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Full-Text Articles in Engineering

Simulation-Based Optimization Of A Dc Microgrid: With Machine-Learning-Based Models And Hybrid Meta-Heuristic Algorithms, Tyler Van Deese Oct 2023

Simulation-Based Optimization Of A Dc Microgrid: With Machine-Learning-Based Models And Hybrid Meta-Heuristic Algorithms, Tyler Van Deese

Theses and Dissertations

The field of economic dispatch (ED) focuses on optimizing power flow in a power system to minimize costs. It has the potential to significantly enhance system effectiveness, and efficiency, and reduce operating costs. Various techniques have been employed to tackle this problem, each with its own strengths and weaknesses. One promising approach is simulation-based optimization (SBO), which allows for accurate modeling of system interactions and improved representation of expected results. However, SBO requires running numerous simulations to identify an optimal solution, and there is a possibility of not achieving the global optimum. This work aims to address these challenges using …


Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector Apr 2022

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …


Methods For Object Tracking With Machine Vision, Zachary Simon Stamler Jan 2021

Methods For Object Tracking With Machine Vision, Zachary Simon Stamler

Dissertations and Theses

As machine learning and deep learning systems continue to find applications in science and engineering, the problem of providing these systems with high-quality data continues to increase in importance. Many of these systems utilize machine vision as their primary source of information, and in order to maximally leverage their abilities it is important to be able to provide them with high quality, accurate data. Unfortunately, many sets of tracking data extracted from video suffer from the problem of missing frames, which can arise from a multitude of causes depending on the system. These missing frames can result in confusion between …


Clustered Hyperspectral Target Detection, Sean Onufer Stalley Dec 2020

Clustered Hyperspectral Target Detection, Sean Onufer Stalley

Dissertations and Theses

Aerial target detection is often used to search for relatively small things over large areas of land. Depending on the size and signature of the target, detection can be a very easy or very difficult task. By capturing images with several hundred color channels, hyperspectral sensors provide a new way of looking at this task, both literally and figuratively. Hyperspectral sensors can be used in many aerial target detection tasks such as identifying unhealthy trees in a forest, searching for minerals at a mining site, or finding the sources of chemical leaks at a factory. The high spectral resolution of …


An Investigation Of The Cortical Learning Algorithm, Anthony C. Samaritano May 2018

An Investigation Of The Cortical Learning Algorithm, Anthony C. Samaritano

Theses and Dissertations

Pattern recognition and machine learning fields have revolutionized countless industries and applications from biometric security to modern industrial assembly lines. The fields continue to accelerate as faster, more efficient processing hardware becomes commercially available. Despite the accelerated growth of the pattern recognition and machine learning fields, computers still are unable to learn, reason, and perform rudimentary tasks that humans and animals find routine. Animals are able to move fluidly, understand their environment, and maximize their chances of survival through adaptation - animals demonstrate intelligence. A primary argument in this thesis that we have not yet achieved a level of intelligence …


Academic Packing For Commercial Fpga Architectures, Travis D. Haroldsen Jul 2017

Academic Packing For Commercial Fpga Architectures, Travis D. Haroldsen

Theses and Dissertations

With a few exceptions, academic packing algorithms for FPGAs are typically applied solely to theoretical architectures. This has allowed the algorithms to focus on the basic components of packing while abstracting away many of the details dictated by real hardware. As commercially available FPGAs have advanced, however, the academic algorithms and architectures have diverged significantly from their commercial counterparts. In this dissertation, the RapidSmith 2 framework is presented. This framework accurately reflects the architecture of Xilinx FPGAs and provides support for integrating custom tools into the commercial CAD tools. Using this framework, the RSVPack packing algorithm is implemented. The RSVPack …


Generalized Differential Calculus And Applications To Optimization, R. Blake Rector Jun 2017

Generalized Differential Calculus And Applications To Optimization, R. Blake Rector

Dissertations and Theses

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations …


Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly Dec 2016

Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly

Dissertations and Theses

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat.

An implantable cardiac …


Evaluation Of Data-Path Topologies For Self-Timed Conditional Statements, Navaneeth Prasannakumar Jamadagni Aug 2015

Evaluation Of Data-Path Topologies For Self-Timed Conditional Statements, Navaneeth Prasannakumar Jamadagni

Dissertations and Theses

This research presents a methodology to evaluate data path topologies that implement a conditional statement for an average-case performance that is better than the worst-case performance. A conditional statement executes one of many alternatives depending on how Boolean conditions evaluate to true or false. Alternatives with simple computations take less time to execute. The self-timed designs can exploit the faster executing alternatives and provide an average-case behavior, where the average depends on the frequency of simple and complex computations, and the difference in the completion times of simple and complex computations. The frequency of simple and complex computations depends on …


Identifying Image Manipulation Software From Image Features, Devlin T. Boyter Mar 2015

Identifying Image Manipulation Software From Image Features, Devlin T. Boyter

Theses and Dissertations

As technology steadily increases in the field of image manipulation, determining which software was used to manipulate an image becomes increasingly complex for law enforcement and intelligence agencies. To combat this difficult problem, new techniques that examine the artifacts left behind by a specific manipulation are converted to features for classification. This research implemented four preexisting image manipulation detection techniques into a framework of modules: Two-Dimensional Second Derivative, One-Dimensional Zero Crossings, Quantization Matrices Identification, and File Metadata analysis. The intent is the creation of a framework to develop a capability to determine which specific image manipulation software program manipulated an …


Snail Algorithm For Task Allocation In Mesh Networks, Bartosz Duszel Dec 2013

Snail Algorithm For Task Allocation In Mesh Networks, Bartosz Duszel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Topic of this master's thesis is connected with task allocation algorithms and mesh networks. Author of this work has already graduated from Wroclaw, University of Technology (Poland) where during his studies he created software simulation environment for two different task allocation algorithms for mesh networks:Adaptive ScanandFrame Sliding. Those algorithms were compared by two, main parame- ters: simulation time and average mesh fulfillment (utilization level). All simulations were done in software environment which was developed specially for that research. This application was based on few, different types of objects: task (width, height, processing time), task queue (different number of tasks), task …


Transient And Distributed Algorithms To Improve Islanding Detection Capability Of Inverter Based Distributed Generation, Mohamed Al Hosani Jan 2013

Transient And Distributed Algorithms To Improve Islanding Detection Capability Of Inverter Based Distributed Generation, Mohamed Al Hosani

Electronic Theses and Dissertations

Recently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten years in anticipation of the tremendous increase in the penetration of Distributed Generation (DG) in distribution system. This work proposes new IDMs that rely on transient and distributed behaviors to …


Spectrum Sharing And Service Pricing In Dynamic Spectrum Access Networks, Swastik Kumar Brahma Jan 2011

Spectrum Sharing And Service Pricing In Dynamic Spectrum Access Networks, Swastik Kumar Brahma

Electronic Theses and Dissertations

Traditionally, radio spectrum has been statically allocated to wireless service providers (WSPs). Regulators, like FCC, give wireless service providers exclusive long term licenses for using specific range of frequencies in particular geographic areas. Moreover, restrictions are imposed on the technologies to be used and the services to be provided. The lack of flexibility in static spectrum allocation constrains the ability to make use of new technologies and the ability to redeploy the spectrum to higher valued uses, thereby resulting in inefficient spectrum utilization [23, 38, 42, 62, 67]. These limitations have motivated a paradigm shift from static spectrum allocation towards …


Global Secure Sets Of Trees And Grid-Like Graphs, Yiu Yu Ho Jan 2011

Global Secure Sets Of Trees And Grid-Like Graphs, Yiu Yu Ho

Electronic Theses and Dissertations

Let G = (V, E) be a graph and let S ⊆ V be a subset of vertices. The set S is a defensive alliance if for all x ∈ S, |N[x] ∩ S| ≥ |N[x] − S|. The concept of defensive alliances was introduced in [KHH04], primarily for the modeling of nations in times of war, where allied nations are in mutual agreement to join forces if any one of them is attacked. For a vertex x in a defensive alliance, the number of neighbors of x inside the alliance, plus the vertex x, is at least the number …


Labeled Sampling Consensus A Novel Algorithm For Robustly Fitting Multiple Structures Using Compressed Sampling, Carl J. Messina Jan 2011

Labeled Sampling Consensus A Novel Algorithm For Robustly Fitting Multiple Structures Using Compressed Sampling, Carl J. Messina

Electronic Theses and Dissertations

The ability to robustly fit structures in datasets that contain outliers is a very important task in Image Processing, Pattern Recognition and Computer Vision. Random Sampling Consensus or RANSAC is a very popular method for this task, due to its ability to handle over 50% outliers. The problem with RANSAC is that it is only capable of finding a single structure. Therefore, if a dataset contains multiple structures, they must be found sequentially by finding the best fit, removing the points, and repeating the process. However, removing incorrect points from the dataset could prove disastrous. This thesis offers a novel …


Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James Mar 2009

Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James

Theses and Dissertations

The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …


Characterization And Implementation Of A Real-World Target Tracking Algorithm On Field Programmable Gate Arrays With Kalman Filter Test Case, Benjamin D. Hancey Mar 2008

Characterization And Implementation Of A Real-World Target Tracking Algorithm On Field Programmable Gate Arrays With Kalman Filter Test Case, Benjamin D. Hancey

Theses and Dissertations

A one dimensional Kalman Filter algorithm provided in Matlab is used as the basis for a Very High Speed Integrated Circuit Hardware Description Language (VHDL) model. The JAVA programming language is used to create the VHDL code that describes the Kalman filter in hardware which allows for maximum flexibility. A one-dimensional behavioral model of the Kalman Filter is described, as well as a one-dimensional and synthesizable register transfer level (RTL) model with optimizations for speed, area, and power. These optimizations are achieved by a focus on parallelization as well as careful Kalman filter sub-module algorithm selection. Newton-Raphson reciprocal is the …


Polarimeter Blind Deconvolution Using Image Diversity, David M. Strong Sep 2007

Polarimeter Blind Deconvolution Using Image Diversity, David M. Strong

Theses and Dissertations

This research presents an algorithm that improves the ability to view objects using an electro-optical imaging system with at least one polarization sensitive channel in addition to the primary channel. An innovative algorithm for detection and estimation of the defocus aberration present in an image is also developed. Using a known defocus aberration, an iterative polarimeter deconvolution algorithm is developed using a generalized expectation-maximization (GEM) model. The polarimeter deconvolution algorithm is extended to an iterative polarimeter multiframe blind deconvolution (PMFBD) algorithm with an unknown aberration. Using both simulated and laboratory images, the results of the new PMFBD algorithm clearly outperforms …


Computational Modeling Of The Dielectric Barrier Discharge (Dbd) Device For Aeronautical Applications, Christopher S. Charles Mar 2006

Computational Modeling Of The Dielectric Barrier Discharge (Dbd) Device For Aeronautical Applications, Christopher S. Charles

Theses and Dissertations

Dielectric Barrier Discharge (DBD) type devices, when used as plasma actuators, have shown significant promise for use in many aeronautical applications. Experimentally, DBD actuator devices have been shown to induce motion in initially still air, and to cause re-attachment of air flow over a wing surface at a high angle of attack. This thesis explores the numerical simulation of the DBD device in both a lD and 2D environment. Using well established fluid equation techniques, along with the appropriate approximations for the regime under which these devices will be operating, computational results for various conditions and geometries are explored. In …


Multiframe Shift Estimation, Stephen A. Bruckart Mar 2006

Multiframe Shift Estimation, Stephen A. Bruckart

Theses and Dissertations

The purpose of this research was to develop a fundamental framework for a new approach to multiframe translational shift estimation in image processing. This thesis sought to create a new multiframe shift estimator, to theoretically prove and experimentally test key properties of it, and to quantify its performance according to several metrics. The new estimator was modeled successfully and was proven to be an unbiased estimator under certain common image noise conditions. Furthermore its performance was shown to be superior to the cross correlation shift estimator, a robust estimator widely used in similar image processing cases, according to several criteria. …


Multiple Model Adaptive Estimator Target Tracker For Maneuvering Targets In Clutter, Brian D. Smith Mar 2005

Multiple Model Adaptive Estimator Target Tracker For Maneuvering Targets In Clutter, Brian D. Smith

Theses and Dissertations

The task of tracking a target in the presence of measurement clutter is a two-fold problem: one of handling measurement association uncertainty (due to clutter), and poorly known or significantly varying target dynamics. Measurement association uncertainty does not allow conventional tracking algorithms (such as Kalman filters) to be implemented directly. Poorly known or varying target dynamics complicate the design of any tracking filter, and filters using only a single dynamics model can rarely handle anything beyond the most benign target maneuvers. In recent years, the Multiple Hypothesis Tracker (MHT) has gained acceptance as a means of handling targets in a …


Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra Mar 2002

Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra

Theses and Dissertations

The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …


Offline And Online Variants Of The Traveling Salesman Problem, John Ebenezer Augustine Jan 2002

Offline And Online Variants Of The Traveling Salesman Problem, John Ebenezer Augustine

LSU Master's Theses

In this thesis, we study several well-motivated variants of the Traveling Salesman Problem (TSP). First, we consider makespan minimization for vehicle scheduling problems on trees with release and handling times. 2-approximation algorithms were known for several variants of the single vehicle problem on a path. A 3/2-approximation algorithm was known for the single vehicle problem on a path where there is a fixed starting point and the vehicle must return to the starting point upon completion. Karuno, Nagamochi and Ibaraki give a 2-approximation algorithm for the single vehicle problem on trees. We develop a Polynomial Time Approximation Scheme (PTAS) for …


Adaptive Notch Filter For Single And Multiple Narrow-Band Interference, Choy Chun Sin Jan 2001

Adaptive Notch Filter For Single And Multiple Narrow-Band Interference, Choy Chun Sin

Theses : Honours

In this project, the adaptive notch filter for single and Multiple narrow-band interference is implemented using simplified LMS algorithm. Performances of the LMS adaptive algorithms is evaluated and analysed through simulation on the computer using Matlab. The algorithm are then written in C programme and implemented using Texas Instrument Tool which consist of TMS320C54x EMV board and Code Composer Studio.


Adaptive Notch Filter For Single And Multiple Narrow-Band Interference, Selina Kuek Lin Mei Jan 2001

Adaptive Notch Filter For Single And Multiple Narrow-Band Interference, Selina Kuek Lin Mei

Theses : Honours

In this project, the adaptive notch filter for single and Multiple narrow-band interference is implemented using simplified LMS algorithm. Performances of the LMS adaptive algorithms is evaluated and analysed through simulation on the computer using Matlab. The algorithm are then written in C programme and implemented using Texas Instrument Tool which consist of TMS320C54x EMV board and Code Composer Studio.


Design And Evaluation Of A Specialized Computer Architecture For Manipulating Binary Decision Diagrams, Robert K. Hatt Jan 2000

Design And Evaluation Of A Specialized Computer Architecture For Manipulating Binary Decision Diagrams, Robert K. Hatt

Dissertations and Theses

Binary Decision Diagrams (BDDs) are an extremely important data structure used in many logic design, synthesis and verification applications. Symbolic problem representations make BDDs a feasible data structure for use on many problems that have discrete representations. Efficient implementations of BOD algorithms on general purpose computers has made manipulating large binary decision diagrams possible. Much research has gone into making BOD algorithms more efficient on general purpose computers. Despite amazing increases in performance and capacity of such computers over the last decade, they may not be the best way to solve large, specialized problems. A computer architecture designed specifically to …


Ultra-Wideband Tem Horns, Transient Arrays And Exponential Curves: A Fdtd Look, Troy S. Utton Mar 1999

Ultra-Wideband Tem Horns, Transient Arrays And Exponential Curves: A Fdtd Look, Troy S. Utton

Theses and Dissertations

This research investigates the possibility of applying exponentially curved conducting plates to single-element Transverse Electromagnetic (TEM) horns and their transient arrays to enhance the UWB characteristics already experienced by these radiators. The first part of this study demonstrates the Finite-Difference Time-Domain (FDTD) method's ability to duplicate experimental data, and establishes the baseline models used throughout the remainder of the research. The baseline models consist of the typical flat-triangle shaped conducting plates. The exponential taper models incorporate the exponential curves in the height, the width, and both the height and width directions. One, two- and four-element baseline configurations are compared to …


Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson Sep 1998

Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson

Theses and Dissertations

Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …


Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki Jun 1998

Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki

Theses and Dissertations

Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications. A mathematical construct called a frame is presented which captures the important time-varying characteristic of speech. Roughly speaking, frames generalize the idea of an orthogonal basis in a Hilbert space, Specific spaces applicable to speech are L2(R) and the Hardy spaces Hp(D) for p> 1 where D is the unit disk in the complex plane. Results are given for representations in the Hardy spaces involving Carleson's inequalities (and its extensions), …


Modified Multiple Model Adaptive Estimation (M3Ae) For Simultaneous Parameter And State Estimation, Mikel M. Miller Mar 1998

Modified Multiple Model Adaptive Estimation (M3Ae) For Simultaneous Parameter And State Estimation, Mikel M. Miller

Theses and Dissertations

In many estimation problems, it is desired to estimate system states and parameters simultaneously. However, inherent to traditional estimation architectures of the past, the designer has had to make a trade-off decision between designs intended for accurate state estimation versus designs concerned with accurate parameter estimation. This research develops one solution to this trade-off decision by proposing a new architecture based on Kalman filtering (KF) and Multiple Model Adaptive Estimation (MMAE) techniques. This new architecture, the Modified-MMAE (M3AE), exploits the benefits of an MMAE designed for accurate parameter estimation, and yet performs at least as well in state …