Physical Sciences and Mathematics Commons^™

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

Charge Transport Properties Of Bo-Chelated Azadipyrromethenes, Tingrui Ma, Muyuan Zhao, Geneviève Sauvé

Intersections Fall 2020

Intramolecular BO-chelated azadipyrromethenes are promising organic semiconductors. Here, we evaluated the electron and hole mobility of a series of BO-chelated azadipyrromethenes using the Space Charge Limited Current(SCLC) method. In order to determine the mobility of the material, Mott Gurney's law was applied using the film thickness and slope of the J1/2 versus voltage plot in the SCLC graph. The best electron mobility observed for BO-chelated materials is 4.64—10-6 cm2V-1s-1 and the best hole mobility is 7.38—10-4 cm2V-1s-1. These results suggest that BO-chelated materials are promising p-type semiconductors for electronic applications.

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

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

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

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

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 …

Adaptation Practices And Lessons Learned, Molly Mitchell

November 16, 2012: Best Practices for Adapting to Sea Level Rise and Flooding

No abstract provided.

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.

City Of Virginia Beach, Virginia Shoreline Inventory Report Methods And Guidelines, Marcia Berman, Harry Berquist, Sharon Killeen, Carl Hershner, Karinna Nunez, Karen Reay, Tamia Rudnicky, Daniel E. Schatt

Reports

The data inventory developed for the Shoreline Inventory is based on a three tiered shoreline assessment approach. In most cases this assessment characterizes conditions that can be observed from a small boat navigating along the shoreline. The three tiered shoreline assessment approach divides the shorezone into three regions:

1 ) the immediate riparian zone, evaluated for land use; 2 ) the bank, evaluated for height, stability, cover and natural protection; and 3 ) the shoreline, describing the presence of shoreline structures for shore protection and recreational purposes. A combination of handheld GPS units and GPS registered videography were used to …

A Confidence-Prioritization Approach To Data Processing In Noisy Data Sets And Resulting Estimation Models For Predicting Streamflow Diel Signals In The Pacific Northwest, Nathaniel Lee Gustafson

Theses and Dissertations

Streams in small watersheds are often known to exhibit diel fluctuations, in which streamflow oscillates on a 24-hour cycle. Streamflow diel fluctuations, which we investigate in this study, are an informative indicator of environmental processes. However, in Environmental Data sets, as well as many others, there is a range of noise associated with individual data points. Some points are extracted under relatively clear and defined conditions, while others may include a range of known or unknown confounding factors, which may decrease those points' validity. These points may or may not remain useful for training, depending on how much uncertainty they …

Book Review: The Basics Of Information Security: Understanding The Fundamentals Of Infosec In Theory And Practice, Katina Michael

Professor Katina Michael

Dr Jason Andress (ISSAP, CISSP, GPEN, CEH) has written a timely book on Information Security. Andress who is a seasoned security professional with experience in both the academic and business worlds, categorically demonstrates through his book that underlying the operation of any successful business today is how to protect your most valuable asset- “information”. Andress completed his doctorate in computer science in the area of data protection, and presently works for a major software company, providing global information security oversight and performing penetration testing and risks assessment.

Natural Xml For Data Binding, Processing, And Persistence, George K. Thiruvathukal, Konstantin Läufer

Konstantin Läufer

The article explains what you need to do to incorporate XML directly into your computational science application. The exploration involves the use of a standard parser to automatically build object trees entirely from application-specific classes. This discussion very much focuses on object-oriented programming languages such as Java and Python, but it can work for non-object-oriented languages as well. The ideas in the article provide a glimpse into the Natural XML research project.

Restfs: Resources And Services Are Filesystems, Too, Joseph P. Kaylor, Konstantin Läufer, George K. Thiruvathukal

Konstantin Läufer

We have designed and implemented RestFS, a software frame-work that provides a uniform, configurable connector layerfor mapping remote web-based resources to local filesystem-based resources, recognizing the similarity between thesetwo types of resources. Such mappings enable programmaticaccess to a resource, as well as composition of two or moreresources, through the local operating system’s standardfilesystem application programming interface (API), script-able file-based command-line utilities, and inter-process com-munication (IPC) mechanisms. The framework supports au-tomatic and manual authentication. We include several ex-amples intended to show the utility and practicality of ourframework.

2012 Chesapeake Bay Bridge Tunnel Station Tide Prediction Calendars, Virginia Institute Of Marine Science, David A. Evans

Miscellaneous

These calendars are produced monthly using David Evans' Tidecal.

2012 Wachapreague Station Tide Prediction Calendars, Virginia Institute Of Marine Science, David A. Evans

Miscellaneous

These calendars are produced monthly using David Evans' Tidecal.

2012 Hampton Roads Station Tide Prediction Calendars, Virginia Institute Of Marine Science, David A. Evans

Miscellaneous

These calendars are produced monthly using David Evans' Tidecal.