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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
On Numerical Stochastic Optimal Control Via Bellman's Dynamic Programming Principle, Prince Osei Aboagye
On Numerical Stochastic Optimal Control Via Bellman's Dynamic Programming Principle, Prince Osei Aboagye
Open Access Theses & Dissertations
In this work, we present an application of Stochastic Control Theory to the Merton's portfolio optimization problem. Then, the dynamic programming methodology is applied to reduce the whole problem to solving the well-known HJB (Hamilton-Jacobi-Bellman) equation that arises from the Merton's portfolio optimization problem subject to the power utility function. Finally, a numerical method is proposed to solve the HJB equation and the optimal strategy. The numerical solutions are compared with the explicit solutions for optimal consumption and investment control policies.
Integrated Statistical And Machine Learning Algorithms For Predicting And Classifying G Protein-Coupled Receptors, Fredrick Ayivor
Integrated Statistical And Machine Learning Algorithms For Predicting And Classifying G Protein-Coupled Receptors, Fredrick Ayivor
Open Access Theses & Dissertations
G protein-coupled receptors (GPCRs) are transmembrane proteins with important functions in signal transduction and often serve as drug targets. With increasing availability of protein sequence information, there is much interest in computationally predicting GPCRs and classifying them according to their biological roles. Such predictions are cost-efficient and can be valuable guides for designing wet lab experiments to help elucidate signaling pathways and expedite drug discovery. There are existing computational tools of GPCR prediction that involve principal component analysis (PCA), intimate sorting (IS), support vector machine, and random forest (RF) techniques using various sequence derived features. While accuracies of over 90\% …
An Efficient Method For Online Identification Of Steady State For Multivariate System, Honglun None Xu
An Efficient Method For Online Identification Of Steady State For Multivariate System, Honglun None Xu
Open Access Theses & Dissertations
Most of the existing steady state detection approaches are designed for univariate signals. For multivariate signals, the univariate approach is often applied to each process variable and the system is claimed to be steady once all signals are steady, which is computationally inefficient and also not accurate. The article proposes an efficient online method for multivariate steady state detection. It estimates the covariance matrices using two different approaches, namely, the mean-squared-deviation and mean-squared-successive-difference. To avoid the usage of a moving window, the process means and the two covariance matrices are calculated recursively through exponentially weighted moving average. A likelihood ratio …
Mathematical Modeling Of Tumor Growth For Free-Boundary Problem By Enhanced Finite Volume Method, Mashriq Ahmed Saleh
Mathematical Modeling Of Tumor Growth For Free-Boundary Problem By Enhanced Finite Volume Method, Mashriq Ahmed Saleh
Open Access Theses & Dissertations
Modeling tumor growth due to infiltration of immune cells presents several challenges in numerical computations. First, it involves multiple cell species whose total number should be a constant, due to the incompressibility assumption; second, by mapping the Eulerian coordinate of the free-boundary problem onto a fixed logical domain, geometric source terms appear and they need to be addressed properly in numerical methods. In this work, we use a simplified model that contains two species and prescribed infiltration velocity and to show that the conventional finite volume methods fail to preserve the trivial (constant) solutions. To this end, we introduce the …
Analysis Of High Performance Scientific Programming Workflows, Withana Kankanamalage Umayanganie Klaassen
Analysis Of High Performance Scientific Programming Workflows, Withana Kankanamalage Umayanganie Klaassen
Open Access Theses & Dissertations
Substantial time is spent on building, optimizing and maintaining large-scale software that is run on supercomputers. However, little has been done to utilize overall resources efficiently when it comes to including expensive human resources. The community is beginning to acknowledge that optimizing the hardware performance such as speed and memory bottlenecks contributes less to the overall productivity than does the development lifecycle of high-performance scientific applications. Researchers are beginning to look at overall scientific workflows for high performance computing. Scientific programming productivity is measured by time and effort required to develop, configure, and maintain a simulation experiment and its constituent …
A Mixed Finite Element Method For The Coupling Of Linear Elasticity And Stokes Flow, Maranda Bean
A Mixed Finite Element Method For The Coupling Of Linear Elasticity And Stokes Flow, Maranda Bean
Open Access Theses & Dissertations
The complex interaction between fluids and structures require the coupling the laws concerning structure mechanics and fluid dynamics and are of vital importance to many scientific and engineering fields. We propose a method for modeling the coupling of a linearly elastic solid and slow fluid flow modeled by Stokes equations. The model equations are expressed in terms of displacement, velocity and stress. With these primary variables, we use a single mixed finite element space based on the Hellinger-Reissner variational principle for linear elasticity to discretize the resulting system spatially. This results in more accurate approximations for stress than those obtained …
The P-Laplacian Problem Via An Euler Equation And The Basis Properties Of Its Eigenfunctions, Luis Suarez Salas
The P-Laplacian Problem Via An Euler Equation And The Basis Properties Of Its Eigenfunctions, Luis Suarez Salas
Open Access Theses & Dissertations
The Laplacian operator is used in many fields of science, such as fluidodynamics, mechanics and elasticity. Mathematically, much research has been devoted to develop a theory with which it and other variations can be understood. In this work, we present the p-Laplacian problem via an Euler equation. We then study the properties of its eigenfunctions which generalize the trigonometric functions sine and cosine. In connection with a Fourier series, we then show the generalized trigonometric functions possess basis properties for L^r((0,1)^d), d=1,2,3. Finally, we introduce the spaces of variable exponent and the analogue p(x)-Laplacian problem which has immense applications such …