An alternative approach to the image reconstruction for parallel data acquisition in MRI

Magnetic resonance imaging with parallel data acquisition requires algorithms for reconstructing the patient's image from a small number of measured k‐space lines. In contrast to well‐known algorithms like SENSE and GRAPPA and its flavours we consider the problem as a non‐linear inverse problem. Fast computation algorithms for the necessary Fréchet derivative and reconstruction algorithms are given. Copyright © 2007 John Wiley & Sons, Ltd.     

An alternative approach to the structure theory of PI-rings

We expose a rather simple and direct approach to the structure theory of prime PI-rings (“Posner’s theorem”), based on fundamental properties of the extended centroid of a prime ring.     

A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management

This paper presents a multi-level Taguchi-factorial two-stage stochastic programming (MTTSP) approach for supporting water resources management under parameter uncertainties and their interactions. MTTSP is capable of performing uncertainty analysis, policy analysis, factor screening, and interaction detection in a comprehensive and systematic way. A water resources management problem is used to demonstrate the applicability of the proposed approach. The results indicate that interval solutions can be generated for the objective function and decision variables, and a variety of decision alternatives can be obtained under different policy scenarios. The experimental data obtained from the Taguchi’s orthogonal array design are helpful in identifying the significant factors affecting the total net benefit. Then the findings from the multi-level factorial experiment reveal the latent interactions among those important factors and their curvature effects on the model response. Such a sequential strategy of experimental designs is useful in analyzing the interactions for a large number of factors in a computationally efficient manner.     

An application of vertex packing to data analysis in the evaluation of pavement deterioration

The analysis of data concerning the deterioration of pavement over time yielded a problem of aggregating the data in a manner that preserved independence of the aggregated data points and maximized the number of points. We show that this problem can be modeled as a maximum cardinality vertex packing problem on a proper internal graph and thus can be solved very efficiently by a greedy algorithm.     

Semantics and factor analysis: An approach to the interpretation of factors

The interpretation of factors constitutes a major problem in factor analysis. Until now the underlying semantic aspects of the question have been studied only occasionally. However, there are some indications that the mechanical interpretation of the results may constitute in the immediate future a real need in the realm of very large problems. On the other hand, the semantic study of multivariate statistical methods is the only way to warrant the validity of the mechanization procedures and the means to identify their limits.     

An alternative approach to establishment of a variational principle for the torsional problem of piezoelastic beams

The semi-inverse method is adopted to search for a variational principle for an unelectroded piezoelastic beam. A trial variational formulation with energy integral is constructed with an unknown function, which is identified so that the Euler–Lagrange equations are equivalent to the governing equations.     

Preference aggregation and DEA: An analysis of the methods proposed to discriminate efficient candidates

There are different ways to allow the voters to express their preferences on a set of candidates. In ranked voting systems, each voter selects a subset of the candidates and ranks them in order of preference. A well-known class of these voting systems are scoring rules, where fixed scores are assigned to the different ranks and the candidates with the highest score are the winners. One of the most important issues in this context is the choice of the scoring vector, since the winning candidate can vary according to the scores used. To avoid this problem, Cook and Kress [W.D. Cook, M. Kress, A data envelopment model for aggregating preference rankings, Management Science 36 (11) (1990) 1302–1310], using a DEA/AR model, proposed to assess each candidate with the most favorable scoring vector for him/her. However, the use of this procedure often causes several candidates to be efficient, i.e., they achieve the maximum score. For this reason, several methods to discriminate among efficient candidates have been proposed. The aim of this paper is to analyze and show some drawbacks of these methods.     

An application of multiobjective programming to the study of workers’ satisfaction in the Spanish labour market

In this paper, a multiobjective scheme is used to study the satisfaction levels of Spanish workers. Data obtained from the European Community Household Panel (ECHP) are used to build a multiobjective model on the basis of a previous statistical and econometric analysis of these data. Then, a Reference Point-based method is implemented to determine the profile of the most satisfied worker in Spain nowadays. Finally, a combined Goal Programming – Reference Point approach is used to determine policies which can be carried out in order to increase workers’ satisfaction levels.     

An adaptive time discretization of the classical and the dual porosity model of Richards’ equation

This paper presents a numerical solution to the equations describing Darcian flow in a variably saturated porous medium—a classical Richards’ equation model Richards (1931) [1] and an extension of it that approximates the flow in media with preferential paths—a dual porosity model Gerke and van Genuchten (1993) [8]. A numerical solver to this problem, the DRUtES computer program, was developed and released during our investigation. A new technique which maintains an adaptive time step, defined here as the Retention Curve Zone Approach, was constructed and tested. The aim was to limit the error of a linear approximation to the time derivative part. Finally, parameter identification was performed in order to compare the behavior of the dual porosity model with data obtained from a non-homogenized fracture and matrix flow simulation experiment.     

An axiomatic approach to noncompensatory sorting methods in MCDM,I: The case of two categories

In the literature on MCDM, many methods have been proposed in order to sort alternatives evaluated on several attributes into ordered categories. Most of them were proposed on an ad hoc basis. The purpose of this paper is to contribute to a recent trend of research aiming at giving these methods sound theoretical foundations. Using tools from conjoint measurement, we provide an axiomatic analysis of the partitions of alternatives into two categories that can be obtained using what we call “noncompensatory sorting models”. These models have strong links with the pessimistic version of ELECTRE TRI. Our analysis allows to pinpoint what appears to be the main distinctive features of ELECTRE TRI when compared to other sorting methods. It also gives hints on the various methods that have been proposed to assess the parameters of ELECTRE TRI on the basis of assignment examples.     

An efficient indicator for structural damage localization using the change of strain energy based on static noisy data

An efficient method is proposed to find multiple damage locations in structural systems. The change of static strain energy (SSE) due to damage is used to establish an indicator for determining the damage location. The SSE is determined using the static analysis information extracted from a finite element modeling. In order to assess the performance of the proposed method for structural damage detection, some benchmark structures having a number of damage scenarios are considered. Numerical results demonstrate that the method can accurately locate the structural damage when considering the measurement noise. The efficiency of the proposed indicator for finding the damage site is also compared with a modal strain energy based index (MSEBI) provided in the literature.     

An evolutionary approach to construction of outranking models for multicriteria classification: The case of the ELECTRE TRI method

Outranking methods constitute an important class of multicriteria classification models. Often, however, their implementation is cumbersome, due to the large number of parameters that the decision maker must specify. Past studies tried to address this issue using linear and nonlinear programming, to elicit the necessary preferential information from assignment examples. In this study, an evolutionary approach, based on the differential evolution algorithm, is proposed in the context of the ELECTRE TRI method. Computational results are given to test the effectiveness of the methodology and the quality of the obtained models.     

An application of the neural network energy function to machine sequencing

We apply a neural network approach for solving a one-machine sequencing problem to minimize either single- or multi-objectives, namely the total tardiness, total flowtime, maximimum tardiness, maximum flowtime, and number of tardy jobs. We formulate correspondingly nonlinear integer models, for each of which we derive a quadratic energy function, a neural network, and a system of differential equations. Simulation results based on solving the nonlinear differential equations demonstrate that our approach can effectively solve the sequencing problems to optimality in most cases and near optimality in a few cases. The neural network approach can also be implemented on a parallel computing network, resulting in significant runtime savings over the optimization approach. This paper should not be disseminated without written permission of the authors.     

Loss data analysis: Analysis of the sample dependence in density reconstruction by maxentropic methods

The problem of determining probability densities of positive random variables from empirical data is important in many fields, in particular in insurance and risk analysis. The method of maximum entropy has proven to be a powerful tool to determine probability densities from a few values of its Laplace transform. This is so even when the amount of data to compute numerically the Laplace transform is small. But in this case, the variability of the reconstruction due to the sample variability in the available data can lead to quite different results. It is the purpose of this note to quantify as much as possible the variability of the densities reconstructed by means of two maxentropic methods: the standard maximum entropy method and its extension to incorporate data with errors.The issues that we consider are of special interest for the advanced measurement approach in operational risk, which is based on loss data analysis to determine regulatory capital, as well as to determine the loss distribution of risks that occur with low frequency.     

New approach for the assignment of new European agricultural subsidies using scores from data envelopment analysis: Application to olive-growing farms in Andalusia (Spain)

More than 60% of olive-growing farms in Andalusia (Spain) would have negative returns without European agricultural subsidies. Agenda 2000 criteria imply that agricultural subsidies currently play the role of enhancing the production quality and the environmental and social values of agriculture. Although the necessity of the modulation of subsidies is stated, the EU regulations do not state which objective criteria should be used or how they should be measured, despite the fact that regulations demand objectivity in this measurement.     

Optimality of the barrier strategy in de Finetti’s dividend problem for spectrally negative Lévy processes: An alternative approach

The optimal dividend problem proposed in de Finetti [1] is to find the dividend-payment strategy that maximizes the expected discounted value of dividends which are paid to the shareholders until the company is ruined. Avram et al. [9] studied the case when the risk process is modelled by a general spectrally negative Lévy process and Loeffen [10] gave sufficient conditions under which the optimal strategy is of the barrier type. Recently Kyprianou et al. [11] strengthened the result of Loeffen [10] which established a larger class of Lévy processes for which the barrier strategy is optimal among all admissible ones. In this paper we use an analytical argument to re-investigate the optimality of barrier dividend strategies considered in the three recent papers.     

Variations on seven points: An introduction to the scope and methods of coding theory and finite geometries

We use a simple example (the projective plane on seven points) to give an introductory survey on the problems and methods in finite geometries — an area of mathematics related to geometry, combinatorial theory, algebra, group theory and number theory as well as to applied mathematics (e.g., coding theory, information theory, statistical design of experiments, tomography, cryptography, etc.). As this list already indicates, finite geometries is — both from the point of view of pure mathematics and from that of applications related to computer science and communication engineering — one of the most interesting and active fields of mathematics. It is the aim of this paper to introduce the nonspecialist to some of these aspects.To Professor Günter Pickert on the occasion of his 65th birthday     

Estimating the p-Variation Index of a Sample Function: An Application to Financial Data Set

In this paper we apply a real analysis approach to test continuous time stochastic models of financial mathematics. Specifically, fractal dimension estimation methods are applied to statistical analysis of continuous time stochastic processes. To estimate a roughness of a sample function we modify a box-counting method typically used in estimating fractal dimension of a graph of a function. Here the roughness of a function f is defined as the infimum of numbers p > 0 such that f has bounded p-variation, which we call the p-variation index of f. The method is also tested on estimating the exponent [1, 2] of a simulated symmetric -stable process, and on estimating the Hurst exponent H (0, 1) of a simulated fractional Brownian motion.