Digital Commons Network^™

Towards Agent-Based Traffic Simulation Using Live Data From Sensors For Smart Cities, Johan Barthelemy, Yan Qian, Pascal Perez

SMART Infrastructure Facility - Papers

The Smart City and Internet-of-Things revolutions enable the collection of various types of data in real-time through sensors. This data can be used to improve the decision tools and simulations used by city planners. This paper presents a new framework for real-time traffic simulation integrating an agent-based methodology with live CCTV and other sensor data while respecting the privacy regulations. The framework simulates traffic flows of pedestrians, vehicles and bicycles and their interactions. The approach has been applied in Liverpool (NSW, Australia) showing promising preliminary results and can easily ingest additional sensor data, e.g. air quality.

Transforming Business Using Digital Innovations: The Application Of Ai, Blockchain, Cloud And Data Analytics, Shahriar Akter, Katina Michael, Muhammad Rajib Uddin, Grace Mccarthy, Mahfuzur Rahman

Sydney Business School - Papers

This study explores digital business transformation through the lens of four emerging technology fields: artificial intelligence, blockchain, cloud and data analytics (i.e., ABCD). Specifically, the study investigates the operations and value propositions of these distinct but increasingly converging technologies. Due to the dynamic nature of innovation, the potential of this ABCD hybridization, integration, recombination and convergence has yet to be considered. Using a multidisciplinary approach, the findings of the study show wide-reaching and diverse applications among a variety of vertical sectors, presenting exploratory research avenues for future investigation. The study also highlights the practical implications of these new technologies.

Apex2s: A Two-Layer Machine Learning Model For Discovery Of Host-Pathogen Protein-Protein Interactions On Cloud-Based Multiomics Data, Huaming Chen, Jun Shen, Lei Wang, Chi-Hung Chi

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Refinement And Augmentation For Data In Micro Learning Activity With An Evolutionary Rule Generators, Geng Sun, Jiayin Lin, Tingru Cui, Jun Shen, Dongming Xu, Mahesh Kayastha

Faculty of Engineering and Information Sciences - Papers: Part B

Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an inner loop. The outer loop runs a genetic algorithm (GA) to produce association rules that can be effective in the micro open learning scenario from a small amount of available data sources; while the inner loop optimizes generated candidates by taking into account …

A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam

Faculty of Engineering and Information Sciences - Papers: Part B

Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV …

On Masking And Releasing Smart Meter Data At Micro-Level: The Multiplicative Noise Approach, John Brackenbury, P. Y. O'Shaughnessy, Yan-Xia Lin

Faculty of Engineering and Information Sciences - Papers: Part B

Smart meter electricity data presents privacy risks when malicious agents gain insights of private information, including residents’ lifestyle and daily habits. When allowing access to record-level data, we apply the multiplicative noise method to mask individual smart meter data, which simultaneously aims to minimise disclosure of a dwelling’s consumption signal to any third party and to enable accurate estimation of the sum of a cluster of households. Three testing criteria are introduced to measure the performance of multiplicative noise masking approach relevant to the smart meter data. We propose a novel ‘Twin Uniform’ noise distribution and derive relevant theoretical results. …

A Framework Towards Data Analysis On Host-Pathogen Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song

Faculty of Engineering and Information Sciences - Papers: Part B

With the rapid development of high-throughput technologies, systems biology is now embracing a great opportunity made possible by the increased accumulation of data available online. Biological data analytics is considered as a critical means to contribute to a better understanding on such data through extraction of the latent features, relationships and the associated mechanisms. Therefore, it is important to evaluate how to involve data analytics from both computational and biological perspectives in practice. This paper has investigated interaction relationships in the proteomics area, which provide insights of the critical molecular processes within infection mechanisms. Specifically, we focused on host–pathogen protein–protein …

Ensemble-Based Satellite-Derived Carbon Dioxide And Methane Column-Averaged Dry-Air Mole Fraction Data Sets (2003-2018) For Carbon And Climate Applications, Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noel, Heinrich Bovensmann, John Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuza, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T Griffith, Rigel Kivi, David Pollard, Frank Hase, Ralf Sussmann, Yao V. Te, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Maziere, Dietrich Feist, Laura T. Iraci, C M. Roehl, Christian Retscher, Dinand Schepers

Faculty of Science, Medicine and Health - Papers: Part B

Satellite retrievals of column-averaged dry-air mole fractions of carbon dioxide (CO2) and methane (CH4), denoted XCO2 and XCH4, respectively, have been used in recent years to obtain information on natural and anthropogenic sources and sinks and for other applications such as comparisons with climate models. Here we present new data sets based on merging several individual satellite data products in order to generate consistent long-term climate data records (CDRs) of these two Essential Climate Variables (ECVs). These ECV CDRs, which cover the time period 2003-2018, have been generated using an ensemble of data products from the satellite sensors SCIAMACHY/ENVISAT and …

Surficial Sediment Data From The Shoalhaven River Delta: Bed Channel And Adjacent Beach, Rafael C. Carvalho, Colin D. Woodroffe

Faculty of Science, Medicine and Health - Papers: Part B

Estuaries on wave-dominated coasts generally comprise three sedimentary environments: fluvial sands and gravels derived from the catchment; marine sands characteristic of the beaches and nearshore; and silts and clays that accumulate in the sheltered central basin. Estuarine transition to deltaic form occurs when geomorphological maturity is achieved during coastal evolution. Sedimentary plains become infilled and a narrow channel connects the catchment and facilitates the transport of fluvial sediments to the coast. Here, we present modern sedimentary data that supports the idea that the wave-dominated Shoalhaven system in southeastern Australia has transitioned from an estuary to delta, transporting fluvial sediments to …

Heterogeneity In Clinical Research Data Quality Monitoring: A National Survey, Lauren Houston, Ping Yu, Allison Martin, Yasmine Probst

Faculty of Science, Medicine and Health - Papers: Part B

Introduction Clinical research is vital in the discovery of new medical knowledge and reducing disease risk in humans. In clinical research poor data quality is one of the major problems, affecting data integrity and the generalisability of the research findings. To achieve high quality data, guidance needs to be provided to clinical studies on the collection, processing and handling of data. However, clinical trials are implementing ad hoc, pragmatic approaches to ensure data quality. This study aims to explore the procedures for ensuring data quality in Australian clinical research studies. Material and methods We conducted a national cross-sectional, mixed-mode multi-contact …

Estimating Travellers’ Trip Purposes Using Public Transport Data And Land Use Information, Bo Du

SMART Infrastructure Facility - Papers

In public transport system, the equipped automated fare collection (AFC) system records travellers’ spatial and temporal information and generates a mass of data daily with more than ever attraction of interest and attention from both academics and practitioners. Advances in data availability and data mining techniques provide great opportunity to investigate various researches in an efficient and effective manner. A comprehensive literature review on the application of public transport smart card data before 2011 can be referred to [1]. As some relevant studies in recent years, [2] proposed a data fusion method to infer passengers’ behavioral attributes of the trips …

Electronic Persistent Pain Outcomes Collaboration Annual Data Report 2018, Hilarie Tardif, Megan B. Blanchard, Karen Quinsey, Meredith P. Bryce, Janelle M. White, Julie A. Blacklock, Kathy Eagar

Australian Health Services Research Institute

ePPOC is a program that aims to improve services and outcomes for people experiencing persistent pain. It involves specialist pain services collecting a standard set of information to measure outcomes for their patients as a result of treatment. Pain services use the information to triage, monitor and plan treatment for individual clients, and also send non-identifiable information to ePPOC for analysis. The results of these analyses are fed back to participating services every six months, allowing pain management services to assess their results, and compare their patients, services and outcomes to other pain management services. ePPOC also uses the information …

Disclosure And Reporting Against The Sustainable Development Goals: Connecting New Stakeholders To Sustainability Data, Theresa Heithaus, Richard Mills, Stephanie Perkiss

Faculty of Business - Papers (Archive)

This case study focuses on the disclosures of thirty seven companies and a unique research approach to making their corporate sustainability performance more open, comparable and engaging. A group of 40 students at the University of Wollongong worked in a structured way to aggregate comparable data on corporate sustainability on a selection of metrics related to the SDGs. This report offers an in depth look at one example of the kind of projects that WikiRate and the Principles for Responsible Management Education (PRME) have been running since 2016, involving more than 2,000 students. For this case study, WikiRate staff reviewed …

Dynamic Service Analytics Capabilities For Service Systems In The Global Big Data Economy - A Systematic Review And Agenda For Future Research, Shahriar Akter, Saradhi Motamarri, Mujahid M. Babu, Mario Fernando, Samuel Fosso Wamba, Kathy Ning Shen

Faculty of Business - Papers (Archive)

Extended abstract presented at the Data, Organisations and Society Conference, 21 November 2018, Coventry, United Kingdom

Are Urban Development And Densification Patterns Aligned With Infrastructure Funding Allocation? Examining Data From Melbourne 1999-2015, Nicole T. Cook, Ilan Wiesel, Fanqi Liu

Faculty of Social Sciences - Papers (Archive)

Densification of cities and suburbs is a contentious issue for many communities in lower-density settings. Local opposition to densification is often premised on concerns about the inadequacy of existing infrastructure to support growing populations and is strongest and most successful in wealthier neighbourhoods. While the urban consolidation agenda in cities such as Melbourne and Sydney is justified in policy contexts as a strategy to improve utilisation of existing infrastructure in built up areas, densification over time also produces new demand for services. Whether or not densification drives new infrastructure spending is therefore an important question in the governance of social …

Examining The High Users Of Hospital Resources: Implications Of A Profile Developed From Australian Health Insurance Claims Data, Joanna Khoo, Helen M. Hasan, Kathy Eagar

Australian Health Services Research Institute

Objective To develop and examine a profile of the demographic, hospital admission and clinical characteristics of high users of hospital resources within a cohort of privately insured Australians.Methods Hospital admissions claims data from a group of private health insurance funds were analysed. The top 1% of hospital users were selected based on three measures of resource utilisation: number of admissions, total bed days and total insurance benefits paid. The demographic, hospital admission and clinical characteristics data were compared for these three measures of resource utilisation.Results Compared with the general insured population, the three high-use cohorts are older, have more public …

Normative Data For Adults Referred For Specialist Pain Management In Australia, Hilarie Tardif, Megan B. Blanchard, Janelle M. White, Meredith P. Bryce

Australian Health Services Research Institute

Nicholas and colleagues have developed an extensive normative dataset for a range of assessment tools used in pain management services. The present paper aims to provide normative data for the measures used in the ePPOC minimum dataset for a large cohort of adults referred to pain management services throughout Australia. This information will provide a description of the people seeking specialist pain management in Australia during the period 2014-17, and allow pain management services to compare scores for individuals seen at their service to these group values.

Normative Data For Children And Adolescents Referred For Specialist Pain Management In Australia, Hilarie Tardif, Megan B. Blanchard, Meredith P. Bryce, Janelle M. White

Australian Health Services Research Institute

This paper aims to provide normative data for the PaedePPOC measures used by specialist paediatric pain management services. This information will provide a description of the children and adolescents referred for specialist pain management in Australia during the period from January 2014 to June 2018, allowing pain management services to compare scores for individuals seen at their service to these group values.

Data Privacy And System Security For Banking And Financial Services Industry Based On Cloud Computing Infrastructure, Abhishek Mahalle, Jianming Yong, Xiaohui Tao, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Fast Multi-Resource Allocation With Patterns In Large Scale Cloud Data Center, Jiyuan Shi, Junzhou Luo, Fang Dong, Jiahui Jin, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

How to achieve fast and efficient resource allocation is an important optimization problem of resource management in cloud data center. On one hand, in order to ensure the user experience of resource requesting, the system has to achieve fast resource allocation to timely process resource requests; on the other hand, in order to ensure the efficiency of resource allocation, how to allocate multi-dimensional resource requests to servers needs to be optimized, such that server's resource utilization can be improved. However, most of existing approaches focus on finding out the mapping of each specific resource request to each specific server. This …

Exploring The Potential Of Big Data On The Health Care Delivery Value Chain (Cdvc): A Preliminary Literature And Research Agenda, William J. Tibben, Samuel Fosso Wamba

Faculty of Engineering and Information Sciences - Papers: Part B

Big data analytics (BDA) is emerging as a game changer in healthcare. While the practitioner literature has been speculating on the high potential of BDA in transforming the healthcare sector, few rigorous empirical studies have been conducted by scholars to assess the real potential of BDA. Drawing on the health care delivery value chain (CDVC) and an extensive literature review, this exploratory study aims to discuss current peer-reviewed articles dealing with BDA across the CDVC and discuss future research directions.

Data Fusion For Maas: Opportunities And Challenges, Jianqing Wu, Luping Zhou, Chen Cai, Jun Shen, S K. Lau, Jianming Yong

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

The Impact Of Integration Quality On Customer Equity In Data Driven Omnichannel Services Marketing, Tasnim M Taufique Hossain, Shahriar Akter, Uraiporn Kattiyapornpong, Samuel Fosso Wamba

Faculty of Business - Papers (Archive)

The plethora of digital channels has shifted multichannel services to an omnichannel environment. In the omnichannel context, the borderline of offline, online and digital channels is diminishing as consumers utilize several channels simultaneously to complete any purchases. Additionally, as more channels are introduced, the amount of customer data collected at each touch point is increasing rapidly. However, the urgent need to integrate all information with service attributes within these channels will result in increasing cost and consequently customer dissatisfaction if they are disintegrated. To address this phenomenon, this research focuses towards developing quality dimension for data driven omnichannel services marketing. …

Data Mining In Educational Technology Classroom Research: Can It Make A Contribution?, Charoula Angeli, Sarah Katherine Howard, Jun Ma, Jie Yang, Paul A. Kirschner

SMART Infrastructure Facility - Papers

The paper addresses and explains some of the key questions about the use of data mining in educational technology classroom research. Two examples of use of data mining techniques, namely, association rules mining and fuzzy representations are presented, from a study conducted in Europe and another in Australia. Both of these studies examine student learning, behaviors, and experiences within computer-supported classroom activities. In the first study, the technique of association rules mining was used to understand better how learners with different cognitive types interacted with a simulation to solve a problem. Association rules mining was found to be a useful …

Investigating The Accuracy Of Georeferenced Social Media Data For Flood Mapping: The Petajakarta.Org Case Study, Robert Ighodaro Ogie, Hugh I. Forehead

SMART Infrastructure Facility - Papers

Georeferenced social media data are gaining increased application in creating near real-time flood maps needed to improve situational awareness in data-starved regions. However, there is growing concern that the georeferenced locations of flood-related social media contents do not always correspond to the actual locations of the flooding event. But to what extent is this true? Without this knowledge, it is difficult to ascertain the accuracy of flood maps created using georeferenced social media contents. This study aims to improve understanding of the extent to which georeferenced locations of social media flood reports deviate from the actual locations of floods. The …

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 …

Comparative Analysis Of Selected Big Data Analytics Tools, Soly Mathew Biju, Alex Mathew

University of Wollongong in Dubai - Papers

Over the last few years, big data has emerged as an important topic of discussion in most firms owing to its ability of creation, storage and processing of content at a reasonable price. Big data consists of advanced tools and techniques to process large volumes of data in organisations. Investment in big data analytics has almost become a necessity in large-sized firms, particularly multinational companies, for its unique benefits, particularly in prediction and identification of various trends. Some of the most popular big data analytics software used today are MapReduce, Hive, Tableau and Hive, while the framework Hadoop enables easy …