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Finite difference numerical methods are developed for the solution system in the biomedical sciences; namely, fox-rabies model. First-order methods and second-order method are developed to solve the fox-rabies equations. The fox-rabies model is extended to one-space dimension to incorporate diffusion. The reaction terms in these systems of partial differential equations contain non-linear expressions. It is seen that the numerical solutions are obtained by solving non-linear algebraic system at each time step, as opposed to solving anon-linear algebraic system which is often required when integrating non-linear partial differential equations. The numerical methods proposed for the solution of the initial-value problem for the fox-rabies model are characterized to be implicit. In each case, however, it seen that the numerical solutions are obtained explicitly. In a series of numerical experiments, in which the ordinary differential equations are solved first of all, it seen that the proposed methods have an identical stability properties to those of the well-known, first-order, Euler method. The proposed methods for the numerical solution of partial differential equations are seen to be economical and reliable. Error analysis for the methods, computer implementation and numerical results are discussed. The stability of the numerical method is analyzed using maximum principle analysis.

In the effort to simulate the biologically inspired continuum robot’s dynamic capabilities, researchers have been faced with the daunting task of simulating—in real-time—the complete three dimensional dynamics of the the “beam-like” structure which includes the three “stiff” degrees-ofreedom transverse and dilational shear. Therefore, researchers have traditionally limited the difficulty of the problem with simplifying assumptions. This study, however, puts forward a solution which makes no simplifying assumptions and trades off only the real-time requirement of the desired solution. The solution is a Finite Difference Time Domain method employing an explicit single step method with cheap right hands sides. The cheap right hand sides are the result of a rather ingenious formulation of the classical beam called the Cosserat rod by, first, the Cosserat brothers and, later, Stuart S. Antman which results in five nonlinear but uncoupled equations that require only multiplication and addition. The method is therefore suitable for hardware implementation thus moving the real-time requirement from a software solution to a hardware solution.

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This thesis is concerned with changes in the behaviour of solutions to parameter-dependent stochastic delay differential equations.

Self-Organizing Maps (SOM) can provide a visualization for multi-dimensional data with two dimensional mappings. By applying unsupervised learning techniques to SOM representations, we can further enhance visual inspection for change detection. In order to obtain a more accurate measurement for the changes of self-organizing maps beyond simple visual inspection, we introduce the Gaussian Mixture Model (GMM) and Kullback-Leibler Divergence (KLD) on top of SOM trained maps. The main contribution in this dissertation focuses on adding numerical methods to SOM algorithms, with anomaly detection as example domain. Through extensive traced-based simulations, it is observed that our techniques can uncover anomalies with an accuracy of 100% at an anomaly mixture-rate as low as 12% from the CTU-13 dataset. Tuning of the KLD threshold further reduces the mixture-rate to 7%, significantly augmenting visual inspection to assist in detecting low-rate anomalies. Suitable hierarchical and distributed SOM-based approaches are also explored, along with other approaches in the literature. Hierarchies in SOM can show the correlations among the neural cells on the self-organizing maps. In order to obtain a higher accuracy for anomaly detection, a new dimension of labels is suggested to be added in the second layer of SOM training. Also for more general distributed SOM-based algorithms, we investigate the use of principal component analysis (PCA) for the separation of dimensions. With the transformed dataset from PCA, the inner dependencies can be reserved in a manageable scale. As a case study, this dissertation uses a SOM-based approach for anomaly detection in Supervisory Control And Data Acquisition (SCADA) networks. We further investigate the use of SOM for the Quality of Service (QoS) in the scenario of wireless SCADA networks. Solving the problem of long computing time of optimizing the cached contents, the new SOM-based approach can also learn and predict the sub-optimal locations for the caching while maintaining a prediction error of 28%. / Graduate

In this dissertation, we study the behavior of microscopic organisms utilizing lateral and spiral bending waves to swim in a fluid. More specifically, spermatozoa encounter different fluid environments filled with mucus, cells, hormones, and other large proteins. These networks of proteins and cells are assumed to be stationary and of low volume fraction. They act as friction, possibly preventing or enhancing forward progression of the swimmers. The flow in the medium is described as a viscous fluid with a resistance term known as a Brinkman fluid. It depends on the Darcy permeability parameter affecting the swimming patterns of the flagella. To further understand these effects we study the asymptotic swimming speeds of an infinite-length swimmer propagating planar or spiral bending waves in a Brinkman fluid. We find that, up to the second order expansion, the swimming speeds are enhanced as the resistance increases. The work to maintain the planar bending and the torque exerted on the fluid are also examined. The Stokes limits of the swimming speeds, the work and the torque are recovered as resistance goes to zero. The analytical solutions are compared with numerical results of finite-length swimmers obtained from the method of Regularized Brinkmanlets (MRB). The study gives insight on the effects of the permeability, the length and the radius of the cylinder on the performance of the swimmers. In addition, we develop a grid-free numerical method to study the bend and twist of an elastic rod immersed in a Brinkman fluid. The rod is discretized using a Kirchhoff Rod (KR) model. The linear and angular velocity of the rod are derived using the MRB. The method is validated through a couple of benchmark examples including the dynamics of an elastic rod, and the planar bending of a flagellum in a Brinkman fluid. The studies show how the permeability and stiffness coefficients affect the waveforms, the energy, and the swimming speeds of the swimmers. Also, the beating pattern of the spermatozoa flagellum depends on the intracellular concentrations of calcium ([Ca2+]). An increase of [Ca2+] is linked to hyperactivated motility. This is characterized by highly asymmetrical beating, which allows spermatozoa to reach the oocyte (egg) or navigate along the female reproductive tract. Here, we couple the [Ca2+] to the bending model of a swimmer in a Brinkman fluid. This computational framework is used to understand how internal flagellar [Ca2+] and fluid resistance in a Brinkman fluid alter swimming trajectories and flagellar bending.

This paper introduces a method to determine the pressure in a fixed thickness, smooth, periodic domain; namely a lead-over-pleat cartridge filter. Finding the pressure within the domain requires the numerical solution of Laplace's equation, the first step of which is approximating, by interpolation, the curved portions of the filter to a circle in the xy plane.A conformal map is then applied to the filter, transforming the region into a rectangle in the uv plane. A finite difference method is introduced to numerically solve Laplace's equation in the rectangular domain. There are currently methods in existence to solve partial differential equations on non- regular domains. In a method employed by Monchmeyer and Muller, a scheme is used to transform from cartesian to spherical polar coordinates. Monchmeyer and Muller stress that for non-linear domains, extrapolation of existing cartesian difference schemes may produce incorrect solutions, and therefore, a volume centered discretization is used. A difference scheme is then derived that relies on mean values. This method has second order accuracy.(Rosenfeld,Moshe, Kwak, Dochan, 1989) The method introduced in this paper is based on a 7-point stencil which takes into account the unequal spacing of the points. From all neighboring pairs, a linear system of equations is constructed, which takes into account the periodic domain.This method is solved by standard iterative methods. The solution is then mapped back to the original domain, with second order accuracy. The method is then tested to obtain a solution to a domain which satisfies $y=sin(x)$ at the center, a shape similar to that of a lead-over-pleat cartridge filter. As a result, a model for the pressure distribution within the filter is obtained.

The Digital Orrery has been used to perform an integration of the motion of the outer planets for 845 million years. This integration indicates that the long-term motion of the planet Pluto is chaotic. Nearby trajectories diverge exponentially with an e-folding time of only about 20 million years.

Heart disease, cancer, diabetes and other complex diseases account for more than half of human mortality in the United States. Other diseases such as AIDS, asthma, Parkinson’s disease, Alzheimer’s disease and cerebrovascular ailments such as stroke not only augment this mortality but also severely deteriorate the quality of human life experience. In spite of enormous financial support and global scientific effort over an extended period of time to combat the challenges posed by these ailments, we find ourselves short of sighting a cure or vaccine. It is widely believed that a major reason for this failure is the traditional reductionist approach adopted by the scientific community in the past. In recent times, however, the systems biology based research paradigm has gained significant favor in the research community especially in the field of complex diseases. One of the critical components of such a paradigm is computational systems biology which is largely driven by mathematical modeling and simulation of biochemical systems. The most common methods for simulating a biochemical system are either: a) continuous deterministic methods or b) discrete event stochastic methods. Although highly popular, none of them are suitable for simulating multi-scale models of biological systems that are ubiquitous in systems biology based research. In this work a novel method for simulating biochemical systems based on a deterministic solution is presented with a modification that also permits the incorporation of stochastic effects. This new method, through extensive validation, has been proven to possess the efficiency of a deterministic framework combined with the accuracy of a stochastic method. The new crossover method can not only handle the concentration and spatial gradients of multi-scale modeling but it does so in a computationally efficient manner. The development of such a method will undoubtedly aid the systems biology researchers by providing them with a tool to simulate multi-scale models of complex diseases.