Drought, which is an important result of the climate change, is one of the most serious natural hazards globally. It has been agreed all over the world that it has adverse impacts on the production of agriculture, which plays a major role in the economy of a country. Studies showed that the results of the drought directly affected the crop yields, and it seems that this negative impact will continue drastically soon. Moreover, many researches revealed that, Turkey will be affected from the results of climate change in many aspects, especially the agricultural production will encounter dry seasons after the rapid changes in the precipitation amount. Insurance is a well-established method, which is used to share the risk based on natural disasters by people and organizations. Furthermore, a new way of insuring against the weather shocks is designing index-based insurance, and it has gained special attention in many developing countries. In this study, our aim is to model weather index based drought insurance product to help the small holder farmers in the Cental Anatolia Region under different models. At first, time series techniques were applied to forecast the wheat yield relying on the past data. Then, the AMS (AgroMetShell) software outputs, NDVI (Normalized Difference Vegetation Index) values were used, and SPI values for distinct time steps were chosen to develop a basic threshold based drought insurance for each province. Linear regression equations were used to calculate the trigger points for weather index, afterwards based on these trigger levels / pure premium and indemnity calculations were made for each province separately. In addition to this, Panel Data Analysis were used to construct an alternative linear model for drought insurance. It can be helpful to understand the direct and actual effects of selected weather index measures on wheat yield and also reduce the basis risks for constructed contracts. A simple ratio was generated to compare the basis risk of the different index-based insurance contracts.

The construction of a substitution box (S-box) with high nonlinearity and high resiliency is an important research area in cryptography. In this thesis, t-resilient nxm S-box construction methods depending on linear block codes presented in &quot / A Construction of Resilient Functions with High Nonlinearity&quot / by T. Johansson and E. Pasalic in 2000, and two years later in &quot / Linear Codes in Generalized Construction of Resilient Functions with Very High Nonlinearity&quot / by E. Pasalic and S. Maitra are compared and the former one is observed to be more promising in terms of nonlinearity. The first construction method uses a set of nonintersecting [n-d,m,t+1] linear block codes in deriving t-resilient S-boxes of nonlinearity 2^(n-1)-2^(n-d-1),where d is a parameter to be maximized for high nonlinearity. For some cases, we have found better results than the results of Johansson and Pasalic, using their construction. As a distinguished reference for nxn S-box construction methods, we study the paper &quot / Differentially Uniform Mappings for Cryptography&quot / presented by K.Nyberg in Eurocrypt 1993. One of the two constructions of this paper, i.e., the inversion mapping described by Nyberg but first noticed in 1957 by L. Carlitz and S. Uchiyama, is used in the S-box of Rijndael, which is chosen as the Advanced Encryption Standard. We complete the details of some theorem and proposition proofs given by Nyberg.

The Swing options are the natural outcomes of the increasing uncertainty in the power markets, which came along with the deregulation process triggered by the UK government&rsquo / s action in 1990 to privatize the national electricity supply industry. Since then, the ways of handling the risks in the price generation process have been explored extensively. Producer-consumers of the power market felt confident as they were naturally hedged against the price fluctuations surrounding the large consumers. Companies with high power consumption liabilities on their books demanded tailored financial products that would shelter them from the upside risks while not preventing them from benefiting the low prices. Furthermore, more effective risk management practices are strongly dependent upon the successful parameterization of the underlying stochastic processes, which is also key to the effective pricing of derivatives traded in the market. In this thesis, we refer to the electricity spot price model developed jointly by Hambly, Howison and Kluge ([13]), which incorporates jumps and still maintains the analytical tractability. We also derive the forward curve dynamics implied by the spot price model and explore the effects on the forward curve dynamics of the spikes in spot price. As the main discussion of this thesis, the Grid Approach, which is a generalization of the Trinomial Forest Method, is applied to the electricity Swing options. We investigate the effects of spikes on the per right values of the Swing options with various number of exercise rights, as well as the sensitivities of the model-implied prices to several parameters.

Distributed optimal control problems with transient convection dominated diffusion convection reaction equations are considered. The problem is discretized in space by using three types of discontinuous Galerkin (DG) method: symmetric interior penalty Galerkin (SIPG), nonsymmetric interior penalty Galerkin (NIPG), incomplete interior penalty Galerkin (IIPG). For time discretization, Crank-Nicolson and backward Euler methods are used. The discretize-then-optimize approach is used to obtain the finite dimensional problem. For one-dimensional unconstrained problem, Newton-Conjugate Gradient method with Armijo line-search. For two-dimensional control constrained problem, active-set method is applied. A priori error estimates are derived for full discretized optimal control problem. Numerical results for one and two-dimensional distributed optimal control problems for diffusion convection equations with boundary layers confirm the predicted orders derived by a priori error estimates.

Two well-known types of water waves are shallow water waves and the solitary waves. The former waves are those waves which have larger wavelength than the local water depth and the latter waves are used for the ones which retain their shape and speed after colliding with each other. The most well known of the latter waves are Korteweg de Vries (KdV) equations, which are widely used in many branches of physics and engineering. These equations are nonlinear long waves and mathematically represented by partial differential equations (PDEs). For solving the KdV and KdV-type equations, several numerical methods were developed in the recent years which preserve their geometric structure, i.e. the Hamiltonian form, symplecticity and the integrals. All these methods are classified as symplectic and multisymplectic integrators. They produce stable solutions in long term integration, but they do not preserve the Hamiltonian and the symplectic structure at the same time. This thesis concerns the application of energy preserving average vector field integrator(AVF) to nonlinear Hamiltonian partial differential equations (PDEs) in canonical and non-canonical forms. Among the PDEs, Korteweg de Vries (KdV) equation, modified KdV equation, the Ito&rsquo / s system and the KdV-KdV systems are discetrized in space by preserving the skew-symmetry of the Hamiltonian structure. The resulting ordinary differential equations (ODEs) are solved with the AVF method. Numerical examples confirm that the energy is preserved in long term integration and the other integrals are well preserved too. Soliton and traveling wave solutions for the KdV type equations are accurate as those solved by other methods. The preservation of the dispersive properties of the AVF method is also shown for each PDE.

The special functions and, particularly, the classical orthogonal polynomials encountered in many branches of applied mathematics and mathematical physics satisfy a second order differential equation, which is known as the equation of the hypergeometric type. The variable coefficients in this equation of the hypergeometric type are of special structures. Depending on the coefficients the classical orthogonal polynomials associated with the names Jacobi, Laguerre and Hermite can be derived as solutions of this equation. In this thesis, these well known classical polynomials as well as another class of polynomials, which receive less attention in the literature called Bessel polynomials have been studied.

In cryptography, periodic sequences with terms in F2 are used almost everywhere. These sequences should have large linear complexity to be cryptographically strong. In fact, the linear complexity of a sequence should be close to its period. In this thesis, we study the expected value for N-periodic sequences with terms in the finite field Fq. This study is entirely devoted to W. Meidl and Harald Niederreiter&rsquo / s paper which is &ldquo / On the Expected Value of the Linear Complexity and the k-Error Linear Complexity of Periodic Sequences&rdquo / We only expand this paper, there is no improvement. In this paper there are important theorems and results about the expected value of linear complexity of periodic sequences.

In this thesis, the work of Menezes on the isomorphism classes of elliptic curves over finite fields of characteristic two is studied. Basic definitions and some facts of the elliptic curves required in this context are reviewed and group structure of elliptic curves are constructed. A fairly detailed investigation is made for the isomorphism classes of elliptic curves due to Menezes and Schoof. This work plays an important role in Elliptic Curve Digital Signature Algorithm. In this context, those isomorphism classes of elliptic curves recommended by National Institute of Standards and Technology are listed and their properties are discussed.

Remote sensing techniques are vital for early detection of several problems such as natural disasters, ecological problems and collecting information necessary for finding optimum solutions to those problems. Remotely sensed information has also important uses in predicting the future risks, urban planning, communication.Recent developments in remote sensing instrumentation offered a challenge to the mathematical and statistical methods to process the acquired information. Classification of satellite images in the context of land cover classification is the main concern of this study. Land cover classification can be performed by statistical learning methods like additive models, decision trees, neural networks, k-means methods which are already popular in unsupervised classification and clustering of image scene inverse problems. Due to the degradation and corruption of satellite images, the classification performance is limited both by the accuracy of clustering and by the extent of the classification. In this study, we are concerned with understanding the performance of the available unsupervised methods with k-means, supervised methods with Gaussian maximum likelihood which are very popular methods in land cover classification. A broader approach to the classification problem based on finding the optimal discriminants from a larger range of functions is considered also in this work. A novel method based on threshold decomposition and Boolean discriminant functions is developed as an implementable application of this approach. All methods are applied to BILSAT and Landsat satellite images using MATLAB software.

The selection of investment strategies and managing investment funds via employing portfolio insurance methods play an important role in asset liability management. Insurance strategies are designed to limit downside risk of portfolio while allowing some participation in potential gain of upside markets. In this thesis, we provide an extensive overview and investigation, particularly on the two most prominent portfolio insurance strategies: the Constant Proportion Portfolio Insurance (CPPI) and the Option-Based Portfolio Insurance (OBPI). The aim of the thesis is to examine, analyze and compare the portfolio insurance strategies in terms of their performances at maturity, via some of their statistical and dynamical properties, and of their optimality over the maximization of expected utility criterion. This thesis presents the financial market model in continuous-time containing no arbitrage opportunies, the CPPI and OBPI strategies with definitions and properties, and the analysis of these strategies in terms of comparing their performances at maturity, of their statistical properties and of their dynamical behaviour and sensitivities to the key parameters during the investment period as well as at the terminal date, with both formulations and simulations. Therefore, we investigate and compare optimal portfolio strategies which maximize the expected utility criterion. As a contribution on the optimality results existing in the literature, an extended study is provided by proving the existence and uniqueness of the appropriate number of shares invested in the unconstrained allocation in a wider interval.