Design Optimisation of UAVs Systems achieved on a Framework Environment via Evolution and Game Theory

Over recent years, Unmanned Air Vehicles or UAVs have become a powerful tool for reconnaissance and surveillance tasks. These vehicles are now available in a broad size and capability range and are intended to fly in regions where the presence of onboard human pilots is either too risky or unnecessary. This paper describes the formulation and application of a design framework that supports the complex task of multidisciplinary design optimisation of UAVs systems via evolutionary computation. The framework includes a Graphical User Interface (GUI), a robust Evolutionary Algorithm optimiser named HAPEA, several design modules, mesh generators and post-processing capabilities in an integrated platform. These population –based algorithms such as EAs are good for cases problems where the search space can be multi-modal, non-convex or discontinuous, with multiple local minima and with noise, and also problems where we look for multiple solutions via Game Theory, namely a Nash equilibrium point or a Pareto set of non-dominated solutions. The application of the methodology is illustrated on conceptual and detailed multi-criteria and multidisciplinary shape design problems. Results indicate the practicality and robustness of the framework to find optimal shapes and trade—offs between the disciplinary analyses and to produce a set of non dominated solutions of an optimal Pareto front to the designer.

Systems-based accident analysis in the led outdoor activity domain : application and evaluation of a risk management framework

Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussen's risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management framework's predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain.

Minimising transport disadvantage to support knowledge city formation : applying the capability approach to select indicators

Purpose–The aims of this paper are to demonstrate the application of Sen’s theory of well-being, the capability approach; to conceptualise the state of transportation disadvantage; and to underpin a theoretical sounds indicator selection process. Design/methodology/approach–This paper reviews and examines various measurement approaches of transportation disadvantage in order to select indicators and develop an innovative framework of urban transportation disadvantage. Originality/value–The paper provides further understanding of the state of transportation disadvantage from the capability approach perspective. In addition, building from this understanding, a validated and systematic framework is developed to select relevant indicators. Practical implications –The multi-indicator approach has a high tendency to double count for transportation disadvantage, increase the number of TDA population and only accounts each indicator for its individual effects. Instead, indicators that are identified based on a transportation disadvantage scenario will yield more accurate results. Keywords – transport disadvantage, the capability approach, accessibility, measuring urban transportation disadvantage, indicators selection Paper type – Academic Research Paper

Sustainable urban development : formulation of indicator-based residential sustainability assessment framework for local level

Purpose–The purpose of this paper is to formulate a conceptual framework for urban sustainability indicators selection. This framework will be used to develop an indicator-based evaluation method for assessing the sustainability levels of residential neighbourhood developments in Malaysia. Design/methodology/approach–We provide a brief overview of existing evaluation frameworks for sustainable development assessment. We then develop a conceptual Sustainable Residential Neighbourhood Assessment (SNA) framework utilising a four-pillar sustainability framework (environmental, social, economic and institutional) and a combination of domain-based and goal-based general frameworks. This merger offers the advantages of both individual frameworks, while also overcoming some of their weaknesses when used to develop the urban sustainability evaluation method for assessing residential neighbourhoods. Originality/value–This approach puts in evidence that many of the existing frameworks for evaluating urban sustainability do not extend their frameworks to include assessing housing sustainability at a local level. Practical implications–It is expected that the use of the indicator-based Sustainable Neighbourhood Assessment framework will present a potential mechanism for planners and developers to evaluate and monitor the sustainability performance of residential neighbourhood developments.

Towards a unified method for the knowledge based urban development framework

Purpose–The growing debate in the literature indicates that the initiative to implement Knowledge Based Urban Development (KBUD) approaches in urban development process is neither simple nor quick. Many research efforts has therefore, been put forward to the development of appropriate KBUD framework and KBUD practical approaches. But this has lead to a fragmented and incoherent methodological approach. This paper outlines and compares a few most popular KBUD frameworks selected from the literature. It aims to identify some key and common features in the effort to achieve a unified method of KBUD framework. Design/methodology/approach–This paper reviews, examines and identifies various popular KBUD frameworks discussed in the literature from urban planners’ viewpoint. It employs a content analysis technique i.e. a research tool used to determine the presence of certain words or concepts within texts or sets of texts. Originality/value–The paper reports on the key and common features of a few selected most popular KBUD frameworks. The synthesis of the results is based from a perspective of urban planners. The findings which encompass a new KBUD framework incorporating the key and common features will be valuable in setting a platform to achieve a unified method of KBUD. Practical implications –The discussion and results presented in this paper should be significant to researchers and practitioners and to any cities and countries that are aiming for KBUD. Keywords – Knowledge based urban development, Knowledge based urban development framework, Urban development and knowledge economy

Developing a knowledge-based urban development analysis framework : the case of multimedia super corridor, Malaysia

Purpose: In the global knowledge economy, investment in knowledge-intensive industries and information and communication technology (ICT) infrastructures are seen as significant factors in improving the overall socio-economic fabric of cities. Consequently knowledge-based urban development (KBUD) has become a new paradigm in urban planning and development, for increasing the welfare and competitiveness of cities and regions. The paper discusses the critical connections between KBUD strategies and knowledge-intensive industries and ICT infrastructures. In particular, it investigates the application of the knowledge-based urban development concept by discussing one of South East Asia’s large scale manifestations of KBUD; Malaysia’s Multimedia Super Corridor. ----- ----- Design/methodology/approach: The paper provides a review of the KBUD concept and develops a knowledge-based urban development assessment framework to provide a clearer understanding of development and evolution of KBUD manifestations. Subsequently the paper investigates the implementation of the KBUD concept within the Malaysian context, and particularly the Multimedia Super Corridor (MSC). ----- ----- Originality/value: The paper, with its KBUD assessment framework, scrutinises Malaysia’s experince; providing an overview of the MSC project and discussion of the case findings. The development and evolution of the MSC is viewed with regard to KBUD policy implementation, infrastructural implications, and the agencies involved in the development and management of the MSC. ----- ----- Practical implications: The emergence of the knowledge economy, together with the issues of globalisation and rapid urbanisation, have created an urgent need for urban planners to explore new ways of strategising planning and development that encompasses the needs and requirements of the knowledge economy and society. In light of the literature and MSC case findings, the paper provides generic recommendations, on the orchestration of knowledge-based urban development, for other cities and regions seeking to transform to the knowledge economy.

Loculus : an ontology-based information management framework for the motion picture industry

"How do you film a punch?" This question can be posed by actors, make-up artists, directors and cameramen. Though they can all ask the same question, they are not all seeking the same answer. Within a given domain, based on the roles they play, agents of the domain have different perspectives and they want the answers to their question from their perspective. In this example, an actor wants to know how to act when filming a scene involving a punch. A make-up artist is interested in how to do the make-up of the actor to show bruises that may result from the punch. Likewise, a director wants to know how to direct such a scene and a cameraman is seeking guidance on how best to film such a scene. This role-based difference in perspective is the underpinning of the Loculus framework for information management for the Motion Picture Industry. The Loculus framework exploits the perspective of agent for information extraction and classification within a given domain. The framework uses the positioning of the agent’s role within the domain ontology and its relatedness to other concepts in the ontology to determine the perspective of the agent. Domain ontology had to be developed for the motion picture industry as the domain lacked one. A rule-based relatedness score was developed to calculate the relative relatedness of concepts with the ontology, which were then used in the Loculus system for information exploitation and classification. The evaluation undertaken to date have yielded promising results and have indicated that exploiting perspective can lead to novel methods of information extraction and classifications.

Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

Approximate Membership Localization within a Web-Based Join Framework

In this paper, we propose a search-based approach to join two tables in the absence of clean join attributes. Non-structured documents from the web are used to express the correlations between a given query and a reference list. To implement this approach, a major challenge we meet is how to efficiently determine the number of times and the locations of each clean reference from the reference list that is approximately mentioned in the retrieved documents. We formalize the Approximate Membership Localization (AML) problem and propose an efficient partial pruning algorithm to solve it. A study using real-word data sets demonstrates the effectiveness of our search-based approach, and the efficiency of our AML algorithm.

Development of the rural statistical sustainability framework tool

It is important to promote a sustainable development approach to ensure that economic, environmental and social developments are maintained in balance. Sustainable development and its implications are not just a global concern, it also affects Australia. In particular, rural Australian communities are facing various economic, environmental and social challenges. Thus, the need for sustainable development in rural regions is becoming increasingly important. To promote sustainable development, proper frameworks along with the associated tools optimised for the specific regions, need to be developed. This will ensure that the decisions made for sustainable development are evidence based, instead of subjective opinions. To address these issues, Queensland University of Technology (QUT), through an Australian Research Council (ARC) linkage grant, has initiated research into the development of a Rural Statistical Sustainability Framework (RSSF) to aid sustainable decision making in rural Queensland. This particular branch of the research developed a decision support tool that will become the integrating component of the RSSF. This tool is developed on the web-based platform to allow easy dissemination, quick maintenance and to minimise compatibility issues. The tool is developed based on MapGuide Open Source and it follows the three-tier architecture: Client tier, Web tier and the Server tier. The developed tool is interactive and behaves similar to a familiar desktop-based application. It has the capability to handle and display vector-based spatial data and can give further visual outputs using charts and tables. The data used in this tool is obtained from the QUT research team. Overall the tool implements four tasks to help in the decision-making process. These are the Locality Classification, Trend Display, Impact Assessment and Data Entry and Update. The developed tool utilises open source and freely available software and accounts for easy extensibility and long-term sustainability.

Feature-domain super-resolution framework for gabor-based face and iris recognition

The low resolution of images has been one of the major limitations in recognising humans from a distance using their biometric traits, such as face and iris. Superresolution has been employed to improve the resolution and the recognition performance simultaneously, however the majority of techniques employed operate in the pixel domain, such that the biometric feature vectors are extracted from a super-resolved input image. Feature-domain superresolution has been proposed for face and iris, and is shown to further improve recognition performance by capitalising on direct super-resolving the features which are used for recognition. However, current feature-domain superresolution approaches are limited to simple linear features such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which are not the most discriminant features for biometrics. Gabor-based features have been shown to be one of the most discriminant features for biometrics including face and iris. This paper proposes a framework to conduct super-resolution in the non-linear Gabor feature domain to further improve the recognition performance of biometric systems. Experiments have confirmed the validity of the proposed approach, demonstrating superior performance to existing linear approaches for both face and iris biometrics.

The maturity model concept as framework for assessing the capability of higher education institutions to address student engagement, success and retention : new horizon or false dawn?

While the engagement, success and retention of first year students are ongoing issues in higher education, they are currently of considerable and increasing importance as the pressures on teaching and learning from the new standards framework and performance funding intensifies. This Nuts & Bolts presentation introduces the concept of a maturity model and its application to the assessment of the capability of higher education institutions to address student engagement, success and retention. Participants will be provided with (a) a concise description of the concept and features of a maturity model; and (b) the opportunity to explore the potential application of maturity models (i) to the management of student engagement and retention programs and strategies within an institution and (ii) to the improvement of these features by benchmarking across the sector.

Development of a data mining-based analysis framework for multi-attribute construction project information

Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.

A capability framework visualisation for multiple heterogeneous UAVs : from a mission commander's perspective

There is an increased interested in Uninhabited Aerial Vehicle (UAV) operations and research into advanced methods for commanding and controlling multiple heterogeneous UAVs. Research into areas of supervisory control has rapidly increased. Past research has investigated various approaches of autonomous control and operator limitation to improve mission commanders' Situation Awareness (SA) and cognitive workload. The aim of this paper is to address this challenge through a visualisation framework of UAV information constructed from Information Abstraction (IA). This paper presents the concept and process of IA, and the visualisation framework (constructed using IA), the concept associated with the Level Of Detail (LOD) indexing method, the visualisation of an example of the framework. Experiments will test the hypothesis that, the operator will be able to achieve increased SA and reduced cognitive load with the proposed framework.