In recent years, numerous methods to aid designers in conceptualizing new products have been developed. These methods intend to give structure to a process that was, at one time, considered to be a purely creative exercise. Resulting from the study, implementation, and refinement of design methodologies is the notion that both the structure of the development process and the structure of the developed product are key factors in creating value in a firm’s product line. With respect to the latter key factor, product architecture, but more specifically, modular product architecture has been the subject of much study. However, prior research in the area of modular product architecture has, with limited exception, focused on the construction of modules that are to be incorporated into a product before it becomes available to its end-users; that is, the modules are incorporated ‘pre-market.’ The research contained in this thesis is focused on two tasks: advancing the notion of a modular product architecture in which modules can be incorporated into a product ‘post-market,’ and creating a method that aids designers in synthesizing these post-market modules. Researchers have examined the idea of post-market modules; however, they do not fully formalize language used to describe these modules, and they also do not give the product space created by post-market modularization well-defined boundaries. Additionally, the prior work gives no method that can be used to create post-market modules. The research presented here addresses these shortcomings in the prior work by first, defining the terms ‘derivative product’ and ‘host product’ to describe the post-market module and the product that the module augments, respectively. Second, by establishing three guidelines that are used to assess the validity of potential derivative products, giving the newly termed host and derivative product space defined boundaries. And lastly, by developing a 7-step, biomimetic-based methodology that can be used to create derivative product concepts (post-market modules). This developed methodology is applied to four case studies in which it is used to create five derivative product concepts for a given host product. Thus, 20 derivative product concepts are developed in this study, demonstrating the qualitative effectiveness of the 7-step methodology.

Spatial processing that exploits the diversity provided by smart antenna arrays, in which the adaptive beamformer is employed, is another alternative to increase the efficiency of wireless system capacity and performance without allocating additional frequency spectrum. An array beamformer is a processor used in conjunction with an array of sensors to provide a versatile form of spatial filtering; it can be designed to form main lobe in direction corresponding to the desired source and nulling the interferences from others direction. They are two types of adaptive array beamformer structures, viz., broadband and narrowband array structures. To deal with the wideband desired signal or interferences the broadband array beamformer is preferred. For broadband interferences suppression, many adaptive array beamforming algorithms, based on the linearly constrained have been extensively used. In this thesis, the beamspace approach for designing the broadband antenna array beamformer, with frequency invariant character, is devised and implemented with the sliding window linearly constrained RLS (SW-LC-RLS) algorithm, to deal with the broadband moving jammers (or interferences) suppression. Also, to combat the pointing error effect of desired user¡¦s look direction, the derivative constraint is adopted for devising the derivative SW-LC-RLS beamforming algorithm for broadband moving jammers suppression. Computer simulation results confirmed that the proposed scheme is more robust against the moving jammers over the conventional algorithms. It can be applied to the existing wideband wireless communications systems to achieve desired performance for supporting high data rate communication services.

In recent years, people pay much attention to derivative pricing subject to credit risk. In this paper, we proposed an autoregressive time series model of log odds ratios to price derivatives. Examples of the proposed model are given via the structural and reduced form approaches. Pricing formulae of the proposed time series models are derived for bonds and options. Furthermore, simulation studies are performed to confirm the accuracy of derived formulae.

Derivative free optimization algorithms are implementations of trust region based derivative-free methods using multivariate polynomial interpolation. These are designed to minimize smooth functions whose derivatives are not available or costly to compute. The trust region based multilevel optimization algorithms for solving large scale unconstrained optimization problems resulting by discretization of partial differential equations (PDEs), make use of different discretization levels to reduce the computational cost. In this thesis, a derivative free multilevel optimization algorithm is derived and its convergence behavior is analyzed. The effectiveness of the algorithms is demonstrated on a shape optimization problem.

In this thesis massive higher derivative gravity theories are analyzed in some detail. One-particle scattering amplitude between two covariantly conserved sources mediated by a graviton exchange is found at tree-level in D dimensional (Anti)-de Sitter and flat spacetimes for the most general quadratic curvature theory augmented with the Pauli-Fierz mass term. From the amplitude expression, the Newtonian potential energies are calculated for various cases. Also, from this amplitude and the propagator structure, a three dimensional unitary theory is identified. In the second part of the thesis, the found three dimensional unitary theory is studied in more detail from a canonical point of view. The general higher order action is written in terms of gauge-invariant functions both in flat and de Sitter backgrounds. The analysis is extended by adding static sources, spinning masses and the gravitational Chern-Simons term separately to the theory in the case of flat spacetime. For all cases the microscopic spectrum and the masses are found. In the discussion of curved spacetime, the masses are found in the relativistic and non-relativistic limits. In the Appendix, some useful calculations that are frequently used in the bulk of the thesis are given.

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Based on the Lyapunov stability theorem, a methodology of designing an nth order adaptive integral variable structure derivative estimator (AIVSDE) is proposed in this thesis. The proposed derivative estimator not only is an improved version of the existing AIVSDE, but also can be used to estimate the nth derivative of a smooth signal which has continuous and bounded derivatives up to n+1. Analysis results show that adjusting some of the parameters can facilitate the derivative estimation of signals with higher frequency noise. The adaptive algorithm is incorporated in the estimation scheme for tracking the unknown upper bounded of the input signal as well as their's derivatives. The stability of the proposed derivative estimator is guaranteed, and the comparison between recently proposed derivative estimator of high-order sliding mode control and AIVSDE is also demonstrated.

This dissertation, studies two specific topics related to the research of surface science by employing the molecular dynamics (MD) approach, that of a water droplet deposited on a poly (methyl methacrylate) (PMMA) substrate and that of a single tricarboxylic acid derivative, 1, 3, 5-tri(carboxymethoxy) benzene (TCMB, C6H3(OCH2COOH)3 ) adsorbed on gold (100) and (110) surfaces. These can help engineers clarify the characteristics and phenomena of physical adsorption of the molecule, as well as contributing to the application of surface science. This work is divided into two parts. Effect of droplet size on the structural and dynamical behavior of a water droplet spreading on a PMMA amorphous surface: note that most experts prefer to consider a rigid model as the substrate in research of surface wetting because it is more efficient to run the MD simulation such that a long simulation can be accomplished in a short time. The results verify that the rigid model is not suitable to act as the PMMA substrate in simulation because it prevents the diffusion of PMMA molecules, which then affects the penetration behavior of water molecules in the droplet upon impact with the PMMA surface. Several sizes of water droplets are considered in order to understand the size influence of the droplet on the properties of water molecules and on the PMMA surface. The penetrated water molecules and the local roughness increase with a decrease in the size of the droplet, which also leads to a smaller contact angle of the water droplet on the PMMA substrate. When the droplet is composed of more than 1000 water molecules, the contact angle shows agreement with experimental results. As regarding the structure of the water molecule in the droplet on PMMA substrate, the average number of hydrogen-bonded penetrating water molecules is in inverse proportion to the size of the droplet By examining the velocity field, the regular motion of the water droplet is found during the equilibrium process and after the droplet reaches the equilibrium state. The diffusion of the water molecules shows a significant decrease for the penetrated water molecules and an increase as it gradually approaches the vapor/liquid interface. Finally, calculations at different regions are made for the vibration spectrum of the oxygen atom, life time, and the relaxation time of the hydrogen bond. The changes of the hydrogen-bond dynamics of the hydrogen bond are consistent with the change of the distribution of the hydrogen bond angle. Effect of surface structure on the structural and dynamical behavior of a tricarboxylic acid derivative molecule on Au surfaces: the dynamical behavior of the single tricarboxylic acid derivative, 1, 3, 5-tri(carboxymethoxy) benzene (TCMB, C6H3(OCH2COOH)3 ) on Au (100) and (110) surfaces by molecular dynamics simulation approach is studied to provide better understanding of surface diffusion. Four possible conformations of the adsorbed TCMB molecule on the Au surface are found, with differences arising from different numbers of CH2 groups adsorbed on the Au substrate. Both the number of CH2 groups in the TCMB molecule that interact with Au surface and the different geometric relationship between the TCMB molecule and the Au surface strongly affect the translational motion, rotational motion, interaction energy and the Lock-and-Key behaviors of the TCMB molecule. A poor complementarity between the TCMB molecule shape and atomic structure of the surface results in significant migration of the molecule and is therefore an unstable adsorption. These results will be useful for the design of a molecular monolayer.

This dissertation can be essentially divided into two parts. The first, consisting of Chapters I, II, and III, studies the graph theoretic nature of complex systems. This includes the spectral properties of such systems and in particular their influence on the systems dynamics. In the second part of this dissertation, or Chapter IV, we consider a new class of one-dimensional dynamical systems or functions with an eventual negative Schwarzian derivative motivated by some maps arising in neuroscience. To aid in understanding the interplay between the graph structure of a network and its dynamics we first introduce the concept of an isospectral graph reduction in Chapter I. Mathematically, an isospectral graph transformation is a graph operation (equivalently matrix operation) that modifies the structure of a graph while preserving the eigenvalues of the graphs weighted adjacency matrix. Because of their properties such reductions can be used to study graphs (networks) modulo any specific graph structure e.g. cycles of length n, cliques of size k, nodes of minimal/maximal degree, centrality, betweenness, etc. The theory of isospectral graph reductions has also lead to improvements in the general theory of eigenvalue approximation. Specifically, such reductions can be used to improved the classical eigenvalue estimates of Gershgorin, Brauer, Brualdi, and Varga for a complex valued matrix. The details of these specific results are found in Chapter II. The theory of isospectral graph transformations is then used in Chapter III to study time-delayed dynamical systems and develop the notion of a dynamical network expansion and reduction which can be used to determine whether a network of interacting dynamical systems has a unique global attractor. In Chapter IV we consider one-dimensional dynamical systems of an interval. In the study of such systems it is often assumed that the functions involved have a negative Schwarzian derivative. Here we consider a generalization of this condition. Specifically, we consider the functions which have some iterate with a negative Schwarzian derivative and show that many known results generalize to this larger class of functions. This includes both systems with regular as well as chaotic dynamic properties.

<p>Several different air pollutions are produced during combustion in a diesel engine, for example nitric oxides, NOx, which can be harmful for humans. This has led to stricter emission legislations for heavy duty trucks. The law requires both lower emissions and an On-Board Diagnosis system for all manufactured heavy duty trucks. The OBD system supervises the engine in order to keep the emissions below legislation demands. The OBD system shall detect malfunctions which may lead to increased emissions. To design the OBD system an automatic model based diagnosis approach has been developed at Scania CV AB where residual generators are generated from an engine model.</p><p>The main objective of this thesis is to improve the existing methods at Scania CV AB to extract residual generators from a model in order to generate more residual generators. The focus lies on the methods to find possible residual generators given an overdetermined subsystem. This includes methods to estimate derivatives of noisy signals.</p><p>A method to use both integral and derivative causality has been developed, called mixed causality. With this method it has been shown that more residual generators can be found when designing a model based diagnosis system, which improves the fault isolation. To use mixed causality, derivatives are estimated with smoothing spline approximation.</p>