Digital Commons Network^™

Can Machine Learning Beat Physics At Modeling Car Crashes?, Gavin Byrne

Dissertations

This study aimed to look at a traditional method used for measuring the severity and principle direction of force of a car crash and see if it could be improved on using machine learning models. The data used was publicly available from the NHTSA database and included descriptions of the vehicle, test and sensors as well as the accelerometer data over the period of the crashes. The models built were SVM classifiers and multinomial regression models. Although the SVM and Regression models were built successfully and gave higher levels of accuracy than the momentum models in terms of the severity, …

Comparing The Effectiveness Of Support Vector Machines And Convolutional Neural Networks For Determining User Intent In Conversational Agents, Kieran O Sullivan

Dissertations

Over the last fifty years, conversational agent systems have evolved in their ability to understand natural language input. In recent years Natural Language Processing (NLP) and Machine Learning (ML) have allowed computer systems to make great strides in the area of natural language understanding. However, little research has been carried out in these areas within the context of conversational systems. This paper identifies Convolutional Neural Network (CNN) and Support Vector Machine (SVM) as the two ML algorithms with the best record of performance in ex isting NLP literature, with CNN indicated as generating the better results of the two. A …

Using Machine Learning Techniques To Predict A Risk Score For New Members Of A Chit Fund Group, Sinead Aherne

Dissertations

Predicting the risk score of new and potential customers is used across the financial industry. By implementing the prediction of risk scores for their customers a chit fund company can improve the knowledge and customer understanding without relying on human knowledge. Data is collected on each customer before they have taken out credit and during the time they contribute to a chit fund. Having collected the necessary data, the company can then decide whether modelling customer risk would benefit them. As the data is available historically, one aspect of risk score prediction will be the focus of this thesis, supervised …

Through The Net: Investigating How User Characteristics Influence Susceptibility To Phishing, Charlie Marriott

Dissertations

In the past 25 years, the internet has grown and evolved from a niche networking technology, used almost exclusively by researchers and enthusiasts, into the driving force of modern economies. Fraud has evolved too, with rates of cybercrime on the increase as criminals become increasingly sophisticated in using technology to deceive their victims. The world is an online place, and data is the new oil. Phishing is a form of social engineering that is not that different from traditional fraud. Phishing attackers try to trick their victims into revealing valuable private information, usually for financial gain, by posing as a …

Automation Of Authorisation Vulnerability Detection In Authenticated Web Applications, Niall Caffrey

Dissertations

In the beginning the World Wide Web, also known as the Internet, consisted mainly of websites. These were essentially information depositories containing static pages, with the flow of information mostly one directional, from the server to the user’s browser. Most of these websites didn’t authenticate users, instead, each user was treated the same, and presented with the same information. A malicious party that gained access to the web server hosting these websites would usually not gain access to confidential information as most of the information on the web server would already be accessible to the public. Instead, the malicious party …

Assesing Completeness Of Solvency And Financial Condition Reports Through The Use Of Machine Learning And Text Classification, Ruairí Nugent

Dissertations

Text mining is a method for extracting useful information from unstructured data through the identification and exploration of large amounts of text. It is a valuable support tool for organisations. It enables a greater understanding and identification of relevant business insights from text. Critically it identifies connections between information within texts that would otherwise go unnoticed. Its application is prevalent in areas such as marketing and political science however, until recently it has been largely overlooked within economics. Central banks are beginning to investigate the benefits of machine learning, sentiment analysis and natural language processing in light of the large …

Augmented Reality As A Potential Tool For Filmmaking, Paul Blachfield

Dissertations

Augmented Reality (AR) has been used for a wide variety of industries. The purpose of this study was to determine the suitability of this technology for use in filmmaking. One of the problems on a film set is the time taken to block a scene. Blocking involves the placement of subjects and props within a scene. Different ideas have been used for blocking including previzualisation and Virtual Reality (VR). This study proposesed the use of AR as a tool to solve this problem. Marker-based and Markerless AR were assessed in turn to determine their suitability for addressing the problem. The …

An Exploration Of Parliamentary Speeches In The Irish Parliament Using Topic Modeling, Fiona Leheny

Dissertations

The only resource available in the public domain which highlights parliamentary ac tivity is parliamentary questions. Up until the last ten years, manual content analysis was carried out to classify these. More recently, machine learning techniques have been used to automatically classify and analyse these data sets. This study analyses the verbal parliamentary speeches in the Irish Parliament (known as the D´ail) over a ten year period using unsupervised machine learning. It does so by applying a less utilised topic modeling technique, known as Non-negative Matrix Factorisation (NMF), to de tect the latent themes in these speeches. A two-layer dynamic …

Intergrating The Fruin Los Into The Multi-Objective Ant Colony System, Tirdad Kiafar

Dissertations

Building evacuation simulation provides the planners and designers an opportunity to analyse the designs and plan a precise, scenario specific instruction for disaster times. Nevertheless, when disaster strikes, the unexpected may happen and many egress paths may get blocked or the conditions of evacuees may not let the execution of emergency plans go smoothly. During disaster times, effective route-finding methods can help efficient evacuation process, in which the directors are able to react to the sudden changes in the environment. This research tries to integrate the highly accepted human dynamics methods proposed by Fruin into the Ant-Colony optimisation route-finding method. …

Identifying And Scoping Context-Specific Use Cases For Blockchain-Enabled Systems In The Wild., Fiona Delaney

Dissertations

Advances in technology often provide a catalyst for digital innovation. Arising from the global banking crisis at the end of the first decade of the 21st Century, decentralised and distributed systems have seen a surge in growth and interest. Blockchain technology, the foundation of the decentralised virtual currency Bitcoin, is one such catalyst. The main component of a blockchain, is its public record of verified, timestamped transactions maintained in an append-only, chain-like, data structure. This record is replicated across n-nodes in a network of co-operating participants. This distribution offers a public proof of transactions verified in the past. Beyond tokens …

Supervised Learning Models To Predict Stock Direction Within Different Sectors In A Bull And Bear Market, Tiffany Razy

Dissertations

Forecasting stock market price movement is a well researched and an alluring topic within the machine learning and financial realm. Supervised machine learning algorithms such as Random Forest (RF) and Support Vector Machines (SVM) have been used independently to gain insight on the market. With such volatility in the market the scope of this study will utilized the RF and SVM in a very volatility market to determine if these models will perform at a high level or outperform each other in both markets. This relative study is performed on 16 stocks in 4 different sectors over the bear market …

Handwritten Digit Recognition And Classification Using Machine Learning, Ke Zhao

Dissertations

In this paper, multiple learning techniques based on Optical character recognition (OCR) for the handwritten digit recognition are examined, and a new accuracy level for recognition of the MNIST dataset is reported. The proposed framework involves three primary parts, image pre-processing, feature extraction and classification. This study strives to improve the recognition accuracy by more than 99% in handwritten digit recognition. As will be seen, pre-processing and feature extraction play crucial roles in this experiment to reach the highest accuracy.

Improved Understanding Of Lightning Characteristics Relative To Radar And Altitude Profiles, Retha Matthee Mecikalski

Dissertations

Cloud electrification leads to the production of nitrogen oxides (NOx), which have an effect on ozone concentrations. Currently uncertainties exist regarding the contribution of lightning to the global and local NOx budget. Most lightning NOx (LNOx) models distribute the LNOx at reflectivities ≥20 dBZ, while vertically, a Gaussian distribution function with a peak at 7–8 km above mean sea level (MSL, -15°C) is used for parameterized cloud-to-ground (CG) flashes and a bimodal distribution function with peaks at 7–8 km (-15°C) and 11–12 km MSL (-45°C) is used for parameterized inter-/intra-cloud (IC) flashes. This research therefore aims to improve our basic …

Machine Learning Of Cyberattack And Defense Strategies, John Andrew Bland

Dissertations

Cybersecurity is an increasingly important challenge for computer systems. In this work, cyberattacks were modeled using an extension of the well-known Petri net formalism. That formalism, designated Petri nets with players, strategies, and costs, models the states of the cyberattack and events during the attack as markings and transition firings in the net respectively. The formalism models the attacker and defender as competing players who may observe the marking of a subset of the net and based on the observed marking act by changing the stochastic firing rates of a subset of the transitions in order to achieve their competing …

Monocular Camera Scene Reconstruction Using Oriented Feature Constellations, Benjamin J. Schmid

Dissertations

This dissertation details a novel class of descriptors called Oriented Feature Constellations (OFC). This new class of descriptors is used to relocate, or match, features in image sequences taken from a monocular camera. It produces faster and more precise results than a highly cited comparison method. Faster, when both are configured to produce the same number of points and more precise, by producing more correct matches when all other variables are held constant. This result directly corresponds to an increase in the precision of the 3D point clouds that can be reconstructed from an image sequence. This dissertation also provides …

Investigation Into The Predictive Power Of Artificial Neural Networks And Logistic Regression For Predicting Default In Chit Funds, Ciara Kerrigan

Dissertations

This study evaluated the performance of an artificial neural network (ANN) multi-layer perceptron model and a logistic regression logitboost (LR) model to predict default in chit funds. The two types of default investigated were late payment of 30 days and late payment of 90 days. The dataset was broken up into training and validation datasets using random sampling and K folds cross validation was used on the training dataset to assess performance of the tuning parameters. The validation dataset was used to compare performance of both algorithms. Principle component analysis (PCA) was used to reduce the feature set while still …

Exploring The Features To Classify The Musical Period Of Western Classical Music, Arturo Martínez Gallardo

Dissertations

Music Information Retrieval (MIR) focuses on extracting meaningful information from music content. MIR is a growing field of research with many applications such as music recommendation systems, fingerprinting, query-by-humming or music genre classification. This study aims to classify the styles of Western classical music, as this has not been explored to a great extent by MIR. In particular, this research will evaluate the impact of different music characteristics on identifying the musical period of Baroque, Classical, Romantic and Modern. In order to easily extract features related to music theory, symbolic representation or music scores were used, instead of audio format. …

Barriers And Perceptions To Obtaining Palliative Care In The Emergency Department, Jacqueline Lucille Saucier

Dissertations

Background:

Purpose: This study explored barriers and perceptions of providing palliative care services while patients are in the emergency department (ED) in order to increase the>likelihood of caregivers to elicit palliative care methodologies for patients with chronic illness, who are not necessarily at the end of life, but rather who are identified through repeated visits to the ED.

Design and Methods: A mixed methods approach was used to explore the barriers and perceptions of providing palliative care services in the ED. By using a qualitative approach, evidenced by grounded theory, this study explored the barriers and perceptions of providing …

Parents' Satisfaction In Non-Title-I And Title-I Schools Within The Archdiocese Of Chicago, Alex Hill

Dissertations

Parents' attitudes about their children's schools matter. Their views can shape their children's attitude about school and influence their residential and school enrollment decisions. This paper describes the use of two survey scales, an existing survey, Stakeholder Satisfaction Survey and a survey developed by the research, Parent Survey, to assess parents' level of satisfaction at their child's school. Specifically, one Catholic school that has students who are recipients of Title-I funds and one Catholic school that does not have students who are recipients of Title-I funds were used in this study. The Stakeholder Satisfaction Survey is a Likert scale used …

Undoing Giftedness: Considering Adolescent Latina Identity Performativity In United States Public Schools, Jenna Nelson

Dissertations

This dissertation employs a series of literary genres to navigate the reader through the importance of complicating normalized notions of giftedness and Latina identity as well as the interrogating the complexity of subjectivities. Using post qualitative inquiry (St. Pierre, 2014), I blend writing practices typically used in fiction and in theoretical inquiry. Fiction writing such as narratives, scriptwriting, poetry, visual-art, journaling, and poetry are implemented to analyze and represent the individuals in this inquiry. This dissertation consists of three Acts and an Intermission to carry the reader through the various stages of my inquiry. Through writing the dissertation in this …

Dynamic Wavefront Capability For Anti-Jam Electronics And Controlled Reception Pattern Antenna, Gregory Reynolds

Dissertations

The need to test and evaluate adaptive nulling technology for Global Navigation Satellite System (GNSS) receivers is increasing commensurately with the demand for additional protection against GNSS interference. Because the cost and time associated with approval to conduct optimum outdoor testing is often prohibitive and safety of flight concerns arise during integration testing as well, affordable and accurate means of simulated testing are desired. This dissertation investigates the theory and implementation of Radio Frequency (RF) wavefront simulation that eliminates expensive RF front-end electronics, as well as other active components that limit dynamic range, add exogenous noise, and restrict maximum power …

Global Stability And Traveling Wave Solutions For A Two-Competing-Prey And One-Predator Lotka-Volterra Model, Cuiping Wang

Dissertations

This dissertation consists of four chapters. In Chapter 1, I give an introduction of background, models to be investigated, and main goal of this dissertation. In Chapter 2, I study the space homogeneous model. The existence and local stability analysis of nonnegative equilibrium points in three cases, as well as the sufficient and necessary conditions for the existence of the positive interior equilibrium point are geiven in Section2.1. In Section 2.2, I perform a careful analysis to show the global stability of the boundary equilibrium point at which two prey coexist with extinction of predator for case 1. In Section …

Some Problems On Graph Colorings, Brett Skinner

Dissertations

Let G be a simple graph. The open neighborhood of a vertex v in G is the set of vertices adjacent to v, denoted as N(v), and the degree of v, denoted as deg(v), is the size of N(v). The maximum degree of a graph, ∆ = ∆(G), is the maximum deg(v) among all vertices in G. The closed neighborhood, N[v], is the set N(v)∪{v}. A proper vertex coloring is an assignment of colors to the vertices of G such that no two adjacent vertices receive the same color. The minimum number of colors required to properly color G is …

Digital Literacy In Early Elementary School: Barriers And Support Systems In The Era Of The Common Core, Delnaz Hosseini

Dissertations

This study examines teachers’ perceptions about digital literacy instruction in early elementary school grades (e.g., Kindergarten through grade 2) so as to identify existing obstacles to digital literacy instruction as well as support systems necessary to enhance instruction. Participants (n = 37) included Kindergarten, first, and second grade teachers from both Title I and non-Title I schools. Data was collected through an online survey with primarily closed-ended questions. Correlations and relationships amongst and across survey questions were analyzed. Analysis revealed that early elementary grade students in this school district are provided with more opportunities to practice computer literacy than …

Effective Leadership For The Implementation Of The Common Core State Standards: Principal Behaviors That Develop Professional Capital To Create Conditions For Positve Change, Eileen Beth Brett

Dissertations

Identifying specific leadership behaviors of elementary school principals that create conditions for positive change is critical to implementing educational reform. The purpose of this research is to identify specific leadership behaviors of principals that have positively impacted the implementation of the Common Core State Standards through the development of professional capital.

The Common Core Standards represent a recent movement to create national standards, founded on the belief that schools have an obligation to ensure that all students are college and career ready (McLaughlin & Overturf, 2012; Conley; 2014a). Implementing the Common Core has challenged principals to develop leadership skills to …

Structural And Chemical Consequences Of High Oxygen Coverages On Rh(111), Rachael Gabrielle Farber

Dissertations

Partial oxidations of small molecules over metal surfaces are central to many heterogeneously catalyzed reactions. However, the identity of the actual surface species that promote or hinder these reactions has remained elusive for a variety of reasons. Recently, the understanding of the role of surface oxides in catalytic activity has changed. Instead of being thought of as poisons, they are now believed to be effective promoters of selective catalysis.

Rhodium (Rh) effectively promotes oxidation reactions and is a benchmark system for models of heterogeneously catalyzed chemistry. For this reason, Rh(111) was chosen as the model system for this dissertation work. …

The Enzymatic Activity And Inhibition Of Dape Encoded N-Succinyl-L,L-Diaminopimelic Acid Dessucinylase, Tahirah Heath

Dissertations

The bacterial enzyme DapE is a hydrolase in the late stage of the mDAP/lysine biosynthetic pathway that catalyzes the hydrolysis of N-succinyl-L,L-diaminopimelic acid (L,L-SDAP) to succinic acid and L,L-diaminopimelate (DAP). The product DAP is ultimately converted to m-DAP and then to lysine which is used in the construction of proteins, whereas for humans, lysine is an essential amino acid obtained through diet. DapE has been shown to be conserved across many strains of bacteria. The m-DAP produced through the succinylase pathway is used by both gram negative and gram-positive bacteria in the construction of the essential peptidoglycan cell wall. Because …

Universal Design For Learning: An Examination Of Leadership Promoting Student Learning For All, Martha Ryan-Toye

Dissertations

Martha Ryan-Toye

Loyola University Chicago

UNIVERSAL DESIGN FOR LEARNING: AN EXAMINATION OF LEADERSHIP PROMOTING STUDENT LEARNING FOR ALL

This study examines the intersection of leadership, Universal Design for Learning and a framework for continuous improvement. Universal Design for Learning is a tool that unites beliefs and actions to address the needs of all children in our educational systems. We fall short in our efforts to close the learning gaps for children with disabilities, children of lower income and children of differing racial and ethnic backgrounds. Universal Design for Learning demonstrates a commitment to proactively addressing the variability of learners so …

The Molecular Pathophysiology Of Sepsis-Associated Disseminated Intravascular Coagulation And Its Pharmacologic Modulation, Amanda Temple Walborn

Dissertations

Sepsis is a life-threatening syndrome characterized by a dysregulated host response to infection. Sepsis patients are at risk of disseminated intravascular coagulation (DIC), a severe blood coagulation disorder. In DIC, inappropriate coagulation leads to the deposition of fibrin in the microvasculature and subsequent organ failure. This consumes platelets and coagulation factors, leaving patients at risk of severe or fatal bleeding. No treatments are approved for DIC in the United States.

In order to test the hypothesis that DIC would be best described by a combination of biomarkers representative of multiple physiological processes, an array of biomarkers, representative of hemostasis, inflammation, …

Principles Of Surface Chemistry Central To The Reactivity Of Organic Semiconductor Materials, Gregory J. Deye

Dissertations

Organic thin-films are rapidly becoming implemented as semiconducting materials in electronic devices and as a result, surface reactivity plays an increasingly important role in the improvement of semiconducting properties. My dissertation addresses how organic thin-films react with gaseous molecules. Previous reports of chemical reactions on organic surfaces claim, “phase rebuilding reaction mechanisms,” whereby reactions only proceed if chemisorbed adsorbate molecules are able to traverse through voids in the molecular lattice. The over-assumptions of this model and lack of correlation to reaction temperature make understanding of organic substrate reactivity incomplete. In contrast, I argue applied heat causes deformation of the molecular …