A General Algorithm for Reusing Krylov Subspace Information. I. Unsteady Navier-Stokes
Carpenter, Mark H.; Vuik, C.; Lucas, Peter; vanGijzen, Martin; Bijl, Hester
2010-01-01
A general algorithm is developed that reuses available information to accelerate the iterative convergence of linear systems with multiple right-hand sides A x = b (sup i), which are commonly encountered in steady or unsteady simulations of nonlinear equations. The algorithm is based on the classical GMRES algorithm with eigenvector enrichment but also includes a Galerkin projection preprocessing step and several novel Krylov subspace reuse strategies. The new approach is applied to a set of test problems, including an unsteady turbulent airfoil, and is shown in some cases to provide significant improvement in computational efficiency relative to baseline approaches.
Matrix Krylov subspace methods for image restoration
Directory of Open Access Journals (Sweden)
khalide jbilou
2015-09-01
Full Text Available In the present paper, we consider some matrix Krylov subspace methods for solving ill-posed linear matrix equations and in those problems coming from the restoration of blurred and noisy images. Applying the well known Tikhonov regularization procedure leads to a Sylvester matrix equation depending the Tikhonov regularized parameter. We apply the matrix versions of the well known Krylov subspace methods, namely the Least Squared (LSQR and the conjugate gradient (CG methods to get approximate solutions representing the restored images. Some numerical tests are presented to show the effectiveness of the proposed methods.
On the numerical stability analysis of pipelined Krylov subspace methods
Czech Academy of Sciences Publication Activity Database
Carson, E.T.; Rozložník, Miroslav; Strakoš, Z.; Tichý, P.; Tůma, M.
submitted 2017 (2018) R&D Projects: GA ČR GA13-06684S Grant - others:GA MŠk(CZ) LL1202 Institutional support: RVO:67985807 Keywords : Krylov subspace methods * the conjugate gradient method * numerical stability * inexact computations * delay of convergence * maximal attainable accuracy * pipelined Krylov subspace methods * exascale computations
Reduced-Rank Adaptive Filtering Using Krylov Subspace
Directory of Open Access Journals (Sweden)
Sergueï Burykh
2003-01-01
Full Text Available A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions of linear systems. The alternative interpretation so obtained is used to study the properties of each considered technique and to relate one reduced-rank method to another as well as to algorithms used in computational linear algebra. Practical issues are discussed and low-complexity versions are also included in our study. It is believed that the insight developed in this paper can be further used to improve existing reduced-rank methods according to known results in the domain of Krylov subspace methods.
An adaptation of Krylov subspace methods to path following
Energy Technology Data Exchange (ETDEWEB)
Walker, H.F. [Utah State Univ., Logan, UT (United States)
1996-12-31
Krylov subspace methods at present constitute a very well known and highly developed class of iterative linear algebra methods. These have been effectively applied to nonlinear system solving through Newton-Krylov methods, in which Krylov subspace methods are used to solve the linear systems that characterize steps of Newton`s method (the Newton equations). Here, we will discuss the application of Krylov subspace methods to path following problems, in which the object is to track a solution curve as a parameter varies. Path following methods are typically of predictor-corrector form, in which a point near the solution curve is {open_quotes}predicted{close_quotes} by some easy but relatively inaccurate means, and then a series of Newton-like corrector iterations is used to return approximately to the curve. The analogue of the Newton equation is underdetermined, and an additional linear condition must be specified to determine corrector steps uniquely. This is typically done by requiring that the steps be orthogonal to an approximate tangent direction. Augmenting the under-determined system with this orthogonality condition in a straightforward way typically works well if direct linear algebra methods are used, but Krylov subspace methods are often ineffective with this approach. We will discuss recent work in which this orthogonality condition is imposed directly as a constraint on the corrector steps in a certain way. The means of doing this preserves problem conditioning, allows the use of preconditioners constructed for the fixed-parameter case, and has certain other advantages. Experiments on standard PDE continuation test problems indicate that this approach is effective.
Krylov subspace methods for solving large unsymmetric linear systems
International Nuclear Information System (INIS)
Saad, Y.
1981-01-01
Some algorithms based upon a projection process onto the Krylov subspace K/sub m/ = Span(r 0 , Ar 0 ,...,A/sup m/-1r 0 ) are developed, generalizing the method of conjugate gradients to unsymmetric systems. These methods are extensions of Arnoldi's algorithm for solving eigenvalue problems. The convergence is analyzed in terms of the distance of the solution to the subspace K/sub m/ and some error bounds are established showing, in particular, a similarity with the conjugate gradient method (for symmetric matrices) when the eigenvalues are real. Several numerical experiments are described and discussed
International Nuclear Information System (INIS)
Ikuno, Soichiro; Chen, Gong; Yamamoto, Susumu; Itoh, Taku; Abe, Kuniyoshi; Nakamura, Hiroaki
2016-01-01
Krylov subspace method and the variable preconditioned Krylov subspace method with communication avoiding technique for a linear system obtained from electromagnetic analysis are numerically investigated. In the k−skip Krylov method, the inner product calculations are expanded by Krylov basis, and the inner product calculations are transformed to the scholar operations. k−skip CG method is applied for the inner-loop solver of Variable Preconditioned Krylov subspace methods, and the converged solution of electromagnetic problem is obtained using the method. (author)
2017-09-27
100 times larger for the minimal Krylov subspace. 0 5 10 15 20 25 Krylov subspace dimension 10-2 10-1 100 101 102 103 104 jjĜ ¡ 1 jj F SVD...approximation Kn (G;u(0) ) 0 5 10 15 20 25 Krylov subspace dimension 10-2 10-1 100 101 102 103 104 jjx jj fo r m in x jjĜ x ¡ bjj SVD approximation Kn (G;u(0
A Krylov Subspace Method for Unstructured Mesh SN Transport Computation
International Nuclear Information System (INIS)
Yoo, Han Jong; Cho, Nam Zin; Kim, Jong Woon; Hong, Ser Gi; Lee, Young Ouk
2010-01-01
Hong, et al., have developed a computer code MUST (Multi-group Unstructured geometry S N Transport) for the neutral particle transport calculations in three-dimensional unstructured geometry. In this code, the discrete ordinates transport equation is solved by using the discontinuous finite element method (DFEM) or the subcell balance methods with linear discontinuous expansion. In this paper, the conventional source iteration in the MUST code is replaced by the Krylov subspace method to reduce computing time and the numerical test results are given
Bochev, Mikhail A.; Oseledets, I.V.; Tyrtyshnikov, E.E.
2013-01-01
The aim of this paper is two-fold. First, we propose an efficient implementation of the continuous time waveform relaxation method based on block Krylov subspaces. Second, we compare this new implementation against Krylov subspace methods combined with the shift and invert technique.
Parallelised Krylov subspace method for reactor kinetics by IQS approach
International Nuclear Information System (INIS)
Gupta, Anurag; Modak, R.S.; Gupta, H.P.; Kumar, Vinod; Bhatt, K.
2005-01-01
Nuclear reactor kinetics involves numerical solution of space-time-dependent multi-group neutron diffusion equation. Two distinct approaches exist for this purpose: the direct (implicit time differencing) approach and the improved quasi-static (IQS) approach. Both the approaches need solution of static space-energy-dependent diffusion equations at successive time-steps; the step being relatively smaller for the direct approach. These solutions are usually obtained by Gauss-Seidel type iterative methods. For a faster solution, the Krylov sub-space methods have been tried and also parallelised by many investigators. However, these studies seem to have been done only for the direct approach. In the present paper, parallelised Krylov methods are applied to the IQS approach in addition to the direct approach. It is shown that the speed-up obtained for IQS is higher than that for the direct approach. The reasons for this are also discussed. Thus, the use of IQS approach along with parallelised Krylov solvers seems to be a promising scheme
Reverse time migration by Krylov subspace reduced order modeling
Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali
2018-04-01
Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.
Domain decomposed preconditioners with Krylov subspace methods as subdomain solvers
Energy Technology Data Exchange (ETDEWEB)
Pernice, M. [Univ. of Utah, Salt Lake City, UT (United States)
1994-12-31
Domain decomposed preconditioners for nonsymmetric partial differential equations typically require the solution of problems on the subdomains. Most implementations employ exact solvers to obtain these solutions. Consequently work and storage requirements for the subdomain problems grow rapidly with the size of the subdomain problems. Subdomain solves constitute the single largest computational cost of a domain decomposed preconditioner, and improving the efficiency of this phase of the computation will have a significant impact on the performance of the overall method. The small local memory available on the nodes of most message-passing multicomputers motivates consideration of the use of an iterative method for solving subdomain problems. For large-scale systems of equations that are derived from three-dimensional problems, memory considerations alone may dictate the need for using iterative methods for the subdomain problems. In addition to reduced storage requirements, use of an iterative solver on the subdomains allows flexibility in specifying the accuracy of the subdomain solutions. Substantial savings in solution time is possible if the quality of the domain decomposed preconditioner is not degraded too much by relaxing the accuracy of the subdomain solutions. While some work in this direction has been conducted for symmetric problems, similar studies for nonsymmetric problems appear not to have been pursued. This work represents a first step in this direction, and explores the effectiveness of performing subdomain solves using several transpose-free Krylov subspace methods, GMRES, transpose-free QMR, CGS, and a smoothed version of CGS. Depending on the difficulty of the subdomain problem and the convergence tolerance used, a reduction in solution time is possible in addition to the reduced memory requirements. The domain decomposed preconditioner is a Schur complement method in which the interface operators are approximated using interface probing.
Krylov subspace methods for the solution of large systems of ODE's
DEFF Research Database (Denmark)
Thomsen, Per Grove; Bjurstrøm, Nils Henrik
1998-01-01
In Air Pollution Modelling large systems of ODE's arise. Solving such systems may be done efficientliy by Semi Implicit Runge-Kutta methods. The internal stages may be solved using Krylov subspace methods. The efficiency of this approach is investigated and verified.......In Air Pollution Modelling large systems of ODE's arise. Solving such systems may be done efficientliy by Semi Implicit Runge-Kutta methods. The internal stages may be solved using Krylov subspace methods. The efficiency of this approach is investigated and verified....
Energy Technology Data Exchange (ETDEWEB)
Druskin, V.; Lee, Ping [Schlumberger-Doll Research, Ridgefield, CT (United States); Knizhnerman, L. [Central Geophysical Expedition, Moscow (Russian Federation)
1996-12-31
There is now a growing interest in the area of using Krylov subspace approximations to compute the actions of matrix functions. The main application of this approach is the solution of ODE systems, obtained after discretization of partial differential equations by method of lines. In the event that the cost of computing the matrix inverse is relatively inexpensive, it is sometimes attractive to solve the ODE using the extended Krylov subspaces, originated by actions of both positive and negative matrix powers. Examples of such problems can be found frequently in computational electromagnetics.
A block Krylov subspace time-exact solution method for linear ordinary differential equation systems
Bochev, Mikhail A.
2013-01-01
We propose a time-exact Krylov-subspace-based method for solving linear ordinary differential equation systems of the form $y'=-Ay+g(t)$ and $y"=-Ay+g(t)$, where $y(t)$ is the unknown function. The method consists of two stages. The first stage is an accurate piecewise polynomial approximation of
International Nuclear Information System (INIS)
Yamamoto, Akio; Tatsumi, Masahiro; Sugimura, Naoki
2007-01-01
The Krylov subspace method is applied to solve nuclide burnup equations used for lattice physics calculations. The Krylov method is an efficient approach for solving ordinary differential equations with stiff nature such as the nuclide burnup with short lived nuclides. Some mathematical fundamentals of the Krylov subspace method and its application to burnup equations are discussed. Verification calculations are carried out in a PWR pin-cell geometry with UO 2 fuel. A detailed burnup chain that includes 193 fission products and 28 heavy nuclides is used in the verification calculations. Shortest half life found in the present burnup chain is approximately 30 s ( 106 Rh). Therefore, conventional methods (e.g., the Taylor series expansion with scaling and squaring) tend to require longer computation time due to numerical stiffness. Comparison with other numerical methods (e.g., the 4-th order Runge-Kutta-Gill) reveals that the Krylov subspace method can provide accurate solution for a detailed burnup chain used in the present study with short computation time. (author)
Krylov subspace method for evaluating the self-energy matrices in electron transport calculations
DEFF Research Database (Denmark)
Sørensen, Hans Henrik Brandenborg; Hansen, Per Christian; Petersen, D. E.
2008-01-01
We present a Krylov subspace method for evaluating the self-energy matrices used in the Green's function formulation of electron transport in nanoscale devices. A procedure based on the Arnoldi method is employed to obtain solutions of the quadratic eigenvalue problem associated with the infinite...... calculations. Numerical tests within a density functional theory framework are provided to validate the accuracy and robustness of the proposed method, which in most cases is an order of magnitude faster than conventional methods.......We present a Krylov subspace method for evaluating the self-energy matrices used in the Green's function formulation of electron transport in nanoscale devices. A procedure based on the Arnoldi method is employed to obtain solutions of the quadratic eigenvalue problem associated with the infinite...
Residual and Backward Error Bounds in Minimum Residual Krylov Subspace Methods
Czech Academy of Sciences Publication Activity Database
Paige, C. C.; Strakoš, Zdeněk
2002-01-01
Roč. 23, č. 6 (2002), s. 1899-1924 ISSN 1064-8275 R&D Projects: GA AV ČR IAA1030103 Institutional research plan: AV0Z1030915 Keywords : linear equations * eigenproblem * large sparse matrices * iterative solutions * Krylov subspace methods * Arnoldi method * GMRES * modified Gram-Schmidt * least squares * total least squares * singular values Subject RIV: BA - General Mathematics Impact factor: 1.291, year: 2002
Czech Academy of Sciences Publication Activity Database
Liesen, J.; Strakoš, Zdeněk
2008-01-01
Roč. 50, č. 3 (2008), s. 485-503 ISSN 0036-1445 R&D Projects: GA AV ČR 1ET400300415; GA AV ČR IAA100300802 Institutional research plan: CEZ:AV0Z10300504 Keywords : Krylov subspace methods * orthogonal bases * short reccurences * conjugate gradient -like methods Subject RIV: IN - Informatics, Computer Science Impact factor: 2.739, year: 2008
Krylov Subspace Methods for Complex Non-Hermitian Linear Systems. Thesis
Freund, Roland W.
1991-01-01
We consider Krylov subspace methods for the solution of large sparse linear systems Ax = b with complex non-Hermitian coefficient matrices. Such linear systems arise in important applications, such as inverse scattering, numerical solution of time-dependent Schrodinger equations, underwater acoustics, eddy current computations, numerical computations in quantum chromodynamics, and numerical conformal mapping. Typically, the resulting coefficient matrices A exhibit special structures, such as complex symmetry, or they are shifted Hermitian matrices. In this paper, we first describe a Krylov subspace approach with iterates defined by a quasi-minimal residual property, the QMR method, for solving general complex non-Hermitian linear systems. Then, we study special Krylov subspace methods designed for the two families of complex symmetric respectively shifted Hermitian linear systems. We also include some results concerning the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.
s-Step Krylov Subspace Methods as Bottom Solvers for Geometric Multigrid
Energy Technology Data Exchange (ETDEWEB)
Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Lijewski, Mike [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Almgren, Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Straalen, Brian Van [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Carson, Erin [Univ. of California, Berkeley, CA (United States); Knight, Nicholas [Univ. of California, Berkeley, CA (United States); Demmel, James [Univ. of California, Berkeley, CA (United States)
2014-08-14
Geometric multigrid solvers within adaptive mesh refinement (AMR) applications often reach a point where further coarsening of the grid becomes impractical as individual sub domain sizes approach unity. At this point the most common solution is to use a bottom solver, such as BiCGStab, to reduce the residual by a fixed factor at the coarsest level. Each iteration of BiCGStab requires multiple global reductions (MPI collectives). As the number of BiCGStab iterations required for convergence grows with problem size, and the time for each collective operation increases with machine scale, bottom solves in large-scale applications can constitute a significant fraction of the overall multigrid solve time. In this paper, we implement, evaluate, and optimize a communication-avoiding s-step formulation of BiCGStab (CABiCGStab for short) as a high-performance, distributed-memory bottom solver for geometric multigrid solvers. This is the first time s-step Krylov subspace methods have been leveraged to improve multigrid bottom solver performance. We use a synthetic benchmark for detailed analysis and integrate the best implementation into BoxLib in order to evaluate the benefit of a s-step Krylov subspace method on the multigrid solves found in the applications LMC and Nyx on up to 32,768 cores on the Cray XE6 at NERSC. Overall, we see bottom solver improvements of up to 4.2x on synthetic problems and up to 2.7x in real applications. This results in as much as a 1.5x improvement in solver performance in real applications.
An efficient preconditioning technique using Krylov subspace methods for 3D characteristics solvers
International Nuclear Information System (INIS)
Dahmani, M.; Le Tellier, R.; Roy, R.; Hebert, A.
2005-01-01
The Generalized Minimal RESidual (GMRES) method, using a Krylov subspace projection, is adapted and implemented to accelerate a 3D iterative transport solver based on the characteristics method. Another acceleration technique called the self-collision rebalancing technique (SCR) can also be used to accelerate the solution or as a left preconditioner for GMRES. The GMRES method is usually used to solve a linear algebraic system (Ax=b). It uses K(r (o) ,A) as projection subspace and AK(r (o) ,A) for the orthogonalization of the residual. This paper compares the performance of these two combined methods on various problems. To implement the GMRES iterative method, the characteristics equations are derived in linear algebra formalism by using the equivalence between the method of characteristics and the method of collision probability to end up with a linear algebraic system involving fluxes and currents. Numerical results show good performance of the GMRES technique especially for the cases presenting large material heterogeneity with a scattering ratio close to 1. Similarly, the SCR preconditioning slightly increases the GMRES efficiency
Development of a Burnup Module DECBURN Based on the Krylov Subspace Method
Energy Technology Data Exchange (ETDEWEB)
Cho, J. Y.; Kim, K. S.; Shim, H. J.; Song, J. S
2008-05-15
This report is to develop a burnup module DECBURN that is essential for the reactor analysis and the assembly homogenization codes to trace the fuel composition change during the core burnup. The developed burnup module solves the burnup equation by the matrix exponential method based on the Krylov Subspace method. The final solution of the matrix exponential is obtained by the matrix scaling and squaring method. To develop DECBURN module, this report includes the followings as: (1) Krylov Subspace Method for Burnup Equation, (2) Manufacturing of the DECBURN module, (3) Library Structure Setup and Library Manufacturing, (4) Examination of the DECBURN module, (5) Implementation to the DeCART code and Verification. DECBURN library includes the decay constants, one-group cross section and the fission yields. Examination of the DECBURN module is performed by manufacturing a driver program, and the results of the DECBURN module is compared with those of the ORIGEN program. Also, the implemented DECBURN module to the DeCART code is applied to the LWR depletion benchmark and a OPR-1000 pin cell problem, and the solutions are compared with the HELIOS code to verify the computational soundness and accuracy. In this process, the criticality calculation method and the predictor-corrector scheme are introduced to the DeCART code for a function of the homogenization code. The examination by a driver program shows that the DECBURN module produces exactly the same solution with the ORIGEN program. DeCART code that equips the DECBURN module produces a compatible solution to the other codes for the LWR depletion benchmark. Also the multiplication factors of the DeCART code for the OPR-1000 pin cell problem agree to the HELIOS code within 100 pcm over the whole burnup steps. The multiplication factors with the criticality calculation are also compatible with the HELIOS code. These results mean that the developed DECBURN module works soundly and produces an accurate solution
An acceleration technique for 2D MOC based on Krylov subspace and domain decomposition methods
International Nuclear Information System (INIS)
Zhang Hongbo; Wu Hongchun; Cao Liangzhi
2011-01-01
Highlights: → We convert MOC into linear system solved by GMRES as an acceleration method. → We use domain decomposition method to overcome the inefficiency on large matrices. → Parallel technology is applied and a matched ray tracing system is developed. → Results show good efficiency even in large-scale and strong scattering problems. → The emphasis is that the technique is geometry-flexible. - Abstract: The method of characteristics (MOC) has great geometrical flexibility but poor computational efficiency in neutron transport calculations. The generalized minimal residual (GMRES) method, a type of Krylov subspace method, is utilized to accelerate a 2D generalized geometry characteristics solver AutoMOC. In this technique, a form of linear algebraic equation system for angular flux moments and boundary fluxes is derived to replace the conventional characteristics sweep (i.e. inner iteration) scheme, and then the GMRES method is implemented as an efficient linear system solver. This acceleration method is proved to be reliable in theory and simple for implementation. Furthermore, as introducing no restriction in geometry treatment, it is suitable for acceleration of an arbitrary geometry MOC solver. However, it is observed that the speedup decreases when the matrix becomes larger. The spatial domain decomposition method and multiprocessing parallel technology are then employed to overcome the problem. The calculation domain is partitioned into several sub-domains. For each of them, a smaller matrix is established and solved by GMRES; and the adjacent sub-domains are coupled by 'inner-edges', where the trajectory mismatches are considered adequately. Moreover, a matched ray tracing system is developed on the basis of AutoCAD, which allows a user to define the sub-domains on demand conveniently. Numerical results demonstrate that the acceleration techniques are efficient without loss of accuracy, even in the case of large-scale and strong scattering
Energy Technology Data Exchange (ETDEWEB)
Koenig, Michael [Institut fuer Theoretische Festkoerperphysik, Universitaet Karlsruhe (Germany); Karlsruhe School of Optics and Photonics (KSOP), Universitaet Karlsruhe (Germany); Niegemann, Jens; Tkeshelashvili, Lasha; Busch, Kurt [Institut fuer Theoretische Festkoerperphysik, Universitaet Karlsruhe (Germany); DFG Forschungszentrum Center for Functional Nanostructures (CFN), Universitaet Karlsruhe (Germany); Karlsruhe School of Optics and Photonics (KSOP), Universitaet Karlsruhe (Germany)
2008-07-01
Numerical simulations of metallic nano-structures are crucial for the efficient design of plasmonic devices. Conventional time-domain solvers such as FDTD introduce large numerical errors especially at metallic surfaces. Our approach combines a discontinuous Galerkin method on an adaptive mesh for the spatial discretisation with a Krylov-subspace technique for the time-stepping procedure. Thus, the higher-order accuracy in both time and space is supported by unconditional stability. As illustrative examples, we compare numerical results obtained with our method against analytical reference solutions and results from FDTD calculations.
Numerical simulations of microwave heating of liquids: enhancements using Krylov subspace methods
Lollchund, M. R.; Dookhitram, K.; Sunhaloo, M. S.; Boojhawon, R.
2013-04-01
In this paper, we compare the performances of three iterative solvers for large sparse linear systems arising in the numerical computations of incompressible Navier-Stokes (NS) equations. These equations are employed mainly in the simulation of microwave heating of liquids. The emphasis of this work is on the application of Krylov projection techniques such as Generalized Minimal Residual (GMRES) to solve the Pressure Poisson Equations that result from discretisation of the NS equations. The performance of the GMRES method is compared with the traditional Gauss-Seidel (GS) and point successive over relaxation (PSOR) techniques through their application to simulate the dynamics of water housed inside a vertical cylindrical vessel which is subjected to microwave radiation. It is found that as the mesh size increases, GMRES gives the fastest convergence rate in terms of computational times and number of iterations.
Numerical simulations of microwave heating of liquids: enhancements using Krylov subspace methods
International Nuclear Information System (INIS)
Lollchund, M R; Dookhitram, K; Sunhaloo, M S; Boojhawon, R
2013-01-01
In this paper, we compare the performances of three iterative solvers for large sparse linear systems arising in the numerical computations of incompressible Navier-Stokes (NS) equations. These equations are employed mainly in the simulation of microwave heating of liquids. The emphasis of this work is on the application of Krylov projection techniques such as Generalized Minimal Residual (GMRES) to solve the Pressure Poisson Equations that result from discretisation of the NS equations. The performance of the GMRES method is compared with the traditional Gauss-Seidel (GS) and point successive over relaxation (PSOR) techniques through their application to simulate the dynamics of water housed inside a vertical cylindrical vessel which is subjected to microwave radiation. It is found that as the mesh size increases, GMRES gives the fastest convergence rate in terms of computational times and number of iterations.
Energy Technology Data Exchange (ETDEWEB)
de la Torre Vega, E. [Instituto de Investigaciones Electricas, Cuernavaca (Mexico); Cesar Suarez Arriaga, M. [Universidad Michoacana SNH, Michoacan (Mexico)
1995-03-01
In geothermal simulation processes, MULKOM uses Integrated Finite Differences to solve the corresponding partial differential equations. This method requires to resolve efficiently big linear dispersed systems of non-symmetrical nature on each temporal iteration. The order of the system is usually greater than one thousand its solution could represent around 80% of CPU total calculation time. If the elapsed time solving this class of linear systems is reduced, the duration of numerical simulation decreases notably. When the matrix is big (N{ge}500) and with holes, it is inefficient to handle all the system`s elements, because it is perfectly figured out by its elements distinct of zero, quantity greatly minor than N{sup 2}. In this area, iteration methods introduce advantages with respect to gaussian elimination methods, because these last replenish matrices not having any special distribution of their non-zero elements and because they do not make use of the available solution estimations. The iterating methods of the Conjugated Gradient family, based on the subspaces of Krylov, possess the advantage of improving the convergence speed by means of preconditioning techniques. The creation of DIOMRES(k,m) method guarantees the continuous descent of the residual norm, without incurring in division by zero. This technique converges at most in N iterations if the system`s matrix is symmetrical, it does not employ too much memory to converge and updates immediately the approximation by using incomplete orthogonalization and adequate restarting. A preconditioned version of DIOMRES was applied to problems related to unsymmetrical systems with 1000 unknowns and less than five terms per equation. We found that this technique could reduce notably the time needful to find the solution without requiring memory increment. The coupling of this method to geothermal versions of MULKOM is in process.
LBAS: Lanczos Bidiagonalization with Subspace Augmentation for Discrete Inverse Problems
DEFF Research Database (Denmark)
Hansen, Per Christian; Abe, Kyniyoshi
The regularizing properties of Lanczos bidiagonalization are powerful when the underlying Krylov subspace captures the dominating components of the solution. In some applications the regularized solution can be further improved by augmenting the Krylov subspace with a low-dimensional subspace tha...
Krylov subspace acceleration of waveform relaxation
Energy Technology Data Exchange (ETDEWEB)
Lumsdaine, A.; Wu, Deyun [Univ. of Notre Dame, IN (United States)
1996-12-31
Standard solution methods for numerically solving time-dependent problems typically begin by discretizing the problem on a uniform time grid and then sequentially solving for successive time points. The initial time discretization imposes a serialization to the solution process and limits parallel speedup to the speedup available from parallelizing the problem at any given time point. This bottleneck can be circumvented by the use of waveform methods in which multiple time-points of the different components of the solution are computed independently. With the waveform approach, a problem is first spatially decomposed and distributed among the processors of a parallel machine. Each processor then solves its own time-dependent subsystem over the entire interval of interest using previous iterates from other processors as inputs. Synchronization and communication between processors take place infrequently, and communication consists of large packets of information - discretized functions of time (i.e., waveforms).
Preconditioned Krylov subspace methods for eigenvalue problems
Energy Technology Data Exchange (ETDEWEB)
Wu, Kesheng; Saad, Y.; Stathopoulos, A. [Univ. of Minnesota, Minneapolis, MN (United States)
1996-12-31
Lanczos algorithm is a commonly used method for finding a few extreme eigenvalues of symmetric matrices. It is effective if the wanted eigenvalues have large relative separations. If separations are small, several alternatives are often used, including the shift-invert Lanczos method, the preconditioned Lanczos method, and Davidson method. The shift-invert Lanczos method requires direct factorization of the matrix, which is often impractical if the matrix is large. In these cases preconditioned schemes are preferred. Many applications require solution of hundreds or thousands of eigenvalues of large sparse matrices, which pose serious challenges for both iterative eigenvalue solver and preconditioner. In this paper we will explore several preconditioned eigenvalue solvers and identify the ones suited for finding large number of eigenvalues. Methods discussed in this paper make up the core of a preconditioned eigenvalue toolkit under construction.
Bisetti, Fabrizio
2012-01-01
with the computational cost associated with the time integration of stiff, large chemical systems, a novel approach is proposed. The approach combines an exponential integrator and Krylov subspace approximations to the exponential function of the Jacobian matrix
Radjavi, Heydar
2003-01-01
This broad survey spans a wealth of studies on invariant subspaces, focusing on operators on separable Hilbert space. Largely self-contained, it requires only a working knowledge of measure theory, complex analysis, and elementary functional analysis. Subjects include normal operators, analytic functions of operators, shift operators, examples of invariant subspace lattices, compact operators, and the existence of invariant and hyperinvariant subspaces. Additional chapters cover certain results on von Neumann algebras, transitive operator algebras, algebras associated with invariant subspaces,
International Nuclear Information System (INIS)
Hindmarsh, A.C.; Petzold, L.R.
2005-01-01
1 - Description of program or function: LSODKR is a new initial value ODE solver for stiff and non-stiff systems. It is a variant of the LSODPK and LSODE solvers, intended mainly for large stiff systems. The main differences between LSODKR and LSODE are the following: a) for stiff systems, LSODKR uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods. The user must supply routines for the preconditioning operations, b) within the corrector iteration, LSODKR does automatic switching between functional (fix point) iteration and modified Newton iteration, The nonlinear iteration method-switching differs from the method-switching in LSODA and LSODAR, but provides similar savings by using the cheaper method in the non-stiff regions of the problem. c) LSODKR includes the ability to find roots of given functions of the solution during the integration. d) LSODKR also improves on the Krylov methods in LSODPK by offering the option to save and reuse the approximate Jacobian data underlying the pre-conditioner. The LSODKR source is commented extensively to facilitate modification. Both a single-precision version and a double-precision version are available. 2 - Methods: It is assumed that the ODEs are given explicitly, so that the system can be written in the form dy/dt = f(t,y), where y is the vector of dependent variables, and t is the independent variable. Integration is by Adams or BDF (Backward Differentiation Formula) methods, at user option. Corrector iteration is by Newton or fix point iteration, determined dynamically. Linear system solution is by a preconditioned Krylov iteration, selected by user from Incomplete Orthogonalization Method, Generalized Minimum Residual Method, and two variants of Preconditioned Conjugate Gradient Method. Preconditioning is to be supplied by the user
KRYSI, Ordinary Differential Equations Solver with Sdirk Krylov Method
International Nuclear Information System (INIS)
Hindmarsh, A.C.; Norsett, S.P.
2001-01-01
1 - Description of program or function: KRYSI is a set of FORTRAN subroutines for solving ordinary differential equations initial value problems. It is suitable for both stiff and non-stiff systems. When solving the implicit stage equations in the stiff case, KRYSI uses a Krylov subspace iteration method called the SPIGMR (Scaled Preconditioned Incomplete Generalized Minimum Residual) method. No explicit Jacobian storage is required, except where used in pre- conditioning. A demonstration problem is included with a description of two pre-conditioners that are natural for its solution by KRYSI. 2 - Method of solution: KRYSI uses a three-stage, third-order singly diagonally implicit Runge-Kutta (SDIRK) method. In the stiff case, a preconditioned Krylov subspace iteration within a (so-called) inexact Newton iteration is used to solve the system of nonlinear algebraic equations
Krylov Subspace Methods for Saddle Point Problems with Indefinite Preconditioning
Czech Academy of Sciences Publication Activity Database
Rozložník, Miroslav; Simoncini, V.
2002-01-01
Roč. 24, č. 2 (2002), s. 368-391 ISSN 0895-4798 R&D Projects: GA ČR GA101/00/1035; GA ČR GA201/00/0080 Institutional research plan: AV0Z1030915 Keywords : saddle point problems * preconditioning * indefinite linear systems * finite precision arithmetic * conjugate gradients Subject RIV: BA - General Mathematics Impact factor: 0.753, year: 2002
KIOPS: A fast adaptive Krylov subspace solver for exponential integrators
Gaudreault, Stéphane; Rainwater, Greg; Tokman, Mayya
2018-01-01
This paper presents a new algorithm KIOPS for computing linear combinations of $\\varphi$-functions that appear in exponential integrators. This algorithm is suitable for large-scale problems in computational physics where little or no information about the spectrum or norm of the Jacobian matrix is known \\textit{a priori}. We first show that such problems can be solved efficiently by computing a single exponential of a modified matrix. Then our approach is to compute an appropriate basis for ...
Iterative solution of linear equations in ODE codes. [Krylov subspaces
Energy Technology Data Exchange (ETDEWEB)
Gear, C. W.; Saad, Y.
1981-01-01
Each integration step of a stiff equation involves the solution of a nonlinear equation, usually by a quasi-Newton method that leads to a set of linear problems. Iterative methods for these linear equations are studied. Of particular interest are methods that do not require an explicit Jacobian, but can work directly with differences of function values using J congruent to f(x + delta) - f(x). Some numerical experiments using a modification of LSODE are reported. 1 figure, 2 tables.
Lattice QCD computations: Recent progress with modern Krylov subspace methods
Energy Technology Data Exchange (ETDEWEB)
Frommer, A. [Bergische Universitaet GH Wuppertal (Germany)
1996-12-31
Quantum chromodynamics (QCD) is the fundamental theory of the strong interaction of matter. In order to compare the theory with results from experimental physics, the theory has to be reformulated as a discrete problem of lattice gauge theory using stochastic simulations. The computational challenge consists in solving several hundreds of very large linear systems with several right hand sides. A considerable part of the world`s supercomputer time is spent in such QCD calculations. This paper presents results on solving systems for the Wilson fermions. Recent progress is reviewed on algorithms obtained in cooperation with partners from theoretical physics.
Domain decomposition methods and deflated Krylov subspace iterations
Nabben, R.; Vuik, C.
2006-01-01
The balancing Neumann-Neumann (BNN) and the additive coarse grid correction (BPS) preconditioner are fast and successful preconditioners within domain decomposition methods for solving partial differential equations. For certain elliptic problems these preconditioners lead to condition numbers which
Energy Technology Data Exchange (ETDEWEB)
Starke, G. [Universitaet Karlsruhe (Germany)
1994-12-31
For nonselfadjoint elliptic boundary value problems which are preconditioned by a substructuring method, i.e., nonoverlapping domain decomposition, the author introduces and studies the concept of subspace orthogonalization. In subspace orthogonalization variants of Krylov methods the computation of inner products and vector updates, and the storage of basis elements is restricted to a (presumably small) subspace, in this case the edge and vertex unknowns with respect to the partitioning into subdomains. The author investigates subspace orthogonalization for two specific iterative algorithms, GMRES and the full orthogonalization method (FOM). This is intended to eliminate certain drawbacks of the Arnoldi-based Krylov subspace methods mentioned above. Above all, the length of the Arnoldi recurrences grows linearly with the iteration index which is therefore restricted to the number of basis elements that can be held in memory. Restarts become necessary and this often results in much slower convergence. The subspace orthogonalization methods, in contrast, require the storage of only the edge and vertex unknowns of each basis element which means that one can iterate much longer before restarts become necessary. Moreover, the computation of inner products is also restricted to the edge and vertex points which avoids the disturbance of the computational flow associated with the solution of subdomain problems. The author views subspace orthogonalization as an alternative to restarting or truncating Krylov subspace methods for nonsymmetric linear systems of equations. Instead of shortening the recurrences, one restricts them to a subset of the unknowns which has to be carefully chosen in order to be able to extend this partial solution to the entire space. The author discusses the convergence properties of these iteration schemes and its advantages compared to restarted or truncated versions of Krylov methods applied to the full preconditioned system.
2016-09-01
We consider the problem of subspace clustering: given points that lie on or near the union of many low-dimensional linear subspaces, recover the subspaces. To this end, one first identifies sets of points close to the same subspace and uses the sets ...
Conformal mapping and convergence of Krylov iterations
Energy Technology Data Exchange (ETDEWEB)
Driscoll, T.A.; Trefethen, L.N. [Cornell Univ., Ithaca, NY (United States)
1994-12-31
Connections between conformal mapping and matrix iterations have been known for many years. The idea underlying these connections is as follows. Suppose the spectrum of a matrix or operator A is contained in a Jordan region E in the complex plane with 0 not an element of E. Let {phi}(z) denote a conformal map of the exterior of E onto the exterior of the unit disk, with {phi}{infinity} = {infinity}. Then 1/{vert_bar}{phi}(0){vert_bar} is an upper bound for the optimal asymptotic convergence factor of any Krylov subspace iteration. This idea can be made precise in various ways, depending on the matrix iterations, on whether A is finite or infinite dimensional, and on what bounds are assumed on the non-normality of A. This paper explores these connections for a variety of matrix examples, making use of a new MATLAB Schwarz-Christoffel Mapping Toolbox developed by the first author. Unlike the earlier Fortran Schwarz-Christoffel package SCPACK, the new toolbox computes exterior as well as interior Schwarz-Christoffel maps, making it easy to experiment with spectra that are not necessarily symmetric about an axis.
DEFF Research Database (Denmark)
Müller, Emmanuel; Assent, Ira; Günnemann, Stephan
2009-01-01
Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace...... clusters. Their results are typically highly redundant, i.e. many clusters are detected multiple times in several projections. In this work, we propose a novel model for relevant subspace clustering (RESCU). We present a global optimization which detects the most interesting non-redundant subspace clusters...... achieves top clustering quality while competing approaches show greatly varying performance....
DEFF Research Database (Denmark)
Müller, Emmanuel; Assent, Ira; Günnemann, Stephan
2009-01-01
Subspace clustering and projected clustering are recent research areas for clustering in high dimensional spaces. As the field is rather young, there is a lack of comparative studies on the advantages and disadvantages of the different algorithms. Part of the underlying problem is the lack...... of available open source implementations that could be used by researchers to understand, compare, and extend subspace and projected clustering algorithms. In this paper, we discuss the requirements for open source evaluation software. We propose OpenSubspace, an open source framework that meets...... these requirements. OpenSubspace integrates state-of-the-art performance measures and visualization techniques to foster research in subspace and projected clustering....
Bisetti, Fabrizio
2012-06-01
Recent trends in hydrocarbon fuel research indicate that the number of species and reactions in chemical kinetic mechanisms is rapidly increasing in an effort to provide predictive capabilities for fuels of practical interest. In order to cope with the computational cost associated with the time integration of stiff, large chemical systems, a novel approach is proposed. The approach combines an exponential integrator and Krylov subspace approximations to the exponential function of the Jacobian matrix. The components of the approach are described in detail and applied to the ignition of stoichiometric methane-air and iso-octane-air mixtures, here described by two widely adopted chemical kinetic mechanisms. The approach is found to be robust even at relatively large time steps and the global error displays a nominal third-order convergence. The performance of the approach is improved by utilising an adaptive algorithm for the selection of the Krylov subspace size, which guarantees an approximation to the matrix exponential within user-defined error tolerance. The Krylov projection of the Jacobian matrix onto a low-dimensional space is interpreted as a local model reduction with a well-defined error control strategy. Finally, the performance of the approach is discussed with regard to the optimal selection of the parameters governing the accuracy of its individual components. © 2012 Copyright Taylor and Francis Group, LLC.
Investigating Multi-Array Antenna Signal Convergence using Wavelet Transform and Krylov Sequence
Directory of Open Access Journals (Sweden)
Muhammad Ahmed Sikander
2018-01-01
Full Text Available In the present world, wireless communication is becoming immensely popular for plethora of applications. Technology has been advancing at an accelerated rate leading to make communication reliable. Still, there are issues need to be address to minimize errors in the transmission. This research study expounds on the rapid convergence of the signal. Convergence is considered to be an important aspect in wireless communication. For rapid convergence, two ambiguities should be addressed; Eigenvalue spread and sparse identification or sparsity of the signal. Eigen value spread is defining as the ratio of minimum to maximum Eigenvalue, whereas sparsity is defining as the loosely bounded system. In this research, two of these attributes are investigated for MAA (Multi-Array Antenna signal using the cascading of Wavelet and Krylov processes. Specifically, the MAA signal is applied in the research because nowadays there are many physical hindrances in the communication path. These hurdles weaken the signal strength which in turn effects the quality of the reception. WT (Wavelet Transform is used to address the Eigenvalue problem and the Krylov sequence is used to attempt the sparse identification of the MAA signal. The results show that the convergence of the MMA signal is improved by applying Wavelet transform and Krylov Subspace.
Investigating multi-array antenna signal convergence using wavelet transform and krylov sequence
International Nuclear Information System (INIS)
Sikander, M.A.; Hussain, R.; Hussain, R.
2018-01-01
In the present world, wireless communication is becoming immensely popular for plethora of applications. Technology has been advancing at an accelerated rate leading to make communication reliable. Still, there are issues need to be address to minimize errors in the transmission. This research study expounds on the rapid convergence of the signal. Convergence is considered to be an important aspect in wireless communication. For rapid convergence, two ambiguities should be addressed; Eigenvalue spread and sparse identification or sparsity of the signal. Eigen value spread is defining as the ratio of minimum to maximum Eigenvalue, whereas sparsity is defining as the loosely bounded system. In this research, two of these attributes are investigated for MAA (Multi-Array Antenna) signal using the cascading of Wavelet and Krylov processes. Specifically, the MAA signal is applied in the research because nowadays there are many physical hindrances in the communication path. These hurdles weaken the signal strength which in turn effects the quality of the reception. WT (Wavelet Transform) is used to address the Eigenvalue problem and the Krylov sequence is used to attempt the sparse identification of the MAA signal. The results show that the convergence of the MMA signal is improved by applying Wavelet transform and Krylov Subspace. (author)
Efficient solution of parabolic equations by Krylov approximation methods
Gallopoulos, E.; Saad, Y.
1990-01-01
Numerical techniques for solving parabolic equations by the method of lines is addressed. The main motivation for the proposed approach is the possibility of exploiting a high degree of parallelism in a simple manner. The basic idea of the method is to approximate the action of the evolution operator on a given state vector by means of a projection process onto a Krylov subspace. Thus, the resulting approximation consists of applying an evolution operator of a very small dimension to a known vector which is, in turn, computed accurately by exploiting well-known rational approximations to the exponential. Because the rational approximation is only applied to a small matrix, the only operations required with the original large matrix are matrix-by-vector multiplications, and as a result the algorithm can easily be parallelized and vectorized. Some relevant approximation and stability issues are discussed. We present some numerical experiments with the method and compare its performance with a few explicit and implicit algorithms.
Energy Technology Data Exchange (ETDEWEB)
Aliaga, José I., E-mail: aliaga@uji.es [Depto. Ingeniería y Ciencia de Computadores, Universitat Jaume I, Castellón (Spain); Alonso, Pedro [Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València (Spain); Badía, José M. [Depto. Ingeniería y Ciencia de Computadores, Universitat Jaume I, Castellón (Spain); Chacón, Pablo [Dept. Biological Chemical Physics, Rocasolano Physics and Chemistry Institute, CSIC, Madrid (Spain); Davidović, Davor [Rudjer Bošković Institute, Centar za Informatiku i Računarstvo – CIR, Zagreb (Croatia); López-Blanco, José R. [Dept. Biological Chemical Physics, Rocasolano Physics and Chemistry Institute, CSIC, Madrid (Spain); Quintana-Ortí, Enrique S. [Depto. Ingeniería y Ciencia de Computadores, Universitat Jaume I, Castellón (Spain)
2016-03-15
We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator (GPU). The method consists of two stages, with the original problem first reduced into a simpler band-structured form by means of a high-performance compute-intensive procedure. This is followed by a memory-intensive but low-cost Krylov iteration, which is off-loaded to be computed on the GPU by means of an efficient data-parallel kernel. The experimental results reveal the performance of the new eigensolver. Concretely, when applied to the simulation of macromolecules with a few thousands degrees of freedom and the number of eigenpairs to be computed is small to moderate, the new solver outperforms other methods implemented as part of high-performance numerical linear algebra packages for multithreaded architectures.
International Nuclear Information System (INIS)
Aliaga, José I.; Alonso, Pedro; Badía, José M.; Chacón, Pablo; Davidović, Davor; López-Blanco, José R.; Quintana-Ortí, Enrique S.
2016-01-01
We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator (GPU). The method consists of two stages, with the original problem first reduced into a simpler band-structured form by means of a high-performance compute-intensive procedure. This is followed by a memory-intensive but low-cost Krylov iteration, which is off-loaded to be computed on the GPU by means of an efficient data-parallel kernel. The experimental results reveal the performance of the new eigensolver. Concretely, when applied to the simulation of macromolecules with a few thousands degrees of freedom and the number of eigenpairs to be computed is small to moderate, the new solver outperforms other methods implemented as part of high-performance numerical linear algebra packages for multithreaded architectures.
On Covering Approximation Subspaces
Directory of Open Access Journals (Sweden)
Xun Ge
2009-06-01
Full Text Available Let (U';C' be a subspace of a covering approximation space (U;C and X⊂U'. In this paper, we show that and B'(X⊂B(X∩U'. Also, iff (U;C has Property Multiplication. Furthermore, some connections between outer (resp. inner definable subsets in (U;C and outer (resp. inner definable subsets in (U';C' are established. These results answer a question on covering approximation subspace posed by J. Li, and are helpful to obtain further applications of Pawlak rough set theory in pattern recognition and artificial intelligence.
Semitransitive subspaces of operators
Czech Academy of Sciences Publication Activity Database
Bernik, J.; Drnovšek, R.; Hadwin, D.; Jafarian, A.; Bukovšek, D.K.; Košir, T.; Fijavž, M.K.; Laffey, T.; Livshits, L.; Mastnak, M.; Meshulam, R.; Müller, Vladimír; Nordgren, E.; Okniński, J.; Omladič, M.; Radjavi, H.; Sourour, A.; Timoney, R.
2006-01-01
Roč. 15, č. 1 (2006), s. 225-238 E-ISSN 1081-3810 Institutional research plan: CEZ:AV0Z10190503 Keywords : semitransitive subspaces Subject RIV: BA - General Mathematics Impact factor: 0.322, year: 2006 http://www.math.technion.ac.il/iic/ ela
Portable, parallel, reusable Krylov space codes
Energy Technology Data Exchange (ETDEWEB)
Smith, B.; Gropp, W. [Argonne National Lab., IL (United States)
1994-12-31
Krylov space accelerators are an important component of many algorithms for the iterative solution of linear systems. Each Krylov space method has it`s own particular advantages and disadvantages, therefore it is desirable to have a variety of them available all with an identical, easy to use, interface. A common complaint application programmers have with available software libraries for the iterative solution of linear systems is that they require the programmer to use the data structures provided by the library. The library is not able to work with the data structures of the application code. Hence, application programmers find themselves constantly recoding the Krlov space algorithms. The Krylov space package (KSP) is a data-structure-neutral implementation of a variety of Krylov space methods including preconditioned conjugate gradient, GMRES, BiCG-Stab, transpose free QMR and CGS. Unlike all other software libraries for linear systems that the authors are aware of, KSP will work with any application codes data structures, in Fortran or C. Due to it`s data-structure-neutral design KSP runs unchanged on both sequential and parallel machines. KSP has been tested on workstations, the Intel i860 and Paragon, Thinking Machines CM-5 and the IBM SP1.
Newton-Krylov-Schwarz methods in unstructured grid Euler flow
Energy Technology Data Exchange (ETDEWEB)
Keyes, D.E. [Old Dominion Univ., Norfolk, VA (United States)
1996-12-31
Newton-Krylov methods and Krylov-Schwarz (domain decomposition) methods have begun to become established in computational fluid dynamics (CFD) over the past decade. The former employ a Krylov method inside of Newton`s method in a Jacobian-free manner, through directional differencing. The latter employ an overlapping Schwarz domain decomposition to derive a preconditioner for the Krylov accelerator that relies primarily on local information, for data-parallel concurrency. They may be composed as Newton-Krylov-Schwarz (NKS) methods, which seem particularly well suited for solving nonlinear elliptic systems in high-latency, distributed-memory environments. We give a brief description of this family of algorithms, with an emphasis on domain decomposition iterative aspects. We then describe numerical simulations with Newton-Krylov-Schwarz methods on an aerodynamic application emphasizing comparisons with a standard defect-correction approach and subdomain preconditioner consistency.
Krylov Techniques for 3D Problems in Transport Theory
International Nuclear Information System (INIS)
Ruben Panta Pazos
2006-01-01
When solving integral-differential equations by means of numerical methods one has to deal with large systems of linear equations, such as happens in transport theory [10]. Many iterative techniques are now used in Transport Theory in order to solve problems of 2D and 3D dimensions. In this paper, we choose two problems to solve the following transport equation, [Equation] where x: represents the spatial variable, μ: the cosine of the angle, ψ: the angular flux, h(x, μ): is the collision frequency, k(x, μ, μ'): the scattering kernel, q(x, μ): the source. The aim of this work is the straightforward application of the Krylov spaces technique [2] to the governing equation or to its discretizations derived of the discrete ordinates method (choosing a finite number of directions and then approximating the integral term by means of a proper sum). The equation (1) can be written in functional form as [Equation] with ψ in the Hilbert space L 2 ([0,a] x [-1,1])., and q is the source function. The operator derived from a discrete ordinates scheme that approximates the operator [Equation] generates the following subspace [Equation] i.e. the subspace generated by the iterations of order 0, 1, 2,..., m-1 of the source function q. Two methods are specially outstanding, the Lanczos method to solve the problem given by equation (2) with certain boundary conditions, and the conjugate gradient method to solve the same problem with identical boundary conditions. We discuss and accelerate the basic iterative method [8]. An important conclusion is the generation of these methods to solve linear systems in Hilbert spaces, if verify the convergence conditions, which are outlined in this work. The first problem is a cubic domain with two regions, one with a source near the vertex at the origin and the shield region. In this case, the Cartesian planes (specifically 0 < x < L, 0 < y < L, 0 < z < L) are reflexive boundaries and the rest faces of the cube are vacuum boundaries. The
Nonlinear Krylov acceleration of reacting flow codes
Energy Technology Data Exchange (ETDEWEB)
Kumar, S.; Rawat, R.; Smith, P.; Pernice, M. [Univ. of Utah, Salt Lake City, UT (United States)
1996-12-31
We are working on computational simulations of three-dimensional reactive flows in applications encompassing a broad range of chemical engineering problems. Examples of such processes are coal (pulverized and fluidized bed) and gas combustion, petroleum processing (cracking), and metallurgical operations such as smelting. These simulations involve an interplay of various physical and chemical factors such as fluid dynamics with turbulence, convective and radiative heat transfer, multiphase effects such as fluid-particle and particle-particle interactions, and chemical reaction. The governing equations resulting from modeling these processes are highly nonlinear and strongly coupled, thereby rendering their solution by traditional iterative methods (such as nonlinear line Gauss-Seidel methods) very difficult and sometimes impossible. Hence we are exploring the use of nonlinear Krylov techniques (such as CMRES and Bi-CGSTAB) to accelerate and stabilize the existing solver. This strategy allows us to take advantage of the problem-definition capabilities of the existing solver. The overall approach amounts to using the SIMPLE (Semi-Implicit Method for Pressure-Linked Equations) method and its variants as nonlinear preconditioners for the nonlinear Krylov method. We have also adapted a backtracking approach for inexact Newton methods to damp the Newton step in the nonlinear Krylov method. This will be a report on work in progress. Preliminary results with nonlinear GMRES have been very encouraging: in many cases the number of line Gauss-Seidel sweeps has been reduced by about a factor of 5, and increased robustness of the underlying solver has also been observed.
International Nuclear Information System (INIS)
Hindmarsh, A.D.; Brown, P.N.
1996-01-01
1 - Description of program or function: LSODKR is a new initial value ODE solver for stiff and non-stiff systems. It is a variant of the LSODPK and LSODE solvers, intended mainly for large stiff systems. The main differences between LSODKR and LSODE are the following: a) for stiff systems, LSODKR uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods. The user must supply routines for the preconditioning operations, b) within the corrector iteration, LSODKR does automatic switching between functional (fix point) iteration and modified Newton iteration, c) LSODKR includes the ability to find roots of given functions of the solution during the integration. 2 - Method of solution: Integration is by Adams or BDF (Backward Differentiation Formula) methods, at user option. Corrector iteration is by Newton or fix point iteration, determined dynamically. Linear system solution is by a preconditioned Krylov iteration, selected by user from Incomplete Orthogonalization Method, Generalized Minimum Residual Method, and two variants of Preconditioned Conjugate Gradient Method. Preconditioning is to be supplied by the user. 3 - Restrictions on the complexity of the problem: None
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Farouq, S.; Neytcheva, M.
2017-01-01
Roč. 74, č. 1 (2017), s. 19-37 ISSN 1017-1398 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution method s * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.241, year: 2016 https://link.springer.com/article/10.1007%2Fs11075-016-0136-5
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Farouq, S.; Neytcheva, M.
2017-01-01
Roč. 74, č. 1 (2017), s. 19-37 ISSN 1017-1398 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution methods * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.241, year: 2016 https://link.springer.com/article/10.1007%2Fs11075-016-0136-5
Krylov solvers for linear algebraic systems
Broyden, Charles George
2004-01-01
The first four chapters of this book give a comprehensive and unified theory of the Krylov methods. Many of these are shown to be particular examples ofthe block conjugate-gradient algorithm and it is this observation thatpermits the unification of the theory. The two major sub-classes of thosemethods, the Lanczos and the Hestenes-Stiefel, are developed in parallel asnatural generalisations of the Orthodir (GCR) and Orthomin algorithms. Theseare themselves based on Arnoldi's algorithm and a generalised Gram-Schmidtalgorithm and their properties, in particular their stability properties,are det
Timmerman, Marieke E; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla
2013-12-01
To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning approaches. To evaluate subspace K-means, we performed a comparative simulation study, in which we manipulated the overlap of subspaces, the between-cluster variance, and the error variance. The study shows that the subspace K-means algorithm is sensitive to local minima but that the problem can be reasonably dealt with by using partitions of various cluster procedures as a starting point for the algorithm. Subspace K-means performs very well in recovering the true clustering across all conditions considered and appears to be superior to its competitor methods: K-means, reduced K-means, factorial K-means, mixtures of factor analyzers (MFA), and MCLUST. The best competitor method, MFA, showed a performance similar to that of subspace K-means in easy conditions but deteriorated in more difficult ones. Using data from a study on parental behavior, we show that subspace K-means analysis provides a rich insight into the cluster characteristics, in terms of both the relative positions of the clusters (via the centroids) and the shape of the clusters (via the within-cluster residuals).
Random matrix improved subspace clustering
Couillet, Romain; Kammoun, Abla
2017-01-01
This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show
Geometric mean for subspace selection.
Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J
2009-02-01
Subspace selection approaches are powerful tools in pattern classification and data visualization. One of the most important subspace approaches is the linear dimensionality reduction step in the Fisher's linear discriminant analysis (FLDA), which has been successfully employed in many fields such as biometrics, bioinformatics, and multimedia information management. However, the linear dimensionality reduction step in FLDA has a critical drawback: for a classification task with c classes, if the dimension of the projected subspace is strictly lower than c - 1, the projection to a subspace tends to merge those classes, which are close together in the original feature space. If separate classes are sampled from Gaussian distributions, all with identical covariance matrices, then the linear dimensionality reduction step in FLDA maximizes the mean value of the Kullback-Leibler (KL) divergences between different classes. Based on this viewpoint, the geometric mean for subspace selection is studied in this paper. Three criteria are analyzed: 1) maximization of the geometric mean of the KL divergences, 2) maximization of the geometric mean of the normalized KL divergences, and 3) the combination of 1 and 2. Preliminary experimental results based on synthetic data, UCI Machine Learning Repository, and handwriting digits show that the third criterion is a potential discriminative subspace selection method, which significantly reduces the class separation problem in comparing with the linear dimensionality reduction step in FLDA and its several representative extensions.
Goals Recycling Green Purchasing Pollution Prevention Reusing Water Resources Environmental Management System Environmental Outreach Feature Stories Individual Permit for Storm Water Public Reading Room Sustainability Â» Reusing Water Reusing Water Millions of gallons of industrial wastewater is recycled at LANL by
Shape analysis with subspace symmetries
Berner, Alexander
2011-04-01
We address the problem of partial symmetry detection, i.e., the identification of building blocks a complex shape is composed of. Previous techniques identify parts that relate to each other by simple rigid mappings, similarity transforms, or, more recently, intrinsic isometries. Our approach generalizes the notion of partial symmetries to more general deformations. We introduce subspace symmetries whereby we characterize similarity by requiring the set of symmetric parts to form a low dimensional shape space. We present an algorithm to discover subspace symmetries based on detecting linearly correlated correspondences among graphs of invariant features. We evaluate our technique on various data sets. We show that for models with pronounced surface features, subspace symmetries can be found fully automatically. For complicated cases, a small amount of user input is used to resolve ambiguities. Our technique computes dense correspondences that can subsequently be used in various applications, such as model repair and denoising. © 2010 The Author(s).
Asgharzadeh, Hafez; Borazjani, Iman
2014-11-01
Time step-size restrictions and low convergence rates are major bottle necks for implicit solution of the Navier-Stokes in simulations involving complex geometries with moving boundaries. Newton-Krylov method (NKM) is a combination of a Newton-type method for super-linearly convergent solution of nonlinear equations and Krylov subspace methods for solving the Newton correction equations, which can theoretically address both bottle necks. The efficiency of this method vastly depends on the Jacobian forming scheme e.g. automatic differentiation is very expensive and Jacobian-free methods slow down as the mesh is refined. A novel, computationally efficient analytical Jacobian for NKM was developed to solve unsteady incompressible Navier-Stokes momentum equations on staggered curvilinear grids with immersed boundaries. The NKM was validated and verified against Taylor-Green vortex and pulsatile flow in a 90 degree bend and efficiently handles complex geometries such as an intracranial aneurysm with multiple overset grids, pulsatile inlet flow and immersed boundaries. The NKM method is shown to be more efficient than the semi-implicit Runge-Kutta methods and Jabobian-free Newton-Krylov methods. We believe NKM can be applied to many CFD techniques to decrease the computational cost. This work was supported partly by the NIH Grant R03EB014860, and the computational resources were partly provided by Center for Computational Research (CCR) at University at Buffalo.
Scalable Density-Based Subspace Clustering
DEFF Research Database (Denmark)
Müller, Emmanuel; Assent, Ira; Günnemann, Stephan
2011-01-01
For knowledge discovery in high dimensional databases, subspace clustering detects clusters in arbitrary subspace projections. Scalability is a crucial issue, as the number of possible projections is exponential in the number of dimensions. We propose a scalable density-based subspace clustering...... method that steers mining to few selected subspace clusters. Our novel steering technique reduces subspace processing by identifying and clustering promising subspaces and their combinations directly. Thereby, it narrows down the search space while maintaining accuracy. Thorough experiments on real...... and synthetic databases show that steering is efficient and scalable, with high quality results. For future work, our steering paradigm for density-based subspace clustering opens research potential for speeding up other subspace clustering approaches as well....
Timmerman, Marieke E.; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla
2013-01-01
To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the
Newton-Krylov methods applied to nonequilibrium radiation diffusion
International Nuclear Information System (INIS)
Knoll, D.A.; Rider, W.J.; Olsen, G.L.
1998-01-01
The authors present results of applying a matrix-free Newton-Krylov method to a nonequilibrium radiation diffusion problem. Here, there is no use of operator splitting, and Newton's method is used to convert the nonlinearities within a time step. Since the nonlinear residual is formed, it is used to monitor convergence. It is demonstrated that a simple Picard-based linearization produces a sufficient preconditioning matrix for the Krylov method, thus elevating the need to form or store a Jacobian matrix for Newton's method. They discuss the possibility that the Newton-Krylov approach may allow larger time steps, without loss of accuracy, as compared to an operator split approach where nonlinearities are not converged within a time step
Subspace preservation, subspace locality, and gluing of completely positive maps
International Nuclear Information System (INIS)
Aaberg, Johan
2004-01-01
Three concepts concerning completely positive maps (CPMs) and trace preserving CPMs (channels) are introduced and investigated. These are named subspace preserving (SP) CPMs, subspace local (SL) channels, and gluing of CPMs. SP CPMs has, in the case of trace preserving CPMs, a simple interpretation as those which preserve probability weights on a given orthogonal sum decomposition of the Hilbert space of a quantum system. The proposed definition of subspace locality of quantum channels is an attempt to answer the question of what kind of restriction should be put on a channel, if it is to act 'locally' with respect to two 'locations', when these naturally correspond to a separation of the total Hilbert space in an orthogonal sum of subspaces, rather than a tensor product decomposition. As a description of the concept of gluings of quantum channels, consider a pair of 'evolution machines', each with the ability to evolve the internal state of a 'particle' inserted into its input. Each of these machines is characterized by a channel describing the operation the internal state has experienced when the particle is returned at the output. Suppose a particle is put in a superposition between the input of the first and the second machine. Here it is shown that the total evolution caused by a pair of such devices is not uniquely determined by the channels of the two machines. Such 'global' channels describing the machine pair are examples of gluings of the two single machine channels. Various expressions to generate the set of SP and SL channels, as well as expressions to generate the set of gluings of given channels, are deduced. We discuss conceptual aspects of the nature of these channels and the nature of the non-uniqueness of gluings
Milan R. Radosavljević; Vanja M. Šušteršič
2013-01-01
Water scarcity and water pollution are some of the crucial issues that must be addressed within local and global perspectives. One of the ways to reduce the impact of water scarcity and to minimizine water pollution is to expand water and wastewater reuse. The local conditions including regulations, institutions, financial mechanisms, availability of local technology and stakeholder participation have a great influence on the decisions for wastewater reuse. The increasing awareness of food s...
Subspace Arrangement Codes and Cryptosystems
2011-05-09
Signature Date Acceptance for the Trident Scholar Committee Professor Carl E. Wick Associate Director of Midshipmen Research Signature Date SUBSPACE...Professor William Traves. I also thank Professor Carl Wick and the Trident Scholar Committee for providing me with the opportunity to conduct this... Sagan . Why the characteristic polynomial factors. Bulletin of the American Mathematical Society, 36(2):113–133, February 1999. [16] Karen E. Smith
Random matrix improved subspace clustering
Couillet, Romain
2017-03-06
This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based on vector channel observations in the context of massive MIMO wireless communication networks is provided.
Consistency Analysis of Nearest Subspace Classifier
Wang, Yi
2015-01-01
The Nearest subspace classifier (NSS) finds an estimation of the underlying subspace within each class and assigns data points to the class that corresponds to its nearest subspace. This paper mainly studies how well NSS can be generalized to new samples. It is proved that NSS is strongly consistent under certain assumptions. For completeness, NSS is evaluated through experiments on various simulated and real data sets, in comparison with some other linear model based classifiers. It is also ...
Controllable Subspaces of Open Quantum Dynamical Systems
International Nuclear Information System (INIS)
Zhang Ming; Gong Erling; Xie Hongwei; Hu Dewen; Dai Hongyi
2008-01-01
This paper discusses the concept of controllable subspace for open quantum dynamical systems. It is constructively demonstrated that combining structural features of decoherence-free subspaces with the ability to perform open-loop coherent control on open quantum systems will allow decoherence-free subspaces to be controllable. This is in contrast to the observation that open quantum dynamical systems are not open-loop controllable. To a certain extent, this paper gives an alternative control theoretical interpretation on why decoherence-free subspaces can be useful for quantum computation.
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...
External Evaluation Measures for Subspace Clustering
DEFF Research Database (Denmark)
Günnemann, Stephan; Färber, Ines; Müller, Emmanuel
2011-01-01
research area of subspace clustering. We formalize general quality criteria for subspace clustering measures not yet addressed in the literature. We compare the existing external evaluation methods based on these criteria and pinpoint limitations. We propose a novel external evaluation measure which meets...
Subspace exclusion zones for damage localization
DEFF Research Database (Denmark)
Bernal, Dionisio; Ulriksen, Martin Dalgaard
2018-01-01
, this is exploited in the context of structural damage localization to cast the Subspace Exclusion Zone (SEZ) scheme, which locates damage by reconstructing the captured field quantity shifts from analytical subspaces indexed by postulated boundaries, the so-called exclusion zones (EZs), in a model of the structure...
Subspace learning from image gradient orientations
Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja
2012-01-01
We introduce the notion of subspace learning from image gradient orientations for appearance-based object recognition. As image data is typically noisy and noise is substantially different from Gaussian, traditional subspace learning from pixel intensities fails very often to estimate reliably the
Kernel based subspace projection of hyperspectral images
DEFF Research Database (Denmark)
Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten
In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF...
Code subspaces for LLM geometries
Berenstein, David; Miller, Alexandra
2018-03-01
We consider effective field theory around classical background geometries with a gauge theory dual, specifically those in the class of LLM geometries. These are dual to half-BPS states of N= 4 SYM. We find that the language of code subspaces is natural for discussing the set of nearby states, which are built by acting with effective fields on these backgrounds. This work extends our previous work by going beyond the strict infinite N limit. We further discuss how one can extract the topology of the state beyond N→∞ and find that, as before, uncertainty and entanglement entropy calculations provide a useful tool to do so. Finally, we discuss obstructions to writing down a globally defined metric operator. We find that the answer depends on the choice of reference state that one starts with. Therefore, within this setup, there is ambiguity in trying to write an operator that describes the metric globally.
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Farouq, S.; Neytcheva, M.
2016-01-01
Roč. 73, č. 3 (2016), s. 631-633 ISSN 1017-1398 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution methods Subject RIV: BA - General Mathematics Impact factor: 1.241, year: 2016 http://link.springer.com/article/10.1007%2Fs11075-016-0111-1
Directory of Open Access Journals (Sweden)
Milan R. Radosavljević
2013-12-01
Full Text Available Water scarcity and water pollution are some of the crucial issues that must be addressed within local and global perspectives. One of the ways to reduce the impact of water scarcity and to minimizine water pollution is to expand water and wastewater reuse. The local conditions including regulations, institutions, financial mechanisms, availability of local technology and stakeholder participation have a great influence on the decisions for wastewater reuse. The increasing awareness of food safety and the influence of the countries which import food are influencing policy makers and agriculturists to improve the standards of wastewater reuse in agriculture. The environmental awareness of consumers has been putting pressure on the producers (industries to opt for environmentally sound technologies including those which conserve water and reduce the level of pollution. It may be observed that we have to move forwards to implement strategies and plans for wastewater reuse. However, their success and sustainability will depend on political will, public awareness and active support from national and international agencies to create favorable environment for the promotion of environmentally sustainable technologies. Wastewater treatment has a long history, especially in agriculture, but also in industry and households. Poor quality of wastewater can pose a significant risk to the health of farmers and users of agricultural products. The World Health Organization (WHO is working on a project for the reuse of wastewater in agriculture. To reduce effects of human activities to the minimum, it is necessary to provide such technical and technological solutions that would on the one hand ensure complying with the existing regulations and legislation, and on the other hand provide economically viable systems as seen through investments and operating costs. The use of wastewater The practice of using wastewater varies from country to country. Its
Sinusoidal Order Estimation Using Angles between Subspaces
Directory of Open Access Journals (Sweden)
Søren Holdt Jensen
2009-01-01
Full Text Available We consider the problem of determining the order of a parametric model from a noisy signal based on the geometry of the space. More specifically, we do this using the nontrivial angles between the candidate signal subspace model and the noise subspace. The proposed principle is closely related to the subspace orthogonality property known from the MUSIC algorithm, and we study its properties and compare it to other related measures. For the problem of estimating the number of complex sinusoids in white noise, a computationally efficient implementation exists, and this problem is therefore considered in detail. In computer simulations, we compare the proposed method to various well-known methods for order estimation. These show that the proposed method outperforms the other previously published subspace methods and that it is more robust to the noise being colored than the previously published methods.
International Nuclear Information System (INIS)
Bakhos, Tania; Saibaba, Arvind K.; Kitanidis, Peter K.
2015-01-01
We consider the problem of estimating parameters in large-scale weakly nonlinear inverse problems for which the underlying governing equations is a linear, time-dependent, parabolic partial differential equation. A major challenge in solving these inverse problems using Newton-type methods is the computational cost associated with solving the forward problem and with repeated construction of the Jacobian, which represents the sensitivity of the measurements to the unknown parameters. Forming the Jacobian can be prohibitively expensive because it requires repeated solutions of the forward and adjoint time-dependent parabolic partial differential equations corresponding to multiple sources and receivers. We propose an efficient method based on a Laplace transform-based exponential time integrator combined with a flexible Krylov subspace approach to solve the resulting shifted systems of equations efficiently. Our proposed solver speeds up the computation of the forward and adjoint problems, thus yielding significant speedup in total inversion time. We consider an application from Transient Hydraulic Tomography (THT), which is an imaging technique to estimate hydraulic parameters related to the subsurface from pressure measurements obtained by a series of pumping tests. The algorithms discussed are applied to a synthetic example taken from THT to demonstrate the resulting computational gains of this proposed method
Energy Technology Data Exchange (ETDEWEB)
Bakhos, Tania, E-mail: taniab@stanford.edu [Institute for Computational and Mathematical Engineering, Stanford University (United States); Saibaba, Arvind K. [Department of Electrical and Computer Engineering, Tufts University (United States); Kitanidis, Peter K. [Institute for Computational and Mathematical Engineering, Stanford University (United States); Department of Civil and Environmental Engineering, Stanford University (United States)
2015-10-15
We consider the problem of estimating parameters in large-scale weakly nonlinear inverse problems for which the underlying governing equations is a linear, time-dependent, parabolic partial differential equation. A major challenge in solving these inverse problems using Newton-type methods is the computational cost associated with solving the forward problem and with repeated construction of the Jacobian, which represents the sensitivity of the measurements to the unknown parameters. Forming the Jacobian can be prohibitively expensive because it requires repeated solutions of the forward and adjoint time-dependent parabolic partial differential equations corresponding to multiple sources and receivers. We propose an efficient method based on a Laplace transform-based exponential time integrator combined with a flexible Krylov subspace approach to solve the resulting shifted systems of equations efficiently. Our proposed solver speeds up the computation of the forward and adjoint problems, thus yielding significant speedup in total inversion time. We consider an application from Transient Hydraulic Tomography (THT), which is an imaging technique to estimate hydraulic parameters related to the subsurface from pressure measurements obtained by a series of pumping tests. The algorithms discussed are applied to a synthetic example taken from THT to demonstrate the resulting computational gains of this proposed method.
Active Subspaces for Wind Plant Surrogate Modeling
Energy Technology Data Exchange (ETDEWEB)
King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Adcock, Christiane [Massachusetts Institute of Technology
2018-01-12
Understanding the uncertainty in wind plant performance is crucial to their cost-effective design and operation. However, conventional approaches to uncertainty quantification (UQ), such as Monte Carlo techniques or surrogate modeling, are often computationally intractable for utility-scale wind plants because of poor congergence rates or the curse of dimensionality. In this paper we demonstrate that wind plant power uncertainty can be well represented with a low-dimensional active subspace, thereby achieving a significant reduction in the dimension of the surrogate modeling problem. We apply the active sub-spaces technique to UQ of plant power output with respect to uncertainty in turbine axial induction factors, and find a single active subspace direction dominates the sensitivity in power output. When this single active subspace direction is used to construct a quadratic surrogate model, the number of model unknowns can be reduced by up to 3 orders of magnitude without compromising performance on unseen test data. We conclude that the dimension reduction achieved with active subspaces makes surrogate-based UQ approaches tractable for utility-scale wind plants.
Active Subspaces of Airfoil Shape Parameterizations
Grey, Zachary J.; Constantine, Paul G.
2018-05-01
Design and optimization benefit from understanding the dependence of a quantity of interest (e.g., a design objective or constraint function) on the design variables. A low-dimensional active subspace, when present, identifies important directions in the space of design variables; perturbing a design along the active subspace associated with a particular quantity of interest changes that quantity more, on average, than perturbing the design orthogonally to the active subspace. This low-dimensional structure provides insights that characterize the dependence of quantities of interest on design variables. Airfoil design in a transonic flow field with a parameterized geometry is a popular test problem for design methodologies. We examine two particular airfoil shape parameterizations, PARSEC and CST, and study the active subspaces present in two common design quantities of interest, transonic lift and drag coefficients, under each shape parameterization. We mathematically relate the two parameterizations with a common polynomial series. The active subspaces enable low-dimensional approximations of lift and drag that relate to physical airfoil properties. In particular, we obtain and interpret a two-dimensional approximation of both transonic lift and drag, and we show how these approximation inform a multi-objective design problem.
Subspace confinement: how good is your qubit?
International Nuclear Information System (INIS)
Devitt, Simon J; Schirmer, Sonia G; Oi, Daniel K L; Cole, Jared H; Hollenberg, Lloyd C L
2007-01-01
The basic operating element of standard quantum computation is the qubit, an isolated two-level system that can be accurately controlled, initialized and measured. However, the majority of proposed physical architectures for quantum computation are built from systems that contain much more complicated Hilbert space structures. Hence, defining a qubit requires the identification of an appropriate controllable two-dimensional sub-system. This prompts the obvious question of how well a qubit, thus defined, is confined to this subspace, and whether we can experimentally quantify the potential leakage into states outside the qubit subspace. We demonstrate how subspace leakage can be characterized using minimal theoretical assumptions by examining the Fourier spectrum of the oscillation experiment
Monomial codes seen as invariant subspaces
Directory of Open Access Journals (Sweden)
García-Planas María Isabel
2017-08-01
Full Text Available It is well known that cyclic codes are very useful because of their applications, since they are not computationally expensive and encoding can be easily implemented. The relationship between cyclic codes and invariant subspaces is also well known. In this paper a generalization of this relationship is presented between monomial codes over a finite field and hyperinvariant subspaces of n under an appropriate linear transformation. Using techniques of Linear Algebra it is possible to deduce certain properties for this particular type of codes, generalizing known results on cyclic codes.
Quantum Computing in Decoherence-Free Subspace Constructed by Triangulation
Bi, Qiao; Guo, Liu; Ruda, H. E.
2010-01-01
A formalism for quantum computing in decoherence-free subspaces is presented. The constructed subspaces are partial triangulated to an index related to environment. The quantum states in the subspaces are just projected states which are ruled by a subdynamic kinetic equation. These projected states can be used to perform ideal quantum logical operations without decoherence.
Quantum Computing in Decoherence-Free Subspace Constructed by Triangulation
Directory of Open Access Journals (Sweden)
Qiao Bi
2010-01-01
Full Text Available A formalism for quantum computing in decoherence-free subspaces is presented. The constructed subspaces are partial triangulated to an index related to environment. The quantum states in the subspaces are just projected states which are ruled by a subdynamic kinetic equation. These projected states can be used to perform ideal quantum logical operations without decoherence.
Application of nonlinear Krylov acceleration to radiative transfer problems
International Nuclear Information System (INIS)
Till, A. T.; Adams, M. L.; Morel, J. E.
2013-01-01
The iterative solution technique used for radiative transfer is normally nested, with outer thermal iterations and inner transport iterations. We implement a nonlinear Krylov acceleration (NKA) method in the PDT code for radiative transfer problems that breaks nesting, resulting in more thermal iterations but significantly fewer total inner transport iterations. Using the metric of total inner transport iterations, we investigate a crooked-pipe-like problem and a pseudo-shock-tube problem. Using only sweep preconditioning, we compare NKA against a typical inner / outer method employing GMRES / Newton and find NKA to be comparable or superior. Finally, we demonstrate the efficacy of applying diffusion-based preconditioning to grey problems in conjunction with NKA. (authors)
Preconditioner considerations for an aerodynamic Newton-Krylov solver
International Nuclear Information System (INIS)
Chisholm, T.; Zingg, D.W.
2003-01-01
A fast Newton-Krylov algorithm is presented for solving the compressible Navier-Stokes equations on structured multi-block grids with application to turbulent aerodynamic flows. The one-equation Spalart-Allmaras model is used to provide the turbulent viscosity. The optimization of the algorithm is discussed. ILU(4) is suggested for a preconditioner, operating on a modified Jacobian matrix. An RCM reordering is used, with a suggested root node in the wake. The advantages of a matrix-free technique for forming matrix-vector products are shown. Three test cases are used to demonstrate convergence rates. Single-element cases are solved in less than 60 seconds on a desktop computer, while the solution of a multi-element case can be found in about 10 minutes. (author)
Subspace System Identification of the Kalman Filter
Directory of Open Access Journals (Sweden)
David Di Ruscio
2003-07-01
Full Text Available Some proofs concerning a subspace identification algorithm are presented. It is proved that the Kalman filter gain and the noise innovations process can be identified directly from known input and output data without explicitly solving the Riccati equation. Furthermore, it is in general and for colored inputs, proved that the subspace identification of the states only is possible if the deterministic part of the system is known or identified beforehand. However, if the inputs are white, then, it is proved that the states can be identified directly. Some alternative projection matrices which can be used to compute the extended observability matrix directly from the data are presented. Furthermore, an efficient method for computing the deterministic part of the system is presented. The closed loop subspace identification problem is also addressed and it is shown that this problem is solved and unbiased estimates are obtained by simply including a filter in the feedback. Furthermore, an algorithm for consistent closed loop subspace estimation is presented. This algorithm is using the controller parameters in order to overcome the bias problem.
Quantum Zeno subspaces induced by temperature
Energy Technology Data Exchange (ETDEWEB)
Militello, B.; Scala, M.; Messina, A. [Dipartimento di Fisica dell' Universita di Palermo, Via Archirafi 36, I-90123 Palermo (Italy)
2011-08-15
We discuss the partitioning of the Hilbert space of a quantum system induced by the interaction with another system at thermal equilibrium, showing that the higher the temperature the more effective is the formation of Zeno subspaces. We show that our analysis keeps its validity even in the case of interaction with a bosonic reservoir, provided appropriate limitations of the relevant bandwidth.
Counting Subspaces of a Finite Vector Space
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 15; Issue 11. Counting Subspaces of a Finite Vector Space – 1. Amritanshu Prasad. General Article Volume 15 Issue 11 November 2010 pp 977-987. Fulltext. Click here to view fulltext PDF. Permanent link:
Newton-Krylov-BDDC solvers for nonlinear cardiac mechanics
Pavarino, L.F.; Scacchi, S.; Zampini, Stefano
2015-01-01
The aim of this work is to design and study a Balancing Domain Decomposition by Constraints (BDDC) solver for the nonlinear elasticity system modeling the mechanical deformation of cardiac tissue. The contraction–relaxation process in the myocardium is induced by the generation and spread of the bioelectrical excitation throughout the tissue and it is mathematically described by the coupling of cardiac electro-mechanical models consisting of systems of partial and ordinary differential equations. In this study, the discretization of the electro-mechanical models is performed by Q1 finite elements in space and semi-implicit finite difference schemes in time, leading to the solution of a large-scale linear system for the bioelectrical potentials and a nonlinear system for the mechanical deformation at each time step of the simulation. The parallel mechanical solver proposed in this paper consists in solving the nonlinear system with a Newton-Krylov-BDDC method, based on the parallel solution of local mechanical problems and a coarse problem for the so-called primal unknowns. Three-dimensional parallel numerical tests on different machines show that the proposed parallel solver is scalable in the number of subdomains, quasi-optimal in the ratio of subdomain to mesh sizes, and robust with respect to tissue anisotropy.
Linear multifrequency-grey acceleration recast for preconditioned Krylov iterations
International Nuclear Information System (INIS)
Morel, Jim E.; Brian Yang, T.-Y.; Warsa, James S.
2007-01-01
The linear multifrequency-grey acceleration (LMFGA) technique is used to accelerate the iterative convergence of multigroup thermal radiation diffusion calculations in high energy density simulations. Although it is effective and efficient in one-dimensional calculations, the LMFGA method has recently been observed to significantly degrade under certain conditions in multidimensional calculations with large discontinuities in material properties. To address this deficiency, we recast the LMFGA method in terms of a preconditioned system that is solved with a Krylov method (LMFGK). Results are presented demonstrating that the new LMFGK method always requires fewer iterations than the original LMFGA method. The reduction in iteration count increases with both the size of the time step and the inhomogeneity of the problem. However, for reasons later explained, the LMFGK method can cost more per iteration than the LMFGA method, resulting in lower but comparable efficiency in problems with small time steps and weak inhomogeneities. In problems with large time steps and strong inhomogeneities, the LMFGK method is significantly more efficient than the LMFGA method
Newton-Krylov-BDDC solvers for nonlinear cardiac mechanics
Pavarino, L.F.
2015-07-18
The aim of this work is to design and study a Balancing Domain Decomposition by Constraints (BDDC) solver for the nonlinear elasticity system modeling the mechanical deformation of cardiac tissue. The contraction–relaxation process in the myocardium is induced by the generation and spread of the bioelectrical excitation throughout the tissue and it is mathematically described by the coupling of cardiac electro-mechanical models consisting of systems of partial and ordinary differential equations. In this study, the discretization of the electro-mechanical models is performed by Q1 finite elements in space and semi-implicit finite difference schemes in time, leading to the solution of a large-scale linear system for the bioelectrical potentials and a nonlinear system for the mechanical deformation at each time step of the simulation. The parallel mechanical solver proposed in this paper consists in solving the nonlinear system with a Newton-Krylov-BDDC method, based on the parallel solution of local mechanical problems and a coarse problem for the so-called primal unknowns. Three-dimensional parallel numerical tests on different machines show that the proposed parallel solver is scalable in the number of subdomains, quasi-optimal in the ratio of subdomain to mesh sizes, and robust with respect to tissue anisotropy.
Unsupervised spike sorting based on discriminative subspace learning.
Keshtkaran, Mohammad Reza; Yang, Zhi
2014-01-01
Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.
INDOOR SUBSPACING TO IMPLEMENT INDOORGML FOR INDOOR NAVIGATION
Directory of Open Access Journals (Sweden)
H. Jung
2015-10-01
Full Text Available According to an increasing demand for indoor navigation, there are great attempts to develop applicable indoor network. Representation for a room as a node is not sufficient to apply complex and large buildings. As OGC established IndoorGML, subspacing to partition the space for constructing logical network is introduced. Concerning subspacing for indoor network, transition space like halls or corridors also have to be considered. This study presents the subspacing process for creating an indoor network in shopping mall. Furthermore, categorization of transition space is performed and subspacing of this space is considered. Hall and squares in mall is especially defined for subspacing. Finally, implementation of subspacing process for indoor network is presented.
Indoor Subspacing to Implement Indoorgml for Indoor Navigation
Jung, H.; Lee, J.
2015-10-01
According to an increasing demand for indoor navigation, there are great attempts to develop applicable indoor network. Representation for a room as a node is not sufficient to apply complex and large buildings. As OGC established IndoorGML, subspacing to partition the space for constructing logical network is introduced. Concerning subspacing for indoor network, transition space like halls or corridors also have to be considered. This study presents the subspacing process for creating an indoor network in shopping mall. Furthermore, categorization of transition space is performed and subspacing of this space is considered. Hall and squares in mall is especially defined for subspacing. Finally, implementation of subspacing process for indoor network is presented.
On the maximal dimension of a completely entangled subspace for ...
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
dim S = d1d2 ...dk − (d1 +···+ dk) + k − 1, where E is the collection of all completely entangled subspaces. When H1 = H2 and k = 2 an explicit orthonormal basis of a maximal completely entangled subspace of H1 ⊗ H2 is given. We also introduce a more delicate notion of a perfectly entangled subspace for a multipartite ...
Directory of Open Access Journals (Sweden)
Gökhan Ekrem ÜSTÜN
2015-07-01
Full Text Available The aim of this study, to examine grey water treatment and reuse. For this aim, previous literature studies been research on and interpreted. Project began with study of physical, chemical and biological characteristics of the gray water. At the second part; grey water treatment and reuse were examined. At the third part; the technologies used for the methods treatment of gray water were explained. Then from costs and previous studies about grey water reuse were mentioned.
Central subspace dimensionality reduction using covariance operators.
Kim, Minyoung; Pavlovic, Vladimir
2011-04-01
We consider the task of dimensionality reduction informed by real-valued multivariate labels. The problem is often treated as Dimensionality Reduction for Regression (DRR), whose goal is to find a low-dimensional representation, the central subspace, of the input data that preserves the statistical correlation with the targets. A class of DRR methods exploits the notion of inverse regression (IR) to discover central subspaces. Whereas most existing IR techniques rely on explicit output space slicing, we propose a novel method called the Covariance Operator Inverse Regression (COIR) that generalizes IR to nonlinear input/output spaces without explicit target slicing. COIR's unique properties make DRR applicable to problem domains with high-dimensional output data corrupted by potentially significant amounts of noise. Unlike recent kernel dimensionality reduction methods that employ iterative nonconvex optimization, COIR yields a closed-form solution. We also establish the link between COIR, other DRR techniques, and popular supervised dimensionality reduction methods, including canonical correlation analysis and linear discriminant analysis. We then extend COIR to semi-supervised settings where many of the input points lack their labels. We demonstrate the benefits of COIR on several important regression problems in both fully supervised and semi-supervised settings.
Environmental Science and Technology, 1975
1975-01-01
The Second National Conference on Complete WateReuse stressed better planning, management, and use of water. The sessions covered: water reuse and its problems; water's interface with air and land, and modification of these interactions by the imposition of energy; and heavy metals in the environment and methods for their removal. (BT)
Smith, Daniel W.
1978-01-01
Presents a literature review of water reclamation and reuse. This review covers: (1) water resources planning; (2) agriculture and irrigation; (3) ground recharge; (4) industrial reuse; (5) health considerations; and (6) technology developments. A list of 217 references is also presented. (HM)
Seismic noise attenuation using an online subspace tracking algorithm
Zhou, Yatong; Li, Shuhua; Zhang, D.; Chen, Yangkang
2018-01-01
We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient
On the dimension of subspaces with bounded Schmidt rank
International Nuclear Information System (INIS)
Cubitt, Toby; Montanaro, Ashley; Winter, Andreas
2008-01-01
We consider the question of how large a subspace of a given bipartite quantum system can be when the subspace contains only highly entangled states. This is motivated in part by results of Hayden et al. [e-print arXiv:quant-ph/0407049; Commun. Math. Phys., 265, 95 (2006)], which show that in large dxd-dimensional systems there exist random subspaces of dimension almost d 2 , all of whose states have entropy of entanglement at least log d-O(1). It is also a generalization of results on the dimension of completely entangled subspaces, which have connections with the construction of unextendible product bases. Here we take as entanglement measure the Schmidt rank, and determine, for every pair of local dimensions d A and d B , and every r, the largest dimension of a subspace consisting only of entangled states of Schmidt rank r or larger. This exact answer is a significant improvement on the best bounds that can be obtained using the random subspace techniques in Hayden et al. We also determine the converse: the largest dimension of a subspace with an upper bound on the Schmidt rank. Finally, we discuss the question of subspaces containing only states with Schmidt equal to r
Subspace methods for pattern recognition in intelligent environment
Jain, Lakhmi
2014-01-01
This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.
On performance of Krylov smoothing for fully-coupled AMG preconditioners for VMS resistive MHD
Energy Technology Data Exchange (ETDEWEB)
Lin, Paul T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shadid, John N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States). Department of Mathematics and Statistics,; Tsuji, Paul H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2017-11-01
Here, this study explores the performance and scaling of a GMRES Krylov method employed as a smoother for an algebraic multigrid (AMG) preconditioned Newton- Krylov solution approach applied to a fully-implicit variational multiscale (VMS) nite element (FE) resistive magnetohydrodynamics (MHD) formulation. In this context a Newton iteration is used for the nonlinear system and a Krylov (GMRES) method is employed for the linear subsystems. The efficiency of this approach is critically dependent on the scalability and performance of the AMG preconditioner for the linear solutions and the performance of the smoothers play a critical role. Krylov smoothers are considered in an attempt to reduce the time and memory requirements of existing robust smoothers based on additive Schwarz domain decomposition (DD) with incomplete LU factorization solves on each subdomain. Three time dependent resistive MHD test cases are considered to evaluate the method. The results demonstrate that the GMRES smoother can be faster due to a decrease in the preconditioner setup time and a reduction in outer GMRESR solver iterations, and requires less memory (typically 35% less memory for global GMRES smoother) than the DD ILU smoother.
A multigrid Newton-Krylov method for flux-limited radiation diffusion
International Nuclear Information System (INIS)
Rider, W.J.; Knoll, D.A.; Olson, G.L.
1998-01-01
The authors focus on the integration of radiation diffusion including flux-limited diffusion coefficients. The nonlinear integration is accomplished with a Newton-Krylov method preconditioned with a multigrid Picard linearization of the governing equations. They investigate the efficiency of the linear and nonlinear iterative techniques
Krylov-Schur-Type restarts for the two-sided arnoldi method
Zwaan, I.N.; Hochstenbach, M.E.
2017-01-01
We consider the two-sided Arnoldi method and propose a two-sided Krylov-Schurtype restarting method. We discuss the restart for standard Rayleigh-Ritz extraction as well as harmonic Rayleigh-Ritz extraction. Additionally, we provide error bounds for Ritz values and Ritz vectors in the context of
Robust adaptive subspace detection in impulsive noise
Ben Atitallah, Ismail
2016-09-13
This paper addresses the design of the Adaptive Subspace Matched Filter (ASMF) detector in the presence of compound Gaussian clutters and a mismatch in the steering vector. In particular, we consider the case wherein the ASMF uses the regularized Tyler estimator (RTE) to estimate the clutter covariance matrix. Under this setting, a major question that needs to be addressed concerns the setting of the threshold and the regularization parameter. To answer this question, we consider the regime in which the number of observations used to estimate the RTE and their dimensions grow large together. Recent results from random matrix theory are then used in order to approximate the false alarm and detection probabilities by deterministic quantities. The latter are optimized in order to maximize an upper bound on the asymptotic detection probability while keeping the asymptotic false alarm probability at a fixed rate. © 2016 IEEE.
Robust adaptive subspace detection in impulsive noise
Ben Atitallah, Ismail; Kammoun, Abla; Alouini, Mohamed-Slim; Al-Naffouri, Tareq Y.
2016-01-01
This paper addresses the design of the Adaptive Subspace Matched Filter (ASMF) detector in the presence of compound Gaussian clutters and a mismatch in the steering vector. In particular, we consider the case wherein the ASMF uses the regularized Tyler estimator (RTE) to estimate the clutter covariance matrix. Under this setting, a major question that needs to be addressed concerns the setting of the threshold and the regularization parameter. To answer this question, we consider the regime in which the number of observations used to estimate the RTE and their dimensions grow large together. Recent results from random matrix theory are then used in order to approximate the false alarm and detection probabilities by deterministic quantities. The latter are optimized in order to maximize an upper bound on the asymptotic detection probability while keeping the asymptotic false alarm probability at a fixed rate. © 2016 IEEE.
An alternative subspace approach to EEG dipole source localization
Xu, Xiao-Liang; Xu, Bobby; He, Bin
2004-01-01
In the present study, we investigate a new approach to electroencephalography (EEG) three-dimensional (3D) dipole source localization by using a non-recursive subspace algorithm called FINES. In estimating source dipole locations, the present approach employs projections onto a subspace spanned by a small set of particular vectors (FINES vector set) in the estimated noise-only subspace instead of the entire estimated noise-only subspace in the case of classic MUSIC. The subspace spanned by this vector set is, in the sense of principal angle, closest to the subspace spanned by the array manifold associated with a particular brain region. By incorporating knowledge of the array manifold in identifying FINES vector sets in the estimated noise-only subspace for different brain regions, the present approach is able to estimate sources with enhanced accuracy and spatial resolution, thus enhancing the capability of resolving closely spaced sources and reducing estimation errors. The present computer simulations show, in EEG 3D dipole source localization, that compared to classic MUSIC, FINES has (1) better resolvability of two closely spaced dipolar sources and (2) better estimation accuracy of source locations. In comparison with RAP-MUSIC, FINES' performance is also better for the cases studied when the noise level is high and/or correlations among dipole sources exist.
An alternative subspace approach to EEG dipole source localization
International Nuclear Information System (INIS)
Xu Xiaoliang; Xu, Bobby; He Bin
2004-01-01
In the present study, we investigate a new approach to electroencephalography (EEG) three-dimensional (3D) dipole source localization by using a non-recursive subspace algorithm called FINES. In estimating source dipole locations, the present approach employs projections onto a subspace spanned by a small set of particular vectors (FINES vector set) in the estimated noise-only subspace instead of the entire estimated noise-only subspace in the case of classic MUSIC. The subspace spanned by this vector set is, in the sense of principal angle, closest to the subspace spanned by the array manifold associated with a particular brain region. By incorporating knowledge of the array manifold in identifying FINES vector sets in the estimated noise-only subspace for different brain regions, the present approach is able to estimate sources with enhanced accuracy and spatial resolution, thus enhancing the capability of resolving closely spaced sources and reducing estimation errors. The present computer simulations show, in EEG 3D dipole source localization, that compared to classic MUSIC, FINES has (1) better resolvability of two closely spaced dipolar sources and (2) better estimation accuracy of source locations. In comparison with RAP-MUSIC, FINES' performance is also better for the cases studied when the noise level is high and/or correlations among dipole sources exist
CSIR Research Space (South Africa)
Afrika, M
2010-10-01
Full Text Available The adoption of the internationally accepted waste management hierarchy (Sakai et al, 1996) into South African policy has changed the focus from “end of pipe” waste management towards waste minimisation (reuse, recycling and cleaner production...
Microscopic theory of dynamical subspace for large amplitude collective motion
International Nuclear Information System (INIS)
Sakata, Fumihiko; Marumori, Toshio; Ogura, Masanori.
1986-01-01
A full quantum theory appropriate for describing large amplitude collective motion is proposed by exploiting the basic idea of the semi-classical theory so far developed within the time-depedent Hartree-Fock theory. A central problem of the quantum theory is how to determine an optimal representation called a dynamical representation specific for the collective subspace where the large amplitude collective motion is replicated as precisely as possible. As an extension of the semi-classical theory where the concept of an approximate integral surface played an important role, the collective subspace is properly characterized by introducing a concept of an approximate invariant subspace of the Hamiltonian. (author)
A New Inexact Inverse Subspace Iteration for Generalized Eigenvalue Problems
Directory of Open Access Journals (Sweden)
Fatemeh Mohammad
2014-05-01
Full Text Available In this paper, we represent an inexact inverse subspace iteration method for computing a few eigenpairs of the generalized eigenvalue problem $Ax = \\lambda Bx$[Q.~Ye and P.~Zhang, Inexact inverse subspace iteration for generalized eigenvalue problems, Linear Algebra and its Application, 434 (2011 1697-1715]. In particular, the linear convergence property of the inverse subspace iteration is preserved.
Water Reuse: Using Reclaimed Water For Irrigation
Haering, Kathryn; Evanylo, Gregory K.; Benham, Brian Leslie, 1960-; Goatley, Michael
2009-01-01
Describes water reuse and reclaimed water, explains how reclaimed water is produced, options for water reuse, water reuse regulations, and agronomic concerns with water reuse, and provides several case studies of water reuse.
Subspace Correction Methods for Total Variation and $\\ell_1$-Minimization
Fornasier, Massimo; Schö nlieb, Carola-Bibiane
2009-01-01
This paper is concerned with the numerical minimization of energy functionals in Hilbert spaces involving convex constraints coinciding with a seminorm for a subspace. The optimization is realized by alternating minimizations of the functional on a
On spectral subspaces and their applications to automorphism groups
International Nuclear Information System (INIS)
Olesen, Dorte
1974-03-01
An attempt is made to give a survey of the theory of spectra and spectral subspaces of group representations in an abstract Banach space setting. The theory is applied to the groups of automorphisms of operator algebras (mostly C*-algebras) and some important results of interest for mathematical physicists are proved (restrictions of the bitransposed action, spectral subspaces for the transposed action on a C*-algebra, and positive states and representations of Rsup(n)) [fr
Parand, K.; Nikarya, M.
2017-11-01
In this paper a novel method will be introduced to solve a nonlinear partial differential equation (PDE). In the proposed method, we use the spectral collocation method based on Bessel functions of the first kind and the Jacobian free Newton-generalized minimum residual (JFNGMRes) method with adaptive preconditioner. In this work a nonlinear PDE has been converted to a nonlinear system of algebraic equations using the collocation method based on Bessel functions without any linearization, discretization or getting the help of any other methods. Finally, by using JFNGMRes, the solution of the nonlinear algebraic system is achieved. To illustrate the reliability and efficiency of the proposed method, we solve some examples of the famous Fisher equation. We compare our results with other methods.
Seismic noise attenuation using an online subspace tracking algorithm
Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang
2018-02-01
We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.
EVD Dualdating Based Online Subspace Learning
Directory of Open Access Journals (Sweden)
Bo Jin
2014-01-01
Full Text Available Conventional incremental PCA methods usually only discuss the situation of adding samples. In this paper, we consider two different cases: deleting samples and simultaneously adding and deleting samples. To avoid the NP-hard problem of downdating SVD without right singular vectors and specific position information, we choose to use EVD instead of SVD, which is used by most IPCA methods. First, we propose an EVD updating and downdating algorithm, called EVD dualdating, which permits simultaneous arbitrary adding and deleting operation, via transforming the EVD of the covariance matrix into a SVD updating problem plus an EVD of a small autocorrelation matrix. A comprehensive analysis is delivered to express the essence, expansibility, and computation complexity of EVD dualdating. A mathematical theorem proves that if the whole data matrix satisfies the low-rank-plus-shift structure, EVD dualdating is an optimal rank-k estimator under the sequential environment. A selection method based on eigenvalues is presented to determine the optimal rank k of the subspace. Then, we propose three incremental/decremental PCA methods: EVDD-IPCA, EVDD-DPCA, and EVDD-IDPCA, which are adaptive to the varying mean. Finally, plenty of comparative experiments demonstrate that EVDD-based methods outperform conventional incremental/decremental PCA methods in both efficiency and accuracy.
International Nuclear Information System (INIS)
Anon.
1997-01-01
The annual Beneficial Reuse Conference was conducted in Knoxville, Tennessee from August 5-7, 1997. Now in its fifth year, this conference has become the national forum for discussing the beneficial reuse and recycle of contaminated buildings, equipment and resources, and the fabrication of useful products from such resources. As in the past, the primary goal of Beneficial Reuse ''97 was to provide a forum for the practitioners of pollution prevention, decontamination and decommissioning, waste minimization, reindustrialization, asset management, privatization and recycling to share their successes and failures, as well as their innovative strategies and operational experiences with the assembled group of stakeholders. Separate abstracts have been indexed into the database for contributions to this conference proceedings
Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation
Cai, Xiao-Chuan; Gropp, William D.; Keyes, David E.; Melvin, Robin G.; Young, David P.
1996-01-01
We study parallel two-level overlapping Schwarz algorithms for solving nonlinear finite element problems, in particular, for the full potential equation of aerodynamics discretized in two dimensions with bilinear elements. The overall algorithm, Newton-Krylov-Schwarz (NKS), employs an inexact finite-difference Newton method and a Krylov space iterative method, with a two-level overlapping Schwarz method as a preconditioner. We demonstrate that NKS, combined with a density upwinding continuation strategy for problems with weak shocks, is robust and, economical for this class of mixed elliptic-hyperbolic nonlinear partial differential equations, with proper specification of several parameters. We study upwinding parameters, inner convergence tolerance, coarse grid density, subdomain overlap, and the level of fill-in in the incomplete factorization, and report their effect on numerical convergence rate, overall execution time, and parallel efficiency on a distributed-memory parallel computer.
Newton-Krylov-Schwarz algorithms for the 2D full potential equation
Energy Technology Data Exchange (ETDEWEB)
Cai, Xiao-Chuan [Univ. of Colorado, Boulder, CO (United States); Gropp, W.D. [Argonne National Lab., IL (United States); Keyes, D.E. [Old Dominion Univ. Norfolk, VA (United States)] [and others
1996-12-31
We study parallel two-level overlapping Schwarz algorithms for solving nonlinear finite element problems, in particular, for the full potential equation of aerodynamics discretized in two dimensions with bilinear elements. The main algorithm, Newton-Krylov-Schwarz (NKS), employs an inexact finite-difference Newton method and a Krylov space iterative method, with a two-level overlapping Schwarz method as a preconditioner. We demonstrate that NKS, combined with a density upwinding continuation strategy for problems with weak shocks, can be made robust for this class of mixed elliptic-hyperbolic nonlinear partial differential equations, with proper specification of several parameters. We study upwinding parameters, inner convergence tolerance, coarse grid density, subdomain overlap, and the level of fill-in in the incomplete factorization, and report favorable choices for numerical convergence rate and overall execution time on a distributed-memory parallel computer.
Accuracy of Two Three-Term and Three Two-Term Recurrences for Krylov Space Solvers
Czech Academy of Sciences Publication Activity Database
Gutknecht, M. H.; Strakoš, Zdeněk
2000-01-01
Roč. 22, č. 1 (2000), s. 213-229 ISSN 0895-4798 R&D Projects: GA ČR GA205/96/0921; GA AV ČR IAA2030706 Institutional research plan: AV0Z1030915 Keywords : linear system of equations * iterative method * Krylov space method * conjugate gradient method * tree-term recurrence * accuracy * roundoff Subject RIV: BA - General Mathematics Impact factor: 1.182, year: 2000
Energy Technology Data Exchange (ETDEWEB)
Clark, M. A. [NVIDIA Corp., Santa Clara; Strelchenko, Alexei [Fermilab; Vaquero, Alejandro [Utah U.; Wagner, Mathias [NVIDIA Corp., Santa Clara; Weinberg, Evan [Boston U.
2017-10-26
Lattice quantum chromodynamics simulations in nuclear physics have benefited from a tremendous number of algorithmic advances such as multigrid and eigenvector deflation. These improve the time to solution but do not alleviate the intrinsic memory-bandwidth constraints of the matrix-vector operation dominating iterative solvers. Batching this operation for multiple vectors and exploiting cache and register blocking can yield a super-linear speed up. Block-Krylov solvers can naturally take advantage of such batched matrix-vector operations, further reducing the iterations to solution by sharing the Krylov space between solves. However, practical implementations typically suffer from the quadratic scaling in the number of vector-vector operations. Using the QUDA library, we present an implementation of a block-CG solver on NVIDIA GPUs which reduces the memory-bandwidth complexity of vector-vector operations from quadratic to linear. We present results for the HISQ discretization, showing a 5x speedup compared to highly-optimized independent Krylov solves on NVIDIA's SaturnV cluster.
Aligning the economic modeling of software reuse with reuse practices
Postmus, D.; Meijler, 27696
In contrast to current practices where software reuse is applied recursively and reusable assets are tailored trough parameterization or specialization, existing reuse economic models assume that (i) the cost of reusing a software asset depends on its size and (ii) reusable assets are developed from
Briscoe, Georgia
1991-01-01
Discussion of recycling paper in law libraries is also applicable to other types of libraries. Results of surveys of law libraries that investigated recycling practices in 1987 and again in 1990 are reported, and suggestions for reducing the amount of paper used and reusing as much as possible are offered. (LRW)
Nijveen, H.; Matus-Garcia, M.; Passel, van M.W.J.
2012-01-01
Anecdotal evidence shows promoters being reused separate from their downstream gene, thus providing a mechanism for the efficient and rapid rewiring of a gene’s transcriptional regulation. We have identified over 4000 groups of highly similar promoters using a conservative sequence similarity search
2012 Guidelines for Water Reuse
This manual is a revision of the "2004 Water Reuse Guidelines." This document is a summary of reuse guidelines, with supporting information, for the benefit of utilities of utilities and regulatory agencies, particularly EPA.
Two-qubit quantum computing in a projected subspace
International Nuclear Information System (INIS)
Bi Qiao; Ruda, H.E.; Zhan, M.S.
2002-01-01
A formulation for performing quantum computing in a projected subspace is presented, based on the subdynamical kinetic equation (SKE) for an open quantum system. The eigenvectors of the kinetic equation are shown to remain invariant before and after interaction with the environment. However, the eigenvalues in the projected subspace exhibit a type of phase shift to the evolutionary states. This phase shift does not destroy the decoherence-free (DF) property of the subspace because the associated fidelity is 1. This permits a universal formalism to be presented--the eigenprojectors of the free part of the Hamiltonian for the system and bath may be used to construct a DF projected subspace based on the SKE. To eliminate possible phase or unitary errors induced by the change in the eigenvalues, a cancellation technique is proposed, using the adjustment of the coupling time, and applied to a two-qubit computing system. A general criteria for constructing a DF-projected subspace from the SKE is discussed. Finally, a proposal for using triangulation to realize a decoherence-free subsystem based on SKE is presented. The concrete formulation for a two-qubit model is given exactly. Our approach is general and appears to be applicable to any type of decoherence
Adiabatic evolution of decoherence-free subspaces and its shortcuts
Wu, S. L.; Huang, X. L.; Li, H.; Yi, X. X.
2017-10-01
The adiabatic theorem and shortcuts to adiabaticity for time-dependent open quantum systems are explored in this paper. Starting from the definition of dynamical stable decoherence-free subspace, we show that, under a compact adiabatic condition, the quantum state remains in the time-dependent decoherence-free subspace with an extremely high purity, even though the dynamics of the open quantum system may not be adiabatic. The adiabatic condition mentioned here in the adiabatic theorem for open systems is very similar to that for closed quantum systems, except that the operators required to change slowly are the Lindblad operators. We also show that the adiabatic evolution of decoherence-free subspaces depends on the existence of instantaneous decoherence-free subspaces, which requires that the Hamiltonian of open quantum systems be engineered according to the incoherent control protocol. In addition, shortcuts to adiabaticity for adiabatic decoherence-free subspaces are also presented based on the transitionless quantum driving method. Finally, we provide an example that consists of a two-level system coupled to a broadband squeezed vacuum field to show our theory. Our approach employs Markovian master equations and the theory can apply to finite-dimensional quantum open systems.
Independence and totalness of subspaces in phase space methods
Vourdas, A.
2018-04-01
The concepts of independence and totalness of subspaces are introduced in the context of quasi-probability distributions in phase space, for quantum systems with finite-dimensional Hilbert space. It is shown that due to the non-distributivity of the lattice of subspaces, there are various levels of independence, from pairwise independence up to (full) independence. Pairwise totalness, totalness and other intermediate concepts are also introduced, which roughly express that the subspaces overlap strongly among themselves, and they cover the full Hilbert space. A duality between independence and totalness, that involves orthocomplementation (logical NOT operation), is discussed. Another approach to independence is also studied, using Rota's formalism on independent partitions of the Hilbert space. This is used to define informational independence, which is proved to be equivalent to independence. As an application, the pentagram (used in discussions on contextuality) is analysed using these concepts.
A generalized Schwinger boson mapping with a physical subspace
International Nuclear Information System (INIS)
Scholtz, F.G.; Geyer, H.B.
1988-01-01
We investigate the existence of a physical subspace for generalized Schwinger boson mappings of SO(2n+1) contains SO(2n) in view of previous observations by Marshalek and the recent construction of such a mapping and subspace for SO(8) by Kaup. It is shown that Kaup's construction can be attributed to the existence of a unique SO(8) automorphism. We proceed to construct a generalized Schwinger-type mapping for SO(2n+1) contains SO(2n) which, in contrast to a similar attempt by Yamamura and Nishiyama, indeed has a corresponding physical subspace. This new mapping includes in the special case of SO(8) the mapping by Kaup which is equivalent to the one given by Yamamura and Nishiyama for n=4. Nevertheless, we indicate the limitations of the generalized Schwinger mapping regarding its applicability to situations where one seeks to establish a direct link between phenomenological boson models and an underlying fermion microscopy. (orig.)
Subspace Correction Methods for Total Variation and $\\ell_1$-Minimization
Fornasier, Massimo
2009-01-01
This paper is concerned with the numerical minimization of energy functionals in Hilbert spaces involving convex constraints coinciding with a seminorm for a subspace. The optimization is realized by alternating minimizations of the functional on a sequence of orthogonal subspaces. On each subspace an iterative proximity-map algorithm is implemented via oblique thresholding, which is the main new tool introduced in this work. We provide convergence conditions for the algorithm in order to compute minimizers of the target energy. Analogous results are derived for a parallel variant of the algorithm. Applications are presented in domain decomposition methods for degenerate elliptic PDEs arising in total variation minimization and in accelerated sparse recovery algorithms based on 1-minimization. We include numerical examples which show e.cient solutions to classical problems in signal and image processing. © 2009 Society for Industrial and Applied Physics.
Roller Bearing Monitoring by New Subspace-Based Damage Indicator
Directory of Open Access Journals (Sweden)
G. Gautier
2015-01-01
Full Text Available A frequency-band subspace-based damage identification method for fault diagnosis in roller bearings is presented. Subspace-based damage indicators are obtained by filtering the vibration data in the frequency range where damage is likely to occur, that is, around the bearing characteristic frequencies. The proposed method is validated by considering simulated data of a damaged bearing. Also, an experimental case is considered which focuses on collecting the vibration data issued from a run-to-failure test. It is shown that the proposed method can detect bearing defects and, as such, it appears to be an efficient tool for diagnosis purpose.
A subspace preconditioning algorithm for eigenvector/eigenvalue computation
Energy Technology Data Exchange (ETDEWEB)
Bramble, J.H.; Knyazev, A.V.; Pasciak, J.E.
1996-12-31
We consider the problem of computing a modest number of the smallest eigenvalues along with orthogonal bases for the corresponding eigen-spaces of a symmetric positive definite matrix. In our applications, the dimension of a matrix is large and the cost of its inverting is prohibitive. In this paper, we shall develop an effective parallelizable technique for computing these eigenvalues and eigenvectors utilizing subspace iteration and preconditioning. Estimates will be provided which show that the preconditioned method converges linearly and uniformly in the matrix dimension when used with a uniform preconditioner under the assumption that the approximating subspace is close enough to the span of desired eigenvectors.
Numerical Validation of the Delaunay Normalization and the Krylov-Bogoliubov-Mitropolsky Method
Directory of Open Access Journals (Sweden)
David Ortigosa
2014-01-01
Full Text Available A scalable second-order analytical orbit propagator programme based on modern and classical perturbation methods is being developed. As a first step in the validation and verification of part of our orbit propagator programme, we only consider the perturbation produced by zonal harmonic coefficients in the Earth’s gravity potential, so that it is possible to analyze the behaviour of the mathematical expressions involved in Delaunay normalization and the Krylov-Bogoliubov-Mitropolsky method in depth and determine their limits.
Solving Eigenvalue response matrix equations with Jacobian-Free Newton-Krylov methods
International Nuclear Information System (INIS)
Roberts, Jeremy A.; Forget, Benoit
2011-01-01
The response matrix method for reactor eigenvalue problems is motivated as a technique for solving coarse mesh transport equations, and the classical approach of power iteration (PI) for solution is described. The method is then reformulated as a nonlinear system of equations, and the associated Jacobian is derived. A Jacobian-Free Newton-Krylov (JFNK) method is employed to solve the system, using an approximate Jacobian coupled with incomplete factorization as a preconditioner. The unpreconditioned JFNK slightly outperforms PI, and preconditioned JFNK outperforms both PI and Steffensen-accelerated PI significantly. (author)
Fast regularizing sequential subspace optimization in Banach spaces
International Nuclear Information System (INIS)
Schöpfer, F; Schuster, T
2009-01-01
We are concerned with fast computations of regularized solutions of linear operator equations in Banach spaces in case only noisy data are available. To this end we modify recently developed sequential subspace optimization methods in such a way that the therein employed Bregman projections onto hyperplanes are replaced by Bregman projections onto stripes whose width is in the order of the noise level
Experimental Comparison of Signal Subspace Based Noise Reduction Methods
DEFF Research Database (Denmark)
Hansen, Peter Søren Kirk; Hansen, Per Christian; Hansen, Steffen Duus
1999-01-01
The signal subspace approach for non-parametric speech enhancement is considered. Several algorithms have been proposed in the literature but only partly analyzed. Here, the different algorithms are compared, and the emphasis is put onto the limiting factors and practical behavior of the estimators...
Recursive subspace identification for in flight modal analysis of airplanes
De Cock , Katrien; Mercère , Guillaume; De Moor , Bart
2006-01-01
International audience; In this paper recursive subspace identification algorithms are applied to track the modal parameters of airplanes on-line during test flights. The ability to track changes in the damping ratios and the influence of the forgetting factor are studied through simulations.
Von Neumann algebras as complemented subspaces of B(H)
DEFF Research Database (Denmark)
Christensen, Erik; Wang, Liguang
2014-01-01
Let M be a von Neumann algebra of type II1 which is also a complemented subspace of B( H). We establish an algebraic criterion, which ensures that M is an injective von Neumann algebra. As a corollary we show that if M is a complemented factor of type II1 on a Hilbert space H, then M is injective...
Lie n-derivations on 7 -subspace lattice algebras
Indian Academy of Sciences (India)
all x ∈ K and all A ∈ Alg L. Based on this result, a complete characterization of linear n-Lie derivations on Alg L is obtained. Keywords. J -subspace lattice algebras; Lie derivations; Lie n-derivations; derivations. 2010 Mathematics Subject Classification. 47B47, 47L35. 1. Introduction. Let A be an algebra. Recall that a linear ...
Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning
DEFF Research Database (Denmark)
Chakraborty, Rudrasis; Hauberg, Søren; Vemuri, Baba C.
2017-01-01
Principal Component Analysis (PCA) is a fundamental method for estimating a linear subspace approximation to high-dimensional data. Many algorithms exist in literature to achieve a statistically robust version of PCA called RPCA. In this paper, we present a geometric framework for computing the p...
Active Subspace Methods for Data-Intensive Inverse Problems
Energy Technology Data Exchange (ETDEWEB)
Wang, Qiqi [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
2017-04-27
The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.
Subspace identification of distributed clusters of homogeneous systems
Yu, C.; Verhaegen, M.H.G.
2017-01-01
This note studies the identification of a network comprised of interconnected clusters of LTI systems. Each cluster consists of homogeneous dynamical systems, and its interconnections with the rest of the network are unmeasurable. A subspace identification method is proposed for identifying a single
Lucchetti, G.; Gray, G.A.
1988-01-01
A small-scale water reuse system (150 L/min) was developed to create an environment for observing fish under a variety of temperature regimes. Key concerns of disease control, water quality, temperature control, and efficiency and case of operation were addressed. Northern squawfish (Ptychocheilus oregonensis) were held at loading densities ranging from 0.11 to 0.97 kg/L per minute and at temperatures from 10 to 20°C for 6 months with no disease problems or degradation ofwater quality in the system. The system required little maintenance during 2 years of operation.
CSIR Research Space (South Africa)
Rosman, Benjamin
2016-02-01
Full Text Available Keywords Policy Reuse · Reinforcement Learning · Online Learning · Online Bandits · Transfer Learning · Bayesian Optimisation · Bayesian Decision Theory. 1 Introduction As robots and software agents are becoming more ubiquitous in many applications.... The agent has access to a library of policies (pi1, pi2 and pi3), and has previously experienced a set of task instances (τ1, τ2, τ3, τ4), as well as samples of the utilities of the library policies on these instances (the black dots indicate the means...
Krylov iterative methods and synthetic acceleration for transport in binary statistical media
International Nuclear Information System (INIS)
Fichtl, Erin D.; Warsa, James S.; Prinja, Anil K.
2009-01-01
In particle transport applications there are numerous physical constructs in which heterogeneities are randomly distributed. The quantity of interest in these problems is the ensemble average of the flux, or the average of the flux over all possible material 'realizations.' The Levermore-Pomraning closure assumes Markovian mixing statistics and allows a closed, coupled system of equations to be written for the ensemble averages of the flux in each material. Generally, binary statistical mixtures are considered in which there are two (homogeneous) materials and corresponding coupled equations. The solution process is iterative, but convergence may be slow as either or both materials approach the diffusion and/or atomic mix limits. A three-part acceleration scheme is devised to expedite convergence, particularly in the atomic mix-diffusion limit where computation is extremely slow. The iteration is first divided into a series of 'inner' material and source iterations to attenuate the diffusion and atomic mix error modes separately. Secondly, atomic mix synthetic acceleration is applied to the inner material iteration and S 2 synthetic acceleration to the inner source iterations to offset the cost of doing several inner iterations per outer iteration. Finally, a Krylov iterative solver is wrapped around each iteration, inner and outer, to further expedite convergence. A spectral analysis is conducted and iteration counts and computing cost for the new two-step scheme are compared against those for a simple one-step iteration, to which a Krylov iterative method can also be applied.
Globalized Newton-Krylov-Schwarz Algorithms and Software for Parallel Implicit CFD
Gropp, W. D.; Keyes, D. E.; McInnes, L. C.; Tidriri, M. D.
1998-01-01
Implicit solution methods are important in applications modeled by PDEs with disparate temporal and spatial scales. Because such applications require high resolution with reasonable turnaround, "routine" parallelization is essential. The pseudo-transient matrix-free Newton-Krylov-Schwarz (Psi-NKS) algorithmic framework is presented as an answer. We show that, for the classical problem of three-dimensional transonic Euler flow about an M6 wing, Psi-NKS can simultaneously deliver: globalized, asymptotically rapid convergence through adaptive pseudo- transient continuation and Newton's method-, reasonable parallelizability for an implicit method through deferred synchronization and favorable communication-to-computation scaling in the Krylov linear solver; and high per- processor performance through attention to distributed memory and cache locality, especially through the Schwarz preconditioner. Two discouraging features of Psi-NKS methods are their sensitivity to the coding of the underlying PDE discretization and the large number of parameters that must be selected to govern convergence. We therefore distill several recommendations from our experience and from our reading of the literature on various algorithmic components of Psi-NKS, and we describe a freely available, MPI-based portable parallel software implementation of the solver employed here.
Physics-based preconditioning and the Newton-Krylov method for non-equilibrium radiation diffusion
International Nuclear Information System (INIS)
Mousseau, V.A.; Knoll, D.A.; Rider, W.J.
2000-01-01
An algorithm is presented for the solution of the time dependent reaction-diffusion systems which arise in non-equilibrium radiation diffusion applications. This system of nonlinear equations is solved by coupling three numerical methods, Jacobian-free Newton-Krylov, operator splitting, and multigrid linear solvers. An inexact Newton's method is used to solve the system of nonlinear equations. Since building the Jacobian matrix for problems of interest can be challenging, the authors employ a Jacobian-free implementation of Newton's method, where the action of the Jacobian matrix on a vector is approximated by a first order Taylor series expansion. Preconditioned generalized minimal residual (PGMRES) is the Krylov method used to solve the linear systems that come from the iterations of Newton's method. The preconditioner in this solution method is constructed using a physics-based divide and conquer approach, often referred to as operator splitting. This solution procedure inverts the scalar elliptic systems that make up the preconditioner using simple multigrid methods. The preconditioner also addresses the strong coupling between equations with local 2 x 2 block solves. The intra-cell coupling is applied after the inter-cell coupling has already been addressed by the elliptic solves. Results are presented using this solution procedure that demonstrate its efficiency while incurring minimal memory requirements
Asymptotic description of plasma turbulence: Krylov-Bogoliubov methods and quasi-particles
International Nuclear Information System (INIS)
Sosenko, P.P.; Bertrand, P.; Decyk, V.K.
2001-01-01
The asymptotic theory of charged particle motion in electromagnetic fields is developed for the general case of finite Larmor-radius effects by means of Krylov-Bogoliubov averaging method. The correspondence between the general asymptotic methods, elaborated by M. Krylov and M.Bogoliubov, the quasi-particle description and gyrokinetics is established. Such a comparison is used to shed more light on the physical sense of the reduced Poisson equation, introduced in gyrokinetics, and the particle polarization drift. It is shown that the modification of the Poisson equation in the asymptotic theory is due to the non-conservation of the magnetic moment and gyrophase trembling. it is shown that the second-order modification of the adiabatic invariant can determine the conditions of global plasma stability and introduces new nonlinear terms into the reduced Poisson equation. Such a modification is important for several plasma orderings, e.g. NHD type ordering. The feasibility of numerical simulation schemes in which the polarization drift is included into the quasi-particle equations of motion, and the Poisson equation remains unchanged is analyzed. A consistent asymptotic model is proposed in which the polarization drift is included into the quasi-particle equations of motion and the particle and quasi-particle velocities are equal. It is shown that in such models there are additional modifications of the reduced Poisson equation. The latter becomes even more complicated in contrast to earlier suggestions
Subspace-based interference removal methods for a multichannel biomagnetic sensor array
Sekihara, Kensuke; Nagarajan, Srikantan S.
2017-10-01
Objective. In biomagnetic signal processing, the theory of the signal subspace has been applied to removing interfering magnetic fields, and a representative algorithm is the signal space projection algorithm, in which the signal/interference subspace is defined in the spatial domain as the span of signal/interference-source lead field vectors. This paper extends the notion of this conventional (spatial domain) signal subspace by introducing a new definition of signal subspace in the time domain. Approach. It defines the time-domain signal subspace as the span of row vectors that contain the source time course values. This definition leads to symmetric relationships between the time-domain and the conventional (spatial-domain) signal subspaces. As a review, this article shows that the notion of the time-domain signal subspace provides useful insights over existing interference removal methods from a unified perspective. Main results and significance. Using the time-domain signal subspace, it is possible to interpret a number of interference removal methods as the time domain signal space projection. Such methods include adaptive noise canceling, sensor noise suppression, the common temporal subspace projection, the spatio-temporal signal space separation, and the recently-proposed dual signal subspace projection. Our analysis using the notion of the time domain signal space projection reveals implicit assumptions these methods rely on, and shows that the difference between these methods results only from the manner of deriving the interference subspace. Numerical examples that illustrate the results of our arguments are provided.
Asgharzadeh, Hafez; Borazjani, Iman
2017-02-15
The explicit and semi-implicit schemes in flow simulations involving complex geometries and moving boundaries suffer from time-step size restriction and low convergence rates. Implicit schemes can be used to overcome these restrictions, but implementing them to solve the Navier-Stokes equations is not straightforward due to their non-linearity. Among the implicit schemes for nonlinear equations, Newton-based techniques are preferred over fixed-point techniques because of their high convergence rate but each Newton iteration is more expensive than a fixed-point iteration. Krylov subspace methods are one of the most advanced iterative methods that can be combined with Newton methods, i.e., Newton-Krylov Methods (NKMs) to solve non-linear systems of equations. The success of NKMs vastly depends on the scheme for forming the Jacobian, e.g., automatic differentiation is very expensive, and matrix-free methods without a preconditioner slow down as the mesh is refined. A novel, computationally inexpensive analytical Jacobian for NKM is developed to solve unsteady incompressible Navier-Stokes momentum equations on staggered overset-curvilinear grids with immersed boundaries. Moreover, the analytical Jacobian is used to form preconditioner for matrix-free method in order to improve its performance. The NKM with the analytical Jacobian was validated and verified against Taylor-Green vortex, inline oscillations of a cylinder in a fluid initially at rest, and pulsatile flow in a 90 degree bend. The capability of the method in handling complex geometries with multiple overset grids and immersed boundaries is shown by simulating an intracranial aneurysm. It was shown that the NKM with an analytical Jacobian is 1.17 to 14.77 times faster than the fixed-point Runge-Kutta method, and 1.74 to 152.3 times (excluding an intensively stretched grid) faster than automatic differentiation depending on the grid (size) and the flow problem. In addition, it was shown that using only the
Asgharzadeh, Hafez; Borazjani, Iman
2016-01-01
The explicit and semi-implicit schemes in flow simulations involving complex geometries and moving boundaries suffer from time-step size restriction and low convergence rates. Implicit schemes can be used to overcome these restrictions, but implementing them to solve the Navier-Stokes equations is not straightforward due to their non-linearity. Among the implicit schemes for nonlinear equations, Newton-based techniques are preferred over fixed-point techniques because of their high convergence rate but each Newton iteration is more expensive than a fixed-point iteration. Krylov subspace methods are one of the most advanced iterative methods that can be combined with Newton methods, i.e., Newton-Krylov Methods (NKMs) to solve non-linear systems of equations. The success of NKMs vastly depends on the scheme for forming the Jacobian, e.g., automatic differentiation is very expensive, and matrix-free methods without a preconditioner slow down as the mesh is refined. A novel, computationally inexpensive analytical Jacobian for NKM is developed to solve unsteady incompressible Navier-Stokes momentum equations on staggered overset-curvilinear grids with immersed boundaries. Moreover, the analytical Jacobian is used to form preconditioner for matrix-free method in order to improve its performance. The NKM with the analytical Jacobian was validated and verified against Taylor-Green vortex, inline oscillations of a cylinder in a fluid initially at rest, and pulsatile flow in a 90 degree bend. The capability of the method in handling complex geometries with multiple overset grids and immersed boundaries is shown by simulating an intracranial aneurysm. It was shown that the NKM with an analytical Jacobian is 1.17 to 14.77 times faster than the fixed-point Runge-Kutta method, and 1.74 to 152.3 times (excluding an intensively stretched grid) faster than automatic differentiation depending on the grid (size) and the flow problem. In addition, it was shown that using only the
Sharkov, N. A.; Sharkova, O. A.
2018-05-01
The paper identifies the importance of the Leonhard Euler's discoveries in the field of shipbuilding for the scientific evolution of academician A. N. Krylov and for the modern knowledge in survivability and safety of ships. The works by Leonard Euler "Marine Science" and "The Moon Motion New Theory" are discussed.
On the Convergence of Q-OR and Q-MR Krylov Methods for Solving Nonsymmetric Linear Systems
Czech Academy of Sciences Publication Activity Database
Duintjer Tebbens, Jurjen; Meurant, G.
2016-01-01
Roč. 56, č. 1 (2016), s. 77-97 ISSN 0006-3835 R&D Projects: GA ČR GA13-06684S Institutional support: RVO:67985807 Keywords : Krylov method * Q-OR method * Q-MR method * BiCG * QMR * CMRH * eigenvalue influence * prescribed convergence Subject RIV: BA - General Mathematics Impact factor: 1.670, year: 2016
Environmental benefits from reusing clothes
DEFF Research Database (Denmark)
Farrant, Laura; Olsen, Stig Irving; Wangel, Arne
2010-01-01
and Estonia, it was assumed that over 100 collected items 60 would be reused, 30 recycled in other ways and 10 go to final disposal Using these inputs, the LCA showed that the collection, processing and transport of second-hand clothing has insignificant impacts on the environment in comparison to the savings...... of establishing the net benefits from introducing clothes reuse. Indeed, it enables to take into consideration all the activities connected to reusing clothes, including, for instance, recycling and disposal of the collected clothes not suitable for reuse. In addition, the routes followed by the collected clothes....... Conclusions The results of the study show that clothes reuse can significantly contribute to reducing the environmental burden of clothing. Recommendations and perspectives It would be beneficial to apply other methods for estimating the avoided production of new clothes in order to check the validity...
Different structures on subspaces of OsckM
Directory of Open Access Journals (Sweden)
Čomić Irena
2013-01-01
Full Text Available The geometry of OsckM spaces was introduced by R. Miron and Gh. Atanasiu in [6] and [7]. The theory of these spaces was developed by R. Miron and his cooperators from Romania, Japan and other countries in several books and many papers. Only some of them are mentioned in references. Here we recall the construction of adapted bases in T(OsckM and T*(OsckM, which are comprehensive with the J structure. The theory of two complementary family of subspaces is presented as it was done in [2] and [4]. The operators J,J, θ,θ, p, p* are introduced in the ambient space and subspaces. Some new relations between them are established. The action of these operators on Liouville vector fields are examined.
Evaluating Clustering in Subspace Projections of High Dimensional Data
DEFF Research Database (Denmark)
Müller, Emmanuel; Günnemann, Stephan; Assent, Ira
2009-01-01
Clustering high dimensional data is an emerging research field. Subspace clustering or projected clustering group similar objects in subspaces, i.e. projections, of the full space. In the past decade, several clustering paradigms have been developed in parallel, without thorough evaluation...... and comparison between these paradigms on a common basis. Conclusive evaluation and comparison is challenged by three major issues. First, there is no ground truth that describes the "true" clusters in real world data. Second, a large variety of evaluation measures have been used that reflect different aspects...... of the clustering result. Finally, in typical publications authors have limited their analysis to their favored paradigm only, while paying other paradigms little or no attention. In this paper, we take a systematic approach to evaluate the major paradigms in a common framework. We study representative clustering...
Integrated Phoneme Subspace Method for Speech Feature Extraction
Directory of Open Access Journals (Sweden)
Park Hyunsin
2009-01-01
Full Text Available Speech feature extraction has been a key focus in robust speech recognition research. In this work, we discuss data-driven linear feature transformations applied to feature vectors in the logarithmic mel-frequency filter bank domain. Transformations are based on principal component analysis (PCA, independent component analysis (ICA, and linear discriminant analysis (LDA. Furthermore, this paper introduces a new feature extraction technique that collects the correlation information among phoneme subspaces and reconstructs feature space for representing phonemic information efficiently. The proposed speech feature vector is generated by projecting an observed vector onto an integrated phoneme subspace (IPS based on PCA or ICA. The performance of the new feature was evaluated for isolated word speech recognition. The proposed method provided higher recognition accuracy than conventional methods in clean and reverberant environments.
Invariant subspaces in some function spaces on symmetric spaces. II
International Nuclear Information System (INIS)
Platonov, S S
1998-01-01
Let G be a semisimple connected Lie group with finite centre, K a maximal compact subgroup of G, and M=G/K a Riemannian symmetric space of non-compact type. We study the problem of describing the structure of closed linear subspaces in various function spaces on M that are invariant under the quasiregular representation of the group G. We consider the case when M is a symplectic symmetric space of rank 1
Quantum cloning of mixed states in symmetric subspaces
International Nuclear Information System (INIS)
Fan Heng
2003-01-01
Quantum-cloning machine for arbitrary mixed states in symmetric subspaces is proposed. This quantum-cloning machine can be used to copy part of the output state of another quantum-cloning machine and is useful in quantum computation and quantum information. The shrinking factor of this quantum cloning achieves the well-known upper bound. When the input is identical pure states, two different fidelities of this cloning machine are optimal
Bi Sparsity Pursuit: A Paradigm for Robust Subspace Recovery
2016-09-27
Bian, Student Member, IEEE, and Hamid Krim, Fellow, IEEE Abstract The success of sparse models in computer vision and machine learning is due to the...16. SECURITY CLASSIFICATION OF: The success of sparse models in computer vision and machine learning is due to the fact that, high dimensional data...vision and machine learning is due to the fact that, high dimensional data is distributed in a union of low dimensional subspaces in many real-world
Index Formulae for Subspaces of Kreĭn Spaces
Dijksma, Aad; Gheondea, Aurelian
1996-01-01
For a subspace S of a Kreĭn space K and an arbitrary fundamental decomposition K = K-[+]K+ of K, we prove the index formula κ-(S) + dim(S⊥ ∩ K+) = κ+(S⊥) + dim(S ∩ K-), where κ±(S) stands for the positive/negative signature of S. The difference dim(S ∩ K-) - dim(S⊥ ∩ K+), provided it is well
Subspace-based Inverse Uncertainty Quantification for Nuclear Data Assessment
Energy Technology Data Exchange (ETDEWEB)
Khuwaileh, B.A., E-mail: bakhuwai@ncsu.edu; Abdel-Khalik, H.S.
2015-01-15
Safety analysis and design optimization depend on the accurate prediction of various reactor attributes. Predictions can be enhanced by reducing the uncertainty associated with the attributes of interest. An inverse problem can be defined and solved to assess the sources of uncertainty, and experimental effort can be subsequently directed to further improve the uncertainty associated with these sources. In this work a subspace-based algorithm for inverse sensitivity/uncertainty quantification (IS/UQ) has been developed to enable analysts account for all sources of nuclear data uncertainties in support of target accuracy assessment-type analysis. An approximate analytical solution of the optimization problem is used to guide the search for the dominant uncertainty subspace. By limiting the search to a subspace, the degrees of freedom available for the optimization search are significantly reduced. A quarter PWR fuel assembly is modeled and the accuracy of the multiplication factor and the fission reaction rate are used as reactor attributes whose uncertainties are to be reduced. Numerical experiments are used to demonstrate the computational efficiency of the proposed algorithm. Our ongoing work is focusing on extending the proposed algorithm to account for various forms of feedback, e.g., thermal-hydraulics and depletion effects.
Comparison Study of Subspace Identification Methods Applied to Flexible Structures
Abdelghani, M.; Verhaegen, M.; Van Overschee, P.; De Moor, B.
1998-09-01
In the past few years, various time domain methods for identifying dynamic models of mechanical structures from modal experimental data have appeared. Much attention has been given recently to so-called subspace methods for identifying state space models. This paper presents a detailed comparison study of these subspace identification methods: the eigensystem realisation algorithm with observer/Kalman filter Markov parameters computed from input/output data (ERA/OM), the robust version of the numerical algorithm for subspace system identification (N4SID), and a refined version of the past outputs scheme of the multiple-output error state space (MOESP) family of algorithms. The comparison is performed by simulating experimental data using the five mode reduced model of the NASA Mini-Mast structure. The general conclusion is that for the case of white noise excitations as well as coloured noise excitations, the N4SID/MOESP algorithms perform equally well but give better results (improved transfer function estimates, improved estimates of the output) compared to the ERA/OM algorithm. The key computational step in the three algorithms is the approximation of the extended observability matrix of the system to be identified, for N4SID/MOESP, or of the observer for the system to be identified, for the ERA/OM. Furthermore, the three algorithms only require the specification of one dimensioning parameter.
Improved Stochastic Subspace System Identification for Structural Health Monitoring
Chang, Chia-Ming; Loh, Chin-Hsiung
2015-07-01
Structural health monitoring acquires structural information through numerous sensor measurements. Vibrational measurement data render the dynamic characteristics of structures to be extracted, in particular of the modal properties such as natural frequencies, damping, and mode shapes. The stochastic subspace system identification has been recognized as a power tool which can present a structure in the modal coordinates. To obtain qualitative identified data, this tool needs to spend computational expense on a large set of measurements. In study, a stochastic system identification framework is proposed to improve the efficiency and quality of the conventional stochastic subspace system identification. This framework includes 1) measured signal processing, 2) efficient space projection, 3) system order selection, and 4) modal property derivation. The measured signal processing employs the singular spectrum analysis algorithm to lower the noise components as well as to present a data set in a reduced dimension. The subspace is subsequently derived from the data set presented in a delayed coordinate. With the proposed order selection criteria, the number of structural modes is determined, resulting in the modal properties. This system identification framework is applied to a real-world bridge for exploring the feasibility in real-time applications. The results show that this improved system identification method significantly decreases computational time, while qualitative modal parameters are still attained.
Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles
Directory of Open Access Journals (Sweden)
Liying Yang
2016-01-01
Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.
Gamow state vectors as functionals over subspaces of the nuclear space
International Nuclear Information System (INIS)
Bohm, A.
1979-12-01
Exponentially decaying Gamow state vectors are obtained from S-matrix poles in the lower half of the second sheet, and are defined as functionals over a subspace of the nuclear space, PHI. Exponentially growing Gamow state vectors are obtained from S-matrix poles in the upper half of the second sheet, and are defined as functionals over another subspace of PHI. On functionals over these two subspaces the dynamical group of time development splits into two semigroups
A subspace approach to high-resolution spectroscopic imaging.
Lam, Fan; Liang, Zhi-Pei
2014-04-01
To accelerate spectroscopic imaging using sparse sampling of (k,t)-space and subspace (or low-rank) modeling to enable high-resolution metabolic imaging with good signal-to-noise ratio. The proposed method, called SPectroscopic Imaging by exploiting spatiospectral CorrElation, exploits a unique property known as partial separability of spectroscopic signals. This property indicates that high-dimensional spectroscopic signals reside in a very low-dimensional subspace and enables special data acquisition and image reconstruction strategies to be used to obtain high-resolution spatiospectral distributions with good signal-to-noise ratio. More specifically, a hybrid chemical shift imaging/echo-planar spectroscopic imaging pulse sequence is proposed for sparse sampling of (k,t)-space, and a low-rank model-based algorithm is proposed for subspace estimation and image reconstruction from sparse data with the capability to incorporate prior information and field inhomogeneity correction. The performance of the proposed method has been evaluated using both computer simulations and phantom studies, which produced very encouraging results. For two-dimensional spectroscopic imaging experiments on a metabolite phantom, a factor of 10 acceleration was achieved with a minimal loss in signal-to-noise ratio compared to the long chemical shift imaging experiments and with a significant gain in signal-to-noise ratio compared to the accelerated echo-planar spectroscopic imaging experiments. The proposed method, SPectroscopic Imaging by exploiting spatiospectral CorrElation, is able to significantly accelerate spectroscopic imaging experiments, making high-resolution metabolic imaging possible. Copyright © 2014 Wiley Periodicals, Inc.
Subspace-based analysis of the ERT inverse problem
Ben Hadj Miled, Mohamed Khames; Miller, Eric L.
2004-05-01
In a previous work, we proposed a source-type formulation to the electrical resistance tomography (ERT) problem. Specifically, we showed that inhomogeneities in the medium can be viewed as secondary sources embedded in the homogeneous background medium and located at positions associated with variation in electrical conductivity. Assuming a piecewise constant conductivity distribution, the support of equivalent sources is equal to the boundary of the inhomogeneity. The estimation of the anomaly shape takes the form of an inverse source-type problem. In this paper, we explore the use of subspace methods to localize the secondary equivalent sources associated with discontinuities in the conductivity distribution. Our first alternative is the multiple signal classification (MUSIC) algorithm which is commonly used in the localization of multiple sources. The idea is to project a finite collection of plausible pole (or dipole) sources onto an estimated signal subspace and select those with largest correlations. In ERT, secondary sources are excited simultaneously but in different ways, i.e. with distinct amplitude patterns, depending on the locations and amplitudes of primary sources. If the number of receivers is "large enough", different source configurations can lead to a set of observation vectors that span the data subspace. However, since sources that are spatially close to each other have highly correlated signatures, seperation of such signals becomes very difficult in the presence of noise. To overcome this problem we consider iterative MUSIC algorithms like R-MUSIC and RAP-MUSIC. These recursive algorithms pose a computational burden as they require multiple large combinatorial searches. Results obtained with these algorithms using simulated data of different conductivity patterns are presented.
Perturbation for Frames for a Subspace of a Hilbert Space
DEFF Research Database (Denmark)
Christensen, Ole; deFlicht, C.; Lennard, C.
1997-01-01
We extend a classical result stating that a sufficiently small perturbation$\\{ g_i \\}$ of a Riesz sequence $\\{ f_i \\}$ in a Hilbert space $H$ is again a Riesz sequence. It turns out that the analog result for a frame does not holdunless the frame is complete. However, we are able to prove a very...... similarresult for frames in the case where the gap between the subspaces$\\overline{span} \\{f_i \\}$ and $\\overline{span} \\{ g_i \\}$ is small enough. We give a geometric interpretation of the result....
International Nuclear Information System (INIS)
Warsa, James S.; Wareing, Todd A.; Morel, Jim E.
2004-01-01
A loss in the effectiveness of diffusion synthetic acceleration (DSA) schemes has been observed with certain S N discretizations on two-dimensional Cartesian grids in the presence of material discontinuities. We will present more evidence supporting the conjecture that DSA effectiveness will degrade for multidimensional problems with discontinuous total cross sections, regardless of the particular physical configuration or spatial discretization. Fourier analysis and numerical experiments help us identify a set of representative problems for which established DSA schemes are ineffective, focusing on diffusive problems for which DSA is most needed. We consider a lumped, linear discontinuous spatial discretization of the S N transport equation on three-dimensional, unstructured tetrahedral meshes and look at a fully consistent and a 'partially consistent' DSA method for this discretization. The effectiveness of both methods is shown to degrade significantly. A Fourier analysis of the fully consistent DSA scheme in the limit of decreasing cell optical thickness supports the view that the DSA itself is failing when material discontinuities are present in a problem. We show that a Krylov iterative method, preconditioned with DSA, is an effective remedy that can be used to efficiently compute solutions for this class of problems. We show that as a preconditioner to the Krylov method, a partially consistent DSA method is more than adequate. In fact, it is preferable to a fully consistent method because the partially consistent method is based on a continuous finite element discretization of the diffusion equation that can be solved relatively easily. The Krylov method can be implemented in terms of the original S N source iteration coding with only slight modification. Results from numerical experiments show that replacing source iteration with a preconditioned Krylov method can efficiently solve problems that are virtually intractable with accelerated source iteration
LogDet Rank Minimization with Application to Subspace Clustering
Directory of Open Access Journals (Sweden)
Zhao Kang
2015-01-01
Full Text Available Low-rank matrix is desired in many machine learning and computer vision problems. Most of the recent studies use the nuclear norm as a convex surrogate of the rank operator. However, all singular values are simply added together by the nuclear norm, and thus the rank may not be well approximated in practical problems. In this paper, we propose using a log-determinant (LogDet function as a smooth and closer, though nonconvex, approximation to rank for obtaining a low-rank representation in subspace clustering. Augmented Lagrange multipliers strategy is applied to iteratively optimize the LogDet-based nonconvex objective function on potentially large-scale data. By making use of the angular information of principal directions of the resultant low-rank representation, an affinity graph matrix is constructed for spectral clustering. Experimental results on motion segmentation and face clustering data demonstrate that the proposed method often outperforms state-of-the-art subspace clustering algorithms.
View subspaces for indexing and retrieval of 3D models
Dutagaci, Helin; Godil, Afzal; Sankur, Bülent; Yemez, Yücel
2010-02-01
View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithms.
Subspace methods for identification of human ankle joint stiffness.
Zhao, Y; Westwick, D T; Kearney, R E
2011-11-01
Joint stiffness, the dynamic relationship between the angular position of a joint and the torque acting about it, describes the dynamic, mechanical behavior of a joint during posture and movement. Joint stiffness arises from both intrinsic and reflex mechanisms, but the torques due to these mechanisms cannot be measured separately experimentally, since they appear and change together. Therefore, the direct estimation of the intrinsic and reflex stiffnesses is difficult. In this paper, we present a new, two-step procedure to estimate the intrinsic and reflex components of ankle stiffness. In the first step, a discrete-time, subspace-based method is used to estimate a state-space model for overall stiffness from the measured overall torque and then predict the intrinsic and reflex torques. In the second step, continuous-time models for the intrinsic and reflex stiffnesses are estimated from the predicted intrinsic and reflex torques. Simulations and experimental results demonstrate that the algorithm estimates the intrinsic and reflex stiffnesses accurately. The new subspace-based algorithm has three advantages over previous algorithms: 1) It does not require iteration, and therefore, will always converge to an optimal solution; 2) it provides better estimates for data with high noise or short sample lengths; and 3) it provides much more accurate results for data acquired under the closed-loop conditions, that prevail when subjects interact with compliant loads.
Beamforming using subspace estimation from a diagonally averaged sample covariance.
Quijano, Jorge E; Zurk, Lisa M
2017-08-01
The potential benefit of a large-aperture sonar array for high resolution target localization is often challenged by the lack of sufficient data required for adaptive beamforming. This paper introduces a Toeplitz-constrained estimator of the clairvoyant signal covariance matrix corresponding to multiple far-field targets embedded in background isotropic noise. The estimator is obtained by averaging along subdiagonals of the sample covariance matrix, followed by covariance extrapolation using the method of maximum entropy. The sample covariance is computed from limited data snapshots, a situation commonly encountered with large-aperture arrays in environments characterized by short periods of local stationarity. Eigenvectors computed from the Toeplitz-constrained covariance are used to construct signal-subspace projector matrices, which are shown to reduce background noise and improve detection of closely spaced targets when applied to subspace beamforming. Monte Carlo simulations corresponding to increasing array aperture suggest convergence of the proposed projector to the clairvoyant signal projector, thereby outperforming the classic projector obtained from the sample eigenvectors. Beamforming performance of the proposed method is analyzed using simulated data, as well as experimental data from the Shallow Water Array Performance experiment.
Structured Kernel Subspace Learning for Autonomous Robot Navigation.
Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai
2018-02-14
This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.
Enhancing Low-Rank Subspace Clustering by Manifold Regularization.
Liu, Junmin; Chen, Yijun; Zhang, JiangShe; Xu, Zongben
2014-07-25
Recently, low-rank representation (LRR) method has achieved great success in subspace clustering (SC), which aims to cluster the data points that lie in a union of low-dimensional subspace. Given a set of data points, LRR seeks the lowest rank representation among the many possible linear combinations of the bases in a given dictionary or in terms of the data itself. However, LRR only considers the global Euclidean structure, while the local manifold structure, which is often important for many real applications, is ignored. In this paper, to exploit the local manifold structure of the data, a manifold regularization characterized by a Laplacian graph has been incorporated into LRR, leading to our proposed Laplacian regularized LRR (LapLRR). An efficient optimization procedure, which is based on alternating direction method of multipliers (ADMM), is developed for LapLRR. Experimental results on synthetic and real data sets are presented to demonstrate that the performance of LRR has been enhanced by using the manifold regularization.
Wawro, Megan; Sweeney, George F.; Rabin, Jeffrey M.
2011-01-01
This paper reports on a study investigating students' ways of conceptualizing key ideas in linear algebra, with the particular results presented here focusing on student interactions with the notion of subspace. In interviews conducted with eight undergraduates, we found students' initial descriptions of subspace often varied substantially from…
Theoretical information reuse and integration
Rubin, Stuart
2016-01-01
Information Reuse and Integration addresses the efficient extension and creation of knowledge through the exploitation of Kolmogorov complexity in the extraction and application of domain symmetry. Knowledge, which seems to be novel, can more often than not be recast as the image of a sequence of transformations, which yield symmetric knowledge. When the size of those transformations and/or the length of that sequence of transforms exceeds the size of the image, then that image is said to be novel or random. It may also be that the new knowledge is random in that no such sequence of transforms, which produces it exists, or is at least known. The nine chapters comprising this volume incorporate symmetry, reuse, and integration as overt operational procedures or as operations built into the formal representations of data and operators employed. Either way, the aforementioned theoretical underpinnings of information reuse and integration are supported.
Preconditioned Krylov and Gauss-Seidel solutions of response matrix equations
International Nuclear Information System (INIS)
Lewis, E.E.; Smith, M.A.; Yang, W.S.; Wollaber, A.
2011-01-01
The use of preconditioned Krylov methods is examined as an alternative to the partitioned matrix acceleration applied to red-black Gauss Seidel (RBGS) iteration that is presently used in the variational nodal code, VARIANT. We employ the GMRES algorithm to treat non-symmetric response matrix equations. A pre conditioner is formulated for the within-group diffusion equation which is equivalent to partitioned matrix acceleration of RBGS iterations. We employ the pre conditioner, which closely parallels two-level p multigrid, to improve RBGS and GMRES algorithms. Of the accelerated algorithms, GMRES converges with less computational effort than RBGS and therefore is chosen for further development. The p multigrid pre conditioner requires response matrices with two or more degrees of freedom (DOF) per interface that are polynomials, which are both orthogonal and hierarchical. It is therefore not directly applicable to very fine mesh calculations that are both slow to converge and that are often modeled with response matrices with only one DOF per interface. Orthogonal matrix aggregation (OMA) is introduced to circumvent this difficulty by combining N×N fine mesh response matrices with one DOF per interface into a coarse mesh response matrix with N orthogonal DOF per interface. Numerical results show that OMA used alone or in combination with p multigrid preconditioning substantially accelerates GMRES solutions. (author)
Preconditioned Krylov and Gauss-Seidel solutions of response matrix equations
Energy Technology Data Exchange (ETDEWEB)
Lewis, E.E., E-mail: e-lewis@northwestern.edu [Department of Mechanical Engineering, Northwestern University, Evanston, IL (United States); Smith, M.A.; Yang, W.S.; Wollaber, A., E-mail: masmith@anl.gov, E-mail: wsyang@anl.gov, E-mail: wollaber@lanl.gov [Nuclear Engineering Division, Argonne National Laboratory, Argonne, IL (United States)
2011-07-01
The use of preconditioned Krylov methods is examined as an alternative to the partitioned matrix acceleration applied to red-black Gauss Seidel (RBGS) iteration that is presently used in the variational nodal code, VARIANT. We employ the GMRES algorithm to treat non-symmetric response matrix equations. A pre conditioner is formulated for the within-group diffusion equation which is equivalent to partitioned matrix acceleration of RBGS iterations. We employ the pre conditioner, which closely parallels two-level p multigrid, to improve RBGS and GMRES algorithms. Of the accelerated algorithms, GMRES converges with less computational effort than RBGS and therefore is chosen for further development. The p multigrid pre conditioner requires response matrices with two or more degrees of freedom (DOF) per interface that are polynomials, which are both orthogonal and hierarchical. It is therefore not directly applicable to very fine mesh calculations that are both slow to converge and that are often modeled with response matrices with only one DOF per interface. Orthogonal matrix aggregation (OMA) is introduced to circumvent this difficulty by combining N×N fine mesh response matrices with one DOF per interface into a coarse mesh response matrix with N orthogonal DOF per interface. Numerical results show that OMA used alone or in combination with p multigrid preconditioning substantially accelerates GMRES solutions. (author)
Water Reuse and Pathogen Tracking
Building product water. By designing our buildings to collect and treat water generated on-site, can be and reused for flushing our toilets and irrigating our landscaping. Several water sources are generated with-in a building including: rainwater, stormwater, graywater, blackwa...
Linear Subspace Ranking Hashing for Cross-Modal Retrieval.
Li, Kai; Qi, Guo-Jun; Ye, Jun; Hua, Kien A
2017-09-01
Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features' ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.
Attitudes and norms affecting scientists' data reuse.
Directory of Open Access Journals (Sweden)
Renata Gonçalves Curty
Full Text Available The value of sharing scientific research data is widely appreciated, but factors that hinder or prompt the reuse of data remain poorly understood. Using the Theory of Reasoned Action, we test the relationship between the beliefs and attitudes of scientists towards data reuse, and their self-reported data reuse behaviour. To do so, we used existing responses to selected questions from a worldwide survey of scientists developed and administered by the DataONE Usability and Assessment Working Group (thus practicing data reuse ourselves. Results show that the perceived efficacy and efficiency of data reuse are strong predictors of reuse behaviour, and that the perceived importance of data reuse corresponds to greater reuse. Expressed lack of trust in existing data and perceived norms against data reuse were not found to be major impediments for reuse contrary to our expectations. We found that reported use of models and remotely-sensed data was associated with greater reuse. The results suggest that data reuse would be encouraged and normalized by demonstration of its value. We offer some theoretical and practical suggestions that could help to legitimize investment and policies in favor of data sharing.
DETECTION OF CHANGES OF THE SYSTEM TECHNICAL STATE USING STOCHASTIC SUBSPACE OBSERVATION METHOD
Directory of Open Access Journals (Sweden)
Andrzej Puchalski
2014-03-01
Full Text Available System diagnostics based on vibroacoustics signals, carried out by means of stochastic subspace methods was undertaken in the hereby paper. Subspace methods are the ones based on numerical linear algebra tools. The considered solutions belong to diagnostic methods according to data, leading to the generation of residuals allowing failure recognition of elements and assemblies in machines and devices. The algorithm of diagnostics according to the subspace observation method was applied – in the paper – for the estimation of the valve system of the spark ignition engine.
The influence of different PAST-based subspace trackers on DaPT parameter estimation
Lechtenberg, M.; Götze, J.
2012-09-01
In the context of parameter estimation, subspace-based methods like ESPRIT have become common. They require a subspace separation e.g. based on eigenvalue/-vector decomposition. In time-varying environments, this can be done by subspace trackers. One class of these is based on the PAST algorithm. Our non-linear parameter estimation algorithm DaPT builds on-top of the ESPRIT algorithm. Evaluation of the different variants of the PAST algorithm shows which variant of the PAST algorithm is worthwhile in the context of frequency estimation.
Geometric subspace updates with applications to online adaptive nonlinear model reduction
DEFF Research Database (Denmark)
Zimmermann, Ralf; Peherstorfer, Benjamin; Willcox, Karen
2018-01-01
In many scientific applications, including model reduction and image processing, subspaces are used as ansatz spaces for the low-dimensional approximation and reconstruction of the state vectors of interest. We introduce a procedure for adapting an existing subspace based on information from...... Estimation (GROUSE). We establish for GROUSE a closed-form expression for the residual function along the geodesic descent direction. Specific applications of subspace adaptation are discussed in the context of image processing and model reduction of nonlinear partial differential equation systems....
Reynolds, Daniel R.
2012-01-01
Single-fluid resistive magnetohydrodynamics (MHD) is a fluid description of fusion plasmas which is often used to investigate macroscopic instabilities in tokamaks. In MHD modeling of tokamaks, it is often desirable to compute MHD phenomena to resistive time scales or a combination of resistive-Alfvén time scales, which can render explicit time stepping schemes computationally expensive. We present recent advancements in the development of preconditioners for fully nonlinearly implicit simulations of single-fluid resistive tokamak MHD. Our work focuses on simulations using a structured mesh mapped into a toroidal geometry with a shaped poloidal cross-section, and a finite-volume spatial discretization of the partial differential equation model. We discretize the temporal dimension using a fully implicit or the backwards differentiation formula method, and solve the resulting nonlinear algebraic system using a standard inexact Newton-Krylov approach, provided by the sundials library. The focus of this paper is on the construction and performance of various preconditioning approaches for accelerating the convergence of the iterative solver algorithms. Effective preconditioners require information about the Jacobian entries; however, analytical formulae for these Jacobian entries may be prohibitive to derive/implement without error. We therefore compute these entries using automatic differentiation with OpenAD. We then investigate a variety of preconditioning formulations inspired by standard solution approaches in modern MHD codes, in order to investigate their utility in a preconditioning context. We first describe the code modifications necessary for the use of the OpenAD tool and sundials solver library. We conclude with numerical results for each of our preconditioning approaches in the context of pellet-injection fueling of tokamak plasmas. Of these, our optimal approach results in a speedup of a factor of 3 compared with non-preconditioned implicit tests, with
Ionizing radiation and water reuse
International Nuclear Information System (INIS)
Borrely, Sueli Ivone; Sampa, Maria Helena de Oliveira; Oikawa, Hiroshi; Silveira, Carlos Gaia da; Duarte, Celina Lopes; Cherbakian, Eloisa Helena
2002-01-01
The aim of the present paper is to point out the possibility of including ionizing radiation for wastewater treatment and reuse. Radiation processing is an efficient technology which can be useful for water reuse once the process can reduce not only the biological contamination but also organic substances, promoting an important acute toxicity removal from aquatic resources. Final secondary effluents from three different wastewater treatment plant were submitted to electron beam radiation and the process efficacy was evaluated. Concerning disinfection, relatively low radiation doses (2,0 - 4,0 kGy) accounted for 4 to 6 cycle log reduction for total coliforms. When radiation was applied for general wastewater improvement related to the chemical contamination, radiation process reduced from 78% up to 100% the total acute toxicity, measured for crustaceans, D. similis, and for V. fiscehri bacteria. (author)
Energy Technology Data Exchange (ETDEWEB)
Wang, Yaqi; Rabiti, Cristian; Palmiotti, Giuseppe, E-mail: yaqi.wang@inl.gov, E-mail: cristian.rabiti@inl.gov, E-mail: giuseppe.palmiotti@inl.gov [Idaho National Laboratory, Idaho Falls, ID (United States)
2011-07-01
This paper proposes a new set of Krylov solvers, CG and GMRes, as an alternative of the Red-Black (RB) algorithm on on solving the steady-state one-speed neutron transport equation discretized with PN in angle and hybrid FEM (Finite Element Method) in space. A pre conditioner with the low-order RB iteration is designed to improve their convergence. These Krylov solvers can reduce the cost of pre-assembling the response matrices greatly. Numerical results with the INSTANT code are presented in order to show that they can be a good supplement on solving the PN-HFEM system. (author)
International Nuclear Information System (INIS)
Wang, Yaqi; Rabiti, Cristian; Palmiotti, Giuseppe
2011-01-01
This paper proposes a new set of Krylov solvers, CG and GMRes, as an alternative of the Red-Black (RB) algorithm on on solving the steady-state one-speed neutron transport equation discretized with PN in angle and hybrid FEM (Finite Element Method) in space. A pre conditioner with the low-order RB iteration is designed to improve their convergence. These Krylov solvers can reduce the cost of pre-assembling the response matrices greatly. Numerical results with the INSTANT code are presented in order to show that they can be a good supplement on solving the PN-HFEM system. (author)
Formalisms for reuse and systems integration
Rubin, Stuart
2015-01-01
Reuse and integration are defined as synergistic concepts, where reuse addresses how to minimize redundancy in the creation of components; while, integration focuses on component composition. Integration supports reuse and vice versa. These related concepts support the design of software and systems for maximizing performance while minimizing cost. Knowledge, like data, is subject to reuse; and, each can be interpreted as the other. This means that inherent complexity, a measure of the potential utility of a system, is directly proportional to the extent to which it maximizes reuse and integration. Formal methods can provide an appropriate context for the rigorous handling of these synergistic concepts. Furthermore, formal languages allow for non ambiguous model specification; and, formal verification techniques provide support for insuring the validity of reuse and integration mechanisms. This edited book includes 12 high quality research papers written by experts in formal aspects of reuse and integratio...
MULTI-LABEL ASRS DATASET CLASSIFICATION USING SEMI-SUPERVISED SUBSPACE CLUSTERING
National Aeronautics and Space Administration — MULTI-LABEL ASRS DATASET CLASSIFICATION USING SEMI-SUPERVISED SUBSPACE CLUSTERING MOHAMMAD SALIM AHMED, LATIFUR KHAN, NIKUNJ OZA, AND MANDAVA RAJESWARI Abstract....
A Comparative Study for Orthogonal Subspace Projection and Constrained Energy Minimization
National Research Council Canada - National Science Library
Du, Qian; Ren, Hsuan; Chang, Chein-I
2003-01-01
...: orthogonal subspace projection (OSP) and constrained energy minimization (CEM). It is shown that they are closely related and essentially equivalent provided that the noise is white with large SNR...
Closed and Open Loop Subspace System Identification of the Kalman Filter
Directory of Open Access Journals (Sweden)
David Di Ruscio
2009-04-01
Full Text Available Some methods for consistent closed loop subspace system identification presented in the literature are analyzed and compared to a recently published subspace algorithm for both open as well as for closed loop data, the DSR_e algorithm. Some new variants of this algorithm are presented and discussed. Simulation experiments are included in order to illustrate if the algorithms are variance efficient or not.
Directory of Open Access Journals (Sweden)
Sebastian Gim
2012-11-01
Full Text Available Continued device scaling into the nanometer region and high frequencies of operation well into the multi-GHz region has given rise to new effects that previously had negligible impact but now present greater challenges and unprecedented complexity to designing successful mixed-signal silicon. The Chameleon-RF project was conceived to address these challenges. Creative use of domain decomposition, multi grid techniques or reduced order modeling techniques (ROM can be selectively applied at all levels of the process to efficiently prune down degrees of freedom (DoFs. However, the simulation of complex systems within a reasonable amount of time remains a computational challenge. This paper presents work done in the incorporation of GPGPU technology to accelerate Krylov based algorithms used for compact modeling of on-chip passive integrated structures within the workflow of the Chameleon-RF project. Based upon insight gained from work done above, a novel GPGPU accelerated algorithm was developed for the Krylov ROM (kROM methods and is described here for the benefit of the wider community.
Turcksin, Bruno; Ragusa, Jean C.; Morel, Jim E.
2012-01-01
It is well known that the diffusion synthetic acceleration (DSA) methods for the Sn equations become ineffective in the Fokker-Planck forward-peaked scattering limit. In response to this deficiency, Morel and Manteuffel (1991) developed an angular multigrid method for the 1-D Sn equations. This method is very effective, costing roughly twice as much as DSA per source iteration, and yielding a maximum spectral radius of approximately 0.6 in the Fokker-Planck limit. Pautz, Adams, and Morel (PAM) (1999) later generalized the angular multigrid to 2-D, but it was found that the method was unstable with sufficiently forward-peaked mappings between the angular grids. The method was stabilized via a filtering technique based on diffusion operators, but this filtering also degraded the effectiveness of the overall scheme. The spectral radius was not bounded away from unity in the Fokker-Planck limit, although the method remained more effective than DSA. The purpose of this article is to recast the multidimensional PAM angular multigrid method without the filtering as an Sn preconditioner and use it in conjunction with the Generalized Minimal RESidual (GMRES) Krylov method. The approach ensures stability and our computational results demonstrate that it is also significantly more efficient than an analogous DSA-preconditioned Krylov method.
Value-based management of design reuse
Carballo, Juan Antonio; Cohn, David L.; Belluomini, Wendy; Montoye, Robert K.
2003-06-01
Effective design reuse in electronic products has the potential to provide very large cost savings, substantial time-to-market reduction, and extra sources of revenue. Unfortunately, critical reuse opportunities are often missed because, although they provide clear value to the corporation, they may not benefit the business performance of an internal organization. It is therefore crucial to provide tools to help reuse partners participate in a reuse transaction when the transaction provides value to the corporation as a whole. Value-based Reuse Management (VRM) addresses this challenge by (a) ensuring that all parties can quickly assess the business performance impact of a reuse opportunity, and (b) encouraging high-value reuse opportunities by supplying value-based rewards to potential parties. In this paper we introduce the Value-Based Reuse Management approach and we describe key results on electronic designs that demonstrate its advantages. Our results indicate that Value-Based Reuse Management has the potential to significantly increase the success probability of high-value electronic design reuse.
Overview of hybrid subspace methods for uncertainty quantification, sensitivity analysis
International Nuclear Information System (INIS)
Abdel-Khalik, Hany S.; Bang, Youngsuk; Wang, Congjian
2013-01-01
Highlights: ► We overview the state-of-the-art in uncertainty quantification and sensitivity analysis. ► We overview new developments in above areas using hybrid methods. ► We give a tutorial introduction to above areas and the new developments. ► Hybrid methods address the explosion in dimensionality in nonlinear models. ► Representative numerical experiments are given. -- Abstract: The role of modeling and simulation has been heavily promoted in recent years to improve understanding of complex engineering systems. To realize the benefits of modeling and simulation, concerted efforts in the areas of uncertainty quantification and sensitivity analysis are required. The manuscript intends to serve as a pedagogical presentation of the material to young researchers and practitioners with little background on the subjects. We believe this is important as the role of these subjects is expected to be integral to the design, safety, and operation of existing as well as next generation reactors. In addition to covering the basics, an overview of the current state-of-the-art will be given with particular emphasis on the challenges pertaining to nuclear reactor modeling. The second objective will focus on presenting our own development of hybrid subspace methods intended to address the explosion in the computational overhead required when handling real-world complex engineering systems.
Subspace identification of Hammer stein models using support vector machines
International Nuclear Information System (INIS)
Al-Dhaifallah, Mujahed
2011-01-01
System identification is the art of finding mathematical tools and algorithms that build an appropriate mathematical model of a system from measured input and output data. Hammerstein model, consisting of a memoryless nonlinearity followed by a dynamic linear element, is often a good trade-off as it can represent some dynamic nonlinear systems very accurately, but is nonetheless quite simple. Moreover, the extensive knowledge about LTI system representations can be applied to the dynamic linear block. On the other hand, finding an effective representation for the nonlinearity is an active area of research. Recently, support vector machines (SVMs) and least squares support vector machines (LS-SVMs) have demonstrated powerful abilities in approximating linear and nonlinear functions. In contrast with other approximation methods, SVMs do not require a-priori structural information. Furthermore, there are well established methods with guaranteed convergence (ordinary least squares, quadratic programming) for fitting LS-SVMs and SVMs. The general objective of this research is to develop new subspace algorithms for Hammerstein systems based on SVM regression.
MODAL TRACKING of A Structural Device: A Subspace Identification Approach
Energy Technology Data Exchange (ETDEWEB)
Candy, J. V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Franco, S. N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ruggiero, E. L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Emmons, M. C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Lopez, I. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Stoops, L. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2017-03-20
Mechanical devices operating in an environment contaminated by noise, uncertainties, and extraneous disturbances lead to low signal-to-noise-ratios creating an extremely challenging processing problem. To detect/classify a device subsystem from noisy data, it is necessary to identify unique signatures or particular features. An obvious feature would be resonant (modal) frequencies emitted during its normal operation. In this report, we discuss a model-based approach to incorporate these physical features into a dynamic structure that can be used for such an identification. The approach we take after pre-processing the raw vibration data and removing any extraneous disturbances is to obtain a representation of the structurally unknown device along with its subsystems that capture these salient features. One approach is to recognize that unique modal frequencies (sinusoidal lines) appear in the estimated power spectrum that are solely characteristic of the device under investigation. Therefore, the objective of this effort is based on constructing a black box model of the device that captures these physical features that can be exploited to “diagnose” whether or not the particular device subsystem (track/detect/classify) is operating normally from noisy vibrational data. Here we discuss the application of a modern system identification approach based on stochastic subspace realization techniques capable of both (1) identifying the underlying black-box structure thereby enabling the extraction of structural modes that can be used for analysis and modal tracking as well as (2) indicators of condition and possible changes from normal operation.
Removing Ocular Movement Artefacts by a Joint Smoothened Subspace Estimator
Directory of Open Access Journals (Sweden)
Ronald Phlypo
2007-01-01
Full Text Available To cope with the severe masking of background cerebral activity in the electroencephalogram (EEG by ocular movement artefacts, we present a method which combines lower-order, short-term and higher-order, long-term statistics. The joint smoothened subspace estimator (JSSE calculates the joint information in both statistical models, subject to the constraint that the resulting estimated source should be sufficiently smooth in the time domain (i.e., has a large autocorrelation or self predictive power. It is shown that the JSSE is able to estimate a component from simulated data that is superior with respect to methodological artefact suppression to those of FastICA, SOBI, pSVD, or JADE/COM1 algorithms used for blind source separation (BSS. Interference and distortion suppression are of comparable order when compared with the above-mentioned methods. Results on patient data demonstrate that the method is able to suppress blinking and saccade artefacts in a fully automated way.
Optimal Design of Large Dimensional Adaptive Subspace Detectors
Ben Atitallah, Ismail
2016-05-27
This paper addresses the design of Adaptive Subspace Matched Filter (ASMF) detectors in the presence of a mismatch in the steering vector. These detectors are coined as adaptive in reference to the step of utilizing an estimate of the clutter covariance matrix using training data of signalfree observations. To estimate the clutter covariance matrix, we employ regularized covariance estimators that, by construction, force the eigenvalues of the covariance estimates to be greater than a positive scalar . While this feature is likely to increase the bias of the covariance estimate, it presents the advantage of improving its conditioning, thus making the regularization suitable for handling high dimensional regimes. In this paper, we consider the setting of the regularization parameter and the threshold for ASMF detectors in both Gaussian and Compound Gaussian clutters. In order to allow for a proper selection of these parameters, it is essential to analyze the false alarm and detection probabilities. For tractability, such a task is carried out under the asymptotic regime in which the number of observations and their dimensions grow simultaneously large, thereby allowing us to leverage existing results from random matrix theory. Simulation results are provided in order to illustrate the relevance of the proposed design strategy and to compare the performances of the proposed ASMF detectors versus Adaptive normalized Matched Filter (ANMF) detectors under mismatch scenarios.
Optimal Design of Large Dimensional Adaptive Subspace Detectors
Ben Atitallah, Ismail; Kammoun, Abla; Alouini, Mohamed-Slim; Alnaffouri, Tareq Y.
2016-01-01
This paper addresses the design of Adaptive Subspace Matched Filter (ASMF) detectors in the presence of a mismatch in the steering vector. These detectors are coined as adaptive in reference to the step of utilizing an estimate of the clutter covariance matrix using training data of signalfree observations. To estimate the clutter covariance matrix, we employ regularized covariance estimators that, by construction, force the eigenvalues of the covariance estimates to be greater than a positive scalar . While this feature is likely to increase the bias of the covariance estimate, it presents the advantage of improving its conditioning, thus making the regularization suitable for handling high dimensional regimes. In this paper, we consider the setting of the regularization parameter and the threshold for ASMF detectors in both Gaussian and Compound Gaussian clutters. In order to allow for a proper selection of these parameters, it is essential to analyze the false alarm and detection probabilities. For tractability, such a task is carried out under the asymptotic regime in which the number of observations and their dimensions grow simultaneously large, thereby allowing us to leverage existing results from random matrix theory. Simulation results are provided in order to illustrate the relevance of the proposed design strategy and to compare the performances of the proposed ASMF detectors versus Adaptive normalized Matched Filter (ANMF) detectors under mismatch scenarios.
Supervised orthogonal discriminant subspace projects learning for face recognition.
Chen, Yu; Xu, Xiao-Hong
2014-02-01
In this paper, a new linear dimension reduction method called supervised orthogonal discriminant subspace projection (SODSP) is proposed, which addresses high-dimensionality of data and the small sample size problem. More specifically, given a set of data points in the ambient space, a novel weight matrix that describes the relationship between the data points is first built. And in order to model the manifold structure, the class information is incorporated into the weight matrix. Based on the novel weight matrix, the local scatter matrix as well as non-local scatter matrix is defined such that the neighborhood structure can be preserved. In order to enhance the recognition ability, we impose an orthogonal constraint into a graph-based maximum margin analysis, seeking to find a projection that maximizes the difference, rather than the ratio between the non-local scatter and the local scatter. In this way, SODSP naturally avoids the singularity problem. Further, we develop an efficient and stable algorithm for implementing SODSP, especially, on high-dimensional data set. Moreover, the theoretical analysis shows that LPP is a special instance of SODSP by imposing some constraints. Experiments on the ORL, Yale, Extended Yale face database B and FERET face database are performed to test and evaluate the proposed algorithm. The results demonstrate the effectiveness of SODSP. Copyright © 2013 Elsevier Ltd. All rights reserved.
A Variational Approach to Video Registration with Subspace Constraints.
Garg, Ravi; Roussos, Anastasios; Agapito, Lourdes
2013-01-01
This paper addresses the problem of non-rigid video registration, or the computation of optical flow from a reference frame to each of the subsequent images in a sequence, when the camera views deformable objects. We exploit the high correlation between 2D trajectories of different points on the same non-rigid surface by assuming that the displacement of any point throughout the sequence can be expressed in a compact way as a linear combination of a low-rank motion basis. This subspace constraint effectively acts as a trajectory regularization term leading to temporally consistent optical flow. We formulate it as a robust soft constraint within a variational framework by penalizing flow fields that lie outside the low-rank manifold. The resulting energy functional can be decoupled into the optimization of the brightness constancy and spatial regularization terms, leading to an efficient optimization scheme. Additionally, we propose a novel optimization scheme for the case of vector valued images, based on the dualization of the data term. This allows us to extend our approach to deal with colour images which results in significant improvements on the registration results. Finally, we provide a new benchmark dataset, based on motion capture data of a flag waving in the wind, with dense ground truth optical flow for evaluation of multi-frame optical flow algorithms for non-rigid surfaces. Our experiments show that our proposed approach outperforms state of the art optical flow and dense non-rigid registration algorithms.
ICT reuse in socio-economic enterprises
International Nuclear Information System (INIS)
Ongondo, F.O.; Williams, I.D.; Dietrich, J.; Carroll, C.
2013-01-01
Highlights: • We analyse ICT equipment reuse operations of socio-economic enterprises. • Most common ICT products dealt with are computers and related equipment. • In the UK in 2010, ∼143,750 appliances were reused. • Marketing and legislative difficulties are the common hurdles to reuse activities. • Socio-economic enterprises can significantly contribute to resource efficiency. - Abstract: In Europe, socio-economic enterprises such as charities, voluntary organisations and not-for-profit companies are involved in the repair, refurbishment and reuse of various products. This paper characterises and analyses the operations of socio-economic enterprises that are involved in the reuse of Information and Communication Technology (ICT) equipment. Using findings from a survey, the paper specifically analyses the reuse activities of socio-economic enterprises in the UK from which Europe-wide conclusions are drawn. The amount of ICT products handled by the reuse organisations is quantified and potential barriers and opportunities to their operations are analysed. By-products from reuse activities are discussed and recommendations to improve reuse activities are provided. The most common ICT products dealt with by socio-economic enterprises are computers and related equipment. In the UK in 2010, an estimated 143,750 appliances were reused. However, due to limitations in data, it is difficult to compare this number to the amount of new appliances that entered the UK market or the amount of waste electrical and electronic equipment generated in the same period. Difficulties in marketing products and numerous legislative requirements are the most common barriers to reuse operations. Despite various constraints, it is clear that organisations involved in reuse of ICT could contribute significantly to resource efficiency and a circular economy. It is suggested that clustering of their operations into “reuse parks” would enhance both their profile and their
ICT reuse in socio-economic enterprises
Energy Technology Data Exchange (ETDEWEB)
Ongondo, F.O., E-mail: f.ongondo@soton.ac.uk [Centre for Environmental Sciences, Faculty of Engineering and the Environment, Lanchester Building, University of Southampton, University Rd., Highfield, Southampton, Hampshire SO17 1BJ (United Kingdom); Williams, I.D. [Centre for Environmental Sciences, Faculty of Engineering and the Environment, Lanchester Building, University of Southampton, University Rd., Highfield, Southampton, Hampshire SO17 1BJ (United Kingdom); Dietrich, J. [Technische Universität Berlin, Centre for Scientific Continuing Education and Cooperation, Cooperation and Consulting for Environmental Questions (kubus) FH10-1, Fraunhoferstraße 33-36, 10587 Berlin (Germany); Carroll, C. [Centre for Environmental Sciences, Faculty of Engineering and the Environment, Lanchester Building, University of Southampton, University Rd., Highfield, Southampton, Hampshire SO17 1BJ (United Kingdom)
2013-12-15
Highlights: • We analyse ICT equipment reuse operations of socio-economic enterprises. • Most common ICT products dealt with are computers and related equipment. • In the UK in 2010, ∼143,750 appliances were reused. • Marketing and legislative difficulties are the common hurdles to reuse activities. • Socio-economic enterprises can significantly contribute to resource efficiency. - Abstract: In Europe, socio-economic enterprises such as charities, voluntary organisations and not-for-profit companies are involved in the repair, refurbishment and reuse of various products. This paper characterises and analyses the operations of socio-economic enterprises that are involved in the reuse of Information and Communication Technology (ICT) equipment. Using findings from a survey, the paper specifically analyses the reuse activities of socio-economic enterprises in the UK from which Europe-wide conclusions are drawn. The amount of ICT products handled by the reuse organisations is quantified and potential barriers and opportunities to their operations are analysed. By-products from reuse activities are discussed and recommendations to improve reuse activities are provided. The most common ICT products dealt with by socio-economic enterprises are computers and related equipment. In the UK in 2010, an estimated 143,750 appliances were reused. However, due to limitations in data, it is difficult to compare this number to the amount of new appliances that entered the UK market or the amount of waste electrical and electronic equipment generated in the same period. Difficulties in marketing products and numerous legislative requirements are the most common barriers to reuse operations. Despite various constraints, it is clear that organisations involved in reuse of ICT could contribute significantly to resource efficiency and a circular economy. It is suggested that clustering of their operations into “reuse parks” would enhance both their profile and their
Factors affecting reuse of wastewater
Energy Technology Data Exchange (ETDEWEB)
Haraszti, L
1981-01-01
Changing the quality of circulating water, raising the effectiveness of sedimentation, examples of biological treatment of wastewater are presented. The necessity of continuing the studies on biological treatment of wastewater is demonstrated. It is considered useful to define the importance of KhPK and BP5 in each case. During biological treatment in ponds, to define the relation BPK5:N:P, research on conditions for nutrient removal must be done. To do this, as well as decrease the significance of KhPK, a mathematical model for defining the effectiveness of biological treatment of wastewater and consequently their reuse must be developed.
Increasing productivity through Total Reuse Management (TRM)
Schuler, M. P.
1991-01-01
Total Reuse Management (TRM) is a new concept currently being promoted by the NASA Langley Software Engineering and Ada Lab (SEAL). It uses concepts similar to those promoted in Total Quality Management (TQM). Both technical and management personnel are continually encouraged to think in terms of reuse. Reuse is not something that is aimed for after a product is completed, but rather it is built into the product from inception through development. Lowering software development costs, reducing risk, and increasing code reliability are the more prominent goals of TRM. Procedures and methods used to adopt and apply TRM are described. Reuse is frequently thought of as only being applicable to code. However, reuse can apply to all products and all phases of the software life cycle. These products include management and quality assurance plans, designs, and testing procedures. Specific examples of successfully reused products are given and future goals are discussed.
Software reuse example and challenges at NSIDC
Billingsley, B. W.; Brodzik, M.; Collins, J. A.
2009-12-01
NSIDC has created a new data discovery and access system, Searchlight, to provide users with the data they want in the format they want. NSIDC Searchlight supports discovery and access to disparate data types with on-the-fly reprojection, regridding and reformatting. Architected to both reuse open source systems and be reused itself, Searchlight reuses GDAL and Proj4 for manipulating data and format conversions, the netCDF Java library for creating netCDF output, MapServer and OpenLayers for defining spatial criteria and the JTS Topology Suite (JTS) in conjunction with Hibernate Spatial for database interaction and rich OGC-compliant spatial objects. The application reuses popular Java and Java Script libraries including Struts 2, Spring, JPA (Hibernate), Sitemesh, JFreeChart, JQuery, DOJO and a PostGIS PostgreSQL database. Future reuse of Searchlight components is supported at varying architecture levels, ranging from the database and model components to web services. We present the tools, libraries and programs that Searchlight has reused. We describe the architecture of Searchlight and explain the strategies deployed for reusing existing software and how Searchlight is built for reuse. We will discuss NSIDC reuse of the Searchlight components to support rapid development of new data delivery systems.
Reuse of hydroponic waste solution.
Kumar, Ramasamy Rajesh; Cho, Jae Young
2014-01-01
Attaining sustainable agriculture is a key goal in many parts of the world. The increased environmental awareness and the ongoing attempts to execute agricultural practices that are economically feasible and environmentally safe promote the use of hydroponic cultivation. Hydroponics is a technology for growing plants in nutrient solutions with or without the use of artificial medium to provide mechanical support. Major problems for hydroponic cultivation are higher operational cost and the causing of pollution due to discharge of waste nutrient solution. The nutrient effluent released into the environment can have negative impacts on the surrounding ecosystems as well as the potential to contaminate the groundwater utilized by humans for drinking purposes. The reuse of non-recycled, nutrient-rich hydroponic waste solution for growing plants in greenhouses is the possible way to control environmental pollution. Many researchers have successfully grown several plant species in hydroponic waste solution with high yield. Hence, this review addresses the problems associated with the release of hydroponic waste solution into the environment and possible reuse of hydroponic waste solution as an alternative resource for agriculture development and to control environmental pollution.
Conjunctive patches subspace learning with side information for collaborative image retrieval.
Zhang, Lining; Wang, Lipo; Lin, Weisi
2012-08-01
Content-Based Image Retrieval (CBIR) has attracted substantial attention during the past few years for its potential practical applications to image management. A variety of Relevance Feedback (RF) schemes have been designed to bridge the semantic gap between the low-level visual features and the high-level semantic concepts for an image retrieval task. Various Collaborative Image Retrieval (CIR) schemes aim to utilize the user historical feedback log data with similar and dissimilar pairwise constraints to improve the performance of a CBIR system. However, existing subspace learning approaches with explicit label information cannot be applied for a CIR task, although the subspace learning techniques play a key role in various computer vision tasks, e.g., face recognition and image classification. In this paper, we propose a novel subspace learning framework, i.e., Conjunctive Patches Subspace Learning (CPSL) with side information, for learning an effective semantic subspace by exploiting the user historical feedback log data for a CIR task. The CPSL can effectively integrate the discriminative information of labeled log images, the geometrical information of labeled log images and the weakly similar information of unlabeled images together to learn a reliable subspace. We formally formulate this problem into a constrained optimization problem and then present a new subspace learning technique to exploit the user historical feedback log data. Extensive experiments on both synthetic data sets and a real-world image database demonstrate the effectiveness of the proposed scheme in improving the performance of a CBIR system by exploiting the user historical feedback log data.
Extending the subspace hybrid method for eigenvalue problems in reactor physics calculation
International Nuclear Information System (INIS)
Zhang, Q.; Abdel-Khalik, H. S.
2013-01-01
This paper presents an innovative hybrid Monte-Carlo-Deterministic method denoted by the SUBSPACE method designed for improving the efficiency of hybrid methods for reactor analysis applications. The SUBSPACE method achieves its high computational efficiency by taking advantage of the existing correlations between desired responses. Recently, significant gains in computational efficiency have been demonstrated using this method for source driven problems. Within this work the mathematical theory behind the SUBSPACE method is introduced and extended to address core wide level k-eigenvalue problems. The method's efficiency is demonstrated based on a three-dimensional quarter-core problem, where responses are sought on the pin cell level. The SUBSPACE method is compared to the FW-CADIS method and is found to be more efficient for the utilized test problem because of the reason that the FW-CADIS method solves a forward eigenvalue problem and an adjoint fixed-source problem while the SUBSPACE method only solves an adjoint fixed-source problem. Based on the favorable results obtained here, we are confident that the applicability of Monte Carlo for large scale reactor analysis could be realized in the near future. (authors)
Subspace-Based Holistic Registration for Low-Resolution Facial Images
Directory of Open Access Journals (Sweden)
Boom BJ
2010-01-01
Full Text Available Subspace-based holistic registration is introduced as an alternative to landmark-based face registration, which has a poor performance on low-resolution images, as obtained in camera surveillance applications. The proposed registration method finds the alignment by maximizing the similarity score between a probe and a gallery image. We use a novel probabilistic framework for both user-independent as well as user-specific face registration. The similarity is calculated using the probability that the face image is correctly aligned in a face subspace, but additionally we take the probability into account that the face is misaligned based on the residual error in the dimensions perpendicular to the face subspace. We perform extensive experiments on the FRGCv2 database to evaluate the impact that the face registration methods have on face recognition. Subspace-based holistic registration on low-resolution images can improve face recognition in comparison with landmark-based registration on high-resolution images. The performance of the tested face recognition methods after subspace-based holistic registration on a low-resolution version of the FRGC database is similar to that after manual registration.
SEL Ada reuse analysis and representations
Kester, Rush
1990-01-01
Overall, it was revealed that the pattern of Ada reuse has evolved from initial reuse of utility components into reuse of generalized application architectures. Utility components were both domain-independent utilities, such as queues and stacks, and domain-specific utilities, such as those that implement spacecraft orbit and attitude mathematical functions and physics or astronomical models. The level of reuse was significantly increased with the development of a generalized telemetry simulator architecture. The use of Ada generics significantly increased the level of verbatum reuse, which is due to the ability, using Ada generics, to parameterize the aspects of design that are configurable during reuse. A key factor in implementing generalized architectures was the ability to use generic subprogram parameters to tailor parts of the algorithm embedded within the architecture. The use of object oriented design (in which objects model real world entities) significantly improved the modularity for reuse. Encapsulating into packages the data and operations associated with common real world entities creates natural building blocks for reuse.
Energy Technology Data Exchange (ETDEWEB)
Joseph, Ilon [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-05-27
Jacobian-free Newton-Krylov (JFNK) algorithms are a potentially powerful class of methods for solving the problem of coupling codes that address dfferent physics models. As communication capability between individual submodules varies, different choices of coupling algorithms are required. The more communication that is available, the more possible it becomes to exploit the simple sparsity pattern of the Jacobian, albeit of a large system. The less communication that is available, the more dense the Jacobian matrices become and new types of preconditioners must be sought to efficiently take large time steps. In general, methods that use constrained or reduced subsystems can offer a compromise in complexity. The specific problem of coupling a fluid plasma code to a kinetic neutrals code is discussed as an example.
ICT reuse in socio-economic enterprises.
Ongondo, F O; Williams, I D; Dietrich, J; Carroll, C
2013-12-01
In Europe, socio-economic enterprises such as charities, voluntary organisations and not-for-profit companies are involved in the repair, refurbishment and reuse of various products. This paper characterises and analyses the operations of socio-economic enterprises that are involved in the reuse of Information and Communication Technology (ICT) equipment. Using findings from a survey, the paper specifically analyses the reuse activities of socio-economic enterprises in the U.K. from which Europe-wide conclusions are drawn. The amount of ICT products handled by the reuse organisations is quantified and potential barriers and opportunities to their operations are analysed. By-products from reuse activities are discussed and recommendations to improve reuse activities are provided. The most common ICT products dealt with by socio-economic enterprises are computers and related equipment. In the U.K. in 2010, an estimated 143,750 appliances were reused. However, due to limitations in data, it is difficult to compare this number to the amount of new appliances that entered the U.K. market or the amount of waste electrical and electronic equipment generated in the same period. Difficulties in marketing products and numerous legislative requirements are the most common barriers to reuse operations. Despite various constraints, it is clear that organisations involved in reuse of ICT could contribute significantly to resource efficiency and a circular economy. It is suggested that clustering of their operations into "reuse parks" would enhance both their profile and their products. Reuse parks would also improve consumer confidence in and subsequently sales of the products. Further, it is advocated that industrial networking opportunities for the exchange of by-products resulting from the organisations' activities should be investigated. The findings make two significant contributions to the current literature. One, they provide a detailed insight into the reuse operations
Re-use of disposable coil dialysers
International Nuclear Information System (INIS)
Abbud Filho, M.
1980-01-01
Re-use of disposable dialysers has been in practice for over 16 years throughout the world but it still is a polemical subject. The main justification for it is the reduction of costs in the hemodialytic treatment. We evaluated the technique of re-use that we adopt by studying 33 patients who should re-utilize coil dialysers for 8 consecutive hemodialysis sessions. We investigated: 1) small and middle molecules clearances trough a radioisotopic method; 2) the integrity of the system regarding bacterial invasion; 3) the frequency of anti-N antibodies; 4) aspects of scanning electron microscopy (SEM) of dialysis membrane after re-use. We observed no changes in the dialysers performance during re-use. We conclude that the re-use of dialyzers is feasible, without risks for the patients, allowing marked reduction of costs, thus making possible to offer treatment to a larger number of uremic patients. (author)
In-Depth Case Studies of Superfund Reuse
SRI’s in-depth case studies explore Superfund reuse stories from start to finish. Their purpose is to see what redevelopment strategies worked, acknowledge reuse barriers and understand how communities overcame the barriers to create new reuse outcomes.
Persymmetric Adaptive Detectors of Subspace Signals in Homogeneous and Partially Homogeneous Clutter
Directory of Open Access Journals (Sweden)
Ding Hao
2015-08-01
Full Text Available In the field of adaptive radar detection, an effective strategy to improve the detection performance is to exploit the structural information of the covariance matrix, especially in the case of insufficient reference cells. Thus, in this study, the problem of detecting multidimensional subspace signals is discussed by considering the persymmetric structure of the clutter covariance matrix, which implies that the covariance matrix is persymmetric about its cross diagonal. Persymmetric adaptive detectors are derived on the basis of the one-step principle as well as the two-step Generalized Likelihood Ratio Test (GLRT in homogeneous and partially homogeneous clutter. The proposed detectors consider the structural information of the covariance matrix at the design stage. Simulation results suggest performance improvement compared with existing detectors when reference cells are insufficient. Moreover, the detection performance is assessed with respect to the effects of the covariance matrix, signal subspace dimension, and mismatched performance of signal subspace as well as signal fluctuations.
Estimation of direction of arrival of a moving target using subspace based approaches
Ghosh, Ripul; Das, Utpal; Akula, Aparna; Kumar, Satish; Sardana, H. K.
2016-05-01
In this work, array processing techniques based on subspace decomposition of signal have been evaluated for estimation of direction of arrival of moving targets using acoustic signatures. Three subspace based approaches - Incoherent Wideband Multiple Signal Classification (IWM), Least Square-Estimation of Signal Parameters via Rotation Invariance Techniques (LS-ESPRIT) and Total Least Square- ESPIRIT (TLS-ESPRIT) are considered. Their performance is compared with conventional time delay estimation (TDE) approaches such as Generalized Cross Correlation (GCC) and Average Square Difference Function (ASDF). Performance evaluation has been conducted on experimentally generated data consisting of acoustic signatures of four different types of civilian vehicles moving in defined geometrical trajectories. Mean absolute error and standard deviation of the DOA estimates w.r.t. ground truth are used as performance evaluation metrics. Lower statistical values of mean error confirm the superiority of subspace based approaches over TDE based techniques. Amongst the compared methods, LS-ESPRIT indicated better performance.
Directory of Open Access Journals (Sweden)
Chen Shi
2014-01-01
Full Text Available Subsynchronous oscillation (SSO usually caused by series compensation, power system stabilizer (PSS, high voltage direct current transmission (HVDC and other power electronic equipment, which will affect the safe operation of generator shafting even the system. It is very important to identify the modal parameters of SSO to take effective control strategies as well. Since the identification accuracy of traditional methods are not high enough, the stochastic subspace identification (SSI method is proposed to improve the identification accuracy of subsynchronous oscillation modal. The stochastic subspace identification method was compared with the other two methods on subsynchronous oscillation IEEE benchmark model and Xiang-Shang HVDC system model, the simulation results show that the stochastic subspace identification method has the advantages of high identification precision, high operation efficiency and strong ability of anti-noise.
Boundary regularity of Nevanlinna domains and univalent functions in model subspaces
International Nuclear Information System (INIS)
Baranov, Anton D; Fedorovskiy, Konstantin Yu
2011-01-01
In the paper we study boundary regularity of Nevanlinna domains, which have appeared in problems of uniform approximation by polyanalytic polynomials. A new method for constructing Nevanlinna domains with essentially irregular nonanalytic boundaries is suggested; this method is based on finding appropriate univalent functions in model subspaces, that is, in subspaces of the form K Θ =H 2 ominus ΘH 2 , where Θ is an inner function. To describe the irregularity of the boundaries of the domains obtained, recent results by Dolzhenko about boundary regularity of conformal mappings are used. Bibliography: 18 titles.
Embeddings of model subspaces of the Hardy space: compactness and Schatten-von Neumann ideals
International Nuclear Information System (INIS)
Baranov, Anton D
2009-01-01
We study properties of the embedding operators of model subspaces K p Θ (defined by inner functions) in the Hardy space H p (coinvariant subspaces of the shift operator). We find a criterion for the embedding of K p Θ in L p (μ) to be compact similar to the Volberg-Treil theorem on bounded embeddings, and give a positive answer to a question of Cima and Matheson. The proof is based on Bernstein-type inequalities for functions in K p Θ . We investigate measures μ such that the embedding operator belongs to some Schatten-von Neumann ideal.
Robust subspace estimation using low-rank optimization theory and applications
Oreifej, Omar
2014-01-01
Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem, which can be solved efficiently using techniques such as the method of Augmented Lagrange Multiplier. In this book,?the authors?discuss fundame
Outlier Ranking via Subspace Analysis in Multiple Views of the Data
DEFF Research Database (Denmark)
Muller, Emmanuel; Assent, Ira; Iglesias, Patricia
2012-01-01
, a novel outlier ranking concept. Outrank exploits subspace analysis to determine the degree of outlierness. It considers different subsets of the attributes as individual outlier properties. It compares clustered regions in arbitrary subspaces and derives an outlierness score for each object. Its...... principled integration of multiple views into an outlierness measure uncovers outliers that are not detectable in the full attribute space. Our experimental evaluation demonstrates that Outrank successfully determines a high quality outlier ranking, and outperforms state-of-the-art outlierness measures....
Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions
DEFF Research Database (Denmark)
Hansen, Per Christian; Jensen, Søren Holdt
We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV and ULLIV). In addition we show how the subspace-based algorithms can be evaluated and compared by means of simple FIR filter interpretations. The algorithms are illustrated...... with working Matlab code and applications in speech processing....
Water Reuse in Brazilian Manufacturing Firms
José Féres; Arnaud Reynaud; Alban Thomas
2015-01-01
This paper examines the factors influencing water reuse in manufacturing firms and analyzes whether the structure of intake water demand differs between firms that adopt water reuse practices and those which do not. To this purpose, we estimate a two-stage econometric model based on a sample of 447 industrial facilities located in the Paraíba do Sul river basin. The first stage applies a probit model for the water reuse decision and the second stage employs an endogenous switching regression ...
An empirical analysis of ontology reuse in BioPortal.
Ochs, Christopher; Perl, Yehoshua; Geller, James; Arabandi, Sivaram; Tudorache, Tania; Musen, Mark A
2017-07-01
Biomedical ontologies often reuse content (i.e., classes and properties) from other ontologies. Content reuse enables a consistent representation of a domain and reusing content can save an ontology author significant time and effort. Prior studies have investigated the existence of reused terms among the ontologies in the NCBO BioPortal, but as of yet there has not been a study investigating how the ontologies in BioPortal utilize reused content in the modeling of their own content. In this study we investigate how 355 ontologies hosted in the NCBO BioPortal reuse content from other ontologies for the purposes of creating new ontology content. We identified 197 ontologies that reuse content. Among these ontologies, 108 utilize reused classes in the modeling of their own classes and 116 utilize reused properties in class restrictions. Current utilization of reuse and quality issues related to reuse are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.
Reuse of Hydrotreating Spent Catalyst
International Nuclear Information System (INIS)
Habib, A.M.; Menoufy, M.F.; Amhed, S.H.
2004-01-01
All hydro treating catalysts used in petroleum refining processes gradually lose activity through coking, poisoning by metal, sulfur or halides or lose surface area from sintering at high process temperatures. Waste hydrotreating catalyst, which have been used in re-refining of waste lube oil at Alexandria Petroleum Company (after 5 years lifetime) compared with the same fresh catalyst were used in the present work. Studies are conducted on partial extraction of the active metals of spent catalyst (Mo and Ni) using three leaching solvents,4% oxidized oxalic acid, 10% aqueous sodium hydroxide and 10% citric acid. The leaching experiments are conducting on the de coked extrude [un crushed] spent catalyst samples. These steps are carried out in order to rejuvenate the spent catalyst to be reused in other reactions. The results indicated that 4% oxidized oxalic acid leaching solution gave total metal removal 45.6 for de coked catalyst samples while NaOH gave 35% and citric acid gave 31.9 % The oxidized leaching agent was the most efficient leaching solvent to facilitate the metal removal, and the rejuvenated catalyst was characterized by the unchanged crystalline phase The rejuvenated catalyst was applied for hydrodesulfurization (HDS) of vacuum gas oil as a feedstock, under different hydrogen pressure 20-80 bar in order to compare its HDS activity
DECONTAMINATION TECHNOLOGIES FOR FACILITY REUSE
International Nuclear Information System (INIS)
Bossart, Steven J.; Blair, Danielle M.
2003-01-01
As nuclear research and production facilities across the U.S. Department of Energy (DOE) nuclear weapons complex are slated for deactivation and decommissioning (D and D), there is a need to decontaminate some facilities for reuse for another mission or continued use for the same mission. Improved technologies available in the commercial sector and tested by the DOE can help solve the DOE's decontamination problems. Decontamination technologies include mechanical methods, such as shaving, scabbling, and blasting; application of chemicals; biological methods; and electrochemical techniques. Materials to be decontaminated are primarily concrete or metal. Concrete materials include walls, floors, ceilings, bio-shields, and fuel pools. Metallic materials include structural steel, valves, pipes, gloveboxes, reactors, and other equipment. Porous materials such as concrete can be contaminated throughout their structure, although contamination in concrete normally resides in the top quarter-inch below the surface. Metals are normally only contaminated on the surface. Contamination includes a variety of alpha, beta, and gamma-emitting radionuclides and can sometimes include heavy metals and organic contamination regulated by the Resource Conservation and Recovery Act (RCRA). This paper describes several advanced mechanical, chemical, and other methods to decontaminate structures, equipment, and materials
Towards a comprehensive framework for reuse: A reuse-enabling software evolution environment
Basili, V. R.; Rombach, H. D.
1988-01-01
Reuse of products, processes and knowledge will be the key to enable the software industry to achieve the dramatic improvement in productivity and quality required to satisfy the anticipated growing demand. Although experience shows that certain kinds of reuse can be successful, general success has been elusive. A software life-cycle technology which allows broad and extensive reuse could provide the means to achieving the desired order-of-magnitude improvements. The scope of a comprehensive framework for understanding, planning, evaluating and motivating reuse practices and the necessary research activities is outlined. As a first step towards such a framework, a reuse-enabling software evolution environment model is introduced which provides a basis for the effective recording of experience, the generalization and tailoring of experience, the formalization of experience, and the (re-)use of experience.
Software Reuse in the Naval Open Architecture
National Research Council Canada - National Science Library
Greathouse, Carlus A
2008-01-01
This thesis describes a web-based continuous learning module (CLM) for use in introducing members of the Department of the Navy s acquisition community to software reuse in the context of Naval Open Architecture...
Water brief-WDM & wastewater reuse
International Development Research Centre (IDRC) Digital Library (Canada)
aalfouns
Wastewater Reuse for Water Demand Management in the Middle East and ... Among the substantial WDM tools in MENA is the use of wastewater to reduce the pressure on scarce freshwater .... recycled water to irrigate crops with associated ...
the greywater reuse case of Jordan
International Development Research Centre (IDRC) Digital Library (Canada)
Fox Run Craftsmen
2003-03-06
Mar 6, 2003 ... new and creative methods and systems of dealing with wastewater reuse. .... and attended by 35 individuals representing 8 different agencies. .... Water and Irrigation calls for covering the operation and maintenance costs for.
Treated Wastewater Reuse on Potato (Solanum Tuberosum)
DEFF Research Database (Denmark)
Battilani, A; Plauborg, Finn; Andersen, Mathias Neumann
2014-01-01
A field experiment was carried out in Northern Italy (Po Valley), within the frame of the EU project SAFIR, to asses the impact of treated wastewater reuse on potato yield, quality and hygiene. The potato crop was drip irrigated and fertigated. Wastewater produced by small communities (≤2000 EI......) was treated by Membrane Bio Reactor (MBR) technology and gravel filter (FTS) during three cropping seasons. Treated wastewater, soil and tubers were analysed for the faecal indicator bacterium E. coli and heavy metals contents. Potato total yield was similar for tap and reused water, while the marketable...... production has been found higher with the latter. The tuber dry matter content as well as reducing sugars were not affected by reused water. Total sugars content was higher with MBR and FTS water. Water use efficiency (WUE) was significantly higher with reused water. Compared to tap water, crop gross margin...
Public opinion on water reuse options
International Nuclear Information System (INIS)
Bruvold, W.H.
1988-01-01
Public policy on waste water reuse options must be informed by public opinion because it is the public who must pay the cost of developing the option and who will be served by the option in the future. For public policy on reuse, guidance for innovative reuse is not as simple as first believed. It seems that public opinion regarding actual community reuse options is affected by the linkage of several factors, including water conservation, health protection, treatment and distribution costs, and environmental enhancement. Probability sampling was used in 7 studies to select respondents who were queried regarding their opinions on various reclaimed water uses such as ranging from cooling tower water to full domestic use. These 7 are briefly reviewed
Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions
DEFF Research Database (Denmark)
Hansen, Per Christian; Jensen, Søren Holdt
2007-01-01
We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... with working Matlab code and applications in speech processing....
DEFF Research Database (Denmark)
Macieszczak, Katarzyna; Zhou, Yanli; Hofferberth, Sebastian
2017-01-01
to stationarity this leads to a slow dynamics, which renders the typical assumption of fast relaxation invalid. We derive analytically the effective nonequilibrium dynamics in the decoherence-free subspace, which features coherent and dissipative two-body interactions. We discuss the use of this scenario...
DEFF Research Database (Denmark)
Müller, Emmanuel; Assent, Ira; Günnemann, Stephan
2011-01-01
comparative studies on the advantages and disadvantages of the different algorithms exist. Part of the underlying problem is the lack of available open source implementations that could be used by researchers to understand, compare, and extend subspace and projected clustering algorithms. In this work, we...
Sparse subspace clustering for data with missing entries and high-rank matrix completion.
Fan, Jicong; Chow, Tommy W S
2017-09-01
Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
Third-order nonlinear differential operators preserving invariant subspaces of maximal dimension
International Nuclear Information System (INIS)
Qu Gai-Zhu; Zhang Shun-Li; Li Yao-Long
2014-01-01
In this paper, third-order nonlinear differential operators are studied. It is shown that they are quadratic forms when they preserve invariant subspaces of maximal dimension. A complete description of third-order quadratic operators with constant coefficients is obtained. One example is given to derive special solutions for evolution equations with third-order quadratic operators. (general)
A frequency domain subspace algorithm for mixed causal, anti-causal LTI systems
Fraanje, Rufus; Verhaegen, Michel; Verdult, Vincent; Pintelon, Rik
2003-01-01
The paper extends the subspacc identification method to estimate state-space models from frequency response function (FRF) samples, proposed by McKelvey et al. (1996) for mixed causal/anti-causal systems, and shows that other frequency domain subspace algorithms can be extended similarly. The method
Revisiting Reuse in Main Memory Database Systems
Dursun, Kayhan; Binnig, Carsten; Cetintemel, Ugur; Kraska, Tim
2016-01-01
Reusing intermediates in databases to speed-up analytical query processing has been studied in the past. Existing solutions typically require intermediate results of individual operators to be materialized into temporary tables to be considered for reuse in subsequent queries. However, these approaches are fundamentally ill-suited for use in modern main memory databases. The reason is that modern main memory DBMSs are typically limited by the bandwidth of the memory bus, thus query execution ...
Beneficial Reuse of Produced and Flowback Water
Water reuse and recycling is a significant issue in the development of oil and gas shale plays in the United StatesDrilling operations – 60,000 to 650,000 gallons per wellHydraulic fracturing operations – 3 million to 5 million gallons per wellDefinition of produced water and flowback waterInteractions of water quality constituents as they relate to water reuse and recyclingTesting criteria in the laboratory and field operations
Recent practices on wastewater reuse in Turkey.
Tanik, A; Ekdal, A; Germirli Babuna, F; Orhon, D
2005-01-01
Reuse of wastewater for irrigational purposes in agriculture has been a widely applied practice all around the world compared to such applications in industries. In most of the developing countries, high costs of wastewater treatment stimulate the direct reuse of raw or partly treated effluent in irrigation despite the socio-cultural objections in some countries regarding religious rituals towards consuming wastewater. In Turkey, reuse applications in agriculture have been in use by indirect application by means of withdrawing water from the downstream end of treatment plants. Such practices affected the deterioration of surface water resources due to the lack of water quality monitoring and control. However, more conscious and planned reuse activities in agriculture have recently started by the operation of urban wastewater treatment plants. Turkey does not face any severe water scarcity problems for the time being, but as the water resources show the signs of water quality deterioration it seems to be one of the priority issues in the near future. The industrial reuse activities are only at the research stage especially in industries consuming high amounts of water. In-plant control implementation is the preferred effort of minimizing water consumption in such industries. The current reuse activities are outlined in the article forming an example from a developing country.
Brunton, Steven L; Brunton, Bingni W; Proctor, Joshua L; Kutz, J Nathan
2016-01-01
In this wIn this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control.ork, we explore finite
Using CUDA Technology for Defining the Stiffness Matrix in the Subspace of Eigenvectors
Directory of Open Access Journals (Sweden)
Yu. V. Berchun
2015-01-01
Full Text Available The aim is to improve the performance of solving a problem of deformable solid mechanics through the use of GPGPU. The paper describes technologies for computing systems using both a central and a graphics processor and provides motivation for using CUDA technology as the efficient one.The paper also analyses methods to solve the problem of defining natural frequencies and design waveforms, i.e. an iteration method in the subspace. The method includes several stages. The paper considers the most resource-hungry stage, which defines the stiffness matrix in the subspace of eigenforms and gives the mathematical interpretation of this stage.The GPU choice as a computing device is justified. The paper presents an algorithm for calculating the stiffness matrix in the subspace of eigenforms taking into consideration the features of input data. The global stiffness matrix is very sparse, and its size can reach tens of millions. Therefore, it is represented as a set of the stiffness matrices of the single elements of a model. The paper analyses methods of data representation in the software and selects the best practices for GPU computing.It describes the software implementation using CUDA technology to calculate the stiffness matrix in the subspace of eigenforms. Due to the input data nature, it is impossible to use the universal libraries of matrix computations (cuSPARSE and cuBLAS for loading the GPU. For efficient use of GPU resources in the software implementation, the stiffness matrices of elements are built in the block matrices of a special form. The advantages of using shared memory in GPU calculations are described.The transfer to the GPU computations allowed a twentyfold increase in performance (as compared to the multithreaded CPU-implementation on the model of middle dimensions (degrees of freedom about 2 million. Such an acceleration of one stage speeds up defining the natural frequencies and waveforms by the iteration method in a subspace
Lyapunov vectors and assimilation in the unstable subspace: theory and applications
International Nuclear Information System (INIS)
Palatella, Luigi; Carrassi, Alberto; Trevisan, Anna
2013-01-01
Based on a limited number of noisy observations, estimation algorithms provide a complete description of the state of a system at current time. Estimation algorithms that go under the name of assimilation in the unstable subspace (AUS) exploit the nonlinear stability properties of the forecasting model in their formulation. Errors that grow due to sensitivity to initial conditions are efficiently removed by confining the analysis solution in the unstable and neutral subspace of the system, the subspace spanned by Lyapunov vectors with positive and zero exponents, while the observational noise does not disturb the system along the stable directions. The formulation of the AUS approach in the context of four-dimensional variational assimilation (4DVar-AUS) and the extended Kalman filter (EKF-AUS) and its application to chaotic models is reviewed. In both instances, the AUS algorithms are at least as efficient but simpler to implement and computationally less demanding than their original counterparts. As predicted by the theory when error dynamics is linear, the optimal subspace dimension for 4DVar-AUS is given by the number of positive and null Lyapunov exponents, while the EKF-AUS algorithm, using the same unstable and neutral subspace, recovers the solution of the full EKF algorithm, but dealing with error covariance matrices of a much smaller dimension and significantly reducing the computational burden. Examples of the application to a simplified model of the atmospheric circulation and to the optimal velocity model for traffic dynamics are given. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Lyapunov analysis: from dynamical systems theory to applications’. (paper)
Brunton, Steven L.; Brunton, Bingni W.; Proctor, Joshua L.; Kutz, J. Nathan
2016-01-01
In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control. PMID:26919740
Keshtkaran, Mohammad Reza; Yang, Zhi
2017-06-01
Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.
Keshtkaran, Mohammad Reza; Yang, Zhi
2017-06-01
Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.
Software Reuse Within the Earth Science Community
Marshall, James J.; Olding, Steve; Wolfe, Robert E.; Delnore, Victor E.
2006-01-01
Scientific missions in the Earth sciences frequently require cost-effective, highly reliable, and easy-to-use software, which can be a challenge for software developers to provide. The NASA Earth Science Enterprise (ESE) spends a significant amount of resources developing software components and other software development artifacts that may also be of value if reused in other projects requiring similar functionality. In general, software reuse is often defined as utilizing existing software artifacts. Software reuse can improve productivity and quality while decreasing the cost of software development, as documented by case studies in the literature. Since large software systems are often the results of the integration of many smaller and sometimes reusable components, ensuring reusability of such software components becomes a necessity. Indeed, designing software components with reusability as a requirement can increase the software reuse potential within a community such as the NASA ESE community. The NASA Earth Science Data Systems (ESDS) Software Reuse Working Group is chartered to oversee the development of a process that will maximize the reuse potential of existing software components while recommending strategies for maximizing the reusability potential of yet-to-be-designed components. As part of this work, two surveys of the Earth science community were conducted. The first was performed in 2004 and distributed among government employees and contractors. A follow-up survey was performed in 2005 and distributed among a wider community, to include members of industry and academia. The surveys were designed to collect information on subjects such as the current software reuse practices of Earth science software developers, why they choose to reuse software, and what perceived barriers prevent them from reusing software. In this paper, we compare the results of these surveys, summarize the observed trends, and discuss the findings. The results are very
Yuan, Xuefei
2012-07-01
Numerical simulations of the four-field extended magnetohydrodynamics (MHD) equations with hyper-resistivity terms present a difficult challenge because of demanding spatial resolution requirements. A time-dependent sequence of . r-refinement adaptive grids obtained from solving a single Monge-Ampère (MA) equation addresses the high-resolution requirements near the . x-point for numerical simulation of the magnetic reconnection problem. The MHD equations are transformed from Cartesian coordinates to solution-defined curvilinear coordinates. After the application of an implicit scheme to the time-dependent problem, the parallel Newton-Krylov-Schwarz (NKS) algorithm is used to solve the system at each time step. Convergence and accuracy studies show that the curvilinear solution requires less computational effort than a pure Cartesian treatment. This is due both to the more optimal placement of the grid points and to the improved convergence of the implicit solver, nonlinearly and linearly. The latter effect, which is significant (more than an order of magnitude in number of inner linear iterations for equivalent accuracy), does not yet seem to be widely appreciated. © 2012 Elsevier Inc.
Yuan, Xuefei; Jardin, Stephen C.; Keyes, David E.
2012-01-01
Numerical simulations of the four-field extended magnetohydrodynamics (MHD) equations with hyper-resistivity terms present a difficult challenge because of demanding spatial resolution requirements. A time-dependent sequence of . r-refinement adaptive grids obtained from solving a single Monge-Ampère (MA) equation addresses the high-resolution requirements near the . x-point for numerical simulation of the magnetic reconnection problem. The MHD equations are transformed from Cartesian coordinates to solution-defined curvilinear coordinates. After the application of an implicit scheme to the time-dependent problem, the parallel Newton-Krylov-Schwarz (NKS) algorithm is used to solve the system at each time step. Convergence and accuracy studies show that the curvilinear solution requires less computational effort than a pure Cartesian treatment. This is due both to the more optimal placement of the grid points and to the improved convergence of the implicit solver, nonlinearly and linearly. The latter effect, which is significant (more than an order of magnitude in number of inner linear iterations for equivalent accuracy), does not yet seem to be widely appreciated. © 2012 Elsevier Inc.
International Nuclear Information System (INIS)
Godoy, William F.; Liu Xu
2012-01-01
The present study introduces a parallel Jacobian-free Newton Krylov (JFNK) general minimal residual (GMRES) solution for the discretized radiative transfer equation (RTE) in 3D, absorbing, emitting and scattering media. For the angular and spatial discretization of the RTE, the discrete ordinates method (DOM) and the finite volume method (FVM) including flux limiters are employed, respectively. Instead of forming and storing a large Jacobian matrix, JFNK methods allow for large memory savings as the required Jacobian-vector products are rather approximated by semiexact and numerical formulations, for which convergence and computational times are presented. Parallelization of the GMRES solution is introduced in a combined memory-shared/memory-distributed formulation that takes advantage of the fact that only large vector arrays remain in the JFNK process. Results are presented for 3D test cases including a simple homogeneous, isotropic medium and a more complex non-homogeneous, non-isothermal, absorbing–emitting and anisotropic scattering medium with collimated intensities. Additionally, convergence and stability of Gram–Schmidt and Householder orthogonalizations for the Arnoldi process in the parallel GMRES algorithms are discussed and analyzed. Overall, the introduction of JFNK methods results in a parallel, yet scalable to the tested 2048 processors, and memory affordable solution to 3D radiative transfer problems without compromising the accuracy and convergence of a Newton-like solution.
Mang, Andreas; Biros, George
2017-01-01
We propose an efficient numerical algorithm for the solution of diffeomorphic image registration problems. We use a variational formulation constrained by a partial differential equation (PDE), where the constraints are a scalar transport equation. We use a pseudospectral discretization in space and second-order accurate semi-Lagrangian time stepping scheme for the transport equations. We solve for a stationary velocity field using a preconditioned, globalized, matrix-free Newton-Krylov scheme. We propose and test a two-level Hessian preconditioner. We consider two strategies for inverting the preconditioner on the coarse grid: a nested preconditioned conjugate gradient method (exact solve) and a nested Chebyshev iterative method (inexact solve) with a fixed number of iterations. We test the performance of our solver in different synthetic and real-world two-dimensional application scenarios. We study grid convergence and computational efficiency of our new scheme. We compare the performance of our solver against our initial implementation that uses the same spatial discretization but a standard, explicit, second-order Runge-Kutta scheme for the numerical time integration of the transport equations and a single-level preconditioner. Our improved scheme delivers significant speedups over our original implementation. As a highlight, we observe a 20 × speedup for a two dimensional, real world multi-subject medical image registration problem.
International Nuclear Information System (INIS)
Thambimuthu, K.; Gupta, M.; Davison, J.
2003-01-01
CO2 capture and storage including its utilization or reuse presents an opportunity to achieve deep reductions in greenhouse gas emissions from fossil energy use. The development and deployment of this option could significantly assist in meeting a future goal of achieving stabilization of the presently rising atmospheric concentration of greenhouse gases. CO2 capture from process streams is an established concept that has achieved industrial practice. Examples of current applications include the use of primarily, solvent based capture technologies for the recovery of pure CO2 streams for chemical synthesis, for utilization as a food additive, for use as a miscible agent in enhanced oil recovery operations and removal of CO2 as an undesired contaminant from gaseous process streams for the production of fuel gases such as hydrogen and methane. In these applications, the technologies deployed for CO2 capture have focused on gas separation from high purity, high pressure streams and in reducing (or oxygen deficient) environments, where the energy penalties and cost for capture are moderately low. However, application of the same capture technologies for large scale abatement of greenhouse gas emissions from fossil fuel use poses significant challenges in achieving (at comparably low energy penalty and cost) gas separation in large volume, dilute concentration and/or low pressure flue gas streams. This paper will focus on a review of existing commercial methods of CO2 capture and the technology stretch, process integration and energy system pathways needed for their large scale deployment in fossil fueled processes. The assessment of potential capture technologies for the latter purpose will also be based on published literature data that are both 'transparent' and 'systematic' in their evaluation of the overall cost and energy penalties of CO2 capture. In view of the of the fact that many of the existing commercial processes for CO2 capture have seen applications in
Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System
Directory of Open Access Journals (Sweden)
Minghong She
2018-01-01
Full Text Available For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. By using the same projection of related data in time offset set and LQ decomposition, the multiplication operation of projection is achieved and dynamics estimation of the unknown equipment system model is obtained. Consequently, we have solved the problem of biased estimation caused when the open-loop subspace identification algorithm is applied to the closed-loop identification. A simulation example is given to show the effectiveness of the proposed approach. In final, the practicability of the identification algorithm is verified by hardware test of UAV servo system in real environment.
Visual tracking based on the sparse representation of the PCA subspace
Chen, Dian-bing; Zhu, Ming; Wang, Hui-li
2017-09-01
We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.
Detecting anomalies in crowded scenes via locality-constrained affine subspace coding
Fan, Yaxiang; Wen, Gongjian; Qiu, Shaohua; Li, Deren
2017-07-01
Video anomaly event detection is the process of finding an abnormal event deviation compared with the majority of normal or usual events. The main challenges are the high structure redundancy and the dynamic changes in the scenes that are in surveillance videos. To address these problems, we present a framework for anomaly detection and localization in videos that is based on locality-constrained affine subspace coding (LASC) and a model updating procedure. In our algorithm, LASC attempts to reconstruct the test sample by its top-k nearest subspaces, which are obtained by segmenting the normal samples space using a clustering method. A sample with a large reconstruction cost is detected as abnormal by setting a threshold. To adapt to the scene changes over time, a model updating strategy is proposed. We experiment on two public datasets: the UCSD dataset and the Avenue dataset. The results demonstrate that our method achieves competitive performance at a 700 fps on a single desktop PC.
International Nuclear Information System (INIS)
Chen, Xudong
2010-01-01
This paper proposes a version of the subspace-based optimization method to solve the inverse scattering problem with an inhomogeneous background medium where the known inhomogeneities are bounded in a finite domain. Although the background Green's function at each discrete point in the computational domain is not directly available in an inhomogeneous background scenario, the paper uses the finite element method to simultaneously obtain the Green's function at all discrete points. The essence of the subspace-based optimization method is that part of the contrast source is determined from the spectrum analysis without using any optimization, whereas the orthogonally complementary part is determined by solving a lower dimension optimization problem. This feature significantly speeds up the convergence of the algorithm and at the same time makes it robust against noise. Numerical simulations illustrate the efficacy of the proposed algorithm. The algorithm presented in this paper finds wide applications in nondestructive evaluation, such as through-wall imaging
Pyshkin, P V; Luo, Da-Wei; Jing, Jun; You, J Q; Wu, Lian-Ao
2016-11-25
Holonomic quantum computation (HQC) may not show its full potential in quantum speedup due to the prerequisite of a long coherent runtime imposed by the adiabatic condition. Here we show that the conventional HQC can be dramatically accelerated by using external control fields, of which the effectiveness is exclusively determined by the integral of the control fields in the time domain. This control scheme can be realized with net zero energy cost and it is fault-tolerant against fluctuation and noise, significantly relaxing the experimental constraints. We demonstrate how to realize the scheme via decoherence-free subspaces. In this way we unify quantum robustness merits of this fault-tolerant control scheme, the conventional HQC and decoherence-free subspace, and propose an expedited holonomic quantum computation protocol.
Experimental fault-tolerant quantum cryptography in a decoherence-free subspace
International Nuclear Information System (INIS)
Zhang Qiang; Pan Jianwei; Yin Juan; Chen Tengyun; Lu Shan; Zhang Jun; Li Xiaoqiang; Yang Tao; Wang Xiangbin
2006-01-01
We experimentally implement a fault-tolerant quantum key distribution protocol with two photons in a decoherence-free subspace [Phys. Rev. A 72, 050304(R) (2005)]. It is demonstrated that our protocol can yield a good key rate even with a large bit-flip error rate caused by collective rotation, while the usual realization of the Bennett-Brassard 1984 protocol cannot produce any secure final key given the same channel. Since the experiment is performed in polarization space and does not need the calibration of a reference frame, important applications in free-space quantum communication are expected. Moreover, our method can also be used to robustly transmit an arbitrary two-level quantum state in a type of decoherence-free subspace
Recursive Subspace Identification of AUV Dynamic Model under General Noise Assumption
Directory of Open Access Journals (Sweden)
Zheping Yan
2014-01-01
Full Text Available A recursive subspace identification algorithm for autonomous underwater vehicles (AUVs is proposed in this paper. Due to the advantages at handling nonlinearities and couplings, the AUV model investigated here is for the first time constructed as a Hammerstein model with nonlinear feedback in the linear part. To better take the environment and sensor noises into consideration, the identification problem is concerned as an errors-in-variables (EIV one which means that the identification procedure is under general noise assumption. In order to make the algorithm recursively, propagator method (PM based subspace approach is extended into EIV framework to form the recursive identification method called PM-EIV algorithm. With several identification experiments carried out by the AUV simulation platform, the proposed algorithm demonstrates its effectiveness and feasibility.
Cumulant-Based Coherent Signal Subspace Method for Bearing and Range Estimation
Directory of Open Access Journals (Sweden)
Bourennane Salah
2007-01-01
Full Text Available A new method for simultaneous range and bearing estimation for buried objects in the presence of an unknown Gaussian noise is proposed. This method uses the MUSIC algorithm with noise subspace estimated by using the slice fourth-order cumulant matrix of the received data. The higher-order statistics aim at the removal of the additive unknown Gaussian noise. The bilinear focusing operator is used to decorrelate the received signals and to estimate the coherent signal subspace. A new source steering vector is proposed including the acoustic scattering model at each sensor. Range and bearing of the objects at each sensor are expressed as a function of those at the first sensor. This leads to the improvement of object localization anywhere, in the near-field or in the far-field zone of the sensor array. Finally, the performances of the proposed method are validated on data recorded during experiments in a water tank.
Kernel based subspace projection of near infrared hyperspectral images of maize kernels
DEFF Research Database (Denmark)
Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben
2009-01-01
In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods ......- tor transform outperform the linear methods as well as kernel principal components in producing interesting projections of the data.......In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods...... including principal component analysis and maximum autocorrelation factor analysis. The latter utilizes the fact that interesting phenomena in images exhibit spatial autocorrelation. However, linear projections often fail to grasp the underlying variability on the data. Therefore we propose to use so...
Quantum theory of dynamical collective subspace for large-amplitude collective motion
International Nuclear Information System (INIS)
Sakata, Fumihiko; Marumori, Toshio; Ogura, Masanori.
1986-03-01
By placing emphasis on conceptual correspondence to the ''classical'' theory which has been developed within the framework of the time-dependent Hartree-Fock theory, a full quantum theory appropriate for describing large-amplitude collective motion is proposed. A central problem of the quantum theory is how to determine an optimal representation called a dynamical representation; the representation is specific for the collective subspace where the large-amplitude collective motion is replicated as satisfactorily as possible. As an extension of the classical theory where the concept of an approximate integral surface plays an important role, the dynamical representation is properly characterized by introducing a concept of an approximate invariant subspace of the Hamiltonian. (author)
Application of Earthquake Subspace Detectors at Kilauea and Mauna Loa Volcanoes, Hawai`i
Okubo, P.; Benz, H.; Yeck, W.
2016-12-01
Recent studies have demonstrated the capabilities of earthquake subspace detectors for detailed cataloging and tracking of seismicity in a number of regions and settings. We are exploring the application of subspace detectors at the United States Geological Survey's Hawaiian Volcano Observatory (HVO) to analyze seismicity at Kilauea and Mauna Loa volcanoes. Elevated levels of microseismicity and occasional swarms of earthquakes associated with active volcanism here present cataloging challenges due the sheer numbers of earthquakes and an intrinsically low signal-to-noise environment featuring oceanic microseism and volcanic tremor in the ambient seismic background. With high-quality continuous recording of seismic data at HVO, we apply subspace detectors (Harris and Dodge, 2011, Bull. Seismol. Soc. Am., doi: 10.1785/0120100103) during intervals of noteworthy seismicity. Waveform templates are drawn from Magnitude 2 and larger earthquakes within clusters of earthquakes cataloged in the HVO seismic database. At Kilauea, we focus on seismic swarms in the summit caldera region where, despite continuing eruptions from vents in the summit region and in the east rift zone, geodetic measurements reflect a relatively inflated volcanic state. We also focus on seismicity beneath and adjacent to Mauna Loa's summit caldera that appears to be associated with geodetic expressions of gradual volcanic inflation, and where precursory seismicity clustered prior to both Mauna Loa's most recent eruptions in 1975 and 1984. We recover several times more earthquakes with the subspace detectors - down to roughly 2 magnitude units below the templates, based on relative amplitudes - compared to the numbers of cataloged earthquakes. The increased numbers of detected earthquakes in these clusters, and the ability to associate and locate them, allow us to infer details of the spatial and temporal distributions and possible variations in stresses within these key regions of the volcanoes.
Hsu, Wei-Ting; Loh, Chin-Hsiung; Chao, Shu-Hsien
2015-03-01
Stochastic subspace identification method (SSI) has been proven to be an efficient algorithm for the identification of liner-time-invariant system using multivariate measurements. Generally, the estimated modal parameters through SSI may be afflicted with statistical uncertainty, e.g. undefined measurement noises, non-stationary excitation, finite number of data samples etc. Therefore, the identified results are subjected to variance errors. Accordingly, the concept of the stabilization diagram can help users to identify the correct model, i.e. through removing the spurious modes. Modal parameters are estimated at successive model orders where the physical modes of the system are extracted and separated from the spurious modes. Besides, an uncertainty computation scheme was derived for the calculation of uncertainty bounds for modal parameters at some given model order. The uncertainty bounds of damping ratios are particularly interesting, as the estimation of damping ratios are difficult to obtain. In this paper, an automated stochastic subspace identification algorithm is addressed. First, the identification of modal parameters through covariance-driven stochastic subspace identification from the output-only measurements is used for discussion. A systematic way of investigation on the criteria for the stabilization diagram is presented. Secondly, an automated algorithm of post-processing on stabilization diagram is demonstrated. Finally, the computation of uncertainty bounds for each mode with all model order in the stabilization diagram is utilized to determine system natural frequencies and damping ratios. Demonstration of this study on the system identification of a three-span steel bridge under operation condition is presented. It is shown that the proposed new operation procedure for the automated covariance-driven stochastic subspace identification can enhance the robustness and reliability in structural health monitoring.
Projected Gauss-Seidel subspace minimization method for interactive rigid body dynamics
DEFF Research Database (Denmark)
Silcowitz-Hansen, Morten; Abel, Sarah Maria Niebe; Erleben, Kenny
2010-01-01
artifacts such as viscous or damped contact response. In this paper, we present a new approach to contact force determination. We formulate the contact force problem as a nonlinear complementarity problem, and discretize the problem to derive the Projected Gauss–Seidel method. We combine the Projected Gauss......–Seidel method with a subspace minimization method. Our new method shows improved qualities and superior convergence properties for specific configurations....
Subspace based adaptive denoising of surface EMG from neurological injury patients
Liu, Jie; Ying, Dongwen; Zev Rymer, William; Zhou, Ping
2014-10-01
Objective: After neurological injuries such as spinal cord injury, voluntary surface electromyogram (EMG) signals recorded from affected muscles are often corrupted by interferences, such as spurious involuntary spikes and background noises produced by physiological and extrinsic/accidental origins, imposing difficulties for signal processing. Conventional methods did not well address the problem caused by interferences. It is difficult to mitigate such interferences using conventional methods. The aim of this study was to develop a subspace-based denoising method to suppress involuntary background spikes contaminating voluntary surface EMG recordings. Approach: The Karhunen-Loeve transform was utilized to decompose a noisy signal into a signal subspace and a noise subspace. An optimal estimate of EMG signal is derived from the signal subspace and the noise power. Specifically, this estimator is capable of making a tradeoff between interference reduction and signal distortion. Since the estimator partially relies on the estimate of noise power, an adaptive method was presented to sequentially track the variation of interference power. The proposed method was evaluated using both semi-synthetic and real surface EMG signals. Main results: The experiments confirmed that the proposed method can effectively suppress interferences while keep the distortion of voluntary EMG signal in a low level. The proposed method can greatly facilitate further signal processing, such as onset detection of voluntary muscle activity. Significance: The proposed method can provide a powerful tool for suppressing background spikes and noise contaminating voluntary surface EMG signals of paretic muscles after neurological injuries, which is of great importance for their multi-purpose applications.
Banach C*-algebras not containing a subspace isomorphic to C0
International Nuclear Information System (INIS)
Basit, B.
1989-09-01
If X is a locally Hausdorff space and C 0 (X) the Banach algebra of continuous functions defined on X vanishing at infinity, we showed that a subalgebra A of C 0 (X) is finite dimensional if it does not contain a subspace isomorphic to the Banach space C 0 of convergent to zero complex sequences. In this paper we extend this result to noncommutative Banach C*-algebras and Banach* algebras. 10 refs
N-screen aware multicriteria hybrid recommender system using weight based subspace clustering.
Ullah, Farman; Sarwar, Ghulam; Lee, Sungchang
2014-01-01
This paper presents a recommender system for N-screen services in which users have multiple devices with different capabilities. In N-screen services, a user can use various devices in different locations and time and can change a device while the service is running. N-screen aware recommendation seeks to improve the user experience with recommended content by considering the user N-screen device attributes such as screen resolution, media codec, remaining battery time, and access network and the user temporal usage pattern information that are not considered in existing recommender systems. For N-screen aware recommendation support, this work introduces a user device profile collaboration agent, manager, and N-screen control server to acquire and manage the user N-screen devices profile. Furthermore, a multicriteria hybrid framework is suggested that incorporates the N-screen devices information with user preferences and demographics. In addition, we propose an individual feature and subspace weight based clustering (IFSWC) to assign different weights to each subspace and each feature within a subspace in the hybrid framework. The proposed system improves the accuracy, precision, scalability, sparsity, and cold start issues. The simulation results demonstrate the effectiveness and prove the aforementioned statements.
A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering
Directory of Open Access Journals (Sweden)
Yubao Sun
2015-01-01
Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.
Directory of Open Access Journals (Sweden)
Carlos A. L. Pires
2017-01-01
Full Text Available We propose an expansion of multivariate time-series data into maximally independent source subspaces. The search is made among rotations of prewhitened data which maximize non-Gaussianity of candidate sources. We use a tensorial invariant approximation of the multivariate negentropy in terms of a linear combination of squared coskewness and cokurtosis. By solving a high-order singular value decomposition problem, we extract the axes associated with most non-Gaussianity. Moreover, an estimate of the Gaussian subspace is provided by the trailing singular vectors. The independent subspaces are obtained through the search of “quasi-independent” components within the estimated non-Gaussian subspace, followed by the identification of groups with significant joint negentropies. Sources result essentially from the coherency of extremes of the data components. The method is then applied to the global sea surface temperature anomalies, equatorward of 65°, after being tested with non-Gaussian surrogates consistent with the data anomalies. The main emerging independent components and subspaces, supposedly generated by independent forcing, include different variability modes, namely, The East-Pacific, the Central Pacific, and the Atlantic Niños, the Atlantic Multidecadal Oscillation, along with the subtropical dipoles in the Indian, South Pacific, and South-Atlantic oceans. Benefits and usefulness of independent subspaces are then discussed.
Potable Water Reuse: What Are the Microbiological Risks?
Nappier, Sharon P; Soller, Jeffrey A; Eftim, Sorina E
2018-06-01
With the increasing interest in recycling water for potable reuse purposes, it is important to understand the microbial risks associated with potable reuse. This review focuses on potable reuse systems that use high-level treatment and de facto reuse scenarios that include a quantifiable wastewater effluent component. In this article, we summarize the published human health studies related to potable reuse, including both epidemiology studies and quantitative microbial risk assessments (QMRA). Overall, there have been relatively few health-based studies evaluating the microbial risks associated with potable reuse. Several microbial risk assessments focused on risks associated with unplanned (or de facto) reuse, while others evaluated planned potable reuse, such as indirect potable reuse (IPR) or direct potable reuse (DPR). The reported QMRA-based risks for planned potable reuse varied substantially, indicating there is a need for risk assessors to use consistent input parameters and transparent assumptions, so that risk results are easily translated across studies. However, the current results overall indicate that predicted risks associated with planned potable reuse scenarios may be lower than those for de facto reuse scenarios. Overall, there is a clear need to carefully consider water treatment train choices when wastewater is a component of the drinking water supply (whether de facto, IPR, or DPR). More data from full-scale water treatment facilities would be helpful to quantify levels of viruses in raw sewage and reductions across unit treatment processes for both culturable and molecular detection methods.
Creating by Reusing Learning Design Solutions
Hernández-Leo, Davinia; Harrer, Andreas; Dodero, Juan Manuel; Asensio-Pérez, Juan; Burgos, Daniel
2006-01-01
Hernández-Leo, D., Harrer, A., Dodero, J. M., Asension-Pérez, J. I., & Burgos, D. (2006). Creating by reusing Learning Design solutions. Proceedings of 8th Simposo Internacional de Informática Educativa, León, Spain: IEEE Technical Committee on Learning Technology. Retrieved October 3rd, 2006, from
The Three Rs: Reduce, Reuse, Recycle.
Science Activities, 1991
1991-01-01
A student hand-out for a recycling unit defines the terms reduce, recycle, and reuse as they relate to solid waste management. Presents the characteristics of recyclable items such as yard wastes, metals, glass, and paper. Lists organizations through which more information about recycling can be obtained. (MCO)
DEFF Research Database (Denmark)
Schwartzbach, Michael Ignatieff; Palsberg, Jens
1991-01-01
Subclassing is reuse of class definitions. It is usually tied to the use of class names, thus relying on the order in which the particular classes in a program are created. This is a burden, however, both when programming and in theoretical studies. This paper presents a structural notion of subc...
Constructed Wetlands for Greywater Recycle and Reuse
Concern over dwindling water supplies for urban areas as well as environmental degradation from existing urban water systems has motivated research into more resilient and sustainable water supply strategies. Greywater reuse has been suggested as a way to diversify local water su...
Asset Reuse of Images from a Repository
Herman, Deirdre
2014-01-01
According to Markus's theory of reuse, when digital repositories are deployed to collect and distribute organizational assets, they supposedly help ensure accountability, extend information exchange, and improve productivity. Such repositories require a large investment due to the continuing costs of hardware, software, user licenses, training,…
MINIMIZATION OF RETRIEVAL TIME DURING SOFTWARE REUSE ...
African Journals Online (AJOL)
eobe
Versions. Label in repository. No. of classifiers in class diagrams. No. of sequence diagrams. No. of messages in all sequence diagrams. Java Game. Maker. (JGM) game engine for developing java games. 1.9, 2.1, 2.2, ... to programming, code-based sizing metrics will be used to estimate reuse effort. The formula employed.
Current Opinion and Controversies of Dialyser Reuse
Directory of Open Access Journals (Sweden)
Brown Colin
2001-01-01
Full Text Available Reuse of dialysers has been an integral part of hemodialysis since its inception. Over the past decade, reuse has increased significantly in many countries, most notably in the United States, while vanishing entirely in some other countries, such as Portugal and France. In the United States, which is most widely used as an example because of the large amount of data available, the mortality of dialysis patients has steadily decreased even as reuse has increased. This improvement is probably the result of a complex of factors including understanding the role of comorbidity, treatment unit characteristics, barriers to adequate dialysis, nutrition, anemia, high flux dialysis and dialyser membrane improvements and the desired dialysis dose. Reuse provides a significant economic benefit that allows the use of more efficient and expensive larger biocompatible synthetic membranes to provide high-quality dialysis in the face of cost inflation, limited medical resources and fixed reimbursement. Rather than being legitimized by clinical practice alone, reprocessing, supported by clinical studies, allows the provision of superior treatment to more patients safely and economically. Recent reports concerning dialyser reprocessing have centered not only on morbidity and mortality, but also on questions of the specific effects of different germicides on various types of dialyser membranes (e.g., cellulosic, synthetic, high-flux, etc. and on the possible role of dialyser reprocessing in the transmission of hepatitis C.
Reuse of drainage water from irrigated areas
Willardson, L.S.; Boels, D.; Smedema, L.K.
1997-01-01
Increasing competition for water of good quality and the expectation that at least half of the required increase in food production in the near-future decades must come from the world's irrigated land requires to produce more food by converting more of the diverted water into food. Reuse of the
Code Reuse and Modularity in Python
Directory of Open Access Journals (Sweden)
William J. Turkel
2012-07-01
Full Text Available Computer programs can become long, unwieldy and confusing without special mechanisms for managing complexity. This lesson will show you how to reuse parts of your code by writing Functions and break your programs into Modules, in order to keep everything concise and easier to debug. Being able to remove a single dysfunctional module can save time and effort.
An overview of reclaimed water reuse in China.
Yi, Lili; Jiao, Wentao; Chen, Xiaoning; Chen, Weiping
2011-01-01
China is facing severe water problems including scarcity and pollution which are now becoming key factors restricting developments. Creating an alternative water resource and reducing effluent discharges, water reuse has been recognized as an integral part of water and wastewater management scheme in China. The government has launched nationwide efforts to optimize the benefits of utilizing reclaimed water. This article reviewed the water reuse activities in China, including: (1) application history and current status; (2) potentials of reclaimed water reuse; (3) laws, policies and regulations governing reclaimed water reuse; (4) risks associated with reclaimed water reuse; (5) issues in reclaimed water reuse. Reclaimed water in Beijing and Tianjin were given as examples. Suggestions for improving the efficiencies of reusing urban wastewater were advanced. Being the largest user of reclaimed wastewater in the world, China's experience can benefit the development of water reuse in other regions.
Minimization of Retrieval Time During Software Reuse | Salami ...
African Journals Online (AJOL)
Minimization of Retrieval Time During Software Reuse. ... Retrieval of relevant software from the repository during software reuse can be time consuming if the repository contains many ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT
Quantifying Functional Reuse from Object Oriented Requirements Specifications
Condori-Fernandez, Nelly; Condori-Fernández, N.; Pastor, O; Daneva, Maia; Abran, A.; Castro, J.; Quer, C.; Carvallo, J. B.; Fernandes da Silva, L.
2008-01-01
Software reuse is essential in improving efficiency and productivity in the software development process. This paper analyses reuse within requirements engineering phase by taking and adapting a standard functional size measurement method, COSMIC FFP. Our proposal attempts to quantify reusability
Presentation: Overview of Water Reuse Challenges and Opportunities
This presentation, Overview of Water Reuse Challenges and Opportunities, was given at the STAR Human and Ecological Health Impacts Associated with Water Reuse and Conservation Practices Kick-off Meeting and Webinar held on Oct. 26-27, 2016.
Qualitative monitoring of a treated wastewater reuse extensive ...
African Journals Online (AJOL)
Qualitative monitoring of a treated wastewater reuse extensive distribution system: ... region where 80 % of the freshwater resources are consumed by agriculture. ... the reuse limits for orchard irrigation, being 80 mg/ℓ and 25 mg/ℓ respectively.
Wastewater and sludge reuse in agriculture
Kalavrouziotis, Ioannis
2016-04-01
The reuse of Municipal wastewaters (TMWW) for irrigation of crops, and of sludge for the amendment of soils, is a multidimensional disposal practice aiming at: (i) minimizing the environmental problems by releasing the pressure exerted by these two inputs on the environment, (ii) providing the growing plants with water and nutrients and (ii) improving soil fertility and productivity, The research work conducted in our University in relation to accomplishing a safe reuse has been focused on the study of the following aspects of reuse: (i) heavy metal accumulation in soils and plants with emphasis on their edible part. This aspect has been studied by conducting a series of experiments aiming at the study of the accumulation of heavy metals in soils, and in plant roots, stalks, leaves and fruits. The conclusions drawn so far with regard to the order of accumulation of heavy metals are: Roots>leaves>stalks>fruits ( edible parts) (ii) interactions between heavy metals, plant nutrients and soil chemical and physical properties. After the examinations of hundreds of interactions, and the development of a quantification of the interactions contribution, it was found that considerable quantities of heavy metals and nutrients are contributed to the soil and to various plant parts , emphasizing the important role of the elemental interactions in plants.(iii) assessment of soil pollution with heavy metals based on pollution indices, Three pollution Indices have been established by our research team and were proposed internationally for application in actual practice for the prediction of soil pollution due to long term reuse of wastewater and sludge. These indices are as follows: (a) Elemental pollution Index (EPI), (b) Heavy Metal Load (HML), and (c) Total Concentration Factor (TCF) and (iv) construction of a computer program for the control of the reuse of TMWW and sludge, and forecasting soil pollution due to accumulation of heavy metal by means of pollution indices.
Savannah River Site Surplus Facilities Available for Reuse
International Nuclear Information System (INIS)
Clarke, R.M.; Owens, M.B.; Lentz, D.W.
1995-01-01
The purpose of this document is to provide a current, centralized list of Savannah River Site facilities, which are surplus and available for reuse. These surplus facilities may be made available for other DOE site missions, commercial economic development reuse, or other governmental reuse. SRS procedures also require that before new construction can be approved, available surplus facilities are screened for possible reuse in lieu of the proposed new construction
How Governance Regimes Shape the Implementation of Water Reuse Schemes
Frijns, Jos; Smith, Heather M.; Brouwer, Stijn; Garnett, Kenisha; Elelman, Richard; Jeffrey, Paul
2016-01-01
The governance dimensions of water reuse scheme development and operation, such as policies and regulatory frameworks, and public involvement and stakeholder collaboration, can serve to both facilitate and constrain wider adoption of water reuse practices. This paper explores the significance and underlying structure of the key governance challenges facing the water reuse sector in Europe. It presents empirical evidence from interviews and focus group sessions conducted at four water reuse sc...
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-02-01
From October 22-24, 1996 the University of Tennessee`s Energy, Environment and Resources Center and the Oak Ridge National Laboratory`s Center for Risk Management cosponsored Beneficial Reuse `96: The Fourth Annual Conference on the Recycle and Reuse of Radioactive Materials. Along with the traditional focus on radioactive scrap metals, this year`s conference included a wide range of topics pertaining to naturally occurring radioactive materials (NORM), and contaminated concrete reuse applications. As with previous Beneficial Reuse conferences, the primary goal of this year`s conference was to bring together stakeholder representatives for presentations, panel sessions and workshops on significant waste minimization issues surrounding the recycle and reuse of contaminated metals and other materials. A wide range of industry, government and public stakeholder groups participated in this year`s conference. An international presence from Canada, Germany and Korea helped to make Beneficial Reuse `96 a well-rounded affair. Selected papers have been processed separately for inclusion in the Energy Science and Technology Database.
Development of waste water reuse water system for power plants
Energy Technology Data Exchange (ETDEWEB)
Park, K K; Kim, D H; Weon, D Y; Yoon, S W; Song, H R [Korea Electric Power Research Institute, Taejeon (Korea, Republic of)
1998-12-31
1. Status of waste water discharge at power plants 2. Present status of waste water reuse at power plants 3. Scheme of waste water reuse at power plants 4. Standardization of optimum system for waste water reuse at power plants 5. Establishment of low cost zero discharge system for waste water 6. Waste water treatment technology of chemical cleaning. (author). 132 figs., 72 tabs.
Patterns of Learning Object Reuse in the Connexions Repository
Duncan, S. M.
2009-01-01
Since the term "learning object" was first published, there has been either an explicit or implicit expectation of reuse. There has also been a lot of speculation about why learning objects are, or are not, reused. This study quantitatively examined the actual amount and type of learning object use, to include reuse, modification, and translation,…
Conceptual Match as a Determinant of Reference Reuse in Dialogue
Knutsen, Dominique; Le Bigot, Ludovic
2017-01-01
As speakers interact, they add references to their common ground, which they can then reuse to facilitate listener comprehension. However, all references are not equally likely to be reused. The purpose of this study was to shed light on how the speakers' conceptualizations of the referents under discussion affect reuse (along with a generation…
Development of waste water reuse water system for power plants
Energy Technology Data Exchange (ETDEWEB)
Park, K.K.; Kim, D.H.; Weon, D.Y.; Yoon, S.W.; Song, H.R. [Korea Electric Power Research Institute, Taejeon (Korea, Republic of)
1997-12-31
1. Status of waste water discharge at power plants 2. Present status of waste water reuse at power plants 3. Scheme of waste water reuse at power plants 4. Standardization of optimum system for waste water reuse at power plants 5. Establishment of low cost zero discharge system for waste water 6. Waste water treatment technology of chemical cleaning. (author). 132 figs., 72 tabs.
How Governance Regimes Shape the Implementation of Water Reuse Schemes
Directory of Open Access Journals (Sweden)
Jos Frijns
2016-12-01
Full Text Available The governance dimensions of water reuse scheme development and operation, such as policies and regulatory frameworks, and public involvement and stakeholder collaboration, can serve to both facilitate and constrain wider adoption of water reuse practices. This paper explores the significance and underlying structure of the key governance challenges facing the water reuse sector in Europe. It presents empirical evidence from interviews and focus group sessions conducted at four water reuse schemes: an indirect potable reuse scheme at Torreele (Belgium, the urban reuse of treated municipal wastewater at the London Olympic Park (United Kingdom and at Sabadell (Spain, and the reuse of agro-industrial effluent for irrigation at Capitanata (Italy. The findings underscore the importance of clarity in policy arrangements around water reuse, as well as of the financial competitiveness of reuse projects compared to alternative water supply options. Operators of water reuse schemes expressed a preference for water quality standards, which focus on appropriateness for use rather than over-emphasise the waters’ origin so that unnecessary treatment and costs can be avoided. Positive public support was widely acknowledged as an important factor in the success or failure of water reuse schemes. We conclude that constructive institutional relationships underpin many of the challenges faced by reuse scheme operators and that greater emphasis should be given to building confidence and gaining trust in water service providers through early identification of how governance regimes shape the viability of new schemes.
Picking Up Artifacts: Storyboarding as a Gateway to Reuse
Wahid, Shahtab; Branham, Stacy M.; Cairco, Lauren; McCrickard, D. Scott; Harrison, Steve
Storyboarding offers designers the opportunity to illustrate a visual narrative of use. Because designers often refer to past ideas, we argue storyboards can be constructed by reusing shared artifacts. We present a study in which we explore how designers reuse artifacts consisting of images and rationale during storyboard construction. We find images can aid in accessing rationale and that connections among features aid in deciding what to reuse, creating new artifacts, and constructing. Based on requirements derived from our findings, we present a storyboarding tool, PIC-UP, to facilitate artifact sharing and reuse and evaluate its use in an exploratory study. We conclude with remarks on facilitating reuse and future work.
Direct Reuse of Rare Earth Permanent Magnets—Coating Integrity
DEFF Research Database (Denmark)
Høgberg, Stig; Holbøll, Joachim; Mijatovic, Nenad
2017-01-01
Rare earth permanent magnets can be reused directly as an alternative to traditional recycling methods, in which scrapped magnets are reprocessed into new magnets by undergoing many of the original energy-intensive and expensive production processes. Direct reuse entails using segmented magnet...... assemblies built by several small standard-sized magnets that can be reused directly in a number of different applications. A central part of the direct reuse strategy is to separate and demagnetize magnets by heating them to the Curie temperature. We investigated the validity of direct reuse as a rare earth...
Study on the reuse of nodular casting
International Nuclear Information System (INIS)
Bermont, V.M; Gomez, C.A; Lamas, J.F; Castillo, R.N
2004-01-01
Nodular cast pieces that have worn out are an attractive alternative to be reused as a cheap raw material for directly making other pieces. This materials recycling process often requires new and successive thermal treatments in order to be machined, to obtain the proper mechanical and microstructural properties. This work includes the results of the microstructural analysis by optic and Scanning Electron Microscopy and of the mechanical tests for traction and hardness of the test pieces submitted to different successive thermal treatments. The results show that by means of successive thermal treatments, followed by austemperizing, the appropriate mechanical and microstructural properties can be recovered permitting the nodular castings that were studied to be reliably reused (CW)
The Adaptive Reuse of Kirkuk Citadel
Mokhtar, Mustafa Sabah Saleh; Korumaz, Mustafa
2017-01-01
Knowledge and memory influence the interpretations of a built environment, implying particular expectations in regard to the built environments and their roles in a society. People and their culture constitute the spirits of a building and a space. Memory also can dominate many heritage users, individuals, social and political groups over many centuries. Memory and spirit of cultural heritage enriches cultural identity under the global development. The adaptive reuse of heritage buildings is ...
Reuse and recycling of radioactive material packaging
International Nuclear Information System (INIS)
Gerulis, Eduardo; Zapparoli, Carlos Leonel; Barboza, Marycel Figols de
2009-01-01
Human development is directly linked to energy consumption. The political decisions (to this human development) result in economic, social and environmental aspects, whose magnitude should maintain the sustainability of every aspect for not to collapsing. The environmental aspect has been a target of research because of the excessive emission of gases which contributes to the greenhouse effect. The production processes emit gases due to the consumption of energy to get it, but it is necessary to maintain the environmental sustainability in order to minimize the contribution to the emission of greenhouse gases. The population control and the energetic efficiency are factors that contribute to the environmental sustainability. Besides them, the culture of consumption is another factor that, when applied to the reduction of emissions, also contributes to the sustainability of the environment. The reuse of materials is one of the sub-factors which contribute to the reduction of emissions. The Radiopharmacy Directory (DIRF) at IPEN-CNEN/SP, produces radiopharmaceuticals that are necessary to improve the Brazilian population's life quality. The radiopharmaceuticals are transported in packaging to the transport of radioactive material. These packages are considered non-biodegradable, because some metals, which make up these packages, pollute the environment. These packages have increased costs, in addition, because it must be approved in tests of integrity. The reuse of packaging in favorable situations to the same purpose is a way to help the environment degradation and costs reduction. The packaging reuse in unfavorable situations disobey rules or return logistics that become effective the transport back, but the consumption culture strengthening can change this situation. This paper describes IPEN's packaging, form and quantities distribution, and the packaging that comes back to be reused. (author)
Heterogeneous IP Ecosystem enabling Reuse (HIER)
2017-03-22
HIER project, DARPA also established additional concepts in the formation of the Common Heterogeneous Integration and IP Reuse Strategies (CHIPS...would need a major change to business model to offer Hard or Soft IP – So CHIPS program can be a better fit to these firms • DoD‐Contractor IP pricing
Hybrid membrane processes for water reuse
Pidou, Marc
2006-01-01
Water recycling is now widely accepted as a sustainable option to respond to the general increase of the fresh water demand, water shortages and for environment protection. Because greywater represents up to 70% of domestic wastewater volume but contains only 30% of the organic fraction and from 9 to 20% of the nutrients (Kujawa-Roeleveld and Zeeman, 2006), it is seen as one of the most appropriate sources to be treated and reuse. A broad range of technologies has been used for...
Electrodialysis and water reuse novel approaches
Rodrigues, Marco; Ferreira, Jane
2014-01-01
This book presents novel techniques to evaluate electrodialysis processes, to synthesize ionic membranes and to characterize their properties. It shows the potential use of membrane process to the treatment of effluents generated in many industrial sectors such as refineries, leather industries, mining and electroplating processes. The book is based on the results obtained by the author's research group during the past decade. It is useful for students, researchers and engineers interested in membrane technologies for water reuse.
Energy Technology Data Exchange (ETDEWEB)
Sakata, Fumihiko [Tokyo Univ., Tanashi (Japan). Inst. for Nuclear Study; Yamamoto, Yoshifumi; Marumori, Toshio; Iida, Shinji; Tsukuma, Hidehiko
1989-11-01
It is the purpose of the present paper to study 'global structure' of the state space of an N-body interacting fermion system, which exhibits regular, transient and stochastic phases depending on strength of the interaction. An optimum representation called a dynamical representation plays an essential role in this investigation. The concept of the dynamical representation has been introduced in the quantum theory of dynamical subspace in our previous paper, in order to determine self-consistently an optimum collective subspace as well as an optimum collective Hamiltonian. In the theory, furthermore, dynamical conditions called separability and stability conditions have been provided in order to identify the optimum collective subspace as an approximate invariant subspace of the Hamiltonian. Physical meaning of these conditions are clarified from a viewpoint to relate breaking of them with bifurcation of the collectivity and an onset of quantum chaos from the regular collective motion, by illustrating the general idea with numerical results obtained for a simple soluble model. It turns out that the onset of the stochastic phase is associated with dissolution of the quantum numbers to specify the collective subspace and this dissolution is induced by the breaking of the separability condition in the dynamical representation. (author).
SRS stainless steel beneficial reuse program
Energy Technology Data Exchange (ETDEWEB)
Boettinger, W.L.
1997-02-01
The US Department of Energy`s (DOE) Savannah River Site (SRS) has thousands of tons of stainless steel radioactive scrap metal (RSNI). Much of the metal is volumetrically contaminated. There is no {open_quotes}de minimis{close_quotes} free release level for volumetric material, and therefore no way to recycle the metal into the normal commercial market. If declared waste, the metal would qualify as low level radioactive waste (LLW) and ultimately be dispositioned through shallow land buried at a cost of millions of dollars. The metal however could be recycled in a {open_quotes}controlled release{close_quote} manner, in the form of containers to hold other types of radioactive waste. This form of recycle is generally referred to as {open_quotes}Beneficial Reuse{close_quotes}. Beneficial reuse reduces the amount of disposal space needed and reduces the need for virgin containers which would themselves become contaminated. Stainless steel is particularly suited for long term storage because of its resistance to corrosion. To assess the practicality of stainless steel RSM recycle the SRS Benficial Reuse Program began a demonstration in 1994, funded by the DOE Office of Science and Technology. This paper discusses the experiences gained in this program.
International Nuclear Information System (INIS)
Yi-Min, Wang; Yan-Li, Zhou; Lin-Mei, Liang; Cheng-Zu, Li
2009-01-01
We propose a feasible scheme to achieve universal quantum gate operations in decoherence-free subspace with superconducting charge qubits placed in a microwave cavity. Single-logic-qubit gates can be realized with cavity assisted interaction, which possesses the advantages of unconventional geometric gate operation. The two-logic-qubit controlled-phase gate between subsystems can be constructed with the help of a variable electrostatic transformer. The collective decoherence can be successfully avoided in our well-designed system. Moreover, GHZ state for logical qubits can also be easily produced in this system
Consistency analysis of subspace identification methods based on a linear regression approach
DEFF Research Database (Denmark)
Knudsen, Torben
2001-01-01
In the literature results can be found which claim consistency for the subspace method under certain quite weak assumptions. Unfortunately, a new result gives a counter example showing inconsistency under these assumptions and then gives new more strict sufficient assumptions which however does n...... not include important model structures as e.g. Box-Jenkins. Based on a simple least squares approach this paper shows the possible inconsistency under the weak assumptions and develops only slightly stricter assumptions sufficient for consistency and which includes any model structure...
Subspace Barzilai-Borwein Gradient Method for Large-Scale Bound Constrained Optimization
International Nuclear Information System (INIS)
Xiao Yunhai; Hu Qingjie
2008-01-01
An active set subspace Barzilai-Borwein gradient algorithm for large-scale bound constrained optimization is proposed. The active sets are estimated by an identification technique. The search direction consists of two parts: some of the components are simply defined; the other components are determined by the Barzilai-Borwein gradient method. In this work, a nonmonotone line search strategy that guarantees global convergence is used. Preliminary numerical results show that the proposed method is promising, and competitive with the well-known method SPG on a subset of bound constrained problems from CUTEr collection
Experimental Study of Generalized Subspace Filters for the Cocktail Party Situation
DEFF Research Database (Denmark)
Christensen, Knud Bank; Christensen, Mads Græsbøll; Boldt, Jesper B.
2016-01-01
This paper investigates the potential performance of generalized subspace filters for speech enhancement in cocktail party situations with very poor signal/noise ratio, e.g. down to -15 dB. Performance metrics output signal/noise ratio, signal/ distortion ratio, speech quality rating and speech...... intelligibility rating are mapped as functions of two algorithm parameters, revealing clear trade-off options between noise, distortion and subjective performances and a recommended choice of trade-off. Given sufficiently good noise statistics, SNR improvements around 20 dB as well as PESQ quality and STOI...
A Comfort-Aware Energy Efficient HVAC System Based on the Subspace Identification Method
Directory of Open Access Journals (Sweden)
O. Tsakiridis
2016-01-01
Full Text Available A proactive heating method is presented aiming at reducing the energy consumption in a HVAC system while maintaining the thermal comfort of the occupants. The proposed technique fuses time predictions for the zones’ temperatures, based on a deterministic subspace identification method, and zones’ occupancy predictions, based on a mobility model, in a decision scheme that is capable of regulating the balance between the total energy consumed and the total discomfort cost. Simulation results for various occupation-mobility models demonstrate the efficiency of the proposed technique.
Practical Low Data-Complexity Subspace-Trail Cryptanalysis of Round-Reduced PRINCE
DEFF Research Database (Denmark)
Grassi, Lorenzo; Rechberger, Christian
2016-01-01
Subspace trail cryptanalysis is a very recent new cryptanalysis technique, and includes differential, truncated differential, impossible differential, and integral attacks as special cases. In this paper, we consider PRINCE, a widely analyzed block cipher proposed in 2012. After the identification......-plaintext category. The attacks have been verified using a C implementation. Of independent interest, we consider a variant of PRINCE in which ShiftRows and MixLayer operations are exchanged in position. In particular, our result shows that the position of ShiftRows and MixLayer operations influences the security...
Random subspaces for encryption based on a private shared Cartesian frame
International Nuclear Information System (INIS)
Bartlett, Stephen D.; Hayden, Patrick; Spekkens, Robert W.
2005-01-01
A private shared Cartesian frame is a novel form of private shared correlation that allows for both private classical and quantum communication. Cryptography using a private shared Cartesian frame has the remarkable property that asymptotically, if perfect privacy is demanded, the private classical capacity is three times the private quantum capacity. We demonstrate that if the requirement for perfect privacy is relaxed, then it is possible to use the properties of random subspaces to nearly triple the private quantum capacity, almost closing the gap between the private classical and quantum capacities
Towards automatic music transcription: note extraction based on independent subspace analysis
Wellhausen, Jens; Hoynck, Michael
2005-01-01
Due to the increasing amount of music available electronically the need of automatic search, retrieval and classification systems for music becomes more and more important. In this paper an algorithm for automatic transcription of polyphonic piano music into MIDI data is presented, which is a very interesting basis for database applications, music analysis and music classification. The first part of the algorithm performs a note accurate temporal audio segmentation. In the second part, the resulting segments are examined using Independent Subspace Analysis to extract sounding notes. Finally, the results are used to build a MIDI file as a new representation of the piece of music which is examined.
Dai, Kaoshan; Wang, Ying; Lu, Wensheng; Ren, Xiaosong; Huang, Zhenhua
2017-04-01
Structural health monitoring (SHM) of wind turbines has been applied in the wind energy industry to obtain their real-time vibration parameters and to ensure their optimum performance. For SHM, the accuracy of its results and the efficiency of its measurement methodology and data processing algorithm are the two major concerns. Selection of proper measurement parameters could improve such accuracy and efficiency. The Stochastic Subspace Identification (SSI) is a widely used data processing algorithm for SHM. This research discussed the accuracy and efficiency of SHM using SSI method to identify vibration parameters of on-line wind turbine towers. Proper measurement parameters, such as optimum measurement duration, are recommended.
Speech Denoising in White Noise Based on Signal Subspace Low-rank Plus Sparse Decomposition
Directory of Open Access Journals (Sweden)
yuan Shuai
2017-01-01
Full Text Available In this paper, a new subspace speech enhancement method using low-rank and sparse decomposition is presented. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank for the underlying human speech signal. Then the low-rank and sparse decomposition is performed with the guidance of speech rank value to remove the noise. Extensive experiments have been carried out in white Gaussian noise condition, and experimental results show the proposed method performs better than conventional speech enhancement methods, in terms of yielding less residual noise and lower speech distortion.
International Nuclear Information System (INIS)
Zhang, Liangwei; Lin, Jing; Karim, Ramin
2015-01-01
The accuracy of traditional anomaly detection techniques implemented on full-dimensional spaces degrades significantly as dimensionality increases, thereby hampering many real-world applications. This work proposes an approach to selecting meaningful feature subspace and conducting anomaly detection in the corresponding subspace projection. The aim is to maintain the detection accuracy in high-dimensional circumstances. The suggested approach assesses the angle between all pairs of two lines for one specific anomaly candidate: the first line is connected by the relevant data point and the center of its adjacent points; the other line is one of the axis-parallel lines. Those dimensions which have a relatively small angle with the first line are then chosen to constitute the axis-parallel subspace for the candidate. Next, a normalized Mahalanobis distance is introduced to measure the local outlier-ness of an object in the subspace projection. To comprehensively compare the proposed algorithm with several existing anomaly detection techniques, we constructed artificial datasets with various high-dimensional settings and found the algorithm displayed superior accuracy. A further experiment on an industrial dataset demonstrated the applicability of the proposed algorithm in fault detection tasks and highlighted another of its merits, namely, to provide preliminary interpretation of abnormality through feature ordering in relevant subspaces. - Highlights: • An anomaly detection approach for high-dimensional reliability data is proposed. • The approach selects relevant subspaces by assessing vectorial angles. • The novel ABSAD approach displays superior accuracy over other alternatives. • Numerical illustration approves its efficacy in fault detection applications
Simultaneous multislice magnetic resonance fingerprinting with low-rank and subspace modeling.
Bo Zhao; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A; Wald, Lawrence L; Setsompop, Kawin
2017-07-01
Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T 1 , T 2 , and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3× speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice.
Robust Switching Control and Subspace Identification for Flutter of Flexible Wing
Directory of Open Access Journals (Sweden)
Yizhe Wang
2018-01-01
Full Text Available Active flutter suppression and subspace identification for a flexible wing model using micro fiber composite actuator were experimentally studied in a low speed wind tunnel. NACA0006 thin airfoil model was used for the experimental object to verify the performance of identification algorithm and designed controller. The equation of the fluid, vibration, and piezoelectric coupled motion was theoretically analyzed and experimentally identified under the open-loop and closed-loop condition by subspace method for controller design. A robust pole placement algorithm in terms of linear matrix inequality that accommodates the model uncertainty caused by identification deviation and flow speed variation was utilized to stabilize the divergent aeroelastic system. For further enlarging the flutter envelope, additional controllers were designed subject to the models beyond the flutter speed. Wind speed was measured online as the decision parameter of switching between the controllers. To ensure the stability of arbitrary switching, Common Lyapunov function method was applied to design the robust pole placement controllers for different models to ensure that the closed-loop system shared a common Lyapunov function. Wind tunnel result showed that the designed controllers could stabilize the time varying aeroelastic system over a wide range under arbitrary switching.
An Improved EMD-Based Dissimilarity Metric for Unsupervised Linear Subspace Learning
Directory of Open Access Journals (Sweden)
Xiangchun Yu
2018-01-01
Full Text Available We investigate a novel way of robust face image feature extraction by adopting the methods based on Unsupervised Linear Subspace Learning to extract a small number of good features. Firstly, the face image is divided into blocks with the specified size, and then we propose and extract pooled Histogram of Oriented Gradient (pHOG over each block. Secondly, an improved Earth Mover’s Distance (EMD metric is adopted to measure the dissimilarity between blocks of one face image and the corresponding blocks from the rest of face images. Thirdly, considering the limitations of the original Locality Preserving Projections (LPP, we proposed the Block Structure LPP (BSLPP, which effectively preserves the structural information of face images. Finally, an adjacency graph is constructed and a small number of good features of a face image are obtained by methods based on Unsupervised Linear Subspace Learning. A series of experiments have been conducted on several well-known face databases to evaluate the effectiveness of the proposed algorithm. In addition, we construct the noise, geometric distortion, slight translation, slight rotation AR, and Extended Yale B face databases, and we verify the robustness of the proposed algorithm when faced with a certain degree of these disturbances.
Directory of Open Access Journals (Sweden)
Omar Eldwaik
2018-01-01
Full Text Available Wind induced noise is one of the major concerns of outdoor acoustic signal acquisition. It affects many field measurement and audio recording scenarios. Filtering such noise is known to be difficult due to its broadband and time varying nature. In this paper, a new method to mitigate wind induced noise in microphone signals is developed. Instead of applying filtering techniques, wind induced noise is statistically separated from wanted signals in a singular spectral subspace. The paper is presented in the context of handling microphone signals acquired outdoor for acoustic sensing and environmental noise monitoring or soundscapes sampling. The method includes two complementary stages, namely decomposition and reconstruction. The first stage decomposes mixed signals in eigen-subspaces, selects and groups the principal components according to their contributions to wind noise and wanted signals in the singular spectrum domain. The second stage reconstructs the signals in the time domain, resulting in the separation of wind noise and wanted signals. Results show that microphone wind noise is separable in the singular spectrum domain evidenced by the weighted correlation. The new method might be generalized to other outdoor sound acquisition applications.
International Nuclear Information System (INIS)
Abdel-Khalik, Hany S.; Zhang, Qiong
2014-01-01
The development of hybrid Monte-Carlo-Deterministic (MC-DT) approaches, taking place over the past few decades, have primarily focused on shielding and detection applications where the analysis requires a small number of responses, i.e. at the detector locations(s). This work further develops a recently introduced global variance reduction approach, denoted by the SUBSPACE approach is designed to allow the use of MC simulation, currently limited to benchmarking calculations, for routine engineering calculations. By way of demonstration, the SUBSPACE approach is applied to assembly level calculations used to generate the few-group homogenized cross-sections. These models are typically expensive and need to be executed in the order of 10 3 - 10 5 times to properly characterize the few-group cross-sections for downstream core-wide calculations. Applicability to k-eigenvalue core-wide models is also demonstrated in this work. Given the favorable results obtained in this work, we believe the applicability of the MC method for reactor analysis calculations could be realized in the near future.
Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.
Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L
2018-02-01
This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Gene selection for microarray data classification via subspace learning and manifold regularization.
Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui
2017-12-19
With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.
Structural damage diagnosis based on on-line recursive stochastic subspace identification
International Nuclear Information System (INIS)
Loh, Chin-Hsiung; Weng, Jian-Huang; Liu, Yi-Cheng; Lin, Pei-Yang; Huang, Shieh-Kung
2011-01-01
This paper presents a recursive stochastic subspace identification (RSSI) technique for on-line and almost real-time structural damage diagnosis using output-only measurements. Through RSSI the time-varying natural frequencies of a system can be identified. To reduce the computation time in conducting LQ decomposition in RSSI, the Givens rotation as well as the matrix operation appending a new data set are derived. The relationship between the size of the Hankel matrix and the data length in each shifting moving window is examined so as to extract the time-varying features of the system without loss of generality and to establish on-line and almost real-time system identification. The result from the RSSI technique can also be applied to structural damage diagnosis. Off-line data-driven stochastic subspace identification was used first to establish the system matrix from the measurements of an undamaged (reference) case. Then the RSSI technique incorporating a Kalman estimator is used to extract the dynamic characteristics of the system through continuous monitoring data. The predicted residual error is defined as a damage feature and through the outlier statistics provides an indicator of damage. Verification of the proposed identification algorithm by using the bridge scouring test data and white noise response data of a reinforced concrete frame structure is conducted
Quantum probabilities as Dempster-Shafer probabilities in the lattice of subspaces
International Nuclear Information System (INIS)
Vourdas, A.
2014-01-01
The orthocomplemented modular lattice of subspaces L[H(d)], of a quantum system with d-dimensional Hilbert space H(d), is considered. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L[H(d)] (it is only valid within the Boolean subalgebras of L[H(d)]). This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. An operator D(H 1 ,H 2 ), which quantifies deviations from Kolmogorov probability theory is introduced, and it is shown to be intimately related to the commutator of the projectors P(H 1 ),P(H 2 ), to the subspaces H 1 , H 2 . As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities
High resolution through-the-wall radar image based on beamspace eigenstructure subspace methods
Yoon, Yeo-Sun; Amin, Moeness G.
2008-04-01
Through-the-wall imaging (TWI) is a challenging problem, even if the wall parameters and characteristics are known to the system operator. Proper target classification and correct imaging interpretation require the application of high resolution techniques using limited array size. In inverse synthetic aperture radar (ISAR), signal subspace methods such as Multiple Signal Classification (MUSIC) are used to obtain high resolution imaging. In this paper, we adopt signal subspace methods and apply them to the 2-D spectrum obtained from the delay-andsum beamforming image. This is in contrast to ISAR, where raw data, in frequency and angle, is directly used to form the estimate of the covariance matrix and array response vector. Using beams rather than raw data has two main advantages, namely, it improves the signal-to-noise ratio (SNR) and can correctly image typical indoor extended targets, such as tables and cabinets, as well as point targets. The paper presents both simulated and experimental results using synthesized and real data. It compares the performance of beam-space MUSIC and Capon beamformer. The experimental data is collected at the test facility in the Radar Imaging Laboratory, Villanova University.
On the selection of user-defined parameters in data-driven stochastic subspace identification
Priori, C.; De Angelis, M.; Betti, R.
2018-02-01
The paper focuses on the time domain output-only technique called Data-Driven Stochastic Subspace Identification (DD-SSI); in order to identify modal models (frequencies, damping ratios and mode shapes), the role of its user-defined parameters is studied, and rules to determine their minimum values are proposed. Such investigation is carried out using, first, the time histories of structural responses to stationary excitations, with a large number of samples, satisfying the hypothesis on the input imposed by DD-SSI. Then, the case of non-stationary seismic excitations with a reduced number of samples is considered. In this paper, partitions of the data matrix different from the one proposed in the SSI literature are investigated, together with the influence of different choices of the weighting matrices. The study is carried out considering two different applications: (1) data obtained from vibration tests on a scaled structure and (2) in-situ tests on a reinforced concrete building. Referring to the former, the identification of a steel frame structure tested on a shaking table is performed using its responses in terms of absolute accelerations to a stationary (white noise) base excitation and to non-stationary seismic excitations of low intensity. Black-box and modal models are identified in both cases and the results are compared with those from an input-output subspace technique. With regards to the latter, the identification of a complex hospital building is conducted using data obtained from ambient vibration tests.
Jalaleddini, Kian; Tehrani, Ehsan Sobhani; Kearney, Robert E
2017-06-01
The purpose of this paper is to present a structural decomposition subspace (SDSS) method for decomposition of the joint torque to intrinsic, reflexive, and voluntary torques and identification of joint dynamic stiffness. First, it formulates a novel state-space representation for the joint dynamic stiffness modeled by a parallel-cascade structure with a concise parameter set that provides a direct link between the state-space representation matrices and the parallel-cascade parameters. Second, it presents a subspace method for the identification of the new state-space model that involves two steps: 1) the decomposition of the intrinsic and reflex pathways and 2) the identification of an impulse response model of the intrinsic pathway and a Hammerstein model of the reflex pathway. Extensive simulation studies demonstrate that SDSS has significant performance advantages over some other methods. Thus, SDSS was more robust under high noise conditions, converging where others failed; it was more accurate, giving estimates with lower bias and random errors. The method also worked well in practice and yielded high-quality estimates of intrinsic and reflex stiffnesses when applied to experimental data at three muscle activation levels. The simulation and experimental results demonstrate that SDSS accurately decomposes the intrinsic and reflex torques and provides accurate estimates of physiologically meaningful parameters. SDSS will be a valuable tool for studying joint stiffness under functionally important conditions. It has important clinical implications for the diagnosis, assessment, objective quantification, and monitoring of neuromuscular diseases that change the muscle tone.
Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang
2018-05-08
When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.
Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan
2018-02-01
In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.
Energy Technology Data Exchange (ETDEWEB)
Renaut, R.; He, Q. [Arizona State Univ., Tempe, AZ (United States)
1994-12-31
In a new parallel iterative algorithm for unconstrained optimization by multisplitting is proposed. In this algorithm the original problem is split into a set of small optimization subproblems which are solved using well known sequential algorithms. These algorithms are iterative in nature, e.g. DFP variable metric method. Here the authors use sequential algorithms based on an inexact subspace search, which is an extension to the usual idea of an inexact fine search. Essentially the idea of the inexact line search for nonlinear minimization is that at each iteration the authors only find an approximate minimum in the line search direction. Hence by inexact subspace search, they mean that, instead of finding the minimum of the subproblem at each interation, they do an incomplete down hill search to give an approximate minimum. Some convergence and numerical results for this algorithm will be presented. Further, the original theory will be generalized to the situation with a singular Hessian. Applications for nonlinear least squares problems will be presented. Experimental results will be presented for implementations on an Intel iPSC/860 Hypercube with 64 nodes as well as on the Intel Paragon.
Directory of Open Access Journals (Sweden)
Alim Samat
2016-03-01
Full Text Available In order to deal with scenarios where the training data, used to deduce a model, and the validation data have different statistical distributions, we study the problem of transformed subspace feature transfer for domain adaptation (DA in the context of hyperspectral image classification via a geodesic Gaussian flow kernel based support vector machine (GFKSVM. To show the superior performance of the proposed approach, conventional support vector machines (SVMs and state-of-the-art DA algorithms, including information-theoretical learning of discriminative cluster for domain adaptation (ITLDC, joint distribution adaptation (JDA, and joint transfer matching (JTM, are also considered. Additionally, unsupervised linear and nonlinear subspace feature transfer techniques including principal component analysis (PCA, randomized nonlinear principal component analysis (rPCA, factor analysis (FA and non-negative matrix factorization (NNMF are investigated and compared. Experiments on two real hyperspectral images show the cross-image classification performances of the GFKSVM, confirming its effectiveness and suitability when applied to hyperspectral images.
On the Kalman Filter error covariance collapse into the unstable subspace
Directory of Open Access Journals (Sweden)
A. Trevisan
2011-03-01
Full Text Available When the Extended Kalman Filter is applied to a chaotic system, the rank of the error covariance matrices, after a sufficiently large number of iterations, reduces to N^{+} + N^{0} where N^{+} and N^{0} are the number of positive and null Lyapunov exponents. This is due to the collapse into the unstable and neutral tangent subspace of the solution of the full Extended Kalman Filter. Therefore the solution is the same as the solution obtained by confining the assimilation to the space spanned by the Lyapunov vectors with non-negative Lyapunov exponents. Theoretical arguments and numerical verification are provided to show that the asymptotic state and covariance estimates of the full EKF and of its reduced form, with assimilation in the unstable and neutral subspace (EKF-AUS are the same. The consequences of these findings on applications of Kalman type Filters to chaotic models are discussed.
Performance Efficient Launch Vehicle Recovery and Reuse
Reed, John G.; Ragab, Mohamed M.; Cheatwood, F. McNeil; Hughes, Stephen J.; Dinonno, J.; Bodkin, R.; Lowry, Allen; Brierly, Gregory T.; Kelly, John W.
2016-01-01
For decades, economic reuse of launch vehicles has been an elusive goal. Recent attempts at demonstrating elements of launch vehicle recovery for reuse have invigorated a debate over the merits of different approaches. The parameter most often used to assess the cost of access to space is dollars-per-kilogram to orbit. When comparing reusable vs. expendable launch vehicles, that ratio has been shown to be most sensitive to the performance lost as a result of enabling the reusability. This paper will briefly review the historical background and results of recent attempts to recover launch vehicle assets for reuse. The business case for reuse will be reviewed, with emphasis on the performance expended to recover those assets, and the practicality of the most ambitious reuse concept, namely propulsive return to the launch site. In 2015, United Launch Alliance (ULA) announced its Sensible, Modular, Autonomous Return Technology (SMART) reuse plan for recovery of the booster module for its new Vulcan launch vehicle. That plan employs a non-propulsive approach where atmospheric entry, descent and landing (EDL) technologies are utilized. Elements of such a system have a wide variety of applications, from recovery of launch vehicle elements in suborbital trajectories all the way to human space exploration. This paper will include an update on ULA's booster module recovery approach, which relies on Hypersonic Inflatable Aerodynamic Decelerator (HIAD) and Mid-Air Retrieval (MAR) technologies, including its concept of operations (ConOps). The HIAD design, as well as parafoil staging and MAR concepts, will be discussed. Recent HIAD development activities and near term plans including scalability, next generation materials for the inflatable structure and heat shield, and gas generator inflation systems will be provided. MAR topics will include the ConOps for recovery, helicopter selection and staging, and the state of the art of parachute recovery systems using large parafoils
Dynamic Membrane Technology for Printing Wastewater Reuse
Liu, Lin; Lu, Xujie; Chen, Jihua
As environmental regulations become rigid and the cost of freshwater increases, wastewater is considered as a major resource in China. The paper presented a study on the implementation of the advanced treatment process using dynamic membrane (DM) in reusing of printing wastewater. The DM was well formed by circulating 1.5g/L of PAC in 20 minutes, the trans-membrane pressure of 200 kPa and the cross-flow velocity of 0.75m/s. The printing effluents were treated in effluent treatment plants comprising a physicochemical option followed by biological process. The treated effluent contained chemical oxygen demand (COD), color and turbidity in the range of 45-60 mg/L, 0.030-0.045 (absorbance at 420 nm) and 3-5 NTU. The results showed that the COD, color and turbidity removal efficiencies of the DM permeate were 84%, 85% and 80%, respectively. The wastewater treated by DM was reused as process water and the final concentrated retentate could be discharged directly into sewage treatment works with no additional treatments. Cleaning and regeneration of DM were very convenient if necessary. The proper process was that the polluted DM was cleaned with tap water at high cross-flow velocity. When irreversible pollutants accumulate, it would be rinsed with chemicals tested and the membrane flux would be restored up to 95%. The result showed that DM was considered as a promising method for purification aimed at reuse of printing wastewater, resulting in direct environmental and economic benefits.
The Adaptive Reuse of Kirkuk Citadel
Directory of Open Access Journals (Sweden)
Mustafa Sabah Saleh Mokhtar
2017-12-01
Full Text Available Knowledge and memory influence the interpretations of a built environment, implying particular expectations in regard to the built environments and their roles in a society. People and their culture constitute the spirits of a building and a space. Memory also can dominate many heritage users, individuals, social and political groups over many centuries. Memory and spirit of cultural heritage enriches cultural identity under the global development. The adaptive reuse of heritage buildings is valued for the contribution for social and environmental sustainability as well as retaining memory. The inherent value of cultural heritage components and their place within the community’s memory helps to reinforce sense of place. In conservation sense identity, memory and the relationships of people give cultural significance to historical places. Evolution of the built environments bridges past and present to the future and embrace memory. However the cities as organisms are in a dilemma along with the loss of city memories and city spirits. These collective memories that bring spirits to a place play very important role and determine the cultural significance of places. The main contribution of this study is to emphasize the importance of adaptive reuse as a carrier of spirits to have a collective memory in order to sustain the development of a place. This article explores the relations between spirit and memory of a place by focusing of adaptive reuse project in Kirkuk citadel. Aim of this study is to question and evaluate restoration of Kirkuk Citadel in terms of urban identity and sense of place referring the early Kirkuk city and development of it. This paper also intends to put important guidelines for the future restoration projects of Kirkuk citadel – which is very urgently required – and high lights the importance of revitalizing this area, which is now the semi-dead heart of the city. The paper advocates policy makers is to increase
[Filing and reuse of research data].
Osler, Merete; Bredahl, Lone; Ousager, Steen
2008-02-25
Currently several scientific journals only publish data from randomised clinical trials which are registered in a public database. Similar requirements on data sharing now follow grants from agencies such as the National Institute of Health. In Denmark the Health unit at the Danish Data Archive (DDA/Health) offers Danish researchers to keep their data for free on conditions that fulfil the above requirements. DDA/Health also passes on research data for reuse, and at present more than 300 studies are available in a database on sundhed.dda.dk.
Results on reuse of reclaimed shower water
Verostko, Charles E.; Garcia, Rafael; Pierson, Duane L.; Reysa, Richard P.; Irbe, Robert
1986-01-01
The Waste Water Recovery System that has been used in conjunction with a microgravity whole body shower to test a closed loop shower water reclamation system applicable to the NASA Space Station employs a Thermoelectric Integrated Hollow Fiber Membrane Evaporation Subsystem. Attention is given to the suitability of a Space Shuttle soap for such crew showers, the effects of shower water on the entire system, and the purification qualities of the recovered water. The chemical pretreatment of the shower water for microorganism control involved activated carbon, mixed ion exchange resin beds, and iodine bactericide dispensing units. The water was recycled five times, demonstrating the feasibility of reuse.
Wang, C.
2005-01-01
Lack of facilities in supporting design reuse is a serious problem in product shape modeling, especially in computer-aided design systems. This becomes a bottleneck of fast shape conceptualization and creation in consumer product design, which consequently prohibits creativity and innovation. In the
Water Reuse Highlights: A Summary Volume of Wastewater Reclamation and Reuse Information.
American Water Works Association, Denver, CO. Research Foundation.
This document reports the efforts of the AWWA Research Foundation to gather, prepare, and distribute current technical information in the wastewater reclamation and reuse field. The information reported has been abstracted from other Foundation publications and only attempts here to highlight the field. Categories discussed include research,…
Evaluation of appropriate technologies for grey water treatments and reuses.
Li, Fangyue; Wichmann, Knut; Otterpohl, Ralf
2009-01-01
As water is becoming a rare resource, the onsite reuse and recycling of grey water is practiced in many countries as a sustainable solution to reduce the overall urban water demand. However, the lack of appropriate water quality standards or guidelines has hampered the appropriate grey water reuses. Based on literature review, a non-potable urban grey water treatment and reuse scheme is proposed and the treatment alternatives for grey water reuse are evaluated according to the grey water characteristics, the proposed standards and economical feasibility.
Dialyzer Reuse and Outcomes of High Flux Dialysis.
Argyropoulos, Christos; Roumelioti, Maria-Eleni; Sattar, Abdus; Kellum, John A; Weissfeld, Lisa; Unruh, Mark L
2015-01-01
The bulk of randomized trial evidence for the expanding use of High Flux (HF) hemodialysis worldwide comes from two randomized controlled trials, one of which (HEMODIALYSIS, HEMO) allowed, while the other (Membrane Outcomes Permeability, MPO) excluded, the reuse of membranes. It is not known whether dialyzer reuse has a differential impact on outcomes with HF vs low flyx (LF) dialyzers. Proportional Hazards Models and Joint Models for longitudinal measures and survival outcomes were used in HEMO to analyze the relationship between β2-microglobulin (β2M) concentration, flux, and reuse. Meta-analysis and regression techniques were used to synthesize the evidence for HF dialysis from HEMO and MPO. In HEMO, minimally reused (membranes (p for interaction between reuse and flux benefit with more extensively reused dialyzers. Meta-regression of HEMO and MPO estimated an adjusted HR of 0.63 (95% CI: 0.51-0.78) for non-reused HF dialyzers compared with non-reused LF membranes. This secondary analysis and synthesis of two large hemodialysis trials supports the widespread use of HF dialyzers in clinical hemodialysis over the last decade. A mechanistic understanding of the effects of HF dialysis and the reuse process on dialyzers may suggest novel biomarkers for uremic toxicity and may accelerate membrane technology innovations that will improve patient outcomes.
Reuse inspection refort of the spent fuel cask
Energy Technology Data Exchange (ETDEWEB)
Park, S. W.; Seo, K. S.; Ku, J. H.; Lee, J. C.; Bang, K. S.; Min, D. K. [Korea Atomic Energy Research Institute, Taejeon (Korea)
2000-04-01
This is the contract result report performed by KAERI under the contract with KPS for the reuse inspection of the KSC-4 No. 2 cask to receive the license for the reuse of next 5 years. According to the revision of the atomic regulations, all type B package should receive and pass the reuse inspection for every 5 years. This report contains the summary of the reuse inspection project, the details of the inspection methods and evaluation criteria, the documents which submitted to the KINS and the license approved by the KINS. 1 tabs. (Author)
International Nuclear Information System (INIS)
Zou, Ling; Zhao, Haihua; Zhang, Hongbin
2015-01-01
Highlights: • Using high-resolution spatial scheme in solving two-phase flow problems. • Fully implicit time integrations scheme. • Jacobian-free Newton–Krylov method. • Analytical solution for two-phase water faucet problem. - Abstract: The majority of the existing reactor system analysis codes were developed using low-order numerical schemes in both space and time. In many nuclear thermal–hydraulics applications, it is desirable to use higher-order numerical schemes to reduce numerical errors. High-resolution spatial discretization schemes provide high order spatial accuracy in smooth regions and capture sharp spatial discontinuity without nonphysical spatial oscillations. In this work, we adapted an existing high-resolution spatial discretization scheme on staggered grids in two-phase flow applications. Fully implicit time integration schemes were also implemented to reduce numerical errors from operator-splitting types of time integration schemes. The resulting nonlinear system has been successfully solved using the Jacobian-free Newton–Krylov (JFNK) method. The high-resolution spatial discretization and high-order fully implicit time integration numerical schemes were tested and numerically verified for several two-phase test problems, including a two-phase advection problem, a two-phase advection with phase appearance/disappearance problem, and the water faucet problem. Numerical results clearly demonstrated the advantages of using such high-resolution spatial and high-order temporal numerical schemes to significantly reduce numerical diffusion and therefore improve accuracy. Our study also demonstrated that the JFNK method is stable and robust in solving two-phase flow problems, even when phase appearance/disappearance exists
Directory of Open Access Journals (Sweden)
Alexander Caicedo
2016-11-01
Full Text Available Clinical data is comprised by a large number of synchronously collected biomedical signals that are measured at different locations. Deciphering the interrelationships of these signals can yield important information about their dependence providing some useful clinical diagnostic data. For instance, by computing the coupling between Near-Infrared Spectroscopy signals (NIRS and systemic variables the status of the hemodynamic regulation mechanisms can be assessed. In this paper we introduce an algorithm for the decomposition of NIRS signals into additive components. The algorithm, SIgnal DEcomposition base on Obliques Subspace Projections (SIDE-ObSP, assumes that the measured NIRS signal is a linear combination of the systemic measurements, following the linear regression model y = Ax + _. SIDE-ObSP decomposes the output such that, each component in the decomposition represents the sole linear influence of one corresponding regressor variable. This decomposition scheme aims at providing a better understanding of the relation between NIRS and systemic variables, and to provide a framework for the clinical interpretation of regression algorithms, thereby, facilitating their introduction into clinical practice. SIDE-ObSP combines oblique subspace projections (ObSP with the structure of a mean average system in order to define adequate signal subspaces. To guarantee smoothness in the estimated regression parameters, as observed in normal physiological processes, we impose a Tikhonov regularization using a matrix differential operator. We evaluate the performance of SIDE-ObSP by using a synthetic dataset, and present two case studies in the field of cerebral hemodynamics monitoring using NIRS. In addition, we compare the performance of this method with other system identification techniques. In the first case study data from 20 neonates during the first three days of life was used, here SIDE-ObSP decoupled the influence of changes in arterial oxygen
Caicedo, Alexander; Varon, Carolina; Hunyadi, Borbala; Papademetriou, Maria; Tachtsidis, Ilias; Van Huffel, Sabine
2016-01-01
Clinical data is comprised by a large number of synchronously collected biomedical signals that are measured at different locations. Deciphering the interrelationships of these signals can yield important information about their dependence providing some useful clinical diagnostic data. For instance, by computing the coupling between Near-Infrared Spectroscopy signals (NIRS) and systemic variables the status of the hemodynamic regulation mechanisms can be assessed. In this paper we introduce an algorithm for the decomposition of NIRS signals into additive components. The algorithm, SIgnal DEcomposition base on Obliques Subspace Projections (SIDE-ObSP), assumes that the measured NIRS signal is a linear combination of the systemic measurements, following the linear regression model y = Ax + ϵ . SIDE-ObSP decomposes the output such that, each component in the decomposition represents the sole linear influence of one corresponding regressor variable. This decomposition scheme aims at providing a better understanding of the relation between NIRS and systemic variables, and to provide a framework for the clinical interpretation of regression algorithms, thereby, facilitating their introduction into clinical practice. SIDE-ObSP combines oblique subspace projections (ObSP) with the structure of a mean average system in order to define adequate signal subspaces. To guarantee smoothness in the estimated regression parameters, as observed in normal physiological processes, we impose a Tikhonov regularization using a matrix differential operator. We evaluate the performance of SIDE-ObSP by using a synthetic dataset, and present two case studies in the field of cerebral hemodynamics monitoring using NIRS. In addition, we compare the performance of this method with other system identification techniques. In the first case study data from 20 neonates during the first 3 days of life was used, here SIDE-ObSP decoupled the influence of changes in arterial oxygen saturation from the
Subspace Dimensionality: A Tool for Automated QC in Seismic Array Processing
Rowe, C. A.; Stead, R. J.; Begnaud, M. L.
2013-12-01
Because of the great resolving power of seismic arrays, the application of automated processing to array data is critically important in treaty verification work. A significant problem in array analysis is the inclusion of bad sensor channels in the beamforming process. We are testing an approach to automated, on-the-fly quality control (QC) to aid in the identification of poorly performing sensor channels prior to beam-forming in routine event detection or location processing. The idea stems from methods used for large computer servers, when monitoring traffic at enormous numbers of nodes is impractical on a node-by node basis, so the dimensionality of the node traffic is instead monitoried for anomalies that could represent malware, cyber-attacks or other problems. The technique relies upon the use of subspace dimensionality or principal components of the overall system traffic. The subspace technique is not new to seismology, but its most common application has been limited to comparing waveforms to an a priori collection of templates for detecting highly similar events in a swarm or seismic cluster. In the established template application, a detector functions in a manner analogous to waveform cross-correlation, applying a statistical test to assess the similarity of the incoming data stream to known templates for events of interest. In our approach, we seek not to detect matching signals, but instead, we examine the signal subspace dimensionality in much the same way that the method addresses node traffic anomalies in large computer systems. Signal anomalies recorded on seismic arrays affect the dimensional structure of the array-wide time-series. We have shown previously that this observation is useful in identifying real seismic events, either by looking at the raw signal or derivatives thereof (entropy, kurtosis), but here we explore the effects of malfunctioning channels on the dimension of the data and its derivatives, and how to leverage this effect for
International Nuclear Information System (INIS)
Arvieu, R.
The assumptions and principles of the spectral distribution method are reviewed. The object of the method is to deduce information on the nuclear spectra by constructing a frequency function which has the same first few moments, as the exact frequency function, these moments being then exactly calculated. The method is applied to subspaces containing a large number of quasi particles [fr
Directory of Open Access Journals (Sweden)
Ulf Hensen
Full Text Available We develop a general minimally coupled subspace approach (MCSA to compute absolute entropies of macromolecules, such as proteins, from computer generated canonical ensembles. Our approach overcomes limitations of current estimates such as the quasi-harmonic approximation which neglects non-linear and higher-order correlations as well as multi-minima characteristics of protein energy landscapes. Here, Full Correlation Analysis, adaptive kernel density estimation, and mutual information expansions are combined and high accuracy is demonstrated for a number of test systems ranging from alkanes to a 14 residue peptide. We further computed the configurational entropy for the full 67-residue cofactor of the TATA box binding protein illustrating that MCSA yields improved results also for large macromolecular systems.
Adaptive Detectors for Two Types of Subspace Targets in an Inverse Gamma Textured Background
Directory of Open Access Journals (Sweden)
Ding Hao
2017-06-01
Full Text Available Considering an inverse Gamma prior distribution model for texture, the adaptive detection problems for both first order Gaussian and second order Gaussian subspace targets are researched in a compound Gaussian sea clutter. Test statistics are derived on the basis of the two-step generalized likelihood ratio test. From these tests, new adaptive detectors are proposed by substituting the covariance matrix with estimation results from the Sample Covariance Matrix (SCM, normalized SCM, and fixed point estimator. The proposed detectors consider the prior distribution model for sea clutter during the design stage, and they model parameters that match the working environment during the detection stage. Analysis and validation results indicate that the detection performance of the proposed detectors out performs existing AMF (Adaptive Matched Filter, AMF and ANMF (Adaptive Normalized Matched Filter, ANMF detectors.
Siddiqui, Bilal A.; El-Ferik, Sami; Abdelkader, Mohamed
2016-01-01
In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.
Prewhitening for Rank-Deficient Noise in Subspace Methods for Noise Reduction
DEFF Research Database (Denmark)
Hansen, Per Christian; Jensen, Søren Holdt
2005-01-01
A fundamental issue in connection with subspace methods for noise reduction is that the covariance matrix for the noise is required to have full rank, in order for the prewhitening step to be defined. However, there are important cases where this requirement is not fulfilled, e.g., when the noise...... has narrow-band characteristics, or in the case of tonal noise. We extend the concept of prewhitening to include the case when the noise covariance matrix is rank deficient, using a weighted pseudoinverse and the quotient SVD, and we show how to formulate a general rank-reduction algorithm that works...... also for rank deficient noise. We also demonstrate how to formulate this algorithm by means of a quotient ULV decomposition, which allows for faster computation and updating. Finally we apply our algorithm to a problem involving a speech signal contaminated by narrow-band noise....
Siddiqui, Bilal A.
2016-07-26
In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.
Acoustic Source Localization via Subspace Based Method Using Small Aperture MEMS Arrays
Directory of Open Access Journals (Sweden)
Xin Zhang
2014-01-01
Full Text Available Small aperture microphone arrays provide many advantages for portable devices and hearing aid equipment. In this paper, a subspace based localization method is proposed for acoustic source using small aperture arrays. The effects of array aperture on localization are analyzed by using array response (array manifold. Besides array aperture, the frequency of acoustic source and the variance of signal power are simulated to demonstrate how to optimize localization performance, which is carried out by introducing frequency error with the proposed method. The proposed method for 5 mm array aperture is validated by simulations and experiments with MEMS microphone arrays. Different types of acoustic sources can be localized with the highest precision of 6 degrees even in the presence of wind noise and other noises. Furthermore, the proposed method reduces the computational complexity compared with other methods.
Rank-defective millimeter-wave channel estimation based on subspace-compressive sensing
Directory of Open Access Journals (Sweden)
Majid Shakhsi Dastgahian
2016-11-01
Full Text Available Millimeter-wave communication (mmWC is considered as one of the pioneer candidates for 5G indoor and outdoor systems in E-band. To subdue the channel propagation characteristics in this band, high dimensional antenna arrays need to be deployed at both the base station (BS and mobile sets (MS. Unlike the conventional MIMO systems, Millimeter-wave (mmW systems lay away to employ the power predatory equipment such as ADC or RF chain in each branch of MIMO system because of hardware constraints. Such systems leverage to the hybrid precoding (combining architecture for downlink deployment. Because there is a large array at the transceiver, it is impossible to estimate the channel by conventional methods. This paper develops a new algorithm to estimate the mmW channel by exploiting the sparse nature of the channel. The main contribution is the representation of a sparse channel model and the exploitation of a modified approach based on Multiple Measurement Vector (MMV greedy sparse framework and subspace method of Multiple Signal Classification (MUSIC which work together to recover the indices of non-zero elements of an unknown channel matrix when the rank of the channel matrix is defected. In practical rank-defective channels, MUSIC fails, and we need to propose new extended MUSIC approaches based on subspace enhancement to compensate the limitation of MUSIC. Simulation results indicate that our proposed extended MUSIC algorithms will have proper performances and moderate computational speeds, and that they are even able to work in channels with an unknown sparsity level.
Beneficial Reuse of San Ardo Produced Water
Energy Technology Data Exchange (ETDEWEB)
Robert A. Liske
2006-07-31
This DOE funded study was performed to evaluate the potential for treatment and beneficial reuse of produced water from the San Ardo oilfield in Monterey County, CA. The potential benefits of a successful full-scale implementation of this project include improvements in oil production efficiency and additional recoverable oil reserves as well as the addition of a new reclaimed water resource. The overall project was conducted in two Phases. Phase I identified and evaluated potential end uses for the treated produced water, established treated water quality objectives, reviewed regulations related to treatment, transport, storage and use of the treated produced water, and investigated various water treatment technology options. Phase II involved the construction and operation of a small-scale water treatment pilot facility to evaluate the process's performance on produced water from the San Ardo oilfield. Cost estimates for a potential full-scale facility were also developed. Potential end uses identified for the treated water include (1) agricultural use near the oilfield, (2) use by Monterey County Water Resources Agency (MCWRA) for the Salinas Valley Water Project or Castroville Seawater Intrusion Project, (3) industrial or power plant use in King City, and (4) use for wetlands creation in the Salinas Basin. All of these uses were found to have major obstacles that prevent full-scale implementation. An additional option for potential reuse of the treated produced water was subsequently identified. That option involves using the treated produced water to recharge groundwater in the vicinity of the oil field. The recharge option may avoid the limitations that the other reuse options face. The water treatment pilot process utilized: (1) warm precipitation softening to remove hardness and silica, (2) evaporative cooling to meet downstream temperature limitations and facilitate removal of ammonia, and (3) reverse osmosis (RO) for removal of dissolved salts, boron
20 CFR 616.10 - Reuse of employment and wages.
2010-04-01
... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Reuse of employment and wages. 616.10 Section 616.10 Employees' Benefits EMPLOYMENT AND TRAINING ADMINISTRATION, DEPARTMENT OF LABOR INTERSTATE ARRANGEMENT FOR COMBINING EMPLOYMENT AND WAGES § 616.10 Reuse of employment and wages. Employment and wages...
Methods & tools for publishing & reusing linked open statistical data
Tambouris, Efthimios; Kalampokis, Evangelos; Janssen, M.F.W.H.A.; Krimmer, Robert; Tarabanis, Konstantinos
2017-01-01
The number of open data available for reuse is rapidly increasing. A large number of these data are numerical thus can be easily visualized. Linked open data technology enables easy reuse and linking of data residing in di.erent locations. In this workshop, we will present a number of
Water Reuse in Industrial food Processing. | Pagella | Journal of ...
African Journals Online (AJOL)
While water, as an industrial commodity, is considered increasingly as a valuable material and the subject of responsible care for the environment, water reuse is increasingly regarded as a tool for substantial reduction in water supply needs, and saving in related costs. A strategic approach to water reuse must be based on ...
Use of ozone in a water reuse system for salmonids
Williams, R.C.; Hughes, S.G.; Rumsey, G.L.
1982-01-01
A water reuse system is described in which ozone is used in addition to biological filters to remove toxic metabolic wastes from the water. The system functions at a higher rate of efficiency than has been reported for other reuse systems and supports excellent growth of rainbow trout (Salmo gairdneri).
Recycling and reuse of wastewater from uranium mining and milling
International Nuclear Information System (INIS)
Xu Lechang; Gao Jie; Zhang Xueli; Wei Guangzhi; Zhang Guopu
2010-01-01
Uranium mining/milling process, and the sources, recycling/reuse approach and treatment methods of process wastewater are introduced. The wastewater sources of uranium mining and milling include effluent, raffinate, tailings water, mine discharge, resin form converted solution, and precipitation mother liquor. Wastewater can be recycled/reused for leachant, eluent, stripping solution,washing solution and tailings slurry. (authors)
OAI Object Re-Use and Exchange
CERN. Geneva
2007-01-01
There is a growing interest in appropriating these tools and modalities to support the scholarly communication process. This begins with leveraging the intrinsic value of scholarly digital objects beyond the borders of the hosting repository. There are numerous examples of the need to re-use objects across repositories in scholarly communication. These include citation, preservation, virtual collections of distributed objects, and the progression of units of scholarly communication through the registration-certification-awareness-archiving chain. The last several years have brought about numerous open source repository systems and their associated communities. The Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) has been the initial catalyst for repository interoperability. However, there is now a rising interest in repositories no longer bein...
Water reuse by membrane bioreactors (MBR)
International Nuclear Information System (INIS)
Garcia, G.; Huete, E.; Martinez, L. C.; Torres, A.
2010-01-01
This paper shows an up-to date overview of the use of membrane bioreactor (MBR) to obtain water treated for reusing it. Considering the existing rules. it has been presented a summary of published studies in which the quality of the effluent is analyzed in terms on physico-chemical and biological parameters. Furthermore, MBR results are compared with the conventional treatment ones. Due to the suitability of MBR technology for removing pathogens, particular attention has been paid to disinfection process and the mechanism that govern it. Results from reviewed studies of MBR have showed equal or better quality of water treated than conventional treatments (activated sludge plus disinfection tertiary treatment by the addition of antibacterial agents). (Author) 32 refs.
Technology for reuse of contaminated concrete constituents
International Nuclear Information System (INIS)
Binkhorst, I.P.; Cornelissen, H.A.W.
1998-01-01
During decommissioning activities of nuclear installations, large amounts of contaminated concrete will have to be processed. All this concrete has to be treated and stored as radioactive waste, which implies major economical and environmental consequences. It was shown that the contamination is mainly concentrated in the porous cement stone. By separating this cement stone from the clean dense aggregate particles, a considerable volume reduction can be reached. KEMA has developed, designed and constructed a pilot plant scale test installation for separation of aggregate from contaminated concrete. The separation is based on a thermal treatment followed by milling and sieving. The clean aggregate can be re-used in concrete, whereas the (slightly) contaminated cement stone could be upgraded to a binder for concrete used in the nuclear industry. (author)
OAI Object Re-Use and Exchange
CERN. Geneva; Jacobs, Neil
2007-01-01
YouTube, Flickr, del.icio.us, blogs, message boards and other "Web 2.0" related technologies are indicative of the contemporary web experience. There is a growing interest in appropriating these tools and modalities to support the scholarly communication process. This begins with leveraging the intrinsic value of scholarly digital objects beyond the borders of the hosting repository. There are numerous examples of the need to re-use objects across repositories in scholarly communication. These include citation, preservation, virtual collections of distributed objects, and the progression of units of scholarly communication through the registration-certification-awareness-archiving chain. The last several years have brought about numerous open source repository systems and their associated communities. The Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) has been the initial catalyst for repository interoperability. However, there is now a rising interest in repositories no longer being stat...
International Conference on water reuse and desalination
International Nuclear Information System (INIS)
1984-01-01
The International conference on water reuse and desalination was held on the 13 November 1984 in Johannesburg, South Africa. Papers delivered on this conference covered the following aspects: desalination technology, industrial effluent control, economics of desalination of wastewaters, consumable supplies in desalination, the world market for seawater desalination equipment, reverse osmosis, evaporation and ultrafiltration, treatment of hazardous wastes, role of reverse osmosis in waste water treatment, as well as the desalination, recovery and recycle of water with high efficiency. A paper was also delivered on the mechanical vapour compression process applied to seawater desalination - as an example the paper presents the largest unit so far constructed by SIDEM using this process: a 1,500 mz/day unit installed in the Nuclear power plant of Flamanville in France
Waste water reuse pathways for processing tomato
DEFF Research Database (Denmark)
Battilani, A; Plauborg, Finn; Andersen, Mathias Neumann
Direct or indirect water reuse involves several aspects: contamination by faecal, inorganic and xenobiotic pollutants; high levels of suspended solids and salinity; rational use of the dissolved nutrients (particularly nitrogen). The challenge is apply new strategies and technologies which allows...... to use the lowest irrigation water quality without harming nor food safety neither yield and fruit or derivatives quality. The EU project SAFIR aims help farmers solve problems with low quality water and decreased access to water. New water treatment devices (prototypes) are under development to allow...... a safe use of waste water produced by small communities/industries (≤2000 EI) or of treated water discharged in irrigation channels. Water treatment technologies are coupled with irrigation strategies and technologies to obtain a flexible, easy to use, integrated management....
Water conservation, recycling, and reuse: US northeast
Energy Technology Data Exchange (ETDEWEB)
Kaplan, E.
1984-10-01
This paper focuses upon present and future possibilities for water conservation, recycling, and reuse in New England and Middle Atlantic states. Telephone interviews and questionnaires sent to trade associations, public utility commissions, federal, state and other agencies were used to supplement information gathered in the literature. Water intake and consumptive demands in 1980 were calculated for industrial, electric utility, agricultural, and residential sectors. Corresponding information for the year 2000 were estimated using data from utilities, public utility commissions, and the US Bureau of Economic Affairs. Water supplies were estimated using the concept of safe yield. Assuming reductions in water use by industries, agriculture and by private residences in the year 2000, it was found that many users, particularly the electric utility sector, would still experience serious water supply shortfalls in several industrialized states. 20 references, 14 tables.
Application of solar energy in water reuse
Energy Technology Data Exchange (ETDEWEB)
Prasad, G.
1987-01-01
The application of photocatalysed oxidation in water reuse technology is described. Results with a sequencing batch reactor showed that 4 hours contact of the raw sewage with 0.5 mg dye sorbed g/sup -1/ fly ash in sunlight, under experimental conditions, significantly reduced the organic and bacteriological load and rendered it fit for use in irrigation or for discharge. The effect of variables such as contact time or amount of dye sorbed on COD, MBAS and MPN counts were investigated and the results interpreted in terms of enhanced photoactivity and biodegradation in the sorbed state. The process appears to be well suited to commercial exploitation as it is safe, quick and economical.
Ultrafiltration to reuse laundering wash water
DEFF Research Database (Denmark)
Giagnorio, Mattia; Søtoft, Lene Fjerbæk; Tiraferri, Alberto
2017-01-01
Laundering industry consumes and discharges large amounts of water and surfactants, and the demand of surface active agents used for washing is increasing worldwide. Some of these substances are considered contaminants of emerging concern, as they persist in the environment. This work aimed...... at evaluating the feasibility of ultrafiltration as a method to treat the wash wastewater and possibly reuse the surfactant-rich permeate stream in laundry facilities. In particular, evaluation of surfactant recovery was performed through analysis of the permeate flux and properties obtained through polymeric...... and ceramic membranes. Wash water samples were collected at an industrial laundering facility for hospital linen and filtered through different ultrafiltration membranes with varying molecular weight cut-off. The critical micelle concentration of the detergent was quantified, and capillarity measurements were...
Beneficial Re-use of Decommissioned Former Nuclear Facilities
International Nuclear Information System (INIS)
Boing, L.E.
1997-01-01
With the decision to decommission a nuclear facility, it is necessary to evaluate whether to fully demolish a facility or to re-use the facility in some capacity. This evaluation is often primarily driven by both the past mission of the site and the facility and the site's perceived future mission. In the case where the facility to be decommissioned is located within a large research or industrial complex and represents a significant resource to the site's future mission, it may be a perfect candidate to be re-used in some fashion. However, if the site is a rather remote older facility with little chance of being modified to today's standards for its re-use, the chances for its re-use will be substantially reduced. In this presentation, some specific cases of former nuclear facilities being decommissioned and re-used will be reviewed and some factors required to be considered in making this decision will be reviewed
Directory of Open Access Journals (Sweden)
Hanseok Jeong
2016-04-01
Full Text Available Climate change and the subsequent change in agricultural conditions increase the vulnerability of agricultural water use. Wastewater reuse is a common practice around the globe and is considered as an alternative water resource in a changing agricultural environment. Due to rapid urbanization, indirect wastewater reuse, which is the type of agricultural wastewater reuse that is predominantly practiced, will increase, and this can cause issues of unplanned reuse. Therefore, water quality standards are needed for the safe and sustainable practice of indirect wastewater reuse in agriculture. In this study, irrigation water quality criteria for wastewater reuse were discussed, and the standards and guidelines of various countries and organizations were reviewed to suggest preliminary standards for indirect wastewater reuse in South Korea. The proposed standards adopted a probabilistic consideration of practicality and classified the use of irrigation water into two categories: upland and rice paddy. The standards suggest guidelines for E. coli, electric conductivity (EC, turbidity, suspended solids (SS, biochemical oxygen demand (BOD, pH, odor, and trace elements. Through proposing the standards, this study attempts to combine features of both the conservative and liberal approaches, which in turn could suggest a new and sustainable practice of agricultural wastewater reuse.
Dialyzer Reuse and Outcomes of High Flux Dialysis.
Directory of Open Access Journals (Sweden)
Christos Argyropoulos
Full Text Available The bulk of randomized trial evidence for the expanding use of High Flux (HF hemodialysis worldwide comes from two randomized controlled trials, one of which (HEMODIALYSIS, HEMO allowed, while the other (Membrane Outcomes Permeability, MPO excluded, the reuse of membranes. It is not known whether dialyzer reuse has a differential impact on outcomes with HF vs low flyx (LF dialyzers.Proportional Hazards Models and Joint Models for longitudinal measures and survival outcomes were used in HEMO to analyze the relationship between β2-microglobulin (β2M concentration, flux, and reuse. Meta-analysis and regression techniques were used to synthesize the evidence for HF dialysis from HEMO and MPO.In HEMO, minimally reused (< 6 times HF dialyzers were associated with a hazard ratio (HR of 0.67 (95% confidence interval, 95%CI: 0.48-0.92, p = 0.015, 0.64 (95%CI: 0.44 - 0.95, p = 0.03, 0.61 (95%CI: 0.41 - 0.90, p = 0.012, 0.53 (95%CI: 0.28 - 1.02, p = 0.057 relative to minimally reused LF ones for all cause, cardiovascular, cardiac and infectious mortality respectively. These relationships reversed for extensively reused membranes (p for interaction between reuse and flux < 0.001, p = 0.005 for death from all cause and cardiovascular causes, while similar trends were noted for cardiac and infectious mortality (p of interaction between reuse and flux of 0.10 and 0.08 respectively. Reduction of β2M explained only 1/3 of the effect of minimally reused HF dialyzers on all cause mortality, while non-β2M related factors explained the apparent attenuation of the benefit with more extensively reused dialyzers. Meta-regression of HEMO and MPO estimated an adjusted HR of 0.63 (95% CI: 0.51-0.78 for non-reused HF dialyzers compared with non-reused LF membranes.This secondary analysis and synthesis of two large hemodialysis trials supports the widespread use of HF dialyzers in clinical hemodialysis over the last decade. A mechanistic understanding of the effects of
Dialyzer Reuse with Peracetic Acid Does Not Impact Patient Mortality
Bond, T. Christopher; Krishnan, Mahesh; Wilson, Steven M.; Mayne, Tracy
2011-01-01
Summary Background and objectives Numerous studies have shown the overall benefits of dialysis filter reuse, including superior biocompatibility and decreased nonbiodegradable medical waste generation, without increased risk of mortality. A recent study reported that dialyzer reprocessing was associated with decreased patient survival; however, it did not control for sources of potential confounding. We sought to determine the effect of dialyzer reprocessing with peracetic acid on patient mortality using contemporary outcomes data and rigorous analytical techniques. Design, setting, participants, & measurements We conducted a series of analyses of hemodialysis patients examining the effects of reuse on mortality using three techniques to control for potential confounding: instrumental variables, propensity-score matching, and time-dependent survival analysis. Results In the instrumental variables analysis, patients at high reuse centers had 16.2 versus 15.9 deaths/100 patient-years in nonreuse centers. In the propensity-score matched analysis, patients with reuse had a lower death rate per 100 patient-years than those without reuse (15.2 versus 15.5). The risk ratios for the time-dependent survival analyses were 0.993 (per percent of sessions with reuse) and 0.995 (per unit of last reuse), respectively. Over the study period, 13.8 million dialyzers were saved, representing 10,000 metric tons of medical waste. Conclusions Despite the large sample size, powered to detect miniscule effects, neither the instrumental variables nor propensity-matched analyses were statistically significant. The time-dependent survival analysis showed a protective effect of reuse. These data are consistent with the preponderance of evidence showing reuse limits medical waste generation without negatively affecting clinical outcomes. PMID:21566107
Directory of Open Access Journals (Sweden)
N. I. Didenko
2015-01-01
Full Text Available This paper presents a conceptual idea of the organization of management of development of the Arctic area of the Russian Federation in the form of a set of target subspace. Among the possible types of target subspace comprising the Arctic zone of the Russian Federation, allocated seven subspace: basic city mobile Camps, site production of mineral resources, recreational area, fishing area, the Northern Sea Route, infrastructure protection safe existence in the Arctic. The task of determining the most appropriate theoretical approach for the development of each target subspaces. To this end, the theoretical approaches of economic growth and development of the theory of "economic base» (Economic Base Theory; resource theory (Staple Theory; Theory sectors (Sector Theory; theory of growth poles (Growth Pole Theory; neoclassical theory (Neoclassical Growth Theory; theory of inter-regional trade (Interregional Trade Theory; theory of the commodity cycle; entrepreneurial theory (Entrepreneurship Theories.
Management optimization in Thermal complex through water reuse
International Nuclear Information System (INIS)
De Souza, S.; Manganelli, A.; Bertolotto, J.; Leys, P.; Garcia, B.
2004-01-01
Water reuse involves the concept of the exploitation of a previously used water, for a new, beneficial purpose. Actually, in Uruguay, thermal water is just utilised for balneological purposes, in this paper is proposed the water reuse taking the excess of used swimming pool water, and using it for heating and greenhouse irrigation, and australian lobster breeding. An important aspect of sustainable thermal water management is the protection of the exploted thermal water resources, so water reuse plays an important role in water resource, and ecosystem management, because it reduces the volume discharged and also reduces the risk of thermal pollution [es
Preserving and reusing high-energy-physics data analyses
Simko, Tibor; Dasler, Robin; Fokianos, Pamfilos; Kuncar, Jiri; Lavasa, Artemis; Mattmann, Annemarie; Rodriguez, Diego; Trzcinska, Anna; Tsanaktsidis, Ioannis
2017-01-01
The revalidation, reuse and reinterpretation of data analyses require having access to the original virtual environments, datasets and software that was used to produce the original scientific result. The CERN Analysis Preservation pilot project is developing a set of tools that support particle physics researchers in preserving the knowledge around analyses so that capturing, sharing, reusing and reinterpreting data becomes easier. In this talk, we shall notably focus on the aspects of reusing a preserved analysis. We describe a system that permits to instantiate the preserved analysis workflow on the computing cloud, paving the way to allowing researchers to revalidate and reinterpret research data even many years after the original publication.
DEFF Research Database (Denmark)
Tatu, Aditya Jayant
This thesis deals with two unrelated issues, restricting curve evolution to subspaces and computing image patches in the equivalence class of Histogram of Gradient orientation based features using nonlinear projection methods. Curve evolution is a well known method used in various applications like...... tracking interfaces, active contour based segmentation methods and others. It can also be used to study shape spaces, as deforming a shape can be thought of as evolving its boundary curve. During curve evolution a curve traces out a path in the infinite dimensional space of curves. Due to application...... specific requirements like shape priors or a given data model, and due to limitations of the computer, the computed curve evolution forms a path in some finite dimensional subspace of the space of curves. We give methods to restrict the curve evolution to a finite dimensional linear or implicitly defined...
Ozone treatment of textile wastewaters for reuse.
Ciardelli, G; Capannelli, G; Bottino, A
2001-01-01
Treatment of textile wastewaters by means of an ozonation pilot plant are described. Wastewaters used were produced by a dyeing and finishing factory and were first treated in an active sludge plant and filtrated through sand. In the appropriate conditions very high colour removal (95-99%) was achieved and the effluent could be reused in production processes requiring water of high quality as dyeing yarns or light colorations. Even if the chemical oxygen demand of treated waters was still in a range (75-120 mg/l, a decrease of up to 60%) that was usually considered to be too high for recycling purposes, recycling experiments were successful. The economical viability of the techniques implementation was also demonstrated and the industrial plant is currently under realisation under an EU financed project. The paper considers also the possible improvement of ozone diffusion by means of membrane contactors realised in a second pilot plant, in order to further reduce operating costs of the technique. With respect to traditional systems, the gas/liquid contact surface is much higher being that of the membrane. Ozone at the interface is therefore immediately solubilized and potentially consumed with no additional resistance to the mass transfer.
Recycling, reducing and reusing: A theoretical framework
International Nuclear Information System (INIS)
Kubursi, A.A.; Butterfield, D.W.
1990-01-01
Macroeconomic models are generally based on a particular national income accounting framework. The current approach treats waste and pollution generation in such a way that any increase in these activities increases directly the gross domestic product of the economy. A reformulation is suggested for the accounting framework so as to treat waste management and pollution abatement as services to business whose costs should be charged against business revenue. Even such costs to households may be considered as costs to output. In this way such expenses appear as a cost to society and not as a final output. A new theoretical framework is developed to correspond to the reformulated accounting principle that allows clear identification of recycling activity and waste management. The rectangular input-output framework is particularly suited for this treatment as it allows different industries to produce the same output and identifies different commodities as inputs in the production of the same output. With the new framework, it is possible to examine the socioeconomic consequences of increased use and production of recyclables. Equally important is the ability to assess the relative efficiency of alternative policies to reuse or reduce the use of products and resources through price incentives and full cost charges. 2 tabs
Centralised urban stormwater harvesting for potable reuse.
McArdle, P; Gleeson, J; Hammond, T; Heslop, E; Holden, R; Kuczera, G
2011-01-01
Urban impervious areas provide a guaranteed source of runoff, especially in cities with high rainfall - this represents a source of water with low sensitivity to unfavourable climate change. Whilst the potential to reuse stormwater has long been recognised, its quality has largely limited usage to non-potable applications requiring the use of a third-pipe network, a prohibitively expensive option in established urban areas. Given recent advances in membrane filtration, this study investigates the potential of harvesting and treating stormwater to a potable standard to enable use of the potable distribution network. A case study based on the Throsby Creek catchment in Newcastle explores the issue. The high seasonally uniform rainfall provides insight into the maximum potential of such an option. Multicriterion optimisation was used to identify Pareto optimal solutions for harvesting, storing and treating stormwater. It is shown that harvesting and treating stormwater from a 13 km² catchment can produce yields ranging from 8.5 to 14.2 ML/day at costs ranging from AU$2.60/kL to AU$2.89/kL, which may become viable as the cost of traditional supply continues to grow. However, there are significant social impacts to deal with including alienation of public land for storage and community acceptance of treated stormwater.
Xia, Ya-Rong; Zhang, Shun-Li; Xin, Xiang-Peng
2018-03-01
In this paper, we propose the concept of the perturbed invariant subspaces (PISs), and study the approximate generalized functional variable separation solution for the nonlinear diffusion-convection equation with weak source by the approximate generalized conditional symmetries (AGCSs) related to the PISs. Complete classification of the perturbed equations which admit the approximate generalized functional separable solutions (AGFSSs) is obtained. As a consequence, some AGFSSs to the resulting equations are explicitly constructed by way of examples.
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe
2014-01-01
Roč. 22, č. 4 (2014), s. 289-310 ISSN 1570-2820 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : preconditioning * additive subspace * small eigenvalues Subject RIV: BA - General Mathematics Impact factor: 2.310, year: 2014 http://www.degruyter.com/view/j/jnma.2014.22.issue-4/jnma-2014-0013/jnma-2014-0013. xml
Banerjee, Amartya S; Lin, Lin; Suryanarayana, Phanish; Yang, Chao; Pask, John E
2018-06-12
We describe a novel iterative strategy for Kohn-Sham density functional theory calculations aimed at large systems (>1,000 electrons), applicable to metals and insulators alike. In lieu of explicit diagonalization of the Kohn-Sham Hamiltonian on every self-consistent field (SCF) iteration, we employ a two-level Chebyshev polynomial filter based complementary subspace strategy to (1) compute a set of vectors that span the occupied subspace of the Hamiltonian; (2) reduce subspace diagonalization to just partially occupied states; and (3) obtain those states in an efficient, scalable manner via an inner Chebyshev filter iteration. By reducing the necessary computation to just partially occupied states and obtaining these through an inner Chebyshev iteration, our approach reduces the cost of large metallic calculations significantly, while eliminating subspace diagonalization for insulating systems altogether. We describe the implementation of the method within the framework of the discontinuous Galerkin (DG) electronic structure method and show that this results in a computational scheme that can effectively tackle bulk and nano systems containing tens of thousands of electrons, with chemical accuracy, within a few minutes or less of wall clock time per SCF iteration on large-scale computing platforms. We anticipate that our method will be instrumental in pushing the envelope of large-scale ab initio molecular dynamics. As a demonstration of this, we simulate a bulk silicon system containing 8,000 atoms at finite temperature, and obtain an average SCF step wall time of 51 s on 34,560 processors; thus allowing us to carry out 1.0 ps of ab initio molecular dynamics in approximately 28 h (of wall time).
Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y
2014-05-01
This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Sun, Weiwei; Ma, Jun; Yang, Gang; Du, Bo; Zhang, Liangpei
2017-06-01
A new Bayesian method named Poisson Nonnegative Matrix Factorization with Parameter Subspace Clustering Constraint (PNMF-PSCC) has been presented to extract endmembers from Hyperspectral Imagery (HSI). First, the method integrates the liner spectral mixture model with the Bayesian framework and it formulates endmember extraction into a Bayesian inference problem. Second, the Parameter Subspace Clustering Constraint (PSCC) is incorporated into the statistical program to consider the clustering of all pixels in the parameter subspace. The PSCC could enlarge differences among ground objects and helps finding endmembers with smaller spectrum divergences. Meanwhile, the PNMF-PSCC method utilizes the Poisson distribution as the prior knowledge of spectral signals to better explain the quantum nature of light in imaging spectrometer. Third, the optimization problem of PNMF-PSCC is formulated into maximizing the joint density via the Maximum A Posterior (MAP) estimator. The program is finally solved by iteratively optimizing two sub-problems via the Alternating Direction Method of Multipliers (ADMM) framework and the FURTHESTSUM initialization scheme. Five state-of-the art methods are implemented to make comparisons with the performance of PNMF-PSCC on both the synthetic and real HSI datasets. Experimental results show that the PNMF-PSCC outperforms all the five methods in Spectral Angle Distance (SAD) and Root-Mean-Square-Error (RMSE), and especially it could identify good endmembers for ground objects with smaller spectrum divergences.
Directory of Open Access Journals (Sweden)
Kohei Fujita
2017-08-01
Full Text Available A system identification (SI problem of high-rise buildings is investigated under restricted data environments. The shear and bending stiffnesses of a shear-bending model (SB model representing the high-rise buildings are identified via the smart combination of the subspace and inverse-mode methods. Since the shear and bending stiffnesses of the SB model can be identified in the inverse-mode method by using the lowest mode of horizontal displacements and floor rotation angles, the lowest mode of the objective building is identified first by using the subspace method. Identification of the lowest mode is performed by using the amplitude of transfer functions derived in the subspace method. Considering the resolution in measuring the floor rotation angles in lower stories, floor rotation angles in most stories are predicted from the floor rotation angle at the top floor. An empirical equation of floor rotation angles is proposed by investigating those for various building models. From the viewpoint of application of the present SI method to practical situations, a non-simultaneous measurement system is also proposed. In order to investigate the reliability and accuracy of the proposed SI method, a 10-story building frame subjected to micro-tremor is examined.
Xu, Y; Li, N
2014-09-01
Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator-prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework.
International Nuclear Information System (INIS)
Xu, Y; Li, N
2014-01-01
Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator–prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework. (paper)
Weinberg, Seth H.; Smith, Gregory D.
2012-01-01
Cardiac myocyte calcium signaling is often modeled using deterministic ordinary differential equations (ODEs) and mass-action kinetics. However, spatially restricted “domains” associated with calcium influx are small enough (e.g., 10−17 liters) that local signaling may involve 1–100 calcium ions. Is it appropriate to model the dynamics of subspace calcium using deterministic ODEs or, alternatively, do we require stochastic descriptions that account for the fundamentally discrete nature of these local calcium signals? To address this question, we constructed a minimal Markov model of a calcium-regulated calcium channel and associated subspace. We compared the expected value of fluctuating subspace calcium concentration (a result that accounts for the small subspace volume) with the corresponding deterministic model (an approximation that assumes large system size). When subspace calcium did not regulate calcium influx, the deterministic and stochastic descriptions agreed. However, when calcium binding altered channel activity in the model, the continuous deterministic description often deviated significantly from the discrete stochastic model, unless the subspace volume is unrealistically large and/or the kinetics of the calcium binding are sufficiently fast. This principle was also demonstrated using a physiologically realistic model of calmodulin regulation of L-type calcium channels introduced by Yue and coworkers. PMID:23509597
Predictor-Year Subspace Clustering Based Ensemble Prediction of Indian Summer Monsoon
Directory of Open Access Journals (Sweden)
Moumita Saha
2016-01-01
Full Text Available Forecasting the Indian summer monsoon is a challenging task due to its complex and nonlinear behavior. A large number of global climatic variables with varying interaction patterns over years influence monsoon. Various statistical and neural prediction models have been proposed for forecasting monsoon, but many of them fail to capture variability over years. The skill of predictor variables of monsoon also evolves over time. In this article, we propose a joint-clustering of monsoon years and predictors for understanding and predicting the monsoon. This is achieved by subspace clustering algorithm. It groups the years based on prevailing global climatic condition using statistical clustering technique and subsequently for each such group it identifies significant climatic predictor variables which assist in better prediction. Prediction model is designed to frame individual cluster using random forest of regression tree. Prediction of aggregate and regional monsoon is attempted. Mean absolute error of 5.2% is obtained for forecasting aggregate Indian summer monsoon. Errors in predicting the regional monsoons are also comparable in comparison to the high variation of regional precipitation. Proposed joint-clustering based ensemble model is observed to be superior to existing monsoon prediction models and it also surpasses general nonclustering based prediction models.
Improved neutron-gamma discrimination for a 3He neutron detector using subspace learning methods
Wang, C. L.; Funk, L. L.; Riedel, R. A.; Berry, K. D.
2017-05-01
3He gas based neutron Linear-Position-Sensitive Detectors (LPSDs) have been used for many neutron scattering instruments. Traditional Pulse-height Analysis (PHA) for Neutron-Gamma Discrimination (NGD) resulted in the neutron-gamma efficiency ratio (NGD ratio) on the order of 105-106. The NGD ratios of 3He detectors need to be improved for even better scientific results from neutron scattering. Digital Signal Processing (DSP) analyses of waveforms were proposed for obtaining better NGD ratios, based on features extracted from rise-time, pulse amplitude, charge integration, a simplified Wiener filter, and the cross-correlation between individual and template waveforms of neutron and gamma events. Fisher Linear Discriminant Analysis (FLDA) and three Multivariate Analyses (MVAs) of the features were performed. The NGD ratios are improved by about 102-103 times compared with the traditional PHA method. Our results indicate the NGD capabilities of 3He tube detectors can be significantly improved with subspace-learning based methods, which may result in a reduced data-collection time and better data quality for further data reduction.
Directory of Open Access Journals (Sweden)
Wilfried B. Krätzig
2014-01-01
Full Text Available This paper applies recent research on structural damage description to earthquake-resistant design concepts. Based on the primary design aim of life safety, this work adopts the necessity of additional protection aims for property, installation, and equipment. This requires the definition of damage indicators, which are able to quantify the arising structural damage. As in present design, it applies nonlinear quasistatic (pushover concepts due to code provisions as simplified dynamic design tools. Substituting so nonlinear time-history analyses, seismic low-cycle fatigue of RC structures is approximated in similar manner. The treatment will be embedded into a finite element environment, and the tangential stiffness matrix KT in tangential subspaces then is identified as the most general entry for structural damage information. Its spectra of eigenvalues λi or natural frequencies ωi of the structure serve to derive damage indicators Di, applicable to quasistatic evaluation of seismic damage. Because det KT=0 denotes structural failure, such damage indicators range from virgin situation Di=0 to failure Di=1 and thus correspond with Fema proposals on performance-based seismic design. Finally, the developed concept is checked by reanalyses of two experimentally investigated RC frames.
International Nuclear Information System (INIS)
Marumori, Toshio; Hayashi, Akihisa; Tomoda, Toshiaki; Kuriyama, Atsushi; Maskawa, Toshihide
1980-01-01
The aim of this series of papers is to propose a microscopic theory to go beyond the situations where collective motions are described by the random phase approximation, i.e., by small amplitude harmonic oscillations about equilibrium. The theory is thus appropriate for the microscopic description of the large amplitude collective motion of soft nuclei. The essential idea is to develop a method to determine the collective subspace (or submanifold) in the many-particle Hilbert space in an optimal way, on the basis of a fundamental principle called the invariance principle of the Schroedinger equation. By using the principle within the framework of the Hartree-Fock theory, it is shown that the theory can clarify the structure of the so-called ''phonon-bands'' by self-consistently deriving the collective Hamiltonian where the number of the ''physical phonon'' is conserved. The purpose of this paper is not to go into detailed quantitative discussion, but rather to develop the basic idea. (author)
International Nuclear Information System (INIS)
Platoni, K.; Lefkopoulos, D.; Grandjean, P.; Schlienger, M.
1999-01-01
A Linac sterotactic irradiation space is characterized by different angular separations of beams because of the geometry of the stereotactic irradiation. The regions of the stereotactic space characterized by low angular separations are one of the causes of ill-conditioning of the stereotactic irradiation inverse problem. The singular value decomposition (SVD) is a powerful mathematical analysis that permits the measurement of the ill-conditioning of the stereotactic irradiation problem. This study examines the ill-conditioning of the stereotactic irradiation space, provoked by the different angular separations of beams, using the SVD analysis. We subdivided the maximum irradiation space (MIS: (AA) AP x (AA) RL =180 x 180 ) into irradiation subspaces (ISSs), each characterized by its own angular separation. We studied the influence of ISSs on the SVD analysis and the evolution of the reconstruction quality of well defined three-dimensional dose matrices in each configuration. The more the ISS is characterized by low angular separation the more the condition number and the reconstruction inaccuracy are increased. Based on the above results we created two reduced irradiation spaces (RIS: (AA) AP x (AA) RL =180 x 140 and (AA) AP x (AA) RL =180 x 120 ) and compared the reconstruction quality of the RISs with respect to the MIS. The more an irradiation space is free of low angular separations the more the irradiation space contains useful singular components. (orig.)
Loizou, Nicolas
2017-12-27
In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.
Ren, W. X.; Lin, Y. Q.; Fang, S. E.
2011-11-01
One of the key issues in vibration-based structural health monitoring is to extract the damage-sensitive but environment-insensitive features from sampled dynamic response measurements and to carry out the statistical analysis of these features for structural damage detection. A new damage feature is proposed in this paper by using the system matrices of the forward innovation model based on the covariance-driven stochastic subspace identification of a vibrating system. To overcome the variations of the system matrices, a non-singularity transposition matrix is introduced so that the system matrices are normalized to their standard forms. For reducing the effects of modeling errors, noise and environmental variations on measured structural responses, a statistical pattern recognition paradigm is incorporated into the proposed method. The Mahalanobis and Euclidean distance decision functions of the damage feature vector are adopted by defining a statistics-based damage index. The proposed structural damage detection method is verified against one numerical signal and two numerical beams. It is demonstrated that the proposed statistics-based damage index is sensitive to damage and shows some robustness to the noise and false estimation of the system ranks. The method is capable of locating damage of the beam structures under different types of excitations. The robustness of the proposed damage detection method to the variations in environmental temperature is further validated in a companion paper by a reinforced concrete beam tested in the laboratory and a full-scale arch bridge tested in the field.
Georgievskii, D. V.
2017-07-01
The mechanical meaning and the relationships among material constants in an n-dimensional isotropic elastic medium are discussed. The restrictions of the constitutive relations (Hooke's law) to subspaces of lower dimension caused by the conditions that an m-dimensional strain state or an m-dimensional stress state (1 ≤ m < n) is realized in the medium. Both the terminology and the general idea of the mathematical construction are chosen by analogy with the case n = 3 and m = 2, which is well known in the classical plane problem of elasticity theory. The quintuples of elastic constants of the same medium that enter both the n-dimensional relations and the relations written out for any m-dimensional restriction are expressed in terms of one another. These expressions in terms of the known constants, for example, of a three-dimensional medium, i.e., the classical elastic constants, enable us to judge the material properties of this medium immersed in a space of larger dimension.
Loizou, Nicolas; Richtarik, Peter
2017-01-01
In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.
Energy Technology Data Exchange (ETDEWEB)
Vrugt, Jasper A [Los Alamos National Laboratory; Hyman, James M [Los Alamos National Laboratory; Robinson, Bruce A [Los Alamos National Laboratory; Higdon, Dave [Los Alamos National Laboratory; Ter Braak, Cajo J F [NETHERLANDS; Diks, Cees G H [UNIV OF AMSTERDAM
2008-01-01
Markov chain Monte Carlo (MCMC) methods have found widespread use in many fields of study to estimate the average properties of complex systems, and for posterior inference in a Bayesian framework. Existing theory and experiments prove convergence of well constructed MCMC schemes to the appropriate limiting distribution under a variety of different conditions. In practice, however this convergence is often observed to be disturbingly slow. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves in the Markov Chain. Here we show that significant improvements to the efficiency of MCMC simulation can be made by using a self-adaptive Differential Evolution learning strategy within a population-based evolutionary framework. This scheme, entitled DiffeRential Evolution Adaptive Metropolis or DREAM, runs multiple different chains simultaneously for global exploration, and automatically tunes the scale and orientation of the proposal distribution in randomized subspaces during the search. Ergodicity of the algorithm is proved, and various examples involving nonlinearity, high-dimensionality, and multimodality show that DREAM is generally superior to other adaptive MCMC sampling approaches. The DREAM scheme significantly enhances the applicability of MCMC simulation to complex, multi-modal search problems.
Energy Landscape of Pentapeptides in a Higher-Order (ϕ,ψ Conformational Subspace
Directory of Open Access Journals (Sweden)
Karim M. ElSawy
2016-01-01
Full Text Available The potential energy landscape of pentapeptides was mapped in a collective coordinate principal conformational subspace derived from principal component analysis of a nonredundant representative set of protein structures from the PDB. Three pentapeptide sequences that are known to be distinct in terms of their secondary structure characteristics, (Ala5, (Gly5, and Val.Asn.Thr.Phe.Val, were considered. Partitioning the landscapes into different energy valleys allowed for calculation of the relative propensities of the peptide secondary structures in a statistical mechanical framework. The distribution of the observed conformations of pentapeptide data showed good correspondence to the topology of the energy landscape of the (Ala5 sequence where, in accord with reported trends, the α-helix showed a predominant propensity at 298 K. The topography of the landscapes indicates that the stabilization of the α-helix in the (Ala5 sequence is enthalpic in nature while entropic factors are important for stabilization of the β-sheet in the Val.Asn.Thr.Phe.Val sequence. The results indicate that local interactions within small pentapeptide segments can lead to conformational preference of one secondary structure over the other where account of conformational entropy is important in order to reveal such preference. The method, therefore, can provide critical structural information for ab initio protein folding methods.
De Filippis, G.; Noël, J. P.; Kerschen, G.; Soria, L.; Stephan, C.
2017-09-01
The introduction of the frequency-domain nonlinear subspace identification (FNSI) method in 2013 constitutes one in a series of recent attempts toward developing a realistic, first-generation framework applicable to complex structures. If this method showed promising capabilities when applied to academic structures, it is still confronted with a number of limitations which needs to be addressed. In particular, the removal of nonphysical poles in the identified nonlinear models is a distinct challenge. In the present paper, it is proposed as a first contribution to operate directly on the identified state-space matrices to carry out spurious pole removal. A modal-space decomposition of the state and output matrices is examined to discriminate genuine from numerical poles, prior to estimating the extended input and feedthrough matrices. The final state-space model thus contains physical information only and naturally leads to nonlinear coefficients free of spurious variations. Besides spurious variations due to nonphysical poles, vibration modes lying outside the frequency band of interest may also produce drifts of the nonlinear coefficients. The second contribution of the paper is to include residual terms, accounting for the existence of these modes. The proposed improved FNSI methodology is validated numerically and experimentally using a full-scale structure, the Morane-Saulnier Paris aircraft.
Similarity measurement method of high-dimensional data based on normalized net lattice subspace
Institute of Scientific and Technical Information of China (English)
Li Wenfa; Wang Gongming; Li Ke; Huang Su
2017-01-01
The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity, leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals, and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this meth-od, three data types are used, and seven common similarity measurement methods are compared. The experimental result indicates that the relative difference of the method is increasing with the di-mensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition, the similarity range of this method in different dimensions is [0, 1], which is fit for similarity analysis after dimensionality reduction.
Cancelli, Alessandro; Micheli, Laura; Laflamme, Simon; Alipour, Alice; Sritharan, Sri; Ubertini, Filippo
2017-04-01
Stochastic subspace identification (SSID) is a first-order linear system identification technique enabling modal analysis through the time domain. Research in the field of structural health monitoring has demonstrated that SSID can be used to successfully retrieve modal properties, including modal damping ratios, using output-only measurements. In this paper, the utilization of SSID for indirectly retrieving structures' stiffness matrix was investigated, through the study of a simply supported reinforced concrete beam subjected to dynamic loads. Hence, by introducing a physical model of the structure, a second-order identification method is achieved. The reconstruction is based on system condensation methods, which enables calculation of reduced order stiffness, damping, and mass matrices for the structural system. The methods compute the reduced order matrices directly from the modal properties, obtained through the use of SSID. Lastly, the reduced properties of the system are used to reconstruct the stiffness matrix of the beam. The proposed approach is first verified through numerical simulations and then validated using experimental data obtained from a full-scale reinforced concrete beam that experienced progressive damage. Results show that the SSID technique can be used to diagnose, locate, and quantify damage through the reconstruction of the stiffness matrix.
A unified classifier for robust face recognition based on combining multiple subspace algorithms
Ijaz Bajwa, Usama; Ahmad Taj, Imtiaz; Waqas Anwar, Muhammad
2012-10-01
Face recognition being the fastest growing biometric technology has expanded manifold in the last few years. Various new algorithms and commercial systems have been proposed and developed. However, none of the proposed or developed algorithm is a complete solution because it may work very well on one set of images with say illumination changes but may not work properly on another set of image variations like expression variations. This study is motivated by the fact that any single classifier cannot claim to show generally better performance against all facial image variations. To overcome this shortcoming and achieve generality, combining several classifiers using various strategies has been studied extensively also incorporating the question of suitability of any classifier for this task. The study is based on the outcome of a comprehensive comparative analysis conducted on a combination of six subspace extraction algorithms and four distance metrics on three facial databases. The analysis leads to the selection of the most suitable classifiers which performs better on one task or the other. These classifiers are then combined together onto an ensemble classifier by two different strategies of weighted sum and re-ranking. The results of the ensemble classifier show that these strategies can be effectively used to construct a single classifier that can successfully handle varying facial image conditions of illumination, aging and facial expressions.
Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF
Directory of Open Access Journals (Sweden)
Yu Ding
2018-01-01
Full Text Available Playing an important role in electromechanical systems, hydraulic servo system is crucial to mechanical systems like engineering machinery, metallurgical machinery, ships, and other equipment. Fault diagnosis based on monitoring and sensory signals plays an important role in avoiding catastrophic accidents and enormous economic losses. This study presents a fault diagnosis scheme for hydraulic servo system using compressed random subspace based ReliefF (CRSR method. From the point of view of feature selection, the scheme utilizes CRSR method to determine the most stable feature combination that contains the most adequate information simultaneously. Based on the feature selection structure of ReliefF, CRSR employs feature integration rules in the compressed domain. Meanwhile, CRSR substitutes information entropy and fuzzy membership for traditional distance measurement index. The proposed CRSR method is able to enhance the robustness of the feature information against interference while selecting the feature combination with balanced information expressing ability. To demonstrate the effectiveness of the proposed CRSR method, a hydraulic servo system joint simulation model is constructed by HyPneu and Simulink, and three fault modes are injected to generate the validation data.
Waste Not Want Not: Water Reuse and Recycling in Texas
The Texas Water Development Board has provided more than $300 million to over 28 projects using its CWSRF to fund a diversification of water reclamation, reuse and supply development solutions to augment community resiliency in the face of drought events.
A Community-Driven Workflow Recommendation and Reuse Infrastructure
National Aeronautics and Space Administration — Promote and encourage process and workflow reuse within NASA Earth eXchange (NEX) by developing a proactive recommendation technology based on collective NEX user...
Reuse of wastewater in urban farming and urban planning ...
African Journals Online (AJOL)
ISHIOMA
status of wastewater reuse in urban farming in Katsina, an important urban area in the semi arid ... officially registered with the Katsina Urban Planning Authority. ..... crop production in the water-short Guanajuato river basin. Mexico. Res. Rep.
Relevance and Benefits of Urban Water Reuse in Tourist Areas
Directory of Open Access Journals (Sweden)
Gaston Tong Sang
2012-01-01
Full Text Available Urban water reuse is one of the most rapidly growing water reuse applications worldwide and one of the major elements of the sustainable management of urban water cycle. Because of the high probability of direct contact between consumers and recycled water, many technical and regulatory challenges have to be overcome in order to minimize health risks at affordable cost. This paper illustrates the keys to success of one of the first urban water reuse projects in the island Bora Bora, French Polynesia. Special emphasis is given on the reliability of operation of the membrane tertiary treatment, economic viability in terms of pricing of recycled water and operating costs, as well as on the benefits of water reuse for the sustainable development of tourist areas.
Water reuse systems: A review of the principal components
Lucchetti, G.; Gray, G.A.
1988-01-01
Principal components of water reuse systems include ammonia removal, disease control, temperature control, aeration, and particulate filtration. Effective ammonia removal techniques include air stripping, ion exchange, and biofiltration. Selection of a particular technique largely depends on site-specific requirements (e.g., space, existing water quality, and fish densities). Disease control, although often overlooked, is a major problem in reuse systems. Pathogens can be controlled most effectively with ultraviolet radiation, ozone, or chlorine. Simple and inexpensive methods are available to increase oxygen concentration and eliminate gas supersaturation, these include commercial aerators, air injectors, and packed columns. Temperature control is a major advantage of reuse systems, but the equipment required can be expensive, particularly if water temperature must be rigidly controlled and ambient air temperature fluctuates. Filtration can be readily accomplished with a hydrocyclone or sand filter that increases overall system efficiency. Based on criteria of adaptability, efficiency, and reasonable cost, we recommend components for a small water reuse system.
Assessment of Cryptosporidium in wastewater reuse for drinking ...
African Journals Online (AJOL)
Assessment of Cryptosporidium in wastewater reuse for drinking water ... water supply needs and/or to reduce costs in many communities around the world. ... in a treatment plant geared for the production of drinking water from wastewater ...
Re-use of seedling containers and Fusarium circinatum association ...
African Journals Online (AJOL)
Re-use of seedling containers and Fusarium circinatum association with asymptomatic Pinus patula planting stock. Andrew R Morris, Gerda Fourie, Izette Greyling, Emma T Steenkamp, Nicoletta B Jones ...
Energy Technology Data Exchange (ETDEWEB)
Zou, Ling; Zhao, Haihua; Zhang, Hongbin
2016-04-01
The phase appearance/disappearance issue presents serious numerical challenges in two-phase flow simulations. Many existing reactor safety analysis codes use different kinds of treatments for the phase appearance/disappearance problem. However, to our best knowledge, there are no fully satisfactory solutions. Additionally, the majority of the existing reactor system analysis codes were developed using low-order numerical schemes in both space and time. In many situations, it is desirable to use high-resolution spatial discretization and fully implicit time integration schemes to reduce numerical errors. In this work, we adapted a high-resolution spatial discretization scheme on staggered grid mesh and fully implicit time integration methods (such as BDF1 and BDF2) to solve the two-phase flow problems. The discretized nonlinear system was solved by the Jacobian-free Newton Krylov (JFNK) method, which does not require the derivation and implementation of analytical Jacobian matrix. These methods were tested with a few two-phase flow problems with phase appearance/disappearance phenomena considered, such as a linear advection problem, an oscillating manometer problem, and a sedimentation problem. The JFNK method demonstrated extremely robust and stable behaviors in solving the two-phase flow problems with phase appearance/disappearance. No special treatments such as water level tracking or void fraction limiting were used. High-resolution spatial discretization and second- order fully implicit method also demonstrated their capabilities in significantly reducing numerical errors.
Development of Policies, Institutions and Procedures for Water Reuse
Demouche, L.; Pfiefer, J.; Hanson, A.; Skaggs, R.
2009-12-01
In the arid, water scarce region of New Mexico and West Texas there is growing interest in the potential for water reuse to extend existing supplies and mitigate drought shortage impacts. There are no new sources of water in New Mexico, except reclaimed water. Communities and individuals are uncertain about and have many unanswered questions about polices, institutions involved (agencies), legal and regulatory requirements, and procedures governing water reuse. Issues to be addressed by this project include: the legal ability to reuse water, ownership of water rights, downstream or third party impacts, regulatory and procedural requirements, water quality concerns, state and local agency involvement, and cost effectiveness of water reuse compared to alternative sources. Presently, there is very little implementation or directives in New Mexico policy that addresses reuse, reclamation, or recycled water. The only regulations pertaining to reuse is New Mexico Environmental Department currently allows the use of reclaimed domestic wastewater for irrigation of golf courses and green spaces, which is listed in the Policy for the Above Ground Use of Reclaimed Domestic Wastewater (NMED, 2003). This document identifies the various reclaimed quality classifications that are required for specific applications and the permits required for application. This document does not identify or address policy applications on the distribution, ownership, or trading of reclaimed water. Even though reclaimed water reuse projects are currently being implemented in many cities in the U.S., mainly for commercial and municipal irrigation (golf courses and green space), its potential has not yet been exploited. A policy analysis matrix (PAM) is being designed to identify and examine the policy framework and consequences of non-policy implementation for decision makers and interest groups and assist them in understanding the consequences of policy actions and project outcomes if no laws or
Trombay symposium on desalination and water reuse: proceedings
International Nuclear Information System (INIS)
2007-02-01
Trombay Symposium on Desalination and Water Reuse (TSDWR-07) addresses the issues related to desalination and water reuse including integrated water resource management. It aims to bring together the desalination and water purification technologists from government R and D, academia, industry and representatives from NGOs and user groups including policy makers. The papers received cover a wide range of topics from water resource management to different aspects of desalination and water purification. Papers relevant to INIS are indexed separately
Structuring Formal Requirements Specifications for Reuse and Product Families
Heimdahl, Mats P. E.
2001-01-01
In this project we have investigated how formal specifications should be structured to allow for requirements reuse, product family engineering, and ease of requirements change, The contributions of this work include (1) a requirements specification methodology specifically targeted for critical avionics applications, (2) guidelines for how to structure state-based specifications to facilitate ease of change and reuse, and (3) examples from the avionics domain demonstrating the proposed approach.
Integrated urban water management for residential areas: a reuse model.
Barton, A B; Argue, J R
2009-01-01
Global concern over growing urban water demand in the face of limited water resources has focussed attention on the need for better management of available water resources. This paper takes the "fit for purpose" concept and applies it in the development of a model aimed at changing current practices with respect to residential planning by integrating reuse systems into the design layout. This residential reuse model provides an approach to the design of residential developments seeking to maximise water reuse. Water balance modelling is used to assess the extent to which local water resources can satisfy residential demands with conditions based on the city of Adelaide, Australia. Physical conditions include a relatively flat topography and a temperate climate, with annual rainfall being around 500 mm. The level of water-self-sufficiency that may be achieved within a reuse development in this environment is estimated at around 60%. A case study is also presented in which a conventional development is re-designed on the basis of the reuse model. Costing of the two developments indicates the reuse scenario is only marginally more expensive. Such costings however do not include the benefit to upstream and downstream environments resulting from reduced demand and discharges. As governments look to developers to recover system augmentation and environmental costs the economics of such approaches will increase.
Scenario of solid waste reuse in Khulna city of Bangladesh
Energy Technology Data Exchange (ETDEWEB)
Bari, Quazi H., E-mail: qhbari@yahoo.com [Department of Civil Engineering, Khulna University of Engineering and Technology, Khulna 9203 (Bangladesh); Mahbub Hassan, K. [Department of Civil Engineering, Khulna University of Engineering and Technology, Khulna 9203 (Bangladesh); Haque, R. [Project Builders Ltd., Dhaka 1000 (Bangladesh)
2012-12-15
The reuse and recycling of waste materials are now sincerely considered to be an integral part of solid waste management in many parts of the world. In this context, a vast number of options ranging from small scale decentralized to larger scale centralized plants have been adopted. This study aimed at investigating the waste reuse schemes in Khulna city located in the southern part of Bangladesh and ranked third largest city in the country. The shops for reusable material (SRM) were mostly situated around railway, waterway, and truck station markets which provided easy transportation to further locations. For the reuses of waste materials and products, a chain system was found to collect reusable wastes under a total number of 310 identified SRM with 859 persons directly or indirectly involved in the scheme. This was a decentralized waste management system with self sufficient (autonomous) management. According to mass balance, about 38.52 tons d{sup -1} solid wastes were reused in Khulna city area, accounting for 7.65% of the total generated wastes. This study revealed that apparently a silent, systematic, smooth, and clean reuse chain has been established in Khulna city area under private initiatives, whose sustainability was confirmed over the years in the country without any official or formal funds. However, proper adjustment between the higher and lower chain in the materials flow path, as well as personal hygiene training for the workers, would further improve the achievements of the established reuse scheme.
Optimal waste heat recovery and reuse in industrial zones
International Nuclear Information System (INIS)
Stijepovic, Mirko Z.; Linke, Patrick
2011-01-01
Significant energy efficiency gains in zones with concentrated activity from energy intensive industries can often be achieved by recovering and reusing waste heat between processing plants. We present a systematic approach to target waste heat recovery potentials and design optimal reuse options across plants in industrial zones. The approach first establishes available waste heat qualities and reuse feasibilities considering distances between individual plants. A targeting optimization problem is solved to establish the maximum possible waste heat recovery for the industrial zone. Then, a design optimization problem is solved to identify concrete waste heat recovery options considering economic objectives. The paper describes the approach and illustrates its application with a case study. -- Highlights: → Developed a systematic approach to target waste heat recovery potentials and to design optimal recovery and reuse options across plants in industrial zones. → Five stage approach involving data acquisition, analysis, assessment, targeting and design. → Targeting optimization problem establishes the maximum possible waste heat recovery and reuse limit for the industrial zone. → Design optimization problem provides concrete waste heat recovery and reuse network design options considering economic objectives.
Public responses to water reuse - Understanding the evidence.
Smith, H M; Brouwer, S; Jeffrey, P; Frijns, J
2018-02-01
Over the years, much research has attempted to unpack what drives public responses to water reuse, using a variety of approaches. A large amount of this work was captured by an initial review that covered research undertaken up to the early 2000s (Hartley, 2006). This paper showcases post-millennium evidence and thinking around public responses to water reuse, and highlights the novel insights and shifts in emphasis that have occurred in the field. Our analysis is structured around four broad, and highly interrelated, strands of thinking: 1) work focused on identifying the range of factors that influence public reactions to the concept of water reuse, and broadly looking for associations between different factors; 2) more specific approaches rooted in the socio-psychological modelling techniques; 3) work with a particular focus on understanding the influences of trust, risk perceptions and affective (emotional) reactions; and 4) work utilising social constructivist perspectives and socio-technical systems theory to frame responses to water reuse. Some of the most significant advancements in thinking in this field stem from the increasingly sophisticated understanding of the 'yuck factor' and the role of such pre-cognitive affective reactions. These are deeply entrenched within individuals, but are also linked with wider societal processes and social representations. Work in this area suggests that responses to reuse are situated within an overall process of technological 'legitimation'. These emerging insights should help stimulate some novel thinking around approaches to public engagement for water reuse. Copyright © 2017 Elsevier Ltd. All rights reserved.
Scenario of solid waste reuse in Khulna city of Bangladesh
International Nuclear Information System (INIS)
Bari, Quazi H.; Mahbub Hassan, K.; Haque, R.
2012-01-01
The reuse and recycling of waste materials are now sincerely considered to be an integral part of solid waste management in many parts of the world. In this context, a vast number of options ranging from small scale decentralized to larger scale centralized plants have been adopted. This study aimed at investigating the waste reuse schemes in Khulna city located in the southern part of Bangladesh and ranked third largest city in the country. The shops for reusable material (SRM) were mostly situated around railway, waterway, and truck station markets which provided easy transportation to further locations. For the reuses of waste materials and products, a chain system was found to collect reusable wastes under a total number of 310 identified SRM with 859 persons directly or indirectly involved in the scheme. This was a decentralized waste management system with self sufficient (autonomous) management. According to mass balance, about 38.52 tons d −1 solid wastes were reused in Khulna city area, accounting for 7.65% of the total generated wastes. This study revealed that apparently a silent, systematic, smooth, and clean reuse chain has been established in Khulna city area under private initiatives, whose sustainability was confirmed over the years in the country without any official or formal funds. However, proper adjustment between the higher and lower chain in the materials flow path, as well as personal hygiene training for the workers, would further improve the achievements of the established reuse scheme.
Performance Analysis of Reuse Distance in Cooperative Broadcasting
Directory of Open Access Journals (Sweden)
Jimmi Grönkvist
2016-01-01
Full Text Available Cooperative broadcasting is a promising technique for robust broadcast with low overhead and delay in mobile ad hoc networks. The technique is attractive for mission-oriented mobile communication, where a majority of the traffic is of broadcast nature. In cooperative broadcasting, all nodes simultaneously retransmit packets. The receiver utilizes cooperative diversity in the simultaneously received signals. The retransmissions continue until all nodes are reached. After the packet has traveled a specific number of hops out from the source, denoted as reuse distance, the source node transmits a new broadcast packet in the time slot used for the previous broadcast packet. If the reuse distance is too small, interference causes packet loss in intermediate nodes. In the literature, a reuse distance of three is common. With an analysis based on a realistic interference model and real terrain data, we show that a reuse distance of at least four is necessary to avoid packet loss in sparsely connected networks, especially for high spectral efficiencies. For frequency hopping, widely used in military systems, we propose a novel method. This method almost eliminates interference for a reuse distance of three, increasing the throughput by 33% compared to systems with a reuse distance of four.
Decontamination and reuse of ORGDP aluminum scrap
International Nuclear Information System (INIS)
Compere, A.L.; Griffith, W.L.; Hayden, H.W.; Wilson, D.F.
1996-12-01
The Gaseous Diffusion Plants, or GDPs, have significant amounts of a number of metals, including nickel, aluminum, copper, and steel. Aluminum was used extensively throughout the GDPs because of its excellent strength to weight ratios and good resistance to corrosion by UF 6 . This report is concerned with the recycle of aluminum stator and rotor blades from axial compressors. Most of the stator and rotor blades were made from 214-X aluminum casting alloy. Used compressor blades were contaminated with uranium both as a result of surface contamination and as an accumulation held in surface-connected voids inside of the blades. A variety of GDP studies were performed to evaluate the amounts of uranium retained in the blades; the volume, area, and location of voids in the blades; and connections between surface defects and voids. Based on experimental data on deposition, uranium content of the blades is 0.3%, or roughly 200 times the value expected from blade surface area. However, this value does correlate with estimated internal surface area and with lengthy deposition times. Based on a literature search, it appears that gaseous decontamination or melt refining using fluxes specific for uranium removal have the potential for removing internal contamination from aluminum blades. A melt refining process was used to recycle blades during the 1950s and 1960s. The process removed roughly one-third of the uranium from the blades. Blade cast from recycled aluminum appeared to perform as well as blades from virgin material. New melt refining and gaseous decontamination processes have been shown to provide substantially better decontamination of pure aluminum. If these techniques can be successfully adapted to treat aluminum 214-X alloy, internal and, possibly, external reuse of aluminum alloys may be possible
Chiemchaisri, Chart; Chiemchaisri, Wilai; Prasertkulsak, Sirilak; Hamjinda, Nutta Sangnarin; Kootatep, Thammarat; Itonaga, Takanori; Yamamoto, Kazuo
2015-01-01
Only 3.4% of total water use in the Bangkok Metropolitan area is reused treated sewage. This study anticipates that further treated-sewage reuse in industrial sectors, commercial buildings and public parks, in addition to present in-plant and street cleaning purposes, would increase total water reuse to about 10%. New water reuse technologies using membrane bioreactor (MBR) and microfiltration (MF) as tertiary treatment were implemented to assess their potential for their application in the Bangkok Metropolitan area. The MBR was applied to the treatment of raw sewage in a central treatment plant of the Bangkok Metropolitan area. The MF membrane was used for polishing the effluent of the treatment plant. The results show the quality of treated water from MBR and tertiary MF treatment could meet stringent water reuse quality standard in terms of biochemical oxygen demand, suspended solids and biological parameters. Constant permeate flux of the membrane was achieved over long-term operation, during which inorganic fouling was observed. This is due to the fact that incoming sewage contains a considerable amount of inorganic constituents contributed from storm water and street inlet in the combined sewerage systems. The total cost of the MBR for sewage treatment and production of reuse water is estimated to be about USD1.10/m3.
ALCALDE SANZ LAURA; GAWLIK BERND
2017-01-01
As an input to the design of a Legal Instrument on Water Reuse in Europe, this report recommends minimum quality requirements for water reuse in agricultural irrigation and aquifer recharge based on a risk management approach.
Data reuse and the open data citation advantage
Directory of Open Access Journals (Sweden)
Heather A. Piwowar
2013-10-01
Full Text Available Background. Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the “citation benefit”. Furthermore, little is known about patterns in data reuse over time and across datasets. Method and Results. Here, we look at citation rates while controlling for many known citation predictors and investigate the variability of data reuse. In a multivariate regression on 10,555 studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% (95% confidence interval: 5% to 13% more citations than similar studies for which the data was not made available. Date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic were included as covariates. The citation benefit varied with date of dataset deposition: a citation benefit was most clear for papers published in 2004 and 2005, at about 30%. Authors published most papers using their own datasets within two years of their first publication on the dataset, whereas data reuse papers published by third-party investigators continued to accumulate for at least six years. To study patterns of data reuse directly, we compiled 9,724 instances of third party data reuse via mention of GEO or ArrayExpress accession numbers in the full text of papers. The level of third-party data use was high: for 100 datasets deposited in year 0, we estimated that 40 papers in PubMed reused a
Data reuse and the open data citation advantage.
Piwowar, Heather A; Vision, Todd J
2013-01-01
Background. Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the "citation benefit". Furthermore, little is known about patterns in data reuse over time and across datasets. Method and Results. Here, we look at citation rates while controlling for many known citation predictors and investigate the variability of data reuse. In a multivariate regression on 10,555 studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% (95% confidence interval: 5% to 13%) more citations than similar studies for which the data was not made available. Date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic were included as covariates. The citation benefit varied with date of dataset deposition: a citation benefit was most clear for papers published in 2004 and 2005, at about 30%. Authors published most papers using their own datasets within two years of their first publication on the dataset, whereas data reuse papers published by third-party investigators continued to accumulate for at least six years. To study patterns of data reuse directly, we compiled 9,724 instances of third party data reuse via mention of GEO or ArrayExpress accession numbers in the full text of papers. The level of third-party data use was high: for 100 datasets deposited in year 0, we estimated that 40 papers in PubMed reused a dataset by year 2, 100 by
Imaging of heart acoustic based on the sub-space methods using a microphone array.
Moghaddasi, Hanie; Almasganj, Farshad; Zoroufian, Arezoo
2017-07-01
Heart disease is one of the leading causes of death around the world. Phonocardiogram (PCG) is an important bio-signal which represents the acoustic activity of heart, typically without any spatiotemporal information of the involved acoustic sources. The aim of this study is to analyze the PCG by employing a microphone array by which the heart internal sound sources could be localized, too. In this paper, it is intended to propose a modality by which the locations of the active sources in the heart could also be investigated, during a cardiac cycle. In this way, a microphone array with six microphones is employed as the recording set up to be put on the human chest. In the following, the Group Delay MUSIC algorithm which is a sub-space based localization method is used to estimate the location of the heart sources in different phases of the PCG. We achieved to 0.14cm mean error for the sources of first heart sound (S 1 ) simulator and 0.21cm mean error for the sources of second heart sound (S 2 ) simulator with Group Delay MUSIC algorithm. The acoustical diagrams created for human subjects show distinct patterns in various phases of the cardiac cycles such as the first and second heart sounds. Moreover, the evaluated source locations for the heart valves are matched with the ones that are obtained via the 4-dimensional (4D) echocardiography applied, to a real human case. Imaging of heart acoustic map presents a new outlook to indicate the acoustic properties of cardiovascular system and disorders of valves and thereby, in the future, could be used as a new diagnostic tool. Copyright © 2017. Published by Elsevier B.V.
Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.
Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang
2017-08-25
We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.
Shokravi, H.; Bakhary, NH
2017-11-01
Subspace System Identification (SSI) is considered as one of the most reliable tools for identification of system parameters. Performance of a SSI scheme is considerably affected by the structure of the associated identification algorithm. Weight matrix is a variable in SSI that is used to reduce the dimensionality of the state-space equation. Generally one of the weight matrices of Principle Component (PC), Unweighted Principle Component (UPC) and Canonical Variate Analysis (CVA) are used in the structure of a SSI algorithm. An increasing number of studies in the field of structural health monitoring are using SSI for damage identification. However, studies that evaluate the performance of the weight matrices particularly in association with accuracy, noise resistance, and time complexity properties are very limited. In this study, the accuracy, noise-robustness, and time-efficiency of the weight matrices are compared using different qualitative and quantitative metrics. Three evaluation metrics of pole analysis, fit values and elapsed time are used in the assessment process. A numerical model of a mass-spring-dashpot and operational data is used in this research paper. It is observed that the principal components obtained using PC algorithms are more robust against noise uncertainty and give more stable results for the pole distribution. Furthermore, higher estimation accuracy is achieved using UPC algorithm. CVA had the worst performance for pole analysis and time efficiency analysis. The superior performance of the UPC algorithm in the elapsed time is attributed to using unit weight matrices. The obtained results demonstrated that the process of reducing dimensionality in CVA and PC has not enhanced the time efficiency but yield an improved modal identification in PC.
Wastewater and Sludge Reuse Management in Agriculture
Directory of Open Access Journals (Sweden)
Ioannis K. Kalavrouziotis
2016-08-01
Full Text Available Huge quantities of treated wastewater (TMWW and biosolids (sludge are produced every day all over the world, which exert a strong pressure on the environment. An important question that is raised is “what to do with them?”.An effort is put by the scientific community to eliminate the concept of “waste” and to replace it with the concept of “recycling of resources”, by means of effective management, which does not concern only the users, but all the other groups involved in the problem, such as facility administrators, operations, politicians, scientific community and the general population. Sludge concentration data showed that there exist 516 chemicals in biosolids which create a serious health risk. It is pointed out that this risk will be greatly exacerbated by chemical toxins present in the sludge which can predispose skin to infection by pathogens. Consequently, the need for science-based policies are necessary to effectively protect public health. The risk assessment due to sludge, is difficult to evaluate of due to the large number of unknown interactions involved. People living near the sludge application sites may suffer from such abnormalities as: eye, nose, and throat irritation, gastrointestinal abnormalities, as nausea, vomiting, diarrhea, including cough, difficulty in breathing, sinus congestion, skin infection and sores. Many problems seem to be related to biosolid and wastewater application in agriculture, which should be solved. A universal one, acknowledged as an “international health crisis” is the resistance of pathogens to antibiotics and to the evolution of multidrug resistance of bacteria”. Certain anthropogenically created environments have been identified as major sources of multidrug resistance bacteria such as in water treatment plants, concentrated animal feeding operations etc. All these, and many other health problems, render the safety of sludge and biosolid and wastewater agricultural reuse, for
Reusing and recycling in Saskatchewan: Environmental benefits of reusing and recycling
Energy Technology Data Exchange (ETDEWEB)
1994-01-01
After an introduction explaining the environmental benefits of reusing and recycling, as well as providing suggestions on minimizing waste and conserving energy, a directory of recyclers and handlers of various kinds of waste in Saskatchewan is presented. Names, addresses/telephone numbers, and types of materials accepted are given for recyclers of animal products, clothing or textiles, glass, compostable materials, industrial hardware, metals, office products, paper, plastic, and tires. Collection depots in the SARCAN recycling program for beverage containers are listed, giving town name, address, hours of operation, and telephone number. Receivers of waste dangerous goods are listed under the categories of ozone-depleting substances, waste batteries, solvents, lubricating oils and oil filters, paint, flammable liquids, antifreeze, drycleaning waste, and miscellaneous.
Tran, Kiet T.
2012-01-01
This study examined the relationship between information technology (IT) governance and software reuse success. Software reuse has been mostly an IT problem but rarely a business one. Studies in software reuse are abundant; however, to date, none has a deep appreciation of IT governance. This study demonstrated that IT governance had a positive…
Environmental impacts and sustainability of degraded water reuse
Energy Technology Data Exchange (ETDEWEB)
Corwin, D.L.; Bradford, S.A. [USDA ARS, Riverside, CA (United States). US Salin Laboratory
2008-09-15
Greater urban demand for finite water resources to meet domestic, agricultural, industrial, and recreational needs; increased frequency of drought resulting from erratic weather; and continued degradation of available water resources from point and nonpoint sources of pollution have focused attention on the reuse of degraded waters as a potential water source. However, short- and long-term detrimental environmental impacts and sustainability of degraded water reuse are not well known or understood. These concerns led to the organization of the 2007 ASA-CSSA-SSSA Symposium entitled Environmental Impacts and Sustainability of Degraded Water Reuse. Out of this symposium came a special collection of 4 review papers and 12 technical research papers focusing on various issues associated with the reuse of agricultural drainage water, well water generated in the production of natural gas from coalbeds, municipal wastewater and biosolids, wastewater from confined animal operations, urban runoff, and food-processing wastewater. Overviews of the papers, gaps in knowledge, and future research directions are presented. The future prognosis of degraded water reuse is promising, provided close attention is paid to managing constituents that pose short- and long-term threats to the environment and the health of humankind.
Does the water reuse affect the fish growth, welfare quality?
Directory of Open Access Journals (Sweden)
Štěpán Lang
2012-01-01
Full Text Available The fish production in aquaculture is growing from year to year. However capacities of current aquaculture facilities are limited. So the need of intensification of old facilities and building new intensive facilities is obvious. The high intensity of fish culture generates some questions. Could water reuse affect fish growth, welfare, health or quality of final product? A lot of research was performed for this issue but just a few works compared water reuse systems (RAS versus flow thru systems (FTS. A problem with CO2 oversaturation was solved by shallow diffusers. Fin erosion seems to be a problem of high stocking density and system hygienic but it is not related directly to water reuse. A few papers were written about biochemical blood stress markers but it was mostly aimed to acute crowding or changes were found at extreme stocking densities over 124 kg.m3 for rainbow trout and 70 kg.m3 for sea bass. The fish are able to accustom to increased noise produced by RAS equipment very fast so it don’t affect fish negatively. There wasn’t found any prove of main water reuse to fish influence in the available literature. All results indicates that if the ecological parameters are kept in natural range for the fish reared in RAS, there is no negative effect of water reuse on fish.
UV disinfection for reuse applications in North America.
Sakamoto, G; Schwartzel, D; Tomowich, D
2001-01-01
In an effort to conserve and protect limited water resources, the States of Florida and California have actively promoted wastewater reclamation and have implemented comprehensive regulations covering a range of reuse applications. Florida has a semi-tropical climate with heavy summer rains that are lost due to run off and evaporation. Much of California is arid and suffers periodic droughts, low annual rainfall and depleted ground water supplies. The high population density combined with heavy irrigation demands has depleted ground water supplies resulting in salt-water intrusion. During the past decade, Florida reuse sites have increased dramatically from 118 to 444 plants representing a total flow capacity of 826 MGD. California presently has over 250 plants producing 1 BGD with a projected increase of 160 sites over the next 20 years. To prevent the transmission of waterborne diseases, disinfection of reclaimed water is controlled by stringent regulations. Many states regulate wastewater treatment processes, nutrient removal, final effluent quality and disinfection criteria based upon the specific reuse application. As a rule, the resulting effluents have low turbidity and suspended solids. For such effluents, UV technology can economically achieve the most stringent disinfection targets that are required by the States of California and Florida for restricted and unrestricted reuse. This paper compares UV disinfection for wastewater reuse sites in California and Florida and discusses the effect of effluent quality on UV disinfection.
Morton, E.; Bilek, S. L.; Rowe, C. A.
2017-12-01
Understanding the spatial extent and behavior of the interplate contact in the Cascadia Subduction Zone (CSZ) may prove pivotal to preparation for future great earthquakes, such as the M9 event of 1700. Current and historic seismic catalogs are limited in their integrity by their short duration, given the recurrence rate of great earthquakes, and by their rather high magnitude of completeness for the interplate seismic zone, due to its offshore distance from these land-based networks. This issue is addressed via the 2011-2015 Cascadia Initiative (CI) amphibious seismic array deployment, which combined coastal land seismometers with more than 60 ocean-bottom seismometers (OBS) situated directly above the presumed plate interface. We search the CI dataset for small, previously undetected interplate earthquakes to identify seismic patches on the megathrust. Using the automated subspace detection method, we search for previously undetected events. Our subspace comprises eigenvectors derived from CI OBS and on-land waveforms extracted for existing catalog events that appear to have occurred on the plate interface. Previous work focused on analysis of two repeating event clusters off the coast of Oregon spanning all 4 years of deployment. Here we expand earlier results to include detection and location analysis to the entire CSZ margin during the first year of CI deployment, with more than 200 new events detected for the central portion of the margin. Template events used for subspace scanning primarily occurred beneath the land surface along the coast, at the downdip edge of modeled high slip patches for the 1700 event, with most concentrated at the northwestern edge of the Olympic Peninsula.
Radiological control criteria for materials considered for recycle and reuse
International Nuclear Information System (INIS)
Kennedy, W.E. Jr.; Hill, R.L.; Aaberg, R.L.; Wallo, A. III.
1995-01-01
Pacific Northwest Laboratory (PNL) is conducting technical analyses to support the U.S. Department of Energy (DOE), Office of Environmental Guidance, Air, Water, and Radiation Division (DOE/EH-232) in developing radiological control criteria for recycling or reuse of metals or equipment containing residual radioactive contamination from DOE operations. The criteria, framed as acceptable concentrations for release of materials for recycling or reuse, are risk-based and were developed through analysis of generic radiation exposure scenarios and pathways. The analysis includes evaluation of relevant radionuclides, potential mechanisms of exposure, and non-health-related impacts of residual radioactivity on electronics and film. The analysis considers 42 key radionuclides that DOE operations are known to generate and that may be contained in recycled or reused metals or equipment. The preliminary results are compared with similar results reported by the International Atomic Energy Agency, by radionuclide grouping. (author)
Reduce, reuse, recycle for robust cluster-state generation
International Nuclear Information System (INIS)
Horsman, Clare; Brown, Katherine L.; Kendon, Vivien M.; Munro, William J.
2011-01-01
Efficient generation of cluster states is crucial for engineering large-scale measurement-based quantum computers. Hybrid matter-optical systems offer a robust, scalable path to this goal. Such systems have an ancilla which acts as a bus connecting the qubits. We show that by generating the cluster in smaller sections of interlocking bricks, reusing one ancilla per brick, the cluster can be produced with maximal efficiency, requiring fewer than half the operations compared with no bus reuse. By reducing the time required to prepare sections of the cluster, bus reuse more than doubles the size of the computational workspace that can be used before decoherence effects dominate. A row of buses in parallel provides fully scalable cluster-state generation requiring only 20 controlled-phase gates per bus use.
Radiological control criteria for materials considered for recycle and reuse
International Nuclear Information System (INIS)
Kennedy, W.E. Jr.; Hill, R.L.; Aaberg, R.L.; Wallo, A. III
1994-11-01
Pacific Northwest Laboratory (PNL) is conducting technical analyses to support the US Department of Energy (DOE), Office of Environmental Guidance, Air, Water, and Radiation Division (DOE/EH-232) in developing radiological control criteria for recycling or reuse of metals or equipment containing residual radioactive contamination from DOE operations. The criteria, framed as acceptable concentrations for release of materials for recycling or reuse, are risk-based and were developed through analysis of generic radiation exposure scenarios and pathways. The analysis includes evaluation of relevant radionuclides, potential mechanisms of exposure, and non-health-related impacts of residual radioactivity on electronics and film. The analysis considers 42 key radionuclides that DOE operations are known to generate and that may be contained in recycled or reused metals or equipment. Preliminary results are compared with similar results reported by the International Atomic Energy Agency, by radionuclide grouping
Optimisation of industrial wastes reuse as construction materials.
Collivignarelli, C; Sorlini, S
2001-12-01
This study concerns the reuse of two inorganic wastes, foundry residues and fly ashes from municipal solid waste incineration, as "recycled aggregate" in concrete production. This kind of reuse was optimised by waste treatment with the following steps: waste washing with water; waste stabilisation-solidification treatment with inorganic reagents; final grinding of the stabilised waste after curing for about 10-20 days. Both the treated wastes were reused in concrete production with different mix-designs. Concrete specimens were characterised by means of conventional physical-mechanical tests (compression, elasticity modulus, shrinkage) and different leaching tests. Experimental results showed that a good structural and environmental quality of "recycled concrete" is due both to a correct waste treatment and to a correct mix-design for concrete mixture.
Beneficial reuse of US DOE Radioactive scrap metal
Energy Technology Data Exchange (ETDEWEB)
Motl, G.P.
1995-01-19
The US Department of Energy (DOE) has more than 2.5 million tons of radioactive scrap metal (RSM) that is either in inventory or expected to be generated over the next 25 years as major facilities within the weapons complex are decommissioned. Since much of this metal cannot be decontaminated easily, past practice has been to either retain this material in inventory or ship it to DOE disposal sites for burial. In an attempt to conserve natural resources and to avoid burial of this material at DOE disposal sites, options are now being explored to ``beneficially reuse`` this material. Under the beneficial reuse concept, RSM that cannot be decontaminated and free released is used in applications where the inherent contamination is not a detriment to its end use. This paper describes initiatives currently in progress in the United States that support the DOE beneficial reuse concept.
Beneficial reuse of US DOE Radioactive scrap metal
International Nuclear Information System (INIS)
Motl, G.P.
1995-01-01
The US Department of Energy (DOE) has more than 2.5 million tons of radioactive scrap metal (RSM) that is either in inventory or expected to be generated over the next 25 years as major facilities within the weapons complex are decommissioned. Since much of this metal cannot be decontaminated easily, past practice has been to either retain this material in inventory or ship it to DOE disposal sites for burial. In an attempt to conserve natural resources and to avoid burial of this material at DOE disposal sites, options are now being explored to ''beneficially reuse'' this material. Under the beneficial reuse concept, RSM that cannot be decontaminated and free released is used in applications where the inherent contamination is not a detriment to its end use. This paper describes initiatives currently in progress in the United States that support the DOE beneficial reuse concept
Water reuse practices in the United States and abroad
Energy Technology Data Exchange (ETDEWEB)
Sheikh, B.
1998-07-01
Reuse of water reclaimed from waste takes various adaptations in different parts of the globe to accommodate the economic forces underlying water supply constraints and local public health and sanitation conditions. The more developed regions have adopted and enforced the most rigorous water reuse regulations. The strong environmental safeguards adopted and the immense investments made in these countries in wastewater treatment provide for a very high quality of discharged effluent. Unfortunately, high (even adequate) levels of investment in sanitation and environmental protection have been lacking in most of the rest of the world. In the developing nations of the world a de facto brand of water reuse is practiced, generally without the benefit of protective standards of acceptable public health practice. Between the extremes of high standards of public health protection on the one hand, and the unsanitary use of raw sewage on the other, there are wide varieties of uses and treatment levels dictated by and evolved to accommodate the local economy.
Oilfield Produced Water Reuse and Reinjection with Membrane
Directory of Open Access Journals (Sweden)
Siagian Utjok W.R.
2018-01-01
Full Text Available Produced water has become a global environmental issue due to its huge volume and toxicity that may pose detrimental effects on receiving environment. Several approaches have been proposed to provide a strategy for produced water handling such as reinjection, reuse, or discharge. With various advantages, membrane technology has been increasingly used in produced water treatment replacing the conventional technologies. However, fouling is a major drawback of membrane processes in this application which needs to be controlled. This paper gives an overview and comparison of different produced water management. Special attention is given to produced water treatment for reuse purpose. Furthermore, the use of membrane processes in produced water reuse including performance, challenges, and future outlook are discussed.
Reuse of waste water: impact on water supply planning
Energy Technology Data Exchange (ETDEWEB)
Mangan, G.F. Jr.
1978-06-01
As the urban population of the world increases and demands on easily developable water supplies are exceeded, cities have recourse to a range of management alternatives to balance municipal water supply and demand. These alternatives range from doing nothing to modifying either the supply or the demand variable in the supply-demand relationship. The reuse or recycling of urban waste water in many circumstances may be an economically attractive and effective management strategy for extending existing supplies of developed water, for providing additional water where no developable supplies exist and for meeting water quality effluent discharge standards. The relationship among municipal, industrial and agricultural water use and the treatment links which may be required to modify the quality of a municipal waste effluent for either recycling or reuse purposes is described. A procedure is described for analyzing water reuse alternatives within a framework of regional water supply and waste water disposal planning and management.
Selecting a Sustainable Disinfection Technique for Wastewater Reuse Projects
Directory of Open Access Journals (Sweden)
Jorge Curiel-Esparza
2014-09-01
Full Text Available This paper presents an application of the Analytical Hierarchy Process (AHP by integrating a Delphi process for selecting the best sustainable disinfection technique for wastewater reuse projects. The proposed methodology provides project managers a tool to evaluate problems with multiple criteria and multiple alternatives which involve non-commeasurable decision criteria, with expert opinions playing a major role in the selection of these treatment technologies. Five disinfection techniques for wastewater reuse have been evaluated for each of the nine criteria weighted according to the opinions of consulted experts. Finally, the VIKOR method has been applied to determine a compromise solution, and to establish the stability of the results. Therefore, the expert system proposed to select the optimal disinfection alternative is a hybrid method combining the AHP with the Delphi method and the VIKOR technique, which is shown to be appropriate in realistic scenarios where multiple stakeholders are involved in the selection of a sustainable disinfection technique for wastewater reuse projects.
REUSE OF AUTOMOTIVE COMPONENTS FROM DISMANTLED END OF LIFE VEHICLES
Directory of Open Access Journals (Sweden)
Piotr NOWAKOWSKI
2013-12-01
Full Text Available The problem of recycling end of life automotive vehicles is serious worldwide. It is one of the most important streams of waste in developed countries. It has big importance as recycling potential of raw materials content in automotive vehicles is valuable. Different parts and assemblies after dismantling can also be reused in vehicles where replacement of specific component is necessary. Reuse of the components should be taken into consideration in selecting the vehicles dismantling strategy. It also complies with European Union policy concerning end of life vehicles (ELV. In the paper it is presented systematic approach to dismantling strategies including disassembly oriented on further reuse of components. It is focused on decision making and possible benefits calculation from economic and environmental point of view.
Contractions without non-trivial invariant subspaces satisfying a positivity condition
Directory of Open Access Journals (Sweden)
Bhaggy Duggal
2016-04-01
Full Text Available Abstract An operator A ∈ B ( H $A\\in B(\\mathcal{H}$ , the algebra of bounded linear transformations on a complex infinite dimensional Hilbert space H $\\mathcal{H}$ , belongs to class A ( n $\\mathcal{A}(n$ (resp., A ( ∗ − n $\\mathcal{A}(*-n$ if | A | 2 ≤ | A n + 1 | 2 n + 1 $\\vert A\\vert^{2}\\leq\\vert A^{n+1}\\vert^{\\frac{2}{n+1}}$ (resp., | A ∗ | 2 ≤ | A n + 1 | 2 n + 1 $\\vert A^{*}\\vert^{2}\\leq \\vert A^{n+1}\\vert^{\\frac{2}{n+1}}$ for some integer n ≥ 1 $n\\geq1$ , and an operator A ∈ B ( H $A\\in B(\\mathcal{H}$ is called n-paranormal, denoted A ∈ P ( n $A\\in \\mathcal{P}(n$ (resp., ∗ − n $*-n$ -paranormal, denoted A ∈ P ( ∗ − n $A\\in \\mathcal{P}(*-n$ if ∥ A x ∥ n + 1 ≤ ∥ A n + 1 x ∥ ∥ x ∥ n $\\Vert Ax\\Vert ^{n+1}\\leq \\Vert A^{n+1}x\\Vert \\Vert x\\Vert ^{n}$ (resp., ∥ A ∗ x ∥ n + 1 ≤ ∥ A n + 1 x ∥ ∥ x ∥ n $\\Vert A^{*}x\\Vert ^{n+1}\\leq \\Vert A^{n+1}x\\Vert \\Vert x\\Vert ^{n}$ for some integer n ≥ 1 $n\\geq 1$ and all x ∈ H $x \\in\\mathcal{H}$ . In this paper, we prove that if A ∈ { A ( n ∪ P ( n } $A\\in\\{\\mathcal{A}(n\\cup \\mathcal{P}(n\\}$ (resp., A ∈ { A ( ∗ − n ∪ P ( ∗ − n } $A\\in\\{\\mathcal{A}(*-n\\cup \\mathcal{P}(*-n\\}$ is a contraction without a non-trivial invariant subspace, then A, | A n + 1 | 2 n + 1 − | A | 2 $\\vert A^{n+1}\\vert^{\\frac{2}{n+1}}-\\vert A\\vert^{2}$ and | A n + 1 | 2 − n + 1 n | A | 2 + 1 $\\vert A^{n+1}\\vert^{2}- {\\frac{n+1}{n}}\\vert A\\vert^{2}+ 1$ (resp., A, | A n + 1 | 2 n + 1 − | A ∗ | 2 $\\vert A^{n+1}\\vert^{\\frac{2}{n+1}}-\\vert A^{*}\\vert^{2}$ and | A n + 2 | 2 − n + 1 n | A | 2 + 1 ≥ 0 $\\vert A^{n+2}\\vert^{2}- {\\frac{n+1}{n}}\\vert A\\vert^{2}+ 1\\geq0$ are proper contractions.
Performing Verification and Validation in Reuse-Based Software Engineering
Addy, Edward A.
1999-01-01
The implementation of reuse-based software engineering not only introduces new activities to the software development process, such as domain analysis and domain modeling, it also impacts other aspects of software engineering. Other areas of software engineering that are affected include Configuration Management, Testing, Quality Control, and Verification and Validation (V&V). Activities in each of these areas must be adapted to address the entire domain or product line rather than a specific application system. This paper discusses changes and enhancements to the V&V process, in order to adapt V&V to reuse-based software engineering.
An alternative process to treat boiler feed water for reuse.
Guirgis, Adel; Ghosh, Jyoti P; Achari, Gopal; Langford, Cooper H; Banerjee, Daliya
2012-09-01
A bench-scale process to treat boiler feed water for reuse in steam generation was developed. Industrial water samples from a steam-assisted gravity drainage plant in northern Alberta, Canada, were obtained and samples characterized. The technology, which consists of coagulation-settling to remove oil/grease and particulates followed by an advanced oxidative treatment, led to clean water samples with negligible organic carbon. Coagulation followed by settling removed most particulates and some insoluble organics. The advanced oxidative treatment removed any remaining color in the samples, decreased the organic content to near-zero, and provided water ready for reuse.
Reusing Implicit Cooperation. A Novel Approach to Knowledge Management
Directory of Open Access Journals (Sweden)
Luigi Lancieri
2008-07-01
Full Text Available The study described in this paper deals with information reuse obtained by implicit co-operation, particularly by recycling the contents of a proxy cache (shared memory. The objective is to automatically feed a Web server with large multimedia objects implicitly centred on community fields of interests. We show that the strategy of reusing previously downloaded information provides interesting advantages at a low cost; in particular, to reduce Web access time, to improve information retrieval, and to reduce Internet bandwidth use. Moreover, we use the conceptual frameworks of forgetting and collective intelligence to develop a model on which the operation of implicit cooperation is based.
A Case Study of Framework Design for Horizontal Reuse
DEFF Research Database (Denmark)
Christensen, Henrik Bærbak; Røn, Henrik
2000-01-01
through the application of design patterns. We outline the reuse process and analyse and classify the problems encountered during the first-instance framework reuse. The major lessons learned are: (1) that, while design patterns are well-known for providing decoupling solutions at the code level, the lack...... of similar decoupling techniques at the non-code level may give rise to technical mismatch problems between the framework and the client systems; (2) that such technical mismatch problems can be costly; and (3) that a reusable framework may beneficially provide a solution template when it cannot provide...
South Africa: Necsa redevelopment and reuse case and history
International Nuclear Information System (INIS)
Fourie, E.; Visagie, A.
2008-01-01
The purpose of this document is to share the experience gained from the decommissioning and redevelopment of redundant Necsa buildings in order to assist in the compilation of a holistic future redevelopment and reuse plan for the Necsa site. This document aims to ensure optimisation of decommissioning and redevelopment actions. This document also aims to facilitate timely and efficient completion of decommissioning projects in that it highlights alternatives for effective Redevelopment and Reuse (R and R) of buildings currently in a decommissioning phase. (author)
SOFTWARE REUSING AND ITS IMPACT ON THE SYSTEM'S COST
Lorena Lazo, Paul; Ruiz Lizama, Edgar
2014-01-01
This article presents two programs in C# that use an SQL server 2002 data access component, which is modified to be used with a 9i data base, with the purpose of evaluating a developer's productivity, making the comparative analysis of two stages: a system developed reusing software, and another one without software reusing. El artículo presenta dos programas en C# que utilizan un componente de acceso de base de datos SQL Server 2002, el cual se modifica para ser utilizado con una Base de ...
Water reuse and desalination in Spain – challenges and opportunities
Directory of Open Access Journals (Sweden)
Teresa Navarro
2018-04-01
Full Text Available This article offers an evaluation of the reuse of reclaimed water and desalination in Spain and aims to provide an overview of the state of the art and Spanish legal framework as far as non-conventional resources are concerned. The fight against the scarcity of water resources in this country, especially in the southeast, has made the production of new alternative water resources a clear priority and has turned the nation into a leader in water reuse and seawater desalination. The assessment presented can be used to help build a more general framework, like the European one, and shed light on other comparative legal experiences.
Improved semantic interoperability for content reuse through knowledge organization systems
Directory of Open Access Journals (Sweden)
José Antonio Moreiro González
2012-04-01
Full Text Available The Knowledge Organization Systems (KOS are resources designed to improve the knowledge interoperability, management and retrieval. As increases the web resources, it’s evidenced the lack of KOS, with the consequent impact in the resources interoperability. The KOSS are, by definition, complicated and costly tools, so much in his creation as in his management. The reuse of similar organizational structures is a necessary element in this context. They analyses experiences of reuse of The KOS and signals like the new standards are impinged on this appearance.
Liu, Y J; Tran, T; Postma, G; Buydens, L M C; Jansen, J
2018-08-22
Principal Component Analysis (PCA) is widely used in analytical chemistry, to reduce the dimensionality of a multivariate data set in a few Principal Components (PCs) that summarize the predominant patterns in the data. An accurate estimate of the number of PCs is indispensable to provide meaningful interpretations and extract useful information. We show how existing estimates for the number of PCs may fall short for datasets with considerable coherence, noise or outlier presence. We present here how Angle Distribution of the Loading Subspaces (ADLS) can be used to estimate the number of PCs based on the variability of loading subspace across bootstrap resamples. Based on comprehensive comparisons with other well-known methods applied on simulated dataset, we show that ADLS (1) may quantify the stability of a PCA model with several numbers of PCs simultaneously; (2) better estimate the appropriate number of PCs when compared with the cross-validation and scree plot methods, specifically for coherent data, and (3) facilitate integrated outlier detection, which we introduce in this manuscript. We, in addition, demonstrate how the analysis of different types of real-life spectroscopic datasets may benefit from these advantages of ADLS. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei
2012-12-01
Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.
Reusing Design Knowledge Based on Design Cases and Knowledge Map
Yang, Cheng; Liu, Zheng; Wang, Haobai; Shen, Jiaoqi
2013-01-01
Design knowledge was reused for innovative design work to support designers with product design knowledge and help designers who lack rich experiences to improve their design capacity and efficiency. First, based on the ontological model of product design knowledge constructed by taxonomy, implicit and explicit knowledge was extracted from some…
Silver Uptake and Reuse of Biomass by Saccharomyces cerevisiae ...
African Journals Online (AJOL)
Studies were carried out on the recovery of bound silver and reuse of Chlorella emersonii and Saccharomyces cerevisiae biomass for further silver uptake after they were placed in contact with 20mg/l silver for 30 minutes to allow for maximum binding. It was found that 0.16M nitric acid gave the best recovery rates of silver.
Potential for reuse of effluent from fish-processing industries
Directory of Open Access Journals (Sweden)
Luana Morena Rodrigues Vitor Dias Ferraciolli
2017-09-01
Full Text Available The most common problems in the fish processing industry relate to high water consumption and the generation of effluents with concentrated organic loads. Given that reuse can represent an alternative for sustainable development, this study sought to assess the potential for recycling effluents produced in a fish-processing plant. In order to do so, the final industrial effluent was analyzed using the American Public Health Association (APHA standard effluent-analysis method (2005. In addition, the study assessed treatments which produce effluents meeting the requirements prescribed by different countries' regulations for reuse and recycling. The results found that effluents with smaller organic loads, such as those from health barriers and monoblock washing, can be treated in order to remove nutrients and solids so that they can be subsequently reused. For effluents produced by the washing and gutting cylinders, it is recommended that large fragments of solid waste be removed beforehand. Effluents can in this way attain a quality compatible with industrial reuse. This study further highlights the possibility of treating effluents so as comply with drinking water standards. This would potentially allow them to be used within the actual fish-processing procedure; in such a case, a revision of standards and measures for controlling use should be considered to prevent microbiological damage to products and risks to handlers and final consumers.
Clearance of building structures for conventional non-nuclear reuse
International Nuclear Information System (INIS)
Buss, K.; Boehringer, S.
1998-01-01
At the example of a fuel assembly plant the strategy of control measurements on building surfaces, which shall be conventionally reused after their clearance, is regarded. Based on the given clearance levels the used measuring methods, especially with regard of possibly covered or intruded uranium contamination, are shown. The possibility of using the in-situ-γ-spectroscopy is discussed. (orig.) [de
Discovery and Reuse of Open Datasets: An Exploratory Study
Directory of Open Access Journals (Sweden)
Sara
2016-07-01
Full Text Available Objective: This article analyzes twenty cited or downloaded datasets and the repositories that house them, in order to produce insights that can be used by academic libraries to encourage discovery and reuse of research data in institutional repositories. Methods: Using Thomson Reuters’ Data Citation Index and repository download statistics, we identified twenty cited/downloaded datasets. We documented the characteristics of the cited/downloaded datasets and their corresponding repositories in a self-designed rubric. The rubric includes six major categories: basic information; funding agency and journal information; linking and sharing; factors to encourage reuse; repository characteristics; and data description. Results: Our small-scale study suggests that cited/downloaded datasets generally comply with basic recommendations for facilitating reuse: data are documented well; formatted for use with a variety of software; and shared in established, open access repositories. Three significant factors also appear to contribute to dataset discovery: publishing in discipline-specific repositories; indexing in more than one location on the web; and using persistent identifiers. The cited/downloaded datasets in our analysis came from a few specific disciplines, and tended to be funded by agencies with data publication mandates. Conclusions: The results of this exploratory research provide insights that can inform academic librarians as they work to encourage discovery and reuse of institutional datasets. Our analysis also suggests areas in which academic librarians can target open data advocacy in their communities in order to begin to build open data success stories that will fuel future advocacy efforts.
Reduce--recycle--reuse: guidelines for promoting perioperative waste management.
Laustsen, Gary
2007-04-01
The perioperative environment generates large amounts of waste, which negatively affects local and global ecosystems. To manage this waste health care facility leaders must focus on identifying correctable issues, work with relevant stakeholders to promote solutions, and adopt systematic procedural changes. Nurses and managers can moderate negative environmental effects by promoting reduction, recycling, and reuse of materials in the perioperative setting.
Integrating reuse measurement practices into the ERP requirements engineering process
Daneva, Maia; Münich, Jürgen; Vierimaa, Matias
2006-01-01
The management and deployment of reuse-driven and architecturecentric requirements engineering processes have become common in many organizations adopting Enterprise Resource Planning solutions. Yet, little is known about the variety of reusability aspects in ERP projects at the level of
Supporting the Reuse of Open Educational Resources through Open Standards
Glahn, Christian; Kalz, Marco; Gruber, Marion; Specht, Marcus
2010-01-01
Glahn, C., Kalz, M., Gruber, M., & Specht, M. (2010). Supporting the Reuse of Open Educational Resources through Open Standards. In T. Hirashima, A. F. Mohd Ayub, L. F. Kwok, S. L. Wong, S. C. Kong, & F. Y. Yu (Eds.), Workshop Proceedings of the 18th International Conference on Computers in
Emergy Evaluation of Different Straw Reuse Technologies in Northeast China
Directory of Open Access Journals (Sweden)
Xiaoxian Zhang
2015-08-01
Full Text Available Open burning of straw in China has degraded agricultural environments and has become a contributor to air pollution. Development of efficient straw-reuse technologies not only can yield economic benefits but also can protect the environment and can provide greater benefit to society. Thus, the overall benefits of straw-reuse technologies must be considered when making regional development planning and enterprise technology decisions. In addition, agricultural areas in China cross several climatic zones and have different weather characteristics and cultural conditions. In the present study, we assessed five types of straw-reuse technologies (straw-biogas production, -briquetting, -based power generation, -gasification, and -bioethanol production, using emergy analysis, in northeast China. Within each type, five individual cases were investigated, and the highest-performing cases were used for comparison across technologies. Emergy indices for comprehensive benefits for each category, namely, EYR, ELR, and ESI were calculated. Calculated indices suggest that straw-briquetting and -biogas production are the most beneficial technologies in terms of economy, environmental impact, and sustainability compared to straw-based power generation, -gasification, and -bioethanol production technologies. These two technologies can thus be considered the most suitable for straw reuse in China.
Reusing open data for learning database design through project development
Directory of Open Access Journals (Sweden)
Jose-Norberto MAZÓN
2015-12-01
Full Text Available This paper describes a novel methodology based on reusing open data for applying project-based learning in a Database Design subject of a university degree. This methodology is applied to the ARA (Alto Rendimiento Académico or High Academic Performance group taught in the degree in Computer Engineering at the University of Alicante (Spain during 2012/2013, 2013/2014, and 2014/2015. Openness philosophy implies that huge amount of data is available to students in tabular format, ready for reusing. In our teaching experience, students propose an original scenario where different open data can be reused to a specific goal. Then, it is proposed to design a database in order to manage this data in the envisioned scenario. Open data in the subject helps in instilling a creative and entrepreneur attitude in students, as well as encourages autonomous and lifelong learning. Surveys made to students at the end of each year shown that reusing open data within project-based learning methodologies makes more motivated students since they are using real data.
Finding source code on the web for remix and reuse
York, Springer New
2013-01-01
First comprehensive treatment of the topic, bringing together results from multiple research areas including information retrieval, programming, software tools, software reuse, testing, and social aspects Presents essential reading for researchers new to the area Includes contributions from leading companies and experts in data structure, software engineering, and HCI
Resource Recovery and Reuse in Organic Solid Waste Management
Lens, P.N.L.; Hamelers, H.V.M.; Hoitink, H.; Bidlingmaier, W.
2004-01-01
Uncontrolled spreading of waste materials leads to health problems and environmental damage. To prevent these problems a waste management infrastructure has been set to collect and dispose of the waste, based on a hierarchy of three principles: waste prevention, recycling/reuse, and final disposal.
Ceramic Ultra- and Nanofiltration for Municipal Wastewater Reuse
Shang, R.
2014-01-01
During the last decade, water reuse has been widely recognized in many regions of the world. Fouling of ceramic membranes, especially hydraulically irreversible fouling, is a critical aspect affecting the operational cost and energy consumption in water treatment plants. In addition, the reverse
Towards a national policy on wastewater reuse in Kenya | Kaluli ...
African Journals Online (AJOL)
Potable water for irrigation and industrial use is generally unavailable, and this calls for alternative water sources. Despite use of wastewater being illegal in Kenya, it is used to irrigate over 720 ha in Nairobi. In order to justify the formulation of a national policy to support wastewater reuse, secondary data which included the ...
Factors Affecting the Intention to Reuse Mobile Banking Service
Directory of Open Access Journals (Sweden)
Ceva Lavenja Arahita
2015-10-01
Full Text Available The accelerated advancement in technology resulted to the appearance of Self Service Technology. One form of self-service technology in the banking sector is the presence of mobile banking. This study aims to examine the influence of five factors toward the reusing of Mobile Bank Central Asia (BCA in Bandung. Those factors used in this study were the extension of Technology Acceptance Model (TAM constructs, i.e perceived usefulness, perceived ease of use, perceived credibility, customer awareness and social influence. Data was collected through distributed questionnaire to 100 respondents who used Mobile BCA by using judgment sampling. Multiple linear regression technique was employed to investigate the influence among variables. This study empirically concluded that consumer intention to reuse BCA mobile services was positively influenced by perceived ease of use, customer awareness and social influence. On the other hand, perceived usefulness and perceived credibility did not influence the intention of reusing Mobile BCA in Bandung. Further study is suggested to use probability sampling technique to cover the real voice of mobile banking user in Bandung and to explore the lack influence of perceived usefulness and perceived credibility toward reusing of Mobile BCA.
Factors Affecting the Intention to Reuse Mobile Banking Service
Directory of Open Access Journals (Sweden)
Ceva Lavenja Arahita
2015-12-01
Full Text Available The accelerated advancement in technology resulted to the appearance of Self Service Technology. One form of self-service technology in the banking sector is the presence of mobile banking. This study aims to examine the influence of five factors toward the reusing of Mobile Bank Central Asia (BCA in Bandung. Those factors used in this study were the extension of Technology Acceptance Model (TAM constructs, i.e perceived usefulness, perceived ease of use, perceived credibility, customer awareness and social influence. Data was collected through distributed questionnaire to 100 respondents who used Mobile BCA by using judgment sampling. Multiple linear regression technique was employed to investigate the influence among variables. This study empirically concluded that consumer intention to reuse BCA mobile services was positively influenced by social influence, customer awareness and perceived ease of use. On the other hand, perceived usefulness and perceived credibility did not influence the intention of reusing Mobile BCA in Bandung. Further study is suggested to use probability sampling technique to cover the real voice of mobile banking user in Bandung and to explore the lack influence of perceived usefulness and perceived credibility toward reusing of Mobile BCA.
The applicability of nanofiltration for the treatment and reuse of ...
African Journals Online (AJOL)
The main aim of the study was to test the feasibility of using nanofiltration (NF) processes for the treatment of reactive dyebath effluents from the textile industry, in order to recover the water and chemicals (salts) for reuse purposes. The study of the reusability of nanofiltered water for dyeing has been given little or no ...
Technology and human issues in reusing learning objects
Collis, Betty; Strijker, A.
2004-01-01
Reusing learning objects is as old as retelling a story or making use of libraries and textbooks, and in electronic form has received an enormous new impetus because of the World Wide Web and Web technologies. Are we at the brink of changing the "shape and form of learning, ... of being able to
The domain theory: patterns for knowledge and software reuse
National Research Council Canada - National Science Library
Sutcliffe, Alistair
2002-01-01
..., retrieval system, or any other means, without prior written permission of the publisher. Lawrence Erlbaum Associates, Inc., Publishers 10 Industrial Avenue Mahwah, New Jersey 07430 Library of Congress Cataloging-in-Publication Data Sutcliffe, Alistair, 1951- The domain theory : patterns for knowledge and software reuse / Alistair Sutcl...
Characterization of winery wastewater for reuse in California
More than thirty percent of the United States is currently in a drought that is expected to have profound social, economic, and environmental impacts. The intensification of drought conditions in southern and western regions of the country has spurred interest in wastewater reuse in agriculture, inc...
Reuse of waste cutting sand at Lawrence Livermore National Laboratory
International Nuclear Information System (INIS)
Mathews, S.; Wilson, K.
1998-01-01
Lawrence Livermore National Laboratory (LLNL) examined the waste stream from a water jet cutting operation, to evaluate the possible reuse of waste garnet sand. The sand is a cutting agent used to shape a variety of materials, including metals. Nearly 70,000 pounds of waste sand is generated annually by the cutting operation. The Environmental Protection Department evaluated two potential reuses for the spent garnet sand: backfill in utility trenches; and as a concrete constituent. In both applications, garnet waste would replace the sand formerly purchased by LLNL for these purposes. Findings supported the reuse of waste garnet sand in concrete, but disqualified its proposed application as trench backfill. Waste sand stabilized in a concrete matrix appeared to present no metals-leaching hazard; however, unconsolidated sand in trenches could potentially leach metals in concentrations high enough to threaten ground water quality. A technical report submitted to the San Francisco Bay Regional Water Quality Control Board was reviewed and accepted by that body. Reuse of waste garnet cutting sand as a constituent in concrete poured to form walkways and patios at LLNL was approved
The reuse of scrap and decontamination waste water from decommissioning
International Nuclear Information System (INIS)
Deng Junxian; Li Xin; Xie Xiaolong
2010-01-01
Huge amount of radioactive scrap with low activity will be generated from reactor decommissioning; the decontamination is concentrated in the surface layer of the scrap. The decontaminated substance can be removed by high pressure water jet to appear the base metal and to reuse the metal. Big amount of radioactive waste water will be generated by this decontamination technology; the radioactive of the waste water is mainly caused by the solid particle from decontamination. To remove the solid particle as clean as possible, the waste water can be reused. Different possible technology to remove the solid particle from the water had been investigated, such as the gravity deposit separation, the filtration and the centrifugal separation etc. The centrifugal separation technology is selected; it includes the hydraulic vortex, the centrifugal filtration and the centrifugal deposit. After the cost benefit analysis at last the centrifugal deposit used butterfly type separator is selected. To reuse the waste water the fresh water consumption and the cost for waste water treatment can be reduced. To reuse the radioactive scrap and the waste water from decommissioning will minimize the radioactive waste. (authors)