Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (15)
- Life Sciences (12)
- Non-linear Dynamics (8)
- Numerical Analysis and Computation (7)
- Ordinary Differential Equations and Applied Dynamics (7)
-
- Control Theory (6)
- Mechanical Engineering (6)
- Electrical and Computer Engineering (5)
- Mathematics (5)
- Medicine and Health Sciences (5)
- Computer Sciences (4)
- Controls and Control Theory (4)
- Dynamics and Dynamical Systems (4)
- Engineering Science and Materials (4)
- Operations Research, Systems Engineering and Industrial Engineering (4)
- Other Operations Research, Systems Engineering and Industrial Engineering (4)
- Partial Differential Equations (4)
- Probability (4)
- Statistics and Probability (4)
- Acoustics, Dynamics, and Controls (3)
- Applied Mechanics (3)
- Chemical Engineering (3)
- Data Science (3)
- Risk Analysis (3)
- Aerospace Engineering (2)
- Artificial Intelligence and Robotics (2)
- Biology (2)
- Institution
-
- Virginia Commonwealth University (8)
- University of Dar es Salaam (5)
- Illinois State University (3)
- Prairie View A&M University (3)
- Michigan Technological University (2)
-
- California Polytechnic State University, San Luis Obispo (1)
- Central Washington University (1)
- Clemson University (1)
- Dartmouth College (1)
- East Tennessee State University (1)
- Florida Institute of Technology (1)
- Georgia Southern University (1)
- Harding University (1)
- Louisiana State University (1)
- Old Dominion University (1)
- Purdue University (1)
- Southern Methodist University (1)
- University of Alkafeel (1)
- University of Louisville (1)
- University of Nebraska - Lincoln (1)
- University of New Mexico (1)
- University of South Carolina (1)
- Washington University in St. Louis (1)
- Wilfrid Laurier University (1)
- Keyword
-
- Epidemiology (3)
- Machine Learning (2)
- Mathematical modeling (2)
- Other (2)
- Reinforcement Learning (2)
-
- ADNI database (1)
- Adaptive Nawaz Enscore Ham (NEH) (1)
- Adjustable Cart (1)
- Air-decking (1)
- Alzheimer’s disease (1)
- Analyis (1)
- Analytical model (1)
- And Artificial neural network (ANN) models (1)
- And Perona-Malik Model (1)
- Angular contact bearings (1)
- Annealing (1)
- Attractors (1)
- Autoencoders (1)
- Bayesian inference (1)
- Bayesian methods (1)
- Bifurcation (1)
- Blast induced ground vibration (BIGV) (1)
- Bound-preserving (1)
- Brain data (1)
- Brain graph (1)
- Cart Can Hitch to Vehicle (1)
- Characteristic Functions (1)
- Characteristic curve (1)
- Charging station (1)
- Cholera (1)
- Publication
-
- Biology and Medicine Through Mathematics Conference (7)
- Tanzania Journal of Engineering and Technology (TJET) (5)
- Annual Symposium on Biomathematics and Ecology Education and Research (3)
- Applications and Applied Mathematics: An International Journal (AAM) (3)
- Dissertations, Master's Theses and Master's Reports (2)
-
- Electronic Theses and Dissertations (2)
- Theses and Dissertations (2)
- Al-Bahir (1)
- All Dissertations (1)
- All Master's Theses (1)
- Cybersecurity Undergraduate Research Showcase (1)
- Dartmouth College Ph.D Dissertations (1)
- Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023– (1)
- Electrical and Computer Engineering ETDs (1)
- Honors College Theses (1)
- Honors Theses (1)
- LSU Doctoral Dissertations (1)
- Mathematics Theses and Dissertations (1)
- McKelvey School of Engineering Graduate Student Theses & Dissertations (1)
- Mechanical Engineering (1)
- Publications (1)
- The Journal of Purdue Undergraduate Research (1)
- Theses and Dissertations (Comprehensive) (1)
- Publication Type
Articles 31 - 40 of 40
Full-Text Articles in Dynamic Systems
Enhanced Post Deposition Annealing Conditions On The Fabrication Of High Quality Thermochromic Vanadium Dioxide Films, Nuru R. Mlyuka
Enhanced Post Deposition Annealing Conditions On The Fabrication Of High Quality Thermochromic Vanadium Dioxide Films, Nuru R. Mlyuka
Tanzania Journal of Engineering and Technology (TJET)
Sputter deposition of thermochromic VO2 thin films for smart window applications has been faced with several challenges including the need for high deposition temperature, extremely precise and narrow range of oxygen/argon flow ratio and target poisoning during sputtering. Deposition of VO2 at room temperature without oxygen followed by post-deposition annealing has been cited as one of the potential mitigations to the challenge. In this study, the effects of post-deposition annealing conditions on the structural, electrical and optical properties of VO2 thin films are reported. The films were prepared on soda lime glass substrates using DC magnetron sputtering of metallic vanadium …
Optimal Load Shedding During Service Restoration In Electrical Secondary Distribution Network Based On Reinforcement Learning, Rukia J. Mwifunyi
Optimal Load Shedding During Service Restoration In Electrical Secondary Distribution Network Based On Reinforcement Learning, Rukia J. Mwifunyi
Tanzania Journal of Engineering and Technology (TJET)
Increased stress in traditional power systems results in blackouts due to voltage instability attributed to a mismatch between available capacity and load demand, especially in distribution networks. Service restoration schemes are designed to return power supply to the affected parts of the networks. The availability of insufficient supply is a complex problem that requires operational experience or an automatic system. The stochastic nature of load demand significantly impacts service restoration as it results in increased restored demand in case a fault occurs during off-peak hours and helps reduce overload if the fault occurs during peak hours. The study adopts an …
Exploration Of Characteristic Curve In Fox Float 3 Shock Dampers To Expedite Shock Damp Tuning., Joshua R. Moore
Exploration Of Characteristic Curve In Fox Float 3 Shock Dampers To Expedite Shock Damp Tuning., Joshua R. Moore
Honors College Theses
The shock absorber is an integral part of a vehicle suspension system and has a strong influence on its performance, especially in the case of motorsports. It is important to study the force versus velocity relationship, commonly known as the characteristic curve of the shock absorber both during compression and rebound. Vendor-supplied characteristics often reflect the behavior of the shock absorber in a particular setting. However, during the installation, the settings inside the shock absorber are adjusted to increase the human comfort level and performance of the vehicle. This may change the characteristic curve of the shock. The available data …
Generation, Dynamics, And Interaction Of Quartic Solitary Waves In Nonlinear Laser Systems, Sabrina Hetzel
Generation, Dynamics, And Interaction Of Quartic Solitary Waves In Nonlinear Laser Systems, Sabrina Hetzel
Mathematics Theses and Dissertations
Solitons are self-reinforcing localized wave packets that have remarkable stability features that arise from the balanced competition of nonlinear and dispersive effects in the medium. Traditionally, the dominant order of dispersion has been the lowest (second), however in recent years, experimental and theoretical research has shown that high, even order dispersion may lead to novel applications. Here, the focus is on investigating the interplay of dominant quartic (fourth-order) dispersion and the self-phase modulation due to the nonlinear Kerr effect in laser systems. One big factor to consider for experimentalists working in laser systems is the effect of noise on the …
Methods, Analyses, And Applications Of Multilayer Temporal Link Prediction In Networks, Xie He
Methods, Analyses, And Applications Of Multilayer Temporal Link Prediction In Networks, Xie He
Dartmouth College Ph.D Dissertations
Many applications stem from the possibility of accurately predicting links in various types of networks. In this thesis, we present methods, analyses, and applications for static, temporal, and multilayer networks. The first part of this thesis demonstrates how static network features serve as efficient and accurate predictors for link prediction in temporal networks. It includes an ensemble learning method we developed and presents experimental results on 90 synthetic stochastic block models and 19 real-world datasets. The second part closely follows, showcasing 20 different sampling methods and their effects on nine different link prediction algorithms for 250 real-world networks across 6 …
Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers
Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers
All Master's Theses
The development of electric vehicles is currently considered one of the most innovative areas in manufacturing. Largely driven by the desire to reduce greenhouse emissions, electric vehicles are seen as a viable alternative to internal combustion engine cars. Starting from consumer cars, a dedicated effort is being made to translate this into commercial vehicles for freight and delivery. This research introduces a novel adaptive Nawaz, Enscore, Ham (NEH) algorithm with constrained nearest neighbor subtour (NEH-NN). This algorithm is tested on the standard benchmark problems in literature and used as a seed solution for the Genetic Algorithm (GA). The performance and …
Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa
Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa
Dissertations, Master's Theses and Master's Reports
Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), …
Discontinuous Galerkin Methods For Compressible Miscible Displacements And Applications In Reservoir Simulation, Yue Kang
Dissertations, Master's Theses and Master's Reports
This dissertation contains research on discontinuous Galerkin (DG) methods applied to the system of compressible miscible displacements, which is widely adopted to model surfactant flooding in enhanced oil recovery (EOR) techniques. In most scenarios, DG methods can effectively simulate problems in miscible displacements.
However, if the problem setting is complex, the oscillations in the numerical results can be detrimental, with severe overshoots leading to nonphysical numerical approximations. The first way to address this issue is to apply the bound-preserving
technique. Therefore, we adopt a bound-preserving Discontinuous Galerkin method
with a Second-order Implicit Pressure Explicit Concentration (SIPEC) time marching
method to …
Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen
Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen
Theses and Dissertations (Comprehensive)
The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain's capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of …
Mathematical Analysis Of Eukaryotic Pericentromere, Puranjan Ghimire
Mathematical Analysis Of Eukaryotic Pericentromere, Puranjan Ghimire
Theses and Dissertations
The centromere is crucial for chromosomal stability and their proper segregation during cell division in eukaryotes. Surrounding the centromere are pericentromeres, made of repetitive DNA elements called pericentromeric repeats, varying from 10 in fission yeast to thousands in humans. These repeats form densely packed heterochromatin, where genes are usually silenced. The silencing mechanism across different pericentromeric repeats remains unclear.
Despite variations in sequence and length, pericentromeric repeats are conserved across eukaryotes, indicating their functional importance. This dissertation presents mathematical models to quantify gene silencing in fission yeast and humans. In fission yeast, my model predicts that silencing occurs only with …