Concesión de explotación de granitos derivada del permiso de investigación “Honor de Miengo”

Este proyecto tiene por objeto el estudio de la viabilidad, tanto económica como técnica, de la apertura y explotación de una cantera de granito para su uso como roca ornamental. Para ello se ha seleccionado una zona de potencial interés en Santa Olalla del Cala (Huelva) debido a los afloramientos y la tonalidad de los mismos. En esta zona se ha realizado un estudio del medio físico y una investigación sobre los tipos de roca existentes en la superficie que comprende el Permiso de Investigación de la compañía minera Canteras Extremeñas S.L. Con todo ello, se han determinado varias áreas de interés en las que se podría realizar el emplazamiento de la cantera. Desde el punto de vista técnico, se ha definido el diseño de la cantera optando por un método de explotación combinando el Método Finlandés con el corte con hilo diamantado, proyectando a su vez una zona de emplazamiento para la futura escombrera temporal, teniendo en cuenta la realización de un estudio de impacto ambiental, plan de restauración, plan de vigilancia ambiental, explosivos y previsión de ejecución de las labores. El estudio realizado de los indicadores económicos nos muestra que el proyecto es rentable, con todo ello se concluye que, tanto técnica como económicamente, la explotación del recurso minero es viable. ABSTRACT This project aims to study the feasibility, both economic and technical, to the opening and operation of a granite quarry for use as an ornamental stone. For this we have selected an area of potential interest in Santa Olalla del Cala (Huelva) due to upwelling and tonality of these. In this area, it has made a study of the physical environment and an investigation into the types of rock on the surface comprising the Research Permit of the mining company Canteras Extremeñas SL. With all this, we have identified several areas of interest in which they could make the location of the quarry. From the technical point of view, we have defined the design of the quarry opting for a mining method combining the Finnish Method with the diamond wire cutting, projecting turn an area of the site for future temporal tip, taking into account the completion of an environmental impact, restoration plan, environmental monitoring plan, explosives and forecasting operations execution. The study of economic indicators shows that the project is profitable, yet it can be concluded that, both technically and economically, exploitation of mineral resources is viable.

Efficient management of available technologies. Aplication to mining operations for industry supplies

Nowadays, processing Industry Sector is going through a series of changes, including right management and reduction of environmental affections. Any productive process which looks for sustainable management is incomplete if Cycle of Life of mineral resources sustainability is not taken into account. Raw materials for manufacturing are provided by mineral resources extraction processes, such as copper, aluminum, iron, gold, silver, silicon, titanium? Those elements are necessary for Mankind development and are obtained from the Earth through mineral extractive processes. Mineral extraction processes are operations which must take care about the environmental consequences. Extraction of huge volumes of rock for their transformation into raw materials for industry must be optimized to reduce ecological cost of the final product as l was possible. Reducing the ecological balance on a global scale has no sense to design an efficient manufacturing in secondary industry (transformation), if in first steps of the supply chain (extraction) impact exceeds the savings of resources in successive phases. Mining operations size suggests that it is an environmental aggressive activity, but precisely because of its great impact must be the first element to be considered. That idea implies that a new concept born: Reduce economical and environmental cost This work aims to make a reflection on the parameters that can be modified to reduce the energy cost of the process without an increasing in operational costs and always ensuring the same production capacity. That means minimize economic and environmental cost at same time. An efficient design of mining operation which has taken into account that idea does not implies an increasing of the operating cost. To get this objective is necessary to think in global operation view to make that all departments involved have common guidelines which make you think in the optimization of global energy costs. Sometimes a single operational cost must be increased to reduce global cost. This work makes a review through different design parameters of surface mining setting some key performance indicators (KPIs) which are estimated from an efficient point of view. Those KPIs can be included by HQE Policies as global indicators. The new concept developed is that a new criteria has to be applied in company policies: improve management, improving OPERATIONAL efficiency. That means, that is better to use current resources properly (machinery, equipment,?) than to replace them with new things but not used correctly. As a conclusion, through an efficient management of current technologies in each extractive operation an important reduction of the energy can be achieved looking at downstream in the process. That implies a lower energetic cost in the whole cycle of life in manufactured product.

Una aproximación a la predicción del valor de acciones en la bolsa de valores aplicando técnicas de Data Mining

La predicción del valor de las acciones en la bolsa de valores ha sido un tema importante en el campo de inversiones, que por varios años ha atraído tanto a académicos como a inversionistas. Esto supone que la información disponible en el pasado de la compañía que cotiza en bolsa tiene alguna implicación en el futuro del valor de la misma. Este trabajo está enfocado en ayudar a un persona u organismo que decida invertir en la bolsa de valores a través de gestión de compra o venta de acciones de una compañía a tomar decisiones respecto al tiempo de comprar o vender basado en el conocimiento obtenido de los valores históricos de las acciones de una compañía en la bolsa de valores. Esta decisión será inferida a partir de un modelo de regresión múltiple que es una de las técnicas de datamining. Para llevar conseguir esto se emplea una metodología conocida como CRISP-DM aplicada a los datos históricos de la compañía con mayor valor actual del NASDAQ.---ABSTRACT---The prediction of the value of shares in the stock market has been a major issue in the field of investments, which for several years has attracted both academics and investors. This means that the information available in the company last traded have any involvement in the future of the value of it. This work is focused on helping an investor decides to invest in the stock market through management buy or sell shares of a company to make decisions with respect to time to buy or sell based on the knowledge gained from the historic values of the shares of a company in the stock market. This decision will be inferred from a multiple regression model which is one of the techniques of data mining. To get this out a methodology known as CRISP-DM applied to historical data of the company with the highest current value of NASDAQ is used.

Mining mobile apps reviews to support release planning

The mobile apps market is a tremendous success, with millions of apps downloaded and used every day by users spread all around the world. For apps’ developers, having their apps published on one of the major app stores (e.g. Google Play market) is just the beginning of the apps lifecycle. Indeed, in order to successfully compete with the other apps in the market, an app has to be updated frequently by adding new attractive features and by fixing existing bugs. Clearly, any developer interested in increasing the success of her app should try to implement features desired by the app’s users and to fix bugs affecting the user experience of many of them. A precious source of information to decide how to collect users’ opinions and wishes is represented by the reviews left by users on the store from which they downloaded the app. However, to exploit such information the app’s developer should manually read each user review and verify if it contains useful information (e.g. suggestions for new features). This is something not doable if the app receives hundreds of reviews per day, as happens for the very popular apps on the market. In this work, our aim is to provide support to mobile apps developers by proposing a novel approach exploiting data mining, natural language processing, machine learning, and clustering techniques in order to classify the user reviews on the basis of the information they contain (e.g. useless, suggestion for new features, bugs reporting). Such an approach has been empirically evaluated and made available in a web-­‐based tool publicly available to all apps’ developers. The achieved results showed that the developed tool: (i) is able to correctly categorise user reviews on the basis of their content (e.g. isolating those reporting bugs) with 78% of accuracy, (ii) produces clusters of reviews (e.g. groups together reviews indicating exactly the same bug to be fixed) that are meaningful from a developer’s point-­‐of-­‐view, and (iii) is considered useful by a software company working in the mobile apps’ development market.