Collecting marine litter during regular fish surveys

NARCIS (Netherlands)

Sluis, van der M.T.; Hal, van R.

2014-01-01

This report presents the results of the marine litter monitoring on the IBTS survey of 2014 and the BTS survey of 2013. Since 2013 marine litter is collected during the International Bottom Trawl Survey (IBTS) and Dutch Beam Trawl Survey (BTS) following a protocol developed by ICES. The composition

Selection of regularization parameter for l1-regularized damage detection

Science.gov (United States)

Hou, Rongrong; Xia, Yong; Bao, Yuequan; Zhou, Xiaoqing

2018-06-01

The l1 regularization technique has been developed for structural health monitoring and damage detection through employing the sparsity condition of structural damage. The regularization parameter, which controls the trade-off between data fidelity and solution size of the regularization problem, exerts a crucial effect on the solution. However, the l1 regularization problem has no closed-form solution, and the regularization parameter is usually selected by experience. This study proposes two strategies of selecting the regularization parameter for the l1-regularized damage detection problem. The first method utilizes the residual and solution norms of the optimization problem and ensures that they are both small. The other method is based on the discrepancy principle, which requires that the variance of the discrepancy between the calculated and measured responses is close to the variance of the measurement noise. The two methods are applied to a cantilever beam and a three-story frame. A range of the regularization parameter, rather than one single value, can be determined. When the regularization parameter in this range is selected, the damage can be accurately identified even for multiple damage scenarios. This range also indicates the sensitivity degree of the damage identification problem to the regularization parameter.

Manufacture of Regularly Shaped Sol-Gel Pellets

Science.gov (United States)

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.

Solution path for manifold regularized semisupervised classification.

Science.gov (United States)

Wang, Gang; Wang, Fei; Chen, Tao; Yeung, Dit-Yan; Lochovsky, Frederick H

2012-04-01

Traditional learning algorithms use only labeled data for training. However, labeled examples are often difficult or time consuming to obtain since they require substantial human labeling efforts. On the other hand, unlabeled data are often relatively easy to collect. Semisupervised learning addresses this problem by using large quantities of unlabeled data with labeled data to build better learning algorithms. In this paper, we use the manifold regularization approach to formulate the semisupervised learning problem where a regularization framework which balances a tradeoff between loss and penalty is established. We investigate different implementations of the loss function and identify the methods which have the least computational expense. The regularization hyperparameter, which determines the balance between loss and penalty, is crucial to model selection. Accordingly, we derive an algorithm that can fit the entire path of solutions for every value of the hyperparameter. Its computational complexity after preprocessing is quadratic only in the number of labeled examples rather than the total number of labeled and unlabeled examples.

Regular Breakfast and Blood Lead Levels among Preschool Children

Directory of Open Access Journals (Sweden)

Needleman Herbert

2011-04-01

Full Text Available Abstract Background Previous studies have shown that fasting increases lead absorption in the gastrointestinal tract of adults. Regular meals/snacks are recommended as a nutritional intervention for lead poisoning in children, but epidemiological evidence of links between fasting and blood lead levels (B-Pb is rare. The purpose of this study was to examine the association between eating a regular breakfast and B-Pb among children using data from the China Jintan Child Cohort Study. Methods Parents completed a questionnaire regarding children's breakfast-eating habit (regular or not, demographics, and food frequency. Whole blood samples were collected from 1,344 children for the measurements of B-Pb and micronutrients (iron, copper, zinc, calcium, and magnesium. B-Pb and other measures were compared between children with and without regular breakfast. Linear regression modeling was used to evaluate the association between regular breakfast and log-transformed B-Pb. The association between regular breakfast and risk of lead poisoning (B-Pb≥10 μg/dL was examined using logistic regression modeling. Results Median B-Pb among children who ate breakfast regularly and those who did not eat breakfast regularly were 6.1 μg/dL and 7.2 μg/dL, respectively. Eating breakfast was also associated with greater zinc blood levels. Adjusting for other relevant factors, the linear regression model revealed that eating breakfast regularly was significantly associated with lower B-Pb (beta = -0.10 units of log-transformed B-Pb compared with children who did not eat breakfast regularly, p = 0.02. Conclusion The present study provides some initial human data supporting the notion that eating a regular breakfast might reduce B-Pb in young children. To our knowledge, this is the first human study exploring the association between breakfast frequency and B-Pb in young children.

Wavelet domain image restoration with adaptive edge-preserving regularization.

Science.gov (United States)

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.

SparseBeads data: benchmarking sparsity-regularized computed tomography

DEFF Research Database (Denmark)

Jørgensen, Jakob Sauer; Coban, Sophia B.; Lionheart, William R. B.

2017-01-01

-regularized reconstruction. A collection of 48 x-ray CT datasets called SparseBeads was designed for benchmarking SR reconstruction algorithms. Beadpacks comprising glass beads of five different sizes as well as mixtures were scanned in a micro-CT scanner to provide structured datasets with variable image sparsity levels...

Regular and chaotic dynamics in time-dependent relativistic mean-field theory

International Nuclear Information System (INIS)

Vretenar, D.; Ring, P.; Lalazissis, G.A.; Poeschl, W.

1997-01-01

Isoscalar and isovector monopole oscillations that correspond to giant resonances in spherical nuclei are described in the framework of time-dependent relativistic mean-field theory. Time-dependent and self-consistent calculations that reproduce experimental data on monopole resonances in 208 Pb show that the motion of the collective coordinate is regular for isoscalar oscillations, and that it becomes chaotic when initial conditions correspond to the isovector mode. Regular collective dynamics coexists with chaotic oscillations on the microscopic level. Time histories, Fourier spectra, state-space plots, Poincare sections, autocorrelation functions, and Lyapunov exponents are used to characterize the nonlinear system and to identify chaotic oscillations. Analogous considerations apply to higher multipolarities. copyright 1997 The American Physical Society

Distance-regular graphs

NARCIS (Netherlands)

van Dam, Edwin R.; Koolen, Jack H.; Tanaka, Hajime

2016-01-01

This is a survey of distance-regular graphs. We present an introduction to distance-regular graphs for the reader who is unfamiliar with the subject, and then give an overview of some developments in the area of distance-regular graphs since the monograph 'BCN'[Brouwer, A.E., Cohen, A.M., Neumaier,

Regular expressions cookbook

CERN Document Server

Goyvaerts, Jan

2009-01-01

This cookbook provides more than 100 recipes to help you crunch data and manipulate text with regular expressions. Every programmer can find uses for regular expressions, but their power doesn't come worry-free. Even seasoned users often suffer from poor performance, false positives, false negatives, or perplexing bugs. Regular Expressions Cookbook offers step-by-step instructions for some of the most common tasks involving this tool, with recipes for C#, Java, JavaScript, Perl, PHP, Python, Ruby, and VB.NET. With this book, you will: Understand the basics of regular expressions through a

Collective stochastic coherence in recurrent neuronal networks

Science.gov (United States)

Sancristóbal, Belén; Rebollo, Beatriz; Boada, Pol; Sanchez-Vives, Maria V.; Garcia-Ojalvo, Jordi

2016-09-01

Recurrent networks of dynamic elements frequently exhibit emergent collective oscillations, which can show substantial regularity even when the individual elements are considerably noisy. How noise-induced dynamics at the local level coexists with regular oscillations at the global level is still unclear. Here we show that a combination of stochastic recurrence-based initiation with deterministic refractoriness in an excitable network can reconcile these two features, leading to maximum collective coherence for an intermediate noise level. We report this behaviour in the slow oscillation regime exhibited by a cerebral cortex network under dynamical conditions resembling slow-wave sleep and anaesthesia. Computational analysis of a biologically realistic network model reveals that an intermediate level of background noise leads to quasi-regular dynamics. We verify this prediction experimentally in cortical slices subject to varying amounts of extracellular potassium, which modulates neuronal excitability and thus synaptic noise. The model also predicts that this effectively regular state should exhibit noise-induced memory of the spatial propagation profile of the collective oscillations, which is also verified experimentally. Taken together, these results allow us to construe the high regularity observed experimentally in the brain as an instance of collective stochastic coherence.

LL-regular grammars

NARCIS (Netherlands)

Nijholt, Antinus

1980-01-01

Culik II and Cogen introduced the class of LR-regular grammars, an extension of the LR(k) grammars. In this paper we consider an analogous extension of the LL(k) grammars called the LL-regular grammars. The relation of this class of grammars to other classes of grammars will be shown. Any LL-regular

An iterative method for Tikhonov regularization with a general linear regularization operator

NARCIS (Netherlands)

Hochstenbach, M.E.; Reichel, L.

2010-01-01

Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems with error-contaminated data. A regularization operator and a suitable value of a regularization parameter have to be chosen. This paper describes an iterative method, based on Golub-Kahan

Regular Expression Pocket Reference

CERN Document Server

Stubblebine, Tony

2007-01-01

This handy little book offers programmers a complete overview of the syntax and semantics of regular expressions that are at the heart of every text-processing application. Ideal as a quick reference, Regular Expression Pocket Reference covers the regular expression APIs for Perl 5.8, Ruby (including some upcoming 1.9 features), Java, PHP, .NET and C#, Python, vi, JavaScript, and the PCRE regular expression libraries. This concise and easy-to-use reference puts a very powerful tool for manipulating text and data right at your fingertips. Composed of a mixture of symbols and text, regular exp

78 FR 44622 - Agency Information Collection; Activity Under OMB Review; Confidential Close Call Reporting System

Science.gov (United States)

2013-07-24

... complete the C\\3\\RS report form and 30-40 minutes to participate in a brief interview.) Data... explicit consent of the respondent. Accordingly, only statistical and non-sensitive information will be... provide information about the reported event by filling out a C\\3\\RS report form (questionnaire) and...

Oblate collectivity in 197,198Pb

International Nuclear Information System (INIS)

Kuhnert, A.; Wang, T.F.; Stoyer, M.A.; Becker, J.A.; Henry, E.A.; Brinkman, M.J.; Yates, S.W.; Draper, J.E.; Deleplanque, M.A.; Diamond, R.M.; Stephens, F.S.; Machiavelli, A.O.; Kelly, W.H.; Korten, W.; Azaiez, F.; Cizewski, J.A.

1993-01-01

Evidence for collective behavior in the high-spin region of neutron deficient lead nuclei is provided by the observation of four collective structures in 197,198 Pb. These bands consist of strong dipole (M1) transitions with a few E2 crossover transitions observed. The transition energies of three of these bands show a rather regular behavior while those of one of them show an irregular behavior. We interpret the regular bands as oblate collective bands built on oblate proton and neutron states, whereas the irregular band might either be built on a state with very small oblate deformation, or be a triaxial rotational band. A lifetime measurement (DSAM) has been done for the regular bands in 198 Pb. Neutron and proton configurations for the bands are suggested from the results of quasi particle Routhians and total Routhian surface (TRS) calculations. (orig.)

Oblate collectivity in 197,198Pb

International Nuclear Information System (INIS)

Kuhnert, A.; Wang, T.F.; Stoyer, M.A.; Becker, J.A.; Henry, E.A.; Brinkman, M.J.; Yates, S.W.; Draper, J.E.; Deleplanque, M.A.; Diamond, R.M.; Stephens, F.S.; Machiavelli, A.O.; Kelly, W.H.; Korten, W.; Azaiez, F.

1992-07-01

Evidence for collective behavior in the high-spin region of neutron deficient lead nuclei is provided by the observation of four collective structures in 197,198 Pb. These bands consist of strong dipole (M1) transitions with a few E2 crossover transitions observed. The transition energies of three of these bands show a rather regular behavior while those of one of them show an irregular behavior. We interpret the regular bands as oblate collective bands built on oblate proton and neutron states, whereas the irregular band might either be built on a state with very small oblate deformation, or be a triaxial rotational band. A lifetime measurement (DSAM) has been done for the regular bands in 198 Pb. Neutron and proton configurations for the bands are suggested from the results of quasi particle Routhians and total Routhian surface (TRS) calculations

The geometry of continuum regularization

International Nuclear Information System (INIS)

Halpern, M.B.

1987-03-01

This lecture is primarily an introduction to coordinate-invariant regularization, a recent advance in the continuum regularization program. In this context, the program is seen as fundamentally geometric, with all regularization contained in regularized DeWitt superstructures on field deformations

Regularized forecasting of chaotic dynamical systems

International Nuclear Information System (INIS)

Bollt, Erik M.

2017-01-01

While local models of dynamical systems have been highly successful in terms of using extensive data sets observing even a chaotic dynamical system to produce useful forecasts, there is a typical problem as follows. Specifically, with k-near neighbors, kNN method, local observations occur due to recurrences in a chaotic system, and this allows for local models to be built by regression to low dimensional polynomial approximations of the underlying system estimating a Taylor series. This has been a popular approach, particularly in context of scalar data observations which have been represented by time-delay embedding methods. However such local models can generally allow for spatial discontinuities of forecasts when considered globally, meaning jumps in predictions because the collected near neighbors vary from point to point. The source of these discontinuities is generally that the set of near neighbors varies discontinuously with respect to the position of the sample point, and so therefore does the model built from the near neighbors. It is possible to utilize local information inferred from near neighbors as usual but at the same time to impose a degree of regularity on a global scale. We present here a new global perspective extending the general local modeling concept. In so doing, then we proceed to show how this perspective allows us to impose prior presumed regularity into the model, by involving the Tikhonov regularity theory, since this classic perspective of optimization in ill-posed problems naturally balances fitting an objective with some prior assumed form of the result, such as continuity or derivative regularity for example. This all reduces to matrix manipulations which we demonstrate on a simple data set, with the implication that it may find much broader context.

Regular expression containment

DEFF Research Database (Denmark)

Henglein, Fritz; Nielsen, Lasse

2011-01-01

We present a new sound and complete axiomatization of regular expression containment. It consists of the conventional axiomatiza- tion of concatenation, alternation, empty set and (the singleton set containing) the empty string as an idempotent semiring, the fixed- point rule E* = 1 + E × E......* for Kleene-star, and a general coin- duction rule as the only additional rule. Our axiomatization gives rise to a natural computational inter- pretation of regular expressions as simple types that represent parse trees, and of containment proofs as coercions. This gives the axiom- atization a Curry......-Howard-style constructive interpretation: Con- tainment proofs do not only certify a language-theoretic contain- ment, but, under our computational interpretation, constructively transform a membership proof of a string in one regular expres- sion into a membership proof of the same string in another regular expression. We...

Supersymmetric dimensional regularization

International Nuclear Information System (INIS)

Siegel, W.; Townsend, P.K.; van Nieuwenhuizen, P.

1980-01-01

There is a simple modification of dimension regularization which preserves supersymmetry: dimensional reduction to real D < 4, followed by analytic continuation to complex D. In terms of component fields, this means fixing the ranges of all indices on the fields (and therefore the numbers of Fermi and Bose components). For superfields, it means continuing in the dimensionality of x-space while fixing the dimensionality of theta-space. This regularization procedure allows the simple manipulation of spinor derivatives in supergraph calculations. The resulting rules are: (1) First do all algebra exactly as in D = 4; (2) Then do the momentum integrals as in ordinary dimensional regularization. This regularization procedure needs extra rules before one can say that it is consistent. Such extra rules needed for superconformal anomalies are discussed. Problems associated with renormalizability and higher order loops are also discussed

Regularization by External Variables

DEFF Research Database (Denmark)

Bossolini, Elena; Edwards, R.; Glendinning, P. A.

2016-01-01

Regularization was a big topic at the 2016 CRM Intensive Research Program on Advances in Nonsmooth Dynamics. There are many open questions concerning well known kinds of regularization (e.g., by smoothing or hysteresis). Here, we propose a framework for an alternative and important kind of regula......Regularization was a big topic at the 2016 CRM Intensive Research Program on Advances in Nonsmooth Dynamics. There are many open questions concerning well known kinds of regularization (e.g., by smoothing or hysteresis). Here, we propose a framework for an alternative and important kind...

Regular Single Valued Neutrosophic Hypergraphs

Directory of Open Access Journals (Sweden)

Muhammad Aslam Malik

2016-12-01

Full Text Available In this paper, we define the regular and totally regular single valued neutrosophic hypergraphs, and discuss the order and size along with properties of regular and totally regular single valued neutrosophic hypergraphs. We also extend work on completeness of single valued neutrosophic hypergraphs.

On a correspondence between regular and non-regular operator monotone functions

DEFF Research Database (Denmark)

Gibilisco, P.; Hansen, Frank; Isola, T.

2009-01-01

We prove the existence of a bijection between the regular and the non-regular operator monotone functions satisfying a certain functional equation. As an application we give a new proof of the operator monotonicity of certain functions related to the Wigner-Yanase-Dyson skew information....

Stochastic analytic regularization

International Nuclear Information System (INIS)

Alfaro, J.

1984-07-01

Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)

Effective field theory dimensional regularization

International Nuclear Information System (INIS)

Lehmann, Dirk; Prezeau, Gary

2002-01-01

A Lorentz-covariant regularization scheme for effective field theories with an arbitrary number of propagating heavy and light particles is given. This regularization scheme leaves the low-energy analytic structure of Greens functions intact and preserves all the symmetries of the underlying Lagrangian. The power divergences of regularized loop integrals are controlled by the low-energy kinematic variables. Simple diagrammatic rules are derived for the regularization of arbitrary one-loop graphs and the generalization to higher loops is discussed

Effective field theory dimensional regularization

Science.gov (United States)

Lehmann, Dirk; Prézeau, Gary

2002-01-01

A Lorentz-covariant regularization scheme for effective field theories with an arbitrary number of propagating heavy and light particles is given. This regularization scheme leaves the low-energy analytic structure of Greens functions intact and preserves all the symmetries of the underlying Lagrangian. The power divergences of regularized loop integrals are controlled by the low-energy kinematic variables. Simple diagrammatic rules are derived for the regularization of arbitrary one-loop graphs and the generalization to higher loops is discussed.

Disposable containers as larval habitats for Aedes aegypti in a city with regular refuse collection: a study in Marília, São Paulo State, Brazil.

Science.gov (United States)

Mazine, C A; Macoris, M L; Andrighetti, M T; Yasumaro, S; Silva, M E; Nelson, M J; Winch, P J

1996-09-01

In Marília, Brazil, refuse is collected at least every other day, yet non-useful, non-returnable containers such as cans, plastic bottles and tires account for almost half of the container habitats found positive for the Aedes aegypti mosquito. A study was therefore conducted to investigate why these containers exist despite regular refuse collection and a high level of awareness of dengue prevention, and how the control program could most effectively respond. Differing community perceptions as to what constitutes refuse were found to lead people to store a variety of containers in their yard. Other dimensions of the problem include the presence of informal refuse collectors in search of saleable materials, and dumping of refuse in vacant lots and along roads. An intervention based on these data will involve the informal refuse collectors in implementation of a community-based recycling project.

Hierarchical regular small-world networks

International Nuclear Information System (INIS)

Boettcher, Stefan; Goncalves, Bruno; Guclu, Hasan

2008-01-01

Two new networks are introduced that resemble small-world properties. These networks are recursively constructed but retain a fixed, regular degree. They possess a unique one-dimensional lattice backbone overlaid by a hierarchical sequence of long-distance links, mixing real-space and small-world features. Both networks, one 3-regular and the other 4-regular, lead to distinct behaviors, as revealed by renormalization group studies. The 3-regular network is planar, has a diameter growing as √N with system size N, and leads to super-diffusion with an exact, anomalous exponent d w = 1.306..., but possesses only a trivial fixed point T c = 0 for the Ising ferromagnet. In turn, the 4-regular network is non-planar, has a diameter growing as ∼2 √(log 2 N 2 ) , exhibits 'ballistic' diffusion (d w = 1), and a non-trivial ferromagnetic transition, T c > 0. It suggests that the 3-regular network is still quite 'geometric', while the 4-regular network qualifies as a true small world with mean-field properties. As an engineering application we discuss synchronization of processors on these networks. (fast track communication)

Improving blood transfusion practice by regular education in the United Arab Emirates.

Science.gov (United States)

Sajwani, F H

2012-07-01

A cross-match to transfused unit ratio of less than 2.0 is frequently used to assess performance in many hospital blood banks. This brief report was initiated to evaluate the practice at a local hospital and to emphasize the importance of regular educational sessions to improve blood transfusion practice. Retrospective data on cross-match : transfused (C : T) ratio of all departments was collected and educational sessions were given to improve practice. Thereafter, a new set of data was collected and change in practice was assessed. Initial data showed total (C : T) ratio of 1.95. After medical staff education, analysis showed clinically significant improvement in blood utilization practice with a (C : T) ratio of 1.60. This brief report indicates the importance of regular physician education, the potential role of blood transfusion committee, and the need to implement clear guidelines for blood transfusion. © 2012 American Association of Blood Banks.

75 FR 76006 - Regular Meeting

Science.gov (United States)

2010-12-07

... FARM CREDIT SYSTEM INSURANCE CORPORATION Regular Meeting AGENCY: Farm Credit System Insurance Corporation Board. ACTION: Regular meeting. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). Date and Time: The meeting of the Board will be held...

General inverse problems for regular variation

DEFF Research Database (Denmark)

Damek, Ewa; Mikosch, Thomas Valentin; Rosinski, Jan

2014-01-01

Regular variation of distributional tails is known to be preserved by various linear transformations of some random structures. An inverse problem for regular variation aims at understanding whether the regular variation of a transformed random object is caused by regular variation of components ...

Teachers' Views about the Education of Gifted Students in Regular Classrooms

Directory of Open Access Journals (Sweden)

Neşe Kutlu Abu

2017-12-01

Full Text Available The purpose of this study was to investigate classroom teachers’ views about the education of gifted students in regular classrooms. The sample of the study is composed of ten primary school teachers working in the city of Amasya and had gifted students in their classes. In the present study, phenomenological research design was used. Data was collected through semi-structured interviews and analyzed descriptively in the QSR N-Vivo package program. The findings showed that teachers did not believe a need for differentiating curriculum for gifted students; rather they expressed that regular curriculum was enough for gifted students. Based on the findings, it is clear that teachers need training both on the need of differentiated education for gifted students and strategies and approaches about how to educate gifted students. Teachers’ attitudes towards gifted students in regular classrooms should be investigated so that teachers’ unsupportive beliefs about differentiation for gifted students also influence their attitudes towards gifted students.

Continuum-regularized quantum gravity

International Nuclear Information System (INIS)

Chan Huesum; Halpern, M.B.

1987-01-01

The recent continuum regularization of d-dimensional Euclidean gravity is generalized to arbitrary power-law measure and studied in some detail as a representative example of coordinate-invariant regularization. The weak-coupling expansion of the theory illustrates a generic geometrization of regularized Schwinger-Dyson rules, generalizing previous rules in flat space and flat superspace. The rules are applied in a non-trivial explicit check of Einstein invariance at one loop: the cosmological counterterm is computed and its contribution is included in a verification that the graviton mass is zero. (orig.)

Online co-regularized algorithms

NARCIS (Netherlands)

Ruijter, T. de; Tsivtsivadze, E.; Heskes, T.

2012-01-01

We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks

Geometric continuum regularization of quantum field theory

International Nuclear Information System (INIS)

Halpern, M.B.

1989-01-01

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

Bypassing the Limits of Ll Regularization: Convex Sparse Signal Processing Using Non-Convex Regularization

Science.gov (United States)

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

Physical Educators' Habitual Physical Activity and Self-Efficacy for Regular Exercise

Science.gov (United States)

Zhu, Xihe; Haegele, Justin A.; Davis, Summer

2018-01-01

The purpose of this study was to examine physical education teachers' habitual physical activity and self-efficacy for regular exercise. In-service physical education teachers (N = 168) voluntarily completed an online questionnaire that included items to collect demographic information (gender, race/ethnicity, years of teaching experience, and…

Using Tikhonov Regularization for Spatial Projections from CSR Regularized Spherical Harmonic GRACE Solutions

Science.gov (United States)

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.

Regularized maximum correntropy machine

KAUST Repository

Wang, Jim Jing-Yan; Wang, Yunji; Jing, Bing-Yi; Gao, Xin

2015-01-01

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.

Regularized maximum correntropy machine

KAUST Repository

Wang, Jim Jing-Yan

2015-02-12

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.

Regularities of Multifractal Measures

Indian Academy of Sciences (India)

First, we prove the decomposition theorem for the regularities of multifractal Hausdorff measure and packing measure in R R d . This decomposition theorem enables us to split a set into regular and irregular parts, so that we can analyze each separately, and recombine them without affecting density properties. Next, we ...

Smoke screen: an ethnographic study of a cigar shop's collective rationalization.

Science.gov (United States)

DeSantis, Alan D

2002-01-01

It is the purpose of this ethnographic study to explain why efforts from the medical establishment, the press, and friends and family are unsuccessful in persuading a group of men at a local cigar shop to stop smoking. I also seek to determine how these men create a linguistic defense shield that, ironically, protects them from the anxiety that such messages are designed to produce. I argue that the regulars at the shop collectively craft and share 6 prosmoking arguments that (a) rebuke the findings of the medical establishment, (b) anesthetize the regulars from the impact of antismoking messages, and (c) relieve cognitive dissonance and anxiety created by the act of smoking. I establish a theoretical foundation for the study, describe how the regulars craft and converge their collective narratives, and detail the 6 collectively created prosmoking narratives most frequently used by the regulars in countering antismoking messages.

Adaptive Regularization of Neural Classifiers

DEFF Research Database (Denmark)

Andersen, Lars Nonboe; Larsen, Jan; Hansen, Lars Kai

1997-01-01

We present a regularization scheme which iteratively adapts the regularization parameters by minimizing the validation error. It is suggested to use the adaptive regularization scheme in conjunction with optimal brain damage pruning to optimize the architecture and to avoid overfitting. Furthermo......, we propose an improved neural classification architecture eliminating an inherent redundancy in the widely used SoftMax classification network. Numerical results demonstrate the viability of the method...

Condition Number Regularized Covariance Estimation.

Science.gov (United States)

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.

SparseBeads data: benchmarking sparsity-regularized computed tomography

Science.gov (United States)

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

2017-12-01

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

76 FR 48799 - Agency Information Collection Activities: Proposed Collection; Comment Request-Characteristics...

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2011-08-09

...: Proposed Collection; Comment Request--Characteristics and Circumstances of Zero-Income SNAP Households... examine the characteristics, circumstances, program dynamics, and benefit redemption patterns of... Service during regular business hours (8:30 a.m. to 5 p.m., Monday through Friday) at 3101 Park Center...

Periodontal Disease, Regular Dental Care Use, and Incident Ischemic Stroke.

Science.gov (United States)

Sen, Souvik; Giamberardino, Lauren D; Moss, Kevin; Morelli, Thiago; Rosamond, Wayne D; Gottesman, Rebecca F; Beck, James; Offenbacher, Steven

2018-02-01

Periodontal disease is independently associated with cardiovascular disease. Identification of periodontal disease as a risk factor for incident ischemic stroke raises the possibility that regular dental care utilization may reduce the stroke risk. In the ARIC (Atherosclerosis Risk in Communities) study, pattern of dental visits were classified as regular or episodic dental care users. In the ancillary dental ARIC study, selected subjects from ARIC underwent fullmouth periodontal measurements collected at 6 sites per tooth and classified into 7 periodontal profile classes (PPCs). In the ARIC study 10 362 stroke-free participants, 584 participants had incident ischemic strokes over a 15-year period. In the dental ARIC study, 6736 dentate subjects were assessed for periodontal disease status using PPC with a total of 299 incident ischemic strokes over the 15-year period. The 7 levels of PPC showed a trend toward an increased stroke risk (χ 2 trend P periodontal disease). Periodontal disease was significantly associated with cardioembolic (hazard ratio, 2.6; 95% confidence interval, 1.2-5.6) and thrombotic (hazard ratio, 2.2; 95% confidence interval, 1.3-3.8) stroke subtypes. Regular dental care utilization was associated with lower adjusted stroke risk (hazard ratio, 0.77; 95% confidence interval, 0.63-0.94). We confirm an independent association between periodontal disease and incident stroke risk, particularly cardioembolic and thrombotic stroke subtype. Further, we report that regular dental care utilization may lower this risk for stroke. © 2018 American Heart Association, Inc.

Matrix of regularity for improving the quality of ECGs

International Nuclear Information System (INIS)

Xia, Henian; Garcia, Gabriel A; Zhao, Xiaopeng; Bains, Jujhar; Wortham, Dale C

2012-01-01

The 12-lead electrocardiography (ECG) is the gold standard for diagnosis of abnormalities of the heart. However, the ECG is susceptible to artifacts, which may lead to wrong diagnosis and thus mistreatment. It is a clinical challenge of great significance differentiating ECG artifacts from patterns of diseases. We propose a computational framework, called the matrix of regularity, to evaluate the quality of ECGs. The matrix of regularity is a novel mechanism to fuse results from multiple tests of signal quality. Moreover, this method can produce a continuous grade, which can more accurately represent the quality of an ECG. When tested on a dataset from the Computing in Cardiology/PhysioNet Challenge 2011, the algorithm achieves up to 95% accuracy. The area under the receiver operating characteristic curve is 0.97. The developed framework and computer program have the potential to improve the quality of ECGs collected using conventional and portable devices. (paper)

Utilitarian cycling in Belgium: a cross-sectional study in a sample of regular cyclists.

OpenAIRE

de Geus, B.; Degraeuwe, B.; Vandenbulcke, G.; INT PANIS, Luc; Thomas, I.; Aertsens, Joris; De Weerdt, Y.; Torfs, R.; Meeusen, R.

2014-01-01

Background: For an accurate estimation of health benefits and hazards of utilitarian cycling, a prospective collection of bicycle usage data (exposure) is fundamental. Individual and environmental correlates are necessary to guide health promotion and traffic safety issues. Firstly, this study aims to report on utilitarian bicycle usage in Belgium, using a prospective data collection in regular adult commuter cyclists. Secondly, the association is explored between the individual variation in ...

Condition Number Regularized Covariance Estimation*

Science.gov (United States)

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

Integral equations of the first kind, inverse problems and regularization: a crash course

International Nuclear Information System (INIS)

Groetsch, C W

2007-01-01

This paper is an expository survey of the basic theory of regularization for Fredholm integral equations of the first kind and related background material on inverse problems. We begin with an historical introduction to the field of integral equations of the first kind, with special emphasis on model inverse problems that lead to such equations. The basic theory of linear Fredholm equations of the first kind, paying particular attention to E. Schmidt's singular function analysis, Picard's existence criterion, and the Moore-Penrose theory of generalized inverses is outlined. The fundamentals of the theory of Tikhonov regularization are then treated and a collection of exercises and a bibliography are provided

Regular-, irregular-, and pseudo-character processing in Chinese: The regularity effect in normal adult readers

Directory of Open Access Journals (Sweden)

Dustin Kai Yan Lau

2014-03-01

Full Text Available Background Unlike alphabetic languages, Chinese uses a logographic script. However, the pronunciation of many character’s phonetic radical has the same pronunciation as the character as a whole. These are considered regular characters and can be read through a lexical non-semantic route (Weekes & Chen, 1999. Pseudocharacters are another way to study this non-semantic route. A pseudocharacter is the combination of existing semantic and phonetic radicals in their legal positions resulting in a non-existing character (Ho, Chan, Chung, Lee, & Tsang, 2007. Pseudocharacters can be pronounced by direct derivation from the sound of its phonetic radical. Conversely, if the pronunciation of a character does not follow that of the phonetic radical, it is considered as irregular and can only be correctly read through the lexical-semantic route. The aim of the current investigation was to examine reading aloud in normal adults. We hypothesized that the regularity effect, previously described for alphabetical scripts and acquired dyslexic patients of Chinese (Weekes & Chen, 1999; Wu, Liu, Sun, Chromik, & Zhang, 2014, would also be present in normal adult Chinese readers. Method Participants. Thirty (50% female native Hong Kong Cantonese speakers with a mean age of 19.6 years and a mean education of 12.9 years. Stimuli. Sixty regular-, 60 irregular-, and 60 pseudo-characters (with at least 75% of name agreement in Chinese were matched by initial phoneme, number of strokes and family size. Additionally, regular- and irregular-characters were matched by frequency (low and consistency. Procedure. Each participant was asked to read aloud the stimuli presented on a laptop using the DMDX software. The order of stimuli presentation was randomized. Data analysis. ANOVAs were carried out by participants and items with RTs and errors as dependent variables and type of stimuli (regular-, irregular- and pseudo-character as repeated measures (F1 or between subject�

The Effect of Regular-Season Rest on Playoff Performance Among Players in the National Basketball Association.

Science.gov (United States)

Belk, John W; Marshall, Hayden A; McCarty, Eric C; Kraeutler, Matthew J

2017-10-01

There has been speculation that rest during the regular season for players in the National Basketball Association (NBA) improves player performance in the postseason. To determine whether there is a correlation between the amount of regular-season rest among NBA players and playoff performance and injury risk in the same season. Cohort study; Level of evidence, 3. The Basketball Reference and Pro Sports Transactions archives were searched from the 2005 to 2015 seasons. Data were collected on players who missed fewer than 5 regular-season games because of rest (group A) and 5 to 9 regular-season games because of rest (group B) during each season. Inclusion criteria consisted of players who played a minimum of 20 minutes per game and made the playoffs that season. Players were excluded if they missed ≥10 games because of rest or suspension or missed ≥20 games in a season for any reason. Matched pairs were formed between the groups based on the following criteria: position, mean age at the start of the season within 2 years, regular-season minutes per game within 5 minutes, same playoff seeding, and player efficiency rating (PER) within 2 points. The following data from the playoffs were collected and compared between matched pairs at each position (point guard, shooting guard, forward/center): points per game, assists per game, PER, true shooting percentage, blocks, steals, and number of playoff games missed because of injury. A total of 811 players met the inclusion and exclusion criteria (group A: n = 744 players; group B: n = 67 players). Among all eligible players, 27 matched pairs were formed. Within these matched pairs, players in group B missed significantly more regular-season games because of rest than players in group A (6.0 games vs 1.3 games, respectively; P NBA regular season does not improve playoff performance or affect the injury risk during the playoffs in the same season.

Regularity effect in prospective memory during aging

Directory of Open Access Journals (Sweden)

Geoffrey Blondelle

2016-10-01

Full Text Available 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

J-regular rings with injectivities

OpenAIRE

Shen, Liang

2010-01-01

A ring $R$ is called a J-regular ring if R/J(R) is von Neumann regular, where J(R) is the Jacobson radical of R. It is proved that if R is J-regular, then (i) R is right n-injective if and only if every homomorphism from an $n$-generated small right ideal of $R$ to $R_{R}$ can be extended to one from $R_{R}$ to $R_{R}$; (ii) R is right FP-injective if and only if R is right (J, R)-FP-injective. Some known results are improved.

Attitude of Regular and Itinerant Teachers Towards the Inclusion of Hearing Impairment Children

Directory of Open Access Journals (Sweden)

Kamal Parhoon

2014-12-01

Full Text Available Objectives: Inclusive education is a process of enabling all children to learn and participate effectively within mainstream school systems. It does not segregate children who have different abilities or needs. This article explores the attitudes of regular and itinerant teachers about inclusion of hearing impairment children in their schools in general education. Methods: In a descriptive Survey research design, the sample included 100 teachers (50 regular and 50 itinerant who were selected randomly, according to a multistage sampling method. Data was collected by using questionnaire with 32 questions regarding their attitudes. One-way Analysis of Variance and t-test were performed to obtain between- group comparisons. Results: The results indicated that the teacher's positive attitudes towards inclusive educational system of students with hearing impairment. Significant difference in attitudes was observed, based on the teaching experience, gender, level of teaching. The results also indicate that most teachers are agreeable to the inclusion of students with hearing impairment in their classrooms. Discussion: successful inclusion for hearing impairment children in regular classrooms entails the positive attitudes of Regular and itinerant teachers through a systematic programming within the classroom.

Iterative Regularization with Minimum-Residual Methods

DEFF Research Database (Denmark)

Jensen, Toke Koldborg; Hansen, Per Christian

2007-01-01

subspaces. We provide a combination of theory and numerical examples, and our analysis confirms the experience that MINRES and MR-II can work as general regularization methods. We also demonstrate theoretically and experimentally that the same is not true, in general, for GMRES and RRGMRES their success......We study the regularization properties of iterative minimum-residual methods applied to discrete ill-posed problems. In these methods, the projection onto the underlying Krylov subspace acts as a regularizer, and the emphasis of this work is on the role played by the basis vectors of these Krylov...... as regularization methods is highly problem dependent....

Iterative regularization with minimum-residual methods

DEFF Research Database (Denmark)

Jensen, Toke Koldborg; Hansen, Per Christian

2006-01-01

subspaces. We provide a combination of theory and numerical examples, and our analysis confirms the experience that MINRES and MR-II can work as general regularization methods. We also demonstrate theoretically and experimentally that the same is not true, in general, for GMRES and RRGMRES - their success......We study the regularization properties of iterative minimum-residual methods applied to discrete ill-posed problems. In these methods, the projection onto the underlying Krylov subspace acts as a regularizer, and the emphasis of this work is on the role played by the basis vectors of these Krylov...... as regularization methods is highly problem dependent....

Multiple graph regularized protein domain ranking.

Science.gov (United States)

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

2012-11-19

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. 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. 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.

Higher derivative regularization and chiral anomaly

International Nuclear Information System (INIS)

Nagahama, Yoshinori.

1985-02-01

A higher derivative regularization which automatically leads to the consistent chiral anomaly is analyzed in detail. It explicitly breaks all the local gauge symmetry but preserves global chiral symmetry and leads to the chirally symmetric consistent anomaly. This regularization thus clarifies the physics content contained in the consistent anomaly. We also briefly comment on the application of this higher derivative regularization to massless QED. (author)

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan

2012-11-19

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. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

KAUST Repository

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

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. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

Directory of Open Access Journals (Sweden)

Wang Jim

2012-11-01

Full Text Available Abstract 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.

75 FR 53966 - Regular Meeting

Science.gov (United States)

2010-09-02

... FARM CREDIT SYSTEM INSURANCE CORPORATION Regular Meeting AGENCY: Farm Credit System Insurance Corporation Board. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). DATE AND TIME: The meeting of the Board will be held at the offices of the Farm...

Work and family life of childrearing women workers in Japan: comparison of non-regular employees with short working hours, non-regular employees with long working hours, and regular employees.

Science.gov (United States)

Seto, Masako; Morimoto, Kanehisa; Maruyama, Soichiro

2006-05-01

This study assessed the working and family life characteristics, and the degree of domestic and work strain of female workers with different employment statuses and weekly working hours who are rearing children. Participants were the mothers of preschoolers in a large Japanese city. We classified the women into three groups according to the hours they worked and their employment conditions. The three groups were: non-regular employees working less than 30 h a week (n=136); non-regular employees working 30 h or more per week (n=141); and regular employees working 30 h or more a week (n=184). We compared among the groups the subjective values of work, financial difficulties, childcare and housework burdens, psychological effects, and strains such as work and family strain, work-family conflict, and work dissatisfaction. Regular employees were more likely to report job pressures and inflexible work schedules and to experience more strain related to work and family than non-regular employees. Non-regular employees were more likely to be facing financial difficulties. In particular, non-regular employees working longer hours tended to encounter socioeconomic difficulties and often lacked support from family and friends. Female workers with children may have different social backgrounds and different stressors according to their working hours and work status.

Breaking of separability condition for dynamical collective subspace; Onset of quantum chaos in large-amplitude collective motion

Energy Technology Data Exchange (ETDEWEB)

Sakata, Fumihiko [Tokyo Univ., Tanashi (Japan). Inst. for Nuclear Study; Yamamoto, Yoshifumi; Marumori, Toshio; Iida, Shinji; Tsukuma, Hidehiko

1989-11-01

It is the purpose of the present paper to study 'global structure' of the state space of an N-body interacting fermion system, which exhibits regular, transient and stochastic phases depending on strength of the interaction. An optimum representation called a dynamical representation plays an essential role in this investigation. The concept of the dynamical representation has been introduced in the quantum theory of dynamical subspace in our previous paper, in order to determine self-consistently an optimum collective subspace as well as an optimum collective Hamiltonian. In the theory, furthermore, dynamical conditions called separability and stability conditions have been provided in order to identify the optimum collective subspace as an approximate invariant subspace of the Hamiltonian. Physical meaning of these conditions are clarified from a viewpoint to relate breaking of them with bifurcation of the collectivity and an onset of quantum chaos from the regular collective motion, by illustrating the general idea with numerical results obtained for a simple soluble model. It turns out that the onset of the stochastic phase is associated with dissolution of the quantum numbers to specify the collective subspace and this dissolution is induced by the breaking of the separability condition in the dynamical representation. (author).

Incremental projection approach of regularization for inverse problems

Energy Technology Data Exchange (ETDEWEB)

Souopgui, Innocent, E-mail: innocent.souopgui@usm.edu [The University of Southern Mississippi, Department of Marine Science (United States); Ngodock, Hans E., E-mail: hans.ngodock@nrlssc.navy.mil [Naval Research Laboratory (United States); Vidard, Arthur, E-mail: arthur.vidard@imag.fr; Le Dimet, François-Xavier, E-mail: ledimet@imag.fr [Laboratoire Jean Kuntzmann (France)

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.

Geometric regularizations and dual conifold transitions

International Nuclear Information System (INIS)

Landsteiner, Karl; Lazaroiu, Calin I.

2003-01-01

We consider a geometric regularization for the class of conifold transitions relating D-brane systems on noncompact Calabi-Yau spaces to certain flux backgrounds. This regularization respects the SL(2,Z) invariance of the flux superpotential, and allows for computation of the relevant periods through the method of Picard-Fuchs equations. The regularized geometry is a noncompact Calabi-Yau which can be viewed as a monodromic fibration, with the nontrivial monodromy being induced by the regulator. It reduces to the original, non-monodromic background when the regulator is removed. Using this regularization, we discuss the simple case of the local conifold, and show how the relevant field-theoretic information can be extracted in this approach. (author)

Adaptive regularization

DEFF Research Database (Denmark)

Hansen, Lars Kai; Rasmussen, Carl Edward; Svarer, C.

1994-01-01

Regularization, e.g., in the form of weight decay, is important for training and optimization of neural network architectures. In this work the authors provide a tool based on asymptotic sampling theory, for iterative estimation of weight decay parameters. The basic idea is to do a gradient desce...

Regularizing portfolio optimization

International Nuclear Information System (INIS)

Still, Susanne; Kondor, Imre

2010-01-01

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.

Regularizing portfolio optimization

Science.gov (United States)

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.

77 FR 6775 - Agency Information Collection Activities; Proposed Collection; Comment Request: Commodity...

Science.gov (United States)

2012-02-09

... the office of the Food and Nutrition Service during regular business hours (8:30 a.m. to 5 p.m. Monday... to provide for the collection of racial/ethnic data and information from applicants for and...) requires State agencies to submit data on the racial/ethnic categories of persons receiving benefits from...

Tessellating the Sphere with Regular Polygons

Science.gov (United States)

Soto-Johnson, Hortensia; Bechthold, Dawn

2004-01-01

Tessellations in the Euclidean plane and regular polygons that tessellate the sphere are reviewed. The regular polygons that can possibly tesellate the sphere are spherical triangles, squares and pentagons.

Accretion onto some well-known regular black holes

International Nuclear Information System (INIS)

Jawad, Abdul; Shahzad, M.U.

2016-01-01

In this work, we discuss the accretion onto static spherically symmetric regular black holes for specific choices of the equation of state parameter. The underlying regular black holes are charged regular black holes using the Fermi-Dirac distribution, logistic distribution, nonlinear electrodynamics, respectively, and Kehagias-Sftesos asymptotically flat regular black holes. We obtain the critical radius, critical speed, and squared sound speed during the accretion process near the regular black holes. We also study the behavior of radial velocity, energy density, and the rate of change of the mass for each of the regular black holes. (orig.)

Accretion onto some well-known regular black holes

Energy Technology Data Exchange (ETDEWEB)

Jawad, Abdul; Shahzad, M.U. [COMSATS Institute of Information Technology, Department of Mathematics, Lahore (Pakistan)

2016-03-15

In this work, we discuss the accretion onto static spherically symmetric regular black holes for specific choices of the equation of state parameter. The underlying regular black holes are charged regular black holes using the Fermi-Dirac distribution, logistic distribution, nonlinear electrodynamics, respectively, and Kehagias-Sftesos asymptotically flat regular black holes. We obtain the critical radius, critical speed, and squared sound speed during the accretion process near the regular black holes. We also study the behavior of radial velocity, energy density, and the rate of change of the mass for each of the regular black holes. (orig.)

Accretion onto some well-known regular black holes

Science.gov (United States)

Jawad, Abdul; Shahzad, M. Umair

2016-03-01

In this work, we discuss the accretion onto static spherically symmetric regular black holes for specific choices of the equation of state parameter. The underlying regular black holes are charged regular black holes using the Fermi-Dirac distribution, logistic distribution, nonlinear electrodynamics, respectively, and Kehagias-Sftesos asymptotically flat regular black holes. We obtain the critical radius, critical speed, and squared sound speed during the accretion process near the regular black holes. We also study the behavior of radial velocity, energy density, and the rate of change of the mass for each of the regular black holes.

Predictability in Pathological Gambling? Applying the Duplication of Purchase Law to the Understanding of Cross-Purchases Between Regular and Pathological Gamblers.

Science.gov (United States)

Lam, Desmond; Mizerski, Richard

2017-06-01

The objective of this study is to explore the gambling participations and game purchase duplication of light regular, heavy regular and pathological gamblers by applying the Duplication of Purchase Law. Current study uses data collected by the Australian Productivity Commission for eight different types of games. Key behavioral statistics on light regular, heavy regular, and pathological gamblers were computed and compared. The key finding is that pathological gambling, just like regular gambling, follows the Duplication of Purchase Law, which states that the dominant factor of purchase duplication between two brands is their market shares. This means that gambling between any two games at pathological level, like any regular consumer purchases, exhibits "law-like" regularity based on the pathological gamblers' participation rate of each game. Additionally, pathological gamblers tend to gamble more frequently across all games except lotteries and instant as well as make greater cross-purchases compared to heavy regular gamblers. A better understanding of the behavioral traits between regular (particularly heavy regular) and pathological gamblers can be useful to public policy makers and social marketers in order to more accurately identify such gamblers and better manage the negative impacts of gambling.

Diagrammatic methods in phase-space regularization

International Nuclear Information System (INIS)

Bern, Z.; Halpern, M.B.; California Univ., Berkeley

1987-11-01

Using the scalar prototype and gauge theory as the simplest possible examples, diagrammatic methods are developed for the recently proposed phase-space form of continuum regularization. A number of one-loop and all-order applications are given, including general diagrammatic discussions of the nogrowth theorem and the uniqueness of the phase-space stochastic calculus. The approach also generates an alternate derivation of the equivalence of the large-β phase-space regularization to the more conventional coordinate-space regularization. (orig.)

Metric regularity and subdifferential calculus

International Nuclear Information System (INIS)

Ioffe, A D

2000-01-01

The theory of metric regularity is an extension of two classical results: the Lyusternik tangent space theorem and the Graves surjection theorem. Developments in non-smooth analysis in the 1980s and 1990s paved the way for a number of far-reaching extensions of these results. It was also well understood that the phenomena behind the results are of metric origin, not connected with any linear structure. At the same time it became clear that some basic hypotheses of the subdifferential calculus are closely connected with the metric regularity of certain set-valued maps. The survey is devoted to the metric theory of metric regularity and its connection with subdifferential calculus in Banach spaces

Temporal regularity of the environment drives time perception

OpenAIRE

van Rijn, H; Rhodes, D; Di Luca, M

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 var- ied. In one experiment, we asked whether the last stim...

Increasing work-time influence: consequences for flexibility, variability, regularity and predictability.

Science.gov (United States)

Nabe-Nielsen, Kirsten; Garde, Anne Helene; Aust, Birgit; Diderichsen, Finn

2012-01-01

This quasi-experimental study investigated how an intervention aiming at increasing eldercare workers' influence on their working hours affected the flexibility, variability, regularity and predictability of the working hours. We used baseline (n = 296) and follow-up (n = 274) questionnaire data and interviews with intervention-group participants (n = 32). The work units in the intervention group designed their own intervention comprising either implementation of computerised self-scheduling (subgroup A), collection of information about the employees' work-time preferences by questionnaires (subgroup B), or discussion of working hours (subgroup C). Only computerised self-scheduling changed the working hours and the way they were planned. These changes implied more flexible but less regular working hours and an experience of less predictability and less continuity in the care of clients and in the co-operation with colleagues. In subgroup B and C, the participants ended up discussing the potential consequences of more work-time influence without actually implementing any changes. Employee work-time influence may buffer the adverse effects of shift work. However, our intervention study suggested that while increasing the individual flexibility, increasing work-time influence may also result in decreased regularity of the working hours and less continuity in the care of clients and co-operation with colleagues.

The uniqueness of the regularization procedure

International Nuclear Information System (INIS)

Brzezowski, S.

1981-01-01

On the grounds of the BPHZ procedure, the criteria of correct regularization in perturbation calculations of QFT are given, together with the prescription for dividing the regularized formulas into the finite and infinite parts. (author)

Learning regularization parameters for general-form Tikhonov

International Nuclear Information System (INIS)

Chung, Julianne; Español, Malena I

2017-01-01

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. (paper)

5 CFR 551.421 - Regular working hours.

Science.gov (United States)

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Regular working hours. 551.421 Section... Activities § 551.421 Regular working hours. (a) Under the Act there is no requirement that a Federal employee... distinction based on whether the activity is performed by an employee during regular working hours or outside...

Regular extensions of some classes of grammars

NARCIS (Netherlands)

Nijholt, Antinus

Culik and Cohen introduced the class of LR-regular grammars, an extension of the LR(k) grammars. In this report we consider the analogous extension of the LL(k) grammers, called the LL-regular grammars. The relations of this class of grammars to other classes of grammars are shown. Every LL-regular

Regular non-twisting S-branes

International Nuclear Information System (INIS)

Obregon, Octavio; Quevedo, Hernando; Ryan, Michael P.

2004-01-01

We construct a family of time and angular dependent, regular S-brane solutions which corresponds to a simple analytical continuation of the Zipoy-Voorhees 4-dimensional vacuum spacetime. The solutions are asymptotically flat and turn out to be free of singularities without requiring a twist in space. They can be considered as the simplest non-singular generalization of the singular S0-brane solution. We analyze the properties of a representative of this family of solutions and show that it resembles to some extent the asymptotic properties of the regular Kerr S-brane. The R-symmetry corresponds, however, to the general lorentzian symmetry. Several generalizations of this regular solution are derived which include a charged S-brane and an additional dilatonic field. (author)

Near-Regular Structure Discovery Using Linear Programming

KAUST Repository

Huang, Qixing

2014-06-02

Near-regular structures are common in manmade and natural objects. Algorithmic detection of such regularity greatly facilitates our understanding of shape structures, leads to compact encoding of input geometries, and enables efficient generation and manipulation of complex patterns on both acquired and synthesized objects. Such regularity manifests itself both in the repetition of certain geometric elements, as well as in the structured arrangement of the elements. We cast the regularity detection problem as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both these aspects are captured by our near-regular structure extraction framework, which alternates between discrete and continuous optimizations. We demonstrate the effectiveness of our framework on a variety of problems including near-regular structure extraction, structure-preserving pattern manipulation, and markerless correspondence detection. Robustness results with respect to geometric and topological noise are presented on synthesized, real-world, and also benchmark datasets. © 2014 ACM.

Regular Expression Matching and Operational Semantics

Directory of Open Access Journals (Sweden)

Asiri Rathnayake

2011-08-01

Full Text Available Many programming languages and tools, ranging from grep to the Java String library, contain regular expression matchers. Rather than first translating a regular expression into a deterministic finite automaton, such implementations typically match the regular expression on the fly. Thus they can be seen as virtual machines interpreting the regular expression much as if it were a program with some non-deterministic constructs such as the Kleene star. We formalize this implementation technique for regular expression matching using operational semantics. Specifically, we derive a series of abstract machines, moving from the abstract definition of matching to increasingly realistic machines. First a continuation is added to the operational semantics to describe what remains to be matched after the current expression. Next, we represent the expression as a data structure using pointers, which enables redundant searches to be eliminated via testing for pointer equality. From there, we arrive both at Thompson's lockstep construction and a machine that performs some operations in parallel, suitable for implementation on a large number of cores, such as a GPU. We formalize the parallel machine using process algebra and report some preliminary experiments with an implementation on a graphics processor using CUDA.

Tetravalent one-regular graphs of order 4p2

DEFF Research Database (Denmark)

Feng, Yan-Quan; Kutnar, Klavdija; Marusic, Dragan

2014-01-01

A graph is one-regular if its automorphism group acts regularly on the set of its arcs. In this paper tetravalent one-regular graphs of order 4p2, where p is a prime, are classified.......A graph is one-regular if its automorphism group acts regularly on the set of its arcs. In this paper tetravalent one-regular graphs of order 4p2, where p is a prime, are classified....

Regularization and error assignment to unfolded distributions

CERN Document Server

Zech, Gunter

2011-01-01

The commonly used approach to present unfolded data only in graphical formwith the diagonal error depending on the regularization strength is unsatisfac-tory. It does not permit the adjustment of parameters of theories, the exclusionof theories that are admitted by the observed data and does not allow the com-bination of data from different experiments. We propose fixing the regulariza-tion strength by a p-value criterion, indicating the experimental uncertaintiesindependent of the regularization and publishing the unfolded data in additionwithout regularization. These considerations are illustrated with three differentunfolding and smoothing approaches applied to a toy example.

Higher order total variation regularization for EIT reconstruction.

Science.gov (United States)

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Zhang, Fan; Mueller-Lisse, Ullrich; Moeller, Knut

2018-01-08

Electrical impedance tomography (EIT) attempts to reveal the conductivity distribution of a domain based on the electrical boundary condition. This is an ill-posed inverse problem; its solution is very unstable. Total variation (TV) regularization is one of the techniques commonly employed to stabilize reconstructions. However, it is well known that TV regularization induces staircase effects, which are not realistic in clinical applications. To reduce such artifacts, modified TV regularization terms considering a higher order differential operator were developed in several previous studies. One of them is called total generalized variation (TGV) regularization. TGV regularization has been successively applied in image processing in a regular grid context. In this study, we adapted TGV regularization to the finite element model (FEM) framework for EIT reconstruction. Reconstructions using simulation and clinical data were performed. First results indicate that, in comparison to TV regularization, TGV regularization promotes more realistic images. Graphical abstract Reconstructed conductivity changes located on selected vertical lines. For each of the reconstructed images as well as the ground truth image, conductivity changes located along the selected left and right vertical lines are plotted. In these plots, the notation GT in the legend stands for ground truth, TV stands for total variation method, and TGV stands for total generalized variation method. Reconstructed conductivity distributions from the GREIT algorithm are also demonstrated.

Application of Turchin's method of statistical regularization

Science.gov (United States)

Zelenyi, Mikhail; Poliakova, Mariia; Nozik, Alexander; Khudyakov, Alexey

2018-04-01

During analysis of experimental data, one usually needs to restore a signal after it has been convoluted with some kind of apparatus function. According to Hadamard's definition this problem is ill-posed and requires regularization to provide sensible results. In this article we describe an implementation of the Turchin's method of statistical regularization based on the Bayesian approach to the regularization strategy.

On the regularized fermionic projector of the vacuum

Science.gov (United States)

Finster, Felix

2008-03-01

We construct families of fermionic projectors with spherically symmetric regularization, which satisfy the condition of a distributional MP-product. The method is to analyze regularization tails with a power law or logarithmic scaling in composite expressions in the fermionic projector. The resulting regularizations break the Lorentz symmetry and give rise to a multilayer structure of the fermionic projector near the light cone. Furthermore, we construct regularizations which go beyond the distributional MP-product in that they yield additional distributional contributions supported at the origin. The remaining freedom for the regularization parameters and the consequences for the normalization of the fermionic states are discussed.

On the regularized fermionic projector of the vacuum

International Nuclear Information System (INIS)

Finster, Felix

2008-01-01

We construct families of fermionic projectors with spherically symmetric regularization, which satisfy the condition of a distributional MP-product. The method is to analyze regularization tails with a power law or logarithmic scaling in composite expressions in the fermionic projector. The resulting regularizations break the Lorentz symmetry and give rise to a multilayer structure of the fermionic projector near the light cone. Furthermore, we construct regularizations which go beyond the distributional MP-product in that they yield additional distributional contributions supported at the origin. The remaining freedom for the regularization parameters and the consequences for the normalization of the fermionic states are discussed

Regularization modeling for large-eddy simulation

NARCIS (Netherlands)

Geurts, Bernardus J.; Holm, D.D.

2003-01-01

A new modeling approach for large-eddy simulation (LES) is obtained by combining a "regularization principle" with an explicit filter and its inversion. This regularization approach allows a systematic derivation of the implied subgrid model, which resolves the closure problem. The central role of

Spatially-Variant Tikhonov Regularization for Double-Difference Waveform Inversion

Energy Technology Data Exchange (ETDEWEB)

Lin, Youzuo [Los Alamos National Laboratory; Huang, Lianjie [Los Alamos National Laboratory; Zhang, Zhigang [Los Alamos National Laboratory

2011-01-01

Double-difference waveform inversion is a potential tool for quantitative monitoring for geologic carbon storage. It jointly inverts time-lapse seismic data for changes in reservoir geophysical properties. Due to the ill-posedness of waveform inversion, it is a great challenge to obtain reservoir changes accurately and efficiently, particularly when using time-lapse seismic reflection data. Regularization techniques can be utilized to address the issue of ill-posedness. The regularization parameter controls the smoothness of inversion results. A constant regularization parameter is normally used in waveform inversion, and an optimal regularization parameter has to be selected. The resulting inversion results are a trade off among regions with different smoothness or noise levels; therefore the images are either over regularized in some regions while under regularized in the others. In this paper, we employ a spatially-variant parameter in the Tikhonov regularization scheme used in double-difference waveform tomography to improve the inversion accuracy and robustness. We compare the results obtained using a spatially-variant parameter with those obtained using a constant regularization parameter and those produced without any regularization. We observe that, utilizing a spatially-variant regularization scheme, the target regions are well reconstructed while the noise is reduced in the other regions. We show that the spatially-variant regularization scheme provides the flexibility to regularize local regions based on the a priori information without increasing computational costs and the computer memory requirement.

Manifold Regularized Correlation Object Tracking.

Science.gov (United States)

Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

2018-05-01

In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped from both target and nontarget regions. Thus, the final classifier in our method is trained with positive, negative, and unlabeled base samples, which is a semisupervised learning framework. A block optimization strategy is further introduced to learn a manifold regularization-based correlation filter for efficient online tracking. Experiments on two public tracking data sets demonstrate the superior performance of our tracker compared with the state-of-the-art tracking approaches.

From recreational to regular drug use

DEFF Research Database (Denmark)

Järvinen, Margaretha; Ravn, Signe

2011-01-01

This article analyses the process of going from recreational use to regular and problematic use of illegal drugs. We present a model containing six career contingencies relevant for young people’s progress from recreational to regular drug use: the closing of social networks, changes in forms...

Regular variation on measure chains

Czech Academy of Sciences Publication Activity Database

Řehák, Pavel; Vitovec, J.

2010-01-01

Roč. 72, č. 1 (2010), s. 439-448 ISSN 0362-546X R&D Projects: GA AV ČR KJB100190701 Institutional research plan: CEZ:AV0Z10190503 Keywords : regularly varying function * regularly varying sequence * measure chain * time scale * embedding theorem * representation theorem * second order dynamic equation * asymptotic properties Subject RIV: BA - General Mathematics Impact factor: 1.279, year: 2010 http://www.sciencedirect.com/science/article/pii/S0362546X09008475

New regular black hole solutions

International Nuclear Information System (INIS)

Lemos, Jose P. S.; Zanchin, Vilson T.

2011-01-01

In the present work we consider general relativity coupled to Maxwell's electromagnetism and charged matter. Under the assumption of spherical symmetry, there is a particular class of solutions that correspond to regular charged black holes whose interior region is de Sitter, the exterior region is Reissner-Nordstroem and there is a charged thin-layer in-between the two. The main physical and geometrical properties of such charged regular black holes are analyzed.

Manifold Regularized Correlation Object Tracking

OpenAIRE

Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

2017-01-01

In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped fr...

On geodesics in low regularity

Science.gov (United States)

Sämann, Clemens; Steinbauer, Roland

2018-02-01

We consider geodesics in both Riemannian and Lorentzian manifolds with metrics of low regularity. We discuss existence of extremal curves for continuous metrics and present several old and new examples that highlight their subtle interrelation with solutions of the geodesic equations. Then we turn to the initial value problem for geodesics for locally Lipschitz continuous metrics and generalize recent results on existence, regularity and uniqueness of solutions in the sense of Filippov.

78 FR 55052 - Agency Information Collection Activities: Proposed Collection; Comment Request-Form FNS-13...

Science.gov (United States)

2013-09-09

... reporting burden hours as a result of automation and the advancement of State systems technology. The... collection techniques or other forms of information technology. Written comments may be sent to Jon Garcia... the office of the Food and Nutrition Service during regular business hours (8:30 a.m. to 5 p.m. Monday...

Manifold Regularized Reinforcement Learning.

Science.gov (United States)

Li, Hongliang; Liu, Derong; Wang, Ding

2018-04-01

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.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Organizational commitment and intrinsic motivation of regular and contractual primary health care providers

Directory of Open Access Journals (Sweden)

Pawan Kumar

2016-01-01

Full Text Available Background: Motivated and committed employees deliver better health care, which results in better outcomes and higher patient satisfaction. Objective: To assess the Organizational Commitment and Intrinsic Motivation of Primary Health Care Providers (HCPs in New Delhi, India. Materials and Methods: Study was conducted in 2013 on a sample of 333 HCPs who were selected using multistage stage random sampling technique. The sample includes medical officers, auxiliary nurses and midwives, and pharmacists and laboratory technicians/assistants among regular and contractual staff. Data were collected using the pretested structured questionnaire for organization commitment (OC, job satisfiers, and intrinsic job motivation. Analysis was done by using SPSS version 18 and appropriate statistical tests were applied. Results: The mean score for OC for entire regular staff is 1.6 ± 0.39 and contractual staff is 1.3 ± 0.45 which has statistically significant difference (t = 5.57; P = 0.00. In both regular and contractual staff, none of them show high emotional attachment with the organization and does not feel part of the family in the organization. Contractual staff does not feel proud to work in a present organization for rest of their career. Intrinsic motivation is high in both regular and contractual groups but intergroup difference is significant (t = 2.38; P < 0.05. Contractual staff has more dissatisfier than regular, and the difference is significant (P < 0.01. Conclusion: Organizational commitment and intrinsic motivation of contractual staff are lesser than the permanent staff. Appropriate changes are required in the predictors of organizational commitment and factors responsible for satisfaction in the organization to keep the contractual human resource motivated and committed to the organization.

Laplacian manifold regularization method for fluorescence molecular tomography

Science.gov (United States)

He, Xuelei; Wang, Xiaodong; Yi, Huangjian; Chen, Yanrong; Zhang, Xu; Yu, Jingjing; He, Xiaowei

2017-04-01

Sparse regularization methods have been widely used in fluorescence molecular tomography (FMT) for stable three-dimensional reconstruction. Generally, ℓ1-regularization-based methods allow for utilizing the sparsity nature of the target distribution. However, in addition to sparsity, the spatial structure information should be exploited as well. A joint ℓ1 and Laplacian manifold regularization model is proposed to improve the reconstruction performance, and two algorithms (with and without Barzilai-Borwein strategy) are presented to solve the regularization model. Numerical studies and in vivo experiment demonstrate that the proposed Gradient projection-resolved Laplacian manifold regularization method for the joint model performed better than the comparative algorithm for ℓ1 minimization method in both spatial aggregation and location accuracy.

The patterning of retinal horizontal cells: normalizing the regularity index enhances the detection of genomic linkage

Directory of Open Access Journals (Sweden)

Patrick W. Keeley

2014-10-01

Full Text Available Retinal neurons are often arranged as non-random distributions called mosaics, as their somata minimize proximity to neighboring cells of the same type. The horizontal cells serve as an example of such a mosaic, but little is known about the developmental mechanisms that underlie their patterning. To identify genes involved in this process, we have used three different spatial statistics to assess the patterning of the horizontal cell mosaic across a panel of genetically distinct recombinant inbred strains. To avoid the confounding effect cell density, which varies two-fold across these different strains, we computed the real/random regularity ratio, expressing the regularity of a mosaic relative to a randomly distributed simulation of similarly sized cells. To test whether this latter statistic better reflects the variation in biological processes that contribute to horizontal cell spacing, we subsequently compared the genetic linkage for each of these two traits, the regularity index and the real/random regularity ratio, each computed from the distribution of nearest neighbor (NN distances and from the Voronoi domain (VD areas. Finally, we compared each of these analyses with another index of patterning, the packing factor. Variation in the regularity indexes, as well as their real/random regularity ratios, and the packing factor, mapped quantitative trait loci (QTL to the distal ends of Chromosomes 1 and 14. For the NN and VD analyses, we found that the degree of linkage was greater when using the real/random regularity ratio rather than the respective regularity index. Using informatic resources, we narrow the list of prospective genes positioned at these two intervals to a small collection of six genes that warrant further investigation to determine their potential role in shaping the patterning of the horizontal cell mosaic.

Learning Sparse Visual Representations with Leaky Capped Norm Regularizers

OpenAIRE

Wangni, Jianqiao; Lin, Dahua

2017-01-01

Sparsity inducing regularization is an important part for learning over-complete visual representations. Despite the popularity of $\\ell_1$ regularization, in this paper, we investigate the usage of non-convex regularizations in this problem. Our contribution consists of three parts. First, we propose the leaky capped norm regularization (LCNR), which allows model weights below a certain threshold to be regularized more strongly as opposed to those above, therefore imposes strong sparsity and...

Adaptive regularization of noisy linear inverse problems

DEFF Research Database (Denmark)

Hansen, Lars Kai; Madsen, Kristoffer Hougaard; Lehn-Schiøler, Tue

2006-01-01

In the Bayesian modeling framework there is a close relation between regularization and the prior distribution over parameters. For prior distributions in the exponential family, we show that the optimal hyper-parameter, i.e., the optimal strength of regularization, satisfies a simple relation: T......: The expectation of the regularization function, i.e., takes the same value in the posterior and prior distribution. We present three examples: two simulations, and application in fMRI neuroimaging....

On infinite regular and chiral maps

OpenAIRE

Arredondo, John A.; Valdez, Camilo Ramírez y Ferrán

2015-01-01

We prove that infinite regular and chiral maps take place on surfaces with at most one end. Moreover, we prove that an infinite regular or chiral map on an orientable surface with genus can only be realized on the Loch Ness monster, that is, the topological surface of infinite genus with one end.

29 CFR 779.18 - Regular rate.

Science.gov (United States)

2010-07-01

... employee under subsection (a) or in excess of the employee's normal working hours or regular working hours... Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR STATEMENTS OF GENERAL POLICY OR... not less than one and one-half times their regular rates of pay. Section 7(e) of the Act defines...

Continuum regularized Yang-Mills theory

International Nuclear Information System (INIS)

Sadun, L.A.

1987-01-01

Using the machinery of stochastic quantization, Z. Bern, M. B. Halpern, C. Taubes and I recently proposed a continuum regularization technique for quantum field theory. This regularization may be implemented by applying a regulator to either the (d + 1)-dimensional Parisi-Wu Langevin equation or, equivalently, to the d-dimensional second order Schwinger-Dyson (SD) equations. This technique is non-perturbative, respects all gauge and Lorentz symmetries, and is consistent with a ghost-free gauge fixing (Zwanziger's). This thesis is a detailed study of this regulator, and of regularized Yang-Mills theory, using both perturbative and non-perturbative techniques. The perturbative analysis comes first. The mechanism of stochastic quantization is reviewed, and a perturbative expansion based on second-order SD equations is developed. A diagrammatic method (SD diagrams) for evaluating terms of this expansion is developed. We apply the continuum regulator to a scalar field theory. Using SD diagrams, we show that all Green functions can be rendered finite to all orders in perturbation theory. Even non-renormalizable theories can be regularized. The continuum regulator is then applied to Yang-Mills theory, in conjunction with Zwanziger's gauge fixing. A perturbative expansion of the regulator is incorporated into the diagrammatic method. It is hoped that the techniques discussed in this thesis will contribute to the construction of a renormalized Yang-Mills theory is 3 and 4 dimensions

Regularity effect in prospective memory during aging

OpenAIRE

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), 1...

20 CFR 226.14 - Employee regular annuity rate.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Employee regular annuity rate. 226.14 Section... COMPUTING EMPLOYEE, SPOUSE, AND DIVORCED SPOUSE ANNUITIES Computing an Employee Annuity § 226.14 Employee regular annuity rate. The regular annuity rate payable to the employee is the total of the employee tier I...

The use of assistive technology resources for disabled children in regular schooling: the teachers’ perception

Directory of Open Access Journals (Sweden)

2012-12-01

Full Text Available The national School Census revealed that 702,603 disabled people were enrolled in regular educationin 2010. The use of assistive technology resources in the school context has been indicated to favor the executionof tasks and the access to educational content and school environments and, consequently, help disabledindividuals’ learning. However, there are few studies showing the impact of these resources in the educationprocess of children with physical disabilities. The aim of this study was to identify, from the teacher’s viewpoint,the contributions and difficulties in the use of technology resources with students with cerebral palsy, focusingon those with severe motor impairment, attending regular education. The study included five teachers of these students who were using assistive technology resources in the execution of writing and/or communicationassignments. Semi-structured interviews were conducted and data were analyzed following the CollectiveSubject Discourse (CSD technique. Results indicated that assistive technology resources are already includedin regular schools and that they have brought contributions to the education process of children with cerebralpalsy in regular class; nevertheless, they are being implemented without systematization, monitoring and/orpartnerships. The study pointed to the need to consider the opinions and requirements of the people involved inthe context where the use of technology is inserted.

Regular algebra and finite machines

CERN Document Server

Conway, John Horton

2012-01-01

World-famous mathematician John H. Conway based this classic text on a 1966 course he taught at Cambridge University. Geared toward graduate students of mathematics, it will also prove a valuable guide to researchers and professional mathematicians.His topics cover Moore's theory of experiments, Kleene's theory of regular events and expressions, Kleene algebras, the differential calculus of events, factors and the factor matrix, and the theory of operators. Additional subjects include event classes and operator classes, some regulator algebras, context-free languages, communicative regular alg

39 CFR 6.1 - Regular meetings, annual meeting.

Science.gov (United States)

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...

29 CFR 42.21 - Data collection.

Science.gov (United States)

2010-07-01

... responsive action on the case. Where available, OSHA shall submit data showing the average length of time..., OSHA, and the Office of the Solicitor (SOL) shall regularly collect statistical data reflecting their... income was restored; and (6) total amount of money restored. (d) OSHA's migrant farmworker enforcement...

Quantifying collective attention from tweet stream.

Directory of Open Access Journals (Sweden)

Kazutoshi Sasahara

Full Text Available Online social media are increasingly facilitating our social interactions, thereby making available a massive "digital fossil" of human behavior. Discovering and quantifying distinct patterns using these data is important for studying social behavior, although the rapid time-variant nature and large volumes of these data make this task difficult and challenging. In this study, we focused on the emergence of "collective attention" on Twitter, a popular social networking service. We propose a simple method for detecting and measuring the collective attention evoked by various types of events. This method exploits the fact that tweeting activity exhibits a burst-like increase and an irregular oscillation when a particular real-world event occurs; otherwise, it follows regular circadian rhythms. The difference between regular and irregular states in the tweet stream was measured using the Jensen-Shannon divergence, which corresponds to the intensity of collective attention. We then associated irregular incidents with their corresponding events that attracted the attention and elicited responses from large numbers of people, based on the popularity and the enhancement of key terms in posted messages or "tweets." Next, we demonstrate the effectiveness of this method using a large dataset that contained approximately 490 million Japanese tweets by over 400,000 users, in which we identified 60 cases of collective attentions, including one related to the Tohoku-oki earthquake. "Retweet" networks were also investigated to understand collective attention in terms of social interactions. This simple method provides a retrospective summary of collective attention, thereby contributing to the fundamental understanding of social behavior in the digital era.

A regularized stationary mean-field game

KAUST Repository

Yang, Xianjin

2016-01-01

In the thesis, we discuss the existence and numerical approximations of solutions of a regularized mean-field game with a low-order regularization. In the first part, we prove a priori estimates and use the continuation method to obtain the existence of a solution with a positive density. Finally, we introduce the monotone flow method and solve the system numerically.

A regularized stationary mean-field game

KAUST Repository

Yang, Xianjin

2016-04-19

In the thesis, we discuss the existence and numerical approximations of solutions of a regularized mean-field game with a low-order regularization. In the first part, we prove a priori estimates and use the continuation method to obtain the existence of a solution with a positive density. Finally, we introduce the monotone flow method and solve the system numerically.

Automating InDesign with Regular Expressions

CERN Document Server

Kahrel, Peter

2006-01-01

If you need to make automated changes to InDesign documents beyond what basic search and replace can handle, you need regular expressions, and a bit of scripting to make them work. This Short Cut explains both how to write regular expressions, so you can find and replace the right things, and how to use them in InDesign specifically.

78 FR 42982 - Submission for Review: Information Collection; Questionnaire for Non-Sensitive Positions (SF 85)

Science.gov (United States)

2013-07-18

... Government civilian or military positions, or positions in private entities performing work for the Federal... adjudication. The SF 85 is completed by civilian employees of the Federal Government, military personnel, and... Security Number and provide the results to OPM. Clarifying language was added to the Authorization for...

Optimal behaviour can violate the principle of regularity.

Science.gov (United States)

Trimmer, Pete C

2013-07-22

Understanding decisions is a fundamental aim of behavioural ecology, psychology and economics. The regularity axiom of utility theory holds that a preference between options should be maintained when other options are made available. Empirical studies have shown that animals violate regularity but this has not been understood from a theoretical perspective, such decisions have therefore been labelled as irrational. Here, I use models of state-dependent behaviour to demonstrate that choices can violate regularity even when behavioural strategies are optimal. I also show that the range of conditions over which regularity should be violated can be larger when options do not always persist into the future. Consequently, utility theory--based on axioms, including transitivity, regularity and the independence of irrelevant alternatives--is undermined, because even alternatives that are never chosen by an animal (in its current state) can be relevant to a decision.

Dimensional regularization in configuration space

International Nuclear Information System (INIS)

Bollini, C.G.; Giambiagi, J.J.

1995-09-01

Dimensional regularization is introduced in configuration space by Fourier transforming in D-dimensions the perturbative momentum space Green functions. For this transformation, Bochner theorem is used, no extra parameters, such as those of Feynman or Bogoliubov-Shirkov are needed for convolutions. The regularized causal functions in x-space have ν-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 functions of ν. Several example are discussed. (author). 9 refs

Matrix regularization of 4-manifolds

OpenAIRE

Trzetrzelewski, M.

2012-01-01

We consider products of two 2-manifolds such as S^2 x S^2, embedded in Euclidean space and show that the corresponding 4-volume preserving diffeomorphism algebra can be approximated by a tensor product SU(N)xSU(N) i.e. functions on a manifold are approximated by the Kronecker product of two SU(N) matrices. A regularization of the 4-sphere is also performed by constructing N^2 x N^2 matrix representations of the 4-algebra (and as a byproduct of the 3-algebra which makes the regularization of S...

On the equivalence of different regularization methods

International Nuclear Information System (INIS)

Brzezowski, S.

1985-01-01

The R-circunflex-operation preceded by the regularization procedure is discussed. Some arguments are given, according to which the results may depend on the method of regularization, introduced in order to avoid divergences in perturbation calculations. 10 refs. (author)

Effects of gasoline engine emissions on preexisting allergic airway responses in mice.

Science.gov (United States)

Day, Kimberly C; Reed, Matthew D; McDonald, Jacob D; Seilkop, Steven K; Barrett, Edward G

2008-10-01

Gasoline-powered vehicle emissions contribute significantly to ambient air pollution. We hypothesized that exposure to gasoline engine emissions (GEE) may exacerbate preexisting allergic airway responses. Male BALB/c mice were sensitized by injection with ovalbumin (OVA) and then received a 10-min aerosolized OVA challenge. Parallel groups were sham-sensitized with saline. Mice were exposed 6 h/day to air (control, C) or GEE containing particulate matter (PM) at low (L), medium (M), or high (H) concentrations, or to the H level with PM removed by filtration (high-filtered, HF). Immediately after GEE exposure mice received another 10-min aerosol OVA challenge (pre-OVA protocol). In a second (post-OVA) protocol, mice were similarly sensitized but only challenged to OVA before air or GEE exposure. Measurements of airway hyperresponsiveness (AHR), bronchoalveolar lavage (BAL), and blood collection were performed approximately 24 h after the last exposure. In both protocols, M, H, and HF GEE exposure significantly decreased BAL neutrophils from nonsensitized mice but had no significant effect on BAL cells from OVA-sensitized mice. In the pre-OVA protocol, GEE exposure increased OVA-specific IgG(1) but had no effect on BAL interleukin (IL)-2, IL-4, IL-13, or interferon (IFN)-gamma in OVA-sensitized mice. Nonsensitized GEE-exposed mice had increased OVA-specific IgG(2a), IgE, and IL-2, but decreased total IgE. In the post-OVA protocol, GEE exposure reduced BAL IL-4, IL-5, and IFN-gamma in nonsensitized mice but had no effect on sensitized mice. These results suggest acute exposure to the gas-vapor phase of GEE suppressed inflammatory cells and cytokines from nonsensitized mice but did not substantially exacerbate allergic responses.

Accreting fluids onto regular black holes via Hamiltonian approach

Energy Technology Data Exchange (ETDEWEB)

Jawad, Abdul [COMSATS Institute of Information Technology, Department of Mathematics, Lahore (Pakistan); Shahzad, M.U. [COMSATS Institute of Information Technology, Department of Mathematics, Lahore (Pakistan); University of Central Punjab, CAMS, UCP Business School, Lahore (Pakistan)

2017-08-15

We investigate the accretion of test fluids onto regular black holes such as Kehagias-Sfetsos black holes and regular black holes with Dagum distribution function. We analyze the accretion process when different test fluids are falling onto these regular black holes. The accreting fluid is being classified through the equation of state according to the features of regular black holes. The behavior of fluid flow and the existence of sonic points is being checked for these regular black holes. It is noted that the three-velocity depends on critical points and the equation of state parameter on phase space. (orig.)

Regular exercise training reverses ectonucleotidase alterations and reduces hyperaggregation of platelets in metabolic syndrome patients.

Science.gov (United States)

Martins, Caroline Curry; Bagatini, Margarete Dulce; Cardoso, Andréia Machado; Zanini, Daniela; Abdalla, Fátima Husein; Baldissarelli, Jucimara; Dalenogare, Diéssica Padilha; Farinha, Juliano Boufleur; Schetinger, Maria Rosa Chitolina; Morsch, Vera Maria

2016-02-15

Alterations in the activity of ectonucleotidase enzymes have been implicated in cardiovascular diseases, whereas regular exercise training has been shown to prevent these alterations. However, nothing is known about it relating to metabolic syndrome (MetS). We investigated the effect of exercise training on platelet ectonucleotidase enzymes and on the aggregation profile of MetS patients. We studied 38 MetS patients who performed regular concurrent exercise training for 30 weeks. Anthropometric measurements, biochemical profiles, hydrolysis of adenine nucleotides in platelets and platelet aggregation were collected from patients before and after the exercise intervention as well as from individuals of the control group. An increase in the hydrolysis of adenine nucleotides (ATP, ADP and AMP) and a decrease in adenosine deamination in the platelets of MetS patients before the exercise intervention were observed (Pexercise training (Pexercise training prevented platelet hyperaggregation in addition to decrease the classic cardiovascular risks. An alteration of ectonucleotidase enzymes occurs during MetS, whereas regular exercise training had a protective effect on these enzymes and on platelet aggregation. Copyright © 2016 Elsevier B.V. All rights reserved.

The effects of regular physical exercise on the human body

Directory of Open Access Journals (Sweden)

Mavrić Fahrudin

2014-01-01

Full Text Available Regular physical activities should be an integral part of an active lifestyle and the proper use of one's time. Programs including such activities are more effectively being applied in the prevention and elimination of health problems, especially those that are the result of decreased movement, inadequate nutrition and excessive nervous tension. Numerous studies have revealed new information about the link between physical activity and quality of life. Each person would have to be involved in physical activity of moderate intensity most days for 30 to 60 minutes, because active people are more healthier and have higher endurance levels, have a positive attitude towards work and cope with everyday stress better. Activity helps you look better, makes you happier and more vital. Studies have clearly shown that physical activity affects health and reduces the risk of many diseases. An active life increases energy, vitality, helps change bad habits, improves health, and strengthens one's energy and desire for life. The aim of this study was to determine the effects of regular physical activity on the human body. The subject matter of this study is the collection and analysis of results which the authors of various studies have obtained. The reviewed literature was collected using a web browser, and consisted of research work available in the Kobson database, through Google Scholar and in journals available in the field of sports science. The method of treatment is descriptive because the studies involved a variety of training programs, people of different ages, and tests carried out by different measuring instruments, so there is no possibility of a comparison of the results by other means.

Bounded Perturbation Regularization for Linear Least Squares Estimation

KAUST Repository

Ballal, Tarig

2017-10-18

This paper addresses the problem of selecting the regularization parameter for linear least-squares estimation. We propose a new technique called bounded perturbation regularization (BPR). In the proposed BPR method, a perturbation with a bounded norm is allowed into the linear transformation matrix to improve the singular-value structure. Following this, the problem is formulated as a min-max optimization problem. Next, the min-max problem is converted to an equivalent minimization problem to estimate the unknown vector quantity. The solution of the minimization problem is shown to converge to that of the ℓ2 -regularized least squares problem, with the unknown regularizer related to the norm bound of the introduced perturbation through a nonlinear constraint. A procedure is proposed that combines the constraint equation with the mean squared error (MSE) criterion to develop an approximately optimal regularization parameter selection algorithm. Both direct and indirect applications of the proposed method are considered. Comparisons with different Tikhonov regularization parameter selection methods, as well as with other relevant methods, are carried out. Numerical results demonstrate that the proposed method provides significant improvement over state-of-the-art methods.

Block matching sparsity regularization-based image reconstruction for incomplete projection data in computed tomography

Science.gov (United States)

Cai, Ailong; Li, Lei; Zheng, Zhizhong; Zhang, Hanming; Wang, Linyuan; Hu, Guoen; Yan, Bin

2018-02-01

In medical imaging many conventional regularization methods, such as total variation or total generalized variation, impose strong prior assumptions which can only account for very limited classes of images. A more reasonable sparse representation frame for images is still badly needed. Visually understandable images contain meaningful patterns, and combinations or collections of these patterns can be utilized to form some sparse and redundant representations which promise to facilitate image reconstructions. In this work, we propose and study block matching sparsity regularization (BMSR) and devise an optimization program using BMSR for computed tomography (CT) image reconstruction for an incomplete projection set. The program is built as a constrained optimization, minimizing the L1-norm of the coefficients of the image in the transformed domain subject to data observation and positivity of the image itself. To solve the program efficiently, a practical method based on the proximal point algorithm is developed and analyzed. In order to accelerate the convergence rate, a practical strategy for tuning the BMSR parameter is proposed and applied. The experimental results for various settings, including real CT scanning, have verified the proposed reconstruction method showing promising capabilities over conventional regularization.

MRI reconstruction with joint global regularization and transform learning.

Science.gov (United States)

Tanc, A Korhan; Eksioglu, Ender M

2016-10-01

Sparsity based regularization has been a popular approach to remedy the measurement scarcity in image reconstruction. Recently, sparsifying transforms learned from image patches have been utilized as an effective regularizer for the Magnetic Resonance Imaging (MRI) reconstruction. Here, we infuse additional global regularization terms to the patch-based transform learning. We develop an algorithm to solve the resulting novel cost function, which includes both patchwise and global regularization terms. Extensive simulation results indicate that the introduced mixed approach has improved MRI reconstruction performance, when compared to the algorithms which use either of the patchwise transform learning or global regularization terms alone. Copyright © 2016 Elsevier Ltd. All rights reserved.

Organizational commitment and intrinsic motivation of regular and contractual primary health care providers.

Science.gov (United States)

Kumar, Pawan; Mehra, Anu; Inder, Deep; Sharma, Nandini

2016-01-01

Motivated and committed employees deliver better health care, which results in better outcomes and higher patient satisfaction. To assess the Organizational Commitment and Intrinsic Motivation of Primary Health Care Providers (HCPs) in New Delhi, India. Study was conducted in 2013 on a sample of 333 HCPs who were selected using multistage stage random sampling technique. The sample includes medical officers, auxiliary nurses and midwives, and pharmacists and laboratory technicians/assistants among regular and contractual staff. Data were collected using the pretested structured questionnaire for organization commitment (OC), job satisfiers, and intrinsic job motivation. Analysis was done by using SPSS version 18 and appropriate statistical tests were applied. The mean score for OC for entire regular staff is 1.6 ± 0.39 and contractual staff is 1.3 ± 0.45 which has statistically significant difference (t = 5.57; P = 0.00). In both regular and contractual staff, none of them show high emotional attachment with the organization and does not feel part of the family in the organization. Contractual staff does not feel proud to work in a present organization for rest of their career. Intrinsic motivation is high in both regular and contractual groups but intergroup difference is significant (t = 2.38; P Organizational commitment and intrinsic motivation of contractual staff are lesser than the permanent staff. Appropriate changes are required in the predictors of organizational commitment and factors responsible for satisfaction in the organization to keep the contractual human resource motivated and committed to the organization.

Strictly-regular number system and data structures

DEFF Research Database (Denmark)

Elmasry, Amr Ahmed Abd Elmoneim; Jensen, Claus; Katajainen, Jyrki

2010-01-01

We introduce a new number system that we call the strictly-regular system, which efficiently supports the operations: digit-increment, digit-decrement, cut, concatenate, and add. Compared to other number systems, the strictly-regular system has distinguishable properties. It is superior to the re...

Analysis of regularized Navier-Stokes equations, 2

Science.gov (United States)

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.

Effects of attitude, social influence, and self-efficacy model factors on regular mammography performance in life-transition aged women in Korea.

Science.gov (United States)

Lee, Chang Hyun; Kim, Young Im

2015-01-01

This study analyzed predictors of regular mammography performance in Korea. In addition, we determined factors affecting regular mammography performance in life-transition aged women by applying an attitude, social influence, and self-efficacy (ASE) model. Data were collected from women aged over 40 years residing in province J in Korea. The 178 enrolled subjects provided informed voluntary consent prior to completing a structural questionnaire. The overall regular mammography performance rate of the subjects was 41.6%. Older age, city residency, high income and part-time job were associated with a high regular mammography performance. Among women who had undergone more breast self-examinations (BSE) or more doctors' physical examinations (PE), there were higher regular mammography performance rates. All three ASE model factors were significantly associated with regular mammography performance. Women with a high level of positive ASE values had a significantly high regular mammography performance rate. Within the ASE model, self-efficacy and social influence were particularly important. Logistic regression analysis explained 34.7% of regular mammography performance and PE experience (β=4.645, p=.003), part- time job (β=4.010, p=.050), self-efficacy (β=1.820, p=.026) and social influence (β=1.509, p=.038) were significant factors. Promotional strategies that could improve self-efficacy, reinforce social influence and reduce geographical, time and financial barriers are needed to increase the regular mammography performance rate in life-transition aged.

Regularities, Natural Patterns and Laws of Nature

Directory of Open Access Journals (Sweden)

Stathis Psillos

2014-02-01

Full Text Available  The goal of this paper is to sketch an empiricist metaphysics of laws of nature. The key idea is that there are regularities without regularity-enforcers. Differently put, there are natural laws without law-makers of a distinct metaphysical kind. This sketch will rely on the concept of a natural pattern and more significantly on the existence of a network of natural patterns in nature. The relation between a regularity and a pattern will be analysed in terms of mereology.  Here is the road map. In section 2, I will briefly discuss the relation between empiricism and metaphysics, aiming to show that an empiricist metaphysics is possible. In section 3, I will offer arguments against stronger metaphysical views of laws. Then, in section 4 I will motivate nomic objectivism. In section 5, I will address the question ‘what is a regularity?’ and will develop a novel answer to it, based on the notion of a natural pattern. In section 6, I will raise the question: ‘what is a law of nature?’, the answer to which will be: a law of nature is a regularity that is characterised by the unity of a natural pattern.

Consistent Partial Least Squares Path Modeling via Regularization.

Science.gov (United States)

Jung, Sunho; Park, JaeHong

2018-01-01

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

Consistent Partial Least Squares Path Modeling via Regularization

Directory of Open Access Journals (Sweden)

Sunho Jung

2018-02-01

Full Text Available Partial least squares (PLS path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc, designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

Regularization of the Boundary-Saddle-Node Bifurcation

Directory of Open Access Journals (Sweden)

Xia Liu

2018-01-01

Full Text Available In this paper we treat a particular class of planar Filippov systems which consist of two smooth systems that are separated by a discontinuity boundary. In such systems one vector field undergoes a saddle-node bifurcation while the other vector field is transversal to the boundary. The boundary-saddle-node (BSN bifurcation occurs at a critical value when the saddle-node point is located on the discontinuity boundary. We derive a local topological normal form for the BSN bifurcation and study its local dynamics by applying the classical Filippov’s convex method and a novel regularization approach. In fact, by the regularization approach a given Filippov system is approximated by a piecewise-smooth continuous system. Moreover, the regularization process produces a singular perturbation problem where the original discontinuous set becomes a center manifold. Thus, the regularization enables us to make use of the established theories for continuous systems and slow-fast systems to study the local behavior around the BSN bifurcation.

Low-Complexity Regularization Algorithms for Image Deblurring

KAUST Repository

Alanazi, Abdulrahman

2016-11-01

Image restoration problems deal with images in which information has been degraded by blur or noise. In practice, the blur is usually caused by atmospheric turbulence, motion, camera shake, and several other mechanical or physical processes. In this study, we present two regularization algorithms for the image deblurring problem. We first present a new method based on solving a regularized least-squares (RLS) problem. This method is proposed to find a near-optimal value of the regularization parameter in the RLS problems. Experimental results on the non-blind image deblurring problem are presented. In all experiments, comparisons are made with three benchmark methods. The results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and structural similarity, as well as the visual quality of the deblurred images. To reduce the complexity of the proposed algorithm, we propose a technique based on the bootstrap method to estimate the regularization parameter in low and high-resolution images. Numerical results show that the proposed technique can effectively reduce the computational complexity of the proposed algorithms. In addition, for some cases where the point spread function (PSF) is separable, we propose using a Kronecker product so as to reduce the computations. Furthermore, in the case where the image is smooth, it is always desirable to replace the regularization term in the RLS problems by a total variation term. Therefore, we propose a novel method for adaptively selecting the regularization parameter in a so-called square root regularized total variation (SRTV). Experimental results demonstrate that our proposed method outperforms the other benchmark methods when applied to smooth images in terms of PSNR, SSIM and the restored image quality. In this thesis, we focus on the non-blind image deblurring problem, where the blur kernel is assumed to be known. However, we developed algorithms that also work

Improvements in GRACE Gravity Fields Using Regularization

Science.gov (United States)

Save, H.; Bettadpur, S.; Tapley, B. D.

2008-12-01

The unconstrained global gravity field models derived from GRACE are susceptible to systematic errors that show up as broad "stripes" aligned in a North-South direction on the global maps of mass flux. These errors are believed to be a consequence of both systematic and random errors in the data that are amplified by the nature of the gravity field inverse problem. These errors impede scientific exploitation of the GRACE data products, and limit the realizable spatial resolution of the GRACE global gravity fields in certain regions. We use regularization techniques to reduce these "stripe" errors in the gravity field products. The regularization criteria are designed such that there is no attenuation of the signal and that the solutions fit the observations as well as an unconstrained solution. We have used a computationally inexpensive method, normally referred to as "L-ribbon", to find the regularization parameter. This paper discusses the characteristics and statistics of a 5-year time-series of regularized gravity field solutions. The solutions show markedly reduced stripes, are of uniformly good quality over time, and leave little or no systematic observation residuals, which is a frequent consequence of signal suppression from regularization. Up to degree 14, the signal in regularized solution shows correlation greater than 0.8 with the un-regularized CSR Release-04 solutions. Signals from large-amplitude and small-spatial extent events - such as the Great Sumatra Andaman Earthquake of 2004 - are visible in the global solutions without using special post-facto error reduction techniques employed previously in the literature. Hydrological signals as small as 5 cm water-layer equivalent in the small river basins, like Indus and Nile for example, are clearly evident, in contrast to noisy estimates from RL04. The residual variability over the oceans relative to a seasonal fit is small except at higher latitudes, and is evident without the need for de-striping or

Prevalence of and factors associated with regular khat chewing among university students in Ethiopia

Directory of Open Access Journals (Sweden)

Astatkie A

2015-02-01

Full Text Available Ayalew Astatkie,1 Meaza Demissie,2 Yemane Berhane,2 Alemayehu Worku2,3 1School of Public and Environmental Health, College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia; 2Addis Continental Institute of Public Health, Addis Ababa, Ethiopia; 3School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia Purpose: Khat (Catha edulis is commonly chewed for its psychostimulant and euphorigenic effects in Africa and the Arabian Peninsula. Students use it to help them study for long hours especially during the period of examination. However, how regularly khat is chewed among university students and its associated factors are not well documented. In this article we report on the prevalence of and factors associated with regular khat chewing among university students in Ethiopia. Methods: We did a cross-sectional study from May 20, 2014 to June 23, 2014 on a sample of 1,255 regular students recruited from all campuses of Hawassa University, southern Ethiopia. The data were collected using self-administered questionnaires. We analyzed the data to identify factors associated with current regular khat chewing using complex sample adjusted logistic regression analysis. Results: The prevalence of current regular khat chewing was 10.5% (95% confidence interval [CI]: 6.1%–14.9%. After controlling for sex, religion, year of study, having a father who chews khat, cigarette smoking and alcohol drinking in the adjusted logistic regression model, living off-campus in rented houses as compared to living in the university dormitory (adjusted odds ratio [95% CI] =8.09 [1.56–42.01], and having friends who chew khat (adjusted odds ratio [95% CI] =4.62 [1.98–10.74] were found to significantly increase the odds of current regular khat use. Conclusion: Students living outside the university campus in rented houses compared to those living in dormitory and those with khat chewing peers are more likely to use

Deterministic automata for extended regular expressions

Directory of Open Access Journals (Sweden)

Syzdykov Mirzakhmet

2017-12-01

Full Text Available In this work we present the algorithms to produce deterministic finite automaton (DFA for extended operators in regular expressions like intersection, subtraction and complement. The method like “overriding” of the source NFA(NFA not defined with subset construction rules is used. The past work described only the algorithm for AND-operator (or intersection of regular languages; in this paper the construction for the MINUS-operator (and complement is shown.

Regularities of intermediate adsorption complex relaxation

International Nuclear Information System (INIS)

Manukova, L.A.

1982-01-01

The experimental data, characterizing the regularities of intermediate adsorption complex relaxation in the polycrystalline Mo-N 2 system at 77 K are given. The method of molecular beam has been used in the investigation. The analytical expressions of change regularity in the relaxation process of full and specific rates - of transition from intermediate state into ''non-reversible'', of desorption into the gas phase and accumUlation of the particles in the intermediate state are obtained

Sparse structure regularized ranking

KAUST Repository

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

2014-01-01

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

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan

2014-04-17

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

20 CFR 226.35 - Deductions from regular annuity rate.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Deductions from regular annuity rate. 226.35... COMPUTING EMPLOYEE, SPOUSE, AND DIVORCED SPOUSE ANNUITIES Computing a Spouse or Divorced Spouse Annuity § 226.35 Deductions from regular annuity rate. The regular annuity rate of the spouse and divorced...

77 FR 5779 - Proposed Collection; Comment Request

Science.gov (United States)

2012-02-06

...; Comment Request AGENCY: Defense Logistics Agency, DLA Small Business Programs, DoD. ACTION: Notice... Small Business Programs via email to [email protected] , or by regular mail to the Defense Logistics Agency... Logistics Agency announces the proposed extension of a public information collection and seeks public...

Regularization theory for ill-posed problems selected topics

CERN Document Server

Lu, Shuai

2013-01-01

Thismonograph is a valuable contribution to thehighly topical and extremly productive field ofregularisationmethods for inverse and ill-posed problems. The author is an internationally outstanding and acceptedmathematicianin this field. In his book he offers a well-balanced mixtureof basic and innovative aspects.He demonstrates new,differentiatedviewpoints, and important examples for applications. The bookdemontrates thecurrent developments inthe field of regularization theory,such as multiparameter regularization and regularization in learning theory. The book is written for graduate and PhDs

20 CFR 226.34 - Divorced spouse regular annuity rate.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Divorced spouse regular annuity rate. 226.34... COMPUTING EMPLOYEE, SPOUSE, AND DIVORCED SPOUSE ANNUITIES Computing a Spouse or Divorced Spouse Annuity § 226.34 Divorced spouse regular annuity rate. The regular annuity rate of a divorced spouse is equal to...

Chimeric mitochondrial peptides from contiguous regular and swinger RNA.

Science.gov (United States)

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.

Fast and compact regular expression matching

DEFF Research Database (Denmark)

Bille, Philip; Farach-Colton, Martin

2008-01-01

We study 4 problems in string matching, namely, regular expression matching, approximate regular expression matching, string edit distance, and subsequence indexing, on a standard word RAM model of computation that allows logarithmic-sized words to be manipulated in constant time. We show how...... to improve the space and/or remove a dependency on the alphabet size for each problem using either an improved tabulation technique of an existing algorithm or by combining known algorithms in a new way....

Dimensional regularization and analytical continuation at finite temperature

International Nuclear Information System (INIS)

Chen Xiangjun; Liu Lianshou

1998-01-01

The relationship between dimensional regularization and analytical continuation of infrared divergent integrals at finite temperature is discussed and a method of regularization of infrared divergent integrals and infrared divergent sums is given

75 FR 26706 - Information Collection; Direct Loan Making

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2010-05-12

... DEPARTMENT OF AGRICULTURE Farm Service Agency Information Collection; Direct Loan Making AGENCY... that supports Direct Loan Making programs. The information is used to determine borrower compliance with loan agreements, assist the borrower in achieving business goals, and regular servicing of the...

Position difference regularity of corresponding R-wave peaks for maternal ECG components from different abdominal points

International Nuclear Information System (INIS)

Zhang Jie-Min; Liu Hong-Xing; Huang Xiao-Lin; Si Jun-Feng; Guan Qun; Tang Li-Ming; Liu Tie-Bing

2014-01-01

We collected 343 groups of abdominal electrocardiogram (ECG) data from 78 pregnant women and deleted the channels unable for experts to determine R-wave peaks from them; then, based on these filtered data, the statistics of position difference of corresponding R-wave peaks for different maternal ECG components from different points were studied. The resultant statistics showed the regularity that the position difference of corresponding maternal R-wave peaks between different abdominal points does not exceed the range of 30 ms. The regularity was also proved using the fECG data from MIT—BIH PhysioBank. Additionally, the paper applied the obtained regularity, the range of position differences of the corresponding maternal R-wave peaks, to accomplish the automatic detection of maternal R-wave peaks in the recorded all initial 343 groups of abdominal signals, including the ones with the largest fetal ECG components, and all 55 groups of ECG data from MIT—BIH PhysioBank, achieving the successful separation of the maternal ECGs. (interdisciplinary physics and related areas of science and technology)

Adapting the curriculum of a student in the regular classroom

Directory of Open Access Journals (Sweden)

Cindy Lorena Rodríguez

2015-02-01

Full Text Available This article is based on a research, adapting the curriculum of a student in the regular classroom, based on a multi-skilled inclusive education whose data was collected between 2010 and 2011 from Colegio Real de los Andes. The study was based on the author’s personal experience with student population inside their regular classroom activities. The author was motivated by the desire to know how one could contribute to society’s expectations on an inclusive and integrated education that takes into account the human being as a unique being endowed with different potentials, great expectations, and dreams that nurture him or her into a major player in his or her dignified project of life that will, in turn, contribute towards their full personality growth and hence strengthen their academic skills. Similarly, this will be of great value towards commitment and devotion for inclusion, construed as a paramount import to educational formation. Hence, the dedication of educators in this inclusivity is a fundamental feature not only from the conceptual point of view, but more importantly, as a fundamental element in the essence of an educator, which must be, a human being formed in the richness of values openly projected on a pedagogy without any prejudice and preconceptions during a pedagogical dispensation.

Regular and conformal regular cores for static and rotating solutions

Energy Technology Data Exchange (ETDEWEB)

Azreg-Aïnou, Mustapha

2014-03-07

Using a new metric for generating rotating solutions, we derive in a general fashion the solution of an imperfect fluid and that of its conformal homolog. We discuss the conditions that the stress–energy tensors and invariant scalars be regular. On classical physical grounds, it is stressed that conformal fluids used as cores for static or rotating solutions are exempt from any malicious behavior in that they are finite and defined everywhere.

Regular and conformal regular cores for static and rotating solutions

International Nuclear Information System (INIS)

Azreg-Aïnou, Mustapha

2014-01-01

Using a new metric for generating rotating solutions, we derive in a general fashion the solution of an imperfect fluid and that of its conformal homolog. We discuss the conditions that the stress–energy tensors and invariant scalars be regular. On classical physical grounds, it is stressed that conformal fluids used as cores for static or rotating solutions are exempt from any malicious behavior in that they are finite and defined everywhere.

Low-rank matrix approximation with manifold regularization.

Science.gov (United States)

Zhang, Zhenyue; Zhao, Keke

2013-07-01

This paper proposes a new model of low-rank matrix factorization that incorporates manifold regularization to the matrix factorization. Superior to the graph-regularized nonnegative matrix factorization, this new regularization model has globally optimal and closed-form solutions. A direct algorithm (for data with small number of points) and an alternate iterative algorithm with inexact inner iteration (for large scale data) are proposed to solve the new model. A convergence analysis establishes the global convergence of the iterative algorithm. The efficiency and precision of the algorithm are demonstrated numerically through applications to six real-world datasets on clustering and classification. Performance comparison with existing algorithms shows the effectiveness of the proposed method for low-rank factorization in general.

Regularity criteria for incompressible magnetohydrodynamics equations in three dimensions

International Nuclear Information System (INIS)

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. (paper)

Regular-fat dairy and human health

DEFF Research Database (Denmark)

Astrup, Arne; Bradley, Beth H Rice; Brenna, J Thomas

2016-01-01

In recent history, some dietary recommendations have treated dairy fat as an unnecessary source of calories and saturated fat in the human diet. These assumptions, however, have recently been brought into question by current research on regular fat dairy products and human health. In an effort to......, cheese and yogurt, can be important components of an overall healthy dietary pattern. Systematic examination of the effects of dietary patterns that include regular-fat milk, cheese and yogurt on human health is warranted....

Bounded Perturbation Regularization for Linear Least Squares Estimation

KAUST Repository

Ballal, Tarig; Suliman, Mohamed Abdalla Elhag; Al-Naffouri, Tareq Y.

2017-01-01

This paper addresses the problem of selecting the regularization parameter for linear least-squares estimation. We propose a new technique called bounded perturbation regularization (BPR). In the proposed BPR method, a perturbation with a bounded

Recognition Memory for Novel Stimuli: The Structural Regularity Hypothesis

Science.gov (United States)

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.…

76 FR 47154 - Proposed Information Collection; Comment Request; California Signage Plan: Evaluation of...

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2011-08-04

... DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration Proposed Information Collection; Comment Request; California Signage Plan: Evaluation of Interpretive Signs AGENCY: National... This request is for a regular submission (new collection). The California Signage Plan is an organized...

Regularization Techniques for Linear Least-Squares Problems

KAUST Repository

Suliman, Mohamed

2016-04-01

Linear estimation is a fundamental branch of signal processing that deals with estimating the values of parameters from a corrupted measured data. Throughout the years, several optimization criteria have been used to achieve this task. The most astonishing attempt among theses is the linear least-squares. Although this criterion enjoyed a wide popularity in many areas due to its attractive properties, it appeared to suffer from some shortcomings. Alternative optimization criteria, as a result, have been proposed. These new criteria allowed, in one way or another, the incorporation of further prior information to the desired problem. Among theses alternative criteria is the regularized least-squares (RLS). In this thesis, we propose two new algorithms to find the regularization parameter for linear least-squares problems. In the constrained perturbation regularization algorithm (COPRA) for random matrices and COPRA for linear discrete ill-posed problems, an artificial perturbation matrix with a bounded norm is forced into the model matrix. This perturbation is introduced to enhance the singular value structure of the matrix. As a result, the new modified model is expected to provide a better stabilize substantial solution when used to estimate the original signal through minimizing the worst-case residual error function. Unlike many other regularization algorithms that go in search of minimizing the estimated data error, the two new proposed algorithms are developed mainly to select the artifcial perturbation bound and the regularization parameter in a way that approximately minimizes the mean-squared error (MSE) between the original signal and its estimate under various conditions. The first proposed COPRA method is developed mainly to estimate the regularization parameter when the measurement matrix is complex Gaussian, with centered unit variance (standard), and independent and identically distributed (i.i.d.) entries. Furthermore, the second proposed COPRA

Regularized Regression and Density Estimation based on Optimal Transport

KAUST Repository

Burger, M.

2012-03-11

The aim of this paper is to investigate a novel nonparametric approach for estimating and smoothing density functions as well as probability densities from discrete samples based on a variational regularization method with the Wasserstein metric as a data fidelity. The approach allows a unified treatment of discrete and continuous probability measures and is hence attractive for various tasks. In particular, the variational model for special regularization functionals yields a natural method for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations and provide a detailed analysis. Moreover, we compute special self-similar solutions for standard regularization functionals and we discuss several computational approaches and results. © 2012 The Author(s).

Energy functions for regularization algorithms

Science.gov (United States)

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.

Three regularities of recognition memory: the role of bias.

Science.gov (United States)

Hilford, Andrew; Maloney, Laurence T; Glanzer, Murray; Kim, Kisok

2015-12-01

A basic assumption of Signal Detection Theory is that decisions are made on the basis of likelihood ratios. In a preceding paper, Glanzer, Hilford, and Maloney (Psychonomic Bulletin & Review, 16, 431-455, 2009) showed that the likelihood ratio assumption implies that three regularities will occur in recognition memory: (1) the Mirror Effect, (2) the Variance Effect, (3) the normalized Receiver Operating Characteristic (z-ROC) Length Effect. The paper offered formal proofs and computational demonstrations that decisions based on likelihood ratios produce the three regularities. A survey of data based on group ROCs from 36 studies validated the likelihood ratio assumption by showing that its three implied regularities are ubiquitous. The study noted, however, that bias, another basic factor in Signal Detection Theory, can obscure the Mirror Effect. In this paper we examine how bias affects the regularities at the theoretical level. The theoretical analysis shows: (1) how bias obscures the Mirror Effect, not the other two regularities, and (2) four ways to counter that obscuring. We then report the results of five experiments that support the theoretical analysis. The analyses and the experimental results also demonstrate: (1) that the three regularities govern individual, as well as group, performance, (2) alternative explanations of the regularities are ruled out, and (3) that Signal Detection Theory, correctly applied, gives a simple and unified explanation of recognition memory data.

Method of transferring regular shaped vessel into cell

International Nuclear Information System (INIS)

Murai, Tsunehiko.

1997-01-01

The present invention concerns a method of transferring regular shaped vessels from a non-contaminated area to a contaminated cell. A passage hole for allowing the regular shaped vessels to pass in the longitudinal direction is formed to a partitioning wall at the bottom of the contaminated cell. A plurality of regular shaped vessel are stacked in multiple stages in a vertical direction from the non-contaminated area present below the passage hole, allowed to pass while being urged and transferred successively into the contaminated cell. As a result, since they are transferred while substantially closing the passage hole by the regular shaped vessels, radiation rays or contaminated materials are prevented from discharging from the contaminated cell to the non-contaminated area. Since there is no requirement to open/close an isolation door frequently, the workability upon transfer can be improved remarkably. In addition, the sealing member for sealing the gap between the regular shaped vessel passing through the passage hole and the partitioning wall of the bottom is disposed to the passage hole, the contaminated materials in the contaminated cells can be prevented from discharging from the gap to the non-contaminated area. (N.H.)

Automatic Constraint Detection for 2D Layout Regularization.

Science.gov (United States)

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.

Automatic Constraint Detection for 2D Layout Regularization

KAUST Repository

Jiang, Haiyong

2015-09-18

In this paper, we address the problem of constraint detection for layout regularization. As layout we consider a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important for digitizing plans or images, such as floor plans and facade images, and for 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 the layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm to automatically detect constraints. In our results, we evaluate the proposed framework on a variety of input layouts from different applications, which demonstrates our method has superior performance to the state of the art.

Lavrentiev regularization method for nonlinear ill-posed problems

International Nuclear Information System (INIS)

Kinh, Nguyen Van

2002-10-01

In this paper we shall be concerned with Lavientiev regularization method to reconstruct solutions x 0 of non ill-posed problems F(x)=y o , where instead of y 0 noisy data y δ is an element of X with absolut(y δ -y 0 ) ≤ δ are given and F:X→X is an accretive nonlinear operator from a real reflexive Banach space X into itself. In this regularization method solutions x α δ are obtained by solving the singularly perturbed nonlinear operator equation F(x)+α(x-x*)=y δ with some initial guess x*. Assuming certain conditions concerning the operator F and the smoothness of the element x*-x 0 we derive stability estimates which show that the accuracy of the regularized solutions is order optimal provided that the regularization parameter α has been chosen properly. (author)

Online Manifold Regularization by Dual Ascending Procedure

Directory of Open Access Journals (Sweden)

Boliang Sun

2013-01-01

Full Text Available We propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offline to online in this paper. Our algorithms are derived by gradient ascent in the dual function. For practical purpose, we propose two buffering strategies and two sparse approximations to reduce the computational complexity. Detailed experiments verify the utility of our approaches. An important conclusion is that our online MR algorithms can handle the settings where the target hypothesis is not fixed but drifts with the sequence of examples. We also recap and draw connections to earlier works. This paper paves a way to the design and analysis of online manifold regularization algorithms.

Statistical analysis in MSW collection performance assessment.

Science.gov (United States)

Teixeira, Carlos Afonso; Avelino, Catarina; Ferreira, Fátima; Bentes, Isabel

2014-09-01

The increase of Municipal Solid Waste (MSW) generated over the last years forces waste managers pursuing more effective collection schemes, technically viable, environmentally effective and economically sustainable. The assessment of MSW services using performance indicators plays a crucial role for improving service quality. In this work, we focus on the relevance of regular system monitoring as a service assessment tool. In particular, we select and test a core-set of MSW collection performance indicators (effective collection distance, effective collection time and effective fuel consumption) that highlights collection system strengths and weaknesses and supports pro-active management decision-making and strategic planning. A statistical analysis was conducted with data collected in mixed collection system of Oporto Municipality, Portugal, during one year, a week per month. This analysis provides collection circuits' operational assessment and supports effective short-term municipality collection strategies at the level of, e.g., collection frequency and timetables, and type of containers. Copyright © 2014 Elsevier Ltd. All rights reserved.

Regular graph construction for semi-supervised learning

International Nuclear Information System (INIS)

Vega-Oliveros, Didier A; Berton, Lilian; Eberle, Andre Mantini; Lopes, Alneu de Andrade; Zhao, Liang

2014-01-01

Semi-supervised learning (SSL) stands out for using a small amount of labeled points for data clustering and classification. In this scenario graph-based methods allow the analysis of local and global characteristics of the available data by identifying classes or groups regardless data distribution and representing submanifold in Euclidean space. Most of methods used in literature for SSL classification do not worry about graph construction. However, regular graphs can obtain better classification accuracy compared to traditional methods such as k-nearest neighbor (kNN), since kNN benefits the generation of hubs and it is not appropriate for high-dimensionality data. Nevertheless, methods commonly used for generating regular graphs have high computational cost. We tackle this problem introducing an alternative method for generation of regular graphs with better runtime performance compared to methods usually find in the area. Our technique is based on the preferential selection of vertices according some topological measures, like closeness, generating at the end of the process a regular graph. Experiments using the global and local consistency method for label propagation show that our method provides better or equal classification rate in comparison with kNN

Physical model of dimensional regularization

Energy Technology Data Exchange (ETDEWEB)

Schonfeld, Jonathan F.

2016-12-15

We explicitly construct fractals of dimension 4-ε 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. (orig.)

Information-theoretic semi-supervised metric learning via entropy regularization.

Science.gov (United States)

Niu, Gang; Dai, Bo; Yamada, Makoto; Sugiyama, Masashi

2014-08-01

We propose a general information-theoretic approach to semi-supervised metric learning called SERAPH (SEmi-supervised metRic leArning Paradigm with Hypersparsity) that does not rely on the manifold assumption. Given the probability parameterized by a Mahalanobis distance, we maximize its entropy on labeled data and minimize its entropy on unlabeled data following entropy regularization. For metric learning, entropy regularization improves manifold regularization by considering the dissimilarity information of unlabeled data in the unsupervised part, and hence it allows the supervised and unsupervised parts to be integrated in a natural and meaningful way. Moreover, we regularize SERAPH by trace-norm regularization to encourage low-dimensional projections associated with the distance metric. The nonconvex optimization problem of SERAPH could be solved efficiently and stably by either a gradient projection algorithm or an EM-like iterative algorithm whose M-step is convex. Experiments demonstrate that SERAPH compares favorably with many well-known metric learning methods, and the learned Mahalanobis distance possesses high discriminability even under noisy environments.

Fluctuations of quantum fields via zeta function regularization

International Nuclear Information System (INIS)

Cognola, Guido; Zerbini, Sergio; Elizalde, Emilio

2002-01-01

Explicit expressions for the expectation values and the variances of some observables, which are bilinear quantities in the quantum fields on a D-dimensional manifold, are derived making use of zeta function regularization. It is found that the variance, related to the second functional variation of the effective action, requires a further regularization and that the relative regularized variance turns out to be 2/N, where N is the number of the fields, thus being independent of the dimension D. Some illustrating examples are worked through. The issue of the stress tensor is also briefly addressed

X-ray computed tomography using curvelet sparse regularization.

Science.gov (United States)

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

2015-04-01

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

Semisupervised Support Vector Machines With Tangent Space Intrinsic Manifold Regularization.

Science.gov (United States)

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.

Regularity and chaos in cavity QED

International Nuclear Information System (INIS)

Bastarrachea-Magnani, Miguel Angel; López-del-Carpio, Baldemar; Chávez-Carlos, Jorge; Lerma-Hernández, Sergio; Hirsch, Jorge G

2017-01-01

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. (paper)

Cognitive Aspects of Regularity Exhibit When Neighborhood Disappears

Science.gov (United States)

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…

An adaptive regularization parameter choice strategy for multispectral bioluminescence tomography

Energy Technology Data Exchange (ETDEWEB)

Feng Jinchao; Qin Chenghu; Jia Kebin; Han Dong; Liu Kai; Zhu Shouping; Yang Xin; Tian Jie [Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China); College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124 (China); Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China); Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China) and School of Life Sciences and Technology, Xidian University, Xi' an 710071 (China)

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

Exercise and food compensation: exploring diet-related beliefs and behaviors of regular exercisers.

Science.gov (United States)

Dohle, Simone; Wansink, Brian; Zehnder, Lorena

2015-03-01

The goal of this qualitative study is to identify common beliefs and behaviors related to exercise and diet. Data were collected in focus group discussions with regular exercisers who were physically active between 1 and 5 h per week. Exercise objectives, beliefs and behaviors regarding food intake before, during, and after exercise, consumption of sport supplements, and dietary patterns on sedentary days were explored. All focus groups were audio-taped and transcribed verbatim. Transcripts were analyzed using a grounded theory approach. Participants reported that they reward themselves for being active by consuming food. Other exercisers had specific beliefs about dietary needs and how to compensate for exercise-induced losses along with exercise-related food likes and dislikes. The participants' food intake also depended on their personal exercise objectives, such as the goal of performing well in competitions. External and physiological factors also played a role in determining participants' dietary patterns. Results of this study show that exercising and dietary patterns are closely intertwined. In addition, we articulate new hypotheses and outline a research agenda that can help improve how regular exercisers eat.

Matrix regularization of embedded 4-manifolds

International Nuclear Information System (INIS)

Trzetrzelewski, Maciej

2012-01-01

We consider products of two 2-manifolds such as S 2 ×S 2 , embedded in Euclidean space and show that the corresponding 4-volume preserving diffeomorphism algebra can be approximated by a tensor product SU(N)⊗SU(N) i.e. functions on a manifold are approximated by the Kronecker product of two SU(N) matrices. A regularization of the 4-sphere is also performed by constructing N 2 ×N 2 matrix representations of the 4-algebra (and as a byproduct of the 3-algebra which makes the regularization of S 3 also possible).

Optimal Tikhonov Regularization in Finite-Frequency Tomography

Science.gov (United States)

Fang, Y.; Yao, Z.; Zhou, Y.

2017-12-01

The last decade has witnessed a progressive transition in seismic tomography from ray theory to finite-frequency theory which overcomes the resolution limit of the high-frequency approximation in ray theory. In addition to approximations in wave propagation physics, a main difference between ray-theoretical tomography and finite-frequency tomography is the sparseness of the associated sensitivity matrix. It is well known that seismic tomographic problems are ill-posed and regularizations such as damping and smoothing are often applied to analyze the tradeoff between data misfit and model uncertainty. The regularizations depend on the structure of the matrix as well as noise level of the data. Cross-validation has been used to constrain data uncertainties in body-wave finite-frequency inversions when measurements at multiple frequencies are available to invert for a common structure. In this study, we explore an optimal Tikhonov regularization in surface-wave phase-velocity tomography based on minimization of an empirical Bayes risk function using theoretical training datasets. We exploit the structure of the sensitivity matrix in the framework of singular value decomposition (SVD) which also allows for the calculation of complete resolution matrix. We compare the optimal Tikhonov regularization in finite-frequency tomography with traditional tradeo-off analysis using surface wave dispersion measurements from global as well as regional studies.

Fractional Regularization Term for Variational Image Registration

Directory of Open Access Journals (Sweden)

Rafael Verdú-Monedero

2009-01-01

Full Text Available Image registration is a widely used task of image analysis with applications in many fields. Its classical formulation and current improvements are given in the spatial domain. In this paper a regularization term based on fractional order derivatives is formulated. This term is defined and implemented in the frequency domain by translating the energy functional into the frequency domain and obtaining the Euler-Lagrange equations which minimize it. The new regularization term leads to a simple formulation and design, being applicable to higher dimensions by using the corresponding multidimensional Fourier transform. The proposed regularization term allows for a real gradual transition from a diffusion registration to a curvature registration which is best suited to some applications and it is not possible in the spatial domain. Results with 3D actual images show the validity of this approach.

Reducing errors in the GRACE gravity solutions using regularization

Science.gov (United States)

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

Likelihood ratio decisions in memory: three implied regularities.

Science.gov (United States)

Glanzer, Murray; Hilford, Andrew; Maloney, Laurence T

2009-06-01

We analyze four general signal detection models for recognition memory that differ in their distributional assumptions. Our analyses show that a basic assumption of signal detection theory, the likelihood ratio decision axis, implies three regularities in recognition memory: (1) the mirror effect, (2) the variance effect, and (3) the z-ROC length effect. For each model, we present the equations that produce the three regularities and show, in computed examples, how they do so. We then show that the regularities appear in data from a range of recognition studies. The analyses and data in our study support the following generalization: Individuals make efficient recognition decisions on the basis of likelihood ratios.

Low-Rank Matrix Factorization With Adaptive Graph Regularizer.

Science.gov (United States)

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.

Online Manifold Regularization by Dual Ascending Procedure

OpenAIRE

Sun, Boliang; Li, Guohui; Jia, Li; Zhang, Hui

2013-01-01

We propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offline to online in this paper. Our algorithms are derived by gradient ascent in the dual function. For practical purpose, we propose two buffering strategies and two sparse approximations to reduce the computational complexity. Detailed experiments verify the utility of our approache...

Degree-regular triangulations of torus and Klein bottle

Indian Academy of Sciences (India)

Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 3 ... A triangulation of a connected closed surface is called degree-regular if each of its vertices have the same degree. ... In [5], Datta and Nilakantan have classified all the degree-regular triangulations of closed surfaces on at most 11 vertices.

The relationship between lifestyle regularity and subjective sleep quality

Science.gov (United States)

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 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.

Borderline personality disorder and regularly drinking alcohol before sex.

Science.gov (United States)

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

Generalized Bregman distances and convergence rates for non-convex regularization methods

International Nuclear Information System (INIS)

Grasmair, Markus

2010-01-01

We generalize the notion of Bregman distance using concepts from abstract convexity in order to derive convergence rates for Tikhonov regularization with non-convex regularization terms. In particular, we study the non-convex regularization of linear operator equations on Hilbert spaces, showing that the conditions required for the application of the convergence rates results are strongly related to the standard range conditions from the convex case. Moreover, we consider the setting of sparse regularization, where we show that a rate of order δ 1/p holds, if the regularization term has a slightly faster growth at zero than |t| p

Breast ultrasound tomography with total-variation regularization

Energy Technology Data Exchange (ETDEWEB)

Huang, Lianjie [Los Alamos National Laboratory; Li, Cuiping [KARMANOS CANCER INSTIT.; Duric, Neb [KARMANOS CANCER INSTIT

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.

Regularization and Complexity Control in Feed-forward Networks

OpenAIRE

Bishop, C. M.

1995-01-01

In this paper we consider four alternative approaches to complexity control in feed-forward networks based respectively on architecture selection, regularization, early stopping, and training with noise. We show that there are close similarities between these approaches and we argue that, for most practical applications, the technique of regularization should be the method of choice.

Manifold regularization for sparse unmixing of hyperspectral images.

Science.gov (United States)

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

2016-01-01

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

Regularization dependence on phase diagram in Nambu–Jona-Lasinio model

International Nuclear Information System (INIS)

Kohyama, H.; Kimura, D.; Inagaki, T.

2015-01-01

We study the regularization dependence on meson properties and the phase diagram of quark matter by using the two flavor Nambu–Jona-Lasinio model. The model also has the parameter dependence in each regularization, so we explicitly give the model parameters for some sets of the input observables, then investigate its effect on the phase diagram. We find that the location or the existence of the critical end point highly depends on the regularization methods and the model parameters. Then we think that regularization and parameters are carefully considered when one investigates the QCD critical end point in the effective model studies

Generalization Performance of Regularized Ranking With Multiscale Kernels.

Science.gov (United States)

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.

Top-down attention affects sequential regularity representation in the human visual system.

Science.gov (United States)

Kimura, Motohiro; Widmann, Andreas; Schröger, Erich

2010-08-01

Recent neuroscience studies using visual mismatch negativity (visual MMN), an event-related brain potential (ERP) index of memory-mismatch processes in the visual sensory system, have shown that although sequential regularities embedded in successive visual stimuli can be automatically represented in the visual sensory system, an existence of sequential regularity itself does not guarantee that the sequential regularity will be automatically represented. In the present study, we investigated the effects of top-down attention on sequential regularity representation in the visual sensory system. Our results showed that a sequential regularity (SSSSD) embedded in a modified oddball sequence where infrequent deviant (D) and frequent standard stimuli (S) differing in luminance were regularly presented (SSSSDSSSSDSSSSD...) was represented in the visual sensory system only when participants attended the sequential regularity in luminance, but not when participants ignored the stimuli or simply attended the dimension of luminance per se. This suggests that top-down attention affects sequential regularity representation in the visual sensory system and that top-down attention is a prerequisite for particular sequential regularities to be represented. Copyright 2010 Elsevier B.V. All rights reserved.

Regularized Discriminant Analysis: A Large Dimensional Study

KAUST Repository

Yang, Xiaoke

2018-04-28

In this thesis, we focus on studying the performance of general regularized discriminant analysis (RDA) classifiers. The data used for analysis is assumed to follow Gaussian mixture model with different means and covariances. RDA offers a rich class of regularization options, covering as special cases the regularized linear discriminant analysis (RLDA) and the regularized quadratic discriminant analysis (RQDA) classi ers. We analyze RDA under the double asymptotic regime where the data dimension and the training size both increase in a proportional way. This double asymptotic regime allows for application of fundamental results from random matrix theory. Under the double asymptotic regime and some mild assumptions, we show that the asymptotic classification error converges to a deterministic quantity that only depends on the data statistical parameters and dimensions. This result not only implicates some mathematical relations between the misclassification error and the class statistics, but also can be leveraged to select the optimal parameters that minimize the classification error, thus yielding the optimal classifier. Validation results on the synthetic data show a good accuracy of our theoretical findings. We also construct a general consistent estimator to approximate the true classification error in consideration of the unknown previous statistics. We benchmark the performance of our proposed consistent estimator against classical estimator on synthetic data. The observations demonstrate that the general estimator outperforms others in terms of mean squared error (MSE).

Adaptive Regularization of Neural Networks Using Conjugate Gradient

DEFF Research Database (Denmark)

Goutte, Cyril; Larsen, Jan

1998-01-01

Andersen et al. (1997) and Larsen et al. (1996, 1997) suggested a regularization scheme which iteratively adapts regularization parameters by minimizing validation error using simple gradient descent. In this contribution we present an improved algorithm based on the conjugate gradient technique........ Numerical experiments with feedforward neural networks successfully demonstrate improved generalization ability and lower computational cost...

20 CFR 226.33 - Spouse regular annuity rate.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Spouse regular annuity rate. 226.33 Section... COMPUTING EMPLOYEE, SPOUSE, AND DIVORCED SPOUSE ANNUITIES Computing a Spouse or Divorced Spouse Annuity § 226.33 Spouse regular annuity rate. The final tier I and tier II rates, from §§ 226.30 and 226.32, are...

Female non-regular workers in Japan: their current status and health.

Science.gov (United States)

Inoue, Mariko; Nishikitani, Mariko; Tsurugano, Shinobu

2016-12-07

The participation of women in the Japanese labor force is characterized by its M-shaped curve, which reflects decreased employment rates during child-rearing years. Although, this M-shaped curve is now improving, the majority of women in employment are likely to fall into the category of non-regular workers. Based on a review of the previous Japanese studies of the health of non-regular workers, we found that non-regular female workers experienced greater psychological distress, poorer self-rated health, a higher smoking rate, and less access to preventive medicine than regular workers did. However, despite the large number of non-regular workers, there are limited researches regarding their health. In contrast, several studies in Japan concluded that regular workers also had worse health conditions due to the additional responsibility and longer work hours associated with the job, housekeeping, and child rearing. The health of non-regular workers might be threatened by the effects of precarious employment status, lower income, a lower safety net, outdated social norm regarding non-regular workers, and difficulty in achieving a work-life balance. A sector wide social approach to consider life course aspect is needed to protect the health and well-being of female workers' health; promotion of an occupational health program alone is insufficient.

Female non-regular workers in Japan: their current status and health

Science.gov (United States)

INOUE, Mariko; NISHIKITANI, Mariko; TSURUGANO, Shinobu

2016-01-01

The participation of women in the Japanese labor force is characterized by its M-shaped curve, which reflects decreased employment rates during child-rearing years. Although, this M-shaped curve is now improving, the majority of women in employment are likely to fall into the category of non-regular workers. Based on a review of the previous Japanese studies of the health of non-regular workers, we found that non-regular female workers experienced greater psychological distress, poorer self-rated health, a higher smoking rate, and less access to preventive medicine than regular workers did. However, despite the large number of non-regular workers, there are limited researches regarding their health. In contrast, several studies in Japan concluded that regular workers also had worse health conditions due to the additional responsibility and longer work hours associated with the job, housekeeping, and child rearing. The health of non-regular workers might be threatened by the effects of precarious employment status, lower income, a lower safety net, outdated social norm regarding non-regular workers, and difficulty in achieving a work-life balance. A sector wide social approach to consider life course aspect is needed to protect the health and well-being of female workers’ health; promotion of an occupational health program alone is insufficient. PMID:27818453

PET regularization by envelope guided conjugate gradients

International Nuclear Information System (INIS)

Kaufman, L.; Neumaier, A.

1996-01-01

The authors propose a new way to iteratively solve large scale ill-posed problems and in particular the image reconstruction problem in positron emission tomography by exploiting the relation between Tikhonov regularization and multiobjective optimization to obtain iteratively approximations to the Tikhonov L-curve and its corner. Monitoring the change of the approximate L-curves allows us to adjust the regularization parameter adaptively during a preconditioned conjugate gradient iteration, so that the desired solution can be reconstructed with a small number of iterations

Regularized Regression and Density Estimation based on Optimal Transport

KAUST Repository

Burger, M.; Franek, M.; Schonlieb, C.-B.

2012-01-01

for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations

Regularization of Nonmonotone Variational Inequalities

International Nuclear Information System (INIS)

Konnov, Igor V.; Ali, M.S.S.; Mazurkevich, E.O.

2006-01-01

In this paper we extend the Tikhonov-Browder regularization scheme from monotone to rather a general class of nonmonotone multivalued variational inequalities. We show that their convergence conditions hold for some classes of perfectly and nonperfectly competitive economic equilibrium problems

Interval matrices: Regularity generates singularity

Czech Academy of Sciences Publication Activity Database

Rohn, Jiří; Shary, S.P.

2018-01-01

Roč. 540, 1 March (2018), s. 149-159 ISSN 0024-3795 Institutional support: RVO:67985807 Keywords : interval matrix * regularity * singularity * P-matrix * absolute value equation * diagonally singilarizable matrix Subject RIV: BA - General Mathematics Impact factor: 0.973, year: 2016

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

Science.gov (United States)

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Regular perturbations in a vector space with indefinite metric

International Nuclear Information System (INIS)

Chiang, C.C.

1975-08-01

The Klein space is discussed in connection with practical applications. Some lemmas are presented which are to be used for the discussion of regular self-adjoint operators. The criteria for the regularity of perturbed operators are given. (U.S.)

Regular Generalized Star Star closed sets in Bitopological Spaces

OpenAIRE

K. Kannan; D. Narasimhan; K. Chandrasekhara Rao; R. Ravikumar

2011-01-01

The aim of this paper is to introduce the concepts of τ1τ2-regular generalized star star closed sets , τ1τ2-regular generalized star star open sets and study their basic properties in bitopological spaces.

Travel time tomography with local image regularization by sparsity constrained dictionary learning

Science.gov (United States)

Bianco, M.; Gerstoft, P.

2017-12-01

We propose a regularization approach for 2D seismic travel time tomography which models small rectangular groups of slowness pixels, within an overall or `global' slowness image, as sparse linear combinations of atoms from a dictionary. The groups of slowness pixels are referred to as patches and a dictionary corresponds to a collection of functions or `atoms' describing the slowness in each patch. These functions could for example be wavelets.The patch regularization is incorporated into the global slowness image. The global image models the broad features, while the local patch images incorporate prior information from the dictionary. Further, high resolution slowness within patches is permitted if the travel times from the global estimates support it. The proposed approach is formulated as an algorithm, which is repeated until convergence is achieved: 1) From travel times, find the global slowness image with a minimum energy constraint on the pixel variance relative to a reference. 2) Find the patch level solutions to fit the global estimate as a sparse linear combination of dictionary atoms.3) Update the reference as the weighted average of the patch level solutions.This approach relies on the redundancy of the patches in the seismic image. Redundancy means that the patches are repetitions of a finite number of patterns, which are described by the dictionary atoms. Redundancy in the earth's structure was demonstrated in previous works in seismics where dictionaries of wavelet functions regularized inversion. We further exploit redundancy of the patches by using dictionary learning algorithms, a form of unsupervised machine learning, to estimate optimal dictionaries from the data in parallel with the inversion. We demonstrate our approach on densely, but irregularly sampled synthetic seismic images.

(2+1-dimensional regular black holes with nonlinear electrodynamics sources

Directory of Open Access Journals (Sweden)

Yun He

2017-11-01

Full Text Available On the basis of two requirements: the avoidance of the curvature singularity and the Maxwell theory as the weak field limit of the nonlinear electrodynamics, we find two restricted conditions on the metric function of (2+1-dimensional regular black hole in general relativity coupled with nonlinear electrodynamics sources. By the use of the two conditions, we obtain a general approach to construct (2+1-dimensional regular black holes. In this manner, we construct four (2+1-dimensional regular black holes as examples. We also study the thermodynamic properties of the regular black holes and verify the first law of black hole thermodynamics.

The reliability of team-based primary data collectors for the collection of exposure and protective equipment use data in community sport

OpenAIRE

Braham, R; Finch, C

2004-01-01

Methods: Nine clubs (23 teams) from a metropolitan Australian Football league in Victoria each provided one primary data collector to monitor exposure and protective equipment use over a regular playing season. Four random audits of this data collection for each team were conducted throughout the regular playing season. The audits were compared with data collected by the club data collectors and the level of agreement assessed.

Regularity of the Maxwell equations in heterogeneous media and Lipschitz domains

KAUST Repository

Bonito, Andrea

2013-12-01

This note establishes regularity estimates for the solution of the Maxwell equations in Lipschitz domains with non-smooth coefficients and minimal regularity assumptions. The argumentation relies on elliptic regularity estimates for the Poisson problem with non-smooth coefficients. © 2013 Elsevier Ltd.

Forcing absoluteness and regularity properties

NARCIS (Netherlands)

Ikegami, D.

2010-01-01

For a large natural class of forcing notions, we prove general equivalence theorems between forcing absoluteness statements, regularity properties, and transcendence properties over L and the core model K. We use our results to answer open questions from set theory of the reals.

Arithmetic properties of $\\ell$-regular overpartition pairs

OpenAIRE

NAIKA, MEGADAHALLI SIDDA MAHADEVA; SHIVASHANKAR, CHANDRAPPA

2017-01-01

In this paper, we investigate the arithmetic properties of $\\ell$-regular overpartition pairs. Let $\\overline{B}_{\\ell}(n)$ denote the number of $\\ell$-regular overpartition pairs of $n$. We will prove the number of Ramanujan-like congruences and infinite families of congruences modulo 3, 8, 16, 36, 48, 96 for $\\overline{B}_3(n)$ and modulo 3, 16, 64, 96 for $\\overline{B}_4(n)$. For example, we find that for all nonnegative integers $\\alpha$ and $n$, $\\overline{B}_{3}(3^{\\alpha}(3n+2))\\equiv ...

Chaos regularization of quantum tunneling rates

International Nuclear Information System (INIS)

Pecora, Louis M.; Wu Dongho; Lee, Hoshik; Antonsen, Thomas; Lee, Ming-Jer; Ott, Edward

2011-01-01

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.

Regularization Tools Version 3.0 for Matlab 5.2

DEFF Research Database (Denmark)

Hansen, Per Christian

1999-01-01

This communication describes Version 3.0 of Regularization Tools, a Matlab package for analysis and solution of discrete ill-posed problems.......This communication describes Version 3.0 of Regularization Tools, a Matlab package for analysis and solution of discrete ill-posed problems....

Spiking Regularity and Coherence in Complex Hodgkin–Huxley Neuron Networks

International Nuclear Information System (INIS)

Zhi-Qiang, Sun; Ping, Xie; Wei, Li; Peng-Ye, Wang

2010-01-01

We study the effects of the strength of coupling between neurons on the spiking regularity and coherence in a complex network with randomly connected Hodgkin–Huxley neurons driven by colored noise. It is found that for the given topology realization and colored noise correlation time, there exists an optimal strength of coupling, at which the spiking regularity of the network reaches the best level. Moreover, when the temporal regularity reaches the best level, the spatial coherence of the system has already increased to a relatively high level. In addition, for the given number of neurons and noise correlation time, the values of average regularity and spatial coherence at the optimal strength of coupling are nearly independent of the topology realization. Furthermore, there exists an optimal value of colored noise correlation time at which the spiking regularity can reach its best level. These results may be helpful for understanding of the real neuron world. (cross-disciplinary physics and related areas of science and technology)

Automated Assume-Guarantee Reasoning for Omega-Regular Systems and Specifications

Science.gov (United States)

Chaki, Sagar; Gurfinkel, Arie

2010-01-01

We develop a learning-based automated Assume-Guarantee (AG) reasoning framework for verifying omega-regular properties of concurrent systems. We study the applicability of non-circular (AGNC) and circular (AG-C) AG proof rules in the context of systems with infinite behaviors. In particular, we show that AG-NC is incomplete when assumptions are restricted to strictly infinite behaviors, while AG-C remains complete. We present a general formalization, called LAG, of the learning based automated AG paradigm. We show how existing approaches for automated AG reasoning are special instances of LAG.We develop two learning algorithms for a class of systems, called infinite regular systems, that combine finite and infinite behaviors. We show that for infinity-regular systems, both AG-NC and AG-C are sound and complete. Finally, we show how to instantiate LAG to do automated AG reasoning for infinite regular, and omega-regular, systems using both AG-NC and AG-C as proof rules

The Analysis of Two-Way Functional Data Using Two-Way Regularized Singular Value Decompositions

KAUST Repository

Huang, Jianhua Z.

2009-12-01

Two-way functional data consist of a data matrix whose row and column domains are both structured, for example, temporally or spatially, as when the data are time series collected at different locations in space. We extend one-way functional principal component analysis (PCA) to two-way functional data by introducing regularization of both left and right singular vectors in the singular value decomposition (SVD) of the data matrix. We focus on a penalization approach and solve the nontrivial problem of constructing proper two-way penalties from oneway regression penalties. We introduce conditional cross-validated smoothing parameter selection whereby left-singular vectors are cross- validated conditional on right-singular vectors, and vice versa. The concept can be realized as part of an alternating optimization algorithm. In addition to the penalization approach, we briefly consider two-way regularization with basis expansion. The proposed methods are illustrated with one simulated and two real data examples. Supplemental materials available online show that several "natural" approaches to penalized SVDs are flawed and explain why so. © 2009 American Statistical Association.

Human visual system automatically encodes sequential regularities of discrete events.

Science.gov (United States)

Kimura, Motohiro; Schröger, Erich; Czigler, István; Ohira, Hideki

2010-06-01

For our adaptive behavior in a dynamically changing environment, an essential task of the brain is to automatically encode sequential regularities inherent in the environment into a memory representation. Recent studies in neuroscience have suggested that sequential regularities embedded in discrete sensory events are automatically encoded into a memory representation at the level of the sensory system. This notion is largely supported by evidence from investigations using auditory mismatch negativity (auditory MMN), an event-related brain potential (ERP) correlate of an automatic memory-mismatch process in the auditory sensory system. However, it is still largely unclear whether or not this notion can be generalized to other sensory modalities. The purpose of the present study was to investigate the contribution of the visual sensory system to the automatic encoding of sequential regularities using visual mismatch negativity (visual MMN), an ERP correlate of an automatic memory-mismatch process in the visual sensory system. To this end, we conducted a sequential analysis of visual MMN in an oddball sequence consisting of infrequent deviant and frequent standard stimuli, and tested whether the underlying memory representation of visual MMN generation contains only a sensory memory trace of standard stimuli (trace-mismatch hypothesis) or whether it also contains sequential regularities extracted from the repetitive standard sequence (regularity-violation hypothesis). The results showed that visual MMN was elicited by first deviant (deviant stimuli following at least one standard stimulus), second deviant (deviant stimuli immediately following first deviant), and first standard (standard stimuli immediately following first deviant), but not by second standard (standard stimuli immediately following first standard). These results are consistent with the regularity-violation hypothesis, suggesting that the visual sensory system automatically encodes sequential

Subcortical processing of speech regularities underlies reading and music aptitude in children

Science.gov (United States)

2011-01-01

Background Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. Methods We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Results Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. Conclusions These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to regularities in auditory input

Subcortical processing of speech regularities underlies reading and music aptitude in children.

Science.gov (United States)

Strait, Dana L; Hornickel, Jane; Kraus, Nina

2011-10-17

Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to regularities in auditory input. Definition of common biological underpinnings

Subcortical processing of speech regularities underlies reading and music aptitude in children

Directory of Open Access Journals (Sweden)

Strait Dana L

2011-10-01

Full Text Available Abstract Background Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. Methods We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Results Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. Conclusions These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to

Surface-based prostate registration with biomechanical regularization

Science.gov (United States)

van de Ven, Wendy J. M.; Hu, Yipeng; Barentsz, Jelle O.; Karssemeijer, Nico; Barratt, Dean; Huisman, Henkjan J.

2013-03-01

Adding MR-derived information to standard transrectal ultrasound (TRUS) images for guiding prostate biopsy is of substantial clinical interest. A tumor visible on MR images can be projected on ultrasound by using MRUS registration. A common approach is to use surface-based registration. We hypothesize that biomechanical modeling will better control deformation inside the prostate than a regular surface-based registration method. We developed a novel method by extending a surface-based registration with finite element (FE) simulation to better predict internal deformation of the prostate. For each of six patients, a tetrahedral mesh was constructed from the manual prostate segmentation. Next, the internal prostate deformation was simulated using the derived radial surface displacement as boundary condition. The deformation field within the gland was calculated using the predicted FE node displacements and thin-plate spline interpolation. We tested our method on MR guided MR biopsy imaging data, as landmarks can easily be identified on MR images. For evaluation of the registration accuracy we used 45 anatomical landmarks located in all regions of the prostate. Our results show that the median target registration error of a surface-based registration with biomechanical regularization is 1.88 mm, which is significantly different from 2.61 mm without biomechanical regularization. We can conclude that biomechanical FE modeling has the potential to improve the accuracy of multimodal prostate registration when comparing it to regular surface-based registration.

Regularization in Matrix Relevance Learning

NARCIS (Netherlands)

Schneider, Petra; Bunte, Kerstin; Stiekema, Han; Hammer, Barbara; Villmann, Thomas; Biehl, Michael

A In this paper, we present a regularization technique to extend recently proposed matrix learning schemes in learning vector quantization (LVQ). These learning algorithms extend the concept of adaptive distance measures in LVQ to the use of relevance matrices. In general, metric learning can

Left regular bands of groups of left quotients

International Nuclear Information System (INIS)

El-Qallali, A.

1988-10-01

A semigroup S which has a left regular band of groups as a semigroup of left quotients is shown to be the semigroup which is a left regular band of right reversible cancellative semigroups. An alternative characterization is provided by using spinned products. These results are applied to the case where S is a superabundant whose set of idempotents forms a left normal band. (author). 13 refs

Sparsity regularization for parameter identification problems

International Nuclear Information System (INIS)

Jin, Bangti; Maass, Peter

2012-01-01

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 ℓ p -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 ℓ p 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

Rotating Hayward’s regular black hole as particle accelerator

International Nuclear Information System (INIS)

Amir, Muhammed; Ghosh, Sushant G.

2015-01-01

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 aregular 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.

Regularity of difference equations on Banach spaces

CERN Document Server

Agarwal, Ravi P; Lizama, Carlos

2014-01-01

This work introduces readers to the topic of maximal regularity for difference equations. The authors systematically present the method of maximal regularity, outlining basic linear difference equations along with relevant results. They address recent advances in the field, as well as basic semigroup and cosine operator theories in the discrete setting. The authors also identify some open problems that readers may wish to take up for further research. This book is intended for graduate students and researchers in the area of difference equations, particularly those with advance knowledge of and interest in functional analysis.

Gamma regularization based reconstruction for low dose CT

International Nuclear Information System (INIS)

Zhang, Junfeng; Chen, Yang; Hu, Yining; Luo, Limin; Shu, Huazhong; Li, Bicao; Liu, Jin; Coatrieux, Jean-Louis

2015-01-01

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 l 0 -norm and l 1 -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. (paper)

Regularization of plurisubharmonic functions with a net of good points

OpenAIRE

Li, Long

2017-01-01

The purpose of this article is to present a new regularization technique of quasi-plurisubharmoinc functions on a compact Kaehler manifold. The idea is to regularize the function on local coordinate balls first, and then glue each piece together. Therefore, all the higher order terms in the complex Hessian of this regularization vanish at the center of each coordinate ball, and all the centers build a delta-net of the manifold eventually.

Optimal Embeddings of Distance Regular Graphs into Euclidean Spaces

NARCIS (Netherlands)

F. Vallentin (Frank)

2008-01-01

htmlabstractIn this paper we give a lower bound for the least distortion embedding of a distance regular graph into Euclidean space. We use the lower bound for finding the least distortion for Hamming graphs, Johnson graphs, and all strongly regular graphs. Our technique involves semidefinite

76 FR 3629 - Regular Meeting

Science.gov (United States)

2011-01-20

... Meeting SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). Date and Time: The meeting of the Board will be held at the offices of the Farm... meeting of the Board will be open to the [[Page 3630

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan

2014-09-07

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan; Wang, Yi; Zhao, Shiguang; Gao, Xin

2014-01-01

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

The equivalence problem for LL- and LR-regular grammars

NARCIS (Netherlands)

Nijholt, Antinus; Gecsec, F.

It will be shown that the equivalence problem for LL-regular grammars is decidable. Apart from extending the known result for LL(k) grammar equivalence to LLregular grammar equivalence, we obtain an alternative proof of the decidability of LL(k) equivalence. The equivalence prob]em for LL-regular

'Regular' and 'emergency' repair

International Nuclear Information System (INIS)

Luchnik, N.V.

1975-01-01

Experiments on the combined action of radiation and a DNA inhibitor using Crepis roots and on split-dose irradiation of human lymphocytes lead to the conclusion that there are two types of repair. The 'regular' repair takes place twice in each mitotic cycle and ensures the maintenance of genetic stability. The 'emergency' repair is induced at all stages of the mitotic cycle by high levels of injury. (author)

Processing SPARQL queries with regular expressions in RDF databases

Science.gov (United States)

2011-01-01

Background As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users’ requests for extracting information from the RDF data as well as the lack of users’ knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. Results In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Conclusions Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns. PMID:21489225

Processing SPARQL queries with regular expressions in RDF databases.

Science.gov (United States)

Lee, Jinsoo; Pham, Minh-Duc; Lee, Jihwan; Han, Wook-Shin; Cho, Hune; Yu, Hwanjo; Lee, Jeong-Hoon

2011-03-29

As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users' requests for extracting information from the RDF data as well as the lack of users' knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.

Fluid queues and regular variation

NARCIS (Netherlands)

O.J. Boxma (Onno)

1996-01-01

textabstractThis paper considers a fluid queueing system, fed by $N$ independent sources that alternate between silence and activity periods. We assume that the distribution of the activity periods of one or more sources is a regularly varying function of index $zeta$. We show that its fat tail

Bit-coded regular expression parsing

DEFF Research Database (Denmark)

Nielsen, Lasse; Henglein, Fritz

2011-01-01

the DFA-based parsing algorithm due to Dub ´e and Feeley to emit the bits of the bit representation without explicitly materializing the parse tree itself. We furthermore show that Frisch and Cardelli’s greedy regular expression parsing algorithm can be straightforwardly modified to produce bit codings...

Closedness type regularity conditions in convex optimization and beyond

Directory of Open Access Journals (Sweden)

Sorin-Mihai Grad

2016-09-01

Full Text Available The closedness type regularity conditions have proven during the last decade to be viable alternatives to their more restrictive interiority type counterparts, in both convex optimization and different areas where it was successfully applied. In this review article we de- and reconstruct some closedness type regularity conditions formulated by means of epigraphs and subdifferentials, respectively, for general optimization problems in order to stress that they arise naturally when dealing with such problems. The results are then specialized for constrained and unconstrained convex optimization problems. We also hint towards other classes of optimization problems where closedness type regularity conditions were successfully employed and discuss other possible applications of them.

Imbalance of positive and negative links induces regularity

International Nuclear Information System (INIS)

Kamal, Neeraj Kumar; Sinha, Sudeshna

2011-01-01

Research highlights: → We consider the behaviour of a random weighted network with chaotic neuronal dynamics at the nodes. → We investigate the effect of the balance of positive and negative links on dynamical regularity. → We find that when the connections are predominantly excitatory or inhibitory, one obtains a spatiotemporal fixed point. → However, when the links are balanced, the chaotic nature of the nodal dynamics of the uncoupled case is preserved. → Further we observe that larger network size leads to greater spatiotemporal regularity. - Abstract: We investigate the effect of the interplay of positive and negative links, on the dynamical regularity of a random weighted network, with neuronal dynamics at the nodes. We investigate how the mean J-bar and the variance of the weights of links, influence the spatiotemporal regularity of this dynamical network. We find that when the connections are predominantly positive (i.e. the links are mostly excitatory, with J-bar>0) the spatiotemporal fixed point is stable. A similar trend is observed when the connections are predominantly negative (i.e. the links are mostly inhibitory, with J-bar<0). However, when the positive and negative feedback is quite balanced (namely, when the mean of the connection weights is close to zero) one observes spatiotemporal chaos. That is, the balance of excitatory and inhibitory connections preserves the chaotic nature of the uncoupled case. To be brought to an inactive state one needs one type of connection (either excitatory or inhibitory) to dominate. Further we observe that larger network size leads to greater spatiotemporal regularity. We rationalize our observations through mean field analysis of the network dynamics.

Spectral Regularization Algorithms for Learning Large Incomplete Matrices.

Science.gov (United States)

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.

Poisson image reconstruction with Hessian Schatten-norm regularization.

Science.gov (United States)

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.

A projection-based approach to general-form Tikhonov regularization

DEFF Research Database (Denmark)

Kilmer, Misha E.; Hansen, Per Christian; Espanol, Malena I.

2007-01-01

We present a projection-based iterative algorithm for computing general-form Tikhonov regularized solutions to the problem minx| Ax-b |2^2+lambda2| Lx |2^2, where the regularization matrix L is not the identity. Our algorithm is designed for the common case where lambda is not known a priori...

Sparse regularization for force identification using dictionaries

Science.gov (United States)

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

2016-04-01

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

Regular black holes: electrically charged solutions, Reissner-Nordstroem outside a De Sitter core

Energy Technology Data Exchange (ETDEWEB)

Lemos, Jose P.S. [Universidade Tecnica de Lisboa (CENTRA/IST/UTL) (Portugal). Instituto Superior Tecnico. Centro Multidisciplinar de Astrofisica; Zanchin, Vilson T. [Universidade Federal do ABC (UFABC), Santo Andre, SP (Brazil). Centro de Ciencias Naturais e Humanas

2011-07-01

Full text: The understanding of the inside of a black hole is of crucial importance in order to have the correct picture of a black hole as a whole. The singularities that lurk inside of the usual black hole solutions are things to avoid. Their substitution by a regular part is of great interest, the process generating regular black holes. In the present work regular black hole solutions are found within general relativity coupled to Maxwell's electromagnetism and charged matter. We show that there are objects which correspond to regular charged black holes, whose interior region is de Sitter, whose exterior region is Reissner-Nordstroem, and the boundary between both regions is made of an electrically charged spherically symmetric coat. There are several solutions: the regular nonextremal black holes with a null matter boundary, the regular nonextremal black holes with a timelike matter boundary, the regular extremal black holes with a timelike matter boundary, and the regular overcharged stars with a timelike matter boundary. The main physical and geometrical properties of such charged regular solutions are analyzed. (author)

On the MSE Performance and Optimization of Regularized Problems

KAUST Repository

Alrashdi, Ayed

2016-11-01

The amount of data that has been measured, transmitted/received, and stored in the recent years has dramatically increased. So, today, we are in the world of big data. Fortunately, in many applications, we can take advantages of possible structures and patterns in the data to overcome the curse of dimensionality. The most well known structures include sparsity, low-rankness, block sparsity. This includes a wide range of applications such as machine learning, medical imaging, signal processing, social networks and computer vision. This also led to a specific interest in recovering signals from noisy compressed measurements (Compressed Sensing (CS) problem). Such problems are generally ill-posed unless the signal is structured. The structure can be captured by a regularizer function. This gives rise to a potential interest in regularized inverse problems, where the process of reconstructing the structured signal can be modeled as a regularized problem. This thesis particularly focuses on finding the optimal regularization parameter for such problems, such as ridge regression, LASSO, square-root LASSO and low-rank Generalized LASSO. Our goal is to optimally tune the regularizer to minimize the mean-squared error (MSE) of the solution when the noise variance or structure parameters are unknown. The analysis is based on the framework of the Convex Gaussian Min-max Theorem (CGMT) that has been used recently to precisely predict performance errors.

The neural substrates of impaired finger tapping regularity after stroke.

Science.gov (United States)

Calautti, Cinzia; Jones, P Simon; Guincestre, Jean-Yves; Naccarato, Marcello; Sharma, Nikhil; Day, Diana J; Carpenter, T Adrian; Warburton, Elizabeth A; Baron, Jean-Claude

2010-03-01

Not only finger tapping speed, but also tapping regularity can be impaired after stroke, contributing to reduced dexterity. The neural substrates of impaired tapping regularity after stroke are unknown. Previous work suggests damage to the dorsal premotor cortex (PMd) and prefrontal cortex (PFCx) affects externally-cued hand movement. We tested the hypothesis that these two areas are involved in impaired post-stroke tapping regularity. In 19 right-handed patients (15 men/4 women; age 45-80 years; purely subcortical in 16) partially to fully recovered from hemiparetic stroke, tri-axial accelerometric quantitative assessment of tapping regularity and BOLD fMRI were obtained during fixed-rate auditory-cued index-thumb tapping, in a single session 10-230 days after stroke. A strong random-effect correlation between tapping regularity index and fMRI signal was found in contralesional PMd such that the worse the regularity the stronger the activation. A significant correlation in the opposite direction was also present within contralesional PFCx. Both correlations were maintained if maximal index tapping speed, degree of paresis and time since stroke were added as potential confounds. Thus, the contralesional PMd and PFCx appear to be involved in the impaired ability of stroke patients to fingertap in pace with external cues. The findings for PMd are consistent with repetitive TMS investigations in stroke suggesting a role for this area in affected-hand movement timing. The inverse relationship with tapping regularity observed for the PFCx and the PMd suggests these two anatomically-connected areas negatively co-operate. These findings have implications for understanding the disruption and reorganization of the motor systems after stroke. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Regularizations: different recipes for identical situations

International Nuclear Information System (INIS)

Gambin, E.; Lobo, C.O.; Battistel, O.A.

2004-03-01

We present a discussion where the choice of the regularization procedure and the routing for the internal lines momenta are put at the same level of arbitrariness in the analysis of Ward identities involving simple and well-known problems in QFT. They are the complex self-interacting scalar field and two simple models where the SVV and AVV process are pertinent. We show that, in all these problems, the conditions to symmetry relations preservation are put in terms of the same combination of divergent Feynman integrals, which are evaluated in the context of a very general calculational strategy, concerning the manipulations and calculations involving divergences. Within the adopted strategy, all the arbitrariness intrinsic to the problem are still maintained in the final results and, consequently, a perfect map can be obtained with the corresponding results of the traditional regularization techniques. We show that, when we require an universal interpretation for the arbitrariness involved, in order to get consistency with all stated physical constraints, a strong condition is imposed for regularizations which automatically eliminates the ambiguities associated to the routing of the internal lines momenta of loops. The conclusion is clean and sound: the association between ambiguities and unavoidable symmetry violations in Ward identities cannot be maintained if an unique recipe is required for identical situations in the evaluation of divergent physical amplitudes. (author)

The effect of regular walking and alternate day fasting on health-related factors in overweight and obese females

Directory of Open Access Journals (Sweden)

Roya Seighali

2017-03-01

Full Text Available Introduction: Obesity is a complex health problem. The aim of this study was to determine the effects of regular walking with alternate day fasting (ADF on health-related factors of overweight and obese females.‎  Methods: 30 healthy inactive, overweight and obese women were divided randomly into three equal groups.  The groups were: control group (BMI: 30.72±4.40 kg/m2; the experimental group I: ADF along with regular walking with 50% to 65% maximal heart rate (BMI: 28.69 ±2.81 kg/m2 and the experimental group II: ADF (BMI: 30.56 ±3.66 kg/m2. Participants were under the diet for six weeks. The diet ADF means that, they had days of fasting and free day (with regular walking, alternately. Two days before and two days after the end of the study, the participants’ fasting blood sugar were measured after 12 hours. Resting heart rate, blood pressure and body composition were assessed in the same day. The collected data were analyzed using paired t-test and ANOVA test. Results: Body mass index in both experimental groups had significant decrease‎ (P

Regular transport dynamics produce chaotic travel times.

Science.gov (United States)

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.

The Impact of Computerization on Regular Employment (Japanese)

OpenAIRE

SUNADA Mitsuru; HIGUCHI Yoshio; ABE Masahiro

2004-01-01

This paper uses micro data from the Basic Survey of Japanese Business Structure and Activity to analyze the effects of companies' introduction of information and telecommunications technology on employment structures, especially regular versus non-regular employment. Firstly, examination of trends in the ratio of part-time workers recorded in the Basic Survey shows that part-time worker ratios in manufacturing firms are rising slightly, but that companies with a high proportion of part-timers...

Barriers to follow-up for pediatric cataract surgery in Maharashtra, India: How regular follow-up is important for good outcome. The Miraj Pediatric Cataract Study II

Directory of Open Access Journals (Sweden)

Parikshit Gogate

2014-01-01

Full Text Available Background: Regular follow up and amblyopia treatment are essential for good outcomes after pediatric cataract surgery. Aim: To study the regularity of follow-up after cataract surgery in children and to gauge the causes of poor compliance to follow up. Subjects: 262 children (393 cataracts who underwent cataract surgery in 2004-8. Materials and Methods: The children were identified and examined in their homes and a "barriers to follow-up" questionnaire completed. Demographic data collected, visual acuity estimated, and ocular examination performed. Statistical Analysis: SPSS version 19. Results: Of the 262 children, only 53 (20.6% had been regularly following up with any hospital, 209 (79.4% had not. A total of 150 (57.3% were boys and the average age was 13.23 years (Std Dev 5 yrs. Poor follow up was associated with the older age group ( P 1 line with regular follow-up. Conclusion: Regular follow-up is important and improves vision; eye care practitioners need to take special efforts to ensure better follow-up.

Lattice regularized chiral perturbation theory

International Nuclear Information System (INIS)

Borasoy, Bugra; Lewis, Randy; Ouimet, Pierre-Philippe A.

2004-01-01

Chiral perturbation theory can be defined and regularized on a spacetime lattice. A few motivations are discussed here, and an explicit lattice Lagrangian is reviewed. A particular aspect of the connection between lattice chiral perturbation theory and lattice QCD is explored through a study of the Wess-Zumino-Witten term

Empirical laws, regularity and necessity

NARCIS (Netherlands)

Koningsveld, H.

1973-01-01

In this book I have tried to develop an analysis of the concept of an empirical law, an analysis that differs in many ways from the alternative analyse's found in contemporary literature dealing with the subject.

1 am referring especially to two well-known views, viz. the regularity and

Inclusion Professional Development Model and Regular Middle School Educators

Science.gov (United States)

Royster, Otelia; Reglin, Gary L.; Losike-Sedimo, Nonofo

2014-01-01

The purpose of this study was to determine the impact of a professional development model on regular education middle school teachers' knowledge of best practices for teaching inclusive classes and attitudes toward teaching these classes. There were 19 regular education teachers who taught the core subjects. Findings for Research Question 1…

Regularization ambiguities in loop quantum gravity

International Nuclear Information System (INIS)

Perez, Alejandro

2006-01-01

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 find

77 FR 55229 - National Farmworker Jobs Program (NFJP) Information Collection Forms; Comment Request for Regular...

Science.gov (United States)

2012-09-07

... the grantees regarding the content of the annual plan narrative and submission requirements. II... through the use of appropriate automated, electronic, mechanical, or other technological collection.... Affected Public: State or local government agencies; not-for-profit organizations. Form(s): Grant Plan...

Processing SPARQL queries with regular expressions in RDF databases

Directory of Open Access Journals (Sweden)

Cho Hune

2011-03-01

Full Text Available Abstract Background As the Resource Description Framework (RDF data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf or Bio2RDF (bio2rdf.org, SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users’ requests for extracting information from the RDF data as well as the lack of users’ knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. Results In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1 We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2 We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3 We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Conclusions Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.

Pairing renormalization and regularization within the local density approximation

International Nuclear Information System (INIS)

Borycki, P.J.; Dobaczewski, J.; Nazarewicz, W.; Stoitsov, M.V.

2006-01-01

We discuss methods used in mean-field theories to treat pairing correlations within the local density approximation. Pairing renormalization and regularization procedures are compared in spherical and deformed nuclei. Both prescriptions give fairly similar results, although the theoretical motivation, simplicity, and stability of the regularization procedure make it a method of choice for future applications

Strong Bisimilarity and Regularity of Basic Parallel Processes is PSPACE-Hard

DEFF Research Database (Denmark)

Srba, Jirí

2002-01-01

We show that the problem of checking whether two processes definable in the syntax of Basic Parallel Processes (BPP) are strongly bisimilar is PSPACE-hard. We also demonstrate that there is a polynomial time reduction from the strong bisimilarity checking problem of regular BPP to the strong...... regularity (finiteness) checking of BPP. This implies that strong regularity of BPP is also PSPACE-hard....

Contour Propagation With Riemannian Elasticity Regularization

DEFF Research Database (Denmark)

Bjerre, Troels; Hansen, Mads Fogtmann; Sapru, W.

2011-01-01

Purpose/Objective(s): Adaptive techniques allow for correction of spatial changes during the time course of the fractionated radiotherapy. Spatial changes include tumor shrinkage and weight loss, causing tissue deformation and residual positional errors even after translational and rotational image...... the planning CT onto the rescans and correcting to reflect actual anatomical changes. For deformable registration, a free-form, multi-level, B-spline deformation model with Riemannian elasticity, penalizing non-rigid local deformations, and volumetric changes, was used. Regularization parameters was defined...... on the original delineation and tissue deformation in the time course between scans form a better starting point than rigid propagation. There was no significant difference of locally and globally defined regularization. The method used in the present study suggests that deformed contours need to be reviewed...

Capped Lp approximations for the composite L0 regularization problem

OpenAIRE

Li, Qia; Zhang, Na

2017-01-01

The composite L0 function serves as a sparse regularizer in many applications. The algorithmic difficulty caused by the composite L0 regularization (the L0 norm composed with a linear mapping) is usually bypassed through approximating the L0 norm. We consider in this paper capped Lp approximations with $p>0$ for the composite L0 regularization problem. For each $p>0$, the capped Lp function converges to the L0 norm pointwisely as the approximation parameter tends to infinity. We point out tha...

Manifold regularized multi-task feature selection for multi-modality classification in Alzheimer's disease.

Science.gov (United States)

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2013-01-01

Accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method.

Fluid queues and regular variation

NARCIS (Netherlands)

Boxma, O.J.

1996-01-01

This paper considers a fluid queueing system, fed by N independent sources that alternate between silence and activity periods. We assume that the distribution of the activity periods of one or more sources is a regularly varying function of index ¿. We show that its fat tail gives rise to an even

Collectivity of dipole bands in {sup 196}Pb

Energy Technology Data Exchange (ETDEWEB)

Carpenter, M.P.; Liang, Y.; Janssens, R.V.F. [and others

1995-08-01

The region of nuclei with mass {approximately} 190 was studied extensively over the last few years following the discovery of superdeformation in {sup 190}Hg. More recently, considerable interest in the neutron-deficient Pb isotopes developed with the discover of a number of bands at high spin connected by dipole transitions in both even {sup 192-200}Pb and odd {sup 197-201}Pb nuclei. The majority of the dipole bands are regular in character (i.e. transition energies increase smoothly with spin) while the remaining bands are referred to as irregular in character, due to the fact that the transition energies do not increase smoothly with spin. The properties of the dipole bands were interpreted in terms of high-K, moderately-deformed oblate states built on configurations involving high-J, shape-driving quasiproton excitations coupled to rotation-aligned quasineutrons. It was suggested that the difference between the regular and irregular dipole sequences is related to the deformation where the irregular sequences are thought to be less collective than their regular counterparts.

Further investigation on "A multiplicative regularization for force reconstruction"

Science.gov (United States)

Aucejo, M.; De Smet, O.

2018-05-01

We have recently proposed a multiplicative regularization to reconstruct mechanical forces acting on a structure from vibration measurements. This method does not require any selection procedure for choosing the regularization parameter, since the amount of regularization is automatically adjusted throughout an iterative resolution process. The proposed iterative algorithm has been developed with performance and efficiency in mind, but it is actually a simplified version of a full iterative procedure not described in the original paper. The present paper aims at introducing the full resolution algorithm and comparing it with its simplified version in terms of computational efficiency and solution accuracy. In particular, it is shown that both algorithms lead to very similar identified solutions.

Regularization method for solving the inverse scattering problem

International Nuclear Information System (INIS)

Denisov, A.M.; Krylov, A.S.

1985-01-01

The inverse scattering problem for the Schroedinger radial equation consisting in determining the potential according to the scattering phase is considered. The problem of potential restoration according to the phase specified with fixed error in a finite range is solved by the regularization method based on minimization of the Tikhonov's smoothing functional. The regularization method is used for solving the problem of neutron-proton potential restoration according to the scattering phases. The determined potentials are given in the table

Variational analysis of regular mappings theory and applications

CERN Document Server

Ioffe, Alexander D

2017-01-01

This monograph offers the first systematic account of (metric) regularity theory in variational analysis. It presents new developments alongside classical results and demonstrates the power of the theory through applications to various problems in analysis and optimization theory. The origins of metric regularity theory can be traced back to a series of fundamental ideas and results of nonlinear functional analysis and global analysis centered around problems of existence and stability of solutions of nonlinear equations. In variational analysis, regularity theory goes far beyond the classical setting and is also concerned with non-differentiable and multi-valued operators. The present volume explores all basic aspects of the theory, from the most general problems for mappings between metric spaces to those connected with fairly concrete and important classes of operators acting in Banach and finite dimensional spaces. Written by a leading expert in the field, the book covers new and powerful techniques, whic...

Factors associated with a continuous regular analgesic use - a population-based study of more than 45,000 Danish women and men 18-45 years of age.

Science.gov (United States)

Hargreave, Marie; Andersen, Tina Veje; Nielsen, Ann; Munk, Christian; Liaw, Kai-Li; Kjaer, Susanne K

2010-01-01

Widespread use of and serious adverse effects associated with use of analgesics accentuates the need to consider factors related to analgesic use. The objective of this study was to describe continuous regular analgesics use and examine factors associated with a continuous regular analgesic use. The study was based on data from two surveys and included a random sample of women and men aged 18-45 years from the general Danish population. Information on analgesics use, self-rated health, demographic and lifestyle factors was collected using a self-administered questionnaire. A total of 28,000 women and 33 000 men were invited to participate and 22,199 women (response-rate 81.4%) and 23,080 men (response-rate 71.0%), respectively, were included in the study. Data were analyzed using multivariate logistic regression. We found that 27% of the women and 18% of the men reported a regular monthly use of at least seven analgesic tablets during the last year (continuous regular analgesics use). Besides poor self-rated health we found in both sexes that increasing age, poor self-rated fitness, and smoking were related to a continuous regular analgesics use. Nulliparity, low level of education, overweight/obesity, binge drinking, and abstinence were associated with a continuous regular analgesics use for women, while underweight and marital/cohabiting status were associated with a continuous regular analgesics use only for men. Regular monthly analgesic use during the last year was generally prevalent. Besides self-rated health, several socio-demographic and lifestyle factors were associated with a continuous regular analgesic use, although with some gender differences.

Iterative regularization in intensity-modulated radiation therapy optimization

International Nuclear Information System (INIS)

Carlsson, Fredrik; Forsgren, Anders

2006-01-01

A common way to solve intensity-modulated radiation therapy (IMRT) optimization problems is to use a beamlet-based approach. The approach is usually employed in a three-step manner: first a beamlet-weight optimization problem is solved, then the fluence profiles are converted into step-and-shoot segments, and finally postoptimization of the segment weights is performed. A drawback of beamlet-based approaches is that beamlet-weight optimization problems are ill-conditioned and have to be regularized in order to produce smooth fluence profiles that are suitable for conversion. The purpose of this paper is twofold: first, to explain the suitability of solving beamlet-based IMRT problems by a BFGS quasi-Newton sequential quadratic programming method with diagonal initial Hessian estimate, and second, to empirically show that beamlet-weight optimization problems should be solved in relatively few iterations when using this optimization method. The explanation of the suitability is based on viewing the optimization method as an iterative regularization method. In iterative regularization, the optimization problem is solved approximately by iterating long enough to obtain a solution close to the optimal one, but terminating before too much noise occurs. Iterative regularization requires an optimization method that initially proceeds in smooth directions and makes rapid initial progress. Solving ten beamlet-based IMRT problems with dose-volume objectives and bounds on the beamlet-weights, we find that the considered optimization method fulfills the requirements for performing iterative regularization. After segment-weight optimization, the treatments obtained using 35 beamlet-weight iterations outperform the treatments obtained using 100 beamlet-weight iterations, both in terms of objective value and of target uniformity. We conclude that iterating too long may in fact deteriorate the quality of the deliverable plan

Correction of engineering servicing regularity of transporttechnological machines in operational process

Science.gov (United States)

Makarova, A. N.; Makarov, E. I.; Zakharov, N. S.

2018-03-01

In the article, the issue of correcting engineering servicing regularity on the basis of actual dependability data of cars in operation is considered. The purpose of the conducted research is to increase dependability of transport-technological machines by correcting engineering servicing regularity. The subject of the research is the mechanism of engineering servicing regularity influence on reliability measure. On the basis of the analysis of researches carried out before, a method of nonparametric estimation of car failure measure according to actual time-to-failure data was chosen. A possibility of describing the failure measure dependence on engineering servicing regularity by various mathematical models is considered. It is proven that the exponential model is the most appropriate for that purpose. The obtained results can be used as a separate method of engineering servicing regularity correction with certain operational conditions taken into account, as well as for the technical-economical and economical-stochastic methods improvement. Thus, on the basis of the conducted researches, a method of engineering servicing regularity correction of transport-technological machines in the operational process was developed. The use of that method will allow decreasing the number of failures.

Analysis of regularized inversion of data corrupted by white Gaussian noise

International Nuclear Information System (INIS)

Kekkonen, Hanne; Lassas, Matti; Siltanen, Samuli

2014-01-01

Tikhonov regularization is studied in the case of linear pseudodifferential operator as the forward map and additive white Gaussian noise as the measurement error. The measurement model for an unknown function u(x) is m(x) = Au(x) + δ ε (x), where δ > 0 is the noise magnitude. If ε was an L 2 -function, Tikhonov regularization gives an estimate T α (m) = u∈H r arg min { ||Au-m|| L 2 2 + α||u|| H r 2 } for u where α = α(δ) is the regularization parameter. Here penalization of the Sobolev norm ||u|| H r covers the cases of standard Tikhonov regularization (r = 0) and first derivative penalty (r = 1). Realizations of white Gaussian noise are almost never in L 2 , but do belong to H s with probability one if s < 0 is small enough. A modification of Tikhonov regularization theory is presented, covering the case of white Gaussian measurement noise. Furthermore, the convergence of regularized reconstructions to the correct solution as δ → 0 is proven in appropriate function spaces using microlocal analysis. The convergence of the related finite-dimensional problems to the infinite-dimensional problem is also analysed. (paper)

47 CFR 76.614 - Cable television system regular monitoring.

Science.gov (United States)

2010-10-01

...-137 and 225-400 MHz shall provide for a program of regular monitoring for signal leakage by... in these bands of 20 uV/m or greater at a distance of 3 meters. During regular monitoring, any leakage source which produces a field strength of 20 uV/m or greater at a distance of 3 meters in the...

Geostatistical regularization operators for geophysical inverse problems on irregular meshes

Science.gov (United States)

Jordi, C.; Doetsch, J.; Günther, T.; Schmelzbach, C.; Robertsson, J. OA

2018-05-01

Irregular meshes allow to include complicated subsurface structures into geophysical modelling and inverse problems. The non-uniqueness of these inverse problems requires appropriate regularization that can incorporate a priori information. However, defining regularization operators for irregular discretizations is not trivial. Different schemes for calculating smoothness operators on irregular meshes have been proposed. In contrast to classical regularization constraints that are only defined using the nearest neighbours of a cell, geostatistical operators include a larger neighbourhood around a particular cell. A correlation model defines the extent of the neighbourhood and allows to incorporate information about geological structures. We propose an approach to calculate geostatistical operators for inverse problems on irregular meshes by eigendecomposition of a covariance matrix that contains the a priori geological information. Using our approach, the calculation of the operator matrix becomes tractable for 3-D inverse problems on irregular meshes. We tested the performance of the geostatistical regularization operators and compared them against the results of anisotropic smoothing in inversions of 2-D surface synthetic electrical resistivity tomography (ERT) data as well as in the inversion of a realistic 3-D cross-well synthetic ERT scenario. The inversions of 2-D ERT and seismic traveltime field data with geostatistical regularization provide results that are in good accordance with the expected geology and thus facilitate their interpretation. In particular, for layered structures the geostatistical regularization provides geologically more plausible results compared to the anisotropic smoothness constraints.

Expressiveness modulo Bisimilarity of Regular Expressions with Parallel Composition (Extended Abstract

Directory of Open Access Journals (Sweden)

Jos C. M. Baeten

2010-11-01

Full Text Available The languages accepted by finite automata are precisely the languages denoted by regular expressions. In contrast, finite automata may exhibit behaviours that cannot be described by regular expressions up to bisimilarity. In this paper, we consider extensions of the theory of regular expressions with various forms of parallel composition and study the effect on expressiveness. First we prove that adding pure interleaving to the theory of regular expressions strictly increases its expressiveness up to bisimilarity. Then, we prove that replacing the operation for pure interleaving by ACP-style parallel composition gives a further increase in expressiveness. Finally, we prove that the theory of regular expressions with ACP-style parallel composition and encapsulation is expressive enough to express all finite automata up to bisimilarity. Our results extend the expressiveness results obtained by Bergstra, Bethke and Ponse for process algebras with (the binary variant of Kleene's star operation.

Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation

International Nuclear Information System (INIS)

Bardsley, Johnathan M; Goldes, John

2009-01-01

In image processing applications, image intensity is often measured via the counting of incident photons emitted by the object of interest. In such cases, image data noise is accurately modeled by a Poisson distribution. This motivates the use of Poisson maximum likelihood estimation for image reconstruction. However, when the underlying model equation is ill-posed, regularization is needed. Regularized Poisson likelihood estimation has been studied extensively by the authors, though a problem of high importance remains: the choice of the regularization parameter. We will present three statistically motivated methods for choosing the regularization parameter, and numerical examples will be presented to illustrate their effectiveness

Chord length distributions between hard disks and spheres in regular, semi-regular, and quasi-random structures

International Nuclear Information System (INIS)

Olson, Gordon L.

2008-01-01

In binary stochastic media in two- and three-dimensions consisting of randomly placed impenetrable disks or spheres, the chord lengths in the background material between disks and spheres closely follow exponential distributions if the disks and spheres occupy less than 10% of the medium. This work demonstrates that for regular spatial structures of disks and spheres, the tails of the chord length distributions (CLDs) follow power laws rather than exponentials. In dilute media, when the disks and spheres are widely spaced, the slope of the power law seems to be independent of the details of the structure. When approaching a close-packed arrangement, the exact placement of the spheres can make a significant difference. When regular structures are perturbed by small random displacements, the CLDs become power laws with steeper slopes. An example CLD from a quasi-random distribution of spheres in clusters shows a modified exponential distribution

Chord length distributions between hard disks and spheres in regular, semi-regular, and quasi-random structures

Energy Technology Data Exchange (ETDEWEB)

Olson, Gordon L. [Computer and Computational Sciences Division (CCS-2), Los Alamos National Laboratory, 5 Foxglove Circle, Madison, WI 53717 (United States)], E-mail: olson99@tds.net

2008-11-15

In binary stochastic media in two- and three-dimensions consisting of randomly placed impenetrable disks or spheres, the chord lengths in the background material between disks and spheres closely follow exponential distributions if the disks and spheres occupy less than 10% of the medium. This work demonstrates that for regular spatial structures of disks and spheres, the tails of the chord length distributions (CLDs) follow power laws rather than exponentials. In dilute media, when the disks and spheres are widely spaced, the slope of the power law seems to be independent of the details of the structure. When approaching a close-packed arrangement, the exact placement of the spheres can make a significant difference. When regular structures are perturbed by small random displacements, the CLDs become power laws with steeper slopes. An example CLD from a quasi-random distribution of spheres in clusters shows a modified exponential distribution.

Zero-One Law for Regular Languages and Semigroups with Zero

OpenAIRE

Sin'ya, Ryoma

2015-01-01

A regular language has the zero-one law if its asymptotic density converges to either zero or one. We prove that the class of all zero-one languages is closed under Boolean operations and quotients. Moreover, we prove that a regular language has the zero-one law if and only if its syntactic monoid has a zero element. Our proof gives both algebraic and automata characterisation of the zero-one law for regular languages, and it leads the following two corollaries: (i) There is an O(n log n) alg...

Catalytic micromotor generating self-propelled regular motion through random fluctuation

Science.gov (United States)

Yamamoto, Daigo; Mukai, Atsushi; Okita, Naoaki; Yoshikawa, Kenichi; Shioi, Akihisa

2013-07-01

Most of the current studies on nano/microscale motors to generate regular motion have adapted the strategy to fabricate a composite with different materials. In this paper, we report that a simple object solely made of platinum generates regular motion driven by a catalytic chemical reaction with hydrogen peroxide. Depending on the morphological symmetry of the catalytic particles, a rich variety of random and regular motions are observed. The experimental trend is well reproduced by a simple theoretical model by taking into account of the anisotropic viscous effect on the self-propelled active Brownian fluctuation.

Globals of Completely Regular Monoids

Institute of Scientific and Technical Information of China (English)

Wu Qian-qian; Gan Ai-ping; Du Xian-kun

2015-01-01

An element of a semigroup S is called irreducible if it cannot be expressed as a product of two elements in S both distinct from itself. In this paper we show that the class C of all completely regular monoids with irreducible identity elements satisfies the strong isomorphism property and so it is globally determined.

Long-term, regular remote ischemic preconditioning improves endothelial function in patients with coronary heart disease

Energy Technology Data Exchange (ETDEWEB)

Liang, Y.; Li, Y.P.; He, F.; Liu, X.Q.; Zhang, J.Y. [Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou (China)

2015-04-28

Remote ischemic preconditioning (RIPre) can prevent myocardial injury. The purpose of this study was to assess the beneficial effects of long-term regular RIPre on human arteries. Forty patients scheduled for coronary artery bypass graft (CABG) surgery were assigned randomly to a RIPre group (n=20) or coronary heart disease (CHD) group (n=20). Twenty patients scheduled for mastectomy were enrolled as a control group. RIPre was achieved by occluding arterial blood flow 5 min with a mercury sphygmomanometer followed by a 5-min reperfusion period, and this was repeated 4 times. The RIPre procedure was repeated 3 times a day for 20 days. In all patients, arterial fragments discarded during surgery were collected to evaluate endothelial function by flow-mediated dilation (FMD), CD34{sup +} monocyte count, and endothelial nitric oxide synthase (eNOS expression). Phosphorylation levels of STAT-3 and Akt were also assayed to explore the underlying mechanisms. Compared with the CHD group, long-term regular RIPre significantly improved FMD after 20 days (8.5±2.4 vs 4.9±4.2%, P<0.05) and significantly reduced troponin after CABG surgery (0.72±0.31 and 1.64±0.19, P<0.05). RIPre activated STAT-3 and increased CD34{sup +} endothelial progenitor cell counts found in arteries. Long-term, regular RIPre improved endothelial function in patients with CHD, possibly due to STAT-3 activation, and this may have led to an increase in endothelial progenitor cells.

Regularization of divergent integrals

OpenAIRE

Felder, Giovanni; Kazhdan, David

2016-01-01

We study the Hadamard finite part of divergent integrals of differential forms with singularities on submanifolds. We give formulae for the dependence of the finite part on the choice of regularization and express them in terms of a suitable local residue map. The cases where the submanifold is a complex hypersurface in a complex manifold and where it is a boundary component of a manifold with boundary, arising in string perturbation theory, are treated in more detail.

Thin accretion disk around regular black hole

Directory of Open Access Journals (Sweden)

QIU Tianqi

2014-08-01

Full Text Available The Penrose′s cosmic censorship conjecture says that naked singularities do not exist in nature.So,it seems reasonable to further conjecture that not even a singularity exists in nature.In this paper,a regular black hole without singularity is studied in detail,especially on its thin accretion disk,energy flux,radiation temperature and accretion efficiency.It is found that the interaction of regular black hole is stronger than that of the Schwarzschild black hole. Furthermore,the thin accretion will be more efficiency to lost energy while the mass of black hole decreased. These particular properties may be used to distinguish between black holes.

Hamilton-Jacobi theorems for regular reducible Hamiltonian systems on a cotangent bundle

Science.gov (United States)

Wang, Hong

2017-09-01

In this paper, some of formulations of Hamilton-Jacobi equations for Hamiltonian system and regular reduced Hamiltonian systems are given. At first, an important lemma is proved, and it is a modification for the corresponding result of Abraham and Marsden (1978), such that we can prove two types of geometric Hamilton-Jacobi theorem for a Hamiltonian system on the cotangent bundle of a configuration manifold, by using the symplectic form and dynamical vector field. Then these results are generalized to the regular reducible Hamiltonian system with symmetry and momentum map, by using the reduced symplectic form and the reduced dynamical vector field. The Hamilton-Jacobi theorems are proved and two types of Hamilton-Jacobi equations, for the regular point reduced Hamiltonian system and the regular orbit reduced Hamiltonian system, are obtained. As an application of the theoretical results, the regular point reducible Hamiltonian system on a Lie group is considered, and two types of Lie-Poisson Hamilton-Jacobi equation for the regular point reduced system are given. In particular, the Type I and Type II of Lie-Poisson Hamilton-Jacobi equations for the regular point reduced rigid body and heavy top systems are shown, respectively.

Circuit complexity of regular languages

Czech Academy of Sciences Publication Activity Database

Koucký, Michal

2009-01-01

Roč. 45, č. 4 (2009), s. 865-879 ISSN 1432-4350 R&D Projects: GA ČR GP201/07/P276; GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10190503 Keywords : regular languages * circuit complexity * upper and lower bounds Subject RIV: BA - General Mathematics Impact factor: 0.726, year: 2009

Tur\\'an type inequalities for regular Coulomb wave functions

OpenAIRE

Baricz, Árpád

2015-01-01

Tur\\'an, Mitrinovi\\'c-Adamovi\\'c and Wilker type inequalities are deduced for regular Coulomb wave functions. The proofs are based on a Mittag-Leffler expansion for the regular Coulomb wave function, which may be of independent interest. Moreover, some complete monotonicity results concerning the Coulomb zeta functions and some interlacing properties of the zeros of Coulomb wave functions are given.

Image deblurring using a perturbation-basec regularization approach

KAUST Repository

Alanazi, Abdulrahman

2017-11-02

The image restoration problem deals with images in which information has been degraded by blur or noise. In this work, we present a new method for image deblurring by solving a regularized linear least-squares problem. In the proposed method, a synthetic perturbation matrix with a bounded norm is forced into the discrete ill-conditioned model matrix. This perturbation is added to enhance the singular-value structure of the matrix and hence to provide an improved solution. A method is proposed to find a near-optimal value of the regularization parameter for the proposed approach. To reduce the computational complexity, we present a technique based on the bootstrapping method to estimate the regularization parameter for both low and high-resolution images. Experimental results on the image deblurring problem are presented. Comparisons are made with three benchmark methods and the results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and SSIM values.

Centered Differential Waveform Inversion with Minimum Support Regularization

KAUST Repository

Kazei, Vladimir

2017-05-26

Time-lapse full-waveform inversion has two major challenges. The first one is the reconstruction of a reference model (baseline model for most of approaches). The second is inversion for the time-lapse changes in the parameters. Common model approach is utilizing the information contained in all available data sets to build a better reference model for time lapse inversion. Differential (Double-difference) waveform inversion allows to reduce the artifacts introduced into estimates of time-lapse parameter changes by imperfect inversion for the baseline-reference model. We propose centered differential waveform inversion (CDWI) which combines these two approaches in order to benefit from both of their features. We apply minimum support regularization commonly used with electromagnetic methods of geophysical exploration. We test the CDWI method on synthetic dataset with random noise and show that, with Minimum support regularization, it provides better resolution of velocity changes than with total variation and Tikhonov regularizations in time-lapse full-waveform inversion.

Manifestly scale-invariant regularization and quantum effective operators

CERN Document Server

Ghilencea, D.M.

2016-01-01

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 break 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 $\\mu(\\sigma)$ which after spontaneous breaking of scale symmetry generates the usual DR subtraction scale $\\mu(\\langle\\sigma\\rangle)$. One consequence is that "evanescent" interactions generated by scale invariance of the action in $d=4-2\\epsilon$ (but vanishing in $d=4$), give rise to new, finite quantum corrections. We find a (finite) correction $\\Delta U(\\phi,\\sigma)$ to the one-loop scalar potential for $\\phi$ and $\\sigma$, beyond the Coleman-Weinberg term. $\\Delta U$ is due to an evanescent correction ($\\propto\\epsilon$) to the field-dependent masses (of...

Image deblurring using a perturbation-basec regularization approach

KAUST Repository

Alanazi, Abdulrahman; Ballal, Tarig; Masood, Mudassir; Al-Naffouri, Tareq Y.

2017-01-01

The image restoration problem deals with images in which information has been degraded by blur or noise. In this work, we present a new method for image deblurring by solving a regularized linear least-squares problem. In the proposed method, a synthetic perturbation matrix with a bounded norm is forced into the discrete ill-conditioned model matrix. This perturbation is added to enhance the singular-value structure of the matrix and hence to provide an improved solution. A method is proposed to find a near-optimal value of the regularization parameter for the proposed approach. To reduce the computational complexity, we present a technique based on the bootstrapping method to estimate the regularization parameter for both low and high-resolution images. Experimental results on the image deblurring problem are presented. Comparisons are made with three benchmark methods and the results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and SSIM values.

Enhancing Low-Rank Subspace Clustering by Manifold Regularization.

Science.gov (United States)

Liu, Junmin; Chen, Yijun; Zhang, JiangShe; Xu, Zongben

2014-07-25

Recently, low-rank representation (LRR) method has achieved great success in subspace clustering (SC), which aims to cluster the data points that lie in a union of low-dimensional subspace. Given a set of data points, LRR seeks the lowest rank representation among the many possible linear combinations of the bases in a given dictionary or in terms of the data itself. However, LRR only considers the global Euclidean structure, while the local manifold structure, which is often important for many real applications, is ignored. In this paper, to exploit the local manifold structure of the data, a manifold regularization characterized by a Laplacian graph has been incorporated into LRR, leading to our proposed Laplacian regularized LRR (LapLRR). An efficient optimization procedure, which is based on alternating direction method of multipliers (ADMM), is developed for LapLRR. Experimental results on synthetic and real data sets are presented to demonstrate that the performance of LRR has been enhanced by using the manifold regularization.

BER analysis of regularized least squares for BPSK recovery

KAUST Repository

Ben Atitallah, Ismail; Thrampoulidis, Christos; Kammoun, Abla; Al-Naffouri, Tareq Y.; Hassibi, Babak; Alouini, Mohamed-Slim

2017-01-01

This paper investigates the problem of recovering an n-dimensional BPSK signal x0 ∈ {−1, 1}ⁿ from m-dimensional measurement vector y = Ax+z, where A and z are assumed to be Gaussian with iid entries. We consider two variants of decoders based on the regularized least squares followed by hard-thresholding: the case where the convex relaxation is from {−1, 1}ⁿ to ℝⁿ and the box constrained case where the relaxation is to [−1, 1]ⁿ. For both cases, we derive an exact expression of the bit error probability when n and m grow simultaneously large at a fixed ratio. For the box constrained case, we show that there exists a critical value of the SNR, above which the optimal regularizer is zero. On the other side, the regularization can further improve the performance of the box relaxation at low to moderate SNR regimes. We also prove that the optimal regularizer in the bit error rate sense for the unboxed case is nothing but the MMSE detector.

BER analysis of regularized least squares for BPSK recovery

KAUST Repository

Ben Atitallah, Ismail

2017-06-20

This paper investigates the problem of recovering an n-dimensional BPSK signal x0 ∈ {−1, 1}ⁿ from m-dimensional measurement vector y = Ax+z, where A and z are assumed to be Gaussian with iid entries. We consider two variants of decoders based on the regularized least squares followed by hard-thresholding: the case where the convex relaxation is from {−1, 1}ⁿ to ℝⁿ and the box constrained case where the relaxation is to [−1, 1]ⁿ. For both cases, we derive an exact expression of the bit error probability when n and m grow simultaneously large at a fixed ratio. For the box constrained case, we show that there exists a critical value of the SNR, above which the optimal regularizer is zero. On the other side, the regularization can further improve the performance of the box relaxation at low to moderate SNR regimes. We also prove that the optimal regularizer in the bit error rate sense for the unboxed case is nothing but the MMSE detector.

Lifshitz anomalies, Ward identities and split dimensional regularization

Energy Technology Data Exchange (ETDEWEB)

Arav, Igal; Oz, Yaron; Raviv-Moshe, Avia [Raymond and Beverly Sackler School of Physics and Astronomy, Tel-Aviv University,55 Haim Levanon street, Tel-Aviv, 69978 (Israel)

2017-03-16

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.

Lifshitz anomalies, Ward identities and split dimensional regularization

International Nuclear Information System (INIS)

Arav, Igal; Oz, Yaron; Raviv-Moshe, Avia

2017-01-01

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.

Mean magnetic susceptibility regularized susceptibility tensor imaging (MMSR-STI) for estimating orientations of white matter fibers in human brain.

Science.gov (United States)

Li, Xu; van Zijl, Peter C M

2014-09-01

An increasing number of studies show that magnetic susceptibility in white matter fibers is anisotropic and may be described by a tensor. However, the limited head rotation possible for in vivo human studies leads to an ill-conditioned inverse problem in susceptibility tensor imaging (STI). Here we suggest the combined use of limiting the susceptibility anisotropy to white matter and imposing morphology constraints on the mean magnetic susceptibility (MMS) for regularizing the STI inverse problem. The proposed MMS regularized STI (MMSR-STI) method was tested using computer simulations and in vivo human data collected at 3T. The fiber orientation estimated from both the STI and MMSR-STI methods was compared to that from diffusion tensor imaging (DTI). Computer simulations show that the MMSR-STI method provides a more accurate estimation of the susceptibility tensor than the conventional STI approach. Similarly, in vivo data show that use of the MMSR-STI method leads to a smaller difference between the fiber orientation estimated from STI and DTI for most selected white matter fibers. The proposed regularization strategy for STI can improve estimation of the susceptibility tensor in white matter. © 2014 Wiley Periodicals, Inc.

Total variation regularization for fMRI-based prediction of behavior

Science.gov (United States)

Michel, Vincent; Gramfort, Alexandre; Varoquaux, Gaël; Eger, Evelyn; Thirion, Bertrand

2011-01-01

While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional MRI (fMRI) data, that provide an indirect measure of task-related or spontaneous neuronal activity, are classically analyzed in a mass-univariate procedure yielding statistical parametric maps. This analysis framework disregards some important principles of brain organization: population coding, distributed and overlapping representations. Multivariate pattern analysis, i.e., the prediction of behavioural variables from brain activation patterns better captures this structure. To cope with the high dimensionality of the data, the learning method has to be regularized. However, the spatial structure of the image is not taken into account in standard regularization methods, so that the extracted features are often hard to interpret. More informative and interpretable results can be obtained with the ℓ1 norm of the image gradient, a.k.a. its Total Variation (TV), as regularization. We apply for the first time this method to fMRI data, and show that TV regularization is well suited to the purpose of brain mapping while being a powerful tool for brain decoding. Moreover, this article presents the first use of TV regularization for classification. PMID:21317080

Analytic regularization of the Yukawa model at finite temperature

International Nuclear Information System (INIS)

Malbouisson, A.P.C.; Svaiter, N.F.; Svaiter, B.F.

1996-07-01

It is analysed the one-loop fermionic contribution for the scalar effective potential in the temperature dependent Yukawa model. Ir order to regularize the model a mix between dimensional and analytic regularization procedures is used. It is found a general expression for the fermionic contribution in arbitrary spacetime dimension. It is also found that in D = 3 this contribution is finite. (author). 19 refs

On Regularity Criteria for the Two-Dimensional Generalized Liquid Crystal Model

Directory of Open Access Journals (Sweden)

Yanan Wang

2014-01-01

Full Text Available We establish the regularity criteria for the two-dimensional generalized liquid crystal model. It turns out that the global existence results satisfy our regularity criteria naturally.

17 CFR 270.10b-1 - Definition of regular broker or dealer.

Science.gov (United States)

2010-04-01

... COMMISSION (CONTINUED) RULES AND REGULATIONS, INVESTMENT COMPANY ACT OF 1940 § 270.10b-1 Definition of regular broker or dealer. The term regular broker or dealer of an investment company shall mean: (a) One... 17 Commodity and Securities Exchanges 3 2010-04-01 2010-04-01 false Definition of regular broker...

Regularity conditions of the field on a toroidal magnetic surface

International Nuclear Information System (INIS)

Bouligand, M.

1985-06-01

We show that a field B vector which is derived from an analytic canonical potential on an ordinary toroidal surface is regular on this surface when the potential satisfies an elliptic equation (owing to the conservative field) subject to certain conditions of regularity of its coefficients [fr

Regularized plane-wave least-squares Kirchhoff migration

KAUST Repository

Wang, Xin

2013-09-22

A Kirchhoff least-squares migration (LSM) is developed in the prestack plane-wave domain to increase the quality of migration images. A regularization term is included that accounts for mispositioning of reflectors due to errors in the velocity model. Both synthetic and field results show that: 1) LSM with a reflectivity model common for all the plane-wave gathers provides the best image when the migration velocity model is accurate, but it is more sensitive to the velocity errors, 2) the regularized plane-wave LSM is more robust in the presence of velocity errors, and 3) LSM achieves both computational and IO saving by plane-wave encoding compared to shot-domain LSM for the models tested.

Effects of regular Tai Chi practice and jogging on neuromuscular reaction during lateral postural control in older people.

Science.gov (United States)

Wang, Shao-Jun; Xu, Dong-Qing; Li, Jing-Xian

2017-01-01

This study examined the effects of regular Tai Chi practice and jogging on the neuromuscular activity of the trunk, hip, and ankle joint muscles of older people during lateral postural perturbation. A total of 42 older people participated in the study and formed the Tai Chi, jogging, and sedentary control groups. Electromyography signals were collected from the peroneus longus, anterior tibialis, gluteus medius, and erector spinae during unpredictable mediolateral perturbation. The Tai Chi group exhibited significantly faster latencies of the tibialis anterior and erector spinae than the control group. The jogging group showed a significantly shorter neuromuscular reaction time of the erector spinae than the control group. No significant difference was observed between the Tai Chi and jogging groups. Long-term regular Tai Chi practice enhanced the neuromuscular reaction of the erector spinae and tibialis anterior to lateral perturbation and will help timely posture correction when lateral postural distributions occur.

Regular and context-free nominal traces

DEFF Research Database (Denmark)

Degano, Pierpaolo; Ferrari, Gian-Luigi; Mezzetti, Gianluca

2017-01-01

Two kinds of automata are presented, for recognising new classes of regular and context-free nominal languages. We compare their expressive power with analogous proposals in the literature, showing that they express novel classes of languages. Although many properties of classical languages hold ...

Stabilization, pole placement, and regular implementability

NARCIS (Netherlands)

Belur, MN; Trentelman, HL

In this paper, we study control by interconnection of linear differential systems. We give necessary and sufficient conditions for regular implementability of a-given linear, differential system. We formulate the problems of stabilization and pole placement as problems of finding a suitable,

The effect of regular medication on the outcome of paracetamol poisoning

DEFF Research Database (Denmark)

Schmidt, L E; Dalhoff, K

2002-01-01

BACKGROUND: Patients admitted with paracetamol overdose frequently receive one or more types of regular medication that may affect the outcome of the paracetamol intoxication. AIM: To describe the use of regular medication in patients with paracetamol poisoning and to evaluate its effects...... on morbidity and mortality. METHODS: Seven hundred and thirty-seven consecutive patients admitted with paracetamol poisoning were studied and the use of regular medication was recorded. The relative risk of hepatic encephalopathy, death or liver transplantation, severe hepatic dysfunction and severe...... hepatocellular injury was evaluated by multivariate analysis. RESULTS: Regular medication was received by 332 patients (45%). Medication with benzodiazepines (105 cases), antidepressants (100 cases), neuroleptics (75 cases), paracetamol (58 cases), oral contraceptives (51 cases), beta-agonists (40 cases), opioid...

Regularity dimension of sequences and its application to phylogenetic tree reconstruction

International Nuclear Information System (INIS)

Pham, Tuan D.

2012-01-01

The concept of dimension is a central development of chaos theory for studying nonlinear dynamical systems. Different types of dimensions have been derived to interpret different geometrical or physical observations. Approximate entropy and its modified methods have been introduced for studying regularity and complexity of time-series data in physiology and biology. Here, the concept of power laws and entropy measure are adopted to develop the regularity dimension of sequences to model a mathematical relationship between the frequency with which information about signal regularity changes in various scales. The proposed regularity dimension is applied to reconstruct phylogenetic trees using mitochondrial DNA (mtDNA) sequences for the family Hominidae, which can be validated according to the hypothesized evolutionary relationships between organisms.

Automatic Traffic Data Collection under Varying Lighting and Temperature Conditions in Multimodal Environments: Thermal versus Visible Spectrum Video-Based Systems

Directory of Open Access Journals (Sweden)

Ting Fu

2017-01-01

Full Text Available Vision-based monitoring systems using visible spectrum (regular video cameras can complement or substitute conventional sensors and provide rich positional and classification data. Although new camera technologies, including thermal video sensors, may improve the performance of digital video-based sensors, their performance under various conditions has rarely been evaluated at multimodal facilities. The purpose of this research is to integrate existing computer vision methods for automated data collection and evaluate the detection, classification, and speed measurement performance of thermal video sensors under varying lighting and temperature conditions. Thermal and regular video data was collected simultaneously under different conditions across multiple sites. Although the regular video sensor narrowly outperformed the thermal sensor during daytime, the performance of the thermal sensor is significantly better for low visibility and shadow conditions, particularly for pedestrians and cyclists. Retraining the algorithm on thermal data yielded an improvement in the global accuracy of 48%. Thermal speed measurements were consistently more accurate than for the regular video at daytime and nighttime. Thermal video is insensitive to lighting interference and pavement temperature, solves issues associated with visible light cameras for traffic data collection, and offers other benefits such as privacy, insensitivity to glare, storage space, and lower processing requirements.

Long-Term Collections

CERN Multimedia

Staff Association

2016-01-01

45 years helping in developing countries! CERN personnel have been helping the least fortunate people on the planet since 1971. How? With the Long-Term Collections! Dear Colleagues, The Staff Association’s Long-Term Collections (LTC) Committee is delighted to share this important milestone in the life of our Laboratory with you. Indeed, whilst the name of CERN is known worldwide for scientific discoveries, it also shines in the many humanitarian projects which have been supported by the LTC since 1971. Several schools and clinics, far and wide, carry its logo... Over the past 45 years, 74 projects have been supported (9 of which are still ongoing). This all came from a group of colleagues who wanted to share a little of what life offered them here at CERN, in this haven of mutual understanding, peace and security, with those who were less fortunate elsewhere. Thus, the LTC were born... Since then, we have worked as a team to maintain the dream of these visionaries, with the help of regular donat...

Snacks, beverages, vending machines, and school stores: a comparison of alternative and regular schools in Minnesota, 2002 to 2008.

Science.gov (United States)

Kubik, Martha Y; Davey, Cynthia; MacLehose, Richard F; Coombes, Brandon; Nanney, Marilyn S

2015-01-01

In US secondary schools, vending machines and school stores are a common source of low-nutrient, energy-dense snacks and beverages, including sugar-sweetened beverages, high-fat salty snacks, and candy. However, little is known about the prevalence of these food practices in alternative schools, which are educational settings for students at risk of academic failure due to truancy, school expulsion, and behavior problems. Nationwide, more than 5,000 alternative schools enroll about one-half million students who are disproportionately minority and low-income youth. Principal survey data from a cross-sectional sample of alternative (n=104) and regular (n=339) schools collected biennially from 2002-2008 as part of the Centers for Disease Control and Prevention Minnesota School Health Profiles were used to assess and compare food practice prevalence over time. Generalized estimating equation models were used to estimate prevalence, adjusting for school demographics. Over time, food practice prevalence decreased significantly for both alternative and regular schools, although declines were mostly modest. However, the decrease in high-fat, salty snacks was significantly less for alternative than regular schools (-22.9% vs -42.2%; Pvending machines and school stores in alternative schools than regular schools, which may contribute to increased snacking behavior among students and extra consumption of salt, fat, and sugar. Study findings support the need to include alternative schools in future efforts that aim to reform the school food environment. Copyright © 2015 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Degree Associated Edge Reconstruction Number of Graphs with Regular Pruned Graph

Directory of Open Access Journals (Sweden)

P. Anusha Devi

2015-10-01

Full Text Available An ecard of a graph $G$ is a subgraph formed by deleting an edge. A da-ecard specifies the degree of the deleted edge along with the ecard. The degree associated edge reconstruction number of a graph $G,~dern(G,$ is the minimum number of da-ecards that uniquely determines $G.$  The adversary degree associated edge reconstruction number of a graph $G, adern(G,$ is the minimum number $k$ such that every collection of $k$ da-ecards of $G$ uniquely determines $G.$ The maximal subgraph without end vertices of a graph $G$ which is not a tree is the pruned graph of $G.$ It is shown that $dern$ of complete multipartite graphs and some connected graphs with regular pruned graph is $1$ or $2.$ We also determine $dern$ and $adern$ of corona product of standard graphs.

Regularities of radiation heredity

International Nuclear Information System (INIS)

Skakov, M.K.; Melikhov, V.D.

2001-01-01

One analyzed regularities of radiation heredity in metals and alloys. One made conclusion about thermodynamically irreversible changes in structure of materials under irradiation. One offers possible ways of heredity transmittance of radiation effects at high-temperature transformations in the materials. Phenomenon of radiation heredity may be turned to practical use to control structure of liquid metal and, respectively, structure of ingot via preliminary radiation treatment of charge. Concentration microheterogeneities in material defect structure induced by preliminary irradiation represent the genetic factor of radiation heredity [ru

Regularity of Minimal Surfaces

CERN Document Server

Dierkes, Ulrich; Tromba, Anthony J; Kuster, Albrecht

2010-01-01

"Regularity of Minimal Surfaces" begins with a survey of minimal surfaces with free boundaries. Following this, the basic results concerning the boundary behaviour of minimal surfaces and H-surfaces with fixed or free boundaries are studied. In particular, the asymptotic expansions at interior and boundary branch points are derived, leading to general Gauss-Bonnet formulas. Furthermore, gradient estimates and asymptotic expansions for minimal surfaces with only piecewise smooth boundaries are obtained. One of the main features of free boundary value problems for minimal surfaces is t

RES: Regularized Stochastic BFGS Algorithm

Science.gov (United States)

Mokhtari, Aryan; Ribeiro, Alejandro

2014-12-01

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.

A Sim(2 invariant dimensional regularization

Directory of Open Access Journals (Sweden)

J. Alfaro

2017-09-01

Full Text Available 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.

Combining kernel matrix optimization and regularization to improve particle size distribution retrieval

Science.gov (United States)

Ma, Qian; Xia, Houping; Xu, Qiang; Zhao, Lei

2018-05-01

A new method combining Tikhonov regularization and kernel matrix optimization by multi-wavelength incidence is proposed for retrieving particle size distribution (PSD) in an independent model with improved accuracy and stability. In comparison to individual regularization or multi-wavelength least squares, the proposed method exhibited better anti-noise capability, higher accuracy and stability. While standard regularization typically makes use of the unit matrix, it is not universal for different PSDs, particularly for Junge distributions. Thus, a suitable regularization matrix was chosen by numerical simulation, with the second-order differential matrix found to be appropriate for most PSD types.

12 CFR 407.3 - Procedures applicable to regularly scheduled meetings.

Science.gov (United States)

2010-01-01

... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Procedures applicable to regularly scheduled meetings. 407.3 Section 407.3 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES REGULATIONS GOVERNING PUBLIC OBSERVATION OF EX-IM BANK MEETINGS § 407.3 Procedures applicable to regularly scheduled...

The Temporal Dynamics of Regularity Extraction in Non-Human Primates

Science.gov (United States)

Minier, Laure; Fagot, Joël; Rey, Arnaud

2016-01-01

Extracting the regularities of our environment is one of our core cognitive abilities. To study the fine-grained dynamics of the extraction of embedded regularities, a method combining the advantages of the artificial language paradigm (Saffran, Aslin, & Newport, [Saffran, J. R., 1996]) and the serial response time task (Nissen & Bullemer,…

Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer’s Disease

Science.gov (United States)

Jie, Biao; Cheng, Bo

2014-01-01

Accurate diagnosis of Alzheimer’s disease (AD), as well as its pro-dromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method. PMID:24505676

Heat adaptation from regular hot water immersion decreases proinflammatory responses, HSP70 expression, and physical heat stress.

Science.gov (United States)

Yang, Fwu-Lin; Lee, Chia-Chi; Subeq, Yi-Maun; Lee, Chung-Jen; Ke, Chun-Yen; Lee, Ru-Ping

2017-10-01

Hot-water immersion (HWI) is a type of thermal therapy for treating various diseases. In our study, the physiological responses to occasional and regular HWI have been explored. The rats were divided into a control group, occasional group (1D), and regular group (7D). The 1D and 7D groups received 42°C during 15mins HWI for 1 and 7 days, respectively. The blood samples were collected for proinflammatory cytokines examinations, the heart, liver and kidney were excised for subsequent IHC analysis to measure the level of heat shock protein 70 (HSP70). The results revealed that the body temperature increased significantly during HWI on Day 3 and significantly declined on Days 6 and 7. For the 7D group, body weight, heart rate, hematocrit, platelet, osmolarity, and lactate level were lower than those in the 1D group. Furthermore, the levels of granulocyte counts, tumor necrosis factor-α, and interleukin-6 were lower in the 7D group than in the 1D group. The induction of HSP70 in the 1D group was higher than in the other groups. Physiological responses to occasional HWI are disadvantageous because of heat stress. However, adaptation to heat from regular HWI resulted in decreased proinflammatory responses and physical heat stress. Copyright © 2017 Elsevier Ltd. All rights reserved.

Regularity of p(ṡ)-superharmonic functions, the Kellogg property and semiregular boundary points

Science.gov (United States)

Adamowicz, Tomasz; Björn, Anders; Björn, Jana

2014-11-01

We study various boundary and inner regularity questions for $p(\\cdot)$-(super)harmonic functions in Euclidean domains. In particular, we prove the Kellogg property and introduce a classification of boundary points for $p(\\cdot)$-harmonic functions into three disjoint classes: regular, semiregular and strongly irregular points. Regular and especially semiregular points are characterized in many ways. The discussion is illustrated by examples. Along the way, we present a removability result for bounded $p(\\cdot)$-harmonic functions and give some new characterizations of $W^{1, p(\\cdot)}_0$ spaces. We also show that $p(\\cdot)$-superharmonic functions are lower semicontinuously regularized, and characterize them in terms of lower semicontinuously regularized supersolutions.

Regular black holes in Einstein-Gauss-Bonnet gravity

Science.gov (United States)

Ghosh, Sushant G.; Singh, Dharm Veer; Maharaj, Sunil D.

2018-05-01

Einstein-Gauss-Bonnet theory, a natural generalization of general relativity to a higher dimension, admits a static spherically symmetric black hole which was obtained by Boulware and Deser. This black hole is similar to its general relativity counterpart with a curvature singularity at r =0 . We present an exact 5D regular black hole metric, with parameter (k >0 ), that interpolates between the Boulware-Deser black hole (k =0 ) and the Wiltshire charged black hole (r ≫k ). Owing to the appearance of the exponential correction factor (e-k /r2), responsible for regularizing the metric, the thermodynamical quantities are modified, and it is demonstrated that the Hawking-Page phase transition is achievable. The heat capacity diverges at a critical radius r =rC, where incidentally the temperature is maximum. Thus, we have a regular black hole with Cauchy and event horizons, and evaporation leads to a thermodynamically stable double-horizon black hole remnant with vanishing temperature. The entropy does not satisfy the usual exact horizon area result of general relativity.

Constrained Perturbation Regularization Approach for Signal Estimation Using Random Matrix Theory

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-10-06

In this work, we propose a new regularization approach for linear least-squares problems with random matrices. In the proposed constrained perturbation regularization approach, an artificial perturbation matrix with a bounded norm is forced into the system model matrix. This perturbation is introduced to improve the singular-value structure of the model matrix and, hence, the solution of the estimation problem. Relying on the randomness of the model matrix, a number of deterministic equivalents from random matrix theory are applied to derive the near-optimum regularizer that minimizes the mean-squared error of the estimator. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods for various estimated signal characteristics. In addition, simulations show that our approach is robust in the presence of model uncertainty.

Critical Behavior of the Annealed Ising Model on Random Regular Graphs

Science.gov (United States)

Can, Van Hao

2017-11-01

In Giardinà et al. (ALEA Lat Am J Probab Math Stat 13(1):121-161, 2016), the authors have defined an annealed Ising model on random graphs and proved limit theorems for the magnetization of this model on some random graphs including random 2-regular graphs. Then in Can (Annealed limit theorems for the Ising model on random regular graphs, arXiv:1701.08639, 2017), we generalized their results to the class of all random regular graphs. In this paper, we study the critical behavior of this model. In particular, we determine the critical exponents and prove a non standard limit theorem stating that the magnetization scaled by n^{3/4} converges to a specific random variable, with n the number of vertices of random regular graphs.

Prediction of the contact sensitizing potential of chemicals using analysis of gene expression changes in human THP-1 monocytes.

Science.gov (United States)

Arkusz, Joanna; Stępnik, Maciej; Sobala, Wojciech; Dastych, Jarosław

2010-11-10

The aim of this study was to find differentially regulated genes in THP-1 monocytic cells exposed to sensitizers and nonsensitizers and to investigate if such genes could be reliable markers for an in vitro predictive method for the identification of skin sensitizing chemicals. Changes in expression of 35 genes in the THP-1 cell line following treatment with chemicals of different sensitizing potential (from nonsensitizers to extreme sensitizers) were assessed using real-time PCR. Verification of 13 candidate genes by testing a large number of chemicals (an additional 22 sensitizers and 8 nonsensitizers) revealed that prediction of contact sensitization potential was possible based on evaluation of changes in three genes: IL8, HMOX1 and PAIMP1. In total, changes in expression of these genes allowed correct detection of sensitization potential of 21 out of 27 (78%) test sensitizers. The gene expression levels inside potency groups varied and did not allow estimation of sensitization potency of test chemicals. Results of this study indicate that evaluation of changes in expression of proposed biomarkers in THP-1 cells could be a valuable model for preliminary screening of chemicals to discriminate an appreciable majority of sensitizers from nonsensitizers. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Sleep Spindles in the Right Hemisphere Support Awareness of Regularities and Reflect Pre-Sleep Activations.

Science.gov (United States)

Yordanova, Juliana; Kolev, Vasil; Bruns, Eike; Kirov, Roumen; Verleger, Rolf

2017-11-01

The present study explored the sleep mechanisms which may support awareness of hidden regularities. Before sleep, 53 participants learned implicitly a lateralized variant of the serial response-time task in order to localize sensorimotor encoding either in the left or right hemisphere and induce implicit regularity representations. Electroencephalographic (EEG) activity was recorded at multiple electrodes during both task performance and sleep, searching for lateralized traces of the preceding activity during learning. Sleep EEG analysis focused on region-specific slow (9-12 Hz) and fast (13-16 Hz) sleep spindles during nonrapid eye movement sleep. Fast spindle activity at those motor regions that were activated during learning increased with the amount of postsleep awareness. Independently of side of learning, spindle activity at right frontal and fronto-central regions was involved: there, fast spindles increased with the transformation of sequence knowledge from implicit before sleep to explicit after sleep, and slow spindles correlated with individual abilities of gaining awareness. These local modulations of sleep spindles corresponded to regions with greater presleep activation in participants with postsleep explicit knowledge. Sleep spindle mechanisms are related to explicit awareness (1) by tracing the activation of motor cortical and right-hemisphere regions which had stronger involvement already during learning and (2) by recruitment of individually consolidated processing modules in the right hemisphere. The integration of different sleep spindle mechanisms with functional states during wake collectively supports the gain of awareness of previously experienced regularities, with a special role for the right hemisphere. © Sleep Research Society 2017. Published by Oxford University Press [on behalf of the Sleep Research Society].

Spent fuel management: Current status and prospects 1997. Proceedings of a regular advisory group meeting

International Nuclear Information System (INIS)

1998-03-01

Spent fuel management has always been one of the important stages in the nuclear fuel cycle and it is still most vital problems common to all countries with nuclear reactors. It begins with the discharge of spent fuel from a power or a research reactor and ends with its ultimate disposition. Two options exist - an open, once-through cycle with direct disposal of the spent fuel and a closed cycle with reprocessing of the spent fuel, recycling of reprocessed plutonium and uranium in new mixed oxide fuels and disposal of the radioactive waste. Continuous attention is being given by the IAEA to the collection, analysis and exchange of information on spent fuel management. Its role in this area is to provide a forum for exchanging information and to co-ordinate and to encourage closer co-operation among Member States in certain research and development activities that are of common interest. Spent fuel management is recognized as a high priority IAEA activity. The Regular Advisory Group on Spent Fuel Management was established in 1982. The objective of the Regular Advisory Group is to serve as a means of exchanging information on the current status and progress of national programmes on spent fuel management and to provide advice to the IAEA. The results of the last Regular Advisory Group meeting (9-12 September 1997) are reflected in this report. It gives an overview of the status of spent fuel management programmes in a number of countries, a description of the current status and prospects of activities in this field and recommendations of the participants

The relationship between synchronization and percolation for regular networks

Science.gov (United States)

Li, Zhe; Ren, Tao; Xu, Yanjie; Jin, Jianyu

2018-02-01

Synchronization and percolation are two essential phenomena in complex dynamical networks. They have been studied widely, but previously treated as unrelated. In this paper, the relationship between synchronization and percolation are revealed for regular networks. Firstly, we discovered a bridge between synchronization and percolation by using the eigenvalues of the Laplacian matrix to describe the synchronizability and using the eigenvalues of the adjacency matrix to describe the percolation threshold. Then, we proposed a method to find the relationship for regular networks based on the topology of networks. Particularly, if the degree distribution of the network is subject to delta function, we show that only the eigenvalues of the adjacency matrix need to be calculated. Finally, several examples are provided to demonstrate how to apply our proposed method to discover the relationship between synchronization and percolation for regular networks.

Annotation of Regular Polysemy

DEFF Research Database (Denmark)

Martinez Alonso, Hector

Regular polysemy has received a lot of attention from the theory of lexical semantics and from computational linguistics. However, there is no consensus on how to represent the sense of underspecified examples at the token level, namely when annotating or disambiguating senses of metonymic words...... and metonymic. We have conducted an analysis in English, Danish and Spanish. Later on, we have tried to replicate the human judgments by means of unsupervised and semi-supervised sense prediction. The automatic sense-prediction systems have been unable to find empiric evidence for the underspecified sense, even...

Viscous Regularization of the Euler Equations and Entropy Principles

KAUST Repository

Guermond, Jean-Luc

2014-03-11

This paper investigates a general class of viscous regularizations of the compressible Euler equations. A unique regularization is identified that is compatible with all the generalized entropies, à la [Harten et al., SIAM J. Numer. Anal., 35 (1998), pp. 2117-2127], and satisfies the minimum entropy principle. A connection with a recently proposed phenomenological model by [H. Brenner, Phys. A, 370 (2006), pp. 190-224] is made. © 2014 Society for Industrial and Applied Mathematics.

Use of regularized algebraic methods in tomographic reconstruction

International Nuclear Information System (INIS)

Koulibaly, P.M.; Darcourt, J.; Blanc-Ferraud, L.; Migneco, O.; Barlaud, M.

1997-01-01

The algebraic methods are used in emission tomography to facilitate the compensation of attenuation and of Compton scattering. We have tested on a phantom the use of a regularization (a priori introduction of information), as well as the taking into account of spatial resolution variation with the depth (SRVD). Hence, we have compared the performances of the two methods by back-projection filtering (BPF) and of the two algebraic methods (AM) in terms of FWHM (by means of a point source), of the reduction of background noise (σ/m) on the homogeneous part of Jaszczak's phantom and of reconstruction speed (time unit = BPF). The BPF methods make use of a grade filter (maximal resolution, no noise treatment), single or associated with a Hann's low-pass (f c = 0.4), as well as of an attenuation correction. The AM which embody attenuation and scattering corrections are, on one side, the OS EM (Ordered Subsets, partitioning and rearranging of the projection matrix; Expectation Maximization) without regularization or SRVD correction, and, on the other side, the OS MAP EM (Maximum a posteriori), regularized and embodying the SRVD correction. A table is given containing for each used method (grade, Hann, OS EM and OS MAP EM) the values of FWHM, σ/m and time, respectively. One can observe that the OS MAP EM algebraic method allows ameliorating both the resolution, by taking into account the SRVD in the reconstruction process and noise treatment by regularization. In addition, due to the OS technique the reconstruction times are acceptable

Ensemble Kalman filter regularization using leave-one-out data cross-validation

KAUST Repository

Rayo Schiappacasse, Lautaro Jeró nimo; Hoteit, Ibrahim

2012-01-01

In this work, the classical leave-one-out cross-validation method for selecting a regularization parameter for the Tikhonov problem is implemented within the EnKF framework. Following the original concept, the regularization parameter is selected

Constrained Perturbation Regularization Approach for Signal Estimation Using Random Matrix Theory

KAUST Repository

Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Kammoun, Abla; Al-Naffouri, Tareq Y.

2016-01-01

random matrix theory are applied to derive the near-optimum regularizer that minimizes the mean-squared error of the estimator. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods for various

Decentralized formation of random regular graphs for robust multi-agent networks

KAUST Repository

Yazicioglu, A. Yasin; Egerstedt, Magnus; Shamma, Jeff S.

2014-01-01

systems. One family of robust graphs is the random regular graphs. In this paper, we present a locally applicable reconfiguration scheme to build random regular graphs through self-organization. For any connected initial graph, the proposed scheme

The Effects of Regular Exercise on the Physical Fitness Levels

Science.gov (United States)

Kirandi, Ozlem

2016-01-01

The purpose of the present research is investigating the effects of regular exercise on the physical fitness levels among sedentary individuals. The total of 65 sedentary male individuals between the ages of 19-45, who had never exercises regularly in their lives, participated in the present research. Of these participants, 35 wanted to be…

Thermodynamics of a class of regular black holes with a generalized uncertainty principle

Science.gov (United States)

Maluf, R. V.; Neves, Juliano C. S.

2018-05-01

In this article, we present a study on thermodynamics of a class of regular black holes. Such a class includes Bardeen and Hayward regular black holes. We obtained thermodynamic quantities like the Hawking temperature, entropy, and heat capacity for the entire class. As part of an effort to indicate some physical observable to distinguish regular black holes from singular black holes, we suggest that regular black holes are colder than singular black holes. Besides, contrary to the Schwarzschild black hole, that class of regular black holes may be thermodynamically stable. From a generalized uncertainty principle, we also obtained the quantum-corrected thermodynamics for the studied class. Such quantum corrections provide a logarithmic term for the quantum-corrected entropy.

Manifold regularized multitask learning for semi-supervised multilabel image classification.

Science.gov (United States)

Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

2013-02-01

It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

Effects of Irregular Bridge Columns and Feasibility of Seismic Regularity

Science.gov (United States)

Thomas, Abey E.

2018-05-01

Bridges with unequal column height is one of the main irregularities in bridge design particularly while negotiating steep valleys, making the bridges vulnerable to seismic action. The desirable behaviour of bridge columns towards seismic loading is that, they should perform in a regular fashion, i.e. the capacity of each column should be utilized evenly. But, this type of behaviour is often missing when the column heights are unequal along the length of the bridge, allowing short columns to bear the maximum lateral load. In the present study, the effects of unequal column height on the global seismic performance of bridges are studied using pushover analysis. Codes such as CalTrans (Engineering service center, earthquake engineering branch, 2013) and EC-8 (EN 1998-2: design of structures for earthquake resistance. Part 2: bridges, European Committee for Standardization, Brussels, 2005) suggests seismic regularity criterion for achieving regular seismic performance level at all the bridge columns. The feasibility of adopting these seismic regularity criterions along with those mentioned in literatures will be assessed for bridges designed as per the Indian Standards in the present study.

Fermion-number violation in regularizations that preserve fermion-number symmetry

Science.gov (United States)

Golterman, Maarten; Shamir, Yigal

2003-01-01

There exist both continuum and lattice regularizations of gauge theories with fermions which preserve chiral U(1) invariance (“fermion number”). Such regularizations necessarily break gauge invariance but, in a covariant gauge, one recovers gauge invariance to all orders in perturbation theory by including suitable counterterms. At the nonperturbative level, an apparent conflict then arises between the chiral U(1) symmetry of the regularized theory and the existence of ’t Hooft vertices in the renormalized theory. The only possible resolution of the paradox is that the chiral U(1) symmetry is broken spontaneously in the enlarged Hilbert space of the covariantly gauge-fixed theory. The corresponding Goldstone pole is unphysical. The theory must therefore be defined by introducing a small fermion-mass term that breaks explicitly the chiral U(1) invariance and is sent to zero after the infinite-volume limit has been taken. Using this careful definition (and a lattice regularization) for the calculation of correlation functions in the one-instanton sector, we show that the ’t Hooft vertices are recovered as expected.

Regular School Teachers’ Concerns and Perceived Barriers to Implement Inclusive Education in New Delhi, India

Directory of Open Access Journals (Sweden)

Nisha Bhatnagar

2014-07-01

Full Text Available Since the passage of The Persons with Disabilities (PWD Act in 1995 and subsequent implementation of various policies and programs by the Indian government to enhance the participation of students with disabilities in regular schools, there has been a steady growth of inclusive education. Such initiatives, however, have placed new demands on schools, especially on teachers who have the major responsibility for implementing inclusion at the classroom level. Literature from other countries indicates that for inclusion to be successful, it is essential that classroom teachers’ concerns about implementing such programs be identified and systematically addressed. Unfortunately, there is a paucity of research about teacher concerns regarding inclusive education in India. This study was undertaken to identify the concerns and perceived barriers of regular school teachers in Delhi, India about the inclusion of students with disabilities. Respondents were secondary school teachers working in schools in Delhi that were involved in teaching special needs children. Two focus group interviews and 20 individual semi-structured interviews were conducted to collect data from the participants. The flexible qualitative analysis program QRS NVivo was utilized for data analysis. Three concerns and eleven barrier themes emerged

78 FR 25059 - Proposed Information Collection; Comment Request; Business and Professional Classification Report...

Science.gov (United States)

2013-04-29

... business activity, company structure, size, and business operations. This information is used to update the.... Form Number: SQ-CLASS. Type of Review: Regular. Affected Public: Businesses and other organizations in... DEPARTMENT OF COMMERCE Census Bureau Proposed Information Collection; Comment Request; Business...

Construction of normal-regular decisions of Bessel typed special system

Science.gov (United States)

Tasmambetov, Zhaksylyk N.; Talipova, Meiramgul Zh.

2017-09-01

Studying a special system of differential equations in the separate production of the second order is solved by the degenerate hypergeometric function reducing to the Bessel functions of two variables. To construct a solution of this system near regular and irregular singularities, we use the method of Frobenius-Latysheva applying the concepts of rank and antirank. There is proved the basic theorem that establishes the existence of four linearly independent solutions of studying system type of Bessel. To prove the existence of normal-regular solutions we establish necessary conditions for the existence of such solutions. The existence and convergence of a normally regular solution are shown using the notion of rank and antirank.

3D first-arrival traveltime tomography with modified total variation regularization

Science.gov (United States)

Jiang, Wenbin; Zhang, Jie

2018-02-01

Three-dimensional (3D) seismic surveys have become a major tool in the exploration and exploitation of hydrocarbons. 3D seismic first-arrival traveltime tomography is a robust method for near-surface velocity estimation. A common approach for stabilizing the ill-posed inverse problem is to apply Tikhonov regularization to the inversion. However, the Tikhonov regularization method recovers smooth local structures while blurring the sharp features in the model solution. We present a 3D first-arrival traveltime tomography method with modified total variation (MTV) regularization to preserve sharp velocity contrasts and improve the accuracy of velocity inversion. To solve the minimization problem of the new traveltime tomography method, we decouple the original optimization problem into two following subproblems: a standard traveltime tomography problem with the traditional Tikhonov regularization and a L2 total variation problem. We apply the conjugate gradient method and split-Bregman iterative method to solve these two subproblems, respectively. Our synthetic examples show that the new method produces higher resolution models than the conventional traveltime tomography with Tikhonov regularization. We apply the technique to field data. The stacking section shows significant improvements with static corrections from the MTV traveltime tomography.

Annotation of regular polysemy and underspecification

DEFF Research Database (Denmark)

Martínez Alonso, Héctor; Pedersen, Bolette Sandford; Bel, Núria

2013-01-01

We present the result of an annotation task on regular polysemy for a series of seman- tic classes or dot types in English, Dan- ish and Spanish. This article describes the annotation process, the results in terms of inter-encoder agreement, and the sense distributions obtained with two methods...

Supervised scale-regularized linear convolutionary filters

DEFF Research Database (Denmark)

Loog, Marco; Lauze, Francois Bernard

2017-01-01

also be solved relatively efficient. All in all, the idea is to properly control the scale of a trained filter, which we solve by introducing a specific regularization term into the overall objective function. We demonstrate, on an artificial filter learning problem, the capabil- ities of our basic...

Formation factor of regular porous pattern in poly-α-methylstyrene film

International Nuclear Information System (INIS)

Yang Ruizhuang; Xu Jiajing; Gao Cong; Ma Shuang; Chen Sufen; Luo Xuan; Fang Yu; Li Bo

2015-01-01

Regular poly-α-methylstyrene (PAMS) porous film with macron-sized cells was prepared by casting the solution in the condition with high humidity. In this paper, the effects of the molecular weight of PAMS, PAMS concentration, humidity, temperature, volatile solvents and the thickness of liquid of solution on formation of regular porous pattern in PAMS film were discussed. The results show that these factors significantly affect the pore size and the pore distribution. The capillary force and Benard-Marangoni convection are main driving forces for the water droplet moving and making pores regular arrangement. (authors)

Ensemble Kalman filter regularization using leave-one-out data cross-validation

KAUST Repository

Rayo Schiappacasse, Lautaro Jerónimo

2012-09-19

In this work, the classical leave-one-out cross-validation method for selecting a regularization parameter for the Tikhonov problem is implemented within the EnKF framework. Following the original concept, the regularization parameter is selected such that it minimizes the predictive error. Some ideas about the implementation, suitability and conceptual interest of the method are discussed. Finally, what will be called the data cross-validation regularized EnKF (dCVr-EnKF) is implemented in a 2D 2-phase synthetic oil reservoir experiment and the results analyzed.

The persistence of the attentional bias to regularities in a changing environment.

Science.gov (United States)

Yu, Ru Qi; Zhao, Jiaying

2015-10-01

The environment often is stable, but some aspects may change over time. The challenge for the visual system is to discover and flexibly adapt to the changes. We examined how attention is shifted in the presence of changes in the underlying structure of the environment. In six experiments, observers viewed four simultaneous streams of objects while performing a visual search task. In the first half of each experiment, the stream in the structured location contained regularities, the shapes in the random location were randomized, and gray squares appeared in two neutral locations. In the second half, the stream in the structured or the random location may change. In the first half of all experiments, visual search was facilitated in the structured location, suggesting that attention was consistently biased toward regularities. In the second half, this bias persisted in the structured location when no change occurred (Experiment 1), when the regularities were removed (Experiment 2), or when new regularities embedded in the original or novel stimuli emerged in the previously random location (Experiments 3 and 6). However, visual search was numerically but no longer reliably faster in the structured location when the initial regularities were removed and new regularities were introduced in the previously random location (Experiment 4), or when novel random stimuli appeared in the random location (Experiment 5). This suggests that the attentional bias was weakened. Overall, the results demonstrate that the attentional bias to regularities was persistent but also sensitive to changes in the environment.

Variational regularization of 3D data experiments with Matlab

CERN Document Server

Montegranario, Hebert

2014-01-01

Variational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as an inverse problem that can be solved by Tikhonov regularization. The proposed solutions are generalizations of one-dimensional splines, applicable to n-dimensional data and the central idea is that these splines can be obtained by regularization theory using a trade-off between the fidelity of the data and smoothness properties.As a foundation, the authors present a comprehensive guide to the necessary fundamentals of functional analysis and variational calculus, as well as splines. The implementation and numerical experiments are illustrated using MATLAB®. The book also includes the necessary theoretical background for approximation methods and some details of the computer implementation of the algorithms. A working knowledge of multivariable calculus and basic vector and matrix methods should serve as an adequat...

Structural characterization of the packings of granular regular polygons.

Science.gov (United States)

Wang, Chuncheng; Dong, Kejun; Yu, Aibing

2015-12-01

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

A constrained regularization method for inverting data represented by linear algebraic or integral equations

Science.gov (United States)

Provencher, Stephen W.

1982-09-01

CONTIN is a portable Fortran IV package for inverting noisy linear operator equations. These problems occur in the analysis of data from a wide variety experiments. They are generally ill-posed problems, which means that errors in an unregularized inversion are unbounded. Instead, CONTIN seeks the optimal solution by incorporating parsimony and any statistical prior knowledge into the regularizor and absolute prior knowledge into equallity and inequality constraints. This can be greatly increase the resolution and accuracyh of the solution. CONTIN is very flexible, consisting of a core of about 50 subprograms plus 13 small "USER" subprograms, which the user can easily modify to specify special-purpose constraints, regularizors, operator equations, simulations, statistical weighting, etc. Specjial collections of USER subprograms are available for photon correlation spectroscopy, multicomponent spectra, and Fourier-Bessel, Fourier and Laplace transforms. Numerically stable algorithms are used throughout CONTIN. A fairly precise definition of information content in terms of degrees of freedom is given. The regularization parameter can be automatically chosen on the basis of an F-test and confidence region. The interpretation of the latter and of error estimates based on the covariance matrix of the constrained regularized solution are discussed. The strategies, methods and options in CONTIN are outlined. The program itself is described in the following paper.

Regularization and the potential of effective field theory in nucleon-nucleon scattering

International Nuclear Information System (INIS)

Phillips, D.R.

1998-04-01

This paper examines the role that regularization plays in the definition of the potential used in effective field theory (EFT) treatments of the nucleon-nucleon interaction. The author considers N N scattering in S-wave channels at momenta well below the pion mass. In these channels (quasi-)bound states are present at energies well below the scale m π 2 /M expected from naturalness arguments. He asks whether, in the presence of such a shallow bound state, there is a regularization scheme which leads to an EFT potential that is both useful and systematic. In general, if a low-lying bound state is present then cutoff regularization leads to an EFT potential which is useful but not systematic, and dimensional regularization with minimal subtraction leads to one which is systematic but not useful. The recently-proposed technique of dimensional regularization with power-law divergence subtraction allows the definition of an EFT potential which is both useful and systematic

12 CFR 725.3 - Regular membership.

Science.gov (United States)

2010-01-01

... UNION ADMINISTRATION CENTRAL LIQUIDITY FACILITY § 725.3 Regular membership. (a) A natural person credit....5(b) of this part, and forwarding with its completed application funds equal to one-half of this... 1, 1979, is not required to forward these funds to the Facility until October 1, 1979. (3...

Regularization of Hamilton-Lagrangian guiding center theories

International Nuclear Information System (INIS)

Correa-Restrepo, D.; Wimmel, H.K.

1985-04-01

The Hamilton-Lagrangian guiding-center (G.C.) theories of Littlejohn, Wimmel, and Pfirsch show a singularity for B-fields with non-vanishing parallel curl at a critical value of vsub(parallel), which complicates applications. The singularity is related to a sudden breakdown, at a critical vsub(parallel), of gyration in the exact particle mechanics. While the latter is a real effect, the G.C. singularity can be removed. To this end a regularization method is defined that preserves the Hamilton-Lagrangian structure and the conservation theorems. For demonstration this method is applied to the standard G.C. theory (without polarization drift). Liouville's theorem and G.C. kinetic equations are also derived in regularized form. The method could equally well be applied to the case with polarization drift and to relativistic G.C. theory. (orig.)

Persistent low-grade inflammation and regular exercise

DEFF Research Database (Denmark)

Åström, Maj-brit; Feigh, Michael; Pedersen, Bente Klarlund

2010-01-01

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.......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...

Human visual system automatically represents large-scale sequential regularities.

Science.gov (United States)

Kimura, Motohiro; Widmann, Andreas; Schröger, Erich

2010-03-04

Our brain recordings reveal that large-scale sequential regularities defined across non-adjacent stimuli can be automatically represented in visual sensory memory. To show that, we adopted an auditory paradigm developed by Sussman, E., Ritter, W., and Vaughan, H. G. Jr. (1998). Predictability of stimulus deviance and the mismatch negativity. NeuroReport, 9, 4167-4170, Sussman, E., and Gumenyuk, V. (2005). Organization of sequential sounds in auditory memory. NeuroReport, 16, 1519-1523 to the visual domain by presenting task-irrelevant infrequent luminance-deviant stimuli (D, 20%) inserted among task-irrelevant frequent stimuli being of standard luminance (S, 80%) in randomized (randomized condition, SSSDSSSSSDSSSSD...) and fixed manners (fixed condition, SSSSDSSSSDSSSSD...). Comparing the visual mismatch negativity (visual MMN), an event-related brain potential (ERP) index of memory-mismatch processes in human visual sensory system, revealed that visual MMN elicited by deviant stimuli was reduced in the fixed compared to the randomized condition. Thus, the large-scale sequential regularity being present in the fixed condition (SSSSD) must have been represented in visual sensory memory. Interestingly, this effect did not occur in conditions with stimulus-onset asynchronies (SOAs) of 480 and 800 ms but was confined to the 160-ms SOA condition supporting the hypothesis that large-scale regularity extraction was based on perceptual grouping of the five successive stimuli defining the regularity. 2010 Elsevier B.V. All rights reserved.

Regularized semiclassical limits: Linear flows with infinite Lyapunov exponents

KAUST Repository

Athanassoulis, Agissilaos; Katsaounis, Theodoros; Kyza, Irene

2016-01-01

Semiclassical asymptotics for Schrödinger equations with non-smooth potentials give rise to ill-posed formal semiclassical limits. These problems have attracted a lot of attention in the last few years, as a proxy for the treatment of eigenvalue crossings, i.e. general systems. It has recently been shown that the semiclassical limit for conical singularities is in fact well-posed, as long as the Wigner measure (WM) stays away from singular saddle points. In this work we develop a family of refined semiclassical estimates, and use them to derive regularized transport equations for saddle points with infinite Lyapunov exponents, extending the aforementioned recent results. In the process we answer a related question posed by P.L. Lions and T. Paul in 1993. If we consider more singular potentials, our rigorous estimates break down. To investigate whether conical saddle points, such as -|x|, admit a regularized transport asymptotic approximation, we employ a numerical solver based on posteriori error control. Thus rigorous upper bounds for the asymptotic error in concrete problems are generated. In particular, specific phenomena which render invalid any regularized transport for -|x| are identified and quantified. In that sense our rigorous results are sharp. Finally, we use our findings to formulate a precise conjecture for the condition under which conical saddle points admit a regularized transport solution for the WM. © 2016 International Press.

Regularized semiclassical limits: Linear flows with infinite Lyapunov exponents

KAUST Repository

Athanassoulis, Agissilaos

2016-08-30

Semiclassical asymptotics for Schrödinger equations with non-smooth potentials give rise to ill-posed formal semiclassical limits. These problems have attracted a lot of attention in the last few years, as a proxy for the treatment of eigenvalue crossings, i.e. general systems. It has recently been shown that the semiclassical limit for conical singularities is in fact well-posed, as long as the Wigner measure (WM) stays away from singular saddle points. In this work we develop a family of refined semiclassical estimates, and use them to derive regularized transport equations for saddle points with infinite Lyapunov exponents, extending the aforementioned recent results. In the process we answer a related question posed by P.L. Lions and T. Paul in 1993. If we consider more singular potentials, our rigorous estimates break down. To investigate whether conical saddle points, such as -|x|, admit a regularized transport asymptotic approximation, we employ a numerical solver based on posteriori error control. Thus rigorous upper bounds for the asymptotic error in concrete problems are generated. In particular, specific phenomena which render invalid any regularized transport for -|x| are identified and quantified. In that sense our rigorous results are sharp. Finally, we use our findings to formulate a precise conjecture for the condition under which conical saddle points admit a regularized transport solution for the WM. © 2016 International Press.

Special needs students in regular education: do they affect their classmates?

NARCIS (Netherlands)

Ruijs, N.

2014-01-01

The impact on regular students is a prominent concern in the inclusive education debate. Recent studies find that the presence of students with special educational needs harms the achievement of regular students. This study investigates inclusive practices in Dutch primary and secondary education,

Stochastic dynamic modeling of regular and slow earthquakes

Science.gov (United States)

Aso, N.; Ando, R.; Ide, S.

2017-12-01

Both regular and slow earthquakes are slip phenomena on plate boundaries and are simulated by a (quasi-)dynamic modeling [Liu and Rice, 2005]. In these numerical simulations, spatial heterogeneity is usually considered not only for explaining real physical properties but also for evaluating the stability of the calculations or the sensitivity of the results on the condition. However, even though we discretize the model space with small grids, heterogeneity at smaller scales than the grid size is not considered in the models with deterministic governing equations. To evaluate the effect of heterogeneity at the smaller scales we need to consider stochastic interactions between slip and stress in a dynamic modeling. Tidal stress is known to trigger or affect both regular and slow earthquakes [Yabe et al., 2015; Ide et al., 2016], and such an external force with fluctuation can also be considered as a stochastic external force. A healing process of faults may also be stochastic, so we introduce stochastic friction law. In the present study, we propose a stochastic dynamic model to explain both regular and slow earthquakes. We solve mode III problem, which corresponds to the rupture propagation along the strike direction. We use BIEM (boundary integral equation method) scheme to simulate slip evolution, but we add stochastic perturbations in the governing equations, which is usually written in a deterministic manner. As the simplest type of perturbations, we adopt Gaussian deviations in the formulation of the slip-stress kernel, external force, and friction. By increasing the amplitude of perturbations of the slip-stress kernel, we reproduce complicated rupture process of regular earthquakes including unilateral and bilateral ruptures. By perturbing external force, we reproduce slow rupture propagation at a scale of km/day. The slow propagation generated by a combination of fast interaction at S-wave velocity is analogous to the kinetic theory of gasses: thermal

Generalized regular genus for manifolds with boundary

Directory of Open Access Journals (Sweden)

Paola Cristofori

2003-05-01

Full Text Available We introduce a generalization of the regular genus, a combinatorial invariant of PL manifolds ([10], which is proved to be strictly related, in dimension three, to generalized Heegaard splittings defined in [12].

76 FR 1602 - Proposed Information Collection; Comment Request; Scientific Research, Exempted Fishing, and...

Science.gov (United States)

2011-01-11

... educational activities with respect to Atlantic HMS. Since the Magnuson-Stevens Act does not consider... recreational fishing platforms. To regulate these fishing activities, NMFS needs information to determine the... Review: Regular submission (extension of a currently approved collection). Affected Public: Non-profit...

Comparing the Reliability of Regular Topologies on a Backbone Network. A Case Study

DEFF Research Database (Denmark)

Cecilio, Sergio Labeage; Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir

2009-01-01

The aim of this paper is to compare the reliability of regular topologies on a backbone network. The study is focused on a large-scale fiberoptic network. Different regular topological solutions as single ring, double ring or 4-Regular grid are applied to the case study, and compared in terms...

Regular periodical public disclosure obligations of public companies

Directory of Open Access Journals (Sweden)

Marjanski Vladimir

2011-01-01

Full Text Available Public companies in the capacity of capital market participants have the obligation to inform the public on their legal and financial status, their general business operations, as well as on the issuance of securities and other financial instruments. Such obligations may be divided into two groups: The first group consists of regular periodical public disclosures, such as the publication of financial reports (annual, semi-annual and quarterly, and the management's reports on the public company's business operations. The second group comprises the obligation of occasional (ad hoc public disclosure. The thesis analyses the obligation of public companies to inform the public in course of their regular reporting. The new Capital Market Law based on two EU Directives (the Transparency Directive and the Directive on Public Disclosure of Inside Information and the Definition of Market Manipulation regulates such obligation of public companies in substantially more detail than the prior Law on the Market of Securities and Other Financial Instruments (hereinafter: ZTHV. Due to the above the ZTHV's provisions are compared to the new solutions within the domain of regular periodical disclosure of the Capital Market Law.

EIT Imaging Regularization Based on Spectral Graph Wavelets.

Science.gov (United States)

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Vauhkonen, Marko; Wolf, Gerhard; Mueller-Lisse, Ullrich; Moeller, Knut

2017-09-01

The objective of electrical impedance tomographic reconstruction is to identify the distribution of tissue conductivity from electrical boundary conditions. This is an ill-posed inverse problem usually solved under the finite-element method framework. In previous studies, standard sparse regularization was used for difference electrical impedance tomography to achieve a sparse solution. However, regarding elementwise sparsity, standard sparse regularization interferes with the smoothness of conductivity distribution between neighboring elements and is sensitive to noise. As an effect, the reconstructed images are spiky and depict a lack of smoothness. Such unexpected artifacts are not realistic and may lead to misinterpretation in clinical applications. To eliminate such artifacts, we present a novel sparse regularization method that uses spectral graph wavelet transforms. Single-scale or multiscale graph wavelet transforms are employed to introduce local smoothness on different scales into the reconstructed images. The proposed approach relies on viewing finite-element meshes as undirected graphs and applying wavelet transforms derived from spectral graph theory. Reconstruction results from simulations, a phantom experiment, and patient data suggest that our algorithm is more robust to noise and produces more reliable images.

Dimensional versus lattice regularization within Luescher's Yang Mills theory

International Nuclear Information System (INIS)

Diekmann, B.; Langer, M.; Schuette, D.

1993-01-01

It is pointed out that the coefficients of Luescher's effective model space Hamiltonian, which is based upon dimensional regularization techniques, can be reproduced by applying folded diagram perturbation theory to the Kogut Susskind Hamiltonian and by performing a lattice continuum limit (keeping the volume fixed). Alternative cutoff regularizations of the Hamiltonian are in general inconsistent, the critical point beeing the correct prediction for Luescher's tadpole coefficient which is formally quadratically divergent and which has to become a well defined (negative) number. (orig.)

Complexity in union-free regular languages

Czech Academy of Sciences Publication Activity Database

Jirásková, G.; Masopust, Tomáš

2011-01-01

Roč. 22, č. 7 (2011), s. 1639-1653 ISSN 0129-0541 Institutional research plan: CEZ:AV0Z10190503 Keywords : Union-free regular language * one-cycle-free-path automaton * descriptional complexity Subject RIV: BA - General Mathematics Impact factor: 0.379, year: 2011 http://www.worldscinet.com/ijfcs/22/2207/S0129054111008933.html

On regular riesz operators | Raubenheimer | Quaestiones ...

African Journals Online (AJOL)

The r-asymptotically quasi finite rank operators on Banach lattices are examples of regular Riesz operators. We characterise Riesz elements in a subalgebra of a Banach algebra in terms of Riesz elements in the Banach algebra. This enables us to characterise r-asymptotically quasi finite rank operators in terms of adjoint ...

Complexity in union-free regular languages

Czech Academy of Sciences Publication Activity Database

Jirásková, G.; Masopust, Tomáš

2011-01-01

Roč. 22, č. 7 (2011), s. 1639-1653 ISSN 0129-0541 Institutional research plan: CEZ:AV0Z10190503 Keywords : Union-free regular language * one-cycle-free- path automaton * descriptional complexity Subject RIV: BA - General Mathematics Impact factor: 0.379, year: 2011 http://www.worldscinet.com/ijfcs/22/2207/S0129054111008933.html

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

Science.gov (United States)

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Asymptotic performance of regularized quadratic discriminant analysis based classifiers

KAUST Repository

Elkhalil, Khalil

2017-12-13

This paper carries out a large dimensional analysis of the standard regularized quadratic discriminant analysis (QDA) classifier designed on the assumption that data arise from a Gaussian mixture model. The analysis relies on fundamental results from random matrix theory (RMT) when both the number of features and the cardinality of the training data within each class grow large at the same pace. Under some mild assumptions, we show that the asymptotic classification error converges to a deterministic quantity that depends only on the covariances and means associated with each class as well as the problem dimensions. Such a result permits a better understanding of the performance of regularized QDA and can be used to determine the optimal regularization parameter that minimizes the misclassification error probability. Despite being valid only for Gaussian data, our theoretical findings are shown to yield a high accuracy in predicting the performances achieved with real data sets drawn from popular real data bases, thereby making an interesting connection between theory and practice.

Collecting Patient Reported Outcomes in the Wild: Opportunities and Challenges.

Science.gov (United States)

Cabitza, Federico; Dui, Linda Greta

2018-01-01

Collecting Patient Reported Outcomes (PROs) is generally seen as an effective way to assess the efficacy and appropriateness of medical interventions, from the patients' perspective. In 2016 the Galeazzi Orthopaedic Institute established a digitized program of PROs collection from spine, hip and knee surgery patients. In this work, we re-port the findings from the data analysis of the responses collected so far about the complementarity of PROs with respect to the data reported by the clinicians, and about the main biases that can undermine their validity and reliability. Although PROs collection is recognized as being far more complex than just asking the patients "how they feel" on a regular basis and it entails costs and devoted electronic platforms, we advocate their further diffusion for the assessment of health technology and clinical procedures.

On finitely generated modules whose first nonzero Fitting ideals are regular

Directory of Open Access Journals (Sweden)

Somayeh Hadjirezaei

2018-01-01

Full Text Available A finitely generated $R$-module is said to be a module of type ($F_r$ if its $(r-1$-th Fitting ideal is the zero ideal and its $r$-th Fitting ideal is a regular ideal. Let $R$ be a commutative ring and $N$ be a submodule of  $R^n$ which is generated by columns of  a matrix $A=(a_{ij}$ with $a_{ij}in R$ for all $1leq ileq n$, $jin Lambda$, where $Lambda $ is a (possibly infinite index set.  Let  $M=R^n/N$ be  a module of type ($F_{n-1}$ and ${rm T}(M$ be the submodule of $M$ consisting of all elements of $M$ that are annihilated by a regular element of $R$. For $ lambdain Lambda $, put $M_lambda=R^n/$. The main result of this paper asserts that if $M_lambda $ is a regular $R$-module, for some $lambdainLambda$, then $M/{rm T}(Mcong M_lambda/{rm T}(M_lambda$. Also it is shown that if $M_lambda$ is a regular torsionfree $R$-module, for some $lambdain Lambda$, then $ Mcong M_lambda. $ As a consequence we characterize all  non-torsionfree modules over a regular ring, whose first nonzero Fitting ideals are maximal.

Shakeout: A New Approach to Regularized Deep Neural Network Training.

Science.gov (United States)

Kang, Guoliang; Li, Jun; Tao, Dacheng

2018-05-01

Recent years have witnessed the success of deep neural networks in dealing with a plenty of practical problems. Dropout has played an essential role in many successful deep neural networks, by inducing regularization in the model training. In this paper, we present a new regularized training approach: Shakeout. Instead of randomly discarding units as Dropout does at the training stage, Shakeout randomly chooses to enhance or reverse each unit's contribution to the next layer. This minor modification of Dropout has the statistical trait: the regularizer induced by Shakeout adaptively combines , and regularization terms. Our classification experiments with representative deep architectures on image datasets MNIST, CIFAR-10 and ImageNet show that Shakeout deals with over-fitting effectively and outperforms Dropout. We empirically demonstrate that Shakeout leads to sparser weights under both unsupervised and supervised settings. Shakeout also leads to the grouping effect of the input units in a layer. Considering the weights in reflecting the importance of connections, Shakeout is superior to Dropout, which is valuable for the deep model compression. Moreover, we demonstrate that Shakeout can effectively reduce the instability of the training process of the deep architecture.

Total variation regularization for a backward time-fractional diffusion problem

International Nuclear Information System (INIS)

Wang, Liyan; Liu, Jijun

2013-01-01

Consider a two-dimensional backward problem for a time-fractional diffusion process, which can be considered as image de-blurring where the blurring process is assumed to be slow diffusion. In order to avoid the over-smoothing effect for object image with edges and to construct a fast reconstruction scheme, the total variation regularizing term and the data residual error in the frequency domain are coupled to construct the cost functional. The well posedness of this optimization problem is studied. The minimizer is sought approximately using the iteration process for a series of optimization problems with Bregman distance as a penalty term. This iteration reconstruction scheme is essentially a new regularizing scheme with coupling parameter in the cost functional and the iteration stopping times as two regularizing parameters. We give the choice strategy for the regularizing parameters in terms of the noise level of measurement data, which yields the optimal error estimate on the iterative solution. The series optimization problems are solved by alternative iteration with explicit exact solution and therefore the amount of computation is much weakened. Numerical implementations are given to support our theoretical analysis on the convergence rate and to show the significant reconstruction improvements. (paper)

Regularization of finite temperature string theories

International Nuclear Information System (INIS)

Leblanc, Y.; Knecht, M.; Wallet, J.C.

1990-01-01

The tachyonic divergences occurring in the free energy of various string theories at finite temperature are eliminated through the use of regularization schemes and analytic continuations. For closed strings, we obtain finite expressions which, however, develop an imaginary part above the Hagedorn temperature, whereas open string theories are still plagued with dilatonic divergences. (orig.)

Spanning k-ended trees of 3-regular connected graphs

Directory of Open Access Journals (Sweden)

Hamed Ghasemian Zoeram

2017-10-01

Full Text Available A vertex of degree one is called an end-vertex and the set of end-vertices of G is denoted by End(G. For a positive integer k, a tree T be called k-ended tree if $|End(T| \\leq k$. In this paper, we obtain sufficient conditions for spanning k-trees of 3-regular connected graphs. We give a construction sequence of graphs satisfying the condition. At the end, we present a conjecture about spanning k-ended trees of 3-regular connected graphs.

Graph Regularized Auto-Encoders for Image Representation.

Science.gov (United States)

Yiyi Liao; Yue Wang; Yong Liu

2017-06-01

Image representation has been intensively explored in the domain of computer vision for its significant influence on the relative tasks such as image clustering and classification. It is valuable to learn a low-dimensional representation of an image which preserves its inherent information from the original image space. At the perspective of manifold learning, this is implemented with the local invariant idea to capture the intrinsic low-dimensional manifold embedded in the high-dimensional input space. Inspired by the recent successes of deep architectures, we propose a local invariant deep nonlinear mapping algorithm, called graph regularized auto-encoder (GAE). With the graph regularization, the proposed method preserves the local connectivity from the original image space to the representation space, while the stacked auto-encoders provide explicit encoding model for fast inference and powerful expressive capacity for complex modeling. Theoretical analysis shows that the graph regularizer penalizes the weighted Frobenius norm of the Jacobian matrix of the encoder mapping, where the weight matrix captures the local property in the input space. Furthermore, the underlying effects on the hidden representation space are revealed, providing insightful explanation to the advantage of the proposed method. Finally, the experimental results on both clustering and classification tasks demonstrate the effectiveness of our GAE as well as the correctness of the proposed theoretical analysis, and it also suggests that GAE is a superior solution to the current deep representation learning techniques comparing with variant auto-encoders and existing local invariant methods.

Enhanced manifold regularization for semi-supervised classification.

Science.gov (United States)

Gan, Haitao; Luo, Zhizeng; Fan, Yingle; Sang, Nong

2016-06-01

Manifold regularization (MR) has become one of the most widely used approaches in the semi-supervised learning field. It has shown superiority by exploiting the local manifold structure of both labeled and unlabeled data. The manifold structure is modeled by constructing a Laplacian graph and then incorporated in learning through a smoothness regularization term. Hence the labels of labeled and unlabeled data vary smoothly along the geodesics on the manifold. However, MR has ignored the discriminative ability of the labeled and unlabeled data. To address the problem, we propose an enhanced MR framework for semi-supervised classification in which the local discriminative information of the labeled and unlabeled data is explicitly exploited. To make full use of labeled data, we firstly employ a semi-supervised clustering method to discover the underlying data space structure of the whole dataset. Then we construct a local discrimination graph to model the discriminative information of labeled and unlabeled data according to the discovered intrinsic structure. Therefore, the data points that may be from different clusters, though similar on the manifold, are enforced far away from each other. Finally, the discrimination graph is incorporated into the MR framework. In particular, we utilize semi-supervised fuzzy c-means and Laplacian regularized Kernel minimum squared error for semi-supervised clustering and classification, respectively. Experimental results on several benchmark datasets and face recognition demonstrate the effectiveness of our proposed method.

Asymptotic analysis of a pile-up of regular edge dislocation walls

KAUST Repository

Hall, Cameron L.

2011-12-01

The idealised problem of a pile-up of regular dislocation walls (that is, of planes each containing an infinite number of parallel, identical and equally spaced dislocations) was presented by Roy et al. [A. Roy, R.H.J. Peerlings, M.G.D. Geers, Y. Kasyanyuk, Materials Science and Engineering A 486 (2008) 653-661] as a prototype for understanding the importance of discrete dislocation interactions in dislocation-based plasticity models. They noted that analytic solutions for the dislocation wall density are available for a pile-up of regular screw dislocation walls, but that numerical methods seem to be necessary for investigating regular edge dislocation walls. In this paper, we use the techniques of discrete-to-continuum asymptotic analysis to obtain a detailed description of a pile-up of regular edge dislocation walls. To leading order, we find that the dislocation wall density is governed by a simple differential equation and that boundary layers are present at both ends of the pile-up. © 2011 Elsevier B.V.

Asymptotic analysis of a pile-up of regular edge dislocation walls

KAUST Repository

Hall, Cameron L.

2011-01-01

The idealised problem of a pile-up of regular dislocation walls (that is, of planes each containing an infinite number of parallel, identical and equally spaced dislocations) was presented by Roy et al. [A. Roy, R.H.J. Peerlings, M.G.D. Geers, Y. Kasyanyuk, Materials Science and Engineering A 486 (2008) 653-661] as a prototype for understanding the importance of discrete dislocation interactions in dislocation-based plasticity models. They noted that analytic solutions for the dislocation wall density are available for a pile-up of regular screw dislocation walls, but that numerical methods seem to be necessary for investigating regular edge dislocation walls. In this paper, we use the techniques of discrete-to-continuum asymptotic analysis to obtain a detailed description of a pile-up of regular edge dislocation walls. To leading order, we find that the dislocation wall density is governed by a simple differential equation and that boundary layers are present at both ends of the pile-up. © 2011 Elsevier B.V.

Regularization of the quantum field theory of charges and monopoles

International Nuclear Information System (INIS)

Panagiotakopoulos, C.

1981-09-01

A gauge invariant regularization procedure for quantum field theories of electric and magnetic charges based on Zwanziger's local formulation is proposed. The bare regularized full Green's functions of gauge invariant operators are shown to be Lorentz invariant. This would have as a consequence the Lorentz invariance of the finite Green's functions that might result after any reasonable subtraction if such a subtraction can be found. (author)

Regularized plane-wave least-squares Kirchhoff migration

KAUST Repository

Wang, Xin; Dai, Wei; Schuster, Gerard T.

2013-01-01

A Kirchhoff least-squares migration (LSM) is developed in the prestack plane-wave domain to increase the quality of migration images. A regularization term is included that accounts for mispositioning of reflectors due to errors in the velocity

Collective ordering of microscale matters in natural analogy.

Science.gov (United States)

Ahn, Sungsook; Lee, Sang Joon

2015-06-01

Collective interaction occurs in many natural and artificial matters in broad scales. In a biological system, collective spatial organization of live individuals in a colony is important for their viability determination. Interactive motions between a single individual and an agglomerate are critical for whole procedure of the collective behaviors, but few has been clarified for these intermediate range behaviors. Here, collective interactions of microscale matters are investigated with human cells, plant seeds and artificial microspheres in terms of commonly occurring spatial arrangements. Human cancer cells are inherently attractive to form an agglomerate by cohesive motion, while plant chia seeds are repulsive by excreting mucilage. Microsphere model is employed to investigate the dynamic assembly equilibrated by an attraction and repulsion. There is a fundamental analogy in terms of an onset of regular pattern formation even without physical contact of individuals. The collective interactions are suggested to start before the individual components become physically agglomerated. This study contributes to fundamental understanding on the microscale particulate matters and natural pattern formation which are further useful for various applications both in academic and industrial areas.

Preference mapping of lemon lime carbonated beverages with regular and diet beverage consumers.

Science.gov (United States)

Leksrisompong, P P; Lopetcharat, K; Guthrie, B; Drake, M A

2013-02-01

The drivers of liking of lemon-lime carbonated beverages were investigated with regular and diet beverage consumers. Ten beverages were selected from a category survey of commercial beverages using a D-optimal procedure. Beverages were subjected to consumer testing (n = 101 regular beverage consumers, n = 100 diet beverage consumers). Segmentation of consumers was performed on overall liking scores followed by external preference mapping of selected samples. Diet beverage consumers liked 2 diet beverages more than regular beverage consumers. There were no differences in the overall liking scores between diet and regular beverage consumers for other products except for a sparkling beverage sweetened with juice which was more liked by regular beverage consumers. Three subtle but distinct consumer preference clusters were identified. Two segments had evenly distributed diet and regular beverage consumers but one segment had a greater percentage of regular beverage consumers (P beverage consumers) did not have a large impact on carbonated beverage liking. Instead, mouthfeel attributes were major drivers of liking when these beverages were tested in a blind tasting. Preference mapping of lemon-lime carbonated beverage with diet and regular beverage consumers allowed the determination of drivers of liking of both populations. The understanding of how mouthfeel attributes, aromatics, and basic tastes impact liking or disliking of products was achieved. Preference drivers established in this study provide product developers of carbonated lemon-lime beverages with additional information to develop beverages that may be suitable for different groups of consumers. © 2013 Institute of Food Technologists®

Regular perturbation theory for two-electron atoms

International Nuclear Information System (INIS)

Feranchuk, I.D.; Triguk, V.V.

2011-01-01

Regular perturbation theory (RPT) for the ground and excited states of two-electron atoms or ions is developed. It is shown for the first time that summation of the matrix elements from the electron-electron interaction operator over all intermediate states can be calculated in a closed form by means of the two-particle Coulomb Green's function constructed in the Letter. It is shown that the second order approximation of RPT includes the main part of the correlation energy both for the ground and excited states. This approach can be also useful for description of two-electron atoms in external fields. -- Highlights: → We develop regular perturbation theory for the two-electron atoms or ions. → We calculate the sum of the matrix elements over all intermediate states. → We construct the two-particle Coulomb Green's function.

Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems

KAUST Repository

Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Al-Naffouri, Tareq Y.

2016-01-01

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.

Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-11-29

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.

Condom use and intimacy among Tajik male migrants and their regular female partners in Moscow.

Science.gov (United States)

Zabrocki, Christopher; Polutnik, Chloe; Jonbekov, Jonbek; Shoakova, Farzona; Bahromov, Mahbat; Weine, Stevan

2015-01-01

This study examined condom use and intimacy among Tajik male migrants and their regular female partners in Moscow, Russia. This study included a survey of 400 Tajik male labour migrants and longitudinal ethnographic interviews with 30 of the surveyed male migrants and 30 of their regular female partners. of the surveyed male migrants, 351 (88%) reported having a regular female partner in Moscow. Findings demonstrated that the migrants' and regular partners' intentions to use condoms diminished with increased intimacy, yet each party perceived intimacy differently. Migrants' intimacy with regular partners was determined by their familiarity and the perceived sexual cleanliness of their partner. Migrants believed that Muslim women were cleaner than Orthodox Christian women and reported using condoms more frequently with Orthodox Christian regular partners. Regular partners reported determining intimacy based on the perceived commitment of the male migrant. When perceived commitment faced a crisis, intimacy declined and regular partners renegotiated condom use. The association between intimacy and condom use suggests that HIV-prevention programmes should aim to help male migrants and female regular partners to dissociate their approaches to condom use from their perceptions of intimacy.

On generalized regular sequences and the finiteness for associated primes of local cohomology modules

International Nuclear Information System (INIS)

Le Thanh Nhan

2003-08-01

Let (R,m) be a Noetherian local ring and M a finitely generated R-module. The two notions of generalized regular sequence and generalized depth are introduced as extensions of the known notions of regular sequence and depth respectively. Some properties of generalized regular sequence and generalized depth, which are closely related to that of regular sequence and depth, are given. If x 1 ,... ,x r is a generalized regular sequence of M then union n1,...,nr Ass M/(x 1 n 1 ,... ,x r n r )M is a finite set. Some finiteness properties for associated primes of local cohomology modules are presented. (author)

Multi-omic data integration enables discovery of hidden biological regularities

DEFF Research Database (Denmark)

Ebrahim, Ali; Brunk, Elizabeth; Tan, Justin

2016-01-01

Rapid growth in size and complexity of biological data sets has led to the 'Big Data to Knowledge' challenge. We develop advanced data integration methods for multi- level analysis of genomic, transcriptomic, ribosomal profiling, proteomic and fluxomic data. First, we show that pairwise integration...... of primary omics data reveals regularities that tie cellular processes together in Escherichia coli: the number of protein molecules made per mRNA transcript and the number of ribosomes required per translated protein molecule. Second, we show that genome- scale models, based on genomic and bibliomic data......, enable quantitative synchronization of disparate data types. Integrating omics data with models enabled the discovery of two novel regularities: condition invariant in vivo turnover rates of enzymes and the correlation of protein structural motifs and translational pausing. These regularities can...

Selecting protein families for environmental features based on manifold regularization.

Science.gov (United States)

Jiang, Xingpeng; Xu, Weiwei; Park, E K; Li, Guangrong

2014-06-01

Recently, statistics and machine learning have been developed to identify functional or taxonomic features of environmental features or physiological status. Important proteins (or other functional and taxonomic entities) to environmental features can be potentially used as biosensors. A major challenge is how the distribution of protein and gene functions embodies the adaption of microbial communities across environments and host habitats. In this paper, we propose a novel regularization method for linear regression to adapt the challenge. The approach is inspired by local linear embedding (LLE) and we call it a manifold-constrained regularization for linear regression (McRe). The novel regularization procedure also has potential to be used in solving other linear systems. We demonstrate the efficiency and the performance of the approach in both simulation and real data.

Defining the Symmetry of the Universal Semi-Regular Autonomous Asynchronous Systems

Directory of Open Access Journals (Sweden)

Serban E. Vlad

2012-02-01

Full Text Available The regular autonomous asynchronous systems are the non-deterministic Boolean dynamical systems and universality means the greatest in the sense of the inclusion. The paper gives four definitions of symmetry of these systems in a slightly more general framework, called semi-regularity, and also many examples.

Novel Harmonic Regularization Approach for Variable Selection in Cox’s Proportional Hazards Model

Directory of Open Access Journals (Sweden)

Ge-Jin Chu

2014-01-01

Full Text Available Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2regularizations, to select key risk factors in the Cox’s proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL, the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods.

Analytic stochastic regularization and gange invariance

International Nuclear Information System (INIS)

Abdalla, E.; Gomes, M.; Lima-Santos, A.

1986-05-01

A proof that analytic stochastic regularization breaks gauge invariance is presented. This is done by an explicit one loop calculation of the vaccum polarization tensor in scalar electrodynamics, which turns out not to be transversal. The counterterm structure, Langevin equations and the construction of composite operators in the general framework of stochastic quantization, are also analysed. (Author) [pt

Faster 2-regular information-set decoding

NARCIS (Netherlands)

Bernstein, D.J.; Lange, T.; Peters, C.P.; Schwabe, P.; Chee, Y.M.

2011-01-01

Fix positive integers B and w. Let C be a linear code over F 2 of length Bw. The 2-regular-decoding problem is to find a nonzero codeword consisting of w length-B blocks, each of which has Hamming weight 0 or 2. This problem appears in attacks on the FSB (fast syndrome-based) hash function and

Preconditioners for regularized saddle point matrices

Czech Academy of Sciences Publication Activity Database

Axelsson, Owe

2011-01-01

Roč. 19, č. 2 (2011), s. 91-112 ISSN 1570-2820 Institutional research plan: CEZ:AV0Z30860518 Keywords : saddle point matrices * preconditioning * regularization * eigenvalue clustering Subject RIV: BA - General Mathematics Impact factor: 0.533, year: 2011 http://www.degruyter.com/view/j/jnma.2011.19.issue-2/jnum.2011.005/jnum.2011.005. xml

Discharge regularity in the turtle posterior crista: comparisons between experiment and theory.

Science.gov (United States)

Goldberg, Jay M; Holt, Joseph C

2013-12-01

Intra-axonal recordings were made from bouton fibers near their termination in the turtle posterior crista. Spike discharge, miniature excitatory postsynaptic potentials (mEPSPs), and afterhyperpolarizations (AHPs) were monitored during resting activity in both regularly and irregularly discharging units. Quantal size (qsize) and quantal rate (qrate) were estimated by shot-noise theory. Theoretically, the ratio, σV/(dμV/dt), between synaptic noise (σV) and the slope of the mean voltage trajectory (dμV/dt) near threshold crossing should determine discharge regularity. AHPs are deeper and more prolonged in regular units; as a result, dμV/dt is larger, the more regular the discharge. The qsize is larger and qrate smaller in irregular units; these oppositely directed trends lead to little variation in σV with discharge regularity. Of the two variables, dμV/dt is much more influential than the nearly constant σV in determining regularity. Sinusoidal canal-duct indentations at 0.3 Hz led to modulations in spike discharge and synaptic voltage. Gain, the ratio between the amplitudes of the two modulations, and phase leads re indentation of both modulations are larger in irregular units. Gain variations parallel the sensitivity of the postsynaptic spike encoder, the set of conductances that converts synaptic input into spike discharge. Phase variations reflect both synaptic inputs to the encoder and postsynaptic processes. Experimental data were interpreted using a stochastic integrate-and-fire model. Advantages of an irregular discharge include an enhanced encoder gain and the prevention of nonlinear phase locking. Regular and irregular units are more efficient, respectively, in the encoding of low- and high-frequency head rotations, respectively.

Optimal Design of the Adaptive Normalized Matched Filter Detector using Regularized Tyler Estimators

KAUST Repository

Kammoun, Abla; Couillet, Romain; Pascal, Frederic; Alouini, Mohamed-Slim

2017-01-01

This article addresses improvements on the design of the adaptive normalized matched filter (ANMF) for radar detection. It is well-acknowledged that the estimation of the noise-clutter covariance matrix is a fundamental step in adaptive radar detection. In this paper, we consider regularized estimation methods which force by construction the eigenvalues of the covariance estimates to be greater than a positive regularization parameter ρ. This makes them more suitable for high dimensional problems with a limited number of secondary data samples than traditional sample covariance estimates. The motivation behind this work is to understand the effect and properly set the value of ρthat improves estimate conditioning while maintaining a low estimation bias. More specifically, we consider the design of the ANMF detector for two kinds of regularized estimators, namely the regularized sample covariance matrix (RSCM), the regularized Tyler estimator (RTE). The rationale behind this choice is that the RTE is efficient in mitigating the degradation caused by the presence of impulsive noises while inducing little loss when the noise is Gaussian. Based on asymptotic results brought by recent tools from random matrix theory, we propose a design for the regularization parameter that maximizes the asymptotic detection probability under constant asymptotic false alarm rates. Provided Simulations support the efficiency of the proposed method, illustrating its gain over conventional settings of the regularization parameter.

Optimal Design of the Adaptive Normalized Matched Filter Detector using Regularized Tyler Estimators

KAUST Repository

Kammoun, Abla

2017-10-25

This article addresses improvements on the design of the adaptive normalized matched filter (ANMF) for radar detection. It is well-acknowledged that the estimation of the noise-clutter covariance matrix is a fundamental step in adaptive radar detection. In this paper, we consider regularized estimation methods which force by construction the eigenvalues of the covariance estimates to be greater than a positive regularization parameter ρ. This makes them more suitable for high dimensional problems with a limited number of secondary data samples than traditional sample covariance estimates. The motivation behind this work is to understand the effect and properly set the value of ρthat improves estimate conditioning while maintaining a low estimation bias. More specifically, we consider the design of the ANMF detector for two kinds of regularized estimators, namely the regularized sample covariance matrix (RSCM), the regularized Tyler estimator (RTE). The rationale behind this choice is that the RTE is efficient in mitigating the degradation caused by the presence of impulsive noises while inducing little loss when the noise is Gaussian. Based on asymptotic results brought by recent tools from random matrix theory, we propose a design for the regularization parameter that maximizes the asymptotic detection probability under constant asymptotic false alarm rates. Provided Simulations support the efficiency of the proposed method, illustrating its gain over conventional settings of the regularization parameter.

Material parameters characterization for arbitrary N-sided regular polygonal invisible cloak

International Nuclear Information System (INIS)

Wu Qun; Zhang Kuang; Meng Fanyi; Li Lewei

2009-01-01

Arbitrary N-sided regular polygonal cylindrical cloaks are proposed and designed based on the coordinate transformation theory. First, the general expressions of constitutive tensors of the N-sided regular polygonal cylindrical cloaks are derived, then there are some full-wave simulations of the cloaks that are composed of inhomogeneous and anisotropic metamaterials, which will bend incoming electromagnetic waves and guide them to propagate around the inner region; such electromagnetic waves will return to their original propagation directions without distorting the waves outside the polygonal cloak. The results of full-wave simulations validate the general expressions of constitutive tensors of the N-sided regular polygonal cylindrical cloaks we derived.

REGULARIZED D-BAR METHOD FOR THE INVERSE CONDUCTIVITY PROBLEM

DEFF Research Database (Denmark)

Knudsen, Kim; Lassas, Matti; Mueller, Jennifer

2009-01-01

A strategy for regularizing the inversion procedure for the two-dimensional D-bar reconstruction algorithm based on the global uniqueness proof of Nachman [Ann. Math. 143 (1996)] for the ill-posed inverse conductivity problem is presented. The strategy utilizes truncation of the boundary integral...... the convergence of the reconstructed conductivity to the true conductivity as the noise level tends to zero. The results provide a link between two traditions of inverse problems research: theory of regularization and inversion methods based on complex geometrical optics. Also, the procedure is a novel...

A new approach to nonlinear constrained Tikhonov regularization

KAUST Repository

Ito, Kazufumi

2011-09-16

We present a novel approach to nonlinear constrained Tikhonov regularization from the viewpoint of optimization theory. A second-order sufficient optimality condition is suggested as a nonlinearity condition to handle the nonlinearity of the forward operator. The approach is exploited to derive convergence rate results for a priori as well as a posteriori choice rules, e.g., discrepancy principle and balancing principle, for selecting the regularization parameter. The idea is further illustrated on a general class of parameter identification problems, for which (new) source and nonlinearity conditions are derived and the structural property of the nonlinearity term is revealed. A number of examples including identifying distributed parameters in elliptic differential equations are presented. © 2011 IOP Publishing Ltd.

An algorithm for total variation regularized photoacoustic imaging

DEFF Research Database (Denmark)

Dong, Yiqiu; Görner, Torsten; Kunis, Stefan

2014-01-01

Recovery of image data from photoacoustic measurements asks for the inversion of the spherical mean value operator. In contrast to direct inversion methods for specific geometries, we consider a semismooth Newton scheme to solve a total variation regularized least squares problem. During the iter......Recovery of image data from photoacoustic measurements asks for the inversion of the spherical mean value operator. In contrast to direct inversion methods for specific geometries, we consider a semismooth Newton scheme to solve a total variation regularized least squares problem. During...... the iteration, each matrix vector multiplication is realized in an efficient way using a recently proposed spectral discretization of the spherical mean value operator. All theoretical results are illustrated by numerical experiments....

Iterated Process Analysis over Lattice-Valued Regular Expressions

DEFF Research Database (Denmark)

Midtgaard, Jan; Nielson, Flemming; Nielson, Hanne Riis

2016-01-01

We present an iterated approach to statically analyze programs of two processes communicating by message passing. Our analysis operates over a domain of lattice-valued regular expressions, and computes increasingly better approximations of each process's communication behavior. Overall the work e...... extends traditional semantics-based program analysis techniques to automatically reason about message passing in a manner that can simultaneously analyze both values of variables as well as message order, message content, and their interdependencies.......We present an iterated approach to statically analyze programs of two processes communicating by message passing. Our analysis operates over a domain of lattice-valued regular expressions, and computes increasingly better approximations of each process's communication behavior. Overall the work...

Partial Regularity for Holonomic Minimisers of Quasiconvex Functionals

Science.gov (United States)

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.

Quasi regular polygons and their duals with Coxeter symmetries Dn represented by complex numbers

International Nuclear Information System (INIS)

Koca, M; Koca, N O

2011-01-01

This paper deals with tiling of the plane by quasi regular polygons and their duals. The problem is motivated from the fact that the graphene, infinite number of carbon molecules forming a honeycomb lattice, may have states with two bond lengths and equal bond angles or one bond length and different bond angles. We prove that the Euclidean plane can be tiled with two tiles consisting of quasi regular hexagons with two different lengths (isogonal hexagons) and regular hexagons. The dual lattice is constructed with the isotoxal hexagons (equal edges but two different interior angles) and regular hexagons. We also give similar tilings of the plane with the quasi regular polygons along with the regular polygons possessing the Coxeter symmetries D n , n=2,3,4,5. The group elements as well as the vertices of the polygons are represented by the complex numbers.

Evaluated data collections from ENSDF

International Nuclear Information System (INIS)

Ewbank, W.B.

1979-01-01

For several years the Nuclear Data Project has been maintaining an Evaluated Nuclear Structure Data File (ENSDF), which is designed to include critically evaluated values for most nuclear spectroscopic quantities. The information in ENSDF is the same as in the Nuclear Data Sheets, which illustrates two particular output formats (drawings and tables). Spectroscopic information for nuclei with A < 45 is put into ENSDF from the evaluations of Aizenberg-Selove and of Endt and van der Leun. An international network was organized to provide regular revisions of the data file. Computer facilities were developed to retrieve collections of evaluated data for special calculations or detailed examination

The Effect of Three Months Regular Aerobic Exercise on Premenstrual Syndrome

Directory of Open Access Journals (Sweden)

Zinat Ghanbari

2008-12-01

Full Text Available Objective: To determine the effects of three-month regular aerobic exercise on the PMS symptoms. Also correlations with age, education, marital status and severity of PMS symptoms were studied.Materials and Methods: A Quasi- Experimental study was conducted on 91 volunteer women with regular menstrual cycle and no history of gynecological, endocrinological and psychological disorders. The study was done during March 2005- March 2007, in Tehran University of Medical Sciences. A Modified Menstrual Distress Questionnaire (MMDQ was used in this study. Participants were divided into two groups: Non-exercised, they also didn't have any past experience of regular exercise (n= 48 and Exercised (n= 43. The exercise time duration was one hour and was carried out three times per week for three months.  Emotional, behavioral, electrolyte, autonomic, neurovegatative and skin symptoms of PMS were compared between two groups. P value was considered significant at < 0.05.Results: A significant difference was observed for electrolytic, neurovegetative and cognitive symptoms before and after the exercise. Also the severity of skin and neurovegetative symptoms were different in experimental groups with and without past history of doing regular exercise. There was no correlation between age, education, marital status and severity of PMS symptoms.Conclusion: Three months of regular aerobic exercise effectively reduces the severity of PMS symptoms.

Regularized Label Relaxation Linear Regression.

Science.gov (United States)

Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung; Fang, Bingwu

2018-04-01

Linear regression (LR) and some of its variants have been widely used for classification problems. Most of these methods assume that during the learning phase, the training samples can be exactly transformed into a strict binary label matrix, which has too little freedom to fit the labels adequately. To address this problem, in this paper, we propose a novel regularized label relaxation LR method, which has the following notable characteristics. First, the proposed method relaxes the strict binary label matrix into a slack variable matrix by introducing a nonnegative label relaxation matrix into LR, which provides more freedom to fit the labels and simultaneously enlarges the margins between different classes as much as possible. Second, the proposed method constructs the class compactness graph based on manifold learning and uses it as the regularization item to avoid the problem of overfitting. The class compactness graph is used to ensure that the samples sharing the same labels can be kept close after they are transformed. Two different algorithms, which are, respectively, based on -norm and -norm loss functions are devised. These two algorithms have compact closed-form solutions in each iteration so that they are easily implemented. Extensive experiments show that these two algorithms outperform the state-of-the-art algorithms in terms of the classification accuracy and running time.

Cultural and Mathematical Meanings of Regular Octagons in Mesopotamia: Examining Islamic Art Designs

Directory of Open Access Journals (Sweden)

Jeanam Park

2018-03-01

Full Text Available The most common regular polygon in Islamic art design is the octagon. Historical evidence of the use of an 8-star polygon and an 8-fold rosette dates back to Jemdet Nasr (3100-2900 B.C. in Mesopotamia. Additionally, in ancient Egypt, octagons can be found in mathematical problem (Ahmose papyrus, Problem number 48, household goods (papyrus storage, architecture (granite columns and decorations (palace decorations. The regular octagon which is a fundamentally important element of Islamic art design, is widely used as arithmetic objects in metric algebra along with other regular polygons in Mesopotamia. The 8-point star polygon has long been a symbol of the ancient Sumerian goddess Inanna and her East Semitic counterpart Ishtar. During the Neo-Assyrian period, the 8-fold rosette occasionally replaced the star as the symbol of Ishtar. In this paper, we discuss how octagonal design prevailed in the Islamic region since the late ninth century, and has existed in Mesopotamia from Jemdet Nasr to the end of third century B.C. We describe reasons why the geometric pattern of regular polygons, including regular octagons, developed in the Islamic world. Furthermore, we also discuss mathematical meanings of regular polygons.

A New Method for Determining Optimal Regularization Parameter in Near-Field Acoustic Holography

Directory of Open Access Journals (Sweden)

Yue Xiao

2018-01-01

Full Text Available Tikhonov regularization method is effective in stabilizing reconstruction process of the near-field acoustic holography (NAH based on the equivalent source method (ESM, and the selection of the optimal regularization parameter is a key problem that determines the regularization effect. In this work, a new method for determining the optimal regularization parameter is proposed. The transfer matrix relating the source strengths of the equivalent sources to the measured pressures on the hologram surface is augmented by adding a fictitious point source with zero strength. The minimization of the norm of this fictitious point source strength is as the criterion for choosing the optimal regularization parameter since the reconstructed value should tend to zero. The original inverse problem in calculating the source strengths is converted into a univariate optimization problem which is solved by a one-dimensional search technique. Two numerical simulations with a point driven simply supported plate and a pulsating sphere are investigated to validate the performance of the proposed method by comparison with the L-curve method. The results demonstrate that the proposed method can determine the regularization parameter correctly and effectively for the reconstruction in NAH.

Regularity and irreversibility of weekly travel behavior

NARCIS (Netherlands)

Kitamura, R.; van der Hoorn, A.I.J.M.

1987-01-01

Dynamic characteristics of travel behavior are analyzed in this paper using weekly travel diaries from two waves of panel surveys conducted six months apart. An analysis of activity engagement indicates the presence of significant regularity in weekly activity participation between the two waves.

Dimensional regularization in position space and a forest formula for regularized Epstein-Glaser renormalization

Energy Technology Data Exchange (ETDEWEB)

Keller, Kai Johannes

2010-04-15

The present work contains a consistent formulation of the methods of dimensional regularization (DimReg) and minimal subtraction (MS) in Minkowski position space. The methods are implemented into the framework of perturbative Algebraic Quantum Field Theory (pAQFT). The developed methods are used to solve the Epstein-Glaser recursion for the construction of time-ordered products in all orders of causal perturbation theory. A solution is given in terms of a forest formula in the sense of Zimmermann. A relation to the alternative approach to renormalization theory using Hopf algebras is established. (orig.)

Dimensional regularization in position space and a forest formula for regularized Epstein-Glaser renormalization

International Nuclear Information System (INIS)

Keller, Kai Johannes

2010-04-01

The present work contains a consistent formulation of the methods of dimensional regularization (DimReg) and minimal subtraction (MS) in Minkowski position space. The methods are implemented into the framework of perturbative Algebraic Quantum Field Theory (pAQFT). The developed methods are used to solve the Epstein-Glaser recursion for the construction of time-ordered products in all orders of causal perturbation theory. A solution is given in terms of a forest formula in the sense of Zimmermann. A relation to the alternative approach to renormalization theory using Hopf algebras is established. (orig.)

Geometrical bucklings for two-dimensional regular polygonal regions using the finite Fourier transformation

International Nuclear Information System (INIS)

Mori, N.; Kobayashi, K.

1996-01-01

A two-dimensional neutron diffusion equation is solved for regular polygonal regions by the finite Fourier transformation, and geometrical bucklings are calculated for regular 3-10 polygonal regions. In the case of the regular triangular region, it is found that a simple and rigorous analytic solution is obtained for the geometrical buckling and the distribution of the neutron current along the outer boundary. (author)

Stream Processing Using Grammars and Regular Expressions

DEFF Research Database (Denmark)

Rasmussen, Ulrik Terp

disambiguation. The first algorithm operates in two passes in a semi-streaming fashion, using a constant amount of working memory and an auxiliary tape storage which is written in the first pass and consumed by the second. The second algorithm is a single-pass and optimally streaming algorithm which outputs...... as much of the parse tree as is semantically possible based on the input prefix read so far, and resorts to buffering as many symbols as is required to resolve the next choice. Optimality is obtained by performing a PSPACE-complete pre-analysis on the regular expression. In the second part we present...... Kleenex, a language for expressing high-performance streaming string processing programs as regular grammars with embedded semantic actions, and its compilation to streaming string transducers with worst-case linear-time performance. Its underlying theory is based on transducer decomposition into oracle...

Extreme values, regular variation and point processes

CERN Document Server

Resnick, Sidney I

1987-01-01

Extremes Values, Regular Variation and Point Processes is a readable and efficient account of the fundamental mathematical and stochastic process techniques needed to study the behavior of extreme values of phenomena based on independent and identically distributed random variables and vectors It presents a coherent treatment of the distributional and sample path fundamental properties of extremes and records It emphasizes the core primacy of three topics necessary for understanding extremes the analytical theory of regularly varying functions; the probabilistic theory of point processes and random measures; and the link to asymptotic distribution approximations provided by the theory of weak convergence of probability measures in metric spaces The book is self-contained and requires an introductory measure-theoretic course in probability as a prerequisite Almost all sections have an extensive list of exercises which extend developments in the text, offer alternate approaches, test mastery and provide for enj...

Least square regularized regression in sum space.

Science.gov (United States)

Xu, Yong-Li; Chen, Di-Rong; Li, Han-Xiong; Liu, Lu

2013-04-01

This paper proposes a least square regularized regression algorithm in sum space of reproducing kernel Hilbert spaces (RKHSs) for nonflat function approximation, and obtains the solution of the algorithm by solving a system of linear equations. This algorithm can approximate the low- and high-frequency component of the target function with large and small scale kernels, respectively. The convergence and learning rate are analyzed. We measure the complexity of the sum space by its covering number and demonstrate that the covering number can be bounded by the product of the covering numbers of basic RKHSs. For sum space of RKHSs with Gaussian kernels, by choosing appropriate parameters, we tradeoff the sample error and regularization error, and obtain a polynomial learning rate, which is better than that in any single RKHS. The utility of this method is illustrated with two simulated data sets and five real-life databases.

Informed community mobilization for dengue prevention in households with and without a regular water supply: Secondary analysis from the Camino Verde trial in Nicaragua.

Science.gov (United States)

Cárcamo, Alvaro; Arosteguí, Jorge; Coloma, Josefina; Harris, Eva; Ledogar, Robert J; Andersson, Neil

2017-05-30

Studies in different countries have identified irregular water supply as a risk factor for dengue virus transmission. In 2013, Camino Verde, a cluster-randomised controlled trial in Managua, Nicaragua, and Mexico's Guerrero State, demonstrated impact of evidence-based community mobilisation on recent dengue infection and entomological indexes of infestation by Aedes aegypti mosquitoes. This secondary analysis of data from the trial impact survey asks: (1) what is the importance of regular water supply in neighbourhoods with and without the trial intervention and (2) can community interventions like Camino Verde reasonably exclude households with adequate water supply? Entomological data collected in the dry season of 2013 in intervention and control communities allow contrasts between households with regular and irregular water supplies. Indicators of entomological risk included the House Index and pupa positive household index. Generalised linear mixed models with cluster as a random effect compared households with and without regular water, and households in intervention and control communities. For the House Index, regular water supply was associated with a protection in both intervention households (OR 0.7, 95%CI 0.6-0.9) and control households (OR 0.6, 95%CI 0.5-0.8). For the pupa positive household index, we found a similar protection from regular water supply in intervention households (OR 0.6, 95%CI 0.4-0.8) and control households (OR 0.7, 95%CI 0.5-0.9). The Camino Verde intervention had a similar impact on House Index in households with regular water supply (OR 0.7, 95%CI 0.5-1.0) and irregular water supply (OR 0.6, 95%CI 0.4-0.8); for the pupa positive household index, the effect of the intervention was very similar in households with regular (OR0.5, 95%CI 0.3-0.8) and irregular (OR 0.5, 95%CI 0.3-0.9) water supply. While Aedes aegypti control efforts based on informed community mobilisation had a strong impact on households without a regular water

Regularized strings with extrinsic curvature

International Nuclear Information System (INIS)

Ambjoern, J.; Durhuus, B.

1987-07-01

We analyze models of discretized string theories, where the path integral over world sheet variables is regularized by summing over triangulated surfaces. The inclusion of curvature in the action is a necessity for the scaling of the string tension. We discuss the physical properties of models with extrinsic curvature terms in the action and show that the string tension vanishes at the critical point where the bare extrinsic curvature coupling tends to infinity. Similar results are derived for models with intrinsic curvature. (orig.)

Thin-shell wormholes from the regular Hayward black hole

Energy Technology Data Exchange (ETDEWEB)

Halilsoy, M.; Ovgun, A.; Mazharimousavi, S.H. [Eastern Mediterranean University, Department of Physics, Mersin 10 (Turkey)

2014-03-15

We revisit the regular black hole found by Hayward in 4-dimensional static, spherically symmetric spacetime. To find a possible source for such a spacetime we resort to the nonlinear electrodynamics in general relativity. It is found that a magnetic field within this context gives rise to the regular Hayward black hole. By employing such a regular black hole we construct a thin-shell wormhole for the case of various equations of state on the shell. We abbreviate a general equation of state by p = ψ(σ) where p is the surface pressure which is a function of the mass density (σ). In particular, linear, logarithmic, Chaplygin, etc. forms of equations of state are considered. In each case we study the stability of the thin shell against linear perturbations.We plot the stability regions by tuning the parameters of the theory. It is observed that the role of the Hayward parameter is to make the TSW more stable. Perturbations of the throat with small velocity condition are also studied. The matter of our TSWs, however, remains exotic. (orig.)

A Large Dimensional Analysis of Regularized Discriminant Analysis Classifiers

KAUST Repository

Elkhalil, Khalil

2017-11-01

This article carries out a large dimensional analysis of standard regularized discriminant analysis classifiers designed on the assumption that data arise from a Gaussian mixture model with different means and covariances. The analysis relies on fundamental results from random matrix theory (RMT) when both the number of features and the cardinality of the training data within each class grow large at the same pace. Under mild assumptions, we show that the asymptotic classification error approaches a deterministic quantity that depends only on the means and covariances associated with each class as well as the problem dimensions. Such a result permits a better understanding of the performance of regularized discriminant analsysis, in practical large but finite dimensions, and can be used to determine and pre-estimate the optimal regularization parameter that minimizes the misclassification error probability. Despite being theoretically valid only for Gaussian data, our findings are shown to yield a high accuracy in predicting the performances achieved with real data sets drawn from the popular USPS data base, thereby making an interesting connection between theory and practice.

Robust regularized least-squares beamforming approach to signal estimation

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2017-05-12

In this paper, we address the problem of robust adaptive beamforming of signals received by a linear array. The challenge associated with the beamforming problem is twofold. Firstly, the process requires the inversion of the usually ill-conditioned covariance matrix of the received signals. Secondly, the steering vector pertaining to the direction of arrival of the signal of interest is not known precisely. To tackle these two challenges, the standard capon beamformer is manipulated to a form where the beamformer output is obtained as a scaled version of the inner product of two vectors. The two vectors are linearly related to the steering vector and the received signal snapshot, respectively. The linear operator, in both cases, is the square root of the covariance matrix. A regularized least-squares (RLS) approach is proposed to estimate these two vectors and to provide robustness without exploiting prior information. Simulation results show that the RLS beamformer using the proposed regularization algorithm outperforms state-of-the-art beamforming algorithms, as well as another RLS beamformers using a standard regularization approaches.

Regular black hole in three dimensions

OpenAIRE

Myung, Yun Soo; Yoon, Myungseok

2008-01-01

We find a new black hole in three dimensional anti-de Sitter space by introducing an anisotropic perfect fluid inspired by the noncommutative black hole. This is a regular black hole with two horizons. We compare thermodynamics of this black hole with that of non-rotating BTZ black hole. The first-law of thermodynamics is not compatible with the Bekenstein-Hawking entropy.

Verbal Working Memory Is Related to the Acquisition of Cross-Linguistic Phonological Regularities.

Science.gov (United States)

Bosma, Evelyn; Heeringa, Wilbert; Hoekstra, Eric; Versloot, Arjen; Blom, Elma

2017-01-01

Closely related languages share cross-linguistic phonological regularities, such as Frisian -âld [ͻ:t] and Dutch -oud [ʱut], as in the cognate pairs kâld [kͻ:t] - koud [kʱut] 'cold' and wâld [wͻ:t] - woud [wʱut] 'forest'. Within Bybee's (1995, 2001, 2008, 2010) network model, these regularities are, just like grammatical rules within a language, generalizations that emerge from schemas of phonologically and semantically related words. Previous research has shown that verbal working memory is related to the acquisition of grammar, but not vocabulary. This suggests that verbal working memory supports the acquisition of linguistic regularities. In order to test this hypothesis we investigated whether verbal working memory is also related to the acquisition of cross-linguistic phonological regularities. For three consecutive years, 5- to 8-year-old Frisian-Dutch bilingual children ( n = 120) were tested annually on verbal working memory and a Frisian receptive vocabulary task that comprised four cognate categories: (1) identical cognates, (2) non-identical cognates that either do or (3) do not exhibit a phonological regularity between Frisian and Dutch, and (4) non-cognates. The results showed that verbal working memory had a significantly stronger effect on cognate category (2) than on the other three cognate categories. This suggests that verbal working memory is related to the acquisition of cross-linguistic phonological regularities. More generally, it confirms the hypothesis that verbal working memory plays a role in the acquisition of linguistic regularities.

Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

Science.gov (United States)

Huang, Yawen; Shao, Ling; Frangi, Alejandro F

2018-03-01

Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

Regularizations of two-fold bifurcations in planar piecewise smooth systems using blowup

DEFF Research Database (Denmark)

Kristiansen, Kristian Uldall; Hogan, S. J.

2015-01-01

type of limit cycle that does not appear to be present in the original PWS system. For both types of limit cycle, we show that the criticality of the Hopf bifurcation that gives rise to periodic orbits is strongly dependent on the precise form of the regularization. Finally, we analyse the limit cycles...... as locally unique families of periodic orbits of the regularization and connect them, when possible, to limit cycles of the PWS system. We illustrate our analysis with numerical simulations and show how the regularized system can undergo a canard explosion phenomenon...

Decentralized formation of random regular graphs for robust multi-agent networks

KAUST Repository

Yazicioglu, A. Yasin

2014-12-15

Multi-agent networks are often modeled via interaction graphs, where the nodes represent the agents and the edges denote direct interactions between the corresponding agents. Interaction graphs have significant impact on the robustness of networked systems. One family of robust graphs is the random regular graphs. In this paper, we present a locally applicable reconfiguration scheme to build random regular graphs through self-organization. For any connected initial graph, the proposed scheme maintains connectivity and the average degree while minimizing the degree differences and randomizing the links. As such, if the average degree of the initial graph is an integer, then connected regular graphs are realized uniformly at random as time goes to infinity.

Regular Gleason Measures and Generalized Effect Algebras

Science.gov (United States)

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.

Adaptive discretizations for the choice of a Tikhonov regularization parameter in nonlinear inverse problems

International Nuclear Information System (INIS)

Kaltenbacher, Barbara; Kirchner, Alana; Vexler, Boris

2011-01-01

Parameter identification problems for partial differential equations usually lead to nonlinear inverse problems. A typical property of such problems is their instability, which requires regularization techniques, like, e.g., Tikhonov regularization. The main focus of this paper will be on efficient methods for determining a suitable regularization parameter by using adaptive finite element discretizations based on goal-oriented error estimators. A well-established method for the determination of a regularization parameter is the discrepancy principle where the residual norm, considered as a function i of the regularization parameter, should equal an appropriate multiple of the noise level. We suggest to solve the resulting scalar nonlinear equation by an inexact Newton method, where in each iteration step, a regularized problem is solved at a different discretization level. The proposed algorithm is an extension of the method suggested in Griesbaum A et al (2008 Inverse Problems 24 025025) for linear inverse problems, where goal-oriented error estimators for i and its derivative are used for adaptive refinement strategies in order to keep the discretization level as coarse as possible to save computational effort but fine enough to guarantee global convergence of the inexact Newton method. This concept leads to a highly efficient method for determining the Tikhonov regularization parameter for nonlinear ill-posed problems. Moreover, we prove that with the so-obtained regularization parameter and an also adaptively discretized Tikhonov minimizer, usual convergence and regularization results from the continuous setting can be recovered. As a matter of fact, it is shown that it suffices to use stationary points of the Tikhonov functional. The efficiency of the proposed method is demonstrated by means of numerical experiments. (paper)

Data Collection Method for Mobile Control Sink Node in Wireless Sensor Network Based on Compressive Sensing

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Ling Yongfa

2016-01-01

Full Text Available The paper proposes a mobile control sink node data collection method in the wireless sensor network based on compressive sensing. This method, with regular track, selects the optimal data collection points in the monitoring area via the disc method, calcu-lates the shortest path by using the quantum genetic algorithm, and hence determines the data collection route. Simulation results show that this method has higher network throughput and better energy efficiency, capable of collecting a huge amount of data with balanced energy consumption in the network.

High-resolution seismic data regularization and wavefield separation

Science.gov (United States)

Cao, Aimin; Stump, Brian; DeShon, Heather

2018-04-01

We present a new algorithm, non-equispaced fast antileakage Fourier transform (NFALFT), for irregularly sampled seismic data regularization. Synthetic tests from 1-D to 5-D show that the algorithm may efficiently remove leaked energy in the frequency wavenumber domain, and its corresponding regularization process is accurate and fast. Taking advantage of the NFALFT algorithm, we suggest a new method (wavefield separation) for the detection of the Earth's inner core shear wave with irregularly distributed seismic arrays or networks. All interfering seismic phases that propagate along the minor arc are removed from the time window around the PKJKP arrival. The NFALFT algorithm is developed for seismic data, but may also be used for other irregularly sampled temporal or spatial data processing.

Summation of Divergent Series and Zeldovich's Regularization Method

International Nuclear Information System (INIS)

Mur, V.D.; Pozdnyakov, S.G.; Popruzhenko, S.V.; Popov, V.S.

2005-01-01

A method for summing divergent series, including perturbation-theory series, is considered. This method is an analog of Zeldovich's regularization method in the theory of quasistationary states. It is shown that the method in question is more powerful than the well-known Abel and Borel methods, but that it is compatible with them (that is, it leads to the same value for the sum of a series). The constraints on the parameter domain that arise upon the removal of the regularization of divergent integrals by this method are discussed. The dynamical Stark shifts and widths of loosely bound s states in the field of a circularly polarized electromagnetic wave are calculated at various values of the Keldysh adiabaticity parameter and the multiquantum parameter

A convergence analysis of the iteratively regularized Gauss–Newton method under the Lipschitz condition

International Nuclear Information System (INIS)

Jin Qinian

2008-01-01

In this paper we consider the iteratively regularized Gauss–Newton method for solving nonlinear ill-posed inverse problems. Under merely the Lipschitz condition, we prove that this method together with an a posteriori stopping rule defines an order optimal regularization method if the solution is regular in some suitable sense

Mathematical Modeling the Geometric Regularity in Proteus Mirabilis Colonies

Science.gov (United States)

Zhang, Bin; Jiang, Yi; Minsu Kim Collaboration

Proteus Mirabilis colony exhibits striking spatiotemporal regularity, with concentric ring patterns with alternative high and low bacteria density in space, and periodicity for repetition process of growth and swarm in time. We present a simple mathematical model to explain the spatiotemporal regularity of P. Mirabilis colonies. We study a one-dimensional system. Using a reaction-diffusion model with thresholds in cell density and nutrient concentration, we recreated periodic growth and spread patterns, suggesting that the nutrient constraint and cell density regulation might be sufficient to explain the spatiotemporal periodicity in P. Mirabilis colonies. We further verify this result using a cell based model.

Multiple graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2013-10-01

Non-negative matrix factorization (NMF) has been widely used as a data representation method based on components. To overcome the disadvantage of NMF in failing to consider the manifold structure of a data set, graph regularized NMF (GrNMF) has been proposed by Cai et al. by constructing an affinity graph and searching for a matrix factorization that respects graph structure. Selecting a graph model and its corresponding parameters is critical for this strategy. This process is usually carried out by cross-validation or discrete grid search, which are time consuming and prone to overfitting. In this paper, we propose a GrNMF, called MultiGrNMF, in which the intrinsic manifold is approximated by a linear combination of several graphs with different models and parameters inspired by ensemble manifold regularization. Factorization metrics and linear combination coefficients of graphs are determined simultaneously within a unified object function. They are alternately optimized in an iterative algorithm, thus resulting in a novel data representation algorithm. Extensive experiments on a protein subcellular localization task and an Alzheimer\\'s disease diagnosis task demonstrate the effectiveness of the proposed algorithm. © 2013 Elsevier Ltd. All rights reserved.

77 FR 12567 - Proposed Information Collection; Comment Request; Submission of Conservation Efforts To Make...

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2012-03-01

... conservation plan or agreement, procedures for monitoring the effectiveness of the plan or agreement, and an...: Regular submission (extension of a currently approved collection). Affected Public: Business or other for... report for successful agreements. Estimated Total Annual Burden Hours: 3,300. Estimated Total Annual Cost...

Estimation of the global regularity of a multifractional Brownian motion

DEFF Research Database (Denmark)

Lebovits, Joachim; Podolskij, Mark

This paper presents a new estimator of the global regularity index of a multifractional Brownian motion. Our estimation method is based upon a ratio statistic, which compares the realized global quadratic variation of a multifractional Brownian motion at two different frequencies. We show that a ...... that a logarithmic transformation of this statistic converges in probability to the minimum of the Hurst functional parameter, which is, under weak assumptions, identical to the global regularity index of the path....

Do the majority of South Africans regularly consult traditional healers?

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Gabriel Louw

2016-12-01

Full Text Available Background The statutory recognition of traditional healers as healthcare practitioners in South Africa in terms of the Traditional Health Practitioners Act 22 of 2007 is based on various assumptions, opinions and generalizations. One of the prominent views is that the majority of South Africans regularly consult traditional healers. It even has been alleged that this number can be as high as 80 per cent of the South African population. For medical doctors and other health practitioners registered with the Health Professions Council of South Africa (HPCSA, this new statutory status of traditional health practitioners, means the required presence of not only a healthcare competitor that can overstock the healthcare market with service lending, medical claims and healthcare costs, but also a competitor prone to malpractice. Aims The study aimed to determine if the majority of South Africans regularly consult traditional healers. Methods This is an exploratory and descriptive study following the modern historical approach of investigation and literature review. The emphasis is on using current documentation like articles, books and newspapers, as primary sources to determine if the majority of South Africans regularly consult traditional healers. The findings are offered in narrative form. Results It is clear that there is no trustworthy statistics on the percentages of South Africans using traditional healers. A scientific survey is needed to determine the extent to which traditional healers are consulted. This will only be possible after the Traditional Health Practitioners Act No 22 has been fully enacted and traditional health practitioners have become fully active in the healthcare sector. Conclusion In poorer, rural areas no more than 11.2 per cent of the South African population regularly consult traditional healers, while the figure for the total population seems to be no more than 1.4 per cent. The argument that the majority of South

Boson models of quadrupole collective motion

International Nuclear Information System (INIS)

Zelevinskij, V.G.

1985-01-01

The subject of the lecture is the low-lying excitations of even-even (e-e) spherical nuclei. The predominant role of the quadrupole mode, which determines the structure of spectra and transitions, is obvious on the background of shell periodicity and pair correlations. Typical E2-transitions are strengthened Ω ∼ A 2/3 times in comparison with single particle evaluations. Together with the regularity of the whole picture it gives evidence about collectivization of quadrupole motion. The collective states are combined in bands, where the transition probability are especially great; frequencies ω of the strengthened transitions are small in comparison with pair separation energies of 2 E-bar ∼ 2 MeV. Thus, the description of low-lying excitations of spherical nuclei has to be based on three principles: collectivity (Ω >> 1), adiabaticity (τ ≡ ω/2E-bar << 1) and quadrupole symmetry

Describing chaotic attractors: Regular and perpetual points

Science.gov (United States)

Dudkowski, Dawid; Prasad, Awadhesh; Kapitaniak, Tomasz

2018-03-01

We study the concepts of regular and perpetual points for describing the behavior of chaotic attractors in dynamical systems. The idea of these points, which have been recently introduced to theoretical investigations, is thoroughly discussed and extended into new types of models. We analyze the correlation between regular and perpetual points, as well as their relation with phase space, showing the potential usefulness of both types of points in the qualitative description of co-existing states. The ability of perpetual points in finding attractors is indicated, along with its potential cause. The location of chaotic trajectories and sets of considered points is investigated and the study on the stability of systems is shown. The statistical analysis of the observing desired states is performed. We focus on various types of dynamical systems, i.e., chaotic flows with self-excited and hidden attractors, forced mechanical models, and semiconductor superlattices, exhibiting the universality of appearance of the observed patterns and relations.

Convex nonnegative matrix factorization with manifold regularization.

Science.gov (United States)

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.

Analytic stochastic regularization and gauge theories

International Nuclear Information System (INIS)

Abdalla, E.; Gomes, M.; Lima-Santos, A.

1987-04-01

We prove that analytic stochatic regularization braks gauge invariance. This is done by an explicit one loop calculation of the two three and four point vertex functions of the gluon field in scalar chromodynamics, which turns out not to be geuge invariant. We analyse the counter term structure, Langevin equations and the construction of composite operators in the general framework of stochastic quantization. (author) [pt

Verbal Working Memory Is Related to the Acquisition of Cross-Linguistic Phonological Regularities

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Evelyn Bosma

2017-09-01

Full Text Available Closely related languages share cross-linguistic phonological regularities, such as Frisian -âld [ͻ:t] and Dutch -oud [ʱut], as in the cognate pairs kâld [kͻ:t] – koud [kʱut] ‘cold’ and wâld [wͻ:t] – woud [wʱut] ‘forest’. Within Bybee’s (1995, 2001, 2008, 2010 network model, these regularities are, just like grammatical rules within a language, generalizations that emerge from schemas of phonologically and semantically related words. Previous research has shown that verbal working memory is related to the acquisition of grammar, but not vocabulary. This suggests that verbal working memory supports the acquisition of linguistic regularities. In order to test this hypothesis we investigated whether verbal working memory is also related to the acquisition of cross-linguistic phonological regularities. For three consecutive years, 5- to 8-year-old Frisian-Dutch bilingual children (n = 120 were tested annually on verbal working memory and a Frisian receptive vocabulary task that comprised four cognate categories: (1 identical cognates, (2 non-identical cognates that either do or (3 do not exhibit a phonological regularity between Frisian and Dutch, and (4 non-cognates. The results showed that verbal working memory had a significantly stronger effect on cognate category (2 than on the other three cognate categories. This suggests that verbal working memory is related to the acquisition of cross-linguistic phonological regularities. More generally, it confirms the hypothesis that verbal working memory plays a role in the acquisition of linguistic regularities.

SAR image regularization with fast approximate discrete minimization.

Science.gov (United States)

Denis, Loïc; Tupin, Florence; Darbon, Jérôme; Sigelle, Marc

2009-07-01

Synthetic aperture radar (SAR) images, like other coherent imaging modalities, suffer from speckle noise. The presence of this noise makes the automatic interpretation of images a challenging task and noise reduction is often a prerequisite for successful use of classical image processing algorithms. Numerous approaches have been proposed to filter speckle noise. Markov random field (MRF) modelization provides a convenient way to express both data fidelity constraints and desirable properties of the filtered image. In this context, total variation minimization has been extensively used to constrain the oscillations in the regularized image while preserving its edges. Speckle noise follows heavy-tailed distributions, and the MRF formulation leads to a minimization problem involving nonconvex log-likelihood terms. Such a minimization can be performed efficiently by computing minimum cuts on weighted graphs. Due to memory constraints, exact minimization, although theoretically possible, is not achievable on large images required by remote sensing applications. The computational burden of the state-of-the-art algorithm for approximate minimization (namely the alpha -expansion) is too heavy specially when considering joint regularization of several images. We show that a satisfying solution can be reached, in few iterations, by performing a graph-cut-based combinatorial exploration of large trial moves. This algorithm is applied to joint regularization of the amplitude and interferometric phase in urban area SAR images.

Prevalence and Correlates of Having a Regular Physician among Women Presenting for Induced Abortion.

Science.gov (United States)

Chor, Julie; Hebert, Luciana E; Hasselbacher, Lee A; Whitaker, Amy K

2016-01-01

To determine the prevalence and correlates of having a regular physician among women presenting for induced abortion. We conducted a retrospective review of women presenting to an urban, university-based family planning clinic for abortion between January 2008 and September 2011. We conducted bivariate analyses, comparing women with and without a regular physician, and multivariable regression modeling, to identify factors associated with not having a regular physician. Of 834 women, 521 (62.5%) had a regular physician and 313 (37.5%) did not. Women with a prior pregnancy, live birth, or spontaneous abortion were more likely than women without these experiences to have a regular physician. Women with a prior induced abortion were not more likely than women who had never had a prior induced abortion to have a regular physician. Compared with women younger than 18 years, women aged 18 to 26 years were less likely to have a physician (adjusted odds ratio [aOR], 0.25; 95% confidence interval [CI], 0.10-0.62). Women with a prior live birth had increased odds of having a regular physician compared with women without a prior pregnancy (aOR, 1.89; 95% CI, 1.13-3.16). Women without medical/fetal indications and who had not been victims of sexual assault (self-indicated) were less likely to report having a regular physician compared with women with medical/fetal indications (aOR, 0.55; 95% CI, 0.17-0.82). The abortion visit is a point of contact with a large number of women without a regular physician and therefore provides an opportunity to integrate women into health care. Copyright © 2016 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

Regularization and asymptotic expansion of certain distributions defined by divergent series

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Ricardo Estrada

1995-01-01

Full Text Available The regularization of the distribution ∑n=−∞∞δ(x−pn. which gives a regularized value to the divergent series ∑n=−∞∞φ(pn is obtained in several spaces of test functions. The asymptotic expansion as ϵ→0+of series of the type ∑n=0∞φ(ϵ pn is also obtained.

Instabilities of the zeta-function regularization in the presence of symmetries

International Nuclear Information System (INIS)

Rasetti, M.

1980-01-01

The zeta-function regularization method requires the calculation of the spectrum-generating function zeta sub(M) of a generic real, elliptic, self-adjoint differential operator on a manifold M. An asymptotic expansion for zeta sub(M) is given for the class of all symmetric spaces of rank 1, sufficient to compute its Mellin transform and deduce the regularization of the corresponding quadratic path integrals. The summability properties of the generalized zeta-function introduce physical instabilities in the system as negative specific heat. The technique (and the instability as well) is shown to hold - under the assumed symmetry properties - in any dimension (preserving both the global and local properties of the manifold, as opposed to the dimensional regularization, where one adds extra flat dimensions only). (author)

DEVELOPMENT OF INNOVATION MANAGEMENT THEORY BASED ON SYSTEM-WIDE REGULARITIES

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Violetta N. Volkova

2013-01-01

Full Text Available The problem of a comprehension of the innovation management theory and an ability of its development on basis of system theory is set up. The authors consider features of management of socio-economic systems as open, self-organising systems with active components and give a classification of the systems’ regularities illustrating these features. The need to take into account the regularities of emergent, hierarchical order, equifinality, Ashby’s law of requisite variety, historicity and self-organization is shown.

Regularization methods in Banach spaces

CERN Document Server

Schuster, Thomas; Hofmann, Bernd; Kazimierski, Kamil S

2012-01-01

Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Usually the mathematical model of an inverse problem consists of an operator equation of the first kind and often the associated forward operator acts between Hilbert spaces. However, for numerous problems the reasons for using a Hilbert space setting seem to be based rather on conventions than on an approprimate and realistic model choice, so often a Banach space setting would be closer to reality. Furthermore, sparsity constraints using general Lp-norms or the B

Determining the flexibility of regular and chaotic attractors

International Nuclear Information System (INIS)

Marhl, Marko; Perc, Matjaz

2006-01-01

We present an overview of measures that are appropriate for determining the flexibility of regular and chaotic attractors. In particular, we focus on those system properties that constitute its responses to external perturbations. We deploy a systematic approach, first introducing the simplest measure given by the local divergence of the system along the attractor, and then develop more rigorous mathematical tools for estimating the flexibility of the system's dynamics. The presented measures are tested on the regular Brusselator and chaotic Hindmarsh-Rose model of an excitable neuron with equal success, thus indicating the overall effectiveness and wide applicability range of the proposed theory. Since responses of dynamical systems to external signals are crucial in several scientific disciplines, and especially in natural sciences, we discuss several important aspects and biological implications of obtained results

Point-splitting regularization of composite operators and anomalies

International Nuclear Information System (INIS)

Novotny, J.; Schnabl, M.

2000-01-01

The point-splitting regularization technique for composite operators is discussed in connection with anomaly calculation. We present a pedagogical and self-contained review of the topic with an emphasis on the technical details. We also develop simple algebraic tools to handle the path ordered exponential insertions used within the covariant and non-covariant version of the point-splitting method. The method is then applied to the calculation of the chiral, vector, trace, translation and Lorentz anomalies within diverse versions of the point-splitting regularization and a connection between the results is described. As an alternative to the standard approach we use the idea of deformed point-split transformation and corresponding Ward-Takahashi identities rather than an application of the equation of motion, which seems to reduce the complexity of the calculations. (orig.)

Nonlocal discrete regularization on weighted graphs: a framework for image and manifold processing.

Science.gov (United States)

Elmoataz, Abderrahim; Lezoray, Olivier; Bougleux, Sébastien

2008-07-01

We introduce a nonlocal discrete regularization framework on weighted graphs of the arbitrary topologies for image and manifold processing. The approach considers the problem as a variational one, which consists of minimizing a weighted sum of two energy terms: a regularization one that uses a discrete weighted p-Dirichlet energy and an approximation one. This is the discrete analogue of recent continuous Euclidean nonlocal regularization functionals. The proposed formulation leads to a family of simple and fast nonlinear processing methods based on the weighted p-Laplace operator, parameterized by the degree p of regularity, the graph structure and the graph weight function. These discrete processing methods provide a graph-based version of recently proposed semi-local or nonlocal processing methods used in image and mesh processing, such as the bilateral filter, the TV digital filter or the nonlocal means filter. It works with equal ease on regular 2-D and 3-D images, manifolds or any data. We illustrate the abilities of the approach by applying it to various types of images, meshes, manifolds, and data represented as graphs.

Restrictive metric regularity and generalized differential calculus in Banach spaces

Directory of Open Access Journals (Sweden)

Bingwu Wang

2004-10-01

Full Text Available We consider nonlinear mappings f:X→Y between Banach spaces and study the notion of restrictive metric regularity of f around some point x¯, that is, metric regularity of f from X into the metric space E=f(X. Some sufficient as well as necessary and sufficient conditions for restrictive metric regularity are obtained, which particularly include an extension of the classical Lyusternik-Graves theorem in the case when f is strictly differentiable at x¯ but its strict derivative ∇f(x¯ is not surjective. We develop applications of the results obtained and some other techniques in variational analysis to generalized differential calculus involving normal cones to nonsmooth and nonconvex sets, coderivatives of set-valued mappings, as well as first-order and second-order subdifferentials of extended real-valued functions.

A Regularization SAA Scheme for a Stochastic Mathematical Program with Complementarity Constraints

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Yu-xin Li

2014-01-01

Full Text Available To reflect uncertain data in practical problems, stochastic versions of the mathematical program with complementarity constraints (MPCC have drawn much attention in the recent literature. Our concern is the detailed analysis of convergence properties of a regularization sample average approximation (SAA method for solving a stochastic mathematical program with complementarity constraints (SMPCC. The analysis of this regularization method is carried out in three steps: First, the almost sure convergence of optimal solutions of the regularized SAA problem to that of the true problem is established by the notion of epiconvergence in variational analysis. Second, under MPCC-MFCQ, which is weaker than MPCC-LICQ, we show that any accumulation point of Karash-Kuhn-Tucker points of the regularized SAA problem is almost surely a kind of stationary point of SMPCC as the sample size tends to infinity. Finally, some numerical results are reported to show the efficiency of the method proposed.

Comparison of different kinds of regularization of perturbation calculations in quantum field theory

International Nuclear Information System (INIS)

Brzezowski, S.

1977-01-01

Different methods of regularization in quantum field theory are compared. It is argued that a regularization is correct if it gives the amplitude with analytical properties predicted by the Cutkosky lemma. (author)

Anaemia in Patients with Diabetes Mellitus attending regular ...

African Journals Online (AJOL)

Anaemia in Patients with Diabetes Mellitus attending regular Diabetic ... Nigerian Journal of Health and Biomedical Sciences ... some patients may omit important food items in their daily diet for fear of increasing their blood sugar level.

Stability of negative ionization fronts: Regularization by electric screening?

International Nuclear Information System (INIS)

Arrayas, Manuel; Ebert, Ute

2004-01-01

We recently have proposed that a reduced interfacial model for streamer propagation is able to explain spontaneous branching. Such models require regularization. In the present paper we investigate how transversal Fourier modes of a planar ionization front are regularized by the electric screening length. For a fixed value of the electric field ahead of the front we calculate the dispersion relation numerically. These results guide the derivation of analytical asymptotes for arbitrary fields: for small wave-vector k, the growth rate s(k) grows linearly with k, for large k, it saturates at some positive plateau value. We give a physical interpretation of these results

Sparse reconstruction by means of the standard Tikhonov regularization

International Nuclear Information System (INIS)

Lu Shuai; Pereverzev, Sergei V

2008-01-01

It is a common belief that Tikhonov scheme with || · ||L 2 -penalty fails in sparse reconstruction. We are going to show, however, that this standard regularization can help if the stability measured in L 1 -norm will be properly taken into account in the choice of the regularization parameter. The crucial point is that now a stability bound may depend on the bases with respect to which the solution of the problem is assumed to be sparse. We discuss how such a stability can be estimated numerically and present the results of computational experiments giving the evidence of the reliability of our approach.

Graded effects of regularity in language revealed by N400 indices of morphological priming.

Science.gov (United States)

Kielar, Aneta; Joanisse, Marc F

2010-07-01

Differential electrophysiological effects for regular and irregular linguistic forms have been used to support the theory that grammatical rules are encoded using a dedicated cognitive mechanism. The alternative hypothesis is that language systematicities are encoded probabilistically in a way that does not categorically distinguish rule-like and irregular forms. In the present study, this matter was investigated more closely by focusing specifically on whether the regular-irregular distinction in English past tenses is categorical or graded. We compared the ERP priming effects of regulars (baked-bake), vowel-change irregulars (sang-sing), and "suffixed" irregulars that display a partial regularity (suffixed irregular verbs, e.g., slept-sleep), as well as forms that are related strictly along formal or semantic dimensions. Participants performed a visual lexical decision task with either visual (Experiment 1) or auditory prime (Experiment 2). Stronger N400 priming effects were observed for regular than vowel-change irregular verbs, whereas suffixed irregulars tended to group with regular verbs. Subsequent analyses decomposed early versus late-going N400 priming, and suggested that differences among forms can be attributed to the orthographic similarity of prime and target. Effects of morphological relatedness were observed in the later-going time period, however, we failed to observe true regular-irregular dissociations in either experiment. The results indicate that morphological effects emerge from the interaction of orthographic, phonological, and semantic overlap between words.

Detecting regular sound changes in linguistics as events of concerted evolution.

Science.gov (United States)

Hruschka, Daniel J; Branford, Simon; Smith, Eric D; Wilkins, Jon; Meade, Andrew; Pagel, Mark; Bhattacharya, Tanmoy

2015-01-05

Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular sound change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Radiometric characterization of Landsat Collection 1 products

Science.gov (United States)

Micijevic, Esad; Haque, Md. Obaidul; Mishra, Nischal

2017-09-01

Landsat data in the U.S. Geological Survey (USGS) archive are being reprocessed to generate a tiered collection of consistently geolocated and radiometrically calibrated products that are suitable for time series analyses. With the implementation of the collection management, no major updates will be made to calibration of the Landsat sensors within a collection. Only calibration parameters needed to maintain the established calibration trends without an effect on derived environmental records will be regularly updated, while all other changes will be deferred to a new collection. This first collection, Collection 1, incorporates various radiometric calibration updates to all Landsat sensors including absolute and relative gains for Landsat 8 Operational Land Imager (OLI), stray light correction for Landsat 8 Thermal Infrared Sensor (TIRS), absolute gains for Landsat 4 and 5 Thematic Mappers (TM), recalibration of Landsat 1-5 Multispectral Scanners (MSS) to ensure radiometric consistency among different formats of archived MSS data, and a transfer of Landsat 8 OLI reflectance based calibration to all previous Landsat sensors. While all OLI/TIRS, ETM+ and majority of TM data have already been reprocessed to Collection 1, a completion of MSS and remaining TM data reprocessing is expected by the end of this year. It is important to note that, although still available for download from the USGS web pages, the products generated using the Pre-Collection processing do not benefit from the latest radiometric calibration updates. In this paper, we are assessing radiometry of solar reflective bands in Landsat Collection 1 products through analysis of trends in on-board calibrator and pseudo invariant site (PICS) responses.

28 CFR 540.50 - Visits to inmates not in regular population status.

Science.gov (United States)

2010-07-01

... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Visits to inmates not in regular population status. 540.50 Section 540.50 Judicial Administration BUREAU OF PRISONS, DEPARTMENT OF JUSTICE... not in regular population status. (a) Admission and holdover status. The Warden may limit to the...

The impact of comorbid cannabis and methamphetamine use on mental health among regular ecstasy users.

Science.gov (United States)

Scott, Laura A; Roxburgh, Amanda; Bruno, Raimondo; Matthews, Allison; Burns, Lucy

2012-09-01

Residual effects of ecstasy use induce neurotransmitter changes that make it biologically plausible that extended use of the drug may induce psychological distress. However, there has been only mixed support for this in the literature. The presence of polysubstance use is a confounding factor. The aim of this study was to investigate whether regular cannabis and/or regular methamphetamine use confers additional risk of poor mental health and high levels of psychological distress, beyond regular ecstasy use alone. Three years of data from a yearly, cross-sectional, quantitative survey of Australian regular ecstasy users was examined. Participants were divided into four groups according to whether they regularly (at least monthly) used ecstasy only (n=936), ecstasy and weekly cannabis (n=697), ecstasy and weekly methamphetamine (n=108) or ecstasy, weekly cannabis and weekly methamphetamine (n=180). Self-reported mental health problems and Kessler Psychological Distress Scale (K10) were examined. Approximately one-fifth of participants self-reported at least one mental health problem, most commonly depression and anxiety. The addition of regular cannabis and/or methamphetamine use substantially increases the likelihood of self-reported mental health problems, particularly with regard to paranoia, over regular ecstasy use alone. Regular cannabis use remained significantly associated with self reported mental health problems even when other differences between groups were accounted for. Regular cannabis and methamphetamine use was also associated with earlier initiation to ecstasy use. These findings suggest that patterns of drug use can help identify at risk groups that could benefit from targeted approaches in education and interventions. Given that early initiation to substance use was more common in those with regular cannabis and methamphetamine use and given that this group had a higher likelihood of mental health problems, work around delaying onset of initiation

Regular examinations for toxic maculopathy in long-term chloroquine or hydroxychloroquine users.

Science.gov (United States)

Nika, Melisa; Blachley, Taylor S; Edwards, Paul; Lee, Paul P; Stein, Joshua D

2014-10-01

According to evidence-based, expert recommendations, long-term users of chloroquine or hydroxychloroquine sulfate should undergo regular visits to eye care providers and diagnostic testing to check for maculopathy. To determine whether patients with rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE) taking chloroquine or hydroxychloroquine are regularly visiting eye care providers and being screened for maculopathy. Patients with RA or SLE who were continuously enrolled in a particular managed care network for at least 5 years between January 1, 2001, and December 31, 2011, were studied. Patients' amount of chloroquine or hydroxychloroquine use in the 5 years since the initial RA or SLE diagnosis was calculated, along with their number of eye care visits and diagnostic tests for maculopathy. Those at high risk for maculopathy were identified. Logistic regression was performed to assess potential factors associated with regular eye care visits (annual visits in ≥3 of 5 years) among chloroquine or hydroxychloroquine users, including those at highest risk for maculopathy. Among chloroquine or hydroxychloroquine users and those at high risk for toxic maculopathy, the proportions with regular eye care visits and diagnostic testing, as well as the likelihood of regular eye care visits. Among 18 051 beneficiaries with RA or SLE, 6339 (35.1%) had at least 1 record of chloroquine or hydroxychloroquine use, and 1409 (7.8%) had used chloroquine or hydroxychloroquine for at least 4 years. Among those at high risk for maculopathy, 27.9% lacked regular eye care visits, 6.1% had no visits to eye care providers, and 34.5% had no diagnostic testing for maculopathy during the 5-year period. Among high-risk patients, each additional month of chloroquine or hydroxychloroquine use was associated with a 2.0% increased likelihood of regular eye care (adjusted odds ratio, 1.02; 95% CI, 1.01-1.03). High-risk patients whose SLE or RA was managed by rheumatologists had a 77