Audio signalling as a backup communication channel for multi-robot systems

This paper presents a low-bandwidth multi-robot communication system designed to serve as a backup communication channel in the event a robot suffers a network device fault. While much research has been performed in the area of distributing network communication across multiple robots within a system, individual robots are still susceptible to hardware failure. In the past, such robots would simply be removed from service, and their tasks re-allocated to other members. However, there are times when a faulty robot might be crucial to a mission, or be able to contribute in a less communication intensive area. By allowing robots to encode and decode messages into unique sequences of DTMF symbols, called words, our system is able to facilitate continued low-bandwidth communication between robots without access to network communication. Our results have shown that the system is capable of permitting robots to negotiate task initiation and termination, and is flexible enough to permit a pair of robots to perform a simple turn taking task.

Automated power semiconductor switching performance feature extraction from experimental double-pulse waveform data

Double-pulse tests are commonly used as a method for assessing the switching performance of power semiconductor switches in a clamped inductive switching application. Data generated from these tests are typically in the form of sampled waveform data captured using an oscilloscope. In cases where it is of interest to explore a multi-dimensional parameter space and corresponding result space it is necessary to reduce the data into key performance metrics via feature extraction. This paper presents techniques for the extraction of switching performance metrics from sampled double-pulse waveform data. The reported techniques are applied to experimental data from characterisation of a cascode gate drive circuit applied to power MOSFETs.

Multi-ciphersuite security of the Secure Shell (SSH) protocol

The Secure Shell (SSH) protocol is widely used to provide secure remote access to servers, making it among the most important security protocols on the Internet. We show that the signed-Diffie--Hellman SSH ciphersuites of the SSH protocol are secure: each is a secure authenticated and confidential channel establishment (ACCE) protocol, the same security definition now used to describe the security of Transport Layer Security (TLS) ciphersuites. While the ACCE definition suffices to describe the security of individual ciphersuites, it does not cover the case where parties use the same long-term key with many different ciphersuites: it is common in practice for the server to use the same signing key with both finite field and elliptic curve Diffie--Hellman, for example. While TLS is vulnerable to attack in this case, we show that SSH is secure even when the same signing key is used across multiple ciphersuites. We introduce a new generic multi-ciphersuite composition framework to achieve this result in a black-box way.

Short-data recursive HMM parameter estimation for rapid vision-based aircraft heading estimation

Rapid recursive estimation of hidden Markov Model (HMM) parameters is important in applications that place an emphasis on the early availability of reasonable estimates (e.g. for change detection) rather than the provision of longer-term asymptotic properties (such as convergence, convergence rate, and consistency). In the context of vision- based aircraft (image-plane) heading estimation, this paper suggests and evaluates the short-data estimation properties of 3 recursive HMM parameter estimation techniques (a recursive maximum likelihood estimator, an online EM HMM estimator, and a relative entropy based estimator). On both simulated and real data, our studies illustrate the feasibility of rapid recursive heading estimation, but also demonstrate the need for careful step-size design of HMM recursive estimation techniques when these techniques are intended for use in applications where short-data behaviour is paramount.

Comparison of the gate drive parameter space for driving power MOSFETs using conventional and cascode configurations

Conventional voltage driven gate drive circuits utilise a resistor to control the switching speed of power MOS-FETs. The gate resistance is adjusted to provide controlled rate of change of load current and voltage. The cascode gate drive configuration has been proposed as an alternative to the conventional resistor-fed gate drive circuit. While cascode drive is broadly understood in the literature the switching characteristics of this topology are not well documented. This paper explores, through both simulation and experimentation, the gate drive parameter space of the cascode gate drive configuration and provides a comparison to the switching characteristics of conventional gate drive.

H2AX phosphorylation screen of cells from radiosensitive cancer patients reveals a novel DNA double-strand break repair cellular phenotype

BACKGROUND: About 1-5% of cancer patients suffer from significant normal tissue reactions as a result of radiotherapy (RT). It is not possible at this time to predict how most patients' normal tissues will respond to RT. DNA repair dysfunction is implicated in sensitivity to RT particularly in genes that mediate the repair of DNA double-strand breaks (DSBs). Phosphorylation of histone H2AX (phosphorylated molecules are known as gammaH2AX) occurs rapidly in response to DNA DSBs, and, among its other roles, contributes to repair protein recruitment to these damaged sites. Mammalian cell lines have also been crucial in facilitating the successful cloning of many DNA DSB repair genes; yet, very few mutant cell lines exist for non-syndromic clinical radiosensitivity (RS). METHODS: Here, we survey DNA DSB induction and repair in whole cells from RS patients, as revealed by gammaH2AX foci assays, as potential predictive markers of clinical radiation response. RESULTS: With one exception, both DNA focus induction and repair in cell lines from RS patients were comparable with controls. Using gammaH2AX foci assays, we identified a RS cancer patient cell line with a novel ionising radiation-induced DNA DSB repair defect; these data were confirmed by an independent DNA DSB repair assay. CONCLUSION: gammaH2AX focus measurement has limited scope as a pre-RT predictive assay in lymphoblast cell lines from RT patients; however, the assay can successfully identify novel DNA DSB repair-defective patient cell lines, thus potentially facilitating the discovery of novel constitutional contributions to clinical RS.

Exploring parents' beliefs about their young child's physical activity and screen time behaviours

Drawing on the belief-based framework of the theory of planned behaviour, 20 adults living in Queensland, Australia participated in semi-structured interviews to elicit salient beliefs regarding their young child’s physical activity (PA) and screen time behaviours. Data were analysed separately for PA and screen time with a range of beliefs emerging that guided parents’ decisions for these important health behaviours. Underlying advantages (e.g., improve family interactions, improve child behaviour), disadvantages (e.g., mess and noise factor, increase in parental distress), barriers (e.g., lack of time, parental fatigue), and facilitators (e.g., access to parks, social support) to engaging their child in adequate PA and limited screen time emerged. Normative pressures were also identified as affecting parents’ decisions for their child in these contexts. Parents experience unique difficulties in engaging their child in adequate PA and limited screen time that interventions can draw on when designing and implementing programs aimed at modifying these important child health behaviours.

Multi-agent systems for modeling high penetration photovoltaic system impacts in distribution networks

This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

Robust clustering of multi-type relational data via a heterogeneous manifold ensemble

High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

Large scale multiuser digital mind mapping tool : a study in usability

Project work can involve multiple people from varying disciplines coming together to solve problems as a group. Large scale interactive displays are presenting new opportunities to support such interactions with interactive and semantically enabled cooperative work tools such as intelligent mind maps. In this paper, we present a novel digital, touch-enabled mind-mapping tool as a first step towards achieving such a vision. This first prototype allows an evaluation of the benefits of a digital environment for a task that would otherwise be performed on paper or flat interactive surfaces. Observations and surveys of 12 participants in 3 groups allowed the formulation of several recommendations for further research into: new methods for capturing text input on touch screens; inclusion of complex structures; multi-user environments and how users make the shift from single- user applications; and how best to navigate large screen real estate in a touch-enabled, co-present multi-user setting.

Non-monetised multi-objective decision making system for road management

This paper presents a performance-based optimisation approach for conducting trade-off analysis between safety (roads) and condition (bridges and roads). Safety was based on potential for improvement (PFI). Road condition was based on surface distresses and bridge condition was based on apparent age per subcomponent. The analysis uses a non-monetised optimisation that expanded upon classical Pareto optimality by observing performance across time. It was found that achievement of good results was conditioned by the availability of early age treatments and impacted by a frontier effect preventing the optimisation algorithm from realising of the long-term benefits of deploying actions when approaching the end of the analysis period. A disaggregated bridge condition index proved capable of improving levels of service in bridge subcomponents.

Multi-modal deformable medical image registration

Non-rigid image registration is an essential tool required for overcoming the inherent local anatomical variations that exist between images acquired from different individuals or atlases. Furthermore, certain applications require this type of registration to operate across images acquired from different imaging modalities. One popular local approach for estimating this registration is a block matching procedure utilising the mutual information criterion. However, previous block matching procedures generate a sparse deformation field containing displacement estimates at uniformly spaced locations. This neglects to make use of the evidence that block matching results are dependent on the amount of local information content. This paper presents a solution to this drawback by proposing the use of a Reversible Jump Markov Chain Monte Carlo statistical procedure to optimally select grid points of interest. Three different methods are then compared to propagate the estimated sparse deformation field to the entire image including a thin-plate spline warp, Gaussian convolution, and a hybrid fluid technique. Results show that non-rigid registration can be improved by using the proposed algorithm to optimally select grid points of interest.

A conceptual approach to track design changes within a multi-disciplinary BIM environment

Successful management of design changes is critical for the efficient delivery of construction projects. Building Information Modeling (BIM) is envisioned to play an important role in integrating design, construction and facility management processes through coordinated changes throughout the project life-cycle. BIM currently provides significant benefits in coordinating changes across different views in a single model, and identifying conflicts between different discipline-specific models. However, current BIM tools provide limited support in managing changes across several discipline-specific models. This paper describes an approach to represent, coordinate, and track changes within a collaborative multi-disciplinary BIM environment. This approach was informed by a detailed case study of a large, complex, fast-tracked BIM project where we investigated numerous design changes, analyzed change management processes, and evaluated existing BIM tools. Our approach characterises design changes in an ontology to represent changed component attributes, dependencies between components, and change impacts. It explores different types of dependencies amongst different design changes and describes how a graph based approach and dependency matrix could assist with automating the propagation and impact of changes in a BIM-based project delivery process.