This unit provides both a conceptual and an empirical foundation for the analysis of relationships between society, the environment and natural resources. In our recent past the rapid rate of global environmental change has necessitated a breakdown of traditional disciplinary boundaries in research and social scientists are increasingly called upon to work alongside natural scientists in unraveling the complexities of the human-environmental nexus. Students will examine a number of environmental issues and consider a variety of social science academic perspectives about environmental management.

This core unit of study aims to introduce the central concepts of integrative systems approaches to addressing complex, multi-dimensional, multi-scale issues. Systems approaches are increasingly being recognised as essential for unravelling the complex network of influences on human health, from biology and nutrition to economics and society. The Charles Perkins Centre is committed to fostering new ways of thinking with systems approaches, which it sees as the key to identifying innovative solutions to the growing global health problems associated with diet and lifestyle. An understanding of concepts from complex systems thinking will help students develop their own thinking about complex health issues and identify novel approaches and research questions.

Students should achieve an understanding of dynamical systems methods applied to complex adaptive systems (CAS). CAS is a new approach to engineering and management that studies and models how relationships between parts give rise to collective and dynamic system-level behaviours, for example, in communication and transport networks, megaprojects, social and eco-systems. Effectively implemented, the methods can dramatically improve a manager's effectiveness in today's complex and interconnected business world, by helping to predict and evaluate indirect effects of actions and policies. This course provides managers with many practical quantitative tools to enhance individual, team, and organisational learning, change, and performance.

The aim of the unit is to introduce students to basic statistical concepts and methods for further studies. Particular attention will be paid to the development of methodologies related to statistical data analysis and Data Mining. A number of useful statistical models will be discussed and computer oriented estimation procedures will be developed. Smoothing and nonparametric concepts for the analysis of large data sets will also be discussed. Students will be exposed to the R computing language to handle all relevant computational aspects in the course.

Globalisation, rapid technological advances, the development of integrated and distributed systems, cross-disciplinary technical collaboration, and the emergence of "evolved" (as opposed to designed) systems are some of the reasons why many systems have begun to be described as complex systems in recent times. Complex technological, biological, socio-economic and socio-ecological systems (power grids, communication and transport systems, food webs, megaprojects, and interdependent civil infrastructure) are composed of large numbers of diverse interacting parts and exhibit self-organisation and/or emergent behaviour. This unit will introduce the basic concepts of "complex systems theory", and focus on methods for the quantitative analysis and modelling of collective emergent phenomena, using diverse computational approaches such as agent-based modelling and simulation, cellular automata, bio-inspired algorithms, and game theory. Students will gain theoretical knowledge of complex adaptive systems, coupled with practical skills in computational simulation and forecasting using a range of modern toolkits.

Our modern day civil infrastructure includes transport networks, telecommunications, power systems, financial infrastructure and emergency services, all of which are growing more and more interconnected. Moreover, the behaviour of the modern infrastructure is not dependent only upon the behaviour of its parts: complex civil systems (such as modern power grids), communication and transport systems, megaprojects, social and eco-systems, generate rich interactions among the individual components with interdependencies across systems. This interdependent behaviour brings about significant new challenges associated with the design and management of complex systems. Cascading power failures, traffic disruptions, epidemic outbreaks, chronic diseases, financial market crashes, and ecosystem collapses are typical manifestations of these challenges, affecting the stability of modern society and civil infrastructure. This unit will develop an understanding of how interdependent systems perform under stress, how to improve resilience and how best to mitigate the effects of various kinds of component failure or human error, by more accurate analysis of interdependent cascades of failures across system boundaries. The studied topics will include dynamical analysis of complex interdependent networks, local and global measures of network structure and evolution, cascading failures, as well as predictive measures of catastrophic failure in complex adaptive systems, and the tools that enable planning for resilient infrastructure. This unit will equip future professionals with sufficient expertise and technical know-how for the design of efficient prevention and intervention policies, and robust crisis forecasting and management. This unit will equip future professionals with sufficient expertise and technical know-how for the design of efficient prevention and intervention policies, and robust crisis forecasting and management.

"Self-organisation" is the evolution of a system into an organised form in the absence of explicit external influences or centralised control. It brings many attractive properties to systems such as robustness, adaptability and scalability. Self-organising systems can be found practically everywhere: gene regulatory networks self-organise into complex patterns and attractors, self-healing sensor networks reconfigure their topology in response to damage, animal swarms change shape in response to an approaching predator, robotic modules self-organise into coordinated motion patterns, and ecosystems develop spatial structures in response to diminishing resources. The unit will study pattern formation and the common principles behind similar patterns in nature and socio-technical systems, developing a critical understanding of self-organisation, and complex adaptive systems applied to technological, social, organisational and biological systems. It will cover cross-disciplinary concepts and methods based on information theory, nonlinear dynamics, including elements of chaos theory and statistical physics, such as fractals, percolation, entropy, open dissipative systems, phase transitions and critical phenomena.

Chemical Engineering requires an understanding of material and energy transformations and how these are driven by molecular interactions. The rate of such transformations is dependent on driving forces and resistances, and these need to be defined in terms of fundamental physical and chemical properties of systems.
This course seeks to provide students with a sound basis of the thermodynamics of chemical and biological systems, and how these, in turn, define limits of behaviour for such real systems. The thermodynamic basis for rate processes is explored, and the role of energy transfer processes in these highlighted, along with criteria for equilibrium and stability. Emphasis is placed on the prediction of physical properties of chemical and biological systems in terms of state variables. The course delivery mechanism is problem-based, and examples from thermal, chemical and biological processes will be considered, covering molecular to macro-systems scale.
In addition, there will be considerable time spent during the semester on advanced topics related to the analysis of the behaviour of chemical and biological systems, and recent associated technological developments.

Visual Analytics aims to facilitate the data analytics process through Information Visualisation. Information Visualisation aims to make good pictures of abstract information, such as stock prices, family trees, and software design diagrams. Well designed pictures can convey this information rapidly and effectively.
The challenge for Visual Analytics is to design and implement effective Visualisation methods that produce pictorial representation of complex data so that data analysts from various fields (bioinformatics, social network, software visualisation and network) can visually inspect complex data and carry out critical decision making.
This unit will provide basic HCI concepts, visualisation techniques and fundamental algorithms to achieve good visualisation of abstract information. Further, it will also provide opportunities for academic research and developing new methods for Visual Analytic methods.

The growing connected-ness of modern society translates into simplifying global communication and accelerating spread of news, information and epidemics. The focus of this unit is on the key concepts to address the challenges induced by the recent scale shift of complex networks. In particular, the course will present how scalable solutions exploiting graph theory, sociology and probability tackle the problems of communicating (routing, diffusing, aggregating) in dynamic and social networks.

The capstone project aims to provide students with the opportunity to carry out a defined piece of independent workplace related research and assessment in a way that fosters the development of practical research skills relevant to Complex Systems. Students will work individually or in small groups on an assigned project, focussed on modelling a complex problem or delivering a novel solution. The concepts covered depend on the nature of the project. The project could be directly tied to student's area of specialisation (major), or to their vocational objectives or interests. Students with expertise in a specific industry sector may be invited to partner with relevant team projects. The project outcomes will be presented in a report that is clear, coherent and logically structured. The project will be judged on the extent and quality of the student's original work and particularly how critical, perceptive and constructive they have been in assessing their work and that of others, in integrating cross-disciplinary complex systems concepts. Students will also be required to present the results of their findings to their peers and supervisors either face to face or by production of a video or other recorded presentation. The skills acquired will be invaluable to students progressing their careers in major multi-national research and development companies, government and crisis management agencies, and large health, construction and transport organisations. Students are expected to take the initiative when pursuing their capstone projects.

The capstone project aims to provide students with the opportunity to carry out a defined piece of independent workplace related research and assessment in a way that fosters the development of practical research skills relevant to Complex Systems. Students will work individually or in small groups on an assigned project, focussed on modelling a complex problem or delivering a novel solution. The concepts covered depend on the nature of the project. The project could be directly tied to student's area of specialisation (major), or to their vocational objectives or interests. Students with expertise in a specific industry sector may be invited to partner with relevant team projects. The project outcomes will be presented in a report that is clear, coherent and logically structured. The project will be judged on the extent and quality of the student's original work and particularly how critical, perceptive and constructive they have been in assessing their work and that of others, in integrating cross-disciplinary complex systems concepts. Students will also be required to present the results of their findings to their peers and supervisors either face to face or by production of a video or other recorded presentation. The skills acquired will be invaluable to students progressing their careers in major multi-national research and development companies, government and crisis management agencies, and large health, construction and transport organisations. Students are expected to take the initiative when pursuing their capstone projects.

On completion of this unit students should be familiar with the major concepts and tools of epidemiology, the study of health in populations, and should be able to judge the quality of evidence in health-related research literature.
This unit covers: historical developments in epidemiology; sources of data on mortality and morbidity; disease rates and standardisation; prevalence and incidence; life expectancy; linking exposure and disease (eg. relative risk, attributable risk); main types of study designs - case series, ecological studies, cross-sectional surveys, case-control studies, cohort or follow-up studies, randomised controlled trials; sources of error (chance, bias, confounding); association and causality; evaluating published papers; epidemics and epidemic investigation; surveillance; prevention; screening; the role of epidemiology in health services research and policy.

Virtually every aspect of a chemical engineer's professional life will involve some use of mathematical techniques. Not only is the modern chemical engineer expected to be proficient in the use of these techniques, they are also expected to be able to utilise computer-based solutions when analytical solutions are unfeasible. This unit of study aims to expose students to an appropriate suite of techniques and enable them to become proficient in the use of mathematics as a tool for the solution of a diversity of chemical engineering problems.
Specifically, this unit consists of two core modules: MODULE A: Applied Statistics for Chemical Engineers and MODULE B: Applied Numerical Methods for Chemical Engineers. These modules aim at furthering knowledge by extending skills in statistical analysis and Chemical Engineering computations. This unit will also enable the development of a systematic approach to solving mathematically oriented Chemical Engineering problems, which will help with making sound engineering decisions. In addition, there will be considerable time spent during the semester on advanced topics related to mathematical analysis techniques in engineering and recent associated developments.

This unit assesses the political and security significance of disease-related events and developments. Whether one contemplates historical experiences with smallpox, the contemporary challenges posed by diseases such as HIV/AIDS and SARS, or the risks arising from new scientific developments such as synthetic biology, it is clear that diseases exercise a powerful influence over civilised humankind. The unit concentrates on areas in which human health and security concerns intersect most closely, including: biological weapons; fast-moving disease outbreaks of natural origin; safety and security in microbiology laboratories; and the relationships between infectious disease patterns, public health capacity, state functioning and violent conflict. The overall aim of the unit is to provide students with a stronger understanding of the scientific and political nature of these problems, why and how they might threaten security, and the conceptual and empirical connections between them.

The research pathway project aims to provide: (a) analytical and computational skills for modelling systems characterised by many interacting heterogeneous variables, (b) adequate programming skills for simulating complex systems. It is aimed at developing a pathway to a research career. The student will work individually on an assigned open-ended research project, focussed on modelling a complex problem or delivering a novel solution. The concepts covered depend on the nature of the project. The project could be directly tied to student's area of specialisation (major), or to their vocational objectives or interests. Students with expertise in a specific industry sector may be invited to partner with relevant team projects. The project outcomes will be presented in a thesis that is clear, coherent and logically structured. The project will be judged on the extent and quality of the student's original work and particularly how innovative, perceptive and constructive they have been in developing and applying cross-disciplinary complex systems concepts. As the result, the student will develop capability for modelling complex systems, from the identification of the relevant variables and interactions to the analysis and simulations of the predictions, having learnt the conceptual and methodological tools (techniques and algorithms) for the analysis and inference of complex models.

The research pathway project aims to provide: (a) analytical and computational skills for modelling systems characterised by many interacting heterogeneous variables, (b) adequate programming skills for simulating complex systems. It is aimed at developing a pathway to a research career. The student will work individually on an assigned open-ended research project, focussed on modelling a complex problem or delivering a novel solution. The concepts covered depend on the nature of the project. The project could be directly tied to student's area of specialisation (major), or to their vocational objectives or interests. Students with expertise in a specific industry sector may be invited to partner with relevant team projects. The project outcomes will be presented in a thesis that is clear, coherent and logically structured. The project will be judged on the extent and quality of the student's original work and particularly how innovative, perceptive and constructive they have been in developing and applying cross-disciplinary complex systems concepts. As the result, the student will develop capability for modelling complex systems, from the identification of the relevant variables and interactions to the analysis and simulations of the predictions, having learnt the conceptual and methodological tools (techniques and algorithms) for the analysis and inference of complex models.

This unit aims to give students an introduction to the planning and operation of modern electricity grids, also known as "smart" grids. Traditional power networks featured a small number of large base-load plants sending power out over transmission lines to be distributed in radial lower voltage networks to loads. In response to the need to reduce carbon impact, future networks will feature diverse generation scattered all over the network including at distribution levels. Also there will be new loads such as electric vehicles and technologies including energy storage and lower voltage power flow control devices. The operation of these new networks will be possible by much greater use of information and communication technology (ICT) and control over the information networks.
The unit will cover recent relevant developments in energy technologies as well as important components of 'smart grids' such as supervisory control and data acquisition (SCADA), substation automation, remote terminal units (RTU), sensors and intelligent electronic devices (IED). Operation of these electricity grids requires a huge amount of data gathering, communication and information processing. The unit will discuss many emerging technologies for such data, information, knowledge and decision processes including communication protocols and network layouts, networking middleware and coordinated control. Information systems and data gathering will be used to assess key performance and security indicators associated with the operation of such grids including stability, reliability and power quality.

This unit aims to teach the basic issues involved in the analysis and design of computer-controlled systems. The emphasis is on theory rather than technological application or industrial practice.
However, students are expected to test some of these ideas on a few benchmark control problems in the laboratory. Completion of the unit will facilitate progression to advanced study in the area and to work in industrial control. This unit assumes a basic knowledge of calculus, functions of real variables, Laplace transform, matrix theory and control theory.
The following topics are covered. Sampled data systems: aliasing. Zero order hold equivalent: inverse of sampling, sampling system with time delay. Properties of difference equations: solution, stability, change of co-ordinates, Z transform. Input output models: pulse response, pulse transfer operator, pulse transfer function, interpretation of poles and zeros.
Analysis of discrete time system: stability (Jury's test, Nyquist criterion, Lyapunov method), sensitivity and robustness, observability (observers, reduced order observers), reachability and controllers, loss of reachability/observability through sampling, output feedback, the Separation theorem. Optimal control: Kalman filter, linear quadratic regulator, output feedback, the Separation theorem.
Approximating continuous time controllers. Finite word length mplementations.

This unit of study serves as an introduction to communications network research. The unit relies on a solid understanding of data communications and mobile networks. It introduces some of the currently most debated research topics in mobile networking and presents an overview of different technical solutions. Students are expected to critically evaluate these solutions in their context and produce an objective analysis of the advantages/disadvantages of the different research proposals. The general areas covered are wireless Internet, mobility management, quality of service in mobile and IP networks, ad hoc networks, and cellular network architectures.
The following topics are covered. Introduction to wireless and mobile Internet. Wireless cellular data networks. Cellular mobile networks. Mobile networks of the future. Quality of service in a mobile environment. Traffic modelling for wireless Internet. Traffic management for wireless Internet. Mobility management in mobile networks. Transport protocols for mobile networks. Internet protocols for mobile networks.

Objectives: How to apply the software package Matlab to achieve engineering solutions; Critical assessment of various computer numerical techniques; Professional project management, teamwork, ethics.
This unit assumes an understanding of the fundamental concepts and building blocks of electrical and electronics circuits. As well as covering the specific topics described in the following paragraphs, it aims to develop skills in professional project management and teamwork and promote an understanding of ethics.
Basic features of Matlab. The Matlab desktop. Interactive use with the command window. Performing arithmetic, using complex numbers and mathematical functions. Writing script and function m-files. Matrix manipulations. Control flow. Two dimensional graphics. Application of Matlab to simple problems from circuit theory, electronics, signals and systems and control. Investigation of the steady state and transient behaviour of LCR circuits.
Matlab based numerical solutions applicable to numerical optimisation, ordinary differential equations, and data fitting. Introduction to symbolic mathematics in Matlab. Applications, including the derivation of network functions for simple problems in circuit analysis. Introduction to the use of Simulink for system modelling and simulation.

This unit of study introduces participants to the power of simulation modelling in understanding and predicting behaviour of natural systems. It covers fundamental concepts, logic, and techniques (including sensitivity analysis), and develops skills in application to environmental problems such as catchment management and population dynamics.

No assessment of potential environmental impacts is possible without relevant information about the ecological consequences. This unit is for those without a quantitative ecology background, to explain the need to quantify and what are relevant measures. Describing and understanding uncertainty will be explained in the context of precautionary principles. Issues about measuring biodiversity and the spatial and temporal problems of ecological systems will be introduced. Field experience will also be available (up to two of six hour sessions) subject to weather, tides and available staffing; please note that these sessions are voluntary.

This unit of study gives an overview of basic spatial data models, and enables students to understand the use of data from a variety of sources within a geographical information system (GIS). The analysis of spatial data, and its manipulation to address questions appropriate to planning or locational applications, will be addressed, as will the development of thematic maps from diverse data layers.

The unit introduces methods associated with acquiring data in the field and examines issues associated with application of spatial data to environmental monitoring, terrain mapping and geocomputing. Students will learn both theoretically and practically how environmental data is collected using different remote sensing techniques, (pre)processing methods of integrating data in a GIS environment and the role of spatial data in understanding landscape processes and quantifying environmental change.

Many issues have been identified that are of potential relevance for planning, implementation and execution of an evaluation study in the health and technology innovations. This unit aims to address issues covering all phases of an evaluation study: Preliminary outline, study design, operationalization of methods, planning, execution and completion of the evaluation study. Students completing this unit will have better insights leading to a higher quality of evaluation studies for health technology solutions.
This unit is an important component towards building stronger evidence and thus to progress towards evidence-based health solutions and technology innovations.
Graduates of this unit of study will have a strong interdisciplinary knowledge base, covering diverse areas such as health, economics, health technologies, health informatics, social science and information systems.
Topics areas covered: 1. Economic Aspects of Health Technology Evaluation; 2. The Development of Health Technologies and Health Informatics Evaluation; 3. The Role of Evaluation in the Use and Diffusion of Health Technology.

This unit of study aims to introduce the student to the strategy of the Charles Perkins Centre to ease the burden of obesity, diabetes and cardiovascular disease. While other approaches would focus on these diseases as purely medical conditions this unit will challenge the student to focus on an interdisciplinary approach, bringing together medicine, biological science, psychology, economics, law, agriculture and other disciplines to understand how real world solutions for these diseases might be developed. Students will be exposed to the world-renowned researchers based in the Charles Perkins Centre and will gain insight into the research strategy of the Centre. Students will also have the opportunity to develop a new interdisciplinary project node for the Centre in collaboration with one of our research leaders.

Managing an organisation's logistics and supply chain management was for many years a neglected management activity. As a result of an article in Fortune in 1962 written by Peter Drucker, businesses became aware that 50 percent of each dollar consumers spent on goods financed activities that occur after the goods leave the factory, thus focusing attention on the potential efficiency savings that managing these activities could achieve. In the 50 years that has passed, business has seen massive changes; a complete management discipline has been built resulting in the integration and coordination of materials flows into, through, and out of, manufacturing facilities achieving exceptionally high levels of productivity. Logistics and supply chain management now plays a major role in implementing organisational strategy and in many industries has sole responsibility for managing customer service. An understanding of the role of this activity within an organisation and how an understanding of logistics and supply chains can assist business managers to better respond to market opportunities is essential for business students. Students undertaking this unit will be given a solid grounding in the language, concepts, techniques and principles that underlie the field of logistics and supply chain management, and how knowledge of these concepts can contribute towards a strategically effective and operationally efficient organisation or network of organisations.

This unit provides a comprehensive introduction to the role of transportation and infrastructure within the economy. The key concepts and theories needed for management of transport and infrastructure are introduced and each of the key transport and infrastructure industries are considered from a market intelligence perspective. In providing the foundational knowledge for students in transport and infrastructure, the unit also introduces students to the professional communication skills needed for success as a student and as a manager. Examples and case studies are drawn from all modes of transport and infrastructure.

Supply chain management as well as logistics, transport and infrastructure management relies on the ability to make effective decisions based on the information provided by careful analysis of data. Students undertaking this unit will develop a strong understanding of the basic techniques underpinning quantitative analysis and will develop highly marketable skills in spreadsheet modelling and the communication and presentation of data to support management decision making. This unit emphasises the practical aspects of quantitative analysis with computer based workshops. Students are guided through the basic theories used in decision making but emphasis is placed on how the theories are applied in practice, drawing on real world experience in quantitative analysis. The unit covers demand forecasting, spreadsheet modelling, optimisation of production and transportation using linear programming, simulation and basic statistics and linear regression techniques.

Successful supply chain management relies upon informed decision making. This unit explores a range of important decisions, and equips students with a toolkit of models and analytical methods that can assist in making informed decisions. The first set of decisions concern supply chain design and strategy, and includes network design and facility location. These decisions provide structure to the supply chain, set the boundaries within which planning decisions will be made, and impact on supply chain performance over the long term. In contrast, planning decisions provide value over the medium and short term. Here, this unit will cover aggregate planning, sales and operations planning, and inventory control. Special attention will be placed on how to handle uncertainty and risk within the supply chain.

Large scale, sudden onset disasters strike with little or no warning. In their wake they leave shattered infrastructure, collapsed services and traumatised populations, while the number of dead, injured and homeless often reaches staggering proportions. Humanitarian aid organisations, such as the Red Cross, Doctors without Borders or Oxfam, to name just a few, are usually amongst the first responders, but depend on extremely agile supply chains to support their worldwide operations. Successful disaster relief missions are characterised by the ability of professionals to cope with time pressure, high uncertainty and unusual restrictions. This unit is designed as an introduction to the coordination and management of humanitarian aid and emergency response logistics. Case studies of real events, such as the 2004 Boxing Day tsunami and the 2010 Haiti earthquake provide the framework for analysis and research, while discussion of operational factors, simulations, workshops and group exercises offer students an interactive learning environment.

Strategic transport planners advise the government on where to plan new infrastructure, where to expand existing infrastructure, or where to introduce or expand public transport services. When deciding on such large long?term investments in infrastructure and transit services, all government bodies ? federal, state, and local ? rely on forecasts of the effects of these investments on traffic flows, congestion, toll revenues and impacts on the environment. This unit provides a basic understanding of the main principles underlying strategic transport models for forecasting, and the knowledge to critically assess forecasts of transport strategies made by transport planners. Students acquire knowledge of strategic forecasting models used by government and consultants as well as the methods to capture travel behaviour such as mode choice and route choice. Simple mathematical models will be discussed in detail, along with numerical examples and applications in the Sydney Metropolitan Area, which are used to illustrate the principles of the methods. The unit equips students to build simple transport models in the computer lab using specialised transport planning software used by governments and consultants.

The world is increasingly filled with systems, devices and sensors collecting large amounts of data on a continual basis. Most of these data are associated with locations that represent everything from the movement of individuals travelling between activities to the flow of goods or transactions along a supply chain and from the location of companies to those of their current and future customers. Taking this spatial context into account transforms analyses, problem solving and provides a powerful method of visualising the world. This is the essence of Geographic Information Systems (GIS) and this unit. This unit starts by introducing students to the 'building blocks' of GIS systems, including data structures, relational databases, spatial queries and analysis. The focus then moves on to sources of spatial data including Global Positioning System (GPS), operational systems such as smartcard ticketing and transaction data along with web-based sources highlighting both the potential and challenges associated with integrating each data source within a GIS environment. The unit is hands-on involving learning how to use the latest GIS software to analyse several problems of interest using real 'big data' sources and to communicate the results in a powerful and effective way. These include identifying potential demand for new services or infrastructure, creating a delivery and scheduling plan for a delivery firm or examining the behaviour of travellers or consumers over time and locations. This unit is aimed at students interested in the spatial impact of decision-making and on the potential for using large spatial datasets for in-depth multi-faceted analytics.

This unit of study introduces contemporary topics from Ecological Economics and Sutainability Analysis, such as metrics for measuring sustainability; planetary boundaries and other natural limits; comparisons between ecological and environmental economics; valuing the environment; intergenerational discounting; global enquality with a focus on the climate change debate; and links between theories of well-being, human behaviour, consumerism and environmental impact. This unit includes guest lecturers from industry and research and an excursion. Each lecture includes hands-on exercises for practical skill-building. The unit sets the scene for the more detailed and specific units PHYS5032, PHYS5033, and PHYS5034.

This unit of study offers a practical introduction to quantitative analysis techniques including multiple regression, uncertainty analysis, integration, structural decomposition, and dynamic systems modelling, with a strong emphasis on demonstrating their usefulness for environmental problem-solving. This unit will show students how mathematics can be brought to life when utilised in powerful applications to deal with environmental and sustainability issues. Throughout the unit of study, example applications will be explained, including climate modelling, ecosystem trophic chain analysis, linking household consumption and environmental impact, identifying socio-demographic drivers of environmental change, and the uncovering the effect of land use patterns on threats to species.

Innovation is widely-recognised as a major driver of economic growth. Yet innovation projects can be difficult to manage: they typically involve a high level of uncertainty, and many organisations are unsatisfied with the level of innovation they achieve. In this unit of study, we focus on issues in the management of innovation projects at the individual project level, organisational level and across networks of organisations. Since a systematic approach can and does improve our effectiveness in managing innovation, we begin by exploring several different process models of the stages through which innovation projects are managed. We discuss context and challenges which impact such projects, as well as the concepts of creativity and intellectual property management. Using focused case studies, we analyse best practice in the structures and processes that organisations can provide to enable innovation, as well as to support the search, selection, implementation, dissemination, feedback and evaluation stages of their innovative projects. We also examine the impact of networks on innovation (e.g. collaboration networks), national innovation policies and systems, and trends towards open innovation.

This unit identifies the causes of some well-known disasters (natural, man-made and projects) and reveals what can be learned by being able to think critically and analyse the issues. The aim of this unit is to outline traditional and contemporary theories in emergency response planning; to provide an overall scope of comprehensive emergency planning and the major elements that must be addressed in an Emergency Response Plan. Student outcomes from this unit include: Developing and implementing an Emergency Response Plan; Specific recommendations for the health and safety of emergency response personnel and provides concise information on learning objectives and a review of important concepts.

This unit provides students with core skills in epidemiology, particularly the ability to critically appraise public health and clinical epidemiological research literature. This unit covers: study types; measures of frequency and association; measurement bias; confounding/effect modification; randomized trials; systematic reviews; screening and test evaluation; infectious disease outbreaks; measuring public health impact and use and interpretation of population health data. It is expected that students spend an additional 2-3 hours at least each week preparing for their tutorials.

This fully online unit aims to provide students with an understanding of the burden of communicable diseases of public health significance in Australia, as well as the biology, epidemiology and surveillance for and control of those communicable diseases. By the end of this unit, the student will have the theoretical background to take up a position as a member of a Communicable Diseases section of a Commonwealth or State Health Department or Public Health Unit. It is expected that the students undertake an extra hour per week of reading, research and preparation for discussion.

This unit introduces students to the extremely close nexus between human health, demographic change and environmental sustainability issues. This relationship is examined within the context of the three pillars of sustainable development with a focus on achieving equitable outcomes. This unit explores the extent to which environmental changes influence population demographics and health, and the extent to which demographic and secular changes impact on the physical environment. The influence of migration, conflict, food insecurity, droughts, flooding, heat stress, emerging and re-emerging infections and chronic health problems on poverty, ageing and dependency, physical, mental and social health and economic sustainability will be analysed alongside the elements needed to preserve the diversity and functioning of the ecosystem for future human survival. International models and policies for mitigating and/or adapting to the negative consequences of globalisation, urbanisation, overconsumption, and resource depletion will be analysed for their potential benefits and harms to sustainable population growth, optimal health and equitable distribution of essential resources.

On completion of this unit students should be familiar with the major concepts and tools of epidemiology, the study of health in populations, and should be able to judge the quality of evidence in health-related research literature.
This unit covers: historical developments in epidemiology; sources of data on mortality and morbidity; disease rates and standardisation; prevalence and incidence; life expectancy; linking exposure and disease (eg. relative risk, attributable risk); main types of study designs - case series, ecological studies, cross-sectional surveys, case-control studies, cohort or follow-up studies, randomised controlled trials; sources of error (chance, bias, confounding); association and causality; evaluating published papers; epidemics and epidemic investigation; surveillance; prevention; screening; the role of epidemiology in health services research and policy.

This unit assesses the political and security significance of disease-related events and developments. Whether one contemplates historical experiences with smallpox, the contemporary challenges posed by diseases such as HIV/AIDS and SARS, or the risks arising from new scientific developments such as synthetic biology, it is clear that diseases exercise a powerful influence over civilised humankind. The unit concentrates on areas in which human health and security concerns intersect most closely, including: biological weapons; fast-moving disease outbreaks of natural origin; safety and security in microbiology laboratories; and the relationships between infectious disease patterns, public health capacity, state functioning and violent conflict. The overall aim of the unit is to provide students with a stronger understanding of the scientific and political nature of these problems, why and how they might threaten security, and the conceptual and empirical connections between them.

Many issues have been identified that are of potential relevance for planning, implementation and execution of an evaluation study in the health and technology innovations. This unit aims to address issues covering all phases of an evaluation study: Preliminary outline, study design, operationalization of methods, planning, execution and completion of the evaluation study. Students completing this unit will have better insights leading to a higher quality of evaluation studies for health technology solutions.
This unit is an important component towards building stronger evidence and thus to progress towards evidence-based health solutions and technology innovations.
Graduates of this unit of study will have a strong interdisciplinary knowledge base, covering diverse areas such as health, economics, health technologies, health informatics, social science and information systems.
Topics areas covered: 1. Economic Aspects of Health Technology Evaluation; 2. The Development of Health Technologies and Health Informatics Evaluation; 3. The Role of Evaluation in the Use and Diffusion of Health Technology.

This unit of study aims to introduce the student to the strategy of the Charles Perkins Centre to ease the burden of obesity, diabetes and cardiovascular disease. While other approaches would focus on these diseases as purely medical conditions this unit will challenge the student to focus on an interdisciplinary approach, bringing together medicine, biological science, psychology, economics, law, agriculture and other disciplines to understand how real world solutions for these diseases might be developed. Students will be exposed to the world-renowned researchers based in the Charles Perkins Centre and will gain insight into the research strategy of the Centre. Students will also have the opportunity to develop a new interdisciplinary project node for the Centre in collaboration with one of our research leaders.

This unit provides students with core skills in epidemiology, particularly the ability to critically appraise public health and clinical epidemiological research literature. This unit covers: study types; measures of frequency and association; measurement bias; confounding/effect modification; randomized trials; systematic reviews; screening and test evaluation; infectious disease outbreaks; measuring public health impact and use and interpretation of population health data. It is expected that students spend an additional 2-3 hours at least each week preparing for their tutorials.

This fully online unit aims to provide students with an understanding of the burden of communicable diseases of public health significance in Australia, as well as the biology, epidemiology and surveillance for and control of those communicable diseases. By the end of this unit, the student will have the theoretical background to take up a position as a member of a Communicable Diseases section of a Commonwealth or State Health Department or Public Health Unit. It is expected that the students undertake an extra hour per week of reading, research and preparation for discussion.

This unit introduces students to the extremely close nexus between human health, demographic change and environmental sustainability issues. This relationship is examined within the context of the three pillars of sustainable development with a focus on achieving equitable outcomes. This unit explores the extent to which environmental changes influence population demographics and health, and the extent to which demographic and secular changes impact on the physical environment. The influence of migration, conflict, food insecurity, droughts, flooding, heat stress, emerging and re-emerging infections and chronic health problems on poverty, ageing and dependency, physical, mental and social health and economic sustainability will be analysed alongside the elements needed to preserve the diversity and functioning of the ecosystem for future human survival. International models and policies for mitigating and/or adapting to the negative consequences of globalisation, urbanisation, overconsumption, and resource depletion will be analysed for their potential benefits and harms to sustainable population growth, optimal health and equitable distribution of essential resources.

This unit of study introduces participants to the power of simulation modelling in understanding and predicting behaviour of natural systems. It covers fundamental concepts, logic, and techniques (including sensitivity analysis), and develops skills in application to environmental problems such as catchment management and population dynamics.

No assessment of potential environmental impacts is possible without relevant information about the ecological consequences. This unit is for those without a quantitative ecology background, to explain the need to quantify and what are relevant measures. Describing and understanding uncertainty will be explained in the context of precautionary principles. Issues about measuring biodiversity and the spatial and temporal problems of ecological systems will be introduced. Field experience will also be available (up to two of six hour sessions) subject to weather, tides and available staffing; please note that these sessions are voluntary.

This unit of study gives an overview of basic spatial data models, and enables students to understand the use of data from a variety of sources within a geographical information system (GIS). The analysis of spatial data, and its manipulation to address questions appropriate to planning or locational applications, will be addressed, as will the development of thematic maps from diverse data layers.

The unit introduces methods associated with acquiring data in the field and examines issues associated with application of spatial data to environmental monitoring, terrain mapping and geocomputing. Students will learn both theoretically and practically how environmental data is collected using different remote sensing techniques, (pre)processing methods of integrating data in a GIS environment and the role of spatial data in understanding landscape processes and quantifying environmental change.

This unit of study introduces contemporary topics from Ecological Economics and Sutainability Analysis, such as metrics for measuring sustainability; planetary boundaries and other natural limits; comparisons between ecological and environmental economics; valuing the environment; intergenerational discounting; global enquality with a focus on the climate change debate; and links between theories of well-being, human behaviour, consumerism and environmental impact. This unit includes guest lecturers from industry and research and an excursion. Each lecture includes hands-on exercises for practical skill-building. The unit sets the scene for the more detailed and specific units PHYS5032, PHYS5033, and PHYS5034.

This unit of study offers a practical introduction to quantitative analysis techniques including multiple regression, uncertainty analysis, integration, structural decomposition, and dynamic systems modelling, with a strong emphasis on demonstrating their usefulness for environmental problem-solving. This unit will show students how mathematics can be brought to life when utilised in powerful applications to deal with environmental and sustainability issues. Throughout the unit of study, example applications will be explained, including climate modelling, ecosystem trophic chain analysis, linking household consumption and environmental impact, identifying socio-demographic drivers of environmental change, and the uncovering the effect of land use patterns on threats to species.

This unit introduces students to the extremely close nexus between human health, demographic change and environmental sustainability issues. This relationship is examined within the context of the three pillars of sustainable development with a focus on achieving equitable outcomes. This unit explores the extent to which environmental changes influence population demographics and health, and the extent to which demographic and secular changes impact on the physical environment. The influence of migration, conflict, food insecurity, droughts, flooding, heat stress, emerging and re-emerging infections and chronic health problems on poverty, ageing and dependency, physical, mental and social health and economic sustainability will be analysed alongside the elements needed to preserve the diversity and functioning of the ecosystem for future human survival. International models and policies for mitigating and/or adapting to the negative consequences of globalisation, urbanisation, overconsumption, and resource depletion will be analysed for their potential benefits and harms to sustainable population growth, optimal health and equitable distribution of essential resources.

Virtually every aspect of a chemical engineer's professional life will involve some use of mathematical techniques. Not only is the modern chemical engineer expected to be proficient in the use of these techniques, they are also expected to be able to utilise computer-based solutions when analytical solutions are unfeasible. This unit of study aims to expose students to an appropriate suite of techniques and enable them to become proficient in the use of mathematics as a tool for the solution of a diversity of chemical engineering problems.
Specifically, this unit consists of two core modules: MODULE A: Applied Statistics for Chemical Engineers and MODULE B: Applied Numerical Methods for Chemical Engineers. These modules aim at furthering knowledge by extending skills in statistical analysis and Chemical Engineering computations. This unit will also enable the development of a systematic approach to solving mathematically oriented Chemical Engineering problems, which will help with making sound engineering decisions. In addition, there will be considerable time spent during the semester on advanced topics related to mathematical analysis techniques in engineering and recent associated developments.

This unit aims to give students an introduction to the planning and operation of modern electricity grids, also known as "smart" grids. Traditional power networks featured a small number of large base-load plants sending power out over transmission lines to be distributed in radial lower voltage networks to loads. In response to the need to reduce carbon impact, future networks will feature diverse generation scattered all over the network including at distribution levels. Also there will be new loads such as electric vehicles and technologies including energy storage and lower voltage power flow control devices. The operation of these new networks will be possible by much greater use of information and communication technology (ICT) and control over the information networks.
The unit will cover recent relevant developments in energy technologies as well as important components of 'smart grids' such as supervisory control and data acquisition (SCADA), substation automation, remote terminal units (RTU), sensors and intelligent electronic devices (IED). Operation of these electricity grids requires a huge amount of data gathering, communication and information processing. The unit will discuss many emerging technologies for such data, information, knowledge and decision processes including communication protocols and network layouts, networking middleware and coordinated control. Information systems and data gathering will be used to assess key performance and security indicators associated with the operation of such grids including stability, reliability and power quality.

This unit aims to teach the basic issues involved in the analysis and design of computer-controlled systems. The emphasis is on theory rather than technological application or industrial practice.
However, students are expected to test some of these ideas on a few benchmark control problems in the laboratory. Completion of the unit will facilitate progression to advanced study in the area and to work in industrial control. This unit assumes a basic knowledge of calculus, functions of real variables, Laplace transform, matrix theory and control theory.
The following topics are covered. Sampled data systems: aliasing. Zero order hold equivalent: inverse of sampling, sampling system with time delay. Properties of difference equations: solution, stability, change of co-ordinates, Z transform. Input output models: pulse response, pulse transfer operator, pulse transfer function, interpretation of poles and zeros.
Analysis of discrete time system: stability (Jury's test, Nyquist criterion, Lyapunov method), sensitivity and robustness, observability (observers, reduced order observers), reachability and controllers, loss of reachability/observability through sampling, output feedback, the Separation theorem. Optimal control: Kalman filter, linear quadratic regulator, output feedback, the Separation theorem.
Approximating continuous time controllers. Finite word length mplementations.

This unit of study serves as an introduction to communications network research. The unit relies on a solid understanding of data communications and mobile networks. It introduces some of the currently most debated research topics in mobile networking and presents an overview of different technical solutions. Students are expected to critically evaluate these solutions in their context and produce an objective analysis of the advantages/disadvantages of the different research proposals. The general areas covered are wireless Internet, mobility management, quality of service in mobile and IP networks, ad hoc networks, and cellular network architectures.
The following topics are covered. Introduction to wireless and mobile Internet. Wireless cellular data networks. Cellular mobile networks. Mobile networks of the future. Quality of service in a mobile environment. Traffic modelling for wireless Internet. Traffic management for wireless Internet. Mobility management in mobile networks. Transport protocols for mobile networks. Internet protocols for mobile networks.

Objectives: How to apply the software package Matlab to achieve engineering solutions; Critical assessment of various computer numerical techniques; Professional project management, teamwork, ethics.
This unit assumes an understanding of the fundamental concepts and building blocks of electrical and electronics circuits. As well as covering the specific topics described in the following paragraphs, it aims to develop skills in professional project management and teamwork and promote an understanding of ethics.
Basic features of Matlab. The Matlab desktop. Interactive use with the command window. Performing arithmetic, using complex numbers and mathematical functions. Writing script and function m-files. Matrix manipulations. Control flow. Two dimensional graphics. Application of Matlab to simple problems from circuit theory, electronics, signals and systems and control. Investigation of the steady state and transient behaviour of LCR circuits.
Matlab based numerical solutions applicable to numerical optimisation, ordinary differential equations, and data fitting. Introduction to symbolic mathematics in Matlab. Applications, including the derivation of network functions for simple problems in circuit analysis. Introduction to the use of Simulink for system modelling and simulation.

Innovation is widely-recognised as a major driver of economic growth. Yet innovation projects can be difficult to manage: they typically involve a high level of uncertainty, and many organisations are unsatisfied with the level of innovation they achieve. In this unit of study, we focus on issues in the management of innovation projects at the individual project level, organisational level and across networks of organisations. Since a systematic approach can and does improve our effectiveness in managing innovation, we begin by exploring several different process models of the stages through which innovation projects are managed. We discuss context and challenges which impact such projects, as well as the concepts of creativity and intellectual property management. Using focused case studies, we analyse best practice in the structures and processes that organisations can provide to enable innovation, as well as to support the search, selection, implementation, dissemination, feedback and evaluation stages of their innovative projects. We also examine the impact of networks on innovation (e.g. collaboration networks), national innovation policies and systems, and trends towards open innovation.

This unit identifies the causes of some well-known disasters (natural, man-made and projects) and reveals what can be learned by being able to think critically and analyse the issues. The aim of this unit is to outline traditional and contemporary theories in emergency response planning; to provide an overall scope of comprehensive emergency planning and the major elements that must be addressed in an Emergency Response Plan. Student outcomes from this unit include: Developing and implementing an Emergency Response Plan; Specific recommendations for the health and safety of emergency response personnel and provides concise information on learning objectives and a review of important concepts.

Managing an organisation's logistics and supply chain management was for many years a neglected management activity. As a result of an article in Fortune in 1962 written by Peter Drucker, businesses became aware that 50 percent of each dollar consumers spent on goods financed activities that occur after the goods leave the factory, thus focusing attention on the potential efficiency savings that managing these activities could achieve. In the 50 years that has passed, business has seen massive changes; a complete management discipline has been built resulting in the integration and coordination of materials flows into, through, and out of, manufacturing facilities achieving exceptionally high levels of productivity. Logistics and supply chain management now plays a major role in implementing organisational strategy and in many industries has sole responsibility for managing customer service. An understanding of the role of this activity within an organisation and how an understanding of logistics and supply chains can assist business managers to better respond to market opportunities is essential for business students. Students undertaking this unit will be given a solid grounding in the language, concepts, techniques and principles that underlie the field of logistics and supply chain management, and how knowledge of these concepts can contribute towards a strategically effective and operationally efficient organisation or network of organisations.

This unit provides a comprehensive introduction to the role of transportation and infrastructure within the economy. The key concepts and theories needed for management of transport and infrastructure are introduced and each of the key transport and infrastructure industries are considered from a market intelligence perspective. In providing the foundational knowledge for students in transport and infrastructure, the unit also introduces students to the professional communication skills needed for success as a student and as a manager. Examples and case studies are drawn from all modes of transport and infrastructure.

Supply chain management as well as logistics, transport and infrastructure management relies on the ability to make effective decisions based on the information provided by careful analysis of data. Students undertaking this unit will develop a strong understanding of the basic techniques underpinning quantitative analysis and will develop highly marketable skills in spreadsheet modelling and the communication and presentation of data to support management decision making. This unit emphasises the practical aspects of quantitative analysis with computer based workshops. Students are guided through the basic theories used in decision making but emphasis is placed on how the theories are applied in practice, drawing on real world experience in quantitative analysis. The unit covers demand forecasting, spreadsheet modelling, optimisation of production and transportation using linear programming, simulation and basic statistics and linear regression techniques.

Successful supply chain management relies upon informed decision making. This unit explores a range of important decisions, and equips students with a toolkit of models and analytical methods that can assist in making informed decisions. The first set of decisions concern supply chain design and strategy, and includes network design and facility location. These decisions provide structure to the supply chain, set the boundaries within which planning decisions will be made, and impact on supply chain performance over the long term. In contrast, planning decisions provide value over the medium and short term. Here, this unit will cover aggregate planning, sales and operations planning, and inventory control. Special attention will be placed on how to handle uncertainty and risk within the supply chain.

Large scale, sudden onset disasters strike with little or no warning. In their wake they leave shattered infrastructure, collapsed services and traumatised populations, while the number of dead, injured and homeless often reaches staggering proportions. Humanitarian aid organisations, such as the Red Cross, Doctors without Borders or Oxfam, to name just a few, are usually amongst the first responders, but depend on extremely agile supply chains to support their worldwide operations. Successful disaster relief missions are characterised by the ability of professionals to cope with time pressure, high uncertainty and unusual restrictions. This unit is designed as an introduction to the coordination and management of humanitarian aid and emergency response logistics. Case studies of real events, such as the 2004 Boxing Day tsunami and the 2010 Haiti earthquake provide the framework for analysis and research, while discussion of operational factors, simulations, workshops and group exercises offer students an interactive learning environment.

Strategic transport planners advise the government on where to plan new infrastructure, where to expand existing infrastructure, or where to introduce or expand public transport services. When deciding on such large long?term investments in infrastructure and transit services, all government bodies ? federal, state, and local ? rely on forecasts of the effects of these investments on traffic flows, congestion, toll revenues and impacts on the environment. This unit provides a basic understanding of the main principles underlying strategic transport models for forecasting, and the knowledge to critically assess forecasts of transport strategies made by transport planners. Students acquire knowledge of strategic forecasting models used by government and consultants as well as the methods to capture travel behaviour such as mode choice and route choice. Simple mathematical models will be discussed in detail, along with numerical examples and applications in the Sydney Metropolitan Area, which are used to illustrate the principles of the methods. The unit equips students to build simple transport models in the computer lab using specialised transport planning software used by governments and consultants.

The world is increasingly filled with systems, devices and sensors collecting large amounts of data on a continual basis. Most of these data are associated with locations that represent everything from the movement of individuals travelling between activities to the flow of goods or transactions along a supply chain and from the location of companies to those of their current and future customers. Taking this spatial context into account transforms analyses, problem solving and provides a powerful method of visualising the world. This is the essence of Geographic Information Systems (GIS) and this unit. This unit starts by introducing students to the 'building blocks' of GIS systems, including data structures, relational databases, spatial queries and analysis. The focus then moves on to sources of spatial data including Global Positioning System (GPS), operational systems such as smartcard ticketing and transaction data along with web-based sources highlighting both the potential and challenges associated with integrating each data source within a GIS environment. The unit is hands-on involving learning how to use the latest GIS software to analyse several problems of interest using real 'big data' sources and to communicate the results in a powerful and effective way. These include identifying potential demand for new services or infrastructure, creating a delivery and scheduling plan for a delivery firm or examining the behaviour of travellers or consumers over time and locations. This unit is aimed at students interested in the spatial impact of decision-making and on the potential for using large spatial datasets for in-depth multi-faceted analytics.

The research pathway project aims to provide: (a) analytical and computational skills for modelling systems characterised by many interacting heterogeneous variables, (b) adequate programming skills for simulating complex systems. It is aimed at developing a pathway to a research career. The student will work individually on an assigned open-ended research project, focussed on modelling a complex problem or delivering a novel solution. The concepts covered depend on the nature of the project. The project could be directly tied to student's area of specialisation (major), or to their vocational objectives or interests. Students with expertise in a specific industry sector may be invited to partner with relevant team projects. The project outcomes will be presented in a thesis that is clear, coherent and logically structured. The project will be judged on the extent and quality of the student's original work and particularly how innovative, perceptive and constructive they have been in developing and applying cross-disciplinary complex systems concepts. As the result, the student will develop capability for modelling complex systems, from the identification of the relevant variables and interactions to the analysis and simulations of the predictions, having learnt the conceptual and methodological tools (techniques and algorithms) for the analysis and inference of complex models.

The research pathway project aims to provide: (a) analytical and computational skills for modelling systems characterised by many interacting heterogeneous variables, (b) adequate programming skills for simulating complex systems. It is aimed at developing a pathway to a research career. The student will work individually on an assigned open-ended research project, focussed on modelling a complex problem or delivering a novel solution. The concepts covered depend on the nature of the project. The project could be directly tied to student's area of specialisation (major), or to their vocational objectives or interests. Students with expertise in a specific industry sector may be invited to partner with relevant team projects. The project outcomes will be presented in a thesis that is clear, coherent and logically structured. The project will be judged on the extent and quality of the student's original work and particularly how innovative, perceptive and constructive they have been in developing and applying cross-disciplinary complex systems concepts. As the result, the student will develop capability for modelling complex systems, from the identification of the relevant variables and interactions to the analysis and simulations of the predictions, having learnt the conceptual and methodological tools (techniques and algorithms) for the analysis and inference of complex models.