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Articles 391 - 420 of 1368

Full-Text Articles in Applied Mathematics

A Mathematical Model For The Adoption Of Information And Communication Technology In School Libraries In Nigeria, Helen Olubunmi Jaiyeola Akinade, Jeremiah Ademola Balogun, Peter Adebayo Idowu Apr 2022

A Mathematical Model For The Adoption Of Information And Communication Technology In School Libraries In Nigeria, Helen Olubunmi Jaiyeola Akinade, Jeremiah Ademola Balogun, Peter Adebayo Idowu

Library Philosophy and Practice (e-journal)

This study focused on the development of a mathematical model required for estimating the number of adopters of ICT devices among libraries located in Nigeria. Data for this study was collected from 121 respondents selected based on a research survey approach using simple random sampling. 9 ICT devices were identified, namely: PCs, printers/fax machines, search engines, e-library systems, bulk SMS services, library management systems, bar/QR code readers, projectors and video conferencing. The results showed that the earliest ICT devices were adopted for use in 1997, such as: PCs, printers/fax machines and search engines. The remaining ICT devices were adopted in …

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Thickness Of Fluvial Deposits Records Climate Oscillations, Xiaoping Yuan, Laure Guerit, Jean Braun, Delphine Rouby, Charles Shobe Apr 2022

Thickness Of Fluvial Deposits Records Climate Oscillations, Xiaoping Yuan, Laure Guerit, Jean Braun, Delphine Rouby, Charles Shobe

Faculty & Staff Scholarship

Fluvial deposits offer Earth’s best-preserved geomorphic record of past climate change over geological timescales. However, quantitatively extracting this information remains challenging in part due to the complexity of erosion, sediment transport and deposition processes and how each of them responds to climate. Furthermore, sedimentary basins have the potential to temporarily store sediments, and rivers subsequently rework those sediments. This may introduce time lags into sedimentary signals and obscure any direct correlation with climate forcing. Here, using a numerical model that combines all three processes—and a new analytical solution—we show that the thickness of fluvial deposits at the outlet of a …

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Representing And Analyzing The Dynamics Of An Agent-Based Adaptive Social Network Model With Partial Integro-Differential Equations, Hiroki Sayama Apr 2022

Representing And Analyzing The Dynamics Of An Agent-Based Adaptive Social Network Model With Partial Integro-Differential Equations, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

We formulated and analyzed a set of partial integro-differential equations that capture the dynamics of our adaptive network model of social fragmentation involving behavioral diversity of agents. Previous results showed that, if the agents’ cultural tolerance levels were diversified, the social network could remain connected while maintaining cultural diversity. Here we converted the original agent-based model into a continuous equation-based one so we can gain more theoretical insight into the model dynamics. We restricted the node states to 1-D continuous values and assumed the network size was very large. As a result, we represented the whole system as a set …

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Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano Apr 2022

Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano

Electrical and Computer Engineering ETDs

Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …

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Toward Suicidal Ideation Detection With Lexical Network Features And Machine Learning, Ulya Bayram, William Lee, Daniel Santel, Ali Minai, Peggy Clark, Tracy Glauser, John Pestian Apr 2022

Toward Suicidal Ideation Detection With Lexical Network Features And Machine Learning, Ulya Bayram, William Lee, Daniel Santel, Ali Minai, Peggy Clark, Tracy Glauser, John Pestian

Northeast Journal of Complex Systems (NEJCS)

In this study, we introduce a new network feature for detecting suicidal ideation from clinical texts and conduct various additional experiments to enrich the state of knowledge. We evaluate statistical features with and without stopwords, use lexical networks for feature extraction and classification, and compare the results with standard machine learning methods using a logistic classifier, a neural network, and a deep learning method. We utilize three text collections. The first two contain transcriptions of interviews conducted by experts with suicidal (n=161 patients that experienced severe ideation) and control subjects (n=153). The third collection consists of interviews conducted by experts …

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Active Polar Liquid Crystal Channel Flows: Analyzing The Roles Of Nematic Strength And Activation Parameter, Lacey Schenk, Ruhai Zhou Apr 2022

Active Polar Liquid Crystal Channel Flows: Analyzing The Roles Of Nematic Strength And Activation Parameter, Lacey Schenk, Ruhai Zhou

College of Sciences Posters

Suspensions of active polar liquid crystalline polymers (APLC) exhibit complex phenomena such as spontaneous flows, pattern formations and defects. Using the Kinetic Model, which couples the Smoluchowski Equation and the Navier-Stokes Equations, we conduct numerical simulations of APLC in a microfluidic channel to investigate the competitive effect among different material constants, such as the nematic concentration (the strength of the potential for nematic order) and active strength (the individual nano-rods strength of their individual movement) with and without a pressure gradient. Both Dirichlet and Neumann boundary conditions on the mathematical model are employed. Steady states, including isotropic and nematic states, …

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A Spatially And Temporally Second Order Method For Solving Parabolic Interface Problems, Kumudu Gamage, Yan Peng Apr 2022

A Spatially And Temporally Second Order Method For Solving Parabolic Interface Problems, Kumudu Gamage, Yan Peng

College of Sciences Posters

Parabolic interface problems have many applications in physics and biology, such as hyperthermia treatment of cancer, underground water flow, and food engineering. Here we present an algorithm for solving two-dimensional parabolic interface problems where the coefficient and the forcing term have a discontinuity across the interface. The Crank-Nicolson scheme is used for time discretization, and the direct immersed interface method is used for spatial discretization. The proposed method is second order in both space and time for both solution and gradients in maximum norm.

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A New Application Of The Central Limit Theorem, Kenneth Winters Apr 2022

A New Application Of The Central Limit Theorem, Kenneth Winters

Selected Honors Theses

This paper discusses the Central Limit Theorem (CLT) and its applications. The paper gives an introduction to what the CLT is and how it can be applied to real life. Additionally, the paper gives a conceptual understanding of the theorem through various examples and visuals. The paper discusses the applications of the CLT in fields such as computer science, psychology, and political science. The author then suggests a new mathematical theorem as an application of the CLT and provides a proof of the theorem. The new theorem relates to expected value and probabilities of random variables and provides a link …

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A Meshless Approach To Computational Pharmacokinetics, Anthony Matthew Khoury Apr 2022

A Meshless Approach To Computational Pharmacokinetics, Anthony Matthew Khoury

Doctoral Dissertations and Master's Theses

The meshless method is an incredibly powerful technique for solving a variety of problems with unparalleled accuracy and efficiency. The pharmacokinetic problem of transdermal drug delivery (TDDD) is one such topic and is of significant complexity. The locally collocated meshless method (LCMM) is developed in solution to this topic. First, the meshless method is formulated to model this transport phenomenon and is then validated against an analytical solution of a pharmacokinetic problem set, to demonstrate this accuracy and efficiency. The analytical solution provides a locus by which convergence behavior are evaluated, demonstrating the super convergence of the locally collocated meshless …

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Quadratic Neural Network Architecture As Evaluated Relative To Conventional Neural Network Architecture, Reid Taylor Apr 2022

Quadratic Neural Network Architecture As Evaluated Relative To Conventional Neural Network Architecture, Reid Taylor

Senior Theses

Current work in the field of deep learning and neural networks revolves around several variations of the same mathematical model for associative learning. These variations, while significant and exceptionally applicable in the real world, fail to push the limits of modern computational prowess. This research does just that: by leveraging high order tensors in place of 2nd order tensors, quadratic neural networks can be developed and can allow for substantially more complex machine learning models which allow for self-interactions of collected and analyzed data. This research shows the theorization and development of mathematical model necessary for such an idea to …

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Bistability And Switching Behavior In Moving Animal Groups, Daniel Strömbom, Stephanie Nickerson, Catherine Futterman, Alyssa Difazio, Cameron Costello, Kolbjørn Tunstrøm Mar 2022

Bistability And Switching Behavior In Moving Animal Groups, Daniel Strömbom, Stephanie Nickerson, Catherine Futterman, Alyssa Difazio, Cameron Costello, Kolbjørn Tunstrøm

Northeast Journal of Complex Systems (NEJCS)

Moving animal groups such as schools of fish and flocks of birds frequently switch between different group structures. Standard models of collective motion have been used successfully to explain how stable groups form via local interactions between individuals, but they are typically unable to produce groups that exhibit spontaneous switching. We are only aware of one model, constructed for barred flagtail fish that are known to rely on alignment and attraction to organize their collective motion, that has been shown to generate this type of behavior in 2D (or 3D). Interestingly, another species of fish, golden shiners, do exhibit switching …

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Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith Mar 2022

Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith

Theses and Dissertations

The growing surge of misinformation among COVID-19 communication can pose great hindrance to truth, magnify distrust in policy makers and/or degrade authorities’ credibility, and it can even harm public health. Classification of textual context on social media data relating to COVID-19 is an effective tool to combat misinformation on social media platforms. In this research, Twitter data was leveraged to 1) develop classification methods to detect misinformation and identify Tweet sentiment with respect to COVID-19 and 2) develop a human-in-the-loop interactive framework to enable identification of keywords associated with social context, here, being misinformation regarding COVID-19. 1) Six fusion-based classification …

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An Optimization Model For Minimization Of Systemic Risk In Financial Portfolios, Zachary Alexander Gelber Mar 2022

An Optimization Model For Minimization Of Systemic Risk In Financial Portfolios, Zachary Alexander Gelber

Master's Theses

In this thesis, we study how sovereign credit default swaps are able to measure systemic risk as well as how they can be used to construct optimal portfolios to minimize risk. We define the clustering coefficient as a proxy for systemic risk and design an optimization problem with the goal of minimizing the mean absolute deviation of the clustering coefficient on a group of nine European countries. Additionally, we define a metric we call the diversity score that measures the diversification of any given portfolio. We solve this problem for a baseline set of parameters, then spend the remainder of …

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Covid-19 Pandemic Analysis By The Volterra Integral Equation Models: A Preliminary Study Of Brazil, Italy, And South Africa, Yajni Warnapala, Emma Dehetre, Kate Gilbert Feb 2022

Covid-19 Pandemic Analysis By The Volterra Integral Equation Models: A Preliminary Study Of Brazil, Italy, And South Africa, Yajni Warnapala, Emma Dehetre, Kate Gilbert

Arts & Sciences Faculty Publications

The COVID-19 pandemic has affected many people throughout the world. The objective of this research project was to find numerical solutions through the Gaussian Quadrature Method for the Volterra Integral Equation Model. The non-homogenous Volterra Integral Equation of the second kind is used to capture a broader range of disease distributions. Volterra Integral equation models are used in the context of applied mathematics, public health, and evolutionary biology. The mathematical models of this integral equation gave valid convergence results for the COVID-19 data for 3 countries Italy, South Africa and Brazil. The modeling of these countries was done using the …

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The Nature Of Numbers: Real Computing, Bradley J. Lucier Jan 2022

The Nature Of Numbers: Real Computing, Bradley J. Lucier

Journal of Humanistic Mathematics

While studying the computable real numbers as a professional mathematician, I came to see the computable reals, and not the real numbers as usually presented in undergraduate real analysis classes, as the natural culmination of my evolving understanding of numbers as a schoolchild. This paper attempts to trace and explain that evolution. The first part recounts the nature of numbers as they were presented to us grade-school children. In particular, the introduction of square roots induced a step change in my understanding of numbers. Another incident gave me insight into the brilliance of Alan Turing in his paper introducing both …

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Analysis Of A Generalized Discrete Periodic Model For The Spread Of Wolbachia In A Mosquito Population, Alexandra Nicole Osgood Fedrigo Jan 2022

Analysis Of A Generalized Discrete Periodic Model For The Spread Of Wolbachia In A Mosquito Population, Alexandra Nicole Osgood Fedrigo

Honors Capstone Projects and Theses

No abstract provided.

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Check Yourself Before You Wrek Yourself: Unpacking And Generalizing Randomized Extended Kaczmarz, William Gilroy Jan 2022

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 …

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A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization, Hesamoddin Tahami, Hengameh Fakhravar Jan 2022

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 …

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Colonial Markets, Consumers, And Trade: A Comparative Analysis Of Historic Ceramics From The Bluefields Bay Area, Westmoreland, Jamaica, Lacy Risner Jan 2022

Colonial Markets, Consumers, And Trade: A Comparative Analysis Of Historic Ceramics From The Bluefields Bay Area, Westmoreland, Jamaica, Lacy Risner

Murray State Theses and Dissertations

The ceramic assemblages from a British colonial settlement in Bluefields Bay, Jamaica, provide a unique window into the market availability, exchange routes, and consumption patterns of the eighteenth century. This study compares the historic ceramics collected from two sites in Bluefields Bay to one another and to other intra-island (Jamaica), intraregional (Lesser Antilles), and international (North America) colonial and postcolonial sites to reveal patterns of individual and global ceramic consumption and distribution in the emergent capitalist networks and markets of the colonial era. Integrating small British colonial sites into the networks of other more extensive studies focusing primarily on plantations …

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Methods Of Anomaly Detection: An Applied Framework And Application To Health Economics, Nathaniel Eric Islip Jan 2022

Methods Of Anomaly Detection: An Applied Framework And Application To Health Economics, Nathaniel Eric Islip

EWU Masters Thesis Collection

No abstract provided.

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A Simple Algorithm For Generating A New Two Sample Type-Ii Progressive Censoring With Applications, E. M. Shokr, Rashad Mohamed El-Sagheer, Mahmoud Mansour, H. M. Faied, B. S. El-Desouky Jan 2022

A Simple Algorithm For Generating A New Two Sample Type-Ii Progressive Censoring With Applications, E. M. Shokr, Rashad Mohamed El-Sagheer, Mahmoud Mansour, H. M. Faied, B. S. El-Desouky

Basic Science Engineering

In this article, we introduce a simple algorithm to generating a new type-II progressive censoring scheme for two samples. It is observed that the proposed algorithm can be applied for any continues probability distribution. Moreover, the description model and necessary assumptions are discussed. In addition, the steps of simple generation algorithm along with programming steps are also constructed on real example. The inference of two Weibull Frechet populations are discussed under the proposed algorithm. Both classical and Bayesian inferential approaches of the distribution parameters are discussed. Furthermore, approximate confidence intervals are constructed based on the asymptotic distribution of the maximum …

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Towards Simulation Of Complex Ocean Flows: Analysis And Algorithm For Computation Of Coupled Partial Differential Equations, Wenbin Dong Jan 2022

Towards Simulation Of Complex Ocean Flows: Analysis And Algorithm For Computation Of Coupled Partial Differential Equations, Wenbin Dong

Dissertations and Theses

The hybrid CFD models which usually consist of 2 sub-models, develop our capability to simulate many emerging problems with multiphysics and multiscale flows, especially for the coastal ocean flows interacted with local phenomena of interest. For most cases, the sub-models are connected with direct interpolation which is easy and workable. It becomes urgently needed to investigate the inner mechanism of such model integration as this simple method does not work well if the two sub-models are different in governing equations, numerical methods, and computational grids. Also, it can not treat complex flow structures as well as the balance in mass …

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Dynamic Nonlinear Gaussian Model For Inferring A Graph Structure On Time Series, Abhinuv Uppal Jan 2022

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 …

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Role Of Inhibition And Spiking Variability In Ortho- And Retronasal Olfactory Processing, Michelle F. Craft Jan 2022

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 …

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Camouflaged Poisoning Attack On Graph Neural Networks, Chao Jiang, Yi He, Richard Chapman, Hongyi Wu Jan 2022

Camouflaged Poisoning Attack On Graph Neural Networks, Chao Jiang, Yi He, Richard Chapman, Hongyi Wu

Computer Science Faculty Publications

Graph neural networks (GNNs) have enabled the automation of many web applications that entail node classification on graphs, such as scam detection in social media and event prediction in service networks. Nevertheless, recent studies revealed that the GNNs are vulnerable to adversarial attacks, where feeding GNNs with poisoned data at training time can lead them to yield catastrophically devastative test accuracy. This finding heats up the frontier of attacks and defenses against GNNs. However, the prior studies mainly posit that the adversaries can enjoy free access to manipulate the original graph, while obtaining such access could be too costly in …

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Stroke Clustering And Fitting In Vector Art, Khandokar Shakib Jan 2022

Stroke Clustering And Fitting In Vector Art, Khandokar Shakib

Senior Independent Study Theses

Vectorization of art involves turning free-hand drawings into vector graphics that can be further scaled and manipulated. In this paper, we explore the concept of vectorization of line drawings and study multiple approaches that attempt to achieve this in the most accurate way possible. We utilize a software called StrokeStrip to discuss the different mathematics behind the parameterization and fitting involved in the drawings.

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Numerical Investigation On The Effect Of Spectral Radiative Heat Transfer Within An Ablative Material, Raghava S. C. Davuluri, Rui Fu, Kaveh A. Tagavi, Alexandre Martin Dec 2021

Numerical Investigation On The Effect Of Spectral Radiative Heat Transfer Within An Ablative Material, Raghava S. C. Davuluri, Rui Fu, Kaveh A. Tagavi, Alexandre Martin

Mechanical Engineering Faculty Publications

The spectral radiative heat flux could impact the material response. In order to evaluate it, a coupling scheme between KATS - MR and P1 approximation model of radiation transfer equation (RTE) is constructed and used. A Band model is developed that divides the spectral domain into small bands of unequal widths. Two verification studies are conducted: one by comparing the simulation computed by the Band model with pure conduction results and the other by comparing with similar models of RTE. The comparative results from the verification studies indicate that the Band model is computationally efficient and can be used to …

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Numerical Study Of The Seiqr Model For Covid-19, Caitlin Holt Dec 2021

Numerical Study Of The Seiqr Model For Covid-19, Caitlin Holt

Departmental Honors & Graduate Capstone Projects

In this research project, we used numerical methods to investigate trends in the susceptible, exposed, infectious, quarantined, recovered, closed cases and insusceptible populations for the COVID-19 pandemic in 2021. We used the SEIQR model containing seven ordinary differential equations, based on the SIR model for epidemics. An analytical solution was derived from a simplified version of the model, created by making various assumptions about the original model. Numerical solutions were generated for the first 100 days of 2021 using algorithms based on Euler's Method, Runge-Kutta Method, and Multistep Methods. Our goal is to show that numerical methods can help us …

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A Chebyshev Spectral Collocation Method For Solving Kdv-Burgers Equation, Mubarak Awadh Assabaai Dec 2021

A Chebyshev Spectral Collocation Method For Solving Kdv-Burgers Equation, Mubarak Awadh Assabaai

Hadhramout University Journal of Natural & Applied Sciences

A mixed spectral/ Runge-Kutta method is used to obtain numerical solutions of Kortewege–de Vries–Burgers’ (KdVB) equation. The suggested method based on Chebyshev spectral collocation is used with Runge-Kutta method of order four. This technique is accomplished by starting with a Chebyshev approximation for the higher order derivatives in the x -direction and generating approximations to the lower derivatives through successive integrations of the highest-order derivative. The proposed technique reduces the problem to a system of ordinary differential equations in the t -direction. The Runge-Kutta method of order four is used to solve this system. Excellent numerical results have been obtained …

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(R1491) Numerical Solution Of The Time-Space Fractional Diffusion Equation With Caputo Derivative In Time By A-Polynomial Method, Saeid Abbasbandy, Jalal Hajishafieiha Dec 2021

(R1491) Numerical Solution Of The Time-Space Fractional Diffusion Equation With Caputo Derivative In Time By A-Polynomial Method, Saeid Abbasbandy, Jalal Hajishafieiha

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, a novel type of polynomial is defined which is equipped with an auxiliary parameter a. These polynomials are a combination of the Chebyshev polynomials of the second kind. The approximate solution of each equation is assumed as the sum of these polynomials and then, with the help of the collocation points, the unknown coefficients of each polynomial, as well as auxiliary parameter, is obtained optimally. Now, by placing the optimal value of a in polynomials, the polynomials are obtained without auxiliary parameter, which is the restarted step of the present method. The time discretization is performed …

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