Modelling the process of dialogic communication in public relations: a role-based approach

This paper takes Kent and Taylor’s (2002) call to develop a dialogic theory of public relations and suggests that a necessary first step is the modelling of the process of dialogic communication in public relations. In order to achieve this, extant literature from a range of fields is reviewed, seeking to develop a definition of dialogic communication that is meaningful to the practice of contemporary public relations. A simple transmission model of communication is used as a starting point. This is synthesised with concepts relating specifically to dialogue, taken here in its broadest sense rather than defined as any one particular outcome. The definition that emerges from this review leads to the conclusion that dialogic communication in public relations involves the interaction of three roles – those of sender, receiver, and responder. These three roles are shown to be adopted at different times by both participants involved in dialogic communication. It is further suggested that variations occur in how these roles are conducted: the sender and receiver roles can be approached in a passive or an active way, while the responder role can be classified as being either resistant or responsive to the information received in dialogic communication. The final modelling of the definition derived provides a framework which can be tested in the field to determine whether variations in the conduct of the roles in dialogic communication actually exist, and if so, whether they can be linked to the different types of outcome from dialogic communication identified previously in the literature.

Social studies disciplinary knowledge: Tensions between state curriculum and national assessment requirements

In this chapter, we are particularly concerned with making visible the general principles underlying the transmission of Social Studies curriculum knowledge, and considering it in light of a high-stakes mandated national assessment task. Specifically, we draw on Bernstein’s theoretical concept of pedagogic models as a tool for analysing orientations to teaching and learning. We introduce a case in point from the Australian context: one state Social Studies curriculum vis-a-vis one part of the Year Three national assessment measure for reading. We use our findings to consider the implications for the disciplinary knowledge of Social Studies in the communities in which we are undertaking our respective Australian Research Council Linkage project work (Glasswell et al.; Woods et al.). We propose that Social Studies disciplinary knowledge is being constituted, in part, through power struggles between different agencies responsible for the production and relay of official forms of state curriculum and national literacy assessment. This is particularly the case when assessment instruments are used to compare and contrast school results in highly visible web based league tables (see, for example, http://myschoolaustralia.ning.com/).

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

An initial technology roadmap for home automation : home and personal life management

Home Automation (HA) has emerged as a prominent ¯eld for researchers and in- vestors confronting the challenge of penetrating the average home user market with products and services emerging from technology based vision. In spite of many technology contri- butions, there is a latent demand for a®ordable and pragmatic assistive technologies for pro-active handling of complex lifestyle related problems faced by home users. This study has pioneered to develop an Initial Technology Roadmap for HA (ITRHA) that formulates a need based vision of 10-15 years, identifying market, product and technology investment opportunities, focusing on those aspects of HA contributing to e±cient management of home and personal life. The concept of Family Life Cycle is developed to understand the temporal needs of family. In order to formally describe a coherent set of family processes, their relationships, and interaction with external elements, a reference model named Fam- ily System is established that identi¯es External Entities, 7 major Family Processes, and 7 subsystems-Finance, Meals, Health, Education, Career, Housing, and Socialisation. Anal- ysis of these subsystems reveals Soft, Hard and Hybrid processes. Rectifying the lack of formal methods for eliciting future user requirements and reassessing evolving market needs, this study has developed a novel method called Requirement Elicitation of Future Users by Systems Scenario (REFUSS), integrating process modelling, and scenario technique within the framework of roadmapping. The REFUSS is used to systematically derive process au- tomation needs relating the process knowledge to future user characteristics identi¯ed from scenarios created to visualise di®erent futures with richly detailed information on lifestyle trends thus enabling learning about the future requirements. Revealing an addressable market size estimate of billions of dollars per annum this research has developed innovative ideas on software based products including Document Management Systems facilitating automated collection, easy retrieval of all documents, In- formation Management System automating information services and Ubiquitous Intelligent System empowering the highly mobile home users with ambient intelligence. Other product ideas include robotic devices of versatile Kitchen Hand and Cleaner Arm that can be time saving. Materialisation of these products require technology investment initiating further research in areas of data extraction, and information integration as well as manipulation and perception, sensor actuator system, tactile sensing, odour detection, and robotic controller. This study recommends new policies on electronic data delivery from service providers as well as new standards on XML based document structure and format.

An investigation of a process for environmental banking appropriate to Queensland

This thesis examines the advanced North American environmental mitigation schemes for their applicability to Queensland. Compensatory wetland mitigation banking, in particular, is concerned with in-perpetuity management and protection - the basic concerns of the Queensland public about its unique environment. The process has actively engaged the North American market and become a thriving industry that (for the most part) effectively designs, creates and builds (or enhances) environmental habitat. A methodology was designed to undertake a comprehensive review of the history, evolution and concepts of the North American wetland mitigation banking system - before and after the implementation of a significant new compensatory wetland mitigation banking regulation in 2008. The Delphi technique was then used to determine the principles and working components of wetland mitigation banking. Results were then applied to formulate a questionnaire to review Australian marketbased instruments (including offsetting policies) against these North American principles. Following this, two case studies established guiding principles for implementation based on two components of the North American wetland mitigation banking program. The subsequent outcomes confirmed that environmental banking is a workable concept in North America and that it is worth applying in Queensland. The majority of offsetting policies in Australia have adopted some principles of the North American mitigation programs. Examination reveals that however, they fail to provide adequate incentives for private landowners to participate because the essential trading mechanisms are not employed. Much can thus be learnt from the North American situation - where private enterprise has devised appropriate free market concepts. The consequent environmental banking process (as adapted from the North American programs) should be implemented in Queensland. It can then focus here on engaging the private sector, where the majority of naturally productive lands are managed.

Designing ePortfolios for music postgraduate study : a practice-led inquiry

In this research I have examined how ePortfolios can be designed for Music postgraduate study through a practice led research enquiry. This process involved designing two Web 2.0 ePortfolio systems for a group of five post graduate music research students. The design process revolved around the application of an iterative methodology called Software Develop as Research (SoDaR) that seeks to simultaneously develop design and pedagogy. The approach to designing these ePortfolio systems applied four theoretical protocols to examine the use of digitised artefacts in ePortfolio systems to enable a dynamic and inclusive dialogue around representations of the students work. The research and design process involved an analysis of existing software and literature with a focus upon identifying the affordances of available Web 2.0 software and the applications of these ideas within 21st Century life. The five post graduate music students each posed different needs in relation to the management of digitised artefacts and the communication of their work amongst peers, supervisors and public display. An ePortfolio was developed for each of them that was flexible enough to address their needs within the university setting. However in this first SoDaR iteration data gathering phase I identified aspects of the university context that presented a negative case that impacted upon the design and usage of the ePortfolios and prevented uptake. Whilst the portfolio itself functioned effectively, the university policies and technical requirements prevented serious use. The negative case analysis of the case study found revealed that Access and Control and Implementation, Technical and Policy Constraints protocols where limiting user uptake. From the semistructured interviews carried out as part of this study participant feedback revealed that whilst the participants did not use the ePortfolio system I designed, each student was employing Web 2.0 social networking and storage processes in their lives and research. In the subsequent iterations I then designed a more ‘ideal’ system that could be applied outside of the University context that draws upon the employment of these resources. In conclusion I suggest recommendations about ePortfolio design that considers what the applications of the theoretical protocols reveal about creative arts settings. The transferability of these recommendations are of course dependent upon the reapplication of the theoretical protocols in a new context. To address the mobility of ePortfolio design between Institutions and wider settings I have also designed a prototype for a business card sized USB portal for the artists’ ePortfolio. This research project is not a static one; it stands as an evolving design for a Web 2.0 ePortfolio that seeks to refer to users needs, institutional and professional contexts and the development of software that can be incorporated within the design. What it potentially provides to creative artist is an opportunity to have a dialogue about art with artefacts of the artist products and processes in that discussion.

Developing a hybrid expert system program to aid in the design of plastic injection molding process

Experts in injection molding often refer to previous solutions to find a mold design similar to the current mold and use previous successful molding process parameters with intuitive adjustment and modification as a start for the new molding application. This approach saves a substantial amount of time and cost in experimental based corrective actions which are required in order to reach optimum molding conditions. A Case-Based Reasoning (CBR) System can perform the same task by retrieving a similar case which is applied to the new case from the case library and uses the modification rules to adapt a solution to the new case. Therefore, a CBR System can simulate human e~pertise in injection molding process design. This research is aimed at developing an interactive Hybrid Expert System to reduce expert dependency needed on the production floor. The Hybrid Expert System (HES) is comprised of CBR, flow analysis, post-processor and trouble shooting systems. The HES can provide the first set of operating parameters in order to achieve moldability condition and producing moldings free of stress cracks and warpage. In this work C++ programming language is used to implement the expert system. The Case-Based Reasoning sub-system is constructed to derive the optimum magnitude of process parameters in the cavity. Toward this end the Flow Analysis sub-system is employed to calculate the pressure drop and temperature difference in the feed system to determine the required magnitude of parameters at the nozzle. The Post-Processor is implemented to convert the molding parameters to machine setting parameters. The parameters designed by HES are implemented using the injection molding machine. In the presence of any molding defect, a trouble shooting subsystem can determine which combination of process parameters must be changed iii during the process to deal with possible variations. Constraints in relation to the application of this HES are as follows. - flow length (L) constraint: 40 mm < L < I 00 mm, - flow thickness (Th) constraint: -flow type: - material types: I mm < Th < 4 mm, unidirectional flow, High Impact Polystyrene (HIPS) and Acrylic. In order to test the HES, experiments were conducted and satisfactory results were obtained.

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.