Dynamic Bayesian network inferencing for non-homogeneous complex systems

Dynamic Bayesian Networks (DBNs) provide a versatile platform for predicting and analysing the behaviour of complex systems. As such, they are well suited to the prediction of complex ecosystem population trajectories under anthropogenic disturbances such as the dredging of marine seagrass ecosystems. However, DBNs assume a homogeneous Markov chain whereas a key characteristics of complex ecosystems is the presence of feedback loops, path dependencies and regime changes whereby the behaviour of the system can vary based on past states. This paper develops a method based on the small world structure of complex systems networks to modularise a non-homogeneous DBN and enable the computation of posterior marginal probabilities given evidence in forwards inference. It also provides an approach for an approximate solution for backwards inference as convergence is not guaranteed for a path dependent system. When applied to the seagrass dredging problem, the incorporation of path dependency can implement conditional absorption and allows release from the zero state in line with environmental and ecological observations. As dredging has a marked global impact on seagrass and other marine ecosystems of high environmental and economic value, using such a complex systems model to develop practical ways to meet the needs of conservation and industry through enhancing resistance and/or recovery is of paramount importance.

WinBUGS code to run a network meta-analysis

WinBUGS code and data to reproduce our network meta-analysis from "Control strategies to prevent total hip replacement-related infections: a systematic review and mixed treatment comparison" published in BMJ Open.

Protection of a Static Frequency Converter fed traction network, a case study

Aurizon, Australia's largest rail freight operator, is introducing the Static Frequency Converter (SFC) technology into its electric railway network as part of the Bauhinia Electrification Project. The introduction of SFCs has significant implications on the protection systems of the 50kV traction network. The traditional distance protection calculation method does not work in this configuration because of the effect that the SFC in combination with the remote grid has on the apparent impedance, and was substantially reviewed. The standard overcurrent (OC) protection scheme is not suitable due to the minimum fault level being below the maximum load level and was revised to incorporate directionality and under-voltage inhibit. Delta protection was reviewed to improve sensitivity. A new protection function was introduced to prevent back-feeding faults in the transmission network through the grid connection. Protection inter-tripping was included to ensure selectivity between the SFC protection and the system downstream.

Residential tariff structure and battery energy storage impact in queensland LV network

Distributed renewable energy has become a significant contender in the supply of power in the distribution network in Queensland and throughout the world. As the cost of battery storage falls, distribution utilities turn their attention to the impacts of battery storage and other storage technologies on the low voltage (LV) network. With access to detailed residential energy usage data, Energex's available residential tariffs are investigated for their effectiveness in providing customers with financial incentives to move to Time-of Use based tariffs and to reward use of battery storage.

Forgery attacks on ++AE authenticated encryption mode

In this paper, we analyse a block cipher mode of operation submitted in 2014 to the cryptographic competition for authenticated encryption (CAESAR). This mode is designed by Recacha and called ++AE (plus-plus-ae). We propose a chosen plaintext forgery attack on ++AE that requires only a single chosen message query to allow an attacker to construct multiple forged messages. Our attack is deterministic and guaranteed to pass ++AE integrity check. We demonstrate the forgery attack using 128-bit AES as the underlying block cipher. Hence, ++AE is insecure as an authenticated encryption mode of operation.

A network forensics tool for precise data packet capture and replay in cyber-physical systems

Network data packet capture and replay capabilities are basic requirements for forensic analysis of faults and security-related anomalies, as well as for testing and development. Cyber-physical networks, in which data packets are used to monitor and control physical devices, must operate within strict timing constraints, in order to match the hardware devices' characteristics. Standard network monitoring tools are unsuitable for such systems because they cannot guarantee to capture all data packets, may introduce their own traffic into the network, and cannot reliably reproduce the original timing of data packets. Here we present a high-speed network forensics tool specifically designed for capturing and replaying data traffic in Supervisory Control and Data Acquisition systems. Unlike general-purpose "packet capture" tools it does not affect the observed network's data traffic and guarantees that the original packet ordering is preserved. Most importantly, it allows replay of network traffic precisely matching its original timing. The tool was implemented by developing novel user interface and back-end software for a special-purpose network interface card. Experimental results show a clear improvement in data capture and replay capabilities over standard network monitoring methods and general-purpose forensics solutions.

DNP3 network scanning and reconnaissance for critical infrastructure

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.

Collaboration on social network sites: Amateurs, professionals and celebrities

Amateurs are found in arts, sports, or entertainment, where they are linked with professional counterparts and inspired by celebrities. Despite the growing number of CSCW studies in amateur and professional domains, little is known about how technologies facilitate collaboration between these groups. Drawing from a 1.5-year field study in the domain of bodybuilding, this paper describes the collaboration between and within amateurs, professionals, and celebrities on social network sites. Social network sites help individuals to improve their performance in competitions, extend their support network, and gain recognition for their achievements. The findings show that amateurs benefit the most from online collaboration, whereas collaboration shifts from social network sites to offline settings as individuals develop further in their professional careers. This shift from online to offline settings constitutes a novel finding, which extends previous work on social network sites that has looked at groups of amateurs and professionals in isolation. As a contribution to practice, we highlight design factors that address this shift to offline settings and foster collaboration between and within groups.

Being online, living offline: The influence of social ties over the appropriation of social network sites

Research on social network sites has examined how people integrate offline and online life, but with a particular emphasis on their use by friendship groups. We extend earlier work by examining a case in which offline ties are non-existent, but online ties strong. Our case is a study of bodybuilders, who explore their passion with like-minded offline 'strangers' in tightly integrated online communities. We show that the integration of offline and online life supports passion-centric activities, such as bodybuilding.

"Hey world, take a look at me!": Appreciating the human body on social network sites

Social network sites (SNSs) such as Facebook have the potential to persuade people to adopt a lifestyle based on exercise and healthy nutrition. We report the findings of a qualitative study of an SNS for bodybuilders, looking at how bodybuilders present themselves online and how they orchestrate the SNS with their offline activities. Discussing the persuasive element of appreciation, we aim to extend previous work on persuasion in web 2.0 technologies.

The university and the knowledge network: A new educational model for 21st century learning and employability

The higher education sector is under ongoing pressure to demonstrate quality and efficacy of educational provision, including graduate outcomes. Preparing students as far as possible for the world of professional work has become one of the central tasks of contemporary universities. This challenging task continues to receive significant attention by policy makers and scholars, in the broader contexts of widespread labour market uncertainty and massification of the higher education system (Tomlinson, 2012). In contrast to the previous era of the university, in which ongoing professional employment was virtually guaranteed to university-qualified individuals, contemporary graduates must now be proactive and flexible. They must adapt to a job market that may not accept them immediately, and has continually shifting requirements (Clarke, 2008). The saying goes that rather than seeking security in employment, graduates must now “seek security in employability”. However, as I will argue in this chapter, the current curricular and pedagogic approaches universities adopt, and indeed the core structural characteristics of university-based education, militate against the development of the capabilities that graduates require now and into the future.

Formal network behaviour analysis using model checking

In this research we modelled computer network devices to ensure their communication behaviours meet various network standards. By modelling devices as finite-state machines and examining their properties in a range of configurations, we discovered a flaw in a common network protocol and produced a technique to improve organisations' network security against data theft.

Green Falcon IV: An Unmanned Aerial System and an integrated Wireless Sensor Network for remote sensing tasks

This report summarises the development of an Unmanned Aerial System and an integrated Wireless Sensor Network (WSN), suitable for the real world application in remote sensing tasks. Several aspects are discussed and analysed to provide improvements in flight duration, performance and mobility of the UAV, while ensuring the accuracy and range of data from the wireless sensor system.

Heritability of the network architecture of intrinsic brain functional connectivity

The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.

Heritability of brain network topology in 853 twins and siblings

Anatomical brain networks change throughout life and with diseases. Genetic analysis of these networks may help identify processes giving rise to heritable brain disorders, but we do not yet know which network measures are promising for genetic analyses. Many factors affect the downstream results, such as the tractography algorithm used to define structural connectivity. We tested nine different tractography algorithms and four normalization methods to compute brain networks for 853 young healthy adults (twins and their siblings). We fitted genetic structural equation models to all nine network measures, after a normalization step to increase network consistency across tractography algorithms. Probabilistic tractography algorithms with global optimization (such as Probtrackx and Hough) yielded higher heritability statistics than 'greedy' algorithms (such as FACT) which process small neighborhoods at each step. Some global network measures (probtrackx-derived GLOB and ST) showed significant genetic effects, making them attractive targets for genome-wide association studies.