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Full-Text Articles in Social and Behavioral Sciences
Effective Practices For Interagency Data Sharing: Insights From Collaborative Research In A Regional Intervention, Pauline M. Mcguirk, Phillip O'Neill, Kathleen Mee
Effective Practices For Interagency Data Sharing: Insights From Collaborative Research In A Regional Intervention, Pauline M. Mcguirk, Phillip O'Neill, Kathleen Mee
Faculty of Social Sciences - Papers (Archive)
Data sharing adds considerable value to interagency programs that seek to tackle complex social problems. Yet data sharing is not easily enacted either technically or as a governance practice, especially considering the multiple forms of risk involved. This article presents insights from a successful data sharing project in a major region in east coast Australia involving a federally funded research partnership between two universities and a number of human services agencies. The Spatial Data Analysis Project sought to establish a community of practice for devising data sharing protocols and embedding data sharing into agency practices. Close dialogue between the project …
Vivambc: Estimating Viral Sequence Variation In Complex Populations From Illumina Deep-Sequencing Data Using Model-Based Clustering, Bie M. P Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
Vivambc: Estimating Viral Sequence Variation In Complex Populations From Illumina Deep-Sequencing Data Using Model-Based Clustering, Bie M. P Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
Faculty of Engineering and Information Sciences - Papers: Part A
Background: Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations. However, technology associated errors may impede a powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores which are derived from a quadruplet of intensities, one channel for each nucleotide type for Illumina sequencing. The highest intensity of the four channels determines the base that is called. Mismatch bases can often be corrected by the second best base, i.e. the base with the second highest intensity in the quadruplet. A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second …
Propensity Score Weighting For Addressing Under-Reporting In Mortality Surveillance: A Proof-Of-Concept Study Using The Nationally Representative Mortality Data In China, Kang Guo, Peng Yin, Lijun Wang, Yibing Ji, Qingfeng Li, David Bishai, Shiwei Liu, Yunning Liu, Thomas Astell-Burt, Xiaoqi Feng, Jinling You, Jiangmei Liu, Maigeng Zhou
Propensity Score Weighting For Addressing Under-Reporting In Mortality Surveillance: A Proof-Of-Concept Study Using The Nationally Representative Mortality Data In China, Kang Guo, Peng Yin, Lijun Wang, Yibing Ji, Qingfeng Li, David Bishai, Shiwei Liu, Yunning Liu, Thomas Astell-Burt, Xiaoqi Feng, Jinling You, Jiangmei Liu, Maigeng Zhou
Faculty of Social Sciences - Papers (Archive)
Background: National mortality data are obtained routinely by the Disease Surveillance Points system (DSPs) in China and under-reporting is a big challenge in mortality surveillance. Methods: We carried out an under-reporting field survey in all 161 DSP sites to collect death cases during 2009 - 2011, using a multi-stage stratified sampling. To identify under-reporting, death data were matched between field survey system and the routine online surveillance system by an automatic computer checking followed by a thorough manual verification. We used a propensity score (PS) weighting method based on a logistic regression to calculate the under-reporting rate in different groups …
Recent Advances In Security And Privacy In Big Data, Yong Yu, Yi Mu, Giuseppe Ateniese
Recent Advances In Security And Privacy In Big Data, Yong Yu, Yi Mu, Giuseppe Ateniese
Faculty of Engineering and Information Sciences - Papers: Part A
Big data has become an important topic in science, engineering, medicine, healthcare, finance, business and ultimately society itself. Big data refers to the massive amount of digital information stored or transmitted in computer systems. Approximately, 2.5 quintillion bytes of data are created every day. Almost 90% of data in the world today are created in the last two years alone. Security and privacy issues becomes more critical due to large volumes and variety, due to data hosted in large-scale cloud infrastructures, diversity of data sources and formats, streaming nature of data acquisition and high volume inter-cloud migration. In large-scale cloud …
Tour-Based Travel Mode Choice Estimation Based On Data Mining And Fuzzy Techniques, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya, Nam N. Huynh, Pascal Perez
Tour-Based Travel Mode Choice Estimation Based On Data Mining And Fuzzy Techniques, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya, Nam N. Huynh, Pascal Perez
Faculty of Engineering and Information Sciences - Papers: Part A
No abstract provided.
Searchable Atribute-Based Mechanism With Efficiient Data Sharing For Secure Cloud Storage, Kaitai Liang, Willy Susilo
Searchable Atribute-Based Mechanism With Efficiient Data Sharing For Secure Cloud Storage, Kaitai Liang, Willy Susilo
Faculty of Engineering and Information Sciences - Papers: Part A
To date, the growth of electronic personal data leads to a trend that data owners prefer to remotely outsource their data to clouds for the enjoyment of the high-quality retrieval and storage service without worrying the burden of local data management and maintenance. However, secure share and search for the outsourced data is a formidable task, which may easily incur the leakage of sensitive personal information. Efficient data sharing and searching with security is of critical importance. This paper, for the first time, proposes a searchable attribute-based proxy re-encryption system. When compared to existing systems only supporting either searchable attribute-based …
Arcgis V.10 Landslide Susceptibility Data Mining Add-In Tool Integrating Data Mining And Gis Techniques To Model Landslide Susceptibility, Darshika Palamakumbure, David Stirling, Phillip N. Flentje, Robin N. Chowdhury
Arcgis V.10 Landslide Susceptibility Data Mining Add-In Tool Integrating Data Mining And Gis Techniques To Model Landslide Susceptibility, Darshika Palamakumbure, David Stirling, Phillip N. Flentje, Robin N. Chowdhury
Faculty of Engineering and Information Sciences - Papers: Part A
Landslide susceptibility modeling is an essential early step towards managing landslide risk. A minimum of $4.8 million is lost due to landslide related damages every year in Illawara region of Australia. At present, Data mining and knowledge discovery techniques are becoming popular in building landslide susceptibility models due to their enhanced predictive performances. Until now, the lack of tools to undertake data extraction and making the predictions have limited the applicability of this novel technique in landslide model building. This paper discusses the development of the LSDM (Landslide Susceptibility Data Mining) toolbar which was designed to utilize machine learning techniques …
Age-Depth Model Of The Past 630 Kyr For Lake Ohrid (Fyrom/Albania) Based On Cyclostratigraphic Analysis Of Downhole Gamma Ray Data, Henrike Baumgarten, Thomas Wonik, D C. Tanner, Alexander Francke, Bernd Wagner, Giovanni Zanchetta, Roberto Sulpizio, Biagio Giaccio, Sebastien Nomade
Age-Depth Model Of The Past 630 Kyr For Lake Ohrid (Fyrom/Albania) Based On Cyclostratigraphic Analysis Of Downhole Gamma Ray Data, Henrike Baumgarten, Thomas Wonik, D C. Tanner, Alexander Francke, Bernd Wagner, Giovanni Zanchetta, Roberto Sulpizio, Biagio Giaccio, Sebastien Nomade
Faculty of Science, Medicine and Health - Papers: part A
Gamma ray (GR) fluctuations and potassium (K) values from downhole logging data obtained in the sediments of Lake Ohrid from 0 to 240 m below lake floor (b.l.f). correlate with fluctuations in δ18O values from the global benthic isotope stack LR04 (Lisiecki and Raymo, 2005). GR and K values are considered a reliable proxy to depict glacial-interglacial cycles, with high clastic input during cold and/or drier periods and high carbonate precipitation during warm and/or humid periods at Lake Ohrid. Spectral analysis was applied to investigate the climate signal and evolution over the length of the borehole. Linking downhole logging data …
Streaming Physiological Data: General Public Perceptions Of Secondary Use And Application To Research In Neonatal Intensive Care, Carolyn P. Mcgregor, Jennifer A. Heath, Yvonne Choi
Streaming Physiological Data: General Public Perceptions Of Secondary Use And Application To Research In Neonatal Intensive Care, Carolyn P. Mcgregor, Jennifer A. Heath, Yvonne Choi
Senior Deputy Vice-Chancellor and Deputy Vice-Chancellor (Education) - Papers
High speed physiological data represents one of the most untapped resources in healthcare today and is a form of Big Data. Physiological data is captured and displayed on a wide range of devices in healthcare environments. Frequently this data is transitory and lost once initially displayed. Researchers wish to store and analyze these datasets, however, there is little evidence of any engagement with citizens regarding their perceptions of physiological data capture for secondary use. This paper presents the findings of a self-administered household survey (n=165, response rate = 34%) that investigated Australian and Canadian citizens' perceptions of such physiological data …
Data Driven Decision Making In Chemistry First Year Subjects, Simon Bernard Bedford, Jennifer A. Heath
Data Driven Decision Making In Chemistry First Year Subjects, Simon Bernard Bedford, Jennifer A. Heath
Senior Deputy Vice-Chancellor and Deputy Vice-Chancellor (Education) - Papers
Analytics is not a new area of endeavour with many industries and other professions being well ahead of the education sector in the uptake of advanced analytics methods and tools (Abdous, He, & Yen, 2012; Dziuban, Moskal, Cavanagh, & Watts, 2012). Wagner and Ice (2012) describe higher education as being on the early side of the analytics adoption curve when compared to retail, telecommunications, financial services and manufacturing. Analytics is often used in higher education institutions to identify and also predict individual students who may be 'at risk' (Fritz, 2011).