Rock pools of critical thought : finding a place to think through my higher degree and what a PhD was all about

The rock pools, salt pans, cliffs and bluffs, and the banks of the Coorooman and Pumpkin Creeks within Darumbal and Woppaburra Country are used as a backdrop in this paper, which offers an exploration of one woman’s quest to undertake her PhD and develop as an Indigenous scholar. The paper describes this Country and the use of Country to nourish, develop, stimulate and support the intellect. It draws on Australian and international literature to demonstrate the intellectual growth and development of Indigenous scholars. The paper offers a highly personal narrative of intellectual journeying which shows how we can be agents of change and power in our individual lives, even while power is being exercised over us and we are being oppressed and marginalised as Indigenous peoples.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.

Assessing genetic diversity in cultured aquatic species : the Sydney Rock Oyster (Saccostrea glomerata) stock improvement program as a model

Genetic variation is the resource animal breeders exploit in stock improvement programs. Both the process of selection and husbandry practices employed in aquaculture will erode genetic variation levels overtime, hence the critical resource can be lost and this may compromise future genetic gains in breeding programs. The amount of genetic variation in five lines of Sydney Rock Oyster (SRO) that had been selected for QX (Queensland unknown) disease resistance were examined and compared with that in a wild reference population using seven specific SRO microsatellite loci. The five selected lines had significantly lower levels of genetic diversity than did the wild reference population with allelic diversity declining approximately 80%, but impacts on heterozygosity per locus were less severe. Significant deficiencies in heterozygotes were detected at six of the seven loci in both mass selected lines and the wild reference population. Against this trend however, a significant excess of heterozygotes was recorded at three loci Sgo9, Sgo14 and Sgo21 in three QX disease resistant lines (#2, #5 and #13). All populations were significantly genetic differentiated from each other based on pairwise FST values. A neighbour joining tree based on DA genetic distances showed a clear separation between all culture and wild populations. Results of this study show clearly, that the impacts of the stock improvement program for SRO has significantly eroded natural levels of genetic variation in the culture lines. This could compromise long-term genetic gains and affect sustainability of the SRO breeding program over the long-term.

Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

Between a rock and a hard place : what do public sector leaders learn from the past as they lead into the future

The purpose of this paper is to bring leadership context into sharper focus and to suggest there are strong constraints on public leaders’ discretion to lead in ways consistent with NPM or NPL. Much of the existing public leadership research focuses on the individual leader and tends to give little attention to the influence of context. This lack of focus on leader context adversely affects our ability to build public leadership capacity. We draw on prior research to establish that (1) there are strong contextual constraints on public leaders’ capacity to lead in ways consistent with NPL, (2) public leaders are subject to contradictory messages and for the most part these contradictions are unacknowledged and unresolved, the impact of which is confusion and informal power-politics, (3) the task of leader transition from traditional leadership to new public leadership is very much underestimated and requires a new way to think about leadership development. On the basis of this analysis, we argue that public leaders find themselves between a rock and a hard place.

Rough fuzzy control of SVC for power system stability enhancement

This paper presents a new approach to the design of a rough fuzzy controller for the control loop of the SVC (static VAR system) in a two area power system for stability enhancement with particular emphasis on providing effective damping for oscillatory instabilities. The performances of the rough fuzzy and the conventional fuzzy controller are compared with that of the conventional PI controller for a variety of transient disturbances, highlighting the effectiveness of the rough fuzzy controller in damping the inter-area oscillations. The effect of the rough fuzzy controller in improving the CCT (critical clearing time) of the two area system is elaborated in this paper as well.

A new database compilation of whole-rock chemical and geochronological data of igneous rocks in Queensland : a new resource for HDR geothermal resource exploration

The Geothermal industry in Australia and Queensland is in its infancy and for hot dry rock (HDR) geothermal energy, it is very much in the target identification and resource definition stages. As a key effort to assist the geothermal industry and exploration for HDR in Queensland, we are developing a comprehensive and new integrated geochemical and geochronological database on igneous rocks. To date, around 18,000 igneous rocks have been analysed across Queensland for chemical and/or age information. However, these data currently reside in a number of disparate datasets (e.g., Ozchron, Champion et al., 2007, Geological Survey of Queensland, journal publications, and unpublished university theses). The goal of this project is to collate and integrate these data on Queensland igneous rocks to improve our understanding of high heat producing granites in Queensland, in terms of their distribution (particularly in the subsurface), dimensions, ages, and controlling factors in their genesis.

Rough Game

Short Story About football Rugby League and City Country Clashes. Written to explore, examine and attempt to subvert generic conventions identified in PhD research. Good football fiction exists and it is plentiful.

Rock, paper, scissors : reflective practice for design process in the novice landscape architect

We describe a pedagogical approach that addresses challenges in design education for novices. These include an inability to frame new problems and limited-to-no design capability or domain knowledge. Such challenges can reduce student engagement with design practice, cause derivative design solutions as well as the inappropriate simplification of design assignments and assessment criteria by educators. We argue that a curriculum that develops the student’s design process will enable them to deal with the uncertain and dynamic situations that characterise design. We describe how this may be achieved and explain our pedagogical approach in terms of methods from Reflective Practice and theories of abstraction and creativity. We present a landscape architecture unit, recently taught, as an example. It constitutes design exercises that require little domain or design expertise to support the development of conceptual thinking and a design rationale. We show how this approach (a) leveraged the novice’s existing spatial and thinking skills while (b) retaining contextually-rich design situations. Examples of the design exercises taught are described along with samples of student work. The assessment rationale is also presented and explained. Finally, we conclude by reflecting on how this approach relates to innovation, sustainability and other disciplines.

Comparison between analytical and 3D finite element solutions for borehole stresses in anisotropic elastic rock

We present a rigorous validation of the analytical Amadei solution for the stress concentration around an arbitrarily orientated borehole in general anisotropic elastic media. First, we revisit the theoretical framework of the Amadei solution and present analytical insights that show that the solution does indeed contain all special cases of symmetry, contrary to previous understanding, provided that the reduced strain coefficients b11 and b55 are not equal. It is shown from theoretical considerations and published experimental data that the b11 and b55 are not equal for realistic rocks. Second, we develop a 3D finite element elastic model within a hybrid analytical–numerical workflow that circumvents the need to rebuild and remesh the model for every borehole and material orientation. Third, we show that the borehole stresses computed from the numerical model and the analytical solution match almost perfectly for different borehole orientations (vertical, deviated and horizontal) and for several cases involving isotropic, transverse isotropic and orthorhombic symmetries. It is concluded that the analytical Amadei solution is valid with no restriction on the borehole orientation or the symmetry of the elastic anisotropy.

Beat-mixing Rock music: Rock and electronic dance music merge to create the Manarays

This research introduces the proposition that Electronic Dance Music’s beat-mixing function could be implemented to create immediacy in other musical genres. The inclusion of rhythmic sections at the beginning and end of each musical work created a ‘DJ friendly’ environment. The term used in this thesis to refer to the application of beat-mixing in Rock music is ‘ClubRock’. Collaboration between a number of DJs and Rock music professionals applied the process of beat-mixing to blend Rock tracks to produce a continuous ClubRock set. The DJ technique of beat-mixing Rock music transformed static renditions into a fluid creative work. The hybridisation of the two genres, EDM and Rock, resulted in a contribution to Rock music compositional approaches and the production of a unique Rock album; Manarays—Get Lucky.

Rough set based approach to text classification

Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.