Physical Sciences and Mathematics Commons^™

Clicking Into Mortgage Arrears: A Study Into Arrears Prediction With Clickstream Data, Gavin O'Brien

Dissertations

This research project investigates the predictive capability of clickstream data when used for the purpose of mortgage arrears prediction. With an ever growing number of people switching to digital channels to handle their daily banking requirements, there is a wealth of ever increasing online usage data, otherwise known as clickstream data. If leveraged correctly, this clickstream data can be a powerful data source for organisations as it provides detailed information about how their customers are interacting with their digital channels. Much of the current literature associated with clickstream data relates to organisations employing it within their customer relationship management mechanisms …

A Performance Comparison Of Neural Network And Svm Classifiers Using Eeg Spectral Features To Predict Epileptic Seizures, Ian Thomas Tennant Watson

Dissertations

Epilepsy is one of the most common neurological disorders, and afflicts approximately 70 million people globally. 30-40% of patients have refractory epilepsy, where seizures cannot be controlled by anti-epileptic medication, and surgery is neither appropriate, nor available. The unpredictable nature of epileptic seizures is the primary cause of mortality among patients, and leads to significant psychosocial disability. If seizures could be predicted in advance, automatic seizure warning systems could transform the lives of millions of people. This study presents a performance comparison of artificial neural network and sup port vector machine classifiers, using EEG spectral features to predict the onset …

Classification Using Association Rules, Colin Kane

Dissertations

This research investigates the use of an unsupervised learning technique, association rules, to make class predictions. The use of association rules to make class predictions is a growing area of focus within data mining research. The research to date has focused predominately on balanced datasets or synthetized imbalanced datasets. There have been concerns raised that the algorithms using association rules to make classifications do not perform well on imbalanced datasets. This research comprehensively evaluates the accuracy of a number of association rule classifiers in predicting home loan sales in an Irish retail banking context. The experiments designed test three associative …

Automatic Table Extension With Open Data, Benedikt Kleppmann

Dissertations

With thousands of data sources available on the web as well as within organisations, data scientists increasingly spend more time searching for data than analysing it. To ease the task of find and integrating relevant data for data mining projects, this dissertation presents two new methods for automatic table extension. Automatic table extension systems take over the task of tata discovery and data integration by adding new columns with new information (new attributes) to any table. The data values in the new columns are extracted from a given corpus of tables.

An Analysis Of Software Testing Practices On Migrations From On Premise To Cloud Hosted Environments, Ronan Mullen

Dissertations

This research project examines the differences between software testing practices that are carried out on software that is installed locally (i.e. on premise) versus software that has migrated to a cloud hosted environment. In conjunction with this, focus was placed on determining what methodologies and frameworks are in existence for assisting with software migrations to the cloud. The reason for carrying out this research project was that the transition to cloud computing is becoming more and more mainstream, as a result organisations are required to focus their efforts on how best to move their software to the cloud while ensuring …

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 …

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.

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. …

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 …

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 …

Predicting Happiness - Comparison Of Supervised Machine Learning Techniques Performance On A Multiclass Classification Problem, Dorota Nieciecka

Dissertations

In the modern world, especially in contemporary economies and politics, a population's subjective well-being is a frequent subject of the public debate. As comparisons of happiness levels in different countries are published, different circumstances and their effect on the value of the subjective well-being reported by people are also analysed. However, a significant amount of the research related to subjective well-being and its determinants is still based upon survey answers and employing conventional statistical methods providing details regarding correlations and causality between different factors and subjective well-being. Application of Supervised Machine Learning techniques for prediction of subjective well-being may provide …

A Demographic Analysis To Determine User Vulnerability Among Several Categories Of Phishing Attacks., Robert Griffin

Dissertations

Phishing attacks have been on a meteoric rise in the last number of years, with 2016 seeing a 65% increase. The attacks range from targeting individuals with personalised messages to spam attacks from bot accounts. With the chances of being targeted by a phishing attack increasing, it is important to identify who is most at risk in order to help alleviate this threat. The aim of this study is to examine members from several demographics and their vulnerability to three types of phishing using data collected from a survey (n = 198). The survey tested the participant’s ability to recognise …

An Investigation Into Factors Which Explain The Scores And Voting Patterns Of The Eurovision Song Contest., Oisín Leonard

Dissertations

The Eurovision Song Contest (ESC) is an annual international television song competition. Participating countries send a group or individual artist to perform an original song at the competition. The winner is decided by all participating countries using a voting system that incorporates both a public televote and an expert jury vote. Countries are excluded from voting for their entry and the country with the highest score wins. A high scoring performance and the voting patterns of the ESC can be explained by a complex set of factors. These factors can be divided into three groups; performance factors, competition factors and …

Image Classification Using Bag-Of-Visual-Words Model, Kaiqiang Huang

Dissertations

Recently, with the explosive growth of digital technologies, there has been a rapid proliferation of the size of image collection. The technique of supervised image clas sification has been widely applied in many domains in order to organize, search, and retrieve images. However, the traditional feature extraction approaches yield the poor classification accuracy. Therefore, the Bag-of-visual-words model, inspired by Bag-of Words model in document classification, was used to present images with the local descriptors for image classification, and also it performs well in some fields. This research provides the empirical evidence to prove that the BoVW model outperforms the traditional …

A Javascript Framework Comparison Based On Benchmarking Software Metrics And Environment Configuration, Jefferson Ferreira

Dissertations

JavaScript is a client-side programming language that can be used in multi-platform applications. It controls HTML and CSS to manipulate page behaviours and is widely used in most websites over the internet. JavaScript frameworks are structures made to help web developers build web applications faster by offering features that enhance the user interaction with the web page. An increasing number of JavaScript frameworks have been released in recent years in the market to help front-end developers build applications in a shorter space of time. Decision makers in software companies have been struggling to determine which frameworks are best suited for …

That Seems Made Up: Deep Learning Classifiers For Fiction & Non Fiction Book Reviews, Clement Manger

Dissertations

The thesis aims to take the first step towards automated extraction of the information found in book reviews, by using machine learning tools to assign a label of fiction or non fiction to the text. The thesis makes use of neural networks and performs experiments around architecture, hyper-parameters and text processing from which an optimized model is produced. The thesis enjoys certain successes; it was possible to match the state of the art achieved by (Kim, 2014) and computation was sped up considerably from the default to the optimized model by 13.8 seconds per 50 steps. Further it is confirmed …

Surface Modification For The Improvement Of Metal/Organic Semiconductor Interfaces, Jonathan Paul Hopwood

Dissertations

Organic electronics have become much of the forefront of scientific research due to their advantages over tradition electronics as well as their applications in consumer devices, medical devices, and harnessing renewable sources of energy. Despite their appeal, two major obstacles are responsible for poor performance and limited applications. These problems occur at the interface between the two main components of the devices, the organic semiconductor and the metal electrodes. The first, high electrical resistance, is a result of the misalignment between the metal’s free electrons and the organic semiconductor’s conduction band. We seek to capitalize on this misalignment using light-responsive …

Biophysical Studies Of Guanine Nucleotide-Binding Alpha Subunits, Brian Leverson

Dissertations

Guanine nucleotide-binding (G?) proteins have been intensely studied over the years due to their role as signal transduction proteins. Proper function depends on three flexible switch regions that are involved in the relatively slow hydrolysis of GTP, allowing for the proteins to act as a molecular on/off switch. The structure of a protein is essential to its biological function. Occurrences of mutations in the genes GNAS and GNAI1 to highly conserved arginine residue in the switch II region have been detected in several types of cancers.

Utilizing the combinations of temperature denaturation, kinetics assays, and molecular dynamics, we plan to …

Application Of Synthetic Organic And Medicinal Chemistry Toward Medical Advances In Cancer, Antibiotics, And Drug Delivery, Marlon Lutz

Dissertations

Cancer and bacterial infections are a great concern in our society and have affected populations worldwide. The objective of this research was to discover new therapies for treating bacterial infections and cancer, and for promoting drug delivery.

DapE is an essential component in succinylase biosynthetic pathway, which is critical to production of lysine and m-DAP which both are essential in protein synthesis and bacterial peptidoglycan cell wall construction. Synthetic approaches were developed to prepare a new substrate for the N-succinyl-L,L-diaminopimelic acid desuccinylase (DapE) enzyme enabling the discovery of new antibiotics that inhibit DapE.

MMPs are over expressed in cancer, in …

Numerical Methods And Simulation For Time Dependent Electrokinetic Flow, Rui Cao

Dissertations

Electrokinetic flow typically occurs when an electric field is applied to a fluid electrolyte in the presence of a boundary or interface. The electric field induces a force that causes oppositely charged ions to migrate in opposite directions while simultaneously diffusing due to Brownian motion. In an unbounded medium this process, which is called electrodiffusion, does not separate bulk electric charge into separate regions and causes no bulk motion of the host fluid solvent. However, in the presence of a boundary or interface that either impedes or is impervious to the movement of ions in the normal direction, the normal …