Engineering Commons^™

Can Phishing Education Enable Users To Recognize Phishing Attacks?, Hanaa Alghamdi

Dissertations

Phishing attacks have increased rapidly and caused many drastic damages and losses for internet users‟ .The purpose of this research is to investigate on effectiveness of phishing education and training to help users identify different forms of phishing threats. The study has been conducted through developing a phishing quiz mobile application which includes four kinds of phishing threats. It tested the ability of users to recognize spoofed emails, SMS phishing (SMshing), scam phone calls (Vishing), and phishing through social media networks. A comprehensive literature review was discussed to investigate on the research area, understand the research problem, support the proposed …

Evaluating The Effectiveness Of The Gestalt Principles Of Perceptual Observation For Virtual Reality User Interface Design, William Macnamara

Dissertations

There is a lot of interest and excitement surrounding the areas of Virtual Reality and Head-Mounted Displays with the recent releases of devices such as the Oculus Rift, Sony PSVR and the HTC Vive. While much of the focus for these devices has been related to sectors of the entertainment industries, namely the cinema and video game industries, there are many more practical applications for these technologies, with potential benefits in educational, training/simulation, therapeutic and modelling/design software. Developing a set of reliable guidelines for Virtual Reality User Interface Design could play a crucial role in whether the medium successfully integrates …

Towards Improving Visqol (Virtual Speech Quality Objective Listener) Using Machine Learning Techniques, Joseph Mcnally

Dissertations

Vast amounts of sound data are transmitted every second over digital networks. VoIP services and cellular networks transmit speech data in increasingly greater volumes. Objective sound quality models provide an essential function to measure the quality of this data in real-time. However, these models can suffer from a lack of accuracy with various degradations over networks. This research uses machine learning techniques to create one support vector regression and three neural network mapping models for use with ViSQOLAudio. Each of the mapping models (including ViSQOL and ViSQOLAudio) are tested against two separate speech datasets in order to comparatively study accuracy …

Critical Comparison Of The Classification Ability Of Deep Convolutional Neural Network Frameworks With Support Vector Machine Techniques In The Image Classification Process, Robert Kelly

Dissertations

Recently, a number of new image classification models have been developed to diversify the number of options available to prospective machine learning classifiers, such as Deep Learning. This is particularly important in the field of medical image classification as a misdiagnosis could have a severe impact on the patient. However, an assessment on the level to which a deep learning based Convolutional Neural Network can outperform a Support Vector Machine has not been discussed. In this project, the use of CNN and SVM classifiers is used on a dataset of approx. 55,000 images. This dataset was used to assess the …

Benchmarking Javascript Frameworks, Carl Lawrence Mariano

Dissertations

JavaScript programming language has been in existence for many years already and is one of the most widely known, if not, the most used front-end programming language in web development. However, JavaScript is still evolving and with the emergence of JavaScript Frameworks (JSF), there has been a major change in how developers develop software nowadays. Developers these days often use more than one framework in order to fulfil their job which has given rise to the problem for developers when it comes to choosing the right JavaScript framework to develop software which is partly due to the availability of countless …

An Exploration Study Of Using The Universities Performance And Enrolments Features For Predicting The International Quality, Aeshah Althagafi

Dissertations

Quality ranking systems are crucial in the assessment of the academic performance of an institution because these assessment systems give details about how different learning institutions deliver their services. Education quality is also of paramount importance to the students because it is through quality education that these students develop skills that are needed in the job market. Besides, education enhances a student's academic and reasoning capacities. When universities are subjected to ranking systems, they are likely to improve their quality to be ranked high in the system. When the university administrators are exposed to ranking, competition gears up. Through competition, …

Exploring The Factors That Affect Secondary Student’S Mathematics And Portuguese Performance In Portugal, Lulu Cheng

Dissertations

Secondary education provides not only knowledge and skills, but also inculcates values, training of instincts, fostering right attitude and habits to enable adolescents to move into tertiary education or to ensure a workplace for students who decided to terminate their secondary schooling. Without secondary education to guide the development of young people through their adolescence, they will be ill prepared for tertiary education or for workplace, moreover, the possibility of juvenile delinquency and teenage pregnancy becomes higher. These negative effects will increase the pressures and expenditures on society and socio-economic. In 2006, Portugal was reported having the higher school-leaving rate …

The Influence Of Sensor-Based Intelligent Traffic Light Control On Traffic Flow In Dublin, Katja Rademacher

Dissertations

With growing cities and the increased use of vehicles for transportation purposes, there is a demand to make the traffic management in cities smarter. An intelligent traffic light control that dynamically adapts to the existing traffic conditions can help reduce traffic congestion and CO2 emissions. This thesis reviews the popular traffic light control approaches - static, actuated and adaptive – based on their influences on recorded traffic conditions in Dublin. The Irish capital relies heavily on busses for public transport adding to the number of already moving vehicles in the city centre. Using vehicle count data from inductive loop detectors …

Comparison Study Of The Most Common Virtual Machine Load Balancing Algorithms In Large-Scale Cloud Environment Using Cloud Simulator, Rowaa Filimban

Dissertations

This is era of internet. There is barely any field where internet do not play important role. Nowadays, CloudComputing links to the internet that has rebelled the whole universe. CloudComputing is a rapid enlarging domain in computing industry and research. Three main services offered by the cloud are SaaS, PaaS and IaaS. With the technology advancement of the CloudComputing, there are many new chances pioneer on how applications can be developed and how several services can be provided to the end user throughout Virtualization, on the internet. What's more, there are cloud service providers who offer and provide large-scaled computing …

Physical Human Activity Recognition Using Machine Learning Algorithms, Haritha Vellampalli

Dissertations

With the rise in ubiquitous computing, the desire to make everyday lives smarter and easier with technology is on the increase. Human activity recognition (HAR) is the outcome of a similar motive. HAR enables a wide range of pervasive computing applications by recognizing the activity performed by a user. In order to contribute to the multi facet applications that HAR is capable to offer, predicting the right activity is of utmost importance. Simplest of the issues as the use of incorrect data manipulation or utilizing a wrong algorithm to perform prediction can hinder the performance of a HAR system. This …

Application Of Supervised Machine Learning To Predict The Mortality Risk In Elderly Using Biomarkers, Priyanka Sonkar

Dissertations

The idea of long-term survival amongst older individuals has been a major medical and social concern. A wide range of biomarkers have been identified to prospectively predict disability, morbidity, and mortality outcomes in older adult populations. The machine learning techniques applied with clinically relevant biomarkers provide new ways of understanding diseases and solutions to tackle challenges to the health of the aging population. This paper describes two supervised machine learning techniques, Logistic Regression (LR) and Support Vector Machine (SVM) which are used in the prediction of the mortality in elderly people. LR is one of the traditionally used predictive modeling …

Modeling Mortgage Assessment With Computational Argumentation Theory And Defeasible Reasoning, Henrik Szucs

Dissertations

In the mortgage lending business of a bank, a key focus area is risk analysis, which supports the mortgage awarding process and the prediction of the risk of defaulting (repayment issues). The standard risk assessment method at most banks is a scorecard calculation. A new way of predicting the defaulting is proposed using Defeasible Reasoning (DR) and computational Argumentation Theory (AT), areas of interdisciplinary research, in the discipline of Articial Intelligence (AI). Argumentation is formalised by reasoning models which are inspired by human reasoning. For a more realistic representation AT employs DR which is a non-monotonic reasoning process, meaning that …

The Evaluation Of Ensemble Sentiment Classification Approach On Airline Services Using Twitter, Zechen Wang

Dissertations

In the field of sentiment classification, much research has been done on reviews of topics such as movies, software and books. Little research has been done in the airline service domain. In the airline industry, the use of social media as a customer service tool has become a growing phenomenon. The research conducted by Wan and Gao (2015) has proposed an ensemble classification approach for airline service sentiment classification using Twitter data. In accordance, the objective of improving the performance of ensemble classification approach is the primary consideration. This research proposed new hybrid classification approach that uses the state-of-art approach …

Nanostructured Morphologies In Glassy Polymer Networks, Brian Greenhoe

Dissertations

The body of this work describes a novel approach for the dispersion of multi-walled carbon nanotubes in a high T_g epoxy prepolymer matrix using a twin screw high-shear continuous reactor. The method demonstrated improves on previous dispersion methods in several ways. It offers increased efficiency through excellent heat transfer, while being solvent-less, scale-able, and tailorable to drive dispersion states to judiciously chosen dispersion states. Furthermore, it was shown that dispersion state and agglomerate morphology can be directed, in several ways, through processing conditions and also by controlling the matrix viscosity profile through cure. Broadband dielectric spectroscopy, optical hot-stage microscopy, …

Design And Synthesis Of Dynamic Covalent Polymer Scaffolds With Controlled Architectures, Emily Annette Hoff

Dissertations

The design and synthesis of functional, controlled polymer architectures is essential to the development of new materials with precise and tailorable properties or applications. The work described in this dissertation focuses on the development of controlled polymer architectures with dynamic linkages for the design of multifunctional materials and surfaces via robust, efficient, and stimuli-responsive strategies.

In Chapter III, a post-polymerization modification strategy based on ambient temperature nucleophilic chemical deblocking of polymer scaffolds bearing N-heterocycle blocked isocyanate moieties is reported. Room temperature RAFT polymerization of three azole-N-carboxamide methacrylates, including 3,5-dimethyl pyrazole, imidazole, and 1,2,4-triazole derivatives, afforded reactive polymer scaffolds …

Indoor Localization Of Mobile Devices Based On Wi-Fi Signals Via Convex Optimization And Bregman Divergence, Osamah Ali Abdullah

Dissertations

Indoor positioning systems (IPS) have been the subject of intense academic and industrial research due to the significance of such systems in a wide range of applications. Applications of IPS include indoor navigation and its associated user services, especially by users in large complex buildings, by emergency healthcare services to locate a patient, and people with vision impairments. IPS can also play an important role in other applications that require tracking and observation, such as those used in care for the elderly or security purposes. Therefore, much research has been focused on IPS methods that fingerprint the Received Signal Strength …

Development Of Printed Cross-Functional Sensors For Gearbox Lubricant Prognostics, John Omondi Manyala

Dissertations

Lubricant oil degradation is a major cause of failures in transportation machinery such as pumps, engines, and gearboxes. Proactive oil maintenance techniques such as the off-line oil sampling for laboratory analysis are not only costly but are also susceptible to various influences during the oil sampling, transportation and testing. In this study, an on-line oil condition monitoring system is presented with an integrated predictive prognostic scheme, describing the evolution in time of the identified fault indicators for purposes of estimating the remaining useful life of oil in real-time inside the gearbox. The proposed methodology facilitates on-demand gearbox maintenance rather than …

Design And Validation Of An Electro-Hydraulic Pressure-Control Valve And Closed-Loop Controller, Jerry Boza

Dissertations

Electro-hydraulic pressure-control valves are used in many applications, such as manufacturing equipment, agricultural machinery, and aircrafts to name a few. They are often used to actuate hydraulic clutches, such as those found in power shift transmissions. A traditional pressure-control valve with open-loop control algorithm is typically used in clutch applications. This scheme often results in inconsistent or undesirable system behavior due to the nature of open-loop control as well as the nonlinear system dynamics and uncertainties.

In this research two new electro-hydraulic pressure-control valves were designed in order to decouple the valve and control port (hydraulic) dynamics. This was achieved …

Support Vector Machines And Artificial Neural Networks: Assessing The Validity Of Using Technical Features For Security Forecasting, James Dipadua

Dissertations

Stock forecasting is an enticing and well-studied problem in both finance and machine learning literature with linear-based models such as ARIMA and ARCH to non-linear Artificial Neural Networks (ANN) and Support Vector Machines (SVM). However, these forecasting techniques also use very different input features, some of which are seen by economists as irrational and theoretically unjustified. In this comparative study using ANNs and SVMs for 12 publicly traded companies, derivative price “technicals” are evaluated against macro- and microeconomic fundamentals to evaluate the efficacy of model performance. Despite the efficient market hypothesis positing the ill-suitability of technicals as model inputs, this …

Support Vector Machines And Artificial Neural Networks: Assessing The Validity Of Using Technical Features For Security Forecasting, James Di Padua

Dissertations

Stock forecasting is an enticing and well studied problem in both finance and machine learning literature with linear based models such as ARIMA and ARCH to nonlinear Artificial Neural Networks (ANN) and Support Vector Machines (SVM). However, these forecasting techniques also use very different input features, some of which are seen by economists as irrational and theoretically unjustified. In this comparative study using ANNs and SVMs for 12 publicly traded companies, derivative price “technicals” are evaluated against macro and microeconomic fundamentals to evaluate the efficacy of model performance. Despite the efficient market hypothesis positing the ill suitability of technicals as …

A Regression Study Of Salary Determinants In Indian Job Markets For Entry Level Engineering Graduates, Rajveer Singh

Dissertations

The economic liberalisation of Indian markets in early 90s boosted the economic growth of the nation in various sectors over the next two decades. One such sector that has seen a massive growth in this time is Information Technology (IT). The IT industry has played a very crucial role in transforming India from a slow moving economy to one of the largest exporters of IT services. This growth created a huge demand in the labour markets for skilled labour, which in turn made engineering one of the top choices of study after high school over the years. In addition, the …

Using Spatialisation To Support Exploratory Search Behaviour, Clement Roux

Dissertations

Information-seekers traditionally interact with digital content through keyword-based search interfaces displaying results in list views. Well-defined lookup search tasks are performed brilliantly with these interfaces, enabling users to find relevant information and develop a relative understanding of the underlying information space. However, it is feasible to suggest that ill-defined and abstract search tasks could be better supported with a different interface that could allow the user to explore a library’s content and develop an appropriate mental model of the information space. One such approach is based on the use of visualisation, an approach to data analysis that aims to reduce …

Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh

Dissertations

This thesis reviews the current state of photometric classification in Astronomy and identifies two main gaps: a dependence on handcrafted rules, and a lack of interpretability in the more successful classifiers. To address this, Deep Learning and Computer Vision were used to create a more interpretable model, using unsupervised training to reduce human bias.

The main contribution is the investigation into the impact of using unsupervised feature-extraction from multi-wavelength image data for the classification task. The feature-extraction is achieved by implementing an unsupervised Deep Belief Network to extract lower-dimensionality features from the multi-wavelength image data captured by the Sloan Digital …

An Exploration Of The Impact Of Animal Agriculture On Human Sustainable Development Index And The Child Health Indicator, Hithesan Pandian

Dissertations

Several studies have shown that animal agriculture is one of the major contributors to climate change due to greenhouse gas emissions, deforestation, land degradation, freshwater shortages, general environmental pollution and world hunger. Apart from this, meat consumption is strongly associated with certain fatal health conditions such as cancer, cardiovascular disease and diabetes (Wu, 2014). Although meat production and export could be economically beneficial in the short run, it could lead to over-exploitation of natural resources and in turn the destruction of the environment in the long run. Hence, it is essential for the leaders of a nation to make smart …

Electrical Characterization Of High-K Gate Dielectrics For Advanced Cmos Gate Stacks, Yi Ming Ding

Dissertations

The oxide/substrate interface quality and the dielectric quality of metal oxide semiconductor (MOS) gate stack structures are critical to future CMOS technology. As SiO₂ was replaced by the high-k dielectric to further equivalent oxide thickness (EOT), high mobility substrates like Ge have attracted increasing in replacing Si substrate to further enhance devices performance. Precise control of the interface between high-k and the semiconductor substrate is the key of the high performance of future transistor. In this study, traditional electrical characterization methods are used on these novel MOS devices, prepared by advanced atomic layer deposition (ALD) process and with pre …

Processing Of Cds/Cdte Solar Cell And The Growth Model Of Cdte Thin Film, Guogen Liu

Dissertations

Cadmium telluride is the only thin film photovoltaic (PV) technology to surpass crystalline silicon PV in the cost. The most common CdTe solar cells consist of a simple p-n heterojunction structure containing a p-doped CdTe layer and n-doped cadmium sulfide (CdS) layer, which acts as a window layer. Cadmium Sulfide (CdS) thin films are often deposited on glass substrates coated with TCO layers by the close-spaced sublimation (CSS) or sputter techniques in industrial because of in-line production integration. It is seldom reported that CdS is deposited by the chemical bath deposition (CBD) batch process. The bottleneck of CBD for commercial …

A Multimodal Investigation In Eye Movements, Raj Jaswal

Dissertations

While functional magnetic resonance imaging (fMRI) has identified which regions of interest (ROIs) are functionally active during a vergence movement (inward or outward eye rotation), task-modulated coactivation between ROIs is less understood. This study tests the following hypotheses: (1) significant task-modulated coactivation would be observed between the frontal eye fields (FEFs), the posterior parietal cortex (PPC), and the cerebellar vermis (CV); (2) significantly more functional activity and task-modulated coactivation would be observed in binocularly normal controls (BNCs) compared with convergence insufficiency (CI) subjects; and (3) after vergence training, the functional activity and task-modulated coactivation would increase in CIs compared with …

Biomimetic And Vascularized 3-D Liver Cancer Model, Derek Yip

Dissertations

Anti-angiogenic drugs have failed to show significant extended mortality, except when co-administered with chemotherapy drugs in clinical trials. This should be predicted by in vitro models, and yet 2D in vitro models of liver cancer co-administered with these two types of drugs show increased cell viability, contradicting clinical trials. In vitro models should mimic clinical trials in order to accurately predict drug outcomes. 2D in vitro models fail because they lack features of the cancer environment such as presence of stromal cells and a vasculature.

In order to achieve a biomimetic and vascularized in vitro model that would better recapitulate …

Optimization Of Headway, Stops, And Time Points Considering Stochastic Bus Arrivals, Liuhui Zhao

Dissertations

With the capability to transport a large number of passengers, public transit acts as an important role in congestion reduction and energy conservation. However, the quality of transit service, in terms of accessibility and reliability, significantly affects model choices of transit users. Unreliable service will cause extra wait time to passengers because of headway irregularity at stops, as well as extra recovery time built into schedule and additional cost to operators because of ineffective utilization of allocated resources.

This study aims to optimize service planning and improve reliability for a fixed bus route, yielding maximum operator’s profit. Three models are …

Application Of Inkjet Printing Technology To Flexible Batteries, Yuan Gu

Dissertations

Printing technologies have been considered as alternative methods to fabricate thin films in recent years. More and more functional devices like resistors, sensors, antennas and even energy storage devices have been fabricated by printing technologies. As a typical digital printing technology, inkjet printing has much more advantages over the traditional mechanical printing technologies such as: low cost, computer controllable shape design and precise deposition. In this investigation, application of inkjet printing is used to fabricate conductive tracks and rechargeable lithium ion batteries.

Particle free silver ink is developed to solve this problem. In this research, silver complex solution is printed …