936 resultados para Montana Mining and Milling Company
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A Montana Public Radio Commentary from Evan Barrett.
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The “Innovatio Educativa Tertio Millennio” group has been 10 years developing educational innovation techniques, actually has reached the level of teaching on the technical teachers has developed, and share them with other groups, that can implement them in their teaching activities. UNESCO Chair of Mining and Industrial Heritage has been years working on heritage, and on the one hand teaching in conservation and maintenance of heritage, and on the other doing raise awareness of the meaning of heritage, the social value and as must be managed effectively. Recently these two groups work together, thus is spreading in a much more effective manner the concepts of heritage, its meaning, its value, and how to manage it and provide effective protection. On one hand being a work of dissemination based on internet and on radio broadcasting, and on the other one of teaching based on educational innovation, and courses, conferences, and face-to-face seminars or distance platforms.
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Twelve years ago a group of teachers began to work in educational innovation. In 2002 we received an award for educational innovation, undergoing several stages. Recently, we have decided to focus on being teachers of educational innovation. We create a web scheduled in Joomla offering various services, among which we emphasize teaching courses of educational innovation. The “Instituto de Ciencias de la Educacion” in “Universidad Politécnica de Madrid” has recently incorporated two of these courses, which has been highly praised. These courses will be reissued in new calls, and we are going to offer them to more Universities. We are in contact with several institutions, radio programs, the UNESCO Chair of Mining and Industrial Heritage, and we are working with them in the creation of heritage courses using methods that we have developed.
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In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.
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A sustainable manufacturing process must rely on an also sustainable raw materials and energy supply. This paper is intended to show the results of the studies developed on sustainable business models for the minerals industry as a fundamental previous part of a sustainable manufacturing process. As it has happened in other economic activities, the mining and minerals industry has come under tremendous pressure to improve its social, developmental, and environmental performance. Mining, refining, and the use and disposal of minerals have in some instances led to significant local environmental and social damage. Nowadays, like in other parts of the corporate world, companies are more routinely expected to perform to ever higher standards of behavior, going well beyond achieving the best rate of return for shareholders. They are also increasingly being asked to be more transparent and subject to third-party audit or review, especially in environmental aspects. In terms of environment, there are three inter-related areas where innovation and new business models can make the biggest difference: carbon, water and biodiversity. The focus in these three areas is for two reasons. First, the industrial and energetic minerals industry has significant footprints in each of these areas. Second, these three areas are where the potential environmental impacts go beyond local stakeholders and communities, and can even have global impacts, like in the case of carbon. So prioritizing efforts in these areas will ultimately be a strategic differentiator as the industry businesses continues to grow. Over the next forty years, world?s population is predicted to rise from 6.300 million to 9.500 million people. This will mean a huge demand of natural resources. Indeed, consumption rates are such that current demand for raw materials will probably soon exceed the planet?s capacity. As awareness of the actual situation grows, the public is demanding goods and services that are even more environmentally sustainable. This means that massive efforts are required to reduce the amount of materials we use, including freshwater, minerals and oil, biodiversity, and marine resources. It?s clear that business as usual is no longer possible. Today, companies face not only the economic fallout of the financial crisis; they face the substantial challenge of transitioning to a low-carbon economy that is constrained by dwindling natural resources easily accessible. Innovative business models offer pioneering companies an early start toward the future. They can signal to consumers how to make sustainable choices and provide reward for both the consumer and the shareholder. Climate change and carbon remain major risk discontinuities that we need to better understand and deal with. In the absence of a global carbon solution, the principal objective of any individual country should be to reduce its global carbon emissions by encouraging conservation. The mineral industry internal response is to continue to focus on reducing the energy intensity of our existing operations through energy efficiency and the progressive introduction of new technology. Planning of the new projects must ensure that their energy footprint is minimal from the start. These actions will increase the long term resilience of the business to uncertain energy and carbon markets. This focus, combined with a strong demand for skills in this strategic area for the future requires an appropriate change in initial and continuing training of engineers and technicians and their awareness of the issue of eco-design. It will also need the development of measurement tools for consistent comparisons between companies and the assessments integration of the carbon footprint of mining equipments and services in a comprehensive impact study on the sustainable development of the Economy.
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The Mount Antero/White area is a popular prospecting area. Recent expansions in the recreation economy is drawing more visitors to the area. Consequently, visitors may be placing unsustainable pressures on the landscape. In order to help rectify this, the legal, ecological, geologic, aesthetic, recreational, historic, social, and economic character of the Antero/White area has been identified. Four feasible management alternatives have also been recognized. They are a) take no new management actions, b) prohibit motorized activities in the area, c) develop a mineralogical park, and d) a combination of options b and c. Option C has been defended, as it best balances the desires of area users with the underlying ecological and geological character of the area.
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Data mining is one of the most important analysis techniques to automatically extract knowledge from large amount of data. Nowadays, data mining is based on low-level specifications of the employed techniques typically bounded to a specific analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Bearing in mind this situation, we propose a model-driven approach which is based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (that is deployed via data-warehousing technology) and the analysis models for data mining (tailored to a specific platform). Thus, analysts can concentrate on understanding the analysis problem via conceptual data-mining models instead of wasting efforts on low-level programming tasks related to the underlying-platform technical details. These time consuming tasks are now entrusted to the model-transformations scaffolding. The feasibility of our approach is shown by means of a hypothetical data-mining scenario where a time series analysis is required.
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The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained show the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.