961 resultados para Complexity science


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The mining industry faces three long term strategic risks in relation to its water and energy use: 1) securing enough water and energy to meet increased production; 2) reducing water use, energy consumption and emissions due to social, environmental and economic pressures; and 3) understanding the links between water and energy, so that an improvement in one area does not create an adverse effect in another. This project helps the industry analyse these risks by creating a hierarchical systems model (HSM) that represents the water and energy interactions on a sub-site, site and regional scales; which is coupled with a flexible risk framework. The HSM consists of: components that represent sources of water and energy; activities that use water and energy and off-site destinations of water and produced emissions. It can also represent more complex components on a site, with inbuilt examples including tailings dams and water treatment plants. The HSM also allows multiple sites and other infrastructure to be connected together to explore regional water and energy interactions. By representing water and energy as a single interconnected system the HSM can explore tradeoffs and synergies. For example, on a synthetic case study, which represents a typical site, simulations suggested that while a synergy in terms of water use and energy use could be made when chemical additives were used to enhance dust suppression, there were trade-offs when either thickened tailings or dry processing were used. On a regional scale, the HSM was used to simulate various scenarios, including: mines only withdrawing water when needed; achieving economics-of-scale through use of a single centralised treatment plant rather than smaller decentralised treatment plants; and capturing of fugitive emissions for energy generation. The HSM also includes an integrated risk framework for interpreting model output, so that onsite and off-site impacts of various water and energy management strategies can be compared in a managerial context. The case studies in this report explored company, social and environmental risks for scenarios of regional water scarcity, unregulated saline discharge, and the use of plantation forestry to offset carbon emissions. The HSM was able to represent the non-linear causal relationship at the regional scale, such as the forestry scheme offsetting a small percentage of carbon emissions but causing severe regional water shortages. The HSM software developed in this project will be released as an open source tool to allow industry personnel to easily and inexpensively quantify and explore the links between water use, energy use, and carbon emissions. The tool can be easily adapted to represent specific sites or regions. Case studies conducted in this project highlighted the potential complexity of these links between water, energy, and carbon emissions, as well as the significance of the cumulative effects of these links over time. A deeper understanding of these links is vital for the mining industry in order to progress to more sustainable operations, and the HSM provides an accessible, robust framework for investigating these links.

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Plant food materials have a very high demand in the consumer market and therefore, improved food products and efficient processing techniques are concurrently being researched in food engineering. In this context, numerical modelling and simulation techniques have a very high potential to reveal fundamentals of the underlying mechanisms involved. However, numerical modelling of plant food materials during drying becomes quite challenging, mainly due to the complexity of the multiphase microstructure of the material, which undergoes excessive deformations during drying. In this regard, conventional grid-based modelling techniques have limited applicability due to their inflexible grid-based fundamental limitations. As a result, meshfree methods have recently been developed which offer a more adaptable approach to problem domains of this nature, due to their fundamental grid-free advantages. In this work, a recently developed meshfree based two-dimensional plant tissue model is used for a comparative study of microscale morphological changes of several food materials during drying. The model involves Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) to represent fluid and solid phases of the cellular structure. Simulation are conducted on apple, potato, carrot and grape tissues and the results are qualitatively and quantitatively compared and related with experimental findings obtained from the literature. The study revealed that cellular deformations are highly sensitive to cell dimensions, cell wall physical and mechanical properties, middle lamella properties and turgor pressure. In particular, the meshfree model is well capable of simulating critically dried tissues at lower moisture content and turgor pressure, which lead to cell wall wrinkling. The findings further highlighted the potential applicability of the meshfree approach to model large deformations of the plant tissue microstructure during drying, providing a distinct advantage over the state of the art grid-based approaches.

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A system is something that can be separated from its surrounds, but this definition leaves much scope for refinement. Starting with the notion of measurement, we explore increasingly contextual system behaviour, and identify three major forms of contextuality that might be exhibited by a system: (a) between components; (b) between system and experimental method, and; (c) between a system and its environment. Quantum Theory is shown to provide a highly useful formalism from which all three forms of contextuality can be analysed, offering numerous tests for contextual behaviour, as well as modelling possibilities for systems that do indeed display it. I conclude with the introduction of a Contextualised General Systems Theory based upon an extension of this formalism.

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Review of The Anatomist by Bill Hayes (Scribe, 2008). Bill Hayes wanted to write about Henry Gray, the author of Gray's Anatomy (1858), which at least until the television series connoted a standard text for anatomy students. Perhaps even more seductive for the biographer than the book's enduring appeal was a sense that Gray himself had partly disappeared from the historical record. Here was a scientist with the sort of brilliant young mind that seemed a specialty of the Victorian Age, and yet one who had not benefited from that period's compulsive documenting of the men of the moment and their deeds. Surely in that mystery there lay a narrative...

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Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.

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"Christy Dena’s online-remix-narrative takes iconic images of popular culture and builds with them a strange world where the human fallibility is programmatically deleted. Both dystopic and playful, Dena’s work is an ironic reimagining of pleasure as a state of robotic flatlining, using tropes of science fiction to critique processes of social normalisation and increasing alienation from emotionality." This creative response began as a completely different story and form. What excited me in the end was the concept of deletion and how it could be an interesting mechanic: where the only thing you can do in the world is delete. I thought about deleting parts of robots to make them better. Healing comes from taking away, from removing things. Memories of Joseph Weizenbaum’s chatbot ELIZA came flooding back: where the (human) player is a patient talking to a Rogerian psychotherapist. But in this work I’m switching the roles and making the player the doctor, a doctor to robots…a doctor that can only prescribe deletions. I conceived of the work as a branching narrative, and started writing it in Twine. With every robot patient, the player chose one of many deletions. But when I realised I wouldn’t be able to arrange an artist and sound designer I looked for another option. I played with Zeega and felt that I could get the mood I was after with that platform. So the piece transformed into a work where the player/viewer is imprisoned in the decisions of the deleting protagonist…which has its own effect on the experience and meaning.

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Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

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Existing planning theories tend to be limited in their analytical scope and often fail to account for the impact of many interactions between the multitudes of stakeholders involved in strategic planning processes. Although many theorists rejected structural–functional approaches from the 1970s, this article argues that many of structural–functional concepts remain relevant and useful to planning practitioners. In fact, structural–functional approaches are highly useful and practical when used as a foundation for systemic analysis of real-world, multi-layered, complex planning systems to support evidence-based governance reform. Such approaches provide a logical and systematic approach to the analysis of the wider governance of strategic planning systems that is grounded in systems theory and complementary to existing theories of complexity and planning. While we do not propose its use as a grand theory of planning, this article discusses how structural–functional concepts and approaches might be applied to underpin a practical analysis of the complex decision-making arrangements that drive planning practice, and to provide the evidence needed to target reform of poorly performing arrangements.

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In this chapter we describe the substantial declines in student participation in senior high school physics, chemistry and biology classes in Australia over the last two decades. We outline some of the explanations commonly offered to account for these declines, focusing on two contrasting positions: first, that they are due to today’s students holding less positive attitudes towards science classes and careers than their predecessors, and second, that the declines are related to policy and structural changes at the upper secondary and tertiary education levels which have affected the relative status of subjects and the dynamics of choice. We describe how the Choosing Science study investigated the extent to which the two hypotheses were supported by empirical evidence, and discuss our findings in the light of a third result from the study concerning the role of self-identity in subject choice. We conclude that the declines in high school science enrolments are most likely related to changes in school and university curriculum options and that within this expanded curriculum marketplace, identity becomes a very important reference point in students’ decisions about whether to take science in the final years of high school.

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The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 10^5, 10^2 and 10^0 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10^-2, 10^-1 and 10^0 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.

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Although science is generally assumed to be well integrated into rational decision-making models, it can be used to destabilise consultative processes, particularly when emotions are involved. Water policies are often seen as debates over technical and engineering issues, but can be highly controversial. Recycled water proposals, in particular, can create highly emotive conflicts. Through a case study regarding the rejection of recycled water proposals in the south-east Queensland, Australia, we explore the influence of science and emotions in contemporary water planning. We highlight the dangers inherent in promoting technical water planning issues at the expense of appropriate consideration of citizen concerns. Combining the science–policy interface and stakeholder engagement literatures, we advocate for collaborative decision-making processes that accommodate emotions and value judgements. A more collaborative stakeholder engagement model, founded on the principles of co-learning, has the potential to broaden the decision-making base and to promote better and more inclusive decision-making.

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Abstract: Australia’s ecosystems are the basis of our current and future prosperity, and our national well-being.A strong and sustainable Australian ecosystem science enterprise is vital for understanding and securing these ecosystems in the face of current and future challenges. This Plan defines the vision and key directions for a national ecosystem science capability that will enable Australia to understand and effectively manage its ecosystems for decades to come.The Plan’s underlying theme is that excellent science supports a range of activities, including public engagement, that enable us to understand and maintain healthy ecosystems.Those healthy ecosystems are the cornerstone of our social and economic well-being.The vision guiding the development of this Plan is that in 20 years’ time the status of Australian ecosystems and how they change will be widely reported and understood, and the prosperity and well-being they provide will be secure. To enable this, Australia’s national ecosystem science capability will be coordinated, collaborative and connected.The Plan is based on an extensive set of collaboratively generated proposals from national town hall meetings that also formthe basis for its implementation. Some directions within the Plan are for the Australian ecosystem science community itself to implement, others will involve the users of ecosystem science and the groups that fund ecosystem science.We identify six equal priority areas for action to achieve our vision: (i) delivering maximum impact for Australia: enhancing relationships between scientists and end-users; (ii) supporting long-termresearch; (iii) enabling ecosystem surveillance; (iv) making the most of data resources; (v) inspiring a generation: empowering the public with knowledge and opportunities; (vi) facilitating coordination, collaboration and leadership. This shared vision will enable us to consolidate our current successes, overcome remaining barriers and establish the foundations to ensure Australian ecosystem science delivers for the future needs of Australia..