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Articles 751 - 780 of 7920
Full-Text Articles in Applied Mathematics
Locally Varying Geostatistical Machine Learning For Spatial Prediction, Francky Fouedjio, Emet Arya
Locally Varying Geostatistical Machine Learning For Spatial Prediction, Francky Fouedjio, Emet Arya
Research outputs 2022 to 2026
Machine learning methods dealing with the spatial auto-correlation of the response variable have garnered significant attention in the context of spatial prediction. Nonetheless, under these methods, the relationship between the response variable and explanatory variables is assumed to be homogeneous throughout the entire study area. This assumption, known as spatial stationarity, is very questionable in real-world situations due to the influence of contextual factors. Therefore, allowing the relationship between the target variable and predictor variables to vary spatially within the study region is more reasonable. However, existing machine learning techniques accounting for the spatially varying relationship between the dependent variable …
Radial, Vortex, And Spiral Solutions To The Nonlinear Schrödinger Equation And Other Reaction--Diffusion Systems, James Redmon Cummins
Radial, Vortex, And Spiral Solutions To The Nonlinear Schrödinger Equation And Other Reaction--Diffusion Systems, James Redmon Cummins
Masters Theses and Doctoral Dissertations
This dissertation explores various solutions to nonlinear reaction-diffusion systems, focusing primarily on the nonlinear Schrödinger equation. Three types of solutions are investigated: radial solutions (with no angular dependence), vortex solutions (with angular dependence but no radial phase dependence), and spiral solutions (which have radial phase dependence). The study considers free particles without potential and trapped particles inside the cylindrical potential with an impenetrable barrier. We show that spiral solutions to the nonlinear Schrödinger equation only exist for a radially constant phase by considering a related system of nonlinear ordinary differential equations. This system is shown to be a special case …
Hitch Cart “Landing Gear”, Rebekah White, Jose Raygoza, Randy Hernandez, Brandon Leon
Hitch Cart “Landing Gear”, Rebekah White, Jose Raygoza, Randy Hernandez, Brandon Leon
Mechanical Engineering
This report aims to allow our sponsor, to review our design process of the Hitch Cart Landing Gear Prototype. In the design overview section of this report, we discuss the primary design modifications we made to the wheel mechanism of the existing hitch cart prototype, including the addition of the ACME screws and the folding brackets. This allows our sponsor to see the intended improvements made to the past prototype and understand the primary goal of our project. Then, in the implementation section, we cover the entire manufacturing process to allow our sponsor to understand what manufacturing steps must be …
(R2098) Dynamic Analysis Of Stochastic Leslie-Gower Biological Predator-Prey Model With Prey Cannibalism, Sada Nand Prasad, Itendra Kumar Universiry Of Delhi, India, Pawan Kumar
(R2098) Dynamic Analysis Of Stochastic Leslie-Gower Biological Predator-Prey Model With Prey Cannibalism, Sada Nand Prasad, Itendra Kumar Universiry Of Delhi, India, Pawan Kumar
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, we study the dynamical analysis of a stochastic Leslie–Gower biological predator– prey model. Earlier, the Leslie–Gower model was studied in the context of biological systems, including cases involving cannibalism. In our model, we investigate the dynamic properties of a stochastic Leslie–Gower predator–prey ecological system using the stability of invariant measures on invariant sets, where the invariant measures are shown to be ergodic. We also conduct a threshold analysis to study the stochastic persistence and extinction of species. Stochastic bifurcation is also examined. The theoretical results are supported by numerical simulations and examples. Intra-species competition is considered and …
(R2102) Chaos Measure In A Discrete Sir Epidemic Model With Constant Recovery, Sonia Aneja, Itendra Kumar, Sada Nand Prasad
(R2102) Chaos Measure In A Discrete Sir Epidemic Model With Constant Recovery, Sonia Aneja, Itendra Kumar, Sada Nand Prasad
Applications and Applied Mathematics: An International Journal (AAM)
A discrete SIR epidemic model with constant recovery and bilinear incidence rate is investigated for emergence of regular and chaotic behaviour in the context of non linear dynamics and different viable settings. The Euler’s discretization method is employed to transform the continuous epidemic model into discrete model which has been used as the study model. Attention is paid to various bifurcation plots obtained by varying certain system parameters while keeping other parameters constant. Bifurcations indicate regular evolution followed by chaos. Regular and chaotic attractors have been drawn in the process. As part of chaos measure, numerical studies are extended to …
(R2097) Impact Of Inclined Magnetic Field On Two Immiscible Viscous Fluids Flow In A Porous Channel With Variable Permeability: A Finite Difference Technique, Angad Prasad, P. K. Singh
(R2097) Impact Of Inclined Magnetic Field On Two Immiscible Viscous Fluids Flow In A Porous Channel With Variable Permeability: A Finite Difference Technique, Angad Prasad, P. K. Singh
Applications and Applied Mathematics: An International Journal (AAM)
This paper is concerned with the flow of two immiscible, viscous, incompressible, and electrically conducting fluids in a horizontal channel containing a porous material under an inclined magnetic field. The flow is propelled by a consistent pressure gradient. These two fluids have different viscosities in two separate layers of equal width. The fluid in the upper layer has a lower viscosity compared to the fluid in the lower layer. The Permeability of a porous medium is variable with the transverse direction. The Brinkman equation is employed to describe fluid flow within a porous medium. Numerical solutions for velocity and volumetric …
(R2104) On The Qualitative Results Of Riemann-Liouville Fractional Order Nonlinear Neutral Singular Systems With Mixed Delays, Abdullah Yiğit, Cemil Tunç
(R2104) On The Qualitative Results Of Riemann-Liouville Fractional Order Nonlinear Neutral Singular Systems With Mixed Delays, Abdullah Yiğit, Cemil Tunç
Applications and Applied Mathematics: An International Journal (AAM)
In this manuscript, we discuss new conditions for asymptotic stability of nonlinear Riemann- Liouville fractional mixed-delay neutral singular systems. By constructing a set of improved Lyapunov-Krasovski˘ı functionals (LKFs), we establish some new delay-dependent conditions in terms of matrix inequality, which guarantees that the systems are asymptotically stable. In the particular case, we give four numerical examples with their solutions and graphs via MATLAB software demonstrating the practical applicability of these proven conditions. With this study, some conditions existing in the literature are developed and generalized.
(R2113) A Numerical Method For Solving Linear First-Order Volterra Integro-Differential Equations With Integral Boundary Condition, Zelal Temel, Musa Cakir
(R2113) A Numerical Method For Solving Linear First-Order Volterra Integro-Differential Equations With Integral Boundary Condition, Zelal Temel, Musa Cakir
Applications and Applied Mathematics: An International Journal (AAM)
We investigate an efficient numerical method for the linear first-order Volterra integro-differential equations with integral boundary condition. To solve this problem, boundaries are determined for its derivative and the solution. The numerical solutions of the problem are modeled over a uniform mesh using the composite right-side rectangle concept for the integral component and the implicit difference rules for the differential component. Next, the stability and convergence of the numerical approach are discussed. The numerical experiments are presented confirming the accuracy of the proposed scheme.
Computational Investigation Of Boundary-Layer Transition Mechanisms In A Blunt Cone, Arturo Rodriguez
Computational Investigation Of Boundary-Layer Transition Mechanisms In A Blunt Cone, Arturo Rodriguez
Open Access Theses & Dissertations
In this study, we have performed two-dimensional steady-state hypersonic CFD and one-and-two-dimensional steady-state heat conduction numerical simulations. We are using them to guide and study hypersonic boundary-layer transition ground testing physical experiments to be performed at Holloman High-Speed Test Track. We use surface heat transfer and fluid flow spot signatures to identify fluid flow regimes using laminar and turbulent numerical simulation solvers to understand boundary-layer transition thermocouple temperatures and fluid flow-forming structures. We have also analyzed the fluid flow in the geometries to be inviscid. We passed the CFD solution into the boundary-layer Harris code developed by NASA to explore …
Enhancing Mathematical Models For Covid-19 Pandemic Response: A Philippine Study, Timothy Robin Teng, Elvira De Lara-Tuprio, Ma. Regina Justina Estuar, Christian Pulmano, Lu Christian S. Ong, Zachary Pangan, Lenard Paulo V. Tamayo, Jasper John V. Segismundo, Mark Anthony C. Tolentino, Alyssa Nicole N. Ty
Enhancing Mathematical Models For Covid-19 Pandemic Response: A Philippine Study, Timothy Robin Teng, Elvira De Lara-Tuprio, Ma. Regina Justina Estuar, Christian Pulmano, Lu Christian S. Ong, Zachary Pangan, Lenard Paulo V. Tamayo, Jasper John V. Segismundo, Mark Anthony C. Tolentino, Alyssa Nicole N. Ty
Mathematics Faculty Publications
Mathematical models supported by a robust automated data pipeline proved to be useful tools for a data-driven and science-based response and policy-making during the COVID-19 pandemic in the Philippines. In the first year of the pandemic, FASSSTER (Feasibility Analysis on Syndromic Surveillance using Spatio-Temporal Epidemiological modeleR) used a compartmental model to generate scenario-based projections of COVID-19 cases. The emergence of the Delta variant, however, and the administration of vaccines over the second half of 2021 caused significant changes in the Philippine pandemic landscape. This necessitated making adjustments to the model to better capture the local disease transmission dynamics and address …
Bayesian Lasso Regularized Quantile Regression And Its Applications, Priscilla Kissi-Appiah
Bayesian Lasso Regularized Quantile Regression And Its Applications, Priscilla Kissi-Appiah
Theses and Dissertations
Since the pioneering work of (Koenker and Bassett Jr 1978), quantile regression has been a popular regression technique that helps researchers investigate a whole distribution of the response variable. In addition, due to the quantile check loss function, it is robust against outliers and heavy-tailed distributions of the response variable and can provide a more comprehensive picture of modeling via exploring the conditional quantiles of the response variable. In this research, we study the lasso regularized quantile regression from a Bayesian perspective. We develop an efficient sampling algorithm to generate posterior samplings for making posterior inference by using a location-scale …
Bounding The Convex Hull Relaxation Of The Unit Commitment Problem With The Shapley-Folkman Theorem, Lauren Henderson
Bounding The Convex Hull Relaxation Of The Unit Commitment Problem With The Shapley-Folkman Theorem, Lauren Henderson
All Theses
The Unit Commitment (UC) problem finds an optimal schedule for a set of generators by minimizing the total operation cost subject to demand and operational constraints. The UC problem is often modeled with a mixed-integer linear program (MILP). We employ the Shapley-Folkman Theorem to provide a bound on the size of fractional solutions of its convex hull relaxation. This result is used to obtain a bound on the optimality gap between the MILP and the convex hull relaxation, which is further tightened using several problem-specific properties of UC. We conduct extensive numerical experiments to study the tightness of this threshold, …
Geoflood: Computational Model For Overland Flooding, Brian Kyanjo
Geoflood: Computational Model For Overland Flooding, Brian Kyanjo
Boise State University Theses and Dissertations
Overland flooding, a critical environmental phenomenon, poses significant challenges for computational modeling due to its complex hydrodynamics and the need for high-resolution data. This thesis presents GeoFlood, a new open-source software package for overland flooding simulations. The computational model solves shallow water equations (SWE) on a quadtree hierarchy of mapped, logically Cartesian grids managed by the parallel, adaptive library ForestClaw (Calhoun & Burstedde, 2017). The model is validated using standard benchmark tests from Neelz & Pender (2013) and against results from the GeoClaw software (George, 2011; Clawpack Development Team, 2020) for the historical Malpasset dam break problem. The benchmark test …
Question-Attentive Review-Level Explanation For Neural Rating Regression, Trung Hoang Le, Hady Wirawan Lauw
Question-Attentive Review-Level Explanation For Neural Rating Regression, Trung Hoang Le, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Recommendation explanations help to improve their acceptance by end users. Explanations come in many different forms. One that is of interest here is presenting an existing review of the recommended item as the explanation. The challenge is in selecting a suitable review, which is customarily addressed by assessing the relative importance or “attention” of each review to the recommendation objective. Our focus is improving review-level explanation by leveraging additional information in the form of questions and answers (QA). The proposed framework employs QA in an attention mechanism that aligns reviews to various QAs of an item and assesses their contribution …
A Dynamical Systems Approach For Modeling Malware Propagating Through A Network And Potential Solutions Towards Mitigating Spread, James Johnson
A Dynamical Systems Approach For Modeling Malware Propagating Through A Network And Potential Solutions Towards Mitigating Spread, James Johnson
Cybersecurity Undergraduate Research Showcase
Many people draw close parallels between malware propagating through a network and an epidemic spreading through a population. Epidemics are often modeled by a Susceptible-Infected-Recovered (SIR) model, in which a similar system of equations can model the spread of a virus through a computer network, and can be simplified when making assumptions about the network itself and its fixed number of nodes and edges. In this instance, malware propagating in a network also should reflect the network it is propagating through, in which the dynamical system will factor in the nodes of the network and their properties. The system itself …
Leveraging Quantitative Systems Pharmacology For Dose Optimization In Oncology Drug Development, Blerta Shtylla
Leveraging Quantitative Systems Pharmacology For Dose Optimization In Oncology Drug Development, Blerta Shtylla
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Kreig: Gaining Insight Into Epidemics Through Use Of Mathematical Modeling, Christina Edholm
Kreig: Gaining Insight Into Epidemics Through Use Of Mathematical Modeling, Christina Edholm
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Shevtsov: Growing Pains And Growing Gains: The Arizona Experience, Tynan Lazarus, Jane Shevtsov
Shevtsov: Growing Pains And Growing Gains: The Arizona Experience, Tynan Lazarus, Jane Shevtsov
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Early Ctdna Kinetics As A Dynamic Biomarker Of Cancer Treatment Response, Aaron Li, Emil Lou, Kevin Leder, Jasmine Foo
Early Ctdna Kinetics As A Dynamic Biomarker Of Cancer Treatment Response, Aaron Li, Emil Lou, Kevin Leder, Jasmine Foo
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
A Paradigm For Ecological Dynamics In Predator-Prey Systems: Applications To Climate Change, Grayson D. Adams, Aditi Ghosh Dr.
A Paradigm For Ecological Dynamics In Predator-Prey Systems: Applications To Climate Change, Grayson D. Adams, Aditi Ghosh Dr.
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Kreig: Examining Affinity Maturation And Antigenic Drift With An Agent-Based Model, Jasmine Af Kreig, Jannatul Ferdous, Ruian Ke, Ruy M. Ribeiro
Kreig: Examining Affinity Maturation And Antigenic Drift With An Agent-Based Model, Jasmine Af Kreig, Jannatul Ferdous, Ruian Ke, Ruy M. Ribeiro
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Modelling Saccharomyces Cerevisiae For The Production Of Fermented Beverages, Paul A. Valle Dr., Yolocuauhtli Salazar Dr., Luis N. Coria Dr., Oscar N. Soto Dr., Jesus B. Paez Dr.
Modelling Saccharomyces Cerevisiae For The Production Of Fermented Beverages, Paul A. Valle Dr., Yolocuauhtli Salazar Dr., Luis N. Coria Dr., Oscar N. Soto Dr., Jesus B. Paez Dr.
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Network Analysis Of Progress In Mathematics Research, Anna Singley
Network Analysis Of Progress In Mathematics Research, Anna Singley
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
From Ecology To Modeling Apps - Newts, Crayfish, And Slopes, Timothy Lucas
From Ecology To Modeling Apps - Newts, Crayfish, And Slopes, Timothy Lucas
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Bodine: Exploring The Versatility Of Agent-Based Modeling In Netlogo: Lessons From Education And Research, Anne E. Yust
Bodine: Exploring The Versatility Of Agent-Based Modeling In Netlogo: Lessons From Education And Research, Anne E. Yust
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Bayesian Networks And Machine Learning For Predicting Breast Cancer Growth From In Vitro Cell Count Data, Widodo Samyono
Bayesian Networks And Machine Learning For Predicting Breast Cancer Growth From In Vitro Cell Count Data, Widodo Samyono
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Seshaiyer: Data-Driven Machine Learning Framework To Predict Dynamics Of Infectious Diseases Incorporating Human Behavior, Alonso Gabriel Ogueda Oliva, Dr. Padmanabhan Seshaiyer
Seshaiyer: Data-Driven Machine Learning Framework To Predict Dynamics Of Infectious Diseases Incorporating Human Behavior, Alonso Gabriel Ogueda Oliva, Dr. Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Bodine: Enhancing Netlogo3d Simulations: Computational Efficiency And Online Accessibility Of A Pain Model, Rachael Miller Neilan
Bodine: Enhancing Netlogo3d Simulations: Computational Efficiency And Online Accessibility Of A Pain Model, Rachael Miller Neilan
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Modeling Opioid Addiction In Hand Surgery Patients, Eli Goldwyn, Grace Bowman, Kathryn Montovan, Julie Blackwood
Modeling Opioid Addiction In Hand Surgery Patients, Eli Goldwyn, Grace Bowman, Kathryn Montovan, Julie Blackwood
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Modeling The Synergistic Interplay Between Malaria Dynamics And Economic Growth, Ruijun Zhao, Hope Enright, Calistus Ngonghala, Olivia Prsoper
Modeling The Synergistic Interplay Between Malaria Dynamics And Economic Growth, Ruijun Zhao, Hope Enright, Calistus Ngonghala, Olivia Prsoper
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.