Digital Commons Network^™

What Do Elevated Background Contaminant Concentrations Mean For Amd Risk Assessment And Management In Western Australia?, Clinton D. Mccullough, J. J Pearce

Research outputs 2014 to 2021

Water quality contaminants include a range of naturally occurring chemicals that can cause degradation of aquatic ecosystem water values when concentration ranges exceed biological tolerances. Both acid and metalliferous drainage (AMD) and acid sulfate soil (ASS) can increase contaminant concentrations through reduced pH and increased solute concentrations especially of toxic metals and metalloids. Water quality guideline criteria are typically used to maintain existing end use value objectives when managing AMD/ASS-affected waters. However, surface and ground waters of catchments comprising mining resources often show elevated solute concentrations in baseline conditions due to their unique geologies. From an AMD and ASS risk …

Mobile Applications For Indian Agriculture Sector: A Case Study, Pratik Shah, Niketa Gandhi, Leisa Armstrong

Research outputs 2014 to 2021

Government, private agencies and the general public are often interested in the decisions made by the Indian farmers as they have large influences beyond the farm boundary. Over many years, the process of adoption of new technologies and policies in the Indian agricultural sector has received considerable academic attention highlighting the role of many social, financial and other influences on their decision making. The Indian government and other development agencies promote income generating projects as a way of encouraging growth through increased agricultural production and the protection of the natural resource base. The impact of new technology to economic growth …

Geospatial Data Pre-Processing On Watershed Datasets: A Gis Approach, Sreedhar Nallan, Leisa Armstrong, Barry Croke, Amiya K. Tripathy

Research outputs 2014 to 2021

Spatial data mining helps to identify interesting patterns from the spatial data sets. However, geo spatial data requires substantial data pre-processing before data can be interrogated further using data mining techniques. Multi-dimensional spatial data has been used to explain the spatial analysis and SOLAP for pre-processing data. This paper examines some of the methods for pre-processing of the data using Arc GIS 10.2 and Spatial Analyst with a case study dataset of a watershed.

A Survey Of Image Processing Techniques For Agriculture, Lalit Saxena, Leisa Armstrong

Research outputs 2014 to 2021

Computer technologies have been shown to improve agricultural productivity in a number of ways. One technique which is emerging as a useful tool is image processing. This paper presents a short survey on using image processing techniques to assist researchers and farmers to improve agricultural practices. Image processing has been used to assist with precision agriculture practices, weed and herbicide technologies, monitoring plant growth and plant nutrition management. This paper highlights the future potential for image processing for different agricultural industry contexts.

Genetic Algorithm With Logistic Regression For Prediction Of Progression To Alzheimer's Disease, Piers Johnson, Luke Vandewater, William Wilson, Paul Maruff, Greg Savage, Petra Graham, Lance S. Macaulay, Kathryn A. Ellis, Cassandra Szoeke, Ralph N. Martins, Christopher Rowe, Colin L. Masters, David Ames, Ping Zhang

Research outputs 2014 to 2021

Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search …

Small To Medium Enterprise Cyber Security Awareness: An Initial Survey Of Western Australian Business, Craig Valli, Ian C. Martinus, Michael N. Johnstone

Research outputs 2014 to 2021

Small to Medium Enterprises (SMEs) represent a large proportion of a nation’s business activity. There are studies and reports reporting the threat to business from cyber security issues resulting in computer hacking that achieve system penetration and information compromise. Very few are focussed on SMEs. Even fewer are focussed on directly surveying the actual SMEs themselves and attempts to improve SME outcomes with respect to cyber security. This paper represents research in progress that outlines an approach being undertaken in Western Australia with SMEs in the northwest metropolitan region of Perth, specifically within the large local government catchments of Joondalup …

Tego - A Framework For Adversarial Planning, Daniel Ashlock, Philip Hingston

Research outputs 2014 to 2021

This study establishes a framework called ∗-Tego for a situation in which two agents are each given a set of players for a competitive game. Each agent places their players in an order. Players on each side at the same position in the order play one another, with the agent's score being the sum of their player's scores. The planning agents are permitted to simultaneous reorder their players in each of several stages. The reordering is termed competitive replanning. The resulting framework is scalable by changing the number of players and the complexity of the replanning process. The framework is …

Cloud Security Meets Telemedicine, Michael N. Johnstone

Research outputs 2014 to 2021

Medical systems are potentially one domain where security is seen as an impediment to patient care and not as an essential part of a system. This is an issue for safety-critical systems where reliability and trust are essential for successful operation. Cloud computing services offer a seamless means to allow medical data to be transferred from patient to medical specialist, whilst maintaining security requirements. This paper uses a case study to investigate the use of cloud computing in a mobile application to assist with diagnostics for patients with Parkinson Disease. It was found that the developers of the app ignored …

Local And Semi-Global Feature-Correlative Techniques For Face Recognition, Asaad Noori Hashim, Zahir Hussain

Research outputs 2014 to 2021

Face recognition is an interesting field of computer vision with many commercial and scientific applications. It is considered as a very hot topic and challenging problem at the moment. Many methods and techniques have been proposed and applied for this purpose, such as neural networks, PCA, Gabor filtering, etc. Each approach has its weaknesses as well as its points of strength. This paper introduces a highly efficient method for the recognition of human faces in digital images using a new feature extraction method that combines the global and local information in different views (poses) of facial images. Feature extraction techniques …

An Information-Theoretic Measure For Face Recognition: Comparison With Structural Similarity, Asmhan Flieh Hassan, Zahir Hussain, Dong Cai-Lin

Research outputs 2014 to 2021

Automatic recognition of people faces is a challenging problem that has received significant attention from signal processing researchers in recent years. This is due to its several applications in different fields, including security and forensic analysis. Despite this attention, face recognition is still one among the most challenging problems. Up to this moment, there is no technique that provides a reliable solution to all situations. In this paper a novel technique for face recognition is presented. This technique, which is called ISSIM, is derived from our recently published information - theoretic similarity measure HSSIM, which was based on joint histogram. …

A Genetic Algorithm-Based Feature Selection, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

This article details the exploration and application of Genetic Algorithm (GA) for feature selection. Particularly a binary GA was used for dimensionality reduction to enhance the performance of the concerned classifiers. In this work, hundred (100) features were extracted from set of images found in the Flavia dataset (a publicly available dataset). The extracted features are Zernike Moments (ZM), Fourier Descriptors (FD), Lengendre Moments (LM), Hu 7 Moments (Hu7M), Texture Properties (TP) and Geometrical Properties (GP). The main contributions of this article are (1) detailed documentation of the GA Toolbox in MATLAB and (2) the development of a GA-based feature …

Editorial - The Changing Face Of Ehealth Security, Patricia Williams, Lizzie Coles-Kemp

Research outputs 2014 to 2021

No abstract provided.

Why Penetration Testing Is A Limited Use Choice For Sound Cyber Security Practice, Craig Valli, Andrew J. Woodward, Peter Hannay, Michael N. Johnstone

Research outputs 2014 to 2021

Penetration testing of networks is a process that is overused when demonstrating or evaluating the cyber security posture of an organisation. Most penetration testing is not aligned with the actual intent of the testing, but rather is driven by a management directive of wanting to be seen to be addressing the issue of cyber security. The use of penetration testing is commonly a reaction to an adverse audit outcome or as a result of being penetrated in the first place. Penetration testing used in this fashion delivers little or no value to the organisation being tested for a number of …

Application Of Cellular Neural Networks And Naive Bayes Classifier In Agriculture, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

This article describes the use of Cellular Neural Networks (a class of Ordinary Differential Equation (ODE)), Fourier Descriptors (FD) and NaiveBayes Classifier (NBC) for automatic identification of images of plant leaves. The novelty of this article is seen in the use of CNN for image segmentation and a combination FDs with NBC. The main advantage of the segmentation method is the computation speed compared with other edge operators such as canny, sobel, Laplacian of Gaussian (LoG). The results herein show the potential of the methods in this paper for examining different agricultural images and distinguishing between different crops and weeds …

A Network That Really Works - The Application Of Artificial Neural Networks To Improve Yield Predictions And Nitrogen Management In Western Australia, Jinsong Leng, Andreas Neuhaus, Leisa Armstrong

Research outputs 2014 to 2021

Yield predictions are notorious for being difficult due to many interdependent factors such as rainfall, soil properties, plant health, plant density etc. This study is based upon the author’s previously published work and extends its findings by further investigating the best mathematical solution to this dilemma. Artificial intelligence (AI) techniques have been applied to a large set of soil, plant, rainfall, and yield data from CSBP’s field research trial program. Here we further differentiate by investigate two ANN techniques, a genetic algorithm with back propagation neural networks (GA-BP-NN) and a particle swarm optimization with back propagation neural networks (PSO-BP-NN). Results …

An Artificial Neural Network For Predicting Crops Yield In Nepal, Tirtha Ranjeet, Leisa Armstrong

Research outputs 2014 to 2021

This paper examines the application of artificial neural networks (ANNs) for predicting crop yields for an agricultural region in Nepal. The neural network algorithm has become an effective data mining tool and the outcome produced by this algorithm is considered to be less error prone than other computer science techniques. The backpropagation algorithm which iteratively finds a suitable weight value is considered for computing the error derivative. Agricultural data was collected from thirteen years from paddy field cultivation in the Siraha district, an eastern region in Nepal, and used for this investigation of neural networks. Additionally, climatic parameters including rainfall, …

Decision Support System Data For Farmer Decision Making, Pornchai Taechatanasat, Leisa Armstrong

Research outputs 2014 to 2021

The capacity of farmers and agricultural scientists to be able to make in-season decisions is dependent on accurate climate, soil and plant data. This paper will provide a review of the types of environmental and crop data that can be collected by sensors which can used for decision support systems (DSS) or be further interrogated for real time data mining and analysis. This paper also presents a review of the data requirements for agricultural decision making by firstly reviewing decision support frameworks and agricultural DSSs, data acquisition, sensors for data acquisition and examples of data incorporation for agricultural DSSs.

Integrating Soil And Plant Tissue Tests And Using An Artificial Intelligence Method For Data Modelling Is Likely To Improve Decisions For In-Season Nitrogen Management, Andreas Neuhaus, Leisa Armstrong, Jinsong Leng, Dean Diepeveen, Geoff Anderson

Research outputs 2014 to 2021

This paper hypothesizes that there is value in combining soil, climate and plant tissue data to give more reliable advice on nitrogen top-ups in-season when compared with models that are currently available. The benefit of soil and climate data is to factor in N mineralisation and potential yield while plant test data is a more direct approach of yield estimates when considering firstly plant N uptake from the whole soil profile and secondly biomass (important yield component). Plant test data are closer to yield in time and space than soil test data, shortening the time period for any yield prognosis …

Are We Approaching Pit Lake Closure From The Wrong Perspective?, Mark A. Lund, Melanie L. Blanchette

Research outputs 2014 to 2021

Pit lakes are similar to natural lakes formed by faulting, glacial action, volcanic action and asteroid collisions. These natural lakes have, after thousands of years, developed into environmentally significant ecosystems. As artificial constructs, pit lakes can be modified prior to filling to enhance lake attributes, such as modification of catchment size, creation of littoral zones and addition of organic matter. Significant advances could be made in successful closure and relinquishment of pit lakes, by 1) choosing appropriate model lakes, 2) understanding successional processes, 3) designing pit lakes to enhance ecological values, and 4) recognizing that it will take time to …

Regulation Of Artisanal Small Scale Gold Mining (Asgm) In Ghana And Indonesia As Currently Implemented Fails To Adequately Protect Aquatic Ecosystems, Karunia F. Macdonald, Mark A. Lund, Melanie L. Blanchette, Clinton D. Mccullough

Research outputs 2014 to 2021

Artisanal small scale gold mining (ASGM) operations are largely unregulated, informal and transient. Rudimentary mining and processing techniques used in ASGM often result in degraded environmental, safety, health and social conditions. ASGM requires permanent sources of water, placing most operations close to natural water bodies. Until recently, the impact on these environments has been largely overlooked, with most studies focussing primarily on mercury contamination and health concerns. Based on Ghanaian and Indonesian experiences, regulation of ASGM is a good step toward improvement, but here we argue that regulation alone is insufficient to improve environmental performance, particularly when the impacts of …

Hybrid Intelligent Model For Software Maintenance Prediction, Abdulrahman Ahmed Bobakr Baqais, Mohammad Alshayeb, Zubair A. Baig

Research outputs 2014 to 2021

Maintenance is an important activity in the software life cycle. No software product can do without undergoing the process of maintenance. Estimating a software’s maintainability effort and cost is not an easy task considering the various factors that influence the proposed measurement. Hence, Artificial Intelligence (AI) techniques have been used extensively to find optimized and more accurate maintenance estimations. In this paper, we propose an Evolutionary Neural Network (NN) model to predict software maintainability. The proposed model is based on a hybrid intelligent technique wherein a neural network is trained for prediction and a genetic algorithm (GA) implementation is used …

Improving Pre-Hospital Care At Mass Gathering Events: Applying Military Intelligence Methodology To The St John Ambulance Wa Event Health Operations, Alan James Davies

Theses : Honours

With the growth of the mass gathering event domain and its ever constant place within the contemporary Australian lifestyle, the number of patrons who attend these events that require medical assistance rises (Zeitz et al., 2007, p. 23; Zeitz, Zeitz, & Arbon, 2005, p. 164; Zeitz, Zeitz, & Kadow-Griffin, 2012). This increased demand and inherited risk to the event organiser, the patrons attending and the pre-hospital care or first aid provider creates a need for the investigation into enhancements to the medical care operations at these events. The provision of pre-hospital care at mass gathering events in Western Australia is …

Western Australian Graduate Diploma Of Education (Primary) Students' Perceptions Of Sustainability, Judith Clare Odgaard

Theses: Doctorates and Masters

In late 2011, the researcher investigated a cohort of Western Australian (WA) Graduate Diploma of Education Primary (GDE-P) students’ perceptions of Sustainability across a broad range of biophysical/natural, social and cultural, economic and political spheres. The study occurred during the seventh year of UNESCO’s Decade of Education for Sustainability Development, and when Sustainability Education became one of three cross-curriculum priorities of the new Australian Curriculum. Importantly, the students’ perceptions were interpreted during the context of the Post Global Financial Crisis and after Julia Gillard replaced Kevin Rudd as the Labor Prime Minister. The intense political context was often supported by …

A Preliminary Investigation Of The Potential Effects Of The Invasive Mozambique Tilapia Oreochromis Mossambicus On The Native Fish Assemblages Of Lake Macleod, Western Australia, Hannah Cameron-Caluori

Theses: Doctorates and Masters

As one of the major threats to biodiversity in aquatic systems, invasive species can alter the structure and function of a community, often through habitat and resource competition, and/or direct predation. This study aims to determine if invasive tilapia (Oreochromis mossambicus) is likely to have an effect on the native fish communities of Lake MacLeod, a unique and important inland, saline lake system in north-western Western Australia, through competition for key resources, namely habitat and food sources. Seven study sites were selected within the Northern Ponds of Lake MacLeod, from which fish abundances were assessed in three habitats …

Bio-Inspired Surface Engineering For Hydrophobicity, Hua Guo

Theses: Doctorates and Masters

Highly evolved, efficient and sophisticated biological systems can be used as models for scientific innovations. This research explored specific surface structures on plant leaves with respect to their hydrophobicity in the context of the often arid Australian climate. The relationships between leaf surface structures and their hydrophobicity could inform the making of artificial surfaces with specially designed hydrophobicity.

Moderate hydrophobicity and strong surface adhesion were discovered on many study plant leaves. Scanning Electron Microscopy (SEM) revealed that their surface morphologies could be categorized into four groups while their water-repellent mechanisms were considered at an individual species level. Specifically, physical models …