Digital Commons Network^™

Aesthetic Choices: Defining The Range Of Aesthetic Views In Interactive Digital Media Including Games And 3d Virtual Environments (3d Ves), Hira Maqbool

Theses: Doctorates and Masters

Defining aesthetic choices for interactive digital media such as games is a challenging task. Objective and subjective factors such as colour, symmetry, order and complexity, and statistical features among others play an important role for defining the aesthetic properties of interactive digital artifacts. Computational approaches developed in this regard also consider objective factors such as statistical image features for the assessment of aesthetic qualities. However, aesthetics for interactive digital media, such as games, requires more nuanced consideration than simple objective and subjective factors, for choosing a range of aesthetic features.

From the study it was found that the there is …

Mass Spectrometry-Based Proteomic Analysis To Characterise Barley Breeding Lines, Mahya Bahmani

Theses: Doctorates and Masters

Barley is a key ingredient in the malting and brewing industry, and it is the fourth most important crop being cultivated worldwide. The protein content of the barley grain is one of the main components determining the quality and nutritive value of the food and beverages prepared from barley. Mass spectrometry-based proteomic analysis is a valuable tool that can guide and inform plant breeding strategies and crop improvement programs. Understanding the proteome changes in barley grain under different growing locations, the impact of different environmental conditions and its relationship with malting characteristics have the potential to inform breeding programs to …

An Investigation Of Change In Drone Practices In Broadacre Farming Environments, Hrishikesh S. Neetye

Theses: Doctorates and Masters

The application of drones in broadacre farming is influenced by novel and emergent factors. Drone technology is subject to legal, financial, social, and technical constraints that affect the Agri-tech sector. This research showed that emerging improvements to drone technology influence the analysis of precision data resulting in disparate and asymmetrically flawed Ag-tech outputs. The novelty of this thesis is that it examines the changes in drone technology through the lens of entropic decay. It considers the planning and controlling of an organisation’s resources to minimise harmful effects through systems change. The rapid advances in drone technology have outpaced the systematic …

Optimising A Defence-Aware Threat Modelling Diagram Incorporating A Defence-In-Depth Approach For The Internet-Of-Things, Menaka L. Godakanda

Theses: Doctorates and Masters

Modern technology has proliferated into just about every aspect of life while improving the quality of life. For instance, IoT technology has significantly improved over traditional systems, providing easy life, time-saving, financial saving, and security aspects. However, security weaknesses associated with IoT technology can pose a significant threat to the human factor. For instance, smart doorbells can make household life easier, save time, save money, and provide surveillance security. Nevertheless, the security weaknesses in smart doorbells could be exposed to a criminal and pose a danger to the life and money of the household. In addition, IoT technology is constantly …

Investigation And Development Of Titanium Nitride Solid-State Potentiometric Ph Sensor, Shimrith Paul Shylendra

Theses: Doctorates and Masters

The measurement of pH value is crucial parameter in various fields like, drinking water monitoring, food preparation, biomedical and environmental applications. The most common device for pH sensing is the conventional pH glass electrode. While glass electrodes have several advantages, such as Nernstian sensitivity, superior ion selectivity, excellent stability, and extensive operating range, they have several key disadvantages. pH glass electrodes need to be stored in buffer solutions, they are fragile and have limited size and shape, making them impractical for some applications, such as being potentially used as miniature pH sensors for capsule endoscopy and ambulatory esophageal pH monitoring. …

Comparison Of Methods For Metabolite Extraction From Rat Polycystic Kidney Tissue For Gas Chromatography-Mass Spectrometry-Based Metabolomics, Matthew Oosthuizen

Theses: Doctorates and Masters

This study included a series of experiments focussed on comparing extraction protocols for metabolomics-based analysis of Lewis rat polycystic kidney (LPK) tissue samples and healthy Lewis rat tissue samples. Firstly, the optimal sample loading (mass of tissue) was investigated. Based on previous studies, the appropriate mass to test was approximately 5 mg. Three different volumes of tissue extract equivalent to 1, 2.5 and 5mg of pooled healthy kidney tissue and pooled polycystic kidney tissue were trialled to see how they differed in terms of the number of reproducible, uniquely identified peaks captured after metabolite extraction, derivatisation and gas chromatography-mass spectrometry …

Social Disorganisation Theory And Violent Crime: A Spatial-Econometric Analysis Of Chicago And Sydney, Anthony N. Greening

Theses: Doctorates and Masters

The spatialisation of violent crime is explored in two large case studies, Chicago and Sydney, using spatial econometric methods and macro-sociological variables derived from Social Disorganisation Theory.

Social Disorganisation Theory (SDT) is introduced in terms of its formulation in response to highly specific conditions arising in Chicago, as well as its adoption of methodological and theoretical developments from existing traditions. This specificity belies its breadth of application and enduring presence in criminology. With “Social Disorganisation Theory” hosting a wealth of highly nuanced academic dialogue conducted under its banner, current incarnations of SDT appear as branches on an evolutionary tree. This …

Deep Learning Augmentation For Medical Image Analysis, Fouzia Altaf

Theses: Doctorates and Masters

Deep learning is at the center of the current rise of computer aided diagnosis in medical imaging. This technology has the ability to mimic extremely complex mathematical functions for predictive tasks. These functions are encoded as computational models that are learned directly from data. Deep learning models are known to achieve human-level accuracy for predictive tasks. However, such a performance requires that the model is trained on a huge amount of training data. For computer aided diagnosis tasks, the relevant training data needs to be carefully annotated by medical experts. This process is laborious and expensive, which generally results in …

Imputation, Modelling And Optimal Sampling Design For Digital Camera Data In Recreational Fisheries Monitoring, Ebenezer Afrifa-Yamoah

Theses: Doctorates and Masters

Digital camera monitoring has evolved as an active application-oriented scheme to help address questions in areas such as fisheries, ecology, computer vision, artificial intelligence, and criminology. In recreational fisheries research, digital camera monitoring has become a viable option for probability-based survey methods, and is also used for corroborative and validation purposes. In comparison to onsite surveys (e.g. boat ramp surveys), digital cameras provide a cost-effective method of monitoring boating activity and fishing effort, including night-time fishing activities. However, there are challenges in the use of digital camera monitoring that need to be resolved. Notably, missing data problems and the cost …

Developing A Music Composition Practice: Exploring The Choreography Of Cymatics, Joshua Jervis

Theses : Honours

Cymatics is an area of physics popularised by Hans Jenny that observes the influence of sound but more simply vibration on physical matter. When sound is directly applied to a substance, for example, water, the vibrations create kaleidoscopic movement within the medium. Specific variables primarily of pitch, container size, and water volume contribute to creating a variety of geometric shapes. Without sound cymatics does not exist and is, therefore, a visual characteristic of sound itself.

With an investigation into the behaviour and application of cymatics, this research uses the findings of an investigation to develop a ‘choreographical’ language that can …

A Defensive Strategy For Detecting Targeted Adversarial Poisoning Attacks In Machine Learning Trained Malware Detection Models, Adrian Michael Wood

Theses: Doctorates and Masters

Machine learning is a subset of Artificial Intelligence which is utilised in a variety of different fields to increase productivity, reduce overheads, and simplify the work process through training machines to automatically perform a task. Machine learning has been implemented in many different fields such as medical science, information technology, finance, and cyber security. Machine learning algorithms build models which identify patterns within data, which when applied to new data, can map the input to an output with a high degree of accuracy. To build the machine learning model, a dataset comprised of appropriate examples is divided into training and …

An Investigation Into The Efficacy Of Url Content Filtering Systems, Brett Ronald Turner

Theses: Doctorates and Masters

Content filters are used to restrict to restrict minors from accessing to online content deemed inappropriate. While much research and evaluation has been done on the efficiency of content filters, there is little in the way of empirical research as to their efficacy. The accessing of inappropriate material by minors, and the role content filtering systems can play in preventing the accessing of inappropriate material, is largely assumed with little or no evidence. This thesis investigates if a content filter implemented with the stated aim of restricting specific Internet content from high school students achieved the goal of stopping students …

Evaluating The Relative Importance Of Stormwater For Nutrient And Metal Contamination To The Urban, Groundwater Dependent Yellagonga Wetlands, Through Wetland Budgeting, Jonas Polifka

Theses: Doctorates and Masters

Wetlands provide numerous ecosystem services and can be utilised as pollutant sinks, however excessive contamination of wetlands can induce adverse effects to wetland ecology and lead to degradation of its values. Runoff from precipitation mobilizes contaminants from impervious surfaces which are, in some case, transported directly to wetlands through stormwater drainage. Urban stormwater can be a significant source of contaminants to wetlands, although its overall importance needs to be assessed for each wetland individually. Wetland budgeting is a management tool used to evaluate the relative importance of contaminant sources to wetlands, by comparing contaminant loads. Environmental management of the Yellagonga …

An Investigation Into The Spatial Distribution, Habitat Selection And Resource Usage Of The Red Fox (Vulpes Vulpes) Inhabiting Urban Reserves Within Perth, Western Australia, Michael Thomas Main

Theses: Doctorates and Masters

I attempted to track a population of urban foxes in Kings Park, but due to collar failure, only one collar was retrieved. The GPS telemetry data from this fox produced home range estimates for minimum convex polygon (MCP) and kernel density (KD) of 0.302 km² and 0.331 km², respectively. The fox was predominantly active at night, with a ten-fold increase in movement during nocturnal periods when compared to daytime movements. Roads and man-made tracks were important for facilitating movement of the fox through its home range, with almost 97% of location fixes recorded within 100m of these features. The fox …

Local Binary Pattern Based Algorithms For The Discrimination And Detection Of Crops And Weeds With Similar Morphologies, Vi Nguyen Thanh Le

Theses: Doctorates and Masters

In cultivated agricultural fields, weeds are unwanted species that compete with the crop plants for nutrients, water, sunlight and soil, thus constraining their growth. Applying new real-time weed detection and spraying technologies to agriculture would enhance current farming practices, leading to higher crop yields and lower production costs. Various weed detection methods have been developed for Site-Specific Weed Management (SSWM) aimed at maximising the crop yield through efficient control of weeds. Blanket application of herbicide chemicals is currently the most popular weed eradication practice in weed management and weed invasion. However, the excessive use of herbicides has a detrimental impact …

A Comprehensive Analysis Of Smart Ship Systems And Underlying Cybersecurity Issues, Dennis Bothur

Theses : Honours

The maritime domain benefits greatly from advanced technology and ubiquitous connectivity. From “smart” sensors to “augmented reality”, the opportunities to save costs and improve safety are endless. The aim of this dissertation is to study the capabilities of smart ship systems in the context of Internet-of-Things and analyse the potential cybersecurity risks and challenges that smart technologies may introduce into this accelerating digital economy.

The first part of this work investigates the architecture of a “Smart Ship System” and the primary subsystems, including the integrated bridge, navigation and communication systems, networking, operational systems, and sensor networks. The mapping of the …

Web Content Management System And Accessibility Awareness: A Comparative Study Of Novice Users And Accessibility Outcomes, Fatima Artiba Diaz

Theses: Doctorates and Masters

Since its creation, the Web has progressively developed and become a vital source of information in every domain and for almost all people. It is crucial to guarantee that the information contained on the Web is available for everyone, especially for people with special needs. Removing accessibility barriers is fundamentally based on tools, skills and support of all contributors, particularly the content creators, to ensure information is navigable and usable in the context of the end users experience. Web Content Management Systems play a significant role in structuring, storing and provision content to the Web and have evolved to address …

Determining Ground-Level Composition And Concentration Of Particulate Matter Across Regional Areas Using The Himawari-8 Satellite, Miles Sowden

Theses: Doctorates and Masters

Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar orbiting imagers, which means that aerosol is only derived during the daytime, and only once or twice per day.

Sub-hourly, infrared (IR), geostationary …

Iot-Mqtt Based Denial Of Service Attack Modelling And Detection, Naeem Firdous Syed

Theses: Doctorates and Masters

Internet of Things (IoT) is poised to transform the quality of life and provide new business opportunities with its wide range of applications. However, the bene_ts of this emerging paradigm are coupled with serious cyber security issues. The lack of strong cyber security measures in protecting IoT systems can result in cyber attacks targeting all the layers of IoT architecture which includes the IoT devices, the IoT communication protocols and the services accessing the IoT data. Various IoT malware such as Mirai, BASHLITE and BrickBot show an already rising IoT device based attacks as well as the usage of infected …

Deriving Statistical Inference From The Application Of Artificial Neural Networks To Clinical Metabolomics Data, Kevin M. Mendez

Theses: Doctorates and Masters

Metabolomics data are complex with a high degree of multicollinearity. As such, multivariate linear projection methods, such as partial least squares discriminant analysis (PLS-DA) have become standard. Non-linear projections methods, typified by Artificial Neural Networks (ANNs) may be more appropriate to model potential nonlinear latent covariance; however, they are not widely used due to difficulty in deriving statistical inference, and thus biological interpretation. Herein, we illustrate the utility of ANNs for clinical metabolomics using publicly available data sets and develop an open framework for deriving and visualising statistical inference from ANNs equivalent to standard PLS-DA methods.

The Challenges Of Digital Legacy Management On The Value Of Digital Objects To Older Australians, Derani Nathasha Dissanayake

Theses: Doctorates and Masters

People spend a considerable amount of time and money in collecting digital objects. Nine out of ten Australians have a social media account but 83% of them have not discussed with their family members what should happen to their social media accounts when they die (Steen, D’Alessandro, Graves, Perkins, Genders, Barbera, Shi, McGrath & Davis, 2017). Only 3% of Australians who had a Will included social media accounts in their Wills. People collect digital objects yet little attention is paid to their preservation. 71% of Australians are unaware of what happens to their digital assets when they die (Ibid, 2017). …

Projected Sea Level Rise And The Conservation Ecology Of The Micronesian Megapode (Megapodius Laperouse Senex) In Palau, Micronesia, Paul M. Radley

Theses: Doctorates and Masters

Climate change has been a subject of numerous studies. While findings suggest that most biological taxa will be affected by its manifestations, aspects of a species life history may increase its susceptibility to climate change. Given their reliance on environmental sources of heat to incubate their eggs, I examined the vulnerability to climate change of the avian family Megapodiidae. I also assessed habitat use, susceptibility to sea level rise, and the effect of introduced rats and tourist presence, as added stressors to climate change, on the Micronesian Megapode (Megapodius

laperouse senex) in Palau.

Based on available literature, I …

Chemical Composition And Toxicity Of Emissions From Burning Five Vegetation Types Of Western Australia Under Experimental Combustion Conditions, T T Trang Dong

Theses: Doctorates and Masters

This study investigated the emission factors (EFs) for inorganic gases (CO2, CO, SO2, NO and NO2), carbonyls (formaldehyde, acetaldehyde, acetone, propionaldehyde, butyraldehyde and benzaldehyde), volatile organic compounds (VOCs) and particulate matter (PM2.5 and PM10) from laboratory-based fires of vegetation from five typical vegetation types of Western Australia. Species burnt were three grasslands (Spinifex represented by Triodia basedowii, Kimberley grass represented by Sehima nervosum and Heteropogon contortus, and an invasive grass represented by Ehrharta calycina (Veldt grass)), Banksia woodland and Jarrah forest under different combustion conditions. Chemical composition (water-soluble metals and polycyclic aromatic hydrocarbons – PAHs) and in vitro toxicity …

Facial Re-Enactment, Speech Synthesis And The Rise Of The Deepfake, Nicholas Gardiner

Theses : Honours

Emergent technologies in the fields of audio speech synthesis and video facial manipulation have the potential to drastically impact our societal patterns of multimedia consumption. At a time when social media and internet culture is plagued by misinformation, propaganda and “fake news”, their latent misuse represents a possible looming threat to fragile systems of information sharing and social democratic discourse. It has thus become increasingly recognised in both academic and mainstream journalism that the ramifications of these tools must be examined to determine what they are and how their widespread availability can be managed.

This research project seeks to examine …

Anomaly Detection In Bacnet/Ip Managed Building Automation Systems, Matthew Peacock

Theses: Doctorates and Masters

Building Automation Systems (BAS) are a collection of devices and software which manage the operation of building services. The BAS market is expected to be a $19.25 billion USD industry by 2023, as a core feature of both the Internet of Things and Smart City technologies. However, securing these systems from cyber security threats is an emerging research area. Since initial deployment, BAS have evolved from isolated standalone networks to heterogeneous, interconnected networks allowing external connectivity through the Internet. The most prominent BAS protocol is BACnet/IP, which is estimated to hold 54.6% of world market share. BACnet/IP security features are …

Gamma Irradiation Response Of Photonic Crystal And Standard Optical Fibre Bragg Grating Sensors For Radiation Dosimetry, Desmond Baccini

Theses: Doctorates and Masters

This study investigates the use of Optical Fibre Bragg Grating Sensors (FBGs) for Gamma Radiation Dosimetry. A comparative analysis of responses to gamma irradiation between standard commercial FBGs and new generation FBGs written in Photonic Crystal fibre (PCF) were examined under similar regimes and conditions. Current research suggests that the FBGs performance, when exposed to Cobalt-60 gamma irradiation, can suffer cross sensitivity problems resulting from different external effects such as temperature. However, FBGs written in PCFs may be able to overcome these problems due to their design, flexibility of the shape, and size of the micro-holes in a PCF.

Previous …

Learning To Grasp In Unstructured Environments With Deep Convolutional Neural Networks Using A Baxter Research Robot, Shehan Caldera

Theses: Doctorates and Masters

Recent advancements in Deep Learning have accelerated the capabilities of robotic systems in terms of visual perception, object manipulation, automated navigation, and human-robot collaboration. The capability of a robotic system to manipulate objects in unstructured environments is becoming an increasingly necessary skill. Due to the dynamic nature of these environments, traditional methods, that require expert human knowledge, fail to adapt automatically. After reviewing the relevant literature a method was proposed to utilise deep transfer learning techniques to detect object grasps from coloured depth images. A grasp describes how a robotic end-effector can be arranged to securely grasp an object and …

On The Spatial Modelling Of Mixed And Constrained Geospatial Data, Hassan Talebi

Theses: Doctorates and Masters

Spatial uncertainty modelling and prediction of a set of regionalized dependent variables from various sample spaces (e.g. continuous and categorical) is a common challenge for geoscience modellers and many geoscience applications such as evaluation of mineral resources, characterization of oil reservoirs or hydrology of groundwater. To consider the complex statistical and spatial relationships, categorical data such as rock types, soil types, alteration units, and continental crustal blocks should be modelled jointly with other continuous attributes (e.g. porosity, permeability, seismic velocity, mineral and geochemical compositions or pollutant concentration). These multivariate geospatial data normally have complex statistical and spatial relationships which should …

An Investigation Into Trust And Security In The Mandatory And Imposed Use Of Financial Icts Upon Older People, David Michael Cook

Theses: Doctorates and Masters

Care needs to be taken to reduce the number of people who are fearful and mistrustful of using ICT where that usage is forced upon them without choice or alternative. The growing incidence of mandatory and imposed online systems can result in confusion, misuse, fear, and rejection by people with only rudimentary ICT skills. A cohort where a high percentage of such people occur is older people, defined in this study as people over the age of 60 Examples of compulsory ICT interactions include some banks limiting bank statement access through online rather than paper-based options. Other examples include the …

Extraction Of Patterns In Selected Network Traffic For A Precise And Efficient Intrusion Detection Approach, Priya Naran Rabadia

Theses: Doctorates and Masters

This thesis investigates a precise and efficient pattern-based intrusion detection approach by extracting patterns from sequential adversarial commands. As organisations are further placing assets within the cyber domain, mitigating the potential exposure of these assets is becoming increasingly imperative. Machine learning is the application of learning algorithms to extract knowledge from data to determine patterns between data points and make predictions. Machine learning algorithms have been used to extract patterns from sequences of commands to precisely and efficiently detect adversaries using the Secure Shell (SSH) protocol. Seeing as SSH is one of the most predominant methods of accessing systems it …