Robust multidisciplinary design optimisation using CFD and advanced evolutionary algorithms

Computation Fluid Dynamics (CFD) has become an important tool in optimization and has seen successful in many real world applications. Most important among these is in the optimisation of aerodynamic surfaces which has become Multi-Objective (MO) and Multidisciplinary (MDO) in nature. Most of these have been carried out for a given set of input parameters such as free stream Mach number and angle of attack. One cannot ignore the fact that in aerospace engineering one frequently deals with situations where the design input parameters and flight/flow conditions have some amount of uncertainty attached to them. When the optimisation is carried out for fixed values of design variables and parameters however, one arrives at an optimised solution that results in good performance at design condition but poor drag or lift to drag ratio at slightly off-design conditions. The challenge is still to develop a robust design that accounts for uncertainty in the design in aerospace applications. In this paper this issue is taken up and an attempt is made to prevent the fluctuation of objective performance by using robust design technique or Uncertainty.

Ontology-based image annotation

With regard to the long-standing problem of the semantic gap between low-level image features and high-level human knowledge, the image retrieval community has recently shifted its emphasis from low-level features analysis to high-level image semantics extrac- tion. User studies reveal that users tend to seek information using high-level semantics. Therefore, image semantics extraction is of great importance to content-based image retrieval because it allows the users to freely express what images they want. Semantic content annotation is the basis for semantic content retrieval. The aim of image anno- tation is to automatically obtain keywords that can be used to represent the content of images. The major research challenges in image semantic annotation are: what is the basic unit of semantic representation? how can the semantic unit be linked to high-level image knowledge? how can the contextual information be stored and utilized for image annotation? In this thesis, the Semantic Web technology (i.e. ontology) is introduced to the image semantic annotation problem. Semantic Web, the next generation web, aims at mak- ing the content of whatever type of media not only understandable to humans but also to machines. Due to the large amounts of multimedia data prevalent on the Web, re- searchers and industries are beginning to pay more attention to the Multimedia Semantic Web. The Semantic Web technology provides a new opportunity for multimedia-based applications, but the research in this area is still in its infancy. Whether ontology can be used to improve image annotation and how to best use ontology in semantic repre- sentation and extraction is still a worth-while investigation. This thesis deals with the problem of image semantic annotation using ontology and machine learning techniques in four phases as below. 1) Salient object extraction. A salient object servers as the basic unit in image semantic extraction as it captures the common visual property of the objects. Image segmen- tation is often used as the �rst step for detecting salient objects, but most segmenta- tion algorithms often fail to generate meaningful regions due to over-segmentation and under-segmentation. We develop a new salient object detection algorithm by combining multiple homogeneity criteria in a region merging framework. 2) Ontology construction. Since real-world objects tend to exist in a context within their environment, contextual information has been increasingly used for improving object recognition. In the ontology construction phase, visual-contextual ontologies are built from a large set of fully segmented and annotated images. The ontologies are composed of several types of concepts (i.e. mid-level and high-level concepts), and domain contextual knowledge. The visual-contextual ontologies stand as a user-friendly interface between low-level features and high-level concepts. 3) Image objects annotation. In this phase, each object is labelled with a mid-level concept in ontologies. First, a set of candidate labels are obtained by training Support Vectors Machines with features extracted from salient objects. After that, contextual knowledge contained in ontologies is used to obtain the �nal labels by removing the ambiguity concepts. 4) Scene semantic annotation. The scene semantic extraction phase is to get the scene type by using both mid-level concepts and domain contextual knowledge in ontologies. Domain contextual knowledge is used to create scene con�guration that describes which objects co-exist with which scene type more frequently. The scene con�guration is represented in a probabilistic graph model, and probabilistic inference is employed to calculate the scene type given an annotated image. To evaluate the proposed methods, a series of experiments have been conducted in a large set of fully annotated outdoor scene images. These include a subset of the Corel database, a subset of the LabelMe dataset, the evaluation dataset of localized semantics in images, the spatial context evaluation dataset, and the segmented and annotated IAPR TC-12 benchmark.

Sapporo World Window : urban interaction through public and private screens

This paper introduces Sapporo World Window, a screen-based application that is currently under development for the new underway passage at the centre of Sapporo City. There are ten large public screens installed in the space, displaying user-generated videos about various aspects of the city and a real-time map that visualises users’ interaction with the city. The application aims to engage the general public by functioning as a unique ‘point of connection’ for socio-cultural and technological interactions, making the space a lively social place where people can have meaningful experiences of interacting with people and places of Sapporo through mobile phones (keitai) and the public screens in the space. This paper first outlines the contextual background and key concept for the application’s design. Then the paper discusses the user interaction processes, technical specifications, and interface design, followed by the conclusions and outlook.

Blast atlas: a virtual observatory for genomes

Following the completion of the draft Human Genome in 2001, genomic sequence data is becoming available at an accelerating rate, fueled by advances in sequencing and computational technology. Meanwhile, large collections of astronomical and geospatial data have allowed the creation of virtual observatories, accessible throughout the world and requiring only commodity hardware. Through a combination of advances in data management, data mining and visualization, this infrastructure enables the development of new scientific and educational applications as diverse as galaxy classification and real-time tracking of earthquakes and volcanic plumes. In the present paper, we describe steps taken along a similar path towards a virtual observatory for genomes – an immersive three-dimensional visual navigation and query system for comparative genomic data.

Sustainable urban and regional infrastructure development : technologies, applications and management

Sustainable Urban and Regional Infrastructure Development: Technologies, Applications and Management, bridges the gap in the current literature by addressing the overall problems present in society's major infrastructures, and the technologies that may be applied to overcome these problems. It focuses on ways in which energy intensive but 'invisible' (to the general public) facilities can become green or greener. The studies presented re lessons to be learnt from our neighbors and from our own backyard, and provide an excellent general overview of the issues facing us all.

Providing a law degree for the “real world” : perspective of an Australian law school

The Queensland University of Technology badges itself as “a university for the real world”. For the last decade the Law Faculty has aimed to provide its students with a ‘real world’ degree, that is, a practical law degree. This has seen skills such as research, advocacy and negotiation incorporated into the undergraduate degree under a University Teaching & Learning grant, a project that gained international recognition and praise. In 2007–2008 the Law Faculty undertook another curriculum review of its undergraduate law degree. As a result of the two year review, QUT’s undergraduate lawdegree has fewer core units, a focus on first year student transition, scaffolding of law graduate capabilities throughout the degree,work integrated learning and transition to the workplace. The revised degree commenced implementation in 2009. This paper focuses on the “real world” approach to the degree achieved through the first year programme, embedding and scaffolding law graduate capabilities through authentic and valid assessment and work integrated learning.

Who are the real “first offenders”?

Drink driving causes more fatal crashes than any other single factor on Australian roads, with a third of crashes having alcohol as a contributing factor. In recent years there has been a plateau in the numbers of drink drivers apprehended by RBT, and around 12% of the general population in self report surveys admit to drinking and driving. There is limited information about the first offender group, particularly the subgroup of these offenders who admit to prior drink driving, the offence therefore being the “first time caught”. This research focuses on the differences between those who report drink driving prior to apprehension for the offence and those who don’t. Methods: 201 first time drink driving offenders were interviewed at the time of their court appearance. Information was collected on socio-demographic variables, driving behaviour, method of apprehension, offence information, alcohol use and self reported previous drink driving. Results: 78% of respondents reported that they had driven over the legal alcohol limit in the 6 months prior to the offence. Analyses revealed that those offenders who had driven over the limit previously without being caught were more likely to be younger and have an issue with risky drinking. When all variables were taken into account in a multivariate model using logistic regression, only risky drinking emerged as significantly related to past drink driving. High risk drinkers were 4.8 times more likely to report having driven over the limit without being apprehended in the previous 6 months. Conclusion: The majority of first offenders are those who are “first time apprehended” rather than “first time drink drivers”. Having an understanding of the differences between these groups may alter the focus of educational or rehabilitation countermeasures. This research is part of a larger project aiming to target first time apprehended offenders for tailored intervention.

Preface : sustainable urban and regional infrastructure development : technologies, applications and management

The concept of ‘sustainability’ has been pushed to the forefront of policy-making and politics as the world wakes up to the impacts of climate change and the effects of the modern urban lifestyle. Climate change has emerged to be one of the biggest challenges faced by our planet today, threatening both built and natural systems with long term consequences which may be irreversible. While there is a vast literature in the market on sustainable cities and urban development, there is currently none that bring together the vital issues of urban and regional development, and the planning, management and implementation of sustainable infrastructure. Large scale infrastructure plays an important part in modern society by not only promoting economic growth, but also by acting as a key indicator for it. More importantly, it supplies municipal/local amenity and services: water, electricity, social and communication facilities, waste removal, transport of people and goods, as well as numerous other services. For the most part, infrastructure has been built by teams lead by engineers who are more concerned about functionality than the concept of sustainability. However, it has been widely stated that current practices and lifestyle cannot continue if we are to leave a healthy living planet to not only the next generation, but also to the generations beyond. Therefore, in order to be sustainable, there are drastic measures that need to be taken. Current single purpose and design infrastructures that are open looped are not sustainable; they are too resource intensive, consume too much energy and support the consumption of natural resources at a rate that will exhaust their supply. Because of this, it is vital that modern society, policy-makers, developers, engineers and planners become pioneers in introducing and incorporating sustainable features into urban and regional infrastructure.

A Taxonomy of image matching techniques for stereo vision

Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Applications of stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics, industrial automation and stereomicroscopy. A key issue in stereo vision is that of image matching, or identifying corresponding points in a stereo pair. The difference in the positions of corresponding points in image coordinates is termed the parallax or disparity. When the orientation of the two cameras is known, corresponding points may be projected back to find the location of the original object point in world coordinates. Matching techniques are typically categorised according to the nature of the matching primitives they use and the matching strategy they employ. This report provides a detailed taxonomy of image matching techniques, including area based, transform based, feature based, phase based, hybrid, relaxation based, dynamic programming and object space methods. A number of area based matching metrics as well as the rank and census transforms were implemented, in order to investigate their suitability for a real-time stereo sensor for mining automation applications. The requirements of this sensor were speed, robustness, and the ability to produce a dense depth map. The Sum of Absolute Differences matching metric was the least computationally expensive; however, this metric was the most sensitive to radiometric distortion. Metrics such as the Zero Mean Sum of Absolute Differences and Normalised Cross Correlation were the most robust to this type of distortion but introduced additional computational complexity. The rank and census transforms were found to be robust to radiometric distortion, in addition to having low computational complexity. They are therefore prime candidates for a matching algorithm for a stereo sensor for real-time mining applications. A number of issues came to light during this investigation which may merit further work. These include devising a means to evaluate and compare disparity results of different matching algorithms, and finding a method of assigning a level of confidence to a match. Another issue of interest is the possibility of statistically combining the results of different matching algorithms, in order to improve robustness.

Developments in texture-based vector field visualisation techniques

Vector field visualisation is one of the classic sub-fields of scientific data visualisation. The need for effective visualisation of flow data arises in many scientific domains ranging from medical sciences to aerodynamics. Though there has been much research on the topic, the question of how to communicate flow information effectively in real, practical situations is still largely an unsolved problem. This is particularly true for complex 3D flows. In this presentation we give a brief introduction and background to vector field visualisation and comment on the effectiveness of the most common solutions. We will then give some examples of current development on texture-based techniques, and given practical examples of their use in CFD research and hydrodynamic applications.

A criminological analysis : using real-time monitoring to gather data on online predators

The Internet presents a constantly evolving frontier for criminology and policing, especially in relation to online predators – paedophiles operating within the Internet for safer access to children, child pornography and networking opportunities with other online predators. The goals of this qualitative study are to undertake behavioural research – identify personality types and archetypes of online predators and compare and contrast them with behavioural profiles and other psychological research on offline paedophiles and sex offenders. It is also an endeavour to gather intelligence on the technological utilisation of online predators and conduct observational research on the social structures of online predator communities. These goals were achieved through the covert monitoring and logging of public activity within four Internet Relay Chat(rooms) (IRC) themed around child sexual abuse and which were located on the Undernet network. Five days of monitoring was conducted on these four chatrooms between Wednesday 1 to Sunday 5 April 2009; this raw data was collated and analysed. The analysis identified four personality types – the gentleman predator, the sadist, the businessman and the pretender – and eight archetypes consisting of the groomers, dealers, negotiators, roleplayers, networkers, chat requestors, posters and travellers. The characteristics and traits of these personality types and archetypes, which were extracted from the literature dealing with offline paedophiles and sex offenders, are detailed and contrasted against the online sexual predators identified within the chatrooms, revealing many similarities and interesting differences particularly with the businessman and pretender personality types. These personality types and archetypes were illustrated by selecting users who displayed the appropriate characteristics and tracking them through the four chatrooms, revealing intelligence data on the use of proxies servers – especially via the Tor software – and other security strategies such as Undernet’s host masking service. Name and age changes, which is used as a potential sexual grooming tactic was also revealed through the use of Analyst’s Notebook software and information on ISP information revealed the likelihood that many online predators were not using any safety mechanism and relying on the anonymity of the Internet. The activities of these online predators were analysed, especially in regards to child sexual grooming and the ‘posting’ of child pornography, which revealed a few of the methods in which online predators utilised new Internet technologies to sexually groom and abuse children – using technologies such as instant messengers, webcams and microphones – as well as store and disseminate illegal materials on image sharing websites and peer-to-peer software such as Gigatribe. Analysis of the social structures of the chatrooms was also carried out and the community functions and characteristics of each chatroom explored. The findings of this research have indicated several opportunities for further research. As a result of this research, recommendations are given on policy, prevention and response strategies with regards to online predators.

Review of Apple iPad news applications : new media service

The launch of the Apple iPad on January 2010 has seen considerable interest from the newspaper and publishing industry in developing content and business models for the tablet PC device that can address the limits of both the print and online news and information media products. It is early days in the iPad’s evolution, and we wait to see what competitor devices will emerge in the near future. It is apparent, however, that it has become a significant “niche” product, with considerable potential for mass market expansion over the next few years, possibly at the expense of netbook sales. The scope for the iPad and tablet PCs to become a “fourth screen” for users, alongside the TV, PC and mobile phone, is in early stages of evolution. The study used five criteria to assess iPad apps: • Content: timeliness; archive; personalisation; content depth; advertisements; the use of multimedia; and the extent to which the content was in sync with the provider brand. • Useability: degree of static content; ability to control multimedia; file size; page clutter; resolution; signposts; and customisation. • Interactivity: hyperlinks; ability to contribute content or provide feedback to news items; depth of multimedia; search function; ability to use plug-ins and linking; ability to highlight, rate and/or save items; functions that may facilitate a community of users. • Transactions capabilities: ecommerce functionality; purchase and download process; user privacy and transaction security. • Openness: degree of linking to outside sources; reader contribution processes; anonymity measures; and application code ownership.

Assessment of commercial network RTK user positioning performance over long inter-station distances

The paper provides an assessment of the performance of commercial Real Time Kinematic (RTK) systems over longer than recommended inter-station distances. The experiments were set up to test and analyse solutions from the i-MAX, MAX and VRS systems being operated with three triangle shaped network cells, each having an average inter-station distance of 69km, 118km and 166km. The performance characteristics appraised included initialization success rate, initialization time, RTK position accuracy and availability, ambiguity resolution risk and RTK integrity risk in order to provide a wider perspective of the performance of the testing systems. ----- ----- The results showed that the performances of all network RTK solutions assessed were affected by the increase in the inter-station distances to similar degrees. The MAX solution achieved the highest initialization success rate of 96.6% on average, albeit with a longer initialisation time. Two VRS approaches achieved lower initialization success rate of 80% over the large triangle. In terms of RTK positioning accuracy after successful initialisation, the results indicated a good agreement between the actual error growth in both horizontal and vertical components and the accuracy specified in the RMS and part per million (ppm) values by the manufacturers. ----- ----- Additionally, the VRS approaches performed better than the MAX and i-MAX when being tested under the standard triangle network with a mean inter-station distance of 69km. However as the inter-station distance increases, the network RTK software may fail to generate VRS correction and then may turn to operate in the nearest single-base RTK (or RAW) mode. The position uncertainty reached beyond 2 meters occasionally, showing that the RTK rover software was using an incorrect ambiguity fixed solution to estimate the rover position rather than automatically dropping back to using an ambiguity float solution. Results identified that the risk of incorrectly resolving ambiguities reached 18%, 20%, 13% and 25% for i-MAX, MAX, Leica VRS and Trimble VRS respectively when operating over the large triangle network. Additionally, the Coordinate Quality indicator values given by the Leica GX1230 GG rover receiver tended to be over-optimistic and not functioning well with the identification of incorrectly fixed integer ambiguity solutions. In summary, this independent assessment has identified some problems and failures that can occur in all of the systems tested, especially when being pushed beyond the recommended limits. While such failures are expected, they can offer useful insights into where users should be wary and how manufacturers might improve their products. The results also demonstrate that integrity monitoring of RTK solutions is indeed necessary for precision applications, thus deserving serious attention from researchers and system providers.

Sequential nonlinear manifold learning

The computation of compact and meaningful representations of high dimensional sensor data has recently been addressed through the development of Nonlinear Dimensional Reduction (NLDR) algorithms. The numerical implementation of spectral NLDR techniques typically leads to a symmetric eigenvalue problem that is solved by traditional batch eigensolution algorithms. The application of such algorithms in real-time systems necessitates the development of sequential algorithms that perform feature extraction online. This paper presents an efficient online NLDR scheme, Sequential-Isomap, based on incremental singular value decomposition (SVD) and the Isomap method. Example simulations demonstrate the validity and significant potential of this technique in real-time applications such as autonomous systems.

A statistical framework for natural feature representation

This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.