This paper explores how known machine learning techniques can be applied in unique ways to simplify software and therefore dramatically increase its usability. As software has increased in popularity, its complexity has increased in lockstep, to a point where it has become burdensome. By shifting the focus from the software to the user, great advances can be achieved by way of simplification. The example problem used in this report is well known: suggest local dining choices tailored to a specific person based on known habits and those of similar people. By analyzing past choices and applying likely probabilities, assumptions can be made to reduce user interaction, allowing the user to realize the benefits of the software faster and more frequently. This is accomplished with Java Servlets, Apache Mahout machine learning libraries, and various third party resources to gather dimensions on each recommendation. / text

In this paper we discuss the identification of parameter functions in material models for elastic large deformations. A model of the the forward problem is given, where the displacement of a deformed material is found as the solution of a n onlinear PDE. Here, the crucial point is the definition of the 2nd Piola-Kirchhoff stress tensor by using several material laws including a number of material parameters. In the main part of the paper we consider the identification of such parameters from measured displacements, where the inverse problem is given as an optimal control problem. We introduce a solution of the identification problem with Lagrange and SQP methods. The presented algorithm is applied to linear elastic material with large deformations.

After introducing concepts from convex analysis, we study how to continuously transform one convex function into another. A natural choice is the arithmetic average, as it is pointwise continuous; however, this choice fails to average functions with different domains. On the contrary, the proximal average is not only continuous (in the epi-topology) but can actually average functions with disjoint domains. In fact, the proximal average not only inherits strict convexity (like the arithmetic average) but also inherits smoothness and differentiability (unlike the arithmetic average). Then we introduce a computational framework for computer-aided convex analysis. Motivated by the proximal average, we notice that the class of piecewise linear-quadratic (PLQ) functions is closed under (positive) scalar multiplication, addition, Fenchel conjugation, and Moreau envelope. As a result, the PLQ framework gives rise to linear-time and linear-space algorithms for convex PLQ functions. We extend this framework to nonconvex PLQ functions and present an explicit convex hull algorithm. Finally, we discuss a method to find primal-dual symmetric antiderivatives from cyclically monotone operators. As these antiderivatives depend on the minimal and maximal Rockafellar functions [5, Theorem 3.5, Corollary 3.10], it turns out that the minimal and maximal function in [12, p.132,p.136] are indeed the same functions. Algorithms used to compute these antiderivatives can be formulated as shortest path problems.

Numerous advantages attained by integrating Distributed Generation (DG) in distribution systems. These advantages include decreasing power losses and improving voltage profiles. Such benefits can be achieved and enhanced if DGs are optimally sized and located in the systems. In this thesis, the optimal DG placement and sizing problem is investigated using two approaches. First, the optimization problem is treated as single-objective optimization problem, where the system’s active power losses are considered as the objective to be minimized. Secondly, the problem is tackled as a multi-objective one, focusing on DG installation costs. These problems are formulated as constrained nonlinear optimization problems using the Sequential Quadratic Programming method. A weighted sum method and a fuzzy decision-making method are presented to generate the Pareto optimal front and also to obtain the best compromise solution. Single and multiple DG installation cases are studied and compared to a case without DG, and a 15-bus radial distribution system and 33-bus meshed distribution system are used to demonstrate the effectiveness of the proposed methods.

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the 18th World Congress The International Federation of Automatic Control, Milano (Italy), August 28 - September 2, 2011

En 1993, Conway et Schneeberger fournirent un critère simple permettant de déterminer si une forme quadratique donnée représente tous les entiers positifs ; le théorème des 15. Dans ce mémoire, nous nous intéressons à un problème analogue, soit la recherche d’un critère similaire permettant de détecter si une forme quadratique en trois variables représente tous les entiers impairs. On débute donc par une introduction générale à la théorie des formes quadratiques, notamment en deux variables, puis on expose différents points de vue sous lesquels on peut les considérer. On décrit ensuite le théorème des 15 et ses généralisations, en soulignant les techniques utilisées dans la preuve de Bhargava. Enfin, on démontre deux théorèmes qui fournissent des critères permettant de déterminer si une forme quadratique ternaire représente tous les entiers impairs. / In 1993, Conway and Schneeberger gave a simple criterion allowing one to determine whether a given quadratic form represents all positive integers ; the 15-theorem. In this thesis, we investigate an analogous problem, that is the search for a similar criterion allowing one to detect if a quadratic form in three variables represents all odd integers. We start with a general introduction to the theory of quadratic forms, namely in two variables, then, we expose different points of view under which quadratic forms can be considered. We then describe the 15-theorem and its generalizations, with a particular emphasis on the techniques used in Bhargava’s proof of the theorem. Finally, we give a proof of two theorems which provide a criteria to determine whether a ternary quadratic form represents all odd integers. / Les calculs numériques ont été effectués à l'aide du logiciel SAGE.

Flutter is one of the primary aeroelastic phenomena that must be considered in aircraft design. Flutter is a self-sustaining structural vibration in which energy is extracted from the air flow and transferred to the structure. The amplitude of the vibration grows exponentially until structural failure occurs. Flutter stability requirements often influence the design of an aircraft, making accurate flutter prediction capabilities an essential part of the design process. Advances in computational fluid dynamics and computational power make it possible to solve the fluid flow and structural dynamics simultaneously, providing highly accurate solutions especially in the transonic flow regime. This procedure is, however, too time-consuming to be used in the design optimisation process. As a result panel codes, e.g., the doublet lattice method, and modal-based structural analysis methods are still being used extensively and continually improved. One application that is lagging in terms of accuracy and simplicity (from the user’s perspective) is the flutter analysis of T-tails. The flutter analysis of a T-tail usually involves the calculation of additional aerodynamic loads, apart from the loads calculated by the standard unsteady aerodynamic codes for conventional empennages. The popular implementations of the doublet lattice method do not calculate loads due to the in-plane motion (i.e., lateral or longitudinal motion) of the horizontal stabiliser or the in-plane loads on the stabiliser. In addition, these loads are dependent on the steady-state load distribution on the stabiliser, which is ignored in the doublet lattice method. The objective of the study was to extend the doublet lattice method to calculate the additional aerodynamic loads that are crucial for T-tail flutter analysis along with the customary unsteady air loads for conventional configurations. This was achieved by employing the Kutta-Joukowski theorem in the calculation of unsteady air loads on lifting surface panels. Calculating the additional unsteady air loads for T-tails within the doublet lattice method significantly reduces the human effort required for T-tail flutter analysis as well as the opportunities for introducing errors into the analysis. During the course of the study it became apparent that it was necessary to consider the quadratic mode shape components in addition to the linear mode shape components. Otherwise the unsteady loads due to the rotation (“tilting”) of the steady-state load on the stabiliser, one of the additional aerodynamic loads that are crucial for T-tail flutter analysis, would give rise to spurious generalised forces. In order to reduce the additional burden of determining the quadratic mode shape components, methods for calculating quadratic mode shape components using linear finite element analysis or estimating them from the linear mode shape components were developed. Wind tunnel tests were performed to validate the proposed computational method. A T-tail flutter model which incorporated a mechanism for changing the incidence angle of the horizontal stabiliser, and consequently the steady-state load distribution on the horizontal stabiliser, was used. The flutter speed of this model as a function of the horizontal stabiliser incidence was determined experimentally and compared to predictions. Satisfactory correlation was found between predicted and experimentally determined flutter speeds. / Thesis (M.Ing. (Chemical Engineering))--North-West University, Potchefstroom Campus, 2012

In this thesis modelling and solution methods for portfolio optimisation are presented. The investigations reported in this thesis extend the Markowitz mean-variance model to the domain of quadratic mixed integer programming (QMIP) models which are 'NP-hard' discrete optimisation problems. In addition to the modelling extensions a number of challenging aspects of solution algorithms are considered. The relative performances of sparse simplex (SSX) as well as the interior point method (IPM) are studied in detail. In particular, the roles of 'warmstart' and dual simplex are highlighted as applied to the construction of the efficient frontier which requires processing a family of problems; that is, the portfolio planning model stated in a parametric form. The method of solving QMIP models using the branch and bound algorithm is first developed; this is followed up by heuristics which improve the performance of the (discrete) solution algorithm. Some properties of the efficient frontier with discrete constraints are considered and a method of computing the discrete efficient frontier (DEF) efficiently is proposed. The computational investigation considers the efficiency and effectiveness in respect of the scale up properties of the proposed algorithm. The extensions of the real world models and the proposed solution algorithms make contribution as new knowledge.

In this thesis, application of linear control methods to control the attitude of a Low-Earth Orbit satellite is studied. Attitude control subsystem is first introduced by explaining attitude determination and control components in detail. Satellite dynamic equations are derived and linearized for controller design. Linear controller and linear quadratic regulator are chosen as controllers for attitude control. The actuators used for control are reaction wheels and magnetic torquers. MATLAB-SIMULINK program is used in order to simulate satellite dynamical model (actual nonlinear model) and controller model. In simulations, the satellite parameters are selected to be similar to the actual BILSAT-1 satellite parameters. In conclusion, simulations obtained from different linear control methods are compared within themselves and with nonlinear control methods, at the same time with that obtained from BILSAT-1 satellite log data.