Factors influencing tourism sustainability : The case of the World Heritage Falun Great Copper Mountain

This thesis focuses on identifying hindrances of achieving a sustainable tourism development on a base of a World Heritage Site. Using a case study of the World Heritage Site Falun Great Copper Mountain, the thesis assesses the situational context by using qualitative methods. Five semi- structured interviews with influential stakeholders were conducted to get an inside view of the current situation and to identify site-specific issues. The thesis identifies a number of factors that determine the successful implementation of measures leading towards sustainable tourism in the long-run; the most important being the lack of clear guidelines for the whole destination and no holistic planning approach within the municipality. The thesis concludes that despite the increased pressures towards establishment of sustainable tourism, the concept remains challenging to operationalize for the World Heritage Site without frameworks and tools from UNESCO.

Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods

Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.

The right to convert exploration licences to mining leases in Australia: a proposed national uniform model

In this article, the authors raise an important proposal for reform to Australia's mining legislation: a nationally-consistent model providing exploration licence holders with a legislative right to be granted a mining lease. This proposed national model will be designed to reflect the present Western Australian system - Western Australia being the only jurisdiction to provide exploration licence holders with the express right to be granted a mining lease on application. The authors believe that the Western Australian system should provide the basis for a national legislative model, given that it is designed to balance appropriately the interests of companies wanting a right to mine to recoup the costs involved in exploring for minerals, and the interests of the public in ensuring that exploration and mining is conducted
reasonably.

Performance analysis of algorithms for frequent pattern generation

Data mining refers to extracting or "mining" knowledge from large amounts of data. It is also called a method of "knowledge presentation" where visualization and knowledge representation techniques are used to present the mined knowledge to the user. Efficient algorithms to mine frequent patterns are crucial to many tasks in data mining. Since the Apriori algorithm was proposed in 1994, there have been several methods proposed to improve its performance. However, most still adopt its candidate set generation-and-test approach. In addition, many methods do not generate all frequent patterns, making them inadequate to derive association rules. The Pattern Decomposition (PD) algorithm that can significantly reduce the size of the dataset on each pass makes it more efficient to mine all frequent patterns in a large dataset. This algorithm avoids the costly process of candidate set generation and saves a large amount of counting time to evaluate support with reduced datasets. In this paper, some existing frequent pattern generation algorithms are explored and their comparisons are discussed. The results show that the PD algorithm outperforms an improved version of Apriori named Direct Count of candidates & Prune transactions (DCP) by one order of magnitude and is faster than an improved FP-tree named as Predictive Item Pruning (PIP). Further, PD is also more scalable than both DCP and PIP.

Finding rule groups to classify high dimensional gene expression datasets

Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. Some approaches of machine learning are widely used to classify and mine biological datasets. However, many gene expression datasets are extremely high dimensionality, traditional machine learning methods can not be applied effectively and efficiently. This paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. Unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes), which are most discriminative to classify samples in different classes, to form rule groups for the classification of expression datasets. Our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches

Primary school music

Primary teaching and music qualifications - a rare combination, not only in New Zealand today but in primary schools the world over for more than a decade. Helen Stowasser (1993) writes of 'insecure music teachers' and questions the adequacy of teacher education courses. The Arts in the New Zealand Curriculum states: 'The arts develop the artistic and
aesthetic dimensions of human experience. They contribute to our intellectual ability and to our social, cultural and spiritual understandings. They are an essential element of daily living and of lifelong learning' [the italics are mine]. If our Ministry of Education truly believes this and wants
to ensure that the music discipline is adequately taught, then there are some issues to be addressed, such as recruitment of musically capable teachers; acceptable standards of professional expertise in music; content, length and timing of pre-service programmes; and making provision for teachers' ongoing development.

Total arsenic accumulation in yabbies (Cherax Destructor Clark) exposed to elevated arsenic levels in Victorian gold mining areas, Australia

Arsenic is a proven carcinogen often found at high concentrations in association with gold and other heavy metals. The freshwater yabby, Cherax destructor Clark (Decapoda, Parastacidae), is a ubiquitous species native to Australia's central and eastern regions, with a growing international commercial market. However, in this region of Australia, yabby farmers often harvest organisms from old mine tailings dams with elevated environmental arsenic levels. Yabbies exposed to elevated environmental arsenic were found to accumulate and store as much as 100 μg/g arsenic in their tissues. The accumulation is proportional to the concentration of arsenic in the sediment and is high enough to be of concern for people who eat the yabbies. A comparison of arsenic levels in wild and lab-fed animals also was performed. Although there was no significant difference in the level of arsenic in the various organs of the wild animals, the animals purchased from a yabby farm showed a significantly higher arsenic concentration in their hepatopancreas (3.7 ± 0.9 μg/g) compared to other organs (0.6–1.8 μg/g). Furthermore, after a 40-d exposure to food containing 200 to 300 μg/g inorganic arsenic, arsenate (As[V])-exposed animals showed a significant increase in tissue-specific arsenic accumulation, whereas arsenite (As[III])-exposed animals showed a lower, nonsignificant increase in As uptake, primarily in the hepatopancreas. These results have important implications for yabby growers and consumers alike.

Trace metal speciation in the Pieman River catchment, western Tasmania

The Pieman River catchment has seen continuous mining of economic deposits of gold, silver, lead, copper, zinc and tin since the 1870’s. Tributaries of this river which receive mining effluent, either directly or from acid mine drainage (AMID), have total metal concentrations considerably above background levels and are of regulatory concern. The lower Pieman River is however classified as a State Reserve in which recreational fishing and tourism are the major activities. It is therefore important that water entering the lower Pieman River from upstream hydroelectric impoundments is of high quality. Metals in natural waters exist in a variety of dissolved, colloidal and particulate forms. The bioavailability and hence toxicity of heavy metal pollutants is very dependant on their physico form. Knowledge of the speciation of a metal in natural aquatic environments is therefore necessary for understanding its geochemical behaviour and biological availability. Complexation of metal ions by natural ligands in aquatic systems is believed to play a significant role in controlling their chemical speciation. This study has investigated temporal and spatial variation in complexation of metal ions in the Pieman River. The influence of pH, temperature, organic matter, salinity, ionic strength and time has been investigated in a series of field studies and in laboratory-based experiments which simulated natural and anthropogenic disturbances. Labile metals were measured using two techniques in various freshwater and estuarine environments. Diffusive gradients in thin-films (DGT) allowed in situ measurement of solution speciation whilst differential pulse anodic stripping voltammetry (DPASV) was used to measure labile metal species in water samples collected from the catchment. Organic complexation was found to be a significant regulating mechanism for copper speciation and the copper-binding ligand concentration usually exceeded the total copper concentration in the river water. Complexation was highly dependent on pH and at the river-seawater interface was also regulated by salinity, probably as a result of competitive complexation by major ions in seawater (eg. Ca 2+ ions). Zinc complexation was also evident, however total zinc concentrations in the water column often far exceeded the potential binding capacity of available ligands. In addition to organic complexation, Zn speciation may also be associated with adsorption by flocculated or resuspended colloidal Mn and/or Fe oxyhydroxides. Metal ion complexation and hence speciation was found to be highly variable within the Pieman River catchment. This presents major difficulties for environmental managers, as it is therefore not possible to make catchment-wide assumptions about the bioavailability of these metals. These results emphasise the importance of site-specific sampling protocols and speciation testing, ideally incorporating continuous, in situ monitoring.

Biobsorbent properties of biosolids for aqueous zinc, manganese and cyanide removal

Biosolids were used to remove zinc, manganese and cyanide from mining wastewaters. The effect of aqueous parameters and reaction variables on contaminant biosorption was quantified. The mechanism of removal was adsorption onto amine and carboxyl functional groups. Immobilisation was investigated to overcome problems of swelling and disintegration of the biosolids.

Metamorphosis of a gold town : Stawell 1900-1940 : a study in local history

Examines the experience of the Wimmera town of Stawell as being representative of the early settlements created by gold rushes, and then threatened with extinction as the industry declined. Attention is paid to the role of community in Stawell's struggle to survive in the period between Federation and the Second World War. Reviews the economic and social processes involved in the eventual recovery. Argues that the forces of Stawell's historical legacy can be detected in the town's reaction to adversity after the closure of the last major mine in 1920.

Finding rule groups to classify high dimensional gene expression datasets

Microarray data provides quantitative information about the transcription profile of cells. To analyse microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. Some approaches of machine learning are widely used to classify and mine biological datasets. However, many gene expression datasets are extremely high dimensionality, traditional machine learning methods cannot be applied effectively and efficiently. This paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. Unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes) to form rule groups for the classification of expression datasets. Our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches.

Status of tailings dumps : let D5s go working in the past?

It was decided in the De Beers v Ataqua Mining (Pty) Ltd that ''tailings dumps'' created by mining companies before the Mineral and Petroleum Resources Development Act, 28 of 2002 ("the MPRDA") came into operation are not governed by its provisions because such dumps are not "residue stockpiles" or "residue deposits" for purposes of the MPRDA. Ownership of tailings dumps is determined by the common law principles of accession. Ownership of a movable dump has to be transferred by one of the recognised forms of delivery of movables. Processing of these dumps will, however, still be subject to compliance with South African environmental, health and safety laws in general. It is submitted that mine dumps or tailings dumps created upon the exercise of "old order mining rights" before the commencement of the MPRDA and even after commencement of the MPRDA until eventual termination of the "old order mining rights" are not subject to the extensive, mining, environmental, empowerment provisions of the MPRDA. Termination of "old order mining rights" takes place upon: (i) refusal of an application for conversion of a mining right during (or even after) the period of transition, (ii) conversion into and registration of new order mining rights during (or even after) the period of transition or (iii) termination of unconverted "old order mining rights" on 30 April 2009. To the extent that this decision has made it possible to embark on a shorter and less cumbersome route in the reprocessing and eventual disappearance of most tailings dumps, it is to be welcomed from an economical, environmental, job creation and aesthetic perspective. Proposed amendments to the MPRDA to undo the impact of the De Beers decision should be carefully considered against these mentioned benefits and a possible finding that it may amount to an expropriation without compensation.

Translating Laurence Louppe

In the light of the increasing corporatisation of academic publishing in English, this paper draws on my experience of translating French critic Laurence Louppe's Poétique de la danse contemporaine (Brussels, 1997) into English (Dance Books, forthcoming 2010) to reflect cross-linguistically upon the need to maintain a diversity of linguistic perspectives and resources in dance commentary. Just as the dancer and the choreographer use each other to learn from the “translation” that their respective bodies and moves represent for each other, so the process of textual translation can provoke a more acute awareness of issues regarding the relationship between language and the complexities of dance experiences. Louppe emphasises that one of the insights of contemporary dance has been that “the body” is not simply a support for verbal language but can have its own, different, communicative modalities. In the light of this, Louppe's own literary poetics seeks in return to mine the etymological layers of her language – and to activate its anthropological roots in sensuous existence. My article discusses the conceptual resources upon which Louppe draws, including those drawn from the modern dance heritage, her own philosophical erudition and literary poetics, and the resources specific to the French language (as these emerge through my perspective from within English) in order to articulate issues of change, corporeality and mobility. This discussion is undertaken in relation to specific terminological and metaphorical examples and makes comparisons with the writings of Isadora Duncan.

Arsenic speciation in the freshwater crayfish, Cherax destructor Clark

Arsenic is a proven carcinogen that is found in the soil in gold mining regions at concentrations that can be thousands of times greater than gold. During mining arsenic is released into the environment, easily entering surrounding water bodies.
The yabby (Cherax destructor) is a common freshwater crustacean native to Australia's central and eastern regions. Increasing aquaculture and export of these animals has led us to question the effects of mine contamination on the yabbies themselves and to assess any potential risks to consumers. This study determined the species of arsenic present in a number of organs from the yabby. Several arsenic contaminated dam sites in the goldfields of western Victoria were sampled for yabby populations. Yabbies from these sites were collected and analysed for arsenic speciation using high performance liquid chromatography–inductively coupled plasma-mass spectrometry (HPLC–ICP-MS). Results showed that type of exposure influenced which arsenic species was present in each organ, and that as arsenic exposure increased the prevalence of inorganic arsenic species, mostly As(V), within the tissues increased. The bioaccessibility of the arsenic present in the abdominal muscle (the edible portion for humans) of the yabbies was assessed. It was found that the majority of the bioaccessible arsenic was present as inorganic As (III) and As(V).