Decision boundary setting and classifier combination for text classification

This thesis presents a promising boundary setting method for solving challenging issues in text classification to produce an effective text classifier. A classifier must identify boundary between classes optimally. However, after the features are selected, the boundary is still unclear with regard to mixed positive and negative documents. A classifier combination method to boost effectiveness of the classification model is also presented. The experiments carried out in the study demonstrate that the proposed classifier is promising.

Two-dimensional bow and stern flows in a finite-depth fluid with constant vorticity

This thesis is concerned with two-dimensional free surface flows past semi-infinite surface-piercing bodies in a fluid of finite-depth. Throughout the study, it is assumed that the fluid in question is incompressible, and that the effects of viscosity and surface tension are negligible. The problems considered are physically important, since they can be used to model the flow of water near the bow or stern of a wide, blunt ship. Alternatively, the solutions can be interpreted as describing the flow into, or out of, a horizontal slot. In the past, all research conducted on this topic has been dedicated to the situation where the flow is irrotational. The results from such studies are extended here, by allowing the fluid to have constant vorticity throughout the flow domain. In addition, new results for irrotational flow are also presented. When studying the flow of a fluid past a surface-piercing body, it is important to stipulate in advance the nature of the free surface as it intersects the body. Three different possibilities are considered in this thesis. In the first of these possibilities, it is assumed that the free surface rises up and meets the body at a stagnation point. For this configuration, the nonlinear problem is solved numerically with the use of a boundary integral method in the physical plane. Here the semi-infinite body is assumed to be rectangular in shape, with a rounded corner. Supercritical solutions which satisfy the radiation condition are found for various values of the Froude number and the dimensionless vorticity. Subcritical solutions are also found; however these solutions violate the radiation condition and are characterised by a train of waves upstream. In the limit that the height of the body above the horizontal bottom vanishes, the flow approaches that due to a submerged line sink in a $90^\circ$ corner. This limiting problem is also examined as a special case. The second configuration considered in this thesis involves the free surface attaching smoothly to the front face of the rectangular shaped body. For this configuration, nonlinear solutions are computed using a similar numerical scheme to that used in the stagnant attachment case. It is found that these solution exist for all supercritical Froude numbers. The related problem of the cusp-like flow due to a submerged sink in a corner is also considered. Finally, the flow of a fluid emerging from beneath a semi-infinite flat plate is examined. Here the free surface is assumed to detach from the trailing edge of the plate horizontally. A linear problem is formulated under the assumption that the elevation of the plate is close to the undisturbed free surface level. This problem is solved exactly using the Wiener-Hopf technique, and subcritical solutions are found which are characterised by a train of sinusoidal waves in the far field. The nonlinear problem is also considered. Exact relations between certain parameters for supercritical flow are derived using conservation of mass and momentum arguments, and these are confirmed numerically. Nonlinear subcritical solutions are computed, and the results are compared to those predicted by the linear theory.

Evaluation of object detection proposals under condition variations

Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.

Technology transfer offices as boundary spanners in the pre-spin-off process: The case of a hybrid model

Over the past decades, universities have increasingly become ambidextrous organizations reconciling scientific and commercial missions. In order to manage this ambidexterity, technology transfer offices (TTOs) were established in most universities. This paper studies a specific, often implemented, but rather understudied type of TTO, namely a hybrid TTO model uniting centralized and decentralized levels. Employing a qualitative research design, we examine how and why the two TTO levels engage in diverse boundary spanning activities to help nascent spin-off companies move through the pre-spin-off process. Our research identifies differences in the types of boundary spanning activities that centralized and decentralized TTOs perform and in the parties they engage with. We find geographical, technological and organizational proximity to be important antecedents of the TTOs’ engagement in external and internal boundary spanning activities. These results have important implications for both academics and practitioners interested in university technology transfer through spin-off creation.

Place recognition with ConvNet landmarks: Viewpoint-robust, condition-robust, training-free

Place recognition has long been an incompletely solved problem in that all approaches involve significant compromises. Current methods address many but never all of the critical challenges of place recognition – viewpoint-invariance, condition-invariance and minimizing training requirements. Here we present an approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition. We use the astonishing power of convolutional neural network features to identify matching landmark proposals between images to perform place recognition over extreme appearance and viewpoint variations. Our system does not require any form of training, all components are generic enough to be used off-the-shelf. We present a range of challenging experiments in varied viewpoint and environmental conditions. We demonstrate superior performance to current state-of-the- art techniques. Furthermore, by building on existing and widely used recognition frameworks, this approach provides a highly compatible place recognition system with the potential for easy integration of other techniques such as object detection and semantic scene interpretation.

Minimising the failure of rail joints through managing the localised condition of track

To effectively address the high rate of failure of Insulated Rail Joints (IRJs) in the heavy haul lines, a research plan was designed and implemented with particular attention to understand their mechanical behaviour and deterioration process. In this paper, part of this ongoing research is described. During the past decades many studies have tried to improve the service life of IRJs by introducing a new structural design or material for IRJ components. This paper looks into this problem from a different perspective highlighting the significance of localised condition of track to the loads and responses of the IRJs. Results from a series of field measurements conducted in a rail track within the Australian Rail Track Corporation (ARTC) network are discussed. The interactive effects of IRJ responses and localised track condition are further investigated using the results obtained from numerical simulations. The field measurements and the simulation results provide valuable insight on the influence of track condition to the behaviour of IRJs.

Boundary crossing: A theoretical framework to understand the operation dynamics of industry-school partnerships

Industry-school partnerships (ISPs) are increasingly being recognised as a new way of providing vocational education opportunities. However, there is limited research investigating their impact on systemic (organisational and structural) and human resource (teachers and education managers) capacity to support school to work transitions. This paper reports on a government led ISP, established by the Queensland state government. ISPs across three industry sectors: minerals and energy; building and construction; and aviation are included in this study. This research adopted a qualitative case study methodology and draws upon boundary crossing theory to understand the dynamics of how each industry sector responded to systemic and human resource issues that emerged in each ISP. The main finding being that the systematic application of boundary crossing mechanisms by all partners pro-duced mutually beneficial outcomes. ISPs from the three sectors adopted different models, leveraged different boundary crossing objects but all maintained the joint vision and mutually agreed outcomes. All three ISPs genuinely crossed boundaries, albeit in different ways, and assisted teachers to co-pro-duce industry-based curriculums, share sector specific knowledge and skills that help enhance the school to work transition for school graduates.

Comparison of visual inspection and structural-health monitoring as bridge condition assessment methods

This paper presents the results of a research project aimed at examining the capabilities and challenges of two distinct but not mutually exclusive approaches to in-service bridge assessment: visual inspection and installed monitoring systems. In this study, the intended functionality of both approaches was evaluated on its ability to identify potential structural damage and to provide decision-making support. Inspection and monitoring are compared in terms of their functional performance, cost, and barriers (real and perceived) to implementation. Both methods have strengths and weaknesses across the metrics analyzed, and it is likely that a hybrid evaluation technique that adopts both approaches will optimize efficiency of condition assessment and ultimately lead to better decision making.

An investigation of Nano-particle deposition in cylindrical tubes under Laminar condition using Lagrangian transport model

Aerosol deposition in cylindrical tubes is a subject of interest to researchers and engineers in many applications of aerosol physics and metrology. Investigation of nano-particles in different aspects such as lungs, upper airways, batteries and vehicle exhaust gases is vital due the smaller size, adverse health effect and higher trouble for trapping than the micro-particles. The Lagrangian particle tracking provides an effective method for simulating the deposition of nano-particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. In this paper, the deposition of nano-particles in cylindrical tubes under laminar condition is studied using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different flow rates are examined. The point analysis in a uniform flow is performed for validating the Brownian motion. The results show good agreement between the calculated deposition efficiency and the analytic correlations in the literature. Furthermore, for the nano-particles with the diameter more than 40 nm, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.

The effect of thermal radiation on the natural convection boundary layer flow over a wavy horizontal surface

In this article, natural convection boundary layer flow is investigated over a semi-infinite horizontal wavy surface. Such an irregular (wavy) surface is used to exchange heat with an external radiating fluid which obeys Rosseland diffusion approximation. The boundary layer equations are cast into dimensionless form by introducing appropriate scaling. Primitive variable formulations (PVF) and stream function formulations (SFF) are independently used to transform the boundary layer equations into convenient form. The equations obtained from the former formulations are integrated numerically via implicit finite difference iterative scheme whereas equations obtained from lateral formulations are simulated through Keller-box scheme. To validate the results, solutions produced by above two methods are compared graphically. The main parameters: thermal radiation parameter and amplitude of the wavy surface are discussed categorically in terms of shear stress and rate of heat transfer. It is found that wavy surface increases heat transfer rate compared to the smooth wall. Thus optimum heat transfer is accomplished when irregular surface is considered. It is also established that high amplitude of the wavy surface in the boundary layer leads to separation of fluid from the plate.

Condition monitoring and rating of bridge components in a rail or road network by using SHM systems within SRP

The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.

Mechanical analysis of foot plantar fascia during normal walking condition

Foot plantar fascia is an important foot tissue in stabilizing the longitudinal arch of human foot. Direct measurement to monitor the mechanical situation of plantar fascia at human locomotion is difficult. The purpose of this study was to construct a three-dimensional finite element model of the foot to calculate the internal stress/strain value of plantar fascia during different stage of gait. The simulated stress distribution of plantar fascia was the lowest at heel-strike, which concentrated on the medial side of calcaneal tubercle. The peak stress of plantar fascia was appeared at push-off, and the value is more than 5 times of the heel-strike position. Current FE model was able to explore the plantar fascia tension trend at the main sub-phases of foot. More detailed fascia model and intrinsic muscle forces could be developed in the further study.

Fluid-structure interaction study on human arterial plaque with patient specific geometry and boundary conditions

Atherosclerotic plaque rupture has been extensively considered as the leading cause of death in western countries. It is believed that high stresses within plaque can be an important factor on triggering the rupture of the plaque. Stress analysis in the coronary and carotid arteries with plaque have been developed by many researchers from 2D to 3-D models, from structure analysis only to the Fluid-Structure Interaction (FSI) models[1].

'Work it out': Evaluation of a chronic condition self-management program for urban Aboriginal and Torres Strait Islander people with or at risk of cardiovascular disease

This thesis evaluates a chronic condition self-management program for Aboriginal and Torres Strait Islander people in urban south-east Queensland who have or are at risk of cardiovascular disease. Outcomes showed short-term improvements for some anthropometry measures which could be a trend for improvement in other anthropometry indicators over the longer term. The program was of particular benefit for participants who had several social and emotional wellbeing conditions. The use of an Aboriginal and Torres Strait Islander conceptual framework was critical in undertaking culturally competent quantitative research in this project.

Repeatable Condition-Invariant Visual Odometry for Sequence-Based Place Recognition

This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.