Digital Commons Network^™

Levee Slide Detection Using Synthetic Aperture Radar Magnitude And Phase, Ramakalavathi Marapareddy

Theses and Dissertations

The objectives of this research are to support the development of state-of-the-art methods using remotely sensed data to detect slides or anomalies in an efficient and cost-effective manner based on the use of SAR technology. Slough or slump slides are slope failures along a levee, which leave areas of the levee vulnerable to seepage and failure during high water events. This work investigates the facility of detecting the slough slides on an earthen levee with different types of polarimetric Synthetic Aperture Radar (polSAR) imagery. The source SAR imagery is fully quad-polarimetric L-band data from the NASA Jet Propulsion Laboratory’s (JPL’s) …

Bm3d Image Denoising Using Learning-Based Adaptive Hard Thresholding, Farhan Bashar

Electronic Thesis and Dissertation Repository

Image denoising is an important pre-processing step in most imaging applications. Block Matching and 3D Filtering (BM3D) is considered to be the current state-of-art algorithm for additive image denoising. But this algorithm uses a fixed hard thresholding scheme to attenuate noise from a 3D block. Experiments show that this fixed hard thresholding deteriorates the performance of BM3D because it does not consider the context of corresponding blocks. In this thesis, we propose a learning based adaptive hard thresholding method to solve this issue. Also, BM3D algorithm requires as an input the value of the noise level in the input image. …

A Generalized Model Of Cognitive Workload, Taylor Carpenter

Theses

Numerous catastrophic accidents have been the result of human operators making poor judgement calls stemming from suboptimal decision making. This suboptimal decision making, in many cases, arises when an operator is either in a high cognitive workload state, overwhelmed with information leading to a greater chance of missing an important detail, or in a low cognitive workload state, distracted and overall not paying attention to the task at hand. If the cognitive workload of an individual can be properly monitored, suboptimal operator conditions can be recognized or prevented, reducing the chance of an accident. While previous research has led to …

Photoacoustic Imaging For Ovarian Cancer Detection: System Development And Classification Algorithm, Hai Li

Doctoral Dissertations

Ovarian cancer is relatively rare but it has the highest mortality with a five-year survival rate of only 30% comparing with other gynecologic cancers. Most of ovarian cancers are diagnosed at late stages because of no efficacious screening techniques. So there is an urgent need to develop new imaging techniques for early stage ovarian cancer detection. Photoacoustic imaging (PAI) inherently combines the merits of optical imaging and ultrasound imaging. In PAI, photoacoustic waves are generated by illuminating tissue samples with a short laser pulse. Photoacoustic waves are then measured by ultrasound transducers to reconstruct optical absorption at ultrasound resolution, which …

Using Machine Learning Techniques For Finding Meaningful Transcripts In Prostate Cancer Progression, Siva Charan Reddy Singi Reddy

Electronic Theses and Dissertations

Prostate Cancer is one of the most common types of cancer among Canadian men. Next generation sequencing that uses RNA-Seq can be valuable in studying cancer, since it provides large amounts of data as a source for information about biomarkers. For these reasons, we have chosen RNA-Seq data for prostate cancer progression in our study. In this research, we propose a new method for finding transcripts that can be used as genomic features. In this regard, we have gathered a very large amount of transcripts. There are a large number of transcripts that are not quite relevant, and we filter …

A Lexical Approach For Classifying Malicious Urls, Michael Darling

Electrical and Computer Engineering ETDs

Given the continuous growth of illicit activities on the Internet, there is a need for intelligent systems to identify malicious web pages. It has been shown that URL anal- ysis is an e\u21b5ective tool for detecting phishing, malware, and other attacks. Previous studies have performed URL classification using a combination of lexical features, network tra c, hosting information, and other strategies. These approaches require time-intensive lookups which introduce significant delay in real-time systems. This paper describes a lightweight approach for classifying malicious web pages using URL lexical analysis alone. The goal is to explore the upper-bound of the classification accuracy …

Automatic Localization Of Epileptic Spikes In Eegs Of Children With Infantile Spasms, Supachan Traitruengsakul

Theses

Infantile Spasms (ISS) characterized by electroencephalogram (EEG) recordings exhibiting hypsarrythmia (HYPS) are a severe form of epilepsy. Many clinicians have been trying to improve ISS outcomes; however, quantification of discharges from hypsarrythmic EEG readings remains challenging.

This thesis describes the development of a novel method that assists clinicians to successfully localize the epileptic discharges associated with ISS in HYPS. The approach includes: construct the time-frequency domain (TFD) of the EEG recording using matching pursuit TFD (MP-TFD), decompose the TFD matrix into two submatrices using nonnegative matrix factorizations (NMF), and employ the decomposed vectors to locate the spikes.

The proposed method …

Event And Intrusion Detection Systems For Cyber-Physical Power Systems, Uttam Adhikari

Theses and Dissertations

High speed data from Wide Area Measurement Systems (WAMS) with Phasor Measurement Units (PMU) enables real and non-real time monitoring and control of power systems. The information and communication infrastructure used in WAMS efficiently transports information but introduces cyber security vulnerabilities. Adversaries may exploit such vulnerabilities to create cyber-attacks against the electric power grid. Control centers need to be updated to be resilient not only to well-known power system contingencies but also to cyber-attacks. Therefore, a combined event and intrusion detection systems (EIDS) is required that can provide precise classification for optimal response. This dissertation describes a WAMS cyber-physical power …

Statistical Shrinkage Methods For Classification, Prediction, And Feature Extraction Using Genomewide Gene Expression Data And Small Sample Sizes, Behrouz Madahian

Electronic Theses and Dissertations

With advent of new technologies, more data is being collected than ever before. Data is pouring in from every conceivable direction: from operational and transactional systems, from Micro array experiments and Genome Wide Association Studies, from inbound and outbound customer contact points, from mobile media and the Web to mention a few. Researchers and investigators in many fields are faced with the problem of identifying important effects among thousands of variables in high dimensional data sets. This process often results in non or weekly identified effects. Nowadays a common problem when processing data sets with large number of variables compared …

Design And Implementation Of A Pivot Shift Prototype For Quantitative Analysis, Marco Antonio Espinoza Sanchez

Electrical and Computer Engineering ETDs

This thesis presents the utilization of a portable medical device intended to help in the diagnosis of the Anterior Cruciate Ligament(ACL) knee injury. The prototype consists of an embedded system integrated with various sensors including accelerometers and gyroscopes to provide force, orientation, and acceleration measurement. The prototype has been used to quantify the results of a medical test called pivot shift which tests the dynamic stability of the patients knee. With the initial prototype built, limited clinical trials were conducted. Two schemes (metric based classification and k nearest neighbors) have been applied to the data set to empirically learn and …

Sudden Cardiac Arrest Prediction Through Heart Rate Variability Analysis, Luke Joseph Plewa

Master's Theses

The increase in popularity for wearable technologies (see: Apple Watch and Microsoft Band) has opened the door for an Internet of Things solution to healthcare. One of the most prevalent healthcare problems today is the poor survival rate of out-of hospital sudden cardiac arrests (9.5% on 360,000 cases in the USA in 2013). It has been proven that heart rate derived features can give an early indicator of sudden cardiac arrest, and that providing an early warning has the potential to save many lives. Many of these new wearable devices are capable of providing this warning through their heart rate …

The Mako Language: Vitality, Grammar And Classification, Jorge E. Rosés Labrada

Electronic Thesis and Dissertation Repository

This dissertation focuses on the documentation and description of Mako, an indigenous language spoken in the Venezuelan Amazon by about 1000 people and for which the only available published material at the start of the project were 38 words. The main goals of the project were to create a collection of annotated ethnographic texts and a grammar that could serve as a starting point for both language maintenance in the community and for further linguistic research. Additionally, the project sought to assess the language’s vitality in the communities where it is spoken and to understand the relationship of Mako to …

Biodynamic Parameters During A Step Down Task In Subjects With Chronic Or Recurrent Low Back Pain Classified With Lumbar Instability, Kim M. Poulsen

Seton Hall University Dissertations and Theses (ETDs)

Background: Low back pain (LBP) affect a majority of the population. Lumbar instability has been identified as a factor in a significant portion of individuals with LBP but movement characteristics of this population has seen limited research regarding functional tasks. Objective: This study examined biodynamic parameters during a step task. Design: Quasi-experimental with 2 factors, group and side (L/R), and 1 repeated measure (stepping). Statistics: Two-way Mixed-Design Repeated Measures ANOVA with Alpha = .05. Movement task: Subjects with LBP and lumbar spine clinical instability classification (N=11) and control subjects (N=11) performed a step down task from a 9.5 inch …

The "Isolated Find" Concept And Its Consequences In Public Archaeology, Jesse Morton

Theses and Dissertations

The term “isolated find” has frequently been taken as a disposable artifact category in cultural resource management (CRM). Efforts were made to empirically demonstrate the fallacy of this concept and its use, using modified field sampling strategies, the inclusion of fine screen artifact analysis, and statistical analyses. Six sites containing prehistoric occupations on Camp McCain National Guard base in Grenada County, Mississippi were reinvestigated using these methods; their datasets were expanded in terms of site size, density, function, and temporal association, which may change their eligibility status for the National Register of Historic Places (NRHP). Fieldwork and classification based solutions …

Classification And Multiple Hypothesis Testing In Microarray And Rna-Seq Experiments, Patrick B. Harrington

Doctoral Dissertations

This thesis focuses on analyzing the type of data returned by two pieces of technology, the older and less expensive microarray, or the next generation sequencing data, RNA-Seq. Both devices return data that is extremely large in volume. Microarray analysis begins by finding genes of interest, which are called differentially expressed (DE). Genes are called DE controlling for some criteria, such as false discovery rate (FDR), and then clustered into groups. A method unifying these two steps was suggested, using a mixture of normal distributions with the appropriate EM algorithm. We compare this to a semi-parametric alternative to the unified …

New Approaches For Data-Mining And Classification Of Mental Disorder In Brain Imaging Data, Mustafa Sinan Cetin

Computer Science ETDs

Brain imaging data are incredibly complex and new information is being learned as approaches to mine these data are developed. In addition to studying the healthy brain, new approaches for using this information to provide information about complex mental illness such as schizophrenia are needed. Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) are two well-known neuroimaging approaches that provide complementary information, both of which provide a huge amount of data that are not easily modelled. Currently, diagnosis of mental disorders is based on a patients self-reported experiences and observed behavior over the longitudinal course of the illness. There is …

Gender As An 'Interplay Of Rules': Detecting Epistemic Interplay Of Medical And Legal Discourse With Sex And Gender Classification In Four Editions Of The Dewey Decimal Classification, Melodie J. Fox

Theses and Dissertations

When groups of people are represented in classification systems, potential exists for them to be structurally or linguistically subordinated, erased or otherwise misrepresented (Olson & Schlegl, 2001). As Bowker & Star (1999) have shown, the real-world application of classification to people can have legal, economic, medical, social, and educational consequences. The purpose of this research is to contribute to knowledge organization by showing how the epistemological stance underlying specific classificatory discourses interactively participates in the formation of concepts. The medical and legal discourses in three timeframes are examined using Foucauldian genealogical discourse analysis to investigate how their depictions of gender …

Classification Of Five-Dimensional Lie Algebras With One-Dimensional Subalgebras Acting As Subalgebras Of The Lorentz Algebra, Jordan Rozum

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Motivated by A. Z. Petrov's classification of four-dimensional Lorentzian metrics, we provide an algebraic classification of the isometry-isotropy pairs of four-dimensional pseudo-Riemannian metrics admitting local slices with five-dimensional isometries contained in the Lorentz algebra. A purely Lie algebraic approach is applied with emphasis on the use of Lie theoretic invariants to distinguish invariant algebra-subalgebra pairs. This method yields an algorithm for identifying isometry-isotropy pairs subject to the aforementioned constraints.

Distribution Of Abc Transporter Genes Across The Plant Kingdom, Thomas Scott Lane

Masters Theses

The ATP-binding cassette (ABC) transporter gene superfamily is ubiquitous among extant organisms. ABC transporters act to transport compounds across cellular membranes and are involved in a diverse range of biological processes and functions including cancer resistance in humans, drug resistance among vertebrates, and herbicide resistance in weeds. This superfamily of genes appears to be larger and more diverse in the plant kingdom—yet, we know relatively less about ABC transporter function in plants compared with mammals and bacteria. Therefore, we undertook a plant kingdom-wide transcriptomic survey of ABC transporters to better understand their diversity.

We utilized sequence similarity-based informatics techniques to …

Accuracy Of Supervised Classification Of Cropland In Sub–Saharan Africa, Sarah Lynn Lewis-Gonzales

Masters Theses

Mali is a country in sub–Saharan Africa where monitoring of cropped land area would greatly benefit food security initiatives and aid organizations. More importantly village–scale studies on cropped land are fundamental to making a difference in the way we look at cropped land area and food availability in this region of the world. Using Landsat surface reflectance imagery and World View–2 derived labeled data, this study focuses on accuracy of supervised classification methods while addressing various levels of scale. Several classification methods are taken into account to determine the best method possible to produce cropped area estimates using this data. …

Immunology Inspired Detection Of Data Theft From Autonomous Network Activity, Theodore O. Cochran

CCE Theses and Dissertations

The threat of data theft posed by self-propagating, remotely controlled bot malware is increasing. Cyber criminals are motivated to steal sensitive data, such as user names, passwords, account numbers, and credit card numbers, because these items can be parlayed into cash. For anonymity and economy of scale, bot networks have become the cyber criminal’s weapon of choice. In 2010 a single botnet included over one million compromised host computers, and one of the largest botnets in 2011 was specifically designed to harvest financial data from its victims. Unfortunately, current intrusion detection methods are unable to effectively detect data extraction techniques …

Using Instance-Level Meta-Information To Facilitate A More Principled Approach To Machine Learning, Michael Reed Smith

Theses and Dissertations

As the capability for capturing and storing data increases and becomes more ubiquitous, an increasing number of organizations are looking to use machine learning techniques as a means of understanding and leveraging their data. However, the success of applying machine learning techniques depends on which learning algorithm is selected, the hyperparameters that are provided to the selected learning algorithm, and the data that is supplied to the learning algorithm. Even among machine learning experts, selecting an appropriate learning algorithm, setting its associated hyperparameters, and preprocessing the data can be a challenging task and is generally left to the expertise of …

Towards Closed-Loop Deep Brain Stimulation: Behavior Recognition From Human Stn, Soroush Niketeghad

Electronic Theses and Dissertations

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson’s disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient’s behavior. Thus behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the …

Identification Of Geostationary Satellites Using Polarization Data From Unresolved Images, Andy Speicher

Electronic Theses and Dissertations

In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. Since resolved images of geosynchronous satellites are not technically feasible with current technology, another method of distinguishing space objects was explored that exploits the polarization signature from unresolved images.

The objective of this study was to collect and analyze visible-spectrum polarization data from unresolved …

Lived Experiences Of Attorneys Who Represent Transgender Clients In Prison Placement, Heidi Jo Green

Walden Dissertations and Doctoral Studies

Researchers have indicated that there are no formal guidelines for placing convicted transgender felons in the United States in correctional facilities and addressing their post-placement medical care and treatment. The problem is that inappropriate placement may lead to the discrimination of transgender offenders; it may also put them in situations that threaten their safety. Attorneys are legal advocates assigned to defend and protect the rights of their clients during the trial and sentencing phase when correctional placement is determined. The purpose of this hermeneutic, phenomenological study was to explore the lived experiences of attorneys who represent transgender clients during the …

Feature Selection And Classification Methods For Decision Making: A Comparative Analysis, Osiris Villacampa

CCE Theses and Dissertations

The use of data mining methods in corporate decision making has been increasing in the past decades. Its popularity can be attributed to better utilizing data mining algorithms, increased performance in computers, and results which can be measured and applied for decision making. The effective use of data mining methods to analyze various types of data has shown great advantages in various application domains. While some data sets need little preparation to be mined, whereas others, in particular high-dimensional data sets, need to be preprocessed in order to be mined due to the complexity and inefficiency in mining high dimensional …

Vehicle Tracking And Classification Via 3d Geometries For Intelligent Transportation Systems, William Mcdowell

Electronic Theses and Dissertations

In this dissertation, we present generalized techniques which allow for the tracking and classification of vehicles by tracking various Point(s) of Interest (PoI) on a vehicle. Tracking the various PoI allows for the composition of those points into 3D geometries which are unique to a given vehicle type. We demonstrate this technique using passive, simulated image based sensor measurements and three separate inertial track formulations. We demonstrate the capability to classify the 3D geometries in multiple transform domains (PCA & LDA) using Minimum Euclidean Distance, Maximum Likelihood and Artificial Neural Networks. Additionally, we demonstrate the ability to fuse separate classifiers …

Novel Classification Of Slow Movement Objects In Urban Traffic Environments Using Wideband Pulse Doppler Radar, Berta Rodriguez Hervas

Open Access Theses & Dissertations

Every year thousands of people are involved in traffic accidents, some of which are fatal. An important percentage of these fatalities are caused by human error, which could be prevented by increasing the awareness of drivers and the autonomy of vehicles. Since driver assistance systems have the potential to positively impact tens of millions of people, the purpose of this research is to study the micro-Doppler characteristics of vulnerable urban traffic components, i.e. pedestrians and bicyclists, based on information obtained from radar backscatter, and to develop a classification technique that allows automatic target recognition with a vehicle integrated system. For …

Contrast Pattern Aided Regression And Classification, Vahid Taslimitehrani

Browse all Theses and Dissertations

Regression and classification techniques play an essential role in many data mining tasks and have broad applications. However, most of the state-of-the-art regression and classification techniques are often unable to adequately model the interactions among predictor variables in highly heterogeneous datasets. New techniques that can effectively model such complex and heterogeneous structures are needed to significantly improve prediction accuracy. In this dissertation, we propose a novel type of accurate and interpretable regression and classification models, named as Pattern Aided Regression (PXR) and Pattern Aided Classification (PXC) respectively. Both PXR and PXC rely on identifying regions in the data space where …

Intelligent Network Intrusion Detection Using An Evolutionary Computation Approach, Samaneh Rastegari

Theses: Doctorates and Masters

With the enormous growth of users' reliance on the Internet, the need for secure and reliable computer networks also increases. Availability of effective automatic tools for carrying out different types of network attacks raises the need for effective intrusion detection systems.

Generally, a comprehensive defence mechanism consists of three phases, namely, preparation, detection and reaction. In the preparation phase, network administrators aim to find and fix security vulnerabilities (e.g., insecure protocol and vulnerable computer systems or firewalls), that can be exploited to launch attacks. Although the preparation phase increases the level of security in a network, this will never completely …