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- Publication
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- Associate Professor Yan-Xia Lin (2)
- Dr Fenghui Ren (2)
- Dr Montserrat Ros (2)
- Adam Trevitt (1)
- Alexandra Burden, Lecturer, School of Mathematics and Applied Statistics, Faculty of Informatics (1)
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- Associate Professor Ghassan Beydoun (1)
- Associate Professor Golshah Naghdy (1)
- Associate Professor Kashem Muttaqi (1)
- Associate Professor Wanqing Li (1)
- B. G. Jones (1)
- Dr Koren Ward (1)
- Dr Muawiyath Shujau (1)
- Dr Peter Vial (1)
- Dr Raymond Chambers (1)
- Dr Sim Kim Lau (1)
- Dr Yanguang Yu (1)
- Joshua P Fan (1)
- Professor David Steel (1)
- Professor Philip Ogunbona (1)
- Professor Salim Bouzerdoum (1)
- Richard G Roberts (1)
Articles 1 - 24 of 24
Full-Text Articles in Physical Sciences and Mathematics
Branching Fractions Of The Cn + C3h6 Reaction Using Synchrotron Photoionization Mass Spectrometry: Evidence For The 3-Cyanopropene Product, Adam Trevitt, Talitha Selby, Craig Taatjes, Satchin Soorkia, J Savee, D L Osborn, S R Leone
Branching Fractions Of The Cn + C3h6 Reaction Using Synchrotron Photoionization Mass Spectrometry: Evidence For The 3-Cyanopropene Product, Adam Trevitt, Talitha Selby, Craig Taatjes, Satchin Soorkia, J Savee, D L Osborn, S R Leone
Adam Trevitt
The gas-phase CN + propene reaction is investigated using synchrotron photoionization mass spectrometry (SPIMS) over the 9.8 - 11.5 eV photon energy range. Experiments are conducted at room temperature in 4 Torr of He buffer gas. The CN + propene addition reaction produces two distinct product mass channels, C3H3N and C4H5N, corresponding to CH3 and H elimination, respectively. The CH3 and H elimination channels are measured to have branching fractions of 0.59 + 0.15 and 0.41 + 0.10, respectively. The absolute photoionization cross sections between 9.8 and 11.5 eV are measured for the three considered H-elimination coproducts: 1-, 2-, and …
Reconstructing Recent Sedimentation In Two Urbanised Coastal Lagoons (Nsw, Australia) Using Radioisotopes And Geochemistry, Brian Jones, H Heijnis, J. Harrison, Suzanne Hollins, S Hankin, Atun Zawadzki
Reconstructing Recent Sedimentation In Two Urbanised Coastal Lagoons (Nsw, Australia) Using Radioisotopes And Geochemistry, Brian Jones, H Heijnis, J. Harrison, Suzanne Hollins, S Hankin, Atun Zawadzki
B. G. Jones
In this study, we combined grain size and geochemical analyses with radioisotope analysis of lead-210 (210Pb), caesium-137 (137Cs) and radiocarbon (14C) ages to reconstruct the sedimentation history of two urbanised coastal lagoons in south-east Australia. Towradgi and Fairy Lagoons were both found to exhibit slow initial sedimentation of less than 1 mm year-1 prior to anthropogenic influences. Land clearing in the catchments increased runoff and erosion in the creeks feeding into the estuaries, and has resulted in progradation of fluvial material into the estuarine systems with a marked increase in sedimentation to between 2 and 7 mm year-1. The upper …
A Dual-Aliquot Regenerative-Dose Protocol (Dap) For Thermoluminescence (Tl) Dating Of Quartz Sediments Using The Light-Sensitive And Isothermally Stimulated Red Emissions, Richard Roberts, Kira Westaway
A Dual-Aliquot Regenerative-Dose Protocol (Dap) For Thermoluminescence (Tl) Dating Of Quartz Sediments Using The Light-Sensitive And Isothermally Stimulated Red Emissions, Richard Roberts, Kira Westaway
Richard G Roberts
No abstract provided.
A Dynamic Platform For Business Process Management (Bpm) Using Service-Oriented Enterprise (Soe), Nantika Prinyapol, Joshua Fan, Sim Lau
A Dynamic Platform For Business Process Management (Bpm) Using Service-Oriented Enterprise (Soe), Nantika Prinyapol, Joshua Fan, Sim Lau
Joshua P Fan
No abstract provided.
Fitness Evaluation For Structural Optimisation Genetic Algorithms Using Neural Networks, Koren Ward, Timothy Mccarthy
Fitness Evaluation For Structural Optimisation Genetic Algorithms Using Neural Networks, Koren Ward, Timothy Mccarthy
Dr Koren Ward
This paper relates to the optimisation of structural design using Genetic Algorithms (GAs) and presents an improved method for determining the fitness of genetic codes that represent possible design solutions by using a neural network to generalize fitness. Two problems that often impede design optimization using genetic algorithms are expensive fitness evaluation and high epistasis. In this paper we show that by using a neural network as a fitness approximator, optimal solutions to certain design problems can be achieved in significantly less generations and with considerably less fitness evaluations.
Separation Of Speech Sources Using An Acoustic Vector Sensor, Ian Burnett, Christian Ritz, Muawiyath Shujau
Separation Of Speech Sources Using An Acoustic Vector Sensor, Ian Burnett, Christian Ritz, Muawiyath Shujau
Dr Muawiyath Shujau
This paper investigates how the directional characteristics of an Acoustic Vector Sensor (AVS) can be used to separate speech sources. The technique described in this work takes advantage of the frequency domain direction of arrival estimates to identify the location, relative to the AVS array, of each individual speaker in a group of speakers and separate them accordingly into individual speech signals. Results presented in this work show that the technique can be used for real-time separation of speech sources using a single 20ms frame of speech, furthermore the results presented show that there is an average improvement in the …
Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li
Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li
Associate Professor Wanqing Li
An approach to the problem of illumination variations in face detection that uses classifier fusion is presented. Multiple face detectors are seperately trained for different illumination environments and their results are combined using a combination rule. To define the illumination environments, the training samples are clustered based on their illumination using unsupervised training. Different methods of clustering the samples and combining the outputs of the classifiers are examined. Experiments with the AR face database show that the proposed method achieves higher accuracy than the traditional monolithic face detection method.
Design Of A P2p Information Sharing Mas Using Mobmas, Numi Tran, Ghassan Beydoun, Graham Low
Design Of A P2p Information Sharing Mas Using Mobmas, Numi Tran, Ghassan Beydoun, Graham Low
Associate Professor Ghassan Beydoun
Most existing agent-oriented methodologies ignore system extensibility, interoperability and reusability issues. In light of this, we have developed MOBMAS – a “Methodology for Ontology-Based MASs” which makes use of ontologies as a central modeling tool, utilising their roles in facilitating interoperability and reusability. As part of an ongoing validation of MOBMAS, we demonstrate in this paper its use on a peer-to-peer (P2P) community-based information sharing application. MOBMAS is used by an experienced software developer, who is not an author of the methodology, to guide the development of the P2P application.
A Data-Fitting Approach For Displacements And Vibration Measurement Using Self-Mixing Interferometers, Yi Zhang, Jiangtao Xi, Joe Chicharo, Yanguang Yu
A Data-Fitting Approach For Displacements And Vibration Measurement Using Self-Mixing Interferometers, Yi Zhang, Jiangtao Xi, Joe Chicharo, Yanguang Yu
Dr Yanguang Yu
This paper presents a signal processing approach for vibration measurement using self-mixing interferometer (SMI). Compared to existing approaches, the proposed approach is able to achieve an accuracy of λ/40 which significantly exceeds the accuracy limit associated with conventional simple SMI systems λ/4.
Design And Simulation Of A Ds-Th-Uwb System Using Simulink/Matlab For First Arriving Rays In A Non Line Of Sight Wireless Scenario, Peter Vial
Dr Peter Vial
An Ultra Wideband system was developed using Simulink in previous work. Using this developed model for Ultra Wideband (UWB) Pulse Position Modulation (PPM) within Simulink, we apply Direct Sequence Walsh codes across Time Hopping Patterns to smooth out the spectral characteristics with Pulse Position Modulation. A non-line of sight Saleh-Valenzuela (SV) model is used to characterize the wireless channel. The system is described and results are presented for the scenario where the first arriving rays are used to detect the transmitted message. For this non-optimum technique (in that for non line of sight the strongest signal rays are available after …
Seasonal Adjustment Of An Aggregate Series Using Univariate And Multivariate Basic Structural Models, David Steel, Yan-Xia Lin, Carole Birrell
Seasonal Adjustment Of An Aggregate Series Using Univariate And Multivariate Basic Structural Models, David Steel, Yan-Xia Lin, Carole Birrell
Professor David Steel
Time series resulting from aggregation of several sub-series can be seasonally adjusted directlyor indirectly. With model-based seasonal adjustment, the sub-series may also be considered as amultivariate system of series and the analysis may be done jointly. This approach has considerableadvantage over the indirect method, as it utilises the covariance structure between the sub-series.This paper compares a model-based univariate and multivariate approach to seasonal adjustment.Firstly, the univariate basic structural model (BSM) is applied directly to the aggregate series. Secondly,the multivariate BSM is applied to a transformed system of sub-series. The prediction meansquared errors of the seasonally adjusted aggregate series resulting from …
A Wireless Sensor Node Architecture Using Remote Power Charging, For Interaction Applications, Matthew D'Souza, Konstanty Bialkowski, Adam Postula, Montserrat Ros
A Wireless Sensor Node Architecture Using Remote Power Charging, For Interaction Applications, Matthew D'Souza, Konstanty Bialkowski, Adam Postula, Montserrat Ros
Dr Montserrat Ros
The wireless sensor node architecture proposed inthis paper is optimized for use in a wireless interactivepoint, listen and see system. In particular, we focus ondeveloping a wireless sensor node that can beremotely charged by harvesting microwave energy.The current system implementation allows a user toaccess information from a remote sensor via theirmobile computing device. These sensors are limited incomplexity due to the limited power available, and arecumbersome since manual intervention is required toreplace its batteries. We propose a system wherebattery powered wireless sensor nodes can berecharged by harvesting energy from a microwaveRadio Frequency (RF) signal source. The remotepower charging module of …
Biometric Monitoring Of Footstep And Heart Rate Using Wireless Inertial Sensors, Montserrat Ros, Matthew D'Souza, Matthew Wallace
Biometric Monitoring Of Footstep And Heart Rate Using Wireless Inertial Sensors, Montserrat Ros, Matthew D'Souza, Matthew Wallace
Dr Montserrat Ros
Inertial sensors are widely used for a variety of biomedicalapplications, such as human activity monitoring. We present awireless biomedical monitoring network used for measuringfootstep parameters and the heart rate of a person. The wirelessbiomedical monitoring network uses inertial sensors to recordand monitor heart rate and consists of multiple monitoringnodes placed on a person, that communicate with a base node.The monitoring nodes placed on a person&¿s ankle measure theacceleration generated during a footstep. By analysing thisdata, we are able to determine the average footstep length andwalking velocity to be 80cm and the average walking speed tobe 1m/s which corresponds to results …
Partners Selection In Multi-Agent Systems By Using Linear And Non-Linear Approaches, Minjie Zhang, Fenghui Ren
Partners Selection In Multi-Agent Systems By Using Linear And Non-Linear Approaches, Minjie Zhang, Fenghui Ren
Dr Fenghui Ren
No abstract provided.
Using Colored Petri Nets To Predict Future States In Agent-Based Scheduling And Planning Systems, Minjie Zhang, John Fulcher, Quan Bai, Fenghui Ren
Using Colored Petri Nets To Predict Future States In Agent-Based Scheduling And Planning Systems, Minjie Zhang, John Fulcher, Quan Bai, Fenghui Ren
Dr Fenghui Ren
No abstract provided.
Objective Functional Capacity Assessment Using Inertial Sensor, David Stirling, Fazel Naghdy, Golshah Naghdy, M. Field, R. Arunglabi, D. Kilpatrick
Objective Functional Capacity Assessment Using Inertial Sensor, David Stirling, Fazel Naghdy, Golshah Naghdy, M. Field, R. Arunglabi, D. Kilpatrick
Associate Professor Golshah Naghdy
Functional capacity assessment is carried out to measure the functional limitations of a subject. While the clinical assessment can be validated against various standards, quantifying the assessment and achieving an objective, repeatable, and reliable score in the clinical assessment is a challenge. Current methods are subjective. The Progressive Iso inertial Lifting Evaluation (PILE) is a lifting test developed for functional capacity assessment. The primary aim of this study is to improve reliability and repeatability of PILE through objective measurement of patient's performance. This is achieved by recording and analysing the movement of a patient by a motion capture system based …
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 …
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Associate Professor Yan-Xia Lin
No abstract provided.
Seasonal Adjustment Of An Aggregate Series Using Univariate And Multivariate Basic Structural Models, David Steel, Yan-Xia Lin, Carole Birrell
Seasonal Adjustment Of An Aggregate Series Using Univariate And Multivariate Basic Structural Models, David Steel, Yan-Xia Lin, Carole Birrell
Associate Professor Yan-Xia Lin
Time series resulting from aggregation of several sub-series can be seasonally adjusted directlyor indirectly. With model-based seasonal adjustment, the sub-series may also be considered as amultivariate system of series and the analysis may be done jointly. This approach has considerableadvantage over the indirect method, as it utilises the covariance structure between the sub-series.This paper compares a model-based univariate and multivariate approach to seasonal adjustment.Firstly, the univariate basic structural model (BSM) is applied directly to the aggregate series. Secondly,the multivariate BSM is applied to a transformed system of sub-series. The prediction meansquared errors of the seasonally adjusted aggregate series resulting from …
A Dynamic Platform For Business Process Management (Bpm) Using Service-Oriented Enterprise (Soe), Nantika Prinyapol, Joshua Fan, Sim Lau
A Dynamic Platform For Business Process Management (Bpm) Using Service-Oriented Enterprise (Soe), Nantika Prinyapol, Joshua Fan, Sim Lau
Dr Sim Kim Lau
No abstract provided.
Small Area Estimation Using A Nonparametric Model-Based Direct Estimator, Raymond Chambers, Nicola Salvati, M. Giovanna Ranalli, Hukum Chandra
Small Area Estimation Using A Nonparametric Model-Based Direct Estimator, Raymond Chambers, Nicola Salvati, M. Giovanna Ranalli, Hukum Chandra
Dr Raymond Chambers
Nonparametric regression is widely used as a method of characterizing a non-linearrelationship between a variable of interest and a set of covariates. Practical application ofnonparametric regression methods in the field of small area estimation is fairly recent,and has so far focussed on the use of empirical best linear unbiased prediction under amodel that combines a penalized spline (p-spline) fit and random area effects. The conceptof model-based direct estimation is used to develop an alternative nonparametric approachto estimation of a small area mean. The suggested estimator is a weighted average of thesample values from the area, with weights derived from a …
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Alexandra Burden, Lecturer, School of Mathematics and Applied Statistics, Faculty of Informatics
No abstract provided.
Adaptive Regularization For Multiple Image Restoration Using An Extended Total Variations Approach, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
Adaptive Regularization For Multiple Image Restoration Using An Extended Total Variations Approach, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
Professor Salim Bouzerdoum
In this paper a Variational Inequality method for multiple in- put, multiple output image restoration is presented using an extended Total Variations (TV) regularizer. This approach calculates an adaptive regularization parameter for each image based on their respective degradations. The proposed ex- tended Total Variations regularizer combines both intra-image and inter-image pixel information for improved restoration performance. Hyperparameters for controlling this new TV measure are calculated using a Bayesian joint maximum a posteriori approach.
Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li
Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
An approach to the problem of illumination variations in face detection that uses classifier fusion is presented. Multiple face detectors are seperately trained for different illumination environments and their results are combined using a combination rule. To define the illumination environments, the training samples are clustered based on their illumination using unsupervised training. Different methods of clustering the samples and combining the outputs of the classifiers are examined. Experiments with the AR face database show that the proposed method achieves higher accuracy than the traditional monolithic face detection method.