Practical application of pseudospectral optimization to robot path planning

To obtain minimum time or minimum energy trajectories for robots it is necessary to employ planning methods which adequately consider the platform’s dynamic properties. A variety of sampling, graph-based or local receding-horizon optimisation methods have previously been proposed. These typically use simplified kino-dynamic models to avoid the significant computational burden of solving this problem in a high dimensional state-space. In this paper we investigate solutions from the class of pseudospectral optimisation methods which have grown in favour amongst the optimal control community in recent years. These methods have high computational efficiency and rapid convergence properties. We present a practical application of such an approach to the robot path planning problem to provide a trajectory considering the robot’s dynamic properties. We extend the existing literature by augmenting the path constraints with sensed obstacles rather than predefined analytical functions to enable real world application.

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.

Franchise nations : theorising diaspora from outside In(dia)

Research on diaspora has long been dominated by approaches that centre on displacement, relocation, mixed identities, cultural hybridity, loss, yearning and disaffection. In this paper, I outline a fresh conceptual framework, franchise nation, which approaches the study of diaspora from the perspective of the state. What this framework allows is the study of the processes that states employ to woo, nurture and engage their diasporas so as to extend their sovereignty extra-territorially, ie. statecraft. The franchise nation concept draws on the notion of cultural expediency and complements two approaches that dominate the study of statecraft today: soft power and nation branding. However, the point of this is not, to borrow Gayatri Spivak’s words, to be either pro or anti-sovereign but rather to stay awake to how sovereignty is “invoked, extended, deterritorialised, aggregated, [and] abrogated” (2007). Far from suggesting the imminent arrival of a post-national period, the intention with the franchise nation concept is to explicate and better understand the complexities that inhabit the terrain between diaspora, home and host nation that allow and accompany the exercise of sovereignty from afar.

Attribute exclusion strategies in airline choice : accounting for exogenous information on decision maker processing strategies in models of discrete choice

We examine the impact of individual-specific information processing strategies (IPSs) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of discrete choice. Current practice assumes that individuals employ a homogenous IPS with regards to how they process attributes of stated choice (SC) experiments. We show how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute may be used in the estimation process, and how such information provides outputs that are IPS segment specific. We contend that accounting the inclusion/exclusion of attributes will result in behaviourally richer population parameter estimates.

The role of legislative, executive and judicial mechanisms in ensuring a fair and effective asylum process

A good faith reading of core international protection obligations requires that states employ appropriate legislative, administrative and judicial mechanisms to ensure the enjoyment of a fair and effective asylum process. Restrictive asylum policies instead seek to ‘denationalize’ the asylum process by eroding access to national statutory, judicial and executive safeguards that ensure a full and fair hearing of an asylum claim. From a broader perspective, the argument in this thesis recognizes hat international human rights depend on domestic institutions for their effective implementation, and that a rights-based international legal order requires that power is limited, whether that power is expressed as an instance of the sovereign right of states in international law or as the authority of governments under domestic constitutions.

Firearm suicide in Queensland

The purpose of this article is to examine firearm suicide in Queensland. In 2006, statistical data were gathered from all closed paper coronial files for the 12-month period of December 2003—December 2004. Of the 567 people who committed suicide in Queensland during this period, 48 (8.5%) used firearms. The following results emerge from this data: first, gun suicides are continuing to decrease in Queensland, most likely as a function of ongoing gun controls, a decrease accompanied by a lesser increase in other methods of suicide, thereby providing little support for substitution theory; second, men continue to be more likely to shoot themselves, particularly elderly men; third, firearms are more likely to be used in rural settings, and by those with no known history of mental illness or previous suicide attempts. Finally, in spite of otherwise very high suicide rates, Aborigines rarely employ firearms, using instead the culturally significant method of hanging.

Review of refugee mental health interventions following resettlement : best practices and recommendations

There are increasing numbers of refugees worldwide, with approximately 16 million refugees in 2007 and over 2.5 million refugees resettled in the United States since the start of its humanitarian program. Psychologists and other health professionals who deliver mental health services for individuals from refugee backgrounds need to have confidence that the therapeutic interventions they employ are appropriate and effective for the clients with whom they work. The current review briefly surveys refugee research, examines empirical evaluations of therapeutic interventions in resettlement contexts, and provides recommendations for best practices and future directions in resettlement countries. The resettlement interventions found to be most effective typically target culturally homogeneous client samples and demonstrate moderate to large outcome effects on aspects of traumatic stress and anxiety reduction. Further evaluations of the array of psychotherapeutic, psychosocial, pharmacological, and other therapeutic approaches, including psychoeducational and community-based interventions that facilitate personal and community growth and change, are encouraged. There is a need for increased awareness, training and funding to implement longitudinal interventions that work collaboratively with clients from refugee backgrounds through the stages of resettlement.

Start playing with your food : fun food experiences with mobile social media

Healthy and sustainable food is gaining more attention from consumers, industry, and researchers. Yet many approaches to date are limited to information dissemination, advertisement or education. We have embarked on a three year collaborative research project (2011 – 2013) to explore urban food practices – eating, cooking, growing food – to support the well-being of people and the environment. Our overall goal is to employ a user-centred interaction design research approach to inform the development of entertaining, real-time, mobile and networked applications, engaging playful feedback to build motivation. Our aspiration for this study is to deliver usable and useful mobile and situated interaction prototypes that employ individual and group strategies to foster food cultures that provide new pathways to produce, share and enjoy food that is green, healthy, and fun.

Open problems in the security of learning

Machine learning has become a valuable tool for detecting and preventing malicious activity. However, as more applications employ machine learning techniques in adversarial decision-making situations, increasingly powerful attacks become possible against machine learning systems. In this paper, we present three broad research directions towards the end of developing truly secure learning. First, we suggest that finding bounds on adversarial influence is important to understand the limits of what an attacker can and cannot do to a learning system. Second, we investigate the value of adversarial capabilities-the success of an attack depends largely on what types of information and influence the attacker has. Finally, we propose directions in technologies for secure learning and suggest lines of investigation into secure techniques for learning in adversarial environments. We intend this paper to foster discussion about the security of machine learning, and we believe that the research directions we propose represent the most important directions to pursue in the quest for secure learning.

Mentoring

For many years mentoring has been a well-recognised learning strategy for workers in a variety of settings such as schools, hospitals, universities and other types of organisations. It has been used to induct, socialise, train and support the knowledge and skill development of novices in all types of professions, including novice leaders. Some organisations have formalised the mentoring process by introducing mentoring programs that are integral to their human resource management strategies. Other organisations employ mentoring programs to address affirmative action requirements thus providing mentoring opportunities to members of particular target groups as a means of developing their competencies and assisting their career progression. Because of the diversity of ways in which mentoring has been used in organisations it has taken different forms and been experienced by mentors and mentees in different ways. The aim of this chapter is to provide some clarity about the term ‘mentoring’ and its practice within organisations. It begins with an exploration of the meaning and purposes of mentoring before reviewing some of the benefits and drawbacks the process provides for mentors, persons who are mentored (i.e. mentees) and for the organisation as a whole. The chapter also considers a number of issues that are important for program planners, as well as issues that mentors and mentees should understand if they are going to make the most out of their mentoring relationship.

Stochastic modelling of T cell homeostasis for two competing clonotypes via the master equation

Stochastic models for competing clonotypes of T cells by multivariate, continuous-time, discrete state, Markov processes have been proposed in the literature by Stirk, Molina-París and van den Berg (2008). A stochastic modelling framework is important because of rare events associated with small populations of some critical cell types. Usually, computational methods for these problems employ a trajectory-based approach, based on Monte Carlo simulation. This is partly because the complementary, probability density function (PDF) approaches can be expensive but here we describe some efficient PDF approaches by directly solving the governing equations, known as the Master Equation. These computations are made very efficient through an approximation of the state space by the Finite State Projection and through the use of Krylov subspace methods when evolving the matrix exponential. These computational methods allow us to explore the evolution of the PDFs associated with these stochastic models, and bimodal distributions arise in some parameter regimes. Time-dependent propensities naturally arise in immunological processes due to, for example, age-dependent effects. Incorporating time-dependent propensities into the framework of the Master Equation significantly complicates the corresponding computational methods but here we describe an efficient approach via Magnus formulas. Although this contribution focuses on the example of competing clonotypes, the general principles are relevant to multivariate Markov processes and provide fundamental techniques for computational immunology.

Distribution trade sector output and productivity performance : a case study of Singapore and Hong Kong 2001-2008

This paper employs the industry of origin approach to compare value added and productivity of Singapore and Hong Kong's Distribution Trade Sector for the period 2001-2008. The direct comparison between these two economies was motivated by the statements of the Singapore government: Its services sector, especially in Retail Trade, lags behind Hong Kong's productivity levels. The results show that since 2005, Singapore's Distribution performance in terms of labour productivity was below Hong Kong's level, which was largely due to poor performance in its Retail Trade sector arising from an influx of foreign workers. Results from total factor productivity (TFP) between these two economies also suggest that Hong Kong's better performance (since 2005) was largely due to its ability to employ more educated and trained workers with limited use of capital. The results suggest that polices that worked in Hong Kong may not work for Singapore because its population is more diverse which poses a challenge to policy-makers in raising its productivity level.

Complementary use of modeling grammars

Conceptual modeling continues to be an important means for graphically capturing the requirements of an information system. Observations of modeling practice suggest that modelers often use multiple modeling grammars in combination to articulate various aspects of real-world domains. We extend an ontological theory of representation to suggest why and how users employ multiple conceptual modeling grammars in combination. We provide an empirical test of the extended theory using survey data and structured interviews about the use of traditional and structured analysis grammars within an automated tool environment. We find that users of the analyzed tool combine grammars to overcome the ontological incompleteness that exists in each grammar. Users further selected their starting grammar from a predicted subset of grammars only. The qualitative data provides insights as to why some of the predicted deficiencies manifest in practice differently than predicted.

Train service timetabling in railway open markets by particle swarm optimisation

Railway timetabling is an important process in train service provision as it matches the transportation demand with the infrastructure capacity while customer satisfaction is also considered. It is a multi-objective optimisation problem, in which a feasible solution, rather than the optimal one, is usually taken in practice because of the time constraint. The quality of services may suffer as a result. In a railway open market, timetabling usually involves rounds of negotiations among a number of self-interested and independent stakeholders and hence additional objectives and constraints are imposed on the timetabling problem. While the requirements of all stakeholders are taken into consideration simultaneously, the computation demand is inevitably immense. Intelligent solution-searching techniques provide a possible solution. This paper attempts to employ a particle swarm optimisation (PSO) approach to devise a railway timetable in an open market. The suitability and performance of PSO are studied on a multi-agent-based railway open-market negotiation simulation platform.

Early years teachers’ attitudes towards mathematics

Worldwide, there is considerable attention to providing a supportive mathematics learning environment for young children because attitude formation and achievement in these early years of schooling have a lifelong impact. Key influences on young children during these early years are their teachers. Practising early years teachers‟ attitudes towards mathematics influence the teaching methods they employ, which in turn, affects young students‟ attitudes towards mathematics, and ultimately, their achievement. However, little is known about practising early years teachers‟ attitudes to mathematics or how these attitudes form, which is the focus of this study. The research questions were: 1. What attitudes do practising early years teachers hold towards mathematics? 2. How did the teachers‟ mathematics attitudes form? This study adopted an explanatory case study design (Yin, 2003) to investigate practising early years teachers‟ attitudes towards mathematics and the formation of these attitudes. The research took place in a Brisbane southside school situated in a middle socio-economic area. The site was chosen due to its accessibility to the researcher. The participant group consisted of 20 early years teachers. They each completed the Attitude Towards Mathematics Inventory (ATMI) (Schackow, 2005), which is a 40 item instrument that measures attitudes across the four dimensions of attitude, namely value, enjoyment, self-confidence and motivation. The teachers‟ total ATMI scores were classified according to five quintiles: strongly negative, negative, neutral, positive and strongly positive. The results of the survey revealed that these teachers‟ attitudes ranged across only three categories with one teacher classified as strongly positive, twelve teachers classified as positive and seven teachers classified as neutral. No teachers were identified as having negative or strongly negative attitudes. Subsequent to the surveys, six teachers with a breadth of attitudes were selected from the original cohort to participate in open-ended interviews to investigate the formation of their attitudes. The interview data were analysed according to the four dimensions of attitudes (value, enjoyment, self-confidence, motivation) and three stages of education (primary, secondary, tertiary). Highlighted in the findings is the critical impact of schooling experiences on the formation of student attitudes towards mathematics. Findings suggest that primary school experiences are a critical influence on the attitudes of adults who become early years teachers. These findings also indicate the vital role tertiary institutions play in altering the attitudes of preservice teachers who have had negative schooling experiences. Experiences that teachers indicated contributed to the formation of positive attitudes in their own education were games, group work, hands-on activities, positive feedback and perceived relevance. In contrast, negative experiences that teachers stated influenced their attitudes were insufficient help, rushed teaching, negative feedback and a lack of relevance of the content. These findings together with the literature on teachers‟ attitudes and mathematics education were synthesized in a model titled a Cycle of Early Years Teachers’ Attitudes Towards Mathematics. This model explains positive and negative influences on attitudes towards mathematics and how the attitudes of adults are passed on to children, who then as adults themselves, repeat the cycle by passing on attitudes to a new generation. The model can provide guidance for practising teachers and for preservice and inservice education about ways to foster positive influences to attitude formation in mathematics and inhibit negative influences. Two avenues for future research arise from the findings of this study both relating to attitudes and secondary school experiences. The first question relates to the resilience of attitudes, in particular, how an individual can maintain positive attitudes towards mathematics developed in primary school, despite secondary school experiences that typically have a negative influence on attitude. The second question relates to the relationship between attitudes and achievement, specifically, why secondary students achieve good grades in mathematics despite a lack of enjoyment, which is one of the dimensions of attitude.