Using object and trajectory analysis to facilitate indexing and retrieval of video

This paper aims to show that by using low level feature extraction, motion and object identifying and tracking methods, features can be extracted and indexed for efficient and effective retrieval for video; such as an awards ceremony video. Video scene/shot analysis and key frame extraction are used as a foundation to identify objects in video and be able to find spatial relationships within the video. The compounding of low level features such as colour, texture and abstract object identification lead into higher level real object identification and tracking and scene detection. The main focus is on using a video style that is different to the heavily used sports and news genres. Using different video styles can open the door to creating methods that could encompass all video types instead of specialized methods for each specific style of video.

Critical infrastructure protection, modelling and management: an Australian commercial case study

This research extends upon the previous work of Pye and Warren (2005) and presents a refinement of the previously proposed critical infrastructure model to enhance further our understanding and apprecication of where the likely inter-play and existance of dependency relationships between infrastructures coexist.

These associations are presented as a number of linkages that exist within each sector of Australia'a critical infrastructure, which is then extended further to the modelling of dependency inter-relationships that exist between critical infrastructures itilising Petri Nets.  The recognition and identification of such reliance relationships between critical infrastructures is necessary to allow both infrastructure owners and the government to identify and effectively manage and maintain the security, stability and availability of their particular critical infrastructure against potential scenario driven effects.  These issues are reflected within a case study as modelled using the Petri Net approach to encapsulate the issues of reliance relationships by drawing upon an Australian commercial case study.

Object focused simultaneous estimation of optical flow and state dynamics

The framework of differential optical flow has been built upon to enhance the performance of motion estimation from optical flow. By coupling optical flow and object state parameters, an effective procedure for object tracking is implemented with the dasiaSimultaneous Estimation of Optical Flow and Object Statepsila (SEOS) technique. The SEOS method utilizes dynamic object parameter information when calculating optical flow for tracking a moving object within a video stream. Optical flow estimation for the SEOS method requires minimization of an error functional containing object physical parameter data. The convergence of an energy functional to a feasible or optimal solution set is not guaranteed. Convergence criteria is often assumed and not shown explicitly. Convergence of the SEOS method for both the Jacobi and Gauss-Seidel numerical resolution methods is evaluated.

Security analysis and modelling framework for critical infrastructure systems

The provision and delivery of many of the services that modern society enjoys are the result of ubiquitous critical infrastructure systems that permeate across many sectors of the Australian community. Moreover, the integration of technological enhancements and networking interconnections between critical infrastructure systems has heightened system interdependence, availability and resilience, including the efficient delivery of services to consumers within Australia's industrialised society. This research delivers a system security analysis and system modelling framework tool based on an associated conceptual methodology as the basis for assessing security and conceptually modelling a critical infrastructure system incident. The intent to identify potential system security issues and gain operational insights that will contribute to improving system resilience, contingency planning development applicable to disaster recovery and ameliorating incident management responses for Australian critical infrastructure system incidents.

Characteristics of the deformed and recrystallised grains obtained after hot plane strain compression of a model Fe-30wt%Ni alloy

The development of physically-based models of microstructural evolution during hot deformation of metallic materials requires knowledge of the grain/subgrain structure and crystallographic texture characteristics over a range of processing conditions. A Fe-30wt%Ni based alloy, retaining a stable austenitic structure at room temperature, was used for modelling the development of austenite microstructure during hot deformation of conventional carbon-manganese steels. A series of plane strain compression tests was carried out at a temperature of 950 °C and strain rates of 10 s-1 and 0.1 s-1 to several strain levels. Evolution of the grain/subgrain structure and crystallographic texture was characterised in detail using quantitative light microscopy and highresolution electron backscatter diffraction. Crystallographic texture characteristics were determined separately for the observed deformed and recrystallised grains. The subgrain geometry and dimensions together with the misorientation vectors across sub-boundaries were quantified in detail across large sample areas and the orientation dependence of these characteristics was determined. Formation mechanisms of the recrystallised grains were established in relation to the deformation microstructure.

Ecological niche modelling and DNA sequencing support a new, morphologically cryptic beetle species unveiled by DNA barcoding

Background: DNA sequencing techniques used to estimate biodiversity, such as DNA barcoding, may reveal cryptic species. However, disagreements between barcoding and morphological data have already led to controversy. Species delimitation should therefore not be based on mtDNA alone. Here, we explore the use of nDNA and bioclimatic modelling in a new species of aquatic beetle revealed by mtDNA sequence data.

Methodology/Principal Findings: The aquatic beetle fauna of Australia is characterised by high degrees of endemism, including local radiations such as the genus Antiporus. Antiporus femoralis was previously considered to exist in two disjunct, but morphologically indistinguishable populations in south-western and south-eastern Australia. We constructed a phylogeny of Antiporus and detected a deep split between these populations. Diagnostic characters from the highly variable nuclear protein encoding arginine kinase gene confirmed the presence of two isolated populations. We then used ecological niche modelling to examine the climatic niche characteristics of the two populations. All results support the status of the two populations as distinct species. We describe the south-western species as Antiporus occidentalis sp.n.

Conclusion/Significance: In addition to nDNA sequence data and extended use of mitochondrial sequences, ecological niche modelling has great potential for delineating morphologically cryptic species. © 2011 Hawlitschek et al.

Efficient Coxian duration modelling for activity recognition in smart environment with the hidden semi-Markov model

In this paper, we exploit the discrete Coxian distribution and propose a novel form of stochastic model, termed as the Coxian hidden semi-Makov model (Cox-HSMM), and apply it to the task of recognising activities of daily living (ADLs) in a smart house environment. The use of the Coxian has several advantages over traditional parameterization (e.g. multinomial or continuous distributions) including the low number of free parameters needed, its computational efficiency, and the existing of closed-form solution. To further enrich the model in real-world applications, we also address the problem of handling missing observation for the proposed Cox-HSMM. In the domain of ADLs, we emphasize the importance of the duration information and model it via the Cox-HSMM. Our experimental results have shown the superiority of the Cox-HSMM in all cases when compared with the standard HMM. Our results have further shown that outstanding recognition accuracy can be achieved with relatively low number of phases required in the Coxian, thus making the Cox-HSMM particularly suitable in recognizing ADLs whose movement trajectories are typically very long in nature.

Critical infrastructure systems : security analysis and modelling approach

A system security analysis and system modelling framework tool is proposed adopting an associated conceptual methodology as the basis for assessing security and conceptually modelling a critical infrastructure system incident. The intent is to identify potential system security issues and gain operational insights that will contribute to improving system resilience, contingency planning, disaster recovery and ameliorating incident management responses for critical infrastructure system incidents. The aforementioned system security analysis and modelling framework is applied to an adverse critical infrastructure system incident case study. This paper reports on the practical application of the framework to a case study of an actual critical infrastructure system failure and the resultant incident implications for the system and the wider regional communities.

Object matching using boundary descriptors

The problem of object recognition is of immense practical importance and potential, and the last decade has witnessed a number of breakthroughs in the state of the art. Most of the past object recognition work focuses on textured objects and local appearance descriptors extracted around salient points in an image. These methods fail in the matching of smooth, untextured objects for which salient point detection does not produce robust results. The recently proposed bag of boundaries (BoB) method is the first to directly address this problem. Since the texture of smooth objects is largely uninformative, BoB focuses on describing and matching objects based on their post-segmentation boundaries. Herein we address three major weaknesses of this work. The first of these is the uniform treatment of all boundary segments. Instead, we describe a method for detecting the locations and scales of salient boundary segments. Secondly, while the BoB method uses an image based elementary descriptor (HoGs + occupancy matrix), we propose a more compact descriptor based on the local profile of boundary normals’ directions. Lastly, we conduct a far more systematic evaluation, both of the bag of boundaries method and the method proposed here. Using a large public database, we demonstrate that our method exhibits greater robustness while at the same time achieving a major computational saving – object representation is extracted from an image in only 6% of the time needed to extract a bag of boundaries, and the storage requirement is similarly reduced to less than 8%.

Convergence of object focused simultaneous estimation of optical flow and state dynamics

The purpose of this study is to prove the convergence of the simultaneous estimation of the optical flow and object state (SEOS) method. The SEOS method utilizes dynamic object parameter information when calculating optical flow in tracking a moving object within a video stream. Optical flow estimation for the SEOS method requires the minimization of an error function containing the object's physical parameter data. When this function is discretized, the Euler-Lagrange equations form a system of linear equations. The system is arranged such that its property matrix is positive definite symmetric, proving the convergence of the Gauss-Seidel iterative methods. The system of linear equations produced by SEOS can alternatively be resolved by Jacobi iterative schemes. The positive definite symmetric property is not sufficient for Jacobi convergence. The convergence of SEOS for a block diagonal Jacobi is proved by analysing the Euclidean norm of the Jacobi matrix. In this paper, we also investigate the use of SEOS for tracking individual objects within a video sequence. The illustrations provided show the effectiveness of SEOS for localizing objects within a video sequence and generating optical flow results.

A review of computational fluid dynamics applications in pressure-driven membrane filtration

Ongoing advances in computational performance and numerics have led to computational fluid dynamics (CFD) becoming a ubiquitous modelling tool. However, CFD methods have only been adopted to simulate pressure-driven membrane filtration systems relatively recently. This paper reviews various approaches to describing the behaviour of these systems using CFD, beginning with the hydrodynamics of membrane channels, including discussion of laminar, turbulent, and transition flow regimes, with reference to the effects of osmotic pressure, concentration polarisation, and cake formation. The use of CFD in describing mass transfer through the membrane itself is then discussed, followed by some concluding comments on commercial membrane simulation packages and future research directions in membrane CFD. © 2013 Springer Science+Business Media Dordrecht.

Modelling of the stiffness evolution of truss core structures damaged by plastic buckling

A finite element study based on 1D beam element model is performed in order to investigate the mechanical behavior of an elasto-plastic beam loaded in axial compression over its buckling limit. The mode of loading is related to the damage of truss-cored beams in truss-cored laminates. The analysis takes into account the effects of geometry and material properties. The results of the FEM analysis are used for developing a simple mechanical model based on the basic Euler-Bernoulli beam theory and accounts for the beam compressibility. The model uses phenomenological functions containing parameters related to the basic material and geometrical properties. The presented model is developed in the form of closed solution which does not require complex numerical methods or extensive parametric studies. Predictions of the compressive stiffness degradation of truss-cored composites are made with the proposed model and compared with the results of FEM simulations. The error of the stiffness prediction with respect to the FEM results is within 10% over a 5 fold range of stiffness.

Greater association of peak neuromuscular performance with cortical bone geometry, bone mass and bone strength than bone density : a study in 417 older women

BACKGROUND: We evaluated which aspects of neuromuscular performance are associated with bone mass, density, strength and geometry. METHODS: 417 women aged 60-94years were examined. Countermovement jump, sit-to-stand test, grip strength, forearm and calf muscle cross-sectional area, areal bone mineral content and density (aBMC and aBMD) at the hip and lumbar spine via dual X-ray absorptiometry, and measures of volumetric vBMC and vBMD, bone geometry and section modulus at 4% and 66% of radius length and 4%, 38% and 66% of tibia length via peripheral quantitative computed tomography were performed. The first principal component of the neuromuscular variables was calculated to generate a summary neuromuscular variable. Percentage of total variance in bone parameters explained by the neuromuscular parameters was calculated. Step-wise regression was also performed. RESULTS: At all pQCT bone sites (radius, ulna, tibia, fibula), a greater percentage of total variance in measures of bone mass, cortical geometry and/or bone strength was explained by peak neuromuscular performance than for vBMD. Sit-to-stand performance did not relate strongly to bone parameters. No obvious differential in the explanatory power of neuromuscular performance was seen for DXA aBMC versus aBMD. In step-wise regression, bone mass, cortical morphology, and/or strength remained significant in relation to the first principal component of the neuromuscular variables. In no case was vBMD positively related to neuromuscular performance in the final step-wise regression models. CONCLUSION: Peak neuromuscular performance has a stronger relationship with leg and forearm bone mass and cortical geometry as well as proximal forearm section modulus than with vBMD.