Facing the climate change challenges in the mining and mineral industry as providers of a sustainable manufacturing process

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.

Open business intelligence: on the importance of data quality awareness in user-friendly data mining

Citizens demand more and more data for making decisions in their daily life. Therefore, mechanisms that allow citizens to understand and analyze linked open data (LOD) in a user-friendly manner are highly required. To this aim, the concept of Open Business Intelligence (OpenBI) is introduced in this position paper. OpenBI facilitates non-expert users to (i) analyze and visualize LOD, thus generating actionable information by means of reporting, OLAP analysis, dashboards or data mining; and to (ii) share the new acquired information as LOD to be reused by anyone. One of the most challenging issues of OpenBI is related to data mining, since non-experts (as citizens) need guidance during preprocessing and application of mining algorithms due to the complexity of the mining process and the low quality of the data sources. This is even worst when dealing with LOD, not only because of the different kind of links among data, but also because of its high dimensionality. As a consequence, in this position paper we advocate that data mining for OpenBI requires data quality-aware mechanisms for guiding non-expert users in obtaining and sharing the most reliable knowledge from the available LOD.

The China-Russia trade relationship and its impact on Europe. Breugel Working Paper Issue 4, 2016

This paper analyses empirically how increasingly close trade relations between China and Russia might affect the European Union (EU). We show that EU countries are complementary to Russia on the Chinese market. However, Chinese exports are increasingly relevant substitutes for EU exports on the Russian market. This means that an increase in China-Russia economic cooperation should have a negative impact on European exports. We simulate a scenario in which trade tariffs between Russia and China are eliminated, which is found to reduce EU exports to Russia. Finally, a more granular approach to the question analyses which sectors in Europe will be more affected by the increasing economic links between China and Russia, and finds that electronic machinery, equipment and machinery, and nuclear reactors will be particularly affected. Such findings obviously show quickly China is moving up the ladder in terms of export structure and how strategically important it is for Europe to continue upgrading its industry to compete at the highest level of that ladder.

Prospecting and mining of copper ore at Santa Rita, New Mexico,

First edition, September 1916. cf. verso of t.-p.

1987 census of manufactures.

Mode of access: Internet.

Annual report of the Bureau of Mines and Mining of the State of Indiana.

Mode of access: Internet.

Modern mining practice : a practical work of reference on mining engineering /

Short bibliography at end of each volume.

Transactions of the American Institute of Mining and Metallurgical Engineers.

Consists of transactions of various Branches and Divisions of the Institute.

Engineering and mining journal.

Published by: Western & Co., 1869-1871; Scientific Publishing Co., 1871-1906; Hill Publishing Co., 1906-1917; McGraw Hill Co., 1917-1922.

Power for operating machinery in printing houses, a treatise on the methods of applying power to printing presses and allied machinery, with particular reference to electric drive./

Mode of access: Internet.

Longwall coal cutting machinery;

Mode of access: Internet.

Research in mechanical farm equipment /

Cover title.

Rossiter Worthington Raymond; a memorial, pub. by the American Institute of Mining and Metallurgical Engineers,

Mode of access: Internet.

Statistics of mines and mining in the states and territories west of the Rocky Mountains; being the [1st-8th] annual report of Rossiter W. Raymond, U.S. commissioner of mining statistics

8th, 1875, 44th Cong., 1st sess., House ex. doc. no. 159

Exploring the integration of data mining and data visualization

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be effective, it is important to include the visualization techniques in the mining process and to generate the discovered patterns for a more comprehensive visual view. In this dissertation, four related problems: dimensionality reduction for visualizing high dimensional datasets, visualization-based clustering evaluation, interactive document mining, and multiple clusterings exploration are studied to explore the integration of data mining and data visualization. In particular, we 1) propose an efficient feature selection method (reliefF + mRMR) for preprocessing high dimensional datasets; 2) present DClusterE to integrate cluster validation with user interaction and provide rich visualization tools for users to examine document clustering results from multiple perspectives; 3) design two interactive document summarization systems to involve users efforts and generate customized summaries from 2D sentence layouts; and 4) propose a new framework which organizes the different input clusterings into a hierarchical tree structure and allows for interactive exploration of multiple clustering solutions.