994 resultados para Mining industries


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Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

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This paper begins with the assertion that research grounded in creative practice constitutes a new paradigm. We argue both for and against the idea. We argue against the idea in terms of applying it to the idealised ‘lone artist’ engaged in the production of their art, whose focus of research is a self-reflection upon the art they produce, and whose art is also the findings of the research. Our position is that such an approach cannot be considered as anything other than a form of auto-phenomenography, that such efforts are part of qualitative research, and they are thus trivial in paradigmatic terms. However, we argue in the positive for understanding the artistic event – by which we mean any mass ecology of artistic practice – as being paradigmatically new in terms of research potentials and demands. Our exemplar for that argument is a practice-led, large-scale annual event called Indie 100 which has run for five years and has demonstrated a distinct paradigmatic ‘settling in’ over its duration while clearly pushing paradigmatic boundaries for research into creative practice.

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The Social Water Assessment Protocol (SWAP) is a tool consisting of a series of questions on fourteen themes designed to capture the social context of water around a mine site. A pilot study of the SWAP, conducted in Prestea-Huni Valley, Ghana, showed that some communities were concerned about whether the groundwater was potable. The mining company’s concern was that there was a cycle of dependency amongst communities that received treated water from the mining company. The pilot identified potential data sources and stakeholder groups for each theme, gaps in themes and suggested refinements to questions to improve the SWAP.

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Many developing countries are experiencing rapid expansion in mining with associated water impacts. In most cases mining expansion is outpacing the building of national capacity to ensure that sustainable water management practices are implemented. Since 2011, Australia's International Mining for Development Centre (IM4DC) has funded capacity building in such countries including a program of water projects. Five projects in particular (principally covering experiences from Peru, Colombia, Ghana, Zambia, Indonesia, Philippines and Mongolia) have provided insight into water capacity building priorities and opportunities. This paper reviews the challenges faced by water stakeholders, and proposes the associated capacity needs. The paper uses the evidence derived from the IM4DC projects to develop a set of specific capacity-building recommendations. Recommendations include: the incorporation of mine water management in engineering and environmental undergraduate courses; secondments of staff to suitable partner organisations; training to allow site staff to effectively monitor water including community impacts; leadership training to support a water stewardship culture; training of officials to support implementation of catchment management approaches; and the empowerment of communities to recognise and negotiate solutions to mine-related risks. New initiatives to fund the transfer of multi-disciplinary knowledge from nations with well-developed water management practices are called for.

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As we enter the second phase of creative industries there is a shift away from the early 1990s ideology of the arts as a creative content provider for the wealth generating ‘knowledge’ economy to an expanded rhetoric encompassing ‘cultural capital’ and its symbolic value. A renewed focus on culture is examined through a regional scan of creative industries in which social engineering of the arts occurs through policy imperatives driven by ‘profit oriented conceptualisations of culture’ (Hornidge 2011, p. 263) In the push for artists to become ‘culturpreneurs’ a trend has emerged where demand for ‘embedded creatives’ (Cunningham 2013) sees an exodus from arts-based employment through use of transferable skills into areas outside the arts. For those that stay, within the performing arts in particular, employment remains project-based, sporadic, underpaid, self-initiated and often self-financed, requiring adaptive career paths. Artist entrepreneurs must balance creation and performance of their art with increasing amounts of time spent on branding, compliance, fundraising and the logistical and commercial requirements of operating in a CI paradigm. The artists’ key challenge thus becomes one of aligning core creative and aesthetic values with market and business considerations. There is also the perceived threat posed by the ‘prosumer’ phenomenon (Bruns 2008), in which digital on-line products are created and produced by those formerly seen as consumers of art or audiences for art. Despite negative aspects to this scenario, a recent study (Steiner & Schneider 2013) reveals that artists are happier and more satisfied than other workers within and outside the creative industries. A lively hybridisation of creative practice is occurring through mobile and interactive technologies with dynamic connections to social media. Continued growth in arts festivals attracts participation in international and transdisciplinary collaborations, whilst cross-sectoral partnerships provide artists with opportunities beyond a socio-cultural setting into business, health, science and education. This is occurring alongside a renewed engagement with place through the rise of cultural precincts in ‘creative cities’ (Florida 2008, Landry 2000), providing revitalised spaces for artists to gather and work. Finally, a reconsideration of the specialist attributes and transferable skills that artists bring to the creative industries suggests ways to dance through both the challenges and opportunities occasioned by the current complexities of arts’ practices.

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Introduction The rapidly burgeoning popularity of cinema at the beginning of the 20th century favored industrialized modes of creativity organized around large production studios that could churn out a steady stream of narrative feature films. By the mid-1910s, a handful of Hollywood studios became leaders in the production, distribution, and exhibition of popular commercial movies. In order to serve incessant demand for new titles, the studios relied on a set of conventions that allowed them to regularize production and realize workplace efficiencies. This entailed a socialized mode of creativity that would later be adopted by radio and television broadcasters. It would also become a model for cinema and media production around the world, both for commercial and state-supported institutions. Even today the core tenets of industrialized creativity prevail in most large media enterprises. During the 1980s and 1990s, however, media industries began to change radically, driven by forces of neoliberalism, corporate conglomeration, globalization, and technological innovation. Today, screen media are created both by large-scale production units and by networked ensembles of talent and skilled labor. Moreover, digital media production may take place in small shops or via the collective labor of media users or fans who have attracted attention due to their hyphenated status as both producers and users of media (i.e., “prosumers”). Studies of screen media labor fall into five conceptual and methodological categories: historical studies of labor relations, ethnographically inspired investigations of workplace dynamics, critical analyses of the spatial and social organization of labor, and normative assessments of industrialized creativity.

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Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

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Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

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Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

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The growth of the information economy has been stellar in the last decade. General-purpose technologies such as the computer and the Internet have promoted productivity growth in a large number of industries. The effect on telecommunications, media and technology industries has been particularly strong. These industries include mobile telecommunications, printing and publishing, broadcasting, software, hardware and Internet services. There have been large structural changes, which have led to new questions on business strategies, regulation and policy. This thesis focuses on four such questions and answers them by extending the theoretical literature on platforms. The questions (with short answers) are: (i) Do we need to regulate how Internet service providers discriminate between content providers? (Yes.) (ii) What are the welfare effects of allowing consumers to pay to remove advertisements from advertisement-supported products?(Ambiguous, but those watching ads are worse off.) (iii) Why are some markets characterized by open platforms, extendable by third parties, and some by closed platforms, which are not extendable? (It is a trade-off between intensified competition for consumers and benefits from third parties) (iv) Do private platform providers allow third parties to access their platform when it is socially desirable? (No.)

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This Working Paper reports the background to the first stage of the ongoing research project, The Quest for Well-being in Growth Industries: A Collaborative Study in Finland and Scotland, conducted under the auspices of the Academy of Finland research programme The Future of Work and Well-being (2008-2011). This collaborative project provides national and transnational data, analysis and outputs. The study is being conducted in the Department of Management and Organisation, Hanken School of Economics, Finland, in collaboration with Glasgow Caledonian University, University of East London, Heriot-Watt University and Reading University, UK. The project examines policies and practices towards the enhancement of work-related well-being in growth industries, and contradictory pressures and tensions posed in this situation. The overall aim is to evaluate the development, implementation and use of work-related well-being policies in four selected growth industries. These sectors – electronics, care, finance and accounting, and tourism – have been selected on the basis of European Union and national forecasts, and demographic and socio-economic trends in employment. In this working paper we outline the background to the research study, the initial research plan, and how the survey of employers has been constructed. The working paper concludes with a brief discussion of general ongoing research issues arising in the project.

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Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

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This working paper reports the ongoing research conducted in the research project, The Quest for Well-being in Growth Industries: A Collaborative Study in Finland and Scotland, under the auspices of Academy of Finland research programme, The Future of Work and Well-being. The research project examines the contradictory pressures for policies and practices towards both the inhibition and the enhancement of work-related well-being that are likely in growth industries. The overall aim is to evaluate the development, implementation and use of work-related well-being policies in four selected growth industries. These – electronics, care, finance and accounting, and tourism – have been selected on the basis of EU and national forecasts, and demographic and socio-economic trends in standard and non-standard employment. In this paper we aim to review the survey that constitutes the second main phase of this research.