Optimization problems for controlled mechanical systems : bridging the gap between theory and application

Mechanical control systems have become a part of our everyday life. Systems such as automobiles, robot manipulators, mobile robots, satellites, buildings with active vibration controllers and air conditioning systems, make life easier and safer, as well as help us explore the world we live in and exploit it’s available resources. In this chapter, we examine a specific example of a mechanical control system; the Autonomous Underwater Vehicle (AUV). Our contribution to the advancement of AUV research is in the area of guidance and control. We present innovative techniques to design and implement control strategies that consider the optimization of time and/or energy consumption. Recent advances in robotics, control theory, portable energy sources and automation increase our ability to create more intelligent robots, and allows us to conduct more explorations by use of autonomous vehicles. This facilitates access to higher risk areas, longer time underwater, and more efficient exploration as compared to human occupied vehicles. The use of underwater vehicles is expanding in every area of ocean science. Such vehicles are used by oceanographers, archaeologists, geologists, ocean engineers, and many others. These vehicles are designed to be agile, versatile and robust, and thus, their usage has gone from novelty to necessity for any ocean expedition.

Processing load and the use of concrete representations and strategies for solving linear equations

This paper is a report of students' responses to instruction which was based on the use of concrete representations to solve linear equations. The sample consisted of 21 Grade 8 students from a middle-class suburban state secondary school with a reputation for high academic standards and innovative mathematics teaching. The students were interviewed before and after instruction. Interviews and classroom interactions were observed and videotaped. A qualitative analysis of the responses revealed that students did not use the materials in solving problems. The increased processing load caused by concrete representations is hypothesised as a reason.

An analytical method to solve a general class of nonlinear reactive transport models

Three recent papers published in Chemical Engineering Journal studied the solution of a model of diffusion and nonlinear reaction using three different methods. Two of these studies obtained series solutions using specialized mathematical methods, known as the Adomian decomposition method and the homotopy analysis method. Subsequently it was shown that the solution of the same particular model could be written in terms of a transcendental function called Gauss’ hypergeometric function. These three previous approaches focused on one particular reactive transport model. This particular model ignored advective transport and considered one specific reaction term only. Here we generalize these previous approaches and develop an exact analytical solution for a general class of steady state reactive transport models that incorporate (i) combined advective and diffusive transport, and (ii) any sufficiently differentiable reaction term R(C). The new solution is a convergent Maclaurin series. The Maclaurin series solution can be derived without any specialized mathematical methods nor does it necessarily involve the computation of any transcendental function. Applying the Maclaurin series solution to certain case studies shows that the previously published solutions are particular cases of the more general solution outlined here. We also demonstrate the accuracy of the Maclaurin series solution by comparing with numerical solutions for particular cases.

Procuring Sydney’s Olympic Stadium : a world class event?

This paper describes and analyses the procurement processes employed in delivering the Sydney Olympic Stadium – arguably the most significant stadia project in the region today. This current high profile project is discussed in terms of a case study into the procurement processes used. Interviews, personal site visits and questionnaires were used to obtain information on the procurement processes used and comments on their application to the project. The alternative procurement process used on this project—Design and Construction within a Build, Own, Operate and Transfer (BOOT) project—is likely to impact on the construction industry as a whole. Already other projects and sectors are following this lead. Based on a series of on-site interviews and questionnaires, a series of benefits and drawbacks to this procurement strategy are provided.The Olympic Stadium project has also been further analysed during construction through a Degree of Interaction framework to determine anticipated project success. This analysis investigates project interaction and user satisfaction to provide a comparable rating. A series of questionnaires were used to collect data to calculate the Degree of Interaction and User Satisfaction ratings.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

Sustaining the next generation of teacher-researchers to work for social justice

This chapter explores a research project involving teachers working with some of the most disadvantaged young people in South Australia, children growing up in poverty, in families struggling with homelessness and ill-health, in the outer southern suburbs. Additionally, there were particular children were struggling with intellectual, emotional and social difficulties which were extreme enough for them not be included in a mainstream class. The research project made two crucial interrelated moves to support teachers to tackle this tough work. First, the project had an explicit social justice agenda. We were not simply researching literacy outcomes, but literacy pedagogies for the students teachers were most worried about. And we wanted to understand how the material conditions of students’ everyday lifeworlds impacted on the working conditions of teachers’ schoolworlds. We sought to open up a discursive space where teachers could talk about poverty, violence, racism and classism in ways that would take them beyond despair and into new imaginings and positive action. Second, the project was designed to start from the urgent questions of early career teachers and to draw on the accumulated practice wisdom of their chosen mentors. Hence we designed not only a teacher-researcher community, but cross-generational networks. Our aim was to build the capacities of both generations to address long-standing educational problems in new ways that drew overtly on their different and complementary resources.

Communicating assessment criteria is not sufficient for influencing students' approaches to assessment tasks – perspectives from a differential equations class

This report presents the findings of an exploratory study into the perceptions held by students regarding the use of criterion-referenced assessment in an undergraduate differential equations class. Students in the class were largely unaware of the concept of criterion referencing and of the various interpretations that this concept has among mathematics educators. Our primary goal was to investigate whether explicitly presenting assessment criteria to students was useful to them and guided them in responding to assessment tasks. Quantitative data and qualitative feedback from students indicates that while students found the criteria easy to understand and useful in informing them as to how they would be graded, the manner in which they actually approached the assessment activity was not altered as a result of the use of explicitly communicated grading criteria.

Gender and municipal politics : problems, perspectives and possibilities

Scholars of local government have repeatedly lamented the lack of literature on the subject (e.g., Mowbray 1997; Pini, Previte, Haslam & McKenzie 2007). As Dollery, Marshall and Worthington (2003: 1) have commented, local government has often been the ‘poor cousin of its more exalted relatives in terms of the attention it attracts from the research community.’ The exalted relatives Dollery et al. (2003) refer to are national political environments, where women’s participation has elicited significant attention. However, the dearth of research on the specific subject of women’s representation in local government is rarely acknowledged (Neyland & Tucker 1996; Whip & Fletcher 1999). This edited book attempts to redress this situation. Each chapter applies an explicit gender analysis to their specific topic of focus, making ‘gender visible in social phenomenon; [and] asking if, how, and why social processes, standards, and opportunities differ systematically for women and men’ (Howard, Risman & Sprague 2003: 1). These analyses in the local government context are critical for understanding the extent and nature of balanced representation at all levels of government. Furthermore, some women start their elective careers serving on school boards, city or town councils or as mayors, before progressing to state and national legislative offices. Hence, the experiences of women in local government illustrate broader notions of democracy and may for some individual women, shape their opportunities further along the political pipeline.

Numerical study of two ill-posed one-phase Stefan problems

We treat two related moving boundary problems. The first is the ill-posed Stefan problem for melting a superheated solid in one Cartesian coordinate. Mathematically, this is the same problem as that for freezing a supercooled liquid, with applications to crystal growth. By applying a front-fixing technique with finite differences, we reproduce existing numerical results in the literature, concentrating on solutions that break down in finite time. This sort of finite-time blow-up is characterised by the speed of the moving boundary becoming unbounded in the blow-up limit. The second problem, which is an extension of the first, is proposed to simulate aspects of a particular two-phase Stefan problem with surface tension. We study this novel moving boundary problem numerically, and provide results that support the hypothesis that it exhibits a similar type of finite-time blow-up as the more complicated two-phase problem. The results are unusual in the sense that it appears the addition of surface tension transforms a well-posed problem into an ill-posed one.

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

Learning the kernel matrix with semidefinite programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.