Navigational safety in port waters: Techniques for modeling collision risk

Navigational collisions are one of the major safety concerns for many seaports. Continuing growth of shipping traffic in number and sizes is likely to result in increased number of traffic movements, which consequently could result higher risk of collisions in these restricted waters. This continually increasing safety concern warrants a comprehensive technique for modeling collision risk in port waters, particularly for modeling the probability of collision events and the associated consequences (i.e., injuries and fatalities). A number of techniques have been utilized for modeling the risk qualitatively, semi-quantitatively and quantitatively. These traditional techniques mostly rely on historical collision data, often in conjunction with expert judgments. However, these techniques are hampered by several shortcomings, such as randomness and rarity of collision occurrence leading to obtaining insufficient number of collision counts for a sound statistical analysis, insufficiency in explaining collision causation, and reactive approach to safety. A promising alternative approach that overcomes these shortcomings is the navigational traffic conflict technique (NTCT), which uses traffic conflicts as an alternative to the collisions for modeling the probability of collision events quantitatively. This article explores the existing techniques for modeling collision risk in port waters. In particular, it identifies the advantages and limitations of the traditional techniques and highlights the potentials of the NTCT in overcoming the limitations. In view of the principles of the NTCT, a structured method for managing collision risk is proposed. This risk management method allows safety analysts to diagnose safety deficiencies in a proactive manner, which consequently has great potential for managing collision risk in a fast, reliable and efficient manner.

Linear and nonlinear propagation of localised plasmon in metallic nanostructures

A major challenge in modern photonics and nano-optics is the diffraction limit of light which does not allow field localisation into regions with dimensions smaller than half the wavelength. Localisation of light into nanoscale regions (beyond its diffraction limit) has applications ranging from the design of optical sensors and measurement techniques with resolutions as high as a few nanometres, to the effective delivery of optical energy into targeted nanoscale regions such as quantum dots, nano-electronic and nano-optical devices. This field has become a major research direction over the last decade. The use of strongly localised surface plasmons in metallic nanostructures is one of the most promising approaches to overcome this problem. Therefore, the aim of this thesis is to investigate the linear and non-linear propagation of surface plasmons in metallic nanostructures. This thesis will focus on two main areas of plasmonic research –– plasmon nanofocusing and plasmon nanoguiding. Plasmon nanofocusing – The main aim of plasmon nanofocusing research is to focus plasmon energy into nanoscale regions using metallic nanostructures and at the same time achieve strong local field enhancement. Various structures for nanofocusing purposes have been proposed and analysed such as sharp metal wedges, tapered metal films on dielectric substrates, tapered metal rods, and dielectric V-grooves in metals. However, a number of important practical issues related to nanofocusing in these structures still remain unclear. Therefore, one of the main aims of this thesis is to address two of the most important of issues which are the coupling efficiency and heating effects of surface plasmons in metallic nanostructures. The method of analysis developed throughout this thesis is a general treatment that can be applied to a diversity of nanofocusing structures, with results shown here for the specific case of sharp metal wedges. Based on the geometrical optics approximation, it is demonstrated that the coupling efficiency from plasmons generated with a metal grating into the nanofocused symmetric or quasi-symmetric modes may vary between ~50% to ~100% depending on the structural parameters. Optimal conditions for nanofocusing with the view to minimise coupling and dissipative losses are also determined and discussed. It is shown that the temperature near the tip of a metal wedge heated by nanosecond plasmonic pulses can increase by several hundred degrees Celsius. This temperature increase is expected to lead to nonlinear effects, self-influence of the focused plasmon, and ultimately self-destruction of the metal tip. This thesis also investigates a different type of nanofocusing structure which consists of a tapered high-index dielectric layer resting on a metal surface. It is shown that the nanofocusing mechanism that occurs in this structure is somewhat different from other structures that have been considered thus far. For example, the surface plasmon experiences significant backreflection and mode transformation at a cut-off thickness. In addition, the reflected plasmon shows negative refraction properties that have not been observed in other nanofocusing structures considered to date. Plasmon nanoguiding – Guiding surface plasmons using metallic nanostructures is important for the development of highly integrated optical components and circuits which are expected to have a superior performance compared to their electronicbased counterparts. A number of different plasmonic waveguides have been considered over the last decade including the recently considered gap and trench plasmon waveguides. The gap and trench plasmon waveguides have proven to be difficult to fabricate. Therefore, this thesis will propose and analyse four different modified gap and trench plasmon waveguides that are expected to be easier to fabricate, and at the same time acquire improved propagation characteristics of the guided mode. In particular, it is demonstrated that the guided modes are significantly screened by the extended metal at the bottom of the structure. This is important for the design of highly integrated optics as it provides the opportunity to place two waveguides close together without significant cross-talk. This thesis also investigates the use of plasmonic nanowires to construct a Fabry-Pérot resonator/interferometer. It is shown that the resonance effect can be achieved with the appropriate resonator length and gap width. Typical quality factors of the Fabry- Pérot cavity are determined and explained in terms of radiative and dissipative losses. The possibility of using a nanowire resonator for the design of plasmonic filters with close to ~100% transmission is also demonstrated. It is expected that the results obtained in this thesis will play a vital role in the development of high resolution near field microscopy and spectroscopy, new measurement techniques and devices for single molecule detection, highly integrated optical devices, and nanobiotechnology devices for diagnostics of living cells.

3D mesenchymal stem/stromal cell osteogenesis and autocrine signalling

Mesenchymal stem/stromal cells (MSC) are rapidly becoming a leading candidate for use in tissue regeneration, with first generation of therapies being approved for use in orthopaedic repair applications. Capturing the full potential of MSC will likely require the development of novel in vitro culture techniques and devices. Herein we describe the development of a straightforward surface modification of an existing commercial product to enable the efficient study of three dimensional (3D) human bone marrow-derived MSC osteogenic differentiation. Hundreds of 3D microaggregates, of either 42 or 168 cells each, were cultured in osteogenic induction medium and their differentiation was compared with that occurring in traditional two dimensional (2D) monolayer cultures. Osteogenic gene expression and matrix composition was significantly enhanced in the 3D microaggregate cultures. Additionally, BMP-2 gene expression was significantly up-regulated in 3D cultures at day 3 and 7 by approximately 25- and 30-fold, respectively. The difference in BMP-2 gene expression between 2D and 3D cultures was negligible in the more mature day 14 osteogenic cultures. These data support the notion that BMP-2 autocrine signalling is up-regulated in 3D MSC cultures, enhancing osteogenic differentiation. This study provides both mechanistic insight into MSC differentiation, as well as a platform for the efficient generation of microtissue units for further investigation or use in tissue engineering applications.

A review of current statistical methodologies for in storage sampling and surveillance in the grains industry

Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, Integrated Pest Management (IPM), to determine grain quality and to satisfy importing nation’s biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in storage sampling strategies concentrating on detection of pest insects within a grain bulk, however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in storage sampling systems.

Visualisation of complex flows using texture-based techniques

Complex flow datasets are often difficult to represent in detail using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows (i.e., complex dynamics and time-dependent). In this paper, we review two popular texture-based techniques and their application to flow datasets sourced from real research projects. The texture-based techniques investigated were Line Integral Convolution (LIC), and Image-Based Flow Visualisation (IBFV). We evaluated these techniques and in this paper report on their visualisation effectiveness (when compared with traditional techniques), their ease of implementation, and their computational overhead.

A qualitative investigation of older pedestrian views of influences on their road crossing safety

With Australia’s population rapidly ageing, older pedestrian safety has begun to receive greater attention from road safety researchers. However, reliance on simulator studies and observational techniques has limited current understanding of why older pedestrians adopt particular crossing behaviours, and how they perceive crossing the road. The current study aimed to investigate the psychological factors that may contribute to older pedestrians’ crash risk by examining their perceptions of the issues they encounter on the road. Qualitative semi-structured interviews with 18 pedestrians aged 55 years and older were conducted, and the interview transcripts underwent thematic analysis. From this analysis, four key themes emerged. Firstly, the physical design of the road was perceived as posing a significant threat for older pedestrians, particularly sloped, semi-mountable kerbs and designated crossings. Secondly, declines in older pedestrians’ confidence in their ability to cross the road were evident through fewer reported risks being taken. Additionally, older pedestrians sensed an increased threat from other road users when crossing the road, particularly from drivers and cyclists. Finally, older pedestrians referred to the informal rules and strategies used to guide their road crossing. The results suggest that the road environment is perceived as increasingly dangerous and hazardous environment for older pedestrians. Implications regarding the physical road design in areas with an existing high proportion of elderly people are discussed.

Visualisation of complex flows using texture-based techniques

Detailed representations of complex flow datasets are often difficult to generate using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows. We review two popular texture based techniques and their application to flow datasets sourced from active research projects. The techniques investigated were Line integral convolution (LIC) [1], and Image based flow visualisation (IBFV) [18]. We evaluated these and report on their effectiveness from a visualisation perspective. We also report on their ease of implementation and computational overheads.

Do thermal agents affect range of movement and mechanical properties in soft tissues? A systematic review

OBJECTIVES: To examine the effect of thermal agents on the range of movement (ROM) and mechanical properties in soft tissue and to discuss their clinical relevance. DATA SOURCES: Electronic databases (Cochrane Central Register of Controlled Trials, MEDLINE, and EMBASE) were searched from their earliest available record up to May 2011 using Medical Subjects Headings and key words. We also undertook related articles searches and read reference lists of all incoming articles. STUDY SELECTION: Studies involving human participants describing the effects of thermal interventions on ROM and/or mechanical properties in soft tissue. Two reviewers independently screened studies against eligibility criteria. DATA EXTRACTION: Data were extracted independently by 2 review authors using a customized form. Methodologic quality was also assessed by 2 authors independently, using the Cochrane risk of bias tool. DATA SYNTHESIS: Thirty-six studies, comprising a total of 1301 healthy participants, satisfied the inclusion criteria. There was a high risk of bias across all studies. Meta-analyses were not undertaken because of clinical heterogeneity; however, effect sizes were calculated. There were conflicting data on the effect of cold on joint ROM, accessory joint movement, and passive stiffness. There was limited evidence to determine whether acute cold applications enhance the effects of stretching, and further evidence is required. There was evidence that heat increases ROM, and a combination of heat and stretching is more effective than stretching alone. CONCLUSIONS: Heat is an effective adjunct to developmental and therapeutic stretching techniques and should be the treatment of choice for enhancing ROM in a clinical or sporting setting. The effects of heat or ice on other important mechanical properties (eg, passive stiffness) remain equivocal and should be the focus of future study.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

Participatory content creation and collective intelligence in Rio de Janeiro's favelas [Virtual presentation]

This proposal combines ethnographic techniques and discourse studies to investigating a collective of people engaged with audiovisual productions who collaborate in Curta Favela’s workshops in Rio de Janeiro’s favelas. ‘Favela’ is often translated simply as ‘slum’ or ‘shantytown’, but these terms connote negative characteristics such as shortage, poverty, and deprivation referring to favelas which end up stigmatizing these low income suburbs. Curta Favela (Favela Shorts) is an independent project which all participants join to use photography and participatory audiovisual production as a tool for social change and raising consciousness. As cameras are not affordable for favelas dwellers, Curta Favela’s volunteers teach favela residents how they can use their mobile phones and compact cameras to take pictures and make movies, and afterwards, how they can edit the data using free editing video software programs and publish it on the Internet. To record audio, they use their mp3 or mobile phones. The main aim of this study is to shed light not only on how this project operates, but also to highlight how collective intelligence can be used as a way of fighting against the lack of basic resources.

Participatory content creation and collective intelligence in Rio de Janeiro's favelas

This proposal combines ethnographic techniques and discourse studies to investigate a collective of people engaged with audiovisual productions who collaborate in Curta Favela’s workshops in Rio de Janeiro’s favelas. ‘Favela’ is often translated simply as ‘slum’ or ‘shantytown’, but these terms connote negative characteristics such as shortage, poverty, and deprivation which end up stigmatizing these low income suburbs. Curta Favela (Favela Shorts) is an independent project in which all participants join to use photography and participatory audiovisual production as tools for social change and to raise consciousness. As cameras are not affordable for favela dwellers, Curta Favela’s volunteers teach favela residents how they can use their mobile phones and compact cameras to take pictures and make movies, and afterwards, how they can edit the data using free editing video software programs and publish it on the Internet. To record audio, they use their mp3 or mobile phones. The main aim of this study is to shed light not only on how this project operates, but also to highlight how collective intelligence can be used as a way of fighting against a lack of basic resources.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Integrated TEM, XRD and electron-microprobe investigation of mixed-layer chlorite smectite from the Point-Sal ophiolite, California

Five basalt samples from the Point Sal ophiolite, California, were examined using HRTEM and AEM in order to compare observations with interpretations of XRD patterns and microprobe analyses. XRD data from ethylene-glycol-saturated samples indicate the following percentages of chlorite in mixed-layer chlorite-smectite identified for each specimen: (i) L2036 almost-equal-to 50%, (ii) L2035 almost-equal-to 70 and 20%, (iii) 1A-13 almost-equal-to 70%, (iv) 1B-42 almost-equal-to 70%, and (v) 1B-55 = 100%. Detailed electron microprobe analyses show that 'chlorite' analyses with high Si, K, Na and Ca contents are the result of interlayering with smectite-like layers. The Fe/(Fe + Mg) ratios of mixed-layer phyllosilicates from Point Sal samples are influenced by the bulk rock composition, not by the percentage of chlorite nor the structure of the phyllosilicate. Measurements of lattice-fringe images indicate that both smectite and chlorite layers are present in the Point Sal samples in abundances similar to those predicted with XRD techniques and that regular alternation of chlorite and smectite occurs at the unit-cell scale. Both 10- and 14-angstrom layers were recorded with HRTEM and interpreted to be smectite and chlorite, respectively. Regular alternation of chlorite and smectite (24-angstrom periodicity) occurs in upper lava samples L2036 and 1A-13, and lower lava sample 1B-42 for as many as seven alternations per crystallite with local layer mistakes. Sample L2035 shows disordered alternation of chlorite and smectite, with juxtaposition of smectite-like layers, suggesting that randomly interlayered chlorite (< 0.5)-smectite exists. Images of lower lava sample 1B-55 show predominantly 14-angstrom layers. Units of 24 angstrom tend to cluster in what may otherwise appear to be disordered mixtures, suggesting the existence of a corrensite end-member having thermodynamic significance.

A Comprehensive Benchmarking Framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM

Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

Adaptive dynamic path re-planning RRT algorithms with game theory for UAVs

The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.