Anisotropic adaptive resolution of boundary layers for heat conduction problems

We deal with the numerical solution of heat conduction problems featuring steep gradients. In order to solve the associated partial differential equation a finite volume technique is used and unstructured grids are employed. A discrete maximum principle for triangulations of a Delaunay type is developed. To capture thin boundary layers incorporating steep gradients an anisotropic mesh adaptation technique is implemented. Computational tests are performed for an academic problem where the exact solution is known as well as for a real world problem of a computer simulation of the thermoregulation of premature infants.

Artificial boundary conditions for the Stokes and Navier-Stokes equations in domains that are layer-like at infinity

Artificial boundary conditions are presented to approximate solutions to Stokes- and Navier-Stokes problems in domains that are layer-like at infinity. Based on results about existence and asymptotics of the solutions v^infinity, p^infinity to the problems in the unbounded domain Omega the error v^infinity - v^R, p^infinity - p^R is estimated in H^1(Omega_R) and L^2(Omega_R), respectively. Here v^R, p^R are the approximating solutions on the truncated domain Omega_R, the parameter R controls the exhausting of Omega. The artificial boundary conditions involve the Steklov-Poincare operator on a circle together with its inverse and thus turn out to be a combination of local and nonlocal boundary operators. Depending on the asymptotic decay of the data of the problems, in the linear case the error vanishes of order O(R^{-N}), where N can be arbitrarily large.

Experimentelle und numerische Untersuchungen zur Dispersion von Dichteströmungen in einem stochastischen Modellaquifer

Es ist bekannt, dass die Dichte eines gelösten Stoffes die Richtung und die Stärke seiner Bewegung im Untergrund entscheidend bestimmen kann. Eine Vielzahl von Untersuchungen hat gezeigt, dass die Verteilung der Durchlässigkeiten eines porösen Mediums diese Dichteffekte verstärken oder abmindern kann. Wie sich dieser gekoppelte Effekt auf die Vermischung zweier Fluide auswirkt, wurde in dieser Arbeit untersucht und dabei das experimentelle sowohl mit dem numerischen als auch mit dem analytischen Modell gekoppelt. Die auf der Störungstheorie basierende stochastische Theorie der macrodispersion wurde in dieser Arbeit für den Fall der transversalen Makodispersion. Für den Fall einer stabilen Schichtung wurde in einem Modelltank (10m x 1.2m x 0.1m) der Universität Kassel eine Serie sorgfältig kontrollierter zweidimensionaler Experimente an einem stochastisch heterogenen Modellaquifer durchgeführt. Es wurden Versuchsreihen mit variierenden Konzentrationsdifferenzen (250 ppm bis 100 000 ppm) und Strömungsgeschwindigkeiten (u = 1 m/ d bis 8 m/d) an drei verschieden anisotrop gepackten porösen Medien mit variierender Varianzen und Korrelationen der lognormal verteilten Permeabilitäten durchgeführt. Die stationäre räumliche Konzentrationsausbreitung der sich ausbreitenden Salzwasserfahne wurde anhand der Leitfähigkeit gemessen und aus der Höhendifferenz des 84- und 16-prozentigen relativen Konzentrationsdurchgang die Dispersion berechnet. Parallel dazu wurde ein numerisches Modell mit dem dichteabhängigen Finite-Elemente-Strömungs- und Transport-Programm SUTRA aufgestellt. Mit dem kalibrierten numerischen Modell wurden Prognosen für mögliche Transportszenarien, Sensitivitätsanalysen und stochastische Simulationen nach der Monte-Carlo-Methode durchgeführt. Die Einstellung der Strömungsgeschwindigkeit erfolgte - sowohl im experimentellen als auch im numerischen Modell - über konstante Druckränder an den Ein- und Auslauftanks. Dabei zeigte sich eine starke Sensitivität der räumlichen Konzentrationsausbreitung hinsichtlich lokaler Druckvariationen. Die Untersuchungen ergaben, dass sich die Konzentrationsfahne mit steigendem Abstand von der Einströmkante wellenförmig einem effektiven Wert annähert, aus dem die Makrodispersivität ermittelt werden kann. Dabei zeigten sich sichtbare nichtergodische Effekte, d.h. starke Abweichungen in den zweiten räumlichen Momenten der Konzentrationsverteilung der deterministischen Experimente von den Erwartungswerten aus der stochastischen Theorie. Die transversale Makrodispersivität stieg proportional zur Varianz und Korrelation der lognormalen Permeabilitätsverteilung und umgekehrt proportional zur Strömungsgeschwindigkeit und Dichtedifferenz zweier Fluide. Aus dem von Welty et al. [2003] mittels Störungstheorie entwickelten dichteabhängigen Makrodispersionstensor konnte in dieser Arbeit die stochastische Formel für die transversale Makrodispersion weiter entwickelt und - sowohl experimentell als auch numerisch - verifiziert werden.

A generic formula for the values at the boundary points of monic classical orthogonal polynomials

In a previous paper we have determined a generic formula for the polynomial solution families of the well-known differential equation of hypergeometric type σ(x)y"n(x)+τ(x)y'n(x)-λnyn(x)=0. In this paper, we give another such formula which enables us to present a generic formula for the values of monic classical orthogonal polynomials at their boundary points of definition.

Approximate Approximations and a Boundary Point Method for the Linearized Stokes System

The method of approximate approximations, introduced by Maz'ya [1], can also be used for the numerical solution of boundary integral equations. In this case, the matrix of the resulting algebraic system to compute an approximate source density depends only on the position of a finite number of boundary points and on the direction of the normal vector in these points (Boundary Point Method). We investigate this approach for the Stokes problem in the whole space and for the Stokes boundary value problem in a bounded convex domain G subset R^2, where the second part consists of three steps: In a first step the unknown potential density is replaced by a linear combination of exponentially decreasing basis functions concentrated near the boundary points. In a second step, integration over the boundary partial G is replaced by integration over the tangents at the boundary points such that even analytical expressions for the potential approximations can be obtained. In a third step, finally, the linear algebraic system is solved to determine an approximate density function and the resulting solution of the Stokes boundary value problem. Even not convergent the method leads to an efficient approximation of the form O(h^2) + epsilon, where epsilon can be chosen arbitrarily small.

Approximate solutions and error estimates for a Stokes boundary value problem

The aim of this paper is the numerical treatment of a boundary value problem for the system of Stokes' equations. For this we extend the method of approximate approximations to boundary value problems. This method was introduced by V. Maz'ya in 1991 and has been used until now for the approximation of smooth functions defined on the whole space and for the approximation of volume potentials. In the present paper we develop an approximation procedure for the solution of the interior Dirichlet problem for the system of Stokes' equations in two dimensions. The procedure is based on potential theoretical considerations in connection with a boundary integral equations method and consists of three approximation steps as follows. In a first step the unknown source density in the potential representation of the solution is replaced by approximate approximations. In a second step the decay behavior of the generating functions is used to gain a suitable approximation for the potential kernel, and in a third step Nyström's method leads to a linear algebraic system for the approximate source density. For every step a convergence analysis is established and corresponding error estimates are given.

Varying the dietary supply of C and N to manipulate the manure composition of water buffalo heifers in Oman

Optimizing the composition of manure has the potential to reduce nutrient losses to the environment and to increase crop yields. In this study the effect of dietary ratios of carbon (C) to nitrogen (N) and neutral detergent fibre (NDF) to soluble carbohydrates (SC) on faeces composition of water buffalo heifers was assessed. Two digestibility trials were conducted with 12 animals each, fed one control and four test diets composed to achieve (1) high C/N and high NDF/SC ratios (HH), (2) low C/N and low NDF/SC ratios (LL), (3) high C/N and low NDF/SC ratios (HL) and (4) low C/N and high NDF/SC (LH) ratios. Faecal C/N ratios were generally lower than dietary C/N ratios, but the reduction was especially large for high C/N ratio diets (HH=55 %, HL=51 %). Faecal N concentration was positively correlated (r^2 = 0.6; P < 0.001) with N intake, but the increase in faecal N was more pronounced for diets that supplied low amounts of N. Faecal NDF concentration was positively related to NDF intake (r^2 = 0.42; P < 0.001), as well as the faecal C/N ratio (r^2 = 0.3; P < 0.001). Results demonstrate that C/N ratio and NDF concentration of buffalo manure were affected by diet composition. Diets with high C/N ratio and low NDF/SC ratio are preferable with regard to manure quality, but may not satisfy the nutritional requirements of producing animals, since N concentration in these diets was low and fibre concentration simultaneously high.

Ansätze einer akteursbasierten Innovationserklärung

Mit der vorliegenden Arbeit soll ein Beitrag zu einer (empirisch) gehaltvollen Mikrofundierung des Innovationsgeschehens im Rahmen einer evolutorischen Perspektive geleistet werden. Der verhaltensbezogene Schwerpunkt ist dabei, in unterschiedlichem Ausmaß, auf das Akteurs- und Innovationsmodell von Herbert Simon bzw. der Carnegie-School ausgerichtet und ergänzt, spezifiziert und erweitert dieses unter anderem um vertiefende Befunde der Kreativitäts- und Kognitionsforschung bzw. der Psychologie und der Vertrauensforschung sowie auch der modernen Innovationsforschung. zudem Bezug auf einen gesellschaftlich und ökonomisch relevanten Gegenstandsbereich der Innovation, die Umweltinnovation. Die Arbeit ist sowohl konzeptionell als auch empirisch ausgerichtet, zudem findet die Methode der Computersimulation in Form zweier Multi-Agentensysteme Anwendung. Als zusammenfassendes Ergebnis lässt sich im Allgemeinen festhalten, dass Innovationen als hochprekäre Prozesse anzusehen sind, welche auf einer Verbindung von spezifischen Akteursmerkmalen, Akteurskonstellationen und Umfeldbedingungen beruhen, Iterationsschleifen unterliegen (u.a. durch Lernen, Rückkoppelungen und Aufbau von Vertrauen) und Teil eines umfassenderen Handlungs- sowie (im Falle von Unternehmen) Organisationskontextes sind. Das Akteurshandeln und die Interaktion von Akteuren sind dabei Ausgangspunkt für Emergenzen auf der Meso- und der Makroebene. Die Ergebnisse der Analysen der in dieser Arbeit enthaltenen fünf Fachbeiträge zeigen im Speziellen, dass der Ansatz von Herbert Simon bzw. der Carnegie-School eine geeignete theoretische Grundlage zur Erfassung einer prozessorientierten Mikrofundierung des Gegenstandsbereichs der Innovation darstellt und – bei geeigneter Ergänzung und Adaption an den jeweiligen Erkenntnisgegenstand – eine differenzierte Betrachtung unterschiedlicher Arten von Innovationsprozessen und deren akteursbasierten Grundlagen sowohl auf der individuellen Ebene als auch auf Ebene von Unternehmen ermöglicht. Zudem wird deutlich, dass der Ansatz von Herbert Simon bzw. der Carnegie-School mit dem Initiationsmodell einen zusätzlichen Aspekt in die Diskussion einbringt, welcher bislang wenig Aufmerksamkeit fand, jedoch konstitutiv für eine ökonomische Perspektive ist: die Analyse der Bestimmungsgrößen (und des Prozesses) der Entscheidung zur Innovation. Denn auch wenn das Verständnis der Prozesse bzw. der Determinanten der Erstellung, Umsetzung und Diffusion von Innovationen von grundlegender Bedeutung ist, ist letztendlich die Frage, warum und unter welchen Umständen Akteure sich für Innovationen entscheiden, ein zentraler Kernbereich einer ökonomischen Betrachtung. Die Ergebnisse der Arbeit sind auch für die praktische Wirtschaftspolitik von Bedeutung, insbesondere mit Blick auf Innovationsprozesse und Umweltwirkungen.

Enlarging a training set for genomic selction by imputation of un-genotyped animals in populations of varying genetic architecture

Background: The most common application of imputation is to infer genotypes of a high-density panel of markers on animals that are genotyped for a low-density panel. However, the increase in accuracy of genomic predictions resulting from an increase in the number of markers tends to reach a plateau beyond a certain density. Another application of imputation is to increase the size of the training set with un-genotyped animals. This strategy can be particularly successful when a set of closely related individuals are genotyped. ----- Methods: Imputation on completely un-genotyped dams was performed using known genotypes from the sire of each dam, one offspring and the offspring’s sire. Two methods were applied based on either allele or haplotype frequencies to infer genotypes at ambiguous loci. Results of these methods and of two available software packages were compared. Quality of imputation under different population structures was assessed. The impact of using imputed dams to enlarge training sets on the accuracy of genomic predictions was evaluated for different populations, heritabilities and sizes of training sets. ----- Results: Imputation accuracy ranged from 0.52 to 0.93 depending on the population structure and the method used. The method that used allele frequencies performed better than the method based on haplotype frequencies. Accuracy of imputation was higher for populations with higher levels of linkage disequilibrium and with larger proportions of markers with more extreme allele frequencies. Inclusion of imputed dams in the training set increased the accuracy of genomic predictions. Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario. Generally, the larger the accuracy already obtained with the genotyped training set, the lower the increase in accuracy achieved by adding imputed dams. ----- Conclusions: Whenever a reference population resembling the family configuration considered here is available, imputation can be used to achieve an extra increase in accuracy of genomic predictions by enlarging the training set with completely un-genotyped dams. This strategy was shown to be particularly useful for populations with lower levels of linkage disequilibrium, for genomic selection on traits with low heritability, and for species or breeds for which the size of the reference population is limited.

An analysis of household farm investment decisions under varying land tenure arrangements in Ghana

Land tenure insecurity is widely perceived as a disincentive for long-term land improvement investment hence the objective of this paper is to evaluate how tenure (in)security associated with different land use arrangements in Ghana influenced households’ plot level investment decisions and choices. The paper uses data from the Farmer-Based Organisations (FBO) survey. The FBO survey collected information from 2,928 households across three ecological zones of Ghana using multistaged cluster sampling. Probit and Tobit models tested the effects of land tenancy and ownership arrangements on households’ investment behaviour while controlling other factors. It was found that marginal farm size was inversely related to tenure insecurity while tenure insecurity correlate positively with value of farm land and not farm size. Individual ownership and documentation of land significantly reduced the probability of households losing uncultivated lands. Individual land ownership increased both the probability of investing and level of investments made in land improvement and irrigation probably due to increasing importance households place on land ownership. Two possible explanations for this finding are: First, that land markets and land relations have changed significantly over the last two decades with increasing money transaction and fixed agreements propelled by population growth and increasing value of land. Secondly, inclusion of irrigation investment as a long term investment in land raises the value of household investment and the time period required to reap the returns on the investments. Households take land ownership and duration of tenancy into consideration if the resource implications of land investments are relatively huge and the time dimension for harvesting returns to investments is relatively long.

Structural Dynamics Model of a Cartesian Robot

Methods are developed for predicting vibration response characteristics of systems which change configuration during operation. A cartesian robot, an example of such a position-dependent system, served as a test case for these methods and was studied in detail. The chosen system model was formulated using the technique of Component Mode Synthesis (CMS). The model assumes that he system is slowly varying, and connects the carriages to each other and to the robot structure at the slowly varying connection points. The modal data required for each component is obtained experimentally in order to get a realistic model. The analysis results in prediction of vibrations that are produced by the inertia forces as well as gravity and friction forces which arise when the robot carriages move with some prescribed motion. Computer simulations and experimental determinations are conducted in order to calculate the vibrations at the robot end-effector. Comparisons are shown to validate the model in two ways: for fixed configuration the mode shapes and natural frequencies are examined, and then for changing configuration the residual vibration at the end of the mode is evaluated. A preliminary study was done on a geometrically nonlinear system which also has position-dependency. The system consisted of a flexible four-bar linkage with elastic input and output shafts. The behavior of the rocker-beam is analyzed for different boundary conditions to show how some limiting cases are obtained. A dimensional analysis leads to an evaluation of the consequences of dynamic similarity on the resulting vibration.

Classification of textures seen from different distances and under varying illumination direction

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

Active regions for colour texture segmentation integrating region and boundary information

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

New delay-dependent stability criteria for uncertain neutral systems with mixed time-varying delays and nonlinear perturbations

The problem of stability analysis for a class of neutral systems with mixed time-varying neutral, discrete and distributed delays and nonlinear parameter perturbations is addressed. By introducing a novel Lyapunov-Krasovskii functional and combining the descriptor model transformation, the Leibniz-Newton formula, some free-weighting matrices, and a suitable change of variables, new sufficient conditions are established for the stability of the considered system, which are neutral-delay-dependent, discrete-delay-range dependent, and distributeddelay-dependent. The conditions are presented in terms of linear matrix inequalities (LMIs) and can be efficiently solved using convex programming techniques. Two numerical examples are given to illustrate the efficiency of the proposed method

Image segmentation integrating colour, texture and boundary information

La tesis se centra en la Visión por Computador y, más concretamente, en la segmentación de imágenes, la cual es una de las etapas básicas en el análisis de imágenes y consiste en la división de la imagen en un conjunto de regiones visualmente distintas y uniformes considerando su intensidad, color o textura. Se propone una estrategia basada en el uso complementario de la información de región y de frontera durante el proceso de segmentación, integración que permite paliar algunos de los problemas básicos de la segmentación tradicional. La información de frontera permite inicialmente identificar el número de regiones presentes en la imagen y colocar en el interior de cada una de ellas una semilla, con el objetivo de modelar estadísticamente las características de las regiones y definir de esta forma la información de región. Esta información, conjuntamente con la información de frontera, es utilizada en la definición de una función de energía que expresa las propiedades requeridas a la segmentación deseada: uniformidad en el interior de las regiones y contraste con las regiones vecinas en los límites. Un conjunto de regiones activas inician entonces su crecimiento, compitiendo por los píxeles de la imagen, con el objetivo de optimizar la función de energía o, en otras palabras, encontrar la segmentación que mejor se adecua a los requerimientos exprsados en dicha función. Finalmente, todo esta proceso ha sido considerado en una estructura piramidal, lo que nos permite refinar progresivamente el resultado de la segmentación y mejorar su coste computacional. La estrategia ha sido extendida al problema de segmentación de texturas, lo que implica algunas consideraciones básicas como el modelaje de las regiones a partir de un conjunto de características de textura y la extracción de la información de frontera cuando la textura es presente en la imagen. Finalmente, se ha llevado a cabo la extensión a la segmentación de imágenes teniendo en cuenta las propiedades de color y textura. En este sentido, el uso conjunto de técnicas no-paramétricas de estimación de la función de densidad para la descripción del color, y de características textuales basadas en la matriz de co-ocurrencia, ha sido propuesto para modelar adecuadamente y de forma completa las regiones de la imagen. La propuesta ha sido evaluada de forma objetiva y comparada con distintas técnicas de integración utilizando imágenes sintéticas. Además, se han incluido experimentos con imágenes reales con resultados muy positivos.