Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Monitoring and regulatory role of the balanced scorecard in controlling organisational identities

This thesis employs the theoretical fusion of disciplinary knowledge, interlacing an analysis from both functional and interpretive frameworks and applies these paradigms to three concepts—organisational identity, the balanced scorecard performance measurement system, and control. As an applied thesis, this study highlights how particular public sector organisations are using a range of multi-disciplinary forms of knowledge constructed for their needs to achieve practical outcomes. Practical evidence of this study is not bound by a single disciplinary field or the concerns raised by academics about the rigorous application of academic knowledge. The study’s value lies in its ability to explore how current communication and accounting knowledge is being used for practical purposes in organisational life. The main focus of this thesis is on identities in an organisational communication context. In exploring the theoretical and practical challenges, the research questions for this thesis were formulated as: 1. Is it possible to effectively control identities in organisations by the use of an integrated performance measurement system—the balanced scorecard—and if so, how? 2. What is the relationship between identities and an integrated performance measurement system—the balanced scorecard—in the identity construction process? Identities in the organisational context have been extensively discussed in graphic design, corporate communication and marketing, strategic management, organisational behaviour, and social psychology literatures. Corporate identity is the self-presentation of the personality of an organisation (Van Riel, 1995; Van Riel & Balmer, 1997), and organisational identity is the statement of central characteristics described by members (Albert & Whetten, 2003). In this study, identity management is positioned as a strategically complex task, embracing not only logo and name, but also multiple dimensions, levels and facets of organisational life. Responding to the collaborative efforts of researchers and practitioners in identity conceptualisation and methodological approaches, this dissertation argues that analysis can be achieved through the use of an integrated framework of identity products, patternings and processes (Cornelissen, Haslam, & Balmer, 2007), transforming conceptualisations of corporate identity, organisational identity and identification studies. Likewise, the performance measurement literature from the accounting field now emphasises the importance of ‘soft’ non-financial measures in gauging performance—potentially allowing the monitoring and regulation of ‘collective’ identities (Cornelissen et al., 2007). The balanced scorecard (BSC) (Kaplan & Norton, 1996a), as the selected integrated performance measurement system, quantifies organisational performance under the four perspectives of finance, customer, internal process, and learning and growth. Broadening the traditional performance measurement boundary, the BSC transforms how organisations perceived themselves (Vaivio, 2007). The rhetorical and communicative value of the BSC has also been emphasised in organisational self-understanding (Malina, Nørreklit, & Selto, 2007; Malmi, 2001; Norreklit, 2000, 2003). Thus, this study establishes a theoretical connection between the controlling effects of the BSC and organisational identity construction. Common to both literatures, the aspects of control became the focus of this dissertation, as ‘the exercise or act of achieving a goal’ (Tompkins & Cheney, 1985, p. 180). This study explores not only traditional technical and bureaucratic control (Edwards, 1981), but also concertive control (Tompkins & Cheney, 1985), shifting the locus of control to employees who make their own decisions towards desired organisational premises (Simon, 1976). The controlling effects on collective identities are explored through the lens of the rhetorical frames mobilised through the power of organisational enthymemes (Tompkins & Cheney, 1985) and identification processes (Ashforth, Harrison, & Corley, 2008). In operationalising the concept of control, two guiding questions were developed to support the research questions: 1.1 How does the use of the balanced scorecard monitor identities in public sector organisations? 1.2 How does the use of the balanced scorecard regulate identities in public sector organisations? This study adopts qualitative multiple case studies using ethnographic techniques. Data were gathered from interviews of 41 managers, organisational documents, and participant observation from 2003 to 2008, to inform an understanding of organisational practices and members’ perceptions in the five cases of two public sector organisations in Australia. Drawing on the functional and interpretive paradigms, the effective design and use of the systems, as well as the understanding of shared meanings of identities and identifications are simultaneously recognised. The analytical structure guided by the ‘bracketing’ (Lewis & Grimes, 1999) and ‘interplay’ strategies (Schultz & Hatch, 1996) preserved, connected and contrasted the unique findings from the multi-paradigms. The ‘temporal bracketing’ strategy (Langley, 1999) from the process view supports the comparative exploration of the analysis over the periods under study. The findings suggest that the effective use of the BSC can monitor and regulate identity products, patternings and processes. In monitoring identities, the flexible BSC framework allowed the case study organisations to monitor various aspects of finance, customer, improvement and organisational capability that included identity dimensions. Such inclusion legitimises identity management as organisational performance. In regulating identities, the use of the BSC created a mechanism to form collective identities by articulating various perspectives and causal linkages, and through the cascading and alignment of multiple scorecards. The BSC—directly reflecting organisationally valued premises and legitimised symbols—acted as an identity product of communication, visual symbols and behavioural guidance. The selective promotion of the BSC measures filtered organisational focus to shape unique identity multiplicity and characteristics within the cases. Further, the use of the BSC facilitated the assimilation of multiple identities by controlling the direction and strength of identifications, engaging different groups of members. More specifically, the tight authority of the BSC framework and systems are explained both by technical and bureaucratic controls, while subtle communication of organisational premises and information filtering is achieved through concertive control. This study confirms that these macro top-down controls mediated the sensebreaking and sensegiving process of organisational identification, supporting research by Ashforth, Harrison and Corley (2008). This study pays attention to members’ power of self-regulation, filling minor premises of the derived logic of their organisation through the playing out of organisational enthymemes (Tompkins & Cheney, 1985). Members are then encouraged to make their own decisions towards the organisational premises embedded in the BSC, through the micro bottom-up identification processes including: enacting organisationally valued identities; sensemaking; and the construction of identity narratives aligned with those organisationally valued premises. Within the process, the self-referential effect of communication encouraged members to believe the organisational messages embedded in the BSC in transforming collective and individual identities. Therefore, communication through the use of the BSC continued the self-producing of normative performance mechanisms, established meanings of identities, and enabled members’ self-regulation in identity construction. Further, this research establishes the relationship between identity and the use of the BSC in terms of identity multiplicity and attributes. The BSC framework constrained and enabled case study organisations and members to monitor and regulate identity multiplicity across a number of dimensions, levels and facets. The use of the BSC constantly heightened the identity attributes of distinctiveness, relativity, visibility, fluidity and manageability in identity construction over time. Overall, this research explains the reciprocal controlling relationships of multiple structures in organisations to achieve a goal. It bridges the gap among corporate and organisational identity theories by adopting Cornelissen, Haslam and Balmer’s (2007) integrated identity framework, and reduces the gap in understanding between identity and performance measurement studies. Parallel review of the process of monitoring and regulating identities from both literatures synthesised the theoretical strengths of both to conceptualise and operationalise identities. This study extends the discussion on positioning identity, culture, commitment, and image and reputation measures in integrated performance measurement systems as organisational capital. Further, this study applies understanding of the multiple forms of control (Edwards, 1979; Tompkins & Cheney, 1985), emphasising the power of organisational members in identification processes, using the notion of rhetorical organisational enthymemes. This highlights the value of the collaborative theoretical power of identity, communication and performance measurement frameworks. These case studies provide practical insights about the public sector where existing bureaucracy and desired organisational identity directions are competing within a large organisational setting. Further research on personal identity and simple control in organisations that fully cascade the BSC down to individual members would provide enriched data. The extended application of the conceptual framework to other public and private sector organisations with a longitudinal view will also contribute to further theory building.

A geometric approach to trajectory design for an autonomous underwater vehicle : surveying the bulbous bow of a ship

In this paper, we present a control strategy design technique for an autonomous underwater vehicle based on solutions to the motion planning problem derived from differential geometric methods. The motion planning problem is motivated by the practical application of surveying the hull of a ship for implications of harbor and port security. In recent years, engineers and researchers have been collaborating on automating ship hull inspections by employing autonomous vehicles. Despite the progresses made, human intervention is still necessary at this stage. To increase the functionality of these autonomous systems, we focus on developing model-based control strategies for the survey missions around challenging regions, such as the bulbous bow region of a ship. Recent advances in differential geometry have given rise to the field of geometric control theory. This has proven to be an effective framework for control strategy design for mechanical systems, and has recently been extended to applications for underwater vehicles. Advantages of geometric control theory include the exploitation of symmetries and nonlinearities inherent to the system. Here, we examine the posed inspection problem from a path planning viewpoint, applying recently developed techniques from the field of differential geometric control theory to design the control strategies that steer the vehicle along the prescribed path. Three potential scenarios for surveying a ship?s bulbous bow region are motivated for path planning applications. For each scenario, we compute the control strategy and implement it onto a test-bed vehicle. Experimental results are analyzed and compared with theoretical predictions.

Geometric Control Theory and its Application to Underwater Vehicles

This dissertation is based on theoretical study and experiments which extend geometric control theory to practical applications within the field of ocean engineering. We present a method for path planning and control design for underwater vehicles by use of the architecture of differential geometry. In addition to the theoretical design of the trajectory and control strategy, we demonstrate the effectiveness of the method via the implementation onto a test-bed autonomous underwater vehicle. Bridging the gap between theory and application is the ultimate goal of control theory. Major developments have occurred recently in the field of geometric control which narrow this gap and which promote research linking theory and application. In particular, Riemannian and affine differential geometry have proven to be a very effective approach to the modeling of mechanical systems such as underwater vehicles. In this framework, the application of a kinematic reduction allows us to calculate control strategies for fully and under-actuated vehicles via kinematic decoupled motion planning. However, this method has not yet been extended to account for external forces such as dissipative viscous drag and buoyancy induced potentials acting on a submerged vehicle. To fully bridge the gap between theory and application, this dissertation addresses the extension of this geometric control design method to include such forces. We incorporate the hydrodynamic drag experienced by the vehicle by modifying the Levi-Civita affine connection and demonstrate a method for the compensation of potential forces experienced during a prescribed motion. We present the design method for multiple different missions and include experimental results which validate both the extension of the theory and the ability to implement control strategies designed through the use of geometric techniques. By use of the extension presented in this dissertation, the underwater vehicle application successfully demonstrates the applicability of geometric methods to design implementable motion planning solutions for complex mechanical systems having equal or fewer input forces than available degrees of freedom. Thus, we provide another tool with which to further increase the autonomy of underwater vehicles.

A Taxonomy of image matching techniques for stereo vision

Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Applications of stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics, industrial automation and stereomicroscopy. A key issue in stereo vision is that of image matching, or identifying corresponding points in a stereo pair. The difference in the positions of corresponding points in image coordinates is termed the parallax or disparity. When the orientation of the two cameras is known, corresponding points may be projected back to find the location of the original object point in world coordinates. Matching techniques are typically categorised according to the nature of the matching primitives they use and the matching strategy they employ. This report provides a detailed taxonomy of image matching techniques, including area based, transform based, feature based, phase based, hybrid, relaxation based, dynamic programming and object space methods. A number of area based matching metrics as well as the rank and census transforms were implemented, in order to investigate their suitability for a real-time stereo sensor for mining automation applications. The requirements of this sensor were speed, robustness, and the ability to produce a dense depth map. The Sum of Absolute Differences matching metric was the least computationally expensive; however, this metric was the most sensitive to radiometric distortion. Metrics such as the Zero Mean Sum of Absolute Differences and Normalised Cross Correlation were the most robust to this type of distortion but introduced additional computational complexity. The rank and census transforms were found to be robust to radiometric distortion, in addition to having low computational complexity. They are therefore prime candidates for a matching algorithm for a stereo sensor for real-time mining applications. A number of issues came to light during this investigation which may merit further work. These include devising a means to evaluate and compare disparity results of different matching algorithms, and finding a method of assigning a level of confidence to a match. Another issue of interest is the possibility of statistically combining the results of different matching algorithms, in order to improve robustness.

Developments in texture-based vector field visualisation techniques

Vector field visualisation is one of the classic sub-fields of scientific data visualisation. The need for effective visualisation of flow data arises in many scientific domains ranging from medical sciences to aerodynamics. Though there has been much research on the topic, the question of how to communicate flow information effectively in real, practical situations is still largely an unsolved problem. This is particularly true for complex 3D flows. In this presentation we give a brief introduction and background to vector field visualisation and comment on the effectiveness of the most common solutions. We will then give some examples of current development on texture-based techniques, and given practical examples of their use in CFD research and hydrodynamic applications.

Digital image processing techniques for pavement macro-texture analysis

Road surface macro-texture is an indicator used to determine the skid resistance levels in pavements. Existing methods of quantifying macro-texture include the sand patch test and the laser profilometer. These methods utilise the 3D information of the pavement surface to extract the average texture depth. Recently, interest in image processing techniques as a quantifier of macro-texture has arisen, mainly using the Fast Fourier Transform (FFT). This paper reviews the FFT method, and then proposes two new methods, one using the autocorrelation function and the other using wavelets. The methods are tested on pictures obtained from a pavement surface extending more than 2km's. About 200 images were acquired from the surface at approx. 10m intervals from a height 80cm above ground. The results obtained from image analysis methods using the FFT, the autocorrelation function and wavelets are compared with sensor measured texture depth (SMTD) data obtained from the same paved surface. The results indicate that coefficients of determination (R2) exceeding 0.8 are obtained when up to 10% of outliers are removed.

Clone detection in repositories of business process models

As organizations reach to higher levels of business process management maturity, they often find themselves maintaining repositories of hundreds or even thousands of process models, representing valuable knowledge about their operations. Over time, process model repositories tend to accumulate duplicate fragments (also called clones) as new process models are created or extended by copying and merging fragments from other models. This calls for methods to detect clones in process models, so that these clones can be refactored as separate subprocesses in order to improve maintainability. This paper presents an indexing structure to support the fast detection of clones in large process model repositories. The proposed index is based on a novel combination of a method for process model decomposition (specifically the Refined Process Structure Tree), with established graph canonization and string matching techniques. Experiments show that the algorithm scales to repositories with hundreds of models. The experimental results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice.

Reliability analysis and economic equipment replacement appraisal for substation and sub-transmission systems with explicit inclusion of non-repairable failures

The modern society has come to expect the electrical energy on demand, while many of the facilities in power systems are aging beyond repair and maintenance. The risk of failure is increasing with the aging equipments and can pose serious consequences for continuity of electricity supply. As the equipments used in high voltage power networks are very expensive, economically it may not be feasible to purchase and store spares in a warehouse for extended periods of time. On the other hand, there is normally a significant time before receiving equipment once it is ordered. This situation has created a considerable interest in the evaluation and application of probability methods for aging plant and provisions of spares in bulk supply networks, and can be of particular importance for substations. Quantitative adequacy assessment of substation and sub-transmission power systems is generally done using a contingency enumeration approach which includes the evaluation of contingencies, classification of the contingencies based on selected failure criteria. The problem is very complex because of the need to include detailed modelling and operation of substation and sub-transmission equipment using network flow evaluation and to consider multiple levels of component failures. In this thesis a new model associated with aging equipment is developed to combine the standard tools of random failures, as well as specific model for aging failures. This technique is applied in this thesis to include and examine the impact of aging equipments on system reliability of bulk supply loads and consumers in distribution network for defined range of planning years. The power system risk indices depend on many factors such as the actual physical network configuration and operation, aging conditions of the equipment, and the relevant constraints. The impact and importance of equipment reliability on power system risk indices in a network with aging facilities contains valuable information for utilities to better understand network performance and the weak links in the system. In this thesis, algorithms are developed to measure the contribution of individual equipment to the power system risk indices, as part of the novel risk analysis tool. A new cost worth approach was developed in this thesis that can make an early decision in planning for replacement activities concerning non-repairable aging components, in order to maintain a system reliability performance which economically is acceptable. The concepts, techniques and procedures developed in this thesis are illustrated numerically using published test systems. It is believed that the methods and approaches presented, substantially improve the accuracy of risk predictions by explicit consideration of the effect of equipment entering a period of increased risk of a non-repairable failure.

Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

Predicting mothers’ decisions to introduce complementary feeding at 6 months : an investigation using an extended theory of planned behaviour

In Australia and other developed countries there is poor adherence to guidelines recommending the introduction of complementary feeding to infants at 6 months of age. We aimed to investigate, via adopting a theory of planned behaviour framework and incorporating additional normative and demographic influences, mothers’ complementary feeding intentions and behaviour. Participants were 375 primiparas who completed an initial questionnaire (infant age 13±3weeks) that assessed the theory of planned behaviour constructs of attitude, subjective norm, and perceived behavioural control, as well as group norm and additional maternal and infant variables of mothers’ age, education level, weight status perception, current maternal feeding practices, and infant birth weight. Approximately, 3 months after completion of the main questionnaire, mothers completed a follow-up questionnaire that assessed the age in months at which the infant was first introduced to solids. The theory of planned behaviour variables of attitude and subjective norm, along with group norm, predicted intentions, with intention, mothers’ age (older more likely), and weight status perception (overweight less likely) predicting behaviour. Overall, the results highlight the importance of attitudes, normative influences, and individual characteristics in complementary feeding decision-making which should be considered when designing interventions aimed at improving adherence to current maternal feeding guidelines.

The development of the extended adolescent injury checklist (E-AIC) : a measure for injury prevention program evaluation

The Extended Adolescent Injury Checklist (E-AIC), a self-report measure of injury based on the model of the Adolescent Injury Checklist (AIC), was developed for use in the evaluation of school-based interventions. The three stages of this development involved focus groups with adolescents and consultations with medical staff, pilot testing of the revised AIC in a high school context, and use of the finalised checklist in pre- and post-questionnaires to examine its utility. Results revealed that responses to the final version of the E-AIC were meaningful and remained consistent over time. The E-AIC appears to be a promising measure of adolescent injury that is simple, time-efficient and appropriate for use in the evaluation of school-based injury prevention programs.

Addressing sustainable living using a collaborative approach and multi-disciplinary techniques

In order to achieve meaningful reductions in individual ecological footprints, individuals must dramatically alter their day to day behaviours. Effective interventions will need to be evidence based and there is a necessity for the rapid transfer or communication of information from the point of research, into policy and practice. A number of health disciplines, including psychology and public health, share a common mission to promote health and well-being and it is becoming clear that the most practical pathway to achieving this mission is through interdisciplinary collaboration. This paper argues that an interdisciplinary collaborative approach will facilitate research that results in the rapid transfer of findings into policy and practice. The application of this approach is described in relation to the Green Living project which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in consultation with an expert panel comprising academics, industry professionals and government representatives, a self-administered mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay (Queensland, Australia). The Green Living survey explored specific beliefs which included attitudes, norms, perceived control, intention and behaviour, as well as a number of other constructs such as environmental concern and altruism. This research has two beneficial outcomes. First, it will inform a practical model for predicting sustainable living behaviours and a number of local councils have already expressed an interest in making use of the results as part of their ongoing community engagement programs. Second, it provides an example of how a collaborative interdisciplinary project can provide a more comprehensive approach to research than can be accomplished by a single disciplinary project.

A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.