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Articles 1 - 30 of 41
Full-Text Articles in Physical Sciences and Mathematics
Towards Querying And Visualization Of Large Spatio-Temporal Databases, Sugam Sharma
Towards Querying And Visualization Of Large Spatio-Temporal Databases, Sugam Sharma
Sugam Sharma
In any database model, data analysis can be eased by extracting a smaller set of the data of interest, called subset, from the mammoth original dataset. Thus, a subset helps enhance the performance of a system by avoiding the iteration through the huge parental data in further analysis. A subset, its specification, or the formal process for its extraction can be complex. In the database community, subsets are extracted through SQL-like queries and through visualization in the Geographic Information System (GIS) community. Both are iterative processes. An SQL query can be a composition of subqueries. Each subquery can be seen …
The Risk Of Public Data Availability On Critical Infrastructure Protection, Roba Abbas
The Risk Of Public Data Availability On Critical Infrastructure Protection, Roba Abbas
Dr Roba Abbas
This paper examines the threat of freely available information on critical infrastructure protection (CIP) efforts. Critical infrastructure are the services required to maintain the stability and security of a country, and comprise both physical and cyber infrastructures. These interdependent entities must be protected from natural disasters, accidental errors, and deliberate attacks. The CIP process typically includes vulnerability assessment, risk assessment and risk management, and has been a global concern for many years; the concern now amplified in Australia due to a number of recent events such the 9/11 attacks, and the Bali bombings. The events have called into question the …
Data-Driven Modeling And Analysis Of Household Travel Mode Choice, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya Denagamage, Nam N. Huynh
Data-Driven Modeling And Analysis Of Household Travel Mode Choice, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya Denagamage, Nam N. Huynh
Nagesh Shukla
One of the important problems studied in the area of travel behavior analysis is travel mode choice which is one of the four crucial steps in transportation demand estimation for urban planning. State of the art models in travel demand modelling can be classified as trip based; tour based; and activity based. In trip based approach, each individual trips is modelled as independent and isolated trips i.e. no connections between different trips. In tour based approach, trips that start and end from the same location (home, work, etc) and trips within a tour are dependent on each other. In past …
Error Correlation Between Co2 And Co As Constraint For Co2 Flux Inversions Using Satellite Data, H Wang, D J. Jacob, M Kopacz, D B. A Jones, P Suntharalingam, J A. Fisher, R Nassar, S Pawson, J E. Nielsen
Error Correlation Between Co2 And Co As Constraint For Co2 Flux Inversions Using Satellite Data, H Wang, D J. Jacob, M Kopacz, D B. A Jones, P Suntharalingam, J A. Fisher, R Nassar, S Pawson, J E. Nielsen
Jenny A Fisher
Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, …
A Model Of Data Structures Commonly Used In Programming Languages And Data Base Management Systems, William L. Honig
A Model Of Data Structures Commonly Used In Programming Languages And Data Base Management Systems, William L. Honig
William L Honig
This thesis claims that contemporary data structures can be understood and studied with an intelligible model which captures their essential differences and similarities and, further, that such a model is an appropriate basis for a top-down description method for data structures. To define the scope of the model, the data structures included in 21 programming languages and data base management systems have been tabulated. Each individual data structure is illustrated with an example drawn from a published paper or a working computer program. This mélange of data structures is divided into three classes (aggregates, associations , and files) and each …
The Smart Way To Manage Research Data, Craig Napier, Despina Clancy, Tim Davies, Katie Elcombe
The Smart Way To Manage Research Data, Craig Napier, Despina Clancy, Tim Davies, Katie Elcombe
Craig Napier
The University of Wollongongs' $62 million SMART (Simulation, Modelling, Analysis, Research, Teaching) Infrastructure Facility will become a research and development powerhouse with an unprecedented level of impact within the broader infrastructure sector nationally and overseas [1]. With a vision to be a world class intellectual leader and educator in 'integrated' infrastructure planning and management and the capacity to host 200 PhD students, comprising 30 integrated research laboratories, data demands and volume are increasing exponetially.
The Representation Of Context In Computer Software, Hisham Assal, Kym Pohl, Jens G. Pohl
The Representation Of Context In Computer Software, Hisham Assal, Kym Pohl, Jens G. Pohl
Hisham Assal
Computers do not have the equivalent of a human cognitive system and therefore store data simply as the numbers and words that are entered into the computer. For a computer to interpret data it requires an information structure that provides at least some level of context. This can be accomplished utilizing an ontology of objects with characteristics, semantic behavior, and a rich set of relationships to create a virtual version of real world situations and provide the context within which intelligent logic (e.g., agents) can automatically operate. This paper discusses the process of developing ontologies that serve to provide context …
Bayesian Hierarchical Analysis Of Minefield Data, Noel A. Cressie, Andrew B. Lawson
Bayesian Hierarchical Analysis Of Minefield Data, Noel A. Cressie, Andrew B. Lawson
Professor Noel Cressie
Based on remote sensing of a potential minefield, point locations are identified, some of which may not be mines. The mines and mine-like objects are to be distinguished based on their point patterns, although it must be emphasized that all we see is the superposition of their locations. In this paper, we construct a hierarchical spatial point-process model that accounts for the different patterns of mines and mine-like objects and uses posterior analysis to distinguish between them. Our Bayesian approach is applied to COBRA image data obtained from the NSWC Coastal Systems Station, Dahlgren Division, Panama City, Florida. 2003 Copyright …
Fast, Resolution-Consistent Spatial Prediction Of Global Processes From Satellite Data, Hsin-Cheng Huang, Noel A. Cressie, John Gabrosek
Fast, Resolution-Consistent Spatial Prediction Of Global Processes From Satellite Data, Hsin-Cheng Huang, Noel A. Cressie, John Gabrosek
Professor Noel Cressie
Polar orbiting satellites remotely sense the earth and its atmosphere, producing datasets that give daily global coverage. For any given day, the data are many and measured at spatially irregular locations. Our goal in this article is to predict values that are spatially regular at different resolutions; such values are often used as input to general circulation models (GCMs) and the like. Not only do we wish to predict optimally, but because data acquisition is relentless, our algorithm must also process the data very rapidly. This article applies a multiresolution autoregressive tree-structured model, and presents a new statistical prediction methodology …
Data Mining Of Misr Aerosol Product Using Spatial Statistics, Tao Shi, Noel A. Cressie
Data Mining Of Misr Aerosol Product Using Spatial Statistics, Tao Shi, Noel A. Cressie
Professor Noel Cressie
In climate models, aerosol forcing is the major source of uncertainty in climate forcing, over the industrial period. To reduce this uncertainty, instruments on satellites have been put in place to collect global data. However, missing and noisy observations impose considerable difficulties for scientists researching global aerosol distribution, aerosol transportation, and comparisons between satellite observations and global-climate-model outputs. In this paper, we propose a Spatial Mixed Effects (SME) statistical model to predict the missing values, denoise the observed values, and quantify the spatial-prediction uncertainties. The computations associated with the SME model are linear scalable to the number of data points, …
Data Security And Information Privacy For Pda Accessible Clinical-Log For Medical Education In Problem-Based Learning (Pbl) Approach, Rattiporn Luanrattana, Khin Than Win, John A. Fulcher
Data Security And Information Privacy For Pda Accessible Clinical-Log For Medical Education In Problem-Based Learning (Pbl) Approach, Rattiporn Luanrattana, Khin Than Win, John A. Fulcher
Dr Khin Win
Data security and information privacy are the important aspects to consider for the use of mobile technology for recording clinical experience and encounter in medical education. Objective: This study aims to address the qualitative findings of the appropriate data security and information privacy for PDA accessible clinical-log in problem-based learning (PBL) approach in medical education. Method: The semi-structured interviews were conducted with the medical faculty members, honorary clinical academics and medical education technology specialists. Results: Data security and information access plan were determined for managing clinical-log data. The results directed the guideline for the future development and implementation of clinical-log …
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 …
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 …
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
Professor Darmawan Sutanto
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 …
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
Professor Darmawan Sutanto
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 …
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 Duane Robinson
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 …
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 Duane Robinson
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 …
Data Management For Large Scale Power Quality Surveys, Murray-Luke Peard, Sean T. Elphick, Victor W. Smith, Victor J. Gosbell, D A. Robinson
Data Management For Large Scale Power Quality Surveys, Murray-Luke Peard, Sean T. Elphick, Victor W. Smith, Victor J. Gosbell, D A. Robinson
Dr Duane Robinson
For large scale power quality surveys, the management of the large amount of data generated is a major issue. This paper presents solutions to three main areas of data management, viz. a data interchange format, database design and data processing. Consideration of these issues has come about as a result of the Long Term National Power Quality Survey currently being conducted by the University of Wollongong, and reference is made to that specific application for illustrative purposes.
Power Line Enhancement For Data Monitoring Of Neural Electrical Activity In The Human Body, Ahmed M. Haidar, Sridhathan C, Abdulsalam Hazza, Ahmed Saleh
Power Line Enhancement For Data Monitoring Of Neural Electrical Activity In The Human Body, Ahmed M. Haidar, Sridhathan C, Abdulsalam Hazza, Ahmed Saleh
Dr Ahmed Mohamed Ahmed Haidar
Distance and real-time data monitoring are the necessary condition that makes any system in good working order. Recent advancements in micro-electronics and wireless technology enable the application of wireless sensors in both industry and wild environments. However, Long-distance wireless communication has several drawbacks like limited bandwidth, considerable costs and unstable connection quality. Therefore, Power Line Communication (PLC) using pre-established Power Lines (PL) becomes more attractive for high data transmission technology. This paper reviews the existing distance data monitoring systems and presents a case study for data transferring of temperature and heart beat measurement. The simulations were carried out on the …
A Discussion About The Importance Of Laws And Policies For Data Sharing For Public Health In The People's Republic Of China, Xiue Fan, Ping Yu
A Discussion About The Importance Of Laws And Policies For Data Sharing For Public Health In The People's Republic Of China, Xiue Fan, Ping Yu
Dr Ping Yu
This paper introduces the current status of data sharing in the People's Republic of China. It discusses barriers to data sharing and proposes three key solutions to overcome these barriers in China. The establishment of national laws and policies for data sharing is considered the key prerequisite to ensuring the successful implementation of resource sharing activities in public health. Driven by established laws and policies, the relevant operational models should be developed. It is also important to have strategies in place to ensure the established laws and policies are implemented by various organizations in different jurisdictions. These discussions are supported …
Privacy Enhanced Data Outsourcing In The Cloud, Miao Zhou, Yi Mu, Willy Susilo, Jun Yan, Liju Dong
Privacy Enhanced Data Outsourcing In The Cloud, Miao Zhou, Yi Mu, Willy Susilo, Jun Yan, Liju Dong
Dr Jun Yan
How to secure outsourcing data in cloud computing is a challenging problem, since a cloud environment cannot been considered to be trusted. The situation becomes even more challenging when outsourced data sources in a cloud environment are managed by multiple outsourcers who hold different access rights. In this paper, we introduce an efficient and novel tree-based key management scheme that allows a data source to be accessed by multiple parties who hold different rights. We ensure that the database remains secure, while some selected data sources can be securely shared with other authorized parties.
Wfms-Based Data Integration For E-Learning, Jianming Yong, Jun Yan, Xiaodi Huang
Wfms-Based Data Integration For E-Learning, Jianming Yong, Jun Yan, Xiaodi Huang
Dr Jun Yan
As more and more organisations and institutions are moving towards the e-learning strategy, more and more disparate data are distributed by different e-learning systems. How to effectively use this vast amount of distributed data becomes a big challenge. This paper addresses this challenge and works out a new mechanism to implement data integration for e-learning. A workflow management system based (WFMS-based) data integration model is contributed to the e-learning.
Privacy Enhanced Data Outsourcing In The Cloud, Miao Zhou, Yi Mu, Willy Susilo, Jun Yan, Liju Dong
Privacy Enhanced Data Outsourcing In The Cloud, Miao Zhou, Yi Mu, Willy Susilo, Jun Yan, Liju Dong
Professor Willy Susilo
How to secure outsourcing data in cloud computing is a challenging problem, since a cloud environment cannot been considered to be trusted. The situation becomes even more challenging when outsourced data sources in a cloud environment are managed by multiple outsourcers who hold different access rights. In this paper, we introduce an efficient and novel tree-based key management scheme that allows a data source to be accessed by multiple parties who hold different rights. We ensure that the database remains secure, while some selected data sources can be securely shared with other authorized parties.
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 …
Privacy Enhanced Data Outsourcing In The Cloud, Miao Zhou, Yi Mu, Willy Susilo, Jun Yan, Liju Dong
Privacy Enhanced Data Outsourcing In The Cloud, Miao Zhou, Yi Mu, Willy Susilo, Jun Yan, Liju Dong
Professor Yi Mu
How to secure outsourcing data in cloud computing is a challenging problem, since a cloud environment cannot been considered to be trusted. The situation becomes even more challenging when outsourced data sources in a cloud environment are managed by multiple outsourcers who hold different access rights. In this paper, we introduce an efficient and novel tree-based key management scheme that allows a data source to be accessed by multiple parties who hold different rights. We ensure that the database remains secure, while some selected data sources can be securely shared with other authorized parties.
Fixed Rank Filtering For Spatio-Temporal Data, Noel Cressie, Tao Shi, Emily L. Kang
Fixed Rank Filtering For Spatio-Temporal Data, Noel Cressie, Tao Shi, Emily L. Kang
Professor Noel Cressie
Datasets from remote-sensing platforms and sensor networks are often spatial, temporal, and very large. Processing massive amounts of data to provide current estimates of the (hidden) state from current and past data is challenging, even for the Kalman filter. A large number of spatial locations observed through time can quickly lead to an overwhelmingly high-dimensional statistical model. Dimension reduction without sacrificing complexity is our goal in this article. We demonstrate how a Spatio-Temporal Random Effects (STRE) component of a statistical model reduces the problem to one of fixed dimension with a very fast statistical solution, a methodology we call Fixed …
Application Of Semistructured Data Model To The Implementation Of Semantic Content-Based Video Retrieval System, Lilac A. E. Al-Safadi, Janusz R. Getta
Application Of Semistructured Data Model To The Implementation Of Semantic Content-Based Video Retrieval System, Lilac A. E. Al-Safadi, Janusz R. Getta
Dr Janusz Getta
Semantic indexing of a video document is a process that performs the identification of elementary and complex semantic units in the indexed document in order to create a semantic index defined as a mapping of semantic units into the sequences of video frames. Semantic content-based video retrieval system is a software system that uses a semantic index built over a collection of video documents to retrieve the sequences of video frames that satisfy the given conditions. This work introduces a new multilevel view of data for the semantic content-based video retrieval systems. At the topmost level, we define an abstract …
Data Security And Information Privacy For Pda Accessible Clinical-Log For Medical Education In Problem-Based Learning (Pbl) Approach, Rattiporn Luanrattana, Khin Than Win, John A. Fulcher
Data Security And Information Privacy For Pda Accessible Clinical-Log For Medical Education In Problem-Based Learning (Pbl) Approach, Rattiporn Luanrattana, Khin Than Win, John A. Fulcher
Professor John Fulcher
Data security and information privacy are the important aspects to consider for the use of mobile technology for recording clinical experience and encounter in medical education. Objective: This study aims to address the qualitative findings of the appropriate data security and information privacy for PDA accessible clinical-log in problem-based learning (PBL) approach in medical education. Method: The semi-structured interviews were conducted with the medical faculty members, honorary clinical academics and medical education technology specialists. Results: Data security and information access plan were determined for managing clinical-log data. The results directed the guideline for the future development and implementation of clinical-log …
A Data-Fitting Approach For Displacements And Vibration Measurement Using Self-Mixing Interferometers, Yi Zhang, Jiangtao Xi, Joe F. Chicharo, Yanguang Yu
A Data-Fitting Approach For Displacements And Vibration Measurement Using Self-Mixing Interferometers, Yi Zhang, Jiangtao Xi, Joe F. Chicharo, Yanguang Yu
Professor Joe F. Chicharo
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.