New approach to solve symmetric fully fuzzy linear systems

Indian Academy of Sciences (India)

concepts of fuzzy set theory and then define a fully fuzzy linear system of equations. .... To represent the above problem as fully fuzzy linear system, we represent x .... Fully fuzzy linear systems can be solved by Linear programming approach, ...

CFD analysis of linear compressors considering load conditions

Science.gov (United States)

Bae, Sanghyun; Oh, Wonsik

2017-08-01

This paper is a study on computational fluid dynamics (CFD) analysis of linear compressor considering load conditions. In the conventional CFD analysis of the linear compressor, the load condition was not considered in the behaviour of the piston. In some papers, behaviour of piston is assumed as sinusoidal motion provided by user defined function (UDF). In the reciprocating type compressor, the stroke of the piston is restrained by the rod, while the stroke of the linear compressor is not restrained, and the stroke changes depending on the load condition. The greater the pressure difference between the discharge refrigerant and the suction refrigerant, the more the centre point of the stroke is pushed backward. And the behaviour of the piston is not a complete sine wave. For this reason, when the load condition changes in the CFD analysis of the linear compressor, it may happen that the ANSYS code is changed or unfortunately the modelling is changed. In addition, a separate analysis or calculation is required to find a stroke that meets the load condition, which may contain errors. In this study, the coupled mechanical equations and electrical equations are solved using the UDF, and the behaviour of the piston is solved considering the pressure difference across the piston. Using the above method, the stroke of the piston with respect to the motor specification of the analytical model can be calculated according to the input voltage, and the piston behaviour can be realized considering the thrust amount due to the pressure difference.

A two-dimensional linear elasticity problem for anisotropic materials, solved with a parallelization code

Directory of Open Access Journals (Sweden)

Mihai-Victor PRICOP

2010-09-01

Full Text Available The present paper introduces a numerical approach of static linear elasticity equations for anisotropic materials. The domain and boundary conditions are simple, to enhance an easy implementation of the finite difference scheme. SOR and gradient are used to solve the resulting linear system. The simplicity of the geometry is also useful for MPI parallelization of the code.

Developing Ill-Structured Problem-Solving Skills through Wilderness Education

Science.gov (United States)

Collins, Rachel H.; Sibthorp, Jim; Gookin, John

2016-01-01

In a society that is becoming more dynamic, complex, and diverse, the ability to solve ill-structured problems (ISPs) has become an increasingly critical skill. Students who enter adult roles with the cognitive skills to address ISPs will be better able to assume roles in the emerging economies. Opportunities to develop and practice these skills…

New approach to solve fully fuzzy system of linear equations using ...

Indian Academy of Sciences (India)

Known example problems are solved to illustrate the efficacy and ... The concept of fuzzy set and fuzzy number were first introduced by Zadeh .... (iii) Fully fuzzy linear systems can be solved by linear programming approach, Gauss elim-.

ADM For Solving Linear Second-Order Fredholm Integro-Differential Equations

Science.gov (United States)

Karim, Mohd F.; Mohamad, Mahathir; Saifullah Rusiman, Mohd; Che-Him, Norziha; Roslan, Rozaini; Khalid, Kamil

2018-04-01

In this paper, we apply Adomian Decomposition Method (ADM) as numerically analyse linear second-order Fredholm Integro-differential Equations. The approximate solutions of the problems are calculated by Maple package. Some numerical examples have been considered to illustrate the ADM for solving this equation. The results are compared with the existing exact solution. Thus, the Adomian decomposition method can be the best alternative method for solving linear second-order Fredholm Integro-Differential equation. It converges to the exact solution quickly and in the same time reduces computational work for solving the equation. The result obtained by ADM shows the ability and efficiency for solving these equations.

Matrix form of Legendre polynomials for solving linear integro-differential equations of high order

Science.gov (United States)

Kammuji, M.; Eshkuvatov, Z. K.; Yunus, Arif A. M.

2017-04-01

This paper presents an effective approximate solution of high order of Fredholm-Volterra integro-differential equations (FVIDEs) with boundary condition. Legendre truncated series is used as a basis functions to estimate the unknown function. Matrix operation of Legendre polynomials is used to transform FVIDEs with boundary conditions into matrix equation of Fredholm-Volterra type. Gauss Legendre quadrature formula and collocation method are applied to transfer the matrix equation into system of linear algebraic equations. The latter equation is solved by Gauss elimination method. The accuracy and validity of this method are discussed by solving two numerical examples and comparisons with wavelet and methods.

Convergence of hybrid methods for solving non-linear partial ...

African Journals Online (AJOL)

This paper is concerned with the numerical solution and convergence analysis of non-linear partial differential equations using a hybrid method. The solution technique involves discretizing the non-linear system of PDE to obtain a corresponding non-linear system of algebraic difference equations to be solved at each time ...

Planning under uncertainty solving large-scale stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G. [Stanford Univ., CA (United States). Dept. of Operations Research]|[Technische Univ., Vienna (Austria). Inst. fuer Energiewirtschaft

1992-12-01

For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.

Diagnosis of the Ill-condition of the RFM Based on Condition Index and Variance Decomposition Proportion (CIVDP)

International Nuclear Information System (INIS)

Qing, Zhou; Weili, Jiao; Tengfei, Long

2014-01-01

The Rational Function Model (RFM) is a new generalized sensor model. It does not need the physical parameters of sensors to achieve a high accuracy that is compatible to the rigorous sensor models. At present, the main method to solve RPCs is the Least Squares Estimation. But when coefficients has a large number or the distribution of the control points is not even, the classical least square method loses its superiority due to the ill-conditioning problem of design matrix. Condition Index and Variance Decomposition Proportion (CIVDP) is a reliable method for diagnosing the multicollinearity among the design matrix. It can not only detect the multicollinearity, but also can locate the parameters and show the corresponding columns in the design matrix. In this paper, the CIVDP method is used to diagnose the ill-condition problem of the RFM and to find the multicollinearity in the normal matrix

Diagnosis of the Ill-condition of the RFM Based on Condition Index and Variance Decomposition Proportion (CIVDP)

Science.gov (United States)

Qing, Zhou; Weili, Jiao; Tengfei, Long

2014-03-01

The Rational Function Model (RFM) is a new generalized sensor model. It does not need the physical parameters of sensors to achieve a high accuracy that is compatible to the rigorous sensor models. At present, the main method to solve RPCs is the Least Squares Estimation. But when coefficients has a large number or the distribution of the control points is not even, the classical least square method loses its superiority due to the ill-conditioning problem of design matrix. Condition Index and Variance Decomposition Proportion (CIVDP) is a reliable method for diagnosing the multicollinearity among the design matrix. It can not only detect the multicollinearity, but also can locate the parameters and show the corresponding columns in the design matrix. In this paper, the CIVDP method is used to diagnose the ill-condition problem of the RFM and to find the multicollinearity in the normal matrix.

Galerkin projection methods for solving multiple related linear systems

Energy Technology Data Exchange (ETDEWEB)

Chan, T.F.; Ng, M.; Wan, W.L.

1996-12-31

We consider using Galerkin projection methods for solving multiple related linear systems A{sup (i)}x{sup (i)} = b{sup (i)} for 1 {le} i {le} s, where A{sup (i)} and b{sup (i)} are different in general. We start with the special case where A{sup (i)} = A and A is symmetric positive definite. The method generates a Krylov subspace from a set of direction vectors obtained by solving one of the systems, called the seed system, by the CG method and then projects the residuals of other systems orthogonally onto the generated Krylov subspace to get the approximate solutions. The whole process is repeated with another unsolved system as a seed until all the systems are solved. We observe in practice a super-convergence behaviour of the CG process of the seed system when compared with the usual CG process. We also observe that only a small number of restarts is required to solve all the systems if the right-hand sides are close to each other. These two features together make the method particularly effective. In this talk, we give theoretical proof to justify these observations. Furthermore, we combine the advantages of this method and the block CG method and propose a block extension of this single seed method. The above procedure can actually be modified for solving multiple linear systems A{sup (i)}x{sup (i)} = b{sup (i)}, where A{sup (i)} are now different. We can also extend the previous analytical results to this more general case. Applications of this method to multiple related linear systems arising from image restoration and recursive least squares computations are considered as examples.

Students' errors in solving linear equation word problems: Case ...

African Journals Online (AJOL)

The study examined errors students make in solving linear equation word problems with a view to expose the nature of these errors and to make suggestions for classroom teaching. A diagnostic test comprising 10 linear equation word problems, was administered to a sample (n=130) of senior high school first year Home ...

A logic circuit for solving linear function by digital method

International Nuclear Information System (INIS)

Ma Yonghe

1986-01-01

A mathematical method for determining the linear relation of physical quantity with rediation intensity is described. A logic circuit has been designed for solving linear function by digital method. Some applications and the circuit function are discussed

A recurrent neural network for solving bilevel linear programming problem.

Science.gov (United States)

He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie; Huang, Junjian

2014-04-01

In this brief, based on the method of penalty functions, a recurrent neural network (NN) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP). Compared with the existing NNs for BLPP, the model has the least number of state variables and simple structure. Using nonsmooth analysis, the theory of differential inclusions, and Lyapunov-like method, the equilibrium point sequence of the proposed NNs can approximately converge to an optimal solution of BLPP under certain conditions. Finally, the numerical simulations of a supply chain distribution model have shown excellent performance of the proposed recurrent NNs.

Chosen interval methods for solving linear interval systems with special type of matrix

Science.gov (United States)

Szyszka, Barbara

2013-10-01

The paper is devoted to chosen direct interval methods for solving linear interval systems with special type of matrix. This kind of matrix: band matrix with a parameter, from finite difference problem is obtained. Such linear systems occur while solving one dimensional wave equation (Partial Differential Equations of hyperbolic type) by using the central difference interval method of the second order. Interval methods are constructed so as the errors of method are enclosed in obtained results, therefore presented linear interval systems contain elements that determining the errors of difference method. The chosen direct algorithms have been applied for solving linear systems because they have no errors of method. All calculations were performed in floating-point interval arithmetic.

Solving linear inequalities in a least squares sense

Energy Technology Data Exchange (ETDEWEB)

Bramley, R.; Winnicka, B. [Indiana Univ., Bloomington, IN (United States)

1994-12-31

Let A {element_of} {Re}{sup mxn} be an arbitrary real matrix, and let b {element_of} {Re}{sup m} a given vector. A familiar problem in computational linear algebra is to solve the system Ax = b in a least squares sense; that is, to find an x* minimizing {parallel}Ax {minus} b{parallel}, where {parallel} {center_dot} {parallel} refers to the vector two-norm. Such an x* solves the normal equations A{sup T}(Ax {minus} b) = 0, and the optimal residual r* = b {minus} Ax* is unique (although x* need not be). The least squares problem is usually interpreted as corresponding to multiple observations, represented by the rows of A and b, on a vector of data x. The observations may be inconsistent, and in this case a solution is sought that minimizes the norm of the residuals. A less familiar problem to numerical linear algebraists is the solution of systems of linear inequalities Ax {le} b in a least squares sense, but the motivation is similar: if a set of observations places upper or lower bounds on linear combinations of variables, the authors want to find x* minimizing {parallel} (Ax {minus} b){sub +} {parallel}, where the i{sup th} component of the vector v{sub +} is the maximum of zero and the i{sup th} component of v.

Stress-constrained truss topology optimization problems that can be solved by linear programming

DEFF Research Database (Denmark)

Stolpe, Mathias; Svanberg, Krister

2004-01-01

We consider the problem of simultaneously selecting the material and determining the area of each bar in a truss structure in such a way that the cost of the structure is minimized subject to stress constraints under a single load condition. We show that such problems can be solved by linear...... programming to give the global optimum, and that two different materials are always sufficient in an optimal structure....

Mathematical Abstraction in the Solving of Ill-Structured Problems by Elementary School Students in Korea

Science.gov (United States)

Hong, Jee Yun; Kim, Min Kyeong

2016-01-01

Ill-structured problems can be regarded as one of the measures that meet recent social needs emphasizing students' abilities to solve real-life problems. This study aimed to analyze the mathematical abstraction process in solving such problems, and to identify the mathematical abstraction level ([I] Recognition of mathematical structure through…

The intelligence of dual simplex method to solve linear fractional fuzzy transportation problem.

Science.gov (United States)

Narayanamoorthy, S; Kalyani, S

2015-01-01

An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.

The Effect of an Extended Wilderness Education Experience on Ill-Structured Problem-Solving Skill Development in Emerging Adult Students

Science.gov (United States)

Collins, Rachel H.

2014-01-01

In a society that is becoming more dynamic, complex, and diverse, the ability to solve ill-structured problems has become an increasingly critical skill. Emerging adults are at a critical life stage that is an ideal time to develop the skills needed to solve ill-structured problems (ISPs) as they are transitioning to adult roles and starting to…

The Intelligence of Dual Simplex Method to Solve Linear Fractional Fuzzy Transportation Problem

Directory of Open Access Journals (Sweden)

S. Narayanamoorthy

2015-01-01

Full Text Available An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.

A goal programming procedure for solving fuzzy multiobjective fractional linear programming problems

Directory of Open Access Journals (Sweden)

Tunjo Perić

2014-12-01

Full Text Available This paper presents a modification of Pal, Moitra and Maulik's goal programming procedure for fuzzy multiobjective linear fractional programming problem solving. The proposed modification of the method allows simpler solving of economic multiple objective fractional linear programming (MOFLP problems, enabling the obtained solutions to express the preferences of the decision maker defined by the objective function weights. The proposed method is tested on the production planning example.

Solution of linear ill-posed problems using overcomplete dictionaries

OpenAIRE

Pensky, Marianna

2016-01-01

In the present paper we consider application of overcomplete dictionaries to solution of general ill-posed linear inverse problems. Construction of an adaptive optimal solution for such problems usually relies either on a singular value decomposition or representation of the solution via an orthonormal basis. The shortcoming of both approaches lies in the fact that, in many situations, neither the eigenbasis of the linear operator nor a standard orthonormal basis constitutes an appropriate co...

Solving polynomial differential equations by transforming them to linear functional-differential equations

OpenAIRE

Nahay, John Michael

2008-01-01

We present a new approach to solving polynomial ordinary differential equations by transforming them to linear functional equations and then solving the linear functional equations. We will focus most of our attention upon the first-order Abel differential equation with two nonlinear terms in order to demonstrate in as much detail as possible the computations necessary for a complete solution. We mention in our section on further developments that the basic transformation idea can be generali...

Approximate source conditions for nonlinear ill-posed problems—chances and limitations

International Nuclear Information System (INIS)

Hein, Torsten; Hofmann, Bernd

2009-01-01

In the recent past the authors, with collaborators, have published convergence rate results for regularized solutions of linear ill-posed operator equations by avoiding the usual assumption that the solutions satisfy prescribed source conditions. Instead the degree of violation of such source conditions is expressed by distance functions d(R) depending on a radius R ≥ 0 which is an upper bound of the norm of source elements under consideration. If d(R) tends to zero as R → ∞ an appropriate balancing of occurring regularization error terms yields convergence rates results. This approach was called the method of approximate source conditions, originally developed in a Hilbert space setting. The goal of this paper is to formulate chances and limitations of an application of this method to nonlinear ill-posed problems in reflexive Banach spaces and to complement the field of low order convergence rates results in nonlinear regularization theory. In particular, we are going to establish convergence rates for a variant of Tikhonov regularization. To keep structural nonlinearity conditions simple, we update the concept of degree of nonlinearity in Hilbert spaces to a Bregman distance setting in Banach spaces

The Role of Content Knowledge in Ill-Structured Problem Solving for High School Physics Students

Science.gov (United States)

Milbourne, Jeff; Wiebe, Eric

2018-02-01

While Physics Education Research has a rich tradition of problem-solving scholarship, most of the work has focused on more traditional, well-defined problems. Less work has been done with ill-structured problems, problems that are better aligned with the engineering and design-based scenarios promoted by the Next Generation Science Standards. This study explored the relationship between physics content knowledge and ill-structured problem solving for two groups of high school students with different levels of content knowledge. Both groups of students completed an ill-structured problem set, using a talk-aloud procedure to narrate their thought process as they worked. Analysis of the data focused on identifying students' solution pathways, as well as the obstacles that prevented them from reaching "reasonable" solutions. Students with more content knowledge were more successful reaching reasonable solutions for each of the problems, experiencing fewer obstacles. These students also employed a greater variety of solution pathways than those with less content knowledge. Results suggest that a student's solution pathway choice may depend on how she perceives the problem.

New approach to solve symmetric fully fuzzy linear systems

Indian Academy of Sciences (India)

In this paper, we present a method to solve fully fuzzy linear systems with symmetric coefficient matrix. The symmetric coefficient matrix is decomposed into two systems of equations by using Cholesky method and then a solution can be obtained. Numerical examples are given to illustrate our method.

Approximate Method for Solving the Linear Fuzzy Delay Differential Equations

Directory of Open Access Journals (Sweden)

S. Narayanamoorthy

2015-01-01

Full Text Available We propose an algorithm of the approximate method to solve linear fuzzy delay differential equations using Adomian decomposition method. The detailed algorithm of the approach is provided. The approximate solution is compared with the exact solution to confirm the validity and efficiency of the method to handle linear fuzzy delay differential equation. To show this proper features of this proposed method, numerical example is illustrated.

New approach to solve fully fuzzy system of linear equations using ...

Indian Academy of Sciences (India)

This paper proposes two new methods to solve fully fuzzy system of linear equations. The fuzzy system has been converted to a crisp system of linear equations by using single and double parametric form of fuzzy numbers to obtain the non-negative solution. Double parametric form of fuzzy numbers is defined and applied ...

Solving large-scale sparse eigenvalue problems and linear systems of equations for accelerator modeling

International Nuclear Information System (INIS)

Gene Golub; Kwok Ko

2009-01-01

The solutions of sparse eigenvalue problems and linear systems constitute one of the key computational kernels in the discretization of partial differential equations for the modeling of linear accelerators. The computational challenges faced by existing techniques for solving those sparse eigenvalue problems and linear systems call for continuing research to improve on the algorithms so that ever increasing problem size as required by the physics application can be tackled. Under the support of this award, the filter algorithm for solving large sparse eigenvalue problems was developed at Stanford to address the computational difficulties in the previous methods with the goal to enable accelerator simulations on then the world largest unclassified supercomputer at NERSC for this class of problems. Specifically, a new method, the Hemitian skew-Hemitian splitting method, was proposed and researched as an improved method for solving linear systems with non-Hermitian positive definite and semidefinite matrices.

Students' errors in solving linear equation word problems: Case ...

African Journals Online (AJOL)

kofi.mereku

Development in most areas of life is based on effective knowledge of science and ... Problem solving, as used in mathematics education literature, refers ... word problems, on the other hand, are those linear equation tasks or ... taught LEWPs in the junior high school, many of them reach the senior high school without a.

Mathematics Literacy of Secondary Students in Solving Simultanenous Linear Equations

Science.gov (United States)

Sitompul, R. S. I.; Budayasa, I. K.; Masriyah

2018-01-01

This study examines the profile of secondary students’ mathematical literacy in solving simultanenous linear equations problems in terms of cognitive style of visualizer and verbalizer. This research is a descriptive research with qualitative approach. The subjects in this research consist of one student with cognitive style of visualizer and one student with cognitive style of verbalizer. The main instrument in this research is the researcher herself and supporting instruments are cognitive style tests, mathematics skills tests, problem-solving tests and interview guidelines. Research was begun by determining the cognitive style test and mathematics skill test. The subjects chosen were given problem-solving test about simultaneous linear equations and continued with interview. To ensure the validity of the data, the researcher conducted data triangulation; the steps of data reduction, data presentation, data interpretation, and conclusion drawing. The results show that there is a similarity of visualizer and verbalizer-cognitive style in identifying and understanding the mathematical structure in the process of formulating. There are differences in how to represent problems in the process of implementing, there are differences in designing strategies and in the process of interpreting, and there are differences in explaining the logical reasons.

CHEBYSHEV ACCELERATION TECHNIQUE FOR SOLVING FUZZY LINEAR SYSTEM

Directory of Open Access Journals (Sweden)

S.H. Nasseri

2011-07-01

Full Text Available In this paper, Chebyshev acceleration technique is used to solve the fuzzy linear system (FLS. This method is discussed in details and followed by summary of some other acceleration techniques. Moreover, we show that in some situations that the methods such as Jacobi, Gauss-Sidel, SOR and conjugate gradient is divergent, our proposed method is applicable and the acquired results are illustrated by some numerical examples.

CHEBYSHEV ACCELERATION TECHNIQUE FOR SOLVING FUZZY LINEAR SYSTEM

Directory of Open Access Journals (Sweden)

S.H. Nasseri

2009-10-01

Full Text Available In this paper, Chebyshev acceleration technique is used to solve the fuzzy linear system (FLS. This method is discussed in details and followed by summary of some other acceleration techniques. Moreover, we show that in some situations that the methods such as Jacobi, Gauss-Sidel, SOR and conjugate gradient is divergent, our proposed method is applicable and the acquired results are illustrated by some numerical examples.

On a new iterative method for solving linear systems and comparison results

Science.gov (United States)

Jing, Yan-Fei; Huang, Ting-Zhu

2008-10-01

In Ujevic [A new iterative method for solving linear systems, Appl. Math. Comput. 179 (2006) 725-730], the author obtained a new iterative method for solving linear systems, which can be considered as a modification of the Gauss-Seidel method. In this paper, we show that this is a special case from a point of view of projection techniques. And a different approach is established, which is both theoretically and numerically proven to be better than (at least the same as) Ujevic's. As the presented numerical examples show, in most cases, the convergence rate is more than one and a half that of Ujevic.

Method for solving fully fuzzy linear programming problems using deviation degree measure

Institute of Scientific and Technical Information of China (English)

Haifang Cheng; Weilai Huang; Jianhu Cai

2013-01-01

A new ful y fuzzy linear programming (FFLP) prob-lem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crispδ-parametric linear programming (LP) problem. Giving the value of deviation degree in each constraint, the δ-fuzzy optimal so-lution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict: to improve the va-lues of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to il ustrate the proposed method.

Fibonacci collocation method with a residual error Function to solve linear Volterra integro differential equations

Directory of Open Access Journals (Sweden)

Salih Yalcinbas

2016-01-01

Full Text Available In this paper, a new collocation method based on the Fibonacci polynomials is introduced to solve the high-order linear Volterra integro-differential equations under the conditions. Numerical examples are included to demonstrate the applicability and validity of the proposed method and comparisons are made with the existing results. In addition, an error estimation based on the residual functions is presented for this method. The approximate solutions are improved by using this error estimation.

Automated finder for the critical condition on the linear stability of fluid motions

International Nuclear Information System (INIS)

Fujimura, Kaoru

1990-03-01

An automated finder routine for the critical condition on the linear stability of fluid motions is proposed. The Newton-Raphson method was utilized for an iteration to solve nonlinear eigenvalue problems appeared in the analysis. The routine was applied to linear stability problem of a free convection between vertical parallel plates with different non-uniform temperatures as well as a plane Poiseuille flow. An efficiency of the finder routine is demonstrated for several parameter sets, numerically. (author)

EZLP: An Interactive Computer Program for Solving Linear Programming Problems. Final Report.

Science.gov (United States)

Jarvis, John J.; And Others

Designed for student use in solving linear programming problems, the interactive computer program described (EZLP) permits the student to input the linear programming model in exactly the same manner in which it would be written on paper. This report includes a brief review of the development of EZLP; narrative descriptions of program features,…

A Meshfree Quasi-Interpolation Method for Solving Burgers’ Equation

Directory of Open Access Journals (Sweden)

Mingzhu Li

2014-01-01

Full Text Available The main aim of this work is to consider a meshfree algorithm for solving Burgers’ equation with the quartic B-spline quasi-interpolation. Quasi-interpolation is very useful in the study of approximation theory and its applications, since it can yield solutions directly without the need to solve any linear system of equations and overcome the ill-conditioning problem resulting from using the B-spline as a global interpolant. The numerical scheme is presented, by using the derivative of the quasi-interpolation to approximate the spatial derivative of the dependent variable and a low order forward difference to approximate the time derivative of the dependent variable. Compared to other numerical methods, the main advantages of our scheme are higher accuracy and lower computational complexity. Meanwhile, the algorithm is very simple and easy to implement and the numerical experiments show that it is feasible and valid.

Detangling the Interrelationships between Self- Regulation and Ill-Structured Problem Solving in Problem-Based Learning

Science.gov (United States)

Ge, Xun; Law, Victor; Huang, Kun

2016-01-01

One of the goals for problem-based learning (PBL) is to promote self-regulation. Although self-regulation has been studied extensively, its interrelationships with ill-structured problem solving have been unclear. In order to clarify the interrelationships, this article proposes a conceptual framework illustrating the iterative processes among…

Comments on new iterative methods for solving linear systems

Directory of Open Access Journals (Sweden)

Wang Ke

2017-06-01

Full Text Available Some new iterative methods were presented by Du, Zheng and Wang for solving linear systems in [3], where it is shown that the new methods, comparing to the classical Jacobi or Gauss-Seidel method, can be applied to more systems and have faster convergence. This note shows that their methods are suitable for more matrices than positive matrices which the authors suggested through further analysis and numerical examples.

Solving Linear Equations by Classical Jacobi-SR Based Hybrid Evolutionary Algorithm with Uniform Adaptation Technique

OpenAIRE

Jamali, R. M. Jalal Uddin; Hashem, M. M. A.; Hasan, M. Mahfuz; Rahman, Md. Bazlar

2013-01-01

Solving a set of simultaneous linear equations is probably the most important topic in numerical methods. For solving linear equations, iterative methods are preferred over the direct methods especially when the coefficient matrix is sparse. The rate of convergence of iteration method is increased by using Successive Relaxation (SR) technique. But SR technique is very much sensitive to relaxation factor, {\\omega}. Recently, hybridization of classical Gauss-Seidel based successive relaxation t...

Optimal Homotopy Asymptotic Method for Solving the Linear Fredholm Integral Equations of the First Kind

Directory of Open Access Journals (Sweden)

Mohammad Almousa

2013-01-01

Full Text Available The aim of this study is to present the use of a semi analytical method called the optimal homotopy asymptotic method (OHAM for solving the linear Fredholm integral equations of the first kind. Three examples are discussed to show the ability of the method to solve the linear Fredholm integral equations of the first kind. The results indicated that the method is very effective and simple.

Insights into the School Mathematics Tradition from Solving Linear Equations

Science.gov (United States)

Buchbinder, Orly; Chazan, Daniel; Fleming, Elizabeth

2015-01-01

In this article, we explore how the solving of linear equations is represented in English­-language algebra text books from the early nineteenth century when schooling was becoming institutionalized, and then survey contemporary teachers. In the text books, we identify the increasing presence of a prescribed order of steps (a canonical method) for…

A new neural network model for solving random interval linear programming problems.

Science.gov (United States)

Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza

2017-05-01

This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Role of Content Knowledge in Ill-Structured Problem Solving for High School Physics Students

Science.gov (United States)

Milbourne, Jeff; Wiebe, Eric

2018-01-01

While Physics Education Research has a rich tradition of problem-solving scholarship, most of the work has focused on more traditional, well-defined problems. Less work has been done with ill-structured problems, problems that are better aligned with the engineering and design-based scenarios promoted by the Next Generation Science Standards. This…

Projective-Dual Method for Solving Systems of Linear Equations with Nonnegative Variables

Science.gov (United States)

Ganin, B. V.; Golikov, A. I.; Evtushenko, Yu. G.

2018-02-01

In order to solve an underdetermined system of linear equations with nonnegative variables, the projection of a given point onto its solutions set is sought. The dual of this problem—the problem of unconstrained maximization of a piecewise-quadratic function—is solved by Newton's method. The problem of unconstrained optimization dual of the regularized problem of finding the projection onto the solution set of the system is considered. A connection of duality theory and Newton's method with some known algorithms of projecting onto a standard simplex is shown. On the example of taking into account the specifics of the constraints of the transport linear programming problem, the possibility to increase the efficiency of calculating the generalized Hessian matrix is demonstrated. Some examples of numerical calculations using MATLAB are presented.

Thinking positively about chronic illness: An exploration of optimism, illness perceptions and well-being in patients with Parkinson's disease.

Science.gov (United States)

Hurt, Catherine S; Burn, David J; Hindle, John; Samuel, Mike; Wilson, Ken; Brown, Richard G

2014-05-01

Holding positive beliefs about illness and having an optimistic outlook have been associated with increased well-being across a range of health conditions. However, research has indicated that being very optimistic may not actually be beneficial, and holding a realistic attitude is more adaptive in some forms of chronic illness, for example, Parkinson's disease (PD). This study aimed to explore the nature of relationships between illness perceptions, optimism and well-being: specifically, whether a linear or non-linear relationship best described the data. Additionally, the proposed moderating effect of optimism on the relationship between illness perceptions and well-being was tested. A total of 109 participants with idiopathic PD completed questionnaire measures of illness perception, optimism, mood and health-related quality of life (HRQoL). Multiple regression analyses were used to explore relationships between illness perceptions, optimism, mood and HRQoL. The potential curvilinear effects of illness perceptions and optimism were modelled using squared variables and linear and quadratic curve estimation. Holding positive illness perceptions predicted better well-being. Some evidence for a non-linear relationship between optimism and mood was found. Optimism had a significant moderating effect on the relationship between specific illness perceptions and outcome. Optimism appears to provide protection against some negative perceptions of illness and was associated with better mood and HRQoL. The findings indicate that specific illness perceptions may be beneficial targets for therapy. Therapeutic interventions should focus on enhancing positive perceptions of PD but potentially more importantly general optimistic attitude to maximize well-being. What is already known on this subject? Positive illness perceptions and high optimism are associated with better well-being in a range of conditions, both chronic and acute. Preliminary studies suggest that in chronic

Numerical method for solving linear Fredholm fuzzy integral equations of the second kind

Energy Technology Data Exchange (ETDEWEB)

Abbasbandy, S. [Department of Mathematics, Imam Khomeini International University, P.O. Box 288, Ghazvin 34194 (Iran, Islamic Republic of)]. E-mail: saeid@abbasbandy.com; Babolian, E. [Faculty of Mathematical Sciences and Computer Engineering, Teacher Training University, Tehran 15618 (Iran, Islamic Republic of); Alavi, M. [Department of Mathematics, Arak Branch, Islamic Azad University, Arak 38135 (Iran, Islamic Republic of)

2007-01-15

In this paper we use parametric form of fuzzy number and convert a linear fuzzy Fredholm integral equation to two linear system of integral equation of the second kind in crisp case. We can use one of the numerical method such as Nystrom and find the approximation solution of the system and hence obtain an approximation for fuzzy solution of the linear fuzzy Fredholm integral equations of the second kind. The proposed method is illustrated by solving some numerical examples.

Analysis of the efficiency of the linearization techniques for solving multi-objective linear fractional programming problems by goal programming

Directory of Open Access Journals (Sweden)

Tunjo Perić

2017-01-01

Full Text Available This paper presents and analyzes the applicability of three linearization techniques used for solving multi-objective linear fractional programming problems using the goal programming method. The three linearization techniques are: (1 Taylor’s polynomial linearization approximation, (2 the method of variable change, and (3 a modification of the method of variable change proposed in [20]. All three linearization techniques are presented and analyzed in two variants: (a using the optimal value of the objective functions as the decision makers’ aspirations, and (b the decision makers’ aspirations are given by the decision makers. As the criteria for the analysis we use the efficiency of the obtained solutions and the difficulties the analyst comes upon in preparing the linearization models. To analyze the applicability of the linearization techniques incorporated in the linear goal programming method we use an example of a financial structure optimization problem.

Solving linear systems in FLICA-4, thermohydraulic code for 3-D transient computations

International Nuclear Information System (INIS)

Allaire, G.

1995-01-01

FLICA-4 is a computer code, developed at the CEA (France), devoted to steady state and transient thermal-hydraulic analysis of nuclear reactor cores, for small size problems (around 100 mesh cells) as well as for large ones (more than 100000), on, either standard workstations or vector super-computers. As for time implicit codes, the largest time and memory consuming part of FLICA-4 is the routine dedicated to solve the linear system (the size of which is of the order of the number of cells). Therefore, the efficiency of the code is crucially influenced by the optimization of the algorithms used in assembling and solving linear systems: direct methods as the Gauss (or LU) decomposition for moderate size problems, iterative methods as the preconditioned conjugate gradient for large problems. 6 figs., 13 refs

AZTEC: A parallel iterative package for the solving linear systems

Energy Technology Data Exchange (ETDEWEB)

Hutchinson, S.A.; Shadid, J.N.; Tuminaro, R.S. [Sandia National Labs., Albuquerque, NM (United States)

1996-12-31

We describe a parallel linear system package, AZTEC. The package incorporates a number of parallel iterative methods (e.g. GMRES, biCGSTAB, CGS, TFQMR) and preconditioners (e.g. Jacobi, Gauss-Seidel, polynomial, domain decomposition with LU or ILU within subdomains). Additionally, AZTEC allows for the reuse of previous preconditioning factorizations within Newton schemes for nonlinear methods. Currently, a number of different users are using this package to solve a variety of PDE applications.

Penalized linear regression for discrete ill-posed problems: A hybrid least-squares and mean-squared error approach

KAUST Repository

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

2016-01-01

This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model

Novel methods for Solving Economic Dispatch of Security-Constrained Unit Commitment Based on Linear Programming

Science.gov (United States)

Guo, Sangang

2017-09-01

There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.

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.

Typed Linear Chain Conditional Random Fields and Their Application to Intrusion Detection

Science.gov (United States)

Elfers, Carsten; Horstmann, Mirko; Sohr, Karsten; Herzog, Otthein

Intrusion detection in computer networks faces the problem of a large number of both false alarms and unrecognized attacks. To improve the precision of detection, various machine learning techniques have been proposed. However, one critical issue is that the amount of reference data that contains serious intrusions is very sparse. In this paper we present an inference process with linear chain conditional random fields that aims to solve this problem by using domain knowledge about the alerts of different intrusion sensors represented in an ontology.

Solving fault diagnosis problems linear synthesis techniques

CERN Document Server

Varga, Andreas

2017-01-01

This book addresses fault detection and isolation topics from a computational perspective. Unlike most existing literature, it bridges the gap between the existing well-developed theoretical results and the realm of reliable computational synthesis procedures. The model-based approach to fault detection and diagnosis has been the subject of ongoing research for the past few decades. While the theoretical aspects of fault diagnosis on the basis of linear models are well understood, most of the computational methods proposed for the synthesis of fault detection and isolation filters are not satisfactory from a numerical standpoint. Several features make this book unique in the fault detection literature: Solution of standard synthesis problems in the most general setting, for both continuous- and discrete-time systems, regardless of whether they are proper or not; consequently, the proposed synthesis procedures can solve a specific problem whenever a solution exists Emphasis on the best numerical algorithms to ...

The H-N method for solving linear transport equation: theory and application

International Nuclear Information System (INIS)

Kaskas, A.; Gulecyuz, M.C.; Tezcan, C.

2002-01-01

The system of singular integral equation which is obtained from the integro-differential form of the linear transport equation as a result of Placzec lemma is solved. Application are given using the exit distributions and the infinite medium Green's function. The same theoretical results are also obtained with the use of the singular eigenfunction of the method of elementary solutions

Solving large mixed linear models using preconditioned conjugate gradient iteration.

Science.gov (United States)

Strandén, I; Lidauer, M

1999-12-01

Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.

A new modified conjugate gradient coefficient for solving system of linear equations

Science.gov (United States)

Hajar, N.; ‘Aini, N.; Shapiee, N.; Abidin, Z. Z.; Khadijah, W.; Rivaie, M.; Mamat, M.

2017-09-01

Conjugate gradient (CG) method is an evolution of computational method in solving unconstrained optimization problems. This approach is easy to implement due to its simplicity and has been proven to be effective in solving real-life application. Although this field has received copious amount of attentions in recent years, some of the new approaches of CG algorithm cannot surpass the efficiency of the previous versions. Therefore, in this paper, a new CG coefficient which retains the sufficient descent and global convergence properties of the original CG methods is proposed. This new CG is tested on a set of test functions under exact line search. Its performance is then compared to that of some of the well-known previous CG methods based on number of iterations and CPU time. The results show that the new CG algorithm has the best efficiency amongst all the methods tested. This paper also includes an application of the new CG algorithm for solving large system of linear equations

Operational matrices with respect to Hermite polynomials and their applications in solving linear dierential equations with variable coecients

Directory of Open Access Journals (Sweden)

A. Aminataei

2014-05-01

Full Text Available In this paper, a new and ecient approach is applied for numerical approximation of the linear dierential equations with variable coecients based on operational matrices with respect to Hermite polynomials. Explicit formulae which express the Hermite expansioncoecients for the moments of derivatives of any dierentiable function in terms of the original expansion coecients of the function itself are given in the matrix form. The mainimportance of this scheme is that using this approach reduces solving the linear dierentialequations to solve a system of linear algebraic equations, thus greatly simplifying the problem. In addition, two experiments are given to demonstrate the validity and applicability of the method

Solving Linear Differential Equations

NARCIS (Netherlands)

Nguyen, K.A.; Put, M. van der

2010-01-01

The theme of this paper is to 'solve' an absolutely irreducible differential module explicitly in terms of modules of lower dimension and finite extensions of the differential field K. Representations of semi-simple Lie algebras and differential Galo is theory are the main tools. The results extend

Chronic physical conditions in older adults with mental illness and/ or substance use disorders.

Science.gov (United States)

Lin, Wen-Chieh; Zhang, Jianying; Leung, Gary Y; Clark, Robin E

2011-10-01

To examine the association between mental illness and chronic physical conditions in older adults and investigate whether co-occurring substance use disorders (SUDs) are associated with greater risk of chronic physical conditions beyond mental illness alone. A retrospective cross-sectional study. Medicare and Medicaid programs in Massachusetts. Massachusetts Medicare and Medicaid members aged 65 and older as of January 1, 2005 (N = 679,182). Diagnoses recorded on Medicare and Medicaid claims were used to identify mental illness, SUDs, and 15 selected chronic physical conditions. Community-dwelling older adults with mental illness or SUDs had higher adjusted risk for 14 of the 15 selected chronic physical conditions than those without these disorders; the only exception was eye diseases. Moreover, those with co-occurring SUDs and mental illness had the highest adjusted risk for 11 of these chronic conditions. For residents of long-term care facilities, mental illness and SUDs were only moderately associated with the risk of chronic physical conditions. Community-dwelling older adults with mental illness or SUDs, particularly when they co-occurred, had substantially greater medical comorbidity than those without these disorders. For residents of long-term care facilities, the generally uniformly high medical comorbidity may have moderated this relationship, although their high prevalence of mental illness and SUDs signified greater healthcare needs. These findings strongly suggest the imminent need for integrating general medical care, mental health services, and addiction health services for older adults with mental illness or SUDs. © 2011, Copyright the Authors Journal compilation © 2011, The American Geriatrics Society.

A Discrete-Time Recurrent Neural Network for Solving Rank-Deficient Matrix Equations With an Application to Output Regulation of Linear Systems.

Science.gov (United States)

Liu, Tao; Huang, Jie

2017-04-17

This paper presents a discrete-time recurrent neural network approach to solving systems of linear equations with two features. First, the system of linear equations may not have a unique solution. Second, the system matrix is not known precisely, but a sequence of matrices that converges to the unknown system matrix exponentially is known. The problem is motivated from solving the output regulation problem for linear systems. Thus, an application of our main result leads to an online solution to the output regulation problem for linear systems.

Iterative methods for symmetric ill-conditioned Toeplitz matrices

Energy Technology Data Exchange (ETDEWEB)

Huckle, T. [Institut fuer Informatik, Muenchen (Germany)

1996-12-31

We consider ill-conditioned symmetric positive definite, Toeplitz systems T{sub n}x = b. If we want to solve such a system iteratively with the conjugate gradient method, we can use band-Toeplitz-preconditioners or Sine-Transform-peconditioners M = S{sub n}{Lambda}S{sub n}, S{sub n} the Sine-Transform-matrix and {Lambda} a diagonal matrix. A Toeplitz matrix T{sub n} = (t{sub i-j)}{sub i}{sup n},{sub j=1} is often related to an underlying function f defined by the coefficients t{sub j}, j = -{infinity},..,-1,0, 1,.., {infinity}. There are four cases, for which we want to determine a preconditioner M: - T{sub n} is related to an underlying function which is given explicitly; - T{sub n} is related to an underlying function that is given by its Fourier coefficients; - T{sub n} is related to an underlying function that is unknown; - T{sub n} is not related to an underlying function. Especially for the first three cases we show how positive definite and effective preconditioners based on the Sine-Transform can be defined for general nonnegative underlying function f. To define M, we evaluate or estimate the values of f at certain positions, and build a Sine-transform matrix with these values as eigenvalues. Then, the spectrum of the preconditioned system is bounded from above and away from zero.

A parallel algorithm for solving linear equations arising from one-dimensional network problems

International Nuclear Information System (INIS)

Mesina, G.L.

1991-01-01

One-dimensional (1-D) network problems, such as those arising from 1- D fluid simulations and electrical circuitry, produce systems of sparse linear equations which are nearly tridiagonal and contain a few non-zero entries outside the tridiagonal. Most direct solution techniques for such problems either do not take advantage of the special structure of the matrix or do not fully utilize parallel computer architectures. We describe a new parallel direct linear equation solution algorithm, called TRBR, which is especially designed to take advantage of this structure on MIMD shared memory machines. The new method belongs to a family of methods which split the coefficient matrix into the sum of a tridiagonal matrix T and a matrix comprised of the remaining coefficients R. Efficient tridiagonal methods are used to algebraically simplify the linear system. A smaller auxiliary subsystem is created and solved and its solution is used to calculate the solution of the original system. The newly devised BR method solves the subsystem. The serial and parallel operation counts are given for the new method and related earlier methods. TRBR is shown to have the smallest operation count in this class of direct methods. Numerical results are given. Although the algorithm is designed for one-dimensional networks, it has been applied successfully to three-dimensional problems as well. 20 refs., 2 figs., 4 tabs

An Improved Method for Solving Multiobjective Integer Linear Fractional Programming Problem

Directory of Open Access Journals (Sweden)

Meriem Ait Mehdi

2014-01-01

Full Text Available We describe an improvement of Chergui and Moulaï’s method (2008 that generates the whole efficient set of a multiobjective integer linear fractional program based on the branch and cut concept. The general step of this method consists in optimizing (maximizing without loss of generality one of the fractional objective functions over a subset of the original continuous feasible set; then if necessary, a branching process is carried out until obtaining an integer feasible solution. At this stage, an efficient cut is built from the criteria’s growth directions in order to discard a part of the feasible domain containing only nonefficient solutions. Our contribution concerns firstly the optimization process where a linear program that we define later will be solved at each step rather than a fractional linear program. Secondly, local ideal and nadir points will be used as bounds to prune some branches leading to nonefficient solutions. The computational experiments show that the new method outperforms the old one in all the treated instances.

A Novel Approach for Solving Semidefinite Programs

Directory of Open Access Journals (Sweden)

Hong-Wei Jiao

2014-01-01

Full Text Available A novel linearizing alternating direction augmented Lagrangian approach is proposed for effectively solving semidefinite programs (SDP. For every iteration, by fixing the other variables, the proposed approach alternatively optimizes the dual variables and the dual slack variables; then the primal variables, that is, Lagrange multipliers, are updated. In addition, the proposed approach renews all the variables in closed forms without solving any system of linear equations. Global convergence of the proposed approach is proved under mild conditions, and two numerical problems are given to demonstrate the effectiveness of the presented approach.

Development and adjustment of programs for solving systems of linear equations

International Nuclear Information System (INIS)

Fujimura, Toichiro

1978-03-01

Programs for solving the systems of linear equations have been adjusted and developed in expanding the scientific subroutine library SSL. The principal programs adjusted are based on the congruent method, method of product form of the inverse, orthogonal method, Crout's method for sparse system, and acceleration of iterative methods. The programs developed are based on the escalator method, direct parallel residue method and block tridiagonal method for band system. Described are usage of the programs developed and their future improvement. FORTRAN lists with simple examples in tests of the programs are also given. (auth.)

Using Problem-solving Therapy to Improve Problem-solving Orientation, Problem-solving Skills and Quality of Life in Older Hemodialysis Patients.

Science.gov (United States)

Erdley-Kass, Shiloh D; Kass, Darrin S; Gellis, Zvi D; Bogner, Hillary A; Berger, Andrea; Perkins, Robert M

2017-08-24

To determine the effectiveness of Problem-Solving Therapy (PST) in older hemodialysis (HD) patients by assessing changes in health-related quality of life and problem-solving skills. 33 HD patients in an outpatient hemodialysis center without active medical and psychiatric illness were enrolled. The intervention group (n = 15) received PST from a licensed social worker for 6 weeks, whereas the control group (n = 18) received usual care treatment. In comparison to the control group, patients receiving PST intervention reported improved perceptions of mental health, were more likely to view their problems with a positive orientation and were more likely to use functional problem-solving methods. Furthermore, this group was also more likely to view their overall health, activity limits, social activities and ability to accomplish desired tasks with a more positive mindset. The results demonstrate that PST may positively impact mental health components of quality of life and problem-solving coping among older HD patients. PST is an effective, efficient, and easy to implement intervention that can benefit problem-solving abilities and mental health-related quality of life in older HD patients. In turn, this will help patients manage their daily living activities related to their medical condition and reduce daily stressors.

Solving the linear inviscid shallow water equations in one dimension, with variable depth, using a recursion formula

Science.gov (United States)

Hernandez-Walls, R.; Martín-Atienza, B.; Salinas-Matus, M.; Castillo, J.

2017-11-01

When solving the linear inviscid shallow water equations with variable depth in one dimension using finite differences, a tridiagonal system of equations must be solved. Here we present an approach, which is more efficient than the commonly used numerical method, to solve this tridiagonal system of equations using a recursion formula. We illustrate this approach with an example in which we solve for a rectangular channel to find the resonance modes. Our numerical solution agrees very well with the analytical solution. This new method is easy to use and understand by undergraduate students, so it can be implemented in undergraduate courses such as Numerical Methods, Lineal Algebra or Differential Equations.

Solving the linear inviscid shallow water equations in one dimension, with variable depth, using a recursion formula

International Nuclear Information System (INIS)

Hernandez-Walls, R; Martín-Atienza, B; Salinas-Matus, M; Castillo, J

2017-01-01

When solving the linear inviscid shallow water equations with variable depth in one dimension using finite differences, a tridiagonal system of equations must be solved. Here we present an approach, which is more efficient than the commonly used numerical method, to solve this tridiagonal system of equations using a recursion formula. We illustrate this approach with an example in which we solve for a rectangular channel to find the resonance modes. Our numerical solution agrees very well with the analytical solution. This new method is easy to use and understand by undergraduate students, so it can be implemented in undergraduate courses such as Numerical Methods, Lineal Algebra or Differential Equations. (paper)

Efficient Implementation of the Riccati Recursion for Solving Linear-Quadratic Control Problems

DEFF Research Database (Denmark)

Frison, Gianluca; Jørgensen, John Bagterp

2013-01-01

In both Active-Set (AS) and Interior-Point (IP) algorithms for Model Predictive Control (MPC), sub-problems in the form of linear-quadratic (LQ) control problems need to be solved at each iteration. The solution of these sub-problems is typically the main computational effort at each iteration....... In this paper, we compare a number of solvers for an extended formulation of the LQ control problem: a Riccati recursion based solver can be considered the best choice for the general problem with dense matrices. Furthermore, we present a novel version of the Riccati solver, that makes use of the Cholesky...... factorization of the Pn matrices to reduce the number of flops. When combined with regularization and mixed precision, this algorithm can solve large instances of the LQ control problem up to 3 times faster than the classical Riccati solver....

Greedy solution of ill-posed problems: error bounds and exact inversion

International Nuclear Information System (INIS)

Denis, L; Lorenz, D A; Trede, D

2009-01-01

The orthogonal matching pursuit (OMP) is a greedy algorithm to solve sparse approximation problems. Sufficient conditions for exact recovery are known with and without noise. In this paper we investigate the applicability of the OMP for the solution of ill-posed inverse problems in general, and in particular for two deconvolution examples from mass spectrometry and digital holography, respectively. In sparse approximation problems one often has to deal with the problem of redundancy of a dictionary, i.e. the atoms are not linearly independent. However, one expects them to be approximatively orthogonal and this is quantified by the so-called incoherence. This idea cannot be transferred to ill-posed inverse problems since here the atoms are typically far from orthogonal. The ill-posedness of the operator probably causes the correlation of two distinct atoms to become huge, i.e. that two atoms look much alike. Therefore, one needs conditions which take the structure of the problem into account and work without the concept of coherence. In this paper we develop results for the exact recovery of the support of noisy signals. In the two examples, mass spectrometry and digital holography, we show that our results lead to practically relevant estimates such that one may check a priori if the experimental setup guarantees exact deconvolution with OMP. Especially in the example from digital holography, our analysis may be regarded as a first step to calculate the resolution power of droplet holography

On the Evaluation of Computational Results Obtained from Solving System of linear Equations With matlab The Dual affine Scalling interior Point

International Nuclear Information System (INIS)

Murfi, Hendri; Basaruddin, T.

2001-01-01

The interior point method for linear programming has gained extraordinary interest as an alternative to simplex method since Karmarkar presented a polynomial-time algorithm for linear programming based on interior point method. In implementation of the algorithm of this method, there are two important things that have impact heavily to performance of the algorithm; they are data structure and used method to solve linear equation system in the algorithm. This paper describes about solving linear equation system in variants of the algorithm called dual-affine scaling algorithm. Next, we evaluate experimentally results of some used methods, either direct method or iterative method. The experimental evaluation used Matlab

On solving wave equations on fixed bounded intervals involving Robin boundary conditions with time-dependent coefficients

Science.gov (United States)

van Horssen, Wim T.; Wang, Yandong; Cao, Guohua

2018-06-01

In this paper, it is shown how characteristic coordinates, or equivalently how the well-known formula of d'Alembert, can be used to solve initial-boundary value problems for wave equations on fixed, bounded intervals involving Robin type of boundary conditions with time-dependent coefficients. A Robin boundary condition is a condition that specifies a linear combination of the dependent variable and its first order space-derivative on a boundary of the interval. Analytical methods, such as the method of separation of variables (SOV) or the Laplace transform method, are not applicable to those types of problems. The obtained analytical results by applying the proposed method, are in complete agreement with those obtained by using the numerical, finite difference method. For problems with time-independent coefficients in the Robin boundary condition(s), the results of the proposed method also completely agree with those as for instance obtained by the method of separation of variables, or by the finite difference method.

Parallel Implementation of Riccati Recursion for Solving Linear-Quadratic Control Problems

DEFF Research Database (Denmark)

Frison, Gianluca; Jørgensen, John Bagterp

2013-01-01

In both Active-Set (AS) and Interior-Point (IP) algorithms for Model Predictive Control (MPC), sub-problems in the form of linear-quadratic (LQ) control problems need to be solved at each iteration. The solution of these sub-problems is usually the main computational effort. In this paper...... an alternative version of the Riccati recursion solver for LQ control problems is presented. The performance of both the classical and the alternative version is analyzed from a theoretical as well as a numerical point of view, and the alternative version is found to be approximately 50% faster than...

Solving a class of generalized fractional programming problems using the feasibility of linear programs.

Science.gov (United States)

Shen, Peiping; Zhang, Tongli; Wang, Chunfeng

2017-01-01

This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.

Psychological interventions for parents of children and adolescents with chronic illness.

Science.gov (United States)

Eccleston, Christopher; Palermo, Tonya M; Fisher, Emma; Law, Emily

2012-08-15

RCTs involving a total of 2723 primary trial participants. Two review authors extracted data from 26 studies. We analysed data using two categories. First, we analysed data by each medical condition across all treatment classes at two time points (immediately post-treatment and the first available follow-up). Second, we analysed data by each treatment class (cognitive behavioural therapy (CBT), family therapy (FT), problem solving therapy (PST) and multisystemic therapy (MST)) across all medical conditions at two time points (immediately post-treatment and the first available follow-up). We assessed treatment effectiveness on six possible outcomes: parent behaviour, parent mental health, child behaviour/disability, child mental health, child symptoms and family functioning. Across all treatment types, psychological therapies that included parents significantly improved child symptoms for painful conditions immediately post-treatment. Across all medical conditions, cognitive behavioural therapy (CBT) significantly improved child symptoms and problem solving therapy significantly improved parent behaviour and parent mental health immediately post-treatment. There were no other effects at post-treatment or follow-up. The risk of bias of included studies is described. There is no evidence on the effectiveness of psychological therapies that include parents in most outcome domains of functioning, for a large number of common chronic illnesses in children. There is good evidence for the effectiveness of including parents in psychological therapies that reduce pain in children with painful conditions. There is also good evidence for the effectiveness of CBT that includes parents for improving the primary symptom complaints when available data were included from chronic illness conditions. Finally, there is good evidence for the effectiveness of problem solving therapy delivered to parents on improving parent problem solving skills and parent mental health. All effects are

Solving portfolio selection problems with minimum transaction lots based on conditional-value-at-risk

Science.gov (United States)

Setiawan, E. P.; Rosadi, D.

2017-01-01

Portfolio selection problems conventionally means ‘minimizing the risk, given the certain level of returns’ from some financial assets. This problem is frequently solved with quadratic or linear programming methods, depending on the risk measure that used in the objective function. However, the solutions obtained by these method are in real numbers, which may give some problem in real application because each asset usually has its minimum transaction lots. In the classical approach considering minimum transaction lots were developed based on linear Mean Absolute Deviation (MAD), variance (like Markowitz’s model), and semi-variance as risk measure. In this paper we investigated the portfolio selection methods with minimum transaction lots with conditional value at risk (CVaR) as risk measure. The mean-CVaR methodology only involves the part of the tail of the distribution that contributed to high losses. This approach looks better when we work with non-symmetric return probability distribution. Solution of this method can be found with Genetic Algorithm (GA) methods. We provide real examples using stocks from Indonesia stocks market.

Associations between illness duration and health-related quality of life in specified mental and physical chronic health conditions: results from a population-based survey.

Science.gov (United States)

Busija, Lucy; Tan, Jeretine; Sanders, Kerrie M

2017-10-01

We compared health-related quality of life (HRQOL) in incident (≤1 year since diagnosis), mid-term (>1-5 years since diagnosis), and long-term (>5 years since diagnosis) cases of mental and physical chronic illness with the general population and assessed the modifying effects of age and gender on the association between HRQOL and illness duration. Data from the 2007 Australian National Health and Mental Wellbeing Survey were used. HRQOL was captured by the Assessment of Quality of Life Scale 4D. Multivariable linear regression analyses compared HRQOL of individuals with different duration of illnesses with those who did not have the condition of interest. The 8841 survey respondents were aged 16-85 years (median 43 years, 50.3% female). For the overall sample, worse HRQOL was associated with incident (P = 0.049) and mid-term (P = 0.036) stroke and long-term depression (P illness is most apparent in stroke and mental illness and differs between age groups.

Polarized electron sources for linear colliders

International Nuclear Information System (INIS)

Clendenin, J.E.; Ecklund, S.D.; Miller, R.H.; Schultz, D.C.; Sheppard, J.C.

1992-07-01

Linear colliders require high peak current beams with low duty factors. Several methods to produce polarized e - beams for accelerators have been developed. The SLC, the first linear collider, utilizes a photocathode gun with a GaAs cathode. Although photocathode sources are probably the only practical alternative for the next generation of linear colliders, several problems remain to be solved, including high voltage breakdown which poisons the cathode, charge limitations that are associated with the condition of the semiconductor cathode, and a relatively low polarization of ≤5O%. Methods to solve or at least greatly reduce the impact of each of these problems are at hand

Self-Regulation in the Midst of Complexity: A Case Study of High School Physics Students Engaged in Ill-Structured Problem Solving

Science.gov (United States)

Milbourne, Jeffrey David

The purpose of this dissertation study was to explore the experiences of high school physics students who were solving complex, ill-structured problems, in an effort to better understand how self-regulatory behavior mediated the project experience. Consistent with Voss, Green, Post, and Penner's (1983) conception of an ill-structured problem in the natural sciences, the 'problems' consisted of scientific research projects that students completed under the supervision of a faculty mentor. Zimmerman and Campillo's (2003) self-regulatory framework of problem solving provided a holistic guide to data collection and analysis of this multi-case study, with five individual student cases. The study's results are explored in two manuscripts, each targeting a different audience. The first manuscript, intended for the Science Education Research community, presents a thick, rich description of the students' project experiences, consistent with a qualitative, case study analysis. Findings suggest that intrinsic interest was an important self-regulatory factor that helped motivate students throughout their project work, and that the self-regulatory cycle of forethought, performance monitoring, and self-reflection was an important component of the problem-solving process. Findings also support the application of Zimmerman and Campillo's framework to complex, ill-structured problems, particularly the cyclical nature of the framework. Finally, this study suggests that scientific research projects, with the appropriate support, can be a mechanism for improving students' selfregulatory behavior. The second manuscript, intended for Physics practitioners, combines the findings of the first manuscript with the perspectives of the primary, on-site research mentor, who has over a decade's worth of experience mentoring students doing physics research. His experience suggests that a successful research experience requires certain characteristics, including: a slow, 'on-ramp' to the research

Oral health conditions affect functional and social activities of terminally-ill cancer patients

Science.gov (United States)

Fischer, D.J.; Epstein, J.B.; Yao, Y.; Wilkie, D.J.

2013-01-01

Purpose Oral conditions are established complications in terminally-ill cancer patients. Yet despite significant morbidity, the characteristics and impact of oral conditions in these patients are poorly documented. The study objective was to characterize oral conditions in terminally-ill cancer patients to determine the presence, severity, and the functional and social impact of these oral conditions. Methods This was an observational clinical study including terminally-ill cancer patients (2.5–3 week life expectancy). Data were obtained via the Oral Problems Scale (OPS) that measures the presence of subjective xerostomia, orofacial pain, taste change, and the functional/social impact of oral conditions and a demographic questionnaire. A standardized oral examination was used to assess objective salivary hypofunction, fungal infection, mucosal erythema, and ulceration. Regression analysis and t test investigated the associations between measures. Results Of 104 participants, most were ≥50 years of age, female, and high-school educated; 45% were African American, 43% Caucasian, and 37% married. Oral conditions frequencies were: salivary hypofunction (98%), mucosal erythema (50%), ulceration (20%), fungal infection (36%), and other oral problems (46%). Xerostomia, taste change, and orofacial pain all had significant functional impact; poral ulcerations had significantly more orofacial pain with a social impact than patients without ulcers (p=.003). Erythema was significantly associated with fungal infection and with mucosal ulceration (pOral conditions significantly affect functional and social activities in terminally-ill cancer patients. Identification and management of oral conditions in these patients should therefore be an important clinical consideration. PMID:24232310

Harmonic Function of Poincare Cone Condition In Solving Dirichlet ...

African Journals Online (AJOL)

Harmonic Function of Poincare Cone Condition In Solving Dirichlet Problem. ... Journal of the Nigerian Association of Mathematical Physics ... theorem, the dirichlet problem and maximum principle where we conclude that the application of sums , differences and scalar multiples of harmonic functions are again harmonic.

Conjugate gradient heat bath for ill-conditioned actions.

Science.gov (United States)

Ceriotti, Michele; Bussi, Giovanni; Parrinello, Michele

2007-08-01

We present a method for performing sampling from a Boltzmann distribution of an ill-conditioned quadratic action. This method is based on heat-bath thermalization along a set of conjugate directions, generated via a conjugate-gradient procedure. The resulting scheme outperforms local updates for matrices with very high condition number, since it avoids the slowing down of modes with lower eigenvalue, and has some advantages over the global heat-bath approach, compared to which it is more stable and allows for more freedom in devising case-specific optimizations.

Simplified neural networks for solving linear least squares and total least squares problems in real time.

Science.gov (United States)

Cichocki, A; Unbehauen, R

1994-01-01

In this paper a new class of simplified low-cost analog artificial neural networks with on chip adaptive learning algorithms are proposed for solving linear systems of algebraic equations in real time. The proposed learning algorithms for linear least squares (LS), total least squares (TLS) and data least squares (DLS) problems can be considered as modifications and extensions of well known algorithms: the row-action projection-Kaczmarz algorithm and/or the LMS (Adaline) Widrow-Hoff algorithms. The algorithms can be applied to any problem which can be formulated as a linear regression problem. The correctness and high performance of the proposed neural networks are illustrated by extensive computer simulation results.

Using Digital Mapping Tool in Ill-Structured Problem Solving

Science.gov (United States)

Bai, Hua

2013-01-01

Scaffolding students' problem solving and helping them to improve problem solving skills are critical in instructional design courses. This study investigated the effects of students' uses of a digital mapping tool on their problem solving performance in a design case study. It was found that the students who used the digital mapping tool…

Using a grid platform for solving large sparse linear systems over GF(2)

OpenAIRE

Kleinjung , Thorsten; Nussbaum , Lucas; Thomé , Emmanuel

2010-01-01

International audience; In Fall 2009, the final step of the factorization of rsa768 was carried out on several clusters of the Grid'5000 platform, leading to a new record in integer factorization. This step involves solving a huge sparse linear system defined over the binary field GF(2). This article aims at describing the algorithm used, the difficulties encountered, and the methodology which led to success. In particular, we illustrate how our use of the block Wiedemann algorithm led to a m...

Best candidates for cognitive treatment of illness perceptions in chronic low back pain: results of a theory-driven predictor study.

Science.gov (United States)

Siemonsma, Petra C; Stuvie, Ilse; Roorda, Leo D; Vollebregt, Joke A; Lankhorst, Gustaaf J; Lettinga, Ant T

2011-04-01

The aim of this study was to identify treatment-specific predictors of the effectiveness of a method of evidence-based treatment: cognitive treatment of illness perceptions. This study focuses on what treatment works for whom, whereas most prognostic studies focusing on chronic non-specific low back pain rehabilitation aim to reduce the heterogeneity of the population of patients who are suitable for rehabilitation treatment in general. Three treatment-specific predictors were studied in patients with chronic non-specific low back pain receiving cognitive treatment of illness perceptions: a rational approach to problem-solving, discussion skills and verbal skills. Hierarchical linear regression analysis was used to assess their predictive value. Short-term changes in physical activity, measured with the Patient-Specific Functioning List, were the outcome measure for cognitive treatment of illness perceptions effect. A total of 156 patients with chronic non-specific low back pain participated in the study. Rational problem-solving was found to be a significant predictor for the change in physical activity. Discussion skills and verbal skills were non-significant. Rational problem-solving explained 3.9% of the total variance. The rational problem-solving scale results are encouraging, because chronic non-specific low back pain problems are complex by nature and can be influenced by a variety of factors. A minimum score of 44 points on the rational problem-solving scale may assist clinicians in selecting the most appropriate candidates for cognitive treatment of illness perceptions.

A Smoothing-Type Algorithm for Solving Linear Complementarity Problems with Strong Convergence Properties

International Nuclear Information System (INIS)

Huang Zhenghai; Gu Weizhe

2008-01-01

In this paper, we construct an augmented system of the standard monotone linear complementarity problem (LCP), and establish the relations between the augmented system and the LCP. We present a smoothing-type algorithm for solving the augmented system. The algorithm is shown to be globally convergent without assuming any prior knowledge of feasibility/infeasibility of the problem. In particular, if the LCP has a solution, then the algorithm either generates a maximal complementary solution of the LCP or detects correctly solvability of the LCP, and in the latter case, an existing smoothing-type algorithm can be directly applied to solve the LCP without any additional assumption and it generates a maximal complementary solution of the LCP; and that if the LCP is infeasible, then the algorithm detect correctly infeasibility of the LCP. To the best of our knowledge, such properties have not appeared in the existing literature for smoothing-type algorithms

A duality approach for solving bounded linear programming problems with fuzzy variables based on ranking functions and its application in bounded transportation problems

Science.gov (United States)

Ebrahimnejad, Ali

2015-08-01

There are several methods, in the literature, for solving fuzzy variable linear programming problems (fuzzy linear programming in which the right-hand-side vectors and decision variables are represented by trapezoidal fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings a new method based on the bounded dual simplex method is proposed to determine the fuzzy optimal solution of that kind of fuzzy variable linear programming problems in which some or all variables are restricted to lie within lower and upper bounds. To illustrate the proposed method, an application example is solved and the obtained results are given. The advantages of the proposed method over existing methods are discussed. Also, one application of this algorithm in solving bounded transportation problems with fuzzy supplies and demands is dealt with. The proposed method is easy to understand and to apply for determining the fuzzy optimal solution of bounded fuzzy variable linear programming problems occurring in real-life situations.

Penalized linear regression for discrete ill-posed problems: A hybrid least-squares and mean-squared error approach

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-12-19

This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model matrix. This perturbation is introduced to enhance the singular-value (SV) structure of the matrix and hence to provide a better solution. The proposed approach is derived to select the regularization parameter in a way that minimizes the mean-squared error (MSE) of the estimator. Numerical results demonstrate that the proposed approach outperforms a set of benchmark methods in most cases when applied to different scenarios of discrete ill-posed problems. Jointly, the proposed approach enjoys the lowest run-time and offers the highest level of robustness amongst all the tested methods.

More on Generalizations and Modifications of Iterative Methods for Solving Large Sparse Indefinite Linear Systems

Directory of Open Access Journals (Sweden)

Jen-Yuan Chen

2014-01-01

Full Text Available Continuing from the works of Li et al. (2014, Li (2007, and Kincaid et al. (2000, we present more generalizations and modifications of iterative methods for solving large sparse symmetric and nonsymmetric indefinite systems of linear equations. We discuss a variety of iterative methods such as GMRES, MGMRES, MINRES, LQ-MINRES, QR MINRES, MMINRES, MGRES, and others.

Solving the Fully Fuzzy Bilevel Linear Programming Problem through Deviation Degree Measures and a Ranking Function Method

OpenAIRE

Aihong Ren

2016-01-01

This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solut...

Living well: an intervention to improve self-management of medical illness for individuals with serious mental illness.

Science.gov (United States)

Goldberg, Richard W; Dickerson, Faith; Lucksted, Alicia; Brown, Clayton H; Weber, Elyssa; Tenhula, Wendy N; Kreyenbuhl, Julie; Dixon, Lisa B

2013-01-01

Individuals with serious mental illness have elevated rates of comorbid chronic general medical conditions and may benefit from interventions designed to support illness self-management. This study examined the effectiveness of a modified version of the Chronic Disease Self-Management Program called Living Well for individuals with serious mental illness. A total of 63 mental health consumers with serious mental illness and at least one concurrent chronic general medical condition were randomly assigned to receive the 13-session peer-cofacilitated Living Well intervention or usual care. Participants were evaluated on attitudinal, behavioral, and functional outcomes at baseline, at the end of the intervention, and at a two-month follow-up. Living Well participants showed significant postintervention improvements across a range of attitudinal (self-efficacy and patient activation), behavioral (illness self-management techniques), and functional (physical and emotional well-being and general health functioning) outcomes. Although attenuation of effect was observed for most outcomes at two months postintervention, evidence was found of continued improvement in general self-management behaviors (use of action planning, brainstorming, and problem-solving). Continued advantage was found for the Living Well group in other areas, such as health-related locus of control and reports of healthy eating and physical activity. Receipt of Living Well was associated with a notable decrease in use of the emergency room for medical care, although the between-group difference was not statistically significant. Living Well shows promise in helping mental health consumers more effectively manage chronic general medical conditions and experience improved functioning and well-being.

A simple method of fitting ill-conditioned polynomials to data

International Nuclear Information System (INIS)

Buckler, A.N.; Lawrence, J.

1979-04-01

A very simple transformation of the independent variable x is shown to cure the ill-conditioning when some polynomial series are fitted to given Y values. Numerical examples are given to illustrate the power of the method. (author)

Inverse problems in linear transport theory

International Nuclear Information System (INIS)

Dressler, K.

1988-01-01

Inverse problems for a class of linear kinetic equations are investigated. The aim is to identify the scattering kernel of a transport equation (corresponding to the structure of a background medium) by observing the 'albedo' part of the solution operator for the corresponding direct initial boundary value problem. This means to get information on some integral operator in an integrodifferential equation through on overdetermined boundary value problem. We first derive a constructive method for solving direct halfspace problems and prove a new factorization theorem for the solutions. Using this result we investigate stationary inverse problems with respect to well posedness (e.g. reduce them to classical ill-posed problems, such as integral equations of first kind). In the time-dependent case we show that a quite general inverse problem is well posed and solve it constructively. (orig.)

A "feasible direction" search for Lineal Programming problem solving

Directory of Open Access Journals (Sweden)

Jaime U Malpica Angarita

2003-07-01

Full Text Available The study presents an approach to solve linear programming problems with no artificial variables. A primal linear minimization problem is standard form and its associated dual linear maximization problem are used. Initially, the dual (or a partial dual program is solved by a "feasible direction" search, where the Karush-Kuhn-Tucker conditions help to verify its optimality and then its feasibility. The "feasible direction" search exploits the characteristics of the convex polyhedron (or prototype formed by the dual program constraints to find a starting point and then follows line segments, whose directions are found in afine subspaces defined by boundary hyperplanes of polyhedral faces, to find next points up to the (an optimal one. Them, the remaining dual constraints not satisfaced at that optimal dual point, if there are any, are handled as nonbasic variables of the primal program, which is to be solved by such "feasible direction" search.

Local Fractional Laplace Variational Iteration Method for Solving Linear Partial Differential Equations with Local Fractional Derivative

Directory of Open Access Journals (Sweden)

Ai-Min Yang

2014-01-01

Full Text Available The local fractional Laplace variational iteration method was applied to solve the linear local fractional partial differential equations. The local fractional Laplace variational iteration method is coupled by the local fractional variational iteration method and Laplace transform. The nondifferentiable approximate solutions are obtained and their graphs are also shown.

Enhancing Linearity of Voltage Controlled Oscillator Thermistor Signal Conditioning Circuit Using Linear Search

Science.gov (United States)

Rana, K. P. S.; Kumar, Vineet; Prasad, Tapan

2018-02-01

Temperature to Frequency Converters (TFCs) are potential signal conditioning circuits (SCCs) usually employed in temperature measurements using thermistors. A NE/SE-566 based SCC has been recently used in several reported works as TFC. Application of NE/SE-566 based SCC requires a mechanism for finding the optimal values of SCC parameters yielding the optimal linearity and desired sensitivity performances. Two classical methods, namely, inflection point and three point have been employed for this task. In this work, the application of these two methods, on NE/SE-566 based SCC in TFC, is investigated in detail and the conditions for its effective usage are developed. Further, since these classical methods offer an approximate linearization of temperature and frequency relationship an application of a linear search based technique is proposed to further enhance the linearity. The implemented linear search method used results obtained from the above mentioned classical methods. The presented simulation studies, for three different industrial grade thermistors, revealed that the linearity enhancements of 21.7, 18.3 and 17.8% can be achieved over the inflection point method and 4.9, 4.7 and 4.7% over the three point method, for an input temperature range of 0-100 °C.

Scilab software as an alternative low-cost computing in solving the linear equations problem

Science.gov (United States)

Agus, Fahrul; Haviluddin

2017-02-01

Numerical computation packages are widely used both in teaching and research. These packages consist of license (proprietary) and open source software (non-proprietary). One of the reasons to use the package is a complexity of mathematics function (i.e., linear problems). Also, number of variables in a linear or non-linear function has been increased. The aim of this paper was to reflect on key aspects related to the method, didactics and creative praxis in the teaching of linear equations in higher education. If implemented, it could be contribute to a better learning in mathematics area (i.e., solving simultaneous linear equations) that essential for future engineers. The focus of this study was to introduce an additional numerical computation package of Scilab as an alternative low-cost computing programming. In this paper, Scilab software was proposed some activities that related to the mathematical models. In this experiment, four numerical methods such as Gaussian Elimination, Gauss-Jordan, Inverse Matrix, and Lower-Upper Decomposition (LU) have been implemented. The results of this study showed that a routine or procedure in numerical methods have been created and explored by using Scilab procedures. Then, the routine of numerical method that could be as a teaching material course has exploited.

Convex variational problems linear, nearly linear and anisotropic growth conditions

CERN Document Server

Bildhauer, Michael

2003-01-01

The author emphasizes a non-uniform ellipticity condition as the main approach to regularity theory for solutions of convex variational problems with different types of non-standard growth conditions. This volume first focuses on elliptic variational problems with linear growth conditions. Here the notion of a "solution" is not obvious and the point of view has to be changed several times in order to get some deeper insight. Then the smoothness properties of solutions to convex anisotropic variational problems with superlinear growth are studied. In spite of the fundamental differences, a non-uniform ellipticity condition serves as the main tool towards a unified view of the regularity theory for both kinds of problems.

Solving non-linear Horn clauses using a linear Horn clause solver

DEFF Research Database (Denmark)

Kafle, Bishoksan; Gallagher, John Patrick; Ganty, Pierre

2016-01-01

In this paper we show that checking satisfiability of a set of non-linear Horn clauses (also called a non-linear Horn clause program) can be achieved using a solver for linear Horn clauses. We achieve this by interleaving a program transformation with a satisfiability checker for linear Horn...... clauses (also called a solver for linear Horn clauses). The program transformation is based on the notion of tree dimension, which we apply to a set of non-linear clauses, yielding a set whose derivation trees have bounded dimension. Such a set of clauses can be linearised. The main algorithm...... dimension. We constructed a prototype implementation of this approach and performed some experiments on a set of verification problems, which shows some promise....

Psychological interventions for parents of children and adolescents with chronic illness

Science.gov (United States)

Eccleston, Christopher; Palermo, Tonya M; Fisher, Emma; Law, Emily

2012-01-01

group was fewer than 10 at post-treatment. Data collection and analysis We included 35 RCTs involving a total of 2723 primary trial participants. Two review authors extracted data from 26 studies. We analysed data using two categories. First, we analysed data by each medical condition across all treatment classes at two time points (immediately post-treatment and the first available follow-up). Second, we analysed data by each treatment class (cognitive behavioural therapy (CBT), family therapy (FT), problem solving therapy (PST) and multisystemic therapy (MST)) across all medical conditions at two time points (immediately post-treatment and the first available follow-up). We assessed treatment effectiveness on six possible outcomes: parent behaviour, parent mental health, child behaviour/disability, child mental health, child symptoms and family functioning. Main results Across all treatment types, psychological therapies that included parents significantly improved child symptoms for painful conditions immediately post-treatment. Across all medical conditions, cognitive behavioural therapy (CBT) significantly improved child symptoms and problem solving therapy significantly improved parent behaviour and parent mental health immediately post-treatment. There were no other effects at post-treatment or follow-up. The risk of bias of included studies is described. Authors' conclusions There is no evidence on the effectiveness of psychological therapies that include parents in most outcome domains of functioning, for a large number of common chronic illnesses in children. There is good evidence for the effectiveness of including parents in psychological therapies that reduce pain in children with painful conditions. There is also good evidence for the effectiveness of CBT that includes parents for improving the primary symptom complaints when available data were included from chronic illness conditions. Finally, there is good evidence for the effectiveness of problem

Evaluating forest management policies by parametric linear programing

Science.gov (United States)

Daniel I. Navon; Richard J. McConnen

1967-01-01

An analytical and simulation technique, parametric linear programing explores alternative conditions and devises an optimal management plan for each condition. Its application in solving policy-decision problems in the management of forest lands is illustrated in an example.

Solving the linearized forward-speed radiation problem using a high-order finite difference method on overlapping grids

DEFF Research Database (Denmark)

Amini Afshar, Mostafa; Bingham, Harry B.

2017-01-01

. Frequency-domain results are then obtained from a Fourier transform of the force and motion signals. In order to make a robust Fourier transform, and capture the response around the critical frequency, the tail of the force signal is asymptotically extrapolated assuming a linear decay rate. Fourth......The linearized potential flow approximation for the forward speed radiation problem is solved in the time domain using a high-order finite difference method. The finite-difference discretization is developed on overlapping, curvilinear body-fitted grids. To ensure numerical stability...

Solving PDEs in Python the FEniCS tutorial I

CERN Document Server

Langtangen, Hans Petter

2016-01-01

This book offers a concise and gentle introduction to finite element programming in Python based on the popular FEniCS software library. Using a series of examples, including the Poisson equation, the equations of linear elasticity, the incompressible Navier–Stokes equations, and systems of nonlinear advection–diffusion–reaction equations, it guides readers through the essential steps to quickly solving a PDE in FEniCS, such as how to define a finite variational problem, how to set boundary conditions, how to solve linear and nonlinear systems, and how to visualize solutions and structure finite element Python programs. This book is open access under a CC BY license.

Instructional Supports for Representational Fluency in Solving Linear Equations with Computer Algebra Systems and Paper-and-Pencil

Science.gov (United States)

Fonger, Nicole L.; Davis, Jon D.; Rohwer, Mary Lou

2018-01-01

This research addresses the issue of how to support students' representational fluency--the ability to create, move within, translate across, and derive meaning from external representations of mathematical ideas. The context of solving linear equations in a combined computer algebra system (CAS) and paper-and-pencil classroom environment is…

A method for solving neutron transport equation

International Nuclear Information System (INIS)

Dimitrijevic, Z.

1993-01-01

The procedure for solving the transport equation by directly integrating for case one-dimensional uniform multigroup medium is shown. The solution is expressed in terms of linear combination of function H n (x,μ), and the coefficient is determined from given conditions. The solution is applied for homogeneous slab of critical thickness. (author)

Non-linear algorithms solved with the help of the GIBIANE macro-language

International Nuclear Information System (INIS)

Ebersolt, L.; Combescure, A.; Millard, A.; Verpeaux, P.

1987-01-01

Non linear finite element problems are often solved with the help of iteratives procedures. In the finite element program CASTEM 2000, the syntax of the dataset permits the user to derive his own algorithm and tune it to his problem. These basic ideas, simple to imagine, needed a proper frame to be materialized in a general purpose finite element program, and three concepts emerged: Operators, the Gibiane macro-language. In the two first paragraphs, we will detail these concepts, in the third paragraph, we will describe the different possibilities of the program, in the fourth paragraph, we will show, by combining operators in a proper order, how to obtain the desired algorithm. (orig./GL)

COMPARISON OF IMPLICIT SCHEMES TO SOLVE EQUATIONS OF RADIATION HYDRODYNAMICS WITH A FLUX-LIMITED DIFFUSION APPROXIMATION: NEWTON–RAPHSON, OPERATOR SPLITTING, AND LINEARIZATION

Energy Technology Data Exchange (ETDEWEB)

Tetsu, Hiroyuki; Nakamoto, Taishi, E-mail: h.tetsu@geo.titech.ac.jp [Earth and Planetary Sciences, Tokyo Institute of Technology, Tokyo 152-8551 (Japan)

2016-03-15

Radiation is an important process of energy transport, a force, and a basis for synthetic observations, so radiation hydrodynamics (RHD) calculations have occupied an important place in astrophysics. However, although the progress in computational technology is remarkable, their high numerical cost is still a persistent problem. In this work, we compare the following schemes used to solve the nonlinear simultaneous equations of an RHD algorithm with the flux-limited diffusion approximation: the Newton–Raphson (NR) method, operator splitting, and linearization (LIN), from the perspective of the computational cost involved. For operator splitting, in addition to the traditional simple operator splitting (SOS) scheme, we examined the scheme developed by Douglas and Rachford (DROS). We solve three test problems (the thermal relaxation mode, the relaxation and the propagation of linear waves, and radiating shock) using these schemes and then compare their dependence on the time step size. As a result, we find the conditions of the time step size necessary for adopting each scheme. The LIN scheme is superior to other schemes if the ratio of radiation pressure to gas pressure is sufficiently low. On the other hand, DROS can be the most efficient scheme if the ratio is high. Although the NR scheme can be adopted independently of the regime, especially in a problem that involves optically thin regions, the convergence tends to be worse. In all cases, SOS is not practical.

Fourth order Douglas implicit scheme for solving three dimension reaction diffusion equation with non-linear source term

Science.gov (United States)

Hasnain, Shahid; Saqib, Muhammad; Mashat, Daoud Suleiman

2017-07-01

This research paper represents a numerical approximation to non-linear three dimension reaction diffusion equation with non-linear source term from population genetics. Since various initial and boundary value problems exist in three dimension reaction diffusion phenomena, which are studied numerically by different numerical methods, here we use finite difference schemes (Alternating Direction Implicit and Fourth Order Douglas Implicit) to approximate the solution. Accuracy is studied in term of L2, L∞ and relative error norms by random selected grids along time levels for comparison with analytical results. The test example demonstrates the accuracy, efficiency and versatility of the proposed schemes. Numerical results showed that Fourth Order Douglas Implicit scheme is very efficient and reliable for solving 3-D non-linear reaction diffusion equation.

Fourth order Douglas implicit scheme for solving three dimension reaction diffusion equation with non-linear source term

Directory of Open Access Journals (Sweden)

Shahid Hasnain

2017-07-01

Full Text Available This research paper represents a numerical approximation to non-linear three dimension reaction diffusion equation with non-linear source term from population genetics. Since various initial and boundary value problems exist in three dimension reaction diffusion phenomena, which are studied numerically by different numerical methods, here we use finite difference schemes (Alternating Direction Implicit and Fourth Order Douglas Implicit to approximate the solution. Accuracy is studied in term of L2, L∞ and relative error norms by random selected grids along time levels for comparison with analytical results. The test example demonstrates the accuracy, efficiency and versatility of the proposed schemes. Numerical results showed that Fourth Order Douglas Implicit scheme is very efficient and reliable for solving 3-D non-linear reaction diffusion equation.

Isogeometric BDDC deluxe preconditioners for linear elasticity

KAUST Repository

Pavarino, L. F.

2018-03-14

Balancing Domain Decomposition by Constraints (BDDC) preconditioners have been shown to provide rapidly convergent preconditioned conjugate gradient methods for solving many of the very ill-conditioned systems of algebraic equations which often arise in finite element approximations of a large variety of problems in continuum mechanics. These algorithms have also been developed successfully for problems arising in isogeometric analysis. In particular, the BDDC deluxe version has proven very successful for problems approximated by Non-Uniform Rational B-Splines (NURBS), even those of high order and regularity. One main purpose of this paper is to extend the theory, previously fully developed only for scalar elliptic problems in the plane, to problems of linear elasticity in three dimensions. Numerical experiments supporting the theory are also reported. Some of these experiments highlight the fact that the development of the theory can help to decrease substantially the dimension of the primal space of the BDDC algorithm, which provides the necessary global component of these preconditioners, while maintaining scalability and good convergence rates.

Isogeometric BDDC deluxe preconditioners for linear elasticity

KAUST Repository

Pavarino, L. F.; Scacchi, S.; Widlund, O. B.; Zampini, Stefano

2018-01-01

Balancing Domain Decomposition by Constraints (BDDC) preconditioners have been shown to provide rapidly convergent preconditioned conjugate gradient methods for solving many of the very ill-conditioned systems of algebraic equations which often arise in finite element approximations of a large variety of problems in continuum mechanics. These algorithms have also been developed successfully for problems arising in isogeometric analysis. In particular, the BDDC deluxe version has proven very successful for problems approximated by Non-Uniform Rational B-Splines (NURBS), even those of high order and regularity. One main purpose of this paper is to extend the theory, previously fully developed only for scalar elliptic problems in the plane, to problems of linear elasticity in three dimensions. Numerical experiments supporting the theory are also reported. Some of these experiments highlight the fact that the development of the theory can help to decrease substantially the dimension of the primal space of the BDDC algorithm, which provides the necessary global component of these preconditioners, while maintaining scalability and good convergence rates.

An Entropic Estimator for Linear Inverse Problems

Directory of Open Access Journals (Sweden)

Amos Golan

2012-05-01

Full Text Available In this paper we examine an Information-Theoretic method for solving noisy linear inverse estimation problems which encompasses under a single framework a whole class of estimation methods. Under this framework, the prior information about the unknown parameters (when such information exists, and constraints on the parameters can be incorporated in the statement of the problem. The method builds on the basics of the maximum entropy principle and consists of transforming the original problem into an estimation of a probability density on an appropriate space naturally associated with the statement of the problem. This estimation method is generic in the sense that it provides a framework for analyzing non-normal models, it is easy to implement and is suitable for all types of inverse problems such as small and or ill-conditioned, noisy data. First order approximation, large sample properties and convergence in distribution are developed as well. Analytical examples, statistics for model comparisons and evaluations, that are inherent to this method, are discussed and complemented with explicit examples.

A feasible DY conjugate gradient method for linear equality constraints

Science.gov (United States)

LI, Can

2017-09-01

In this paper, we propose a feasible conjugate gradient method for solving linear equality constrained optimization problem. The method is an extension of the Dai-Yuan conjugate gradient method proposed by Dai and Yuan to linear equality constrained optimization problem. It can be applied to solve large linear equality constrained problem due to lower storage requirement. An attractive property of the method is that the generated direction is always feasible and descent direction. Under mild conditions, the global convergence of the proposed method with exact line search is established. Numerical experiments are also given which show the efficiency of the method.

ALPS: A Linear Program Solver

Science.gov (United States)

Ferencz, Donald C.; Viterna, Larry A.

1991-01-01

ALPS is a computer program which can be used to solve general linear program (optimization) problems. ALPS was designed for those who have minimal linear programming (LP) knowledge and features a menu-driven scheme to guide the user through the process of creating and solving LP formulations. Once created, the problems can be edited and stored in standard DOS ASCII files to provide portability to various word processors or even other linear programming packages. Unlike many math-oriented LP solvers, ALPS contains an LP parser that reads through the LP formulation and reports several types of errors to the user. ALPS provides a large amount of solution data which is often useful in problem solving. In addition to pure linear programs, ALPS can solve for integer, mixed integer, and binary type problems. Pure linear programs are solved with the revised simplex method. Integer or mixed integer programs are solved initially with the revised simplex, and the completed using the branch-and-bound technique. Binary programs are solved with the method of implicit enumeration. This manual describes how to use ALPS to create, edit, and solve linear programming problems. Instructions for installing ALPS on a PC compatible computer are included in the appendices along with a general introduction to linear programming. A programmers guide is also included for assistance in modifying and maintaining the program.

Constrained non-linear optimization in 3D reflexion tomography; Problemes d'optimisation non-lineaire avec contraintes en tomographie de reflexion 3D

Energy Technology Data Exchange (ETDEWEB)

Delbos, F

2004-11-01

Reflexion tomography allows the determination of a subsurface velocity model from the travel times of seismic waves. The introduction of a priori information in this inverse problem can lead to the resolution of a constrained non-linear least-squares problem. The goal of the thesis is to improve the resolution techniques of this optimization problem, whose main difficulties are its ill-conditioning, its large scale and an expensive cost function in terms of CPU time. Thanks to a detailed study of the problem and to numerous numerical experiments, we justify the use of a sequential quadratic programming method, in which the tangential quadratic programs are solved by an original augmented Lagrangian method. We show the global linear convergence of the latter. The efficiency and robustness of the approach are demonstrated on several synthetic examples and on two real data cases. (author)

Minimization of Linear Functionals Defined on| Solutions of Large-Scale Discrete Ill-Posed Problems

DEFF Research Database (Denmark)

Elden, Lars; Hansen, Per Christian; Rojas, Marielba

2003-01-01

The minimization of linear functionals de ned on the solutions of discrete ill-posed problems arises, e.g., in the computation of con dence intervals for these solutions. In 1990, Elden proposed an algorithm for this minimization problem based on a parametric-programming reformulation involving...... the solution of a sequence of trust-region problems, and using matrix factorizations. In this paper, we describe MLFIP, a large-scale version of this algorithm where a limited-memory trust-region solver is used on the subproblems. We illustrate the use of our algorithm in connection with an inverse heat...

Incidence and impact of pain conditions and comorbid illnesses

Directory of Open Access Journals (Sweden)

Davis JA

2011-10-01

Full Text Available Jessica A Davis, Rebecca L Robinson, Trong Kim Le, Jin XieLilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USABackground: Individuals with pain often present with more than one painful condition. The purpose of this study was to characterize the rates of comorbidity, pain medication use, and health care costs for 23 selected pain conditions in a large health plan using administrative claims data from 2005 to 2007.Methods: Eligible patients included 1,211,483 adults with at least one pain condition during the one-year study period. Pain condition cohorts were classified based on the first diagnosis present in the claims during the study period.Results: Musculoskeletal pain conditions were among the most prevalent cohorts including low back pain, osteoarthritis, and fibromyalgia. Cancer pain was the least prevalent cohort. Conditions with the lowest illness severity included migraine and painful bladder syndrome cohorts, while cohorts with diabetic neuropathy, human immunodeficiency virus (HIV-associated pain, and cancer pain were the most severe. Across cohorts, the mean number of comorbid pain conditions ranged from 1.39 (for cancer pain and migraine to 2.65 (for multiple sclerosis pain. High rates of mental health conditions were found in cohorts with HIV-associated pain and multiple sclerosis pain (42.59% and 34.78% and were lowest among cohorts with rheumatoid arthritis and psoriatic arthropathy (12.73% and 13.31%, respectively. Rates of sleep disorders ranged from 5.47% (for painful bladder syndrome to 11.59% (for multiple sclerosis pain. Overall, patients averaged 3.53 unique pain medications during the study period. Considerable annual total health care costs were observed in the cancer pain cohort and the lowest costs were observed in the postherpetic neuropathy, surgically-induced pain, migraine, and irritable bowel syndrome cohorts. Costs attributed to pain were highest among the multiple sclerosis, HIV, and cancer

Electrostatic point charge fitting as an inverse problem: Revealing the underlying ill-conditioning

International Nuclear Information System (INIS)

Ivanov, Maxim V.; Talipov, Marat R.; Timerghazin, Qadir K.

2015-01-01

Atom-centered point charge (PC) model of the molecular electrostatics—a major workhorse of the atomistic biomolecular simulations—is usually parameterized by least-squares (LS) fitting of the point charge values to a reference electrostatic potential, a procedure that suffers from numerical instabilities due to the ill-conditioned nature of the LS problem. To reveal the origins of this ill-conditioning, we start with a general treatment of the point charge fitting problem as an inverse problem and construct an analytical model with the point charges spherically arranged according to Lebedev quadrature which is naturally suited for the inverse electrostatic problem. This analytical model is contrasted to the atom-centered point-charge model that can be viewed as an irregular quadrature poorly suited for the problem. This analysis shows that the numerical problems of the point charge fitting are due to the decay of the curvatures corresponding to the eigenvectors of LS sum Hessian matrix. In part, this ill-conditioning is intrinsic to the problem and is related to decreasing electrostatic contribution of the higher multipole moments, that are, in the case of Lebedev grid model, directly associated with the Hessian eigenvectors. For the atom-centered model, this association breaks down beyond the first few eigenvectors related to the high-curvature monopole and dipole terms; this leads to even wider spread-out of the Hessian curvature values. Using these insights, it is possible to alleviate the ill-conditioning of the LS point-charge fitting without introducing external restraints and/or constraints. Also, as the analytical Lebedev grid PC model proposed here can reproduce multipole moments up to a given rank, it may provide a promising alternative to including explicit multipole terms in a force field

Local Ray-Based Traveltime Computation Using the Linearized Eikonal Equation

KAUST Repository

Almubarak, Mohammed S.

2013-05-01

The computation of traveltimes plays a critical role in the conventional implementations of Kirchhoff migration. Finite-difference-based methods are considered one of the most effective approaches for traveltime calculations and are therefore widely used. However, these eikonal solvers are mainly used to obtain early-arrival traveltime. Ray tracing can be used to pick later traveltime branches, besides the early arrivals, which may lead to an improvement in velocity estimation or in seismic imaging. In this thesis, I improved the accuracy of the solution of the linearized eikonal equation by constructing a linear system of equations (LSE) based on finite-difference approximation, which is of second-order accuracy. The ill-conditioned LSE is initially regularized and subsequently solved to calculate the traveltime update. Numerical tests proved that this method is as accurate as the second-order eikonal solver. Later arrivals are picked using ray tracing. These traveltimes are binned to the nearest node on a regular grid and empty nodes are estimated by interpolating the known values. The resulting traveltime field is used as an input to the linearized eikonal algorithm, which improves the accuracy of the interpolated nodes and yields a local ray-based traveltime. This is a preliminary study and further investigation is required to test the efficiency and the convergence of the solutions.

Constrained non-linear optimization in 3D reflexion tomography; Problemes d'optimisation non-lineaire avec contraintes en tomographie de reflexion 3D

Energy Technology Data Exchange (ETDEWEB)

Delbos, F.

2004-11-01

Reflexion tomography allows the determination of a subsurface velocity model from the travel times of seismic waves. The introduction of a priori information in this inverse problem can lead to the resolution of a constrained non-linear least-squares problem. The goal of the thesis is to improve the resolution techniques of this optimization problem, whose main difficulties are its ill-conditioning, its large scale and an expensive cost function in terms of CPU time. Thanks to a detailed study of the problem and to numerous numerical experiments, we justify the use of a sequential quadratic programming method, in which the tangential quadratic programs are solved by an original augmented Lagrangian method. We show the global linear convergence of the latter. The efficiency and robustness of the approach are demonstrated on several synthetic examples and on two real data cases. (author)

Using linear programming to analyze and optimize stochastic flow lines

DEFF Research Database (Denmark)

Helber, Stefan; Schimmelpfeng, Katja; Stolletz, Raik

2011-01-01

This paper presents a linear programming approach to analyze and optimize flow lines with limited buffer capacities and stochastic processing times. The basic idea is to solve a huge but simple linear program that models an entire simulation run of a multi-stage production process in discrete time...... programming and hence allows us to solve buffer allocation problems. We show under which conditions our method works well by comparing its results to exact values for two-machine models and approximate simulation results for longer lines....

Solving block linear systems with low-rank off-diagonal blocks is easily parallelizable

Energy Technology Data Exchange (ETDEWEB)

Menkov, V. [Indiana Univ., Bloomington, IN (United States)

1996-12-31

An easily and efficiently parallelizable direct method is given for solving a block linear system Bx = y, where B = D + Q is the sum of a non-singular block diagonal matrix D and a matrix Q with low-rank blocks. This implicitly defines a new preconditioning method with an operation count close to the cost of calculating a matrix-vector product Qw for some w, plus at most twice the cost of calculating Qw for some w. When implemented on a parallel machine the processor utilization can be as good as that of those operations. Order estimates are given for the general case, and an implementation is compared to block SSOR preconditioning.

A new methodological development for solving linear bilevel integer programming problems in hybrid fuzzy environment

Directory of Open Access Journals (Sweden)

Animesh Biswas

2016-04-01

Full Text Available This paper deals with fuzzy goal programming approach to solve fuzzy linear bilevel integer programming problems with fuzzy probabilistic constraints following Pareto distribution and Frechet distribution. In the proposed approach a new chance constrained programming methodology is developed from the view point of managing those probabilistic constraints in a hybrid fuzzy environment. A method of defuzzification of fuzzy numbers using ?-cut has been adopted to reduce the problem into a linear bilevel integer programming problem. The individual optimal value of the objective of each DM is found in isolation to construct the fuzzy membership goals. Finally, fuzzy goal programming approach is used to achieve maximum degree of each of the membership goals by minimizing under deviational variables in the decision making environment. To demonstrate the efficiency of the proposed approach, a numerical example is provided.

Predicting birth weight with conditionally linear transformation models.

Science.gov (United States)

Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten

2016-12-01

Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.

Stability and response bounds of non-conservative linear systems

DEFF Research Database (Denmark)

Pommer, Christian

2003-01-01

For a linear system of second order differential equations the stability is studied by Lyapunov's direct method. The Lyapunov matrix equation is solved and a sufficient condition for stability is expressed by the system matrices. For a system which satisfies the condition for stability the Lyapunov...

Using the Multiplicative Schwarz Alternating Algorithm (MSAA) for Solving the Large Linear System of Equations Related to Global Gravity Field Recovery up to Degree and Order 120

Science.gov (United States)

Safari, A.; Sharifi, M. A.; Amjadiparvar, B.

2010-05-01

The GRACE mission has substantiated the low-low satellite-to-satellite tracking (LL-SST) concept. The LL-SST configuration can be combined with the previously realized high-low SST concept in the CHAMP mission to provide a much higher accuracy. The line of sight (LOS) acceleration difference between the GRACE satellite pair is the mostly used observable for mapping the global gravity field of the Earth in terms of spherical harmonic coefficients. In this paper, mathematical formulae for LOS acceleration difference observations have been derived and the corresponding linear system of equations has been set up for spherical harmonic up to degree and order 120. The total number of unknowns is 14641. Such a linear equation system can be solved with iterative solvers or direct solvers. However, the runtime of direct methods or that of iterative solvers without a suitable preconditioner increases tremendously. This is the reason why we need a more sophisticated method to solve the linear system of problems with a large number of unknowns. Multiplicative variant of the Schwarz alternating algorithm is a domain decomposition method, which allows it to split the normal matrix of the system into several smaller overlaped submatrices. In each iteration step the multiplicative variant of the Schwarz alternating algorithm solves linear systems with the matrices obtained from the splitting successively. It reduces both runtime and memory requirements drastically. In this paper we propose the Multiplicative Schwarz Alternating Algorithm (MSAA) for solving the large linear system of gravity field recovery. The proposed algorithm has been tested on the International Association of Geodesy (IAG)-simulated data of the GRACE mission. The achieved results indicate the validity and efficiency of the proposed algorithm in solving the linear system of equations from accuracy and runtime points of view. Keywords: Gravity field recovery, Multiplicative Schwarz Alternating Algorithm, Low

A literature review of expert problem solving using analogy

OpenAIRE

Mair, C; Martincova, M; Shepperd, MJ

2009-01-01

We consider software project cost estimation from a problem solving perspective. Taking a cognitive psychological approach, we argue that the algorithmic basis for CBR tools is not representative of human problem solving and this mismatch could account for inconsistent results. We describe the fundamentals of problem solving, focusing on experts solving ill-defined problems. This is supplemented by a systematic literature review of empirical studies of expert problem solving of non-trivial pr...

T-Stability of the Heun Method and Balanced Method for Solving Stochastic Differential Delay Equations

Directory of Open Access Journals (Sweden)

Xiaolin Zhu

2014-01-01

Full Text Available This paper studies the T-stability of the Heun method and balanced method for solving stochastic differential delay equations (SDDEs. Two T-stable conditions of the Heun method are obtained for two kinds of linear SDDEs. Moreover, two conditions under which the balanced method is T-stable are obtained for two kinds of linear SDDEs. Some numerical examples verify the theoretical results proposed.

Combining the CORS and BiCORSTAB Iterative Methods with MLFMA and SAI Preconditioning for Solving Large Linear Systems in Electromagnetics

NARCIS (Netherlands)

Carpentieri, Bruno; Jing, Yan-Fei; Huang, Ting-Zhu; Pi, Wei-Chao; Sheng, Xin-Qing

We report on experiments with a novel family of Krylov subspace methods for solving dense, complex, non-Hermitian systems of linear equations arising from the Galerkin discretization of surface integral equation models in Electromagnetics. By some experiments on realistic radar-cross-section

Global stabilization of linear continuous time-varying systems with bounded controls

International Nuclear Information System (INIS)

Phat, V.N.

2004-08-01

This paper deals with the problem of global stabilization of a class of linear continuous time-varying systems with bounded controls. Based on the controllability of the nominal system, a sufficient condition for the global stabilizability is proposed without solving any Riccati differential equation. Moreover, we give sufficient conditions for the robust stabilizability of perturbation/uncertain linear time-varying systems with bounded controls. (author)

On the hyperbolicity condition in linear elasticity

Directory of Open Access Journals (Sweden)

Remigio Russo

1991-05-01

Full Text Available This talk, which is mainly expository and based on [2-5], discusses the hyperbolicity conditions in linear elastodynamics. Particular emphasis is devoted to the key role it plays in the uniqueness questions associated with the mixed boundary-initial value problem in unbounded domains.

A novel algebraic procedure for solving non-linear evolution equations of higher order

International Nuclear Information System (INIS)

Huber, Alfred

2007-01-01

We report here a systematic approach that can easily be used for solving non-linear partial differential equations (nPDE), especially of higher order. We restrict the analysis to the so called evolution equations describing any wave propagation. The proposed new algebraic approach leads us to traveling wave solutions and moreover, new class of solution can be obtained. The crucial step of our method is the basic assumption that the solutions satisfy an ordinary differential equation (ODE) of first order that can be easily integrated. The validity and reliability of the method is tested by its application to some non-linear evolution equations. The important aspect of this paper however is the fact that we are able to calculate distinctive class of solutions which cannot be found in the current literature. In other words, using this new algebraic method the solution manifold is augmented to new class of solution functions. Simultaneously we would like to stress the necessity of such sophisticated methods since a general theory of nPDE does not exist. Otherwise, for practical use the algebraic construction of new class of solutions is of fundamental interest

Ten-Year-Old Students Solving Linear Equations

Science.gov (United States)

Brizuela, Barbara; Schliemann, Analucia

2004-01-01

In this article, the authors seek to re-conceptualize the perspective regarding students' difficulties with algebra. While acknowledging that students "do" have difficulties when learning algebra, they also argue that the generally espoused criteria for algebra as the ability to work with the syntactical rules for solving equations is…

A matrix formalism to solve interface condition equations in a reactor system

Energy Technology Data Exchange (ETDEWEB)

Matausek, M V [Boris Kidric Institute of Nuclear Sciences Vinca, Beograd (Yugoslavia)

1970-05-15

When a nuclear reactor or a reactor lattice cell is treated by an approximate procedure to solve the neutron transport equation, as the last computational step often appears a problem of solving systems of algebraic equations stating the interface and boundary conditions for the neutron flux moments. These systems have usually the coefficient matrices of the block-bi diagonal type, containing thus a large number of zero elements. In the present report it is shown how such a system can be solved efficiently accounting for all the zero elements both in the coefficient matrix and in the free term vector. The procedure is presented here for the case of multigroup P{sub 3} calculation of neutron flux distribution in a cylindrical reactor lattice cell. Compared with the standard gaussian elimination method, this procedure is more advantageous both in respect to the number of operations needed to solve a given problem and in respect to the computer memory storage requirements. A similar formalism can also be applied for other approximate methods, for instance for multigroup diffusion treatment of a multi zone reactor. (author)

An Efficient Numerical Approach for Solving Nonlinear Coupled Hyperbolic Partial Differential Equations with Nonlocal Conditions

Directory of Open Access Journals (Sweden)

A. H. Bhrawy

2014-01-01

Full Text Available One of the most important advantages of collocation method is the possibility of dealing with nonlinear partial differential equations (PDEs as well as PDEs with variable coefficients. A numerical solution based on a Jacobi collocation method is extended to solve nonlinear coupled hyperbolic PDEs with variable coefficients subject to initial-boundary nonlocal conservation conditions. This approach, based on Jacobi polynomials and Gauss-Lobatto quadrature integration, reduces solving the nonlinear coupled hyperbolic PDEs with variable coefficients to a system of nonlinear ordinary differential equation which is far easier to solve. In fact, we deal with initial-boundary coupled hyperbolic PDEs with variable coefficients as well as initial-nonlocal conditions. Using triangular, soliton, and exponential-triangular solutions as exact solutions, the obtained results show that the proposed numerical algorithm is efficient and very accurate.

Programmable Solution for Solving Non-linearity Characteristics of Smart Sensor Applications

Directory of Open Access Journals (Sweden)

S. Khan

2007-10-01

Full Text Available This paper presents a simple but programmable technique to solve the problem of non-linear characteristics of sensors used in more sensitive applications. The nonlinearity of the output response becomes a very sensitive issue in cases where a proportional increase in the physical quantity fails to bring about a proportional increase in the signal measured. The nonlinearity is addressed by using the interpolation method on the characteristics of a given sensor, approximating it to a set of tangent lines, the tangent points of which are recognized in the code of the processor by IF-THEN code. The method suggested here eliminates the use of external circuits for interfacing, and eases the programming burden on the processor at the cost of proportionally reduced memory requirements. The mathematically worked out results are compared with the simulation and experimental results for an IR sensor selected for the purpose and used for level measurement. This work will be of paramount importance and significance in applications where the controlled signal is required to follow the input signal precisely particularly in sensitive robotic applications.

Periodic solutions of asymptotically linear Hamiltonian systems without twist conditions

Energy Technology Data Exchange (ETDEWEB)

Cheng Rong [Coll. of Mathematics and Physics, Nanjing Univ. of Information Science and Tech., Nanjing (China); Dept. of Mathematics, Southeast Univ., Nanjing (China); Zhang Dongfeng [Dept. of Mathematics, Southeast Univ., Nanjing (China)

2010-05-15

In dynamical system theory, especially in many fields of applications from mechanics, Hamiltonian systems play an important role, since many related equations in mechanics can be written in an Hamiltonian form. In this paper, we study the existence of periodic solutions for a class of Hamiltonian systems. By applying the Galerkin approximation method together with a result of critical point theory, we establish the existence of periodic solutions of asymptotically linear Hamiltonian systems without twist conditions. Twist conditions play crucial roles in the study of periodic solutions for asymptotically linear Hamiltonian systems. The lack of twist conditions brings some difficulty to the study. To the authors' knowledge, very little is known about the case, where twist conditions do not hold. (orig.)

Algorithm for solving the linear Cauchy problem for large systems of ordinary differential equations with the use of parallel computations

Energy Technology Data Exchange (ETDEWEB)

Moryakov, A. V., E-mail: sailor@orc.ru [National Research Centre Kurchatov Institute (Russian Federation)

2016-12-15

An algorithm for solving the linear Cauchy problem for large systems of ordinary differential equations is presented. The algorithm for systems of first-order differential equations is implemented in the EDELWEISS code with the possibility of parallel computations on supercomputers employing the MPI (Message Passing Interface) standard for the data exchange between parallel processes. The solution is represented by a series of orthogonal polynomials on the interval [0, 1]. The algorithm is characterized by simplicity and the possibility to solve nonlinear problems with a correction of the operator in accordance with the solution obtained in the previous iterative process.

Simon on Problem-Solving

DEFF Research Database (Denmark)

Foss, Kirsten; Foss, Nicolai Juul

as a general approach to problem solving. We apply these Simonian ideas to organizational issues, specifically new organizational forms. Specifically, Simonian ideas allow us to develop a morphology of new organizational forms and to point to some design problems that characterize these forms.Keywords: Herbert...... Simon, problem-solving, new organizational forms. JEL Code: D23, D83......Two of Herbert Simon's best-known papers are "The Architecture of Complexity" and "The Structure of Ill-Structured Problems." We discuss the neglected links between these two papers, highlighting the role of decomposition in the context of problems on which constraints have been imposed...

General treatment of a non-linear gauge condition

International Nuclear Information System (INIS)

Malleville, C.

1982-06-01

A non linear gauge condition is presented in the frame of a non abelian gauge theory broken with the Higgs mechanism. It is shown that this condition already introduced for the standard SU(2) x U(1) model can be generalized for any gauge model with the same type of simplification, namely the suppression of any coupling of the form: massless gauge boson, massive gauge boson, unphysical Higgs [fr

Pareto optimality in infinite horizon linear quadratic differential games

NARCIS (Netherlands)

Reddy, P.V.; Engwerda, J.C.

2013-01-01

In this article we derive conditions for the existence of Pareto optimal solutions for linear quadratic infinite horizon cooperative differential games. First, we present a necessary and sufficient characterization for Pareto optimality which translates to solving a set of constrained optimal

A composite step conjugate gradients squared algorithm for solving nonsymmetric linear systems

Science.gov (United States)

Chan, Tony; Szeto, Tedd

1994-03-01

We propose a new and more stable variant of the CGS method [27] for solving nonsymmetric linear systems. The method is based on squaring the Composite Step BCG method, introduced recently by Bank and Chan [1,2], which itself is a stabilized variant of BCG in that it skips over steps for which the BCG iterate is not defined and causes one kind of breakdown in BCG. By doing this, we obtain a method (Composite Step CGS or CSCGS) which not only handles the breakdowns described above, but does so with the advantages of CGS, namely, no multiplications by the transpose matrix and a faster convergence rate than BCG. Our strategy for deciding whether to skip a step does not involve any machine dependent parameters and is designed to skip near breakdowns as well as produce smoother iterates. Numerical experiments show that the new method does produce improved performance over CGS on practical problems.

Schwarzian conditions for linear differential operators with selected differential Galois groups

International Nuclear Information System (INIS)

Abdelaziz, Y; Maillard, J-M

2017-01-01

We show that non-linear Schwarzian differential equations emerging from covariance symmetry conditions imposed on linear differential operators with hypergeometric function solutions can be generalized to arbitrary order linear differential operators with polynomial coefficients having selected differential Galois groups. For order three and order four linear differential operators we show that this pullback invariance up to conjugation eventually reduces to symmetric powers of an underlying order-two operator. We give, precisely, the conditions to have modular correspondences solutions for such Schwarzian differential equations, which was an open question in a previous paper. We analyze in detail a pullbacked hypergeometric example generalizing modular forms, that ushers a pullback invariance up to operator homomorphisms. We finally consider the more general problem of the equivalence of two different order-four linear differential Calabi–Yau operators up to pullbacks and conjugation, and clarify the cases where they have the same Yukawa couplings. (paper)

Schwarzian conditions for linear differential operators with selected differential Galois groups

Science.gov (United States)

Abdelaziz, Y.; Maillard, J.-M.

2017-11-01

We show that non-linear Schwarzian differential equations emerging from covariance symmetry conditions imposed on linear differential operators with hypergeometric function solutions can be generalized to arbitrary order linear differential operators with polynomial coefficients having selected differential Galois groups. For order three and order four linear differential operators we show that this pullback invariance up to conjugation eventually reduces to symmetric powers of an underlying order-two operator. We give, precisely, the conditions to have modular correspondences solutions for such Schwarzian differential equations, which was an open question in a previous paper. We analyze in detail a pullbacked hypergeometric example generalizing modular forms, that ushers a pullback invariance up to operator homomorphisms. We finally consider the more general problem of the equivalence of two different order-four linear differential Calabi-Yau operators up to pullbacks and conjugation, and clarify the cases where they have the same Yukawa couplings.

Oxidative Stress and Mitochondrial Injury in Chronic Multisymptom Conditions: From Gulf War Illness to Autism Spectrum Disorder

OpenAIRE

Beatrice A. Golomb

2012-01-01

Background: Overlapping chronic multisymptom illnesses (CMI) include Chronic Fatigue Syndrome (CFS), fibromyalgia, irritable bowel syndrome, multiple chemical sensitivity, and Gulf War illness (GWI), and subsets of autism spectrum disorder (ASD). GWI entails a more circumscribed set of experiences that may provide insights of relevance to overlapping conditions.

Linear System of Equations, Matrix Inversion, and Linear Programming Using MS Excel

Science.gov (United States)

El-Gebeily, M.; Yushau, B.

2008-01-01

In this note, we demonstrate with illustrations two different ways that MS Excel can be used to solve Linear Systems of Equation, Linear Programming Problems, and Matrix Inversion Problems. The advantage of using MS Excel is its availability and transparency (the user is responsible for most of the details of how a problem is solved). Further, we…

Minimum Energy Control of 2D Positive Continuous-Discrete Linear Systems

Directory of Open Access Journals (Sweden)

Kaczorek Tadeusz

2014-09-01

Full Text Available The minimum energy control problem for the 2D positive continuous-discrete linear systems is formulated and solved. Necessary and sufficient conditions for the reachability at the point of the systems are given. Sufficient conditions for the existence of solution to the problem are established. It is shown that if the system is reachable then there exists an optimal input that steers the state from zero boundary conditions to given final state and minimizing the performance index for only one step (q = 1. A procedure for solving of the problem is proposed and illustrated by a numerical example.

A Chess-Like Game for Teaching Engineering Students to Solve Large System of Simultaneous Linear Equations

Science.gov (United States)

Nguyen, Duc T.; Mohammed, Ahmed Ali; Kadiam, Subhash

2010-01-01

Solving large (and sparse) system of simultaneous linear equations has been (and continues to be) a major challenging problem for many real-world engineering/science applications [1-2]. For many practical/large-scale problems, the sparse, Symmetrical and Positive Definite (SPD) system of linear equations can be conveniently represented in matrix notation as [A] {x} = {b} , where the square coefficient matrix [A] and the Right-Hand-Side (RHS) vector {b} are known. The unknown solution vector {x} can be efficiently solved by the following step-by-step procedures [1-2]: Reordering phase, Matrix Factorization phase, Forward solution phase, and Backward solution phase. In this research work, a Game-Based Learning (GBL) approach has been developed to help engineering students to understand crucial details about matrix reordering and factorization phases. A "chess-like" game has been developed and can be played by either a single player, or two players. Through this "chess-like" open-ended game, the players/learners will not only understand the key concepts involved in reordering algorithms (based on existing algorithms), but also have the opportunities to "discover new algorithms" which are better than existing algorithms. Implementing the proposed "chess-like" game for matrix reordering and factorization phases can be enhanced by FLASH [3] computer environments, where computer simulation with animated human voice, sound effects, visual/graphical/colorful displays of matrix tables, score (or monetary) awards for the best game players, etc. can all be exploited. Preliminary demonstrations of the developed GBL approach can be viewed by anyone who has access to the internet web-site [4]!

Quantum osp-invariant non-linear Schroedinger equation

International Nuclear Information System (INIS)

Kulish, P.P.

1985-04-01

The generalizations of the non-linear Schroedinger equation (NS) associated with the orthosymplectic superalgebras are formulated. The simplest osp(1/2)-NS model is solved by the quantum inverse scattering method on a finite interval under periodic boundary conditions as well as on the wholeline in the case of a finite number of excitations. (author)

Finite-Time Stability Analysis of Discrete-Time Linear Singular Systems

Directory of Open Access Journals (Sweden)

Songlin Wo

2014-01-01

Full Text Available The finite-time stability (FTS problem of discrete-time linear singular systems (DTLSS is considered in this paper. A necessary and sufficient condition for FTS is obtained, which can be expressed in terms of matrix inequalities. Then, another form of the necessary and sufficient condition for FTS is also given by using matrix-null space technology. In order to solve the stability problem expediently, a sufficient condition for FTS is given via linear matrix inequality (LMI approach; this condition can be expressed in terms of LMIs. Finally, an illustrating example is also given to show the effectiveness of the proposed method.

Exertional Heat Illnesses and Environmental Conditions During High School Football Practices.

Science.gov (United States)

Tripp, Brady L; Eberman, Lindsey E; Smith, Michael Seth

2015-10-01

Guidelines for preventing exertional heat illnesses (EHIs) during extreme heat stress should be specific to regional environments, age, and sport and should be based on evidence of reducing the risk. Each year in the United States, over 1 million high school football players practice in the August heat; however, no published data describe the incidence of EHIs in these athletes. To describe the environmental conditions and incidence of EHIs during high school football practices over a 3-month period. Descriptive epidemiology study. For a 3-month period (August-October), athletic trainers at 12 high schools in North Central Florida recorded the practice time and length, environmental conditions (wet-bulb globe temperature), and incidences of EHIs in varsity football athletes. Athletes suffered 57 total EHIs during 29,759 athlete-exposures (AEs) for the 3-month data collection period (rate = 1.92/1000 AEs). August accounted for the majority of all EHIs, with 82.5% (47/57) and the highest rate (4.35/1000 AEs). Of total heat illnesses, heat cramps accounted for 70.2% (40/57), heat exhaustion 22.8% (13/57), and heat syncope 7.0% (4/57). The odds ratio indicated that athletes in August practices that lasted longer than the recommended 3 hours were 9.84 times more likely to suffer a heat illness than those in practices lasting ≤3 hours. The highest rate of EHIs was during August. Practices in August that exceeded the recommended 3 hours were associated with a greater risk of heat illnesses. The overall rate of EHIs was lower for the high school football athletes observed in the study compared with that reported for collegiate football athletes in the region. The low rates of EHIs recorded suggest that the prevention guidelines employed by sports medicine teams are appropriate for the region and population. Team physicians and athletic trainers should employ evidence-based, region- and population-specific EHI prevention guidelines. Sports medicine teams, coaches, and

Structured Control of Affine Linear Parameter Varying Systems

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Stoustrup, Jakob

2011-01-01

This paper presents a new procedure to design structured controllers for discrete-time affine linear parametervarying systems (A LPV). The class of control structures includes decentralized of any order, fixed order output feedback, simultaneous plant-control design, among others. A parametervarying...... non-convex condition for an upper bound on the induced L2-norm performance is solved by an iterative linear matrix inequalities (LMI) optimization algorithm. Numerical examples demostrate the effectiveness of the proposed approach....

Path integral solution of linear second order partial differential equations I: the general construction

International Nuclear Information System (INIS)

LaChapelle, J.

2004-01-01

A path integral is presented that solves a general class of linear second order partial differential equations with Dirichlet/Neumann boundary conditions. Elementary kernels are constructed for both Dirichlet and Neumann boundary conditions. The general solution can be specialized to solve elliptic, parabolic, and hyperbolic partial differential equations with boundary conditions. This extends the well-known path integral solution of the Schroedinger/diffusion equation in unbounded space. The construction is based on a framework for functional integration introduced by Cartier/DeWitt-Morette

Solving a Deconvolution Problem in Photon Spectrometry

CERN Document Server

Aleksandrov, D; Hille, P T; Polichtchouk, B; Kharlov, Y; Sukhorukov, M; Wang, D; Shabratova, G; Demanov, V; Wang, Y; Tveter, T; Faltys, M; Mao, Y; Larsen, D T; Zaporozhets, S; Sibiryak, I; Lovhoiden, G; Potcheptsov, T; Kucheryaev, Y; Basmanov, V; Mares, J; Yanovsky, V; Qvigstad, H; Zenin, A; Nikolaev, S; Siemiarczuk, T; Yuan, X; Cai, X; Redlich, K; Pavlinov, A; Roehrich, D; Manko, V; Deloff, A; Ma, K; Maruyama, Y; Dobrowolski, T; Shigaki, K; Nikulin, S; Wan, R; Mizoguchi, K; Petrov, V; Mueller, H; Ippolitov, M; Liu, L; Sadovsky, S; Stolpovsky, P; Kurashvili, P; Nomokonov, P; Xu, C; Torii, H; Il'kaev, R; Zhang, X; Peresunko, D; Soloviev, A; Vodopyanov, A; Sugitate, T; Ullaland, K; Huang, M; Zhou, D; Nystrand, J; Punin, V; Yin, Z; Batyunya, B; Karadzhev, K; Nazarov, G; Fil'chagin, S; Nazarenko, S; Buskenes, J I; Horaguchi, T; Djuvsland, O; Chuman, F; Senko, V; Alme, J; Wilk, G; Fehlker, D; Vinogradov, Y; Budilov, V; Iwasaki, T; Ilkiv, I; Budnikov, D; Vinogradov, A; Kazantsev, A; Bogolyubsky, M; Lindal, S; Polak, K; Skaali, B; Mamonov, A; Kuryakin, A; Wikne, J; Skjerdal, K

2010-01-01

We solve numerically a deconvolution problem to extract the undisturbed spectrum from the measured distribution contaminated by the finite resolution of the measuring device. A problem of this kind emerges when one wants to infer the momentum distribution of the neutral pions by detecting the it decay photons using the photon spectrometer of the ALICE LHC experiment at CERN {[}1]. The underlying integral equation connecting the sought for pion spectrum and the measured gamma spectrum has been discretized and subsequently reduced to a system of linear algebraic equations. The latter system, however, is known to be ill-posed and must be regularized to obtain a stable solution. This task has been accomplished here by means of the Tikhonov regularization scheme combined with the L-curve method. The resulting pion spectrum is in an excellent quantitative agreement with the pion spectrum obtained from a Monte Carlo simulation. (C) 2010 Elsevier B.V. All rights reserved.

Portraying mental illness and drug addiction as treatable health conditions: effects of a randomized experiment on stigma and discrimination.

Science.gov (United States)

McGinty, Emma E; Goldman, Howard H; Pescosolido, Bernice; Barry, Colleen L

2015-02-01

Despite significant advances in treatment, stigma and discrimination toward persons with mental illness and drug addiction have remained constant in past decades. Prior work suggests that portraying other stigmatized health conditions (i.e., HIV/AIDS) as treatable can improve public attitudes toward those affected. Our study compared the effects of vignettes portraying persons with untreated and symptomatic versus successfully treated and asymptomatic mental illness and drug addiction on several dimensions of public attitudes about these conditions. We conducted a survey-embedded randomized experiment using a national sample (N = 3940) from an online panel. Respondents were randomly assigned to read one of ten vignettes. Vignette one was a control vignette, vignettes 2-5 portrayed individuals with untreated schizophrenia, depression, prescription pain medication addiction and heroin addiction, and vignettes 6-10 portrayed successfully treated individuals with the same conditions. After reading the randomly assigned vignette, respondents answered questions about their attitudes related to mental illness or drug addiction. Portrayals of untreated and symptomatic schizophrenia, depression, and heroin addiction heightened negative public attitudes toward persons with mental illness and drug addiction. In contrast, portrayals of successfully treated schizophrenia, prescription painkiller addiction, and heroin addiction led to less desire for social distance, greater belief in the effectiveness of treatment, and less willingness to discriminate against persons with these conditions. Portrayal of persons with successfully treated mental illness and drug addiction is a promising strategy for reducing stigma and discrimination toward persons with these conditions and improving public perceptions of treatment effectiveness. Copyright © 2014 Elsevier Ltd. All rights reserved.

A neural network method for solving a system of linear variational inequalities

International Nuclear Information System (INIS)

Lan Hengyou; Cui Yishun

2009-01-01

In this paper, we transmute the solution for a new system of linear variational inequalities to an equilibrium point of neural networks, and by using analytic technique, some sufficient conditions are presented. Further, the estimation of the exponential convergence rates of the neural networks is investigated. The new and useful results obtained in this paper generalize and improve the corresponding results of recent works.

Convergence of the standard RLS method and UDUT factorisation of covariance matrix for solving the algebraic Riccati equation of the DLQR via heuristic approximate dynamic programming

Science.gov (United States)

Moraes Rêgo, Patrícia Helena; Viana da Fonseca Neto, João; Ferreira, Ernesto M.

2015-08-01

The main focus of this article is to present a proposal to solve, via UDUT factorisation, the convergence and numerical stability problems that are related to the covariance matrix ill-conditioning of the recursive least squares (RLS) approach for online approximations of the algebraic Riccati equation (ARE) solution associated with the discrete linear quadratic regulator (DLQR) problem formulated in the actor-critic reinforcement learning and approximate dynamic programming context. The parameterisations of the Bellman equation, utility function and dynamic system as well as the algebra of Kronecker product assemble a framework for the solution of the DLQR problem. The condition number and the positivity parameter of the covariance matrix are associated with statistical metrics for evaluating the approximation performance of the ARE solution via RLS-based estimators. The performance of RLS approximators is also evaluated in terms of consistence and polarisation when associated with reinforcement learning methods. The used methodology contemplates realisations of online designs for DLQR controllers that is evaluated in a multivariable dynamic system model.

Psychosocial well-being in young adults with chronic illness since childhood: the role of illness cognitions

Science.gov (United States)

2014-01-01

Background More and more pediatric patients reach adulthood. Some of them are successfully integrating in adult life, but many others are not. Possibly Illness cognitions (IC) - the way people give meaning to their illness/disability – may play a role in individual differences on long-term adjustment. This study explored the association of IC with disease–characteristics and Health Related Quality of Life (HRQoL), anxiety and depression in young adults with a disability benefit due to childhood-onset chronic condition. Methods In a cross-sectional study, young adults (22–31 years, N = 377) who claimed a disability benefit because of a somatic condition since childhood, completed the Illness Cognition Questionnaire (acceptance-helplessness-benefits), RAND-36 (HRQoL) and HADS (anxiety and depression) online. Besides descriptive statistics, linear regression analyses were conducted to predict (1) illness cognitions by age, gender and disease-characteristics, and (2) HRQoL (Mental and Physical Component Scale), Anxiety and Depression by illness cognitions, controlling for disease-characteristics, age and gender. Results Respectively 90.2%, 83.8% and 53.3% of the young adults with a disability benefit experienced feelings of acceptance, benefits and helplessness. Several disease-characteristics were associated with IC. More acceptance and less helplessness were associated with better mental (β = 0.31; β = −0.32) and physical (β = 0.16; β = −0.15) HRQoL and with less anxiety (β = −0.27; β = 0.28) and depression (β = −0.29; β = 0.31). Conclusions IC of young adult beneficiaries were associated with their HRQoL and feelings of anxiety and depression. Early recognition of psychological distress and negative IC might be a key to the identification of pediatric patients at risk for long-term dysfunction. Identification of maladaptive illness cognitions enables the development of psychosocial interventions to optimise

Linear perturbations of a self-similar solution of hydrodynamics with non-linear heat conduction

International Nuclear Information System (INIS)

Dubois-Boudesocque, Carine

2000-01-01

The stability of an ablative flow, where a shock wave is located upstream a thermal front, is of importance in inertial confinement fusion. The present model considers an exact self-similar solution to the hydrodynamic equations with non-linear heat conduction for a semi-infinite slab. For lack of an analytical solution, a high resolution numerical procedure is devised, which couples a finite difference method with a relaxation algorithm using a two-domain pseudo-spectral method. Stability of this solution is studied by introducing linear perturbation method within a Lagrangian-Eulerian framework. The initial and boundary value problem is solved by a splitting of the equations between a hyperbolic system and a parabolic equation. The boundary conditions of the hyperbolic system are treated, in the case of spectral methods, according to Thompson's approach. The parabolic equation is solved by an influence matrix method. These numerical procedures have been tested versus exact solutions. Considering a boundary heat flux perturbation, the space-time evolution of density, velocity and temperature are shown. (author) [fr

Identification problems in linear transformation system

International Nuclear Information System (INIS)

Delforge, Jacques.

1975-01-01

An attempt was made to solve the theoretical and numerical difficulties involved in the identification problem relative to the linear part of P. Delattre's theory of transformation systems. The theoretical difficulties are due to the very important problem of the uniqueness of the solution, which must be demonstrated in order to justify the value of the solution found. Simple criteria have been found when measurements are possible on all the equivalence classes, but the problem remains imperfectly solved when certain evolution curves are unknown. The numerical difficulties are of two kinds: a slow convergence of iterative methods and a strong repercussion of numerical and experimental errors on the solution. In the former case a fast convergence was obtained by transformation of the parametric space, while in the latter it was possible, from sensitivity functions, to estimate the errors, to define and measure the conditioning of the identification problem then to minimize this conditioning as a function of the experimental conditions [fr

Performance prediction of gas turbines by solving a system of non-linear equations

Energy Technology Data Exchange (ETDEWEB)

Kaikko, J

1998-09-01

This study presents a novel method for implementing the performance prediction of gas turbines from the component models. It is based on solving the non-linear set of equations that corresponds to the process equations, and the mass and energy balances for the engine. General models have been presented for determining the steady state operation of single components. Single and multiple shad arrangements have been examined with consideration also being given to heat regeneration and intercooling. Emphasis has been placed upon axial gas turbines of an industrial scale. Applying the models requires no information of the structural dimensions of the gas turbines. On comparison with the commonly applied component matching procedures, this method incorporates several advantages. The application of the models for providing results is facilitated as less attention needs to be paid to calculation sequences and routines. Solving the set of equations is based on zeroing co-ordinate functions that are directly derived from the modelling equations. Therefore, controlling the accuracy of the results is easy. This method gives more freedom for the selection of the modelling parameters since, unlike for the matching procedures, exchanging these criteria does not itself affect the algorithms. Implicit relationships between the variables are of no significance, thus increasing the freedom for the modelling equations as well. The mathematical models developed in this thesis will provide facilities to optimise the operation of any major gas turbine configuration with respect to the desired process parameters. The computational methods used in this study may also be adapted to any other modelling problems arising in industry. (orig.) 36 refs.

Solving the Fully Fuzzy Bilevel Linear Programming Problem through Deviation Degree Measures and a Ranking Function Method

Directory of Open Access Journals (Sweden)

Aihong Ren

2016-01-01

Full Text Available This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solution of the problem, we apply deviation degree measures to deal with the fuzzy constraints and use a ranking function method of fuzzy numbers to rank the upper and lower level fuzzy objective functions. Then the fully fuzzy bilevel linear programming problem can be transformed into a deterministic bilevel programming problem. Considering the overall balance between improving objective function values and decreasing allowed deviation degrees, the computational procedure for finding a fuzzy optimal solution is proposed. Finally, a numerical example is provided to illustrate the proposed approach. The results indicate that the proposed approach gives a better optimal solution in comparison with the existing method.

Two-level preconditioned conjugate gradient methods with applications to bubbly flow problems

NARCIS (Netherlands)

Tang, J.M.

2008-01-01

The Preconditioned Conjugate Gradient (PCG) method is one of the most popular iterative methods for solving large linear systems with a symmetric and positive semi-definite coefficient matrix. However, if the preconditioned coefficient matrix is ill-conditioned, the convergence of the PCG method

Exploring cross-sectional associations between common childhood illness, housing and social conditions in remote Australian Aboriginal communities

Directory of Open Access Journals (Sweden)

Brewster David

2010-03-01

Full Text Available Abstract Background There is limited epidemiological research that provides insight into the complex web of causative and moderating factors that links housing conditions to a variety of poor health outcomes. This study explores the relationship between housing conditions (with a primary focus on the functional state of infrastructure and common childhood illness in remote Australian Aboriginal communities for the purpose of informing development of housing interventions to improve child health. Methods Hierarchical multi-level analysis of association between carer report of common childhood illnesses and functional and hygienic state of housing infrastructure, socio-economic, psychosocial and health related behaviours using baseline survey data from a housing intervention study. Results Multivariate analysis showed a strong independent association between report of respiratory infection and overall functional condition of the house (Odds Ratio (OR 3.00; 95%CI 1.36-6.63, but no significant association between report of other illnesses and the overall functional condition or the functional condition of infrastructure required for specific healthy living practices. Associations between report of child illness and secondary explanatory variables which showed an OR of 2 or more included: for skin infection - evidence of poor temperature control in the house (OR 3.25; 95%CI 1.06-9.94, evidence of pests and vermin in the house (OR 2.88; 95%CI 1.25-6.60; for respiratory infection - breastfeeding in infancy (OR 0.27; 95%CI 0.14-0.49; for diarrhoea/vomiting - hygienic state of food preparation and storage areas (OR 2.10; 95%CI 1.10-4.00; for ear infection - child care attendance (OR 2.25; 95%CI 1.26-3.99. Conclusion These findings add to other evidence that building programs need to be supported by a range of other social and behavioural interventions for potential health gains to be more fully realised.

Non-Interior Continuation Method for Solving the Monotone Semidefinite Complementarity Problem

International Nuclear Information System (INIS)

Huang, Z.H.; Han, J.

2003-01-01

Recently, Chen and Tseng extended non-interior continuation smoothing methods for solving linear/ nonlinear complementarity problems to semidefinite complementarity problems (SDCP). In this paper we propose a non-interior continuation method for solving the monotone SDCP based on the smoothed Fischer-Burmeister function, which is shown to be globally linearly and locally quadratically convergent under suitable assumptions. Our algorithm needs at most to solve a linear system of equations at each iteration. In addition, in our analysis on global linear convergence of the algorithm, we need not use the assumption that the Frechet derivative of the function involved in the SDCP is Lipschitz continuous. For non-interior continuation/ smoothing methods for solving the nonlinear complementarity problem, such an assumption has been used widely in the literature in order to achieve global linear convergence results of the algorithms

Iterative Runge–Kutta-type methods for nonlinear ill-posed problems

International Nuclear Information System (INIS)

Böckmann, C; Pornsawad, P

2008-01-01

We present a regularization method for solving nonlinear ill-posed problems by applying the family of Runge–Kutta methods to an initial value problem, in particular, to the asymptotical regularization method. We prove that the developed iterative regularization method converges to a solution under certain conditions and with a general stopping rule. Some particular iterative regularization methods are numerically implemented. Numerical results of the examples show that the developed Runge–Kutta-type regularization methods yield stable solutions and that particular implicit methods are very efficient in saving iteration steps

Topics in computational linear optimization

DEFF Research Database (Denmark)

Hultberg, Tim Helge

2000-01-01

Linear optimization has been an active area of research ever since the pioneering work of G. Dantzig more than 50 years ago. This research has produced a long sequence of practical as well as theoretical improvements of the solution techniques avilable for solving linear optimization problems...... of high quality solvers and the use of algebraic modelling systems to handle the communication between the modeller and the solver. This dissertation features four topics in computational linear optimization: A) automatic reformulation of mixed 0/1 linear programs, B) direct solution of sparse unsymmetric...... systems of linear equations, C) reduction of linear programs and D) integration of algebraic modelling of linear optimization problems in C++. Each of these topics is treated in a separate paper included in this dissertation. The efficiency of solving mixed 0-1 linear programs by linear programming based...

Stability and Linear Quadratic Differential Games of Discrete-Time Markovian Jump Linear Systems with State-Dependent Noise

Directory of Open Access Journals (Sweden)

Huiying Sun

2014-01-01

Full Text Available We mainly consider the stability of discrete-time Markovian jump linear systems with state-dependent noise as well as its linear quadratic (LQ differential games. A necessary and sufficient condition involved with the connection between stochastic Tn-stability of Markovian jump linear systems with state-dependent noise and Lyapunov equation is proposed. And using the theory of stochastic Tn-stability, we give the optimal strategies and the optimal cost values for infinite horizon LQ stochastic differential games. It is demonstrated that the solutions of infinite horizon LQ stochastic differential games are concerned with four coupled generalized algebraic Riccati equations (GAREs. Finally, an iterative algorithm is presented to solve the four coupled GAREs and a simulation example is given to illustrate the effectiveness of it.

Linear versus non-linear supersymmetry, in general

Energy Technology Data Exchange (ETDEWEB)

Ferrara, Sergio [Theoretical Physics Department, CERN,CH-1211 Geneva 23 (Switzerland); INFN - Laboratori Nazionali di Frascati,Via Enrico Fermi 40, I-00044 Frascati (Italy); Department of Physics and Astronomy, UniversityC.L.A.,Los Angeles, CA 90095-1547 (United States); Kallosh, Renata [SITP and Department of Physics, Stanford University,Stanford, California 94305 (United States); Proeyen, Antoine Van [Institute for Theoretical Physics, Katholieke Universiteit Leuven,Celestijnenlaan 200D, B-3001 Leuven (Belgium); Wrase, Timm [Institute for Theoretical Physics, Technische Universität Wien,Wiedner Hauptstr. 8-10, A-1040 Vienna (Austria)

2016-04-12

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

Linear versus non-linear supersymmetry, in general

International Nuclear Information System (INIS)

Ferrara, Sergio; Kallosh, Renata; Proeyen, Antoine Van; Wrase, Timm

2016-01-01

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

Perceived quality of chronic illness care is associated with self-management: Results of a nationwide study in the Netherlands.

Science.gov (United States)

van Houtum, L; Heijmans, M; Rijken, M; Groenewegen, P

2016-04-01

Healthcare providers are increasingly expected to help chronically ill patients understand their own central role in managing their illness. The aim of this study was to determine whether experiencing high-quality chronic illness care and having a nurse involved in their care relate to chronically ill people's self-management. Survey data from 699 people diagnosed with chronic diseases who participated in a nationwide Dutch panel-study were analysed using linear regression analysis, to estimate the association between chronic illness care and various aspects of patients' self-management, while controlling for their socio-demographic and illness characteristics. Chronically ill patients reported that the care they received was of high quality to some extent. Patients who had contact with a practise nurse or specialised nurse perceived the quality of the care they received as better than patients who only had contact with a GP or medical specialist. Patients' perceptions of the quality of care were positively related to all aspects of their self-management, whereas contact with a practise nurse or specialised nurse in itself was not. Chronically ill patients who have the experience to receive high-quality chronic illness care that focusses on patient activation, decision support, goal setting, problem solving, and coordination of care are better self-managers. Having a nurse involved in their care seems to be positively valued by chronically ill patients, but does not automatically imply better self-management. Copyright © 2016. Published by Elsevier Ireland Ltd.

PCX, Interior-Point Linear Programming Solver

International Nuclear Information System (INIS)

Czyzyk, J.

2004-01-01

1 - Description of program or function: PCX solves linear programming problems using the Mehrota predictor-corrector interior-point algorithm. PCX can be called as a subroutine or used in stand-alone mode, with data supplied from an MPS file. The software incorporates modules that can be used separately from the linear programming solver, including a pre-solve routine and data structure definitions. 2 - Methods: The Mehrota predictor-corrector method is a primal-dual interior-point method for linear programming. The starting point is determined from a modified least squares heuristic. Linear systems of equations are solved at each interior-point iteration via a sparse Cholesky algorithm native to the code. A pre-solver is incorporated in the code to eliminate inefficiencies in the user's formulation of the problem. 3 - Restriction on the complexity of the problem: There are no size limitations built into the program. The size of problem solved is limited by RAM and swap space on the user's computer

A program package for solving linear optimization problems

International Nuclear Information System (INIS)

Horikami, Kunihiko; Fujimura, Toichiro; Nakahara, Yasuaki

1980-09-01

Seven computer programs for the solution of linear, integer and quadratic programming (four programs for linear programming, one for integer programming and two for quadratic programming) have been prepared and tested on FACOM M200 computer, and auxiliary programs have been written to make it easy to use the optimization program package. The characteristics of each program are explained and the detailed input/output descriptions are given in order to let users know how to use them. (author)

Numerical methods for the design of large-scale nonlinear discrete ill-posed inverse problems

International Nuclear Information System (INIS)

Haber, E; Horesh, L; Tenorio, L

2010-01-01

Design of experiments for discrete ill-posed problems is a relatively new area of research. While there has been some limited work concerning the linear case, little has been done to study design criteria and numerical methods for ill-posed nonlinear problems. We present an algorithmic framework for nonlinear experimental design with an efficient numerical implementation. The data are modeled as indirect, noisy observations of the model collected via a set of plausible experiments. An inversion estimate based on these data is obtained by a weighted Tikhonov regularization whose weights control the contribution of the different experiments to the data misfit term. These weights are selected by minimization of an empirical estimate of the Bayes risk that is penalized to promote sparsity. This formulation entails a bilevel optimization problem that is solved using a simple descent method. We demonstrate the viability of our design with a problem in electromagnetic imaging based on direct current resistivity and magnetotelluric data

Assessment of Two Analytical Methods in Solving the Linear and Nonlinear Elastic Beam Deformation Problems

DEFF Research Database (Denmark)

Barari, Amin; Ganjavi, B.; Jeloudar, M. Ghanbari

2010-01-01

and fluid mechanics. Design/methodology/approach – Two new but powerful analytical methods, namely, He's VIM and HPM, are introduced to solve some boundary value problems in structural engineering and fluid mechanics. Findings – Analytical solutions often fit under classical perturbation methods. However......, as with other analytical techniques, certain limitations restrict the wide application of perturbation methods, most important of which is the dependence of these methods on the existence of a small parameter in the equation. Disappointingly, the majority of nonlinear problems have no small parameter at all......Purpose – In the last two decades with the rapid development of nonlinear science, there has appeared ever-increasing interest of scientists and engineers in the analytical techniques for nonlinear problems. This paper considers linear and nonlinear systems that are not only regarded as general...

Linear differential equations to solve nonlinear mechanical problems: A novel approach

OpenAIRE

Nair, C. Radhakrishnan

2004-01-01

Often a non-linear mechanical problem is formulated as a non-linear differential equation. A new method is introduced to find out new solutions of non-linear differential equations if one of the solutions of a given non-linear differential equation is known. Using the known solution of the non-linear differential equation, linear differential equations are set up. The solutions of these linear differential equations are found using standard techniques. Then the solutions of the linear differe...

Computing with linear equations and matrices

International Nuclear Information System (INIS)

Churchhouse, R.F.

1983-01-01

Systems of linear equations and matrices arise in many disciplines. The equations may accurately represent conditions satisfied by a system or, more likely, provide an approximation to a more complex system of non-linear or differential equations. The system may involve a few or many thousand unknowns and each individual equation may involve few or many of them. Over the past 50 years a vast literature on methods for solving systems of linear equations and the associated problems of finding the inverse or eigenvalues of a matrix has been produced. These lectures cover those methods which have been found to be most useful for dealing with such types of problem. References are given where appropriate and attention is drawn to the possibility of improved methods for use on vector and parallel processors. (orig.)

An ill-conditioning conformal radiotherapy analysis based on singular values decomposition

International Nuclear Information System (INIS)

Lefkopoulos, D.; Grandjean, P.; Bendada, S.; Dominique, C.; Platoni, K.; Schlienger, M.

1995-01-01

Clinical experience in stereotactic radiotherapy of irregular complex lesions had shown that optimization algorithms were necessary to improve the dose distribution. We have developed a general optimization procedure which can be applied to different conformal irradiation techniques. In this presentation this procedure is tested on the stereotactic radiotherapy modality of complex cerebral lesions treated with multi-isocentric technique based on the 'associated targets methodology'. In this inverse procedure we use the singular value decomposition (SVD) analysis which proposes several optimal solutions for the narrow beams weights of each isocentre. The SVD analysis quantifies the ill-conditioning of the dosimetric calculation of the stereotactic irradiation, using the condition number which is the ratio of the bigger to smaller singular values. Our dose distribution optimization approach consists on the study of the irradiation parameters influence on the stereotactic radiotherapy inverse problem. The adjustment of the different irradiation parameters into the 'SVD optimizer' procedure is realized taking into account the ratio of the quality reconstruction to the time calculation. It will permit a more efficient use of the 'SVD optimizer' in clinical applications for real 3D lesions. The evaluation criteria for the choice of satisfactory solutions are based on the dose-volume histograms and clinical considerations. We will present the efficiency of ''SVD optimizer'' to analyze and predict the ill-conditioning in stereotactic radiotherapy and to recognize the topography of the different beams in order to create optimal reconstructed weighting vector. The planification of stereotactic treatments using the ''SVD optimizer'' is examined for mono-isocentrically and complex dual-isocentrically treated lesions. The application of the SVD optimization technique provides conformal dose distribution for complex intracranial lesions. It is a general optimization procedure

Scaling Sparse Matrices for Optimization Algorithms

OpenAIRE

Gajulapalli Ravindra S; Lasdon Leon S

2006-01-01

To iteratively solve large scale optimization problems in various contexts like planning, operations, design etc., we need to generate descent directions that are based on linear system solutions. Irrespective of the optimization algorithm or the solution method employed for the linear systems, ill conditioning introduced by problem characteristics or the algorithm or both need to be addressed. In [GL01] we used an intuitive heuristic approach in scaling linear systems that improved performan...

Two-dimensional differential transform method for solving linear and non-linear Schroedinger equations

International Nuclear Information System (INIS)

Ravi Kanth, A.S.V.; Aruna, K.

2009-01-01

In this paper, we propose a reliable algorithm to develop exact and approximate solutions for the linear and nonlinear Schroedinger equations. The approach rest mainly on two-dimensional differential transform method which is one of the approximate methods. The method can easily be applied to many linear and nonlinear problems and is capable of reducing the size of computational work. Exact solutions can also be achieved by the known forms of the series solutions. Several illustrative examples are given to demonstrate the effectiveness of the present method.

Finite-Time Robust H∞ Control for Uncertain Linear Continuous-Time Singular Systems with Exogenous Disturbances

Directory of Open Access Journals (Sweden)

Songlin Wo

2018-01-01

Full Text Available Singular systems arise in a great deal of domains of engineering and can be used to solve problems which are more difficult and more extensive than regular systems to solve. Therefore, in this paper, the definition of finite-time robust H∞ control for uncertain linear continuous-time singular systems is presented. The problem we address is to design a robust state feedback controller which can deal with the singular system with time-varying norm-bounded exogenous disturbance, such that the singular system is finite-time robust bounded (FTRB with disturbance attenuation γ. Sufficient conditions for the existence of solutions to this problem are obtained in terms of linear matrix equalities (LMIs. When these LMIs are feasible, the desired robust controller is given. A detailed solving method is proposed for the restricted linear matrix inequalities. Finally, examples are given to show the validity of the methodology.

Essential linear algebra with applications a problem-solving approach

CERN Document Server

Andreescu, Titu

2014-01-01

This textbook provides a rigorous introduction to linear algebra in addition to material suitable for a more advanced course while emphasizing the subject’s interactions with other topics in mathematics such as calculus and geometry. A problem-based approach is used to develop the theoretical foundations of vector spaces, linear equations, matrix algebra, eigenvectors, and orthogonality. Key features include: • a thorough presentation of the main results in linear algebra along with numerous examples to illustrate the theory;  • over 500 problems (half with complete solutions) carefully selected for their elegance and theoretical significance; • an interleaved discussion of geometry and linear algebra, giving readers a solid understanding of both topics and the relationship between them.   Numerous exercises and well-chosen examples make this text suitable for advanced courses at the junior or senior levels. It can also serve as a source of supplementary problems for a sophomore-level course.    ...

A linear programming manual

Science.gov (United States)

Tuey, R. C.

1972-01-01

Computer solutions of linear programming problems are outlined. Information covers vector spaces, convex sets, and matrix algebra elements for solving simultaneous linear equations. Dual problems, reduced cost analysis, ranges, and error analysis are illustrated.

Some Applications of Algebraic System Solving

Science.gov (United States)

Roanes-Lozano, Eugenio

2011-01-01

Technology and, in particular, computer algebra systems, allows us to change both the way we teach mathematics and the mathematical curriculum. Curiously enough, unlike what happens with linear system solving, algebraic system solving is not widely known. The aim of this paper is to show that, although the theory lying behind the "exact…

Solving applied mathematical problems with Matlab

CERN Document Server

Xue, Dingyu

2008-01-01

Computer Mathematics Language-An Overview. Fundamentals of MATLAB Programming. Calculus Problems. MATLAB Computations of Linear Algebra Problems. Integral Transforms and Complex Variable Functions. Solutions to Nonlinear Equations and Optimization Problems. MATLAB Solutions to Differential Equation Problems. Solving Interpolations and Approximations Problems. Solving Probability and Mathematical Statistics Problems. Nontraditional Solution Methods for Mathematical Problems.

The Effects of Case Libraries in Supporting Collaborative Problem-Solving in an Online Learning Environment

Science.gov (United States)

Tawfik, Andrew A.; Sánchez, Lenny; Saparova, Dinara

2014-01-01

Various domains require practitioners to encounter and resolve ill-structured problems using collaborative problem-solving. As such, problem-solving is an essential skill that educators must emphasize to prepare learners for practice. One potential way to support problem-solving is through further investigation of instructional design methods that…

Comparison of open-source linear programming solvers.

Energy Technology Data Exchange (ETDEWEB)

Gearhart, Jared Lee; Adair, Kristin Lynn; Durfee, Justin David.; Jones, Katherine A.; Martin, Nathaniel; Detry, Richard Joseph

2013-10-01

When developing linear programming models, issues such as budget limitations, customer requirements, or licensing may preclude the use of commercial linear programming solvers. In such cases, one option is to use an open-source linear programming solver. A survey of linear programming tools was conducted to identify potential open-source solvers. From this survey, four open-source solvers were tested using a collection of linear programming test problems and the results were compared to IBM ILOG CPLEX Optimizer (CPLEX) [1], an industry standard. The solvers considered were: COIN-OR Linear Programming (CLP) [2], [3], GNU Linear Programming Kit (GLPK) [4], lp_solve [5] and Modular In-core Nonlinear Optimization System (MINOS) [6]. As no open-source solver outperforms CPLEX, this study demonstrates the power of commercial linear programming software. CLP was found to be the top performing open-source solver considered in terms of capability and speed. GLPK also performed well but cannot match the speed of CLP or CPLEX. lp_solve and MINOS were considerably slower and encountered issues when solving several test problems.

Fuzzy linear programming approach for solving transportation

Indian Academy of Sciences (India)

Transportation problem (TP) is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy demands at ...

A METHOD FOR SOLVING LINEAR PROGRAMMING PROBLEMS WITH FUZZY PARAMETERS BASED ON MULTIOBJECTIVE LINEAR PROGRAMMING TECHNIQUE

OpenAIRE

M. ZANGIABADI; H. R. MALEKI

2007-01-01

In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...

High-order quantum algorithm for solving linear differential equations

International Nuclear Information System (INIS)

Berry, Dominic W

2014-01-01

Linear differential equations are ubiquitous in science and engineering. Quantum computers can simulate quantum systems, which are described by a restricted type of linear differential equations. Here we extend quantum simulation algorithms to general inhomogeneous sparse linear differential equations, which describe many classical physical systems. We examine the use of high-order methods (where the error over a time step is a high power of the size of the time step) to improve the efficiency. These provide scaling close to Δt 2 in the evolution time Δt. As with other algorithms of this type, the solution is encoded in amplitudes of the quantum state, and it is possible to extract global features of the solution. (paper)

Mental illness from the perspective of theoretical neuroscience.

Science.gov (United States)

Thagard, Paul

2008-01-01

Theoretical neuroscience, which characterizes neural mechanisms using mathematical and computational models, is highly relevant to central problems in the philosophy of psychiatry. These models can help to solve the explanation problem of causally connecting neural processes with the behaviors and experiences found in mental illnesses. Such explanations will also be useful for generating better classifications and treatments of psychiatric disorders. The result should help to eliminate concerns that mental illnesses such as depression and schizophrenia are not objectively real. A philosophical approach to mental illness based on neuroscience need not neglect the inherently social and historical nature of mental phenomena.

Yager’s ranking method for solving the trapezoidal fuzzy number linear programming

Science.gov (United States)

Karyati; Wutsqa, D. U.; Insani, N.

2018-03-01

In the previous research, the authors have studied the fuzzy simplex method for trapezoidal fuzzy number linear programming based on the Maleki’s ranking function. We have found some theories related to the term conditions for the optimum solution of fuzzy simplex method, the fuzzy Big-M method, the fuzzy two-phase method, and the sensitivity analysis. In this research, we study about the fuzzy simplex method based on the other ranking function. It is called Yager's ranking function. In this case, we investigate the optimum term conditions. Based on the result of research, it is found that Yager’s ranking function is not like Maleki’s ranking function. Using the Yager’s function, the simplex method cannot work as well as when using the Maleki’s function. By using the Yager’s function, the value of the subtraction of two equal fuzzy numbers is not equal to zero. This condition makes the optimum table of the fuzzy simplex table is undetected. As a result, the simplified fuzzy simplex table becomes stopped and does not reach the optimum solution.

Diomres (k,m): An efficient method based on Krylov subspaces to solve big, dispersed, unsymmetrical linear systems

Energy Technology Data Exchange (ETDEWEB)

de la Torre Vega, E. [Instituto de Investigaciones Electricas, Cuernavaca (Mexico); Cesar Suarez Arriaga, M. [Universidad Michoacana SNH, Michoacan (Mexico)

1995-03-01

In geothermal simulation processes, MULKOM uses Integrated Finite Differences to solve the corresponding partial differential equations. This method requires to resolve efficiently big linear dispersed systems of non-symmetrical nature on each temporal iteration. The order of the system is usually greater than one thousand its solution could represent around 80% of CPU total calculation time. If the elapsed time solving this class of linear systems is reduced, the duration of numerical simulation decreases notably. When the matrix is big (N{ge}500) and with holes, it is inefficient to handle all the system`s elements, because it is perfectly figured out by its elements distinct of zero, quantity greatly minor than N{sup 2}. In this area, iteration methods introduce advantages with respect to gaussian elimination methods, because these last replenish matrices not having any special distribution of their non-zero elements and because they do not make use of the available solution estimations. The iterating methods of the Conjugated Gradient family, based on the subspaces of Krylov, possess the advantage of improving the convergence speed by means of preconditioning techniques. The creation of DIOMRES(k,m) method guarantees the continuous descent of the residual norm, without incurring in division by zero. This technique converges at most in N iterations if the system`s matrix is symmetrical, it does not employ too much memory to converge and updates immediately the approximation by using incomplete orthogonalization and adequate restarting. A preconditioned version of DIOMRES was applied to problems related to unsymmetrical systems with 1000 unknowns and less than five terms per equation. We found that this technique could reduce notably the time needful to find the solution without requiring memory increment. The coupling of this method to geothermal versions of MULKOM is in process.

Inverse and Ill-posed Problems Theory and Applications

CERN Document Server

Kabanikhin, S I

2011-01-01

The text demonstrates the methods for proving the existence (if et all) and finding of inverse and ill-posed problems solutions in linear algebra, integral and operator equations, integral geometry, spectral inverse problems, and inverse scattering problems. It is given comprehensive background material for linear ill-posed problems and for coefficient inverse problems for hyperbolic, parabolic, and elliptic equations. A lot of examples for inverse problems from physics, geophysics, biology, medicine, and other areas of application of mathematics are included.

Fast Solvers for Dense Linear Systems

Energy Technology Data Exchange (ETDEWEB)

Kauers, Manuel [Research Institute for Symbolic Computation (RISC), Altenbergerstrasse 69, A4040 Linz (Austria)

2008-10-15

It appears that large scale calculations in particle physics often require to solve systems of linear equations with rational number coefficients exactly. If classical Gaussian elimination is applied to a dense system, the time needed to solve such a system grows exponentially in the size of the system. In this tutorial paper, we present a standard technique from computer algebra that avoids this exponential growth: homomorphic images. Using this technique, big dense linear systems can be solved in a much more reasonable time than using Gaussian elimination over the rationals.

Investigating Students' Success in Solving and Attitudes towards Context-Rich Open-Ended Problems in Chemistry

Science.gov (United States)

Overton, Tina L.; Potter, Nicholas M.

2011-01-01

Much research has been carried out on how students solve algorithmic and structured problems in chemistry. This study is concerned with how students solve open-ended, ill-defined problems in chemistry. Over 200 undergraduate chemistry students solved a number of open-ended problem in groups and individually. The three cognitive variables of…

Acute Care Use for Ambulatory Care-Sensitive Conditions in High-Cost Users of Medical Care with Mental Illness and Addictions.

Science.gov (United States)

Hensel, Jennifer M; Taylor, Valerie H; Fung, Kinwah; Yang, Rebecca; Vigod, Simone N

2018-01-01

The role of mental illness and addiction in acute care use for chronic medical conditions that are sensitive to ambulatory care management requires focussed attention. This study examines how mental illness or addiction affects risk for repeat hospitalization and/or emergency department use for ambulatory care-sensitive conditions (ACSCs) among high-cost users of medical care. A retrospective, population-based cohort study using data from Ontario, Canada. Among the top 10% of medical care users ranked by cost, we determined rates of any and repeat care use (hospitalizations and emergency department [ED] visits) between April 1, 2011, and March 31, 2012, for 14 consensus established ACSCs and compared them between those with and without diagnosed mental illness or addiction during the 2 years prior. Risk ratios were adjusted (aRR) for age, sex, residence, and income quintile. Among 314,936 high-cost users, 35.9% had a mental illness or addiction. Compared to those without, individuals with mental illness or addiction were more likely to have an ED visit or hospitalization for any ACSC (22.8% vs. 19.6%; aRR, 1.21; 95% confidence interval [CI], 1.20-1.23). They were also more likely to have repeat ED visits or hospitalizations for the same ACSC (6.2% vs. 4.4% of those without; aRR, 1.48; 95% CI, 1.44-1.53). These associations were stronger in stratifications by mental illness diagnostic subgroup, particularly for those with a major mental illness. The presence of mental illness and addiction among high-cost users of medical services may represent an unmet need for quality ambulatory and primary care.

Effective quadrature formula in solving linear integro-differential equations of order two

Science.gov (United States)

Eshkuvatov, Z. K.; Kammuji, M.; Long, N. M. A. Nik; Yunus, Arif A. M.

2017-08-01

In this note, we solve general form of Fredholm-Volterra integro-differential equations (IDEs) of order 2 with boundary condition approximately and show that proposed method is effective and reliable. Initially, IDEs is reduced into integral equation of the third kind by using standard integration techniques and identity between multiple and single integrals then truncated Legendre series are used to estimate the unknown function. For the kernel integrals, we have applied Gauss-Legendre quadrature formula and collocation points are chosen as the roots of the Legendre polynomials. Finally, reduce the integral equations of the third kind into the system of algebraic equations and Gaussian elimination method is applied to get approximate solutions. Numerical examples and comparisons with other methods reveal that the proposed method is very effective and dominated others in many cases. General theory of existence of the solution is also discussed.

Low-sensitivity H ∞ filter design for linear delta operator systems with sampling time jitter

Science.gov (United States)

Guo, Xiang-Gui; Yang, Guang-Hong

2012-04-01

This article is concerned with the problem of designing H ∞ filters for a class of linear discrete-time systems with low-sensitivity to sampling time jitter via delta operator approach. Delta-domain model is used to avoid the inherent numerical ill-condition resulting from the use of the standard shift-domain model at high sampling rates. Based on projection lemma in combination with the descriptor system approach often used to solve problems related to delay, a novel bounded real lemma with three slack variables for delta operator systems is presented. A sensitivity approach based on this novel lemma is proposed to mitigate the effects of sampling time jitter on system performance. Then, the problem of designing a low-sensitivity filter can be reduced to a convex optimisation problem. An important consideration in the design of correlation filters is the optimal trade-off between the standard H ∞ criterion and the sensitivity of the transfer function with respect to sampling time jitter. Finally, a numerical example demonstrating the validity of the proposed design method is given.

Peer-Led Self-Management of General Medical Conditions for Patients With Serious Mental Illnesses: A Randomized Trial.

Science.gov (United States)

Druss, Benjamin G; Singh, Manasvini; von Esenwein, Silke A; Glick, Gretl E; Tapscott, Stephanie; Tucker, Sherry Jenkins; Lally, Cathy A; Sterling, Evelina W

2018-02-01

Individuals with serious mental illnesses have high rates of general medical comorbidity and challenges in managing these conditions. A growing workforce of certified peer specialists is available to help these individuals more effectively manage their health and health care. However, few studies have examined the effectiveness of peer-led programs for self-management of general medical conditions for this population. This randomized study enrolled 400 participants with a serious mental illness and one or more chronic general medical conditions across three community mental health clinics. Participants were randomly assigned to the Health and Recovery Peer (HARP) program, a self-management program for general medical conditions led by certified peer specialists (N=198), or to usual care (N=202). Assessments were conducted at baseline and three and six months. At six months, participants in the intervention group demonstrated a significant differential improvement in the primary study outcome, health-related quality of life. Specifically, compared with the usual care group, intervention participants had greater improvement in the Short-Form Health Survey physical component summary (an increase of 2.7 versus 1.4 points, p=.046) and mental component summary (4.6 versus 2.5 points, p=.039). Significantly greater six-month improvements in mental health recovery were seen for the intervention group (p=.02), but no other between-group differences in secondary outcome measures were significant. The HARP program was associated with improved physical health- and mental health-related quality of life among individuals with serious mental illness and comorbid general medical conditions, suggesting the potential benefits of more widespread dissemination of peer-led disease self-management in this population.

Diagonalization of Bounded Linear Operators on Separable Quaternionic Hilbert Space

International Nuclear Information System (INIS)

Feng Youling; Cao, Yang; Wang Haijun

2012-01-01

By using the representation of its complex-conjugate pairs, we have investigated the diagonalization of a bounded linear operator on separable infinite-dimensional right quaternionic Hilbert space. The sufficient condition for diagonalizability of quaternionic operators is derived. The result is applied to anti-Hermitian operators, which is essential for solving Schroedinger equation in quaternionic quantum mechanics.

Synthesis of models for order-sorted first-order theories using linear algebra and constraint solving

Directory of Open Access Journals (Sweden)

Salvador Lucas

2015-12-01

Full Text Available Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In this setting, Order-Sorted First-Order Logic provides a powerful framework to represent declarative programs. It also provides a target logic to obtain models for other logics via transformations. We investigate the automatic generation of numerical models for order-sorted first-order logics and its use in program analysis, in particular in termination analysis of declarative programs. We use convex domains to give domains to the different sorts of an order-sorted signature; we interpret the ranked symbols of sorted signatures by means of appropriately adapted convex matrix interpretations. Such numerical interpretations permit the use of existing algorithms and tools from linear algebra and arithmetic constraint solving to synthesize the models.

A Newton method for solving continuous multiple material minimum compliance problems

DEFF Research Database (Denmark)

Stolpe, M; Stegmann, Jan

method, one or two linear saddle point systems are solved. These systems involve the Hessian of the objective function, which is both expensive to compute and completely dense. Therefore, the linear algebra is arranged such that the Hessian is not explicitly formed. The main concern is to solve...

A Newton method for solving continuous multiple material minimum compliance problems

DEFF Research Database (Denmark)

Stolpe, Mathias; Stegmann, Jan

2007-01-01

method, one or two linear saddle point systems are solved. These systems involve the Hessian of the objective function, which is both expensive to compute and completely dense. Therefore, the linear algebra is arranged such that the Hessian is not explicitly formed. The main concern is to solve...

Linear parameter varying control of wind turbines covering both partial load and full load conditions

DEFF Research Database (Denmark)

Østergaard, Kasper Zinck; Stoustrup, Jakob; Brath, Per

2009-01-01

operations tend to be ill-conditioned. The paper proposes a controller construction algorithm together with various remedies for improving the numerical conditioning the algorithm.The proposed algorithm is applied to the design of a LPV controller for wind turbines, and a comparison is made with a controller...... designed using classical techniques to conclude that an improvement in performance is obtained for the entire operating envelope....

Simon on problem solving

DEFF Research Database (Denmark)

Foss, Kirsten; Foss, Nicolai Juul

2006-01-01

as a general approach to problem solving. We apply these Simonian ideas to organisational issues, specifically new organisational forms. Specifically, Simonian ideas allow us to develop a morphology of new organisational forms and to point to some design problems that characterise these forms.......Two of Herbert Simon's best-known papers are 'The Architecture of Complexity' and 'The Structure of Ill-Structured Problems.' We discuss the neglected links between these two papers, highlighting the role of decomposition in the context of problems on which constraints have been imposed...

Social integration, socioeconomic conditions and type of ill health preceding disability pension in young women: a Swedish population-based study.

Science.gov (United States)

Gustafsson, Klas; Aronsson, Gunnar; Marklund, Staffan; Wikman, Anders; Hagman, Maud; Floderus, Birgitta

2014-02-01

Disability pension has increased in recent decades and is seen as a public health and socioeconomic problem in Western Europe. In the Nordic countries, the increase has been particularly steep among young women. The aim was to analyze the influence of low social integration, socioeconomic risk conditions and different measures of self-reported ill health on the risk of receiving disability pension in young women. The study comprised all Swedish women born in 1960 to 1979, who had been interviewed in any of the annual Swedish Surveys of Living Conditions (1990-2002). The assumed predictors were related to disability pension by Cox proportional hazard regression. The mean number of years of follow-up for the 10,936 women was 7 years (SD 3.8), and the study base was restricted to the ages 16 to 43 years of age. An increased risk of receiving a disability pension was found among lone women, those who had sparse contacts with others, job-seeking women, homemakers, as well as women with low education, and poor private financial situations. A tenfold increase in the risk of receiving a disability pension was found among women reporting a long-standing illness and poor self-rated health, compared to women without a long-standing illness and good self-rated health. Psychiatric diagnoses and symptoms/unspecified illness were the strongest predictors of disability pension, particularly before 30 years of age. The study suggests that weak social relations and weak connections to working life contribute to increase the risk of disability pension in young women, also after control for socioeconomic conditions and self-reported ill health. Self-rated health was the strongest predictor, followed by long-standing illness and not having a job (job seekers and homemakers).

ITMETH, Iterative Routines for Linear System

International Nuclear Information System (INIS)

Greenbaum, A.

1989-01-01

1 - Description of program or function: ITMETH is a collection of iterative routines for solving large, sparse linear systems. 2 - Method of solution: ITMETH solves general linear systems of the form AX=B using a variety of methods: Jacobi iteration; Gauss-Seidel iteration; incomplete LU decomposition or matrix splitting with iterative refinement; diagonal scaling, matrix splitting, or incomplete LU decomposition with the conjugate gradient method for the problem AA'Y=B, X=A'Y; bi-conjugate gradient method with diagonal scaling, matrix splitting, or incomplete LU decomposition; and ortho-min method with diagonal scaling, matrix splitting, or incomplete LU decomposition. ITMETH also solves symmetric positive definite linear systems AX=B using the conjugate gradient method with diagonal scaling or matrix splitting, or the incomplete Cholesky conjugate gradient method

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

Factors affecting the social problem-solving ability of baccalaureate nursing students.

Science.gov (United States)

Lau, Ying

2014-01-01

The hospital environment is characterized by time pressure, uncertain information, conflicting goals, high stakes, stress, and dynamic conditions. These demands mean there is a need for nurses with social problem-solving skills. This study set out to (1) investigate the social problem-solving ability of Chinese baccalaureate nursing students in Macao and (2) identify the association between communication skill, clinical interaction, interpersonal dysfunction, and social problem-solving ability. All nursing students were recruited in one public institute through the census method. The research design was exploratory, cross-sectional, and quantitative. The study used the Chinese version of the Social Problem Solving Inventory short form (C-SPSI-R), Communication Ability Scale (CAS), Clinical Interactive Scale (CIS), and Interpersonal Dysfunction Checklist (IDC). Macao nursing students were more likely to use the two constructive or adaptive dimensions rather than the three dysfunctional dimensions of the C-SPSI-R to solve their problems. Multiple linear regression analysis revealed that communication ability (ß=.305, pproblem-solving after controlling for covariates. Macao has had no problem-solving training in its educational curriculum; an effective problem-solving training should be implemented as part of the curriculum. With so many changes in healthcare today, nurses must be good social problem-solvers in order to deliver holistic care. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Matlab Radial Basis Function Toolbox

Directory of Open Access Journals (Sweden)

Scott A. Sarra

2017-03-01

Full Text Available Radial Basis Function (RBF methods are important tools for scattered data interpolation and for the solution of Partial Differential Equations in complexly shaped domains. The most straight forward approach used to evaluate the methods involves solving a linear system which is typically poorly conditioned. The Matlab Radial Basis Function toolbox features a regularization method for the ill-conditioned system, extended precision floating point arithmetic, and symmetry exploitation for the purpose of reducing flop counts of the associated numerical linear algebra algorithms.

Vectorization of linear discrete filtering algorithms

Science.gov (United States)

Schiess, J. R.

1977-01-01

Linear filters, including the conventional Kalman filter and versions of square root filters devised by Potter and Carlson, are studied for potential application on streaming computers. The square root filters are known to maintain a positive definite covariance matrix in cases in which the Kalman filter diverges due to ill-conditioning of the matrix. Vectorization of the filters is discussed, and comparisons are made of the number of operations and storage locations required by each filter. The Carlson filter is shown to be the most efficient of the filters on the Control Data STAR-100 computer.

Linearization: Geometric, Complex, and Conditional

Directory of Open Access Journals (Sweden)

Asghar Qadir

2012-01-01

Full Text Available Lie symmetry analysis provides a systematic method of obtaining exact solutions of nonlinear (systems of differential equations, whether partial or ordinary. Of special interest is the procedure that Lie developed to transform scalar nonlinear second-order ordinary differential equations to linear form. Not much work was done in this direction to start with, but recently there have been various developments. Here, first the original work of Lie (and the early developments on it, and then more recent developments based on geometry and complex analysis, apart from Lie’s own method of algebra (namely, Lie group theory, are reviewed. It is relevant to mention that much of the work is not linearization but uses the base of linearization.

Simulation of dynamics of a permanent magnet linear actuator

DEFF Research Database (Denmark)

Yatchev, Ivan; Ritchie, Ewen

2010-01-01

Comparison of two approaches for the simulation of the dynamic behaviour of a permanent magnet linear actuator is presented. These are full coupled model, where the electromagnetic field, electric circuit and mechanical motion problems are solved simultaneously, and decoupled model, where first...... flexibility when the actuator response is required to be estimated for different external conditions, e.g. external circuit parameters or mechanical loads....

A Stream Function Theory Based Calculation of Wave Kinematics for Very Steep Waves Using a Novel Non-linear Stretching Technique

DEFF Research Database (Denmark)

Stroescu, Ionut Emanuel; Sørensen, Lasse; Frigaard, Peter Bak

2016-01-01

A non-linear stretching method was implemented for stream function theory to solve wave kinematics for physical conditions close to breaking waves in shallow waters, with wave heights limited by the water depth. The non-linear stretching method proves itself robust, efficient and fast, showing good...

Mixed H∞ and passive control for linear switched systems via hybrid control approach

Science.gov (United States)

Zheng, Qunxian; Ling, Youzhu; Wei, Lisheng; Zhang, Hongbin

2018-03-01

This paper investigates the mixed H∞ and passive control problem for linear switched systems based on a hybrid control strategy. To solve this problem, first, a new performance index is proposed. This performance index can be viewed as the mixed weighted H∞ and passivity performance. Then, the hybrid controllers are used to stabilise the switched systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. The design of state updating controllers not only depends on the pre-switching subsystem and the post-switching subsystem, but also depends on the measurable output signal. The hybrid controllers proposed in this paper can include some existing ones as special cases. Combine the multiple Lyapunov functions approach with the average dwell time technique, new sufficient conditions are obtained. Under the new conditions, the closed-loop linear switched systems are globally uniformly asymptotically stable with a mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example and a practical example are given.

RECTC/RECTCF, 2. Order Elliptical Partial Differential Equation, Arbitrary Boundary Conditions

International Nuclear Information System (INIS)

Hackbusch, W.

1983-01-01

1 - Description of problem or function: A general linear elliptical second order partial differential equation on a rectangle with arbitrary boundary conditions is solved. 2 - Method of solution: Multi-grid iteration

Linear stochastic differential equations with anticipating initial conditions

DEFF Research Database (Denmark)

Khalifa, Narjess; Kuo, Hui-Hsiung; Ouerdiane, Habib

In this paper we use the new stochastic integral introduced by Ayed and Kuo (2008) and the results obtained by Kuo et al. (2012b) to find a solution to a drift-free linear stochastic differential equation with anticipating initial condition. Our solution is based on well-known results from...... classical Itô theory and anticipative Itô formula results from Kue et al. (2012b). We also show that the solution obtained by our method is consistent with the solution obtained by the methods of Malliavin calculus, e.g. Buckdahn and Nualart (1994)....

Modular Regularization Algorithms

DEFF Research Database (Denmark)

Jacobsen, Michael

2004-01-01

The class of linear ill-posed problems is introduced along with a range of standard numerical tools and basic concepts from linear algebra, statistics and optimization. Known algorithms for solving linear inverse ill-posed problems are analyzed to determine how they can be decomposed into indepen...

Finite element method with quadratic quadrilateral unit for solving two dimensional incompressible N-S equation

International Nuclear Information System (INIS)

Tao Ganqiang; Yu Qing; Xiao Xiao

2011-01-01

Viscous and incompressible fluid flow is important for numerous engineering mechanics problems. Because of high non linear and incompressibility for Navier-Stokes equation, it is very difficult to solve Navier-Stokes equation by numerical method. According to its characters of Navier-Stokes equation, quartic derivation controlling equation of the two dimensional incompressible Navier-Stokes equation is set up firstly. The method solves the problem for dealing with vorticity boundary and automatically meets incompressibility condition. Then Finite Element equation for Navier-Stokes equation is proposed by using quadratic quadrilateral unit with 8 nodes in which the unit function is quadratic and non linear.-Based on it, the Finite Element program of quadratic quadrilateral unit with 8 nodes is developed. Lastly, numerical experiment proves the accuracy and dependability of the method and also shows the method has good application prospect in computational fluid mechanics. (authors)

Lack of anomalous diffusion in linear translationally-invariant systems determined by only one initial condition

International Nuclear Information System (INIS)

Khorrami, Mohammad; Shariati, Ahmad; Aghamohammadi, Amir; Fatollahi, Amir H.

2012-01-01

It is shown that as far as the linear diffusion equation meets both time- and space-translational invariance, the time dependence of a moment of degree α is a polynomial of degree at most equal to α, while all connected moments are at most linear functions of time. As a special case, the variance is an at most linear function of time. -- Highlights: ► The sufficient conditions for having the non-anomalous diffusion are given. ► Conditions are linearity, space-time translation invariance, solution uniqueness. ► Some versions of the fractional derivatives lack the translational invariance. ► It is shown the encoded inhomogeneity in derivatives causes anomalous behavior.

Lack of anomalous diffusion in linear translationally-invariant systems determined by only one initial condition

Energy Technology Data Exchange (ETDEWEB)

Khorrami, Mohammad, E-mail: mamwad@mailaps.org [Department of Physics, Alzahra University, Tehran 19938-93973 (Iran, Islamic Republic of); Shariati, Ahmad, E-mail: shariati@mailaps.org [Department of Physics, Alzahra University, Tehran 19938-93973 (Iran, Islamic Republic of); Aghamohammadi, Amir, E-mail: mohamadi@alzahra.ac.ir [Department of Physics, Alzahra University, Tehran 19938-93973 (Iran, Islamic Republic of); Fatollahi, Amir H., E-mail: ahfatol@gmail.com [Department of Physics, Alzahra University, Tehran 19938-93973 (Iran, Islamic Republic of)

2012-01-16

It is shown that as far as the linear diffusion equation meets both time- and space-translational invariance, the time dependence of a moment of degree α is a polynomial of degree at most equal to α, while all connected moments are at most linear functions of time. As a special case, the variance is an at most linear function of time. -- Highlights: ► The sufficient conditions for having the non-anomalous diffusion are given. ► Conditions are linearity, space-time translation invariance, solution uniqueness. ► Some versions of the fractional derivatives lack the translational invariance. ► It is shown the encoded inhomogeneity in derivatives causes anomalous behavior.

Exact solutions of linearized Schwinger endash Dyson equation of fermion self-energy

International Nuclear Information System (INIS)

Zhou, B.

1997-01-01

The Schwinger endash Dyson equation of fermion self-energy in the linearization approximation is solved exactly in a theory with gauge and effective four-fermion interactions. Different expressions for the independent solutions, which, respectively, submit to irregular and regular ultraviolet boundary condition are derived and expounded. copyright 1997 American Institute of Physics

Subjective Health Complaints in Individuals with Psoriasis and Psoriatic Arthritis: Associations with the Severity of the Skin Condition and Illness Perceptions - A Cross-Sectional Study.

Science.gov (United States)

Nordbø, Emma Charlott Andersson; Aamodt, Geir; Ihlebæk, Camilla Martha

2017-06-01

High comorbidity has been reported among persons with psoriasis and psoriatic arthritis (PsA), but the occurrence of subjective health complaints (SHCs) in these patient groups is poorly understood. The study aimed to describe the prevalence of SHCs among individuals with psoriasis and PsA in Norway, and investigate whether the severity of their skin condition and their illness perceptions were associated with the number and severity of health complaints. Participants were recruited through the Psoriasis and Eczema Association of Norway (PEF) (n = 942). The participants answered a self-administered questionnaire covering subjective health complaints, the severity of their skin condition, and their illness perceptions measured with the Brief Illness Perception Questionnaire (BIPQ-R). The prevalence and severity of SHCs were high. Participants with PsA reported more complaints and higher severity of complaints compared with participants with psoriasis. In both groups, the severity of the skin condition was associated with the number and severity of SHCs. Cognitive illness perceptions (consequences) and emotional illness perceptions (emotional affect) were associated with SHCs in participants with psoriasis, whereas only cognitive illness perceptions (consequences and identity) were associated with SHCs in participants with PsA. The high prevalence and severity of SHCs among individuals with psoriasis and PsA were associated with the severity of the skin condition and illness perceptions. Somatic and cognitive sensitizations are proposed as possible mechanisms. The findings suggest that holistic approaches are essential when managing these patient groups in health care institutions and clinical practice.

Methane combustion kinetic rate constants determination: an ill-posed inverse problem analysis

Directory of Open Access Journals (Sweden)

Bárbara D. L. Ferreira

2013-01-01

Full Text Available Methane combustion was studied by the Westbrook and Dryer model. This well-established simplified mechanism is very useful in combustion science, for computational effort can be notably reduced. In the inversion procedure to be studied, rate constants are obtained from [CO] concentration data. However, when inherent experimental errors in chemical concentrations are considered, an ill-conditioned inverse problem must be solved for which appropriate mathematical algorithms are needed. A recurrent neural network was chosen due to its numerical stability and robustness. The proposed methodology was compared against Simplex and Levenberg-Marquardt, the most used methods for optimization problems.

Linearly Ordered Attribute Grammar Scheduling Using SAT-Solving

NARCIS (Netherlands)

Bransen, Jeroen; van Binsbergen, L.Thomas; Claessen, Koen; Dijkstra, Atze

2015-01-01

Many computations over trees can be specified using attribute grammars. Compilers for attribute grammars need to find an evaluation order (or schedule) in order to generate efficient code. For the class of linearly ordered attribute grammars such a schedule can be found statically, but this problem

Slamming Simulations in a Conditional Wave

DEFF Research Database (Denmark)

Seng, Sopheak; Jensen, Jørgen Juncher

2012-01-01

A study of slamming events in conditional waves is presented in this paper. The ship is sailing in head sea and the motion is solved for under the assumption of rigid body motion constrained to two degree-of-freedom i.e. heave and pitch. Based on a time domain non-linear strip theory most probable...

MODLP program description: A program for solving linear optimal hydraulic control of groundwater contamination based on MODFLOW simulation. Version 1.0

International Nuclear Information System (INIS)

Ahlfeld, D.P.; Dougherty, D.E.

1994-11-01

MODLP is a computational tool that may help design capture zones for controlling the movement of contaminated groundwater. It creates and solves linear optimization programs that contain constraints on hydraulic head or head differences in a groundwater system. The groundwater domain is represented by USGS MODFLOW groundwater flow simulation model. This document describes the general structure of the computer program, MODLP, the types of constraints that may be imposed, detailed input instructions, interpretation of the output, and the interaction with the MODFLOW simulation kernel

Solving nonlinear nonstationary problem of heat-conductivity by finite element method

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Антон Янович Карвацький

2016-11-01

Full Text Available Methodology and effective solving algorithm of non-linear dynamic problems of thermal and electric conductivity with significant temperature dependence of thermal and physical properties are given on the basis of finite element method (FEM and Newton linearization method. Discrete equations system FEM was obtained with the use of Galerkin method, where the main function is the finite element form function. The methodology based on successive solving problems of thermal and electrical conductivity has been examined in the work in order to minimize the requirements for calculating resources (RAM. in particular. Having used Mathcad software original programming code was developed to solve the given problem. After investigation of the received results, comparative analyses of accurate solution data and results of numerical solutions, obtained with the use of Matlab programming products, was held. The geometry of one fourth part of the finite sized cylinder was used to test the given numerical model. The discretization of the calculation part was fulfilled using the open programming software for automated Gmsh nets with tetrahedral units, while ParaView, which is an open programming code as well, was used to visualize the calculation results. It was found out that the maximum value violation of potential and temperature determination doesn`t exceed 0,2-0,83% in the given work according to the problem conditions

Hyers-Ulam stability for second-order linear differential equations with boundary conditions

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Pasc Gavruta

2011-06-01

Full Text Available We prove the Hyers-Ulam stability of linear differential equations of second-order with boundary conditions or with initial conditions. That is, if y is an approximate solution of the differential equation $y''+ eta (x y = 0$ with $y(a = y(b =0$, then there exists an exact solution of the differential equation, near y.

Linear and non-linear calculations of the hose instability in the ion-focused regime

International Nuclear Information System (INIS)

Buchanan, H.L.

1982-01-01

A simple model is adopted to study the hose instability of an intense relativistic electron beam in a partially neutralized, low density ion channel (ion focused regime). Equations of motion for the beam and the channel are derived and linearized to obtain an approximate dispersion relation. The non-linear equations of motion are then solved numerically and the results compared to linearized data

Stability Analysis for Fractional-Order Linear Singular Delay Differential Systems

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Hai Zhang

2014-01-01

Full Text Available We investigate the delay-independently asymptotic stability of fractional-order linear singular delay differential systems. Based on the algebraic approach, the sufficient conditions are presented to ensure the asymptotic stability for any delay parameter. By applying the stability criteria, one can avoid solving the roots of transcendental equations. An example is also provided to illustrate the effectiveness and applicability of the theoretical results.

Support for decision making and problem solving in abnormal conditions in nuclear power plants

International Nuclear Information System (INIS)

Embrey, D.; Humphreys, P.

1985-01-01

Under abnormal plant condition effective decision support has to take into account the operator's or other decision maker's mental model of the plant, derived from operating experience. This will be different from the engineering model incorporated in Disturbance Analysis Systems. Recently developed approaches for gaining access to the structure of this mental model provided the basis for the development of an interactive computer system capable of representing and exploring expert knowledge concerning inferences about causal patterns, starting from the information available to the operator in the control room. This system has potential application as an interactive diagnostic aid in support of decision making and problem solving during abnormal conditions. (Auth.)

Non-linear imaging condition to image fractures as non-welded interfaces

NARCIS (Netherlands)

Minato, S.; Ghose, R.

2014-01-01

Hydraulic properties of a fractured reservoir are often controlled by large fractures. In order to seismically detect and characterize them, a high-resolution imaging method is necessary. We apply a non-linear imaging condition to image fractures, considered as non-welded interfaces. We derive the

The relationship between physical ill-health and mental ill-health in adults with intellectual disabilities.

Science.gov (United States)

Dunham, A; Kinnear, D; Allan, L; Smiley, E; Cooper, S-A

2018-05-01

People with intellectual disabilities face a much greater burden and earlier onset of physical and mental ill-health than the general adult population. Physical-mental comorbidity has been shown to result in poorer outcomes in the general population, but little is known about this relationship in adults with intellectual disabilities. To identify whether physical ill-health is associated with mental ill-health in adults with intellectual disabilities and whether the extent of physical multi-morbidity can predict the likelihood of mental ill-health. To identify any associations between types of physical ill-health and mental ill-health. A total of 1023 adults with intellectual disabilities underwent comprehensive health assessments. Binary logistic regressions were undertaken to establish any association between the independent variables: total number of physical health conditions, physical conditions by International Classification of Disease-10 chapter and specific physical health conditions; and the dependent variables: problem behaviours, mental disorders of any type. All regressions were adjusted for age, gender, level of intellectual disabilities, living arrangements, neighbourhood deprivation and Down syndrome. The extent of physical multi-morbidity was not associated with mental ill-health in adults with intellectual disabilities as only 0.8% of the sample had no physical conditions. Endocrine disease increased the risk of problem behaviours [odds ratio (OR): 1.22, 95% confidence interval (CI): 1.02-1.47], respiratory disease reduced the risk of problem behaviours (OR: 0.73, 95% CI: 0.54-0.99) and mental ill-health of any type (OR: 0.73, 95% CI: 0.58-0.92), and musculoskeletal disease reduced the risk of mental ill-health of any type (OR: 0.84, 95% CI: 0.73-0.98). Ischaemic heart disease increased the risk of problem behaviours approximately threefold (OR: 3.29, 95% CI: 1.02-10.60). The extent of physical multi-morbidity in the population with intellectual

The effect of subliminal evaluative conditioning of cognitive self-schema and illness schema on pain tolerance.

Science.gov (United States)

Meerman, Esther E; Brosschot, Jos F; van der Togt, Stefanie A M; Verkuil, Bart

2013-12-01

Cognitive models explaining medically unexplained complaints propose that activating illness-related memory causes increased complaints such as pain. However, our previous studies showed conflicting support for this theory. Illness-related memory is more likely to influence reporting of complaints when its activation is enmeshed with that of self-related memory. We, therefore, investigated whether inducing this association would cause a stronger decrease in pain tolerance. In addition, we examined whether SFA acted as a moderator of this effect. We used subliminal evaluative conditioning (SEC) to induce an association between activated self-related and illness-related memory. Seventy-six participants were randomly assigned to four combinations of two priming factors: (1) the self-referent word "I" versus the nonself-referent "X" to manipulate activated self-related memory and (2) health complaint (HC) words versus neutral words to manipulate activated illness-related memory. Pain tolerance was assessed using a cold pressor task (CPT). Participants primed with the self-referent "I" and HC words did not demonstrate the expected lower pain tolerance. However, SFA acted as a moderator of the main effect of the self-prime: priming with "I" resulted in increased pain tolerance in participants with low SFA. The current study did not support the hypothesis that associations between activated self-related memory and illness-related memory cause increased reporting of complaints. Instead, activating self-related memory increased pain tolerance in participants with low SFA. This seems to indicate that the self-prime might cause an increase in SFA and suggests possible new ways to promote adaptive coping with pain.

Transiently chaotic neural networks with piecewise linear output functions

Energy Technology Data Exchange (ETDEWEB)

Chen, S.-S. [Department of Mathematics, National Taiwan Normal University, Taipei, Taiwan (China); Shih, C.-W. [Department of Applied Mathematics, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, Taiwan (China)], E-mail: cwshih@math.nctu.edu.tw

2009-01-30

Admitting both transient chaotic phase and convergent phase, the transiently chaotic neural network (TCNN) provides superior performance than the classical networks in solving combinatorial optimization problems. We derive concrete parameter conditions for these two essential dynamic phases of the TCNN with piecewise linear output function. The confirmation for chaotic dynamics of the system results from a successful application of the Marotto theorem which was recently clarified. Numerical simulation on applying the TCNN with piecewise linear output function is carried out to find the optimal solution of a travelling salesman problem. It is demonstrated that the performance is even better than the previous TCNN model with logistic output function.

Behavioral modeling of the dominant dynamics in input-output transfer of linear(ized) circuits

NARCIS (Netherlands)

Beelen, T.G.J.; Maten, ter E.J.W.; Sihaloho, H.J.; Eijndhoven, van S.J.L.

2010-01-01

We present a powerful procedure for determining both the dominant dynamics of the inputoutput transfer and the corresponding most influential circuit parameters of a linear(ized) circuit. The procedure consists of several steps in which a specific (sub)problem is solved and its solution is used in

Calculation of relative tube/tube support plate displacements in steam generators under accident condition loads using non-linear dynamic analysis methodologies

International Nuclear Information System (INIS)

Smith, R.E.; Waisman, R.; Hu, M.H.; Frick, T.M.

1995-01-01

A non-linear analysis has been performed to determine relative motions between tubes and tube support plates (TSP) during a steam line break (SLB) event for steam generators. The SLB event results in blowdown of steam and water out of the steam generator. The fluid blowdown generates pressure drops across the TSPS, resulting in out-of-plane motion. The SLB induced pressure loads are calculated with a computer program that uses a drift-flux modeling of the two-phase flow. In order to determine the relative tube/TSP motions, a nonlinear dynamic time-history analysis is performed using a structural model that considers all of the significant component members relative to the tube support system. The dynamic response of the structure to the pressure loads is calculated using a special purpose computer program. This program links the various substructures at common degrees of freedom into a combined mass and stiffness matrix. The program accounts for structural non-linearities, including potential tube and TSP interaction at any given tube position. The program also accounts for structural damping as part of the dynamic response. Incorporating all of the above effects, the equations of motion are solved to give TSP displacements at the reduced set of DOF. Using the displacement results from the dynamic analysis, plate stresses are then calculated using the detailed component models. Displacements form the dynamic analysis are imposed as boundary conditions at the DOF locations, and the finite element program then solves for the overall distorted geometry. Calculations are also performed to assure that assumptions regarding elastic response of the various structural members and support points are valid

Central sensitivity syndromes: a new paradigm and group nosology for fibromyalgia and overlapping conditions, and the related issue of disease versus illness.

Science.gov (United States)

Yunus, Muhammad B

2008-06-01

To discuss the current terminologies used for fibromyalgia syndrome (FMS) and related overlapping conditions, to examine if central sensitivity syndromes (CSS) is the appropriate nosology for these disorders, and to explore the issue of disease versus illness. A literature search was performed through PubMed, Web of Science, and ScienceDirect using a number of keywords, eg, functional somatic syndromes, somatoform disorders, medically unexplained symptoms, organic and nonorganic, and diseases and illness. Relevant articles were then reviewed and representative ones cited. Terminologies currently used for CSS conditions predominantly represent a psychosocial construct and are inappropriate. On the other hand, CSS seems to be the logical nosology based on a biopsychosocial model. Such terms as "medically unexplained symptoms," "somatization," "somatization disorder," and "functional somatic syndromes" in the context of CSS should be abandoned. Given current scientific knowledge, the concept of disease-illness dualism has no rational basis and impedes proper patient-physician communication, resulting in poor patient care. The concept of CSS is likely to promote research, education, and proper patient management. CSS seems to be a useful paradigm and an appropriate terminology for FMS and related conditions. The disease-illness, as well as organic/non-organic dichotomy, should be rejected.

Representation of Students in Solving Simultaneous Linear Equation Problems Based on Multiple Intelligence

Science.gov (United States)

Yanti, Y. R.; Amin, S. M.; Sulaiman, R.

2018-01-01

This study described representation of students who have musical, logical-mathematic and naturalist intelligence in solving a problem. Subjects were selected on the basis of multiple intelligence tests (TPM) consists of 108 statements, with 102 statements adopted from Chislet and Chapman and 6 statements equal to eksistensial intelligences. Data were analyzed based on problem-solving tests (TPM) and interviewing. See the validity of the data then problem-solving tests (TPM) and interviewing is given twice with an analyzed using the representation indikator and the problem solving step. The results showed that: the stage of presenting information known, stage of devising a plan, and stage of carrying out the plan those three subjects were using same form of representation. While he stage of presenting information asked and stage of looking back, subject of logical-mathematic was using different forms of representation with subjects of musical and naturalist intelligence. From this research is expected to provide input to the teacher in determining the learning strategy that will be used by considering the representation of students with the basis of multiple intelligences.

Modified truncated randomized singular value decomposition (MTRSVD) algorithms for large scale discrete ill-posed problems with general-form regularization

Science.gov (United States)

Jia, Zhongxiao; Yang, Yanfei

2018-05-01

In this paper, we propose new randomization based algorithms for large scale linear discrete ill-posed problems with general-form regularization: subject to , where L is a regularization matrix. Our algorithms are inspired by the modified truncated singular value decomposition (MTSVD) method, which suits only for small to medium scale problems, and randomized SVD (RSVD) algorithms that generate good low rank approximations to A. We use rank-k truncated randomized SVD (TRSVD) approximations to A by truncating the rank- RSVD approximations to A, where q is an oversampling parameter. The resulting algorithms are called modified TRSVD (MTRSVD) methods. At every step, we use the LSQR algorithm to solve the resulting inner least squares problem, which is proved to become better conditioned as k increases so that LSQR converges faster. We present sharp bounds for the approximation accuracy of the RSVDs and TRSVDs for severely, moderately and mildly ill-posed problems, and substantially improve a known basic bound for TRSVD approximations. We prove how to choose the stopping tolerance for LSQR in order to guarantee that the computed and exact best regularized solutions have the same accuracy. Numerical experiments illustrate that the best regularized solutions by MTRSVD are as accurate as the ones by the truncated generalized singular value decomposition (TGSVD) algorithm, and at least as accurate as those by some existing truncated randomized generalized singular value decomposition (TRGSVD) algorithms. This work was supported in part by the National Science Foundation of China (Nos. 11771249 and 11371219).

Investigating Integer Restrictions in Linear Programming

Science.gov (United States)

Edwards, Thomas G.; Chelst, Kenneth R.; Principato, Angela M.; Wilhelm, Thad L.

2015-01-01

Linear programming (LP) is an application of graphing linear systems that appears in many Algebra 2 textbooks. Although not explicitly mentioned in the Common Core State Standards for Mathematics, linear programming blends seamlessly into modeling with mathematics, the fourth Standard for Mathematical Practice (CCSSI 2010, p. 7). In solving a…

Analysis of separation test for automatic brake adjuster based on linear radon transformation

Science.gov (United States)

Luo, Zai; Jiang, Wensong; Guo, Bin; Fan, Weijun; Lu, Yi

2015-01-01

The linear Radon transformation is applied to extract inflection points for online test system under the noise conditions. The linear Radon transformation has a strong ability of anti-noise and anti-interference by fitting the online test curve in several parts, which makes it easy to handle consecutive inflection points. We applied the linear Radon transformation to the separation test system to solve the separating clearance of automatic brake adjuster. The experimental results show that the feature point extraction error of the gradient maximum optimal method is approximately equal to ±0.100, while the feature point extraction error of linear Radon transformation method can reach to ±0.010, which has a lower error than the former one. In addition, the linear Radon transformation is robust.

Autobiographical memory specificity and the persistence of depressive symptoms in HIV-positive patients: rumination and social problem-solving skills as mediators.

Science.gov (United States)

Yanes, Paula K; Morse, Gene; Hsiao, Chiu-Bin; Simms, Leonard; Roberts, John E

2012-01-01

Individuals infected with human immunodeficiency virus (HIV) are at elevated risk for depressive conditions, which in turn can negatively impact health-related behaviours and the course of illness. The present study tested the role of autobiographical memory specificity and its interaction with perceived stress in the persistence of depressive symptoms among dysphoric HIV-positive individuals. Additionally, we examined whether rumination and social problem solving mediated these effects. Results indicated that memory specificity moderated the impact of perceived stress, such that perceived stress was more strongly associated with follow-up depressive symptoms among those with greater memory specificity. Rumination, but not social problem solving, mediated this effect. Implications of these findings are discussed.

The Effects of Successful versus Failure-Based Cases on Argumentation while Solving Decision-Making Problems

Science.gov (United States)

Tawfik, Andrew; Jonassen, David

2013-01-01

Solving complex, ill-structured problems may be effectively supported by case-based reasoning through case libraries that provide just-in-time domain-specific principles in the form of stories. The cases not only articulate previous experiences of practitioners, but also serve as problem-solving narratives from which learners can acquire meaning.…

Coping and resilience of children of a mentally ill parent.

Science.gov (United States)

Pölkki, Pirjo; Ervast, Sari-Anne; Huupponen, Marika

2004-01-01

This paper examines the needs and stress reactions of children of mentally ill parents, as well as coping and resilience. The study is based on the interviews of six 9-11 years old children and narratives of seventeen female grown up children of mentally ill parents. The younger and older children of the mentally ill parents had not been informed about their parent's illness. The illness of the parent aroused a variety of emotions in them. The children used both practical problem solving and emotional coping mechanisms. Informal social support was available to them but seldom from the public services. It is recommended that professionals in mental health and child welfare services clarify their roles when working with mentally ill parents. The best interest of the child and the parenting they need should be carefully assessed. Open care measures should be offered to families early enough to prevent serious child welfare and mental problems.

Oscillation and non-oscillation criterion for Riemann–Weber type half-linear differential equations

Directory of Open Access Journals (Sweden)

Petr Hasil

2016-08-01

Full Text Available By the combination of the modified half-linear Prüfer method and the Riccati technique, we study oscillatory properties of half-linear differential equations. Taking into account the transformation theory of half-linear equations and using some known results, we show that the analysed equations in the Riemann–Weber form with perturbations in both terms are conditionally oscillatory. Within the process, we identify the critical oscillation values of their coefficients and, consequently, we decide when the considered equations are oscillatory and when they are non-oscillatory. As a direct corollary of our main result, we solve the so-called critical case for a certain type of half-linear non-perturbed equations.

Projected regression method for solving Fredholm integral equations arising in the analytic continuation problem of quantum physics

International Nuclear Information System (INIS)

Arsenault, Louis-François; Millis, Andrew J; Neuberg, Richard; Hannah, Lauren A

2017-01-01

We present a supervised machine learning approach to the inversion of Fredholm integrals of the first kind as they arise, for example, in the analytic continuation problem of quantum many-body physics. The approach provides a natural regularization for the ill-conditioned inverse of the Fredholm kernel, as well as an efficient and stable treatment of constraints. The key observation is that the stability of the forward problem permits the construction of a large database of outputs for physically meaningful inputs. Applying machine learning to this database generates a regression function of controlled complexity, which returns approximate solutions for previously unseen inputs; the approximate solutions are then projected onto the subspace of functions satisfying relevant constraints. Under standard error metrics the method performs as well or better than the Maximum Entropy method for low input noise and is substantially more robust to increased input noise. We suggest that the methodology will be similarly effective for other problems involving a formally ill-conditioned inversion of an integral operator, provided that the forward problem can be efficiently solved. (paper)

Do Cases Teach Themselves? A Comparison of Case Library Prompts in Supporting Problem-Solving during Argumentation

Science.gov (United States)

Tawfik, Andrew A.

2017-01-01

Theorists have argued instructional strategies that emphasize ill-structured problem solving are an effective means to support higher order learning skills such as argumentation. However, argumentation is often difficult because novices lack the expertise or experience needed to solve contextualized problems. One way to supplement this lack of…

An implicit measure of associations with mental illness versus physical illness: response latency decomposition and stimuli differential functioning in relation to IAT order of associative conditions and accuracy.

Science.gov (United States)

Mannarini, Stefania; Boffo, Marilisa

2014-01-01

The present study aimed at the definition of a latent measurement dimension underlying an implicit measure of automatic associations between the concept of mental illness and the psychosocial and biogenetic causal explanatory attributes. To this end, an Implicit Association Test (IAT) assessing the association between the Mental Illness and Physical Illness target categories to the Psychological and Biologic attribute categories, representative of the causal explanation domains, was developed. The IAT presented 22 stimuli (words and pictures) to be categorized into the four categories. After 360 university students completed the IAT, a Many-Facet Rasch Measurement (MFRM) modelling approach was applied. The model specified a person latency parameter and a stimulus latency parameter. Two additional parameters were introduced to denote the order of presentation of the task associative conditions and the general response accuracy. Beyond the overall definition of the latent measurement dimension, the MFRM was also applied to disentangle the effect of the task block order and the general response accuracy on the stimuli response latency. Further, the MFRM allowed detecting any differential functioning of each stimulus in relation to both block ordering and accuracy. The results evidenced: a) the existence of a latency measurement dimension underlying the Mental Illness versus Physical Illness - Implicit Association Test; b) significant effects of block order and accuracy on the overall latency; c) a differential functioning of specific stimuli. The results of the present study can contribute to a better understanding of the functioning of an implicit measure of semantic associations with mental illness and give a first blueprint for the examination of relevant issues in the development of an IAT.

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

Robust Control of an Ill-Conditioned Aircraft

DEFF Research Database (Denmark)

Breslin, S.G.; Tøffner-Clausen, S.; Grimble, M.J.

1996-01-01

A robust controller is designed for a linear model of an Advanced Short Take-Off and Vertical Landing (ASTOVL) aircraft at one operating point.......A robust controller is designed for a linear model of an Advanced Short Take-Off and Vertical Landing (ASTOVL) aircraft at one operating point....

Fuzzy Multi-objective Linear Programming Approach

Directory of Open Access Journals (Sweden)

Amna Rehmat

2007-07-01

Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.

A Strongly and Superlinearly Convergent SQP Algorithm for Optimization Problems with Linear Complementarity Constraints

International Nuclear Information System (INIS)

Jian Jinbao; Li Jianling; Mo Xingde

2006-01-01

This paper discusses a kind of optimization problem with linear complementarity constraints, and presents a sequential quadratic programming (SQP) algorithm for solving a stationary point of the problem. The algorithm is a modification of the SQP algorithm proposed by Fukushima et al. [Computational Optimization and Applications, 10 (1998),5-34], and is based on a reformulation of complementarity condition as a system of linear equations. At each iteration, one quadratic programming and one system of equations needs to be solved, and a curve search is used to yield the step size. Under some appropriate assumptions, including the lower-level strict complementarity, but without the upper-level strict complementarity for the inequality constraints, the algorithm is proved to possess strong convergence and superlinear convergence. Some preliminary numerical results are reported

Feedback linearization based control of a variable air volume air conditioning system for cooling applications.

Science.gov (United States)

Thosar, Archana; Patra, Amit; Bhattacharyya, Souvik

2008-07-01

Design of a nonlinear control system for a Variable Air Volume Air Conditioning (VAVAC) plant through feedback linearization is presented in this article. VAVAC systems attempt to reduce building energy consumption while maintaining the primary role of air conditioning. The temperature of the space is maintained at a constant level by establishing a balance between the cooling load generated in the space and the air supply delivered to meet the load. The dynamic model of a VAVAC plant is derived and formulated as a MIMO bilinear system. Feedback linearization is applied for decoupling and linearization of the nonlinear model. Simulation results for a laboratory scale plant are presented to demonstrate the potential of keeping comfort and maintaining energy optimal performance by this methodology. Results obtained with a conventional PI controller and a feedback linearizing controller are compared and the superiority of the proposed approach is clearly established.

Polarized atomic orbitals for linear scaling methods

Science.gov (United States)

Berghold, Gerd; Parrinello, Michele; Hutter, Jürg

2002-02-01

We present a modified version of the polarized atomic orbital (PAO) method [M. S. Lee and M. Head-Gordon, J. Chem. Phys. 107, 9085 (1997)] to construct minimal basis sets optimized in the molecular environment. The minimal basis set derives its flexibility from the fact that it is formed as a linear combination of a larger set of atomic orbitals. This approach significantly reduces the number of independent variables to be determined during a calculation, while retaining most of the essential chemistry resulting from the admixture of higher angular momentum functions. Furthermore, we combine the PAO method with linear scaling algorithms. We use the Chebyshev polynomial expansion method, the conjugate gradient density matrix search, and the canonical purification of the density matrix. The combined scheme overcomes one of the major drawbacks of standard approaches for large nonorthogonal basis sets, namely numerical instabilities resulting from ill-conditioned overlap matrices. We find that the condition number of the PAO overlap matrix is independent from the condition number of the underlying extended basis set, and consequently no numerical instabilities are encountered. Various applications are shown to confirm this conclusion and to compare the performance of the PAO method with extended basis-set calculations.

Solving the Rational Polynomial Coefficients Based on L Curve

Science.gov (United States)

Zhou, G.; Li, X.; Yue, T.; Huang, W.; He, C.; Huang, Y.

2018-05-01

The rational polynomial coefficients (RPC) model is a generalized sensor model, which can achieve high approximation accuracy. And it is widely used in the field of photogrammetry and remote sensing. Least square method is usually used to determine the optimal parameter solution of the rational function model. However the distribution of control points is not uniform or the model is over-parameterized, which leads to the singularity of the coefficient matrix of the normal equation. So the normal equation becomes ill conditioned equation. The obtained solutions are extremely unstable and even wrong. The Tikhonov regularization can effectively improve and solve the ill conditioned equation. In this paper, we calculate pathological equations by regularization method, and determine the regularization parameters by L curve. The results of the experiments on aerial format photos show that the accuracy of the first-order RPC with the equal denominators has the highest accuracy. The high order RPC model is not necessary in the processing of dealing with frame images, as the RPC model and the projective model are almost the same. The result shows that the first-order RPC model is basically consistent with the strict sensor model of photogrammetry. Orthorectification results both the firstorder RPC model and Camera Model (ERDAS9.2 platform) are similar to each other, and the maximum residuals of X and Y are 0.8174 feet and 0.9272 feet respectively. This result shows that RPC model can be used in the aerial photographic compensation replacement sensor model.

Krylov subspace methods for solving large unsymmetric linear systems

International Nuclear Information System (INIS)

Saad, Y.

1981-01-01

Some algorithms based upon a projection process onto the Krylov subspace K/sub m/ = Span(r 0 , Ar 0 ,...,A/sup m/-1r 0 ) are developed, generalizing the method of conjugate gradients to unsymmetric systems. These methods are extensions of Arnoldi's algorithm for solving eigenvalue problems. The convergence is analyzed in terms of the distance of the solution to the subspace K/sub m/ and some error bounds are established showing, in particular, a similarity with the conjugate gradient method (for symmetric matrices) when the eigenvalues are real. Several numerical experiments are described and discussed

Solving a mixed-integer linear programming model for a multi-skilled project scheduling problem by simulated annealing

Directory of Open Access Journals (Sweden)

H Kazemipoor

2012-04-01

Full Text Available A multi-skilled project scheduling problem (MSPSP has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time.

Development of an e-supported illness management and recovery programme for consumers with severe mental illness using intervention mapping, and design of an early cluster randomized controlled trial.

Science.gov (United States)

Beentjes, Titus A A; van Gaal, Betsie G I; Goossens, Peter J J; Schoonhoven, Lisette

2016-01-19

E-mental health is a promising medium to keep mental health affordable and accessible. For consumers with severe mental illness the evidence of the effectiveness of e-health is limited. A number of difficulties and barriers have to be addressed concerning e-health for consumers with severe mental illness. One possible solution might be to blend e-health with face-to-face delivery of a recovery-oriented treatment, like the Illness Management & Recovery (IMR) programme. This paper describes the development of an e-health application for the IMR programme and the design of an early clustered randomized controlled trial. We developed the e-IMR intervention according to the six-step protocol of Intervention Mapping. Consumers joined the development group to address important and relevant issues for the target group. Decisions during the six-step development process were based on qualitative evaluations of the Illness Management & Recovery programme, structured interviews, discussion in the development group, and literature reviews on qualitative papers concerning consumers with severe mental illness, theoretical models, behavioural change techniques, and telemedicine for consumers with severe mental illness. The aim of the e-IMR intervention is to help consumers with severe mental illness to involve others, manage achieving goals, and prevent relapse. The e-IMR intervention consists of face-to-face delivery of the Illness Management & Recovery programme and an e-health application containing peer-testimonials on videos, follow up on goals and coping strategies, monitoring symptoms, solving problems, and communication opportunities. We designed an early cluster randomized controlled trial that will evaluate the e-IMR intervention. In the control condition the Illness Management & Recovery programme is provided. The main effect-study parameters are: illness management, recovery, psychiatric symptoms severity, self-management, quality of life, and general health. The

Linear Matrix Inequalities in Multirate Control over Networks

Directory of Open Access Journals (Sweden)

Ángel Cuenca

2012-01-01

Full Text Available This paper faces two of the main drawbacks in networked control systems: bandwidth constraints and timevarying delays. The bandwidth limitations are solved by using multirate control techniques. The resultant multirate controller must ensure closed-loop stability in the presence of time-varying delays. Some stability conditions and a state feedback controller design are formulated in terms of linear matrix inequalities. The theoretical proposal is validated in two different experimental environments: a crane-based test-bed over Ethernet, and a maglev based platform over Profibus.

Non-linear Bayesian update of PCE coefficients

KAUST Repository

Litvinenko, Alexander

2014-01-06

Given: a physical system modeled by a PDE or ODE with uncertain coefficient q(?), a measurement operator Y (u(q), q), where u(q, ?) uncertain solution. Aim: to identify q(?). The mapping from parameters to observations is usually not invertible, hence this inverse identification problem is generally ill-posed. To identify q(!) we derived non-linear Bayesian update from the variational problem associated with conditional expectation. To reduce cost of the Bayesian update we offer a unctional approximation, e.g. polynomial chaos expansion (PCE). New: We apply Bayesian update to the PCE coefficients of the random coefficient q(?) (not to the probability density function of q).

Non-linear Bayesian update of PCE coefficients

KAUST Repository

Litvinenko, Alexander; Matthies, Hermann G.; Pojonk, Oliver; Rosic, Bojana V.; Zander, Elmar

2014-01-01

Given: a physical system modeled by a PDE or ODE with uncertain coefficient q(?), a measurement operator Y (u(q), q), where u(q, ?) uncertain solution. Aim: to identify q(?). The mapping from parameters to observations is usually not invertible, hence this inverse identification problem is generally ill-posed. To identify q(!) we derived non-linear Bayesian update from the variational problem associated with conditional expectation. To reduce cost of the Bayesian update we offer a unctional approximation, e.g. polynomial chaos expansion (PCE). New: We apply Bayesian update to the PCE coefficients of the random coefficient q(?) (not to the probability density function of q).

Computation of the Short-Time Linear Canonical Transform with Dual Window

Directory of Open Access Journals (Sweden)

Lei Huang

2017-01-01

Full Text Available The short-time linear canonical transform (STLCT, which maps the time domain signal into the joint time and frequency domain, has recently attracted some attention in the area of signal processing. However, its applications are still limited due to the fact that selection of coefficients of the short-time linear canonical series (STLCS is not unique, because time and frequency elementary functions (together known as basis function of STLCS do not constitute an orthogonal basis. To solve this problem, this paper investigates a dual window solution. First, the nonorthogonal problem that suffered from original window is fulfilled by orthogonal condition with dual window. Then based on the obtained condition, a dual window computation approach of the GT is extended to the STLCS. In addition, simulations verify the validity of the proposed condition and solutions. Furthermore, some possible applied directions are discussed.

A Regularized Approach for Solving Magnetic Differential Equations and a Revised Iterative Equilibrium Algorithm

International Nuclear Information System (INIS)

Hudson, S.R.

2010-01-01

A method for approximately solving magnetic differential equations is described. The approach is to include a small diffusion term to the equation, which regularizes the linear operator to be inverted. The extra term allows a 'source-correction' term to be defined, which is generally required in order to satisfy the solvability conditions. The approach is described in the context of computing the pressure and parallel currents in the iterative approach for computing magnetohydrodynamic equilibria.

Impact of chronic illness timing and persistence at school entry on child and parent outcomes: Australian longitudinal study.

Science.gov (United States)

Quach, Jon; Barnett, Tony

2015-01-01

To understand the prevalence and timing of child chronic illness at school entry; associations with child learning, behavior and health-related quality of life and parent mental health at ages 6 to 7, 8 to 9, and 10 to 11 years; and cumulative health care costs. Data were drawn from the first 4 waves of the Longitudinal Study of Australian Children. Children were aged 4 to 5 years at wave 1, with data collection every 2 years. Parent-reported timing of child chronic illness at school entry was categorized into 4 chronic illness groups based on changes between waves 1 and 2: none, resolving, incident and persistent. Child outcomes included: parent-reported quality of life, parent- and teacher-reported behavior, teacher-reported child learning, teacher-reported child-teacher relationship, directly assessed nonverbal and verbal cognition and parent self-reported mental health. Linear regression, adjusted for gender and socioeconomic position, was used to quantify longitudinal associations between chronic illness timing at school entry with outcomes at age 6 to 7 years, 8 to 9 years and 10 to 11 years. Of the 4983 children enrolled in the study, chronic illness data was available for 4464 children (89.6%) at both waves 1 and 2. From wave 1, 6.1% had a condition that persisted until wave 2, while 14.1% had a condition that resolved. Furthermore, 4.7% had a newly emerging condition at wave 2. Compared with the no chronic illness group, children with persistent or emerging chronic illness during school entry had the poorest outcomes (except father's mental health) at all time points, while children with resolving conditions had smaller differences. Child chronic illness at school entry is associated with poorer longitudinal child and maternal outcomes. Therefore, future research should aim to determine the risk and protective factors that contribute to the poorer child and parent outcomes experienced in this growing population. Copyright © 2015 Academic Pediatric

Cascade Structure of Digital Predistorter for Power Amplifier Linearization

Directory of Open Access Journals (Sweden)

E. B. Solovyeva

2015-12-01

Full Text Available In this paper, a cascade structure of nonlinear digital predistorter (DPD synthesized by the direct learning adaptive algorithm is represented. DPD is used for linearization of power amplifier (PA characteristic, namely for compensation of PA nonlinear distortion. Blocks of the cascade DPD are described by different models: the functional link artificial neural network (FLANN, the polynomial perceptron network (PPN and the radially pruned Volterra model (RPVM. At synthesis of the cascade DPD there is possibility to overcome the ill conditionality problem due to reducing the dimension of DPD nonlinear operator approximation. Results of compensating nonlinear distortion in Wiener–Hammerstein model of PA at the GSM–signal with four carriers are shown. The highest accuracy of PA linearization is produced by the cascade DPD containing PPN and RPVM.

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)

FUNDAMENTAL MATRIX OF LINEAR CONTINUOUS SYSTEM IN THE PROBLEM OF ESTIMATING ITS TRANSPORT DELAY

Directory of Open Access Journals (Sweden)

N. A. Dudarenko

2014-09-01

Full Text Available The paper deals with the problem of quantitative estimation for transport delay of linear continuous systems. The main result is received by means of fundamental matrix of linear differential equations solutions specified in the normal Cauchy form for the cases of SISO and MIMO systems. Fundamental matrix has the dual property. It means that the weight function of the system can be formed as a free motion of systems. Last one is generated by the vector of initial system conditions, which coincides with the matrix input of the system being researched. Thus, using the properties of the system- solving for fundamental matrix has given the possibility to solve the problem of estimating transport linear continuous system delay without the use of derivation procedure in hardware environment and without formation of exogenous Dirac delta function. The paper is illustrated by examples. The obtained results make it possible to solve the problem of modeling the pure delay links using consecutive chain of aperiodic links of the first order with the equal time constants. Modeling results have proved the correctness of obtained computations. Knowledge of transport delay can be used when configuring multi- component technological complexes and in the diagnosis of their possible functional degeneration.

Study of Piezoelectric Vibration Energy Harvester with non-linear conditioning circuit using an integrated model

Science.gov (United States)

Manzoor, Ali; Rafique, Sajid; Usman Iftikhar, Muhammad; Mahmood Ul Hassan, Khalid; Nasir, Ali

2017-08-01

Piezoelectric vibration energy harvester (PVEH) consists of a cantilever bimorph with piezoelectric layers pasted on its top and bottom, which can harvest power from vibrations and feed to low power wireless sensor nodes through some power conditioning circuit. In this paper, a non-linear conditioning circuit, consisting of a full-bridge rectifier followed by a buck-boost converter, is employed to investigate the issues of electrical side of the energy harvesting system. An integrated mathematical model of complete electromechanical system has been developed. Previously, researchers have studied PVEH with sophisticated piezo-beam models but employed simplistic linear circuits, such as resistor, as electrical load. In contrast, other researchers have worked on more complex non-linear circuits but with over-simplified piezo-beam models. Such models neglect different aspects of the system which result from complex interactions of its electrical and mechanical subsystems. In this work, authors have integrated the distributed parameter-based model of piezo-beam presented in literature with a real world non-linear electrical load. Then, the developed integrated model is employed to analyse the stability of complete energy harvesting system. This work provides a more realistic and useful electromechanical model having realistic non-linear electrical load unlike the simplistic linear circuit elements employed by many researchers.

An efficient method for generalized linear multiplicative programming problem with multiplicative constraints.

Science.gov (United States)

Zhao, Yingfeng; Liu, Sanyang

2016-01-01

We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.

A nonlinear plate control without linearization

Directory of Open Access Journals (Sweden)

Yildirim Kenan

2017-03-01

Full Text Available In this paper, an optimal vibration control problem for a nonlinear plate is considered. In order to obtain the optimal control function, wellposedness and controllability of the nonlinear system is investigated. The performance index functional of the system, to be minimized by minimum level of control, is chosen as the sum of the quadratic 10 functional of the displacement. The velocity of the plate and quadratic functional of the control function is added to the performance index functional as a penalty term. By using a maximum principle, the nonlinear control problem is transformed to solving a system of partial differential equations including state and adjoint variables linked by initial-boundary-terminal conditions. Hence, it is shown that optimal control of the nonlinear systems can be obtained without linearization of the nonlinear term and optimal control function can be obtained analytically for nonlinear systems without linearization.

Rate-Independent Processes with Linear Growth Energies and Time-Dependent Boundary Conditions

Czech Academy of Sciences Publication Activity Database

Kružík, Martin; Zimmer, J.

2012-01-01

Roč. 5, č. 3 (2012), s. 591-604 ISSN 1937-1632 R&D Projects: GA AV ČR IAA100750802 Grant - others:GA ČR(CZ) GAP201/10/0357 Institutional research plan: CEZ:AV0Z10750506 Keywords : concentrations * oscillations * time - dependent boundary conditions * rate-independent evolution Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2011/MTR/kruzik-rate-independent processes with linear growth energies and time - dependent boundary conditions.pdf

Clinically Practical Approach for Screening of Low Muscularity Using Electronic Linear Measures on Computed Tomography Images in Critically Ill Patients.

Science.gov (United States)

Avrutin, Egor; Moisey, Lesley L; Zhang, Roselyn; Khattab, Jenna; Todd, Emma; Premji, Tahira; Kozar, Rosemary; Heyland, Daren K; Mourtzakis, Marina

2017-12-06

Computed tomography (CT) scans performed during routine hospital care offer the opportunity to quantify skeletal muscle and predict mortality and morbidity in intensive care unit (ICU) patients. Existing methods of muscle cross-sectional area (CSA) quantification require specialized software, training, and time commitment that may not be feasible in a clinical setting. In this article, we explore a new screening method to identify patients with low muscle mass. We analyzed 145 scans of elderly ICU patients (≥65 years old) using a combination of measures obtained with a digital ruler, commonly found on hospital radiological software. The psoas and paraspinal muscle groups at the level of the third lumbar vertebra (L3) were evaluated by using 2 linear measures each and compared with an established method of CT image analysis of total muscle CSA in the L3 region. There was a strong association between linear measures of psoas and paraspinal muscle groups and total L3 muscle CSA (R 2 = 0.745, P < 0.001). Linear measures, age, and sex were included as covariates in a multiple logistic regression to predict those with low muscle mass; receiver operating characteristic (ROC) area under the curve (AUC) of the combined psoas and paraspinal linear index model was 0.920. Intraclass correlation coefficients (ICCs) were used to evaluate intrarater and interrater reliability, resulting in scores of 0.979 (95% CI: 0.940-0.992) and 0.937 (95% CI: 0.828-0.978), respectively. A digital ruler can reliably predict L3 muscle CSA, and these linear measures may be used to identify critically ill patients with low muscularity who are at risk for worse clinical outcomes. © 2017 American Society for Parenteral and Enteral Nutrition.

Understanding Mental Illness Stigma Toward Persons With Multiple Stigmatized Conditions: Implications of Intersectionality Theory.

Science.gov (United States)

Oexle, Nathalie; Corrigan, Patrick W

2018-05-01

People with mental illness are often members of multiple stigmatized social groups. Therefore, experienced disadvantage might not be determined solely by mental illness stigma. Nevertheless, most available research does not consider the effects and implications of membership in multiple stigmatized social groups among people with mental illness. Reflecting on intersectionality theory, the authors discuss two intersectional effects determining disadvantage among people with mental illness who are members of multiple stigmatized social groups, namely double disadvantage and prominence. To be effective, interventions to reduce disadvantage experienced by people with mental illness need to be flexible and targeted rather than universal in order to address the implications of intersectionality. Whereas education-based approaches usually assume homogeneity and use universal strategies, contact-based interventions consider diversity among people with mental illness.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter; Taká č, Martin

2017-01-01

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter

2017-06-04

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Iterative solution of linear systems in the 20­th century

NARCIS (Netherlands)

Saad, Y.; Vorst, H.A. van der

2000-01-01

This paper sketches the main research developments in the area of iterative methods for solving linear systems during the 20th century. Although iterative methods for solving linear systems find their origin in the early nineteenth century (work by Gauss), the field has seen an explosion of

A mixed Fourier–Galerkin–finite-volume method to solve the fluid dynamics equations in cylindrical geometries

International Nuclear Information System (INIS)

Núñez, Jóse; Ramos, Eduardo; Lopez, Juan M

2012-01-01

We describe a hybrid method based on the combined use of the Fourier Galerkin and finite-volume techniques to solve the fluid dynamics equations in cylindrical geometries. A Fourier expansion is used in the angular direction, partially translating the problem to the Fourier space and then solving the resulting equations using a finite-volume technique. We also describe an algorithm required to solve the coupled mass and momentum conservation equations similar to a pressure-correction SIMPLE method that is adapted for the present formulation. Using the Fourier–Galerkin method for the azimuthal direction has two advantages. Firstly, it has a high-order approximation of the partial derivatives in the angular direction, and secondly, it naturally satisfies the azimuthal periodic boundary conditions. Also, using the finite-volume method in the r and z directions allows one to handle boundary conditions with discontinuities in those directions. It is important to remark that with this method, the resulting linear system of equations are band-diagonal, leading to fast and efficient solvers. The benefits of the mixed method are illustrated with example problems. (paper)

Arbitrary Lagrangian-Eulerian method for non-linear problems of geomechanics

International Nuclear Information System (INIS)

Nazem, M; Carter, J P; Airey, D W

2010-01-01

In many geotechnical problems it is vital to consider the geometrical non-linearity caused by large deformation in order to capture a more realistic model of the true behaviour. The solutions so obtained should then be more accurate and reliable, which should ultimately lead to cheaper and safer design. The Arbitrary Lagrangian-Eulerian (ALE) method originated from fluid mechanics, but has now been well established for solving large deformation problems in geomechanics. This paper provides an overview of the ALE method and its challenges in tackling problems involving non-linearities due to material behaviour, large deformation, changing boundary conditions and time-dependency, including material rate effects and inertia effects in dynamic loading applications. Important aspects of ALE implementation into a finite element framework will also be discussed. This method is then employed to solve some interesting and challenging geotechnical problems such as the dynamic bearing capacity of footings on soft soils, consolidation of a soil layer under a footing, and the modelling of dynamic penetration of objects into soil layers.

Parallel preconditioning techniques for sparse CG solvers

Energy Technology Data Exchange (ETDEWEB)

Basermann, A.; Reichel, B.; Schelthoff, C. [Central Institute for Applied Mathematics, Juelich (Germany)

1996-12-31

Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role in numerical methods for solving discretized partial differential equations. The large size and the condition of many technical or physical applications in this area result in the need for efficient parallelization and preconditioning techniques of the CG method. In particular for very ill-conditioned matrices, sophisticated preconditioner are necessary to obtain both acceptable convergence and accuracy of CG. Here, we investigate variants of polynomial and incomplete Cholesky preconditioners that markedly reduce the iterations of the simply diagonally scaled CG and are shown to be well suited for massively parallel machines.

Effects of acute beta-adrenergic antagonism on verbal problem solving in autism spectrum disorder and exploration of treatment response markers.

Science.gov (United States)

Zamzow, Rachel M; Ferguson, Bradley J; Ragsdale, Alexandra S; Lewis, Morgan L; Beversdorf, David Q

2017-08-01

Autism spectrum disorder (ASD) is characterized by impairments in social communication as well as restricted, repetitive behaviors. Evidence suggests that some individuals with ASD have cognitive impairments related to weak central coherence and hyperrestricted processing. Reducing noradrenergic activity may improve aspects of network processing and thus improve cognitive abilities, such as verbal problem solving, in individuals with ASD. The present pilot study explores the effects of acute administration of the beta-adrenergic antagonist propranolol on verbal problem solving in adults and adolescents with ASD. In a within-subject crossover-design, 20 participants with ASD received a single dose of propranolol or placebo on one of two sessions in a double-blinded, counterbalanced manner. Verbal problem solving was assessed via an anagram task. Baseline measurements of autonomic nervous system functioning were obtained, and anxiety was assessed at baseline and following drug administration. Participants solved the anagrams more quickly in the propranolol condition, as compared to the placebo condition, suggesting a potential cognitive benefit of this agent. Additionally, we observed a negative linear relationship between response to propranolol on the anagram task and two measures of baseline autonomic activity, as well as a positive linear relationship between drug response and baseline anxiety. These relationships propose potential markers for treatment response, as propranolol influences both autonomic functioning and anxiety. Further investigation is needed to expand on the present single-dose psychopharmacological challenge and explore the observed effects of propranolol in a serial-dose setting.

Living with Mentally Ill Parent

Directory of Open Access Journals (Sweden)

Kadriye Buldukoglu

2011-12-01

Full Text Available The present review seeks to identify and analyze qualitative studies that examined experiences of children whose parents have a mental illness. This study reported that children whose parents have a mental illness had some common experiences. These experiences may have negative effects on children’s coping skills, resilience to tough living conditions and ability to maintain their mental health. In spite of these negative conditions, some of these children have much more self-confidence, resilience and independence because of inner development and early maturation. Some effective intervention programs are needed to promote information to children and other family members about mental illness, coping behaviors. Availability of such psychiatric services and nation-wide programs with professionals to deal with these problems should be organized properly to increase quality of life of these children. Furthermore, qualitative researches that explore the experiences of children whose parents with mental illness should also be conducted in our country.

Solution of generalized shifted linear systems with complex symmetric matrices

International Nuclear Information System (INIS)

Sogabe, Tomohiro; Hoshi, Takeo; Zhang, Shao-Liang; Fujiwara, Takeo

2012-01-01

We develop the shifted COCG method [R. Takayama, T. Hoshi, T. Sogabe, S.-L. Zhang, T. Fujiwara, Linear algebraic calculation of Green’s function for large-scale electronic structure theory, Phys. Rev. B 73 (165108) (2006) 1–9] and the shifted WQMR method [T. Sogabe, T. Hoshi, S.-L. Zhang, T. Fujiwara, On a weighted quasi-residual minimization strategy of the QMR method for solving complex symmetric shifted linear systems, Electron. Trans. Numer. Anal. 31 (2008) 126–140] for solving generalized shifted linear systems with complex symmetric matrices that arise from the electronic structure theory. The complex symmetric Lanczos process with a suitable bilinear form plays an important role in the development of the methods. The numerical examples indicate that the methods are highly attractive when the inner linear systems can efficiently be solved.

Review on solving the forward problem in EEG source analysis

Directory of Open Access Journals (Sweden)

Vergult Anneleen

2007-11-01

Full Text Available Abstract Background The aim of electroencephalogram (EEG source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the inverse problem which is defined as finding brain sources which are responsible for the measured potentials at the EEG electrodes. Methods While other reviews give an extensive summary of the both forward and inverse problem, this review article focuses on different aspects of solving the forward problem and it is intended for newcomers in this research field. Results It starts with focusing on the generators of the EEG: the post-synaptic potentials in the apical dendrites of pyramidal neurons. These cells generate an extracellular current which can be modeled by Poisson's differential equation, and Neumann and Dirichlet boundary conditions. The compartments in which these currents flow can be anisotropic (e.g. skull and white matter. In a three-shell spherical head model an analytical expression exists to solve the forward problem. During the last two decades researchers have tried to solve Poisson's equation in a realistically shaped head model obtained from 3D medical images, which requires numerical methods. The following methods are compared with each other: the boundary element method (BEM, the finite element method (FEM and the finite difference method (FDM. In the last two methods anisotropic conducting compartments can conveniently be introduced. Then the focus will be set on the use of reciprocity in EEG source localization. It is introduced to speed up the forward calculations which are here performed for each electrode position rather than for each dipole position. Solving Poisson's equation utilizing FEM and FDM corresponds to solving a large sparse linear system. Iterative

Hybrid Method for Solving Inventory Problems with a Linear ...

African Journals Online (AJOL)

Osagiede and Omosigho (2004) proposed a direct search method for identifying the number of replenishment when the demand pattern is linearly increasing. The main computational task in this direct search method was associated with finding the optimal number of replenishments. To accelerate the use of this method, the ...

Stress in adolescents with a chronically ill parent: inspiration from Rolland's Family Systems-Illness model

NARCIS (Netherlands)

Sieh, D.S.; Dikkers, A.L.C.; Visser-Meily, J.M.A.; Meijer, A.M.

2012-01-01

This article was inspired by Rolland’s Family Systems-Illness (FSI) model, aiming to predict adolescent stress as a function of parental illness type. Ninety-nine parents with a chronic medical condition, 82 partners, and 158 adolescent children (51 % girls; mean age = 15.1 years) participated in

Elementary linear programming with applications

CERN Document Server

Kolman, Bernard

1995-01-01

Linear programming finds the least expensive way to meet given needs with available resources. Its results are used in every area of engineering and commerce: agriculture, oil refining, banking, and air transport. Authors Kolman and Beck present the basic notions of linear programming and illustrate how they are used to solve important common problems. The software on the included disk leads students step-by-step through the calculations. The Second Edition is completely revised and provides additional review material on linear algebra as well as complete coverage of elementary linear program

Analytical exact solution of the non-linear Schroedinger equation

International Nuclear Information System (INIS)

Martins, Alisson Xavier; Rocha Filho, Tarcisio Marciano da

2011-01-01

Full text: In this work we present how to classify and obtain analytical solutions of the Schroedinger equation with a generic non-linearity in 1+1 dimensions. Our approach is based on the determination of Lie symmetry transformation mapping solutions into solutions, and non-classical symmetry transformations, mapping a given solution into itself. From these symmetries it is then possible to reduce the equation to a system of ordinary differential equations which can then be solved using standard methods. The generic non-linearity is handled by considering it as an additional unknown in the determining equations for the symmetry transformations. This results in an over-determined system of non-linear partial differential equations. Its solution can then be determined in some cases by reducing it to the so called involutive (triangular) form, and then solved. This reduction is very tedious and can only performed using a computer algebra system. Once the determining system is solved, we obtain the explicit form for the non-linearity admitting a Lie or non-classical symmetry. The analytical solutions are then derived by solving the reduced ordinary differential equations. The non-linear determining system for the non-classical symmetry transformations and Lie symmetry generators are obtaining using the computer algebra package SADE (symmetry analysis of differential equations), developed at our group. (author)

Spontaneous gestures influence strategy choices in problem solving.

Science.gov (United States)

Alibali, Martha W; Spencer, Robert C; Knox, Lucy; Kita, Sotaro

2011-09-01

Do gestures merely reflect problem-solving processes, or do they play a functional role in problem solving? We hypothesized that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving. Participants in two experiments solved problems requiring the prediction of gear movement, either with gesture allowed or with gesture prohibited. Such problems can be correctly solved using either a perceptual-motor strategy (simulation of gear movements) or an abstract strategy (the parity strategy). Participants in the gesture-allowed condition were more likely to use perceptual-motor strategies than were participants in the gesture-prohibited condition. Gesture promoted use of perceptual-motor strategies both for participants who talked aloud while solving the problems (Experiment 1) and for participants who solved the problems silently (Experiment 2). Thus, spontaneous gestures influence strategy choices in problem solving.

The illness/non-illness model: hypnotherapy for physically ill patients.

Science.gov (United States)

Navon, Shaul

2014-07-01

This article proposes a focused, novel sub-set of the cognitive behavioral therapy approach to hypnotherapy for physically ill patients, based upon the illness/non-illness psychotherapeutic model for physically ill patients. The model is based on three logical rules used in differentiating illness from non-illness: duality, contradiction, and complementarity. The article discusses the use of hypnotic interventions to help physically ill and/or disabled patients distinguish between illness and non-illness in their psychotherapeutic themes and attitudes. Two case studies illustrate that patients in this special population group can be taught to learn the language of change and to use this language to overcome difficult situations. The model suggests a new clinical mode of treatment in which individuals who are physically ill and/or disabled are helped in coping with actual motifs and thoughts related to non-illness or non-disability.

The Pade approximate method for solving problems in plasma kinetic theory

International Nuclear Information System (INIS)

Jasperse, J.R.; Basu, B.

1992-01-01

The method of Pade Approximates has been a powerful tool in solving for the time dependent propagator (Green function) in model quantum field theories. We have developed a modified Pade method which we feel has promise for solving linearized collisional and weakly nonlinear problems in plasma kinetic theory. In order to illustrate the general applicability of the method, in this paper we discuss Pade solutions for the linearized collisional propagator and the collisional dielectric function for a model collisional problem. (author) 3 refs., 2 tabs

Research Projects in Physics: A Mechanism for Teaching Ill-Structured Problem Solving

Science.gov (United States)

Milbourne, Jeff; Bennett, Jonathan

2017-01-01

Physics education research has a tradition of studying problem solving, exploring themes such as physical intuition and differences between expert and novice problem solvers. However, most of this work has focused on traditional, or well-structured, problems, similar to what might appear in a textbook. Less work has been done with open-ended, or…

Bayesian Inference for Linear Parabolic PDEs with Noisy Boundary Conditions

KAUST Repository

Ruggeri, Fabrizio; Sawlan, Zaid A; Scavino, Marco; Tempone, Raul

2016-01-01

In this work we develop a hierarchical Bayesian setting to infer unknown parameters in initial-boundary value problems (IBVPs) for one-dimensional linear parabolic partial differential equations. Noisy boundary data and known initial condition are assumed. We derive the likelihood function associated with the forward problem, given some measurements of the solution field subject to Gaussian noise. Such function is then analytically marginalized using the linearity of the equation. Gaussian priors have been assumed for the time-dependent Dirichlet boundary values. Our approach is applied to synthetic data for the one-dimensional heat equation model, where the thermal diffusivity is the unknown parameter. We show how to infer the thermal diffusivity parameter when its prior distribution is lognormal or modeled by means of a space-dependent stationary lognormal random field. We use the Laplace method to provide approximated Gaussian posterior distributions for the thermal diffusivity. Expected information gains and predictive posterior densities for observable quantities are numerically estimated for different experimental setups.

Bayesian Inference for Linear Parabolic PDEs with Noisy Boundary Conditions

KAUST Repository

Ruggeri, Fabrizio

2015-01-07

In this work we develop a hierarchical Bayesian setting to infer unknown parameters in initial-boundary value problems (IBVPs) for one-dimensional linear parabolic partial differential equations. Noisy boundary data and known initial condition are assumed. We derive the likelihood function associated with the forward problem, given some measurements of the solution field subject to Gaussian noise. Such function is then analytically marginalized using the linearity of the equation. Gaussian priors have been assumed for the time-dependent Dirichlet boundary values. Our approach is applied to synthetic data for the one-dimensional heat equation model, where the thermal diffusivity is the unknown parameter. We show how to infer the thermal diffusivity parameter when its prior distribution is lognormal or modeled by means of a space-dependent stationary lognormal random field. We use the Laplace method to provide approximated Gaussian posterior distributions for the thermal diffusivity. Expected information gains and predictive posterior densities for observable quantities are numerically estimated for different experimental setups.

Bayesian Inference for Linear Parabolic PDEs with Noisy Boundary Conditions

KAUST Repository

Ruggeri, Fabrizio

2016-01-06

In this work we develop a hierarchical Bayesian setting to infer unknown parameters in initial-boundary value problems (IBVPs) for one-dimensional linear parabolic partial differential equations. Noisy boundary data and known initial condition are assumed. We derive the likelihood function associated with the forward problem, given some measurements of the solution field subject to Gaussian noise. Such function is then analytically marginalized using the linearity of the equation. Gaussian priors have been assumed for the time-dependent Dirichlet boundary values. Our approach is applied to synthetic data for the one-dimensional heat equation model, where the thermal diffusivity is the unknown parameter. We show how to infer the thermal diffusivity parameter when its prior distribution is lognormal or modeled by means of a space-dependent stationary lognormal random field. We use the Laplace method to provide approximated Gaussian posterior distributions for the thermal diffusivity. Expected information gains and predictive posterior densities for observable quantities are numerically estimated for different experimental setups.

Non-linear time series analysis on flow instability of natural circulation under rolling motion condition

International Nuclear Information System (INIS)

Zhang, Wenchao; Tan, Sichao; Gao, Puzhen; Wang, Zhanwei; Zhang, Liansheng; Zhang, Hong

2014-01-01

Highlights: • Natural circulation flow instabilities in rolling motion are studied. • The method of non-linear time series analysis is used. • Non-linear evolution characteristic of flow instability is analyzed. • Irregular complex flow oscillations are chaotic oscillations. • The effect of rolling parameter on the threshold of chaotic oscillation is studied. - Abstract: Non-linear characteristics of natural circulation flow instabilities under rolling motion conditions were studied by the method of non-linear time series analysis. Experimental flow time series of different dimensionless power and rolling parameters were analyzed based on phase space reconstruction theory. Attractors which were reconstructed in phase space and the geometric invariants, including correlation dimension, Kolmogorov entropy and largest Lyapunov exponent, were determined. Non-linear characteristics of natural circulation flow instabilities under rolling motion conditions was studied based on the results of the geometric invariant analysis. The results indicated that the values of the geometric invariants first increase and then decrease as dimensionless power increases which indicated the non-linear characteristics of the system first enhance and then weaken. The irregular complex flow oscillation is typical chaotic oscillation because the value of geometric invariants is at maximum. The threshold of chaotic oscillation becomes larger as the rolling frequency or rolling amplitude becomes big. The main influencing factors that influence the non-linear characteristics of the natural circulation system under rolling motion are thermal driving force, flow resistance and the additional forces caused by rolling motion. The non-linear characteristics of the natural circulation system under rolling motion changes caused by the change of the feedback and coupling degree among these influencing factors when the dimensionless power or rolling parameters changes

Solving Graph Laplacian Systems Through Recursive Bisections and Two-Grid Preconditioning

Energy Technology Data Exchange (ETDEWEB)

Ponce, Colin [Cornell Univ., Ithaca, NY (United States); Vassilevski, Panayot S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2016-02-18

We present a parallelizable direct method for computing the solution to graph Laplacian-based linear systems derived from graphs that can be hierarchically bipartitioned with small edge cuts. For a graph of size n with constant-size edge cuts, our method decomposes a graph Laplacian in time O(n log n), and then uses that decomposition to perform a linear solve in time O(n log n). We then use the developed technique to design a preconditioner for graph Laplacians that do not have this property. Finally, we augment this preconditioner with a two-grid method that accounts for much of the preconditioner's weaknesses. We present an analysis of this method, as well as a general theorem for the condition number of a general class of two-grid support graph-based preconditioners. Numerical experiments illustrate the performance of the studied methods.

An Application of Linear Algebra over Lattices

OpenAIRE

M. Hosseinyazdi

2008-01-01

In this paper, first we consider L n as a semimodule over a complete bounded distributive lattice L. Then we define the basic concepts of module theory for L n. After that, we proved many similar theorems in linear algebra for the space L n. An application of linear algebra over lattices for solving linear systems, was given

Illness Perceptions and Fatigue in Systemic Vasculitis

Science.gov (United States)

Grayson, Peter C.; Amudala, Naomi A.; McAlear, Carol A.; Leduc, Renée L.; Shereff, Denise; Richesson, Rachel; Fraenkel, Liana; Merkel, Peter A.

2014-01-01

Objective To compare illness perceptions among patients with different forms of vasculitis, identify risk factors for negative illness perceptions, and determine the association between illness perceptions and fatigue. Methods Participants were recruited from an online registry in vasculitis to complete the revised Illness Perception Questionnaire (IPQ-R). Mean scores on each IPQ-R dimension were compared across types of vasculitis. Cluster analysis and stepwise regression identified predictors of negative illness perception. Fatigue was measured using the general subscale of the Multidimensional Fatigue Inventory (MFI). Patient-reported measures of disease activity and IPQ-R dimensions were assessed in relation to MFI scores using linear regression in sequential, additive models with model-fit comparisons. Results 692 participants with 9 forms of vasculitis completed the IPQ-R. For 6 out of 8 IPQ-R dimensions, there were no significant differences in mean scores between the different vasculitides. Scores in identity and cyclical dimensions were significantly higher in Behçet’s disease compared to other types of vasculitis (13.5 vs 10.7; 4.0 vs 3.2, pvasculitis, and younger age is a risk factor for negative illness perceptions. Illness perceptions explain differences in fatigue scores beyond what can be explained by measures of disease activity. PMID:23861259

Generalised Assignment Matrix Methodology in Linear Programming

Science.gov (United States)

Jerome, Lawrence

2012-01-01

Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…

Solution of systems of linear algebraic equations by the method of summation of divergent series

International Nuclear Information System (INIS)

Kirichenko, G.A.; Korovin, Ya.S.; Khisamutdinov, M.V.; Shmojlov, V.I.

2015-01-01

A method for solving systems of linear algebraic equations has been proposed on the basis on the summation of the corresponding continued fractions. The proposed algorithm for solving systems of linear algebraic equations is classified as direct algorithms providing an exact solution in a finite number of operations. Examples of solving systems of linear algebraic equations have been presented and the effectiveness of the algorithm has been estimated [ru

The duality of health technology in chronic illness: how designers envision our future.

Science.gov (United States)

Lehoux, Pascale

2008-06-01

This essay critically explores the role of technological innovation in the constitution of chronic states and illness. Drawing on the co-construction of technology and society perspective, it focuses more specifically on the way in which innovation designers envisage the enhancement of the chronically ill and build certain kinds of socio-technical configuration to deal with chronic illness. Using the case of ;intelligent distance patient monitoring' as an illustration, the paper argues that technology creates as much as it solves the problem of chronic illness. Technology is recursively embedded in chronic illness and it generates dual effects: it constrains and sustains users' daily practices. Only by recognizing technology's duality and eventually transcending it will research and policy initiatives be able to deal creatively and responsibly with the design of our future health experiences.

Linear Programming and Network Flows

CERN Document Server

Bazaraa, Mokhtar S; Sherali, Hanif D

2011-01-01

The authoritative guide to modeling and solving complex problems with linear programming-extensively revised, expanded, and updated The only book to treat both linear programming techniques and network flows under one cover, Linear Programming and Network Flows, Fourth Edition has been completely updated with the latest developments on the topic. This new edition continues to successfully emphasize modeling concepts, the design and analysis of algorithms, and implementation strategies for problems in a variety of fields, including industrial engineering, management science, operations research

Class differences in the social consequences of illness?

DEFF Research Database (Denmark)

Lindholm, C; Burström, B; Diderichsen, F

2002-01-01

with eight years interval 1979-89 and 1986-97. Sociodemographic characteristics, self reported longstanding illness, employment situation and financial conditions were measured at baseline. Social consequences (economic inactivity, unemployment, financial difficulties) of limiting longstanding illness were......STUDY OBJECTIVE: To investigate adverse social consequences of limiting longstanding illness and the modifying effect of socioeconomic position on these consequences. DESIGN: Cohort study on the panel within the annual Swedish Survey of Living Conditions where participants were interviewed twice...

Stopping test of iterative methods for solving PDE

International Nuclear Information System (INIS)

Wang Bangrong

1991-01-01

In order to assure the accuracy of the numerical solution of the iterative method for solving PDE (partial differential equation), the stopping test is very important. If the coefficient matrix of the system of linear algebraic equations is strictly diagonal dominant or irreducible weakly diagonal dominant, the stopping test formulas of the iterative method for solving PDE is proposed. Several numerical examples are given to illustrate the applications of the stopping test formulas

A multiple-scale power series method for solving nonlinear ordinary differential equations

Directory of Open Access Journals (Sweden)

Chein-Shan Liu

2016-02-01

Full Text Available The power series solution is a cheap and effective method to solve nonlinear problems, like the Duffing-van der Pol oscillator, the Volterra population model and the nonlinear boundary value problems. A novel power series method by considering the multiple scales $R_k$ in the power term $(t/R_k^k$ is developed, which are derived explicitly to reduce the ill-conditioned behavior in the data interpolation. In the method a huge value times a tiny value is avoided, such that we can decrease the numerical instability and which is the main reason to cause the failure of the conventional power series method. The multiple scales derived from an integral can be used in the power series expansion, which provide very accurate numerical solutions of the problems considered in this paper.

Object matching using a locally affine invariant and linear programming techniques.

Science.gov (United States)

Li, Hongsheng; Huang, Xiaolei; He, Lei

2013-02-01

In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.

Solving Conic Systems via Projection and Rescaling

OpenAIRE

Pena, Javier; Soheili, Negar

2015-01-01

We propose a simple projection and rescaling algorithm to solve the feasibility problem \\[ \\text{ find } x \\in L \\cap \\Omega, \\] where $L$ and $\\Omega$ are respectively a linear subspace and the interior of a symmetric cone in a finite-dimensional vector space $V$. This projection and rescaling algorithm is inspired by previous work on rescaled versions of the perceptron algorithm and by Chubanov's projection-based method for linear feasibility problems. As in these predecessors, each main it...

MPE inference in conditional linear gaussian networks

DEFF Research Database (Denmark)

Salmerón, Antonio; Rumí, Rafael; Langseth, Helge

2015-01-01

Given evidence on a set of variables in a Bayesian network, the most probable explanation (MPE) is the problem of finding a configuration of the remaining variables with maximum posterior probability. This problem has previously been addressed for discrete Bayesian networks and can be solved using...

An Application of Linear Algebra over Lattices

Directory of Open Access Journals (Sweden)

M. Hosseinyazdi

2008-03-01

Full Text Available In this paper, first we consider L n as a semimodule over a complete bounded distributive lattice L. Then we define the basic concepts of module theory for L n. After that, we proved many similar theorems in linear algebra for the space L n. An application of linear algebra over lattices for solving linear systems, was given

Controls/CFD Interdisciplinary Research Software Generates Low-Order Linear Models for Control Design From Steady-State CFD Results

Science.gov (United States)

Melcher, Kevin J.

1997-01-01

somewhat so that linear models can also be generated from two- and three-dimensional steady-state results. Standard techniques are adequate for reducing the order of one-dimensional CFD-based linear models. However, reduction of linear models based on two- and three-dimensional CFD results is complicated by very sparse, ill-conditioned matrices. Some novel approaches are being investigated to solve this problem.

Do informal caregivers in mental illness feel more burdened? A comparative study of mental versus somatic illnesses.

Science.gov (United States)

Hastrup, Lene H; Van Den Berg, Bernard; Gyrd-Hansen, Dorte

2011-08-01

This study investigates a possible added subjective burden among informal caregivers to care recipients with a mental illness or a combination of mental and somatic illnesses compared with caregivers to care recipients with a somatic illness. The study also investigates the subjective caregiver burden by caregivers' characteristics and objective burden. The association between subjective caregiver burden and socio-demographic factors, objective burden, and health-related quality of life was analyzed in a population of 865 Dutch informal caregivers, using multiple linear regression analysis. Controlling for other factors in the analysis, we found that caring for a recipient with mental illness or a combination of mental and somatic illness was associated with an extra subjective caregiver burden (measured by Caregiver Strain Index). Objective burden, in terms of more than 50 hours of care provision per week, less than three years of caregiving, or living together with the care recipients was associated with higher subjective caregiver burden. Other factors associated with higher subjective caregiver burden were being partners or a child of care recipient, having a paid job, a low health-related quality of life (EQ-5D), or having an illness. This study suggests that caregivers to care recipients with a mental and especially a combination of mental and somatic illnesses have a higher subjective caregiver burden compared with caregivers to care recipients with a somatic illness. Because the study is not representative of all caregivers, more research focusing on identifying and contacting informal caregivers is needed to confirm the result.

Particle Dynamics under Quasi-linear Interaction with Electromagnetic Waves

Energy Technology Data Exchange (ETDEWEB)

Castejon, F.; Eguilior, S.

2003-07-01

Langevin equations for quasi-linear wave particle interaction are obtained taking advantage of the unique vocal equivalence between Fokker-Plank equation and the former ones. Langevin equations are solved numerically and, hence, the evolution of a single particle embedded in an electromagnetic field in momentum space is obtained. The equations are relativistic and valid for any wave. It is also shown that the stochastic part of the equations is negligible in comparison with the deterministic term, except for the momentum to the resonance condition for the main parallel refractive index. (Author) 24 refs.

Particle Dynamics under Quasi-linear Interaction with Electromagnetic Waves

International Nuclear Information System (INIS)

Castejon, F.; Eguilior, S.

2003-01-01

Langevin equations for quasi-linear wave particle interaction are obtained taking advantage of the unique vocal equivalence between Fokker-Plank equation and the former ones. Langevin equations are solved numerically and, hence, the evolution of a single particle embedded in an electromagnetic field in momentum space is obtained. The equations are relativistic and valid for any wave. It is also shown that the stochastic part of the equations is negligible in comparison with the deterministic term, except for the momentum to the resonance condition for the main parallel refractive index. (Author) 24 refs

Menu-Driven Solver Of Linear-Programming Problems

Science.gov (United States)

Viterna, L. A.; Ferencz, D.

1992-01-01

Program assists inexperienced user in formulating linear-programming problems. A Linear Program Solver (ALPS) computer program is full-featured LP analysis program. Solves plain linear-programming problems as well as more-complicated mixed-integer and pure-integer programs. Also contains efficient technique for solution of purely binary linear-programming problems. Written entirely in IBM's APL2/PC software, Version 1.01. Packed program contains licensed material, property of IBM (copyright 1988, all rights reserved).

An intuitionistic fuzzy multi-objective non-linear programming model for sustainable irrigation water allocation under the combination of dry and wet conditions

Science.gov (United States)

Li, Mo; Fu, Qiang; Singh, Vijay P.; Ma, Mingwei; Liu, Xiao

2017-12-01

Water scarcity causes conflicts among natural resources, society and economy and reinforces the need for optimal allocation of irrigation water resources in a sustainable way. Uncertainties caused by natural conditions and human activities make optimal allocation more complex. An intuitionistic fuzzy multi-objective non-linear programming (IFMONLP) model for irrigation water allocation under the combination of dry and wet conditions is developed to help decision makers mitigate water scarcity. The model is capable of quantitatively solving multiple problems including crop yield increase, blue water saving, and water supply cost reduction to obtain a balanced water allocation scheme using a multi-objective non-linear programming technique. Moreover, it can deal with uncertainty as well as hesitation based on the introduction of intuitionistic fuzzy numbers. Consideration of the combination of dry and wet conditions for water availability and precipitation makes it possible to gain insights into the various irrigation water allocations, and joint probabilities based on copula functions provide decision makers an average standard for irrigation. A case study on optimally allocating both surface water and groundwater to different growth periods of rice in different subareas in Heping irrigation area, Qing'an County, northeast China shows the potential and applicability of the developed model. Results show that the crop yield increase target especially in tillering and elongation stages is a prevailing concern when more water is available, and trading schemes can mitigate water supply cost and save water with an increased grain output. Results also reveal that the water allocation schemes are sensitive to the variation of water availability and precipitation with uncertain characteristics. The IFMONLP model is applicable for most irrigation areas with limited water supplies to determine irrigation water strategies under a fuzzy environment.

Clinical Reasoning Terms Included in Clinical Problem Solving Exercises?

Science.gov (United States)

Musgrove, John L; Morris, Jason; Estrada, Carlos A; Kraemer, Ryan R

2016-05-01

Background Published clinical problem solving exercises have emerged as a common tool to illustrate aspects of the clinical reasoning process. The specific clinical reasoning terms mentioned in such exercises is unknown. Objective We identified which clinical reasoning terms are mentioned in published clinical problem solving exercises and compared them to clinical reasoning terms given high priority by clinician educators. Methods A convenience sample of clinician educators prioritized a list of clinical reasoning terms (whether to include, weight percentage of top 20 terms). The authors then electronically searched the terms in the text of published reports of 4 internal medicine journals between January 2010 and May 2013. Results The top 5 clinical reasoning terms ranked by educators were dual-process thinking (weight percentage = 24%), problem representation (12%), illness scripts (9%), hypothesis generation (7%), and problem categorization (7%). The top clinical reasoning terms mentioned in the text of 79 published reports were context specificity (n = 20, 25%), bias (n = 13, 17%), dual-process thinking (n = 11, 14%), illness scripts (n = 11, 14%), and problem representation (n = 10, 13%). Context specificity and bias were not ranked highly by educators. Conclusions Some core concepts of modern clinical reasoning theory ranked highly by educators are mentioned explicitly in published clinical problem solving exercises. However, some highly ranked terms were not used, and some terms used were not ranked by the clinician educators. Effort to teach clinical reasoning to trainees may benefit from a common nomenclature of clinical reasoning terms.

How to deal with burden of critical illness: A comparison of strategies in different areas of China.

Science.gov (United States)

Liu, Pengcheng; Jiang, Liwen; Li, Chengyue; Sun, Mei; Rieger, Alexander; Hao, Mo

2014-05-01

This article aims to introduce, compare and analyze the design and development of Critical Illness Insurance systems in different parts of China under different social and economic conditions, to explain their characteristics and similarities. It may provide references to other countries, especially developing countries, to solve the problem of high medical costs. According to the methods in Comparative Economics, 3 areas (Taicang in Jiangsu, Zhanjiang in Guangdong, Xunyi in Shanxi) which are in high, medium and low socio-economic condition respectively were chosen in China. Their critical illness insurance systems were analyzed in the study. Each system shares several common points, including coordinating urban and rural medical insurance fund, financing from the basic medical insurance surplus, and exploring payment reform and so on. But in the way of management, Taicang and Zhanjiang cooperate with commercial insurance agencies, but Xunyi chooses autonomous management by government. In Xunyi, multi-channel financing is relatively more dispersed, while funds of Taicang and Zhanjiang are mainly from the basic medical insurance surplus. The specific method of payment is different among these three areas. Because of the differences in economic development, population structure, and sources of funds, each area took their own mode on health policy orientation, financing, payment, coverage, and fund management to design their Critical Illness Insurance systems. This might provide references to other areas in China and other developing countries in the world.

Two pathographies: a study in illness and literature.

Science.gov (United States)

Hawkins, A

1984-08-01

This study compares two autobiographical descriptions of illness--the seventeenth-century John Donne's Devotions Upon Emergent Occasions and the twentieth-century Cornelius and Kathryn Ryan's A Private Battle. I begin by identifying the basic structure in both narratives as parallel to that of the case history, and then show how each individual's experience is shaped by the conditions of illness appropriate to their respective cultures. Lastly, I discuss the way in which both authors understand and represent sickness, as well as their respective therapies, in terms of a particular metaphoric construct: for Donne, it is the analogy between illness of the body and illness of the soul; for Ryan it is the analogy between illness and war. The stance of each towards his illness is conditioned by this metaphoric model: Donne's is one of acceptance, of conforming to the will of God; Ryan's is one of resistance, of fighting heroically until the very end. Thus these metaphors are functional as well as aesthetic: they serve as figural modalities whereby the patient/author hopes to transcend his illness.

Chronic conditions, fluid states: chronicity and the anthropology of illness

National Research Council Canada - National Science Library

Manderson, Lenore; Smith-Morris, Carolyn

2010-01-01

.... Breaking new ground in medical anthropology by challenging the chronic/acute divide in illness and disease, the editors, along with a group of rising scholars and some of the most influential minds...

A semi-analytical iterative technique for solving chemistry problems

Directory of Open Access Journals (Sweden)

Majeed Ahmed AL-Jawary

2017-07-01

Full Text Available The main aim and contribution of the current paper is to implement a semi-analytical iterative method suggested by Temimi and Ansari in 2011 namely (TAM to solve two chemical problems. An approximate solution obtained by the TAM provides fast convergence. The current chemical problems are the absorption of carbon dioxide into phenyl glycidyl ether and the other system is a chemical kinetics problem. These problems are represented by systems of nonlinear ordinary differential equations that contain boundary conditions and initial conditions. Error analysis of the approximate solutions is studied using the error remainder and the maximal error remainder. Exponential rate for the convergence is observed. For both problems the results of the TAM are compared with other results obtained by previous methods available in the literature. The results demonstrate that the method has many merits such as being derivative-free, and overcoming the difficulty arising in calculating Adomian polynomials to handle the non-linear terms in Adomian Decomposition Method (ADM. It does not require to calculate Lagrange multiplier in Variational Iteration Method (VIM in which the terms of the sequence become complex after several iterations, thus, analytical evaluation of terms becomes very difficult or impossible in VIM. No need to construct a homotopy in Homotopy Perturbation Method (HPM and solve the corresponding algebraic equations. The MATHEMATICA® 9 software was used to evaluate terms in the iterative process.

DESIGN OF EDUCATIONAL PROBLEMS ON LINEAR PROGRAMMING USING SYSTEMS OF COMPUTER MATHEMATICS

Directory of Open Access Journals (Sweden)

Volodymyr M. Mykhalevych

2013-11-01

Full Text Available From a perspective of the theory of educational problems a problem of substitution in the conditions of ICT use of one discipline by an educational problem of another discipline is represented. Through the example of mathematical problems of linear programming it is showed that a student’s method of operation in the course of an educational problem solving is determinant in the identification of an educational problem in relation to a specific discipline: linear programming, informatics, mathematical modeling, methods of optimization, automatic control theory, calculus etc. It is substantiated the necessity of linear programming educational problems renovation with the purpose of making students free of bulky similar arithmetic calculations and notes which often becomes a barrier to a deeper understanding of key ideas taken as a basis of algorithms used by them.

The Effect of Dimensions of Illness Perceptions on the Variation of Quality of Life in Patients With Coronary Artery Disease

Directory of Open Access Journals (Sweden)

Maryam Sadat Madani

2018-03-01

Full Text Available According to previous studies in patients with Coronary artery disease (CAD, it is important to consider both medical conditions and psychological factors such as illness perceptions to explain differences in Health-Related Quality of Life (HRQoL. Patient’s illness perception is formed based on Patient’s beliefs and perceived information about their conditions, presumably influencing the individual’s mental health and how the patients deal with the medical conditions. The objective of this study was to analyze the relationship between illness perception and quality of life in patients with CAD. In this cross-sectional study, 99 CAD patients filled out questionnaires, including the brief illness perception questionnaire, the Health-related quality of life scale (SF36. The data were analyzed using multiple linear regression.When corrected for confounders, identity (β=−0.47 was  associated with Physical Component (PCS. Identity  and age explained 53% of the variation in PCS (R2=0.53. Personal control (β=0.20, identity (β=−0.23 and Emotional response (β=−0.25  were associated with Mental Component (MCS. They explained 47% of the variation in the Mental Component (R2=0.47 domain. This study showed that there is a relationship between illness perception and quality of life in patients with CAD. Better HRQoL was found in patients who have a better understanding of the disease, experience better personal control, and have less of a physical and mental response. Results from this study provide starting points for the development of interventions focusing on illness perceptions to support CAD patients in their disease management and to improve HRQoL.

Illness narratives of people who are homeless

Directory of Open Access Journals (Sweden)

Cecilia Håkanson

2016-11-01

Full Text Available Multiple illnesses are common in all homeless populations. While most previous studies have focused on experiences of mental illness, there is a scarcity of studies about experiences of bodily illness among people who are homeless. This study aimed to explore illness narratives of people who are homeless, and how homelessness as a social context shapes the experience of multiple and/or advancing somatic conditions. The design was a qualitative single-case study, using interpretive description. Data were generated through interviews, with nine participants who were homeless rough sleepers in Stockholm, Sweden, recruited while receiving care in a support home for homeless people with complex care needs. The findings revealed experiences of illness embedded in narratives about falling ill, being ill, and the future. The particularity of these illness narratives and the way that they are shaped by homelessness give rise to several observations: the necessity of a capable body for survival; chaos and profound solitude in illness and self-care management; ambiguous feelings about receiving care, transitioning from independence, and “freedom” in the streets to dependency and being institutionalized; and finally, the absence of hope and desire for recovery or a better future. The narratives are discussed from the perspective of Frank's four types of illness stories (restitution, chaos, quest, and testimony. The findings stress that to provide appropriate care and support to people who are homeless and have multiple and/or advancing somatic conditions, health care professionals need to be informed both about the individual's biography and about the circumstances under which illness and self-care takes place in the streets.

Variational iteration method for solving coupled-KdV equations

International Nuclear Information System (INIS)

Assas, Laila M.B.

2008-01-01

In this paper, the He's variational iteration method is applied to solve the non-linear coupled-KdV equations. This method is based on the use of Lagrange multipliers for identification of optimal value of a parameter in a functional. This technique provides a sequence of functions which converge to the exact solution of the coupled-KdV equations. This procedure is a powerful tool for solving coupled-KdV equations

Preconditioned Iterative Methods for Solving Weighted Linear Least Squares Problems

Czech Academy of Sciences Publication Activity Database

Bru, R.; Marín, J.; Mas, J.; Tůma, Miroslav

2014-01-01

Roč. 36, č. 4 (2014), A2002-A2022 ISSN 1064-8275 Institutional support: RVO:67985807 Keywords : preconditioned iterative methods * incomplete decompositions * approximate inverses * linear least squares Subject RIV: BA - General Mathematics Impact factor: 1.854, year: 2014

Coping strategies of caregivers towards aggressive behaviors of persons with severe mental illness.

Science.gov (United States)

Madathumkovilakath, Neethu Bhaskaran; Kizhakkeppattu, Sindhu; Thekekunnath, Saleem; Kazhungil, Firoz

2018-04-24

Aggression is one of the chief determinants of caregiver burden in severe mental illnesses. Clinical and treatment implications of aggression in mental illness are predominantly studied in perspectives of mental health care professionals. Coping style of caregivers towards aggression of persons with mental illness is understudied. So we studied coping strategies used by caregivers of patients with severe mental illness towards aggressive behaviors of patients and relationship between aggressive behavior and coping strategies. We assessed two hundreds and seventy caregivers of patients with severe mental illness attending outpatient psychiatry department using Modified Overt Aggression Scale and the Ways of Coping Scale - revised. 95.6% of the caregivers perceived verbal aggression followed by aggression against property (67%), auto aggression (33.7%) and physical aggression (25.6%). The study revealed that adaptive coping strategies - planful problem solving and seeking social support were used by 40% each of caregivers to deal with aggressive behavior. Only 4.4% of caregivers resorted to escape avoidance which is maladaptive coping strategy. Though adaptive strategies were used by caregivers these were not used in appropriate situations. Physical aggression and aggression against property were not significantly associated with planful problem solving (r = 0.105; p = 0.08 and r = 0.110; p = 0.07 respectively). But verbal aggression, aggression against property and physical aggression were associated with escape avoidance (r = 0.152; p = 0.01 and r = 0.168; p = 0.01 and r = 0.23; p = mental illness is maladaptive with respect to aggression. Coping skills training would play a major role to address this issue. Copyright © 2018 Elsevier B.V. All rights reserved.

Minimizing the ILL-conditioning in the analysis by gamma radiation

Energy Technology Data Exchange (ETDEWEB)

Cardoso, Halisson Alberdan C.; Melo, Silvio de Barros; Dantas, Carlos; Lima, Emerson Alexandre; Silva, Ricardo Martins; Moreira, Icaro Valgueiro M., E-mail: hacc@cin.ufpe.br, E-mail: sbm@cin.ufpe.br, E-mail: rmas@cin.ufpe.br, E-mail: ivmm@cin.ufpe.br, E-mail: ccd@ufpe.br, E-mail: eal@cin.ufpe.br [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil); Meric, Ilker, E-mail: lker.Meric@ift.uib.no [University Of Bergen (Norway)

2015-07-01

A non-invasive method which can be employed for elemental analysis is the Prompt-Gamma Neutron Activation Analysis. The aim is to estimate the mass fractions of the different constituent elements present in the unknown sample basing its estimations on the energies of all the photopeaks in their spectra. Two difficulties arise in this approach: the constituents are unknown, and the composed spectrum of the unknown sample is a nonlinear combination of the spectra of its constituents (which are called libraries). An iterative method that has become popular is the Monte Carlo Library Least Squares. One limitation with this method is that the amount of noise present in the spectra is not negligible, and the magnitude differences in the photon counting produce a bad conditioning in the covariance matrix employed by the least squares method, affecting the numerical stability of the method. A method for minimizing the numerical instability provoked by noisy spectra is proposed. Corresponding parts of different spectra are selected as to minimize the condition number of the resulting covariance matrix. This idea is supported by the assumption that the unknown spectrum is a linear combination of its constituent's spectra, and the fact that the amount of constituents is so small (typically ve of them). The selection of spectrum parts is done through Greedy Randomized Adaptive Search Procedures, where the cost function is the condition number that derives from the covariance matrix produced out of the selected parts. A QR factorization is also applied to the nal covariance matrix to reduce further its condition number, and transferring part of its bad conditioning to the basis conversion matrix. (author)

Minimizing the ILL-conditioning in the analysis by gamma radiation

International Nuclear Information System (INIS)

Cardoso, Halisson Alberdan C.; Melo, Silvio de Barros; Dantas, Carlos; Lima, Emerson Alexandre; Silva, Ricardo Martins; Moreira, Icaro Valgueiro M.; Meric, Ilker

2015-01-01

A non-invasive method which can be employed for elemental analysis is the Prompt-Gamma Neutron Activation Analysis. The aim is to estimate the mass fractions of the different constituent elements present in the unknown sample basing its estimations on the energies of all the photopeaks in their spectra. Two difficulties arise in this approach: the constituents are unknown, and the composed spectrum of the unknown sample is a nonlinear combination of the spectra of its constituents (which are called libraries). An iterative method that has become popular is the Monte Carlo Library Least Squares. One limitation with this method is that the amount of noise present in the spectra is not negligible, and the magnitude differences in the photon counting produce a bad conditioning in the covariance matrix employed by the least squares method, affecting the numerical stability of the method. A method for minimizing the numerical instability provoked by noisy spectra is proposed. Corresponding parts of different spectra are selected as to minimize the condition number of the resulting covariance matrix. This idea is supported by the assumption that the unknown spectrum is a linear combination of its constituent's spectra, and the fact that the amount of constituents is so small (typically ve of them). The selection of spectrum parts is done through Greedy Randomized Adaptive Search Procedures, where the cost function is the condition number that derives from the covariance matrix produced out of the selected parts. A QR factorization is also applied to the nal covariance matrix to reduce further its condition number, and transferring part of its bad conditioning to the basis conversion matrix. (author)

A simplified multi-particle model for lithium ion batteries via a predictor-corrector strategy and quasi-linearization

International Nuclear Information System (INIS)

Li, Xiaoyu; Fan, Guodong; Rizzoni, Giorgio; Canova, Marcello; Zhu, Chunbo; Wei, Guo

2016-01-01

The design of a simplified yet accurate physics-based battery model enables researchers to accelerate the processes of the battery design, aging analysis and remaining useful life prediction. In order to reduce the computational complexity of the Pseudo Two-Dimensional mathematical model without sacrificing the accuracy, this paper proposes a simplified multi-particle model via a predictor-corrector strategy and quasi-linearization. In this model, a predictor-corrector strategy is used for updating two internal states, especially used for solving the electrolyte concentration approximation to reduce the computational complexity and reserve a high accuracy of the approximation. Quasi-linearization is applied to the approximations of the Butler-Volmer kinetics equation and the pore wall flux distribution to predict the non-uniform electrochemical reaction effects without using any nonlinear iterative solver. Simulation and experimental results show that the isothermal model and the model coupled with thermal behavior are greatly improve the computational efficiency with almost no loss of accuracy. - Highlights: • A simplified multi-particle model with high accuracy and computation efficiency is proposed. • The electrolyte concentration is solved based on a predictor-corrector strategy. • The non-uniform electrochemical reaction is solved based on quasi-linearization. • The model is verified by simulations and experiments at various operating conditions.

Shared decision making among parents of children with mental health conditions compared to children with chronic physical conditions.

Science.gov (United States)

Butler, Ashley M; Elkins, Sara; Kowalkowski, Marc; Raphael, Jean L

2015-02-01

High quality care in pediatrics involves shared decision making (SDM) between families and providers. The extent to which children with common mental health disorders experience SDM is not well known. The objectives of this study were to examine how parent-reported SDM varies by child health (physical illness, mental health condition, and comorbid mental and physical conditions) and to examine whether medical home care attenuates any differences. We analyzed data on children (2-17 years) collected through the 2009/2010 National Survey of Children with Special Health Care Needs. The sample consisted of parents of children in one of three child health categories: (1) children with a chronic physical illness but no mental health condition; (2) children with a common mental health condition but no chronic physical condition; and (3) children with comorbid mental and chronic physical conditions. The primary dependent variable was parent-report of provider SDM. The primary independent variable was health condition category. Multivariate linear regression analyses were conducted. Multivariate analyses controlling for sociodemographic variables and parent-reported health condition impact indicated lower SDM among children with a common mental health condition-only (B = -0.40; p mental health condition-only were no longer significant in the model adjusting for medical home care. However, differences in SDM for children with comorbid conditions persisted after adjusting for medical home care. Increasing medical home care may help mitigate differences in SDM for children with mental health conditions-only. Other interventions may be needed to improve SDM among children with comorbid mental and physical conditions.

Intuitionistic Fuzzy Goal Programming Technique for Solving Non-Linear Multi-objective Structural Problem

Directory of Open Access Journals (Sweden)

Samir Dey

2015-07-01

Full Text Available This paper proposes a new multi-objective intuitionistic fuzzy goal programming approach to solve a multi-objective nonlinear programming problem in context of a structural design. Here we describe some basic properties of intuitionistic fuzzy optimization. We have considered a multi-objective structural optimization problem with several mutually conflicting objectives. The design objective is to minimize weight of the structure and minimize the vertical deflection at loading point of a statistically loaded three-bar planar truss subjected to stress constraints on each of the truss members. This approach is used to solve the above structural optimization model based on arithmetic mean and compare with the solution by intuitionistic fuzzy goal programming approach. A numerical solution is given to illustrate our approach.

Krylov Subspace Methods for Complex Non-Hermitian Linear Systems. Thesis

Science.gov (United States)

Freund, Roland W.

1991-01-01

We consider Krylov subspace methods for the solution of large sparse linear systems Ax = b with complex non-Hermitian coefficient matrices. Such linear systems arise in important applications, such as inverse scattering, numerical solution of time-dependent Schrodinger equations, underwater acoustics, eddy current computations, numerical computations in quantum chromodynamics, and numerical conformal mapping. Typically, the resulting coefficient matrices A exhibit special structures, such as complex symmetry, or they are shifted Hermitian matrices. In this paper, we first describe a Krylov subspace approach with iterates defined by a quasi-minimal residual property, the QMR method, for solving general complex non-Hermitian linear systems. Then, we study special Krylov subspace methods designed for the two families of complex symmetric respectively shifted Hermitian linear systems. We also include some results concerning the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.

Simplified Linear Equation Solvers users manual

Energy Technology Data Exchange (ETDEWEB)

Gropp, W. [Argonne National Lab., IL (United States); Smith, B. [California Univ., Los Angeles, CA (United States)

1993-02-01

The solution of large sparse systems of linear equations is at the heart of many algorithms in scientific computing. The SLES package is a set of easy-to-use yet powerful and extensible routines for solving large sparse linear systems. The design of the package allows new techniques to be used in existing applications without any source code changes in the applications.

A controlled trial of trauma-focused therapy versus problem-solving in Islamic children affected by civil conflict and disaster in Aceh, Indonesia.

Science.gov (United States)

Dawson, Katie; Joscelyne, Amy; Meijer, Catherine; Steel, Zachary; Silove, Derrick; Bryant, Richard A

2018-03-01

To evaluate the relative efficacies of trauma-focused cognitive behavior therapy and problem-solving therapy in treating post-traumatic stress disorder in children affected by civil conflict in Aceh, Indonesia. A controlled trial of children with post-traumatic stress disorder ( N = 64) randomized children to either five individual weekly sessions of trauma-focused cognitive behavior therapy or problem-solving therapy provided by lay-counselors who were provided with brief training. Children were assessed by blind independent assessors at pretreatment, posttreatment and 3-month follow-up on post-traumatic stress disorder, depression and anger, as well as caregiver ratings of the child's post-traumatic stress disorder levels. Intent-to-treat analyses indicated no significant linear time × treatment condition interaction effects for post-traumatic stress disorder at follow-up ( t(129.05) = -0.55, p = 0.58), indicating the two conditions did not differ. Across both conditions, there were significant reductions in post-traumatic stress disorder on self-reported ( t(131.26) = -9.26, p solving: 2.68, 95% confidence interval = [2.07, 3.29]). These findings suggest that trauma-focused cognitive behavior therapy and problem-solving approaches are comparably successful in reducing post-traumatic stress disorder and anger in treating mental health in children in a post-conflict setting. This pattern may reflect the benefits of non-specific therapy effects or gains associated with trauma-focused or problem-solving approaches.

An optimal iterative algorithm to solve Cauchy problem for Laplace equation

KAUST Repository

Majeed, Muhammad Usman

2015-05-25

An optimal mean square error minimizer algorithm is developed to solve severely ill-posed Cauchy problem for Laplace equation on an annulus domain. The mathematical problem is presented as a first order state space-like system and an optimal iterative algorithm is developed that minimizes the mean square error in states. Finite difference discretization schemes are used to discretize first order system. After numerical discretization algorithm equations are derived taking inspiration from Kalman filter however using one of the space variables as a time-like variable. Given Dirichlet and Neumann boundary conditions are used on the Cauchy data boundary and fictitious points are introduced on the unknown solution boundary. The algorithm is run for a number of iterations using the solution of previous iteration as a guess for the next one. The method developed happens to be highly robust to noise in Cauchy data and numerically efficient results are illustrated.

Mixed problems for linear symmetric hyperbolic systems with characteristic boundary conditions

International Nuclear Information System (INIS)

Secchi, P.

1994-01-01

We consider the initial-boundary value problem for symmetric hyperbolic systems with characteristic boundary of constant multiplicity. In the linear case we give some results about the existence of regular solutions in suitable functions spaces which take in account the loss of regularity in the normal direction to the characteristic boundary. We also consider the equations of ideal magneto-hydrodynamics under perfectly conducting wall boundary conditions and give some results about the solvability of such mixed problem. (author). 16 refs

A Reduced Dantzig-Wolfe Decomposition for a Suboptimal Linear MPC

DEFF Research Database (Denmark)

Standardi, Laura; Poulsen, Niels Kjølstad; Jørgensen, John Bagterp

2014-01-01

Linear Model Predictive Control (MPC) is an efficient control technique that repeatedly solves online constrained linear programs. In this work we propose an economic linear MPC strategy for operation of energy systems consisting of multiple and independent power units. These systems cooperate...

Plane answers to complex questions the theory of linear models

CERN Document Server

Christensen, Ronald

1987-01-01

This book was written to rigorously illustrate the practical application of the projective approach to linear models. To some, this may seem contradictory. I contend that it is possible to be both rigorous and illustrative and that it is possible to use the projective approach in practical applications. Therefore, unlike many other books on linear models, the use of projections and sub­ spaces does not stop after the general theory. They are used wherever I could figure out how to do it. Solving normal equations and using calculus (outside of maximum likelihood theory) are anathema to me. This is because I do not believe that they contribute to the understanding of linear models. I have similar feelings about the use of side conditions. Such topics are mentioned when appropriate and thenceforward avoided like the plague. On the other side of the coin, I just as strenuously reject teaching linear models with a coordinate free approach. Although Joe Eaton assures me that the issues in complicated problems freq...

Finite-time H∞ control for linear continuous system with norm-bounded disturbance

Science.gov (United States)

Meng, Qingyi; Shen, Yanjun

2009-04-01

In this paper, the definition of finite-time H∞ control is presented. The system under consideration is subject to time-varying norm-bounded exogenous disturbance. The main aim of this paper is focused on the design a state feedback controller which ensures that the closed-loop system is finite-time bounded (FTB) and reduces the effect of the disturbance input on the controlled output to a prescribed level. A sufficient condition is presented for the solvability of this problem, which can be reduced to a feasibility problem involving linear matrix inequalities (LMIs). A detailed solving method is proposed for the restricted linear matrix inequalities. Finally, examples are given to show the validity of the methodology.

Train Repathing in Emergencies Based on Fuzzy Linear Programming

Directory of Open Access Journals (Sweden)

Xuelei Meng

2014-01-01

Full Text Available Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.

Train repathing in emergencies based on fuzzy linear programming.

Science.gov (United States)

Meng, Xuelei; Cui, Bingmou

2014-01-01

Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.

Linear collider: a preview

Energy Technology Data Exchange (ETDEWEB)

Wiedemann, H.

1981-11-01

Since no linear colliders have been built yet it is difficult to know at what energy the linear cost scaling of linear colliders drops below the quadratic scaling of storage rings. There is, however, no doubt that a linear collider facility for a center of mass energy above say 500 GeV is significantly cheaper than an equivalent storage ring. In order to make the linear collider principle feasible at very high energies a number of problems have to be solved. There are two kinds of problems: one which is related to the feasibility of the principle and the other kind of problems is associated with minimizing the cost of constructing and operating such a facility. This lecture series describes the problems and possible solutions. Since the real test of a principle requires the construction of a prototype I will in the last chapter describe the SLC project at the Stanford Linear Accelerator Center.

Linear collider: a preview

International Nuclear Information System (INIS)

Wiedemann, H.

1981-11-01

Since no linear colliders have been built yet it is difficult to know at what energy the linear cost scaling of linear colliders drops below the quadratic scaling of storage rings. There is, however, no doubt that a linear collider facility for a center of mass energy above say 500 GeV is significantly cheaper than an equivalent storage ring. In order to make the linear collider principle feasible at very high energies a number of problems have to be solved. There are two kinds of problems: one which is related to the feasibility of the principle and the other kind of problems is associated with minimizing the cost of constructing and operating such a facility. This lecture series describes the problems and possible solutions. Since the real test of a principle requires the construction of a prototype I will in the last chapter describe the SLC project at the Stanford Linear Accelerator Center

Acute Illness Among Surfers After Exposure to Seawater in Dry- and Wet-Weather Conditions.

Science.gov (United States)

Arnold, Benjamin F; Schiff, Kenneth C; Ercumen, Ayse; Benjamin-Chung, Jade; Steele, Joshua A; Griffith, John F; Steinberg, Steven J; Smith, Paul; McGee, Charles D; Wilson, Richard; Nelsen, Chad; Weisberg, Stephen B; Colford, John M

2017-10-01

Rainstorms increase levels of fecal indicator bacteria in urban coastal waters, but it is unknown whether exposure to seawater after rainstorms increases rates of acute illness. Our objective was to provide the first estimates of rates of acute illness after seawater exposure during both dry- and wet-weather periods and to determine the relationship between levels of indicator bacteria and illness among surfers, a population with a high potential for exposure after rain. We enrolled 654 surfers in San Diego, California, and followed them longitudinally during the 2013-2014 and 2014-2015 winters (33,377 days of observation, 10,081 surf sessions). We measured daily surf activities and illness symptoms (gastrointestinal illness, sinus infections, ear infections, infected wounds). Compared with no exposure, exposure to seawater during dry weather increased incidence rates of all outcomes (e.g., for earache or infection, adjusted incidence rate ratio (IRR) = 1.86, 95% confidence interval (CI): 1.27, 2.71; for infected wounds, IRR = 3.04, 95% CI: 1.54, 5.98); exposure during wet weather further increased rates (e.g., for earache or infection, IRR = 3.28, 95% CI: 1.95, 5.51; for infected wounds, IRR = 4.96, 95% CI: 2.18, 11.29). Fecal indicator bacteria measured in seawater (Enterococcus species, fecal coliforms, total coliforms) were strongly associated with incident illness only during wet weather. Urban coastal seawater exposure increases the incidence rates of many acute illnesses among surfers, with higher incidence rates after rainstorms. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

Treating symptoms or assisting human development: Can different environmental conditions affect personal development for patients with severe mental illness? A qualitative study.

Science.gov (United States)

Lauveng, Arnhild; Tveiten, Sidsel; Ekeland, Tor-Johan; Torleif, Ruud

2016-01-01

Recent research suggests that a basic anomaly in self-experience may be a core factor in patients with severe mental illnesses. Given the importance of sense of self, the traditional treatment of symptoms might not be the most effective for these groups of patients. This qualitative study examines how differences in social environmental conditions, organized as education or treatment, might affect personal development in patients with severe mental illness. A qualitative hermeneutical design was used. Data were collected through qualitative interviews. Informants included 14 patients in psychiatric treatment and 15 students at schools for adults with mental illness. Most informants were interviewed on two occasions, 6-8 months apart, totaling 47 interviews. All participants had been diagnosed with severe mental illness with pronounced impact on daily functioning (most often psychoses or personality disorders) for a minimum of 2 years. Findings and interpretations showed that the students experienced a supportive environment focused mostly on education. They described personal and enduring development in areas such as capacity for relationships, regulation of symptoms, subjective well-being, and integration in society. The patients experienced an environment focused more on treatment of their illness and less on personal development and interests. They described little development, much loneliness, a poor quality of life, an objectifying attitude of themselves and others, and hopelessness. Even if more research is needed, findings indicate that for this group of patients, problems may be closely related to identity development. Therefore, instead of solemnly focusing on specific symptoms, it might be more effective to support patients' personal and social development by offering intensive and lasting social environmental conditions. This includes stable and mutual relationships, intrinsically motivated activities, and an environment that supports personal choices

Solving ill-posed control problems by stabilized finite element methods: an alternative to Tikhonov regularization

Science.gov (United States)

Burman, Erik; Hansbo, Peter; Larson, Mats G.

2018-03-01

Tikhonov regularization is one of the most commonly used methods for the regularization of ill-posed problems. In the setting of finite element solutions of elliptic partial differential control problems, Tikhonov regularization amounts to adding suitably weighted least squares terms of the control variable, or derivatives thereof, to the Lagrangian determining the optimality system. In this note we show that the stabilization methods for discretely ill-posed problems developed in the setting of convection-dominated convection-diffusion problems, can be highly suitable for stabilizing optimal control problems, and that Tikhonov regularization will lead to less accurate discrete solutions. We consider some inverse problems for Poisson’s equation as an illustration and derive new error estimates both for the reconstruction of the solution from the measured data and reconstruction of the source term from the measured data. These estimates include both the effect of the discretization error and error in the measurements.

Have I Ever Done Anything Like This Before? Older Adults Solving Ill-Defined Problems in Intensive Volunteering.

Science.gov (United States)

Cheek, Cheryl; Piercy, Kathleen W; Kohlenberg, Meranda

2015-01-01

This study examined the ways in which individuals over 50 years old solved problems while volunteering in intensive humanitarian and disaster relief service. Thirty-seven men and women in the sample were sponsored by three religious organizations well known for providing humanitarian and disaster relief service. Semistructured interviews yielded data that were analyzed qualitatively, using McCracken's five-step process for analysis. We found that volunteers used three different abilities to solve problems: drawing upon experience to create strategies, maintaining emotional stability in the midst of trying circumstances, and applying strategies in a context-sensitive manner. These findings illustrate that these factors, which are comparable to those used in solving everyday problems, are unique in the way they are applied to intensive volunteering. The volunteers' sharing of knowledge, experience, and support with each other were also noticeable in their accounts of their service. This sharing contributed strongly to their sense of emotional stability and effectiveness in solving problems. © The Author(s) 2015.

Transport equation solving methods

International Nuclear Information System (INIS)

Granjean, P.M.

1984-06-01

This work is mainly devoted to Csub(N) and Fsub(N) methods. CN method: starting from a lemma stated by Placzek, an equivalence is established between two problems: the first one is defined in a finite medium bounded by a surface S, the second one is defined in the whole space. In the first problem the angular flux on the surface S is shown to be the solution of an integral equation. This equation is solved by Galerkin's method. The Csub(N) method is applied here to one-velocity problems: in plane geometry, slab albedo and transmission with Rayleigh scattering, calculation of the extrapolation length; in cylindrical geometry, albedo and extrapolation length calculation with linear scattering. Fsub(N) method: the basic integral transport equation of the Csub(N) method is integrated on Case's elementary distributions; another integral transport equation is obtained: this equation is solved by a collocation method. The plane problems solved by the Csub(N) method are also solved by the Fsub(N) method. The Fsub(N) method is extended to any polynomial scattering law. Some simple spherical problems are also studied. Chandrasekhar's method, collision probability method, Case's method are presented for comparison with Csub(N) and Fsub(N) methods. This comparison shows the respective advantages of the two methods: a) fast convergence and possible extension to various geometries for Csub(N) method; b) easy calculations and easy extension to polynomial scattering for Fsub(N) method [fr

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems.

Science.gov (United States)

Salleh, Faridah Hani Mohamed; Zainudin, Suhaila; Arif, Shereena M

2017-01-01

Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

Solving the relativistic Rankine-Hugoniot condition in the presence of a magnetic field in the astrophysical scenario of a neutron star

International Nuclear Information System (INIS)

Mallick, Ritam

2011-01-01

The Rankine-Hugoniot condition has been solved to study phase transition in an astrophysical scenario mainly in the case of phase transition from a neutron star (NS) to a quark star (QS). The equations of state and temperature play a huge role in determining the nature of the front propagation, which brings about the phase transition in a NS. The shock jump conditions can be solved analytically, but the situation changes drastically by the inclusion of the magnetic field. High magnetic fields, which are always associated with a NS play a huge role in determining the structure and evolution of a NS. So, a magnetic field has been introduced in the shock jump condition in the de Hoffmann-Teller frame. The modified conservation condition for the perpendicular and oblique shocks is obtained in this frame. Numerical solution of the perpendicular shock has been obtained, which shows considerable deviation from the nonmagnetic case. The results show that the magnetic field helps in shock generation. It also indirectly hints at the instability of the matter and thereby the NS for very high magnetic field, implying that NSs can only support a magnetic field of some finite strength.

On the stability, the periodic solutions and the resolution of certain types of non linear equations, and of non linearly coupled systems of these equations, appearing in betatronic oscillations

International Nuclear Information System (INIS)

Valat, J.

1960-12-01

Universal stability diagrams have been calculated and experimentally checked for Hill-Meissner type equations with square-wave coefficients. The study of these equations in the phase-plane has then made it possible to extend the periodic solution calculations to the case of non-linear differential equations with periodic square-wave coefficients. This theory has been checked experimentally. For non-linear coupled systems with constant coefficients, a search was first made for solutions giving an algebraic motion. The elliptical and Fuchs's functions solve such motions. The study of non-algebraic motions is more delicate, apart from the study of nonlinear Lissajous's motions. A functional analysis shows that it is possible however in certain cases to decouple the system and to find general solutions. For non-linear coupled systems with periodic square-wave coefficients it is then possible to calculate the conditions leading to periodic solutions, if the two non-linear associated systems with constant coefficients fall into one of the categories of the above paragraph. (author) [fr

Miniaturized Stretchable and High-Rate Linear Supercapacitors

OpenAIRE

Zhu, Wenjun; Zhang, Yang; Zhou, Xiaoshuang; Xu, Jiang; Liu, Zunfeng; Yuan, Ningyi; Ding, Jianning

2017-01-01

Linear stretchable supercapacitors have attracted much attention because they are well suited to applications in the rapidly expanding field of wearable electronics. However, poor conductivity of the electrode material, which limits the transfer of electrons in the axial direction of the linear supercapacitors, leads to a serious loss of capacity at high rates. To solve this problem, we use gold nanoparticles to decorate aligned multiwall carbon nanotube to fabricate stretchable linear electr...

What is a mental illness? Public views and their effects on attitudes and disclosure.

Science.gov (United States)

Rüsch, Nicolas; Evans-Lacko, Sara; Thornicroft, Graham

2012-07-01

'Mental illness' is a common label. However, the general public may or may not consider various conditions, ranging from major psychiatric disorders to stress, as mental illnesses. It is unclear how such public views affect attitudes towards people with mental illness and reactions to one's own potential mental illness, e.g. in terms of help-seeking or disclosure. In representative English population surveys the classification of six conditions (schizophrenia, bipolar disorder, depression, drug addiction, stress, grief) as a mental illness was assessed as well as attitudes towards, and contact with, people with mental illness, intentions to disclose a mental illness and to seek treatment. A factor analysis of how strongly respondents perceived the six conditions as a mental illness yielded two factors: (i) major psychiatric disorders and (ii) stress- and behaviour-related conditions including drug addiction. In regression analyses, higher scores on the first, but not the second, factor predicted less perceived responsibility of people with mental illness for their actions, and more support for a neurobiological illness model and help-seeking. Classifying stress-related/behaviour-related conditions as mental illnesses, as well as not referring to major psychiatric disorders as mental illnesses, was associated with more negative attitudes and increased social distance, but also with stronger intentions to disclose a mental illness to an employer. Negative attitudes and social distance were also related to ethnic minority status and lower social grade. Referring to major psychiatric disorders as mental illnesses may reflect higher mental health literacy, better attitudes towards people with mental illness and help-seeking. A broader concept of mental illness could, although increasing negative attitudes, facilitate disclosure in the workplace. Public views on what is a mental illness may have context-dependent effects and should be taken into account in anti

Illness causal beliefs in Turkish immigrants

Directory of Open Access Journals (Sweden)

Klimidis Steven

2007-07-01

Full Text Available Abstract Background People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Methods Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Results Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Conclusion Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes

Illness causal beliefs in Turkish immigrants.

Science.gov (United States)

Minas, Harry; Klimidis, Steven; Tuncer, Can

2007-07-24

People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes persists despite modernizing and acculturative influences. Different

Approaches to self-management in chronic illness.

Science.gov (United States)

Novak, Marta; Costantini, Lucia; Schneider, Sabrina; Beanlands, Heather

2013-01-01

Management of a chronic medical condition is a complex process and requires coordinated action between healthcare providers and patients. This process is further complicated by the fact that an increasing number of patients suffer from multiple chronic conditions. Self-management involves active participation of the patients in the everyday care of the symptoms of their illness(es) and medical treatments, as well as maintaining general health and prevention of progression of medical conditions. Managing the psychosocial consequences of illness is also an important component of self-management. Data have demonstrated that enhancing self-management improves quality of life, coping, symptom management, disability, and reduces healthcare expenditures and service utilization. To foster self-management, potential barriers to implementation as well as facilitators and supports for this approach must be acknowledged. In this article, we review various aspects of self-management in chronic illness, focusing on chronic kidney disease. Better understanding of these concepts will facilitate patient-provider collaboration, improve patient care with increased patient and staff satisfaction, and may ultimately result in better clinical outcomes and enhanced quality of life for both the patients and their families. © 2013 Wiley Periodicals, Inc.

An overset grid approach to linear wave-structure interaction

DEFF Research Database (Denmark)

Read, Robert; Bingham, Harry B.

2012-01-01

A finite-difference based approach to wave-structure interaction is reported that employs the overset approach to grid generation. A two-dimensional code that utilizes the Overture C++ library has been developed to solve the linear radiation problem for a floating body of arbitrary form. This sof......A finite-difference based approach to wave-structure interaction is reported that employs the overset approach to grid generation. A two-dimensional code that utilizes the Overture C++ library has been developed to solve the linear radiation problem for a floating body of arbitrary form...

[Profile of social problem solving and coping profile in anxious and depressed Chileans].

Science.gov (United States)

Kramp, Uwe

2012-11-01

According to the Pan American Health Organization and the World Health Organization, in 2020, depression will become the second cause of disability worldwide. In Chile, anxiety and depressive disorders account for almost 28% of the total years of healthy life lost due to illness. This research seeks to explore a profile of social problem solving and coping present in people who suffer from anxious and depressive symptoms. The sample consisted of 1179 analogous Chilean participants (55.9% women), with a mean of 22.23 years (range between 18-48 years). The results suggest statistically significant differences for all social problem solving and coping strategies evaluated. Thus, if anxious or depressive symptoms increase, social problem solving or coping strategies become less adaptive.

2010 Pantex Plant Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-06-29

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2007 Hanford Site Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety, and Security

2009-07-16

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Pantex Plant Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-05-19

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Hanford Site Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-05-14

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Hanford Site Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-10-05

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2007 Pantex Plant Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-07-31

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

Numerical Methods for Solution of the Extended Linear Quadratic Control Problem

DEFF Research Database (Denmark)

Jørgensen, John Bagterp; Frison, Gianluca; Gade-Nielsen, Nicolai Fog

2012-01-01

In this paper we present the extended linear quadratic control problem, its efficient solution, and a discussion of how it arises in the numerical solution of nonlinear model predictive control problems. The extended linear quadratic control problem is the optimal control problem corresponding...... to the Karush-Kuhn-Tucker system that constitute the majority of computational work in constrained nonlinear and linear model predictive control problems solved by efficient MPC-tailored interior-point and active-set algorithms. We state various methods of solving the extended linear quadratic control problem...... and discuss instances in which it arises. The methods discussed in the paper have been implemented in efficient C code for both CPUs and GPUs for a number of test examples....

Case Designs for Ill-Structured Problems: Analysis and Implications for Practice

Science.gov (United States)

Dabbagh, Nada; Blijd, Cecily Williams

2009-01-01

This study is a third in a series of studies that examined students' information seeking and problem solving behaviors while interacting with one of two types of web-based representations of an ill-structured instructional design case: hierarchical (tree-like) and heterarchical (network-like). A Java program was used to track students' hypermedia…

Psychosocial conditions on and off the job and psychological ill health: depressive symptoms, impaired psychological wellbeing, heavy consumption of alcohol.

Science.gov (United States)

Michélsen, H; Bildt, C

2003-07-01

Psychiatric epidemiology has revealed a number of associations between gender, socioeconomic status, and psychiatric disorders. To examine psychosocial conditions on and off the job in relation to psychological ill health. Longitudinal design with 24 year follow up of employed persons (190 women, 177 men). Interview and questionnaire data on work and leisure conditions were collected in 1969 and 1993. Risk analyses were performed in relation to three outcomes in 1993: depression within the preceding 12 months, impaired psychological wellbeing, and heavy alcohol use. Thirteen per cent of the women and 11% of the men showed symptoms of depression, 21% and 22% had impaired psychological wellbeing, and 7% and 15% respectively were heavy alcohol users. Dissatisfaction with the quality (women) or quantity (men) of social contacts 24 years earlier was a significant risk factor for depression. Dissatisfaction with the quality of social contacts was also associated with impaired psychological wellbeing (among women), and dissatisfaction with leisure time activities was associated with heavy alcohol use (among men). Frequent overtime work 24 years earlier was associated with heavy alcohol use among women. Cross sectional analyses also showed associations between psychological ill health and some work related factors (mentally demanding work and lack of job pride). Perceived inadequacies in social contacts, and practical obstacles to social relationships are viewed as risk factors for depression. In this longitudinal study, work related factors, including mental demands and time pressure, do not appear sufficiently associated with psychological ill health.

Linear algebra

CERN Document Server

Edwards, Harold M

1995-01-01

In his new undergraduate textbook, Harold M Edwards proposes a radically new and thoroughly algorithmic approach to linear algebra Originally inspired by the constructive philosophy of mathematics championed in the 19th century by Leopold Kronecker, the approach is well suited to students in the computer-dominated late 20th century Each proof is an algorithm described in English that can be translated into the computer language the class is using and put to work solving problems and generating new examples, making the study of linear algebra a truly interactive experience Designed for a one-semester course, this text adopts an algorithmic approach to linear algebra giving the student many examples to work through and copious exercises to test their skills and extend their knowledge of the subject Students at all levels will find much interactive instruction in this text while teachers will find stimulating examples and methods of approach to the subject

Viewing or Visualising Which Concept Map Strategy Works Best on Problem-Solving Performance?

Science.gov (United States)

Lee, Youngmin; Nelson, David W.

2005-01-01

The purpose of this study was to investigate the effects of two types of maps (generative vs. completed) and the amount of prior knowledge (high vs. low) on well-structured and ill-structured problem-solving performance. Forty-four undergraduates who were registered in an introductory instructional technology course participated in the study.…

Towards lexicographic multi-objective linear programming using grossone methodology

Science.gov (United States)

Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.

2016-10-01

Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.

DEVELOPING PROBLEM SOLVING SKILLS FOR LIFELONG LEARNING THROUGH WORK-BASED LEARNING AMONG COMMUNITY COLLEGE STUDENTS

OpenAIRE

Wan Azlinda Wan Mohamed; Badrul Omar; Mohd Faroul Rafiq Romli

2010-01-01

Many training providers are working to improve their curricula to meet the demand of today’s industries. The Malaysian College Communities, one of the major providers for lifelong learning program, had introduced the Work-Based Learning (WBL) concept since 2007 to ensure that their graduates met these demands. One of the key skills required by industry is problem solving skill. The ability to solve a complex or an ill-structured work problem in the workplace is the kind of skill demanded at a...

A Fuzzy Linear Programming Approach for Aggregate Production Planning

DEFF Research Database (Denmark)

Iris, Cagatay; Cevikcan, Emre

2014-01-01

a mathematical programming framework for aggregate production planning problem under imprecise data environment. After providing background information about APP problem, together with fuzzy linear programming, the fuzzy linear programming model of APP is solved on an illustrative example for different a...

Efficient Solving of Large Non-linear Arithmetic Constraint Systems with Complex Boolean Structure

Czech Academy of Sciences Publication Activity Database

Fränzle, M.; Herde, C.; Teige, T.; Ratschan, Stefan; Schubert, T.

2007-01-01

Roč. 1, - (2007), s. 209-236 ISSN 1574-0617 Grant - others:AVACS(DE) SFB/TR 14 Institutional research plan: CEZ:AV0Z10300504 Keywords : interval-based arithmetic constraint solving * SAT modulo theories Subject RIV: BA - General Mathematics

Ill-posedness in modeling mixed sediment river morphodynamics

Science.gov (United States)

Chavarrías, Víctor; Stecca, Guglielmo; Blom, Astrid

2018-04-01

In this paper we analyze the Hirano active layer model used in mixed sediment river morphodynamics concerning its ill-posedness. Ill-posedness causes the solution to be unstable to short-wave perturbations. This implies that the solution presents spurious oscillations, the amplitude of which depends on the domain discretization. Ill-posedness not only produces physically unrealistic results but may also cause failure of numerical simulations. By considering a two-fraction sediment mixture we obtain analytical expressions for the mathematical characterization of the model. Using these we show that the ill-posed domain is larger than what was found in previous analyses, not only comprising cases of bed degradation into a substrate finer than the active layer but also in aggradational cases. Furthermore, by analyzing a three-fraction model we observe ill-posedness under conditions of bed degradation into a coarse substrate. We observe that oscillations in the numerical solution of ill-posed simulations grow until the model becomes well-posed, as the spurious mixing of the active layer sediment and substrate sediment acts as a regularization mechanism. Finally we conduct an eigenstructure analysis of a simplified vertically continuous model for mixed sediment for which we show that ill-posedness occurs in a wider range of conditions than the active layer model.

High profile students’ growth of mathematical understanding in solving linier programing problems

Science.gov (United States)

Utomo; Kusmayadi, TA; Pramudya, I.

2018-04-01

Linear program has an important role in human’s life. This linear program is learned in senior high school and college levels. This material is applied in economy, transportation, military and others. Therefore, mastering linear program is useful for provision of life. This research describes a growth of mathematical understanding in solving linear programming problems based on the growth of understanding by the Piere-Kieren model. Thus, this research used qualitative approach. The subjects were students of grade XI in Salatiga city. The subjects of this study were two students who had high profiles. The researcher generally chose the subjects based on the growth of understanding from a test result in the classroom; the mark from the prerequisite material was ≥ 75. Both of the subjects were interviewed by the researcher to know the students’ growth of mathematical understanding in solving linear programming problems. The finding of this research showed that the subjects often folding back to the primitive knowing level to go forward to the next level. It happened because the subjects’ primitive understanding was not comprehensive.

Hyperbolicity and constrained evolution in linearized gravity

International Nuclear Information System (INIS)

Matzner, Richard A.

2005-01-01

Solving the 4-d Einstein equations as evolution in time requires solving equations of two types: the four elliptic initial data (constraint) equations, followed by the six second order evolution equations. Analytically the constraint equations remain solved under the action of the evolution, and one approach is to simply monitor them (unconstrained evolution). Since computational solution of differential equations introduces almost inevitable errors, it is clearly 'more correct' to introduce a scheme which actively maintains the constraints by solution (constrained evolution). This has shown promise in computational settings, but the analysis of the resulting mixed elliptic hyperbolic method has not been completely carried out. We present such an analysis for one method of constrained evolution, applied to a simple vacuum system, linearized gravitational waves. We begin with a study of the hyperbolicity of the unconstrained Einstein equations. (Because the study of hyperbolicity deals only with the highest derivative order in the equations, linearization loses no essential details.) We then give explicit analytical construction of the effect of initial data setting and constrained evolution for linearized gravitational waves. While this is clearly a toy model with regard to constrained evolution, certain interesting features are found which have relevance to the full nonlinear Einstein equations

Embodied, Symbolic and Formal Thinking in Linear Algebra

Science.gov (United States)

Stewart, Sepideh; Thomas, Michael O. J.

2007-01-01

Students often find their first university linear algebra experience very challenging. While coping with procedural aspects of the subject, solving linear systems and manipulating matrices, they may struggle with crucial conceptual ideas underpinning them, making it very difficult to progress in more advanced courses. This research has sought to…

Monte Carlo method for solving a parabolic problem

Directory of Open Access Journals (Sweden)

Tian Yi

2016-01-01

Full Text Available In this paper, we present a numerical method based on random sampling for a parabolic problem. This method combines use of the Crank-Nicolson method and Monte Carlo method. In the numerical algorithm, we first discretize governing equations by Crank-Nicolson method, and obtain a large sparse system of linear algebraic equations, then use Monte Carlo method to solve the linear algebraic equations. To illustrate the usefulness of this technique, we apply it to some test problems.

Need for Linear Revitalization - Gdynia Case

Science.gov (United States)

Sas-Bojarska, Aleksandra

2017-10-01

The aim of the article is to discuss the need of defining and implementation of the linear revitalization - the new approach related to the revitalization processes. The results of the preliminary investigations indicate that this kind of revitalization seems to be an important tool supporting city management and planning, especially in cases of cities fragmentation - causing lack of physical, social, economic and ecological cohesion. The problems which may occur in such situations could be, in author’s opinion, solved with the use of linear revitalization. Linear revitalization relates to various linear city structures, which need a renewal. The article presents the idea of new attitude, character of specific actions related to degraded linear structures, draft classification, as well as the potential benefits to the city structure which could be reached due to the linear revitalization implementation. The theoretical deliberations are supplemented by the description and assessment of the chosen case study from Gdynia in Poland. The Kwiatkowskiego Route in Gdynia, playing important role in the city traffic as the external connection, creates the barrier in the city structure, causing many negative effects. Author presents specific problems related to chosen example, and the ways to solve them and to connect city structure. The main conclusion of the study is that the presented approach may be, in author’s opinion, the beginning of the discussion related to the linear revitalization, which may become an important and effective tool of sustainable city development. It may help overcoming physical barriers, and minimise functional, economic, social, mental and environmental conflicts caused by city fragmentation.

A Systematic Approach for Solving the Great Circle Track Problems based on Vector Algebra

Directory of Open Access Journals (Sweden)

Chen Chih-Li

2016-04-01

Full Text Available A systematic approach, based on multiple products of the vector algebra (S-VA, is proposed to derive the spherical triangle formulae for solving the great circle track (GCT problems. Because the mathematical properties of the geometry and algebra are both embedded in the S-VA approach, derivations of the spherical triangle formulae become more understandable and more straightforward as compared with those approaches which use the complex linear combination of a vector basis. In addition, the S-VA approach can handle all given initial conditions for solving the GCT problems simpler, clearer and avoid redundant formulae existing in the conventional approaches. With the technique of transforming the Earth coordinates system of latitudes and longitudes into the Cartesian one and adopting the relative longitude concept, the concise governing equations of the S-VA approach can be easily and directly derived. Owing to the advantage of the S-VA approach, it makes the practical navigator quickly adjust to solve the GCT problems. Based on the S-VA approach, a program namely GCTPro_VA is developed for friendly use of the navigator. Several validation examples are provided to show the S-VA approach is simple and versatile to solve the GCT problems.

Pharmacokinetics of linezolid in critically ill patients.

Science.gov (United States)

Sazdanovic, Predrag; Jankovic, Slobodan M; Kostic, Marina; Dimitrijevic, Aleksandra; Stefanovic, Srdjan

2016-06-01

Linezolid is an oxazolidinone antibiotic active against Gram-positive bacteria, and is most commonly used to treat life-threatening infections in critically ill patients. The pharmacokinetics of linezolid are profoundly altered in critically ill patients, partly due to decreased function of vital organs, and partly because life-sustaining drugs and devices may change the extent of its excretion. This article is summarizes key changes in the pharmacokinetics of linezolid in critically ill patients. The changes summarized are clinically relevant and may serve as rationale for dosing recommendations in this particular population. While absorption and penetration of linezolid to tissues are not significantly changed in critically ill patients, protein binding of linezolid is decreased, volume of distribution increased, and metabolism may be inhibited leading to non-linear kinetics of elimination; these changes are responsible for high inter-individual variability of linezolid plasma concentrations, which requires therapeutic plasma monitoring and choice of continuous venous infusion as the administration method. Acute renal or liver failure decrease clearance of linezolid, but renal replacement therapy is capable of restoring clearance back to normal, obviating the need for dosage adjustment. More population pharmacokinetic studies are necessary which will identify and quantify the influence of various factors on clearance and plasma concentrations of linezolid in critically ill patients.

Boundary Layers for the Navier-Stokes Equations Linearized Around a Stationary Euler Flow

Science.gov (United States)

Gie, Gung-Min; Kelliher, James P.; Mazzucato, Anna L.

2018-03-01

We study the viscous boundary layer that forms at small viscosity near a rigid wall for the solution to the Navier-Stokes equations linearized around a smooth and stationary Euler flow (LNSE for short) in a smooth bounded domain Ω \\subset R^3 under no-slip boundary conditions. LNSE is supplemented with smooth initial data and smooth external forcing, assumed ill-prepared, that is, not compatible with the no-slip boundary condition. We construct an approximate solution to LNSE on the time interval [0, T], 0Math J 45(3):863-916, 1996), Xin and Yanagisawa (Commun Pure Appl Math 52(4):479-541, 1999), and Gie (Commun Math Sci 12(2):383-400, 2014).

Healthcare disparities in critical illness.

Science.gov (United States)

Soto, Graciela J; Martin, Greg S; Gong, Michelle Ng

2013-12-01

To summarize the current literature on racial and gender disparities in critical care and the mechanisms underlying these disparities in the course of acute critical illness. MEDLINE search on the published literature addressing racial, ethnic, or gender disparities in acute critical illness, such as sepsis, acute lung injury, pneumonia, venous thromboembolism, and cardiac arrest. Clinical studies that evaluated general critically ill patient populations in the United States as well as specific critical care conditions were reviewed with a focus on studies evaluating factors and contributors to health disparities. Study findings are presented according to their association with the prevalence, clinical presentation, management, and outcomes in acute critical illness. This review presents potential contributors for racial and gender disparities related to genetic susceptibility, comorbidities, preventive health services, socioeconomic factors, cultural differences, and access to care. The data are organized along the course of acute critical illness. The literature to date shows that disparities in critical care are most likely multifactorial involving individual, community, and hospital-level factors at several points in the continuum of acute critical illness. The data presented identify potential targets as interventions to reduce disparities in critical care and future avenues for research.

A Photon Free Method to Solve Radiation Transport Equations

International Nuclear Information System (INIS)

Chang, B

2006-01-01

The multi-group discrete-ordinate equations of radiation transfer is solved for the first time by Newton's method. It is a photon free method because the photon variables are eliminated from the radiation equations to yield a N group XN direction smaller but equivalent system of equations. The smaller set of equations can be solved more efficiently than the original set of equations. Newton's method is more stable than the Semi-implicit Linear method currently used by conventional radiation codes

ORACLS: A system for linear-quadratic-Gaussian control law design

Science.gov (United States)

Armstrong, E. S.

1978-01-01

A modern control theory design package (ORACLS) for constructing controllers and optimal filters for systems modeled by linear time-invariant differential or difference equations is described. Numerical linear-algebra procedures are used to implement the linear-quadratic-Gaussian (LQG) methodology of modern control theory. Algorithms are included for computing eigensystems of real matrices, the relative stability of a matrix, factored forms for nonnegative definite matrices, the solutions and least squares approximations to the solutions of certain linear matrix algebraic equations, the controllability properties of a linear time-invariant system, and the steady state covariance matrix of an open-loop stable system forced by white noise. Subroutines are provided for solving both the continuous and discrete optimal linear regulator problems with noise free measurements and the sampled-data optimal linear regulator problem. For measurement noise, duality theory and the optimal regulator algorithms are used to solve the continuous and discrete Kalman-Bucy filter problems. Subroutines are also included which give control laws causing the output of a system to track the output of a prescribed model.

Are immigrants and descendants with ill health more prone to unemployment? Evidence from 18 European countries.

Science.gov (United States)

Heggebø, Kristian

2017-08-01

Previous research has established that both ill health and minority status are associated with unemployment. Less is known, however, about the interplay between having ill health and being from minority background. The present study examines whether immigrants and descendants with ill health are particularly prone to unemployment during an economic downturn in Europe. The European Union Statistics on Income and Living Conditions (EU-SILC) cross-sectional data material is utilized, and linear probability models are estimated. The analysis is run for countries in which the two minority samples are acceptably large (N ≥ 100), resulting in 18 included European countries. The year 2011 is chosen because it is possible to identify both immigrants and descendants in EU-SILC due to a module on intergenerational transfer of disadvantages. The results indicate - as expected - that both ill health and minority status are independently related to higher unemployment likelihood. Immigrants and descendants with ill health, however, are not particularly likely to be unemployed. This finding is robust to a number of sensitivity tests, and the empirical pattern is very similar across the 18 included countries. Both minority status and ill health are associated with high unemployment probability in Europe. However, there does not seem to exist a 'double disadvantage' for immigrants and descendants with ill health, which is in line with a human capital perspective on how employers evaluate potential employees. Both a non-native-sounding name and bad health status are interpreted as a risk factor, but there is no reason to expect ill health to lower the productivity level more if the applicant is a descendant or immigrant.

The Fight against Stigma toward Mental Illness

Directory of Open Access Journals (Sweden)

Olcay Cam

2010-02-01

Full Text Available In many health conditions, stigma is receiving increasing attention. Public stigmatization toward mental illness can affect particularly the patients and family memberships to help seeking behavior and treatment. These stigmatized persons in the society are deprived of rights and benefits. In this paper, reasons and consequences of stigma associated with mental illness are reviewed and combat against mental illnesses originated stigma are discussed. [TAF Prev Med Bull 2010; 9(1.000: 71-78

Polynomial approach method to solve the neutron point kinetics equations with use of the analytic continuation

Energy Technology Data Exchange (ETDEWEB)

Tumelero, Fernanda; Petersen, Claudio Zen; Goncalves, Glenio Aguiar [Universidade Federal de Pelotas, Capao do Leao, RS (Brazil). Programa de Pos Graduacao em Modelagem Matematica; Schramm, Marcelo [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Engenharia Mecanica

2016-12-15

In this work, we report a solution to solve the Neutron Point Kinetics Equations applying the Polynomial Approach Method. The main idea is to expand the neutron density and delayed neutron precursors as a power series considering the reactivity as an arbitrary function of the time in a relatively short time interval around an ordinary point. In the first interval one applies the initial conditions and the analytical continuation is used to determine the solutions of the next intervals. A genuine error control is developed based on an analogy with the Rest Theorem. For illustration, we also report simulations for different approaches types (linear, quadratic and cubic). The results obtained by numerical simulations for linear approximation are compared with results in the literature.

Solving or resolving inadequate and noisy tomographic systems

NARCIS (Netherlands)

Nolet, G.

1985-01-01

Tomography in seismology often leads to underdetermined and inconsistent systems of linear equations. When solving, care must be taken to keep the propagation of data errors under control. In this paper I test the applicability of three types of damped least-squares algorithms to the kind of

2009 Pantex Plant Annual Illness and Injury Surveillance

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Security, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2010-12-15

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of epidemiologic surveillance activities that provide an early warning system for health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence of workdays, occupational injuries and illnesses, and disabilities and deaths among current workers.

Linear MHD equilibria

International Nuclear Information System (INIS)

Scheffel, J.

1984-03-01

The linear Grad-Shafranov equation for a toroidal, axisymmetric plasma is solved analytically. Exact solutions are given in terms of confluent hyper-geometric functions. As an alternative, simple and accurate WKBJ solutions are presented. With parabolic pressure profiles, both hollow and peaked toroidal current density profiles are obtained. As an example the equilibrium of a z-pinch with a square-shaped cross section is derived.(author)

Schwarz maps of algebraic linear ordinary differential equations

Science.gov (United States)

Sanabria Malagón, Camilo

2017-12-01

A linear ordinary differential equation is called algebraic if all its solution are algebraic over its field of definition. In this paper we solve the problem of finding closed form solution to algebraic linear ordinary differential equations in terms of standard equations. Furthermore, we obtain a method to compute all algebraic linear ordinary differential equations with rational coefficients by studying their associated Schwarz map through the Picard-Vessiot Theory.

Fractional order differentiation by integration: An application to fractional linear systems

KAUST Repository

Liu, Dayan

2013-02-04

In this article, we propose a robust method to compute the output of a fractional linear system defined through a linear fractional differential equation (FDE) with time-varying coefficients, where the input can be noisy. We firstly introduce an estimator of the fractional derivative of an unknown signal, which is defined by an integral formula obtained by calculating the fractional derivative of a truncated Jacobi polynomial series expansion. We then approximate the FDE by applying to each fractional derivative this formal algebraic integral estimator. Consequently, the fractional derivatives of the solution are applied on the used Jacobi polynomials and then we need to identify the unknown coefficients of the truncated series expansion of the solution. Modulating functions method is used to estimate these coefficients by solving a linear system issued from the approximated FDE and some initial conditions. A numerical result is given to confirm the reliability of the proposed method. © 2013 IFAC.

A parametric FE modeling of brake for non-linear analysis

Energy Technology Data Exchange (ETDEWEB)

Ahmed,Ibrahim; Fatouh, Yasser [Automotive and Tractors Technology Department, Faculty of Industrial Education, Helwan University, Cairo (Egypt); Aly, Wael [Refrigeration and Air-Conditioning Technology Department, Faculty of Industrial Education, Helwan University, Cairo (Egypt)

2013-07-01

A parametric modeling of a drum brake based on 3-D Finite Element Methods (FEM) for non-contact analysis is presented. Many parameters are examined during this study such as the effect of drum-lining interface stiffness, coefficient of friction, and line pressure on the interface contact. Firstly, the modal analysis of the drum brake is also studied to get the natural frequency and instability of the drum to facilitate transforming the modal elements to non-contact elements. It is shown that the Unsymmetric solver of the modal analysis is efficient enough to solve this linear problem after transforming the non-linear behavior of the contact between the drum and the lining to a linear behavior. A SOLID45 which is a linear element is used in the modal analysis and then transferred to non-linear elements which are Targe170 and Conta173 that represent the drum and lining for contact analysis study. The contact analysis problems are highly non-linear and require significant computer resources to solve it, however, the contact problem give two significant difficulties. Firstly, the region of contact is not known based on the boundary conditions such as line pressure, and drum and friction material specs. Secondly, these contact problems need to take the friction into consideration. Finally, it showed a good distribution of the nodal reaction forces on the slotted lining contact surface and existing of the slot in the middle of the lining can help in wear removal due to the friction between the lining and the drum. Accurate contact stiffness can give a good representation for the pressure distribution between the lining and the drum. However, a full contact of the front part of the slotted lining could occur in case of 20, 40, 60 and 80 bar of piston pressure and a partially contact between the drum and lining can occur in the rear part of the slotted lining.

Pseudoinverse preconditioners and iterative methods for large dense linear least-squares problems

Directory of Open Access Journals (Sweden)

Oskar Cahueñas

2013-05-01

Full Text Available We address the issue of approximating the pseudoinverse of the coefficient matrix for dynamically building preconditioning strategies for the numerical solution of large dense linear least-squares problems. The new preconditioning strategies are embedded into simple and well-known iterative schemes that avoid the use of the, usually ill-conditioned, normal equations. We analyze a scheme to approximate the pseudoinverse, based on Schulz iterative method, and also different iterative schemes, based on extensions of Richardson's method, and the conjugate gradient method, that are suitable for preconditioning strategies. We present preliminary numerical results to illustrate the advantages of the proposed schemes.

Numerical solution of large sparse linear systems

International Nuclear Information System (INIS)

Meurant, Gerard; Golub, Gene.

1982-02-01

This note is based on one of the lectures given at the 1980 CEA-EDF-INRIA Numerical Analysis Summer School whose aim is the study of large sparse linear systems. The main topics are solving least squares problems by orthogonal transformation, fast Poisson solvers and solution of sparse linear system by iterative methods with a special emphasis on preconditioned conjuguate gradient method [fr

Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing; Koltun, Vladlen; Guibas, Leonidas

2011-01-01

program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems

Directory of Open Access Journals (Sweden)

Faridah Hani Mohamed Salleh

2017-01-01

Full Text Available Gene regulatory network (GRN reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C as a direct interaction (A → C. Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

Linearization Method and Linear Complexity

Science.gov (United States)

Tanaka, Hidema

We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N(≅2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.

Numerical linear algebra with applications using Matlab

CERN Document Server

Ford, William

2014-01-01

Designed for those who want to gain a practical knowledge of modern computational techniques for the numerical solution of linear algebra problems, Numerical Linear Algebra with Applications contains all the material necessary for a first year graduate or advanced undergraduate course on numerical linear algebra with numerous applications to engineering and science. With a unified presentation of computation, basic algorithm analysis, and numerical methods to compute solutions, this book is ideal for solving real-world problems. It provides necessary mathematical background information for

The Impact of Mental Health Reform on Mental Illness Stigmas in Israel.

Science.gov (United States)

Ben Natan, Merav; Drori, Tal; Hochman, Ohad

2017-12-01

This study examined public perception of stigmas relating to mental illness six months after a reform, which integrated mental health care into primary care in Israel. The results reveal that the public feels uncomfortable seeking referral to mental health services through the public health system, with Arab Israelis and men expressing lower levels of comfort than did Jewish Israelis. The current reform has not solved the issue of public stigma regarding mental health care. The study suggests that the current reforms must be accompanied over time with appropriate public education regarding mental illness. Copyright © 2017 Elsevier Inc. All rights reserved.

Solving potential field problems in composite media with complicated geometries

International Nuclear Information System (INIS)

Yeh, H.

1977-01-01

Recently, Yeh developed a method of solving potential field problems for complicated geometries and theorems of piecewise continuous eigenfunctions which can be used to solve boundary-value problems in composite media by the separation of variables. This paper shows that by a proper arrangement of matching conditions and boundary conditions, this method and these theorems can be applied simultaneously so that the problems in composite media with complicated geometries can be solved. To illustrate this, a heat-conduction problem in a composite cylinder with an abrupt change in cross-section area is solved. Also presented in this paper are the method of handling the nonhomogeneous boundary conditions for composite media and the extension of one of the above-mentioned theorems to include imperfect contact on material boundaries

Solving conic optimization problems via self-dual embedding and facial reduction: A unified approach

DEFF Research Database (Denmark)

Permenter, Frank; Friberg, Henrik A.; Andersen, Erling D.

2017-01-01

it fails to return a primal-dual optimal solution or a certificate of infeasibility. Using this observation, we give an algorithm based on facial reduction for solving the primal problem that, in principle, always succeeds. (An analogous algorithm is easily stated for the dual problem.) This algorithm has...... the appealing property that it only performs facial reduction when it is required, not when it is possible; e.g., if a primal-dual optimal solution exists, it will be found in lieu of a facial reduction certificate even if Slater's condition fails. For the case of linear, second-order, and semidefinite...

Pinning Synchronization of Linear Complex Coupling Synchronous Generators Network of Hydroelectric Generating Set

Directory of Open Access Journals (Sweden)

Xuefei Wu

2014-01-01

Full Text Available A novel linear complex system for hydroturbine-generator sets in multimachine power systems is suggested in this paper and synchronization of the power-grid networks is studied. The advanced graph theory and stability theory are combined to solve the problem. Here we derive a sufficient condition under which the synchronous state of power-grid networks is stable in disturbance attenuation. Finally, numerical simulations are provided to illustrate the effectiveness of the results by the IEEE 39 bus system.

A Linear-Elasticity Solver for Higher-Order Space-Time Mesh Deformation

Science.gov (United States)

Diosady, Laslo T.; Murman, Scott M.

2018-01-01

A linear-elasticity approach is presented for the generation of meshes appropriate for a higher-order space-time discontinuous finite-element method. The equations of linear-elasticity are discretized using a higher-order, spatially-continuous, finite-element method. Given an initial finite-element mesh, and a specified boundary displacement, we solve for the mesh displacements to obtain a higher-order curvilinear mesh. Alternatively, for moving-domain problems we use the linear-elasticity approach to solve for a temporally discontinuous mesh velocity on each time-slab and recover a continuous mesh deformation by integrating the velocity. The applicability of this methodology is presented for several benchmark test cases.

An implicit iterative scheme for solving large systems of linear equations

International Nuclear Information System (INIS)

Barry, J.M.; Pollard, J.P.

1986-12-01

An implicit iterative scheme for the solution of large systems of linear equations arising from neutron diffusion studies is presented. The method is applied to three-dimensional reactor studies and its performance is compared with alternative iterative approaches

A Second-Order Conditionally Linear Mixed Effects Model with Observed and Latent Variable Covariates

Science.gov (United States)

Harring, Jeffrey R.; Kohli, Nidhi; Silverman, Rebecca D.; Speece, Deborah L.

2012-01-01

A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a…

Introduction to computational linear algebra

CERN Document Server

Nassif, Nabil; Erhel, Jocelyne

2015-01-01

Introduction to Computational Linear Algebra introduces the reader with a background in basic mathematics and computer programming to the fundamentals of dense and sparse matrix computations with illustrating examples. The textbook is a synthesis of conceptual and practical topics in ""Matrix Computations."" The book's learning outcomes are twofold: to understand state-of-the-art computational tools to solve matrix computations problems (BLAS primitives, MATLAB® programming) as well as essential mathematical concepts needed to master the topics of numerical linear algebra. It is suitable for s

Improved solution for ill-posed linear systems using a constrained optimization ruled by a penalty: evaluation in nuclear medicine tomography

International Nuclear Information System (INIS)

Walrand, Stephan; Jamar, François; Pauwels, Stanislas

2009-01-01

Ill-posed linear systems occur in many different fields. A class of regularization methods, called constrained optimization, aims to determine the extremum of a penalty function whilst constraining an objective function to a likely value. We propose here a novel heuristic way to screen the local extrema satisfying the discrepancy principle. A modified version of the Landweber algorithm is used for the iteration process. After finding a local extremum, a bound is performed to the 'farthest' estimate in the data space still satisfying the discrepancy principle. Afterwards, the modified Landweber algorithm is again applied to find a new local extremum. This bound-iteration process is repeated until a satisfying solution is reached. For evaluation in nuclear medicine tomography, a novel penalty function that preserves the edge steps in the reconstructed solution was evaluated on Monte Carlo simulations and using real SPECT acquisitions as well. Surprisingly, the first bound always provided a significantly better solution in a wide range of statistics

A Globally Convergent Matrix-Free Method for Constrained Equations and Its Linear Convergence Rate

Directory of Open Access Journals (Sweden)

Min Sun

2014-01-01

Full Text Available A matrix-free method for constrained equations is proposed, which is a combination of the well-known PRP (Polak-Ribière-Polyak conjugate gradient method and the famous hyperplane projection method. The new method is not only derivative-free, but also completely matrix-free, and consequently, it can be applied to solve large-scale constrained equations. We obtain global convergence of the new method without any differentiability requirement on the constrained equations. Compared with the existing gradient methods for solving such problem, the new method possesses linear convergence rate under standard conditions, and a relax factor γ is attached in the update step to accelerate convergence. Preliminary numerical results show that it is promising in practice.

A parallel solver for huge dense linear systems

Science.gov (United States)

Badia, J. M.; Movilla, J. L.; Climente, J. I.; Castillo, M.; Marqués, M.; Mayo, R.; Quintana-Ortí, E. S.; Planelles, J.

2011-11-01

HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facilitate the parallel solution of very large dense systems to scientists and engineers. The API makes use of parallelism to yield an efficient solution of the systems on a wide range of parallel platforms, from clusters of processors to massively parallel multiprocessors. It exploits out-of-core strategies to leverage the secondary memory in order to solve huge linear systems O(100.000). The API is based on the parallel linear algebra library PLAPACK, and on its Out-Of-Core (OOC) extension POOCLAPACK. Both PLAPACK and POOCLAPACK use the Message Passing Interface (MPI) as the communication layer and BLAS to perform the local matrix operations. The API provides a friendly interface to the users, hiding almost all the technical aspects related to the parallel execution of the code and the use of the secondary memory to solve the systems. In particular, the API can automatically select the best way to store and solve the systems, depending of the dimension of the system, the number of processes and the main memory of the platform. Experimental results on several parallel platforms report high performance, reaching more than 1 TFLOP with 64 cores to solve a system with more than 200 000 equations and more than 10 000 right-hand side vectors. New version program summaryProgram title: Huge Dense System Solver (HDSS) Catalogue identifier: AEHU_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHU_v1_1.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 87 062 No. of bytes in distributed program, including test data, etc.: 1 069 110 Distribution format: tar.gz Programming language: Fortran90, C Computer: Parallel architectures: multiprocessors, computer clusters Operating system

2007 Idaho National Laboratory Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2009-05-04

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Brookhaven National Laboratory Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-03-06

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2007 Brookhaven National Laboratory Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-07-31

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Idaho National Laboratory Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-09-26

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Kansas City Plant Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-06-13

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Savannah River Site Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-09-12

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Savannah River Site Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-08-20

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Sandia National Laboratory Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-10-26

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Nevada Test Site Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-04-24

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Kansas City Plant Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-06-20

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Brookhaven National Laboratory Annual Illness and Injury Surveillance Report

Energy Technology Data Exchange (ETDEWEB)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-08-16

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

Stability Criterion of Linear Stochastic Systems Subject to Mixed H2/Passivity Performance

Directory of Open Access Journals (Sweden)

Cheung-Chieh Ku

2015-01-01

Full Text Available The H2 control scheme and passivity theory are applied to investigate the stability criterion of continuous-time linear stochastic system subject to mixed performance. Based on the stochastic differential equation, the stochastic behaviors can be described as multiplicative noise terms. For the considered system, the H2 control scheme is applied to deal with the problem on minimizing output energy. And the asymptotical stability of the system can be guaranteed under desired initial conditions. Besides, the passivity theory is employed to constrain the effect of external disturbance on the system. Moreover, the Itô formula and Lyapunov function are used to derive the sufficient conditions which are converted into linear matrix inequality (LMI form for applying convex optimization algorithm. Via solving the sufficient conditions, the state feedback controller can be established such that the asymptotical stability and mixed performance of the system are achieved in the mean square. Finally, the synchronous generator system is used to verify the effectiveness and applicability of the proposed design method.

Comparison of Problem Solving from Engineering Design to Software Design

DEFF Research Database (Denmark)

Ahmed-Kristensen, Saeema; Babar, Muhammad Ali

2012-01-01

Observational studies of engineering design activities can inform the research community on the problem solving models that are employed by professional engineers. Design is defined as an ill-defined problem which includes both engineering design and software design, hence understanding problem...... solving models from other design domains is of interest to the engineering design community. For this paper an observational study of two software design sessions performed for the workshop on “Studying professional Software Design” is compared to analysis from engineering design. These findings provide...... useful insights of how software designers move from a problem domain to a solution domain and the commonalities between software designers’ and engineering designers’ design activities. The software designers were found to move quickly to a detailed design phase, employ co-.evolution and adopt...

Comparison of Problem Solving from Engineering Design to Software Design

DEFF Research Database (Denmark)

Ahmed-Kristensen, Saeema; Babar, Muhammad Ali

2012-01-01

solving models from other design domains is of interest to the engineering design community. For this paper an observational study of two software design sessions performed for the workshop on “Studying professional Software Design” is compared to analysis from engineering design. These findings provide......Observational studies of engineering design activities can inform the research community on the problem solving models that are employed by professional engineers. Design is defined as an ill-defined problem which includes both engineering design and software design, hence understanding problem...... useful insights of how software designers move from a problem domain to a solution domain and the commonalities between software designers’ and engineering designers’ design activities. The software designers were found to move quickly to a detailed design phase, employ co-.evolution and adopt...

Beyond negative thinking: illness cognitions and demographics as ...

African Journals Online (AJOL)

Despite ample research evidence suggesting a strong link between illness cognitions and patients\\' psychological health, research in this direction in Nigeria is rather scanty, especially in a chronic condition like HIV/AIDS. This study explored the relationship between illness cognitions (helplessness, acceptance and ...

Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

Science.gov (United States)

Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

2007-02-01

Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

Solution of linear and nonlinear matrix systems. Application to a nonlinear diffusion equation

International Nuclear Information System (INIS)

Bonnet, M.; Meurant, G.

1978-01-01

The object of this study is to compare different methods of solving linear and nonlinear algebraic systems and to apply them to the nonlinear system obtained by discretizing a nonlinear diffusion equation. For linear systems the conventional methods of alternating direction type or Gauss Seidel's methods are compared to more recent ones of the type of generalized conjugate gradient; the superiority of the latter is shown by numerical examples. For nonlinear systems, a method of nonlinear conjugate gradient is studied together with Newton's method and some of its variants. It should be noted, however, that Newton's method is found to be more efficient when coupled with a good method for solving the linear system. As a conclusion, these methods are used to solve a nonlinear diffusion problem and the numerical results obtained are compared [fr

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