Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Model and prototype for querying multiple linked scientific datasets

Scientists need to transfer semantically similar queries across multiple heterogeneous linked datasets. These queries may require data from different locations and the results are not simple to combine due to differences between datasets. A query model was developed to make it simple to distribute queries across different datasets using RDF as the result format. The query model, based on the concept of publicly recognised namespaces for parts of each scientific dataset, was implemented with a configuration that includes a large number of current biological and chemical datasets. The configuration is flexible, providing the ability to transparently use both private and public datasets in any query. A prototype implementation of the model was used to resolve queries for the Bio2RDF website, including both Bio2RDF datasets and other datasets that do not follow the Bio2RDF URI conventions.

Ecological aspects of biosecurity surveillance design for the detection of multiple invasive animal species

Complex surveillance problems are common in biosecurity, such as prioritizing detection among multiple invasive species, specifying risk over a heterogeneous landscape, combining multiple sources of surveillance data, designing for specified power to detect, resource management, and collateral effects on the environment. Moreover, when designing for multiple target species, inherent biological differences among species result in different ecological models underpinning the individual surveillance systems for each. Species are likely to have different habitat requirements, different introduction mechanisms and locations, require different methods of detection, have different levels of detectability, and vary in rates of movement and spread. Often there is a further challenge of a lack of knowledge, literature, or data, for any number of the above problems. Even so, governments and industry need to proceed with surveillance programs which aim to detect incursions in order to meet environmental, social and political requirements. We present an approach taken to meet these challenges in one comprehensive and statistically powerful surveillance design for non-indigenous terrestrial vertebrates on Barrow Island, a high conservation nature reserve off the Western Australian coast. Here, the possibility of incursions is increased due to construction and expanding industry on the island. The design, which includes mammals, amphibians and reptiles, provides a complete surveillance program for most potential terrestrial vertebrate invaders. Individual surveillance systems were developed for various potential invaders, and then integrated into an overall surveillance system which meets the above challenges using a statistical model and expert elicitation. We discuss the ecological basis for the design, the flexibility of the surveillance scheme, how it meets the above challenges, design limitations, and how it can be updated as data are collected as a basis for adaptive management.

The mechanical heterogeneity of the hard callus influences local tissue strains during bone healing : a finite element study based on sheep experiments

During secondary fracture healing, various tissue types including new bone are formed. The local mechanical strains play an important role in tissue proliferation and differentiation. To further our mechanobiological understanding of fracture healing, a precise assessment of local strains is mandatory. Until now, static analyses using Finite Elements (FE) have assumed homogenous material properties. With the recent quantification of both the spatial tissue patterns (Vetter et al., 2010) and the development of elastic modulus of newly formed bone during healing (Manjubala et al., 2009), it is now possible to incorporate this heterogeneity. Therefore, the aim of this study is to investigate the effect of this heterogeneity on the strain patterns at six successive healing stages. The input data of the present work stemmed from a comprehensive cross-sectional study of sheep with a tibial osteotomy (Epari et al., 2006). In our FE model, each element containing bone was described by a bulk elastic modulus, which depended on both the local area fraction and the local elastic modulus of the bone material. The obtained strains were compared with the results of hypothetical FE models assuming homogeneous material properties. The differences in the spatial distributions of the strains between the heterogeneous and homogeneous FE models were interpreted using a current mechanobiological theory (Isakson et al., 2006). This interpretation showed that considering the heterogeneity of the hard callus is most important at the intermediate stages of healing, when cartilage transforms to bone via endochondral ossification.

Recent developments in photocatalytic degradation of pesticides and phenols in storm and wastewater effluent

The heterogeneous photocatalytic oxidation process offers a versatile promise in the detoxification and disinfection of wastewater containing hazardous organic compounds such as pesticides and phenolic compounds in storm and wastewater effluent. This process has gained wide attention due to its effectiveness in degrading and mineralizing the organic compounds into harmless and often useful components. To develop an efficient photocatalytic process, titanium dioxide has been actively studied in recent years due to its excellent performance as a photocatalyst under UV light irradiation. This paper aims at critically evaluating and highlighting the recent developments of the heterogeneous photocatalytic systems with a special focus on storm and wastewater treatment applications.

Forced landing technologies for unmanned aerial vehicles : towards safer operations

While using unmanned systems in combat is not new, what will be new in the foreseeable future is how such systems are used and integrated in the civilian space. The potential use of Unmanned Aerial Vehicles in civil and commercial applications is becoming a fact, and is receiving considerable attention by industry and the research community. The majority of Unmanned Aerial Vehicles performing civilian tasks are restricted to flying only in segregated space, and not within the National Airspace. The areas that UAVs are restricted to flying in are typically not above populated areas, which in turn are the areas most useful for civilian applications. The reasoning behind the current restrictions is mainly due to the fact that current UAV technologies are not able to demonstrate an Equivalent Level of Safety to manned aircraft, particularly in the case of an engine failure which would require an emergency or forced landing. This chapter will preset and guide the reader through a number of developments that would facilitate the integration of UAVs into the National Airspace. Algorithms for UAV Sense-and-Avoid and Force Landings are recognized as two major enabling technologies that will allow the integration of UAVs in the civilian airspace. The following sections will describe some of the techniques that are currently being tested at the Australian Research Centre for Aerospace Automation (ARCAA), which places emphasis on the detection of candidate landing sites using computer vision, the planning of the descent path trajectory for the UAV, and the decision making process behind the selection of the final landing site.

Influence of culture conditions on the molecular signature of mesenchymal stem cells

Cell based therapies require cells capable of self renewal and differentiation, and a prerequisite is the ability to prepare an effective dose of ex vivo expanded cells for autologous transplants. The in vivo identification of a source of physiologically relevant cell types suitable for cell therapies is therefore an integral part of tissue engineering. Bone marrow is the most easily accessible source of mesenchymal stem cells (MSCs), and harbours two distinct populations of adult stem cells; namely hematopoietic stem cells (HSCs) and bone mesenchymal stem cells (BMSCs). Unlike HSCs, there are yet no rigorous criteria for characterizing BMSCs. Changing understanding about the pluripotency of BMSCs in recent studies has expanded their potential application; however, the underlying molecular pathways which impart the features distinctive to BMSCs remain elusive. Furthermore, the sparse in vivo distribution of these cells imposes a clear limitation to their in vitro study. Also, when BMSCs are cultured in vitro there is a loss of the in vivo microenvironment which results in a progressive decline in proliferation potential and multipotentiality. This is further exacerbated with increased passage number, characterized by the onset of senescence related changes. Accordingly, establishing protocols for generating large numbers of BMSCs without affecting their differentiation potential is necessary. The principal aims of this thesis were to identify potential molecular factors for characterizing BMSCs from osteoarthritic patients, and also to attempt to establish culture protocols favourable for generating large number of BMSCs, while at the same time retaining their proliferation and differentiation potential. Previously published studies concerning clonal cells have demonstrated that BMSCs are heterogeneous populations of cells at various stages of growth. Some cells are higher in the hierarchy and represent the progenitors, while other cells occupy a lower position in the hierarchy and are therefore more committed to a particular lineage. This feature of BMSCs was made evident by the work of Mareddy et al., which involved generating clonal populations of BMSCs from bone marrow of osteoarthritic patients, by a single cell clonal culture method. Proliferation potential and differentiation capabilities were used to group cells into fast growing and slow growing clones. The study presented here is a continuation of the work of Mareddy et al. and employed immunological and array based techniques to identify the primary molecular factors involved in regulating phenotypic characteristics exhibited by contrasting clonal populations. The subtractive immunization (SI) was used to generate novel antibodies against favourably expressed proteins in the fast growing clonal cell population. The difference between the clonal populations at the transcriptional level was determined using a Stem Cell RT2 Profiler TM PCR Array which focuses on stem cell pathway gene expression. Monoclonal antibodies (mAb) generated by SI were able to effectively highlight differentially expressed antigenic determinants, as was evident by Western blot analysis and confocal microscopy. Co-immunoprecipitation, followed by mass spectroscopy analysis, identified a favourably expressed protein as the cytoskeletal protein vimentin. The stem cell gene array highlighted genes that were highly upregulated in the fast growing clonal cell population. Based on their functions these genes were grouped into growth factors, cell fate determination and maintenance of embryonic and neural stem cell renewal. Furthermore, on a closer analysis it was established that the cytoskeletal protein vimentin and nine out of ten genes identified by gene array were associated with chondrogenesis or cartilage repair, consistent with the potential role played by BMSCs in defect repair and maintaining tissue homeostasis, by modulating the gene expression pattern to compensate for degenerated cartilage in osteoarthritic tissues. The gene array also presented transcripts for embryonic lineage markers such as FOXA2 and Sox2, both of which were significantly over expressed in fast growing clonal populations. A recent groundbreaking study by Yamanaka et al imparted embryonic stem cell (ESCs) -like characteristic to somatic cells in a process termed nuclear reprogramming, by the ectopic expression of the genes Sox2, cMyc and Oct4. The expression of embryonic lineage markers in adult stem cells may be a mechanism by which the favourable behaviour of fast growing clonal cells is determined and suggests a possible active phenomenon of spontaneous reprogramming in fast growing clonal cells. The expression pattern of these critical molecular markers could be indicative of the competence of BMSCs. For this reason, the expression pattern of Sox2, Oct4 and cMyc, at various passages in heterogeneous BMSCs population and tissue derived cells (osteoblasts and chondrocytes), was investigated by a real-time PCR and immunoflourescence staining. A strong nuclear staining was observed for Sox2, Oct4 and cMyc, which gradually weakened accompanied with cytoplasmic translocation after several passage. The mRNA and protein expression of Sox2, Oct4 and cMyc peaked at the third passage for osteoblasts, chondrocytes and third passage for BMSCs, and declined with each subsequent passage, indicating towards a possible mechanism of spontaneous reprogramming. This study proposes that the progressive decline in proliferation potential and multipotentiality associated with increased passaging of BMSCs in vitro might be a consequence of loss of these propluripotency factors. We therefore hypothesise that the expression of these master genes is not an intrinsic cell function, but rather an outcome of interaction of the cells with their microenvironment; this was evident by the fact that when removed from their in vivo microenvironment, BMSCs undergo a rapid loss of stemness after only a few passages. One of the most interesting aspects of this study was the integration of factors in the culture conditions, which to some extent, mimicked the in vivo microenvironmental niche of the BMSCs. A number of studies have successfully established that the cellular niche is not an inert tissue component but is of prime importance. The total sum of stimuli from the microenvironment underpins the complex interplay of regulatory mechanisms which control multiple functions in stem cells most importantly stem cell renewal. Therefore, well characterised factors which affect BMSCs characteristics, such as fibronectin (FN) coating, and morphogens such as FGF2 and BMP4, were incorporated into the cell culture conditions. The experimental set up was designed to provide insight into the expression pattern of the stem cell related transcription factors Sox2, cMyc and Oct4, in BMSCs with respect to passaging and changes in culture conditions. Induction of these pluripotency markers in somatic cells by retroviral transfection has been shown to confer pluripotency and an ESCs like state. Our study demonstrated that all treatments could transiently induce the expression of Sox2, cMyc and Oct4, and favourably affect the proliferation potential of BMSCs. The combined effect of these treatments was able to induce and retain the endogenous nuclear expression of stem cell transcription factors in BMSCs over an extended number of in vitro passages. Our results therefore suggest that the transient induction and manipulation of endogenous expression of transcription factors critical for stemness can be achieved by modulating the culture conditions; the benefit of which is to circumvent the need for genetic manipulations. In summary, this study has explored the role of BMSCs in the diseased state of osteoarthritis, by employing transcriptional profiling along with SI. In particular this study pioneered the use of primary cells for generating novel antibodies by SI. We established that somatic cells and BMSCs have a basal level of expression of pluripotency markers. Furthermore, our study indicates that intrinsic signalling mechanisms of BMSCs are intimately linked with extrinsic cues from the microenvironment and that these signals appear to be critical for retaining the expression of genes to maintain cell stemness in long term in vitro culture. This project provides a basis for developing an “artificial niche” required for reversion of commitment and maintenance of BMSC in their uncommitted homeostatic state.

Path planning, guidance and control for a UAV forced landing

A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.

A hardware-based multi-disciplinary design optimization method for aeronautical applications

There are many applications in aeronautics where there exist strong couplings between disciplines. One practical example is within the context of Unmanned Aerial Vehicle(UAV) automation where there exists strong coupling between operation constraints, aerodynamics, vehicle dynamics, mission and path planning. UAV path planning can be done either online or offline. The current state of path planning optimisation online UAVs with high performance computation is not at the same level as its ground-based offline optimizer's counterpart, this is mainly due to the volume, power and weight limitations on the UAV; some small UAVs do not have the computational power needed for some optimisation and path planning task. In this paper, we describe an optimisation method which can be applied to Multi-disciplinary Design Optimisation problems and UAV path planning problems. Hardware-based design optimisation techniques are used. The power and physical limitations of UAV, which may not be a problem in PC-based solutions, can be approached by utilizing a Field Programmable Gate Array (FPGA) as an algorithm accelerator. The inevitable latency produced by the iterative process of an Evolutionary Algorithm (EA) is concealed by exploiting the parallelism component within the dataflow paradigm of the EA on an FPGA architecture. Results compare software PC-based solutions and the hardware-based solutions for benchmark mathematical problems as well as a simple real world engineering problem. Results also indicate the practicality of the method which can be used for more complex single and multi objective coupled problems in aeronautical applications.

Unbiased estimation of the half-life to price index convergence among U.S. cities

Estimates of the half-life to convergence of prices across a panel of cities are subject to bias from three potential sources: inappropriate cross-sectional aggregation of heterogeneous coefficients, presence of lagged dependent variables in a model with individual fixed effects, and time aggregation of commodity prices. This paper finds no evidence of heterogeneity bias in annual CPI data for 17 U.S. cities from 1918 to 2006, but correcting for the “Nickell bias” and time aggregation bias produces a half-life of 7.5 years, shorter than estimates from previous studies.

SOA efforts

As the Service-oriented architecture paradigm has become ever more popular, different standardization efforts have been proposed by various consortia to enable interaction among heterogeneous environments through this paradigm. This chapter will overview the most prevalent of these SOA Efforts. It will first show how technical services can be described, how they can interact with each other and be discovered by users. Next, the chapter will present different standards to facilitate service composition and to design service-oriented environments in light of a universal understanding of service orientation. The chapter will conclude with a summary and a discussion on the limitations of the reviewed standards along their ability to describe service properties. This paves the way to the next chapters where the USDL standard will be presented, which aim to lift such limitations.

New variational Bayesian approaches for statistical data mining : with applications to profiling and differentiating habitual consumption behaviour of customers in the wireless telecommunication industry

This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.

Using complex network metrics to predict the persistence of metapopulations with asymmetric connectivity patterns

Almost all metapopulation modelling assumes that connectivity between patches is only a function of distance, and is therefore symmetric. However, connectivity will not depend only on the distance between the patches, as some paths are easy to traverse, while others are difficult. When colonising organisms interact with the heterogeneous landscape between patches, connectivity patterns will invariably be asymmetric. There have been few attempts to theoretically assess the effects of asymmetric connectivity patterns on the dynamics of metapopulations. In this paper, we use the framework of complex networks to investigate whether metapopulation dynamics can be determined by directly analysing the asymmetric connectivity patterns that link the patches. Our analyses focus on “patch occupancy” metapopulation models, which only consider whether a patch is occupied or not. We propose three easily calculated network metrics: the “asymmetry” and “average path strength” of the connectivity pattern, and the “centrality” of each patch. Together, these metrics can be used to predict the length of time a metapopulation is expected to persist, and the relative contribution of each patch to a metapopulation’s viability. Our results clearly demonstrate the negative effect that asymmetry has on metapopulation persistence. Complex network analyses represent a useful new tool for understanding the dynamics of species existing in fragmented landscapes, particularly those existing in large metapopulations.