Social and Behavioral Sciences Commons^™

Whole Grain Intake Of Australians Estimated From A Cross-Sectional Analysis Of Dietary Intake Data From The 2011-13 Australian Health Survey, Leanne M. Galea, Eleanor J. Beck, Yasmine Probst, Chris Cashman

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

Objective: The Australian Dietary Guidelines recommend Australians choose mostly whole-grain and/or high-fibre varieties within the grains (cereal) foods category, with other groups specifying a whole grain Daily Target Intake of 48 g for Australians aged 9 years or above. The USA and UK report estimates of whole grain intake that are low and declining, and no comprehensive studies on whole grain intake in the Australian population are available. The present study aimed to determine national estimates of whole grain intake, compared with current recommendations. Design: A recently updated whole grain database was applied to the most current population dietary intake …

Tropospheric Water Vapour Isotopologue Data (H216O, H218O, And Hd16O) As Obtained From Ndacc/Ftir Solar Absorption Spectra, Sabine Barthlott, Matthias Schneider, Frank Hase, Thomas Blumenstock, Matthaus Kiel, Darko Dubravica, Omaira García, Eliezer Sepúlveda, Gizaw Mengistu Tsidu, Samuel Takele Kenea, Michel Grutter, Eddy F. Plaza-Medina, Wolfgang Stremme, Kimberly Strong, Dan Weaver, Mathias Palm, Thorsten Warneke, Justus Notholt, Emmanuel Mahieu, Christian Servais, Nicholas B. Jones, David W. T Griffith, D Smale, John Robinson

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

We report on the ground-based FTIR (Fourier transform infrared) tropospheric water vapour isotopologue remote sensing data that have been recently made available via the database of NDACC (Network for the Detection of Atmospheric Composition Change; ftp://ftp.cpc.ncep.noaa.gov/ndacc/MUSICA/) and via doi:10.5281/zenodo.48902. Currently, data are available for 12 globally distributed stations. They have been centrally retrieved and quality-filtered in the framework of the MUSICA project (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). We explain particularities of retrieving the water vapour isotopologue state (vertical distribution of H2¹⁶O, H2¹⁸O, and HD¹⁶O) and reveal …

'Multimorbidity In Australia: Comparing Estimates Derived Using Administrative Data Sources And Survey Data', Sanja Lujic, Judy Simpson, Nicholas Arnold Zwar, Hassan Hosseinzadeh, Louisa R. Jorm

Faculty of Social Sciences - Papers (Archive)

Background

Estimating multimorbidity (presence of two or more chronic conditions) using administrative data is becoming increasingly common. We investigated (1) the concordance of identification of chronic conditions and multimorbidity using self-report survey and administrative datasets; (2) characteristics of people with multimorbidity ascertained using different data sources; and (3) whether the same individuals are classified as multimorbid using different data sources.

Methods

Baseline survey data for 90,352 participants of the 45 and Up Study—a cohort study of residents of New South Wales, Australia, aged 45 years and over—were linked to prior two-year pharmaceutical claims and hospital admission records. Concordance of eight …

Identity-Based Remote Data Integrity Checking With Perfect Data Privacy Preserving For Cloud Storage, Yong Yu, Man Ho Au, Giuseppe Ateniese, Xinyi Huang, Willy Susilo, Yuanshun Dai, Geyong Min

Faculty of Engineering and Information Sciences - Papers: Part A

Remote data integrity checking (RDIC) enables a data storage server, say a cloud server, to prove to a verifier that it is actually storing a data owner's data honestly. To date, a number of RDIC protocols have been proposed in the literature. However, most of the constructions suffer from the issue of requiring complex key management. That is, they rely on the expensive public key infrastructure (PKI), which might hinder the deployment of RDIC in practice. In this paper, we propose a new construction of identity-based (ID-based) RDIC protocol by making use of key-homomorphic cryptographic primitive to reduce the system …

Sharing Social Network Data: Differentially Private Estimation Of Exponential Family Random-Graph Models, Vishesh Karwa, Pavel N. Krivitsky, Aleksandra B. Slavkovic

Faculty of Engineering and Information Sciences - Papers: Part A

Motivated by a real life problem of sharing social network data that contain sensitive personal information, we propose a novel approach to release and analyse synthetic graphs to protect privacy of individual relationships captured by the social network while maintaining the validity of statistical results. A case-study using a version of the Enron e-mail corpus data set demonstrates the application and usefulness of the proposed techniques in solving the challenging problem of maintaining privacy and supporting open access to network data to ensure reproducibility of existing studies and discovering new scientific insights that can be obtained by analysing such data. …

Collaborative Data Analytics Towards Prediction On Pathogen-Host Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song

Faculty of Engineering and Information Sciences - Papers: Part B

Nowadays more and more data are being sequenced and accumulated in system biology, which bring the data analytics researchers to a brand new era, namely 'big data', to extract the inner relationship and knowledge from the huge amount of data.

Towards Massive Data And Sparse Data In Adaptive Micro Open Educational Resource Recommendation: A Study On Semantic Knowledge Base Construction And Cold Start Problem, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Fang Dong, Dongming Xu, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs.

Cost-Effective Big Data Mining In The Cloud: A Case Study With K-Means, Qiang He, Xiaodong Zhu, Dongwei Li, Shuliang Wang, Jun Shen, Yun Yang

Faculty of Engineering and Information Sciences - Papers: Part B

Mining big data often requires tremendous computationalresources. This has become a major obstacle to broad applicationsof big data analytics. Cloud computing allows data scientists to access computationalresources on-demand for building their big data analytics solutions in the cloud.

Metamorphic Testing For Adobe Data Analytics Software, Darryl C. Jarman, Zhiquan Zhou, Tsong Yueh Chen

Faculty of Engineering and Information Sciences - Papers: Part B

It is challenging to test data analytics software because a test oracle might not be available. This study reports our experience of applying metamorphic testing to Adobe's data analytics software that is used for anomaly detection in a set of time series data. We make use of geometric transformations to build metamorphic relations and generate simple time series data as the source test cases. The results of this study show that metamorphic testing is highly effective for both verification and validation purposes. An investigation of the issues detected during metamorphic testing revealed three bugs in the software under test.

Towards Cost Reduction In Cloud-Based Workflow Management Through Data Replication, Fei Xie, Jun Yan, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Text Data Mining Of Aged Care Accreditation Reports To Identify Risk Factors In Medication Management In Australian Residential Aged Care Homes, Tao Jiang, Siyu Qian, David M. Hailey, Jun Ma, Ping Yu

Faculty of Engineering and Information Sciences - Papers: Part B

This study aimed to identify risk factors in medication management in Australian residential aged care (RAC) homes. Only 18 out of 3,607 RAC homes failed aged care accreditation standard in medication management between 7th March 2011 and 25th March 2015. Text data mining methods were used to analyse the reasons for failure. This led to the identification of 21 risk indicators for an RAC home to fail in medication management. These indicators were further grouped into ten themes. They are overall medication management, medication assessment, ordering, dispensing, storage, stock and disposal, administration, incident report, monitoring, staff and resident satisfaction. The …