<p>This thesis describes initial language extensions to the Modelica language to define a more general language called PDEModelica, with built-in support for modeling with partial differential equations (PDEs). Modelica® is a standardized modeling language for objectoriented, equation-based modeling. It also supports component-based modeling where existing components with modified parameters can be combined into new models. The aim of the language presented in this thesis is to maintain the advantages of Modelica and also add partial differential equation support.</p><p>Partial differential equations can be defined using a coefficient-based approach, where a predefined PDE is modified by changing its coefficient values. Language operators to directly express PDEs in the language are also discussed. Furthermore, domain geometry description is handled and language extensions to describe geometries are presented. Boundary conditions, required for a complete PDE problem definition, are also handled.</p><p>A prototype implementation is described as well. The prototype includes a translator written in the relational meta-language, RML, and interfaces to external software such as mesh generators and PDE solvers, which are needed to solve PDE problems. Finally, a few examples modeled with PDEModelica and solved using the prototype are presented.</p> / Report code: LiU-Tek-Lic-2002:63.

<p>Modelica is an equation-based object-oriented language (EOO). PELAB at Linköping University along with the OpenModelica development group, is developing a metamodeling extension, MetaModelica, to this language along with a compiler called the OpenModelica Compiler (OMC).</p><p>The goal of this thesis was to analyze the compiler, extend it with union type support and then write a report about the extension with union types in particular and extension with high level data structures in general, to facilitate further development. </p><p>The implementation made by this thesis was implemented with the goal of keeping the current structure intact and extending case-clauses where possible. The main parts of the extension is implemented by this thesis work but some parts concerning the pattern matching algorithms are still to be extended. The main goal of this is to bootstrap the OpenModelica Compiler, making it able to compile itself although this is still a goal for the future.</p><p>With this thesis I also introduce some guidelines for implementing a new highlevel data structure into the compiler and which modules needs extension.</p>

Modelica is an equation-based object-oriented language (EOO). PELAB at Linköping University along with the OpenModelica development group, is developing a metamodeling extension, MetaModelica, to this language along with a compiler called the OpenModelica Compiler (OMC). The goal of this thesis was to analyze the compiler, extend it with union type support and then write a report about the extension with union types in particular and extension with high level data structures in general, to facilitate further development. The implementation made by this thesis was implemented with the goal of keeping the current structure intact and extending case-clauses where possible. The main parts of the extension is implemented by this thesis work but some parts concerning the pattern matching algorithms are still to be extended. The main goal of this is to bootstrap the OpenModelica Compiler, making it able to compile itself although this is still a goal for the future. With this thesis I also introduce some guidelines for implementing a new highlevel data structure into the compiler and which modules needs extension.

Background: With the burgeoning volumes of data, efficient data transformation techniques are crucial. RDF mapping language has been recognized as a conventional method, whileIKEA the Knowledge graph’s approach brings a new perspective with tailored functions and schema definitions. Objectives: This study aims to compare the efficiency and effectiveness of the RDF mapping language (RML) and IKEA Knowledge graph(IKG) approaches in transforming JSON data into RDF format. It explores their performance across different complexity levels to provide insights into their strengths and limitations. Methods: We began our research by studying how professionals in the industry currently transform JSON data into Resource description framework(RDF) formats through a literature review. After gaining this understanding, we conducted practical experiments to compare the RDF mapping language (RML) and IKEA Knowledge graph(IKG)approaches at various complexity levels. We assessed user-friendliness, adaptability, execution time, and overall performance. This combined approach aimed to connect theoretical knowledge with experimental data transformation practices. Results: The results demonstrate the superiority of the IKEA Knowledge graph approach(IKG), particularly in intricate scenarios involving conditional mapping and external graph data lookup. It showcases the IKEA Knowledge Graph (IKG) method’s versatility and efficiency in managing diverse data transformation tasks. Conclusions: Through practical experimentation and thorough analysis, this study concludes that the IKEA Knowledge graph approach demonstrates superior performance in handling complex data transformations compared to the RDF mapping language (RML) approach. This research provides valuable insights for choosing an optimal data trans-formation approach based on the specific task complexities and requirements

This thesis describes initial language extensions to the Modelica language to define a more general language called PDEModelica, with built-in support for modeling with partial differential equations (PDEs). Modelica® is a standardized modeling language for objectoriented, equation-based modeling. It also supports component-based modeling where existing components with modified parameters can be combined into new models. The aim of the language presented in this thesis is to maintain the advantages of Modelica and also add partial differential equation support. Partial differential equations can be defined using a coefficient-based approach, where a predefined PDE is modified by changing its coefficient values. Language operators to directly express PDEs in the language are also discussed. Furthermore, domain geometry description is handled and language extensions to describe geometries are presented. Boundary conditions, required for a complete PDE problem definition, are also handled. A prototype implementation is described as well. The prototype includes a translator written in the relational meta-language, RML, and interfaces to external software such as mesh generators and PDE solvers, which are needed to solve PDE problems. Finally, a few examples modeled with PDEModelica and solved using the prototype are presented. / <p>Report code: LiU-Tek-Lic-2002:63.</p>

Thesis (M.App.Sc.) - Carleton University, / Includes bibliographical references (p. 82-88). Also available in electronic format on the Internet.

Subprime residential mortgage loan securitization and its associated risks have been a major topic of discussion since the onset of the subprime mortgage crisis (SMC) in 2007. In this regard, the thesis addresses the issues of subprime residential mortgage loan (RML) securitization in discrete-, continuous-and discontinuous-time and their connections with the SMC. In this regard, the main issues to be addressed are discussed in Chapters 2, 3 and 4. In Chapter 2, we investigate the risk allocation choices of an investing bank (IB) that has to decide between risky securitized subprime RMLs and riskless Treasuries. This issue is discussed in a discrete-time framework with IB being considered to be regret- and risk-averse before and during the SMC, respectively. We conclude that if IB takes regret into account it will be exposed to higher risk when the difference between the expected returns on securitized subprime RMLs and Treasuries is small. However, there is low risk exposure when this difference is high. Furthermore, we assess how regret can influence IB's view - as a swap protection buyer - of the rate of return on credit default swaps (CDSs), as measured by the premium based on default swap spreads. We find that before the SMC, regret increases IB's willingness to pay lower premiums for CDSs when its securitized RML portfolio is considered to be safe. On the other hand, both risk- and regret-averse IBs pay the same CDS premium when their securitized RML portfolio is considered to be risky. Chapter 3 solves a stochastic optimal credit default insurance problem in continuous-time that has the cash outflow rate for satisfying depositor obligations, the investment in securitized loans and credit default insurance as controls. As far as the latter is concerned, we compute the credit default swap premium and accrued premium by considering the credit rating of the securitized mortgage loans. In Chapter 4, we consider a problem of IB investment in subprime residential mortgage-backed securities (RMBSs) and Treasuries in discontinuous-time. In order to accomplish this, we develop a Levy process-based model of jump diffusion-type for IB's investment in subprime RMBSs and Treasuries. This model incorporates subprime RMBS losses which can be associated with credit risk. Furthermore, we use variance to measure such risk, and assume that the risk is bounded by a certain constraint. We are now able to set-up a mean-variance optimization problem for IB's investment which determines the optimal proportion of funds that needs to be invested in subprime RMBSs and Treasuries subject to credit risk measured by the variance of IE's investment. In the sequel, we also consider a mean swaps-at-risk (SaR) optimization problem for IB's investment which determines the optimal portfolio which consists of subprime RMBSs and Treasuries subject to the protection by CDSs required against the possible losses. In this regard, we define SaR as indicative to IB on how much protection from swap protection seller it must have in order to cover the losses that might occur from credit events. Moreover, SaR is expressed in terms of Value-at-Risk (VaR). Finally, Chapter 5 provides an analysis of discrete-, continuous- and discontinuous-time models for subprime RML securitization discussed in the aforementioned chapters and their connections with the SMC. The work presented in this thesis is based on 7 peer-reviewed international journal articles (see [25], [44], [45], [46], [47], [48] and [55]), 4 peer-reviewed chapters in books (see [42], [50j, [51J and [52]) and 2 peer-reviewed conference proceedings papers (see [11] and [12]). Moreover, the article [49] is currently being prepared for submission to an lSI accredited journal. / Thesis (Ph.D. (Applied Mathematics))--North-West University, Potchefstroom Campus, 2010.

The subprime mortgage crisis (SMC) is an ongoing housing and nancial crisis that was triggered by a marked increase in mortgage delinquencies and foreclosures in the U.S. It has had major adverse consequences for banks and nancial markets around the globe since it became apparent in 2007. In our research, we examine an originator's (OR's) nonlinear stochastic optimal control problem related to choices regarding deposit inflow rates and marketable securities allocation. Here, the primary aim is to minimize liquidity risk, more speci cally, funding and credit crunch risk. In this regard, we consider two reference processes, namely, the deposit reference process and the residential mortgage loan (RML) reference process. This enables us to specify optimal deposit inflows as well as optimal marketable securities allocation by using actuarial cost methods to establish an ideal level of subprime RML extension. In our research, relationships are established in order to construct a stochastic continuous-time banking model to determine a solution for this optimal control problem which is driven by geometric Brownian motion. In this regard, the main issues to be addressed in this dissertation are discussed in Chapters 2 and 3. In Chapter 2, we investigate uncertain banking behavior. In this regard, we consider continuous-time stochastic models for OR's assets, liabilities, capital, balance sheet as well as its reference processes and give a description of their dynamics for each stochastic model as well as the dynamics of OR's stylized balance sheet. In this chapter, we consider RML and deposit reference processes which will serve as leading indicators in order to establish a desirable level of subprime RMLs to be extended at the end of the risk horizon. Chapter 3 states the main results that pertain to the role of stochastic optimal control in OR's risk management in Theorem 2.5.1 and Corollary 2.5.2. Prior to the stochastic control problem, we discuss an OR's risk factors, the stochastic dynamics of marketable securities as well as the RML nancing spread method regarding an OR. Optimal portfolio choices are made regarding deposit and marketable securities inflow rates given by Theorem 3.4.1 in order to obtain the ideal RML extension level. We construct the stochastic continuoustime model to determine a solution for this optimal control problem to obtain the optimal marketable securities allocation and deposit inflow rate to ensure OR's stability and security. According to this, a spread method of RML financing is imposed with an existence condition given by Lemma 3.3.2. A numerical example is given in Section 3.5 to illustrates the main issues raised in our research. / Thesis (M.Sc. (Applied Mathematics))--North-West University, Potchefstroom Campus, 2011.

The subprime mortgage crisis (SMC) is an ongoing housing and nancial crisis that was triggered by a marked increase in mortgage delinquencies and foreclosures in the U.S. It has had major adverse consequences for banks and nancial markets around the globe since it became apparent in 2007. In our research, we examine an originator's (OR's) nonlinear stochastic optimal control problem related to choices regarding deposit inflow rates and marketable securities allocation. Here, the primary aim is to minimize liquidity risk, more speci cally, funding and credit crunch risk. In this regard, we consider two reference processes, namely, the deposit reference process and the residential mortgage loan (RML) reference process. This enables us to specify optimal deposit inflows as well as optimal marketable securities allocation by using actuarial cost methods to establish an ideal level of subprime RML extension. In our research, relationships are established in order to construct a stochastic continuous-time banking model to determine a solution for this optimal control problem which is driven by geometric Brownian motion. In this regard, the main issues to be addressed in this dissertation are discussed in Chapters 2 and 3. In Chapter 2, we investigate uncertain banking behavior. In this regard, we consider continuous-time stochastic models for OR's assets, liabilities, capital, balance sheet as well as its reference processes and give a description of their dynamics for each stochastic model as well as the dynamics of OR's stylized balance sheet. In this chapter, we consider RML and deposit reference processes which will serve as leading indicators in order to establish a desirable level of subprime RMLs to be extended at the end of the risk horizon. Chapter 3 states the main results that pertain to the role of stochastic optimal control in OR's risk management in Theorem 2.5.1 and Corollary 2.5.2. Prior to the stochastic control problem, we discuss an OR's risk factors, the stochastic dynamics of marketable securities as well as the RML nancing spread method regarding an OR. Optimal portfolio choices are made regarding deposit and marketable securities inflow rates given by Theorem 3.4.1 in order to obtain the ideal RML extension level. We construct the stochastic continuoustime model to determine a solution for this optimal control problem to obtain the optimal marketable securities allocation and deposit inflow rate to ensure OR's stability and security. According to this, a spread method of RML financing is imposed with an existence condition given by Lemma 3.3.2. A numerical example is given in Section 3.5 to illustrates the main issues raised in our research. / Thesis (M.Sc. (Applied Mathematics))--North-West University, Potchefstroom Campus, 2011.

Subprime residential mortgage loan securitization and its associated risks have been a major topic of discussion since the onset of the subprime mortgage crisis (SMC) in 2007. In this regard, the thesis addresses the issues of subprime residential mortgage loan (RML) securitization in discrete-, continuous-and discontinuous-time and their connections with the SMC. In this regard, the main issues to be addressed are discussed in Chapters 2, 3 and 4. In Chapter 2, we investigate the risk allocation choices of an investing bank (IB) that has to decide between risky securitized subprime RMLs and riskless Treasuries. This issue is discussed in a discrete-time framework with IB being considered to be regret- and risk-averse before and during the SMC, respectively. We conclude that if IB takes regret into account it will be exposed to higher risk when the difference between the expected returns on securitized subprime RMLs and Treasuries is small. However, there is low risk exposure when this difference is high. Furthermore, we assess how regret can influence IB's view - as a swap protection buyer - of the rate of return on credit default swaps (CDSs), as measured by the premium based on default swap spreads. We find that before the SMC, regret increases IB's willingness to pay lower premiums for CDSs when its securitized RML portfolio is considered to be safe. On the other hand, both risk- and regret-averse IBs pay the same CDS premium when their securitized RML portfolio is considered to be risky. Chapter 3 solves a stochastic optimal credit default insurance problem in continuous-time that has the cash outflow rate for satisfying depositor obligations, the investment in securitized loans and credit default insurance as controls. As far as the latter is concerned, we compute the credit default swap premium and accrued premium by considering the credit rating of the securitized mortgage loans. In Chapter 4, we consider a problem of IB investment in subprime residential mortgage-backed securities (RMBSs) and Treasuries in discontinuous-time. In order to accomplish this, we develop a Levy process-based model of jump diffusion-type for IB's investment in subprime RMBSs and Treasuries. This model incorporates subprime RMBS losses which can be associated with credit risk. Furthermore, we use variance to measure such risk, and assume that the risk is bounded by a certain constraint. We are now able to set-up a mean-variance optimization problem for IB's investment which determines the optimal proportion of funds that needs to be invested in subprime RMBSs and Treasuries subject to credit risk measured by the variance of IE's investment. In the sequel, we also consider a mean swaps-at-risk (SaR) optimization problem for IB's investment which determines the optimal portfolio which consists of subprime RMBSs and Treasuries subject to the protection by CDSs required against the possible losses. In this regard, we define SaR as indicative to IB on how much protection from swap protection seller it must have in order to cover the losses that might occur from credit events. Moreover, SaR is expressed in terms of Value-at-Risk (VaR). Finally, Chapter 5 provides an analysis of discrete-, continuous- and discontinuous-time models for subprime RML securitization discussed in the aforementioned chapters and their connections with the SMC. The work presented in this thesis is based on 7 peer-reviewed international journal articles (see [25], [44], [45], [46], [47], [48] and [55]), 4 peer-reviewed chapters in books (see [42], [50j, [51J and [52]) and 2 peer-reviewed conference proceedings papers (see [11] and [12]). Moreover, the article [49] is currently being prepared for submission to an lSI accredited journal. / Thesis (Ph.D. (Applied Mathematics))--North-West University, Potchefstroom Campus, 2010.