An algorithm to cluster the spectra in a spectrogram

The work described in this technical report is part of an ongoing project at QUT to build practical tools for the manipulation, analysis and visualisation of recordings of the natural environment. This report describes the algorithm we use to cluster the spectra in a spectrogram. The report begins with a brief description of the signal processing that prepares the spectrograms.

Using formative feedback to identify and support first year chemistry students with missing or misconceptions. A Practice Report

Students entering tertiary studies possess a diverse range of prior experiences in their academic preparation for tertiary chemistry so academics need tools to enable them to respond to issues in diversity in conceptual models possessed by entering students. Concept inventories can be used to provide formative feedback to help students identify concepts that they need to address to improve construction of subsequent understanding enabling their learning. Modular, formative learning activities that can be administered inside or outside of class in first year chemistry courses have been developed. These activities address key missing and mis-conceptions possessed by incoming student. Engagement in these learning activities by students and academics will help shift the culture of diagnostic and formative assessment within the tertiary context and address issues around the secondary/tertiary transition. This diagnostic/intervention framework is currently being trialed across five Australian tertiary institutions encompassing a large heterogeneous sample of students.

A semi-supervised graph-based algorithm for detecting outliers in online-social-networks

In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.

A hybrid genetic algorithm for the minimum interconnection cut problem

In the real world there are many problems in network of networks (NoNs) that can be abstracted to a so-called minimum interconnection cut problem, which is fundamentally different from those classical minimum cut problems in graph theory. Thus, it is desirable to propose an efficient and effective algorithm for the minimum interconnection cut problem. In this paper we formulate the problem in graph theory, transform it into a multi-objective and multi-constraint combinatorial optimization problem, and propose a hybrid genetic algorithm (HGA) for the problem. The HGA is a penalty-based genetic algorithm (GA) that incorporates an effective heuristic procedure to locally optimize the individuals in the population of the GA. The HGA has been implemented and evaluated by experiments. Experimental results have shown that the HGA is effective and efficient.

Inside the research incubator : a case study of an intensive undergraduate research experience for nursing and midwifery students

Undergraduate research experiences are an increasing component of nursing and midwifery degrees. The Summer Research Scholarship Programme (SRSP) is a tertiary education initiative in Australia to provide an intensive undergraduate research experience. Between 2009 and 2010, six students and four academic faculty mentors in School of Nursing and Midwifery participated in an inaugural SRSP. This study explores the experiences of both students and faculty mentors to determine how this undergraduate research experience impacted student learning and interest in research. A qualitative case study approach was used to explore the research experiences of undergraduate student and faculty participants in an inaugural undergraduate research programme. Based on the results of two surveys four main themes were identified: (1) acquisition of research skills, (2) expectations, (3) academic engagement, and (4) continued interest in research. An intensive undergraduate research experience is a valuable component of student learning that has the capacity to contribute to immediate and longer-term learning and research outcomes.

An efficient algorithm for the detection of Eden

In this paper, a polynomial time algorithm is presented for solving the Eden problem for graph cellular automata. The algorithm is based on our neighborhood elimination operation which removes local neighborhood configurations which cannot be used in a pre-image of a given configuration. This paper presents a detailed derivation of our algorithm from first principles, and a detailed complexity and accuracy analysis is also given. In the case of time complexity, it is shown that the average case time complexity of the algorithm is \Theta(n^2), and the best and worst cases are \Omega(n) and O(n^3) respectively. This represents a vast improvement in the upper bound over current methods, without compromising average case performance.

Algorithm clustering for multi-algorithm processor design

An Application Specific Instruction-set Processor (ASIP) is a specialized processor tailored to run a particular application/s efficiently. However, when there are multiple candidate applications in the application’s domain it is difficult and time consuming to find optimum set of applications to be implemented. Existing ASIP design approaches perform this selection manually based on a designer’s knowledge. We help in cutting down the number of candidate applications by devising a classification method to cluster similar applications based on the special-purpose operations they share. This provides a significant reduction in the comparison overhead while resulting in customized ASIP instruction sets which can benefit a whole family of related applications. Our method gives users the ability to quantify the degree of similarity between the sets of shared operations to control the size of clusters. A case study involving twelve algorithms confirms that our approach can successfully cluster similar algorithms together based on the similarity of their component operations.

Robust control algorithm for grid-interfaced three-phase inverters with high-bandwidth LCL filter

The paper introduces the design of robust current and voltage control algorithms for a grid-connected three-phase inverter which is interfaced to the grid through a high-bandwidth three-phase LCL filter. The algorithms are based on the state feedback control which have been designed in a systematic approach and improved by using oversampling to deal with the issues arising due to the high-bandwidth filter. An adaptive loop delay compensation method has also been adopted to minimize the adverse effects of loop delay in digital controller and to increase the robustness of the control algorithm in the presence of parameter variations. Simulation results are presented to validate the effectiveness of the proposed algorithm.

Particle Swarm algorithm with Fuzzy decision making for a multi-objective economic and environmental optimization of design of a thermal system

Multi-Objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the thermoeconomic and Environmental aspects have been considered, simultaneously. The environmental objective function has been defined and expressed in cost terms. One of the most suitable optimization techniques developed using a particular class of search algorithms known as; Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been used here. This approach has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of fuzzy decision-making with the aid of Bellman-Zadeh approach has been presented and a final optimal solution has been introduced.

CFO inside debt and corporate innovation

This thesis examines the importance of CFO incentives on the value maximization of firm. It examines the association between CFO inside debt compensation i.e., CFO pensions and deferred compensation, and investment in corporate innovation. It finds that instead of encouraging innovation, CFO inside debt appears to have a dampening effect on investment in innovation.

Digitally enabled?! An analysis of law and justice students' use of smart devices

The research seeks to understand the nature of law and justice students’ use of technology for their learning purposes. There is often an assumption made that all students have, and engage with, technology to the same degree. The research tests these assumptions by means of a survey conducted of first year law and justice students to determine their actual use of smart devices inside and outside classes. The analysis of results reveals that while the majority of respondents own at least one smart device; most rarely use their device for their learning purposes.

Inside the pleasure dome : cultural tourism on Australia’s Gold Coast

In 2018 the City of the Gold Coast in south-east Queensland, Australia, will host the next Commonwealth Games. The City is made up a 57 km stretch of coastline and hinterland divided by a major highway. The famous surfing beaches are framed by high-rise development while the hinterland is marketed as a green, unspoilt environment. The winning bid for the Games, and discussion about future infrastructure and marketing of the region’s attributes, has focussed attention on the way City residents and policy makers think about their region in broad terms. Whereas in the past tourism marketing has been directed towards the pleasures of sun and surf by day and bright lights by night, various regional tourist stakeholders are beginning to reorient their programs. This paper considers some of the competing aims of the various stakeholders in this region and the interaction of existing ‘cultures’ with new technology and the demands of permanent residents, using data from a case study of e-literary trails developed in Brisbane, the capital city of Queensland. The importance of tourist imaginaries as a basis for using rich accounts of the past for future planning is emphasized.

Correlating flow induced shear stress and chondrocytes activity in micro-porous scaffold using computational fluid dynamics and rapid prototyping

Flow induced shear stress plays an important role in regulating cell growth and distribution in scaffolds. This study sought to correlate wall shear stress and chondrocytes activity for engineering design of micro-porous osteochondral grafts based on the hypothesis that it is possible to capture and discriminate between the transmitted force and cell response at the inner irregularities. Unlike common tissue engineering therapies with perfusion bioreactors in which flow-mediated stress is the controlling parameter, this work assigned the associated stress as a function of porosity to influence in vitro proliferation of chondrocytes. D-optimality criterion was used to accommodate three pore characteristics for appraisal in a mixed level fractional design of experiment (DOE); namely, pore size (4 levels), distribution pattern (2 levels) and density (3 levels). Micro-porous scaffolds (n=12) were fabricated according to the DOE using rapid prototyping of an acrylic-based bio-photopolymer. Computational fluid dynamics (CFD) models were created correspondingly and used on an idealized boundary condition with a Newtonian fluid domain to simulate the dynamic microenvironment inside the pores. In vitro condition was reproduced for the 3D printed constructs seeded by high pellet densities of human chondrocytes and cultured for 72 hours. The results showed that cell proliferation was significantly different in the constructs (p<0.05). Inlet fluid velocity of 3×10-2mms-1 and average shear stress of 5.65×10-2 Pa corresponded with increased cell proliferation for scaffolds with smaller pores in hexagonal pattern and lower densities. Although the analytical solution of a Poiseuille flow inside the pores was found insufficient for the description of the flow profile probably due to the outside flow induced turbulence, it showed that the shear stress would increase with cell growth and decrease with pore size. This correlation demonstrated the basis for determining the relation between the induced stress and chondrocyte activity to optimize microfabrication of engineered cartilaginous constructs.

Review essay : Crime, risk and money : "The Currency of Justice : Fines and Damages in Consumer Societies" and "Crime and Risk", both by Pat O'Malley

Sharing some closely related themes and a common theoretical orientation based on the governmentality analytic, these are nevertheless two very different contributions to criminological knowledge and theory. The first, The Currency of Justice: Fines and Damages in Consumer Societies (COJ), is a sustained and highly original analysis of that most pervasive yet overlooked feature of modern legal orders; their reliance on monetary sanctions. Crime and Risk (CAR), on the other hand, is a short synoptic overview of the many dimensions and trajectories of risk in contemporary debate and practice, both the practices of crime and the governance of crime. It is one of the first in a new series by Sage, 'Compact Criminology', in which authors survey in little more than a hundred pages some current field of debate. With this small gem, Pat O'Malley has set the bar very high for those who follow. For all its brevity, CAR traverses a massive expanse of research, debates and issues, while also opening up new and challenging questions around the politics of risk and the relationship between criminal risk-taking and the governance of risk and crime. The two books draw together various threads of O'Malley's rich body of work on these issues, and once again demonstrate that he is one of the foremost international scholars of risk inside and outside criminology.

Eight weeks of episodic visual navigation inside a non-stationary environment using adaptive spherical views

This paper presents a long-term experiment where a mobile robot uses adaptive spherical views to localize itself and navigate inside a non-stationary office environment. The office contains seven members of staff and experiences a continuous change in its appearance over time due to their daily activities. The experiment runs as an episodic navigation task in the office over a period of eight weeks. The spherical views are stored in the nodes of a pose graph and they are updated in response to the changes in the environment. The updating mechanism is inspired by the concepts of long- and short-term memories. The experimental evaluation is done using three performance metrics which evaluate the quality of both the adaptive spherical views and the navigation over time.