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- Data (3)
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Articles 1 - 13 of 13
Full-Text Articles in Physical Sciences and Mathematics
Scene Analysis For Autonomous System Control, David Ngan Luu, David A. Stirling
Scene Analysis For Autonomous System Control, David Ngan Luu, David A. Stirling
Dr David Stirling
The potential of autonomous airborne platforms have long been considered for applications in surveillance, exploration and search and rescue. For example, an autonomous blimp or airship, able to navigate through complex unstructured environments, could be used to survey the aftermath of dangerous earthquake zones, or be employed to provide unique replay angles in sporting events. Therefore autonomous airships fill an important gap in the spectrum of aerial observations, supplying images with better resolution and much more acquisition flexibility than those acquired through satellite or airplanes. This paper proposes to configure a semi-autonomous Unmanned Aerial Vehicle (UAV) for research into navigation …
A Hot Metal Temperature Predictor Based On Hybrid Decision Tree Techniques, Chao Sun, David A. Stirling, Bryan Wright, Paul Zulli, Christian Ritz
A Hot Metal Temperature Predictor Based On Hybrid Decision Tree Techniques, Chao Sun, David A. Stirling, Bryan Wright, Paul Zulli, Christian Ritz
Dr David Stirling
HEAT level control (HLC) is one of the important elements for operating an iron-making blast furnace (BF). The goal of HLC is to maintain the hot metal temperature (HMT) as close to a preset aim as possible. HMT is an important indicator of both the product quality and fuel efficiency, and is measured from tapped out liquid iron. For instance, high values of HMT mean unnecessary fuel consumption together with sub-optimal hot metal chemistry, whilst low values of HMT may indicate insufficient fuel consumption, which may consequently lead to dangerous situation of freezing the slag inside the BF. Once an …
Clustering Of Harmonic Monitoring Data Using Data Mining, Danny Sutanto, A. Asheibi, David A. Stirling
Clustering Of Harmonic Monitoring Data Using Data Mining, Danny Sutanto, A. Asheibi, David A. Stirling
Dr David Stirling
A comprehensive harmonic monitoring program has been designed and implemented on a typical medium-voltage distribution system in Australia. The monitoring program involved measurements of the three-phase harmonic currents and voltages from the residential, commercial, and industrial load sectors. Data over a three year period have been downloaded and available for analysis. The large amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. More sophisticated analysis methods are required to automatically determine which part of the measurement data are of importance. Based on this information, a closer inspection of smaller …
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
Dr David Stirling
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 …
Using Spatial Cues For Meeting Speech Segmentation, E Cheng, J Lukasiak, Ian S. Burnett, David A. Stirling
Using Spatial Cues For Meeting Speech Segmentation, E Cheng, J Lukasiak, Ian S. Burnett, David A. Stirling
Dr David Stirling
This work investigates the validity and accuracy of using spatialcues with Time-Delay Estimation (TDE) as a method of segmenting multichannel recorded speech by speaker location. In environments such as meetings where speakers do not significantly alter position, segmentation by speaker location essentially leads to segmentation by speaker ‘ turn’. The proposed system calculates location information using TDEs and spatial cues extracted from multichannel meeting audio recordings. This location information is then input into a simple segmentation algorithm. Experiments have been performed on both theoretical and real meeting recordings with non-overlapping speakers, and theoretical recordings with overlapping speakers. Segmentation results reveal …
Empirical Modelling Of Human Gaits For Bipedal Robots, Matthew Field, David A. Stirling, Fazel Naghdy, Zengxi Pan
Empirical Modelling Of Human Gaits For Bipedal Robots, Matthew Field, David A. Stirling, Fazel Naghdy, Zengxi Pan
Dr David Stirling
Modelling of human motion through a discrete sequence of motion primitives, retaining elements of skillful or unique motion of an individual is addressed. Using wireless inertial motion sensors, a skeletal model of the fluid human gait was gathered. The posture of the human model is described by nine sets of euler angles for each sample. An intrinsic classification algorithm known as Minimum Message Length encoding (MML) is deployed to segment the stream of data and subsequently formulate certain Gaussian Mixture Models (GMM) that contain a plausible range of motion primitives. The removal of certain less seemingly important modes has been …
Clustering, Classification And Explanatory Rules From Harmonic Monitoring Data, Ali Asheibi, David A. Stirling, Danny Sutanto, D A. Robinson
Clustering, Classification And Explanatory Rules From Harmonic Monitoring Data, Ali Asheibi, David A. Stirling, Danny Sutanto, D A. Robinson
Dr David Stirling
A method based on the successful AutoClass (Cheeseman & Stutz, 1996) and the Snob research programs (Wallace & Dowe, 1994); (Baxter & Wallace, 1996) has been chosen for our research work on harmonic classification. The method utilizes mixture models (McLachlan, 1992) as a representation of the formulated clusters. This research is principally based on the formation of such mixture models (typically based on Gaussian distributions) through a Minimum Message Length (MML) encoding scheme (Wallace & Boulton, 1968). During the formation of such mixture models the various derivative tools (algorithms) allow for the automated selection of the number of clusters and …
Evaluation Of Human Gait Through Observing Body Movements, Amir S. Hesami, Fazel Naghdy, David A. Stirling, Harold C. Hill
Evaluation Of Human Gait Through Observing Body Movements, Amir S. Hesami, Fazel Naghdy, David A. Stirling, Harold C. Hill
Dr David Stirling
A new modelling and classification approach for human gait evaluation is proposed. The body movements are obtained using a sensor suit recording inertial signals that are subsequently modelled on a humanoid frame with 23 degrees of freedom (DOF). Measured signals include position, velocity, acceleration, orientation, angular velocity and angular acceleration. Using the features extracted from the sensory signals, a system with induced symbolic classification models, such as decision trees or rule sets, based on a range of several concurrent features has been used to classify deviations from normal gait. It is anticipated that this approach will enable the evaluation of …
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
Dr David Stirling
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 …
Analyzing Harmonic Monitoring Data Using Data Mining, Ali Asheibi, David A. Stirling, Danny Sutanto
Analyzing Harmonic Monitoring Data Using Data Mining, Ali Asheibi, David A. Stirling, Danny Sutanto
Dr David Stirling
Harmonic monitoring has become an important tool for harmonic management in distribution systems. A comprehensive harmonic monitoring program has been designed and implemented on a typical electrical MV distribution system in Australia. The monitoring program involved measurements of the three-phase harmonic currents and voltages from the residential, commercial and industrial load sectors. Data over a three year period has been downloaded and available for analysis. The large amount of acquired data makes it difficult to identify operational events that impact significantly on the harmonics generated on the system. More sophisticated analysis methods are required to automatically determine which part of …
Perception Of Human Gestures Through Observing Body Movements, Amir S. Hesami, Fazel Naghdy, David A. Stirling, Harold C. Hill
Perception Of Human Gestures Through Observing Body Movements, Amir S. Hesami, Fazel Naghdy, David A. Stirling, Harold C. Hill
Dr David Stirling
A new approach to modelling and classification of human gait is proposed. Body movements are obtained using a sensor suit that records inertial signals that are subsequently modelled on a humanoid frame with 23 degrees of freedom (DOF). Measured signals include position, velocity, acceleration, orientation, angular velocity and angular acceleration. Using a range of concurrent features extracted from the sensor signals, a system using induced symbolic classification models, such as decision trees or rule sets, has been used for classification of identity. It is anticipated that this approach will also enable the identification of a variety of gestures. The feasibility …
Performance Of Mpeg-7 Low Level Audio Descriptors With Compressed Data, Jason Lukasiak, David A. Stirling, N. Harders, S. Perrow
Performance Of Mpeg-7 Low Level Audio Descriptors With Compressed Data, Jason Lukasiak, David A. Stirling, N. Harders, S. Perrow
Dr David Stirling
This paper presents a detailed analysis of lossy compression effects on a set of the MPEG-7 low-level audio descriptors. The analysis results show that lossy compression has a detrimental effect on the integrity of practical search and retrieval schemes that utilize the low level audio descriptors. Methods are then proposed to reduce the detrimental effects of compression in searching schemes. These proposed methods include multi-frame searching and machine learning derived prediction. The proposed mechanisms greatly reduce the effect of compression on the set of MPEG-7 descriptors; however, future scope is identified to develop new audio descriptors that account for compression …
Application Of Mml To Motor Skills Acquisition, Chao Sun, Fazel Naghdy, David A. Stirling
Application Of Mml To Motor Skills Acquisition, Chao Sun, Fazel Naghdy, David A. Stirling
Dr David Stirling
Study on modeling human psychomotor behaviour based on tracked motion data is reported. The motion data is acquired through various integrated inertial sensors, and represented as Euler angles and accelerations. The Minimum Message Length (MML) algorithm is used to identify frames of intrinsic segmentations and to acquire a classification basis for unsupervised machine learning. The classification model can ultimately be deployed in recognizing certain skilled behaviors. The prior results are analyzed as FSMs' (Finite State Machines) to extract the potential rules underlying behaviors. The progress made so far and plan for further work is reported.