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Full-Text Articles in Numerical Analysis and Scientific Computing

Wildfire Emissions In The Context Of Global Change And The Implications For Mercury Pollution, Aditya Kumar Jan 2018

Wildfire Emissions In The Context Of Global Change And The Implications For Mercury Pollution, Aditya Kumar

Dissertations, Master's Theses and Master's Reports

Wildfires are episodic disturbances that exert a significant influence on the Earth system. They emit substantial amounts of atmospheric pollutants, which can impact atmospheric chemistry/composition and the Earth’s climate at the global and regional scales. This work presents a collection of studies aimed at better estimating wildfire emissions of atmospheric pollutants, quantifying their impacts on remote ecosystems and determining the implications of 2000s-2050s global environmental change (land use/land cover, climate) for wildfire emissions following the Intergovernmental Panel on Climate Change (IPCC) A1B socioeconomic scenario.

A global fire emissions model is developed to compile global wildfire emission inventories for major atmospheric …


Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr Dec 2017

Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr

LSU New Orleans Theses and Dissertations

This project started early in the summer of 2016 when it became evident there was a need for an effective and efficient signal analysis toolkit for the Littoral Acoustic Demonstration Center Gulf Ecological Monitoring and Modeling (LADC-GEMM) Research Consortium. LADC-GEMM collected underwater acoustic data in the northern Gulf of Mexico during the summer of 2015 using Environmental Acoustic Recording Systems (EARS) buoys. Much of the visualization of data was handled through short scripts and executed through terminal commands, each time requiring the data to be loaded into memory and parameters to be fed through arguments. The vision was to develop …


Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr Dec 2017

Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr

Journal of International Technology and Information Management

The discovery of useful or worthwhile process models must be performed with due regards to the transformation that needs to be achieved. The blend of the data representations (i.e data mining) and process modelling methods, often allied to the field of Process Mining (PM), has proven to be effective in the process analysis of the event logs readily available in many organisations information systems. Moreover, the Process Discovery has been lately seen as the most important and most visible intellectual challenge related to the process mining. The method involves automatic construction of process models from event logs about any domain …


Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad Dec 2017

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

School of Computing: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …


A High Quality, Eulerian 3d Fluid Solver In C++, Lejon Anthony Mcgowan Nov 2017

A High Quality, Eulerian 3d Fluid Solver In C++, Lejon Anthony Mcgowan

Computer Science and Software Engineering

Fluids are a part of everyday life, yet are one of the hardest elements to properly render in computer graphics. Water is the most obvious entity when thinking of what a fluid simulation can achieve (and it is indeed the focus of this project), but many other aspects of nature, like fog, clouds, and particle effects. Real-time graphics like video games employ many heuristics to approximate these effects, but large-scale renderers aim to simulate these effects as closely as possible.

In this project, I wish to achieve effects of the latter nature. Using the Eulerian technique of discrete grids, I …


Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang Aug 2017

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …


Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico Aug 2017

Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico

The Summer Undergraduate Research Fellowship (SURF) Symposium

Neuroimaging, particularly functional magnetic resonance imaging (fMRI), is a rapidly growing research area and has applications ranging from disease classification to understanding neural development. With new advancements in imaging technology, researchers must employ new techniques to accommodate the influx of high resolution data sets. Here, we replicate a new technique: connectome-based predictive modeling (CPM), which constructs a linear predictive model of brain connectivity and behavior. CPM’s advantages over classic machine learning techniques include its relative ease of implementation and transparency compared to “black box” opaqueness and complexity. Is this method efficient, powerful, and reliable in the prediction of behavioral measures …


Improving The Accuracy For The Long-Term Hydrologic Impact Assessment (L-Thia) Model, Anqi Zhang, Lawrence Theller, Bernard A. Engel Aug 2017

Improving The Accuracy For The Long-Term Hydrologic Impact Assessment (L-Thia) Model, Anqi Zhang, Lawrence Theller, Bernard A. Engel

The Summer Undergraduate Research Fellowship (SURF) Symposium

Urbanization increases runoff by changing land use types from less impervious to impervious covers. Improving the accuracy of a runoff assessment model, the Long-Term Hydrologic Impact Assessment (L-THIA) Model, can help us to better evaluate the potential uses of Low Impact Development (LID) practices aimed at reducing runoff, as well as to identify appropriate runoff and water quality mitigation methods. Several versions of the model have been built over time, and inconsistencies have been introduced between the models. To improve the accuracy and consistency of the model, the equations and parameters (primarily curve numbers in the case of this model) …


Optimization And Control Of Production Of Graphene, Atharva Hans, Nimish M. Awalgaonkar, Majed Alrefae, Ilias Bilionis, Timothy S. Fisher Aug 2017

Optimization And Control Of Production Of Graphene, Atharva Hans, Nimish M. Awalgaonkar, Majed Alrefae, Ilias Bilionis, Timothy S. Fisher

The Summer Undergraduate Research Fellowship (SURF) Symposium

Graphene is a 2-dimensional element of high practical importance. Despite its exceptional properties, graphene’s real applications in industrial or commercial products have been limited. There are many methods to produce graphene, but none has been successful in commercializing its production. Roll-to-roll plasma chemical vapor deposition (CVD) is used to manufacture graphene at large scale. In this research, we present a Bayesian linear regression model to predict the roll-to-roll plasma system’s electrode voltage and current; given a particular set of inputs. The inputs of the plasma system are power, pressure and concentration of gases; hydrogen, methane, oxygen, nitrogen and argon. This …


Structure-Force Field Generator For Molecular Dynamics Simulations, Carlos M. Patiño, Lorena Alzate, Alejandro Strachan Aug 2017

Structure-Force Field Generator For Molecular Dynamics Simulations, Carlos M. Patiño, Lorena Alzate, Alejandro Strachan

The Summer Undergraduate Research Fellowship (SURF) Symposium

Atomistic and molecular simulations have become an important research field due to the progress made in computer performance and the necessity of new and improved materials. Despite this, first principle simulations of large molecules are still not possible because the high computational time and resources required. Other methods, such as molecular dynamics, allow the simplification of calculations by defining energy terms to describe multiple atom interactions without compromising accuracy significantly. A group of these energy terms is called a force field, and each force field has its own descriptions and parameters. The objective of this project was to develop a …


Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni Jul 2017

Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni

Computer Science ETDs

In the era of new technologies, computer scientists deal with massive data of size hundreds of terabytes. Smart cities, social networks, health care systems, large sensor networks, etc. are constantly generating new data. It is non-trivial to extract knowledge from big datasets because traditional data mining algorithms run impractically on such big datasets. However, distributed systems have come to aid this problem while introducing new challenges in designing scalable algorithms. The transition from traditional algorithms to the ones that can be run on a distributed platform should be done carefully. Researchers should design the modern distributed algorithms based on the …


Querying And Visualization Of Moving Objects Using Constraint Databases, Semere M. Woldemariam Jul 2017

Querying And Visualization Of Moving Objects Using Constraint Databases, Semere M. Woldemariam

School of Computing: Dissertations, Theses, and Student Research

Good querying and visualization of moving objects and their trajectories is still an open problem. This thesis investigates three types of moving objects. First, projectiles, whose parabolic motion is difficult to represent. Second, moving objects that slide down a slope. The representation of these objects is challenging because of their accelerating motion. Third, the motion of migrating animals. The motion of migrating animals is challenging because it also involves some spatio-temporal interpolation. The thesis shows a solution to these problems using ideas from physics and an implementation in the MLPQ constraint databases system. The MLPQ implementation enables several complex spatio-temporal …


Homogenization Of Plastic Deformation In Heterogeneous Lamella Structures, Rui Yuan, Irene J. Beyerlein, Caizhi Zhou Jul 2017

Homogenization Of Plastic Deformation In Heterogeneous Lamella Structures, Rui Yuan, Irene J. Beyerlein, Caizhi Zhou

Materials Science and Engineering Faculty Research & Creative Works

It has been shown that unlike its constituent nanocrystalline (NC) phase, a heterogeneous lamella (HL) composite comprising NC and coarse-grain layers exhibits greatly improved ductility. To understand the origin of this enhancement, we present a 3D discrete dislocation, crystal plasticity finite element model to study the development of strains across this microstructure. Here we show that the HL structure homogenizes the plastic strains in the NC layer, weakening the effect of strain concentrations. These findings can provide valuable insight into the effects of material length scales on material instabilities, which is needed to design heterogeneous structures with superior properties.


Molecular Dynamics Simulations Of Dna-Functionalized Nanoparticle Building Blocks On Gpus, Tyler Landon Fochtman May 2017

Molecular Dynamics Simulations Of Dna-Functionalized Nanoparticle Building Blocks On Gpus, Tyler Landon Fochtman

Graduate Theses and Dissertations

This thesis discusses massively parallel molecular dynamics simulations of nBLOCKs using graphical processing units. nBLOCKs are nanoscale building blocks composed of gold nanoparticles functionalized with single-stranded DNA molecules. To explore greater simulation time scales we implement our nBLOCK computational model as an extension to the coarse grain molecular simulator oxDNA. oxDNA is parameterized to match the thermodynamics of DNA strand hybridization as well as the mechanics of single stranded DNA and double stranded DNA. In addition to an in-depth review of our implementation details we also provide results of the model validation and performance tests. These validation and performance tests …


Evaluating A Personal Stress Monitoring System, Sneha Gogineni May 2017

Evaluating A Personal Stress Monitoring System, Sneha Gogineni

Theses and Dissertations

Now-a-days, Life is generally much more stressful than in the past. "Stress" is the word that we use when we feel that we are overloaded mentally in our thoughts and wonder whether we can really cope with those placed upon us. Sometimes, stress gets us going and they are good for us but at other times, it could be the cause to undermine both our mental and physical health. The way we respond to a challenge can be considered as a kind of stress. Part of our response to a challenge is physiological and affects our own physical state. When …


A Robust Framework For Mining Youtube Data, Zifeng Tian Jan 2017

A Robust Framework For Mining Youtube Data, Zifeng Tian

Theses, Dissertations and Capstones

YouTube is currently the most popular and successful video sharing website. As YouTube has broad and profound social impact, YouTube analytics has become a hot research area. The videos on YouTube have become a treasure of data. However, getting access to the immense and massive YouTube data is a challenge. Previous research, studies, and analysis so far, are only conducted on very small volumes of YouTube video data. To date, there exists no mechanism to systematically and continuously collect, process and store the rich set of YouTube data. This thesis presents a methodology to systematically and continuously mine and store …


High Performance Techniques Applied In Partial Differential Equations Library, Shilei Lin Jan 2017

High Performance Techniques Applied In Partial Differential Equations Library, Shilei Lin

All College Thesis Program, 2016-2019

This thesis explores various Trilinos packages to determine a method for updating the deal.ii library, which specializes in solving partial differential equations by finite element methods. It begins with introducing related concepts and general goals, followed by exploring computational and mathematical methods which are analytical solutions of one-dimensional Boussinesq equations and developing newer prototypes for solvers in deal.ii based on Trilinos packages. After demonstrating the methods, it indicates the reducing solving time in newer prototypes. Based on results from the prototype, similar methods are applied to update the deal.ii library. In the end, a testing program is exploited to demonstrate …


An Out-Of-Core Gpu Based Dimensionality Reduction Algorithm For Big Mass Spectrometry Data And Its Application In Bottom-Up Proteomics, Muaaz Awan, Fahad Saeed Jan 2017

An Out-Of-Core Gpu Based Dimensionality Reduction Algorithm For Big Mass Spectrometry Data And Its Application In Bottom-Up Proteomics, Muaaz Awan, Fahad Saeed

Parallel Computing and Data Science Lab Technical Reports

Modern high resolution Mass Spectrometry instruments can generate millions of spectra in a single systems biology experiment. Each spectrum consists of thousands of peaks but only a small number of peaks actively contribute to deduction of peptides. Therefore, pre-processing of MS data to detect noisy and non-useful peaks are an active area of research. Most of the sequential noise reducing algorithms are impractical to use as a pre-processing step due to high time-complexity. In this paper, we present a GPU based dimensionality-reduction algorithm, called G-MSR, for MS2 spectra. Our proposed algorithm uses novel data structures which optimize the memory and …


A Physics-Based Approach To Modeling Wildland Fire Spread Through Porous Fuel Beds, Tingting Tang Jan 2017

A Physics-Based Approach To Modeling Wildland Fire Spread Through Porous Fuel Beds, Tingting Tang

Theses and Dissertations--Mechanical and Aerospace Engineering

Wildfires are becoming increasingly erratic nowadays at least in part because of climate change. CFD (computational fluid dynamics)-based models with the potential of simulating extreme behaviors are gaining increasing attention as a means to predict such behavior in order to aid firefighting efforts. This dissertation describes a wildfire model based on the current understanding of wildfire physics. The model includes physics of turbulence, inhomogeneous porous fuel beds, heat release, ignition, and firebrands. A discrete dynamical system for flow in porous media is derived and incorporated into the subgrid-scale model for synthetic-velocity large-eddy simulation (LES), and a general porosity-permeability model is …


Hybrid Parallelization Of The Nasa Gemini Electromagnetic Modeling Tool, Buxton L. Johnson Sr. Jan 2017

Hybrid Parallelization Of The Nasa Gemini Electromagnetic Modeling Tool, Buxton L. Johnson Sr.

Theses and Dissertations--Electrical and Computer Engineering

Understanding, predicting, and controlling electromagnetic field interactions on and between complex RF platforms requires high fidelity computational electromagnetic (CEM) simulation. The primary CEM tool within NASA is GEMINI, an integral equation based method-of-moments (MoM) code for frequency domain electromagnetic modeling. However, GEMINI is currently limited in the size and complexity of problems that can be effectively handled. To extend GEMINI’S CEM capabilities beyond those currently available, primary research is devoted to integrating the MFDlib library developed at the University of Kentucky with GEMINI for efficient filling, factorization, and solution of large electromagnetic problems formulated using integral equation methods. A secondary …


Anomaly Detection In Rfid Networks, Alaa Alkadi Jan 2017

Anomaly Detection In Rfid Networks, Alaa Alkadi

UNF Graduate Theses and Dissertations

Available security standards for RFID networks (e.g. ISO/IEC 29167) are designed to secure individual tag-reader sessions and do not protect against active attacks that could also compromise the system as a whole (e.g. tag cloning or replay attacks). Proper traffic characterization models of the communication within an RFID network can lead to better understanding of operation under “normal” system state conditions and can consequently help identify security breaches not addressed by current standards. This study of RFID traffic characterization considers two piecewise-constant data smoothing techniques, namely Bayesian blocks and Knuth’s algorithms, over time-tagged events and compares them in the context …


Computational Fluid Dynamics Is Key To Better Flying Aircraft, Nihad E. Daidzic Dec 2016

Computational Fluid Dynamics Is Key To Better Flying Aircraft, Nihad E. Daidzic

Aviation Department Publications

No abstract provided.


Shape Analysis Of Traffic Flow Curves Using A Hybrid Computational Analysis, Wasim Irshad Kayani, Shikhar P. Acharya, Ivan G. Guardiola, Donald C. Wunsch, B. Schumacher, Isaac Wagner-Muns Nov 2016

Shape Analysis Of Traffic Flow Curves Using A Hybrid Computational Analysis, Wasim Irshad Kayani, Shikhar P. Acharya, Ivan G. Guardiola, Donald C. Wunsch, B. Schumacher, Isaac Wagner-Muns

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper highlights and validates the use of shape analysis using Mathematical Morphology tools as a means to develop meaningful clustering of historical data. Furthermore, through clustering more appropriate grouping can be accomplished that can result in the better parameterization or estimation of models. This results in more effective prediction model development. Hence, in an effort to highlight this within the research herein, a Back-Propagation Neural Network is used to validate the classification achieved through the employment of MM tools. Specifically, the Granulometric Size Distribution (GSD) is used to achieve clustering of daily traffic flow patterns based solely on their …


Fractal Analysis Of Dna Sequences, Christian G. Arias, Pedro Antonio Moreno Phd, Carlos Tellez Oct 2016

Fractal Analysis Of Dna Sequences, Christian G. Arias, Pedro Antonio Moreno Phd, Carlos Tellez

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Nondestructive Testing And Structural Health Monitoring Based On Adams And Svm Techniques, Gang Jiang, Yi Ming Deng, Ji Tai Niu Oct 2016

Nondestructive Testing And Structural Health Monitoring Based On Adams And Svm Techniques, Gang Jiang, Yi Ming Deng, Ji Tai Niu

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.


A Parallel 3d Phase-Field Simulation Of Multi-Grain Growth Based On The Full Thread Tree, Ya-Jun Yin, Min Wang, Jian-Xin Zhou, Dun-Ming Liao, Xu Shen, Tao Chen Oct 2016

A Parallel 3d Phase-Field Simulation Of Multi-Grain Growth Based On The Full Thread Tree, Ya-Jun Yin, Min Wang, Jian-Xin Zhou, Dun-Ming Liao, Xu Shen, Tao Chen

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.


Computer-Aided Design Of Algorithms Of Pulsed Control Of Arc Welding Process Based On Numerical Simulation, Oksana I. Shpigunova, Anatoliy A. Glazunov Oct 2016

Computer-Aided Design Of Algorithms Of Pulsed Control Of Arc Welding Process Based On Numerical Simulation, Oksana I. Shpigunova, Anatoliy A. Glazunov

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.


Numerical Simulation Of The Through Process Of Aerospace Titanium Alloy Casting Filling, Solidification, And Hot Isostatic Pressing, Jian-Xin Zhou, Zhao Guo, Ya-Jun Yin, Chang-Chang Liu Oct 2016

Numerical Simulation Of The Through Process Of Aerospace Titanium Alloy Casting Filling, Solidification, And Hot Isostatic Pressing, Jian-Xin Zhou, Zhao Guo, Ya-Jun Yin, Chang-Chang Liu

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.


Development And Computer Simulation Of A New Combined Energy-Saving Technological Process Of Production Of High-Quality Wire With Sub-Ultrafine-Grained Structure, Abdrakhman Naizabekov, Sergey Lezhnev, Evgeniy Panin, Igor Mazur Oct 2016

Development And Computer Simulation Of A New Combined Energy-Saving Technological Process Of Production Of High-Quality Wire With Sub-Ultrafine-Grained Structure, Abdrakhman Naizabekov, Sergey Lezhnev, Evgeniy Panin, Igor Mazur

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.


Study On Growth Model Of Cellular Automata Method In Solidification Simulation, Zhao Guo, Jian-Xin Zhou, Ya-Jun Yin, Chang-Chang Liu Oct 2016

Study On Growth Model Of Cellular Automata Method In Solidification Simulation, Zhao Guo, Jian-Xin Zhou, Ya-Jun Yin, Chang-Chang Liu

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.