Algorithm engineering for expression dag based number types

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

A note on parallelizing the parameterized expectations algorithm

The parameterized expectations algorithm (PEA) involves a long simulation and a nonlinear least squares (NLS) fit, both embedded in a loop. Both steps are natural candidates for parallelization. This note shows that parallelization can lead to important speedups for the PEA. I provide example code for a simple model that can serve as a template for parallelization of more interesting models, as well as a download link for an image of a bootable CD that allows creation of a cluster and execution of the example code in minutes, with no need to install any software.

Financial health, exports, and rm survival: Evidence from UK and French firms

We use firm level data to assess the role of exporting in the link between financial health and rm survival. The data are for the UK and France. We examine whether fi rms at diff erent stages of export activity (starters, exiters, continuers, switchers) react di fferently to changes in financial variables. In general, export starters and exiters experience much stronger adverse e ffects of fi nancial constraints for their survival prospects. By contrast, the exit probability of continuous exporters and export switchers is less negatively a ffected by financial characteristics. These relationships between exporting, finance and survival are broadly similar in the British and French sub-samples.

An objective anisotropic elastic plastic model and Algorithm applicable to bone mechanics

The implicit projection algorithm of isotropic plasticity is extended to an objective anisotropic elastic perfectly plastic model. The recursion formula developed to project the trial stress on the yield surface, is applicable to any non linear elastic law and any plastic yield function.A curvilinear transverse isotropic model based on a quadratic elastic potential and on Hill's quadratic yield criterion is then developed and implemented in a computer program for bone mechanics perspectives. The paper concludes with a numerical study of a schematic bone-prosthesis system to illustrate the potential of the model.

A numerical algorithm for finding solutions of a generalized Nash equilibrium problem

A family of nonempty closed convex sets is built by using the data of the Generalized Nash equilibrium problem (GNEP). The sets are selected iteratively such that the intersection of the selected sets contains solutions of the GNEP. The algorithm introduced by Iusem-Sosa (2003) is adapted to obtain solutions of the GNEP. Finally some numerical experiments are given to illustrate the numerical behavior of the algorithm.

An algorithm for semi-infinite polynomial optimization

"Vegeu el resum a l'inici del document del fitxer adjunt."

An approximation algorithm for #k-SAT

"Vegeu el resum a l'inici del document del fitxer adjunt"

Métodos automatizados de segmentación para cuantificar el grosor cortical en RM en pacientes con deterioro cognitivo y enfermedad de Parkinson

El objetivo del presente estudio es encontrar la relación que existe entre los síntomas de deterioro cognitivo y el grosor cortical cerebral en una muestra de 45 pacientes con Enfermedad de Parkinson diagnosticados y tratados en la consulta externa del Servicio de Neurología del Hospital de la Santa Creu i Sant Pau de Barcelona, quienes fueron sometidos a tests neuropsicológicos que evaluaban su función mental y motora y a quienes se les realizó un estudio de Resonancia Magnética 3 Tesla para evaluar, mediante técnicas de postprocesados, su grosor cortical. Los resultados demostraron una clara disminución del grosor cortical en determinadas áreas que se correlacionaban con las funciones cognitivas afectadas en estos pacientes.

Estudio comparativo de los valores de difusión por RM de las radiaciones ópticas en pacientes diagnosticados de síndrome clínico aislado con pacientes controles.

Diversos estudis han demostrat que, en pacients amb esclerosi múltiple, existeixen alteracions als paràmetres de difusió mesurats amb Resonància Magnètica als tractes de substància blanca que es mostren aparentment normals en les seqüències convencionals. Amb l’objectiu de demostrar si aquestes alteracions apareixen precoçment en la fase de síndrome clínic aïllada, es van analitzar una sèrie d’estudis de Resonància Magnètica cerebral amb seqüències potenciades en difusió i tractografia de les radiacions òptiques, de pacients amb el diagnòstic de síndrome clínic aïllada i pacients controls, mesurant en tots ells els valors dels paràmetres principals de difusió: coeficient de difusió aparent y fracció d’anisotropia. Amb aquestes exploracions no es van demostrar alteracions als paràmetres de difusió en fases tan precoces de la malaltia als pacients casos davant els controls.

Optimización de la secuencia de difusión en RM 3T con modelo multifactorial IVIM en el estudio de la próstata.

La utilització de la seqüència de difusió en RM 3T amb un model multifactorial IVIM (Intravoxel Incoherent Motion) ofereix la possibilitat d'estudiar per separat la caiguda del senyal deguda a la difusió pròpiament dita, de la deguda als nuclis d'H de l'aigua lliure que es mouen en la xarxa de microcapil•lars del volum estudiat. Mostrem la nostra experiència en la implementació del model IVIM en l'estudi de la pròstata, demostrant que pot resultar útil en la comparació del teixit prostàtic respecte al teixit patològic amb diferències inicials estadísticament significatives, sent superior al càlcul de l'ADC.

Estudio comparativo de RM perfusión en pacientes diagnosticados de hidrocefalia normotensiva con pacientes controles.

Diversos estudis han demostrat que existeix una disminució en la irrigació de la substància blanca periventricular en pacients diagnosticats d’hidrocefàlia normotensiva quan es comparen amb subjectes normals. Amb l’objectiu de demostrar aquestes troballes, pacients afectes d’aquesta patología es van sotmetre a una RM cerebral morfológica, un estudi de dinàmica de fluxe de LCR i un estudi de perfusió. Amb aquestes exploracions es va demostrar un augment en l’índex d’Evans i una disminución dels valors de VSC (Volum Sanguini Cerebral) de la substància blanca periventricular als pacients casos enfront dels controls.

An iterative Multiscale Finite-Volume algorithm converging to the exact solution

The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

Proposal of a parallel architecture for a motion detection algorithm

This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed