SMART Research Brochure by University of Wollongong

SMART INFRASTRUCTURE FACILITY RESEARCH HIGHLIGHTS 2012-2013

INTRODUCTION

The release of a first annual scientific report is a very special event. Mixed emotions crossed my mind as I was reading through the final proof. Comfort in the high-quality work being presented, and anguish at the thought that we should have produced more. The reality is that the SMART Infrastructure Facility, at the University of Wollongong, is still in its infancy. We entered our brand new building in February 2011 and the research team has grown threefold since inception. In a relatively short period of time we have had to define our scientific identity, learn how to work together, engage with our peers, convince our partners or clients and, last but not least, deliver innovative research outcomes. In retrospect, the whole of SMART has become greater than the sum of its parts which is an essential quality when you aim at changing the way we plan for, design, manage and use our infrastructure systems. This Research Highlights 2013 covers our first two years of scientific production (2012 and 2013). It has been a challenging period as we had to simultaneously undertake significant commissioned research projects and to structure our inter-disciplinary scientific

content. The current organisation of our Research Groups has been partly shaped by the nature of the early projects we had to focus on. This demand-driven approach stems from the original concept associated with the SMART Infrastructure Facility: a research hub breaking down disciplinary silos and providing comprehensive solutions to complex infrastructure problems, as demonstrated by the early creation of our Rail Logistics group. We do not intend to become domain experts in all aspects of infrastructure systems and services but rather trusted analysts who can develop sophisticated data mining and computer simulation frameworks, in collaboration with our peers and partners. There already exist many research centres focusing on transport, water or energy distribution in Australia; the aim of the SMART infrastructure Facility is to complement the existing offering rather than to compete against it. In this regard, most of the recently delivered projects described in this report have tried to move away from a â&#x20AC;&#x2DC;business-as-usualâ&#x20AC;&#x2122; standpoint and propose new paradigms for urban modelling (see: Shaping the Sydney of Tomorrow project) or evidence-

based regional planning (see: SMART Infrastructure Dashboard project). The SMART Infrastructure Facility has now established strong collaborations with prominent research groups in Australia (Queensland University of Technology, University of South Australia, University of Melbourne and University of Sydney) and beyond (University College London, University of Oxford, Delft University of Technology and Arizona State University), leading to the highly successful organisation of the first International Symposium for Next Generation Infrastructure (ISNGI 2013, Wollongong, September 2013). We are also proud to have become a trusted partner for Transport for NSW, Sydney Trains, Sydney Water, Endeavour Energy, Remondis, Port Kembla Port Corporation, NSW Office of Environment and Heritage and the Australian National Data Service, as well as most of the public institutions and industry associations in the Illawarra region.

Prof Pascal Perez SMART Research Director

RESEARCH ORGANISATION

In 2013, the SMART Infrastructure Facility included three laboratories:

The IDS Lab provides support and capacity to the SRL Lab whenever needed.

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In 2013, the SRL Lab included Mr. A. McCusker and A/Prof. M. T. Ho. The role of the SRL Lab is to provide advice to the industry through consulting, inform IEG and IDS Labs about research needs of the industry and to translate scientific knowledge into practical outcomes.

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The Infrastructure Economics and Governance Laboratory (IEG Lab), led by Prof. Henry Ergas. The Infrastructure Data and Simulation Laboratory (IDS Lab), led by Prof. Pascal Perez. The SMART Rail Logistics Laboratory (SRL Lab), led by Mr. Andrew McCusker.

The IEG Lab focuses on contributing to the public debate on current and future status of infrastructure services and deliveries in Australia. In 2013, the IEG laboratory was lead by Prof. Henry Ergas. The IEG Lab is currently undertaking an ex-post cost-benefit analysis of large scale infrastructure projects in Queensland, Victoria and New South Wales (see: Infrastructure Cost Drivers project). The IDS Lab focuses on developing relevant resources for evidence-based infrastructure planning and management. These resources include data analytics and integrated modelling. In 2013, the IDS Lab included two senior academics (Prof. P. Perez and Prof. P. Campbell), twelve research fellows and four HDR students.

Research conducted by the IDS Lab has been organised within a capacity x delivery matrix (figure 1). Our capacity is distributed across five Research Groups: • • • • •

Advanced Geomatics for Regional and Urban Planning (AG4RUP) Computer Intelligence for Optimal Decisions and Operations (CI4ODO) Computer Simulation for Sustainable Transport Systems (CS4STS) Geo-social Intelligence for Urban Resilience and Liveability (GI4URL) Social Simulation for Demographic Dynamics and Transitions (SS4DDT)

Our various research groups contribute – whenever relevant – to specific commissioned research projects (delivery side of the matrix), and have to achieve pre-identified academic KPIs (publications, HDR students and competitive research grants). Commissioned research projects

and consultancies contribute to the sustainability of the SMART Infrastructure Facility through revenue, impact and strategic partnerships.

POSITION WITHIN UOW The University of Wollongong has a proud history of providing strong research that has national and international significance. SMART has leveraged the research of the University’s faculties and built strong collaborative partnerships with world leading organisations in the infrastructure research area. SMART plays an integral part in extending the University’s global reputation as a compelling intellectual partner in the development of infrastructure in Australia and abroad.

INFRASTRUCTURE ECONOMICS & GOVERNANCE LABORATORY (IEG LAB)

In 2013, the IEG laboratory included Prof. Henry Ergas (leader), Mr Garry Bowditch (CEO), Prof. Brian Collins (Visiting), Dr. Mark Harrison, Prof. Graham Harris (Honorary), Prof. John Gardiner (Honorary), Prof. Peter McVean (Honorary), Prof. Les Hosking (Honorary) and Mr Joe Branigan (Senior Research Fellow). If the ultimate goal of studying infrastructure is to ensure the best possible assets are built to promote the best possible liveability environments in our cities and towns, then the nature of infrastructure, being large, costly and long-lived assets, requires a careful study of the economics and governance arrangements around decisions to plan and build, price and set service delivery standards. Professor Henry Ergas, one of Australia’s leading economists, is the Director of the IEG Lab. His research interests cover a wide range of important public policy issues including the regulation of large infrastructure networks and best-practice cost benefit appraisal techniques. His expertise and publications range across many industries including transport, telecommunications, mining and

defence. Professor Ergas is a regular columnist for The Australian newspaper. Dr Mark Harrison’s main current research project is on road pricing. Traffic congestion and traffic accidents impose large external costs and determine the efficiency effects of real world road pricing schemes. The project examines the optimal combination of, and trade-offs between road charging, tort law and regulation to minimise the social cost of accidents, taking account of existing legal rules and government policies, including tax distortions, government mandated insurance requirements (such as compulsory third party and no-fault insurance) and problems with tort law and insurance markets. He is also continuing research on project evaluation, focusing on discounting in the long term (across over-lapping generations). Mr Joe Branigan is undertaking a large study into the cost drivers of infrastructure projects, particularly mega-projects worth more than 1 billion dollars. The cost of building new roads and rail lines has increased markedly over the past two decades, driven not only by rising labour and materials costs but also by the cumulative and pervasive

effects of regulations – such as more onerous technical standards, increasing red tape around environmental and safety standards as well as increased complexity caused by building in brownfields contexts. The study has the financial and data support of the NSW, Queensland and Victorian governments. The study will also benchmark these three participating jurisdictions against each other. Selected publications “Evidence-free Policy: The Case of the National Injury Insurance Scheme’ Agenda, Volume 20, Number 1, 2013 pp.55-69. http://epress.anu. edu.au/wp-content/uploads/2013/07/Evidencefree-Policy-The-Case-of-the-National-InjuryInsurance-Scheme-Mark-Harrison.pdf Ergas, H., Pincus J. (2013), ‘Have Mining Royalties been beneficial to Australia?’ Economic Papers. Ergas, H. (2013), ‘National Disability Insurance Scheme Funding: The Case for Hypothecation’, The Australian Economic Review, vol. 46, no. 3, pp. 338-44. Ergas, H. (2013) ‘Why Johnny Can’t Regulate: The Case of Natural Monopoly’, Agenda, A Journal of Policy Analysis and Reform, Vol.20, No. 1. Ergas, H. and Robson, A. (2013), ‘Revenue Allocation under the MRRT: Economic Aspects’, Journal of Australian Taxation, Vol. 14, No. 2.

SMART RAIL LOGISTICS LABORATORY (SRL LAB)

In 2011, the SMART Rail Logistics Laboratory (SRL) was established. Headed by Mr Andrew McCusker, the SRL Lab is a research body committed to developing railway transport management systems and enhancing competitiveness in the rail industry through research and development. Rail is an integrated system of society and technology. In order to sustainably operate this complex system, the SRL Lab’s approach focuses on affordability, customer satisfaction, profitability, knowledge management and competitive performance. The SRL Lab collaborates closely with partners to contribute to advanced rail infrastructure productivity, planning and modernisation. Our focus covers a number of research dimensions developed through consultation with industry. Our research portfolios include: •

Society and human dynamics for railway systems

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Commercial sustainability and resilience for primary assets

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Business life cycle for principle asset

Selected Publications

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Technology and knowledge transfer

(2014). Towards Better Understanding the

•

Policy and evaluation

Currently, the SRL Lab is focussing on five different research topics: 1.

Social network approaches to enhancing corporate capability

Modelling customer preference heterogeneity in mode choice

Complexity management model for passenger railway service

4. Evaluation of KPIs for productive railway system management 5.

Commercial asset life cycle management

The SRL Lab also conducts masterclasses for rail professionals in regards to technology and knowledge transfer. Current master class themes involve creating a world class rail organisation, decision making in a complex world, leadership for leaders and risk and culture conflict.

Anwar, A.H.M.M., McCusker, A. and Perez, P. Effect of Social Network on Organisational Success. The 11th International Conference on Intellectual Capital, Knowledge Management & Organisational Learning (ICICKM2014), Sydney, Australia, 6-7 November. Anwar, A.H.M.M., Tieu, K., Gibson, P., Berryman, M., and Win, K.T. (2014). Analysing the Heterogeneity of Traveller Mode Choice Preference Using A Random Parameter Logit Model from the Perspective of Principal-Agent Theory. International Journal of Logistics Systems Management, Vol. 17, No. 4, pp. 447471. Anwar, A.H.M.M., Tieu, K., Gibson, P., Berryman, M., and Win, K.T. (2013). Analysing the Merit of Latent Variables over Traditional Objective Attributes for Traveller Mode Choice Using RPL Model. Presented in the International Choice Modelling Conference, Sydney, Australia, July 3-5.

INFRASTRUCTURE DATA & SIMULATION LABORATORY (IDS LAB) Funding, Partnership, Impact

090903 090505 120505 140218 080110 010206 090507 090505 080109 080108 010206 150309 160301 160810 080502 080709 080110 010401 120505 160301

AG4RUP CS4STS CI4ODO

PublicaQon Grant HDR

GI4URL SS4DDT PKPC

T4NSW

NHMRC

ANDS

AURIN

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Figure 1 – SMART MATRIX

A major challenge for the Infrastructure Data and Simulation stream has been to develop a suitable scientific organisation while responding as swiftly as possible to external demands in order to support a sustainable growth. Our current research organisation reflects upon this constant and positive tension between capacity building and project delivery. Another challenge arose from the early decision to grow scientific leadership from within rather than trying to import too many senior academics from inception. This risky social experiment has proven to be a successful one; not only have research groups forged their identity through a learning-by-doing process but they have developed well-respected leaders. The Advanced Geomatics for Regional and Urban Planning (AG4RUP) group, led by Dr. Rohan Wickramasuriya, develops two complementary research activities. The first one focuses on collecting, warehousing and analysing regional infrastructure data across various utilities (transport, water, energy and waste) in order to provide

comprehensive sources of information to regional planners, managers and researchers. The second activity aims at developing a new generation of regional planning models stepping away from traditional and limited feed-forward trend modelling. The Computer Intelligence for Optimal Decision and Operation (CI4ODO) group, led by Dr. Nagesh Shukla, develops advanced statistical methods and machine learning algorithms in order to extract temporal and spatial patterns from various data sets. Domains of application include transport behaviour, demographics, population health and logistics. The Computer Simulation for Sustainable Transport Systems (CS4STS) group, led by Dr. Nam Huynh, uses various modelling paradigms, like crowd motion simulations and regional traffic optimisation, in order to better understand drivers and limiting factors to sustainable transport systems. The CS4STS group offers a unique mix of expertise ranging from operation research to agent-based modelling.

The Geo-social Intelligence for Urban Resilience and Liveability (GI4URL) group, led by Dr. Etienne Turpin, undertakes ground-breaking research on advanced use of social media and mobile technologies in order to implement co-management strategies for the maintenance of infrastructure assets or the deployment of emergency responses. This group also revisits the concept of urban liveability by bringing together objective and subjective approaches. The Social Simulation for Demographic Dynamics and Transitions (SS4DDT) group, led by Dr. Mohammad Namazi Rad, is working closely with the National Institute for Applied Statistics Research Australia (NIASRA) in order to create and evolve small scale synthetic populations and activity models. This research is essential to better understand and anticipate social responses to policy or technological changes.

Projects SMART Infrastructure Dashboard. Funding: ANDS. Period: 2011-13. Contact: R. Wickramasuriya. Shaping the Sydney of Tomorrow. Funding: Transport for NSW. Period: 2010-13. Contact: P. Perez. Selected publications Wickramasuriya, R., Ma, J., Berryman, M. & Perez, P. (2013). Using geospatial business intelligence to support regional infrastructure governance. Knowledge-Based Systems, 53: 80-89. Holderness, T., Barr, S., Dawson, R. & Hall, J. (2013). An evaluation of thermal Earth observation for characterizing urban heatwave event dynamics using the urban heat island intensity metric. International Journal of Remote Sensing, 34 (3), 864-884.

ADVANCED GEOMATICS FOR REGIONAL AND URBAN PLANNING (AG4RUP)

Ma, J., Wickramasuriya, R., Safadi, M., Davies, T. & Perez, P. (2013). A conceptual method for modeling residential utility consumption using complex fuzzy sets. In: W. Pedrycz & M. Z. Reformat (Eds.), Proceedings of the Joint World Congress and NAFIPS Annual Meeting). IEEE Xplore: Digital Library, IFSA 2013, pp 1227-1232. Online: http:// ieeexplore.ieee.org/xpls/icp.jsp?arnumber=6608576 Members J. Ma (SMART, UOW) T. Holderness (SMART, UOW) V. L. Cao (SMART, UOW) N. Shukla (SMART, UOW) M. Namazi-Rad (SMART, UOW) Associates

Fusion of GIS & Business Intelligence

P. Winberg (SMH, UOW) A. Masouman (BUS, UOW) C. Woodroffe (SMH, UOW)

Social communities and environments they inhabit co-evolve in space and time, resulting in complex and dynamic interdependencies. Advanced geomatics provides tools and methods to better understand these spatio-temporal dynamics in order to better inform urban and regional planning. This Research Group uses GIS mapping, spatial topology, data mining and business intelligence techniques together to explore urban and regional development, infrastructure network interdependencies and vulnerabilities. In particular, they use the Genomica platform to couple spatially disaggregated land use models with regional input/output economic models and transport models.

E. Lengham (UTS, Aus)

Future work will include collaboration with the Australian Urban Research Infrastructure Network (AURIN) on developing and federating regional spatial data hubs across Australia. Our SMART Research Group will also collaborate with the Industrial Ecology Lab (IE Lab) consortium to explore regional socio-economic scenarios associated with the collapse or emergence of new transformation or manufacturing industries.

SEO Codes

C. Pettit (Uni Melbourne, Aus) D. Anderson (Uni Newcastle, UK) FOR Codes 090903-Geospatial Information Systems 090505-Infrastructure Asset Management 120505-Regional Analysis & Development 140218-Urban & Regional Economics 8701-Construction Planning 8506-Energy Distribution & Supply 8801-Ground Transport 9004-Water & Waste Services

Key areas of research:

Project Lead Rohan Wickramasuriya

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Developing user-friendly online infrastructure dashboards for urban and regional planners

Email rohan@uow.edu.au

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Identifying vulnerabilities associated with increasingly interdependent infrastructure networks

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Understanding urban heat island effect through remote sensing and high performance computing

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Uncovering hidden pattern within large infrastructure datasets using spatiotemporal data mining

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Simulating regional planning scenarios through spatially and socially disaggregated modelling.

Projects SMART Infrastructure Dashboard. Funding: ANDS. Period: 2011-13. Contact: R. Wickramasuriya. Shaping the Sydney of Tomorrow. Funding: Transport for NSW. Period: 2010-13. Contact: P. Perez. Selected publications Nagesh Shukla, M K Tiwari, D. Ceglarek (2013). Genetic Algorithm based algorithm portfolios for Inventory Routing problems. Published online in International Journal of Production Research.

COMPUTATIONAL INTELLIGENCE FOR OPTIMAL DECISION AND OPERATION (C14ODO)

Ulutas, A., Kiridena, S., Gibson, P. & Shukla, N. (2012). A novel integrated model to measure supplier performance considering qualitative and quantitative criteria used in the supplier selection process. International Journal of Logistics and SCM Systems, 6 (1), 57-70. Dunbar, M., J. M. Murray, L. A. Cysique, B. J. Brew and V. Jeyakumar (2010). Simultaneous classification and feature selection via convex quadratic programming with application to HIVassociated neurocognitive disorder assessment. European Journal of Operational Research, 206, 470–478 Members J. Ma (SMART, UOW) N. Huynh (SMART, UOW) M. Dunbar (SMART, UOW) J. Yang (SMART, UOW) A. M. Anwar (SMART, UOW)

Data-driven Analysis for Evidence-based Decisions The increasing availability of large datasets associated with various infrastructure systems – ranging from transportation and energy to logistics and supply chains, has triggered the development and successful application of advanced computational intelligence to help with smarter decisions, faster actions and better outcomes associated with industrial or infrastructural issues. Computational intelligence uses machine learning and optimisation techniques to recognise patterns and to extract meaningful information out from reliable datasets. While a specific method (neural network or fuzzy logic, for example) may provide a satisfying solution to a given problem, there is no guarantee that it will be the case for a slightly more complex instance of the same problem or an equivalent problem in a totally different domain of application. Drawing from experience in Operations Research (OR) and data mining, this Research Group aims to improve or combine existing methods and to develop new solutions for computational intelligence applied to infrastructure management, logistics and supply chain. One particular focus is to bring together different aspects of nature-inspired computing research work on neural networks, support vector machines, fuzzy logic and evolutionary computation. Some of the topics we are currently working on are: • Using machine learning methods and fuzzy logic to improve travel mode choice predictions • Using data mining and optimisation techniques to understand and model social dynamics • Using optimisation to assist computational models in materials engineering and manufacturing • Using operation research techniques to solve logistics and supply chain issues.

Associates T. Boehme (SBS, UOW) S. Wang (EIS, UOW) S. Kiridena (EIS, UOW) A. Munoz (EIS, UOW) A. Miller (EIS, UOW) W. Zhao (EIS, UOW) FOR Codes 080109-Pattern Recognition & Data Mining 080108 –Nueral & Evolutionary Computation 010206-Operations Research 150309-Logistics & Supply Chain Management SEO Codes 8801-Ground Transport 9104-Management & Productivity 9202-Health & Support Services Project Lead Nagesh Shukla Email nshukla@uow.edu.au

Projects PetaJakarta.org. Funding: UOW, ANDS, Global Challenges,. Period: 2013-2015. Contact: E. Turpin. Shaping the Sydney of Tomorrow. Funding: Transport for NSW. Period: 2010-13. Contact: P. Perez. Selected publications Namazi-Rad M., Berryman M., Perez P. (2014). Dynamic Modeling of Residential Choice based on Empirical Determination of Perceived Liveability. Accepted by Social Indicators Research. Turpin, E. (2013). Architecture in the Anthropocene: Encounters Among Deep Time, Design, Science and Philosophy. Ann Arbor: MPublishing/Open Humanities Press.

GEO-SOCIAL INTELLIGENCE FOR URBAN RESILIENCE AND LIVEABILITY (G14URL)

Grant, R. G., Clarke, R. J. & Kyriazis, E. (2013). Modelling real-time online information needs: A new research approach for complex consumer behaviour. Journal of Marketing Management, 29 (7), 950-972 Members T. Holderness (SMART, UOW) R. Wickramasuriya (SMART,UOW) M. Namazi-Rad (SMART, UOW) M. Safadi (SMART, UOW) Associates R. Clarke (BUS, UOW) I. Buchanan (LHA, UOW) G. Waitt (SS, UOW) L. Oades (BUS, UOW)

From Crowd-sourcing to Geo-social Intelligence This Research Group focuses on two complementary social aspects of urban and infrastructure development in Australia and South East Asia: liveability and resilience. Despite a significant volume of international research on well-being and happiness, the way physical and social environments influence peopleâ&#x20AC;&#x2122;s quality of life has long been explored using so-called objective indicators. Although they present some advantage for comparing cities around the world, they fail to provide insight into how people perceive and react to their environment. This Research Group uses methods coming from ethnography and quantitative sociology mixed with social informatics (mobile technology and social media) to better understand and model social responses to policy or infrastructure changes. Urban Resilience research advances our capacity to understand and promote the resilience of cities to sudden extreme events as well as long-term infrastructure transformation needed to adapt to them. These events can have natural causes (flooding, bushfire or hurricane) or human ones (terrorism, pollution or infrastructure failure). CogniCity A Geo-Social Intelligence framework sorts the noise of social media into knowledge about the city; this framework allows us to capture critical social media data about environmental variables, infrastructure functionality, and individual and government responses to extreme events in real time and relays this information through public information systems and next generation decision support tools. Our Geo-Social Intelligence platform, called CogniCity, allows for situational information to be collected and disseminated by community members through their locationenabled mobile devices and optimises infrastructure surveys and asset management for governmental actors. Equipped with scalable mapping technology for mobile devices and a critical alert service, this software enables the communication of two-way timecritical information to and from individuals and government agencies.

L. Buys (QUT, Aus) R. Stimson (Uni Melbourne, Aus) K. Djaja (Universitas Indonesia) P. Perez (SMART, UOW) FOR Codes 160301-Family & Household Studies 160810-Urban Sociology 7 Community Studies 080502-Mobile Technologies 080709-Social & Community Informatics SEO Codes 8701-Construction Planning 8801-Ground Transport 9004-Water & Waste Services 9204-Public Health Project Lead Etienne Turpin Email eturpin@uow.edu.au

SOCIAL SIMULATION FOR DEMOGRAPHIC DYNAMICS AND TRANSITIONS (SS4DDT) Projects Shaping the Sydney of Tomorrow. Funding: Transport for NSW. Period: 2010-13. Contact: P. Perez. The value of providing health interventions for heroin use: a cost-benefit analysis. Funding: NHMRC (APP1042923). Period: 2012-2015. Contact. N. Shukla. Selected publications Namazi-Rad M., Mokhtarian P., Perez P. (2014). Generating a Dynamic Synthetic Population Using and Age-Structured Two-Sex Model for Household Dynamics. Accepted by PLOS-ONE.

When Demographics Meets Agent-based Modelling This Research Group focuses on three complementary aspects of social simulation: (1) creating and evolving accurate synthetic populations (2) developing realistic activity models for synthetic individuals and households

Huynh. N., Namazi-Rad M., Perez P., Berryman M.J., Chen Q., Barthelemy J. (2013). Generating a Synthetic Population in Support of AgentBased Modelling of Transportation in Sydney. In Piantadosi J., Anderssen R.S. and Boland J. (eds) MODSIM2013, 20th International Congress on Modelling and Simulation. MSSANZ, Canberra, pp1357-1363. http://www.mssanz.org.au/ modsim2013/B1/Huynh.pdf. Members M. Berryman (SMART, UOW)

(3) integrating these active synthetic individuals into spatially explicit agent-based models.

P. Mokhtarian (EIS, UOW)

A synthetic population (SP) aims at faithfully reproducing actual social entities, individuals and households, and their characteristics as described in a population census. Depending on the quality and completeness of the input data sets, as well as the number of variables of interest and hierarchical levels (usually, individual and household), we use synthetic reconstruction or combinatorial optimisation (e.g. Hill Climbing approach) to generate the initial population. Our most recent research focuses on developing a dynamic SP using an age-structured, two-sex model for household dynamics.

N. Shukla (SMART, UOW)

N. Huynh (SMART, UOW) P. Perez (SMART, UOW) Associates R. Chambers (EIS, UOW) A. Miller (EIS, UOW) G. Singh (CSIRO, AUS) C. Barrett (Virginia Tech, USA)

Developing a SP is often a means to an end as synthetic individuals have to perform some tasks or display behavioural patterns, the consequences of which are of interest to researchers and practitioners.

J. Barthelemy (Uni Namur, B)

Activity Models

120505-Regional Analysis & Development

FOR Codes 010401-Applied Statistics 080110-Simulation & Modelling

It is the role of Activity Models (AM) to provide each individual with specific goals and associated means. When a specific survey data set is available, computational intelligence is used to directly extract the relevant information (see SMART Research Group CI4OIS).

160301-Family & Household Studies

For example, in transport modelling, travel diaries and transport mode choices can often be inferred from household travel surveys. In other cases, rules have to be created based on utility maximisation principles or simple heuristics.

9204-Public Health

Synthetic Populations and Activity Models have been traditionally used with microsimulation to generate behavioural evolution and heterogeneity for transport planning, taxation policy and other trend analyses. Unfortunately, integrated urban or infrastructure planning is often faced with strong spatial and social interactions and feedbacks that cannot be ignored by the model-in-use. Agent-based modelling (ABM) offers a versatile and spatially explicit approach to social simulation. Our SMART Research Group has overcome a usual limitation of ABM by deploying the RePAST-HPC platform on our high performance computing cluster, allowing for the implementation of massive ABM applications.

SEO Codes 8701-Construction Planning 8801-Ground Transport 9004-Water & Waste Services

Project Lead M. Namazi-Rad Email mrad@uow.edu.au

Projects Shaping the Sydney of Tomorrow. Funding: Transport for NSW. Period: 2010-2013. Contact: P. Perez. RailNet â&#x20AC;&#x201C; maximizing coal throughput at Port Kembla terminal with rail constraints. Funding: Port Kembla Port Authority. Period: 2010-2011. Contact: N. Huynh. Selected publications Shukla N., Munoz A., Ma J., and Huynh N.(2013). Hybrid Agent based Simulation with Adaptive Learning of Travel Mode Choices for University Commuters. In: Workshop on model-driven approaches for simulation engineering (Mod4Sim) Symposium on Theory of Modeling and Simulation (SCS SpringSim 2013 conference, April 7-10, 2013, San Diego, CA).

COMPUTER SIMULATION FOR SUSTAINABLE TRANSPORT SYSTEMS (CS4STS) Sophisticated Modelling to Explore Complex Problems This Research Group aims at enhancing our understanding of capacity and robustness of transport networks. Various elements of a transport system are examined, such as road/ rail/air traffic, design and operation of railway stations or airport terminals. We use various computer simulation techniques like constraint modelling, micro-simulation, network analysis or crowd simulation to explore complex problems at hand. Current research focuses on four domains of application: (1) coupling of traffic micro-simulation with residential mobility modelling, (2) vulnerability analysis of rail networks, (3) crowd simulation in railway stations and airport terminals, and (4) accessibility to and synchronisation of urban transport hubs. TransMob Model Our TransMob model, developed for Transport for NSW, is a first attempt to couple a traffic micro-simulator with a residential mobility model for exploring long-term consequences of various transport and land use planning scenarios. This model was developed in collaboration with SMART Research Group SS4DDT. Our work on vulnerability analysis of rail networks focuses on rail services (freight and passenger) in Sydneyâ&#x20AC;&#x2122;s Greater Metropolitan Area. We use constraint optimisation (see SMART Research Group CI4ODO) in conjunction with computer simulation platforms e.g. OpenTrack and FlexSim, to assess the network vulnerability to various types of disruption. We use state-of-the-art crowd simulators e.g. Mass Motion and CAST Terminal, to explore the consequences of an increase in people with a limited mobility (due to ageing or health issues) on operations in railway stations and airport terminals. Finally, our research on transport hubs focuses on integrating scheduling with graph-based network models to understand how feeder-service frequency impacts transport hub accessibility for surrounding populations. These models can provide a suite of decision-making tools for analysis of investment strategies and policy scenarios.

Wang S. (2013). Efficiency and equity of speed limits in transportation networks. Transport Research Part C: Emerging Technologies, Pergamon, 61-75. Chen, S.K., Ho, T.K. and Mao, B.H. (2014). Maintenance Schedule Optimisation for a Railway Power Supply System. Accepted by International Journal of Production Research. Members P. Campbell (SMART, UOW) V. L. Cao (SMART, UOW) J. Yang (SMART, UOW) M. Dunbar (SMART, UOW) T. K. Ho (SMART, UOW) M. Berryman (SMART, UOW) Associates A. Munoz (BUS, UOW) S. Wang (EIS, UOW) A. Ghose (EIS, UOW) C. Macal (EIS, UOW) M. Mujica Mota (Uni Amsterdam, NL) J. Barthelemy (Uni Namur, B) FOR Codes 080110-Simulation & Modelling 010206-Operations Research 090507-Transport Engineering 090505-Infrastructure Engineering & Asset Management SEO Codes 8801-Ground Transport 8803-Aerospace Transport 9104-Management & Productivity Project Lead Dr Nam Huynh Email nhuynh@uow.edu.au

RESEARCH PROJECTS SHAPING THE SYDNEY OF TOMORROW

SMART INFRASTRUCTURE DASHBOARD

Since 2010, Transport for NSW and the SMART Infrastructure Facility have collaborated on developing an interactive, visually intuitive and highly flexible simulation platform to support transport and urban planning in Sydney. In the resulting agent based model “TransMob”, simulation agents represent individuals and households living in an urban area. The heterogeneity of this synthetic population is represented in terms of demographic characteristics, environmental perceptions (e.g. traffic congestions, number of available facilities of various types available per person, availability and affordability of housing stocks) and decision making behaviours. Inherently, the simulated population will evolve over time facilitating the interactions between dynamics of residential relocation of households, transportation behaviours and population growth. Thanks to this feature, the model can be used for exploring longterm (e.g. 20 year time horizon) consequences of various transport and land use planning scenarios.

The SMART Infrastructure Dashboard (SID) is a user-friendly, web-accessible, analytical and visualisation platform that supports decision making related to local and regional governance of infrastructure services. SID aims to inform planners and policy makers about the current and the past statuses of infrastructure systems and services, as well as their spatial and temporal interdependencies. SID also enables planning for the future by allowing planners to run ‘what-if’ scenarios on issues ranging from forecasting of utility usage, potential financial and Co2 savings from energy efficiency programs to transportation planning.

The simulation workflow includes an agent-based model (RePAST) and a micro-simulation traffic model (TRANSIMS). In order to view the outputs, a YellowFin based platform is included for the visual interface. The project was funded by Transport for NSW for 3 years (2010-13). PROJECT LEAD Dr Nam Huynh EMAIL nhuynh@uow.edu.au

SID receives data from both public and private institutes such as city councils, Australian Bureau of Statistics, Bureau of Meteorology, Sydney Water, Endeavour Energy and REMONDIS. Industry-strength Extract, Transform and Load (ETL) workflows migrate incoming data into a star schema-based data warehouse. Geospatial Business Intelligence tools are used to author private and public analytical reports and dashboards that can be consumed by subscribers depending on their access level privileges. SID strongly rests on a collaborative model where stakeholders can contribute not only through data provision, but also by managing data and authoring reports. This is a unique feature of SID that ensures its sustainability as a decision support system. PROJECT LEAD Dr Rohan Wickramasuriya EMAIL rohan@uow.edu.au

CONSTRAINT MODELLING OF RAILWAY SYSTEM

UOW TRAFFIC MODELLING

SMART has developed a simulation freight model (â&#x20AC;&#x153;RailNetâ&#x20AC;?) to provide the Port Kembla Port Corporation and Collaborating Partner Organisations with a tool to model the NSW rail network serving the Port of Port Kembla. The model will identify any additional freight paths available in the rail network leading to the port after all the passenger trains are also placed in the network. In addition, the introduced freight paths had to be scheduled to run with minimal dwelling/staging, and synchronise with Port Kembla Coal Terminal (PKCT) operations. The proposed objective is to maximise the freight throughput allowing for predetermined and ad hoc network availability.

This project aims at developing a hybrid agent based and micro-simulation model to simulate the travel mode choices of commuters (students and staff) to and from the University of Wollongong (UOW) main campus for study and work. This helps us understand the current modal splits and factors affecting the travel mode choice decisions. The model also enables investigations of future travel scenarios for the commuters coming to and from UOW.

The model was calibrated so that it can accommodate dynamic system changes that result from changed freight operating parameters, other operators and RailCorp. The model provides the Port Kembla Port Corporation, as well as users of the rail network, the ability to quantify the capacity of the rail network to provide sufficient access to the port, which was imperative before any commitment of huge capital expenditures for infrastructure upgrades at the port. This project was funded by Port Kembla Port Corporation, Port Kembla Coal Terminal, Pacific National and BlueScope for 1 year and was in collaboration with CSIRO and RailCorp. PROJECT LEAD Dr Dr Nam Huynh EMAIL nhuynh@uow.edu.au

The project largely utilises the information available from the UOW Transport Questionnaire Survey conducted in 2009 and 2011 by the Facilities Management Division (UOW); NSW Roads and Maritime Services; and UOW students and staff data. The UOW transport surveys capture the travel movements undertaken by commuters (staff and students) of the University of Wollongong for their daily activities. Questions in these surveys are designed to (1) measure the transport modal splits, (2) provide insights into attitudes of commuters for changing transport options and (3) report issues with the current transport options. PROJECT LEAD Dr Nam Huynh EMAIL nhuynh@uow.edu.au

VALUE OF HEALTH INTERVENTIONS FOR HEROIN USE

CANCER RADIOTHERAPY MODELLING PROJECT

The aim of the project is to assess the net social benefit of the current treatment strategy for drug users and to evaluate, through modelled scenarios, different combinations of treatment. This will lead to better informed decisions about the mix and type of treatments in which governments invest. Illicit drug use has created an enormous burden at societal, familial and personal levels. Every year a significant amount of resources are allocated for treatment and consequences of illicit drug use in Australia and around the world.

This project will aim at developing an integrated approach for radiotherapy service planning that combines future geographical projections of cancer incidence with the placement of new radiotherapy (RT) services designed to maximise patient uptake rates (due to travel distances).

Heroin is one of the major forms of illicit drugs and several independent heroin treatment strategies or interventions exist. State-of-the-art research demonstrates their efficacy and relative cost-effectiveness. However, assessing total potential gains and burden from providing all treatment interventions or varying the mix of heroin treatments has never been attempted. Furthermore, the need to include multiple treatments, multiple important outcomes and the chaotic nature of drug dependence means costeffectiveness studies are not able to provide evidence on the net benefit of providing heroin treatments over a lifetime. Evaluations of the current mix of treatment provision remain very limited. This project will discuss an individual level model which addresses net social benefit that can accommodate the complexity of individuals going in and out of multiple treatments and their corresponding costs and benefits arising from different treatments during the life-course of heroin users. This model is intended to serve as an effective tool for economic evaluation and policy making in illicit drug areas in Australia. This project is funded by NHMRC for three years in collaboration with NDARC, University of NSW. PROJECT LEAD Dr Nagesh Shukla EMAIL nshukla@uow.edu.au

The main objective of this research is to develop a model of demand and supply for RT services based on past and present data and future predictions and develop a systematic tool for the assessment of placement options of new RT services so as to maximise future access to RT treatment. This research study will assess current RT services planning strategy and to evaluate, through modelled population projections and incidences, future planning of radiotherapy services. This will lead to better patient access to RT treatment services and survival; and informed decisions about the government investment concerning the placement of new RT treatment services. PROJECT LEAD Dr Mohammad-Reza Namazi-Rad EMAIL mrad@uow.edu.au

INFRASTRUCTURE COST DRIVERS This project endeavours to understand the cause of rising transport infrastructure costs in Australia over the past two to three decades. SMART’s economic team is undertaking a detailed comparison of transport infrastructure costs over time, across jurisdictions, transport modes and by project scale. The aim is to unpack the drivers behind the increases in the costs of building and maintaining new roads, rail networks and other transport infrastructure. Furthermore, we aim to establish a database so as to benchmark these cost drivers to inform future policy design and implementation of projects. To better inform this research we need to gather and analyse detailed case studies. We have identified 15-20 matched case studies for roads in QLD and developed a cost database for these particular case studies which includes some initial analysis. Early analytical results suggest that the economic cycle has been a key cost driver (in boom times accounting for up to a 25% premium above ‘normal’ costs). Changes in environmental and safety regulations over time have also been a key factor in rising costs, although many experts have argued that the increased safety requirements have largely been worthwhile despite the increase in cost. The NSW study is focussed on rail projects and preliminary analysis of rail construction costs (per track km) reveal an extraordinarily wide variation in costs across projects. The average total construction cost per track kilometre for rail projects for NSW projects is around $50 million, which is almost double some estimates for the rest of Australia.

In general terms, the methodology for undertaking this project is to: •

Collect cost of infrastructure data by individual cost driver (materials, labour, etc.) across time and by related projects (eg. large road project in Sydney in the 1980s, 1990s and 2000s)

•

Undertake mathematical and/or econometric analysis to determine which parameters are the main cost drivers of infrastructure project costs

•

Cross-check this analysis with publicly available ‘macro’ data from the ABS and BITRE and other public data sources

•

Ask, what are the reasons for these increases in costs? For instance, if the cost (in real terms) of laying 10 km of freeway has doubled between decades, does this reflect, for example, resource scarcity (whether materials, labour or capital), or does it reflect a change contract design, quality standards, risk sharing or governance?

•

Being able to answer this question directly (as opposed to indirectly or a ‘residual’) will require high quality interviews and case studies being supplied by participants. This is because the contracts that set the approved costs for these projects are not publicly available.

The NSW and QLD Governments have engaged SMART to undertake this research as they see the benefit in understanding the motivators behind cost increases in this domain. PROJECT LEAD Mr Joe Branigan EMAIL joe_branigan@uow.edu.au

RESEARCH TEAM Professor Pascal Perez – Research Director Professor Pascal Perez is a world leader in participatory modelling of complex systems. He is the co-editor of ‘Complex Science for a Complex World – Exploring Human Ecosystems with Agents” (ANUE-Press). Before joining the University of Wollongong, he was a Team Leader at CSIRO and an Associate Professor at the Australian National University. Professor Pascal Perez has 20 years experience working in South East Asia, Western Africa, Pacific Island Countries and Australia. He is responsible for the management and delivery of all aspects of infrastructure modelling and simulation at the SMART Infrastructure Facility. As Research Director he is responsible for SMART’s academic governance and for establishing strategic scientific partnerships in Australia and beyond.

Mr Andrew McCusker – Director, Rail Logistics Appointed as SMART’s inaugural Director of Rail Logistics in late 2011, Andrew is currently developing and leading the SMART Rail Logistics Division in establishing a research capability to support and champion the role of rail as part of the broader transport network in Australia. To date, has provided executive learning in building higher performance rail organizations through a series of module development and master class delivery for the industry and has also been supporting the NSW government on the rail strategy for Sydney and NSW. Andrew serves on a number of committees concerned with the strategy and execution of rail futures in NSW.

Prior to his current role, Andrew has worked in the Hong Kong MTR Corporation for 24 years. An organisation that is recognised as one of the world’s leading railway companies renowned for leading edge customer service and service performance in passenger rail. Prior to his career in rail, Andrew was Chief Engineer to the Bahrain State Power Authority where he was in charge of power & water production, network control and new construction. During his time in Bahrain he oversaw the transformation of the electrical system from one with endemic failures to establishing a highly secure electricity and water supply system which achieved international standards.

SENIOR ACADEMICS

Peter Campbell – Professor of Infrastructure Systems Professor Peter Campbell is a world authority on agent-based modelling. He is the former Director, Advanced Computer Applications Center at Argonne National Laboratory in Chicago. Professor Campbell has interdisciplinary modelling experience across the physical, biological and social domains that enable him to play a key role in shaping a strong interdisciplinary collaborative culture at SMART. His experience in research and consulting management allows him to provide project leadership to SMART’s commissioned research projects.

Henry Ergas – Professor of Infrastructure Economics Professor Henry Ergas held a range of leading positions at the OECD before returning to Australia in the mid-1990s. He chaired the Australian Intellectual Property and Competition Review Committee for the Australian Government in 1999-2000 and was a member of the Prime Minister’s Export Infrastructure Task Force in 2005 and the Defence Industry Policy Review in 2006. He has published extensively on infrastructure regulation and cost-benefit analysis.

He is the inaugural Professor of Infrastructure Economics at SMART where his focus is on the economic, regulatory and public policy research program. He takes a special interest in the development and application of cost-benefit analysis and in the analysis of pricing and investment decisions in regulated infrastructure industries. Professor Ergas is also a regular columnist in The Australian and Senior Economic Adviser at Deloitte Access Economics.

Joe Branigan – Senior Research Fellow Mr Joe Branigan is an economist specialising in the economic regulation of infrastructure. His experience has covered both government and the private sector roles, including with the Federal Treasury and Productivity Commission, as well as Ernst & Young and the Queensland Competition Authority. Joe has many years experience and expertise advising in a number of sectors including resources, electricity, water, ports and roads. He holds a Bachelor of Economics (Hons) from the University of Queensland and is a member of the Economics Society of Australia.

Mark Harrison – Senior Research Fellow Dr Mark Harrison is part of Professor Ergas’ infrastructure economics team at SMART and a Lecturer at the ANU College of Business and Economics. Mark has 30 years experience in undertaking applied economic research and providing policy advice as a public servant, academic and consultant. He has been a visiting researcher at the Research School of Social Sciences at the ANU, the George Stigler Centre for the Study of the Economy and the State at the University of Chicago and the Productivity Commission and Australian Bureau of Agricultural and Resource Economics in the Australian Government. He has a PhD in economics economics from the University of Chicago (USA).

RESEARCHERS

Dr. Matthew Berryman Dr Matthew Berryman completed his PhD in complex systems modelling and analysis at the University of Adelaide in 2007. From 2007-2009, he worked for the Australian Defence Science and Technology Organisation before joining the University of South Australia in 2009. Matthew has extensive experience in systems engineering and agent-based modelling of complex systems. At the SMART Infrastructure Facility, he applies these skills to model Australia’s future infrastructure needs and to make existing infrastructure smarter though the use of technology.

Mr. Vu Lam Cao

Dr. Nam Huynh

Mr. Vu Lam Cao completed his Bachelor of Information Technology at Ho Chi Minh City University of Foreign Languages and Information Technology followed by a Master of Information Technology Management and Master of Information and Communication Technology at the University of Wollongong. Vu Lam has extensive experience using and developing traffic micro-simulation software to build up and analyse the transportation network and agent reaction.

Dr. Nam Huynh received his Bachelor of Engineering degree in Aeronautical Engineering from the Vietnam National University, Ho Chi Minh City, Vietnam in 2004. He received his Master of Engineering Practice degree in Mechatronics in 2005, and a PhD degree in Mechanical Engineering in 2010 from the University of Wollongong. His research interests include modelling of engineering systems (eg with finite element method – FEM), logistics and supply chain systems and agent based simulation.

Dr. Michelle Dunbar

Dr. Jun Ma

Dr. Michelle Dunbar recently completed her PhD in Applied Mathematics at the University of New South Wales. Michelle has experience in applying mathematical optimisation techniques to real-world airline networks; to assist in the integration of key operational decisions and in providing robust solutions under operational uncertainty. She also has experience in applying non-linear optimisation tools to a variety of medical datasets to allow for improved disease detection and diagnosis; one of these tools has subsequently been taken up by a health care company.

Dr. Jun Ma is an experienced researcher in uncertain information processing and dynamic analysis. Before joining the SMART Infrastructure Facility, he worked as a senior research associate at the University of Technology, Sydney (UTS). He has over 10 years experience working in a research and teaching capacity in China and Australia.

Dr. Mohammad-Reza Namazi-Rad

Dr. Tomas Holderness Before coming to Australia Tomas was working as a research associate at the School of Civil Engineering and Geosciences, Newcastle University, UK, where he was responsible for developing a modelling framework for integrated urban assessment models created as part of the Tyndall Centre Engineering Cities project.

Tom completed his PhD, investigating the use of long-temporal baseline Earth observation datasets for urban climate analysis, at the University of Newcastle, UK.

Dr. Mohammad Namazi has been working as a statistician across a number of institutes since 2004. Over the last 10 years, he has completed numerical studies, performing well in working with different data-sets. His research experiences assist him in designing surveys and collecting, organising and interpreting quantifiable data. Since 2011, Dr. Namazi has been working at the SMART Infrastructure Facility as the Research Fellow in Statistical Modelling & Simulation. In his role at SMART, he is responsible for conducting research on the statistical methodology for simulating reliable infrastructure models while being responsible for leading and

undertaking commercial research and contributing towards the research effort and research expertise of SMART in relation to the development and application of infrastructure simulation and modelling.

considers the social consequences of infrastructure transformation as a result of rapid development and climate change. Through site-based, empirical data collection and novel uses of social media and Geo-Social Intelligence, his work develops new tools to help democratise processes of urban transformation by more fully engaging the concerns and capacities of the urban poor.

Dr. Nagesh Shukla Dr. Nagesh Shukla is a well-known researcher in the Industrial & Systems Engineering domain, particularly in the areas of Simulation Modelling and Optimisation. He has research experience working with large hospitals in United Kingdom and major OEMs (original equipment manufacturers) such as General Electric, to develop tools and techniques for analysis of workflow issues in delivering specialised care services to patients. He has contributed more than 18 research publications in conferences, journals, book chapters, and technical reports. His one patent is in review with USA Patent Office based on his research work related to Variations Modelling Healthcare. He is involved in rail logistics and integrated land use and transportation modelling projects at the SMART Infrastructure Facility.

Dr. Etienne Turpin Dr. Etienne Turpin researches the effects of climate change and other forms of environmental violence on the urban poor. He has experience in coordinating and conducting urban field research in multidisciplinary projects addressing social and environmental transformations. Prior to joining SMART, Etienne taught architecture and advanced design research at the Taubman College of Architecture and Urban Planning, University of Michigan, where he was also a Research Fellow at the Center for Southeast Asian Studies. Dr. Turpin’s editing, writing, and scholarship, as well as his design and curatorial practice, engage complex urban systems and their manifold political histories to advocate for greater social and environmental justice. At SMART, he is the Project Lead for the Geo-social Intelligence for Urban Resilience and Liveability Research Group; he is also the Co-Chief Investigator, with Dr. Tomas Holderness and Dr. Rohan Wickramasuriya, of the Map Jakarta Project. His research

Dr. Rohan Wickramasuriya Dr. Rohan Wickramasuriya is a Research Fellow in Geomatics Engineering at the SMART Infrastructure Facility. His research focuses on applying geosimulation, spatiotemporal analytics, geo-visualisation and remote sensing techniques to understand complex dynamics in urban and regional systems. He has over 10 years of experience in applied geospatial research, particularly in integrated land use and transportation modelling. At SMART, he leads the research group ‘Advanced Geomatics for Urban and Regional Planning’, serves as the principal developer of the SMART Infrastructure Dashboard, and acts as the technical lead of the project ‘Regional Dynamic Planning Tool for the Illawarra’. Prior to joining SMART, he has worked as a Geospatial Specialist at a number of leading international research institutes including the Research Institute for Knowledge Systems in The Netherlands and the International Water Management Institute in Sri Lanka.

Dr. Jie(Jack) Yang Dr. Jie (Jack) Yang has extensive experience in machine learning and cloud computing. Prior to joining University of Wollongong as a PhD candidate, Jie completed his Master degree from Huazhong University of Science and Technology (HUST), China. He was awarded the “University Prize for Top Ten Students in Scientific Research” from HUST, and also received the second prize from “China National Mathematical Modelling” in 2007. Since 2008, he has been working towards his Ph.D degree and involved in various

projects, including pedestrian detection, image retrieval and through-the-wall radar imaging. These projects involve the application of the novel signal processing paradigm of compressive sensing to develop efficient techniques for machine learning and cloud computing. He has received three university or national awards related to his work. At SMART, Dr. Yang is responsible for translating conceptual models into implementation programs and code prototyping (in particular, machine learning algorithms). Dr. Yang also assists with the migration of machine-based workflows to SMART’s new cloud computing facility.

SMART RESEARCH TEAM

HDR STUDENTS

Prof. Ian Buchanan – Faculty of Law, Humanities and The Arts, University of Wollongong

Mehbub Anwar

Prof. Gordon Waitt – Faculty of Social Sciences, University of Wollongong

Jesse Baaner Ashkan Masouman Shiva Pedram Brett William

ASSOCIATE MEMBERS

Prof. Lindsay Oades – Faculty of Business, University of Wollongong A/Prof. Charles Harvie – Faculty of Business, University of Wollongong Prof. Laurie Buys – QUT (AUS) Robert Stimson – Uni Melbourne (AUS)

David Anderson – Newcastle University (UK)

K. Djaja – Universitas Indonesia (ID)

A/Prof. Chris Pettit – University of Melbourne (AUS)

Prof. Ray Chambers – Faculty of Engineering and Information Sciences, University of Wollongong

Prof. Colin Woodroffe – Faculty of Science, Medicine and Health, University of Wollongong

Dr. Gaurav Singh – CSIRO (AUS)

Ed Lengham – UTS (AUS)

Prof. Chris Barrett – Virginia Tech (USA)

Dr. Tillmann Boehme – Faculty of Business, University of Wollongong

Dr. Glenn Geers – NICTA (AUS)

Dr. Shuaian Wang – Faculty of Engineering and Information Sciences, University of Wollongong

Dr. Rocco Zitto – Uni SA (AUS)

Prof. Edward Chung – QUT (AUS)

Dr. Senevi Kiridina – Faculty of Engineering and Information Sciences, University of Wollongong

A/Prof. Kurt Iveson – Uni Sydney (AUS)

Dr. Albert Munoz – Faculty of Business, University of Wollongong

Prof. Margot Weijnen – Delft University of Technology (NL)

Prof. Andrew Miller – Faculty of Science, Medicine and Health, University of Wollongong

Prof. Ram Pendyala – Arizona State University (USA)

Dr. Weiliang Zhao – Faculty of Engineering and Information Sciences, University of Wollongong

Prof. Jim Hall – University of Oxford (UK)

Prof. Aditya Ghose – Faculty of Engineering and Information Sciences, University of Wollongong

VISITING AND HONORARY MEMBERS

Prof. Charles Macal – Argonne National Lab (USA)

Prof. B. Collins (Visiting)

Miguel Mujica Mota – Amsterdam University (NL)

Prof. G. Harris (Honorary)

Dr. Johan Barthelemy – University of Namur (B)

Mr. J. Gardiner (Honorary)

A/Prof. Rodney Clarke – Faculty of Business, University of Wollongong

Mr. P. McVean (Honorary) Mr. L. Hosking (Honorary)

SMART SCIENTIFIC PARTNERS At the heart of SMART is a core belief that by working together and sharing knowledge and perspectives that we can be greater than the sum of our parts. This ethos is reflected in every aspect of SMARTâ&#x20AC;&#x2122;s research and teaching programs and in our commitment to working collaboratively with other national and international institutions.

INTERNATIONAL Arizona State University, US

Stanford University, US

Argonne National Laboratory, US

University College London, UK

Delft University of Technology, The Netherlands

University of Wollongong, Dubai

Newcastle University, UK

Virginia Tech, US

Oxford University, UK

Twitter

NATIONAL Australian National Data Service (ANDS)

The University of South Australia (UniSA), Adelaide

CISCO

Transport for NSW

Queensland University of Technology, Brisbane

Endeavour Energy

NSW Government NSW Ports QLD Government The Australian Urban Research Infrastructure Network (AURIN)

Remondis Sydney Water Local Councils Droppoint NSW Trains

EVENTS AND AWARDS

(left to right) Prof. Jim Hall - University of Oxford, Mr Garry Bowdicth – SMART Infrastructure Facility, Prof. Brian Collins – University College London, Prof. Judy Raper – University of Wollongong, Prof. Pascal Perez – SMART Infrastructure Facility, Prof Margot Weijnen – Delft University of Technology, The Netherlands and Prof. Ram Pendyala, Arizona State University, US

International Symposium for Next Generation Infrastructure The delivery of the International Symposium for Next Generation Infrastructure (ISNGI) 2013 Australia program was an important global achievement for the infrastructure community. The significance and uniqueness of the Symposium was that it brought together four disparate groups – policymakers, academic researchers, business practitioners and the community – all of whom have an important stake in infrastructure and rarely have an opportunity for deep dialogue and knowledge exchange. Many delegates noted the very influential, eclectic and multidisciplinary groups of people the Symposium brought together. This confirmed that the future of infrastructure lies in these rich interdisciplinary settings. All delegates were clearly committed to improving our individual and collective ability to undertake better infrastructure planning and development. Yet we are challenged by the modesty of conceptual frameworks, data, analytical tools and research to support these undertakings. The societies in which we live however cannot wait for a new infrastructure science to emerge that will deliver the so-called ‘silver bullet’ solutions. Our goal from the 2013 Symposium has been to help empower governments and the community to plan and be front footed to change. This will entail the rigorous prioritisation of projects as part of the broader infrastructure system and to undertake quality community consultation on what matters to them. The possibilities of developing an infrastructure science can only be realised from the process of doing: that is planning, designing, procuring, investing, constructing and renovating infrastructure. Having in place the ability to record and capture the lessons as they occur is fundamental, as well as the institutions to learn and disseminate these findings. The ISNGI community of experts is an important piece of the jigsaw for a more learned and professional global infrastructure community.

We heard from many experts that confirmed innovation and changing the framework in which we deal with infrastructure is critical to the Factor 8 grand challenge of the Symposium. “What is required to design, develop and carry through the effective provision of Infrastructure to sustain the development of modern society? Given that infrastructure is not an ‘engineering artefact’ but an ‘agent of change’, is it possible to imagine infrastructure systems that can meet the needs of twice today’s population with half today’s resources while providing twice the liveability?” The language that resonated with many delegates such as ‘Infrastructure is Personal’ and to ask ‘What are cities for?’ are all good starting points for reframing of opportunities and problems. People and therefore the community are essential ingredients to infrastructure. Yet this is often overlooked in planning. Engineering blueprints too easily draw attention to physical attributes of infrastructure rather than proper identification of the problem being addressed, the quality of service outcomes and how these impact the community. Liveability, resilience and productivity together form some of the key drivers of change in our societies, and infrastructure decisions must be more accountable to these drivers. However, accountability can only be established with policymakers when stronger conceptual frameworks are available to connect how infrastructure actually makes a difference to economic and social outcomes. This is an important area of immediate focus for the ISNGI community. The most reassuring aspect of the Symposium was the overwhelming support from sponsors, delegates, partners and the community for their willingness to generously contribute to changing the status quo in infrastructure.

Urban Liveability Workshop

TEDxU Wollongong

UOW Pitch

In February 2013, SMART convened a panel of international experts from academia, industry and public authorities to discuss and debate the concept and measurement of urban liveability and its role in urban and infrastructure planning.

Planning for and designing more liveable cities is becoming one of the most important challenges of the 21st century. Although the notion of liveability has attracted much attention in recent years, it is fair to recognise that several misconceptions have hindered its coming into practice.

The UOW Pitch competition is designed to promote student and staff involvement in entrepreneurialism and commercialisation of ideas, inventions and research at the University of Wollongong. Short-listed entrants were required to present a five-minute pitch to a panel of industry experts and investors in a ‘Dragons Den’ style interview.

The event provided important dialogue relating to how people assess quality of life, wellbeing and citizen aspirations and translated and scaled them to inform how cities and regional centres can be better designed and managed. In particular, attendees looked at defining conditions under which scientific models can encapsulate adaptive and heterogeneous social responses in a meaningful way, testing the viability of the conceptual development of liveability as part of long term planning for Infrastructure development and driving new knowledge development into the interaction of assets, people and networks across critical aspects of the infrastructure system.

In order to address some of these misconceptions, SMART’s Research Director, Professor Pascal Perez was invited to present at the University’s second TEDxU event where he discussed the importance of modelling urban liveability. Prof. Pascal outlined the need to accept the fact that urban environments influence people’s behaviour as much as people progressively shape their built environment. As a consequence, liveability is a highly subjective construct based on individual perceptions rather than pre-identified sets of urban features. Another misconception stems from the notion that liveable cities of the future will be sustainable ones as well. Based on current behavioural patterns, so-called liveable cities will be anything but sustainable. Making the transition will require a formidable cultural shift for most modern and urbanised societies.

SMART’s Dr Tomas Holderness pitched “Exposure” a software platform developed by SMART to build powerful spatial data visualisations, which is currently used in a number of SMART’s research projects. The pitch was a success, and Dr Holderness was awarded an encouragement prize of $1,000 by the panel, who commended him on an excellent presentation.

SMART SEMINAR SERIES SMART hosts regular interactive seminars throughout the year. Each seminar runs for approximately an hour and a half, including the opportunity for a questions and answer session. The presentations are topical, thought provoking and free to attend.

December 11, 2013

From the Gong to Facebook Inc. Presented by Cooper Lees.

November 29, 2013

The Reinvention of Social Capital in Self-Organising Electronic Institutions and Socio-Technical Systems. By Jeremy Pitt, Department of Electrical & Electronic Engineering, Imperial College London

November 29, 2013

London Overground â&#x20AC;&#x201C; A Success Story: Transformation of Neglected Urban Rail Infrastructure into an Orbital Network. By Nicole Badstuber. Research Associate, Department of Civil, Environmental and Geomatic Engineering, University College London

November 25, 2013

Integrated Modelling for Regional Planning and Policy Support. By Hedwig Van Delden.Â Director, Research Institute for Knowledge Systems, The Netherlands & Adjunct Professor, University of Adelaide

November 1, 2013

Just the City: Rethinking the Image of Urban Poverty. Presented by Professor AbdouMaliq Simone, University of South Australia and Dr Etienne Turpin, SMART Infrastructure Facility

August 23, 2013

A National Database for Mapping Avoidable Electricity Network Investment. Presented by Ed Langham, University of Technology Sydney

August 3, 2013

Opportunities for R&D in Australian Local Government. Presented by Professor John Martin, Director of the Centre for Sustainable Regional Communities, La Trobe University

May 13, 2013

Governance of Integrated Infrastructure. Presented by Professor Brian Collins CBE, Professor of Engineering Policy at University College London and Director of the UCL Centre of Engineering Policy.

May 3, 2013

Future of Business Intelligence: Information 2020. Presented by Ian Bertram, Manager of the Analytics and Business Intelligence Research Team and Head of Research for Asia Pacific at Gartner

April 19, 2013

Application of Discrete Event Simulation to the Review of Logistics Systems. Presented by Geoff Gray, Director and Principal Consultant with Simulation Modelling Services Pty Ltd

April 3, 2013

Commercialisation of renewable energy. Presented by Tony Thorp, Director of Tenax Energy

March 4, 2013

Methodology and Philosophy issues for the Complexities of Infrastructure Research. Presented by Professor Graham Harris, Honorary Professorial Fellow in the SMART Infrastructure Facility, University of Wollongong

February, 2013

Cyber-Physical Society. Presented by Professor Hai Zhuge, professor at the Chinese Academy of Sciences, the Chief Scientist of National Basic Research Program of China, and the Chief Scientist of the Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences and Vice Chairman of its Academic Committee.

January 18, 2013

Towards an intelligent future energy grid. Presented by Professor Zhaoyang Dong, chair of Ausgrid and Director of the Centre for Intelligent Electricity Networks at the University of Newcastle

December 10, 2012

Addressing well-being in the long-term: a review of intergenerational equity, discount rates in climate change analysis Presented by Dr Mark Harrsion, Senior Research Fellow, SMART Infrastructure Facility, University of Wollongong

November 23, 2012

Railway Systems Complexity and Management. Presented by Professor Felix Schmid, Programme Director MSc in Railway Systems Engineering and Integration, University of Birmingham, UK

September 27, 2012

How Do We Supply the World's Energy Needs? Presented by Prof. Derek Abbott, School of Electrical and Electronic Engineering, University of Adelaide

September 26, 2012

Massively Interacting Systems: Thinking and Deciding in the Age of Big Data. Presented by Prof. Chris Barrett, Virginia Tech

September 5, 2012

My Journey in Rail Transport Research. Presented by Mark Ho, A/Prof. Rail Logistics, SMART Infrastructure Facility, University of Wollongong

August 13, 2012

The Hive: Cracking the Codes of Cooperation. Presented by Annamaria Talas, Science filmmaker and Visiting Fellow, Australian National University

August 3, 2012

When Simplifying Assumptions are too Simple: Developing a Catalogue of Agglomeration Economies and Other Spatial Impacts of Infrastructure. Presented by A/Prof. Cameron Gordon, Associate Professor, Economics, University of Canberra, Visiting Professor, Imperial College, London, Centre for Transport Studies

July 17, 2012

Resilient Futures: Operationalising Resilience for UK Infrastructure and Its Stakeholders. Presented by Prof. Seth Bullock, Institute for Complex Systems Simulation (ICSS) Agents, Interaction and Complexity (AIC) Group School of Electronics and Computer Science University of Southampton, UK

July 9, 2012

Information Systems Research: Research Issues and Theoretical Foundations. Presented by A/Prof. Rajeev Sharma, School of Information Systems & Technology (SISAT), University of Wollongong

July 2, 2012

The Long Term Dynamics of Interdependent Infrastructure Systems: The Emerging Evidence from Britain. Presented by Prof. John Preston, Transportation Research Group, Civil, Maritime and Environmental Engineering and Science, University of Southampton, UK

June 28, 2012

Agent-Based Simulation of Socio-Technical Process. Presented by A/Prof. Neil Yorke-Smith, American University of Beirut and SRI International

SMART PUBLICATIONS

Books and Monographs 1.

Dichmont, C, Pascoe, SD, Jebreen, EJ, Pears, R, Brooks, K & Perez, P 2012, Providing social science objectives and indicators to compare management options in

the Queensland trawl planning process, CSIRO, Queensland. 2.

Ergas, H & Branigan, J 2012, Rebooting the Boom: Unfinished Business on the Supply Side, Minerals Council of Australia, Canberra, Australia.

McCusker, A & Shukla, N 2012, Short report on: Inquiry into the utilisation of rail and infrastructure corridors, NSW Legislative Assembly, Committee on

Transport and Infrastructure, University of Wollongong, Wollongong, Australia. 4.

Turpin, E (ed.) 2013, Architecture in the Anthropocene: Encounters Among Design, Deep Time, Science and Philosophy, Open Humanities Press, Ann Arbor,

Michigan. 5.

Turpin, E 2013, The Architecture of Mineralization, Journal of Aesthetics & Protest Press, Los Angeles, United States of America.

Turpin, E, Bobbette, A & Miller, M (eds) 2013, Jakarta: Architecture + Adaptation, Universitas Indonesia Press, Depok, Indonesia.

Book Sections 1.

Alford, ML, Boschetti, F, Davies, H, Dodds, S, Lowe, I & Perez, P 2013, ‘Australia 2050: Social Perspectives’, in Finnigan, J & Raupack, M (eds), Negotiating Our

Future: Living Scenarios for Australia to 2050 (Volume 1), Australian Academy of Science, Canberra, Australia, pp. 93-114. 2.

Barreteau, O, Bots, P, Daniell, K, Etienne, M, Perez, P, Barnaud, C, Bazile, D, Becu, N, Castell, J, Daré, W & Trebuil, G 2013, ‘Participatory Approaches’, in

Edmonds, B & Myer, R (eds), Simulating Social Complexity: A Handbook, Springer, New York, United States of America, pp. 197-234. 3.

Ergas, H 2012, ‘Urban Infrastructure and Land Use’, in Pincus, J & Hugo, G (eds), A Greater Australia: Population, policies and governance, Committee for the

Economic Development of Australia, Melbourne, Australia, pp. 182-201. 4.

Ergas, H 2013, 'Defence Inquiries', in Passer, S & Tracey, H (eds), Royal Commissions and Public Inquiries, Connor Court Publishing, Sydney, Australia.

Perez, P 2013, ‘Science to inform and models to engage’, in Finnigan, J, & Raupack, M (eds), Negotiating Our Future: Living scenarios for Australia to 2050

(Volume 2), Australian Academy of Science, Canberra, Australia, pp. 147-160. 6.

Turpin, E 2012, ‘An Archaeology of the Showroom: This Model Society’, in Migone, C (ed.), Wood 2: A Compendium of the Blackwood Gallery’s Exhibitions and

Projects in 2010-2011, Blackwood Press, Toronto, Canada, pp. 142-149. 7.

Turpin, E 2012, ‘The Politics of the Triassic: Premonitions of the Anthropocene in the Work of Robert Smithson’, in Kruse, J & Ellsworth, L, Making a Geological

Turn, Punctum Books, New York, United States of America, pp. 173-178. 8.

Turpin, E and Federighi, V (eds), ‘A New Force, A New Element, A New Input: Antonio Stoppani’s Anthropozoica’, trans. V. Federighi, in Kruse, J & Ellsworth, L,

Making a Geological Turn, Punctum Books, New York, United States of America, pp. 34-41.

Journal Articles 1.

Bai, Y, Ho, TK, Mao, BH, Dong, Y & Chen, SK 2013, ‘Energy-efficient Locomotive Operation for Chinese Mainline Railways by Fuzzy Predictive Control’, IEEE

Transactions on Intelligent Transportation Systems, vol. 15, no. 3, pp. 938-948. 2.

Balbi, S, Giupponi, C, Perez, P & Alberti, M 2013, ‘A spatial agent-based model for assessing strategies of adaptation to climate and tourism demand changes in

an alpine tourism destination’, Environmental Modelling and Software, vol. 45, pp. 29-51. 3.

Barthelemy, J & Toint, PL 2013, ‘Synthetic population generation without a sample’, Transportation Science, vol. 47, no. 2, pp. 266-279.

Bobette, A, Miller, M & Turpin, E 2013, ‘Architecture, adaptive capacities, and the futures of hypercomplexity’, Kerb, vol. 21, pp. 98-103.

Bowditch, G 2013, ‘Australia’s infrastructure cost conundrum’, The Conversation, 23 October, <http://theconversation.com/australias-infrastructure-cost-

conundrum-19037> 6.

Bowditch, G 2013, ‘Should users pay the toll for Australia’s infrastructure problem?’, The Conversation, 03 December, <http://theconversation.com/should-

users-pay-the-toll-for-australias-infrastructure-problem-20774> 7.

Chen, SK, Ho, TK & Mao, BH 2013, ‘Maintenance Schedule Optimisation for a Railway Power Supply System’, International Journal of Production Research, vol.

51, no. 16, pp. 4896-4910. 8.

Cleland, D, Dray, A, Perez, P, Cruz-Trinidad, A & Geronimo, R 2012, ‘Simulating the dynamics of subsistence fishing communities: REEFGAME as a learning and

data-gathering computer-assisted role-play game’, Simulation and Gaming: An International Journal of Theory, Design and Research, vol. 43, no. 1, pp. 102-117. 9.

Dichmont, C, Pascoe, SD, Jebreem, E, Pears, R, Brooks, K & Perez, P 2012, ‘Choosing a fishery’s governance structure using data poor methods’, Marine Policy,

vol. 37, pp. 123-131. 10. Do, Q, Cook, S, Campbell, P, Robinson, W, Power, W & Tramoundanis, D 2012, ‘Requirements for a metamodel to facilitate knowledge sharing between project stakeholders’, Procedia Computer Science, vol. 8, pp. 285-292. 11. Dray, A, Perez, P, Moore, DR, Dietze, P, Bammer, G, Jenkinson, R, Siokou, C, Green, R, Hudson, SL & Maher, L 2012, ‘Are drug detection dogs and mass-media campaigns likely to be effective policy responses to psychostimulant use and related harm? Results from an agent-based simulation model’, International Journal of Drug Policy, vol. 23, no. 2, pp. 148-153. 12. Dunbar, M, Froyland, G & Wu, C 2012, ‘Robust airline schedule planning: minimizing propagated delay in an integrated routing and crewing framework’, Transportation Science, vol. 46, no. 2, pp. 204-216. 13. Ebrahimpour, M, Putnins, TJ, Berryman, MJ, Allison, A, Ng, B W-H & Abbott, D 2013, ‘Automated authorship attribution using advanced signal classification techniques’, PLoS One, vol. 8, no. 2, e54998, pp. 1-12. 14. Ergas, H & Robson, A 2013, 'Revenue Allocation under the MRRT: Economic Aspects', Journal of Australian Taxation, vol. 14, no. 2, pp. 183-206. 15. Ergas, H 2012, ‘Australia’s defence: a review of the “reviews”’, Agenda – A Journal of Policy Analysis and Reform, vol. 19, no. 1, pp. 63-71. 16. Ergas, H 2012, ‘Australia’s handout-addicted car industry needs some tough love’, The Conversation, 11 January, <http://theconversation.com/australiashandout-addicted-car-industry-needs-some-tough-love-4907> 17. Ergas, H 2012, ‘Funding and providing aged care: lessons from the last decade’, The Australian Economic Review, vol. 45, no. 3, pp. 362-367. 18. Ergas, H 2012, ‘Policy forum: designing a carbon price policy: using market-based mechanisms for emission abatement: are the assumptions plausible?’, The Australian Economic Review, vol. 45, no. 1, pp. 86-95. 19. Ergas, H 2013, 'National Disability Insurance Scheme Funding: The Case for Hypothecation', The Australian Economic Review, vol. 46, no. 3, pp. 338-44. 20. Ergas, H 2013, 'Why Johnny Can't Regulate: The Case of Natural Monopoly', Agenda: A Journal of Policy Analysis and Reform, vol. 20, no. 1, pp. 47-54. 21. Espinilla, M, Lu, J, Ma, J & Martínez, L 2012, ‘An extended version of the fuzzy multicriteria group decision-making method in evaluation processes’, Communications in Computer and Information Science, vol. 297, pp. 191-200. 22. Gao, Y, Zhang, G, Lu, J & Ma, J 2013, ‘A bi-level decision model for customer churn analysis’, Computational Intelligence, Online First. 23. Gollan, P, Bendemra, H, Ergas, H, van Acker, E, Economou, N & Toner, P 2013, ‘Holden to cease making cars in Australia by 2017: experts react’, The Conversation, 11 December, <http://theconversation.com/holden-to-cease-making-cars-in-australia-by-2017-experts-react-21369> 24. Golmohammadi, P, Mokhtarian, P, Safaei, F, & Raad, R 2013, ‘An Analytical Model of Network Connectivity in Vehicular Ad Hoc Networks using Spatial Point Processes’, IEEE Transactions on Vehicular Networks. 25. Harris, G 2012, ‘Apocalypse Not: doomsday thinkers of Oz should get out more’, The Conversation, 6 August, <http://theconversation.com/apocalypse-notdoomsday-thinkers-of-oz-should-get-out-more-7277>

26. Harris, G 2012, ‘Don’t wait for science to ‘settle’; decide what society needs’, The Conversation, 12 September, <http://theconversation.com/dont-wait-forscience-to-settle-decide-what-society-needs-8805> 27. Harris, G 2012, ‘Ecology is failing and needs to be freed from our limitations’, The Conversation, 28 June, <http://theconversation.com/ecology-is-failing-andneeds-to-be-freed-from-our-limitations-7276> 28. Harris, G 2012, ‘Science’s stagnant thinking: our rivers need a revolution’, The Conversation, 30 April, <http://theconversation.com/sciences-stagnant-thinkingour-rivers-need-a-revolution-6457> 29. Harrison, M 2013, ‘A critique of the Productivity Commission’s Cost Benefit Analysis in the ‘Disability Care and Support’, Agenda – A Journal of Policy Analysis and Reform, vol. 20, no. 2, pp. 77-88. 30. Harrison, M 2013, ‘Evidence-free Policy: The Case of the National Injury Insurance Scheme’, Agenda – A Journal of Policy Analysis and Reform, vol. 20, no. 1, pp. 55-69. 31. Harrison, MD 2012, ‘The problem of road congestion: the futility of “avoidable cost” estimates’, Agenda – A Journal of Policy Analysis and Reform, vol. 19, no. 2, pp. 77-86. 32. Hawkes, D, Lea, CE & Berryman, MJ 2013, ‘Answering human papillomavirus vaccine concerns; a matter of science and time’, Infectious Agents and Cancer, vol. 8, no. 22, pp. 1-8. 33. Ho, TK, Tsang, CW, Ip, KH & Kwan, KS 2012, ‘Train service timetabling in railway open markets by particle swarm optimisation’, Expert Systems with Applications, vol. 39, no. 1, pp. 861-868. 34. Holderness, T, Barr, S, Dawson, R & Hall, J 2013, ‘An evaluation of thermal Earth observation for characterizing urban heatwave event dynamics using the urban heat island intensity metric’, International Journal of Remote Sensing, vol. 34, no. 3, pp. 864-884. 35. Huynh, N, Lu, C, Michal, G & Tieu, K 2013, ‘A misorientation dependent criterion for crack opening in FCC single crystal’, Material Science Forum, vol. 773, pp. 293-311. 36. Kennedy-Walker, R, Holderness, T, Alderson, D, Evans, B & Barr, S 2013, ‘Network modelling for improved sanitation infrastructure’, Institute of Civil Engineers – Municipal Engineer. 37. Liu, Z, Meng, Q & Wang, S 2013, ‘Speed-based toll design for cordon-based congestion pricing scheme’, Transportation Research Part C: Emerging Technologies, vol. 31, pp. 83-98. 38. Lu, SF, Hillmansen, S, Ho, TK & Roberts, C 2013, ‘Single Train Trajectory Optimisation’, IEEE Transactions on Intelligent Transportation Systems, vol. 14, no. 2, pp. 743-750. 39. Lynam, T, Mathevet, R, Etienne, M, Stone-Jovicich, S, Leitch, A, Jones, N, Ross, H, Du Toit, D, Pollard, S, Biggs, H & Perez, P 2012, ‘Waypoints on a journey of discovery: mental models in human environment interactions’, Ecology and Society: A Journal of Integrative Science for Resilience and Sustainability, vol. 17, no. 3, pp. 23-33. 40. Melbourne-Thomas, J, Johnson, CR, Perez, P, Eustache, J, Fulton, EA & Cleland, D 2011, ‘Coupling biophysical and socioeconomic models for coral reef systems in Quintana Roo, Mexican Caribbean’, Ecology and Society: A Journal of Integrative Science for Resilience and Sustainability, vol. 16, no. 3, pp. 1-21. 41. Meng, Q, Wang, S, Andersson, H & Thun, K 2013, ‘Containership routing and scheduling in liner shipping: overview and future research directions’, Transportation Science, vol. 48, no. 2, pp. 265-280. 42. Moglia, M, Perez, P & Burn, S 2012, ‘Assessing the likelihood of realizing idealized goals: the case of urban water strategies’, Environmental Modelling and Software, vol. 35, pp. 50-60. 43. Naficy, S, Kawakami, S, Sadegholvaad, S, Wakisaka, M & Spinks, GM 2013, ‘Mechanical Properties of Interpenetrating Polymer Network Hydrogels Based on Hybrid Ionically and Covalently Crosslinked Networks’, Journal of Applied Polymer Science, vol. 130, no. 4, pp. 2504-2513. 44. Nagabhatla, N, Mishra, S, Finlayson, M, Sellamuttu, SS, Van Brakel, M, Wickramasuriya, R, Pattanaik, C & Prasad, SN 2012, ‘A case study approach to demonstrate assessment and monitoring as a tool for participatory management of ecological resources’, Ecologia, vol. 2, no. 3, pp. 60-75. 45. Nagabhatla, N, Sellamuttu, S, Bobba, A, Finlayson, M, Wickramasuriya, R, Van Brakel, M, Prasad, S & Pattanaik, C 2012, ‘Insight to Ecosystem Based Approach (EBA) at Landscape Level Using a Geospatial Medium’, Journal of the Indian Society of Remote Sensing, vol. 40, no. 1, pp. 47-64. 46. Perez, P, Dray, A, Moore, D, Dietze, P, Bammer, G, Jenkinson, R, Siokou, C, Green, R, Hudson, SL & Maher, L 2012, ‘SimAmph: an agent-based simulation model for exploring the use of psychostimulants and related harm amongst young Australians’, International Journal of Drug Policy, vol. 23, no. 1, pp. 62-71. 47. Prettejohn, BJ, Berryman, MJ & McDonnell, MD 2013, ‘A model of the effects of authority on consensus formation in adaptive networks: Impact on network topology and robustness’, Physica A: Statistical Mechanics and its Applications, vol. 392, no. 4, pp. 857-868. 48. Shukla, N, Ceglarek, D & Tiwari, MK 2013, ‘Key characteristics-based sensor distribution in multi-station assembly processes’, Journal of Intelligent Manufacturing, March, pp. 1-16.

49. Shukla, N, Choudhary, AK, Prakash, PKS, Fernandes, KJ & Tiwari, MK 2013, ‘Algorithm portfolios for logistics optimization considering stochastic demands and mobility allowance’, International Journal of Production Economics, vol. 141, no. 1, pp. 146-166. 50. Shukla, N, Dashora, Y, Tiwari, MK & Shankar, R 2013, ‘Design of computer network topologies: A Vroom Inspired Psychoclonal Algorithm’, Applied Mathematical Modelling: Simulation and Computation for Engineering and Environmental Systems, vol. 37, no. 3, pp. 888-902. 51. Shukla, N, Tiwari, MK & Ceglarek, D 2013, ‘Genetic-algorithms-based algorithm portfolio for inventory routing problem with stochastic demand’, International Journal of Production Research, vol. 51, no. 1, pp. 118-137. 52. Turpin, E & Denizen, S 2012, ‘Stratophysical Approximations: A Conversation with Seth Denizen on the Urban Soils of the Anthropocene’ OrgansEverywhere, no. 4, pp. 30-45. 53. Turpin, E & Hirmer, L 2012, ‘Unintentional Aesthetics of the Anthropocene: A Textual- Photographic Précis’, Horizonte: Zeitschrift für Architekturdiskurs, no. 5, pp. 161-170. 54. Turpin, E 2012, ‘Art After the Nostalgia for Belonging’, Big Red and Shiny, vol. 2, no. 3. 55. Turpin, E 2013, ‘A stroll through the bubbles of chemicals and men’, New Work for a Biosynthetic World, vol. 35, pp. 42-47. 56. Turpin, E 2013, ‘Architecture in our Humanitarian Present (A review of Eyal Weizman’s The Least of All Possible Evils)’, Fuse: Art + Culture + Politics, vol. 36, no. 2, pp. 53-54 57. Turpin, E (ed.) 2013, Scapegoat: Architecture/Landscape/Political Economy, Vol. 5. 58. Turpin, E, Bobbette, A & Miller, M 2013, ‘Architecture, Adaptive Capacity, and the Futures of Hypercomplexity’, Kerb: Journal of Landscape Architecture, no. 21 pp. 98-103. 59. Turpin, E, Bobbette, A and Miller, M 2012, ‘Jakarta: Design Research and the Futures of Hypercomplexity’, MONU, vol. 17. 60. Ulutas, A, Kiridena, S, Gibson, P & Shukla, N 2012, ‘A novel integrated model to measure supplier performance considering qualitative and quantitative criteria used in the supplier selection process’, International Journal of Logistics and SCM Systems, vol. 6, no. 1, pp. 57-70. 61. Wang, S 2013, ‘A novel hybrid-link-based container routing model’, Transportation Research: Logistics and Transportation Review, vol. 61, pp. 165-175. 62. Wickramasuriya, R, Chisholm, L, Puotinen, M, Gill, N & Klepeis, P 2013, ‘A Method to Dynamically Subdivide Parcels in Land Use Change Models’, International Journal of Geographical Information Science, vol. 27, no. 8, pp. 1497-1513. 63. Wickramasuriya, R, Ma, J, Berryman, M & Perez, P 2013, ‘Using Geospatial Business Intelligence to Support Regional Infrastructure Governance’, KnowledgeBased Systems, vol. 53, November, pp. 80-89. 64. Zheng, H, Zhao, W, Yang, J & Bouguettaya, A 2013, ‘QoS Analysis in Service Oriented Computing’, IEEE Transactions on Services Computing, vol. 6, no. 3, pp. 373-386.

Conference Papers 1.

Anwar, AM, Tieu, K, Gibson, P, Win, KT & Berryman, MJ 2013, ‘Analysing the Merit of Latent Variables over Traditional Objective Attributes for Traveller Mode

Choice Using RPL Model’, in The International Choice Modelling Conference, Sydney, Australia, 3-5 July. 2.

Cornelis, E, Hollaert, L, Barthelemy, J & Toint, PL 2013 ‘An original synthetic population tool applied to Belgian case: VirtualBelgium’, in Proceedings of NTTS –

Conferences on New Techniques and Technologies for Statistics: The Meeting Place for Research in Official Statistics, Eurostat, Brussels, Belgium, pp. 695-701. 3.

Deng, G, Lu, C, Su, L, Tieu, A, Yu, H, Si, L, Liu, X & Zhu, H 2012, ‘Crystal plasticity finite element analysis of influence of initial crystal orientation on texture

evolution and deformation heterogeneity of cold-rolled aluminium’, in Proceedings of the 14th International Conference of Metal Forming, Wiley, Germany, pp. 11191122. 4.

Ding, L, Cooper, P, Zhao, W, Perez, P & Robinson, DA 2013, ‘Smart home system: integration of energy facilities and environmental factors’, in 7th International

Conference on Energy Efficiency in Domestic Appliances and Lighting, Coimbra, Portugal, pp. 1-10. 5.

Huynh, N, Namazi-Rad, M, Perez, P, Berryman, MJ, Chen, Q, & Barthelemy, J 2013, ‘Generating a Synthetic Population in Support of Agent-Based Modelling

of Transportation in Sydney’, in 20th International Conference on Modelling and Simulation (MODSIM), The Modelling and Simulation Society of Australia and New Zealand Inc, Adelaide, Australia, 1-6 December, pp. 1357-1363. 6.

Huynh, N, Shukla, N, Munoz, A, Cao, VL & Perez, P 2013, ‘A semi-deterministic approach for modelling of urban travel demand’, in International Symposium for

Next Generation Infrastructure, University of Wollongong, Wollongong, Australia, 1-4 October. 7.

Lamy, F, Bossomaier, T & Perez, P 2013, ‘SIMUSE: Modelling Recreational Polydrug Use through an Agent-based Model’, in International Conference on

Autonomous Agents and Multi-Agent Systems, Saint Paul, United States of America, 6-10 May. 8.

Liu, Z, Meng, Q, Wang, S & Sun, Z 2013 ‘Global intermodal liner shipping network design’, in Annual Meeting of Transportation Research Board, Washington DC,

United States of America, 13-17 January.

Ma, J, Lin, H, Lu, J & Zhang, G 2013, ‘A hybrid model for migrating customer segmentation with missing attributes’, in Pedrycz, W & Reformat, MZ (eds), in

Proceedings of the Joint World Congress and NAFIPS Annual Meeting, IEEE, United States of America, pp. 825-830. 10. Ma, J, Wickramasuriya, R & Perez, P 2013, ‘A Conceptual Method for Modelling Residential Utility Consumption Using Complex Fuzzy Sets’, in Proceedings of the Joint World Congress and NAFIPS Annual Meeting, IEEE, Edmonton, Canada, 24-28 June, pp. 1227-1232,. 11. Masouman, A & Harvie, C 2012, ‘Regional economic modelling: a comparison of econometric, input-output and integrated modelling of the Illawarra economy’, in Dalziel, P (ed.), Refereed Proceedings of the Australia and New Zealand Regional Science Association International (ANZRSAI) Conference, AERU Research Unit, Canterbury, New Zealand, pp. 133-150. 12. Masouman, A & Harvie, C 2012, ‘Regional economic modelling: taxonomic application of three integration approaches to the Illawarra’s economy’, in Dalziel, P (ed.), Refereed Proceedings of the Australia and New Zealand Regional Science Association International (ANZRSAI) Conference, AERU Research Unit, Canterbury, New Zealand, pp. 151-168. 13. Masouman, A & Harvie, C 2013, ‘Development of integrated intersectoral-time series strategies to investigate the economic significance of knowledge sectors in the Illawarra, New South Wales’, in Butler, D & Mangano, M (eds), The 42nd Australian Conference of Economists Conference Proceedings, Murdoch University, Perth, Australia, pp. 1-28. 14. Masouman, A & Harvie, C 2013, ‘Evaluation of regional economy through an embedded econometric-interindustry model’, in Dalziel, P (ed.), Annual Conference of the Australian and New Zealand Regional Science Association International, AERU Research Unit, Canterbury, New Zealand, pp. 84-102. 15. Masouman, A & Harvie, C 2013, ‘Incorporating Time-Series into an Interindustry Analysis to Model the Regional Economic Structure: a Case Study of the Illawarra’, in International Symposium for Next General Infrastructure Australia 2013 Conference, Wollongong, Australia, 1 October. 16. Masouman, A 2013, ‘An Integrated Econometric Input-Output Model for Impact Analysis of Structural Shifts in a Region in Transition: a Case Study of the Illawarra’, in Western Regional Science Association 52nd Annual Meeting, Santa Barbara, United States of America, 25 February. 17. Masouman, A 2013, ‘Application of an Input-Output Econometric Model to Investigate the Illawarra Economy’, in 2013 Faculty of Business Higher Degree Research Student Conference, Innovation Campus, Wollongong, Australia, August. 18. Mokhtarian, P, Namazi-Rad, M, Ho, TK, & Suesse, T 2013, ‘Bayesian Nonparametric Reliability Analysis for a Railway System at Component Level’, in IEEE International Conference on Intelligent Rail Transportation (ICIRT), Beijing, China, 30 August-1 September. 19. Munoz Aneiros, A 2012, ‘Quantifying the effectiveness of SCOR measures in make-to-forecast supply chains’, in Proceedings of the 10th ANZAM Operations, Supply Chain and Service Management Symposium, ANZAM, Melbourne, Australia. 20. Namazi Rad, M, Lamy, F, Perez, P & Berryman, M 2012, ‘A heuristic analytical technique for location-based liveability measurement’, in The Fifth Annual ASEARC Research Conference: Looking to the future, University of Wollongong, Australia, pp. 1-5. 21. Namazi Rad, M, Perez, P, Berryman, M & Lamy, F 2012, ‘An experimental determination of perceived liveability in Sydney’, RC33 Eighth International Conference on Social Science Methodology, ACSPRI Conferences, Australia, pp. 1-13. 22. Namazi-Rad, M & Mokhtarian, P 2013, ‘An Age-structured Two-sex Model for Household Dynamics in Sydney’, paper presented at World Statistics Congress, Hong Kong, China, 25-30 August. 23. Napier, C, Clancy, D, Davies, T & Elcombe, K 2012, ‘The smart way to manage research data’, in eResearch Australasia 2012, pp. 1-3. 24. Pedram, S, Perez, P, & Dowsett, B 2013, ‘Impact of Virtual Training on Safety and Productivity in the Mining Industry’, in 20th International Conference on Modelling and Simulation (MODSIM), The Modelling and Simulation Society of Australia and New Zealand Inc, Adelaide, Australia, 1-6 December. 25. Perez, P 2013, ‘Defining Urban Liveability – From Static Observations to Dynamic Models’, in Foliente, G & Wang, C (eds), Proceedings of Sustainability and the City: A Science Frontier Symposium, Melbourne, Australia, 12-14 June. 26. Safaei, F, Mokhtarian, P, Shidanshidi, H, Li, W, Namazi-Rad, M & Mousavinia, A 2013, ‘Scene-adaptive Configuration of Two Cameras using the Correspondence Field Function’, in IEEE International Conference on Multimedia and Expo (ICME 2013), San Jose, California, United States of America, July 15-19. 27. Shukla, N, Kiridena, S & Mishra, N 2012, ‘Reducing unwarranted variation in healthcare service delivery systems: key issues, research challenges and potential solutions’, in 26th ANZAM Conference. 28. Shukla, N, Ma, J, Wickramasuriya, R & Huynh, N 2013, ‘Data-driven Modelling and Analysis of Household Travel Mode Choice’, in 20th International Conference on Modelling and Simulation (MODSIM), The Modelling and Simulation Society of Australia and New Zealand Inc, Adelaide, Australia, 1-6 December, pp. 92-98. 29. Shukla, N, Munoz, A, Ma, J & Huynh N 2013, ‘Hybrid Agent based Simulation with Adaptive Learning of Travel Mode Choices for University Commuters’, in Proceedings of the Symposium on Theory of Modeling & Simulation – DEVS Integrative M&S Symposium, Society for Computer Simulation International, United States of America, pp. 1-6. 30. Turpin, E & Hirmer, L 2013, ‘Cumulus Landscapes, or, Aesthetics in Abeyance,’ in Association of American Geographers Annual Meeting, Association of American Geographers, Los Angeles, California, United States of America. 31. Turpin, E & Miller, M 2012, ‘Inundation Jakarta: Designing for Hypercomplexity’, in 49th International Federation of Landscape Architecture World Congress – Landscapes in Transition, Cape Town, South Africa.

32. Turpin, E 2012, ‘Conceptual Persona non grata: Deleuze’s Image of Bataille’, in Deleuze Studies Conference, Tulane University, New Orleans, United States of America. 33. Turpin, E 2013, ‘Anexact practices,’ in ‘The Anthropocene-Project’ Workshop, Haus der Kulturen der Welt, and the International Curators’ Network, Berlin, Germany. 34. Turpin, E 2013, ‘Anthropocene urbanism’, in 8th Encuentro of the Hemispheric Institute, Hemispheric Institute, Sao Paolo, Brazil. 35. Turpin, E 2013, ‘Design for Hypercomplexity: Megacities and Adaptation in the Anthropocene’, in International Symposium on Next Generation Infrastructure, Sydney/Wollongong, SMART Infrastructure Facility, Faculty of Engineering & Information Sciences, University of Wollongong, Wollongong, Australia. 36. Turpin, E 2013, ‘Presentation to the Politics in and as Visual Culture working group’, in Mirzoeff, N (ed.), NYU Hemispheric Institute’s Encuento, Cities|Bodies|Action — The Politics of Passion in the Americas, Universidade de São Paulo, Brazil. 37. Turpin, E 2013, ‘Reading Catalytic Force: On the Aesthetics of Mineralization from Stoppani to Deleuze’, in Annual Meeting of the American Comparative Literature Association, University of Toronto, Canada. 38. Turpin, E, Bobette, A & Miller, M 2013, ‘Navigating postnatural landscapes: Jakarta as the city of the Anthropocene’, in European Council of Landscape Architecture Schools Annual Conference, European Council of Landscape Architecture Schools, Hafen City University, Hamburg, Germany. 39. Turpin, E (ed.) 2012, ‘The Geologic Turn: Architecture’s New Alliance,’ in A Design Research Symposium on the Anthropocene, Taubman College of Architecture and Urban Planning, University of Michigan, Ann Arbor, United States of America. 40. Wang, S, Gardner, LM & Waller, ST 2013, ‘Global optimization method for robust pricing of transportation networks under uncertain demand’, in Annual Meeting of Transportation Research Board, Washington DC, United States of America, 13-17 January. 41. Wang, S, Harrison, M & Dunbar, M 2013, ‘Analysis of toll pricing on Sydney Harbour Bridge with uncertain demand’, in The International Symposium for Next Generation Infrastructure, University of Wollongong, Australia, 1-4 October. 42. Wang, S, Meng, Q & Liu, Z 2013, ‘Overview of bunker consumption optimization in shipping’, in Annual Meeting of Transportation Research Board, Washington DC, United States of America, 13-17 January. 43. Wang, S, Meng, Q & Liu, Z 2013, ‘Systematic network design for liner shipping services’, in Annual Meeting of Transportation Research Board, Washington DC, United States of America, 13-17 January. 44. Wang, S, Qu, X & Liu Z 2013, ‘Suburban bus route design’, in Proceedings of the Eastern Asia Society for Transportation Studies, Taipei, Taiwan, 9-12 September. 45. Wickramasuriya, R, Ma, J, Perez, P & Berryman, M 2013, ‘Adapting Geospatial Business Intelligence for Regional Infrastructure Planning’, in 20th International Conference on Modelling and Simulation (MODSIM), The Modelling and Simulation Society of Australia and New Zealand Inc, Adelaide, Australia, 1-6 December, pp.3057-3063. 46. Williams, B & Perez, P 2013, ‘Evaluation of accessibility measures in practitioner policy and their effectiveness in non-metropolitan areas’, in International Symposium for Next Generation Infrastructure, University of Wollongong, Wollongong, Australia, 1-4 October.

The SMART Infrastructure Facility at University of Wollongong is one of the largest infrastructure research centres in the world.

WORK WITH SMART The SMART Infrastructure Facility is uniquely placed to design, model and simulate the complex interdependencies of infrastructure networks and projects for research clients. SMART is actively engaging with industry and government to work on projects that can deliver better outcomes for the sector and community. We are undertaking projects for clients that range from information gathering, assessment and research, to developing sophisticated computational decision making tools.

FOR MORE INFORMATION PLEASE CONTACT Prof Pascal Perez Director pascal_perez@uow.edu.au

Ms Victoria Black Strategic Marketing Manager vblack@uow.edu.au

Ms Tania Brown Chief Operating Officer +61 4298 1431 tania_brown@uow.edu.au

smart.uow.edu.au Follow SMART on social media:

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