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Articles 31 - 60 of 70
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Unravelling Ecological Analysis, David Steel, Mark Tranmer, D Holt
Unravelling Ecological Analysis, David Steel, Mark Tranmer, D Holt
Professor David Steel
No abstract provided.
A Comparison Of Analysis Methods For Late-Stage Variety Evaluation Trials, Sue Welham, Beverley Gogel, Alison Smith, Robin Thompson, Brian Cullis
A Comparison Of Analysis Methods For Late-Stage Variety Evaluation Trials, Sue Welham, Beverley Gogel, Alison Smith, Robin Thompson, Brian Cullis
Dr Alison Smith
The statistical analysis of late-stage variety evaluation trials using a mixed model is described, with one- or two-stage approaches to the analysis. Two sets of trials, from Australia and the UK, were used to provide realistic scenarios for a simulation study to evaluate the different methods of analysis. This study showed that a one-stage approach gave the most accurate predictions of variety performance overall or within each environment, across a range of models, as measured by mean squared error of prediction or realized genetic gain. A weighted two-stage approach performed adequately for variety predictions both overall and within environments, but …
Enhanced Diagnostics For The Spatial Analysis Of Field Trials, Katia Stefanova, Alison Smith, Brian Cullis
Enhanced Diagnostics For The Spatial Analysis Of Field Trials, Katia Stefanova, Alison Smith, Brian Cullis
Dr Alison Smith
We report an analysis of a series of uniformity field trials using the technique proposed by Gilmour, Cullis, and Verbyla. In particular, we clarify the role of the sample variogram and present a range of enhanced graphical diagnostics to aid the spatial modeling process.We highlight the implications of the presence of extraneous variation related to commonly used agronomic practices, such as serpentine harvesting.
Towards Knowledge Management In Sports Event Management: Context Analysis Of Malaysian Biannual Games With Commonkads, Azizul Abdul Ghaffar, Ghassan Beydoun, Jun Shen, William Tibben
Towards Knowledge Management In Sports Event Management: Context Analysis Of Malaysian Biannual Games With Commonkads, Azizul Abdul Ghaffar, Ghassan Beydoun, Jun Shen, William Tibben
Dr Jun Shen
Context Analysis (CA) is typically used as an early phase preceding the development of a knowledge-based systems in order to indicate how the system should interact with its environment and the various stakeholders. We undertake a detailed context analysis of business processes of the Malaysian Games (MG)to highlight blind spots of the process and enable the identification of an initial sports event knowledge management (KM) framework. Firstly, our CommonKADS driven analysis highlights how we can improve the business process and enable the organization to develop, distribute and apply its knowledge resources effectively. Secondly, the paper highlights specific features about the …
Research Methods And The Relevance Of The Is Discipline: A Critical Analysis Of The Role Of Methodological Pluralism, Rajeev Sharma
Research Methods And The Relevance Of The Is Discipline: A Critical Analysis Of The Role Of Methodological Pluralism, Rajeev Sharma
Associate Professor Rajeev Sharma
No abstract provided.
Fault Analysis Of The Katan Family Of Block Ciphers, Shekh Faisal Abdul-Latip, Mohammad Reza Reyhanitabar, Willy Susilo, Jennifer Seberry
Fault Analysis Of The Katan Family Of Block Ciphers, Shekh Faisal Abdul-Latip, Mohammad Reza Reyhanitabar, Willy Susilo, Jennifer Seberry
Dr Reza Reyhanitabar
In this paper, we investigate security of the KATAN family of block ciphers against differential fault attacks. KATAN consists of three variants with 32, 48 and 64-bit block sizes, called KATAN32, KATAN48 and KATAN64, respectively. All three variants have the same key length of 80 bits. We assume a single-bit fault injection model where the adversary is supposed to be able to corrupt a single random bit of the internal state of the cipher and this fault induction process can be repeated (by resetting the cipher); i.e., the faults are transient rather than permanent. First, we show how to identify …
Evaluating Participatory Modeling: Developing A Framework For Cross-Case Analysis. Socio-Economics And The Environment In Discussion (Seed), Natalie A. Jones, Pascal Perez, Thomas G. Measham, Gail J. Kelly, Patrick D'Aquino, Katherine Daniell, Anne Dray, Nils Ferrand
Evaluating Participatory Modeling: Developing A Framework For Cross-Case Analysis. Socio-Economics And The Environment In Discussion (Seed), Natalie A. Jones, Pascal Perez, Thomas G. Measham, Gail J. Kelly, Patrick D'Aquino, Katherine Daniell, Anne Dray, Nils Ferrand
Professor Pascal Perez
Participatory modeling is increasingly recognised as an effective way to assist collective decision-making processes in the domain of natural resource management. This paper introduces a framework for evaluating projects that have adopted a participatory modeling approach. This framework – known as the ‘Protocol of Canberra’ – was developed through a collaboration between French and Australian researchers engaged in participatory modeling and evaluation research. The framework seeks to assess the extent to which different participatory modeling practices reinforce or divert from the theoretical assumptions they are built upon. The paper discusses the application of the framework in three case-studies, two from …
Power Quality Survey Factor Analysis Using Multivariable Linear Regression (Mvlr), Chandana Herath, Victor J. Gosbell, Sarath Perera, David A. Stirling
Power Quality Survey Factor Analysis Using Multivariable Linear Regression (Mvlr), Chandana Herath, Victor J. Gosbell, Sarath Perera, David A. Stirling
Associate Professor Sarath Perera
During the past two decades, there has been a considerable number of Power Quality (PQ) monitoring programs completed throughout the world. The information collected during these surveys can provide a detailed picture of the expected electrical environment help utilities to plan their future networks in relation to power quality performance. The mass of data gathered for a sample of sites of a large-scale power quality (PQ) survey of this nature has the potential to reveal good and bad influences on power quality if an appropriate procedure for analysis can be determined. If it is known which characteristics are more important …
Power Quality Data Analysis Using Unsupervised Data Mining, Ali Asheibi, David A. Stirling, Sarath Perera, D A. Robinson
Power Quality Data Analysis Using Unsupervised Data Mining, Ali Asheibi, David A. Stirling, Sarath Perera, D A. Robinson
Associate Professor Sarath Perera
The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Data mining is a process that uses a variety of data analysis tools to identify hidden patterns and relationships within large samples of data. This paper presents several data mining tools and techniques that are applicable to power quality data analysis to enable efficient reporting of disturbance indices and identify network problems through pattern recognition. This paper also presents results of data mining techniques applied …
Dynamic Modelling Of Hydroelectric Turbine-Generator Unit Connected To A Hvdc System For Small Signal Stability Analysis, Yin Chin Choo, Ashish P. Agalgaonkar, Kashem Muttaqi, Sarath Perera, Michael Negnevitsky
Dynamic Modelling Of Hydroelectric Turbine-Generator Unit Connected To A Hvdc System For Small Signal Stability Analysis, Yin Chin Choo, Ashish P. Agalgaonkar, Kashem Muttaqi, Sarath Perera, Michael Negnevitsky
Associate Professor Sarath Perera
This paper presents the linearised small-signal dynamic modelling of hydroelectric turbine-generator (TG) unit with CIGRE first high-voltage direct current (HVDC) benchmark system in the synchronously rotating D-Q reference frame for small-signal stability analysis. The interaction behaviour between the hydroelectric unit and the dynamics and control of HVDC system is investigated utilising eigen-analysis,participation factor analysis and by conducting sensitivity studies. The computation of eigenvalues and eigenvectors for small signal stability analysis provides an invaluable insight onto the power system dynamic behaviour by characterising the damping and frequency of the system oscillatory modes. Theconsequences of different operating conditions, such as active and …
The Analysis Of Utility Voltage Sag Data, Victor Gosbell, D Robinson, Sarath Perera
The Analysis Of Utility Voltage Sag Data, Victor Gosbell, D Robinson, Sarath Perera
Associate Professor Sarath Perera
No abstract provided.
Texture Analysis Using Gabor Wavelets, Golshah Naghdy, Jianli Wang, Philip Ogunbona
Texture Analysis Using Gabor Wavelets, Golshah Naghdy, Jianli Wang, Philip Ogunbona
Associate Professor Golshah Naghdy
Receptive field profiles of simple cells in the visual cortex have been shown to resemble even- symmetric or odd-symmetric Gabor filters. Computational models employed in the analysis of textures have been motivated by two-dimensional Gabor functions arranged in a multi-channel architecture. More recently wavelets have emerged as a powerful tool for non-stationary signal analysis capable of encoding scale-space information efficiently. A multi-resolution implementation in the form of a dyadic decomposition of the signal of interest has been popularized by many researchers. In this paper, Gabor wavelet configured in a 'rosette' fashion is used as a multi-channel filter-bank feature extractor for …
Assessment Of Distributed Generation Impacts On Distribution Networks Using Unbalanced Three-Phase Power Flow Analysis, Md Jan-E- Alam, Kashem Muttaqi, Danny Sutanto
Assessment Of Distributed Generation Impacts On Distribution Networks Using Unbalanced Three-Phase Power Flow Analysis, Md Jan-E- Alam, Kashem Muttaqi, Danny Sutanto
Associate Professor Kashem Muttaqi
Impacts of Distributed Generation (DG) resources on distribution networks have been studied. A Newton-Raphson algorithm based three phase unbalance power flow program has been developed to incorporate the effects of system unbalance and single phase DG injection. Power flow equations have been formulated and solved in phase coordinated form. Effects of substation load-tap changer, voltage regulator, shunt capacitor and different type of load models have been considered in the development of the program. Phase asymmetry of distribution networks has been treated by modifying the Jacobian matrix. The proposed technique has been tested on IEEE 34 bus distribution test system for …
Dynamic Modelling Of Hydroelectric Turbine-Generator Unit Connected To A Hvdc System For Small Signal Stability Analysis, Yin Chin Choo, Ashish Agalgaonkar, Kashem Muttaqi, Sarath Perera, Michael Negnevitsky
Dynamic Modelling Of Hydroelectric Turbine-Generator Unit Connected To A Hvdc System For Small Signal Stability Analysis, Yin Chin Choo, Ashish Agalgaonkar, Kashem Muttaqi, Sarath Perera, Michael Negnevitsky
Associate Professor Kashem Muttaqi
This paper presents the linearised small-signal dynamic modelling of hydroelectric turbine-generator (TG) unit with CIGRE first high-voltage direct current (HVDC) benchmark system in the synchronously rotating D-Q reference frame for small-signal stability analysis. The interaction behaviour between the hydroelectric unit and the dynamics and control of HVDC system is investigated utilising eigen-analysis,participation factor analysis and by conducting sensitivity studies. The computation of eigenvalues and eigenvectors for small signal stability analysis provides an invaluable insight onto the power system dynamic behaviour by characterising the damping and frequency of the system oscillatory modes. Theconsequences of different operating conditions, such as active and …
Further Analysis Of A Practical Hierarchical Identity-Based Encryption Scheme, Ying Sun, Yong Yu, Yi Mu
Further Analysis Of A Practical Hierarchical Identity-Based Encryption Scheme, Ying Sun, Yong Yu, Yi Mu
Professor Yi Mu
No abstract provided.
Hierarchical Model Building, Fitting, And Checking: A Behind-The-Scenes Look At A Bayesian Analysis Of Arsenic Exposure Pathways, Peter F. Craigmile, Catherine A. Calder, Hongfei Li, Rajib Paul, Noel Cressie
Hierarchical Model Building, Fitting, And Checking: A Behind-The-Scenes Look At A Bayesian Analysis Of Arsenic Exposure Pathways, Peter F. Craigmile, Catherine A. Calder, Hongfei Li, Rajib Paul, Noel Cressie
Professor Noel Cressie
In this article, we present a behind-the-scenes look at a Bayesian hierarchical analysis of pathways of exposure to arsenic (a toxic heavy metal) using the Phase I National Human Exposure Assessment Survey carried out in Arizona. Our analysis combines individual-level personal exposure measurements (biomarker and environmental media) with water, soil, and air observations from the ambient environment. We include details of our model-building exercise that involved a combination of exploratory data analysis and substantive knowledge in exposure science. Then we present our strategies for model fitting, which involved piecing together components of the hierarchical model in a systematic fashion to …
Accounting For Uncertainty In Ecological Analysis: The Strengths And Limitations Of Hierarchical Statistical Modeling, Noel Cressie, Catherine Calder, James Clark, Jay Ver Hoef, Christopher Wikle
Accounting For Uncertainty In Ecological Analysis: The Strengths And Limitations Of Hierarchical Statistical Modeling, Noel Cressie, Catherine Calder, James Clark, Jay Ver Hoef, Christopher Wikle
Professor Noel Cressie
Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple …
Security Analysis Of Michael: The Ieee 802.11i Message Integrity Code, Jianyong Huang, Jennifer Seberry, Willy Susilo, Martin W. Bunder
Security Analysis Of Michael: The Ieee 802.11i Message Integrity Code, Jianyong Huang, Jennifer Seberry, Willy Susilo, Martin W. Bunder
Dr Martin Bunder
The latest IEEE 802.11i uses a keyed hash function, called Michael, as the message integrity code. This paper describes some properties and weaknesses of Michael. We provide a necessary and sufficient condition for finding collisions of Michael. Our observation reveals that the collision status of Michael only depends on the second last block message and the output of the block function in the third last round. We show that Michael is not collision-free by providing a method to find collisions of this keyed hash function. Moreover, we develop a method to find fixed points of Michael. If the output of …
The Analysis Of Pattern Change In Intron Sequences, Jinda Kongcharoen, Yan-Xia Lin, Rachel Caldwell, Yiren Yang, Ren Zhang
The Analysis Of Pattern Change In Intron Sequences, Jinda Kongcharoen, Yan-Xia Lin, Rachel Caldwell, Yiren Yang, Ren Zhang
Associate Professor Yan-Xia Lin
The Generalized Bernoulli Modeling approach is used to analyze the pattern change in intron sequences of a model plant species Arabidopsis thaliana. The influence of the intron length and the number of GC on the intron sequence pattern changes is examined. Two other gene properties, the gene expression level and the protein function encoded are also assessed. Among the random sampled intron sequences,10.71% of them have been identified to have sequence pattern change. Our study shows that the number of GC and the intron length significantly influence the intron pattern change while the gene expression level and the protein function …
Automated Change Impact Analysis For Agent Systems, Aditya Ghose, Hoa Dam
Automated Change Impact Analysis For Agent Systems, Aditya Ghose, Hoa Dam
Dr Hoa Dam
Intelligent agent technology has evolved rapidly over the past few years along with the growing number of agent systems in various domains. Although a substantial amount of work in agent-oriented software engineering has provided methodologies for analysing, designing and implementing agent-based systems, recent studies have highlighted that there has been very little work on maintenance and evolution of agent-based systems. A critical issue in software maintenance and evolution is change impact analysis: determining the potential consequences of a proposed change. There has been a proliferation of techniques proposed to support change impact analysis of procedural or object-oriented systems, but to …
Multivariate Whole Genome Average Interval Mapping: Qtl Analysis For Multiple Traits And/Or Environments, Arunas P. Verbyla, Brian R. Cullis
Multivariate Whole Genome Average Interval Mapping: Qtl Analysis For Multiple Traits And/Or Environments, Arunas P. Verbyla, Brian R. Cullis
Professor Brian Cullis
A major aim in some plant-based studies is the determination of quantitative trait loci (QTL) for multiple traits or across multiple environments. Understanding these QTL by trait or QTL by environment interactions can be of great value to the plant breeder. A whole genome approach for the analysis of QTL is presented for such multivariate applications. The approach is an extension of whole genome average interval mapping in which all intervals on a linkage map are included in the analysis simultaneously. A random effects working model is proposed for the multivariate (trait or environment) QTL effects for each interval, with …
The Analysis Of Longitudinal Data Using Mixed Model L-Splines, S. Welham, Brian Cullis, M. Kenward, R Thompson
The Analysis Of Longitudinal Data Using Mixed Model L-Splines, S. Welham, Brian Cullis, M. Kenward, R Thompson
Professor Brian Cullis
L-splines are a large family of smoothing splines defined in terms of a linear differential operator. This article develops L-splines within the context of linear mixed models and uses the resulting mixed model L-spline to analyze longitudinal data from a grassland experiment. In the spirit of time-series analysis, a periodic mixed model L-spline is developed, which partitions data into a smooth periodic component plus smooth long-term trend.
A Comparison Of Analysis Methods For Late-Stage Variety Evaluation Trials, Sue Welham, Beverley Gogel, Alison Smith, Robin Thompson, Brian Cullis
A Comparison Of Analysis Methods For Late-Stage Variety Evaluation Trials, Sue Welham, Beverley Gogel, Alison Smith, Robin Thompson, Brian Cullis
Professor Brian Cullis
The statistical analysis of late-stage variety evaluation trials using a mixed model is described, with one- or two-stage approaches to the analysis. Two sets of trials, from Australia and the UK, were used to provide realistic scenarios for a simulation study to evaluate the different methods of analysis. This study showed that a one-stage approach gave the most accurate predictions of variety performance overall or within each environment, across a range of models, as measured by mean squared error of prediction or realized genetic gain. A weighted two-stage approach performed adequately for variety predictions both overall and within environments, but …
The Design And Analysis Of Multi-Phase Plant Breeding Experiments, A B. Smith, P Lim, Brian R. Cullis
The Design And Analysis Of Multi-Phase Plant Breeding Experiments, A B. Smith, P Lim, Brian R. Cullis
Professor Brian Cullis
Despite the importance of selection for quality characteristics in plant improvement programmes, literature on experimental design and statistical analysis for these traits is scarce. Most quality traits are obtained from multi-phase experiments in which plant varieties are first grown in a field trial then further processed in the laboratory. In the present paper a general mixed model approach for the analysis of multi-phase data is described, with particular emphasis on quality trait data that are often highly unbalanced and involve substantial sources of non-genetic variation and correlation. Also detailed is a new approach for experimental design that employs partial replication …
The Analysis Of Qtl By Simultaneous Use Of The Full Linkage Map, A. Verbyla, Brian Cullis, R Thompson
The Analysis Of Qtl By Simultaneous Use Of The Full Linkage Map, A. Verbyla, Brian Cullis, R Thompson
Professor Brian Cullis
An extension of interval mapping is presented that incorporates all intervals on the linkage map simultaneously. The approach uses a working model in which the sizes of putative QTL for all intervals across the genome are random effects. An outlier detection method is used to screen for possible QTL. Selected QTL are subsequently fitted as fixed effects. This screening and selection approach is repeated until the variance component for QTL sizes is not statistically significant. A comprehensive simulation study is conducted in which map uncertainty is included. The proposed method is shown to be superior to composite interval mapping in …
Analysis Of Yield And Oil From A Series Of Canola Breeding Trials. Part I. Fitting Factor Analytic Mixed Models With Pedigree Information, C Beeck, W Cowling, A Smith, Brian Cullis
Analysis Of Yield And Oil From A Series Of Canola Breeding Trials. Part I. Fitting Factor Analytic Mixed Models With Pedigree Information, C Beeck, W Cowling, A Smith, Brian Cullis
Professor Brian Cullis
In this paper multiplicative mixed models have been used for the analysis of multi-environment trial (MET) data for canola oil and grain yield. Information on pedigrees has been included to allow for the modelling of additive and nonadditive genetic effects. The MET data set included a total of 19 trials (synonymous with sites or environments), which were sown across southern Australia in 2007 and 2008. Each trial was designed as a p-rep design using DiGGeR with the default prespecified spatial model. Lines in their first year of testing were unreplicated, whereas there were two or three replications of advanced …
The Analysis Of Crop Cultivar Breeding And Evaluation Trials: An Overview Of Current Mixed Model Approaches, A Smith, Brian Cullis, R Thompson
The Analysis Of Crop Cultivar Breeding And Evaluation Trials: An Overview Of Current Mixed Model Approaches, A Smith, Brian Cullis, R Thompson
Professor Brian Cullis
The analysis of series of crop variety trials has a long history with the earliest approaches being based on ANOVA methods. Kempton (1984) discussed the inadequacies of this approach, summarized the alternatives available at that time and noted that all of these approaches could be classified as multiplicative models. Recently, mixed model approaches have become popular for the analysis of series of variety trials. There are numerous reasons for their use, including the ease with which incomplete data (not all varieties in all trials) can be handled and the ability to appropriately model within-trial error variation. Currently, the most common …
Enhanced Diagnostics For The Spatial Analysis Of Field Trials, Katia Stefanova, Alison Smith, Brian Cullis
Enhanced Diagnostics For The Spatial Analysis Of Field Trials, Katia Stefanova, Alison Smith, Brian Cullis
Professor Brian Cullis
We report an analysis of a series of uniformity field trials using the technique proposed by Gilmour, Cullis, and Verbyla. In particular, we clarify the role of the sample variogram and present a range of enhanced graphical diagnostics to aid the spatial modeling process.We highlight the implications of the presence of extraneous variation related to commonly used agronomic practices, such as serpentine harvesting.
Analysis Of Economic Data Collected In Farm Surveys, Raymond Chambers, Phillip Kokic, Nhu Che
Analysis Of Economic Data Collected In Farm Surveys, Raymond Chambers, Phillip Kokic, Nhu Che
Dr Raymond Chambers
No abstract provided.
Regression Analysis Under Incomplete Linkage, Gunky Kim, Raymond Chambers
Regression Analysis Under Incomplete Linkage, Gunky Kim, Raymond Chambers
Dr Raymond Chambers
Most probability-based methods used to link records from two distinct data sets corresponding to the same target population do not lead to perfect linkage, i.e. there are linkage errors in the merged data. Further, the linkage is often incomplete, in the sense that many records in the two data sets remain unmatched at the completion of the linkage process. This paper introduces methods that correct for the biases due to linkage errors and incomplete linkage when carrying out regression analysis using linked data. In particular, it focuses on the case where one of the linked data sets is a sample …