The University of Southern Mississippi
California Polytechnic State University - San Luis Obispo
Rose-Hulman Institute of Technology
Marshall University
University of Pennsylvania
University of Nebraska-Lincoln
The Graduate Center, City University of New York
College of William and Mary
Iowa State University
Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland,
2018
Wojciech Budzianowski Consulting Services
Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski
Wojciech Budzianowski
No abstract provided.
Semi-Tensor Product Representations Of Boolean Networks,
2018
Illinois State University
Semi-Tensor Product Representations Of Boolean Networks, Matthew Macauley
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Introducing The Fractional Differentiation For Clinical Data-Justified Prostate Cancer Modelling Under Iad Therapy,
2018
Illinois State University
Introducing The Fractional Differentiation For Clinical Data-Justified Prostate Cancer Modelling Under Iad Therapy, Ozlem Ozturk Mizrak
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Ideals, Big Varieties, And Dynamic Networks,
2018
Portland State University
Ideals, Big Varieties, And Dynamic Networks, Ian H. Dinwoodie
Mathematics and Statistics Faculty Publications and Presentations
The advantage of using algebraic geometry over enumeration for describing sets related to attractors in large dynamic networks from biology is advocated. Examples illustrate the gains.
Physical Applications Of The Geometric Minimum Action Method,
2018
The Graduate Center, City University of New York
Physical Applications Of The Geometric Minimum Action Method, George L. Poppe Jr.
All Dissertations, Theses, and Capstone Projects
This thesis extends the landscape of rare events problems solved on stochastic systems by means of the \textit{geometric minimum action method} (gMAM). These include partial differential equations (PDEs) such as the real Ginzburg-Landau equation (RGLE), the linear Schroedinger equation, along with various forms of the nonlinear Schroedinger equation (NLSE) including an application towards an ultra-short pulse mode-locked laser system (MLL).
Additionally we develop analytical tools that can be used alongside numerics to validate those solutions. This includes the use of instanton methods in deriving state transitions for the linear Schroedinger equation and the cubic diffusive NLSE.
These analytical solutions ...
Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso).,
2018
University of Louisville
Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch
Electronic Theses and Dissertations
The performance and stability of the Particle Swarm Optimization algorithm depends on parameters that are typically tuned manually or adapted based on knowledge from empirical parameter studies. Such parameter selection is ineffectual when faced with a broad range of problem types, which often hinders the adoption of PSO to real world problems. This dissertation develops a dynamic self-optimization approach for the respective parameters (inertia weight, social and cognition). The effects of self-adaption for the optimal balance between superior performance (convergence) and the robustness (divergence) of the algorithm with regard to both simple and complex benchmark functions is investigated. This work ...
Iterative Methods To Solve Systems Of Nonlinear Algebraic Equations,
2018
Western Kentucky University
Iterative Methods To Solve Systems Of Nonlinear Algebraic Equations, Md Shafiful Alam
Masters Theses & Specialist Projects
Iterative methods have been a very important area of study in numerical analysis since the inception of computational science. Their use ranges from solving algebraic equations to systems of differential equations and many more. In this thesis, we discuss several iterative methods, however our main focus is Newton's method. We present a detailed study of Newton's method, its order of convergence and the asymptotic error constant when solving problems of various types as well as analyze several pitfalls, which can affect convergence. We also pose some necessary and sufficient conditions on the function f for higher order of ...
P-46 A Periodic Matrix Model Of Seabird Behavior And Population Dynamics,
2018
Andrews University
P-46 A Periodic Matrix Model Of Seabird Behavior And Population Dynamics, Mykhaylo M. Malakhov, Benjamin Macdonald, Shandelle M. Henson, J. M. Cushing
Honors Scholars & Undergraduate Research Poster Symposium Programs
Rising sea surface temperatures (SSTs) in the Pacific Northwest lead to food resource reductions for surface-feeding seabirds, and have been correlated with several marked behavioral changes. Namely, higher SSTs are associated with increased egg cannibalism and egg-laying synchrony in the colony. We study the long-term effects of climate change on population dynamics and survival by considering a simplified, cross-season model that incorporates both of these behaviors in addition to density-dependent and environmental effects. We show that cannibalism can lead to backward bifurcations and strong Allee effects, allowing the population to survive at lower resource levels than would be possible otherwise.
Learning And Control Using Gaussian Processes,
2018
University of Pennsylvania
Learning And Control Using Gaussian Processes, Achin Jain, Truong X Nghiem, Manfred Morari, Rahul Mangharam
Real-Time and Embedded Systems Lab (mLAB)
Building physics-based models of complex physical systems like buildings and chemical plants is extremely cost and time prohibitive for applications such as real-time optimal control, production planning and supply chain logistics. Machine learning algorithms can reduce this cost and time complexity, and are, consequently, more scalable for large-scale physical systems. However, there are many practical challenges that must be addressed before employing machine learning for closed-loop control. This paper proposes the use of Gaussian Processes (GP) for learning control-oriented models: (1) We develop methods for the optimal experiment design (OED) of functional tests to learn models of a physical system ...
Extensions Of The Morse-Hedlund Theorem,
2018
Bucknell University
Extensions Of The Morse-Hedlund Theorem, Eben Blaisdell
Honors Theses
Bi-infinite words are sequences of characters that are infinite forwards and backwards; for example "...ababababab...". The Morse-Hedlund theorem says that a bi-infinite word f repeats itself, in at most n letters, if and only if the number of distinct subwords of length n is at most n. Using the example, "...ababababab...", there are 2 subwords of length 3, namely "aba" and "bab". Since 2 is less than 3, we must have that "...ababababab..." repeats itself after at most 3 letters. In fact it does repeat itself every two letters. Interestingly, there are many extensions of this theorem to multiple dimensions ...
Homeomorphisms Of The Sierpinski Carpet,
2018
Bard College
Homeomorphisms Of The Sierpinski Carpet, Karuna S. Sangam
Senior Projects Spring 2018
The Sierpinski carpet is a fractal formed by dividing the unit square into nine congruent squares, removing the center one, and repeating the process for each of the eight remaining squares, continuing infinitely many times. It is a well-known fractal with many fascinating topological properties that appears in a variety of different contexts, including as rational Julia sets. In this project, we study self-homeomorphisms of the Sierpinski carpet. We investigate the structure of the homeomorphism group, identify its finite subgroups, and attempt to define a transducer homeomorphism of the carpet. In particular, we find that the symmetry groups of platonic ...
Distributed Evolution Of Spiking Neuron Models On Apache Mahout For Time Series Analysis,
2017
Cylance, Inc.
Distributed Evolution Of Spiking Neuron Models On Apache Mahout For Time Series Analysis, Andrew Palumbo
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
An Improved Pairwise- Approximation Technique For Studying The Dynamics Of A Probabilistic, Two- State Lattice Model Of Intracellular Cardiac Calcium,
2017
Loyola Marymount University
An Improved Pairwise- Approximation Technique For Studying The Dynamics Of A Probabilistic, Two- State Lattice Model Of Intracellular Cardiac Calcium, Robert J. Rovetti
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Mathematical Modeling Of Inhibitory Effects On Chemically Coupled Neurons,
2017
Illinois State University
Mathematical Modeling Of Inhibitory Effects On Chemically Coupled Neurons, Nathhaniel Harraman, Epaminondas Rosa
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Temperature Effects On Neuronal Tonic-To-Bursting Transitions,
2017
Illinois State University
Temperature Effects On Neuronal Tonic-To-Bursting Transitions, Manuela Burek, Epaminondas Rosa
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
A Brief History Of Neuroscience,
2017
Illinois State University
A Brief History Of Neuroscience, Zachary Mobille, Epaminondas Rosa
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Asymptotic Counting Formulas For Markoff-Hurwitz Tuples,
2017
The Graduate Center, City University of New York
Asymptotic Counting Formulas For Markoff-Hurwitz Tuples, Ryan Ronan
All Dissertations, Theses, and Capstone Projects
The Markoff equation is a Diophantine equation in 3 variables first studied in Markoff's celebrated work on indefinite binary quadratic forms. We study the growth of solutions to an n variable generalization of the Markoff equation, which we refer to as the Markoff-Hurwitz equation. We prove explicit asymptotic formulas counting solutions to this generalized equation with and without a congruence restriction. After normalizing and linearizing the equation, we show that all but finitely many solutions appear in the orbit of a certain semigroup of maps acting on finitely many root solutions. We then pass to an accelerated subsemigroup of ...
Morphogenesis And Growth Driven By Selection Of Dynamical Properties,
2017
The Graduate Center, City University of New York
Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor
All Dissertations, Theses, and Capstone Projects
Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms.
Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world ...
A Real Options Approach To Criminal Careers,
2017
FURG and PPGOM/UFPel
A Real Options Approach To Criminal Careers, Cristiano Aguiar De Oliveira, Giácomo Balbinotto Neto
The Latin American and Iberian Journal of Law and Economics
This paper proposes a dynamic model based on real options to evaluate the criminal career. In the model, individuals can choose the best moment to engage in crime (illegal activity). The model proposed allows the evaluation of the impact of different risk preferences, punishment probability, punishment severity and, mainly time discount in the individual’s decision. Through model calibration it is possible to observe that the option for a criminal career depends on a high return in the illegal activity even when individuals are risk neutral and when they have a low time discount. The paper also discusses youth participation ...
Modeling Economic Systems As Locally-Constructive Sequential Games,
2017
Iowa State University
Modeling Economic Systems As Locally-Constructive Sequential Games, Leigh Tesfatsion
Economics Working Papers
Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these properties imply real-world economies are locally-constructive sequential games. This study discusses a modeling approach, agent-based computational economics (ACE), that permits researchers to study economic systems from this point of view. ACE modeling principles and ...
