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Fast, Sparse Matrix Factorization And Matrix Algebra Via Random Sampling For Integral Equation Formulations In Electromagnetics, Owen Tanner Wilkerson 2019 University of Kentucky

Fast, Sparse Matrix Factorization And Matrix Algebra Via Random Sampling For Integral Equation Formulations In Electromagnetics, Owen Tanner Wilkerson

Theses and Dissertations--Electrical and Computer Engineering

Many systems designed by electrical & computer engineers rely on electromagnetic (EM) signals to transmit, receive, and extract either information or energy. In many cases, these systems are large and complex. Their accurate, cost-effective design requires high-fidelity computer modeling of the underlying EM field/material interaction problem in order to find a design with acceptable system performance. This modeling is accomplished by projecting the governing Maxwell equations onto finite dimensional subspaces, which results in a large matrix equation representation (Zx = b) of the EM problem. In the case of integral equation-based formulations of EM problems, the M-by-N system matrix, Z, is generally dense. For this reason, when treating large problems, it is necessary to use compression methods to store and manipulate Z. One such sparse representation is provided by so-called H^2 matrices. At low-to-moderate frequencies, H^2 matrices provide a controllably accurate data-sparse representation of Z.

The scale at which problems in EM are considered ``large'' is continuously being redefined to be larger. This growth of problem scale is not only happening in EM, but respectively across all other sub-fields of computational science as well. The pursuit of increasingly large problems is unwavering in all these sub-fields, and this drive has long outpaced the rate of advancements in processing and storage capabilities in computing. This has caused computational science communities to now face the computational limitations of standard linear algebraic methods that have been relied upon for decades to run quickly and efficiently on modern computing hardware. This common set of algorithms can only produce reliable results quickly and efficiently for small to mid-sized matrices that fit into the memory of the host computer. Therefore, the drive to pursue larger problems has even began to outpace the reasonable capabilities of these common numerical algorithms; the deterministic numerical linear algebra algorithms that have gotten matrix computation this far have proven to be inadequate for many problems of current interest. This has computational science communities focusing on improvements in their mathematical and software approaches in order to push further advancement. Randomized numerical linear algebra (RandNLA) is an emerging area that both academia and industry believe to be strong candidates to assist in overcoming the limitations faced when solving massive and computationally expensive problems.

This thesis presents results of recent work that uses a random sampling method (RSM) to implement algebraic operations ...


On Learning And Visualizing Lexicographic Preference Trees, Ahmed S. Moussa 2019 University of North Florida

On Learning And Visualizing Lexicographic Preference Trees, Ahmed S. Moussa

UNF Graduate Theses and Dissertations

Preferences are very important in research fields such as decision making, recommendersystemsandmarketing. The focus of this thesis is on preferences over combinatorial domains, which are domains of objects configured with categorical attributes. For example, the domain of cars includes car objects that are constructed withvaluesforattributes, such as ‘make’, ‘year’, ‘model’, ‘color’, ‘body type’ and ‘transmission’.Different values can instantiate an attribute. For instance, values for attribute ‘make’canbeHonda, Toyota, Tesla or BMW, and attribute ‘transmission’ can haveautomaticormanual. To this end,thisthesis studiesproblemsonpreference visualization and learning for lexicographic preference trees, graphical preference models that often are compact over complex domains of ...


Predicting Dynamic Modulus Of Asphalt Mixture Using Data Obtained From Indirect Tension Mode Of Testing, Parnian Ghasemi, Shibin Lin, Derrick K. Rollins, R. Christopher Williams 2019 Iowa State University

Predicting Dynamic Modulus Of Asphalt Mixture Using Data Obtained From Indirect Tension Mode Of Testing, Parnian Ghasemi, Shibin Lin, Derrick K. Rollins, R. Christopher Williams

Chemical and Biological Engineering Publications

Understanding stress-strain behavior of asphalt pavement under repetitive traffic loading is of critical importance to predict pavement performance and service life. For viscoelastic materials, the stress-strain relationship can be represented by the dynamic modulus. The dynamic modulus test in indirect tension mode can be used to measure the modulus of each specific layer of asphalt pavements using representative samples. Dynamic modulus is a function of material properties, loading, and environmental conditions. Developing predictive models for dynamic modulus is efficient and cost effective. This article focuses on developing an accurate Finite Element (FE) model using mixture elastic modulus and asphalt binder ...


Immunity-Based Framework For Autonomous Flight In Gps-Challenged Environment, Mohanad Al Nuaimi 2019 West Virginia University

Immunity-Based Framework For Autonomous Flight In Gps-Challenged Environment, Mohanad Al Nuaimi

Graduate Theses, Dissertations, and Problem Reports

In this research, the artificial immune system (AIS) paradigm is used for the development of a conceptual framework for autonomous flight when vehicle position and velocity are not available from direct sources such as the global navigation satellite systems or external landmarks and systems. The AIS is expected to provide corrections of velocity and position estimations that are only based on the outputs of onboard inertial measurement units (IMU). The AIS comprises sets of artificial memory cells that simulate the function of memory T- and B-cells in the biological immune system of vertebrates. The innate immune system uses information about ...


Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski 2018 Wojciech Budzianowski Consulting Services

Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.


Elevated Temperature Progressive Damage And Failure Of Duplex Stainless Steel, Darren P. Luke 2018 University of New Mexico - Main Campus

Elevated Temperature Progressive Damage And Failure Of Duplex Stainless Steel, Darren P. Luke

Civil Engineering ETDs

Ductile failure of metals has been the focus of research efforts within academia and industry for many years since it is tremendously important for understanding the failure of structures under extreme loading conditions. However, limited research has been dedicated to elevated temperature ductile failure, which is critical for evaluating catastrophic events such as industrial, structural or shipping vessel fires. A detailed investigation was conducted on the structural response of Duplex Stainless Steel at elevated temperatures. The temperature dependence of elastic modulus, yield strength, ultimate strength, and ductility was measured up to 1000°C and a continuum damage plasticity model was ...


Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali 2018 The University of Western Ontario

Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali

Electronic Thesis and Dissertation Repository

The main concept behind business intelligence (BI) is how to use integrated data across different business systems within an enterprise to make strategic decisions. It is difficult to map internal and external BI’s users to subsets of the enterprise’s data warehouse (DW), resulting that protecting the privacy of this data while maintaining its utility is a challenging task. Today, such DW systems constitute one of the most serious privacy breach threats that an enterprise might face when many internal users of different security levels have access to BI components. This thesis proposes a data masking framework (iMaskU: Identify ...


Variable Input Observer For Nonstationary High-Rate Dynamic Systems, Jonathan Hong, Simon Laflamme, Liang Cao, Jacob Dodson, Bryan Joyce 2018 Iowa State University

Variable Input Observer For Nonstationary High-Rate Dynamic Systems, Jonathan Hong, Simon Laflamme, Liang Cao, Jacob Dodson, Bryan Joyce

Civil, Construction and Environmental Engineering Publications

Engineering systems experiencing events of amplitudes higher than 100 gn for a duration under 100 ms, here termed high-rate dynamics, can undergo rapid damaging effects. If the structural health of such systems could be accurately estimated in a timely manner, preventative measures could be employed to minimize adverse effects. For complex high-rate problems, adaptive observers have shown promise due to their capability to deal with nonstationary, noisy, and uncertain systems. However, adaptive observers have slow convergence rates, which impede their applicability to the high-rate problems. To improve on the convergence rate, we propose a variable input space concept for ...


Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran MINH, Chanh Minh TRAN, Tuan An LE, Binh Thai NGUYEN, Triet Minh TRAN, Rajesh Krishna BALAN 2018 Singapore Management University

Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan

Research Collection School Of Information Systems

This paper provides a fog-based approach to solving the traffic light optimization problem which utilizes the Adaptive Traffic Signal Control (ATSC) model. ATSC systems demand the ability to strictly reflect real-time traffic state. The proposed fog computing framework, namely FogFly, aligns with this requirement by its natures in location-awareness, low latency and affordability to the changes in traffic conditions. As traffic data is updated timely and processed at fog nodes deployed close to data sources (i.e., vehicles at intersections) traffic light cycles can be optimized efficiently while virtualized resources available at network edges are efficiently utilized. Evaluation results show ...


A Computational Analysis Of The Gradient Concentration Profile Of Deet And The Mosquito Behavioral Response, Brandon Carver 2018 University of Southern Mississippi

A Computational Analysis Of The Gradient Concentration Profile Of Deet And The Mosquito Behavioral Response, Brandon Carver

Master's Theses

DEET is a common active ingredient in most spatial repellents. DEET is also a volatile organic compound. DEET prevents mosquitoes from detecting and coming into contact with an human individual. Gas sensing technologies such as metal oxide semiconductor sensors can detect VOCs. The World Health Organization provides the majority of efficacy testing methods. This research adapts methods from the WHO and use of MOS sensors to further understand how and why DEET affects mosquitos. A custom developed system is used to measure DEET dissipation and observe mosquito behavioral response to the DEET. DEET dissipations and mosquito behavior is measured within ...


Blokus Game Solver, Chin Chao 2018 California Polytechnic State University, San Luis Obispo

Blokus Game Solver, Chin Chao

Computer Engineering

Blokus (officially pronounced as “Block us”) is an abstract strategy board game with transparent Tetris-shaped, color pieces that players are trying to place onto the board. However, the players can only place a piece that touches at least one corner of their own pieces on the board. The ultimate goal of the game is to place as many pieces onto the board as a player can while blocking off the opponent’s ability to place more pieces onto the board. Each player has pieces with different shapes and sizes that can be placed onto the board, where each block within ...


Fingerprint Database Privacy Guard: An Open-Source System That Secures Fingerprints With Locality Sensitive Hashing Algorithms, Enrique Sanchez 2018 University of Arkansas, Fayetteville

Fingerprint Database Privacy Guard: An Open-Source System That Secures Fingerprints With Locality Sensitive Hashing Algorithms, Enrique Sanchez

Computer Science and Computer Engineering Undergraduate Honors Theses

Fingerprint identification is one of the most accurate sources of identification, yet it is not widely used in public facilities for security concerns. Moreover, the cost of fingerprint system is inaccessible for small-budget business because of their high cost. Therefore, this study created an open-source solution to secure fingerprint samples in the database while using low-cost hardware components. Locality Sensitive Hashing Algorithms such as ORB and Image hash were compared in this study as a potential alternative to SURF. To test the design, fifteen samples were collected and stored in a database without verifying the quality of the samples. Then ...


A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. McPherson 2018 University of Arkansas, Fayetteville

A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. Mcpherson

Computer Science and Computer Engineering Undergraduate Honors Theses

Cooperative 3D printing is an emerging technology that aims to increase the 3D printing speed and to overcome the size limit of the printable object by having multiple mobile 3D printers (printhead-carrying mobile robots) work together on a single print job on a factory floor. It differs from traditional layer-by-layer 3D printing due to requiring multiple mobile printers to work simultaneously without interfering with each other. Therefore, a new approach for slicing a digital model and generating commands for the mobile printers is needed, which has not been discussed in literature before. We propose a chunk-by-chunk based slicer that divides ...


Landmine Detection Using Semi-Supervised Learning., Graham Reid 2018 University of Louisville

Landmine Detection Using Semi-Supervised Learning., Graham Reid

Electronic Theses and Dissertations

Landmine detection is imperative for the preservation of both military and civilian lives. While landmines are easy to place, they are relatively difficult to remove. The classic method of detecting landmines was by using metal-detectors. However, many present-day landmines are composed of little to no metal, necessitating the use of additional technologies. One of the most successful and widely employed technologies is Ground Penetrating Radar (GPR). In order to maximize efficiency of GPR-based landmine detection and minimize wasted effort caused by false alarms, intelligent detection methods such as machine learning are used. Many sophisticated algorithms are developed and employed to ...


A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert 2018 Southwestern Oklahoma State University

A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert

Student Research

Artificial Intelligence(AI) is a growing topic in Computer Science and has many uses in real world applications. One application is using Al, or more specifically Neural Networks to model data and predict outcomes. Neural Networks have been used in the past to predict weather changes, create facial recognition software , and to create self-driving cars. Our project is a validation study of, “Modeling Time Series Data With Deep Fourier Neural Networks” by Gashler and Ashmore, 2016. Here we show that a neural network can be trained to be an effective predictor of weather patterns in Alaska over several years. Our ...


Toward Building Resilient, Sustainable, And Smart Infrastructure In The 21st Century, Aly Mousaad Aly 2018 Louisiana State University

Toward Building Resilient, Sustainable, And Smart Infrastructure In The 21st Century, Aly Mousaad Aly

Faculty Publications

In recent years, as a result of significant climate change, stringent windstorms are becoming more frequent than before. Given the threat that windstorms bring to people and property, wind/structural engineering research is imperative to improve the resilience of existing and new infrastructure, for community safety and assets protection. The Windstorm Impact, Science and Engineering (WISE) research program at Louisiana State University (LSU) focuses on creating new knowledge applicable to the mitigation of existing and new infrastructure, to survive and perform optimally under natural hazards. To achieve our research goals, we address two imperious challenges: (i) characterization of realistic wind ...


Dynamic Fracture Of Pmma, Intefacial Failure, And Local Heating, Javad Mehrmashhadi, Longzhen Wang, Florin Bobaru Ph.D. 2018 University of Nebraska - Lincoln

Dynamic Fracture Of Pmma, Intefacial Failure, And Local Heating, Javad Mehrmashhadi, Longzhen Wang, Florin Bobaru Ph.D.

Javad Mehrmashhadi

Recent impact experiments showed the influence of a strong or weak interface in a bi-layered PMMA material has on dynamic fracture mechanisms. We show that a linear elastic with brittle damage peridynamic model, which works very well for glass, leads to crack propagation speeds significantly faster than those measured experimentally in the PMMA system. We propose an explanation for this behavior: localized heating in the region near the crack tip (due to high strain rates) softens the material sufficiently to make a difference. We introduce this effect in our peridynamic model, via a bi-linear bond force-strain relationship, and the computed ...


A Multi-Task Approach To Incremental Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher 2018 Technological University Dublin

A Multi-Task Approach To Incremental Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher

Conference papers

Incrementality is a fundamental feature of language in real world use. To this point, however, the vast majority of work in automated dialogue processing has focused on language as turn based. In this paper we explore the challenge of incremental dialogue state tracking through the development and analysis of a multi-task approach to incremental dialogue state tracking. We present the design of our incremental dialogue state tracker in detail and provide evaluation against the well known Dialogue State Tracking Challenge 2 (DSTC2) dataset. In addition to a standard evaluation of the tracker, we also provide an analysis of the Incrementality ...


Web-Based Archaeology And Collaborative Research, Fabrizio Galeazzi, Heather Richards-Rissetto 2018 University of York

Web-Based Archaeology And Collaborative Research, Fabrizio Galeazzi, Heather Richards-Rissetto

Anthropology Faculty Publications

While digital technologies have been part of archaeology for more than fifty years, archaeologists still look for more efficient methodologies to integrate digital practices of fieldwork recording with data management, analysis, and ultimately interpretation.This Special Issue of the Journal of Field Archaeology gathers international scholars affiliated with universities, organizations, and commercial enterprises working in the field of Digital Archaeology. Our goal is to offer a discussion to the international academic community and practitioners. While the approach is interdisciplinary, our primary audience remains readers interested in web technology and collaborative platforms in archaeology


Esense 2.0: Modeling Biomimetic Predation With Multi-Agent Multi-Team Distributed Artificial Intelligence, D. Michael Franklin, Derek Martin 2018 Kennesaw State University

Esense 2.0: Modeling Biomimetic Predation With Multi-Agent Multi-Team Distributed Artificial Intelligence, D. Michael Franklin, Derek Martin

Georgia Undergraduate Research Conference (GURC)

Biologic predation is a complex interaction amongst sets of predators and prey operating within the same environment. There are many disparate factors for each member of each set to consider as they interact. Additionally, they each must seek food while avoiding other predators, meaning that they must prioritize their actions based on policies. eSense provides a powerful yet simplistic reinforcement learning algorithm that employs model-based behavior across multiple learning layers. These independent layers split the learning objectives across multiple layers, avoiding the learning-confusion common in many multi-agent systems. The new eSense 2.0 increases the number of layers and the ...


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