386 resultados para Ecological Infrastructure
Resumo:
Public-Private Partnerships (PPP) are established globally as an important mode of procurement and the features of PPP, not least of which the transfer of risk, appeal to governments and particularly in the current economic climate. There are many other advantages of PPP that are claimed as outweighing the costs of PPP and affording Value for Money (VfM) relative to traditionally financed projects or non-PPP. That said, it is the case that we lack comparative whole-life empirical studies of VfM in PPP and non-PPP. Whilst we await this kind of study, the pace and trajectory of PPP seem set to continue and so in the meantime, the virtues of seeking to improve PPP appear incontrovertible. The decision about which projects, or parts of projects, to offer to the market as a PPP and the decision concerning the allocation or sharing risks as part of engagement of the PPP consortium are among the most fundamental decisions that determine whether PPP deliver VfM. The focus in the paper is on latter decision concerning governments’ attitudes towards risk and more specifically, the effect of this decision on the nature of the emergent PPP consortium, or PPP model, including its economic behavior and outcomes. This paper presents an exploration into the extent to which the seemingly incompatible alternatives of risk allocation and risk sharing, represented by the orthodox/conventional PPP model and the heterodox/alliance PPP model respectively, can be reconciled along with suggestions for new research directions to inform this reconciliation. In so doing, an important step is taken towards charting a path by which governments can harness the relative strengths of both kinds of PPP model.
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This is presentation of the refereed paper accepted for the Conferences' proceedings. The presentation was given on Tuesday, 1 December 2015.
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This paper presents an ecological/evolutionary approach to enterprise education. Ecological approaches are used at the University of Tasmania to heighten the awareness of students to a raft of difficult to observe environmental factors associated with developing enterprising ideas. At Sheffield University, the discovery and exploitation of entrepreneurial opportunities is viewed as a co-evolving system of emerging business ideas, and routines/heuristics respectively. It is argued that using both approaches enables students to develop a greater awareness of their situated environment, and ultimately the degree of fit between their learning process and a changing external world. The authors argue that in order to improve the chances of longer-term survival what is needed is a new level of organisation where the individual is capable of developing a representation of the external world that he or she can use to sense the appropriateness of local decisions. This reinterpretation of events allows individuals to step back and examine the broader consequences of their actions through the interpretation and anticipation of feedback from the environment. These approaches thus seek to develop practice-based heuristics which individuals can use to make sense of their lived experiences, as they learn to evolve in an increasingly complex world.
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Much of our understanding and management of ecological processes requires knowledge of the distribution and abundance of species. Reliable abundance or density estimates are essential for managing both threatened and invasive populations, yet are often challenging to obtain. Recent and emerging technological advances, particularly in unmanned aerial vehicles (UAVs), provide exciting opportunities to overcome these challenges in ecological surveillance. UAVs can provide automated, cost-effective surveillance and offer repeat surveys for pest incursions at an invasion front. They can capitalise on manoeuvrability and advanced imagery options to detect species that are cryptic due to behaviour, life-history or inaccessible habitat. UAVs may also cause less disturbance, in magnitude and duration, for sensitive fauna than other survey methods such as transect counting by humans or sniffer dogs. The surveillance approach depends upon the particular ecological context and the objective. For example, animal, plant and microbial target species differ in their movement, spread and observability. Lag-times may exist between a pest species presence at a site and its detectability, prompting a need for repeat surveys. Operationally, however, the frequency and coverage of UAV surveys may be limited by financial and other constraints, leading to errors in estimating species occurrence or density. We use simulation modelling to investigate how movement ecology should influence fine-scale decisions regarding ecological surveillance using UAVs. Movement and dispersal parameter choices allow contrasts between locally mobile but slow-dispersing populations, and species that are locally more static but invasive at the landscape scale. We find that low and slow UAV flights may offer the best monitoring strategy to predict local population densities in transects, but that the consequent reduction in overall area sampled may sacrifice the ability to reliably predict regional population density. Alternative flight plans may perform better, but this is also dependent on movement ecology and the magnitude of relative detection errors for different flight choices. Simulated investigations such as this will become increasingly useful to reveal how spatio-temporal extent and resolution of UAV monitoring should be adjusted to reduce observation errors and thus provide better population estimates, maximising the efficacy and efficiency of unmanned aerial surveys.
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Major infrastructure and construction (MIC) projects are those with significant traffic or environmental impact, of strategic and regional significance and high sensitivity. The decision making process of schemes of this type is becoming ever more complicated, especially with the increasing number of stakeholders involved and their growing tendency to defend their own varied interests. Failing to address and meet the concerns and expectations of stakeholders may result in project failures. To avoid this necessitates a systematic participatory approach to facilitate decision-making. Though numerous decision models have been established in previous studies (e.g. ELECTRE methods, the analytic hierarchy process and analytic network process) their applicability in the decision process during stakeholder participation in contemporary MIC projects is still uncertain. To resolve this, the decision rule approach is employed for modeling multi-stakeholder multi-objective project decisions. Through this, the result is obtained naturally according to the “rules” accepted by any stakeholder involved. In this sense, consensus is more likely to be achieved since the process is more convincing and the result is easier to be accepted by all concerned. Appropriate “rules”, comprehensive enough to address multiple objectives while straightforward enough to be understood by multiple stakeholders, are set for resolving conflict and facilitating consensus during the project decision process. The West Kowloon Cultural District (WKCD) project is used as a demonstration case and a focus group meeting is conducted in order to confirm the validity of the model established. The results indicate that the model is objective, reliable and practical enough to cope with real world problems. Finally, a suggested future research agenda is provided.
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The Distributed Network Protocol v3.0 (DNP3) is one of the most widely used protocols to control national infrastructure. The move from point-to-point serial connections to Ethernet-based network architectures, allowing for large and complex critical infrastructure networks. However, networks and con- figurations change, thus auditing tools are needed to aid in critical infrastructure network discovery. In this paper we present a series of intrusive techniques used for reconnaissance on DNP3 critical infrastructure. Our algorithms will discover DNP3 outstation slaves along with their DNP3 addresses, their corresponding master, and class object configurations. To validate our presented DNP3 reconnaissance algorithms and demonstrate it’s practicality, we present an implementation of a software tool using a DNP3 plug-in for Scapy. Our implementation validates the utility of our DNP3 reconnaissance technique. Our presented techniques will be useful for penetration testing, vulnerability assessments and DNP3 network discovery.
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In order to understand student engagement in higher education through the use of digital technologies, it is necessary to appreciate the broader use of differing technologies. Forty-eight first-year university students completed an online survey that queried patterns of digital activity across home, school and community contexts and that included rating scale items that measured learning style (i.e., active-reflective, sensing-intuitive, visual-verbal, sequential-global). Results suggest that students vary widely in digital activities and that such variation is related to differences in learning style. For example, active learners were more likely than reflective learners to engage in digital activities in the community and users of some specific application, as opposed to non-users, were more likely to be verbal than visual learners. Implications for instructional applications of digital technology in higher education are presented.
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Multimetric ecological condition assessment has become an important biodiversity management tool. This study was the first to examine the reliability of these ecological surrogates across variable environments, and the implications for surrogate efficacy. It was demonstrated that through strategic application and design of the multimetric ecological condition index, the effects of environmental gradients and disturbance regimes can be mitigated, and that ecological condition assessment may serve as a scientifically rigorous approach for conservation planning.
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There has been a recent spate of high profile infrastructure cost overruns in Australia and internationally. This is just the tip of a longer-term and more deeply-seated problem with initial budget estimating practice, well recognised in both academic research and industry reviews: the problem of uncertainty. A case study of the Sydney Opera House is used to identify and illustrate the key causal factors and system dynamics of cost overruns. It is conventionally the role of risk management to deal with such uncertainty, but the type and extent of the uncertainty involved in complex projects is shown to render established risk management techniques ineffective. This paper considers a radical advance on current budget estimating practice which involves a particular approach to statistical modelling complemented by explicit training in estimating practice. The statistical modelling approach combines the probability management techniques of Savage, which operate on actual distributions of values rather than flawed representations of distributions, and the data pooling technique of Skitmore, where the size of the reference set is optimised. Estimating training employs particular calibration development methods pioneered by Hubbard, which reduce the bias of experts caused by over-confidence and improve the consistency of subjective decision-making. A new framework for initial budget estimating practice is developed based on the combined statistical and training methods, with each technique being explained and discussed.
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A comprehensive study was conducted on potential systems of integrated building utilities and transport power solutions that can simultaneously contain rising electricity, hot water and personal transport costs for apartment residents. The research developed the Commuter Energy and Building Utilities System (CEBUS) and quantified the economic, social and environmental benefits of incorporating such a system in future apartment developments. A decision support tool was produced to assist the exploration of the CEBUS design variants. A set of implementation guidelines for CEBUS was also developed for the property development industry.
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Construction firms that employ collaborative procurement approaches develop operating routines through joint learning so as to improve infrastructure project performance. This paper reports a study based on a survey sample of 320 construction practitioners which were involved in collaborative infrastructure delivery in Australia. The study developed valid and reliable scales for measuring collaborative learning capability (CLC), and used the scales to evaluate the CLC of contractor and consultant firms within the sample. The evaluation suggests that whilst these firms explore knowledge from both internal and external sources, transform both explicit and tacit knowledge, and apply and internalise new knowledge, they can improve the extent to which these routines are applied to optimise project performance.