Physical Sciences and Mathematics Commons^™

Performance Comparison Of Hybrid Cnn-Svm And Cnn-Xgboost Models In Concrete Crack Detection, Sahana Thiyagarajan

Dissertations

Detection of cracks mainly has been a sort of essential step in visual inspection involved in construction engineering as it is the commonly used building material and cracks in them is an early sign of de-basement. It is hard to find cracks by a visual check for the massive structures. So, the development of crack detecting systems generally has been a critical issue. The utilization of contextual image processing in crack detection is constrained, as image data usually taken under real-world situations vary widely and also includes the complex modelling of cracks and the extraction of handcrafted features. Therefore the …

Hierarchical Cluster Analysis: A New Type Of Ranking Criteria Based On Arwu Ranking Data, Zhengshuo Li

Dissertations

The advent of big data leads to many applications of Machine Learning techniques. University rankings is one of the applicable domains, which is currently playing a crucial role in the assessment of the universities' performance. Currently, the rankings are usually carried out by some authoritative ranking institutions by means of weighting techniques and the results are conveyed in numerical rankings. Three of the most famous university ranking institutions have been introduced from a technical perspective. However, these institutions have been proven to be subjective in relation to their data selection and weighting method.

An Evaluation Of The Information Security Awareness Of University Students, Alan Pike

Dissertations

Between January 2017 and March 2018, it is estimated that more than 1.9 billion personal and sensitive data records were compromised online. The average cost of a data breach in 2018 was reported to be in the region of US$3.62 million. These figures alone highlight the need for computer users to have a high level of information security awareness (ISA). This research was conducted to establish the ISA of students in a university. There were three aspects to this piece of research. The first was to review and analyse the security habits of students in terms of their own personal …

Noise Reduction In Eeg Signals Using Convolutional Autoencoding Techniques, Conor Hanrahan

Dissertations

The presence of noise in electroencephalography (EEG) signals can significantly reduce the accuracy of the analysis of the signal. This study assesses to what extent stacked autoencoders designed using one-dimensional convolutional neural network layers can reduce noise in EEG signals. The EEG signals, obtained from 81 people, were processed by a two-layer one-dimensional convolutional autoencoder (CAE), whom performed 3 independent button pressing tasks. The signal-to-noise ratios (SNRs) of the signals before and after processing were calculated and the distributions of the SNRs were compared. The performance of the model was compared to noise reduction performance of Principal Component Analysis, with …

An Investigation Into The Predictive Capability Of Customer Spending In Modelling Mortgage Default, Donal Finn [Thesis]

Dissertations

The mortgage arrears crisis in Ireland was and is among the most severe experienced on record and although there has been a decreasing trend in the number of mortgages in default in the past four years, it still continues to cause distress to borrowers and vulnerabilities to lenders. There are indications that one of the main factors associated with mortgage default is loan affordability, of which the level of disposable income is a driver. Additionally, guidelines set out by the European Central Bank instructed financial institutions to adopt measures to further reduce and prevent loans defaulting, including the implementation and …

Multi-Scale Interactions Between The Diurnal Cycle, The Mjo, And Convectively Coupled Equatorial Waves Over The Maritime Continent, Lakemariam Yohannes Worku

Dissertations

Given the Maritime Continent’s (MC’s) critical role in the global climate, examining variations in diurnal cycle and its interaction with the Madden–Julian Oscillation (MJO), Kelvin and Equatorial Rossby waves may lead to improved sub-seasonal forecasts. This study used satellite data of TRMM, TRMM Precipitation Features (PFs), and convective classifications from ISCCP. The convection becomes more organized through the afternoon and evening, leading to peak rainfall over the islands around 1800–2100 local standard time (LST). Over the next few hours, some of that rainfall transitions to stratiform rain over land. The convection then propagates offshore overnight with rainfall peaking along the …

Modeling And Evaluating Cost-Effectiveness Of Host-Microbiome Investigations, Renuka Panchagavi

Dissertations

Cost-effectiveness modeling accounts for how expenditures impact outcomes and is an appropriate step towards efficacy of the different methods used for modeling the dynamics of microbial communities. This will help to identify challenging aspects of microbiome studies and the associated costs, including the major differences in research designs (cross-sectional or time series-based) used for conducting such studies. The two major stages of our investigation were to first collect and model cost variable data for microbiome investigations, and then to evaluate how trade-offs related to sample size and expenditures impact investigational outcomes. We screened different potential sources of data for microbiome …

Sources And Atmospheric Oxidation Of Sulfur Dioxide And Formaldehyde Based On Wintertime Aircraft Observations Over The Eastern United States, Jaime R. Green

Dissertations

Plume intercepts from flights on the NSF-C-130 during the Wintertime Investigation of Transport, Emission and Reactivity (WINTER) campaign were used to estimate (1) the oxidation rates of Sulfur Dioxide (SO2) under wintertime conditions and the factors that determine SO2 removal; and (2) to examine the oxidation, lifetime and source apportionment of formaldehyde (HCHO). Observations suggest that OH governs the rate SO2 oxidation in the eastern United States during winter. The range of mean oxidation rates during the day from power plants were 0.22–0.71%/hr, producing SO2 lifetimes of 13–43 days, if SO2 consumption is assumed to occur during 10.5 hr of …

Comparing Procedural Content Generation Algorithms For Creating Levels In Video Games, Zina Monaghan

Dissertations

Procedural Content Generation (PCG) is used frequently in games to increase replayability by introducing variety to playghrough of a game and reduce development time by allowing complex game worlds to be developed by a smaller team over a more limited amount of time.

Predicting Violent Crime Reports From Geospatial And Temporal Attributes Of Us 911 Emergency Call Data, Vincent Corcoran

Dissertations

The aim of this study is to create a model to predict which 911 calls will result in crime reports of a violent nature. Such a prediction model could be used by the police to prioritise calls which are most likely to lead to violent crime reports. The model will use geospatial and temporal attributes of the call to predict whether a crime report will be generated. To create this model, a dataset of characteristics relating to the neighbourhood where the 911 call originated will be created and combined with characteristics related to the time of the 911 call. Geospatial …

Using Supervised Learning To Predict English Premier League Match Results From Starting Line-Up Player Data, Runzuo Yang

Dissertations

Soccer is one of the most popular sports around the world. Many people, whether they are a fan of a soccer team, a player of online soccer games or even the professional coach of a soccer team, will attempt to use some relevant data to predict the result of a match. Many of these kinds of prediction models are built based on data from the match itself, such as the overall number of shots, yellow or red cards, fouls committed, etc. of the home and away teams. However, this research attempted to predict soccer game results (win, draw or loss) …

Multi-Sensory Deep Learning Architectures For Slam Dunk Scene Classification, Paul Minogue

Dissertations

Basketball teams at all levels of the game invest a considerable amount of time and effort into collecting, segmenting, and analysing footage from their upcoming opponents previous games. This analysis helps teams identify and exploit the potential weaknesses of their opponents and is commonly cited as one of the key elements required to achieve success in the modern game. The growing importance of this type of analysis has prompted research into the application of computer vision and audio classification techniques to help teams classify scoring sequences and key events using game footage. However, this research tends to focus on classifying …

Is There A Correlation Between Wikidata Revisions And Trending Hashtags On Twitter?, Paula Dooley [Thesis]

Dissertations

Twitter is a microblogging application used by its members to interact and stay socially connected by sharing instant messages called tweets that are up to 280 characters long. Within these tweets, users can add hashtags to relate the message to a topic that is shared among users. Wikidata is a central knowledge base of information relying on its members and machines bots to keeping its content up to date. The data is stored in a highly structured format with the added SPARQL protocol and RDF Query Language (SPARQL) endpoint to allow users to query its knowledge base.

Forecasting Anomalous Events And Performance Correlation Analysis In Event Data, Sonya Leech [Thesis]

Dissertations

Classical and Deep Learning methods are quite common approaches for anomaly detection. Extensive research has been conducted on single point anomalies. Collective anomalies that occur over a set of two or more durations are less likely to happen by chance than that of a single point anomaly. Being able to observe and predict these anomalous events may reduce the risk of a server’s performance. This paper presents a comparative analysis into time-series forecasting of collective anomalous events using two procedures. One is a classical SARIMA model and the other is a deep learning Long-Short Term Memory (LSTM) model. It then …

Enhancing Partially Labelled Data: Self Learning And Word Vectors In Natural Language Processing, Eamon Mcentee

Dissertations

There has been an explosion in unstructured text data in recent years with services like Twitter, Facebook and WhatsApp helping drive this growth. Many of these companies are facing pressure to monitor the content on their platforms and as such Natural Language Processing (NLP) techniques are more important than ever. There are many applications of NLP ranging from spam filtering, sentiment analysis of social media, automatic text summarisation and document classification.

Detection Of Offensive Youtube Comments, A Performance Comparison Of Deep Learning Approaches, Priyam Bansal

Dissertations

Social media data is open, free and available in massive quantities. However, there is a significant limitation in making sense of this data because of its high volume, variety, uncertain veracity, velocity, value and variability. This work provides a comprehensive framework of text processing and analysis performed on YouTube comments having offensive and non-offensive contents.

YouTube is a platform where every age group of people logs in and finds the type of content that most appeals to them. Apart from this, a massive increase in the use of offensive language has been apparent. As there are massive volume of new …

Domain Decomposition Methods For The Solution Of Multiple Scattering Problems, Michael Pedneault

Dissertations

This presents a Schur complement Domain Decomposition (DD) algorithm for the solution of frequency domain multiple scattering problems. Just as in the classical DD methods,(1) the ensemble of scatterers is enclosed in a domain bounded by an artificial boundary, (2) this domain is subdivided into a collection of nonoverlapping subdomains so that the boundaries of the subdomains do not intersect any of the scatterers, and (3) the solutions of the subproblems are connected via Robin boundary conditions matching on the common interfaces between subdomains. Subdomain Robin-to-Robin maps are used to recast the DD problem as a sparse linear system whose …

Storage Systems For Mobile-Cloud Applications, Nafize R. Paiker

Dissertations

Mobile devices have become the major computing platform in todays world. However, some apps on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud.

This dissertation aims to ensure that the tasks in a mobile app that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. …

Methods To Improve The Remediation Of Polycyclic Aromatic Hydrocarbons (Pahs) In Aerobic And Anaerobic Environments, Brian Wartell

Dissertations

Oil spills occur regularly in terrestrial environments and crude oil can contain many compounds that are highly resistant to degradation. Among these compounds are high levels of polycyclic aromatic hydrocarbons (PAHs) which are not only toxic but can also be carcinogenic and/or mutagenic. The first chapter of this dissertation includes an extensive review chapter on the variables affecting the anaerobic degradation of hydrocarbons, with a particular focus on PAHs. Electron acceptors, electron donors, temperature, salinity, pH all play key roles in determining the possibility effective of effective degradation occurring. Thus, by addressing solutions, such as biostimulation, improving environmental variables for …

High-Speed Data Communications For Vehicular Networks Using Free-Space Optical Communications, Yagiz Kaymak

Dissertations

The demand for high-speed Internet access for vehicles, such as high-speed trains (HSTs) and cars, is on the rise. Several Internet access technologies that use radio frequency are being considered for vehicular networking. Radio-frequency communications technologies cannot provide high data rates due to interference, bandwidth limitations, and the inherent limited data rates of radio technology. Free-space optical communications (FSOC) is an alternative approach and a line-of-sight (LOS) technology that uses modulated light to transfer data between two free-space optical (FSO) transceivers. FSOC systems for vehicular networks are expected to provide data rates in the range of Gbps for stationary and …

Fwer Controlling Procedures In Simultaneous And Selective Inference, Li Yu

Dissertations

With increasing complexity of research objectives in clinical trials, a variety of relatively complex and less intuitive multiple testing procedures (MTPs) have been developed and applied in clinical data analysis. In order to make testing strategies more explicit and intuitive to communicate with non-statisticians, several flexible and powerful graphical approaches have recently been introduced in the literature for developing and visualizing newer MTPs. Nevertheless, some theoretical as well as methodological issues still remain to be fully addressed. This dissertation addresses several important issues arising in graphical approaches and related selective inference problems. It consists of three parts.

In the first …

Functionalized Carbon Nanotubes In Hydrophobic Drug Delivery, Kun Chen

Dissertations

The direct incorporation of carboxylated carbon nanotubes (f-CNTs) into hydrophobic drug particles during their formation via anti-solvent precipitation is presented. The approach is tested using two drugs namely antifungal agent Griseofulvin (GF) and antibiotic Sulfamethoxazole (SMZ) that have very different aqueous solubility. It is observed that the f-CNTs dispersed in the water serve as nucleating sites for crystallization and are readily incorporated into the drug particles without altering crystal structure or other properties. The results show that the hydrophilic f-CNTs dramatically enhance dissolution rate for both drugs. The increased degree of functionalization leads to higher hydrophilicity and therefore faster dissolution …

Deep Learning Methods For Mining Genomic Sequence Patterns, Xin Gao

Dissertations

Nowadays, with the growing availability of large-scale genomic datasets and advanced computational techniques, more and more data-driven computational methods have been developed to analyze genomic data and help to solve incompletely understood biological problems. Among them, deep learning methods, have been proposed to automatically learn and recognize the functional activity of DNA sequences from genomics data. Techniques for efficient mining genomic sequence pattern will help to improve our understanding of gene regulation, and thus accelerate our progress toward using personal genomes in medicine.

This dissertation focuses on the development of deep learning methods for mining genomic sequences. First, we compare …

Development Of Flexible Nickel-Zinc And Nickel-Iron Batteries, Xianyang Meng

Dissertations

The fabrication of flexible nickel-zinc batteries using a facile mixing of electroactive components for electrode preparation is presented. Polytetrafluoroethylene (PTFE) is found to be an effective binder by reducing concentration polarization, providing chemical/physical stability and enhancing flexibility. The zinc electrode containing PTFE maintains its original porous morphology even after hundreds of cycles while polymers such as PEO show morphology change. Each component, as well as the assembled flexible cells show desired flexibility and stability even under bending conditions.

The fabrication of flexible nickel-iron batteries using printable composite electrodes embedded with multiwalled carbon nanotubes (CNT) is also presented. All the metal …

Computational Intelligence In Steganography: Adaptive Image Watermarking, Xin Zhong

Dissertations

Digital image watermarking, as an extension of traditional steganography, refers to the process of hiding certain messages into cover images. The transport image, called marked-image or stego-image, conveys the hidden messages while appears visibly similar to the cover-image. Therefore, image watermarking enables various applications such as copyright protection and covert communication. In a watermarking scheme, fidelity, capacity and robustness are considered as crucial factors, where fidelity measures the similarity between the cover- and marked-images, capacity measures the maximum amount of watermark that can be embedded, and robustness concerns the watermark extraction under attacks on the marked-image. Watermarking techniques are often …

The Dynamical State Of A Young Stellar Cluster, Timothy Sullivan

Dissertations

The dynamical state of the young star-forming cluster Rho Ophiuchi is considered, with emphasis on the L1688 cloud. Radial velocities are derived for 32 YSOs, with some being multi-epoch, using Markov-Chain Monte Carlo routines based upon the package emcee. Sources are chosen based upon their spectral index to focus on the earlier stages of star formation, in this case, Class I and Flat spectrum objects, and compared with a sample of Class II and III objects from the same embedded cluster. It is found that the radial velocity dispersion for these younger objects is ∆v = 2.8 ± 0.6 km …

Efficacy Of Deep Learning In Support Of Smart Services, Basheer Mohammed Basheer Qolomany

Dissertations

The massive amount of streaming data generated and captured by smart service appliances, sensors and devices needs to be analyzed by algorithms, transformed into information, and minted to extract knowledge to facilitate timely actions and better decision making. This can lead to new products and services that can dramatically transform our lives. Machine learning and data analytics will undoubtedly play a critical role in enabling the delivery of smart services. Within the machine-learning domain, Deep Learning (DL) is emerging as a superior new approach that is much more effective than any rule or formula used by traditional machine learning. Furthermore, …

Towards Automated Domain-Oriented Lexicon Construction And Dimension Reduction For Arabic Sentiment Analysis, Hasan A. Alshahrani

Dissertations

Sentiment analysis is a type of text mining that uses Natural Language Processing (NLP) tools to identify and label opinionated text. There are two main approaches of sentiment analysis: lexicon-based, and statistical approach. In our research, we use the lexicon-based approach because the lexicon contains sentiment words and phrases which are the main linguistic units to express sentiments. More specifically, we work with domain-oriented lexicons as they are more efficient than general ones because the polarity is heavily driven by domains.

Arabic language has a degree of uniqueness that makes it hard to be processed with the available cross-language tools …

Retinex-Based Visibility Enhancement System For Inclement Weather With Tracking And Distance Estimation Capabilities, Marwan S. Alluhaidan

Dissertations

Road conditions affected by weather are well known to have an impact on the number of vehicle accidents and fatalities, due to low- to no-visibility conditions. According to the U.S. Department of Transportation, there are more than 1,259,000 crashes each year. On average, 6,000 people are killed and more than 445,000 people are injured annually due to severe weather conditions. These accidents could be significantly reduced if real-time visibility enhancement systems were made available. However, eliminating the impact of weather conditions on visibility is still lacking and beyond our control. The time has come to develop technology that is capable …

A New Generation Of Functional Polyisobutylenes For Advanced Applications, Corey M. Parada

Dissertations

Polyisobutylene (PIB) is a fully saturated, aliphatic polymer of high commercial importance due to its superior gas barrier properties and high chemical/oxidative stability. One commercial end-use for PIB is in insulated glass windows (IGU), where it acts as a gas/moisture barrier and sealant. Under certain adverse conditions, catastrophic failure of the PIB sealant may result in aesthetic and functional failure of the IGU, which necessitates replacement of the unit. Thus, there exists a need to improve current generations of thermoplastic PIB sealants to be able to withstand the harsh environments found in current real-world applications.

In the first project, we …