents, which can reduce the accuracy of algorithms that analyze their color and texture information. To re- duce the unwanted color variations, various supervised and unsupervised color normalization methods have been proposed. Compared with supervised color normalization methods, unsupervised color normalization methods have advantages of time and cost efficient and universal applicability. Most of the unsupervised color normaliza- tion methods for histology are based on stain separation. Based on the fact that stain concentration cannot be negative and different parts of the tissue absorb different stains, nonnegative matrix factorization (NMF), and particular its sparse version (SNMF), are good candidates for stain separation. However, most of the existing unsupervised color normalization method like PCA, ICA, NMF and SNMF fail to consider important information about sparse manifolds that its pixels occupy, which could potentially result in loss of texture information during color normalization. Manifold learning methods like Graph Laplacian have proven to be very effective in interpreting high-dimensional data. In this paper, we propose a novel unsupervised stain separation method called graph regularized sparse nonnegative matrix factorization (GSNMF). By considering the sparse prior of stain concentration together with manifold information from high-dimensional image data, our method shows better performance in stain color deconvolution than existing unsupervised color deconvolution methods, especially in keeping connected texture information. To utilized the texture information, we construct a nearest neighbor graph between pixels within a spatial area of an image based on their distances using heat kernal in lαβ space. The
Review of Draft Crystalline Repository Project reports [sited on Indian reservation]: Final report
International Nuclear Information System (INIS)
Thorson, R.M.
1988-01-01
The Mashantucket Pequot Tribal Council was concerned about the possible emplacement of a nuclear waste repository in the crystalline rocks of Eastern Connecticut and Rhode Island. The Tribe was especially concerned with the hydrological problems because the Tribe's lands occur in an area with all of the complications cited above, including one of the highest concentrations of large brittle-fractures in southern New England. We questioned whether the intermediate and(or) regional groundwater systems might intersect the Cedar Swamp - a major groundwater discharge point at the junction of the Mesozoic brittle fractures and the Honey Hill Thrust. If the Cedar Swamp intersected the regional groundwater flow system, and if the groundwater flows were substantial (i.e., 5% of total flow during dry periods), the regional contribution to the surface discharge might possibly be measurable from surface data. 4 refs., 12 figs
Fracture toughness of glass sealants for solid oxide fuel cell application
DEFF Research Database (Denmark)
Abdoli, Hamid; Alizadeh, Parvin; Boccaccini, Dino
2014-01-01
-opening displacements in the near regions of a crack tip. Both approaches exhibited good agreement. La-containing glass showed higher stiffness, hardness and fracture toughness, which has been related to the in-situ toughening mechanism caused by devitrification and formation of crystalline phases. © 2013 Elsevier B.V....
[Trochanteric femoral fractures].
Douša, P; Čech, O; Weissinger, M; Džupa, V
2013-01-01
At the present time proximal femoral fractures account for 30% of all fractures referred to hospitals for treatment. Our population is ageing, the proportion of patients with post-menopausal or senile osteoporosis is increasing and therefore the number of proximal femoral fractures requiring urgent treatment is growing too. In the age category of 50 years and older, the incidence of these fractures has increased exponentially. Our department serves as a trauma centre for half of Prague and part of the Central Bohemia Region with a population of 1 150 000. Prague in particular has a high number of elderly citizens. Our experience is based on extensive clinical data obtained from the Register of Proximal Femoral Fractures established in 1997. During 14 years, 4280 patients, 3112 women and 1168 men, were admitted to our department for treatment of proximal femoral fractures. All patients were followed up until healing or development of complications. In the group under study, 82% were patients older than 70 years; 72% of those requiring surgery were in their seventies and eighties. Men were significantly younger than women (pfractures were 2.3-times more frequent in women than in men. In the category under 60 years, men significantly outnumbered women (pfractures were, on the average, eight years older than the patients with intertrochanteric fractures, which is a significant difference (pTrochanteric fractures accounted for 54.7% and femoral neck fractures for 45.3% of all fractures. The inter-annual increase was 5.9%, with more trochanteric than femoral neck fractures. There was a non-significant decrease in intertrochanteric (AO 31-A3) fractures. On the other hand, the number of pertrochanteric (AO 31-A1+2) fractures increased significantly (pfractures were treated with a proximal femoral nail; a short nail was used in 1260 and a long nail in 134 of them. A dynamic hip screw (DHS) was employed to treat 947 fractures. Distinguishing between pertrochanteric (21-A1
Used fuel disposition in crystalline rocks
Energy Technology Data Exchange (ETDEWEB)
Wang, Y. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hadgu, Teklu [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kalinina, Elena Arkadievna [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jerden, James L. [Argonne National Lab. (ANL), Argonne, IL (United States); Copple, Jacqueline M. [Argonne National Lab. (ANL), Argonne, IL (United States); Cruse, T. [Argonne National Lab. (ANL), Argonne, IL (United States); Ebert, W. [Argonne National Lab. (ANL), Argonne, IL (United States); Buck, E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Eittman, R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Tinnacher, R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Tournassat, Christophe. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Davis, J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Viswanathan, H. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chu, S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dittrich, T. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hyman, F. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Karra, S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Makedonska, N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reimus, P. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Zavarin, Mavrik [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Joseph, C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2016-09-01
The U.S. Department of Energy Office of Nuclear Energy, Office of Fuel Cycle Technology established the Used Fuel Disposition Campaign (UFDC) in fiscal year 2010 (FY10) to conduct the research and development (R&D) activities related to storage, transportation and disposal of used nuclear fuel and high level nuclear waste. The objective of the Crystalline Disposal R&D Work Package is to advance our understanding of long-term disposal of used fuel in crystalline rocks and to develop necessary experimental and computational capabilities to evaluate various disposal concepts in such media.
Irradiation induced crystalline to amorphous transition
International Nuclear Information System (INIS)
Bourgoin, J.
1980-01-01
Irradiation of a crystalline solid with energetic heavy particles results in cascades of defects which, with increasing dose, overlap and form a continuous disordered layer. In semiconductors the physical properties of such disordered layers are found to be similar to those of amorphous layers produced by evaporation. It is shown in the case of silicon, that the transition from a disordered crystalline (X) layer to an amorphous (α) layer occurs when the Gibbs energy of the X phase and of the defects it contains becomes larger than the Gibbs energy of the α phase. (author)
Electronic processes in non-crystalline materials
Mott, Nevill Francis
2012-01-01
Since the first edition of this highly successful book the field saw many great developments both in experimental and theoretical studies of electrical properties of non-crystalline solids. It became necessary to rewrite nearly the whole book, while the aims of the second edition remained the same: to set out the theoretical concepts, to test them by comparison with experiment for a wide variety of phenomena, and to apply them to non-crystalline materials. Sir Nevill Mott shared the1977 Nobel Prize for Physics, awarded for his research work in this field. The reissue of this book as part of th
Dentate Gyrus circuitry features improve performance of sparse approximation algorithms.
Directory of Open Access Journals (Sweden)
Panagiotis C Petrantonakis
Full Text Available Memory-related activity in the Dentate Gyrus (DG is characterized by sparsity. Memory representations are seen as activated neuronal populations of granule cells, the main encoding cells in DG, which are estimated to engage 2-4% of the total population. This sparsity is assumed to enhance the ability of DG to perform pattern separation, one of the most valuable contributions of DG during memory formation. In this work, we investigate how features of the DG such as its excitatory and inhibitory connectivity diagram can be used to develop theoretical algorithms performing Sparse Approximation, a widely used strategy in the Signal Processing field. Sparse approximation stands for the algorithmic identification of few components from a dictionary that approximate a certain signal. The ability of DG to achieve pattern separation by sparsifing its representations is exploited here to improve the performance of the state of the art sparse approximation algorithm "Iterative Soft Thresholding" (IST by adding new algorithmic features inspired by the DG circuitry. Lateral inhibition of granule cells, either direct or indirect, via mossy cells, is shown to enhance the performance of the IST. Apart from revealing the potential of DG-inspired theoretical algorithms, this work presents new insights regarding the function of particular cell types in the pattern separation task of the DG.