Numerical aspects in the data model of conceptual information systems

While most data analysis and decision support tools use numerical aspects of the data, Conceptual Information Systems focus on their conceptual structure. This paper discusses how both approaches can be combined.

Ein Algorithmus zur numerischen Verifikation der äquivarianten Tamagawazahlvermutung für eine Familie von Zahlkörpererweiterungen

Sei $N/K$ eine galoissche Zahlkörpererweiterung mit Galoisgruppe $G$, so dass es in $N$ eine Stelle mit voller Zerlegungsgruppe gibt. Die vorliegende Arbeit beschäftigt sich mit Algorithmen, die für das gegebene Fallbeispiel $N/K$, die äquivariante Tamagawazahlvermutung von Burns und Flach für das Paar $(h^0(Spec(N), \mathbb{Z}[G]))$ (numerisch) verifizieren. Grob gesprochen stellt die äquivariante Tamagawazahlvermutung (im Folgenden ETNC) in diesem Spezialfall einen Zusammenhang her zwischen Werten von Artinschen $L$-Reihen zu den absolut irreduziblen Charakteren von $G$ und einer Eulercharakteristik, die man in diesem Fall mit Hilfe einer sogenannten Tatesequenz konstruieren kann. Unter den Voraussetzungen 1. es gibt eine Stelle $v$ von $N$ mit voller Zerlegungsgruppe, 2. jeder irreduzible Charakter $\chi$ von $G$ erfüllt eine der folgenden Bedingungen 2a) $\chi$ ist abelsch, 2b) $\chi(G) \subset \mathbb{Q}$ und $\chi$ ist eine ganzzahlige Linearkombination von induzierten trivialen Charakteren; wird ein Algorithmus entwickelt, der ETNC für jedes Fallbeispiel $N/\mathbb{Q}$ vollständig beweist. Voraussetzung 1. erlaubt es eine Idee von Chinburg ([Chi89]) umzusetzen zur algorithmischen Berechnung von Tatesequenzen. Dabei war es u.a. auch notwendig lokale Fundamentalklassen zu berechnen. Im höchsten zahm verzweigten Fall haben wir hierfür einen Algorithmus entwickelt, der ebenfalls auf den Ideen von Chinburg ([Chi85]) beruht, die auf Arbeiten von Serre [Ser] zurück gehen. Für nicht zahm verzweigte Erweiterungen benutzen wir den von Debeerst ([Deb11]) entwickelten Algorithmus, der ebenfalls auf Serre's Arbeiten beruht. Voraussetzung 2. wird benötigt, um Quotienten aus den $L$-Werten und Regulatoren exakt zu berechnen. Dies gelingt, da wir im Fall von abelschen Charakteren auf die Theorie der zyklotomischen Einheiten zurückgreifen können und im Fall (b) auf die analytische Klassenzahlformel von Zwischenkörpern. Ohne die Voraussetzung 2. liefern die Algorithmen für jedes Fallbeispiel $N/K$ immer noch eine numerische Verifikation bis auf Rechengenauigkeit. Den Algorithmus zur numerischen Verifikation haben wir für $A_4$-Erweiterungen über $\mathbb{Q}$ in das Computeralgebrasystem MAGMA implementiert und für 27 Erweiterungen die äquivariante Tamagawazahlvermutung numerisch verifiziert.

Numerical Methods for the Unsteady Compressible Navier-Stokes Equations

We consider numerical methods for the compressible time dependent Navier-Stokes equations, discussing the spatial discretization by Finite Volume and Discontinuous Galerkin methods, the time integration by time adaptive implicit Runge-Kutta and Rosenbrock methods and the solution of the appearing nonlinear and linear equations systems by preconditioned Jacobian-Free Newton-Krylov, as well as Multigrid methods. As applications, thermal Fluid structure interaction and other unsteady flow problems are considered. The text is aimed at both mathematicians and engineers.

Die aeroelastische Stabilitätsanalyse – ein praxisnaher Ansatz zur intervalltheoretischen Betrachtung von Modellierungsunsicherheiten am Flugzeug

Die Untersuchung des dynamischen aeroelastischen Stabilitätsverhaltens von Flugzeugen erfordert sehr komplexe Rechenmodelle, welche die wesentlichen elastomechanischen und instationären aerodynamischen Eigenschaften der Konstruktion wiedergeben sollen. Bei der Modellbildung müssen einerseits Vereinfachungen und Idealisierungen im Rahmen der Anwendung der Finite Elemente Methode und der aerodynamischen Theorie vorgenommen werden, deren Auswirkungen auf das Simulationsergebnis zu bewerten sind. Andererseits können die strukturdynamischen Kenngrößen durch den Standschwingungsversuch identifiziert werden, wobei die Ergebnisse Messungenauigkeiten enthalten. Für eine robuste Flatteruntersuchung müssen die identifizierten Unwägbarkeiten in allen Prozessschritten über die Festlegung von unteren und oberen Schranken konservativ ermittelt werden, um für alle Flugzustände eine ausreichende Flatterstabilität sicherzustellen. Zu diesem Zweck wird in der vorliegenden Arbeit ein Rechenverfahren entwickelt, welches die klassische Flatteranalyse mit den Methoden der Fuzzy- und Intervallarithmetik verbindet. Dabei werden die Flatterbewegungsgleichungen als parameterabhängiges nichtlineares Eigenwertproblem formuliert. Die Änderung der komplexen Eigenlösung infolge eines veränderlichen Einflussparameters wird mit der Methode der numerischen Fortsetzung ausgehend von der nominalen Startlösung verfolgt. Ein modifizierter Newton-Iterations-Algorithmus kommt zur Anwendung. Als Ergebnis liegen die berechneten aeroelastischen Dämpfungs- und Frequenzverläufe in Abhängigkeit von der Fluggeschwindigkeit mit Unschärfebändern vor.

Numerical Feasibility Study for Treated Wastewater Recharge as a Tool to Impede Saltwater Intrusion in the Coastal Aquifer of Gaza – Palestine

The ongoing depletion of the coastal aquifer in the Gaza strip due to groundwater overexploitation has led to the process of seawater intrusion, which is continually becoming a serious problem in Gaza, as the seawater has further invaded into many sections along the coastal shoreline. As a first step to get a hold on the problem, the artificial neural network (ANN)-model has been applied as a new approach and an attractive tool to study and predict groundwater levels without applying physically based hydrologic parameters, and also for the purpose to improve the understanding of complex groundwater systems and which is able to show the effects of hydrologic, meteorological and anthropogenic impacts on the groundwater conditions. Prediction of the future behaviour of the seawater intrusion process in the Gaza aquifer is thus of crucial importance to safeguard the already scarce groundwater resources in the region. In this study the coupled three-dimensional groundwater flow and density-dependent solute transport model SEAWAT, as implemented in Visual MODFLOW, is applied to the Gaza coastal aquifer system to simulate the location and the dynamics of the saltwater–freshwater interface in the aquifer in the time period 2000-2010. A very good agreement between simulated and observed TDS salinities with a correlation coefficient of 0.902 and 0.883 for both steady-state and transient calibration is obtained. After successful calibration of the solute transport model, simulation of future management scenarios for the Gaza aquifer have been carried out, in order to get a more comprehensive view of the effects of the artificial recharge planned in the Gaza strip for some time on forestall, or even to remedy, the presently existing adverse aquifer conditions, namely, low groundwater heads and high salinity by the end of the target simulation period, year 2040. To that avail, numerous management scenarios schemes are examined to maintain the ground water system and to control the salinity distributions within the target period 2011-2040. In the first, pessimistic scenario, it is assumed that pumping from the aquifer continues to increase in the near future to meet the rising water demand, and that there is not further recharge to the aquifer than what is provided by natural precipitation. The second, optimistic scenario assumes that treated surficial wastewater can be used as a source of additional artificial recharge to the aquifer which, in principle, should not only lead to an increased sustainable yield of the latter, but could, in the best of all cases, revert even some of the adverse present-day conditions in the aquifer, i.e., seawater intrusion. This scenario has been done with three different cases which differ by the locations and the extensions of the injection-fields for the treated wastewater. The results obtained with the first (do-nothing) scenario indicate that there will be ongoing negative impacts on the aquifer, such as a higher propensity for strong seawater intrusion into the Gaza aquifer. This scenario illustrates that, compared with 2010 situation of the baseline model, at the end of simulation period, year 2040, the amount of saltwater intrusion into the coastal aquifer will be increased by about 35 %, whereas the salinity will be increased by 34 %. In contrast, all three cases of the second (artificial recharge) scenario group can partly revert the present seawater intrusion. From the water budget point of view, compared with the first (do nothing) scenario, for year 2040, the water added to the aquifer by artificial recharge will reduces the amount of water entering the aquifer by seawater intrusion by 81, 77and 72 %, for the three recharge cases, respectively. Meanwhile, the salinity in the Gaza aquifer will be decreased by 15, 32 and 26% for the three cases, respectively.

An O(N) Algorithm for Three-Dimensional N-Body Simulations

We develop an algorithm that computes the gravitational potentials and forces on N point-masses interacting in three-dimensional space. The algorithm, based on analytical techniques developed by Rokhlin and Greengard, runs in order N time. In contrast to other fast N-body methods such as tree codes, which only approximate the interaction potentials and forces, this method is exact ?? computes the potentials and forces to within any prespecified tolerance up to machine precision. We present an implementation of the algorithm for a sequential machine. We numerically verify the algorithm, and compare its speed with that of an O(N2) direct force computation. We also describe a parallel version of the algorithm that runs on the Connection Machine in order 0(logN) time. We compare experimental results with those of the sequential implementation and discuss how to minimize communication overhead on the parallel machine.

Natural Object Categorization

This thesis addresses the problem of categorizing natural objects. To provide a criteria for categorization we propose that the purpose of a categorization is to support the inference of unobserved properties of objects from the observed properties. Because no such set of categories can be constructed in an arbitrary world, we present the Principle of Natural Modes as a claim about the structure of the world. We first define an evaluation function that measures how well a set of categories supports the inference goals of the observer. Entropy measures for property uncertainty and category uncertainty are combined through a free parameter that reflects the goals of the observer. Natural categorizations are shown to be those that are stable with respect to this free parameter. The evaluation function is tested in the domain of leaves and is found to be sensitive to the structure of the natural categories corresponding to the different species. We next develop a categorization paradigm that utilizes the categorization evaluation function in recovering natural categories. A statistical hypothesis generation algorithm is presented that is shown to be an effective categorization procedure. Examples drawn from several natural domains are presented, including data known to be a difficult test case for numerical categorization techniques. We next extend the categorization paradigm such that multiple levels of natural categories are recovered; by means of recursively invoking the categorization procedure both the genera and species are recovered in a population of anaerobic bacteria. Finally, a method is presented for evaluating the utility of features in recovering natural categories. This method also provides a mechanism for determining which features are constrained by the different processes present in a multiple modal world.

A Compilation Strategy for Numerical Programs Based on Partial Evaluation

This work demonstrates how partial evaluation can be put to practical use in the domain of high-performance numerical computation. I have developed a technique for performing partial evaluation by using placeholders to propagate intermediate results. For an important class of numerical programs, a compiler based on this technique improves performance by an order of magnitude over conventional compilation techniques. I show that by eliminating inherently sequential data-structure references, partial evaluation exposes the low-level parallelism inherent in a computation. I have implemented several parallel scheduling and analysis programs that study the tradeoffs involved in the design of an architecture that can effectively utilize this parallelism. I present these results using the 9- body gravitational attraction problem as an example.

KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods

KAM is a computer program that can automatically plan, monitor, and interpret numerical experiments with Hamiltonian systems with two degrees of freedom. The program has recently helped solve an open problem in hydrodynamics. Unlike other approaches to qualitative reasoning about physical system dynamics, KAM embodies a significant amount of knowledge about nonlinear dynamics. KAM's ability to control numerical experiments arises from the fact that it not only produces pictures for us to see, but also looks at (sic---in its mind's eye) the pictures it draws to guide its own actions. KAM is organized in three semantic levels: orbit recognition, phase space searching, and parameter space searching. Within each level spatial properties and relationships that are not explicitly represented in the initial representation are extracted by applying three operations ---(1) aggregation, (2) partition, and (3) classification--- iteratively.

Parameter Estimation in Chaotic Systems

This report examines how to estimate the parameters of a chaotic system given noisy observations of the state behavior of the system. Investigating parameter estimation for chaotic systems is interesting because of possible applications for high-precision measurement and for use in other signal processing, communication, and control applications involving chaotic systems. In this report, we examine theoretical issues regarding parameter estimation in chaotic systems and develop an efficient algorithm to perform parameter estimation. We discover two properties that are helpful for performing parameter estimation on non-structurally stable systems. First, it turns out that most data in a time series of state observations contribute very little information about the underlying parameters of a system, while a few sections of data may be extraordinarily sensitive to parameter changes. Second, for one-parameter families of systems, we demonstrate that there is often a preferred direction in parameter space governing how easily trajectories of one system can "shadow'" trajectories of nearby systems. This asymmetry of shadowing behavior in parameter space is proved for certain families of maps of the interval. Numerical evidence indicates that similar results may be true for a wide variety of other systems. Using the two properties cited above, we devise an algorithm for performing parameter estimation. Standard parameter estimation techniques such as the extended Kalman filter perform poorly on chaotic systems because of divergence problems. The proposed algorithm achieves accuracies several orders of magnitude better than the Kalman filter and has good convergence properties for large data sets.

On Convergence Properties of the EM Algorithm for Gaussian Mixtures

"Expectation-Maximization'' (EM) algorithm and gradient-based approaches for maximum likelihood learning of finite Gaussian mixtures. We show that the EM step in parameter space is obtained from the gradient via a projection matrix $P$, and we provide an explicit expression for the matrix. We then analyze the convergence of EM in terms of special properties of $P$ and provide new results analyzing the effect that $P$ has on the likelihood surface. Based on these mathematical results, we present a comparative discussion of the advantages and disadvantages of EM and other algorithms for the learning of Gaussian mixture models.

Hierarchical Mixtures of Experts and the EM Algorithm

We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are generalized linear models (GLIM's). Learning is treated as a maximum likelihood problem; in particular, we present an Expectation-Maximization (EM) algorithm for adjusting the parameters of the architecture. We also develop an on-line learning algorithm in which the parameters are updated incrementally. Comparative simulation results are presented in the robot dynamics domain.

The Kineticist's Workbench: Combining Symbolic and Numerical Methods in the Simulation of Chemical Reaction Mechanisms

The Kineticist's Workbench is a program that simulates chemical reaction mechanisms by predicting, generating, and interpreting numerical data. Prior to simulation, it analyzes a given mechanism to predict that mechanism's behavior; it then simulates the mechanism numerically; and afterward, it interprets and summarizes the data it has generated. In performing these tasks, the Workbench uses a variety of techniques: graph- theoretic algorithms (for analyzing mechanisms), traditional numerical simulation methods, and algorithms that examine simulation results and reinterpret them in qualitative terms. The Workbench thus serves as a prototype for a new class of scientific computational tools---tools that provide symbiotic collaborations between qualitative and quantitative methods.

Preconditioning and iterative solution of symmetric indefinite linear systems arising from interior point methods for linear programming

We study the preconditioning of symmetric indefinite linear systems of equations that arise in interior point solution of linear optimization problems. The preconditioning method that we study exploits the block structure of the augmented matrix to design a similar block structure preconditioner to improve the spectral properties of the resulting preconditioned matrix so as to improve the convergence rate of the iterative solution of the system. We also propose a two-phase algorithm that takes advantage of the spectral properties of the transformed matrix to solve for the Newton directions in the interior-point method. Numerical experiments have been performed on some LP test problems in the NETLIB suite to demonstrate the potential of the preconditioning method discussed.