On Implementing And Testing The Rsa Algorithm, 2022 The College of Wooster
On Implementing And Testing The Rsa Algorithm, Kien Trung Le
Senior Independent Study Theses
In this work, we give a comprehensive introduction to the RSA cryptosystem, implement it in Java, and compare it empirically to three other RSA implementations. We start by giving an overview of the field of cryptography, from its primitives to the composite constructs used in the field. Then, the paper presents a basic version of the RSA algorithm. With this information in mind, we discuss several problems with this basic conception of RSA, including its speed and some potential attacks that have been attempted. Then, we discuss possible improvements that can make RSA runs faster and more secure. On the …
A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization, 2022 Old Dominion University
A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization, Hesamoddin Tahami, Hengameh Fakhravar
Engineering Management & Systems Engineering Faculty Publications
There are several approaches for solving hard optimization problems. Mathematical programming techniques such as (integer) linear programming-based methods and metaheuristic approaches are two extremely effective streams for combinatorial problems. Different research streams, more or less in isolation from one another, created these two. Only several years ago, many scholars noticed the advantages and enormous potential of building hybrids of combining mathematical programming methodologies and metaheuristics. In reality, many problems can be solved much better by exploiting synergies between these approaches than by “pure” classical algorithms. The key question is how to integrate mathematical programming methods and metaheuristics to achieve such …
Guide To The Dr. L.S. Dederick Papers, 1908-1956, Undated, 2022 Bridgewater State University
Guide To The Dr. L.S. Dederick Papers, 1908-1956, Undated, Orson Kingsley, Patrick Koetsch
Archives & Special Collections Finding Aids
Louis Serle (L.S.) Dederick was born in Chicago in 1883. He received his Ph.D. in Mathematics from Harvard University in 1909. From 1909 – 1917 he was a professor at Princeton University. From 1917 – 1924 he was professor at the U.S. Naval Academy in Annapolis, Maryland. In 1926 Dederick began working for the U.S. Army, Ordnance. During his time there he was the Associate Director of the Ballistic Research Laboratory at the Aberdeen Proving Grounds in Aberdeen, Maryland where he focused on ballistics research.
While Dederick worked as a mathematician at the Aberdeen Proving Grounds, he was involved with …
Empirical Comparison Of Machine Learning Methods For Wind Power Predictions, 2022 Eastern Washington University
Empirical Comparison Of Machine Learning Methods For Wind Power Predictions, Sidny M. Stewart
EWU Masters Thesis Collection
No abstract provided.
An Effective Model For The Iris Regional Characteristics Andclassification Using Deep Learning Alex Network, 2022 Molloy University
An Effective Model For The Iris Regional Characteristics Andclassification Using Deep Learning Alex Network, Thiyaneswaran Balashanmugam, Kumarganesh Sengottaiyan, Martin Sagayam Kulandairaj, Helen Dang
Faculty Works: MCS (1984-2023)
Iris biometrics is one of the fastest-growing technologies, and it has received a lot ofattention from the community. Iris-biometric-based human recognition does not requirecontact with the human body. Iris is a combination of crypts, wolflin nodules, concen-trated furrows, and pigment spots. The existing methods feed the eye image into deeplearning network which result in improper iris features and certainly reduce the accuracy.This research study proposes a model to feed preprocessed accurate iris boundary intoAlexnet deep learning neural network-based system for classification. The pupil centre andboundary are initially recorded and identified from the given eye images. The iris boundaryand the centre …
Analyzing Marriage Statistics As Recorded In The Journal Of The American Statistical Association From 1889 To 2012, 2022 Claremont Colleges
Analyzing Marriage Statistics As Recorded In The Journal Of The American Statistical Association From 1889 To 2012, Annalee Soohoo
CMC Senior Theses
The United States has been tracking American marriage statistics since its founding. According to the United States Census Bureau, “marital status and marital history data help federal agencies understand marriage trends, forecast future needs of programs that have spousal benefits, and measure the effects of policies and programs that focus on the well-being of families, including tax policies and financial assistance programs.”[1] With such a wide scope of applications, it is understandable why marriage statistics are so highly studied and well-documented.
This thesis will analyze American marriage patterns over the past 100 years as documented in the Journal of …
Smoothed Bounded-Confidence Opinion Dynamics On The Complete Graph, 2022 Claremont Colleges
Smoothed Bounded-Confidence Opinion Dynamics On The Complete Graph, Solomon Valore-Caplan
HMC Senior Theses
We present and analyze a model for how opinions might spread throughout a network of people sharing information. Our model is called the smoothed bounded-confidence model and is inspired by the bounded-confidence model of opinion dynamics proposed by Hegselmann and Krause. In the Hegselmann–Krause model, agents move towards the average opinion of their neighbors. However, an agent only factors a neighbor into the average if their opinions are sufficiently similar. In our model, we replace this binary threshold with a logarithmic weighting function that rewards neighbors with similar opinions and minimizes the effect of dissimilar ones. This weighting function can …
An Adaptive Hegselmann–Krause Model Of Opinion Dynamics, 2022 Claremont Colleges
An Adaptive Hegselmann–Krause Model Of Opinion Dynamics, Phousawanh Peaungvongpakdy
HMC Senior Theses
Models of opinion dynamics have been used to understand how the spread
of information in a population evolves, such as the classical Hegselmann–
Krause model (Hegselmann and Krause, 2002). One extension of the model
has been used to study the impact of media ideology on social media
networks (Brooks and Porter, 2020). In this thesis, we explore various
models of opinions and propose our own model, which is an adaptive
version of the Hegselmann–Krause model. The adaptive version implements
the social phenomenon of homophily—the tendency for like-minded agents to
associate together. This is done by having agents dissolve connections …
Check Yourself Before You Wrek Yourself: Unpacking And Generalizing Randomized Extended Kaczmarz, 2022 Claremont Colleges
Check Yourself Before You Wrek Yourself: Unpacking And Generalizing Randomized Extended Kaczmarz, William Gilroy
HMC Senior Theses
Linear systems are fundamental in many areas of science and engineering. With the advent of computers there now exist extremely large linear systems that we are interested in. Such linear systems lend themselves to iterative methods. One such method is the family of algorithms called Randomized Kaczmarz methods.
Among this family, there exists a Randomized Kaczmarz variant called Randomized
Extended Kaczmarz which solves for least squares solutions in inconsistent linear systems.
Among Kaczmarz variants, Randomized Extended Kaczmarz is unique in that it modifies input system in a special way to solve for the least squares solution. In this work we …
An Exploration Of Voting With Partial Orders, 2022 Harvey Mudd College
An Exploration Of Voting With Partial Orders, Mason Acevedo
HMC Senior Theses
In this thesis, we discuss existing ideas and voting systems in social choice theory. Specifically, we focus on the Kemeny rule and the Borda count. Then, we begin trying to understand generalizations of these voting systems in a setting where voters can submit partial rankings on their ballot, instead of complete rankings.
Dynamic Nonlinear Gaussian Model For Inferring A Graph Structure On Time Series, 2022 Claremont Colleges
Dynamic Nonlinear Gaussian Model For Inferring A Graph Structure On Time Series, Abhinuv Uppal
CMC Senior Theses
In many applications of graph analytics, the optimal graph construction is not always straightforward. I propose a novel algorithm to dynamically infer a graph structure on multiple time series by first imposing a state evolution equation on the graph and deriving the necessary equations to convert it into a maximum likelihood optimization problem. The state evolution equation guarantees that edge weights contain predictive power by construction. After running experiments on simulated data, it appears the required optimization is likely non-convex and does not generally produce results significantly better than randomly tweaking parameters, so it is not feasible to use in …
Several Problems In Nonlinear Schrödinger Equations, 2022 Missouri University of Science and Technology
Several Problems In Nonlinear Schrödinger Equations, Tim Van Hoose
Masters Theses
“We study several different problems related to nonlinear Schrödinger equations….
We prove several new results for the first equation: a modified scattering result for both an averaged version of the equation and the full equation, as well as a set of Strichartz estimates and a blowup result for the 3d cubic problem.
We also present an exposition of the classical work of Bourgain on invariant measures for the second equation in the mass-subcritical regime”--Abstract, page iv.
Variational Data Assimilation For Two Interface Problems, 2022 Missouri University of Science and Technology
Variational Data Assimilation For Two Interface Problems, Xuejian Li
Doctoral Dissertations
“Variational data assimilation (VDA) is a process that uses optimization techniques to determine an initial condition of a dynamical system such that its evolution best fits the observed data. In this dissertation, we develop and analyze the variational data assimilation method with finite element discretization for two interface problems, including the Parabolic Interface equation and the Stokes-Darcy equation with the Beavers-Joseph interface condition. By using Tikhonov regularization and formulating the VDA into an optimization problem, we establish the existence, uniqueness and stability of the optimal solution for each concerned case. Based on weak formulations of the Parabolic Interface equation and …
Data-Driven Modeling And Simulations Of Seismic Waves, 2022 Missouri University of Science and Technology
Data-Driven Modeling And Simulations Of Seismic Waves, Yixuan Wu
Doctoral Dissertations
"In recent decades, nonlocal models have been proved to be very effective in the study of complex processes and multiscale phenomena arising in many fields, such as quantum mechanics, geophysics, and cardiac electrophysiology. The fractional Laplacian(−Δ)𝛼/2 can be reviewed as nonlocal generalization of the classical Laplacian which has been widely used for the description of memory and hereditary properties of various material and process. However, the nonlocality property of fractional Laplacian introduces challenges in mathematical analysis and computation. Compared to the classical Laplacian, existing numerical methods for the fractional Laplacian still remain limited. The objectives of this research are …
Role Of Inhibition And Spiking Variability In Ortho- And Retronasal Olfactory Processing, 2022 Virginia Commonwealth University
Role Of Inhibition And Spiking Variability In Ortho- And Retronasal Olfactory Processing, Michelle F. Craft
Theses and Dissertations
Odor perception is the impetus for important animal behaviors, most pertinently for feeding, but also for mating and communication. There are two predominate modes of odor processing: odors pass through the front of nose (ortho) while inhaling and sniffing, or through the rear (retro) during exhalation and while eating and drinking. Despite the importance of olfaction for an animal’s well-being and specifically that ortho and retro naturally occur, it is unknown whether the modality (ortho versus retro) is transmitted to cortical brain regions, which could significantly instruct how odors are processed. Prior imaging studies show different …
Introducing R, 2022 William & Mary
Introducing R, Lawrence Leemis
Arts & Sciences Book Chapters
R is an open source programming language and interactive programming environment that has become the software tool of choice in data analytics. Learning Base R provides an introduction to the language for those with and without prior programming experience. It introduces the key topics that you will need to begin analyzing data and programming in R. The focus here is on the R language rather than a particular application. Within the text, there are 200 exercises to assess your R skills.
Reinforcement Learning: Low Discrepancy Action Selection For Continuous States And Actions, 2022 Georgia Southern University
Reinforcement Learning: Low Discrepancy Action Selection For Continuous States And Actions, Jedidiah Lindborg
Electronic Theses and Dissertations
In reinforcement learning the process of selecting an action during the exploration or exploitation stage is difficult to optimize. The purpose of this thesis is to create an action selection process for an agent by employing a low discrepancy action selection (LDAS) method. This should allow the agent to quickly determine the utility of its actions by prioritizing actions that are dissimilar to ones that it has already picked. In this way the learning process should be faster for the agent and result in more optimal policies.
Eeg Signals Classification Using Lstm-Based Models And Majority Logic, 2022 Georgia Southern University
Eeg Signals Classification Using Lstm-Based Models And Majority Logic, James A. Orgeron
Electronic Theses and Dissertations
The study of elecroencephalograms (EEGs) has gained enormous interest in the last decade with the increase of computational power and availability of EEG signals collected from various human activities or produced during medical tests. The applicability of analyzing EEG signals ranges from helping impaired people communicate or move (using appropriate medical equipment) to understanding people's feelings and detecting diseases.
We proposed new methodology and models for analyzing and classifying EEG signals collected from individuals observing visual stimuli. Our models rely on powerful Long-Short Term Memory (LSTM) Neural Network models, which are currently the state of the art models for performing …
Dynamics Of Mutualism In A Two Prey, One Predator System With Variable Carrying Capacity, 2022 University of North Florida
Dynamics Of Mutualism In A Two Prey, One Predator System With Variable Carrying Capacity, Randy Huy Lee
UNF Graduate Theses and Dissertations
We considered the livelihood of two prey species in the presence of a predator species. To understand this phenomenon, we developed and analyzed two mathematical models considering indirect and direct mutualism of two prey species and the influence of one predator species. Both types of mutualism are represented by an increase in the preys' carrying capacities based on direct and indirect interactions between the prey. Because of mutualism, as the death rate parameter of the predator species goes through some critical value, the model shows transcritical bifurcation. Additionally, in the direct mutualism model, as the death rate parameter decreases to …
Interpretable Design Of Reservoir Computing Networks Using Realization Theory, 2022 Linkedin
Interpretable Design Of Reservoir Computing Networks Using Realization Theory, Wei Miao, Vignesh Narayanan, Jr-Shin Li
Publications
The reservoir computing networks (RCNs) have been successfully employed as a tool in learning and complex decision-making tasks. Despite their efficiency and low training cost, practical applications of RCNs rely heavily on empirical design. In this article, we develop an algorithm to design RCNs using the realization theory of linear dynamical systems. In particular, we introduce the notion of α-stable realization and provide an efficient approach to prune the size of a linear RCN without deteriorating the training accuracy. Furthermore, we derive a necessary and sufficient condition on the irreducibility of the number of hidden nodes in linear RCNs based …