Fractal and multifractal properties of a family of fractal networks

In this work, we study the fractal and multifractal properties of a family of fractal networks introduced by Gallos et al (2007 Proc. Nat. Acad. Sci. USA 104 7746). In this fractal network model, there is a parameter e which is between 0 and 1, and allows for tuning the level of fractality in the network. Here we examine the multifractal behavior of these networks, the dependence relationship of the fractal dimension and the multifractal parameters on parameter e. First, we find that the empirical fractal dimensions of these networks obtained by our program coincide with the theoretical formula given by Song et al (2006 Nature Phys. 2 275). Then from the shape of the τ(q) and D(q) curves, we find the existence of multifractality in these networks. Last, we find that there exists a linear relationship between the average information dimension 〈D(1)〉 and the parameter e.

A quantitative metric to identify critical elements within seafood supply networks

A theoretical basis is required for comparing key features and critical elements in wild fisheries and aquaculture supply chains under a changing climate. Here we develop a new quantitative metric that is analogous to indices used to analyse food-webs and identify key species. The Supply Chain Index (SCI) identifies critical elements as those elements with large throughput rates, as well as greater connectivity. The sum of the scores for a supply chain provides a single metric that roughly captures both the resilience and connectedness of a supply chain. Standardised scores can facilitate cross-comparisons both under current conditions as well as under a changing climate. Identification of key elements along the supply chain may assist in informing adaptation strategies to reduce anticipated future risks posed by climate change. The SCI also provides information on the relative stability of different supply chains based on whether there is a fairly even spread in the individual scores of the top few key elements, compared with a more critical dependence on a few key individual supply chain elements. We use as a case study the Australian southern rock lobster Jasus edwardsii fishery, which is challenged by a number of climate change drivers such as impacts on recruitment and growth due to changes in large-scale and local oceanographic features. The SCI identifies airports, processors and Chinese consumers as the key elements in the lobster supply chain that merit attention to enhance stability and potentially enable growth. We also apply the index to an additional four real-world Australian commercial fishery and two aquaculture industry supply chains to highlight the utility of a systematic method for describing supply chains. Overall, our simple methodological approach to empirically-based supply chain research provides an objective method for comparing the resilience of supply chains and highlighting components that may be critical.

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to ‘empty’ reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence.

Application of power electronics in improving power quality and supply efficiency of AC traction networks

Major advances in power electronics during recent years have prompted considerable interest within the traction community. The capability of new technologies to reduce the AC railway networks' effect on power quality and improve their supply efficiency is expected to significantly decrease the cost of electric rail supply systems. Of particular interest are Static Frequency Converter (SFC), Rail Power Conditioner (RPC), High Voltage Direct Current (HVDC) and Energy Storage Systems (ESS) solutions. Substantial impacts on future feasibility of railway electrification are anticipated. Aurizon, Australia's largest heavy haul railway operator, has recently commissioned the world's first 50Hz/50Hz SFC installation and is currently investigating SFC, RPC, HVDC and ESS solutions. This paper presents a summary of current and emerging technologies with a particular focus on the potential techno-economic benefits.

Covalently bonded networks through surface-confined polymerization

The prospect of synthesizing ordered, covalently bonded structures directly on a surface has recently attracted considerable attention due to its fundamental interest and for potential applications in electronics and photonics. This prospective article focuses on efforts to synthesize and characterize epitaxial one- and two-dimensional (1D and 2D, respectively) polymeric networks on single crystal surfaces. Recent studies, mostly performed using scanning tunneling microscopy (STM), demonstrate the ability to induce polymerization based on Ullmann coupling, thermal dehalogenation and dehydration reactions. The 2D polymer networks synthesized to date have exhibited structural limitations and have been shown to form only small domains on the surface. We discuss different approaches to control 1D and 2D polymerization, with particular emphasis on the surface phenomena that are critical to the formation of larger ordered domains.

Compositional agent-based models for electricity distribution networks

This thesis presents a novel approach to building large-scale agent-based models of networked physical systems using a compositional approach to provide extensibility and flexibility in building the models and simulations. A software framework (MODAM - MODular Agent-based Model) was implemented for this purpose, and validated through simulations. These simulations allow assessment of the impact of technological change on the electricity distribution network looking at the trajectories of electricity consumption at key locations over many years.

A thermometer for interdependence: Exploring patterns of interdependence using networks of affordances

Interdependence is a central concept in systems and organizations, yet our methods for measuring it are not well developed. Here, we report on a novel method for transforming digital trace data into networks of events that can be used to visualize and measure interdependence. The edges in the network represent sequential flow and the vertices represent actors, actions and artifacts. We refer to this representation as an affordance network. As with conventional approaches such as process mining, our method uses input from a stream of time-stamped occurrences, but the representation is simpler and more appropriate for exploration and theory building. As digital trace data becomes more widely available, this method may become more useful in information systems research and practice. Like a thermometer, it helps us measure a basic property of a system that would otherwise be difficult to see.

The impacts of policy change on collaborative governance networks

For many complex natural resources problems, planning and management efforts involve groups of organizations working collaboratively through networks (Agranoff, 2007; Booher & Innes, 2010). These networks sometimes involve formal roles and relationships, but often include informal elements (Edelenbos & Klijn, 2007). All of these roles and relationships undergo change in response to changes in personnel, priorities and policy. There has been considerable focus in the planning and public policy literature on describing and characterizing these networks (Mandell & Keast, 2008; Provan & Kenis, 2007). However, there has been far less research assessing how networks change and adjust in response to policy and political change. In the Australian state of Queensland, Natural Resource Management (NRM) organizations were created as lead organizations to address land and water management issues on a regional basis with Commonwealth funding and state support. In 2012, a change in state government signaled a dramatic change in policy that resulted in a significant reduction of state support and commitment. In response to this change, NRM organizations have had to adapt their networks and relationships. In this study, we examine the issues of network relationships, capacity and changing relationships over time using written surveys and focus groups with NRM CEOs, managers and planners (note: data collection events scheduled for March and April 2015). The research team will meet with each of these three groups separately, conduct an in-person survey followed by a facilitated focus group discussion. The NRM participant focus groups will also be subdivided by region, which correlates with capacity (inland/low capacity; coastal/high capacity). The findings focus on how changes in state government commitment have affected NRM networks and their relationships with state agencies. We also examine how these changes vary according to the level within the organization and the capacity of the organization. We hypothesize that: (1) NRM organizations have struggled to maintain capacity in the wake of state agency withdrawal of support; (2) NRM organizations with the lowest capacity have been most adversely affected, while some high capacity NRM organizations may have become more resilient as they have sought out other partners; (3) Network relationships at the highest levels of the organization have been affected the most by state policy change; (4) NRM relationships at the lowest levels of the organizations have changed the least, as formal relationships are replaced by informal networks and relationships.

Sharism and social awareness of the Chinese One Child Generation: Urban youth and digital networks

This thesis is a study of Chinese One Child Generation's digital and social sharing. It examines urban youth grassroots communities, including an urban farmers' community and volunteers in educational camps. These case studies explain the emergence of 'sharism' in reaction to the growing risks in China, such as food safety and environmental degradation emanating from China's rapid economic development, and growing urbanism, globalisation, and consumerism. The new forms of 'sharism' are linked to guanxi (social relations) and connected youth communities, which are made possible by increasing accessibility to digital and networked technologies.

Comparing China's city transportation and economic networks

The city system has been a prevailing research issue in the fields of urban geography and regional economics. Not only do the relationships between cities in the city system exist in the form of rankings, but also in a more general network form. Previous work has examined the spatial structure of the city system in terms of its separate industrial networks, such as in transportation and economic activity, but little has been done to compare different networks. To rectify this situation, this study analyzes and reveals the spatial structural features of China’s city system by comparing its transportation and economic urban networks, thus providing new avenues for research on China’s city network. The results indicate that these two networks relate with each other by sharing structural equivalence with a basic diamond structure and a layered intercity structure decreasing outwards from the national centers. A decoupling effect also exists between them as the transportation network contributes to a balanced regional development, while the economic network promotes agglomeration economies. The law of economic development and the government both play important roles in the articulation between these two networks, and the gap between them can be shortened by related policy reforms and the improvement of the transportation network.

Evaluating the effects of international exposure from networks ties and mimetic pressure on clustered SMEs in Brazil

Research on the internationalisation of small and medium-sized enterprises (SMEs) has received increasing attention in recent years due to the important role they play in today’s economic environment. Internationalisation prompting, or awareness, is an already recognised phase of the innovation-related stages model (I-model). This phase of awareness is closely related to the international exposure that a firm may experience during the occasion when it realises its competitors are already internationalising. Although the literature has discussed the various forms in which international exposure may happen, there has been limited attention given to the extent of its effect on the internationalisation of clustered SMEs that behave according to the I-Model. This study will assess the applicability of the I-Model in a dynamic, competitive and co-operative setting of an industrial cluster. It also evaluates the impact (if any) of international exposure derived from networks and the mimetic pressure that these firms may experience due to their embeddedness in an industrial cluster. Results from this study will indicate the effectiveness of the improved adapted model that will provide a richer insight for both academic researchers and policy makers.

Knowledge networks and Australian Football League coach development: People of influence

Australian Football League (AFL) generally recognised as the ‘national game’ in Australia has a well established program of coach development. However, research examining AFL coaches’ work and how they learn to perform that work has hitherto not been conducted. The effective preparation of coaches is of prime concern to the AFL and should be informed by an examination of how coaches within the code come to know how to do their coaching work. Therefore, the purpose of this AFL-funded research was to inform coach development programs for current and aspiring AFL coaches.

Using enterprise social networks as innovation platforms

Do enterprise social network platforms in an organization make the company more innovative? In theory, through communication, collaboration, and knowledge exchange, innovation ideas can easily be expressed, shared, and discussed with many partners in the organization. Yet, whether this guarantees innovation success remains to be seen. The authors studied how innovation ideas moved--or not--from an enterprise social network platform to regular innovation processes at a large Australian retailer. They found that the success of innovation ideas depends on how easily understandable the idea is on the platform, how long it has been discussed, and how powerful the social network participants are in the organization. These findings inform management strategies for the governance of enterprise social network use and the organizational innovation process.

Posters versus lurkers. Improving participation in enterprise social networks through management interventions

This thesis investigated the phenomenon of underutilised Enterprise social networks (ESNs). Guided by established theories, we identified key reasons that drive ESN members to either post (i.e., create content) or lurk (i.e., read others' content) and examined the influence of three management interventions - aim to boost participation - on lurkers' and posters' beliefs and participation. We test our model with data collected from 366 members in Google⁺ communities in a large Australian retail organization. We find that posters and lurkers are motivated and hindered by different factors. Moreover, management interventions do not – always – yield the hoped-for results among lurkers.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.