Inflation-indexed instruments provide a real return and protect investors from the erosion of the purchasing power of money. Hence, inflation-indexed markets grow very fast day by day. In this thesis, we focus on pricing of the inflation-indexed swaps and swaptions which are the most liquid derivative products traded in the inflation-indexed markets. Firstly, we review the Hull-White extended Vasicek model in the HJM framework. Then, we use this model to price inflation-indexed swaps. Also, pricing of inflation-indexed swaptions is given using Black&rsquo / s market model.

This paper discusses the approximate and the exact n-point D-optimal design problems for the common multivariate linear and quadratic polynomial regression on some convex design spaces. For the linear polynomial regression, the design space considered are q-simplex, q-ball and convex hull of a set of finite points. It is shown that the approximate and the exact n-point D-optimal designs are concentrated on the extreme points of the design space. The structure of the optimal designs on regular polygons or regular polyhedra is also discussed. For the quadratic polynomial regression, the design space considered is a q-ball. The configuration of the approximate and the exact n-point D-optimal designs for quadratic model in two variables on a disk are investigated.

Our work applies techniques for blending and tightening solid shapes represented by sets. We require that the output contain one set and exclude a second set, and then we optimize the boundary separating the two sets. Working within that framework, we present mason, tightening, tight hulls, tight blends, and the medial cover, with details for implementation. Mason uses opening and closing techniques from mathematical morphology to smooth small features. By contrast, tightening uses mean curvature flow to minimize the measure of the boundary separating the opening of the interior of the closed input set from the opening of its complement, guaranteeing a mean curvature bound. The tight hull offers a significant generalization of the convex hull subject to volumetric constraints, introducing developable boundary patches connecting the constraints. Tight blends then use opening to replicate some of the behaviors from tightenings by applying tight hulls. The medial cover provides a means for adjusting the topology of a tight hull or tight blend, and it provides an implementation technique for two-dimensional polygonal inputs. Collectively, we offer applications for boundary estimation, three-dimensional solid design, blending, normal field simplification, and polygonal repair. We consequently establish the value of blending and tightening as tools for solid modeling.

Ph. D. : Computer science : Univ. of California at Berkeley : 1994.

All possible convex hull (i.e. the minimum area convex polygon containing the planar set) algorithms ever published in scientific press have been analysed in this work. Two new convex hull algorithms created by myself have been presented. The running time of analysed algorithms has been surveyed. Three most popular algorithms (Graham Scan, Jarvis March and Quickhull), the oldest algorithm (Brute Force) as well as the both new ones have been implemented. Efficiency experiments have been carried out with them. The algorithms created by me achieved the best results. In order to raise the efficiency of all the algorithms I suggested a priori filtration of points, which decreases the amount of the original points by almost 50% and, consequently, the speed of algorithms is increased. The major part of this master work will be published in the magazine “Technological and economic development of economy”. Besides, the report of this work has been made in the conference of Lithuanian young scientists, called “Operation analysis and application”.

Šiame darbe yra trumpai aprašomi algoritmai, kurie naudoja nereikalingus skaičiavimus, ieškant iškilojo apvalkalo taškų. Pateikiamas naujas „Radaro“ algoritmas, kuris iškilojo apvalkalo taškus randa išrinkimo būdu. Pateikiamos ir trys „Radaro“ algoritmo realizacijos. Graham, Jarvi, „Radaro“ algoritmai bei „Radaro“ algoritmo trys realizacijos realizuojamos dvejais būdais: statiniais masyvais ir dinaminiais masyvais. Realizavus tris algoritmus (Graham, Jarvi, „Radaro“) ir tris „Radaro“ algoritmo realizacijas, buvo analizuojamas algoritmų atlikimo laikas. / There are shortly presented algorithms which use unnecessary calculations in order to find convex hull. In this work you can discover new “Radar” algorithm which finds convex hull by using selecting method and three ways of realization of this algorithm. Graham, Jarvi, “Radar” algorithms and three ways of realization of “Radar” algorithm are realized in two ways: static array and dynamic array. There were analyzed time needed for execution of three algorithms (Graham, Jarvi and “Radar”) and three ways of realization of “Radar” algorithm.

Cellular automata (CA) are an interesting computation medium to study because of their simplicity and inherently parallel operation. These characteristics make them a useful and efficient computation tool for applications such as cryptography and physical systems modelling, particularly when implemented on specialized parallel hardware. In this dissertation, we study a number of applications of CA and develop new theoretical results used for them. We begin by presenting conditions which guarantee that a composition of marker cellular automata has the same neighbourhood as each of the individual components. We show that, under certain technical assumptions, a marker cellular automaton has a unique inverse with a given neighbourhood. We use these results to develop a working key generation algorithm for a public-key cryptosystem based on reversible cellular automata originally conceived by Kari. We also give an improvement to a CA algorithm which solves a version of the convex hull problem, ensuring that the algorithm does not require a global rule change and correcting the operation in a special case. Finally, we study a modified version of an established CA-based car traffic flow model for the single-lane highway case, and use CA as a modelling tool to investigate the coverage problem in wireless sensor network design. We developed functional software implementations for all of these experiments. / Thesis (Master, Computing) -- Queen's University, 2009-03-23 11:20:58.666

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A series of experiments were conducted to investigate the nutritional value of a new oat variety developed by the Crop Development Centre at the University of Saskatchewan. Trials 1 and 2 evaluated performance of steers fed a low lignin hull, high oil groat (LLH-HOG) oat as a replacement for barley or corn. In trial 1, 400 steers were fed one of two diets with barley or the LLH-HOG oat at 37.8% of the diet DM. Dry matter intake was lower (P=0.02) and gain to feed improved (P0.01) for steers fed the oat-based diet. In trial 2, 240 steers were finished diets with barley, corn or the LLH-HOG oat at 88.2% of the finishing diet (DM). During finishing, steers on the oat diet had lower (P0.01) ADG, body and carcass (P<0.01) weights than barley or corn-fed cattle reflecting lower (P0.01) DMI. In trial 3, 20 steers were fed one of seven diets consisting of barley silage and 0, 28, 56, or 84% LLH-HOG oat or barley grain (DM basis) to compare nutrient digestibility. Apparent DM, OM, ADF and NDF digestibility coefficients were lower (P<0.05) for LLH-HOG oat-based diets compared to barley-based diets. Apparent CP and EE digestibility coefficients were higher (P<0.05) for the LLH-HOG oat diets. Trial 4 was conducted to assess ruminal fermentation differences between LLH-HOG oat- or barley-based finishing diets using four rumen cannulated steers. No diet effects (P>0.05) were observed for total ruminal VFA concentration or molar proportions of individual VFA however mean ruminal pH was lower (P=0.01) for steers fed the LLH-HOG oat-finishing diet. Further, the extent of pH decline in oat-fed cattle was greater (P<0.01) than for barley-fed cattle. The results indicate that the energy value of the LLH-HOG oat is equivalent or superior to that of barley for growing cattle. However, further research is required to identify factors limiting feed intake of cattle fed this new oat type in finishing diets.

In the current water resources scientific literature, a wide variety of engineering design problems are solved in a simulation-optimization framework. These problems can have single or multiple objective functions and their decision variables can have discrete or continuous values. The majority of current literature in the field of water resources systems optimization report using heuristic global optimization algorithms, including evolutionary algorithms, with great success. These algorithms have multiple parameters that control their behavior both in terms of computational efficiency and the ability to find near globally optimal solutions. Values of these parameters are generally obtained by trial and error and are case study dependent. On the other hand, water resources simulation-optimization problems often have computationally intensive simulation models that can require seconds to hours for a single simulation. Furthermore, analysts may have limited computational budget to solve these problems, as such, the analyst may not be able to spend some of the computational budget to fine-tune the algorithm settings and parameter values. So, in general, algorithm parsimony in the number of parameters is an important factor in the applicability and performance of optimization algorithms for solving computationally intensive problems. A major contribution of this thesis is the development of a highly efficient, single objective, parsimonious optimization algorithm for solving problems with discrete decision variables. The algorithm is called Hybrid Discrete Dynamically Dimensioned Search, HD-DDS, and is designed based on Dynamically Dimensioned Search (DDS) that was developed by Tolson and Shoemaker (2007) for solving single objective hydrologic model calibration problems with continuous decision variables. The motivation for developing HD-DDS comes from the parsimony and high performance of original version of DDS. Similar to DDS, HD-DDS has a single parameter with a robust default value. HD-DDS is successfully applied to several benchmark water distribution system design problems where decision variables are pipe sizes among the available pipe size options. Results show that HD-DDS exhibits superior performance in specific comparisons to state-of-the-art optimization algorithms. The parsimony and efficiency of the original and discrete versions of DDS and their successful application to single objective water resources optimization problems with discrete and continuous decision variables motivated the development of a multi-objective optimization algorithm based on DDS. This algorithm is called Pareto Archived Dynamically Dimensioned Search (PA-DDS). The algorithm parsimony is a major factor in the design of PA-DDS. PA-DDS has a single parameter from its search engine DDS. In each iteration, PA-DDS selects one archived non-dominated solution and perturbs it to search for new solutions. The solution perturbation scheme of PA-DDS is similar to the original and discrete versions of DDS depending on whether the decision variable is discrete or continuous. So, PA-DDS can handle both types of decision variables. PA-DDS is applied to several benchmark mathematical problems, water distribution system design problems, and water resources model calibration problems with great success. It is shown that hypervolume contribution, HVC1, as defined in Knowles et al. (2003) is the superior selection metric for PA-DDS when solving multi-objective optimization problems with Pareto fronts that have a general (unknown) shape. However, one of the main contributions of this thesis is the development of a selection metric specifically designed for solving multi-objective optimization problems with a known or expected convex Pareto front such as water resources model calibration problems. The selection metric is called convex hull contribution (CHC) and makes the optimization algorithm sample solely from a subset of archived solutions that form the convex approximation of the Pareto front. Although CHC is generally applicable to any stochastic search optimization algorithm, it is applied to PA-DDS for solving six water resources calibration case studies with two or three objective functions. These case studies are solved by PA-DDS with CHC and HVC1 selections using 1,000 solution evaluations and by PA-DDS with CHC selection and two popular multi-objective optimization algorithms, AMALGAM and ε-NSGAII, using 10,000 solution evaluations. Results are compared based on the best case and worst case performances (out of multiple optimization trials) from each algorithm to measure the expected performance range for each algorithm. Comparing the best case performance of these algorithms shows that, PA-DDS with CHC selection using 1,000 solution evaluations perform very well in five out of six case studies. Comparing the worst case performance of the algorithms shows that with 1,000 solution evaluations, PA-DDS with CHC selection perform well in four out of six case studies. Furthermore, PA-DDS with CHC selection using 10,000 solution evaluations perform comparable to AMALGAM and ε-NSGAII. Therefore, it is concluded that PA-DDS with CHC selection is a powerful optimization algorithm for finding high quality solutions of multi-objective water resources model calibration problems with convex Pareto front especially when the computational budget is limited.