Iterated fractional Tikhonov regularization
NASA Astrophysics Data System (ADS)
Bianchi, Davide; Buccini, Alessandro; Donatelli, Marco; Serra-Capizzano, Stefano
2015-05-01
Fractional Tikhonov regularization methods have been recently proposed to reduce the oversmoothing property of the Tikhonov regularization in standard form, in order to preserve the details of the approximated solution. Their regularization and convergence properties have been previously investigated showing that they are of optimal order. This paper provides saturation and converse results on their convergence rates. Using the same iterative refinement strategy of iterated Tikhonov regularization, new iterated fractional Tikhonov regularization methods are introduced. We show that these iterated methods are of optimal order and overcome the previous saturation results. Furthermore, nonstationary iterated fractional Tikhonov regularization methods are investigated, establishing their convergence rate under general conditions on the iteration parameters. Numerical results confirm the effectiveness of the proposed regularization iterations.
Dimensional Regularization is Generic
NASA Astrophysics Data System (ADS)
Fujikawa, Kazuo
The absence of the quadratic divergence in the Higgs sector of the Standard Model in the dimensional regularization is usually regarded to be an exceptional property of a specific regularization. To understand what is going on in the dimensional regularization, we illustrate how to reproduce the results of the dimensional regularization for the λϕ4 theory in the more conventional regularization such as the higher derivative regularization; the basic postulate involved is that the quadratically divergent induced mass, which is independent of the scale change of the physical mass, is kinematical and unphysical. This is consistent with the derivation of the Callan-Symanzik equation, which is a comparison of two theories with slightly different masses, for the λϕ4 theory without encountering the quadratic divergence. In this sense the dimensional regularization may be said to be generic in a bottom-up approach starting with a successful low energy theory. We also define a modified version of the mass independent renormalization for a scalar field which leads to the homogeneous renormalization group equation. Implications of the present analysis on the Standard Model at high energies and the presence or absence of SUSY at LHC energies are briey discussed.
Illusory Liberalism in "Atlas de Geografía Humana"
ERIC Educational Resources Information Center
Ryan, Lorraine
2014-01-01
"Atlas de Geografía Humana" constitutes a critique of the much vaunted notion of a progressive Spain that has rectified the gender inequalities of the Francoist era, as one of the highly educated and successful protagonists, Fran, unwittingly adopts her mother's alignment with patriarchal norms. This novel elucidates the incompatibility…
Illusory Liberalism in "Atlas de Geografía Humana"
ERIC Educational Resources Information Center
Ryan, Lorraine
2014-01-01
"Atlas de Geografía Humana" constitutes a critique of the much vaunted notion of a progressive Spain that has rectified the gender inequalities of the Francoist era, as one of the highly educated and successful protagonists, Fran, unwittingly adopts her mother's alignment with patriarchal norms. This novel elucidates the incompatibility…
Sparsity regularized image reconstruction
NASA Astrophysics Data System (ADS)
Hero, Alfred
2015-03-01
Most image reconstruction problems are under-determined: there are far more pixels to be resolved than there are measurements available. This means that the image space has more degrees of freedom than the measurement space. To make headway in such under-determined image reconstruction problems one must either incorporate domain knowledge or regularize. Domain knowledge restricts the size of the image space while regularization introduces bias, e.g., by forcing the reconstructed image to be smooth or have limited support. Both approaches are equivalent and can be interpreted as making the image sparse in some domain. This paper will provide a selective overview of some of the principal methods of sparsity regularized image reconstruction.
Bronnikov, K A; Fabris, J C
2006-06-30
We study self-gravitating, static, spherically symmetric phantom scalar fields with arbitrary potentials (favored by cosmological observations) and single out 16 classes of possible regular configurations with flat, de Sitter, and anti-de Sitter asymptotics. Among them are traversable wormholes, bouncing Kantowski-Sachs (KS) cosmologies, and asymptotically flat black holes (BHs). A regular BH has a Schwarzschild-like causal structure, but the singularity is replaced by a de Sitter infinity, giving a hypothetic BH explorer a chance to survive. It also looks possible that our Universe has originated in a phantom-dominated collapse in another universe, with KS expansion and isotropization after crossing the horizon. Explicit examples of regular solutions are built and discussed. Possible generalizations include k-essence type scalar fields (with a potential) and scalar-tensor gravity.
Regularized Structural Equation Modeling.
Jacobucci, Ross; Grimm, Kevin J; McArdle, John J
A new method is proposed that extends the use of regularization in both lasso and ridge regression to structural equation models. The method is termed regularized structural equation modeling (RegSEM). RegSEM penalizes specific parameters in structural equation models, with the goal of creating easier to understand and simpler models. Although regularization has gained wide adoption in regression, very little has transferred to models with latent variables. By adding penalties to specific parameters in a structural equation model, researchers have a high level of flexibility in reducing model complexity, overcoming poor fitting models, and the creation of models that are more likely to generalize to new samples. The proposed method was evaluated through a simulation study, two illustrative examples involving a measurement model, and one empirical example involving the structural part of the model to demonstrate RegSEM's utility.
Synchronization of Regular Automata
NASA Astrophysics Data System (ADS)
Caucal, Didier
Functional graph grammars are finite devices which generate the class of regular automata. We recall the notion of synchronization by grammars, and for any given grammar we consider the class of languages recognized by automata generated by all its synchronized grammars. The synchronization is an automaton-related notion: all grammars generating the same automaton synchronize the same languages. When the synchronizing automaton is unambiguous, the class of its synchronized languages forms an effective boolean algebra lying between the classes of regular languages and unambiguous context-free languages. We additionally provide sufficient conditions for such classes to be closed under concatenation and its iteration.
Manifold Regularized Reinforcement Learning.
Li, Hongliang; Liu, Derong; Wang, Ding
2017-01-27
This paper introduces a novel manifold regularized reinforcement learning scheme for continuous Markov decision processes. Smooth feature representations for value function approximation can be automatically learned using the unsupervised manifold regularization method. The learned features are data-driven, and can be adapted to the geometry of the state space. Furthermore, the scheme provides a direct basis representation extension for novel samples during policy learning and control. The performance of the proposed scheme is evaluated on two benchmark control tasks, i.e., the inverted pendulum and the energy storage problem. Simulation results illustrate the concepts of the proposed scheme and show that it can obtain excellent performance.
Geometry of spinor regularization
NASA Technical Reports Server (NTRS)
Hestenes, D.; Lounesto, P.
1983-01-01
The Kustaanheimo theory of spinor regularization is given a new formulation in terms of geometric algebra. The Kustaanheimo-Stiefel matrix and its subsidiary condition are put in a spinor form directly related to the geometry of the orbit in physical space. A physically significant alternative to the KS subsidiary condition is discussed. Derivations are carried out without using coordinates.
ERIC Educational Resources Information Center
Sokol, William
This autoinstructional unit deals with the phenomena of regularity in chemical behavior. The prerequisites suggested are two other autoinstructional lessons (Experiments 1 and 2) identified in the Del Mod System as SE 018 020 and SE 018 023. The equipment needed is listed and 45 minutes is the suggested time allotment. The Student Guide includes…
Forghan, B. Takook, M.V.; Zarei, A.
2012-09-15
In this paper, the electron self-energy, photon self-energy and vertex functions are explicitly calculated in Krein space quantization including quantum metric fluctuation. The results are automatically regularized or finite. The magnetic anomaly and Lamb shift are also calculated in the one loop approximation in this method. Finally, the obtained results are compared to conventional QED results. - Highlights: Black-Right-Pointing-Pointer Krein regularization yields finite values for photon and electron self-energies and vertex function. Black-Right-Pointing-Pointer The magnetic anomaly is calculated and is exactly the same as the conventional result. Black-Right-Pointing-Pointer The Lamb shift is calculated and is approximately the same as in Hilbert space.
Regularized Hamiltonians and Spinfoams
NASA Astrophysics Data System (ADS)
Alesci, Emanuele
2012-05-01
We review a recent proposal for the regularization of the scalar constraint of General Relativity in the context of LQG. The resulting constraint presents strengths and weaknesses compared to Thiemann's prescription. The main improvement is that it can generate the 1-4 Pachner moves and its matrix elements contain 15j Wigner symbols, it is therefore compatible with the spinfoam formalism: the drawback is that Thiemann anomaly free proof is spoiled because the nodes that the constraint creates have volume.
Regularizing portfolio optimization
NASA Astrophysics Data System (ADS)
Still, Susanne; Kondor, Imre
2010-07-01
The optimization of large portfolios displays an inherent instability due to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting, which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification 'pressure'. This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade off between the two, depending on the size of the available dataset.
1973-10-01
The theory of strongly regular graphs was introduced by Bose r7 1 in 1963, in connection with partial geometries and 2 class association schemes. One...non adjacent vertices is constant and equal to ~. We shall denote by ~(p) (reap.r(p)) the set of vertices adjacent (resp.non adjacent) to a vertex p...is the complement of .2’ if the set of vertices of ~ is the set of vertices of .2’ and if two vertices in .2’ are adjacent if and only if they were
Flexible sparse regularization
NASA Astrophysics Data System (ADS)
Lorenz, Dirk A.; Resmerita, Elena
2017-01-01
The seminal paper of Daubechies, Defrise, DeMol made clear that {{\\ell }}p spaces with p\\in [1,2) and p-powers of the corresponding norms are appropriate settings for dealing with reconstruction of sparse solutions of ill-posed problems by regularization. It seems that the case p = 1 provides the best results in most of the situations compared to the cases p\\in (1,2). An extensive literature gives great credit also to using {{\\ell }}p spaces with p\\in (0,1) together with the corresponding quasi-norms, although one has to tackle challenging numerical problems raised by the non-convexity of the quasi-norms. In any of these settings, either superlinear, linear or sublinear, the question of how to choose the exponent p has been not only a numerical issue, but also a philosophical one. In this work we introduce a more flexible way of sparse regularization by varying exponents. We introduce the corresponding functional analytic framework, that leaves the setting of normed spaces but works with so-called F-norms. One curious result is that there are F-norms which generate the ℓ 1 space, but they are strictly convex, while the ℓ 1-norm is just convex.
Regularized versus non-regularized statistical reconstruction techniques
NASA Astrophysics Data System (ADS)
Denisova, N. V.
2011-08-01
An important feature of positron emission tomography (PET) and single photon emission computer tomography (SPECT) is the stochastic property of real clinical data. Statistical algorithms such as ordered subset-expectation maximization (OSEM) and maximum a posteriori (MAP) are a direct consequence of the stochastic nature of the data. The principal difference between these two algorithms is that OSEM is a non-regularized approach, while the MAP is a regularized algorithm. From the theoretical point of view, reconstruction problems belong to the class of ill-posed problems and should be considered using regularization. Regularization introduces an additional unknown regularization parameter into the reconstruction procedure as compared with non-regularized algorithms. However, a comparison of non-regularized OSEM and regularized MAP algorithms with fixed regularization parameters has shown very minor difference between reconstructions. This problem is analyzed in the present paper. To improve the reconstruction quality, a method of local regularization is proposed based on the spatially adaptive regularization parameter. The MAP algorithm with local regularization was tested in reconstruction of the Hoffman brain phantom.
Mainstreaming the Regular Classroom Student.
ERIC Educational Resources Information Center
Kahn, Michael
The paper presents activities, suggested by regular classroom teachers, to help prepare the regular classroom student for mainstreaming. The author points out that regular classroom children need a vehicle in which curiosity, concern, interest, fear, attitudes and feelings can be fully explored, where prejudices can be dispelled, and where the…
Ensemble manifold regularization.
Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng
2012-06-01
We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.
On regular rotating black holes
NASA Astrophysics Data System (ADS)
Torres, R.; Fayos, F.
2017-01-01
Different proposals for regular rotating black hole spacetimes have appeared recently in the literature. However, a rigorous analysis and proof of the regularity of this kind of spacetimes is still lacking. In this note we analyze rotating Kerr-like black hole spacetimes and find the necessary and sufficient conditions for the regularity of all their second order scalar invariants polynomial in the Riemann tensor. We also show that the regularity is linked to a violation of the weak energy conditions around the core of the rotating black hole.
Regular polygons in taxicab geometry
NASA Astrophysics Data System (ADS)
Hanson, J. R.
2014-10-01
A polygon of n sides will be called regular in taxicab geometry if it has n equal angles and n sides of equal taxicab length. This paper will show that there are no regular taxicab triangles and no regular taxicab pentagons. The sets of taxicab rectangles and taxicab squares will be shown to be the same, respectively, as the sets of Euclidean rectangles and Euclidean squares. A method of construction for a regular taxicab 2n-gon for any n will be demonstrated.
Linear regularity and [phi]-regularity of nonconvex sets
NASA Astrophysics Data System (ADS)
Ng, Kung Fu; Zang, Rui
2007-04-01
In this paper, we discuss some sufficient conditions for the linear regularity and bounded linear regularity (and their variations) of finitely many closed (not necessarily convex) sets in a normed vector space. The accompanying necessary conditions are also given in the setting of Asplund spaces.
Regularized Generalized Canonical Correlation Analysis
ERIC Educational Resources Information Center
Tenenhaus, Arthur; Tenenhaus, Michel
2011-01-01
Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to three or more sets of variables. It constitutes a general framework for many multi-block data analysis methods. It combines the power of multi-block data analysis methods (maximization of well identified criteria) and…
Federal Register 2010, 2011, 2012, 2013, 2014
2011-01-20
... From the Federal Register Online via the Government Publishing Office FARM CREDIT SYSTEM INSURANCE CORPORATION Farm Credit System Insurance Corporation Board Regular Meeting SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). Date and Time: The...
Trajectory optimization using regularized variables
NASA Technical Reports Server (NTRS)
Lewallen, J. M.; Szebehely, V.; Tapley, B. D.
1969-01-01
Regularized equations for a particular optimal trajectory are compared with unregularized equations with respect to computational characteristics, using perturbation type numerical optimization. In the case of the three dimensional, low thrust, Earth-Jupiter rendezvous, the regularized equations yield a significant reduction in computer time.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-07
... Board (Board). Date and Time: The meeting of the Board will be held at the offices of the Farm Credit Administration in McLean, Virginia, on December 9, 2010, from 12:30 p.m. until such time as the Board concludes... CORPORATION Regular Meeting AGENCY: Farm Credit System Insurance Corporation Board. ACTION: Regular meeting...
Regularly timed events amid chaos
NASA Astrophysics Data System (ADS)
Blakely, Jonathan N.; Cooper, Roy M.; Corron, Ned J.
2015-11-01
We show rigorously that the solutions of a class of chaotic oscillators are characterized by regularly timed events in which the derivative of the solution is instantaneously zero. The perfect regularity of these events is in stark contrast with the well-known unpredictability of chaos. We explore some consequences of these regularly timed events through experiments using chaotic electronic circuits. First, we show that a feedback loop can be implemented to phase lock the regularly timed events to a periodic external signal. In this arrangement the external signal regulates the timing of the chaotic signal but does not strictly lock its phase. That is, phase slips of the chaotic oscillation persist without disturbing timing of the regular events. Second, we couple the regularly timed events of one chaotic oscillator to those of another. A state of synchronization is observed where the oscillators exhibit synchronized regular events while their chaotic amplitudes and phases evolve independently. Finally, we add additional coupling to synchronize the amplitudes, as well, however in the opposite direction illustrating the independence of the amplitudes from the regularly timed events.
Quantum Ergodicity on Regular Graphs
NASA Astrophysics Data System (ADS)
Anantharaman, Nalini
2017-07-01
We give three different proofs of the main result of Anantharaman and Le Masson (Duke Math J 164(4):723-765, 2015), establishing quantum ergodicity—a form of delocalization—for eigenfunctions of the laplacian on large regular graphs of fixed degree. These three proofs are much shorter than the original one, quite different from one another, and we feel that each of the four proofs sheds a different light on the problem. The goal of this exploration is to find a proof that could be adapted for other models of interest in mathematical physics, such as the Anderson model on large regular graphs, regular graphs with weighted edges, or possibly certain models of non-regular graphs. A source of optimism in this direction is that we are able to extend the last proof to the case of anisotropic random walks on large regular graphs.
Rotating regular black hole solution
NASA Astrophysics Data System (ADS)
Abdujabbarov, Ahmadjon
2016-07-01
Based on the Newman-Janis algorithm, the Ayón-Beato-García spacetime metric [Phys. Rev. Lett. 80, 5056 (1998)] of the regular spherically symmetric, static, and charged black hole has been converted into rotational form. It is shown that the derived solution for rotating a regular black hole is regular and the critical value of the electric charge for which two horizons merge into one sufficiently decreases in the presence of the nonvanishing rotation parameter a of the black hole.
NONCONVEX REGULARIZATION FOR SHAPE PRESERVATION
CHARTRAND, RICK
2007-01-16
The authors show that using a nonconvex penalty term to regularize image reconstruction can substantially improve the preservation of object shapes. The commonly-used total-variation regularization, {integral}|{del}u|, penalizes the length of the object edges. They show that {integral}|{del}u|{sup p}, 0 < p < 1, only penalizes edges of dimension at least 2-p, and thus finite-length edges not at all. We give numerical examples showing the resulting improvement in shape preservation.
Condition Number Regularized Covariance Estimation.
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2013-06-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n" setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.
Condition Number Regularized Covariance Estimation*
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2012-01-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197
Geometric continuum regularization of quantum field theory
Halpern, M.B. . Dept. of Physics)
1989-11-08
An overview of the continuum regularization program is given. The program is traced from its roots in stochastic quantization, with emphasis on the examples of regularized gauge theory, the regularized general nonlinear sigma model and regularized quantum gravity. In its coordinate-invariant form, the regularization is seen as entirely geometric: only the supermetric on field deformations is regularized, and the prescription provides universal nonperturbative invariant continuum regularization across all quantum field theory. 54 refs.
Word regularity affects orthographic learning.
Wang, Hua-Chen; Castles, Anne; Nickels, Lyndsey
2012-01-01
Share's self-teaching hypothesis proposes that orthographic representations are acquired via phonological decoding. A key, yet untested, prediction of this theory is that there should be an effect of word regularity on the number and quality of word-specific orthographic representations that children acquire. Thirty-four Grade 2 children were exposed to the sound and meaning of eight novel words and were then presented with those words in written form in short stories. Half the words were assigned regular pronunciations and half irregular pronunciations. Lexical decision and spelling tasks conducted 10 days later revealed that the children's orthographic representations of the regular words appeared to be stronger and more extensive than those of the irregular words.
Dimensional regularization in configuration space
Bollini, C.G. |; Giambiagi, J.J.
1996-05-01
Dimensional regularization is introduced in configuration space by Fourier transforming in {nu} dimensions the perturbative momentum space Green functions. For this transformation, the Bochner theorem is used; no extra parameters, such as those of Feynman or Bogoliubov and Shirkov, are needed for convolutions. The regularized causal functions in {ital x} space have {nu}-dependent moderated singularities at the origin. They can be multiplied together and Fourier transformed (Bochner) without divergence problems. The usual ultraviolet divergences appear as poles of the resultant analytic functions of {nu}. Several examples are discussed. {copyright} {ital 1996 The American Physical Society.}
Resource Guide for Regular Teachers.
ERIC Educational Resources Information Center
Kampert, George J.
The resource guide for regular teachers provides policies and procedures of the Flour Bluff (Texas) school district regarding special education of handicapped students. Individual sections provide guidelines for the following areas: the referral process; individual assessment; participation on student evaluation and placement committee; special…
Sparsity regularization in dynamic elastography.
Honarvar, M; Sahebjavaher, R S; Salcudean, S E; Rohling, R
2012-10-07
We consider the inverse problem of continuum mechanics with the tissue deformation described by a mixed displacement-pressure finite element formulation. The mixed formulation is used to model nearly incompressible materials by simultaneously solving for both elasticity and pressure distributions. To improve numerical conditioning, a common solution to this problem is to use regularization to constrain the solutions of the inverse problem. We present a sparsity regularization technique that uses the discrete cosine transform to transform the elasticity and pressure fields to a sparse domain in which a smaller number of unknowns is required to represent the original field. We evaluate the approach by solving the dynamic elastography problem for synthetic data using such a mixed finite element technique, assuming time harmonic motion, and linear, isotropic and elastic behavior for the tissue. We compare our simulation results to those obtained using the more common Tikhonov regularization. We show that the sparsity regularization is less dependent on boundary conditions, less influenced by noise, requires no parameter tuning and is computationally faster. The algorithm has been tested on magnetic resonance elastography data captured from a CIRS elastography phantom with similar results as the simulation.
Regularized Generalized Structured Component Analysis
ERIC Educational Resources Information Center
Hwang, Heungsun
2009-01-01
Generalized structured component analysis (GSCA) has been proposed as a component-based approach to structural equation modeling. In practice, GSCA may suffer from multi-collinearity, i.e., high correlations among exogenous variables. GSCA has yet no remedy for this problem. Thus, a regularized extension of GSCA is proposed that integrates a ridge…
Regularized Generalized Structured Component Analysis
ERIC Educational Resources Information Center
Hwang, Heungsun
2009-01-01
Generalized structured component analysis (GSCA) has been proposed as a component-based approach to structural equation modeling. In practice, GSCA may suffer from multi-collinearity, i.e., high correlations among exogenous variables. GSCA has yet no remedy for this problem. Thus, a regularized extension of GSCA is proposed that integrates a ridge…
Giftedness in the Regular Classroom.
ERIC Educational Resources Information Center
Green, Anne
This paper presents a rationale for serving gifted students in the regular classroom and offers guidelines for recognizing students who are gifted in the seven types of intelligence proposed by Howard Gardner. Stressed is the importance of creating in the classroom a community of learners that allows all children to actively explore ideas and…
Rotations of the Regular Polyhedra
ERIC Educational Resources Information Center
Jones, MaryClara; Soto-Johnson, Hortensia
2006-01-01
The study of the rotational symmetries of the regular polyhedra is important in the classroom for many reasons. Besides giving the students an opportunity to visualize in three dimensions, it is also an opportunity to relate two-dimensional and three-dimensional concepts. For example, rotations in R[superscript 2] require a point and an angle of…
Regularization of Localized Degradation Processes
1996-12-28
order to assess the regularization properties of non-classical micropolar Cosserat continua which feature non-symmetric stress and strain tensors because...of the presence of couple-stresses and micro-curvatures. It was shown that micropolar media may only exhibit localized failure in the form of tensile
Temporal regularity in speech perception: Is regularity beneficial or deleterious?
Geiser, Eveline; Shattuck-Hufnagel, Stefanie
2012-04-01
Speech rhythm has been proposed to be of crucial importance for correct speech perception and language learning. This study investigated the influence of speech rhythm in second language processing. German pseudo-sentences were presented to participants in two conditions: 'naturally regular speech rhythm' and an 'emphasized regular rhythm'. Nine expert English speakers with 3.5±1.6 years of German training repeated each sentence after hearing it once over headphones. Responses were transcribed using the International Phonetic Alphabet and analyzed for the number of correct, false and missing consonants as well as for consonant additions. The over-all number of correct reproductions of consonants did not differ between the two experimental conditions. However, speech rhythmicization significantly affected the serial position curve of correctly reproduced syllables. The results of this pilot study are consistent with the view that speech rhythm is important for speech perception.
Regular languages, regular grammars and automata in splicing systems
NASA Astrophysics Data System (ADS)
Mohamad Jan, Nurhidaya; Fong, Wan Heng; Sarmin, Nor Haniza
2013-04-01
Splicing system is known as a mathematical model that initiates the connection between the study of DNA molecules and formal language theory. In splicing systems, languages called splicing languages refer to the set of double-stranded DNA molecules that may arise from an initial set of DNA molecules in the presence of restriction enzymes and ligase. In this paper, some splicing languages resulted from their respective splicing systems are shown. Since all splicing languages are regular, languages which result from the splicing systems can be further investigated using grammars and automata in the field of formal language theory. The splicing language can be written in the form of regular languages generated by grammar. Besides that, splicing systems can be accepted by automata. In this research, two restriction enzymes are used in splicing systems namely BfuCI and NcoI.
Regular Motions of Resonant Asteroids
NASA Astrophysics Data System (ADS)
Ferraz-Mello, S.
1990-11-01
RESUMEN. Se revisan resultados analiticos relativos a soluciones regulares del problema asteroidal eliptico promediados en la vecindad de una resonancia con jupiten Mencionamos Ia ley de estructura para libradores de alta excentricidad, la estabilidad de los centros de liberaci6n, las perturbaciones forzadas por la excentricidad de jupiter y las 6rbitas de corotaci6n. ABSTRAC This paper reviews analytical results concerning the regular solutions of the elliptic asteroidal problem averaged in the neighbourhood of a resonance with jupiter. We mention the law of structure for high-eccentricity librators, the stability of the libration centers, the perturbations forced by the eccentricity ofjupiter and the corotation orbits. Key words: ASThROIDS
Energy functions for regularization algorithms
NASA Technical Reports Server (NTRS)
Delingette, H.; Hebert, M.; Ikeuchi, K.
1991-01-01
Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.
Physical model of dimensional regularization
NASA Astrophysics Data System (ADS)
Schonfeld, Jonathan F.
2016-12-01
We explicitly construct fractals of dimension 4{-}ɛ on which dimensional regularization approximates scalar-field-only quantum-field theory amplitudes. The construction does not require fractals to be Lorentz-invariant in any sense, and we argue that there probably is no Lorentz-invariant fractal of dimension greater than 2. We derive dimensional regularization's power-law screening first for fractals obtained by removing voids from 3-dimensional Euclidean space. The derivation applies techniques from elementary dielectric theory. Surprisingly, fractal geometry by itself does not guarantee the appropriate power-law behavior; boundary conditions at fractal voids also play an important role. We then extend the derivation to 4-dimensional Minkowski space. We comment on generalization to non-scalar fields, and speculate about implications for quantum gravity.
Diffusion on regular random fractals
NASA Astrophysics Data System (ADS)
Aarão Reis, Fábio D. A.
1996-12-01
We study random walks on structures intermediate to statistical and deterministic fractals called regular random fractals, constructed introducing randomness in the distribution of lacunas of Sierpinski carpets. Random walks are simulated on finite stages of these fractals and the scaling properties of the mean square displacement 0305-4470/29/24/007/img1 of N-step walks are analysed. The anomalous diffusion exponents 0305-4470/29/24/007/img2 obtained are very near the estimates for the carpets with the same dimension. This result motivates a discussion on the influence of some types of lattice irregularity (random structure, dead ends, lacunas) on 0305-4470/29/24/007/img2, based on results on several fractals. We also propose to use these and other regular random fractals as models for real self-similar structures and to generalize results for statistical systems on fractals.
Regular connections among generalized connections
NASA Astrophysics Data System (ADS)
Fleischhack, Christian
2003-09-01
The properties of the space A of regular connections as a subset of the space Ā of generalized connections in the Ashtekar framework are studied. For every choice of compact structure group and smoothness category for the paths, it is determined whether A is dense in Ā or not. Moreover, it is proven that A has Ashtekar-Lewandowski measure zero for every non-trivial structure group and every smoothness category. The analogous results hold for gauge orbits instead of connections.
On different facets of regularization theory.
Chen, Zhe; Haykin, Simon
2002-12-01
This review provides a comprehensive understanding of regularization theory from different perspectives, emphasizing smoothness and simplicity principles. Using the tools of operator theory and Fourier analysis, it is shown that the solution of the classical Tikhonov regularization problem can be derived from the regularized functional defined by a linear differential (integral) operator in the spatial (Fourier) domain. State-of-the-art research relevant to the regularization theory is reviewed, covering Occam's razor, minimum length description, Bayesian theory, pruning algorithms, informational (entropy) theory, statistical learning theory, and equivalent regularization. The universal principle of regularization in terms of Kolmogorov complexity is discussed. Finally, some prospective studies on regularization theory and beyond are suggested.
NASA Astrophysics Data System (ADS)
Fukushima, Toshio
2007-01-01
We present a new scheme to regularize a three-dimensional two-body problem under perturbations. It is a combination of Sundman's time transformation and Levi-Civita's spatial coordinate transformation applied to the two-dimensional components of the position and velocity vectors in the osculating orbital plane. We adopt a coordinate triad specifying the plane as a function of the orbital angular momentum vector only. Since the magnitude of the orbital angular momentum is explicitly computed from the in-the-plane components of the position and velocity vectors, only two components of the orbital angular momentum vector are to be determined. In addition to these, we select the total energy of the two-body system and the physical time as additional components of the new variables. The equations of motion of the new variables have no singularity even when the mutual distance is extremely small, and therefore, the new variables are suitable to deal with close encounters. As a result, the number of dependent variables in the new scheme becomes eight, which is significantly smaller than the existing schemes to avoid close encounters: two less than the Kustaanheimo-Stiefel and the Bürdet-Ferrandiz regularizations, and five less than the Sperling-Bürdet/Bürdet-Heggie regularization.
Regular sun exposure benefits health.
van der Rhee, H J; de Vries, E; Coebergh, J W
2016-12-01
Since it was discovered that UV radiation was the main environmental cause of skin cancer, primary prevention programs have been started. These programs advise to avoid exposure to sunlight. However, the question arises whether sun-shunning behaviour might have an effect on general health. During the last decades new favourable associations between sunlight and disease have been discovered. There is growing observational and experimental evidence that regular exposure to sunlight contributes to the prevention of colon-, breast-, prostate cancer, non-Hodgkin lymphoma, multiple sclerosis, hypertension and diabetes. Initially, these beneficial effects were ascribed to vitamin D. Recently it became evident that immunomodulation, the formation of nitric oxide, melatonin, serotonin, and the effect of (sun)light on circadian clocks, are involved as well. In Europe (above 50 degrees north latitude), the risk of skin cancer (particularly melanoma) is mainly caused by an intermittent pattern of exposure, while regular exposure confers a relatively low risk. The available data on the negative and positive effects of sun exposure are discussed. Considering these data we hypothesize that regular sun exposure benefits health. Copyright © 2016 Elsevier Ltd. All rights reserved.
Knowledge and regularity in planning
NASA Technical Reports Server (NTRS)
Allen, John A.; Langley, Pat; Matwin, Stan
1992-01-01
The field of planning has focused on several methods of using domain-specific knowledge. The three most common methods, use of search control, use of macro-operators, and analogy, are part of a continuum of techniques differing in the amount of reused plan information. This paper describes TALUS, a planner that exploits this continuum, and is used for comparing the relative utility of these methods. We present results showing how search control, macro-operators, and analogy are affected by domain regularity and the amount of stored knowledge.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-11-18
... of Humana Insurance Company, a Division of CareNetwork, Inc., Front End Operations and Account Installation- Product Testing Groups, Green Bay, Wisconsin, to apply for Trade Adjustment Assistance (TAA). On... De Pere, and not Green Bay, Wisconsin. Accordingly, the subject workers are workers at...
MAXIMAL POINTS OF A REGULAR TRUTH FUNCTION
Every canonical linearly separable truth function is a regular function, but not every regular truth function is linearly separable. The most...promising method of determining which of the regular truth functions are linearly separable r quires finding their maximal and minimal points. In this...report is developed a quick, systematic method of finding the maximal points of any regular truth function in terms of its arithmetic invariants. (Author)
Natural frequency of regular basins
NASA Astrophysics Data System (ADS)
Tjandra, Sugih S.; Pudjaprasetya, S. R.
2014-03-01
Similar to the vibration of a guitar string or an elastic membrane, water waves in an enclosed basin undergo standing oscillatory waves, also known as seiches. The resonant (eigen) periods of seiches are determined by water depth and geometry of the basin. For regular basins, explicit formulas are available. Resonance occurs when the dominant frequency of external force matches the eigen frequency of the basin. In this paper, we implement the conservative finite volume scheme to 2D shallow water equation to simulate resonance in closed basins. Further, we would like to use this scheme and utilizing energy spectra of the recorded signal to extract resonant periods of arbitrary basins. But here we first test the procedure for getting resonant periods of a square closed basin. The numerical resonant periods that we obtain are comparable with those from analytical formulas.
Regularized degenerate multi-solitons
NASA Astrophysics Data System (ADS)
Correa, Francisco; Fring, Andreas
2016-09-01
We report complex {P}{T} -symmetric multi-soliton solutions to the Korteweg de-Vries equation that asymptotically contain one-soliton solutions, with each of them possessing the same amount of finite real energy. We demonstrate how these solutions originate from degenerate energy solutions of the Schrödinger equation. Technically this is achieved by the application of Darboux-Crum transformations involving Jordan states with suitable regularizing shifts. Alternatively they may be constructed from a limiting process within the context Hirota's direct method or on a nonlinear superposition obtained from multiple Bäcklund transformations. The proposed procedure is completely generic and also applicable to other types of nonlinear integrable systems.
Rule extraction by successive regularization.
Ishikawa, M
2000-12-01
Knowledge acquisition is, needless to say, important, because it is a key to the solution to one of the bottlenecks in artificial intelligence. Recently, knowledge acquisition using neural networks, called rule extraction, is attracting wide attention because of its computational simplicity and ability to generalize. Proposed in this paper is a novel approach to rule extraction named successive regularization. It generates a small number of dominant rules at an earlier stage and less dominant rules or exceptions at later stages. It has various advantages such as robustness of computation, better understanding, and similarity to child development. It is applied to the classification of mushrooms, the recognition of promoters in DNA sequences and the classification of irises. Empirical results indicate superior performance of rule extraction in terms of the number and the size of rules for explaining data.
Some Cosine Relations and the Regular Heptagon
ERIC Educational Resources Information Center
Osler, Thomas J.; Heng, Phongthong
2007-01-01
The ancient Greek mathematicians sought to construct, by use of straight edge and compass only, all regular polygons. They had no difficulty with regular polygons having 3, 4, 5 and 6 sides, but the 7-sided heptagon eluded all their attempts. In this article, the authors discuss some cosine relations and the regular heptagon. (Contains 1 figure.)
Regular Pentagons and the Fibonacci Sequence.
ERIC Educational Resources Information Center
French, Doug
1989-01-01
Illustrates how to draw a regular pentagon. Shows the sequence of a succession of regular pentagons formed by extending the sides. Calculates the general formula of the Lucas and Fibonacci sequences. Presents a regular icosahedron as an example of the golden ratio. (YP)
22 CFR 120.39 - Regular employee.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Regular employee. 120.39 Section 120.39 Foreign Relations DEPARTMENT OF STATE INTERNATIONAL TRAFFIC IN ARMS REGULATIONS PURPOSE AND DEFINITIONS § 120.39 Regular employee. (a) A regular employee means for purposes of this subchapter: (1) An...
22 CFR 120.39 - Regular employee.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Regular employee. 120.39 Section 120.39 Foreign Relations DEPARTMENT OF STATE INTERNATIONAL TRAFFIC IN ARMS REGULATIONS PURPOSE AND DEFINITIONS § 120.39 Regular employee. (a) A regular employee means for purposes of this subchapter: (1) An...
22 CFR 120.39 - Regular employee.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Regular employee. 120.39 Section 120.39 Foreign Relations DEPARTMENT OF STATE INTERNATIONAL TRAFFIC IN ARMS REGULATIONS PURPOSE AND DEFINITIONS § 120.39 Regular employee. (a) A regular employee means for purposes of this subchapter: (1) An...
Class of regular bouncing cosmologies
NASA Astrophysics Data System (ADS)
Vasilić, Milovan
2017-06-01
In this paper, I construct a class of everywhere regular geometric sigma models that possess bouncing solutions. Precisely, I show that every bouncing metric can be made a solution of such a model. My previous attempt to do so by employing one scalar field has failed due to the appearance of harmful singularities near the bounce. In this work, I use four scalar fields to construct a class of geometric sigma models which are free of singularities. The models within the class are parametrized by their background geometries. I prove that, whatever background is chosen, the dynamics of its small perturbations is classically stable on the whole time axis. Contrary to what one expects from the structure of the initial Lagrangian, the physics of background fluctuations is found to carry two tensor, two vector, and two scalar degrees of freedom. The graviton mass, which naturally appears in these models, is shown to be several orders of magnitude smaller than its experimental bound. I provide three simple examples to demonstrate how this is done in practice. In particular, I show that graviton mass can be made arbitrarily small.
A multiplicative regularization for force reconstruction
NASA Astrophysics Data System (ADS)
Aucejo, M.; De Smet, O.
2017-02-01
Additive regularizations, such as Tikhonov-like approaches, are certainly the most popular methods for reconstructing forces acting on a structure. These approaches require, however, the knowledge of a regularization parameter, that can be numerically computed using specific procedures. Unfortunately, these procedures are generally computationally intensive. For this particular reason, it could be of primary interest to propose a method able to proceed without defining any regularization parameter beforehand. In this paper, a multiplicative regularization is introduced for this purpose. By construction, the regularized solution has to be calculated in an iterative manner. In doing so, the amount of regularization is automatically adjusted throughout the resolution process. Validations using synthetic and experimental data highlight the ability of the proposed approach in providing consistent reconstructions.
Total variation regularization with bounded linear variations
NASA Astrophysics Data System (ADS)
Makovetskii, Artyom; Voronin, Sergei; Kober, Vitaly
2016-09-01
One of the most known techniques for signal denoising is based on total variation regularization (TV regularization). A better understanding of TV regularization is necessary to provide a stronger mathematical justification for using TV minimization in signal processing. In this work, we deal with an intermediate case between one- and two-dimensional cases; that is, a discrete function to be processed is two-dimensional radially symmetric piecewise constant. For this case, the exact solution to the problem can be obtained as follows: first, calculate the average values over rings of the noisy function; second, calculate the shift values and their directions using closed formulae depending on a regularization parameter and structure of rings. Despite the TV regularization is effective for noise removal; it often destroys fine details and thin structures of images. In order to overcome this drawback, we use the TV regularization for signal denoising subject to linear signal variations are bounded.
Testing times: regularities in the historical sciences.
Jeffares, Ben
2008-12-01
The historical sciences, such as geology, evolutionary biology, and archaeology, appear to have no means to test hypotheses. However, on closer examination, reasoning in the historical sciences relies upon regularities, regularities that can be tested. I outline the role of regularities in the historical sciences, and in the process, blur the distinction between the historical sciences and the experimental sciences: all sciences deploy theories about the world in their investigations.
Regularity effect in prospective memory during aging
Blondelle, Geoffrey; Hainselin, Mathieu; Gounden, Yannick; Heurley, Laurent; Voisin, Hélène; Megalakaki, Olga; Bressous, Estelle; Quaglino, Véronique
2016-01-01
Background Regularity effect can affect performance in prospective memory (PM), but little is known on the cognitive processes linked to this effect. Moreover, its impacts with regard to aging remain unknown. To our knowledge, this study is the first to examine regularity effect in PM in a lifespan perspective, with a sample of young, intermediate, and older adults. Objective and design Our study examined the regularity effect in PM in three groups of participants: 28 young adults (18–30), 16 intermediate adults (40–55), and 25 older adults (65–80). The task, adapted from the Virtual Week, was designed to manipulate the regularity of the various activities of daily life that were to be recalled (regular repeated activities vs. irregular non-repeated activities). We examine the role of several cognitive functions including certain dimensions of executive functions (planning, inhibition, shifting, and binding), short-term memory, and retrospective episodic memory to identify those involved in PM, according to regularity and age. Results A mixed-design ANOVA showed a main effect of task regularity and an interaction between age and regularity: an age-related difference in PM performances was found for irregular activities (older < young), but not for regular activities. All participants recalled more regular activities than irregular ones with no age effect. It appeared that recalling of regular activities only involved planning for both intermediate and older adults, while recalling of irregular ones were linked to planning, inhibition, short-term memory, binding, and retrospective episodic memory. Conclusion Taken together, our data suggest that planning capacities seem to play a major role in remembering to perform intended actions with advancing age. Furthermore, the age-PM-paradox may be attenuated when the experimental design is adapted by implementing a familiar context through the use of activities of daily living. The clinical implications of regularity
Regular Decompositions for H(div) Spaces
Kolev, Tzanio; Vassilevski, Panayot
2012-01-01
We study regular decompositions for H(div) spaces. In particular, we show that such regular decompositions are closely related to a previously studied “inf-sup” condition for parameter-dependent Stokes problems, for which we provide an alternative, more direct, proof.
12 CFR 725.3 - Regular membership.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Regular membership. 725.3 Section 725.3 Banks and Banking NATIONAL CREDIT UNION ADMINISTRATION REGULATIONS AFFECTING CREDIT UNIONS NATIONAL CREDIT UNION ADMINISTRATION CENTRAL LIQUIDITY FACILITY § 725.3 Regular membership. (a) A natural person...
Continuum regularization of quantum field theory
Bern, Z.
1986-04-01
Possible nonperturbative continuum regularization schemes for quantum field theory are discussed which are based upon the Langevin equation of Parisi and Wu. Breit, Gupta and Zaks made the first proposal for new gauge invariant nonperturbative regularization. The scheme is based on smearing in the ''fifth-time'' of the Langevin equation. An analysis of their stochastic regularization scheme for the case of scalar electrodynamics with the standard covariant gauge fixing is given. Their scheme is shown to preserve the masslessness of the photon and the tensor structure of the photon vacuum polarization at the one-loop level. Although stochastic regularization is viable in one-loop electrodynamics, two difficulties arise which, in general, ruins the scheme. One problem is that the superficial quadratic divergences force a bottomless action for the noise. Another difficulty is that stochastic regularization by fifth-time smearing is incompatible with Zwanziger's gauge fixing, which is the only known nonperturbaive covariant gauge fixing for nonabelian gauge theories. Finally, a successful covariant derivative scheme is discussed which avoids the difficulties encountered with the earlier stochastic regularization by fifth-time smearing. For QCD the regularized formulation is manifestly Lorentz invariant, gauge invariant, ghost free and finite to all orders. A vanishing gluon mass is explicitly verified at one loop. The method is designed to respect relevant symmetries, and is expected to provide suitable regularization for any theory of interest. Hopefully, the scheme will lend itself to nonperturbative analysis. 44 refs., 16 figs.
12 CFR 725.3 - Regular membership.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 12 Banks and Banking 6 2011-01-01 2011-01-01 false Regular membership. 725.3 Section 725.3 Banks... UNION ADMINISTRATION CENTRAL LIQUIDITY FACILITY § 725.3 Regular membership. (a) A natural person credit... stock subscription;1 and 1 A credit union which submits its application for membership prior to...
12 CFR 725.3 - Regular membership.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 12 Banks and Banking 7 2014-01-01 2014-01-01 false Regular membership. 725.3 Section 725.3 Banks... UNION ADMINISTRATION CENTRAL LIQUIDITY FACILITY § 725.3 Regular membership. (a) A natural person credit... stock subscription;1 and 1 A credit union which submits its application for membership prior to...
12 CFR 725.3 - Regular membership.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 7 2012-01-01 2012-01-01 false Regular membership. 725.3 Section 725.3 Banks... UNION ADMINISTRATION CENTRAL LIQUIDITY FACILITY § 725.3 Regular membership. (a) A natural person credit... stock subscription;1 and 1 A credit union which submits its application for membership prior to...
12 CFR 725.3 - Regular membership.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 7 2013-01-01 2013-01-01 false Regular membership. 725.3 Section 725.3 Banks... UNION ADMINISTRATION CENTRAL LIQUIDITY FACILITY § 725.3 Regular membership. (a) A natural person credit... stock subscription;1 and 1 A credit union which submits its application for membership prior to...
Numerical Regularization of Ill-Posed Problems.
1980-07-09
Unione Matematica Italiana. 4. The parameter choice problem in linear regularization: a mathematical introduction, in "Ill-Posed Problems: Theory and...vector b which is generally unavailable (see [21], [22]). Kdckler [33] has shon however that in the case of Tikhonov regularization for matrices it may
Transport Code for Regular Triangular Geometry
1993-06-09
DIAMANT2 solves the two-dimensional static multigroup neutron transport equation in planar regular triangular geometry. Both regular and adjoint, inhomogeneous and homogeneous problems subject to vacuum, reflective or input specified boundary flux conditions are solved. Anisotropy is allowed for the scattering source. Volume and surface sources are allowed for inhomogeneous problems.
Regularity Re-Revisited: Modality Matters
ERIC Educational Resources Information Center
Tsapkini, Kyrana; Jarema, Gonia; Kehayia, Eva
2004-01-01
The issue of regular-irregular past tense formation was examined in a cross-modal lexical decision task in Modern Greek, a language where the orthographic and phonological overlap between present and past tense stems is the same for both regular and irregular verbs. The experiment described here is a follow-up study of previous visual lexical…
Regularization techniques in realistic Laplacian computation.
Bortel, Radoslav; Sovka, Pavel
2007-11-01
This paper explores regularization options for the ill-posed spline coefficient equations in the realistic Laplacian computation. We investigate the use of the Tikhonov regularization, truncated singular value decomposition, and the so-called lambda-correction with the regularization parameter chosen by the L-curve, generalized cross-validation, quasi-optimality, and the discrepancy principle criteria. The provided range of regularization techniques is much wider than in the previous works. The improvement of the realistic Laplacian is investigated by simulations on the three-shell spherical head model. The conclusion is that the best performance is provided by the combination of the Tikhonov regularization and the generalized cross-validation criterion-a combination that has never been suggested for this task before.
A linear functional strategy for regularized ranking.
Kriukova, Galyna; Panasiuk, Oleksandra; Pereverzyev, Sergei V; Tkachenko, Pavlo
2016-01-01
Regularization schemes are frequently used for performing ranking tasks. This topic has been intensively studied in recent years. However, to be effective a regularization scheme should be equipped with a suitable strategy for choosing a regularization parameter. In the present study we discuss an approach, which is based on the idea of a linear combination of regularized rankers corresponding to different values of the regularization parameter. The coefficients of the linear combination are estimated by means of the so-called linear functional strategy. We provide a theoretical justification of the proposed approach and illustrate them by numerical experiments. Some of them are related with ranking the risk of nocturnal hypoglycemia of diabetes patients.
On regularizations of the Dirac delta distribution
NASA Astrophysics Data System (ADS)
Hosseini, Bamdad; Nigam, Nilima; Stockie, John M.
2016-01-01
In this article we consider regularizations of the Dirac delta distribution with applications to prototypical elliptic and hyperbolic partial differential equations (PDEs). We study the convergence of a sequence of distributions SH to a singular term S as a parameter H (associated with the support size of SH) shrinks to zero. We characterize this convergence in both the weak-* topology of distributions and a weighted Sobolev norm. These notions motivate a framework for constructing regularizations of the delta distribution that includes a large class of existing methods in the literature. This framework allows different regularizations to be compared. The convergence of solutions of PDEs with these regularized source terms is then studied in various topologies such as pointwise convergence on a deleted neighborhood and weighted Sobolev norms. We also examine the lack of symmetry in tensor product regularizations and effects of dissipative error in hyperbolic problems.
Quantitative regularities in floodplain formation
NASA Astrophysics Data System (ADS)
Nevidimova, O.
2009-04-01
Quantitative regularities in floodplain formation Modern methods of the theory of complex systems allow to build mathematical models of complex systems where self-organizing processes are largely determined by nonlinear effects and feedback. However, there exist some factors that exert significant influence on the dynamics of geomorphosystems, but hardly can be adequately expressed in the language of mathematical models. Conceptual modeling allows us to overcome this difficulty. It is based on the methods of synergetic, which, together with the theory of dynamic systems and classical geomorphology, enable to display the dynamics of geomorphological systems. The most adequate for mathematical modeling of complex systems is the concept of model dynamics based on equilibrium. This concept is based on dynamic equilibrium, the tendency to which is observed in the evolution of all geomorphosystems. As an objective law, it is revealed in the evolution of fluvial relief in general, and in river channel processes in particular, demonstrating the ability of these systems to self-organization. Channel process is expressed in the formation of river reaches, rifts, meanders and floodplain. As floodplain is a periodically flooded surface during high waters, it naturally connects river channel with slopes, being one of boundary expressions of the water stream activity. Floodplain dynamics is inseparable from the channel dynamics. It is formed at simultaneous horizontal and vertical displacement of the river channel, that is at Y=Y(x, y), where х, y - horizontal and vertical coordinates, Y - floodplain height. When dу/dt=0 (for not lowering river channel), the river, being displaced in a horizontal plane, leaves behind a low surface, which flooding during high waters (total duration of flooding) changes from the maximum during the initial moment of time t0 to zero in the moment tn. In a similar manner changed is the total amount of accumulated material on the floodplain surface
Functional MRI using regularized parallel imaging acquisition.
Lin, Fa-Hsuan; Huang, Teng-Yi; Chen, Nan-Kuei; Wang, Fu-Nien; Stufflebeam, Steven M; Belliveau, John W; Wald, Lawrence L; Kwong, Kenneth K
2005-08-01
Parallel MRI techniques reconstruct full-FOV images from undersampled k-space data by using the uncorrelated information from RF array coil elements. One disadvantage of parallel MRI is that the image signal-to-noise ratio (SNR) is degraded because of the reduced data samples and the spatially correlated nature of multiple RF receivers. Regularization has been proposed to mitigate the SNR loss originating due to the latter reason. Since it is necessary to utilize static prior to regularization, the dynamic contrast-to-noise ratio (CNR) in parallel MRI will be affected. In this paper we investigate the CNR of regularized sensitivity encoding (SENSE) acquisitions. We propose to implement regularized parallel MRI acquisitions in functional MRI (fMRI) experiments by incorporating the prior from combined segmented echo-planar imaging (EPI) acquisition into SENSE reconstructions. We investigated the impact of regularization on the CNR by performing parametric simulations at various BOLD contrasts, acceleration rates, and sizes of the active brain areas. As quantified by receiver operating characteristic (ROC) analysis, the simulations suggest that the detection power of SENSE fMRI can be improved by regularized reconstructions, compared to unregularized reconstructions. Human motor and visual fMRI data acquired at different field strengths and array coils also demonstrate that regularized SENSE improves the detection of functionally active brain regions.
Functional MRI Using Regularized Parallel Imaging Acquisition
Lin, Fa-Hsuan; Huang, Teng-Yi; Chen, Nan-Kuei; Wang, Fu-Nien; Stufflebeam, Steven M.; Belliveau, John W.; Wald, Lawrence L.; Kwong, Kenneth K.
2013-01-01
Parallel MRI techniques reconstruct full-FOV images from undersampled k-space data by using the uncorrelated information from RF array coil elements. One disadvantage of parallel MRI is that the image signal-to-noise ratio (SNR) is degraded because of the reduced data samples and the spatially correlated nature of multiple RF receivers. Regularization has been proposed to mitigate the SNR loss originating due to the latter reason. Since it is necessary to utilize static prior to regularization, the dynamic contrast-to-noise ratio (CNR) in parallel MRI will be affected. In this paper we investigate the CNR of regularized sensitivity encoding (SENSE) acquisitions. We propose to implement regularized parallel MRI acquisitions in functional MRI (fMRI) experiments by incorporating the prior from combined segmented echo-planar imaging (EPI) acquisition into SENSE reconstructions. We investigated the impact of regularization on the CNR by performing parametric simulations at various BOLD contrasts, acceleration rates, and sizes of the active brain areas. As quantified by receiver operating characteristic (ROC) analysis, the simulations suggest that the detection power of SENSE fMRI can be improved by regularized reconstructions, compared to unregularized reconstructions. Human motor and visual fMRI data acquired at different field strengths and array coils also demonstrate that regularized SENSE improves the detection of functionally active brain regions. PMID:16032694
Regularity detection by haptics and vision.
Cecchetto, Stefano; Lawson, Rebecca
2017-01-01
For vision, mirror-reflectional symmetry is usually easier to detect when it occurs within 1 object than when it occurs across 2 objects. The opposite pattern has been found for a different regularity, repetition. We investigated whether these results generalize to our sense of active touch (haptics). This was done to examine whether the interaction observed in vision results from intrinsic properties of the environment, or whether it is a consequence of how that environment is perceived and explored. In 4 regularity detection experiments, we haptically presented novel, planar shapes and then visually presented images of the same shapes. In addition to modality (haptics, vision), we varied regularity-type (symmetry, repetition), objectness (1, 2) and alignment of the axis of regularity with respect to the body midline (aligned, across). For both modalities, performance was better overall for symmetry than repetition. For vision, we replicated the previously reported regularity-type by objectness interaction for both stereoscopic and pictorial presentation, and for slanted and frontoparallel views. In contrast, for haptics, there was a 1-object advantage for repetition, as well as for symmetry when stimuli were explored with 1 hand, and no effect of objectness was found for 2-handed exploration. These results suggest that regularity is perceived differently in vision and in haptics, such that regularity detection does not just reflect modality-invariant, physical properties of our environment. (PsycINFO Database Record
The hypergraph regularity method and its applications
Rödl, V.; Nagle, B.; Skokan, J.; Schacht, M.; Kohayakawa, Y.
2005-01-01
Szemerédi's regularity lemma asserts that every graph can be decomposed into relatively few random-like subgraphs. This random-like behavior enables one to find and enumerate subgraphs of a given isomorphism type, yielding the so-called counting lemma for graphs. The combined application of these two lemmas is known as the regularity method for graphs and has proved useful in graph theory, combinatorial geometry, combinatorial number theory, and theoretical computer science. Here, we report on recent advances in the regularity method for k-uniform hypergraphs, for arbitrary k ≥ 2. This method, purely combinatorial in nature, gives alternative proofs of density theorems originally due to E. Szemerédi, H. Furstenberg, and Y. Katznelson. Further results in extremal combinatorics also have been obtained with this approach. The two main components of the regularity method for k-uniform hypergraphs, the regularity lemma and the counting lemma, have been obtained recently: Rödl and Skokan (based on earlier work of Frankl and Rödl) generalized Szemerédi's regularity lemma to k-uniform hypergraphs, and Nagle, Rödl, and Schacht succeeded in proving a counting lemma accompanying the Rödl–Skokan hypergraph regularity lemma. The counting lemma is proved by reducing the counting problem to a simpler one previously investigated by Kohayakawa, Rödl, and Skokan. Similar results were obtained independently by W. T. Gowers, following a different approach. PMID:15919821
Multiple graph regularized protein domain ranking
2012-01-01
Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. PMID:23157331
Completeness and regularity of generalized fuzzy graphs.
Samanta, Sovan; Sarkar, Biswajit; Shin, Dongmin; Pal, Madhumangal
2016-01-01
Fuzzy graphs are the backbone of many real systems like networks, image, scheduling, etc. But, due to some restriction on edges, fuzzy graphs are limited to represent for some systems. Generalized fuzzy graphs are appropriate to avoid such restrictions. In this study generalized fuzzy graphs are introduced. In this study, matrix representation of generalized fuzzy graphs is described. Completeness and regularity are two important parameters of graph theory. Here, regular and complete generalized fuzzy graphs are introduced. Some properties of them are discussed. After that, effective regular graphs are exemplified.
Partitioning of regular computation on multiprocessor systems
NASA Technical Reports Server (NTRS)
Lee, Fung Fung
1988-01-01
Problem partitioning of regular computation over two dimensional meshes on multiprocessor systems is examined. The regular computation model considered involves repetitive evaluation of values at each mesh point with local communication. The computational workload and the communication pattern are the same at each mesh point. The regular computation model arises in numerical solutions of partial differential equations and simulations of cellular automata. Given a communication pattern, a systematic way to generate a family of partitions is presented. The influence of various partitioning schemes on performance is compared on the basis of computation to communication ratio.
Partitioning of regular computation on multiprocessor systems
NASA Technical Reports Server (NTRS)
Lee, Fung F.
1990-01-01
Problem partitioning of regular computation over two dimensional meshes on multiprocessor systems is examined. The regular computation model considered involves repetitive evaluation of values at each mesh point with local communication. The computational workload and the communication pattern are the same at each mesh point. The regular computation model arises in numerical solutions of partial differential equations and simulations of cellular automata. Given a communication pattern, a systematic way to generate a family of partitions is presented. The influence of various partitioning schemes on performance is compared on the basis of computation to communication ratio.
Regular subalgebras of affine Kac Moody algebras
NASA Astrophysics Data System (ADS)
Felikson, Anna; Retakh, Alexander; Tumarkin, Pavel
2008-09-01
We classify regular subalgebras of Kac-Moody algebras in terms of their root systems. In the process, we establish that a root system of a subalgebra is always an intersection of the root system of the algebra with a sublattice of its root lattice. We also discuss applications to investigations of regular subalgebras of hyperbolic Kac-Moody algebras and conformally invariant subalgebras of affine Kac-Moody algebras. In particular, we provide explicit formulae for determining all Virasoro charges in coset constructions that involve regular subalgebras.
Partitioning of regular computation on multiprocessor systems
Lee, F. . Computer Systems Lab.)
1990-07-01
Problem partitioning of regular computation over two-dimensional meshes on multiprocessor systems is examined. The regular computation model considered involves repetitive evaluation of values at each mesh point with local communication. The computational workload and the communication pattern are the same at each mesh point. The regular computation model arises in numerical solutions of partial differential equations and simulations of cellular automata. Given a communication pattern, a systematic way to generate a family of partitions is presented. The influence of various partitioning schemes on performance is compared on the basis of computation to communication ratio.
Continuum regularization of gauge theory with fermions
Chan, H.S.
1987-03-01
The continuum regularization program is discussed in the case of d-dimensional gauge theory coupled to fermions in an arbitrary representation. Two physically equivalent formulations are given. First, a Grassmann formulation is presented, which is based on the two-noise Langevin equations of Sakita, Ishikawa and Alfaro and Gavela. Second, a non-Grassmann formulation is obtained by regularized integration of the matter fields within the regularized Grassmann system. Explicit perturbation expansions are studied in both formulations, and considerable simplification is found in the integrated non-Grassmann formalism.
Regularization of B-Spline Objects.
Xu, Guoliang; Bajaj, Chandrajit
2011-01-01
By a d-dimensional B-spline object (denoted as ), we mean a B-spline curve (d = 1), a B-spline surface (d = 2) or a B-spline volume (d = 3). By regularization of a B-spline object we mean the process of relocating the control points of such that they approximate an isometric map of its definition domain in certain directions and is shape preserving. In this paper we develop an efficient regularization method for , d = 1, 2, 3 based on solving weak form L(2)-gradient flows constructed from the minimization of certain regularizing energy functionals. These flows are integrated via the finite element method using B-spline basis functions. Our experimental results demonstrate that our new regularization method is very effective.
Regular Sleep Makes for Happier College Students
... https://medlineplus.gov/news/fullstory_166856.html Regular Sleep Makes for Happier College Students When erratic snoozers ... studying and socializing, college students often have crazy sleep schedules, and new research suggests that a lack ...
[Serum ferritin in donors with regular plateletpheresis].
Ma, Chun-Hui; Guo, Ru-Hua; Wu, Wei-Jian; Yan, Jun-Xiong; Yu, Jin-Lin; Zhu, Ye-Hua; He, Qi-Tong; Luo, Yi-Hong; Huang, Lu; Ye, Rui-Yun
2011-04-01
This study was aimed to evaluate the impact of regular donating platelets on serum ferritin (SF) of donors. A total of 93 male blood donors including 24 initial plateletpheresis donors and 69 regular plateletpheresis donors were selected randomly. Their SF level was measured by ELISA. The results showed that the SF level of initial plateletpheresis donors and regular plateletpheresis donors were 91.08 ± 23.38 µg/L and 57.16 ± 35.48 µg/L respectively, and all were in normal levels, but there was significant difference between the 2 groups (p < 0.05). The SF level decreased when the donation frequency increased, there were no significant differences between the groups with different donation frequency. Correlation with lifetime donations of platelets was not found. It is concluded that regular plateletpheresis donors may have lower SF level.
Epigenetic adaptation to regular exercise in humans.
Ling, Charlotte; Rönn, Tina
2014-07-01
Regular exercise has numerous health benefits, for example, it reduces the risk of cardiovascular disease and cancer. It has also been shown that the risk of type 2 diabetes can be halved in high-risk groups through nonpharmacological lifestyle interventions involving exercise and diet. Nevertheless, the number of people living a sedentary life is dramatically increasing worldwide. Researchers have searched for molecular mechanisms explaining the health benefits of regular exercise for decades and it is well established that exercise alters the gene expression pattern in multiple tissues. However, until recently it was unknown that regular exercise can modify the genome-wide DNA methylation pattern in humans. This review will focus on recent progress in the field of regular exercise and epigenetics.
The Volume of the Regular Octahedron
ERIC Educational Resources Information Center
Trigg, Charles W.
1974-01-01
Five methods are given for computing the area of a regular octahedron. It is suggested that students first construct an octahedron as this will aid in space visualization. Six further extensions are left for the reader to try. (LS)
On a class of coedge regular graphs
NASA Astrophysics Data System (ADS)
Makhnev, A. A.; Paduchikh, D. V.
2005-12-01
We study graphs in which \\lambda(a,b)=\\lambda_1,\\lambda_2 for every edge \\{a,b\\} and all \\mu-subgraphs are 2-cocliques. We give a description of connected edge-regular graphs for k\\ge (b_1^2+3b_1-4)/2. In particular, the following examples confirm that the inequality k>b_1(b_1+3)/2 is a sharp bound for strong regularity: the n-gon, the icosahedron graph, the graph in \\mathrm{MP}(6) and the distance-regular graph of diameter 4 with intersection massive \\{x,x-1,4,1;1,2,x-1,x\\}, which is an antipodal 3-covering of the strongly regular graph with parameters ((x+2)(x+3)/6,x,0,6).
Wavelet Characterizations of Multi-Directional Regularity
NASA Astrophysics Data System (ADS)
Slimane, Mourad Ben
2011-05-01
The study of d dimensional traces of functions of m several variables leads to directional behaviors. The purpose of this paper is two-fold. Firstly, we extend the notion of one direction pointwise Hölder regularity introduced by Jaffard to multi-directions. Secondly, we characterize multi-directional pointwise regularity by Triebel anisotropic wavelet coefficients (resp. leaders), and also by Calderón anisotropic continuous wavelet transform.
Probabilistic regularization in inverse optical imaging.
De Micheli, E; Viano, G A
2000-11-01
The problem of object restoration in the case of spatially incoherent illumination is considered. A regularized solution to the inverse problem is obtained through a probabilistic approach, and a numerical algorithm based on the statistical analysis of the noisy data is presented. Particular emphasis is placed on the question of the positivity constraint, which is incorporated into the probabilistically regularized solution by means of a quadratic programming technique. Numerical examples illustrating the main steps of the algorithm are also given.
Usual Source of Care in Preventive Service Use: A Regular Doctor versus a Regular Site
Xu, K Tom
2002-01-01
Objective To compare the effects of having a regular doctor and having a regular site on five preventive services, controlling for the endogeneity of having a usual source of care. Data Source The Medical Expenditure Panel Survey 1996 conducted by the Agency for Healthcare Research and Quality and the National Center for Health Statistics. Study Design Mammograms, pap smears, blood pressure checkups, cholesterol level checkups, and flu shots were examined. A modified behavioral model framework was presented, which controlled for the endogeneity of having a usual source of care. Based on this framework, a two-equation empirical model was established to predict the probabilities of having a regular doctor and having a regular site, and use of each type of preventive service. Principal Findings Having a regular doctor was found to have a greater impact than having a regular site on discretional preventive services, such as blood pressure and cholesterol level checkups. No statistically significant differences were found between the effects a having a regular doctor and having a regular site on the use of flu shots, pap smears, and mammograms. Among the five preventive services, having a usual source of care had the greatest impact on cholesterol level checkups and pap smears. Conclusions Promoting a stable physician–patient relationship can improve patients’ timely receipt of clinical prevention. For certain preventive services, having a regular doctor is more effective than having a regular site. PMID:12546284
Assessment of regularization techniques for electrocardiographic imaging
Milanič, Matija; Jazbinšek, Vojko; MacLeod, Robert S.; Brooks, Dana H.; Hren, Rok
2014-01-01
A widely used approach to solving the inverse problem in electrocardiography involves computing potentials on the epicardium from measured electrocardiograms (ECGs) on the torso surface. The main challenge of solving this electrocardiographic imaging (ECGI) problem lies in its intrinsic ill-posedness. While many regularization techniques have been developed to control wild oscillations of the solution, the choice of proper regularization methods for obtaining clinically acceptable solutions is still a subject of ongoing research. However there has been little rigorous comparison across methods proposed by different groups. This study systematically compared various regularization techniques for solving the ECGI problem under a unified simulation framework, consisting of both 1) progressively more complex idealized source models (from single dipole to triplet of dipoles), and 2) an electrolytic human torso tank containing a live canine heart, with the cardiac source being modeled by potentials measured on a cylindrical cage placed around the heart. We tested 13 different regularization techniques to solve the inverse problem of recovering epicardial potentials, and found that non-quadratic methods (total variation algorithms) and first-order and second-order Tikhonov regularizations outperformed other methodologies and resulted in similar average reconstruction errors. PMID:24369741
Modified sparse regularization for electrical impedance tomography
Fan, Wenru Xue, Qian; Wang, Huaxiang; Cui, Ziqiang; Sun, Benyuan; Wang, Qi
2016-03-15
Electrical impedance tomography (EIT) aims to estimate the electrical properties at the interior of an object from current-voltage measurements on its boundary. It has been widely investigated due to its advantages of low cost, non-radiation, non-invasiveness, and high speed. Image reconstruction of EIT is a nonlinear and ill-posed inverse problem. Therefore, regularization techniques like Tikhonov regularization are used to solve the inverse problem. A sparse regularization based on L{sub 1} norm exhibits superiority in preserving boundary information at sharp changes or discontinuous areas in the image. However, the limitation of sparse regularization lies in the time consumption for solving the problem. In order to further improve the calculation speed of sparse regularization, a modified method based on separable approximation algorithm is proposed by using adaptive step-size and preconditioning technique. Both simulation and experimental results show the effectiveness of the proposed method in improving the image quality and real-time performance in the presence of different noise intensities and conductivity contrasts.
Regularity re-revisited: modality matters.
Tsapkini, Kyrana; Jarema, Gonia; Kehayia, Eva
2004-06-01
The issue of regular-irregular past tense formation was examined in a cross-modal lexical decision task in Modern Greek, a language where the orthographic and phonological overlap between present and past tense stems is the same for both regular and irregular verbs. The experiment described here is a follow-up study of previous visual lexical decision experiments (Tsapkini, Kehayia, & Harema, 2002) that also addressed the regular-irregular distinction in Greek. In the present experiment, we investigated the effect of input modality in lexical processing and compared different types of regular and irregular verbs. In contrast to our previous intra-modal (visual-visual) priming experiments, in this cross-modal (auditory-visual) priming study, we found that regular verbs with an orthographically salient morphemic aspectual marker elicited the same facilitation as those without an orthographically salient marker. However, irregular verbs did not exhibit a different priming pattern with respect to modality. We interpret these results in the framework of a two-level lexical processing approach with modality-specific access representations at a surface level and modality-independent morphemic representations at a deeper level.
Shadow of rotating regular black holes
NASA Astrophysics Data System (ADS)
Abdujabbarov, Ahmadjon; Amir, Muhammed; Ahmedov, Bobomurat; Ghosh, Sushant G.
2016-05-01
We study the shadows cast by the different types of rotating regular black holes viz. Ayón-Beato-García (ABG), Hayward, and Bardeen. These black holes have in addition to the total mass (M ) and rotation parameter (a ), different parameters as electric charge (Q ), deviation parameter (g ), and magnetic charge (g*). Interestingly, the size of the shadow is affected by these parameters in addition to the rotation parameter. We found that the radius of the shadow in each case decreases monotonically, and the distortion parameter increases when the values of these parameters increase. A comparison with the standard Kerr case is also investigated. We have also studied the influence of the plasma environment around regular black holes to discuss its shadow. The presence of the plasma affects the apparent size of the regular black hole's shadow to be increased due to two effects: (i) gravitational redshift of the photons and (ii) radial dependence of plasma density.
Strong regularizing effect of integrable systems
Zhou, Xin
1997-11-01
Many time evolution problems have the so-called strong regularization effect, that is, with any irregular initial data, as soon as becomes greater than 0, the solution becomes C{sup {infinity}} for both spacial and temporal variables. This paper studies 1 x 1 dimension integrable systems for such regularizing effect. In the work by Sachs, Kappler [S][K], (see also earlier works [KFJ] and [Ka]), strong regularizing effect is proved for KdV with rapidly decaying irregular initial data, using the inverse scattering method. There are two equivalent Gel`fand-Levitan-Marchenko (GLM) equations associated to an inverse scattering problem, one is normalized at x = {infinity} and another at x = {infinity}. The method of [S][K] relies on the fact that the KdV waves propagate only in one direction and therefore one of the two GLM equations remains normalized and can be differentiated infinitely many times. 15 refs.
Surface counterterms and regularized holographic complexity
NASA Astrophysics Data System (ADS)
Yang, Run-Qiu; Niu, Chao; Kim, Keun-Young
2017-09-01
The holographic complexity is UV divergent. As a finite complexity, we propose a "regularized complexity" by employing a similar method to the holographic renor-malization. We add codimension-two boundary counterterms which do not contain any boundary stress tensor information. It means that we subtract only non-dynamic back-ground and all the dynamic information of holographic complexity is contained in the regularized part. After showing the general counterterms for both CA and CV conjectures in holographic spacetime dimension 5 and less, we give concrete examples: the BTZ black holes and the four and five dimensional Schwarzschild AdS black holes. We propose how to obtain the counterterms in higher spacetime dimensions and show explicit formulas only for some special cases with enough symmetries. We also compute the complexity of formation by using the regularized complexity.
Perturbations in a regular bouncing universe
Battefeld, T.J.; Geshnizjani, G.
2006-03-15
We consider a simple toy model of a regular bouncing universe. The bounce is caused by an extra timelike dimension, which leads to a sign flip of the {rho}{sup 2} term in the effective four dimensional Randall Sundrum-like description. We find a wide class of possible bounces: big bang avoiding ones for regular matter content, and big rip avoiding ones for phantom matter. Focusing on radiation as the matter content, we discuss the evolution of scalar, vector and tensor perturbations. We compute a spectral index of n{sub s}=-1 for scalar perturbations and a deep blue index for tensor perturbations after invoking vacuum initial conditions, ruling out such a model as a realistic one. We also find that the spectrum (evaluated at Hubble crossing) is sensitive to the bounce. We conclude that it is challenging, but not impossible, for cyclic/ekpyrotic models to succeed, if one can find a regularized version.
Nonlinear electrodynamics and regular black holes
NASA Astrophysics Data System (ADS)
Sajadi, S. N.; Riazi, N.
2017-03-01
In this work, an exact regular black hole solution in General Relativity is presented. The source is a nonlinear electromagnetic field with the algebraic structure T00=T11 for the energy-momentum tensor, partially satisfying the weak energy condition but not the strong energy condition. In the weak field limit, the EM field behaves like the Maxwell field. The solution corresponds to a charged black hole with q≤0.77 m. The metric, the curvature invariants, and the electric field are regular everywhere. The BH is stable against small perturbations of spacetime and using the Weinhold metric, geometrothermodynamical stability has been investigated. Finally we investigate the idea that the observable universe lives inside a regular black hole. We argue that this picture might provide a viable description of universe.
Numerical Comparison of Two-Body Regularizations
NASA Astrophysics Data System (ADS)
Fukushima, Toshio
2007-06-01
We numerically compare four schemes to regularize a three-dimensional two-body problem under perturbations: the Sperling-Bürdet (S-B), Kustaanheimo-Stiefel (K-S), and Bürdet-Ferrandiz (B-F) regularizations, and a three-dimensional extension of the Levi-Civita (L-C) regularization we developed recently. As for the integration time of the equation of motion, the least time is needed for the unregularized treatment, followed by the K-S, the extended L-C, the B-F, and the S-B regularizations. However, these differences become significantly smaller when the time to evaluate perturbations becomes dominant. As for the integration error after one close encounter, the K-S and the extended L-C regularizations are tied for the least error, followed by the S-B, the B-F, and finally the unregularized scheme for unperturbed orbits with eccentricity less than 2. This order is not changed significantly by various kinds of perturbations. As for the integration error of elliptical orbits after multiple orbital periods, the situation remains the same except for the rank of the S-B scheme, which varies from the best to the second worst depending on the length of integration and/or on the nature of perturbations. Also, we confirm that Kepler energy scaling enhances the performance of the unregularized, K-S, and extended L-C schemes. As a result, the K-S and the extended L-C regularizations with Kepler energy scaling provide the best cost performance in integrating almost all the perturbed two-body problems.
Regular transport dynamics produce chaotic travel times
NASA Astrophysics Data System (ADS)
Villalobos, Jorge; Muñoz, Víctor; Rogan, José; Zarama, Roberto; Johnson, Neil F.; Toledo, Benjamín; Valdivia, Juan Alejandro
2014-06-01
In the hope of making passenger travel times shorter and more reliable, many cities are introducing dedicated bus lanes (e.g., Bogota, London, Miami). Here we show that chaotic travel times are actually a natural consequence of individual bus function, and hence of public transport systems more generally, i.e., chaotic dynamics emerge even when the route is empty and straight, stops and lights are equidistant and regular, and loading times are negligible. More generally, our findings provide a novel example of chaotic dynamics emerging from a single object following Newton's laws of motion in a regularized one-dimensional system.
Regular transport dynamics produce chaotic travel times.
Villalobos, Jorge; Muñoz, Víctor; Rogan, José; Zarama, Roberto; Johnson, Neil F; Toledo, Benjamín; Valdivia, Juan Alejandro
2014-06-01
In the hope of making passenger travel times shorter and more reliable, many cities are introducing dedicated bus lanes (e.g., Bogota, London, Miami). Here we show that chaotic travel times are actually a natural consequence of individual bus function, and hence of public transport systems more generally, i.e., chaotic dynamics emerge even when the route is empty and straight, stops and lights are equidistant and regular, and loading times are negligible. More generally, our findings provide a novel example of chaotic dynamics emerging from a single object following Newton's laws of motion in a regularized one-dimensional system.
Demosaicing as the problem of regularization
NASA Astrophysics Data System (ADS)
Kunina, Irina; Volkov, Aleksey; Gladilin, Sergey; Nikolaev, Dmitry
2015-12-01
Demosaicing is the process of reconstruction of a full-color image from Bayer mosaic, which is used in digital cameras for image formation. This problem is usually considered as an interpolation problem. In this paper, we propose to consider the demosaicing problem as a problem of solving an underdetermined system of algebraic equations using regularization methods. We consider regularization with standard l1/2-, l1 -, l2- norms and their effect on quality image reconstruction. The experimental results showed that the proposed technique can both be used in existing methods and become the base for new ones
Recollections on Dimensional Regularization and Related Topics
NASA Astrophysics Data System (ADS)
Bollini, Carlos Guido
Professor Juan José Giambiagi and I started working on divergent diagrams in different number of dimensions in 1970. We had a certain idea about the behavior in odd or even number of dimensions, but the most important factor in our work, I think, was the previous experience with an analytical regularization method. We had developed it a few years before. Within this method the amplitudes turned out to be analytic functions of the regularizing parameter, with poles at the physical value of that parameter…
Existence of constants in regular splicing languages.
Bonizzoni, Paola; Jonoska, Nataša
2015-06-01
In spite of wide investigations of finite splicing systems in formal language theory, basic questions, such as their characterization, remain unsolved. It has been conjectured that a necessary condition for a regular language L to be a splicing language is that L must have a constant in the Schutzenberger sense. We prove this longstanding conjecture to be true. The result is based on properties of strongly connected components of the minimal deterministic finite state automaton for a regular splicing language. Using constants of the corresponding languages, we also provide properties of transitive automata and pathautomata.
Existence of constants in regular splicing languages
Jonoska, Nataša
2015-01-01
In spite of wide investigations of finite splicing systems in formal language theory, basic questions, such as their characterization, remain unsolved. It has been conjectured that a necessary condition for a regular language L to be a splicing language is that L must have a constant in the Schutzenberger sense. We prove this longstanding conjecture to be true. The result is based on properties of strongly connected components of the minimal deterministic finite state automaton for a regular splicing language. Using constants of the corresponding languages, we also provide properties of transitive automata and pathautomata. PMID:27185985
Generalised hyperbolicity in spacetimes with Lipschitz regularity
NASA Astrophysics Data System (ADS)
Sanchez Sanchez, Yafet; Vickers, James A.
2017-02-01
In this paper we obtain general conditions under which the wave equation is well-posed in spacetimes with metrics of Lipschitz regularity. In particular, the results can be applied to spacetimes where there is a loss of regularity on a hypersurface such as shell-crossing singularities, thin shells of matter, and surface layers. This provides a framework for regarding gravitational singularities not as obstructions to the world lines of point-particles, but rather as obstruction to the dynamics of test fields.
Regular homotopy for immersions of graphs into surfaces
NASA Astrophysics Data System (ADS)
Permyakov, D. A.
2016-06-01
We study invariants of regular immersions of graphs into surfaces up to regular homotopy. The concept of the winding number is used to introduce a new simple combinatorial invariant of regular homotopy. Bibliography: 20 titles.
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2010-09-21
... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF LABOR Employment and Training Administration Humana Insurance Company, a Division Of Carenetwork, Inc., Green Bay..., Inc., Green Bay, Wisconsin was based on the findings that the subject firm did not, during the...
A Quantitative Measure of Memory Reference Regularity
Mohan, T; de Supinski, B R; McKee, S A; Mueller, F; Yoo, A
2001-10-01
The memory performance of applications on existing architectures depends significantly on hardware features like prefetching and caching that exploit the locality of the memory accesses. The principle of locality has guided the design of many key micro-architectural features, including cache hierarchies, TLBs, and branch predictors. Quantitative measures of spatial and temporal locality have been useful for predicting the performance of memory hierarchy components. Unfortunately, the concept of locality is constrained to capturing memory access patterns characterized by proximity, while sophisticated memory systems are capable of exploiting other predictable access patterns. Here, we define the concepts of spatial and temporal regularity, and introduce a measure of spatial access regularity to quantify some of this predictability in access patterns. We present an efficient online algorithm to dynamically determine the spatial access regularity in an application's memory references, and demonstrate its use on a set of regular and irregular codes. We find that the use of our algorithm, with its associated overhead of trace generation, slows typical applications by a factor of 50-200, which is at least an order of magnitude better than traditional full trace generation approaches. Our approach can be applied to the characterization of program access patterns and in the implementation of sophisticated, software-assisted prefetching mechanisms, and its inherently parallel nature makes it well suited for use with multi-threaded programs.
Strategies of Teachers in the Regular Classroom
ERIC Educational Resources Information Center
De Leeuw, Renske Ria; De Boer, Anke Aaltje
2016-01-01
It is known that regular schoolteachers have difficulties in educating students with social, emotional and behavioral difficulties (SEBD), mainly because of their disruptive behavior. In order to manage the disruptive behavior of students with SEBD many advices and strategies are provided in educational literature. However, very little is known…
Regular Gleason Measures and Generalized Effect Algebras
NASA Astrophysics Data System (ADS)
Dvurečenskij, Anatolij; Janda, Jiří
2015-12-01
We study measures, finitely additive measures, regular measures, and σ-additive measures that can attain even infinite values on the quantum logic of a Hilbert space. We show when particular classes of non-negative measures can be studied in the frame of generalized effect algebras.
Regular Polygons with Rational Area or Perimeter.
ERIC Educational Resources Information Center
Killgrove, R. B.; Koster, D. W.
1991-01-01
Discussed are two approaches to determining which regular polygons, either inscribed within or circumscribed about the unit circle, exhibit rational area or rational perimeter. One approach involves applications of abstract theory from a typical modern algebra course, whereas the other approach employs material from a traditional…
Regularization of turbulence - a comprehensive modeling approach
NASA Astrophysics Data System (ADS)
Geurts, B. J.
2011-12-01
Turbulence readily arises in numerous flows in nature and technology. The large number of degrees of freedom of turbulence poses serious challenges to numerical approaches aimed at simulating and controlling such flows. While the Navier-Stokes equations are commonly accepted to precisely describe fluid turbulence, alternative coarsened descriptions need to be developed to cope with the wide range of length and time scales. These coarsened descriptions are known as large-eddy simulations in which one aims to capture only the primary features of a flow, at considerably reduced computational effort. Such coarsening introduces a closure problem that requires additional phenomenological modeling. A systematic approach to the closure problem, know as regularization modeling, will be reviewed. Its application to multiphase turbulent will be illustrated in which a basic regularization principle is enforced to physically consistently approximate momentum and scalar transport. Examples of Leray and LANS-alpha regularization are discussed in some detail, as are compatible numerical strategies. We illustrate regularization modeling to turbulence under the influence of rotation and buoyancy and investigate the accuracy with which particle-laden flow can be represented. A discussion of the numerical and modeling errors incurred will be given on the basis of homogeneous isotropic turbulence.
Starting flow in regular polygonal ducts
NASA Astrophysics Data System (ADS)
Wang, C. Y.
2016-06-01
The starting flows in regular polygonal ducts of S = 3, 4, 5, 6, 8 sides are determined by the method of eigenfunction superposition. The necessary S-fold symmetric eigenfunctions and eigenvalues of the Helmholtz equation are found either exactly or by boundary point match. The results show the starting time is governed by the first eigenvalue.
Regularity Aspects in Inverse Musculoskeletal Biomechanics
NASA Astrophysics Data System (ADS)
Lund, Marie; Stâhl, Fredrik; Gulliksson, Mârten
2008-09-01
Inverse simulations of musculoskeletal models computes the internal forces such as muscle and joint reaction forces, which are hard to measure, using the more easily measured motion and external forces as input data. Because of the difficulties of measuring muscle forces and joint reactions, simulations are hard to validate. One way of reducing errors for the simulations is to ensure that the mathematical problem is well-posed. This paper presents a study of regularity aspects for an inverse simulation method, often called forward dynamics or dynamical optimization, that takes into account both measurement errors and muscle dynamics. Regularity is examined for a test problem around the optimum using the approximated quadratic problem. The results shows improved rank by including a regularization term in the objective that handles the mechanical over-determinancy. Using the 3-element Hill muscle model the chosen regularization term is the norm of the activation. To make the problem full-rank only the excitation bounds should be included in the constraints. However, this results in small negative values of the activation which indicates that muscles are pushing and not pulling, which is unrealistic but the error maybe small enough to be accepted for specific applications. These results are a start to ensure better results of inverse musculoskeletal simulations from a numerical point of view.
On the regularity in some variational problems
NASA Astrophysics Data System (ADS)
Ragusa, Maria Alessandra; Tachikawa, Atsushi
2017-01-01
Our main goal is the study some regularity results where are considered estimates in Morrey spaces for the derivatives of local minimizers of variational integrals of the form 𝒜 (u ,Ω )= ∫Ω F (x ,u ,D u ) dx where Ω is a bounded domain in ℝm and the integrand F have some different forms.
Effective Special Education in Regular Classes.
ERIC Educational Resources Information Center
Wang, Margaret C.; Birch, Jack W.
1984-01-01
A study of 156 K-3 classrooms revealed that the Adaptive Learning Enviornments Model, an educational approach that accommodates, in regular classes, a wider-than-usual range of individual differences, can be implemented effectively in a variety of settings, and that favorable student outcome measures coincide with high degrees of program…
Fast Image Reconstruction with L2-Regularization
Bilgic, Berkin; Chatnuntawech, Itthi; Fan, Audrey P.; Setsompop, Kawin; Cauley, Stephen F.; Wald, Lawrence L.; Adalsteinsson, Elfar
2014-01-01
Purpose We introduce L2-regularized reconstruction algorithms with closed-form solutions that achieve dramatic computational speed-up relative to state of the art L1- and L2-based iterative algorithms while maintaining similar image quality for various applications in MRI reconstruction. Materials and Methods We compare fast L2-based methods to state of the art algorithms employing iterative L1- and L2-regularization in numerical phantom and in vivo data in three applications; 1) Fast Quantitative Susceptibility Mapping (QSD), 2) Lipid artifact suppression in Magnetic Resonance Spectroscopic Imaging (MRSI), and 3) Diffusion Spectrum Imaging (DSI). In all cases, proposed L2-based methods are compared with the state of the art algorithms, and two to three orders of magnitude speed up is demonstrated with similar reconstruction quality. Results The closed-form solution developed for regularized QSM allows processing of a 3D volume under 5 seconds, the proposed lipid suppression algorithm takes under 1 second to reconstruct single-slice MRSI data, while the PCA based DSI algorithm estimates diffusion propagators from undersampled q-space for a single slice under 30 seconds, all running in Matlab using a standard workstation. Conclusion For the applications considered herein, closed-form L2-regularization can be a faster alternative to its iterative counterpart or L1-based iterative algorithms, without compromising image quality. PMID:24395184
Semantic Gender Assignment Regularities in German
ERIC Educational Resources Information Center
Schwichtenberg, Beate; Schiller, Niels O.
2004-01-01
Gender assignment relates to a native speaker's knowledge of the structure of the gender system of his/her language, allowing the speaker to select the appropriate gender for each noun. Whereas categorical assignment rules and exceptional gender assignment are well investigated, assignment regularities, i.e., tendencies in the gender distribution…
Regularizing cosmological singularities by varying physical constants
Dąbrowski, Mariusz P.; Marosek, Konrad E-mail: k.marosek@wmf.univ.szczecin.pl
2013-02-01
Varying physical constant cosmologies were claimed to solve standard cosmological problems such as the horizon, the flatness and the Λ-problem. In this paper, we suggest yet another possible application of these theories: solving the singularity problem. By specifying some examples we show that various cosmological singularities may be regularized provided the physical constants evolve in time in an appropriate way.
Dyslexia in Regular Orthographies: Manifestation and Causation
ERIC Educational Resources Information Center
Wimmer, Heinz; Schurz, Matthias
2010-01-01
This article summarizes our research on the manifestation of dyslexia in German and on cognitive deficits, which may account for the severe reading speed deficit and the poor orthographic spelling performance that characterize dyslexia in regular orthographies. An only limited causal role of phonological deficits (phonological awareness,…
A Sim(2) invariant dimensional regularization
NASA Astrophysics Data System (ADS)
Alfaro, J.
2017-09-01
We introduce a Sim (2) invariant dimensional regularization of loop integrals. Then we can compute the one loop quantum corrections to the photon self energy, electron self energy and vertex in the Electrodynamics sector of the Very Special Relativity Standard Model (VSRSM).
Generalisation of Regular and Irregular Morphological Patterns.
ERIC Educational Resources Information Center
Prasada, Sandeep; and Pinker, Steven
1993-01-01
When it comes to explaining English verbs' patterns of regular and irregular generalization, single-network theories have difficulty with the former, rule-only theories with the latter process. Linguistic and psycholinguistic evidence, based on observation during experiments and simulations in morphological pattern generation, independently call…
Regular Nonchaotic Attractors with Positive Plural
NASA Astrophysics Data System (ADS)
Zhang, Xu
2016-12-01
The study of the strange nonchaotic attractors is an interesting topic, where the dynamics are neither regular nor chaotic (the word chaotic means the positive Lyapunov exponents), and the shape of the attractors has complicated geometry structure, or fractal structure. It is found that in a class of planar first-order nonautonomous systems, it is possible that there exist attractors, where the shape of the attractors is regular, the orbits are transitive on the attractors, and the dynamics are not chaotic. We call this type of attractors as regular nonchaotic attractors with positive plural, which are different from the strange nonchaotic attractors, attracting fixed points, or attracting periodic orbits. Several examples with computer simulations are given. The first two examples have annulus-shaped attractors. Another two examples have disk-shaped attractors. The last two examples with externally driven terms at two incommensurate frequencies have regular nonchaotic attractors with positive plural, implying that the existence of externally driven terms at two incommensurate frequencies might not be the sufficient condition to guarantee that the system has strange nonchaotic attractors.
Exploring the structural regularities in networks.
Shen, Hua-Wei; Cheng, Xue-Qi; Guo, Jia-Feng
2011-11-01
In this paper, we consider the problem of exploring structural regularities of networks by dividing the nodes of a network into groups such that the members of each group have similar patterns of connections to other groups. Specifically, we propose a general statistical model to describe network structure. In this model, a group is viewed as a hidden or unobserved quantity and it is learned by fitting the observed network data using the expectation-maximization algorithm. Compared with existing models, the most prominent strength of our model is the high flexibility. This strength enables it to possess the advantages of existing models and to overcome their shortcomings in a unified way. As a result, not only can broad types of structure be detected without prior knowledge of the type of intrinsic regularities existing in the target network, but also the type of identified structure can be directly learned from the network. Moreover, by differentiating outgoing edges from incoming edges, our model can detect several types of structural regularities beyond competing models. Tests on a number of real world and artificial networks demonstrate that our model outperforms the state-of-the-art model in shedding light on the structural regularities of networks, including the overlapping community structure, multipartite structure, and several other types of structure, which are beyond the capability of existing models.
Prox-regular functions in Hilbert spaces
NASA Astrophysics Data System (ADS)
Bernard, Frédéric; Thibault, Lionel
2005-03-01
This paper studies the prox-regularity concept for functions in the general context of Hilbert space. In particular, a subdifferential characterization is established as well as several other properties. It is also shown that the Moreau envelopes of such functions are continuously differentiable.
Regularities in Spearman's Law of Diminishing Returns.
ERIC Educational Resources Information Center
Jensen, Arthur R.
2003-01-01
Examined the assumption that Spearman's law acts unsystematically and approximately uniformly for various subtests of cognitive ability in an IQ test battery when high- and low-ability IQ groups are selected. Data from national standardization samples for Wechsler adult and child IQ tests affirm regularities in Spearman's "Law of Diminishing…
Regularities in Spearman's Law of Diminishing Returns.
ERIC Educational Resources Information Center
Jensen, Arthur R.
2003-01-01
Examined the assumption that Spearman's law acts unsystematically and approximately uniformly for various subtests of cognitive ability in an IQ test battery when high- and low-ability IQ groups are selected. Data from national standardization samples for Wechsler adult and child IQ tests affirm regularities in Spearman's "Law of Diminishing…
TAUBERIAN THEOREMS FOR MATRIX REGULAR VARIATION
MEERSCHAERT, M. M.; SCHEFFLER, H.-P.
2013-01-01
Karamata’s Tauberian theorem relates the asymptotics of a nondecreasing right-continuous function to that of its Laplace-Stieltjes transform, using regular variation. This paper establishes the analogous Tauberian theorem for matrix-valued functions. Some applications to time series analysis are indicated. PMID:24644367
Strategies of Teachers in the Regular Classroom
ERIC Educational Resources Information Center
De Leeuw, Renske Ria; De Boer, Anke Aaltje
2016-01-01
It is known that regular schoolteachers have difficulties in educating students with social, emotional and behavioral difficulties (SEBD), mainly because of their disruptive behavior. In order to manage the disruptive behavior of students with SEBD many advices and strategies are provided in educational literature. However, very little is known…
Regularity of rotational travelling water waves.
Escher, Joachim
2012-04-13
Several recent results on the regularity of streamlines beneath a rotational travelling wave, along with the wave profile itself, will be discussed. The survey includes the classical water wave problem in both finite and infinite depth, capillary waves and solitary waves as well. A common assumption in all models to be discussed is the absence of stagnation points.
NASA Astrophysics Data System (ADS)
Save, H.; Bettadpur, S. V.
2013-12-01
It has been demonstrated before that using Tikhonov regularization produces spherical harmonic solutions from GRACE that have very little residual stripes while capturing all the signal observed by GRACE within the noise level. This paper demonstrates a two-step process and uses Tikhonov regularization to remove the residual stripes in the CSR regularized spherical harmonic coefficients when computing the spatial projections. We discuss methods to produce mass anomaly grids that have no stripe features while satisfying the necessary condition of capturing all observed signal within the GRACE noise level.
42 CFR 61.3 - Purpose of regular fellowships.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 42 Public Health 1 2013-10-01 2013-10-01 false Purpose of regular fellowships. 61.3 Section 61.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES FELLOWSHIPS, INTERNSHIPS, TRAINING FELLOWSHIPS Regular Fellowships § 61.3 Purpose of regular fellowships. Regular fellowships...
42 CFR 61.3 - Purpose of regular fellowships.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 42 Public Health 1 2014-10-01 2014-10-01 false Purpose of regular fellowships. 61.3 Section 61.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES FELLOWSHIPS, INTERNSHIPS, TRAINING FELLOWSHIPS Regular Fellowships § 61.3 Purpose of regular fellowships. Regular fellowships...
42 CFR 61.3 - Purpose of regular fellowships.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 42 Public Health 1 2011-10-01 2011-10-01 false Purpose of regular fellowships. 61.3 Section 61.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES FELLOWSHIPS, INTERNSHIPS, TRAINING FELLOWSHIPS Regular Fellowships § 61.3 Purpose of regular fellowships. Regular fellowships...
42 CFR 61.3 - Purpose of regular fellowships.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 42 Public Health 1 2012-10-01 2012-10-01 false Purpose of regular fellowships. 61.3 Section 61.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES FELLOWSHIPS, INTERNSHIPS, TRAINING FELLOWSHIPS Regular Fellowships § 61.3 Purpose of regular fellowships. Regular fellowships...
Chaos regularization of quantum tunneling rates.
Pecora, Louis M; Lee, Hoshik; Wu, Dong-Ho; Antonsen, Thomas; Lee, Ming-Jer; Ott, Edward
2011-06-01
Quantum tunneling rates through a barrier separating two-dimensional, symmetric, double-well potentials are shown to depend on the classical dynamics of the billiard trajectories in each well and, hence, on the shape of the wells. For shapes that lead to regular (integrable) classical dynamics the tunneling rates fluctuate greatly with eigenenergies of the states sometimes by over two orders of magnitude. Contrarily, shapes that lead to completely chaotic trajectories lead to tunneling rates whose fluctuations are greatly reduced, a phenomenon we call regularization of tunneling rates. We show that a random-plane-wave theory of tunneling accounts for the mean tunneling rates and the small fluctuation variances for the chaotic systems.
Tracking magnetogram proper motions by multiscale regularization
NASA Technical Reports Server (NTRS)
Jones, Harrison P.
1995-01-01
Long uninterrupted sequences of solar magnetograms from the global oscillations network group (GONG) network and from the solar and heliospheric observatory (SOHO) satellite will provide the opportunity to study the proper motions of magnetic features. The possible use of multiscale regularization, a scale-recursive estimation technique which begins with a prior model of how state variables and their statistical properties propagate over scale. Short magnetogram sequences are analyzed with the multiscale regularization algorithm as applied to optical flow. This algorithm is found to be efficient, provides results for all the spatial scales spanned by the data and provides error estimates for the solutions. It is found that the algorithm is less sensitive to evolutionary changes than correlation tracking.
Variational regularized 2-D nonnegative matrix factorization.
Gao, Bin; Woo, W L; Dlay, S S
2012-05-01
A novel approach for adaptive regularization of 2-D nonnegative matrix factorization is presented. The proposed matrix factorization is developed under the framework of maximum a posteriori probability and is adaptively fine-tuned using the variational approach. The method enables: (1) a generalized criterion for variable sparseness to be imposed onto the solution; and (2) prior information to be explicitly incorporated into the basis features. The method is computationally efficient and has been demonstrated on two applications, that is, extracting features from image and separating single channel source mixture. In addition, it is shown that the basis features of an information-bearing matrix can be extracted more efficiently using the proposed regularized priors. Experimental tests have been rigorously conducted to verify the efficacy of the proposed method.
Convex nonnegative matrix factorization with manifold regularization.
Hu, Wenjun; Choi, Kup-Sze; Wang, Peiliang; Jiang, Yunliang; Wang, Shitong
2015-03-01
Nonnegative Matrix Factorization (NMF) has been extensively applied in many areas, including computer vision, pattern recognition, text mining, and signal processing. However, nonnegative entries are usually required for the data matrix in NMF, which limits its application. Besides, while the basis and encoding vectors obtained by NMF can represent the original data in low dimension, the representations do not always reflect the intrinsic geometric structure embedded in the data. Motivated by manifold learning and Convex NMF (CNMF), we propose a novel matrix factorization method called Graph Regularized and Convex Nonnegative Matrix Factorization (GCNMF) by introducing a graph regularized term into CNMF. The proposed matrix factorization technique not only inherits the intrinsic low-dimensional manifold structure, but also allows the processing of mixed-sign data matrix. Clustering experiments on nonnegative and mixed-sign real-world data sets are conducted to demonstrate the effectiveness of the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.
Regularity of nuclear structure under random interactions
Zhao, Y. M.
2011-05-06
In this contribution I present a brief introduction to simplicity out of complexity in nuclear structure, specifically, the regularity of nuclear structure under random interactions. I exemplify such simplicity by two examples: spin-zero ground state dominance and positive parity ground state dominance in even-even nuclei. Then I discuss two recent results of nuclear structure in the presence of random interactions, in collaboration with Prof. Arima. Firstly I discuss sd bosons under random interactions, with the focus on excited states in the yrast band. We find a few regular patterns in these excited levels. Secondly I discuss our recent efforts towards obtaining eigenvalues without diagonalizing the full matrices of the nuclear shell model Hamiltonian.
Effort variation regularization in sound field reproduction.
Stefanakis, Nick; Jacobsen, Finn; Sarris, John
2010-08-01
In this paper, active control is used in order to reproduce a given sound field in an extended spatial region. A method is proposed which minimizes the reproduction error at a number of control positions with the reproduction sources holding a certain relation within their complex strengths. Specifically, it is suggested that the phase differential of the source driving signals should be in agreement with the phase differential of the desired sound pressure field. The performance of the suggested method is compared with that of conventional effort regularization, wave field synthesis (WFS), and adaptive wave field synthesis (AWFS), both under free-field conditions and in reverberant rooms. It is shown that effort variation regularization overcomes the problems associated with small spaces and with a low ratio of direct to reverberant energy, improving thus the reproduction accuracy in the listening room.
Modeling Regular Replacement for String Constraint Solving
NASA Technical Reports Server (NTRS)
Fu, Xiang; Li, Chung-Chih
2010-01-01
Bugs in user input sanitation of software systems often lead to vulnerabilities. Among them many are caused by improper use of regular replacement. This paper presents a precise modeling of various semantics of regular substitution, such as the declarative, finite, greedy, and reluctant, using finite state transducers (FST). By projecting an FST to its input/output tapes, we are able to solve atomic string constraints, which can be applied to both the forward and backward image computation in model checking and symbolic execution of text processing programs. We report several interesting discoveries, e.g., certain fragments of the general problem can be handled using less expressive deterministic FST. A compact representation of FST is implemented in SUSHI, a string constraint solver. It is applied to detecting vulnerabilities in web applications
Symmetries and regular behavior of Hamiltonian systems.
Kozlov, Valeriy V.
1996-03-01
The behavior of the phase trajectories of the Hamilton equations is commonly classified as regular and chaotic. Regularity is usually related to the condition for complete integrability, i.e., a Hamiltonian system with n degrees of freedom has n independent integrals in involution. If at the same time the simultaneous integral manifolds are compact, the solutions of the Hamilton equations are quasiperiodic. In particular, the entropy of the Hamiltonian phase flow of a completely integrable system is zero. It is found that there is a broader class of Hamiltonian systems that do not show signs of chaotic behavior. These are systems that allow n commuting "Lagrangian" vector fields, i.e., the symplectic 2-form on each pair of such fields is zero. They include, in particular, Hamiltonian systems with multivalued integrals. (c) 1996 American Institute of Physics.
Power-law regularities in human language
NASA Astrophysics Data System (ADS)
Mehri, Ali; Lashkari, Sahar Mohammadpour
2016-11-01
Complex structure of human language enables us to exchange very complicated information. This communication system obeys some common nonlinear statistical regularities. We investigate four important long-range features of human language. We perform our calculations for adopted works of seven famous litterateurs. Zipf's law and Heaps' law, which imply well-known power-law behaviors, are established in human language, showing a qualitative inverse relation with each other. Furthermore, the informational content associated with the words ordering, is measured by using an entropic metric. We also calculate fractal dimension of words in the text by using box counting method. The fractal dimension of each word, that is a positive value less than or equal to one, exhibits its spatial distribution in the text. Generally, we can claim that the Human language follows the mentioned power-law regularities. Power-law relations imply the existence of long-range correlations between the word types, to convey an especial idea.
Charged fermions tunneling from regular black holes
Sharif, M. Javed, W.
2012-11-15
We study Hawking radiation of charged fermions as a tunneling process from charged regular black holes, i.e., the Bardeen and ABGB black holes. For this purpose, we apply the semiclassical WKB approximation to the general covariant Dirac equation for charged particles and evaluate the tunneling probabilities. We recover the Hawking temperature corresponding to these charged regular black holes. Further, we consider the back-reaction effects of the emitted spin particles from black holes and calculate their corresponding quantum corrections to the radiation spectrum. We find that this radiation spectrum is not purely thermal due to the energy and charge conservation but has some corrections. In the absence of charge, e = 0, our results are consistent with those already present in the literature.
Regular black holes with flux tube core
Zaslavskii, Oleg B.
2009-09-15
We consider a class of black holes for which the area of the two-dimensional spatial cross section has a minimum on the horizon with respect to a quasiglobal (Krusckal-like) coordinate. If the horizon is regular, one can generate a tubelike counterpart of such a metric and smoothly glue it to a black hole region. The resulting composite space-time is globally regular, so all potential singularities under the horizon of the original metrics are removed. Such a space-time represents a black hole without an apparent horizon. It is essential that the matter should be nonvacuum in the outer region but vacuumlike in the inner one. As an example we consider the noninteracting mixture of vacuum fluid and matter with a linear equation of state and scalar phantom fields. This approach is extended to distorted metrics, with the requirement of spherical symmetry relaxed.
Regular Magnetic Black Hole Gravitational Lensing
NASA Astrophysics Data System (ADS)
Liang, Jun
2017-05-01
The Bronnikov regular magnetic black hole as a gravitational lens is studied. In nonlinear electrodynamics, photons do not follow null geodesics of background geometry, but move along null geodesics of a corresponding effective geometry. To study the Bronnikov regular magnetic black hole gravitational lensing in the strong deflection limit, the corresponding effective geometry should be obtained firstly. This is the most important and key step. We obtain the deflection angle in the strong deflection limit, and further calculate the angular positions and magnifications of relativistic images as well as the time delay between different relativistic images. The influence of the magnetic charge on the black hole gravitational lensing is also discussed. Supported by the Natural Science Foundation of Education Department of Shannxi Province under Grant No 15JK1077, and the Doctorial Scientific Research Starting Fund of Shannxi University of Science and Technology under Grant No BJ12-02.
Superfast Tikhonov Regularization of Toeplitz Systems
NASA Astrophysics Data System (ADS)
Turnes, Christopher K.; Balcan, Doru; Romberg, Justin
2014-08-01
Toeplitz-structured linear systems arise often in practical engineering problems. Correspondingly, a number of algorithms have been developed that exploit Toeplitz structure to gain computational efficiency when solving these systems. The earliest "fast" algorithms for Toeplitz systems required O(n^2) operations, while more recent "superfast" algorithms reduce the cost to O(n (log n)^2) or below. In this work, we present a superfast algorithm for Tikhonov regularization of Toeplitz systems. Using an "extension-and-transformation" technique, our algorithm translates a Tikhonov-regularized Toeplitz system into a type of specialized polynomial problem known as tangential interpolation. Under this formulation, we can compute the solution in only O(n (log n)^2) operations. We use numerical simulations to demonstrate our algorithm's complexity and verify that it returns stable solutions.
3D Gravity Inversion using Tikhonov Regularization
NASA Astrophysics Data System (ADS)
Toushmalani, Reza; Saibi, Hakim
2015-08-01
Subsalt exploration for oil and gas is attractive in regions where 3D seismic depth-migration to recover the geometry of a salt base is difficult. Additional information to reduce the ambiguity in seismic images would be beneficial. Gravity data often serve these purposes in the petroleum industry. In this paper, the authors present an algorithm for a gravity inversion based on Tikhonov regularization and an automatically regularized solution process. They examined the 3D Euler deconvolution to extract the best anomaly source depth as a priori information to invert the gravity data and provided a synthetic example. Finally, they applied the gravity inversion to recently obtained gravity data from the Bandar Charak (Hormozgan, Iran) to identify its subsurface density structure. Their model showed the 3D shape of salt dome in this region.
Speech enhancement using local spectral regularization
NASA Astrophysics Data System (ADS)
Sandoval-Ibarra, Yuma; Diaz-Ramirez, Victor H.; Kober, Vitaly; Diaz, Arnoldo
2016-09-01
A locally-adaptive algorithm for speech enhancement based on local spectral regularization is presented. The algorithm is able to retrieve a clean speech signal from a noisy signal using locally-adaptive signal processing. The proposed algorithm is able to increase the quality of a noisy signal in terms of objective metrics. Computer simulation results obtained with the proposed algorithm are presented and discussed in processing speech signals corrupted with additive noise.
A regularization approach to hydrofacies delineation
Wohlberg, Brendt; Tartakovsky, Daniel
2009-01-01
We consider an inverse problem of identifying complex internal structures of composite (geological) materials from sparse measurements of system parameters and system states. Two conceptual frameworks for identifying internal boundaries between constitutive materials in a composite are considered. A sequential approach relies on support vector machines, nearest neighbor classifiers, or geostatistics to reconstruct boundaries from measurements of system parameters and then uses system states data to refine the reconstruction. A joint approach inverts the two data sets simultaneously by employing a regularization approach.
Spectra of sparse regular graphs with loops.
Metz, F L; Neri, I; Bollé, D
2011-11-01
We derive exact equations that determine the spectra of undirected and directed sparsely connected regular graphs containing loops of arbitrary lengths. The implications of our results for the structural and dynamical properties of network models are discussed by showing how loops influence the size of the spectral gap and the propensity for synchronization. Analytical formulas for the spectrum are obtained for specific lengths of the loops.
Bouncing cosmology inspired by regular black holes
NASA Astrophysics Data System (ADS)
Neves, J. C. S.
2017-09-01
In this article, we present a bouncing cosmology inspired by a family of regular black holes. This scale-dependent cosmology deviates from the cosmological principle by means of a scale factor which depends on the time and the radial coordinate as well. The model is isotropic but not perfectly homogeneous. That is, this cosmology describes a universe almost homogeneous only for large scales, such as our observable universe.
Sparse regularization for force identification using dictionaries
NASA Astrophysics Data System (ADS)
Qiao, Baijie; Zhang, Xingwu; Wang, Chenxi; Zhang, Hang; Chen, Xuefeng
2016-04-01
The classical function expansion method based on minimizing l2-norm of the response residual employs various basis functions to represent the unknown force. Its difficulty lies in determining the optimum number of basis functions. Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions. The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process. First, according to the profile of the unknown force, the dictionary composed of basis functions is determined. Second, a sparsity convex optimization model for force identification is constructed. Third, given the transfer function and the operational response, Sparse reconstruction by separable approximation (SpaRSA) is developed to solve the sparse regularization problem of force identification. Finally, experiments including identification of impact and harmonic forces are conducted on a cantilever thin plate structure to illustrate the effectiveness and applicability of SpaRSA. Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame. The discrete cosine functions can also successfully reconstruct the harmonic forces including the sinusoidal, square and triangular forces. Conversely, the traditional Tikhonov regularization method with the L-curve criterion fails to identify both the impact and harmonic forces in these cases.
Optical tomography by means of regularized MLEM
NASA Astrophysics Data System (ADS)
Majer, Charles L.; Urbanek, Tina; Peter, Jörg
2015-09-01
To solve the inverse problem involved in fluorescence mediated tomography a regularized maximum likelihood expectation maximization (MLEM) reconstruction strategy is proposed. This technique has recently been applied to reconstruct galaxy clusters in astronomy and is adopted here. The MLEM algorithm is implemented as Richardson-Lucy (RL) scheme and includes entropic regularization and a floating default prior. Hence, the strategy is very robust against measurement noise and also avoids converging into noise patterns. Normalized Gaussian filtering with fixed standard deviation is applied for the floating default kernel. The reconstruction strategy is investigated using the XFM-2 homogeneous mouse phantom (Caliper LifeSciences Inc., Hopkinton, MA) with known optical properties. Prior to optical imaging, X-ray CT tomographic data of the phantom were acquire to provide structural context. Phantom inclusions were fit with various fluorochrome inclusions (Cy5.5) for which optical data at 60 projections over 360 degree have been acquired, respectively. Fluorochrome excitation has been accomplished by scanning laser point illumination in transmission mode (laser opposite to camera). Following data acquisition, a 3D triangulated mesh is derived from the reconstructed CT data which is then matched with the various optical projection images through 2D linear interpolation, correlation and Fourier transformation in order to assess translational and rotational deviations between the optical and CT imaging systems. Preliminary results indicate that the proposed regularized MLEM algorithm, when driven with a constant initial condition, yields reconstructed images that tend to be smoother in comparison to classical MLEM without regularization. Once the floating default prior is included this bias was significantly reduced.
Regularization Parameter Selections via Generalized Information Criterion
Zhang, Yiyun; Li, Runze; Tsai, Chih-Ling
2009-01-01
We apply the nonconcave penalized likelihood approach to obtain variable selections as well as shrinkage estimators. This approach relies heavily on the choice of regularization parameter, which controls the model complexity. In this paper, we propose employing the generalized information criterion (GIC), encompassing the commonly used Akaike information criterion (AIC) and Bayesian information criterion (BIC), for selecting the regularization parameter. Our proposal makes a connection between the classical variable selection criteria and the regularization parameter selections for the nonconcave penalized likelihood approaches. We show that the BIC-type selector enables identification of the true model consistently, and the resulting estimator possesses the oracle property in the terminology of Fan and Li (2001). In contrast, however, the AIC-type selector tends to overfit with positive probability. We further show that the AIC-type selector is asymptotically loss efficient, while the BIC-type selector is not. Our simulation results confirm these theoretical findings, and an empirical example is presented. Some technical proofs are given in the online supplementary material. PMID:20676354
Regularity and chaos in cavity QED
NASA Astrophysics Data System (ADS)
Bastarrachea-Magnani, Miguel Angel; López-del-Carpio, Baldemar; Chávez-Carlos, Jorge; Lerma-Hernández, Sergio; Hirsch, Jorge G.
2017-05-01
The interaction of a quantized electromagnetic field in a cavity with a set of two-level atoms inside it can be described with algebraic Hamiltonians of increasing complexity, from the Rabi to the Dicke models. Their algebraic character allows, through the use of coherent states, a semiclassical description in phase space, where the non-integrable Dicke model has regions associated with regular and chaotic motion. The appearance of classical chaos can be quantified calculating the largest Lyapunov exponent over the whole available phase space for a given energy. In the quantum regime, employing efficient diagonalization techniques, we are able to perform a detailed quantitative study of the regular and chaotic regions, where the quantum participation ratio (P R ) of coherent states on the eigenenergy basis plays a role equivalent to the Lyapunov exponent. It is noted that, in the thermodynamic limit, dividing the participation ratio by the number of atoms leads to a positive value in chaotic regions, while it tends to zero in the regular ones.
Guaranteed classification via regularized similarity learning.
Guo, Zheng-Chu; Ying, Yiming
2014-03-01
Learning an appropriate (dis)similarity function from the available data is a central problem in machine learning, since the success of many machine learning algorithms critically depends on the choice of a similarity function to compare examples. Despite many approaches to similarity metric learning that have been proposed, there has been little theoretical study on the links between similarity metric learning and the classification performance of the resulting classifier. In this letter, we propose a regularized similarity learning formulation associated with general matrix norms and establish their generalization bounds. We show that the generalization error of the resulting linear classifier can be bounded by the derived generalization bound of similarity learning. This shows that a good generalization of the learned similarity function guarantees a good classification of the resulting linear classifier. Our results extend and improve those obtained by Bellet, Habrard, and Sebban (2012). Due to the techniques dependent on the notion of uniform stability (Bousquet & Elisseeff, 2002), the bound obtained there holds true only for the Frobenius matrix-norm regularization. Our techniques using the Rademacher complexity (Bartlett & Mendelson, 2002) and its related Khinchin-type inequality enable us to establish bounds for regularized similarity learning formulations associated with general matrix norms, including sparse L1-norm and mixed (2,1)-norm.
Automatic detection of regularly repeating vocalizations
NASA Astrophysics Data System (ADS)
Mellinger, David
2005-09-01
Many animal species produce repetitive sounds at regular intervals. This regularity can be used for automatic recognition of the sounds, providing improved detection at a given signal-to-noise ratio. Here, the detection of sperm whale sounds is examined. Sperm whales produce highly repetitive ``regular clicks'' at periods of about 0.2-2 s, and faster click trains in certain behavioral contexts. The following detection procedure was tested: a spectrogram was computed; values within a certain frequency band were summed; time windowing was applied; each windowed segment was autocorrelated; and the maximum of the autocorrelation within a certain periodicity range was chosen. This procedure was tested on sets of recordings containing sperm whale sounds and interfering sounds, both low-frequency recordings from autonomous hydrophones and high-frequency ones from towed hydrophone arrays. An optimization procedure iteratively varies detection parameters (spectrogram frame length and frequency range, window length, periodicity range, etc.). Performance of various sets of parameters was measured by setting a standard level of allowable missed calls, and the resulting optimium parameters are described. Performance is also compared to that of a neural network trained using the data sets. The method is also demonstrated for sounds of blue whales, minke whales, and seismic airguns. [Funding from ONR.
Regular Language Constrained Sequence Alignment Revisited
NASA Astrophysics Data System (ADS)
Kucherov, Gregory; Pinhas, Tamar; Ziv-Ukelson, Michal
Imposing constraints in the form of a finite automaton or a regular expression is an effective way to incorporate additional a priori knowledge into sequence alignment procedures. With this motivation, Arslan [1] introduced the Regular Language Constrained Sequence Alignment Problem and proposed an O(n 2 t 4) time and O(n 2 t 2) space algorithm for solving it, where n is the length of the input strings and t is the number of states in the non-deterministic automaton, which is given as input. Chung et al. [2] proposed a faster O(n 2 t 3) time algorithm for the same problem. In this paper, we further speed up the algorithms for Regular Language Constrained Sequence Alignment by reducing their worst case time complexity bound to O(n 2 t 3/logt). This is done by establishing an optimal bound on the size of Straight-Line Programs solving the maxima computation subproblem of the basic dynamic programming algorithm. We also study another solution based on a Steiner Tree computation. While it does not improve the run time complexity in the worst case, our simulations show that both approaches are efficient in practice, especially when the input automata are dense.
Regularization Parameter Selections via Generalized Information Criterion.
Zhang, Yiyun; Li, Runze; Tsai, Chih-Ling
2010-03-01
We apply the nonconcave penalized likelihood approach to obtain variable selections as well as shrinkage estimators. This approach relies heavily on the choice of regularization parameter, which controls the model complexity. In this paper, we propose employing the generalized information criterion (GIC), encompassing the commonly used Akaike information criterion (AIC) and Bayesian information criterion (BIC), for selecting the regularization parameter. Our proposal makes a connection between the classical variable selection criteria and the regularization parameter selections for the nonconcave penalized likelihood approaches. We show that the BIC-type selector enables identification of the true model consistently, and the resulting estimator possesses the oracle property in the terminology of Fan and Li (2001). In contrast, however, the AIC-type selector tends to overfit with positive probability. We further show that the AIC-type selector is asymptotically loss efficient, while the BIC-type selector is not. Our simulation results confirm these theoretical findings, and an empirical example is presented. Some technical proofs are given in the online supplementary material.
Discovering Structural Regularity in 3D Geometry
Pauly, Mark; Mitra, Niloy J.; Wallner, Johannes; Pottmann, Helmut; Guibas, Leonidas J.
2010-01-01
We introduce a computational framework for discovering regular or repeated geometric structures in 3D shapes. We describe and classify possible regular structures and present an effective algorithm for detecting such repeated geometric patterns in point- or mesh-based models. Our method assumes no prior knowledge of the geometry or spatial location of the individual elements that define the pattern. Structure discovery is made possible by a careful analysis of pairwise similarity transformations that reveals prominent lattice structures in a suitable model of transformation space. We introduce an optimization method for detecting such uniform grids specifically designed to deal with outliers and missing elements. This yields a robust algorithm that successfully discovers complex regular structures amidst clutter, noise, and missing geometry. The accuracy of the extracted generating transformations is further improved using a novel simultaneous registration method in the spatial domain. We demonstrate the effectiveness of our algorithm on a variety of examples and show applications to compression, model repair, and geometry synthesis. PMID:21170292
NASA Astrophysics Data System (ADS)
Parekh, Ankit
Sparsity has become the basis of some important signal processing methods over the last ten years. Many signal processing problems (e.g., denoising, deconvolution, non-linear component analysis) can be expressed as inverse problems. Sparsity is invoked through the formulation of an inverse problem with suitably designed regularization terms. The regularization terms alone encode sparsity into the problem formulation. Often, the ℓ1 norm is used to induce sparsity, so much so that ℓ1 regularization is considered to be `modern least-squares'. The use of ℓ1 norm, as a sparsity-inducing regularizer, leads to a convex optimization problem, which has several benefits: the absence of extraneous local minima, well developed theory of globally convergent algorithms, even for large-scale problems. Convex regularization via the ℓ1 norm, however, tends to under-estimate the non-zero values of sparse signals. In order to estimate the non-zero values more accurately, non-convex regularization is often favored over convex regularization. However, non-convex regularization generally leads to non-convex optimization, which suffers from numerous issues: convergence may be guaranteed to only a stationary point, problem specific parameters may be difficult to set, and the solution is sensitive to the initialization of the algorithm. The first part of this thesis is aimed toward combining the benefits of non-convex regularization and convex optimization to estimate sparse signals more effectively. To this end, we propose to use parameterized non-convex regularizers with designated non-convexity and provide a range for the non-convex parameter so as to ensure that the objective function is strictly convex. By ensuring convexity of the objective function (sum of data-fidelity and non-convex regularizer), we can make use of a wide variety of convex optimization algorithms to obtain the unique global minimum reliably. The second part of this thesis proposes a non-linear signal
Sparsity regularization for parameter identification problems
NASA Astrophysics Data System (ADS)
Jin, Bangti; Maass, Peter
2012-12-01
The investigation of regularization schemes with sparsity promoting penalty terms has been one of the dominant topics in the field of inverse problems over the last years, and Tikhonov functionals with ℓp-penalty terms for 1 ⩽ p ⩽ 2 have been studied extensively. The first investigations focused on regularization properties of the minimizers of such functionals with linear operators and on iteration schemes for approximating the minimizers. These results were quickly transferred to nonlinear operator equations, including nonsmooth operators and more general function space settings. The latest results on regularization properties additionally assume a sparse representation of the true solution as well as generalized source conditions, which yield some surprising and optimal convergence rates. The regularization theory with ℓp sparsity constraints is relatively complete in this setting; see the first part of this review. In contrast, the development of efficient numerical schemes for approximating minimizers of Tikhonov functionals with sparsity constraints for nonlinear operators is still ongoing. The basic iterated soft shrinkage approach has been extended in several directions and semi-smooth Newton methods are becoming applicable in this field. In particular, the extension to more general non-convex, non-differentiable functionals by variational principles leads to a variety of generalized iteration schemes. We focus on such iteration schemes in the second part of this review. A major part of this survey is devoted to applying sparsity constrained regularization techniques to parameter identification problems for partial differential equations, which we regard as the prototypical setting for nonlinear inverse problems. Parameter identification problems exhibit different levels of complexity and we aim at characterizing a hierarchy of such problems. The operator defining these inverse problems is the parameter-to-state mapping. We first summarize some
Convergence and Fluctuations of Regularized Tyler Estimators
NASA Astrophysics Data System (ADS)
Kammoun, Abla; Couillet, Romain; Pascal, Ferderic; Alouini, Mohamed-Slim
2016-02-01
This article studies the behavior of regularized Tyler estimators (RTEs) of scatter matrices. The key advantages of these estimators are twofold. First, they guarantee by construction a good conditioning of the estimate and second, being a derivative of robust Tyler estimators, they inherit their robustness properties, notably their resilience to the presence of outliers. Nevertheless, one major problem that poses the use of RTEs in practice is represented by the question of setting the regularization parameter $\\rho$. While a high value of $\\rho$ is likely to push all the eigenvalues away from zero, it comes at the cost of a larger bias with respect to the population covariance matrix. A deep understanding of the statistics of RTEs is essential to come up with appropriate choices for the regularization parameter. This is not an easy task and might be out of reach, unless one considers asymptotic regimes wherein the number of observations $n$ and/or their size $N$ increase together. First asymptotic results have recently been obtained under the assumption that $N$ and $n$ are large and commensurable. Interestingly, no results concerning the regime of $n$ going to infinity with $N$ fixed exist, even though the investigation of this assumption has usually predated the analysis of the most difficult $N$ and $n$ large case. This motivates our work. In particular, we prove in the present paper that the RTEs converge to a deterministic matrix when $n\\to\\infty$ with $N$ fixed, which is expressed as a function of the theoretical covariance matrix. We also derive the fluctuations of the RTEs around this deterministic matrix and establish that these fluctuations converge in distribution to a multivariate Gaussian distribution with zero mean and a covariance depending on the population covariance and the parameter $\\rho$.
Regular physical exercise: way to healthy life.
Siddiqui, N I; Nessa, A; Hossain, M A
2010-01-01
Any bodily activity or movement that enhances and maintains overall health and physical fitness is called physical exercise. Habit of regular physical exercise has got numerous benefits. Exercise is of various types such as aerobic exercise, anaerobic exercise and flexibility exercise. Aerobic exercise moves the large muscle groups with alternate contraction and relaxation, forces to deep breath, heart to pump more blood with adequate tissue oxygenation. It is also called cardiovascular exercise. Examples of aerobic exercise are walking, running, jogging, swimming etc. In anaerobic exercise, there is forceful contraction of muscle with stretching, usually mechanically aided and help to build up muscle strength and muscle bulk. Examples are weight lifting, pulling, pushing, sprinting etc. Flexibility exercise is one type of stretching exercise to improve the movements of muscles, joints and ligaments. Walking is a good example of aerobic exercise, easy to perform, safe, effective, does not require any training or equipment and less chance of injury. Regular 30 minutes brisk walking in the morning with 150 minutes per week is a good exercise. Regular exercise improves the cardiovascular status, reduces the risk of cardiac disease, high blood pressure and cerebrovascular disease. It reduces body weight, improves insulin sensitivity, helps in glycemic control, prevents obesity and diabetes mellitus. It is helpful for relieving anxiety, stress, brings a sense of well being and overall physical fitness. Global trend is mechanization, labor savings and leading to epidemic of long term chronic diseases like diabetes mellitus, cardiovascular diseases etc. All efforts should be made to create public awareness promoting physical activity, physically demanding recreational pursuits and providing adequate facilities.
Regular Expression Analysis of Procedures and Exceptions,
1985-06-01
L D-RI63 817 REGULAR EXPRESSION ANALYSIS OF PROCEDURES AND1/7 EXCEPTIONS(U) ROYAL SIGNALS AND RADAR ESTABLISHNENT NALVERN ( ENGLAND ) J M FOSTER JUN 85...34 means composition in sequence, that is a.b denotes the path formed by a followed by b. The constant 1I. " is a unit for the dot operation, so L.a - a...s.c a b.c right distribution of . over . - l.a-a I is a left unit for. a.1 -a I is a right unit for. . .. *. . . ". .. -.•. S
Regularization ambiguities in loop quantum gravity
NASA Astrophysics Data System (ADS)
Perez, Alejandro
2006-02-01
One of the main achievements of loop quantum gravity is the consistent quantization of the analog of the Wheeler-DeWitt equation which is free of ultraviolet divergences. However, ambiguities associated to the intermediate regularization procedure lead to an apparently infinite set of possible theories. The absence of an UV problem—the existence of well-behaved regularization of the constraints—is intimately linked with the ambiguities arising in the quantum theory. Among these ambiguities is the one associated to the SU(2) unitary representation used in the diffeomorphism covariant “point-splitting” regularization of the nonlinear functionals of the connection. This ambiguity is labeled by a half-integer m and, here, it is referred to as the m ambiguity. The aim of this paper is to investigate the important implications of this ambiguity. We first study 2+1 gravity (and more generally BF theory) quantized in the canonical formulation of loop quantum gravity. Only when the regularization of the quantum constraints is performed in terms of the fundamental representation of the gauge group does one obtain the usual topological quantum field theory as a result. In all other cases unphysical local degrees of freedom arise at the level of the regulated theory that conspire against the existence of the continuum limit. This shows that there is a clear-cut choice in the quantization of the constraints in 2+1 loop quantum gravity. We then analyze the effects of the ambiguity in 3+1 gravity exhibiting the existence of spurious solutions for higher representation quantizations of the Hamiltonian constraint. Although the analysis is not complete in 3+1 dimensions—due to the difficulties associated to the definition of the physical inner product—it provides evidence supporting the definitions quantum dynamics of loop quantum gravity in terms of the fundamental representation of the gauge group as the only consistent possibilities. If the gauge group is SO(3) we
The regular state in higher order gravity
NASA Astrophysics Data System (ADS)
Cotsakis, Spiros; Kadry, Seifedine; Trachilis, Dimitrios
2016-08-01
We consider the higher-order gravity theory derived from the quadratic Lagrangian R + 𝜖R2 in vacuum as a first-order (ADM-type) system with constraints, and build time developments of solutions of an initial value formulation of the theory. We show that all such solutions, if analytic, contain the right number of free functions to qualify as general solutions of the theory. We further show that any regular analytic solution which satisfies the constraints and the evolution equations can be given in the form of an asymptotic formal power series expansion.
Total-variation regularization with bound constraints
Chartrand, Rick; Wohlberg, Brendt
2009-01-01
We present a new algorithm for bound-constrained total-variation (TV) regularization that in comparison with its predecessors is simple, fast, and flexible. We use a splitting approach to decouple TV minimization from enforcing the constraints. Consequently, existing TV solvers can be employed with minimal alteration. This also makes the approach straightforward to generalize to any situation where TV can be applied. We consider deblurring of images with Gaussian or salt-and-pepper noise, as well as Abel inversion of radiographs with Poisson noise. We incorporate previous iterative reweighting algorithms to solve the TV portion.
Multichannel image regularization using anisotropic geodesic filtering
Grazzini, Jacopo A
2010-01-01
This paper extends a recent image-dependent regularization approach introduced in aiming at edge-preserving smoothing. For that purpose, geodesic distances equipped with a Riemannian metric need to be estimated in local neighbourhoods. By deriving an appropriate metric from the gradient structure tensor, the associated geodesic paths are constrained to follow salient features in images. Following, we design a generalized anisotropic geodesic filter; incorporating not only a measure of the edge strength, like in the original method, but also further directional information about the image structures. The proposed filter is particularly efficient at smoothing heterogeneous areas while preserving relevant structures in multichannel images.
Regularization ambiguities in loop quantum gravity
Perez, Alejandro
2006-02-15
One of the main achievements of loop quantum gravity is the consistent quantization of the analog of the Wheeler-DeWitt equation which is free of ultraviolet divergences. However, ambiguities associated to the intermediate regularization procedure lead to an apparently infinite set of possible theories. The absence of an UV problem--the existence of well-behaved regularization of the constraints--is intimately linked with the ambiguities arising in the quantum theory. Among these ambiguities is the one associated to the SU(2) unitary representation used in the diffeomorphism covariant 'point-splitting' regularization of the nonlinear functionals of the connection. This ambiguity is labeled by a half-integer m and, here, it is referred to as the m ambiguity. The aim of this paper is to investigate the important implications of this ambiguity. We first study 2+1 gravity (and more generally BF theory) quantized in the canonical formulation of loop quantum gravity. Only when the regularization of the quantum constraints is performed in terms of the fundamental representation of the gauge group does one obtain the usual topological quantum field theory as a result. In all other cases unphysical local degrees of freedom arise at the level of the regulated theory that conspire against the existence of the continuum limit. This shows that there is a clear-cut choice in the quantization of the constraints in 2+1 loop quantum gravity. We then analyze the effects of the ambiguity in 3+1 gravity exhibiting the existence of spurious solutions for higher representation quantizations of the Hamiltonian constraint. Although the analysis is not complete in 3+1 dimensions - due to the difficulties associated to the definition of the physical inner product - it provides evidence supporting the definitions quantum dynamics of loop quantum gravity in terms of the fundamental representation of the gauge group as the only consistent possibilities. If the gauge group is SO(3) we find
New Regularization Method for EXAFS Analysis
Reich, Tatiana Ye.; Reich, Tobias; Korshunov, Maxim E.; Antonova, Tatiana V.; Ageev, Alexander L.; Moll, Henry
2007-02-02
As an alternative to the analysis of EXAFS spectra by conventional shell fitting, the Tikhonov regularization method has been proposed. An improved algorithm that utilizes a priori information about the sample has been developed and applied to the analysis of U L3-edge spectra of soddyite, (UO2)2SiO4{center_dot}2H2O, and of U(VI) sorbed onto kaolinite. The partial radial distribution functions g1(UU), g2(USi), and g3(UO) of soddyite agree with crystallographic values and previous EXAFS results.
Supporting Regularized Logistic Regression Privately and Efficiently
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738
Tomographic laser absorption spectroscopy using Tikhonov regularization.
Guha, Avishek; Schoegl, Ingmar
2014-12-01
The application of tunable diode laser absorption spectroscopy (TDLAS) to flames with nonhomogeneous temperature and concentration fields is an area where only few studies exist. Experimental work explores the performance of tomographic reconstructions of species concentration and temperature profiles from wavelength-modulated TDLAS measurements within the plume of an axisymmetric McKenna burner. Water vapor transitions at 1391.67 and 1442.67 nm are probed using calibration-free wavelength modulation spectroscopy with second harmonic detection (WMS-2f). A single collimated laser beam is swept parallel to the burner surface, where scans yield pairs of line-of-sight (LOS) data at multiple radial locations. Radial profiles of absorption data are reconstructed using Tikhonov regularized Abel inversion, which suppresses the amplification of experimental noise that is typically observed for reconstructions with high spatial resolution. Based on spectral data reconstructions, temperatures and mole fractions are calculated point-by-point. Here, a least-squares approach addresses difficulties due to modulation depths that cannot be universally optimized due to a nonuniform domain. Experimental results show successful reconstructions of temperature and mole fraction profiles based on two-transition, nonoptimally modulated WMS-2f and Tikhonov regularized Abel inversion, and thus validate the technique as a viable diagnostic tool for flame measurements.
Supporting Regularized Logistic Regression Privately and Efficiently.
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.
Accelerating Large Data Analysis By Exploiting Regularities
NASA Technical Reports Server (NTRS)
Moran, Patrick J.; Ellsworth, David
2003-01-01
We present techniques for discovering and exploiting regularity in large curvilinear data sets. The data can be based on a single mesh or a mesh composed of multiple submeshes (also known as zones). Multi-zone data are typical to Computational Fluid Dynamics (CFD) simulations. Regularities include axis-aligned rectilinear and cylindrical meshes as well as cases where one zone is equivalent to a rigid-body transformation of another. Our algorithms can also discover rigid-body motion of meshes in time-series data. Next, we describe a data model where we can utilize the results from the discovery process in order to accelerate large data visualizations. Where possible, we replace general curvilinear zones with rectilinear or cylindrical zones. In rigid-body motion cases we replace a time-series of meshes with a transformed mesh object where a reference mesh is dynamically transformed based on a given time value in order to satisfy geometry requests, on demand. The data model enables us to make these substitutions and dynamic transformations transparently with respect to the visualization algorithms. We present results with large data sets where we combine our mesh replacement and transformation techniques with out-of-core paging in order to achieve significant speed-ups in analysis.
Motion regularization for matting motion blurred objects.
Lin, Hai Ting; Tai, Yu-Wing; Brown, Michael S
2011-11-01
This paper addresses the problem of matting motion blurred objects from a single image. Existing single image matting methods are designed to extract static objects that have fractional pixel occupancy. This arises because the physical scene object has a finer resolution than the discrete image pixel and therefore only occupies a fraction of the pixel. For a motion blurred object, however, fractional pixel occupancy is attributed to the object’s motion over the exposure period. While conventional matting techniques can be used to matte motion blurred objects, they are not formulated in a manner that considers the object’s motion and tend to work only when the object is on a homogeneous background. We show how to obtain better alpha mattes by introducing a regularization term in the matting formulation to account for the object’s motion. In addition, we outline a method for estimating local object motion based on local gradient statistics from the original image. For the sake of completeness, we also discuss how user markup can be used to denote the local direction in lieu of motion estimation. Improvements to alpha mattes computed with our regularization are demonstrated on a variety of examples.
Nonlinear regularization techniques for seismic tomography
Loris, I. Douma, H.; Nolet, G.; Regone, C.
2010-02-01
The effects of several nonlinear regularization techniques are discussed in the framework of 3D seismic tomography. Traditional, linear, l{sub 2} penalties are compared to so-called sparsity promoting l{sub 1} and l{sub 0} penalties, and a total variation penalty. Which of these algorithms is judged optimal depends on the specific requirements of the scientific experiment. If the correct reproduction of model amplitudes is important, classical damping towards a smooth model using an l{sub 2} norm works almost as well as minimizing the total variation but is much more efficient. If gradients (edges of anomalies) should be resolved with a minimum of distortion, we prefer l{sub 1} damping of Daubechies-4 wavelet coefficients. It has the additional advantage of yielding a noiseless reconstruction, contrary to simple l{sub 2} minimization ('Tikhonov regularization') which should be avoided. In some of our examples, the l{sub 0} method produced notable artifacts. In addition we show how nonlinear l{sub 1} methods for finding sparse models can be competitive in speed with the widely used l{sub 2} methods, certainly under noisy conditions, so that there is no need to shun l{sub 1} penalizations.
Words cluster phonetically beyond phonotactic regularities.
Dautriche, Isabelle; Mahowald, Kyle; Gibson, Edward; Christophe, Anne; Piantadosi, Steven T
2017-06-01
Recent evidence suggests that cognitive pressures associated with language acquisition and use could affect the organization of the lexicon. On one hand, consistent with noisy channel models of language (e.g., Levy, 2008), the phonological distance between wordforms should be maximized to avoid perceptual confusability (a pressure for dispersion). On the other hand, a lexicon with high phonological regularity would be simpler to learn, remember and produce (e.g., Monaghan et al., 2011) (a pressure for clumpiness). Here we investigate wordform similarity in the lexicon, using measures of word distance (e.g., phonological neighborhood density) to ask whether there is evidence for dispersion or clumpiness of wordforms in the lexicon. We develop a novel method to compare lexicons to phonotactically-controlled baselines that provide a null hypothesis for how clumpy or sparse wordforms would be as the result of only phonotactics. Results for four languages, Dutch, English, German and French, show that the space of monomorphemic wordforms is clumpier than what would be expected by the best chance model according to a wide variety of measures: minimal pairs, average Levenshtein distance and several network properties. This suggests a fundamental drive for regularity in the lexicon that conflicts with the pressure for words to be as phonologically distinct as possible. Copyright © 2017 Elsevier B.V. All rights reserved.
Incremental projection approach of regularization for inverse problems
Souopgui, Innocent; Ngodock, Hans E.; Vidard, Arthur Le Dimet, François-Xavier
2016-10-15
This paper presents an alternative approach to the regularized least squares solution of ill-posed inverse problems. Instead of solving a minimization problem with an objective function composed of a data term and a regularization term, the regularization information is used to define a projection onto a convex subspace of regularized candidate solutions. The objective function is modified to include the projection of each iterate in the place of the regularization. Numerical experiments based on the problem of motion estimation for geophysical fluid images, show the improvement of the proposed method compared with regularization methods. For the presented test case, the incremental projection method uses 7 times less computation time than the regularization method, to reach the same error target. Moreover, at convergence, the incremental projection is two order of magnitude more accurate than the regularization method.
Laplacian embedded regression for scalable manifold regularization.
Chen, Lin; Tsang, Ivor W; Xu, Dong
2012-06-01
Semi-supervised learning (SSL), as a powerful tool to learn from a limited number of labeled data and a large number of unlabeled data, has been attracting increasing attention in the machine learning community. In particular, the manifold regularization framework has laid solid theoretical foundations for a large family of SSL algorithms, such as Laplacian support vector machine (LapSVM) and Laplacian regularized least squares (LapRLS). However, most of these algorithms are limited to small scale problems due to the high computational cost of the matrix inversion operation involved in the optimization problem. In this paper, we propose a novel framework called Laplacian embedded regression by introducing an intermediate decision variable into the manifold regularization framework. By using ∈-insensitive loss, we obtain the Laplacian embedded support vector regression (LapESVR) algorithm, which inherits the sparse solution from SVR. Also, we derive Laplacian embedded RLS (LapERLS) corresponding to RLS under the proposed framework. Both LapESVR and LapERLS possess a simpler form of a transformed kernel, which is the summation of the original kernel and a graph kernel that captures the manifold structure. The benefits of the transformed kernel are two-fold: (1) we can deal with the original kernel matrix and the graph Laplacian matrix in the graph kernel separately and (2) if the graph Laplacian matrix is sparse, we only need to perform the inverse operation for a sparse matrix, which is much more efficient when compared with that for a dense one. Inspired by kernel principal component analysis, we further propose to project the introduced decision variable into a subspace spanned by a few eigenvectors of the graph Laplacian matrix in order to better reflect the data manifold, as well as accelerate the calculation of the graph kernel, allowing our methods to efficiently and effectively cope with large scale SSL problems. Extensive experiments on both toy and real
Charge regularization in phase separating polyelectrolyte solutions.
Muthukumar, M; Hua, Jing; Kundagrami, Arindam
2010-02-28
Theoretical investigations of phase separation in polyelectrolyte solutions have so far assumed that the effective charge of the polyelectrolyte chains is fixed. The ability of the polyelectrolyte chains to self-regulate their effective charge due to the self-consistent coupling between ionization equilibrium and polymer conformations, depending on the dielectric constant, temperature, and polymer concentration, affects the critical phenomena and phase transitions drastically. By considering salt-free polyelectrolyte solutions, we show that the daughter phases have different polymer charges from that of the mother phase. The critical point is also altered significantly by the charge self-regularization of the polymer chains. This work extends the progress made so far in the theory of phase separation of strong polyelectrolyte solutions to a higher level of understanding by considering chains which can self-regulate their charge.
Multiloop integrals in dimensional regularization made simple.
Henn, Johannes M
2013-06-21
Scattering amplitudes at loop level can be expressed in terms of Feynman integrals. The latter satisfy partial differential equations in the kinematical variables. We argue that a good choice of basis for (multi)loop integrals can lead to significant simplifications of the differential equations, and propose criteria for finding an optimal basis. This builds on experience obtained in supersymmetric field theories that can be applied successfully to generic quantum field theory integrals. It involves studying leading singularities and explicit integral representations. When the differential equations are cast into canonical form, their solution becomes elementary. The class of functions involved is easily identified, and the solution can be written down to any desired order in ϵ within dimensional regularization. Results obtained in this way are particularly simple and compact. In this Letter, we outline the general ideas of the method and apply them to a two-loop example.
Regularity of inviscid shell models of turbulence
NASA Astrophysics Data System (ADS)
Constantin, Peter; Levant, Boris; Titi, Edriss S.
2007-01-01
In this paper we continue the analytical study of the sabra shell model of energy turbulent cascade. We prove the global existence of weak solutions of the inviscid sabra shell model, and show that these solutions are unique for some short interval of time. In addition, we prove that the solutions conserve energy, provided that the components of the solution satisfy ∣un∣≤Ckn-1/3[nlog(n+1)]-1 for some positive absolute constant C , which is the analog of the Onsager’s conjecture for the Euler’s equations. Moreover, we give a Beal-Kato-Majda type criterion for the blow-up of solutions of the inviscid sabra shell model and show the global regularity of the solutions in the “two-dimensional” parameters regime.
Regularization of Nutation Time Series at GSFC
NASA Astrophysics Data System (ADS)
Le Bail, K.; Gipson, J. M.; Bolotin, S.
2012-12-01
VLBI is unique in its ability to measure all five Earth orientation parameters. In this paper we focus on the two nutation parameters which characterize the orientation of the Earth's rotation axis in space. We look at the periodicities and the spectral characteristics of these parameters for both R1 and R4 sessions independently. The study of the most significant periodic signals for periods shorter than 600 days is common for these four time series (period of 450 days), and the type of noise determined by the Allan variance is a white noise for the four series. To investigate methods of regularizing the series, we look at a Singular Spectrum Analysis-derived method and at the Kalman filter. The two methods adequately reproduce the tendency of the nutation time series, but the resulting series are noisier using the Singular Spectrum Analysis-derived method.
Thermodynamics of regular accelerating black holes
NASA Astrophysics Data System (ADS)
Astorino, Marco
2017-03-01
Using the covariant phase space formalism, we compute the conserved charges for a solution, describing an accelerating and electrically charged Reissner-Nordstrom black hole. The metric is regular provided that the acceleration is driven by an external electric field, in spite of the usual string of the standard C-metric. The Smarr formula and the first law of black hole thermodynamics are fulfilled. The resulting mass has the same form of the Christodoulou-Ruffini irreducible mass. On the basis of these results, we can extrapolate the mass and thermodynamics of the rotating C-metric, which describes a Kerr-Newman-(A)dS black hole accelerated by a pulling string.
Regularization destriping of remote sensing imagery
NASA Astrophysics Data System (ADS)
Basnayake, Ranil; Bollt, Erik; Tufillaro, Nicholas; Sun, Jie; Gierach, Michelle
2017-07-01
We illustrate the utility of variational destriping for ocean color images from both multispectral and hyperspectral sensors. In particular, we examine data from a filter spectrometer, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar Partnership (NPP) orbiter, and an airborne grating spectrometer, the Jet Population Laboratory's (JPL) hyperspectral Portable Remote Imaging Spectrometer (PRISM) sensor. We solve the destriping problem using a variational regularization method by giving weights spatially to preserve the other features of the image during the destriping process. The target functional penalizes the neighborhood of stripes
(strictly, directionally uniform features) while promoting data fidelity, and the functional is minimized by solving the Euler-Lagrange equations with an explicit finite-difference scheme. We show the accuracy of our method from a benchmark data set which represents the sea surface temperature off the coast of Oregon, USA. Technical details, such as how to impose continuity across data gaps using inpainting, are also described.
Regularized discriminative direction for shape difference analysis.
Zhou, Luping; Hartley, Richard; Wang, Lei; Lieby, Paulette; Barnes, Nick
2008-01-01
The "discriminative direction" has been proven useful to reveal the subtle difference between two anatomical shape classes. When a shape moves along this direction, its deformation will best manifest the class difference detected by a kernel classifier. However, we observe that such a direction cannot maintain a shape's "anatomical" correctness, introducing spurious difference. To overcome this drawback, we develop a regularized discriminative direction by requiring a shape to conform to its population distribution when it deforms along the discriminative direction. Instead of iterative optimization, an analytic solution is provided to directly work out this direction. Experimental study shows its superior performance in detecting and localizing the difference of hippocampal shapes for sex. The result is supported by other independent research in the same domain.
Conformal regularization of Einstein's field equations
NASA Astrophysics Data System (ADS)
Röhr, Niklas; Uggla, Claes
2005-09-01
To study asymptotic structures, we regularize Einstein's field equations by means of conformal transformations. The conformal factor is chosen so that it carries a dimensional scale that captures crucial asymptotic features. By choosing a conformal orthonormal frame, we obtain a coupled system of differential equations for a set of dimensionless variables, associated with the conformal dimensionless metric, where the variables describe ratios with respect to the chosen asymptotic scale structure. As examples, we describe some explicit choices of conformal factors and coordinates appropriate for the situation of a timelike congruence approaching a singularity. One choice is shown to just slightly modify the so-called Hubble-normalized approach, and one leads to dimensionless first-order symmetric hyperbolic equations. We also discuss differences and similarities with other conformal approaches in the literature, as regards, e.g., isotropic singularities.
Regularity of free boundaries a heuristic retro
Caffarelli, Luis A.; Shahgholian, Henrik
2015-01-01
This survey concerns regularity theory of a few free boundary problems that have been developed in the past half a century. Our intention is to bring up different ideas and techniques that constitute the fundamentals of the theory. We shall discuss four different problems, where approaches are somewhat different in each case. Nevertheless, these problems can be divided into two groups: (i) obstacle and thin obstacle problem; (ii) minimal surfaces, and cavitation flow of a perfect fluid. In each case, we shall only discuss the methodology and approaches, giving basic ideas and tools that have been specifically designed and tailored for that particular problem. The survey is kept at a heuristic level with mainly geometric interpretation of the techniques and situations in hand. PMID:26261372
Charge regularization in phase separating polyelectrolyte solutions
Muthukumar, M.; Hua, Jing; Kundagrami, Arindam
2010-01-01
Theoretical investigations of phase separation in polyelectrolyte solutions have so far assumed that the effective charge of the polyelectrolyte chains is fixed. The ability of the polyelectrolyte chains to self-regulate their effective charge due to the self-consistent coupling between ionization equilibrium and polymer conformations, depending on the dielectric constant, temperature, and polymer concentration, affects the critical phenomena and phase transitions drastically. By considering salt-free polyelectrolyte solutions, we show that the daughter phases have different polymer charges from that of the mother phase. The critical point is also altered significantly by the charge self-regularization of the polymer chains. This work extends the progress made so far in the theory of phase separation of strong polyelectrolyte solutions to a higher level of understanding by considering chains which can self-regulate their charge. PMID:20192314
Regularization for Atmospheric Temperature Retrieval Problems
NASA Technical Reports Server (NTRS)
Velez-Reyes, Miguel; Galarza-Galarza, Ruben
1997-01-01
Passive remote sensing of the atmosphere is used to determine the atmospheric state. A radiometer measures microwave emissions from earth's atmosphere and surface. The radiance measured by the radiometer is proportional to the brightness temperature. This brightness temperature can be used to estimate atmospheric parameters such as temperature and water vapor content. These quantities are of primary importance for different applications in meteorology, oceanography, and geophysical sciences. Depending on the range in the electromagnetic spectrum being measured by the radiometer and the atmospheric quantities to be estimated, the retrieval or inverse problem of determining atmospheric parameters from brightness temperature might be linear or nonlinear. In most applications, the retrieval problem requires the inversion of a Fredholm integral equation of the first kind making this an ill-posed problem. The numerical solution of the retrieval problem requires the transformation of the continuous problem into a discrete problem. The ill-posedness of the continuous problem translates into ill-conditioning or ill-posedness of the discrete problem. Regularization methods are used to convert the ill-posed problem into a well-posed one. In this paper, we present some results of our work in applying different regularization techniques to atmospheric temperature retrievals using brightness temperatures measured with the SSM/T-1 sensor. Simulation results are presented which show the potential of these techniques to improve temperature retrievals. In particular, no statistical assumptions are needed and the algorithms were capable of correctly estimating the temperature profile corner at the tropopause independent of the initial guess.
Discriminative Elastic-Net Regularized Linear Regression.
Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen
2017-03-01
In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.
Black hole mimickers: Regular versus singular behavior
Lemos, Jose P. S.; Zaslavskii, Oleg B.
2008-07-15
Black hole mimickers are possible alternatives to black holes; they would look observationally almost like black holes but would have no horizon. The properties in the near-horizon region where gravity is strong can be quite different for both types of objects, but at infinity it could be difficult to discern black holes from their mimickers. To disentangle this possible confusion, we examine the near-horizon properties, and their connection with far away asymptotic properties, of some candidates to black mimickers. We study spherically symmetric uncharged or charged but nonextremal objects, as well as spherically symmetric charged extremal objects. Within the uncharged or charged but nonextremal black hole mimickers, we study nonextremal {epsilon}-wormholes on the threshold of the formation of an event horizon, of which a subclass are called black foils, and gravastars. Within the charged extremal black hole mimickers we study extremal {epsilon}-wormholes on the threshold of the formation of an event horizon, quasi-black holes, and wormholes on the basis of quasi-black holes from Bonnor stars. We elucidate whether or not the objects belonging to these two classes remain regular in the near-horizon limit. The requirement of full regularity, i.e., finite curvature and absence of naked behavior, up to an arbitrary neighborhood of the gravitational radius of the object enables one to rule out potential mimickers in most of the cases. A list ranking the best black hole mimickers up to the worst, both nonextremal and extremal, is as follows: wormholes on the basis of extremal black holes or on the basis of quasi-black holes, quasi-black holes, wormholes on the basis of nonextremal black holes (black foils), and gravastars. Since in observational astrophysics it is difficult to find extremal configurations (the best mimickers in the ranking), whereas nonextremal configurations are really bad mimickers, the task of distinguishing black holes from their mimickers seems to
Regularization of Instantaneous Frequency Attribute Computations
NASA Astrophysics Data System (ADS)
Yedlin, M. J.; Margrave, G. F.; Van Vorst, D. G.; Ben Horin, Y.
2014-12-01
We compare two different methods of computation of a temporally local frequency:1) A stabilized instantaneous frequency using the theory of the analytic signal.2) A temporally variant centroid (or dominant) frequency estimated from a time-frequency decomposition.The first method derives from Taner et al (1979) as modified by Fomel (2007) and utilizes the derivative of the instantaneous phase of the analytic signal. The second method computes the power centroid (Cohen, 1995) of the time-frequency spectrum, obtained using either the Gabor or Stockwell Transform. Common to both methods is the necessity of division by a diagonal matrix, which requires appropriate regularization.We modify Fomel's (2007) method by explicitly penalizing the roughness of the estimate. Following Farquharson and Oldenburg (2004), we employ both the L curve and GCV methods to obtain the smoothest model that fits the data in the L2 norm.Using synthetic data, quarry blast, earthquakes and the DPRK tests, our results suggest that the optimal method depends on the data. One of the main applications for this work is the discrimination between blast events and earthquakesFomel, Sergey. " Local seismic attributes." , Geophysics, 72.3 (2007): A29-A33.Cohen, Leon. " Time frequency analysis theory and applications." USA: Prentice Hall, (1995).Farquharson, Colin G., and Douglas W. Oldenburg. "A comparison of automatic techniques for estimating the regularization parameter in non-linear inverse problems." Geophysical Journal International 156.3 (2004): 411-425.Taner, M. Turhan, Fulton Koehler, and R. E. Sheriff. " Complex seismic trace analysis." Geophysics, 44.6 (1979): 1041-1063.
The Essential Special Education Guide for the Regular Education Teacher
ERIC Educational Resources Information Center
Burns, Edward
2007-01-01
The Individuals with Disabilities Education Act (IDEA) of 2004 has placed a renewed emphasis on the importance of the regular classroom, the regular classroom teacher and the general curriculum as the primary focus of special education. This book contains over 100 topics that deal with real issues and concerns regarding the regular classroom and…
The Essential Special Education Guide for the Regular Education Teacher
ERIC Educational Resources Information Center
Burns, Edward
2007-01-01
The Individuals with Disabilities Education Act (IDEA) of 2004 has placed a renewed emphasis on the importance of the regular classroom, the regular classroom teacher and the general curriculum as the primary focus of special education. This book contains over 100 topics that deal with real issues and concerns regarding the regular classroom and…
Recognition Memory for Novel Stimuli: The Structural Regularity Hypothesis
ERIC Educational Resources Information Center
Cleary, Anne M.; Morris, Alison L.; Langley, Moses M.
2007-01-01
Early studies of human memory suggest that adherence to a known structural regularity (e.g., orthographic regularity) benefits memory for an otherwise novel stimulus (e.g., G. A. Miller, 1958). However, a more recent study suggests that structural regularity can lead to an increase in false-positive responses on recognition memory tests (B. W. A.…
Recognition Memory for Novel Stimuli: The Structural Regularity Hypothesis
ERIC Educational Resources Information Center
Cleary, Anne M.; Morris, Alison L.; Langley, Moses M.
2007-01-01
Early studies of human memory suggest that adherence to a known structural regularity (e.g., orthographic regularity) benefits memory for an otherwise novel stimulus (e.g., G. A. Miller, 1958). However, a more recent study suggests that structural regularity can lead to an increase in false-positive responses on recognition memory tests (B. W. A.…
39 CFR 6.1 - Regular meetings, annual meeting.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 39 Postal Service 1 2010-07-01 2010-07-01 false Regular meetings, annual meeting. 6.1 Section 6.1 Postal Service UNITED STATES POSTAL SERVICE THE BOARD OF GOVERNORS OF THE U.S. POSTAL SERVICE MEETINGS (ARTICLE VI) § 6.1 Regular meetings, annual meeting. The Board shall meet regularly on a schedule...
5 CFR 532.203 - Structure of regular wage schedules.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Structure of regular wage schedules. 532... PREVAILING RATE SYSTEMS Prevailing Rate Determinations § 532.203 Structure of regular wage schedules. (a) Each nonsupervisory and leader regular wage schedule shall have 15 grades, which shall be designated as...
ERIC Educational Resources Information Center
Brown, Joyceanne; And Others
1991-01-01
This survey of 201 regular education teachers found that the most frequently used prereferral strategies used to facilitate classroom adjustment and achievement were consultation with other professionals, parent conferences, and behavior management techniques. Elementary teachers implemented more strategies than secondary-level teachers.…
Bishops reaffirm Humanae Vitae as "the authentic and constant teaching of the Magisterium".
1993-01-01
The US National Conference of Catholic Bishops' Committee for Pro-Life Activities reaffirm the 25-year old "Humanae Vitae." According to the secular world, sexual intercourse is a natural response to human instinct and need and contraception is a means to separate sexual intercourse from unwanted pregnancy and to free people from religious teachings. The true nature of human sexuality is understanding of human life and the human spirit. Sexual intercourse cannot be disconnected from the nature and dignity of human life and the means by which life is conveyed. The foundation of this encyclical is natural law as revealed by God. The Catholic church upholds this law through its teachings. Sexual intercourse is a couple's dignified expression of love for one another. Marital love reflects God's love, so marriage leads to union with God. Love between spouses stabilizes marriage and allows couples to make responsible decisions about birth spacing and family size. They celebrate their love via sexual intercourse and are open to life each time they have intercourse. There are 2 inseparable goods of marital intercourse: procreation and strengthening of interpersonal unity. Married couples want to share their life and love in creating new life and building a family . Parenthood is both a privilege and responsibility. Each child is a child of God with invaluable dignity who God calls to fulfill his/her human destiny and to be active in the Church's mission. Responsible parenthood intimates openness to life. Parents should be free to make family planning decisions while considering their duty to God, themselves, family, and society. Unproven claims about population growth and cultural attitudes debasing the value of children comprise the couple's freedom. Nonmarital cohabitation, abortion, illegitimate pregnancy, and divorce reflect confusion over human sexuality. The family is the basic unit of society. Natural family planning allows couples to have a richer appreciation of
The connection between regularization operators and support vector kernels.
Smola, Alex J.; Schölkopf, Bernhard; Müller, Klaus Robert
1998-06-01
In this paper a correspondence is derived between regularization operators used in regularization networks and support vector kernels. We prove that the Green's Functions associated with regularization operators are suitable support vector kernels with equivalent regularization properties. Moreover, the paper provides an analysis of currently used support vector kernels in the view of regularization theory and corresponding operators associated with the classes of both polynomial kernels and translation invariant kernels. The latter are also analyzed on periodical domains. As a by-product we show that a large number of radial basis functions, namely conditionally positive definite functions, may be used as support vector kernels.
Preparation of Regular Specimens for Atom Probes
NASA Technical Reports Server (NTRS)
Kuhlman, Kim; Wishard, James
2003-01-01
A method of preparation of specimens of non-electropolishable materials for analysis by atom probes is being developed as a superior alternative to a prior method. In comparison with the prior method, the present method involves less processing time. Also, whereas the prior method yields irregularly shaped and sized specimens, the present developmental method offers the potential to prepare specimens of regular shape and size. The prior method is called the method of sharp shards because it involves crushing the material of interest and selecting microscopic sharp shards of the material for use as specimens. Each selected shard is oriented with its sharp tip facing away from the tip of a stainless-steel pin and is glued to the tip of the pin by use of silver epoxy. Then the shard is milled by use of a focused ion beam (FIB) to make the shard very thin (relative to its length) and to make its tip sharp enough for atom-probe analysis. The method of sharp shards is extremely time-consuming because the selection of shards must be performed with the help of a microscope, the shards must be positioned on the pins by use of micromanipulators, and the irregularity of size and shape necessitates many hours of FIB milling to sharpen each shard. In the present method, a flat slab of the material of interest (e.g., a polished sample of rock or a coated semiconductor wafer) is mounted in the sample holder of a dicing saw of the type conventionally used to cut individual integrated circuits out of the wafers on which they are fabricated in batches. A saw blade appropriate to the material of interest is selected. The depth of cut and the distance between successive parallel cuts is made such that what is left after the cuts is a series of thin, parallel ridges on a solid base. Then the workpiece is rotated 90 and the pattern of cuts is repeated, leaving behind a square array of square posts on the solid base. The posts can be made regular, long, and thin, as required for samples
Error analysis for matrix elastic-net regularization algorithms.
Li, Hong; Chen, Na; Li, Luoqing
2012-05-01
Elastic-net regularization is a successful approach in statistical modeling. It can avoid large variations which occur in estimating complex models. In this paper, elastic-net regularization is extended to a more general setting, the matrix recovery (matrix completion) setting. Based on a combination of the nuclear-norm minimization and the Frobenius-norm minimization, we consider the matrix elastic-net (MEN) regularization algorithm, which is an analog to the elastic-net regularization scheme from compressive sensing. Some properties of the estimator are characterized by the singular value shrinkage operator. We estimate the error bounds of the MEN regularization algorithm in the framework of statistical learning theory. We compute the learning rate by estimates of the Hilbert-Schmidt operators. In addition, an adaptive scheme for selecting the regularization parameter is presented. Numerical experiments demonstrate the superiority of the MEN regularization algorithm.
On a space-frequency regularization for source reconstruction
NASA Astrophysics Data System (ADS)
Aucejo, Mathieu; De Smet, Olivier
2016-09-01
To identify mechanical sources acting on a structure, Tikhonov-like regularizations are generally used. These approaches, referred to as additive regularizations, require the calculation of a regularization parameter from adapted selection procedures such as the L- curve method. However, such selection procedures can be computationally intensive. In this contribution, a space-frequency multiplicative regularization is introduced. The proposed strategy has the merit of avoiding the need for the determination of a regularization parameter beforehand, while taking advantage of one's prior knowledge of the type of the sources as well as the nature of the excitation signal. By construction, the regularized solution is computed in an iterative manner, which allows adapting the importance of the regularization term all along the resolution process. The validity of the proposed approach is illustrated numerically on a simply supported beam.
Degenerate Regularization of Forward-Backward Parabolic Equations: The Regularized Problem
NASA Astrophysics Data System (ADS)
Smarrazzo, Flavia; Tesei, Alberto
2012-04-01
We study a quasilinear parabolic equation of forward-backward type in one space dimension, under assumptions on the nonlinearity which hold for a number of important mathematical models (for example, the one-dimensional Perona-Malik equation), using a degenerate pseudoparabolic regularization proposed in Barenblatt et al. (SIAM J Math Anal 24:1414-1439, 1993), which takes time delay effects into account. We prove existence and uniqueness of positive solutions of the regularized problem in a space of Radon measures. We also study qualitative properties of such solutions, in particular concerning their decomposition into an absolutely continuous part and a singular part with respect to the Lebesgue measure. In this respect, the existence of a family of viscous entropy inequalities plays an important role.
Information theoretic regularization in diffuse optical tomography.
Panagiotou, Christos; Somayajula, Sangeetha; Gibson, Adam P; Schweiger, Martin; Leahy, Richard M; Arridge, Simon R
2009-05-01
Diffuse optical tomography (DOT) retrieves the spatially distributed optical characteristics of a medium from external measurements. Recovering the parameters of interest involves solving a nonlinear and highly ill-posed inverse problem. This paper examines the possibility of regularizing DOT via the introduction of a priori information from alternative high-resolution anatomical modalities, using the information theory concepts of mutual information (MI) and joint entropy (JE). Such functionals evaluate the similarity between the reconstructed optical image and the prior image while bypassing the multimodality barrier manifested as the incommensurate relation between the gray value representations of corresponding anatomical features in the two modalities. By introducing structural information, we aim to improve the spatial resolution and quantitative accuracy of the solution. We provide a thorough explanation of the theory from an imaging perspective, accompanied by preliminary results using numerical simulations. In addition we compare the performance of MI and JE. Finally, we have adopted a method for fast marginal entropy evaluation and optimization by modifying the objective function and extending it to the JE case. We demonstrate its use on an image reconstruction framework and show significant computational savings.
Color correction optimization with hue regularization
NASA Astrophysics Data System (ADS)
Zhang, Heng; Liu, Huaping; Quan, Shuxue
2011-01-01
Previous work has suggested that observers are capable of judging the quality of an image without any knowledge of the original scene. When no reference is available, observers can extract the apparent objects in an image and compare them with the typical colors of similar objects recalled from their memories. Some generally agreed upon research results indicate that although perfect colorimetric rendering is not conspicuous and color errors can be well tolerated, the appropriate rendition of certain memory colors such as skin, grass, and sky is an important factor in the overall perceived image quality. These colors are appreciated in a fairly consistent manner and are memorized with slightly different hues and higher color saturation. The aim of color correction for a digital color pipeline is to transform the image data from a device dependent color space to a target color space, usually through a color correction matrix which in its most basic form is optimized through linear regressions between the two sets of data in two color spaces in the sense of minimized Euclidean color error. Unfortunately, this method could result in objectionable distortions if the color error biased certain colors undesirably. In this paper, we propose a color correction optimization method with preferred color reproduction in mind through hue regularization and present some experimental results.
Manifold Regularized Experimental Design for Active Learning.
Zhang, Lining; Shum, Hubert P H; Shao, Ling
2016-12-02
Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one sample after another in a greedy manner. However, this is not very effective because the classification models has to be retrained for each newly labeled sample. Moreover, many popular active learning approaches utilize the most uncertain samples by leveraging the classification hyperplane of the classifier, which is not appropriate since the classification hyperplane is inaccurate when the training data are small-sized. The problem of insufficient training data in real-world systems limits the potential applications of these approaches. This paper presents a novel method of active learning called manifold regularized experimental design (MRED), which can label multiple informative samples at one time for training. In addition, MRED gives an explicit geometric explanation for the selected samples to be labeled by the user. Different from existing active learning methods, our method avoids the intrinsic problems caused by insufficiently labeled samples in real-world applications. Various experiments on synthetic datasets, the Yale face database and the Corel image database have been carried out to show how MRED outperforms existing methods.
Determinants of Scanpath Regularity in Reading.
von der Malsburg, Titus; Kliegl, Reinhold; Vasishth, Shravan
2015-09-01
Scanpaths have played an important role in classic research on reading behavior. Nevertheless, they have largely been neglected in later research perhaps due to a lack of suitable analytical tools. Recently, von der Malsburg and Vasishth (2011) proposed a new measure for quantifying differences between scanpaths and demonstrated that this measure can recover effects that were missed with the traditional eyetracking measures. However, the sentences used in that study were difficult to process and scanpath effects accordingly strong. The purpose of the present study was to test the validity, sensitivity, and scope of applicability of the scanpath measure, using simple sentences that are typically read from left to right. We derived predictions for the regularity of scanpaths from the literature on oculomotor control, sentence processing, and cognitive aging and tested these predictions using the scanpath measure and a large database of eye movements. All predictions were confirmed: Sentences with short words and syntactically more difficult sentences elicited more irregular scanpaths. Also, older readers produced more irregular scanpaths than younger readers. In addition, we found an effect that was not reported earlier: Syntax had a smaller influence on the eye movements of older readers than on those of young readers. We discuss this interaction of syntactic parsing cost with age in terms of shifts in processing strategies and a decline of executive control as readers age. Overall, our results demonstrate the validity and sensitivity of the scanpath measure and thus establish it as a productive and versatile tool for reading research.
Menstrual Bleeding Patterns Among Regularly Menstruating Women
Dasharathy, Sonya S.; Mumford, Sunni L.; Pollack, Anna Z.; Perkins, Neil J.; Mattison, Donald R.; Wactawski-Wende, Jean; Schisterman, Enrique F.
2012-01-01
Menstrual bleeding patterns are considered relevant indicators of reproductive health, though few studies have evaluated patterns among regularly menstruating premenopausal women. The authors evaluated self-reported bleeding patterns, incidence of spotting, and associations with reproductive hormones among 201 women in the BioCycle Study (2005–2007) with 2 consecutive cycles. Bleeding patterns were assessed by using daily questionnaires and pictograms. Marginal structural models were used to evaluate associations between endogenous hormone concentrations and subsequent total reported blood loss and bleeding length by weighted linear mixed-effects models and weighted parametric survival analysis models. Women bled for a median of 5 days (standard deviation: 1.5) during menstruation, with heavier bleeding during the first 3 days. Only 4.8% of women experienced midcycle bleeding. Increased levels of follicle-stimulating hormone (β = 0.20, 95% confidence interval: 0.13, 0.27) and progesterone (β = 0.06, 95% confidence interval: 0.03, 0.09) throughout the cycle were associated with heavier menstrual bleeding, and higher follicle-stimulating hormone levels were associated with longer menses. Bleeding duration and volume were reduced after anovulatory compared with ovulatory cycles (geometric mean blood loss: 29.6 vs. 47.2 mL; P = 0.07). Study findings suggest that detailed characterizations of bleeding patterns may provide more insight than previously thought as noninvasive markers for endocrine status in a given cycle. PMID:22350580
Flip to Regular Triangulation and Convex Hull.
Gao, Mingcen; Cao, Thanh-Tung; Tan, Tiow-Seng
2017-02-01
Flip is a simple and local operation to transform one triangulation to another. It makes changes only to some neighboring simplices, without considering any attribute or configuration global in nature to the triangulation. Thanks to this characteristic, several flips can be independently applied to different small, non-overlapping regions of one triangulation. Such operation is favored when designing algorithms for data-parallel, massively multithreaded hardware, such as the GPU. However, most existing flip algorithms are designed to be executed sequentially, and usually need some restrictions on the execution order of flips, making them hard to be adapted to parallel computation. In this paper, we present an in depth study of flip algorithms in low dimensions, with the emphasis on the flexibility of their execution order. In particular, we propose a series of provably correct flip algorithms for regular triangulation and convex hull in 2D and 3D, with implementations for both CPUs and GPUs. Our experiment shows that our GPU implementation for constructing these structures from a given point set achieves up to two orders of magnitude of speedup over other popular single-threaded CPU implementation of existing algorithms.
Compression and regularization with the information bottleneck
NASA Astrophysics Data System (ADS)
Strouse, Dj; Schwab, David
Compression fundamentally involves a decision about what is relevant and what is not. The information bottleneck (IB) by Tishby, Pereira, and Bialek formalized this notion as an information-theoretic optimization problem and proposed an optimal tradeoff between throwing away as many bits as possible, and selectively keeping those that are most important. The IB has also recently been proposed as a theory of sensory gating and predictive computation in the retina by Palmer et al. Here, we introduce an alternative formulation of the IB, the deterministic information bottleneck (DIB), that we argue better captures the notion of compression, including that done by the brain. As suggested by its name, the solution to the DIB problem is a deterministic encoder, as opposed to the stochastic encoder that is optimal under the IB. We then compare the IB and DIB on synthetic data, showing that the IB and DIB perform similarly in terms of the IB cost function, but that the DIB vastly outperforms the IB in terms of the DIB cost function. Our derivation of the DIB also provides a family of models which interpolates between the DIB and IB by adding noise of a particular form. We discuss the role of this noise as a regularizer.
Reverberation mapping by regularized linear inversion
NASA Astrophysics Data System (ADS)
Krolik, Julian H.; Done, Christine
1995-02-01
Reverberation mapping of active galactic nucleus (AGN) emission-line regions requires the numerical deconvolution of two time series. We suggest the application of a new method, regularized linear inversion, to the solution of this problem. This method possesses many good features; it imposes no restrictions on the sign of the response function; it can provide clearly defined uncertainty estimates; it involves no guesswork about unmeasured data; it can give a clear indication of when the underlying convolution model is inadequate; and it is computationally very efficient. Using simulated data, we find the minimum S/N and length of the time series in order for this method to work satisfactorily. We also define guidelines for choosing the principal tunable parameter of the method and for interpreting the results. Finally, we reanalyze published data from the 1989 NGC 5548 campaign using this new method and compare the results to those previously obtained by maximum entropy analysis. For some lines we find good agreement, but for others, especially C III lambda(1909) and Si IV lambda(1400), we find significant differences. These can be attributed to the inability of the maximum entropy method to find negative values of the response function, but also illustrate the nonuniqueness of any deconvolution technique. We also find evidence that certain line light curves (e.g., C IV lambda(1549)) cannot be fully described by the simple linear convolution model.
Reverberation mapping by regularized linear inversion
NASA Technical Reports Server (NTRS)
Krolik, Julian H.; Done, Christine
1995-01-01
Reverberation mapping of active galactic nucleus (AGN) emission-line regions requires the numerical deconvolution of two time series. We suggest the application of a new method, regularized linear inversion, to the solution of this problem. This method possesses many good features; it imposes no restrictions on the sign of the response function; it can provide clearly defined uncertainty estimates; it involves no guesswork about unmeasured data; it can give a clear indication of when the underlying convolution model is inadequate; and it is computationally very efficient. Using simulated data, we find the minimum S/N and length of the time series in order for this method to work satisfactorily. We also define guidelines for choosing the principal tunable parameter of the method and for interpreting the results. Finally, we reanalyze published data from the 1989 NGC 5548 campaign using this new method and compare the results to those previously obtained by maximum entropy analysis. For some lines we find good agreement, but for others, especially C III lambda(1909) and Si IV lambda(1400), we find significant differences. These can be attributed to the inability of the maximum entropy method to find negative values of the response function, but also illustrate the nonuniqueness of any deconvolution technique. We also find evidence that certain line light curves (e.g., C IV lambda(1549)) cannot be fully described by the simple linear convolution model.
Wave dynamics of regular and chaotic rays
McDonald, S.W.
1983-09-01
In order to investigate general relationships between waves and rays in chaotic systems, I study the eigenfunctions and spectrum of a simple model, the two-dimensional Helmholtz equation in a stadium boundary, for which the rays are ergodic. Statistical measurements are performed so that the apparent randomness of the stadium modes can be quantitatively contrasted with the familiar regularities observed for the modes in a circular boundary (with integrable rays). The local spatial autocorrelation of the eigenfunctions is constructed in order to indirectly test theoretical predictions for the nature of the Wigner distribution corresponding to chaotic waves. A portion of the large-eigenvalue spectrum is computed and reported in an appendix; the probability distribution of successive level spacings is analyzed and compared with theoretical predictions. The two principal conclusions are: 1) waves associated with chaotic rays may exhibit randomly situated localized regions of high intensity; 2) the Wigner function for these waves may depart significantly from being uniformly distributed over the surface of constant frequency in the ray phase space.
Temporal Regularity of the Environment Drives Time Perception
2016-01-01
It’s reasonable to assume that a regularly paced sequence should be perceived as regular, but here we show that perceived regularity depends on the context in which the sequence is embedded. We presented one group of participants with perceptually regularly paced sequences, and another group of participants with mostly irregularly paced sequences (75% irregular, 25% regular). The timing of the final stimulus in each sequence could be varied. In one experiment, we asked whether the last stimulus was regular or not. We found that participants exposed to an irregular environment frequently reported perfectly regularly paced stimuli to be irregular. In a second experiment, we asked participants to judge whether the final stimulus was presented before or after a flash. In this way, we were able to determine distortions in temporal perception as changes in the timing necessary for the sound and the flash to be perceived synchronous. We found that within a regular context, the perceived timing of deviant last stimuli changed so that the relative anisochrony appeared to be perceptually decreased. In the irregular context, the perceived timing of irregular stimuli following a regular sequence was not affected. These observations suggest that humans use temporal expectations to evaluate the regularity of sequences and that expectations are combined with sensory stimuli to adapt perceived timing to follow the statistics of the environment. Expectations can be seen as a-priori probabilities on which perceived timing of stimuli depend. PMID:27441686
Howe, Andrew; Eyck, Laura Ten; Dufour, Robert; Shah, Neel; Harrison, David J
2014-12-01
A variety of biologic therapies are currently used for the treatment of inflammatory autoimmune diseases, including rheumatoid arthritis (RA), psoriasis (PsO), psoriatic arthritis (PsA), and ankylosing spondylitis (AS). These diseases require long-term treatment, and information regarding the use and costs of biologic therapies can be valuable in making treatment and formulary decisions for clinicians and payers. To evaluate current utilization and annual costs of biologic therapies for treatment of RA, PsO, PsA, and AS in a real-world setting. This retrospective observational cohort analysis utilized data from the Humana commercial claims database. Eligible patients had an index (first) claim between February 1, 2008, and September 30, 2011, for abatacept, adalimumab, certolizumab pegol, etanercept, golimumab, infliximab, rituximab, or ustekinumab and a diagnosis of RA, PsO, PsA, AS, or combination of these diseases. Patients with and without a claim for their index therapy within 180 days prior to their index dates were defined as continuing and new patients, respectively. Outcomes included 1-year rates of persistence; rates of restarting, discontinuing, or switching for patients who were not persistent; and annual costs. Costs were based on dose and the October 2013 wholesale acquisition cost (WAC). Total expenditure was calculated as the (total index biologic drug utilization × WAC) + (number of administrations × Medicare fee schedule) + Σ(biologic dose after discontinuation × associated WAC price). Of 2,721 patients analyzed, 1,308 (48%) were new patients, and 1,413 (52%) were continuing patients. Across approved indications, the most commonly used biologics were adalimumab, etanercept, and infliximab. Continuing patients had higher rates of persistence on index therapy than new patients. The mean annual cost [SD] per treated patient for new patients across all indications was numerically lowest for adalimumab ($20,916 [$7,572]), followed by infliximab
Elementary Particle Spectroscopy in Regular Solid Rewrite
NASA Astrophysics Data System (ADS)
Trell, Erik
2008-10-01
The Nilpotent Universal Computer Rewrite System (NUCRS) has operationalized the radical ontological dilemma of Nothing at All versus Anything at All down to the ground recursive syntax and principal mathematical realisation of this categorical dichotomy as such and so governing all its sui generis modalities, leading to fulfilment of their individual terms and compass when the respective choice sequence operations are brought to closure. Focussing on the general grammar, NUCRS by pure logic and its algebraic notations hence bootstraps Quantum Mechanics, aware that it "is the likely keystone of a fundamental computational foundation" also for e.g. physics, molecular biology and neuroscience. The present work deals with classical geometry where morphology is the modality, and ventures that the ancient regular solids are its specific rewrite system, in effect extensively anticipating the detailed elementary particle spectroscopy, and further on to essential structures at large both over the inorganic and organic realms. The geodetic antipode to Nothing is extension, with natural eigenvector the endless straight line which when deployed according to the NUCRS as well as Plotelemeian topographic prescriptions forms a real three-dimensional eigenspace with cubical eigenelements where observed quark-skewed quantum-chromodynamical particle events self-generate as an Aristotelean phase transition between the straight and round extremes of absolute endlessness under the symmetry- and gauge-preserving, canonical coset decomposition SO(3)×O(5) of Lie algebra SU(3). The cubical eigen-space and eigen-elements are the parental state and frame, and the other solids are a range of transition matrix elements and portions adapting to the spherical root vector symmetries and so reproducibly reproducing the elementary particle spectroscopy, including a modular, truncated octahedron nano-composition of the Electron which piecemeal enter into molecular structures or compressed to each
Elementary Particle Spectroscopy in Regular Solid Rewrite
Trell, Erik
2008-10-17
The Nilpotent Universal Computer Rewrite System (NUCRS) has operationalized the radical ontological dilemma of Nothing at All versus Anything at All down to the ground recursive syntax and principal mathematical realisation of this categorical dichotomy as such and so governing all its sui generis modalities, leading to fulfilment of their individual terms and compass when the respective choice sequence operations are brought to closure. Focussing on the general grammar, NUCRS by pure logic and its algebraic notations hence bootstraps Quantum Mechanics, aware that it ''is the likely keystone of a fundamental computational foundation'' also for e.g. physics, molecular biology and neuroscience. The present work deals with classical geometry where morphology is the modality, and ventures that the ancient regular solids are its specific rewrite system, in effect extensively anticipating the detailed elementary particle spectroscopy, and further on to essential structures at large both over the inorganic and organic realms. The geodetic antipode to Nothing is extension, with natural eigenvector the endless straight line which when deployed according to the NUCRS as well as Plotelemeian topographic prescriptions forms a real three-dimensional eigenspace with cubical eigenelements where observed quark-skewed quantum-chromodynamical particle events self-generate as an Aristotelean phase transition between the straight and round extremes of absolute endlessness under the symmetry- and gauge-preserving, canonical coset decomposition SO(3)xO(5) of Lie algebra SU(3). The cubical eigen-space and eigen-elements are the parental state and frame, and the other solids are a range of transition matrix elements and portions adapting to the spherical root vector symmetries and so reproducibly reproducing the elementary particle spectroscopy, including a modular, truncated octahedron nano-composition of the Electron which piecemeal enter into molecular structures or compressed to each
TRANSIENT LUNAR PHENOMENA: REGULARITY AND REALITY
Crotts, Arlin P. S.
2009-05-20
Transient lunar phenomena (TLPs) have been reported for centuries, but their nature is largely unsettled, and even their existence as a coherent phenomenon is controversial. Nonetheless, TLP data show regularities in the observations; a key question is whether this structure is imposed by processes tied to the lunar surface, or by terrestrial atmospheric or human observer effects. I interrogate an extensive catalog of TLPs to gauge how human factors determine the distribution of TLP reports. The sample is grouped according to variables which should produce differing results if determining factors involve humans, and not reflecting phenomena tied to the lunar surface. Features dependent on human factors can then be excluded. Regardless of how the sample is split, the results are similar: {approx}50% of reports originate from near Aristarchus, {approx}16% from Plato, {approx}6% from recent, major impacts (Copernicus, Kepler, Tycho, and Aristarchus), plus several at Grimaldi. Mare Crisium produces a robust signal in some cases (however, Crisium is too large for a 'feature' as defined). TLP count consistency for these features indicates that {approx}80% of these may be real. Some commonly reported sites disappear from the robust averages, including Alphonsus, Ross D, and Gassendi. These reports begin almost exclusively after 1955, when TLPs became widely known and many more (and inexperienced) observers searched for TLPs. In a companion paper, we compare the spatial distribution of robust TLP sites to transient outgassing (seen by Apollo and Lunar Prospector instruments). To a high confidence, robust TLP sites and those of lunar outgassing correlate strongly, further arguing for the reality of TLPs.
Transient Lunar Phenomena: Regularity and Reality
NASA Astrophysics Data System (ADS)
Crotts, Arlin P. S.
2009-05-01
Transient lunar phenomena (TLPs) have been reported for centuries, but their nature is largely unsettled, and even their existence as a coherent phenomenon is controversial. Nonetheless, TLP data show regularities in the observations; a key question is whether this structure is imposed by processes tied to the lunar surface, or by terrestrial atmospheric or human observer effects. I interrogate an extensive catalog of TLPs to gauge how human factors determine the distribution of TLP reports. The sample is grouped according to variables which should produce differing results if determining factors involve humans, and not reflecting phenomena tied to the lunar surface. Features dependent on human factors can then be excluded. Regardless of how the sample is split, the results are similar: ~50% of reports originate from near Aristarchus, ~16% from Plato, ~6% from recent, major impacts (Copernicus, Kepler, Tycho, and Aristarchus), plus several at Grimaldi. Mare Crisium produces a robust signal in some cases (however, Crisium is too large for a "feature" as defined). TLP count consistency for these features indicates that ~80% of these may be real. Some commonly reported sites disappear from the robust averages, including Alphonsus, Ross D, and Gassendi. These reports begin almost exclusively after 1955, when TLPs became widely known and many more (and inexperienced) observers searched for TLPs. In a companion paper, we compare the spatial distribution of robust TLP sites to transient outgassing (seen by Apollo and Lunar Prospector instruments). To a high confidence, robust TLP sites and those of lunar outgassing correlate strongly, further arguing for the reality of TLPs.
On reductibility of degenerate optimization problems to regular operator equations
NASA Astrophysics Data System (ADS)
Bednarczuk, E. M.; Tretyakov, A. A.
2016-12-01
We present an application of the p-regularity theory to the analysis of non-regular (irregular, degenerate) nonlinear optimization problems. The p-regularity theory, also known as the p-factor analysis of nonlinear mappings, was developed during last thirty years. The p-factor analysis is based on the construction of the p-factor operator which allows us to analyze optimization problems in the degenerate case. We investigate reducibility of a non-regular optimization problem to a regular system of equations which do not depend on the objective function. As an illustration we consider applications of our results to non-regular complementarity problems of mathematical programming and to linear programming problems.
Phase-regularized polygon computer-generated holograms.
Im, Dajeong; Moon, Eunkyoung; Park, Yohan; Lee, Deokhwan; Hahn, Joonku; Kim, Hwi
2014-06-15
The dark-line defect problem in the conventional polygon computer-generated hologram (CGH) is addressed. To resolve this problem, we clarify the physical origin of the defect and address the concept of phase-regularization. A novel synthesis algorithm for a phase-regularized polygon CGH for generating photorealistic defect-free holographic images is proposed. The optical reconstruction results of the phase-regularized polygon CGHs without the dark-line defects are presented.
Analysis of regularized Navier-Stokes equations. I, II
NASA Technical Reports Server (NTRS)
Ou, Yuh-Roung; Sritharan, S. S.
1991-01-01
A regularized form of the conventional Navier-Stokes equations is analyzed. The global existence and uniqueness are established for two classes of generalized solutions. It is shown that the solution of this regularized system converges to the solution of the conventional Navier-Stokes equations for low Reynolds numbers. Particular attention is given to the structure of attractors characterizing the solutions. Both local and global invariant manifolds are found, and the regularity properties of these manifolds are analyzed.
The analyzation of 2D complicated regular polygon photonic lattice
NASA Astrophysics Data System (ADS)
Lv, Jing; Gao, Yuanmei
2017-06-01
We have numerically simulated the light intensity distribution, phase distribution, far-field diffraction of the two dimensional (2D) regular octagon and regular dodecagon lattices in detail. In addition, using the plane wave expansion (PWE) method, we numerically calculate the energy band of the two lattices. Both of the photonic lattices have the band gap. And the regular octagon lattice possesses the wide complete band gap while the regular dodecagon lattice has the incomplete gap. Moreover, we simulated the preliminary transmission image of photonic lattices. It may inspire the academic research both in light control and soliton.
Regularization of multiplicative iterative algorithms with nonnegative constraint
NASA Astrophysics Data System (ADS)
Benvenuto, Federico; Piana, Michele
2014-03-01
This paper studies the regularization of the constrained maximum likelihood iterative algorithms applied to incompatible ill-posed linear inverse problems. Specifically, we introduce a novel stopping rule which defines a regularization algorithm for the iterative space reconstruction algorithm in the case of least-squares minimization. Further we show that the same rule regularizes the expectation maximization algorithm in the case of Kullback-Leibler minimization, provided a well-justified modification of the definition of Tikhonov regularization is introduced. The performances of this stopping rule are illustrated in the case of an image reconstruction problem in the x-ray solar astronomy.
Lagrangian averaging, nonlinear waves, and shock regularization
NASA Astrophysics Data System (ADS)
Bhat, Harish S.
In this thesis, we explore various models for the flow of a compressible fluid as well as model equations for shock formation, one of the main features of compressible fluid flows. We begin by reviewing the variational structure of compressible fluid mechanics. We derive the barotropic compressible Euler equations from a variational principle in both material and spatial frames. Writing the resulting equations of motion requires certain Lie-algebraic calculations that we carry out in detail for expository purposes. Next, we extend the derivation of the Lagrangian averaged Euler (LAE-alpha) equations to the case of barotropic compressible flows. The derivation in this thesis involves averaging over a tube of trajectories etaepsilon centered around a given Lagrangian flow eta. With this tube framework, the LAE-alpha equations are derived by following a simple procedure: start with a given action, expand via Taylor series in terms of small-scale fluid fluctuations xi, truncate, average, and then model those terms that are nonlinear functions of xi. We then analyze a one-dimensional subcase of the general models derived above. We prove the existence of a large family of traveling wave solutions. Computing the dispersion relation for this model, we find it is nonlinear, implying that the equation is dispersive. We carry out numerical experiments that show that the model possesses smooth, bounded solutions that display interesting pattern formation. Finally, we examine a Hamiltonian partial differential equation (PDE) that regularizes the inviscid Burgers equation without the addition of standard viscosity. Here alpha is a small parameter that controls a nonlinear smoothing term that we have added to the inviscid Burgers equation. We show the existence of a large family of traveling front solutions. We analyze the initial-value problem and prove well-posedness for a certain class of initial data. We prove that in the zero-alpha limit, without any standard viscosity
Full L1-regularized Traction Force Microscopy over whole cells.
Suñé-Auñón, Alejandro; Jorge-Peñas, Alvaro; Aguilar-Cuenca, Rocío; Vicente-Manzanares, Miguel; Van Oosterwyck, Hans; Muñoz-Barrutia, Arrate
2017-08-10
Traction Force Microscopy (TFM) is a widespread technique to estimate the tractions that cells exert on the surrounding substrate. To recover the tractions, it is necessary to solve an inverse problem, which is ill-posed and needs regularization to make the solution stable. The typical regularization scheme is given by the minimization of a cost functional, which is divided in two terms: the error present in the data or data fidelity term; and the regularization or penalty term. The classical approach is to use zero-order Tikhonov or L2-regularization, which uses the L2-norm for both terms in the cost function. Recently, some studies have demonstrated an improved performance using L1-regularization (L1-norm in the penalty term) related to an increase in the spatial resolution and sensitivity of the recovered traction field. In this manuscript, we present a comparison between the previous two regularization schemes (relying in the L2-norm for the data fidelity term) and the full L1-regularization (using the L1-norm for both terms in the cost function) for synthetic and real data. Our results reveal that L1-regularizations give an improved spatial resolution (more important for full L1-regularization) and a reduction in the background noise with respect to the classical zero-order Tikhonov regularization. In addition, we present an approximation, which makes feasible the recovery of cellular tractions over whole cells on typical full-size microscope images when working in the spatial domain. The proposed full L1-regularization improves the sensitivity to recover small stress footprints. Moreover, the proposed method has been validated to work on full-field microscopy images of real cells, what certainly demonstrates it is a promising tool for biological applications.
NASA Astrophysics Data System (ADS)
Ioan Boţ, Radu; Hein, Torsten
2012-10-01
In this paper, we consider an iterative regularization scheme for linear ill-posed equations in Banach spaces. As opposed to other iterative approaches, we deal with a general penalty functional from Tikhonov regularization and take advantage of the properties of the regularized solutions which where supported by the choice of the specific penalty term. We present convergence and stability results for the presented algorithm. Additionally, we demonstrate how these theoretical results can be applied to L1- and TV-regularization approaches and close the paper with a short numerical example.
Regular and Special Educators Inservice: A Model of Cooperative Effort.
ERIC Educational Resources Information Center
van Duyne, H. John; And Others
The Regular Education Inservice Program (REIT) at Bowling Green State University (Ohio) assists instructional resource centers (IRC's) and local educational agencies (LEA's) in developing and implementing inservice non-degree programs which respond to the mandates of Public Law 94-142. The target population is regular education personnel working…
12 CFR 311.5 - Regular procedure for closing meetings.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Regular procedure for closing meetings. 311.5 Section 311.5 Banks and Banking FEDERAL DEPOSIT INSURANCE CORPORATION PROCEDURE AND RULES OF PRACTICE RULES GOVERNING PUBLIC OBSERVATION OF MEETINGS OF THE CORPORATION'S BOARD OF DIRECTORS § 311.5 Regular...
39 CFR 3010.7 - Schedule of regular rate changes.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 39 Postal Service 1 2011-07-01 2011-07-01 false Schedule of regular rate changes. 3010.7 Section 3010.7 Postal Service POSTAL REGULATORY COMMISSION PERSONNEL REGULATION OF RATES FOR MARKET DOMINANT PRODUCTS General Provisions § 3010.7 Schedule of regular rate changes. (a) The Postal Service shall...
39 CFR 3010.7 - Schedule of regular rate changes.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 39 Postal Service 1 2012-07-01 2012-07-01 false Schedule of regular rate changes. 3010.7 Section 3010.7 Postal Service POSTAL REGULATORY COMMISSION PERSONNEL REGULATION OF RATES FOR MARKET DOMINANT PRODUCTS General Provisions § 3010.7 Schedule of regular rate changes. (a) The Postal Service shall...
39 CFR 3010.7 - Schedule of regular rate changes.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 39 Postal Service 1 2013-07-01 2013-07-01 false Schedule of regular rate changes. 3010.7 Section 3010.7 Postal Service POSTAL REGULATORY COMMISSION PERSONNEL REGULATION OF RATES FOR MARKET DOMINANT PRODUCTS General Provisions § 3010.7 Schedule of regular rate changes. (a) The Postal Service shall...
20 CFR 216.13 - Regular current connection test.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 20 Employees' Benefits 1 2011-04-01 2011-04-01 false Regular current connection test. 216.13... ELIGIBILITY FOR AN ANNUITY Current Connection With the Railroad Industry § 216.13 Regular current connection test. An employee has a current connection with the railroad industry if he or she meets one of the...
20 CFR 216.13 - Regular current connection test.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Regular current connection test. 216.13... ELIGIBILITY FOR AN ANNUITY Current Connection With the Railroad Industry § 216.13 Regular current connection test. An employee has a current connection with the railroad industry if he or she meets one of the...
The residual method for regularizing ill-posed problems
Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar
2011-01-01
Although the residual method, or constrained regularization, is frequently used in applications, a detailed study of its properties is still missing. This sharply contrasts the progress of the theory of Tikhonov regularization, where a series of new results for regularization in Banach spaces has been published in the recent years. The present paper intends to bridge the gap between the existing theories as far as possible. We develop a stability and convergence theory for the residual method in general topological spaces. In addition, we prove convergence rates in terms of (generalized) Bregman distances, which can also be applied to non-convex regularization functionals. We provide three examples that show the applicability of our theory. The first example is the regularized solution of linear operator equations on Lp-spaces, where we show that the results of Tikhonov regularization generalize unchanged to the residual method. As a second example, we consider the problem of density estimation from a finite number of sampling points, using the Wasserstein distance as a fidelity term and an entropy measure as regularization term. It is shown that the densities obtained in this way depend continuously on the location of the sampled points and that the underlying density can be recovered as the number of sampling points tends to infinity. Finally, we apply our theory to compressed sensing. Here, we show the well-posedness of the method and derive convergence rates both for convex and non-convex regularization under rather weak conditions. PMID:22345828
47 CFR 76.614 - Cable television system regular monitoring.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 47 Telecommunication 4 2010-10-01 2010-10-01 false Cable television system regular monitoring. 76... SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Technical Standards § 76.614 Cable television system regular monitoring. Cable television operators transmitting carriers in the frequency bands 108...
47 CFR 76.614 - Cable television system regular monitoring.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 47 Telecommunication 4 2012-10-01 2012-10-01 false Cable television system regular monitoring. 76... SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Technical Standards § 76.614 Cable television system regular monitoring. Cable television operators transmitting carriers in the frequency bands 108...
47 CFR 76.614 - Cable television system regular monitoring.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 47 Telecommunication 4 2013-10-01 2013-10-01 false Cable television system regular monitoring. 76... SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Technical Standards § 76.614 Cable television system regular monitoring. Cable television operators transmitting carriers in the frequency bands 108...
47 CFR 76.614 - Cable television system regular monitoring.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 47 Telecommunication 4 2014-10-01 2014-10-01 false Cable television system regular monitoring. 76... SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Technical Standards § 76.614 Cable television system regular monitoring. Cable television operators transmitting carriers in the frequency bands 108...
Cognitive Aspects of Regularity Exhibit When Neighborhood Disappears
ERIC Educational Resources Information Center
Chen, Sau-Chin; Hu, Jon-Fan
2015-01-01
Although regularity refers to the compatibility between pronunciation of character and sound of phonetic component, it has been suggested as being part of consistency, which is defined by neighborhood characteristics. Two experiments demonstrate how regularity effect is amplified or reduced by neighborhood characteristics and reveals the…
Chimeric mitochondrial peptides from contiguous regular and swinger RNA.
Seligmann, Hervé
2016-01-01
Previous mass spectrometry analyses described human mitochondrial peptides entirely translated from swinger RNAs, RNAs where polymerization systematically exchanged nucleotides. Exchanges follow one among 23 bijective transformation rules, nine symmetric exchanges (X ↔ Y, e.g. A ↔ C) and fourteen asymmetric exchanges (X → Y → Z → X, e.g. A → C → G → A), multiplying by 24 DNA's protein coding potential. Abrupt switches from regular to swinger polymerization produce chimeric RNAs. Here, human mitochondrial proteomic analyses assuming abrupt switches between regular and swinger transcriptions, detect chimeric peptides, encoded by part regular, part swinger RNA. Contiguous regular- and swinger-encoded residues within single peptides are stronger evidence for translation of swinger RNA than previously detected, entirely swinger-encoded peptides: regular parts are positive controls matched with contiguous swinger parts, increasing confidence in results. Chimeric peptides are 200 × rarer than swinger peptides (3/100,000 versus 6/1000). Among 186 peptides with > 8 residues for each regular and swinger parts, regular parts of eleven chimeric peptides correspond to six among the thirteen recognized, mitochondrial protein-coding genes. Chimeric peptides matching partly regular proteins are rarer and less expressed than chimeric peptides matching non-coding sequences, suggesting targeted degradation of misfolded proteins. Present results strengthen hypotheses that the short mitogenome encodes far more proteins than hitherto assumed. Entirely swinger-encoded proteins could exist.
Comments on Regularization Ambiguities and Local Gauge Symmetries
NASA Astrophysics Data System (ADS)
Casana, R.; Pimentel, B. M.
We study the regularization ambiguities in an exact renormalized (1 +1)-dimensional field theory. We show a relation between the regularization ambiguities and the coupling parameters of the theory as well as their role in the implementation of a local gauge symmetry at quantum level.
Analysis of regularized Navier-Stokes equations, 2
NASA Technical Reports Server (NTRS)
Ou, Yuh-Roung; Sritharan, S. S.
1989-01-01
A practically important regularization of the Navier-Stokes equations was analyzed. As a continuation of the previous work, the structure of the attractors characterizing the solutins was studied. Local as well as global invariant manifolds were found. Regularity properties of these manifolds are analyzed.
Context-Sensitive Regularities in English Vowel Spelling.
ERIC Educational Resources Information Center
Aronoff, Mark; Koch, Eric
1996-01-01
Compares the predictive value of rime spellings in English to other types of regularities beyond the level of the single letter. Computer-analyzes a list of 24,000 written words, each paired with its corresponding pronunciation. Reveals that only a small number of rime spellings are highly regular in pronunciations. Suggests English spelling is…
Asymptotic inequalities on the parameters of a strongly regular graph
NASA Astrophysics Data System (ADS)
Vieira, Luís António de Almeida
2017-07-01
We first consider a strongly regular G whose adjacency matrix is A, next we associate a real three dimensional Euclidean Jordan algebra 𝒜 with rank three to the matrix A. Finally, from the analyze of the spectra of a binomial Hadamard Series of an element of 𝒜 we establish asymptotical inequalities on the parameters of a strongly regular graph.
29 CFR 778.500 - Artificial regular rates.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 29 Labor 3 2012-07-01 2012-07-01 false Artificial regular rates. 778.500 Section 778.500 Labor... Circumvent the Act Devices to Evade the Overtime Requirements § 778.500 Artificial regular rates. (a) Since... of his compensation. Payment for overtime on the basis of an artificial “regular” rate will...
29 CFR 778.500 - Artificial regular rates.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 29 Labor 3 2013-07-01 2013-07-01 false Artificial regular rates. 778.500 Section 778.500 Labor... Circumvent the Act Devices to Evade the Overtime Requirements § 778.500 Artificial regular rates. (a) Since... of his compensation. Payment for overtime on the basis of an artificial “regular” rate will...
29 CFR 778.500 - Artificial regular rates.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 29 Labor 3 2010-07-01 2010-07-01 false Artificial regular rates. 778.500 Section 778.500 Labor... Circumvent the Act Devices to Evade the Overtime Requirements § 778.500 Artificial regular rates. (a) Since... of his compensation. Payment for overtime on the basis of an artificial “regular” rate will...
29 CFR 778.500 - Artificial regular rates.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 29 Labor 3 2014-07-01 2014-07-01 false Artificial regular rates. 778.500 Section 778.500 Labor... Circumvent the Act Devices to Evade the Overtime Requirements § 778.500 Artificial regular rates. (a) Since... of his compensation. Payment for overtime on the basis of an artificial “regular” rate will...
29 CFR 778.500 - Artificial regular rates.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 29 Labor 3 2011-07-01 2011-07-01 false Artificial regular rates. 778.500 Section 778.500 Labor... Circumvent the Act Devices to Evade the Overtime Requirements § 778.500 Artificial regular rates. (a) Since... of his compensation. Payment for overtime on the basis of an artificial “regular” rate will...
29 CFR 553.233 - “Regular rate” defined.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 29 Labor 3 2014-07-01 2014-07-01 false âRegular rateâ defined. 553.233 Section 553.233 Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR REGULATIONS APPLICATION... Enforcement Employees of Public Agencies Overtime Compensation Rules § 553.233 “Regular rate” defined. The...
29 CFR 553.233 - “Regular rate” defined.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 29 Labor 3 2012-07-01 2012-07-01 false âRegular rateâ defined. 553.233 Section 553.233 Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR REGULATIONS APPLICATION... Enforcement Employees of Public Agencies Overtime Compensation Rules § 553.233 “Regular rate” defined. The...
29 CFR 553.233 - “Regular rate” defined.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 29 Labor 3 2013-07-01 2013-07-01 false âRegular rateâ defined. 553.233 Section 553.233 Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR REGULATIONS APPLICATION... Enforcement Employees of Public Agencies Overtime Compensation Rules § 553.233 “Regular rate” defined. The...
39 CFR 3010.7 - Schedule of regular rate changes.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 39 Postal Service 1 2010-07-01 2010-07-01 false Schedule of regular rate changes. 3010.7 Section... PRODUCTS General Provisions § 3010.7 Schedule of regular rate changes. (a) The Postal Service shall... estimated implementation dates for future Type 1-A rate changes for each separate class of mail, should...
Fundamental and Regular Elementary Schools: Do Differences Exist?
ERIC Educational Resources Information Center
Weber, Larry J.; And Others
This study compared the academic achievement and other outcomes of three public fundamental elementary schools with three regular elementary schools in a metropolitan school district. Modeled after the John Marshal Fundamental School in Pasadena, California, which opened in the fall of 1973, fundamental schools differ from regular schools in that…
Cognitive Aspects of Regularity Exhibit When Neighborhood Disappears
ERIC Educational Resources Information Center
Chen, Sau-Chin; Hu, Jon-Fan
2015-01-01
Although regularity refers to the compatibility between pronunciation of character and sound of phonetic component, it has been suggested as being part of consistency, which is defined by neighborhood characteristics. Two experiments demonstrate how regularity effect is amplified or reduced by neighborhood characteristics and reveals the…
29 CFR 778.408 - The specified regular rate.
Code of Federal Regulations, 2014 CFR
2014-07-01
... employee's compensation. Suppose, for example, that the compensation of an employee is normally made up in...) with an employee whose regular weekly earnings are made up in part by the payment of regular bonuses... compensation, over and above the guaranteed amount, by way of extra premiums for work on holidays, or...
20 CFR 216.13 - Regular current connection test.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 20 Employees' Benefits 1 2014-04-01 2012-04-01 true Regular current connection test. 216.13... ELIGIBILITY FOR AN ANNUITY Current Connection With the Railroad Industry § 216.13 Regular current connection test. An employee has a current connection with the railroad industry if he or she meets one of the...
20 CFR 216.13 - Regular current connection test.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 20 Employees' Benefits 1 2012-04-01 2012-04-01 false Regular current connection test. 216.13... ELIGIBILITY FOR AN ANNUITY Current Connection With the Railroad Industry § 216.13 Regular current connection test. An employee has a current connection with the railroad industry if he or she meets one of the...
20 CFR 216.13 - Regular current connection test.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 20 Employees' Benefits 1 2013-04-01 2012-04-01 true Regular current connection test. 216.13... ELIGIBILITY FOR AN ANNUITY Current Connection With the Railroad Industry § 216.13 Regular current connection test. An employee has a current connection with the railroad industry if he or she meets one of the...
Nonconvex regularizations in fluorescence molecular tomography for sparsity enhancement
NASA Astrophysics Data System (ADS)
Zhu, Dianwen; Li, Changqing
2014-06-01
In vivo fluorescence imaging has been a popular functional imaging modality in preclinical imaging. Near infrared probes used in fluorescence molecular tomography (FMT) are designed to localize in the targeted tissues, hence sparse solution to the FMT image reconstruction problem is preferred. Nonconvex regularization methods are reported to enhance sparsity in the fields of statistical learning, compressed sensing etc. We investigated such regularization methods in FMT for small animal imaging with numerical simulations and phantom experiments. We adopted a majorization-minimization algorithm for the iterative reconstruction process and compared the reconstructed images using our proposed nonconvex regularizations with those using the well known L1 regularization. We found that the proposed nonconvex methods outperform L1 regularization in accurately recovering sparse targets in FMT.
Regular expression order-sorted unification and matching
Kutsia, Temur; Marin, Mircea
2015-01-01
We extend order-sorted unification by permitting regular expression sorts for variables and in the domains of function symbols. The obtained signature corresponds to a finite bottom-up unranked tree automaton. We prove that regular expression order-sorted (REOS) unification is of type infinitary and decidable. The unification problem presented by us generalizes some known problems, such as, e.g., order-sorted unification for ranked terms, sequence unification, and word unification with regular constraints. Decidability of REOS unification implies that sequence unification with regular hedge language constraints is decidable, generalizing the decidability result of word unification with regular constraints to terms. A sort weakening algorithm helps to construct a minimal complete set of REOS unifiers from the solutions of sequence unification problems. Moreover, we design a complete algorithm for REOS matching, and show that this problem is NP-complete and the corresponding counting problem is #P-complete. PMID:26523088
Learning rates of lq coefficient regularization learning with gaussian kernel.
Lin, Shaobo; Zeng, Jinshan; Fang, Jian; Xu, Zongben
2014-10-01
Regularization is a well-recognized powerful strategy to improve the performance of a learning machine and l(q) regularization schemes with 0 < q < ∞ are central in use. It is known that different q leads to different properties of the deduced estimators, say, l(2) regularization leads to a smooth estimator, while l(1) regularization leads to a sparse estimator. Then how the generalization capability of l(q) regularization learning varies with q is worthy of investigation. In this letter, we study this problem in the framework of statistical learning theory. Our main results show that implementing l(q) coefficient regularization schemes in the sample-dependent hypothesis space associated with a gaussian kernel can attain the same almost optimal learning rates for all 0 < q < ∞. That is, the upper and lower bounds of learning rates for l(q) regularization learning are asymptotically identical for all 0 < q < ∞. Our finding tentatively reveals that in some modeling contexts, the choice of q might not have a strong impact on the generalization capability. From this perspective, q can be arbitrarily specified, or specified merely by other nongeneralization criteria like smoothness, computational complexity or sparsity.
Learning regularization parameters for general-form Tikhonov
NASA Astrophysics Data System (ADS)
Chung, Julianne; Español, Malena I.
2017-07-01
Computing regularization parameters for general-form Tikhonov regularization can be an expensive and difficult task, especially if multiple parameters or many solutions need to be computed in real time. In this work, we assume training data is available and describe an efficient learning approach for computing regularization parameters that can be used for a large set of problems. We consider an empirical Bayes risk minimization framework for finding regularization parameters that minimize average errors for the training data. We first extend methods from Chung et al (2011 SIAM J. Sci. Comput. 33 3132-52) to the general-form Tikhonov problem. Then we develop a learning approach for multi-parameter Tikhonov problems, for the case where all involved matrices are simultaneously diagonalizable. For problems where this is not the case, we describe an approach to compute near-optimal regularization parameters by using operator approximations for the original problem. Finally, we propose a new class of regularizing filters, where solutions correspond to multi-parameter Tikhonov solutions, that requires less data than previously proposed optimal error filters, avoids the generalized SVD, and allows flexibility and novelty in the choice of regularization matrices. Numerical results for 1D and 2D examples using different norms on the errors show the effectiveness of our methods.
Two hybrid regularization frameworks for solving the electrocardiography inverse problem.
Jiang, Mingfeng; Xia, Ling; Shou, Guofa; Liu, Feng; Crozier, Stuart
2008-09-21
In this paper, two hybrid regularization frameworks, LSQR-Tik and Tik-LSQR, which integrate the properties of the direct regularization method (Tikhonov) and the iterative regularization method (LSQR), have been proposed and investigated for solving ECG inverse problems. The LSQR-Tik method is based on the Lanczos process, which yields a sequence of small bidiagonal systems to approximate the original ill-posed problem and then the Tikhonov regularization method is applied to stabilize the projected problem. The Tik-LSQR method is formulated as an iterative LSQR inverse, augmented with a Tikhonov-like prior information term. The performances of these two hybrid methods are evaluated using a realistic heart-torso model simulation protocol, in which the heart surface source method is employed to calculate the simulated epicardial potentials (EPs) from the action potentials (APs), and then the acquired EPs are used to calculate simulated body surface potentials (BSPs). The results show that the regularized solutions obtained by the LSQR-Tik method are approximate to those of the Tikhonov method, the computational cost of the LSQR-Tik method, however, is much less than that of the Tikhonov method. Moreover, the Tik-LSQR scheme can reconstruct the epcicardial potential distribution more accurately, specifically for the BSPs with large noisy cases. This investigation suggests that hybrid regularization methods may be more effective than separate regularization approaches for ECG inverse problems.
Semisupervised Support Vector Machines With Tangent Space Intrinsic Manifold Regularization.
Sun, Shiliang; Xie, Xijiong
2016-09-01
Semisupervised learning has been an active research topic in machine learning and data mining. One main reason is that labeling examples is expensive and time-consuming, while there are large numbers of unlabeled examples available in many practical problems. So far, Laplacian regularization has been widely used in semisupervised learning. In this paper, we propose a new regularization method called tangent space intrinsic manifold regularization. It is intrinsic to data manifold and favors linear functions on the manifold. Fundamental elements involved in the formulation of the regularization are local tangent space representations, which are estimated by local principal component analysis, and the connections that relate adjacent tangent spaces. Simultaneously, we explore its application to semisupervised classification and propose two new learning algorithms called tangent space intrinsic manifold regularized support vector machines (TiSVMs) and tangent space intrinsic manifold regularized twin SVMs (TiTSVMs). They effectively integrate the tangent space intrinsic manifold regularization consideration. The optimization of TiSVMs can be solved by a standard quadratic programming, while the optimization of TiTSVMs can be solved by a pair of standard quadratic programmings. The experimental results of semisupervised classification problems show the effectiveness of the proposed semisupervised learning algorithms.
Encoding of configural regularity in the human visual system.
Kubilius, Jonas; Wagemans, Johan; Op de Beeck, Hans P
2014-08-13
The visual system is very efficient in encoding stimulus properties by utilizing available regularities in the inputs. To explore the underlying encoding strategies during visual information processing, we presented participants with two-line configurations that varied in the amount of configural regularity (or degrees of freedom in the relative positioning of the two lines) in a fMRI experiment. Configural regularity ranged from a generic configuration to stimuli resembling an "L" (i.e., a right-angle L-junction), a "T" (i.e., a right-angle midpoint T-junction), or a "+",-the latter being the most regular stimulus. We found that the response strength in the shape-selective lateral occipital area was consistently lower for a higher degree of regularity in the stimuli. In the second experiment, using multivoxel pattern analysis, we further show that regularity is encoded in terms of the fMRI signal strength but not in the distributed pattern of responses. Finally, we found that the results of these experiments could not be accounted for by low-level stimulus properties and are distinct from norm-based encoding. Our results suggest that regularity plays an important role in stimulus encoding in the ventral visual processing stream.
Regular Patterns in Cerebellar Purkinje Cell Simple Spike Trains
Shin, Soon-Lim; Hoebeek, Freek E.; Schonewille, Martijn; De Zeeuw, Chris I.; Aertsen, Ad; De Schutter, Erik
2007-01-01
Background Cerebellar Purkinje cells (PC) in vivo are commonly reported to generate irregular spike trains, documented by high coefficients of variation of interspike-intervals (ISI). In strong contrast, they fire very regularly in the in vitro slice preparation. We studied the nature of this difference in firing properties by focusing on short-term variability and its dependence on behavioral state. Methodology/Principal Findings Using an analysis based on CV2 values, we could isolate precise regular spiking patterns, lasting up to hundreds of milliseconds, in PC simple spike trains recorded in both anesthetized and awake rodents. Regular spike patterns, defined by low variability of successive ISIs, comprised over half of the spikes, showed a wide range of mean ISIs, and were affected by behavioral state and tactile stimulation. Interestingly, regular patterns often coincided in nearby Purkinje cells without precise synchronization of individual spikes. Regular patterns exclusively appeared during the up state of the PC membrane potential, while single ISIs occurred both during up and down states. Possible functional consequences of regular spike patterns were investigated by modeling the synaptic conductance in neurons of the deep cerebellar nuclei (DCN). Simulations showed that these regular patterns caused epochs of relatively constant synaptic conductance in DCN neurons. Conclusions/Significance Our findings indicate that the apparent irregularity in cerebellar PC simple spike trains in vivo is most likely caused by mixing of different regular spike patterns, separated by single long intervals, over time. We propose that PCs may signal information, at least in part, in regular spike patterns to downstream DCN neurons. PMID:17534435
Generalization Performance of Regularized Ranking With Multiscale Kernels.
Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin
2016-05-01
The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.
Exploring the spectrum of regularized bosonic string theory
Ambjørn, J. Makeenko, Y.
2015-03-15
We implement a UV regularization of the bosonic string by truncating its mode expansion and keeping the regularized theory “as diffeomorphism invariant as possible.” We compute the regularized determinant of the 2d Laplacian for the closed string winding around a compact dimension, obtaining the effective action in this way. The minimization of the effective action reliably determines the energy of the string ground state for a long string and/or for a large number of space-time dimensions. We discuss the possibility of a scaling limit when the cutoff is taken to infinity.
Iterative regularization and adaptivity for an electromagnetic coefficient inverse problem
NASA Astrophysics Data System (ADS)
Malmberg, John Bondestam; Beilina, Larisa
2017-07-01
We study how the choice of the regularization parameter affects the quality of the reconstruction of the dielectric permittivity for an inhomogeneous medium, with data consisting of boundary observations of the electric field. Our method is based on the minimization of a Tikhonov functional and uses a finite element method for computations of the electric field. We conclude that the choice of the regularization parameter does not affect the quality of the reconstruction significantly in the studied cases, and can even be removed with results not significantly different from those with regularization.
Structural source identification using a generalized Tikhonov regularization
NASA Astrophysics Data System (ADS)
Aucejo, M.
2014-10-01
This paper addresses the problem of identifying mechanical exciting forces from vibration measurements. The proposed approach is based on a generalized Tikhonov regularization that allows taking into account prior information on the measurement noise as well as on the main characteristics of sources to identify like its sparsity or regularity. To solve such a regularization problem efficiently, a Generalized Iteratively Reweighted Least-Squares (GIRLS) algorithm is introduced. Proposed numerical and experimental validations reveal the crucial role of prior information in the quality of the source identification and the performance of the GIRLS algorithm.
Universality in the flooding of regular islands by chaotic states.
Bäcker, Arnd; Ketzmerick, Roland; Monastra, Alejandro G
2007-06-01
We investigate the structure of eigenstates in systems with a mixed phase space in terms of their projection onto individual regular tori. Depending on dynamical tunneling rates and the Heisenberg time, regular states disappear and chaotic states flood the regular tori. For a quantitative understanding we introduce a random matrix model. The resulting statistical properties of eigenstates as a function of an effective coupling strength are in very good agreement with numerical results for a kicked system. We discuss the implications of these results for the applicability of the semiclassical eigenfunction hypothesis.
Bias-Variance Tradeoff of Graph Laplacian Regularizer
NASA Astrophysics Data System (ADS)
Chen, Pin-Yu; Liu, Sijia
2017-08-01
This paper presents a bias-variance tradeoff of graph Laplacian regularizer, which is widely used in graph signal processing and semi-supervised learning tasks. The scaling law of the optimal regularization parameter is specified in terms of the spectral graph properties and a novel signal-to-noise ratio parameter, which suggests selecting a mediocre regularization parameter is often suboptimal. The analysis is applied to three applications, including random, band-limited, and multiple-sampled graph signals. Experiments on synthetic and real-world graphs demonstrate near-optimal performance of the established analysis.
Blind image deblurring with edge enhancing total variation regularization
NASA Astrophysics Data System (ADS)
Shi, Yu; Hong, Hanyu; Song, Jie; Hua, Xia
2015-04-01
Blind image deblurring is an important issue. In this paper, we focus on solving this issue by constrained regularization method. Motivated by the importance of edges to visual perception, the edge-enhancing indicator is introduced to constrain the total variation regularization, and the bilateral filter is used for edge-preserving smoothing. The proposed edge enhancing regularization method aims to smooth preferably within each region and preserve edges. Experiments on simulated and real motion blurred images show that the proposed method is competitive with recent state-of-the-art total variation methods.
Some results on the spectra of strongly regular graphs
NASA Astrophysics Data System (ADS)
Vieira, Luís António de Almeida; Mano, Vasco Moço
2016-06-01
Let G be a strongly regular graph whose adjacency matrix is A. We associate a real finite dimensional Euclidean Jordan algebra 𝒱, of rank three to the strongly regular graph G, spanned by I and the natural powers of A, endowed with the Jordan product of matrices and with the inner product as being the usual trace of matrices. Finally, by the analysis of the binomial Hadamard series of an element of 𝒱, we establish some inequalities on the parameters and on the spectrum of a strongly regular graph like those established in theorems 3 and 4.
Quaternion regularization and stabilization of perturbed central motion. II
NASA Astrophysics Data System (ADS)
Chelnokov, Yu. N.
1993-04-01
Generalized regular quaternion equations for the three-dimensional two-body problem in terms of Kustaanheimo-Stiefel variables are obtained within the framework of the quaternion theory of regularizing and stabilizing transformations of the Newtonian equations for perturbed central motion. Regular quaternion equations for perturbed central motion of a material point in a central field with a certain potential Pi are also derived in oscillatory and normal forms. In addition, systems of perturbed central motion equations are obtained which include quaternion equations of perturbed orbit orientations in oscillatory or normal form, and a generalized Binet equation is derived. A comparative analysis of the equations is carried out.
Low-Rank Matrix Factorization With Adaptive Graph Regularizer.
Lu, Gui-Fu; Wang, Yong; Zou, Jian
2016-05-01
In this paper, we present a novel low-rank matrix factorization algorithm with adaptive graph regularizer (LMFAGR). We extend the recently proposed low-rank matrix with manifold regularization (MMF) method with an adaptive regularizer. Different from MMF, which constructs an affinity graph in advance, LMFAGR can simultaneously seek graph weight matrix and low-dimensional representations of data. That is, graph construction and low-rank matrix factorization are incorporated into a unified framework, which results in an automatically updated graph rather than a predefined one. The experimental results on some data sets demonstrate that the proposed algorithm outperforms the state-of-the-art low-rank matrix factorization methods.
29 CFR 541.701 - Customarily and regularly.
Code of Federal Regulations, 2010 CFR
2010-07-01
... DELIMITING THE EXEMPTIONS FOR EXECUTIVE, ADMINISTRATIVE, PROFESSIONAL, COMPUTER AND OUTSIDE SALES EMPLOYEES Definitions and Miscellaneous Provisions § 541.701 Customarily and regularly. The phrase “customarily and...
Regularized Chapman-Enskog expansion for scalar conservation laws
NASA Technical Reports Server (NTRS)
Schochet, Steven; Tadmor, Eitan
1990-01-01
Rosenau has recently proposed a regularized version of the Chapman-Enskog expansion of hydrodynamics. This regularized expansion resembles the usual Navier-Stokes viscosity terms at law wave-numbers, but unlike the latter, it has the advantage of being a bounded macroscopic approximation to the linearized collision operator. The behavior of Rosenau regularization of the Chapman-Enskog expansion (RCE) is studied in the context of scalar conservation laws. It is shown that thie RCE model retains the essential properties of the usual viscosity approximation, e.g., existence of traveling waves, monotonicity, upper-Lipschitz continuity..., and at the same time, it sharpens the standard viscous shock layers. It is proved that the regularized RCE approximation converges to the underlying inviscid entropy solution as its mean-free-path epsilon approaches 0, and the convergence rate is estimated.
On almost regularity and π-normality of topological spaces
NASA Astrophysics Data System (ADS)
Saad Thabit, Sadeq Ali; Kamarulhaili, Hailiza
2012-05-01
π-Normality is a weaker version of normality. It was introduced by Kalantan in 2008. π-Normality lies between normality and almost normality (resp. quasi-normality). The importance of this topological property is that it behaves slightly different from normality and almost normality (quasi-normality). π-Normality is neither a productive nor a hereditary property in general. In this paper, some properties of almost regular spaces are presented. In particular, a few results on almost regular spaces are improved. Some relationships between almost regularity and π-normality are presented. π-Generalized closed sets are used to obtain a characterization and preservation theorems of π-normal spaces. Also, we investigate that an almost regular Lindelöf space (resp. with σ-locally finite base) is not necessarily π-normal by giving two counterexamples. An almost normality of the Rational Sequence topology is proved.
Lipschitz regularity results for nonlinear strictly elliptic equations and applications
NASA Astrophysics Data System (ADS)
Ley, Olivier; Nguyen, Vinh Duc
2017-10-01
Most of Lipschitz regularity results for nonlinear strictly elliptic equations are obtained for a suitable growth power of the nonlinearity with respect to the gradient variable (subquadratic for instance). For equations with superquadratic growth power in gradient, one usually uses weak Bernstein-type arguments which require regularity and/or convex-type assumptions on the gradient nonlinearity. In this article, we obtain new Lipschitz regularity results for a large class of nonlinear strictly elliptic equations with possibly arbitrary growth power of the Hamiltonian with respect to the gradient variable using some ideas coming from Ishii-Lions' method. We use these bounds to solve an ergodic problem and to study the regularity and the large time behavior of the solution of the evolution equation.
5 CFR 550.1307 - Authority to regularize paychecks.
Code of Federal Regulations, 2011 CFR
2011-01-01
... caused by work scheduling cycles that result in varying hours in the firefighters' tours of duty from pay... for regular tours of duty over the firefighter's entire work scheduling cycle must, to the extent...
Automatic Constraint Detection for 2D Layout Regularization.
Jiang, Haiyong; Nan, Liangliang; Yan, Dong-Ming; Dong, Weiming; Zhang, Xiaopeng; Wonka, Peter
2016-08-01
In this paper, we address the problem of constraint detection for layout regularization. The layout we consider is a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important in digitizing plans or images, such as floor plans and facade images, and in the improvement of user-created contents, such as architectural drawings and slide layouts. To regularize a layout, we aim to improve the input by detecting and subsequently enforcing alignment, size, and distance constraints between layout elements. Similar to previous work, we formulate layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm that automatically detects constraints. We evaluate the proposed framework using a variety of input layouts from different applications. Our results demonstrate that our method has superior performance to the state of the art.
Photon-limited depth and reflectivity imaging with sparsity regularization
NASA Astrophysics Data System (ADS)
Yan, Kang; Lifei, Li; Xuejie, Duan; Tongyi, Zhang; Dongjian, Li; Wei, Zhao
2017-06-01
We demonstrate a depth and reflectivity imaging system at low light level based on sparsity regularization method. Depth and reflectivity imaging from the time-correlated single photon counting (TCSPC) measurement in limit of few photon counts are reconstructed through exploiting transform-domain sparsity. Two different sparsity-based penalty function: total variation (TV) penalty and l1 norm penalty measuring sparsity in the discrete cosine transform(DCT) basis, are applied to the experimental data. The results show that compared with traditional image denoising method, sparsity regularization approach achieves better accuracy with fewer photon measurements. Further more, the performance of TV regularization is proved better than l1-DCT regularization method for photon-limited imaging at first time, especially in the case of depth imaging. Our system is a photon-limited imaging device for a variety of applications, such as target detection, space surveillance, and distance measurement.
Thermodynamical Stability of a New Regular Black Hole
NASA Astrophysics Data System (ADS)
Saadat, Hassan
2013-09-01
In this paper we consider a new regular black hole and calculate thermodynamical variables such as entropy, specific heat and free energy. Then we study thermodynamical stability of this black hole by using the specific heat in constant volume.
Simple Constructions for the Regular Pentagon and Heptadecagon.
ERIC Educational Resources Information Center
DeTemple, Duane W.
1989-01-01
Discussed are two Euclidean constructions (synthetic approach and coordinate method) to inscribe regular polygons of 5 and 17 sides in a circle. Each step of the constructions is described using diagrams and mathematical expressions. (YP)
A novel regularized edge-preserving super-resolution algorithm
NASA Astrophysics Data System (ADS)
Yu, Hui; Chen, Fu-sheng; Zhang, Zhi-jie; Wang, Chen-sheng
2013-09-01
Using super-resolution (SR) technology is a good approach to obtain high-resolution infrared image. However, Image super-resolution reconstruction is essentially an ill-posed problem, it is important to design an effective regularization term (image prior). Gaussian prior is widely used in the regularization term, but the reconstructed SR image becomes over-smoothness. Here, a novel regularization term called non-local means (NLM) term is derived based on the assumption that the natural image content is likely to repeat itself within some neighborhood. In the proposed framework, the estimated high image is obtained by minimizing a cost function. The iteration method is applied to solve the optimum problem. With the progress of iteration, the regularization term is adaptively updated. The proposed algorithm has been tested in several experiments. The experimental results show that the proposed approach is robust and can reconstruct higher quality images both in quantitative term and perceptual effect.
Spelling-stress regularity effects are intact in developmental dyslexia.
Mundy, Ian R; Carroll, Julia M
2013-01-01
The current experiment investigated conflicting predictions regarding the effects of spelling-stress regularity on the lexical decision performance of skilled adult readers and adults with developmental dyslexia. In both reading groups, lexical decision responses were significantly faster and significantly more accurate when the orthographic structure of a word ending was a reliable as opposed to an unreliable predictor of lexical stress assignment. Furthermore, the magnitude of this spelling-stress regularity effect was found to be equivalent across reading groups. These findings are consistent with intact phoneme-level regularity effects also observed in dyslexia. The paper discusses how findings of intact spelling-sound regularity effects at both prosodic and phonemic levels, as well as other similar results, can be reconciled with the obvious difficulties that people with dyslexia experience in other domains of phonological processing.
Many Under 40 May Not Need Regular Cholesterol Checks
... fullstory_165582.html Many Under 40 May Not Need Regular Cholesterol Checks: Study But heart experts note ... HealthDay News) -- Many adults under 40 may not need to have routine cholesterol screenings, a new study ...
Are Pupils in Special Education Too "Special" for Regular Education?
NASA Astrophysics Data System (ADS)
Pijl, Ysbrand J.; Pijl, Sip J.
1998-01-01
In the Netherlands special needs pupils are often referred to separate schools for the Educable Mentally Retarded (EMR) or the Learning Disabled (LD). There is an ongoing debate on how to reduce the growing numbers of special education placements. One of the main issues in this debate concerns the size of the difference in cognitive abilities between pupils in regular education and those eligible for LD or EMR education. In this study meta-analysis techniques were used to synthesize the findings from 31 studies on differences between pupils in regular primary education and those in special education in the Netherlands. Studies were grouped into three categories according to the type of measurements used: achievement, general intelligence and neuropsychological tests. It was found that pupils in regular education and those in special education differ in achievement and general intelligence. Pupils in schools for the educable mentally retarded in particular perform at a much lower level than is common in regular Dutch primary education.
Mini-Stroke vs. Regular Stroke: What's the Difference?
... How is a ministroke different from a regular stroke? Answers from Jerry W. Swanson, M.D. When ... brain, spinal cord or retina, which may cause stroke-like symptoms but does not damage brain cells ...
Loop Invariants, Exploration of Regularities, and Mathematical Games.
ERIC Educational Resources Information Center
Ginat, David
2001-01-01
Presents an approach for illustrating, on an intuitive level, the significance of loop invariants for algorithm design and analysis. The illustration is based on mathematical games that require the exploration of regularities via problem-solving heuristics. (Author/MM)
Deaths in the UK Regular Armed Forces 2006
2007-03-30
DEATHS IN THE UK REGULAR ARMED FORCES 2006 INTRODUCTION • This National Statistic Notice provides summary statistics on deaths in 2006...categories of cause of death for 2006 (Table 2 and Figure 2). • Several changes have been made in the presentation of data from previous years. As...the Brigade of Gurkhas is part of the regular Army this Notice has been amended to include both the numbers of deaths for Gurkhas and the age
Borderline personality disorder and regularly drinking alcohol before sex.
Thompson, Ronald G; Eaton, Nicholas R; Hu, Mei-Chen; Hasin, Deborah S
2017-07-01
Drinking alcohol before sex increases the likelihood of engaging in unprotected intercourse, having multiple sexual partners and becoming infected with sexually transmitted infections. Borderline personality disorder (BPD), a complex psychiatric disorder characterised by pervasive instability in emotional regulation, self-image, interpersonal relationships and impulse control, is associated with substance use disorders and sexual risk behaviours. However, no study has examined the relationship between BPD and drinking alcohol before sex in the USA. This study examined the association between BPD and regularly drinking before sex in a nationally representative adult sample. Participants were 17 491 sexually active drinkers from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. Logistic regression models estimated effects of BPD diagnosis, specific borderline diagnostic criteria and BPD criterion count on the likelihood of regularly (mostly or always) drinking alcohol before sex, adjusted for controls. Borderline personality disorder diagnosis doubled the odds of regularly drinking before sex [adjusted odds ratio (AOR) = 2.26; confidence interval (CI) = 1.63, 3.14]. Of nine diagnostic criteria, impulsivity in areas that are self-damaging remained a significant predictor of regularly drinking before sex (AOR = 1.82; CI = 1.42, 2.35). The odds of regularly drinking before sex increased by 20% for each endorsed criterion (AOR = 1.20; CI = 1.14, 1.27) DISCUSSION AND CONCLUSIONS: This is the first study to examine the relationship between BPD and regularly drinking alcohol before sex in the USA. Substance misuse treatment should assess regularly drinking before sex, particularly among patients with BPD, and BPD treatment should assess risk at the intersection of impulsivity, sexual behaviour and substance use. [Thompson Jr RG, Eaton NR, Hu M-C, Hasin DS Borderline personality disorder and regularly drinking alcohol
Regular satellite formation and evolution in a dead zone
NASA Astrophysics Data System (ADS)
Chen, Cheng; Martin, Rebecca G.
2017-01-01
The dead zone in a circumplanetary disk is a non-turbulent region at the disk midplane that is an ideal location for regular satellite formation. The lower viscosity in the dead zone allows small objects to accrete and grow. We model the evolution of a circumplanetary disk with a dead zone for a range of disk and dead zone parameters. We investigate how these affect the formation and subsequent evolution of regular satellites that form in the disk.
Two-dimensional chiral anomaly in differential regularization
NASA Astrophysics Data System (ADS)
Chen, W. F.
1999-07-01
The two-dimensional chiral anomaly is calculated using differential regularization. It is shown that the anomaly emerges naturally in the vector and axial Ward identities on the same footing as the four-dimensional case. The vector gauge symmetry can be achieved by an appropriate choice of the mass scales without introducing the seagull term. We have analyzed the reason why such a universal result can be obtained in differential regularization.
On maximal parabolic regularity for non-autonomous parabolic operators
NASA Astrophysics Data System (ADS)
Disser, Karoline; ter Elst, A. F. M.; Rehberg, Joachim
2017-02-01
We consider linear inhomogeneous non-autonomous parabolic problems associated to sesquilinear forms, with discontinuous dependence of time. We show that for these problems, the property of maximal parabolic regularity can be extrapolated to time integrability exponents r ≠ 2. This allows us to prove maximal parabolic Lr-regularity for discontinuous non-autonomous second-order divergence form operators in very general geometric settings and to prove existence results for related quasilinear equations.
The relationship between lifestyle regularity and subjective sleep quality
NASA Technical Reports Server (NTRS)
Monk, Timothy H.; Reynolds, Charles F 3rd; Buysse, Daniel J.; DeGrazia, Jean M.; Kupfer, David J.
2003-01-01
In previous work we have developed a diary instrument-the Social Rhythm Metric (SRM), which allows the assessment of lifestyle regularity-and a questionnaire instrument--the Pittsburgh Sleep Quality Index (PSQI), which allows the assessment of subjective sleep quality. The aim of the present study was to explore the relationship between lifestyle regularity and subjective sleep quality. Lifestyle regularity was assessed by both standard (SRM-17) and shortened (SRM-5) metrics; subjective sleep quality was assessed by the PSQI. We hypothesized that high lifestyle regularity would be conducive to better sleep. Both instruments were given to a sample of 100 healthy subjects who were studied as part of a variety of different experiments spanning a 9-yr time frame. Ages ranged from 19 to 49 yr (mean age: 31.2 yr, s.d.: 7.8 yr); there were 48 women and 52 men. SRM scores were derived from a two-week diary. The hypothesis was confirmed. There was a significant (rho = -0.4, p < 0.001) correlation between SRM (both metrics) and PSQI, indicating that subjects with higher levels of lifestyle regularity reported fewer sleep problems. This relationship was also supported by a categorical analysis, where the proportion of "poor sleepers" was doubled in the "irregular types" group as compared with the "non-irregular types" group. Thus, there appears to be an association between lifestyle regularity and good sleep, though the direction of causality remains to be tested.
An information approach to regularization parameter selection under model misspecification
NASA Astrophysics Data System (ADS)
Urmanov, A. M.; Gribok, A. V.; Hines, J. W.; Uhrig, R. E.
2002-10-01
We review the information approach to regularization parameter selection and its information complexity extension for the solution of discrete ill posed problems. An information criterion for regularization parameter selection was first proposed by Shibata in the context of ridge regression as an extension of Takeuchi's information criterion. In the information approach, the regularization parameter value is chosen to maximize the mean expected log likelihood (MELL) of a model whose parameters are estimated using the maximum penalized likelihood method. Under the Gaussian noise assumption such a choice coincides with the minimum of mean predictive error choice. Maximization of the MELL corresponds to minimization of the mean Kullback-Leibler information, that measures the deviation of the approximating (model) distribution from the true one. The resulting regularization parameter selection methods can handle possible functional and distributional misspecifications when the usual assumptions of Gaussian noise and/or linear relationship have been made but not met. We also suggest that in engineering applications it is beneficial to find ways of lowering the risk of getting grossly under-regularized solutions and that the new information complexity regularization parameter selection method (RPSM) is one of the possibilities. Several examples of applying the reviewed RPSMs are given.
Iterative CT reconstruction using shearlet-based regularization
NASA Astrophysics Data System (ADS)
Vandeghinste, Bert; Goossens, Bart; Van Holen, Roel; Vanhove, Christian; Pizurica, Aleksandra; Vandenberghe, Stefaan; Staelens, Steven
2012-03-01
In computerized tomography, it is important to reduce the image noise without increasing the acquisition dose. Extensive research has been done into total variation minimization for image denoising and sparse-view reconstruction. However, TV minimization methods show superior denoising performance for simple images (with little texture), but result in texture information loss when applied to more complex images. Since in medical imaging, we are often confronted with textured images, it might not be beneficial to use TV. Our objective is to find a regularization term outperforming TV for sparse-view reconstruction and image denoising in general. A recent efficient solver was developed for convex problems, based on a split-Bregman approach, able to incorporate regularization terms different from TV. In this work, a proof-of-concept study demonstrates the usage of the discrete shearlet transform as a sparsifying transform within this solver for CT reconstructions. In particular, the regularization term is the 1-norm of the shearlet coefficients. We compared our newly developed shearlet approach to traditional TV on both sparse-view and on low-count simulated and measured preclinical data. Shearlet-based regularization does not outperform TV-based regularization for all datasets. Reconstructed images exhibit small aliasing artifacts in sparse-view reconstruction problems, but show no staircasing effect. This results in a slightly higher resolution than with TV-based regularization.
Regularity criteria for incompressible magnetohydrodynamics equations in three dimensions
NASA Astrophysics Data System (ADS)
Lin, Hongxia; Du, Lili
2013-01-01
In this paper, we give some new global regularity criteria for three-dimensional incompressible magnetohydrodynamics (MHD) equations. More precisely, we provide some sufficient conditions in terms of the derivatives of the velocity or pressure, for the global regularity of strong solutions to 3D incompressible MHD equations in the whole space, as well as for periodic boundary conditions. Moreover, the regularity criterion involving three of the nine components of the velocity gradient tensor is also obtained. The main results generalize the recent work by Cao and Wu (2010 Two regularity criteria for the 3D MHD equations J. Diff. Eqns 248 2263-74) and the analysis in part is based on the works by Cao C and Titi E (2008 Regularity criteria for the three-dimensional Navier-Stokes equations Indiana Univ. Math. J. 57 2643-61 2011 Gobal regularity criterion for the 3D Navier-Stokes equations involving one entry of the velocity gradient tensor Arch. Rational Mech. Anal. 202 919-32) for 3D incompressible Navier-Stokes equations.
An adaptive regularization parameter choice strategy for multispectral bioluminescence tomography
Feng Jinchao; Qin Chenghu; Jia Kebin; Han Dong; Liu Kai; Zhu Shouping; Yang Xin; Tian Jie
2011-11-15
Purpose: Bioluminescence tomography (BLT) provides an effective tool for monitoring physiological and pathological activities in vivo. However, the measured data in bioluminescence imaging are corrupted by noise. Therefore, regularization methods are commonly used to find a regularized solution. Nevertheless, for the quality of the reconstructed bioluminescent source obtained by regularization methods, the choice of the regularization parameters is crucial. To date, the selection of regularization parameters remains challenging. With regards to the above problems, the authors proposed a BLT reconstruction algorithm with an adaptive parameter choice rule. Methods: The proposed reconstruction algorithm uses a diffusion equation for modeling the bioluminescent photon transport. The diffusion equation is solved with a finite element method. Computed tomography (CT) images provide anatomical information regarding the geometry of the small animal and its internal organs. To reduce the ill-posedness of BLT, spectral information and the optimal permissible source region are employed. Then, the relationship between the unknown source distribution and multiview and multispectral boundary measurements is established based on the finite element method and the optimal permissible source region. Since the measured data are noisy, the BLT reconstruction is formulated as l{sub 2} data fidelity and a general regularization term. When choosing the regularization parameters for BLT, an efficient model function approach is proposed, which does not require knowledge of the noise level. This approach only requests the computation of the residual and regularized solution norm. With this knowledge, we construct the model function to approximate the objective function, and the regularization parameter is updated iteratively. Results: First, the micro-CT based mouse phantom was used for simulation verification. Simulation experiments were used to illustrate why multispectral data were used
Regular treatment with salmeterol for chronic asthma: serious adverse events
Cates, Christopher J; Cates, Matthew J
2014-01-01
Background Epidemiological evidence has suggested a link between beta2-agonists and increases in asthma mortality. There has been much debate about possible causal links for this association, and whether regular (daily) long-acting beta2-agonists are safe. Objectives The aim of this review is to assess the risk of fatal and non-fatal serious adverse events in trials that randomised patients with chronic asthma to regular salmeterol versus placebo or regular short-acting beta2-agonists. Search methods We identified trials using the Cochrane Airways Group Specialised Register of trials. We checked websites of clinical trial registers for unpublished trial data and FDA submissions in relation to salmeterol. The date of the most recent search was August 2011. Selection criteria We included controlled parallel design clinical trials on patients of any age and severity of asthma if they randomised patients to treatment with regular salmeterol and were of at least 12 weeks’ duration. Concomitant use of inhaled corticosteroids was allowed, as long as this was not part of the randomised treatment regimen. Data collection and analysis Two authors independently selected trials for inclusion in the review. One author extracted outcome data and the second checked them. We sought unpublished data on mortality and serious adverse events. Main results The review includes 26 trials comparing salmeterol to placebo and eight trials comparing with salbutamol. These included 62,815 participants with asthma (including 2,599 children). In six trials (2,766 patients), no serious adverse event data could be obtained. All-cause mortality was higher with regular salmeterol than placebo but the increase was not significant (Peto odds ratio (OR) 1.33 (95% CI 0.85 to 2.08)). Non-fatal serious adverse events were significantly increased when regular salmeterol was compared with placebo (OR 1.15 95% CI 1.02 to 1.29). One extra serious adverse event occurred over 28 weeks for every 188 people
Nondissipative Velocity and Pressure Regularizations for the ICON Model
NASA Astrophysics Data System (ADS)
Restelli, M.; Giorgetta, M.; Hundertmark, T.; Korn, P.; Reich, S.
2009-04-01
A challenging aspect in the numerical simulation of atmospheric and oceanic flows is the multiscale character of the problem both in space and time. The small spacial scales are generated by the turbulent energy and enstrophy cascades, and are usually dealt with by means of turbulence parametrizations, while the small temporal scales are governed by the propagation of acoustic and gravity waves, which are of little importance for the large scale dynamics and are often eliminated by means of a semi-implicit time discretization. We propose to treat both phenomena of subgrid turbulence and temporal scale separation in a unified way by means of nondissipative regularizations of the underlying model equations. More precisely, we discuss the use of two regularized equation sets: the velocity regularization, also know as Lagrangian averaged Navier-Stokes system, and the pressure regularization. Both regularizations are nondissipative since they do not enhance the dissipation of energy and enstrophy of the flow. The velocity regularization models the effects of the subgrid velocity fluctuations on the mean flow, it has thus been proposed as a turbulence parametrization and it has been found to yield promising results in ocean modeling [HHPW08]. In particular, the velocity regularization results in a higher variability of the numerical solution. The pressure regularization, discussed in [RWS07], modifies the propagation of acoustic and gravity waves so that the resulting system can be discretized explicitly in time with time steps analogous to those allowed by a semi-implicit method. Compared to semi-implicit time integrators, however, the pressure regularization takes fully into account the geostrophic balance of the flow. We discuss here the implementation of the velocity and pressure regularizations within the numerical framework of the ICON general circulation model (GCM) [BR05] for the case of the rotating shallow water system, showing how the original numerical
NASA Astrophysics Data System (ADS)
Chen, De-Han; Hofmann, Bernd; Zou, Jun
2017-01-01
We consider the ill-posed operator equation Ax = y with an injective and bounded linear operator A mapping between {{\\ell}2} and a Hilbert space Y, possessing the unique solution {{x}\\dagger}=≤ft\\{{{x}\\dagger}k\\right\\}k=1∞ . For the cases that sparsity {{x}\\dagger}\\in {{\\ell}0} is expected but often slightly violated in practice, we investigate in comparison with the {{\\ell}1} -regularization the elastic-net regularization, where the penalty is a weighted superposition of the {{\\ell}1} -norm and the {{\\ell}2} -norm square, under the assumption that {{x}\\dagger}\\in {{\\ell}1} . There occur two positive parameters in this approach, the weight parameter η and the regularization parameter as the multiplier of the whole penalty in the Tikhonov functional, whereas only one regularization parameter arises in {{\\ell}1} -regularization. Based on the variational inequality approach for the description of the solution smoothness with respect to the forward operator A and exploiting the method of approximate source conditions, we present some results to estimate the rate of convergence for the elastic-net regularization. The occurring rate function contains the rate of the decay {{x}\\dagger}k\\to 0 for k\\to ∞ and the classical smoothness properties of {{x}\\dagger} as an element in {{\\ell}2} .
Particle motion and Penrose processes around rotating regular black hole
NASA Astrophysics Data System (ADS)
Abdujabbarov, Ahmadjon
2016-07-01
The neutral particle motion around rotating regular black hole that was derived from the Ayón-Beato-García (ABG) black hole solution by the Newman-Janis algorithm in the preceding paper (Toshmatov et al., Phys. Rev. D, 89:104017, 2014) has been studied. The dependencies of the ISCO (innermost stable circular orbits along geodesics) and unstable orbits on the value of the electric charge of the rotating regular black hole have been shown. Energy extraction from the rotating regular black hole through various processes has been examined. We have found expression of the center of mass energy for the colliding neutral particles coming from infinity, based on the BSW (Baňados-Silk-West) mechanism. The electric charge Q of rotating regular black hole decreases the potential of the gravitational field as compared to the Kerr black hole and the particles demonstrate less bound energy at the circular geodesics. This causes an increase of efficiency of the energy extraction through BSW process in the presence of the electric charge Q from rotating regular black hole. Furthermore, we have studied the particle emission due to the BSW effect assuming that two neutral particles collide near the horizon of the rotating regular extremal black hole and produce another two particles. We have shown that efficiency of the energy extraction is less than the value 146.6 % being valid for the Kerr black hole. It has been also demonstrated that the efficiency of the energy extraction from the rotating regular black hole via the Penrose process decreases with the increase of the electric charge Q and is smaller in comparison to 20.7 % which is the value for the extreme Kerr black hole with the specific angular momentum a= M.
Another look at statistical learning theory and regularization.
Cherkassky, Vladimir; Ma, Yunqian
2009-09-01
The paper reviews and highlights distinctions between function-approximation (FA) and VC theory and methodology, mainly within the setting of regression problems and a squared-error loss function, and illustrates empirically the differences between the two when data is sparse and/or input distribution is non-uniform. In FA theory, the goal is to estimate an unknown true dependency (or 'target' function) in regression problems, or posterior probability P(y/x) in classification problems. In VC theory, the goal is to 'imitate' unknown target function, in the sense of minimization of prediction risk or good 'generalization'. That is, the result of VC learning depends on (unknown) input distribution, while that of FA does not. This distinction is important because regularization theory originally introduced under clearly stated FA setting [Tikhonov, N. (1963). On solving ill-posed problem and method of regularization. Doklady Akademii Nauk USSR, 153, 501-504; Tikhonov, N., & V. Y. Arsenin (1977). Solution of ill-posed problems. Washington, DC: W. H. Winston], has been later used under risk-minimization or VC setting. More recently, several authors [Evgeniou, T., Pontil, M., & Poggio, T. (2000). Regularization networks and support vector machines. Advances in Computational Mathematics, 13, 1-50; Hastie, T., Tibshirani, R., & Friedman, J. (2001). The elements of statistical learning: Data mining, inference and prediction. Springer; Poggio, T. and Smale, S., (2003). The mathematics of learning: Dealing with data. Notices of the AMS, 50 (5), 537-544] applied constructive methodology based on regularization framework to learning dependencies from data (under VC-theoretical setting). However, such regularization-based learning is usually presented as a purely constructive methodology (with no clearly stated problem setting). This paper compares FA/regularization and VC/risk minimization methodologies in terms of underlying theoretical assumptions. The control of model
NASA Astrophysics Data System (ADS)
Lu, Yao; Chan, Heang-Ping; Wei, Jun; Hadjiiski, Lubomir; Zhou, Chuan
2012-03-01
Digital breast tomosynthesis (DBT) holds strong promise for improving the sensitivity of detecting subtle mass lesions. Detection of microcalcifications is more difficult because of high noise and subtle signals in the large DBT volume. It is important to enhance the contrast-to-noise ratio (CNR) of microcalcifications in DBT reconstruction. A major challenge of implementing microcalcification enhancement or noise regularization in DBT reconstruction is to preserve the image quality of masses, especially those with ill-defined margins and subtle spiculations. We are developing a new multiscale regularization (MSR) method for the simultaneous algebraic reconstruction technique (SART) to improve the CNR of microcalcifications without compromising the quality of masses. Each DBT slice is stratified into different frequency bands via wavelet decomposition and the regularization method applies different degrees of regularization to different frequency bands to preserve features of interest and suppress noise. Regularization is constrained by a characteristic map to avoid smoothing subtle microcalcifications. The characteristic map is generated via image feature analysis to identify potential microcalcification locations in the DBT volume. The MSR method was compared to the non-convex total pvariation (TpV) method and SART with no regularization (NR) in terms of the CNR and the full width at half maximum of the line profiles intersecting calcifications and mass spiculations in DBT of human subjects. The results demonstrated that SART regularized by the MSR method was superior to the TpV method for subtle microcalcifications in terms of CNR enhancement. The MSR method preserved the quality of subtle spiculations better than the TpV method in comparison to NR.
Early family regularity protects against later disruptive behavior.
Rijlaarsdam, Jolien; Tiemeier, Henning; Ringoot, Ank P; Ivanova, Masha Y; Jaddoe, Vincent W V; Verhulst, Frank C; Roza, Sabine J
2016-07-01
Infants' temperamental anger or frustration reactions are highly stable, but are also influenced by maturation and experience. It is yet unclear why some infants high in anger or frustration reactions develop disruptive behavior problems whereas others do not. We examined family regularity, conceptualized as the consistency of mealtime and bedtime routines, as a protective factor against the development of oppositional and aggressive behavior. This study used prospectively collected data from 3136 families participating in the Generation R Study. Infant anger or frustration reactions and family regularity were reported by mothers when children were ages 6 months and 2-4 years, respectively. Multiple informants (parents, teachers, and children) and methods (questionnaire and interview) were used in the assessment of children's oppositional and aggressive behavior at age 6. Higher levels of family regularity were associated with lower levels of child aggression independent of temperamental anger or frustration reactions (β = -0.05, p = 0.003). The association between child oppositional behavior and temperamental anger or frustration reactions was moderated by family regularity and child gender (β = 0.11, p = 0.046): family regularity reduced the risk for oppositional behavior among those boys who showed anger or frustration reactions in infancy. In conclusion, family regularity reduced the risk for child aggression and showed a gender-specific protective effect against child oppositional behavior associated with anger or frustration reactions. Families that ensured regularity of mealtime and bedtime routines buffered their infant sons high in anger or frustration reactions from developing oppositional behavior.
Regular treatment with formoterol for chronic asthma: serious adverse events
Cates, Christopher J; Cates, Matthew J
2014-01-01
Background Epidemiological evidence has suggested a link between beta2-agonists and increases in asthma mortality. There has been much debate about possible causal links for this association, and whether regular (daily) long-acting beta2-agonists are safe. Objectives The aim of this review is to assess the risk of fatal and non-fatal serious adverse events in trials that randomised patients with chronic asthma to regular formoterol versus placebo or regular short-acting beta2-agonists. Search methods We identified trials using the Cochrane Airways Group Specialised Register of trials. We checked websites of clinical trial registers for unpublished trial data and Food and Drug Administration (FDA) submissions in relation to formoterol. The date of the most recent search was January 2012. Selection criteria We included controlled, parallel design clinical trials on patients of any age and severity of asthma if they randomised patients to treatment with regular formoterol and were of at least 12 weeks’ duration. Concomitant use of inhaled corticosteroids was allowed, as long as this was not part of the randomised treatment regimen. Data collection and analysis Two authors independently selected trials for inclusion in the review. One author extracted outcome data and the second author checked them. We sought unpublished data on mortality and serious adverse events. Main results The review includes 22 studies (8032 participants) comparing regular formoterol to placebo and salbutamol. Non-fatal serious adverse event data could be obtained for all participants from published studies comparing formoterol and placebo but only 80% of those comparing formoterol with salbutamol or terbutaline. Three deaths occurred on regular formoterol and none on placebo; this difference was not statistically significant. It was not possible to assess disease-specific mortality in view of the small number of deaths. Non-fatal serious adverse events were significantly increased when
Reducing errors in the GRACE gravity solutions using regularization
NASA Astrophysics Data System (ADS)
Save, Himanshu; Bettadpur, Srinivas; Tapley, Byron D.
2012-09-01
The nature of the gravity field inverse problem amplifies the noise in the GRACE data, which creeps into the mid and high degree and order harmonic coefficients of the Earth's monthly gravity fields provided by GRACE. Due to the use of imperfect background models and data noise, these errors are manifested as north-south striping in the monthly global maps of equivalent water heights. In order to reduce these errors, this study investigates the use of the L-curve method with Tikhonov regularization. L-curve is a popular aid for determining a suitable value of the regularization parameter when solving linear discrete ill-posed problems using Tikhonov regularization. However, the computational effort required to determine the L-curve is prohibitively high for a large-scale problem like GRACE. This study implements a parameter-choice method, using Lanczos bidiagonalization which is a computationally inexpensive approximation to L-curve. Lanczos bidiagonalization is implemented with orthogonal transformation in a parallel computing environment and projects a large estimation problem on a problem of the size of about 2 orders of magnitude smaller for computing the regularization parameter. Errors in the GRACE solution time series have certain characteristics that vary depending on the ground track coverage of the solutions. These errors increase with increasing degree and order. In addition, certain resonant and near-resonant harmonic coefficients have higher errors as compared with the other coefficients. Using the knowledge of these characteristics, this study designs a regularization matrix that provides a constraint on the geopotential coefficients as a function of its degree and order. This regularization matrix is then used to compute the appropriate regularization parameter for each monthly solution. A 7-year time-series of the candidate regularized solutions (Mar 2003-Feb 2010) show markedly reduced error stripes compared with the unconstrained GRACE release 4
Regularization methods for near-field acoustical holography.
Williams, E G
2001-10-01
The reconstruction of the pressure and normal surface velocity provided by near-field acoustical holography (NAH) from pressure measurements made near a vibrating structure is a linear, ill-posed inverse problem due to the existence of strongly decaying, evanescentlike waves. Regularization provides a technique of overcoming the ill-posedness and generates a solution to the linear problem in an automated way. We present four robust methods for regularization; the standard Tikhonov procedure along with a novel improved version, Landweber iteration, and the conjugate gradient approach. Each of these approaches can be applied to all forms of interior or exterior NAH problems; planar, cylindrical, spherical, and conformal. We also study two parameter selection procedures, the Morozov discrepancy principle and the generalized cross validation, which are crucial to any regularization theory. In particular, we concentrate here on planar and cylindrical holography. These forms of NAH which rely on the discrete Fourier transform are important due to their popularity and to their tremendous computational speed. In order to use regularization theory for the separable geometry problems we reformulate the equations of planar, cylindrical, and spherical NAH into an eigenvalue problem. The resulting eigenvalues and eigenvectors couple easily to regularization theory, which can be incorporated into the NAH software with little sacrifice in computational speed. The resulting complete automation of the NAH algorithm for both separable and nonseparable geometries overcomes the last significant hurdle for NAH.
Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.
Feng, Yunlong; Lv, Shao-Gao; Hang, Hanyuan; Suykens, Johan A K
2016-03-01
Kernelized elastic net regularization (KENReg) is a kernelization of the well-known elastic net regularization (Zou & Hastie, 2005). The kernel in KENReg is not required to be a Mercer kernel since it learns from a kernelized dictionary in the coefficient space. Feng, Yang, Zhao, Lv, and Suykens (2014) showed that KENReg has some nice properties including stability, sparseness, and generalization. In this letter, we continue our study on KENReg by conducting a refined learning theory analysis. This letter makes the following three main contributions. First, we present refined error analysis on the generalization performance of KENReg. The main difficulty of analyzing the generalization error of KENReg lies in characterizing the population version of its empirical target function. We overcome this by introducing a weighted Banach space associated with the elastic net regularization. We are then able to conduct elaborated learning theory analysis and obtain fast convergence rates under proper complexity and regularity assumptions. Second, we study the sparse recovery problem in KENReg with fixed design and show that the kernelization may improve the sparse recovery ability compared to the classical elastic net regularization. Finally, we discuss the interplay among different properties of KENReg that include sparseness, stability, and generalization. We show that the stability of KENReg leads to generalization, and its sparseness confidence can be derived from generalization. Moreover, KENReg is stable and can be simultaneously sparse, which makes it attractive theoretically and practically.
Fast multislice fluorescence molecular tomography using sparsity-inducing regularization
NASA Astrophysics Data System (ADS)
Hejazi, Sedigheh Marjaneh; Sarkar, Saeed; Darezereshki, Ziba
2016-02-01
Fluorescence molecular tomography (FMT) is a rapidly growing imaging method that facilitates the recovery of small fluorescent targets within biological tissue. The major challenge facing the FMT reconstruction method is the ill-posed nature of the inverse problem. In order to overcome this problem, the acquisition of large FMT datasets and the utilization of a fast FMT reconstruction algorithm with sparsity regularization have been suggested recently. Therefore, the use of a joint L1/total-variation (TV) regularization as a means of solving the ill-posed FMT inverse problem is proposed. A comparative quantified analysis of regularization methods based on L1-norm and TV are performed using simulated datasets, and the results show that the fast composite splitting algorithm regularization method can ensure the accuracy and robustness of the FMT reconstruction. The feasibility of the proposed method is evaluated in an in vivo scenario for the subcutaneous implantation of a fluorescent-dye-filled capillary tube in a mouse, and also using hybrid FMT and x-ray computed tomography data. The results show that the proposed regularization overcomes the difficulties created by the ill-posed inverse problem.
Regularized friction and continuation: Comparison with Coulomb's law
NASA Astrophysics Data System (ADS)
Vigué, Pierre; Vergez, Christophe; Karkar, Sami; Cochelin, Bruno
2017-02-01
Periodic solutions of systems with friction are difficult to investigate because of the non-smooth nature of friction laws. This paper examines periodic solutions and most notably stick-slip, on a simple one-degree-of-freedom system (mass, spring, damper, and belt), with Coulomb's friction law, and with a regularized friction law (i.e. the friction coefficient becomes a function of relative speed, with a stiffness parameter). With Coulomb's law, the stick-slip solution is constructed step by step, which gives a usable existence condition. With the regularized law, the Asymptotic Numerical Method and the Harmonic Balance Method provide bifurcation diagrams with respect to the belt speed or normal force, and for several values of the regularization parameter. Formulations from the Coulomb case give the means of a comparison between regularized solutions and a standard reference. With an appropriate definition, regularized stick-slip motion exists, its amplitude increases with respect to the belt speed and its pulsation decreases with respect to the normal force.
X-ray computed tomography using curvelet sparse regularization
Wieczorek, Matthias Vogel, Jakob; Lasser, Tobias; Frikel, Jürgen; Demaret, Laurent; Eggl, Elena; Pfeiffer, Franz; Kopp, Felix; Noël, Peter B.
2015-04-15
Purpose: Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. Methods: In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Results: Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method’s strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. Conclusions: The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.
Enumeration of Extended m-Regular Linear Stacks.
Guo, Qiang-Hui; Sun, Lisa H; Wang, Jian
2016-12-01
The contact map of a protein fold in the two-dimensional (2D) square lattice has arc length at least 3, and each internal vertex has degree at most 2, whereas the two terminal vertices have degree at most 3. Recently, Chen, Guo, Sun, and Wang studied the enumeration of [Formula: see text]-regular linear stacks, where each arc has length at least [Formula: see text] and the degree of each vertex is bounded by 2. Since the two terminal points in a protein fold in the 2D square lattice may form contacts with at most three adjacent lattice points, we are led to the study of extended [Formula: see text]-regular linear stacks, in which the degree of each terminal point is bounded by 3. This model is closed to real protein contact maps. Denote the generating functions of the [Formula: see text]-regular linear stacks and the extended [Formula: see text]-regular linear stacks by [Formula: see text] and [Formula: see text], respectively. We show that [Formula: see text] can be written as a rational function of [Formula: see text]. For a certain [Formula: see text], by eliminating [Formula: see text], we obtain an equation satisfied by [Formula: see text] and derive the asymptotic formula of the numbers of [Formula: see text]-regular linear stacks of length [Formula: see text].
Regularization of inverse planning for intensity-modulated radiotherapy.
Chvetsov, Alexei V; Calvetti, Daniela; Sohn, Jason W; Kinsella, Timothy J
2005-02-01
The performance of a variational regularization technique to improve robustness of inverse treatment planning for intensity modulated radiotherapy is analyzed and tested. Inverse treatment planning is based on the numerical solutions to the Fredholm integral equation of the first kind which is ill-posed. Therefore, a fundamental problem with inverse treatment planning is that it may exhibit instabilities manifested in nonphysical oscillations in the beam intensity functions. To control the instabilities, we consider a variational regularization technique which can be applied for the methods which minimize a quadratic objective function. In this technique, the quadratic objective function is modified by adding of a stabilizing functional that allows for arbitrary order regularization. An optimal form of stabilizing functional is selected which allows for both regularization and good approximation of beam intensity functions. The regularized optimization algorithm is shown, by comparison for a typical case of a head-and-neck cancer treatment, to be significantly more accurate and robust than the standard approach, particularly for the smaller beamlet sizes.
Rotating Hayward's regular black hole as particle accelerator
NASA Astrophysics Data System (ADS)
Amir, Muhammed; Ghosh, Sushant G.
2015-07-01
Recently, Bañados, Silk and West (BSW) demonstrated that the extremal Kerr black hole can act as a particle accelerator with arbitrarily high center-of-mass energy ( E CM) when the collision takes place near the horizon. The rotating Hayward's regular black hole, apart from Mass ( M) and angular momentum ( a), has a new parameter g ( g > 0 is a constant) that provides a deviation from the Kerr black hole. We demonstrate that for each g, with M = 1, there exist critical a E and r {/H E }, which corresponds to a regular extremal black hole with degenerate horizons, and a E decreases whereas r {/H E } increases with increase in g. While a < a E describe a regular non-extremal black hole with outer and inner horizons. We apply the BSW process to the rotating Hayward's regular black hole, for different g, and demonstrate numerically that the E CM diverges in the vicinity of the horizon for the extremal cases thereby suggesting that a rotating regular black hole can also act as a particle accelerator and thus in turn provide a suitable framework for Plank-scale physics. For a non-extremal case, there always exist a finite upper bound for the E CM, which increases with the deviation parameter g.
Regularized negative correlation learning for neural network ensembles.
Chen, Huanhuan; Yao, Xin
2009-12-01
Negative correlation learning (NCL) is a neural network ensemble learning algorithm that introduces a correlation penalty term to the cost function of each individual network so that each neural network minimizes its mean square error (MSE) together with the correlation of the ensemble. This paper analyzes NCL and reveals that the training of NCL (when lambda = 1) corresponds to training the entire ensemble as a single learning machine that only minimizes the MSE without regularization. This analysis explains the reason why NCL is prone to overfitting the noise in the training set. This paper also demonstrates that tuning the correlation parameter lambda in NCL by cross validation cannot overcome the overfitting problem. The paper analyzes this problem and proposes the regularized negative correlation learning (RNCL) algorithm which incorporates an additional regularization term for the whole ensemble. RNCL decomposes the ensemble's training objectives, including MSE and regularization, into a set of sub-objectives, and each sub-objective is implemented by an individual neural network. In this paper, we also provide a Bayesian interpretation for RNCL and provide an automatic algorithm to optimize regularization parameters based on Bayesian inference. The RNCL formulation is applicable to any nonlinear estimator minimizing the MSE. The experiments on synthetic as well as real-world data sets demonstrate that RNCL achieves better performance than NCL, especially when the noise level is nontrivial in the data set.
Incorporating anatomical side information into PET reconstruction using nonlocal regularization.
Nguyen, Van-Giang; Lee, Soo-Jin
2013-10-01
With the introduction of combined positron emission tomography (PET)/computed tomography (CT) or PET/magnetic resonance imaging (MRI) scanners, there is an increasing emphasis on reconstructing PET images with the aid of the anatomical side information obtained from X-ray CT or MRI scanners. In this paper, we propose a new approach to incorporating prior anatomical information into PET reconstruction using the nonlocal regularization method. The nonlocal regularizer developed for this application is designed to selectively consider the anatomical information only when it is reliable. As our proposed nonlocal regularization method does not directly use anatomical edges or boundaries which are often used in conventional methods, it is not only free from additional processes to extract anatomical boundaries or segmented regions, but also more robust to the signal mismatch problem that is caused by the indirect relationship between the PET image and the anatomical image. We perform simulations with digital phantoms. According to our experimental results, compared to the conventional method based on the traditional local regularization method, our nonlocal regularization method performs well even with the imperfect prior anatomical information or in the presence of signal mismatch between the PET image and the anatomical image.
SPECT reconstruction using DCT-induced tight framelet regularization
NASA Astrophysics Data System (ADS)
Zhang, Jiahan; Li, Si; Xu, Yuesheng; Schmidtlein, C. R.; Lipson, Edward D.; Feiglin, David H.; Krol, Andrzej
2015-03-01
Wavelet transforms have been successfully applied in many fields of image processing. Yet, to our knowledge, they have never been directly incorporated to the objective function in Emission Computed Tomography (ECT) image reconstruction. Our aim has been to investigate if the ℓ1-norm of non-decimated discrete cosine transform (DCT) coefficients of the estimated radiotracer distribution could be effectively used as the regularization term for the penalized-likelihood (PL) reconstruction, where a regularizer is used to enforce the image smoothness in the reconstruction. In this study, the ℓ1-norm of 2D DCT wavelet decomposition was used as a regularization term. The Preconditioned Alternating Projection Algorithm (PAPA), which we proposed in earlier work to solve penalized likelihood (PL) reconstruction with non-differentiable regularizers, was used to solve this optimization problem. The DCT wavelet decompositions were performed on the transaxial reconstructed images. We reconstructed Monte Carlo simulated SPECT data obtained for a numerical phantom with Gaussian blobs as hot lesions and with a warm random lumpy background. Reconstructed images using the proposed method exhibited better noise suppression and improved lesion conspicuity, compared with images reconstructed using expectation maximization (EM) algorithm with Gaussian post filter (GPF). Also, the mean square error (MSE) was smaller, compared with EM-GPF. A critical and challenging aspect of this method was selection of optimal parameters. In summary, our numerical experiments demonstrated that the ℓ1-norm of discrete cosine transform (DCT) wavelet frame transform DCT regularizer shows promise for SPECT image reconstruction using PAPA method.
Rhythm's gonna get you: regular meter facilitates semantic sentence processing.
Rothermich, Kathrin; Schmidt-Kassow, Maren; Kotz, Sonja A
2012-01-01
Rhythm is a phenomenon that fundamentally affects the perception of events unfolding in time. In language, we define 'rhythm' as the temporal structure that underlies the perception and production of utterances, whereas 'meter' is defined as the regular occurrence of beats (i.e. stressed syllables). In stress-timed languages such as German, this regularity functions as a powerful temporal and structural cue in speech comprehension. Recent evidence shows that it also interacts with higher level linguistic faculties such as syntax (Schmidt-Kassow & Kotz, 2009a). The current ERP experiment investigated the impact of metric structure on lexico-semantic processing, comparing the effects of semantic and metric expectancy in regular and irregular metric sentence contexts. We predicted that (1) semantically unexpected words would result in an increased N400 amplitude and (2) metric context modulates the N400 amplitude. Our results confirm these predictions: semantically unexpected words elicit an N400 that is significantly smaller in a metrically regular than a metrically irregular sentence context. The current findings support the idea that metric regularity enhances the prediction of stress locations in a sentence context, which in turn facilitates lexico-semantic integration. Copyright © 2011 Elsevier Ltd. All rights reserved.
Nonparametric Tikhonov Regularized NMF and Its Application in Cancer Clustering.
Mirzal, Andri
2014-01-01
The Tikhonov regularized nonnegative matrix factorization (TNMF) is an NMF objective function that enforces smoothness on the computed solutions, and has been successfully applied to many problem domains including text mining, spectral data analysis, and cancer clustering. There is, however, an issue that is still insufficiently addressed in the development of TNMF algorithms, i.e., how to develop mechanisms that can learn the regularization parameters directly from the data sets. The common approach is to use fixed values based on a priori knowledge about the problem domains. However, from the linear inverse problems study it is known that the quality of the solutions of the Tikhonov regularized least square problems depends heavily on the choosing of appropriate regularization parameters. Since least squares are the building blocks of the NMF, it can be expected that similar situation also applies to the NMF. In this paper, we propose two formulas to automatically learn the regularization parameters from the data set based on the L-curve approach. We also develop a convergent algorithm for the TNMF based on the additive update rules. Finally, we demonstrate the use of the proposed algorithm in cancer clustering tasks.
Structure-, stratigraphy- and fault-guided regularization in geophysical inversion
NASA Astrophysics Data System (ADS)
Wu, Xinming
2017-07-01
Geophysical inversion is often ill-posed because of inaccurate and insufficient data. Regularization is often applied to the inversion problem to obtain a stable solution by imposing additional constraints on the model. Common regularization schemes impose isotropic smoothness on solutions and may have difficulties in obtaining geologically reasonable models that are often supposed to be anisotropic and conform to subsurface structural and stratigraphic features. I introduce a general method to incorporate constraints of seismic structural and stratigraphic orientations and fault slips into geophysical inversion problems. I first use a migrated seismic image to estimate structural and stratigraphic orientations and fault slip vectors that correlate fault blocks on opposite sides of a fault. I then use the estimated orientations and fault slips to construct simple and convenient anisotropic regularization operators in inversion problems to spread information along structural and stratigraphic orientations and across faults. In this way, we are able to compute inverted models that conform to seismic reflectors, faults and stratigraphic features such as channels. The regularization is also helpful to integrate well-log properties into the inversion by spreading the measured rock properties away from the well-log positions into the whole inverted model across faults and along structural and stratigraphic orientations. I use a 3-D synthetic example of impedance inversion to illustrate the structure-, stratigraphy- and fault-guided regularization method. I further applied the method to estimate seismic interval velocity and to compute structure- and stratigraphy-oriented semblance.
A Generic Path Algorithm for Regularized Statistical Estimation.
Zhou, Hua; Wu, Yichao
2014-01-01
Regularization is widely used in statistics and machine learning to prevent overfitting and gear solution towards prior information. In general, a regularized estimation problem minimizes the sum of a loss function and a penalty term. The penalty term is usually weighted by a tuning parameter and encourages certain constraints on the parameters to be estimated. Particular choices of constraints lead to the popular lasso, fused-lasso, and other generalized ℓ1 penalized regression methods. In this article we follow a recent idea by Wu (2011, 2012) and propose an exact path solver based on ordinary differential equations (EPSODE) that works for any convex loss function and can deal with generalized ℓ1 penalties as well as more complicated regularization such as inequality constraints encountered in shape-restricted regressions and nonparametric density estimation. Non-asymptotic error bounds for the equality regularized estimates are derived. In practice, the EPSODE can be coupled with AIC, BIC, Cp or cross-validation to select an optimal tuning parameter, or provides a convenient model space for performing model averaging or aggregation. Our applications to generalized ℓ1 regularized generalized linear models, shape-restricted regressions, Gaussian graphical models, and nonparametric density estimation showcase the potential of the EPSODE algorithm.
Alternating Direction Method of Multiplier for Tomography With Nonlocal Regularizers
Dewaraja, Yuni K.; Fessler, Jeffrey A.
2015-01-01
The ordered subset expectation maximization (OSEM) algorithm approximates the gradient of a likelihood function using a subset of projections instead of using all projections so that fast image reconstruction is possible for emission and transmission tomography such as SPECT, PET, and CT. However, OSEM does not significantly accelerate reconstruction with computationally expensive regularizers such as patch-based nonlocal (NL) regularizers, because the regularizer gradient is evaluated for every subset. We propose to use variable splitting to separate the likelihood term and the regularizer term for penalized emission tomographic image reconstruction problem and to optimize it using the alternating direction method of multiplier (ADMM). We also propose a fast algorithm to optimize the ADMM parameter based on convergence rate analysis. This new scheme enables more sub-iterations related to the likelihood term. We evaluated our ADMM for 3-D SPECT image reconstruction with a patch-based NL regularizer that uses the Fair potential function. Our proposed ADMM improved the speed of convergence substantially compared to other existing methods such as gradient descent, EM, and OSEM using De Pierro’s approach, and the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm. PMID:25291351
Wavelet domain image restoration with adaptive edge-preserving regularization.
Belge, M; Kilmer, M E; Miller, E L
2000-01-01
In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.
Adiabatic regularization for gauge fields and the conformal anomaly
NASA Astrophysics Data System (ADS)
Chu, Chong-Sun; Koyama, Yoji
2017-03-01
Adiabatic regularization for quantum field theory in conformally flat spacetime is known for scalar and Dirac fermion fields. In this paper, we complete the construction by establishing the adiabatic regularization scheme for the gauge field. We show that the adiabatic expansion for the mode functions and the adiabatic vacuum can be defined in a similar way using Wentzel-Kramers-Brillouin-type (WKB-type) solutions as the scalar fields. As an application of the adiabatic method, we compute the trace of the energy momentum tensor and reproduce the known result for the conformal anomaly obtained by the other regularization methods. The availability of the adiabatic expansion scheme for the gauge field allows one to study various renormalized physical quantities of theories coupled to (non-Abelian) gauge fields in conformally flat spacetime, such as conformal supersymmetric Yang Mills, inflation, and cosmology.
Context effects on orthographic learning of regular and irregular words.
Wang, Hua-Chen; Castles, Anne; Nickels, Lyndsey; Nation, Kate
2011-05-01
The self-teaching hypothesis proposes that orthographic learning takes place via phonological decoding in meaningful texts, that is, in context. Context is proposed to be important in learning to read, especially when decoding is only partial. However, little research has directly explored this hypothesis. The current study looked at the effect of context on orthographic learning and examined whether there were different effects for novel words given regular and irregular pronunciations. Two experiments were conducted using regular and irregular novel words, respectively. Second-grade children were asked to learn eight novel words either in stories or in a list of words. The results revealed no significant effect of context for the regular items. However, in an orthographic decision task, there was a facilitatory effect of context on irregular novel word learning. The findings support the view that contextual information is important to orthographic learning, but only when the words to be learned contain irregular spelling-sound correspondences.
Structural characterization of the packings of granular regular polygons
NASA Astrophysics Data System (ADS)
Wang, Chuncheng; Dong, Kejun; Yu, Aibing
2015-12-01
By using a recently developed method for discrete modeling of nonspherical particles, we simulate the random packings of granular regular polygons with three to 11 edges under gravity. The effects of shape and friction on the packing structures are investigated by various structural parameters, including packing fraction, the radial distribution function, coordination number, Voronoi tessellation, and bond-orientational order. We find that packing fraction is generally higher for geometrically nonfrustrated regular polygons, and can be increased by the increase of edge number and decrease of friction. The changes of packing fraction are linked with those of the microstructures, such as the variations of the translational and orientational orders and local configurations. In particular, the free areas of Voronoi tessellations (which are related to local packing fractions) can be described by log-normal distributions for all polygons. The quantitative analyses establish a clearer picture for the packings of regular polygons.
Consistent regularization and renormalization in models with inhomogeneous phases
NASA Astrophysics Data System (ADS)
Adhikari, Prabal; Andersen, Jens O.
2017-02-01
In many models in condensed matter and high-energy physics, one finds inhomogeneous phases at high density and low temperature. These phases are characterized by a spatially dependent condensate or order parameter. A proper calculation requires that one takes the vacuum fluctuations of the model into account. These fluctuations are ultraviolet divergent and must be regularized. We discuss different ways of consistently regularizing and renormalizing quantum fluctuations, focusing on momentum cutoff, symmetric energy cutoff, and dimensional regularization. We apply these techniques calculating the vacuum energy in the Nambu-Jona-Lasinio model in 1 +1 dimensions in the large-Nc limit and in the 3 +1 dimensional quark-meson model in the mean-field approximation both for a one-dimensional chiral-density wave.
Analysis of the "Learning in Regular Classrooms" movement in China.
Deng, M; Manset, G
2000-04-01
The Learning in Regular Classrooms experiment has evolved in response to China's efforts to educate its large population of students with disabilities who, until the mid-1980s, were denied a free education. In the Learning in Regular Classrooms, students with disabilities (primarily sensory impairments or mild mental retardation) are educated in neighborhood schools in mainstream classrooms. Despite difficulties associated with developing effective inclusive programming, this approach has contributed to a major increase in the enrollment of students with disabilities and increased involvement of schools, teachers, and parents in China's newly developing special education system. Here we describe the development of the Learning in Regular Classroom approach and the challenges associated with educating students with disabilities in China.
Breast ultrasound tomography with total-variation regularization
Huang, Lianjie; Li, Cuiping; Duric, Neb
2009-01-01
Breast ultrasound tomography is a rapidly developing imaging modality that has the potential to impact breast cancer screening and diagnosis. A new ultrasound breast imaging device (CURE) with a ring array of transducers has been designed and built at Karmanos Cancer Institute, which acquires both reflection and transmission ultrasound signals. To extract the sound-speed information from the breast data acquired by CURE, we have developed an iterative sound-speed image reconstruction algorithm for breast ultrasound transmission tomography based on total-variation (TV) minimization. We investigate applicability of the TV tomography algorithm using in vivo ultrasound breast data from 61 patients, and compare the results with those obtained using the Tikhonov regularization method. We demonstrate that, compared to the Tikhonov regularization scheme, the TV regularization method significantly improves image quality, resulting in sound-speed tomography images with sharp (preserved) edges of abnormalities and few artifacts.
On partial regularity problem for 3D Boussinesq equations
NASA Astrophysics Data System (ADS)
Fang, Daoyuan; Liu, Chun; Qian, Chenyin
2017-10-01
In this paper, we study the partial regularity of the solutions for the three-dimensional Boussinesq equations. We first prove a criterion of local Hölder continuous of the suitable weak solutions of the Boussinesq equations, and show that one-dimensional Hausdorff measure of the singular point set is zero. Secondly, we present a local uniform gradient estimate on the suitable weak solutions and assert that the local behavior of the solution can be dominated by some scaled quantities, such as the scaled local L3-norm of the velocity. Besides, when the initial data v0 and θ0 decay sufficiently rapidly at ∞, the distribution of the regular point set of the suitable weak solutions is also considered. Based on it, one can find that MHD equations are more similar to Navier-Stokes equations than Boussinesq equations. Finally, we give a local regularity criterion of the suitable weak solutions near the boundary.
Manufacture of Regularly Shaped Sol-Gel Pellets
NASA Technical Reports Server (NTRS)
Leventis, Nicholas; Johnston, James C.; Kinder, James D.
2006-01-01
An extrusion batch process for manufacturing regularly shaped sol-gel pellets has been devised as an improved alternative to a spray process that yields irregularly shaped pellets. The aspect ratio of regularly shaped pellets can be controlled more easily, while regularly shaped pellets pack more efficiently. In the extrusion process, a wet gel is pushed out of a mold and chopped repetitively into short, cylindrical pieces as it emerges from the mold. The pieces are collected and can be either (1) dried at ambient pressure to xerogel, (2) solvent exchanged and dried under ambient pressure to ambigels, or (3) supercritically dried to aerogel. Advantageously, the extruded pellets can be dropped directly in a cross-linking bath, where they develop a conformal polymer coating around the skeletal framework of the wet gel via reaction with the cross linker. These pellets can be dried to mechanically robust X-Aerogel.
Regularity Detection As A Strategy In Object Modelling And Recognition
NASA Astrophysics Data System (ADS)
van Gool, Luc J.; Wagemans, Johan; Oosterlinck, Andre J.
1989-03-01
Human subjects easily perceive and extensively use shape regularities such as symmetry or periodicity when they are confronted with the task of object description and recognition. A computer vision algorithm is presented which emulates such behaviour in that it similarly makes use of shape redundancies for the concise description and meaningful segmentation of object contours. This can be compared with the way in which designers proceed in using CAD/CAM. In order to make the problem more accessible to computer programming, the contours are analyzed in so-called 'arc length space'. This novel mapping facilitates the detection and elimination of regularities under a broad range of viewing conditions and yields a natural basis for the formulation of the corresponding model compression rules. Several of the regularities which have traditionally been treated separately, are given a unified substrate.
Radial basis function networks and complexity regularization in function learning.
Krzyzak, A; Linder, T
1998-01-01
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function network. Our approach differs from previous complexity regularization neural-network function learning schemes in that we operate with random covering numbers and l(1) metric entropy, making it possible to consider much broader families of activation functions, namely functions of bounded variation. Some constraints previously imposed on the network parameters are also eliminated this way. The network is trained by means of complexity regularization involving empirical risk minimization. Bounds on the expected risk in terms of the sample size are obtained for a large class of loss functions. Rates of convergence to the optimal loss are also derived.
Gamma regularization based reconstruction for low dose CT.
Zhang, Junfeng; Chen, Yang; Hu, Yining; Luo, Limin; Shu, Huazhong; Li, Bicao; Liu, Jin; Coatrieux, Jean-Louis
2015-09-07
Reducing the radiation in computerized tomography is today a major concern in radiology. Low dose computerized tomography (LDCT) offers a sound way to deal with this problem. However, more severe noise in the reconstructed CT images is observed under low dose scan protocols (e.g. lowered tube current or voltage values). In this paper we propose a Gamma regularization based algorithm for LDCT image reconstruction. This solution is flexible and provides a good balance between the regularizations based on l0-norm and l1-norm. We evaluate the proposed approach using the projection data from simulated phantoms and scanned Catphan phantoms. Qualitative and quantitative results show that the Gamma regularization based reconstruction can perform better in both edge-preserving and noise suppression when compared with other norms.
Zigzag stacks and m-regular linear stacks.
Chen, William Y C; Guo, Qiang-Hui; Sun, Lisa H; Wang, Jian
2014-12-01
The contact map of a protein fold is a graph that represents the patterns of contacts in the fold. It is known that the contact map can be decomposed into stacks and queues. RNA secondary structures are special stacks in which the degree of each vertex is at most one and each arc has length of at least two. Waterman and Smith derived a formula for the number of RNA secondary structures of length n with exactly k arcs. Höner zu Siederdissen et al. developed a folding algorithm for extended RNA secondary structures in which each vertex has maximum degree two. An equation for the generating function of extended RNA secondary structures was obtained by Müller and Nebel by using a context-free grammar approach, which leads to an asymptotic formula. In this article, we consider m-regular linear stacks, where each arc has length at least m and the degree of each vertex is bounded by two. Extended RNA secondary structures are exactly 2-regular linear stacks. For any m ≥ 2, we obtain an equation for the generating function of the m-regular linear stacks. For given m, we deduce a recurrence relation and an asymptotic formula for the number of m-regular linear stacks on n vertices. To establish the equation, we use the reduction operation of Chen, Deng, and Du to transform an m-regular linear stack to an m-reduced zigzag (or alternating) stack. Then we find an equation for m-reduced zigzag stacks leading to an equation for m-regular linear stacks.
Local conservative regularizations of compressible magnetohydrodynamic and neutral flows
NASA Astrophysics Data System (ADS)
Krishnaswami, Govind S.; Sachdev, Sonakshi; Thyagaraja, A.
2016-02-01
Ideal systems like magnetohydrodynamics (MHD) and Euler flow may develop singularities in vorticity ( w =∇×v ). Viscosity and resistivity provide dissipative regularizations of the singularities. In this paper, we propose a minimal, local, conservative, nonlinear, dispersive regularization of compressible flow and ideal MHD, in analogy with the KdV regularization of the 1D kinematic wave equation. This work extends and significantly generalizes earlier work on incompressible Euler and ideal MHD. It involves a micro-scale cutoff length λ which is a function of density, unlike in the incompressible case. In MHD, it can be taken to be of order the electron collisionless skin depth c/ωpe. Our regularization preserves the symmetries of the original systems and, with appropriate boundary conditions, leads to associated conservation laws. Energy and enstrophy are subject to a priori bounds determined by initial data in contrast to the unregularized systems. A Hamiltonian and Poisson bracket formulation is developed and applied to generalize the constitutive relation to bound higher moments of vorticity. A "swirl" velocity field is identified, and shown to transport w/ρ and B/ρ, generalizing the Kelvin-Helmholtz and Alfvén theorems. The steady regularized equations are used to model a rotating vortex, MHD pinch, and a plane vortex sheet. The proposed regularization could facilitate numerical simulations of fluid/MHD equations and provide a consistent statistical mechanics of vortices/current filaments in 3D, without blowup of enstrophy. Implications for detailed analyses of fluid and plasma dynamic systems arising from our work are briefly discussed.
Regularization of languages by adults and children: A mathematical framework.
Rische, Jacquelyn L; Komarova, Natalia L
2016-02-01
The fascinating ability of humans to modify the linguistic input and "create" a language has been widely discussed. In the work of Newport and colleagues, it has been demonstrated that both children and adults have some ability to process inconsistent linguistic input and "improve" it by making it more consistent. In Hudson Kam and Newport (2009), artificial miniature language acquisition from an inconsistent source was studied. It was shown that (i) children are better at language regularization than adults and that (ii) adults can also regularize, depending on the structure of the input. In this paper we create a learning algorithm of the reinforcement-learning type, which exhibits patterns reported in Hudson Kam and Newport (2009) and suggests a way to explain them. It turns out that in order to capture the differences between children's and adults' learning patterns, we need to introduce a certain asymmetry in the learning algorithm. Namely, we have to assume that the reaction of the learners differs depending on whether or not the source's input coincides with the learner's internal hypothesis. We interpret this result in the context of a different reaction of children and adults to implicit, expectation-based evidence, positive or negative. We propose that a possible mechanism that contributes to the children's ability to regularize an inconsistent input is related to their heightened sensitivity to positive evidence rather than the (implicit) negative evidence. In our model, regularization comes naturally as a consequence of a stronger reaction of the children to evidence supporting their preferred hypothesis. In adults, their ability to adequately process implicit negative evidence prevents them from regularizing the inconsistent input, resulting in a weaker degree of regularization. Copyright © 2015 Elsevier Inc. All rights reserved.
Mixing of regular and chaotic orbits in beams
Courtlandt L. Bohn et al.
2002-09-04
Phase mixing of chaotic orbits exponentially distributes the orbits through their accessible phase space. This phenomenon, commonly called ''chaotic mixing'', stands in marked contrast to phase mixing of regular orbits which proceeds as a power law in time. It is inherently irreversible; hence, its associated e-folding time scale sets a condition on any process envisioned for emittance compensation. We numerically investigate phase mixing in the presence of space charge, distinguish between the evolution of regular and chaotic orbits, and discuss how phase mixing potentially influences macroscopic properties of high-brightness beams.
Regularized and generalized solutions of infinite-dimensional stochastic problems
Alshanskiy, Maxim A; Mel'nikova, Irina V
2011-11-30
The paper is concerned with solutions of Cauchy's problem for stochastic differential-operator equations in separable Hilbert spaces. Special emphasis is placed on the case when the operator coefficient of the equation is not a generator of a C{sub 0}-class semigroup, but rather generates some regularized semigroup. Regularized solutions of equations in the Ito form with a Wiener process as an inhomogeneity and generalized solutions of equations with white noise are constructed in various spaces of abstract distributions. Bibliography: 23 titles.
Lifshitz anomalies, Ward identities and split dimensional regularization
NASA Astrophysics Data System (ADS)
Arav, Igal; Oz, Yaron; Raviv-Moshe, Avia
2017-03-01
We analyze the structure of the stress-energy tensor correlation functions in Lifshitz field theories and construct the corresponding anomalous Ward identities. We develop a framework for calculating the anomaly coefficients that employs a split dimensional regularization and the pole residues. We demonstrate the procedure by calculating the free scalar Lifshitz scale anomalies in 2 + 1 spacetime dimensions. We find that the analysis of the regularization dependent trivial terms requires a curved spacetime description without a foliation structure. We discuss potential ambiguities in Lifshitz scale anomaly definitions.
The structure of split regular BiHom-Lie algebras
NASA Astrophysics Data System (ADS)
Calderón, Antonio J.; Sánchez, José M.
2016-12-01
We introduce the class of split regular BiHom-Lie algebras as the natural extension of the one of split Hom-Lie algebras and so of split Lie algebras. We show that an arbitrary split regular BiHom-Lie algebra L is of the form L = U +∑jIj with U a linear subspace of a fixed maximal abelian subalgebra H and any Ij a well described (split) ideal of L, satisfying [Ij ,Ik ] = 0 if j ≠ k. Under certain conditions, the simplicity of L is characterized and it is shown that L is the direct sum of the family of its simple ideals.
UV radiation transmittance: regular clothing versus sun-protective clothing.
Bielinski, Kenneth; Bielinski, Nolan
2014-09-01
There are many clothing options available for patients who are interested in limiting their exposure to UV radiation; however, these options can be confusing for patients. For dermatologists, there is limited clinical data regarding the advantages, if any, of sun-protective clothing. In this study, we examined the UV radiation transmittance of regular clothing versus sun-protective clothing. We found that regular clothing may match or even exceed sun-protective clothing in blocking the transmittance of UV radiation. These data will help dermatologists better counsel their patients on clothing options for sun protection.
Regularization for Inverting the Radon Transform with Wedge Consideration (PREPRINT)
2006-11-01
medical imaging , and industrial testing, the object of interest is scanned over a limited angular range, which is less than the full 180 deg mathematically required for density reconstruction. The use of standard full-range reconstruction algorithms produces results with notorious "butter-fly" or "wedge" artifacts. In this work we propose a reconstruction technique with a regularization term that takes into account the orientation of the missing angular range, also denoted as missing wedge. We show that a regularization that penalizes non-uniformly in the
Regular bouncing cosmological solutions in effective actions in four dimensions
NASA Astrophysics Data System (ADS)
Constantinidis, C. P.; Fabris, J. C.; Furtado, R. G.; Picco, M.
2000-02-01
We study cosmological scenarios resulting from effective actions in four dimensions which are, under some assumptions, connected with multidimensional, supergravity and string theories. These effective actions are labeled by the parameters ω, the dilaton coupling constant, and n which establishes the coupling between the dilaton and a scalar field originating from the gauge field existing in the original theories. There is a large class of bouncing as well as Friedmann-like solutions. We investigate under which conditions bouncing regular solutions can be obtained. In the case of the string effective action, regularity is obtained through the inclusion of contributions from the Ramond-Ramond sector of superstring.
Construction of regular black holes in general relativity
NASA Astrophysics Data System (ADS)
Fan, Zhong-Ying; Wang, Xiaobao
2016-12-01
We present a general procedure for constructing exact black hole solutions with electric or magnetic charges in general relativity coupled to a nonlinear electrodynamics. We obtain a variety of two-parameter family spherically symmetric black hole solutions. In particular, the singularity at the center of the space-time can be canceled in the parameter space and the black hole solutions become regular everywhere in space-time. We study the global properties of the solutions and derive the first law of thermodynamics. We also generalize the procedure to include a cosmological constant and construct regular black hole solutions that are asymptotic to anti-de Sitter space-time.
Solar reflection from a regular array of horizontally finite clouds
NASA Technical Reports Server (NTRS)
Weinman, J. A.; Harshvardhan, MR.
1982-01-01
The reflected flux from a regular array of 2- and 3-D clouds has been computed to estimate the effect of fractional cloud cover on albedos and the solar flux available to heat the earth's surface. The broken clouds are represented by a regular array of identical cuboids for the 3-D problem and equally spaced, infinitely long, bars for the 2-D problem. A diffusion approximation to the radiative transfer equation is used to compute the fluxes leaving each face of the cloud. Interaction between clouds is simulated by assuming diffuse exitance from the cloud faces and applying angle factors to obtain modified boundary conditions on each cloud face.
Adding Asymmetrically Dominated Alternatives: Violations of Regularity & the Similarity Hypothesis.
1981-07-01
statistically significant ( McNemar Test, Siegel 1956) at a p. < 0.05 level. Technically, however, the test of regularity should code switching to the de- coy as...who switched between target and competitor 63% switched to the target, 37% to the competitor McNemar Test: =(28 )/109 = 7.2 , p4.05 4. Grouping those...who switched to the decoy with the competitor (for a strong test of regularity) 59% switched to the target while 41% switched away McNemar Test: l
One-way regular electromagnetic mode immune to backscattering.
Deng, Xiaohua; Hong, Lujun; Zheng, Xiaodong; Shen, Linfang
2015-05-10
In this paper, we present a basic model of robust one-way electromagnetic modes at microwave frequencies, which is formed by a semi-infinite gyromagnetic yttrium-iron-garnet with dielectric cladding terminated by a metal plate. It is shown that this system supports not only one-way surface magnetoplasmons (SMPs) but also a one-way regular mode, which is guided by the mechanism of total internal reflection. Like one-way SMPs, the one-way regular mode can be immune to backscattering, and two types of one-way modes together make up a complete dispersion band for the system.
76 FR 55387 - Farm Credit Administration Board; Sunshine Act; Regular Meeting
Federal Register 2010, 2011, 2012, 2013, 2014
2011-09-07
... From the Federal Register Online via the Government Publishing Office FARM CREDIT ADMINISTRATION Farm Credit Administration Board; Sunshine Act; Regular Meeting AGENCY: Farm Credit Administration... the regular meeting of the Farm Credit Administration Board (Board). DATE AND TIME: The regular...
Analysis of Tikhonov regularization for function approximation by neural networks.
Burger, Martin; Neubauer, Andreas
2003-01-01
This paper is devoted to the convergence and stability analysis of Tikhonov regularization for function approximation by a class of feed-forward neural networks with one hidden layer and linear output layer. We investigate two frequently used approaches, namely regularization by output smoothing and regularization by weight decay, as well as a combination of both methods to combine their advantages. We show that in all cases stable approximations are obtained converging to the approximated function in a desired Sobolev space as the noise in the data tends to zero (in the weaker L(2)-norm) if the regularization parameter and the number of units in the network are chosen appropriately. Under additional smoothness assumptions we are able to show convergence rates results in terms of the noise level and the number of units in the network. In addition, we show how the theoretical results can be applied to the important classes of perceptrons with one hidden layer and to translation networks. Finally, the performance of the different approaches is compared in some numerical examples.
Exploring How Special and Regular Education Teachers Work Together Collaboratively
ERIC Educational Resources Information Center
Broyard-Baptiste, Erin
2012-01-01
This study was based on the need for additional research to explore the nature of collaborative teaching experiences in the K-12 education setting. For that reason, this study was designed to examine the experiences and perceptions of special education and regular education teachers with respect to inclusion and the perceptions of these teachers…
Global Regularity for Several Incompressible Fluid Models with Partial Dissipation
NASA Astrophysics Data System (ADS)
Wu, Jiahong; Xu, Xiaojing; Ye, Zhuan
2017-09-01
This paper examines the global regularity problem on several 2D incompressible fluid models with partial dissipation. They are the surface quasi-geostrophic (SQG) equation, the 2D Euler equation and the 2D Boussinesq equations. These are well-known models in fluid mechanics and geophysics. The fundamental issue of whether or not they are globally well-posed has attracted enormous attention. The corresponding models with partial dissipation may arise in physical circumstances when the dissipation varies in different directions. We show that the SQG equation with either horizontal or vertical dissipation always has global solutions. This is in sharp contrast with the inviscid SQG equation for which the global regularity problem remains outstandingly open. Although the 2D Euler is globally well-posed for sufficiently smooth data, the associated equations with partial dissipation no longer conserve the vorticity and the global regularity is not trivial. We are able to prove the global regularity for two partially dissipated Euler equations. Several global bounds are also obtained for a partially dissipated Boussinesq system.
ERIC Educational Resources Information Center
Hawaii Univ., Honolulu. Community Coll. System.
An analysis of student enrollment statistics of the 7 campuses in the Hawaii community college system for fall 1977 yielded the following summary information: regular credit students comprised 77% of the total enrollment; enrollment decreased 1% over fall 1976, the first decrease since the system began in 1965; males outnumbered females by the…
Identifying and Exploiting Spatial Regularity in Data Memory References
Mohan, T; de Supinski, B R; McKee, S A; Mueller, F; Yoo, A; Schulz, M
2003-07-24
The growing processor/memory performance gap causes the performance of many codes to be limited by memory accesses. If known to exist in an application, strided memory accesses forming streams can be targeted by optimizations such as prefetching, relocation, remapping, and vector loads. Undetected, they can be a significant source of memory stalls in loops. Existing stream-detection mechanisms either require special hardware, which may not gather statistics for subsequent analysis, or are limited to compile-time detection of array accesses in loops. Formally, little treatment has been accorded to the subject; the concept of locality fails to capture the existence of streams in a program's memory accesses. The contributions of this paper are as follows. First, we define spatial regularity as a means to discuss the presence and effects of streams. Second, we develop measures to quantify spatial regularity, and we design and implement an on-line, parallel algorithm to detect streams - and hence regularity - in running applications. Third, we use examples from real codes and common benchmarks to illustrate how derived stream statistics can be used to guide the application of profile-driven optimizations. Overall, we demonstrate the benefits of our novel regularity metric as a low-cost instrument to detect potential for code optimizations affecting memory performance.
Information fusion in regularized inversion of tomographic pumping tests
Bohling, G.C.; ,
2008-01-01
In this chapter we investigate a simple approach to incorporating geophysical information into the analysis of tomographic pumping tests for characterization of the hydraulic conductivity (K) field in an aquifer. A number of authors have suggested a tomographic approach to the analysis of hydraulic tests in aquifers - essentially simultaneous analysis of multiple tests or stresses on the flow system - in order to improve the resolution of the estimated parameter fields. However, even with a large amount of hydraulic data in hand, the inverse problem is still plagued by non-uniqueness and ill-conditioning and the parameter space for the inversion needs to be constrained in some sensible fashion in order to obtain plausible estimates of aquifer properties. For seismic and radar tomography problems, the parameter space is often constrained through the application of regularization terms that impose penalties on deviations of the estimated parameters from a prior or background model, with the tradeoff between data fit and model norm explored through systematic analysis of results for different levels of weighting on the regularization terms. In this study we apply systematic regularized inversion to analysis of tomographic pumping tests in an alluvial aquifer, taking advantage of the steady-shape flow regime exhibited in these tests to expedite the inversion process. In addition, we explore the possibility of incorporating geophysical information into the inversion through a regularization term relating the estimated K distribution to ground penetrating radar velocity and attenuation distributions through a smoothing spline model. ?? 2008 Springer-Verlag Berlin Heidelberg.
A non-iterative regularization approach to blind deconvolution
NASA Astrophysics Data System (ADS)
Justen, L.; Ramlau, R.
2006-06-01
Blind deconvolution, where both an original image and a blurring kernel are reconstructed from a blurred and noisy image, is a nonlinear and ill-posed image processing problem. Recently, classical methods for the regularization of non-blind deconvolution have been adapted to this problem. We investigate the behaviour of minimum norm solutions. Under certain applicable conditions, we prove existence as well as uniqueness and derive the explicit form of the minimum norm solution. This constitutes a nonlinear inversion operator for the blind deconvolution problem. The solution depends continuously on the given data provided that the data fulfil a weak smoothness condition. In a sense, blind deconvolution is less ill-posed than non-blind deconvolution. Given noisy data, this smoothness condition is no longer satisfied. We utilize Tikhonov regularization of a Sobolev embedding operator to restore smoothness, so that the inversion operator may be applied. We note that regularization and inversion are two separate tasks. We prove convergence of the regularized solution to the noise-free minimum norm solution and, when the noise-free data fulfil a stronger Sobolev smoothness condition, we give a convergence rate result. Our approach is non-iterative and thus very fast. It conserves mass and symmetry of the kernel and works robustly for a wide range of images and kernels. No knowledge of exact kernel shape and support size is necessary.
Rhythm's Gonna Get You: Regular Meter Facilitates Semantic Sentence Processing
ERIC Educational Resources Information Center
Rothermich, Kathrin; Schmidt-Kassow, Maren; Kotz, Sonja A.
2012-01-01
Rhythm is a phenomenon that fundamentally affects the perception of events unfolding in time. In language, we define "rhythm" as the temporal structure that underlies the perception and production of utterances, whereas "meter" is defined as the regular occurrence of beats (i.e. stressed syllables). In stress-timed languages such as German, this…
32 CFR 901.14 - Regular airmen category.
Code of Federal Regulations, 2010 CFR
2010-07-01
... SCHOOLS APPOINTMENT TO THE UNITED STATES AIR FORCE ACADEMY Nomination Procedures and Requirements § 901.14... United States Air Force Academy Under Quota Allotted to Enlisted Members of the Regular and Reserve.... Applicants not selected are reassigned on Academy notification to the CBPO. Applicants to technical school...
Statistical regularities in art: Relations with visual coding and perception.
Graham, Daniel J; Redies, Christoph
2010-07-21
Since at least 1935, vision researchers have used art stimuli to test human response to complex scenes. This is sensible given the "inherent interestingness" of art and its relation to the natural visual world. The use of art stimuli has remained popular, especially in eye tracking studies. Moreover, stimuli in common use by vision scientists are inspired by the work of famous artists (e.g., Mondrians). Artworks are also popular in vision science as illustrations of a host of visual phenomena, such as depth cues and surface properties. However, until recently, there has been scant consideration of the spatial, luminance, and color statistics of artwork, and even less study of ways that regularities in such statistics could affect visual processing. Furthermore, the relationship between regularities in art images and those in natural scenes has received little or no attention. In the past few years, there has been a concerted effort to study statistical regularities in art as they relate to neural coding and visual perception, and art stimuli have begun to be studied in rigorous ways, as natural scenes have been. In this minireview, we summarize quantitative studies of links between regular statistics in artwork and processing in the visual stream. The results of these studies suggest that art is especially germane to understanding human visual coding and perception, and it therefore warrants wider study.
Identifying Basketball Performance Indicators in Regular Season and Playoff Games
García, Javier; Ibáñez, Sergio J.; De Santos, Raúl Martinez; Leite, Nuno; Sampaio, Jaime
2013-01-01
The aim of the present study was to identify basketball game performance indicators which best discriminate winners and losers in regular season and playoffs. The sample used was composed by 323 games of ACB Spanish Basketball League from the regular season (n=306) and from the playoffs (n=17). A previous cluster analysis allowed splitting the sample in balanced (equal or below 12 points), unbalanced (between 13 and 28 points) and very unbalanced games (above 28 points). A discriminant analysis was used to identify the performance indicators either in regular season and playoff games. In regular season games, the winning teams dominated in assists, defensive rebounds, successful 2 and 3-point field-goals. However, in playoff games the winning teams’ superiority was only in defensive rebounding. In practical applications, these results may help the coaches to accurately design training programs to reflect the importance of having different offensive set plays and also have specific conditioning programs to prepare for defensive rebounding. PMID:23717365
Regular Class Participation System (RCPS). A Final Report.
ERIC Educational Resources Information Center
Ferguson, Dianne L.; And Others
The Regular Class Participation System (RCPS) project attempted to develop, implement, and validate a system for placing and maintaining students with severe disabilities in general education classrooms, with a particular emphasis on achieving both social and learning outcomes for students. A teacher-based planning strategy was developed and…
The Student with Albinism in the Regular Classroom.
ERIC Educational Resources Information Center
Ashley, Julia Robertson
This booklet, intended for regular education teachers who have children with albinism in their classes, begins with an explanation of albinism, then discusses the special needs of the student with albinism in the classroom, and presents information about adaptations and other methods for responding to these needs. Special social and emotional…
From Numbers to Letters: Feedback Regularization in Visual Word Recognition
ERIC Educational Resources Information Center
Molinaro, Nicola; Dunabeitia, Jon Andoni; Marin-Gutierrez, Alejandro; Carreiras, Manuel
2010-01-01
Word reading in alphabetic languages involves letter identification, independently of the format in which these letters are written. This process of letter "regularization" is sensitive to word context, leading to the recognition of a word even when numbers that resemble letters are inserted among other real letters (e.g., M4TERI4L). The present…
Regular Strongly Typical Blocks of {mathcal{O}^{mathfrak {q}}}
NASA Astrophysics Data System (ADS)
Frisk, Anders; Mazorchuk, Volodymyr
2009-10-01
We use the technique of Harish-Chandra bimodules to prove that regular strongly typical blocks of the category {mathcal{O}} for the queer Lie superalgebra {mathfrak{q}_n} are equivalent to the corresponding blocks of the category {mathcal{O}} for the Lie algebra {mathfrak {gl}_n}.
75 FR 1057 - Farm Credit Administration Board; Regular Meeting
Federal Register 2010, 2011, 2012, 2013, 2014
2010-01-08
... [Federal Register Volume 75, Number 5 (Friday, January 8, 2010)] [Notices] [Page 1057] [FR Doc No: 2010-246] FARM CREDIT ADMINISTRATION Farm Credit Administration Board; Regular Meeting AGENCY: Farm Credit Administration. SUMMARY: Notice is hereby given, pursuant to the Government in the Sunshine Act (5...
Implicit Learning of L2 Word Stress Regularities
ERIC Educational Resources Information Center
Chan, Ricky K. W.; Leung, Janny H. C.
2014-01-01
This article reports an experiment on the implicit learning of second language stress regularities, and presents a methodological innovation on awareness measurement. After practising two-syllable Spanish words, native Cantonese speakers with English as a second language (L2) completed a judgement task. Critical items differed only in placement of…
Mainstreaming: Educable Mentally Retarded Children in Regular Classes.
ERIC Educational Resources Information Center
Birch, Jack W.
Described in the monograph are mainstreaming programs for educable mentally retarded (EMR) children in six variously sized school districts within five states. It is noted that mainstreaming is based on the principle of educating most children in the regular classroom and providing special education on the basis of learning needs rather than…
Multiple Learning Strategies Project. Dietetic Assistant. [Regular Vocational. Vol. 1.
ERIC Educational Resources Information Center
Noffze, Elaine; And Others
This instructional package is one of two designed for regular vocational students on the vocational area of dietetic assistant. The eighty-nine learning modules are organized into three units: nutrition; menu planning and food ordering; and housekeeping and safety. Each module includes these elements: a performance objective page telling what will…
Rotating bearings in regular and irregular granular shear packings.
Aström, J A
2008-01-01
For 2D regular dense packings of solid mono-size non-sliding disks there is a mechanism for bearing formation under shear that can be explained theoretically. There is, however, no easy way to extend this model to include random dense packings which would better describe natural packings. A numerical model that simulates shear deformation for both near-regular and irregular packings is used to demonstrate that rotating bearings appear roughly with the same density in random and regular packings. The main difference appears in the size distribution of the rotating clusters near the jamming threshold. The size distribution is well described by a scaling form with a large-size cut-off that seems to grow without bounds for regular packings at the jamming threshold, while it remains finite for irregular packings. At packing densities above the jamming transition there can be no shear, unless the disks are allowed to break. Breaking of disks induces a large number of small local bearings. Clusters of rotating particles may contribute to e.g. pre-rupture yielding in landslides, snow avalanches and to the formation of aseismic gaps in tectonic fault zones.
Psychological Benefits of Regular Physical Activity: Evidence from Emerging Adults
ERIC Educational Resources Information Center
Cekin, Resul
2015-01-01
Emerging adulthood is a transitional stage between late adolescence and young adulthood in life-span development that requires significant changes in people's lives. Therefore, identifying protective factors for this population is crucial. This study investigated the effects of regular physical activity on self-esteem, optimism, and happiness in…
Interrupting Sitting Time with Regular Walks Attenuates Postprandial Triglycerides.
Miyashita, M; Edamoto, K; Kidokoro, T; Yanaoka, T; Kashiwabara, K; Takahashi, M; Burns, S
2016-02-01
We compared the effects of prolonged sitting with the effects of sitting interrupted by regular walking and the effects of prolonged sitting after continuous walking on postprandial triglyceride in postmenopausal women. 15 participants completed 3 trials in random order: 1) prolonged sitting, 2) regular walking, and 3) prolonged sitting preceded by continuous walking. During the sitting trial, participants rested for 8 h. For the walking trials, participants walked briskly in either twenty 90-sec bouts over 8 h or one 30-min bout in the morning (09:00-09:30). Except for walking, both exercise trials mimicked the sitting trial. In each trial, participants consumed a breakfast (08:00) and lunch (11:00). Blood samples were collected in the fasted state and at 2, 4, 6 and 8 h after breakfast. The serum triglyceride incremental area under the curve was 15 and 14% lower after regular walking compared with prolonged sitting and prolonged sitting after continuous walking (4.73±2.50 vs. 5.52±2.95 vs. 5.50±2.59 mmol/L∙8 h respectively, main effect of trial: P=0.023). Regularly interrupting sitting time with brief bouts of physical activity can reduce postprandial triglyceride in postmenopausal women.
New vision based navigation clue for a regular colonoscope's tip
NASA Astrophysics Data System (ADS)
Mekaouar, Anouar; Ben Amar, Chokri; Redarce, Tanneguy
2009-02-01
Regular colonoscopy has always been regarded as a complicated procedure requiring a tremendous amount of skill to be safely performed. In deed, the practitioner needs to contend with both the tortuousness of the colon and the mastering of a colonoscope. So, he has to take the visual data acquired by the scope's tip into account and rely mostly on his common sense and skill to steer it in a fashion promoting a safe insertion of the device's shaft. In that context, we do propose a new navigation clue for the tip of regular colonoscope in order to assist surgeons over a colonoscopic examination. Firstly, we consider a patch of the inner colon depicted in a regular colonoscopy frame. Then we perform a sketchy 3D reconstruction of the corresponding 2D data. Furthermore, a suggested navigation trajectory ensued on the basis of the obtained relief. The visible and invisible lumen cases are considered. Due to its low cost reckoning, such strategy would allow for the intraoperative configuration changes and thus cut back the non-rigidity effect of the colon. Besides, it would have the trend to provide a safe navigation trajectory through the whole colon, since this approach is aiming at keeping the extremity of the instrument as far as possible from the colon wall during navigation. In order to make effective the considered process, we replaced the original manual control system of a regular colonoscope by a motorized one allowing automatic pan and tilt motions of the device's tip.
12 CFR 311.5 - Regular procedure for closing meetings.
Code of Federal Regulations, 2011 CFR
2011-01-01
... RULES GOVERNING PUBLIC OBSERVATION OF MEETINGS OF THE CORPORATION'S BOARD OF DIRECTORS § 311.5 Regular... deciding whether to close a meeting or portion of a meeting, the Board will consider whether the public... which is proposed to be closed in whole or in part to the public. A single vote may be taken with...
12 CFR 311.5 - Regular procedure for closing meetings.
Code of Federal Regulations, 2012 CFR
2012-01-01
... RULES GOVERNING PUBLIC OBSERVATION OF MEETINGS OF THE CORPORATION'S BOARD OF DIRECTORS § 311.5 Regular... deciding whether to close a meeting or portion of a meeting, the Board will consider whether the public... which is proposed to be closed in whole or in part to the public. A single vote may be taken with...
Regularized Partial and/or Constrained Redundancy Analysis
ERIC Educational Resources Information Center
Takane, Yoshio; Jung, Sunho
2008-01-01
Methods of incorporating a ridge type of regularization into partial redundancy analysis (PRA), constrained redundancy analysis (CRA), and partial and constrained redundancy analysis (PCRA) were discussed. The usefulness of ridge estimation in reducing mean square error (MSE) has been recognized in multiple regression analysis for some time,…
Cost Effectiveness of Premium Versus Regular Gasoline in MCPS Buses.
ERIC Educational Resources Information Center
Baacke, Clifford M.; Frankel, Steven M.
The primary question posed in this study is whether premium or regular gasoline is more cost effective for the Montgomery County Public School (MCPS) bus fleet, as a whole, when miles-per-gallon, cost-per-gallon, and repair costs associated with mileage are considered. On average, both miles-per-gallon, and repair costs-per-mile favor premium…
5 CFR 551.511 - Hourly regular rate of pay.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Hourly regular rate of pay. 551.511 Section 551.511 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS PAY ADMINISTRATION UNDER THE FAIR LABOR STANDARDS ACT Overtime Pay Provisions Overtime Pay Computations § 551.511...
Involving Impaired, Disabled, and Handicapped Persons in Regular Camp Programs.
ERIC Educational Resources Information Center
American Alliance for Health, Physical Education, and Recreation, Washington, DC. Information and Research Utilization Center.
The publication provides some broad guidelines for serving impaired, disabled, and handicapped children in nonspecialized or regular day and residential camps. Part One on the rationale and basis for integrated camping includes three chapters which cover mainstreaming and the normalization principle, the continuum of services (or Cascade System)…
Poisson image reconstruction with Hessian Schatten-norm regularization.
Lefkimmiatis, Stamatios; Unser, Michael
2013-11-01
Poisson inverse problems arise in many modern imaging applications, including biomedical and astronomical ones. The main challenge is to obtain an estimate of the underlying image from a set of measurements degraded by a linear operator and further corrupted by Poisson noise. In this paper, we propose an efficient framework for Poisson image reconstruction, under a regularization approach, which depends on matrix-valued regularization operators. In particular, the employed regularizers involve the Hessian as the regularization operator and Schatten matrix norms as the potential functions. For the solution of the problem, we propose two optimization algorithms that are specifically tailored to the Poisson nature of the noise. These algorithms are based on an augmented-Lagrangian formulation of the problem and correspond to two variants of the alternating direction method of multipliers. Further, we derive a link that relates the proximal map of an l(p) norm with the proximal map of a Schatten matrix norm of order p. This link plays a key role in the development of one of the proposed algorithms. Finally, we provide experimental results on natural and biological images for the task of Poisson image deblurring and demonstrate the practical relevance and effectiveness of the proposed framework.
Adult Regularization of Inconsistent Input Depends on Pragmatic Factors
ERIC Educational Resources Information Center
Perfors, Amy
2016-01-01
In a variety of domains, adults who are given input that is only partially consistent do not discard the inconsistent portion (regularize) but rather maintain the probability of consistent and inconsistent portions in their behavior (probability match). This research investigates the possibility that adults probability match, at least in part,…
Low thrust space vehicle trajectory optimization using regularized variables
NASA Technical Reports Server (NTRS)
Schwenzfeger, K. J.
1974-01-01
Optimizing the trajectory of a low thrust space vehicle usually means solving a nonlinear two point boundary value problem. In general, accuracy requirements necessitate extensive computation times. In celestial mechanics, regularizing transformations of the equations of motion are used to eliminate computational and analytical problems that occur during close approaches to gravitational force centers. It was shown in previous investigations that regularization in the formulation of the trajectory optimization problem may reduce the computation time. In this study, a set of regularized equations describing the optimal trajectory of a continuously thrusting space vehicle is derived. The computational characteristics of the set are investigated and compared to the classical Newtonian unregularized set of equations. The comparison is made for low thrust, minimum time, escape trajectories and numerical calculations of Keplerian orbits. The comparison indicates that in the cases investigated for bad initial guesses of the known boundary values a remarkable reduction in the computation time was achieved. Furthermore, the investigated set of regularized equations shows high numerical stability even for long duration flights and is less sensitive to errors in the guesses of the unknown boundary values.
Regularization of the Hamiltonian constraint compatible with the spinfoam dynamics
NASA Astrophysics Data System (ADS)
Alesci, Emanuele; Rovelli, Carlo
2010-08-01
We introduce a new regularization for Thiemann’s Hamiltonian constraint. The resulting constraint can generate the 1-4 Pachner moves and is therefore more compatible with the dynamics defined by the spinfoam formalism. We calculate its matrix elements and observe the appearance of the 15j Wigner symbol in these.
Model Spaces of Regularity Structures for Space-Fractional SPDEs
NASA Astrophysics Data System (ADS)
Berglund, Nils; Kuehn, Christian
2017-07-01
We study model spaces, in the sense of Hairer, for stochastic partial differential equations involving the fractional Laplacian. We prove that the fractional Laplacian is a singular kernel suitable to apply the theory of regularity structures. Our main contribution is to study the dependence of the model space for a regularity structure on the three-parameter problem involving the spatial dimension, the polynomial order of the nonlinearity, and the exponent of the fractional Laplacian. The goal is to investigate the growth of the model space under parameter variation. In particular, we prove several results in the approaching subcriticality limit leading to universal growth exponents of the regularity structure. A key role is played by the viewpoint that model spaces can be identified with families of rooted trees. Our proofs are based upon a geometrical construction similar to Newton polygons for classical Taylor series and various combinatorial arguments. We also present several explicit examples listing all elements with negative homogeneity by implementing a new symbolic software package to work with regularity structures. We use this package to illustrate our analytical results and to obtain new conjectures regarding coarse-grained network measures for model spaces.
Regularized Partial and/or Constrained Redundancy Analysis
ERIC Educational Resources Information Center
Takane, Yoshio; Jung, Sunho
2008-01-01
Methods of incorporating a ridge type of regularization into partial redundancy analysis (PRA), constrained redundancy analysis (CRA), and partial and constrained redundancy analysis (PCRA) were discussed. The usefulness of ridge estimation in reducing mean square error (MSE) has been recognized in multiple regression analysis for some time,…
The Visually Impaired Student in the Regular Classroom.
ERIC Educational Resources Information Center
Alberta Dept. of Education, Edmonton.
The guide provides strategies for regular teachers to use with visually impaired (VI) students in the province of Alberta, Canada. After an introduction, definitions of terms such as "adventitiously blind" are presented. Next addressed are effects of visual impairment on cognitive development, emotional and social aspects, and…
Preverbal Infants Infer Intentional Agents from the Perception of Regularity
ERIC Educational Resources Information Center
Ma, Lili; Xu, Fei
2013-01-01
Human adults have a strong bias to invoke intentional agents in their intuitive explanations of ordered wholes or regular compositions in the world. Less is known about the ontogenetic origin of this bias. In 4 experiments, we found that 9-to 10-month-old infants expected a human hand, but not a mechanical tool with similar affordances, to be the…
29 CFR 778.408 - The specified regular rate.
Code of Federal Regulations, 2010 CFR
2010-07-01
... POLICY OR INTERPRETATION NOT DIRECTLY RELATED TO REGULATIONS OVERTIME COMPENSATION Exceptions From the Regular Rate Principles Guaranteed Compensation Which Includes Overtime Pay § 778.408 The specified... reasonably be expected to be operative in controlling the employee's compensation. (c) The rate specified...
Nonlinear run-ups of regular waves on sloping structures
NASA Astrophysics Data System (ADS)
Hsu, T.-W.; Liang, S.-J.; Young, B.-D.; Ou, S.-H.
2012-12-01
For coastal risk mapping, it is extremely important to accurately predict wave run-ups since they influence overtopping calculations; however, nonlinear run-ups of regular waves on sloping structures are still not accurately modeled. We report the development of a high-order numerical model for regular waves based on the second-order nonlinear Boussinesq equations (BEs) derived by Wei et al. (1995). We calculated 160 cases of wave run-ups of nonlinear regular waves over various slope structures. Laboratory experiments were conducted in a wave flume for regular waves propagating over three plane slopes: tan α =1/5, 1/4, and 1/3. The numerical results, laboratory observations, as well as previous datasets were in good agreement. We have also proposed an empirical formula of the relative run-up in terms of two parameters: the Iribarren number ξ and sloping structures tan α. The prediction capability of the proposed formula was tested using previous data covering the range ξ ≤ 3 and 1/5 ≤ tan α ≤ 1/2 and found to be acceptable. Our study serves as a stepping stone to investigate run-up predictions for irregular waves and more complex geometries of coastal structures.
Image super-resolution via adaptive filtering and regularization
NASA Astrophysics Data System (ADS)
Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming
2014-11-01
Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert
2010-01-01
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 106 × 106 incomplete matrix with 105 observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques. PMID:21552465
Spectral Regularization Algorithms for Learning Large Incomplete Matrices.
Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert
2010-03-01
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 10(6) × 10(6) incomplete matrix with 10(5) observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques.
Implicit Learning of L2 Word Stress Regularities
ERIC Educational Resources Information Center
Chan, Ricky K. W.; Leung, Janny H. C.
2014-01-01
This article reports an experiment on the implicit learning of second language stress regularities, and presents a methodological innovation on awareness measurement. After practising two-syllable Spanish words, native Cantonese speakers with English as a second language (L2) completed a judgement task. Critical items differed only in placement of…
Elementary Teachers' Perspectives of Inclusion in the Regular Education Classroom
ERIC Educational Resources Information Center
Olinger, Becky Lorraine
2013-01-01
The purpose of this qualitative study was to examine regular education and special education teacher perceptions of inclusion services in an elementary school setting. In this phenomenological study, purposeful sampling techniques and data were used to conduct a study of inclusion in the elementary schools. In-depth one-to-one interviews with 8…
Regular Writing Practice--Strategies for Implementation and Evaluation.
ERIC Educational Resources Information Center
Rucker, Gary H.
Intended for teachers of elementary and secondary school writing, this paper describes the Regular Writing Practice (RWP) program, which combines the philosophical and pedagogical bases of Lyman Hunt's Uninterrupted Sustained Silent Reading program with the instructional methodology of creative writing and composition. The first portion of the…
Regular design fabrics for low cost scaling of integrated circuits
NASA Astrophysics Data System (ADS)
Jhaveri, Tejas
A method for enabling economical scaling for future ICs by the use of regular design to co-develop process and design is discussed. We have made contributions towards creating the framework required for defining the pattern set used for process optimization, process optimization for regular design fabrics, and the analysis of the economic benefit of the prescribed methodology. We describe the technique used to define a small set of equivalent pattern classes that can be used for process optimization and characterization. We employ a novel methodology for determining a smaller optical interaction range by analyzing the change in aerial image by introducing deviations to the underlying regular fabric. We also introduce the concept of critical patterns based on sensitivity to yield detractors as well as discuss means of classifying patterns into equivalent pattern classes based on printability metrics. We demonstrate process simplification with the use of regular design fabrics. The application of single exposure lithography for the 32nm technology node as well as an simplified OPC solution are both discussed. The economic benefit of such process simplification as well as improved yield is quantified by analyzing the lithography cost per good die metric. The lithography cost per good die metric is then applied to analytically determine the optimum design style for 32nm as well as the optimum lithography solution for the 22nm technology node.
Nonnative Processing of Verbal Morphology: In Search of Regularity
ERIC Educational Resources Information Center
Gor, Kira; Cook, Svetlana
2010-01-01
There is little agreement on the mechanisms involved in second language (L2) processing of regular and irregular inflectional morphology and on the exact role of age, amount, and type of exposure to L2 resulting in differences in L2 input and use. The article contributes to the ongoing debates by reporting the results of two experiments on Russian…
Rotating bearings in regular and irregular granular shear packings
NASA Astrophysics Data System (ADS)
Ström, J. A. Ã.
2008-01-01
For 2D regular dense packings of solid mono-size non-sliding disks there is a mechanism for bearing formation under shear that can be explained theoretically. There is, however, no easy way to extend this model to include random dense packings which would better describe natural packings. A numerical model that simulates shear deformation for both near-regular and irregular packings is used to demonstrate that rotating bearings appear roughly with the same density in random and regular packings. The main difference appears in the size distribution of the rotating clusters near the jamming threshold. The size distribution is well described by a scaling form with a large-size cut-off that seems to grow without bounds for regular packings at the jamming threshold, while it remains finite for irregular packings. At packing densities above the jamming transition there can be no shear, unless the disks are allowed to break. Breaking of disks induces a large number of small local bearings. Clusters of rotating particles may contribute to e.g. pre-rupture yielding in landslides, snow avalanches and to the formation of aseismic gaps in tectonic fault zones.
5 CFR 532.203 - Structure of regular wage schedules.
Code of Federal Regulations, 2012 CFR
2012-01-01
... schedule for the area, plus 20 percent of the rate for step 2 of NA-8; (2) For grades NS-9 through NS-15...) Each nonsupervisory and leader regular wage schedule shall have 15 grades, which shall be designated as follows: (1) WG means an appropriated fund nonsupervisory grade; (2) WL means an appropriated fund leader...
Regularity and Energy Conservation for the Compressible Euler Equations
NASA Astrophysics Data System (ADS)
Feireisl, Eduard; Gwiazda, Piotr; Świerczewska-Gwiazda, Agnieszka; Wiedemann, Emil
2017-03-01
We give sufficient conditions on the regularity of solutions to the inhomogeneous incompressible Euler and the compressible isentropic Euler systems in order for the energy to be conserved. Our strategy relies on commutator estimates similar to those employed by Constantin et al. for the homogeneous incompressible Euler equations.
Mainstreaming: Educable Mentally Retarded Children in Regular Classes.
ERIC Educational Resources Information Center
Birch, Jack W.
Described in the monograph are mainstreaming programs for educable mentally retarded (EMR) children in six variously sized school districts within five states. It is noted that mainstreaming is based on the principle of educating most children in the regular classroom and providing special education on the basis of learning needs rather than…
Maximal regularity for perturbed integral equations on periodic Lebesgue spaces
NASA Astrophysics Data System (ADS)
Lizama, Carlos; Poblete, Verónica
2008-12-01
We characterize the maximal regularity of periodic solutions for an additive perturbed integral equation with infinite delay in the vector-valued Lebesgue spaces. Our method is based on operator-valued Fourier multipliers. We also study resonances, characterizing the existence of solutions in terms of a compatibility condition on the forcing term.
Global Regularity for Several Incompressible Fluid Models with Partial Dissipation
NASA Astrophysics Data System (ADS)
Wu, Jiahong; Xu, Xiaojing; Ye, Zhuan
2016-09-01
This paper examines the global regularity problem on several 2D incompressible fluid models with partial dissipation. They are the surface quasi-geostrophic (SQG) equation, the 2D Euler equation and the 2D Boussinesq equations. These are well-known models in fluid mechanics and geophysics. The fundamental issue of whether or not they are globally well-posed has attracted enormous attention. The corresponding models with partial dissipation may arise in physical circumstances when the dissipation varies in different directions. We show that the SQG equation with either horizontal or vertical dissipation always has global solutions. This is in sharp contrast with the inviscid SQG equation for which the global regularity problem remains outstandingly open. Although the 2D Euler is globally well-posed for sufficiently smooth data, the associated equations with partial dissipation no longer conserve the vorticity and the global regularity is not trivial. We are able to prove the global regularity for two partially dissipated Euler equations. Several global bounds are also obtained for a partially dissipated Boussinesq system.
Simulated Administration of a Regular Guidance Operation (SARGO).
ERIC Educational Resources Information Center
Fredrickson, Ronald H.; Popken, Charles F.
Simulated Administration of a Regular Guidance Operation (SARGO) is a program for the training of directors of guidance and pupil personnel services. The objective of SARGO is to prepare directors of guidance services to: (1) prepare a written description of a pupil personnel program; (2) interact with a school administrator to clarify role…
Regularization in Short-Term Memory for Serial Order
ERIC Educational Resources Information Center
Botvinick, Matthew; Bylsma, Lauren M.
2005-01-01
Previous research has shown that short-term memory for serial order can be influenced by background knowledge concerning regularities of sequential structure. Specifically, it has been shown that recall is superior for sequences that fit well with familiar sequencing constraints. The authors report a corresponding effect pertaining to serial…
Rhythm's Gonna Get You: Regular Meter Facilitates Semantic Sentence Processing
ERIC Educational Resources Information Center
Rothermich, Kathrin; Schmidt-Kassow, Maren; Kotz, Sonja A.
2012-01-01
Rhythm is a phenomenon that fundamentally affects the perception of events unfolding in time. In language, we define "rhythm" as the temporal structure that underlies the perception and production of utterances, whereas "meter" is defined as the regular occurrence of beats (i.e. stressed syllables). In stress-timed languages such as German, this…
A Policy for Systemwide Implementation of the "Regular Education Initiative."
ERIC Educational Resources Information Center
Doyle, Robert J.; LaGrasta, Thomas M.
This policy statement developed on behalf of the Sharon (Massachusetts) public school system focuses on the need to decrease referrals for special education services, provide support to regular classroom teachers to adapt instruction for all students, and improve the effectiveness of the supplementary instruction provided to students with learning…
An Interesting Lemma for Regular C-fractions
NASA Astrophysics Data System (ADS)
Chen, Kwang-Wu
2003-12-01
In this short note we give an interesting lemma for regular C-fractions. Applying this lemma we obtain some congruence properties of some classical numbers such as the Springer numbers of even index, the median Euler numbers, the median Genocchi numbers, and the tangent numbers.
Preverbal Infants Infer Intentional Agents from the Perception of Regularity
ERIC Educational Resources Information Center
Ma, Lili; Xu, Fei
2013-01-01
Human adults have a strong bias to invoke intentional agents in their intuitive explanations of ordered wholes or regular compositions in the world. Less is known about the ontogenetic origin of this bias. In 4 experiments, we found that 9-to 10-month-old infants expected a human hand, but not a mechanical tool with similar affordances, to be the…
Elementary Teachers' Perspectives of Inclusion in the Regular Education Classroom
ERIC Educational Resources Information Center
Olinger, Becky Lorraine
2013-01-01
The purpose of this qualitative study was to examine regular education and special education teacher perceptions of inclusion services in an elementary school setting. In this phenomenological study, purposeful sampling techniques and data were used to conduct a study of inclusion in the elementary schools. In-depth one-to-one interviews with 8…
New Technologies in Portugal: Regular Middle and High School
ERIC Educational Resources Information Center
Florentino, Teresa; Sanchez, Lucas; Joyanes, Luis
2010-01-01
Purpose: The purpose of this paper is to elaborate upon the relation between information and communication technologies (ICT), particularly web-based resources, and their use, programs and learning in Portuguese middle and high regular public schools. Design/methodology/approach: Adding collected documentation on curriculum, laws and other related…
Adult Regularization of Inconsistent Input Depends on Pragmatic Factors
ERIC Educational Resources Information Center
Perfors, Amy
2016-01-01
In a variety of domains, adults who are given input that is only partially consistent do not discard the inconsistent portion (regularize) but rather maintain the probability of consistent and inconsistent portions in their behavior (probability match). This research investigates the possibility that adults probability match, at least in part,…
The properties of probabilistic simple regular sticker system
NASA Astrophysics Data System (ADS)
Selvarajoo, Mathuri; Fong, Wan Heng; Sarmin, Nor Haniza; Turaev, Sherzod
2015-10-01
A mathematical model for DNA computing using the recombination behavior of DNA molecules, known as a sticker system, has been introduced in 1998. In sticker system, the sticker operation is based on the Watson-Crick complementary feature of DNA molecules. The computation of sticker system starts from an incomplete double-stranded sequence. Then by iterative sticking operations, a complete double-stranded sequence is obtained. It is known that sticker systems with finite sets of axioms and sticker rule (including the simple regular sticker system) generate only regular languages. Hence, different types of restrictions have been considered to increase the computational power of the languages generated by the sticker systems. In this paper, we study the properties of probabilistic simple regular sticker systems. In this variant of sticker system, probabilities are associated with the axioms, and the probability of a generated string is computed by multiplying the probabilities of all occurrences of the initial strings. The language are selected according to some probabilistic requirements. We prove that the probabilistic enhancement increases the computational power of simple regular sticker systems.
The Hearing Impaired Student in the Regular Classroom.
ERIC Educational Resources Information Center
Alberta Dept. of Education, Edmonton.
The guide provides strategies for teachers to use with deaf and hearing impaired (HI) students in regular classrooms in the province of Alberta, Canada. An introductory section includes symptoms of a suspected hearing loss and a sample audiogram to aid teachers in recognizing the problem. Ways to meet special needs at different age levels are…
The Physically/Medically Handicapped Student in the Regular Classroom.
ERIC Educational Resources Information Center
Alberta Dept. of Education, Edmonton.
The guide outlines modifications, adaptations, and social interaction approaches for school staff to use with physically handicapped and regular students in integrated classrooms in the province of Alberta, Canada. Guidelines are provided for the following main categories and subsets (in parentheses): lifting and transferring techniques (methods…
From Numbers to Letters: Feedback Regularization in Visual Word Recognition
ERIC Educational Resources Information Center
Molinaro, Nicola; Dunabeitia, Jon Andoni; Marin-Gutierrez, Alejandro; Carreiras, Manuel
2010-01-01
Word reading in alphabetic languages involves letter identification, independently of the format in which these letters are written. This process of letter "regularization" is sensitive to word context, leading to the recognition of a word even when numbers that resemble letters are inserted among other real letters (e.g., M4TERI4L). The present…
47 CFR 76.614 - Cable television system regular monitoring.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 47 Telecommunication 4 2011-10-01 2011-10-01 false Cable television system regular monitoring. 76.614 Section 76.614 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Technical Standards § 76.614 Cable television...
Designing and Implementing a Mainstream Course for Regular Early Educators.
ERIC Educational Resources Information Center
Wolf, Judith M.
The University of Minnesota and the Minnesota State Department of Education joined forces to design and implement a course to prepare regular educators to work with handicapped children. The purposes of the course were to present a rationale and philosophy for integrating special needs children into mainstream settings and to offer a variety of…
Regular and homeward travel speeds of arctic wolves
Mech, L.D.
1994-01-01
Single wolves (Canis lupus arctos), a pair, and a pack of five habituated to the investigator on an all-terrain vehicle were followed on Ellesmere Island, Northwest Territories, Canada, during summer. Their mean travel speed was measured on barren ground at 8.7 km/h during regular travel and 10.0 km/h when returning to a den.
A simple way to measure daily lifestyle regularity
NASA Technical Reports Server (NTRS)
Monk, Timothy H.; Frank, Ellen; Potts, Jaime M.; Kupfer, David J.
2002-01-01
A brief diary instrument to quantify daily lifestyle regularity (SRM-5) is developed and compared with a much longer version of the instrument (SRM-17) described and used previously. Three studies are described. In Study 1, SRM-17 scores (2 weeks) were collected from a total of 293 healthy control subjects (both genders) aged between 19 and 92 years. Five items (1) Get out of bed, (2) First contact with another person, (3) Start work, housework or volunteer activities, (4) Have dinner, and (5) Go to bed were then selected from the 17 items and SRM-5 scores calculated as if these five items were the only ones collected. Comparisons were made with SRM-17 scores from the same subject-weeks, looking at correlations between the two SRM measures, and the effects of age and gender on lifestyle regularity as measured by the two instruments. In Study 2 this process was repeated in a group of 27 subjects who were in remission from unipolar depression after treatment with psychotherapy and who completed SRM-17 for at least 20 successive weeks. SRM-5 and SRM-17 scores were then correlated within an individual using time as the random variable, allowing an indication of how successful SRM-5 was in tracking changes in lifestyle regularity (within an individual) over time. In Study 3 an SRM-5 diary instrument was administered to 101 healthy control subjects (both genders, aged 20-59 years) for two successive weeks to obtain normative measures and to test for correlations with age and morningness. Measures of lifestyle regularity from SRM-5 correlated quite well (about 0.8) with those from SRM-17 both between subjects, and within-subjects over time. As a detector of irregularity as defined by SRM-17, the SRM-5 instrument showed acceptable values of kappa (0.69), sensitivity (74%) and specificity (95%). There were, however, differences in mean level, with SRM-5 scores being about 0.9 units [about one standard deviation (SD)] above SRM-17 scores from the same subject-weeks. SRM-5
Sparse regularization techniques provide novel insights into outcome integration processes.
Mohr, Holger; Wolfensteller, Uta; Frimmel, Steffi; Ruge, Hannes
2015-01-01
By exploiting information that is contained in the spatial arrangement of neural activations, multivariate pattern analysis (MVPA) can detect distributed brain activations which are not accessible by standard univariate analysis. Recent methodological advances in MVPA regularization techniques have made it feasible to produce sparse discriminative whole-brain maps with highly specific patterns. Furthermore, the most recent refinement, the Graph Net, explicitly takes the 3D-structure of fMRI data into account. Here, these advanced classification methods were applied to a large fMRI sample (N=70) in order to gain novel insights into the functional localization of outcome integration processes. While the beneficial effect of differential outcomes is well-studied in trial-and-error learning, outcome integration in the context of instruction-based learning has remained largely unexplored. In order to examine neural processes associated with outcome integration in the context of instruction-based learning, two groups of subjects underwent functional imaging while being presented with either differential or ambiguous outcomes following the execution of varying stimulus-response instructions. While no significant univariate group differences were found in the resulting fMRI dataset, L1-regularized (sparse) classifiers performed significantly above chance and also clearly outperformed the standard L2-regularized (dense) Support Vector Machine on this whole-brain between-subject classification task. Moreover, additional L2-regularization via the Elastic Net and spatial regularization by the Graph Net improved interpretability of discriminative weight maps but were accompanied by reduced classification accuracies. Most importantly, classification based on sparse regularization facilitated the identification of highly specific regions differentially engaged under ambiguous and differential outcome conditions, comprising several prefrontal regions previously associated with
Semi-regular biorthogonal pairs and generalized Riesz bases
NASA Astrophysics Data System (ADS)
Inoue, H.
2016-11-01
In this paper we introduce general theories of semi-regular biorthogonal pairs, generalized Riesz bases and its physical applications. Here we deal with biorthogonal sequences {ϕn} and {ψn} in a Hilbert space H , with domains D ( ϕ ) = { x ∈ H ; ∑ k = 0 ∞ |" separators=" ( x | ϕ k ) | 2 < ∞ } and D ( ψ ) = { x ∈ H ; ∑ k = 0 ∞ |" separators=" ( x | ψ k ) | 2 < ∞ } and linear spans Dϕ ≡ Span{ϕn} and Dψ ≡ Span{ψn}. A biorthogonal pair ({ϕn}, {ψn}) is called regular if both Dϕ and Dψ are dense in H , and it is called semi-regular if either Dϕ and D(ϕ) or Dψ and D(ψ) are dense in H . In a previous paper [H. Inoue, J. Math. Phys. 57, 083511 (2016)], we have shown that if ({ϕn}, {ψn}) is a regular biorthogonal pair then both {ϕn} and {ψn} are generalized Riesz bases defined in the work of Inoue and Takakura [J. Math. Phys. 57, 083505 (2016)]. Here we shall show that the same result holds true if the pair is only semi-regular by using operators Tϕ,e, Te,ϕ, Tψ,e, and Te,ψ defined by an orthonormal basis e in H and a biorthogonal pair ({ϕn}, {ψn}). Furthermore, we shall apply this result to pseudo-bosons in the sense of the papers of Bagarello [J. Math. Phys. 51, 023531 (2010); J. Phys. A 44, 015205 (2011); Phys. Rev. A 88, 032120 (2013); and J. Math. Phys. 54, 063512 (2013)].
A theoretical foundation for multi-scale regular vegetation patterns.
Tarnita, Corina E; Bonachela, Juan A; Sheffer, Efrat; Guyton, Jennifer A; Coverdale, Tyler C; Long, Ryan A; Pringle, Robert M
2017-01-18
Self-organized regular vegetation patterns are widespread and thought to mediate ecosystem functions such as productivity and robustness, but the mechanisms underlying their origin and maintenance remain disputed. Particularly controversial are landscapes of overdispersed (evenly spaced) elements, such as North American Mima mounds, Brazilian murundus, South African heuweltjies, and, famously, Namibian fairy circles. Two competing hypotheses are currently debated. On the one hand, models of scale-dependent feedbacks, whereby plants facilitate neighbours while competing with distant individuals, can reproduce various regular patterns identified in satellite imagery. Owing to deep theoretical roots and apparent generality, scale-dependent feedbacks are widely viewed as a unifying and near-universal principle of regular-pattern formation despite scant empirical evidence. On the other hand, many overdispersed vegetation patterns worldwide have been attributed to subterranean ecosystem engineers such as termites, ants, and rodents. Although potentially consistent with territorial competition, this interpretation has been challenged theoretically and empirically and (unlike scale-dependent feedbacks) lacks a unifying dynamical theory, fuelling scepticism about its plausibility and generality. Here we provide a general theoretical foundation for self-organization of social-insect colonies, validated using data from four continents, which demonstrates that intraspecific competition between territorial animals can generate the large-scale hexagonal regularity of these patterns. However, this mechanism is not mutually exclusive with scale-dependent feedbacks. Using Namib Desert fairy circles as a case study, we present field data showing that these landscapes exhibit multi-scale patterning-previously undocumented in this system-that cannot be explained by either mechanism in isolation. These multi-scale patterns and other emergent properties, such as enhanced resistance to
Two vortex-blob regularization models for vortex sheet motion
NASA Astrophysics Data System (ADS)
Sohn, Sung-Ik
2014-04-01
Evolving vortex sheets generally form singularities in finite time. The vortex blob model is an approach to regularize the vortex sheet motion and evolve past singularity formation. In this paper, we thoroughly compare two such regularizations: the Krasny-type model and the Beale-Majda model. It is found from a linear stability analysis that both models have exponentially decaying growth rates for high wavenumbers, but the Beale-Majda model has a faster decaying rate than the Krasny model. The Beale-Majda model thus gives a stronger regularization to the solution. We apply the blob models to the two example problems: a periodic vortex sheet and an elliptically loaded wing. The numerical results show that the solutions of the two models are similar in large and small scales, but are fairly different in intermediate scales. The sheet of the Beale-Majda model has more spiral turns than the Krasny-type model for the same value of the regularization parameter δ. We give numerical evidences that the solutions of the two models agree for an increasing amount of spiral turns and tend to converge to the same limit as δ is decreased. The inner spiral turns of the blob models behave differently with the outer turns and satisfy a self-similar form. We also examine irregular motions of the sheet at late times and find that the irregular motions shrink as δ is decreased. This fact suggests a convergence of the blob solution to the weak solution of infinite regular spiral turns.
Tollen, Laura A; Ross, Murray N; Poor, Stephen
2004-08-01
To determine whether the offering of a consumer-directed health plan (CDHP) is likely to cause risk segmentation in an employer group. STUDY SETTING AND DATA SOURCE: The study population comprises the approximately 10,000 people (employees and dependents) enrolled as members of the employee health benefit program of Humana Inc. at its headquarters in Louisville, Kentucky, during the benefit years starting July 1, 2000, and July 1, 2001. This analysis is based on primary collection of claims, enrollment, and employment data for those employees and dependents. This is a case study of the experience of a single employer in offering two consumer-directed health plan options ("Coverage First 1" and "Coverage First 2") to its employees. We assessed the risk profile of those choosing the Coverage First plans and those remaining in more traditional health maintenance organization (HMO) and preferred provider organization (PPO) coverage. Risk was measured using prior claims (in dollars per member per month), prior utilization (admissions/1,000; average length of stay; prescriptions/1,000; physician office visit services/1,000), a pharmacy-based risk assessment tool (developed by Ingenix), and demographics. Complete claims and administrative data were provided by Humana Inc. for the two-year study period. Unique identifiers enabled us to track subscribers' individual enrollment and utilization over this period. Based on demographic data alone, there did not appear to be a difference in the risk profiles of those choosing versus not choosing Coverage First. However, based on prior claims and prior use data, it appeared that those who chose Coverage First were healthier than those electing to remain in more traditional coverage. For each of five services, prior-year usage by people who subsequently enrolled in Coverage First 1 (CF1) was below 60 percent of the average for the whole group. Hospital and maternity admissions per thousand were less than 30 percent of the overall
Tollen, Laura A; Ross, Murray N; Poor, Stephen
2004-01-01
Objective To determine whether the offering of a consumer-directed health plan (CDHP) is likely to cause risk segmentation in an employer group. Study Setting and Data Source The study population comprises the approximately 10,000 people (employees and dependents) enrolled as members of the employee health benefit program of Humana Inc. at its headquarters in Louisville, Kentucky, during the benefit years starting July 1, 2000, and July 1, 2001. This analysis is based on primary collection of claims, enrollment, and employment data for those employees and dependents. Study Design This is a case study of the experience of a single employer in offering two consumer-directed health plan options (“Coverage First 1” and “Coverage First 2”) to its employees. We assessed the risk profile of those choosing the Coverage First plans and those remaining in more traditional health maintenance organization (HMO) and preferred provider organization (PPO) coverage. Risk was measured using prior claims (in dollars per member per month), prior utilization (admissions/1,000; average length of stay; prescriptions/1,000; physician office visit services/1,000), a pharmacy-based risk assessment tool (developed by Ingenix), and demographics. Data Collection/Extraction Methods Complete claims and administrative data were provided by Humana Inc. for the two-year study period. Unique identifiers enabled us to track subscribers' individual enrollment and utilization over this period. Principal Findings Based on demographic data alone, there did not appear to be a difference in the risk profiles of those choosing versus not choosing Coverage First. However, based on prior claims and prior use data, it appeared that those who chose Coverage First were healthier than those electing to remain in more traditional coverage. For each of five services, prior-year usage by people who subsequently enrolled in Coverage First 1 (CF1) was below 60 percent of the average for the whole group
Separate Magnitude and Phase Regularization via Compressed Sensing
Noll, Douglas C.; Nielsen, Jon-Fredrik; Fessler, Jeffrey A.
2012-01-01
Compressed sensing (CS) has been used for accelerating magnetic resonance imaging (MRI) acquisitions, but its use in applications with rapid spatial phase variations is challenging, e.g., proton resonance frequency shift (PRF-shift) thermometry and velocity mapping. Previously, an iterative MRI reconstruction with separate magnitude and phase regularization was proposed for applications where magnitude and phase maps are both of interest, but it requires fully sampled data and unwrapped phase maps. In this paper, CS is combined into this framework to reconstruct magnitude and phase images accurately from undersampled data. Moreover, new phase regularization terms are proposed to accommodate phase wrapping and to reconstruct images with encoded phase variations, e.g., PRF-shift thermometry and velocity mapping. The proposed method is demonstrated with simulated thermometry data and in-vivo velocity mapping data and compared to conventional phase corrected CS. PMID:22552571
Regularization of inverse photomask synthesis to enhance manufacturability
NASA Astrophysics Data System (ADS)
Jia, Ningning; Wong, Alfred K.; Lam, Edmund Y.
2009-12-01
Mask manufacturability has been considered as a major issue in the adoption of inverse lithography (IL) in practice. With smaller technology nodes, IL distorts the mask pattern more aggressively. The distorted mask often contains curvilinear contour and irregular shapes, which cast a heavy computation burden on segmentation and data preparation. Total variation (TV) has been used for regularization in previous work, but it is not very effective in regulating the mask shape to be rectangular. In this paper, we apply TV regularization not only on the mask image but also on the mask edges, which forces the curves of edges to be more vertical or horizontal, because they give smaller TV values. Except for rectilinearity, a group of geometrical specifications of the mask pattern set by mask manufacture rule control (MRC) is also important for mask manufacturability. To prevent these characteristics from appearing, we also propose an intervention scheme into the optimization framework.
Note on entanglement entropy and regularization in holographic interface theories
NASA Astrophysics Data System (ADS)
Gutperle, Michael; Trivella, Andrea
2017-03-01
We discuss the computation of holographic entanglement entropy for interface conformal field theories. The fact that globally well-defined Fefferman-Graham coordinates are difficult to construct makes the regularization of the holographic theory challenging. We introduce a simple new cutoff procedure, which we call "double cutoff" regularization. We test the new cutoff procedure by comparing the results for holographic entanglement entropies using other cutoff procedures and find agreement. We also study three dimensional conformal field theories with a two dimensional interface. In that case the dual bulk geometry is constructed using warped geometry with an AdS3 factor. We define an effective central charge to the interface through the Brown-Henneaux formula for the AdS3 factor. We investigate two concrete examples, showing that the same effective central charge appears in the computation of entanglement entropy and governs the conformal anomaly.
Resolving intravoxel fiber architecture using nonconvex regularized blind compressed sensing.
Chu, C Y; Huang, J P; Sun, C Y; Liu, W Y; Zhu, Y M
2015-03-21
In diffusion magnetic resonance imaging, accurate and reliable estimation of intravoxel fiber architectures is a major prerequisite for tractography algorithms or any other derived statistical analysis. Several methods have been proposed that estimate intravoxel fiber architectures using low angular resolution acquisitions owing to their shorter acquisition time and relatively low b-values. But these methods are highly sensitive to noise. In this work, we propose a nonconvex regularized blind compressed sensing approach to estimate intravoxel fiber architectures in low angular resolution acquisitions. The method models diffusion-weighted (DW) signals as a sparse linear combination of unfixed reconstruction basis functions and introduces a nonconvex regularizer to enhance the noise immunity. We present a general solving framework to simultaneously estimate the sparse coefficients and the reconstruction basis. Experiments on synthetic, phantom, and real human brain DW images demonstrate the superiority of the proposed approach.
Automated graph regularized projective nonnegative matrix factorization for document clustering.
Pei, Xiaobing; Wu, Tao; Chen, Chuanbo
2014-10-01
In this paper, a novel projective nonnegative matrix factorization (PNMF) method for enhancing the clustering performance is presented, called automated graph regularized projective nonnegative matrix factorization (AGPNMF). The idea of AGPNMF is to extend the original PNMF by incorporating the automated graph regularized constraint into the PNMF decomposition. The key advantage of this approach is that AGPNMF simultaneously finds graph weights matrix and dimensionality reduction of data. AGPNMF seeks to extract the data representation space that preserves the local geometry structure. This character makes AGPNMF more intuitive and more powerful than the original method for clustering tasks. The kernel trick is used to extend AGPNMF model related to the input space by some nonlinear map. The proposed method has been applied to the problem of document clustering using the well-known Reuters-21578, TDT2, and SECTOR data sets. Our experimental evaluations show that the proposed method enhances the performance of PNMF for document clustering.
Partial Regularity for Holonomic Minimisers of Quasiconvex Functionals
NASA Astrophysics Data System (ADS)
Hopper, Christopher P.
2016-10-01
We prove partial regularity for local minimisers of certain strictly quasiconvex integral functionals, over a class of Sobolev mappings into a compact Riemannian manifold, to which such mappings are said to be holonomically constrained. Our approach uses the lifting of Sobolev mappings to the universal covering space, the connectedness of the covering space, an application of Ekeland's variational principle and a certain tangential A-harmonic approximation lemma obtained directly via a Lipschitz approximation argument. This allows regularity to be established directly on the level of the gradient. Several applications to variational problems in condensed matter physics with broken symmetries are also discussed, in particular those concerning the superfluidity of liquid helium-3 and nematic liquid crystals.
Giant regular polyhedra from calixarene carboxylates and uranyl
Pasquale, Sara; Sattin, Sara; Escudero-Adán, Eduardo C.; Martínez-Belmonte, Marta; de Mendoza, Javier
2012-01-01
Self-assembly of large multi-component systems is a common strategy for the bottom-up construction of discrete, well-defined, nanoscopic-sized cages. Icosahedral or pseudospherical viral capsids, built up from hundreds of identical proteins, constitute typical examples of the complexity attained by biological self-assembly. Chemical versions of the so-called 5 Platonic regular or 13 Archimedean semi-regular polyhedra are usually assembled combining molecular platforms with metals with commensurate coordination spheres. Here we report novel, self-assembled cages, using the conical-shaped carboxylic acid derivatives of calix[4]arene and calix[5]arene as ligands, and the uranyl cation UO22+ as a metallic counterpart, which coordinates with three carboxylates at the equatorial plane, giving rise to hexagonal bipyramidal architectures. As a result, octahedral and icosahedral anionic metallocages of nanoscopic dimensions are formed with an unusually small number of components. PMID:22510690
Drop impact upon superhydrophobic surfaces with regular and hierarchical roughness
NASA Astrophysics Data System (ADS)
Lv, Cunjing; Hao, Pengfei; Zhang, Xiwen; He, Feng
2016-04-01
Recent studies demonstrate that roughness and morphologies of the textures play essential roles on the dynamics of water drop impacting onto superhydrophobic substrates. Particularly, significant reduction of contact time has greatly attracted people's attention. We experimentally investigate drop impact dynamics onto three types of superhydrophobic surfaces, consisting of regular micropillars, two-tier textures with nano/micro-scale roughness, and hierarchical textures with random roughness. It shows that the contact time is controlled by the Weber number and the roughness of the surface. Compared with drop impact on regular micropillared surfaces, the contact time can be finely reduced by increasing the Weber number on surfaces with two-tier textures, but can be remarkably reduced on surfaces with hierarchical textures resulting from the prompt splash and fragmentation of liquid lamellae. Our study may shed lights on textured materials fabrication, allowing a rapid drop detachment to realize broad applications.
Detection of Fukushima plume within regular Slovenian environmental radioactivity surveillance.
Glavič-Cindro, D; Benedik, L; Kožar Logar, J; Vodenik, B; Zorko, B
2013-11-01
After the Fukushima accident aerosol and rain water samples collected within regular national monitoring programmes were carefully analysed. In rain water samples, aerosol and iodine filters collected in the second half of March and in April 2011 I-131, Cs-134 and Cs-137 were detected. In May 2011 the activities of I-131 and Cs-134 were close or below the detection limit and Cs-137 reached values from the period before the Fukushima accident. Additionally plutonium and americium activity concentrations in aerosol filters were analysed. These measured data were compared with measured data after the Chernobyl contamination in Slovenia in 1986. We can conclude that with adequate regular monitoring programmes influences of radioactivity contamination due to nuclear accidents worldwide can be properly assessed. Copyright © 2013 Elsevier Ltd. All rights reserved.
Compressing Regular Expressions' DFA Table by Matrix Decomposition
NASA Astrophysics Data System (ADS)
Liu, Yanbing; Guo, Li; Liu, Ping; Tan, Jianlong
Recently regular expression matching has become a research focus as a result of the urgent demand for Deep Packet Inspection (DPI) in many network security systems. Deterministic Finite Automaton (DFA), which recognizes a set of regular expressions, is usually adopted to cater to the need for real-time processing of network traffic. However, the huge memory usage of DFA prevents it from being applied even on a medium-sized pattern set. In this article, we propose a matrix decomposition method for DFA table compression. The basic idea of the method is to decompose a DFA table into the sum of a row vector, a column vector and a sparse matrix, all of which cost very little space. Experiments on typical rule sets show that the proposed method significantly reduces the memory usage and still runs at fast searching speed.
Statistical regularities in the rank-citation profile of scientists
Petersen, Alexander M.; Stanley, H. Eugene; Succi, Sauro
2011-01-01
Recent science of science research shows that scientific impact measures for journals and individual articles have quantifiable regularities across both time and discipline. However, little is known about the scientific impact distribution at the scale of an individual scientist. We analyze the aggregate production and impact using the rank-citation profile ci(r) of 200 distinguished professors and 100 assistant professors. For the entire range of paper rank r, we fit each ci(r) to a common distribution function. Since two scientists with equivalent Hirsch h-index can have significantly different ci(r) profiles, our results demonstrate the utility of the βi scaling parameter in conjunction with hi for quantifying individual publication impact. We show that the total number of citations Ci tallied from a scientist's Ni papers scales as . Such statistical regularities in the input-output patterns of scientists can be used as benchmarks for theoretical models of career progress. PMID:22355696
Persistent low-grade inflammation and regular exercise.
Astrom, Maj-Briit; Feigh, Michael; Pedersen, Bente Klarlund
2010-01-01
Persistent low-grade systemic inflammation is a feature of chronic diseases such as cardiovascular disease (CVD), type 2 diabetes and dementia and evidence exists that inflammation is a causal factor in the development of insulin resistance and atherosclerosis. Regular exercise offers protection against all of these diseases and recent evidence suggests that the protective effect of exercise may to some extent be ascribed to an anti-inflammatory effect of regular exercise. Visceral adiposity contributes to systemic inflammation and is independently associated with the occurrence of CVD, type 2 diabetes and dementia. We suggest that the anti-inflammatory effects of exercise may be mediated via a long-term effect of exercise leading to a reduction in visceral fat mass and/or by induction of anti-inflammatory cytokines with each bout of exercise.
Mechanisms of evolution of avalanches in regular graphs.
Handford, Thomas P; Pérez-Reche, Francisco J; Taraskin, Sergei N
2013-06-01
A mapping of avalanches occurring in the zero-temperature random-field Ising model to life periods of a population experiencing immigration is established. Such a mapping allows the microscopic criteria for the occurrence of an infinite avalanche in a q-regular graph to be determined. A key factor for an avalanche of spin flips to become infinite is that it interacts in an optimal way with previously flipped spins. Based on these criteria, we explain why an infinite avalanche can occur in q-regular graphs only for q>3 and suggest that this criterion might be relevant for other systems. The generating function techniques developed for branching processes are applied to obtain analytical expressions for the durations, pulse shapes, and power spectra of the avalanches. The results show that only very long avalanches exhibit a significant degree of universality.
Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms
NASA Astrophysics Data System (ADS)
Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan
2010-12-01
This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.
Unnoticed regularity violation elicits change-related brain activity.
Czigler, István; Pató, Lívia
2009-03-01
Event-related brain electric activity (ERP) was investigated to unnoticed visual changes. The orientation of grid elements (vertical or horizontal) changed after the presentation of 10-15 identical stimuli. The grid patterns were task irrelevant, and were presented in the background of a shape discrimination task. During the first half of the session, participants were unaware of the stimulus change. However, in comparison to the ERPs to the fifth identical stimuli, stimulus change elicited posterior negativities in the 270-375 ms range (visual mismatch negativity, vMMN). With participants instructed on the stimulus change, negativities emerged with earlier onset and with wider distribution. When stimulus change was preceded by only two identical stimuli, there were no such ERP effects. As the results show, a longer sequence of identical unattended stimuli may establish the memory representation of stimulus regularity, and violation of regularity is indicated by posterior negative ERP components (vMMN).
Existence and Regularity for Dynamic Viscoelastic Adhesive Contact with Damage
Kuttler, Kenneth L. Shillor, Meir Fernandez, Jose R.
2006-01-15
A model for the dynamic process of frictionless adhesive contact between a viscoelastic body and a reactive foundation, which takes into account the damage of the material resulting from tension or compression, is presented. Contact is described by the normal compliance condition. Material damage is modelled by the damage field, which measures the pointwise fractional decrease in the load-carrying capacity of the material, and its evolution is described by a differential inclusion. The model allows for different damage rates caused by tension or compression. The adhesion is modelled by the bonding field, which measures the fraction of active bonds on the contact surface. The existence of the unique weak solution is established using the theory of set-valued pseudomonotone operators introduced by Kuttler and Shillor (1999). Additional regularity of the solution is obtained when the problem data is more regular and satisfies appropriate compatibility conditions.
Validity and Regularization of Classical Half-Space Equations
NASA Astrophysics Data System (ADS)
Li, Qin; Lu, Jianfeng; Sun, Weiran
2017-01-01
Recent result (Wu and Guo in Commun Math Phys 336(3):1473-1553, 2015) has shown that over the 2D unit disk, the classical half-space equation (CHS) for the neutron transport does not capture the correct boundary layer behaviour as long believed. In this paper we develop a regularization technique for CHS to any arbitrary order and use its first-order regularization to show that in the case of the 2D unit disk, although CHS misrepresents the boundary layer behaviour, it does give the correct boundary condition for the interior macroscopic (Laplace) equation. Therefore CHS is still a valid equation to recover the correct boundary condition for the interior Laplace equation over the 2D unit disk.
Generalization Bounds Derived IPM-Based Regularization for Domain Adaptation.
Meng, Juan; Hu, Guyu; Li, Dong; Zhang, Yanyan; Pan, Zhisong
2016-01-01
Domain adaptation has received much attention as a major form of transfer learning. One issue that should be considered in domain adaptation is the gap between source domain and target domain. In order to improve the generalization ability of domain adaption methods, we proposed a framework for domain adaptation combining source and target data, with a new regularizer which takes generalization bounds into account. This regularization term considers integral probability metric (IPM) as the distance between the source domain and the target domain and thus can bound up the testing error of an existing predictor from the formula. Since the computation of IPM only involves two distributions, this generalization term is independent with specific classifiers. With popular learning models, the empirical risk minimization is expressed as a general convex optimization problem and thus can be solved effectively by existing tools. Empirical studies on synthetic data for regression and real-world data for classification show the effectiveness of this method.
Improved regularized solution of the inverse problem in turbidimetric measurements.
Mroczka, Janusz; Szczuczyński, Damian
2010-08-20
We present results of simulation research on the constrained regularized least-squares (RLS) solution of the ill-conditioned inverse problem in turbidimetric measurements. The problem is formulated in terms of the discretized Fredholm integral equation of the first kind. The inverse problem in turbidimetric measurements consists in determining particle size distribution (PSD) function of particulate system on the basis of turbidimetric measurements. The desired PSD should satisfy two constraints: nonnegativity of PSD values and normalization of PSD to unity when integrated over the whole range of particle size. Incorporating the constraints into the RLS method leads to the constrained regularized least-squares (CRLS) method, which is realized by means of an active set algorithm of quadratic programming. Results of simulation research prove that the CRLS method performs considerably better with reconstruction of PSD than the RLS method in terms of better fidelity and smaller uncertainty.
Soft Constraints in Nonlinear Spectral Fitting with Regularized Lineshape Deconvolution
Zhang, Yan; Shen, Jun
2012-01-01
This paper presents a novel method for incorporating a priori knowledge into regularized nonlinear spectral fitting as soft constraints. Regularization was recently introduced to lineshape deconvolution as a method for correcting spectral distortions. Here, the deconvoluted lineshape was described by a new type of lineshape model and applied to spectral fitting. The non-linear spectral fitting was carried out in two steps that were subject to hard constraints and soft constraints, respectively. The hard constraints step provided a starting point and, therefore, only the changes of the relevant variables were constrained in the soft constraints step and incorporated into the linear sub-steps of the Levenberg-Marquardt algorithm. The method was demonstrated using localized averaged echo time point resolved spectroscopy (PRESS) proton spectroscopy of human brains. PMID:22618964
Information transmission using non-poisson regular firing.
Koyama, Shinsuke; Omi, Takahiro; Kass, Robert E; Shinomoto, Shigeru
2013-04-01
In many cortical areas, neural spike trains do not follow a Poisson process. In this study, we investigate a possible benefit of non-Poisson spiking for information transmission by studying the minimal rate fluctuation that can be detected by a Bayesian estimator. The idea is that an inhomogeneous Poisson process may make it difficult for downstream decoders to resolve subtle changes in rate fluctuation, but by using a more regular non-Poisson process, the nervous system can make rate fluctuations easier to detect. We evaluate the degree to which regular firing reduces the rate fluctuation detection threshold. We find that the threshold for detection is reduced in proportion to the coefficient of variation of interspike intervals.
The unique maximal GF-regular submodule of a module.
Abduldaim, Areej M; Chen, Sheng
2013-01-01
An R-module A is called GF-regular if, for each a ∈ A and r ∈ R, there exist t ∈ R and a positive integer n such that r(n)tr(n)a = r(n)a. We proved that each unitary R-module A contains a unique maximal GF-regular submodule, which we denoted by M GF(A). Furthermore, the radical properties of A are investigated; we proved that if A is an R-module and K is a submodule of A, then MGF(K) = K∩M GF(A). Moreover, if A is projective, then MGF(A) is a G-pure submodule of A and MGF(A) = M(R) · A.
The Unique Maximal GF-Regular Submodule of a Module
Abduldaim, Areej M.; Chen, Sheng
2013-01-01
An R-module A is called GF-regular if, for each a ∈ A and r ∈ R, there exist t ∈ R and a positive integer n such that r n tr n a = r n a. We proved that each unitary R-module A contains a unique maximal GF-regular submodule, which we denoted by M GF(A). Furthermore, the radical properties of A are investigated; we proved that if A is an R-module and K is a submodule of A, then M GF(K) = K∩M GF(A). Moreover, if A is projective, then M GF(A) is a G-pure submodule of A and M GF(A) = M(R) · A. PMID:24163628
Regularizing the r-mode Problem for Nonbarotropic Relativistic Stars
NASA Technical Reports Server (NTRS)
Lockitch, Keith H.; Andersson, Nils; Watts, Anna L.
2004-01-01
We present results for r-modes of relativistic nonbarotropic stars. We show that the main differential equation, which is formally singular at lowest order in the slow-rotation expansion, can be regularized if one considers the initial value problem rather than the normal mode problem. However, a more physically motivated way to regularize the problem is to include higher order terms. This allows us to develop a practical approach for solving the problem and we provide results that support earlier conclusions obtained for uniform density stars. In particular, we show that there will exist a single r-mode for each permissible combination of 1 and m. We discuss these results and provide some caveats regarding their usefulness for estimates of gravitational-radiation reaction timescales. The close connection between the seemingly singular relativistic r-mode problem and issues arising because of the presence of co-rotation points in differentially rotating stars is also clarified.
Statistical regularities in the rank-citation profile of scientists
NASA Astrophysics Data System (ADS)
Petersen, Alexander M.; Stanley, H. Eugene; Succi, Sauro
2011-12-01
Recent science of science research shows that scientific impact measures for journals and individual articles have quantifiable regularities across both time and discipline. However, little is known about the scientific impact distribution at the scale of an individual scientist. We analyze the aggregate production and impact using the rank-citation profile ci(r) of 200 distinguished professors and 100 assistant professors. For the entire range of paper rank r, we fit each ci(r) to a common distribution function. Since two scientists with equivalent Hirsch h-index can have significantly different ci(r) profiles, our results demonstrate the utility of the βi scaling parameter in conjunction with hi for quantifying individual publication impact. We show that the total number of citations Ci tallied from a scientist's Ni papers scales as . Such statistical regularities in the input-output patterns of scientists can be used as benchmarks for theoretical models of career progress.
Regular Expression-Based Learning for METs Value Extraction.
Redd, Douglas; Kuang, Jinqiu; Mohanty, April; Bray, Bruce E; Zeng-Treitler, Qing
2016-01-01
Functional status as measured by exercise capacity is an important clinical variable in the care of patients with cardiovascular diseases. Exercise capacity is commonly reported in terms of Metabolic Equivalents (METs). In the medical records, METs can often be found in a variety of clinical notes. To extract METs values, we adapted a machine-learning algorithm called REDEx to automatically generate regular expressions. Trained and tested on a set of 2701 manually annotated text snippets (i.e. short pieces of text), the regular expressions were able to achieve good accuracy and F-measure of 0.89 and 0.86. This extraction tool will allow us to process the notes of millions of cardiovascular patients and extract METs value for use by researchers and clinicians.
On the Regularization of the Two-Fluid Model
NASA Astrophysics Data System (ADS)
Dinh, Nam; Nourgaliev, Robert; Theofanous, Theo
2003-11-01
The two-fluid model belongs to the multifield modeling approach based on an interpenetrating continua description of multiphase flow. The model is ill-posed and mathematically complex, in the sense that the equation system is non-hyperbolic, non-linear and non-conservative. We revisit regularizing techniques and examine their potential to offer a convergent series of weak solutions even at the singularity (discontinuity) plane. Numerical examples illustrate the roles of hyperbolicity and conservatism for robust numerical treatment. We discuss a Virtual Spacetime Relaxation (VSR) method, which employs virtual time to achieve hyperbolicity of an initial-value elliptic Cauchy problem and iterative procedure (successive approximation of well-posed problems) for regularization. Mathematical properties and implications of the VSR method are studied, showing the main challenge being able to construct a physics-based convergence (stoppage) criterion.
Universal regularizers for robust sparse coding and modeling.
Ramírez, Ignacio; Sapiro, Guillermo
2012-09-01
Sparse data models, where data is assumed to be well represented as a linear combination of a few elements from a dictionary, have gained considerable attention in recent years, and their use has led to state-of-the-art results in many signal and image processing tasks. It is now well understood that the choice of the sparsity regularization term is critical in the success of such models. Based on a codelength minimization interpretation of sparse coding, and using tools from universal coding theory, we propose a framework for designing sparsity regularization terms which have theoretical and practical advantages when compared with the more standard l(0) or l(1) ones. The presentation of the framework and theoretical foundations is complemented with examples that show its practical advantages in image denoising, zooming and classification.
Generalized LASSO with under-determined regularization matrices.
Duan, Junbo; Soussen, Charles; Brie, David; Idier, Jérôme; Wan, Mingxi; Wang, Yu-Ping
2016-10-01
This paper studies the intrinsic connection between a generalized LASSO and a basic LASSO formulation. The former is the extended version of the latter by introducing a regularization matrix to the coefficients. We show that when the regularization matrix is even- or under-determined with full rank conditions, the generalized LASSO can be transformed into the LASSO form via the Lagrangian framework. In addition, we show that some published results of LASSO can be extended to the generalized LASSO, and some variants of LASSO, e.g., robust LASSO, can be rewritten into the generalized LASSO form and hence can be transformed into basic LASSO. Based on this connection, many existing results concerning LASSO, e.g., efficient LASSO solvers, can be used for generalized LASSO.
Total Variation Regularization of Matrix-Valued Images
Christiansen, Oddvar; Lee, Tin-Man; Lie, Johan; Sinha, Usha; Chan, Tony F.
2007-01-01
We generalize the total variation restoration model, introduced by Rudin, Osher, and Fatemi in 1992, to matrix-valued data, in particular, to diffusion tensor images (DTIs). Our model is a natural extension of the color total variation model proposed by Blomgren and Chan in 1998. We treat the diffusion matrix D implicitly as the product D = LL T, and work with the elements of L as variables, instead of working directly on the elements of D. This ensures positive definiteness of the tensor during the regularization flow, which is essential when regularizing DTI. We perform numerical experiments on both synthetical data and 3D human brain DTI, and measure the quantitative behavior of the proposed model. PMID:18256729
Generalized LASSO with under-determined regularization matrices
Duan, Junbo; Soussen, Charles; Brie, David; Idier, Jérôme; Wan, Mingxi; Wang, Yu-Ping
2016-01-01
This paper studies the intrinsic connection between a generalized LASSO and a basic LASSO formulation. The former is the extended version of the latter by introducing a regularization matrix to the coefficients. We show that when the regularization matrix is even- or under-determined with full rank conditions, the generalized LASSO can be transformed into the LASSO form via the Lagrangian framework. In addition, we show that some published results of LASSO can be extended to the generalized LASSO, and some variants of LASSO, e.g., robust LASSO, can be rewritten into the generalized LASSO form and hence can be transformed into basic LASSO. Based on this connection, many existing results concerning LASSO, e.g., efficient LASSO solvers, can be used for generalized LASSO. PMID:27346902
Compound L0 regularization method for image blind motion deblurring
NASA Astrophysics Data System (ADS)
Liu, Qiaohong; Sun, Liping; Shao, Zeguo
2016-09-01
Blind image deblurring is one of the challenging problems in image processing and computer vision. The main purpose of blind image deblurring is to estimate the correct blur kernel and restore the latent image with edge-preservation, details-protection, and ringing suppression. In order to achieve ideal results, an innovative compound L0-regularized model is proposed to estimate the blur kernel by regularizing the sparsity property of natural images and two characteristics of blur kernel, such as continuity and sparsity. In the alternating direction framework, the split Bregman algorithm and half-quadratic splitting rule are alternatively employed to optimize the proposed kernel estimation model. Finally, a nonblind restoration method with ringing suppression is developed to obtain the ultimate latent image. Extensive experiments demonstrate the efficiency and viability of the proposed method compared with some state-of-the-art blind deblurring methods.
Chaos at Uranus Spreads Dust Across the Regular Satellites
NASA Astrophysics Data System (ADS)
Tamayo, Dan; Burns, J. A.; Nicholson, P. D.; Hamilton, D. P.
2012-05-01
The short collision timescales between the Uranian irregular satellites argue for the past generation of vast quantities of dust at the outer reaches of Uranus’ Hill sphere (Bottke et al. 2010). Uranus’ extreme obliquity (98 degrees) renders the orbits of large objects unstable to eccentricity perturbations in the radial range a ≈ 60 - 75 Rp. (Tremaine et al. 2009). We study the effect on dust by investigating how the instability is modified by radiation pressure. We find that dust particles generated at the orbits of the irregular satellites move inward as radiation forces cause their orbits to decay (Burns et al. 1979). When they reach the unstable region, grain orbits undergo chaotic large-amplitude eccentricity oscillations that bring their pericenters inside the orbits of the regular satellites. We argue that the impact probabilities and expected spatial distribution across the satellite surfaces might explain the observed hemispherical color asymmetries common to the outer four regular satellites.
Regularization of hidden dynamics in piecewise smooth flows
NASA Astrophysics Data System (ADS)
Novaes, Douglas D.; Jeffrey, Mike R.
2015-11-01
This paper studies the equivalence between differentiable and non-differentiable dynamics in Rn. Filippov's theory of discontinuous differential equations allows us to find flow solutions of dynamical systems whose vector fields undergo switches at thresholds in phase space. The canonical convex combination at the discontinuity is only the linear part of a nonlinear combination that more fully explores Filippov's most general problem: the differential inclusion. Here we show how recent work relating discontinuous systems to singular limits of continuous (or regularized) systems extends to nonlinear combinations. We show that if sliding occurs in a discontinuous systems, there exists a differentiable slow-fast system with equivalent slow invariant dynamics. We also show the corresponding result for the pinching method, a converse to regularization which approximates a smooth system by a discontinuous one.
Random noise attenuation using an improved anisotropic total variation regularization
NASA Astrophysics Data System (ADS)
Gemechu, Diriba; Yuan, Huan; Ma, Jianwei
2017-09-01
In seismic data processing, attenuation of random noise from the observed data is the basic step which improves the signal-to-noise ratio (SNR) of seismic data. In this paper, we proposed an anisotropic total bounded variation regularization approach to attenuate noise. An improved constraint convex optimization model is formulated for this approach and then the split Bregman algorithm is used to solve the optimization model. Generalized cross validation (GCV) technique is used to estimate the regularization parameter. Synthetic and real seismic data are considered to show the out performance of the proposed method in terms of event-preserving denoising, in comparison with FX deconvolution, shearlet hard thresholding, and anisotropic total variation methods. The numerical results indicate that the proposed method effectively attenuates random noise by preserving the structure and important features of seismic data.
Experimental evidence for formation mechanism of regular circular fringes
NASA Astrophysics Data System (ADS)
Wang, Y.; Zhu, R.; Wang, G.; Wang, P.; Li, H.; Zhang, W.; Ren, G.
2016-10-01
Laser active suppressing jamming is one of the most effective technologies to cope with optoelectric imaging systems. In the process of carrying out laser disturbing experiment, regular circular fringes often appeared on the detector, besides laser spot converging by optical system. First of all, the formation of circular fringes has been experimentally investigated by using a simple converging lens to replace the complex optical system. Moreover, circular fringes have been simulated based on the interference theory of coherent light. The coherence between the experimental phenomena and the simulated results showed that the formation mechanism of regular circular fringes was the interference effect between reflected light by back surface of lens and directly refractive light on the detector. At last, the visibility of circular fringes has been calculated from 0.05 to 0.22 according to the current plating standard of lens surface and manufacture technique of optoelectric detector.
Gevrey regularity for the supercritical quasi-geostrophic equation
NASA Astrophysics Data System (ADS)
Biswas, Animikh
2014-09-01
In this paper, following the techniques of Foias and Temam, we establish suitable Gevrey class regularity of solutions to the supercritical quasi-geostrophic equations in the whole space, with initial data in “critical” Sobolev spaces. Moreover, the Gevrey class that we obtain is “near optimal” and as a corollary, we obtain temporal decay rates of higher order Sobolev norms of the solutions. Unlike the Navier-Stokes or the subcritical quasi-geostrophic equations, the low dissipation poses a difficulty in establishing Gevrey regularity. A new commutator estimate in Gevrey classes, involving the dyadic Littlewood-Paley operators, is established that allow us to exploit the cancellation properties of the equation and circumvent this difficulty.
Resolving intravoxel fiber architecture using nonconvex regularized blind compressed sensing
NASA Astrophysics Data System (ADS)
Chu, C. Y.; Huang, J. P.; Sun, C. Y.; Liu, W. Y.; Zhu, Y. M.
2015-03-01
In diffusion magnetic resonance imaging, accurate and reliable estimation of intravoxel fiber architectures is a major prerequisite for tractography algorithms or any other derived statistical analysis. Several methods have been proposed that estimate intravoxel fiber architectures using low angular resolution acquisitions owing to their shorter acquisition time and relatively low b-values. But these methods are highly sensitive to noise. In this work, we propose a nonconvex regularized blind compressed sensing approach to estimate intravoxel fiber architectures in low angular resolution acquisitions. The method models diffusion-weighted (DW) signals as a sparse linear combination of unfixed reconstruction basis functions and introduces a nonconvex regularizer to enhance the noise immunity. We present a general solving framework to simultaneously estimate the sparse coefficients and the reconstruction basis. Experiments on synthetic, phantom, and real human brain DW images demonstrate the superiority of the proposed approach.
Regular Expression-Based Learning for METs Value Extraction
Redd, Douglas; Kuang, Jinqiu; Mohanty, April; Bray, Bruce E.; Zeng-Treitler, Qing
2016-01-01
Functional status as measured by exercise capacity is an important clinical variable in the care of patients with cardiovascular diseases. Exercise capacity is commonly reported in terms of Metabolic Equivalents (METs). In the medical records, METs can often be found in a variety of clinical notes. To extract METs values, we adapted a machine-learning algorithm called REDEx to automatically generate regular expressions. Trained and tested on a set of 2701 manually annotated text snippets (i.e. short pieces of text), the regular expressions were able to achieve good accuracy and F-measure of 0.89 and 0.86. This extraction tool will allow us to process the notes of millions of cardiovascular patients and extract METs value for use by researchers and clinicians. PMID:27570673
L1-Regularized Boltzmann Machine Learning Using Majorizer Minimization
NASA Astrophysics Data System (ADS)
Ohzeki, Masayuki
2015-05-01
We propose an inference method to estimate sparse interactions and biases according to Boltzmann machine learning. The basis of this method is L1 regularization, which is often used in compressed sensing, a technique for reconstructing sparse input signals from undersampled outputs. L1 regularization impedes the simple application of the gradient method, which optimizes the cost function that leads to accurate estimations, owing to the cost function's lack of smoothness. In this study, we utilize the majorizer minimization method, which is a well-known technique implemented in optimization problems, to avoid the non-smoothness of the cost function. By using the majorizer minimization method, we elucidate essentially relevant biases and interactions from given data with seemingly strongly-correlated components.
[Iterated Tikhonov Regularization for Spectral Recovery from Tristimulus].
Xie, De-hong; Li, Rui; Wan, Xiao-xia; Liu, Qiang; Zhu, Wen-feng
2016-01-01
Reflective spectra in a multispectral image can objectively and originally represent color information due to their high dimensionality, illuminant independent and device independent. Aiming to the problem of loss of spectral information when the spectral data reconstructed from three-dimensional colorimetric data in the trichromatic camera-based spectral image acquisition system and its subsequent problem of loss of color information, this work proposes an iterated Tikhonov regularization to reconstruct the reflectance spectra. First of all, according to relationship between the colorimetric value and the reflective spectra in the colorimetric theory, this work constructs a spectral reconstruction equation which can reconstruct high dimensional spectral data from three dimensional colorimetric data acquired by the trichromatic camera. Then, the iterated Tikhonov regularization, inspired by the idea of the pseudo inverse Moore-Penrose, is used to cope with the linear ill-posed inverse problem during solving the equation of reconstructing reflectance spectra. Meanwhile, the work also uses the L-curve method to obtain an optimal regularized parameter of the iterated Tikhonov regularization by training a set of samples. Through these methods, the ill condition of the spectral reconstruction equation can be effectively controlled and improved, and subsequently loss of spectral information of the reconstructed spectral data can be reduced. The verification experiment is performed under another set of training samples. The experimental results show that the proposed method reconstructs the reflective spectra with less spectral information loss in the trichromatic camera-based spectral image acquisition system, which reflects in obvious decreases of spectral errors and colorimetric errors compared with the previous method.
Spatially adaptive regularized iterative high-resolution image reconstruction algorithm
NASA Astrophysics Data System (ADS)
Lim, Won Bae; Park, Min K.; Kang, Moon Gi
2000-12-01
High resolution images are often required in applications such as remote sensing, frame freeze in video, military and medical imaging. Digital image sensor arrays, which are used for image acquisition in many imaging systems, are not dense enough to prevent aliasing, so the acquired images will be degraded by aliasing effects. To prevent aliasing without loss of resolution, a dense detector array is required. But it may be very costly or unavailable, thus, many imaging systems are designed to allow some level of aliasing during image acquisition. The purpose of our work is to reconstruct an unaliased high resolution image from the acquired aliased image sequence. In this paper, we propose a spatially adaptive regularized iterative high resolution image reconstruction algorithm for blurred, noisy and down-sampled image sequences. The proposed approach is based on a Constrained Least Squares (CLS) high resolution reconstruction algorithm, with spatially adaptive regularization operators and parameters. These regularization terms are shown to improve the reconstructed image quality by forcing smoothness, while preserving edges in the reconstructed high resolution image. Accurate sub-pixel motion registration is the key of the success of the high resolution image reconstruction algorithm. However, sub-pixel motion registration may have some level of registration error. Therefore, a reconstruction algorithm which is robust against the registration error is required. The registration algorithm uses a gradient based sub-pixel motion estimator which provides shift information for each of the recorded frames. The proposed algorithm is based on a technique of high resolution image reconstruction, and it solves spatially adaptive regularized constrained least square minimization functionals. In this paper, we show that the reconstruction algorithm gives dramatic improvements in the resolution of the reconstructed image and is effective in handling the aliased information. The
On c_2 invariants of some 4-regular Feynman graphs
NASA Astrophysics Data System (ADS)
Doryn, Dmitry
2017-03-01
The obstruction for application of techniques like denominator reduction for the computation of the c_2 invariant of Feynman graphs in general is the absence of a 3-valent vertex. In this paper such a formula for a 4-valent vertex is derived. The formula allows us to compute the c_2 invariant of new graphs, for instance, some 4-regular graphs with small loop number.
Avoidance of cigarette pack health warnings among regular cigarette smokers.
Maynard, Olivia M; Attwood, Angela; O'Brien, Laura; Brooks, Sabrina; Hedge, Craig; Leonards, Ute; Munafò, Marcus R
2014-03-01
Previous research with adults and adolescents indicates that plain cigarette packs increase visual attention to health warnings among non-smokers and non-regular smokers, but not among regular smokers. This may be because regular smokers: (1) are familiar with the health warnings, (2) preferentially attend to branding, or (3) actively avoid health warnings. We sought to distinguish between these explanations using eye-tracking technology. A convenience sample of 30 adult dependent smokers participated in an eye-tracking study. Participants viewed branded, plain and blank packs of cigarettes with familiar and unfamiliar health warnings. The number of fixations to health warnings and branding on the different pack types were recorded. Analysis of variance indicated that regular smokers were biased towards fixating the branding rather than the health warning on all three pack types. This bias was smaller, but still evident, for blank packs, where smokers preferentially attended the blank region over the health warnings. Time-course analysis showed that for branded and plain packs, attention was preferentially directed to the branding location for the entire 10s of the stimulus presentation, while for blank packs this occurred for the last 8s of the stimulus presentation. Familiarity with health warnings had no effect on eye gaze location. Smokers actively avoid cigarette pack health warnings, and this remains the case even in the absence of salient branding information. Smokers may have learned to divert their attention away from cigarette pack health warnings. These findings have implications for cigarette packaging and health warning policy. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Avoidance of Cigarette Pack Health Warnings among Regular Cigarette Smokers
Maynard, Olivia M.; Attwood, Angela; O’Brien, Laura; Brooks, Sabrina; Hedge, Craig; Leonards, Ute; Munafò, Marcus R.
2016-01-01
Background Previous research with adults and adolescents indicates that plain cigarette packs increase visual attention to health warnings among non-smokers and non-regular smokers, but not among regular smokers. This may be because regular smokers: 1) are familiar with the health warnings, 2) preferentially attend to branding, or 3) actively avoid health warnings. We sought to distinguish between these explanations using eye-tracking technology. Method A convenience sample of 30 adult dependant smokers were recruited to participate in an eye-tracking study. Participants viewed branded, plain and blank packs of cigarettes with familiar and unfamiliar health warnings. The number of fixations to health warnings and branding on the different pack types were recorded. Results Analysis of variance indicated that regular smokers were biased towards fixating the branding location rather than the health warning location on all three pack types (p < 0.002). This bias was smaller, but still evident, for blank packs, where smokers preferentially attended the blank region over the health warnings. Time-course analysis showed that for branded and plain packs, attention was preferentially directed to the branding location for the entire 10 seconds of the stimulus presentation, while for blank packs this occurred for the last 8 seconds of the stimulus presentation. Familiarity with health warnings had no effect on eye gaze location. Conclusion Smokers actively avoid cigarette pack health warnings, and this remains the case even in the absence of salient branding information. Smokers may have learned to divert their attention away from cigarette pack health warnings. These findings have policy implications for the design of health warning on cigarette packs. PMID:24485554
[Structural regularities in activated cleavage sites of thrombin receptors].
Mikhaĭlik, I V; Verevka, S V
1999-01-01
Comparison of thrombin receptors activation splitting sites sequences testifies to their similarity both in activation splitting sites of protein precursors and protein proteinase inhibitors reactive sites. In all these sites corresponded to effectory sites P2'-positions are placed by hydrophobic amino-acids only. The regularity defined conforms with previous thesis about the role of effectory S2'-site in regulation of the processes mediated by serine proteinases.
Exploiting Lexical Regularities in Designing Natural Language Systems.
1988-04-01
ELEMENT. PROJECT. TASKN Artificial Inteligence Laboratory A1A4WR NTumet 0) 545 Technology Square Cambridge, MA 02139 Ln *t- CONTROLLING OFFICE NAME AND...RO-RI95 922 EXPLOITING LEXICAL REGULARITIES IN DESIGNING NATURAL 1/1 LANGUAGE SYSTENS(U) MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE...oes.ary and ftdou.Ip hr Nl wow" L,2This paper presents the lexical component of the START Question Answering system developed at the MIT Artificial
Manifestly scale-invariant regularization and quantum effective operators
NASA Astrophysics Data System (ADS)
Ghilencea, D. M.
2016-05-01
Scale-invariant theories are often used to address the hierarchy problem. However the regularization of their quantum corrections introduces a dimensionful coupling (dimensional regularization) or scale (Pauli-Villars, etc) which breaks this symmetry explicitly. We show how to avoid this problem and study the implications of a manifestly scale-invariant regularization in (classical) scale-invariant theories. We use a dilaton-dependent subtraction function μ (σ ) which, after spontaneous breaking of the scale symmetry, generates the usual dimensional regularization subtraction scale μ (⟨σ ⟩) . One consequence is that "evanescent" interactions generated by scale invariance of the action in d =4 -2 ɛ (but vanishing in d =4 ) give rise to new, finite quantum corrections. We find a (finite) correction Δ U (ϕ ,σ ) to the one-loop scalar potential for ϕ and σ , beyond the Coleman-Weinberg term. Δ U is due to an evanescent correction (∝ɛ ) to the field-dependent masses (of the states in the loop) which multiplies the pole (∝1 /ɛ ) of the momentum integral to give a finite quantum result. Δ U contains a nonpolynomial operator ˜ϕ6/σ2 of known coefficient and is independent of the subtraction dimensionless parameter. A more general μ (ϕ ,σ ) is ruled out since, in their classical decoupling limit, the visible sector (of the Higgs ϕ ) and hidden sector (dilaton σ ) still interact at the quantum level; thus, the subtraction function must depend on the dilaton only, μ ˜σ . The method is useful in models where preserving scale symmetry at quantum level is important.
Knowing More than One Can Say: The Early Regular Plural
ERIC Educational Resources Information Center
Zapf, Jennifer A.; Smith, Linda B.
2009-01-01
This paper reports on partial knowledge in two-year-old children's learning of the regular English plural. In Experiments 1 and 2, children were presented with one kind and its label and then were either presented with two of that same kind (A[right arrow]AA) or the initial picture next to a very different thing (A[right arrow]AB). The children in…
Effects of registration regularization and atlas sharpness on segmentation accuracy.
Yeo, B T Thomas; Sabuncu, Mert R; Desikan, Rahul; Fischl, Bruce; Golland, Polina
2008-10-01
In non-rigid registration, the tradeoff between warp regularization and image fidelity is typically determined empirically. In atlas-based segmentation, this leads to a probabilistic atlas of arbitrary sharpness: weak regularization results in well-aligned training images and a sharp atlas; strong regularization yields a "blurry" atlas. In this paper, we employ a generative model for the joint registration and segmentation of images. The atlas construction process arises naturally as estimation of the model parameters. This framework allows the computation of unbiased atlases from manually labeled data at various degrees of "sharpness", as well as the joint registration and segmentation of a novel brain in a consistent manner. We study the effects of the tradeoff of atlas sharpness and warp smoothness in the context of cortical surface parcellation. This is an important question because of the increasingly availability of atlases in public databases, and the development of registration algorithms separate from the atlas construction process. We find that the optimal segmentation (parcellation) corresponds to a unique balance of atlas sharpness and warp regularization, yielding statistically significant improvements over the FreeSurfer parcellation algorithm. Furthermore, we conclude that one can simply use a single atlas computed at an optimal sharpness for the registration-segmentation of a new subject with a pre-determined, fixed, optimal warp constraint. The optimal atlas sharpness and warp smoothness can be determined by probing the segmentation performance on available training data. Our experiments also suggest that segmentation accuracy is tolerant up to a small mismatch between atlas sharpness and warp smoothness.