Social and Behavioral Sciences Commons^™

Addressing The Deficiencies In The Evidence-Base For Primary Practice In Regional Australia - Sentinel Practices Data Sourcing (Spds) Project: A Pilot Study, Abhijeet Ghosh, Karen E. Charlton, Lisa Girdo, Marijka J. Batterham, Keith Mcdonald

Faculty of Science, Medicine and Health - Papers: part A

Background Chronic disease risk on a population level can be quantified through health surveys, either continuous or periodic. To date, information gathered from primary care interactions, using sentinel sites, has not been investigated as a potentially valuable surveillance system in Australia.

Methods A pilot study was conducted in a single General Practice in a regional area of New South Wales, Australia to assess the feasibility of accessing data obtained through a computerised chronic disease management program that has been designed for desktop application (Pen Computer Systems (PCS) Clinical Audit Tool: ™ PCS CAT). Collated patient data included information on chronic …

Utility Of Coi, Cad And Morphological Data For Resolving Relationships Within The Genus Sarcophaga (Sensu Lato) (Diptera: Sarcophagidae): A Preliminary Study, Kelly A. Meiklejohn, James F. Wallman, Thomas Pape, Stephen L. Cameron, Mark Dowton

Faculty of Science, Medicine and Health - Papers: part A

Currently there are ∼3000 known species of Sarcophagidae (Diptera), which are classified into 173 genera in three subfamilies. Almost 25% of sarcophagids belong to the genus Sarcophaga (sensu lato) however little is known about the validity of, and relationships between the ∼150 (or more) subgenera of Sarcophaga s.l. In this preliminary study, we evaluated the usefulness of three sources of data for resolving relationships between 35 species from 14 Sarcophaga s.l. subgenera: the mitochondrial COI barcode region, ∼800 bp of the nuclear gene CAD, and 110 morphological characters. Bayesian, maximum likelihood (ML) and maximum parsimony (MP) analyses were performed on …

Improvement Of The Retrieval Algorithm For Gosat Swir Xco2 And Xch4 And Their Validation Using Tccon Data, Y Yoshida, N Kikuchi, I Morino, O Uchino, S Oshchepkov, A Bril, T Saeki, N Schutgens, G C. Toon, D Wunch, C M. Roehl, P O. Wennberg, D W. T Griffith, N M. Deutscher, T Warneke, J Notholt, J Robinson, V Sherlock, B Connor, M Rettinger, R Sussmann, P Ahonen, P Heikkinen, E Kyro, J Mendonca, K Strong, F Hase, S Dohe, T Yokota

Faculty of Science, Medicine and Health - Papers: part A

The column-averaged dry-air mole fractions of carbon dioxide and methane (XCO2 and XCH4) have been retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations and released as a SWIR L2 product from the National Institute for Environmental Studies (NIES). XCO2 and XCH4 retrieved using the version 01.xx retrieval algorithm showed large negative biases and standard deviations (−8.85 and 4.75 ppm for XCO2 and −20.4 and 18.9 ppb for XCH4, respectively) compared with data of the Total Carbon Column Observing Network (TCCON). Multiple reasons for these error characteristics (e.g., solar irradiance database, handling of aerosol scattering) are identified and …

Analyzing Weight Loss Intervention Studies With Missing Data: Which Method Should Be Used?, Marijka J. Batterham, Linda C. Tapsell, Karen E. Charlton

Faculty of Science, Medicine and Health - Papers: part A

Objective: Missing data due to study dropout is common in weight loss trials and several statistical methods exist to account for it. The aim of this study was to identify methods in the literature and to compare the effects of methods of analysis using simulated data sets. Methods: Literature was obtained for a 1-y period to identify analytical methods used in reporting weight loss trials. A comparison of methods with large or small between-group weight loss, and missing data that was, or was not, missing randomly was conducted in simulated data sets based on previous research. Results: Twenty-seven studies, some …

More Thinking About Less Data: A Perspective From The 2nd Provence Summer Workshop, M Valenzuela, D Bartres-Faz, E Bullmore, A Fjell, M Maletic-Savetic, R Martins, N Solowij, M Yucel

Faculty of Social Sciences - Papers (Archive)

Doppler intuited that a sound’s pitch could be altered by the relative velocity between the source and an observer-70 years later Hubble used the same principle and 42 data points to prove the universe was indeed expanding. Arguably, no other data set of 0.042 Kb has done more to change our understanding of the cosmos. Although modest in volume, it took Hubble several years to acquire these precious numbers.

Der-Nsw Evaluation: Conclusions From The 2013 Data Collection, Sarah Howard, Adrian Mozejko

Faculty of Social Sciences - Papers (Archive)

The following report considers final results of the evaluation of the Australian Commonwealth Government's Digital Education Revolution in New South Wales (DERNSW) one-to-one laptop program, in relation to student and teachers' developing engagement and use of ICTs.

Cost And Time Aware Ant Colony Algorithm For Data Replica In Alpha Magnetic Spectrometer Experiment, Lijuan Wang, Junzhou Luo, Jun Shen, Fang Dong

Faculty of Engineering and Information Sciences - Papers: Part A

Huge collections of data have been created in recent years. Cloud computing provides a way to enable massive amounts of data to work together as data-intensive services. Considering Big Data and the cloud together, which is a practical and economical way to deal with Big Data, will accelerate the availability and acceptability of analysis of the data. Providing an efficient mechanism for optimized data-intensive services will become critical to meet the expected growth in demand. Because the competition is an extremely important factor in the marketplace, the cost model for data-intensive service provision is the key to provide a sustainable …

A Random Effect Block Bootstrap For Clustered Data, Raymond L. Chambers, Hukum Chandra

Faculty of Engineering and Information Sciences - Papers: Part A

Random effects models for hierarchically dependent data, e.g. clustered data, are widely used. A popular bootstrap method for such data is the parametric bootstrap based on the same random effects model as that used in inference. However, it is hard to justify this type of bootstrap when this model is known to be an approximation. In this paper we describe a random effect block bootstrap approach for clustered data that is simple to implement, free of both the distribution and the dependence assumptions of the parametric bootstrap and is consistent when the mixed model assumptions are valid. Results based on …

Sample Design Using Imperfect Design Data, Robert Graham Clark

Faculty of Engineering and Information Sciences - Papers: Part A

A well-designed sampling plan can greatly enhance the information that can be produced from a survey. Once a broad sample design is identified, specific design parameters such as sample sizes and selection probabilities need to be chosen. This is typically achieved using an optimal sample design, which minimizes the variance of a key statistic or statistics, expressed as a function of design parameters and population characteristics, subject to a cost constraint. In practice, only imprecise estimates of population characteristics are available, but the effects of this variability are usually ignored. A general approach to sample allocation allowing for imprecise design …

Parameter Identification Study Of Frequency Response Data For A Trilayer Conjugated Polymer Actuator Displacement Model, Emmanuel D. Blanchard, Mitchell J. Smith, Chuc H. Nguyen

Faculty of Engineering and Information Sciences - Papers: Part A

This article investigates the effect of three uncertain parameters on a model of conjugated polymer actuators. These uncertain parameters are the diffusion coefficient (D), the resistance (R), and the double-layer WKLFNQHVV / 7KH PRGHO VHQVLWLvity to these parameters is analyzed and a parameter estimation study is performed using artificially generated data as well as laboratory yielded experimental measurements. The parameter estimation method used in this article is based on a Bayesian cost function, and gives us an insight on how much the estimation can be trusted, which is useful information for the design of controllers. Results indicate that for stochastic …

An Extension Of The Wilcoxon-Mann-Whitney Test For Analyzing Rt-Qpcr Data, Jan De Neve, Olivier Thas, Jean-Pierre Ottoy, Lieven Clement

Faculty of Engineering and Information Sciences - Papers: Part A

Classical approaches for analyzing reverse transcription quantitative polymerase chain reaction (RT-qPCR) data commonly require normalization before assessing differential expression (DE). Normalization often has a substantial effect on the interpretation and validity of the subsequent analysis steps, but at the same time it causes a reduction in variance and introduces dependence among the normalized outcomes. These effects can be substantial, however, they are typically ignored. Most normalization techniques and methods for DE focus on mean expression and are sensitive to outliers. Moreover, in cancer studies, for example, oncogenes are often only expressed in a subsample of the populations during sampling. This …

Choosing An Optimal Model For Failure Data Analysis By Graphical Approach, Tieling Zhang, Richard Dwight

Faculty of Engineering and Information Sciences - Papers: Part A

Many models involving combination of multiple Weibull distributions, modification of Weibull distribution or extension of its modified ones, etc. have been developed to model a given set of failure data. The application of these models to modeling a given data set can be based on plotting the data on Weibull probability paper (WPP). Of them, two or more models are appropriate to model one typical shape of the fitting plot, whereas a specific model may be fit for analyzing different shapes of the plots. Hence, a problem arises, that is how to choose an optimal model for a given data …

A Personalized Hybrid Recommendation System Oriented To E-Commerce Mass Data In The Cloud, Fang Dong, Junzhou Luo, Xia Zhu, Yuxiang Wang, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part A

Personalized recommendation technology in Ecommerce is widespread to solve the problem of product information overload. However, with the further growth of the number of E-commerce users and products, the original recommendation algorithms and systems will face several new challenges: (1) to model user’s interests more accurately; (2) to provide more diverse recommendation modes; and (3) to support large-scale expansion. To address these challenges, from the actual demands of E-commerce applications (as Made-in-China website), a personalized hybrid recommendation system, which can support massive data set, is designed and implemented in this paper by using Cloud technology. Hereinto, the recommendation algorithms are …

Do We Have The Reliable Data? An Exploration Of Data Quality For Aids Information System In China, Hong Chen, Ping Yu, Ning Wang

Faculty of Engineering and Information Sciences - Papers: Part A

A national AIDS program evaluation system has been applied to the ranking of the performance of involved public health organizations in China since 2007. The system provides quantitative performance comparison information based on automatic mining of the data stored in a unified web-based national information system, China AIDS Comprehensive Response Information Management System (the CRIMS). Hence, the quality of the AIDS program evaluation system is directly related to the data quality in the CRIMS. This study aims to evaluate the performance of the AIDS program evaluation system. The research method is qualitative interview of public health practitioners in Jiangxi Province. …

Approximation Algorithm For Data Broadcasting In Duty Cycled Multi-Hop Wireless Networks, Dianbo Zhao, Kwan-Wu Chin

Faculty of Engineering and Information Sciences - Papers: Part A

Broadcast is a fundamental operation in wireless networks. To this end, many past studies have studied the NP-hard, broadcast problem for always-on multi-hop networks. However, in wireless sensor networks, nodes are powered by batteries, meaning, they have finite energy. Consequently, nodes are required to have a low duty cycle, whereby they switch between active and sleep state periodically. This means that a transmission from a node may not reach all of its neighbors simultaneously. Consequently, any developed broadcast protocols must consider collisions and the wake-up times of neighboring nodes. Henceforth, this paper studies the minimum latency broadcast scheduling problem in …

Transmit Antenna Subset Selection With Power Balancing For High Data Rate Mimo-Ofdm Uwb Systems, Ngoc Phuc Le, Le Chung Tran, Farzad Safaei

Faculty of Engineering and Information Sciences - Papers: Part A

This paper proposes per-subcarrier transmit antenna subset selection with power balancing for MIMO-OFDM UWB systems to simultaneously improve the system error performance and increase data rates. The deployment of the per-subcarrier antenna subset selection may result in a power unbalance across antennas, which could cause power amplifiers (PAs) to operate in their non-linear regions. To overcome this disadvantage, we formulate a linear optimization problem for the optimal allocation of data subcarriers under a constraint that all antennas have the same number of assigned data symbols. This optimization problem could be applied to systems with an arbitrary number of multiplexed data …

Ionization Cross Section Data Of Nitrogen, Methane, And Propane For Light Ions And Electrons And Their Suitability For Use In Track Structure Simulations, Marion Bug, Elisabetta Gargioni, Heidi Nettelbeck, Woon Yong Baek, Gerhard Hilgers, Anatoly B. Rosenfeld, Hans Rabus

Faculty of Engineering and Information Sciences - Papers: Part A

Track structure Monte Carlo simulations are frequently applied in micro- and nanodosimetry to calculate the radiation transport in detail. The use of a well-validated set of cross section data in such simulation codes ensures accurate calculations of transport parameters, such as ionization yields. These cross section data are, however, scarce and often discrepant when measured by different groups. This work surveys literature data on ionization and charge-transfer cross sections of nitrogen, methane, and propane for electrons, protons, and helium particles, focusing on the energy range between 100 keV and 20 MeV. Based on the evaluated data, different models for the …

Integrating Building Information Modelling (Bim) Into Engineering Education: An Exploratory Study Of Industry Perceptions Using Social Network Data, Kriengsak Panuwatwanich, Mei Liang Wong, Jeung-Hwan Doh, Rodney A. Stewart, Timothy J. Mccarthy

Faculty of Engineering and Information Sciences - Papers: Part A

Building Information Modelling (BIM) has been widely acknowledged as an emerging technological and procedural shift within the Architecture, Engineering and Construction (AEC) industry. BIM represents a methodology to manage the building design and project data in digital format throughout a building lifecycle. With the implementation of BIM, the design, construction and operation processes can be better streamlined to improve project efficiency. Because of its far-reaching benefits, there is a current push for BIM by governments worldwide, including Australia. However, a significant lack of the understanding of BIM and industry readiness has been identified as a major hindrance; hence, there is …

A Scalable Unsupervised Feature Merging Approach To Efficient Dimensionality Reduction Of High-Dimensional Visual Data, Lingqiao Liu, Lei Wang

Faculty of Engineering and Information Sciences - Papers: Part A

To achieve a good trade-off between recognition accuracy and computational efficiency, it is often needed to reduce high-dimensional visual data to medium-dimensional ones. For this task, even applying a simple full-matrix-based linear projection causes significant computation and memory use. When the number of visual data is large, how to efficiently learn such a projection could even become a problem. The recent feature merging approach offers an efficient way to reduce the dimensionality, which only requires a single scan of features to perform reduction. However, existing merging algorithms do not scale well with high-dimensional data, especially in the unsupervised case. To …

Multivariate Statistic And Time Series Analyses Of Grain-Size Data In Quaternary Sediments Of Lake El'gygytgyn, Ne Russia, Alexander Francke, V Wennrich, M A. Sauerbrey, O Juschus, Martin Melles, J Brigham-Grette

Faculty of Science, Medicine and Health - Papers: part A

Lake El'gygytgyn, located in the Far East Rus- sian Arctic, was formed by a meteorite impact about 3.58 Ma ago. In 2009, the International Continental Scientific Drilling Program (ICDP) at Lake El'gygytgyn obtained a continu- ous sediment sequence of the lacustrine deposits and the up- per part of the impact breccia. Here, we present grain-size data of the past 2.6 Ma. General downcore grain-size varia- tions yield coarser sediments during warm periods and finer ones during cold periods. According to principal component analysis (PCA), the climate-dependent variations in grain- size distributions mainly occur in the coarse silt and very fine …

Paleoclimate Data-Model Comparison And The Role Of Climate Forcings Over The Past 1500 Years, Steven J. Phipps, Helen V. Mcgregor, Joelle Gergis, Ailie J. E Gallant, Raphael Neukom, Samantha Stevenson, Duncan Ackerley, Josephine R. Brown, Matt J. Fischer, Tas D. Van Ommen

Faculty of Science, Medicine and Health - Papers: part A

The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. …

Towards Minimizing Cost For Composite Data-Intensive Services, Lijuan Wang, Changyan Di, Yan Li, Jun Shen, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part A

Service-oriented architecture provides a scalable and flexible framework to implement loosely-coupled, standardsbased, and protocol-independent distribute computing. One of its goals is to make use of the distributed services with different functions to build powerful composite services. Service composition is an active research area in service computing. Existing research is endeavoring to achieve desirable quality levels of composite services and improve customer satisfaction. The service-oriented approach using Web services is also of great interest for the implementation of data-intensive processes such as data mining, image processing and so on. The applications based on data-intensive services have become the most challenging type …

Economical Data-Intensive Service Provision Supported With A Modified Genetic Algorithm, Lijuan Wang, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part A

The explosion of digital data and the dependence on data-intensive services have been recognized as the most significant characteristics of the decade. Providing efficient mechanisms for optimized data-intensive services will become critical to meet the expected growing demand. In order to create a cost minimizing data-intensive service composition solution, we design two steps and two negotiation processes over the lifetime of a data-intensive service composition. The solution for the first step is presented in this paper. The proposed service selection algorithm is based on a modified genetic algorithm, which some modifications of crossover and mutation operators are adopted in order …

Influence Of Initial Severity Of Depression On Effectiveness Of Low Intensity Interventions: Meta-Analysis Of Individual Patient Data, Peter Bower, Evangelos Kontopantelis, Alex Sutton, Tony Kendrick, David A. Richards, Simon Gilbody, Sarah Knowles, Pim Cuijpers, Gerhard Andersson, Helen Christensen, Bjorn Meyer, Marcus Huibers, Filip Smit, Annemieke Van Straten, Lisanne Warmerdam, Michael Barkham, Linda Bilich, Karina Lovell, Emily Tsung-Hsueh Liu

Faculty of Social Sciences - Papers (Archive)

Objective To assess how initial severity of depression affects the benefit derived from low intensity interventions for depression. Design Meta-analysis of individual patient data from 16 datasets comparing low intensity interventions with usual care. Setting Primary care and community settings. Participants 2470 patients with depression. Interventions Low intensity interventions for depression (such as guided self help by means of written materials and limited professional support, and internet delivered interventions). Main outcome measures Depression outcomes (measured with the Beck Depression Inventory or Center for Epidemiologic Studies Depression Scale), and the effect of initial depression severity on the effects of low intensity …

The Vicious Cycle: Fundraising And Perceived Viability In U.S. Presidential Primaries, Cameron A. Shelton, James J. Feigenbaum

CMC Faculty Publications and Research

Scholars of presidential primaries have long posited a dynamic positive feedback loop between fundraising and electoral success. Yet existing work on both directions of this feedback remains inconclusive and is often explicitly cross-sectional, ignoring the dynamic aspect of the hypothesis. Pairing high-frequency FEC data on contributions and expenditures with Iowa Electronic Markets data on perceived probability of victory, we examine the bidirectional feedback between contributions and viability. We find robust, significant positive feedback in both directions. This might suggest multiple equilibria: a candidate initially anointed as the front-runner able to sustain such status solely by the fundraising advantage conferred despite …

Data Information Literacy: Multiple Paths To A Single Goal, Jake Carlson, Sarah Wright, Brian Westra, Jon Jeffryes

Libraries Faculty and Staff Presentations

The Institute of Museum and Library Services funded a two-year project for five teams (each made up of two librarians, one of whom specialized in data services, and a faculty researcher) from four institutions (Purdue University, University of Oregon, University of Minnesota, and Cornell University) to examine the data information literacy needs of graduate student researchers. After identifying the needs of their audience each team developed a tailored approach to bring instruction to their respective graduate students. The involvement of a faculty researcher in each team and pre-instruction interviews of graduate students ensured that the program developed was indeed relevant …