404 resultados para Perak former tin mining areas


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With the overwhelming increase in the amount of texts on the web, it is almost impossible for people to keep abreast of up-to-date information. Text mining is a process by which interesting information is derived from text through the discovery of patterns and trends. Text mining algorithms are used to guarantee the quality of extracted knowledge. However, the extracted patterns using text or data mining algorithms or methods leads to noisy patterns and inconsistency. Thus, different challenges arise, such as the question of how to understand these patterns, whether the model that has been used is suitable, and if all the patterns that have been extracted are relevant. Furthermore, the research raises the question of how to give a correct weight to the extracted knowledge. To address these issues, this paper presents a text post-processing method, which uses a pattern co-occurrence matrix to find the relation between extracted patterns in order to reduce noisy patterns. The main objective of this paper is not only reducing the number of closed sequential patterns, but also improving the performance of pattern mining as well. The experimental results on Reuters Corpus Volume 1 data collection and TREC filtering topics show that the proposed method is promising.

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This report presents a snapshot from work which was funded by the Queensland Injury Prevention Council in 2010-11 titled “Feasibility of Using Health Data Sources to Inform Product Safety Surveillance in Queensland children”. The project provided an evaluation of the current available evidence-base for identification and surveillance of product-related injuries in children in Queensland and Australia. A comprehensive 300 page report was produced (available at: http://eprints.qut.edu.au/46518/) and a series of recommendations were made which proposed: improvements in the product safety data system, increased utilisation of health data for proactive and reactive surveillance, enhanced collaboration between the health sector and the product safety sector, and improved ability of health data to meet the needs of product safety surveillance. At the conclusion of the project, a Consumer Product Injury Research Advisory group (CPIRAG) was established as a working party to the Queensland Injury Prevention Council (QIPC), to prioritise and advance these recommendations and to work collaboratively with key stakeholders to promote the role of injury data to support product safety policy decisions at the Queensland and national level. This group continues to meet monthly and is comprised of the organisations represented on the second page of this report. One of the key priorities of the CPIRAG group for 2012 was to produce a snapshot report to highlight problem areas for potential action arising out of the larger report. Subsequent funding to write this snapshot report was provided by the Institute for Health and Biomedical Innovation, Injury Prevention and Rehabilitation Domain at QUT in 2012. This work was undertaken by Dr Kirsten McKenzie and researchers from QUT's Centre for Accident Research and Road Safety - Queensland. This snapshot report provides an evidence base for potential further action on a range of children’s products that are significantly represented in injury data. Further information regarding injury hazards, safety advice and regulatory responses are available on the Office of Fair Trading (OFT) Queensland website and the Product Safety Australia websites. Links to these resources are provided for each product reviewed.

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Big data is big news in almost every sector including crisis communication. However, not everyone has access to big data and even if we have access to big data, we often do not have necessary tools to analyze and cross reference such a large data set. Therefore this paper looks at patterns in small data sets that we have ability to collect with our current tools to understand if we can find actionable information from what we already have. We have analyzed 164390 tweets collected during 2011 earthquake to find out what type of location specific information people mention in their tweet and when do they talk about that. Based on our analysis we find that even a small data set that has far less data than a big data set can be useful to find priority disaster specific areas quickly.

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With the explosive growth of resources available through the Internet, information mismatching and overload have become a severe concern to users. Web users are commonly overwhelmed by huge volume of information and are faced with the challenge of finding the most relevant and reliable information in a timely manner. Personalised information gathering and recommender systems represent state-of-the-art tools for efficient selection of the most relevant and reliable information resources, and the interest in such systems has increased dramatically over the last few years. However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from a technological and social perspective. Aiming to promote high quality research in order to overcome these challenges, this paper provides a comprehensive survey on the recent work and achievements in the areas of personalised web information gathering and recommender systems. The report covers concept-based techniques exploited in personalised information gathering and recommender systems.

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It is a big challenge to find useful associations in databases for user specific needs. The essential issue is how to provide efficient methods for describing meaningful associations and pruning false discoveries or meaningless ones. One major obstacle is the overwhelmingly large volume of discovered patterns. This paper discusses an alternative approach called multi-tier granule mining to improve frequent association mining. Rather than using patterns, it uses granules to represent knowledge implicitly contained in databases. It also uses multi-tier structures and association mappings to represent association rules in terms of granules. Consequently, association rules can be quickly accessed and meaningless association rules can be justified according to the association mappings. Moreover, the proposed structure is also an precise compression of patterns which can restore the original supports. The experimental results shows that the proposed approach is promising.

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Interest in nanowires of metal oxide oxides has been exponentially growing in the last years, due to the attracting potential of application in electronic, optical and sensor field. We have focused our attention on the sensing properties of semiconducting nanowires as conductometric and optical gas sensors. Single crystal tin dioxide nanostructures were synthesized to explore and study their capability in form of multi-nanowires sensors. The nanowires of SnO2 have been used to produce a novel gas sensor based on Pt/oxide/SiC structure and operating as Schottky diode. For the first time, a reactive oxide layer in this device has been replaced by SnO2 nanowires. Proposed sensor has maintained the advantageous properties of known SiC- based MOS devices, that can be employed for the monitoring of gases (hydrogen and hydrocarbons) emitted by industrial combustion processes.

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Understanding network traffic behaviour is crucial for managing and securing computer networks. One important technique is to mine frequent patterns or association rules from analysed traffic data. On the one hand, association rule mining usually generates a huge number of patterns and rules, many of them meaningless or user-unwanted; on the other hand, association rule mining can miss some necessary knowledge if it does not consider the hierarchy relationships in the network traffic data. Aiming to address such issues, this paper proposes a hybrid association rule mining method for characterizing network traffic behaviour. Rather than frequent patterns, the proposed method generates non-similar closed frequent patterns from network traffic data, which can significantly reduce the number of patterns. This method also proposes to derive new attributes from the original data to discover novel knowledge according to hierarchy relationships in network traffic data and user interests. Experiments performed on real network traffic data show that the proposed method is promising and can be used in real applications. Copyright2013 John Wiley & Sons, Ltd.

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The characteristics of dust particles deposited during the 2009 dust storm in the Gold Coast and Brisbane regions of Australia are discussed in this paper. The study outcomes provide important knowledge in relation to the potential impacts of dust storm related pollution on ecosystem health in the context that the frequency of dust storms is predicted to increase due to anthropogenic desert surface modifications and climate change impacts. The investigated dust storm contributed a large fraction of fine particles to the environment with an increased amount of total suspended solids, compared to dry deposition under ambient conditions. Although the dust storm passed over forested areas, the organic carbon content in the dust was relatively low. The primary metals present in the dust storm deposition were aluminium, iron and manganese, which are common soil minerals in Australia. The dust storm deposition did not contain significant loads of nickel, cadmium, copper and lead, which are commonly present in the urban environment. Furthermore, the comparison between the ambient and dust storm chromium and zinc loads suggested that these metals were contributed to the dust storm by local anthropogenic sources. The potential ecosystem health impacts of the 2009 dust storm include, increased fine solids deposition on ground surfaces resulting in an enhanced capacity to adsorb toxic pollutants as well as increased aluminium, iron and manganese loads. In contrast, the ecosystem health impacts related to organic carbon and other metals from dust storm atmospheric deposition are not considered to be significant.

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This research develops a new framework to be used as a tool for analysing and designing walkable communities. The literature review recognises the work of other researchers combining their findings with the theory of activity nodes and considers how a framework may be used on a more global basis. The methodology develops a set of criteria through the analysis of noted successful case studies and this is then tested against an area with very low walking rates in Brisbane, Australia. Results of the study suggest that as well as the accepted criteria of connectivity, accessibility, safety, security, and path quality further criteria in the form or planning hierarchy, activity nodes and climate mitigation could be added to allow the framework to cover a broader context. Of particular note is the development of the nodal approach, which allows simple and effective analysis of existing conditions, and may also prove effective as a tool for planning and design of walkable communities.

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The coal industry in Queensland operates in a very complex regulatory environment with a matrix of Federal and State laws covering the environment, health and safety, taxation and royalties, tenure, and development approvals. The Queensland Government in 2012 recognised the validity of certain industry concerns and passed two Acts being the Environmental Protection (Greentape Reduction) Amendment Act 2012 (the Greentape Act) and the Mines Legislation (Streamlining) Amendment Act 2012 (the Streamlining Act). Other changes are foreshadowed in relation to overlapping tenure and in the development of common resources legislation. Accordingly there is a great level of activity and change that has occurred or which is on the horizon. This article focuses upon these regulatory changes and foreshadows other areas requiring consideration. It commences with a consideration of the changes that have already occurred, examines those regulatory amendments that are on the drawing board and concludes with suggestions as to further interventions and amendments that have the potential to enhance the efficiency and effectiveness of the legislative framework in which coal mining is conducted.

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Crude petroleum remains the single most imported commodity into Australia and is sourced from a number of countries around the world (Department of Foreign Affairs and Trade (DFAT), 2011a). While interest in crude petroleum is widespread, in recent years Australia's focus has been drawn to the continent of Africa, where increased political stability, economic recovery and an improved investment climate has made one of the largest oil reserves in the world increasingly more attractive. Despite improvement across the continent, there remain a number of risks which have the potential to significantly damage Australia's economic interests in the petroleum sector,including government policies and legislation, corruption and conflict. The longest exporters of crude petroleum products to Australia – Nigeria and Libya – have been subject to these factors in recent years and, accordingly, are the focus of this paper. Once identified, the impact of political instability, conflict, government corruption and other risk factors to Australia's mining interests within these countries is examined, and efforts to manage such risks are discussed.

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The surface formation energies of four low-indexed surfaces, including (001), (100), (110) and (011), of tin dioxide (SnO2) terminated by nonmetals (H, N, O, F, Cl, Br, and I) have been studied with the frameworks of density functional theory. A strong dependence of relative surface stabilities on surface atoms has been presented based on the calculations. Several instructions, in particular the selection of specific precursors and morphology controlling agents, have been further illustrated as a guideline for experimentalists.

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This thesis improves the process of recommending people to people in social networks using new clustering algorithms and ranking methods. The proposed system and methods are evaluated on the data collected from a real life social network. The empirical analysis of this research confirms that the proposed system and methods achieved improvements in the accuracy and efficiency of matching and recommending people, and overcome some of the problems that social matching systems usually suffer.

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A large literature shows that violence against women in intimate relationships varies across racial/ethnic groups. However, it is unclear whether such variations differ across urban, suburban, and rural areas. The main objective of this article is to examine this issue using 1992 to 2009 National Crime Victimization Survey data. We also test the hypothesis that racial/ethnic minority women living in rural areas are more likely to be assaulted by their current and former intimate partners than are their urban and suburban counterparts. Contrary to expectations, results indicated virtually no differences in the rates at which urban, suburban, and rural racial/ethnic minority females were victims of intimate violence. The results indicate the great need of additional research into this important topic.